Materials-based failure analysis in design of electronic devices, and prediction of operating life
The technology includes methods, a system, and a computer readable medium for predicting the time to failure of an electronic component, by generating a finite element model of the component, developing a microstructure-based failure model for each representative volume element associated with each node in the finite element model, and calculating a time to failure of the component from the shortest predicted time to failure of any node when a value of a stress variable is applied to the microstructure-based failure model of each node. The technology further includes methods, system, and a medium programmed to predict failure of a system that includes an electronic component, based on predicting time to failure of the component.
1. A method of predicting time to failure of a metallic component of an electronic device, the method comprising:
generating a finite element model of the component, wherein the finite element model comprises a plurality of nodes, and wherein a value of at least one stress variable is associated with each node of the plurality of nodes;
defining at least one representative volume element for each node of the plurality of nodes;
developing a microstructure-based failure model for each of the representative volume elements, wherein the microstructure-based failure model uses random initial values for one or more properties of a material microstructure within each of the representative volume elements, and wherein the microstructure-based failure model represents heterogeneous microstructures in the component, and comprises one or more cyclic fatigue models selected from a first group consisting of crack nucleation, short crack growth, and long crack growth models, and further comprises one or more time-dependent fatigue models selected from a second group consisting of crack nucleation, short crack growth, and long crack growth models;
simulating failure of each node by applying the value of the at least one stress variable for that node to the microstructure-based failure model for each of the representative volume elements for that node, thereby calculating a predicted time to failure for each representative volume element; and
calculating a time to failure for the component by choosing the shortest predicted time to failure for any node.
2. The method of claim 1 , further comprising:
performing the simulating of failure for each node a plurality of times, using different initial values for the one or more properties of the material microstructure, thereby producing a plurality of predicted times to failure for the component; and
deriving a probabilistic model of failure of the component based on the plurality of predicted times to failure.
3. The method of claim 1 , wherein one or more of the crack nucleation and short crack growth models further comprises a phase coarsening model.
4. A computer system, configured to predict time to failure of a metallic component of an electronic device, the system comprising:
a memory; and
a processor, wherein the processor is configured to execute instructions stored in the memory for:
generating a finite element model of the component, wherein the finite element model comprises a plurality of nodes, and wherein a value of at least one stress variable is associated with each node of the plurality of nodes;
defining at least one representative volume element for each node of the plurality of nodes;
developing a microstructure-based failure model for each of the representative volume elements, wherein the microstructure-based failure model uses random initial values for one or more properties of a material microstructure within each of the representative volume elements, and wherein the microstructure-based failure model represents heterogeneous microstructures in the component, and comprises one or more cyclic fatigue models selected from a first group consisting of crack nucleation, short crack growth, and long crack growth models, and further comprises one or more time-dependent fatigue models selected from a second group consisting of crack nucleation, short crack growth, and long crack growth models;
simulating failure of each node by applying the value of the at least one stress variable for that node to the microstructure-based failure model for each of the representative volume elements for that node, thereby calculating a predicted time to failure for each representative volume element; and
calculating a time to failure for the component by choosing the shortest predicted time to failure for any node.
5. The system of claim 4 , wherein the processor is further configured to execute instructions comprising:
performing the simulating of failure for each node a plurality of times, using different initial values for the one or more properties of the material microstructure, thereby producing a plurality of predicted times to failure for the component; and
deriving a probabilistic model of failure of the component based on the plurality of predicted times to failure.
6. The system of claim 4 , wherein one or more of the crack nucleation and short crack growth models further comprises a phase coarsening model.
7. A computer readable non-transitory medium, storing instructions for predicting time to failure of an electronic component, the instructions, when executed by a processor, cause the processor to perform operations comprising:
generating a finite element model of the component, wherein the finite element model comprises a plurality of nodes, and wherein a value of at least one stress variable is associated with each node of the plurality of nodes;
defining at least one representative volume element for each node of the plurality of nodes;
developing a microstructure-based failure model for each of the representative volume elements, wherein the microstructure-based failure model uses random initial values for one or more properties of a material microstructure within each of the representative volume elements, and wherein the microstructure-based failure model represents heterogeneous microstructures in the component, and comprises one or more cyclic fatigue models selected from a first group consisting of crack nucleation, short crack growth, and long crack growth models, and further comprises one or more time-dependent fatigue models selected from a second group consisting of crack nucleation, short crack growth, and long crack growth models;
simulating failure of each node by applying the value of the at least one stress variable for that node to the microstructure-based failure model for each of the representative volume elements for that node, thereby calculating a predicted time to failure for each representative volume element; and
calculating a time to failure for the component by choosing the shortest predicted time to failure for any node.
8. The computer readable medium of claim 7 , wherein the medium is further encoded with instructions to:
perform the simulating of failure for each node a plurality of times, using different initial values for the one or more properties of the material microstructure, thereby producing a plurality of predicted times to failure for the component; and
derive a probabilistic model of failure of the component based on the plurality of predicted times to failure.
9. The medium of claim 7 , wherein one or more of the crack nucleation and short crack growth models further comprises a phase coarsening model.