Physics-Based Gaussian Process Method for Predicting Average Product Lifetime in Design Stage

The average lifetime or the mean time to failure (MTTF) of a product is an important metric to measure the product reliability. Current methods of evaluating the MTTF are mainly based on statistics or data. They need lifetime testing on a number of products to get the lifetime samples, which are then used to estimate the MTTF. The lifetime testing, however, is expensive in terms of both time and cost. The efficiency is also low because it cannot be effectively incorporated in the early design stage where many physics-based models are available. We propose to predict the MTTF in the design stage by means of a physics-based Gaussian process (GP) method. Since the physics-based models are usually computationally demanding, we face a problem with both big data (on the model input side) and small data (on the model output side). The proposed adaptive supervised training method with the Gaussian process regression can quickly predict the MTTF with a reduced number of physical model calls. The proposed method can enable continually improved design by changing design variables until reliability measures, including the MTTF, are satisfied. The effectiveness of the method is demonstrated by three examples

Approximation to Multivariate Normal Integral and Its Application in Time-Dependent Reliability Analysis

It is common to evaluate high-dimensional normal probabilities in many uncertainty-related applications such as system and time-dependent reliability analysis. An accurate method is proposed to evaluate high-dimensional normal probabilities, especially when they reside in tail areas. The normal probability is at first converted into the cumulative distribution function of the extreme value of the involved normal variables. Then the series expansion method is employed to approximate the extreme value with respect to a smaller number of mutually independent standard normal variables. The moment generating function of the extreme value is obtained using the Gauss-Hermite quadrature method. The saddlepoint approximation method is finally used to estimate the cumulative distribution function of the extreme value, thereby the desired normal probability. The proposed method is then applied to time-dependent reliability analysis where a large number of dependent normal variables are involved with the use of the First Order Reliability Method. Examples show that the proposed method is generally more accurate and robust than the widely used randomized quasi Monte Carlo method and equivalent component method

Adaptive Kriging Method for Uncertainty Quantification of the Photoelectron Sheath and Dust Levitation on the Lunar Surface

This paper presents an adaptive Kriging based method to perform uncertainty quantification (UQ) of the photoelectron sheath and dust levitation on the lunar surface. The objective of this study is to identify the upper and lower bounds of the electric potential and that of dust levitation height, given the intervals of model parameters in the one-dimensional (1D) photoelectron sheath model. To improve the calculation efficiency, we employ the widely used adaptive Kriging method (AKM). A task-oriented learning function and a stopping criterion are developed to train the Kriging model and customize the AKM. Experiment analysis shows that the proposed AKM is both accurate and efficient

Elucidating the mesoscale deformation in a multi-principle element alloy with hexagonal closed-packed crystal structure

To date, the exploration of multi-principal element alloys (MPEAs) has rarely ventured into the realm of hexagonal close-packed (HCP) structures. In this research, we embarked on a pioneering systematic comparison between a single-phase Ti-Zr-Hf HCP-MPEA and Ti regarding their dislocation activities and mesoscale deformation homogeneity. Through large-area high-resolution quasi-in-situ slip trace analysis and crystal plasticity finite element modeling, we identified HCP-MPEA’s significantly enhanced pyramidal slip activities—resulted from minimized disparities among different deformation modes—notably improve the material’s intragranular deformation homogeneity. Alongside MPEA’s intrinsically high slip resistance, it renders HCP-MPEA an outstanding strength-toughness combination relative to its conventional HCP counterparts

DDX3X loss is an adverse prognostic marker in diffuse large B-cell lymphoma and is associated with chemoresistance in aggressive non-Hodgkin lymphoma subtypes.

Funder: addenbrooke's charitable trust, cambridge university hospital

Direct Stimulation of Adult Neural Stem/Progenitor Cells In Vitro and Neurogenesis In Vivo by Salvianolic Acid B

Background: Small molecules have been shown to modulate the neurogenesis processes. In search for new therapeutic drugs, the herbs used in traditional medicines for neurogenesis are promising candidates. Methodology and Principal Findings: We selected a total of 45 natural compounds from Traditional Chinese herbal medicines which are extensively used in China to treat stroke clinically, and tested their proliferation-inducing activities on neural stem/progenitor cells (NSPCs). The screening results showed that salvianolic acid B (Sal B) displayed marked effects on the induction of proliferation of NSPCs. We further demonstrated that Sal B promoted NSPCs proliferation in dose- and time-dependent manners. To explore the molecular mechanism, PI3K/Akt, MEK/ERK and Notch signaling pathways were investigated. Cell proliferation assay demonstrated that Ly294002 (PI3K/Akt inhibitor), but neither U0126 (ERK inhibitor) nor DAPT (Notch inhibitor) inhibited the Sal B-induced proliferation of cells. Western Blotting results showed that stimulation of NSPCs with Sal B enhanced the phosphorylation of Akt, and Ly294002 abolished this effect, confirming the role of Akt in Sal B mediated proliferation of NSPCs. Rats exposed to transient cerebral ischemia were treated for 4 weeks with Sal B from the 7th day after stroke. BrdU incorporation assay results showed that exposure Sal B could maintain the proliferation of NSPCs after cerebral ischemia. Morris water maze test showed that delayed post-ischemic treatment with Sal B improved cognitive impairment after stroke in rats