Common Vehicle Research Articles

Increasing the post-repair resource of the wheels attachment bolts of transport machinery

Abstract. Problem. The state of war in our country and a significant reduction in the production of new vehicles exacerbated the problem of increasing their operational resource due to repairs. Improving the quality and increasing the efficiency of transport vehicles involves, first of all, the fight against wear and tear, because the reason for their premature failure (from 75 to 90%) is significant wear and tear of parts. A significant number of parts of the main structural units of vehicles are exposed to cyclic loads, so it is quite reasonable to pay attention to the issue of increasing the fatigue strength of products. Considering the significant shortage and high cost of spare parts, an expedient and economically beneficial solution to these problems is the restoration and strengthening of the surface layers of products during repair The parts that mostly fail prematurely and require repair using rational methods of recovery include the bolts of fastening the wheels of buses - a very common vehicle that is intensively operated in very difficult conditions. The development of effective technological processes for the restoration of bolts with a simultaneous increase in the post-repair resource at the lowest costs is definitely an urgent issue, because it will prevent another possible premature failure in operation Goal. The purpose of the work is to restore and increase the post-repair resource of the bolts for fastening the disks of the rear wheels of the bus. Methodology. The subject of the study were the serial bolts for fastening the discs of the rear wheels of the bus made of 40X steel after quenching and tempering at 500-550º C with a trostite-bainite structure and a hardness of 35-37 НРС. For vibro-arc surfacing, electrode wire Нп-30ХГСА with a diameter of 1.2 mm was used. Food carbon dioxide was used as a protective gas, and a 5% solution of soda ash in water was used as an accelerating coolant. After surfacing, the surface was subjected to bombardment with low-energy (up to 3 keV) titanium ions in an argon environment at the Bulat - 3t installation. After the specified methods of bolt processing, the roughness and surface profile were evaluated, the microstructure was studied, and the mechanical properties were determined. The strength limit of the slotted part of the bolt was determined using special samples on the CD10 universal machine (made in Germany). Cyclic tests of welded samples were carried out according to the scheme "tension during rotation of the cantilever-loaded sample" on the UMP-02 machine. Tensile tests were performed according to standard methods. Originality. To increase the cyclic durability and wear resistance of bolts, a modern method of surface modification was used - ion bombardment with low-energy ions (without coating), which made it possible to strengthen the surface layer without losing plasticity. An increase in the resource was achieved due to a change in the state of the surface (obtaining ultrafine crystalline nano-sized grain, healing of surface stress concentrators), and a change in the mechanism of plastic deformation - from dislocation to rotational with grain-boundary sliding of ultra-fine grains. Practical value. The recommended mode of vibro-arc surfacing provides surface hardness for the possibility of further mechanical processing without additional thermal weakening, which increases the cost-effectiveness of the process of compensation of the worn surface layer. Modification of the surface by ion brombarbing after surfacing made it possible to increase the cyclic durability by 2 times, significantly increase the static strength without loss of plasticity, and increase the hardness to ensure wear resistance.

Evaluation of Operability and Exhaust Emissions of Common Rail Direct Injection Engine using Biodiesel Blends in Moderate Cold Environment

Malaysia has restricted the use of biodiesel blends to B7 in the highlands due to challenges related to cold flow operability, while B10 and B20 are used in the lowlands. This study evaluated the performance and emissions of a light-duty, 4-cylinder Euro III turbocharged common rail direct injection diesel vehicle using palm biodiesel blends (B10, B20, and B30) at speeds of 60, 80, and 100 km/h under simulated cold temperatures of 10, 15, and 20°C in a controlled cold chamber. The combustion of B10 and B20 in the diesel engine showed enhancements in power and torque of 3.9% and 4.6%, respectively, compared to Euro 2M (B7) diesel. These improvements are likely the result of the synergistic effects of the enriched oxygen levels in biodiesel and the increased density of cold air, which enhance combustion efficiency. CO2 emissions decreased by 1.5%, 4.3%, and 11.2% with the use of B10, B20, and B30 fuels, respectively. NOx emissions decreased as biodiesel content increased at 10 and 15°C; however, the emissions increased by 17.6% and 38.2% for B20 and B30, respectively, in comparison to B10 at 20°C. B20 demonstrated good engine performance and emissions at 15°C, with improvements of 1.3% in power and 3.7% in torque, which compensated for a 3.2% increase in fuel consumption, and there were reductions of 8.9% in NOx emissions and 0.9% in CO2 emissions compared to B7 diesel. Palm biodiesel blends ranging from 7 wt.% to 20 wt.% are capable of withstanding the moderate cold ambient temperatures of the highlands without compromising engine operation.

Knowledge, attitudes, and practices towards poultry handling and Salmonella risk among households in Beirut, Lebanon

Food-Borne Disease (FBD) is defined as an illness resulting from consuming foods contaminated with bacteria, their toxins, viruses, or parasites. Food poisoning due to improper food handling is a major global public health problem. In Lebanon, numerous challenges affect safe food consumption, with poultry being a common vehicle for many pathogens, such as Salmonella spp. This bacterium can cause serious illnesses, including gastroenteritis, characterized by abdominal pain, vomiting, diarrhea, and fever. This study aimed to examine the Knowledge, Attitudes, and Practices (KAPs) towards poultry handling among households in Beirut, Lebanon, and identify factors influencing KAP levels. A cross-sectional study was conducted through face-to-face interviews with 125 households in different areas of Beirut. The interview was divided into four main parts: sociodemographic characteristics, knowledge, attitudes, and practices. The results showed that consumers' knowledge and practices were inadequate, though their attitude was positive. Participants aged 43–55 had higher odds of having a good knowledge level than those aged 18–29 (OR = 3.889, p = 0.02). Additionally, those with a college education were 7.442 times more likely to have a positive attitude towards food safety compared to those with no formal education (p = 0.005). Most participants (91.2 %) do not regularly check their refrigerator and freezer temperatures. Furthermore, significant associations (p < 0.001) existed between the different KAP levels. This study aimed to raise public awareness regarding the handling of chicken to minimize food-borne illnesses by evaluating food handlers’ knowledge and behaviors. Insights from this study can used in campaigns to raise awareness about Salmonella and transmission risks among households. Moreover, findings may guide policymakers to create regulations for safe handling of poultry.

Ionizable Cationic Lipids and Helper Lipids Synergistically Contribute to RNA Packing and Protection in Lipid-Based Nanomaterials.

Lipid-based nanomaterials are used as a common delivery vehicle for RNA therapeutics. They typically include a formulation containing ionizable cationic lipids, cholesterol, phospholipids, and a small molar fraction of PEGylated lipids. The ionizable cationic lipids are considered a crucial element of the formulation for the way they mediate interactions with the anionic RNA as a function of pH. Here, we show, by means of molecular dynamics simulation of lipid formulations containing two different ionizable cationic lipids (DLinDMA and DLinDAP), that the direct interactions of those lipids with RNA, taken alone, may not be sufficient to determine the level of protection and packaging of mRNA. Our simulations help and highlight how the collective behavior of the lipids in the formulation, which determines the ability to envelop the RNA, and the level of hydration of the lipid-RNA interface may also play a significant role. This allows the drawing of a hypothesis about the experimentally observed differences in the transfection efficiency of the two ionizable cationic lipids.

Nanogene editing drug delivery systems in the treatment of liver fibrosis.

Liver fibrosis is a group of diseases that seriously affect the health of the world's population. Despite significant progress in understanding the mechanisms of liver fibrogenesis, the technologies and drugs used to treat liver fibrosis have limited efficacy. As a revolutionary genetic tool, gene editing technology brings new hope for treating liver fibrosis. Combining nano-delivery systems with gene editing tools to achieve precise delivery and efficient expression of gene editing tools that can be used to treat liver fibrosis has become a rapidly developing field. This review provides a comprehensive overview of the principles and methods of gene editing technology and commonly used gene editing targets for liver fibrosis. We also discuss recent advances in common gene editing delivery vehicles and nano-delivery formulations in liver fibrosis research. Although gene editing technology has potential advantages in liver fibrosis, it still faces some challenges regarding delivery efficiency, specificity, and safety. Future studies need to address these issues further to explore the potential and application of liver fibrosis technologies in treating liver fibrosis.

Validation of a generic finite element vehicle buck model for near-side crashes

Objective Finite element (FE) reconstructions of motor vehicle crashes using human body models are effective tools for developing a better understanding of occupant kinematics and injuries in real-world lateral crash conditions, but current near-side reconstruction methods are limited by the paucity of full-scale FE vehicle models. The objective of this study was to validate a generic vehicle model equipped with left-side airbags and intrusion capability by simulating a series of near-side crash tests for a range of vehicles and assessing model accuracy using objective evaluation methods. Methods Moving deformable barrier crash tests were reconstructed for five common vehicle classifications (compact passenger, mid-size passenger, sport utility vehicle, pickup truck, and van) using an updated version of a previously developed simplified vehicle model. Unknown vehicle and intrusion properties (pretensioner force, seatback airbag pressure, curtain airbag pressure, door panel stiffness, ratio of dynamic-to-static intrusion, intrusion velocity, and intrusion scaling factor) were estimated by parameterizing them across 224 simulations per crash test using a Latin hypercube design of experiments. Model accuracy was assessed for 13 anthropomorphic test device signals using the Correlation and Analysis (CORA) objective rating method and injury metric comparisons. Results Maximum ratings of 0.69, 0.67, 0.52, 0.52, and 0.62 were achieved for the compact passenger, midsize passenger, sport utility vehicle, pickup truck, and van classifications, respectively. On average, the abdomen displayed the most accurate behavior (0.51 ± 0.12), followed by the thorax (0.50 ± 0.10) and head (0.50 ± 0.07). The pelvis displayed the least accurate behavior (0.46 ± 0.18) of any region. Reconstructions overpraedicted injury metrics in all cases. Conclusions All vehicles achieved “fair” biofidelity ratings and the compact passenger and midsize passenger vehicles achieved “good” biofidelity ratings, validating them for kinematic evaluations with vehicle-to-vehicle nearside crash reconstructions. Regression models were developed for injuries and CORA ratings and can be used to optimize vehicle parameters in future studies.

Solving low-carbon last mile delivery problem using discrete marine predators algorithm

With the increasing concentration of greenhouse gases, carbon peaking and carbon neutrality have gradually become a global issue. As the last link of e-commerce logistics, the last mile delivery should not only focus on customer satisfaction and enterprise cost, but also reduce carbon emission and promote green development. In order to solve the last mile delivery problem, this paper builds the last mile delivery model for two common delivery vehicles, considering the impact of transportation cost, carbon emission and customer satisfaction on the last mile delivery path planning. The last mile delivery is an NP-hard problem, a novel Discrete Marine Predators Algorithm(DMPA) is proposed to solve the problem, which combines neighborhood search strategy and RS hybrid operator. Six different test examples are generated based on Solomon for simulation experiments, and the experimental results verify that the proposed algorithm is obviously superior to the marine predators algorithm, simulated annealing algorithm and genetic algorithm. DMPA obtains significantly higher customer satisfaction than other algorithms. The customer satisfaction of C101 and C201 is as high as 0.99, which is close to the optimal value of 1. DMPA can achieve lower transportation costs and less carbon emissions compared with other algorithms. DMPA reduces the transportation cost by at least 61.12$ and the carbon emission by at least 1033.64 kg for C101 by minivan delivery. DMPA reduces the transportation cost by at least 28.89$ and the carbon emission by at least 210.9 kg for C101 by electric tricycle delivery. It can effectively reduce carbon emission, lower transportation cost, improve service level, and promote the integration of the dual carbon target with the internal requirements of national development.

A least-squares identification method for vehicle cornering stiffness identification from common vehicle sensor data

In this study, we present a robust framework for vehicle tire cornering stiffness identification, leveraging commonly available lateral acceleration and yaw rate measurements. In contrast to most of the state-of-the-art approaches, our methodology does not rely on (augmented) state estimation, but on batch least-squares optimisation of larger time windows. This batch-approach has as a major benefit that many of the observability issues which are encountered in estimation-based methods are completely eliminated. By immediately exploiting the measurement equations, rather than comparing dynamic simulation responses, we obtain a very efficient and sparse formulation which enables online processing. The methodology was validated on (openly available) datasets from two different vehicles – a Ferrari 250LM and Range Rover Evoque, delivering consistent and accurate results for both vehicles. This work shows that batch optimisation can be a very promising alternative for the more common state-estimation approaches for extracting reliable vehicle cornering stiffnesses in various driving scenarios with a much more straightforward tuning.

Evaluation of the accuracy of remote emission sensing measurements via real-world vehicle dynamic tests

To evaluate the measurement accuracy of horizontal and vertical remote emission sensing (RES) equipment, a real-world dynamic test was carried out in Chengdu by using electric vehicles equipped with various concentrations of standard gases. In addition, a new Image-based Spectral Processing Algorithm (ISPA) for vertical remote sensing spectral data was developed to improve the measurement capability. The results showed that the ISPA provided a greater percentage of valid data and lower relative errors; thus, our new algorithm could more effectively analyze the spectral data to measure vehicle emission levels. The percentages of valid horizontal and vertical RES data were 71% and 84%, respectively. The mean relative errors of CO2, CO, HC and NO measured by the vertical RES were about 5%, 20%, 20% and 40%, respectively, and those of CO2, CO and NO measured by the horizontal RES were 3%, 13% and 15%, respectively. For the common vehicle emission concentration, the percentage of valid data for the two RES types increased with increasing gas concentration. As the vehicle speed increased, the relative errors of the horizontal RES equipment showed an increasing trend for the same concentration of gas. Furthermore, for the same speed segment, the relative errors of the horizontal RES equipment increased as the simulated emission concentration decreased. The vertical RES equipment did not exhibit a consistent trend in terms of changes. This study provides a data quality reference for further RES applications.

Sumonity: Bridging SUMO and Unity for Enhanced Traffic Simulation Experiences

This paper presents "Sumonity," an interface that bridges SUMO (Simulation of Urban MObility) and Unity, combining SUMO's robust traffic modeling capabilities with Unity's advanced graphical and physical engine, enhancing realism in traffic simulations. The study explores Sumonity's development and implementation, showcasing its capabilities. The interface offers a significant improvement in simulation fidelity by adopting a pure pursuit control approach within Unity for simulating each traffic agent. This methodological shift allows for more granular control over individual vehicle behaviors, aligning with autonomous and common vehicle dynamics. The paper also discusses the broader implications of Sumonity for future research in this field.

Inventory of the Sterilization Units at a Tertiary-Level South Tunisian University Hospital

Sterilization of reusable medical devices (RMD) is considered as one of the major components of healthcare associated infection (HAI) prevention that should be strictly maintained. Microorganisms responsible for HAI can be transmitted from a common inanimate vehicle such as medical RMD to patients. Sterilization is a complete process with a set of successive steps to finally achieve a sterile RMD. In addition to these steps, which must be carefully controlled, the whole environment of this process should also conform to quality and security standards and criteria in order to ensure a robust sterilization process and a secure RMD. Therefore, a complete and exhaustive evaluation of this process is highly recommended. This evaluation aimed firstly to examine the inventory of sterilization process, architecture, and environment as well as to present recommendations to be adopted to adjust the practices and failures recorded accordingly.

Vehicle Classification and Counting for Traffic Analysis based on Single-stage YOLOv8 Model

Intelligent traffic systems are emerging and becoming part of smart city infrastructure that requires computer vision applications to provide traffic information like vehicle classification and counting in real-time. Vehicle counting helps detect heavy traffic on roads, and vehicle classification helps enforce further processes like speed estimation to enforce speed limit laws based on the vehicle class. Deep learning computer vision-based systems provide automatic feature extractions that are robust to changes in lighting, shadows, and occlusions. This paper proposes a software solution for a real-time traffic monitoring system based on a cutting-edge single-stage deep learning model through the state-of-the-art YOLOv8 algorithm. YOLOv8 is the most recent model of the YOLO family, which provides object detection and classification through its CNN architecture. The proposed work detects vehicles and counts them based on their class. The four common vehicle classes are sedan cars, buses, trucks, and motorcycles, and a counter for each class is displayed on the system’s output screen in real-time and recorded in a log file. The results of the proposed system running on the Nvidia GTX 1070 GPU show an average accuracy of 96.58% with an average error of 3.42% for vehicle detection and an average accuracy of 97.54% with a 2.46% average error for vehicle counting. For vehicle classification, the results for the four vehicle classes (car, bus, truck, and motorcycle) show an accuracy of (94.7%, 94.7%, 96.2%, 99.7%), precision (95%, 100%, 81.4%, 100%), recall (97.9%, 36.3%, 100%, 66.6%), and the f1-score (96.3%, 53.2%, 89.7%, 79.9%), respectively. Index Terms— Computer Vision, Deep Learning, Vehicle Detection, Traffic Analysis, YOLO.

A comparison of the performance of contemporary, historical, and cross-lab controls in QTc assessment in conscious nonhuman primates

Cardiovascular safety pharmacology and toxicology studies include vehicle control animals in most studies. Electrocardiogram data on common vehicles is accumulated relatively quickly. In the interests of the 3Rs principles it may be useful to use this historical information to reduce the use of animals or to refine the sensitivity of studies.We used implanted telemetry data from a large nonhuman primate (NHP) cardiovascular study (n = 48) evaluating the effect of moxifloxacin. We extracted 24 animals to conduct a n = 3/sex/group analysis. The remaining 24 animals were used to generate 1000 unique combinations of 3 male and 3 female NHP to act as control groups for the three treated groups in the n = 3/sex/group analysis. The distribution of treatment effects, median minimum detectable difference (MDD) values were gathered from the 1000 studies. These represent contemporary controls.Data were available from 42 NHP from 3 other studies in the same laboratory using the same technology. These were used to generate 1000 unique combinations of 6, 12, 18, 24 and 36 NHP to act as historical control animals for the 18 animals in the treated groups of the moxifloxacin study. Data from an additional laboratory were also available for 20 NHP.The QT, RR and QT-RR data from the three sources were comparable. However, differences in the time course of QTc effect in the vehicle data from the two laboratories meant that it was not possible to use cross-lab controls. In the case of historical controls from the same laboratory, these could be used in place of the contemporary controls in determining a treatment's effect. There appeared to be an advantage in using larger (≥18) group sizes for historical controls. These data support the opportunity of using historical controls to reduce the number of animals used in new cardiovascular studies.

Do large registered investment funds undermine shareholder activism? Evidence from hedge fund proposals

We examine the voting behavior of Registered Investment Funds (Mutual Funds, ETFs and Close-end Funds) on Hedge Funds proposals, a common vehicle of value-driven shareholder activism. We compare the support rates of Registered Funds versus other voting shareholders on different types of proposals set up for voting at shareholders meetings and explore fund-level characteristics that may explain the variation in support rates. Our results show that Registered Funds support rates on Hedge Fund proposals vary depending on the proposal category. In general, the support rates of Registered Funds are about 4 percentage points lower compared to other investors. However, that difference rises to 10 p.p. for proposals that are more confrontational to the incumbent management of the target company. Interestingly, the average lower support rates of Registered Funds are driven by the ten largest funds. On the contrary, Registered Funds from smaller parent groups tend to be more supportive of Hedge Fund activism. We document a 18 p.p. reduction in the probability of favorable votes on Hedge Fund proposals by the largest Registered Funds compared to smaller funds. Our results suggest that the growing ownership in public companies by large Registered Funds reduces the overall support of shareholder activism through Hedge Fund proposals.

Investigation of Surface-Catalycity Effects on Hypersonic Glide Vehicle Trajectory Optimization

The optimization of a hypersonic glide vehicle’s reachable domain is studied using different models to constrain the stagnation-point heat transfer. The vehicle is modeled as a high-lift common aero vehicle that uses bank-angle modulation for crossrange maneuvering with a leading-edge thermal protection system made of an ultra-high-temperature ceramic. A constrained nonlinear optimization problem is formulated to determine the range of feasible trajectories that satisfy aerodynamic heating and loading constraints. The optimal control profile is determined using a modified particle swarm optimization routine that employs a penalty function approach to handle path and terminal constraints. Baseline trajectories are determined using an existing convective heat-flux correlation, and the effect of surface catalycity on the optimized trajectories is investigated by applying a correction factor, derived from high-fidelity computational fluid dynamics simulations, to the heat-flux correlation. Results demonstrate a high sensitivity of the optimized trajectories to the underlying aerothermodynamics model such that accounting for surface catalycity expands the reachability by an order of magnitude.

Global phylogeography and genomic characterization of blaKPC and blaNDM-positive clinical Klebsiella aerogenes isolates from China, 2016-2022

Carbapenem-resistant Klebsiella aerogenes (CRKA), being one of the members of carbapenem-resistant Enterobacteriaceae (CRE), has caused great public health concern, but with fewer studies compared to other CRE members. Furthermore, studies on phylogenetic analysis based on whole genome Single-Nucleotide Polymorphism (SNP) of CRKA were limited. Here, 20 CRKA isolates (11 blaKPC-2-bearing and 9 blaNDM-1/5-harboring) were characterized by antimicrobial susceptibility testing, conjugation assay, whole genome sequencing (WGS) and bioinformatics analysis. Additionally, the phylogeographic relationships of K. aerogenes were further investigated from public databases. All isolates were multidrug-resistant (MDR) bacteria, and they demonstrated susceptibility to colistin. Most blaKPC-2 or blaNDM-1/5-carrying plasmids were found to be conjugative. Phylogenetic analysis revealed the clonal dissemination of K. aerogenes primarily occurred within clinical settings. Notably, some strains in this study showed the potential for clonal transmission, sharing few SNPs between K. aerogenes and KPC- and/or NDM-positive K. aerogenes isolated from various countries. The STs of K. aerogenes strains had significant diversity. WGS analysis showed that the IncFIIK plasmid was the most prevalent carrier of blaKPC-2, and, blaNDM-1/5 were detected on the IncX3 plasmids. The Tn6296 and Tn3000 transposons were most common vehicles for facilitating the transmission of blaKPC-2 and blaNDM-1/5, respectively. This study highlights the importance of continuous screening and surveillance by WGS for analysis of drug-resistant strains in hospital settings, and provide clinical information that supports epidemiological and public health research on human pathogens.

Difference analysis and characteristics of incompatibility group plasmid replicons in gram-negative bacteria with different antimicrobial phenotypes in Henan, China

BackgroundMulti-drug-resistant organisms (MDROs) in gram-negative bacteria have caused a global epidemic, especially the bacterial resistance to carbapenem agents. Plasmid is the common vehicle for carrying antimicrobial resistance genes (ARGs), and the transmission of plasmids is also one of the important reasons for the emergence of MDROs. Different incompatibility group plasmid replicons are highly correlated with the acquisition, dissemination, and evolution of resistance genes. Based on this, the study aims to identify relevant characteristics of various plasmids and provide a theoretical foundation for clinical anti-infection treatment.Methods330 gram-negative strains with different antimicrobial phenotypes from a tertiary hospital in Henan Province were included in this study to clarify the difference in incompatibility group plasmid replicons. Additionally, we combined the information from the PLSDB database to elaborate on the potential association between different plasmid replicons and ARGs. The VITEK mass spectrometer was used for species identification, and the VITEK-compact 2 automatic microbial system was used for the antimicrobial susceptibility test (AST). PCR-based replicon typing (PBRT) detected the plasmid profiles, and thirty-three different plasmid replicons were determined. All the carbapenem-resistant organisms (CROs) were tested for the carbapenemase genes.Results21 plasmid replicon types were detected in this experiment, with the highest prevalence of IncFII, IncFIB, IncR, and IncFIA. Notably, the detection rate of IncX3 plasmids in CROs is higher, which is different in strains with other antimicrobial phenotypes. The number of plasmid replicons they carried increased with the strain resistance increase. Enterobacterales took a higher number of plasmid replicons than other gram-negative bacteria. The same strain tends to have more than one plasmid replicon type. IncF-type plasmids tend to be associated with MDROs. Combined with PLSDB database analysis, IncFII and IncX3 are critical platforms for taking blaKPC−2 and blaNDM.ConclusionsMDROs tend to carry more complex plasmid replicons compared with non-MDROs. The plasmid replicons that are predominantly prevalent and associated with ARGs differ in various species. The wide distribution of IncF-type plasmids and their close association with MDROs should deserve our attention. Further investigation into the critical role of plasmids in the carriage, evolution, and transmission of ARGs is needed.

A pressure control method for increasing the energy efficiency of the hydraulic system powering agricultural implements

Agricultural tractors and their implements are at the basis of modern farming. Besides propulsion, in such system, most of the mechanical actuations are performed with a fluid power system that is highly power-dense and versatile, but has a low energy efficiency. This article first describes the challenges of the state-of-the-art hydraulic system that cause poor efficiency. Afterward, it proposes and demonstrates a solution that can significantly increase such efficiency without affecting the cost and functionality of the overall hydraulic control system. The proposed solution is based on a peculiar control approach to the hydraulic supply units that power the implement functions through the hydraulic remote connections. The approach is based on an impressed-pressure control methodology, as opposed to the traditional impressed flow method used in off-road machinery. The result is that the typical energy-inefficient pressure saturation conditions that often occur in common vehicles are mitigated and brought to a more efficient state. To support the development of the technology, the research takes into consideration the circuit of a 400-hp tractor and a 16-row planter. A simulation model of the hydraulic system of the two vehicles was implemented and validated against experiments. The model was then utilized to estimate the reduction in the energy consumption achieved by the proposed solution. Lab tests and field experiments of the proposed solutions applied to the reference tractor and planter system confirmed an overall 18% energy efficiency improvement.

A multispectral vision-based machine learning framework for non-contact vehicle weigh-in-motion

The present study proposes an automated non-contact weigh-in-motion framework using multispectral vision and machine learning method, which provides an all-weather monitoring of heavy vehicles on transportation infrastructures. Multispectral based computer vision techniques consist of two steps, one is acquiring the tire deformation parameters from thermal imaging camera and the latter is obtaining the sidewall characters from the ordinary one. A novel edge detection algorithm is designed for thermal image-based tire deformation estimation. A general recognition model with well-established tire characters database for universal tire sidewall markings, such as non-standard fonts or non-text characters, curved markings or inverted markings, and is developed based on Efficient neural network (E-NET) and YOLOV5S methods. A machine learning-based model for estimating the various vehicles tire-roadway contact forces is established based on eXtreme Gradient Boosting (XGBoost). A database of different vehicles’ tires with a total of 1127 samples from 19 types of tires and 648 of laboratory datasets from common vehicles are collected to train the model. The Bayesian optimization is employed to capture the optimal model, and a hybrid training strategy including biased data is applied to update the model. An importance analysis for 11 features is conducted to validate the performance proposed model. The accuracy, feasibility, and effectiveness of the proposed method is carefully investigated by field experiments for trucks and sport utility vehicles under static and low-speed drive. A maximum of 5 % difference is witnessed by comparing the results with that of the traditional WIM system. The present method presents a cost-effective means with no sensors on structures for vehicle weighting, that demonstrates a great potential to implement in toll station, highway infrastructures as well as health monitoring of civil engineering fields.

Different-grain-sized boehmite nanoparticles for stable all-solid-state lithium metal batteries.

PEO is one of the common composite polymer electrolyte vehicles; however, the presence of crystalline phase at room temperature, high interface impedance, and low oxidation resistance (<4.0 V) limit its application in stable all-solid-state lithium metal batteries. Herein, we designed a PEO-based solid polymer electrolyte (SPE) by adding boehmite nanoparticles to address the above-mentioned issues. Different-grain-sized boehmite nanoparticles were synthesized by adjusting the hydrothermal temperature. Moreover, the impacts of these distinct grain-sized boehmite nanoparticles used to fabricate boehmite/PEO polymer electrolytes (BPEs) on the performance of all-solid-state lithium metal batteries were investigated. It was found that with the increase in boehmite's grain size, BPEs show better performance. The best BPE exhibited an improved Li+ transference number (0.59), high ionic conductivity (1.25 × 10-4 S m-1), and wide electrochemical window (∼4.5 V) at 60 °C. The assembled lithium symmetric battery can stably undergo 500 hours of lithium plating/stripping at 0.1 mA cm-2. At the same time, the LiFePO4/BPE/Li battery exhibits excellent cycling stability after 100 cycles at 0.5C. This reasonable design strategy with a superior capacity retention rate (86%) demonstrates great potential in achieving high ionic conductivity and good interface stability for all-solid-state lithium metal batteries simultaneously.