Our expertise on computation design and analysis revolves around highly customizable product development, predictive models, and performative design, as well as digitization of physical models for further development. Bio-inspired algorithmic procedures, physics simulation engines, generative design, and optimization through evolutionary solvers are some of our extended R&D interests and capabilities.
Computational/Algorithmic design
Our design expertise on visual programming and scripting techniques involves parametric, generative and performance-driven design, discretization, penalization, and voxelization strategies, lattice design and agent-based modelling.
Computational Analysis
BioG3D has extensive experience in CFD and FEA for structural optimization and product development. Physical performance (e.g. dynamic, non-linear, multiphase flow and fluid-structure interaction), as well as human centric (e.g. biomechanical, psychometric, environmental, and acoustic) analysis provide insight of complex physical phenomena and human comfort through simulation results.
Engineering design
By employing a wide range of design and engineering modelling tools, a diverse collection of additive manufacturing technologies and our engineering and materials science know-how BioG3D develops on-demand solutions and functional prototypes for industrial and consumer applications. Taking into consideration a product’s functional requirements, identifying structural and thermal operating loads as well as kinematic restrictions and combining them with the most suitable materials and Design for Additive manufacturing (DfAM) principles we implement flexibility and personalization in prototype development.
Reverse Engineering
Reverse engineering refers to the analysis of the functionality and digital recreation of the geometry of a working component with the aim to create duplicates. In BioG3D we utilize structured light 3D scanning to captivate the three-dimensional form of an object with high precision and accuracy. Processing and conversion of the data, along with our engineering insight and in combination with optimization techniques provide a printable object with potentially enhanced properties.