Product design and engineering

Recent advancements in additive manufacturing have enabled the design of tailored lattice structures, suitable for a range of applications, including biomedical implants. The design of lattice structures for biomedical applications requires accurate prediction of both stiffness and strength. This study presents a numerical framework to estimate the effective elastic properties and limit stresses of periodic lattice structures using a strain energy-based homogenization method combined with an efficient method to assess limit stresses along the different directions of the lattice structures. Four cell topologies (ACC, BCC, SC-BCC, F2CC) with varying strut diameters were analysed. The effective elastic constants were computed by applying periodic boundary conditions to the representative volume element of the lattice structure. To estimate the effective limit stresses, a method based on the volume-averaged stress over a subset of the most stressed elements (Ω) was proposed. Three selection strategies for Ω were developed and evaluated through sensitivity analyses. Results show that the estimated limit stresses strongly depends on the definition of Ω. The proposed method enables early-stage design of lattice-based implants with tailored mechanical behaviour and controlled failure limits, enhancing safety and biological integration, contributing to the development of computational tools for patient-specific implant design.

Keywords: Additive manufacturing , Finite Element Analysis , Homogenization , Lattice structure , Osseointegration

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

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

In this research, the energy absorption and plastic deformation of circular polyethylene tubes under lateral compression were investigated, comparing empty tubes with those filled with polyurethane foam. The effects of tube length, diameter, wall thickness, and filler density on load-bearing capacity and energy absorption were evaluated. Absorbed energy and lateral load were found to increase with tube length, although the ductile response of polyethylene produced pronounced fluctuations in the load–displacement curve. Diameter influenced the two configurations differently: in empty tubes, smaller diameters yielded greater energy absorption, whereas in foam-filled tubes, larger diameters increased the flattening load and total absorbed energy, underscoring the critical role of diameter in foam-filled systems. Increasing wall thickness enhanced energy absorption, but polyurethane-foam filling was more effective and yielded a more consistent, predictable load–displacement response. Foam-filled tubes outperformed empty tubes overall; dominant damage mechanisms were identified as foam fracture, crushing, and densification. For applications prioritizing structural efficiency and specific absorbed energy (SAE), the use of higher-density polyurethane foam is recommended. Adhesion between the foam and the tube's inner surface significantly increased peak load capacity. After relaxation, a uniform diameter reduction of approximately 12.7% was observed across specimens, indicating consistency in the final morphology. These findings provide guidance for the design of load-bearing systems employing polyethylene tubes and polyurethane foam.

Keywords: Energy absorbing , Lateral compression , Plastic deformation , Polyethylene tubes , Polyurethane foam

The EU-DEMO is one of the most ambitious projects of EUROfusion, aimed at designing a prototype of a nuclear fusion power plant. In 2025 a new Low-Aspect-Ratio (LAR) configuration has been introduced, replacing the past baseline by changing the aspect ratio (A) of the tokamak from 3.1 to 2.8. The LAR has several benefits from the divertor point of view, the main one is the lower heat load on the plasma facing components (PFCs). The peak heat flux to the divertor during reattachment decreased, with respect to the previous EU-DEMO configuration, by about 45%, from ≈82 MW/m2 to ≈44 MW/m2. This work presents the design of the divertor system in the LAR configuration by adopting System Engineering (SE) approach. Starting from previous baseline, the current design is updated with aim of improving the manufacturing, shielding and structural performances. Using the SE approach, previously implemented features can be transferred and modified in a rational way in the new LAR configuration. New PFCs have been proposed as well as new cooling layout for the cassette body. The inboard vertical target design has been modified based on the results obtained from the previous baseline, aiming to improve the shielding performance and reduce the temperature of the supports in normal operations.

Keywords: Divertor , EU-DEMO , Eurofer97 , Systems engineering , Virtual prototyping

In the context of EUROfusion activities for the development of the DEMO reactor design, the divertor configuration is a major challenge. The current conceptual divertor design is based on the use of EUROFER97 for the divertor cassette body, while tungsten monoblocks bonded to CuCrZr pipes are used for plasma-facing targets. The evaluations developed to identify the best water coolant thermal–hydraulic conditions avoiding material embrittlement (for EUROFER 97) and softening/hardening (for copper alloy pipes) led to the identification of a new divertor baseline solution, based on the new cooling water operating conditions, named Divertor Single Null High-Temperature (SNHT). Such conditions require water at relatively high temperature (295 °C) and pressure (15.5 MPa), posing new challenging issues related to the general layout of the divertor cassette, its structural robustness and the manufacturing technologies. This work presents a comparative assessment between two different solutions proposed for the design and manufacturing of the divertor cassette body. A preliminary structural assessment and technological parameters are considered, as well as shielding and thermo-hydraulic performances.

Keywords: Divertor , EU-DEMO , Eurofer97

Additive Manufacturing (AM) is being explored as a promising solution for producing complex components in nuclear fusion plants, which are still under development. Traditional manufacturing struggles with the intricate geometries and customization required for these parts, making AM an attractive alternative due to its design flexibility and cost-effectiveness. This paper investigates the potential of AM—specifically Laser Powder Bed Fusion (L-PBF)—in fabricating the Outboard Target Body (OTB) of the DEMO divertor, a key component in controlling plasma impurities and heat. The OTB must meet strict technical and functional requirements, and AM offers the possibility to optimize its design while integrating advanced cooling channels and complex shapes that are difficult to achieve with conventional methods. The study evaluates the structural performance and fluid dynamics of the OTB prototype, considering how AM can influence design improvements and enable more efficient production. Overall, AM represents a critical innovation in advancing fusion reactor component manufacturing.

Keywords: Additive Manufacturing , DEMO , L-PBF

Image-generation tools have been widely adopted in product conceptual design, showing promise in supporting cognitive activities and fostering creativity. However, existing studies have primarily focused on the aggregate-level impact, overlooking individual differences in designers' cognitive styles, making it difficult for AI to understand and adapt to the needs of different groups. To fill this gap, we aim to explore whether and how image-generation tools affect designers' cognitive styles and to analyze the relationship between cognitive style and design performance. Through a within-subject experiment, we invited 28 designers to complete conceptual design tasks under SK-condition (traditional sketching) and AI-condition (image-generation tools). We found that AI-condition significantly influenced designers' cognitive styles, with approximately 50% of designers exhibiting cognitive style shifts. Although changes in cognitive style did not have a significant impact on design performance, there was a significant association between cognitive style and design performance under AI-condition. Designers identified as Treasure Hunters performed best in novelty, variety, and fluency, while those exhibiting Focused Prober style, traditionally associated with experts, performed worse under AI-condition. These empirical findings provide valuable insights for customising tools and educational approaches that align with the needs of different cognitive styles.

Keywords: cognitive process , cognitive style , design performance , Generative artificial intelligence , product conceptual design

AbstractA feasibility study of a new testing facility, i.e., the Volumetric Neutron Source (VNS) in a tokamak configuration, was initiated in 2023 and is now under way to address potential showstoppers. Key outcomes of the engineering activities are presented in [1] and the latest improvements in [2]. The main goal of the VNS is to provide a realistic environment to test the in-vessel components of fusion reactors, in particular the tritium-breeding blanket. Lessons learned during previous years of DEMO development point to the need for thorough nuclear design integration already at the level of the basic machine design; hence, issues related to the maintenance of the in-vessel components have been addressed at a basic level. The work presented here describes the remote maintenance strategy for VNS blanket segments, which is an adaptation of the concept proposed for DEMO in previous years [3]. The work discusses the basic approach for the development of an integrated remote blanket strategy for the VNS blanket. Consistent with the initial requirements of the machine, the remote replacement sequence of the blankets, the potential list of the required tools and transporter, and the conceptual design of some of the main tools are presented and discussed in this article.

Keywords: CAD , Conceptual design , FEM , Remote handling , Volumetric neutron source

The development of a closed tritium fuel cycle is essential for the sustainable operation of future fusion power plants. Within the EUROfusion roadmap, the Water-Cooled Lithium Lead (WCLL) breeding blanket is a key candidate for the Demonstration Fusion Power Reactor (DEMO). It uses pressurized water as coolant and a liquid lithium-lead (LiPb) eutectic alloy as both breeder and neutron multiplier. The current WCLL design features modular inboard and outboard Breeding Units (BUs) composed of helical Double Wall Tubes (DWTs) immersed in LiPb. This configuration improves heat removal and reduces the water inventory in the Breeding Zone, thereby potentially increasing tritium generation. This work presents an assessment of the WCLL DEMO nuclear performances in terms of shielding effectiveness and tritium self-sufficiency, based on 3D radiation transport simulations performed using the Monte Carlo MCNP code and JEFF nuclear data libraries. A detailed MCNP model has been developed, including a fully heterogeneous representation of the Breeding Zone and first wall (FW) water channels. Radial profiles of fast and total neutron fluxes, along with nuclear heating, are evaluated at the equatorial level, providing 3D maps of these quantities as well. The total Tritium Breeding Ratio (TBR) has been evaluated, accounting for contributions from both the BZ and LiPb manifolds. To further enhance tritium generation and support the long-term viability of the WCLL concept, design modifications to the latest layout have been explored through a prospective approach. The effectiveness of these modifications has been assessed by means of parametric studies and discussed in light of their potential impact on overall reactor performance.

Keywords: Breeding blanket , DEMO , MCNP , Neutronics , Tritium , WCLL

The rise of automated vehicles marks a major shift in the transportation landscape, yet widespread public scepticism remains a barrier to their acceptance. Among the key challenges is the issue of trust, which significantly influences users' willingness to adopt self-driving technologies. This study explores the potential of Biophilic design -a concept rooted in the human affinity for nature- to improve trust and comfort within automated vehicle interiors. By incorporating natural elements such as materials, lighting, and visual aesthetics, the vehicle environment can become more psychologically supportive. This human-centred approach may not only enhance user experience but also promote broader acceptance of autonomous vehicles.

Keywords: Automated vehicles , Comfort Driving , Human-Technology Interaction , Pleasant Design , User Experience

This study investigates the development of workwear designed to withstand harsh conditions and support physically demanding tasks. Its central aim is to create garments that enhance workers' comfort and mobility by optimizing ergonomic and anthropometric factors. First of all, expert surveys were collected, and the importance of posture adaptability and material comfort was highlighted. To investigate realistic body–garment interactions, the 3D body scans of the upper body from 34 participants in common working poses were captured. These scans revealed the zones of high deformation, guiding the placement of elastic inserts to improve flexibility in targeted areas. The redesigned garments underwent a two-stage evaluation process. First, Clo3D virtual fittings provided qualitative insights into overall jacket fit and movement behavior. Next, stress and strain mapping offered quantitative validation, showing that fabric stress levels remained below 120 kPa, providing evidence that the added elasticity effectively reduced mechanical load and improved wearability. Expert reviewers confirmed the enhanced fit and functional performance. Overall, the study demonstrates an integrated design strategy that unites textile behavior, body dimensions and biomechanics. This approach not only improves workwear but also offers a transferable framework for developing specialized clothing across other physically intensive professions.

Keywords: anthropometry , strain map , stress map , virtual fitting , workwear optimization

Model-based Systems Engineering (MBSE) has emerged as a decisive approach in complex systems design. Within the MBSE landscape, terminologies such as “approach”, “methodology”, “method”, “process”, and other related definitions, along with synonymous terms, play crucial roles in shaping practices, guiding research, and fostering clarity in communication. However, the interpretation and application of these terms can vary across the literature, which may lead to confusion and inconsistency in their usage. This paper proposes a unified set of MBSE definitions to establish clearer distinctions and improve understanding. To validate the proposed definitions, this paper analyzes recently published journal articles, examining how accurately these terms are applied in real-world studies. By comparing the theoretical definitions with the terminology used in practice, the current paper highlights areas of misapplication and suggests ways to improve clarity and consistency in future research. The goal is to contribute to a more precise and consistent use of terminology within the MBSE community, thereby fostering better communication and a more effective application of these concepts.

Keywords: Approach , Method , Methodology , Model-based Systems Engineering , Taxonomy , Terminology

This paper presents a comparative analysis of widely adopted Model-Based Systems Engineering (MBSE) methodologies, with a particular focus on how they manage traceability and integrate preliminary design aspects. While MBSE offers a structured approach to system development through models, many methodologies fail to ensure consistency across model views or to adequately bridge the gap between high-level system modeling and early design phases such as sizing. The study evaluates ten methodologies using a set of qualitative criteria, including development phases, traceability implementation, design-level support, tooling, language, metamodel, and ontology usage. The analysis reveals recurring gaps, such as limited integration of design calculations, inconsistent traceability mechanisms, and insufficient semantic grounding. Based on these findings, a roadmap is proposed to enhance future MBSE practices by integrating sizing views, defining semantic frameworks, and strengthening traceability verification.

Keywords: Design , MBSE Methodologies , Model-based Systems Engineering , Qualitative Analysis , Traceability

Multi-material additive manufacturing (MMAM) enables integration of multiple materials within single products, but existing design methodologies lack systematic frameworks linking detailed consolidation decisions to product-level functional requirements while preserving functional independence. This paper presents a methodology that extends the conventional design process model with a reverse-traced workflow connecting part-level decisions to higher-level product architecture. By tracing how Design for MMAM (DfMMAM) affects design decisions in reverse, designers can identify the best opportunities to use MMAM based on their project scope. The methodology introduces a Level of Process Integration (LPI) framework based on design novelty that structures redesign scope according to whether changes affect part geometry, component assembly, or function allocation, enabling designers to balance consolidation benefits against validation complexity at each level. Sequential decision-making workflows systematically determine which functions can be co-located within unified components while maintaining functional independence through zone-specific design parameters. The methodology is illustrated through a qualitative case study on trail running shoe design across three integration levels, identifying substantial consolidation potential while establishing the foundation for future quantitative validation. Unlike existing approaches limited to part-level redesign, this framework traces detailed consolidation decisions back to product architecture trade-offs, clarifying redesign scope and validation rigor required at each integration level.

Keywords: Design for MMAM (DfMMAM) , function combination , function sharing , Level of Process Integration (LPI) , Multi-Material Additive Manufacturing (MMAM) , part consolidation , product architecture

The conservation of submerged cultural heritage is increasingly prioritized, especially after the adoption of frameworks such as the 2001 UNESCO Convention on the Protection of the Underwater Cultural Heritage. The degradation of underwater archaeological sites, exacerbated by harsh marine conditions, requires effective in-situ restoration and environmental monitoring. Traditional approaches often rely on separate tools for mortar injection, water sampling, and sediment analysis, leading to logistical inefficiencies and operational challenges for divers. This study presents a novel battery-powered, multipurpose underwater tool designed to support and improve conservation work conducted by archaeologists and restorers. The device addresses multiple operational needs in a single solution, allowing underwater restorers to perform hydraulic mortar injection for structural consolidation, collect water samples for environmental monitoring, and extract sediment for archaeological analysis. The tool features a modular architecture, an ergonomic design for diver usability, a precision extrusion system for mortar delivery, and a rotating carousel with interchangeable cartridges. By combining these capabilities in one compact instrument, the device enhances the efficiency of underwater conservation and monitoring efforts. This integrated approach reduces the equipment burden, simplifies logistics, and enables faster, more flexible field interventions. Ultimately, the proposed system contributes to more sustainable and effective management of submerged cultural heritage, promoting more responsive and streamlined underwater conservation efforts.

Keywords: Product design , Underwater cultural heritage , Underwater injector device , Underwater sampling device

Monitoring marine environments is essential for understanding ecological dynamics and preserving underwater sites of scientific and cultural interest. While autonomous robotic systems can cover large areas and collect high-quality water data, scientific divers remain indispensable for survey operations due to their direct observations and selective sampling. However, underwater navigation presents significant challenges for researchers, including poor visibility, marine currents, and the absence of GNSS signals. To address these challenges, this study proposes the conceptual design of a motorized smart buoy capable of autonomous environmental monitoring and providing operational support to divers. The system integrates a suite of sensors for real-time measurement of physicochemical water parameters, a GNSS module for surface localization, and an acoustic positioning system to enhance underwater navigation. This system determines the diver's position by emitting and receiving acoustic signals. Once the position is calculated, the information is transmitted directly to the diver's tablet, enabling real-time awareness of their location, improving navigational safety, and allowing the collection of georeferenced data for more accurate environmental analysis. Furthermore, the implementation of Deep Reinforcement Learning (DRL) algorithms has been considered to optimize the trajectory of the smart buoy in dynamic marine environments, enhancing energy efficiency and monitoring accuracy. The proposed system represents a significant advancement in marine ecosystem monitoring, combining operational autonomy with adaptability to diverse application scenarios.

Keywords: Deep Reinforcement Learning (DRL) , Diver support , Marine monitoring , Smart buoy

The concept of User Experience (UX) in design has evolved beyond usability and aesthetics to encompass broader dimensions of emotional, cognitive, and social wellbeing. This paper explores the intersection of UX and wellbeing, proposing a shift in design thinking toward experience-driven, human-centered approaches that support holistic wellbeing. Drawing on interdisciplinary research from psychology, environmental science, human–computer interaction, and architecture, the study highlights the diverse methods and tools used to assess wellbeing, including self-reports, physiological measures, and digital technologies. It also examines how design can influence wellbeing through user-centered, positive, and ethical frameworks, addressing key challenges in conceptual clarity, methodological rigor, and practical implementation. The paper concludes with a research agenda focused on integrating wellbeing into UX design through new assessment methods, cross-disciplinary collaboration, and development of culturally sensitive, sustainable design principles. By aligning UX with wellbeing, the study aims to guide future research and practice in creating more meaningful, engaging, and health-promoting user experiences.

Keywords: Design for wellbeing , Design methods , Hedonism , Pleasure , User experience

With the increasing attention paid to sustainability and sustainable consumption, many products are redesigned to diminish their environmental footprint. This is also triggered by changes in legislation and the growing consumers' interest in what is supposed to be more environmentally friendly. As a consequence, more and more products are getting certified by governmental and other bodies. However, the proliferation of eco-labels leads to consumers' difficulty in distinguishing them in terms of their relevance, actual contribution to sustainability, and genuineness. In this context, the aim of the paper is to collect from the literature and catalog the design factors influencing the effectiveness of eco-labels and other forms of sustainability- and environment-related communication. The main outcome is the presentation of recommendations as a first core of design guidelines for products including eco-labels. These guidelines, seen as the final goal of this research, should support designers in making appropriate choices when designing products including eco-labels while willing to convey sustainability-related information most successfully and effectively. However, this study also highlights that much research is still needed to get knowledge about eco-labels' design and support designers appropriately. Hence, the paper stresses the large number of areas requiring further investigation and most pressing open issues.

Keywords: Certification , Eco-Labels , Logos , Recommendations , Sustainable design

Origami-inspired design and additive manufacturing enable the rapid fabrication of compact parallel mechanisms with integrated compliance and reduced assembly complexity. This article presents OriDelta, an origami-inspired Delta robot (137 × 158 × 84 mm) fabricated via multimaterial extrusion additive manufacturing with compliant flexural joints. Experimental validation using optical motion capture revealed a systematic, configuration-dependent platform tilt arising from the interaction between mechanism geometry and flexure joint compliance. This parasitic motion exhibits a strong linear correlation with platform position and directly contributes to the positioning error. Exploiting this predictability, we develop a two-stage feedforward compensation model to predict tilt from commanded positions and correct the resulting position error. The proposed approach reduced the rms positioning error to 1.21 ± 0.53 mm, corresponding to an average improvement of 50.2% in kinematic accuracy across all trajectories and protocols. These results demonstrate the effectiveness of model-based compensation in compliant origami mechanisms and provide quantitative insight into the role of compliance-induced parasitic motion in origami-inspired parallel manipulators.

Keywords: Compliant hinges , kinematic model , origami design , parallel robot

In response to the growing need for adaptive optimization algorithms capable of handling complex, multimodal, and high-dimensional search spaces, this paper introduces the Structured Random Cycle-guided Algorithm (SRCA). SRCA is not presented as a fundamentally new optimization paradigm, but rather as an architectural synthesis and a unified adaptive framework for dynamic operator selection. Based on a cycle-structured architecture, directional and stochastic search behaviors are dynamically selected at the individual level. The algorithm orchestrates well-established structured movements with a diverse pool of stochastic exploration strategies, enabling a coherent and adaptive balance between exploration and exploitation throughout the optimization process. Unlike traditional metaheuristics that rely on fixed behavioral roles or static movement schemes, SRCA allows each individual to adapt its search strategy based on real-time population feedback, monitored through convergence and dispersion indicators. The performance of SRCA is quantitatively assessed under strictly identical experimental conditions on a comprehensive set of 23 benchmark functions, including multimodal and high-dimensional problems, as well as on six classical constrained engineering design problems. Numerical results demonstrate competitive convergence reliability and robustness across diverse optimization tasks, confirming the effectiveness of the proposed adaptive cycle-based framework.

Keywords: benchmark functions , constrained optimization , Metaheuristic algorithms , optimization , structured random cycle-guided algorithm