ASPEN中NIST数据库的使用即物性数据查寻。

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Aspenplus化工物性数据和相平衡数据的查询与估算PPT教学课件

等； • ⑷化学反应与热化学数据，如反应热、生成热、燃烧热、反应速率常数、活化能、
化学平衡常数等； • ⑸与温度相关的传递性质，如等张比容、液体粘度、液体导热系数、表面张力、扩
散系数等。 • 混合物的物性数据往往需要在纯物质物性数据的基础上由合适的混合规则计算得到。
⑵-⑸类数据必须知道系统的温度、压力，然后通过计算(函数关系式)或插值 (列表函数)才能得到。
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1.1 化工物性数据的查询
•1 . 1 . 2 从包溶A括液S P9的E0计N0种算P离L。U子关S 化软键合件参数物数据的有库参：中数水最组查，合主分找用热要的于，的物电无纯性解限组参质分数物。性主数要据纯库组，分包数含据库18的00内种容以是上在纯 • AS稀PE释N状P态LU下S的软吉件自布带斯的生数成据自库由不称能断为，更系以新统及扩数无展据和库改，进其的中，含因有此大从量一纯个物版质本和到混下合一物的 • 物系性包的斯统数括热自限以数据大化由稀向据，约学能释上库可2数和状兼4是被据热5态容A0方，容下。个S便P关关的组E地键联N水分查数系合P（询L据数相大U、是。S热多调的焓对容数用一、于，个如起是。部熵给该版果模无分、出数本使拟机，吉的据的用结物并布一库A更果）与S可新的AP的不SEPN数同EPN据。LPU库LS进U某S行一个模起参拟同数计时值算被可，安能可装改能。变会。引
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1.2 纯物质的物性估算 • 1.2.2 与温度相关的热力学性质 • 理想气体热容：PCES用用多项式(式1-3)、Benson 方法和Joback 方法估算，温度范围280-1100K，误差< 2%; • 临界温度以下纯组分液体热容和液体焓：PCES用DIPPR、PPDS、IK-CAPE、 NIST等关联式计算； • 液体摩尔体积: PCES用带有RKTZRA参数的Rackett模型方程(式1-5)估算; • 液体蒸汽压: 数据库组分用扩展Antoine方程(式1-6)进行估算，非数据库组分采用 Riedel、Li-Ma、Mani三种方法估计； • 汽化潜热: 数据库组分用Clausius-Clapeyron 方程和Watson方程(式1-7)估算，非数据库组分用Veter e、Gan i、Du cros 、Li-Ma等化合物官能团贡献方法进行估算， Vetere 方法的平均误差为1 .6 % ，Li-Ma方法平均误差为1 .05 % 。

Aspen功能简介 (物性数据库)

Aspen Plus介绍 (物性数据库)•Aspen Plus---生产装置设计、稳态模拟和优化的大型通用流程模拟系统•Aspen Plus是大型通用流程模拟系统，源于美国能源部七十年代后期在麻省理工学院（MIT）组织的会战，开发新型第三代流程模拟软件。

该项目称为“过程工程的先进系统”(AdvancedSystem for Process Engineering，简称ASPEN）,并于1981年底完成。

1982年为了将其商品化，成立了AspenTech公司，并称之为Aspen Plus。

该软件经过20多年来不断地改进、扩充和提高，已先后推出了十多个版本，成为举世公认的标准大型流程模拟软件，应用案例数以百万计。

全球各大化工、石化、炼油等过程工业制造企业及著名的工程公司都是Aspen Plus的用户。

它以严格的机理模型和先进的技术赢得广大用户的信赖，它具有以下特性：1.ASPEN PLUS有一个公认的跟踪记录，在一个工艺过程的制造的整个生命周期中提供巨大的经济效益，制造生命周期包括从研究与开发经过工程到生产。

2.ASPEN PLUS使用最新的软件工程技术通过它的Microsoft Windows 图形界面和交互式客户-服务器模拟结构使得工程生产力最大。

3.ASPEN PLUS拥有精确模拟范围广泛的实际应用所需的工程能力，这些实际应用包括从炼油到非理想化学系统到含电解质和固体的工艺过程。

4.ASPEN PLUS是AspenTech的集成聪明制造系统技术的一个核心部分，该技术能在你公司的整个过程工程基本设施范围内捕获过程专业知识并充分利用。

5.在实际应用中，ASPEN PLUS可以帮助工程师解决快速闪蒸计算、设计一个新的工艺过程、查找一个原油加工装置的故障或者优化一个乙烯全装置的操作等工程和操作的关键问。

Aspen Plus功能Aspen Plus AspenTech工程套装软件(AES)的一个成员，它是一套非常完整产品，特别对整个工厂、企业工程流程工程实践和优化和自动化有着非常重要的促进作用。

Aspen功能简介 (物性数据库)

该项目称为“过程工程的先进系统”(AdvancedSystem for Process Engineering，简称ASPEN）,并于1981年底完成。

1982年为了将其商品化，成立了AspenTech公司，并称之为Aspen Plus。

该软件经过20多年来不断地改进、扩充和提高，已先后推出了十多个版本，成为举世公认的标准大型流程模拟软件，应用案例数以百万计。

全球各大化工、石化、炼油等过程工业制造企业及著名的工程公司都是Aspen Plus的用户。

2.ASPEN PLUS使用最新的软件工程技术通过它的Microsoft Windows 图形界面和交互式客户-服务器模拟结构使得工程生产力最大。

3.ASPEN PLUS拥有精确模拟范围广泛的实际应用所需的工程能力，这些实际应用包括从炼油到非理想化学系统到含电解质和固体的工艺过程。

4.ASPEN PLUS是AspenTech的集成聪明制造系统技术的一个核心部分，该技术能在你公司的整个过程工程基本设施范围内捕获过程专业知识并充分利用。

第三章 ASPEN PLUS的物性数据库及其应用

第 4 页
固有性质
物性
代号
物性
代号
分子量临界温度
临界压力临界体积
MW TC
PC VC
临界压缩因子偏心因子
偶极距回转半径
ZC OMEGA
MUP RGYR
第 5 页
标准态下的物性
物性生成热生成自由能沸点标准沸点下的摩尔体积汽化热凝固点相对密度代号 DHFORM DGFORM TB VB DHVLB TEP SG 物性 API重度溶解度参数等张比容气体粘度液体粘度导热系数表面张力代号 API DELTA PARC MUVDIP MULAND KVDIP SIGDIP
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3.4.1 ASPEN PLUS的物性分析功能
计算ASPEN PLUS数据库中所有的组分的热力学性质以及传递性质；生成简单的图表，验证物性模型和数据的准确性。
例3-1：采用ASPEN PLUS的理想气体方法（Ideal Gas Method）查找水在1 atm和100~500℃范围内的摩尔体积和压缩因子。
使用物性估算的步骤
1. 在Properties Molecular Structure窗口上定义分子结构。 2. 利用Parameters或Data窗体输入实验数据。
实验数据如标准沸点(TB)对于许多估算方法都是非常重要的。因此只要有可能就应该输入实验数据。
3. 在Properties Estimation Input窗口上激活 Property Estimation并选择物性估算选项。
Redlich-Kwong-Soave
Nothnagel Hayden-O Connell HF状态方程

使用aspen查物性

1.新建一个Aspen临时文件，选Template,选Blank Simulation也一样2.选择“PropertyAnalysis”3.按“N→”继续，Aspen中“N→”表示下一步，设置完当页后点这个按钮就会自动到下一页的设置页面中，以下类似4.输入标题，随便输入注意图中红色方框，是设置该aspen文档的默认单位集，默认是ENG，即英制单位，其温度是“F”，后边会讲到。

点“N→”下一步5.输入“water”或者”H2O”都可以，点回车后图片如下继续点“N→”下一步6.选择“Process type”，常用物性方法计算类型，里面是不同的物性方法分类，比如当前选择的“COMMON”为常用方法，”CHEMICAL”化学工艺计算，“ELECTROL ”为电解质计算，不同的物质计算要选择不同的物性计算方法集，当然同一种物质也可在不同物性方法集中的选择物性计算方法，不同的物性计算方法集计算出来的物性会有所区别，精确度也不一样，具体见附件本例中选择“COMMON”集即可7.然后选择计算方法“STEAMNBS”此表为水和蒸汽计算8. 继续点“N→”下一步后如图，点确定即可9.点“New”10.选“GENERIC”，普通即可11.方框内设置流量及流量表示方法和单位，有摩尔，质量，体积12.这里设置温度和压力，注意温度和压力单位，英制单位默认温度为‘F’，压力为’psia’ ,“rearly”的帖子“如何用ASPEN11.1查询物理性质”中默认为‘C’，这是因为他在第4张图片中默认单位选的METCKGCM或SI-CBAR，至于单位集可百度13.我们将压力设置为一个大气压，选择温度为变化量14.选中“Temperature”,点击“Range/List”选择结果列表方式在“rearly”的帖子“如何用ASPEN11.1查询物理性质”中，他设置的”Lower”为10，很多海友反应计算结果报错，这就是开头第4项默认单位选择的问题，英制中温度单位为“F”，10F=-12℃，这时候的水已经成冰了，就不是计算方法“STEAMNBS”水和蒸汽计算范围了，所以会报错，故最低应设成32以上15.选中“HXDESIGN”点“>”右移，HXDESIGN是计算热交换为主，下面计算密度，热容等等，可参考下面的英文解释16.选择完成后不要点“N→”下一步，这里还有一个定义你想查询的物性，这个是可选的点击左边树形图，选择方框所示MASSVFRA：混合物的气相分率MASSFLMX:混合物的质量流率HMX:混合物的焓RHOMX:混合物的密度CPMX:混合物的恒压热容PCMX：混合物临界状态下的临界压力MUMX：混合物粘度KMX：混合物的导热系数SIGMAMX:表面张力MWMX：混合物分子量单位可根据个人习惯选择，物性可右键删除17.一路确定计算完毕，点击上图中红色方框内图标查看计算结果18.点击左边树状图方框内文件夹图标，最后得到计算结果如下可见变量“TEMP”变量中温度单位为’F’，点击改成“C”后就是我们熟悉的摄氏度了。

Aspen中NIST使用方法

NIST ThermoData EngineUse this dialog box to estimate pure component parameters using the NIST Thermo Data Engine (TDE), or retrieve binary parameters from NIST. If at least two components are defined, you can choose at the top to evaluate either pure properties or binary mixture properties.If you choose databank component(s) or one(s) which have already had their structural formula specified, you can click Evaluate Now to run TDE to estimate properties immediately.If you choose a user-defined component, you can click Enter Additional Data to open the User-Defined Component Wizard for that component. Once you have specified the structural formula and optional additional data, you will be able to run TDE from within the wizard.TDE takes a few minutes to run. When it finishes running, the TDE Pure Results or TDE Binary Results window will appear with the results of the estimation.See AlsoUsing the NIST Thermo Data Engine (TDE)User-Defined Component WizardUsing the NIST Thermo Data Engine (TDE)You can use the ThermoData Engine (TDE) from the National Institute of Standards and Technology (NIST) to estimate property parameters for any component or pair of components given one of the following for each component:∙CAS number∙Molecular structure. TDE can only use molecular structure saved in an MDL file (*.mol) or specified using the drawing tool in the User Defined Component Wizard. It cannot use molecular structurespecified by atom and connectivity.Note: Only MDL files of version V2000 are supported. The version V3000 files, sometimes called Extended MDL files, are not supported.TDE has a variety of group contribution methods available to estimate pure component property parameters based on molecular structure. Based on TDE's large database of experimental data, these methods have been rankedfor which data is available is To run TDE:1.Specify the component(s) on the Components | Specifications |Selection sheet.2.On the Home tab of the ribbon, in the Data Source group, click NIST.The NIST ThermoData Engine dialog box appears.3.Choose Pure or Binary mixture.4.Select the component from the list in the dialog box. For binarymixture properties select a component from the second list as well.5.If the CAS number or molecular structure is specified for eachcomponent, then the Evaluate Now button (for pure componentproperties) or Retrieve Data button (for binary mixture properties) is enabled. Click it to estimate property parameters.ORFor pure component parameters, if neither CAS number nor molecular structure is specified, click Enter Additional Data. The UserDefined Component Wizard appears, allowing you to specify themolecular structure and optionally other data about the component.You will be given the option to run TDE to estimate parameters after specifying data.The following data can be sent to TDE:∙Vapor pressure data∙Liquid density∙Ideal gas heat capacity∙Normal boiling point∙Molecular structure (if specified using a version V2000 MDL file or using the drawing tool in the User Defined Component Wizard) Note: TDE takes a couple minutes to run on a typical computer.6.When TDE is finished, the results will appear in the TDE Pure windowor the TDE Binary window.See AlsoAbout the NIST ThermoData Engine (TDE)User Defined Component WizardNIST TDE Data Evaluation MethodologyNIST TDE vs. NIST-TRC DatabankUsing TDE ResultsAbout the NIST ThermoData Engine (TDE)The ThermoData Engine (TDE) is a thermodynamic data correlation, evaluation, and prediction tool provided with Aspen Plus and Aspen Properties through a long-term collaboration agreement with the National Institute of Standards and Technology (NIST).The purpose of the ThermoData Engine software is to provide critically evaluated thermodynamic and transport property data based on the principles of dynamic data evaluation.Critical evaluation is based on:∙Published experimental data stored in a program database∙Predicted values based on molecular structure andcorresponding-states methods∙User supplied data, if anyThe primary focus of the current version is pure organic compounds comprised of the elements: C, H, N, O, F, Cl, Br, I, S, and P. The principles upon which the ThermoData Engine software are based are fully discussed in two articles.1,2 The first article describes the foundations of TDE while the second describes the extension of TDE for dynamicequation-of-state evaluation and online updating. Online updating is not available in Aspen Plus.ThermoData Engine is the first software fully implementing all major principles of the concept of dynamic data evaluation formulated at NIST Thermodynamic Research Center (TRC). This concept requires thedevelopment of large electronic databases capable of storing essentially all raw experimental data known to date with detailed descriptions of relevant metadata and uncertainties. The combination of these databases with expert software designed primarily to generate recommended data based on available raw experimental data and their uncertainties leads to the possibility of producing data compilations automatically to order, forming a dynamic data infrastructure. The NIST TRC SOURCE data archival system currently containing more than 3 million experimental data points is used in conjunction with ThermoData Engine as a comprehensive storage facility for experimental thermophysical and thermochemical property data. The SOURCE database is continually updated and is the source for the experimental database used with TDE.The ThermoData Engine software incorporates all major stages of the concept implementation, including data retrieval, grouping, normalization, sorting, consistency enforcement, fitting, and prediction. The ThermoData Engine emphasizes enforcement of consistency between related properties (including those obtained from predictions), and incorporates a large variety of models for fitting properties. Predicted values are provided using the following set of Prediction MethodsThe experimental database containing raw property data for a very large number of components (over 17,000 compounds) is included automatically with Aspen Plus/Aspen Properties. Results of the TDE evaluations –model parameters – can be saved to the Aspen Plus simulation and used in process calculations. Experimental data can also be saved to the simulation and used with the Aspen Plus Data Regression System, if needed, for example, to fit other property models, or to fit data over limited temperature ranges that correspond to the process conditions of interest.Note:AspenTech has provided the regression results for much of this data in the NIST-TRC databank. You can use this databank to gain most of the advantage of NIST without spending the time to run TDE dynamically. The models linked below (used in many property methods) provide access to these properties when the NIST-TRC databank is used. See NIST TDE vs. NIST-TRC Databank for more information.Note: NIST TDE is a complementary technology of the existing Property Estimation System of Aspen Plus. The two features work independently of each other and will co-exist. However, we anticipate that TDE will continue to be enhanced with additional raw data and new or improved estimation methods and will be used in preference to the Property Estimation System in the future.The Aspen Plus - TDE interface covers the following properties of pure molecular compounds. Most of them can be estimated for new compounds based on molecular structure, using the methods listed below. Where multiple methods are listed for a property, they are ranked for accuracy for each compound class based on the data in the experimental database, and the highest-ranked one for the given structure is automatically selected.Single-Valued PropertiesTemperature-Dependent PropertiesReferences1.ThermoData Engine (TDE): Software Implementation of the DynamicData Evaluation Concept, J. Chem. Inf. Model., 45 (4), 816 -838, 2005. /TDEarticle.pdf2.ThermoData Engine (TDE): Software Implementation of the DynamicData Evaluation Concept. 2. Equations of State on Demand and Dynamic Updates over the Web, J. Chem. Inf. Model., 47, 1713-1754, 2007./TDEarticle2.pdf3.K. G. Joback, R. C. Reid. Estimation of Pure-Component Propertiesfrom Group-Contributions. Chem. Eng. Comm. 1987, 57, 233-243.4.L. Constantinou, R. Gani. New Group-Contribution Method forEstimating Properties of Pure Compounds. AIChE J. 1994, 40,1697-1710.5.J. Marrero-Morejon, E. Pardillo-Fontdevila. Estimation of PureCompound Properties Using Group-Interaction Contributions. AIChE J. 1999, 45, 615-621.6.G. M. Wilson, L. V. Jasperson. Critical Constants T c, P c. EstimationBased on Zero, First, Second-Order Methods. AIChE Meeting, NewOrleans, LA, 1996.7. D. Ambrose, J. Walton. Vapor-Pressures up to TheirCritical-Temperatures of Normal Alkanes and Alkanols. Pure Appl.Chem. 1989, 61, 1395-1403.8.T. Yamada, R. D. Gunn. Saturated Liquid Molar Volumes. The RackettEquation. J. Chem. Eng. Data 1973, 18, 234-236.9.L. Riedel. Chem.-Ing.-Tech. 1954, 26, 259-264. As modified in: J.L. Hales, R. Townsend. J. Chem. Thermodyn. 1972, 4, 763-772.10.B. E. Poling, J. M. Prausnitz, J. P. O'Connell. The Properties ofGases and Liquids, 5th ed.; McGraw-Hill: New York, 2001.11.S. R. S. Sastri, K. K. Rao. A New Group Contribution Method forPredicting Viscosity of Organic Liquids. Chem. Eng. J. Bio. Eng.J. 1992, 50, 9-25.12.T. H. Chung, M. Ajlan, L. L. Lee, K. E. Starling, GeneralizedMultiparameter Correlation for Nonpolar and Polar FluidTransport-Properties. Ind. Eng. Chem. Res. 1988, 27, 671-679.13.B. E. Poling, J. M. Prausnitz, J. P. O'Connell. The properties ofGases and Liquids, 5th ed.; McGraw-Hill: New York, 2001 (page 9.9 for low-pressure gas and page 9.35 Lucas model for high-pressure).14.T. H. Chung, L. L. Lee, K. E. Starling. Applications of Kinetic GasTheories and Multiparameter Correlation for Prediction of Dilute Gas Viscosity and Thermal-Conductivity. Ind. Eng. Chem. Fund.1984, 23, 8-13.See AlsoNIST TDE vs. NIST-TRC DatabankUsing the NIST ThermoData EngineNIST TDE Data EvaluationNIST TDE Data Evaluation MethodologyThe NIST ThermoData Engine (TDE) uses dynamic data evaluation to determine the data to be used in regressing property parameters from the collected raw experimental data in NIST's database. The data evaluation is broken into several phases.The data are broken into four blocks:∙Phase diagram: triple point, critical temperature, phase boundary pressure∙Volumetric: critical density, saturated & single phase density, volumetric coefficients∙Energetic: energy differences, energy derivatives, speed of sound ∙Other: transport properties, surface tension, refractionThe blocks are first processed individually. The following thermodynamic consistency tests are performed within the phase diagram, volumetric, and energetic data:∙Vapor pressures of phases must be equal at triple points, and slope/enthalpy change must be consistent∙Condensed phase boundaries must converge to the triple point∙Gas and liquid saturation density curves must converge at the critical temperature∙First derivative of saturated density must trend toward infinity at the critical temperature∙Single-phase densities must converge to saturated densitiesThen, the vapor pressure, saturated density, and enthalpy of vaporization are checked for consistency, and the other data is processed.See AlsoAbout the NIST ThermoData Engine (TDE)NIST TDE vs. NIST-TRC DatabankIn addition to the raw property data available with NIST TDE, the Aspen Physical Property System includes the NIST-TRC databank, which contains parameters regressed with TDE for compounds for which a significant amount of data was available. NIST-TRC and associated property models available in Aspen Plus provide all that most users need to use property data from NIST in their simulations.NIST TDE provides additional capabilities for users who need them: ∙You can perform dynamic data evaluation using the raw property database delivered with Aspen Physical Property System.∙You can trace back to the original data sources.∙You can save the data into Aspen Plus to perform additional data regressions beyond those automated by TDE, such as fitting to a different property model or fitting data over a differenttemperature range which corresponds to the process conditions of interest.Note: The NIST-TRC databank is only available when using the Aspen Properties Enterprise Database. Starting in version V7.0, Aspen Plus and Aspen Properties are configured to use the enterprise database when installed.Using TDE ResultsPure component resultsOn the left side of the TDE Pure Results window under Properties for component ID is a list of the property parameters available, with All at the top. Selecting All displays a summary of the parameter results. For T-dependent parameters, a + is displayed; you can click this to open the display of the estimated values for each element of these parameters.Selecting any parameter displays details about that parameter on a multi-tab display, including any experimental data and estimated property values. In the display of experimental data, one column indicates which data points were used in regression and which were rejected as outliers.With the Experimental Data, Predicted Values, or Evaluated Results tab of any T-dependent parameter open, in the Home tab of the ribbon, in the Plot group, you can click Prop-T in the ribbon to generate a plot of that data vs. temperature. The plot displays all available experimental data and predicted values along with the curve of evaluated values.If you want to save this data as part of your simulation, you must click Save Parameters to save it on Parameters and Data forms. See Saving data to forms, below.Binary mixture resultsOn the left side of the TDE Binary Results window is a list of the property parameters available, with Data for ID(1) and ID(2)at the top. Clicking Data for ID(1) and ID(2) displays a summary of the parameter results. The retrieved parameters appear in a tree at the left; selecting categories in the tree displays a summary of the data available under that category. Selecting the individual numbered results displays the experimental data. Double-clicking a row in any of the summary views also displays its experimental data.With any experimental data set open, in the Home tab of the ribbon, the Plot group displays buttons for ways you can plot that data.If you want to save this data as part of your simulation, you must click Save Data to save it on Data forms. See Saving data to forms, below.Once you have saved some results to forms, you can click Data Regression to create a data regression case with this data. See NIST TDE Data Evaluation/Regression.Click the Consistency Test tab to run consistency tests on the VLE data. See NIST TDE VLE Consistency Test for details.Saving results to formsClick Save Parameters or Save Dava to save any of the pure component TDE results and most categories of pure component or binary experimental data in forms in your current Aspen Plus or Aspen Properties run. A dialog box appears, allowing you to select which parameters you want to save data for. For pure component experimental data, a checkbox (selected by default) lets you specify to save only accepted data; if this is selected then experimental data points which were rejected by TDE are not saved to forms. For binary data, a checkbox allows you to save both the data and its uncertainty. The data is saved to:∙Methods | Parameters | Pure Component| TDE-1 form (scalar parameter values)∙Methods | Parameters | Pure Component|Parameter Name forms (T-dependent parameter values)∙Data | Pure-Comp forms (pure component experimental data)∙Data | Mixture forms (binary experimental data)Note: TDE results are only saved if you use Save Data. Otherwise, they are discarded when you close the window. Values are saved in SI units. These are treated as user-entered parameters.See AlsoNIST TDE Data Evaluation。

使用aspen查物性(精)

点“N→”下一步5.输入“water”或者”H2O”都可以，点回车后图片如下继续点“N→”下一步6.选择“Process type”，常用物性方法计算类型，里面是不同的物性方法分类，比如当前选择的“COMMON”为常用方法，”CHEMICAL”化学工艺计算，“ELECTROL ”为电解质计算，不同的物质计算要选择不同的物性计算方法集，当然同一种物质也可在不同物性方法集中的选择物性计算方法，不同的物性计算方法集计算出来的物性会有所区别，精确度也不一样，具体见附件本例中选择“COMMON”集即可7.然后选择计算方法“STEAMNBS”此表为水和蒸汽计算8. 继续点“N→”下一步后如图，点确定即可9.点“New”10.选“GENERIC”，普通即可11.方框内设置流量及流量表示方法和单位，有摩尔，质量，体积12.这里设置温度和压力，注意温度和压力单位，英制单位默认温度为…F‟，压力为‟psia‟ ,“rearly”的帖子“如何用ASPEN11.1查询物理性质”中默认为…C‟，这是因为他在第4张图片中默认单位选的METCKGCM或SI-CBAR，至于单位集可百度13.我们将压力设置为一个大气压，选择温度为变化量14.选中“Temperature”,点击“Range/List”选择结果列表方式在“rearly”的帖子“如何用ASPEN11.1查询物理性质”中，他设置的”Lower”为10，很多海友反应计算结果报错，这就是开头第4项默认单位选择的问题，英制中温度单位为“F”，10F=-12℃，这时候的水已经成冰了，就不是计算方法“STEAMNBS”水和蒸汽计算范围了，所以会报错，故最低应设成32以上15.选中“HXDESIGN”点“>”右移，HXDESIGN是计算热交换为主，下面计算密度，热容等等，可参考下面的英文解释16.选择完成后不要点“N→”下一步，这里还有一个定义你想查询的物性，这个是可选的点击左边树形图，选择方框所示MASSVFRA：混合物的气相分率MASSFLMX:混合物的质量流率HMX:混合物的焓RHOMX:混合物的密度CPMX:混合物的恒压热容PCMX：混合物临界状态下的临界压力MUMX：混合物粘度KMX：混合物的导热系数SIGMAMX:表面张力MWMX：混合物分子量单位可根据个人习惯选择，物性可右键删除17.一路确定计算完毕，点击上图中红色方框内图标查看计算结果18.点击左边树状图方框内文件夹图标，最后得到计算结果如下可见变量“TEMP”变量中温度单位为‟F‟，点击改成“C”后就是我们熟悉的摄氏度了。

ASPEN ONE 2006中直接查看数据库中的物质物性

1、我们在2006种可以这样Aspen Tech---Aspen Engineering Sutie ----Aspen Plus 2006---aspen
Properties Database Selector
2、稍等片刻会出现下图选择第一个，点击OK后该窗口自动关闭
5、接着我们这样Aspen Tech---Aspen Engineering Sutie ----Aspen Plus 2006---aspen Properties Database Manager
6、会出现下面的对话框，我们单击OK
7、可能会出现下面的情况，不管它继续单击OK
8、我们继续单击OK
9、这个时候会出现线面这个对话框，看到了吗？数据库NIST06种有15396种物质。

10、点击上图左栏中的NIST06----Selected---Compounds---- Find Compounds 弹出
11、在上面的对话框中选择选择你要查看的物质，单击Add selected compound，然后关闭
12、然后点击左栏周Ddatabanks----NIST-TRC ---Pure，在View中分别选择all，单击右边的Compare就会出现下图；这个就是物性。

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ASPEN中NIST数据库的使用
ASPEN中的NIST数据库可以查询二元物性参数，也可以查询纯物质参数，二院物性参数的查询论Step1 输入组分
Step2 选择物性方法
Step3 执行物性估算
Step4 点击NIST
Step5 选择pure，二元估算选择Binary mixture
Step6 点击evaluate NOW
Step7 查看结果，图中TPT即为苯的三相点
所查寻的数据英文可以一起全部复制和百度翻译。

数据库
step1
step2
step4
Step5
Step7
Name Description OMEGA Pitzer acentric factor
ZC Critical compressibility factor VC Critical volume
TC Critical temperature
DNLEXSAT TDE expansion for liquid molar density
MUP Dipole moment
HFUS Heat of fusion
DHVLTDEW TDE Watson equation for heat of vaporization DGFORM Gibbs energy of formation (ideal gas)
CPSTMLPO ThermoML polynomials for solid Cp
CPIALEE TDE Aly-Lee ideal gas Cp
CPLTMLPO ThermoML polynomials for liquid Cp
DHFORM Heat of formation (ideal gas)
MW Molecular weight
TB Normal boiling point
FREEZEPT Freeze point temperature
DELTA Solubility parameter @ 25 C
SG Specific gravity
VLSTD API standard liquid molar volume
SIGTDEW TDE Watson equation for liquid-gas surface tension KVTMLPO ThermoML polynomials for vapor thermal conductivity KLTMLPO ThermoML polynomials for liquid thermal conductivity TPT Triple point temperature
PSTDEPOL TDE polynomials for solid vapor pressure
WAGNER25 TDE Wagner 25 liquid vapor pressure
MUVTMLPO ThermoML polynomials for vapor viscosity
MULNVE TDE equation for liquid viscosity
FAMILY Compound family name
SUB FAMILY Compound sub family name
OMEGA Pitzer acentric factor
欧米茄Pitzer偏心因子
ZC Critical compressibility factor
ZC临界压缩因子
VC Critical volume
VC临界体积
TC Critical temperature
超导临界温度
DNLEXSAT TDE expansion for liquid molar density
液体的摩尔密度dnlexsat TDE膨胀
MUP Dipole moment
MUP的偶极矩
HFUS Heat of fusion
超声热融合
DHVLTDEW TDE Watson equation for heat of vaporization dhvltdew TDE沃森方程的汽化热
DGFORM Gibbs energy of formation (ideal gas)
dgform生成吉布斯能（理想气体）
CPSTMLPO ThermoML polynomials for solid Cp
cpstmlpo ThermoML的多项式的固态CP
CPIALEE TDE Aly-Lee ideal gas Cp
cpialee TDE阿里李理想气体的CP
CPLTMLPO ThermoML polynomials for liquid Cp
cpltmlpo ThermoML液体CP多项式
DHFORM Heat of formation (ideal gas)
形成DhForm热（理想气体）
MW Molecular weight
MW分子量
TB Normal boiling point
结核病的正常沸点
FREEZEPT Freeze point temperature
freezept冻结点温度
DELTA Solubility parameter @ 25 C
三角洲“25 C的溶解度参数
SG Specific gravity
比重
VLSTD API standard liquid molar volume
vlstd API标准液的摩尔体积
SIGTDEW TDE Watson equation for liquid-gas surface tension sigtdew TDE沃森方程的液-气表面张力
KVTMLPO ThermoML polynomials for vapor thermal conductivity kvtmlpo ThermoML的多项式的蒸气导热系数
KLTMLPO ThermoML polynomials for liquid thermal conductivity
kltmlpo ThermoML的多项式液体导热系数
TPT Triple point temperature
TPT三相点温度
PSTDEPOL TDE polynomials for solid vapor pressure pstdepol TDE多项式的固体的蒸气压
WAGNER25 TDE Wagner 25 liquid vapor pressure wagner25 TDE瓦格纳25液体的蒸气压
MUVTMLPO ThermoML polynomials for vapor viscosity muvtmlpo ThermoML的多项式的气相粘度
MULNVE TDE equation for liquid viscosity
液体的粘度mulnve TDE方程
FAMILY Compound family name
族化合物的姓
SUB FAMILY Compound sub family name
亚族化合物亚家族的名字。