A method and system for predicting an insulated gate bipolar transistor (IGBT) lifetime based on compound failure mode coupling are provided. First, a simultaneous failure probability model of a bonding wire and a solder layer is calculated. Next, expectancy of the simultaneous failure probability model is calculated and recorded as a lifetime under a coupling effect. A coupling function relation is established. A lifetime of the solder layer and a lifetime of the bonding wire are predicted. An IGBT lifetime prediction model not taking the coupling effect into account is established. An IGBT lifetime prediction model taking the coupling effect into account is established. In the disclosure, the lifetime of the IGBT module under the coupling effect of the solder layer and the bonding wire may be accurately predicted.

The present invention discloses an optimization method for a screen surface dynamic load of a vibrating screen. The method includes the following steps: step 1. selecting design variables, and establishing an experimental matrix; step 2. performing a response curved surface experiment; step 3. establishing two double-objective optimization models and solving the same to obtain two groups of Pareto solution sets, wherein the solution sets respectively represent screening efficiency optimization paths of the vibrating screen under the conditions of a high screen surface dynamic load and a low screen surface dynamic load; and step 4. calculating an optimization space for a screen surface dynamic load under a high screening efficiency. According to the method of the present invention, the screen surface dynamic load can be directly reduced, and the service life of the screen surface and the whole vibrating screen is prolonged.

Methods and systems for calculating a probability of failure and/or estimating a lifetime of an equipment component are disclosure. In an embodiment, a method of calculating a probability of failure of an equipment component comprises: generating a finite element model of the equipment component using device properties of the equipment component; using the finite element model of the equipment component to construct a polynomial basis for a polynomial chaos expansion; calculating expansion coefficients for the polynomial chaos expansion which express creep stress and strain in the equipment component as a function of operating parameters of the equipment component; receiving measured operating parameter values for the equipment component; and calculating a probability of failure of the equipment component using the measured operating parameter values.

A method for assessing fatigue damage and a fatigue life based on a crystal plastic welding process model. According to the new method, consideration is given to the effects of the crystal slip system and the polycrystal plastic strain on the welding process performance of the material. A welding process damage and fatigue life assessment model is established on the mesoscopic scale. The effect of microscopic characterizations of materials on the welding process performance, as well as on the fatigue damage and life of welded joints, can be studied from the mesoscopic point of view. The relationship between the welding process and the evolution of the material performance can be determined by the macro-mesoscopic coupling calculation model to further determine the effect and degree of welding processes on the fatigue damage and life of materials.

A computer-implemented method is provided for predicting a fatigue response of a material. The method includes receiving a user input specifying one or more surface roughness parameters that characterize a surface of a material for which fatigue life is to be predicted. The method further includes generating at least one realistic virtual surface profile from the specified one or more surface roughness parameters. The method further includes predicting fatigue life of the material in dependence of a stress field applied to the generated virtual surface profile. In accordance with specific embodiments, the prediction of the fatigue life may be carried out using finite element analysis based simulations, machine learning methods, or combinations thereof.

According to one implementation of the present disclosure, a method includes providing one or more tuning parameters of a transistor device at a first temperature of a range of temperatures below a temperature threshold; and adjusting the one or more tuning parameters until one or more second parameters of the transistor device corresponds to substantially the same value at the first temperature as a second temperature above the temperature threshold.

Systems, apparatuses and methods provides for technology that generates a plurality of discrete and finite elements associated with a component, where a number of the plurality of discrete and finite elements corresponds to a size of an estimated process zone. The technology further identifies material input properties of the component, models crack propagation throughout the plurality of discrete and finite elements based on the material input properties and models a release response in the plurality of discrete and finite elements based on the material input properties.

A method for predicting a remaining lifetime parameter of a component installed in a system is provided, in particular of an engine component and/or a filter, the method comprising: repeatedly sensing at least one parameter of the system to obtain a history of data values;

fitting an aging pattern to the data values; and

determining a remaining lifetime parameter of the component from the aging pattern, wherein at least some data values are erased with time such that the fitting is based on a subset of the data values determined since an initialization of the algorithm, wherein data values from an initial phase are not erased but retained as anchor values for the fitting throughout the lifetime determination of the component.

The present invention discloses an optimization method for a screen surface dynamic load of a vibrating screen. The method includes the following steps: step 1. selecting design variables, and establishing an experimental matrix; step 2. performing a response curved surface experiment; step 3. establishing two double-objective optimization models and solving the same to obtain two groups of Pareto solution sets, wherein the solution sets respectively represent screening efficiency optimization paths of the vibrating screen under the conditions of a high screen surface dynamic load and a low screen surface dynamic load; and step 4. calculating an optimization space for a screen surface dynamic load under a high screening efficiency. According to the method of the present invention, the screen surface dynamic load can be directly reduced, and the service life of the screen surface and the whole vibrating screen is prolonged.

Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using generative design processes. A method includes performing numerical simulation of a modeled object in accordance with a current version of the three dimensional shape and the one or more in-use load cases; finding a maximized stress or strain element, for each in-use load cases; determining an expected number of loading cycles for each of the one or more in-use load cases for the physical structure using the maximized stress or strain element and data relating fatigue strength to loading cycles; redefining a fatigue safety factor inequality constraint for the modeled object; computing shape change velocities for an implicit surface in a level-set representation of the three dimensional shape in accordance with at least the fatigue safety factor inequality constraint; and updating the level-set representation using the shape change velocities.