Uncertainty quantification on industrial high pressure die casting process

High pressure die casting (HPDC) is a famous manufacturing technology in industry. This manufacturing process is simulated by commercial code to shed the light on the quality of casting product. The casting product quality might be affected by the uncertainty in the simulation parameter settings. Thus, the uncertainty quantification on HPDC process is significant to improve the casting quality and the manufacturing efficiency. In this work, three uncertainty quantifications and sensitivity analyses on the A380 aluminum alloy HPDC process of intermediate speed plate are performed. The material thermophysical properties, boundary conditions of the model, and operational as well as artificial parameters with their uncertainties, are considered as the inputs of interest. Uncertainty quantification and sensitivity analyses are investigated for the outputs of interest including percent volume of porosity result, percent volume of fraction solid less than 1, and the percent volume that solidified during multiple solidification times. The most influential input parameter for predicting the outputs of interest is the boundary condition of metal-die interfacial air gap

KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution

Although current deep learning-based methods have gained promising performance in the blind single image super-resolution (SISR) task, most of them mainly focus on heuristically constructing diverse network architectures and put less emphasis on the explicit embedding of the physical generation mechanism between blur kernels and high-resolution (HR) images. To alleviate this issue, we propose a model-driven deep neural network, called KXNet, for blind SISR. Specifically, to solve the classical SISR model, we propose a simple-yet-effective iterative algorithm. Then by unfolding the involved iterative steps into the corresponding network module, we naturally construct the KXNet. The main specificity of the proposed KXNet is that the entire learning process is fully and explicitly integrated with the inherent physical mechanism underlying this SISR task. Thus, the learned blur kernel has clear physical patterns and the mutually iterative process between blur kernel and HR image can soundly guide the KXNet to be evolved in the right direction. Extensive experiments on synthetic and real data finely demonstrate the superior accuracy and generality of our method beyond the current representative state-of-the-art blind SISR methods. Code is available at: https://github.com/jiahong-fu/KXNet.Comment: Accepted by ECCV202

Crucial Role of miR-433 in Regulating Cardiac Fibrosis

Dysregulation of microRNAs has been implicated in many cardiovascular diseases including fibrosis. Here we report that miR-433 was consistently elevated in three models of heart disease with prominent cardiac fibrosis, and was enriched in fibroblasts compared to cardiomyocytes. Forced expression of miR-433 in neonatal rat cardiac fibroblasts increased proliferation and their differentiation into myofibroblasts as determined by EdU incorporation, α-SMA staining, and expression levels of fibrosis-associated genes. Conversely, inhibition of miR-433 exhibited opposite results. AZIN1 and JNK1 were identified as two target genes of miR-433. Decreased level of AZIN1 activated TGF-β1 while down-regulation of JNK1 resulted in activation of ERK and p38 kinase leading to Smad3 activation and ultimately cardiac fibrosis. Importantly, systemic neutralization of miR-433 or adeno-associated virus 9 (AAV9)-mediated cardiac transfer of a miR-433 sponge attenuated cardiac fibrosis and ventricular dysfunction following myocardial infarction. Thus, our work suggests that miR-433 is a potential target for amelioration of cardiac fibrosis

Association of inpatient use of angiotensin converting enzyme inhibitors and angiotensin II receptor blockers with mortality among patients with hypertension hospitalized with COVID-19

Rationale: Use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) is a major concern for clinicians treating coronavirus disease 2019 (COVID-19) in patients with hypertension. Objective: To determine the association between in-hospital use of ACEI/ARB and all-cause mortality in COVID-19 patients with hypertension. Methods and Results: This retrospective, multi-center study included 1128 adult patients with hypertension diagnosed with COVID-19, including 188 taking ACEI/ARB (ACEI/ARB group; median age 64 [IQR 55-68] years; 53.2% men) and 940 without using ACEI/ARB (non-ACEI/ARB group; median age 64 [IQR 57-69]; 53.5% men), who were admitted to nine hospitals in Hubei Province, China from December 31, 2019 to February 20, 2020. Unadjusted mortality rate was lower in the ACEI/ARB group versus the non-ACEI/ARB group (3.7% vs. 9.8%; P = 0.01). In mixed-effect Cox model treating site as a random effect, after adjusting for age, gender, comorbidities, and in-hospital medications, the detected risk for all-cause mortality was lower in the ACEI/ARB group versus the non-ACEI/ARB group (adjusted HR, 0.42; 95% CI, 0.19-0.92; P =0.03). In a propensity score-matched analysis followed by adjusting imbalanced variables in mixed-effect Cox model, the results consistently demonstrated lower risk of COVID-19 mortality in patients who received ACEI/ARB versus those who did not receive ACEI/ARB (adjusted HR, 0.37; 95% CI, 0.15-0.89; P = 0.03). Further subgroup propensity score-matched analysis indicated that, compared to use of other antihypertensive drugs, ACEI/ARB was also associated with decreased mortality (adjusted HR, 0.30; 95%CI, 0.12-0.70; P = 0.01) in COVID-19 patients with hypertension. Conclusions: Among hospitalized COVID-19 patients with hypertension, inpatient use of ACEI/ARB was associated with lower risk of all-cause mortality compared with ACEI/ARB non-users. While study interpretation needs to consider the potential for residual confounders, it is unlikely that in-hospital use of ACEI/ARB was associated with an increased mortality risk

Numerical Study and Structural Optimization of Vehicular Oil Cooler Based on 3D Impermeable Flow Model

A non-uniform permeable flow numerical model of vehicular oil cooler was proposed to simulate the thermal performance of oil cooler, due to the complex internal structure of cooler and the anisotropy of coolant flow and heat transfer. By comparing the numerical simulation results with the experimental results, the maximum error of the simulation results under different working conditions is 9.2%, which indicates that the modelling method is reliable and can improve the development efficiency. On this basis, through the three-dimensional numerical simulation to establish and optimize the oil cooler’s parameters. The thermal performance under different structural oil cooler were compared using the comprehensive evaluation factor j/f. The results and the experimental data show that under the impermeable flow model can obtain good heat transfer efficiency with low flow resistance at the same time. When the cross-sectional area is 3 mm2, length of 90 mm, layer number of 11, the model accuracy was 0.6%, as the optimal structure parameters, the heat transfer increase by 47% and with the total pressure drop increased by only 30%

Comparative Analysis of Flow and Heat Transfer for Vehicular Independent Cooling Modules

To explore the internal flow distributions and heat transfer mechanism in different types of independent cooling modules for automotive, numerical, and experimental studies were conducted. According to the study, the independent cooling modules with parallel structure, on which the heat exchangers were located separately and close to the inlets, the performance improvement was significant. In addition, the opposite model in parallel structure was considered to be more efficient for it can obtain the same heat rejection at a lower fan speed, effectively reducing the fan power. Besides, the parallel structure in independent cooling modules offered the possibility to control the mass flow on each heat exchanger precisely with active grille shutter. This technology deserves more attention in terms of energy saving and emission reduction