In present study, the subgrid scale （SGS） stress and dissipation for multiscale formulation of large eddy simulation are analyzed using the data of turbulent channel flow at Ret = 180 obtained by direct numerical si...In present study, the subgrid scale （SGS） stress and dissipation for multiscale formulation of large eddy simulation are analyzed using the data of turbulent channel flow at Ret = 180 obtained by direct numerical simulation. It is found that the small scale SGS stress is much smaller than the large scale SGS stress for all the stress components. The dominant contributor to large scale SGS stress is the cross stress between small scale and subgrid scale motions, while the cross stress between large scale and subgrid scale motions make major contributions to small scale SGS stress. The energy transfer from resolved large scales to subgrid scales is mainly caused by SGS Reynolds stress, while that between resolved small scales and subgrid scales are mainly due to the cross stress. The multiscale formulation of SGS models are evaluated a priori, and it is found that the small- small model is superior to other variants in terms of SGS dissipation.展开更多
[目的/意义]根系是植物组成的重要部分,其生长发育至关重要。根系图像分割是根系表型分析的重要方法,受限于图像质量、复杂土壤环境、低效传统方法,根系图像分割存在一定挑战。[方法]为提高根系图像分割的准确性和鲁棒性,本研究以UNet...[目的/意义]根系是植物组成的重要部分,其生长发育至关重要。根系图像分割是根系表型分析的重要方法,受限于图像质量、复杂土壤环境、低效传统方法,根系图像分割存在一定挑战。[方法]为提高根系图像分割的准确性和鲁棒性,本研究以UNet模型为基础,提出了一种多尺度特征提取根系分割算法,并结合数据增强和迁移学习进一步提高改进UNet模型的泛化性和通用性。首先,获取棉花根系单一数据集和开源多作物混合数据集,基于单一数据集的消融试验测试多尺度特征提取模块(Conv_2+Add)的有效性,与UNet、PSPNet、SegNet、DeeplabV3Plus算法对比验证其优势。基于混合数据集验证改进算法(UNet+Conv_2+Add)在迁移学习的优势。[结果和讨论] UNet+Conv_2+Add相比其他算法(UNet、PSPNet、SegNet、DeeplabV3Plus),mIoU、mRecall和根系F_1调和平均值分别为81.62%、86.90%和78.39%。UNet+Conv_2+Add算法的迁移学习相比于普通训练在根系的交并比(Intersection over Union,IoU)值提升1.25%,根系的Recall值提升1.79%,F_1调和平均值提升0.92%,且模型的整体收敛速度快。[结论]本研究采用的多尺度特征提取策略能准确、高效地分割根系,为作物根系表型研究提供重要的研究基础。展开更多
作为多模式公交的重要组成部分,地铁与地面公交的衔接换乘是城市客运交通一体化的关键环节。本文基于南京市多源数据分析地铁与公交之间的换乘需求,以地铁公交换乘量为因变量构建多尺度地理加权回归模型,揭示地铁站点周边共享单车使用...作为多模式公交的重要组成部分,地铁与地面公交的衔接换乘是城市客运交通一体化的关键环节。本文基于南京市多源数据分析地铁与公交之间的换乘需求,以地铁公交换乘量为因变量构建多尺度地理加权回归模型,揭示地铁站点周边共享单车使用量、公交供给特性、换乘可达性以及地铁网络特性对换乘需求的影响及其空间异质性。研究结果表明:多尺度地理加权回归模型相比于线性回归模型以及传统的地理加权回归模型具有更强的解释力,地铁公交换乘量的影响因素具有显著的空间异质性;公交运营班次供给以及可达站点数量的提升能够促进地铁公交间的换乘;公交站点周边住宅型POI(Point of Interest)数量在城市外围区域对换乘量起到促进作用,企业型POI数量则对换乘量起到抑制作用;共享单车借用量会抑制地铁与公交之间的换乘需求,特别是在与中心城区联系紧密的城市外围区域。展开更多
The flow behaviors of the resin during the resin transfer molding(RTM) process of sisal fiber reinforced composites was studied at different scales with the consideration of the unique hierarchical and lumen structure...The flow behaviors of the resin during the resin transfer molding(RTM) process of sisal fiber reinforced composites was studied at different scales with the consideration of the unique hierarchical and lumen structures of sisal fibers compared to those of manmade fibers. The work mainly focused on the development of the multi-scale flow models which include the resin flow inside lumens, intra-bundles and inter-bundles. The models not only quantified the lumen flow based on the Hagen-Poiseuille equation,but also ensured the continuity of the velocity and stress on the boundaries between intra-bundle and inter-bundle regions by applying Brinkman equation. Three dedicated experiments were designed and implemented to validate the effectiveness of the proposed models. The absorbed resin mass over the infiltration time obtained from the single sisal fiber and sisal fiber bundle infiltration experiments showed good agreement with the calculated curves. In terms of the RTM process, the dynamic flow front of the resin was perfectly predicted by the proposed model at macro-scale.展开更多
基金supported by the National Natural Science Foundation of China(10472053 and 10772098)
文摘In present study, the subgrid scale （SGS） stress and dissipation for multiscale formulation of large eddy simulation are analyzed using the data of turbulent channel flow at Ret = 180 obtained by direct numerical simulation. It is found that the small scale SGS stress is much smaller than the large scale SGS stress for all the stress components. The dominant contributor to large scale SGS stress is the cross stress between small scale and subgrid scale motions, while the cross stress between large scale and subgrid scale motions make major contributions to small scale SGS stress. The energy transfer from resolved large scales to subgrid scales is mainly caused by SGS Reynolds stress, while that between resolved small scales and subgrid scales are mainly due to the cross stress. The multiscale formulation of SGS models are evaluated a priori, and it is found that the small- small model is superior to other variants in terms of SGS dissipation.
文摘[目的/意义]根系是植物组成的重要部分,其生长发育至关重要。根系图像分割是根系表型分析的重要方法,受限于图像质量、复杂土壤环境、低效传统方法,根系图像分割存在一定挑战。[方法]为提高根系图像分割的准确性和鲁棒性,本研究以UNet模型为基础,提出了一种多尺度特征提取根系分割算法,并结合数据增强和迁移学习进一步提高改进UNet模型的泛化性和通用性。首先,获取棉花根系单一数据集和开源多作物混合数据集,基于单一数据集的消融试验测试多尺度特征提取模块(Conv_2+Add)的有效性,与UNet、PSPNet、SegNet、DeeplabV3Plus算法对比验证其优势。基于混合数据集验证改进算法(UNet+Conv_2+Add)在迁移学习的优势。[结果和讨论] UNet+Conv_2+Add相比其他算法(UNet、PSPNet、SegNet、DeeplabV3Plus),mIoU、mRecall和根系F_1调和平均值分别为81.62%、86.90%和78.39%。UNet+Conv_2+Add算法的迁移学习相比于普通训练在根系的交并比(Intersection over Union,IoU)值提升1.25%,根系的Recall值提升1.79%,F_1调和平均值提升0.92%,且模型的整体收敛速度快。[结论]本研究采用的多尺度特征提取策略能准确、高效地分割根系,为作物根系表型研究提供重要的研究基础。
基金supported by the National Natural Science Foundation of China(62262010,61906050)Guangxi Technology R&D Program(2018AD11018)Innovation Project of GUET Graduate Education(2018YJCX44)。
文摘作为多模式公交的重要组成部分,地铁与地面公交的衔接换乘是城市客运交通一体化的关键环节。本文基于南京市多源数据分析地铁与公交之间的换乘需求,以地铁公交换乘量为因变量构建多尺度地理加权回归模型,揭示地铁站点周边共享单车使用量、公交供给特性、换乘可达性以及地铁网络特性对换乘需求的影响及其空间异质性。研究结果表明:多尺度地理加权回归模型相比于线性回归模型以及传统的地理加权回归模型具有更强的解释力,地铁公交换乘量的影响因素具有显著的空间异质性;公交运营班次供给以及可达站点数量的提升能够促进地铁公交间的换乘;公交站点周边住宅型POI(Point of Interest)数量在城市外围区域对换乘量起到促进作用,企业型POI数量则对换乘量起到抑制作用;共享单车借用量会抑制地铁与公交之间的换乘需求,特别是在与中心城区联系紧密的城市外围区域。
基金supported by the National Natural Science Foundation of China for Distinguished Young Scholars(Grant No.11625210)the Shanghai Outstanding Academic Leaders Plan(Grant No.16XD1402900)the Fundamental Research Funds for the Central Universities
文摘The flow behaviors of the resin during the resin transfer molding(RTM) process of sisal fiber reinforced composites was studied at different scales with the consideration of the unique hierarchical and lumen structures of sisal fibers compared to those of manmade fibers. The work mainly focused on the development of the multi-scale flow models which include the resin flow inside lumens, intra-bundles and inter-bundles. The models not only quantified the lumen flow based on the Hagen-Poiseuille equation,but also ensured the continuity of the velocity and stress on the boundaries between intra-bundle and inter-bundle regions by applying Brinkman equation. Three dedicated experiments were designed and implemented to validate the effectiveness of the proposed models. The absorbed resin mass over the infiltration time obtained from the single sisal fiber and sisal fiber bundle infiltration experiments showed good agreement with the calculated curves. In terms of the RTM process, the dynamic flow front of the resin was perfectly predicted by the proposed model at macro-scale.
