What is computational science?

Computational science augments traditional research methods by accelerating and guiding experimental work and providing insight into processes and results. It is used across Shell’s businesses to predict everything from the chemistry of catalysts and batteries to capturing flow through reactors, pipelines and rocks. These are complex simulations which require high performance computing and algorithm optimisation.

A key aim of computational science is to use computer models to predict the performance of materials and systems in specific situations. One of the most striking aspects of computational science projects is their breadth of scale. This multiscale modelling covers interactions at the atomic and molecular levels to the design of reactors in industrial plants.

Computational technology in Shell.

Our grasp of computational technology helped us to lead the way in technological developments in exploration in the 1960s, 70s and 80s. Demand for computational design and analysis has increased dramatically since mid-2000’s across increasingly varied domains. The growth in computer power from Moore’s law has made realistic catalyst modelling and complex fluid flow studies possible that were unthinkable only 15 years ago. Shell has a diverse team of chemical engineers, mechanical engineers, aerospace engineers, chemists, material scientists, mathematicians, physicists and computational scientists. This expertise in mathematics and computing is what gives us such a strong advantage today in developing and adopting digital technology.

By combining data-based models with physics/chemistry based computational models, we augment the power of both by integrating the speed and agility of AI with the interpretability and explainability of Computational Science, we move towards an era of Augmented Intelligence, where we augment our decision making manifold. Find out more in our recent publication on developing machine learning models for materials datasets.

Find out more

Shell.ai scientific conference 2022

Shell and the Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR) are conveying a symposium on integrated digital and experimental design of materials, in Bengaluru, India.

Research collaborations for low-carbon energy

Read how a rich ecosystem of external research partnerships supports Shell’s in developing low-carbon technologies.

System level modelling to pioneer net-zero carbon emissions in cement manufacturing

Read how Shell uses system level modelling to help heavy industry – such as India’s Dalmia Cement (Bharat) Limited - find pathways to decarbonise.

How we use supercomputers to develop Shell E-Fluids

Read how Shell Computational Science team played a critical role in demonstrating the improved performance of Shell E‑Fluids, a coolant liquid for batteries used for electric vehicles.

High Performance Computing for a sustainable hydrogen economy

Find out more how we use digital solutions to scale up the share of hydrogen in the energy system.

The road towards faster and sharper insights

Read how our experts in High Performance Computing (HPC) technologies are helping us run algorithms faster and more efficiently.

Other fields of application of Computational Science

  • Optimal spatial planning for offshore windfarms

    Optimal spatial planning for offshore windfarms

    Computational Science researchers have developed an innovative design framework rooted in computational fluid dynamics and systems modelling to reduce the so called wake-effect in offshore wind farms. The framework integrates accurate wake predictions to inform the layout of future offshore assets. With this research, we have a better understanding of yield production of individual windmills in a farm, which enables a better economic assessment of projects as well as their optimized spatial planning. 

  • Technology innovation for carbon capture systems

    Technology innovation for carbon capture systems

    Computational science supports the development of efficient and less costly amine-based solid adsorbent sequestration technologies to capture carbon dioxide from flue gases and, eventually, directly from the atmosphere. Our researchers have developed an experimentally validated mathematical workflow based on continuum models, for analysing the carbon capture processes in a fixed-bed reactor with solid adsorbent. This research enhances experimental studies to enable quick and robust scientific exploration of better designs for Carbon capture systems.

  • Battery model

    Improving battery performance to increase potential for renewable energy and safety

    Chemical storage of electrical energy is an important aspect of meeting modern energy demands. It can mitigate the intermittency and spatial variability of renewable energy availability. Combining traditional physics and chemistry with simulation and advanced imaging technology enables us to compare different kinds of batteries, not only looking at which materials perform better, but also which are more sustainable. We are looking across the end-to-end life of the battery from design and use right through to materials recovery and recycling. Shell is modelling the changes in the physical state and composition of electrodes and electrolytes in batteries as well as performance at pack level. Find out more about the research conducted with University of California Berkeley.

  • Optimal design for the maritime transport of hydrogen

    Optimal design for the maritime transport of hydrogen

    Shell leads an international research consortium that aim to develop thermal modelling and insulation strategies for the optimal design of large-scale cryogenic hydrogen storage tanks (20,000 – 100,000 m3). This fundamental research has application for the maritime and international trade of hydrogen, which as a versatile fuel and feedstock can decarbonise different sectors. To date, there is no robust thermal and insulation property for such storage systems. Our deep understanding of thermodynamic modelling of molecules and systems integration would be a key differentiator in our contributions to this consortium. This research is sponsored by the US department of Energy.