Digital twinHow Much Training is Needed with a Digital Twin?arXiv API — полнотекстовый поиск "digital twin" · yesterdayDigital twinPUR-1 Cyber-Physical Digital TwinarXiv — Computational Engineering, Finance, and Science (cs.CE) · yesterdayDigital twinForesight session on the future of cyber-physical systems security in RussiaspbIT · yesterdayForecastingStochastic Nonlinear MPC with Gaussian Mixture Uncertainty PropagationarXiv — Systems and Control (eess.SY) · yesterdayMarket & productsUS Nurses Protest Against Hospital Contracts with PalantirCNews · 2dModellingDigital Sector Expands AI Practice with Agentic ScenariosCNews · 2dModellingMechanics of Democratic Dominance: System Dynamics for Consent EngineeringarXiv — Physics and Society (physics.soc-ph) · 2dDigital twinRemote-Sensing-Based Channel Modeling for 6G Digital TwinsarXiv API — полнотекстовый поиск "digital twin" · 2dForecastingDistributed MPC for Optimal Consensus of Heterogeneous Multi-Agent SystemsarXiv — Systems and Control (eess.SY) · 2dEnergyInitialization Is Key in Federated Short-Term Load ForecastingarXiv — Systems and Control (eess.SY) · 2dDigital twinSpec2Twin-Chain: Automating Blockchain Digital Twin ConstructionarXiv API — полнотекстовый поиск "digital twin" · 2dDigital twinCyber-Physical Machine Tool with Real-Time Machining Process Digital TwinarXiv API — полнотекстовый поиск "digital twin" · 2d
What is happening worldwide in digital twins, mathematical modelling and the management of large-scale systems: research, press releases, product news. From the US, China, ASEAN and Africa — translated and summarised.
Investigates how many training pilots are needed when a digital twin of a wireless channel is used for channel estimation. The twin is treated as a complementary measurement fused with pilot observations. For the first time, this trade-off is formalized and quantified.
The article discusses an architecture of a digital twin for nuclear systems, integrating multiple models (physics-based and data-driven) to support decision making, state estimation, predictive control, and real-time data processing. The twin must synchronize with the physical facility faster than its operational cycle.
A new stochastic nonlinear model predictive control method for systems with additive noise is proposed. State distribution is approximated by Gaussian mixture with error bounds in Wasserstein distance. This yields closed-form expressions for expected costs and chance constraints, and the problem is solvable via nonlinear programming with correctness guarantees.
The company 'Aktiv' has finalized a document based on the foresight session held in Moscow in March 2025. The document includes strategic recommendations and forecasts for the industry development until 2040.
Coordinated protests against Palantir took place in eight US cities, organized by nurses, patients, and activists. They demand that hospitals and authorities terminate contracts with Palantir due to concerns about surveillance, including its use by immigration services, and the company's growing presence in healthcare.
Digital Sector, having launched a practice of integrating AI components into custom web systems, is expanding it with corporate agentic scenarios. Details are not disclosed, but it implies the use of an agent-based approach in corporate AI solutions.
A new interdisciplinary paradigm, Dynamic Consent Engineering (DCE), is introduced, synthesizing Edward Bernays' principles of public relations with the S-E-E-D (Snowball, Equilibrium, Elasticity, Dominance) framework of system dynamics. The authors expand Bernaysian operational constraints into a four-dimensional resource matrix incorporating algorithmic media infrastructure and mathematically formalize how democratic institutions construct, optimize, and sustain political dominance.
The paper addresses the distributed optimal consensus control problem for constrained heterogeneous multi-agent systems within a model predictive control (MPC) framework. The approach optimizes both the control input sequence and the dynamically feasible consensus equilibrium simultaneously, resulting in a coupled optimization problem at each prediction step. A distributed primal-dual algorithm is developed, and locally verifiable conditions for its convergence are derived. Sufficient terminal conditions are established to guarantee recursive feasibility and asymptotic consensus of the closed-loop system.
The study focuses on federated learning for short-term load forecasting (STLF), addressing data privacy concerns. The authors identify structured heterogeneity in clients' load data: different responses to exogenous factors and distinct temporal load profiles, which degrade forecasting performance in federated learning. To mitigate these issues, they propose two model initialization strategies — global and local — that improve forecasting accuracy.
A method for channel modeling based on satellite imagery for 6G communication digital twins is proposed. The framework includes deterministic ray tracing, statistical processing, and RT augmentation, enabling channel models for large areas without detailed 3D maps.
A framework Spec2Twin-Chain for automated construction of blockchain digital twins is presented. The process is formulated as bi-level optimization where an LLM proposes and revises architectures based on specifications and behavioral data. Aimed at improving reuse and simplifying twin creation.
A hierarchical digital twin framework for a machine tool is presented, including real-time twins of the machine and the machining process. It integrates CNC data, voxel-based workpiece representation, vibration measurements, and a part repository for traceability and synthetic data generation.
A robot-assisted sliding palpation system uses a calibrated digital twin to generate labeled tactile sequences, reducing reliance on real-world data. The model of sensor-vessel contact is calibrated using Bayesian optimization against real palpation trajectories. A spatio-temporal graph neural network trained on simulated marker trajectories performs vessel classification and creates a localisation map.
The paper presents an approach to formal verification of digital twin (DT) qualities in systems-of-systems (SoS). The authors use a case study of a greenhouse SoS modeled in VDM-RT, with executable formal models and property-based account of DT qualities. Obstacles to composing these artifacts at the SoS level are analyzed.
COMSOL is advancing integration of multiphysics simulation with digital twin technologies. This enables more accurate and comprehensive models for industrial and engineering applications.
A trans-domain digital twin framework is proposed for closed cattle barns, integrating a climate simulator, livestock growth simulator, model predictive control, and lightweight reinforcement learning. It captures the mutual influence of microclimate and animal growth, enabling optimized conditions and energy use.
The DINIRS digital twin was developed and validated to estimate individualized treatment effects (mortality and ventilation duration) for patients with acute respiratory failure. It was trained on 23 baseline clinical variables from the first 24 ICU hours using the MIMIC-IV database (5,336 patients).
COMSOL participated in a forum on industrial AI and digital twins, demonstrating the use of multiphysics simulation for digital transformation in industry. The company emphasized the role of simulation in creating digital twins of manufacturing processes.
MathWorks announced a new workflow for creating digital twins for radar and satellite communications. The tool is intended for modeling and simulation of RF systems.
Hanwha Construction, together with E8, Seoul University, and the Korea Institute of Construction Technology, participates in a national project to develop and validate a digital twin-based building energy management simulator using BIM. The project aims to improve energy efficiency.
Palantir Technologies lost an $875 million contract with the US Federal Aviation Administration (FAA), but its commercial segment surged 93%, improving financial results. Business growth is outpacing expectations despite expensive shares.