Search Results (160)

To meet the requirements of the high spatiotemporal three-dimensional (3D) airflow field within the glide path corridor during carrier-based aircraft/unmanned aerial vehicles (UAVs) landings, this paper proposes a prediction method for high spatiotemporal resolution 3D ship airwake along the glide path by integrating computational fluid dynamics (CFD), backpropagation (BP) neural network, and Doppler wind lidar (DWL). Firstly, taking the conceptual design aircraft carrier model as the research object, CFD numerical simulations of the ship airwake within the glide path region are carried out using the Poly-Hexcore grid and the detached eddy simulation (DES)/the Reynolds-averaged Navier–Stokes (RANS) turbulence models. Then, using the high spatial resolution ship airwake along the glide path obtained from steady RANS computations under different inflow conditions as a sample dataset, the BP neural network prediction models were trained and optimized. Along the ideal glide path within 200 m behind the stern, the correlation coefficients between the predicted results of the BP neural network and the headwind, crosswind, and vertical wind of the testing samples exceeded 0.95, 0.91, and 0.82, respectively. Finally, using the inflow speed and direction with high temporal resolution from the bow direction obtained by the shipborne DWL as input, the BP prediction models can achieve accurate prediction of the 3D ship airwake along the glide path with high spatiotemporal resolution (3 m, 3 Hz). Full article

In response to the challenges of urbanization, digitalization, and the e-commerce surge intensified by the COVID-19 pandemic, Smart Urban Logistics (SUL) has become a key framework for addressing last-mile delivery issues, congestion, and environmental impacts. This study introduces a System Dynamics (SD)-based approach to investigate how urban logistics and access management policies may interact. At the center, there is a Causal Loop Diagram (CLD) that illustrates dynamic interdependencies among fleet composition, access regulations, logistics productivity, and environmental externalities. The CLD is a conceptual basis for future stock-and-flow simulations to support data-driven decision-making. The approach highlights the importance of route optimization, dynamic access control, and smart parking management systems as strategic tools, increasingly enabled by Industry 4.0 technologies, such as IoT, big data analytics, AI, and cyber-physical systems, which support real-time monitoring and adaptive planning. In alignment with the Industry 5.0 paradigm, this technological integration is paired with social and environmental sustainability goals. The study also emphasizes public–private collaboration in designing access policies and promoting alternative fuel vehicle adoption, supported by specific incentives. These coordinated efforts contribute to achieving the objectives of the 2030 Agenda, fostering a cleaner, more efficient, and inclusive urban logistics ecosystem. Full article

Despite decades of development, micro air vehicles (MAVs) still face challenges related to endurance. While solar power has been successfully implemented in larger aircraft as a clean and renewable source of energy, its adaptation to MAVs presents unique challenges due to payload constraints and complex surface geometries. To address this, this work proposes an automated algorithm for optimal solar panel arrangement on complex upper surfaces of the MAV. In addition to that, the aerodynamic performance is evaluated through computational fluid dynamics (CFD) simulations based on the Reynolds-Averaged Navier–Stokes (RANS) method. A multi-objective optimization approach simultaneously considers photovoltaic energy generation and aerodynamic efficiency. Wind tunnel validation and stability analysis of flight dynamics confirm the advantages of our optimized design. To our knowledge, this represents the first systematic framework for the energy–aerodynamic co-optimization of solar-powered MAVs (SMAVs). Flight tests of a $500\mathrm{mm}$-span tailless prototype demonstrate the practical feasibility of our approach with maximum solar cell deployment. Full article

Wingtip devices like winglets and other types have been created to improve the aerodynamic efficiency of aircraft based on minimizing the induced drag of tip vortices. This study aims to investigate the aerodynamic characteristics of these devices at low Reynolds numbers. In the present study, the models of a basic non-swept tapered wing and a wing with arc-shaped wingtips are examined. For this purpose, the basic model is equipped with replaceable tips with different geometries. The measurements are performed in a low-speed wind tunnel at a Reynolds number of around 100,000. The analysis of the collected data shows that the best aerodynamic characteristics have a configuration with a 45-degree dihedral angle at the tips of the wing. These results can be used in the conceptual design of small unmanned aerial vehicles (UAVs) to improve their performance in terms of range and endurance. Full article

Passengers’ trust in Shared Autonomous Vehicles (SAVs) can be affected by different factors, such as their attitudes toward new technologies and perceptions of the vehicles’ reputation. While the existing literature has begun to explore these issues, there is limited research investigating how industrial design in SAVs can enhance passengers’ trust levels. To address this gap, this study responds to the central question: How can passengers’ trust in the vehicle itself and in fellow passengers be enhanced through design intervention? This question conceptualises trust in the vehicle and trust in strangers as an integrated trust issue within the SAV context. To fill this gap, this study adopts a project-grounded methodology. The design work is guided by five trust principles: anthropomorphic design, a defensible space, system transparency, personalisation features, and a restorative environment. Drawing on insights from an auto-ethnography of current ride-sharing services, these principles are further explored and applied to identify design opportunities for both the physical and digital elements of SAVs. The final conceptual SAV design demonstrates how different design elements can be orchestrated to engender user trust. The outcome contributes to ongoing design practices and helps researchers and designers better understand trust design for SAVs. Full article

Traffic safety assessments rely on Surrogate Safety Measures (SSMs), yet their diversity hinders understanding and selection. This paper proposes a novel conceptual framework to systematically categorize SSMs through what we term Motion Scenario Mapping, an approach inspired by queuing theory notation and the concept of short-term behavioral storytelling. The framework explicitly defines interaction stories between a following and leading vehicle to reveal hidden assumptions within each SSM, achieved through a combined coding system. Examining ten common SSMs, the research demonstrates that the framework effectively exposes underlying assumptions, enabling critical evaluation of their contextual validity. By emphasizing short-term risk dynamics, this approach offers a structured understanding of interaction mechanisms and provides a systematic foundation for comparing existing SSMs, identifying research gaps, and guiding future development. This structured ontology has the potential to enhance the analysis and design of safety measures for future transportation systems. Full article

Few studies have examined Hybrid Aquatic–Aerial Vehicles (HAAVs), autonomous vehicles designed to operate in both air and water, especially those that are aircraft-launched and recovered, with a variable-sweep design to free dive into a body of water and breach under buoyant and propulsive force to re-achieve flight. The novel design research examines the viability of a recoverable sonar-search child aircraft for maritime patrol, one which can overcome the prohibitive sea state limitations of all current HAAV designs in the research literature. This paper reports on the analysis from computational fluid dynamic (CFD) simulations of such an HAAV diving into static seawater at low speeds due to the reverse thrust of two retractable electric-ducted fans (EDFs) and its subsequent breach back into flight initially using a fast buoyancy engine developed for deep-sea research vessels. The HAAV model entered the water column at speeds around 10 ms⁻¹ and exited at 5 ms⁻¹ under various buoyancy cases, normal to the surface. Results revealed that impact force magnitudes varied with entry speed and were more acute according to vehicle mass, while a sufficient portion of the fuselage was able to clear typical wave heights during its breach for its EDF propulsors and wings to protract unhindered. Examining the medium transition dynamics of such a novel HAAV has provided insight into the structural, propulsive, buoyancy, and control requirements for future conceptual design iterations. Research is now focused on validating these unperturbed CFD dive and breach cases with pool experiments before then parametrically and numerically examining the effects of realistic ocean sea states. Full article

The vertical-takeoff–horizontal-landing (VTHL) two-stage-to-orbit (TSTO) system is a kind of novel launch vehicle in which a reusable first stage can take off vertically like a rocket and land horizontally like an airplane. The advantage of the VTHL TSTO vehicle is that the launch costs can be reduced significantly due to its reusable first stage. This paper presents an application of multidisciplinary analysis optimization on preliminary sizing in conceptual design of the VTHL TSTO vehicle. The VTHL TSTO concept is evaluated by multidisciplinary analysis, including geometry, propulsion, aerodynamics, mass, trajectory, and static stability. The preliminary sizing of the VTHL TSTO vehicle is formulated as a multidisciplinary optimization problem. The focus of this paper is to investigate the impacts of the first-stage reusability and propellant selection on the staging altitude and velocity, size, and mass of the VTHL TSTO vehicles. The observations from the results show that the velocity and altitude of the optimal staging point are determined mainly by the reusability of the first stage, which in turn affects the size and mass of the upper stage and the first stage. The first stage powered by hydrocarbon fuel has a lower dry mass compared with that powered by liquid hydrogen. Full article

The rapid evolution of military technology has led to an increased interest in Unmanned Combat Aerial Vehicles (UCAVs). This research focuses on the conceptual design of a low-cost, turbofan-powered UCAV, specifically a Class-III aircraft as defined by NATO classification (STANAG 4670), with a target take-off weight of approximately one tonne. The study adopts a “from scratch” design approach, recognizing the limitations of existing data and the potential for scaling errors. This approach involves a meticulous design process that includes the development of precise requirements, weight estimations, and iterative optimization of the aircraft layout to ensure aerodynamic efficiency and operational functionality. A key element of this conceptual design is its focus on a low-cost profile, achieved through the adoption of a simplified structural layout, and the integration of off-the-shelf components where possible. The design process involves an iterative approach, beginning with fundamental requirements and progressing through the detailed development of individual components and their integration into a cohesive aircraft. The study details the selection of an existing and operational engine due to its power output. The design and analysis of the wing, fuselage, and V-tail configuration are presented, incorporating considerations for aerodynamic efficiency, stability, weight estimation, and internal component layout. The study concludes by outlining recommendations for future work, including high-fidelity CFD simulations, structural analysis, and the integration of advanced electronic systems and AI capabilities essential for the Loyal Wingman concept. Full article

The variable camber wing (VCW) is a morphing wing design anticipated to enhance unmanned aerial vehicles’ (UAVs’) performance in flight through continuously changing shape. The performance of VCWs has been proven, but techniques for their integration, including aerodynamic analysis, mechanism synthesis, and structural tests, still lag in development at the conceptual design stage. Therefore, this research focuses on designing a variable camber wing, a key area for the advancement of morphing aircraft. Inspired by the high-lift capabilities of traditional aircraft devices but aiming for smoother airflow through continuous shape alteration, this research proposes a novel three-step design for a structurally integrated VCW. This approach begins with a critical aerodynamic analysis to determine wing shape adaptations across various flight conditions, followed by a mechanism synthesis phase to design a four-bar linkage that accurately approximates the desired trailing edge deflections by utilizing a variant of teaching–learning-based optimization. The objective is to minimize error between the intended and actual coupler link while adhering to design constraints for proper integration in the wing structure. Finally, structural analysis evaluates the skin’s ability to withstand operational loads and ensure the integrity of the VCW system. The design result demonstrates the success of this three-step approach to synthesizing a VCW mechanism that meets the defined aerodynamic (actual deflection of 9.1764°) and structural targets (maximum Von Mises stress of 81.5 MPa and maximum deflection of 0.073 m), paving the way for enhanced aircraft performance. Full article

This paper presents a microsimulation-driven framework to analyze the performance of connected and automated vehicles (CAVs) alongside vehicles with human drivers (VHDs), channeled towards assessing project alternatives in road intersection design. The transition to fully automated mobility is driving the development of new intersection geometries and traffic configurations, influenced by increasing market entry rates (MERs) for CAVs (CAV-MERs), which were analyzed in a microsimulation environment. A suburban signalized intersection from the Polish road network was selected as a representative case study. Two alternative design hypotheses regarding the intersection’s geometric configurations were proposed. The Aimsun micro-simulator was used to hone the driving model parameters by calibrating the simulated data with reference capacity functions (RCFs) based on CAV factors derived from the Highway Capacity Manual 2022. Cross-referencing the conceptualized geometric design solutions, including a two-lane roundabout and an innovative knee-turbo roundabout, allowed the experimental results to demonstrate that CAV operation is influenced by the intersection layout and CAV-MERs. The research provides an overview of potential future traffic settings featuring CAVs and VHDs operating within various intersection designs. Additionally, the findings can support project proposals for the geometric and functional design of intersections by highlighting the potential benefits expected from smart driving. Full article

This paper establishes an analytical model for component mass, takeoff weight, and performance constraints of distributed electric propulsion (DEP) propeller-driven short takeoff and landing (STOL) unmanned aerial vehicles (UAV), and develops a conceptual design method considering propulsive/aerodynamic coupling effects. The proposed approach was applied to design a 350 kilogram-class DEP UAV with STOL capability, verifying the feasibility and effectiveness of the design method. To investigate the layout design and propulsive/aerodynamic coupling characteristics of DEP UAV, three UAV configurations with different DEP arrangements are formulated and studied, and the results indicate that the flap deflection significantly increases the lift coefficient of the UAV during takeoff, and under the same total thrust and power conditions, the lift-enhancement using DEP arrangement is more significant. In addition, it is necessary to fully consider the propulsive/aerodynamic coupling effects in the conceptual design process, and this is of great significance for the future development of DEP STOL UAV. Full article

With the rapid expansion of the Electric Sport Utility Vehicle (ESUV) market, capturing consumer aesthetic preferences and emotional needs through front-end styling has become a key issue in automotive design. However, traditional Kansei Engineering (KE) approaches suffer from limited timeliness, subjectivity, and low predictive accuracy when extracting affective vocabulary and modeling the nonlinear relationship between product form and Kansei imagery. To address these challenges, this study proposes an improved KE-based ESUV styling framework that integrates data mining, machine learning, and generative AI. First, real consumer reviews and front-end styling samples are collected via Python-based web scraping. Next, the Biterm Topic Model (BTM) and Analytic Hierarchy Process (AHP) are used to extract representative Kansei vocabulary. Subsequently, the Back Propagation Neural Network (BPNN) and Support Vector Regression (SVR) models are constructed and optimized using the Seagull Optimization Algorithm (SOA) and Particle Swarm Optimization (PSO). Experimental results show that SOA-BPNN achieves superior predictive accuracy. Finally, Stable Diffusion is applied to generate ESUV design schemes, and the optimal model is employed to evaluate their Kansei imagery. The proposed framework offers a systematic and data-driven approach for predicting consumer affective responses in the conceptual styling stage, effectively addressing the limitations of conventional experience-based design. Thus, this study offers both methodological innovation and practical guidance for integrating affective modeling into ESUV styling design. Full article

Hydrogen plays a pivotal role in the decarbonization of the transport sector, necessitating the development of an adequate infrastructure in the form of hydrogen refueling stations (HRSs) to support hydrogen-powered vehicles. This study investigates the characteristics of hydrogen refueling stations to optimize their spatial design and provide key performance indicators for spatial efficiency. An overview of HRS components and their operational requirements is provided, alongside the classification of stations into distinct categories. The primary focus is on analyzing the relationship between station area and capacity. Utilizing spatial data from hydrogen stations, areas are determined through Google Maps analysis. Linear and power regression models are applied to quantify the relationship, with both models proving effective for capturing these dynamics. Based on the findings, spatially efficient design recommendations are proposed, supplemented by examples and a conceptual blueprint for optimized HRS construction, which are then summarized in a morphological design catalog. Full article

This paper introduces a methodology for structural mass optimization of High-Altitude Long Endurance (HALE) aircraft across a complete mission profile, tailored for use in preliminary design. A conceptual HALE vehicle and its mission profile are assumed for this study, which also evaluates the impact of risk-based design decisions on optimized mass. The research incorporates a coupled aeroelastic solver and a mass optimization algorithm based on classical laminate theory to construct a geometrically accurate spar model. A novel approach is proposed to minimize the spar mass of the aircraft throughout the mission profile. This algorithm is applied to a representative T-Tail HALE model to compare optimized mass between two mission profiles differing in turbulence exceedance levels during the ascent and descent mission stages, while maintaining the same design robustness for on-station operation. Sample numerical results reveal a 10.9% reduction in structural mass for the mission profile with lower turbulence robustness design criteria applied for ascent and descent mission phases. The significant mass savings revealed in the optimization framework allow for a trade-off analysis between robustness to turbulence impacts and critical HALE platform parameters such as empty weight. The reduced empty vehicle weight, while beneficial to vehicle performance metrics, may be realized but comes with the added safety of flight risk unless turbulent conditions can be avoided during ascent and descent through risk mitigation strategies employed by operators. The optimization framework developed can be incorporated into system engineering tools that evaluate mission effectiveness, vehicle performance, vehicle risk of loss, and system availability over a desired operating area subject to environmental conditions. Full article