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学者姓名:张挺

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An ordinary state-based peridynamic model for granular fracture in polycrystalline materials with arbitrary orientations in cubic crystals SCIE
期刊论文 | 2024 , 301 | ENGINEERING FRACTURE MECHANICS
WoS CC Cited Count: 14
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Abstract :

Granular fracture holds significant implications in material mechanics. However, the previous studies in ordinary state-based peridynamic (OSB-PD) framework often neglect the internal crystalline structure of particles or only consider limited crystal orientation. To address this gap, a novel OSB-PD model for granular fracture within polycrystalline materials is proposed, in which the periodic functions are incorporated in the PD strain energy density, taking into account the inherent random orientation in cubic crystals. By comparing energy density from PD and the classical continuum mechanics, four PD material parameters are defined. Moreover, the corresponding surface correction method in the global coordinate system is also proposed. Several numerical examples including fracture analysis of polycrystalline materials are conducted to validate the effectiveness of the proposed method. The proposed ordinary state-based peridynamic model offers a fresh perspective for investigating granular fracture behaviors within polycrystalline materials.

Keyword :

Cubic crystals Cubic crystals Grain orientation Grain orientation Granular fracture Granular fracture Peridynamics Peridynamics Polycrystalline materials Polycrystalline materials

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GB/T 7714 Zhang, Ting , Gu, Tiantian , Jiang, Jin et al. An ordinary state-based peridynamic model for granular fracture in polycrystalline materials with arbitrary orientations in cubic crystals [J]. | ENGINEERING FRACTURE MECHANICS , 2024 , 301 .
MLA Zhang, Ting et al. "An ordinary state-based peridynamic model for granular fracture in polycrystalline materials with arbitrary orientations in cubic crystals" . | ENGINEERING FRACTURE MECHANICS 301 (2024) .
APA Zhang, Ting , Gu, Tiantian , Jiang, Jin , Zhang, Jianzhi , Zhou, Xiaoping . An ordinary state-based peridynamic model for granular fracture in polycrystalline materials with arbitrary orientations in cubic crystals . | ENGINEERING FRACTURE MECHANICS , 2024 , 301 .
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基于自动终止准则改进的kd-tree粒子近邻搜索研究
期刊论文 | 2024 , 56 (6) , 217-229 | 工程科学与技术
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对于大规模运动模拟问题而言,近邻点的搜索效率将对整体的运算效率产生显著影响.本文基于关联性分析建立kd-tree的最大深度dmax与粒子总数N的自适应关系式,提出了kd-tree自动终止准则,即ATC-kd-tree,同时还考虑了叶子节点大小阈值no对近邻搜索效率的影响.试验表明,ATC-kd-tree具有更高的近邻搜索效率,相较于不使用自动终止准则的kd-tree搜索效率最高提升46%,且适用性更强,可求解不同N值的近邻搜索问题,解决了粒子总数N发生改变时需要再次率定最大深度dmax的问题.同时,本文还提出了网格搜索法组合坐标下降法的两步参数优化算法GSCD法.通过2维阿米巴虫形状的参数优化试验发现,GSCD法可更为快速地率定ATC-kd-tree的可变参数,其优化效率比网格搜索法最高提升了205%,相较于改进网格搜索法最高提升了90%.研究结果表明,ATC-kd-tree和GSCD法不仅提高了近邻搜索的效率,也为复杂运动中近邻粒子搜索问题提供了一种更为高效的解决方案,能够显著降低计算资源的消耗,进一步提升模拟的精度和效率.

Keyword :

kd-tree kd-tree 坐标下降法 坐标下降法 粒子近邻搜索 粒子近邻搜索 网格搜索法 网格搜索法 自适应 自适应

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GB/T 7714 张挺 , 王宗锴 , 林震寰 et al. 基于自动终止准则改进的kd-tree粒子近邻搜索研究 [J]. | 工程科学与技术 , 2024 , 56 (6) : 217-229 .
MLA 张挺 et al. "基于自动终止准则改进的kd-tree粒子近邻搜索研究" . | 工程科学与技术 56 . 6 (2024) : 217-229 .
APA 张挺 , 王宗锴 , 林震寰 , 郑相涵 . 基于自动终止准则改进的kd-tree粒子近邻搜索研究 . | 工程科学与技术 , 2024 , 56 (6) , 217-229 .
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基于多源数据的山区小流域降水融合模型 CSCD PKU
期刊论文 | 2024 , 35 (1) , 74-84 | 水科学进展
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Abstract :

为准确获取山区小流域的降水空间分布及其资源量, 采用Kriging插值法对低分辨率卫星数据进行空间降尺度处理, 通过长短期记忆网络(Long Short-Term Memory, LSTM)将局部卫星与观测数据进行降水融合, 引入前期降水信息加强卫星与观测降水之间的时间相关性, 并利用该模型进行流域降水空间分布估计。结果表明: 从空间分布来看, 融合模型对暴雨中心位置的捕捉更加精确; 从降水量来看, 所提模型在短时强降水下的探测率和临界成功指数分别为0.60和0.50, 能够改善原始低分辨率卫星降水数据, 使其更接近实际情况; 从雨量站数量来看, 融合降水的精度随着站点数量的增加而提高, 当站点数量达到某个临界值时, 融合降水的精度趋于稳定。Kriging-LSTM模型为准确获取山区小流域的降水资源提供了新思路。

Keyword :

Kriging插值法 Kriging插值法 山区小流域 山区小流域 长短期记忆网络(LSTM) 长短期记忆网络(LSTM) 降水空间估计 降水空间估计 降水融合 降水融合

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GB/T 7714 詹昌洵 , 张挺 , 蒋嘉伟 . 基于多源数据的山区小流域降水融合模型 [J]. | 水科学进展 , 2024 , 35 (1) : 74-84 .
MLA 詹昌洵 et al. "基于多源数据的山区小流域降水融合模型" . | 水科学进展 35 . 1 (2024) : 74-84 .
APA 詹昌洵 , 张挺 , 蒋嘉伟 . 基于多源数据的山区小流域降水融合模型 . | 水科学进展 , 2024 , 35 (1) , 74-84 .
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Multi-source data-based precipitation fusion model for small mountainous watersheds∗ EI CSCD PKU
期刊论文 | 2024 , 35 (1) , 74-84 | Advances in Water Science
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To accurately acquire the spatial distribution and resources of precipitation in small mountainous watersheds, this study employed the Kriging interpolation method for spatial downscaling of low- resolution satellite data. It integrated local satellite and observational data using the long short- term memory (LSTM) network, enhancing the temporal correlation between satellite and observed precipitation by incorporating antecedent precipitation information. This model was further utilized to estimate the spatial distribution of watershed precipitation. The results indicate that, spatially, the fusion model captures the location of rainstorm centers with greater precision. In terms of precipitation amount, the proposed model shows a probability of detection and a critical success index of 0. 60 and 0. 50, respectively, under short- duration intense rainfall, improving the original low-resolution satellite rainfall data to better approximate actual conditions. As for the number of precipitation stations, the accuracy of the merged precipitation data increases with the number of stations, reaching stability when a critical value of station density is achieved. The Kriging- LSTM model offers a novel approach for precisely acquiring precipitation resources in small mountainous watersheds. © 2024 International Research and Training Center on Erosion and Sedimentation and China Water and Power Press. All rights reserved.

Keyword :

Brain Brain Interpolation Interpolation Long short-term memory Long short-term memory Rain Rain Satellites Satellites Spatial distribution Spatial distribution Storms Storms Watersheds Watersheds

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GB/T 7714 Zhan, Changxun , Zhang, Ting , Jiang, Jiawei . Multi-source data-based precipitation fusion model for small mountainous watersheds∗ [J]. | Advances in Water Science , 2024 , 35 (1) : 74-84 .
MLA Zhan, Changxun et al. "Multi-source data-based precipitation fusion model for small mountainous watersheds∗" . | Advances in Water Science 35 . 1 (2024) : 74-84 .
APA Zhan, Changxun , Zhang, Ting , Jiang, Jiawei . Multi-source data-based precipitation fusion model for small mountainous watersheds∗ . | Advances in Water Science , 2024 , 35 (1) , 74-84 .
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Application of Fourier feature physics-information neural network in model of pipeline conveying fluid SCIE
期刊论文 | 2024 , 198 | THIN-WALLED STRUCTURES
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In addressing the intricate dynamic responses of pipeline conveying fluid characterized by spatiotemporal multiscales and multi-modal contributions, Fourier feature-embedded physics-information neural network (FF-PINN) is proposed. By introducing Fourier feature mapping to decompose the temporal and spatial scale information, FF-PINN precisely captures the relatively low-frequencies on the macroscopic time scale as well as the relatively high-frequencies on the microscopic scale of the pipeline's vibration. This approach significantly overcomes the spectral bias encountered by PINN when learning high-frequency information. To verify the effectiveness and accuracy of this method, the proposed FF-PINN is applied to solve the pipeline conveying fluid model with fixed support at both ends. The relative L2 error between the obtained results and the reference solution is 1.8 x 10-2, concurrently with a significant reduction in computational time. Additionally, an analysis of hyperparameter sigma selection is conducted to evaluate its impact on the performance of FF-PINN, while establishing the correspondence between hyperparameter and eigenvector frequency. The results demonstrate that choosing appropriate hyperparameters empowers FF-PINN to better learn the vibration of specific frequencies, enabling the accurate modeling of pipeline vibrations' dynamic response. It provides a potent solution for solving spatiotemporal multi-scale complexity problems involving the superposition of high-and low-frequencies.

Keyword :

Fourier feature Fourier feature Physics-information neural network Physics-information neural network Pipeline conveying fluid Pipeline conveying fluid Spatiotemporal multi-scales Spatiotemporal multi-scales Vibration characteristics Vibration characteristics

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GB/T 7714 Zhang, Ting , Yan, Rui , Zhang, Siqian et al. Application of Fourier feature physics-information neural network in model of pipeline conveying fluid [J]. | THIN-WALLED STRUCTURES , 2024 , 198 .
MLA Zhang, Ting et al. "Application of Fourier feature physics-information neural network in model of pipeline conveying fluid" . | THIN-WALLED STRUCTURES 198 (2024) .
APA Zhang, Ting , Yan, Rui , Zhang, Siqian , Yang, Dingying , Chen, Anhao . Application of Fourier feature physics-information neural network in model of pipeline conveying fluid . | THIN-WALLED STRUCTURES , 2024 , 198 .
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A hydrological process-based neural network model for hourly runoff forecasting SCIE
期刊论文 | 2024 , 176 | ENVIRONMENTAL MODELLING & SOFTWARE
WoS CC Cited Count: 8
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Abstract :

Neural network models have been widely used in runoff forecasting, but are often criticized for their lack of physical interpretability. In this study, we present a simple but useful approach to developing hydrological models by designing neural networks based on the principles of runoff generation and concentration, which we refer to as a Hydrological Process-based Neural Network (HPNN) model. The Convolutional neural network (CNN) and softmax function are used because of their similar formula to the conventional runoff generation and unit hydrograph approach used in hydrology. We apply the HPNN model and four other benchmark models to forecast runoff in two catchments (Yutan and Chenda) in China. Results show that the HPNN model has higher computational efficiency, its parameters are interpretable and closely linked to the processes of runoff generation and concentration, and the HPNN model outperforms conventional GRU-based models.

Keyword :

HPNN model HPNN model Neural network Neural network Physical interpretability Physical interpretability Runoff forecasting Runoff forecasting

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GB/T 7714 Gao, Shuai , Zhang, Shuo , Huang, Yuefei et al. A hydrological process-based neural network model for hourly runoff forecasting [J]. | ENVIRONMENTAL MODELLING & SOFTWARE , 2024 , 176 .
MLA Gao, Shuai et al. "A hydrological process-based neural network model for hourly runoff forecasting" . | ENVIRONMENTAL MODELLING & SOFTWARE 176 (2024) .
APA Gao, Shuai , Zhang, Shuo , Huang, Yuefei , Han, Jingcheng , Zhang, Ting , Wang, Guangqian . A hydrological process-based neural network model for hourly runoff forecasting . | ENVIRONMENTAL MODELLING & SOFTWARE , 2024 , 176 .
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Flash-flood susceptibility mapping: a novel credal decision tree-based ensemble approaches SCIE
期刊论文 | 2023 , 16 (4) , 3143-3161 | EARTH SCIENCE INFORMATICS
WoS CC Cited Count: 4
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Abstract :

Escalation in flash floods and the enhanced devastations, especially in the arid and semiarid regions of the world has required precise mapping of the flash flood susceptible zones. In this study, we applied six novel credal decision tree (CDT)-based ensemble models-1. CDT, 2. CDT Alternative Decision Tree (ADTree), 3. CDT- Reduced Error Pruning Tree (REPT), 4. CDT- Rotational Forest (RF), 5. CDT-FT, 6. CDT- Naive Bias Tree (NBTree). For preparing the flash flood susceptibility maps (FFSM), 206 flood locations were selected in the Neka-roud watershed of Iran with 70% as training data and 30% as testing data. Moreover, 18 flood conditing factors were considered for FFSM and a multi-colinearity test was performed for determining the role of the factors. Our results show that the distance from the stream plays a vital role in flash floods. The CDT-FT is the best-fit model out of the six novel algorithms employed in this study as demonstrated by the highest values of the area under the curve (AUC) of the receiver operating curve (ROC) (AUROC 0.986 for training data and 0.981 for testing data). Our study provides a novel approach and useful tool for flood management.

Keyword :

Credal decision tree Credal decision tree Flash flood mapping Flash flood mapping Flood management Flood management Machine learning algorithms Machine learning algorithms Neka-roud watershed Neka-roud watershed Novel Ensemble models Novel Ensemble models

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GB/T 7714 Yang, Dingying , Zhang, Ting , Arabameri, Alireza et al. Flash-flood susceptibility mapping: a novel credal decision tree-based ensemble approaches [J]. | EARTH SCIENCE INFORMATICS , 2023 , 16 (4) : 3143-3161 .
MLA Yang, Dingying et al. "Flash-flood susceptibility mapping: a novel credal decision tree-based ensemble approaches" . | EARTH SCIENCE INFORMATICS 16 . 4 (2023) : 3143-3161 .
APA Yang, Dingying , Zhang, Ting , Arabameri, Alireza , Santosh, M. , Saha, Ujwal Deep , Islam, Aznarul . Flash-flood susceptibility mapping: a novel credal decision tree-based ensemble approaches . | EARTH SCIENCE INFORMATICS , 2023 , 16 (4) , 3143-3161 .
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Efficient photo-degradation of antibiotics by waste eggshells derived AgBr-CaCO3 heterostructure under visible light SCIE
期刊论文 | 2023 , 314 | SEPARATION AND PURIFICATION TECHNOLOGY
WoS CC Cited Count: 7
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The semiconductors have created a great avenue in visible-light photocatalysis and recently insulator photocatalysis has become an appealing research spot. Herein, a novel waste eggshells derived AgBr-CaCO3 heterostructure was finely designed and constructed through a simple co-precipitation method for efficient antibiotics photo-degradation under visible light. The optimal heterostructure achieved a pseudo-first-order kinetic constant of 6.0 x 10(-2) min(-1) for tetracycline (TC) degradation, with 72 and seven-fold enhancement than eggshell (ES) and AgBr, which also exhibited superior performance towards ofloxacin and sulfamethoxazole. The density functional theory (DFT) calculations revealed that the covalent interaction of Ag-O provided a specific channel for interfacial electrons transfer from the semiconductor to the insulator and thus greatly elevated the photocatalytic activity. The highly selective .CO3- radicals generated by ES, as the main active species, also accelerated the antibiotics degradation. Furthermore, the possible degradation pathways, aquatic toxicity and mutagenicity variation of TC were thoroughly elucidated. This current study illuminated a new pathway for the design of insulator photocatalysts based upon waste solids and demonstrated its application prospect in the field of antibiotics degradation.

Keyword :

AgBr AgBr CaCO3 CaCO3 Heterostructure Heterostructure Tetracycline Tetracycline Visible -light photocatalysis Visible -light photocatalysis

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GB/T 7714 Chen, Qiaoshan , Gao, Ming , Yu, Mingfei et al. Efficient photo-degradation of antibiotics by waste eggshells derived AgBr-CaCO3 heterostructure under visible light [J]. | SEPARATION AND PURIFICATION TECHNOLOGY , 2023 , 314 .
MLA Chen, Qiaoshan et al. "Efficient photo-degradation of antibiotics by waste eggshells derived AgBr-CaCO3 heterostructure under visible light" . | SEPARATION AND PURIFICATION TECHNOLOGY 314 (2023) .
APA Chen, Qiaoshan , Gao, Ming , Yu, Mingfei , Zhang, Ting , Wang, Jianchun , Bi, Jinhong et al. Efficient photo-degradation of antibiotics by waste eggshells derived AgBr-CaCO3 heterostructure under visible light . | SEPARATION AND PURIFICATION TECHNOLOGY , 2023 , 314 .
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A multi-objective optimization strategy for building carbon emission from the whole life cycle perspective SCIE
期刊论文 | 2023 , 262 | ENERGY
WoS CC Cited Count: 35
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Abstract :

This research proposed an integrated strategy for building performance optimization from the whole life cycle perspective to explore the optimal building scheme. After the feature elimination, the ensemble learning model (ELM) was trained to obtain a high-precision model for predicting life cycle carbon emissions (LCCE), life cycle costs (LCC), and indoor discomfort hours (IDH). Then, the optimal optimization algorithm was selected among three different optimization algorithms. Finally, the best building scheme was chosen according to the newly proposed solution. The results showed that the ELM could achieve high prediction efficiency by combining input feature evaluation and screening, multi-sampling methods, and hyperparameter optimization. The R2 value of ELM can reach 0.980, while the Two-Archive Evolutionary Algorithm for Constrained multi-objective optimi-zation (C-TAEA) was the optimal optimization algorithm. The best equilibrium solution proposed in this study solved the problem of different optimization ranges of different objectives and maximized the optimization value. Finally, the best equilibrium scheme reduced the LCCE by 34.7%, the LCC by 13.9%, and the IDH by 26.6%. Therefore, this strategy can efficiently optimize building objectives and produce a more balanced and optimal building scheme, thus making it widely applicable in building performance optimization.

Keyword :

Best equilibrium solution Best equilibrium solution Building performance optimization Building performance optimization Carbon emission Carbon emission Machine learning Machine learning Sensitivity analysis Sensitivity analysis

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GB/T 7714 Chen, Ruijun , Tsay, Yaw-Shyan , Zhang, Ting . A multi-objective optimization strategy for building carbon emission from the whole life cycle perspective [J]. | ENERGY , 2023 , 262 .
MLA Chen, Ruijun et al. "A multi-objective optimization strategy for building carbon emission from the whole life cycle perspective" . | ENERGY 262 (2023) .
APA Chen, Ruijun , Tsay, Yaw-Shyan , Zhang, Ting . A multi-objective optimization strategy for building carbon emission from the whole life cycle perspective . | ENERGY , 2023 , 262 .
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Flash-flood susceptibility mapping: a novel credal decision tree-based ensemble approaches SCIE
期刊论文 | 2023 , 16 (4) , 3143-3161 | EARTH SCIENCE INFORMATICS
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Abstract :

Escalation in flash floods and the enhanced devastations, especially in the arid and semiarid regions of the world has required precise mapping of the flash flood susceptible zones. In this study, we applied six novel credal decision tree (CDT)-based ensemble models-1. CDT, 2. CDT Alternative Decision Tree (ADTree), 3. CDT- Reduced Error Pruning Tree (REPT), 4. CDT- Rotational Forest (RF), 5. CDT-FT, 6. CDT- Naive Bias Tree (NBTree). For preparing the flash flood susceptibility maps (FFSM), 206 flood locations were selected in the Neka-roud watershed of Iran with 70% as training data and 30% as testing data. Moreover, 18 flood conditing factors were considered for FFSM and a multi-colinearity test was performed for determining the role of the factors. Our results show that the distance from the stream plays a vital role in flash floods. The CDT-FT is the best-fit model out of the six novel algorithms employed in this study as demonstrated by the highest values of the area under the curve (AUC) of the receiver operating curve (ROC) (AUROC 0.986 for training data and 0.981 for testing data). Our study provides a novel approach and useful tool for flood management.

Keyword :

Credal decision tree Credal decision tree Flash flood mapping Flash flood mapping Flood management Flood management Machine learning algorithms Machine learning algorithms Neka-roud watershed Neka-roud watershed Novel Ensemble models Novel Ensemble models

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GB/T 7714 Yang, Dingying , Zhang, Ting , Arabameri, Alireza et al. Flash-flood susceptibility mapping: a novel credal decision tree-based ensemble approaches [J]. | EARTH SCIENCE INFORMATICS , 2023 , 16 (4) : 3143-3161 .
MLA Yang, Dingying et al. "Flash-flood susceptibility mapping: a novel credal decision tree-based ensemble approaches" . | EARTH SCIENCE INFORMATICS 16 . 4 (2023) : 3143-3161 .
APA Yang, Dingying , Zhang, Ting , Arabameri, Alireza , Santosh, M. , Saha, Ujwal Deep , Islam, Aznarul . Flash-flood susceptibility mapping: a novel credal decision tree-based ensemble approaches . | EARTH SCIENCE INFORMATICS , 2023 , 16 (4) , 3143-3161 .
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