Design methods for mobility

This vision paper presents a prospective architecture for the phased deployment of intelligent and connected vehicle (ICV) systems under mixed traffic conditions. We propose a Vehicle–Road–Cloud–Human (VRCH) integrated architecture to address key technical and socio-technical challenges in autonomous mobility, including edge-case handling, behavioral predictability, and infrastructure compatibility. The architecture reallocates decision-making across distributed roadside infrastructure and cloud services to reduce vehicle-side burden, while ensuringsafety, efficiency and user trust. A phased deployment roadmap for Dedicated Autonomous Lanes (DALs) is introduced, featuring digitally credentialed access, in-transit transition mechanisms (ITTM). Emphasizing human-machine interaction during mode transitions, the framework supports scalable, cost-effective deployment without capital-intensive infrastructure overhaul. Future work includes pilot zone deployment, infrastructure co-design, and scenario-based validation to support the evolution to realize a robust, human-centered intelligent transport systems (ITS) ecosystem.

Keywords: 5G-V2X , Dedicated Autonomous Lanes , Human Factors in Automation , Human–Machine Interaction (HMI) , Intelligent transport systems (ITS) , Intelligent Transportation Infrastructure , Mobility System Design , Urban Autonomy , Vehicle–Road–Cloud–Human (VRCH) Architecture

The aerospace industry requires an extensive phase of testing, validation, and certification of components and systems. To support those activities, large testing machines are necessary to test full-scale components. The design and installation of such machines can be challenging because of their large dimensions. The SpaceLab project requires designing and manufacturing a machine to simulate the pyroshock capable of simulating the loads acting on payloads during the detaching of rocket stages using explosive bolts. Moreover, a machine is under development to simulate the outgassing of materials in space. To support the design and installation, an Augmented Reality-based tool has been developed to overlay a CAD model of a testing machine in the external environment. A case study has been implemented to show how the tool can support the design and installation activities. The tool has been applied in the field, and good usability, flexibility, and situational awareness results have been noticed.

Keywords: Aerospace , Augmented Reality , Testing machines

The droop-nose leading-edge morphing wing offers promising potential for reducing aerodynamic drag and noise during take-off and landing, thereby helping to lower aircraft fuel consumption and align with greener aviation goals outlined in Flightpath 2050 by the EU and ICAO declarations. Despite technological challenges and current technology readiness levels (TRL), droop-nose leading-edge (DNLE) wings are primarily tested and evaluated in unmanned aerial systems to reduce costs and risks. The literature proposes various optimisation methods for airfoil skin and morphing mechanisms; however, additional research contributions are needed to develop an effective design methodology. High actuator forces required for morphing, the trade-off between skin flexibility and load-bearing capacity, and the difficulty of obtaining smooth and continuous airfoil deformations are still under investigation. The present research introduces an optimisation methodology tailored for DNLE composite laminate skin and morphing mechanism structures. Its application to the UAS-S45 unmanned vehicle is utilised as a case study. Applying this design and optimisation methodology can lead to an 88% reduction in actuator mechanism force for a DNLE optimised for 6° angle-of-attack, considering an airfoil. This approach significantly enhances airfoil shape smoothness across sections and spanwise direction during morphing conditions. The proposed approach reduces the computational effort, as non-linear finite element method (FEM) analyses are not required within the optimisation loop, except at selected verification stages. A mechanism prototype was constructed to validate the FEM analyses and understand the limits of the simulation. Further investigations are required to achieve a morphing shape closer to aerodynamically optimised shapes.

Keywords: aeronautical design , composite materials , morphing airfoil , structural optimisation

Additive manufacturing technologies enable the realization of complex and free-form geometries that are difficult or impossible to realize with traditional subtractive processes. The development and widespread use of algorithmic optimization methods, including topology and shape optimization, lattice structures, and generative design, accelerate this manufacturing revolution. The redesign of existing parts is a common practice to improve the overall performance of mechanical systems. The practice of designing additive manufacturing components, known as Design for Additive Manufacturing, enables designers to enhance functionality, reduce the number of parts, and minimize the overall weight, thereby obtaining an optimized shape for the analyzed item. This paper proposes a method to support designers in applying optimization techniques for mechanical components. The paper also applies the proposed approach to redesign an automotive suspension arm for a C-segment passenger car. The case study begins with the analysis of a reference part produced using conventional manufacturing and ends with the proposal of a new geometry to be realized by metal 3D printing.

Keywords: Design for Additive Manufacturing , Design Optimization , Shape Optimization , Suspension arm , Topology Optimization

This study presents a genetic algorithm-based methodology for reconstructing the nominal profile of airfoils belonging to the NACA four- and five-digit series. By minimizing the geometric deviations between measured point clouds and parametrically generated airfoil profiles, the algorithm identifies the best-fitting nominal geometry. The approach was implemented using Rhino 8, Grasshopper, and the Galapagos plugin, and validated through extensive testing on 3D-printed samples. Across 200 test runs, the algorithm consistently identified the correct nominal geometry, demonstrating robustness despite inherent stochastic variability and computational challenges. The average number of iterations needed to converge was found to be 953 across all cases. This methodology offers a valuable tool for reverse engineering and metrological applications, providing a parametric and efficient alternative to traditional free-form surface reconstruction.

Keywords: Airfoil Design , Airfoil inspection , Genetic Algorithm , Reverse Engineering

The aerospace industry increasingly relies on digital twins to estimate unmeasured quantities through Virtual Sensing techniques. In this context, this work presents the experimental validation of a computational fluid dynamics (CFD) model of an aluminum wing with a NACA 0018 profile. Wind tunnel measurements were collected at various flow conditions and compared against CFD simulations performed in Simcenter STAR-CCM+. The strong agreement, quantified through pressure distribution comparisons and Normalized Root Mean Square Error (NRMSE), confirms the reliability of the numerical model. Crucially, the validated CFD setup provides the basis for future implementation of Virtual Sensing schemes based on the Augmented Kalman Filter (AKF), enabling the estimation of aerodynamic pressure loads using limited sensor data. This validation step is thus essential to ensure the predictive quality of the digital twin in such Virtual Sensing frameworks for structural monitoring and control.

Keywords: Aerodynamics , CFD , Virtual Sensing , Wind tunnel

The growing need for sustainable mobility is driving the search for solutions to reduce energy waste and harmful environmental emissions. In this context, the design of vehicle lighting presents a promising approach. The use of composite materials, along with the automation of their manufacturing and assembly processes, is increasingly in demand to strike a balance between cost, lightweight, and the required performance of vehicle chassis. Carbon Fiber Sheet Molding Compounds allow complex car body parts to be produced through a one-step compression molding process. Manual labor represents a crucial operation in preparing the compound charge and subsequent manipulation towards compression molding. However, it directly affects productivity. The continuity between the preparation and manipulation phases can be relaxed by implementing robotic solutions to handle the pre-shaped uncured composite charge, automating loading onto the press mold. Efficient robotic handling requires grippers designed to match the shape of the compound charge. Specifically, the gripper must control the deformation of the temporary form of the composite charges, ensuring that the shape deviations stay within acceptable limits for proper fit in the compression mold. This work presents a systematic approach to designing and optimizing robotic grippers to pick up and place deformable compound layers. The key design parameter that guides this method is the maximum distortion threshold, which regulates the process in the two stages. The first stage focuses on finding the optimal balance between the lowest grasping points and acceptable distortion to define the grasping layout. In contrast, the second stage addresses the gripper structure, aiming to create the lightest, yet stiffest frame. The approach is fully integrated into a computer-assisted design platform.

Keywords: CF-SMC , Integrated design , Limp uncured composite geometries , PLM Platform , Robotic Grippers

Directed Energy Deposition (DED) is increasingly utilized for the construction of large components, repair of worn and damaged parts, and integration into Hybrid Manufacturing systems to leverage diverse technological features. A burgeoning application of DED is in Additive Remanufacturing (ARem), by which existing components can be enhanced with additional features and materials to improve functionalities. This paper presents a systematic and integrated approach for Design for Additive Remanufacturing (DARem), focusing on the optimization of product structural requirements to enhance performance and the process design to minimize flaws while ensuring material integrity and expected tolerances. The suggested approach involves product and process design phases within a computer aided design platform. Identification of critical issues in the original product design is the fundamental phase that drives the selection of the appropriate materials and quantities for deposition. Next, topological optimization is employed to shape and position additional volumes, generating enhanced design variants. A simulation phase ends the product design steps, assessing the actual improvement of the component over its original design. Subsequent phases are related to process design assessment. Selection of process parameters and build strategies, and next, the behavioral simulation of deposition are fundamental to verify feasibility and generate paths instructions. Finally, thermomechanical simulation is conducted to estimate the final component state accurately, ensuring it meets functional requirements before proceeding to actual manufacturing pre-processing, material deposition, and post-processing phases. A case study involving an automotive suspension component is used to demonstrate the feasibility of the proposed integrated approach. Experimental phases are performed to define DED material properties for the redesign and investigate the reliable simulation of process-induced distortions. By reducing stress in critical areas through localized deposition of 316L stainless steel alloy using laser powder DED, the study explores the impact of toolpath strategies on process-induced distortions through a Design of Experiments (DoE) approach. The results confirm the feasibility of the deposition process in meeting functional requirements, particularly geometrical tolerances, highlighting the potential of DARem for the redesign and enhancement of existing components.

Keywords: 316L, Remanufacturing , Directed Energy Deposition , Finite Element Method , Product-Process design

The integration of automation into the Compression Molding process for mass production of automotive components using Carbon Fiber Sheet Molding Compound (CF-SMC) represents a significant improvement in the sector. It improves efficiency, precision, and safety while reducing production costs and allowing product customization. A review of current technologies highlights the limitations of manual lay-up and the potential of automated pick-and-place systems to transfer uncured charges from the preform stage to the mold. Needle grippers have emerged as the most suitable solution to minimize the retention time of composite material in the heated mold, reducing the risk of premature curing. This study proposes a validation model to analyze the needle insertion process, which includes the piercing, detachment, transfer, and release phases, with the goal of developing a numerical model capable of accurately replicating real physical behavior. Focusing on the piercing phase, the analytical model identifies key design parameters that correlate the insertion force, the tilt angle, and the geometry of the needle and the CF–SMC. Subsequently, a hybrid FEM–SPH numerical model, known for its suitability to simulate large-deformation problems, was then implemented in Abaqus.

Keywords: Carbon Fiber Sheet Molding Compound (CF-SMC) , Compression molding , Integrated design , Robotic Grippers

Extended Reality (XR) Technologies enable the creation of immersive and interactive environments in which it is possible to safely test products and operational contexts at an early design stage. Such capability makes XR simulations extremely significant for the actual development of innovative modes of transport Urban Air Mobility (UAM). In fact, the implementation of transport of goods and passengers with autonomous and electrical vehicles in urban areas is still in its starting phase and, to efficiently progress, it requires testing, collaboration and visualization between different stakeholders with different needs and backgrounds. Moreover, XR can efficiently support the prediction of the social impact of UAM solutions. Since each UAM mission scenario involves visualizing one or more specific aircraft in a specific environment, there is a need to create a diverse library of 3D scenarios that are ready for simulation and can be tailored as required. These scenarios are based on 3D models of environments and aircraft that must meet complex functional and user requirements. This paper reports on a list of requirements for UAM 3D aircraft models for XR simulations, as well as the process for generating 3D UAM aircraft models to populate a database tailored for UAM XR-based simulations. The proposed four-phase process named identification, screening, tailoring and inclusion, is designed to simplify the modelling workflow, facilitating rapid model reuse and integration in XR environments.

Keywords: Advanced Air Mobility , Urban Air Mobility , XR Extended Reality

This study aims to gather a sustainable understanding of additive manufacturing and other Manufacturing 4.0 approaches like horizontal and vertical integration and cloud computing techniques with a focus on industrial applications. The DfAM will apply 4.0 tools to gather product feasibility and execution, with CAE—FEM analysis and CAM. This publication focuses on the redesign of a vehicle suspension arm. The main objective is to apply innovative design techniques that optimize component performance while minimizing cost and time. The IDeS method and TRIZ methodology were used, resulting in a composite element, aiming to make the FDM-sourced process a viable option, with a weight reduction of more than 80%, with less material consumption and, hence, less vehicle energy consumption. The part obtained is holistically sustainable as it was obtained by reducing the overall labor used and material/scrap generated, and the IDES data sharing minimized rework and optimized the overall production time.

Keywords: additive manufacturing , IDeS , product design , product reverse engineering , TRIZ

Road safety is still a critical concern for all countries of the world since most of the reports state that traffic fatalities remain very high. Despite the reduction of fatal situations while driving, traffic collisions, especially due to unsafe behaviors, are the leading cause of death among young individuals. Governments use safety campaigns to promote safer driving, but traditional methods such as videos conveyed through 2D screens may have a limited impact. Cinematic Virtual Reality (CVR), with its immersive features, could offer a more effective way to deliver road safety messages. This study proposes a between-subject design to explore how CVR influences attitudes, behaviors, and physiological responses related to traffic safety. A sample of 95 young participants, split into two groups, watched either a fear-based or a positive-based 360° CVR video. They completed the Attitudes Towards Traffic Safety (ATTS) and Driving Behavior Questionnaire (DBQ) at different stages (before and after CVR experience and in follow-up condition), as well as a User Experience Questionnaire (UEQ) and a Virtual Reality Sickness Questionnaire (VRSQ). ECG data were collected during the CVR experience to assess physiological response. The results demonstrate that CVR significantly impacts safety attitudes and behavior, with a statistically stronger effect observed in the fear-based approach. Furthermore, CVR markedly impacts users' physiological responses, as evidenced by ECG analysis. Physiological data underscore CVR's effectiveness in engaging users and reveal that responses vary significantly based on the nature of the immersive experience, highlighting CVR's potential as a targeted intervention tool for traffic safety education.

Keywords: Cinematic virtual reality , Educational intervention , Physiological response , Risky driving , Road safety , Young drivers

In an era where aviation systems face mounting complexity and heightened performance demands, traditional design methods often underperform in capturing the full spectrum of stakeholders' value. This paper introduces the Value Enhancement Methodology, a novel and structured framework aimed at embedding value-driven decision-making into the development of complex systems. The methodology was applied to evaluate a ground anti-collision system within the OPTIMATE project, with a focus on airline companies as key stakeholders. Using operational data from U.S. and Australian databases, the number of mitigable taxi-phase events was quantified. Findings indicate that the safety-related benefits are limited, especially in relation to the significant investment and procedural adaptation required for implementation. Conversely, other values, such as Profitability, Operability, and Sustainability may present more persuasive incentives for adoption. These results emphasize the importance of a multi-dimensional, stakeholder-centered evaluation approach when assessing technological innovations in aviation, particularly within an increasingly constrained and competitive industry landscape.

Keywords: Aeronautics , Design methodology , Product development process (PDP) , Systems engineering (SE) , Value driven design (VDD)

This study presents a simulation-based optimization of the upper control arm in a transverse push-rod suspension system for a Formula SAE vehicle. The design process centers on the parametric variation of the three critical connection points that define the arm's geometry, resulting in a nine-variable configuration space. By systematically exploring this space through a Design of Experiments (DOE) framework, a Response Surface Methodology (RSM) is applied to both identify optimal geometries and assess the sensitivity of component behavior to each variable. Mechanical simulations under various dynamic conditions, such as braking, acceleration, and cornering, provide the performance data used in statistical modeling. The approach enables early-stage prediction of structural response, guiding CAD development and physical prototyping while significantly reducing trial-and-error iterations. Beyond optimization, this work offers insight into the relative influence of design parameters, supporting more informed and resource-efficient decision-making in the suspension design workflow in an early stage of product development, even before CAD prototyping.

Keywords: DOE , RSM , Suspension Geometry Optimization , Sustainable Design , Vehicle Design , Virtual Prototyping

The maritime industry is looking for ways to decarbonize rapidly through design strategies, and technologies, also developing solutions for eco-friendly boating. The hydrofoil technology is one of the most promising due to its high efficiency compared to traditional planing or displacing vessels. The research was focused on the development of a systematic design method for fully submerged hydrofoil wing system with a longitudinal flight control. Starting from a reference hull model, five alternative wing configurations were designed based on geometric, hydrodynamic, and dynamic criteria. A preliminary hydrodynamic model was developed to determine the dimensions and positions of the wing systems in five different configurations. The equations of the motion were numerically implemented, and a longitudinal double PID flight control for the wing systems was developed. The configurations were designed benefiting from a parametric CAD model and simulated through transient CFD analysis at different speeds. In terms of drag, the lowest values were found for R4 (62 N) and R3 (64 N) during cruise. R1 and R0.75 were the best configurations in terms of following the flight pattern. Furthermore, at the same speed and displacement condition, the drag estimated for R4 was more than halved, if compared to the original model (130 N).

Keywords: Computational fluid dynamics , Double PID flight control system , Hydrofoil , Measurements , Parametric design and modelling

In the field of boating, the design of eco-sustainable solutions has been recently focused on hydrofoils. Such technology is employed in small and large vessels. A great challenge may be represented by the reconstruction of geometric details in objects with large sizes through traditional approaches based on simple and manual instrumentations and measuring systems. With regard to reverse engineering techniques, photogrammetry may be suitable for reconstructing devices with large sizes. The aim of the work was to report and provide an analysis on the last progresses related to the feasibility of the photogrammetric approach in the hydrofoil research, summarising a specific methodology reported in the literature to acquire and reconstruct the outer sector of the front wing of a Kolkhida-class hydrofoil. The potential of computational fluid dynamics was also stressed in the evaluation of the characteristic curves, focusing on drag and lift coefficients as well as on the error due to the reconstruction through photogrammetry. Data analysis and research generally require the possibility of sifting through a great amount of information, thus providing a very overwhelming and time-consuming approach. In this scenario, the focused summarising approach may play an important role in providing a simplification of the complex content and technical features into digestible insights. This means that the proposed summarising approach should be able to boost retention providing a help in remembering key features more effectively through their condensation to a reduced number of information and steps.

Keywords: computational fluid dynamics , Design methods , hydrofoil , measurements , reverse engineering

The work is part of the research activities performed within the framework of the “Nemesi- New Engineering & Manufacturing Enhanced System Innovation” research and development program. The aim of the research is to evaluate the accuracy and measurement uncertainty characterizing the entire process of the digitized acquisition, scanning and measurement of surface defects on aluminum aircraft fuselage. Additionally, it aims to determine the combinations of the main process parameters that make it less sensitive, and therefore robust, to the effect of disturbing factors, such as technological imperfection and environmental variations. Special attention was put on the study of two specific types of aircraft surface defects: scratches and depressions (dents). For scratches, three different morphological configurations were studied: linear, crossed, and curved scratches. Reference depth measurement of the defects was obtained by using a digital depth micrometer (comparator), an instrument currently certified in the aeronautical field. These values were compared with the outputs measured using the 3D scanner system Atos Q – Zeiss and the related analysis software Gom Inspect Pro. The analysis of the results showed very accurate and reliable defect depth values when compared with the reference depth values obtained from the certified digital micrometer/comparator. Future developments of this research will focus on expanding the range of the analysed defect types, including further surface anomalies and complexities, as well as several materials. With regards to future trends, the integration of machine learning algorithms to enhance the predictive capabilities of defect detection and measurement processes will also be explored.

Keywords: Design of Experiments , Non-contact Reverse Engineering systems , Non-destructive inspection , Quality control , Structured light systems , Surface defects

Sustainable energy systems demand energy-dense, scalable, manufacturable, and readily integrable lithium-ion batteries, yet available literature provides fragmented comparisons of commercial cell formats. Here we report a unified, industrially grounded benchmarking framework for cylindrical, pouch, and prismatic cells using parameters selected for high-fidelity derivability across formats and direct relevance to manufacturing and system integration. At cell level, active/inactive volume allocation, gravimetric and volumetric energy densities, and assembly complexity are quantified. At pack level, we evaluate nominal voltage and capacity, pack energy, gravimetric cell-to-pack ratio, cooling, and structural integration descriptors. Chemistry-dependent single-cell and pack-scaled costs are estimated from prospective cost trajectories. Fast-charging capability, resistance growth and aging, and quantitative thermal performance are excluded due to noncomparable datasets; pack thermal implications are discussed qualitatively. The framework shows cylindrical lithium nickel manganese cobalt oxide cells maximizes cell-level energy density but increases structural overhead, whereas lithium iron phosphate blade designs maximize cell-to-pack ratio, pack volumetric energy, and cost competitiveness.

Keywords: cell design optimization , cell formats , cell-to-pack integration , cost-performance trade-offs , electric vehicles , lithium-ion battery manufacturing , teardown-based modeling

Objective: Joint replacement surgery, also known as arthroplasty, is a common procedure that restores mobility and relieves pain in patients with severe joint pathologies. Despite being considered routine, arthroplasties are complex interventions with potential complications and variable clinical outcomes. Accurate evaluation of replaced joint mobility to ensure implant stability within the patient's functional range of motion (ROM) is a major challenge in postoperative care. However, the reliability of current assessment methods is limited due to their lack of standardized and quantitative tools. This study presents a patient-specific Mixed Reality (MR) framework designed to enhance postoperative evaluation in joint replacement with a focus on total hip arthroplasty (THA). Methods: The proposed system enables objective quantification and MR visualization of prosthesis biomechanics by integrating ROM simulation and 3D modeling, promoting explainability and interpretability of surgery outcomes. A retrospective analysis of 67 THAs was performed to compare simulated ROM results with clinical assessments and literature benchmarks. Additionally, surgeons evaluated the system's clinical relevance and usability through a preliminary study, including completion of the System Usability Scale (SUS). Results: Simulated ROM measurements showed good agreement with both clinical assessments and established literature reference values across ten movements commonly examined in orthopedic practice. The MR tool demonstrated high accuracy, repeatability, and potential to support postoperative decision-making, with usability testing yielding a favorable median SUS score of 82.5, indicating strong acceptance among clinicians. Conclusion: The patient-specific MR framework provides a reliable, quantitative, and interpretable method for assessing prosthetic joint performance after replacement, supporting its integration into postoperative workflows for improved surgical outcome assessment.

Keywords: Computer-aided surgery , Human-computer interaction , Joint replacement , Mixed reality , Orthopedic surgery , Total Hip arthroplasty