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MODELLING AND SIMULATION g


Engineering expertise Esteco has been working in the optimisation field for nearly two decades, with a focus on real-life engineering problems. It promotes an approach based on ‘optimisation driven design’, where users can advance their design process with intelligent algorithms, which utilise machine learning techniques. These algorithms ‘understand’ each specific problem and find optimal designs in less time, at lower cost and using fewer computational resources than traditional techniques. Matteo Nicolich, Volta product manager


at Esteco, explained: ‘When building workflows composed of complex software chains, having a tool that automates all the repetitive work needed to interface one software with the other, or to interface the output of one software with the input of the following one is essential.’ Esteco also focuses on parametric optimisation. ‘This type of optimisation – based on the management of ‘free’, user- defined parameters – allows to apply the same techniques to a significantly more vast spectrum of problems compared to topological optimisation, which remains limited to geometry problems,’ Nicolich added. Esteco’s optimisation tools have been


used as part of the GasVessel project in Cyprus, where researchers are developing a prototype tank containment system, which will be installed on a vessel and used to transport compressed natural gas (CNG). The Volta platform has incorporated


a deterministic simulation to generate results as cost per cubic unit. Athos Kleanthous, commercial analyst at Cyprus Hydrocarbons Company (CHC), explained: ‘More specifically, we are running a simulation of a vessel, which lifts a cargo from point A and has to travel a certain number of nautical miles to point B, where it should discharge the cargo.’ The simulation needs a number


“We provide our customers with algorithms that are not only able to deploy multiple strategies at once to the same engineering problem, but are also able to learn from the problem itself and adapt accordingly”


32 Scientific Computing World October/November 2018


 Shape optimisation analysis of a mounting bracket created using Comsol Multiphysics software


of variables, which will be used by Volta, either as range limits or specific predetermined sets. Kleanthous said: ‘Volta has incorporated those variables into easily editable number sets. Volta has given us the opportunity to run optimisation and sensitivity analysis for the various scenarios our vessel was tested on.’ The cargo capacity, vessel’s speed, distance travelled, supply and demand variables have all been optimised using the Volta platform. CHC is working with Esteco to add new features or change specific processes in the simulation algorithm. It also expects to integrate Volta with its other projects. Kleanthous said: ‘Volta has helped


identify the smallest vessel capacity possible for a specific route, less number of ships employed in the specific supply chain and optimal speed to achieve on- time deliveries of the cargo in transit.’ ‘The results Volta has returned have shed light to the development team for the directions to follow, in order to deliver a viable project.


‘Besides the algorithm and the results


itself, Volta is a web-based tool, which is easily accessible through any internet browser, having inputs in a simple format and also offers an extremely simple user interface,’ Kleanthous added.


Autonomous future Esteco is now focusing on its optimisation automation tools. Nicolich explained the reasoning for this approach: ‘One of the biggest issues can be finding the most effective strategy to tackle the problem at hand. This is why we invested in researching and developing a whole new


set of smart algorithms that come with a possibility to run in ‘autonomous’ mode.’ ‘We provide our customers with algorithms that are not only able to deploy multiple strategies at once to the same engineering problem, but are also able to learn from the problem itself and adapt accordingly. ‘This is not about optimisation for dummies, but it is about obtaining viable and accurate insights with little time or information about the product at hand.’ However, such automation opens up another can of worms: management of the huge swathes of data that result. ‘Together with the management of simulation processes, there is the big issue of managing the data and all the work in progress that is related to the construction and creation of process automation, and all the data that are generated upon the execution of these processes,’ Nicolich added. Esteco has developed a Simulation Data Management tool, which allows users to keep track of all the information related to a simulation process, so they can cycle back along the history to see how a single piece of information was created, by which data and which model. Nicolich said: ‘With the Engineering


Data Intelligence tool, we want the set of functionalities to understand and mine information in this potentially huge amount of engineering data, and extract information on how to predict the next step of the design iteration.’ It’s an innovative approach and one that should help Esteco future proof its optimisation tools as automation and the resulting reams of big data start to impact the simulation and modelling space.


@scwmagazine | www.scientific-computing.com


COMSOL


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