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Finite Element Modelling of Car Seat with Hyperelastic and Viscoelastic Foam Material Properties to Assess Vertical Vibration in Terms of Acceleration

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engineering（科研） 2020年第3期12卷 177-193页

作者： Purnendu Mondal Subramaniam Arunachalam School of Architecture Computing and Engineering University of East London (Docklands Campus) London UK

Primary objective of automobile seats is to offer adequate level of safety and comfort to the seated human occupant, primarily against vibration. Ideally, any sort of automotive seat is constructed by mechanical framework, cushion, backrest and headrest. The frame structures are made of metallic alloys, while the cushion, backrest and headrest are made of polyurethane foam material. During the design phase of automotive seat, the greatest challenge is to assign realistic material properties to foam material;as it is non-linear in nature and exhibit hysteresis at low level stress. In this research paper, a car seat has been modelled in finite element environment by implementing both hyperelastic and viscoelastic material properties to polyurethane foam. The car seat has been excited with the loads due to car acceleration and human object and the effects of vibration in terms of vertical acceleration at different locations have been measured. The aims of this simulation study are to establish a car seat with the foam material properties as accurately as possible and provide a finite element set up of car seat to monitor the vertical acceleration responses in a reasonable way. The RMS acceleration values for headrest, backrest and cushion have been found to be 0.91 mm/sec2, 0.54 mm/sec2 and 0.47 mm/sec2, respectively, which showed that the car seat foam can effectively be modelled through combined hyperelastic and viscoelastic material formulations. The simulation outputs have been validated through real life testing data, which clearly indicates that this computerized simulation technique is capable of anticipating the acceleration responses at different car seat segments in a justified way.

关键词： Car Seat Hyperelastic Material Viscoelastic Material Finite Element Vertical Acceleration Vertical Vibration

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Crosslinker energy landscape effects on dynamic mechanical properties of ideal polymer hydrogels

arXiv

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arXiv 2023年

作者： Khare, Eesha Alcantara, Amadeus Lee, Nic Skaf, Munir S. Buehler, Markus Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA United States Department of Materials Science and Engineering Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA United States Department of Computational Mechanics School of Mechanical Engineering University of Campinas - UNICAMP Campinas Sao Paulo Brazil Center for Computing in Engineering & Sciences CCES University of Campinas - UNICAMP Campinas Sao Paulo Brazil School of Architecture and Planning Media Lab Massachusetts Institute of Technology 75 Amherst Street CambridgeMA United States Institute of Chemistry School of Mechanical Engineering University of Campinas - UNICAMP Campinas Sao Paulo Brazil Center for Computational Science and Engineering Schwarzman College of Computing Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA United States

Reversible crosslinkers can enable several desirable mechanical properties, such as improved toughness and self-healing, when incorporated in polymer networks for bioengineering and structural applications. In this work, we performed coarse-grained molecular dynamics to investigate the effect of the energy landscape of reversible crosslinkers on the dynamic mechanical properties of crosslinked polymer network hydrogels. We report that, for an ideal network, the energy potential of the crosslinker interaction drives the viscosity of the network, where a stronger potential results in a higher viscosity. Additional topographical analyses reveal a mechanistic understanding of the structural rearrangement of the network as it deforms and indicate that as the number of defects increases in the network, the viscosity of the network increases. As an important validation for the relationship between the energy landscape of a crosslinker chemistry and the resulting dynamic mechanical properties of a crosslinked ideal network hydrogel, this work enhances our understanding of deformation mechanisms in polymer networks that cannot easily be revealed by experiment and reveals design ideas that can lead to better performance of the polymer network at the macroscale. © 2023, CC BY-NC-SA.

关键词： Hydrogels

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Sustainability and carbon neutrality in UK's district heating: A review and analysis

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e-Prime - Advances in Electrical engineering, Electronics and Energy 2023年 4卷

作者： Hepple, Ryan Du, Hu Feng, Haibo Shan, Shan Yang, Siliang School of Built Environment Engineering and Computing Leeds Beckett University Leeds United Kingdom Sine Consulting Limited Durham United Kingdom School of Civil Engineering and Built Environment Liverpool John Moores University Liverpool United Kingdom Welsh School of Architecture Cardiff University Cardiff United Kingdom Department of Wood Science University of British Columbia Vancouver Canada School of Strategy and Leadership Coventry University Coventry United Kingdom

The UK is currently approaching a critical point in the fight against climate change. To achieve carbon neutral by 2050, it is crucial that the way in which buildings are heated are reviewed to determine the most suitable solution. The UK government has acknowledged that district heating (also referred to as heat networks) forms an important part of their plan for future sustainability in heating homes as well as improving energy costs. At present, there are five generations of district heating with distinctive improvements between each. However, research shows a lack of progression with only minor improvements to efficiencies and carbon emissions in the past two decades. Therefore, this paper aimed to review the key technologies and design principles of the low-impact network which shall be implemented into future networks to ensure sustainability and carbon neutral. Furthermore, data were utilised from UK government's ‘Heat Network Project Pipeline’ documents which cover a wide range of projects supported through the development stage by the UK Heat Network Delivery Unit. A statistical analysis was also undertaken to identify popular heat source technologies currently being implemented into the UK networks. Information such as technologies, size and costs were analysed to establish the intercorrelations, which may influence the type of technologies being selected. The results show that 56% of total networks contained Combined Heat and Power (CHP) as a primary heat source, of which over 40% were gas fired CHP, displaying the current dominance of the technology. Overall, it is evident in the UK that, the new networks have been improved from previous generations with a high concentration of renewable energy technologies and heat recovery methods being used. However, there is still a high reliance on natural gas, which does not fulfil the characteristics of a low-impact heating network. © 2023 The Author(s)

关键词： Carbon neutrality Low temperature heating Renewable and sustainable energy technologies UK district heating

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Reducing Driver’s Cognitive Load with the Use of Artificial Intelligence and Augmented Reality 23rd

Reducing Driver’s Cognitive Load with the Use of Artificial...

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23rd International Conference on Human-Computer Interaction , HCII 2021

作者： Bram-Larbi, Kweku F. Charissis, Vassilis Lagoo, Ramesh Wang, Shu Khan, Soheeb Altarteer, Samar Harrison, David K. Drikakis, Dimitris School of Computing Engineering and Built Environment Glasgow Caledonian University Glasgow United Kingdom Research and Development Core Lab + Ltd Glasgow United Kingdom Research and Development Volkswagen Beijing China School of Design and Architecture Dar Al-Hekma University Jeddah Saudi Arabia Defence and Security Research Institute University of Nicosia Nicosia Cyprus

ISBN: (纸本)9783030909659

Multiple infotainment sources can significantly overload the driver’s cognitive load and increase the collision probabilities. Current solutions provided have attempted to alleviate this issue with the centralization of infotainment devices to single touchscreen devices in the dashboard area. Yet this solution still requires the driver to take the eyes from the road and concentrate on operating the secondary tasks unrelated to the driving process. The paper presents a prototype Augmented Reality Head-Up Display (AR HUD) system that superimposes a selected number of infotainment data on the vehicle’s windshield only when this is safe for the driver. The selection of infotainment data and projection timing is calculated by a prototype Artificial Intelligence (AI) Co-Driver that aims to reduce the driver’s cognitive load. The proposed system was evaluated by 50 users against a typical touchscreen dashboard system. This work presents and discusses the subjective feedback related to the cognitive load that the users perceived during the trials. The paper concludes with a future plan for improving both the AI and AR HUD elements to perform in an urban environment. © 2021, Springer Nature Switzerland AG.

关键词： Augmented reality

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Correction: RILEM TC 277-LHS report: How hot are hot-lime-mixed mortars? A review

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Materials and Structures 2023年第7期56卷 1-2页

作者： Pavia, S. Veiga, R. Hughes, J. Pesce, G. Valek, J. Alvarez, J. I. Faria, P. Padovnik, A. Department of Civil Engineering Trinity College Dublin Dublin Ireland Buildings Department National Laboratory for Civil Engineering–LNEC Lisbon Portugal School of Computing Engineering and Physical Sciences University of the West of Scotland Paisley Scotland UK Department of Architecture and Built Environment Northumbria University Newcastle Upon Tyne UK Institute of Theoretical and Applied Mechanics Academy of Sciences of the Czech Republic Prague 9 Czech Republic Materials and Cultural Heritage MATCH Research Group Department of Chemistry School of Sciences University of Navarra Pamplona Spain CERIS and Department of Civil Engineering NOVA School of Science and Technology Universidade NOVA de Lisboa Caparica Portugal Faculty of Civil and Geodetic Engineering University of Ljubljana Ljubljana Slovenia

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A Novel Cross-layer Mobile Data-gathering Protocol for Underwater Sensor Networks 91

A Novel Cross-layer Mobile Data-gathering Protocol for Under...

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91st IEEE Vehicular Technology Conference, VTC Spring 2020

作者： Alfouzan, Faisal Abdulaziz Ghoreyshi, Seyed Mohammad Shahrabi, Alireza Ghahroudi, Mahsa Sadeghi Al Yamamah University College of Engineering and Architecture Riyadh Saudi Arabia University of Southampton School of Mathematical Sciences Southampton United Kingdom Glasgow Caledonian University School of Computing Engineering and Built Environment Glasgow United Kingdom

ISBN: (纸本)9781728152073

In this paper, a novel Cross-Layer Mobile Data gathering (CLMD) scheme for Underwater Sensor Networks (UWSNs) is presented to improve the performance with a cross-layer design in the MAC and routing layer. CLMD develops a distributed cross-layer mobile data gathering solution that allows multiple sensors to efficiently and fairly share the bandwidth-limited high-delay underwater acoustic medium and aggregate data packets in a group of cluster heads which are visited by Autonomous Underwater Vehicle (AUV) in the periodic tours. The network lifetime is prolonged by reselecting the cluster heads in the different operational phases while the tour length is kept short to reduce the latency. The effectiveness of CLMD is validated through an extensive simulation study which reveals the performance improvement in the energy-saving, network lifetime, and packet delivery ratio. © 2020 IEEE.

关键词： Underwater acoustics

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Effect of Semi-Transparent A-Si Pv Glazing within Double-Skin Façades on Visual and Energy Performances Under the UK Climate Condition

SSRN

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SSRN 2022年

作者： Roberts, Frank Yang, Siliang Du, Hu Yang, Rebecca School of Built Environment Engineering and Computing Leeds Beckett University LeedsLS2 8AG United Kingdom School of Civil Engineering and Built Environment Liverpool John Moores University Liverpool United Kingdom Welsh School of Architecture Cardiff University Cardiff United Kingdom School of Property Construction and Project Management RMIT University Melbourne Australia

Various studies have assessed the energy performance alterations affected by the novel technology of Building-Integrated Photovoltaic in Double-Skin Facades (BIPV-DSF), while lighting performance tied to the BIPV-DSF has not received much attention. This paper provides numerical modelling to assess the effect of BIPV-DSF on both indoor visual condition and energy consumption for an office module under a typical climate in the United Kingdom. The proposed study was focused on the comparisons between a reference case (a DSF office module with both layers using clear double glazing) and a design case of the same office module with BIPV-DSF using semi-transparent Amorphous Silicon PV glazing. Results show a significant drop in maximum daylight illuminance of 73% by configuring the BIPV-DSF with reference to the regular DSF. It was also reported the resultant average and minimum daylight factors (0.65% and 0.00%) were not able to meet indoor visual comfort requirements for office environments. Furthermore, it was found that the use of BIPV-DSF resulted in a net increase of 8% in building energy consumption over the reference DSF. Therefore, it is concluded that in the present context the BIPV-DSF is not viable for a commercial installation under the UK’s climate conditions. © 2022, The Authors. All rights reserved.

关键词： Energy utilization

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FLOOD-PREPARED: A NOWCASTING SYSTEM for REAL-TIME IMPACT ADAPTION to SURFACE WATER FLOODING in CITIES 5

FLOOD-PREPARED: A NOWCASTING SYSTEM for REAL-TIME IMPACT ADA...

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5th International Conference on Smart Data and Smart Cities, SDSC 2020

作者： Barr, S.L. Johnson, S. Ming, X. Peppa, M. Dong, N. Wen, Z. Robson, C. Smith, L. James, P. Wilkinson, D. Heaps, S. Laing, Q. Xiao, W. Dawson, R. Ranjan, R. School of Design University of Melbourne Australia Australia School of Engineering Newcastle University United Kingdom School of Mathematics Statistics and Physics Newcastle University United Kingdom School of Computing Newcastle University United Kingdom School of Architecture Building and Civil Engineering Loughborough University United Kingdom

Extreme rainfall events pose an ever increasing threat to cities due to the potential for surface water flooding resulting in damage to properties and major disruption of transport systems. Modern sensor networks offer enormous potential for the real-time monitoring of urban systems and potentially allow improved situational awareness of impeding hazards and their impacts such as flooding. However, monitoring in itself is not enough if we are to be able to adapt in in real-time to hazards. Systems are required that allow analytics and models, that feed of real-time observations, to make predictions of impacts and suggest adaption options ahead of the hazard event. The Flood-PREPARED project is developing a system for real-time adaption to surface water flooding. The system comprises of advanced spatiotemporal models of rainfall, surface water flooding and road traffic impacts. These models are linked and orchestrated within into a Big Data workflow that allows events to be simulated using emerging rainfall data recorded by a short range weather radar. This approach allows nowcasting to be undertaken where predictions of surface water inundation and impacts on the road network can be predicted ahead of the rainfall event reaching the city;thus providing the ability for an improved adaptive response to the actual event. © 2020 S. L. Barr et al.

关键词： Floods

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On How Data are Used in Model Development: The Elephant in the Room

SSRN

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SSRN 2023年

作者： Maier, Holger R. Zheng, Feifei Gupta, Hoshin Chen, Junyi Mai, Juliane Savic, Dragan Loritz, Ralf Wu, Wenyan Guo, Danlu Bennett, Andrew Zhao, Jianshi School of Architecture and Civil Engineering The University of Adelaide Adelaide Australia College of Civil Engineering and Architecture Zhejiang University China Department of Hydrology and Atmospheric Sciences The University of Arizona Tucson United States Computational Hydrosystems Helmholtz Centre for Environmental Research–UFZ Leipzig Germany Center for Scalable Data Analytics and Artificial Intelligence–ScaDS.AI Leipzig Germany KWR Water Research Institute Netherlands Centre for Water Systems University of Exeter Exeter United Kingdom Institute of Water and River Basin Management Karlsruhe Germany Department of Infrastructure Engineering The University of Melbourne Melbourne Australia School of Engineering College of Engineering Computing & Cybernetics Australian National University Canberra Australia Department of Hydraulic Engineering Tsinghua University Beijing China

Models are widely used to support the development of understanding regarding the physical nature of Earth and environmental systems, with a view to improving their planning and management. Data is crucial to the development of such models, and it is common to partition the available data into separate subsets to be used for model development and evaluation. Although the manner by which the data is partitioned can significantly affect the model’s ability to generalize to novel conditions, this issue has (surprisingly) been largely ignored (i.e., the elephant in the room). Here we highlight the importance of careful attention to this aspect of the model development process and how it can impact the generalization ability of models. We report on the problems with commonly used, as well as more advanced data-splitting approaches. We also map out a way forward to enable us to address the elephant in the room. © 2023, The Authors. All rights reserved.

关键词： Data handling

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FLP: Factor lattice pattern-based automated detection of Parkinson's disease and specific language impairment using recorded speech

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Computers in Biology and Medicine 2024年 173卷 108280-108280页

作者： Tuncer, Turker Dogan, Sengul Baygin, Mehmet Barua, Prabal Datta Palmer, Elizabeth Emma March, Sonja Ciaccio, Edward J. Tan, Ru-San Acharya, U. Rajendra Department of Digital Forensics Engineering Technology Faculty Firat University Elazig Turkey Department of Computer Engineering Faculty of Engineering and Architecture Erzurum Technical University Erzurum Turkey University of Southern Queensland Australia Centre of Clinical Genetics Sydney Children's Hospitals Network Randwick2031 Australia School of Women's and Children's Health University of New South Wales Randwick2031 Australia School of Psychology and Counselling and Centre for Health Research University of Southern Queensland Springfield Australia Department of Medicine Columbia University Irving Medical Center United States Department of Cardiology National Heart Centre Singapore Singapore Duke-NUS Medical School Singapore School of Mathematics Physics and Computing University of Southern Queensland Springfield Australia Centre for Health Research University of Southern Queensland Australia

Background: Timely detection of neurodevelopmental and neurological conditions is crucial for early intervention. Specific Language Impairment (SLI) in children and Parkinson's disease (PD) manifests in speech disturbances that may be exploited for diagnostic screening using recorded speech signals. We were motivated to develop an accurate yet computationally lightweight model for speech-based detection of SLI and PD, employing novel feature engineering techniques to mimic the adaptable dynamic weight assignment network capability of deep learning architectures. Materials and methods: In this research, we have introduced an advanced feature engineering model incorporating a novel feature extraction function, the Factor Lattice Pattern (FLP), which is a quantum-inspired method and uses a superposition-like mechanism, making it dynamic in nature. The FLP encompasses eight distinct patterns, from which the most appropriate pattern was discerned based on the data structure. Through the implementation of the FLP, we automatically extracted signal-specific textural features. Additionally, we developed a new feature engineering model to assess the efficacy of the FLP. This model is self-organizing, producing nine potential results and subsequently choosing the optimal one. Our speech classification framework consists of (1) feature extraction using the proposed FLP and a statistical feature extractor;(2) feature selection employing iterative neighborhood component analysis and an intersection-based feature selector;(3) classification via support vector machine and k-nearest neighbors;and (4) outcome determination using combinational majority voting to select the most favorable results. Results: To validate the classification capabilities of our proposed feature engineering model, designed to automatically detect PD and SLI, we employed three speech datasets of PD and SLI patients. Our presented FLP-centric model achieved classification accuracy of more than 95% and 99.79%

关键词： Feature extraction

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