Cyber-Physical System Test Bed Data Sources, Communications and Controls Formulation
This is a report that provides the test bed design for the DOE-SETO SolarSTARTS project as a milestone.
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Microcontroller-based aerosol jet printer control software
This software is used with a microcontroller to control an aerosol jet printing system. It was written for a 32-bit ARM microcontroller, providing greater processing speed and complexity relative to more conventional low-cost printer controllers. The microcontroller software was written using a real-time operating system (FreeRTOS), which simplifies parallel operation of multiple functions and further customization. It supports simultaneous motion planning, pulse generation for stepper motors, reading encoder feedback, communicating with multiple mass flow controllers, controlling solid state relays, handling a software-based emergency stop, and sending data to the client PC. The program is written in C and communicates with the client PC via USB connection. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-0436 O
Secor, EthanBenjamin↗
The Role of the Digital Thread for Security, Resilience, and Adaptability in Manufacturing
The manufacturing sector is dramatically evolving with recent technical and digital advances. Among these, the digital thread is revolutionizing manufacturing operations well beyond the historic downloading of programs to computer numerically controlled (CNC) machine tools and the uploading of edited programs from CNC controllers. The digital thread is “the communication framework that enables a connected data flow and integrated view of the asset’s data throughout its lifecycle across traditionally siloed functional perspectives” (Leiva 2016). It is pervasive around the world and has changed the way society operates; for example, map apps are used to provide time-optimal directions to destinations using real-time traffic feedback. The digital thread makes it possible to digitally verify products, ensure that the latest technologies are deployed across the entire manufacturing ecosystem, and strengthen the workforce by making each individual more efficient and effective. These three foundational advanced manufacturing concepts will ensure a next-generation secure, resilient, and adaptable manufacturing ecosystem and sustainably support current and future needs of society (Lynn et al. 2020).
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Communication device for implementing selective encryption in a software defined network
The present disclosure pertains to systems and methods for selectively encrypting data flows within a software defined network (SDN). In one embodiment, a communication device may be configured to receive a plurality of unencrypted data packets. The communication device may receive from an SDN controller a criterion used to identify at least one of the unencrypted data flows to be encrypted. Based on the criterion, an encryption subsystem may generate an encrypted data flow the unencrypted data packets based on an encryption key. In some embodiments, the encryption system may parse the packets and encrypt the data payloads without encrypting the routing information associated with the packet. In other embodiments, the encryption subsystem may be configured to encapsulate and encrypt the entire unencrypted data packet. In some embodiments, the encryption subsystem may further be configured to authenticate a sending device and/or to verify the integrity of a message.
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Redis-Based Streaming Architecture for Accelerator Beam Instrumentation DAQ Systems
The Fermilab Acceleraor Division, Beam Instrumentation Department, is always adopting modern and current software methodologies for complex DAQ architectures. This paper highlights the Redis Adapter (RA) as the key software component enabling high performance, modular communication between digitizers and distributed control systems by leveraging Redis and containerization. The RA provides a unified, efficient interface between Redis based data streams and consumer systems. In the legacy architecture, digitized data flowed through the custom, UDP based Distributed Data Communication Protocol in the middle layer. In the current system, DDCP remains the ingestion path, while the RA serves as the decoupling layer. The proposed system replaces old VME digitizers with a SOM-based digitizer that communicates with Redis using the RA. The RA acts as both a performance-critical bridge and a protocol-agnostic adapter, ensuring compatibility with legacy control frameworks while enabling future scalability and modularity. This restructuring of the middle layer also helps the system achieve high throughput, reduce latency, and simplify the data path. Finally, we will demonstrate how RA is utilized in our two core products to deliver both legacy compatibility and future flexibility.
Joshi, S. [Fermilab]↗
A Typing Discipline for High-Assurance Control Systems
This poster describes a typing discipline for high-assurance industrial systems based on three novel type systems. The first type system, information flow control (IFC), controls the flow of data through the system. The second system, dependent session types, restricts messages exchanged during the execution of a communication protocol to avoid dangerous states. The third system uses dimensional analysis to avoid subtle bugs that adversaries can exploit to cause the system to enter a dangerous state. This poster describes how a combination of these approaches can prevent sophisticated cyber attacks, such as the infamous Stuxnet incident, from occurring. In addition, we provide experimental evidence to support the claim that these approaches can be applied in control systems that are resource-constrained.
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SmartFuse: Reconfigurable Smart Switches to Accelerate Fused Collectives in HPC Applications
Communication switches have sometimes been augmented to process collectives (e.g., the IBM BlueGene project and the Mellanox SHArP switch). In this work, we find that there is a great acceleration opportunity through the further augmentation of switches to accelerate more complex functions that combine communication with computation. We consider three types of such functions. The first is fully-fused collectives built by fusing multiple existing collectives like Allreduce with Alltoall. The second is semi-fused collectives built by combining a collective with another computation. The third we refer to as higher-order collectives built by combining multiple computations and communications, such as to perform matrix-matrix multiply (PGEMM). In this work, we propose a framework called SmartFuse to accelerate fused collective functions. The core of SmartFuse is a reconfigurable smart switch to support these operations. The semi/fully fused collectives are implemented with a CGRAlike architecture, while higher-order collectives are implemented with a more specialized computational unit that can also schedule communication. Supporting our framework is software to evaluate and translate relevant parts of the input program, compile them into a control data flow graph, and then map this graph to the switch hardware. The proposed framework, once deployed, has the strong potential to accelerate existing HPC applications transparently by encapsulation within an MPI implementation. Experimental results show that this approach improves the performance of the PGEMM kernel, MINIFE, and AMG by, on average, 94%, 15%, and 13%, respectively.
Haghi, Pouya↗
Deep Cyber-Physical Situational Awareness for Energy Systems: A Secure Foundation for Next-Generation Energy Management
This document provides the final report for the CYPRES project. The purpose is (1) to highlight and summarize its major accomplishments and (2) to provide guidance on how its outcomes have informed and can inform important additional research and technology transfer. The goal of CYPRES was the research, development, and demonstration of a security-oriented next generation cyber-physical EMS for electric power systems that detects malicious and abnormal events through the fusion of cyber and physical data. To achieve this, the CYPRES project team researched, developed, and built a prototype of the solution, referred to as the CYPRES EMS. The CYPRES EMS is a proof-of-concept cyber-physical platform that demonstrates the management of the energy system, communications, security, and cyber-physical grid modeling and analytics. As part of the capabilities of the CYPRES EMS, the team designed and developed a suite of power system applications for monitoring, risk analyses, detection, and control that are inherently cyberaware. At its core, the project aimed to research, develop, and demonstrate a security-oriented next-generation cyber-physical Energy Management System (EMS) capable of detecting malicious and abnormal events through the innovative fusion of cyber and physical data. This approach represents a fundamental shift from traditional EMS, reimagining how critical infrastructure can be protected through unified cyber-aware and physics-aware secure data flow pipelines. The project’s cornerstone deliverable, the CYPRES EMS, serves as a proof-of-concept cyber-physical platform that revolutionizes the management of energy systems, communications, security, and cyber-physical grid modeling and analytics. This prototype implements a comprehensive suite of power system applications for monitoring, risk analyses, detection, and control, all designed with inherent cyber awareness. The system’s architecture extends from end-devices in the field through to control center applications, establishing a secure and resilient control framework that addresses the challenges posed by diverse devices of unknown trustworthiness connecting to modern power systems. Through this innovative approach to deep cyber-physical situational awareness, the CYPRES project not only advances the state-of-the-art in energy infrastructure protection but also establishes a new paradigm for how EMS can be designed, deployed, and operated in an increasingly complex threat landscape. The findings and developments from this project provide crucial insights for stakeholders across the energy sector, offering a blueprint for enhancing the reliability and resilience of our nation’s critical energy infrastructure in the face of evolving cyber threats.
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Implementation Aspects of Smart Grids Cyber-Security Cross-Layered Framework for Critical Infrastructure Operation
Communication networks in power systems are a major part of the smart grid paradigm. It enables and facilitates the automation of power grid operation as well as self-healing in contingencies. Such dependencies on communication networks, though, create a roam for cyber-threats. An adversary can launch an attack on the communication network, which in turn reflects on power grid operation. Attacks could be in the form of false data injection into system measurements, flooding the communication channels with unnecessary data, or intercepting messages. Using machine learning-based processing on data gathered from communication networks and the power grid is a promising solution for detecting cyber threats. In this paper, a co-simulation of cyber-security for cross-layer strategy is presented. The advantage of such a framework is the augmentation of valuable data that enhances the detection as well as identification of anomalies in the operation of the power grid. The framework is implemented on the IEEE 118-bus system. The system is constructed in Mininet to simulate a communication network and obtain data for analysis. A distributed three controller software-defined networking (SDN) framework is proposed that utilizes the Open Network Operating System (ONOS) cluster. According to the findings of our suggested architecture, it outperforms a single SDN controller framework by a factor of more than ten times the throughput. This provides for a higher flow of data throughout the network while decreasing congestion caused by a single controller’s processing restrictions. Furthermore, our CECD-AS approach outperforms state-of-the-art physics and machine learning-based techniques in terms of attack classification. The performance of the framework is investigated under various types of communication attacks.
cross-layered↗
Wave Tank Testing Report for Controls Validation of a Heaving Point Absorber
The core objectives of this project is to improve the power capture of three different wave energy conversion (WEC) devices by more than 50% using an advanced control system and validate the attained improvements using wave tank and full scale testing. In parallel, we will bring along the development of a wave prediction system that is required to enable effective control and test it at full scale. The purposes of this report are to: 1. Plan and document the 1/25th scale device testing at the wave-tank facility; 2. Document the test article, setup and methodology, sensor and instrumentation, mooring, electronics, wiring, and data flow and quality assurance; 3. Communicate the testing results between the associated members; 4. Facilitate reviews that will help to ensure all aspects (risk, safety, testing procedures, etc.); 5. Provide a systematic guide to setting up, executing and decommissioning the experiment.
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My vehicle is a data mine
In this talk we explore how analysis of vehicle data provides information of individual vehicle behaviors, information of other vehicles in the flow of traffic, and insights into the behavior of drivers. Over the last two decades traditional passenger vehicles have been transformed from integrated two-port electrical nodes to cyber-physical systems of communicating computational nodes whose individual state and control variables are shared on a standard controller area network (CAN) bus. As driver assistance systems have crept into vehicles as safety features, driver behaviors can be observed through analysis of the data streams on the CAN bus as these new nodes communicate with one another. The properties of these data streams, as well as architectures and approaches to gather the data, are important to consider when drawing conclusions on the relevance of the data in making decisions at varying levels of the information hierarchy. We will demonstrate several technical challenges associated with these data collection processes, as well as preliminary results that demonstrate application relevance of the data to behavior, traffic, and systems domains.
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Scalable, Physical Effects Measureable Microgridfor Cyber Resilience Analysis
SPEMMCRA provides a low-cost simulated method to provide for testing of control theory and cybersecurity approaches to microgrid implementations. Specifically, this physics-based approach provides realistic responses to compare control strategies in simulation, but also to demonstrate actions that can or cannot be taken in taking cybersecurity actions . As communications interfaces or other actions are taken that affect the flow of data, SPEMMCRA can show whether the microgrid operation is adversely affected by what is intended to mitigate a cybersecurity event.
Rieger, CraigG↗
A Data-Driven Algorithm for Enabling Delay Tolerance in Resilient Microgrid Controls Using Dynamic Mode Decomposition
The increased implementation of smart grid technologies in the power distribution grid presents unique opportunities that enable resiliency, but also brings challenges motivating needs for novel solutions and mitigation techniques. The bi-directional power and data flow allow for the grid to operate with increased resiliency, which is the ability to avoid discontinuity of service to end-use loads during extreme events. However, in applications where control of the distribution grid or microgrid relies on communication networks, the degradation of communication systems in the form of loss or high latency can cause maloperation and result in loss of end-use loads. Here this paper presents a novel framework to enable delay tolerance of centralized microgrid control schemes to mitigate communication system latency impacts and guarantee successful control action. We demonstrate the delay tolerance on a control scheme that operates a battery energy storage system (BESS) to offset the sudden loss of generation and maintain system frequency. During periods of severely degraded communication system performance, the proposed delay-tolerant algorithm compensates for the latency by utilizing a data-driven model generated at the device level using dynamic mode decomposition (DMD) to determine the performance of the communications. The DMD technique predicts the system’s frequency using device-level terminal measurements and provides updated control signals. The HELICS cosimulation platform evaluates the cyber-physical interaction of the power system model in GridLAB-D, the centralized control agent in Python, and the discrete network model in NS-3. The framework is tested and validated on the IEEE-123 node system modified to represent a networked remote microgrid model, and the results show an improvement in the dynamic performance
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Advanced Reactor Control and Operations (ARCO): A University Research Facility for Developing Optimized Digital Control Rooms
The Advanced Reactor Control and Operations (ARCO) facility was constructed in January 2018 to serve as a test bed for advanced reactor control rooms and operator support systems. Since then, it has supported human-machine interface user experience research, fault detection and mitigation technology development, control room concept of operations development, and remote operations research. ARCO serves as the control room for the Compact Integral Effects Test (CIET) facility, which replicates the primary-side flow paths and thermal-hydraulic behavior of a fluoride-salt-cooled high-temperature reactor (FHR) using simulant fluids and scaling principles. New reactor designs feature different operating conditions and scenarios than those in existing reactors. ARCO supports the research and development of digital tools for operator communications, intuitive real-time data analysis, online health monitoring and prognostics, and control room cybersecurity. By integrating these different technologies, ARCO acts as a prototypical control system to iteratively develop methods and tools of operation in advanced small modular nuclear reactors. This paper describes the features of and challenges to operating advanced small modular reactors underlying the design basis for ARCO and its operator support systems.
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Adaptive Reinforcement Learning (ARL) Control of a Multi-port Resonant Converter in UAV Systems
This study presents an adaptive reinforcement learning (ARL) control framework for a multi-port resonant converter used in hybrid unmanned aerial vehicle (UAV) power systems. The converter integrates high-frequency half-bridge input ports connected to a rectified engine–generator set and a battery energy storage system, along with a semi-bridgeless active rectifier supplying the propulsion load. A deep RL agent is trained to dynamically regulate inter-port phase-shift commands in real time based on flight conditions and load power demand. The ARL controller autonomously identifies phase-shift combinations that maximize conversion efficiency while maintaining stable and coordinated power flow, even under rapidly varying operating scenarios. This data-driven approach eliminates the need for explicit system modeling or extensive manual tuning and enables coordinated control among multiple power ports without inter-port communication. Experimental results validate that the ARL based strategy achieves reliable power sharing and consistently high-efficiency operation across diverse UAV operating conditions.
Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
Distributed ADMM Using Private Blockchain for Power Flow Optimization in Distribution Network With Coupled and Mixed-Integer Constraints
The optimization problem for scheduling distributed energy resources (DERs) and battery energy storage systems (BESS) integrated with the power grid is important to minimize energy consumption from conventional sources in response to demand. Conventionally this optimization problem is solved in a centralized manner, limiting the size of the problem that can be solved and creating a high communication overhead because all the data is transferred to the central controller. These limitations are addressed by the proposed distributed consensus-based alternating direction method of multiplier (DC-ADMM) optimization algorithm, which decomposes the optimization problem into subproblems with private cost function and constraints. The distribution feeder is partitioned into low coupling subnetworks/regions, which solves the private subproblem locally and exchanges information with the neighboring regions to reach consensus. The relaxation strategy is employed for mixed-integer and coupled constraints introduced in the optimal power flow (OPF) problem by stationary and transportable BESS because DC-ADMM convergence is only guaranteed for strict convex problems. The information exchange and synchronization between subnetworks/regions are vital for distributed optimization. In this work, both of these aspects are addressed by the blockchain. The smart contract deployed on the blockchain network acts as a mediator for secure data exchange and synchronization in distributed computation. The blockchain-based distributed optimization problem’s effectiveness is tested for a 0.5-MW laboratory microgrid for one hour ahead and day-ahead for the IEEE 123-bus and EPRI J1 test feeders, and results are compared with a centralized solution.
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Cyber-Power Co-Simulation for End-to-End Synchrophasor Network Analysis and Applications
The resiliency, reliability and security of the next generation cyber-power smart grid depend upon efficiently leveraging advanced communication and computing technologies. Also, developing real-time data-driven applications is critical to enable wide-area monitoring and control of the cyber-power grid given high-resolution data from Phasor Measurement Units (PMUs). North American Synchrophasor Initiative Network (NASPlnet) provides guidance for PMU data exchanges. With the advancement in networking and grid operation, it is necessary to evaluate the performance of different data flow architectures suggested by NASPInet and analyze the impact on applications. Therefore, we need a cyber-power co-simulation framework that supports very large-scale co-simulation capable of running in parallel, high-performance computing platforms and capturing real-life network behavior. This work presents an end-to-end automated and user-driven cyber-power co-simulation using NS3 to model communication networks, GridPACK to model the power grid, and HELICS as a co-simulation engine. Comparative analysis of latency in synchrophasor networks and a performance evaluation of a power system stabilizer application utilizing PMU data in an IEEE 39 bus test system is presented using this cosimulation testbed.
Mustafa, Hussain M.↗
Concept of Operations of Next-Generation Traffic Control Utilizing Infrastructure-Based Cooperative Perception
This paper provides a system architecture for an infrastructure-based cooperative perception fusion engine for next-generation traffic control. This engine will provide a complete state-space digital representation with measurable accuracy to support a wide-range of applications. The architecture includes inputs, functional flow, data standardization recommendations, outputs, and supported applications. The cooperative perception engine addresses critical needs with respect to accelerating the benefits of automation through intelligent roadway infrastructure, which complements and accelerates connected and automated vehicle (CAV) technology. The cooperative perception acquires and fuses information from sensors (radar, LiDAR, and cameras) and CAVs to perceive roadway traffic states of moving objects, creates a complete 3D digital representation of that state-space, and communicates it to downstream application such as intelligent signal control, safety and energy applications, and cooperate driving applications. The intelligent roadway infrastructure approach, as opposed to a vehicle-centric approach, is more scalable because it can be deployed to the roughly 300,000 signalized intersections more readily than over 300 million vehicles in the United States, and accrues early-stage benefits equitable to all roadway users addressing safety, equity, fuel efficiency, and greenhouse gas reduction.
ADVANCED PROPULSION SYSTEMS↗