Wangzhi Zou , Xinqian Zheng , Weitao Liu , Jun Lai , Baotong Wang
{"title":"0D-1D coupled method for performance design and analysis of adaptive cycle engine - Modeling, simulation and validation","authors":"Wangzhi Zou , Xinqian Zheng , Weitao Liu , Jun Lai , Baotong Wang","doi":"10.1016/j.energy.2024.133666","DOIUrl":null,"url":null,"abstract":"<div><div>Adaptive cycle engine (ACE) can efficiently operate in different modes to fulfill complex mission requirements, which features better mission adaptability than the conventional engine, but also brings great challenges to the performance design and analysis. To deal with the low accuracy of the traditional zero-dimensional (0D) method in predicting the ACE performance under variable geometry and off-design conditions, a zero-dimensional and one-dimensional (0D-1D) coupled simulation method is proposed and validated in this paper. The physics-based 1D mean-line models for the adaptive fan and variable geometry turbine are established, and then coupled with the 0D engine model by iteratively coupled method. Besides, an adaptive selection strategy on the coupling parameters is proposed to improve the convergence issue related to the usage of generic performance maps and accelerate the convergence. Different coupled methods are also compared regarding engine performance, component characteristics and computing time. The 0D-1D coupled method provides a more physical, more accurate and efficient solution for reasonably considering the effects of the design parameters and variable geometry parameters on the ACE performance. The maximum computing time for a single operating point is less than 2 min, which is significant for the quick iteration in the stage of ACE conceptual and preliminary design.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133666"},"PeriodicalIF":9.0000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360544224034443","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Adaptive cycle engine (ACE) can efficiently operate in different modes to fulfill complex mission requirements, which features better mission adaptability than the conventional engine, but also brings great challenges to the performance design and analysis. To deal with the low accuracy of the traditional zero-dimensional (0D) method in predicting the ACE performance under variable geometry and off-design conditions, a zero-dimensional and one-dimensional (0D-1D) coupled simulation method is proposed and validated in this paper. The physics-based 1D mean-line models for the adaptive fan and variable geometry turbine are established, and then coupled with the 0D engine model by iteratively coupled method. Besides, an adaptive selection strategy on the coupling parameters is proposed to improve the convergence issue related to the usage of generic performance maps and accelerate the convergence. Different coupled methods are also compared regarding engine performance, component characteristics and computing time. The 0D-1D coupled method provides a more physical, more accurate and efficient solution for reasonably considering the effects of the design parameters and variable geometry parameters on the ACE performance. The maximum computing time for a single operating point is less than 2 min, which is significant for the quick iteration in the stage of ACE conceptual and preliminary design.
期刊介绍:
Energy is a multidisciplinary, international journal that publishes research and analysis in the field of energy engineering. Our aim is to become a leading peer-reviewed platform and a trusted source of information for energy-related topics.
The journal covers a range of areas including mechanical engineering, thermal sciences, and energy analysis. We are particularly interested in research on energy modelling, prediction, integrated energy systems, planning, and management.
Additionally, we welcome papers on energy conservation, efficiency, biomass and bioenergy, renewable energy, electricity supply and demand, energy storage, buildings, and economic and policy issues. These topics should align with our broader multidisciplinary focus.