Coefficient Ratio Exceeds 1.0e8 - Check Results |verified| [ AUTHENTIC 2024 ]

The warning threshold of 1.0e8 is conservative and safety-oriented. In some cases, it can be safely ignored, but these are rare:

In mathematical terms: max(|A_ij|) / min(|A_ij|) > 1.0 × 10^8 coefficient ratio exceeds 1.0e8 - check results

The warning does not appear out of nowhere. It is almost always traceable to one of five fundamental modeling errors. The warning threshold of 1

When a solver builds an FEA model, it evaluates each individual element to construct a global matrix: Ku=Fbold cap K bold u equals bold cap F When a solver builds an FEA model, it

This warning typically appears in (often during structural or thermal analysis) and signals that your model's global stiffness matrix is ill-conditioned Ansys Innovation Space

What causes this catastrophic imbalance? The most common culprit is —specifically, extreme multicollinearity where two or more predictor variables are almost perfectly correlated. For example, consider a regression analyzing house prices that includes both “price in US Dollars” and “price in Japanese Yen” at the same time. The coefficient for Dollars might be 1, while the coefficient for Yen would be approximately 0.01. The ratio between them is only 100. But if you include “age of house in years” and “age of house in seconds,” the latter coefficient becomes astronomically tiny (1 year ≈ 31.5 million seconds). The ratio between the coefficient for seconds (tiny) and the coefficient for a normalized variable (e.g., number of bathrooms, around 1) will easily exceed 1.0e8. Other causes include scaling errors (mixing millimeters and kilometers) or redundant dummy variables (the classic “dummy variable trap” where you include one category for every possible outcome plus an intercept).