JOURNAL ARTICLE
Ammonia Synthesis Loop: A Dynamic Simulation‐Based HAZOP Study.
Published In: Asia-Pacific Journal of Chemical Engineering, 2025, v. 20, n. 4. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Kubra, Kadeejathul; Soloman, P. A. 3 of 3
Abstract
Ammonia (NH₃) is a crucial industrial chemical used mostly in agriculture, with a global production of approximately 150 million metric tons by 2023. Despite its significance, ammonia manufacturing poses significant safety risks because of its high pressure, hydrogen content, and potential for hazardous accidents. To improve the safety analysis of ammonia synthesis, this study uses a dynamic simulation with Honeywell UniSim Design software. The simulation models the dynamic behavior of a 1000 TPD ammonia synthesis loop, based on the Haber‐Bosch process, at the Fertilizers and Chemicals Travancore Limited plant in Udyogamandal, Kerala, India. This study evaluated two primary risk scenarios: leakage in the ammonia synthesis pipeline and abnormal liquid levels in the ammonia separator, using dynamic simulation‐based Hazard and Operability Analysis (HAZOP). These results suggest that high liquid levels in the separator can cause liquid ammonia entrainment, compressor failure, and toxic leakage in the event of equipment failure. The pipeline leakage study points out the possibility of explosions and ammonia poisoning, with ammonia concentrations exceeding hazardous levels within minutes. This dynamic simulation‐based method provides important insights for process safety management in industrial ammonia production by better identifying risks and quantifying safety concerns than traditional steady‐state models. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Asia-Pacific Journal of Chemical Engineering. 2025/07, Vol. 20, Issue 4, p1
- Document Type:Article
- Subject Area:History
- Publication Date:2025
- ISSN:1932-2135
- DOI:10.1002/apj.70034
- Accession Number:189333045
- Copyright Statement:Copyright of Asia-Pacific Journal of Chemical Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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