Calculation and Analysis of TVMS Considering Profile Shifts and Surface Wear Evolution Process of Spur Gear

Profile shift is a highly effective technique for optimizing the performance of spur gear transmission systems.However,tooth surface wear is inevitable during gear meshing due to inadequate lubrication and long-term operation.Both profile shift and tooth surface wear(TSW)can impact the meshing characteristics by altering the involute tooth profile.In this study,a tooth stiffness model of spur gears that incorporates profile shift,TSW,tooth deformation,tooth contact deformation,fillet-foundation deformation,and gear body structure coupling is established.This model efficiently and accurately determines the time-varying mesh stiffness(TVMS).Additionally,an improved wear depth prediction method for spur gears is developed,which takes into consideration the mutually prime teeth numbers and more accurately reflects actual gear meshing conditions.Results show that consideration of the mutual prime of teeth numbers will have a certain impact on the TSW process.Furthermore,the finite element method(FEM)is employed to accurately verify the values of TVMS and load sharing ratio(LSR)of profile-shifted gears and worn gears.This study quantitatively analyzes the effect of profile shift on the surface wear process,which suggests that gear profile shift can partially alleviate the negative effects of TSW.The contribution of this study provides valuable insights into the design and maintenance of spur gear systems.

The Estimation of the Higher Heating Value of Biochar by Data-Driven Modeling

Biomass is a carbon-neutral renewable energy resource.Biochar produced from biomass pyrolysis exhibits preferable characteristics and potential for fossil fuel substitution.For time-and cost-saving,it is vital to establish predictive models to predict biochar properties.However,limited studies focused on the accurate prediction of HHV of biochar by using proximate and ultimate analysis results of various biochar.Therefore,the multi-linear regression(MLR)and the machine learning(ML)models were developed to predict the measured HHV of biochar from the experiment data of this study.In detail,52 types of biochars were produced by pyrolysis from rice straw,pig manure,soybean straw,wood sawdust,sewage sludge,Chlorella Vulgaris,and their mixtures at the temperature ranging from 300 to 800℃.The results showed that the co-pyrolysis of the mixed biomass provided an alternative method to increase the yield of biochar production.The contents of ash,fixed carbon(FC),and C increased as the incremental pyrolysis temperature for most biochars.The Pearson correlation(r)and relative importance analysis between HHV values and the indicators derived from the proximate and ultimate analysis were carried out,and the measured HHV was used to train and test the MLR and the ML models.Besides,ML algorithms,including gradient boosted regression,random forest,and support vector machine,were also employed to develop more widely applicable models for predicting HHV of biochar from an expanded dataset(total 149 data points,including 97 data collected from the published literature).Results showed HHV had strong correlations(|r|>0.9,p<0.05)with ash,FC,and C.The MLR correlations based on either proximate or ultimate analysis showed acceptable prediction performance with test R2>0.90.The ML models showed better performance with test R^(2)around 0.95(random forest)and 0.97–0.98 before and after adding extra data for model construction,respectively.Feature importance analysis of the ML models showed that ash and C were the most important inputs to predict biochar HHV.

Breakthrough Technologies for the Biorefining of Organic Solid and Liquid Wastes

Organic solid and liquid wastes contain large amounts of energy, nutrients, and water, and should not be perceived as merely waste. Recycling, composting, and combustion of non-recyclables have been practiced for decades to capture the energy and values from municipal solid wastes. Treatment and disposal have been the primary management strategy for wastewater. As new technologies are emerging, alternative options for the utilization of both solid wastes and wastewater have become available. Considering the complexity of the chemical, physical, and biological properties of these wastes, multiple technologies may be required to maximize the energy and value recovery from the wastes. For this purpose, biorefin- ing tends to be an appropriate approach to completely utilize the energy and value available in wastes. Research has demonstrated that non-recyclable waste materials and bio-solids can be converted into usable heat, electricity, fuel, and chemicals through a variety of processes, and the liquid waste streams have the potential to support crop and algae growth and provide other energy recovery and food production options. In this paper, we propose new biorefining schemes aimed at organic solid and liquid wastes from municipal sources, food and biological processing plants, and animal production facilities. Four new breakthrough technologies-namely, vacuum-assisted thermophilic anaerobic digestion, extended aquaponics, oily wastes to biodiesel via glycerolysis, and microwave-assisted thermochemical conversion-can be incorporated into the biorefining schemes, thereby enabling the complete utilization of those wastes for the production of chemicals, fertilizer, energy （biogas, syngas, biodiesel, and bio-oil）, foods, and feeds, and resulting in clean water and a significant reduction in pollutant emissions.

High-performance extended short-wavelength infrared PBn photodetectors based on InAs/GaSb/AlSb superlattices

High performance short-wavelength infrared PBn photodetectors based on InAs/GaSb/AlSb superlattices on GaSb substrate have been demonstrated.At 300 K,the device exhibits a 50%cut-off wavelength of~2.1μm as predicted from the band structure calculation;the device responsivity peaks at 0.85 A/W,corresponding to a quantum efficiency(QE)of 56%for 2.0μm-thick absorption region.The dark current density of 1.03×10^(-3)A/cm^(2)is obtained under 50 mV applied bias.The device exhibits a saturated dark current shot noise limited specific detectivity(D*)of 3.29×1010cm·Hz^(1/2)/W(at a peak responsivity of 2.0μm)under-50 mV applied bias.

The measurement of responsivity of infrared photodetectors using a cavity blackbody

For the measurement of responsivity of an infrared photodetector,the most-used radiation source is a blackbody.In such a measurement system,distance between the blackbody,the photodetector and the aperture diameter are two parameters that contribute most measurement errors.In this work,we describe the configuration of our responsivity measurement system in great detail and present a method to calibrate the distance and aperture diameter.The core of this calibration method is to transfer direct measurements of these two parameters into an extraction procedure by fitting the experiment data to the calculated results.The calibration method is proved experimentally with a commercially extended InGaAs detector at a wide range of blackbody temperature,aperture diameter and distance.Then proof procedures are further extended into a detector fabricated in our laboratory and consistent results were obtained.

Modelling the thresholds of nitrogen/phosphorus concentration and hydraulic retention time for bloom control in reclaimed water landscape

The risks posed by algal blooms caused by nitrogen and phosphorus in reclaimed water used in urban water landscapes need to be carefully controlled.In this study,the combined effects of the nitrogen and phosphorus concentrations and the light intensity and temperature on the specific growth rates of algae were determined using Monod,Steele,and Arrhenius models,then an integrated algal growth model was developed.The algae biomass,nitrogen concentration,and phosphorus concentration mass balance equations were used to establish a new control model describing the nitrogen and phosphorus concentration and hydraulic retention time thresholds for algal blooms.The model parameters were determined by fitting the models to data acquired experimentally.Finally,the control model and numerical simulations for six typical algae and mixed algae under standard conditions were used to determine nitrogen/phosphorus concentration and hydraulic retention time thresholds for landscape water to which reclaimed water is supplied(i.e.,for a reclaimed water landscape).