Tips & Tricks

Visual-Environment Highlight of Visual-CFD: Adjoint Optimisation

The adjoint method has long been considered as the tool of choice for gradient-based optimisation in computational fluid dynamics (CFD). The adjoint method, allows computation of sensitivities, i.e. the derivative of the objective function with respect to the design variables and later shape optimisation. The OpenFOAM supports the continuous adjoint method, it is faster and requires less memory than the discrete adjoint method. However, it requires fine meshes to get desired/optimal output. Visual-CFD makes it even simpler to define and calculate the sensitivities and optimisation with its ease-of-use functionality. Currently it is available for incompressible laminar and turbulent flows with objective functions of lift, drag, momentum for external flow and pressure loss for internal flows.

Raj Kumar Barnawal Virtual Integration Platform

Visual-Environment Highlight of Visual-CFD: Reacting Species

Modelling reactive systems is numerically expensive since the non-linear reaction kinetics leads to stiff-ODE systems in the species and energy conservation equations. Special solution algorithms, capable of handling these stiff systems of equations, different ODE solvers are supported for the same. Strategies to reduce the numerical effort to solve reactive flows include chemistry tabulation, which is also supported. A critical choice in simulating reactive flows is the combustion model, there are different combustion model has been supported which can be picked based on user’s choice. Enough intelligence has been put in Visual-CFD for user, while creating chemical reaction, in case reaction is not stoichiometrically balanced user will be warned for the same.

Raj Kumar Barnawal Virtual Integration Platform

Visual-Environment Highlight of Visual-Seat: STAN Thermal Dummy

STAN is a thermal dummy to test thermal comfort and moisture management characteristics of automobile, truck, and airplane seating. This device is commercialized by Thermetrics® and some relevant information can be found here: https://thermetrics.com/products/manikin/stan/. In collaboration with Thermetrics, ESI developed a numerical model of the STAN dummy for the prediction of its thermal behavior. No humidity is managed in this version of the model. A process for the setup of the seating and the thermal simulations of the STAN dummy have been added in this version.

Christian Marca Virtual Seat, Virtual Integration Platform

Visual-Environment Highlight of Visual-Seat: Sewing Simulation Guided Setup

Sewing simulations aim at assembling flat cover patterns and wrapping them around deformable foam block. This application exists in Visual-Seat for many versions as a set of toolboxes and functionalities enabling to set-up this type of input. This has been enhanced with a workflow gathering all tools and functionalities and proposing them in the right sequential order to provide some user guidance.

Christian Marca Virtual Seat, Virtual Integration Platform

Visual-Environment Highlight of Visual-Seat: Foam Blocks Positioning

When assembling the different components of the seat, it may happen that the foam at rest is intersecting the frame and/or the suspensions. In order to remove those intersections, a simulation-based technique had been implemented previously by applying surface pressure on foam. Upon customer request, a new method has been added where the frame (and suspensions) can be scaled down and moved initially to retrieve progressively their size and position during simulation, when the contact with foam is active.

Christian Marca Virtual Seat, Virtual Integration Platform