Muhammad Naveed Khan, Abdullah M. S. Alhuthali, Ayesha Amjad, Muhammad Saqlain, Mohammad Yar, Nizal Alshammry, M. Elkotb
{"title":"Numerical Investigation of Mixed Convective Flow of Micropolar Casson Fluid with Cattaneo-Christov Heat Flux Model on an Inclined Vertical Stretching Surface","authors":"Muhammad Naveed Khan, Abdullah M. S. Alhuthali, Ayesha Amjad, Muhammad Saqlain, Mohammad Yar, Nizal Alshammry, M. Elkotb","doi":"10.1093/jcde/qwae045","DOIUrl":"https://doi.org/10.1093/jcde/qwae045","url":null,"abstract":"\u0000 It is vitally critical to understand the dynamics of the non-Newtonian fluids model from an engineering and industrial perspective. Many industrial and technical activities, such as the extrusion of polymer sheets, the manufacturing of paper, and the development of photographic films, require non-Newtonian fluids. Energy transportation has numerous industrial applications, and Classical heat and mass transfer laws do not accurately anticipate thermal and solute relaxation times. This study applies the modified Ohm law to heat and mass transport, utilizing Fick's and generalized Fourier concepts. And the primary purpose of this study is to explore the characteristics of heat and mass transport in the MHD mixed convective flow involving a micropolar Casson fluid across the vertically inclined starching surface with multiple slip effects. Moreover, the study considers additional factors like thermal radiation, heat generation, chemical reactions, and the influence of thermophoretic to analyze both energy and nanoparticle concentration aspects comprehensively. To simplify the flow analysis, the original flow model is transformed into a couple of ODEs (ordinary differential equations) by employing relevant similarity transformations. These ODEs establish a system that is solved numerically by using the Bvp4c solver through MATLAB. It is worth noticing that a more substantial estimation of the thermal and concentration relaxation parameters decays the fluid temperature and nanoparticle concentration, respectively, and the growth of the material parameter reduces the drag force, which consequently augmenting the fluid velocity. Furthermore, the enhancement occurs in the skin friction due to greater estimation of the micropolar parameter, while the Casson fluid parameter causes the opposite trend.","PeriodicalId":48611,"journal":{"name":"Journal of Computational Design and Engineering","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140985142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Additive manufacturing-driven simultaneous optimization of topology and print direction for thermoelastic structures considering strength failure","authors":"Hexin Jiang, Zhicheng He, Eric Li, Chao Jiang","doi":"10.1093/jcde/qwae043","DOIUrl":"https://doi.org/10.1093/jcde/qwae043","url":null,"abstract":"\u0000 This paper presents a strength-based simultaneous optimization method for optimizing thermoelastic structural topology and print direction in the presence of anisotropy induced by additive manufacturing. The approach utilizes the bi-directional evolutionary structural optimization (BESO) framework and defines design variables including element density and print-off angle. Firstly, an anisotropic thermoelastic constitutive model is established for finite element analysis. By introducing the Tsai-Hill failure criteria, the strength constraint to evaluate the stress level of additively manufactured anisotropic components is formulated. The P-norm aggregation function is employed to approximate the maximum strength failure coefficient. Then, the aggregated strength constraint is augmented to the optimization objective through a Lagrange multiplier. Sensitivity analysis of the new objective function with respect to the elemental design variables is performed, and an analytical approach is proposed to optimize the print-off angle. To improve the stability of the optimization procedure, a series of numerical algorithms and parameter updating strategies are developed. The effectiveness of our proposed method is demonstrated through typical numerical examples, highlighting a desirable match between the structural topology and the print direction can greatly improve the structural performance.","PeriodicalId":48611,"journal":{"name":"Journal of Computational Design and Engineering","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140989014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Monarch Butterfly Optimization-Based Genetic Algorithm Operators for Nonlinear Constrained Optimization and Design of Engineering Problems","authors":"M. A. El-Shorbagy, Taghreed Hamdi Alhadbani","doi":"10.1093/jcde/qwae044","DOIUrl":"https://doi.org/10.1093/jcde/qwae044","url":null,"abstract":"\u0000 This paper aims to present a hybrid method to solve nonlinear constrained optimization problems and engineering design problems (EDPs). The hybrid method is a combination of MBO with the crossover and mutation operators of the genetic algorithm (GA). It is called a hybrid monarch butterfly optimization with genetic algorithm operators (MBO-GAO). Combining MBO and GA operators is meant to overcome the drawbacks of both algorithms while merging their advantages. The self-adaptive crossover (SAC) and the real-valued mutation are the GA operators that are used in MBO-GAO. These operators are merged in a distinctive way within MBO processes to improve the variety of solutions in the later stages of the search process, speed up the convergence process, keep the search from getting stuck in local optima, and achieve a balance between the tendencies of exploration and exploitation. In addition, the greedy approach is presented in both the migration operator and the butterfly adjusting operator, which can only accept offspring of the monarch butterfly groups who are fitter than their parents. Finally, popular test problems, including a set of 19 benchmark problems, are used to test the proposed hybrid algorithm, MBO-GAO. The findings obtained provide evidence supporting the higher performance of MBO-GAO compared to other search techniques. Additionally, the performance of the MBO-GAO is examined for several engineering design problems. The computational results show that the MBO-GAO method exhibits competitiveness and superiority over other optimization algorithms employed for the resolution of engineering design problems.","PeriodicalId":48611,"journal":{"name":"Journal of Computational Design and Engineering","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140999317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seung-Wan Cho, Yeong-Hyun Lim, Kyung-Min Seo, Jungin Kim
{"title":"Integration of Eye-Tracking and Object Detection in a Deep Learning System for Quality Inspection Analysis","authors":"Seung-Wan Cho, Yeong-Hyun Lim, Kyung-Min Seo, Jungin Kim","doi":"10.1093/jcde/qwae042","DOIUrl":"https://doi.org/10.1093/jcde/qwae042","url":null,"abstract":"\u0000 During quality inspection in manufacturing, the gaze of a worker provides pivotal information for identifying surface defects of a product. However, it is challenging to digitize the gaze information of workers in a dynamic environment where the positions and postures of the products and workers are not fixed. A robust, deep learning-based system, ISGOD (Integrated System with worker's Gaze and Object Detection), is proposed, which analyzes data to determine which part of the object is observed by integrating object detection and eye-tracking information in dynamic environments. The ISGOD employs a 6D pose estimation algorithm for object detection, considering the location, orientation, and rotation of the object. Eye-tracking data were obtained from Tobii Glasses, which enable real-time video transmission and eye-movement tracking. A latency reduction method is proposed to overcome the time delays between object detection and eye-tracking information. Three evaluation indices, namely, gaze score, accuracy score, and concentration index are suggested for comprehensive analysis. Two experiments were conducted: a robustness test to confirm the suitability for real-time object detection and eye-tracking, and a trend test to analyze the difference in gaze movement between experts and novices. In the future, the proposed method and system can transfer the expertise of experts to enhance defect detection efficiency significantly.","PeriodicalId":48611,"journal":{"name":"Journal of Computational Design and Engineering","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141011045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Twin Support Vector Machines Based on Chaotic Mapping Dung Beetle Optimization Algorithm","authors":"Huajuan Huang, Zhenhua Yao, Xiuxi Wei, Yongquan Zhou","doi":"10.1093/jcde/qwae040","DOIUrl":"https://doi.org/10.1093/jcde/qwae040","url":null,"abstract":"\u0000 Twin Support Vector Machine (TSVM) is a powerful machine learning method that is usually used to solve binary classification problems. But although the classification speed and performance of Twin Support Vector Machine is better than that of primitive Support Vector Machine, Twin Support Vector Machine still faces the problem of difficult parameter selection, therefore, to overcome the problem of parameter selection of Twin Support Vector Machine, this paper proposes a Chaotic Mapping Dung Beetle Optimization Algorithm based Twin Support Vector Machine (CMDBO-TSVM) for automatic parameter selection. Due to the uncertainty of the random initialization population of the original dung beetle optimization algorithm, this paper additionally adds chaotic mapping initialization to improve the dung beetle optimization algorithm. Experiments on the dataset through this paper show that the classification accuracy of the twin support vector machine based on the chaotic mapping dung beetle optimization algorithm has a better performance.","PeriodicalId":48611,"journal":{"name":"Journal of Computational Design and Engineering","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140675360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhuangyu Li, W. Xiao, Gang Zhao, Ziqi Zhou, Shulin Chen, Changri Xiong
{"title":"Virtual-trim: A parametric geometric modeling method for heterogeneous strut-based lattice structures","authors":"Zhuangyu Li, W. Xiao, Gang Zhao, Ziqi Zhou, Shulin Chen, Changri Xiong","doi":"10.1093/jcde/qwae034","DOIUrl":"https://doi.org/10.1093/jcde/qwae034","url":null,"abstract":"\u0000 Geometric modeling has been integral to the design process with the introduction of Computer-Aided Design. With Additive Manufacturing (AM), design freedom has reached new heights, allowing for the production of complex lattice structures not feasible with traditional manufacturing methods. However, there remains a significant challenge in the geometric modeling of these lattice structures, especially for heterogeneous strut-based lattice structures. Current methods show limitations in accuracy or geometric control. This paper presents the Virtual-Trim, a novel method for the geometric modeling of heterogeneous strut-based lattice structures that is both efficient and robust. Virtual-Trim begins with user-defined wireframe models and geometric information to create STL models ready for AM, eliminating the need for labor-intensive Boolean operations. The fundamental principles and steps involved in Virtual-Trim are extensively described within. Additionally, various models using Virtual-Trim method are designed, and the performance of Virtual-Trim in terms of generation time and model size is analyzed. The successful printing of these models attests to the method's excellent manufacturability.","PeriodicalId":48611,"journal":{"name":"Journal of Computational Design and Engineering","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140723166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reimagining space layout design through deep reinforcement learning","authors":"R. Kakooee, Benjamin Dillenburger","doi":"10.1093/jcde/qwae025","DOIUrl":"https://doi.org/10.1093/jcde/qwae025","url":null,"abstract":"\u0000 Space layout design is a critical aspect of architectural design, influencing functionality and aesthetics. The inherent combinatorial nature of layout design poses challenges for traditional planning approaches; thus, it demands the exploration of novel methods. This paper presents a novel framework that leverages the potential of deep reinforcement learning (RL) algorithms to optimize space layouts. RL has demonstrated remarkable success in addressing complex decision-making problems, yet its application in the design process remains relatively unexplored. We argue that RL is particularly well-suited for the design process due to its ability to accommodate offline tasks and seamless integration with existing CAD software, effectively acting as a simulator for design exploration. Framing space layout design as an RL problem and employing RL methods allows for the automated exploration of the expansive design space, thereby enhancing the discovery of innovative solutions. This paper also elucidates the synergy between the design process and the RL problem, which opens new avenues for exploring the potential of RL algorithms in design. We aim to foster experimentation and collaboration within the RL and architecture communities. To facilitate our research, we have developed SpaceLayoutGym, an environment specifically designed for space layout design tasks. SpaceLayoutGym serves as a customizable environment that encapsulates the essential elements of the layout design process within an RL framework. To showcase the effectiveness of SpaceLayoutGym and the capabilities of RL as an artificial space layout designer, we employ the PPO algorithm to train the RL agent in selected design scenarios with both geometrical constraints and topological objectives. The study further extends to contrast the effectiveness of PPO agents with that of genetic algorithms, and also includes a comparative analysis with existing layouts. Our results demonstrate the potential of RL to optimize space layouts, offering a promising direction for the future of AI-aided design.","PeriodicalId":48611,"journal":{"name":"Journal of Computational Design and Engineering","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140374715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-strategy augmented Harris hawks optimization: performance design for feature selection","authors":"Zisong Zhao, Helong Yu, Hongliang Guo, Huiling Chen","doi":"10.1093/jcde/qwae030","DOIUrl":"https://doi.org/10.1093/jcde/qwae030","url":null,"abstract":"\u0000 In the context of increasing data scale, contemporary optimization algorithms struggle with cost and complexity in addressing the feature selection (FS) problem. This paper introduces a Harris hawks optimization (HHO) variant, enhanced with a multi-strategy augmentation (CXSHHO), for FS. The CXSHHO incorporates a communication and collaboration strategy (CC) into the baseline HHO, facilitating better information exchange among individuals, thereby expediting algorithmic convergence. Additionally, a directional crossover (DX) component refines the algorithm's ability to thoroughly explore the feature space. Furthermore, the soft-rime strategy (SR) broadens population diversity, enabling stochastic exploration of an extensive decision space and reducing the risk of local optima entrapment. The CXSHHO's global optimization efficacy is demonstrated through experiments on 30 functions from CEC2017, where it outperforms 15 established algorithms. Moreover, the paper presents a novel FS method based on CXSHHO, validated across 18 varied datasets from UCI. The results confirm CXSHHO's effectiveness in identifying subsets of features conducive to classification tasks.","PeriodicalId":48611,"journal":{"name":"Journal of Computational Design and Engineering","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140216169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Peng Zhang, Yuyu Li, Kejun Tang, Lairong Yin, Long Huang, Hongbing Wang
{"title":"Trajectory optimization for automated tape placement on triangular mesh surfaces considering gap requirements","authors":"Peng Zhang, Yuyu Li, Kejun Tang, Lairong Yin, Long Huang, Hongbing Wang","doi":"10.1093/jcde/qwae032","DOIUrl":"https://doi.org/10.1093/jcde/qwae032","url":null,"abstract":"\u0000 Automated tape placement (ATP) is an important automated process adopted for the fabrication of large composite components. Trajectory planning is the key link of ATP, which directly affects the precision and efficiency of the layup process, and the quality of final products. Presently, most existing trajectory optimization methods for ATP focus on smooth surfaces. Nevertheless, as commercial CAD/CAM software generally uses NURBS (Non-uniform Rational B-Splines) for modelling, the difficulty of finding the solution and the low efficiency associated with the calculation process are inevitable. The discrete methods provide alternatives for designing layup trajectories, whereas their accuracy is seldom analyzed. Furthermore, a path optimization algorithm for eliminating gap problems while preventing wrinkles on discrete models is rarely reported. In this paper, the adjustment of layup trajectories for ATP is considered on triangular meshes. Firstly, the triangular mesh is reconstructed as a Nagata patch to recover the original geometry with good accuracy. Then, a numerical method for tracing desired paths on the Nagata patch set is provided, and the computation efficiency is validated. Next, two optimization methodologies are proposed to improve the layup of composite tapes while avoiding wrinkles. Finally, the presented two strategies are examined on a discrete hyperbolic surface and a discrete freeform surface, and some of the results are delivered.","PeriodicalId":48611,"journal":{"name":"Journal of Computational Design and Engineering","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140216831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Hierarchical RNNs with Graph Policy and Attention for Drone Swarm","authors":"XiaoLong Wei, WenPeng Cui, Xianglin Huang, Lifang Yang, XiaoQi Geng, Zhulin Tao, Yan Zhai","doi":"10.1093/jcde/qwae031","DOIUrl":"https://doi.org/10.1093/jcde/qwae031","url":null,"abstract":"\u0000 In recent years, the drone swarm has experienced remarkable growth, finding applications across diverse domains such as agricultural surveying, disaster rescue, and logistics delivery. However, the rapid expansion of drone swarm usage underscores the necessity for innovative approaches in the field. Traditional algorithms face challenges in adapting to complex tasks, environmental modeling, and computational complexity, highlighting the need for more advanced solutions like multi-agent deep reinforcement learning to enhance efficiency and robustness in drone swarm. Our proposed approach tackles this challenge by embracing temporal and spatial. In terms of the temporal, the proposed approach builds upon historical data, it enhances the predictive capabilities regarding future behaviors. In the spatial, the proposed approach leverage graph theory to model the swarm's features, while attention mechanisms strengthen the relationships between individual drones. The proposed approach addresses the unique characteristics of drone swarms by incorporating temporal dependencies, spatial structures, and attention mechanisms. Extensive experiments validate the effectiveness of the proposed approach.","PeriodicalId":48611,"journal":{"name":"Journal of Computational Design and Engineering","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140219615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}