Hongsheng Su, Shilin Song^*, Xingsheng Wang

Energy Engineering, Vol.121, No.11, pp. 3289-3303, 2024, DOI:10.32604/ee.2024.054643 - 21 October 2024

Abstract This paper introduces the Particle Swarm Optimization (PSO) algorithm to enhance the Latin Hypercube Sampling (LHS) process. The key objective is to mitigate the issues of lengthy computation times and low computational accuracy typically encountered when applying Monte Carlo Simulation (MCS) to LHS for probabilistic trend calculations. The PSO method optimizes sample distribution, enhances global search capabilities, and significantly boosts computational efficiency. To validate its effectiveness, the proposed method was applied to IEEE34 and IEEE-118 node systems containing wind power. The performance was then compared with Latin Hypercubic Important Sampling (LHIS), which integrates significant sampling More >

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 >

Delfina Arancio Sidoti^1,2, Juan Manuel Zeberio^1,3,*, Guadalupe Peter^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.8, pp. 2115-2125, 2024, DOI:10.32604/phyton.2024.053483 - 30 August 2024

Abstract Argentina is the country with the highest proportion of arid and semi-arid ecosystems in Latin America. In the rangelands of Southwestern Buenos Aires (Patagones Department), there is a clear advancement of the agricultural frontier to the detriment of the native forest in this region. Due to rainfall variation and seed acquisition, Thinopyrum ponticum is cultivated as a forage perennial crop in this region. Our objective was to evaluate the performance of T. ponticum as a facilitating crop for the medium-term rehabilitation of natural grasslands in semi-arid areas. The working hypotheses were that: 1) native perennial grass cover… More >

Ping Yang¹, Pengyang Zhao^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.010047

Abstract Composite materials may be subjected to an extreme condition where the surface is exposed to high-energy photon radiation (e.g., laser radiation), which can cause severe damage and destruction of the structure component. How the radiation energy is deposited in the composite material can greatly influence the subsequent damage process, which may include local heating, phase transformation, heat-induced shock waves, plasticity, etc. While the interaction of high-energy photons with homogeneous materials have been well studied, it is still a challenge to model the photon transport in composite materials, which have been increasingly used in more and… More >

Heba S. Mohammed¹, Mazen Nassar^2,3, Refah Alotaibi¹, Ahmed Elshahhat^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2761-2793, 2023, DOI:10.32604/cmes.2023.028826 - 03 August 2023

Abstract A new extended exponential lifetime model called Harris extended-exponential (HEE) distribution for data modelling with increasing and decreasing hazard rate shapes has been considered. In the reliability context, researchers prefer to use censoring plans to collect data in order to achieve a compromise between total test time and/or test sample size. So, this study considers both maximum likelihood and Bayesian estimates of the Harris extended-exponential distribution parameters and some of its reliability indices using a progressive Type-II censoring strategy. Under the premise of independent gamma priors, the Bayesian estimation is created using the squared-error and… More >

Junling Qiu^*, Huihui Sun, Shuya Wang

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2077-2109, 2023, DOI:10.32604/cmes.2023.027353 - 03 August 2023

Abstract As indispensable components of superconducting circuit-based quantum computers, Josephson junctions determine how well superconducting qubits perform. Reverse Monte Carlo (RMC) can be used to recreate Josephson junction’s atomic structure based on experimental data, and the impact of the structure on junctions’ properties can be investigated by combining different analysis techniques. In order to build a physical model of the atomic structure and then analyze the factors that affect its performance, this paper briefly reviews the development and evolution of the RMC algorithm. It also summarizes the modeling process and structural feature analysis of the Josephson More >

Vivash Karki¹, Roseline Mostafa², Bhaskaran Gopalakrishnan^2,*, Derek R. Johnson³

Energy Engineering, Vol.120, No.2, pp. 561-586, 2023, DOI:10.32604/ee.2023.025218 - 29 November 2022

Abstract Building Energy Management Systems (BEMS) are computer-based systems that aid in managing, controlling, and monitoring the building technical services and energy consumption by equipment used in the building. The effectiveness of BEMS is dependent upon numerous factors, among which the operational characteristics of the building and the BEMS control parameters also play an essential role. This research develops a user-driven simulation tool where users can input the building parameters and BEMS controls to determine the effectiveness of their BEMS. The simulation tool gives the user the flexibility to understand the potential energy savings by employing… More > Graphic Abstract

Qingqing Li^1,2, Zhiwen Duan^1,2,*, Dandan Yang^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 155-168, 2023, DOI:10.32604/cmes.2022.019249 - 29 September 2022

Abstract With the development of molecular imaging, Cherenkov optical imaging technology has been widely concerned. Most studies regard the partial boundary flux as a stochastic variable and reconstruct images based on the steadystate diffusion equation. In this paper, time-variable will be considered and the Cherenkov radiation emission process will be regarded as a stochastic process. Based on the original steady-state diffusion equation, we first propose a stochastic partial differential equation model. The numerical solution to the stochastic partial differential model is carried out by using the finite element method. When the time resolution is high enough, More >

Nima Pirhadi¹, Xusheng Wan¹, Jianguo Lu¹, Jilei Hu^2,3,*, Mahmood Ahmad^4,5, Farzaneh Tahmoorian⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 733-754, 2023, DOI:10.32604/cmes.2022.022207 - 29 September 2022

Abstract Liquefaction is one of the most destructive phenomena caused by earthquakes, which has been studied in the issues of potential, triggering and hazard analysis. The strain energy approach is a common method to investigate liquefaction potential. In this study, two Artificial Neural Network (ANN) models were developed to estimate the liquefaction resistance of sandy soil based on the capacity strain energy concept (W) by using laboratory test data. A large database was collected from the literature. One group of the dataset was utilized for validating the process in order to prevent overtraining the presented model. To… More >

Hong Zhang¹, Lukai Song^1,2,*, Guangchen Bai¹

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1871-1897, 2023, DOI:10.32604/cmes.2022.021880 - 20 September 2022

Abstract

The reliability and sensitivity analyses of stator blade regulator usually involve complex characteristics like high-nonlinearity, multi-failure regions, and small failure probability, which brings in unacceptable computing efficiency and accuracy of the current analysis methods. In this case, by fitting the implicit limit state function (LSF) with active Kriging (AK) model and reducing candidate sample pool with adaptive importance sampling (AIS), a novel AK-AIS method is proposed. Herein, the AK model and Markov chain Monte Carlo (MCMC) are first established to identify the most probable failure region(s) (MPFRs), and the adaptive kernel density estimation (AKDE) importance sampling

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