![]() The feasibility of these models and of the proposed platform to achieve the desired part properties will be demonstrated on a unique fully-instrumented open-architecture networked machine: Directed Energy Deposition (one form of additive manufacturing). The part geometry (from CAD), analysis meshes and part properties will all be saved through an innovative volumetric representation providing a common data structure, optimized for performance on Graphical Processing Units (GPUs). The StudentVUE Mobile app works with the Synergy information system in much the same way as the StudentVUE web portal, allowing students to stay on top of: Upcoming school events Classroom information Assignments Scores and grades Attendance and more Note: Chesapeake Public Schools does not provide support for personal devices. This research targets the formulation of a new processing platform in which part geometry, process parameters, numerical process simulation, and predicted mechanical behavior all interact via a common data structure for process control and certification. In spite of their flexibility, the functional properties and performance of the produced parts is difficult to predict. At the forefront of this innovation are processes in which geometrically and structurally complex parts based on digital models (CAD) can be produced. The landscape of manufacturing is gradually becoming predominantly digital due to the emergence of Cyber Physical Systems. The envisioned cyber-physical engineering platform will allow users to quickly determine the process parameters needed to yield the desired part attributes in a given process or process chain. Login Credentials Chesapeake Public Schools Document Self-Service Login Username: Password: Credentials are case sensitive Use your 09 employee number as your Username. This platform will be powered by next-generation cyber-physical infrastructure to control desired part characteristics in terms of attributes/properties such as microstructure, porosity, residual stresses, and geometric and surface features. CPS GROUP is a global industrial conglomerate that originated in Italy from the synergy of well-established brands operating in the iron and steel business. This research will establish the scientific and technological foundation for a futuristic manufacturing platform in a distributed network that seamlessly and efficiently integrates physical processes and numerical simulations in a fast predictive framework. ![]() ![]() Privacy in Cyber-Physical SystemsĬPS: Medium: Collaborative Research: Building Information, Inhabitant, Interaction and Intelligent Integrated Modeling (BI5M)ĬPS: Medium: LEAR-CPS: Low-Energy computing for Autonomous mobile Robotic CPS via Co-Design of Algorithms and Integrated CircuitsĬPS:Small: Syntax-Guided Synthesis for Cyber-Physical SystemsĬPS: Medium: Collaborative Research: Augmented reality for control of reservation-based intersections with mixed flowsĬPS: TTP Option: Medium: Collaborative Research: Trusted CPS from Untrusted ComponentsĬPS: Medium: Resilient-by-Cognition Cyber-Physical SystemsĬPS: Medium: Collaborative Research: Human-on-the-Loop Control for Smart Ultrasound ImagingĬPS: Medium: Collaborative Research: Security vs.NSF CPS: Synergy: An Integrated Simulation and Process Control Platform for Distributed Manufacturing Process Chains ![]() CAREER: Towards Reliable and Optimized Data-Driven Cyber-Physical Systems using Human-Centric SensingĬAREER: High-Assurance Design of Learning-Enabled Cyber-Physical Systems with Deep ContractsĬAREER: Multi-Agent Decision Making and Optimization using Communication as a SensorĬAREER: Decision Procedures for High-Assurance, AI-Controlled, Cyber-Physical SystemsĬAREER: Robustifying Machine Learning for Cyber-Physical SystemsĬPS: Small: Collaborative Research: Models and System-Level Coordination Algorithms for Power-in-the-Loop Autonomous Mobility-on-Demand SystemsĬPS: Small: Behaviorally Compatible, Energy Efficient, and Network-Aware Vehicle Platooning Using Connected Vehicle TechnologyĬPS: Small: Mechanical Vibration Based Prognostic Monitoring of Machinery Health with Sub-millisecond Accuracy Using Backscatter SignalsĬPS: Medium: Collaborative Research: Security vs.
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