Waste Heat Recovery via Organic Rankine Cycle
Project Overview
The team models industrial heat streams and designs a DWSIM-based ORC to recover energy efficiently, pairing it with techno-economic analysis to validate feasibility.
Tech Stack
Team
Mentors
- Sanjo Kedavath
- Dathu Vikas
- Shubhank Hiremath
Mentees
- Soumili Dey
- Antara Dongre
- Chowhan Deepak
Problem Statement
Heat exchangers face fouling and efficiency loss, while non-intrusive internal monitoring is difficult with conventional sensing.
Objectives
- - Develop PINN-based digital twin for heat exchanger
- - Use hypernetwork to map boundary conditions to model weights
- - Enable real-time internal temperature estimation
Methodology
The project follows a structured implementation approach that includes Generate datasets across boundary conditions, Train hypernetwork for PINN parameter prediction, Deploy inference pipeline from sensor inputs, and Validate against simulated plant conditions. These steps are executed iteratively to validate assumptions, improve performance, and ensure reliable delivery of the final solution.
Expected Outcome
By the end of this project, the team is expected to deliver Low-error real-time prediction pipeline, Early fouling and efficiency-drop detection, and Predictive maintenance dashboard readiness. Together, these outcomes reflect both technical feasibility and practical value for demos, evaluation, and future scaling.
Future Scope
- - Extend to boilers, condensers and reactors
- - Integrate with IoT fleet monitoring