DTUAV: a novel cloud–based digital twin system for unmanned aerial vehicles

The digital twin (DT) mainly acts as a virtual exemplification of a real-world entity, system, or process via multiphysical and logical models, allowing the capture and synchronization of its functions and attributes. The bridge between the actual system and the digital realm can be utilized to optimize the system’s performance, and forecast and predict its behavior. Incorporating intelligent and adaptive reasoning mechanisms into DTs is crucial to enable them to reason, adapt, and take efficacious actions in complex and dynamic environments. To this end, we introduce an approach for deploying agent-based DTs for cyber-physical systems. The foundation pillars of this approach are (1) integrating the concepts, entities, and relations of Zeigler’s modeling and simulation framework from the perspective of agent-based DTs; (2) utilizing an expandable and scalable architecture for designing and materializing these twins, which handily enables extending and scaling physical and digital assets of the system; and finally (3) a two-tier reasoning strategy; reactive and rational models are conceptually redefined in the context of the modeling and simulation framework of agent-based DTs and technically deployed to boost the adaptive reasoning and decision-making function of DTs. As a result, an implemented simulation and control platform for a multi-robot system demonstrates the approach’s applicability and feasibility, manifesting its usability and efficiency. The platform represents physical entities as autonomous agents, creates their DTs, and assigns adequate reasoning capability to promote adaptive planning, autonomous resource management, and flexible logical decision-making to handle different situations and scenarios.

Section: Digital Twins For Robotic Systemsmentioning

confidence: 99%

Adaptive hybrid reasoning for agent-based digital twins of distributed multi-robot systems

Marah,

Challenger

2024

“…As simulationists, we have access to many simulation models developed as part of our research and industry projects. Many existing simulation models (such as those in Meng et al 96 and Grigoryan et al 97 ) have the potential to be used as learning context for PBL activities through the ISBL framework summarized in Figure 2. Moreover, in recent years, many simulation software offer enhanced animation features as well as VR compatibility.…”

Section: A Sample Isbl Modulementioning

confidence: 99%

Simulation in engineering education: The transition from physical experimentation to digital immersive simulated environments

Negahban

2024

Besides its use as a powerful systems analysis tool, simulation has also been used for decades in educational settings as a teaching and learning method. Simulation can replace or augment real-world inquiry-based experiences by providing learners with a low-cost and risk-free experimentation platform to develop knowledge and skills in a simulated environment. This paper presents an overview of current applications and the ongoing transition from physical experimentation to digital simulations and immersive simulated learning environments in engineering education. The paper highlights major implementation and research gaps related to simulation-based learning and immersive simulated learning environments, namely, lack of integration with learning theories and limited formal assessments of effectiveness. Potential implementation approaches and important areas for future educational research are discussed and exemplified in response to the identified gaps. The discussions presented are intended for simulationists, educational researchers, and instructors who are interested in designing and/or utilizing engineering education interventions involving simulated learning environments and immersive technologies in their teaching and educational research. In particular, the Immersive Simulation-Based Learning (ISBL) approach discussed in the paper provides a framework for simulationists to reuse the models developed as part of their simulation projects for educational purposes.

“…Therefore, it is crucial to determine the appropriate level of fidelity for DT. 72 Jones et al (2020) 62 argue that DT fidelity levels comprise multiple dimensions, including the number of parameters, the precision of those parameters, and the degree of abstraction in the reciprocal 62 x x x Liu et al 64 x x x x Moyne et al 63 x x x Rasheed et al 60 x x x x Sjarov et al 65 x x Meng et al 4 x x x x Talkhestani et al 66 x Wagner et al 50 x x Wang et al 67 x Zhang et al 68 x x Table 1. DT interoperability literature considerations.…”

Section: Interoperability Interoperability Is the Ability Of Twomentioning

confidence: 99%

“…Computational science has even been called the third pillar of science for that reason. 3 In recent years, the Digital Twin (DT) concept has surfaced in many areas, e.g., aerospace, 4 manufacturing, 5 healthcare, 6 transportation systems 7 and smart cities. 8 The DT approach landed in the top strategic technology trends, as shown in the Gartner hype cycle of 2017 9 and 2018.…”

Section: Introductionmentioning

confidence: 99%

From modeling and simulation to Digital Twin: evolution or revolution?

Ali,

Biglari,

Denil

et al. 2024

As digitalization is permeating all sectors of society toward the concept of “smart everything,” and virtual technologies and data are gaining a dominant place in the engineering and control of intelligent systems, the Digital Twin (DT) concept has surfaced as one of the top technologies to adopt. This paper discusses the DT concept from the viewpoint of Modeling and Simulation (M&S) experts. It both provides literature review elements and adopts a commentary-driven approach. We first examine the DT from a historical perspective, tracing the historical development of M&S from its roots in computational experiments to its applications in various fields and the birth of DT-related and allied concepts. We then approach DTs as an evolution of M&S, acknowledging the overlap in these different concepts. We also look at the M&S workflow and its evolution toward a DT workflow from a software engineering perspective, highlighting significant changes. Finally, we look at new challenges and requirements DTs entail, potentially leading to a revolutionary shift in M&S practices. In this way, we hope to foster the discussion on DTs and provide the M&S expert with innovative perspectives.