We present three-dimensional(3-D)modeling method of marine controlled-source electromagnetic(CSEM)fields in general anisotropic media using an adaptive finite element approach based on the vector-scalar potential.The ...We present three-dimensional(3-D)modeling method of marine controlled-source electromagnetic(CSEM)fields in general anisotropic media using an adaptive finite element approach based on the vector-scalar potential.The modeling is based on the governing Helmholtz equations in the vector-scalar potential system.Unstructured tetrahedral grids are employed,which can exactly simulate the terrain relief and complex electrical structures.Moreover,based on the gradient recovery technology,the adaptive finite element approach is used to drive the mesh refinement,and make the finite element solutions converge gradually to the exact solutions.The primary-secondary field approach is used to improve the numerical accuracy of CSEM fields near the source point,where the primary field is calculated by using the quasi-analytical formula.The accuracy of this approach is verified by a one-dimensional model.Two 3-D models are used to demonstrate the effectiveness of the adaptive mesh refinement and the influences of dipping anisotropy layer on the marine CSEM responses for both inline and broadside geometries.The complex synthetic model is simulated to show the capability and flexibility of the approach for geometrically complex situations.展开更多
该文基于美国国家浮标资料中心(National Data Buoy Center,NDBC)浮标观测数据对哨兵一号搭载的合成孔径雷达(synthetic aperture radar,SAR)反演风速数据进行精度分析,并利用BP神经网络(back propagation neural network)对SAR反演风...该文基于美国国家浮标资料中心(National Data Buoy Center,NDBC)浮标观测数据对哨兵一号搭载的合成孔径雷达(synthetic aperture radar,SAR)反演风速数据进行精度分析,并利用BP神经网络(back propagation neural network)对SAR反演风速的偏差进行校正;同时针对环境要素、BP神经网络训练输入的样本量以及神经网络结构参数设计了敏感性试验;最后将SAR标量风场数据转换为用u、v矢量表示的风场数据,并对u向风和v向风分别进行了精度分析和校正。实验结果表明:SAR反演风速相较于浮标观测数据出现了低估现象;经过BP神经网络校正后,SAR反演风速数据的精度得到了改善,风速的平均偏差绝对值从0.78 m s下降到0.04 m s,均方根误差从1.98 m s下降到了1.77 m s;敏感性试验表明输入质量较差的环境要素数据时BP神经网络的校正效果有所下降,而增加训练集样本量能改善校正效果;将标量风场数据转换为u、v矢量风场数据后的校正结果也显示BP神经网络具有较好的校正效果。展开更多
The massive vector bosons Z o, W ± and the scalar Higgs-boson H o assumed in weak interaction theory, but also the six quarks required in strong interactions are well understood in an alternative quantum field th...The massive vector bosons Z o, W ± and the scalar Higgs-boson H o assumed in weak interaction theory, but also the six quarks required in strong interactions are well understood in an alternative quantum field theory of fermions and bosons: Z o and W ± as well as all quark-antiquark states (here only the tt¯state is discussed) are described by bound states with scalar coupling between their massless constituents and have a structure similar to leptons. However, the scalar Higgs-boson H o corresponds to a state with vector coupling between the elementary constituents. Similar scalar states are expected also in the mass region of the mesons ω (0.782 GeV) - Υ ( 9.46 GeV). The underlying calculations can be run on line using the Web-address https://h2909473.stratoserver.net.展开更多
数字信号处理器(digital signal processor,DSP)通常采用超长指令字(very long instruction word,VLIW)和单指令多数据(single instruction multiple data,SIMD)的架构来提升处理器整体计算性能,从而适用于高性能计算、图像处理、嵌入...数字信号处理器(digital signal processor,DSP)通常采用超长指令字(very long instruction word,VLIW)和单指令多数据(single instruction multiple data,SIMD)的架构来提升处理器整体计算性能,从而适用于高性能计算、图像处理、嵌入式系统等各个领域.飞腾迈创数字处理器(FT-Matrix)作为国防科技大学自主研制的高性能通用数字信号处理器,其极致计算性能的体现依赖于对VLIW与SIMD架构特点的充分挖掘.不止是飞腾迈创系列,绝大多数处理器上高度优化的内核代码或核心库函数都依赖于底层汇编级工具或手工开发.然而,手工编写内核算子的开发方法总是需要大量的时间和人力开销来充分释放硬件的性能潜力.尤其是VLIW+SIMD的处理器,专家级汇编开发的难度更为突出.针对这些问题,提出一种面向飞腾迈创数字处理器的高性能的内核代码自动生成框架(automatic kernel code-generation framework on FT-Matrix),将飞腾迈创处理器的架构特性引入到多层次的内核代码优化方法中.该框架包括3层优化组件:自适应循环分块、标向量协同的自动向量化和细粒度的指令级优化.该框架可以根据硬件的内存层次结构和内核的数据布局自动搜索最优循环分块参数,并进一步引入标量-向量单元协同的自动向量化指令选择与数据排布,以提高内核代码执行时的数据复用和并行性.此外,该框架提供了类汇编的中间表示,以应用各种指令级优化来探索更多指令级并行性(ILP)的优化空间,同时也为其他硬件平台提供了后端快速接入和自适应代码生成的模块,以实现高效内核代码开发的敏捷设计.实验表明,该框架生成的内核基准测试代码的平均性能是目标-数字信号处理器(DSP)--的手工函数库的3.25倍,是使用普通向量C语言编写的内核代码的20.62倍.展开更多
基金support from the Natural Science Foundation of Jiangxi Province,China(Nos.20202ACBL211006,20202BAB213017)the National Natural Science Foundation of China(Nos.41774078,41904075).
文摘We present three-dimensional(3-D)modeling method of marine controlled-source electromagnetic(CSEM)fields in general anisotropic media using an adaptive finite element approach based on the vector-scalar potential.The modeling is based on the governing Helmholtz equations in the vector-scalar potential system.Unstructured tetrahedral grids are employed,which can exactly simulate the terrain relief and complex electrical structures.Moreover,based on the gradient recovery technology,the adaptive finite element approach is used to drive the mesh refinement,and make the finite element solutions converge gradually to the exact solutions.The primary-secondary field approach is used to improve the numerical accuracy of CSEM fields near the source point,where the primary field is calculated by using the quasi-analytical formula.The accuracy of this approach is verified by a one-dimensional model.Two 3-D models are used to demonstrate the effectiveness of the adaptive mesh refinement and the influences of dipping anisotropy layer on the marine CSEM responses for both inline and broadside geometries.The complex synthetic model is simulated to show the capability and flexibility of the approach for geometrically complex situations.
文摘该文基于美国国家浮标资料中心(National Data Buoy Center,NDBC)浮标观测数据对哨兵一号搭载的合成孔径雷达(synthetic aperture radar,SAR)反演风速数据进行精度分析,并利用BP神经网络(back propagation neural network)对SAR反演风速的偏差进行校正;同时针对环境要素、BP神经网络训练输入的样本量以及神经网络结构参数设计了敏感性试验;最后将SAR标量风场数据转换为用u、v矢量表示的风场数据,并对u向风和v向风分别进行了精度分析和校正。实验结果表明:SAR反演风速相较于浮标观测数据出现了低估现象;经过BP神经网络校正后,SAR反演风速数据的精度得到了改善,风速的平均偏差绝对值从0.78 m s下降到0.04 m s,均方根误差从1.98 m s下降到了1.77 m s;敏感性试验表明输入质量较差的环境要素数据时BP神经网络的校正效果有所下降,而增加训练集样本量能改善校正效果;将标量风场数据转换为u、v矢量风场数据后的校正结果也显示BP神经网络具有较好的校正效果。
文摘The massive vector bosons Z o, W ± and the scalar Higgs-boson H o assumed in weak interaction theory, but also the six quarks required in strong interactions are well understood in an alternative quantum field theory of fermions and bosons: Z o and W ± as well as all quark-antiquark states (here only the tt¯state is discussed) are described by bound states with scalar coupling between their massless constituents and have a structure similar to leptons. However, the scalar Higgs-boson H o corresponds to a state with vector coupling between the elementary constituents. Similar scalar states are expected also in the mass region of the mesons ω (0.782 GeV) - Υ ( 9.46 GeV). The underlying calculations can be run on line using the Web-address https://h2909473.stratoserver.net.
文摘数字信号处理器(digital signal processor,DSP)通常采用超长指令字(very long instruction word,VLIW)和单指令多数据(single instruction multiple data,SIMD)的架构来提升处理器整体计算性能,从而适用于高性能计算、图像处理、嵌入式系统等各个领域.飞腾迈创数字处理器(FT-Matrix)作为国防科技大学自主研制的高性能通用数字信号处理器,其极致计算性能的体现依赖于对VLIW与SIMD架构特点的充分挖掘.不止是飞腾迈创系列,绝大多数处理器上高度优化的内核代码或核心库函数都依赖于底层汇编级工具或手工开发.然而,手工编写内核算子的开发方法总是需要大量的时间和人力开销来充分释放硬件的性能潜力.尤其是VLIW+SIMD的处理器,专家级汇编开发的难度更为突出.针对这些问题,提出一种面向飞腾迈创数字处理器的高性能的内核代码自动生成框架(automatic kernel code-generation framework on FT-Matrix),将飞腾迈创处理器的架构特性引入到多层次的内核代码优化方法中.该框架包括3层优化组件:自适应循环分块、标向量协同的自动向量化和细粒度的指令级优化.该框架可以根据硬件的内存层次结构和内核的数据布局自动搜索最优循环分块参数,并进一步引入标量-向量单元协同的自动向量化指令选择与数据排布,以提高内核代码执行时的数据复用和并行性.此外,该框架提供了类汇编的中间表示,以应用各种指令级优化来探索更多指令级并行性(ILP)的优化空间,同时也为其他硬件平台提供了后端快速接入和自适应代码生成的模块,以实现高效内核代码开发的敏捷设计.实验表明,该框架生成的内核基准测试代码的平均性能是目标-数字信号处理器(DSP)--的手工函数库的3.25倍,是使用普通向量C语言编写的内核代码的20.62倍.
