Michele Zannoni, Ludovica Rosato, Diego Pucci
et al.
In the context of the digital transition of the Italian textile industry, this paper explores how design can act as a mediator between emerging technologies, sustainable practices, and sector-specific knowledge. The research adopts the perspective of the Transitional Industrial Designer (TID), a figure capable of integrating vertical technical expertise, adaptability to change, interdisciplinary collaboration, and systemic thinking. Through a practice-based experimentation on the virtualization of textile materials, the project investigates the role of design in enabling accessible, scalable, and collaborative processes. The focus is not on technological solutions alone, but on the design practices that mediate complexity and facilitate the adoption of immersive and digital tools across different stakeholders. Structured as an interconnected system rather than a linear workflow, the experimentation combines acquisition, interaction, and archiving of virtual materials to support sustainable, distributed design practices. The outcomes highlight the potential of anticipatory design approaches in activating new modes of interaction with materiality and in supporting the circular transition of Made in Italy industries. Ultimately, the study offers a methodological reflection on how designers can responsibly navigate digital complexity by constructing meaningful, relational, and adaptive project frameworks.
The proliferation of data across the system lifecycle presents both a significant opportunity and a challenge for Engineering Design and Systems Engineering (EDSE). While this "digital thread" has the potential to drive innovation, the fragmented and inaccessible nature of existing datasets hinders method validation, limits reproducibility, and slows research progress. Unlike fields such as computer vision and natural language processing, which benefit from established benchmark ecosystems, engineering design research often relies on small, proprietary, or ad-hoc datasets. This paper addresses this challenge by proposing a systematic framework for a "Map of Datasets in EDSE." The framework is built upon a multi-dimensional taxonomy designed to classify engineering datasets by domain, lifecycle stage, data type, and format, enabling faceted discovery. An architecture for an interactive discovery tool is detailed and demonstrated through a working prototype, employing a knowledge graph data model to capture rich semantic relationships between datasets, tools, and publications. An analysis of the current data landscape reveals underrepresented areas ("data deserts") in early-stage design and system architecture, as well as relatively well-represented areas ("data oases") in predictive maintenance and autonomous systems. The paper identifies key challenges in curation and sustainability and proposes mitigation strategies, laying the groundwork for a dynamic, community-driven resource to accelerate data-centric engineering research.
Florista F. Marimba, Ahmad Faizin, Andreas S. Widodo
et al.
One of the initial problems faced by young interior designers is to make a creative pattern to draw potential consumers’ attention. Their belief in the creative pattern should fit consumers’ expectations. This study scrutinized the relationship between young interior designers and potential consumers about both expectation, designers’ capital, and designers’ strategy to cap-ture the pattern in the design market. To this end, young interior designers (n=100) and potential design consumers (n=100) were recruited as respon-dents. Multiple linear regression and ordinal logisic regression were applied. The data analysis result demonstrated young designers’ marketing patterns to draw potential consumers’ attention. A correlation was found between young designers and design consumers. The expectation, capital, and strategy of designers were found to be interrelated by 48.1%, while those of consumers were interrelated by 28.6%. The research variables, which are designer capital, designer strategy and the two respondent groups, were found to have an impact on the expectation by 94.5%. This study concludes that young designers have a marketing pattern to draw poten-tial consumers’ attention. It showed a relationship between designers’ and consumers’ expectations, designers’ capital or information received by consumers, and designers’ strategy. This study may serve as a refer-ence for young designers’ behaviors when entering the market design.
This paper describes the design process of a smart system monitoring and training the gait and posture of people with Parkinson’s disease. The project aimed to develop an innovative mHealth system and validate it in a laboratory context. The designed solution is supposed to help people in postponing the rise of the most impairing symptoms and prolong autonomy. The project was divided into three main design cycles regarding respectively the design and test of sensory signals, the smart wearable devices transmitting them, and the system interface.
The multidisciplinary team involved in the project followed a User-Centered methodology, involving users in the design process to improve the system’s usability and accessibility.
The adopted methodological strategy led to satisfactory results and proved to be particularly suitable for multidisciplinary design processes involving both human and technological factors related to the development of smart systems targeted to niche users.
Science museums have the important cultural mission of mentoring society in scientific and technological progress. To pursue this objective many resources have been invested in digital communication and marketing, but this is not sufficient to reach audiences that are not engaged with scientific culture. To overcome the challenge of attracting uninterested visitors, some museums have chosen to extend their outreach beyond physical walls occupying highly frequented public spaces. This approach aims to capture the attention of citizens through exhibits and environments that encourage curiosity, entertainment, exploration, creativity, and social connection. By reviewing the international literature and project examples in this field, the paper proposes new audience development strategies for science museums to rethink the relationship between museums and society through a “museum outside the walls” inclusive perspective.
Giuseppe Mincolelli, Gian Andrea Giacobone, Michele Marchi
Nowadays the world is characterized by an increasingly aging society. This phenomenon represents a risk for the sustainability of the healthcare system. One of the factors that can accelerate the consequences of the aging process is sedentary behavior. Currently, there is a large availability of wearable smart devices and mobile applications, that can collect data.
However, some social and functional problems were observed, therefore we believe that there is great room for improvement (Mincolelli et al., 2018).
In addition, the paradigm of the Internet of Things is enabling those applications to share data with other programs and smart devices, which, in turn, can generate an ecosystem of services that can improve the quality of life, not only of the single user, but of many groups of a determined social context.
The contribution presents a case study (PLEINAIR project) that focuses specifically on the development of Human-Centered outdoor smart technologies that can adapt themselves to the necessities of people of all ages and abilities in order to encourage them of taking care of their health.
3D rendering of dynamic face captures is a challenging problem, and it demands improvements on several fronts$\unicode{x2014}$photorealism, efficiency, compatibility, and configurability. We present a novel representation that enables high-quality volumetric rendering of an actor's dynamic facial performances with minimal compute and memory footprint. It runs natively on commodity graphics soft- and hardware, and allows for a graceful trade-off between quality and efficiency. Our method utilizes recent advances in neural rendering, particularly learning discrete radiance manifolds to sparsely sample the scene to model volumetric effects. We achieve efficient modeling by learning a single set of manifolds for the entire dynamic sequence, while implicitly modeling appearance changes as temporal canonical texture. We export a single layered mesh and view-independent RGBA texture video that is compatible with legacy graphics renderers without additional ML integration. We demonstrate our method by rendering dynamic face captures of real actors in a game engine, at comparable photorealism to state-of-the-art neural rendering techniques at previously unseen frame rates.
Data-based methods have gained increasing importance in engineering, especially but not only driven by successes with deep artificial neural networks. Success stories are prevalent, e.g., in areas such as data-driven modeling, control and automation, as well as surrogate modeling for accelerated simulation. Beyond engineering, generative and large-language models are increasingly helping with tasks that, previously, were solely associated with creative human processes. Thus, it seems timely to seek artificial-intelligence-support for engineering design tasks to automate, help with, or accelerate purpose-built designs of engineering systems, e.g., in mechanics and dynamics, where design so far requires a lot of specialized knowledge. However, research-wise, compared to established, predominantly first-principles-based methods, the datasets used for training, validation, and test become an almost inherent part of the overall methodology. Thus, data publishing becomes just as important in (data-driven) engineering science as appropriate descriptions of conventional methodology in publications in the past. This article analyzes the value and challenges of data publishing in mechanics and dynamics, in particular regarding engineering design tasks, showing that the latter raise also challenges and considerations not typical in fields where data-driven methods have been booming originally. Possible ways to deal with these challenges are discussed and a set of examples from across different design problems shows how data publishing can be put into practice. The analysis, discussions, and examples are based on the research experience made in a priority program of the German research foundation focusing on research on artificially intelligent design assistants in mechanics and dynamics.
The catastrophic effects of the Anthropocene are evident. Manifestations of crisis are not only environmental, but also economic, social, political and ethical: combined with the dystopian imaginaries of the future, they suggest the need for a paradigm shift. The Commons are seen as an alternative for a transition to a post-capitalist economy. Yet, Design for social innovation is understood as a humanitarian action and remains linked to the logic of commodification; reason why some call for decolonizing Design from Western abstractions. The focus is on the relationship between Design and Commons, with particular attention to decolonial thinking. Following an action research approach that consisted in “inhabiting” the oasis of Chenini in Tunisia as a Commons in crisis, the idea was to understand the role of Design in the paradigm shift from an extractivist growth economy to a resource economy; Design as attached to situations rather than objects.
Supermassive black holes accreting matter at very high, perhaps even super-Eddington rates appear in the sky as a special class of luminous active galactic nuclei. The Eigenvector 1/quasar main sequence parameter space allows for the definition of easy-to-implement selection criteria in the rest-frame visual and UV spectral ranges. The systematic trends of the main sequence are believed to reflect a change in accretion modes: at high accretion rates, an optically thick, geometrically thick, advection-dominated accretion disk is expected to develop. Even if the physical processes occurring in advection-dominated accretion flows are still not fully understood, a robust inference from the models—supported by a wealth of observational data—is that these extreme quasars should radiate at maximum radiative efficiency for a given black hole mass. A key empirical result is that lines emitted by ionic species of low ionization are mainly broadened because of virial motions even in such extreme radiative conditions. “Virial luminosity” estimates from emission line widths then become possible, in analogy to the scaling laws defined for galaxies. In this contribution, we summarize aspects related to their structure and to the complex interplay between accretion flow and line emitting region, involving dynamics of the line emitting regions, metal content, and spectral energy distribution.
Mechanical drawing. Engineering graphics, Physical and theoretical chemistry
Here, we discuss the possibility of the admixture of baryons to the DM primordial planets, with the DM particles varying in mass from 20 GeV to 100 GeV. We have considered different fractions of admixture particles to form the planet. The mass of the primordial planet made completely of DM ranges from asteroid mass to Neptune mass. However, the mass of primordial planets (admixed with DM and baryonic matter) is found to increase with the fraction of baryonic matter in the planets, and the mass of these objects can go well beyond the mass of Jupiter (around 40 times Jupiter’s mass) and can also approach sub-stellar mass (brown dwarf mass). So far, thousands of exoplanets have been discovered by the Kepler mission and more will be found by NASA’s Transiting Exoplanet Survey Satellite (TESS) mission, which is observing the entire sky to locate planets orbiting the nearest and brightest stars. Many exoplanets, such as exo-Jupiter, discovered so far fall in this mass range, and unsure whether these exoplanets are entirely made of baryons. Some of the exoplanets with a mass several times Jupiter’s mass could be possible signatures of the presence of primordial planets with an admixture of baryonic and DM particles. It is also found that some of these planets could reach even sub-stellar mass (10<sup>32</sup> g), such as that of a brown dwarf. Additionally, even if a small fraction of DM particles is trapped in these objects, the flux of ambient DM particles would be reduced significantly. This could be one of the many reasons for not detecting the DM particles in various experiments, such as XENON1T, etc., as suggested earlier. If two such primordial planets (in a binary system) merge, they will release a lot of energy. The energy released in gravitational waves, as well as the time scale of the merger of these objects, is found to increase with the mass of primordial objects. The frequency of gravitational waves emitted in these systems is matching within the range of LIGO. The objects near the galactic center could consist of such primordial objects, planets, comets, etc. We also discuss the possibility of the tidal break up of these primordial objects in the presence of a BH. The mass of BH required for tidal break up is calculated, and it is found that the mass of BH required for tidal break up increases with the DM particle mass and also with the increase in the fraction of baryons in these objects. The energy released during tidal breakup will be emitted as gravitational waves. The energy released, as well as the frequency of waves, is tabulated, and the frequency is in the sensitivity range of LIGO.
Mechanical drawing. Engineering graphics, Physical and theoretical chemistry
Riccardo Nicolaidis, Francesco Nozzoli, Giancarlo Pepponi
et al.
An accurate flux measurement of low-energy charged particles trapped in the magnetosphere is necessary for space weather characterization and to study the coupling between the lithosphere and magnetosphere, which allows for the investigation of the correlations between seismic events and particle precipitation from Van Allen belts. In this work, the project of a CubeSat space spectrometer, the Low-Energy Module (LEM), is shown. The detector will be able to perform an event-based measurement of the energy, arrival direction, and composition of low-energy charged particles down to 0.1 MeV. Moreover, thanks to a CdZnTe mini-calorimeter, the LEM spectrometer also allows for photon detection in the sub-MeV range, joining the quest for the investigation of the nature of Gamma-ray bursts. The particle identification of the LEM relies on the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>Δ</mo><mi>E</mi><mo>−</mo><mi>E</mi></mrow></semantics></math></inline-formula> technique performed by thin silicon detectors. This multipurpose spectrometer will fit within a 10 × 10 × 10 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>cm</mi><mn>3</mn></msup></semantics></math></inline-formula> CubeSat frame, and it will be constructed as a joint project between the University of Trento, FBK, and INFN-TIFPA. To fulfil the size and mass requirements, an innovative approach, based on active particle collimation, was designed for the LEM; this avoids the heavy/bulky passive collimators of previous space detectors. In this paper, we will present the LEM geometry, its detection concept, and the results from the developed GEANT4 simulation.
Mechanical drawing. Engineering graphics, Physical and theoretical chemistry
This paper shows that the field defined by the Wheeler–DeWitt equation for <i>pure gravity</i> is neither a standard gravitational field nor the field representing a particular universe. The theory offers a unified description of geometry and matter, with geometry being fundamental. The quantum theory possesses gravitational decoherence when the signature of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mrow><mo>(</mo><mn>3</mn><mo>)</mo></mrow></msup></semantics></math></inline-formula> changes. The quantum theory resolves singularities dynamically. Application to the FLRW <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>κ</mi><mo>=</mo><mn>0</mn></mrow></semantics></math></inline-formula> shows the creation of local geometries during quantum evolution. The 3-metric is modified near the classical singularity in the case of the Schwarzschild geometry.
Mechanical drawing. Engineering graphics, Physical and theoretical chemistry
Many institutes of higher education overlook a very important tool namely, Geometric Dimensioning and Tolerancing (GD&T). GD&T is the symbolic language used in manufacturing to communicate the design, production, and quality control requirements. Over the years, several employers have voiced concerns about the students’ lack of knowledge in identifying and applying GD&T concepts in engineering drawings. This has resulted in the employers spending time and money to bring the students up to company standards. Lack of GD&T knowledge adversely affects the design and engineering department, production line, and quality control and assurance department, three critical areas in every manufacturing company. In addition, senior level students typically encounter issues during their design/capstone project where they are unable properly define tolerances subsequently affecting manufacturing and jeopardizing deadlines. As part of continuous improvement, the mechanical engineering program decided to create and offer the GD&T course as an elective for the first time in Fall 2022. The three-credit elective consisted of a total of 14 sessions, and the culminating experience of the course was an extensive project which they completed over time. The project had students working in teams of four, and the requirement was making a gib and slide assembly which consisted of no more than 5 pieces. The course evaluations were highly positive, and the students described it as intellectually stimulating where they were able to finally learn techniques that they could implement at their workplace. A major recommendation was to improve organization such that students can break the final product into two or three subassemblies that are due during the midterms. Given the global importance of GD&T, it is recommended that such a course be made a prerequisite for students engaged in senior design projects.
Franziska Scheibel, Wei Liu, Lukas Pfeuffer
et al.
A multi-stimuli cooling cycle can be used to increase the cyclic caloric performance of multicaloric materials like Ni-Mn-In Heusler alloys. However, the use of a uniaxial compressive stress as an additional external stimulus to a magnetic field requires good mechanical stability. Improvement of mechanical stability and strength by doping has been shown in several studies. However, doping is always accompanied by grain refinement and a change in transition temperature. This raises the question of the extent to which mechanical strength is related to grain refinement, transition temperature, or precipitates. This study shows a direct comparison between a single-phase Ni-Mn-Sn and a two-phase Gd-doped Ni-Mn-In alloy with the same transition temperature and grain size. It is shown that the excellent magnetocaloric properties of the Ni-Mn-In matrix are maintained with doping. The isothermal entropy change and adiabatic temperature change are reduced by only 15% in the two-phase Ni-Mn-In-Heusler alloy compared to the single-phase alloy, which is resulting from a slight increase in thermal hysteresis and the width of the transition. Due to the same grain size and transition temperature, this effect can be directly related to the precipitates. The introduction of Gd precipitates leads to a 100% improvement in mechanical strength, which is significantly lower than the improvement observed for Ni-Mn-In alloys with grain refinement and Gd precipitates. This reveals that a significant contribution to the improved mechanical stability in Gd-doped Heusler alloys is related to grain refinement.
Software companies have widely used online A/B testing to evaluate the impact of a new technology by offering it to groups of users and comparing it against the unmodified product. However, running online A/B testing needs not only efforts in design, implementation, and stakeholders' approval to be served in production but also several weeks to collect the data in iterations. To address these issues, a recently emerging topic, called "Offline A/B Testing", is getting increasing attention, intending to conduct the offline evaluation of new technologies by estimating historical logged data. Although this approach is promising due to lower implementation effort, faster turnaround time, and no potential user harm, for it to be effectively prioritized as requirements in practice, several limitations need to be addressed, including its discrepancy with online A/B test results, and lack of systematic updates on varying data and parameters. In response, in this vision paper, I introduce AutoOffAB, an idea to automatically run variants of offline A/B testing against recent logging and update the offline evaluation results, which are used to make decisions on requirements more reliably and systematically.
Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and DALL-E, in real-world applications necessitates vast, domain-specific, and publicly accessible datasets. Unfortunately, the scarcity of such datasets poses a significant challenge for researchers aiming to apply these breakthroughs in engineering design. Synthetic datasets emerge as a viable alternative. However, practitioners are often uncertain about generating high-quality datasets that accurately represent real-world data and are suitable for the intended downstream applications. This study aims to fill this knowledge gap by proposing comprehensive guidelines for generating, annotating, and validating synthetic datasets. The trade-offs and methods associated with each of these aspects are elaborated upon. Further, the practical implications of these guidelines are illustrated through the creation of a turbo-compressors dataset. The study underscores the importance of thoughtful sampling methods to ensure the appropriate size, diversity, utility, and realism of a dataset. It also highlights that design diversity does not equate to performance diversity or realism. By employing test sets that represent uniform, real, or task-specific samples, the influence of sample size and sampling strategy is scrutinized. Overall, this paper offers valuable insights for researchers intending to create and publish synthetic datasets for engineering design, thereby paving the way for more effective applications of AI advancements in the field. The code and data for the dataset and methods are made publicly accessible at https://github.com/cyrilpic/radcomp .