Dynamic analysis of traction motor in a locomotive considering surface waviness on races of a motor bearing

The traction motor is the power source of the locomotive. If the surface waviness occurs on the races of the motor bearing, it will cause abnormal vibration and noise, accelerate fatigue and wear, and seriously affect the stability and safety of the traction power transmission. In this paper, an excitation model coupling the time-varying displacement and contact stiffness excitations is adopted to investigate the effect of the surface waviness of the motor bearing on the traction motor under the excitation from the locomotive-track coupled system. The detailed mechanical power transmission path and the internal/external excitations (e.g., wheel–rail interaction, gear mesh, and internal interactions of the rolling bearing) of the locomotive are comprehensively considered to provide accurate dynamic loads for the traction motor. Effects of the wavenumber and amplitude of the surface waviness on the traction motor and its neighbor components of the locomotive are investigated. The results indicate that controlling the amplitude of the waviness and avoiding the wavenumber being an integer multiple of the number of the rollers are helpful for reducing the abnormal vibration and noise of the traction motor.

     

Effects of (Li0.5Sm0.5)/W co-substitution and sintering temperature on the structure and electrical properties of ultrahigh Curie temperature piezoceramics,Ca0.92(Li0.5Sm0.5)0.08Bi2Nb2-xWxO9

With co-substitution of (Li_0.5Sm_0.5) at A site and W at B site, the electrical properties of modified Ca_0.92(Li_0.5Sm_0.5)_0.08Bi₂Nb_2-xW_xO₉ [(CLS)BN-xW, x = 0, 0.015 and 0.03] piezoceramics with ultrahigh Curie temperature (T_C) of > 930 °C were enhanced dramatically. The increased resistivity induced by the co-substitution ensure them to be polarized under an enough high field. Combined with the increase of spontaneous ferroelectric polarization (P_S), the significant enhancements in the piezoelectric, dielectric and ferroelectric properties can be obtained in the composition x = 0.015. Furthermore, the piezoelectric activity (d₃₃) and bulk resistivity (ρ_b) of (CLS)BN-0.015 W can be further enhanced at an appropriate sintering temperature. This optimum composition sintered at 1170 °C shows ultrahigh T_C of ～948 °C, d₃₃ of ～17.3 pC/N and ρ_b of ～6.9 MΩ cm at 600 °C, which are comparable to those of the reported high-temperature Aurivillius piezoceramics with T_C > 850 °C.     

自重湿陷性黄土地基预钻孔浸水处理的可靠度设计方法

为解决传统预浸水法存在的浸水时间长、浸水处理范围难以确定等不足,基于土体中水分运移规律,依据可靠度理论、极限状态设计方法及复合 Poisson 过程原理,提出一种消除黄土湿陷性的处理浸水方法——预钻孔浸水法。给出了利用预钻孔浸水法对自重湿陷性黄土地基进行浸水时,水平向及竖直向浸水影响范围的确定模型;在此基础上结合达西定律给出了浸水孔设计参数如孔深、孔间距及浸水孔个数的确定方法。结合铜川某工程,设计进行了现场预钻孔浸水试验,对该方法的合理性进行了验证,并通过现场钻探、现场勘探、室内湿陷性试验等方法对该方法的处理效果进行了评价。该浸水方法具有浸水时间短、浸水影响范围可根据浸水孔布设进行控制等优点,且浸水处理效果良好,完全符合施工要求。     

Grain orientation evolution and multi-scale interfaces enhanced thermoelectric properties of textured Sr0.9La0.1TiO3 based ceramics

Sr_0.9La_0.1TiO₃ based textured ceramics (SLTT-S3T) with a texture fraction of 0.81 are successfully fabricated by the reactive template grain growth method, in which Sr_0.9La_0.1TiO₃/20 wt%Ti was used as matrix and 10 wt% plate-like Sr₃Ti₂O₇ template seeds were used as templates. The phase transition, microstructure evolution, and the anisotropic thermoelectric properties of SLTT-S3T ceramics were investigated. The results show that the ceramics are mainly composed of Sr_0.9La_0.1TiO₃ and rutile TiO₂ phases. Grains grow with a preferred orientation along (h00). A maximum ZT of 0.26 at 1073 K was achieved in the direction perpendicular to the tape casting direction. The low lattice thermal conductivity of 1.9 W/(m K) at 1073 K was obtained decreased by 34%, 40%, and 38% compared with non-textured, SrTiO₃ and Sr_0.9La_0.1TiO₃ ceramics prepared by the same process, can be attributed to the enhanced phonon scattering by the complex multi-scale boundaries and interfaces. This work provides a strategy of microstructural design for thermoelectric oxides to decrease intrinsic lattice thermal conductivity and further regulate thermoelectric properties via texture engineering.     

Enhanced mechanical properties of porous titanium implants via in-situ synthesized titanium carbide in lamellar pore walls

Directional lamellar porous titanium scaffolds are widely used as bone implant bearing materials because of their anisotropic pore structure. Their mechanical properties can be effectively improved by enhancing the strength of pore walls through the introduction of ceramics. In this work, porous titanium implants were prepared by freeze casting combined with TiH₂ decomposition. The graphene was introduced into the pore walls of porous titanium, which could transform into titanium carbide (TiC) in situ upon sintering. TiC was evenly distributed in the lamellar pore walls, and the interface was well bonded. The compression strength of the fabricated implants was up to 389.94 MPa when the graphene content was 3 wt%, which was 377.8% times as high as the porous titanium. The crack propagation was resisted by TiC because of the “pinning” effect on the pore wall. Some of TiC were pulled out from the matrix, and others were fractured. The strength of the fabricated implants was improved significantly by the large consumption of fracture energy. Also, fabricated porous titanium implants with TiC are suitable for bone implantation.     

Flash cosintering of a lanthanum strontium cobalt ferrite nanofibre/Gd-doped ceria bilayer structure

For solid oxide fuel cells, an important structural requirement is that the electrolyte layer needs to be dense and the electrode layer porous, which is difficult to obtain by conventional cosintering. In this work, flash cosintering of a double layer structure consisting of a Gd-doped ceria substrate with a lanthanum strontium cobalt ferrite nanofibre coating is investigated. Experimental and finite element modelling results reveal that when the LSCF layer is connected to the electrode, the heat is concentrated in the LSCF layer, which leads to a huge temperature gradient and introduces severe cracking. When the LSCF layer is electrically isolated from the electrode, the heat is concentrated in the GDC layer, and the temperature gradient is dramatically reduced. In this situation, the density of GDC can reach 92.86% while a high porosity of 52.26% is maintained in the LSCF layer, which is higher than that of the conventional cosintered sample.     

Process knowledge-based random forest regression for model predictive control on a nonlinear production process with multiple working conditions

In process industry, predictive control approaches have been widely used for nonlinear production processes. Practically, the predictor in a predictive controller is extremely important since it provides future states for the optimization problem of controllers. The conventional predictive controller with precise mathematical predictors approximating the state space of physical systems is difficult and time-consuming for nonlinear production processes, and it performs poorly over a wide range of working conditions and with significant disturbances. To address the challenges, the trend of applying artificial intelligence emerges. However, the industrial process-specific knowledge is ignored in most cases. In this study, a predictive controller with a control process knowledge-based random forest (RF) model is proposed. Specifically, working data are clustered at first to handle diverse working conditions. Then, a process knowledge-based forest predictor, namely MIW-RF model with a redesigned cascading RF structure, is proposed to incorporate control process knowledge into modeling. Thus, future states of controlled variables could be more accurately acquired for the optimizer. A simplified version of the predictive model is also developed with quick model training and updating. The proposed predictive methods are finally introduced into the controller design. According to the empirical results, the proposed methods deliver a better control performance against benchmarks, including more accurate anticipated controlled-variable responses, better set-point tracking and disturbance rejection capability.     

Insights from proteome to phosphorylated proteome: deciphering different regulatory mechanisms in goat muscles with high- and low-meat quality

To investigate the inner mechanisms of meat quality differences between high-quality (HQ) and low-quality (LQ), a comparative quantitative study between longissimus thoracis and external intercostals of goat muscle was performed from proteome to phosphorylated proteome using RP-HPLC in combination with the ‘isobaric tag’ for relative and absolute quantitation (iTRAQ) labelling strategy. Altogether, 1441 proteins were identified in our study, of which 673 were phosphoproteins, and a total of twenty were common differentially expressed proteins. Myosin, carbonic anhydrase, and phosphoglucomutase could be used as proteins marker for HQ and LQ meat. Bioinformatics analysis showed that these proteins exhibited different rates for glycolysis and oxidative phosphorylation reaction, thus causing the different pH and NADH change rates, and resulting in better colour, tenderness, and water retention in HQ meat. The release of Ca²⁺ and adenosine triphosphate changed the meat quality through calcium signalling. Our finding provides a comprehensive view of proteome changes and their phosphorylation levels in goat muscle, involved in producing meats of different muscle parts. It also gives a better understanding of the regulation of protein on various biological processes that determine the final meat quality attributes.     

Special Issue on Artificial Intelligence and Technology: Trend,Challenges, and Opportunities

Mobile Networks and Applications -