Proceedings of ESCAPE 35ISSN: 2818-4734
Volume: 4 (2025)
Table of Contents
LAPSE:2025.0436v1
Published Article
LAPSE:2025.0436v1
Application of Artificial Intelligence in process simulation tool
Nikhil Rajeev, Suresh Jayaraman, Prajnan Das, Srividya Varada
June 27, 2025
Abstract
Process engineers in the Chemical and Oil & Gas industries extensively use process simulation for the design, development, analysis, and optimization of complex systems. This study investigates the integration of Artificial Intelligence (AI) with AVEVATM Process Simulation (APS), a next-generation commercial simulation tool. We propose a framework for a custom chatbot application designed to assist engineers in developing and troubleshooting simulations. This chatbot application utilizes a custom-trained model to transform engineer prompts into standardized queries, facilitating access to essential information from APS. The chatbot extracts critical data regarding solvers and thermodynamic models directly from APS to help engineers develop and troubleshoot process simulations. Furthermore, we compare the performance of our custom model against OpenAI technology. Our findings indicate that this integration significantly enhances the usability of process simulation tools, promoting more innovative and cost-effective engineering solutions.
Suggested Citation
Rajeev N, Jayaraman S, Das P, Varada S. Application of Artificial Intelligence in process simulation tool. Systems and Control Transactions 4:1769-1774 (2025) https://doi.org/10.69997/sct.126215
Author Affiliations
Rajeev N: AVEVA Group Ltd, United States of America
Jayaraman S: AVEVA Group Ltd, United States of America
Das P: Cognizant Technology Solutions U.S. Corporation, United States of America
Varada S: AVEVA Group Ltd, United States of America
Journal Name
Systems and Control Transactions
Volume
4
First Page
1769
Last Page
1774
Year
2025
Publication Date
2025-07-01
Version Comments
Original Submission
Other Meta
PII: 1769-1774-1366-SCT-4-2025, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2025.0436v1
This Record
Document

LAPSE:2025.0019
Application of Artificial Intellige...
External Link

https://doi.org/10.69997/sct.126215
Article DOI
Download
Files
Jun 27, 2025
Main Article
License
CC BY-SA 4.0
Meta
Record Statistics
Record Views
1084
Version History
[v1] (Original Submission)
Jun 27, 2025
 
Verified by curator on
Jun 27, 2025
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2025.0436v1
 
Record Owner
PSE Press
Links to Related Works
Directly Related to This Work
Supplementary Material
Article DOI
References Cited
  1. Julien B, Cal D. The role of process engineering in the digital transformation. Computers & Chemical Engineering (2021)
  2. Zeinab H, Shokoufe T, Mohammad HEA. Application of AI in Chemical Engineering. InTechOpen (2018)
  3. Venkat V. The promise of artificial intelligence in chemical engineering: Is it here, finally?. AIChE Journal 65:466-478 (2018) https://doi.org/10.1002/aic.16489
  4. Konstantinos S, Charis N, Paris V, Elias K, Patrik K, Serafeim M. Enhancing property prediction and process optimization in building materials through machine learning: A review. Computational Materials Science 220 (2023) https://doi.org/10.1016/j.commatsci.2023.112031
  5. Mohammad A, Bassel S, Mohamed M, Enas S, Maryam A, Abrar I, Muaz R, Abdul O. Progress of artificial neural networks applications in hydrogen production. Chemical Engineering Research and Design 182:66-86 (2022) https://doi.org/10.1016/j.cherd.2022.03.030
  6. Haley H, Mohannad N, Xinyan H, John G. The role of large language models (AI chatbots) in fire engineering: An examination of technical questions against domain knowledge. Natural Hazards Research (2024)
  7. Chung L. What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature. Education Sciences 410 (2023) https://doi.org/10.3390/educsci13040410
  8. Mohannad N. Machine Learning for Civil and Environmental Engineers: A Practical Approach to Data-Driven Analysis, Explainability, and Causality. New Jersey: Wiley (2023)
  9. Alipour H, Nick P, Kohinoor R. ChatGPT Alternative Solutions: Large Language Models Survey. arXiv preprint arXiv (2024) https://doi.org/10.5121/csit.2024.1405114
  10. Dhiah S. Jaccard Coefficients based Clustering of XML Web Messages for Network Traffic Aggregation. Journal of Al-Qadisiyah for computer science and mathematic 11:82-91 (2019) https://doi.org/10.29304/jqcm.2019.11.2.592
  11. Faisal R, Teruaki K, Masayoshi A. Semantic cosine similarity. 7th international student conference on advanced science and technology ICAST 4 (2012)
  12. Seo N, Sangwoo K, Cheonyoung J. A Lightweight Program Similarity Detection Model using XML and Levenshtein Distance. FECS 3-9 (2006)

[0.95 s]