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  • Conference paper
    Daugintis R, Barumerli R, Picinali L, Geronazzo Met al., 2023,

    Classifying non-individual head-related transfer functions with a computational auditory model: calibration and metrics

    , ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 1-5

    This study explores the use of a multi-feature Bayesian auditory sound localisation model to classify non-individual head-related transfer functions (HRTFs). Based on predicted sound localisation performance, these are grouped into ‘good’ and ‘bad’, and the ‘best’/‘worst’ is selected from each category. Firstly, we present a greedy algorithm for automated individual calibration of the model based on the individual sound localisation data. We then discuss data analysis of predicted directional localisation errors and present an algorithm for categorising the HRTFs based on the localisation error distributions within a limited range of directions in front of the listener. Finally, we discuss the validity of the classification algorithm when using averaged instead of individual model parameters. This analysis of auditory modelling results aims to provide a perceptual foundation for automated HRTF personalisation techniques for an improved experience of binaural spatial audio technologies.
  • Conference paper
    Pauwels J, Picinali L, 2023,

    On the relevance of the differences between HRTF measurement setups for machine learning

    , ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 1-5

    As spatial audio is enjoying a surge in popularity, data-driven machine learning techniques that have been proven successful in other domains are increasingly used to process head-related transfer function measurements. However, these techniques require much data, whereas the existing datasets are ranging from tens to the low hundreds of datapoints. It therefore becomes attractive to combine multiple of these datasets, although they are measured under different conditions. In this paper, we first establish the common ground between a number of datasets, then we investigate potential pitfalls of mixing datasets. We perform a simple experiment to test the relevance of the remaining differences between datasets when applying machine learning techniques. Finally, we pinpoint the most relevant differences.
  • Journal article
    Alibasa MJ, Calvo RA, Yacef K, 2023,

    Predicting mood from digital footprints using frequent sequential context patterns features

    , International Journal of Human-Computer Interaction, Vol: 39, Pages: 2061-2075, ISSN: 1044-7318

    Understanding the relationship between technology and wellbeing is important in order to raise awareness and to improve interaction designs with digital technologies. Most studies used the time spent and frequency information of digital technology usage, very few explored the sequences and the patterns of how the activity occurs. We introduce the concept of “digital context,” a representation of activity data occurring in a short time-window. Using data from our study, we determined whether: (1) there are digital context patterns that are more frequent in a particular mood compared to other moods; and (2) in the case such patterns exist, whether they can be used to improve the performance of mood prediction models. Our results showed that a mood prediction model that include digital context features yielded an accuracy of 77.8%, which is an improvement compared with the models proposed in past studies.
  • Journal article
    Valk S, Chen Y, Dieckmann E, Mougenot Cet al., 2023,

    Supporting collaborative biodesign ideation with contextualised knowledge from bioscience

    , CoDesign, Vol: 19, ISSN: 1571-0882

    The objective of this work is to support co-creation of novel ideas in biodesign during fast-paced and facilitated workshops. We created a card-based tool which simultaneously provides knowledge on both ‘science’ and ‘context’. The tool was used to trigger and inspire collaborative ideation in two biodesign workshops in which participants from scientific and design backgrounds produced ideas for healthcare-related innovations. To understand the perception of the tool and the mechanism of scientific knowledge integration in ideation, we conducted post-workshop interviews with 10 participants. Our qualitative analysis shows that the exposure to contextualised scientific knowledge provided by the tool enabled participants to generate ideas that cover a wide spectrum from the micro-scale of bioscience to the macro-scale of socio-political contexts, and thus supported the acceleration of ideation in biodesign workshops.
  • Journal article
    Faria AS, Soares T, Orlandini T, Oliveira C, Sousa T, Pinson P, Matos Met al., 2023,

    P2P market coordination methodologies with distribution grid management

    , Sustainable Energy, Grids and Networks, Vol: 34

    As prosumers and energy communities gain prominence in power systems, energy trading between prosumers in local P2P markets is paramount. Within this novel market design, peers can directly exchange energy with each other, leading to economic advantages while supporting the decarbonization of the sector. To ensure that voltage and congestion issues are properly addressed, a thorough coordination between the P2P market and the Distribution System Operator is required. This paper presents and compares three mutual-benefit coordination methods. The first method entails applying product differentiation on an iterative basis to avoid exceeding the lines thermal limits, which is performed through penalties on P2P exchanges that may be overloading the network. The second method uses the P2P market with an AC-OPF, ensuring network operation through a flexibility market via upward and downward flexibility. The last one proposes an integrated operation of the P2P market with AC-OPF. All methods are assessed in a typical distribution network with high prosumers integration. The results show that the second method is the one that, fulfilling the network constraints, presents greater social welfare.
  • Journal article
    Pedersen RL, Picinali L, Kajs N, Patou Fet al., 2023,

    Virtual-Reality-Based Research in Hearing Science: A Platforming Approach

    , AES: Journal of the Audio Engineering Society, Vol: 71, Pages: 374-389, ISSN: 1549-4950

    The lack of ecological validity in clinical assessment, as well as the challenge of investigating multimodal sensory processing, remain key challenges in hearing science. Virtual Reality (VR) can support hearing research in these domains by combining experimental control with situational realism. However, the development of VR-based experiments is traditionally highly resource demanding, which places a significant entry barrier for basic and clinical researchers looking to embrace VR as the research tool of choice. The Oticon Medical Virtual Reality (OMVR) experiment platform fast-tracks the creation or adaptation of hearing research experiment templates to be used to explore areas such as binaural spatial hearing, multimodal sensory integration, cognitive hearing behavioral strategies, auditory-visual training, etc. In this paper, the OMVR’s functionalities, architecture, and key elements of implementation are presented, important performance indicators are characterized, and a use-case perceptual evaluation is presented.
  • Journal article
    Zheng K, He Z, Qu H, Chen F, Han Y, Zheng J-H, Li Net al., 2023,

    A novel quench-form and in-die creep age process for hot forming of 2219 thin aluminum sheets with high precision and efficiency

    , Journal of Materials Processing Technology, Vol: 315, Pages: 1-13, ISSN: 0924-0136

    This work introduces a novel forming process, named Quench-form and In-die Creep Age (short for QICA). It integrates a hot stamping by warm dies (named quench-form) with a fast in-die creep age to significantly improve the dimensional accuracy of the formed part with maintained post-form mechanical properties and reduced total processing time. The process principle and underlying mechanisms were revealed by experimental forming tests, tensile tests, TEM observations. The optimum processing temperature range has been determined, and the processing window for industrial significance has been discussed. Results showed that under a heat treatment condition of 240 °C × 5 min followed by 175 °C × 4 h, the panel spring-back is significantly reduced by 75%, from 21′ to 5′, compared to that under the T6 forming condition. The total processing time is also dramatically reduced from the conventional 12–4.5 h, increasing the overall production efficiency by 62.5%. From industry perspective, an 80 °C temperature operation window, from 160 °C to 240 °C, is suggested to guarantee a yield strength of > 280 MPa (93% of the T6 strength). The effectiveness of the process has also been verified by forming an aircraft engine inlet lip part. The maximum clearance between the formed part and die was reduced from 7.00 mm to 2.01 mm by replacing the HFQ® technique with the QICA technique. The proposed novel process delivers an alternative energy-efficient method to produce high-accurate extra-large parts that are beneficial for aircraft and aerospace OEMs.
  • Journal article
    Dubarry M, Howey D, Wu B, 2023,

    Enabling battery digital twins at the industrial scale

    , Joule, Vol: 7, Pages: 1134-1144, ISSN: 2542-4351

    Digital twins are cyber-physical systems that fuse real-time sensor data with models to make accurate, asset-specific predictions and optimal decisions. For batteries, this concept has been applied across length scales, from materials to systems. However, a holistic approach with a strong conceptual and mathematical framework is needed for battery digital twins to achieve their full potential at the industrial scale. Developing a standardized and transparent approach for data sharing between stakeholders that respects confidentiality is essential. Industrial battery digital twins also need principled methods to quantify and propagate uncertainty from sensors and models to predictions. Ensuring retention of physical understanding is important for the identification of “stiff” parameters, which require careful measurement. Combined with uncertainty analysis, this can unlock optimal data-driven sensor selection and placement and improved root-cause analysis. However, better physical modeling and sensing approaches for battery manufacturing and thermal runaway are needed. Furthermore, immutability of data is also necessary for industrial uptake, with digital ledger technology providing new avenues of research. We believe that digital twins could be transformative for the current lithium-ion battery technologies and also as an enabler for emerging new battery technologies, optimizing lifetime and value through asset-specific control.
  • Journal article
    Mulvey B, Lalitharatne TD, Nanayakkara T, 2023,

    DeforMoBot: a bio-inspired deformable mobile robot for navigation among obstacles

    , IEEE Robotics and Automation Letters, Vol: 8, Pages: 3828-3835, ISSN: 2377-3766

    Many animals can move in cluttered environments by conforming their body shape to geometric constraints in their surroundings such as narrow gaps. Most robots are rigid structures and do not possess these capabilities. Navigation around movable or compliant obstacles results in a loss of efficiency—and possible mission failure—compared to progression through them. In this paper, we propose the novel design of a deformable mobile robot; it can adopt a wider stance for greater stability (and possible higher payload capacity), or a narrower stance to become capable of fitting through small gaps and progressing through flexible obstacles. We use a whisker-based feedback control approach in order to match the amount of the robot's deformation with the compliance level of the obstacle. We present a real-time algorithm which uses whisker feedback and performs shape adjustment in uncalibrated environments. The developed robot was tested navigating among obstacles with varying physical properties from different approach angles. Our results highlight the importance of co-development of environment perception and physical reaction capabilities for improved performance of mobile robots in unstructured environments.
  • Journal article
    Hauser H, Nanayakkara T, Forni F, 2023,

    Leveraging Morphological Computation for Controlling Soft Robots LEARNING FROM NATURE TO CONTROL SOFT ROBOTS

    , IEEE CONTROL SYSTEMS MAGAZINE, Vol: 43, Pages: 114-129, ISSN: 1066-033X
  • Conference paper
    Armitage J, Magnusson T, McPherson A, 2023,

    A scale-based ontology of digital musical instrument design

    , International Conference on New Interfaces for Musical Expression, Publisher: NIME, Pages: 339-349, ISSN: 2220-4806

    Subtlety and detail are fundamental to what makes musical instruments special, and worth dedicating a life's practice to, for designer, maker, player and listener alike. However, research into digital musical instrument (DMI) design tools and processes have so far mainly focused on high-level conceptual concerns and low-level technical abstractions, leaving subtlety and detail underexplored and undervalued. These nuances, and the processes they result from, cannot be fully articulated in words alone, yet they largely define an instrument's quality, and it is therefore important to understand how they come to be. We introduce a scale-based ontology that divides design details into three levels - macro, meso and micro - and we present a literature review of DMI design from the perspective of this ontology. Finally we extrapolate the ontology to consider its utility in broader contexts, and consider future directions.
  • Conference paper
    Armitage J, Magnusson T, McPherson A, 2023,

    Studying subtle and detailed digital lutherie: motivational contexts and technical needs

    , International Conference on New Interfaces for Musical Expression, Publisher: NIME, Pages: 1-9, ISSN: 2220-4806

    Subtlety and detail are fundamental to what makes musical instruments special, but accounts of their development in digital lutherie have been constrained to ethnographies, in-the-wild studies, and personal reflections. Though insightful, these accounts are imprecise, incomparable, and inefficient for understanding how fluency with the subtle details of digital musical instruments (DMIs) develops. We have been designing DMI design probes and activities for closed and constrained observation of subtle and detailed DMI design, but in two previous studies these failed to motivate subtle and detailed responses. In this paper we report on our third attempt, where we designed a tuned percussion DMI and a hybrid handcraft tool for sculpting its sound using clay, and a one hour activity. Among 26 study participants were digital luthiers, violin luthiers and musicians, who all engaged with what we define as micro scale DMI design. We observed technical desires and needs for experiencing and comparing subtle details systematically, and also widely varying, subjective emotional and artistic relationships with detail in participants' own practices. We reflect on the contexts that motivate subtle and detailed digital lutherie, and discuss the implications for DMI design researchers and technologists for studying and supporting this aspect of DMI design and craft practice in future.
  • Journal article
    Collis B, Baxter W, Baird HM, Meade K, Webb TLet al., 2023,

    Signs of use present a barrier to reusable packaging systems for takeaway food

    , Sustainability, Vol: 15, Pages: 1-15, ISSN: 2071-1050

    Single-use packaging is one of the biggest contributors to plastic waste, and reuse has been identified as a key strategy to reduce such waste. However, reusable containers typically become worn, which may influence how consumers think and feel about reuse. The present research explored whether and how evaluations of a takeaway food service changed depending on the appearance of a reusable container. Two studies were conducted (using opportunity sampling) to (i) investigate the effects that signs of use have on people’s perceptions of reusable packaging systems using quantitative methods (Study 1) and (ii) understand the rationale underpinning these evaluations using qualitative methods (Study 2). Study 1 involved an online questionnaire where participants (n = 292) were shown images of reusable bowls for takeaway food with various levels of staining and asked to evaluate the container and the restaurant serving the food using rating scales. Study 2 involved in-person interviews where participants (n = 22) were given the opportunity to inspect either a clean bowl or a stained bowl and then were asked questions about the bowls. Signs of previous use seemed to undermine people’s willingness to reuse containers in the future and were associated with more negative evaluations of the packaging, product, and restaurant serving the food. These findings provide insights into the factors that affect people’s willingness to engage with reusable packaging systems, and we use these findings to suggest behavioural and design interventions that might mitigate negative evaluations and encourage reuse.
  • Journal article
    Aloufi R, Haddadi H, Boyle D, 2023,

    Paralinguistic privacy protection at the edge

    , ACM Transactions on Privacy and Security, Vol: 26, Pages: 1-27, ISSN: 2471-2566

    Voice user interfaces and digital assistants are rapidly entering our lives and becoming singular touch points spanning our devices. These always-on services capture and transmit our audio data to powerful cloud services for further processing and subsequent actions. Our voices and raw audio signals collected through these devices contain a host of sensitive paralinguistic information that is transmitted to service providers regardless of deliberate or false triggers. As our emotional patterns and sensitive attributes like our identity, gender, and well-being are easily inferred using deep acoustic models, we encounter a new generation of privacy risks by using these services. One approach to mitigate the risk of paralinguistic-based privacy breaches is to exploit a combination of cloud-based processing with privacy-preserving, on-device paralinguistic information learning and filtering before transmitting voice data.In this article we introduce EDGY, a configurable, lightweight, disentangled representation learning framework that transforms and filters high-dimensional voice data to identify and contain sensitive attributes at the edge prior to offloading to the cloud. We evaluate EDGY’s on-device performance and explore optimization techniques, including model quantization and knowledge distillation, to enable private, accurate, and efficient representation learning on resource-constrained devices. Our results show that EDGY runs in tens of milliseconds with 0.2% relative improvement in “zero-shot” ABX score or minimal performance penalties of approximately 5.95% word error rate (WER) in learning linguistic representations from raw voice signals, using a CPU and a single-core ARM processor without specialized hardware.
  • Journal article
    Brial E, Aunger R, Muangi WC, Baxter Wet al., 2023,

    Development of a novel hand cleansing product for low-income contexts: the case of tab soap

    , PLoS One, Vol: 18, Pages: 1-30, ISSN: 1932-6203

    Handwashing with soap is a widely advocated public health measure, but seldom practiced, partly because it is often difficult (especially outside of rich Western country contexts) to make both soap and water readily available in relevant situations. This study used both Behaviour Centred Design and Human Centred Design to guide development of a novel hand cleansing technology appropriate for the context of post-toilet hand cleansing in resource-poor societies. Extensive prototyping and field testing resulted in the pilot production of 'tab' soap, a small but durable single-use, decomposable substrate embedded with soap. It can be produced in dispenser roll or tear-off formats. With this affordable solution, one may use soap without worrying about contamination pretty much anytime and anywhere. A small-scale field test showed that all poor households in rural and peri-urban areas in Tanzania included in the proof-of-concept study (N = 12 households) would use the product reliably over the medium term. Tab soap awaits full-scale production and marketing but could make hand cleansing a more popular practice around the world.
  • Journal article
    Hong F, Lampret B, Myant C, Hodges S, Boyle Det al., 2023,

    5-axis multi-material 3D printing of curved electrical traces

    , ADDITIVE MANUFACTURING, Vol: 70, ISSN: 2214-8604
  • Journal article
    Burnell R, Peters D, Ryan RM, Calvo Ret al., 2023,

    Technology evaluations are associated with psychological need satisfaction across different levels of experience: An application of the METUX Scales

    , Frontiers in Psychology, Vol: 14, Pages: 1-12, ISSN: 1664-1078

    Digital technologies have the capacity to impact psychological wellbeing in both positive and negative ways. Improving technologies with respect to wellbeing requires nuanced understanding of this impact and reliable ways to measure it. Across two experiments with 1,521 participants, we investigated the relations between psychological needs and people’s evaluations of technologies (with respect to satisfaction, usability, and measures of value). To do so, we improved and validated four scales, first put forward as part of the METUX model of technology interaction, that measure psychological needs at the life, behavior, task,and interface levels. Each of these scales had good psychometric properties when applied to four separate technologies (Facebook, TikTok, Blackboard, and Moodle). At each of the four levels, psychological need satisfaction and frustration were associated with standard measures of usability and user satisfaction, and correlation patterns supported the METUX model and its approach to differentiating spheres of technology experience
  • Journal article
    Yao X, Lu X, Zhou Y, Samoril T, Bi J, Masteghin MG, Zhang H, Askew L, Kim J, Xiong F, Wang J, Cox DC, Sui T, Gilmore I, Silva SRP, Mai L, Hinds G, Shearing PR, Park J, Zhao Yet al., 2023,

    Rectifying interphases for preventing Li dendrite propagation in solid-state electrolytes

    , ENERGY & ENVIRONMENTAL SCIENCE, Vol: 16, Pages: 2167-2176, ISSN: 1754-5692
  • Journal article
    Seminara L, Dosen S, Mastrogiovanni F, Bianchi M, Watt S, Beckerle P, Nanayakkara T, Drewing K, Moscatelli A, Klatzky RL, Loeb GEet al., 2023,

    A hierarchical sensorimotor control framework for human-in-the-loop robotic hands.

    , Science Robotics, Vol: 8, Pages: 1-8, ISSN: 2470-9476

    Human manual dexterity relies critically on touch. Robotic and prosthetic hands are much less dexterous and make little use of the many tactile sensors available. We propose a framework modeled on the hierarchical sensorimotor controllers of the nervous system to link sensing to action in human-in-the-loop, haptically enabled, artificial hands.
  • Journal article
    Su T, Calvo RA, Jouaiti M, Daniels S, Kirby P, Dijk D-J, Della Monica C, Vaidyanathan Ret al., 2023,

    Assessing a sleep interviewing chatbot to improve subjective and objective sleep: protocol for an observational feasibility study

    , JMIR Research Protocols, Vol: 12, Pages: 1-10, ISSN: 1929-0748

    BACKGROUND: Sleep disorders are common among the aging population and people with neurodegenerative diseases. Sleep disorders have a strong bidirectional relationship with neurodegenerative diseases, where they accelerate and worsen one another. Although one-to-one individual cognitive behavioral interventions (conducted in-person or on the internet) have shown promise for significant improvements in sleep efficiency among adults, many may experience difficulties accessing interventions with sleep specialists, psychiatrists, or psychologists. Therefore, delivering sleep intervention through an automated chatbot platform may be an effective strategy to increase the accessibility and reach of sleep disorder intervention among the aging population and people with neurodegenerative diseases. OBJECTIVE: This work aims to (1) determine the feasibility and usability of an automated chatbot (named MotivSleep) that conducts sleep interviews to encourage the aging population to report behaviors that may affect their sleep, followed by providing personalized recommendations for better sleep based on participants' self-reported behaviors; (2) assess the self-reported sleep assessment changes before, during, and after using our automated sleep disturbance intervention chatbot; (3) assess the changes in objective sleep assessment recorded by a sleep tracking device before, during, and after using the automated chatbot MotivSleep. METHODS: We will recruit 30 older adult participants from West London for this pilot study. Each participant will have a sleep analyzer installed under their mattress. This contactless sleep monitoring device passively records movements, heart rate, and breathing rate while participants are in bed. In addition, each participant will use our proposed chatbot MotivSleep, accessible on WhatsApp, to describe their sleep and behaviors related to their sleep and receive personalized recommendations for better sleep tailored to their specific reasons for disrup
  • Journal article
    Miller JA, Veprek LH, Deterding S, Cooper Set al., 2023,

    Practical recommendations from a multi-perspective needs and challenges assessment of citizen science games

    , PLOS ONE, Vol: 18, ISSN: 1932-6203
  • Journal article
    Niu Z, Zhao W, Wu B, Wang H, Lin W, Pinfield VJ, Xuan Jet al., 2023,

    π learning: a performance‐Informed framework for microstructural electrode design

    , Advanced Energy Materials, Vol: 13, Pages: 1-14, ISSN: 1614-6832

    Designing high-performance porous electrodes is the key to next-generation electrochemical energy devices. Current machine-learning-based electrode design strategies are mainly orientated toward physical properties; however, the electrochemical performance is the ultimate design objective. Performance-orientated electrode design is challenging because the current data driven approaches do not accurately extract high-dimensional features in complex multiphase microstructures. Herein, this work reports a novel performance-informed deep learning framework, termed π learning, which enables performance-informed microstructure generation, toward overall performance prediction of candidate electrodes by adding most relevant physical features into the learning process. This is achieved by integrating physics-informed generative adversarial neural networks (GANs) with convolutional neural networks (CNNs) and with advanced multi-physics, multi-scale modeling of 3D porous electrodes. This work demonstrates the advantages of π learning by employing two popular design philosophies: forward and inverse designs, for the design of solid oxide fuel cells electrodes. π learning thus has the potential to unlock performance-driven learning in the design of next generation porous electrodes for advanced electrochemical energy devices such as fuel cells and batteries.
  • Journal article
    Burge T, Jeffers J, Myant C, 2023,

    A computational design of experiments based method for evaluation of off-the-shelf total knee replacement implants

    , Computer Methods in Biomechanics and Biomedical Engineering, Vol: 26, Pages: 629-638, ISSN: 1025-5842

    A methodology to explore the design space of off-the-shelf total knee replacement implant designs is outlined. Generic femur component and tibia plate designs were scaled to thousands of sizes and virtually fitted to 244 test subjects. Various implant designs and sizing requirements between genders and ethnicities were evaluated. 5 sizes optimised via the methodology produced a good global fit for most subjects. However, clinically significant over/underhang was present in 19% of subjects for tibia plates and 25% for femur components, reducing to 11/20% with 8 sizes. The analysis highlighted subtly better fit performance was obtained using sizes with unequal spacing.
  • Journal article
    Baker CE, Yu X, Patel S, Ghajari Met al., 2023,

    A review of cyclist head injury, impact characteristics and the implications for helmet assessment methods

    , Annals of Biomedical Engineering, Vol: 51, Pages: 875-904, ISSN: 0090-6964

    Head injuries are common for cyclists involved in collisions. Such collision scenarios result in a range of injuries, with different head impact speeds, angles, locations, or surfaces. A clear understanding of these collision characteristics is vital to design high fidelity test methods for evaluating the performance of helmets. We review literature detailing real-world cyclist collision scenarios and report on these key characteristics. Our review shows that helmeted cyclists have a considerable reduction in skull fracture and focal brain pathologies compared to non-helmeted cyclists, as well as a reduction in all brain pathologies. The considerable reduction in focal head pathologies is likely to be due to helmet standards mandating thresholds of linear acceleration. The less considerable reduction in diffuse brain injuries is likely to be due to the lack of monitoring head rotation in test methods. We performed a novel meta-analysis of the location of 1809 head impacts from ten studies. Most studies showed that the side and front regions are frequently impacted, with one large, contemporary study highlighting a high proportion of occipital impacts. Helmets frequently had impact locations low down near the rim line. The face is not well protected by most conventional bicycle helmets. Several papers determine head impact speed and angle from in-depth reconstructions and computer simulations. They report head impact speeds from 5 to 16 m/s, with a concentration around 5 to 8 m/s and higher speeds when there was another vehicle involved in the collision. Reported angles range from 10° to 80° to the normal, and are concentrated around 30°-50°. Our review also shows that in nearly 80% of the cases, the head impact is reported to be against a flat surface. This review highlights current gaps in data, and calls for more research and data to better inform improvements in testing methods of standards and rating schemes and raise helmet s
  • Journal article
    Harkin R, Wu H, Nikam S, Yin S, Lupoi R, Walls P, McKay W, McFadden Set al., 2023,

    Evaluation of the role of hatch-spacing variation in a lack-of-fusion defect prediction criterion for laser-based powder bed fusion processes

    , International Journal of Advanced Manufacturing Technology, Vol: 126, Pages: 659-673, ISSN: 0178-0026

    Lack of fusion (LOF) defects impact adversely on the mechanical properties of additively manufactured components produced via laser-based powder bed fusion. Following a stress-relieving heat treatment, the tensile properties and hardness of Ti6Al4V components were found to be negatively impacted by the presence of LOF defects. This work considers a geometrical-based inequality for the prediction of LOF defects. We critically evaluate an LOF criterion using both the experimentally and analytically obtained melt pool geometries. Experimentally, we determined melt pool dimensions by analysing a single-layer, multi-track deposition with oversized hatch spacing in order to establish depth and width from non-overlapping melt pools. Analytically, Rosenthal-based predictions of melt pool size (width and depth) are applied. To investigate LOF defects, we used hatch spacing as the main parameter variation to investigate defects while keeping all other controllable parameters unchanged. An original LOF criterion from the literature was found to be an adequate predictor of LOF defects when experimentally obtained melt pool geometry was used. Critically, however, the analytical expressions for melt pool geometry were found to be in error and this caused the LOF criterion to fail in predicting LOF defects in all cases where defects were observed experimentally. However, an adaptation to the LOF prediction criterion is proposed whereby it is recommended that a correction factor (or ) is used with the analytically derived melt pool geometry. Furthermore, this correction is extended into the laser power versus scanning speed operating space to give minimum (corrected) line energy for LOF avoidance in Ti6Al4V components.
  • Journal article
    Engel I, Daugintis R, Vicente T, Hogg AOT, Pauwels J, Tournier AJ, Picinali Let al., 2023,

    The SONICOM HRTF dataset

    , Journal of the Audio Engineering Society, Vol: 71, Pages: 241-253, ISSN: 0004-7554

    Immersive audio technologies, ranging from rendering spatialized sounds accurately to efficient room simulations, are vital to the success of augmented and virtual realities. To produce realistic sounds through headphones, the human body and head must both be taken into account. However, the measurement of the influence of the external human morphology on the sounds incoming to the ears, which is often referred to as head-related transfer function (HRTF), is expensive and time-consuming. Several datasets have been created over the years to help researcherswork on immersive audio; nevertheless, the number of individuals involved and amount of data collected is often insufficient for modern machine-learning approaches. Here, the SONICOM HRTF dataset is introduced to facilitate reproducible research in immersive audio. This dataset contains the HRTF of 120 subjects, as well as headphone transfer functions; 3D scans of ears, heads, and torsos; and depth pictures at different angles around subjects' heads.
  • Journal article
    Pinson P, 2023,

    What may future electricity markets look like?

    , Journal of Modern Power Systems and Clean Energy, Vol: 11, Pages: 705-713, ISSN: 2196-5625

    Should the organization, design and functioning of electricity markets be taken for granted? Definitely not. While decades of evolution of electricity markets in countries that committed early to restructure their electric power sector made us believe that we may have found the right and future-proof model, the substantially and rapidly evolving context of our power and energy systems is challenging this idea in many ways. Actually, that situation brings both challenges and opportunities. Challenges include accommodation of renewable energy generation, decentralization and support to investment, while opportunities are mainly that advances in technical and social sciences provide us with many more options in terms of future market design. We here take a holistic point of view, by trying to understand where we are coming from with electricity markets and where we may be going. Future electricity markets should be made fit for purpose by considering them as a way to organize and operate a socio-techno-economic system.
  • Journal article
    MacManus DB, Khorshidi MA, Ghajari M, Sedighi HMet al., 2023,

    Micromechanics in biology and medicine

    , IET Nanobiotechnology, Vol: 17, Pages: 125-126, ISSN: 1751-8741
  • Conference paper
    Wang B, Zuo H, Cai Z, Yin Y, Childs P, Sun L, Chen Let al., 2023,

    A task-decomposed AI-aided approach for generative conceptual design

    , ASME 2023 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE2023)

    Generative algorithm-based conceptual design has beeninnovatively applied as an emerging digital design paradigm forearly-stage design ideation. With powerful large languagemodels (LLMs), designers can enter an initial prompt as a designrequirement to generate using machine reasoning capabilitydescriptive natural language content. The machine-generatedoutput can be used as stimuli to inspire designers during designideation. However, the lack of transparency and insufficientcontrollability of LLMs can limit their effectiveness whenassisting humans on a generative conceptual design task. Thisgeneration process lacks theoretical guidance and acomprehensive understanding of design requirements, whichmay potentially lead to generated concepts that are mismatchedor lack creativity. Inspired by the Function-Behavior-Structure(FBS) model, this paper proposes a task-decomposed AI-aidedapproach for generative conceptual design. We decompose aconceptual design task into three sub-tasks including functionalreasoning, behavioral reasoning, and structural reasoning.Prompt templates and specification signifiers are specified fordifferent steps to guide the LLMs to generate reasonable results,controllably. The output of each step becomes the input of thenext, aiding in aggregating gains per step and embedding theselection preferences of human designers at each stage. Aconceptual design experiment is conducted, and the results showthat the conceptual design ideation with our method are morereasonable and creative in comparison to a baseline.
  • Journal article
    Arrese-Igor M, Vong M, Orue A, Kassanos P, George C, Aguesse F, Mysyk R, Radacsi N, Lopez-Aranguren Pet al., 2023,

    Solid-state Li-ion batteries with carbon microfiber electrodes via 3D electrospinning

    , APPLIED PHYSICS LETTERS, Vol: 122, ISSN: 0003-6951

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