Due to geometric discontinuities introduced by welding and joining processes, stresses or strain cannot be calculated reliably calculated using modern analytical and computer methods as result of stress or strain singularity at joint locations, which leads to severe mesh sensitivity. Design and fatigue evaluation of these structures remain empirical. This disclosure addresses mesh insensitivity of stress/strain calculations for welded structures through a cut-plane traction stress method through a novel post processing of conventional finite element computation results, as well as provides a unified fatigue evaluation procedure for fatigue design and structural life evaluation for both low-cycle and high cycle fatigue regime subjected to either proportional or non-proportional multiaxial fatigue loading, as well as a simple and reliable method for treating spot welds.

Due to geometric discontinuities introduced by welding and joining processes, stresses or strain cannot be calculated reliably calculated using modern analytical and computer methods as result of stress or strain singularity at joint locations, which leads to severe mesh sensitivity. Design and fatigue evaluation of these structures remain empirical. This disclosure addresses mesh insensitivity of stress/strain calculations for welded structures through a cut-plane traction stress method through a novel post processing of conventional finite element computation results, as well as provides a unified fatigue evaluation procedure for fatigue design and structural life evaluation for both low-cycle and high cycle fatigue regime subjected to either proportional or non-proportional multiaxial fatigue loading, as well as a simple and reliable method for treating spot welds.

This invention discloses a method for predicting the service life of a retired power battery. The service life of a retired power battery may be predicted by its power battery life attenuation curve. The power battery life attenuation curve is obtained by establishing a power battery life model and a charge and discharge characteristic curve of the power battery by utilizing the temperature T, the discharge rate C and the discharge depth DOD in the charging and discharging process of the power battery. This invention establishes a three-dimensional relation graph with a cycle life with respect to the capacity loss rate and the functional relationship ω=ƒ(T,C) by using the power battery life attenuation curve. The three-dimensional relation graph is applied to the same type of battery. And the attenuation of the battery in the full life cycle may be predicted.

A method and a system for predicting remaining useful life of an analog circuit are provided. A simulation model of the analog circuit is built, and an output voltage is selected as a degradation variable. Different degradation cycles are set to extract degradation features of the output voltage. Key features that can reflect a degradation trend of a circuit component are selected. Multi-feature fusion and similarity model are adopted to construct a health indicator curve to characterize a degradation process of a full life cycle of different circuit components. A prediction model is established based on a temporal convolutional network and an attention mechanism, and preferably selected features and a constructed health indicator database are used as an input of a TCN-attention network to predict the remaining useful life of the circuit component.

A method and a system for comprehensively evaluating reliability of a multi-chip parallel IGBT module are provided. The method includes: establishing a gate-emitter voltage reliability model of the multi-chip parallel IGBT module, performing a chip fatigue failure test, and selecting a gate-emitter voltage as a failure characteristic quantity; establishing a transconductance reliability model of the multi-chip parallel IGBT module, performing a bonding wire shedding failure test, and selecting a transmission characteristic curve of the module as a failure characteristic quantity; using a Pearson correlation coefficient to characterize a degree of health of the IGBT module, and respectively calculating degrees of health PPMCC.sub.C and PPMCC.sub.B in different degrees of chip fatigue and bonding wire shedding failure states; and comprehensively evaluating the reliability of the multi-chip parallel IGBT module according to PPMCC.sub.C and PPMCC.sub.B.

The present disclosure provides a method and an apparatus for testing a semiconductor device. The method includes providing an active area in an integrated circuit design layout; grouping the active area into a first region and a second region; calculating a first self-heating temperature of the first region of the active area; calculating a second self-heating temperature of the second region of the active area; and determining an Electromigration (EM) evaluation based on the first self-heating temperature and the second self-heating temperature.

Disclosed herein is a method for making embryonic bio-inspired hardware efficient against faults through self-healing, fault prediction, and fault-prediction assisted self-healing. The disclosed self-healing recovers a faulty embryonic cell through innovative usage of healthy cells. Through experimentations, it is observed that self-healing is effective, but it takes a considerable amount of time for the hardware to recover from a fault that occurs suddenly without forewarning. To get over this problem of delay, novel deep learning-based formulations are utilized for fault predictions. The self-healing technique is then deployed along with the disclosed fault prediction methods to gauge the accuracy and delay of embryonic hardware.

Technologies and techniques for operating a dynamically updatable computer system. A design tool generates a three-dimensional (3D) model base having plurality of model subcomponents with different characteristics. First dynamic metadata and second dynamic metadata associated with each of the plurality of model subcomponents are received, wherein the second dynamic metadata is associated with the first dynamic metadata, and wherein the first dynamic metadata and second dynamic metadata is configured to change over time. Each of the first dynamic metadata are linked to respective portions of the plurality of model subcomponents, based on the model component characteristics. Each of the second dynamic metadata are linked to the respective portions of the plurality of model subcomponents linked to the first dynamic metadata. A 3D model is generated that includes the processed first and second dynamic metadata, wherein the first dynamic metadata and second dynamic metadata is automatically updated within the 3D model.

The invention concerns a method for determining a mechanical stress of a runner (40), of a hydraulic machine (10), wherein the runner is arranged to rotate around a rotation axis, wherein the hydraulic machine comprises a hydraulic channel delimited by hydraulic surfaces of the runner, the hydraulic surfaces being the surfaces against which a stream of water exerts the forces when the runner is driven in rotation by said stream of water, wherein the runner further comprises a sensor (G) on protected areas positioned away from the hydraulic channel, the method comprises the steps of: a) collecting a physical quantity measured by the sensor (G), b) determining a mechanical stress on a specific location of the hydraulic surface, via a transfer function that correlates the physical quantity measured in step a) and said mechanical stress on the specific location.

A method for device monitoring includes: providing a plurality of fleet measurement data for at least one device, where the plurality of fleet measurement data includes a number of fleet device data measurements “Nfleet;” providing a plurality of device measurement data for a monitored device, where the plurality of device measurement data includes a number of monitor device data measurements “Ndata;” determining a fleet distribution “Fdist” determined as a distribution of differences between consecutive measurements of the plurality of fleet measurement data; determining a device distribution “Ddist” determined as a distribution of differences between consecutive measurements of the device measurement data; determining an effective number of data measurements “Neff” and determining a probability of failure of the monitored device, the determining including utilising the fleet distribution “Fdist,” the device distribution “Ddist,” the number of monitor device data measurements “Ndata,” and the effective number of data measurements “Neff.”