Zhao Zhang^1,*, Xiang Gao¹, Yifei Wang¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.012115

Abstract Wire arc additive manufacturing (WAAM) reveals its high efficiency for the fabrications in comparison with laser additive manufacturing. To reveal the relationship between arc settings and the microstructural evolutions, phase field model and Monte Carlo model are established for the simulation of the microstructural evolutions and dislocation dynamics model is established for the simulation of the anisotropic properties in WAAM. Numerical results are compared with Experiments to validate the proposed models. The length/width ratio of the formed grains in solidification becomes smaller when the scanning speed is decreased or the input powder is increased. The… More >

Jian-Guo Hu^1,*, Shao-Yi Wu^1,*, Yi Yang¹, Qin-Sheng Zhu¹, Xiao-Yu Li¹, Shan Yang²

Journal of Quantum Computing, Vol.4, No.1, pp. 53-61, 2022, DOI:10.32604/jqc.2022.027683 - 12 August 2022

Abstract As one of the major methods for the simulation of option pricing, Monte Carlo method assumes random fluctuations in the distribution of asset prices. Under certain uncertainties process, different evolution paths could be simulated so as to finally yield the expectation value of the asset price, which requires a lot of simulations to ensure the accuracy based on huge and expensive calculations. In order to solve the above computational problem, quantum Monte Carlo (QMC) has been established and applied in the relevant systems such as European call options. In this work, both MC and QM More >

Qi Wu^*, Jianan Li, Lianchun Long, Linao Liu

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 99-116, 2021, DOI:10.32604/cmes.2021.015669 - 24 August 2021

Abstract During heat treatment or mechanical processing, most polycrystalline materials experience grain growth, which significantly affects their mechanical properties. Microstructure simulation on a mesoscopic scale is an important way of studying grain growth. A key research focus of this type of method has long been how to efficiently and accurately simulate the grain growth caused by a non-uniform temperature field with temperature gradients. In this work, we propose an improved 3D Monte Carlo Potts (MCP) method to quantitatively study the relationship between non-uniform temperature fields and final grain morphologies. Properties of the aluminum alloy AA6061-T6 are… More >

Quanjia Zuo¹, Fanyi Meng^1,*, Yang Bai²

Energy Engineering, Vol.118, No.2, pp. 303-322, 2021, DOI:10.32604/EE.2021.013239 - 23 December 2020

Abstract As one of the most important commodity futures, the price forecasting of natural gas futures is of great significance for hedging and risk aversion. This paper mainly focuses on natural gas futures pricing which considers seasonality fluctuations. In order to study this issue, we propose a modified approach called six-factor model, in which the influence of seasonal fluctuations are eliminated in every random factor. Using Monte Carlo method, we first assess and comparative analyze the fitting ability of three-factor model and six-factor model for the out of sample data. It is found that six-factor model More >

Hui Sheng Lim^1,*, Christopher K. H. Chin¹, Shuhong Chai¹, Neil Bose^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 33-50, 2020, DOI:10.32604/cmes.2020.011648 - 18 September 2020

Abstract This paper presents an online AUV (autonomous underwater vehicle) path planner that employs path replanning approach and the SDEQPSO (selective differential evolution-hybridized quantum-behaved particle swarm optimization) algorithm to optimize an AUV mission conducted in an unknown, dynamic and cluttered ocean environment. The proposed path replanner considered the effect of ocean currents in path optimization to generate a Pareto-optimal path that guides the AUV to its target within minimum time. The optimization was based on the onboard sensor data measured from the environment, which consists of a priori unknown dynamic obstacles and spatiotemporal currents. Different sensor… More >

Meiling Zhuang^1,2,3, Changqing Miao^1,2,*, Rongfeng Chen^1,2

Structural Durability & Health Monitoring, Vol.14, No.1, pp. 51-79, 2020, DOI:10.32604/sdhm.2020.07663 - 01 March 2020

Abstract Taizhou Yangtze River Bridge as a long-span suspension bridge, the finite element model (FEM) of it is established using the ANSYS Software. The beam4 element is used to simulate the main beam to establish the “spine beam” model of the Taizhou Yangtze River Bridge. The calculated low-order vibration mode frequency of the FEM is in good agreement with the completion test results. The model can simulate the overall dynamic response of the bridge. Based on the vehicle load survey, the Monte Carlo method is applied to simulate the traffic load flow. Then the overall dynamic… More >

Chen Ding¹, Guizhi Wang^1,*, Qi Liu²

Journal on Big Data, Vol.1, No.2, pp. 55-69, 2019, DOI:10.32604/jbd.2019.06110

Abstract Haze concentration prediction, especially PM2.5, has always been a significant focus of air quality research, which is necessary to start a deep study. Aimed at predicting the monthly average concentration of PM2.5 in Beijing, a novel method based on Monte Carlo model is conducted. In order to fully exploit the value of PM2.5 data, we take logarithmic processing of the original PM2.5 data and propose two different scales of the daily concentration and the daily chain development speed of PM2.5 respectively. The results show that these data are both approximately normal distribution. On the basis… More >

D. C. Knupp^1,2, A. J. Silva Neto³

CMES-Computer Modeling in Engineering & Sciences, Vol.96, No.5, pp. 339-360, 2013, DOI:10.3970/cmes.2013.096.339

Abstract Inverse radiative transfer problems in heterogeneous participating media applications include determining gas properties in combustion chambers, estimating environmental and atmospheric conditions, and remote sensing, among others. In recent papers the spatially variable single scattering albedo has been estimated by expanding this unknown function as a series of known functions, and then estimating the expansion coefficients with parameter estimation techniques. In the present work we assume that there is no prior information on the functional form of the unknown spatially variable albedo and, making use of the Bayesian approach, we propose the development of a posterior… More >

Xinhua Liu^1,2, Yongzhi Liu¹, Hao Liu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.91, No.1, pp. 65-80, 2013, DOI:10.3970/cmes.2013.091.065

Abstract In order to study the rheological characteristics of magnetorheological fluids, a simulation approach through integration of Monte Carlo method and GPU accelerated technology was proposed and the three-dimensional micro-structure of magnetic particles in different strength magnetic fields were simulated. The Monte Carlo method to magnetic particles of magnetorheological fluids and its key steps such as particle modeling, magnetic energy equations calculating and system state updating were elaborated. Moreover, GPU accelerated technology was applied to the simulation of magnetorheological fluids to reduce computational time and a flowchart for the proposed approach was designed. Finally, a physics More >

C. Wang¹, W. Gao¹, C.W. Yang¹, C.M. Song¹

CMC-Computers, Materials & Continua, Vol.25, No.1, pp. 19-46, 2011, DOI:10.3970/cmc.2011.025.019

Abstract The random interval response and probabilistic interval reliability of structures with a mixture of random and interval properties are studied in this paper. Structural stiffness matrix is a random interval matrix if some structural parameters and loads are modeled as random variables and the others are considered as interval variables. The perturbation-based stochastic finite element method and random interval moment method are employed to develop the expressions for the mean value and standard deviation of random interval structural displacement and stress responses. The lower bound and upper bound of the mean value and standard deviation More >