Design methods for mobility

Ni-based superalloys, known for their excellent mechanical strength and corrosion resistance at high temperature, are widely used in aeronautic, aerospace, and energy industries. Since both the materials and manufacturing processes required to produce high-performance components made of these alloys are expensive, the welding repair of damaged components plays a crucial role in industrial applications. High energy density welding techniques, such as laser beam welding (LBW) and electron beam welding (EBW), are the most promising to achieve high-quality welds. Nevertheless, welding processes significantly affect the microstructure and mechanical properties of both the melted zone (MZ) and the heat-affected zone (HAZ). This may result in alloying element segregation, precipitation of undesired secondary phases, and the presence of residual stresses that can lead to crack formation. Therefore, a comprehensive investigation of the effects of process parameters on weld seam properties is essential to maintain high performance standards. In this work, LBW was employed to join 2.5 mm thick plates of equiaxed IN625 superalloy. The seams were produced by varying three parameters: the two characteristic parameters of LBW, i.e., laser power (P = 1700, 2000, 2300 W) and welding speed (v = 15, 20, 25 mm/s), alongside power modulation (Γ = Pmin/Pmax = 0.6, 0.8, 1). The scope of this work is to evaluate the effect of the combined variation of all these welding parameters on the final characteristics of welded seams. The resulting microstructures were characterized by using digital radiography, Light Microscopy (LM), Scanning Electron Microscopy (SEM), and X-ray Diffraction (XRD). Vickers microhardness measurements were performed across the weld seams to evaluate the mechanical properties in the MZ and HAZ. The optimal set of welding parameters, producing defect-free seams without cracks and pores, was identified as P = 2000 W, v = 25 mm/s, and Γ = 0.6.

Keywords: IN625 , laser beam welding , microstructure , Ni-based superalloys

Lattice structures are lightweight architected materials particularly suitable for aerospace and automotive applications due to their ability to combine mechanical strength with reduced mass. Among various topologies, Body-Centered Cubic (BCC) lattices are widely employed for their geometric regularity and favorable strength-to-weight ratio. Advances in Additive Manufacturing (AM) have enabled the precise and customizable fabrication of such complex architectures, reducing material waste and increasing design flexibility. This study investigates the low-velocity impact behavior of two polylactic acid (PLA)-based BCC lattice panels differing in strut diameter: BCC1.5 (1.5 mm) and BCC2 (2 mm). Experimental impact tests and finite element simulations were performed to evaluate their energy absorption ((Formula presented.)) capabilities. In addition to conventional global performance indices, a dimensionless parameter, (Formula presented.) is introduced to quantify the ratio between local plastic indentation and global displacement, allowing for a refined characterization of deformation modes and structural efficiency. Results show that BCC1.5 absorbs more energy than BCC2, despite the latter's higher stiffness. This suggests that thinner struts enhance energy dissipation under dynamic loading. Despite minor discrepancies, numerical simulations provide accurate estimations of (Formula presented.) and support the robustness of the (Formula presented.

Keywords: additive manufacturing , dimensionless index , drop-weight impact test , lattice structures , numerical and experimental comparison , PLA

This study presents a comparative analysis of two portable 3D scanning technologies, structured light and LiDAR, applied to the reverse engineering of fiberglass boat molds. Key aspects such as acquisition speed, data completeness, resolution, feature detectability, and operational usability were evaluated. Due to the absence of a CAD reference, a relative geometric deviation analysis between the overlapping regions of the scans was performed. Results indicate that while the LiDAR-based scanner offers rapid and comprehensive coverage suitable for large-scale geometry capture, the structured light scanner provides higher resolution in localized areas but requires more careful setup and markers for effective scanning. The complementary nature of these technologies suggests potential advantages in hybrid scanning strategies for marine manufacturing applications.

Keywords: 3D scans , LiDAR scanning , quality control , reverse engineering , structured light scanning

The growing demand for automation in industrial production, especially in the automotive industry, has made it crucial to adopt integrated design methodologies that ensure efficiency, quality, and shorter product development timelines. Currently, the design of welded assemblies involves several stages: product design, design of the related welding fixtures, definition of the welding process, and subsequent evaluation of residual stresses. This process requires effective management of product and process data through a well-organized flow across design iterations. In this context, assuming a robotic welding automation process, this study introduces an approach for designing, simulating, and optimizing welded assemblies using a single, integrated software platform that combines CAD, CAM, and CAE functionalities. The platform supports the development of a streamlined workflow covering the entire design process for welded joints: from component modeling to thermo-structural simulation of the robotic welding process, and assessment with specific key performance indicators. The approach was applied to a case study involving a simplified automotive chassis, aiming to identify the most effective welding sequence in terms of minimizing product deformations and reducing process execution time. The results confirm the viability of the proposed method and highlight new opportunities for using integrated digital tools in the design of complex products and processes.

Keywords: Integrated approach , Process effectiveness indicator , Product and process design , Robotic welding

Stroke affects approximately fifteen million people worldwide annually, with impaired hand function being one of its most common effects. Hemiparetic post-stroke patients suffer a mild loss of strength involving one side of their body: though not fully debilitating, it still impacts their everyday life activities. To prevent mobility deterioration, patients must perform well-focused and repetitive exercises during chronic rehabilitation. Virtual Reality (VR) emerges as an interesting tool in this framework, offering the possibility of training and measuring the patient's performances in ecologically valid, engaging, and challenging environments. In recent years, there has been an increasing diffusion of accessible head-mounted displays that enhance the sense of realism and immersion in a virtual scene. To explore the feasibility and efficacy of VR immersion and game mechanics in rehabilitation programs, a VR system that allows users to rehabilitate their motor skills in a home-based environment has been designed and tested considering standard measures related to usability, immersion, workload, and simulator sickness, and with the involvement of rehabilitation experts. The results demonstrate how users and experts have received the application positively, highlighting the potential of VR applications for the future development of home-based rehabilitation programs.

Keywords: Exergames , Post-Stroke Rehabilitation , Virtual Reality

The idea presented in this contribution stems from the authors' interest and previous experience in designing aids for individuals with disabilities in the field of Accessible Tourism - AT. Specifically, the focus has been directed towards devices utilized in the seaside sector, with an analysis conducted on beach wheelchairs. The study involved both a market analysis and an examination of the regulatory framework. Two main results were obtained. Firstly, the analysis of the regulatory framework revealed potential challenges in interpreting rules and regulations, particularly regarding design, safety, and testing requirements. Secondly, the market analysis demonstrated that all currently available devices necessitate users switching from their personal wheelchairs to beach wheelchairs. Considering these findings, a conceptual solution is proposed to adapt one's personal wheelchair for movement on sandy terrains. This solution entails a kit comprising beach wheels mounted on a lightweight frame, potentially incorporating a self-propelled device to replace the manual wheelchair's existing wheels. It is important to note that this solution is intended to supplement existing beach wheelchairs rather than replace them, thereby broadening the options available to individuals with mobility impairments.

Keywords: Accessible Tourism , Assistive products , Beach wheelchairs , Design methods , User-Centered Design

Cell adhesion is a phenomenon characterizing cell-environment interactions and affects cellular behavior. Cell-substrate adhesion is ensured by focal adhesions (FAs), which are multilayer protein complexes. External mechanical stimulus perceived by FAs is rapidly transmitted first to cytoskeleton load-bearing structures and finally to the nucleus thanks to an interlinked cellular architecture, thus inducing transcription mechanisms and changes in cell functionality. Prestress of cytoskeletal filaments allows mechanical information to be transferred along these stiffer transportation channels with respect to neighboring cell regions, thus avoiding the energy dissipation typical of soft matter. Peculiar items concerning adhesion mechanisms, i.e., stiffness inhomogeneity in cell architecture, and auto-supporting tension-based cell structure, can be effectively handled thanks to modeling strategies provided by finite element method (FEM), which represents a valid tool for simulating cell adhesion. With the aim of replicating experimental results and predicting cell behavior, useful guidelines for simulating cellular adhesion will be outlined in the proposed work.

Keywords: Cell Adhesion , Finite Element Method , Mechanotransduction

The development of an Autonomous Underwater Vehicle (AUV) is driven by careful design choices in order to obtain the best trade-off between mission performance and cost. Currently, several companies provide off-the-shelf solutions for a wide variety of operational scenarios offering highly modular systems. This allows users to customize the AUV integrating custom payloads tailored for specific applications. The factory customization has a strong impact on time and resources due to significant precautions to be taken. In particular, some design constraints must be respected for the mechanical integration ensuring, at the same time, the overall neutral buoyancy of the module to preserve the final trim of the AUV. Therefore, without a careful approach during the design phase, the risk of impairing the integrity and operation of the AUV could be high. This paper describes a design methodology for the proper development of custom payloads aimed to be integrated in AUVs. The proposed methodology has been applied in the manufacturing of a custom payload that has been integrated in the AUV X-300 of Graal Tech s.r.l. The methodology results as a useful tool for AUVs customization by providing detailed guidelines for the development of specific payloads for a wide range of applications.

Keywords: Autonomous Underwater Vehicle , Balance Identification , Modular Payload Design , Shape Optimization

Inverse modelling with deep learning algorithms involves training deep architecture to predict device's parameters from its static behaviour. Inverse device modelling is suitable to reconstruct drifted physical parameters of devices temporally degraded or to retrieve physical configuration. There are many variables that can influence the performance of an inverse modelling method. In this work the authors propose a deep learning method trained for retrieving physical parameters of Level-3 model of Power Silicon-Carbide MOSFET (SiC Power MOS). The SiC devices are used in applications where classical silicon devices failed due to high-temperature or high switching capability. The key application of SiC power devices is in the automotive field (i.e. in the field of electrical vehicles). Due to physiological degradation or high-stressing environment, SiC Power MOS shows a significant drift of physical parameters which can be monitored by using inverse modelling. The aim of this work is to provide a possible deep learning-based solution for retrieving physical parameters of the SiC Power MOSFET. Preliminary results based on the retrieving of channel length of the device are reported. Channel length of power MOSFET is a key parameter involved in the static and dynamic behaviour of the device. The experimental results reported in this work confirmed the effectiveness of a multi-layer perceptron designed to retrieve this parameter.

Keywords: channel length modeling , Deep network , Power MOS inverse modeling

The increasing demand for designing complex structures using Functionally Graded Material boosts the research on reliable joining processes. For several industrial applications in the automotive, tooling, and petrochemical industries, the joining of a stainless steel with a low-alloy steel is often required to obtain a variation of mechanical and corrosion properties when different parts of the same structure are subjected to different working conditions. Welding a stainless steel with a low-alloy steel is a challenging operation because it is not easy to control the microstructure of the welded joint and to avoid metallurgical defects such as hot cracks. Moreover, traditional welding methods can only be applied to relatively simple geometries. To design and produce multi-material components, characterised by complex geometries, Selective Laser Melting process capabilities can be exploited. In this paper, an AISI 316L stainless steel is joined to 16MnCr5 steel by carefully tuning the process parameters. Metallurgical investigations coupled with Energy Dispersion Spectroscopy analyses allowed to evaluate the soundness of the joint and the effect of the process thermal cycle on the alloy microstructures and properties. The results are very promising and show that a careful selection of process parameters allows to obtain a continuous joint.

Keywords: 16MnCr5 , AISI 316L , Functionally Graded Material , Microstructure , Selective Laser Melting

Additive Manufacturing is widely applied in aerospace, automotive and marine engineering. Indeed, large-scale components are often required in these applications, such as for non-structural parts of aircraft, spare parts or small lots of cars or marine components. Fused Deposition Modelling is one of the Additive Manufacturing processes used to affordably convert digital models into mockups, prototypes, and functional parts: a slicing software converts the object's digital model into a list of instructions for the machine. However, commercial slicing software packages often fail to accurately estimate the time required to produce models, especially when their size is significant: the errors could be up to several hours, which cannot be adequate in a real-life industrial context where production must be scheduled in a precise way. This manuscript compares the build time estimation of several commercial slicing software considering a real-life part. Furthermore, the evaluation of the manufacturing setting mainly affects the error in estimating the build time achieved through a Design of Experiment approach. The more time-impacting printing parameters have been detected, allowing fine helpful tuning to increase the accuracy of the build time in commercial slicing software. A case study included in the manuscript supports the analyses. Proper setting of the commercial slicing software can significantly improve the accuracy of the printing time.

Keywords: Additive Manufacturing , Design of Experiment , Fused Deposition Modelling , Slicing , Time Estimation

Point cloud 3D models are gaining increasing popularity due to the proliferation of scanning systems in various fields, including autonomous vehicles and robotics. When employed for rendering purposes, point clouds are typically depicted with their original colors acquired during the acquisition, often without taking into account the lighting conditions of the scene in which the model is situated. This can result in a lack of realism in numerous contexts, especially when dealing with animated point clouds used in eXtended reality applications, where it is desirable for the model to respond to incoming light and seamlessly blend with the surrounding environment. This paper proposes the application of physically based rendering (PBR), a rendering technique widely used in real-time computer graphics applications, to animated point cloud models for reproducing specular reflections, and achieving a photo-realistic and physically accurate look under any lighting condition. To achieve this, we first explore the extension of commonly used animated point cloud formats to incorporate normal vectors and PBR parameters, like roughness and metalness. Additionally, the encoding of the animated environment maps necessary for the PBR technique is investigated. Then, an animated point cloud model is rendered with a shader implementing the proposed PBR method. Finally, we compare the outcomes of this PBR pipeline with traditional renderings of the same point cloud produced using commonly used shaders, taking into account different lighting conditions and environments. Through these comparisons, we demonstrate how the proposed PBR method enhances the visual integration of the point cloud with its surroundings. Furthermore, it will be shown that using this rendering technique, it is possible to render different materials, by exploiting the features of PBR and the encoding of the surrounding environment.

Keywords: extended reality , point cloud , real-time rendering

This paper presents a computer-based methodology to support the design for additive manufacturing of metal components. Metal additive manufacturing, and in particular powder bed fusion systems, are playing a prominent role in the industry 4.0 scenario. The state of the art concerning design methods and tools to support design for additive manufacturing is reviewed by the authors. The key phases of product design and process design to achieve lightweight functional designs and reliable processes are deepened, and the computer-aided technologies to support the approaches implementation are described. Indeed, the state of the art design for additive manufacturing general workflow can be enriched by holistic approaches, use of numerical simulation, and integration and automation between the required tasks. The paper provides a methodology based on the systematic use of numerical simulation to achieve the optimization of both products and associated processes. To take advantage of the holistic perspective, the approach relies on the use of integrated product-process design platforms, allowing to streamline the digital process chain. Product design is based on the systematic integration of topology optimization and automatized tools for concept development and selection and subsequent product simulation driven design refinement. Process design is based on a systematic use of process simulation to prevent manufacturing flaws related to the high thermal gradients of metal processes and minimize residual stress and deformations. This is achieved by working on both the build cycles layouts and the 3D models' distortion compensation. An automotive use case of product and process design performed through the proposed simulation-driven integrated approach is provided to assess the actual method suitability for effective re-designs of additive manufacturing high-performance metal products. The bridged gaps are systematically outlined, and further developments are discussed.

Keywords: Computer-aided engineering , Design method , Design optimization , Finite element method , Integrated design , Process simulation

The supply of automotive spare parts, especially for historic vehicles, is not guaranteed by car manufacturers. Usually, car restorers look for original components at flea markets and fairs, but often they have to produce replicas from broken parts or, worse, without information about the original parts. A possible support in mechanical craftsmanship comes from digital tools commonly used in industry today. With the goal of replicating a component that no longer exists, this paper provides a workflow that integrates traditional manufacturing technologies with computer-based tools. The core is the digital model, which is used to prototype and test the replica for functionality as well as simulate its manufacturing process. An engine valve cover of a historic racing car was chosen as a case study, for which information sources were practically unobtainable. Firstly, a 3D model and a 3D printed prototype were developed. Sand casting was chosen based on the original process and computer simulations allowed to reconstruct the casting equipment and define the best part design. A faithful and functional replica is then manufactured and assembled with the original engine, respecting the original part in terms of form, materials and production. The proposed design approach can be further adopted in different contexts requiring on-demand, one-off or small-batch production.

Keywords: 3D modelling , Additive Manufacturing , Car restoration , Component reproduction , Computer-Aided Engineering , Sand casting

Additive Manufacturing (AM) Powder Bed Fusion (PBF) metal processes enable significant design freedom, addressing design complexity in high-end sectors. To build performant products, several Design for Additive Manufacturing guidelines must be considered. Nevertheless, it is still noticeable a lack of reliability for AM processes, which is a key factor to guarantee both the expected enhanced product requirements and the manufacturability. Even though few rules and best practices to mitigate defects are provided either by standards or equipment suppliers, they are still missing approaches to predict build failures and process flaws, and therefore achieve faultless build processes. This work suggests a concurrent product and process design approach, in which Computer Aided Engineering tools are involved in both product and process design to identify the components' shapes that match the expected performance and a feasible PBF build layout. An automotive component is the use case, whose design based on topology optimization and product validation is enriched by integrating the associated process simulation. The build process is modeled by (a) the additive manufacturing simulation to identify flaws and resources usage, and (b) the thermo-mechanical finite element -based simulation to predict residual stress and distortions. The approach based on CAD platforms integrates product and process design to reduce design iterations, trial-error practices, and build failures.

Keywords: Design for Additive Manufacturing , Finite Element Analysis , Laser Powder Bed Fusion , Process simulation , Product-process design

Cyclists are at a higher risk of being involved in accidents. To this end, a safer environment for cyclists should be pursued so that they can feel safe while riding their bicycles. Focusing on safety risks that cyclists may face is the main key to preserving safe mobility, reducing accidents, and improving their level of safety during their travel. Identifying and assessing risk factors, as well as informing cyclists about them may lead to an efficient and integrated transportation system. Therefore, the purpose of this research is to introduce a risk index that can be adapted to different road areas in order to measure the degree of how risky these areas are for biking. Cyclists' behavior and demographics were integrated into the risk index calculation. The methodology followed to obtain the risk index composed of four phases: risk factor identification, risk factor weighting, risk index formulation, and risk index validation. Nineteen risk factors are categorized into four major groups: facility features, infrastructure features, cyclist behavior, and weather and traffic conditions.

Keywords: cyclist behavior , risk index , risk weighting , road characteristics

The design of a product consists of several stages to be carried out in sequence until the result is achieved, some of them are performed trough the help of CAD software. This design step is very rigorous with as little margin for error as possible, and it often goes to make a clean break from other stages that precede it. On the other hand, virtual reality technology is certainly an element of interest within various design areas. One of the most promising uses of this type of technology is in the visualization and review of products in the design process. But in this paper we will see a next step compared to this just described, that is, the application of virtual reality within the design making itself. By delving into the design timeline, we will then go on to explore how this technology can provide support not limited to visualization alone, but extended to modeling, what possibilities can be offered by the realization of three-dimensional surfaces, modeled already at the correct scale, and how these aspects can be efficiently integrated within a methodology, assessing variations in timing and quality of work. We will also try to intercept any downsides to try to get a clear understanding of what possibilities could be offered soon by this technology and whether indeed these types of processes can replace current methods, established for years.

Keywords: Design Methods , Industrial Design , Virtual Reality

The role played by emotions and attention is crucial for the development of advanced driver assistance systems that improve safety by flexibly adapting to the current state of the driver. In the present study, we used immersive virtual reality as a testing tool to investigate how different emotional states affect drivers' attention in a divided attention task. Two different emotional states, diversified by valence and arousal, were induced before performing a divided attention task in a driving simulation. The experimental task developed for this study allowed us to explore if and how two different emotional states can affect the way drivers divide their attention between a central driving-related task and a peripheral visual task. Our results showed that scared drivers presented lower reaction times at the central task compared to relaxed drivers. On the contrary, the emotional state did not affect the performance at the peripheral task, which revealed instead a significant effect of the eccentricity at which the visual stimuli were presented, influencing both the accuracy of targets' perception and participants' reaction times.

Keywords: ADAS , Attention , Emotions , Virtual reality

The wind has been a natural and renewable resource used for professional and recreational maritime transportation of small and large vessels since human history. Sailing is making a comeback due to the growing focus on sustainability, accelerated by the recent global energy crisis. Seafarers rely on wind and bearing angle visualization to navigate efficiently and safely, thanks to the use of sensors and compasses. This paper focuses on Augmented Reality in Head-Mounted Displays visualization of wind and bearing angle data. We analyzed the literature and generated a heatmap of the used areas in the user's field of view. Second, we designed and implemented two interfaces that use two different visualization techniques: Boat Stabilized (BS) and Head Stabilized (HS). We compared them in between the subject experiment (N = 44), using a simulated Virtual Reality simulator of the sailing scenario. The user's primary task is wind events recognition, while obstacles (buoys) detection is secondary. We measured both task errors and reaction time, and submit NASA RTLX, SUS, UEQ, and visive auditive and kinesthetic (VAK) questionnaires. We found that BS has a significantly lower reaction time and better usability in the primary and secondary tasks. Both visualization techniques have similar users perceived cognitive load and user experience evaluation. VAK test showed that BS is better for kinaesthetic types and HS is better for visual types.

Keywords: Augmented reality , Human–computer interaction , Nautical , Navigation , Sailing , User study

This article introduces a methodology for conducting comparative evaluations of vibration-induced discomfort. The aim is to outline a procedure specifically focused on assessing and comparing the discomfort caused by vibrations. The article emphasizes the metrics that can effectively quantify vibration-induced discomfort and provides insights on utilizing available information to facilitate the assessment of differences observed during the comparisons. The study also addresses the selection of appropriate target scenarios and test environments within the context of the comparative evaluation procedure. A practical case study is presented, highlighting the comparison of wheel corner concepts in the development of new vehicle architectures. Currently, the evaluation criteria and difference thresholds available allow for comparative evaluations within a limited range of vehicle vibration characteristics.

Keywords: Comfort , Comparative evaluation , Ride , Vehicle vibration