Modelling & Simulation
Modelling and simulation, when done right, is an extremely powerful tool for gaining insight into the behaviour of complex multiphysics systems. Emergent behaviour is not generally intuitive and very often designs require domain knowledge that for various reasons designers may not have – a new technology being implemented; physics that you are not familiar with; complexity that goes beyond intuition. For many companies, keeping the in-house resources to conduct modelling and simulation may not always make sense, and that is where we can step in to help.
Developing your designs digitally is much more cost effective than conducting numerous tests. In addition, testing generally gives you full detail at the points which you measure, but the rest remains hidden. With a validated model, the whole system opens up to you and you can probe for information anywhere. This generally means that you get to your system test with the confidence that it will be a success.
Modelling and simulation is one of our core strengths. Whether you need CFD, FEA, multiphysics or bespoke models – trust Engenya.
The importance of using the right tool for the job cannot be understated in the context of modelling and simulation. Sometimes the driver is capability while at other times it is cost…usually it is both. Engenya will work with you to identify the best tool for your simulation, considering not only the required capabilities, but also future use and integration into your own processes and data access and storage requirements. To this end, we implement a range of tools that include both open source and proprietary solvers and post processors. We conduct our simulations in-house on our own Linux cluster. Examples of tools we implement include:
- LS-Dyna (Leading commercial solver for FEA, CFD and multiphysics implicit and explicit solutions)
- Code Aster (Open source solver for FEA implicit and explicit solutions, released and supported by SDF France)
- Converge (Commercial CFD solver)
- OpenFOAM (Open source library of CFD solvers)
- Octave (Open source equivalent of Matlab used for data analysis and numerical simulation)
- Vensim (Commercial solver for system dynamics modelling)
- OpenModelica (Open source system modeling solver)
- LS-PrePost (Commercial pre- and post-processor for LS-Dyna)
- Tecplot (Commercial data analysis and post-processing software)
- Paraview (Open source data analysis and post processing software)
- Salome (Open source pre- and post-processor for use with Code Aster and OpenFOAM)
Computational Fluid Dynamics can be applied to a broad class of problems that generally deal with mass transport and heat transfer. While the majority of cases consider the flow of a single fluid, much more complex cases involving multi-phase flow, phase change and combustion can be solved. The example below, for instance, contains gas, liquid and solid particles (size exaggerated) and studies the interaction between these media under a set of specified conditions.
While it is commonly understood that the design of aircraft, cars, trains and boats would never be as efficient as it is today without CFD, many more objects benefit from this technology in their design. The design of piping systems and valves for example, the design of propellers to avoid cavitation, the design of your kettle’s thermal management, the design of your building’s air conditioning system, the evaluation of flow around buildings in metropolitan areas, the design of your oven’s air circulation and many more. Engenya has experience in applying CFD to a wide range of problems, from the analysis of valve operation to the simulation of explosives used in oil reservoir perforation.
Just like CFD, Finite Element Analysis is a powerful computational method that can be applied to a wide range of problems. Whereas CFD solves flow and pressure fields, FEA is concerned primarily with deformation, stress and strain of solid materials. In reality, methods are available for solving problems involving static and dynamic response of elastic, plastic and hyperelastic materials to name a few. CFD and FEA are often coupled to resolve the behaviour of structures subject to loading by fluids and vice versa. The possibilities are endless and if you take a look at our experience page, you will see some examples of what we have done in the past.
FEA helps reduce the uncertainty when designing complex components or structures, subject to complex loading and environmental conditions that could include thermal, electromagnetic or blast loads – or all of them simultaneously.
The application of FEA in solving complex problems is one of Engenya’s core strengths. Our people have over 30 years of experience doing this and have worked on problems for the automotive, aerospace, energy, medtech, defence and manufacturing industries.
Let us help you develop your product, system or device. With properly applied FEA you will be able to reduce testing and ensure that the first time you test is also the last.
With the ever increasing computing power at our disposal, we are able to simulate increasingly complex coupled phenomena. In nature, coupled systems are not the exception but rather the norm. The most common couplings generally happen between fluid and structure, such as that shown alongside. In this example, a shaped charge is simulated using a CFD solver while the target is simulated using an FEA solver. All of this happens within an integrated environment, but the result is a direct calculation of the penetration of the hypersonic jet into the solid target. In the same way, couplings can be used to calculate conjugate heat transfer, electromagnetic effects, multi-phase material couplings, aeroelastic phenomena, lubrication and so on.
Deciding on how to go about coupling different elements of a physical problem is critical in determining how effective the simulation is. We have experience with this.
System models can take many forms that go from representing a system’s requirements and their interactions, to representing the behaviour of the system’s components on a physical level, making the extraction of emergent behaviour that is not intuitive possible and enabling the evaluation of system performance. Such models, if properly applied, become powerful decision making tools when designing systems.
These tools do not need to be confined to the realm of physics, they can be applied to social systems as well. Consider the example – this is a simplified Vensim system dynamics project model. It is a tool that enables the testing of project management policy scenarios in order to provide decision making insight. Its power comes from being able to uncover unexpected consequences to well meant actions. Naturally, it can also be used to model the performance of a … gearbox, bicycle, etc.
Then of course, we have more dedicated system performance modeling tools such as OpenModelica, which are more explicitly geared to the technical side and enable the functional and physical architecture to be reflected in the model.
Sometimes the tools at our disposal fall just short of what we need. In such cases, we can choose to write our own code to either augment what other tools deliver or we can simply build our own models from first principles. We can do this within the framework of a tool such as Octave and its various toolboxes, or we can turn to a programming language directly. It is quite rare that we have to go to these lengths, but it is possible if required.
We have used this approach in the augmentation of results we obtain in our completion job simulations. Read about the details here.