Cargo Vehicles Research Articles

Research and development of automation subroutine for forecasting the number and load of cargo vehicles depending on the stochastic formation of dangerous goods collection centers

The issues of forecasting the load of vehicles, route networks, formation of collection centers for cargo flows, including dangerous goods, in territorial planning systems determine the need for transition from deterministic models to dynamic models with the possibility of taking into account the influence of the external environment. Existing information transportation systems in the sphere of work with dangerous goods are based on deterministic models and allow to study the problems of forecasting changes to a limited extent. Models of routing networks construction on cargo vehicles are limitedly applicable when there is a task of dangerous goods transportation taking into account the presence of a distributed system of accumulation centers both in the city and, for example, within a large transport hub, seaport with different terminals. The paper presents routing models adapted to the conditions of dangerous goods transportation. Determining transport efficiency and the main costs of transport enterprises is the scheme of traffic flows, fixed in the territorial scheme. The task of the study is to develop a separate automation toolkit for decision making on the number and type of specialized transport (depending on the load capacity) to work with dangerous goods and large-sized objects within the existing flow scheme. On the basis of the research of the group of companies the conclusion is presented that today the task of choosing the optimal amount of transport by carriers is solved, as a rule, not systematically, but by operative construction of a set of routes, and does not involve primary analysis of the territory and parameters of accumulation sites. The presented study considers a new approach to the analysis of the system of transportation of hazardous waste, associated large cargoes, in terms of assessing the necessary list of universal structured input data, which are primary principled and characterize the complexity of work in the selected facility, terminal. To solve the problem of forecasting the load of vehicles is offered developed a new automation subprogram based on the organization of client-server access to data, and implemented in the internal programming language “1C. Management of motor transport” (version ММT 8.2). The presented automation subprogram provides data connectivity on volumes of dangerous goods cargo flows, cargo flow collection centers, available data on vehicles and planned data on removal schedules. Work of the subprogram provides integration of work with other databases of transport companies and allows to carry out modeling of various variants of placement of centers of collection of dangerous goods, centers of cargo flows with high accuracy. The obtained results allow to determine the required number of vehicles, their load taking into account different types and technical capabilities, as well as to determine the required number of vehicle trips in the serviced area taking into account the dynamic influence of the external environment. The presented methodology of working with data, performed in a separate automation subprogram, presented routing models, adapted to the transportation of dangerous goods, can be applied to various transport systems, including sea cargo ports and terminals, which determines the universality of the presented approach.

Методика оценки экологического эффекта от применения биотоплив

Purpose: the fight for ecology in the transport sector is ensured by improving the design of vehicles and engines, the working processes of internal combustion engines, as well as the use of alternative fuels. To determine the rational use of biofuels in vehicles, it is necessary to assess the environmental effect that will be achieved when using them. Methods: the existing methods of estimating exhaust gas emissions from motor vehicles are considered. Based on them, improvements have been made, which include the introduction of additional coefficients that take into account changes in the environmental load depending on the percentage of biofuels mixed with traditional hydrocarbon fuels. Results: the calculation of the environmental effect from the use of biofuels was carried out using the example of adding biodiesel to petroleum diesel fuel, for which, based on statistical data from the US Environmental Protection Agency and data, WE established dependences of changes in annual emissions of harmful substances and carbon dioxide for a heavy-duty cargo vehicle. In addition to the calculation, the article presents graphs of emissions of harmful substances, taking into account their relative aggressiveness and the amount of carbon dioxide released during the combustion of biodiesel mixtures. Practical significance: The proposed method for calculating the environmental effect makes it possible to estimate the volume of emissions of harmful substances and carbon dioxide depending on the concentration of biofuels mixed with traditional fuels. Such an approach can provide an overall picture of the effect of using biodiesel, and at the same time, the coefficients used need to be clarified.

Agricultural Tire Test: Straw Cover Effect on Reducing Soil Compaction by Cargo Vehicles

Agricultural cargo vehicles are responsible for applying severe soil pressures. However, the ground straw cover can attenuate the loads applied by wheels to the soil surface. This research evaluated the effect of three tires, p1—Radial Very Flex, p2—Radial Improved Flex, and a p3—Bias Ply tire, on three amounts of straw on the soil surface (0, 15, and 30 Mg ha−1). We adopted a completely randomized design (CRD) with a rigid surface for three replications for the total contact area and punctual area claws. The soil bin test verified the deformable surface, tread marks, and soil penetration resistance (SPR). The tire’s claw design determines its punctual contact area, and the construction model determines the total contact area. The contact area in the soil bin increased linearly due to a increase in straw covering, reducing sinkage; p2 to 30 Mg ha−1 straw shows the most significant contact area, p1 and p3 showed no difference. A straw increase from 0 to 30 Mg ha−1 increased the contact areas by 25.5, 38.0, and 20.0% for p1, p2, and p3, respectively. Compared to the rigid surface, the p1 and p3 contact areas in the soil bin increased 6.2, 6.8, and 7.8 times in bare soil, 15, and 30 Mg ha−1; for p2, this increase was up to 4.2, 4.5, and 5.9 times on the same surfaces. Keeping the straw on the soil improves its physical quality by reducing the SPR, so the straw has a buffer function in the wheel–soil relationship.

An optically responsive cancer vaccine for inducing robust anti-tumor immunity by apoptotic body carrying nanoadjuvants

A cancer vaccine based on nano-adjuvant fusion represents an effective strategy for anti-tumor immunity. Compared with other cancer vaccine formulations, the ones based on apoptotic bodies not only possess higher load-bearing capacity and biosafety, but also present greater clinical translational potential. In this study, we developed an optically responsive cancer vaccine that induced robust anti-tumor immunity by encapsulating genipin-crosslinked nano-adjuvants in tumor cell apoptotic bodies. The vaccine may potentially be used for prophylactic or therapeutic purposes. As an antigen source and a cargo vehicle, apoptotic bodies can co-deliver antigens and adjuvants simultaneously to antigen-presenting cells to activate T cells. Nano-adjuvants promote the targeted delivery of adjuvants for effective immune responses. Genipin-crosslinked nano-adjuvants enable visual tracking of the tumor vaccine. In addition, the photothermal properties of genipin-crosslinked nano-adjuvants promote lysosomal escape of tumor antigens to enhance cross-presentation. These characteristics enable visualization and controllability of cancer vaccines, thereby avoiding the need for exogenous photosensitive reagents. Apoptotic body-based vaccines can be used to prevent or treat tumors by triggering a strong systemic immune response by promoting T-cell infiltration and improving the tumor immune microenvironment.

Unsteady Surface Pressure Characterization on Launch Vehicle in Liftoff Configuration

Acquisition of unsteady pressure using remote scanners can provide practical advantages over making the same measurements directly using flush-mounted pressure transducers. However, pneumatic distortion of the signal is introduced by the tubing between the sensing module and surface port. This typically limits the usefulness of such measurements to averaged, steady data only, restricting the application of pressure scanners for unsteady pressure measurements in wind-tunnel and flight-testing applications. In this work, unsteady pressure on the surface of a 1.75%-scale model of the NASA Space Launch System Block 1B Cargo vehicle was remotely measured using an electronic scanning pressure module at the NASA Langley Research Center 14-by 22-Foot Subsonic Tunnel. Subsequent reconstruction using an empirically tuned, Wiener-filtered inverse transfer function produced excellent agreement compared to nearby surface-mounted transducers within a usable bandwidth of approximately 500 Hz. Interactions between the launch vehicle and the support tower produced strong oscillations that were absent in the vehicle-alone configuration, and it is likely that the wake interaction leads to a resonant flow response when the launch tower is immediately downstream of the vehicle.

A System of IoT Devices to Prevent Under-Loading Over-Loading of Cargo Vehicles

Efficient and safe cargo transportation is a cornerstone of modern logistics and the loading of cargo vehicle is a crucial aspect of this process. This project introduces a comprehensive system of IOT Devices designed to prevent both under-loading and overloading of CARGO VEHICLE.The system incorporates an Arduino UNO microcontroller, load cells for load detection, MEMS sensors to act as virtual doors for theft detection, IOT modules for sending SMS alerts and cloud data upload, GPS for location tracking and information sharing and an LCD display for data visualization.

Extracellular vesicles in pancreatic cancer: a new era in precision medicine.

Pancreatic cancer (PC) is a lethal disease that presents a considerable challenge to healthcare providers and patients, given its low survival rate. However, recent advancements in precision medicine and innovative technologies have transformed the management of this disease. Among these advancements, extracellular vesicles (EVs) have emerged as crucial players in cancer progression. In PC, EVs play a pivotal role by facilitating cell-cell communication, impeding immune response, promoting cancer cell proliferation and survival, and supporting angiogenesis and chemoresistance. Cancer-derived EVs have a distinct oncogenic composition supporting tumour development and progression. Hence, they are critical biomarker candidates for various cancers, including PC. Notably, EVs can be isolated from diverse biological fluids such as blood, urine, and saliva, making them an ideal minimally invasive diagnostic and monitoring tool for PC patients. Despite the promising findings in the field of EVs, clinical validation as biomarkers is lacking. Furthermore, EVs being biocompatible, can act as drug carriers, delivering therapeutic molecules directly to cancer cells while minimizing toxicity to healthy cells. Therefore, understanding the role of EVs as biomarkers and their potential as drug cargo vehicles may revolutionise early detection, prognostication, and treatment in cancer. This mini-review summarises the latest understanding of their role in intercellular communication, involvement as potential biomarkers and drug carriers.

Estimation of stops of last-mile delivery vehicles: An application in the food industry in the city of Santiago de Chile

The study of vehicle stops in last-mile delivery has gained ground in the specialized logistics literature. An efficient last-mile delivery reduces distribution costs and mitigates negative externalities such as pollution and congestion. This paper estimates the stops of last-mile trucks that deliver food products in Santiago, Chile. The aim is to study last-mile delivery operations using a non-intrusive, low-cost method. Particularly, we devise a novel methodology that employs multiple data sources to detect the primary stops of cargo vehicles. The proposed methodology involves the following two steps. First, we use GPS data to identify all the candidates for stops, that is, clusters of points close to each other in terms of distance and time, and then, these stops are classified as primary according to the proximity to planned visits or check-out markings. Finally, we conduct a case study involving food distribution, deriving managerial and public policy insights. We find that the most adequate time threshold to detect stops in our context is 4 min, which is considerably lower than previous studies. This last may be explained by the last-mile nature of our study. Our results show that primary (i.e., delivery) stops are concentrated mainly in the center of Santiago, with a duration that decreases as the hours go by. This last means that some of the externalities caused by truck stops (e.g., road capacity reduction) are exacerbated during the morning rush hour. We also find that the average duration of the primary stops is 12.5 min, while the mean distance traveled between two consecutive stops is 4.68 km.

Precision control of one-/two-dimensional assemblies for Poly(hexamethylene carbonate) block copolymers

The precision control of monodisperse nanomaterials with spatially distinct functionalities and properties is of particular interest in materials science. Creating biocompatible/biodegradable nanoparticles that can be colloidally stable in aqueous solution further paves the way to a broad range of bio-related applications. In present work, we demonstrate the precise fabrication of aliphatic polycarbonate based one-dimensional (1D) cylinders and 2D platelet micelles using living crystallization-driven self-assembly (CDSA) by seeded growth method. By synthesizing aliphatic polycarbonate core-forming block copolymers with different corona-to-core ratios, excellent control over dimensions of 1D cylinders and 2D platelets with good uniformity is achieved through effectively epitaxial growth in ethanol based on the mass ratios of unimer-to-seed. Meanwhile, segmented nanoparticles with spatially-defined chemistries can further be prepared by sequential seeded growth approach. Moreover, these 1D/2D nanostructures are colloidally stable in water, and further show excellently biocompatible property towards L929 cells. These promising properties of polycarbonate-based micelles enable to a wide application as cargo vehicles in bio-related fields.

Signal synchronization methods when measuring tailpipe emissions with PEMS

This study describes the effects of using different signal synchronization methods on the tailpipe emission factors obtained by on-road tests using PEMS (Portable Emission Measurement Systems). The event-based, static correlation, and dynamics correlation methods were applied to data obtained using different PEMS. The first database included 36 cargo vehicles following the same driving cycle in various cities in Colombia. The second database involved 16 passenger transport vehicles monitored under real operating conditions in Mexico. When comparing results with the event-based synchronization method as the reference, significant differences in emission factors (>25 %) were observed. Those differences depend directly on the physical setup of the PEMS. The dynamic correlation method exhibited the best performance in all cases. When using this method, we recommend to synchronize the CO2 mass flow and fuel consumption variables first and then adjust the obtained synchronization to other species to account for differences in species diffusivities.

Numerical Study of Reinforced Aluminum Composites for Steering Knuckles in Last-Mile Electric Vehicles

The steering knuckle is a critical component of the suspension and steering drive systems of electric vehicles. The electrification of last-mile vehicles presents a challenge in terms of cost, driving range and compensation of battery weight. This work presents a numerical methodology to evaluate 60XX series aluminum metal matrix composites (AMMCs) with reinforcement ceramic particles for steering knuckle components in medium heavy-duty last-mile cargo vehicles. The use of AMMCs provides lightweight knuckles with sufficient strength, stiffness and safety conditions for electrical vehicle cargo configurations. The numerical study includes three aluminum alloys, two AMMC alloys and an Al 6061-T6 alloy as reference materials. The medium-duty heavy vehicle class < 12 t, such as electrical vehicle cargo configurations, is considered for the numerical study (class 1–4). The maximum von Mises stress for class 4 AMMC alloys exceeds 350 MPa, limited by fracture toughness. The weight reduction is about 65% when compared with commercial cast iron. Moreover, Al 6061-T6 alloys exhibit stress values surpassing 300 MPa, constraining their suitability for heavier vehicles. The study proposes assessing the feasibility of implementing AMMC alloys in critical components like steering knuckles and suggests solutions to enhance conventional vehicle suspension systems and overcome associated challenges. It aims to serve as a lightweight design guide, offering insights into stress variations with differing load conditions across various cargo vehicles.

Power Consumption Analysis of a Prototype Lightweight Autonomous Electric Cargo Robot in Agricultural Field Operation Scenarios

The continuous growth of the urban electric vehicles market and the rapid progress of the electronics industry create positive prospects towards fostering the development of autonomous robotic solutions for covering critical production sectors. Agriculture can be seen as such, as its digital transformation is a promising necessity for protecting the environment, and for tackling the degradation of natural resources and increasing nutritional needs of the population on Earth. Many studies focus on the potential of agricultural robotic vehicles to perform operations of increased intelligence. In parallel, the study of the activity footprint of these vehicles can be the basis for supervising, detecting the malfunctions, scaling up, modeling, or optimizing the related operations. In this regard, this work, employing a prototype lightweight autonomous electric cargo vehicle, outlines a simple and cost-effective mechanism for a detailed robot’s power consumption logging. This process is conducted at a fine time granularity, allowing for detailed tracking. The study also discusses the robot’s energy performance across various typical agricultural field operation scenarios. In addition, a comparative analysis has been conducted to evaluate the performance of two different types of batteries for powering the robot for all the operation scenarios. Even non-expert users can conduct the field operation experiments, while directions are provided for the potential use of the data being collected. Given the linear relationship between the size and the consumption of electric robotic vehicles, the energy performance of the prototype agricultural cargo robot can serve as a basis for various studies in the area.

Complex fuzzy intelligent decision modeling for optimizing economic sustainability in transportation sector

AbstractThis paper introduces the concept of complex quadratic Diophantine fuzzy sets (CQDFS) which serves as a robust framework for effectively dealing with uncertainty within decision-making challenges. The study comprehensively explores the properties and characteristics of CQDFS by conducting a systematic comparative analysis to demonstrate its superiority over existing techniques in managing complex fuzzy information. This foundation contributes to the theoretical understanding of CQDFS and also provides valuable practical insights into a wide range of transportation strategies and economic efficiency. These insights offer practical solutions to enhance decision-making within these important and interconnected domains. The proposed complex information system serves as a versatile and adaptive tool, significantly strengthening the flexibility available for addressing complex decision-making challenges, particularly in contexts such as the management of GPS-enabled cargo vehicles and cargo loading operations, where precision and efficiency are of great importance.

Biofuels and energy transition policy in Brazil: contributions, limits and possibilities given the need for climate justice in the Capitalocene

The article aims to discuss about the climate change has imposed a new agenda in the scope of international relations, bringing to regulation the need for reconciliation between different fields of knowledge, such as law, study of energy, issues of an economic, political and social nature, with multiple interests, agendas, demands that need to be modulated, not in favor of immediate interests, but of future generations. In this way, based on the concepts of climate justice and energy transition, the work seeks to analyze the role of biofuels within the Brazilian energy transition strategy. It was presented how the Capitalocene is responsible for an unprecedented crisis that threatens the existence of life on the planet. It was highlighted that technologies need to be more than sustainable, as it is no longer enough to be renewable, they also need to have low CO2 emissions, to be able to break the catastrophic future that lies ahead. In this context, Brazilian biofuels such as ethanol and biodiesel stand out in comparison to the array of electric engines in the reorganization of the fleet of light and cargo vehicles, in the definition of transition policy.

Telematics and diagnosis system for autonomous cargo vehicle

The article deals with the problem of managing the operation and maintenance of autonomous trucks KAMAZ using a telematics and diagnostics system. The functions and composition of the onboard module of a robotic vehicle are described. The main controlled values are determined. The presence of a developed system for monitoring the state of units and assemblies provides a solution to the problem of controlling the modes of the car operation. The structure of the telematics and diagnostics system has been developed and implemented. The main blocks of the proposed system are shown. The main diagnostic and forecasting functions are performed on a workstation with an analytical module. It is proposed to use an approach based on previous conditions matrixes. An example of matrix analysis for a car engine cooling system is given. Modeling of the engine cooling system was carried out and graphs of transient processes were obtained. The analytical module is designed using artificial neural networks to analyze time series of car parameter values. To conduct virtual tests of a car in various operating modes, a simulation model was developed on a stochastic time colored Petri net. The model simulates both the movement of the vehicle to the point of production operations and the change in the technical condition of the car. The model makes it possible to describe and study the influence of random factors on the time of execution of production tasks, to take into account the probabilistic characteristics of failure events or defects in vehicle components and assemblies. The use of an artificial neural network in the analytical module of the diagnostic system workstation makes it possible to predict the technical condition of vehicle components and systems in real time, followed by verification of the dynamics of processes on a simulation model on a Petri net.

The influence of weight control parameters of cargo vehicles on their performance

The article examines the problem of incomplete use of the carrying capacity of vehicles due to regulatory restrictions on the permissible weight of the vehicle and the permissible load on the axle of the vehicle, analyzes the conditions under which the vehicle becomes heavy, and their owners may be subject to fines for violating current legislation in the field of weight control of vehicles, an example of the results of calculating the coefficient of utilization of the carrying capacity of a specific vehicle with axle loads not exceeding permissible is given for a highway with a standard load of 6, 10 and 11.5 tons, proposals are formulated for the effective use of vehicles in terms of carrying capacity under the conditions of normatively established weight restrictions. Keywords heavy vehicle, weight control, standard road loads, vehicle axle load

Engineered and hybrid human megakaryocytic extracellular vesicles for targeted non-viral cargo delivery to hematopoietic (blood) stem and progenitor cells.

Native and engineered extracellular vesicles generated from human megakaryocytes (huMkEVs) or from the human megakaryocytic cell line CHRF (CHEVs) interact with tropism delivering their cargo to both human and murine hematopoietic stem and progenitor cells (HSPCs). To develop non-viral delivery vectors to HSPCs based on MkEVs, we first confirmed, using NOD-scid IL2Rγnull (NSG™) mice, the targeting potential of the large EVs, enriched in microparticles (huMkMPs), chosen for their large cargo capacity. 24h post intravenous infusion into NSG mice, huMkEVs induced a nearly 50% increase in murine platelet counts. PKH26-labeled huMkEVs or CHEVs localized to the HSPC-rich bone marrow preferentially interacting with murine HSPCs, thus confirming their receptor-mediated tropism for NSG HSPCs, and their potential to treat thromobocytopenias. We explored this tropism to functionally deliver synthetic cargo, notably plasmid DNA coding for a fluorescent reporter, to NSG HSPCs both in vitro and in vivo. We loaded huMkEVs with plasmid DNA either through electroporation or by generating hybrid particles with preloaded liposomes. Both methods facilitated successful functional targeted delivery of pDNA, as tissue weight-normalized fluorescence intensity of the expressed fluorescent reporter was significantly higher in bone marrow than other tissues. Furthermore, the fraction of fluorescent CD117+ HSPCs was nearly 19-fold higher than other cell types within the bone marrow 72-h following administration of the hybrid particles, further supporting that HSPC tropism is retained when using hybrid particles. These data demonstrate the potential of these EVs as a non-viral, HSPC-specific cargo vehicle for gene therapy applications to treat hematological diseases.

ЦИФРОВОЙ ДВОЙНИК ЭЛЕКТРОПРИВОДА ГРУЗОВОГО ТРИЦИКЛА ДЛЯ ТРАНСПОРТИРОВКИ СЕМЯН

One of the most important directions of the development of the agricultural sector is the renewal of tractor and road transport for agricultural purposes, which is due to the predominance of manual labor on loading and unloading and transport operations, increased labor intensity of processes. The methods of selecting the optimal characteristics of vehicles are focusing on the average power characteristics, as well as the average values of the economic indicators of a particular vehicle. The paper is devoted to the study and optimization of the parameters of an electric cargo vehicle depending on the set conditions of the transport task of an agricultural enterprise by the method of simulation modeling. (Research purpose) The research purpose is to obtain optimal traction-power and energy-economic characteristics of the vehicle through simulation of the performance of the transport task of harvesting breeding grain at an agricultural enterprise. (Materials and methods) Conducted a study of simulation simulation of the transport cycle for harvesting breeding grain by a vehicle to identify the optimal parameters of the electric drive and batteries. It was determined that the simulation model contains the parameters of the transport cycle in the form of the distances of the track segments, the required speed of movement, the characteristics of the road surface, as well as the characteristics of the vehicle chassis and the weight with the load. Traction-speed and energy-economic characteristics of an electric vehicle were chosen as objects of research. (Results and discussion) The result of the simulation simulation was the dependence of the required power of the electric motor, taking into account its overload capacity, on the conditions of external factors of the transport cycle. (Conclusions) The analysis of the battery discharge made it possible to establish a minimum capacity of 80 ampere-hours for the full performance of the entire transport task of harvesting breeding grain. The function of overloading the motor twice for a given time of two seconds is justified in order to reduce the required rated power of the electric motor.

Optimal Trajectory Design for Unmanned Aerial Vehicle Cargo Pickup and Delivery System based on Radio Map

Optimal Trajectory Design for Unmanned Aerial Vehicle Cargo Pickup and Delivery System based on Radio Map

A Framework for In-Car Loading Optimization Problem

Speed is a crucial evaluation criterion in the cargo transportation industry. The processes carried out during transfers before cargo reaches the destination unit are vital for timely delivery. Time spent at cargo distribution centers should be minimized, the maximum number of packages should be transported in a single action between transfers, and cargo vehicles should be used as accurately and efficiently as possible. Minimizing unused space inside the vehicles and ensuring that vehicles at cargo transfer centers are arranged correctly and efficiently for faster departures and increased cargo capacity are of great importance. In pursuit of this goal, the present research concentrates on optimizing the loading of vehicle interiors. This investigation proposes a method that determines the optimal dimensions of packages to be loaded within the vehicle, with the intention of maximizing the number of cargo packages while minimizing the interior volume used. A preliminary implementation of the suggested approach has been created. This developed prototype application can assist cargo transportation companies in planning their cargo loading and optimizing the utilization of vehicle interiors. The efficacy of the prototype application was evaluated using a representative vehicle loading dataset, and the results demonstrate its success.