Related papers: Digital twin, physics-based model, and machine lea…
Control Co-Design (CCD) integrates physical and control system design to improve the performance of dynamic and autonomous systems. Despite advances in uncertainty-aware CCD methods, real-world uncertainties remain highly unpredictable.…
A Mobility Digital Twin is an emerging implementation of digital twin technology in the transportation domain, which creates digital replicas for various physical mobility entities, such as vehicles, drivers, and pedestrians. Although a few…
Digital twin (DT) offers significant opportunities for enhancing facility management (FM) in campus environments. However, existing research often focuses narrowly on isolated domains, such as point-cloud geometry or energy analytics,…
The emerging data-driven methods based on artificial intelligence (AI) have paved the way for intelligent, flexible, and adaptive network management in vehicular applications. To enhance network management towards network automation, this…
Animal behavior reflects interactions between the nervous system, body, and environment. Therefore, biomechanics and environmental context must be considered to understand algorithms for behavioral control. Neuromechanical digital twins,…
This survey examines recent advances in generating digital twins from visual data. These digital twins - virtual 3D replicas of physical assets - can be applied to robotics, media content creation, design or construction workflows. We…
Simulation-based digital twins must provide accurate, robust and reliable digital representations of their physical counterparts. Quantifying the uncertainty in their predictions plays, therefore, a key role in making better-informed…
Machine learning classifiers in dynamic environments face concept drift -- changes in the data-generating process that degrade performance. Conventional evaluation via static test sets or noise perturbations fails to preserve causal…
Digital twins enable real-time simulation and prediction in engineering systems. This paper presents a novel framework for predictive digital twins of a headlamp heatsink, integrating physics-based reduced-order models (ROMs) from…
Most modeling approaches lie in either of the two categories: physics-based or data-driven. Recently, a third approach which is a combination of these deterministic and statistical models is emerging for scientific applications. To leverage…
Digital Twins (DTs) are virtual representations of physical objects or processes that can collect information from the real environment to represent, validate, and replicate the physical twin's present and future behavior. The DTs are…
Digital transformation in the built environment offers new opportunities to improve building maintenance through data-driven approaches. Smart monitoring, predictive modeling, and artificial intelligence can enhance decision-making and…
Smart ecosystems are the drivers of modern society. They control infrastructures of socio-techno-economic importance, ensuring their stable and sustainable operation. Smart ecosystems are governed by digital twins -- real-time virtual…
As digital twin technologies are increasingly incorporated into battery management systems to meet the growing need for transparent and lifecycle-aware operation, existing battery digital twins still suffer from fragmented operational…
Digital twins (DTs) are increasingly utilized to monitor, manage, and optimize complex systems across various domains, including civil engineering. A core requirement for an effective DT is to act as a fast, accurate, and maintainable…
This study introduces a physics-based machine learning framework for modeling both brittle and ductile fractures. Unlike physics-informed neural networks, which solve partial differential equations by embedding physical laws as soft…
In this paper, a hyperparameter tuning based Bayesian optimization of digital twins is carried out to diagnose various faults in grid connected inverters. As fault detection and diagnosis require very high precision, we channelize our…
Generation IV (Gen-IV) nuclear power plants are envisioned to replace the current reactor fleet, bringing improvements in performance, safety, reliability, and sustainability. However, large cost investments currently inhibit the deployment…
The transformation to Industry 4.0 also transforms the processes of how we develop intelligent manufacturing production systems. To advance the software development of these new (embedded) software systems, digital twins may be employed.…
Surrogate modeling has brought about a revolution in computation in the branches of science and engineering. Backed by Artificial Intelligence, a surrogate model can present highly accurate results with a significant reduction in…