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DOE OSTI2019

Cybersecurity Assessments on Emulated DER Communication Networks

An increasing number of public utility commissions are adopting Distributed Energy Resource (DER) interconnection standards which require photovoltaic (PV) inverters, energy storage systems, and other DER to include interoperable grid-support functionality. The recently updated national standard, IEEE 1547-2018, requires all DER to include a Sun Spec Modbus, IEEE 2030.5, or IEEE 1815 communication interface in order to provide local and bulk power system services. Those communication protocols and associated information models will ensure system interoperability for PV and storage systems, but these new utility-to-DER communication networks must be deployed with sufficient cybersecurity to protect the U.S. power system and other critical infrastructure reliant on dependable power. Unlike bulk generators, DER are commonly connected to grid operators via public internet channels. These DER networks are exposed to a large attack surface that may leverage sophisticated techniques and infrastructure developed on IT systems, including remote exploits and distributed attacks. Although DER make up a growing portion of the national generation mix, they have limited processing capabilities and do not typically support modern security features such as encryption or authentication. In this work, Sandia National Laboratories constructed simulated DER communication net- works with a range of security features in order to study the security posture of different communication approaches. The experimental test environment was created in a Sandia-developed co-simulation platform, called SCEPTRE, which emulated Sun Spec-compliant DER equipment, the utility DER management system, communication network, and distribution power system. Adversary-based assessments were conducted and a quantitative scoring criteria was applied to evaluate the resilience of various architectures against cyber attacks and to measure the systemic impact during such attacks. The team found that network segmentation, encryption, and moving target defense improved the security of these networks and would be recommended for utility, aggregator, and local DER networks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1990

Two Axis Pointing System (TAPS) attitude acquisition, determination, and control

The Two Axis Pointing System (TAPS) is a 2 axis gimbal system designed to provide fine pointing of Space Transportation System (STS) borne instruments. It features center-of-mass instrument mounting and will accommodate instruments of up to 1134 kg (2500 pounds) which fit within a 1.0 by 1.0 by 4.2 meter (40 by 40 by 166 inch) envelope. The TAPS system is controlled by a microcomputer based Control Electronics Assembly (CEA), a Power Distribution Unit (PDU), and a Servo Control Unit (SCU). A DRIRU-II inertial reference unit is used to provide incremental angles for attitude propagation. A Ball Brothers STRAP star tracker is used for attitude acquisition and update. The theory of the TAPS attitude determination and error computation for the Broad Band X-ray Telescope (BBXRT) are described. The attitude acquisition is based upon a 2 star geometric solution. The acquisition theory and quaternion algebra are presented. The attitude control combines classical position, integral and derivative (PID) control with techniques to compensate for coulomb friction (bias torque) and the cable harness crossing the gimbals (spring torque). Also presented is a technique for an adaptive bias torque compensation which adjusts to an ever changing frictional torque environment. The control stability margins are detailed, with the predicted pointing performance, based upon simulation studies. The TAPS user interface, which provides high level operations commands to facilitate science observations, is outlined.

Azzolini, John D.↗

NASA NTRS1996

A Comparison of Single-Cycle Versus Multiple-Cycle Proof Testing Strategies

Single-cycle and multiple-cycle proof testing (SCPT and MCPT) strategies for reusable aerospace propulsion system components are critically evaluated and compared from a rigorous elastic-plastic fracture mechanics perspective. Earlier MCPT studies are briefly reviewed. New J-integral estimation methods for semi-elliptical surface cracks and cracks at notches are derived and validated. Engineering methods are developed to characterize crack growth rates during elastic-plastic fatigue crack growth (FCG) and the tear-fatigue interaction near instability. Surface crack growth experiments are conducted with Inconel 718 to characterize tearing resistance, FCG under small-scale yielding and elastic-plastic conditions, and crack growth during simulated MCPT. Fractography and acoustic emission studies provide additional insight. The relative merits of SCPT and MCPT are directly compared using a probabilistic analysis linked with an elastic-plastic crack growth computer code. The conditional probability of failure in service is computed for a population of components that have survived a previous proof test, based on an assumed distribution of initial crack depths. Parameter studies investigate the influence of proof factor, tearing resistance, crack shape, initial crack depth distribution, and notches on the MCPT vs. SCPT comparison. The parameter studies provide a rational basis to formulate conclusions about the relative advantages and disadvantages of SCPT and MCPT. Practical engineering guidelines are proposed to help select the optimum proof test protocol in a given application.

McClung, R. C.↗

NASA NTRS1996

A Comparison of Single-Cycle Versus Multiple-Cycle Proof Testing Strategies

McClung, R. C.↗

NASA NTRS1979

Simulation of three-dimensional compressible viscous flow on the Illiac IV computer

Complicated three-dimensional viscous transonic flows about bodies at high angles of attack are solved on the Illiac IV computer. It is shown that certain approximate forms of the compressible Reynolds-averaged Navier-Stokes equations can be computed about realistic three-dimensional geometries with relative ease on the Illiac IV. The ease and efficiency with which this can be done depend on the approximations made in the basic equations, the choice of the numerical algorithm used for the solution, and the data-base system that controls the data management and identifies and manipulates the vectors. A pencil data-base system is found to be particularly suitable for the approximations and numerical method chosen to produce the results presented. In addition, some comparisons are made of computer predictions with experimental results for various lows about hemisphere-cylinders in both subsonic and supersonic free streams. The same viscous model and numerical model are used, showing good qualitative agreement in the location of separation lines and pressure distributions.

Pulliam, T. H.↗

DOE OSTI2026

Parametric reduced order models for graded lattice structures

Graded lattice structures, characterized by smoothly varying mechanical properties, hold significant promise for optimizing material distribution in advanced engineering applications. However, accurately modeling these structures poses substantial computational challenges due to the continuous geometric variations within their unit cells. Here, to address these challenges, this paper introduces a novel Efficient Reduced Order Model (EROM) that integrates the Matrix Discrete Empirical Interpolation Method (MDEIM) and Discrete Empirical Interpolation Method (DEIM) with polynomial regression to efficiently manage geometric parametrization in lattice structures. Unlike traditional reduced order models (ROMs) that require extensive precomputed libraries for each geometric configuration, our approach enables continuous geometric variations through a flexible algebraic formulation, significantly reducing computational costs while preserving high accuracy. The method constructs projection matrices for individual unit cells that can be efficiently assembled into global systems, leveraging the repetitive nature of lattice structures. Numerical studies demonstrate that our EROM achieves displacement errors below 1% and von Mises stress prediction errors below 4%, coupled with computational speedups exceeding two orders of magnitude compared to full-order simulations. The proposed method's modularity and scalability make it particularly suitable for design optimization and real-time simulation of functionally graded lattice structures, with applications spanning aerospace to biomedical engineering.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

Efficient Modeling of HIL Multi-Grid System for Scalability & Concurrency in CPS Security Testbed

Cyber-event-triggered power grid blackout compels utility operators to intensify cyber-aware and physics-constrained recovery and restoration process. Recently, coordinated cyber attacks on the Ukrainian grid witnessed such a cyber-event-triggered power system blackout. Various cyber-physical system (CPS) testbeds have attempted with multitude designs to analyze such interdependent events and evaluate remedy measures. However, resource constraints and modular integration designs have been significant barriers while modeling large-scale grid models (scalability) and multi-grid isolated models (concurrency) under a single real-time execution environment for the hardware-in-the-loop (HIL) CPS security testbeds. This paper proposes a meticulous design and effective modeling for simulating large-scale grid models and multi-grid isolated models in a HIL realtime digital simulator environment integrated with industry-grade hardware and software systems. We have used our existing HIL CPS security testbed to demonstrate scalability by the realtime performance of a Texas-2000 bus US synthetic grid model and concurrency by the real-time performance of simultaneous ten IEEE-39 bus grid models and an IEEE-118 bus grid model. The experiments demonstrated significant results by 100% realtime performance with zero overruns, low latency while receiving and executing control signals from SEL Relays via IEC-61850 protocol and low latency while computing and transmitting grid data streams including stability measures via IEEE C37.118 synchrophasor data protocol to SEL Phasor Data Concentrators.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Variational quantum eigensolver with reduced circuit complexity

Abstract The variational quantum eigensolver (VQE) is one of the most promising algorithms to find eigenstates of a given Hamiltonian on noisy intermediate-scale quantum devices (NISQ). The practical realization is limited by the complexity of quantum circuits. Here we present an approach to reduce quantum circuit complexity in VQE for electronic structure calculations. Our ClusterVQE algorithm splits the initial qubit space into clusters which are further distributed on individual (shallower) quantum circuits. The clusters are obtained based on mutual information reflecting maximal entanglement between qubits, whereas inter-cluster correlation is taken into account via a new “dressed” Hamiltonian. ClusterVQE therefore allows exact simulation of the problem by using fewer qubits and shallower circuit depth at the cost of additional classical resources, making it a potential leader for quantum chemistry simulations on NISQ devices. Proof-of-principle demonstrations are presented for several molecular systems based on quantum simulators as well as IBM quantum devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Demystifying Cyberattacks: Potential for Securing Energy Systems With Explainable AI : Preprint

Modernization of energy systems has led to in- creased interactions among multiple critical infrastructures and diverse stakeholders making the challenge of operational decision making more complex and at times beyond cognitive capabilities of human operators. The state-of-the-art machine learning and deep learning approaches show promise of supporting users with complex decision-making challenges, such as those occurring in our rapidly transforming cyber-physical energy systems. However, successful adoption of data-driven decision support technology for critical infrastructure will be dependent on the ability of these technologies to be trustworthy and contextually interpretable. In this paper, we investigate the feasibility of implementing XAI for interpretable detection of cyberattacks in the energy system. Leveraging a proof-of-concept simulation use case of detection of a data falsification attack on a photovoltaic system using XGBoost algorithm, we demonstrate how Local Interpretable Model-Agnostic Explanations (LIME), a flavor XAI approach, can help provide contextual and actionable interpretation of cyberattack detection.

artificial intelligence↗

DOE OSTI2020

Assessment of wind power scenario creation methods for stochastic power systems operations

Probabilistic scenarios of renewable energy production, such as wind, have been gaining popularity for use in stochastic variants of power systems operations scheduling problems, allowing for optimal decision-making under uncertainty. The quality of the scenarios has a direct impact on the value of the resulting decisions, but until now, methods for creating scenarios have not been compared under realistic operational conditions. Here, we compare the quality of scenario sets created using three different methods, based on a simulated re-enactment of stochastic day-ahead unit commitment and subsequent dispatch for a realistic test system. We create scenarios using a dataset of forecasted and actual wind power values, scaled to evaluate the effects of increasing wind penetration levels. We show that the choice of scenario set can significantly impact system operating cost, renewable energy use, and the ability of the system to meet demand. This result has implications for the ability of system operators to efficiently integrate renewable production into their day-ahead planning, highlighting the need for the use of performance-based assessments for scenario evaluation.

17 WIND ENERGY↗

DOE OSTI2024

Integrated photonic structures for photon-mediated entanglement of trapped ions

Trapped atomic ions are natural candidates for quantum information processing and have the potential to realize or improve quantum computing, sensing, and networking. These applications often require the collection of individual photons emitted from ions into guided optical modes, in some cases for the production of entanglement between separated ions. Proof-of-principle demonstrations of such photon collection from trapped ions have been performed using high-numerical-aperture lenses or cavities and single-mode fibers, but integrated photonic elements in ion-trap structures offer advantages in scalability and manufacturability over traditional optics. In this paper we analyze structures monolithically fabricated with an ion trap for collecting ion-emitted photons, coupling them into waveguides, and manipulating them via interference. We calculate geometric limitations on collection efficiency for this scheme, simulate a single-layer grating that shows performance comparable to demonstrated free-space optics, and discuss practical fabrication and fidelity considerations. Based on this analysis, we conclude that integrated photonics can support scalable systems of trapped ions that can distribute quantum information via photon-mediated entanglement.

Knollmann, Felix W.↗

DOE OSTI2022

Quantum Markov chain Monte Carlo with digital dissipative dynamics on quantum computers

Modeling the dynamics of a quantum system connected to the environment is critical for advancing our understanding of complex quantum processes, as most quantum processes in nature are affected by an environment. Modeling a macroscopic environment on a quantum simulator may be achieved by coupling independent ancilla qubits that facilitate energy exchange in an appropriate manner with the system and mimic an environment. This approach requires a large, and possibly exponential number of ancillary degrees of freedom which is impractical. In contrast, we develop a digital quantum algorithm that simulates interaction with an environment using a small number of ancilla qubits. By combining periodic modulation of the ancilla energies, or spectral combing, with periodic reset operations, we are able to mimic interaction with a large environment and generate thermal states of interacting many-body systems. We evaluate the algorithm by simulating preparation of thermal states of the transverse Ising model. Our algorithm can also be viewed as a quantum Markov chain Monte Carlo process that allows sampling of the Gibbs distribution of a multivariate model. To illustrate this we evaluate the accuracy of sampling Gibbs distributions of simple probabilistic graphical models using the algorithm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Water Network Tool for Resilience (WNTR). User Manual, Version 0.2.3

The Water Network Tool for Resilience (WNTR, pronounced winter) is a Python package designed to simulate and analyze resilience of water distribution networks. Here, a network refers to the collection of pipes, pumps, valves, junctions, tanks, and reservoirs that make up a water distribution system. WNTR has an application programming interface (API) that is flexible and allows for changes to the network structure and operations, along with simulation of disruptive incidents and recovery actions. WNTR is based upon EPANET, which is a tool to simulate the movement and fate of drinking water constituents within distribution systems. Users are encouraged to be familiar with the use of EPANET and/or should have background knowledge in hydraulics and pressurized pipe network modeling before using WNTR. EPANET has a graphical user interface that might be a useful tool to facilitate the visualization of the network and the associated analysis results. Information on EPANET can be found at https://www.epa.gov/water-research/epanet. WNTR is compatible with EPANET 2.00.12 [Ross00]. In addition, users should have experience using Python, including the installation of additional Python packages. General information on Python can be found at https://www.python.org/.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1994

Implications of the BATSE data for a helocentric origin of gamma-ray bursts

Several possible models have been suggested to explain the observed distribution of gamma-ray bursts: heliocentric distributions such as the Oort cloud, large galactic halos, and cosmological models. We report here on an investigation into the implications of the Burst and Transient Source Experiment (BATSE) gamma-ray burst distribution (Meegan et al. 1992a) data on the possible helocentric origin of gamma-ray bursts. We find no statistically significant anisotropy in the angular distribution of the bursts in a Sun-referenced coordinate system; there is no dipole moment in the direction of the Sun, and no quardrupole moment associated with the ecliptic plane. We have employed direct analytic calculations and Monte Carlo simulations of sources in the Oort cloud to constrain possible helicentric burst distributions. These can produce distributions consistent with the observed angular isotropy, the meal value of V/V(sub max), and the observed C/C(sub min) distribution of BATSE, and provide limits to burst energy of a few times approximately 10(exp 27) ergs. However, the agreement of the heliocentric C/C(sub min) distributions with the BATSE data is attributable to the relatively limited sampling of strong, nearby bursts. These bursts are known from observation to be homogeneously distributed, yet the density of sources in the Oort cloud is not constant in this region. Integral number-intensity distributions from the Oort cloud for larger numbers of bursts cannot reproduce the known homogeneity of the strong bursts without modification to the computed cometary number density and are therefore unlikely explanations of the gamma-ray burst distribution.

Horack, J. M.↗

NASA NTRS2014

TPSAS-NF1676L-19238-DND

The 24-hour cycle of solar insolation drives diurnal cycles in Earth system processes critical to climate: radiation, convection, turbulence, and cloud processes. Cloud properties, temperature, radiative fluxes, and precipitation exhibit robust diurnal cycles as a result. The presence of these robust diurnal cycles fundamentally changes the time mean and variability of the TOA energy budget. Therefore, there is a need to understand the diurnal cycle contributions to the TOA energy budget in both observations and climate models. The first objective of this study is to quantify the diurnal cycle impact on the time mean and variability of the TOA energy budget in observations defined as the difference between TOA fluxes computed with diurnally uniform and diurnally varying cloud properties. The required observational input is observed from the combined Terra+Aqua Cloud and Earth's Radiant Energy System (CERES) data products ranging from June 2002 through October 2012. The second objective of this study is to evaluate the impact of known errors in the model diurnal cycle simulation on the time mean and variability of the TOA energy budget. The results indicate that (1) the diurnal cycle impacts on the regional time mean Tropical longwave and shortwave fluxes range from 1-3 W m 2 and 5 25 W m 2, respectively; (2) the diurnal cycle contributions to TOA flux variability exceeds 50% in land convective regions (e.g., central South America and central Africa);(3) the diurnal cycle contributions to the TOA shortwave and longwave flux time mean and variability in the CanAM4 GCM are too small in land convective regions due to errors in the diurnal distribution of convective clouds grid box errors exceed 100%.

Patrick C Taylor↗

DOE OSTI2026

Co-Simulation Meets AI: MCP-Driven Power System Analysis

GridGPT, a fine-tuned Generative AI model is designed for on-premise use in grid control rooms. This presentation will demonstrate how eGridGPT can seamlessly integrate with control room solutions to offer operators, engineers, and corporate users enhanced guidance and decision support. It is to show how this innovative AI solution can improve state estimation, boost variable energy forecasting, and optimize grid operations. By leveraging eGridGPT's unique features, audience will learn to unlock new levels of automation, predictive analytics, and reliability within their power systems, ultimately leading to reduced downtime and improved operational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2013

Adaptive Distributed Environment for Procedure Training (ADEPT)

ADEPT (Adaptive Distributed Environment for Procedure Training) is designed to provide more effective, flexible, and portable training for NASA systems controllers. When creating a training scenario, an exercise author can specify a representative rationale structure using the graphical user interface, annotating the results with instructional texts where needed. The author's structure may distinguish between essential and optional parts of the rationale, and may also include "red herrings" - hypotheses that are essential to consider, until evidence and reasoning allow them to be ruled out. The system is built from pre-existing components, including Stottler Henke's SimVentive instructional simulation authoring tool and runtime. To that, a capability was added to author and exploit explicit control decision rationale representations. ADEPT uses SimVentive's Scalable Vector Graphics (SVG)- based interactive graphic display capability as the basis of the tool for quickly noting aspects of decision rationale in graph form. The ADEPT prototype is built in Java, and will run on any computer using Windows, MacOS, or Linux. No special peripheral equipment is required. The software enables a style of student/ tutor interaction focused on the reasoning behind systems control behavior that better mimics proven Socratic human tutoring behaviors for highly cognitive skills. It supports fast, easy, and convenient authoring of such tutoring behaviors, allowing specification of detailed scenario-specific, but content-sensitive, high-quality tutor hints and feedback. The system places relatively light data-entry demands on the student to enable its rationale-centered discussions, and provides a support mechanism for fostering coherence in the student/ tutor dialog by including focusing, sequencing, and utterance tuning mechanisms intended to better fit tutor hints and feedback into the ongoing context.

Domeshek, Eric↗

NASA NTRS2015

Continental Spatio-Temporal Data Analysis with Linear Spectral Mixture Model Using FOSS

This work demonstrates the development and implementation of a Fully Constrained Least Squares (FCLS) unmixing model developed in C++ programming language with OpenCV package and boost C++ libraries in the NASA Earth Exchange (NEX). Visualization of the results is supported by GRASS GIS and statistical analysis is carried in R in a Linux system environment. FCLS was first tested on computer simulated data with Gaussian noise of various signal-to-noise ratio, and Landsat data of an agricultural scenario and an urban environment using a set of global end members of substrate (soils, sediments, rocks, and non-photosynthetic vegetation), vegetation that includes green photosynthetic plants and dark objects which encompasses absorptive substrate materials, clear water, deep shadows, etc. For the agricultural scenario, a spectrally diverse collection of 11 scenes of Level 1 terrain corrected, cloud free Landsat-5 TM data of Fresno, California, USA were unmixed and the results were validated with the corresponding ground data. To study an urbanized landscape, a clear sky Landsat-5 TM data were unmixed and validated with coincident World View-2 abundance maps (of 2 m spatial resolution) for an area of San Francisco, California, USA. The results were evaluated using descriptive statistics, correlation coefficient, RMSE, probability of success, boxplot and bivariate distribution function. Finally, FCLS was used for sub-pixel land cover analysis of the monthly WELD (Wen-enabled Landsat data) repository from 2008 to 2011 of North America. The abundance maps in conjunction with DMSP-OLS nighttime lights data were used to extract the urban land cover features and analyze their spatial-temporal growth.

Landsat Satellites↗