Experimental Studies on Novel Multi Tubular Reactor with Shell Having Integrated Buffer Storage
JOURNAL OF ENERGY STORAGE（2023）
Indian Inst Technol
Abstract
This study concentrates on experimental analysis of a large scale metal hydride based hydrogen storage reactor having 50 kg LaNi5. In order to cater the heat transfer limitations of hydrogen storage in large scale systems, the present design have been developed as multi tubular reactor with shell having integrated buffer storage configuration with 7 tubes supported by means of 4 baffles having total 50 kg LaNi5 distributed equally among them and water as heat transfer fluid flows across the shell for heat transfer. The experimental study was per-formed for studying the absorption and desorption performance of the present hydrogen reactor wherein in case of absorption the parameters varied were HTF flow rate at 30 degrees C and supply pressure of hydrogen and in case of desorption which was carried out at atmospheric pressure, HTF flow rate and HTF temperature were varied. The metal hydride reactor reversibly stores 680 g of hydrogen amounting to 1.34 wt% of gravimetric capacity of metal hydride and equivalent energy storage of 10.4 MJ. In case of absorption, when the flow rate selected was 20 LPM the absorption time for 90 % reaction completion was observed to be 1286 s (21.4 min) at 30 bar H2 supply pressure. In case of desorption studies, it was observed that the varying flow rate from 15 to 25 LPM has negligible effect on hydrogen desorption hence 15 LPM was selected as flow rate for further desorption exper-iments. Further increasing HTF temperature from 60 degrees C to 80 degrees C improves the performance significantly.
MoreTranslated text
Key words
Metal hydride,Hydrogen storage,Shell and tube arrangement
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined