scholarly journals Evaluating dynamic failure probability for streams with (m, k)-firm deadlines

1997 ◽  
Vol 46 (12) ◽  
pp. 1325-1337 ◽  
Author(s):  
M. Hamsaoui ◽  
P. Ramanathan
Keyword(s):  
Failure Probability ◽  
Dynamic Failure ◽  
Firm Deadlines

Reliability Analysis for Structures With Multiple Temporal and Spatial Parameters Based on the Effective First-Crossing Point

2017 ◽  
Vol 139 (12) ◽  
Author(s):  
Yan Shi ◽  
Zhenzhou Lu ◽  
Kaichao Zhang ◽  
Yuhao Wei
Keyword(s):  
Failure Probability ◽  
Limit State ◽  
Function Technique ◽  
State Function ◽  
Fourth Moment ◽  
Dynamic Failure ◽  
Dynamic Reliability ◽  
Spatial Parameters ◽  
Temporal And Spatial ◽  
Crossing Point

For efficiently estimating the dynamic failure probability of the structure with the multiple temporal and spatial parameters, a transferred limit state function technique is first proposed in this paper. By finding the effective first-crossing point which controls the failure of the structural system, the transferred technique is constructed to transform the dynamic reliability problem into a static one. For determining the effective first-crossing point, the parameter domain is first divided into different dominant domain corresponding to every parameter. Based on the parameter dominant domain, the first-crossing point about each parameter is obtained by comparing the difference value between the point on the failure boundary and the corresponding parameter upper bound. Finally, the effective first-crossing point is determined by finding the point which controls the structure failure. With the transferred technique, two strategies (including the sparse grid integration based on fourth-moment method and the maximum entropy based on dimensional reduction method) are proposed to efficiently estimate the dynamic failure probability. Several examples are employed to illustrate the significance and effectiveness of the transferred technique and the proposed methods for solving the multiple temporal and spatial parameters dynamic reliability. The results show that the proposed methods can estimate the multiple temporal and spatial parameters dynamic failure probability efficiently and accurately.

Dynamic reliability analysis for structure with temporal and spatial multi-parameter

2019 ◽  
Vol 233 (6) ◽  
pp. 1002-1013
Author(s):  
Yan Shi ◽  
Zhenzhou Lu
Keyword(s):  
Random Field ◽  
Failure Probability ◽  
Gaussian Random Field ◽  
Simulation Method ◽  
Dynamic Failure ◽  
Performance Function ◽  
Dynamic Reliability ◽  
Field Transformation ◽  
Real Performance ◽  
Temporal And Spatial

For efficiently estimating the dynamic failure probability of the structure with random variables, stochastic processes and temporal and spatial multi-parameter, an estimation strategy is presented based on the random field transformation. The random field transformation focusing on the dynamic reliability with only one time parameter is further investigated, and it is extended to temporal and spatial multi-parameter issue, which simulates the output as multi-dimensional Gaussian random field. Also, the active learning Kriging method is used to construct the surrogate models for the mean function and auto-covariance function of performance function. After that, the temporal and spatial dynamic failure probability can be obtained by the simulation method. Although it doesn’t need to call the real performance function during the process of simulation method, it is time computationally expensive. To address this issue, the optimization algorithm procedure is established to estimate the dynamic failure probability. Several examples including an aero engine turbine disk and a cylindrical pressure vessel are introduced to illustrate the significance and effectiveness of the proposed methods for analyzing the temporal and spatial multi-parameter dynamic failure probability.

Test Circuit Conditioning for Soft Defect Localization

2014 ◽  
Author(s):  
Kristopher D. Staller ◽  
Corey Goodrich
Keyword(s):  
Laser Beam ◽  
Failure Analysis ◽  
Signal Frequency ◽  
Dynamic Failure ◽  
The Third ◽  
Analysis Technique ◽  
Test Circuit ◽  
Defect Localization ◽  
Manual Input ◽  
Fast Dynamic

Abstract Soft Defect Localization (SDL) is a dynamic laser-based failure analysis technique that can detect circuit upsets (or cause a malfunctioning circuit to recover) by generation of localized heat or photons from a rastered laser beam. SDL is the third and seldom used method on the LSM tool. Most failure analysis LSM sessions use the endo-thermic mode (TIVA, XIVA, OBIRCH), followed by the photo-injection mode (LIVA) to isolate most of their failures. SDL is seldom used or attempted, unless there is a unique and obvious failure mode that can benefit from the application. Many failure analysts, with a creative approach to the analysis, can employ SDL. They will benefit by rapidly finding the location of the failure mechanism and forgoing weeks of nodal probing and isolation. This paper will cover circuit signal conditioning to allow for fast dynamic failure isolation using an LSM for laser stimulation. Discussions of several cases will demonstrate how the laser can be employed for triggering across a pass/fail boundary as defined by voltage levels, supply currents, signal frequency, or digital flags. A technique for manual input of the LSM trigger is also discussed.

Dynamic Failure of Materials. Volume 1 - Experiments and Analyses

1998 ◽  
Author(s):  
Tarabay H. Antoun ◽  
Lynn Seaman ◽  
Donald R. Curran
Keyword(s):  
Dynamic Failure
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