Relevant bibliographies by topics / Digital Models/Shadows/Twins

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Digital Models/Shadows/Twins'

Author: Grafiati
Published: 2 June 2025
Last updated: 19 July 2025

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Journal articles on the topic "Digital Models/Shadows/Twins"

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Massel, Lyudmila V., and Alexey G. Massel. "Development Of Digital Twins And Digital Shadows Of Energy Objects And Systems Using Scientific Tools For Energy Research." E3S Web of Conferences 209 (2020): 02019. http://dx.doi.org/10.1051/e3sconf/202020902019.

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The article discusses an approach to the construction of digital twins and digital shadows, based on the use of scientific tools for complex energy research in Russia. It is proposed to use, as their basis, mathematical models of energy systems and software systems and databases developed at the Energy Systems Institute of SB RAS, for calculations using these models. For each area of research, an ontological model is developed, over which mathematical and information models are built and integrated, as the basis of digital twins and digital shadows of energy objects. In turn, scientific protot
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Anokhov, I. V. "Digital shadow as a tool for industry exploring." E-Management 5, no. 1 (2022): 80–92. http://dx.doi.org/10.26425/2658-3445-2022-5-1-80-92.

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Digitalisation contributes both to fundamental changes in production processes and to the web of relationships between business units. According to contemporary views, it will result in the common widespread using of the real objects’ digital models (digital twins). Their quality will define the competitiveness of a certain economic pattern. Thus, all the digital twin data automatically becomes a trade secret. In this context, external investigators are able to analyse only visible representation of digital twins – digital footprints, imprints and shadows. The aim of the article is to formalis
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Kassen, Stefan, Holger Tammen, Maximilian Zarte, and Agnes Pechmann. "Concept and Case Study for a Generic Simulation as a Digital Shadow to Be Used for Production Optimisation." Processes 9, no. 8 (2021): 1362. http://dx.doi.org/10.3390/pr9081362.

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Optimising an existing production plant is a challenging task for companies. Necessary physical test runs disturb running production processes. Simulation models are one opportunity to limit these physical test runs. This is particularly important since today’s fast and intelligent networking opportunities in production systems are in line with the call of Industry 4.0 for substantial and frequent changes. Creating simulation models for those systems requires high effort and in-depth knowledge of production processes. In the current literature, digital twins promise several advantages for prod
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Horr, Amir M., and Hugo Drexler. "Real-Time Models for Manufacturing Processes: How to Build Predictive Reduced Models." Processes 13, no. 1 (2025): 252. https://doi.org/10.3390/pr13010252.

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New data science and real-time modeling techniques facilitate better monitoring and control of manufacturing processes. By using real-time data models, industries can improve their processes and identify areas where resources are being wasted. Despite the challenges associated with implementing these data models in transient and multi-physical processes, they can significantly optimize operations, reduce trial and error, and minimize the overall environmental footprint. Implementing real-time data analytics allows industries to make quicker, informed decisions and immediate corrections to mate
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Prielipp, Riccardo, Michael Bojko, Nadine Göhlert, and Luigi Pelliccia. "Smart Services auf Basis „Digitaler Zwillinge“/Business models based on digital twins and digital shadows in the textile industry." wt Werkstattstechnik online 111, no. 07-08 (2021): 531–35. http://dx.doi.org/10.37544/1436-4980-2021-07-08-63.

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Die Methoden und Werkzeuge des „Digitalen Zwillings“ (DZ) und „Digitalen Schattens“ (DS) erlauben die Realisierung dienstleistungs- und datenbasierter Geschäftsmodelle im industriellen Kontext. Zwar sehen sich Unternehmen zunehmend in die Lage versetzt, DZ und DS technisch umzusetzen, jedoch bestehen nach wie vor Herausforderungen, marktfähige Smart Services abzuleiten. Dieser Beitrag zeigt eine Methode zur Konzeptionierung von Geschäftsmodellen für DZ und DS am Beispiel der Textilbranche auf.   The methods and tools of digital twins (DT) and digital shadows (DS) allow for implementin
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Romero, David, Thorsten Wuest, Ramy Harik, and Klaus-Dieter Thoben. "Towards a Cyber-Physical PLM Environment: The Role of Digital Product Models, Intelligent Products, Digital Twins, Product Avatars and Digital Shadows." IFAC-PapersOnLine 53, no. 2 (2020): 10911–16. http://dx.doi.org/10.1016/j.ifacol.2020.12.2829.

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Dimitrov, H., and D. Petrova-Antonova. "3D CITY MODEL AS A FIRST STEP TOWARDS DIGITAL TWIN OF SOFIA CITY." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2021 (June 30, 2021): 23–30. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2021-23-2021.

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Abstract. Semantic 3D city models are increasingly applied for a wide range of analysis and simulations of large urban areas. Such models are used as a foundation for development of city digital twins, representing with high accuracy the landscapes and urban areas as well as dynamic of the city in terms of processes and events. In this context, this paper presents a 3D city model, which is a starting point for development of digital twin of Sofia city. The 3D model is compliant with CityGML 2.0 in LOD1, supporting integration of the buildings and terrain and enriching the buildings’ attributes
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Brauner, Philipp, Manuela Dalibor, Matthias Jarke, et al. "A Computer Science Perspective on Digital Transformation in Production." ACM Transactions on Internet of Things 3, no. 2 (2022): 1–32. http://dx.doi.org/10.1145/3502265.

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The Industrial Internet-of-Things (IIoT) promises significant improvements for the manufacturing industry by facilitating the integration of manufacturing systems by Digital Twins. However, ecological and economic demands also require a cross-domain linkage of multiple scientific perspectives from material sciences, engineering, operations, business, and ergonomics, as optimization opportunities can be derived from any of these perspectives. To extend the IIoT to a true Internet of Production , two concepts are required: first, a complex, interrelated network of Digital Shadows which combine d
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Iatchevici, Vadim, Alexei Toca, Tatiana Nitulenco, and Aurel Stroncea. "Technological transfer under the conditions of digitalization of products and processes." Journal of Engineering Science 30, no. 4 (2023): 31–44. https://doi.org/10.52326/jes.utm.2023.30(4).03.

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Technological development is largely determined by technology transfer, which is conditioned by the absorption capacity of new technologies, and new technologies are deeply digitized technologies. Success depends on creating basic digital skills, both technical and human, developing digital infrastructure, ensuring accessibility to digital technologies. In the context of Industry 4.0 technologies, the efforts to design products with pronounced physical-cybernetic elements are important, but especially those aimed at creating digital twins, gradually moving from intermediate variants of digital
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Vikas Prajapati. "Exploring the Role of Digital Twin Technologies in Transforming Modern Supply Chain Management." International Journal of Science and Research Archive 14, no. 3 (2025): 1387–95. https://doi.org/10.30574/ijsra.2025.14.3.0792.

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The advent of digital twins (DTs) has improved operational efficiency, sustainability, and predictive analytics, hence transforming the field of supply chain management. This study explores the role of DTs in optimizing supply chain processes, distinguishing them from digital models and shadows by emphasizing bidirectional data flow and real-time synchronization. The study showcases DT applications across a range of sectors, elucidating their revolutionary influence: manufacturing, healthcare, smart cities, education, and next-generation networks. Key supply chain use cases such as demand fore
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Dissertations / Theses on the topic "Digital Models/Shadows/Twins"

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Irastorza, valera Luis. "Learning Techniques for Optimization in Engineering : Data-Driven Tools for Mechanical and Biomedical Settings." Electronic Thesis or Diss., Paris, ENSAM, 2025. http://www.theses.fr/2025ENAME020.

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La présente thèse de doctorat englobe une série de casuistiques dans divers domaines de l’ingénierie et de la médecine dont les points communs sont leur complexité conceptuelle et numérique. Cela compromet à son tour la disponibilité et la fiabilité des données expérimentales qui avalisent leurs modèles constitutifs correspondants, si existants. Souvent, ces modèles basés sur des expressions analytiques souffrent d’une complexité inabordable pour l'ordinateur ("malédiction de la dimensionnalité") et/ou sont alourdis par des biais induits dans leur définition (e.g. variables internes non observ
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Books on the topic "Digital Models/Shadows/Twins"

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Digital Transformation in Industry: Digital Twins and New Business Models. Springer International Publishing AG, 2022.

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Stary, Christian, and Franz Barachini. From Digital Twins to Digital Selves and Beyond: Engineering and Social Models for a Trans-Humanist World. Springer International Publishing AG, 2022.

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Nitsch, Verena, Dirk Lüttgens, Sebastian Pütz, Frank T. Piller, and Alexander Mertens. Forecasting Next Generation Manufacturing: Digital Shadows, Human-Machine Collaboration, and Data-Driven Business Models. Springer International Publishing AG, 2022.

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Forecasting Next Generation Manufacturing: Digital Shadows, Human-Machine Collaboration, and Data-Driven Business Models. Springer International Publishing AG, 2023.

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Book chapters on the topic "Digital Models/Shadows/Twins"

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van der Aalst, Wil M. P., Matthias Jarke, István Koren, and Christoph Quix. "Digital Shadows: Infrastructuring the Internet of Production." In Internet of Production. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-98062-7_25-1.

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AbstractDigitization in the field of production is fragmented in very different domains, ranging from materials to production technology to process and business models. Each domain comes with specialized knowledge, often incorporated into mathematical models. This heterogeneity makes it hard to naively exploit advances in data-driven machine learning that could facilitate situation adaptation and experience transfer. Innovative combinations of model-driven and data-driven solutions must be invented but also made comparable and interoperable to avoid ending up in information silos. In future World Wide Labs (WWLs), experiences can be shared, aggregated, and used for innovation. WWLs will be complex, evolving socio-technical networks of interconnected devices, software, data stores, and humans as users and contributors of expert knowledge and feedback. Integrating a large number of research labs, engineering, and production sites requires a capable cross-domain Internet of Production (IoP) infrastructure. The IoP project claims Digital Shadows (DSs) to offer a shared conceptual foundation for infrastructuring the IoP. In engineering, DSs were introduced as the data provision link to Digital Twins, whereas in computer science, DSs generalize the well-established concept of database views. In this chapter, we elaborate on the roles of DSs in infrastructuring the IoP from three perspectives: analytic functionality, conceptual organization, and technical networking. As an example where an integrative DS-like approach is already highly successful, we showcase the approach and infrastructure of the process mining field.
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van der Aalst, Wil, Matthias Jarke, István Koren, and Christoph Quix. "Digital Shadows: Infrastructuring the Internet of Production." In Internet of Production. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-44497-5_25.

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AbstractDigitization in the field of production is fragmented in very different domains, ranging from materials to production technology to process and business models. Each domain comes with specialized knowledge, often incorporated into mathematical models. This heterogeneity makes it hard to naively exploit advances in data-driven machine learning that could facilitate situation adaptation and experience transfer. Innovative combinations of model-driven and data-driven solutions must be invented but also made comparable and interoperable to avoid ending up in information silos. In future World Wide Labs (WWLs), experiences can be shared, aggregated, and used for innovation. WWLs will be complex, evolving socio-technical networks of interconnected devices, software, data stores, and humans as users and contributors of expert knowledge and feedback. Integrating a large number of research labs, engineering, and production sites requires a capable cross-domain Internet of Production (IoP) infrastructure. The IoP project claims Digital Shadows (DSs) to offer a shared conceptual foundation for infrastructuring the IoP. In engineering, DSs were introduced as the data provision link to Digital Twins, whereas in computer science, DSs generalize the well-established concept of database views. In this chapter, we elaborate on the roles of DSs in infrastructuring the IoP from three perspectives: analytic functionality, conceptual organization, and technical networking. As an example where an integrative DS-like approach is already highly successful, we showcase the approach and infrastructure of the process mining field.
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Böhlen, Marc. "On models and digital twins." In On the Logics of Planetary Computing. Routledge, 2024. http://dx.doi.org/10.4324/9781003519690-8.

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Garnero, Gabriele, and Gloria Tarantino. "3D City Models in Planning Activities." In Handbook of Digital Twins. CRC Press, 2024. http://dx.doi.org/10.1201/9781003425724-42.

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Braun, Stefan, Manuela Dalibor, Nico Jansen, et al. "Engineering Digital Twins and Digital Shadows as Key Enablers for Industry 4.0." In Digital Transformation. Springer Berlin Heidelberg, 2023. http://dx.doi.org/10.1007/978-3-662-65004-2_1.

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Gomes, Cláudio, Hao Feng, Zahra Kazemi, and Ken Pierce. "Calibration of Models for Digital Twins." In The Engineering of Digital Twins. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-66719-0_6.

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Korablyov, Mykola, Sergey Lutskyy, Ihor Ivanisenko, and Oleksandr Fomichov. "System-Information Models of Digital Twins." In Intelligent Sustainable Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8031-4_10.

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Chu, Yingguang, Guoyuan Li, Vilmar Æsøy, and Houxiang Zhang. "Models and Sub-domain Models for Digital Twins." In Digital Twins for Vessel Life Cycle Service. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4768-9_5.

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Magnani, Marta, and Antonello Provenzale. "Models, Digital Twins and Virtual Research Environments." In Advances in Critical Zone Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-69076-1_11.

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Holtzapple, Alex, Sander Arnout, and Els Nagels. "Evolution of Process Models to Digital Twins." In The Minerals, Metals & Materials Series. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92563-5_55.

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Conference papers on the topic "Digital Models/Shadows/Twins"

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Stevnsborg, Mads, Krist V. Gernaey, and Jakob K. Huusom. "Digital Shadow of a Pilot Scale Packed Batch Distillation Column for Real-Time Operator Training- and Support." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.182519.

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Digital twins and digital shadows are frequently used terms by industry and academia to describe data-centric models that accurately depict a physical system intended for process monitoring and control. Processes restricted by a low degree of automation rely greatly on operator competencies in key decision-making; a digital shadow can here assist as a guidance tool [1-4]. This work presents a practical implementation of a digital shadow to support operators running a pilot scale-packed batch distillation column at the Technical University of Denmark (DTU) primarily used in education and teachi
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Orsolits, Horst, Sebastian Rauh, and Robert Fellner. "XR Integration into higher education using digital shadows and digital twins." In 2024 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). IEEE, 2024. https://doi.org/10.1109/ismar-adjunct64951.2024.00021.

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Haugen, Øystein. "Digital Twins: Models Everywhere." In 13th International Conference on Model-Based Software and Systems Engineering. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013454700003896.

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Heermann, Hagen, Moritz Herzog, Johannes Koch, and Christoph Grimm. "Generating Digital Twins from SysMLv2 Models." In 2024 IEEE 22nd International Conference on Industrial Informatics (INDIN). IEEE, 2024. https://doi.org/10.1109/indin58382.2024.10774476.

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Munko, Marek Jan, Matjaz Vidmar, Conchúr M. Ó Brádaigh, Fergus Cuthill, Miguel Angel Valdivia Camacho, and Sergio Lopez Dubon. "Do Digital Twins Require Physical Simulations? A Study of Developing Digital Twins with Varying Reliance on Physics-Based Models." In 2024 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC). IEEE, 2024. https://doi.org/10.1109/ice/itmc61926.2024.10794252.

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Lwele, Emmanuel, and Alex Shenfield. "AI-Based Surrogate Models of Digital Twins for Industrial Processes." In 2024 IEEE Industrial Electronics and Applications Conference (IEACon). IEEE, 2024. https://doi.org/10.1109/ieacon61321.2024.10797334.

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Barbie, Philippe, Andreas Pollom, Rene-Pascal Fischer, and Martin Becker. "Automated Generation of Standardised Digital Twins Based on MBSE Models." In 13th International Conference on Model-Based Software and Systems Engineering. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013190300003896.

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Ayello, Francois, Guanlan Liu, Yonghe Yang, Yuchong Zhang, Long Li, and Shuhui Zhang. "Probabilistic Digital Twins for Transmission Pipelines." In CORROSION 2021. AMPP, 2021. https://doi.org/10.5006/c2021-16780.

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Abstract Digitalization in the oil and gas industry has led to the formation of digital twins. Digital twins bring closer the physical and virtual world as data is transmitted seamlessly between real time sensors, databases and models. The strength of the digital twin concept is the interconnectivity of data and models. Any model can use any combination of inputs (e.g. operator owned data sets and sensors, third-party databases such as soil composition or weather data, results from other models such as flow assurance, threat modelling or risk modelling). Consequently, the result of one model m
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Zaki-Hindi, Ayat, Jean-Sébastien Sottet, Ion Turcanu, and Sébastien Faye. "Network Digital Twins for 6G: Defining Data Taxonomy and Data Models." In 2024 IEEE Conference on Standards for Communications and Networking (CSCN). IEEE, 2024. https://doi.org/10.1109/cscn63874.2024.10849705.

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Mabrich, Alexander, and Burak Boyaci. "Beyond BIM: Digital Twins for 3D Digital Project Deliverables." In IABSE Congress, San José 2024: Beyond Structural Engineering in a Changing World. International Association for Bridge and Structural Engineering (IABSE), 2024. https://doi.org/10.2749/sanjose.2024.0621.

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<p>As the infrastructure industry is consolidating on the use of 3D models and applying the BIM methodology, the challenge is to build a comprehensive model of the entire project and not just its individual parts: roadways, bridges, drainage, geotechnical and vertical structures. These different disciplines use specific software solutions and file formats to accomplish the tasks at hand. However, to combine them into a single model for design reviews, construction, operation, and maintenance is not an easy endeavor.</p><p>The purpose of this paper is to show how a digital twi
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Reports on the topic "Digital Models/Shadows/Twins"

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Broderick, Conlan, and Sarah Bunn. Digital twins - dynamic models that respond to real-time data. Parliamentary Office of Science and Technology, 2025. https://doi.org/10.58248/rr82.

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This briefing explains digital twin technology and how they are used in different sectors. It also outlines how the UK is investing to develop national capability in this technology, and the associated opportunities and challenges for its wider application.
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Phillips, Paul. The Adoption of Digital Twins in Integrated Vehicle Health Management. SAE International, 2023. http://dx.doi.org/10.4271/epr2023024.

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<div class="section abstract"><div class="htmlview paragraph">To many, a digital twin offers “functionality,” or the ability to virtually rerun events that have happened on the real system and the ability to simulate future performance. However, this requires models based on the physics of the system to be built into the digital twin, links to data from sensors on the real live system, and sophisticated algorithms incorporating artificial intelligence (AI) and machine learning (ML). All of this can be used for integrated vehicle health management (IVHM) decisions, such as determini
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Xie, Haiyan, and Mangolika Bhattacharya. MATH-DT: Development of Mathematical Models for Large-Scale Nonlinear Optimization for Digital Twins Nomenclature Table. Illinois State University, 2025. https://doi.org/10.30707/1741890724.245225.

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The nomenclature table for the Mathematical Digital Twin project description systematically defines key variables, parameters, and mathematical symbols used throughout the research. The table is deposited for open access, allowing other researchers to reference and build upon the work to enhance transparency and reproducibility.
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Williams, Wesley, and Elvis Dominguez-Ontiveros. Building Initial Dynamic System Models for Digital Twins of the Cryogenic Moderator System at the ORNL Spallation Neutron Source. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1871109.

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Williams, Wesley, and Elvis Dominguez-Ontiveros. Building Initial Dynamic System Models for Digital Twins of the Cryogenic Moderator System at the ORNL Spallation Neutron Source. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1871109.

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Baete, Christophe, and Keith Parker. PR405-213601-R04 Validation of Digital Twins for Monitoring, Optimization, and Compliance of CP Systems. Pipeline Research Council International, Inc. (PRCI), 2023. http://dx.doi.org/10.55274/r0012254.

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The digital twin used in this research is a mechanistic (or deterministic) computer model that represents the cathodic protection behavior of a pipeline network. The model is calibrated based on field data such that it mimics the real-world behavior of the pipeline. The objective of this research is to validate the accuracy of the digital twin model on three industry cases. First, the sensitivity of the independent variables (soil, coating and cathodic protection properties) that are the inputs of the digital twin was investigated during a literature study, a lab and field-based modeling on a
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Moskicheva, Elena. Integration of Artificial Intelligence in Industrial Design: From Generative Models to Intelligent Automation. Intellectual Archive, 2025. https://doi.org/10.32370/iaj.3263.

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This article examines the role of artificial intelligence in transforming industrial design processes. Special attention is given to generative design, the use of AI in CAD environments, and the concept of digital twins. Practical examples of intelligent systems applied in product development are provided, demonstrating increased efficiency, reduced timeframes, and improved quality of design solutions. The paper also discusses future prospects for AI integration and the associated ethical challenges.
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Building Greener, Resilient Transport Infrastructure: Innovating with Artificial Intelligence and Digital Twins in Road Design in Uzbekistan. Asian Development Bank, 2023. http://dx.doi.org/10.22617/tim230342.

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This publication provides a case study of how digital tools can help optimize road design to strengthen climate resilience, safety, and efficient resource use. It explains how virtual models can be used to simulate and analyze the effects of potential design choices and future scenarios such as climatic conditions. It shows how greater use of data and digital solutions can help build greener, more durable transport infrastructure and bolster safety. The case study was developed in collaboration with ORIS as part of a project to upgrade a section of the A380 Highway in Uzbekistan.
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