Inversion of Interlayer Pressure in High-Vacuum Multilayer Insulation Structures for Cryogen Storage Using Extreme Learning Machine

Author:

Wu Hao1,Tan Hongbo1ORCID

Affiliation:

1. Department of Refrigeration and Cryogenic Engineering, Xi’an Jiaotong University, No. 28, Xianning West Road, Xi’an 710049, China

Abstract

Revealing the interlayer pressure distribution in multilayer insulation (MLI) for cryogen (e.g., liquid hydrogen) containers is very important to improve the insulation-performance-predicting quality. This paper proposed an inversion method to reconstruct the interlayer pressure of multilayer insulations on the basis of experimentally measuring the reflectors’ temperatures. The layer-by-layer (LBL) model was modified by considering the interlayer pressure distribution in MLIs to calculate the reflectors’ temperatures. Groups of pre-given interlayer pressure distributions and the corresponding temperature distributions calculated by the LBL model were used to train an extreme learning machine (ELM) algorithm. Finally, the interlayer pressure distribution of the MLI was reconstructed by the trained ELM algorithm based on the measured reflectors’ temperatures. The method was validated by four additional testing cases. The results showed that the proposed algorithm was accurate in reconstructing the interlayer pressures. Published experimentally measured temperature distributions of a 60-layer MLI were used as input data. The abovementioned inversion method was adopted, and a reasonable interlayer pressure distribution was obtained. Moreover, the thermal insulation performance of the MLI was calculated by the LBL model considering the reconstructed interlayer pressure distribution. We found that the predicted heat flux of the MLI deviated from the experimental results by only 2.77%, while the error of the classical LBL model ignoring the non-ideal vacuum condition was as high as 89%. Meanwhile, the predicted corresponding temperature distribution deviated from the tested value by less than 1.13 K. The proposed method can be applied to assess the interlayer pressure distribution of industrial cryogen containers and precisely predict the thermal insulation performance of a practical multilayer insulation structure.

Funder

National Key R&D Program of China

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference22 articles.

1. Fesmire, J.E. (2015, January 26). Layered Thermal Insulation Systems for Industrial and Commercial Applications. Presented at the NASA Tech Briefs Webinar, Merritt Island, FL, USA.

2. Measuring the gas pressure within a high-performance insulation blanket;Price;Adv. Cryog. Eng.,1968

3. Experimental investigations of MLI;Bapat;Cryogenics,1990

4. Zhou, C. (1998). Experimental Study on Vacuum Level between High Vacuum Multilayer Insulation Layers. [Master’s Thesis, Shanghai Jiaotong University].

5. Investigations into the thermal performance of multilayer insulation (300-77 K) Part 2: Thermal analysis;Jacob;Cryogenics,1992

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3