Validation Using Ansys Mechnical, Low-Code AI in Matlab, Crash Safety with LS-DYNA
💨 Turbulence breaks a tree’s branches, but only tickles an eagle’s wings.
💻 Validation and Insight Using Ansys Mechanical
Reviewing the calculated results is the most critical part of any simulation. Evaluating deformation and stresses is a primary objective of our analysis, and we may need to determine our engineered design’s safety factors. However, postprocessing also helps us verify that our model setup was correct and that we don't have unexpected behaviors we can't account for. Moreover, we can compare results from different designs to evaluate the optimal configuration.
💧Understand the Physics of Re-Entry Vehicles Using Numerical Modeling and Simulation
Recreating the atmospheric conditions of Mars is a challenging task. Traditional continuum mechanics assumptions are ineffective at high Mach numbers and low densities, making it difficult to replicate re-entry velocity and temperature in wind tunnels. In such situations, numerical methods and computer simulations help understand the underlying physics of re-entry vehicles.
In this detailed case study, learn about computation methodology, atmospheric chemistry modelling, and test cases for vehicle re-entry into the Mars atmosphere.
🤖 Low-Code AI in MATLAB R2023b
Updates for explainability in the Classification Learner and Regression Learner apps. You can now use LIME and Shapley to explain how trained models predict locally.
💻 Higher crash safety of composites through simulation with LS-DYNA
Crashworthiness is one of the most critical factors that every car manufacturer must take into account during the development phase of a vehicle. The safety of occupants and pedestrians depends largely on the vehicle's crashworthiness. An optimal vehicle body design for crash performance ensures that occupants and pedestrians are maximally protected in traffic accidents.
At the same time, regulations for vehicle crashworthiness are becoming increasingly stringent. To reliably and efficiently predict and demonstrate the crashworthiness of lightweight composite components, particular expertise is required to simulate highly dynamic processes and understand the composite materials used.
🧠 Surrogate Modeling Toolbox
The surrogate modeling toolbox (SMT) is a Python package that contains a collection of surrogate modeling methods, sampling techniques, and benchmarking functions. This package provides a library of surrogate models that is simple to use and facilitates the implementation of additional methods.
SMT is different from existing surrogate modeling libraries because of its emphasis on derivatives, including training derivatives used for gradient-enhanced modeling, prediction derivatives, and derivatives with respect to the training data.
💻 Engineering Tool of the Week – Sparselizard
Sparselizard is a high-performance, multiphysics, hp-adaptive, open source C++ finite element library running on Linux, Mac and Windows. A fast algorithm for mesh-to-mesh interpolation and a general implementation of the mortar finite element method allow to work with non-matching meshes and provide general periodic conditions easily. FEM simulations can be weakly or strongly coupled to lumped electric circuits.
Sparselizard can handle a general set of problems in 3D, 2D axisymmetric, 2D and 1D such as mechanical (anisotropic elasticity, geometric nonlinearity, buckling, contact, crystal orientation), fluid flow (laminar, creeping, incompressible, compressible), stabilized advection-diffusion, nonlinear acoustic, thermal, thermoacoustic, fluid-structure interaction, electric, magnetic, electromagnetic, piezoelectric, superconductor,... problems with a transient, (multi)harmonic or damped/undamped eigenmode analysis.
📚Book of the Week
Notes on Computational Fluid Dynamics: General Principles
Notes on Computational Fluid Dynamics (CFD) was written for people who use CFD in their work, research or study, providing essential knowledge to perform CFD analysis with confidence. It offers a modern perspective on CFD with the finite volume method, as implemented in OpenFOAM and other popular general-purpose CFD software.
Fluid dynamics, turbulence modelling and boundary conditions are presented alongside the numerical methods and algorithms in a series of short, digestible topics, or notes, that contain complete, concise and relevant information. The book benefits from the experience of the authors: Henry Weller, core developer of OpenFOAM since writing its first lines in 1989; and, Chris Greenshields, who has delivered over 650 days of CFD training with OpenFOAM.
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Keep engineering your mind! 🧠
Jousef