HyperCurve

A component can fail without ever carrying a heavy load. Heat it, cool it, heat it again, and if its expansion is restrained - by a bolted joint, by a neighbouring material, or simply by its own cooler interior - every cycle forces the material to strain a little, then unstrain, then strain again. No external force is pushing on it. The temperature swing alone is doing the work, and eventually a crack appears. Thermal fatigue analysis using FEA is how engineers predict where that crack will start and how many cycles it will take, before the part goes into service. Key takeaways Thermal fatigue is driven by restrained expansion and contraction, not external loading - the stress comes from the temperature change itself. The main drivers are constraint, temperature gradients through the part, and CTE mismatch between joined materials. It is usually a low-cycle fatigue problem involving cyclic plastic strain, so strain-life methods such as Coffin-Manson are the usual approach. ...

Run a linear FEA study on a component that bends, snaps or stretches significantly, and the software will still give you an answer - it just won't necessarily be the right one. Linear analysis assumes the structure's stiffness stays constant as it deforms, an assumption that quietly breaks down the moment deflection, rotation or strain moves beyond a small range. Large deformation analysis removes that assumption, recalculating geometry and stiffness as the structure actually changes shape under load - which is exactly what components like snap-fit clips, elastomer seals, thin sheet parts and cables need to be analysed honestly. Key takeaways Linear FEA assumes small deflections and constant stiffness - an assumption that breaks down for large rotations, large strains, or changing load paths. Geometric nonlinearity is one of three sources of nonlinear behaviour; material and contact nonlinearity often show up alongside it in the same component. Large deformation pro...

How to Perform a Mesh Convergence Study in ANSYS Mechanical A stress result that looks correct on screen is not the same as a stress result you can trust. Colour contours render whether the mesh is adequate or not — the software will not warn you that your peak von Mises stress is 40% too high because of a coarse mesh near a fillet. The only way to know your result has actually converged on the true solution is to run a structured mesh convergence study. This guide walks through the process in ANSYS Mechanical, from setting up refinement levels to applying Richardson extrapolation and the Grid Convergence Index (GCI). Key takeaways A single mesh, however fine it looks, proves nothing about accuracy on its own Convergence studies need at least three systematically refined meshes, not two Track a scalar result at a specific location (e.g. peak stress at a fillet), not an average Richardson extrapolation estimates the "true...

Most parts are heavier than they need to be - not because anyone designed them carelessly, but because a first-pass design is almost always conservative, built with generous safety margins and uniform section thickness that "feels" strong everywhere. The problem is that real stress isn't distributed evenly. Some regions of a part carry almost none of the load and could lose material with zero structural consequence; others are genuinely critical and can't be touched. FEA is what tells you, precisely, which is which - turning weight reduction from a risky guess into a targeted, defensible design decision. Key takeaways Most initial designs are over-built in some regions and just-adequate in others - stress is never uniform, so uniform thickness wastes material. FEA maps that distribution, showing exactly where material can be safely removed and where it must stay. Topology optimisation automates material placement based on loads and constraints; manual FEA-...

Most fan energy waste isn't caused by the fan. It's caused by everything the fan has to push air through to get where it's going - a tight elbow here, an oversized damper there, a transition fitting installed too close to the fan outlet - each one quietly adding resistance that the fan then has to overcome by working harder, drawing more power, every single hour it runs. CFD is what makes that hidden resistance visible, turning "the fan seems to be working hard" into a specific answer about exactly which part of the duct run is costing the most energy, and what to actually do about it. Key takeaways Fan energy consumption is driven by system resistance as much as by the fan itself - a poorly designed duct run makes any fan work harder. CFD reveals the true system curve for the actual installed geometry, which standard fitting-loss tables only approximate. Oversizing a fan to compensate for poor duct design usually makes the efficiency problem worse, no...