Exploring AI: from Process Simulation to Economic Evaluation applied to CO2 capture

IFP Energies nouvelles (IFPEN) est un acteur majeur de la recherche et de la formation dans les domaines de l’énergie, du transport et de l’environnement. De la recherche à l’industrie, l’innovation technologique est au cœur de son action, articulée autour de quatre priorités stratégiques : Mobilité Durable, Energies Nouvelles, Climat / Environnement / Economie circulaire et Hydrocarbures Responsables.

Dans le cadre de la mission d’intérêt général confiée par les pouvoirs publics, IFPEN concentre ses efforts sur :

• l’apport de solutions aux défis sociétaux de l’énergie et du climat, en favorisant la transition vers une mobilité durable et l’émergence d’un mix énergétique plus diversifié ;
• la création de richesse et d’emplois, en soutenant l’activité économique française et européenne et la compétitivité des filières industrielles associées.

Partie intégrante d’IFPEN, l’école d’ingénieurs IFP School prépare les générations futures à relever ces défis.

Exploring AI: from Process Simulation to Economic Evaluation applied to CO2 capture

As process engineers, we see significant potential in leveraging artificial intelligence to transform our field, although its actual impact remains to be fully demonstrated. In theory, AI could code simulations, extract their results, exploit scientific literature to design standard equipment, and even generate cost evaluations for installations, all of this based on a simple prompt. How close are we to achieving this vision in real-world applications?

Description

This internship seeks to validate the feasibility of leveraging artificial intelligence across three critical steps in process engineering: simulation, equipment design, and cost evaluation.

The project will focus on a practical case study - a conventional CO2 capture process - to rigorously compare traditional methodologies with AI-driven approaches. The goal is to uncover AI's true potential in automating and enhancing these tasks while assessing the relevance and efficiency of the tools and methods used.

The intern will play a key role in evaluating the applicability of AI techniques and identifying the most suitable LLM (Large Language Model) for each task. By the end of the internship, the findings will contribute to shaping innovative practices in process engineering.

The work will be divided into the following tasks:

• Conduct a comprehensive literature review on the current capabilities of AI in process engineering.
• Perform a traditional simulation, equipment design, and cost evaluation for a CO2 capture process.
• Develop an AI-based approach to replicate the same tasks.
• Compare and analyze the results from both traditional and AI-based methods.
• Assess the relevance and performance of AI tools and methodologies.
• Provide recommendations on the most appropriate tools, frameworks, and programming languages for future applications.

Required profile

Student specializing in process engineering or equivalent, interested in artificial intelligence and its industrial applications, critical thinking and analytical skills.

Additional information

Duration of the internship : 6 months
Workplace : IFPEN Lyon, Rond-point de l'échangeur de Solaize, 69360 Solaize
Transport : public transportation / personal vehicle
Paid internship 1130€/month (gross)