Design methods for mobility

This work proposes a multi-domain modelling methodology to support the design of new battery packs for automotive applications. The methodology allows electro-thermal evaluation of different spatial arrangements of the storage cells by exploiting the implementation of numerical and geometrical battery pack models. Concerning the case study on Li-NMC battery technology, the study has completed the electro-thermal characterization of the storage cells starting from the collected experimental data, considering both the thermal interactions among cells and the effects of the state of health. This work also investigates the effects of forced air-cooling systems focusing on battery pack hot spots and temperature distributions. The results show a good fit between numerical models and data obtained from single-cell experiments. The virtual linking of geometric and numerical lumped-parameter models proved to be effective in rapid battery pack prototyping for electric vehicles, helping designers and manufacturers find suitable solutions for specific automotive applications.

Keywords: Battery electric vehicles , Electro-thermal analysis , Multi-domain modelling

The reliability and availability of a Jet Unmanned Aerial Vehicle (JUAV) for balloon downing are evaluated in this third part of the paper. The paper delves into the challenges faced by traditional air defence systems in countering high-altitude balloons, leading to the proposal of substituting missiles with Unmanned Aerial Vehicles (UAVs), specifically the Jet Unmanned Aerial Vehicle (JUAV). The best solution found in the previous section is a derivation of the 1:6 scale RC model of the Lockheed F104C. This is designed for balloon downing, and the essay meticulously analyses its reliability, failure probabilities, and maintenance strategies for various subsystems. The engine is replaced with a more powerful micro-jet, and an 84 mm recoilless cannon is added at the base of the tail. The scaled-down model can use most data derived from the full-scale airplane flight manual, corrected for larger thrust-to-weight and lower wing-loading. Several adjustments and additions are made on sensors, autopilot, On-Line Diagnostic System, communication system, and firing system to increase the reliability of the system. Due to the relatively short design life of the RC model, the Time Between Overhaul (TBO) of the UAV is reduced to 25 h. Consequently, the study emphasizes the importance of simplicity, operational reliability, and adaptability in the development and assessment of modern missile defence systems. The reliability of the JUAVI is presented as 98.14% for 50 consecutive fully automatic missions, highlighting its potential significance in bolstering national security.

Keywords: Aerospace Engineering , availability , balloon killer , cost-effective , D T Pham , Design , Mechanical Engineering , Mechanical Engineering Design , Mechanics , re-usable , Reliability , Transport & Vehicle Engineering , UAV , UK , University of Birmingham

Submerged lifting surfaces technology, born in the early 1900s, allows boats to lift the hull above the water and, in some cases, halves the resistance compared to dislocated and planning boats. This paper illustrates the state-of-the-art on hydrofoil technology, highlighting the fundamental aspects of the study of submerged wings and focusing on the problems that this technology presents, evaluating the solutions currently used to optimize its work. Key aspects of hydrofoil design are addressed, such as the choice of geometric configurations and two-dimensional profiles suitable for each type of mission. This results in addressing issues associated with cavitation and ventilation and emphasizing structural solutions that reduce these phenomena, thus improving hydrofoil efficiency. The study analyses and discusses the problems of wing systems used in existing applications, with the aim of developing a sustainable transport technology compatible with ecological propulsions such as hydrogen and electric.

Keywords: green , hydrodynamics , hydrofoil , sustainable

Environmental sustainability, greenhouse emissions, and air pollution reduction are among the major drivers for the electrification of the transport and mobility sector. In this regard, industry and academia have started developing electrified solutions for the off-highway industry, but it comes with high development costs. Modeling and simulation can greatly help system-level design but building the mathematical model of an entire machinery is not trivial. In this regard, using physics-based industrial-oriented modeling software like Simscape can simplify it, especially for small niche manufacturers, which usually have lower resources. In this paper, an electrified material handler is modeled using Simscape. The main movements of the machinery are compared with experimental data, and a good match is found for hydraulic pressure and flow. Even if the modeling of other subsystems is needed for more in-depth and accurate analysis, the paper already shows how modern industrial-oriented modeling software can be used to model complex subsystems and to get sensible results. Taking advantage of transient-state system design is indeed key to better assessing energy consumption and getting at a better overall system design, even for small and niche manufacturers.

Keywords: Electrification , Modeling , Off-highway machinery , Simulation

Remaining useful life prediction guarantees a reliable and safe operation of turbofan engines. Long-range dependence (LRD) and heavy-tailed characteristics of degradation modeling make this method advantageous for the prediction of RUL. In this study, we propose fractional Lévy stable motion for degradation modeling. First, we define fractional Lévy stable motion simulation algorithms. Then, we demonstrate the LRD and heavy-tailed property of fLsm to provide support for the model. The proposed method is validated with the C-MAPSS dataset obtained from the turbofan engine. Principle components analysis (PCA) is conducted to extract sources of variance. Experimental data show that the predictive model based on fLsm with exponential drift exhibits superior accuracy relative to the existing methods.

Keywords: feature fusion , fractional Lévy stable motion , long-range dependence , remaining useful life , self-similar

Sustainability-oriented new product development process is becoming of key importance in many sectors of the industry. Especially in the automotive industry, it plays a major role as this sector is historically associated with resource-intensive production and fossil fuel consumption, and thus has to implement solutions that will contribute to restraint of climate change. Manufacturing companies are currently faced with the challenge of adapting their business models to changing market expectations and requirements resulting from the sustainable development path. Moreover, the development of the new digital factories and pressure from the legislators require adjustment of existing Product Lifecycle Management systems. To enhance the concept of the Green Product Lifecycle Management which is still under development, in this work we propose a new three-step methodology composed of three main steps: (1) assessing indicators' importance for sustainable business goals and business models, (2) assessing indicators and their importance in the automotive industry, (3) assessing “greenness” of the product. This complex approach is innovative as it is based on the business-oriented perspective. Selecting suitable business goals and corresponding business models leads to the selection of the appropriate subset of green indicators. Several more aspects are taken into account in this holistic analysis: the indicator's features, relevance for the company, importance to sustainable business goals, importance in terms of subsectors of the automotive industry as well as environmental, economic, and social impact. This approach enables the company to compute the value of the greenness of the product in reference to the key green indicators.

Keywords: Automotive industry , Business goals , Circular economy , Digital manufacturing , Product lifecycle management , Sustainability

This paper presents a practical method for analyzing drivers' eye movements, providing a valuable tool for understanding their behavior during driving simulations. The method, which utilizes an image processing technique, addresses the challenges when the driver's attention is on points without information about the image depth. The screen image changes or moves with the simulation. It allows us to identify the gaze position relative to the road, determining whether the glance is inside or outside. This is achieved by transforming RGB images (frames) collected by the eye-tracker video camera into a b/w image using the Canny filter. This filter can identify objects' contours by evaluating the change in color of their surfaces. A window is then applied to these new images to extract information about the gaze position in the real world. Four drivers were used as a sample for the method's testing. The findings demonstrate various driver variations and a disparity between driving in curved and rectilinear segments. The gaze is typically inside the road in curved sections, whereas in rectilinear sections, the gaze is frequently outside.

Keywords: driver behavior , driving simulator , eye-tracker , gaze analysis , image processing

The topology optimization methodology is widely utilized in industrial engineering for designing lightweight and efficient components. In this framework, considering natural frequencies is crucial for adequately designing components and structures exposed to dynamic loads, as in aerospace or automotive applications. The scientific community has shown the efficiency of Bi-directional Evolutionary Structural Optimization (BESO), showcasing its ability to converge towards optimal solid-void or bi-material solutions for a wide range of frequency optimization problems in continuum structures. However, these methods show limits when the complexity of the domain volume increases; thus, they are well-suited for academic case studies but may fail when dealing with industrial applications that require more complex shapes. The connectivity of the structures resulting from the optimization also plays a fundamental role in choosing the best optimization approach, as some available commercial and open-source codes nowadays return unfeasible sparse structures. An improved voxel-based BESO algorithm has been developed in this work to cope with current limits in lightweight structure optimization. A significant case study has been developed to evaluate the performances of the new methodology and compare it with existing algorithms. In contrast to previous studies, the method we developed guarantees that the final structure respects constraints on the initial design volume and that the structure's connection is preserved, thus enabling the manufacturing of the component with Additive Manufacturing technologies. The proposed approach can be complemented by smoothing algorithms to obtain a structure with externally appealing surfaces.

Keywords: Additive manufacturing , Bi-directional evolutionary structural optimization (BESO) , Natural frequency , Optimal design , Topology optimization

Air pollution causes many diseases and is a major environmental threat, therefore, it is essential to monitor and improve the air quality. With this work, we aim to assess atmospheric pollution using drone-mounted air sensors, with specific applications in Vietnam. We aim to measure Green-House Gas (GHG) emissions and other pollutants in urban and non-urban areas of interest including, but not limited to landfills and airports, to evaluate the effects of pollution on climate and health. The project will use a novel and creative approach to collect three-dimensional atmospheric data using smart sensors mounted on Unmanned Aerial Vehicles (UAVs). UAVs have been extensively applied in recent years, both in Vietnam and on a global scale, to multiple fields and with different scopes. Surveying, crop monitoring, irrigation and fertilization, surveillance and rescue support, and 2D and 3D mapping, are just a few examples of how UAVs can be used for agriculture, archaeology, forestry, urban planning, and architecture. In this project, we develop an integrated system of UAVs and smart sensors for air quality monitoring. To develop mitigation and adaptation strategies for reducing the environmental impact of transport, it is imperative to assess the emission sources and trends. Therefore, we are developing a system able to collect comprehensive atmospheric data using remote aerosol sampling, and chemical speciation. Furthermore, the potential of using smart sensors on other flying devices is explored.

Keywords: Air pollution , air quality monitoring , Unmanned Aerial Vehicles

The increasing emissions of greenhouse gases (GHG) and pollutants like particulate matter and nitrogen oxides (NOx) have led to environmental concerns. Hybrid and electric powertrains are being introduced as means to reduce pollutant emissions, especially at the local level. Additionally, the finite availability of fossil fuel sources, which are used to produce gasoline and diesel, highlights the need for alternative technical solutions. One approach to partly address these issues is lightweighting, which involves reducing the weight of vehicles to minimize their impact during the use phase. Mathematical models are employed to simulate the longitudinal dynamics of vehicles and estimate the energy required to accomplish driving missions. Appropriate metrics have been developed to quantify energy-saving effects that, in addition, can support the decision making, design, and development phase of future vehicles. To facilitate this process, it would be useful to build a database of ERV (Energy Reduction Value) and FRV (Fuel Reduction Value) figures derived through a unified procedure. Such a database would be useful in evaluating the effectiveness of vehicle lightweighting and its impact on energy consumption and pollutant emissions. The last phase of the analysis is the assessment of the overall reduction in the environmental impact of the vehicle throughout its life cycle by using the LCA (Life Cycle Assessment) approach. From this study, it was possible to conclude that lightweighting can be an appropriate solution to improve the energy efficiency of vehicles and that appropriate metrics, can support the development of new car models. The potential to integrate enhanced energy efficiency, lower emissions, and higher safety features into our everyday vehicles would represent a significant advancement in the automotive industry. There is a gap in the scientific literature on the effects of lightweighting on vehicle dynamics and energy usage which deserves to be investigated.

Reduction of aerodynamic drag is a crucial aspect of cycling. Currently, to optimize aerodynamics, athletes rely on wind tunnel tests or CFD simulations. Despite the undeniable advantage of the latter in terms of cost and time effort, they still require validation through wind tunnel measurements. This paper introduces a novel workflow that aims to streamline and accelerate the aerodynamic analysis process for cycling. The proposed workflow focuses on utilizing a full-sized mannequin and integrates CFD simulations, wind tunnel validation, 3D scanning, and rigging animation techniques. The animation technique involves the creation of a virtual skeleton that allows the scanned model to be posed in any desired position, eliminating the need for physical adjustments and repetitive wind tunnel testing. To showcase the time-saving advantages of this approach, a steady CFD analysis is conducted to compare six different configurations obtained using the rigged model, in terms of drag areas, velocity streamlines, and pressure coefficient distribution. The obtained data trends closely align with previous similar studies in the literature and the results from the simulation have been compared with wind tunnel test measurements. Additionally, future adjustments to the position or equipment can be easily made using the virtual rigging model. By integrating virtual techniques with CFD simulations and wind tunnel validation, the proposed workflow enables rapid evaluation of aerodynamic performance in a more efficient and cost-effective manner.

Keywords: CFD , Cyclist , Rigging Animation

The vertebral column represents an essential element for support, mobility, and the protection of the central nervous system. Various pathologies can compromise these vital functions, leading to pain and a decrease in the quality of life. Within the scope of this study, a novel redesign of the Intersomatic Cage, traditionally used in the presence of discopathy, was proposed. The adoption of additive manufacturing technology allowed for the creation of highly complex geometries, focusing on the lumbosacral tract, particularly on the L4-L5 and L5-S1 intervertebral discs. In addition to the tensile analysis carried out using Finite Element Analysis (FEA) in static simulations, a parallel study on the range of motion (ROM) of the aforementioned vertebral pairs was conducted. The ROM represents the relative movement range between various vertebral pairs. The introduction of the intersomatic cage between the vertebrae, replacing the pulpy nucleus of the intervertebral disc, could influence the ROM, thus having significant clinical implications. For the analysis, the ligaments were modelled using a 1D approach. Their constraint reaction and deformability upon load application were analysed to better understand the potential biomechanical implications arising from the adoption of the cages. During the FEA simulations, two types of cages were analysed: LLIF for L4-L5 and ALIF for L5-S1, subjecting them to four different loading conditions. The results indicate that the stresses exhibited by cages with a NET structure are generally lower compared to those of traditional cages. This stress reduction in cages with NET structure suggests a more optimal load distribution, but it is essential to assess potential repercussions on the surrounding bone structure.

Keywords: Biomedical computer aided design , CAE method , Magnetic resonance imaging , Range of motion

Composite materials, pioneered by aerospace engineering due to their lightness, strength, and durability properties, are increasingly adopted in the high-performance automotive sector. Besides the acknowledged composite components' performance, enabled lightweighting is becoming even more crucial for energy efficiency, and therefore emissions along vehicle use phase from a decarbonization perspective. However, their use entails energy-intensive and polluting processes involved in the production of raw materials, manufacturing processes, and particularly their end-of-life disposal. Carbon footprint is the established indicator to assess the environmental impact of climate-changing factors on products or services. Research on different carbon footprint sources reduction is increasing, and even the European Composites Industry Association is demanding the development of specific Design for Sustainability approaches. This paper analyzes the early strategies for providing low-carbon aerospace and automotive composite components by design. The goal is to enable design approaches that consider the material life cycle from product and process design, material selection and fabrication, to eventual recycling and reuse. The investigation includes the design approaches and tools, and the aspects concerning ultimate trends of materials development, shapes generation, and manufacturing processes. Among these, we discuss the potential role of emerging technologies such as digital intelligence, Biocomposites, biomimicry, generative AI, and additive manufacturing. The aim is to identify the framework of possible drivers for Design for Sustainability approaches, rethinking lightweight products lifecycles and highlighting the resulting challenges and future developments. Moreover, as practical examples, a few innovative cases are provided to prove the effective potentials of such guidelines. The conclusive remarks discuss the advantages and disadvantages of the design drivers and the need for assessment and validation through vehicle Life Cycle Assessment approaches.

The concept of an innovative human–machine interface and interaction modes based on virtual and augmented reality technologies for airport control towers has been developed with the aim of increasing the human performances and situational awareness of air traffic control operators. By presenting digital information through see-through head-mounted displays superimposed over the out-of-the-tower view, the proposed interface should stimulate controllers to operate in a head-up position and, therefore, reduce the number of switches between a head-up and a head-down position even in low visibility conditions. This paper introduces the developed interface and describes the exercises conducted to validate the technical solutions developed, focusing on the simulation platform and exploited technologies, to demonstrate how virtual and augmented reality, along with additional features such as adaptive human–machine interface, multimodal interaction and attention guidance, enable a more natural and effective interaction in the control tower. The results of the human-in-the-loop real-time validation exercises show that the prototype concept is feasible from both an operational and technical perspective, the solution proves to support the air traffic controllers in working in a head-up position more than head-down even with low-visibility operational scenarios, and to lower the time to react in critical or alerting situations with a positive impact on the human performances of the user. While showcasing promising results, this study also identifies certain limitations and opportunities for refinement, aimed at further optimising the efficacy and usability of the proposed interface.

Keywords: Air traffic control , Airport control tower , Augmented reality , Human machine interface , Multimodal interaction , Safety nets

Now a days new products are evaluated in the initial phases of product development in order to identify all design problems as early as possible before the prototype or manufacturing of the product. With advent growth in innovative technologies, simulation and testing of the human centered product designs are being performed using digital models & immersive to semi-immersive environments. There are numerous concepts and methods for this purpose, which have evidently proven to be effective solutions, such as Digital Human Modelling (DHM) or Human Model in the Loop simulations (HMITL), to facilitate ergonomic evaluations without interactions, and Virtual Reality (VR) technology to enable Human in the Loop (HIL) simulations in immersive environments along with interactions. These simulations are performed utilizing various software, which makes the data integration phase a complicated and time taking process. This paper elaborates on a new approach of adapting DHM analysis in a VR simulation for analyzing living space inside a 3D model using a single open-source platform, UNITY 3D. This process is expected to reduce the need for multiple programs during simulations, thereby reducing costs and time while providing uncomplicated visualizations. A use case scenario in view of assessing living space inside a novel aircraft lavatory design with baby table integration is also presented. This paper serves as a step towards inclusive design analysis and predicts its potential in various fields to study ergonomics and interaction of products at the early stage of product development.

Keywords: aircraft cabin design , Digital Human Modeling , Human Centered Design , product development , User Experience , Virtual Reality

In response to the increasing number of traffic accidents, industrialized countries are investing in educational programs to raise awareness of safe driving. The most common type of intervention to reduce risky driving behaviors is the showing of traumatic experience videos related to the occurrence of traffic accidents caused by incorrect and high-risk driving habits. However, the effectiveness of this intervention depends on several factors, including how this content is experienced. Nowadays, thanks to Cinematic Virtual Reality (CVR) technologies, new modalities of video content fruition can be exploited. In this work, we implemented a CVR application to show 360° videos of traffic accidents and evaluate the effectiveness of CVR as an educational intervention tool to improve drivers' attitudes toward traffic safety. A sample of 86 users aged 18 to 56 years answered a questionnaire on Attitudes Toward Traffic Safety Scale (ATTSS) administered before and after the CVR experience. In addition, a user experience questionnaire (UEQ) was administered. The results analysis of ATTSS questionnaires shows that the CVR experience increases risk awareness by inducing greater attention to safety while driving. Finally, the results of the UEQ questionnaire reveal that users positively evaluate the experience of using the system from hedonistic, pragmatic, and usability perspectives.

Keywords: 360 video , Educational Intervention , Traffic Safety , Virtual Reality

In recent years, many industrial companies have embraced new technologies for Industry 4.0, the fourth industrial revolution. This global manufacturing trend connects real-life industry with the virtual world. Digitalization tools play a crucial role in allowing companies to decrease design and production costs, as well as accelerate the product development process. Regarding an actual industrial case study of an Italian automotive company, this work focuses on the use of digital technologies in designing complex manufacturing systems, showing the benefits that can be obtained with respect to traditional methods. Digitalization tools have aided in the design of intricate manufacturing systems that demand advanced automation to optimize the arrangement, workflow, and equipment configuration within a manufacturing facility or production line. After examining the features of the virtual approach employed by the considered company, the virtual commissioning of a screwing station for an electric axle assembly line is analyzed in detail to show the efficiency and effectiveness of digitalization.

Keywords: Automotive , Complex Manufacturing Systems , Digital Technologies , Industry 4.0 , Virtual Commissioning

Designers need to be aware early in the design phase of the environmental impact of their choices over the entire product life cycle. This paper proposes an eco-design method to support designers of different categories of electric vehicles, such as self-driving vehicles, cars, shuttles and buses. The methodology developed aims to realize a model for predicting the environmental impact of industrial electric vehicles. The proposed approach exploits machine learning methods to develop models with the design features of a generic electric vehicle, such as vehicle mass and distance traveled during its entire lifetime as independent parameters, to estimate the emissions of new products. The environmental impact indicator for this study is Climate Change, the dependent parameter chosen for the impact model. Machine learning algorithms were trained on training data retrieved from an automatic environmental impact estimation software tool based on an analytical approach. All stages of the product life cycle have been considered in the construction of the database, and the model provides quantitative results that consider the consumption of material and energy resources. Finally, the model is tested by estimating the environmental impact of a tourist shuttle.

Keywords: Data Science , Design , Life Cycle Assessment , Machine Learning , Sustainability

The intervertebral disc (IVD) is a complex biological structure that ensures the spine strength, stability, mobility, and flexibility. This is achieved due to its biphasic nature which is attained by its solid phase (annulus fibrosus) and fluid phases (nucleus pulposus). Hence, the IVD biomechanical response to long-term loads, which is critical as it affects hydration, and nutrients-water transport influencing disc height reduction, has been further explored and mathematically modelled in this paper. An in-vitro study was performed on seven human lumbar spine specimens (L4-5), to assess if the classical rheological models and Nutting's power law can model in a simple way the intermediate characteristics between solid and fluid of the IVD. Creep tests were conducted by applying a static compression load of 500 N for 15 min. A correlation analysis was done (Pearson, p < 0.05) between the model parameters and the maximum value of Disc Height Reduction, followed by a linear regression analysis. In summary, the long-term IVD mechanical behavior was modeled in a simple way, emphasizing that yet there is no mathematical certainty about this mechanical behavior. Hence, a future aim might be to develop intervertebral disc prostheses capable of replicating only the disc mechanical response, without necessarily considering the microscopic-level biological drivers. Therefore, a future goal is to fully understand and model the disc's mechanical response toward the design of new disc prostheses that would consider only the macroscopic aspect, without considering the biological aspects.

Keywords: Creep test , Intervertebral disc , Lumbar spine , Mechanobiology , Spine , Viscoelasticity

In the shipbuilding, construction, automotive, and aerospace industries, welding is still a crucial manufacturing process because it can be utilized to create massive, intricate structures with exact dimensional specifications. These kinds of structures are essential for urbanization considering they are used in applications such as tanks, ships, and bridges. However, one of the most important types of structural damage in welding continues to be fatigue. Therefore, it is necessary to take this phenomenon into account when designing and to assess it while a structure is in use. Although traditional methodologies including strain life, linear elastic fracture mechanics, and stress-based procedures are useful for diagnosing fatigue failures, these techniques are typically geometry restricted, require a lot of computing time, are not self-improving, and have limited automation capabilities. Meanwhile, following the conception of machine learning, which can swiftly discover failure trends, cut costs, and time while also paving the way for automation, many damage problems have shown promise in receiving exceptional solutions. This study seeks to provide a thorough overview of how algorithms of machine learning are utilized to forecast the life span of structures joined with welding. It will also go through their drawbacks and advantages. Specifically, the perspectives examined are from the views of the material type, application, welding method, input parameters, and output parameters. It is seen that input parameters such as arc voltage, welding speed, stress intensity factor range, crack growth parameters, stress histories, thickness, and nugget size influence output parameters in the manner of residual stress, number of cycles to failure, impact strength, and stress concentration factors, amongst others. Steel (including high strength steel and stainless steel) accounted for the highest frequency of material usage, while bridges were the most desired area of application. Meanwhile, the predominant taxonomy of machine learning was the random/hybrid-based type. Thus, the selection of the most appropriate and reliable algorithm for any requisite matter in this area could ultimately be determined, opening new research and development opportunities for automation, testing, structural integrity, structural health monitoring, and damage-tolerant design of welded structures.

Keywords: fatigue , finite element , machine learning , metal , Monte Carlo , neural network , predict , regression , structural health monitoring , weld