Energy
Building resilience into the future energy network requires novel solutions that do not yet exist.
The energy challenge
The challenge is not in any one area in the energy industry. It’s in joining up disconnected systems and embracing new technology.
A combination of heavily aged infrastructure, a shift to renewable energy sources, increasing energy demand, market volatility, grid connectivity challenges, heavily regulated planning processes and new technologies are creating significant complexity within the energy sector. Understanding uncertainty in energy systems, exploring alternative new systems and predicting behaviour is critical.
These are the perfect set of challenges for advanced modelling and simulation. Through uncertainty quantification, whole system modelling and digital twin technology we’re able to better understand complex energy systems, supporting teams to make design and operational decisions, improving efficiency and innovation.
How we work in energy
Our use cases in Energy.
The challenges facing the Energy industry are complex and the perfect candidate for digital methods. Discover our key use cases in the sector. Want to discuss your challenge? Get in touch.
Conceptual Design Modelling
Understand the energy system’s operational window by quantifying variability in performance across a range of input parameters using physics-based models. Modelling novel systems in this way can help shape their detailed designs as they move towards realisation.
Whole System Modelling
Develop and deploy simulations of complex energy systems to better understand their behaviour. Coupled with high performance compute and design space exploration, engineers can holistically consider performance and gain insight into the impact of changes across the entire system.
Uncertainty Quantification
Predict expected system behaviour of network energy systems through physics-based simulation. Leverage high performance compute and uncertainty quantification to run large-scale simulations to understand typical variability in the system. Better understand the system and improve performance by identifying discrepancies and key sources of uncertainty.
Collaborative Digital Twins
Design and deploy scalable digital twin platforms to improve infrastructure resilience, support the energy transition and address climate adaptation across large scale systems. Immersive 3D visualisation together with real time monitoring and predictive analytics of physical assets support operational decision making, training and maintenance planning.
Graphite Core Modelling
Coupling high-temperature neutronics simulations with structural mechanics to enable the modelling of graphite cores in advanced gas-cooled reactors to improve lifetime, predict performance degradation and support decommission efforts.
Impact studies
Energy problems we have solved.
Discover the energy challenges we’ve solved in the energy industry from advanced digital twins to complex Multi-physics simulations and uncertainty quantification.
Uncertainty Quantification for Nuclear Systems
Uncertainty has a huge impact on the expected performance of systems, particularly in the case of nuclear fusion reactors, where designs are still emergent. Uncertainty quantification identifies key drivers that have a significant impact on the output, highlighting key focus areas, helping to steer development.
Whole system asset modelling
Unaccounted-for-Gas arises predominantly from metering bias rather than physical gas loss and represents a significant operational and financial burden for National Gas Transmissions. A high-fidelity, forward-looking mathematical model was created to rapidly predict expected sensor readings which were used to compare measured values and identify discrepancies.
Why CFMS in energy
What CFMS provides that an in-house energy team cannot.
With our deep expertise in complex digital engineering, we act as an extension of your team, working with them to understand complexity in your energy system and uncover solutions to challenges.
Proven tools
We work with you to understand the energy challenges you face. Our proven knowledge in tools like MOOSE means we can support your teams in exploring systems, quantifying uncertainty and producing more robust designs.
Physics Capabilities
We’ve created tools that support the simulation of complex Multiphysics providing a deeper view of how a system will behave under certain conditions. These Multiphysics simulations are tightly coupled and can be run at HPC scale.
Modelling for Complexity
Through our whole system engineering approach, we holistically approach models to understand whole system behaviour, drilling into where a change in one part of a system has an impact on other areas of the system.
Sector thinking
Insights from the energy team.
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Using Uncertainty Quantification to Strengthen Engineering Decisions
Using Uncertainty Quantification to Strengthen Engineering Decisions
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Design optimisation for silver print heating circuits
Design optimisation for silver print heating circuits
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There’s always a place for you in engineering – INWED 2026
There’s always a place for you in engineering – INWED 2026
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CFMS appoints non-executive director to support greater digital engineering adoption
CFMS appoints non-executive director to support greater digital engineering adoption
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Digital Catapult and CFMS Announce Strategic Partnership
Digital Catapult and CFMS Announce Strategic Partnership
Common questions about energy systems simulation.
Energy systems are subject to large amounts of uncertainty. Due to a range of factors on both the load and generation, they often don’t perform as expected. Uncertainty quantification can help identify key drivers of system performance, supporting targeted investigations, proactive maintenance and improving performance.
Energy systems often rely on the interplay between several physical domains, for example heat, fluids and phase changes. Tightly coupled physics simulations consider all these domains simultaneously, solving for all parameters at the same time. This process enables more accurate simulations which better model the intricate nature of these systems. The improvement in accuracy reduces uncertainty, providing more realistic estimates of performance and therefore a deeper understanding of the system.
A digital twin utilises 3D visualisation along with real-time monitoring from assets and predictive analytics to support decision making. It enables you to assess performance, make quicker decisions and make decisions to move forward.
For new systems, being able to understand behaviour and the impact of decisions is critical and helps to improve the quality of decisions.
Work with CFMS
Tell us about your energy challenge.
To create resilient energy systems, ensuring demand can be met and market volatility can be managed is crucial. Understanding uncertainty, exploring new systems and predicting behaviour will enable this. We’re keen to discuss how we can support your challenges.