Search

Because of the complex nonlinear relationship between working conditions, the prediction of tribological properties has become a difficult problem in the field of tribology. In this study, we employed three distinct machine learning (ML) models, namely random forest regression (RFR), gradient boosting regression (GBR), and extreme gradient boosting (XGBoost), to predict the tribological properties of polytetrafluoroethylene (PTFE) composites under high-speed and high-temperature conditions. Firstly, PTFE composites were successfully prepared, and tribological properties under different temperature, speed, and load conditions were studied in order to explore wear mechanisms. Then, the investigation focused on establishing correlations between the friction and wear of PTFE composites by testing these parameters through the prediction of the friction coefficient and wear rate. Importantly, the correlation results illustrated that the friction coefficient and wear rate gradually decreased with the increase in speed, which was also proven by the correlation coefficient. In addition, the GBR model could effectively predict the tribological properties of the PTFE composites. Furthermore, an analysis of relative importance revealed that both load and speed exerted a greater influence on the prediction of the friction coefficient and wear rate. [ABSTRACT FROM AUTHOR]

High-solids simultaneous saccharification and fermentation integrating single-stage anaerobic digestion was designed for bioenergy conversion from steam-exploded Pennisetum purpereum , a perennial C 4 grass. Three scenarios for ethanol production, methane production and ethanol-methane co-production were investigated and compared in terms of production yield. A terminal ethanol titer of 62.6 ± 1.9 g/L with the highest ethanol yield of 90.9% was achieved when the fed-batch mode was carried out at a final substrate loading of 35% (w/v) dry matter content. The ethanol stillage was used for methane production in a semi-continuous CSTR system operated with different organic loading rates (OLRs) at a hydraulic retention time (HRT) of 30 days. The high performance was achieved at OLR of 6.0 g VS·L −1  d −1 , average yielding 358.7L CH 4 per kilogram volatile solid (VS) with a total VS removal rate of 73.8%. On the basis of mass balance, the overall production yield achieved in this study was: 121.6 g ethanol + 110.6 g methane per kilogram grass with a finally 89.6% of cellulose recovery + 62.5% hemicellulose recovery. These results indicated that the high-solids ethanol fermentation with single-stage methane anaerobic digestion of lignocellulosic biomass is a valid approach to maximize the holocellulose bioconversion and improve the bioenergy production. [ABSTRACT FROM AUTHOR]

Four gridding methods for GPS velocities are compared in terms of their precision, applicability and robustness by analyzing simulated data with uncertainties from 0.0 to ±3.0 mm/a. When the input data are 1° × 1° grid sampled and the uncertainty of the additional error is greater than ±1.0 mm/a, the gridding results show that the least-squares collocation method is highly robust while the robustness of the Kriging method is low. In contrast, the spherical harmonics and the multi-surface function are moderately robust, and the regional singular values for the multi-surface function method and the edge effects for the spherical harmonics method become more significant with increasing uncertainty of the input data. When the input data (with additional errors of ±2.0 mm/a) are decimated by 50% from the 1° × 1° grid data and then erased in three 6° × 12° regions, the gridding results in these three regions indicate that the least-squares collocation and the spherical harmonics methods have good performances, while the multi-surface function and the Kriging methods may lead to singular values. The gridding techniques are also applied to GPS horizontal velocities with an average error of ±0.8 mm/a over the Chinese mainland and the surrounding areas, and the results show that the least-squares collocation method has the best performance, followed by the Kriging and multi-surface function methods. Furthermore, the edge effects of the spherical harmonics method are significantly affected by the sparseness and geometric distribution of the input data. In general, the least-squares collocation method is superior in terms of its robustness, edge effect, error distribution and stability, while the other methods have several positive features. [ABSTRACT FROM AUTHOR]

The principal strain rate, derived from GPS velocities from the Tibetan Plateau and the India Plate, shows that the Himalayan tectonic belt exhibits compression deformation in a NE–NS–NE direction from the west to the east. The GPS velocity profiles reflect that the distribution of strain accumulation is uneven: there is a 17.1 mm/yr. compressive deformation distributed over 400 km along 85° E longitude, a 20.9–22.2 mm/yr. compressive deformation dispersed across 400–500 km along 79° E longitude, and a 15.3–16.9 mm/yr. compressive deformation spread across 500–600 km along 91° E longitude. The M W 7.8 Gorkha earthquake occurred at the edge of an intense compression deformation zone of about 6.0 × 10 − 8 /yr. in a north–south direction, and an about 90% compressive strain is absorbed in the 300 km region near the Main Frontal Thrust (MFT). Coseismic displacements, larger than three standard deviations (3SD), are mainly concentrated within 360 km from the epicenter. The nodal plane of the main shock divides the areas where tensile strain release in an exponential attenuation pattern is dominant to the north, and where compressive strain with upward movement is dominant to the south. The results inversed by the SDM program reveal that the maximal slip of the Gorkha earthquake is 5.33 m, and its moment magnitude is M W 7.85, and the largest stress drop is 4.21 Mpa. Slips larger than 0.5 m are mainly distributed in a region approximately 135 km × 105 km, which show that the rupture of the Gorkha earthquake does not reach the surface. Finally, we estimate that the recurrence period of this earthquake is about 166 ± 20 years according to the strain accumulation before the earthquake and the coseismic release feature. [ABSTRACT FROM AUTHOR]