Cybersecurity Applicability of Physical Resilience Design Features for Embedded Systems.
Abstract not provided.
Williams, R. A.↗
SEARCH · Engineering Papers
Results for “Embedded Systems”
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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Hardware-based Intrusion Detection for Critical Embedded Systems.
Abstract not provided.
Edwards, Nathan J↗
IoT2 ? A Benchmark for Microcontroller-Based Embedded Systems in the Internet of Things.
Abstract not provided.
Almakhdhub, Naif Saleh↗
SymPLe 1131: A novel architectural solution for the realization of verifiable digital I and C systems and embedded digital devices - 387
One of the main reasons for the increasing popularity of FPGAs in embedded systems and digital I and C systems is that they provide many of the advantages from both hardware and software components. FPGAs provide configurability approaching that of SW, while at the same time delivering deterministic behavior of pure hardware solutions. However, with regard to Software Common Cause Failures (CCF), the use of FPGAs in digital I and C platforms should not be seen as plug-in remedy for reduction or elimination of CCF. To address CCF, we argue that it is not enough to manage the complexity of an I and C device or system, but we must also have the ability to constrain complexity (as needed) and rigorously reason about execution and device functionality. This paper presents the work done regarding an FPGA overlay architecture called SymPLe. SymPLe is designed to reduce the gap between software and hardware approaches for digital I and C systems and increases deterministic behavior and verifiability of the application, architecture and safety-critical system while reasoning about CCF. (authors)
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
The First Tri-Lab Workshop on Formal Verification: Capabilities, Challenges, Research Opportunities, and Exemplars
The First Tri-Lab Workshop on Formal Verification was held in Santa Fe, New Mexico, on December 5th, 2023. This workshop gathered staff from Sandia, Los Alamos, and Lawrence Livermore National Laboratories and NASA’s Jet Propulsion Laboratory. This report summarizes and expands on the presentations given and discussion had at this workshop. In this report, we describe the current capabilities and research needs related to formal methods at the NNSA labs. In particular, we identify medium-term and long-term research gaps in programming languages, formalization efforts of complex systems, embedded systems verification, hardware verification, cybersecurity, formal methods usability, workflows, numerical methods, the use of formal methods for artificial intelligence (and its converse, artificial intelligence for formal methods), and collaboration opportunities and considerations on these topics. We conclude with a small number of exemplar research problems related to these topics.
97 MATHEMATICS AND COMPUTING↗
Embedding spatial decomposition in parareal in time power system simulation
We propose an approach for combining two decompositions in power system simulation, temporal and spatial, with a goal to achieve faster simulation time than utilizing either one of them alone. The proposed approach builds upon the structure of the Parareal algorithm for temporal decomposition and explores an efficient way of embedding the spatial decomposition into its coarse and fine solutions. This introduces two types of simultaneous parallelism in power system simulations - parallelism between system areas and between coarse integration intervals for time integration. The results from the application of the proposed approach are shown on a two-area system comprised of the IEEE 16-machine, 68-bus, and the IEEE 50-machine, 145-bus system.
Duan, Nan↗
Linear embedding of nonlinear dynamical systems and prospects for efficient quantum algorithms
The simulation of large nonlinear dynamical systems, including systems generated by discretization of hyperbolic partial differential equations, can be computationally demanding. Such systems are important in both fluid and kinetic computational plasma physics. This motivates exploring whether a future error-corrected quantum computer could perform these simulations more efficiently than any classical computer. In this work, we describe a method for mapping any finite nonlinear dynamical system to an infinite linear dynamical system (embedding) and detail three specific cases of this method that correspond to previously studied mappings. Then we explore an approach for approximating the resulting infinite linear system with finite linear systems (truncation). Using a number of qubits only logarithmic in the number of variables of the nonlinear system, a quantum computer could simulate truncated systems to approximate output quantities if the nonlinearity is sufficiently weak. Other aspects of the computational efficiency of the three detailed embedding strategies are also discussed.
97 MATHEMATICS AND COMPUTING↗
Test and Evaluation of Systems with Embedded Machine Learning Components
As Machine Learning (ML) continues to advance, it is being integrated into more systems. Often, the ML component represents a significant portion of the system that reduces the burden on the end user or significantly improves task performance. However, the ML component represents an unknown complex phenomenon that is learned from collected data without the need to be explicitly programmed. Despite the improvement in task performance, the models are often black boxes. Evaluating the credibility and the vulnerabilities of ML models poses a gap in current test and evaluation practice. For high consequence applications, the lack of testing and evaluation procedures represents a significant source of uncertainty and risk. To help reduce that risk, here we present considerations to evaluate systems embedded with an ML component within a red-teaming inspired methodology. We focus on (1) cyber vulnerabilities to an ML model, (2) evaluating performance gaps, and (3) adversarial ML vulnerabilities.
97 MATHEMATICS AND COMPUTING↗
Dynamic Capabilities of an Energy Storage-Embedded DFIG System
Power electronic-based wind turbine generators (WTGs) are capable of providing inertial response to the grid by releasing kinetic energy from the turbine blade; thus, as conventional power plants are retired, the reduction of online inertia can be compensated by designing frequency controls for the WTGs. Deployment of energy storage technology for renewable generations has been increased to have the renewables centralized with a system operator as an independent power supply by making up for their nature of generation. In addition, the cost of energy storage has dropped over time and global research activities on energy storage have been funded by private industries and governments. This paper investigates the opportunity of deploying an energy storage on a doubly fed induction generator (DFIG)-based WTG to respond to the system frequency, and then explores dynamic capabilities of the energy storage-embedded DFIG to boost its contribution while the frequency response is being provided by the power system's online inertia; thus, enabling an effective delivery of ancillary services to the system. To do this, the dynamic models of DFIG and energy storage are combined and simulated under the different operating conditions of a DFIG, such as subsynchronous, synchronous, and supersynchronous operations, using the PSCAD.
24 POWER TRANSMISSION AND DISTRIBUTION↗