Nanjing Tech University
毕业设计英文资料翻译
Translation of the English Documents for Graduation Design
原文：
ACQUISITION OF BUILDING GEOMETRYIN THE SIMULATION OF ENERGY PERFORMANCE
ABSTRACT
Building geometry is essential to any simulation of building performance.This paper examines the importing of building geometry into simulation of energy performance from the usersrsquo; point of view. It lists performance requirements for graphic user interfaces that input building geometry, and discusses the basic options in moving from two-to three-dimensional definition of geometry and the ways to import that geometry into energy simulation. The obvious answer lies in software interoperability. With the BLIS group of interoperable software one can interactively import building geometry from CAD into EnergyPlus and dramatically reduce the effort otherwise needed for manual input.
The resulting savings may greatly increase the value obtained from simulation, the number of projects in which energy performance simulation is used, and expedite decision making in the design process.
INTRODUCTION
The current standard practice in preparing energy simulation input typically involves repetitive manual operation that in essence amounts to duplication of already existing data. The process is error-prone and the resulting simulation input code is difficult to debug.As the complexity of the building and the simulation increase, input preparation becomes more and more the main catalyst for abandoning (or not even starting) the simulation project.
The largest portion of the effort to prepare simulation input is absorbed by the definition of building geometry. Because few buildings are defined as a true 3-D model, the complete set of information needed to define the building geometry is usually distributed over a large number of 2-D drawings; this requires a substantial effort to comprehend and extract all the pertinent information.
Most architects and engineers depend on the use of some“mission-critical” software in their work.To execute, such software typically requires information about the buildingrsquo;s geometry. In the course of design of a building, building geometry may get recreated as much as seven or eight times or more: Structural, mechanical and electrical engineering, as well as plumbing, energy performance calculation, lighting, code checking and cost estimating software all depend on building geometry information to do their work. In most cases building geometry is completely regenerated because one cannot import the needed definitions directly from CAD files that contain the original information.
When budgeting for building energy performance simulation, one can use the rule of thumb that says that the cost of input preparation and the cost of analysis of results should be approximately the same; relative to these, the cost of simulation runs (i.e., computer run management and computer time) is minimal today.
Simply observing the preparation of different energy performance simulation inputs and runs reveals the typical distribution of effort and resources. Most of the effort in the preparation of simulation input is in getting the first successful run.The process that consists of input definition, debugging, and computer runs and analysis of results is repetitive and based on feedback; it often takes many iterations before the result is satisfactory. Subsequent additions and modifications to simulation input that may be needed for parametric runs require comparatively little effort.In the case of building energy performance simulation, up to 80% of the effort in input preparation may be consumed on the definition of building geometry .By definition, most of the building geometry must be defined for the first successful run.The actual distribution of effort varies greatly from building to building for several reasons: It depends on the complexity and size of the building and its geometry, on the purpose and goals of the simulation, on the expertise and experience of those who are setting up the simulation and preparing the input, on the computer aids that are used in the process, on the schedule and budget, and on several other factors that may affect the case.
Manual input of building geometry and debugging require continuous high level of concentration and consistency. It is a tedious process that can result in frustration. It tempts one to resort to“approximation of convenience” to “get something running” sooner; that can cause very serious difficulties later and possibly compromise the entire simulation effort.
In reality, the simulation of building energy/thermal performance is often not used the way simulation is supposed to work in its classical sense: to perform multiple experiments and rely on statistical analysis of results to determine meaningful future outcomes [Naylor et al. 1966]. All too often the investigation of alternatives is limited to one or only a few simulation runs and the results are accepted as definitive answers. Many factors are responsible for that; one can argue that the effort and cost of acquisition of building geometry and the associated high cost of simulation input preparation play a prominent role.
Those who prepare input and use simulation models often dream of tools that could automatically import building geometry. While the completely automatic acquisition may never be achieved, it is now possible to partially automate the process and significantly reduce the effort and its c
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Nanjing Tech University
毕业设计英文资料翻译
Translation of the English Documents for Graduation Design
学生姓名： 周聪
学 号： 1715160127
所在学院： 艺术设计学院
专 业： 环境设计
指导老师: 张安华
2020年 1 月 1日
原文：
ACQUISITION OF BUILDING GEOMETRYIN THE SIMULATION OF ENERGY PERFORMANCE
ABSTRACT
Building geometry is essential to any simulation of building performance.This paper examines the importing of building geometry into simulation of energy performance from the usersrsquo; point of view. It lists performance requirements for graphic user interfaces that input building geometry, and discusses the basic options in moving from two-to three-dimensional definition of geometry and the ways to import that geometry into energy simulation. The obvious answer lies in software interoperability. With the BLIS group of interoperable software one can interactively import building geometry from CAD into EnergyPlus and dramatically reduce the effort otherwise needed for manual input.
The resulting savings may greatly increase the value obtained from simulation, the number of projects in which energy performance simulation is used, and expedite decision making in the design process.
INTRODUCTION
The current standard practice in preparing energy simulation input typically involves repetitive manual operation that in essence amounts to duplication of already existing data. The process is error-prone and the resulting simulation input code is difficult to debug.As the complexity of the building and the simulation increase, input preparation becomes more and more the main catalyst for abandoning (or not even starting) the simulation project.
The largest portion of the effort to prepare simulation input is absorbed by the definition of building geometry. Because few buildings are defined as a true 3-D model, the complete set of information needed to define the building geometry is usually distributed over a large number of 2-D drawings; this requires a substantial effort to comprehend and extract all the pertinent information.
Most architects and engineers depend on the use of some“mission-critical” software in their work.To execute, such software typically requires information about the buildingrsquo;s geometry. In the course of design of a building, building geometry may get recreated as much as seven or eight times or more: Structural, mechanical and electrical engineering, as well as plumbing, energy performance calculation, lighting, code checking and cost estimating software all depend on building geometry information to do their work. In most cases building geometry is completely regenerated because one cannot import the needed definitions directly from CAD files that contain the original information.
When budgeting for building energy performance simulation, one can use the rule of thumb that says that the cost of input preparation and the cost of analysis of results should be approximately the same; relative to these, the cost of simulation runs (i.e., computer run management and computer time) is minimal today.
Simply observing the preparation of different energy performance simulation inputs and runs reveals the typical distribution of effort and resources. Most of the effort in the preparation of simulation input is in getting the first successful run.The process that consists of input definition, debugging, and computer runs and analysis of results is repetitive and based on feedback; it often takes many iterations before the result is satisfactory. Subsequent additions and modifications to simulation input that may be needed for parametric runs require comparatively little effort.In the case of building energy performance simulation, up to 80% of the effort in input preparation may be consumed on the definition of building geometry .By definition, most of the building geometry must be defined for the first successful run.The actual distribution of effort varies greatly from building to building for several reasons: It depends on the complexity and size of the building and its geometry, on the purpose and goals of the simulation, on the expertise and experience of those who are setting up the simulation and preparing the input, on the computer aids that are used in the process, on the schedule and budget, and on several other factors that may affect the case.
Manual input of building geometry and debugging require continuous high level of concentration and consistency. It is a tedious process that can result in frustration. It tempts one to resort to“approximation of convenience” to “get something running” sooner; that can cause very serious difficulties later and possibly compromise the entire simulation effort.
In reality, the simulation of building energy/thermal performance is often not used the way simulation is supposed to work in its classical sense: to perform multiple experiments and rely on statistical analysis of results to determine meaningful future outcomes [Naylor et al. 1966]. All too often the investigation of alternatives is limited to one or only a few simulation runs and the results are accepted as definitive answers. Many factors are responsible for that; one can argue that the effort and cost of acquisition of building geometry and the associated high cost of simulation input preparation play a prominent role.
Those who prepare input and use simulation models often dream of tools that could automatically import building geometry. While the completely automatic acquisition may never be achieved, it is now possible to partially automate the process and significantly reduce the effort and its c
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