1 Introduction CSE 252c Fall 03. Project Report. Calibration-Free Augmented Reality

合集下载

Physical-properties-of-the-shallow-sediments-in-late-Pleistocene-formations-Ursa-Basin-Gulf-of-Mexic

Physical properties of the shallow sediments in late Pleistocene formations,Ursa Basin,Gulf of Mexico,and their implications for generation and preservation of shallow overpressuresN.T.T.Binh a ,*,T.Tokunaga a ,1,T.Nakamura b ,2,K.Kozumi b ,2,M.Nakajima b ,2,M.Kubota b ,2,H.Kameya c ,3,M.Taniue c ,3aDepartment of Environment Systems,School of Frontier Sciences,University of Tokyo,5-1-5Kashiwanoha,Kashiwa-shi,Chiba 277-8563,Japan bGeotechnical Department,Dia Consultants,Saitama,Japan cCore Laboratory,Oyo Corporation,Niigata,Japana r t i c l e i n f oArticle history:Received 14September 2007Received in revised form 20January 2009Accepted 23January 2009Available online 31January 2009Keywords:Basin modellingShallow overpressure Fluid ﬂowDeepwater environmenta b s t r a c tUnderstanding the evolution of abnormally high ﬂuid pressures within sedimentary formations is critical for analysing hydrogeological processes and assessing drilling risks.We have constructed a two-dimensional basin model and have performed numerical simulations to increase the understanding of the history of ﬂuid ﬂow and shallow overpressures in the Pleistocene and Holocene formations in the Ursa basin,deepwater Gulf of Mexico.We measured physical properties of sediments,such as porosity and permeability,in the laboratory and estimated in situ pore pressures from preconsolidation pressures.We obtained porosity–effective stress relationships from measurements of bulk density,grain density and preconsolidation pressures in the laboratory.Porosity–effective stress relationships were also obtained from downhole density logs and measured pore pressures.The porosity–effective stress and porosity–permeability relationships obtained were applied in two-dimensional basin simulations.Results showed that high pore pressures developed shortly after sediment deposition.Peaks in pore pressure ratios were related to high sedimentation rates of mass transport deposits and the incision of the Ursa teral ﬂows from the area where the overburden is thick towards the area where it is thin have occurred at least since 30ka.Present pore pressure and temperature distributions suggest that lateral ﬂows play a role in re-distributing heat in the basin.Ó2009Elsevier Ltd.All rights reserved.1.IntroductionUnderstanding pore pressure regimes and ﬂuid ﬂow patterns in sedimentary basins and their temporal changes is important for investigating the evolution of sedimentary basins,the stability of slopes,and related geodynamics.For example,lateral ﬂuid ﬂows in a sedimentary formation are controlled by pore pressure gradients,sedimentation rates,and permeability distribution (Bethke,1986).Flemings et al.(2005)speculated that focusing of ﬂuid ﬂows may result in slope instability on continental slopes.In 2005,the Inte-grated Ocean Drilling Program (IODP)conducted Expedition 308tostudy shallow overpressure and ﬂuid ﬂow in the Ursa region,continental slope of the Gulf of Mexico.Eight holes were drilled at three well sites U1324,U1323and U1322.The wells were logged and in situ measurements were made.Geopressured sediments from Pleistocene and Holocene formations were found in these wells (Expedition 308Scientists,2005;Myers et al.,2007).In this area,Byrd et al.(1996),Eaton (1999),Ostermeier et al.(2002),and Flemings et al.(2005)described the existence of shallow water ﬂow phenomena,and discussed the problems encountered with shallow water ﬂows.Shallow water ﬂows are associated with a variety of drilling problems and seaﬂoor damage,including uncontrolled ﬂow of sands in the annulus of the borehole being drilled,borehole washouts,craters,and cracks on the seaﬂoor (Alberty et al.,1997;Alberty,2000;Faul et al.,2000;Ostermeier et al.,2002).They are considered to be the cause of major problems for the oil and gas industry working in the Mark-Ursa region (Alberty,2000).The loss of many wells in the Ursa Development Project in the Mississippi Canyon Block 810was an extreme example of severe damage due to violent shallow water ﬂows (Furlow,1998).*Corresponding author.Department of Earth Sciences,Durham University,Durham DH13LE,United Kingdom.Tel.:þ44(0)1913343972;fax:þ44(0)1913342301.E-mail address:binh.nguyen@ (N.T.T.Binh).1Tel.:þ81471364708;fax:þ81471364709.2Tel.:þ81486543011;fax:þ81486543833.3Tel.:þ81252745656;fax:þ81252716765.Contents lists available at ScienceDirectMarine and Petroleum Geologyjournal homepage :www.else /locate /marpetgeo0264-8172/$–see front matter Ó2009Elsevier Ltd.All rights reserved.doi:10.1016/j.marpetgeo.2009.01.018Marine and Petroleum Geology 26(2009)474–486Recently,Sawyer et al.(2007a)described the lithology of the main depositional elements in the Mars-Ursa region and interpreted the geological evolution of the area for the past70ky based on high resolution3D seismic data and well log data.Long et al.(2007)and Flemings et al.(2006,2008)presented pore pressure penetrometer measurements made during IODP Expedition308and documented vertical and lateral variation in overpressure at Sites U1322and U1324.They showed that overpressures have reached60%of the hydrostatic effective stress at Site U1322and70%at Site U1324. Sawyer et al.(2007b)and Dugan et al.(2007)integrated physical properties of mass transport complexes(MTCs)and concluded that consolidation behaviour in MTCs is different from that in the sedi-ments encasing the MTCs.Furthermore,low permeability in MTCs precludes drainage of overpressure in the Ursa region.In this study,we conducted numerical modelling,supported by data from laboratory experiments using samples obtained from IODP Expedition308,to examine lateralﬂuidﬂow and pore pressure evolution in the Pleistocene and Holocene sedimentary sections of the Ursa basin.In the geotechnical laboratory,we measured physical properties of sediments such as porosity and permeability and estimated in situ pore pressures from preconsolidation pressures. Then porosity–effective stress relationships were constructed from IODP results and the estimated in situ pore pressures.The porosity–effective stress and porosity–permeability relationships obtained were applied in two-dimensional basin simulations.Two-dimensional modelling cases presented here include the effects of both the uneven sedimentation rates along the cross-section and the ancient channel activities on the hydrogeological system.The modelling results can help to improve the under-standing of the history ofﬂuidﬂow and overpressure in the study area.2.Geological settingIn this section,we summarize what is known from previous research results about the lithology and deposition of sediments in the Ursa basin.This information will be used to construct the geological model for our basin modelling study which will be dis-cussed in Section4.The Ursa Basin is located about200km southeast of New Orleans on the continental slope of the Gulf of Mexico(Fig.1).It is a salt-withdrawal mini-basin with water depth in the range800–1400m,and with sediments originating from the Mississippi River system(Expedition308Scientists,2005).This study focuses on the Late Pleistocene to Holocene sedimentary section of the Ursa Basin, i.e.,from the base of the Blue Unit to the seaﬂoor(Fig.2).According to Sawyer et al.(2007a)and Expedition308Scientists (2005),sediments deposited from the base of the Blue Unit to the seaﬂoor can be divided intoﬁve units from bottom to top:the Blue Unit,the Ursa Canyon channel-levee system,the Southwest Pass Canyon channel-levee system,mass transport deposits,and the distal deposits and hemipelagic drape(Fig.2).The Blue Unit is composed of interbedded sands and clays with a maximum two-way travel time of250–300ms(Sawyer et al.,2007a).In the study area,the Blue Unit thins towards west due to the incision by the Southwest Pass and Ursa Canyon systems(Fig.2)(Sawyer et al., 2007a).The Blue Unit was most likely deposited during the MIS Stage4eustatic sea level fall and at the time of an eastward shift in the drainage pattern of the Mississippi River(Piggott and Pulham, 1993;Winker and Booth,2000;Ruddiman,2001).The base of the Blue Unit was interpreted to have been deposited at around68ka based on biostratigraphic data from nannofossils assemblages (Winker and Booth,2000).Note that Urgeles et al.(2007)recently suggested the age of the base of the Blue Unit to be89ka,but without giving a reason.Thus,we assumed the age of deposition to be68ka. The Ursa Canyon runs from the northwest to the southeast(Sawyer et al.,2007a).The channel-levee system is composed of a channelﬁll, channel-margin slides,and levees(Sawyer et al.,2007a).The channel margin and levees consist of silty clays while the channelﬁll consists of sands and silty clays(Sawyer et al.,2007a).The Ursa Canyon incised the Blue Unit and channel-margin slides play as hydraulic barrier within the Blue Unit(Fig.2)(Sawyer et al.,2007a).Fig.1.Location of the study area and the cross-section used for two-dimensional basin modelling.Contours show water depth.The names of the blocks are also shown.After Sawyer et al.(2007b).N.T.T.Binh et al./Marine and Petroleum Geology26(2009)474–486475The Southwest Pass Canyon system is younger than,and lies to the west of the Ursa Canyon system (Fig.2).It eroded much of the western levee of the Ursa channel and completely buried its ﬁll and eastern levee.It has similar characteristics as the Ursa Canyon system but is even larger (Sawyer et al.,2007a ).The Southwest Pass Canyon also contains a belt of rotated channel-margin slides (Fig.2),which is up to 5.5km wide.The canyon ﬁll itself is approximately 1.3–1.6km wide (Sawyer et al.,2007a ).Mass transport deposits (MTDs)are situated within the mud-rich levee deposits above the Blue Unit in the studied area (Fig.2)(Sawyer et al.,2007a ).MTDs consist of silty clays (Sawyer et al.,2007b;Dugan et al.,2007).The ﬁrst mass transport deposit is located on the eastern levee of the Ursa Canyon channel-levee system,and the second mass transport deposit is located within the eastern levee of the Southwest Pass Canyon channel-levee system (Fig.2b)(Sawyer et al.,2007a ).Distal deposits and hemipelagic drape overlie the MTDs.The distal deposits are composed primarily of olive-green and reddish brown clay interbedded with black clay and are capped by hemi-pelagic clay that is rich in nannofossils and foraminifera (Expedi-tion 308Scientists,2005).3.Physical properties of the soft sedimentsSoft sediment samples obtained from IODP Expedition 308were analysed,focusing mainly on porosity–permeability relationships.Index properties of the samples used for consolidation tests are shown in Table 1.Grain densities were in the range 2760–2900kg/m 3and were found to be higher than those measured onboard the ship (2667–2780kg/m 3)(Expedition 308Scientists,2005).We fol-lowed JIS A 1202-1999(Japanese Industrial Standards Committee,1999)and JGS 0111-2000(Japanese Geotechnical Society,2000a )for the measurements of the grain densities of the samples,so the reasons for the discrepancy between the density measurements are unknown.However,the effects of the differences of the grain densities on the calculated porosities were rather small,i.e.,less than 2%,and hence were not signiﬁcant,at least for this study.3.1.Porosity–permeability relationships3.1.1.Evaluation of permeability from 1-D consolidation testsA total of fourteen samples were tested either by using an incremental loading oedometer (IL)or aconstant-rate-of-strainFig.2.(a)Seismic line AA 0and (b)interpreted cross-section.The dotted blue box shows the modelled area.Modiﬁed from Sawyer et al.(2007a)(For interpretation of the references to colour in this ﬁgure legend,the reader is referred to the web version of this article).N.T.T.Binh et al./Marine and Petroleum Geology 26(2009)474–486476oedometer (CRS).Both the IL and CRS oedometers had a loading capability up to 10MPa.Prior to testing,the samples were removed from the sealed core liner and trimmed to a height of 2.5cm and a diameter of 6.0cm.Once trimmed,the wet mass of the sample was recorded before the sample was transferred into the consolidation cell.The cells for both oedometers were made of stainless steel so that only vertical sediment deformation could occur.The sample was set into the cell and placed between two porous stones.Saturated ﬁlter papers were used to separate the sample from the porous stones and to prevent ﬁne-grained sediment particles from blocking the drainage paths through the porous stones.After the cell was assembled,it was transferred to the oedometer.Side friction was minimized using silicone grease.General sample preparation and testing procedures followed the guidelines set out by JIS A 1217-2000and JIS A 1227-2000(Japanese Industrial Standards Committee,2000b,c )and JGS 0411-2000and JGS 0412-2000(Japanese Geotechnical Society,2000c,d ).In the IL tests,the cells were submerged in saline water to keep the samples fully water-saturated.The samples were allowed to settle for 24h after the application of each incremental load.Time,loading pressure,and the change in specimen height were measured.The end of primary consolidation was evaluated using the square root of time method proposed by Taylor (1948).Then,the coefﬁcient of vertical consolidation (C v )and the coefﬁcient of volume compressibility (m v )were indirectly evaluated based on the one-dimensional Terzaghi’s consolidation theory (Terzaghi,1943;Lambe and Whitman,1979).In the CRS tests,backpressure of 200kPa was applied to the samples for 24h to ensure they were fully water-saturated before loading with a constant axial strain rate of 0.03%/min.Backpressure was kept constant at 200kPa until the end of the tests.Time,axial load,the change in specimen height,and excess pore pressure at the base of the sample were measured.C v and m v were calculated using linear ﬁnite strain theory (Smith and Wahls,1969).Hydraulic conductivity (K )was estimated from C v ,m v and density of water (r w )byK ¼C v m v r w g(1)where g is gravitational acceleration (Lambe and Whitman,1979).In the equation (1),the unit of K is m/s,C v is m 2/s,m v is 1/Pa,g is m/s 2,r w is kg/m 3.Intrinsic permeability can be obtained from hydraulic conduc-tivity through the following relationship (Hubbert,1940)K ¼k r w gm(2)where k is intrinsic permeability (m 2)and m is viscosity of pore ﬂuid (Pa s).The intrinsic permeability reported here is for seawater with density and viscosity to be 1025kg/m 3and 0.963Â10À3Pa s,respectively.3.1.2.ResultsThe permeability values obtained from fourteen consolidation tests ranged from 5Â10À17to 1Â10À19m 2.For comparison,the results are plotted in Figs.3and 4with data from a previous study in the Gulf of Mexico (Bryant et al.,1975).Bryant et al.(1975)classiﬁed their measurements based on the grain size of the samples.For grain size analysis,we used a hydrometer and fol-lowed the method JIS A 1204-2000(Japanese Industrial Standards Committee,2000a )and JGS 0131-2000(Japanese Geotechnical Society,2000b ).We also estimated shale volume of the sediments from gamma ray log data.The analysed samples from MTDs and silty clays have shale volumes in the range 59–78%(Table 1).Thus,the data obtained for MTDs and silty clays were compared with group 2of Bryant et al.(1975),which had clay content in the range 60–80%(Fig.3).Since the gamma ray data were not good enough at very shallow depths near the seaﬂoor,we did not use these datatoTable 11E-191E-181E-171E-161E-15PorosityP e r m e a b i l i t y (m 2)Silty clays MTDs Group 2 (Bryant et al., 1975)Fig. 3.Porosity and permeability obtained from IL tests and CRS tests for mass transport deposits (open triangles)and silty clays (open squares)in the Ursa Basin,and the published results in the Gulf of Mexico (black circles)(Bryant et al.,1975).The dotted line and the black line were modelled porosity–vertical permeability relation-ship used for MTDs and for silty clays,respectively.N.T.T.Binh et al./Marine and Petroleum Geology 26(2009)474–486477calculate shale volumes for hemipelagic clay.Based on visual core description and smear slide analyses,hemipelagic clay samples are mainly composed of clay (Expedition 308Scientists,2005).Therefore,we assume that the data for hemipelagic clays should be comparable with the group 1samples of Bryant et al.(1975)which had clay content higher than 80%(Fig.4).Based on these compar-isons,the results from this study were conﬁrmed to be consistent with data from the previous study.An IL test and a CRS test were conducted with specimens from the same sample U1324B-19H-CC for comparison.The intrinsic permeability values obtained from the CRS test were about 1.17–1.2times higher than those obtained from the IL test for the same porosity (Fig.5).However,the slopes of the permeability–porosity lines on the semi logarithmic plots were parallel (Fig.5),suggesting that the trend of permeability reduction by mechanical consoli-dation can be estimated from this slope.We used the equationk ¼A exp ðB f Þ(3)where A and B are lithology-dependent constants to express rela-tionships between permeability (k )and porosity (4)(Table 2).We used the porosity–permeability relationships shown in Table 2for the two-dimensional simulation described in the next section.3.2.Preconsolidation pressure measurementsPreconsolidation pressure is usually interpreted to be the maximum effective overburden stress that sediments have expe-rienced (Casagrande,1936;Lambe and Whitman,1979).Knowing the preconsolidation pressure (P c )and in situ overburden stress (S v ),we can estimate the in situ pore pressure (P p )through the following equation assuming that the sediments are normally consolidated.P p ¼S v ÀP c (4)In this study,preconsolidation pressures of the sediments were determined by using Casagrande (1936)’s method to analyse the IL and CRS test data.In situ pore pressures calculated from P c are shown in Table 3.The values obtained are consistent with in situ measurements (Flemings et al.,2008)(Fig.6)except for the point at 1566mbsl (metres below sea level)at site U1324.Also,in situ pore pressuremeasurements at 1316.5mbsl and 1366.5mbsl seemed to be lower than the expected pore pressures from preconsolidation pressures.The in situ measurements were conducted with good coupling between the measurement device and the formation at these depths (Flemings et al.,2008).These differences could be explained by the declines of pore pressures due to recent drilling activity,as suggested at the site U1322by Flemings et al.(2008)even though the precise reason is quite difﬁcult to state.Based on the data shown in Fig.6,we consider that the sections between seaﬂoor and 1127mbsl at site U1324and between seaﬂoor and 1375.5mbsl at site U1322are normally consolidated.3.3.Porosity–effective stress relationshipsPorosity–effective stress relationships were constructed for normal consolidation sections based on porosities calculated from density logs at sites U1324and U1322(Expedition 308Scientists,2005)(Fig.7).Overburden stress was estimated from density logs and water depths.In hemipelagic clay sections,porosities decrease quickly from 80%to 55%(Fig.7(a)).For mass transport deposits and silty clays,porosities can be modelled by porosity–effective stress relation-ships of the Athy (1930)type,with different parameters for the silty clays and mass transport deposits (Fig.7(b),(c)).4.Two-dimensional pore pressure and ﬂuid ﬂow modelling Basin modelling is one of the methods which can be used to predict pore pressure as well as ﬂuid ﬂow in a sedimentary basin(e.g.,Welte and Yalcin,1988;Burrus et al.,1992;Dore´et al.,1993;Hermanrud,1993;Neuzil,2003).Fully coupled and integrated basin simulators provide information on pore pressures,porosities,temperatures and ﬂuid ﬂow patterns through time.We conducted two-dimensional simulation using SIGMA-2D (Okui et al.,1996,1998).1.E-191.E-181.E-171.E-16PorosityP e r m e a b i l i t y (m 2)Fig.5.Porosity–permeability relationships obtained from the IL test (black squares)andCRS test (open squares)on the sample 1324B-19H-CC.The lines were obtained by least square ﬁts.Table 2Constants obtained for vertical permeability–porosity relationships.See text for 1.E-191.E-181.E-171.E-161.E-151.E-14PorosityP e r m e a b i l i t y (m 2)Fig.4.Porosity and permeability obtained from hemipelagic clays in the Ursa Basin using IL consolidation tests (open squares),and the published results in the Gulf of Mexico (black circles)(Bryant et al.,1975).The black line was used as the modelled porosity–vertical permeability relationship for hemipelagic clays.N.T.T.Binh et al./Marine and Petroleum Geology 26(2009)474–4864784.1.Model construction:geological model,lithology model,and physical propertiesThe cross-section was chosen to be parallel to the local slope direction in the study area (Fig.1).Hence,it is considered to contain the principal direction of ﬂuid ﬂow related to sedimentation and topography.There are three IODP Expedition 308well sites along this section,i.e.,U1324,U1323and U1322,and data from these wells can be used for calibration.A lithology model was made based on previous studies in the area (Expedition 308Scientists,2005;Sawyer et al.,2007a ).Because of the lack of detailed data,it was necessary to simplify the lithology distribution.Four types of lithology,hemipelagic clays,mass transport deposits,sands,and silty clays,were used to model the sediments in the study area (Fig.8).Since sheet sands in the Blue Unit have been considered to be the source of shallow water ﬂows in the Ursa area (Eaton,1999;Ostermeier et al.,2002;Winker and Shipp,2002),the distribution of sheet sands in the Blue Unit and the Ursa channel ﬁll sands were modelled in detail,whereas the other lithologies were rather simpliﬁed.The modelled cross-section was part of cross-section AA 0in Fig.2(b),and was divided into 28columns,26layers and one erosion event (Fig.8).Based on previous research results (Expedition 308Scientists,2005;Sawyer et al.,2007a ),the distribution of the sediments was set as follows (Table 4).From seaﬂoor to seismic horizon S10,the lithology is hemipelagic clays (layers 1and 2).From seismic horizon S10to seismic horizon S20,the lithology is silty clays and MTDs (layers 3–6).From seismic horizon S20to seismic horizon S30,the lithology is MTDs (layers 7–9).From seismic horizon S30to seismic horizon S60,the lithology is silty clays and MTDs with small amounts of sand (layers 10–13).The Ursa channel (layers 14–17)was modelled as sands and silty clays with the lithology distribu-tion being based on the seismic interpretation (Fig.2)(Sawyer et al.,2007a ).The Blue Unit includes sands and interbedded silty clays (layers 18to 24).Layers 25and 26are silty clays below the Blue Unit.The simulation was run for a total period of 85ky.Erosion by the incision of the Ursa Canyon was considered (Fig.8).Based on previous studies on sea level cycles in the Mis-sissippi river depositional system and in the Gulf of Mexico (Ruddiman,2001;LoDico et al.,2006),we considered that erosion had occurred after the deposition of the Blue Unit and before the sea level rise at 58ka.The timing of erosion was set to lie between 60ka and 58ka (Table 4).The eroded thickness was modelled to be between 50and 250m,assuming that the thickness of the Blue Unit had been constant throughout this cross-section before erosion occurred.During erosion,the palaeo-water depth in the eroded area increased by an amount equals to the eroded thickness.The relationships between porosity and vertical effective stress and between porosity and permeability for hemipelagic clays,MTDs and silty clays obtained from our experimental study (Figs.3,4and 7and Table 2)were used as input data for basin simulation.We also used published relationships between porosity and vertical effective stress and between porosity and permeability for sands in the Gulf of Mexico (Aniekwena et al.,2003)(Fig.9).Anisotropy in permeability was considered.Freeze and Cherry (1979)suggested that clays and shales show horizontal toverticalTable 3aU1324U1322Pressure (MPa)D e p t h (m b s l )Overburden stressCalculated from PcPressure (MPa)Fig.6.Pore pressures calculated from preconsolidation pressures (ﬁlled squares)(a)at site U1324and (b)at site U1322.The in situ measurements (Flemings et al.,2008)are also shown by open triangles.The units mbsl are metres below sea level.N.T.T.Binh et al./Marine and Petroleum Geology 26(2009)474–486479anisotropy ratio in the range3:1–10:1.In this study,the ratios between horizontal permeability and vertical permeability were chosen to be10:1for hemipelagic clays and mass transport deposits,and to be3:1for silty clays.For sands,since the perme-ability in the horizontal direction was found to be nearly equal to,or only slightly larger than that in the vertical direction(Hatanaka et al.,1997),the horizontal to vertical anisotropy ratio was chosen to be1:1.Other physical properties for each lithology required for the two-dimensional basin modelling include grain density,matrix thermal conductivity,and heat capacity.These data were estimated from published results(Expedition308Scientists,2005;Rossane et al.,2004;Waples and Waples,2004)(Table5).4.2.Boundary and initial conditionsGeological information can be used to select the appropriate boundary conditions.For this purpose,the distribution of faults in the layers of higher hydraulic conductivity was studied.Because the majority of sediments are clays and silty clays,and fault displacements tend to produceﬁne-grained material in general(e.g.,Ferrill and Morris,2001),all faults are assumed to act as sealing faults.Faults are located at the eastern boundary of the cross-section(Fig.2(b)).At the western boundary,the Blue Unit is completely eroded by the incision of the Southwest Pass channel (Fig.2).Thus,the body of low hydraulic conductivity in the Southwest Pass channel can be treated as a seal for westwardﬂuid Fig.8.The geological model used for the basin modelling.Dotted line shows erosion by the Ursa Canyon.50100150200250PorosityVerticaleffectivestress(kPa)100200300400500600700800PorosityVerticaleffectivestress(kPa)Porositya b cFig.7.Porosity–effective stress relationships for(a)hemipelagic clays,(b)MTDs,and(c)silty clays.Lines in theﬁgure and the equations show the modelled porosity–effective stress relationships used for two-dimensional basin modelling.N.T.T.Binh et al./Marine and Petroleum Geology26(2009)474–486480ﬂow in the Blue Unit.Therefore,no-ﬂow boundary conditions were assigned to both side boundaries.For the basal boundary,no ﬂuid ﬂow conditions were set because the base of the cross-section is composed of a mud-rich layer.The initial pore pressures at each time step were set to be the calculated pore pressures at the previous time step.For the newly added grids,hydrostatic pore pressures were applied.The initial temperatures were set to be those obtained from the previous time step for existing grids,and seawater temperature for the newly added grids.Boundary conditions for the heat ﬂow in SIGMA-2D are speciﬁed temperatures along the upper boundary,a speciﬁed heat ﬂux along the bottom,and no ﬂux along side boundaries (Okui et al.,1996,1998).At the upper surface of the model,temperatureand pressure were modelled as seaﬂoor temperature and seaﬂoor pressure.Temperatures at the seaﬂoor were set to be in the range 4.0–4.5 C depending on the water depth.Pressure at the seaﬂoor was considered to be hydrostatic.4.3.Model calibrationDuring calibration,the measured data from wells,i.e.,pore pressure,temperature,and porosity,were compared with the simulated results at the well locations to optimize the parameters used in the model.Sedimentation rates were adjusted by trial-and-error to obtain reasonable agreement between simulated and observed values.The geological model used in this study was made up of 26layers (Fig.8and Table 4).In the modelled cross-section,the ages of the top of the layers 1,2,6,9,12,13,15and 19were determined based on the estimated ages of the known key horizons (Table 4)(Expedition 308Scientists,2005;Sawyer et al.,2007a ).Because other layers were situated between horizons of known ages,the ages of these layers were adjusted to lie within the constrained ranges.Through this procedure,the appropriate sedimentation rates (Table 4)were chosen to obtain good correlations between the calculated results and the measured data.Present-day heat ﬂow at the base of the model was estimated by ﬁtting temperatures calculated from the model and in situ measurements (Expedition 308Scientists,2005).The heat ﬂow value obtained was 36.3mW/m 2.This value is quite low in comparison with heat ﬂow values seen in the continental crust,which ranges from 40to 46mW/m 2(Smith and Dees,1982).Mello and Karner (1996),Nagihara and Jones (2005)and Jones et al.(2003)suggested that the rapid deposition of thick sections of young sediments in the Mississippi fan has suppressed regional isotherms,resulting in anomalously low heat ﬂow.We assumed that the palaeo heat ﬂows were the same as present-day heatﬂows.Table 4Ages and thicknesses for the modelled cross-section AA 0.S10to S80represents keyTable 5Physical properties of four types of lithology estimated from Expedition 308050010001500200025003000350040000.30.40.50.60.70.8PorosityV e r t i c a l e f f e c t i v e s t r e s s (k P a)1.0E-151.0E-141.0E-131.0E-121.0E-111.0E-100.10.20.30.40.5PorosityP e r m e a b i l i t y (m 2)abFig.9.(a)Porosity–effective stress and (b)porosity–permeability relationships for sand.From Aniekwena et al.(2003).N.T.T.Binh et al./Marine and Petroleum Geology 26(2009)474–486481。

Pearson Edexcel Level 3 GCE W59279A 商品说明书

Pearson Edexcel Level 3 GCE*W59279A*Turn over W59279A©2019 Pearson Education Ltd.1/1/1You do not need any other materials.Instructions• All assessment materials must be sent to the examiner to arrive by 15 May 2019.• For 2019 the durations assigned to the Briefs assessing technique are as follows:– Bach chorale 2 minutes 10 seconds– Two-part counterpoint 2 minutes 5 seconds– Arrangement/Remix minimum duration 1 minute• The materials submitted must include:– Score - see page 35 of the specification.– Recording - see pages 34-35 of the specification and the Administrative Support Guide,released online on 1 September.– Completed authentication sheet – found online.• Back-up copies of all submitted materials must be retained within the centre in case of loss or damage.• The candidates must spend at least 2 hours on the development of the Free choice composition,plus the final write-up and recording of their composition, in the centre under the teacher’ssupervision (see page 34 of the specification).• Teachers are advised to refer to the Administrative Support Guide, released online on 1 September.Information for Candidates• You must submit two compositions:– One composition (free choice composition) can be chosen from six briefs relating to areasof study, or free composition, carrying 40 of the marks for the composing assessment. Thiscomposition must be at least 4 minutes in duration.– One composition must be from a list of four briefs assessing technique, carrying 20 of the marksfor the composing assessment. These briefs are released on 1 April in the year of certification.• Both compositions must have a combined minimum duration of 6 minutes. If you submitcompositions that are less than a total of six minutes you will not be awarded any marks.• The statements you make to introduce yourself and your compositions at the start of the recording and any gaps between the pieces do not count towards the composition time.• The maximum mark for this component is 60.• You are reminded of the importance of clear and orderly presentation of your scoreand recording.Paper Reference 9MU0/02Release date: Saturday 1 September 2018MusicAdvancedComponent 2: ComposingFree choice composition briefs2W59279AComposition TaskYou will compose one piece of music. This can be either a free composition or to a set brief related to an area of study.Free compositionYou are free to draw inspiration or starting points from set works and briefs from previous years as well as exploring your own interests and music from the world around you. The piece you compose may be for any instrument or voice, or combination of instruments and/or voices, and in any style.You must identify the intended audience and occasion and indicate them on the Composition Authentication Sheet. Assessment will be based on the creation anddevelopment of musical ideas with coherence, expressive control and technical control.Set briefSubject to the brief, you may compose for any instrument or voice, or combination of instruments and/or voices, and in any style. You are free to draw inspiration or starting points from set works and other music.You should consider the audience and occasion specified in your chosen brief. Assessment will be based on the creation and development of musical ideas with coherence, expressive control and technical control.3W59279A Choose one of the following briefs.Select one of the following briefs, and compose your piece of music according to the brief.Brief 1 – Vocal MusicCompose a Recitative and Aria for an opera or for a piece of musical theatre. Your piece must feature at least one voice and instrumental accompaniment.Brief 2 – Instrumental MusicCompose a piece in Sonata Form for a piano trio (piano, violin, cello) that would be suitable for performance at an international chamber music festival.Brief 3 – Music for FilmCompose music for the opening titles for a modern Western film. Your music should depict at least three contrasting scenes or characters from the film.Brief 4 – Popular Music and JazzCompose an instrumental piece in a heavy rock style, using suitable forces, to be heard as the backing to the launch of a new sports car.Brief 5 – FusionsCompose a piece for use in a ballroom dancing competition combining a Latin American musical style with the Viennese Waltz.Brief 6 – New DirectionsCompose an instrumental piece in an atonal idiom, with or without electronicmanipulation, that would be suitable to accompany an exhibition of astronomical images at a science museum.。

数模软件ECLIPSE初学指南

记得上大学最早学围棋时总感觉无从入手，看身边的朋友下棋时学着聂卫平从容入定，潇洒自如的样子，很是羡慕。

后来从书店买来围棋入门指南，夜深人静时照着指南慢慢学如何吃子，如何做眼，什么是打劫，怎么样布局。

掌握了一点基本知识以后开始找水平最差的下，输了一定不能弃擂，脸皮要厚，缠着对方接着下。

赢了水平最差的人后去找中等水平的人下。

这样经过一年半载，再看以前那些学着聂卫平从容入定，潇洒自如下棋的同学，心想他们原来不过如此，赶老聂差十万八千里哪。

在这里也有许多人把我叫大师，专家，如果哪一天你觉得其实我的水平也很一般，那你就到了专业段位了。

市场上有不少关于油藏数值模拟的书，但好像没有类似围棋入门指南那样从基础开始一步一步介绍的书。

我收到不下二十个问油藏数值模拟如何入门的问题。

我尝试写一写油藏数值模拟入门指南，希望对那些刚刚开始进入油藏数值模拟领域的工作者有所帮助。

第一：从掌握一套商业软件入手。

我给所有预从事油藏数值模拟领域工作的人员第一个建议是先从学一套商业数值模拟软件开始。

起点越高越好，也就是说软件功能越强越庞大越好。

现在在市场上流通的ECLIPSE,VIP和CMG都可以。

如果先学小软件容易走弯路。

有时候掌握一套小软件后再学商业软件会有心里障碍。

对于软件的学习，当然如果能参加软件培训最好。

如果没有机会参加培训，这时候你就需要从软件安装时附带的练习做起。

油藏数值模拟软件通常分为主模型，数模前处理和数模后处理。

主模型是数模的模拟器，即计算部分。

这部分是最重要的部分也是最难掌握的部分。

它可以细分为黑油模拟器，组分模拟气，热采模拟器，流线法模拟器等。

数模前处理是一些为主模拟器做数据准备的模块。

比如准备油田的构造模型，属性模型，流体的PVT参数，岩石的相渗曲线和毛管压力参数，油田的生产数据等。

数模后处理是显示模拟计算结果以及进行结果分析。

以ECLIPSE软件为例，ECLIPSE100,ECLIPSE300和FrontSim是主模拟器。

Networks 1_ Systems Biology, Metabolic Kinetic & Flux Balance Optimization Methods

10
Glycolysis Dynamic Mass Balances
d (G 6 P ) = vHK − vPGI − vG 6 PDH dt d (F 6 P ) = vPGI − vPFK + vTA + vTKII dt d (FDP ) = vPFK − v ALD dt d (DHAP ) = v ALD − vTPI dt d (GA3P ) = v ALD + vTPI − vGAPDH + vTKI + vTKII − vTA dt d (1,3DPG ) = vGAPDH − vPGK − vDPGM dt
(/exec/obidos/ASIN/185578047X/)
2) Enzymes & substrates are closer to equimolar than in classical in vitro experiments. 3) Proteins close to crystalline densities so some reactions occur faster while some normally spontaneous reactions become undetectably slow. e.g. Bouffard, et al., Dependence of lactose metabolism upon
1. vj is the jth reaction rate, b is the transport rate vecchiometric matrix” = moles of metabolite i produced in reaction j
8
RBC model integration

TI-83 84 Guide for Introductory Statistics说明书

TI-83/84Guide for Introductory Statistics Includes step-by-step instructions,practice exercises,and links to videotutorials.Covers all calculator featuresneeded for AP®Statistics ExamInstructions excerpted fromAdvanced High School Statistics,3rd ed.available for FREE at /ahssLeah DorazioSan Francisco University High School******************May23,2022Copyright©2022OpenIntro,Inc.Third Edition.Updated:May23,2022.This guide is available under a Creative Commons license.Visit for a free PDF,to download the sourceﬁles,or for more information about the license.AP®is a trademark registered and owned by the College Board,which was not involved in the production of, and does not endorse,this product.2ContentsSummarizing data5 Entering data (5)Calculating summary statistics (5)Drawing a box plot (6)What to do if you cannotﬁnd L1or another list (6)Practice exercises (7)Finding area under the normal curve (7)Find a Z-score that corresponds to a percentile (8)Practice exercises (8)Probability10 Computing the binomial coeﬃcient (10)Computing the binomial formula (11)Computing a cumulative binomial probability (11)Practice exercises (11)Inference for categorical data13 1-proportion Z-interval and Z-test (13)Practice exercises (14)2-proportion Z-interval and Z-test (15)Practice exercises (16)Finding area unders the Chi-square curve (17)Chi-square goodness ofﬁt test (17)Chi-square test for two-way tables (18)Practice exercises (19)Inference for numerical data20 1-sample t-test and t-interval (20)Practice exercises (21)1-sample t-test and t-interval with paired data (22)Practice exercises (23)2-sample t-test and t-interval (24)Practice exercises (26)Introduction to linear regression27 Finding a,b,R2,and r for a linear model (27)What to do if r2and r do not show up on a TI-83/84 (28)What to do if a TI-83/84returns:ERR:DIM MISMATCH (28)34CONTENTS Practice exercises (29)t-test and t-interval for the slope of a regression line (30)Summarizing dataEntering dataTI-83/84:ENTERING DATATheﬁrst step in summarizing data or making a graph is to enter the data set into a e STAT,Edit.1.Press STAT.2.Choose1:Edit.3.Enter data into L1or another list.Calculating summary statisticsTI-84:Usestandard1.2.3.4.5.6.7.TI-83:5Calculating the summary statistics will return the following information.It will be neces-sary to hit the down arrow to see all of the summary statistics.¯x Mean n Sample size or#of data points Σx Sum of all the data values minX MinimumΣx2Sum of all the squared data values Q1First quartileSx Sample standard deviation Med Medianσx Population standard deviation maxX MaximumDrawing a box plotTI-83/84:1.2.3.4.5.6.7.What to do if you cannotﬁnd L1or another listTI-83/84:Restore1.2.3.Practice exercisesGUIDED PRACTICE0.1Enter the following10data points into a list on a calculator:5,8,1,19,3,1,11,18,20,5Find the summary statistics and make a box plot of the data.1Finding area under the normal curveTI-84:FINDING AREA UNDER THE NORMAL CURVEUse2ND VARS,normalcdf toﬁnd an area/proportion/probability to the left or right of a Z-score or between two Z-scores.1.Choose2ND VARS(i.e.DISTR).2.Choose2:normalcdf.3.Enter the Z-scores that correspond to the lower(left)and upper(right)bounds.4.Leaveµas0andσas1.5.Down arrow,choose Paste,and hit ENTER.TI-83:Do steps1-2,then enter the lower bound and upper bound separated by a comma,e.g.normalcdf(2,5),and hit ENTER.1The summary statistics should be¯x=9.1,Sx=7.475,Q1=3,etc.The box plot should be as follows.Find a Z-score that corresponds to a percentileTI-84:FIND A Z-SCORE THAT CORRESPONDS TO A PERCENTILEUse2ND VARS,invNorm toﬁnd the Z-score that corresponds to a given percentile.1.Choose2ND VARS(i.e.DISTR).2.Choose3:invNorm.3.Let Area be the percentile as a decimal(the area to the left of desired Z-score).4.Leaveµas0andσas1.5.Down arrow,choose Paste,and hit ENTER.TI-83:Do steps1-2,then enter the percentile as a decimal,e.g.invNorm(.40),then hit ENTER.Practice exercisesGUIDED PRACTICE0.3Find the area under the normal curve to right of Z=2.32normalcdf gives the result without drawing the graph.To draw the graph,do2nd VARS,DRAW, 1:ShadeNorm.However,beware of errors caused by other plots that might interfere with this plot.3Now we want to shade to the right.Therefore our lower bound will be2and the upper bound will be5(or a number bigger than5)to get P(Z>2)=0.023.GUIDED PRACTICE 0.4Find the area under the normal curve between -1.5and 1.5.4GUIDED PRACTICE 0.6Find the Z-score such that 20percent of the area is to the right of that Z-score.5GUIDED PRACTICE 0.8Approximately what percent of these babies weighed greater than 10pounds?74Herewe are given both the lower and the upper bound.Lower bound is -1.5and upper bound is 1.5.The area under the normal curve between -1.5and 1.5=P (−1.5<Z <1.5)=0.866.5If 20%of the area is the right,then 80%of the area is to the left.Letting area be 0.80,we get Z =0.841./1471-2393/8/57Z =10−7.441.33=ing a lower bound of 2and an upper bound of 5,we get P (Z >1.925)=0.027.Approximately 2.7%of the newborns weighed over 10pounds.Probability and probability distributionsComputing the binomial coeﬃcientTI-83/84:Usesame1.2.3.4.5.6.Example:10Computing the binomial formulaTI-84:Useindependent1.2.3.4.5.6.TI-83:binompdf(n,Computing a cumulative binomial probabilityTI-84:Userences1.2.3.4.5.6.TI-83:follows:Practice exercisesGUIDED PRACTICE0.9Find the number of ways of arranging3blue marbles and2red marbles.8 8Here n=5and k=3.Doing5nCr3gives the number of combinations as10.GUIDED PRACTICE0.10There are13marbles in a bag.4are blue and9are red.Randomly draw5marbles with replacement.Find the probability you get exactly3blue marbles.9GUIDED PRACTICE0.11There are13marbles in a bag.4are blue and9are red.Randomly draw5marbles withreplacement.Find the probability you get at most3blue marbles(i.e.less than or equal to3blue marbles).109Here,n=5,p=4/13,and k=3,so set trials=5,p=4/13and x value=3.The probability is0.1396.10Similarly,set trials=5,p=4/13and x value=3.The cumulative probability is0.9662.Inference for categorical data 1-proportion Z-interval and Z-testTI-83/84:13TI-83/84:Use1.2.3.4.5.6.7.8.Practice exercisesGUIDED PRACTICE0.12Using a calculator,evaluate the conﬁdence interval from the example on intelligent life.Recall that we wanted toﬁnd a95%conﬁdence interval for the proportion of U.S.adults who think there is intelligent life on other planets.The sample percent was68%and the sample size was1,033.11GUIDED PRACTICE0.13Using a calculator,ﬁnd the test statistic and p-value for the example on nuclear energy.Recall that we were looking for evidence that more than half of U.S.adults oppose nuclear energy.The sample percent was54%,and the sample size was1019.1211Navigate to1-PropZInt on the calculator.Toﬁnd x,the number of yes responses in the sample,we multiply the sample proportion by the sample size.Here0.68×1033=702.44.We must round this to an integer,so we use x=702.Also,n=1033and C-Level=0.95.The95%conﬁdence interval is(0.651, 0.708).12Navigate to1-PropZTest on the calculator.Let p0=0.5.Toﬁnd x,do0.54×1019=550.26.This needs to be an integer,so round to the closest integer.Here x=550.Also,n=1019.We are looking for evidence that greater than half oppose,so choose>p0.When we do Calculate,we get the test statistic: Z=2.64and the p-value:p=0.006.2-proportion Z-interval and Z-testTI-83/84:TI-83/84:Practice exercisesGUIDED PRACTICE0.14A quality control engineer collects a sample of gears,examining1000gears from eachcompany andﬁnds that879gears pass inspection from the current supplier and958pass inspection from the prospective e a calculator toﬁnd a95%conﬁdence interval for the diﬀerence(current−prospective)in the proportion that would pass inspection.1313Navigate to2-PropZInt on the calculator.Let x1=879,n1=1000,x2=958,and n2=1000.C-Level is.95.This should lead to an interval of(-0.1027,-0.0553),which matches what we found previously.14Navigate to2-PropZTest on the calculator.Correctly going through the calculator steps should lead to a solution with the test statistic z=-2.977and the p-value p=0.00145.These two values match our calculated values from the previous example to within rounding error.The pooled proportion is given as ^p=0.0133.Note:values for x1and x2were given in the table.If,instead,proportions are given,ﬁnd x1 and x2by multiplying the proportions by the sample sizes and rounding the result to an integer.Finding areas under the chi-square curveTI-84:Chi-square goodness ofﬁt testTI-84:Use1.2.3.4.5.6.7.TI-83:manually,L3Chi-square test for two-way tablesTI-83/84:ENTERING DATA INTO A TWO-WAY TABLE1.Hit2ND x−1(i.e.MATRIX).2.Right arrow to EDIT.3.Hit1or ENTER to select matrix A.4.Enter the dimensions by typing#rows,ENTER,#columns,ENTER.5.Enter the data from the two-way table.TI-83/84:CHI-SQUARE TEST OF HOMOGENEITY AND INDEPENDENCE Use STAT,TESTS,χ2-Test.1.First enter two-way table data as described in the previous box.2.Choose STAT.3.Right arrow to TESTS.4.Down arrow and choose C:χ2-Test.5.Down arrow,choose Calculate,and hit ENTER,which returnsχ2chi-square test statisticp p-valuedf degrees of freedomPractice exercisesGUIDED PRACTICE0.16Use a calculator toﬁnd the upper tail area for the the chi-square distribution with5degrees of freedom and aχ2=5.1.1515Use a lower bound of5.1,an upper bound of1000,and d f=5.The upper tail area is0.4038.16Enter the observed counts into L1and the expected counts into L2.the GOF test.Make sure that Observed:is L1and Expected:is L2.Let df:be5.You shouldﬁnd thatχ2=17.36and p-value=0.004.17First create a2×3matrix with the data.Theﬁnal summaries should beχ2=106.4,p-value isp=8.06×10−24≈0,and df=2.Below is the matrix of expected values:Obama Congr.Dem.Congr.Rep.Approve731.59693.45693.96Disapprove726.41688.55689.04Inference for numerical data 1-sample t-test and t-intervalTI-83/84:20TI-83/84:Use1.2.3.4.5.6.Practice exercisesGUIDED PRACTICE0.19The average time for all runners whoﬁnished the Cherry Blossom Run in2006was93.3 minutes.In2017,the average time for100randomly selected participants was97.3,witha standard deviation e a calculator toﬁnd the T-statistic and p-value for the appropriate test to see if the average time for the participants in2017is diﬀerent than it was in2006.18GUIDED PRACTICE0.20Use a calculator toﬁnd a95%conﬁdence interval for the mean mercury content in croakerwhiteﬁsh(Paciﬁc).The sample size was15,and the sample mean and standard deviation were computed as0.287and0.069ppm(parts per million),respectively.1918Navigate to T-Test.Letµ0be93.3.¯x is97.3,S x is17.0,and n=100.Choose=to correspond to H A.We get t=2.353and the p-value p=0.021.The d f=100−1=99.19Navigate to TInterval.We do not have all the data,so choose Stats.Enter¯x and Sx.Note:Sx is the sample standard deviation(0.069),not the SE of the sample mean.Let n=15and C-Level=0.95. This should give the interval(0.249,0.325).The d f=15−1=141-sample t-test and t-interval with paired dataTI-83/84:1-SAMPLE T-TEST WITH PAIRED DATAUse STAT,TESTS,T-Test.1.Choose STAT.2.Right arrow to TESTS.3.Down arrow and choose2:T-Test.4.Choose Data if you have all the data or Stats if you have the mean and standarddeviation.5.Letµ0be the null or hypothesized value ofµdiff.•If you choose Data,let List be L3or the list in which you entered thediﬀerences(don’t forget to enter the diﬀerences!)and let Freq be1.•If you choose Stats,enter the mean,SD,and sample size of the diﬀerences.6.Choose=,<,or>to correspond to H A.7.Choose Calculate and hit ENTER,which returns:t t statisticp p-value¯x the sample mean of the diﬀerencesSx the sample SD of the diﬀerencesn the sample size of the diﬀerencesPractice exercisesGUIDED PRACTICE0.22Use the data in the table above toﬁnd the test statistic and p-value for a test of H0:µdiﬀ=0versus H A:µdiﬀ=0.2120Navigate to TInterval.We do not have all the data,so choose Stats.Enter¯x=3.58and Sx=13.42. Let n=68and C-Level=0.95.This should give the interval(0.332,6.828).The intervals are equivalent when rounded to two decimal places.21Navigate to T-Test.We do not have all the data,so choose Stats.Enterµ0=0,¯x=3.58,Sx= 13.42,n=68,and choose=µ0since the alternative hypothesis is two-sided.This should give the interval t=2.2and p=0.031.2-sample t-test and t-intervalTI-83/84:2-SAMPLE T-TESTUse STAT,TESTS,2-SampTTest.1.Choose STAT.2.Right arrow to TESTS.3.Choose4:2-SampTTest.4.Choose Data if you have all the data or Stats if you have the means and standarddeviations.•If you choose Data,let List1be L1or the list that contains sample1andlet List2be L2or the list that contains sample2(don’t forget to enter thedata!).Let Freq1and Freq2be1.•If you choose Stats,enter the mean,SD,and sample size for sample1andfor sample25.Choose=,<,or>to correspond to H A.6.Let Pooled be NO.7.Choose Calculate and hit ENTER,which returns:t t statistic Sx1SD of sample1p p-value Sx2SD of sample2df degrees of freedom n1size of sample1¯x1mean of sample1n2size of sample2¯x2mean of sample2TI-83/84: Use1.2.3.4.5.6.Practice exercises22Navigate to2-SampTTest.Because we have the summary statistics rather than all of the data,choose Stats.Let¯x1=3.50,Sx1=5.17,n1=9,¯x2=-4.33,Sx2=2.76,and n2=9.We get t=4.01,and the p-value p=8.4×10−4=0.00084.The degrees of freedom for the test is df=12.2.23Navigate to2-SampTInt.Because we have the summary statistics rather than all of the data,choose Stats.Let¯x1=79.41,Sx1=14,n1=30,¯x2=74.1,Sx2=20,and n2=30.The interval is(−3.6,14.2)with d f=51.9.Introduction to linear regression Finding a,b,R2,and r for a linear modelR,AND r FOR A LINEAR MODELTI-84:FINDING a,b,2Use STAT,CALC,LinReg(a+bx).1.Choose STAT.2.Right arrow to CALC.3.Down arrow and choose8:LinReg(a+bx).•Caution:choosing4:LinReg(ax+b)will reverse a and b.4.Let Xlist be L1and Ylist be L2(don’t forget to enter the x and y values in L1and L2before doing this calculation).5.Leave FreqList blank.6.Leave Store RegEQ blank.7.Choose Calculate and hit ENTER,which returns:a a,the y-intercept of the bestﬁt lineb b,the slope of the bestﬁt liner2R2,the explained variancer r,the correlation coeﬃcientTI-83:Do steps1-3,then enter the x list and y list separated by a comma,e.g. LinReg(a+bx)L1,L2,then hit ENTER.27What to do if r2and r do not show up on a TI-83/84WHAT TO DO IF2r AND r DO NOT SHOW UP ON A TI-83/84If r2and r do now show up when doing STAT,CALC,LinReg,the diagnostics must be turned on.This only needs to be once and the diagnostics will remain on.1.Hit2ND0(i.e.CATALOG).2.Scroll down until the arrow points at DiagnosticOn.3.Hit ENTER and ENTER again.The screen should now say:DiagnosticOnDoneWhat to do if a TI-83/84returns:ERR:DIM MIS-MATCHPractice exercisesGUIDED PRACTICE0.25The data set loan50,introduced in Chapter1,contains information on randomly sampledloans oﬀered through the Lending Club.A subset of the data matrix is shown in Figure1. Use a calculator toﬁnd the equation of the least squares regression line for predicting loan amount from total income.24total income loan amount159********260000600037500025000475000600052540002500066700064007288003000Figure1:Sample of data from loan50.24a=11121and b=0.0043,thereforeˆy=11121+0.0043x.t-test and t-interval for the slope of a regression lineTI-83/84:TI-84:。

CourseForge_SDS

CourseForge_SDSCourseForgeChris Schlechty, Kenneth Kuan, Scott Clifford, Guanyu Chu, Kansu Dincer, Sarah Tachibana, Andy Hou System Design Specification and Planning Document Draft 1.09April 25, 2007CSE 403 - CSRocks Inc.1. IntroductionCourseForge relies on a LAMP architecture. User and course information is stored ina MySQL database, which is accessed via AJAX XMLHttpRequest calls to PHPfunctions which make queries and convert the result to XML. The XML data isparsed and put on screen via Javascript/DOM modification. The database itself is populated using both data given to us by UW, as well as data collected using a Java screen scraper to parse professor ratings information.The modular breakdown of CourseForge follows: prior to interacting with thescheduling system, users must login. The Login module manages authentication, new user registration, and password recovery. The rest of the interface is representedthrough a Student module, which contains a VisualSchedule and a Search module.The VisualSchedule module manages individual Tabs, while the Search modulehandles queries and addition of courses to the schedule.2. Implementation view3. Design view - UML class diagram4. Process view – UML sequence diagrams5. Database Schema6. Design Alternatives and/or AssumptionsWe considered a few alternative representations and implementations of CourseForge before settling on the current version with our customer. These included: ? Information Gathering: We weren’t originally sure whether UW would provide us the course information necessary to implement our system, so weput thought into a screen scraper module that would periodically parse theonline course catalog. This would of course be more inconvenient, but for thetime being UW has given us a copy of a quarter’s worth of course information.We assume that, should CourseForge see widespread use, UW will continueto give us access to the necessary informationSchedule Representation: Given the limited screen estate available to us, we tried to think of other ways to represent the visual schedule. One was have a separate graph for each day. Times would be aligned horizontally, and eachrow would consist of a class, with a horizontal bar representing that class’duration. However, this view doesn’t allow for a holistic week view, andstudents are presumably already used to the day-per-column view used in thecurrent Visual Schedule, which we decided to stick with.General assumptions for this architecture include:We assume that Javascript, AJAX, and PHP will all support our object-oriented design. Javascript in particular is a more procedural language, andmay require extra effort to fit into the rest of the framework.We assume that Google Web Toolkit will provide us with coherent modules to piece together. GWT makes creating AJAX applications much easier, but depending on the resulting modules, it may be difficult to test and/or modifyin the future.1. Team StructureCourseforge will be divided into three main teams for the work up to the beta release: test team, AJAX team, and serverside/database team. There is member crossover between teams, and the serverside/database team will all be assimilated into the other teams once their work is complete.The test team is responsible for unit testing, user testing, and system testing,though everyone is expected to run prelim tests on their own code. This team is composed of: Kansu, Scott, Kenneth, and Andy. The AJAX team is responsible for java coding, HTML, CSS, and other UI-related features. It is composed of: Scott, Kansu, Andy, and Kenneth. Finally, the database team is responsible for the PHP coding and the setup/maintenance of the database. It is composed of: Chris and Guanyu. Chris is primarily database; Guanyu is primarily PHP.2. Project Schedule3. Risk Assessment1. Test Plan1.Unit test strategyo Unit tests will exercise the modules.o We will establish an artificial environment in which the module can live and then invoke the routines of the module. We will consider a test passedonly if the module satisfies its predetermined behavior.o Unit tests will be run every time a developer wishes to add/update the module to the repository.2.System test strategyo This type of testing will be used to test the functionality of the subsystems and the overall system.o The tests will highly depend on the use cases prepared for development.o System tests will be run once after every build./doc/4842452f0066f5335a81219f.html ability test strategyo With the usability tests, we aim to test the ease and efficieny with which our product can be used.o We will use both the prototypes and the actual product tested by real people from within the target audience.o Prototype testing will be (and to some extent has been) employed during the early design stages. Product testing will be accomplished once for theuser interface and once more with nearly full product functionality (beta?).4.The client-server nature of the product and the variety of tools used bring up anadditional challenge for the testing team. The scarcity of the tools available to test dynamic content such as JavaScript (AJAX in particular) on the client end is another obstacle. High source code coverage will be our goal.5.We will use bugzilla for bug tracking purposes. The developer / tester whoemploys the unit testing will post a bug report to notify the rest of the team about the bug.2. Documentation PlanThere are two types of documentation we would like to provide which correspond to strictly internal use and internal/external use.The internal documentation, which only developers will view, will consist of bug tracking, source control, and code comments. We will track bugs using Bugzilla, and we will use Subversion for source control.The code comments will be produced as modules and components are coded. The idea behind this is to write comments while the code written is fresh in the developers mind. This way, the developer may give better explanations of their code. Also, if another team member would like to edit or understand a component, having the comments their immediately allows for easier understanding and the team members do not necessarily have to explain their code verbally if something is not clear (provided the comments are adequate).The conventions that we will use for commenting is as follows:1.Header/Overview Description of Componentsa.Title of the component.b.Brief overview of the component.2.Function Explanationsa.Short explanation of functionality.b.List of parameters if applicable.c.Return value if applicable.3.Inline comments/doc/4842452f0066f5335a81219f.html ed at the developers discretion for clarity.The internal/external documentation will serve as a reference for both developers and users of the system. This will allow for a centralized source of documentation so that two forms of documentation (one for developers and one for users) will not need to be updated when changes are made.These documents will be written in the form of help guides for the CourseForge sys tem. The goal is to make them much like the “Help” guides you would find in any standard program these days. The documents would be accessible via a “Help” link on the system UI.The help guides will be formatted as follows:Finally, we will write an installation guide which will describe the process of installing our project on a personal server.。

________________________________________________ Session S3C MINORITY ENGINEERING PROGRAM C

________________________________________________ 1Joseph E. Urban, Arizona State University, Department of Computer Science and Engineering, P.O. Box 875406, Tempe, Arizona, 85287-5406, joseph.urban@ 2Maria A. Reyes, Arizona State University, College of Engineering and Applied Sciences, Po Box 874521, Tempe, Arizona 852189-955, maria@ 3Mary R. Anderson-Rowland, Arizona State University, College of Engineering and Applied Sciences, P.O. Box 875506, Tempe, Arizona 85287-5506, mary.Anderson@MINORITY ENGINEERING PROGRAM COMPUTER BASICS WITH AVISIONJoseph E. Urban 1, Maria A. Reyes 2, and Mary R. Anderson-Rowland 3Abstract - Basic computer skills are necessary for success in an undergraduate engineering degree program. Students who lack basic computer skills are immediately at risk when entering the university campus. This paper describes a one semester, one unit course that provided basic computer skills to minority engineering students during the Fall semester of 2001. Computer applications and software development were the primary topics covered in the course that are discussed in this paper. In addition, there is a description of the manner in which the course was conducted. The paper concludes with an evaluation of the effort and future directions.Index Terms - Minority, Freshmen, Computer SkillsI NTRODUCTIONEntering engineering freshmen are assumed to have basic computer skills. These skills include, at a minimum, word processing, sending and receiving emails, using spreadsheets, and accessing and searching the Internet. Some entering freshmen, however, have had little or no experience with computers. Their home did not have a computer and access to a computer at their school may have been very limited. Many of these students are underrepresented minority students. This situation provided the basis for the development of a unique course for minority engineering students. The pilot course described here represents a work in progress that helped enough of the students that there is a basis to continue to improve the course.It is well known that, in general, enrollment, retention, and graduation rates for underrepresented minority engineering students are lower than for others in engineering, computer science, and construction management. For this reason the Office of Minority Engineering Programs (OMEP, which includes the Minority Engineering Program (MEP) and the outreach program Mathematics, Engineering, Science Achievement (MESA)) in the College of Engineering and Applied Sciences (CEAS) at Arizona State University (ASU) was reestablished in 1993to increase the enrollment, retention, and graduation of these underrepresented minority students. Undergraduate underrepresented minority enrollment has increased from 400 students in Fall 1992 to 752 students in Fall 2001 [1]. Retention has also increased during this time, largely due to a highly successful Minority Engineering Bridge Program conducted for two weeks during the summer before matriculation to the college [2] - [4]. These Bridge students were further supported with a two-unit Academic Success class during their first semester. This class included study skills, time management, and concept building for their mathematics class [5]. The underrepresented minority students in the CEAS were also supported through student chapters of the American Indian Science and Engineering Society (AISES), the National Society of Black Engineers (NSBE), and the Society of Hispanic Professional Engineers (SHPE). The students received additional support from a model collaboration within the minority engineering student societies (CEMS) and later expanded to CEMS/SWE with the addition of the student chapter of the Society of Women Engineers (SWE) [6]. However, one problem still persisted: many of these same students found that they were lacking in the basic computer skills expected of them in the Introduction to Engineering course, as well as introductory computer science courses.Therefore, during the Fall 2001 Semester an MEP Computer Basics pilot course was offered. Nineteen underrepresented students took this one-unit course conducted weekly. Most of the students were also in the two-unit Academic Success class. The students, taught by a Computer Science professor, learned computer basics, including the sending and receiving of email, word processing, spreadsheets, sending files, algorithm development, design reviews, group communication, and web page development. The students were also given a vision of advanced computer science courses and engineering and of computing careers.An evaluation of the course was conducted through a short evaluation done by each of five teams at the end of each class, as well as the end of semester student evaluations of the course and the instructor. This paper describes theclass, the students, the course activities, and an assessment of the short-term overall success of the effort.M INORITY E NGINEERING P ROGRAMSThe OMEP works actively to recruit, to retain, and to graduate historically underrepresented students in the college. This is done through targeted programs in the K-12 system and at the university level [7], [8]. The retention aspects of the program are delivered through the Minority Engineering Program (MEP), which has a dedicated program coordinator. Although the focus of the retention initiatives is centered on the disciplines in engineering, the MEP works with retention initiatives and programs campus wide.The student’s efforts to work across disciplines and collaborate with other culturally based organizations give them the opportunity to work with their peers. At ASU the result was the creation of culturally based coalitions. Some of these coalitions include the American Indian Council, El Concilio – a coalition of Hispanic student organizations, and the Black & African Coalition. The students’ efforts are significant because they are mirrored at the program/staff level. As a result, significant collaboration of programs that serve minority students occurs bringing continuity to the students.It is through a collaboration effort that the MEP works closely with other campus programs that serve minority students such as: Math/Science Honors Program, Hispanic Mother/Daughter Program, Native American Achievement Program, Phoenix Union High School District Partnership Program, and the American Indian Institute. In particular, the MEP office had a focus on the retention and success of the Native American students in the College. This was due in large part to the outreach efforts of the OMEP, which are channeled through the MESA Program. The ASU MESA Program works very closely with constituents on the Navajo Nation and the San Carlos Apache Indian Reservation. It was through the MESA Program and working with the other campus support programs that the CEAS began investigating the success of the Native American students in the College. It was a discovery process that was not very positive. Through a cohort investigation that was initiated by the Associate Dean of Student Affairs, it was found that the retention rate of the Native American students in the CEAS was significantly lower than the rate of other minority populations within the College.In the spring of 2000, the OMEP and the CEAS Associate Dean of Student Affairs called a meeting with other Native American support programs from across the campus. In attendance were representatives from the American Indian Institute, the Native American Achievement Program, the Math/Science Honors Program, the Assistant Dean of Student Life, who works with the student coalitions, and the Counselor to the ASU President on American Indian Affairs, Peterson Zah. It was throughthis dialogue that many issues surrounding student success and retention were discussed. Although the issues andconcerns of each participant were very serious, the positiveeffect of the collaboration should be mentioned and noted. One of the many issues discussed was a general reality that ahigh number of Native American students were c oming to the university with minimal exposure to technology. Even through the efforts in the MESA program to expose studentsto technology and related careers, in most cases the schoolsin their local areas either lacked connectivity or basic hardware. In other cases, where students had availability to technology, they lacked teachers with the skills to help them in their endeavors to learn about it. Some students were entering the university with the intention to purse degrees in the Science, Technology, Engineering, and Mathematics (STEM) areas, but were ill prepared in the skills to utilize technology as a tool. This was particularly disturbing in the areas of Computer Science and Computer Systems Engineering where the basic entry-level course expected students to have a general knowledge of computers and applications. The result was evident in the cohort study. Students were failing the entry-level courses of CSE 100 (Principals of Programming with C++) or CSE 110 (Principals of Programming with Java) and CSE 200 (Concepts of Computer Science) that has the equivalent of CSE 100 or CSE 110 as a prerequisite. The students were also reporting difficulty with ECE 100, (Introduction to Engineering Design) due to a lack of assumed computer skills. During the discussion, it became evident that assistance in the area of technology skill development would be of significance to some students in CEAS.The MEP had been offering a seminar course inAcademic Success – ASE 194. This two-credit coursecovered topics in study skills, personal development, academic culture issues and professional development. The course was targeted to historically underrepresented minority students who were in the CEAS [3]. It was proposed by the MEP and the Associate Dean of Student Affairs to add a one-credit option to the ASE 194 course that would focus entirely on preparing students in the use of technology.A C OMPUTERB ASICSC OURSEThe course, ASE 194 – MEP Computer Basics, was offered during the Fall 2001 semester as a one-unit class that met on Friday afternoons from 3:40 pm to 4:30 pm. The course was originally intended for entering computer science students who had little or no background using computer applications or developing computer programs. However, enrollment was open to non-computer science students who subsequently took advantage of the opportunity. The course was offered in a computer-mediated classroom, which meantthat lectures, in- class activities, and examinations could all be administered on comp uters.During course development prior to the start of the semester, the faculty member did some analysis of existing courses at other universities that are used by students to assimilate computing technology. In addition, he did a review of the comp uter applications that were expected of the students in the courses found in most freshman engineering programs.The weekly class meetings consisted of lectures, group quizzes, accessing computer applications, and group activities. The lectures covered hardware, software, and system topics with an emphasis on software development [9]. The primary goals of the course were twofold. Firstly, the students needed to achieve a familiarity with using the computer applications that would be expected in the freshman engineering courses. Secondly, the students were to get a vision of the type of activities that would be expected during the upper division courses in computer science and computer systems engineering and later in the computer industry.Initially, there were twenty-two students in the course, which consisted of sixteen freshmen, five sophomores, and one junior. One student, a nursing freshman, withdrew early on and never attended the course. Of the remaining twenty-one students, there were seven students who had no degree program preference; of which six students now are declared in engineering degree programs and the seventh student remains undecided. The degree programs of the twenty-one students after completion of the course are ten in the computing degree programs with four in computer science and six in computer systems engineering. The remaining nine students includes one student in social work, one student is not decided, and the rest are widely distributed over the College with two students in the civil engineering program and one student each in bioengineering, electrical engineering, industrial engineering, material science & engineering, and mechanical engineering.These student degree program demographics presented a challenge to maintain interest for the non-computing degree program students when covering the software development topics. Conversely, the computer science and computer systems engineering students needed motivation when covering applications. This balance was maintained for the most part by developing an understanding that each could help the other in the long run by working together.The computer applications covered during the semester included e-mail, word processing, web searching, and spreadsheets. The original plan included the use of databases, but that was not possible due to the time limitation of one hour per week. The software development aspects included discussion of software requirements through specification, design, coding, and testing. The emphasis was on algorithm development and design review. The course grade was composed of twenty-five percent each for homework, class participation, midterm examination, and final examination. An example of a homework assignment involved searching the web in a manner that was more complex than a simple search. In order to submit the assignment, each student just had to send an email message to the faculty member with the information requested below. The email message must be sent from a student email address so that a reply can be sent by email. Included in the body of the email message was to be an answer for each item below and the URLs that were used for determining each answer: expected high temperature in Centigrade on September 6, 2001 for Lafayette, LA; conversion of one US Dollar to Peruvian Nuevo Sols and then those converted Peruvian Nuevo Sols to Polish Zlotys and then those converted Polish Zlotys to US Dollars; birth date and birth place of the current US Secretary of State; between now and Thursday, September 6, 2001 at 5:00 pm the expected and actual arrival times for any US domestic flight that is not departing or arriving to Phoenix, AZ; and your favorite web site and why the web site is your favorite. With the exception of the favorite web site, each item required either multiple sites or multiple levels to search. The identification of the favorite web site was introduced for comparison purposes later in the semester.The midterm and final examinations were composed of problems that built on the in-class and homework activities. Both examinations required the use of computers in the classroom. The submission of a completed examination was much like the homework assignments as an e-mail message with attachments. This approach of electronic submission worked well for reinforcing the use of computers for course deliverables, date / time stamping of completed activities, and a means for delivering graded results. The current technology leaves much to be desired for marking up a document in the traditional sense of hand grading an assignment or examination. However, the students and faculty member worked well with this form of response. More importantly, a major problem occurred after the completion of the final examination. One of the students, through an accident, submitted the executable part of a browser as an attachment, which brought the e-mail system to such a degraded state that grading was impossible until the problem was corrected. An ftp drop box would be simple solution in order to avoid this type of accident in the future until another solution is found for the e-mail system.In order to get students to work together on various aspects of the course, there was a group quiz and assignment component that was added about midway through the course. The group activities did not count towards the final grade, however the students were promised an award for the group that scored the highest number of points.There were two group quizzes on algorithm development and one out-of-class group assignment. The assignment was a group effort in website development. This assignment involved the development of a website that instructs. The conceptual functionality the group selected for theassignment was to be described in a one-page typed double spaced written report by November 9, 2001. During the November 30, 2001 class, each group presented to the rest of the class a prototype of what the website would look like to the end user. The reports and prototypes were subject to approval and/or refinement. Group members were expected to perform at approximately an equal amount of effort. There were five groups with four members in four groups and three members in one group that were randomly determined in class. Each group had one or more students in the computer science or computer systems engineering degree programs.The three group activities were graded on a basis of one million points. This amount of points was interesting from the standpoint of understanding relative value. There was one group elated over earning 600,000 points on the first quiz until the group found out that was the lowest score. In searching for the group award, the faculty member sought a computer circuit board in order to retrieve chips for each member of the best group. During the search, a staff member pointed out another staff member who salvages computers for the College. This second staff member obtained defective parts for each student in the class. The result was that each m ember of the highest scoring group received a motherboard, in other words, most of the internals that form a complete PC. All the other students received central processing units. Although these “awards” were defective parts, the students viewed these items as display artifacts that could be kept throughout their careers.C OURSE E VALUATIONOn a weekly basis, there were small assessments that were made about the progress of the course. One student was selected from each team to answer three questions about the activities of the day: “What was the most important topic covered today?”, “What topic covered was the ‘muddiest’?”, and “About what topic would you like to know more?”, as well as the opportunity to provide “Other comments.” Typically, the muddiest topic was the one introduced at the end of a class period and to be later elaborated on in the next class. By collecting these evaluation each class period, the instructor was able to keep a pulse on the class, to answer questions, to elaborate on areas considered “muddy” by the students, and to discuss, as time allowed, topics about which the students wished to know more.The overall course evaluation was quite good. Nineteen of the 21 students completed a course evaluation. A five-point scale w as used to evaluate aspects of the course and the instructor. An A was “very good,” a B was “good,” a C was “fair,” a D was “poor,” and an E was “not applicable.” The mean ranking was 4.35 on the course. An average ranking of 4.57, the highest for the s even criteria on the course in general, was for “Testbook/ supplementary material in support of the course.” The “Definition and application of criteria for grading” received the next highest marks in the course category with an average of 4.44. The lowest evaluation of the seven criteria for the course was a 4.17 for “Value of assigned homework in support of the course topics.”The mean student ranking of the instructor was 4.47. Of the nine criteria for the instructor, the highest ranking of 4.89 was “The instructor exhibited enthusiasm for and interest in the subject.” Given the nature and purpose of this course, this is a very meaningful measure of the success of the course. “The instructor was well prepared” was also judged high with a mean rank of 4.67. Two other important aspects of this course, “The instructor’s approach stimulated student thinking” and “The instructor related course material to its application” were ranked at 4.56 and 4.50, respectively. The lowest average rank of 4.11 was for “The instructor or assistants were available for outside assistance.” The instructor keep posted office hours, but there was not an assistant for the course.The “Overall quality of the course and instruction” received an average rank of 4.39 and “How do you rate yourself as a student in this course?” received an average rank of 4.35. Only a few of the students responded to the number of hours per week that they studies for the course. All of the students reported attending at least 70% of the time and 75% of the students said that they attended over 90% of the time. The students’ estimate seemed to be accurate.A common comment from the student evaluations was that “the professor was a fun teacher, made class fun, and explained everything well.” A common complaint was that the class was taught late (3:40 to 4:30) on a Friday. Some students judged the class to be an easy class that taught some basics about computers; other students did not think that there was enough time to cover all o f the topics. These opposite reactions make sense when we recall that the students were a broad mix of degree programs and of basic computer abilities. Similarly, some students liked that the class projects “were not overwhelming,” while other students thought that there was too little time to learn too much and too much work was required for a one credit class. Several students expressed that they wished the course could have been longer because they wanted to learn more about the general topics in the course. The instructor was judged to be a good role model by the students. This matched the pleasure that the instructor had with this class. He thoroughly enjoyed working with the students.A SSESSMENTS A ND C ONCLUSIONSNear the end of the Spring 2002 semester, a follow-up survey that consisted of three questions was sent to the students from the Fall 2001 semester computer basics course. These questions were: “Which CSE course(s) wereyou enrolled in this semester?; How did ASE 194 - Computer Basi cs help you in your coursework this semester?; and What else should be covered that we did not cover in the course?”. There were eight students who responded to the follow-up survey. Only one of these eight students had enrolled in a CSE course. There was consistency that the computer basics course helped in terms of being able to use computer applications in courses, as well as understanding concepts of computing. Many of the students asked for shortcuts in using the word processing and spreadsheet applications. A more detailed analysis of the survey results will be used for enhancements to the next offering of the computer basics course. During the Spring 2002 semester, there was another set of eight students from the Fall 2001 semester computer basi cs course who enrolled in one on the next possible computer science courses mentioned earlier, CSE 110 or CSE 200. The grade distribution among these students was one grade of A, four grades of B, two withdrawals, and one grade of D. The two withdrawals appear to be consistent with concerns in the other courses. The one grade of D was unique in that the student was enrolled in a CSE course concurrently with the computer basics course, contrary to the advice of the MEP program. Those students who were not enrolled in a computer science course during the Spring 2002 semester will be tracked through the future semesters. The results of the follow-up survey and computer science course grade analysis will provide a foundation for enhancements to the computer basics course that is planned to be offered again during the Fall 2002 semester.S UMMARY A ND F UTURE D IRECTIONSThis paper described a computer basics course. In general, the course was considered to be a success. The true evaluation of this course will be measured as we do follow-up studies of these students to determine how they fare in subsequent courses that require basic computer skills. Future offerings of the course are expected to address non-standard computing devices, such as robots as a means to inspire the students to excel in the computing field.R EFERENCES[1] Office of Institutional Analysis, Arizona State UniversityEnro llment Summary, Fall Semester , 1992-2001, Tempe,Arizona.[2] Reyes, Maria A., Gotes, Maria Amparo, McNeill, Barry,Anderson-Rowland, Mary R., “MEP Summer Bridge Program: A Model Curriculum Project,” 1999 Proceedings, American Society for Engineering Education, Charlotte, North Carolina, June 1999, CD-ROM, 8 pages.[3] Reyes, Maria A., Anderson-Rowland, Mary R., andMcCartney, Mary Ann, “Learning from our MinorityEngineering Students: Improving Retention,” 2000Proceedings, American Society for Engineering Education,St. Louis, Missouri, June 2000, Session 2470, CD-ROM, 10pages.[4] Adair, Jennifer K,, Reyes, Maria A., Anderson-Rowland,Mary R., McNeill, Barry W., “An Education/BusinessPartnership: ASU’s Minority Engineering Program and theTempe Chamber of Commerce,” 2001 Proceeding, AmericanSociety for Engineering Education, Albuquerque, NewMexico, June 2001, CD-ROM, 9 pages.[5] Adair, Jennifer K., Reyes, Maria A., Anderson-Rowland,Mary R., Kouris, Demitris A., “Workshops vs. Tutoring:How ASU’s Minority Engineering Program is Changing theWay Engineering Students Learn, “ Frontiers in Education’01 Conference Proceedings, Reno, Nevada, October 2001,CD-ROM, pp. T4G-7 – T4G-11.[6] Reyes, Maria A., Anderson-Rowland, Mary R., Fletcher,Shawna L., and McCartney, Mary Ann, “ModelCollaboration within Minority Engineering StudentSocieties,” 2000 Proceedings, American Society forEngineering Education, St. Louis, Missouri, June 2000, CD-ROM, 8 pages.[7] Anderson-Rowland, Mary R., Blaisdell, Stephanie L.,Fletcher, Shawna, Fussell, Peggy A., Jordan, Cathryne,McCartney, Mary Ann, Reyes, Maria A., and White, Mary,“A Comprehensive Programmatic Approach to Recruitmentand Retention in the College of Engineering and AppliedSciences,” Frontiers in Education ’99 ConferenceProceedings, San Juan, Puerto Rico, November 1999, CD-ROM, pp. 12a7-6 – 12a7-13.[8] Anderson-Rowland, Mary R., Blaisdell, Stephanie L.,Fletcher, Shawna L., Fussell, Peggy A., McCartney, MaryAnn, Reyes, Maria A., and White, Mary Aleta, “ACollaborative Effort to Recruit and Retain UnderrepresentedEngineering Students,” Journal of Women and Minorities inScience and Engineering, vol.5, pp. 323-349, 1999.[9] Pfleeger, S. L., Software Engineering: Theory and Practice,Prentice-Hall, Inc., Upper Saddle River, NJ, 1998.。

Hankison型号Hankison 型号 TR I P-L-TRAP

The Importance of Condensate ManagementCondensate drains are one of the most ignored components in a compressed air system, however, these components are one ofthe most important parts to an effective treatment system.Contaminants enter a system at the compressor intake or can be introduced into the airstream during operation. Oil, water oil/water, lubricants , rust and pipe scale are all separated and filtered out by use of the filtration components installed in the system,but if the drains are not installed or do not operate properly the filters and separators are not successful.Drain TechnologiesIn a typical manufacturing facility many different types of drains can be utilized to prevent contaminants from entering thecompressed air system.. Of these there are two main technologies that Hankison offers,: Pneumatic and Timed ElectricCondensate Drains.Pneumatic Condensate DrainsPneumatic drains are an economical option for light to medium service duty. This type of drain offers versatile installation due tothe fact there is no need for electrical safety concerns during installation. Pneumatic drains are powered by air, not electricity, sothey are ideally suited for remote or portable applications. They are also safe to operate in any hazardous area. Drains offered byHankison are also zero-loss, meaning no compressed air is lost during the drain process. This results in energy savings.Timed Electric Condensate DrainsTimed Electric drains operate by utilizing two timed settings that a user can program according to their application and drainage requirements. The drains have one timer that is set for the interval between each time the drain opens. The second timer is set forthe amount of time that the drain is open. During the draining process there will be a minimal amount of air loss.Energy EfficiencyHow do your drains improve system efficiency? Besides the obvious savings of compressed air with a no-waste drain choice, thereare other less obvious ways drains can save energy or cost you energy if not properly maintained. They are key components in thequest for system efficiency and reliability.Installing automatic condensate drains has several benefits for every compressed air system• Saves Man Hours»Eliminate time draining air lines and equipment»Eliminate purging air lines before work begins• Prevents the receiver tank from filling up with condensate and causing the compressor to short cycle• Zero loss drains save on wasted compressed air created when valves are cracked open to purge the air lines of condensate• Ensures timely and effective condensate removal during working hours to protect end products and processes from contamination3Pneumatic DrainsHankison’s level actuated, pneumatically operated condensate drains automatically discharge water, oil, and oil/water emulsions from separators, receiver tanks, dryers, filters, after-coolers and drip legs. Each drain is engineered to reduce system downtime by eliminating the need to manually drain compressed air lines and equipment.Unlike simple float operated drains, these drains feature an air powered piston for positive opening and closing of the discharge port. This operation prevents clogging of the compressed air system while the baffle protects the operating mechanism fromCapacity1Materials ofConstruction7530 Series Product Specifications532 SeriesFeatures• Resistant to large particles 1/2” maximum diameter • Internal pilot operated diaphragm solenoid valve• H igh pressure model available: maximum working pressure 1500 psig (105 barg)• C omplete with strainer (not available on the high pressure drain)Model 532-03 and 532-04• Maximum working pressure:»300 psig, (21 barg)• Discharge port size:»3/8” in ( 9.5 mm) for 03 model »1/2” in (12.7 mm) for 04 model• Includes combination isolation valve and inlet strainerElectric Timed DrainsModel 531FrontSide HFront Side Model 532Global locationsBased in Charlotte, North Carolina, SPX Corporation (NYSE: SPW) is a global Fortune 500 multi-industry manufacturing leader. For more information, please visit SPX reserves the right to incorporate our latest design and material changes without notice or obligation. Design features, materials of construction and dimensional data, as described in this bulletin, are provided for your information only and should not be relied upon unless confirmed in writing. Please contact your local sales representative for product availability in your region. For more information visit . The green “>” is a trademark of SPX Corporation, Inc.ISSUED 09/2015 CDSCOPYRIGHT © 2015 SPX CorporationS PX FLOW TE CH N OLOGY4647 SW 40th AvenueOcala, Florida 34474-5788 U.S.A. P: (724) 745-1555F: (724) 745-6040E:**********************S PX U SAHankison Headquarters4647 SW 40th AvenueOcala, Florida 34474-5788 U.S.A. P: (724) 745-1555F: (724) 745-6040E:**********************Hankison Rental Northeast100 Commerce Drive, Suite 40Washington, PA 15301P: (724) 225-1470F: (724) 222-1317Hankison Rental Southwest1486 Champion Drive T errell, TX 75160 U.S.A.P: (800) 379-3711F: (972) 563-9991S PX CanadaHankison Canada1415 California AvenueBrockville, ON, Canada k6v 7h7P: (800) 267-3884F: (800) 318-0952S PX MexicoHankison MexicoAvenida Constitución #2165 -B Colonia JuliÁn Carrillo San Luis Potosí, S.L.P.C.P. 78250 MéxicoP: +52 (444) 815-7074F: +52 (444) 815-8295S PX South America Hankison BrazilRua Joao Daprat, 231 b09600-010-SÃ0 Bernardo Do Campo, SP BrazilP: +55 (11) 2166-4050 F: +55 (11) 2166-4070S PX EuropeHankison IrelandKillarney, Co Kerry IrelandP: (+353) 6466-33322 F: (+353) 6466-33371Hankison NetherlandsMunnikenheiweg 41Postbus 5704870 NE Etten-Leur Netherlands P: (+31) 76-5085800 F: (+31) 76-5085800Hankison GermanyKonrad-Zuse-Str. 25D-47445 Moers Germany P: (+49) 2841-8190 F: (+49) 2841-87112S PX IndiaSPX India PVT, L TD Manufacturing G-72/73Riico Industrial AreaMansarovar, RAJASTHAN Jaipur 302 020 IndiaP: (+91) 141-2396759 F:(+91) 141-2395048S PX Asia Pacific S PX China5th Floor, Park Center,No.1568 Huashan Road, Shanghai China P: +86 (021) 2208-5840 F: +86 (021) 2208-5866S PX Korea#940-1 Y erim-RiJeonggwan-Myeon Gijang-Gun, Busan, Rep. of Korea P: +82 (51) 728-5360 F: +82 (51) 728-5359。

1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。

Figure 1: Examples of test data. Camera is placed at 2 feet (top) and 5 feet (bottom) away from the scene. Perspective distortion can be observed from the shape of the title deed card.
1 Introduction
Augmented Reality (AR) is the technology that enhances the user’s view of the real world with computer-generated information. Considered a cutting-edge technology for computeruser interface, AR opens many new applications in a broad range of domains, from entertainment to military training. A comprehensive survey on AR could be found at [1]. One of the most challenged task in implementing AR system is registration. In order to align the virtual objects to the user’s view of the world, AR systems need to accurately track the position and orientation of the user’s head (or cameras). This process, known as registration, need to be accurate, robust and fast. Described as ”closed loop” system [2], vision-based emerges as the most potential solution for registration among other techniques like magnetic, optical or mechanical tracker. In [3], camera position is recovered based on frame-to-frame homographies. This algorithm demands the existence of planar surfaces in the scene. Although this requirement seems to be satisﬁed in most scenarios, the method may fail with the plain (non-texture) surface for it strongly depends on the corner detection. Besides, the paper does not give a clear solution to prevent registration error propagating through the sequence. Some approaches employ ﬁducial points to help tracking. State et al. [4] uses 12 special color landmarks. This system combines vision-based with magnetic tracker to reduce the registration error down to 1 pixels. However, cumbersome initialization, involving placing landmarks and calibration, and limitation of the magnetic tracker’s range makes this approach undesirable for general use. Kutulakos and Vallino [5] develop a method based on afﬁne transformation. Without the need of camera calibration and require only few ﬁducial points, the system can achieve the accuracy within 15 pixels for 640x480 images. The major drawback of the algorithm is constraints of the afﬁne space and the ﬁducial points must be visible at all times. Seo and Hong [6] extends this algorithm to the perspective case and able to compute shadow of the virtual object.
(a) (b)
100 200 300 400 200 400 600
100 200 300 400 200 400 600
Figure 2: (a) - thresholded image. (b) - the tracking result. Position of the landmarks (indicated by * ) are computed by ﬁnding the centroid of each ellipse 3.3 Register virtual object The virtual object chosen for this project is a Rubik cube. We arbitrary select four corners of the Rubik as in ﬁgure 3.3. The location of these four points are manually entered for two different frames. By solving equation 2 (appendix 1), the afﬁne coordinate of the points are found (see Matlab code in appendix 3). Kutulakos and Vallino suggest using epipolar constraints to ensure the points are matched in these two frames. In our implementation, we follow the algorithm in [7] (see appendix 2) to recover the afﬁne fundamental matrix. However, due to error in ﬁnding correspondent pairs and/or round-off errors, the result is not perfect. The simple alternation we use is aligning the object with regard to the existing interest points in the scene. 3.4 Render virtual object Once the afﬁne coordinates of these four points are known, we can compute the position of any point in the virtual object using equation (1). The paper also points out that using the projection equation (4), virtual object can be rendered by using graphics hardware directly. In our experiment, we do not take advantages of this powerful feature. To render the Rubik cube, we compute the corners and draw each face with texture mapping (with Matlab ’warp’ function). Notice that, with particular conﬁguration as in ﬁgure 3.3, other corners are easily represented by a linear combination of these points. Besides, we do not calculate
2 Objective
Our project is closely resembled to the work by [5]. Our concentration in this project will be accurate rendering a virtual object into the scene. Although tracking is a essential part of the project, we will relax this problem by running the tracking process separately and
CSE 252c Fall 03. Project Report. Calibration-Free Augmented Reality