Simulation Model for High Efficiency of Solar Cells
高层建筑供热管道支架受力数值模拟方法仿真
第37卷第12期计算机仿真2020年12月文章编号：1006 - 9348 (2020)12 - 0409 - 05高层建筑供热管道支架受力数值模拟方法仿真孙守江，邵宗义(北京建筑大学环境与能源工程学院，北京1〇_)摘要:为了使供热管道能够更加安全稳固，提出一种高层建筑供热管道支架受力数值模拟方法。
通过马斯顿土压力思想分 析供热管道在运作时，管道支架的横向压缩反力与轴向摩擦力，根据管道支架的受力状态将掩护支架与顶端支架作为隔离 体，获取供热管道支架的前连杆受力状态，通过管道支架有限元分析，得到不同因素对管道支架受力变形的干扰，计算供热 管道的间距与特征向量，采用主成分分析法将特征向量与间距之间的关联变量，转变成一种没有关联的变量，将所有因素的 关联性问题简易化，进而完成对供热管道支架受力的数值模拟。
仿真结果证明，所提方法能够对供热管道支架的受力情况进行更为精准的数值模拟，且模拟的效率较高。
关键词：数值模拟;支架受力；主成分分析;有限元法中图分类号:TP393 文献标识码：BSimulation of Numerical Simulation Methodfor Heat Supply Pipe Support of High - Rise BuildingSUN Shou - jiang，SHAO Zong -y i(S c h o o l o f E n v i r o n m e n t a l and Energy E n g i n e e r i n g,B e i j i n g J i a n z h u U n i v e r s i t y,B e i j i n g 100044, China)A B S T R A C T：I n o r d e r t o make t h e h e a t- s u p p l y p i p e l i n e more s t a b l e,a method t o n u m e r i c a l l y s i m u l a t e t h e f o r c e o fh e a t- s u p p l y p i p e l i n e s u p p o r t i n h i g h- r i s e b u i l d i n g s was p u t f o r w a r d.Based on t h e i d e a o f Ma rs to n’s s o i l p r e s s u r e，t h e r e a c t i v e f o r c e o f t r a n s v e r s e c o m p r e s s i o n and a x i a l f r i c t i o n f o r c e o f t h e p i p e s u p p o r t w e re a n a l y z e d when t h e h e a t- s u p p l y p i p e l i n e was i n o p e r a t i o n.Ac co r d i n g t o t h e s t r e s s o f p i p e su p p o r t,t h e s h i e l d s u p p o r t and t h e t o p s u p p o r t w e r e t a k e n a s t h e i s o l a t e d body t o o b t a i n t h e s t r e s s o f t h e f r o n t c o n n e c t i n g r o d o f h e a t- s u p p l y p i p e s u p p o r t.Based on t h ef i n i t e e l e m e n t a n a l y s i s f o r p i p e s u p p o r t,t h e i n t e r f e r e n c e o f d i f f e r e n t f a c t o r s on t h e s t r e s s and d e f o r m a t i o n o f p i p e supp o r t was o b t a i n e d.Moreover,t h e d i s t a n c e be t w e e n h e a t- s u p p l y p i p e l i n e s and t h e e i g e n v e c t o r s were c a l c u l a t e d.F u rth er m o r e,t h e c o r r e l a t i o n v a r i a b l e be tw ee n e i g e n v e c t o r and d i s t a n c e was t r a n s f o r m e d i n t o a k i n d o f u n r e l a t e d v a r i a b l eb y p r i nc i p a l component a n a l y s i s.F i n a l l y,t h e c o r r e l a t i o n o f a l l f a c t o r s was s i m p l i f i e d,s o t h a t t h e n u m e r i c a l s i m u l at i o n was co mp le te d.The s i m u l a t i o n r e s u l t s show t h a t t h e p r o p o s e d method h a s more a c c u r a t e n u m e r i c a l s i m u l a t i o n f o rh e a t- s u p p l y p i p e l i n e s u p p o r t,and t h e s i m u l a t i o n e f f i c i e n c y i s h i g h e r.K E Y W O R D S：N u m e r i c a l s i m u l a t i o n；S u p p o r t load；P r i n c i p a l component a n a l y s i s；F i n i t e e l e m e n t methodi引言在城市发展与规划内，架空敷设因为不会受到地下水位、土质与其他管线的干扰,因此使其得到了快速的发展，而 架空敷设中最为常见的就是高层建筑的管道，因其构造简 单、维修方便，使其变成了一种较为经济的敷设方式,而在遇 到供热区域地形复杂的情况时，就需要对供热管道提供支架，使其不会出现管道连接破损的情况[1]。
基于离散位错动力学的铜晶体材料力学特性研究
摘要近年来，随着航空航天、精密机械等产业的迅猛发展，对微机电系统需求量大幅增加，同时也对微机电系统提出了更高的性能要求。
铜晶体材料被广泛应用在微机电系统中作为基本构件，其尺寸在微米及亚微米尺度。
在该尺度下铜晶体表现出与尺度相关的力学特性，无法使用传统宏观力学进行解释。
因此，为了提高微机电系统性能及可靠度，迫切需要对小尺度铜晶体材料的力学性能开展研究，研究其与尺度相关的力学特性，为微机电系统的设计提供理论及实验基础。
针对小尺度下的材料仿真，离散位错动力学方法在拥有很高计算效率的同时，能分析晶体内部位错运动行为，是一种有效的介观尺度研究方法。
然而，针对小尺度材料测试中常用的微拉伸、纳米压痕两种实验方法，在离散位错动力学层面上对其研究并不完备。
本文中使用自主开发的离散位错动力学软件对这两种典型实验条件进行研究，对进一步了解小尺度铜晶体材料塑性力学特性的内在机理具有积极意义。
本文首先基于2.5D离散位错动力学框架，结合ABAQUS软件的接触算法，使用MATLAB软件及PYTHON语言开发了小尺度下铜晶体离散位错动力学-有限元耦合计算程序。
在该程序的基础上，开发相应的位错初始化模块、云图、曲线后处理模块。
在自主开发的铜晶体单向拉伸离散位错动力学-有限元耦合计算程序的基础上，建立了铜晶体单向拉伸有限元模型。
通过耦合计算，本文分析了铜晶体单向拉伸中的应力分布及内部位错运动机理。
针对铜晶体厚度、取向两方面分别展开研究，揭示了影响铜晶体单向拉伸性能的内在机理。
建立了铜晶体纳米压痕仿真模型，得到了纳米压痕过程中位错行为规律及压痕力-位移曲线。
明确了纳米压痕力-位移曲线与位错增殖速度及平均间距两个因素间的联系，并从位错源密度、初始位错密度两个方面研究其对纳米压痕结果的影响方式。
最后，本文对单晶铜进行纳米压痕实验，得到了单晶铜的力-位移数据。
使用扫描电子显微镜分析压痕周围的表面形貌，使用透射电子显微镜分析压痕周围位错线的分布规律，通过高分辨率透射电镜在原子堆垛层面上观察位错的具体状态，验证了仿真结果的正确性。
仿真算法知识点总结
仿真算法知识点总结一、简介仿真算法是一种通过生成模型和运行模拟来研究系统或过程的方法。
它是一种用计算机模拟真实世界事件的技术，可以用来解决各种问题，包括工程、商业和科学领域的问题。
仿真算法可以帮助研究人员更好地理解系统的行为，并预测系统未来的发展趋势。
本文将对仿真算法的基本原理、常用技术和应用领域进行总结，以期帮助读者更好地了解和应用仿真算法。
二、基本原理1. 离散事件仿真（DES）离散事件仿真是一种基于离散时间系统的仿真技术。
在离散事件仿真中，系统中的事件和状态都是离散的，而时间是连续变化的。
离散事件仿真通常用于建模和分析复杂系统，例如生产线、通信网络和交通系统等。
离散事件仿真模型可以用于分析系统的性能、验证系统的设计和决策支持等方面。
2. 连续仿真（CS）连续仿真是一种基于连续时间系统的仿真技术。
在连续仿真中，系统中的状态和事件都是连续的，而时间也是连续的。
连续仿真通常用于建模和分析动态系统，例如电力系统、控制系统和生态系统等。
连续仿真模型可以用于分析系统的稳定性、动态特性和系统参数的设计等方面。
3. 混合仿真（HS）混合仿真是一种同时兼具离散事件仿真和连续仿真特点的仿真技术。
混合仿真可以用于建模和分析同时包含离散和连续过程的系统，例如混合生产系统、供应链系统和环境系统等。
混合仿真模型可以用于分析系统的整体性能、协调离散和连续过程以及系统的优化设计等方面。
4. 随机仿真随机仿真是一种基于概率分布的仿真技术。
在随机仿真中，系统的状态和事件都是随机的，而时间也是随机的。
随机仿真通常用于建模和分析具有随机性质的系统，例如金融系统、天气系统和生物系统等。
随机仿真模型可以用于分析系统的风险、概率特性和对策选择等方面。
5. Agent-Based ModelingAgent-based modeling (ABM) is a simulation technique that focuses on simulating the actions and interactions of autonomous agents within a system. This approach is often used for modeling complex and decentralized systems, such as social networks, biologicalecosystems, and market economies. In ABM, individual agents are modeled with their own sets of rules, behaviors, and decision-making processes, and their interactions with other agents and the environment are simulated over time. ABM can be used to study the emergent behavior and dynamics of complex systems, and to explore the effects of different agent behaviors and interactions on system-level outcomes.三、常用技术1. Monte Carlo方法蒙特卡洛方法是一种基于随机模拟的数值计算技术。
插电式混合动力汽车控制策略与建模
106机械设计与制造Machinery Design & Manufacture第3期2021年3月插电式混合动力汽车控制策略与建模宫唤春(燕京理工学院，北京065201)摘要：为了深入分析插电式混合动力汽车能量管理控制策略就需要建立准确的插电式混合动力汽车仿真测试模型，分析影响能量管理系统的因素。
利用M A T L A B/S I M U L I N K软件基于实验数据和理论模型相结合的方法对插电式混合动力汽车建模，根据插电式混合动力汽车传动系部件的工作特征对应建立各部件的数学模型，并建立了基于规则的能量管理控制策略对整车的动力性与经济性进行计算仿真验证，计算结果表明建立的插电式混合动力汽车仿真糢型和能量管理控制策略能够有效确保发动机处于高效区域运行并改善整车燃油经济性，控制策略可靠有效。
关键词:插电式混合动力汽车;建模;能量管理;控制策略中图分类号:T H16文献标识码:A文章编号：1001-3997(2021)03-0106-04Control Strategy and Modeling of Plug-in Hybrid Electric VehiclesGONG Huan-chun(Yanching Institute of Technology, Beijing 065201, China)Abstract ：/n order to deeply analyze the energy management control strategy o f plug-in hybrid vehicles, it is necessary to establish an accurate plug-in hybrid vehicle simulation test model and analyze the factors affecting the energy management systerruThe M A T L A B/S I M U L I N K software is used to model the p lu g—in hybrid vehicle based on the combination of experimented data and theoretical model. The mathematical model o f each component is established according to the working characteristics o f the powertrain o f the p lu g-in hybrid vehicle y and the basis is established. The energy management and control strategy o f the rule calculates and verifies the power and economy o f the vehicle. The calculation results show that the plug—in hybrid vehicle simulation model and energy management control strategy established in this paper can effectively ensure that the engine is running in an efficient area and improve the whole. Vehicle fu el economy, control strategy is reliableand effective.Key Words:Plug-in Hybrid Vehicle; Modeling; Energy Management; Control Strategyl引言插电式混合动力汽车(Plug-in Hybrid Electric Vehicle, P H E V)是基于传统混合动力汽车衍生出的一种车辆，该类型汽车可以直 接接人电网进行充电，纯电动模式下续驶里程更远，同时统发动 机更省油等优点，已经成为电动汽车领域重点研发的产品之一插电式混合动力汽车对动力传动系统的设计及能量管理系统控制等要求较高从而使得其工作模式与传动混合动力汽车相比更为复杂。
基于SolidWorks的换热器换热效率模拟分析
基于SolidWorks的换热器换热效率模拟分析基于SolidWorks的换热器换热效率模拟分析摘要换热器是化工、炼油、动力、食品、轻工、原子能、制药、航空及其他许多工业部门广泛使用的一种通用工艺设备。
换热器不仅能够合理调节工艺介质的温度以满足工艺流程的需要，也是余热、废热回收利用的有效装置。
鉴于换热器在工业生产中的重要作用及其能耗较大的现状，改进和提高换热器的性能及传热效率成为节能降耗的重要途径，将产生重要的经济和社会效益。
目前，计算机仿真已经成为一种重要的科研方法，我们可以利用计算机仿真进行换热情况的研究。
本论文首先阐述了换热器的发展特点及国内外的研究情况，其次对流体力学分析从基本理论、处理问题的思路步骤和在软件SolidWorks中的应用进行了阐述，并通过SolidWorks对套管式进行三维建模，利用流体分析工具Flow Simulation插件对换热器进行动态分析。
从而得到分析数据，数据主要利用图例从对称边界条件、流体子区域、边界条件、固体材料、体积目标说明换热器的换热情况。
应用SolidWorks软件仿真可以降低研究成本，缩短产品的开发周期，提高工作效率。
本文通过对换热器的三维建模，有助于了解换热器的基本结构。
对换热器的运动仿真及应用Flow Simulation进行仿真的方法可以为换热器安全性和经济效率的后续研究提供了一些参考。
关键词：SolidWorks；Flow Simulation；换热器；三维建模；流体分析Analysis of heat exchanger efficiency based on the Solidworks flow simulationAbstractHeat exchanger is a universal process equipment of chemical, food, light industry and pharmacy, aerospace, nuclear and many other industrial departments. Heat exchanger not only can be reasonable adjustment process medium temperature to satisfy the need, but also can be process waste heat recovery and utilization device. Since heat exchanger in industrial production have the important role of the status of large energy consumption, improving the efficiency of heat exchanger performance and becoming the important way, energy consumption will produce an important economic and social benefits. At present, the computer simulation has become an important tool, we can use the computer simulation research of stamping safety.This paper elaborates the characteristics and development of heat exchanger and the research situation of physical analysis, secondly, the convection from basic theory, handling problems and application in software SolidWorks are expounded, and through three-dimensional type of casing SolidWorks modeling, Simulation of fluid Flow analysis tool for heat exchanger for dynamic analysis .To analyze data, using data from the symmetrical boundary conditions, and illustrations area, fluid boundary conditions, the solid material, the volume of the heat exchanger that goal.Application of SolidWorks software simulation studies to reduce costs, shorten product development cycles, improving work efficiency. Based on the three-dimensional modeling of the heat exchanger, heat exchanger can understand the basic structure of the heat exchanger . The motionsimulation of heat flow and application simulation method of simulation for safety and economic efficiency of heat exchanger follow-up study provides some reference.Key words：SolidWorks; Flow Simulation; heat exchanger; three-dimensional modeling；fluid analysis目录摘要 (I)Abstract .............................................................................................................. I I第1章绪论 (6)1.1 课题背景 (6)1.2 国内、外研究现状 (6)1.3 研究内容、目的及意义 (10)第2章建模仿真方法 (12)2.1 三维建模 (12)2.2 SolidWorks 软件简介 (13)系统简介 (13)系统要求 (14)2.3 Solidworks软件建模 (16)2.4 模拟仿真 (20)第3章换热器的建模 (22)3.1 换热器模型的建立 (22)模型的简化 (22)建模方案 (22)换热器主要零件模型的建立 (23)换热器盖体的建立 (26)3.2 换热器模型的装配 (27)装配体基本操作方法 (27)换热器的装配 (27)第4章应用Flow Simulation进行数值模拟及验证 (31)4.1 套管式换热器换热系数的计算公式 (31)4.2 创建Flow Simulation数值仿真项目 (31)创建项目 (31)定义流体子区域 (33)4.3 定义边界条件 (35)定义边界范围 (35)4.3.2 定义固体材料 (36)定义体积目标 (36)4.4 验证数据及观察图形 (37)运行计算 (37)观察目标 (37)创建切面云图 (38)显示流动迹线 (40)表面参数计算 (41)计算热交换系数 (43)定义参数显示范围 (44)结论 (46)致谢 (47)参考文献 (48)附录 (50)第1章绪论1.1课题背景换热器是将热流体的部分热量传递给冷流体的设备，又称热交换器。
基于超大涡模拟的燃烧室气动性能仿真研究进展
收稿日期：2023-02-07基金项目：航空动力基础研究项目资助作者简介：张宏达（1988），男，博士，高级工程师。
引用格式：张宏达，韩省思，刘太秋，等.基于超大涡模拟的燃烧室气动性能仿真研究进展[J].航空发动机，2023，49（4）：68-79.ZHANG Hongda ，HAN Xingsi ，LIU Taiqiu ，et al.Progress of combustor aerodynamic performance simulation based on very large eddy simulation[J].Aeroengine ，2023，49（4）：68-79.基于超大涡模拟的燃烧室气动性能仿真研究进展张宏达1，韩省思2，刘太秋1，朱健1，马宏宇1，任祝寅3（1.中国航发沈阳发动机研究所，沈阳110015；2.南京航空航天大学能源与动力学院，南京210016；3.清华大学航空发动机研究院，北京100084）摘要：航空发动机燃烧室涉及旋流、雾化蒸发、掺混、化学反应、湍流与火焰相互作用等多尺度强耦合物理化学过程，相关的高精度建模和数值模拟面临极大的挑战。
超大涡模拟是近些年发展的兼顾计算精度、计算效率和强鲁棒性的数值模拟新方法，具备试验室尺度和复杂工程应用场景下湍流流动与燃烧仿真能力。
针对航空发动机燃烧室相关流动与燃烧基本特征，阐述了超大涡模拟的理论方法及特点，从旋流流动、湍流燃烧、液雾雾化、碳烟生成、燃烧不稳定等典型多物理过程，以及双旋流模型燃烧室和高温升燃烧室气动性能集成仿真等方面介绍了超大涡模拟的研究进展，对涉及的物理机制进行了分析，为超大涡模拟在航空发动机燃烧室中规模化工程应用提供了坚实支撑。
超大涡模拟在较低的计算资源消耗下具备与传统大涡模拟相当的计算精度，是一种经济可承受的燃烧室高精度气动性能仿真新方法。
关键词：燃烧室；超大涡模拟；气动性能；数值仿真；航空发动机中图分类号：V231.2文献标识码：Adoi ：10.13477/ki.aeroengine.2023.04.009Progress of Combustor Aerodynamic Performance Simulation Based onVery Large Eddy SimulationZHANG Hong-da 1，HAN Xing-si 2，LIU Tai-qiu 1，ZHU Jian 1，MA Hong-yu 1，REN Zhu-yin 3（1.AECC Shenyang Engine Research Institute ，Shenyang 110015，China ；2.College of Energy and Power Engineering ，Nanjing University of Aeronautics and Astronautics ，Nanjing 210016，China ；3.Institute for Aero Engine ，Tsinghua University ，Beijing 100084，China ）Abstract ：The turbulent flow and combustion in the combustor of aeroengines involved multi-scale strongly-coupled physicochemical processes such as swirling flow,atomization evaporation,mixing,chemical reaction,turbulence-flame interactions,etc.The relevant high-fidelity modeling and numerical simulation face with great challenges.Very Large Eddy Simulation Method,i.e.VLES,was a newly-devel⁃oped numerical method in recent years with a good balance in robustness,computational accuracy,and efficiency.It has the ability to simu⁃late complex turbulent flow and combustion from laboratory scale to complex engineering application scenarios.According to the character⁃istics of flow and combustion in the chamber,the fundamental theoretical framework and characteristics of VLES method are presented,and the research progress of high-fidelity numerical simulation application of VLES is introduced from typical multi-scale physicochemical processes including swirling flow,turbulent combustion,liquid atomization,soot,combustion instability,etc.and integrated aerodynamicperformance simulations of double-swirl model combustors as well as high-temperature-rise combustors.The physical mechanism in⁃volved is analyzed,which provides solid support for the large-scale engineering application of VLES technology for aeroengine combustors.The VLES method has a comparable simulation accuracy as the traditional large eddy simulation method under the condition of low compu⁃tational resource consumption.Thus,it is an economically affordable new method for high-fidelity numerical simulation for the aerodynam⁃ic performance of combustors.Key words ：combustor;very large eddy simulation;aerodynamic performance;numerical simulation;aeroengine第49卷第4期2023年8月Vol.49No.4Aug.2023航空发动机Aeroengine张宏达等：基于超大涡模拟的燃烧室气动性能仿真研究进展第4期0引言燃烧室是航空发动机的核心部件之一，燃烧室气动性能对整机性能起到至关重要的作用[1-2]。
机车智能驾驶纯数字仿真测试系统研究
收稿日期：2020-08-28作者简介：黄旺（1985—），男，硕士，工程师，主要从事软件测试工具开发和测试技术的研究工作。
机车智能驾驶纯数字仿真测试系统研究黄 旺，刘布麒，刘梦琪，彭辉水（中车株洲电力机车研究所有限公司，湖南 株洲 412001）摘 要：针对机车智能驾驶软件测试，若采用传统软件测试方法，则存在测试环境建设成本高、测试设备占地面积大、系统通用性差及测试执行效率低等问题。
为此，文章提出一种基于纯数字仿真的测试方法，其通过Visual C++语言编写软件，模拟自动驾驶装置、人机交互单元、LKJ 装置及车载控制系统装置等硬件设备。
该纯数字仿真测试系统已被用于西康线机车自动驾驶项目，结果表明，其不仅可自适配不同运行线路，而且具备仿真加速功能，测试环境成本降低90%，测试时间缩短75%，测试效率提升4倍以上。
关键词：智能驾驶；软件测试；纯数字仿真；自动驾驶中图分类号 ：TP13；U260.1 文献标识码 ：A 文章编号 ：2096-5427(2020)06-0014-05doi:10.13889/j.issn.2096-5427.2020.06.003Research on Full Digital Simulation Test System for Locomotive Intelligent DrivingHUANG Wang, LIU Buqi, LIU Mengqi, PENG Huishui( CRRC Zhuzhou Institute Co., Ltd., Zhuzhou, Hunan 412001, China )Abstract: In view of the problems of high construction cost of test environment, large area occupation of test equipments, poor system generality and low test execution efficiency encountered by traditional software testing methods in the process of locomotive intelligent driving software testing, this paper presented a test method based on full digital simulation. It uses software with Visual C++ to simulate the functions of hardware devices such as automatic train operation device, driver machine interface, LKJ device and onboard central control unit, etc. The proposed digital simulation test system has been applied to the locomotive automatic driving project of Xikang line. The results show that the method can adapt to different running lines with the function of simulation acceleration to significantly reduce 90% test cost and 75% test time, and the test efficiency is increased to more than 4 times of the existing hardware in the loop simulation test efficiency.Keywords: intelligent driving; software test; full digital simulation; automatic driving0 引言随着列车速度规划曲线神经网络算法[1-2]、节能优化操纵算法及基于增量特征学习的深度学习算法[3-5]等技术的不断涌现，铁路行业机车智能驾驶技术的理论研究在不断深入,应用范围也日趋广泛。
Simcenter STAR-CCM+V2302 主要新功能介绍
increasing container ship efficiency with SimcenterSTAR-CCM+DNV uses simulation to explore many design options for optimizing hull shape to reduce resistance.$3M Annual fuel savingsper shipDNVIncreasing container ship efficiency with Simcenter STAR-CCM+ Optimizing vessel hydrodynamic performance“UsingSimcenter STAR-CCM+, we can make as many modifications and adjustmentsas necessary and immediately see how these decisions will affect other areas of thedesign.”•Achieved 36% improvement in energyefficiency without sacrificing containercapacity•Estimated fuel savings of $3 million pership•Enhanced market position ofparticipating companies •Analyze and optimize hull for a range of operating conditions •Collaboration between ship owner, shipyard and advisory group Olav Rognebakke, Head of Ship Hydrodynamics and StabilityVisualization of bow wave at 19 kts Wave pattern from initial and final hullsModel the complexity Ensuring decision confidenceModel the complexityEnsuring decision confidence Go fasterAchieving speed and agilityExplore the possibilitiesEnabling insightsStay integratedConnecting all activitiesChallengeSetting up battery thermal runaway is complexSolutionNew dedicated thermal runaway workflow withinthe Batteries solution and a cell exothermalempirical heat release modelBenefits•Fast setup in minutes, for a full pack withhundreds or thousands of cells•No complex field functions or countless reports•Improved understanding of runaway propagation•Provides critical insights prior to costlycertification safety tests•Helps in the design of mitigation measures Battery thermal runaway workflowThermal runaway simulation configurator: heat release model Workflow demonstrationChallengeHigh computational cost of applications withmultiple multiphase regimes combining mixturesand free surfacesSolutionImplicit Multi-Step enables sub-stepping for thevolume fraction multiple times within the flowtimestepBenefits•Speed up multiphase simulations•Decouples flow from need for small timestep forvolume fraction•Allows larger flow timestep•Mirrors implementation for VOF Implicit Multi-Step for Mixture Multiphase with Large Scale Interface (MMP-LSI)N=1N=163.8x Speed-UpImplicit Multi-Step for Mixture Multiphase –Large Scale Interface (MMP-LSI)Sp ee d-U p Number of Sub-StepsAdaptive Mesh Refinement(AMR) and AdaptiveTimestep Used for FreeSurfaceMirrors implementation for VOFChallenge Predict particle motion and phase-change for applications that dry wet solids Solution Model the evaporation of liquid components in Discrete Element Method (DEM) particles Benefits •Accurately simulate drying processes in direct, convection-based dryers like drum dryers,spray dryers, fluidized bed dryers or indirectconduction-based dryers•Enabling many applications in the chemicalprocessing, mining, steel, food and batterymanufacturing industrySpray drying including Liquid-solid-gas material option for DEM particlesLiquid-Solid-Gas material option for DEM particlesChallengeMany applications involve motion with close-proximity of solid bodies which requires dynamicmesh adjustments for maximum solution stabilitySolutionOverset region mesh refinement is matched to thebackground region meshBenefits•Improved solution robustness•Fully automatic with no additional setup effortsby the user•Enhancing a wide range of applications:Transmission gear boxes, store separation,valves etc.Refine high priority (foreground) and background region during Overset Adaptive Mesh Refinement (AMR)LES turbulence models compatible with porous regions D3953High-fidelity simulation of flows with porous regions via liftingthe incompatibility with LES turbulence models•Allows Wall-Modeled LES (WMLES) simulation for fullvehicle external aerodynamics with radiators and heatexchangers•Expands HVAC (Heat, Ventilation & Air Conditioning) simulation capabilities where filters or heat exchangers are typically modeled with porous regionsChallengeObtaining highly accurate solutions requires considerable solver adjustments by the user SolutionA new gradients hybridization scheme replacing the previous Least Squares –Green Gauss hybridschemeBenefits•Improved accuracy of results•Improved convergence behavior •Significantly reduced need for user intervention while obtaining better levels of accuracy4.5 stages axial compressorImproved accuracy and convergence rate with a newgradients hybridization scheme22102302Model the complexityEnsuring decision confidenceStay integratedConnecting all activities Go fasterAchieving speed and agilityChallengeHandling the exploration of results in VR poses a challenge to non-frequent VR usersSolutionGuide any user through simulation results by looking “through the eyes” of an expert user Benefits•Enable anyone to easily dive into CFD results •Jointly explore insights to make better engineering decisionsAdditional VR EnhancementQuick re-use of existing scene through server state saving (Particle settings, plane sections, probes etc.)and reconnection possibility Guided Tour Mode for Virtual RealityChallenge Quickly and easily generate performance maps with two independent and one dependent variable, e.g. for Turbomachinery Solution •Adding a layer of information to the XY plot through contour plots •Interpolation used to draw the contour lines •External data supported through tables Benefits Insights into a complete performance maps with iso-efficiency lines in a few clicks Contour plotsModel the complexity Ensuring decision confidence Stay integratedConnecting all activities Explore the possibilities Enabling insightsGo fasterAchieving speed and agilityARM64 CPU architecture supportChallengeRun CFD simulation in the most efficient way inincreasingly heterogeneuos hardware landscape SolutionSupport CFD simulation on ARM64 CPUs Benefits•Greater performance per price and energy consumption compared to equivalent x86 CPUs•Technology available through different Cloud vendors like AWS EC2 instances and Fugaku super-computer by Fujitsu in JapanCurrent Limitations Linux only, Batch jobs only, no support of Intelligent Design Exploration, CAD importers, Client for NX, material database*Pricing based on AWS On Demand list price for EC2 instancesGPU -enabled acceleration: Memory consumption reduction and further performance improvementsChallengeSize of simulation that can be run on GPUs islimited by the available memory (RAM)SolutionReduced memory overhead and improvedperformance through more efficient use of AmgXBenefits•Memory reduction of up to 40 %•Immediate performance and efficiencyincrease, especially for large simulationsAdditional runtime performance improvements compared to previous versions of up to 10%0.10.20.30.40.50.60.70.80.91Case A Case BNormalizedGPUResidentmemory22102302Case A: Cold flow combustor, 115M polyhedral cells, RANS, segregated flow and energy Case B: Corvette, 110M trimmed cells, DES, segregated flow with MRFGPU performance improvements -memory usage*Assuming 2.0 GB RAM per million cells (2210) and 1.25GB RAM per million cells (2302). Mixed precision, trimmed mesh, segregated flow.Multiple GPUs can be used for larger problem sizesGPU CardDescriptionRAM (GB)Estimated max mesh size per GPU*22102302Quadro RTX4000Standard workstation GPU 84M cells 6.4M cells Quadro RTX6000High-end workstation GPU 2412M cells 19M cells Quadro RTX8000High-end workstation GPU4824M cells38M cellsQuadro RTX A5000Top-end workstation GPU 2412M cells 19M cells Tesla V100Older server GPU 3216M cells 25.5M cells Tesla A100Top-end server GPU 40/8020M / 40M cells 32M / 64M cells Tesla H100Next generation server GPU40/8020M / 40M cells32M / 64M cellsChallengeFaster time to convergence and solution without additional hardware investments Array SolutionSIMPLEC, a new unsteady implicit schemeBenefits•Same accuracy as Simple with a reduced number of inner iterations•Significant speed-up of transient flow simulation•Deeper convergence within the time-stepSIMPLEC available for Segregated Flow solverSignificant speed-up of transient flow simulation with a newunsteady implicit scheme•Same accuracy as SIMPLE can be achieved with a reducednumber of inner iterationsDrivAer •Deeper convergence within the time-step•Example: using convergence-based stopping•1 order of magnitude drop for continuity residualsAvailable for the Segregated Flow solver•Modified formulation of the pressure correction equation that does not require under relaxation•Pressure URF = 1•Velocity URF = 0.8 -1•This ensures a deeper convergence within the time-stepSIMPLE SIMPLECEasily leverage between the choice for accuracy or speed with SIMPLEC•Increase the accuracy maintaining the same turnaround time as SIMPLE: 8 drag counts gained•Speed-up the simulation maintaining the same level of accuracy as SIMPLE: 20% fasterDrivAerDrag coefficientElapsed time [h]Exp. valueModel the complexityEnsuring decision confidenceGo fasterAchieving speed and agilityExplore the possibilitiesEnabling insightsSimulation GuideChallengeEfficient collaboration and sharing of informationon CFD simulation setup right where needed Array S olutionCentralize your simulation information in one place(right in the sim file) by using simulation guide•Built-in editor, supporting text, tables, images,links to simulation tree nodesBenefits•Increased productivity and trust•Seamlessly share, update and reviewinformation relevant to the simulation•Collaborate and build collective knowledge•One file for everythingSimulation GuideEnhanced productivity with clear embeddedinstructions•Increased user confidenceFor the simulation template authors•Easily create and maintain workflow instructions •Explicit custom user guidanceFor the simulation template users•Quickly understand setup steps•Leverage streamlined workflow instructionsWeb Viewer integration in Xcelerator Share Effortlessly share simulation results with different internal andexternal stakeholders•Upload and view Scene files directly in Xcelerator Share, with no software download needed•Secure storage for Scene files in the cloudCustomizable naming for scenes and plotEfficient organization of results with customizable naming for scenes and plots•Append multiple field functions as a suffix to the file nameEffective searching and filtering by using file name•State of simulation visible through inclusion of field dataCustomized file name example:Temperature_1_OutletPressure_134765.738_Pa_OutletTemperature_4 55.823_KParts-based motion specificationImproved productivity with Parts-based motion values specification•Facilitates templating and automation•Reduction in the number of Regions due motion specification at Part sub-group level •Applications: Vehicle thermal management, external aerodynamics etc.BackgroundSolutionParts-based motion specificationRemoval of Region-Based Meshing (*******)Region-based meshing has been removed. Specific changes in the Simcenter STAR-CCM+ UI 22102302Removal of Region-Based MeshingRegion-based meshing has been removed. Specific changes in the Simcenter STAR-CCM+ UI 22102302New Tutorials•Reacting Flow•Acoustic Modal Analysis: Thermo-Acoustic Stability of a Cylindrical Burner •Battery•Thermal Runaway: Battery Pack Heat Release and Venting•Heat Transfer and Radiation•Dual Stream Heat Exchanger: Car Radiator•Coupling with CAE Codes▪•FMU Co-Simulation with Simcenter Amesim: Check ValveUpdated Tutorials•Adjoint Topology Optimization: Channel Flow –removed for this cycle pending revision•Acoustic Suppression Zone Modeling: Direct Noise Simulation –renamed to Sponge Layer Modeling: Simplified Tailpipe, and revised to use Sponge Layer model instead of the Acoustic Suppression Zone model•Multi-Part Solid: Graphics Card Cooling –updated to use the contact browser•Parts-Based Shells: Exhaust Pipe –updated for UI changes•Morphing: Cylinder with Boundary Motion –now uses the B-Spline morpher instead of the RBF morpher•FSI and 6-DOF Motion: Stress Analysis on Boat Propeller –minor change to setup•Eulerian: Wall Boiling –initial SMD for vapor set to 0.001 m•Fluid-Structure Interaction: Vibrating Pipe –changes to convergence criteria•FSI with Opening and Closing Flow Paths: Diaphragm Valve –replaced infinite plane contact with tessellated part contact •Normal Modes Solver: Wind Turbine Blade –added rotating reference frame•Turbomachinery Mesher: Compressor Stage –implemented custom control in the stator•VOF: Tank Sloshing with Adaptive Meshing –updated to include the Implicit Multi-stepping VOF solver•VOF: Multi-Stepping –retired due to updates made within the VOF: Tank Sloshing with Adaptive Meshing tutorial that cover the same theme•Parts-Based Meshing External Aerodynamics –updated to use a Boundary March Angle of 85Page 41Unrestricted | © Siemens 2023 | Siemens Digital Industries SoftwareGo fasterModel the complexity。
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The one-dimensional continuity equation for electrons in the ith section of the diffused p-region, with a photon flux F’0 of monochromatic light incident upon the front surface of the cell is given by :
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Copyright © Canadian Research & Development Center of Sciences and Cultures
Simulation Model for High Efficiency of Solar Cells
etal. 1990). In theoretical understanding of the limits of solar cell efficiencies, several authors (e.g. Fahrenbruch and Bube,1983 and the references therein and Gangadhar and Kaushika,1992 ) have investigated the quantum and collection efficiencies of graded base solar cells to obtain their solar spectral response .These analyses have not considered in detail the variability’s of the built in field as well as of mobility values in the graded base region. .In the present analysis a more rigorous simulation model of graded base solar cell is presented to investigate the effect of geometrical and other parameters related to material processing in the fabrication (Runyan, 1985) of solar cells for their high performance.
the state and quality of the silicon material there are three types of solar cells that have been produced and marketed: 1. Mono-crystalline Cells: These cells use pure monocrystalline silicon with almost no defects or impurities. In practice these cells are made from wafers of about 450500 micrometer thickness and are characterized by the impurity grading in their base region. They are expensive to produce. They have a solar conversion efficiency of about 15-17%. 2. Polycrystalline cells: These cells are produced from slightly poorer grades of mono-crystalline silicon or semiconductor grade silicon. The cells have white speckles on the surface due to impurities. They are comparatively less expensive since simpler processes are involved in their production. They have a solar conversion efficiency of about 10-12%. 3. Amorphous silicon cells/thin film cells: These are often referred to as second generation solar cells and are made from amorphous silicon rather than silicon of crystal structure. They absorb light more effectively than crystalline cells and can, therefore, be thinner. Thin film technology has been successfully used on rigid, flexible, curved and foldable substrates. They have lower cost than crystalline cells but have a lower conversion efficiency of 5-7%. However, the reduced cost often overweighs the reduced efficiency, leading to a net increase in ratio of performance to cost. Past two decades have witnessed remarkable improvement in solar cell efficiencies. Most of the improvements have originated from improved cell structures and processing techniques). The improvements in Mono-crystalline Cells include effective light trapping schemes, reduction of recombination along the top cell surface using thermal oxide passivation and reduction in bulk recombination by an appropriate rear contact. (Blaker and Green, 1986; Blaker etal.1989 ;Green etal.1990) The most efficient and expensive single-junction silicon cells have been reported to have about 24% efficiency (Wang
Simulation Model for High Efficiency of Solar Cells
N.D.Kaushika1,*; Reeta2
Amity University ,Sector 125 Noida, U.P, India D.J.(PG) College Baraut, Meerut, India * Corresponding author. Email: ndkaushika@
Energy Science and Technology
Vol. 2, No. 1, 2011, pp. 57-61 DOI:10.3968/j.est.1923847920110201.589
ISSN 1923-8460[PRINT] ISSN 1923-8479[ONLINE]
Kaushika, N.D., & Reeta(2011). Simulation Model for High Efficiency of Solar Cells. Energy Science and Technology, 2 ( 1 ) , 5 7 - 6 1 . Av a i l a b l e f r o m : U R L : h t t p : / / w w w. c s c a n a d a . net/index.php/est/article/view/j.est.1923847920110201.589 DOI: /10.3968/j.est.1923847920110201.589
2
1
Received 9 June 2011; accepted 13 July 2011
Abstracts
Hale Waihona Puke Simulation model of solar cell device is developed to investigate the optimization of conversion efficiency as a function of its geometrical and materials parameters. An arbitrary profile of impurity distribution in the base region is taken into account by using the method of piece wise integration by exponential approximations .The spatially varying built-in field and mobility are explicitly taken into account. Illustrative numerical computations of quantum & collection efficiencies as well as of solar conversion parameters are presented. Simulation conversion efficiency of mono- crystalline silicon solar cell is in conformity with the 24% efficiency reported in Australia for the PERL structure when reasonably effective (about 2-3%) light trapping is taken into account. The model also supports the structure of multi junction thin film solar cells for ultra high efficiency. Key words: Solar cell; Mono-crystalline; Simulation model; Ultrahigh efficiency