High-temperature lubrication mechanism of alkaline borates

Like any other metalworking processes, lubrication plays a crucial role in hot metal forming (e.g. hot rolling). An effective lubrication ensures high energy efficiency, low material loss and optimal product quality. The current study investigates potential lubrication properties of alkaline borates at elevated temperature by extensive experimental work. Advanced microscopy analysis allows insights into working mechanics of the lubricants at different scales which help addressing some fundamental questions arise from the past literatures. Tribological behaviors of sodium borate were thoroughly studied by pin-on-disc testing. With a transition point around 525oC, the material exhibits exceptional lubrication performance over the range of 600oC-800oC on sliding steel pair (GCr15/mild steel). This is demonstrated by remarkable reduction in friction coefficient and wear loss volume on both contact surfaces lubricated by sodium borate compared to the unlubricated case..

Open-set person identification based on mm-Wave Radar Point-clouds using Siamese Neural Networks.

openMillimeter-wave (mm-Wave) radar has been widely used in numerous applications in recent years, including drive-assistance system or short-range sensing due to its numerous advantages over other sensing technologies. The mm-Wave radar can measure the micro-Doppler phenomenon caused by moving objects in a scene, including people. The micro-Doppler effect induced by hunan gait has been proved to be a weak biometric identifier, due to the unique way of walking of each individual. In this work, we propose an open-set person identification based on the obtained mm-Wave radar point-clouds which intend to distinguish a new, unknown person from a known set of people. There are three main tasks studied: (1) extending a deep learning classification model to better distinguish unknown subjects in an open-set scenario; (2) applying Siamese Neural Network (SNN) for open-set identification to detect the new person in the recognized group of people; (3) evaluating the proposed method on our own measured data from a mm-Wave device on 20 subjects. We obtain useful experimental results to guide future work in this area.Millimeter-wave (mm-Wave) radar has been widely used in numerous applications in recent years, including drive-assistance system or short-range sensing due to its numerous advantages over other sensing technologies. The mm-Wave radar can measure the micro-Doppler phenomenon caused by moving objects in a scene, including people. The micro-Doppler effect induced by hunan gait has been proved to be a weak biometric identifier, due to the unique way of walking of each individual. In this work, we propose an open-set person identification based on the obtained mm-Wave radar point-clouds which intend to distinguish a new, unknown person from a known set of people. There are three main tasks studied: (1) extending a deep learning classification model to better distinguish unknown subjects in an open-set scenario; (2) applying Siamese Neural Network (SNN) for open-set identification to detect the new person in the recognized group of people; (3) evaluating the proposed method on our own measured data from a mm-Wave device on 20 subjects. We obtain useful experimental results to guide future work in this area

Implicitly estimating the cost of mental illness in Australia: a standard-of-living approach

Background Estimating the costs of mental illness provides useful policy and managerial information to improve the quality of life of people living with a mental illness and their families. Objective This paper estimates the costs of mental health in Australia using the standard-of-living approach. Methods The cost of mental illness was estimated implicitly using a standard of living approach. We analyse data from 16 waves of the Household, Income and Labour Dynamics in Australia Survey (HILDA) using 209,871 observations. Unobserved heterogeneity was mitigated using an extended random-effects estimator. Results The equivalised disposable income of people with mental illness, measured by a self-reported mental health condition, needs to be 50% higher to achieve a similar living standard as those without a mental illness. The cost estimates vary considerably with measures of mental illness and standard of living. An alternative measure of mental illness using the first quintile of the SF-36 mental health score distribution resulted in an increase of estimated costs to 80% equivalised disposable income. Conclusion People with mental illness need to increase equivalised disposable income, which includes existing financial supports, by 50%-80% to achieve a similar level of financial satisfaction as those without a mental illness. The cost estimate can be substantially higher if the overall life satisfaction is used to proxy for standard of living

Sideslip-induced static pressure errors in flight-test measurements

During lateral flight-test maneuvers of a V/STOL research aircraft, large errors in static pressure were observed. An investigation of the data showed a strong correlation of the pressure record with variations in sideslip angle. The sensors for both measurements were located on a standard air-data nose boom. An algorithm based on potential flow over a cylinder that was developed to correct the pressure record for sideslip-induced errors is described. In order to properly apply the correction algorithm, it was necessary to estimate and correct the lag error in the pressure system. The method developed for estimating pressure lag is based on the coupling of sideslip activity into the static ports and can be used as a standard flight-test procedure. The estimation procedure is discussed and the corrected static-pressure record for a typical lateral maneuver is presented. It is shown that application of the correction algorithm effectively attenuates sideslip-induced errors

Wet Torrefaction of forest Residues – Combustion Kinetics

AbstractFresh branches of Norway spruce and birch were torrefied in hot compressed water at varied temperatures(175, 200, or 225°C) and for 30minutes. The combustion of untreated and torrefied branchesin synthetic air (21% O2 and 79% N2) wasexperimentally studied by means ofa thermogravimetric analyzer, followed by a kinetic analysis adopting the distributed activation energy model. It appears that, wet torrefaction has significant effects on the combustion reactivity of forest residues. Compared with the raw materials, wet-torrefied branches are less reactive during devolatilization, but more reactive in the char combustion stage