检索结果-内蒙古大学图书馆

modeling parameters for Finite Element Simulation of Residual Stress in Cold Spray and the Stress Evolution and Distribution

引用

JOURNAL OF THERMAL SPRAY TECHNOLOGY 2023年第7期32卷 1966-1984页

作者： Meng, Fanchao Fan, Xiaping Chi, Zonglin Chen, Shuying Chu, Xin Yantai Univ Inst Adv Studies Precis Mat Yantai 264005 Shandong Peoples R China Guangdong Acad Sci Inst New Mat Natl Engn Lab Modern Mat Surface Engn Technol Guangzhou 510650 Guangdong Peoples R China

Residual stress is an important factor that affects the properties of cold spray coatings. The study performed 2D single-, 3D single-, and 3D multiple-particle finite element simulations based on the Eulerian method, and hole drilling measurements to study residual stress in cold-sprayed copper coatings. The study examined how the basic modeling parameters affect residual stress in the 2D system. It found that the mesh size, substrate dimension, and simulation duration change the residual stress;while material failure does not have much effect because failure is localized. It also found that thermal softening, which occurs when the initial temperature and/or plastic deformation increase, helps to reduce the residual stress. In addition, the residual stress along the axisymmetric axis of the particle changes from being compressive at first to being compressive-tensile-compressive along the through-depth thickness direction with the interfacial stress being tensile that mainly originates from friction shear of the interfacial layers. For the 3D single-particle simulations, the average residual stress to the through-depth thickness shows tension to compression transition and is similar to the 2D cases. For the 3D multiple-particle simulations, the residual stresses in the coatings/substrate are all compressive because of the repeated and strong impact of the particles, which agree with the experimental measurements. The study also found that the compressive stresses decrease when the coating thickness increases because of more plastic deformation-induced thermal softening. This paper clarifies the effects of Eulerian-based finite element parameters on simulating residual stress in cold spray and will serve as a valuable reference for future studies.

关键词： cold spray finite element analysis hole drilling method modeling parameters residual stress

来源：评论

学校读者我要写书评

暂无评论

Nonlinear modeling parameters of RC coupling beams in a coupled wall system

引用

EARTHQUAKES AND STRUCTURES 2014年第5期7卷 817-842页

作者： Gwon, Seongwoo Shin, Myoungsu Pimentel, Benjamin Lee, Deokjung Ulsan Natl Inst Sci & Technol UNIST Sch Urban & Environm Engn Ulsan South Korea Rosenwasser Grossman Consulting Engineers New York NY USA Ulsan Natl Inst Sci & Technol UNIST Interdisciplinary Sch Green Energy Ulsan South Korea

ASCE/SEI 41-13 provides modeling parameters and numerical acceptance criteria for various types of members that are useful for evaluating the seismic performance of reinforced concrete (RC) building structures. To accurately evaluate the global performance of a coupled wall system, it is crucial to first properly define the component behaviors (i.e., force-displacement relationships of shear walls and coupling beams). However, only a few studies have investigated on the modeling of RC coupling beams subjected to earthquake loading to date. The main objective of this study is to assess the reliability of ASCE 41-13 modeling parameters specified for RC coupling beams with various design details, based on a database compiling almost all coupling beam tests available worldwide. Several recently developed coupling beam models are also reviewed. Finally, a rational method is proposed for determining the chord yield rotation of RC coupling beams.

关键词： ASCE/SEI 41-13 modeling parameters coupling beam chord yield rotation

来源：评论

学校读者我要写书评

暂无评论

Machine learning tools to improve nonlinear modeling parameters of RC columns

引用

JOURNAL OF BUILDING ENGINEERING 2024年 84卷

作者： Koodiani, Hamid Khodadadi Jafari, Elahe Majlesi, Arsalan Shahin, Mohammad Matamoros, Adolfo Alaeddini, Adel Univ Texas San Antonio Civil Engn Dept San Antonio TX 78249 USA Univ Texas San Antonio Mech Engn Dept San Antonio TX USA

modeling parameters are essential to the fidelity of nonlinear models of concrete structures subjected to earthquake ground motions, especially when simulating seismic events strong enough to cause collapse. This paper addresses two of the most significant barriers to improving nonlinear modeling provisions in seismic evaluation standards using experimental data sets: identifying the most likely mode of failure of structural components, and implementing data fitting techniques capable of recognizing interdependencies between input parameters and nonlinear relationships between input parameters and model outputs. Machine learning tools in the Scikit-learn and Pytorch libraries were used to calibrate equations and black -box numerical models for nonlinear modeling parameters (MP) a and b of reinforced concrete columns defined in the ASCE 41 and ACI 369.1 standards, and to estimate their most likely mode of failure. It was found that machine learning regression models and machine learning black -boxes were more accurate than current provisions in the ACI 369.1/ASCE 41 Standards. Among the regression models, Regularized Linear Regression was the most accurate for estimating MP a, and Polynomial Regression was the most accurate for estimating MP b. The two black -box models evaluated, namely the Gaussian Process Regression and the Neural Network (NN), provided the most accurate estimates of MPs a and b. The NN model was the most accurate machine learning tool of all evaluated. A multi -class classification tool from the Scikit-learn machine learning library correctly identified column mode of failure with 79 % accuracy for rectangular columns and with 81 % accuracy for circular columns, a substantial improvement over the classification rules in ASCE 41-13.

关键词： ACI 369.1 ASCE 41 Classification Concrete columns Machine learning Modes of failure modeling parameters Nonlinear response

来源：评论

学校读者我要写书评

暂无评论

Nonlinear modeling parameters of Reinforced Concrete Coupling Beams

引用

ACI STRUCTURAL JOURNAL 2022年第2期119卷 89-101页

作者： Eom, Tae-Sung Lee, Seung-Jae Kang, Su-Min Park, Hong-Gun Dankook Univ Yongin Gyeonggi South Korea Soongsil Univ Seoul South Korea Seoul Natl Univ Dept Architecture & Architectural Engn Seoul South Korea

The present study investigated nonlinear modeling parameters for reinforced concrete coupling beams. Based on a review of the existing test results of 79 coupling beams, modeling parameters of varying aspect ratios and transverse reinforcement ratios were proposed. First, the effective stiffness and yield deformation were formulated as functions of aspect ratio. Second, the deformation capacity varying with reinforcement details was examined, and its design equation was defined as a function of transverse reinforcement ratio. Thud, the energy dissipation ratio to define hysteresis loop under cyclic loading was suggested as a function of aspect ratio and reinforcement details. For verification, the modeling results of load-deformation relations were compared with the existing test results. The predicted load-deformation relations showed good agreement with the test results. Finally, practical applications to computer modeling are discussed.

关键词： coupled wall coupling beam effective stiffness modeling parameters nonlinear modeling

来源：评论

学校读者我要写书评

暂无评论

A study on the effect of different modeling parameters on the dynamic response of a jacket-type offshore wind turbine in the Korean Southwest Sea

引用

RENEWABLE ENERGY 2013年 58卷 50-59页

作者： Shi, Wei Park, Hyunchul Han, Jonghoon Na, Sangkwon Kim, Changwan Konkuk Univ Sch Mech Engn Seoul 143701 South Korea POSTECH Grad Sch Wind Energy Pohang 790784 Kyungbuk South Korea Daewoo Shipbldg & Marine Engn Co Ltd Cent R&D Inst Seoul 135010 South Korea Res Inst Ind Sci & Technol Inchon 406840 South Korea

As a country mostly surrounded by water, Korea has good potential for offshore wind energy utilization. With offshore wind turbines growing larger and with increasing water depth, jacket structures are attracting increased attention because they appear to be cost-effective, but they are still at an early stage of development for use in the offshore wind industry. This paper aims to design a jacket structure to support a 5 MW wind turbine in 33 m deep water for a Korean offshore demonstration project and to investigate the effects of different modeling parameters (including joint can, overlap, flooding of the member, marine growth and mass of the transition piece) on the dynamic response of an offshore wind turbine with a jacket substructure. For this purpose, modal analysis and aero-servo-hydro-elastic simulation with varying modeling parameters are performed under Korean environmental conditions. The results show that joint can, overlap and marine growth strongly affect the dynamic response and there is a small effect on the natural frequencies of the designed structure. Choosing the appropriate transition piece mass may reduce the extreme loads in the members. This study provides applicable knowledge of the utilization of large-scale offshore wind turbines for intermediate water depths in Korea. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Offshore wind turbine Jacket foundation Dynamic response modeling parameters

来源：评论

学校读者我要写书评

暂无评论

modeling parameters and acceptable plastic chord rotations for diagonally reinforced concrete coupling beams

引用

JOURNAL OF BUILDING ENGINEERING 2021年 44卷

作者： Han, Sang Whan Lee, Chang Seok Cho, Eun Seon Hanyang Univ Dept Architectural Engn 222 Wangsimni Ro Seoul 04763 South Korea

Nonlinear analyses are commonly used when evaluating the seismic performance of buildings. To produce reliable results in a seismic performance evaluation, the modeling parameters used in numerical models must be determined accurately for building components. In addition, proper values of acceptance criteria need to be used in the evaluation. In this study, modeling parameters and acceptance criteria for plastic chord rotations are proposed for diagonally reinforced concrete coupling beams (DRCBs). Empirical equations to calculate the values of modeling parameters for DRCBs are proposed by conducting stepwise nonlinear regression analyses with test data of 42 collected DRCB specimens. The proposed equations predicted the measured values of modeling parameters of DRCBs more accurately than the values specified in ASCE 41-16. The acceptance criteria for IO, LS and CP levels are proposed, based on the target exceedance probabilities.

关键词： Coupling beams Nonlinear analysis modeling parameters Acceptance criteria Empirical equation

来源：评论

学校读者我要写书评

暂无评论

Analysis of modeling parameters on Threaded Screws

Analysis of Modeling Parameters on Threaded Screws

引用

作者： Vigil, M. S Brake, M. R Vangoethem, D Sandia National Labs. Albuquerque NM.

Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation properties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connection. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.

关键词： Threaded screws modeling parameters Bolted connections STRUCTURAL DYNAMICS Joints

来源：评论

学校读者我要写书评

暂无评论

modeling and computing parameters of three-dimensional Voronoi models in nonlinear finite element simulation of closed-cell metallic foams

引用

MECHANICS OF ADVANCED MATERIALS AND STRUCTURES 2018年第15-16期25卷 1265-1275页

作者： Zhang, Xiaoyang Wu, Yidong Tang, Liqun Liu, Zejia Jiang, Zhenyu Liu, Yiping Xi, Huifeng South China Univ Technol State Key Lab Subtrop Bldg Sci Sch Civil Engn & Transportat Guangzhou 510640 Guangdong Peoples R China Jinan Univ Inst Appl Mech Guangzhou Guangdong Peoples R China

modeling and computing parameters in nonlinear finite element simulations significantly affect simulation accuracy and efficiency even when it is carried out using commercial software, such as ABAQUS, ANSYS, etc. Yet comprehensive effects of these parameters on simulation results have seldom been reported. In this article, we explore the effects of several important parameters, such as mass scaling type and value, element type and size, and loading velocity, on the accuracy and efficiency of nonlinear finite element simulation of metallic foams based on three-dimensional Voronoi mesostructures. Analysis indicated that these parameters did affect simulation accuracy and efficiency, and three optimized nondimensional parameters were recommended. Based on the verified model and optimized parameters, effects of cell-wall thickness distribution on the uniaxial properties of metallic foams were also investigated. Simulation results showed that the different distribution of cell-wall thickness in modeling may induce varied elastic moduli and yield stress of metal foams. Our analysis showed that modeling and computing parameters must be paid attention to in the nonlinear FE simulation, and that the recommended parameters constitute a good reference for numerical simulation of metallic foams in predicting mechanical behaviors.

关键词： Cell-wall thickness computing parameters metallic foam modeling parameters nonlinear analysis simulation accuracy simulation efficiency

来源：评论

学校读者我要写书评

暂无评论

Error propagation of partial least squares for parameters optimization in NIR modeling

引用

SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2018年 192卷 244-250页

作者： Du, Chenzhao Dai, Shengyun Qiao, Yanjiang Wu, Zhisheng Beijing Univ Chinese Med Beijing 100102 Peoples R China Minist Educ Pharmaceut Engn & New Drug Dev Tradit Chinese Med Beijing 100102 Peoples R China State Adm TCM Key Lab TCM Informat Engn Beijing 100102 Peoples R China

A novel methodology is proposed to determine the error propagation of partial least-square (PIS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type I and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. (C) 2017 Published by Elsevier B.V.

关键词： Error propagation Multivariate detection limits modeling parameters Partial least-squares Near-infrared

来源：评论

学校读者我要写书评

暂无评论

Method of optimization for Target Localization Model parameters Based on LSSVR

引用

International Conference on Computational Materials Science (CMS 2011)

作者： He Xuewen Liu Guixiong Zhu Haibing Zhang Xiaoping S China Univ Technol Dept Mech & Automobile Engn Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9783037851555

Aiming at improving localization accuracy in Wireless Sensor Networks (WSN) based on Least Square Support Vector Regression (LSSVR), making LSSVR localization method more practicable, the mechanism of effects of the kernel function for target localization based on LSSVR is discussed based on the mathematical solution process of LSSVR localization method. A novel method of modeling parameters optimization for LSSVR model using particle swarm optimization is proposed. Construction method of fitness function for modeling parameters optimization is researched. In addition, the characteristics of particle swarm parameters optimization are analyzed. The computational complexity of parameters optimization is taken into consideration comprehensively. Experiments of target localization based on CC2430 show that localization accuracy using LSSVR method with modeling parameters optimization increased by 23%similar to 36% in compare with the maximum likelihood method(MLE) and the localization error is close to the minimum with different LSSVR modeling parameters. Experimental results show that adapting a reasonable fitness function for modeling parameters optimization using particle swarm optimization could enhance the anti-noise ability significantly and improve the LSSVR localization performance.

关键词： Wireless Sensor Networks (WSN) Least Square Support Vector Regression (LSSVR) Target Localization modeling parameters Particle Swarm Optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：