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Abstract Unlike conventional launch vehicles the winged body reusable launch vehicle needs to be tested and evaluated for its functionality during the pre-flight preparation at the runway. The ground based checkout systems for the avionics and actuators performance testing during pre-flight evaluation and actuation are not designed for rapid movement. The new kind of launch vehicle with conventional rocket motor first-stage and winged body upper-stage demands the system testing at Launchpad and at runway. In the developmental flights of the winged body part of the vehicle, the pre-flight testing needs to be carried out extensively at runway. The safety protocol forbids the permanent structure for hosting the checkout system near runway. The alternative is the development of a rapidly deployable and removable checkout system. A design methodology adopting conventional industrial instrumentation systems and maintaining mobility is presented.

Advanced Air Mobility (AAM) envisions heterogenous airborne entities like crewed and uncrewed passenger and cargo vehicles within, and between urban and rural environment. To achieve this, a paradigm shift to a cooperative operating environment similar to Extensible Traffic Management (xTM) is needed. This requires the blending of Traditional Air Traffic Services (ATS) with the new generation AAM vehicles having their unique flight dynamics and handling characteristics. A hybrid environment needs to be established with enhanced shared situational awareness for all stakeholders, enabling equitable airspace access, minimizing risk, optimized airspace use, and providing flexible and adaptable airspace rules. This paper introduces a novel concept of distributed airspace management which would be apt for all kinds of operational scenarios perceived for AAM. The proposal is centered around the efficiency and safety in air space management being achieved by self-discipline.

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Autonomous driving technology is more and more important nowadays, it has been changing the living style of our society. As for autonomous driving planning and control, vehicle dynamics has strong nonlinearity and uncertainty, so vehicle dynamics and control is one of the most challenging parts. At present, many kinds of specific vehicle dynamics models have been proposed, this review attempts to give an overview of the state of the art of vehicle dynamics models for autonomous driving. Firstly, this review starts from the simple geometric model, vehicle kinematics model, dynamic bicycle model, double-track vehicle model and multi degree of freedom (DOF) dynamics model, and discusses the specific use of these classical models for autonomous driving state estimation, trajectory prediction, motion planning, motion control and so on.

Under complex and extreme operating conditions, the road adhesion coefficient emerges as a critical state parameter for tire force analysis and vehicle dynamics control. In contrast to model-based estimation methods, intelligent tire technology enables the real-time feedback of tire-road interaction information to the vehicle control system. This paper proposes an approach that integrates intelligent tire systems with machine learning to acquire precise road adhesion coefficients for vehicles. Firstly, taking into account the driving conditions, sensor selection is conducted to develop an intelligent tire hardware acquisition system based on MEMS (Micro-Electro-Mechanical Systems) three-axis acceleration sensors, utilizing a simplified hardware structure and wireless transmission mode. Secondly, through the collection of real vehicle experiment data on different road surfaces, a dataset is gathered for machine learning training.

When the aircraft towing operations are carried out in narrow areas such as the hangars or parking aprons, it has a high safety risk for aircraft that the wingtips may collide with the surrounding aircraft or the airport facility. A real-time trajectory prediction method for the towbarless aircraft taxiing system (TLATS) is proposed to evaluate the collision risk based on image recognition. The Yolov7 module is utilized to detect objects and extract the corresponding features. By obtaining information about the configuration of the airplane wing and obstacles in a narrow region, a Long Short-Term Memory (LSTM) encoder-decoder model is utilized to predict future motion trends. In addition, a video dataset containing the motions of various airplane wings in real traction scenarios is constructed for training and testing.

Compared with urban areas, the road surface in mountainous areas generally has a larger slope, larger curvature and narrower width, and the vehicle may roll over and other dangers on such a road. In the case of limited driver information, if the two cars on the mountain road approach fast, it is very likely to occur road blockage or even collision. Multi-vehicle cooperative control technology can integrate the driving data of nearby vehicles, expand the perception range of vehicles, assist driving through multi-objective optimization algorithm, and improve the driving safety and traffic system reliability. Most existing studies on cooperative control of multiple vehicles is mainly focused on urban areas with stable environment, while ignoring complex conditions in mountainous areas and the influence of driver status. In this study, a digital twin based multi-vehicle cooperative warning system was proposed to improve the safety of multiple vehicles on mountain roads.

The study emphasizes transitioning school buses from diesel to electric to mitigate their environmental impact, addressing challenges like limited driving range through predictive models. This research introduces a comprehensive control-oriented model for estimating auxiliary loads in electric school buses. It begins by developing a transient thermal model capturing cabin behavior, divided into passenger and driver zones. Integrated with a control-oriented HVAC model, it estimates heating and cooling loads for desired cabin temperatures under various conditions. Real-world operational data from school bus specifications enhance the model’s practicality. The models are calibrated using experimental cabin-HVAC data, resulting in a remarkable overall Root Mean Square Error (RMSE) of 2.35°C and 1.88°C between experimental and simulated cabin temperatures.

Currently, the rapid expansion of the global road transport industry and the imperative to reduce carbon emissions are propelling the advancement of electrified highways (EH). In order to conduct a comprehensive economic analysis of EH, it is crucial to develop a detailed /8.and comprehensive economic model that takes into account various transportation modes and factors that influence the economy. However, the existing economic models for EH lack comprehensiveness in terms of considering different transportation modes and economic factors. This study aims to fill this gap by designing an economic model for an EH-based Online DC-driven system (ODS) for long distance heavy-duty transport vehicle incorporating multi-factor sensitivities. Firstly, the performance parameters of the key components of the system are calculated using vehicle dynamics equations which involves selecting and matching the relevant components and determining the fundamental cost of vehicle transformation.

This document includes recommendations of installations of adequate landing and taxiing lighting systems in aircraft of the following categories: a Single engine personal and/or liaison type b Light twin engine c Large multiengine propeller d Large multiengine turbojet e Military high-performance fighter and attack f Helicopter g Electric Vertical Takeoff and Landing (EVTOL) and Urban Air Mobility (UAM)

This specification covers a runway deicing and anti-icing product in the form of a solid. Unless otherwise stated, all specifications referenced herein are latest (current) revision.

This specification covers runway deicing and anti-icing products in the form of a liquid. Unless otherwise stated, all specifications referenced herein are latest (current) revision.

In numerous industries such as aerospace and energy, components must perform under significant extreme environments. This imposes stringent requirements on the accuracy with which these components are manufactured and assembled. One such example is the positional tolerance of drilled holes for close clearance applications, as seen in the “EN3201:2008 Aerospace Series – Holes for metric fasteners” standard. In such applications, the drilled holes must be accurate to within ±0.1 mm. Traditionally, this required the use of Computerised Numerical Control (CNC) systems to achieve such tight tolerances. However, with the increasing popularity of robotic arms in machining applications, as well as their relatively lower cost compared to CNC systems, it becomes necessary to assess the ability of robotic arms to achieve such tolerances. This review paper discusses the sources of errors in robotic arm drilling and reviews the current techniques for improving its accuracy.

This document focuses on the latest in-force regulations. However, in addition to latest information, the report may include historical information. As regulations are superseded, the previous entry will remain to help understand the change in requirements over time. The initial focus of the document includes light-, medium-, and heavy-duty on-road vehicles with all propulsion systems. The document will include information from the United States and Canada, with later publications expanding to other regions. Forecasts for future regulations will not be included in the spreadsheet but be kept in a separate document. The document may be expanded to other types of applications/vehicles as information becomes available.

Tyre wear is of significant concern for the automotive industry due to multiple reasons including vehicle performance, safety, economy, environmental (particulate matter emission) aspects, etc. Therefore, ensuring enhanced tyre tread wear resistance is one of the most important criteria while developing a new tyre. Tyre wear phenomenon is influenced by various factors, such as road conditions, driving habits, maintenance practices and tyre design parameters (construction, geometry and material). The wear assessment through the classical field-testing approach consumes significant time and resources. Therefore, digital predictive tools are very useful in predicting wear characteristics at the early stage of the tyre development process. In this study, an attempt has been made to capture the impact of tread geometry, tread material, vehicle geometry, vehicle speed, test track geometry, etc. on tyre wear.