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剪切带内部应变(率)分析及基于能量准则的失稳判据 被引量:39
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作者 王学滨 潘一山 马瑾 《工程力学》 EI CSCD 北大核心 2003年第2期111-115,共5页
应用应变梯度塑性理论对局部化剪切带内部(塑性)剪应变(率)规律进行了理论分析。研究了剪切降模量及岩石材料内部长度等参数对剪切带内部应变(率)的影响。推导了剪应力(率)与剪切带相对错距(速度)的本构关系。研究了剪切降模量和岩石材... 应用应变梯度塑性理论对局部化剪切带内部(塑性)剪应变(率)规律进行了理论分析。研究了剪切降模量及岩石材料内部长度等参数对剪切带内部应变(率)的影响。推导了剪应力(率)与剪切带相对错距(速度)的本构关系。研究了剪切降模量和岩石材料内部长度对剪切带稳定性的影响。将岩石试件直剪试验试验机简化为钢块,采用能量准则对岩石试件(剪切带)及钢块系统的稳定性进行了理论研究,提出了系统失稳判据。研究表明:岩石材料的剪切降模量越大,岩石材料的内部长度越小,试验机的剪切刚度越小及试验机的等效高度越大剪切带--钢块系统越容易失稳。 展开更多
关键词 应变梯度 应变(率)局部化 剪切带 试验机 失稳判据
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Discrete element simulation of mechanical characteristic of conditioned sands in earth pressure balance shield tunneling 被引量:11
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作者 武力 屈福政 《Journal of Central South University》 SCIE EI CAS 2009年第6期1028-1033,共6页
The discrete element method (DEM) was used to simulate the flow characteristic and strength characteristic of the conditioned sands in the earth pressure balance (EPB) tunneling. In the laboratory the conditioned sand... The discrete element method (DEM) was used to simulate the flow characteristic and strength characteristic of the conditioned sands in the earth pressure balance (EPB) tunneling. In the laboratory the conditioned sands were reproduced and the slump test and the direct shear test of the conditioned sands were implemented. A DEM equivalent model that can simulate the macro mechanical characteristic of the conditioned sands was proposed,and the corresponding numerical models of the slump test and the shear test were established. By selecting proper DEM model parameters,the errors of the slump values between the simulation results and the test results are in the range of 10.3%-14.3%,and the error of the curves between the shear displacement and the shear stress calculated with the DEM simulation is 4.68%-16.5% compared with that of the laboratory direct shear test. This illustrates that the proposed DEM equivalent model can approximately simulate the mechanical characteristics of the conditioned sands,which provides the basis for further simulation of the interaction between the conditioned soil and the chamber pressure system of the EPB machine. 展开更多
关键词 conditioned sands slump test direct shear test discrete element simulation earth pressure balance shield machine
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小型飞剪机现状与发展 被引量:3
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作者 李克涵 《冶金设备》 1994年第6期18-19,29,共3页
本文简要介绍了目前国内外小型飞剪机在设计与发展方面的情况,并就主要几种型式飞剪的性能特点做了定性的分析,指出了它们各自的优点和存在的问题,可供使用者熟悉了解及合理选用。
关键词 飞剪机 机电一体化 离合器 制动器
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基于机器视觉的锥形旋压件起皱缺陷在线检测方法 被引量:6
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作者 李永婷 夏琴香 +1 位作者 肖刚锋 程秀全 《锻压技术》 CAS CSCD 北大核心 2019年第1期134-141,共8页
获取成形缺陷的快速、准确在线检测方法是实现旋压成形智能化的基础。通过对起皱特征和图像识别流程进行研究,提出了一种基于机器视觉的起皱缺陷在线检测方法,并将其应用于锥形件剪切旋压成形过程起皱缺陷的在线检测。构建旋压成形图像... 获取成形缺陷的快速、准确在线检测方法是实现旋压成形智能化的基础。通过对起皱特征和图像识别流程进行研究,提出了一种基于机器视觉的起皱缺陷在线检测方法,并将其应用于锥形件剪切旋压成形过程起皱缺陷的在线检测。构建旋压成形图像在线采集系统,实现成形时旋压件图像的实时获取;利用Halcon软件对图像进行ROI提取、直方图均衡化等预处理,能够获得高对比度的清晰图像;通过Otsu法改进传统Canny边缘检测算法,实现了根据图像梯度自动确定高低阈值,准确地提取出锥形件的图像轮廓。以锥形旋压件起皱后口部轮廓波纹个数及大小为特征,设计了起皱缺陷识别算法,成功检测出锥形件起皱缺陷;并通过剪切旋压实验进行起皱识别算法的可靠性验证。实验结果表明,该方法可以准确、快速地检测出起皱缺陷,平均响应时间为0. 225 s,能够满足实时检测的要求。 展开更多
关键词 锥形件 剪切旋压 起皱缺陷 机器视觉 在线检测
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Prediction of Shear Bond Strength of Asphalt Concrete Pavement Using Machine Learning Models and Grid Search Optimization Technique
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作者 Quynh-Anh Thi Bui Dam Duc Nguyen +2 位作者 Hiep Van Le Indra Prakash Binh Thai Pham 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第1期691-712,共22页
Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement structures.The study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Ext... Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement structures.The study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input parameters.Also,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the models.The models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat rate.Model validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the SBS.Results show that these models accurately predict SBS,with LGBM providing outstanding performance.SHAP(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on SBS.Consequently,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design. 展开更多
关键词 shear bond asphalt pavement grid search OPTIMIZATION machine learning
剪切闸板量化评价方法 被引量:5
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作者 王鹏程 叶玉麟 谢冲 《石油矿场机械》 2016年第3期33-37,共5页
剪切闸板是闸板防喷器的核心部件之一,其技术性能直接关系到整个井控系统工作的可靠性。剪切闸板一旦失效,将可能发生井喷、井涌等严重事故,危及地面人员及装备的安全,增加钻井、完井过程中的作业风险。分析了剪切闸板量化评价方法的意... 剪切闸板是闸板防喷器的核心部件之一,其技术性能直接关系到整个井控系统工作的可靠性。剪切闸板一旦失效,将可能发生井喷、井涌等严重事故,危及地面人员及装备的安全,增加钻井、完井过程中的作业风险。分析了剪切闸板量化评价方法的意义以及目前剪切闸板评价存在的问题,结合现场应用条件,基于机器视觉技术和图像处理技术建立了一套科学、快速、高精度的剪切闸板量化评价方法,为钻井完井的安全作业提供保障,对完善剪切闸板量化检测技术具有一定的指导作用。 展开更多
关键词 剪切闸板 量化评价 机器视觉
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Engineering punching shear strength of flat slabs predicted by nature-inspired metaheuristic optimized regression system
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作者 Dinh-Nhat TRUONG Van-Lan TO +1 位作者 Gia Toai TRUONG Hyoun-Seung JANG 《Frontiers of Structural and Civil Engineering》 SCIE EI CSCD 2024年第4期551-567,共17页
Reinforced concrete(RC)flat slabs,a popular choice in construction due to their flexibility,are susceptible to sudden and brittle punching shear failure.Existing design methods often exhibit significant bias and varia... Reinforced concrete(RC)flat slabs,a popular choice in construction due to their flexibility,are susceptible to sudden and brittle punching shear failure.Existing design methods often exhibit significant bias and variability.Accurate estimation of punching shear strength in RC flat slabs is crucial for effective concrete structure design and management.This study introduces a novel computation method,the jellyfish-least square support vector machine(JS-LSSVR)hybrid model,to predict punching shear strength.By combining machine learning(LSSVR)with jellyfish swarm(JS)intelligence,this hybrid model ensures precise and reliable predictions.The model’s development utilizes a real-world experimental data set.Comparison with seven established optimizers,including artificial bee colony(ABC),differential evolution(DE),genetic algorithm(GA),and others,as well as existing machine learning(ML)-based models and design codes,validates the superiority of the JS-LSSVR hybrid model.This innovative approach significantly enhances prediction accuracy,providing valuable support for civil engineers in estimating RC flat slab punching shear strength. 展开更多
关键词 punching shear strength reinforced concrete flat slabs machine learning jellyfish search support vector machine
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Shear wave velocity prediction:A review of recent progress and future opportunities
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作者 John Oluwadamilola Olutoki Jian-guo Zhao +5 位作者 Numair Ahmed Siddiqui Mohamed Elsaadany AKM Eahsanul Haque Oluwaseun Daniel Akinyemi Amany H.Said Zhaoyang Zhao 《Energy Geoscience》 EI 2024年第4期36-54,共19页
Shear logs,also known as shear velocity logs,are used for various types of seismic analysis,such as determining the relationship between amplitude variation with offset(AVO)and interpreting multiple types of seismic d... Shear logs,also known as shear velocity logs,are used for various types of seismic analysis,such as determining the relationship between amplitude variation with offset(AVO)and interpreting multiple types of seismic data.This log is an important tool for analyzing the properties of rocks and interpreting seismic data to identify potential areas of oil and gas reserves.However,these logs are often not collected due to cost constraints or poor borehole conditions possibly leading to poor data quality,though there are various approaches in practice for estimating shear wave velocity.In this study,a detailed review of the recent advances in the various techniques used to measure shear wave(S-wave)velocity is carried out.These techniques include direct and indirect measurement,determination of empirical relationships between S-wave velocity and other parameters,machine learning,and rock physics models.Therefore,this study creates a collection of employed techniques,enhancing the existing knowledge of this significant topic and offering a progressive approach for practical implementation in the field. 展开更多
关键词 shear wave(S-wave)velocity Direct and indirect measurement Empirical relationship Artificial intelligence(AI) machine learning Rock physics model
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A new integrated intelligent computing paradigm for predicting joints shear strength
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作者 Shijie Xie Zheyuan Jiang +4 位作者 Hang Lin Tianxing Ma Kang Peng Hongwei Liu Baohua Liu 《Geoscience Frontiers》 SCIE CAS CSCD 2024年第6期176-193,共18页
Joints shear strength is a critical parameter during the design and construction of geotechnical engineering structures.The prevailing models mostly adopt the form of empirical functions,employing mathematical regress... Joints shear strength is a critical parameter during the design and construction of geotechnical engineering structures.The prevailing models mostly adopt the form of empirical functions,employing mathematical regression techniques to represent experimental data.As an alternative approach,this paper proposes a new integrated intelligent computing paradigm that aims to predict joints shear strength.Five metaheuristic optimization algorithms,including the chameleon swarm algorithm(CSA),slime mold algorithm,transient search optimization algorithm,equilibrium optimizer and social network search algorithm,were employed to enhance the performance of the multilayered perception(MLP)model.Efficiency comparisons were conducted between the proposed CSA-MLP model and twelve classical models,employing statistical indicators such as root mean square error(RMSE),correlation coefficient(R2),mean absolute error(MAE),and variance accounted for(VAF)to evaluate the performance of each model.The sensitivity analysis of parameters that impact joints shear strength was conducted.Finally,the feasibility and limitations of this study were discussed.The results revealed that,in comparison to other models,the CSA-MLP model exhibited the most appropriate performance in terms of R2(0.88),RMSE(0.19),MAE(0.15),and VAF(90.32%)values.The result of sensitivity analysis showed that the normal stress and the joint roughness coefficient were the most critical factors influencing joints shear strength.This paper presented an efficacious attempt toward swift prediction of joints shear strength,thus avoiding the need for costly in-site and laboratory tests. 展开更多
关键词 Rock discontinuities Joints shear strength Metaheuristic optimization algorithms machine learning
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基于裂缝滑移模型的无腹筋RC梁抗剪承载力计算
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作者 巩忠文 熊二刚 +2 位作者 王文翔 曹涛 付重阳 《华南理工大学学报(自然科学版)》 EI CAS CSCD 北大核心 2024年第5期114-126,共13页
为了考虑翼缘对无腹筋钢筋混凝土(RC)梁抗剪承载力的影响,基于裂缝滑移模型,考虑了受压区的贡献、销栓作用贡献和受拉区骨料咬合作用的贡献,提出了一种无腹筋RC梁抗剪承载力计算公式。为验证该计算公式的准确性,分别应用该公式和国内外... 为了考虑翼缘对无腹筋钢筋混凝土(RC)梁抗剪承载力的影响,基于裂缝滑移模型,考虑了受压区的贡献、销栓作用贡献和受拉区骨料咬合作用的贡献,提出了一种无腹筋RC梁抗剪承载力计算公式。为验证该计算公式的准确性,分别应用该公式和国内外规范对收集的444根矩形截面梁与172根T形截面梁的试验数据进行计算,并将结果与国内外规范计算结果进行对比;基于所收集的数据集,利用5种常用的机器学习算法对收集的数据集进行回归分析,在数据集较小的情况下验证各算法的拟合度。结果表明:各国规范提出的抗剪承载力计算公式与试验值吻合较好;相较于规范的计算方法,该研究提出的计算方法较为准确,且可以有效地考虑T形截面梁翼缘对于抗剪承载力的贡献;选取的5个机器学习算法在测试集上表现良好,且与计算结果表现出了相同的规律,验证了机器学习算法在数据集较小的情况下对钢筋混凝土梁抗剪承载力计算的适用性。 展开更多
关键词 裂缝滑移模型 钢筋混凝土 抗剪承载力 T梁 机器学习
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Ensemble for evaluating diagnostic efficacy of non-invasive indices in predicting liver fibrosis in untreated hepatitis C virus population
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作者 Navneet Kaur Gitanjali Goyal +2 位作者 Ravinder Garg Chaitanya Tapasvi Umit Demirbaga 《World Journal of Methodology》 2024年第3期90-105,共16页
BACKGROUND Hepatitis C virus(HCV)infection progresses through various phases,starting with inflammation and ending with hepatocellular carcinoma.There are several invasive and non-invasive methods to diagnose chronic ... BACKGROUND Hepatitis C virus(HCV)infection progresses through various phases,starting with inflammation and ending with hepatocellular carcinoma.There are several invasive and non-invasive methods to diagnose chronic HCV infection.The invasive methods have their benefits but are linked to morbidity and complications.Thus,it is important to analyze the potential of non-invasive methods as an alternative.Shear wave elastography(SWE)is a non-invasive imaging tool widely validated in clinical and research studies as a surrogate marker of liver fibrosis.Liver fibrosis determination by invasive liver biopsy and non-invasive SWE agree closely in clinical studies and therefore both are gold standards.AIM To analyzed the diagnostic efficacy of non-invasive indices[serum fibronectin,aspartate aminotransferase to platelet ratio index(APRI),alanine aminotransferase ratio(AAR),and fibrosis-4(FIB-4)]in relation to SWE.We have used an Artificial Intelligence method to predict the severity of liver fibrosis and uncover the complex relationship between non-invasive indices and fibrosis severity.METHODS We have conducted a hospital-based study considering 100 untreated patients detected as HCV positive using a quantitative Real-Time Polymerase Chain Reaction assay.We performed statistical and probabilistic analyses to determine the relationship between non-invasive indices and the severity of fibrosis.We also used standard diagnostic methods to measure the diagnostic accuracy for all the subjects.RESULTS The results of our study showed that fibronectin is a highly accurate diagnostic tool for predicting fibrosis stages(mild,moderate,and severe).This was based on its sensitivity(100%,92.2%,96.2%),specificity(96%,100%,98.6%),Youden’s index(0.960,0.922,0.948),area under receiver operating characteristic curve(0.999,0.993,0.922),and Likelihood test(LR+>10 and LR-<0.1).Additionally,our Bayesian Network analysis revealed that fibronectin(>200),AAR(>1),APRI(>3),and FIB-4(>4)were all strongly associated with patients who had severe fibr 展开更多
关键词 Hepatitis C virus Non-invasive biomarkers shear wave elastography FIBRONECTIN Bayesian network machine learning Liver fibrosis
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Shear Deformation of DLC Based on Molecular Dynamics Simulation and Machine Learning
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作者 Chaofan Yao Huanhuan Cao +1 位作者 Zhanyuan Xu Lichun Bai 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第12期2107-2119,共13页
Shear deformation mechanisms of diamond-like carbon(DLC)are commonly unclear since its thickness of several micrometers limits the detailed analysis of its microstructural evolution and mechanical performance,which fu... Shear deformation mechanisms of diamond-like carbon(DLC)are commonly unclear since its thickness of several micrometers limits the detailed analysis of its microstructural evolution and mechanical performance,which further influences the improvement of the friction and wear performance of DLC.This study aims to investigate this issue utilizing molecular dynamics simulation and machine learning(ML)techniques.It is indicated that the changes in the mechanical properties of DLC are mainly due to the expansion and reduction of sp3 networks,causing the stick-slip patterns in shear force.In addition,cluster analysis showed that the sp2-sp3 transitions arise in the stick stage,while the sp3-sp2 transitions occur in the slip stage.In order to analyze the mechanisms governing the bond breaking/re-formation in these transitions,the Random Forest(RF)model in ML identifies that the kinetic energies of sp3 atoms and their velocities along the loading direction have the highest influence.This is because high kinetic energies of atoms can exacerbate the instability of the bonding state and increase the probability of bond breaking/re-formation.Finally,the RF model finds that the shear force of DLC is highly correlated to its potential energy,with less correlation to its content of sp3 atoms.Since the changes in potential energy are caused by the variances in the content of sp3 atoms and localized strains,potential energy is an ideal parameter to evaluate the shear deformation of DLC.The results can enhance the understanding of the shear deformation of DLC and support the improvement of its frictional and wear performance. 展开更多
关键词 Diamond-like carbon shear deformation bond breaking/re-formation molecular dynamics machine learning
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基于机器学习的钢-自燃煤矸石混凝土组合梁栓钉抗剪承载力研究 被引量:2
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作者 王庆贺 张提睿 +2 位作者 李永进 任庆新 包龙生 《沈阳建筑大学学报(自然科学版)》 CAS 北大核心 2023年第2期227-233,共7页
目的确定影响栓钉抗剪承载力的主要因素,量化自燃煤矸石骨料取代率对栓钉抗剪承载力的影响。方法基于机器学习中的随机森林算法,选取影响栓钉抗剪承载力的7个因素作为输入变量、将栓钉抗剪承载力作为输出变量,构建栓钉抗剪承载力预测模... 目的确定影响栓钉抗剪承载力的主要因素,量化自燃煤矸石骨料取代率对栓钉抗剪承载力的影响。方法基于机器学习中的随机森林算法,选取影响栓钉抗剪承载力的7个因素作为输入变量、将栓钉抗剪承载力作为输出变量,构建栓钉抗剪承载力预测模型,并利用现有试验结果验证模型的可靠性,进行输入变量的特征重要性分析;收集现有考虑不同骨料取代率的自燃煤矸石混凝土抗压强度与弹性模量,量化自燃煤矸石骨料取代率对栓钉抗剪承载力的影响。结果基于机器学习建立的模型判定系数R2为0.94、平均绝对误差MAE为10.56、均方误差MSE为180.44、均方根误差RMSE为13.43;栓钉抗剪承载力的影响因素主要为栓钉直径和混凝土抗压强度,而且栓钉直径与混凝土抗压强度对栓钉抗剪承载力的影响存在耦合关系;与普通混凝土试件相比,取代率为25%、50%、75%和100%时栓钉的抗剪承载力平均降低2.49%、4.46%、6.35%和7.31%。结论基于随机森林算法所建立的模型具有较高的预测精度;栓钉直径、混凝土抗压强度是影响栓钉抗剪承载力的主要因素;栓钉抗剪承载力随自燃煤矸石骨料取代率的增加而降低。 展开更多
关键词 组合梁 自燃煤矸石混凝土 抗剪栓钉 抗剪承载力 随机森林 机器学习
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乏燃料模拟组件剪切断裂过程分析 被引量:2
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作者 张迅 王湘江 《南华大学学报(自然科学版)》 2015年第4期27-32,共6页
目前我国乏燃料后处理关键设备之一的剪切机仍存在一些技术性问题,为了进一步合理使用,需要得到详细的剪切力变化趋势、间隙与刀具磨损对剪切力和剪切质量的影响.本文利用ABAQUS软件对乏燃料模拟组件剪切过程进行有限元分析,得到了断裂... 目前我国乏燃料后处理关键设备之一的剪切机仍存在一些技术性问题,为了进一步合理使用,需要得到详细的剪切力变化趋势、间隙与刀具磨损对剪切力和剪切质量的影响.本文利用ABAQUS软件对乏燃料模拟组件剪切过程进行有限元分析,得到了断裂区单元应力、应变趋势和剪切过程中剪切力的变化曲线.通过建立不同间隙和倒角时单根燃料棒剪切的有限元模型,分析了主副刀间隙和刀具磨损对剪切力和剪切质量的影响.并在乏燃料剪切实验装置上进行实验研究,实验结果与模拟结果一致,为乏燃料剪切机的有效应用提供了可靠的依据. 展开更多
关键词 乏燃料 剪切机 剪切断裂 剪切力 实验研究
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激光剪切干涉用于在线表面测量的特性分析 被引量:2
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作者 刘晓军 高咏生 《激光技术》 CAS CSCD 北大核心 2006年第4期337-339,343,共4页
为探讨和证明双折射晶体激光剪切干涉仪用于在线表面精密测量的可能性,推导了该干涉仪中光传输和实现表面测量的模型,分析了其抗振特性,模拟了相当的振动条件对其抗振特性进行实验测试。分析和实验证明了该干涉仪具有良好的抗振能力,适... 为探讨和证明双折射晶体激光剪切干涉仪用于在线表面精密测量的可能性,推导了该干涉仪中光传输和实现表面测量的模型,分析了其抗振特性,模拟了相当的振动条件对其抗振特性进行实验测试。分析和实验证明了该干涉仪具有良好的抗振能力,适合应用于在线表面精密测量。 展开更多
关键词 仪器测量与计量 剪切干涉 在线 分析
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Climatology of Shear Line and Related Rainstorm over the Southern Yangtze River Valley Based on an Improved Intelligent Identification Method 被引量:1
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作者 LIU Jin-qing CHEN He XU Jing-yu 《Journal of Tropical Meteorology》 SCIE 2022年第4期413-424,共12页
Based on four reanalysis datasets including CMA-RA,ERA5,ERA-Interim,and FNL,this paper proposes an improved intelligent method for shear line identification by introducing a second-order zonal-wind shear.Climatic char... Based on four reanalysis datasets including CMA-RA,ERA5,ERA-Interim,and FNL,this paper proposes an improved intelligent method for shear line identification by introducing a second-order zonal-wind shear.Climatic characteristics of shear lines and related rainstorms over the Southern Yangtze River Valley(SYRV)during the summers(June-August)from 2008 to 2018 are then analyzed by using two types of unsupervised machine learning algorithm,namely the t-distributed stochastic neighbor embedding method(t-SNE)and the k-means clustering method.The results are as follows:(1)The reproducibility of the 850 hPa wind fields over the SYRV using China’s reanalysis product CMARA is superior to that of European and American products including ERA5,ERA-Interim,and FNL.(2)Theory and observations indicate that the introduction of a second-order zonal-wind shear criterion can effectively eliminate the continuous cyclonic curvature of the wind field and identify shear lines with significant discontinuities.(3)The occurrence frequency of shear lines appearing in the daytime and nighttime is almost equal,but the intensity and the accompanying rainstorm have a clear diurnal variation:they are significantly stronger during daytime than those at nighttime.(4)Half(47%)of the shear lines can cause short-duration rainstorms(≥20 mm(3h)^(-1)),and shear line rainstorms account for one-sixth(16%)of the total summer short-duration rainstorms.Rainstorms caused by shear lines are significantly stronger than that caused by other synoptic forcing.(5)Under the influence of stronger water vapor transport and barotropic instability,shear lines and related rainstorms in the north and middle of the SYRV are stronger than those in the south. 展开更多
关键词 transverse shear line second-order zonal-wind shear short-duration rainstorm shear line rainstorm unsupervised machine learning
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SPT based determination of undrained shear strength:Regression models and machine learning 被引量:2
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作者 Walid Khalid MBARAK Esma Nur CINICIOGLU Ozer CINICIOGLU 《Frontiers of Structural and Civil Engineering》 SCIE EI CSCD 2020年第1期185-198,共14页
The purpose of this study is the accurate prediction of undrained shear strength using Standard Penetration Test results and soil consistency indices,such as water content and Atterberg limits.With this study,along wi... The purpose of this study is the accurate prediction of undrained shear strength using Standard Penetration Test results and soil consistency indices,such as water content and Atterberg limits.With this study,along with the conventional methods of simple and multiple linear regression models,three machine learning algorithms,random forest,gradient boosting and stacked models,are developed for prediction of undrained shear strength.These models are employed on a relatively large data set from different projects around Turkey covering 230 observations.As an improvement over the available studies in literature,this study utilizes correct statistical analyses techniques on a relatively large database,such as using a train/test split on the data set to avoid overfitting of the developed models.Furthermore,the validity and consistency of the prediction results are ensured with the correct use of statistical measures like p-value and cross-validation which were missing in previous studies.To compare the performances of the models developed in this study with the prior ones existing in literature,all models were applied on the test data set and their performances are evaluated in terms of the resulting root mean squared error(RMSE)values and coefficient of determination(R^2).Accordingly,the models developed in this study demonstrate superior prediction capabilities compared to all of the prior studies.Moreover,to facilitate the use of machine learning algorithms for prediction purposes,entire source code prepared for this study and the collected data set are provided as supplements of this study. 展开更多
关键词 UNDRAINED shear strength linear regression random FOREST gradient BOOSTING machine learning standard PENETRATION test
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液压摆式剪板机主油缸活塞杆侧推力有限元分析 被引量:2
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作者 夏卫明 嵇宽斌 潘世宏 《锻压装备与制造技术》 2009年第5期73-76,共4页
本文针对某型液压摆式剪板机主油缸活塞杆磨损破坏造成液压油的泄漏问题,应用有限元法,将空间三维模型简化为平面应力问题,大大提高了求解的效率和计算的精度。通过对液压缸活塞杆侧推力的有限元分析,得出了活塞杆破坏的位置和侧推力的... 本文针对某型液压摆式剪板机主油缸活塞杆磨损破坏造成液压油的泄漏问题,应用有限元法,将空间三维模型简化为平面应力问题,大大提高了求解的效率和计算的精度。通过对液压缸活塞杆侧推力的有限元分析,得出了活塞杆破坏的位置和侧推力的变化规律。计算表明,减小球头关节和刀架斜垫板接触面的摩擦系数,能降低活塞杆的磨损,利用程序内嵌优化设计模块对刀架处于上极限位置球头关节被卡死的最小摩擦系数进行了求解,得出结论为:该位置上球头关节被卡死的最小摩擦系数为0.17。 展开更多
关键词 机械制造 主油缸活塞杆失效 剪板机 有限元法分析
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生活垃圾破碎机的开发 被引量:2
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作者 王振海 傅磊 +2 位作者 艾洪超 何佩珍 孙希财 《天津科技》 2016年第8期75-77,82,共4页
破碎机作为生活垃圾处理线的一个重要装备,其作用是将大件垃圾破碎成所需尺寸,便于运输、焚烧、制肥、造粒等后续工艺。以往公司的固废处理线上的破碎机都采用进口产品,不仅费用高,供货周期长,且受制于人。经过充分的市场调研和全面的... 破碎机作为生活垃圾处理线的一个重要装备,其作用是将大件垃圾破碎成所需尺寸,便于运输、焚烧、制肥、造粒等后续工艺。以往公司的固废处理线上的破碎机都采用进口产品,不仅费用高,供货周期长,且受制于人。经过充分的市场调研和全面的技术论证,成功开发出了具有独立知识产权的旋转剪切式双轴破碎机,产品获多项中国实用新型专利。 展开更多
关键词 生活垃圾 旋转剪切式 双轴 破碎机
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高温和冲击作用下结构负载测试方法研究及应用 被引量:2
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作者 滑广军 吴运新 +1 位作者 唐宏宾 雷新军 《中南大学学报(自然科学版)》 EI CAS CSCD 北大核心 2011年第7期1981-1985,共5页
以某条钢剪切机剪刃为例,对利用应变测试技术确定高温、冲击作用下结构负载的方法进行研究。通过对剪刃结构的改造改变剪刃的约束状态,提供应变计安装空间;利用静态标定方法确定常温静载下载荷与应变的关系;基于冲击理论、模态分析理论... 以某条钢剪切机剪刃为例,对利用应变测试技术确定高温、冲击作用下结构负载的方法进行研究。通过对剪刃结构的改造改变剪刃的约束状态,提供应变计安装空间;利用静态标定方法确定常温静载下载荷与应变的关系;基于冲击理论、模态分析理论及有限元技术对结构动态特性进行分析,研究冲击波形对测试精度的影响;基于高温应变计热输出和灵敏度温度系数曲线对测试结果进行修正。研究结果表明,对于该结构,静态标定结果能够用于其实际冲击工况下测试数据的分析,冲击响应误差为±0.7%;对应变测试数据的温度修正能够提高对数据的分析精度。 展开更多
关键词 应变电测技术 剪切机 仿真技术 冲击 应力
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