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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Forced response testing of an axi-centrifugal turboshaft engine

Dynamic data from tests of a T55-L-712 engine are presented. Engine stall/surge data were analyzed using digital signal processing techniques. In addition, forced response testing (system identification studies) was done at various engine speeds. Forced response testing was done using eight jet ejectors approximately equally circumferentially spaced about the compressor front face. This paper presents some preliminary results for the ground idle (approximately 60% of design speed) point. Brief descriptions of the jet injection system, the test matrix, and analysis techniques used are presented. Results of these analyses indicate a substantial transfer of energy across the compressor first stage at some frequencies and that the ejectors are effective in modifying the local flow conditions in front of the first compressor stage.

Owen, A. Karl↗
NASA NTRS1996

Forced Response Testing of an Axi-Centrifugal Turboshaft Engine

Dynamic data from tests of a T55-L,712 engine are presented. Engine stall/surge data were analyzed using digital signal processing techniques. In addition, forced response testing (system identification studies) was done at various engine speeds. Forced response testing was done using eight jet ejectors approximately equally circumferentially spaced about the compressor front face. This paper presents some preliminary results for the ground idle (approximately 60% of design speed) point. Brief descriptions of the jet injection system, the test matrix, and analysis techniques used are presented. Results of these analyses indicate a substantial transfer of energy across the compressor first stage at some frequencies and that the ejectors are effective in modifying the local flow conditions in front of the first compressor stage.

Owen, A. Karl↗
NASA NTRSDate not supplied

Dynamic Vehicle Assessment for Intelligent Contingency Management for Urban Air Mobility Vehicles

New algorithms will be required to ensure passenger and bystander safety during the expected era of autonomous urban air mobility (UAM) aircraft. This paper examines an approach for assessing the vehicle capability to fly itself and to complete a mission safely. The concepts combine elements of system identification, adaptive control, flight dynamics, envelope predictions, and handling qualities, as well as human pilot intuition. The approach is applied to a simulation of a generic distributed electric propulsion urban air mobility-type aircraft, which was developed under the NASA Transformational Tools and Technologies (TTT) project, Autonomous Systems / Intelligent Contingency Management subproject.

flight envelope prediction↗
NASA NTRS1988

In-flight identification of the Galileo spacecraft flexible mode characteristics

The Galileo scan platform is controlled in two degrees of freedom. A clock (Spin Bearing) actuator controls the relative position between the rotor and stator, and a cone actuator controls the position between the stator and the platform. Instruments on the platform are required to point to 140 micro-rad accuracy and 50 micro-rad per second stability. The system identification objectives were to identify dominant structural resonance frequencies, mode shapes, and damping ratio which exist in the transfer function between the clock actuator and the gyro sensor; and position the notch filter to limit undesirable actuator torque output to ensure stability and performance.

Wong, Edward C.↗
DOE OSTI2022

Ransomware Security Threat Modeling for Photovoltaic Systems

Ransomware attacks are one of the most dangerous cyber-attacks which can disrupt the operation of photovoltaic (PV) systems and incur an enormous economic loss. This paper introduces a ransomware security threat modeling method that identifies potential vulnerabilities, threats, and impacts of ransomware attacks targeting a PV system. Here, the security threat modeling consists of three steps: 1) system identification, 2) threat modeling that finds existing vulnerabilities, 3) attack modeling that designs attack profiles to succeed ransomware attacks, and 4) penetration testing that performs authorized cyber-attacks and analyzes impacts of the ransomware attack profiles using a real-time hardware-in-the-loop (HIL) PV system security testbed.

attack modeling↗
DOE OSTI2013

High-Resolution Hypernuclear Spectroscopy at JLab Hall A. Results and perspectives

Hypernuclear spectroscopy via electromagnetic induced reactions is a valuable and powerful way to study hypernuclei, hadronic systems with non-zero strangeness content, providing an alternative to the hadron induced reactions mainly studied so far. Electron-induced hypernuclear spectroscopy has been studied in Hall A at Je!erson Lab [1] on three nuclei, 12C, 16O, and 9Be with unprecedented resolution and with an improved particle identification system, using a RICH detector, in order to unambiguously identify kaons, thus allowing the measurement of high-quality, almost backgroundfree, hypernuclear spectra. Two superconducting septum magnets were added to the existing apparatus in order to permit particle detection at very forward angle providing a reasonable counting rate. These studies have provided the first quantitative information on core-excited states in hypernuclei. In the case of oxygen, a waterfall target has been employed allowing for the simultaneous measurement of hypernuclear production on oxygen and of elementary kaon-? electro-production on protons: a crucial measurement to disentangle the contribution of the elementary reaction from the measured hypernuclear production cross section, yielding direct access to the nucleus-hypernucleus transition structure. A ? binding energy value for 16 ?N calibrated against the elementary (e, e?K+) reaction on hydrogen, has been obtained. Final results for 12C, 16O, 9Be will be presented [1-3]. Results of Hall C experiments will be presented in another talk in this Conference. Since it is essential for further theoretical study of hypernuclei to collect enough information about L production on nucleons and about excitation spectra of a wide variety of ? hypernuclei, a continuation of the successful hypernuclear program at JLab is very desirable. For these reasons Hall A and Hall C Jefferson Lab hypernuclear collaborations decided to merge and propose a new layout for the 12 GeV Jefferson Lab era that has the advantages of both the experimental setups. In fact the new experimental design not only widens and deepens the physics range but also dramatically improves production yield and efficiency allowing to study both mass spectroscopy on a wide range of nuclei (from few body to 208Pb) and pion decay spectroscopy at the same time [4]. Figs.1, 2 show the results obtained for 12C and 16O. Fig. 3 shows the new layout.

Garibaldi, Franco↗
NASA NTRS2006

Exploratory Studies in Generalized Predictive Control for Active Gust Load Alleviation

The results of numerical simulations aimed at assessing the efficacy of Generalized Predictive Control (GPC) for active gust load alleviation using trailing- and leading-edge control surfaces are presented. The equations underlying the method are presented and discussed, including system identification, calculation of control law matrices, and calculation of commands applied to the control effectors. Both embedded and explicit feedforward paths for inclusion of disturbance effects are addressed. Results from two types of simulations are shown. The first used a 3-DOF math model of a mass-spring-dashpot system subject to user-defined external disturbances. The second used open-loop data from a wind-tunnel test in which a wing model was excited by sinusoidal vertical gusts; closed-loop behavior was simulated in post-test calculations. Results obtained from these simulations have been decidedly positive. In particular, results of closed-loop simulations for the wing model showed reductions in root moments by factors as high as 1000, depending on whether the excitation is from a constant- or variable-frequency gust and on the direction of the response.

Kvaternik, Raymond G.↗
DOE OSTI2013

Identification and control of plasma vertical position using neural network in Damavand tokamak

In this work, a nonlinear model is introduced to determine the vertical position of the plasma column in Damavand tokamak. Using this model as a simulator, a nonlinear neural network controller has been designed. In the first stage, the electronic drive and sensory circuits of Damavand tokamak are modified. These circuits can control the vertical position of the plasma column inside the vacuum vessel. Since the vertical position of plasma is an unstable parameter, a direct closed loop system identification algorithm is performed. In the second stage, a nonlinear model is identified for plasma vertical position, based on the multilayer perceptron (MLP) neural network (NN) structure. Estimation of simulator parameters has been performed by back-propagation error algorithm using Levenberg-Marquardt gradient descent optimization technique. The model is verified through simulation of the whole closed loop system using both simulator and actual plant in similar conditions. As the final stage, a MLP neural network controller is designed for simulator model. In the last step, online training is performed to tune the controller parameters. Simulation results justify using of the NN controller for the actual plant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Physics-constrained, low-dimensional models for magnetohydrodynamics: First-principles and data-driven approaches

Plasmas are highly nonlinear and multiscale, motivating a hierarchy of models to understand and describe their behavior. However, there is a scarcity of plasma models of lower fidelity than magnetohydrodynamics (MHD), although these reduced models hold promise for understanding key physical mechanisms, efficient computation, and real-time optimization and control. Galerkin models, obtained by projection of the MHD equations onto a truncated modal basis, and data-driven models, obtained by modern machine learning and system identification, can furnish this gap in the lower levels of the model hierarchy. This work develops a reduced-order modeling framework for compressible plasmas, leveraging decades of progress in projection-based and data-driven modeling of fluids. We begin by formalizing projection-based model reduction for nonlinear MHD systems. To avoid separate modal decompositions for the magnetic, velocity, and pressure fields, we introduce an energy inner product to synthesize all of the fields into a dimensionally consistent, reduced-order basis. Next, we obtain an analytic model by Galerkin projection of the Hall-MHD equations onto these modes. We illustrate how global conservation laws constrain the model parameters, revealing symmetries that can be enforced in data-driven models, directly connecting these models to the underlying physics. We demonstrate the effectiveness of this approach on data from high-fidelity numerical simulations of a three-dimensional spheromak experiment. Finally, this manuscript builds a bridge to the extensive Galerkin literature in fluid mechanics and facilitates future principled development of projection-based and data-driven models for plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

MODAL FREQUENCY TRACKING: Performance Analysis on Noisy Experimental Ground Test Data

Mechanical devices operating in an environment contaminated by noise, uncertainties, and extraneous disturbances lead to low signal-to-noise-ratios creating an extremely challenging signal processing problem—especially for on-line, realtime, in-flight application. In this report, we discuss a model-based approach to incorporate physical device features into a dynamic structure that can be used to perform on-line tracking of modal frequencies. The approach we take, after pre-processing the raw measurement data, is to obtain a representation of the structural device under test that captures its underlying response to a suite of excitations and operating conditions. One approach is to apply modern system identification techniques based on stochastic subspace methods capable of both: (1) identifying the underlying black-box structure enabling the extraction of structural modes that can be used for analysis; and (2) modal tracking under continued vibrational excitation as in a real-time, in-flight like environment. The vibrational signature of the structural device is measured directly using a suite of tri-axial accelerometers characterizing a multiple input/multiple output (MIMO) dynamic system. In this analysis, we have 15 tri-axial accelerometer measurements or 45 total output channels along with a single excitation also measured with a tri-axial accelerometer providing a 3-input system for processing. We initially describe the experiment and then briefly develop the necessary background in stochastic subspace realization, discuss the algorithm and apply it to the isolated structural device, first, characterized by the set of noisy MIMO accelerometer measurements extracting the modal model from the data (subspace identification), extract the unique modal frequencies (modal coordinate transformation), track their evolution (real-time tracker) to evaluate the overall performance of the processor. Next we evaluate processor performance when the structural device is incorporated into a flight vehicle for further performance analysis. We summarize the results and predict performance.

42 ENGINEERING↗
NASA NTRS2019

Nonlinear Analysis of a Two-Parachute System Undergoing Pendulum Motion

Motion resembling that of a pendulum undergoing large-amplitude limit cycle oscillation was observed during a series of flight tests of an unoccupied Orion Capsule Parachute Assembly System (CPAS) comprised of two parachutes and a capsule payload. Large excursions away from vertical by the capsule could cause it to strike the ground or ocean at a large angle with respect to vertical, or at a large horizontal speed. These conditions are undesirable because they would endanger the occupants of the capsule in an actual mission. A simplified planar dynamics model in conjunction with a nonlinear normal force coefficient vs. angle of attack model serves as the basis of an analytical investigation of the fundamental dynamics of this pendulum motion. Output error methodology from system identification theory was used to identify the parameters of the nonlinear aerodynamics model. The identified model yielded excellent comparison with portions of flight test data where the pendulum motion occurred. Due to the inherent nonlinear nature of the pendulum motion limit cycle, traditional nonlinear analysis techniques were applied to gain further insight into the system. Lyapunov’s direct method provided mathematical proof in the absolute stability of the pendulum mode. Describing Function method was used to predict the amplitude and frequency of the limit cycle oscillation. Finally, phase plane analysis allowed easy visualization on the size and shape of the limit cycle with respect to variations in key aerodynamic parameters.

Pei, Jing↗
DOE OSTI2026

Machine learning-enhanced hybrid modeling approach for better identification of a building thermal network model and improved prediction

The gray-box modeling approach, which uses a semi-physical thermal network model, has been widely used in building prediction applications, such as model predictive control (MPC). However, unmeasured disturbances, such as occupants, lighting, and in/exfiltration loads, make it challenging to apply this approach to practical buildings. In this word, we propose a hybrid modeling approach that integrates the gray-box model with a model for unmeasured disturbance. After reviewing several system identification approaches, we systematically designed the unmeasured disturbance model with a model selection process based on statistical tests to make it robust. We generated data based on the building model calibrated by real operational data and then trained the hybrid model for two different weather conditions. The hybrid model approach demonstrates an RMSE reduction of approximately 0.2–0.9 °C and 0.3–2 °C on 1-day ahead temperature prediction compared to the Conventional approach for mild (Berkeley, CA) and cold (Chicago, IL) climates, respectively. In addition, this approach was applied to experimental data obtained from the laboratory building to be used for the MPC application, showing superior prediction performances.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems

The high complexity and multiscale nature of many engineered systems—such as those in nuclear power plants—make representing and forecasting their dynamic behavior challenging. Physics-based models can be overly complex and computationally intractable, whereas machine learning (ML) tools are often data-hungry and prone to unphysical solutions. This study proposes a knowledge-informed ML-aided hybrid residual modeling approach that offers accurate and efficient time series forecasting for the operation of dynamical engineered systems. Hybrid residual modeling entails a baseline solution from domain knowledge and known physics expressions about the system dynamics integrated with an ML model to capture undiscovered information from the mismatch (i.e., residuals) between true states from measurements and baseline-predicted outputs. This study further quantifies the ML model uncertainty to provide trustworthy solutions. Real-time operational data from thermal-hydraulic flow loops of the cryogenic moderator system in Oak Ridge National Laboratory’s Spallation Neutron Source facility were used to demonstrate the potential of knowledge-informed uncertainty-aware ML in real-world applications. The state variables of the cryogenic helium loop were modeled with (1) first principles–based system identification (sysID), (2) long short-term memory (LSTM) neural network, and (3) hybrid sysID (baseline) + LSTM (residual). The superior predictive capability of the sysID+LSTM model versus stand-alone sysID and LSTM is confirmed by average performance metrics and individual data points across different prediction horizons. By creating a robust representation of the underlying physical system, the widely applicable hybrid residual modeling approach will enable the future development of digital twins for performance prediction, prognostics, and operation control.

Zhao, Xingang↗
NASA NTRS2008

Closing the Certification Gaps in Adaptive Flight Control Software

Over the last five decades, extensive research has been performed to design and develop adaptive control systems for aerospace systems and other applications where the capability to change controller behavior at different operating conditions is highly desirable. Although adaptive flight control has been partially implemented through the use of gain-scheduled control, truly adaptive control systems using learning algorithms and on-line system identification methods have not seen commercial deployment. The reason is that the certification process for adaptive flight control software for use in national air space has not yet been decided. The purpose of this paper is to examine the gaps between the state-of-the-art methodologies used to certify conventional (i.e., non-adaptive) flight control system software and what will likely to be needed to satisfy FAA airworthiness requirements. These gaps include the lack of a certification plan or process guide, the need to develop verification and validation tools and methodologies to analyze adaptive controller stability and convergence, as well as the development of metrics to evaluate adaptive controller performance at off-nominal flight conditions. This paper presents the major certification gap areas, a description of the current state of the verification methodologies, and what further research efforts will likely be needed to close the gaps remaining in current certification practices. It is envisioned that closing the gap will require certain advances in simulation methods, comprehensive methods to determine learning algorithm stability and convergence rates, the development of performance metrics for adaptive controllers, the application of formal software assurance methods, the application of on-line software monitoring tools for adaptive controller health assessment, and the development of a certification case for adaptive system safety of flight.

Jacklin, Stephen A.↗
NASA NTRS1993

Feasibility study of an orbiting laboratory for testing CSI technology

A concept for an orbiting laboratory for testing Controls-Structures Integration (CSI) technology is described. The CSI-Star concept reflects a lower cost, higher risk approach. The concept supports demonstration and validation testing for critical CSI technologies at a cost of $20M to $26M with a 1-year reliability of approximately 0.9. The Ball Aerospace QuickStar bus is the carrier for the CSI test article. QuickStar is launched as a secondary payload on the McDonnell Douglas Delta 2. The QuickStar/Delta 2 approach is flight proven. The CSI test article is a 20 foot, 1 Hz, truss beam which is deployed from the QuickStar bus. The test article is well instrumented for quality system identification. The laboratory provides three layers of active control consisting of global vibration suppression along the truss beam, vibration isolation between the beam and instrument platforms, and vibration compensation through the use of gimbaled platforms which point lasers relative to optical sensor targets. The configuration simulates the dynamics of multi-instrument science platforms such as those of the Earth Observation System (EOS) while maintaining strong ties to astrophysics missions such as the Optical Interferometer. Uplink/downlink services and a reprogrammable computer provide flexibility for long-term investigations by members of the CSI community (NASA, DoD, academia, and industry). CSI-Star fills the gap between short-term experiments, which have been conducted primarily on the Shuttle, and future science missions which require the technology. The on-orbit maturity of CSI technology must be established to obtain acceptance by project managers and to promote injection of the technology into future science missions.

Bicos, Andrew S.↗
DOE OSTI2021

Bilinear dynamic mode decomposition for quantum control

Abstract Data-driven methods for establishing quantum optimal control (QOC) using time-dependent control pulses tailored to specific quantum dynamical systems and desired control objectives are critical for many emerging quantum technologies. We develop a data-driven regression procedure, bilinear dynamic mode decomposition (biDMD), that leverages time-series measurements to establish quantum system identification for QOC. The biDMD optimization framework is a physics-informed regression that makes use of the known underlying Hamiltonian structure. Further, the biDMD can be modified to model both fast and slow sampling of control signals, the latter by way of stroboscopic sampling strategies. The biDMD method provides a flexible, interpretable, and adaptive regression framework for real-time, online implementation in quantum systems. Further, the method has strong theoretical connections to Koopman theory, which approximates nonlinear dynamics with linear operators. In comparison with many machine learning paradigms minimal data is needed to construct a biDMD model, and the model is easily updated as new data is collected. We demonstrate the efficacy and performance of the approach on a number of representative quantum systems, showing that it also matches experimental results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The CLAS12 Forward Time-of-Flight system

The Forward Time-of-Flight system for the large-acceptance CLAS12 spectrometer in Hall B at the Thomas Jefferson National Accelerator Facility is described. The system is positioned at distances in the range from 6.2 m to 7.2 m from the beam–target interaction point and spans laboratory polar angles from 5 deg → 45 deg and nearly the full azimuth. The system consists of 540 individual scintillation counters with double-ended readout that range in length from 17 cm to 426 cm of discrete widths of 6 cm, 15 cm, and 22 cm, and of discrete thicknesses of 5 cm and 6 cm. We see the effective counter time resolution for passing charged particles varies from 50 ps for the shortest counters at small angles to 200 ps for the longest counters at large angles. The detectors are part of the forward-angle particle identification system for CLAS12 during offline event reconstruction and are a component of the online data acquisition trigger to select final state event topologies with forward-going charged particles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Design of a supervisory control system for autonomous operation of advanced reactors

Advanced reactors to be deployed in the coming decades will face deregulated energy markets, and may adopt flexible operation to boost profitability. To aid in the transition from baseload to flexible operation paradigm, autonomous operation is sought. This work focuses on the control aspect of autonomous operation. Specifically, a hierarchical control system is designed to support constraint enforcement during routine operational transients. Within the system, data-driven modeling, physics-based state observation, and classical control algorithms are integrated to provide an adaptable and robust solution. A 320 MW Fluoride-cooled High-temperature Pebble-bed Reactor is the design basis for demonstrating the proposed control system. The hierarchical control system consists of a supervisory layer and low-level layer. The supervisory layer receives requests to change the system's operating conditions (e.g., the current reactor power to meet a load -follow), and accepts or rejects them based on constraints that have been assigned. Constraints are issued to keep the plant within an optimal operating region. The low-level layer interfaces with the actuators of the system to fulfill requested changes, while maintaining tracking and regulation duties. Further, to accept requests at the supervisory layer, the Reference Governor algorithm was adopted. To model the dynamics of the reactor, a system identification algorithm, Dynamic Mode Decomposition, was utilized. To estimate the evolution of process variables that cannot be directly measured (e.g., the propagation of delayed neutron precursors), the Unscented Kalman Filter, incorporating a nonlinear model of nuclear dynamics, was adopted. The composition of these algorithms led to a numerical demonstration of constraint enforcement during a 40% power drop transient (at a rate of 5 %/min). Uncontrolled secondary-side temperatures were successfully constrained. Adaptability of the proposed system was demonstrated by modifying the constraint values, and enforcing them during the transient. Robustness was also demonstrated by enforcing constraints under noisy environments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗