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  • Open Access

    ARTICLE

    EFFECT OF DIFFERENT SHAPES ON CHARACTERISTICS OF CONJUGATE HEAT TRANSFER OF MICRO CHANNEL HEAT SINK

    Ankit Kanor, R Manimaran*

    Frontiers in Heat and Mass Transfer, Vol.7, pp. 1-5, 2016, DOI:10.5098/hmt.7.25

    Abstract One of the effective liquid cooling techniques for microelectronic devices is attaching micro channel heat sink to the inactive side of chip. A micro channel heat sink is a device that decreases temperature by flowing coolant through micro channels. The present study focuses on the conjugate heat transfer analyses for different cross-sections (trapezoidal, hexagonal, octagonal and circular).After present study is validated with the published result in the literature, the comparative study of parallel and counter flow configuration is performed. Different geometries are modeled using CATIA V5 software and simulated in ANSYS Fluent R14. From these CFD simulations, preferred configuration of… More >

  • Open Access

    ARTICLE

    Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

    Xiaoyan Su1,*, Shuwen Shang1, Zhihui Xu2, Hong Qian1, Xiaolei Pan1

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1813-1826, 2024, DOI:10.32604/cmes.2023.030957

    Abstract With the improvement of equipment reliability, human factors have become the most uncertain part in the system. The standardized Plant Analysis of Risk-Human Reliability Analysis (SPAR-H) method is a reliable method in the field of human reliability analysis (HRA) to evaluate human reliability and assess risk in large complex systems. However, the classical SPAR-H method does not consider the dependencies among performance shaping factors (PSFs), which may cause overestimation or underestimation of the risk of the actual situation. To address this issue, this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the… More > Graphic Abstract

    Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

  • Open Access

    PROCEEDINGS

    Comprehensive Simulation of Hot Shape Rolling by Considering the Casting Defects

    Umut Hanoglu1,2,*, Božidar Šarler1,2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09610

    Abstract In this research, a rolling simulation system based on a novel meshless solution procedure is upgraded considering casting defects in the material model. The improved model can predict the final stage of the defects after multi-pass rolling. The casted steel billet that enters the rolling mill arrives with casting defects. Those defects may be porosity due to the shrinkage and cavity or micro-cracks near the surface due to hot tearing. In this work, porosity is considered the main defect source since it can easily be determined experimentally. The damage theory develops a damaged stiffness matrix with a scalar damage value.… More >

  • Open Access

    PROCEEDINGS

    On the Fatigue Crack Initiation in Metallic Sealing Rings: From Manufacture to Service

    Pandi Zhao1, Zebang Zheng1,*, Mei Zhan1, Hongwei Li1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09508

    Abstract Metallic sealing rings made from nickel-based superalloys are critical components of aero engines that prevent the leakage of high-pressure liquid or gas fuel. As one of the main failure modes, fatigue cracking has been a concern for the aerospace industries because the formation of even a micro-crack may cause an aviation accident. For the purpose of manufacturing fatigue-resisting sealing rings, much effort has been spent on the lifetime predicting under fatigue loadings. However, the fatigue analysis of metallic sealing rings is challenging due to several aspects. On the one hand, the diameter of the rings (>100mm) is orders of magnitude… More >

  • Open Access

    PROCEEDINGS

    Robust Shape Optimization of Sound Barriers Based on Isogeometric Boundary Element Method and Polynomial Chaos Expansion

    Xuhang Lin1, Haibo Chen1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09388

    Abstract As an important and useful tool for reducing noise, the sound barrier is of practical significance. The sound barrier has different noise reduction effects for different sizes, shapes and properties of the sound absorbing material. Liu et al. [1] have performed shape optimization of sound barriers by using isogeometric boundary element method and method of moving asymptotes (MMA). However, in engineering practice, it is difficult to determine some parameters accurately such as material properties, geometries, external loads. Therefore, it is necessary to consider these uncertainty conditions in order to ensure the rationality of the numerical calculation of engineering problems. In… More >

  • Open Access

    ARTICLE

    Fusion of Feature Ranking Methods for an Effective Intrusion Detection System

    Seshu Bhavani Mallampati1, Seetha Hari2,*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1721-1744, 2023, DOI:10.32604/cmc.2023.040567

    Abstract Expanding internet-connected services has increased cyberattacks, many of which have grave and disastrous repercussions. An Intrusion Detection System (IDS) plays an essential role in network security since it helps to protect the network from vulnerabilities and attacks. Although extensive research was reported in IDS, detecting novel intrusions with optimal features and reducing false alarm rates are still challenging. Therefore, we developed a novel fusion-based feature importance method to reduce the high dimensional feature space, which helps to identify attacks accurately with less false alarm rate. Initially, to improve training data quality, various preprocessing techniques are utilized. The Adaptive Synthetic oversampling… More >

  • Open Access

    ARTICLE

    Explainable Artificial Intelligence-Based Model Drift Detection Applicable to Unsupervised Environments

    Yongsoo Lee, Yeeun Lee, Eungyu Lee, Taejin Lee*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1701-1719, 2023, DOI:10.32604/cmc.2023.040235

    Abstract Cybersecurity increasingly relies on machine learning (ML) models to respond to and detect attacks. However, the rapidly changing data environment makes model life-cycle management after deployment essential. Real-time detection of drift signals from various threats is fundamental for effectively managing deployed models. However, detecting drift in unsupervised environments can be challenging. This study introduces a novel approach leveraging Shapley additive explanations (SHAP), a widely recognized explainability technique in ML, to address drift detection in unsupervised settings. The proposed method incorporates a range of plots and statistical techniques to enhance drift detection reliability and introduces a drift suspicion metric that considers… More >

  • Open Access

    PROCEEDINGS

    A Shape Optimization Approach for 3D Doubly-Periodic Multi-Layered Systems

    Haibo Chen1,*, Fuhang Jiang1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09414

    Abstract Acoustic wave propagation has been the subject of many studies in engineering and physics. Researchers have shown an increased interest in recent years in the acoustic scattering of periodic systems, such as phononic crystals and metamaterials [1]. These artificial periodic systems possess some particular acoustic characteristics including noise control, waveguides and negative refraction, which manifest excellent potential applicability in acoustic engineering. Based on the isogeometric acoustic boundary element method (BEM) [2], an efficient shape optimization approach is proposed in this research for threedimensional doubly-periodic multi-layered systems. The interfaces between different acoustic mediums are infinite doubly periodic surfaces, which can be… More >

  • Open Access

    PROCEEDINGS

    Inertial and Particle Shape Effects on Fluid-Particle Suspension Flows: A Resolved SPH-DEM Study

    Yueting Li1,*, Ning Guo1, Zhongxuan Yang1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09970

    Abstract The rheological behavior of fluid-particle suspensions affects the flow dynamics of natural processes such as lavas, flow-type landslides and sediment transport. This study presents results of fully resolved simulations of monodisperse non-Brownian suspensions in a Couette flow using the smoothed particle hydrodynamics (SPH) method coupled with discrete element method (DEM), which allows for simulation of arbitrary-shaped particles. Several benchmark tests have been conducted to verify the reliability of the method. Two density ratios are considered in the study, i.e., 2.65 and 10, with the average particle area fraction varying from 14% to 47% and particle Reynolds number varying from 0.15… More >

  • Open Access

    ARTICLE

    Explainable AI and Interpretable Model for Insurance Premium Prediction

    Umar Abdulkadir Isa*, Anil Fernando*

    Journal on Artificial Intelligence, Vol.5, pp. 31-42, 2023, DOI:10.32604/jai.2023.040213

    Abstract Traditional machine learning metrics (TMLMs) are quite useful for the current research work precision, recall, accuracy, MSE and RMSE. Not enough for a practitioner to be confident about the performance and dependability of innovative interpretable model 85%–92%. We included in the prediction process, machine learning models (MLMs) with greater than 99% accuracy with a sensitivity of 95%–98% and specifically in the database. We need to explain the model to domain specialists through the MLMs. Human-understandable explanations in addition to ML professionals must establish trust in the prediction of our model. This is achieved by creating a model-independent, locally accurate explanation… More >

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