Did you know that Darwin contributes to thermal comfort in train stations?

In what ways can we ensure thermal comfort in semi-open plan glazed buildings all year round? This is a challenging question for experts in digital simulation in the fields of fluid mechanics and heat transfer.
Darwin's marble bust on the colored spectrogram of thermal studies

Thermal comfort in indoor environments can be confidently predicted by using empirical indicators and human body balance equations but the same is not true for open plan buildings, also known as buildings featuring semi-outdoor spaces. Rapid changes in ambient conditions require metabolic rate modelling in dynamic conditions. The teams of AREP's Civil Engineering Division regularly carry out predictive studies in order to support architects and urban planners in their work within the broader context of designing spaces for people on the move.


Let's take the example of Chambéry multimodal interchange hub


The issue

Designing a glazed / transparent railway station capable of providing thermal comfort all year round with a minimum energy footprint.


The values

Train stations with transparent facades lacking air conditioning or natural ventilation feature too high temperatures in summer (around 30°C). In winter, temperatures in stations with neither double glazing nor heating reach extremely low temperatures (3 to 4°C).

The idea

In the case of Chambéry multimodal interchange hub, the decision was made from the start to add silkscreen printing on the transparent walls and optimize insulation.

However, depending on the season of the year, solutions with respect to comfort may differ, the main difficulty being to find a solution which remains satisfying all year round while based on criteria that may be contrasting (for example, limiting solar gains and ensuring maximum luminosity).


By what means?

By using genetic algorithms, i.e. a process invented to mimic natural selection which is used on a population of candidate solutions.

The initial population of solutions is randomly generated, then the fittest are selected on the basis of predetermined criteria to form a new generation by crossing the best parameters of the “parents”. The basic techniques follow the principles laid down by Charles Darwin: reproduction, crossover and natural selection of… data! The process leads to successive generations of solutions where random mutations may be introduced in order to further explore all available possibilities.

These techniques are not new but they haven’t been applied on buildings until recently, the increase in available digital resources allowing to test every single solution and scenario.