Results
- Showing results for:
- Reset all filters
Search results
-
Journal articleRuan H, Chen J, Ai W, et al., 2022,
Generalised diagnostic framework for rapid battery degradation quantification with deep learning
, Energy and AI, Vol: 9, Pages: 1-13, ISSN: 2666-5468Diagnosing lithium-ion battery degradation is challenging due to the complex, nonlinear, and path-dependent nature of the problem. Here, we develop a generalised and rapid degradation diagnostic method with a deep learning-convolutional neural network that quantifies degradation modes of batteries aged under various conditions in 0.012 s without feature engineering. Rather than performing extensive aging experiments, synthetic aging datasets for network training are generated. This dramatically lowers training cost/time, with these datasets covering almost all the aging paths, enabling a generalised degradation diagnostic framework. We show that the five thermodynamic degradation modes are correlated, and systematically elucidate their correlations. We thus propose a non-invasive comprehensive evaluation method and find the degradation diagnostic errors to be less than 1.22% for three leading commercial battery chemistries. The comparison with the traditional diagnostic methods confirms the high accuracy and fast nature of the proposed approach. Quantification of degradation modes with the partial discharge/charge data using the proposed diagnostic framework validates the real-world feasibility of this approach. This work, therefore, enables the promise of online identification of battery degradation and efficient analysis of large-data sets, unlocking potential for long lifetime energy storage systems.
-
Journal articleTosatto A, Beseler XM, Ostergaard J, et al., 2022,
North Sea Energy Islands: Impact on national markets and grids
, ENERGY POLICY, Vol: 167, ISSN: 0301-4215 -
Journal articleZhang J, Zhang L, Zhao Y, et al., 2022,
High-Performance Rechargeable Aluminum-Ion Batteries Enabled by Composite FeF<sub>3</sub> @ Expanded Graphite Cathode and Carbon Nanotube-Modified Separator
, ADVANCED ENERGY MATERIALS, Vol: 12, ISSN: 1614-6832- Author Web Link
- Cite
- Citations: 6
-
Journal articleAnderson J, Cardin M-A, Grogan P, 2022,
Design and analysis of flexible multi-layer staged deployment for satellite mega-constellations under demand uncertainty
, Acta Astronautica, Vol: 198, ISSN: 0094-5765Internet satellite constellations are expected to play an important role in accommodating the rising global demand for internet access. Such rise in demand, however, is highly uncertain. Staged deployment is an approach that provides flexibility to tackle demand uncertainty by enabling the real option to reconfigure a constellation if demand changes. Advancements in satellite technology have led to the emergence of multi-layered constellations. This opens the opportunity to enhance staged deployment by enabling an additional real option: adding a new layer to a constellation. This real option has no associated reconfiguration costs, and therefore has the potential to reduce the cost of staged systems deployment. This paper proposes a framework to design multi-layer staged deployment systems and analyse their effectiveness in modern mega-constellations under global demand uncertainty. The framework is applied to four case studies based on market projections. Results show that multi-layer staged deployment decreases the expected life-cycle cost (ELCC) by 42.8% compared to optimal traditional single-layer deployment. Multi-layer staged deployment is more cost effective than single-layer staged deployment in all practical cases, which decreases ELCC by 22.9% compared to traditional deployment. Several cost altering mechanisms in staged deployment are identified. The results and analysis provide improved economic performance and better resource utilization, thus contributing in the long term to improved sustainability and market resilience. An accompanying decision support system provides system engineers with valuable insights on how to reduce deployment costs using the proposed multi-layered staged strategy.
-
Journal articleMao A, Giraudet CSE, Liu K, et al., 2022,
Automated identification of chicken distress vocalizations using deep learning models.
, Journal of the Royal Society Interface, Vol: 19, Pages: 1-11, ISSN: 1742-5662The annual global production of chickens exceeds 25 billion birds, which are often housed in very large groups, numbering thousands. Distress calling triggered by various sources of stress has been suggested as an 'iceberg indicator' of chicken welfare. However, to date, the identification of distress calls largely relies on manual annotation, which is very labour-intensive and time-consuming. Thus, a novel convolutional neural network-based model, light-VGG11, was developed to automatically identify chicken distress calls using recordings (3363 distress calls and 1973 natural barn sounds) collected on an intensive farm. The light-VGG11 was modified from VGG11 with significantly fewer parameters (9.3 million versus 128 million) and 55.88% faster detection speed while displaying comparable performance, i.e. precision (94.58%), recall (94.89%), F1-score (94.73%) and accuracy (95.07%), therefore more useful for model deployment in practice. To additionally improve light-VGG11's performance, we investigated the impacts of different data augmentation techniques (i.e. time masking, frequency masking, mixed spectrograms of the same class and Gaussian noise) and found that they could improve distress calls detection by up to 1.52%. Our distress call detection demonstration on continuous audio recordings, shows the potential for developing technologies to monitor the output of this call type in large, commercial chicken flocks.
-
Journal articleDeterding S, Malmdorf Andersen M, Kiverstein J, et al., 2022,
Mastering uncertainty: a predictive processing account of enjoying uncertain success in video game play
, Frontiers in Psychology, Vol: 13, Pages: 1-16, ISSN: 1664-1078Why do we seek out and enjoy uncertain success in playing games? Game designers and researchers suggest that games whose challenges match player skills afford engaging experiences of achievement, competence, or effectance – of doing well. Yet, current models struggle to explain why such balanced challenges best afford these experiences and do not straightforwardly account for the appeal of high- and low-challenge game genres like Idle and Soulslike games. In this article, we show that Predictive Processing (PP) provides a coherent formal cognitive framework which can explain the fun in tackling game challenges with uncertain success as the dynamic process of reducing uncertainty surprisingly efficiently. In gameplay as elsewhere, people enjoy doing better than expected, which can track learning progress. In different forms, balanced, Idle, and Soulslike games alike afford regular accelerations of uncertainty reduction. We argue that this model also aligns with a popular practitioner model, Raph Koster’s Theory of Fun for Game Design, and can unify currently differentially modelled gameplay motives around competence and curiosity.
-
Journal articleLalitharatne TD, Costi L, Hasheem R, et al., 2022,
Face mediated human–robot interaction for remote medical examination
, Scientific Reports, Vol: 12, ISSN: 2045-2322Realtime visual feedback from consequences of actions is useful for future safety-critical human–robot interaction applications such as remote physical examination of patients. Given multiple formats to present visual feedback, using face as feedback for mediating human–robot interaction in remote examination remains understudied. Here we describe a face mediated human–robot interaction approach for remote palpation. It builds upon a robodoctor–robopatient platform where user can palpate on the robopatient to remotely control the robodoctor to diagnose a patient. A tactile sensor array mounted on the end effector of the robodoctor measures the haptic response of the patient under diagnosis and transfers it to the robopatient to render pain facial expressions in response to palpation forces. We compare this approach against a direct presentation of tactile sensor data in a visual tactile map. As feedback, the former has the advantage of recruiting advanced human capabilities to decode expressions on a human face whereas the later has the advantage of being able to present details such as intensity and spatial information of palpation. In a user study, we compare these two approaches in a teleoperated palpation task to find the hard nodule embedded in the remote abdominal phantom. We show that the face mediated human–robot interaction approach leads to statistically significant improvements in localizing the hard nodule without compromising the nodule position estimation time. We highlight the inherent power of facial expressions as communicative signals to enhance the utility and effectiveness of human–robot interaction in remote medical examinations.
-
Journal articleJi S, Ghajari M, Mao H, et al., 2022,
Use of brain biochemical models for monitoring impact exposure in contact sports
, Annals of Biomedical Engineering, Vol: 50, Pages: 1389-1408, ISSN: 0090-6964Head acceleration measurement sensors are now widely deployed in the field to monitor head kinematic exposure in contact sports. The wealth of impact kinematics data provides valuable, yet challenging, opportunities to study the biomechanical basis of mild traumatic brain injury (mTBI) and subconcussive kinematic exposure. Head impact kinematics are translated into brain mechanical responses through physics-based computational simulations using validated brain models to study the mechanisms of injury. First, this article reviews representative legacy and contemporary brain biomechanical models primarily used for blunt impact simulation. Then, it summarizes perspectives regarding the development and validation of these models, and discusses how simulation results can be interpreted to facilitate injury risk assessment and head acceleration exposure monitoring in the context of contact sports. Recommendations and consensus statements are presented on the use of validated brain models in conjunction with kinematic sensor data to understand the biomechanics of mTBI and subconcussion. Mainly, there is general consensus that validated brain models have strong potential to improve injury prediction and interpretation of subconcussive kinematic exposure over global head kinematics alone. Nevertheless, a major roadblock to this capability is the lack of sufficient data encompassing different sports, sex, age and other factors. The authors recommend further integration of sensor data and simulations with modern data science techniques to generate large datasets of exposures and predicted brain responses along with associated clinical findings. These efforts are anticipated to help better understand the biomechanical basis of mTBI and improve the effectiveness in monitoring kinematic exposure in contact sports for risk and injury mitigation purposes.
-
Journal articleGuo B, Fu Y, Wang J, et al., 2022,
Strategies and characterization methods for achieving high performance PEO-based solid-state lithium-ion batteries
, CHEMICAL COMMUNICATIONS, Vol: 58, Pages: 8182-8193, ISSN: 1359-7345- Author Web Link
- Cite
- Citations: 13
-
Book chapterReyes-Lecuona A, Bouchara T, Picinali L, 2022,
Immersive sound for XR
, Roadmapping Extended Reality: Fundamentals and Applications, Pages: 75-102Sound plays a very important role in everyday life as well as in XR applications, as it will be explained in this chapter. Recent advances and challenges in immersive audio research are presented, discussing how, why, and to which extent there is potential for further development of these technologies applied to XR. The fundamentals of immersive audio rendering for XR are introduced before presenting the main technological challenges still open in the area. Finally, a series of future applications is presented, which the authors envision being examples of the potential of immersive audio in XR, and a research roadmap is outlined.
-
Journal articleIjaz K, Tran TTM, Kocaballi AB, et al., 2022,
Design considerations for immersive virtual reality applications for older adults: a scoping review
, Multimodal Technologies and Interaction, Vol: 6, Pages: 1-26, ISSN: 2414-4088Immersive virtual reality (iVR) has gained considerable attention recently with increasing affordability and accessibility of the hardware. iVR applications for older adults present tremendous potential for diverse interventions and innovations. The iVR literature, however, provides a limited understanding of guiding design considerations and evaluations pertaining to user experience (UX). To address this gap, we present a state-of-the-art scoping review of literature on iVR applications developed for older adults over 65 years. We performed a search in ACM Digital Library, IEEE Xplore, Scopus, and PubMed (1 January 2010–15 December 2019) and found 36 out of 3874 papers met the inclusion criteria. We identified 10 distinct sets of design considerations that guided target users and physical configuration, hardware use, and software design. Most studies carried episodic UX where only 2 captured anticipated UX and 7 measured longitudinal experiences. We discuss the interplay between our findings and future directions to design effective, safe, and engaging iVR applications for older adults.
-
Journal articleSadan MK, Jeon M, Yun J, et al., 2022,
Ultrafast sodium-ion storage in an interconnected Ni/Ni<sub>3</sub>S<sub>2</sub> nanocomposite with long-term cycling performance
, JOURNAL OF ALLOYS AND COMPOUNDS, Vol: 909, ISSN: 0925-8388 -
Journal articleComunita M, Gerino A, Picinali L, 2022,
PlugSonic: a web- and mobile-based platform for dynamic and navigable binaural audio
, Eurasip Journal on Audio, Speech, and Music Processing, Vol: 18, ISSN: 1687-4714PlugSonic is a series of web- and mobilebased applications designed to: edit samples and applyaudio effects (PlugSonic Sample), create and experience dynamic and navigable soundscapes and sonic narratives (PlugSonic Soundscape). The audio processingwithin PlugSonic is based on the Web Audio API whilethe binaural rendering uses the 3D Tune-In Toolkit.Exploration of soundscapes in a physical space is madepossible by adopting Apple’s ARKit. The present paperdescribes the implementation details, the signal processing chain and the necessary steps to curate and experience a soundscape. We also include some metricsand performance details. The main goal of PlugSonic isto give users a complete set of tools, without the needfor specific devices, external software and/or hardware,specialised knowledge or custom development; with theidea that spatial audio has the potential to become areadily accessible and easy to understand technology,for anyone to adopt, whether for creative or researchpurposes.
-
Journal articleCooper SJ, Roberts SA, Liu Z, et al., 2022,
Methods—Kintsugi imaging of battery electrodes: distinguishing pores from the carbon binder domain using Pt deposition
, Journal of The Electrochemical Society, Vol: 169, ISSN: 0013-4651The mesostructure of porous electrodes used in lithium-ion batteries strongly influences cell performance. Accurate imaging of the distribution of phases in these electrodes would allow this relationship to be better understood through simulation. However, imaging the nanoscale features in these components is challenging. While scanning electron microscopy is able to achieve the required resolution, it has well established difficulties imaging porous media. This is because the flat imaging planes prepared using focused ion beam milling will intersect with the pores, which makes the images hard to interpret as the inside walls of the pores are observed. It is common to infiltrate porous media with resin prior to imaging to help resolve this issue, but both the nanoscale porosity and the chemical similarity of the resins to the battery materials undermine the utility of this approach for most electrodes. In this study, a technique is demonstrated which uses in situ infiltration of platinum to fill the pores and thus enhance their contrast during imaging. Reminiscent of the Japanese art of repairing cracked ceramics with precious metals, this technique is referred to as the kintsugi method. The images resulting from applying this technique to a conventional porous cathode are presented and then segmented using a multi-channel convolutional method. We show that while some cracks in active material particles were empty, others appear to be filled (perhaps with the carbon binder phase), which will have implications for the rate performance of the cell. Energy dispersive X-ray spectroscopy was used to validate the distribution of phases resulting from image analysis, which also suggested a graded distribution of the binder relative to the carbon additive. The equipment required to use the kintsugi method is commonly available in major research facilities and so we hope that this method will be rapidly adopted to improve the imaging of electrode materials and porous media i
-
Conference paperWang Y, O'Keeffe J, Qian Q, et al., 2022,
KinoJGM: A framework for efficient and accurate quadrotor trajectory generation and tracking in dynamic environments
, IEEE International Conference on Robotics and Automation (ICRA), Publisher: IEEE, Pages: 11036-11043, ISSN: 1050-4729Unmapped areas and aerodynamic disturbances render autonomous navigation with quadrotors extremely challenging. To fly safely and efficiently, trajectory planners and trackers must be able to navigate unknown environments with unpredictable aerodynamic effects in real-time. When encountering aerodynamic effects such as strong winds, most current approaches to quadrotor trajectory planning and tracking will not attempt to deviate from a determined plan, even if it is risky, in the hope that any aerodynamic disturbances can be resisted by a robust controller. This paper presents a novel systematic trajectory planning and tracking framework for autonomous quadrotors. We propose a Kinodynamic Jump Space Search (Kino-JSS) to generate a safe and efficient route in unknown environments with aerodynamic disturbances. A real-time Gaussian Process is employed to model the errors caused by aerodynamic disturbances, which we then integrate with a Model Predictive Controller to achieve efficient and accurate trajectory optimization and tracking. We demonstrate our system to improve the efficiency of trajectory generation in unknown environments by up to 75% in the cases tested, compared with recent state-of-the-art. We also show that our system improves the accuracy of tracking in selected environments with unpredictable aerodynamic effects. Our implementation is available in an open source package 1 1 https://github.com/Alex-yanranwang/Imperial-KinoJGM.
-
Journal articleYu X, Nguyen T, Wu T, et al., 2022,
Non-lethal blasts can generate cavitation in cerebrospinal fluid while severe helmeted impacts cannot: a novel mechanism for blast brain injury
, Frontiers in Bioengineering and Biotechnology, Vol: 10, ISSN: 2296-4185Cerebrospinal fluid (CSF) cavitation is a likely physical mechanism for producing traumatic brain injury (TBI) under mechanical loading. In this study, we investigated CSF cavitation under blasts and helmeted impacts which represented loadings in battlefield and road traffic/sports collisions. We first predicted the human head response under the blasts and impacts using computational modelling and found that the blasts can produce much lower negative pressure at the contrecoup CSF region than the impacts. Further analysis showed that the pressure waves transmitting through the skull and soft tissue are responsible for producing the negative pressure at the contrecoup region. Based on this mechanism, we hypothesised that blast, and not impact, can produce CSF cavitation. To test this hypothesis, we developed a one-dimensional simplified surrogate model of the head and exposed it to both blasts and impacts. The test results confirmed the hypothesis and computational modelling of the tests validated the proposed mechanism. These findings have important implications for prevention and diagnosis of blast TBI.
-
Journal articleTomaszewska A, Doel R, Parkes M, et al., 2022,
Investigating Li Plating Distribution Caused By a Thermal Gradient through Modelling, Differential Voltage, and Post-Mortem Analysis
, ECS Meeting Abstracts, Vol: MA2022-01, Pages: 186-186<jats:p> Relatively slow charging speeds are often quoted as a key barrier to customer acceptance of EVs. Currently, the charging rates are limited primarily by the risk of lithium plating. While traditionally lithium plating has been associated with low temperature charging, recent reports point to the fact that thermal heterogeneity can significantly affect the plating behaviour, sometimes making it more likely or accelerated in the warmer regions in a cell [1][2]. In EVs, through-plane thermal gradients often develop across individual pouch cells due to the widespread use of surface cooling, particularly during fast charging, when the heat generation rates are also increased. This work investigates the effects of such through-plane thermal gradients on the lithium plating behaviour using a multilayer 2D electrochemical-thermal model and high-rate cycling experiments. The results show that the thermal gradient can result in preferential plating in either the colder or warmer cell regions, depending on the average cell temperature and the activation energies of solid diffusion and lithium plating. While the diffusion rates are slower in the colder cell layers, warmer ones attract higher currents and either of these effects may dominate the plating behaviour. The experimental validation consists of differential voltage analysis, post-mortem visual examination and measurement of remaining capacity in coin cells harvested from Li-ion cells fast charged under uniform temperatures and under thermal gradients. The limitations of DVA as a technique to quantify lithium plating are highlighted. These stem from the fact that the quantification technique requires assuming that only lithium stripping and no de-intercalation takes place up to the differential voltage minimum. In reality, the current is divided between both reactions, and both the temperature and concentration of the metallic lithium may affect the rate of stripping, shifting the location of the minimum
-
Conference paperCaputo C, Cardin M-A, Korre A, et al., 2022,
Energy System Evolution Strategies for Mobile Micro-grids using Deep Reinforcement Learning Flexibility Analysis
, Espoo, Finland, 32nd European Conference on Operational Research (EURO 2022) -
Journal articleCursi F, Bai W, Li W, et al., 2022,
Augmented neural network for full robot kinematic modelling in SE(3)
, IEEE Robotics and Automation Letters, Vol: 7, Pages: 7140-7147, ISSN: 2377-3766Due to the increasing complexity of robotic structures, modelling robots is becoming more and more challenging, and analytical models are very difficult to build. Machine learning approaches have shown great capabilities in learning complex mapping and have widely been used in robot model learning and control. Generally, the inverse kinematics is directly learned, yet, learning the forward kinematics is simpler and allows computing exploiting the optimality of the controllers. Nevertheless, the learning method has no knowledge about the differential relationship between the position and velocity mappings. Currently, few works have targeted learning full robot poses considering both position and orientation. In this letter, we present a novel feedforward Artificial Neural network (ANN) architecture to learn full robot pose in SE(3) incorporating differential relationships in the learning process. Simulation and real world experiments show the capabilities of the proposed network to properly model the robot pose and its advantages over standard ANN.
-
Journal articleMandeno P, Baxter WL, 2022,
Six principles for the design of better networking events
, Business Horizons, Vol: 65, Pages: 493-503, ISSN: 0007-6813Networking events are seen as an essential activity for the establishment and maintenance of professional connections. Despite their ubiquity and perceived importance, networking events are often ineffective and unenjoyable. Suggestions for the improvement of networking outcomes typically focus on event selection or participant capabilities. In this article, we posit that greater success can be achieved by improving the design of networking events themselves. We adopt a research through design approach to derive the design features that explain the success of Wok+Wine, a networking event that consistently delivers positive functional and experiential outcomes across a range of cultural and organizational contexts. From a synthesis of these design features, we derive six generalizable design principles that can support managers in the creation of better networking events as well as the analysis and selection of existing ones.
-
Journal articleWang AA, OKane SEJ, Brosa Planella F, et al., 2022,
Review of parameterisation and a novel database (LiionDB) for continuum Li-ion battery models
, Progress in Energ, Vol: 4, Pages: 1-40, ISSN: 2516-1083The Doyle–Fuller–Newman (DFN) framework is the most popular physics-based continuum-level description of the chemical and dynamical internal processes within operating lithium-ion-battery cells. With sufficient flexibility to model a wide range of battery designs and chemistries, the framework provides an effective balance between detail, needed to capture key microscopic mechanisms, and simplicity, needed to solve the governing equations at a relatively modest computational expense. Nevertheless, implementation requires values of numerous model parameters, whose ranges of applicability, estimation, and validation pose challenges. This article provides a critical review of the methods to measure or infer parameters for use within the isothermal DFN framework, discusses their advantages or disadvantages, and clarifies limitations attached to their practical application. Accompanying this discussion we provide a searchable database, available at www.liiondb.com, which aggregates many parameters and state functions for the standard DFN model that have been reported in the literature.
-
Journal articleNguyen QT, Mougenot C, 2022,
A systematic review of empirical studies on multidisciplinary design collaboration: findings, methods, and challenges
, Design Studies, Vol: 81, ISSN: 0142-694XWhile multidisciplinary collaboration is increasingly considered as a prerequisite for innovation in design, it is unclear what has been studied and what to investigate next. To addressthis, we conducted a systematic literature review on multidisciplinary design collaboration,focussing on what has been found, and how these studies have been implemented. Followinga PRISMA approach, 17 papers were selected for a critical review. A co-occurrence analysisfound that the selected literature covered five themes centred on communication, all highlighting the importance of shared understanding in multidisciplinary design collaboration.Further analysis revealed biases and differences between the methodological approach followed in the studies. For future research, we suggest investigating two under-explored areasof design collaboration: distributed work and digital/service-oriented design activities.
-
Journal articleCursi F, Bai W, Yeatman EM, et al., 2022,
Model learning with backlash compensation for a tendon-driven surgical Robot
, IEEE Robotics and Automation Letters, Vol: 7, Pages: 7958-7965, ISSN: 2377-3766Robots for minimally invasive surgery are becoming more and more complex, due to miniaturization and flexibility requirements. The vast majority of surgical robots are tendon-driven and this, along with the complex design, causes high nonlinearities in the system which are difficult to model analytically. In this work we analyse how incorporating a backlash model and compensation can improve model learning and control. We combine a backlash compensation technique and a Feedforward Artificial Neural Network (ANN) with differential relationships to learn the kinematics at position and velocity level of highly articulated tendon-driven robots. Experimental results show that the proposed backlash compensation is effective in reducing nonlinearities in the system, that compensating for backlash improves model learning and control, and that our proposed ANN outperforms traditional ANN in terms of path tracking accuracy.
-
Journal articleHong F, Tendera L, Myant C, et al., 2022,
Vacuum-Formed 3D Printed Electronics: Fabrication of Thin, Rigid and Free-Form Interactive Surfaces
, SN Computer Science, Vol: 3, ISSN: 2662-995XVacuum-forming is a common manufacturing technique for constructing thin plastic shell products by pressing heated plastic sheets onto a mold using atmospheric pressure. Vacuum-forming is ubiquitous in packaging and casing products in the industry, spanning fast moving consumer goods to connected devices. Integrating advanced functionality, which may include sensing, computation and communication, within thin structures is desirable for various next-generation interactive devices. Hybrid additive manufacturing techniques like thermoforming are becoming popular for prototyping freeform surfaces owing to their design flexibility, speed and cost-effectiveness. This paper presents a new hybrid method for constructing thin, rigid and free-form interconnected surfaces via fused deposition modelling (FDM) 3D printing and vacuum-forming that builds on recent advances in thermoforming circuits. 3D printing the sheet material allows for the embedding of conductive traces within thin layers of the substrate, which can be vacuum-formed but remain conductive and insulated. This is an unexplored fabrication technique within the context of designing and manufacturing connected things. In addition to explaining the method, this paper characterizes the behavior of vacuum-formed 3D printed sheets, analyses the electrical performance of printed traces after vacuum-forming, and showcases a range of sample artefacts constructed using the technique. In addition, the paper describes a new design interface for designing conformal interconnects that allows designers to draw conductive patterns in 3D and export pre-distorted sheet models ready to be printed.
-
Journal articlePetropoulos F, Apiletti D, Assimakopoulos V, et al., 2022,
Forecasting: theory and practice
, INTERNATIONAL JOURNAL OF FORECASTING, Vol: 38, Pages: 705-871, ISSN: 0169-2070 -
Journal articleAlibasa MJ, Purwanto RW, Yacef K, et al., 2022,
Doing and feeling: relationships between moods, productivity and task-switching
, IEEE Transactions on Affective Computing, Vol: 13, Pages: 1140-1154, ISSN: 1949-3045Digital technology influences behaviours, moods and wellbeing. The relationships are complex, but users are increasingly interested in finding how to balance a digital life with psychological wellbeing. We present an approach for investigating the relationship between lifestyle aspects and digital technology usage patterns that combines MindGauge, a mobile app enabling users collect and analyse their moods and behaviours, with a productivity tool (RescueTime). We then report a 16-month study in which we collected computer and smartphone usage and self-reports from 72 participants. We present methods for analysing the relationship between productivity, task-switching, mood and lifestyle, and more specifically how digital technology usage associates with productivity and task-switching. Our study also investigates how lifestyle aspects (sleep quality, physical activity, workload, social interaction and alcoholic drink consumption) relate to mood, task-switching and productivity. Results show that more frequent task-switching is associated with negative moods. A few lifestyle aspects, such as sleep quality and physical activity, had a significant relationship with positive moods. We also contribute a mood detection model that utilise both digital footprints and lifestyle contexts, yielding an accuracy of 87%. The study provides evidence that such methods can be used to understand the impact of technology on wellbeing.
-
Journal articleSowe J, Varela Barreras J, Schimpe M, et al., 2022,
Model-informed battery current derating strategies: Simple methods to extend battery lifetime in islanded mini-grids
, Journal of Energy Storage, Vol: 51, Pages: 1-9, ISSN: 2352-152XIslanded mini-grids with batteries are crucial to enable universal access to energy. However, batteries are still costly, and how to select and operate them in an optimal manner is often unclear. The combination of variable climates with simple and low-cost passive thermal management also poses a challenge. Many techno-economic sizing tools usually consider simple battery degradation models, which disregard the impact of climatic conditions and operating strategy on battery performance. This study uses a semi-empirical Li-ion battery degradation model alongside an open-source techno-economic model to capture key insights. These are used to inform simple state of charge and temperature-based current derating strategies to increase lifetime. We demonstrate that such strategies can increase battery lifetime by 45% or 5–7 years in commercial systems already operational. It was found that, irrespective of climatic conditions, 80–90% of capacity fade can be attributed to calendar aging, due to low C-rates. SOC-based derating was found to be the most effective strategy, with temperature-based derating being less effective at extending lifetime and also leading to increased blackout periods. These results highlight the importance of accurate degradation modelling to achieve lifetime extension through improved operational strategies.
-
Journal articleNikam S, Wu H, Harkin R, et al., 2022,
On the application of the anisotropic enhanced thermal conductivity approach to thermal modelling of laser-based powder bed fusion processes
, Additive Manufacturing, Vol: 55, ISSN: 2214-7810Computational simulation of the Powder Bed Fusion (PBF) process is a useful tool for predicting and analysing melt pool geometry during the deposition process. Advanced models that use Computational Fluid Dynamics (CFD) can accurately simulate the complex melt pool dynamics of the process but are typically computationally onerous to implement. CFD models require thermophysical data over a large temperature range that may be difficult to acquire for the material systems of interest. Heat conduction models, which are useful to industrial end users are easier to implement, but their accuracy can be compromised. The main difference between heat conduction and CFD modelling is the absence of convection (especially Marangoni convection). However, several sources in literature have highlighted a simple approach to mimicking the effects of Marangoni convection on the melt pool by artificially increasing the thermal conductivity of the liquid. However, due to its simplicity and lack of agreement within literature, the modified heat conduction approach is neither sufficiently robust nor universally consistent. Comparison to experimental data is lacking. In the present work, the heat conduction model is modified using an orthotropic description of anisotropic thermal conductivity in the liquid phase by applying directional correction factors. The correction factors are calibrated by comparing the predicted geometry against experimentally-obtained melt pool dimensions for single-layer, multiple tracks in Ti-6Al-4V processed by laser-PBF. After appropriate correction factors were selected, the modified heat conduction model gave results in good agreement with experiments. To test the general applicability of the approach, data from literature were analysed and simulated using the model. After correction factors were adjusted accordingly, the simulated results were validated over the range of power levels and scan speeds.
-
Journal articleCacciarelli D, Kulahci M, 2022,
A novel fault detection and diagnosis approach based on orthogonal autoencoders
, Computers & Chemical Engineering, Vol: 163, Pages: 107853-107853, ISSN: 0098-1354 -
Journal articleJedwab RM, Hutchinson AM, Manias E, et al., 2022,
<p>Change in nurses' psychosocial characteristics pre- and post-electronic medical record system implementation coinciding with the SARS-CoV-2 pandemic: pre- and post-cross-sectional surveys</p>
, INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, Vol: 163, ISSN: 1386-5056- Author Web Link
- Cite
- Citations: 1
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.
Contact us
Dyson School of Design Engineering
Imperial College London
25 Exhibition Road
South Kensington
London
SW7 2DB
design.engineering@imperial.ac.uk
Tel: +44 (0) 20 7594 8888