What is computational mechanics?

The field of research known as computational mechanics uses computational techniques to investigate events regulated by the laws of mechanics. Computational mechanics was traditionally regarded as a branch of applied mechanics until computational science (also known as scientific computing) emerged as a "third way" in addition to theoretical and experimental sciences. It is currently regarded as a branch of computational science.

Among the various specializations found within CM are computational fluid dynamics, computational thermodynamics, computational electromagnetics, and computational solid mechanics.

Mathematics

Partial differential equations, linear algebra, and numerical analysis are the mathematical subfields that have the closest connections to computational mechanics.

The finite element, finite difference, and boundary element methods are the most widely used numerical techniques in that order. While finite difference approaches are almost equally relevant in fluid mechanics, thermodynamics, and electromagnetic, finite element methods are much more common in solid mechanics. Although the boundary element method is less common overall, it does have a place in some fields, such as acoustics engineering.

Computing Science

Computer programming, algorithms, and parallel computing all have a significant impact on CM from a computing perspective. FORTRAN is the most used programming language in the scientific world, including computational mechanics. Popularity of C++ has grown recently.

The adoption of C++ as the de facto language in the scientific computing community has been sluggish. The proprietary language/environment MATLAB is also frequently used, particularly for quick application development and model verification, because to its extremely intuitive way of expressing mathematical operations and its built-in visualization capabilities.

Process

Computational mechanics researchers use a set of procedures to examine a particular mechanical process:

1. The physical phenomenon is given a mathematical model. This typically entails using partial differential equations to represent the natural or technical system. A complex system is formalized in this step using physics.
2. The equations are transformed into formats appropriate for digital processing. Because it entails converting the initial continuous model into a roughly discrete model, this process is known as discretization. It typically converts a system of partial differential equations (or a set of them) into a set of algebraic equations. Numerical analysis is a field that studies the procedures involved in this stage.
3. Iterative approaches (which start with a trial solution and eventually arrive at the actual answer via consecutive refining) or direct methods (which start with a trial solution and ultimately result in the solution) are used to solve discretized equations in computer programmes. At this point, supercomputers or parallel computers may be used, depending on the nature of the problem.
4. Utilising either experimental data or simplified models with precise analytical solutions, the mathematical model, numerical processes, and computer codes are validated. New numerical or computational approaches are usually tested by comparing their outcomes to those of already widely used numerical methods. Benchmark difficulties are frequently offered as well. The numerical results must also be visualised, and they are frequently given a physical meaning.

Applications

Vehicle crash simulation, petroleum reservoir modelling, biomechanics, glass manufacture, and semiconductor modelling are a few instances of practical applications of computational mechanics.

With the aid of computational mechanics' tools, complex systems that would be very challenging or impossible to tackle using analytical approaches have been successfully simulated.

Computational mechanics

Computational mechanics is the use of modelling and simulation to comprehend and forecast increasingly complicated physical phenomena in science and industry. The research focuses on fields like solid mechanics, fluid mechanics, fluid structure interaction, multiphase flow, material science, mathematics, and numerical methods that incorporate and enhance the application of mechanics.

It discusses cutting-edge techniques and complicated computational technology. As an illustration, the governing equations in fluid mechanics frequently exhibit stochastic behavior in a deterministic environment and are typically non-linear, time- and history-dependent.

With stable research funding, international recognition, industry-based research, and successful results, the Department has reached a critical mass. The following areas have been the focus of our effort:

• To comprehending complex non-Newtonian fluid behaviors or multiphase fluid flow, it is necessary to develop new and effective numerical methods and algorithms, such as the particle and mesh free approaches.
• Gaining new knowledge about physical flow processes, such as how pulse detonating engines work and how fiber-reinforced prototypes are made via additive manufacturing.
• A deeper knowledge of the failure mechanisms of composites, especially hybrid composites and metamaterials, as well as the development of modelling and simulation tools for composites design.
• The creation of tools for modelling and simulating sound and vibration, particularly the creation of strategies for the reduction of noise from traffic, construction, and aircraft fly-bys.
• Creation of simulation and modelling software to aid in the comprehension of plastic deformation processes and high strain rate deformation for blast mitigation.