Twin Concepts Research Articles

An Approach Integrating Model-Based Systems Engineering, IoT, and Digital Twin for the Design of Electric Unmanned Autonomous Vehicles

This article proposes a novel methodology aimed at streamlining the system’s development process. By examining existing state-of-the-art approaches and the capabilities inherent in Model-Based Systems Engineering (MBSE) tools, the article introduces a methodology centered around transforming a descriptive Systems Modeling Language (SysML) model into a digital twin. This virtual representation of the physical asset leverages real-time data and simulations to mirror its behavior and characteristics. When integrated with MBSE, this synergy allows for a comprehensive and dynamic approach, enhancing innovation by providing a holistic and adaptable framework for designing, analyzing, and optimizing complex systems throughout their lifecycle. The practical application of this Real-Time Communication and Data Acquisition (RT-CDA) methodology is implemented in a context and operational scenario of an electric unmanned autonomous vehicle employing both Software-in-the-Loop (SITL) and Hardware-in-the-Loop (HITL) approaches. The methodology empowers systems engineers to iteratively update and refine their system model’s fidelity based on real-world testing insights. The article specifically demonstrates the real-time communication capabilities achieved between an electric unmanned autonomous vehicle (a physical asset) and a descriptive (SysML) model, illustrating the real-time data aspect integral to the concept of a digital twin. This study serves as a foundation for future endeavors, envisioning real-time communication among virtual and physical models to construct comprehensive digital twins of complex systems to predict behavior and performance.

Proactive perceptive road: a digital twin-driven intelligent road infrastructure towards proactive road state perception and deduction

Abstract The emergence of the digital twin (DT) concept provides a new development direction for the digital transformation and upgrading of road health monitoring and maintenance management. Current road digitization technologies primarily focus on the integration and management of easily perceived and measurable asset and maintenance data. However, they struggle to effectively connect the physical state of the road with various computational and analytical modules, making it difficult to sense and integrate complex, hard-to-measure implicit state information and resulting in an inability to support more comprehensive road condition monitoring and precise maintenance decision-making. This paper introduces the concept of proactive perceptive road (PPR), an intelligent road infrastructure driven by DT technology, capable of actively sensing and deducing explicit and implicit road state information. PPR comprises physical space (air, surface, and internal subspaces) entities and DT models and sensing engines in the virtual space. The paper outlines the application logic and core capabilities of PPR and, based on this, proposes an example architecture for its implementation. Two application case studies are presented—one for monitoring construction quality and another for sensing road structure responses—demonstrating the value and potential of PPR in real-time sensing of implicit road state information. The challenges that remain in practical application are also discussed including perceptual, data, and simulation techniques. The proposed concept of PPR represents the next phase of development, offering insights and methodologies for sensing and extracting complex, implicit structural performance data and road health conditions. The presented cases can serve as references for applying DT in the road sector and guide the development of customized solutions for specific scenarios.

Defining the Legal Status of an Individual’s Digital Twin (Surrogate)

With the rapid expansion of the internet, the extensive digitalization of all aspects of modern society, and the accelerated adoption of artificial intelligence technologies, the concept of digital twins has become increasingly relevant. However, modern legal science still needs to bridge the gap in regulating digital twins and establish clear approaches to their use. In this article, the legal status of digital twins, a concept new to Russian law, was examined. The potential impact of digital twins on legal relations was estimated. The major legal problems and risks resulting from the use of digital twins of humans were identified and discussed. It was proposed to legally define the concept of a digital twin (surrogate) and digital human rights, set legal boundaries for the actions of an AI-driven digital twin, adjust access levels for various services, delineate the legal implications of actions taken by digital twins in virtual environments, and outline clear and effective methods to protect digital twins.

Smart textile as advanced human digital interface in metaverse

It is important to recognize that, while digitization has made significant advancements, it has largely overlooked everyday clothing, which remains a vital aspect of our lives. This gap can be attributed to the noticeable lag in the textile industry compared to the microelectronics sector. This concept review emphasizes the significance of creating smart clothing that features a digital interface and explores its potential benefits within the metaverse. Our idea focuses on enhancing such garments to implement a human digital twin concept, which we believe, could enable an evolution of our innate abilities in the digital realm. To achieve this, we have identified essential requirements for the smooth integration of smart clothing into the metaverse and have elaborated on these needs. Nonetheless, despite the anticipated benefits, our proposed model faces several challenges, that have been outlined, including issues related to energy consumption, production methods, safety standards, and sustainability considerations.

Digital twin enhanced agile design of ship pipeline systems

The shipbuilding industry plays a pivotal role in national strategic security and economic development, and one critical challenge is the pipeline layout design problem. It predominantly relies on designers’ subjective experience, and it is marked by a lack of efficient knowledge sharing and the absence of smart pipe routing algorithms. This paper proposes an agile design system, which integrates ship pipeline design knowledge management, semi-automatic design that involves frequent interaction with human designers, and automatic rule checking. The framework is refined by digital twin concepts, facilitating close collaboration between physical and digital systems. The paradigm shift holds the potential to substantially enhance the efficiency of ship pipeline layout design, while concurrently reducing the reliance on manual labor.

Fuzzy energy management strategies for energy harvesting IoT nodes based on a digital twin concept

Fuzzy energy management strategies for energy harvesting IoT nodes based on a digital twin concept

Challenging the hijab ban in India: plural embodiment and secular constitutionalism

Abstract This paper examines the core twin concepts of secularism and pluralism and their location within the Indian constitutional discourse, through a discussion of the hijab ban in the South Indian state of Karnataka. I suggest that attempts at Hindu majoritarian subversion of these core principles face challenges due to the structure of the Indian Constitution, and due to the constitutional agency and mutinies set in motion by women through their legal challenge of state action. I discuss the hijab ban in India and the two judgments on the ban as an example of this attempted subversion but also of its failure, suggesting that these judgments fall short in their reading of this interrelationship between secularism and pluralism. In doing so, I introduce a threefold analytical categorisation, pluralist constitutionalism, constitutional appropriation and constitutional derailment, to help us outline the tensions inherent in constitutional politics in the present.

Development of a Baseline Digital Twin Model as a Prerequisite for the Digital Twin Definition of a PSC-I Bridge with Model Updating Considering Member Stiffness

Structural health monitoring using various sensors has been widely employed to assess the structural conditions of bridges. In addition, the concept of a digital twin was introduced, which encompasses the life cycle information of a bridge and its real-time data acquisition and utilization. However, the obtained real-time data from sensors primarily reflect the global behavior of the system, making it challenging to identify the root causes of structural changes. For a highly reliable assessment of the global behavior of a bridge, previous history information, that is, a prerequisite model, is required. This study defines a baseline digital twin model (B-DTM) as the stage preceding real-time data utilization in digital twins. The B-DTM is structured into a pre-update phase, which involves the collection of members and system historical data, and a post-update phase, which focuses on model updating. For the case of model updating, due to the inherent complexity of bridge systems, identifying the global optimum for updating remains challenging. In the pre-update phase, a probabilistic approach to historical data such as member stiffness restricts the search domain for model updating, whereas, in the post-update phase, deflection, mode shapes, and natural frequencies derived from load test results representing the real bridge’s behavior are utilized to explore the global optimum solution. The proposed B-DTM was validated using collected data and load test results from a PSC-I girder bridge decommissioned after 45 years of service.

Digital Twin - An Innovative Strategy in Healthcare Transformation: An Extensive Review

In an age where the physical and digital worlds progressively intersect, the concept of the digital twin has aroused as a transformative force across various industries. Digital twins are dynamic digital imitations of physical objects; systems are procedures that can be used to simulate, analyse, and optimize their real-world analogue. In the health care field, a lot of work has gone into establishing digital twin of patient and medical devices. The digital twin of the patient is created by digitising the patient’s physical traits and bodily alterations. Real-world utilization of this technology includes accurate maintenance, advanced operational efficiency, and support for well-informed decision-making, all of which are trans-formative. The digital twin revolution is changing how healthcare professionals approach patient care, treatment planning, and facility administration. Digital twins provide instantaneous monitoring, personalized therapy, and predictive analytics by generating dynamic virtual replicas of patients, medical equipment, and healthcare systems. By offering insights on energy use, material consumption, and other vital variables, digital twin facilitates improved resource management and boosts businesses by cutting costs and waste. Digital twins are positioned to play a vital role in modern healthcare, inciting innovation and efficiency throughout the sector as technology advances. We focused on applications and development of digital twin in healthcare sector by analyzing a large number of studies from distinct medical sector, the effectiveness of digital twin in imaging studies and diagnosis, cancer, cardiology, neurology has been discussed in this review.

Optimizing operations of flexible assembly systems: demonstration of a digital twin concept with optimized planning and control, sensors and visualization

AbstractThis paper presents the development of an optimized planning and control method for flexible manufacturing and assembly systems. While the significant potential of flexible manufacturing concepts to help producers adapt to market developments is recognized, the complexity of the flexible systems and the need to optimally plan and control them is a major obstacle in their practical implementation. Thus, this paper aims to develop a comprehensive digital planning method, based on a digital twin and to demonstrate the feasibility of the approach for practical application scenarios. The approach consists of four modules: (1) a simulation-based optimization module that applies reinforcement learning and genetic algorithms to optimize the module configuration and job routing in cellular reconfigurable manufacturing systems; (2) a synchronization module that links the physical and virtual systems via sensors and event handling; (3) a sensor module that enables a continuous status update for the digital twin; and (4) a visualization module that communicates the optimized plans and control measures to the shop floor staff. The demonstrator implementation and evaluation are implemented in a learning factory. The results include solutions for the method components and demonstrate their successful interaction in a digital twin, while also pointing towards the current technology readiness and future work required to transfer this demonstrator implementation to a full-scale industrial implementation.

Interoperable information modelling leveraging asset administration shell and large language model for quality control toward zero defect manufacturing

In the era of Industry 4.0, Zero Defect Manufacturing (ZDM) has emerged as a prominent strategy for quality improvement, emphasizing data-driven approaches for defect prediction, prevention, and mitigation. The success of ZDM heavily depends on the availability and quality of data typically collected from diverse and heterogeneous sources during production and quality control, presenting challenges in data interoperability. Addressing this, we introduce a novel approach leveraging Asset Administration Shell (AAS) and Large Language Models (LLMs) for creating interoperable information models that incorporate semantic contextual information to enhance the interoperability of data integration in the quality control process. AAS, initiated by German industry stakeholders, shows a significant advancement in information modeling, blending ontology and digital twin concepts for the virtual representation of assets. In this work, we develop a systematic, use-case-driven methodology for AAS-based information modeling. This methodology guides the design and implementation of AAS models, ensuring model properties are presented in a unified structure and reference external standardized vocabularies to maintain consistency across different systems. To automate this referencing process, we propose a novel LLM-based algorithm to semantically search model properties within a standardized vocabulary repository. This algorithm significantly reduces manual intervention in model development. A case study in the injection molding domain demonstrates the practical application of our approach, showcasing the integration and linking of product quality and machine process data with the help of the developed AAS models. Statistical evaluation of our LLM-based semantic search algorithm confirms its efficacy in enhancing data interoperability. This methodology offers a scalable and adaptable solution for various industrial use cases, promoting widespread data interoperability in the context of Industry 4.0.

Evaluation of product lifecycle management and digital twin integration in aviation field

In today's world, digital transformation is becoming increasingly crucial in industry. The Digital Twins and simulations become much more important with growing complexity of products, the need to accelerate product development processes while reducing costs. The increasing value of Digital Twins is prompting organizations in the aviation industry to actively utilize them in research and development efforts. However, due the idea of difficulties of using Digital Twins in the industries, product developers don’t have a clear idea where to begin. This article provides readers with a general overview of the current situation by offering an examination of the aviation sector. Initially, the concept of Digital Twin, its evolution, and relevant studies are explored, followed by an examination of the impact of creating Digital Twins for companies operating in aviation on the product development process. In this study, unlike other published works, the concept of Digital Twin is explained under three subheadings. These include the Design Digital Twin for design steps, the Production Digital Twin for manufacturing processes, and the Performance Digital Twin for post-delivery work related to the product. The final section of the study evaluates the contribution of Product Lifecycle Management (PLM) systems to the process of creating Digital Twins and the advantages they provide to companies in product development processes. The present research work does not contain any studies performed on animals/humans subjects by any of the authors.

Developing of a Digital Twin for Urban Planning in an International Context

The digital twin, adapted to the needs of urban planning and monitoring systems, is the subject of research and development in the academic, commercial and public sectors. The article provides international context in conceptual and practical implementation through their maturity level, scope, purpose, structure, input, processing features and output. The City of Zagreb is presented as an example of the implementation of GIS and 3D city models in urban planning, with activities towards a digital twin city. Based on research and local specifics, the concept of a digital city twin was proposed for the needs of urban planning, and future challenges were identified.

Real-Time Modeling for Design and Control of Material Additive Manufacturing Processes

The use of digital twin and shadow concepts for industrial material processes has introduced new approaches to bridge the gap between physical and cyber manufacturing processes. Consequently, many multidisciplinary areas, such as advanced sensor technologies, material science, data analytics, and machine learning algorithms, are employed to create these hybrid systems. Meanwhile, new additive manufacturing (AM) processes for metals and polymers, based on emerging technologies, have shown promise for the manufacturing of sophisticated parts with complex geometries. These processes are undergoing a major transformation with the advent of digital technology, hybrid physical-data-driven modeling, and fast-reduced models. This study presents a fresh perspective on hybrid physical-data-driven and reduced order modeling (ROM) techniques for the digitalization of AM processes within a digital twin concept. The main contribution of this study is to demonstrate the benefits of ROM and machine learning (ML) technologies for process data handling, optimization/control, and their integration into the real-time assessment of AM processes. Therefore, a novel combination of efficient data-solver technology and an architecturally designed neural network (NN) module is developed for transient manufacturing processes with high heating/cooling rates. Furthermore, a real-world case study is presented, showcasing the use of hybrid modeling with ROM and ML schemes for an industrial wire arc AM (WAAM) process.

The e-COL+ Project, an Opportunity to Reflect on the Concept of Digital Twin

Abstract The mass digitization efforts associated with the e-COL+ project, focusing on French natural history collections, provide an invaluable opportunity to reassess the need to build a comprehensive 3D digital collection to complement existing 2D digital repositories. This article explores the importance of incorporating 3D data into digital collections, highlighting its significant impact on scientific research, conservation efforts, and public outreach campaigns. Although the e-COL+ project faces practical obstacles related to digitization, it also raises important theoretical questions about the complex interplay between physical and digital objects. Here, we challenge the concepts of digital clone and digital twin that are commonly used in the construction of digital collections. The digital twin concept more accurately captures the intricate and adaptive connection between physical and digital entities that results from the precise digitization techniques used and the evolving characteristics of the specimens found in natural history collections.

Application of Digital Twins in Designing Safety Systems for Robotic Stations

The aim of this paper is to present examples and original solutions related to the application of the digital twin concept in designing safety systems for robotic stations. This paper includes a review of publications on robot safety systems and digital twins. Based on this review, it was concluded that further work in this area is justified. This paper demonstrates the use of a digital model of a robotic casting mold preparation station to design safety components for an industrial cell. A key element of this paper is the presentation of developed algorithms and their applications in building digital twins of existing robotic stations. By characterizing advanced safety systems used in robotic stations, an example of using a digital twin of a robotic station to create safety zones and so-called restricted zones for the robot was developed. As part of the research conducted, a real, comprehensive example of creating safety zones based on the robot’s TCP paths was carried out.

3D Remote Monitoring and Diagnosis during a Pandemic: Holoportation and Digital Twin Requirements

COVID-19 regulations presented clinicians with a new set of challenges that affected their ability to efficiently provide patient care and, as a result, telemedicine was rapidly adopted to deliver care remotely. However, these telemedicine platforms undermine patient care due to clinicians' inability to acquire all the relevant patient information required to diagnose and treat the patient. To explore this gap, we conducted a requirements analysis for the development of a 3D remote patient monitoring and diagnosis platform, by using a user-centric design methodology. In this requirements analysis, we elicited information about the clinical domain, identified clinicians’ requirements, elicited clinicians’ insights, and documented the clinicians' requirements. The outcome was the emergence of refined clinicians' requirements to guide the implementation of the Digital Twin concept paired with holoportation for remote 3D monitoring and diagnosis of patients. We anticipate that the application of a 3D telemedicine platform with these requirements for patient care during a pandemic could potentially enhance clinicians' efficiency and the effectiveness of remote patient care.

Open-Source Solutions for Real-Time 3D Geospatial Web Integration

Abstract. The recent development of Urban Digital Twin (UDT) structures and the spread of Internet of Things (IoT) technology have extended the concept of Digital Twin (DT) to urban environment representation, enabling real-time connections between geospatial representations and their real-world counterparts. Concurrently, advancements in surveying technologies and web geospatial services have facilitated the acquisition of extensive 2D and 3D geospatial data, making their spatial integration essential. While some proprietary software solutions have recently enabled initial examples of UDT by integrating various 3D geospatial data and real-time sensor acquisition, the development of open-source solutions for real-time web-based geospatial management remains a challenge. This work demonstrates a possible open-source solution for developing a UDT accessible via the web. The case study involves the web visualization platform of the new Faculty of ITC building at the University of Twente in Enschede (The Netherlands), which is connected in real-time with weather data services provided by Visual Crossing (1). The platform is based on an HTML5 framework and employs WebGL JavaScript graphic libraries to visualize different modules of 3D web visualization that integrate various local and remote 3D datasets. The framework adopted in this experiment can be used in the future for developing low-cost UDT web platforms beneficial for researchers, municipalities, and private companies interested in the real-time geospatial management of urban environments.

A LiDAR-Based Digital Twinning Workflow for Traffic Monitoring and Simulation

Abstract. The process of ensuring efficient and safe urban transportation is closely linked to urban planning, particularly through the aspects of transportation planning. Transportation planning is a pivotal concern for urban regions worldwide, reflecting the growing need to increase mobility while ensuring safety and sustainability in densely populated areas. This research focuses on developing a novel digital-twin-based approach for micro-traffic simulation to support data-driven decision-making for increasing traffic safety through scenario planning. Leveraging the traffic data obtained through monitoring one of the busiest intersections in Sofia city, this research workflow shows the effective integration of LiDAR data and the urban digital twin concept in intelligent transportation systems (ITS). The research addresses problems related to moving object classification, trajectory analysis, and reclassification of unrecognised objects by processing the LiDAR data, pre-processed in a .osef format, thereby transforming it to make it suitable for simulation. The proposed solution for the monitoring of urban traffic is demonstrated by the usage of SUMO (Simulation of Urban MObility) for performing simulations and a Random Forest model for unrecognized object reclassification to pre-existing vehicles and pedestrian classes. The architecture of the proposed workflow can possibly be applied in other similar urban settings, providing a scalable solution for both traffic management and urban planning. The study’s results support the wider use of urban digital twin principles in ITS by highlighting the value of advanced modelling tools and high-quality data in addressing today's urban transportation challenges.

To the problem of digital immortality

The idea of reproducing personality by means of digital (neural network) technologies (“digital immortality”), together with the concept of Digital Twin (DT), still attracts great attention. Recent advances in the DT industry permit to expect the production of perfect “mirror” DT in the near future. We argue that the “immortality in the memory of other people” could be approached quite closely due to creating an analogue of personal DT by simulating the personality. For this purpose, it is necessary to compose the “constructive portrait” of a chosen person (by extracting the key features and traits of personality) and try to reproduce it by means of a chosen model. We are developing an original model Natural Constructive Cognitive Architecture (NCCA) that inherently provides the interpretation of logical and intuitive thinking, subconscious, etc. This model should be adjusted to specific set of knowledge inherent in a particular person (books, films, photographs, etc.), with an emphasis on personal lexicons (verbal, emotion, behavioral). NCCA contains a large set of free model parameters, which enables us to reproduce a wide range of personality features, from thinking style to temperament. It is shown that popular Generative Pre-trained Transformers (GPTs) have much in common with NCCA and could be adapted and used as an analog of DT of a specific person. We argue that the proposed program would provide the possibility to create an analog of DT, which could give an impression (at least, an illusion) of communication with the desired specific person.