Metadata schema for virtual building models in digital twins: VB schema implemented in GPT-based applications

The paper aims to compare NX Mechatronic Concept Designer (MCD) and Tecnomatix Process Simulate (TPS) and their suitability for simulating mechatronic machines in digital twinning. A Digital Twin (DT) is a virtual model that serves as a real-time digital counterpart of a physical object or process. Compared to a conventional simulation, it differs in its ability to model the behavior of the actual counterpart from many points of view and with much greater complexity. Digital Twins have a crucial role in the Fourth Industrial Revolution but are also used in different areas like meteorology, traffic simulation in smart cities, and civil engineering. Digital Twins in industrial engineering help maintain the optimal pace of assembly lines, flexibly adapt production, increase manufacturing process efficiency, and generate cost-effective products. Increasing usage of IoT solutions drives the Digital Twin market, which is growing exponentially. The paper discusses the two software packages’ possibilities, advantages, and disadvantages and proposes the methodology and philosophy of making DT. The contribution of this work is to compare the possibilities of making mechatronic devices for educational and research purposes from scratch through to their final implementation.

ABSTRACTWhile extensive modelling - both physical and virtual - is imperative to develop right-first-time products, the parallel use of virtual and physical models gives rise to two interrelated issues: the lack of revision control for physical prototypes; and the need for designers to manually inspect, measure, and interpret modifications to either virtual or physical models, for subsequent update of the other. The Digital Twin paradigm addresses similar problems later in the product life-cycle, and while these digital twins, or the “twinning” process, have shown significant value, there is little work to date on their implementation in the earlier design stages. With large prospective benefits in increased product understanding, performance, and reduced design cycle time and cost, this paper explores the concept of using the Digital Twin in early design, including an introduction to digital twinning, examination of opportunities for and challenges of their implementation, a presentation of the structure of Early Stage Twins, and evaluation via two implementation cases.

Digital twins are a new paradigm for our time, offering the possibility of interconnected virtual representations of the real world. The concept is very versatile and has been adopted by multiple communities of practice, policymakers, researchers, and innovators. A significant part of the digital twin paradigm is about interconnecting digital objects, many of which have previously not been combined. As a result, members of the newly forming digital twin community are often talking at cross-purposes, based on different starting points, assumptions, and cultural practices. These differences are due to the philosophical world-view adopted within specific communities. In this paper, we explore the philosophical context which underpins the digital twin concept. We offer the building blocks for a philosophical framework for digital twins, consisting of 21 principles that are intended to help facilitate their further development. Specifically, we argue that the philosophy of digital twins is fundamentally holistic and emergentist. We further argue that in order to enable emergent behaviors, digital twins should be designed to reconstruct the behavior of a physical twin by “dynamically assembling” multiple digital “components”. We also argue that digital twins naturally include aspects relating to the philosophy of artificial intelligence, including learning and exploitation of knowledge. We discuss the following four questions (i) What is the distinction between a model and a digital twin? (ii) What previously unseen results can we expect from a digital twin? (iii) How can emergent behaviours be predicted? (iv) How can we assess the existence and uniqueness of digital twin outputs?

Deep-learning-enhanced digital twinning of complex composite structures and real-time mechanical interaction

Digital twinning is a rapidly emerging technique for building virtual replicas of physical artefacts that can be used for a range of engineering purposes from design through to asset management. In this paper, we describe details of work to create a prototype example of a digital twin of a three-storey, small-scale building. The concept is based on combining information from a series of ‘digital components‘. Each component is managed by an ‘agent’ and operated within a software container. The containers are coordinated across a container network. This digital twin architecture allows us to combine information from heterogeneous sources including (but not limited to) computer-aided design, finite element analysis, ordinary differential equations and Bayesian calibration. The information in the digital twin is curated in an overall knowledge model of the structure based on a dynamic knowledge graph. The resulting digital twin can provide the user with a range of information, depending on the context. To illustrate the approach we describe how the digital twin functionalities can be used to answer natural language queries.

Digital twins are virtual counterparts of objects throughout their entire life cycle. Primarily adopted by NASA, today are a crucial component of the ongoing digital transformation. Civil engineering has spotted the benefits coming from digitization, but the current stage of technological adoption is still in its infancy. Digital twinning can empower the automation and efficiency of civil engineering and prepare it for future challenges. However, for the growth of the digital twinning idea, extended research and practical implementations are needed. Current trends in civil engineering, such as Building Information Modeling and Structural Health Monitoring, prepare civil engineering to adopt the concept of digital twins. Nevertheless, to fulfill the requirements of and benefit from multi-industrial digitization, civil engineering must evolute its methodologies in the digital twinning fashion. Reviewed examples of implementations (focusing on concrete bridges) show practical benefits for automating processes and increasing the resilience of structures. The article describes the key components of a proposed bridge digital twin framework: BIM, SHM, and Artificial Intelligence, and explains their roles in the digital twinning concept.

Digital twins offer a unique opportunity to design, test, deploy, monitor, and control real-world robotic processes. In this paper we present a novel, modular digital twinning framework developed for the investigation of safety within collaborative robotic manufacturing processes. The modular architecture supports scalable representations of user-defined cyber-physical environments, and tools for safety analysis and control. This versatile research tool facilitates the creation of mixed environments of Digital Models, Digital Shadows, and Digital Twins, whilst standardising communication and physical system representation across different hardware platforms. The framework is demonstrated as applied to an industrial case-study focused on the safety assurance of a collaborative robotic manufacturing process. We describe the creation of a digital twin scenario, consisting of individual digital twins of entities in the manufacturing case study, and the application of a synthesised safety controller from our wider work. We show how the framework is able to provide adequate evidence to virtually assess safety claims made against the safety controller using a supporting validation module and testing strategy. The implementation, evidence and safety investigation is presented and discussed, raising exciting possibilities for the use of digital twins in robotic safety assurance.

Climate-smart forestry is a sustainable forest management approach for increasing positive climate impacts on society. As climate-smart forestry is focusing on more sustainable solutions that are resource-efficient and circular, digitalization plays an important role in its implementation. The article aimed to validate an automatic workflow of processing 3D pointclouds to produce digital twins for every tree on large 1-ha sample plots using a GeoSLAM mobile LiDAR scanner and VirtSilv AI platform. Specific objectives were to test the efficiency of segmentation technique developed in the platform for individual trees from an initial cloud of 3D points observed in the field and to quantify the efficiency of digital twinning by comparing the automatically generated results of (DBH, H, and Volume) with traditional measurements. A number of 1399 trees were scanned with LiDAR to create digital twins and, for validation, were measured with traditional tools such as forest tape and vertex. The segmentation algorithm developed in the platform to extract individual 3D trees recorded an accuracy varying between 95 and 98%. This result was higher in accuracy than reported by other solutions. When compared to traditional measurements the bias for diameter at breast height (DBH) and height was not significant. Digital twinning offers a blockchain solution for digitalization, and AI platforms are able to provide technological advantage in preserving and restoring biodiversity with sustainable forest management.

In the evolving landscape of digital technology, the concept of digital twinning has emerged as one of the most important innovations. Digital twinning, characterized by a one‐to‐one correlation with physical structures in a digital environment, has become an important tool in transferring physical dynamics into digital replicas. This platform, integrating advanced sensor technologies and analytical tools, enables a comprehensive monitoring, diagnosis, and optimization concept. The present research focuses on the application of digital twinning in addressing the complex challenge of managing fault types in freight car brakes. A Digital Twin (DT) model of a freight car braking system is developed that forms the basis for an innovative approach to fault classification. This approach leverages the ability of the DT to emulate and analyze the behavior of the braking system under different conditions. The effectiveness of the proposed method is evaluated through extensive testing and analysis with an experimental data set. The results show that the method is able to accurately diagnose different types of faults. This represents a significant advance in the field of freight car brake system diagnosis.

The impacts on ecosystems of global and local shifts in the environment due to e.g. climate change, land use change, and urbanisation present us with complex and interacting societal challenges. Solving a single problem often aggravates another. Scientific insights needed to face these challenges are based on interdisciplinary multi-scale research. It requires that we work together across (sub)disciplinary boundaries and combine our insights and knowledge to understand the complexities and interrelatedness within ecosystems. Making this combination is currently hampered by the availability and scatteredness of datasets and the lack of methods and tools to combine knowledge, data and models. Developing digital twins of ecosystems could provide a paradigm to achieve this combination of knowledge, data and models, and generate the insight and knowledge that we require to face the challenges of global and local change. A digital twin of an ecosystem is a digital representation of an ecosystem tailored to the user’s research objectives and perspective of that ecosystem. They bring together (long-term) data collected of multiple ecosystem facets and across multiple scales, process-based models, and data science and computational modelling tools, making them a versatile instrument. Digital twins can be used to understand ecosystem functioning, by aiding the discovery of intricate ecological relationships not yet understood or measured. Furthermore, they are ideal for exploring the effects of in situ management strategies, or for the detection of early-warning signals of global change impacts on ecosystem dynamics. LTER-LIFE is a scientific infrastructure, embedded in LTER-NL (Long-Term Ecosystem Research Netherlands) and LifeWatch ERIC, aimed at supporting shared and integrated ecological research, providing scientists the platform and tools to build digital twins of ecosystems. We do this by supporting the sharing of data and models and bringing these together into a site-focused virtual lab where people can work together. LTER sites provide an ideal opportunity for this as they often come with a long history of extensive data collection and research across multiple spheres. Drawing on experience of building digital twins in the Veluwe LTSER platform, this keynote will take you through the journey of digital twinning parts of an ecosystem with a long legacy of ecological and environmental research and data collection. As these data exist in many different formats, we built data mobilisation and FAIRification pipelines to augment the focal experimental sites in the Veluwe with relevant historical, privately-owned or national datasets. Subsequently, we explored the potential of the Notebook as a Virtual Research Environment (NaaVRE), which provided us with a virtual lab in which we developed workflows for processing and linking FAIRified data with process-based and data-driven models. Ultimately, we show that this way of working can bring together researchers to generate insights on the impacts of climate change, land use change, and urbanisation on the functioning of the ecosystem, providing scientific support for management and policy decisions.

With global urbanisation anticipated to reach 68% by 2050, there is a significant risk of exacerbating urban transport emissions. Urban transport decarbonisation is a complex adaptive system challenge, the understanding and optimisation of which could be supported by digital twins (DTs). Although prior research has explored digital and big data technology applications, creating actionable insights requires human-centred designs. We conducted a structured workshop to gather practitioner views on how urban-scale DTs can support transport decarbonisation. Specifically, we explored the outcomes they aim to achieve, the interventions they are interested in, and the value digital twinning offers compared to current methods. The data was synthesised and analysed to identify (1) impacts, (2) interventions, (3) location types, (4) data sources and (5) feedback mechanisms of importance to participants. These five aspects are proposed as a framework to support the definition of digital twinning use cases targeting urban transport decarbonisation. Application of the framework encourages creators to explicitly consider the services to be provided to users, how the derived insights influence the real world and the data connections between the physical and digital, noting that these are often overlooked in reported research. A framework application is illustrated through an example use case described for the West Midlands, UK.

High speed crafts demand lighter structural weight to enhance transportation efficiency, which, in turn, increases the risk of premature structural failure. As such the use of aluminium structures requires closer attention to fatigue cracks. There is a clear technological trend towards equipping high-speed vessels with Structural Health Monitoring (SHM) systems that provide structural diagnosis and prognosis capabilities to support operation and maintenance decisions. The intelligent data processing capabilities of a digital twin make it an ideal platform for achieving real-time structural health awareness of the entire hull, even with a limited number of sensors. Unfortunately, current digital twin applications for ship structures are primarily implemented on large displacement cargo vessels or offshore structures and are not readily applicable to high-speed crafts due to the unique challenges associated with predicting their responses: (1) lack of information of the highly non-linear slamming load experienced at high-speed; (2) the absence of efficient models to predict non-linear hydrodynamic responses under dynamic operating conditions, including planning effects, porpoising, and wave-induced motions. To address these challenges, a customized SHM solution via digital twinning has been developed for an ultra-high speed patrol craft (Froude number Fn>2.0). This paper presents the research work conducted in Phase 1. The Dynamic Loading Approach (DLA) and Spectral-Based Fatigue Analysis (SFA) are utilized for structural evaluation when the craft navigates at loitering speeds (Fn<0.4), Whereas a coupled Computational Fluid Dynamics (CFD)+Finite Element (FE) analysis framework is developed to address the slamming load effects on global and local structure responses in semi-planning or planning state (Fn≥0.4). The insights gained from these numerical analyses have been instrumental in designing the sensor placement plan and developing the architecture of the SHM solution, which serve as the foundation for SHM system development in Phase II. At last, a quantitative cost-benefit analysis has been conducted, highlighting the economic feasibility and added value of SHM implementation for highspeed crafts.

Based on the basic concept of digital twinning and virtual reality, this paper constructs the five-dimensional structure model of logistics distribution digital twinning and the overall framework of logistics distribution system driven by digital twinning. At the same time, this paper studies and designs the intelligent scheduling management system and establishes the software system architecture and communication network. The system aims at the problem of simultaneous distribution vehicle routing with random cargo demand under multi-center joint distribution mode. At the same time, the width and depth of adaptive neighborhood search frequency strategy and adaptive inferior solution acceptance mechanism are proposed to balance population evolution. The experimental simulation shows that the system can effectively solve the road disturbance caused by vehicles or vehicles in the distribution process and achieve better logistics distribution.

Selling value generated by digital solutions for customers is different than selling traditional physical equipment. The purpose of this chapter is to study how digital twin sales can be promoted. The chapter combines the literature of business-to-business (B2B) sales with new information coming from a study on digital twinning in a manufacturing context. The study includes the results of ten semi-structured theme interviews that were conducted in January and February of 2020 with six digital twin provider companies from the areas of intelligent machine control systems, software solutions, real-time simulation, and machine engineering. The result is a model illustrating the levels of customer and data-based-solution understanding needed to successfully sell digital twins in the B2B market. The model was applied to the six case companies, each with a different digital-twin solution, and practical examples are presented that were revealed during the qualitative interviews. The empirical study identified different challenges related to the sale of differing levels of the digital-twin solution. The results indicate that companies that targeted more complex digital-twin developments required a higher level of technological proficiency from their salespeople and a stronger understanding of the value elements for the customers, their businesses, and their business ecosystems.

To overcome the technical bottleneck faced by the traditional equipment battle damage assessment method by analyzing the application status of digital twins in battle damage assessment, the application needs and the existing problems of current digital twin technology in damage assessment were summarized. Relying on battle damage tests, based on combing the current status of equipment battle damage test evaluation and digital twin technology research, the connotation and application features of digital twinning technology-oriented to equipment battle damage test assessment were explored. The architecture and implementation plan of the digital twin oriented to equipment battle damage test assessment were structured. The key technology and realization of digital twin oriented to battle damage test assessment were proposed. This study provided a theoretical reference and method guidance for the application of digital twins in battle damage assessment, which is of great reference significance for the development of digital twin battlefield construction and battle damage assessment.