Lei Wang^1,2,*, Yuxin Qi^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 325-339, 2023, DOI:10.32604/cmes.2022.019730 - 29 September 2022

Abstract Currently, energy conservation draws wide attention in industrial manufacturing systems. In recent years, many studies have aimed at saving energy consumption in the process of manufacturing and scheduling is regarded as an effective approach. This paper puts forwards a multi-objective stochastic parallel machine scheduling problem with the consideration of deteriorating and learning effects. In it, the real processing time of jobs is calculated by using their processing speed and normal processing time. To describe this problem in a mathematical way, a multi-objective stochastic programming model aiming at realizing makespan and energy consumption minimization is formulated. More >

Roberto Bellas^{1, *}, Javier Martínez¹, Ignacio Rivera², Ramón Touza², Miguel Gómez¹, Rafael Carreño¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.3, pp. 971-995, 2020, DOI:10.32604/cmes.2020.07530 - 01 March 2020

Abstract The study of emergency evacuation in public spaces, buildings and large ships may present parallel characteristic in terms of complexity of the layout but there are also significant differences that can hindering passengers to reach muster stations or the lifeboats. There are many hazards on a ship that can cause an emergency evacuation, the most severe result in loss of lives. Providing safe and effective evacuation of passengers from ships in an emergency situation becomes critical. Recently, computer simulation has become an indispensable technology in various fields, among them, the evacuation models that recently evolved… More >

Wei Huang^∗, Jun Shi^†, R. T. Yen^†,‡

Molecular & Cellular Biomechanics, Vol.9, No.4, pp. 269-284, 2012, DOI:10.3970/mcb.2012.009.269

Abstract The objective of our study was to develop a computing program for computing the transit time frequency distributions of red blood cell in human pulmonary circulation, based on our anatomic and elasticity data of blood vessels in human lung. A stochastic simulation model was introduced to simulate blood flow in human pulmonary circulation. In the stochastic simulation model, the connectivity data of pulmonary blood vessels in human lung was converted into a probability matrix. Based on this model, the transit time of red blood cell in human pulmonary circulation and the output blood pressure were More >

C.-D. Tran¹, N. Mai-Duy^1,1, K. Le-Cao¹, T. Tran-Cong¹

CMES-Computer Modeling in Engineering & Sciences, Vol.85, No.6, pp. 499-520, 2012, DOI:10.3970/cmes.2012.085.499

Abstract A numerical computation of continuum-microscopic model for visco-elastic flows based on the Integrated Radial Basis Function (IRBF) Control Volume and the Stochastic Simulation Techniques (SST) is reported in this paper. The macroscopic flow equations are closed by a stochastic equation for the extra stress at the microscopic level. The former are discretised by a 1D-IRBF-CV method while the latter is integrated with Euler explicit or Predictor-Corrector schemes. Modelling is very efficient as it is based on Cartesian grid, while the integrated RBF approach enhances both the stability of the procedure and the accuracy of the More >

C.-D. Tran¹, D.-A. An-Vo¹, N. Mai-Duy¹, T. Tran-Cong¹

CMES-Computer Modeling in Engineering & Sciences, Vol.82, No.2, pp. 137-162, 2011, DOI:10.32604/cmes.2011.082.137

Abstract This paper presents a numerical approach for macro-micro multi-scale modelling of visco-elastic fluid flows based on the Integrated Radial Basis Function Networks (IRBFNs) and the Stochastic Simulation Technique (SST). The extra stress is calculated using the Brownian configuration fields (BCFs) technique while the velocity field is locally approximated at a set of collocation points using 1D-IRBFNs. In this approach, the stress is decoupled from the velocity field and computed from the molecular configuration directly without the need for a closed form rheological constitutive equation. The equations governing the macro flow field are discretised using a More >

Tae-Hyuk Ahn¹, Layne T. Watson^1,2, Yang Cao^1,1, Clifford A. Shaffer¹, William T. Baumann³

CMES-Computer Modeling in Engineering & Sciences, Vol.51, No.1, pp. 27-52, 2009, DOI:10.3970/cmes.2009.051.027

Abstract For biochemical systems, where some chemical species are represented by small numbers of molecules, discrete and stochastic approaches are more appropriate than continuous and deterministic approaches. The continuous deterministic approach using ordinary differential equations is adequate for understanding the average behavior of cells, while the discrete stochastic approach accurately captures noisy events in the growth-division cycle. Since the emergence of the stochastic simulation algorithm (SSA) by Gillespie, alternative algorithms have been developed whose goal is to improve the computational efficiency of the SSA. This paper explains and empirically compares the performance of some of these More >