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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Control System of Multi-Port Autonomous Reconfigurable Solar Power Plant (MARS) & HIL Platforms for Design

Multi-port autonomous reconfigurable solar power plant (MARS) provides an attractive alternative to connect photovoltaic (PV) and energy storage systems (ESSs) to high-voltage direct current (HVdc) links and high-voltage alternating current (ac) grids. In this paper, a unique hierarchical control system of MARS is proposed and evaluated. To evaluate the control system and associated algorithms in early-stage research of complex architectures like MARS, it is important to develop unique suitable hardware-in-the-loop (HIL) platforms. In this paper, the HIL platforms for MARS to evaluate the performance of the hierarchical control system and the control algorithms implemented are presented. Further, they help with the design process of control systems. The real-time simulation models and algorithms that are utilized for MARS in the HIL platforms are also discussed in the paper. The HIL experiments of the control system of MARS showcase the capability to provide continuity of operation under faults and frequency support to the power grid during loss of generation. They also showcase the stability of the proposed hierarchical control system of MARS.

14 SOLAR ENERGY↗

NASA NTRS2003

The Fizeau Interferometer Testbed

The Fizeau Interferometer Testbed (FIT) is a collaborative effort between NASA's Goddard Space Flight Center, the Naval Research Laboratory, Sigma Space Corporation, and the University of Maryland. The testbed will be used to explore the principles of and the requirements for the full, as well as the pathfinder, Stellar Imager mission concept. It has a long term goal of demonstrating closed-loop control of a sparse array of numerous articulated mirrors to keep optical beams in phase and optimize interferometric synthesis imaging. In this paper we present the optical and data acquisition system design of the testbed, and discuss the wavefront sensing and control algorithms to be used. Currently we have completed the initial design and hardware procurement for the FIT. The assembly and testing of the Testbed will be underway at Goddard's Instrument Development Lab in the coming months.

OPTICS DESIGN↗

DOE OSTI2021

Computing Free Energies with Fluctuation Relations on Quantum Computers

One of the most promising applications for quantum computers is the dynamic simulation of quantum materials. Current hardware, however, sets stringent limitations on how long such simulations can run before decoherence begins to corrupt results. The Jarzynski equality, a fluctuation theorem that allows for the computation of equilibrium free energy differences from an ensemble of short, non-equilibrium dynamics simulations, can make use of such short-time simulations on quantum computers. Here, we present a quantum algorithm based on the Jarzynski equality for computing free energies of quantum materials. We demonstrate our algorithm using the transverse field Ising model on both a quantum simulator and real quantum hardware. As the free energy is a central thermodynamic property that allows one to compute virtually any equilibrium property of a physical system, the ability to perform this algorithm for larger quantum systems in the future has implications for a wide range of applications including the construction of phase diagrams, prediction of transport properties and reaction constants, and computer-aided drug design.

Bassman, Lindsay↗

NASA NTRSDate not supplied

Space Flown Rodent Liver RNA Sequencing Data for Machine Learning in Space Biology Research

High-throughput nucleic acid sequencing (DNA-seq, RNA-seq) has become widespread in biomedical research due to the growing availability and affordability of these assays. Data analysis has been accelerated in recent years by the adoption of artificial intelligence (AI) and machine learning (ML) techniques by biomedical researchers. In space biology research, RNAseq datasets from space-flown experimental samples are critical for characterizing the gene expression aberrations associated with exposure to spaceflight stressors. However, space biological experiments tend to be very low sample size, so identifying proper AI/ML algorithms for sequencing data analysis is an ongoing challenge since these algorithms typically require large sample size. The NASA Science Mission Directorate (SMD) has started the “Benchmark Initiative for AI/ML”, focused on creating datasets meant for three main applications: 1) scientific benchmarking, which finds the best algorithm for a specific problem; 2) application benchmarking, which measures algorithm performance against a set of parameters; and 3) system benchmarking, which evaluates performance of hardware and software architecture. These scientific benchmarks consist of an AI-ready dataset and a reference implementation on a specific scientific question. In this work, we focused on generating standardized datasets to allow the scientific community to benchmark AI/ML algorithms in the domain of space biology. We present here a standardized, AI-ready, publicly available benchmark dataset for space biology RNA-seq data as a collaboration between the NASA AI4LS (Artificial Intelligence for Life Sciences) working group. and NASA’s SMD. This dataset consists of space-flown and ground control mouse liver found in the NASA GeneLab omics database. However, to amplify the small sample number (n=112 samples) for ML purposes, we employ Gaussian noise and a generative adversarial network to extend this dataset to 6,000 synthetic samples, matching the original gene expression characteristics.

James Casaletto↗

NASA NTRS1987

Computer architecture for efficient algorithmic executions in real-time systems: New technology for avionics systems and advanced space vehicles

Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processing elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed.

Carroll, Chester C.↗

DOE OSTI2025

Comparison of Sequence Component-Based Fault Detection and Relay Coordination Algorithms in Inverter-Based Networks

Protection of inverter-based microgrids using sequence component-based relaying schemes is a promising solution. These methods offer several advantages, including lower computational requirements, compatibility with commercial relay systems, and cost-effectiveness compared to communication-based approaches. This article investigate the performance of various sequence component based schemes with the objective of identifying the algorithms that provide the best fault detection and relay coordination, solely relying on local voltages and current at relay terminals. Positive, negative and zero sequence impedance, admittance and power detection algorithms were tested on modified IEEE 13 bus test network for various shunt faults (LG, LL, LLG, LLL). Hardware-in-the-loop validation was achieved using the Typhoon real-time simulator, interfacing with a SEL 751 relay. This research demonstrates that while several algorithms are capable of detecting faults with sufficient accuracy, only a few are effective in achieving proper coordination. Validation results indicate that the negative sequence power approach provides the best performance in both fault detection and coordination.

Patel, Deepika [ORNL] (ORCID:0000000341099994)↗

DOE OSTI2020

Multiphysics for nuclear energy applications using a cohesive computational framework

With the recent development of advanced numerical algorithms, software design, and low-cost high-performance computer hardware, reliance on coupled multiphysics to predict the behavior of complex physical systems is beginning to become standard practice. This is especially true in nuclear energy applications where strong nonlinear interdependencies exist between reactor physics, radiation transport, multi-scale nuclear fuels performance, thermal fluids, etc. Resolving these nonlinear dependencies requires choices in multiphysics software approaches. Two main multiphysics modeling and simulation approaches have emerged. The first is based upon "code coupling" where disparate physics codes of different software design, code languages, and spatial and temporal integration schemes are coupled together with relatively complex data passing interfaces. The second multiphysics software approach is to employ a "cohesive" framework where all physics applications are developed with a common software design, i.e., data structures, syntax, input format, integrated spatial and temporal discretization schemes, etc. In this paper we present the Multiphysics Object-Oriented Simulation Environment (MOOSE) development and runtime framework and describe the framework's cohesive modeling and simulation multiphysics approach. Then, a "cohesive-like" extension of the MOOSE framework is presented where MOOSE-based physics software applications are efficiently coupled to non-MOOSE (external) physics codes to form multiphysics applications using MOOSE's unique interface capabilities. Finally, several examples of MOOSE's cohesive and cohesive-like multiphysics applications will be demonstrated. These multiphysics demonstrations will incorporate both MOOSE-based applications and external codes, including Nek5000, RELAP-7, TRACE, BISON, and Pronghorn.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Improved particle-flow event reconstruction with scalable neural networks for current and future particle detectors

Abstract Efficient and accurate algorithms are necessary to reconstruct particles in the highly granular detectors anticipated at the High-Luminosity Large Hadron Collider and the Future Circular Collider. We study scalable machine learning models for event reconstruction in electron-positron collisions based on a full detector simulation. Particle-flow reconstruction can be formulated as a supervised learning task using tracks and calorimeter clusters. We compare a graph neural network and kernel-based transformer and demonstrate that we can avoid quadratic operations while achieving realistic reconstruction. We show that hyperparameter tuning significantly improves the performance of the models. The best graph neural network model shows improvement in the jet transverse momentum resolution by up to 50% compared to the rule-based algorithm. The resulting model is portable across Nvidia, AMD and Habana hardware. Accurate and fast machine-learning based reconstruction can significantly improve future measurements at colliders.

Physics↗

DOE OSTI2021

Experimental quantum learning of a spectral decomposition

Currently available quantum hardware allows for small-scale implementations of quantum machine learning algorithms. Such experiments aid the search for applications of quantum computers by benchmarking the near-term feasibility of candidate algorithms. Here we demonstrate the quantum learning of a two-qubit unitary by a sequence of three parameterized quantum circuits containing a total of 21 variational parameters. Moreover, we variationally diagonalize the unitary to learn its spectral decomposition, i.e., its eigenvalues and eigenvectors. We illustrate how this can be used as a subroutine to compress the depth of dynamical quantum simulations. One can view our implementation as a demonstration of entanglement-enhanced machine learning, as only a single (entangled) training data pair is required to learn a 4 × 4 unitary matrix.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1975

Engineering studies of vectorcardiographs in blood pressure measuring systems, appendix 3

The following subjects were covered: (1) ASM80 manual, (2) signal preprocessing as an aid to on-line EKG analysis, and (3) high speed evaluation of magnetic tape recordings of electrocardiograms. A description of the ASM80 symbolic assembly program for the INTEL 8080 microprocessor and a user's manual were presented. The capability of three redundancy reduction algorithms to produce adequate representations of electrocardiographic data was examined. A hardware device was constructed which carried out zero order interpolation on a signal. Examination of the zero order interpolators reconstructed signal indicated that this representation was adequate for analysis of rhythm. A system to analyze magnetic tapes of electrocardiograms recorded over 24 hour intervals was designed. The recordings are sampled 200 times per second using a Nova computer and a special interface system. This system was tested on several recordings of clinical data, containing over 75 premature ventricular contractions, each one of which was flagged.

Mark, R. G.↗

NASA NTRS1978

Three-dimensional computational aerodynamics in the 1980's

The future requirements for constructing codes that can be used to compute three-dimensional flows about aerodynamic shapes should be assessed in light of the constraints imposed by future computer architectures and the reality of usable algorithms that can provide practical three-dimensional simulations. On the hardware side, vector processing is inevitable in order to meet the CPU speeds required. To cope with three-dimensional geometries, massive data bases with fetch/store conflicts and transposition problems are inevitable. On the software side, codes must be prepared that: (1) can be adapted to complex geometries, (2) can (at the very least) predict the location of laminar and turbulent boundary layer separation, and (3) will converge rapidly to sufficiently accurate solutions.

Lomax, H.↗

NASA NTRS1990

Spread-spectrum code acquisition in the presence of Doppler shift and data modulation

A spread-spectrum code acquisition technique for a direct-sequence (DS) system in the presence of Doppler effect and data modulation is investigated. Both the carrier-frequency offset and code-frequency offset due to severe Doppler effect are considered. The code-chip slipping during the correlation process caused by code-frequency offset can degrade the acquisition performance significantly. However, this issue can be alleviated by compensating code-frequency offset in an appropriate manner. Results are presented for the cases with and without data modulation. Coherent detection is considered when there is no data modulation. If data modulation is present, the authors partition the correlation time into subintervals and the integration results in these subintervals are square-law noncoherently combined for detection. The implementation of this code acquisition technique using the fast Fourier transform (FFT) algorithm is described. The use of theoretical results to estimate the hardware complexity of an actual system is illustrated step by step, showing that implementation is feasible with existing technology. The tradeoff between hardware complexity and acquisition performance is discussed.

Cheng, Unjeng↗

NASA NTRS1989

New computing systems and their impact on computational mechanics

Recent advances in computer technology that are likely to impact computational mechanics are reviewed. The technical needs for computational mechanics technology are outlined. The major features of new and projected computing systems, including supersystems, parallel processing machines, special-purpose computing hardware, and small systems are described. Advances in programming environments, numerical algorithms, and computational strategies for new computing systems are reviewed, and a novel partitioning strategy is outlined for maximizing the degree of parallelism on multiprocessor computers with a shared memory.

Noor, Ahmed K.↗

NASA NTRS1994

Robotic NDE inspection of advanced solid rocket motor casings

The Advanced Solid Rocket Motor program determined the need to inspect ASRM forgings and segments for potentially catastrophic defects. To minimize costs, an automated eddy current inspection system was designed and manufactured for inspection of ASRM forgings in the initial phases of production. This system utilizes custom manipulators and motion control algorithms and integrated six channel eddy current data acquisition and analysis hardware and software. Total system integration is through a personal computer based workcell controller. Segment inspection demands the use of a gantry robot for the EMAT/ET inspection system. The EMAT/ET system utilized similar mechanical compliancy and software logic to accommodate complex part geometries. EMAT provides volumetric inspection capability while eddy current is limited to surface and near surface inspection. Each aspect of the systems are applicable to other industries, such as, inspection of pressure vessels, weld inspection, and traditional ultrasonic inspection applications.

Mcneelege, Glenn E.↗

NASA NTRS1998

Solar Flare Physics

We have continued our previous efforts in studies of fourier imaging methods applied to hard X-ray flares. We have performed physical and theoretical analysis of rotating collimator grids submitted to GSFC(Goddard Space Flight Center) for the High Energy Solar Spectroscopic Imager (HESSI). We have produced simulation algorithms which are currently being used to test imaging software and hardware for HESSI. We have developed Maximum-Entropy, Maximum-Likelihood, and "CLEAN" methods for reconstructing HESSI images from count-rate profiles. This work is expected to continue through the launch of HESSI in July, 2000. Section 1 shows a poster presentation "Image Reconstruction from HESSI Photon Lists" at the Solar Physics Division Meeting, June 1998; Section 2 shows the text and viewgraphs prepared for "Imaging Simulations" at HESSI's Preliminary Design Review on July 30, 1998.

Schmahl, Edward J.↗

NASA NTRS2003

Cooperative Multi-Agent Mobile Sensor Platforms for Jet Engine Inspection: Concept and Implementation

Cooperative behavior algorithms utilizing swarm intelligence are being developed for mobile sensor platforms to inspect jet engines on-wing. Experiments are planned in which several relatively simple autonomous platforms will work together in a coordinated fashion to carry out complex maintenance-type tasks within the constrained working environment modeled on the interior of a turbofan engine. The algorithms will emphasize distribution of the tasks among multiple units; they will be scalable and flexible so that units may be added in the future; and will be designed to operate on an individual unit level to produce the desired global effect. This proof of concept demonstration will validate the algorithms and provide justification for further miniaturization and specialization of the hardware toward the true application of on-wing in situ turbine engine maintenance.

Litt, Jonathan S.↗

NASA NTRS2007

Towards Autonomous Inspection of Space Systems Using Mobile Robotic Sensor Platforms

The space transportation systems required to support NASA's Exploration Initiative will demand a high degree of reliability to ensure mission success. This reliability can be realized through autonomous fault/damage detection and repair capabilities. It is crucial that such capabilities are incorporated into these systems since it will be impractical to rely upon Extra-Vehicular Activity (EVA), visual inspection or tele-operation due to the costly, labor-intensive and time-consuming nature of these methods. One approach to achieving this capability is through the use of an autonomous inspection system comprised of miniature mobile sensor platforms that will cooperatively perform high confidence inspection of space vehicles and habitats. This paper will discuss the efforts to develop a small scale demonstration test-bed to investigate the feasibility of using autonomous mobile sensor platforms to perform inspection operations. Progress will be discussed in technology areas including: the hardware implementation and demonstration of robotic sensor platforms, the implementation of a hardware test-bed facility, and the investigation of collaborative control algorithms.

Wong, Edmond↗

NASA NTRS2007

A Low-Complexity Circuit for On-Sensor Concurrent A/D Conversion and Compression

A low-complexity circuit for on-sensor compression is presented. The proposed circuit achieves complexity savings by combining a single-slope analog-to-digital converter with a Golomb-Rice entropy encoder and by implementing a low-complexity adaptation rule. The adaptation rule monitors the output codewords and minimizes their length by incrementing or decrementing the value of the Golomb-Rice coding parameter k. Its hardware implementation is one order of magnitude lower than existing adaptive algorithms. The compression circuit has been fabricated using a 0.35 micrometers CMOS technology and occupies an area of 0.0918 mm2. Test measurements confirm the validity of the design

Leon-Salas, Walter D.↗