X-RHEA
The Real Power of Simulation
X-RHEA is co-developed by EnginSoft and Vection Technologies.
X-RHEA is co-developed by EnginSoft and Vection Technologies.
X-RHEA (EXtended Reality for Human Engineering Application) is the immersive solution for the visualization and presentation of CAE (Computer-Aided Engineering) data.
The goal of X-RHEA is to enhance the presentation of studies and simulations to expedite comparison sessions among multidisciplinary teams and simplify technical-commercial communication.
X-RHEA is a cutting-edge suite to visualize in extender reality any engineering simulation results. This innovation merges tradition with modern technology, providing a powerful tool. X-RHEA revolutionizes technical-commercial communication, turning complex 2D reports into immersive experiences on Industrial Metaverse and enabling Artificial Intelligence integration.
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CASE STUDY
This paper presents the RENAULT F1 Team’s AM process for an aerodynamic insert in titanium Ti6Al4V. Production was optimized by identifying the best orientation for the parts and the best positioning for the support structures in the melting chamber, in addition to using the ANSYS Additive Print module, a simulation software useful for predicting the distortion of a part and for developing a new, 3D, compensated model that guarantees the best “as-built” quality.
automotive additive-manufacturing optimization
training courses
The training course on geometric product specification and tolerance analysis addresses the issues related to tolerance management and the approach known as "Dimensional Management", which defines the activities involved and their sequence for achieving the desired quality at the lowest possible cost. We offer a wide range of training courses – scheduled, on-demand and customized – designed to meet the varying needs of individuals and/or the company in which they work: SO-GPS, ASME-GD&T standards, Tolerance analysis and model-based definition, and Software technologies training.
cetol tolerances
CASE STUDY
The ultimate goal of the study was to optimize the Drift Chamber’s performance in terms of stiffness, strength and weight o be mounted on the Mu2e particle detector at FermiLAB in Chicago
construction modefrontier ansys optimization energy
CASE STUDY
The article discusses advancements in low cycle fatigue analysis for an electric motor's rotor, focusing on a new method implemented in the FEMFAT software. Traditional methods have limitations in accurately predicting material plasticization due to a lack of consideration for the sequence of load peaks, which can affect component lifespan.
automotive femfat
CASE STUDY
A new methodology is presented, following an integrated process-product analysis approach, showing some benefits related to increased accuracy and the potential application of new optimization methods.
ls-dyna automotive composites