Ray tracing is a computer graphics method that renders images realistically. As the name suggests, this technique primarily traces the path of light rays interacting with objects in a scene [1], permitting the calcula...Ray tracing is a computer graphics method that renders images realistically. As the name suggests, this technique primarily traces the path of light rays interacting with objects in a scene [1], permitting the calculation of lighting and reflecting impact [2]. As ray tracing is a time-consuming process, the need for parallelization to solve this problem arises. One downside of this solution is the existence of race conditions. In this work, we explore and experiment with a different, well-known solution for this race condition. Starting with the introduction and the background section, a brief overview of the topic is followed by a detailed part of how the race conditions may occur in the case of the ray tracing algorithm. Continuing with the methods and results section, we have used OpenMP to parallelize the Ray tracing algorithm with the different compiler directives critical, atomic, and first-private. Hence, it concluded that both critical and atomic are not efficient solutions to produce a good-quality picture, but first-private succeeded in producing a high-quality picture.展开更多
针对油浸式变压器2维流-热耦合仿真计算效率低的问题,提出了基于混合有限元法的并行计算方法。首先,在Visual Studio 2019中采用C++语言实现无量纲最小二乘有限元法以及迎风有限元法的串行计算方法。然后,基于图形处理器(graphic proces...针对油浸式变压器2维流-热耦合仿真计算效率低的问题,提出了基于混合有限元法的并行计算方法。首先,在Visual Studio 2019中采用C++语言实现无量纲最小二乘有限元法以及迎风有限元法的串行计算方法。然后,基于图形处理器(graphic processing unit,GPU)实现流体场的并行计算,针对单分区分匝模型对比分析了不同GPU卡在不同网格条件下的并行计算效率,分析结果表明数据规模越大,GPU卡流处理器越多并行效果越好。其次,基于Intel MKL(Intel math kernel library)函数库结合共享存储并行编程(open multi-processing,OpenMP)实现了2维温度场的并行计算,并对比分析了不同网格数量对并行效率的影响。最后,在此基础上提出了根据不同仿真条件的混合并行计算方法,并应用到大型油浸式变压器绕组模型的2维温升热点分析中。结果表明,相较于串行程序,混合有限元并行计算方法的加速比达到了69.5,实验测试结果进一步验证了并行计算结果的准确性,研究成果为大型油浸式变压器流-热耦合问题的快速计算奠定了基础。展开更多
储能系统采用串并联结构(串联的储能单元为一组,多组并联)可以实现将小容量、低电压等级的储能单元接入直流微电网中,并且可以实现系统扩容和提高端电压。为避免串并联结构的储能单元因荷电状态(state of charge,SOC)和额定容量差别导...储能系统采用串并联结构(串联的储能单元为一组,多组并联)可以实现将小容量、低电压等级的储能单元接入直流微电网中,并且可以实现系统扩容和提高端电压。为避免串并联结构的储能单元因荷电状态(state of charge,SOC)和额定容量差别导致个别储能单元提前退运的短板效应,提出一种考虑储能SOC和额定容量的控制方法,实现串联模块间的电压和并联模块间的功率合理分配。考虑到功率分配后期因储能单元间SOC差别较小导致均衡速度较慢的问题,引入变异系数对下垂系数进行动态优化。考虑到升压或扩容导致各组总容量不同,引入容量权重因子,使储能单元达到均衡出力。通过搭建MATLAB/Simulink仿真模型,验证了策略的可行性。展开更多
文摘Ray tracing is a computer graphics method that renders images realistically. As the name suggests, this technique primarily traces the path of light rays interacting with objects in a scene [1], permitting the calculation of lighting and reflecting impact [2]. As ray tracing is a time-consuming process, the need for parallelization to solve this problem arises. One downside of this solution is the existence of race conditions. In this work, we explore and experiment with a different, well-known solution for this race condition. Starting with the introduction and the background section, a brief overview of the topic is followed by a detailed part of how the race conditions may occur in the case of the ray tracing algorithm. Continuing with the methods and results section, we have used OpenMP to parallelize the Ray tracing algorithm with the different compiler directives critical, atomic, and first-private. Hence, it concluded that both critical and atomic are not efficient solutions to produce a good-quality picture, but first-private succeeded in producing a high-quality picture.
文摘针对油浸式变压器2维流-热耦合仿真计算效率低的问题,提出了基于混合有限元法的并行计算方法。首先,在Visual Studio 2019中采用C++语言实现无量纲最小二乘有限元法以及迎风有限元法的串行计算方法。然后,基于图形处理器(graphic processing unit,GPU)实现流体场的并行计算,针对单分区分匝模型对比分析了不同GPU卡在不同网格条件下的并行计算效率,分析结果表明数据规模越大,GPU卡流处理器越多并行效果越好。其次,基于Intel MKL(Intel math kernel library)函数库结合共享存储并行编程(open multi-processing,OpenMP)实现了2维温度场的并行计算,并对比分析了不同网格数量对并行效率的影响。最后,在此基础上提出了根据不同仿真条件的混合并行计算方法,并应用到大型油浸式变压器绕组模型的2维温升热点分析中。结果表明,相较于串行程序,混合有限元并行计算方法的加速比达到了69.5,实验测试结果进一步验证了并行计算结果的准确性,研究成果为大型油浸式变压器流-热耦合问题的快速计算奠定了基础。
文摘储能系统采用串并联结构(串联的储能单元为一组,多组并联)可以实现将小容量、低电压等级的储能单元接入直流微电网中,并且可以实现系统扩容和提高端电压。为避免串并联结构的储能单元因荷电状态(state of charge,SOC)和额定容量差别导致个别储能单元提前退运的短板效应,提出一种考虑储能SOC和额定容量的控制方法,实现串联模块间的电压和并联模块间的功率合理分配。考虑到功率分配后期因储能单元间SOC差别较小导致均衡速度较慢的问题,引入变异系数对下垂系数进行动态优化。考虑到升压或扩容导致各组总容量不同,引入容量权重因子,使储能单元达到均衡出力。通过搭建MATLAB/Simulink仿真模型,验证了策略的可行性。
