FluxTwin CFD
Interactive thermal digital twins to visualize and assess your data center directly from your browser.
FluxTwin Insight
KPI-based analytics platform for the assessment of energy efficiency in data centers
ECO-EAWA
Energy-aware workload assigment tool for the reduction of IT energy consumption in data centers

Visualize complex airflow dynamics, instantly identify dangerous hotspots, and validate cooling strategies before physical deployment.

Redesign containment and HVAC architectures to achieve peak performance, unlock stranded capacity, and minimize cooling costs.

Identify Hot Spots Before They Happen
Simulations can predict temperature distribution within the data center, revealing potential hot spots where equipment could overheat and malfunction. This allows for adjustments to cooling systems or server placement before construction begins, saving time, money, and preventing costly equipment failures down the line.

Optimize Cooling System Design
Simulations allow you to test different cooling configurations air conditioning placement and airflow patterns to find the most efficient setup for your specific data center layout and equipment. This can lead to significant cost savings on cooling infrastructure and energy use.

Optimizing Airflow Effectiveness
Simulations can reveal areas of stagnant air or uneven cooling. This allows for adjustments to airflow patterns to ensure all equipment receives cool air efficiently, minimizing energy wasted on unnecessary cooling.

Right-Sizing Cooling Equipment
By accurately predicting cooling needs through simulations, you can avoid over-sizing cooling systems. This saves money on upfront equipment costs and ongoing energy consumption.
Our CFD simulations can capture hot air recirculations and cold air by-passes that reduce thermal efficiency and increase cooling energy consumption.

Digital Twin Simulation
We build a highly accurate 3D thermal model of your existing infrastructure to baseline current performance, visualize airflow, and pinpoint critical inefficiencies.
Predictive Analysis & Scenario Testing
Leverage advanced CFD algorithms to run “what-if” scenarios, test N-1 cooling failures, and discover hidden optimization opportunities without physical risk.
Deploy Peak Optimization
Implement data-driven architectural changes that drastically reduce PUE, unlock stranded IT capacity, and minimize your operational cooling costs.



We simulate thermal structures of air and liquid-cooled pilot sites for the energy-efficient management of small data centers

We develop digital solutions for the energy optimization of server rooms integrated to the tertiary bulidings

We introduce the Self-Assessment Tool (SAT) as a unified, modular, and extensible framework for the evaluation of thermal and energy performance of data centers based on IT and cooling data sourced from data monitoring systems.

This study introduces a novel methodology for maximizing waste heat capture from the cooling coils by optimizing workload distribution in an edge data center consisting of air-cooled servers. The maximization of outlet temperatures algorithm (MOTA) was developed using a validated fast thermal evaluation approach.
Numerical simulations conducted using the validated CHT model show that the MOTA can improve heat recovery by up to 17.1% under various IT loads. Furthermore, optimizing the water flow rate can reduce the cooling load by up to 53.2%. These combined results highlight the potential of the proposed algorithm for energy-efficient management of data centers.

This study investigates efficiency assessment of two European pilot data centers, located in Denmark and Poland, according to the KPIs calculated through Computational Fluid Dynamics (CFD) simulations of airflow and thermal structures.
Numerical simulations demonstrate that the efficiency of an existing data center can be enhanced by up to 75% using the presented approach, although the improvement varied significantly with the specific KPIs. The computational approach proposed here can be readily generalized to guide the efficiency assessment and improvement of existing data centers.

This study represents the development and optimization of a micro-baffle design to enhance heat transfer in film boiling. Numerical simulations are performed using an open-source computational fluid dynamics (CFD) model, which incorporates the Lee model for momentum source associated with the phase change, and the Volume of Fluid (VOF) method to capture bubble dynamics. This study demonstrates the potential of micro-baffle designs in controlling bubble dynamics and improving heat transfer in film boiling, thereby aiding the design of efficient thermal systems.

In this study, an open-source computational fluid dynamics (CFD) model was developed based on OpenFOAM libraries for the accurate and robust simulation of thermal distribution in a data center.

The data center has been retrofitted by creating a hot aisle with the implementation of a moving baffle at the rear of the rack. Numerical simulations conducted for two working scenarios have demonstrated that such a minor modification could result in remarkable enhancement in the cooling efficiency. Efficiency of the data center has improved by 47.2% and 22.7% with respect to the RCI (Rack Cooling Index) and RHI (Return Heat Index), respectively.

This article provides experimental and numerical data for the flow and thermal distributions inside an air-cooled data center. The experimental data contains the exhaust temperature profile obtained from an experimental campaign and the numerical data contains OpenFOAM and script files for the simulation of the thermal structure based on the experimental study.

In this study, a conjugate heat transfer (CHT) numerical model is developed and validated with experimental data to simulate heat transfer from the CPU to the air and cold plate considering the effect of thermal paste. The cooling performance of an in-house developed cold plate design is thoroughly investigated via the validated CHT model.

