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In this study, the dispersion and explosion of liquid hydrogen (LH 2) in leakage accidents are investigated using the Flame Accelerator Simulator (FLACS) code. The study focus was a liquid hydrogen research facility in Gimhae, South Korea. Simulations were conducted under various conditions by varying the mass flow rates (0.61 and 0.3 kg/s), directions (lateral in areas with minimal structures, lateral towards a tube trailer truck, and downward), and durations (90 and 180 s) of leakage. The results indicated that higher leakage mass flow rates produce a larger flammable cloud volume (FCV), resulting in higher maximum overpressures than that caused by lower flow rates. Downward leakage generally resulted in a larger FCV and higher overpressure than lateral leakage. The explosion characteristics were also influenced by geometry of LH 2 facility, including the presence of structures in the leakage path. Contrastingly, leakage duration had a minimal effect on the maximum overpressure because an increased duration causes a greater dilution of hydrogen, only slightly expanding the FCV. According to the overpressure–impulse diagram, higher leakage flow rates cause severe health risks, approaching thresholds for lung rupture and 100% fatality. Contrary to the minor damages caused by lower leakage flow rates. High flow rates, particularly with downward leaks, can cause significant structural damage in brick buildings, potentially leading to partial demolition. • Higher leakage mass flow rates result in larger flammable cloud volumes and increased maximum overpressures. • Downward hydrogen leaks lead to larger flammable clouds and higher overpressures than lateral leaks. • Facility geometry and structures significantly affect explosion overpressure magnitude and distribution. • Leakage duration has a minimal effect on maximum overpressure due to hydrogen dilution during leakage. [ABSTRACT FROM AUTHOR]

The modular construction industry struggles to implement the modularization strategy appropriately due to a poor understanding of the differences between stick-built and modular construction methods and unique modular challenges. Among many modular challenges, transporting prefinished volumetric modules is one of the underinvestigated key challenges—the conventional methods for module transportation [e.g., truck, self-propelled modular transporter (SPMT), and so on), although fitting for projects comprising multiple modules, are not ideal for projects with fewer modules and limited jobsite space. This study investigates hydraulic jacks and trailer bogie as the potential alternative transporting and module lifting/offloading methods by examining how the prefinished volumetric housing module is affected during the lifting, transporting (on-road and jobsite), and offloading phases of transportation. A sensor was installed on the volumetric housing module to record transportation-induced shocks in front-to-back tilt and left-to-right roll, deformation, and impact. The peaks and lows recorded for tilt and roll during each transportation phase were 42, 57, 1, and 0, and 346, 70, 6, and 14, respectively. The results indicated that impacts to the module were more directly associated with left-to-right rolls than front-to-back tilt, because high rolls primarily reflected the module making wide turns, whereas no deformation or impact was recorded. This study contributes to the body of knowledge by highlighting the hydraulic jack and trailer bogie as potential alternatives to the conventional crane and truck under certain conditions through the assessment of the transportation-induced impact on the prefinished volumetric housing module. [ABSTRACT FROM AUTHOR]

The direct‐to‐consumer (D2C) shipping mode presents new opportunity for fresh peach sales in North America where demand over the past four decades has steadily declined. The hazards in this distribution mode are severe, and fresh peaches are fragile emphasizing the need for proper protection. A full analysis that not only encompasses the effects of the D2C distribution environment but also incorporates analyses of the environmental and economic impact of the packages utilized for transit of peaches is necessary. In this study, we use the metrics of peach grade, firmness, soluble solids concentration and percent softness before and after the distribution simulation to compare the protective performance of six DTC packaging systems. All six packages consist of a single layer corrugated box with varying primary packaging. A life cycle analysis of each package system is performed as well as an economic analysis on the packaged materials and cost to ship. We conclude that peach damage in shock testing is related to the freedom of movement that peaches have within each package type and varies by package system. All the package types evaluated amplify input vibration in the frequency range commonly associated with the input from the tires of truck‐trailer systems. There are no statistical differences between package systems in the distribution simulation of the six package types except in peach softness and grade of melting flesh peaches. Finally, we found that a reduction in material use and change in format, that is, foam sheets to foam netting, provides for sufficient peach protection while reducing environmental and economic impact. [ABSTRACT FROM AUTHOR]

This paper presents a novel Continuous Variable Transmission (CVT) design. CVT is highly beneficial for actuators with rotary output as it can improve the energy efficiency of the actuators by providing an optimum transmission ratio. This property of CVT is highly beneficial for fossil-fuel-based vehicles, electric vehicles, wind turbines, industrial robots, etc. With the exception of Spherical CVT and DH CVT, all known CVTs like push belt CVTs, toroidal CVTs, Milner CVTs, etc., require additional gear sets and clutches for direction reversal and neutral gear ratio. However, Spherical CVT and DH CVT have low torque capacity due to a single traction point constraint. Foregoing in view, a new CVT named CAD CVT has been developed. The paper presents the design conception, the operating principle, the transmission ratio, the torque capacity, frictional losses, and experimental verification of the basic functionality by manufacturing a Proof of Concept (PoC). The proposed CVT is the only CVT capable of independent direction reversal and high torque capacity as it can transmit torque through multiple traction points. The new CVT will significantly impact high-torque applications in different engineering applications, especially land transport consisting of heavy vehicles like trucks, buses, and trailers. [ABSTRACT FROM AUTHOR]

A vehicle's long‐duration impacts events are experienced during turning, braking, and accelerating and decelerating. These long‐duration events are mixed with random impacts and shocks from various patterns and magnitudes. This study reports a comprehensive measurement and assessment of horizontal long‐duration impact dynamics for less‐than‐truckload (LTL) transportation. The collected horizontal impacts were synchronized with GPS data, allowing for the geographical location and identification of the event's signatures. All critical horizontal long‐duration impacts were detected by a MATLAB‐based algorithm and clustered into designated groups. A maximum collected environment and statistical analysis were assessed for the collected data, including the range, mean and cumulative probabilities. The study revealed that horizontal impacts caused by left‐turning and longitudinal braking are likely the most critical horizontal impacts. Additionally, lateral and longitudinal linear jerks were obtained for comparison with the EUMOS standard. [ABSTRACT FROM AUTHOR]

The dissipativity‐based analysis and synthesis issues of Takagi‐Sugeno (T‐S) fuzzy systems by applying aperiodic memory sampling control are investigated in this paper. Compared with the more conservative dissipative conditions and controller design methods proposed in the past based on Lyapunov theory, the main purpose of this paper is to obtain a less conservative dissipative criterion and devise an aperiodic memory sampled‐data controller. Firstly, the sampling controller is assumed to work in aperiodic sample mode, and the time delay in the communication network is considered. Next, an augmented delay‐product‐type looped‐functional is proposed such that the whole information of sampling and delay, which has not been studied before, is well taken into account. A new dissipative criterion and an aperiodic sampled‐data control strategy are proposed by applying free‐matrix‐based integral inequalities consequently. Finally, a truck‐trailer system is implemented to elaborate the availability and the merit of the designed strategy. [ABSTRACT FROM AUTHOR]

Multi-sensing technologies in vehicles have the potential to improve road and pedestrian safety. Freighting trucks with extended trailer face challenges in urban maneuvering due to limited visibility. In this paper, we evaluate and validate extended trailer dynamics for Heavy-Duty Trucks in road traffic situations with multi-sensor object tracking emphasizing trailer dynamics, back-end parameters, and characteristics that influence decision-making strategies. A custom in-vehicle compute unit, in combination with the onboard truck's computer, facilitated this research. [ABSTRACT FROM AUTHOR]

This paper analyzes the lateral control technology of autonomous semi-trailer trucks. Existing researches on the lateral control algorithm of semi-trailer trucks focus on making the head-truck or trailer follow a track well while ignoring the motion characteristics during the turning process, leading to specific security issues. Meanwhile, it is difficult to cope with the complex and uncertain factors influencing lateral control effect, such as the curvature of the desired trajectory, the load, and the velocity of the semi-trailer truck. This paper proposes a parametric self-learning model predictive control (MPC) based on the Proximal Policy Optimization of One Step (OSPPO) method to solve these problems. After modeling the kinematics of the semi-trailer truck, a lateral motion controller for the relationship between the head-truck and trailer based on the MPC method is established. The traditional MPC method has difficulty in adapting to the changeable influencing factors. Thus, a deep reinforcement learning algorithm named OSPPO is introduced to improve the flexibility of the MPC method. OSPPO establishes the nonlinear mapping relationship between the critical parameter of the MPC method and the factors influencing control effect by self-learning, avoiding a large amount of labeled data for training. In simulations, Trucksim and Matlab were used to conduct co-simulation to verify the usefulness of the control method. The method was implemented on an autonomous semi-trailer truck for many outdoor scenes. The actual experimental results showed the validity and advantages of the proposed method. [ABSTRACT FROM AUTHOR]

This paper addresses the generalized dissipative problem for fuzzy systems with memory sampled-data control. The aim is to devise the memory sampled-data controller such that the considered system is generalized dissipative. By considering the time derivative of the membership functions and some helpful terms, an improved time-dependent Lyapunov-Krasovskii functional (LKF) is constructed to commendably capture the useful information about the real sampling pattern. Together with some new inequalities and the upper bounds of the time derivative of the membership functions, some new criteria are established to guarantee the fuzzy systems to be generalized dissipative. Moreover, the memory sampled-data controller is devised to include delayed state information with the common sampled-data proportional controller as its special case, which can improve the controller performance. Finally, the merits of the proposed results are demonstrated by the truck-trailer system and Rossler's system. [ABSTRACT FROM AUTHOR]

Object detection is a widely studied task in computer vision. Current methods often focus on images captured from appropriate viewpoints. However, there is a large disparity between objects observed from different viewpoints in the real world. Dynamic Object Detection (DOD) method automatically adjusts the camera viewpoint in a visual scene to sequentially find optimal viewpoints. Currently, the DOD tasks are usually modeled as a sequential decision-making problem and solved using reinforcement learning methods. Existing approaches face challenges with sparse rewards and training instability. To tackle these issues, we proposed a single-step reward function and a lightweight network, respectively. The single-step reward function, which provides timely feedback, gives an efficient training process for DOD tasks. The lightweight network with few parameters can ensure the stability of the training process. To evaluate the effectiveness of our method, we developed a simulation dataset based on UE4, which consists of 1800 training images and 450 testing images. The dataset includes five object categories: vans, cars, trailers, box trucks and SUVs. Experiments demonstrate that our method outperforms SOTA object detectors on our simulation dataset. Specifically, the average precisions(APs) are improved from 89.1% to 96.0% when using the YOLOv8 object detector. [ABSTRACT FROM AUTHOR]

Purpose: Realistic composite vehicles with 2, 3, 5 and 9 axles, consisting of a truck with one or two trailers, are addressed in this paper by computational models for vehicle–bridge interaction analysis. Design/methodology/approach: The vehicle–bridge interaction (VBI) models are formed by sets of 2-D rigid blocks interconnected by mass, damping and stiffness elements to simulate their suspension system. The passage of the vehicles is performed at different speeds. Several rolling surface profiles are admitted, considering the maintenance grade of the pavement. The spectral density functions are generated from an experimental database to form the longitudinal surface irregularity profiles. A computational code written in Phyton based on the finite element method was developed considering the Euler–Bernoulli beam model. Findings: Several models of composite heavy vehicles are presented as manufactured and currently travel on major roads. Dynamic amplification factors are presented for each type of composite vehicle. Research limitations/implications: The VBI models for compound heavy vehicles are 2-D. Social implications: This work contributes to improving the safety and lifetime of the bridges, as well as the stability and comfort of the vehicles when passing over a bridge. Originality/value: The structural response of the bridge is affected by the type and size of the compound vehicles, their speed and the conservative grade of the pavement. Moreover, one axle produces vibrations that can be superposed by the vibrations of the other axles. This effect can generate not usual dynamic responses. [ABSTRACT FROM AUTHOR]

To plan the postal deliveries of our industry partner DHL Group (DHL), the single truck and trailer routing problem with satellite depots (STTRPSD) is solved to optimize mail carriers routes. In this application context, instances feature a high number of customers and satellites, and they are based on real street networks. This motivates the study of the asymmetric STTRPSD (ASTTRPSD). The heuristic solution methods proposed in the literature for the STTRPSD can either solve only the symmetric problem variant, or it is unclear whether they can also be used to solve the ASTTRPSD. We introduce an iterated local search, called ILS‐ASTTRPSD, which generates different first‐level tours in the perturbation phase, and improves the second‐level tours in the local search phase. To speed up the search, granular neighborhoods are used. The computational results on instances from the literature prove the capability of ILS‐ASTTRPSD to return high‐quality solutions. On DHL instances, ILS‐ASTTRPSD significantly decreases total travel times of the mail carriers and returns solutions with a different structure compared to the ones provided by DHL. Based on these differences, we give recommendations on how DHL could design more efficient mail carrier practices. Dedicated computational experiments reveal that considering parking and loading times when solving the ASTTRPSD leads to lower travel times, and that ignoring parking times is more counterproductive than ignoring loading times. Moreover, we assess the robustness of our solutions under parking time fluctuations. Finally, we derive properties of instances for which optimal solutions contain multiple second‐level tours rooted at the same parking spot and for which the optimal solutions of the ASTTRPSD correspond to the ones of a pure traveling salesman problem. [ABSTRACT FROM AUTHOR]

In this contribution, a simulation chain for the thermo-mechanical and hydromechanical analysis (surface drainage) of a pavement structure during its whole service life is applied to a typical asphalt pavement (Bk100) used for motorways in Germany. Transient load signals for each tyre position of a truck-trailer combination (vehicle) are generated from a multibody analysis of the vehicle driving on a motorway with rough pavement surface. Material model parameters are derived from experimental identification tests of asphalt materials. The model parameters are used together with a continuum-mechanical description of the asphalt material representing the thermo-mechanical material behaviour at the material scale. The material response of the pavement layers is integrated on the structural scale by using the finite element method (FEM) in combination with an arbitrary Lagrangian-Eulerian (ALE) formulation and equivalent tyre loads of a representative, finite element (FE) discretised truck tyre rolling on an FE discretised pavement section. Different scenarios of rut formation are computed by varying different influence factors (climate temperature, vertical tyre force, type of asphalt material of the surface layers etc.). During the subsequent hydromechanical analysis of the pavement, the simulated deformed geometry of the pavement surface is used to numerically compute surface drainage characteristics. [ABSTRACT FROM AUTHOR]

Camera-based mirror systems (CBMSs) are a relatively new technology in the automotive industry, and much of the United States' medium- and heavy-duty commercial fleet has been reluctant to convert from standard glass, or "west coast", mirrors to CBMSs. CBMSs have the potential to reduce the number of truck and passenger vehicle incidents, improving overall fleet safety. CBMSs also have the potential to improve operational efficiency by improving aerodynamics and reducing drag, resulting in better fuel economy, and improving maneuverability. Improvements in overall safety are also possible; the field of view for the driver is potentially 360° with the addition of trailer cameras, allowing for visibility of the rear of the trailer and the front of the truck. These potential improvements seem promising, but the literature on driver surveys clearly shows that there is reluctance to adopt this technology for many reasons. Additionally, more robust testing in the laboratory and in the field is necessary to determine whether CBMSs are adequate to replace standard mirrors on trucks. This analysis provides an overview of key research questions for CBMS testing based on the current literature on the topic (surveys, standards, and previous testing). The purpose of this analysis is to serve as guidance in developing further testing of CBMSs, especially testing involving human subjects. [ABSTRACT FROM AUTHOR]

In the past few years, there has been a growing interest among researchers in developing control systems for autonomous vehicles, specifically for tractor-trailer systems. This newfound interest is driven by the potential benefits of enhancing safety, reducing costs, and addressing labor shortages in the industry. Two industries that could reap the rewards of these systems' advancements are cargo and agriculture transportation. One of the challenging tasks for the truck trailer vehicle is driving in reverse. Backward path tracking of tractor-trailers is a complex control problem with practical applications. The difficulty in controlling the vehicle arises due to its unstable internal dynamics, coupled nonlinear terms, and the under-actuated nature of the system. There is also a limit to the angle at which the steering can be turned before the risk of a jackknife accident increases significantly. In response to these challenges, this paper introduces a robust sliding mode controller designed for path tracking in reverse-driving tractor-trailer systems. The novelty of our work lies in addressing these challenges, which have not been extensively studied in the past. The proposed controller is analyzed, and its performance is tested and verified using different scenarios. The simulation examples show superior control performance, and we anticipate that this novel controller holds the potential to be widely adopted as a fundamental component in the path-tracking algorithms of autonomous truck trailer systems. [ABSTRACT FROM AUTHOR]

This paper assesses the transport system of Addis Ababa, Ethiopia, taking factors such as the number of vehicles, roadway width, speed of vehicles, longitudinal grade, and proportion of both fuel and electrical vehicles by dividing vehicles into seven classes, namely, car, minibus, small bus, coach, small truck, heavy truck, and truck trailer, to determine CO2 emission, CO emission fuel consumption, and electric consumption in addition to the percent to replace ICE vehicles. After selecting eight representative road sections in Addis Ababa city, input data was collected from both primary and secondary sources. Simulation of urban mobility (SUMO) is used to model the existing road transport system and two other scenarios, cases being 20% and 40% replacement of internal combustion engine vehicles by electric vehicles. Among the vehicle types studied under this paper, the SUMO results show that coaches are with the highest CO2 emission, releasing an average amount of 28.442 grams of CO2 every time step, while cars are with the lowest CO2 emission value of 6.542 grams. Minibuses are the top CO emitters, releasing an average of 0.420 grams of CO every time step, and truck trailers emit the smallest CO emission, 0.025 grams. Regarding electric consumption, the truck trailer is the vehicle type with the highest electric consumption, with a value of 2.282 kwh (watthour) consumption every time step, and cars are the least electricity-consuming vehicles, with a value of 0.151 kwh. The fourth point is fuel consumption; besides the high CO2 emission, coaches' consumption of fuel is leading by 8.946 grams, and cars use 2.087 grams of fuel every time step. Totally, public transport vehicles are responsible for higher emissions and huge fuel consumption. Therefore, if our transport system encourages the penetration of electric vehicles into the road transport system, a healthy and energy-efficient environment is reserved. Again, from a financial and environmental standpoint, the replacement of 40% of ICE vehicles by EVs enhances us with reduced costs and a green environment. [ABSTRACT FROM AUTHOR]

This work studies the H ∞ performance of T-S fuzzy networked control systems under denial-of-service (DoS) attacks. First, the weight coefficient is introduced to measure the damage to the control signal caused by DoS attacks. Then, novel looped Lyapunov-Krasovskii functions are constructed based on the fuzzy membership function, and the nonlinear problem of the system is considered under the premise of reducing the initial condition constraints. Next, the issue of finding the suitable sampling period is transformed into an optimization problem of finding the optimal sampling period to reduce sampling times. An intelligent sampling controller is designed to ensure the asymptotic stability of the system. Finally, the effectiveness of the proposed method is verified with a truck trailer model. [ABSTRACT FROM AUTHOR]