The phrase "accurate failure" is correct and usable in written English.
It can be used to describe a failure that is precisely identified or understood, often in a context where the reasons for the failure are clear and well-defined.
Example: "The project was deemed an accurate failure, as the team was able to pinpoint the exact reasons for its shortcomings."
Alternatives: "precise failure" or "clear failure".
The M5Tree significantly increased the efficiency of reliability analysis with accurate failure probability.
Due to the complex microstructure of advanced pipelines more accurate failure prediction is thus necessary.
The unified treatment of these derating factors is crucial to obtain accurate failure probability.
The first is a deterministic model that is intended for use by stakeholders with access to accurate failure rate data.
This paper proposes an accurate failure criterion of spot welds under combined axial and shear loading condition.
Approximation of the accurate failure probability is very time-consuming and inefficient based on Monte Carlo simulation (MCS) for complex performance functions.
By improving the efficiency of reliability method using accurate approximated failure probability, an efficient reliability method using the MCS and M5Tree is proposed to calibrate the performance function and estimate the failure probability, respectively.
We have embedded these techniques in a specific test flow to perform CADless accurate device failure analysis and characterization of margin evolutions in operating parameters for reliability study purposes.
We present the architecture and a detailed pre-fabrication analysis of a digital measurement ASIC facilitating long-term irradiation experiments of basic asynchronous circuits, which also demonstrates the suitability of the general approach for obtaining accurate radiation failure models developed in our FATAL project.
Finally, for a limited subset of experiments, F.E. analysis allowed the accurate prediction of failure.
The assessment affirms that the analytic models provide accurate predictions when failure initiation is controlled by yielding.
