Theoretical and Applied Mechanics Letters最新文献_第9页

Exit problem of stochastic SIR model with limited medical resource 有限医疗资源下随机SIR模型的退出问题

IF 3.4 3区工程技术

Theoretical and Applied Mechanics Letters Pub Date : 2023-01-01 DOI: 10.1016/j.taml.2022.100393

Y.C. Mao, X.B. Liu

引用次数: 1

Stability analysis of the projectile based on random center manifold reduction 基于随机中心流形约简的弹丸稳定性分析

IF 3.4 3区工程技术

Theoretical and Applied Mechanics Letters Pub Date : 2023-01-01 DOI: 10.1016/j.taml.2022.100385

Yong Huang, Chunyan Yang

引用次数: 0

Effect of leading-edge tubercles on the flow over low-aspect-ratio wings at low Reynolds number 前缘圆管对低雷诺数低展弦比机翼流动的影响

IF 3.4 3区工程技术

Theoretical and Applied Mechanics Letters Pub Date : 2023-01-01 DOI: 10.1016/j.taml.2022.100386

Pengxin Yang, Yichen Zhu, Jinjun Wang

引用次数: 1

A review on stress determination and control in metal-based additive manufacturing 金属基增材制造中应力测定与控制研究进展

IF 3.4 3区工程技术

Theoretical and Applied Mechanics Letters Pub Date : 2023-01-01 DOI: 10.1016/j.taml.2022.100396

Haoyang Luo , Xing Sun , Le Xu , Wei He , Xiaoyu Liang

引用次数: 2

Artificial neural network-based subgrid-scale models for LES of compressible turbulent channel flow 基于人工神经网络的可压缩湍流通道LES亚网格模型

IF 3.4 3区工程技术

Theoretical and Applied Mechanics Letters Pub Date : 2023-01-01 DOI: 10.1016/j.taml.2022.100399

Qingjia Meng , Zhou Jiang , Jianchun Wang

{"title":"Artificial neural network-based subgrid-scale models for LES of compressible turbulent channel flow","authors":"Qingjia Meng , Zhou Jiang , Jianchun Wang","doi":"10.1016/j.taml.2022.100399","DOIUrl":"10.1016/j.taml.2022.100399","url":null,"abstract":"<div><p>Fully connected neural networks (FCNNs) have been developed for the closure of subgrid-scale (SGS) stress and SGS heat flux in large-eddy simulations of compressible turbulent channel flow. The FCNN-based SGS model trained using data with Mach number <span><math><mrow><mi>M</mi><mi>a</mi><mo>=</mo><mn>3.0</mn></mrow></math></span> and Reynolds number <span><math><mrow><mi>R</mi><mi>e</mi><mo>=</mo><mn>3000</mn></mrow></math></span> was applied to situations with different Mach numbers and Reynolds numbers. The input variables of the neural network model were the filtered velocity gradients and temperature gradients at a single spatial grid point. The <em>a priori</em> test showed that the FCNN model had a correlation coefficient larger than 0.91 and a relative error smaller than 0.43, with much better reconstructions of SGS unclosed terms than the dynamic Smagorinsky model (DSM). In <em>a posteriori</em> test, the behavior of the FCNN model was marginally better than that of the DSM in predicting the mean velocity profiles, mean temperature profiles, turbulent intensities, total Reynolds stress, total Reynolds heat flux, and mean SGS flux of kinetic energy, and outperformed the Smagorinsky model.</p></div>","PeriodicalId":46902,"journal":{"name":"Theoretical and Applied Mechanics Letters","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42455273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Artificial neural network-based one-equation model for simulation of laminar-turbulent transitional flow 基于人工神经网络的层流-湍流过渡流单方程模拟

IF 3.4 3区工程技术

Theoretical and Applied Mechanics Letters Pub Date : 2023-01-01 DOI: 10.1016/j.taml.2022.100387

Lei Wu , Bing Cui , Zuoli Xiao

{"title":"Artificial neural network-based one-equation model for simulation of laminar-turbulent transitional flow","authors":"Lei Wu , Bing Cui , Zuoli Xiao","doi":"10.1016/j.taml.2022.100387","DOIUrl":"https://doi.org/10.1016/j.taml.2022.100387","url":null,"abstract":"<div><p>A mapping function between the Reynolds-averaged Navier-Stokes mean flow variables and transition intermittency factor is constructed by fully connected artificial neural network (ANN), which replaces the governing equation of the intermittency factor in transition-predictive Spalart-Allmaras (SA)-<span><math><mi>γ</mi></math></span> model. By taking SA-<span><math><mi>γ</mi></math></span> model as the benchmark, the present ANN model is trained at two airfoils with various angles of attack, Mach numbers and Reynolds numbers, and tested with unseen airfoils in different flow states. The <em>a posteriori</em> tests manifest that the mean pressure coefficient, skin friction coefficient, size of laminar separation bubble, mean streamwise velocity, Reynolds shear stress and lift/drag/moment coefficient from the present two-way coupling ANN model almost coincide with those from the benchmark SA-<span><math><mi>γ</mi></math></span> model. Furthermore, the ANN model proves to exhibit a higher calculation efficiency and better convergence quality than traditional SA-<span><math><mi>γ</mi></math></span> model.</p></div>","PeriodicalId":46902,"journal":{"name":"Theoretical and Applied Mechanics Letters","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49709032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

New algorithm of shape-finding of suspension bridge with spatial cables 具有空间索的悬索桥寻形新算法

IF 3.4 3区工程技术

Theoretical and Applied Mechanics Letters Pub Date : 2023-01-01 DOI: 10.1016/j.taml.2022.100402

Xiao-Kang Deng , Zhuo Deng , Xin Ren

引用次数: 0

Predicting solutions of the Lotka‐Volterra equation using hybrid deep network 利用混合深度网络预测Lotka‐Volterra方程的解

IF 3.4 3区工程技术

Theoretical and Applied Mechanics Letters Pub Date : 2022-11-01 DOI: 10.1016/j.taml.2022.100384

Zi-Fei Lin , Yan-Ming Liang , Jia-Li Zhao , Jiao-Rui Li

{"title":"Predicting solutions of the Lotka‐Volterra equation using hybrid deep network","authors":"Zi-Fei Lin , Yan-Ming Liang , Jia-Li Zhao , Jiao-Rui Li","doi":"10.1016/j.taml.2022.100384","DOIUrl":"10.1016/j.taml.2022.100384","url":null,"abstract":"<div><p>Prediction of Lotka-Volterra equations has always been a complex problem due to their dynamic properties. In this paper, we present an algorithm for predicting the Lotka-Volterra equation and investigate the prediction for both the original system and the system driven by noise. This demonstrates that deep learning can be applied in dynamics of population. This is the first study that uses deep learning algorithms to predict Lotka-Volterra equations. Several numerical examples are presented to illustrate the performances of the proposed algorithm, including Predator nonlinear breeding and prey competition systems, one prey and two predator competition systems, and their respective systems. All the results suggest that the proposed algorithm is feasible and effective for predicting Lotka-Volterra equations. Furthermore, the influence of the optimizer on the algorithm is discussed in detail. These results indicate that the performance of the machine learning technique can be improved by constructing the neural networks appropriately.</p></div>","PeriodicalId":46902,"journal":{"name":"Theoretical and Applied Mechanics Letters","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2095034922000642/pdfft?md5=206b18bf31ec90ab00a5aa32543d0d0b&pid=1-s2.0-S2095034922000642-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41553026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Influence of physical parameters on the collapse of a spherical bubble 物理参数对球形气泡崩塌的影响

IF 3.4 3区工程技术

Theoretical and Applied Mechanics Letters Pub Date : 2022-11-01 DOI: 10.1016/j.taml.2022.100369

Bo-Hua Sun

引用次数: 0

Numerical simulation of laser ultrasonic detection of the surface microdefects on laser powder bed fusion additive manufactured 316L stainless steel 激光超声检测316L不锈钢表面微缺陷的数值模拟

IF 3.4 3区工程技术

Theoretical and Applied Mechanics Letters Pub Date : 2022-11-01 DOI: 10.1016/j.taml.2022.100398

Yang Liu , Zhixin Peng , Sheng Liu , Ping Hu

{"title":"Numerical simulation of laser ultrasonic detection of the surface microdefects on laser powder bed fusion additive manufactured 316L stainless steel","authors":"Yang Liu , Zhixin Peng , Sheng Liu , Ping Hu","doi":"10.1016/j.taml.2022.100398","DOIUrl":"10.1016/j.taml.2022.100398","url":null,"abstract":"<div><p>A numerical model is presented in this article to investigate the interactions between laser generated ultrasonic and the microdefects (0.01 to 0.1 mm), which are on the surface of the laser powder bed fusion additive manufactured 316L stainless steel. Firstly, the influence of the transient sound field and detection positions on Rayleigh wave signals are investigated. The interactions between the varied microdefects and the laser ultrasonic are studied. It is shown that arrival time of reflected Rayleigh (RR) waves wave is only related to the location of defects. The depth can be checked from the feature point Q, the displacement amplitude and time delay of converted transverse (RS) wave, while the width information can be evaluated from the RS wave time delay. With the aid of fitting curves, it is found to be linearly related. This simulation study provides a theoretical basis for quantitative detection of surface microdefects of additive manufactured 316L stainless steel components.</p></div>","PeriodicalId":46902,"journal":{"name":"Theoretical and Applied Mechanics Letters","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2095034922000782/pdfft?md5=63604a6a53c0a05319279df70aa597b2&pid=1-s2.0-S2095034922000782-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46778561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2