Thermal Modeling β€’ Test-Aware Design β€’ Electronics Hardware

Instrumented Electronics Enclosure

Designed a compact, avionics-style electronics enclosure with internal heat dissipation and thermocouple access to support transient thermal prediction, design trade studies, and validation-ready model correlation across power and ambient conditions.

Methods: Reduced-order RC thermal network β†’ COMSOL transient conduction with convection boundary conditions β†’ power & ambient sweeps.

System overview

  • Mechanical layout: aluminum baseplate, enclosure walls, removable lid, and mounting features for a representative internal load.
  • Heat source representation: internal dissipating component (heater/dummy load) coupled to the baseplate conduction path.
  • Interfaces: fastener-driven assembly and contact surfaces treated as thermal resistances to capture realistic heat flow.
  • Instrumentation: thermocouple access features placed to measure hot spots, gradients, and external surface response.
Primary risk drivers: convection uncertainty, contact resistance, sensor placement, boundary condition assumptions.

Modeling approach

  • Reduced-order model: RC thermal network to estimate dominant paths, time constant, and steady-state response prior to FEM.
  • COMSOL FEM: transient conduction in solids with convection boundary conditions; interfaces included via contact resistance where relevant.
  • Parameter sweeps: power (5/10/15 W), ambient (cold/nominal/hot), wall thickness, insulation placement strategy.
Engineering focus: identify the dominant thermal bottleneck, quantify margin under worst-case conditions, and drive design decisions with measurable criteria.

Design trades

  • Wall thickness: balanced spreading resistance and peak temperature reduction against mass and transient response time.
  • Insulation strategy: compared internal liner vs external wrap to manage gradients and preserve margin across ambient conditions.
  • Sensor placement: selected locations to validate predicted hot spots and isolate conduction vs convection effects.
  • Interface quality: evaluated sensitivity to contact resistance assumptions to bound model uncertainty.

Validation plan

  • Step-power transient: compare warm-up curve shape and time constant (model vs measurement).
  • Steady-state plateau: compare peak and surface temperatures; compute error and margin impact.
  • Uncertainty framing: bound convection coefficient and contact resistance to explain model error and improve prediction confidence.
Correlation deliverable: predicted vs measured temperatures (source/interior/exterior) with error attribution + updated boundary assumptions.