FEA goes beyond classical formulae (e.g., Poisson effects), but always remember, FEA is an approximation.
Actual Performance vs. FEA: Assumption = Possible source of error
Stiffness: effected by actual E, cold working, porosity, processing
Geometric: tolerance vs. nominal, curvature is approximated, ignoring small features (holes, fillets, chamfers, etc.)
Simple Two Spring Model (1D)
F = K*x means
Applied Force = Internal Force in the Spring
leads to a [K] matrix with both spring constants:
Degrees of Freedom (DOF): motions that are possible at a node.
In 3D, maximum = 6 (3 translations + 3 rotations)
Also, shows ability to transmit loads.
In 3D, maximum = 6 (3 forces + 3 moments)
Boundary Conditions: constraints and loads on a model
Nodes: points in space, corners, ends, or mid-edge points of elements
Elements: stiffness relationship between nodes
Shape functions: represent assumed shape (i.e., behavior) of elems.
Smaller element size makes the shape functions a better approx.
Convergence: reducing local error in a model, by either:
(Either method will improve the solutions accuracy)
FOUR PRIMARY ASSUMPTIONS:
- Geometry: "the mesh represents the geometry adequately"
- Properties: "all parts produced have the same properties"
- Mesh: "Accuracy depends on the mesh quality"
"A good-looking mesh has well-shaped elements"- Boundary Conditions: "do the B.C.s really represent the parts and effects which are not explicitly modeled ?"
DISAGREE: The analyst's job is to make a proper mesh that will be accurate and represent the geometry adequately. How do YOU do this ?
Christopher Wright P.E. (XANSYS, 10/26/06):
"You can also find yourself in a position where 80% of an answer in time to make changes is worth a great deal more than 100% of an answer furnished after the point where the design can't be modified".Einstein quote: "simplify as much as possible - but not more!"
Hamming's Motto: "the purpose of computing is insight, not numbers."
Behind every decision you make are assumptions that may effect the accuracy and correctness of the model.