Thermal Digital Twin with Ansys Twin Builder
Distil a full FEA thermal model into a real-time digital twin that runs on a laptop.
Last reviewed: March 2026Overview
A digital twin is a real-time computational model of a physical system that receives live sensor inputs, predicts current state, and provides insight that sensors alone cannot — such as internal temperatures at locations where thermocouples cannot be installed, or predicted time-to-failure given the current thermal load profile. The bottleneck for digital twins is computational speed: a full FEA thermal simulation of an avionics bay takes minutes to hours, while a digital twin must respond in seconds or faster. Reduced-Order Models (ROMs) solve this by capturing the dominant physics of the full FEA in a model with thousands of degrees of freedom instead of millions, running in milliseconds while retaining high accuracy.
Ansys Twin Builder provides an integrated environment for creating and deploying ROMs. You will use the thermal ROM workflow: first run parametric FEA thermal simulations in Ansys Mechanical (varying heat dissipation levels for each avionics unit as the design parameter), extract the temperature field snapshots, apply Proper Orthogonal Decomposition (POD) to reduce the dimensionality, and generate a ROM that maps heat dissipation inputs to temperature field outputs. This ROM is then imported into Twin Builder, connected to a simulated telemetry data source, and run in real time to predict the thermal state of the avionics bay under a realistic mission profile.
Thermal digital twins are in active deployment at aircraft OEMs for avionics bay design (Airbus, Boeing), engine health monitoring (Rolls-Royce, GE Aerospace), and spacecraft thermal management (JPL, ESA). Ansys Twin Builder proficiency is specifically cited in job postings for simulation and digital engineering roles at these organisations, making this project a direct career investment.
What You'll Learn
- ✓ Set up and run parametric Ansys Mechanical thermal simulations to generate ROM training snapshots
- ✓ Apply Proper Orthogonal Decomposition in Ansys to reduce a thermal FEA model to a compact ROM
- ✓ Deploy a ROM in Ansys Twin Builder connected to time-varying heat dissipation inputs
- ✓ Validate ROM temperature predictions against full FEA solutions and quantify accuracy across the input space
- ✓ Interpret digital twin outputs to predict thermal margin violations under a realistic avionics mission profile
Step-by-Step Guide
Build the avionics bay FEA thermal model
Create a simplified avionics bay geometry in Ansys Mechanical: a rectangular aluminium enclosure (300×200×150 mm, 3 mm wall thickness) with five avionics units modelled as solid blocks of known heat dissipation and thermal conductivity. Apply convective boundary conditions on the exterior faces (h = 15 W/m²K, ambient 55°C representing a hot-day ground scenario). Define five input parameters: heat dissipation of each avionics unit (range 5–50 W each). Mesh with Hex20 elements and verify the mesh quality metrics.
Run parametric FEA sweeps for ROM training
Use Ansys Mechanical's Parameter Set manager to define a design-of-experiments table covering the five heat dissipation inputs with a space-filling Latin hypercube design of 50 parameter combinations. Run all 50 steady-state thermal simulations. Export the temperature field for each simulation as a snapshot data file. These 50 temperature field snapshots form the training data for the ROM. Verify the range of maximum temperatures across the design space (expect 60–130°C).
Generate the ROM with POD in Twin Builder
Import the Ansys Mechanical project and snapshot data into Ansys Twin Builder using the ROM Builder workflow. Configure the POD settings: select the temperature field as the output quantity of interest, set the number of retained modes to capture 99.9% of the energy, and define the five heat dissipation values as the ROM input parameters. Generate the ROM and inspect the singular value decay plot to verify the chosen truncation level is appropriate.
Validate ROM accuracy on held-out FEA solutions
Run 10 additional Ansys Mechanical simulations with input combinations not used during ROM training (random samples from the parameter space). Query the ROM for the same input combinations and compare the predicted temperature fields against the FEA solutions. Compute the maximum absolute temperature error and the L2 norm error across the field for each test case. Plot the ROM vs. FEA maximum temperatures in a parity plot and compute the R² value.
Build the real-time Twin Builder dashboard
In Ansys Twin Builder, create a system diagram connecting the ROM to: (a) a CSV-driven signal source simulating a 4-hour avionics mission profile where heat dissipation varies by operational phase (standby, cruise, high-activity), and (b) a threshold monitor block that triggers a warning flag when any predicted temperature exceeds the avionics qualification limit of 85°C. Run the simulation and visualise the predicted temperature time history at five critical avionics locations.
Analyse thermal margins and write the digital twin report
Identify which avionics unit first exceeds the 85°C limit during the mission profile and at what mission elapsed time. Compute the remaining thermal margin (°C below the limit) for each unit at the peak load phase. Explore what reduction in heat dissipation from the highest-power unit prevents any violation. Write a Digital Twin Validation Report: model description, ROM accuracy metrics, mission profile simulation results, thermal margin analysis, and a recommendation section on whether the current avionics bay design is thermally adequate for the defined mission.
Career Connection
See how this project connects to real aerospace careers.
Aerospace Engineer →
Thermal and systems engineers at aircraft and spacecraft OEMs build and maintain thermal digital twins using Twin Builder and equivalent tools as part of the production design and sustainment process.
Avionics Technician →
Technicians diagnosing avionics overheating issues can use digital twin thermal models to identify root causes and evaluate corrective action effectiveness without pulling hardware.
Aerospace Manufacturing →
Manufacturing engineers use thermal ROMs to predict component temperatures during process steps (composite curing, soldering) and optimise process parameters for yield.
Space Operations →
Spacecraft thermal operations teams use ROM-based digital twins to predict onboard temperatures during eclipse/sunlight transitions and plan heater cycling.
Go Further
- Extend the ROM to transient thermal analysis by including time as a parameter and validating the ROM's ability to predict thermal ramp-up rates during power-on sequences.
- Connect the Twin Builder ROM to a live OPC-UA data server using the Twin Builder runtime API, simulating a real-time digital thread from avionics telemetry to the thermal prediction model.
- Perform uncertainty quantification on the ROM: treat the convection coefficient h as an uncertain input (±30%) and use Monte Carlo sampling through the ROM to compute the probability that any component exceeds 85°C.
- Compare the Ansys Twin Builder ROM against a hand-coded POD ROM implemented in Python using NumPy, verifying that both give identical temperature predictions and identifying any numerical differences in the POD truncation.