search.noResults

search.searching

saml.title
dataCollection.invalidEmail
note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
MODELLING AND SIMULATION


Rising renewables


GEMMA CHURCH EXAMINES HOW SIMULATION AND MODELLING AID THE INCREASINGLY DIVERSE RENEWABLE ENERGY FIELD


Renewables are growing in both scale and complexity as an increasing number of industries


search for an eco-alternative to meet their energy needs. The global lockdown has partially


driven this trend, as emissions dropped drastically over the last year, with government targets also pushing an increasing number of renewable energy initiatives. The UK, for example, plans to move to net-zero by 2050 and China is aiming for carbon neutrality by 2060. This is where simulation can help both nations and organisations meet their ambitious targets, as Jonathan Bailey, director of energy and materials, infrastructure and cities, EuroNorth at Dassault Systèmes, explained: ‘To achieve the UK’s aim by 2050, engineers need to work more collaboratively by integrating data, people and processes to optimise decision-making and to make “right-first- time” the norm. ‘Primarily, we are seeing this done


through the digitisation of businesses and them leveraging virtual twin technology,


which has a key role to play in simulation,’ Bailey added. ‘In the energy industry, virtual twins are being deployed to create anything from a model of a wind turbine to nuclear reactors or even the orchestration of construction workers tasked with creating an energy storage facility. This concept reduces the need for physical prototypes and increases the accuracy of the data used to assess the viability of an innovation.’ But, from fuel cells to wind turbines


and solar panels, the growing diversity of the renewables industry is introducing challenges for simulation and modelling. This is because each renewable option brings with it a unique set of challenges, many of which span multiple modelling scales and scientific disciplines, while requiring a high degree of specialist knowledge. Understanding electrochemistry and


semiconductor physics, for example, is one challenge for engineers, according to Ed Fontes, CTO of Comsol, who added: ‘When you have such an expansive field, there are simply not enough scientists and engineers that are experts in the theory and mathematical modeling of electrochemical and photovoltaic cells. So, many of our customers have to develop and learn in parallel. The same issue may be valid regarding electromagnetic motors and generators.’ To address this lack of specialist


knowledge, ‘it is very important that we provide accurate and ready-made descriptions of the involved physics


phenomena, reliable material properties, as well as thermodynamic and kinetics models,’ Fontes added. ‘A non-expert should be able to define the input data required for high-fidelity multiphysics models.’ Non-experts should also be able to


work across different scales as Fontes explained: ‘This implies that you can stay with one tool all the way from the microscale to the macroscale. You can also link the models at the different scales to be accurate over a wide range of operating conditions.’


Wider changes must also be made to the design process at the organisational level. Dr Uwe Schramm, CTO at Altair, said: ‘Traditionally, the entire design process and, namely, simulation has been applied by means of standalone models in departments that used to work in silos.’ ‘To address the challenges, companies


need to break those silos, eliminate standalone simulation models, and start thinking from a multiphysics, data-


”To address the challenges, companies need to break those silos, eliminate standalone simulation models, and start thinking from a multiphysics, data- integrated point of view”


26 Scientific Computing World Winter 2021


@scwmagazine | www.scientific-computing.com


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34