Acceleration of Gain Recovery in Semiconductor Optical Amplifiers by Optical Injection Near

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解剖型跟骨钛板治疗跟骨骨折疗效观察

解剖型跟骨钛板治疗跟骨骨折疗效观察

临床骨科杂志 2〇17 Apr;2〇(2)• 221 •d o i:10. 3969/j. issn. 1008-0287. 2017. 02. 037•临床论著•解剖型跟骨钛板治疗跟骨骨折疗效观察张胜国,谢旖静,邵楠,赵小魁摘要:目的评价解剖型跟骨钛板治疗新鲜跟骨骨折的临床疗效。

方法采用解剖型跟骨钛板治疗31例新鲜跟骨骨折患者(38足)。

术后根据A0FAS踝-足评分标准和Maryland足部功能评分系统评定功能恢复情况。

结果术后3足出现浅表感染,1足出现创伤性关节炎,无皮肤坏死、内固定失效发生。

患者均获得随访,时间13 ~26个月。

术后10 ~ 19周骨折均达到临床愈合,Biihlei■角和G脱a n e角、跟骨外形基本恢复正常。

末次随访时,按A0FA S踝-足评分标准评定:优21足,良12足,可5足,优良率86. 8%。

根据Maryland足部功能评分系统评定:优20足,良14足,可4足,优良率89.5%。

结论解剖型跟骨钛板治疗新鲜关节内跟骨骨折,符合生物力学固定,能够最大限度恢复患足功能。

手术时机恰当、术中操作仔细,可以降低并发症的发生率。

关键词:跟骨骨折;骨折固定术,内;解剖型跟骨钛板;术后并发症中图分类号:R683. 42; R687. 3 文献标识码:A文章编号:1008 -0287(2017)02 -0221 -03Treatment of calcaneal fractures with anatomical calcaneal titanium plate ZHANG Sheng-guo,XIE Yi-jing,SHAO Nan,ZHAO Xiao-kui( Dept of Orthopaedics, China Meitan (General Hos­pital, Beijing 100028, China)Abstract:Objective To evaluate the results of the treatment of fresh calcaneal fractures with calcaneal anatomicaltitanium plate fixation. Methods Thirty-one cases (38 feet) of calcaneal fractures were treated with anatomical cal­caneal titanium plate fixation. During the follow-up, functional outcomes were evaluated with AOFAS score and Mary­land score system, respectively. Results Three feet of wound superficial infections occurred, and traumatic arthritisoccurred in 1 foot. No other complications such as skin necrosis and internal fixation failure occurred. The 31 patientswho had follow-up period of 13 〜26 months,they got clinical healing in 10 〜19 weeks. The Bohler angle, Gissaneangle, calcaneal width and height were reduced close to normal anatomic structure. In the last follow-up, according toAOFAS ankle-foot score criterion, the operation results were excellent in 21 feet, good in 12, and fair in 5. The ex­cellent and good rate was 86. 8%. According to Maryland foot score criterion, the operation results were excellent in20 feet, good in 14 and fair in 4. The overall satisfactory results was 89. 5% .Conclusions Anatomical calcaneal ti­tanium plate in fixation of fresh intra-articular calcaneal fractures which fit to biomechanics, the foot can gain themaximum recovery of function, and which has suitable surgical timing and intraoperative careful operation, can reducethe incidence of complications.Key words :calcaneal fractures ;fracture fixation, internal ;anatomical calcaneal titanium plate ;postoperative compli­cation跟骨骨折多由足跟遭受垂直重击、瞬间强大暴 力所造成[1]。

2、Resource Sustainability

2、Resource Sustainability
a
8 Lynmar Avenue, Asheville, North Carolina, NC 28804, U.S.A. 3 Linden Road, Hartland, Vermont, VT 05048, U.S.A. E-mail: dseville@ Ł Andrew Jones, 8 Lynmar Avenue, Asheville, North Carolina, NC 28804, U.S.A.; E-mail: apjones@ The authors gratefully acknowledge the Rockefeller Brothers Fund, the Turner Foundation, the Wallace Global Fund, and the Luce Foundation for supporting this research, the Switzer Environmental Leadership Program Fund of the New Hampshire Charitable Foundation for supporting the follow-on workshops, and the Northern Forest Center for helping guide the project and organize the advisory board. We thank the members of the advisory board for their time and ideas, the New Hampshire Charitable Foundation and Society for the Protection of New Hampshire Forests for their meeting spaces, and John Sterman for comments and suggestions on the article.

CCUS-EOR开发同步埋存阶段长度的确定方法

CCUS-EOR开发同步埋存阶段长度的确定方法

第30卷第2期油气地质与采收率Vol.30,No.22023年3月Petroleum Geology and Recovery EfficiencyMar.2023—————————————收稿日期:2022-11-20。

作者简介:王高峰(1980—),男,河南许昌人,高级工程师,硕士,从事注气技术研究工作。

E-mail :**************************.cn 。

基金项目:中国石油上游科技项目“碳驱油碳埋存一体化协同技术研究”(kt2022-8-20)和“冀东高深北区高66X1断块E s 33II 油组碳驱油碳埋存先导试验”(2022ZS0806)。

文章编号:1009-9603(2023)02-0168-06DOI :10.13673/37-1359/te.202211013CCUS-EOR 开发同步埋存阶段长度的确定方法王高峰1,曹亚明2,解志薇3,刘媛3(1.中国石油勘探开发研究院,北京100083;2.中国石油冀东油田分公司,河北唐山063000;3.中国石油华北油田公司,河北沧州062550)摘要:CCUS-EOR 开发周期分为同步埋存和深度埋存两大阶段,确定同步埋存阶段长度是CCUS-EOR 开发方案设计的一项重要内容。

根据CO 2驱产油量变化情况,可将同步埋存阶段进一步划分为上产期、稳产期和递减期。

上产期的时间长度由见气见效时的累积注入量与年注气速度计算,稳产期的时间长度即稳产年限借助气驱“油墙”集中采出时间测算,递减期内的阶段采出程度变化情况则利用典型产量递减规律研究,气驱产量递减率和稳产期采油速度需根据气驱增产倍数概念确定,从而建立了CO 2驱阶段采出程度评价数学模型,提出将阶段采出程度逼近最终采收率的时刻作为同步埋存阶段与深度埋存阶段的转换点并引入阶段转换判据;同步埋存阶段长度扣除上产期和稳产年限即为递减期的时间长度。

关键词:CCUS-EOR 开发;同步埋存;深度埋存;阶段采出程度评价模型;阶段转换判据;CO 2驱中图分类号:TE311文献标识码:AMethod for determining time length of simultaneoussequestration phase of CCUS-EOR developmentWANG Gaofeng 1,CAO Yaming 2,XIE Zhiwei 3,LIU Yuan 3(1.Research Institute of Petroleum Exploration &Development ,Beijing City ,100083,China ;2.Jidong Oilfield of PetroChina ,Tangshan City ,Hebei Province ,063000,China ;3.Huabei Oilfield of PetroChina ,Cangzhou City ,Hebei Province ,062550,China )Abstract :The life cycle of CCUS-EOR development can be divided into two parts.One is the simultaneous sequestration phase (SSP ),and the other is the deep burial phase (DBP )of CCS.Determining the time length of SSP is an important part of CCUS-EOR development scheme design.According to the change trend of oil production under CO 2flooding ,SSP can be further divided into an oil production rising period ,a stable oil production period ,and an oil production declining period.The time length of the oil production rising period is calculated from the annual gas injection rate and the cumulative injec⁃tion amount at the gas emergence time.The time length of the stable oil production period under gas flooding is calculatedby means of “centralized recovery time of oil bank ”.The change of stage recovery during the oil production declining peri⁃od is studied by using the representative decline curves.The oil recovery rate during the stable oil production period and oilproduction decline rate under gas flooding are measured based on the concept of “oil production multiplier due to gas flood⁃ing ”.Thus ,a mathematical model for evaluating stage recovery in the case of CO 2flooding is established.The moment when the stage recovery under CO 2flooding approaches the estimated ultimate recovery is proposed as the transition point be⁃tween SSP and DBP.On this basis ,a phase transition criterion is introduced.The time length of SSP minus those of the oil production rising period and the stable oil production period is the time length of the oil production declining period.Key words :CCUS-EOR development ;simultaneous sequestration ;deep burial ;evaluation model of stage recovery ;phasetransition criterion ;CO 2flooding全球范围内通过CCUS 方式注入地下的二氧化碳达到10亿吨级,其大规模碳埋存能力已被证第30卷第2期王高峰等.CCUS-EOR开发同步埋存阶段长度的确定方法·169·实[1-2],被视为石油企业碳中和的托底技术。

5Multiobjective Production Planning Optimization Using Hybrid Evolutionary Algorithms for Mineral

5Multiobjective Production Planning Optimization Using Hybrid Evolutionary Algorithms for Mineral

Multiobjective Production Planning Optimization Using Hybrid Evolutionary Algorithms forMineral ProcessingGang Yu,Tianyou Chai,Fellow,IEEE,and Xiaochuan Luo,Member,IEEEAbstract—The production planning optimization for mineral processing is important for non-renewable raw mineral resource utilization.This paper presents a nonlinear multiobjective programming model for a mineral processing production planning(MPPP)for optimizingfive production indices, including its iron concentrate output,the concentrate grade,the concentration ratio,the metal recovery,and the production cost.A gradient-based hybrid operator is proposed in two evolutionary algorithms named the gradient-based NSGA-II(G-NSGA-II)and the gradient-based SPEA2(G-SPEA2)for MPPP optimization. The gradient-based operator of the proposed hybrid operator is normalized as a strictly convex cone combination of negative gradient direction of each objective,and is provided to move each selected point along some descent direction of the objective functions to the Pareto front,so as to reduce the invalid trial times of crossover and mutation.Two theorems are established to reveal a descent direction for the improvement of all objective functions.Experiments on standard test problems,namely ZDT 1-3,CONSTR,SRN,and TNK,have demonstrated that the proposed algorithms can improve the chance of minimizing all objectives compared to pure evolutionary algorithms in solving the multiobjective optimization problems with differentiable objective functions under short running time putational experiments in MPPP application case have indicated that the proposed algorithms can achieve better production indices than those of NSGA-II,T-NSGA-FD, T-NSGA-SP,and SPEA2in the case of small number of generations.Also,those experimental results show that the proposed hybrid operators have better performance than that of pure gradient-based operators in attaining either a broad distribution or maintaining much diversity of obtained non-dominated solutions.Index Terms—Gradient-based operator,hybrid multiobjec-tive evolutionary algorithm,multiobjective production planning optimization,production indices.I.IntroductionT ODAY,METALS are extensively used in many industries such as construction,transportation,energy distribution, Manuscript received August28,2009;revised January18,2010and May 22,2010;accepted July30,2010.Date of current version July29,2011. This work was supported in part by the National Basic Research Program of China,under Grant2009CB320601,in part by the National Natural Science Foundation of China,under Grants70721001and60974091,in part by the Funds for Creative Research Groups of China,under Grant60521003,and in part by the111Project B08015.G.Yu is with the Key Laboratory of Integrated Automation of Process Industry,Ministry of Education,Northeastern University,Shenyang110004, China(e-mail:friends.yugang@).T.Chai and X.Luo are with Northeastern University,Shenyang110004, China(e-mail:tychai@;luoxch@).Color versions of one or more of thefigures in this paper are available online at .Digital Object Identifier10.1109/TEVC.2010.2073472communications,and the aircraft industry.The pursuit of industrial development and the progress and the use of tech-nology have made China as an even more mineral resources-dependent country than ever before.Indeed,the worldwide increase in demand for mineral is expected continuance[1]. However,mineral resources reserves have declined in the world over time due to increased mining activities.Mineral processing is a process of beneficiating valuable minerals(concentrate)by separating tailings and waste rock from raw ores in order to increase the grade of valuable minerals while reducing the impurity content.The main task of production planning of mineral processing is to optimize production resources(i.e.,raw minerals and processing equip-ments,and so on)so as to achieve the desired production tar-gets.In these targets,there arefive major production indices, namely concentrate output,concentrate grade,concentration ratio,metal recovery,and cost indicators.Concentrate is the product of mineral processing and concentrate output refers to the yield of processing plant under given equipments,limited raw ores,and production ually,the higher the yield, the higher the equipment utilization is required.Concentrate grade is the content of useful components in concentrate product,so it is usually expressed as mass fraction of useful components such as Fe,Cu,and so on(unit%).This is an important indicator reflecting the quality of concentrate,the higher the grade,the better purity of concentrate would be. Concentration ratio or beneficiation ratio is the ratio of raw ore amount to concentrate amount.Practically,the lower the ratio, the more the raw ore resources can be saved.Metal recovery is another important production indicator that represents the recovery capacity of beneficiation plant.It is expressed as the weight ratio of the metal contained in concentrate to such metal contained in raw ore.Also,the higher recovery, the more metal will be recovered in concentrate or the less metal contained in tailings will be discarded.Concentrate cost consists of the expense of raw ore,energy,manufacturing, and so on.Therefore,the lower the cost,the more profits the industrial company will gain.Ideally,thesefive indicators are all expected to be the best at the same time.However,it is very difficult,if not possible,to get such utopian result that all the indicators are the best because there exist several mutual conflicts among them.For example,the production of high-grade concentrate requires high-grade and therefore expensive raw ore,leading to1089-778X/$26.00c 2011IEEEFig.1.Scheme of a mineral processing plant.The raw ores x i are sent to the productionflow to be divided into the powder ores x1,i and the lump ores x2,i in the sieving cell,the powder ores are processed in the high intensity magnetic separation cell to produce concentrate y1,i and tailings z1,i while the lump ores are roasted in roasting cell and then processed in the low intensity magnetic separation cell to produce concentrate y2,i and tailings z2,i(see Section II-D for the explanation of the notations).increased cost.Again,it is not possible that concentrate grade and metal recovery can always be increased simultaneously. Actually over-pursuit of recovery will result in grade reduc-tion,which can be confirmed by the grade-recovery curves [2].Additionally,raw ore with low beneficiation ratio is high in price,and pursuing high-yield may lead to high-impurity and low grade as well.Therefore,inappropriate assignment of these indicators and production resources(i.e.,equipment, raw ore,and so on)may not only lead to quality problem of concentrate product but also difficulty in guaranteeing the continuity and stability production,even the accomplishment of the production indices of mineral process[3]. Consequently,given the production demand and resource constraints for a mineral processing plant,the following issues should be considered.1)Which raw ore should be used and how much should beassigned?2)How much yield of concentrate should be assigned in acertain period of time?3)How much concentrate grade,ratio,recovery rate shouldbe set?4)How much cost per ton of concentrate should be? However,it is a challenge task to solve these problems for the complexity of defining optimization criteria and optimal operating conditions.For instance,the overall control objective of a mineral processing plant and these complexities have been discussed by Hodouin et al.[4]and Kelly[6],and it is also faced with these complexities in mineral processing production planning.In addition,it is confronted with the difficulties in decision-making because many managers with respective responsibilities at different departments compete with each other in seeking selfish allocation solutions,as detailed in Section ually,these conflicting objectives are coordinated by either experiences or empirical rules,but operators’ability can be found limited sometimes so that it is not sufficient to increase process efficiency depending on the experiences of metallurgists and process engineers only [4].Due to lack of effective methods,the production indices mentioned previously are often set by managers with incoher-ent empirical knowledge during different production periods (e.g.,days,weeks to months).As a result,the production plan is made to meet rough requirements only,and seldom is it an optimal or suboptimal.As a consequence,the production plan-ning involving multiple conflicting objectives is a complicated issue to formulate on a plant-wide optimization and obviously difficult to implement for mineral processing management. In this paper,a nonlinear multiobjective programming model that can be utilized in a decision support system for mineral processing production planning is proposed,and two hybrid multiobjective evolutionary algorithms called gradient-based NSGA-II(G-NSGA-II)and gradient-based SPEA2 (G-SPEA2),which are based on state-of-the-art multiobjective evolutionary algorithms NSGA-II[7]and SPEA2[8],are presented to solve the production planning optimization model. The focus of the underlying model is on the quantities ofYU et al.:MULTIOBJECTIVE PRODUCTION PLANNING OPTIMIZATION USING HYBRID EVOLUTIONARY ALGORITHMS FOR MINERAL PROCESSING489mineral resources where raw ore is the main resource that can be assigned in an economic manner.II.Problem DescriptionA.BackgroundOne kind of production process for mineral processing in China is shown in Fig.1.The plant can be divided into several sub-processes such as the sieving cell(process P1),the roast-ing cell(process P2),the high intensity magnetic separator cell(process P3),the low intensity magnetic separator cell (process P4),the concentrate process cell(process P5),and the tailings process cell(process P6).These sub-processes are continuous,and the minerals such as raw ore,slurry,and concentrate are delivered from one cell to another by belts and pipelines transportation.First,the raw ores(x1,i)are crushed and screened to lump ores and powder ores in the raw ores sieving cell P1,then the powder ores are buffered in the cylindrical ore bins and the lump ores are buffered in the ore silo.Second,the powder ores are grinded by ball mill and separated in the process P3to produce concentrate(y1,i)(denoted as the H-concentrate)and tailings(z1,i)(denoted as the H-tailings).Meanwhile,the lump ores are sent into the shaft furnaces to produce roasted ores with high magnetic property,and the waste ores are separated out from the lump ores in the roasting cell P2at the same time. These roasted ores are then sent into ball mill and magnetic separator in the process P4to produce concentrate(y2,i) (denoted as the L-concentrate)and tailings(z2)(denoted as the L-tailings).Finally,concentrate(y1,i)and(y2,i)are mixed in concentrating pool,and the integrated concentrate(y)is sent into concentrate warehouse after concentrating and dewatering process P5.Similarly,tailings(z1,i)and(z2,i)are mixed in the tailings pool,and the integrated tailings(z)are piled up in the tailings dam after concentrating and dewatering process. The production planning management for mineral process-ing is a tradeoff between the individual objectives of the planners involved.First,some kinds of raw ores with property characteristics such as ore grade,lump ore rate,beneficiation ratio,and price are selected and the quantity of each raw ore is initially decided by the planners in planning department of mineral processing plant.Then,the production indices such as theoretical yields,the concentrate grade,the metal recovery,the overall beneficiation ratio,and the production cost per ton of concentrate are derived by the theoretical metal balance method.However,the result is not easy to be satisfied with by different departments and production process segments at the same time.This is because these departments or segments are responsible for the specific production indices. For example,the quality department is responsible for the grade and recovery indicator reflecting the quality of interme-diate material and thefinal concentrate,while the production organization department is concerned about the production capacity,and the energy management department is concerned about whether there are enough fresh water,electricity,and gas energy resources to provide.Also,the cost management department is concerned with whether it is a reasonable production cost or ideal profit.Similarly,the mangers and operators in different production cell(e.g.,processes P1–P6in Fig.1)are concerned about their local production yields and quality,respectively.However,improper coordination in these process segments may lead to concentrate waste.Anyway, all management departments and process segments care about their respective production indices which are conflicting local objectives.This is because any undesired target will make the manager of relevant departments and segments bear the financial penalties,individuals are often overly concerned with local interests resulting in the difficulty to achieve the basic integrated production targets,not to mention the plant-wide optimization.Therefore,coordination is repeated among the various individual planners until afinal compromise is reached in the preparation of production plan for mineral processing. Thus,plant-wide optimal production planning management inherently involves multiple conflicting objectives.The ultimate goals are multiple comprehensive production targets previously referred to as the concentrate output,the grade,the recovery,the beneficiation ratio,and the cost per ton of concentrate from the views of the whole mineral processing factory rather than a single-objective optimization problem.It is hard to determine an ideal global optimum for each production index to be optimal under given mineral processing resource limitation due to the conflict mentioned above.Therefore,the decision-support model for the allocation of mineral processing resource should determine a set of compromise solutions namely Pareto optimal set.B.Literature ReviewConventionally,the multiobjectives of mineral processing planning optimization problem are aggregated into a single objective function by weighted-sum aggregation which is still widely used due to its simplicity.[9]–[11]presented a scheduling method based on production indices optimization for minerals processing on the basis of ensuring the grade of concentrate ore,reducing concentrate inventory and improving equipment utilization.However,the other production indices such as recovery rate and production cost,and so on,are not involved in the model.Moreover,in the absence of any other high level preference information,the non-dominant optimal solutions in a Pareto set are equally competitive and none of them can dominate others.Thus,the solution obtained by aggregating multiple objectives into single objective function in these researches,which is often a weighted-average of the several objectives,depends largely on the values assigned to the weighting factors used.Multiobjective evolutionary algorithms were used in the plant designs,process operation optimization,and control of mineral processing.While et al.[12]developed a multiob-jective evolutionary algorithm to create and evaluated the crusher internal geometry.They used an evolutionary strategy to vary the shape of cone crusher liners and various operating parameters so as to simultaneously maximize the quality of the product and the capacity of the circuit.In[13],a multiobjective algorithm was used to optimize the composition and the number of machines to use,as well as their opera-tional settings for multiple components in a processing plant. Other researchers have reported similar work subsequently490IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION,VOL.15,NO.4,AUGUST2011[14]–[16].For example,Huband et al.[17]described the application of an evolutionary algorithm to the problem of optimizing the performance of a comminution plant for two different types of feed and their algorithm returns a range of designs offering different tradeoffs between them.Mitraa and Gopinath[18]solved a multiobjective optimization problem for an industrial lead–zinc grinding operation considering two contradictive objectives.One objective is to maximize the grinding product throughput whereas the second objective is to maximize the percentage passing of the midsize.Pareto solutions are found out by a genetic algorithm namely NSGA II.The most multiobjective evolutionary algorithms applied in the plant design,operation control problem in these papers are mostly used to optimize the indices within some local specific process segments,instead of plant-wide production planning for mineral processing.In addition,in the area of operation optimization of mining, Everett[19]discussed a variety of algorithms and simulation models,such as the standard quadratic programming,the heuristic hill-climbing approach,and the exponential smooth-ing method to aid several stages of scheduling decisions, from the mine phase,through railing,stockpiling,and ship loading.Xu and Wei[5]developed an intelligent system to assist the programming of decision-making on mineral resource exploitation for operating mines by means of the systematic combination of optimization technology with an artificial neural network,an expert system,computer-aided design,and operational research.Recently,there are some literatures that have focused on production indices optimization for mineral processing plan-ning by multiobjective evolutionary algorithm.For example, Ma et al.[20]established a goal programming model min-imizing the deviation from the desired concentrate grade, output,and cost in one ore-dressing plant.They applied genetic algorithm to solve the model according to the priority of production indices.However,the beneficiation ratio,the metal recovery rate,and the production equipment capacity constraints have not been considered.[21]applied a particle swarm algorithm to optimize the daily global production indices of mineral processing.Also,[22]used a particle swarm algorithm to optimize the daily decomposition of production indices for mineral processing.However,more comprehen-sive production indices and real restrictive conditions of mineral processing production,such as specific equipment capacity and energy limitation,should be considered in these researches.C.Material and Metal Balance ModelA metal balance(or called a mass balance)states that the metal content of the raw ore must be equal to the metal content contained in the concentrate,tailings and waste.It is fundamental for mineral processing production planning.According to the mass balance principle[23],[24],the total amount of raw ore is equal to the sum of concentrate amount, tailings amount and waste amount as given byQ raw=Q concentrate+Q tailings+Q waste(1)where Q raw,Q concentrate,Q tailings,and Q waste represent the raw ore quantity,the concentrate output,the tailings output, and the waste amount,respectively.The metal content contained in the material is also balanced between the input and output of a process according to metal balance[23],[24]Q raw·α=Q concentrate·β+Q tailings·θ+Q waste·ν(2) whereαis the raw ore grade,βis the concentrate grade,θis the tailings grade,andνis the waste grade.Concentrate ore is the product of useful component(i.e., valuable mineral)of raw ore from which most of gangue is removed by beneficiation process,and tailing ore is the product of low content valuable mineral after beneficiation process. Several important indices are used to measure the performance of mineral processing production.Grade represents the weight percentage of useful ingredients in either raw minerals or beneficiation product.It is an important production indicator. One of the aims of mineral processing is to upgrade a lower grade of raw ore to a higher grade of concentrate product. Metal recovery is another important indicator which rep-resents the recovery capacity of beneficiation plant,and the metal recovery formula is as follows[23],[24]:ε=βQ concentrateαQ raw×100%.(3)Beneficiation ratio is the ratio of raw ore amount to con-centrate amount,i.e.,the required tons of raw ore for a ton of concentrate product[23],[24]K=Q rawQ concentrate.(4)D.NotationsThe notations of indices,decision variables,and parameters are listed in Table I.These notations will be used throughout this paper.E.ObjectivesThe aim of mineral processing production planning is to determine high level decisions such as integrated production indices and mineral raw materials amount under given pro-duction conditions such as mineral raw materials properties, limited equipment capacity,limited inventories,and energy resources over a specified time horizon(e.g.,weeks,months to years).1)Concentrate Yield Objective:One objective of pro-duction planning for mineral processing is the maximization of concentrate yield within its objective interval[Q L,Q H] while satisfying inventory constraints.This can be expressed mathematically as follows:max Q(x)=Ii=1(1−u i)x i/k1,i+Ii=1u i x i/k2,i(5)where the decision variable vector x consists of the quantity of each raw ore[i.e.,x=(x1,x2,...,x i,...,x I)T],andYU et al.:MULTIOBJECTIVE PRODUCTION PLANNING OPTIMIZATION USING HYBRID EVOLUTIONARY ALGORITHMS FOR MINERAL PROCESSING491TABLE INotationsNotation Description Notation DescriptionIndices k2,i The beneficiation ratio of lump ore separated from thei th raw ore by the sieving process shown in Fig.1.i The i th raw ore,i=1,2,...I.r i The price of the raw ore i.j The j th type of equipment,j=1,2,...J.ηb The roasting ratio,the ratio of roasted ore to lump oreby the roasting process shown in Fig.1.k The number of production series,i.e.,the number of ball mill-magnetic separator series,k=1,2,...N.ηw The waste rock rate,the ratio of waste rock to lump ore by the roasting process shown in Fig.1.p The p th kind of energy,p=1,2,...P.βw The waste rock grade(%).Variablesβb The roasted ore grade(%).x i The quantity of the raw ore i(ton).Q b The quantity of roasted ore produced by the roastingprocess shown in Fig.1.x The decision variable vector x=(x1,x2,...,x i,...,x I)T.εL The lower bound of the metal recovery rate.β(x)The concentrate grade(%).K H The upper bound of the total beneficiation.Q(x)The yield of concentrate.C H The upper bound of the cost per unit of concentrate. K(x)The total beneficiation ratio.C energy The comprehensive energy cost per unit of concentrateproduct.ε(x)The metal recovery.C other The other totalfixed fee except for raw ore cost andenergy cost,including quota fee,controllable manufac-turing costs and so on.C(x)The cost per ton of concentrate.N k,j The operating number of the j th type of equipmentwhen the production series is k.θl(x)The total tailings grade(%)if l=0,the H-tailings grade (%)if l=1,the L-tailings grade(%)if l=2.T k The production time of k in a time period(e.g.,months to years).q j(x)The throughput per hour fed into the j th type of equipment.q j,H The upper bound of the j th type of equipment capacity,i.e.,maximal average throughput per hour fed into thej th type of equipment.Q E,p(x)The consumption of the p th kind of energy(e.g.,fresh water,electricity,and gas).θl,H The upper bound of total tailings grade(%)if l=0, H-tailings grade(%)if l=1,L-tailings grade(%)ifl=2.Parameters q E,p The consumption of the p th type of energy resourcerequired for a ton of concentrate.αi The grade(%)of the raw ore i.Q EH,p The maximal supply amount of the p th kind of energyresource.α1,i The grade(%)of the powder ore separated from the raw ore i by the sieving process shown in Fig.1.[βL,βH]The objective interval of the concentrate grade(%),βL is lower bound,andβH is upper bound.α2,i Grade(%)of lump ore separated from the raw ore i by the sieving process shown in Fig.1.Q S The quantity of concentrate sold or consumed by sin-tering plant.β1,i The high intensity magnetic concentrate grade(%)of raw ore i.I0The quantity of concentrate remained in concentrate warehouse at the beginning of a time horizon.β2,i The low intensity magnetic concentrate grade(%)of raw ore i.[I L,I H]The available storage interval for the concentrate at theend of a time horizon,I L is lower bound,and I H isupper bound.u i The lump ore rate of the raw ore i,i.e.,the ratio of separated lump ore to raw ore.[Q L,Q H]The objective interval of the concentrate yield,Q L is lower bound,and Q H is upper bound.k1,i The beneficiation ratio of powder ore separated from the i th raw ore by the sieving process shown in Fig.1.[Q i,min,Q i,max]The available amount interval of the raw ore i,Q i,minis lower bound,and Q i,max is upper bound.(1−u i)x i the quantity of powder ore separated fromthe i th raw oreu i x i the quantity of lump ore(1−u i)x i/k1,i the concentrate output of powder oreu i x i/k2,i the concentrate output of lump ore.The total yield Q(x)is the sum of concentrate output produced by sub-processes P3and P4as shown in Fig.1,and (5)is obtained based on(4),relative notations are described in Section II-D.2)Concentrate Grade Objective:An important objective of production planning for mineral processing is to maximize the concentrate grade within concentrate grade objective inter-val[βL,βH]as stated in the following:maxβ(x)=Ii=1(1−u i)β1,i x i/k1,i+Ii=1u iβ2,i x i/k2,iIi=1(1−u i)x i/k1,i+Ii=1u i x i/k2,i.(6)Equation(6)represents the metal content percentage in concentrate product.It should be noted that the expression of denominator in(6)is just the concentrate yield Q(x)in (5),and the numerator in(6)is the sum of the metal content contained in the H-concentrate and the L-concentrate(i.e.,the total metal content contained in concentrate product).492IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION,VOL.15,NO.4,AUGUST2011 3)Total Beneficiation Ratio Objective:Minimization ofthe total beneficiation ratio is also an objective of mineralprocessing production planning,and often is required an upperK H bound constraint in mineral processing plantmin K(x)=(Ii=1x i)/[Ii=1(1−u i)x i/k1,i+Ii=1u i x i/k2,i].(7)Equation(7)can be obtained from(4),it is the expression of the total beneficiation ratio[i.e.,the ratio of total raw ore amount to concentrate yield Q(x)].In general,the smaller of the total beneficiation ratio,the less of raw ore consumption is for per ton of concentrate product.4)Metal Recovery Objective:Maximization of the metal recovery is another objective of mineral processing production planning,and it is especially important for some rare metal mineral processing plants.A lower boundεL constraint is re-quired for many plants and even prescribed in the specification of national standardization.This means that one needs to solve the following problem:maxε(x)=Ii=1(1−u i)β1,i x i/k1,i+Ii=1u iβ2,i x i/k2,iIi=1x iαi.(8)In(8),the expression of numerator is the total metal content contained in the concentrate product whilst the expression of denominator is the total metal content contained in the raw ore used.The ideal goal is that all of the metal contained in the raw ore is completely recovered although it is impossible in practice.5)Concentrate Cost Objective:Minimization of the cost of concentrate is always the goal of mineral processing plant for its profit pursuit.An upper bound C H constraint of cost per unit of concentrate is requiredmin C(x)=Ii=1r i x i+C otherIi=1(1−u i)x i/k1,i+Ii=1u i x i/k2,i+C energy(9)where the total unit cost C(x)is made up of the raw ore cost, the energy cost and the other cost including quota cost,the controllable manufacturing costs,and so on.In(9),C other is a fixed cost in a time period,and C energy is afixed unit energy cost considered here.Mineral raw materials cost make up most of the total unit cost of concentrate product.F.Constraints1)Comprehensive Production Indices Constraints:The real concentrate yield is constrained by its lower and upper limits as follows:Q L≤Q(x)≤Q H(10)I L≤Q(x)+I0−Q S≤I H.(11)In(10),the objective interval[Q L,Q H]of concentrate yield is initially determined by decision-making departments. Constraint(11)means that the surplus quantity of concentrate product in warehouse is restricted by the lower and upper storage limits after Q S(tons of)concentrate are either sold or consumed by the sintering process which is a process next to mineral process at the end of a time period.Provided that the expression[Q L,Q H]∩[Q S+I L−I0, Q S+I H−I0]= always holds,then(10)and(11)can be combined into the following constraint:max(Q L,Q S+I L−I0)≤Q(x)≤min(Q H,Q S+I H−I0).(12) Sometimes,in mineral processing plants,the objective in-terval[Q L,Q H]determined by manager can almost satisfy the condition[Q L,Q H]⊂[Q S+I L−I0,Q S+I H−I0],and then(10)is sufficient whilst(11)is redundant.We use(12) as a unified expression which is stillfit for such situation. The other four comprehensive production indices constraints should be satisfied as follows:βL≤β(x)≤βH(13)K(x)≤K H(14)ε(x)≥εL(15)C(x)≤C H.(16) In(13)–(16),the interval[ßL,ßH],upper limit K H and C H, lower limitεL have already been mentioned in Section II-E.Constraint(13)is used to ensure the range of concentrate grade.Constraint(14)is used to ensure that the ratio of the total raw ore consumption to the concentrate product output does not exceed a given upper limit.Constraint(15)avoids excessive metal loss,andfinally(16)ensures that cost does not exceed a predetermined limit.2)Equipment Capacity Constraints:The average feed throughput per hour for the j th type of equipment is restricted by its upper limit.There arefive types of equipments mainly in mineral processing plant shown as Fig.1.Thesefive types of equipments are the shaft furnace(j=1),the ball mill in high intensity magnetic separation cell(j=2),the ball mill in low intensity magnetic separation cell(j=3),the high intensity magnetic separator(j=4),and thefilter(j=5), respectively.Their capacity constraints are given as follows:q j(x)=Ii=1u i x iKk=1N k,j T k≤q j,H k∈{1,2,···K}j=1(17) q j(x)=Ii=1(1−u i)x iKk=1N k,j T k≤q j,H k∈{1,2,···K}j=2(18)。

Providence Bass Boot Comp BTC-1 说明书

Providence Bass Boot Comp BTC-1 说明书

BASS BOOT COMP BTC-1OWNER’S MANUALThank you for choosing Providence. In order to take full advantage of the product’s features and performance, please read this manual thoroughly and keep it in a safe place for future reference.■BASS BOOT COMP Features ●The Bass Boot Comp delivers super-smooth compression that can take your bass sound to new heights. Attack time and sustain controls allow the Bass Boot Comp to produce smoothly lingering long tones as well as percussive limiter type effects.●A threshold control optimizes compression response for the bass guitar’s pickups as well as picking strength. The attack time and sustain controls can then be used to produce effects ranging from fat, high-density limiting to fast compression that lets note attack come through for a more percussive feel. A red gain reduc-tion LED provides a visual indication of how much compression is being applied.●A mix control adjusts the ratio of direct to compressed sound, enabling a wide range of sonic variationsthat are not possible with simpler compression pedals: emphasize touch nuances while maintaining a solidtonal core, allow the natural tonal character of the instrument to come through in a smoothly compressedsignal, and much more.■Controls & Functions ①LEVEL :Adjusts the output level when the effect is ON.②SUSTAIN :Adjusts sustain time. Rotate counterclockwise for shorter sustain and a more limiter-like effectthat will only compress high-level input peaks. Rotate clockwise for longer sustain.③ATTACK :Adjusts the attack time (the amount of time it takes to reach maximum compression after aninput signal is detected). Rotate counterclockwise for shorter attack time and a more limiter-like effect thatwill only compress high-level input peaks. Rotate clockwise for longer attack times that will allow more of theinstrument’s natural attack to come through. Attack time can be adjusted from 0.1 to 10 milliseconds.④MIX :Adjusts the mix between the direct and compressed sound. When rotated fully counterclockwiseonly the direct sound is output, and when rotated fully clockwise only the effect (compressed) sound is out-put.⑤THRESHOLD :Adjusts the threshold level (the input signal level at which compression begins). Rotatecounterclockwise to raise the threshold level and reduce the overall amount of compression, or rotate clock-wise to lower the threshold level and increase overall compression. ⑥Gain Reduction LED :Indicates the approximate amount of compression being applied. The LED lightsdimly when a small amount of compression is being applied, with increasing brightness as more compres-sion is applied. This LED may light when power to the pedal is initially turned ON even when no input signalis present. This is normal behavior.⑦LED Indicator :Lights when the effect is ON. The LED will start to dim when the battery voltage dropsbelow approximately 7 volts. The effect will still function when the LED begins to dim, but performance maynot be optimum and the battery should be replaced as soon as possible.⑧IN :The output from a bass guitar, electronic musical instrument, or preceding effect pedal should beconnected here.⑨OUT :This jack should be connected to the input of an amplifier or effect unit. ⑩Footswitch :Turns the effect ON or OFF. ⑪DC9V INPUT :The DC output cable of an optional AC adaptor can be plugged in here.■Main Specification ●Controls: LEVEL, ATTACK, SUSTAIN, MIX, THRESHOLD ●Connectors: 1/4-inch phone jack x 2 (INPUT and OUTPUT), DC 9V input jack (AC adaptor jack)●Power Supply: 9V battery or AC adaptor (not included)●Power Consumption: DC9V, 25mA approx.●Dimensions: 115(D) x 73(W) x 50(H) mm ●Weight: 230 g approx. (Not including battery)■Battery ReplacementTo replace the battery, remove the bottom panel by unscrewing the four screws that hold it in place. Usea 9-volt 006P type battery. Be careful not to apply excessive force to the wiring when changing the bat-tery to avoid broken connections and other damage.■Precautions• Inserting or removing a plug from the input jack while the unit's output is connected to anamplifier/speakers can cause noise that can damage the speakers.• If the unit malfunctions or behaves abnormally, cease operation immediately and refer the problem tothe supplier.• If the unit will not be used for an extended period of time, remove the battery to prevent damage due tochemical leakage from the battery.• Use only an AC adaptor with internal voltage regulation.• When the battery voltage drops too low for proper operation the effect sound may become weak, theoutput level may drop, or no output will be produced at all. Be sure to replace the battery as soon as pos-sible if such symptoms occur.■TroubleshootingIf the indicator LED does not light: Replace the battery with a new one orconnect an appropriate AC adaptor.* Specifications and appearance are subject to change without notice.PPD1515-01Rev1.0。

Enhancing landfill gas recovery

Enhancing landfill gas recovery

Enhancing land fill gas recoveryAntti Niskanen *,Hanna Värri,Jouni Havukainen,Ville Uusitalo,Mika HorttanainenLUT Energy,Environmental Engineering,Lappeenranta University of Technology,P.O.Box 20,FI-53851Lappeenranta,Finlanda r t i c l e i n f oArticle history:Received 9April 2011Received in revised form 12April 2012Accepted 29May 2012Available online xxx Keywords:Land fill gasGreenhouse gas Land fill Recovery Utilizationa b s t r a c tThe land filling of municipal solid waste (MSW)may cause potential environmental impacts like global warming (GW),soil contaminations,and groundwater pollution.The degradation of MSW in anaerobic circumstances generates methane emissions,and can hence contribute the GW.As the GW is nowadays considered as one of the most serious environmental threats,the mitigation of methane emissions should obviously be aimed at on every land fill site where methane generation occurs.In this study,the treatment and utilization options for the generated LFG at case land fills which are located next to each other are examined.The yearly GHG emission balances are estimated for three different gas management scenarios.The first scenario is the combined heat and power (CHP)production with a gas engine.The second scenario is the combination of heat generation for the asphalt production process in the summer and district heat production by a water boiler in the winter.The third scenario is the LFG upgrading to biomethane.The estimation results illustrate that the LFG collection ef ficiency affects strongly on the magnitudes of GHG emissions.According to the results,the CHP production gives the highest GHG emission savings and is hence recommended as a gas utilization option for case land fills.Furthermore,aspects related to the case land fills ’extraction are discussed.Crown Copyright Ó2012Published by Elsevier Ltd.All rights reserved.1.Introduction 1.1.BackgroundLand filling has been the only disposal method that can deal with all the materials in the solid waste stream and it has also been considered to be the simplest and in many areas the cheapest disposal method (Mc Dougall et al.,2001).Thus,the majority of the generated solid waste is disposed at land fills.The nature of the disposed waste is different compared to the material found in the surroundings of land fills,and it may thereby affect negatively the environment (Christensen,2011).Land fills may pose negative environmental impacts to air,land,and water,like GHG emissions,soil contaminations,and groundwater pollution.Since huge amounts of solid waste is disposed at land fills,it is really important to pay attention to the adequately environmental management within whole life cycle of land fills with the aim to mitigate the potential environmental impacts caused by land filling.Land filled organic waste generates land fill gas (LFG)when it degrades in anaerobic circumstances.Without treatment,the released methane of LFG can create notable greenhouse gas (GHG)emissions.In 2005,the total anthropogenic GHG emissions wereapproximately 49Gt CO 2Àeq and the emissions of the waste and wastewater management sector were approximately 1.5Gt CO 2Àeq (Bogner et al.,2008).Globally,LFG emissions from land fills contribute to approximately half of all GHG emissions from the waste and wastewater management sector (Bogner et al.,2008).According to the Intergovernmental Panel on Climate Change (IPCC),CH 4recovery from land fills is a key to the GHG mitigation practices in the waste management sector (IPCC,2007).According to Statistics Finland,municipal waste land fills generated 1.12Mt CO 2Àeq of emissions in 2008(Statistics of Finland,2010a ).This amount creates 84%of all GHG emissions from the waste management sector in Finland.The great attention paid to the mitigation of greenhouse gas (GHG)emissions has been the catalyst for numerous policies worldwide.EU and Finnish regulations and strategies on waste management strongly encourage restricting the land filling of biodegradable waste and increasing of the utilization of waste in order to decrease LFG emissions (EU 99/31/EC ;EU Commission,2005;Huhtinen et al.,2007;Ministry of the Environment,2010a ;VnP 861/97).In addition,gas energy utiliza-tion is preferred in the EU directive,Finnish regulations,and IPCC guidelines (EU 99/31/EC ;IPCC,2007;VnP 861/97).Moreover,at the national level,the Working Group called “Bioenergy from Waste ”proposed 13waste-to-energy actions in Finland in February 2010.One of those actions is the reduction of GHG emissions from land fills which means that in practice LFG should be recovered more ef ficiently (Ministry of the Environment,2010b ).Although*Corresponding author.Tel.:þ358400230627;fax:þ35856246399.E-mail address:Antti.Niskanen@lut.fi(A.Niskanen).Contents lists available at SciVerse ScienceDirectJournal of Cleaner Productionjournal homepage:www.elsevier.co m/locate/jclepro0959-6526/$e see front matter Crown Copyright Ó2012Published by Elsevier Ltd.All rights reserved./10.1016/j.jclepro.2012.05.042Journal of Cleaner Production xxx (2012)1e 5the target of waste management regulations and strategies is to promote the LFG utilization,the number of landfills with an active gas collection system has not grown during the years2005e2008.After the closure of a landfill,the methane generation of LFG decreases making the utilization difficult.Although the amount of yearly generated methane reduces,the generation may continue decades after the closure and thus create notable cumulative GHG emissions in the long term.After an intensive gas generation phase, landfilled waste could also be recovered for energy production purposes.In the earlier studies(Obermeier and Saure,1995;Cossu et al.,1995;Rettenberger,1995;Hogland et al.,2004),energy values from11up to20MJ kgÀ1have been observed for extracted waste, and such high values can be sufficient for the incineration.On the other hand,naturally notable lower values can be obtained depending on the waste material content.The challenging long-term after-care of landfills could be shortened and made easier if the organic material were extracted and recovered for energy production.Thus,waste utilization could give GHG emission savings due to the replaced fossil fuels.In addition,impure wood and plastic fractions which are not suited for recycling could also be utilized in energy production.In addition to energy production and GHG emission saving advantages,also other environmental bene-fits could be achieved,like the avoidance of risks related to the surrounding soil or groundwater pollution.Also,economical benefits could be achieved because the after-care period is shorter and the overall costs of landfill operations decrease.Many economical drivers can also promote the extraction and utilization of waste materials from landfills,as van der Zee et al.have noticed (Van der Zee et al.,2004).Valuable precious metals of landfilled electrical devices can be separated and recovered,as well as other materials(Zhao et al.,2007).On the other hand,the impurity of the separated materials can limit their markets(Williams,2005).In addition,the observed pollution or the possibility of the pollution of the surrounding environment can be avoided which are the common motives for landfill extraction(Van der Zee et al.,2004). According to the directive on the landfill of waste,LFG collection and treatment is obligatory in European countries(EU99/31/EC).If LFG is recovered as an energy or material product,it can be regarded as a phase of landfill mining.Also,it can be considered as a necessary pre-treatment phase for later landfill mining.This study focuses on the LFG recovery and utilization and particularly on the LFG recovery performance improvements and the utilization option comparison using case landfills from the Kymenlaakso Jäte Oy in South-East Finland.During the recent years,the LFG generation in the new landfill has increased signif-icantly.Therefore,the LFG management solution examination is a very current topic.The objective of this paper is to estimate the yearly GHG emissions for three optional LFG management scenarios.In addition,landfilled waste extraction aspects are discussed.2.Materials and methods2.1.LFG generation at case landfillsTwo typical Finnish medium size municipal solid waste(MSW) landfills(the new landfill of7.8ha and the old landfill of9.1ha)are operated by Kymenlaakson jäte Oy in the Kymenlaakso region. Landfills are located next to each other.The old landfill was closed in2001and the new one was opened the same year.The bottom lining of new landfill fulfills the environmental protection requirements defined in the EU directive on the landfill of waste, whereas the lining of old landfill does not fulfill those require-ments.The amount of landfill gas collected from the old landfill is approximately0.88Â106m3yrÀ1with an average methane content of33%(Sarlin,2006,2007).According to the annual statistics of Kymenlaakson jäte Oy,from65Â103to72Â103t of waste(mainly MSW from households)is landfilled yearly in the new landfill.In2008,the total generation of landfill gas was eval-uated to be0.80Â106m3yrÀ1(Detes,2008).In spring2010,the Finnish Meteorological Institute carried out gas emission measurements with a micrometeorological method for the new landfill.According to micrometeorological measurements,the gas generation was approximated4.5Â106m3yrÀ1(Laurila,2010). According to these studies,the gas generation has increased significantly in the new landfill during the two years from2008to 2010.2.2.Scenario settings for gas recoveryBased on the gas generation and collection measurements carried out at case landfill sites,the energy potential of the landfill gas is shown in Table1.In this study,the gas collection efficiency for the new landfill is set to75%as recommend by USEPA(2008).With this collection efficiency,the total amount for available energy content of yearly collected LFG is21,300MWh which is a reference unit for each gas utilization scenario.In GHG emission estimations,the collected LFG is assumed to be utilized according to one of the following utili-zation options:Scenario1:Combined heat and power(CHP)production witha gas engine.Scenario2:The combination of heat generation for the asphalt production process in the summer and district heat production by a water boiler in the winter.Scenario3:LFG upgrading to biomethane(corresponding to the quality of natural gas).Scenarios1and2are chosen based on previous feasibility studies(Karttunen,2007;Niskanen et al.,2009a).Scenario3can be seen as an innovative option in Finland,and hence it is included in this study.The gas utilization options were studied to determine the GHG emissions that could be yearly avoided if energy produc-tion by fossil fuels is replaced by LFG.2.3.Other scenario assumptionsThe yearly utilization period is assumed to be8000h for each utilization option.When the collected landfill gas is not utilized,it is treated byflaring.The treatment efficiency for methane byflaring is assumed to be99%(SEPA,2002).The gas engine efficiency is assumed to be44%for heat and39%for electricity generation (Wong et al.,2001).The efficiency of heat generation both in district heating and in the asphalt production process is assumed to be90%. The overall internal energy consumption of the upgrading process is estimated to be9.1%,including the CH4loss which is set to1.5%of the total amount of collected CH4(Pertl et al.,2010).It is assumedTable1Energy potential of landfill gas from the old and new landfill.Landfill CollectedLFG[Â106m3yrÀ1]Methaneconcentration[%]Collectedmethane[Â106m3yrÀ1]Energy contentpotential[MWh/yr]Old landfill0.80a33a0.262600New landfill 3.34b,c56b 1.8718,700SUM 4.14 2.1321,300a Sarlin,2006and Sarlin,2007.b Laurila,2010.c with gas collection efficiency of75%.A.Niskanen et al./Journal of Cleaner Production xxx(2012)1e5 2that the lost CH4is not released into the atmosphere without treatment.It is also assumed that the LFG collection system consumes the electricity produced by the average Finnish elec-tricity production structure,and that the upgrading process would consume marginal electricity because if the utilization process is realized,it will increase the load of electricity consumption.GHG emissions for the average electricity production are assumed to be 207kg/MWh e and for the marginal electricity production with a coal condensing power plant823kg/MWh e(Dahlbo et al.,2005; Statistics of Finland,2010b).The methane oxidation efficiency in the landfill cover for released LFG is assumed to be10%.The GHG emission factor(GHG emissions per production,for energyproduction in unit:kg CO2Àeq /MWh)and other assumptions for LFGutilization and the emissions of replaced fuels are presented in Table2.For each Scenario,1,2,and3,the GHG emission and emission saving magnitudes(Fig.1)caused by the management of yearly collected LFG,as well as the GHG balances of yearly generated LFG (Fig.2)are estimated based on the collected data,scenario settings, and assumptions(presented above).3.Results and discussionThe GHG emissions due to the utilization of collected LFG (4.14Â106m3yrÀ1)for Scenarios1,2,and3are presented in Fig.1.As the results demonstrate(Fig.1),the highest amount of GHG emission savings,approximately8000t CO2Àeq/yr,can be achieved if the collected LFG is utilized in Scenario1.The main contributor for the avoided GHG emissions is the replaced electricity.If LFG is utilized in Scenario3,emission savings of approximately 6800t CO2Àeq/yr can be reached.On the other hand,the electricity consumption of the upgrading process leads to the highest GHG emissions,1200t CO2Àeq/yr,and thus reducing the GHG emission balance of Scenario 3.Scenario2leads to significantly lower emission savings,approximately4300t CO2Àeq/yr,than the other scenarios.The estimated GHG balances(including the GHG emis-sions from fugitively released LFG)for the generated LFG on three gas management options are shown in Fig.2.As the results clearly illustrate(Fig.2),the GHG emission balance for Scenario1,approximately3600t CO2Àeq/yr,is signifi-cantly lower than for Scenario2,approximately7300t CO2Àeq/yr,and for Scenario3,approximately6300t CO2Àeq/yr.The magnitude of the GHG emission balance for Scenario3is approximately14%lower than for Scenario2.With the LFG collection efficiency of75%,the gas utilization can notably compensate for the GHG emissions caused by the uncollected LFG of11,400t CO2Àeq/yr.As discovered in many studies(Börjesson et al.,2007;Spokas et al.,2006;Themelis and Ulloa,2007),the LFG collection efficiency ranges extensively in individual municipal landfills.USEPA has given75%as a default value for the collection efficiency(USEPA,2008;Sullivan,2010)when the collection system is in use and operates without problems.The collection efficiency of75%was the assumption also in this study for the new landfill.Obviously,assumptions related to the recovery of LFG can have significant impacts on the assessment of GHG emissions,as presented in earlier studies(Manfredi et al.,2009a; Moberg et al.,2005;Wanichpongpan and Gheewala,2007). Higher gas collection efficiency increases the amount of LFG available for utilization purposes and hence enables higher GHG emission savings while direct gas emissions from the landfills to the atmosphere decrease.As discussed in a number of other studies(Lombardi et al.,2006;Manfredi et al.,2009a;Niskanen et al.,2009b),the direct emissions are typically the main contributor to the GHG emissions from landfilling.In this case,if the gas collection efficiency were85%and all the collected LFG would be utilized in Scenario1,the fugitive emissions from the landfills would decrease by40%and the GHG emission savings through utilization would increase by11.8%.In other words,with higher collection efficiency(85%),the emission balance of Scenario1would be numerally negative,À2220t CO2Àeq/yr(Fig.3), when the GHG emission savings are higher than the emissions. On the other hand,if the collection efficiency were65%,the emissions from the landfill would grow by40%and the avoided emissions would be reduced by13.3%.In that case,the GHG emission balance of Scenario1would be9000t CO2Àeq/yr(Fig.3). Considering the fact that the gas collection efficiency is a crucial factor in the mitigation of GHG emissions,it is important to pursue as high collection efficiency as possible.After the gas is collected,it can be treated,thus decreasing the global warming effect strongly.Logically,gas utilization is more advantageous than treatment because the LFG utilization can replace the use of fossil fuels(Hao et al.,2008;Lombardi et al.,2006;Manfredi et al.,2009b).Due to the improved gas collection,it is possible to mitigate the GHG emissions resulting from landfilling significantly.In Finland, where the LFG emissions form84%of all GHG emissions caused by the waste management sector,the effective gas collection affects strongly the emissions of the entire waste management sector.Table2Assumptions of replaced processes and emission factors.Utilization process Replaced process Basis for theassumption GHG emission factor[kg CO2Àeq/MWh]CHP heat production by LFG Local heat productionby natural gasCurrent fuel fordistrict heating213aCHP electricity production by LFG Marginal electricityproduction by coalin FinlandChange in electricitygeneration823aDistrict heat by LFG Local heat productionby natural gas Current fuel fordistrict heating213aHeat production in asphalt production process Heat production by lightfuel oil(specific process)Current fuel in asphaltproduction process220bCHP heat production by up-graded LFG Local heat productionby natural gasCurrent fuel for districtheating213aCHP electricity production by up-graded LFG Marginal electricityproduction by coalin FinlandChange in electricitygeneration823aa GHG emissions based on fuel classification of Statistics of Finland(2010b)and heat and electricity production efficiencies reported by Flyktman and Helynen(2003).b The heat production efficiency for natural gas is assumed to be90%.A.Niskanen et al./Journal of Cleaner Production xxx(2012)1e53Like the LFG collection ef ficiency,the emission factors can also vary extensively.Obviously,the selected factors have a notable effect on the results of the GHG emission estimations of the considered processes.The amount of emission savings due to energy recovery substantially depends strongly on the data used for emissions calculations (Finnveden et al.,2005;Fruergaard et al.,2009;Manfredi et al.,2009a ).In this study,it is assumed that the additional electricity production by gas utilization replaces the marginal electricity produced by coal condensing power plants.The Finnish average electricity production includes a notable share of CO 2emission neutral production,such as hydropower and nuclear electricity generation.Thus,if average fuel mix were assumed to be replaced,the amount of emissions and emission savings from the electricity production could be signi ficantly lower,and hence the differences between utilization options would change.Country-speci fic emission data for energy production can vary signi fi-cantly,and hence dissimilar outcomes for emission estimations are possible (Fruergaard et al.,2009).However,the marginal data was used in this study for the replaced electricity data,as preferred by Fruergaard et al.(2009).Uncertainties related to emissions caused by collected LFG do not change the superiority of the examined utilization options from the GHG emission point of view.Higher amounts of emissions from the treatment process or a lower collection ef ficiency of LFG would diminish the overall GHG emission balance of the considered system.If the amount of available gas were lower,it would decrease the emission savings and the feasibility of utilization,and in contrast,an obviously higher amount of gas would increase the emission savings and decrease the investment risks.From the GHG emission point of view,the CHP utilization option seems to be the most rational alternative.However,the GHG emission aspect cannot be the only criterion in the selection of the most convenient gas utilization technology.Other aspects,such as technical and economic ones,have to be taken into account.Each utilization technology sets requirements for the amount and quality of the generated LFG.In addition,the utilization technology must be adaptable to the existing infrastructure.For example,thedistrict heat generation is locally-oriented and requires an existing district heating network,and the utilization in an industrial process requires a suitable business near the land fill.Long distance trans-portation of the collected LFG is not feasible,and hence the gas needs to be utilized on-site or near the land fill.Obviously,this restricts the choice of the location for the gas nd fills are often apart from residential areas,and thus,the possibilities for heat recovery from LFG may be limited.It is,nevertheless,possible to situate industry that demands heat close to the waste manage-ment site.A signi ficant supply of heat energy may encourage such industries to relocate near the land fill.Moreover,the decline of LFG generation after the land fill closure must be taken into account.After the gas generation is diminished and the methane content is too low for energy utilization purposes,the land fill after-care period can be reduced through extraction measures.The most valuable waste fraction can be separated and the residues can be routed to incineration.Thus,the recovery of energy can be maxi-mized,the material recovery is enhanced,and the risk of soil contamination and groundwater pollution decreases in after-care period.4.ConclusionThe results show that the performance of LFG collection has a very strong impact on the GHG emissions of the land fill and on the amount of LFG available for utilization.In addition,the results show that emission savings through the utilization of collected LFG can signi ficantly compensate for the released LFG.According to the estimated GHG balance results,the combined heat and power (CHP)production with a gas engine is the recommended option for collected gas utilization.After the methane generation is too low for gas utilization,land filled material could be extracted for incineration.Thus,the recovery of energy can be maximized,the material recovery is enhanced,and the risk of pollution decreases.Furthermore,possible economic bene fits can be achieved through reduced after-care period.AcknowledgmentsThe authors would like gratefully to acknowledge the Fortum Foundation and the Lappeenranta University of Technology Research Foundation for their financial support to this study.ReferencesBogner,J.,Pipatti,R.,Hashimoto,S.,Diaz,C.,Mareckova,K.,Diaz,L.,Kjeldsen,P.,Monni,S.,Faaij, A.,Gao,Q.,Zhang,T.,Ahmed,M.A.,Sutamihardja,R.T.M.,Gregory,R.,2008.Mitigation of global greenhouse gas emissions from waste:conclusions and strategies from the Intergovernmental Panel on ClimateFig.3.Effect of LFG collection ef ficiency on the GHG emission balance,avoided GHG emissions,and GHG emissions caused by the released LFG of Scenario 1.Fig.2.Estimated overall 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微电子词典中英文对照

微电子词典中英文对照

微电子词典Abrupt junction 突变结Accelerated testing 加速实验Acceptor 受主Acceptor atom 受主原子Accumulation 积累、堆积Accumulating contact 积累接触Accumulation region 积累区Accumulation layer 积累层Active region 有源区Active component 有源元Active device 有源器件Activation 激活Activation energy 激活能Active region 有源(放大)区Admittance 导纳Allowed band 允带Alloy-junction device合金结器件Aluminum(Aluminium) 铝Aluminum – oxide 铝氧化物Aluminum passivation 铝钝化Ambipolar 双极的Ambient temperature 环境温度Amorphous 无定形的,非晶体的Amplifier 功放扩音器放大器Analogue(Analog) comparator 模拟比较器Angstrom 埃Anneal 退火Anisotropic 各向异性的Anode 阳极Arsenic (AS) 砷Auger 俄歇Auger process 俄歇过程Avalanche 雪崩Avalanche breakdown 雪崩击穿Avalanche excitation雪崩激发Background carrier 本底载流子Background doping 本底掺杂Backward 反向Backward bias 反向偏置Ballasting resistor 整流电阻Ball bond 球形键合Band 能带Band gap 能带间隙Barrier 势垒Barrier layer 势垒层Barrier width 势垒宽度Base 基极Base contact 基区接触Base stretching 基区扩展效应Base transit time 基区渡越时间Base transport efficiency基区输运系数Base-width modulation基区宽度调制Basis vector 基矢Bias 偏置Bilateral switch 双向开关Binary code 二进制代码Binary compound semiconductor 二元化合物半导体Bipolar 双极性的Bipolar Junction Transistor (BJT)双极晶体管Bloch 布洛赫Blocking band 阻挡能带Blocking contact 阻挡接触Body - centered 体心立方Body-centred cubic structure 体立心结构Boltzmann 波尔兹曼Bond 键、键合Bonding electron 价电子Bonding pad 键合点Bootstrap circuit 自举电路Bootstrapped emitter follower 自举射极跟随器Boron 硼Borosilicate glass 硼硅玻璃Boundary condition 边界条件Bound electron 束缚电子Breadboard 模拟板、实验板Break down 击穿Break over 转折Brillouin 布里渊Brillouin zone 布里渊区Built-in 内建的Build-in electric field 内建电场Bulk 体/体内Bulk absorption 体吸收Bulk generation 体产生Bulk recombination 体复合Burn - in 老化Burn out 烧毁Buried channel 埋沟Buried diffusion region 隐埋扩散区Can 外壳Capacitance 电容Capture cross section 俘获截面Capture carrier 俘获载流子Carrier 载流子、载波Carry bit 进位位Carry-in bit 进位输入Carry-out bit 进位输出Cascade 级联Case 管壳Cathode 阴极Center 中心Ceramic 陶瓷(的)Channel 沟道Channel breakdown 沟道击穿Channel current 沟道电流Channel doping 沟道掺杂Channel shortening 沟道缩短Channel width 沟道宽度Characteristic impedance 特征阻抗Charge 电荷、充电Charge-compensation effects 电荷补偿效应Charge conservation 电荷守恒Charge neutrality condition 电中性条件Charge drive/exchange/sharing/transfer/storage 电荷驱动/交换/共享/转移/存储Chemmical etching 化学腐蚀法Chemically-Polish 化学抛光Chemmically-Mechanically Polish (CMP) 化学机械抛光Chip 芯片Chip yield 芯片成品率Clamped 箝位Clamping diode 箝位二极管Cleavage plane 解理面Clock rate 时钟频率Clock generator 时钟发生器Clock flip-flop 时钟触发器Close-packed structure 密堆积结构Close-loop gain 闭环增益Collector 集电极Collision 碰撞Compensated OP-AMP 补偿运放Common-base/collector/emitter connection 共基极/集电极/发射极连接Common-gate/drain/source connection 共栅/漏/源连接Common-mode gain 共模增益Common-mode input 共模输入Common-mode rejection ratio (CMRR) 共模抑制比Compatibility 兼容性Compensation 补偿Compensated impurities 补偿杂质Compensated semiconductor 补偿半导体Complementary Darlington circuit 互补达林顿电路Complementary Metal-Oxide-Semiconductor Field-Effect-Transistor(CMOS)互补金属氧化物半导体场效应晶体管Complementary error function 余误差函数Computer-aided design (CAD)/test(CAT)/manufacture(CAM) 计算机辅助设计/ 测试/制造Compound Semiconductor 化合物半导体Conductance 电导Conduction band (edge) 导带(底) Conduction level/state 导带态Conductor 导体Conductivity 电导率Configuration 组态Conlomb 库仑Conpled Configuration Devices 结构组态Constants 物理常数Constant energy surface 等能面Constant-source diffusion恒定源扩散Contact 接触Contamination 治污Continuity equation 连续性方程Contact hole 接触孔Contact potential 接触电势Continuity condition 连续性条件Contra doping 反掺杂Controlled 受控的Converter 转换器Conveyer 传输器Copper interconnection system 铜互连系统Couping 耦合Covalent 共阶的Crossover 跨交Critical 临界的Crossunder 穿交Crucible坩埚Crystal defect/face/orientation/lattice 晶体缺陷/晶面/晶向/晶格Current density 电流密度Curvature 曲率Cut off 截止Current drift/dirve/sharing 电流漂移/驱动/共享Current Sense 电流取样Curvature 弯曲Custom integrated circuit 定制集成电路Cylindrical 柱面的Czochralshicrystal 直立单晶Czochralski technique 切克劳斯基技术(Cz法直拉晶体J)Dangling bonds 悬挂键Dark current 暗电流Dead time 空载时间Debye length 德拜长度De.broglie 德布洛意Decderate 减速Decibel (dB) 分贝Decode 译码Deep acceptor level 深受主能级Deep donor level 深施主能级Deep impurity level 深度杂质能级Deep trap 深陷阱Defeat 缺陷Degenerate semiconductor 简并半导体Degeneracy 简并度Degradation 退化Degree Celsius(centigrade) /Kelvin 摄氏/开氏温度Delay 延迟Density 密度Density of states 态密度Depletion 耗尽Depletion approximation 耗尽近似Depletion contact 耗尽接触Depletion depth 耗尽深度Depletion effect 耗尽效应Depletion layer 耗尽层Depletion MOS 耗尽MOS Depletion region 耗尽区Deposited film 淀积薄膜Deposition process 淀积工艺Design rules 设计规则Die 芯片(复数dice)Diode 二极管Dielectric 介电的Dielectric isolation 介质隔离Difference-mode input 差模输入Differential amplifier 差分放大器Differential capacitance 微分电容Diffused junction 扩散结Diffusion 扩散Diffusion coefficient 扩散系数Diffusion constant 扩散常数Diffusivity 扩散率Diffusion capacitance/barrier/current/furnace 扩散电容/势垒/电流/炉Digital circuit 数字电路Dipole domain 偶极畴Dipole layer 偶极层Direct-coupling 直接耦合Direct-gap semiconductor 直接带隙半导体Direct transition 直接跃迁Discharge 放电Discrete component 分立元件Dissipation 耗散Distribution 分布Distributed capacitance 分布电容Distributed model 分布模型Displacement 位移Dislocation 位错Domain 畴Donor 施主Donor exhaustion 施主耗尽Dopant 掺杂剂Doped semiconductor 掺杂半导体Doping concentration 掺杂浓度Double-diffusive MOS(DMOS)双扩散MOS.Drift 漂移Drift field 漂移电场Drift mobility 迁移率Dry etching 干法腐蚀Dry/wet oxidation 干/湿法氧化Dose 剂量Duty cycle 工作周期Dual-in-line package (DIP)双列直插式封装Dynamics 动态Dynamic characteristics 动态属性Dynamic impedance 动态阻抗Early effect 厄利效应Early failure 早期失效Effective mass 有效质量Einstein relation(ship) 爱因斯坦关系Electric Erase Programmable Read Only Memory(E2PROM) 一次性电可擦除只读存储器Electrode 电极Electrominggratim 电迁移Electron affinity 电子亲和势Electronic -grade 电子能Electron-beam photo-resist exposure 光致抗蚀剂的电子束曝光Electron gas 电子气Electron-grade water 电子级纯水Electron trapping center 电子俘获中心Electron Volt (eV) 电子伏Electrostatic 静电的Element 元素/元件/配件Elemental semiconductor 元素半导体Ellipse 椭圆Ellipsoid 椭球Emitter 发射极Emitter-coupled logic 发射极耦合逻辑Emitter-coupled pair 发射极耦合对Emitter follower 射随器Empty band 空带Emitter crowding effect 发射极集边(拥挤)效应Endurance test =life test 寿命测试Energy state 能态Energy momentum diagram 能量-动量(E-K)图Enhancement mode 增强型模式Enhancement MOS 增强性MOS Entefic (低)共溶的Environmental test 环境测试Epitaxial 外延的Epitaxial layer 外延层Epitaxial slice 外延片Expitaxy 外延Equivalent curcuit 等效电路Equilibrium majority /minority carriers 平衡多数/少数载流子Erasable Programmable ROM (EPROM)可搽取(编程)存储器Error function complement 余误差函数Etch 刻蚀Etchant 刻蚀剂Etching mask 抗蚀剂掩模Excess carrier 过剩载流子Excitation energy 激发能Excited state 激发态Exciton 激子Extrapolation 外推法Extrinsic 非本征的Extrinsic semiconductor 杂质半导体Face - centered 面心立方Fall time 下降时间Fan-in 扇入Fan-out 扇出Fast recovery 快恢复Fast surface states 快界面态Feedback 反馈Fermi level 费米能级Fermi-Dirac Distribution 费米-狄拉克分布Femi potential 费米势Fick equation 菲克方程(扩散)Field effect transistor 场效应晶体管Field oxide 场氧化层Filled band 满带Film 薄膜Flash memory 闪烁存储器Flat band 平带Flat pack 扁平封装Flicker noise 闪烁(变)噪声Flip-flop toggle 触发器翻转Floating gate 浮栅Fluoride etch 氟化氢刻蚀Forbidden band 禁带Forward bias 正向偏置Forward blocking /conducting正向阻断/导通Frequency deviation noise频率漂移噪声Frequency response 频率响应Function 函数Gain 增益Gallium-Arsenide(GaAs) 砷化钾Gamy ray r 射线Gate 门、栅、控制极Gate oxide 栅氧化层Gauss(ian)高斯Gaussian distribution profile 高斯掺杂分布Generation-recombination 产生-复合Geometries 几何尺寸Germanium(Ge) 锗Graded 缓变的Graded (gradual) channel 缓变沟道Graded junction 缓变结Grain 晶粒Gradient 梯度Grown junction 生长结Guard ring 保护环Gummel-Poom model 葛谋-潘模型Gunn - effect 狄氏效应Hardened device 辐射加固器件Heat of formation 形成热Heat sink 散热器、热沉Heavy/light hole band 重/轻空穴带Heavy saturation 重掺杂Hell - effect 霍尔效应Heterojunction 异质结Heterojunction structure 异质结结构Heterojunction Bipolar Transistor(HBT)异质结双极型晶体High field property 高场特性High-performance MOS.( H-MOS)高性能MOS. Hormalized 归一化Horizontal epitaxial reactor 卧式外延反应器Hot carrior 热载流子Hybrid integration 混合集成Image - force 镜象力Impact ionization 碰撞电离Impedance 阻抗Imperfect structure 不完整结构Implantation dose 注入剂量Implanted ion 注入离子Impurity 杂质Impurity scattering 杂志散射Incremental resistance 电阻增量(微分电阻)In-contact mask 接触式掩模Indium tin oxide (ITO) 铟锡氧化物Induced channel 感应沟道Infrared 红外的Injection 注入Input offset voltage 输入失调电压Insulator 绝缘体Insulated Gate FET(IGFET)绝缘栅FET Integrated injection logic集成注入逻辑Integration 集成、积分Interconnection 互连Interconnection time delay 互连延时Interdigitated structure 交互式结构Interface 界面Interference 干涉International system of unions国际单位制Internally scattering 谷间散射Interpolation 内插法Intrinsic 本征的Intrinsic semiconductor 本征半导体Inverse operation 反向工作Inversion 反型Inverter 倒相器Ion 离子Ion beam 离子束Ion etching 离子刻蚀Ion implantation 离子注入Ionization 电离Ionization energy 电离能Irradiation 辐照Isolation land 隔离岛Isotropic 各向同性Junction FET(JFET) 结型场效应管Junction isolation 结隔离Junction spacing 结间距Junction side-wall 结侧壁Latch up 闭锁Lateral 横向的Lattice 晶格Layout 版图Lattice binding/cell/constant/defect/distortion 晶格结合力/晶胞/晶格/晶格常熟/晶格缺陷/晶格畸变Leakage current (泄)漏电流Level shifting 电平移动Life time 寿命linearity 线性度Linked bond 共价键Liquid Nitrogen 液氮Liquid-phase epitaxial growth technique 液相外延生长技术Lithography 光刻Light Emitting Diode(LED) 发光二极管Load line or Variable 负载线Locating and Wiring 布局布线Longitudinal 纵向的Logic swing 逻辑摆幅Lorentz 洛沦兹Lumped model 集总模型Majority carrier 多数载流子Mask 掩膜板,光刻板Mask level 掩模序号Mask set 掩模组Mass - action law质量守恒定律Master-slave D flip-flop主从D触发器Matching 匹配Maxwell 麦克斯韦Mean free path 平均自由程Meandered emitter junction梳状发射极结Mean time before failure (MTBF) 平均工作时间Megeto - resistance 磁阻Mesa 台面MESFET-Metal Semiconductor金属半导体FETMetallization 金属化Microelectronic technique 微电子技术Microelectronics 微电子学Millen indices 密勒指数Minority carrier 少数载流子Misfit 失配Mismatching 失配Mobile ions 可动离子Mobility 迁移率Module 模块Modulate 调制Molecular crystal分子晶体Monolithic IC 单片IC MOSFET金属氧化物半导体场效应晶体管Mos. Transistor(MOST )MOS. 晶体管Multiplication 倍增Modulator 调制Multi-chip IC 多芯片ICMulti-chip module(MCM) 多芯片模块Multiplication coefficient倍增因子Naked chip 未封装的芯片(裸片)Negative feedback 负反馈Negative resistance 负阻Nesting 套刻Negative-temperature-coefficient 负温度系数Noise margin 噪声容限Nonequilibrium 非平衡Nonrolatile 非挥发(易失)性Normally off/on 常闭/开Numerical analysis 数值分析Occupied band 满带Officienay 功率Offset 偏移、失调On standby 待命状态Ohmic contact 欧姆接触Open circuit 开路Operating point 工作点Operating bias 工作偏置Operational amplifier (OPAMP)运算放大器Optical photon =photon 光子Optical quenching光猝灭Optical transition 光跃迁Optical-coupled isolator光耦合隔离器Organic semiconductor有机半导体Orientation 晶向、定向Outline 外形Out-of-contact mask非接触式掩模Output characteristic 输出特性Output voltage swing 输出电压摆幅Overcompensation 过补偿Over-current protection 过流保护Over shoot 过冲Over-voltage protection 过压保护Overlap 交迭Overload 过载Oscillator 振荡器Oxide 氧化物Oxidation 氧化Oxide passivation 氧化层钝化Package 封装Pad 压焊点Parameter 参数Parasitic effect 寄生效应Parasitic oscillation 寄生振荡Passination 钝化Passive component 无源元件Passive device 无源器件Passive surface 钝化界面Parasitic transistor 寄生晶体管Peak-point voltage 峰点电压Peak voltage 峰值电压Permanent-storage circuit 永久存储电路Period 周期Periodic table 周期表Permeable - base 可渗透基区Phase-lock loop 锁相环Phase drift 相移Phonon spectra 声子谱Photo conduction 光电导Photo diode 光电二极管Photoelectric cell 光电池Photoelectric effect 光电效应Photoenic devices 光子器件Photolithographic process 光刻工艺(photo) resist (光敏)抗腐蚀剂Pin 管脚Pinch off 夹断Pinning of Fermi level 费米能级的钉扎(效应)Planar process 平面工艺Planar transistor 平面晶体管Plasma 等离子体Plezoelectric effect 压电效应Poisson equation 泊松方程Point contact 点接触Polarity 极性Polycrystal 多晶Polymer semiconductor聚合物半导体Poly-silicon 多晶硅Potential (电)势Potential barrier 势垒Potential well 势阱Power dissipation 功耗Power transistor 功率晶体管Preamplifier 前置放大器Primary flat 主平面Principal axes 主轴Print-circuit board(PCB) 印制电路板Probability 几率Probe 探针Process 工艺Propagation delay 传输延时Pseudopotential method 膺势发Punch through 穿通Pulse triggering/modulating 脉冲触发/调制PulseWiden Modulator(PWM) 脉冲宽度调制Punchthrough 穿通Push-pull stage 推挽级Quality factor 品质因子Quantization 量子化Quantum 量子Quantum efficiency量子效应Quantum mechanics 量子力学Quasi – Fermi-level准费米能级Quartz 石英Radiation conductivity 辐射电导率Radiation damage 辐射损伤Radiation flux density 辐射通量密度Radiation hardening 辐射加固Radiation protection 辐射保护Radiative - recombination辐照复合Radioactive 放射性Reach through 穿通Reactive sputtering source 反应溅射源Read diode 里德二极管Recombination 复合Recovery diode 恢复二极管Reciprocal lattice 倒核子Recovery time 恢复时间Rectifier 整流器(管)Rectifying contact 整流接触Reference 基准点基准参考点Refractive index 折射率Register 寄存器Registration 对准Regulate 控制调整Relaxation lifetime 驰豫时间Reliability 可靠性Resonance 谐振Resistance 电阻Resistor 电阻器Resistivity 电阻率Regulator 稳压管(器)Relaxation 驰豫Resonant frequency共射频率Response time 响应时间Reverse 反向的Reverse bias 反向偏置Sampling circuit 取样电路Sapphire 蓝宝石(Al2O3)Satellite valley 卫星谷Saturated current range电流饱和区Saturation region 饱和区Saturation 饱和的Scaled down 按比例缩小Scattering 散射Schockley diode 肖克莱二极管Schottky 肖特基Schottky barrier 肖特基势垒Schottky contact 肖特基接触Schrodingen 薛定厄Scribing grid 划片格Secondary flat 次平面Seed crystal 籽晶Segregation 分凝Selectivity 选择性Self aligned 自对准的Self diffusion 自扩散Semiconductor 半导体Semiconductor-controlled rectifier 可控硅Sendsitivity 灵敏度Serial 串行/串联Series inductance 串联电感Settle time 建立时间Sheet resistance 薄层电阻Shield 屏蔽Short circuit 短路Shot noise 散粒噪声Shunt 分流Sidewall capacitance 边墙电容Signal 信号Silica glass 石英玻璃Silicon 硅Silicon carbide 碳化硅Silicon dioxide (SiO2) 二氧化硅Silicon Nitride(Si3N4) 氮化硅Silicon On Insulator 绝缘硅Siliver whiskers 银须Simple cubic 简立方Single crystal 单晶Sink 沉Skin effect 趋肤效应Snap time 急变时间Sneak path 潜行通路Sulethreshold 亚阈的Solar battery/cell 太阳能电池Solid circuit 固体电路Solid Solubility 固溶度Sonband 子带Source 源极Source follower 源随器Space charge 空间电荷Specific heat(PT) 热Speed-power product 速度功耗乘积Spherical 球面的Spin 自旋Split 分裂Spontaneous emission 自发发射Spreading resistance扩展电阻Sputter 溅射Stacking fault 层错Static characteristic 静态特性Stimulated emission 受激发射Stimulated recombination 受激复合Storage time 存储时间Stress 应力Straggle 偏差Sublimation 升华Substrate 衬底Substitutional 替位式的Superlattice 超晶格Supply 电源Surface 表面Surge capacity 浪涌能力Subscript 下标Switching time 开关时间Switch 开关Tailing 扩展Terminal 终端Tensor 张量Tensorial 张量的Thermal activation 热激发Thermal conductivity 热导率Thermal equilibrium 热平衡Thermal Oxidation 热氧化Thermal resistance 热阻Thermal sink 热沉Thermal velocity 热运动Thermoelectricpovoer 温差电动势率Thick-film technique 厚膜技术Thin-film hybrid IC薄膜混合集成电路Thin-Film Transistor(TFT) 薄膜晶体Threshlod 阈值Thyistor 晶闸管Transconductance 跨导Transfer characteristic 转移特性Transfer electron 转移电子Transfer function 传输函数Transient 瞬态的Transistor aging(stress) 晶体管老化Transit time 渡越时间Transition 跃迁Transition-metal silica 过度金属硅化物Transition probability 跃迁几率Transition region 过渡区Transport 输运Transverse 横向的Trap 陷阱Trapping 俘获Trapped charge 陷阱电荷Triangle generator 三角波发生器Triboelectricity 摩擦电Trigger 触发Trim 调配调整Triple diffusion 三重扩散Truth table 真值表Tolerahce 容差Tunnel(ing) 隧道(穿)Tunnel current 隧道电流Turn over 转折Turn - off time 关断时间Ultraviolet 紫外的Unijunction 单结的Unipolar 单极的Unit cell 原(元)胞Unity-gain frequency 单位增益频率Unilateral-switch单向开关Vacancy 空位Vacuum 真空Valence(value) band 价带Value band edge 价带顶Valence bond 价键Vapour phase 汽相Varactor 变容管Varistor 变阻器Vibration 振动Voltage 电压Wafer 晶片Wave equation 波动方程Wave guide 波导Wave number 波数Wave-particle duality 波粒二相性Wear-out 烧毁Wire routing 布线Work function 功函数Worst-case device 最坏情况器件Yield 成品率Zener breakdown 齐纳击穿Zone melting 区熔法。

黑龙江省哈尔滨师范大学附属中学2024-2025学年高三上学期10月月考英语试题

黑龙江省哈尔滨师范大学附属中学2024-2025学年高三上学期10月月考英语试题

黑龙江省哈尔滨师范大学附属中学2024-2025学年高三上学期10月月考英语试题一、听力选择题1.How many of the dresses does the woman have?A.One.B.Two.C.Three.2.How does the man feel about the shoes?A.Satisfied.B.Embarrassed.C.Dissatisfied.3.Where are the speakers probably?A.In a store.B.In an office.C.In a classroom.4.What is the relationship between the speakers?A.Strangers.B.Friends.C.Husband and wife. 5.What is the weather like now?A.Cloudy.B.Sunny.C.Rainy.听下面一段较长对话,回答以下小题。

6.What do we know about the woman?A.She likes the outdoors.B.She tripped up on a rock.C.She never camped in the woods.7.What is hard in the dark according to the man?A.Setting up a tent.B.Avoiding rocks.C.Building a fire.听下面一段较长对话,回答以下小题。

8.What did the man do yesterday?A.He called his friends.B.He visited the gallery.C.He made a reservation. 9.What is the man’s problem?A.He found the gallery was full of people.B.He didn’t know where to pick up the tickets.C.His name is not on the list.10.What will the woman most likely do next?A.Give some tickets to the man.B.Close the gallery.C.Contact a lady.听下面一段较长对话,回答以下小题。

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IEEE Photonics Technology Letters:/archives/January 2002VOLUME 14NUMBER 1IPTLEL(ISSN 1041-1135)PAPERCopyright © 2002 IEEE.This material is posted here with permission of the IEEE.Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must beobtained from the IEEE by sending a blank email message topubs-permissions@.By choosing to view this document, you agree to all provisions ofthe copyright laws protecting it.Reprinted fromIEEE Photonics Technology Letters, vol. 14, no. 1, pp. 12-15, Jan. 2002Acceleration of Gain Recovery in Semiconductor Optical Amplifiersby Optical Injection near Transparency WavelengthJ.L. Pleumeekers, M. Kauer, K. Dreyer, C. Burrus, A.G. Dentai, S. Schunk, J. Leuthold, C.H. Joyner12IEEE PHOTONICS TECHNOLOGY LETTERS,VOL.14,NO.1,JANUARY2002 Acceleration of Gain Recovery in Semiconductor Optical Amplifiers by Optical InjectionNear Transparency WavelengthJacco L.Pleumeekers,Matthias Kauer,Member,IEEE,Kevin Dreyer,Charles Burrus,Life Fellow,IEEE, Andrew G.Dentai,Fellow,IEEE,Steve Shunk,Jürg Leuthold,Member,IEEE,and Charles H.Joyner,Member,IEEEAbstract—By using optical injection near the transparency wavelength of semiconductor optical amplifiers,we show exper-imentally that both the saturation output power and the gain recovery can be greatly improved.By injecting80mW of pump power,we observe a3-dB increase in saturation output power.For 73mW of pump power,we find a reduction in gain recovery time from over200ps down to below40ps,while maintaining14dB of fiber-to-fiber gain at1555-nm wavelength.Index Terms—Gain recovery,optical injection,saturation output power,semiconductor optical amplifier.I.I NTRODUCTIONI T IS EXPECTED that future high-speed telecommunicationsystems will use all-optical technologies to avoid costly elec-trooptic conversions.Semiconductor optical amplifiers(SOAs) can be used to perform a variety of all-optical functions,such as wavelength conversion,regeneration,and switching.They have the advantage of being compact,consume low-power,and can be used over a wide wavelength range.For many high-speed applications,the SOA must have a fast gain recovery to avoid system penalties arising from bit pattern dependencies[1].The gain recovery of SOAs is limited by the carrier lifetime,which itself depends on the applied current and the optical intensity in the active layer.A high current provides a large carrier density and also a high amplified spontaneous emission power,both of which tend to shorten the carrier lifetime.Therefore,to obtain a fast gain recovery,a high current must be applied.Another way to enhance the gain recovery is by increasing the optical intensity in the active layer.This leads to a higher stimulated re-combination rate,and therefore,to a shorter carrier lifetime.The optical intensity can either be generated inside the SOA,or in-jected into the SOA from an external laser.The first case is the so-called gain-clamped SOA(GCSOA)which has distributed Bragg reflector(DBR)gratings to make the SOA lase at a wave-length offset by a few tens of nanometers from the gain peak[2]. The gain of GCSOAs is fixed by the device design and is lower than for an SOA.The GCSOAs can have high optical intensities, and therefore,fast gain recovery,but the internal lasing mode leads to relaxation oscillations in the gain recovery.The second case,where the optical intensity is injected into the SOA by anManuscript received July6,2001;revised September10,2001.The authors are with Lucent Technologies-Bell Labs,Holmdel,NJ07733 USA(e-mail:jaccop@).Publisher Item Identifier S1041-1135(02)00011-3.external laser,is more flexible as the gain of the SOA is not fixed by the design and the wavelength of the external laser can be changed.The gain recovery of the externally injected SOA exhibits an exponential recovery without oscillations.Several research groups have reported theoretical and experimental re-sults on externally injected SOAs.It has been shown that the injected light accelerates the gain recovery[3]–[6],enhances the gain linearity[7],and increases the saturation output power [4],[7]–[9].The injection wavelength is typically chosen in the gain region[9],[10],or toward the transparency wavelength, [4]–[8].In the latter case,the required optical injection power will be high,but the available gain of the SOA will also remain high[4],[6],[8].By using a wavelength around the gain max-imum,the required acceleration can be obtained with small op-tical injection power,but the gain of the SOA is greatly reduced. In this article,we report experimental data for optical injec-tion around the transparency wavelength.By using a high-power pump laser,we obtained an increase in saturation output power of3dB and a reduction in gain recovery time from more than 200ps to less than40ps,while maintaining a fiber-to-fiber gain of14dB at1555nm.To the authors’knowledge,this is the first time that such large improvements are reported while main-taining useful gain in the1550-nm wavelength band.II.E XPERIMENTAL R ESULTSThe experiments are performed on a2-mm-long polariza-tion independent bulk SOA.The maximum operation current is450mA,for which the device has a fiber-to-fiber gain of 21dB at1555nm,and a gain maximum of28dB at1510 nm.As discussed in[6],an important parameter for external pumping is the material transparency wavelength(PLEUMEEKERS et al.:ACCELERA TION OF GAIN RECOVERY IN SEMICONDUCTOR OPTICAL AMPLIFIERS13Fig.1.Pump output power spectrum for different output powers.On the x axisthe material transparency wavelengths are indicated for four different SOA biascurrents.the pump can be set in the absorption,transparency,or gain re-gion by adjusting the bias current of the SOA.The pump outputpower spectrum is shown in Fig.1for different output powers.The wavelength of the pump is around1470nm at low outputpowers and shifts to1480nm at higher output powers.From thisfigure,it is also seen that the spectral width of the pump lightincreases from around4to10nm when increasing the outputpower.The material transparency wavelength for four differentSOA bias currents is indicated in the same figure.First,we characterize the gain saturation curve of the SOA asa function of applied current and pump power.The pump poweris injected counterpropagating to the1555-nm signal power viaa1480/1550wavelength-division-multiplexing(WDM)cou-pler.The saturation curves for different pump powers are shownin Fig.2for SOA bias currents of150and450mA.The signalwavelength was set to1555nm.At150mA of SOA current,the pump is in the absorption region for output powers below80mW and approaches the material transparency wavelengthat80mW of output power,due to its output power dependentwavelength shift(cf.Fig.1).From Fig.2(a),it is seen that thesmall signal gain varies less than1dB with pump power,whichconfirms that the pump is very close to transparency.The3-dBsaturation output power is increased from5dBm byinjecting80mW of pump power.At450mA of SOA current,the pump is always in the gain region,and therefore,the smallsignal gain decreases with increasing pump power.Without thepump,the small signal gain is21dB and at80mW of pumppower it is reduced to14dB.The3-dB saturation output poweris increased from13dBm by injecting80mW ofpump power.These results confirm that optical injection canincrease the saturation output power of SOAs[4],[7]–[9],andtherefore,reduce interchannel crosstalk in WDM applications[10].However,a higher saturation output power also meansthat more input power is needed to induce a14IEEE PHOTONICS TECHNOLOGY LETTERS,VOL.14,NO.1,JANUARY2002Fig.4.(a)Streak camera measurement of the gain recovery for a SOA current of300mA with no pump input power and73mW of pump power.(b) Extracted exponential gain recovery time as a function of injected pump power for different SOA currents.In Fig.4(a),the gain recovery of the SOA is shown for a bias current of300mA.In the absence of1480-nm pump power,the signal has not yet reached its steady-state after a full period of 400ps,as indicated by the increase of the signal output power for negative times.The extracted gain recovery time is207ps without1480pump,and is reduced to39ps by injecting100 mW of pump power.Similar results were obtained for SOA bias currents of150and450mA.The extracted gain recovery times for all currents are shown in Fig.4(b).The gain recovery accel-eration saturates for higher input powers and beyond73mW,no further improvement in speed is observed.By injecting pump powers of73mW or more,the gain recovery speed was im-proved by up to a factor of five,depending on current.As ex-pected,the fastest gain recovery(27ps)was obtained at the highest SOA current.From Figs.2(b)and4(b),it is seen that at450mA of SOA current and injection of around75mW of pump power the small signal fiber-to-fiber gain is14dB,the 3-dB saturation output power is14dBm,and the gain recovery time is27ps.This type of SOA performance is very useful for high-speed all-optical signal processing applications.With the pump set close to transparency,one may expect that multiple SOAs can share the same optical pump.However,by measuring the pump output power,we find a very strong non-linear attenuation of the1480-nm pump,even at450mA of SOA current when the pump is in the gain region.At450mA,the pump output power is around16mW for input powers ranging from20to126mW.The origin of this strong nonlinear absorp-tion is not clear,but may be due to two-photon absorption[11] and prevents the pump output power from being used to pump a second SOA.In summary,we have demonstrated that optical injection of 80mW near the transparency point of SOAs can improve the 3-dB saturation output power by3dB,and the gain recovery can be accelerated by a factor of five to values as low as27ps,while maintaining a useful gain of14dB in the1550-nm wavelength band.A CKNOWLEDGMENTThe authors would like to acknowledge J.Centanni for lending the1480-nm pump laser and WDM coupler.R EFERENCES[1]J.Leuthold,B.Mikkelsen,G.Raybon,C.H.Joyner,J.L.Pleumeekers,ler,K.Dreyer,and R.E.Behringer,“All-optical wavelengthconversion between10and100gb/s with soa delayed-interference con-figuration,”Optical and Quantum Electronics,vol.33,pp.939–952, Aug.2001.[2]J.-C.Simon,P.Doussière,mouler,I.Valiente,and F.Riou,“Trav-elling wave soa with reduced nonlinear distortions,”Electron.Lett.,vol.30,pp.49–50,1994.[3]R.J.Manning and D.A.O.Davies,“Three-wavelength device for all-optical signal processing,”Opt.Lett.,vol.19,pp.889–891,1994.[4]K.Inoue and 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