{"title":"一个基于噪声的框架,用于随机生成具有逼真几何形状的土壤颗粒","authors":"Chen‐Xi Tong, Jia‐Jun Li, Quan Sun, Sheng Zhang, Wan‐Huan Zhou, Daichao Sheng","doi":"10.1111/mice.13424","DOIUrl":null,"url":null,"abstract":"Particle morphology influences the mechanical behavior of granular soils. Generating particles with realistic shapes for discrete element method simulations is gaining popularity. However, it is still challenging to efficiently generate very angular particles with less computational cost. Addressing this challenge, this paper introduces a novel noise‐based framework for generating realistic soil particle geometry. Noise algorithms are utilized to apply random variations with certain morphological patterns on the surface of the base geometry (e.g., a sphere), thereby generating a variety of particles with morphological patterns ranging from very angular to rounded. In addition, the base geometry can be replaced with other geometries including real particle scans, allowing rapid generation of realistic particles with morphological characteristics of the base geometry. The framework stands out for its simplicity, the wide range of particle morphologies generated, reducing the need for extensive computation and scanning, and provides a new idea for the granular soil behavior simulations.","PeriodicalId":156,"journal":{"name":"Computer-Aided Civil and Infrastructure Engineering","volume":"44 1","pages":""},"PeriodicalIF":8.5000,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A noise‐based framework for randomly generating soil particle with realistic geometry\",\"authors\":\"Chen‐Xi Tong, Jia‐Jun Li, Quan Sun, Sheng Zhang, Wan‐Huan Zhou, Daichao Sheng\",\"doi\":\"10.1111/mice.13424\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Particle morphology influences the mechanical behavior of granular soils. Generating particles with realistic shapes for discrete element method simulations is gaining popularity. However, it is still challenging to efficiently generate very angular particles with less computational cost. Addressing this challenge, this paper introduces a novel noise‐based framework for generating realistic soil particle geometry. Noise algorithms are utilized to apply random variations with certain morphological patterns on the surface of the base geometry (e.g., a sphere), thereby generating a variety of particles with morphological patterns ranging from very angular to rounded. In addition, the base geometry can be replaced with other geometries including real particle scans, allowing rapid generation of realistic particles with morphological characteristics of the base geometry. The framework stands out for its simplicity, the wide range of particle morphologies generated, reducing the need for extensive computation and scanning, and provides a new idea for the granular soil behavior simulations.\",\"PeriodicalId\":156,\"journal\":{\"name\":\"Computer-Aided Civil and Infrastructure Engineering\",\"volume\":\"44 1\",\"pages\":\"\"},\"PeriodicalIF\":8.5000,\"publicationDate\":\"2025-01-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer-Aided Civil and Infrastructure Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1111/mice.13424\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer-Aided Civil and Infrastructure Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1111/mice.13424","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
A noise‐based framework for randomly generating soil particle with realistic geometry
Particle morphology influences the mechanical behavior of granular soils. Generating particles with realistic shapes for discrete element method simulations is gaining popularity. However, it is still challenging to efficiently generate very angular particles with less computational cost. Addressing this challenge, this paper introduces a novel noise‐based framework for generating realistic soil particle geometry. Noise algorithms are utilized to apply random variations with certain morphological patterns on the surface of the base geometry (e.g., a sphere), thereby generating a variety of particles with morphological patterns ranging from very angular to rounded. In addition, the base geometry can be replaced with other geometries including real particle scans, allowing rapid generation of realistic particles with morphological characteristics of the base geometry. The framework stands out for its simplicity, the wide range of particle morphologies generated, reducing the need for extensive computation and scanning, and provides a new idea for the granular soil behavior simulations.
期刊介绍:
Computer-Aided Civil and Infrastructure Engineering stands as a scholarly, peer-reviewed archival journal, serving as a vital link between advancements in computer technology and civil and infrastructure engineering. The journal serves as a distinctive platform for the publication of original articles, spotlighting novel computational techniques and inventive applications of computers. Specifically, it concentrates on recent progress in computer and information technologies, fostering the development and application of emerging computing paradigms.
Encompassing a broad scope, the journal addresses bridge, construction, environmental, highway, geotechnical, structural, transportation, and water resources engineering. It extends its reach to the management of infrastructure systems, covering domains such as highways, bridges, pavements, airports, and utilities. The journal delves into areas like artificial intelligence, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, internet-based technologies, knowledge discovery and engineering, machine learning, mobile computing, multimedia technologies, networking, neural network computing, optimization and search, parallel processing, robotics, smart structures, software engineering, virtual reality, and visualization techniques.