02.07.2025
Blog

Why Dynamic Thermal Simulation is key to sustainable revalorisation

Simulation thermique dynamique

What Is Dynamic Thermal Simulation (DTS)?

Unlike traditional static calculations, DTS models a building’s thermal behavior on an hourly basis over a full year. It factors in:

🏢 The building envelope (insulation, glazing, airtightness, etc.),

💡 Internal loads (equipment, lighting, occupancy),

☀️Solar gains (depending on building orientation),

🌦️Climate data (historical or future RCP*-based scenarios),

🌬️Ventilation, heating, and cooling systems.

In a revalorisation context, DTS enables us to simulate various upgrade scenarios and pinpoint the most impactful investments—for comfort, energy efficiency, and long-term ROI.

*RCP: Representative Concentration Pathways. These are climate projections developed by the IPCC (Intergovernmental Panel on Climate Change) to model future climate evolution based on different levels of greenhouse gas emissions.

Real-world case: targeting overheating in Hasselt

During a building assessment in Hasselt, our experts detected severe overheating issues in several office zones, particularly open spaces. To define the smartest retrofit path, we conducted a DTS on two representative areas: a standard floor and the top floor under a flat roof.

credits: Faast

Initial setup
 

  • Climate: future RCP4.5 scenario, anticipating climate change effects.
  • Internal loads: 70W/person, 12m²/person, 70% average occupancy.
  • Lighting: 10.4W/m²; office equipment: 11.3W/m².
  • Building envelope: poor insulation, inefficient double glazing (Ug > 3), 12cm PU roof insulation, average airtightness.
  • HVAC: heating at 22°C; no active ventilation or cooling.

Key findings

  • Solar gains accounted for 40% of thermal loads—more than lighting or occupancy.
  • Several zones exceeded comfort thresholds (over 5% of occupied hours > 25°C).
  • DTS enabled precise quantification and testing of multiple retrofit strategies.
Solar vs other sources lighting occupation elec

Internal and external monthly charges during occupancy hours (Open space 1 – typical floor). Solar gains accounted for 40% of thermal loads and more than lighting or occupancy | Credits: Faast

From data to actionable insights

Among the scenarios we tested:

✔️High-performance glazing: reduced overheating time by 20%.

✔️Frame replacement: minimal additional benefit due to small surface area, though improved airtightness slightly.

✔️External blinds (automated): 13% reduction—not as effective as glazing replacement and less predictable in user behavior.

✔️Daytime natural ventilation: simple yet effective—manual window opening reduced overheating by up to 30% in targeted areas.

✔️Fixed solar shading: up to 25% overheating reduction, but led to a 9% increase in winter heating demand.

Best-performing combo: high-performance glazing + natural daytime ventilation = up to 44% reduction in overheating and a 14% cut in total energy consumption.

The best-performing combo? High-performance glazing combined with natural daytime ventilation — it can reduce overheating by up to 44% and cut total energy consumption by 14%.

Bart StevensEnergy Advisor pulse

High performance glazing

Solar radiation: base vs high-performance glazing | Credits: Faast

External blinds

Solar radiation: base vs external blinds | Credits: Faast

Why it matters for investors

🔍 Data-backed decisions – Compare interventions based on their real, measured impact.

🏢 Protect asset value – Address thermal discomfort before it affects occupancy rates.

📈 Maximise impact– Prioritise actions with the greatest comfort and energy benefits.

🌍 Future-proof your asset – DTS allows simulation under future climate scenarios (RCPs), supporting long-term resilience.

Conclusion: model first, invest smart

At PULSE, we don’t just speculate—we simulate. Dynamic Thermal Simulation is a cornerstone of our pragmatic, ROI-driven revalorisation strategy. It brings clarity, precision, and credibility to your investment roadmap.

Ready to unlock the hidden potential of your building data?

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