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Lean and interpretable digital twins for building energy monitoring - A case study with smart thermostatic radiator valves and gas absorption heat pumps

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Energy and AI

Energy and AI 2023年第4期14卷 645-659页

作者： Massimiliano Manfren Patrick AB James Victoria Aragon Lamberto Tronchin Faculty of Engineering and Physical Sciences University of SouthamptonBoldrewood Campus–SO167QF SouthamptonUnited Kingdom Department of Architecture(DA) University of BolognaVia Cavalcavia 6147521 CesenaItaly

The transition to low carbon energy systems poses challenges in terms of energy efficiency.In building refur-bishment projects,efficient technologies such as smart controls and heat pumps are increasingly being used as a substitute for conventional technologies with the aim of reducing carbon emissions and determining operational energy and cost savings,together with other benefits.Measured building performance,however,often reveals a significant gap between the predicted energy use(design stage)and actual energy use(operation stage).For this reason,lean and interpretable digital twins are needed for building energy monitoring aimed at persistence of savings and continuous performance improvement.In this research,interpretable regression models are built with data at multiple temporal resolutions(monthly,daily and hourly)and seamlessly integrated with the goal of verifying the performance improvements due to Smart thermostatic radiator valves(TRVs)and gas absorption heat pumps(GAHPs)as well as giving insights on the performance of the building as a whole.Further,as part of modelling research,time of week and temperature(TOWT)approach is reformulated and benchmarked against its original implementation.The case study chosen is Hale Court sheltered housing,located in the city of Portsmouth(UK).This building has been used for the field-testing of innovative technologies such as TRVs and GAHPs within the EU Horizon 2020 project THERMOSS.The results obtained are used to illustrate possible extensions of the use of energy signature modelling,highlighting implications for energy management and innovative building technologies development.

关键词： Data-driven methods digital twins Energy signature Thermostatic radiator valves Gas absorption heat pumps Energy management Energy Analytics

Design and Implementation of Secure and Reliable Information Interaction Architecture for digital twins

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China Communications 2023年第2期20卷 79-93页

作者： Qian Wang Wanwan Wu Liping Qian Yiming Cai Jiang Qian Limin Meng College of Information Engineering Zhejiang University of TechnologyHangzhou 310023China

In order to improve the comprehensive defense capability of data security in digital twins(DTs),an information security interaction architecture is proposed in this paper to solve the inadequacy of data protection and transmission mechanism at present.Firstly,based on the advanced encryption standard(AES)encryption,we use the keystore to expand the traditional key,and use the digital pointer to avoid the key transmission in a wireless channel.Secondly,the identity authentication technology is adopted to ensure the data integrity,and an automatic retransmission mechanism is added for the endogenous properties of the wireless channel.Finally,the software defined radio(SDR)platform composed of universal software radio peripheral(USRP)and GNU radio is used to simulate the data interaction between the physical entity and the virtual entity.The numerical results show that the DTs architecture can guarantee the encrypted data transmitted completely and decrypted accurately with high efficiency and reliability,thus providing a basis for intelligent and secure information interaction for DTs in the future.

关键词： digital twins AES encryption digital pointer identity authentication automatic retransmission SDR

Collaborative Clustering Parallel Reinforcement Learning for Edge-Cloud digital twins Manufacturing System

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China Communications 2022年第8期19卷 138-148页

作者： Fan Yang Tao Feng Fangmin Xu Huiwen Jiang Chenglin Zhao School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China China Tendering Center for Mechanical and Electrical Equipment Ministry of Industry and Information TechnologyBeijing 100142China

To realize high-accuracy physical-cyber digital twin(DT)mapping in a manufacturing system,a huge amount of data need to be collected and analyzed in real-time.Traditional DTs systems are deployed in cloud or edge servers independently,whilst it is hard to apply in real production systems due to the high interaction or execution delay.This results in a low consistency in the temporal dimension of the physical-cyber model.In this work,we propose a novel efficient edge-cloud DT manufacturing system,which is inspired by resource scheduling technology.Specifically,an edge-cloud collaborative DTs system deployment architecture is first constructed.Then,deterministic and uncertainty optimization adaptive strategies are presented to choose a more powerful server for running DT-based applications.We model the adaptive optimization problems as dynamic programming problems and propose a novel collaborative clustering parallel Q-learning(CCPQL)algorithm and prediction-based CCPQL to solve the problems.The proposed approach reduces the total delay with a higher convergence rate.Numerical simulation results are provided to validate the approach,which would have great potential in dynamic and complex industrial internet environments.

关键词： edge-cloud collaboration digital twins job shop scheduling parallel reinforcement learning

Modeling Methods of 3D Model in digital twins

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Computer Modeling in Engineering & Sciences 2023年第8期136卷 985-1022页

作者： Ruijun Liu Haisheng Li Zhihan Lv School of Computer Science and Engineering Beijing Technology and Business UniversityBeijing100080China Department of Game Design Faculty of ArtUppsala UniversityUppsalaS-75105Sweden

To understand the current application and development of 3D modeling in digital twins(DTs),abundant literatures on DTs and 3D modeling are investigated by means of literature review.The transition process from 3D modeling to DTs modeling is analyzed,as well as the current application of DTs modeling in various industries.The application of 3D DTs modeling in the􀀀elds of smartmanufacturing,smart ecology,smart transportation,and smart buildings in smart cities is analyzed in detail,and the current limitations are summarized.It is found that the 3D modeling technology in DTs has broad prospects for development and has a huge impact on all walks of life and even human lifestyles.At the same time,the development of DTs modeling relies on the development and support capabilities of mature technologies such as Big Data,Internet of Things,Cloud Computing,Articial Intelligence,and game technology.Therefore,although some results have been achieved,there are still limitations.This work aims to provide a good theoretical support for the further development of 3D DTs modeling.

关键词： digital twins 3D modeling smart manufacturing smart city smart buildings

Regional Economic Development Trend Prediction Method Based on digital twins and Time Series Network

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Computers, Materials & Continua 2023年第8期76卷 1781-1796页

作者： Runguo Xu Xuehan Yu Xiaoxue Zhao School of International Relations Yonsei UniversitySeoul03722Korea

At present,the interpretation of regional economic development(RED)has changed from a simple evaluation of economic growth to a focus on economic growth and the optimization of economic structure,the improvement of economic relations,and the change of institutional innovation.This article uses the RED trend as the research object and constructs the RED index to conduct the theoretical analysis.Then this paper uses the attention mechanism based on digital twins and the time series network model to verify the actual data.Finally,the regional economy is predicted according to the theoretical model.The specific research work mainly includes the following aspects:1)This paper introduced the development status of research on time series networks and economic forecasting at home and abroad.2)This paper introduces the basic principles and structures of long and short-term memory(LSTM)and convolutional neural network(CNN),constructs an improved CNN-LSTM model combined with the attention mechanism,and then constructs a regional economic prediction index system.3)The best parameters of the model are selected through experiments,and the trained model is used for simulation experiment prediction.The results show that the CNN-LSTM model based on the attentionmechanism proposed in this paper has high accuracy in predicting regional economies.

关键词： Regional economic development attention mechanism digital twins time series network

Integrating digital twins and deep learning for medical image analysis in the era of COVID-19

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Virtual Reality & Intelligent Hardware 2022年第4期4卷 292-305页

作者： Imran AHMED Misbah AHMAD Gwanggil JEON School of Computing and Information Science Faculty of Science and EngineeringAnglia Ruskin UniversityEast RoadCambridgeEnglandUK Center of Excellence in IT Institute of Management SciencesHayatabadPeshawarPakistan Department of Embedded Systems Engineering Incheon National UniversityIncheonKorea

Background digital twins are virtual representations of devices and processes that capture the physical properties of the environment and operational algorithms/techniques in the context of medical devices and tech-nologies.digital twins may allow healthcare organizations to determine methods of improving medical processes,enhancing patient experience,lowering operating expenses,and extending the value of care.During the present COVID-19 pandemic,various medical devices,such as X-rays and CT scan machines and processes,are constantly being used to collect and analyze medical images.When collecting and processing an extensive volume of data in the form of images,machines and processes sometimes suffer from system failures,creating critical issues for hospitals and patients.Methods To address this,we introduce a digital-twin-based smart healthcare system in-tegrated with medical devices to collect information regarding the current health condition,configuration,and maintenance history of the device/machine/system.Furthermore,medical images,that is,X-rays,are analyzed by using a deep-learning model to detect the infection of COVID-19.The designed system is based on the cascade recurrent convolution neural network(RCNN)architecture.In this architecture,the detector stages are deeper and more sequentially selective against small and close false positives.This architecture is a multi-stage extension of the RCNN model and sequentially trained using the output of one stage for training the other.At each stage,the bounding boxes are adjusted to locate a suitable value of the nearest false positives during the training of the different stages.In this manner,the arrangement of detectors is adjusted to increase the intersection over union,overcoming the problem of overfitting.We train the model by using X-ray images as the model was previously trained on another dataset.Results The developed system achieves good accuracy during the detection phase of COVID-19.The experimental outcomes reveal the efficiency of the detection a

关键词： digital twins Deep learning Healthcare COVID-19 Chest X-rays Artificial intelligence

Building the metaverse using digital twins at all scales,states,and relations

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Virtual Reality & Intelligent Hardware 2022年第6期4卷 459-470页

作者： Zhihan LV Shuxuan XIE Yuxi LI M.Shamim HOSSAIN Abdulmotaleb El SADDIK Department of Game Design Faculty of ArtsUppsala UniversitySweden College of Computer Science and Technology Qingdao UniversityQingdaoChina Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia School of Electrical Engineering and Computer Science(EECS) University of OttawaOttawaOntarioCanada

Developments in new-generation information technology have enabled digital twins to reshape the physical world into a virtual digital space and provide technical support for constructing the Metaverse.Metaverse objects can be at the micro-,meso-,or macroscale.The Metaverse is a complex collection of solid,liquid,gaseous,plasma,and other uncertain states.Additionally,the Metaverse integrates tangibles with social relations,such as interpersonal(friends,partners,and family)and social relations(ethics,morality,and law).This review introduces some principles and laws,such as broken windows theory,small-world phenomenon,survivor bias,and herd behavior,for constructing a digital twins model for social relations.Therefore,from multiple perspectives,this article reviews mappings of tangible and intangible real-world objects to the Metaverse using the digital twins model.

关键词： digital twins Metaverse Sensor

Deep inside molecules-digital twins at the nanoscale

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Virtual Reality & Intelligent Hardware 2022年第4期4卷 324-341页

作者： Marc BAADEN CNRS Universitéde ParisUPR 9080Laboratoire de Biochimie Théorique13 rue Pierre et Marie CurieF-75005ParisFrance Institut de Biologie Physico-Chimique-Fondation Edmond de Rothschild ParisFrance

Background digital twins offer rich potential for exploration in virtual reality(VR).Using interactive molecular simulation approaches,they enable a human operator to access the physical properties of molecular objects and to build,manipulate,and study their assemblies.Integrative modeling and drug design are important applications of this technology.Methods In this study,head-mounted virtual reality displays connected to mole-cular simulation engines were used to create interactive and immersive digital twins.They were used to perform tasks relevant to specific use cases.Results Three areas were investigated,including model building,rational design,and tangible models.Here,we report several membrane-embedded systems of ion channels,viral com-ponents,and artificial water channels.We were able to improve and create molecular designs based on digital twins.Conclusions The molecular application domain offers great opportunities,and most of the technical and tech-nological aspects have been solved.Wider adoption is expected once the onboarding of VR is simplified and the technology gains wider acceptance.

关键词： digital twins Molecular simulation Virtual reality

Revisiting digital twins: Origins, fundamentals, and practices

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Frontiers of Engineering Management 2022年第4期9卷 668-676页

作者： Jiehan ZHOU Shouhua ZHANG Mu GU University of Oulu Oulu 90570Finland Hebei University Baoding 071002China Beijing Aerospace Smart Manufacturing Technology Development Co. Ltd.Beijing 100043China

The digital twins(DT)has quickly become a hot topic since it was proposed.It appears in all kinds of commercial propaganda and is widely quoted by academic circles.However,the term DT has misstatements and is misused in business and academics.This study revisits DT and defines it to be a more advanced system/product/service modeling and simulation environment that combines most modern information communication technologies(ICTs)and engineering mechanism digitization and characterized by system/product/service life cycle management,physically geometric visualization,real-time sensing and measurement of system operating conditions,predictability of system performance/safety/lifespan,and complete engineering mechanisms-based simulations.The idea of DT originates from modeling and simulation practices of engineering informatization,including virtual manufacturing(VM),model predictive control,and building information modeling(BIM).On the basis of the two-element VM model,we propose a three-element model to represent DT.DT does not have its unique technical characteristics.The existing practices of DT are extensions of the engineering informatization embracing modern ICTs.These insights clarify the origin of DT and its technical essentials.

关键词： virtual manufacturing digital twins modeling and simulation digitization computational engineering