检索结果-南通市图书馆

Identification of partial differential equations from noisy data with integrated knowledge discovery and embedding using evolutionary neural networks

在线全文

学校读者我要写书评

暂无评论

Theoretical & Applied Mechanics Letters 2024年第2期14卷 90-97页

作者： Hanyu Zhou Haochen Li Yaomin Zhao HEDPS Center for Applied Physics and Technologyand College of EngineeringPeking UniversityBeijing 100871China state key laboratory for turbulence and complex systems College of EngineeringPeking UniversityBeijing 100871China

Identification of underlying partial differential equations(PDEs)for complex systems remains a formidable challenge.In the present study,a robust PDE identification method is proposed,demonstrating the ability to extract accurate governing equations under noisy conditions without prior knowledge.Specifically,the proposed method combines gene expression programming,one type of evolutionary algorithm capable of generating unseen terms based solely on basic operators and functional terms,with symbolic regression neural networks.These networks are designed to represent explicit functional expressions and optimize them with data gradients.In particular,the specifically designed neural networks can be easily transformed to physical constraints for the training data,embedding the discovered PDEs to further optimize the metadata used for iterative PDE identification.The proposed method has been tested in four canonical PDE cases,validating its effectiveness without preliminary information and confirming its suitability for practical applications across various noise levels.

关键词： PDE discovery Gene Expression Programming Deep Learning Knowledge embedding

Fast measurement and prediction method for electromagnetic susceptibility of receiver

在线全文

学校读者我要写书评

暂无评论

Journal of systems Engineering and Electronics 2024年第2期35卷 275-285页

作者： CHEN Yan LU Zhonghao LIU Yunxia state key laboratory of complex Electromagnetic Environment Effects on Electronics and Information system College of Electronic Science and TechnologyNational University of Defense TechnologyChangsha 410073China state key laboratory of Astronautic Dynamics Xi’an 710043China

Aiming at evaluating and predicting rapidly and accurately a high sensitivity receiver’s adaptability in complex electromagnetic environments,a novel testing and prediction method based on dual-channel multi-frequency is proposed to improve the traditional two-tone test.Firstly,two signal generators are used to generate signals at the radio frequency(RF)by frequency scanning,and then a rapid measurement at the intermediate frequency(IF)output port is carried out to obtain a huge amount of sample data for the subsequent analysis.Secondly,the IF output response data are modeled and analyzed to construct the linear and nonlinear response constraint equations in the frequency domain and prediction models in the power domain,which provide the theoretical criteria for interpreting and predicting electromagnetic susceptibility(EMS)of the receiver.An experiment performed on a radar receiver confirms the reliability of the method proposed in this paper.It shows that the interference of each harmonic frequency and each order to the receiver can be identified and predicted with the sensitivity model.Based on this,fast and comprehensive evaluation and prediction of the receiver’s EMS in complex environment can be efficiently realized.

关键词： electromagnetic susceptibility(EMS) receiver dualchannel multi-frequency nonlinear response frequency domain power domain

Constrained re-calibration of two-equation Reynolds-averaged Navier–Stokes models

在线全文

学校读者我要写书评

暂无评论

Theoretical & Applied Mechanics Letters 2024年第2期14卷 82-89页

作者： Yuanwei Bin Xiaohan Hu Jiaqi Li Samuel J.Grauer Xiang I.A.Yang Department of Mechanical Engineering Pennsylvania State UniversityUniversity ParkPA 16802USA state key laboratory for turbulence and complex systems Peking UniversityBeijing 100871China College of Engineering Peking UniversityBeijing 100871China

Machine-learned augmentations to turbulence models can be advantageous for flows within the training dataset but can often cause harm outside.This lack of generalizability arises because the constants(as well as the functions)in a Reynolds-averaged Navier–Stokes(RANS)model are coupled,and un-constrained re-calibration of these constants(and functions)can disrupt the calibrations of the baseline model,the preservation of which is critical to the model's generalizability.To safeguard the behaviors of the baseline model beyond the training dataset,machine learning must be constrained such that basic calibrations like the law of the wall are kept intact.This letter aims to identify such constraints in two-equation RANS models so that future machine learning work can be performed without violating these constraints.We demonstrate that the identified constraints are not limiting.Furthermore,they help preserve the generalizability of the baseline model.

关键词： Machine learning turbulence modeling Reynolds-averaged Navier-Stokes

A novel triple periodic minimal surface-like plate lattice and its data-driven optimization method for superior mechanical properties

在线全文

学校读者我要写书评

暂无评论

Applied Mathematics and Mechanics(English Edition) 2024年第2期45卷 217-238页

作者： Yanda WANG Yanping LIAN Zhidong WANG Chunpeng WANG Daining FANG state key laboratory for turbulence and complex systems&Center for Applied Physics and Technology College of EngineeringPeking UniversityBeijing 100871China Institute of Advanced Structure Technology Beijing Institute of TechnologyBeijing 100081China

Lattice structures can be designed to achieve unique mechanical properties and have attracted increasing attention for applications in high-end industrial equipment,along with the advances in additive manufacturing(AM)technologies.In this work,a novel design of plate lattice structures described by a parametric model is proposed to enrich the design space of plate lattice structures with high connectivity suitable for AM processes.The parametric model takes the basic unit of the triple periodic minimal surface(TPMS)lattice as a skeleton and adopts a set of generation parameters to determine the plate lattice structure with different topologies,which takes the advantages of both plate lattices for superior specific mechanical properties and TPMS lattices for high connectivity,and therefore is referred to as a TPMS-like plate lattice(TLPL).Furthermore,a data-driven shape optimization method is proposed to optimize the TLPL structure for maximum mechanical properties with or without the isotropic constraints.In this method,the genetic algorithm for the optimization is utilized for global search capability,and an artificial neural network(ANN)model for individual fitness estimation is integrated for high efficiency.A set of optimized TLPLs at different relative densities are experimentally validated by the selective laser melting(SLM)fabricated samples.It is confirmed that the optimized TLPLs could achieve elastic isotropy and have superior stiffness over other isotropic lattice structures.

关键词： lattice structure triple periodic minimal surface(TPMS) plate lattice structural optimization machine learning

Investigation on the influence of vortex generator on particle resuspension

在线全文

学校读者我要写书评

暂无评论

Particuology 2024年第3期86卷 126-136页

作者： Dongchi Yu Jun-Li Lin Jin-Han Xie ASML 80W Tasman DrSan Jose95134CaliforniaUSA Department of Mechanics and Engineering Science at College of Engineering and state key laboratory for turbulence and complex systems Peking UniversityBeijing100081China

The vortex generator(VG)and its well-known effect in flow optimization are widely studied and employed across different engineering sectors.However,while the same working principles of VG may be well suited for the applications on surface-cleaning technologies,such promising potential is hardly,if any,explored in the published literature.Therefore,in the present study,the influence on flow-induced particle resuspension brought by a rectangular vG in a channel flow is investigated with the help of highfidelity computational fluid dynamics simulations.Substantial increases of particle removal forces and resuspension rates are discovered in long,strip-like regions with reduced boundary-layer thickness resulted from the vG-induced vortices,and the enhancement effect is especially significant for configurations with the VG installed at a greater angle of attack.It is also shown that while the resuspension enhancements on the lower and the upper surfaces of the channel exhibit distinct statistical characteristics,having a VG in the channel improves the overall particle-removing capability of the channel flow by introducing higher surface-averaged removal forces and particle resuspension rates.Last but not least,the increase of resuspension rate is especially significant for the smaller,micron-scale particles which are otherwise hardly disturbed by a VG-less channel flow,and such resuspension-enhancement effectgenerally subsides with increasing particle size.

关键词： Particle resuspension Vortexgenerator CFD Surface cleaning

On the Polygonal Wear Evolution of Heavy-Haul Locomotive Wheels due to Wheel/Rail Flexibility and Its Mitigation Measures

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Mechanical Engineering 2024年第1期37卷 40-61页

作者： Yunfan Yang Feifan Chai Pengfei Liu Liang Ling Kaiyun Wang Wanming Zhai state key laboratory of Mechanical Behavior and system Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang 050043China state key laboratory of Rail Transit Vehicle system Southwest Jiaotong UniversityChengdu 610031China

Wheel polygonal wear can immensely worsen wheel/rail interactions and vibration performances of the train and track,and ultimately,lead to the shortening of service life of railway components.At present,wheel/rail medium-or high-frequency frictional interactions are perceived as an essential reason of the high-order polygonal wear of railway wheels,which are potentially resulted by the flexible deformations of the train/track system or other external excitations.In this work,the effect of wheel/rail flexibility on polygonal wear evolution of heavy-haul locomotive wheels is explored with aid of the long-term wheel polygonal wear evolution simulations,in which different flexible modeling of the heavy-haul wheel/rail coupled system is implemented.Further,the mitigation measures for the polygonal wear of heavy-haul locomotive wheels are discussed.The results point out that the evolution of polygonal wear of heavy-haul locomotive wheels can be veritably simulated with consideration of the flexible effect of both wheelset and rails.Execution of mixed-line operation of heavy-haul trains and application of multicut wheel re-profiling can effectively reduce the development of wheel polygonal wear.This research can provide a deep-going understanding of polygonal wear evolution mechanism of heavy-haul locomotive wheels and its mitigation measures.

关键词： Heavy-haul locomotive Wheel polygonal wear Wheel/rail flexibility Long-term polygonal wear evolution Mitigation measures

Parallel system Based Quantitative Assessment and Self-evolution for Artificial Intelligence of Active Power Corrective Control

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

CSEE Journal of Power and Energy systems 2024年第1期10卷 13-28页

作者： Tianyun Zhang Jun Zhang Feiyue Wang Peidong Xu Tianlu Gao Haoran Zhang Ruiqi Si School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072HubeiChina state key laboratory for Management and Control of complex system Institute of AutomationChinese Academy of SciencesBeijing 100190China

In artificial intelligence(AI)based-complex power system management and control technology,one of the urgent tasks is to evaluate AI intelligence and invent a way of autonomous intelligence evolution.However,there is,currently,nearly no standard technical framework for objective and quantitative intelligence evaluation.In this article,based on a parallel system framework,a method is established to objectively and quantitatively assess the intelligence level of an AI agent for active power corrective control of modern power systems,by resorting to human intelligence evaluation theories.On this basis,this article puts forward an AI self-evolution method based on intelligence assessment through embedding a quantitative intelligence assessment method into automated reinforcement learning(AutoRL)systems.A parallel system based quantitative assessment and self-evolution(PLASE)system for power grid corrective control AI is thereby constructed,taking Bayesian Optimization as the measure of AI evolution to fulfill autonomous evolution of AI under guidance of their intelligence assessment results.Experiment results exemplified in the power grid corrective control AI agent show the PLASE system can reliably and quantitatively assess the intelligence level of the power grid corrective control agent,and it could promote evolution of the power grid corrective control agent under guidance of intelligence assessment results,effectively,as well as intuitively improving its intelligence level through selfevolution.

关键词： AI quantitative intelligence assessment and self-evolution automated reinforcement learning Bayesian optimization corrective control parallel system

Influence of vibration on the lubrication effect of a splash-lubricated gearbox

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2024年第4期25卷 324-339页

作者： Yi LIU Kailin ZHANG Shuai SHAO Hongxu XIANG Zhijian YE state key laboratory of Rail Transit Vehicle system Southwest Jiaotong UniversityChengdu 610031China

In this study,we investigate the effect of rail vibrations on the lubrication and efficiency of a splash-lubricated gearbox;specifically,the gearbox of a rail-transit vehicle.A high-fidelity 3D numerical model of the gearbox in a moving reference system is described,as well as computational fluid dynamics(CFD)simulations of the gearbox with different vibration directions.The effects of rotational speed,oil-immersion depth,and different oil-injection volume rates on lubrication and efficiency are discussed.We propose a method of evaluating the internal lubrication condition of a splash-lubricated gearbox and quantitatively compare the effects of different operating parameters on lubrication and efficiency.Finally,our experiment to verify the feasibility of the simulation method is described.The results show that with vibration,the churning loss and oil supply for the bearings are significantly higher than those under static conditions.In addition,among different vibrational directions,lateral vibration has the greatest influence on the lubrication condition and efficiency of the gearbox.For the studied railway-vehicle gearbox,the best lubrication condition is achieved at a rotational speed of 1600 r/min and an oil-immersion depth of two times the tooth height(2.Oh).Rotational speed is the operating parameter that has the most significant effect on the lubrication and efficiencyofthegearbox.

关键词： Comprehensive lubrication evaluation Churning loss Moving reference system Splash lubrication Vibrational excitation Gearbox

A novel domain decomposition-based model for efficient dynamic predictions of large composite machine tools

在线全文

学校读者我要写书评

暂无评论

Science China Technological Sciences 2024年第6期67卷 1765-1782页

作者： YU YangBo JI Yu Lei CHEN YanRen XU Kun BI QingZhen state key laboratory of Mechanical system and Vibration School of Mechanical EngineeringShanghai Jiao Tong University

We propose a large combined moving component composed of carbon fiber reinforced polymer(CFRP) laminates for making lightweight machine tools with high dynamic performance. The accurate dynamic prediction of composite machine tools is essential for the new generation machine tool. This paper aims to address two challenges in numerical dynamic modeling and the design of composite machine tools to enhance development efficiency.(1) Anisotropic composite laminates, which form the composite machine tool, exhibit coupling in various directions. We propose the generalized continuity condition of the boundary to tackle this dynamic modeling challenge.(2) Composite machine tools feature numerous composite-metal coupled structures.The mechanical model correction of isotropic metals is performed to address their dynamics. We take the example of a five-axis gantry machine tool with composite moving parts, establish a dynamic model for efficient prediction, and verify it through simulation and experimentation. The proposed method yields remarkable results, with an average relative error of only 3.85% in modal frequency prediction and a staggering 99.7% reduction in solution time compared to finite element analysis. We further discuss the dynamic performance of the machine tool under varied stacking angles and layer numbers of the composite machine tool. We propose general design criteria for composite machine tools to consider the modal frequency and manufacturing cost of machine tools.

关键词： machine tool dynamics carbon fiber reinforced polymer composite laminates