Pai Liu^1,*, Weida Wu¹, Yangjun Luo¹, Yifan Zhang¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09893

Abstract Lightweight metamaterials with negative Poisson’s ratios (NPRs) have great potential for controlling deformation, absorbing energy, etc. The topology optimization [1] technique is an effective way to design metamaterials. However, as studied in [2], the NPR metamaterial configuration obtained under small deformation assumption may not maintain the desired Poisson’s ratio under relatively large deformation conditions. This paper focuses on the large-deformation NPR metamaterial design based on a gradient-free topology optimization method, i.e. the material-field series expansion (MFSE) method [3]. The metamaterial’s performance is evaluated using the finite element method, taking into account the geometry nonlinearity. By considering the spatial correlation of… More >

Cho Mar Aye¹, Kittinan Wansaseub², Sumit Kumar³, Ghanshyam G. Tejani⁴, Sujin Bureerat¹, Ali R. Yildiz⁵, Nantiwat Pholdee^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2111-2128, 2023, DOI:10.32604/cmes.2023.028632

Abstract This work presents multi-fidelity multi-objective infill-sampling surrogate-assisted optimization for airfoil shape optimization. The optimization problem is posed to maximize the lift and drag coefficient ratio subject to airfoil geometry constraints. Computational Fluid Dynamic (CFD) and XFoil tools are used for high and low-fidelity simulations of the airfoil to find the real objective function value. A special multi-objective sub-optimization problem is proposed for multiple points infill sampling exploration to improve the surrogate model constructed. To validate and further assess the proposed methods, a conventional surrogate-assisted optimization method and an infill sampling surrogate-assisted optimization criterion are applied with multi-fidelity simulation, while their… More > Graphic Abstract

Jiawei Zhang^*, Qing Wang, Hongchun Huang, Haige Wang, Guodong Ji, Meng Cui, Hongyuan Zhang

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.9, pp. 2305-2314, 2023, DOI:10.32604/fdmp.2023.026304

Abstract Formation pressure is the key parameter for the analysis of wellbore safety. With increasing drilling depth, however, the behavior of this variable becomes increasingly complex. In this work, a 3D model of the formation pressure under uncertainty is presented. Moreover a relevant algorithm is elaborated. First, the logging data of regional key drilling wells are collected and a one-dimensional formation pressure profile along the well depth is determined. Then, a 3D model of regional formation pressure of the hierarchical group layer is defined by using the Kriging interpolation algorithm relying on a support vector machine (SVM) and the formation pressure… More >

Nazia Afrin^a,*, Jonathan Lopez, Juan Ocampo

Frontiers in Heat and Mass Transfer, Vol.18, pp. 1-7, 2022, DOI:10.5098/hmt.18.46

Abstract Large number of numerical computer simulations in engineering places is a serious burden on associated optimization problems nowadays. Kriging Surrogate based optimization (KSBO) becomes standard practice in analyzing expensive and time-consuming simulation. This paper aims to investigate the surrogate based analyze and optimization of thermal damage in living biological tissue by laser irradiation using a generalized duel phase model. The relationships of maximum temperature and thermal damage in living biological tissues of the response with two variables at a time are studied. The result shows that the surrogate model predicted response variables i.e, temperature and thermal damage are in good… More >

Qiang Qin^1,2,*, Xiaolei Cao¹, Shengpeng Zhang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1457-1480, 2023, DOI:10.32604/cmes.2023.022078

Abstract In this work, an improved active kriging method based on the AK-IS and truncated importance sampling (TIS) method is proposed to efficiently evaluate structural reliability. The novel method called AWK-TIS is inspired by AK-IS and RBF-GA previously published in the literature. The innovation of the AWK-TIS is that TIS is adopted to lessen the sample pool size significantly, and the whale optimization algorithm (WOA) is employed to acquire the optimal Kriging model and the most probable point (MPP). To verify the performance of the AWK-TIS method for structural reliability, four numerical cases which are utilized as benchmarks in literature and… 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

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 function is constructed to… More >

Christy James Jose^1,*, M. S. Rajasree²

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1357-1372, 2023, DOI:10.32604/csse.2023.025672

Abstract The predominant method for smart phone accessing is confined to methods directing the authentication by means of Point-of-Entry that heavily depend on physiological biometrics like, fingerprint or face. Implicit continuous authentication initiating to be loftier to conventional authentication mechanisms by continuously confirming users’ identities on continuing basis and mark the instant at which an illegitimate hacker grasps dominance of the session. However, divergent issues remain unaddressed. This research aims to investigate the power of Deep Reinforcement Learning technique to implicit continuous authentication for mobile devices using a method called, Gaussian Weighted Cauchy Kriging-based Continuous Czekanowski’s (GWCK-CC). First, a Gaussian Weighted… More >

Yang Liu^1,3, Xiaoyu Liu^2,3, Xiu Dai¹, Guanglian Xun¹, Ni Ren^1,*, Rui Kang^1,4, Xiaojuan Mao¹

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1653-1663, 2022, DOI:10.32604/iasc.2022.017049

Abstract Environmental parameters such as air temperature (T) and air relative humidity (RH) should be intensively monitored in a greenhouse in real time. In most cases, one set of sensors is installed in the centre of a greenhouse. However, as the microclimate of a greenhouse is always heterogeneous, the sensor installation location is crucial for practical cultivation. In this study, the T and RH monitoring performance of different sensors were compared. Two types of real-time environmental sensors (Air Temperature and Humidity sensor and Activity Monitoring sensor, referred as ATH and AM) were selected and calibrated by reliable non-real-time sensors (Honest Observer… More >

Da Teng¹, Yunwen Feng^1,*, Cheng Lu^1,2, Chengwei Fei², Jiaqi Liu¹, Xiaofeng Xue^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 1029-1049, 2021, DOI:10.32604/cmes.2021.016945

Abstract Turbine blisks are assembled using blades, disks and casings. They can endure complex loads at a high temperature, high pressure and high speed. The safe operation of assembled structures depends on the reliability of each component. Monte Carlo (MC) simulation is commonly used to analyze structural reliability, but this method needs to run thousands of computations. In order to assess the clearance reliability of assembled structures in an efficient and precise manner, the novel Kriging-based decomposed-coordinated (DC) (DCNK) approach is proposed by integrating the DC strategy, the Kriging model and the importance sampling-based Markov chain (MCIS) technique. In this method,… More >

Shufang Song^1,*, Ruyang He¹, Zhaoyin Shi¹, Weiya Zhang²

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 65-85, 2021, DOI:10.32604/cmes.2021.015378

Abstract The variable importance measure (VIM) can be implemented to rank or select important variables, which can effectively reduce the variable dimension and shorten the computational time. Random forest (RF) is an ensemble learning method by constructing multiple decision trees. In order to improve the prediction accuracy of random forest, advanced random forest is presented by using Kriging models as the models of leaf nodes in all the decision trees. Referring to the Mean Decrease Accuracy (MDA) index based on Out-of-Bag (OOB) data, the single variable, group variables and correlated variables importance measures are proposed to establish a complete VIM system… More >