theleo.zone/thermal-model source code (formerly thermalmodel.com)

MATLAB code and data for the article 📋: I. Daminov, A. Prokhorov, R. Caire, M-C Alvarez-Herault, “Assessment of dynamic transformer rating, considering current and temperature limitations” in International Journal of Electrical Power & Energy Systems (IF: 3,588, Q1), 2021

Python code to model thermal energy flows for Battery Energy Storage Systems (BESS) under realistic load and environmental conditions.

Thermal simulation in python

MATLAB code and data for the article Ildar Daminov, Anne Blavette, Salvy Bourguet, Hamid Ben Ahmed, Thomas Soulard, Pierre Warlop, "Economic performance of overplanted offshore wind farm under several commitment strategies and dynamic thermal ratings of submarine export cable," in Applied Energy, 2023, https://doi.org/10.1016/j.apenergy.2023.121326

Mars Subsurface Ice Model (MSIM): Thermal and Ice Evolution Models for Mars

World's Hottest Thermal Solver

MATLAB code for the paper "optimal ageing limit of oil-immersed transformers in flexible power systems". in CIRED 2021

MATLAB code and data for the paper I. Daminov, A. Prokhorov,T. Moiseeva, M-C. Alvarez-Hérault, R. Caire,"Application of dynamic transformer ratings to increase the reserve of primary substations for new load interconnection" in CIRED conference, Madrid, Spain, 2019.

MATLAB code and data for the research article : I. Daminov, A. Prokhorov, R. Caire, M-C Alvarez-Herault, “Energy limit of oil‐immersed transformers: A concept and its application in different climate conditions” in IET Generation, Transmission & Distribution (IF: 2,862, Q1), 2021,

Python module to calculate Near-Earth Asteroids Thermal properties

A dynamic simulation of an HVAC room temperature control system using MATLAB Simulink and Simscape. Features a PID controller tuned for thermal regulation against environmental heat transfer.

Power Switch Thermal Cauer Model

Simulation thermique dynamique (du bâtiment)

Cooling Performance Estimation of A public-figure-inspired outfit

A program that provides the ability to configure and compute discrete model of thermal processes in a rectangular object

A physics-informed neural network approach is proposed for control-oriented building thermal modeling, combining data with physical laws to improve accuracy and reduce training data needs. The method predicts room temperature, power use, and hidden thermal states more reliably than standard neural networks.