Search

With the rapid development of electric vehicles, the safety accidents caused by the damage and failure of lithium-ion batteries under mechanical load are increasing gradually, which increases the significance of collision safety in lithium-ion batteries. The failure threshold of the cell in a free state is different from that of the cells in the module. Therefore, the safety characteristics of cells and modules under vertical dynamic impact conditions were studied in this paper. Lithium iron phosphate (LiFePO4) batteries and assembled 2-in-10 series modules with a 100% state of charge (SOC) were tested. Analyses included the voltage, temperature, and mechanical behavior of test samples under different impact loads, extrusion positions, and indenter shapes. The results showed that the damage behavior of a battery was closely related to the contact shape, contact area, and contact position. A smaller contact area led to greater deformation; moreover, the contact area being closer to the edge position meant greater deformation and weaker load-carrying capacity. The load-carrying capacity of the cell in a free state was weaker than that of the module, but the failure threshold of the cell in a free state was higher than that of the module. It can be concluded that the failure threshold of the cell cannot reflect the failure threshold of the module. [ABSTRACT FROM AUTHOR]

In view of the service characteristics of driving devices such as construction machinery， aerospace， rail transit and electric vehicle in the variable speed and variable torsion， the damage mechanism of thermal-scuffing failure for gear transmission is expounded， the multi factor coupling correlation relationship of thermal-scuffing is constructed， and the influences of transmission torque， gear speed， oil viscosity and oil temperature on the contact temperature for meshing tooth surfaces are analyzed， the corresponding design ideas to improve the thermal-scuffing load capacity is formed. At the same time， aiming at the combination of 18CrNiMo7-6 carburizing and quenching +ISO-VG 220 lubricating oil transmission gear， series of tests are carried out. The action weights of contact temperature and oil film thickness in thermal-scuffing analysis are determined. The value of failure boundary temperature for thermal-scuffing is also measured， the basis data for accurate evaluation on the gear thermal-scuffing bearing capacity in variable speed and variable torque in engineering application can be provided.

With the rapid development of electric vehicles, the safety accidents caused by the damage and failure of lithium-ion batteries under mechanical load are increasing gradually, which increases the significance of collision safety in lithium-ion batteries. The failure threshold of the cell in a free state is different from that of the cells in the module. Therefore, the safety characteristics of cells and modules under vertical dynamic impact conditions were studied in this paper. Lithium iron phosphate (LiFePO4) batteries and assembled 2-in-10 series modules with a 100% state of charge (SOC) were tested. Analyses included the voltage, temperature, and mechanical behavior of test samples under different impact loads, extrusion positions, and indenter shapes. The results showed that the damage behavior of a battery was closely related to the contact shape, contact area, and contact position. A smaller contact area led to greater deformation; moreover, the contact area being closer to the edge position meant greater deformation and weaker load-carrying capacity. The load-carrying capacity of the cell in a free state was weaker than that of the module, but the failure threshold of the cell in a free state was higher than that of the module. It can be concluded that the failure threshold of the cell cannot reflect the failure threshold of the module.

Various adaptive reliability analysis methods based on surrogate models have recently been developed. A multi-mode failure boundary exploration and exploitation framework (MFBEEF) was proposed for system reliability assessment using the adaptive kriging model based on sample space partitioning to reduce computational cost and use the characteristics of the failure boundary in multiple failure mode systems. The efficiency of the adaptive construction of kriging model can be improved by using the characteristics of the center sample of the small space to represent the characteristics of all samples in the small space. This method proposes a failure boundary exploration and exploitation strategy and a convergence criterion based on the maximum failure probability error for a system with multiple failure modes to adaptively approximate the failure boundary of a system with multiple failure modes. A multiple-failure-mode learning function was used to identify the optimal training sample to gradually update the kriging model during the failure boundary exploration and exploitation stages. In addition, a complex failure boundary-oriented adaptive hybrid importance sampling method was developed to improve the applicability of the MFBEEF method to small failure probability assessments. Finally, the MFBEEF method was proven to be effective using five system reliability analysis examples: a series system, a parallel system, a series–parallel hybrid system, a multi-dimensional series system with multiple failure modes, and an engineering problem with multiple implicit performance functions. • A multi-mode failure boundary exploration and exploitation framework is proposed. • The construction process of adaptive Kriging model is divided into two phases. • Different candidate samples are used to enrich DoE in different phases. • A convergence criterion based on maximum failure probability error is developed. • A complex failure boundary-oriented adaptive hybrid importance sampling method is proposed. [ABSTRACT FROM AUTHOR]

This paper analyzes the functional principle and functional hazard analysis for a landing gear cabin door lock mechanism, concluding that the unlocking function of the lock mechanism is the one at most risk. Then the failure probability of the unlocking process of the lock mechanism is calculated, based on the simulation model of the lock mechanism and the response surface method. At last, the failure boundary of the lock mechanism is studied, including: (a) A method for the failure boundary analysis of the lock mechanism is proposed; (b) The failure boundaries respectively with single-parameter and with double-parameter are obtained based on the simulation model; (c) With the lock mechanism's assembly error taken into consideration, the failure boundary of the lock-ring position is verified through the cabin door lock system test, which is quite helpful for the maintenance and management of the aircraft lock mechanism. [ABSTRACT FROM AUTHOR]

The safety of a Nuclear Power Plant (NPP) is verified by analyzing the system responses under normal and accidental conditions. This is done by resorting to a Best-Estimate (BE) Thermal-Hydraulic (TH) code, whose outcomes are compared to given safety thresholds enforced by regulation. This allows identifying the limit-state function that separates the failure domain from the safe domain. In practice, the TH model response is affected by uncertainties (both epistemic and aleatory), which make the limit-state function and the failure domain probabilistic. The present paper sets forth an innovative approach to identify the failure domain together with the safest plant operating conditions. The approach relies on the use of Reduced Order Models (ROMs) and K-D Tree. The model failure boundary is approximated by Support Vector Machines (SVMs) and, then, projected onto the space of the controllable variables (i.e., the model inputs that can be manipulated by the plant operator, such as reactor control-rods position, feed-water flow-rate through the plant primary loops, accumulator water temperature and pressure, repair times, etc.). The farthest point from the failure boundary is, then, computed by means of a K-D Tree-based nearest neighbor algorithm; this point represents the combination of input values corresponding to the safest operating conditions. The approach is shown to give satisfactory results with reference to one analytical example and one real case study regarding the Peak Cladding Temperature (PCT) reached in a Boiling Water Reactor (BWR) during a Station-Black-Out (SBO), simulated using RELAP5-3D. [ABSTRACT FROM AUTHOR]

• A failure boundary exploration and exploitation framework is proposed. • A partitioning strategy is proposed with slice sampling and K-means clustering. • The construction process of adaptive Kriging model is divided into two phases. • Different candidate samples are used to enrich DoE in different phases. • A new stopping criterion based on maximum failure probability error is developed. Surrogate model-based methods have gradually become a vital method to assess reliability. However, the existing methods usually ignore the memory problems of matching candidate samples with the level of failure probability, which leads to inefficiency and even restricts their applicability. Therefore, this work combining the adaptive Kriging model and sample space partitioning strategy proposes a failure boundary exploration and exploitation framework (FBEEF), which divides the construction process of the adaptive Kriging model into two phases using different candidate samples to enrich training samples. In the exploration phase, a sample space partitioning strategy combining K-means clustering and slice sampling is employed to obtain several subsets and static candidate samples. In the exploitation phase, the approximate distances between the static candidate samples and the failure boundary are calculated to identify important subsets, whose samples are named dynamic candidate samples. Furthermore, a new stopping criterion is developed by combining leave-one-out method and weighted simulation method. To improve the efficiency of FBEEF Monte Carlo simulation or Importance Sampling is selected to estimate the final failure probability. Five examples were analyzed to test the effectiveness of FBEEF, and the results show that FBEEF can obtain good results with fewer training samples and lower analysis time. [ABSTRACT FROM AUTHOR]