Guanglu Xie¹, Zhimin Xue¹, Bo Xiong¹, Yaowen Huang¹, Chaoming Chen¹, Qing Liao¹, Cheng Yang^2,*, Xiaoqian Ma²

Energy Engineering, Vol.121, No.6, pp. 1495-1519, 2024, DOI:10.32604/ee.2024.047832 - 21 May 2024

Abstract The determination of source-side extracted heating parameters is of great significance to the economic operation of cogeneration systems. This paper investigated the coupling performance of a cogeneration heating and power system multidimensionally based on the operating characteristics of the cogeneration units, the hydraulic and thermodynamic characteristics of the heating network, and the energy loads. Taking a steam network supported by a gas-steam combined cycle cogeneration system as the research case, the interaction effect among the source-side prime movers, the heating networks, and the terminal demand thermal parameters were investigated based on the designed values, the… More >

Yue Mei^1,2,3, Jianwei Deng^1,2, Dongmei Zhao^1,2, Changjiang Xiao^1,2, Tianhang Wang⁴, Li Dong⁵, Xuefeng Zhu^1,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 911-935, 2024, DOI:10.32604/cmes.2023.043810 - 30 December 2023

Abstract Elastography is a non-invasive medical imaging technique to map the spatial variation of elastic properties of soft tissues. The quality of reconstruction results in elastography is highly sensitive to the noise induced by imaging measurements and processing. To address this issue, we propose a deep learning (DL) model based on conditional Generative Adversarial Networks (cGANs) to improve the quality of nonhomogeneous shear modulus reconstruction. To train this model, we generated a synthetic displacement field with finite element simulation under known nonhomogeneous shear modulus distribution. Both the simulated and experimental displacement fields are used to validate More >

Jiepeng Yao^1,2, Zhanjia Peng^1,2, Jingjing Liu^1,2, Chengxiao Fan^1,2, Zhongyi Wang^1,2,3, Lan Huang^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2243-2265, 2023, DOI:10.32604/cmes.2023.028101 - 03 August 2023

Abstract In the establishment of differential equations, the determination of time-varying parameters is a difficult problem, especially for equations related to life activities. Thus, we propose a new framework named BioE-PINN based on a physical information neural network that successfully obtains the time-varying parameters of differential equations. In the proposed framework, the learnable factors and scale parameters are used to implement adaptive activation functions, and hard constraints and loss function weights are skillfully added to the neural network output to speed up the training convergence and improve the accuracy of physical information neural networks. In this… More >

Zhonghai Jiang¹, Qian Wang¹, Liangbing Zhou^2,*, Chun Xiao³

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1693-1708, 2023, DOI:10.32604/fdmp.2023.025270 - 30 January 2023

Abstract A two-layer implicit difference scheme is employed in the present study to determine the temperature distribution in an asphalt pavement. The calculation of each layer only needs four iterations to achieve convergence. Furthermore, in order to improve the calculation accuracy a swarm intelligence optimization algorithm is also exploited to inversely analyze the laws by which the thermal physical parameters of the asphalt pavement materials change with temperature. Using the basic cuckoo and the gray wolf algorithms, an adaptive hybrid optimization algorithm is obtained and used to determine the relationship between the thermal diffusivity of two More >

Haytham A. Ali^1,2,*, Hiroyuki Kudo¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3741-3756, 2022, DOI:10.32604/cmc.2022.029394 - 16 June 2022

Abstract This paper proposes a new level-set-based shape recovery approach that can be applied to a wide range of binary tomography reconstructions. In this technique, we derive generic evolution equations for shape reconstruction in terms of the underlying level-set parameters. We show that using the appropriate basis function to parameterize the level-set function results in an optimization problem with a small number of parameters, which overcomes many of the problems associated with the traditional level-set approach. More concretely, in this paper, we use Gaussian functions as a basis function placed at sparse grid points to represent… More >

Chih-Wen Chang^*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 433-451, 2022, DOI:10.32604/cmc.2022.027021 - 18 May 2022

Abstract We retrieve unknown nonlinear large space-time dependent forces burdened with the vibrating nonlinear Euler-Bernoulli beams under varied boundary data, comprising two-end fixed, cantilevered, clamped-hinged, and simply supported conditions in this study. Even though some researchers used several schemes to overcome these forward problems of Euler-Bernoulli beams; however, an effective numerical algorithm to solve these inverse problems is still not available. We cope with the homogeneous boundary conditions, initial data, and final time datum for each type of nonlinear beam by employing a variety of boundary shape functions. The unknown nonlinear large external force can be… More >

Jianghui Zhu^1,3, Xiaotong Chang², Xueli Zhang², Yutai Su², Xu Long^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1719-1735, 2022, DOI:10.32604/cmes.2022.019140 - 30 December 2021

Abstract The estimation of the disturbance input acting on a vehicle from its given responses is an inverse problem. To overcome some of the issues related to ill-posed inverse problems, this work proposes a method of reconstructing the road roughness based on the Kalman filter method. A half-car model that considers both the vehicle and equipment is established, and the joint input-state estimation method is used to identify the road profile. The capabilities of this methodology in the presence of noise are numerically demonstrated. Moreover, to reduce the influence of the driving speed on the estimation More >

M. J. Huntul^1,*, Taki-Eddine Oussaeif²

Computer Systems Science and Engineering, Vol.40, No.3, pp. 1109-1126, 2022, DOI:10.32604/csse.2022.020175 - 24 September 2021

Abstract In this paper, we consider the unique solvability of the inverse problem of determining the right-hand side of a parabolic equation whose leading coefficient depends on time variable under nonlocal integral overdetermination condition. We obtain sufficient conditions for the unique solvability of the inverse problem. The existence and uniqueness of the solution of the inverse parabolic problem upon the data are established using the fixed point theorem. This inverse problem appears extensively in the modelling of various phenomena in engineering and physics. For example, seismology, medicine, fusion welding, continuous casting, metallurgy, aircraft, oil and gas… More >

M. J. Huntul¹, D. Lesnic^{2, *}

CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.2, pp. 475-494, 2020, DOI:10.32604/cmes.2020.08791 - 01 May 2020

Abstract In this paper, we consider solving numerically for the first time inverse problems of determining the time-dependent thermal diffusivity coefficient for a weakly degenerate heat equation, which vanishes at the initial moment of time, and/or the convection coefficient along with the temperature for a one-dimensional parabolic equation, from some additional information about the process (the so-called over-determination conditions). Although uniquely solvable these inverse problems are still ill-posed since small changes in the input data can result in enormous changes in the output solution. The finite difference method with the Crank-Nicolson scheme combined with the nonlinear More >

Davide Piovesan^{1, *}, Roberto Bortoletto²

CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.1, pp. 23-47, 2020, DOI:10.32604/cmes.2020.09231 - 01 April 2020

Abstract Exoskeletons are designed to control the forces exerted during the physical coupling between the human and the machine. Since the human is an active system, the control of an exoskeleton requires coordinated action between the machine and the load so to obtain a reciprocal adaptation. Humans in the control loop can be modeled as active mechanical loads whose stiffness is continuously changing. The direct measurement of human stiffness is difficult to obtain in real-time, thus posing a significant limitation to the design of wearable robotics controllers. Electromyographic (EMG) recordings can provide an indirect estimation of… More >