Computational Modelling of Parachute Deployment to allow better Optimisation through Parachute Design

降落伞展开的计算模型可通过降落伞设计实现更好的优化

• 批准号: 10062651
• 金额: $ 0.92万
• 依托单位: IRVINGQ LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10062651
• 关键词: Computational; Modelling; Parachute; Deployment; allow

IrvinGQ have a long history designing and manufacturing parachutes and aerial delivery equipment, primarily for the military market. IrvinGQ have developed many parachutes using empirical design principles and extensive testing programmes to ensure that parachutes meet the required performance characteristics. Physical testing is an expensive and time-consuming process and IrvinGQ want to research the validity of using more computational simulation and experimental data explorations in their parachute development process.This project is to (i) develop and validate a computational modelling methodology to predict parachute performance, such as rate of decent and carried mass, to improve on existing designs. The computational simulation, considered initially on a scaled parachute model being tested by IrvinGQ, and will simulate a full model afterwards to identify and guide performance optimisation features through design changes. In addition, and supported by company available full-scale parachute data, (ii) a machine learning tool will be developed for future design optimisation and enhanced performance of new parachutes.

IrvingGQ 在设计和制造降落伞和空中投送设备方面拥有悠久的历史，主要面向军事市场。 IrvingGQ 采用经验设计原理和广泛的测试计划开发了许多降落伞，以确保降落伞满足所需的性能特征。物理测试是一个昂贵且耗时的过程，IrvinGQ 希望研究在降落伞开发过程中使用更多计算模拟和实验数据探索的有效性。该项目旨在 (i) 开发和验证计算建模方法来预测降落伞性能，例如体面率和承载质量，以改进现有设计。计算模拟最初是在 IrvinGQ 正在测试的按比例降落伞模型上考虑的，随后将模拟完整的模型，以通过设计更改来识别和指导性能优化功能。此外，在公司现有的全尺寸降落伞数据的支持下，(ii) 将开发机器学习工具，用于未来设计优化和增强新型降落伞的性能。