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  • Journal article
    Chen L, Zuo H, Cai Z, Yin Y, Zhang Y, Sun L, Childs PRN, Wang Bet al., 2024,

    Towards controllable generative design: a conceptual design generation approach leveraging the FBS ontology and Large Language Models

    , Journal of Mechanical Design, Vol: 146, ISSN: 1050-0472

    Recent research in the field of design engineering is primarily focusing on using AI technologies such as Large Language Models (LLMs) to assist early-stage design. The engineer or designer can use LLMs to explore, validate and compare thousands of generated conceptual stimuli and make final choices. This was seen as a significant stride in advancing the status of the generative approach in computer-aided design. However, it is often difficult to instruct LLMs to obtain novel conceptual solutions and requirement-compliant in real design tasks, due to the lack of transparency and insufficient controllability of LLMs. This study presents an approach to leverage LLMs to infer Function-Behavior-Structure (FBS) ontology for high-quality design concepts. Prompting design based on the FBS model decomposes the design task into three sub-tasks including functional, behavioral, and structural reasoning. In each sub-task, prompting templates and specification signifiers are specified to guide the LLMs to generate concepts. User can determine the selected concepts by judging and evaluating the generated function-structure pairs. A comparative experiment has been conducted to evaluate the concept generation approach. According to the concept evaluation results, our approach achieves the highest scores in concept evaluation, and the generated concepts are more novel, useful, functional, and low-cost compared to the baseline.
  • Journal article
    Cutting J, Deterding S, 2024,

    The task-attention theory of game learning: a theory and research agenda

    , Human-Computer Interaction, Vol: 39, Pages: 257-287, ISSN: 0737-0024

    Why do learning games fail or succeed? Recent evidence suggests that attention forms an important moderator of learning from games. While existing media effects and learning theories acknowledge the role of attentional limits, they fail to account for the specific ways that games as interactive media steer attention. In response, we here develop the Task-Attention Theory of Game Learning. Drawing on current psychological and games research, task-attention theory argues that games as interactive media demand and structure the pursuit of tasks, which ties into distinct attentional mechanisms, namely learned attentional sets which focus attentional selection onto task-relevant features, as well as active sampling: users navigate and manipulate the game to elicit task-relevant information. This active sampling and selection precedes and moderates what information can be learned. We identify task-related game features (mechanics, goals, rewards and uncertainty) and demands (cognitive and perceptual load, pressure) that affect active sampling and attentional selection. We articulate implications and future work for game-based learning research and design, as well as wider media effects, learning, and HCI research.
  • Journal article
    Zhao Y, Li H, Zhou H, Attar HR, Pfaff T, Li Net al., 2024,

    A review of graph neural network applications in mechanics-related domains

    , Artificial Intelligence Review: an international survey and tutorial journal, Vol: 57, ISSN: 0269-2821

    Mechanics-related tasks often present unique challenges in achieving accurate geometric and physical representations, particularly for non-uniform structures. Graph neural networks (GNNs) have emerged as a promising tool to tackle these challenges by adeptly learning from graph data with irregular underlying structures. Consequently, recent years have witnessed a surge in complex mechanics-related applications inspired by the advancements of GNNs. Despite this process, there is a notable absence of a systematic review addressing the recent advancement of GNNs in solving mechanics-related tasks. To bridge this gap, this review article aims to provide an in-depth overview of the GNN applications in mechanics-related domains while identifying key challenges and outlining potential future research directions. In this review article, we begin by introducing the fundamental algorithms of GNNs that are widely employed in mechanics-related applications. We provide a concise explanation of their underlying principles to establish a solid understanding that will serve as a basis for exploring the applications of GNNs in mechanics-related domains. The scope of this paper is intended to cover the categorisation of literature into solid mechanics, fluid mechanics, and interdisciplinary mechanics-related domains, providing a comprehensive summary of graph representation methodologies, GNN architectures, and further discussions in their respective subdomains. Additionally, open data and source codes relevant to these applications are summarised for the convenience of future researchers. This article promotes an interdisciplinary integration of GNNs and mechanics and provides a guide for researchers interested in applying GNNs to solve complex mechanics-related tasks.
  • Journal article
    Ge Y, Zong R, Chen X, Nanayakkara Tet al., 2024,

    An origami-inspired endoscopic capsule with tactile perception for early tissue anomaly detection

    , IEEE Robotics and Automation Letters, Vol: 9, Pages: 10018-10025, ISSN: 2377-3766

    Video Capsule Endoscopy (VCE) is currently one of the most effective methods for detecting intestinal diseases. However, it is challenging to detect early-stage small nodules with this method because they lack obvious color or shape features. In this letter, we present a new origami capsule endoscope to detect early small intestinal nodules using tactile sensing. Four soft tactile sensors made out of piezoresistive material feed four channels of phase-shifted data that are processed using a particle filter. The particle filter uses an importance assignment template designed using experimental data from six known sizes of nodules. Moreover, the proposed capsule can use shape changes to move forward or backward under peristalsis passively. In the experiment, it was able to return to a specific area for repeated detection in a straight, two-dimensional intestinal model. Experimental results show that the proposed capsule can detect nodules of more than 3 mm diameter with 100% accuracy.
  • Journal article
    Qian Q, Wang Y, Boyle D, 2024,

    On solving close enough orienteering problems with overlapped neighborhoods

    , European Journal of Operational Research, Vol: 318, Pages: 369-387, ISSN: 0377-2217

    The Close Enough Traveling Salesman Problem (CETSP) is a well-known variant of the classic TravelingSalesman Problem whereby the agent may complete its mission at any point within a target neighborhood.Heuristics based on overlapped neighborhoods, known as Steiner Zones (SZ), have gained attention inaddressing CETSPs. While SZs offer effective approximations to the original graph, their inherent overlapimposes constraints on the search space, potentially conflicting with global optimization objectives. Here weshow how such limitations can be converted into advantages in the Close Enough Orienteering Problem (CEOP)by aggregating prizes across overlapped neighborhoods. We further extend the classic CEOP with Non-uniformNeighborhoods (CEOP-) by introducing non-uniform cost considerations for prize collection. To tackle CEOP(and CEOP-), we develop a new approach featuring a Randomized Steiner Zone Discretization (RSZD)scheme coupled with a hybrid algorithm based on Particle Swarm Optimization (PSO) and Ant Colony System(ACS) — CRaSZe-AntS. The RSZD scheme identifies sub-regions for PSO exploration, and ACS determinesthe discrete visiting sequence. We evaluate the RSZD’s discretization performance on CEOP instances derivedfrom established CETSP instances and compare CRaSZe-AntS against the most relevant state-of-the-art heuristicfocused on single-neighborhood optimization for CEOP instances. We also compare the performance of theinterior search within SZs and the boundary search on individual neighborhoods in the context of CEOP-. Ourexperimental results show that CRaSZe-AntS can yield comparable solution quality with significantly reducedcomputation time compared to the single neighborhood strategy, where we observe an averaged 140.44%increase in prize collection and 55.18% reduction of algorithm execution time. CRaSZe-AntS is thus highlyeffective in solving emerging CEOP-, examples of which include truck-and-drone delivery scenarios.
  • Journal article
    Carman F, Ewen J, Bresme F, Wu B, Dini Det al., 2024,

    Molecular Simulations of Thermal Transport across Iron Oxide-Hydrocarbon Interfaces

    , ACS Applied Materials and Interfaces, ISSN: 1944-8244
  • Journal article
    Wang Q, Dai H-N, Yang J, Guo C, Childs P, Kleinsmann M, Guo Y, Wang Pet al., 2024,

    Learning-based Artificial Intelligence Artwork: Methodology Taxonomy and Quality Evaluation

    , ACM Computing Surveys, ISSN: 0360-0300

    <jats:p>With the development of the theory and technology of computer science, machine or computer painting is increasingly being explored in the creation of art. Machine-made works are referred to as artificial intelligence (AI) artworks. Early methods of AI artwork generation have been classified as non-photorealistic rendering (NPR) and, latterly, neural-style transfer methods have also been investigated. As technology advances, the variety of machine-generated artworks and the methods used to create them have proliferated. However, there is no unified and comprehensive system to classify and evaluate these works. To date, no work has generalised methods of creating AI artwork including learning-based methods for painting or drawing. Moreover, the taxonomy, evaluation and development of AI artwork methods face many challenges. This paper is motivated by these considerations. We first investigate current learning-based methods for making AI artworks and classify the methods according to art styles. Furthermore, we propose a consistent evaluation system for AI artworks and conduct a user study to evaluate the proposed system on different AI artworks. This evaluation system uses six criteria: beauty, color, texture, content detail, line and style. The user study demonstrates that the six-dimensional evaluation index is effective for different types of AI artworks.</jats:p>
  • Conference paper
    Davison M, Webb CJ, Ducceschi M, McPherson APet al., 2024,

    A self-sensing haptic actuator for tactile interaction with physical modelling synthesis

    , The International Conference on New Interfaces for Musical Expression (NIME 2024), Publisher: NIME Community, Pages: 574-581, ISSN: 2220-4806

    The use of transducers to excite physical modelling synthesisers with real-world audio signals is a well established practice within the digital musical instrument design community, yet it is normally presented as a unidirectional process – energy is transferred into the system from human to instrument. In this paper, a novel approach to tactile interaction with physical modelling synthesis is presented, through the use of a self-sensing vibrotactile transducer. This enables simultaneous collocated sensing and haptic actuation with a single moving coil transducer. A current drive amplifier is used for haptic actuation, using signals derived from the physical modelling synthesiser. The varying impedance of the transducer (due to changes in the mechanical damping) enables the sensing of force applied upon the device whilst also acting as a pickup to excite the physical model, all with simultaneous haptic actuation. A digital filter equivalent of the transducer’s impedance is used to prevent feedback in the system, allowing simultaneous excitation and haptic actuation without self-oscillation
  • Journal article
    Mulvey B, Nanayakkara T, 2024,

    HAVEN: haptic and visual environment navigation by a shape-changing mobile robot with multimodal perception

    , Scientific Reports, ISSN: 2045-2322

    Many animals exhibit agile mobility in obstructed environments due to their ability to tune their bodies to negotiate andmanipulate obstacles and apertures. Most mobile robots are rigid structures and avoid obstacles where possible. In this work,we introduce a new framework named Haptic And Visual Environment Navigation (HAVEN) Architecture to combine vision andproprioception for a deformable mobile robot to be more agile in obstructed environments. The algorithms enable the robot to beautonomously a) predictive by analysing visual feedback from the environment and preparing its body accordingly, b) reactiveby responding to proprioceptive feedback, and c) active by manipulating obstacles and gap sizes using its deformable body.The robot was tested approaching differently sized apertures in obstructed environments ranging from greater than its shapeto smaller than its narrowest possible size. The experiments involved multiple obstacles with different physical properties.The results show higher navigation success rates and an average 32% navigation time reduction when the robot activelymanipulates obstacles using its shape-changing body.
  • Journal article
    Yu X, Baker CE, Ghajari M, 2024,

    Head impact location, speed and angle from falls and trips in the workplace

    , Annals of Biomedical Engineering, Vol: 52, Pages: 2687-2702, ISSN: 0090-6964

    Traumatic brain injury (TBI) is a common injury in the workplace. Trips and falls are the leading causes of TBI in the workplace. However, industrial safety helmets are not designed for protecting the head under these impact conditions. Instead, they are designed to pass the regulatory standards which test head protection against falling heavy and sharp objects. This is likely to be due to the limited understanding of head impact conditions from trips and falls in workplace. In this study, we used validated human multi-body models to predict the head impact location, speed and angle (measured from the ground) during trips, forward falls and backward falls. We studied the effects of worker size, initial posture, walking speed, width and height of the tripping barrier, bracing and falling height on the head impact conditions. Overall, we performed 1692 simulations. The head impact speed was over two folds larger in falls than trips, with backward falls producing highest impact speeds. However, the trips produced impacts with smaller impact angles to the ground. Increasing the walking speed increased the head impact speed but bracing reduced it. We found that 41% of backward falls and 19% of trips/forward falls produced head impacts located outside the region of helmet coverage. Next, we grouped all the data into three sub-groups based on the head impact angle: [0°, 30°], (30°, 60°] and (60°, 90°] and excluded groups with small number of cases. We found that most trips and forward falls lead to impact angles within the (30°, 60°] and (60°, 90°] groups while all backward falls produced impact angles within (60°, 90°] group. We therefore determined five representative head impact conditions from these groups by selecting the 75th percentile speed, mean value of angle intervals and median impact location (determined by elevation and azimuth angles) of each group. This led to two representative head impact conditions for trip
  • Journal article
    Peters D, Sadek M, Ahmadpour N, 2024,

    Collaborative workshops at scale: a method for non-facilitated virtual collaborative design workshops

    , International Journal of Human-Computer Interaction, Vol: 40, Pages: 5997-6014, ISSN: 1044-7318

    This article introduces a method for conducting a fully online collaborative design workshop requiring no facilitation which we refer to as a Self-guided Collaborative Online Workshop (SCOW). The article provides three main contributions. Firstly, we present a process for the conversion of a face-to-face facilitated design workshop into a SCOW using a method we call the “playboard” which draws on concepts from CSCL literature. Secondly, we evaluate the efficacy of SCOWs using an iterative evaluation with 75 participants, including measures for participant satisfaction, subjective and objective learning outcomes, quality of the online and self-guided experience, and comparison with face-to-face workshops. Results across all measures indicate that the self-guided workshop was as successful as the in-person facilitated original. Moreover, participants reported advantages of the more scalable format including improved access to those with non-visible disabilities and in the Global South. Finally, based on our findings, we present a set of recommendations for others interested in using SCOWs as an inclusive and scalable way to support collaborative experiences.
  • Journal article
    van der Meer D, Pinson P, Camal S, Kariniotakis Get al., 2024,

    CRPS-based online learning for nonlinear probabilistic forecast combination

    , International Journal of Forecasting, Vol: 40, Pages: 1449-1466, ISSN: 0169-2070

    Forecast combination improves upon the component forecasts. Most often, combination approaches are restricted to the linear setting only. However, theory shows that if the component forecasts are neutrally dispersed—a requirement for probabilistic calibration—linear forecast combination will only increase dispersion and thus lead to miscalibration. Furthermore, the accuracy of the component forecasts may vary over time and the combination weights should vary accordingly, necessitating updates as time progresses. In this paper, we develop an online version of the beta-transformed linear pool, which theoretically can transform the probabilistic forecasts such that they are neutrally dispersed. We show that, in the case of stationary synthetic time series, the performance of the developed method converges to that of the optimal combination in hindsight. Moreover, in the case of nonstationary real-world time series from a wind farm in mid-west France, the developed model outperforms the optimal combination in hindsight.
  • Journal article
    Lou Z, Min X, Li G, Avery J, Stewart Ret al., 2024,

    Advancing sensing resolution of impedance hand gesture recognition devices

    , IEEE Journal of Biomedical and Health Informatics, Vol: 28, Pages: 5855-5864, ISSN: 2168-2194

    Gestures are composed of motion information (e.g. movements of fingers) and force information (e.g. the force exerted on fingers when interacting with other objects). Current hand gesture recognition solutions such as cameras and strain sensors primarily focus on correlating hand gestures with motion information and force information is seldom addressed. Here we propose a bio-impedance wearable that can recognize hand gestures utilizing both motion information and force information. Compared with previous impedance-based gesture recognition devices that can only recognize a few multi-degrees-of-freedom gestures, the proposed device can recognize 6 single-degree-of-freedom gestures and 20 multiple-degrees-of-freedom gestures, including 8 gestures in 2 force levels. The device uses textile electrodes, is benchmarked over a selected frequency spectrum, and uses a new drive pattern. Experimental results show that 179 kHz achieves the highest signal-to-noise ratio (SNR) and reveals the most distinct features. By analyzing the 49,920 samples from 6 participants, the device is demonstrated to have an average recognition accuracy of 98.96%. As a comparison, the medical electrodes achieved an accuracy of 98.05%.
  • Journal article
    Chen L, Cai Z, Jiang Z, Luo J, Sun L, Childs P, Zuo Het al., 2024,

    AskNatureNet: a divergent thinking tool based on bio-inspired design knowledge

    , Advanced Engineering Informatics: the science of supporting knowledge-intensive activities, Vol: 62, ISSN: 0954-1810

    Divergent thinking is a process in design by exploring multiple possible solutions, is crucial in the early stages of design to break fixation and expand the design ideation. Design-by-Analogy promotes divergent thinking, by studying solutions have solved similar problems and using this knowledge to make inferences and solve problems in new and unfamiliar situations. Bio-inspired design (BID) is a form of design by analogy and its knowledge provides diverse sources for analogy, making BID knowledge as a potential source for divergent thinking. Existing BID database has focused on collecting BID cases and facilitating the retrieval of biological knowledge. Despite its success, applying BID knowledge into divergent thinking still encounters challenge, as the association between source domain and target domain are always limited within a single case. In this work, a novel approach is proposed to support divergent thinking from three subsequent phases: encoding, retrieval and mapping. Specifically, biological knowledge is encoded in a triple form by employing a large language model (LLM) to extract key information from a well-known BID knowledge base. The created triples are implemented in a semantic network to facilitate bidirectional retrieval modes: problem-driven and solution-driven, as well as mapping for divergent thinking. The mapping algorithm calculates the semantic similarity between nodes in the semantic network based on their attributes in three progressive steps by following the paradigm of divergent thinking. The proposed approach is implemented as tool called AskNatureNet,1 which supports divergent thinking by retrieving and mapping knowledge in a visualized interactive semantic network. An ideation case study on evaluating the effectiveness of AskNatureNet shows that our tool is capable of supporting divergent thinking efficiently.
  • Book
    Childs P, Masen M, 2024,

    Mechanical Design Engineering Handbook

    , Publisher: Elsevier, ISBN: 9780443220777

    The aim of this handbook is to present an overview of the design process and to introduce the technology and selection of specific machine elements that are fundamental to a wide range of mechanical engineering design applications.
  • Journal article
    Zou Y, Zhao C, Childs P, Luh D-Bet al., 2024,

    Cross-cultural design in costume: case study on totemic symbols of China and Thailand

    , Humanities and Social Sciences Communications, Vol: 11, ISSN: 2662-9992

    Cross-cultural design has emerged as a pivotal domain of significance within the context of globalization. In the field of cross-cultural design, designers are tasked with addressing user requirements and identity characteristic contexts across diverse cultural backgrounds, aiming to achieve enhanced service delivery and cultural dissemination outcomes. Nonetheless, the landscape of contemporary fashion design research exhibits a noticeable dearth in studies that effectively integrate with cross-cultural design. This study selects the iconic cultural symbols of the Chinese loong (dragon) and Thai naga as case subjects, embarking upon research that employs costume design as a medium and bridge for cross-cultural design and communication. The research methodology integrates qualitative and quantitative approaches, including field investigations, participatory research, and Analytic Hierarchy Process (AHP) analysis, thereby substantiating theoretical constructs through empirical investigation. The study proposes that cross-cultural costume design, undertaken with the purpose of cross-cultural communication, can be conceptualized as a cyclical process involving multiple encoding and decoding iterations. The research elaborates on how costume, functioning as a non-verbal language, serve as a medium for facilitating cross-cultural interactions. Furthermore, the design extraction of cultural symbols is approached through a four-tiered framework. By articulating its research perspective, methodologies, and design cases, this study contributes valuable insights to researchers and practitioners engaged in cross-cultural design and related fields.
  • Journal article
    Patel AM, Baxter W, Porat T, 2024,

    Towards guidelines for designing holistic integrated information visualisations [hi-viz] for time-critical contexts: a systematic review

    , Journal of Medical Internet Research, ISSN: 1438-8871
  • Journal article
    Aunger R, Deterding S, Zhao X, Baxter Wet al., 2024,

    Applying the Barker School concept of 'behaviour settings' to virtual contexts

    , Philosophical Transactions of the Royal Society B: Biological Sciences, Vol: 379, ISSN: 0962-8436

    People are spending more and more time interacting with virtual objects and environments. We argue that Roger Barker's concept of a 'behaviour setting' can be usefully applied to such experiences with relatively little modification if we recognize subjective aspects of such experiences such as presence and immersion. We define virtual behaviour settings as virtual environments where the partly or fully digital milieu is synomorphic with and circumjacent to embodied behaviour, as opposed to the fragmented behaviour settings of much-mediated interaction. We present two tools that can help explain and predict the outcomes of virtual experiences-the behaviour setting canvas (BSC) and model-and demonstrate their utility through examples. We conclude that the behaviour setting concept is helpful in both designing virtual environments and understanding their impact, while virtual environments offer a powerful new methodological paradigm for studying behaviour settings. This article is part of the theme issue 'People, places, things, and communities: expanding behaviour settings theory in the twenty-first century'.
  • Journal article
    Baker CE, Yu X, Lovell B, Tan R, Patel S, Ghajari Met al., 2024,

    How well do popular bicycle helmets protect from different types of head injury?

    , Annals of Biomedical Engineering, ISSN: 0090-6964

    Bicycle helmets are designed to protect against skull fractures and associated focal brain injuries, driven by helmet standards. Another type of head injury seen in injured cyclists is diffuse brain injuries, but little is known about the protection provided by bicycle helmets against these injuries. Here, we examine the performance of modern bicycle helmets in preventing diffuse injuries and skull fractures under impact conditions that represent a range of real-world incidents. We also investigate the effects of helmet technology, price, and mass on protection against these pathologies. 30 most popular helmets among UK cyclists were purchased within 9.99-135.00 GBP price range. Helmets were tested under oblique impacts onto a 45° anvil at 6.5 m/s impact speed and four locations, front, rear, side, and front-side. A new headform, which better represents the average human head's mass, moments of inertia and coefficient of friction than any other available headforms, was used. We determined peak linear acceleration (PLA), peak rotational acceleration (PRA), peak rotational velocity (PRV), and BrIC. We also determined the risk of skull fractures based on PLA (linear risk), risk of diffuse brain injuries based on BrIC (rotational risk), and their mean (overall risk). Our results show large variation in head kinematics: PLA (80-213 g), PRV (8.5-29.9 rad/s), PRA (1.6-9.7 krad/s2), and BrIC (0.17-0.65). The overall risk varied considerably with a 2.25 ratio between the least and most protective helmet. This ratio was 1.76 for the linear and 4.21 for the rotational risk. Nine best performing helmets were equipped with the rotation management technology MIPS, but not all helmets equipped with MIPS were among the best performing helmets. Our comparison of three tested helmets which have MIPS and no-MIPS versions showed that MIPS reduced rotational kinematics, but not linear kinematics. We found no significant effect of helmet price on exposure-adjusted inju
  • Journal article
    Yu Z, Childs P, Ge Y, Nanayakkara Tet al., 2024,

    Whisker sensor for robot environments perception: a review

    , IEEE Sensors Journal, Vol: 24, Pages: 28504-28521, ISSN: 1530-437X

    Nocturnal mammals such as rats heavily depend onwhisker based tactile perception to find their way through burrows and to identify objects. There is diversity in the whiskers in terms of the physical structure and nervous innervation. The robotics community has developed many different whisker sensors inspired by this biological basis. They take diverse mechanical, electronic, andcomputational approaches to use whiskers to identify the geometry, mechanical properties, and texture of objects. Some work address specific object features and some others address multiple features. Therefore, it is vital to have a comprehensive discussion of the literature and to understand the merits of both bio-inspired and pureengineered approaches to whisker based tactile perception. In this paper we report and discuss the progress in following areas: The body of mammalian whisker follicle, unimodal whiskered sensors, multimodal whiskered sensors with variable stiffness that can capture tactile sensory stimuli of different frequencies, obstacles detection, shape detection, texture classification and robot navigation using whiskers.
  • Journal article
    Baker CE, Martin P, Montemeglio A, Li R, Wilson M, Sharp DJ, Ghajari Met al., 2024,

    Inherent uncertainty in pedestrian collision reconstruction: How evidence variability affects head kinematics and injury prediction.

    , Accid Anal Prev, Vol: 208

    Reconstructing individual cases from real-world collision data is used as a tool to better understand injury biomechanics and determine injury thresholds. However, real-world data tends to have inherent uncertainty within parameters, such as ranges of impact speed, pre-impact pedestrian stance or pedestrian anthropometric characteristics. The implications of this input parameter uncertainty on the conclusions made from case reconstruction about injury biomechanics and risk is not well investigated, with a 'best-fit' approach more frequently adopted, leaving uncertainty unexplored. This study explores the implications of uncertain parameters in real-world data on the biomechanical kinematic metrics related to head injury risk in reconstructed real-world pedestrian-car collisions. We selected six pedestrian-car cases involving seven pedestrians from the highly detailed GB Road Accident In-Depth Studies (RAIDS) database. The collisions were reconstructed from the images, damage measurements and dynamics available in RAIDS. For each case, we varied input parameters within uncertain ranges and report the range of head kinematic metrics from each case. This includes variations of reconstructed collision scenarios that fits within the constraints of the available evidence. We used a combination of multibody and finite element modelling in Madymo to test whether the effect of input data uncertainty is the same on the initial head-vehicle and latter head-ground impact phase. Finally, we assessed whether the predicted range of head kinematics correctly predicted the injuries sustained by the pedestrian. Varying the inputs resulted in a range of output head kinematic parameters. Real-world evidence such as CCTV footage enabled predicted simulated values to be further constrained, by ruling out unrealistic scenarios which do not fit the available evidence. We found that input data uncertainty had different implications for the initial head-vehicle and latter head-ground impact
  • Conference paper
    Hu X, Li J, Picinali L, Hogg Aet al., 2024,

    HRTF spatial upsampling in the spherical harmonics domain employing a generative adversarial network

    , 27th International Conference on Digital Audio Effects (DAFx24), Publisher: University of Surrey, Pages: 396-403

    A Head-Related Transfer Function (HRTF) is able to capture alterations a sound wave undergoes from its source before it reaches the entrances of a listener’s left and right ear canals, and is imperative for creating immersive experiences in virtual and augmented reality (VR/AR). Nevertheless, creating personalized HRTFs demands sophisticated equipment and is hindered by time-consuming data acquisition processes. To counteract these challenges, various techniques for HRTF interpolation and up-sampling have been proposed. This paper illustrates how Generative Adversarial Networks (GANs) can be applied to HRTF data upsampling in the spherical harmonics domain. We propose using Autoencoding Generative Adversarial Networks (AE-GAN) to upsample low-degree spherical harmonics coefficients and get a more accurate representation of the full HRTF set. The proposed method is bench-marked against two baselines: barycentric interpolation and HRTFselection. Results from log-spectral distortion (LSD) evaluation suggest that the proposed AE-GAN has significant potential for upsampling very sparse HRTFs, achieving 17% improvement over baseline methods.
  • Journal article
    Ferraro P, Yu JY, Ghosh R, Alam SE, Marecek J, Wirth F, Shorten Ret al., 2024,

    On unique ergodicity of coupled AIMD flows

    , International Journal of Control, Vol: 97, Pages: 2151-2161, ISSN: 0020-7179

    The AIMD algorithm, which underpins the Transmission Control Protocol (TCP) for transporting data packets in communication networks, is perhaps the most successful control algorithm ever deployed. Recently, its use has been extended beyond communication networks, and successful applications of the AIMD algorithm have been reported in transportation, energy, and mathematical biology. A very recent development in the use of AIMD is its application in solving large-scale optimisation and distributed control problems without the need for inter-agent communication. In this context, an interesting problem arises when multiple AIMD networks are coupled in some sense (usually through a nonlinearity). The purpose of this note is to prove that such systems in certain settings inherit the ergodic properties of individual AIMD networks. This result has important consequences for the convergence of the aforementioned optimisation algorithms. The arguments in the paper also correct conceptual and technical errors in Alam et al. (2020, The convergence of finite-averaging of AIMD for distributed heterogeneous resource allocations. arXiv:2001.08083 [math.OC].).
  • Journal article
    Lin L, Hamedmoghadam H, Shorten R, Stone Let al., 2024,

    Quantifying indirect and direct vaccination effects arising in the SIR model.

    , J R Soc Interface, Vol: 21

    Vaccination campaigns have both direct and indirect effects that act to control an infectious disease as it spreads through a population. Indirect effects arise when vaccinated individuals block disease transmission in any infection chain they are part of, and this in turn can benefit both vaccinated and unvaccinated individuals. Indirect effects are difficult to quantify in practice but, in this article, working with the susceptible-infected-recovered (SIR) model, they are analytically calculated in important cases, through pivoting on the final size formula for epidemics. Their relationship to herd immunity is also clarified. The analysis allows us to identify the important distinction between quantifying the indirect effects of vaccination at the 'population level' versus the 'per capita' level, which often results in radically different conclusions. As an example, our analysis unpacks why the population-level indirect effect can appear significantly larger than its per capita analogue. In addition, we consider a recently proposed epidemiological non-pharmaceutical intervention (by the means of recovered individuals) used over the COVID-19 pandemic, referred to as 'shielding', and study its impact on our mathematical analysis. The shielding scheme is extended to take advantage of vaccination including imperfect vaccination.
  • Journal article
    Wu B, 2024,

    Addressing the battery talent shortage with interdisciplinarity

    , Nature Energy, Vol: 9, Pages: 1044-1045, ISSN: 2058-7546
  • Journal article
    Pan Y, Ruan H, Wu B, Regmi YN, Wang H, Brandon NPet al., 2024,

    A machine learning driven 3D+1D model for efficient characterization of proton exchange membrane fuel cells

    , Energy and AI, Vol: 17, ISSN: 2666-5468

    The computational demands of 3D continuum models for proton exchange membrane fuel cells remain substantial. One prevalent approach is the hierarchical model combining a 2D/3D flow field with a 1D sub-model for the catalyst layers and membrane. However, existing studies often simplify the 1D domain to a linearized 0D lumped model, potentially resulting in significant errors at high loads. In this study, we present a computationally efficient neural network driven 3D+1D model for proton exchange membrane fuel cells. The 3D sub-model captures transport in the gas channels and gas diffusion layers and is coupled with a 1D electrochemical sub-model for microporous layers, membrane, and catalyst layers. To reduce computational intensity of the full 1D description, a neural network surrogates the 1D electrochemical sub-model for coupling with the 3D domain. Trained by model-generated large synthetic datasets, the neural network achieves root mean square errors of less than 0.2%. The model is validated against experimental results under various relative humidities. It is then employed to investigate the nonlinear distribution of internal states under different operating conditions. With the neural network operating at 0.5% of the computing cost of the 1D sub-model, the hybrid model preserves a detailed and nonlinear representation of the internal fuel cell states while maintaining computational costs comparable to conventional 3D+0D models. The presented hybrid data-driven and physical modeling framework offers high accuracy and computing speed across a broad spectrum of operating conditions, potentially aiding the rapid optimization of both the membrane electrode assembly and the gas channel geometry.
  • Journal article
    Heath BE, Suzuki R, LePenru NP, Skinner J, Orme CDL, Ewers RM, Sethi SS, Picinali Let al., 2024,

    Spatial ecosystem monitoring with a Multichannel Acoustic Autonomous Recording Unit (MAARU)

    , Methods in Ecology and Evolution, Vol: 15, Pages: 1568-1579, ISSN: 2041-210X

    1. Multi-microphone recording adds spatial information to recorded audio with emerging applications in ecosystem monitoring. Specifically placing sounds in space can improve animal count accuracy, locate illegal activity like logging and poaching, track animals to monitor behaviour and habitat use and allow for ‘beamforming’ to amplify sounds from target directions for downstream classification. Studies have shown many advantages of spatial acoustics, but uptake remains limited as the equipment is often expensive, complicated, inaccessible or only suitable for short-term deployments.2. With an emphasis on enhanced uptake and usability, we present a low-cost, open-source, six-channel recorder built entirely from commercially available components which can be integrated into a solar-powered, online system. The MAARU (Multichannel Acoustic Autonomous Recording Unit) works as an independent node in long-term autonomous, passive and/or short-term deployments. Here, we introduce MAARU's hardware and software and present the results of lab and field tests investigating the device's durability and usability.3. MAARU records multichannel audio with similar costs and power demands to equivalent omnidirectional recorders. MAARU devices have been deployed in the United Kingdom and Brazil, where we have shown MAARUs can accurately localise pure tones up to 6 kHz and bird calls as far as 8 m away (±10° range, 100% and >60% of signals, respectively). Louder calls may have even further detection radii. We also show how beamforming can be used with MAARUs to improve species ID confidence scores.4. MAARU is an accessible, low-cost option for those looking to explore spatial acoustics accurately and easily with a single device, and without the formidable expenses and processing complications associated with establishing arrays. Ultimately, the added directional element of the multichannel recording provided by MAARU allows for enhanced recording
  • Journal article
    Espinoza F, Re MD, Calvo RA, 2024,

    Designing with community health workers in Latin America

    , Interactions, Vol: 31, Pages: 55-57, ISSN: 1072-5520

    Community + Culture features practitioner perspectives on designing technologies for and with communities. We highlight compelling projects and provocative points of view that speak to both community technology practice and the interaction design field as a whole.
  • Journal article
    Kench S, Squires I, Dahari A, Brosa Planella F, Roberts SA, Cooper SJet al., 2024,

    Li-ion battery design through microstructural optimization using generative AI

    , Matter, ISSN: 2590-2385
  • Journal article
    Li H, Zhou H, Li N, 2024,

    An integrated convolutional neural network-based surrogate model for crashworthiness performance prediction of hot-stamped vehicle panel components

    , MATEC Web of Conferences, Vol: 401, ISSN: 2261-236X

    During the structural design of vehicle components, Finite Element (FE) modelling has been extensively used for simulations of physical experiments. A typical design optimisation task requires iterative simulations to identify the optimum design, where FE simulations can be too time-consuming. Surrogate models have been developed to approximate complex simulations, which can reduce computational time and improve the efficiency of the design cycle. This paper presents a novel application of convolutional neural network (CNN) on rapid predictions of crashworthiness performance of vehicle panel components considering manufacturability. The dataset for training the model was generated based on the FE results of hot-stamped ultra-high strength steel (UHSS) B-pillar components. The formed components were analysed with a simplified lateral crash test to evaluate the deformation under impact. The trained model can instantly predict the deformation of the designed component with high accuracy compared to the FE results. Due to its high computational efficiency and precision, the surrogate model enables faster and more extensive design evaluations.

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