Analysis of vibration traits of underwater vehicle propulsion shafting and optimization design of support parameters

In this paper, the calculation model of the propulsion shafting structure was established to solve the problem of flexural vibration of the shafting system for the underwater vehicle with relatively small scale. By using the transfer matrix method and the finite element method, the vibration characteristics of the shafting system subjected to the transverse unsteady excitation force were calculated by MATLAB software and ABAQUS software. Two aspects of the displacement response and the vibration power flow were analyzed and compared. Analysis showed that the results of the two methods were very close to each other and all met the requirements of vibration engineering calculation. The influence of the mass of propeller and the bearing stiffness in different positions on the vibration characteristics were analyzed by using the transfer matrix method. Finally, based on the transfer matrix method, the parameters of the bearing stiffness at different supports were optimized with design optimization, and then use ABAQUS software to verify the effectiveness of the optimization. The analysis results showed that, after optimization calculation, the vibration power flow input to the bases of different bearings were significantly decreased

A digital twin to quantitatively understand aging mechanisms coupled effects of NMC battery using dynamic aging profiles

Traditional lithium-ion battery modeling does not provide sufficient information to accurately verify battery performance under real-time dynamic operating conditions, particularly when considering various aging modes and mechanisms. To improve the current methods, this paper proposes a lithium-ion battery digital twin that can capture real-time data and integrate the strong coupling between SEI layer growth, anode crack propagation, and lithium plating. It can be utilized to estimate aging behavior from macroscopic full-cell level to microscopic particle level, including voltage-current profiles in dynamic aging conditions, predict the degradation behavior of Nickel-Manganese-Cobalt-Oxide (NMC) based lithium-ion batteries, and assist in electrochemical analysis. This model can improve the root cause analysis of cell aging, enabling a quantitative understanding of aging mechanism coupled effects. Three charging protocols with dynamic discharging profiles are developed to simulate real vehicle operation scenarios and used to validate the digital twin, combining operando impedance measurements, post-mortem analysis, and SEM to further prove the conclusions. The digital twin can accurately predict battery capacity fade within 0.4% MAE. The results indicate that SEI layer growth is the primary contributor to capacity degradation and resistance increase. Based on the analysis of the model, it is concluded that one of the proposed multi-step charging protocols, in comparison to a standard continuous charging protocol, can reduce the degradation of NMC-based lithium-ion batteries. This paper represents a firm physical foundation for future physics-informed machine learning development

Temperature distribution of 10 kV and 15 kV SiC-MOSFETs with large edge area

Thermal simulations evaluated temperature distribution of 10kV and 15kV SiC-MOSFETs with larger die edge areas. Experimental temperature measurements of the die surface confirmed thermal modeling. The results revealed that larger edges amplified die surface temperature variation compared to 1.2kV SiC-MOSFET. Simulation results also mentioned temperature variation of bond wires and solder during power cycle testing

A First Generation Microsatellite- and SNP-Based Linkage Map of Jatropha

Jatropha curcas is a potential plant species for biodiesel production. However, its seed yield is too low for profitable production of biodiesel. To improve the productivity, genetic improvement through breeding is essential. A linkage map is an important component in molecular breeding. We established a first-generation linkage map using a mapping panel containing two backcross populations with 93 progeny. We mapped 506 markers (216 microsatellites and 290 SNPs from ESTs) onto 11 linkage groups. The total length of the map was 1440.9 cM with an average marker space of 2.8 cM. Blasting of 222 Jatropha ESTs containing polymorphic SSR or SNP markers against EST-databases revealed that 91.0%, 86.5% and 79.2% of Jatropha ESTs were homologous to counterparts in castor bean, poplar and Arabidopsis respectively. Mapping 192 orthologous markers to the assembled whole genome sequence of Arabidopsis thaliana identified 38 syntenic blocks and revealed that small linkage blocks were well conserved, but often shuffled. The first generation linkage map and the data of comparative mapping could lay a solid foundation for QTL mapping of agronomic traits, marker-assisted breeding and cloning genes responsible for phenotypic variation

RAB9A Plays an Oncogenic Role in Human Liver Cancer Cells

Background. RAB9, as a member of the Rab GTPase family, is required for the transport of the mannose-6-phosphate receptor (MPR) from late endosomes to trans-Golgi network (TGN). However, the role of RAB9A in tumors, including liver cancer, is still unknown. Methods. We used pcDNA3.1 plasmid to upregulate the expression of RAB9A in Hep3b cells and used specific shRNA to downregulate the expression of RAB9A in HepG2 cells. Biological functions of RAB9A were performed by CCK-8 assay, colony formation assay, apoptosis analysis, transwell assays, and wound healing assays. Finally, an in-depth mechanism study was performed by western blot. Results. RAB9A promoted the proliferation and clonality of Hep3b and HepG2 cells. RAB9A also inhibited apoptosis and the activation of mitochondrial apoptotic pathway. In addition, RAB9A promoted the invasion and migration of Hep3b and HepG2 cells. Importantly, RAB9A activated the AKT/mTOR signaling pathway in human liver cancer cells. A double-effect inhibitor (BEZ235) significantly hindered the effect of RAB9A overexpression on the proliferation and invasion of Hep3b cells. Conclusion. Our data suggest that RAB9A plays a carcinogenic role in human liver cancer progression partially through AKT signaling pathways, suggesting that RAB9A may serve as a potential therapeutic target for liver cancer therapy

Effects of Atmospheric Turbulence on OAM-POL-FDM Hybrid Multiplexing Communication System

This paper proposes a 32-channel-hybrid-multiplexing system on atmospheric turbulence. With the utilization of the hybrid multiplexing of orbital angular momentum (OAM), polarization, and frequency, the communication speed of the system can be significantly improved, and this system can be well combined with the existing frequency division multiplexing (FDM) optical communication network. Within this communication system, we discuss the effects of different turbulence intensities on the phase, OAM crosstalk, spectrum, and bit error rate (BER) in turbulent channels. Under strong turbulence, 46.8% of the energy leaks to the neighbor OAM and become noise when multiple topological charge states are transmitted. The research reflects the impact of various parameters of the OAM hybrid multiplexing system under turbulence, which is closer to a practical application scenario and is significant for implementing OAM communication in the turbulence channel

Identification of mechanism consistency for LFP/C batteries during accelerated aging tests based on statistical distributions

This study establishes a novel approach to investigate if accelerated aging tests can accurately model realistic cell aging in a short time while also maintaining the consistency of the involved aging mechanisms. As a trade-off between efficiency and consistent mechanism, the application of accelerated aging necessitates carefully selecting stress factors to identify the operational range and the significance of aging-related stress factors. Based on three levels of major stress factors designed for 43-month calendar aging tests and 10-month cyclic aging tests, this work aims at the stress ranking and indicating suitable operational intervals for commercial LFP/C batteries, taking two of the most popular lifetime distributions for batteries, namely log-normal and Weibull. Statistical distributions of lithium-ion batteries are attained from discharge capacity loss with nonlinear mixed-effects (NLME) models. Results prove that log-normal is the preferred model, and the right-skewed Weibull becomes more pronounced with deeper aging, especially in calendar aging. The evolution law of distribution parameters guided by the consistent acceleration factor was derived. The likelihood ratio parametric bootstrap approach based on the NLME model for life samples consistently yields that test conditions with the temperature above 47.5 °C and average state-of-charge (SOC) for cycling aging above 72.5% can result in different life behaviors. In contrast, the combination of SOC levels and higher temperatures does not lead to a change in the calendar aging mechanisms. The temperature is the most significant stress, followed by temperature-coupled cycle depth and SOC levels. This method can offer a reference to make reasonable test plans for detecting battery's performance to predict their life more accurately

How to identify mechanism consistency for LFP/C batteries during accelerated calendar and cycling aging using the lognormal distribution

The accelerated aging test is a powerful tool to stress batteries and predict their performance. Although some test conditions cause the battery to age more rapidly, it may force other unexpected effects on how they age over time, leading to a misunderstanding of normal lifetime results. This paper explores the experimental stress intervals for commercial LFP/C batteries to ensure mechanistic consistency based on a 43-month calendar aging test and a 10-month cyclic aging test, taking the log-normal distribution as a time-to-failure statistical lifetime model. A comprehensive study is performed based on capacity measurements during calendar aging considering two stress factors (the temperature and the state-of-charge (SOC) level) and cycling aging considering three stress factors (the temperature, the SOC level, and the cycle-depth (CD) level). The permutation test using likelihood ratio (LR) is used to determine the consistency of parameter estimates. Based on the consistent acceleration factor principle, test conditions causing different lifetime behaviors can be pointed out. The ranking of different stress effects in the test range can be obtained. This method can be used as a reference to make reasonable test plans for detecting battery's performance, thereby, predicting their lifetime more accurately.</p

Identification of mechanism consistency for LFP/C batteries during accelerated aging tests based on statistical distributions

This study establishes a novel approach to investigate if accelerated aging tests can accurately model realistic cell aging in a short time while also maintaining the consistency of the involved aging mechanisms. As a trade-off between efficiency and consistent mechanism, the application of accelerated aging necessitates carefully selecting stress factors to identify the operational range and the significance of aging-related stress factors. Based on three levels of major stress factors designed for 43-month calendar aging tests and 10-month cyclic aging tests, this work aims at the stress ranking and indicating suitable operational intervals for commercial LFP/C batteries, taking two of the most popular lifetime distributions for batteries, namely log-normal and Weibull. Statistical distributions of lithium-ion batteries are attained from discharge capacity loss with nonlinear mixed-effects (NLME) models. Results prove that log-normal is the preferred model, and the right-skewed Weibull becomes more pronounced with deeper aging, especially in calendar aging. The evolution law of distribution parameters guided by the consistent acceleration factor was derived. The likelihood ratio parametric bootstrap approach based on the NLME model for life samples consistently yields that test conditions with the temperature above 47.5 °C and average state-of-charge (SOC) for cycling aging above 72.5% can result in different life behaviors. In contrast, the combination of SOC levels and higher temperatures does not lead to a change in the calendar aging mechanisms. The temperature is the most significant stress, followed by temperature-coupled cycle depth and SOC levels. This method can offer a reference to make reasonable test plans for detecting battery's performance to predict their life more accurately