A novel approach for distributed dynamic load reconstruction by space–time domain decoupling

2015 ◽  
Vol 348 ◽  
pp. 137-148 ◽  
Author(s):  
Kun Li ◽  
Jie Liu ◽  
Xu Han ◽  
Xingsheng Sun ◽  
Chao Jiang
Keyword(s):  
Time Domain ◽  
Dynamic Load ◽  
Space Time ◽  
Novel Approach

scholarly journals Modeling Transient Flows in Heterogeneous Layered Porous Media Using the Space–Time Trefftz Method

2021 ◽  
Vol 11 (8) ◽  
pp. 3421
Author(s):  
Cheng-Yu Ku ◽  
Li-Dan Hong ◽  
Chih-Yu Liu ◽  
Jing-En Xiao ◽  
Wei-Po Huang
Keyword(s):  
Porous Media ◽  
Time Domain ◽  
Numerical Solutions ◽  
Space Time ◽  
Two Dimensional ◽  
Transient Flows ◽  
Layered Porous Media ◽  
Time Marching ◽  
Time Basis ◽  
Marching Scheme

In this study, we developed a novel boundary-type meshless approach for dealing with two-dimensional transient flows in heterogeneous layered porous media. The novelty of the proposed method is that we derived the Trefftz space–time basis function for the two-dimensional diffusion equation in layered porous media in the space–time domain. The continuity conditions at the interface of the subdomains were satisfied in terms of the domain decomposition method. Numerical solutions were approximated based on the superposition principle utilizing the space–time basis functions of the governing equation. Using the space–time collocation scheme, the numerical solutions of the problem were solved with boundary and initial data assigned on the space–time boundaries, which combined spatial and temporal discretizations in the space–time manifold. Accordingly, the transient flows through the heterogeneous layered porous media in the space–time domain could be solved without using a time-marching scheme. Numerical examples and a convergence analysis were carried out to validate the accuracy and the stability of the method. The results illustrate that an excellent agreement with the analytical solution was obtained. Additionally, the proposed method was relatively simple because we only needed to deal with the boundary data, even for the problems in the heterogeneous layered porous media. Finally, when compared with the conventional time-marching scheme, highly accurate solutions were obtained and the error accumulation from the time-marching scheme was avoided.

Plumpness Analysis of Indicator Diagram for Vehicle Damper

2013 ◽  
Vol 415 ◽  
pp. 582-585
Author(s):  
Xing Xu ◽  
Zhen Cui ◽  
Jin Chao Zhang
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Dynamic Load ◽  
Performance Indicators ◽  
Load Distribution ◽  
The Body ◽  
Quantitative Index ◽  
Indicator Diagram ◽  
Vehicle Demand ◽  
Mathematical Relationships

According to the indicator diagram of damper, the indicator diagram plumpness was proposed as a quantitative index, and its mathematical relationships with the sprung mass acceleration, suspension dynamic travel and tire dynamic load were built. Moreover, the influence of the total area on suspension characteristics was analyzed in time domain and frequency domain. The results show that, the increase of the indicator diagram plumpness can effectively restrain the variation of suspension dynamic travel and tire dynamic load, meanwhile, the body acceleration will be enlarged. Excessive indicator diagram plumpness also affects the dynamic tire load distribution in frequency domain, and it will decrease the driving security. Therefore, it should be reasonably selected from the performance indicators, which is based on the requirement of vehicle demand in the design process.

scholarly journals Space-Time Domain Tensor Neural Networks: An Application on Human Pose Classification

2021 ◽  
Author(s):  
Konstantinos Makantasis ◽  
Athanasios Voulodimos ◽  
Anastasios Doulamis ◽  
Nikolaos Bakalos ◽  
Nikolaos Doulamis
Keyword(s):  
Neural Networks ◽  
Time Domain ◽  
Space Time ◽  
Human Pose

scholarly journals A Denoising Autoencoder-Based Bearing Fault Diagnosis System for Time-Domain Vibration Signals

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yi Gu ◽  
Jiawei Cao ◽  
Xin Song ◽  
Jian Yao
Keyword(s):  
Fault Diagnosis ◽  
Time Domain ◽  
Rolling Bearing ◽  
Rolling Bearings ◽  
Bp Network ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Novel Approach ◽  
Fault Diagnosis System ◽  
Original Time

The condition monitoring of rotating machinery is always a focus of intelligent fault diagnosis. In view of the traditional methods’ excessive dependence on prior knowledge to manually extract features, their limited capacity to learn complex nonlinear relations in fault signals and the mixing of the collected signals with environmental noise in the course of the work of rotating machines, this article proposes a novel approach for detecting the bearing fault, which is based on deep learning. To effectively detect, locate, and identify faults in rolling bearings, a stacked noise reduction autoencoder is utilized for abstracting characteristic from the original vibration of signals, and then, the characteristic is provided as input for backpropagation (BP) network classifier. The results output by this classifier represent different fault categories. Experimental results obtained on rolling bearing datasets show that this method can be used to effectively diagnose bearing faults based on original time-domain signals.

Complex Permittivity and Thickness Evaluation of Low-Loss Dielectrics From Uncalibrated Free-Space Time-Domain Measurements

2021 ◽  
pp. 1-10
Author(s):  
Ugur Cem Hasar ◽  
Yunus Kaya ◽  
Hamdullah Ozturk ◽  
Mucahit Izginli ◽  
Joaquim Jose Barroso ◽  
...  
Keyword(s):  
Time Domain ◽  
Complex Permittivity ◽  
Free Space ◽  
Space Time ◽  
Low Loss ◽  
Thickness Evaluation

A Multi-Field Space-Time Finite Element Method for Structural Acoustics

1995 ◽  
Author(s):  
Lonny L. Thompson
Keyword(s):  
Finite Element ◽  
Time Domain ◽  
Acoustic Waves ◽  
Space Time ◽  
High Order ◽  
Elastic Structure ◽  
Structural Acoustics ◽  
Field Representation ◽  
Element Discretization ◽  
Acoustic Fluid

Abstract A Computational Structural Acoustics (CSA) capability for solving scattering, radiation, and other problems related to the acoustics of submerged structures has been developed by employing some of the recent algorithmic trends in Computational Fluid Dynamics (CFD), namely time-discontinuous Galerkin Least-Squares finite element methods. Traditional computational methods toward simulation of acoustic radiation and scattering from submerged elastic bodies have been primarily based on frequency domain formulations. These classical time-harmonic approaches (including boundary element, finite element, and finite difference methods) have been successful for problems involving a limited range of frequencies (narrow band response) and scales (wavelengths) that are large compared to the characteristic dimensions of the elastic structure. Attempts at solving large-scale structural acoustic systems with dimensions that are much larger than the operating wavelengths and which are complex, consisting of many different components with different scales and broadband frequencies, has revealed limitations of many of the classical methods. As a result, there has been renewed interest in new innovative approaches, including time-domain approaches. This paper describes recent advances in the development of a new class of high-order accurate and unconditionally stable space-time methods for structural acoustics which employ finite element discretization of the time domain as well as the usual discretization of the spatial domain. The formulation is based on a space-time variational equation for both the acoustic fluid and elastic structure together with their interaction. Topics to be discussed include the development and implementation of higher-order accurate non-reflecting boundary conditions based on the exact impedance relation through the. Dirichlet-to-Neumann (DtN) map, and a multi-field representation for the acoustic fluid based on independent pressure and velocity potential variables. Numerical examples involving radiation and scattering of acoustic waves are presented to illustrate the high-order accuracy achieved by the new methodology for CSA.

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