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Design of Prismatic Beams for Bending01:23

Design of Prismatic Beams for Bending

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The design of prismatic beams, structural elements with a uniform cross-section, focuses on ensuring safety and structural integrity under load. The design process begins by determining the allowable stress, either from material properties tables, or by dividing the material's ultimate strength by a safety factor. This safety factor is essential for accommodating uncertainties, and varies depending on the material—timber, steel, or concrete—with each having unique strength and...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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Unsymmetric Loading of Thin-Walled Members: Problem Solving01:07

Unsymmetric Loading of Thin-Walled Members: Problem Solving

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The shear center of a channel section with uniform thickness, height, and width, is determined by computing the shear force in the member and calculating the moments of inertia of the sections.
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One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

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Design Example: Calculating Safe Diameter for Wind-Exposed Disc01:17

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Assessing safety in wind-exposed installations is crucial to preventing potential failures. This example explores the calculation and design adjustments needed to mount a circular disc on a building facade, where wind forces are a primary concern. A 4-meter diameter disc was initially designed as an aesthetic feature facing winds at a velocity of 25 meters per second, with an air density of 1.25 kilograms per cubic meter. Given these conditions, the drag force on the disc was determined using...
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Design Example: Application of Archimedes' Principle01:11

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Archimedes' principle is fundamental in analyzing the buoyant force and stability of floating bodies. In this example, a wooden block with a rectangular section floats in seawater. Based on the block's dimensions, its specific gravity and the specific weight of seawater are used to find the volume of water displaced and the center of buoyancy.
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Video Experimental Relacionado

Updated: Sep 9, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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GWOA: Un algoritmo de optimización de ballenas mejorado de múltiples estrategias para la optimización del diseño de

Yanzhao Gu1, Junhao Wei1, Zikun Li2

  • 1Faculty of Applied Sciences, Macao Polytechnic University, Macao 999078, China.

PloS one
|September 3, 2025
PubMed
Resumen
Este resumen es generado por máquina.

El mejorado algoritmo de optimización de ballenas (GWOA) mejora la búsqueda global y la convergencia de problemas complejos. GWOA demuestra un rendimiento superior en tareas de benchmark y optimización de ingeniería, ofreciendo una solución más estable y eficiente.

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Área de la Ciencia:

  • Inteligencia computacional
  • Algoritmos de optimización
  • Las metaheurísticas

Sus antecedentes:

  • El algoritmo de optimización de ballenas tradicional (WOA) sufre de óptima local, convergencia lenta y búsqueda global limitada de problemas de alta dimensión.
  • Las variantes de WOA existentes pueden no abordar completamente estas limitaciones en escenarios de optimización complejos.

Objetivo del estudio:

  • Proponer un algoritmo mejorado de optimización de ballenas (GWOA) que aborde las deficiencias de la WOA tradicional.
  • Mejorar la capacidad de búsqueda global, la velocidad de convergencia y la precisión de la solución para problemas de optimización complejos.

Principales métodos:

  • Integración del ajuste de parámetros adaptativos, mejor cerco de presas y estrategias de búsqueda de seno-cosino en WOA.
  • Prueba de GWOA en 23 funciones de referencia (unimodal, multimodal, de composición) y problemas de diseño de ingeniería (recipiente a presión, resorte).
  • Análisis comparativo con metaheurística básica, variantes de WOA y algoritmos de última generación, incluidos los experimentos de escalabilidad.

Principales resultados:

  • GWOA demostró una velocidad de convergencia y una precisión de solución superiores en la mayoría de las funciones de referencia, especialmente para problemas multimodales y de composición.
  • Alcanzó una eficiencia global (OE) del 74,46% en las pruebas de referencia.
  • Reducción efectiva de costos y cumplimiento de las restricciones en los problemas de optimización de ingeniería, mostrando una mayor estabilidad y capacidad de optimización.

Conclusiones:

  • GWOA mejora significativamente la búsqueda global, la velocidad de convergencia y la estabilidad de la solución a través de la integración de múltiples estrategias.
  • GWOA muestra un gran potencial para resolver problemas de optimización complejos y sirve como una herramienta eficiente para aplicaciones de ingeniería.
  • El GWOA propuesto ofrece una alternativa robusta y eficaz a los algoritmos de optimización tradicionales.