Overview
ABSTRACT
This article gives a general overview on numerical modelling, a technique widely used by engineers from the industry. Simulation is the exploitation of the mathematical modeling and its coupling with the computing power offered by modern computer, in order to understand, design, forecast and optimize. The article highlights various theoretical and practical aspects of computational modelling in the industrial sector and opens to some of the major innovations challenges which may change its practices (e.g. multi-physic modelling, reduced-order modelling, GPU computing and quantum computer).
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Jean-François SIGRIST: Research engineer, science journalist - Expertise & communication scientifiques (eye-PI) – Tours, France
INTRODUCTION
In the space of just a few decades, digital simulation has become one of the most widely used techniques by engineers in industry. Not only does it support the development of new products, it also helps to demonstrate and optimize their performance (e.g., reducing noise and energy consumption in land, sea and air transport, increasing the lifespan of mechanical structures and electronic components, and ensuring that buildings withstand environmental stresses such as wind, waves and earthquakes).
In the industrial sector in the broadest sense of the term, the use of this technique is becoming more widespread: while large industrial groups were the first to deploy it on a massive scale, it has gradually spread to smaller companies. It has also become a decision-making tool, used in many sectors beyond industry (e.g. agriculture, basic sciences – such as Earth and Universe – meteorology or climatology, medicine and health, etc.).
The aim of this article is to show the concepts underlying simulation, illustrate them with concrete examples, and discuss its practices and some of the innovation issues involved in its application to the industrial sector.
Readers will find references in the "Further reading" section associated with this article. An additional bibliography and links to websites provide useful resources for furthering knowledge on the subject.
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KEYWORDS
numerical simulation | data science | computational science
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Numerical simulation
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