Since you can extract any data anywhere in the mesh from any solution, you can specify margin of safety checks anywhere and StressCheck® will automatically identify the points where those margins have been exceeded.
Margin Check Solver
When and where does failure occur? It's clear now.
The Margin Check Solver combines a nonlinear load step analysis with the parametric formula to compute margins of safety (MS) at specified locations (regions) in the model. Failure criteria (MS equations) are constructed as formula and associated with a region (area or volume) in the model. The formula is evaluated at each load increment to determine if the failure criteria has been exceeded. Returns a table showing the margins of safety at each load level.
Key Features and Advantages
- Define formulae that represent margin criteria to be checked during the Margin Check solution
- Define named extraction settings that calculate these formulae at any location
- Select the named extraction settings that will be checked as the load increases
The Margin Check Solver is simple to use:
- First, run a linear analysis for a load value that produces little or no plasticity. By running a p-extension, say p=1 to 8, the use can assess the quality of the linear solution.
- Second, setup a Margin Check analysis based on user defined values for load step and limit load. You can choose to stop the analysis upon reaching the first negative margin of safety or you can opt to let the analysis continue up to the limit load.
- Third, select a linear solution as a starting solution and provide a tolerance for convergence. In this case we would want to select p=6 as our starting solution since convergence is verified
- SOLVE! – a summary table is generated that list the names of each of the acceptance criteria along with the calculated margin of safety for the failure load or limit load depending on which option was selected
Recent News & Events
Engineering organizations need to institute simulation governance. This means that management has to understand that finite element modeling is not numerical simulation and begin to exercise command and control over all aspects of numerical simulation. This includes adoption of the best available simulation practices, solution verification, data verification, model validation and revision of mathematical models in the light of new information collected from physical experiments. The primary goal of simulation governance is to ensure and enhance the reliability of predictions based on numerical simulation
Dr. Barna SzabóChairman and Co-Founder, ESRD