Design methods for mobility

The high-performance car industry demands increasingly lightweight and durable components, driving the development of innovative manufacturing techniques and increasingly high performing materials. Among critical automotive components, mechanical hinges with close supports play a key role in ensuring high functionality in limited spaces while contributing to the structural efficiency and safety of vehicles. This study examines an accurate design and manufacturing process for hinges with close-range bushings. In particular, the manufacturing technology of the Polytetrafluoroethylene (PTFE)-coated bronze bushing connected with a FeZnNi pin inside the hinges was analysed and optimised. A predictive mathematical model was developed and validated with measurements using an appropriate experimental set-up created by the authors. Specifically, the experimental tests were performed by simulating and automating the rotation of the hinge; this made it possible to accurately assess the resistant torques due to assembly errors, tightening torques, geometric and dimensional tolerances. Through the proposed methodology, the resistant torque was related to the correct manufacture, the PTFE coefficient of friction, and the operating temperatures, guaranteeing long-lasting performance and reliable integration of hinge components. The results demonstrated that the proposed methodology enhances the manufacturing process by allowing the production of reliable and high-performance mechanical hinges.

Keywords: Fe-Zn-Ni alloy , Geometric and dimensional tolerances , Long-lasting performance , PTFE-coated bronze bushing , Resistant torque

Maintenance activities on transportation infrastructures, particularly on the underside of bridges and viaducts, present critical challenges related to safety, accessibility and cost-efficiency. Conventional solutions, such as scaffolding or mobile platforms, often exhibit substantial operational limitations. In this context, modular articulated robotic arms present a promising, safer, and more flexible alternative. This study introduces a functionality and data-driven design methodology for the modular development of articulated robotic arms specifically tailored for bridge maintenance applications. The proposed approach integrates Finite Element Analysis with clustering algorithms to identify mechanically equivalent joint modules based on their structural response under realistic loading conditions, including self-weight and external forces. Subsequently, topology optimisation techniques are applied to refine the geometry of selected joints, enhancing their stiffness-to-weight ratio while preserving manufacturability and modularity. Additionally, the application of Geometric Dimensioning and Tolerancing ensures mechanical reliability and precision during assembly. The effectiveness of the methodology is demonstrated through comparative Finite Element Analysis assessments between the initial and optimised designs, along with the construction of a functional prototype. The proposed framework paves the way for scalable, robust, and repeatable robotic solutions in the infrastructure maintenance sector.

Keywords: Bridge Maintenance , Clustering Algorithms , Geometric Dimensioning and Tolerancing , Modular Robotic Arms , Topology Optimisation

This paper presents a novel design-driven methodology for fabricating marine sandwich structures using additive manufacturing (AM). The approach leverages the geometric freedom enabled by Fused Filament Fabrication (FFF) to produce complex lattice cores from PA12-GF15, a fibreglass-reinforced nylon, directly integrated into sandwich panels with laminated glass fibre skins. A hull portion of the Chichester Scow dinghy was selected as a case study to demonstrate the method's feasibility. The core geometry was generated through volumetric lattice modelling in Blender, enabling full customisation of the internal structure to match the outer hull surface. The resulting sandwich panel was produced entirely in-house and compared against traditional fibreglass laminates and aluminium-honeycomb-core panels. The results show that the 3D-printed sandwich structure achieves an approximate 58,7% weight reduction compared to solid fibreglass construction, while also offering improved manufacturing flexibility and potential for performance tuning through localised lattice control. This study highlights the potential of AM in marine engineering and lays the groundwork for future research on structural behaviour and large-scale implementation.

Keywords: Additive Manufacturing , Lattice structures , Lightweight design , Marine Engineering , Sandwich structures

The design and management of Industry X.0 manufacturing systems is based on several simulation tools and digital models, used to predict and optimize the final performance. The lack of a seamless interoperability between such tools requires the development of a Digital Thread, a communication framework able to connect and synchronize digital models with the physical assets throughout their lifecycles. This study presents a novel Digital Thread based framework for the simulation and Virtual Commissioning of robotic systems, built on a Docker infrastructure integrated with Hadoop 3.2.0. It leverages AutomationML (AML) as a data exchange standard and the Robot Operating System (ROS) for distributed robotic control. The proposed architecture supports offline programming and facilitates the deployment of custom, multi-brand robotic systems, while enabling seamless integration of AML-based Digital Twins. The proposed methodology is validated on a large scale robotic manufacturing cell for aircraft fuselage assembly, demonstrating its capability in terms of performance validation, operational coordination, and optimization of production sequences.

Keywords: AutomationML , Engineering Methods , ROS , Simulation Framework , Virtual Prototyping

Wear tests were carried out in rolling-sliding condition by a bi-disc machine on specimens made by two railway wheel steels, coupled with the same rail steel. Contact load and sliding speed were varied from mild to very severe working conditions. The weight loss and coefficient of friction were monitored throughout the tests. At the end of the tests, the surface state was evaluated by roughness measurements obtained by an innovative laser distance sensor. Microscopic analyses of the subsurface strain state and wear debris were performed on some specimens to identify the wear regime. The results showed that, with increasing load and sliding speed, there is a sudden transition of wear from mild or severe to catastrophic. This is correlated with both parameters, but the sliding speed showed a stronger effect on the wear regime, whereas the contact load affected especially the thickness of the plasticized depth. The roughness at the test end was strongly correlated with the sliding speed. The SUPERLOS® steel showed a better performance than the ER8 one. To assess the wear regime, the correlation between the Archard wear number and various existing wear models (T-gamma, p-gamma, shakedown map), based on the working condition parameters, was evaluated, but it proved unsatisfactory. Therefore, a new model, named “p-vs2”, was introduced to better approximate the effect of the sliding speed: it showed an overall good correlation with the wear number, appearing as a promising model for predicting the wear regime up to very severe working conditions.

Keywords: Railway wheel steels , Rolling contact tests , Wear model , Wear regime

Environmental sustainability and increasingly stringent emission regulations are accelerating the electrification of non-road mobile machinery. While retrofitting presents a cost-effective path forward – particularly for small and medium-sized manufacturers – it often fails to unlock the full benefits offered by electrification. This shortfall is especially evident in machines that retain traditional hydraulic architectures, where energy inefficiencies persist. This study focuses on the virtual prototype of a retrofitted battery-powered material handler derived from an internal combustion engine variant, where the original load-sensing hydraulic system remains unchanged. Being previously validated, the virtual prototype is used to investigate a novel energy-saving control strategy. This strategy controls the electric motor speed based on the combined efficiency map of the electric motor and hydraulic pump, moving beyond conventional load-sensing control logic. The paper focuses on the modeling methodology for both components. Then, simulations show that control optimization based on combined efficiency reduces the energy consumptions compared to the baseline strategy. Indeed, overall efficiency of the machine increases from 36.6% to 39.1%. The proposed approach offers a cost-efficient pathway for improving performance without requiring extensive mechanical modifications, thus supporting broader electrification in the non-road mobile machinery industry.

Keywords: Electrification , Multi-physics Modeling , Non-Road Mobile Machinery , Off-Highway Vehicles

This study investigates the archaeological significance and preservation state of the Lombardo, a XIX century paddle steamer closely associated with Garibaldi's Mille Expedition and now resting off the Tremiti Islands. The research aims to contextualize the vessel's historical role and to reconstruct its steam engine, paddle wheel and shipwreck dynamics, providing the first comprehensive three-dimensional documentation of the site. Underwater photogrammetry was carried out using high-resolution imaging, a dedicated geodetic network of coded markers, and Structure-from-Motion workflows to generate a scaled 3D model of the wreck. Historical and technical sources were also examined to identify the original configuration of the steam engine and paddle wheel. The results show a highly fragmented site distributed between 9 and 22 m depth, where the surviving remains corroborate historical accounts of post-wreck salvage operations and subsequent natural collapse processes. Analysis of the wreck reveals that the ship's steam engine was a Maudslay Siamese double-cylinder type, driving radial paddle wheels. The distribution of the remains also suggests that the vessel originally settled on its port side, oriented along a north–south axis. The conclusions demonstrate how integrated archaeological, geomatic, and archival methods could clarify the technical characteristics of the Lombardo and improve understanding of its post-depositional transformation, providing a robust basis for future conservation and dissemination activities.

Keywords: Italian Risorgimento , marine steam engine , maritime archaeology , shipwreck , underwater heritage , underwater photogrammetry

Wrist impairments are common in post-stroke and elderly populations, often requiring rehabilitation to restore joint mobility and strength. However, clinic-based programs pose accessibility challenges, especially for patients with limited mobility. This paper presents W.R.I.S.T. (Wrist Rehabilitation Intelligent Support Tool), a soft robotic prototype designed to facilitate wrist flexion-extension exercises in home settings. The system features an inflatable silicone handle integrated into a 3D-printed structure, equipped with a flexion sensor for monitoring and a pneumatic circuit for real-time resistance modulation. A microcontroller manages pressure regulation and sensor data acquisition, enabling adaptive therapies and personalized training. Experimental validation confirmed a predominantly linear relationship (R2 > 0.85) between sensor output and flexion angle across pressure levels, ensuring reliable motion tracking. Additionally, a game-based interface was developed to enhance user engagement, transforming repetitive exercises into an interactive task with customizable difficulty. The integration of adjustable mechanical resistance and interactive feedback supports progressive rehabilitation while promoting adherence. W.R.I.S.T. offers an affordable, customizable, and valid solution for decentralized rehabilitation, particularly suitable for elderly users or those with limited access to clinical services.

Keywords: 3D printing , Pneumatic , Rehabilitation , Soft Material , Wrist

Over the past few years, Silicon Carbide (SiC) power MOSFETs had a huge success both in terms of performances and impact on market. However, threshold voltage (Vth) instability is still a key aspect to attention, especially in long-term switching behavior. In this work, we have implemented Dynamic Gate Stress (DGS) reliability test on an automotive grade, planar-gate, SiC MOSFET. We have assessed the impact of duty cycles values, namely 25 % and 50 %, combined with different Rg values, namely 0 Ω and 6.8 Ω. As a result, a limited impact of duty cycle has been noticed on Vth and on-state resistance (RDS,ON) drifts, independently from the gate resistance value adopted. Besides, for each combination of parameters analyzed, gate–source voltage (VGS) waveforms have been acquired before and after the stress, and, consequently, a statistical analysis have been implemented. No significant variations in peak values and slew rates have been noticed.

Keywords: Duty cycle , Dynamic Gate Stress , Gate resistance , MOSFET , Reliability , Silicon Carbide

Viscoelastic polymers are increasingly employed in lattice structures for their absorption and damping capabilities, particularly in applications involving vibration suppression or impacts. These structures exhibit remarkable properties, such as high specific stiffness, specific strength and energy absorption capacity, making them highly attractive for applications in aerospace, automotive, and biomedical fields. However, the accurate modeling by taking into account frequency-dependent behavior, especially for applications involving damping, remains challenging due to the interplay between geometric complexity and material viscoelasticity. To address this challenge, this study makes use of a general numerical homogenisation method enhanced for frequency-dependent material properties in order to predict the damping of the lattice structure at the macroscopic scale. A fractional derivative constitutive model is used to describe the frequency-depend behaviour of the bulk material, while a custom Ansys APDL code is developed to adapt the homogenisation method to the case of material with frequency-dependent properties. The results demonstrate that, for lattice structures made of a single material phase, it is possible to perform the homogenisation process at an arbitrary frequency. The resulting stiffness tensor of the equivalent homogeneous anisotropic material that replaces the structure at the macroscopic scale varies with frequency according to the same law used for the bulk material at a lower scale. Furthermore, the results show that even if the stiffness tensor of the lattice structure at the upper scale exhibits elastic symmetry depending on the topology of the unit cell, the damping matrix at the upper scale is unaffected by the lattice topology.

Keywords: Homogeneization , Lattice structures

The transition to clean and sustainable transportation highlights the importance of hydrogen and fuel cell technologies as promising solutions for reducing greenhouse gas emissions. This paper presents the development and assessment of an adaptive frequency separation-based energy management strategy using fuzzy logic for fuel cell–battery hybrid vehicles. The studied system integrates a proton exchange membrane fuel cell as the primary source and a lithium-ion battery as the secondary source, both interfaced with the DC bus through DC/DC converters. A PI controller ensures DC bus voltage stability, while a sliding mode hysteresis controller provides robust regulation of the fuel cell current. Unlike conventional frequency separation methods, which only allocate low-frequency demand to the fuel cell and high-frequency demand to the battery, the proposed strategy introduces an adaptive correction mechanism based on the state of charge (SOC) of the battery and instantaneous load variations. This ensures efficient power allocation according to source dynamics while actively regulating the SOC within a safe operating range. Simulation results under UDDS and NEDC driving cycles confirm that the proposed strategy maintains the SOC between 40% and 80% with convergence toward the target value of 60%, while reducing the apparent hydrogen consumption by 30%. These improvements highlight the robustness and efficiency of the proposed strategy, making it a promising solution to extend the lifespan of hybrid energy sources in hybrid fuel cell electric vehicles.

Keywords: Energy management strategy , Frequency separation , Fuel cell hybrid electric vehicle , Fuzzy logic , Hydrogen , PI controller , Sliding-mode control

Car seat comfort represents a fundamental dimension of automotive ergonomics, yet its assessment and optimization remain predominantly reliant on subjective feedback and iterative physical prototyping, limiting scalability and responsiveness in the design process. This study presents a novel data-driven framework that synergistically integrates statistical analysis and deep learning architectures enhanced with attention mechanisms to predict perceived driver discomfort from pressure distribution patterns. A comprehensive dataset acquired from 192 participants was used to extract biomechanical descriptors, such as contact area and peak pressure, across 9 anatomical regions, which were subsequently correlated with subjective discomfort ratings collected on a 10-point Likert scale. The proposed hybrid deep neural network achieved a modelling accuracy of R2 = 0.82 for overall discomfort, with peak pressure emerging as the most influential factor (Spearman's r = 0.78). Moreover, Finite Element Analysis (FEA) was employed to validate geometry refinements suggested by the AI model, resulting in an 18% reduction in peak seat pressure without compromising structural integrity. The findings underscore the transformative potential of integrating artificial intelligence with CAD–CAE methodologies to enable rapid, user-centered, and simulation-driven ergonomic design early in the vehicle development cycle, minimizing the need for physical prototypes and enhancing occupant comfort.

Keywords: AI-Driven Comfort Models , Deep Learning with Attention Mechanisms , Ergonomic Seat Design Optimization , Finite Element Validation of Human-Centric Design , Pressure Mapping and Biomechanical Analysis

This study investigates the development of advanced technologies for subsurface monitoring, with significant implications in geophysics, natural hazard mitigation, and environmental engineering. Specifically, the research focuses on the application of Distributed Acoustic Sensing using a 28 km long scientific electro-optical cable deployed in deep-sea conditions as a sensor for the detection of vibrations and mechanical disturbances along its path. DAS enables continuous, high-resolution monitoring of the underwater acoustic environment. However, the system's sensitivity and accuracy are strongly influenced by the degree of mechanical coupling between the optical fiber and the surrounding medium, which in turn depends on both the structural characteristics of the cable and the nature of the seabed where it is installed. To address these challenges, a digital twin of the experimental configuration has been developed. This virtual model allows for the simulation and optimization of the cable's mechanical behavior under various environmental conditions. Particular emphasis is placed on the analysis of the cable's static equilibrium state, which is essential for understanding the actual transmission of mechanical stress to the optical fiber and for the calibration of numerical models against experimental data. The manuscript is organized as follows: Introduction, Cable Architecture, Experimental Setup, Methodology, Results, and Conclusions.

Keywords: Digital twin , Distributed Acoustic Sensing (DAS) , Mechanical Coupling , Optical Fibers

The GeoINQUIRE project (GEO_INQUIRE, HORIZON-INFRA-2021-SERV-01, GA - 101058518) is a European initiative aimed at developing innovative research infrastructures for monitoring the subsurface, with applications in the fields of geophysics, natural hazards and environmental engineering. In this context, the Laboratori Nazionali del Sud – Istituto Nazionale di Fisica Nucleare are working on the application of Distributed Acoustic Sensing (DAS) technology, using a proprietary 28 km-long scientific deep-sea electro-optical cable as sensor to detect vibrations and mechanical changes along its path, to provide continuous, high-resolution monitoring of the soundscape. The effectiveness of DAS in such applications depends on the ability to accurately simulate the response of the system, since the mechanical coupling between optical fiber and soil, mediated by the cable jacket, varies significantly depending on the type of cable used and the characteristics of the soil (rocky, sandy, etc.). To address this issue, the development of a digital twin of the configuration has been initiated to model, simulate and optimize the behaviour of the optical fiber under different operating and environmental conditions and using cables different manufacture. The integration of experimental data into digital simulations enables the prediction and improvement of DAS performance, helping to optimize design solutions and promote the evolution of smart manufacturing.

Keywords: Digital twin of optical fiber cable , Distributed Acoustic Sensing , Mechanical coupling , Modal analysis , Optical fibers cable manufacture

Background: Pumping in Laser-class sailing is a dynamic propulsion technique used in marginal wind conditions and characterized by repetitive, coordinated oscillations of the sailor–sail system. Despite its practical relevance, its biomechanical and ergonomic demands remain insufficiently characterized. Methods: A mixed-methods framework was applied combining questionnaire data, kinematic analysis, ergonomic assessment, and musculoskeletal modelling. Thirty-six competitive Laser sailors completed a Borg CR-10-based questionnaire on perceived discomfort/fatigue across body regions at predefined time points (during pumping, immediately after training, and the following day). A controlled land-based multi-angle video acquisition was used to reconstruct a standardized pumping posture and parameterize a digital human model in DELMIA® for postural/kinematic analysis. Ergonomic risk was assessed using REBA, and muscle activity was estimated using the AnyBody® Modeling System (simulation-derived normalized muscle activity across 129 muscles). Results: the simulation identified high neuromuscular demand in the trunk and shoulder complex, with several deep trunk stabilizers and the left latissimus dorsi reaching 100% modeled normalized muscle activity. Marked lateral asymmetry was observed, with right-sided trunk dominance and left-sided shoulder dominance. Kinematic analysis showed substantial joint excursions, with large lumbar motion amplitudes, while REBA yielded a score of 11 (Very-High Risk). Questionnaire data indicated a high prevalence of pumping-related musculoskeletal discomfort (72.2%), most frequently involving the lower back, shoulders, and knees. A dissociation was observed between modeled muscle activity and perceived fatigue, with the lower limbs rated as most fatigued despite lower modeled activation than the trunk. Conclusions: Findings identify the deep trunk stabilizers, latissimus dorsi, and lower extremities as key regions involved in pumping, with marked lateral asymmetry and high ergonomic risk. They support targeted training, injury-prevention, and ergonomic strategies to improve performance and reduce injury risk in competitive sailing.

Keywords: discomfort , laser sailing , muscle activation , musculoskeletal simulation , pumping maneuver , REBA ergonomic assessment

The global demographic shift toward an aging population presents significant implications for automotive design and safety. This research addresses a critical gap in the literature by conducting a comprehensive ergonomic assessment of elderly drivers during two essential driving tasks: reverse gear maneuvers and seat belt engagement. Through a methodologically rigorous approach combining quantitative discomfort evaluations and postural analyses, this study examined a sample of 20 elderly people, a B-segment car and a strategically positioned recording equipment. The investigation revealed statistically significant patterns of discomfort concentration in the upper body regions, particularly the shoulders and cervical area, with Rapid Upper Limb Assessment (RULA) scores indicating substantial musculoskeletal risk factors. The findings demonstrate that conventional automotive configurations impose asymmetric postural stresses that are particularly problematic for elderly users due to age-related physiological changes. This research contributes to the theoretical understanding of aging-specific ergonomic requirements and provides empirical evidence supporting the necessity for adaptive design modifications to enhance safety, comfort, and continued mobility independence among the elderly population.

Keywords: Elderly population , Ergonomics , Postural Discomfort

The use of multi-layered foam pad as filler for cushions, seats components and furniture, is widely spread in many industries, especially in car-seat manufacturing ones. The mechanical behavior of these materials is directly connected to the perceived comfort and discomfort by users. This work presents a numerical investigation of the mechanical response of two foam materials under localized compression loading: a standard polyurethane foam and a viscoelastic memory foam. The analysis focuses on two key phenomena relevant to comfort applications: pressure absorption, i.e. the material's ability to attenuate peak stresses, and pressure diffusion, i.e. the spatial redistribution of contact forces across internal layers. Finite Element Method (FEM) simulations were performed on a layered foam block (200 × 200 × 100 mm), indented centrally by a rigid cylindrical indenter (30 mm diameter) up to 50 mm depth. The block was discretized into ten 10-mm-thick layers, enabling pressure analysis throughout the thickness. Results show that memory foam achieves significantly lower peak pressures and smoother vertical gradients compared to standard foam, indicating superior performance in both absorption and diffusion. Conventional foam, while more resilient, exhibits greater pressure concentration at deeper layers. These outcomes support the use of memory foam in applications requiring high comfort and soft tissue protection, such as bedding, seating, and wearable protective equipment. Moreover, the study highlights FEM is effective for predicting pressure behavior in layered, deformable media.

Keywords: Finite Element Method , Pressure distribution , Viscoelastic foams

Background: In-depth studies highlight that trust is essential for the effective interaction with autonomous vehicles, which, have not yet gained public trust. Objective: The aim of this study was to develop and validate a comprehensive questionnaire to evaluate people's trust in autonomous vehicles. Methods: After identifying influential factors in trust by interviews and brainstorming sessions, 75 questions across 5 dimensions were developed, which were then narrowed to 69 in 3 dimensions using “thinking aloud”. This version was assessed by 24 experts, resulting in 19 responses and the exclusion of 22 questions based on CVI and CVR. Finally, the reliability was determined using Cronbach's Alpha after an experiment with 24 participants. Results: A 47-item questionnaire, with 3 dimensions including personal, social, and technical factors, and 21 sub-dimensions was developed. The lowest CVI (0.63) was for “mental complexity” and the highest (0.90) belonged to “personality”. The least CVR (0.56) for “meaningfulness attitude” was acquired, while the highest CVR (1.00) was recorded for 9 questions. Total Cronbach's Alpha coefficient (0.93) showed satisfactory reliability. Conclusions: This validated instrument offers a comprehensive tool for evaluating trust in AVs for future studies.

Keywords: automated driving , autonomous vehicles , questionnaire , reliability , trust , validity

Comfort is a pivotal construct in human-centered design, connecting technical functionality with well-being across products, services, and systems. The 2023 International Comfort Congress (ICC2023) brought together researchers and practitioners to explore how new contexts of use, predictive approaches, and user diversity are reshaping this field. Contributions in this special issue address comfort in automated driving and turboprop aviation, where physical, psychological, and environmental factors converge. Advances in predictive comfort science demonstrate how objective measures, physiological sensing, and modeling complement traditional self-reports. At the same time, inclusive design approaches—ranging from XR-based co-creation to analyses of posture and movement variability—highlight the importance of accounting for heterogeneous user needs and comfort trade-offs. Together, these studies illustrate a shift toward more adaptive, accessible, and sustainable systems, underscoring comfort as a multidimensional construct that evolves with technological innovation and societal change.

Keywords: accessibility , automated driving , comfort research , human-centered design , predictive modeling , user diversity

Nowadays, to counteract the sedentary behavior in children, playground parks with their pieces of playground equipment can have a significant impact. In this context, the paper proposes a methodology based on wearable surface electromyography and inertial sensors data to derive functional data sheets for each piece of playground equipment and two novel synthetic indices for the assessment of physical fitness and motor coordination. These indices are built from: (i) muscle activation of nine forearm and leg muscles; (ii) acceleration data from two inertial sensors located on the forearm and lower back. The synthetic indices are based on the assessment of the muscular force rate and motor control in terms of smoothness. The validation of the proposed methodology is carried out through field tests, on seven pieces of playground equipment. The results confirm that: (i) the functional data sheet offers the possibility to obtain quick and intuitive visualization of the pieces of playground equipment in terms of required muscle activation; (ii) the proposed methodology represents a reliable and valuable tool to estimate physical fitness and motor coordination. This approach can be implemented in different playground parks even to guide the choice of the equipment to ensure specific levels of physical fitness and motor coordination.

Keywords: motor coordination , physical fitness , playground equipment , wearable sensors