Hasil untuk "Engineering"

Benyamin Abdollahzadeh, F. S. Gharehchopogh, S. Mirjalili

Abstract Metaheuristics play a crucial role in solving optimization problems. The majority of such algorithms are inspired by collective intelligence and foraging of creatures in nature. In this paper, a new metaheuristic is proposed inspired by African vultures' lifestyles. The algorithm is named African Vultures Optimization Algorithm (AVOA) and simulates African vultures’ foraging and navigation behaviors. To evaluate the performance of AVOA, it is first tested on 36 standard benchmark functions. A comparative study is conducted that demonstrates the superiority of the proposed algorithm compared to several existing algorithms. To showcase the applicability of the AVOA and its black box nature, it is employed to find optimal solutions for eleven engineering design problems. Various experiments show that the AVOA performs better than the comparative algorithms in most engineering case studies. As the experiment results, the AVOA algorithm in 30 benchmarks out of 36 benchmarks has achieved better results than the optimizer algorithms and has a significant and better performance on the majority of engineering problems. Wilcoxon rank-sum test has been used for statistical evaluation and indicates the significant superiority of the AVOA algorithm at a 95% confidence interval.

G. Skačej, P. Ziherl

M. Geyer, Benjamin Hiller, Sascha Meinert

F. Incropera

M. Prince

P. Milgram, F. Kishino

A. Konak, D. Coit, Alice E. Smith

B. Logan, B. Hamelers, R. Rozendal et al.

R. Rubinstein

J. Yeh, S. Chen, Su-Jien Lin et al.

M. Neuts

M. Morari, E. Zafiriou

M. Ashby, D. Cebon

Frederick P. Brooks

E. Cussler

B. Finlayson

Gabriel Jesús Montúfar Chiriboga

La regulación de los recursos naturales en proyectos de ingeniería civil constituye uno de sus principales pilares para el desarrollo sostenible, especialmente en aquellos espacios donde la extracción y uso de recursos como la arena, los sedimentos y los residuos de la construcción son capaces de propiciar altos impactos ambientales. Esta revisión sistemática indaga en investigaciones recientes en gobernanza sobre la extracción de arena, la economía circular de la construcción, las prácticas de dragado, las compras públicas ecológicas y las evaluaciones de impacto ambiental, con el objetivo de determinar alternativas que concilien el avance económico con la protección/conciencia ecológica. Se incorporan veintinueve artículos seleccionados en función de los criterios de inclusión criterios de idoneidad temáticas y robustez metodológica para regiones como Ghana, Malasia, Vietnam y otras partes del mundo. Los resultados destacan que la extracción ilegal de la arena degrada la fertilidad del suelo y las comunidades agrícolas; la economía circular genera menos desperdicio debido al reciclado de materiales; las políticas de compras públicas ecológicas extreman los criterios ambientales aplicados a las licitaciones; y la evaluación de impacto ambiental demanda simplificaciones de los modelos de forma coherente para no provocar un cierto retraso, pero, a la vez, sin limitar una cierta protección.

Jianjun Cao, Bailing An, Enran Hou et al.

This study presents a novel local meshless approach for solving one-dimensional Fisher’s equation, combining a local scheme, Gaussian radial basis functions (G-RBF), and a collocation technique. The method leverages the Gaussian basis’s nonlinear fitting capability, the sparsity of the local scheme to avoid ill-conditioned matrices, and the simplicity of collocation. After time discretization using a finite difference scheme, the method constructs local approximations at each collocation point using G-RBFs over small subsets of neighboring nodes. Numerical experiments confirm its effectiveness in solving Fisher-type problems, with errors decreasing smoothly as collocation points increase and maintaining stable accuracy over time. The proposed method demonstrates computational efficiency, robustness, and potential for handling large-scale reaction-diffusion systems.

Jefferson S. Costa, Angelo Lunardi, Alessio Iovine et al.

Model predictive control (MPC) has emerged as a highly regarded control strategy in power electronics for renewable energy applications. While it minimizes tracking errors and control effort, a significant challenge is the lack of systematic tuning strategies to meet these systems’ energy quality performance requirements. This paper proposes a comprehensive MPC tuning methodology for grid-integrating converters with LCL filters, incorporating modulation and delay compensation. We conduct a stability analysis to define precise constraints for cost function weights. The fine-tuning strategy systematically maps a Figure of Merit (FoM) for system performance using an advanced computational model, revealing that optimal tunings reside in narrow parameter regions. Experimental validation on a 2 kW workbench confirmed that all proposed MPC tunings met IEEE Std. 519-2014 power quality criteria and consistently outperformed a two-sample deadbeat controller, exhibiting enhanced dynamic response and power quality.

Jin-Hua Liu, Jie Zheng, Mang Niu et al.

Summary: Among various electrocatalysts, high-entropy alloys (HEAs) have gained significant attention for their unique properties and excellent catalytic activity in the hydrogen evolution reaction (HER). However, the precise synthesis of HEA catalysts in small sizes remains challenging, which limits further improvement in their catalytic performance. In this study, boron- and nitrogen-doped HEA porous carbon nanofibers (HE-BN/PCNF) with an in situ–grown dendritic structure were successfully prepared, inspired by the germination and growth of tree branches. Furthermore, the dendritic fibers constrained the growth of HEA particles, leading to the synthesis of quantum dot-sized (1.67 nm) HEA particles, which also provide a pathway for designing HEA quantum dots in the future. This work provides design ideas and guiding suggestions for the preparation of borated HEA fibers with different elemental combinations and for the application of dendritic nanofibers in various fields.