Evaluation of wearing comfort of dust masks.

Dust masks are widely used to prevent the inhalation of particulate matter into the human respiratory organs in polluted air environments. The filter of a dust mask inherently obstructs the natural respiratory air flows, and this flow resistance is mainly responsible for the discomfort experienced when wearing a dust mask. In atmospheric conditions seriously contaminated with fine dust, it is recommended that common citizens wear a dust mask in their everyday lives, yet many people are reluctant to wear a dust mask owing to the discomfort experienced when wearing it for a long time. Understanding of physical reasons for the discomfort is thus crucial in designing a dust mask, but remains far from clear. This study presents a technique to quantify the wearing comfort of dust masks. By developing a respiration simulator to measure the pressure loss across a dust mask, we assessed the energy costs to overcome flow resistance when breathing through various types of dust masks. The energy cost for a single inhalation varies with the mask type in a range between 0 and 10 mJ. We compared the results with the survey results of 40 people about the wearing comfort of the dust masks, which revealed that the wearing comfort crucially depends on the energy cost required for air inhalation though the dust mask. Using the measured energy cost during inhalation as a parameter to quantify the wearing comfort, we present a comprehensive evaluation of the performance of dust masks in terms of not only the filtering performance but also the wearing comfort. Our study suggests some design principles for dust mask filters, auxiliary electric fans, and check valves

Fatigue Life Prediction Methodology of Hot Work Tool Steel Dies for High-Pressure Die Casting Based on Thermal Stress Analysis

High-pressure die casting (HPDC) can produce precise geometries in a highly productive manner. In this paper, the failure location and cycles were identified by analyzing the fatigue behavior of the die subjected to repeated thermal stress. An energy-based semi-empirical fatigue life prediction model was developed to handle the complex stress history. The proposed model utilizing mean stress, amplitudes of stress, and strain was calculated by one-way coupling numerical analysis of computational fluid dynamics (CFD) and finite element analysis (FEA). CFD temperature results of the die differed from the measured results by 2.19%. The maximum stress distribution obtained from FEA was consistent with the actual fracture location, demonstrating the reliability of the analytical model with a 2.27% average deviation between the experimental and simulation results. Furthermore, the model showed an excellent correlation coefficient of R2 = 97.6%, and its accuracy was verified by comparing the calculated fatigue life to the actual die breakage results with an error of 20.6%. As a result, the proposed model is practical and can be adopted to estimate the fatigue life of hot work tool steels for various stress and temperature conditions