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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Technical Assessment of the Passive Neutron Enrichment Meter (PNEM) for an Unattended Cylinder Verification Station (UCVS)

The International Atomic Energy Agency (IAEA) is exploring the potential roles of an Unattended Cylinder Verifications Station (UCVS) in a new generation of safeguards technology for uranium enrichment plants. The UCVS is envisioned to combine an operator accountancy scale, a nondestructive assay (NDA) system such as the Passive Neutron Enrichment Meter (PNEM), a cylinder identification system, and a surveillance system for verification of product, feed, and tails cylinders as well as continuity of knowledge at material balance area boundaries. The IAEA has identified several preliminary requirements and development questions for the UCVS. Specifically, the IAEA has identified the accuracy of the enrichment assay as the key metric for the NDA system with uncertainty targets of 3%, 6%, and 9% on product, feed, and tails cylinders, respectively. The NDA system should also provide full volume interrogation of the cylinders in order to ensure detection of partial defects within the cylinder. The development questions are concerned primarily with the sources and magnitude of the uncertainty and quantitative analysis of the interrogation depth and partial defect sensitivity. The objective of this report is to address these requirements and questions based on Monte Carlo modeling and field trial experience with the PNEM.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1983

Structural control research and experiments at NASA/LaRC

The advances made in the area of structural dynamics and control using the flexible beam facility at the NASA Langley Research Center are surveyed. Spectral attention is given to the progress in adaptive control and reliability improvements using advanced control concepts. Both theoretical and experimental results are given to delineate the nature of the work being undertaken. With regard to adaptive control, emphasis is placed on parameter and system identification and on comparisons between competing on-line algorithms. In addition, results are presented for on-line modal control laws that are interfaced to a parameter identification scheme. This gives an on-line distributed adaptive control system. With regard to reliability, a design process is outlined that incorporates reliability over the design mission life.

Montgomery, R. C.↗
NASA NTRS1983

Structural control research and experiments at NASA/LaRC

Research progress in the area of structural dynamics and control using the flexible beam facility at the NASA Langley Research Center is reviewed. Particular attention is placed on the progress in adaptive control and reliability improvements using advanced control concepts. Both theoretical and experimental results are given to indicate the nature of the work being undertaken. In the adaptive control area, emphasis is placed on parameter and system identification and in comparison of competing on-line algorithms. Also, results are presented for on-line modal control laws that are interfaced to a parameter identification scheme. This provides an on-line distributed adaptive control system. In the reliability area, a design process is outlined that incorporates reliability over the design mission life.

Montgomery, R. C.↗
NASA NTRS2000

Structural Modeling Using "Scanning and Mapping" Technique

Supported by NASA Glenn Center, we are in the process developing a structural damage diagnostic and monitoring system for rocket engines, which consists of five modules: Structural Modeling, Measurement Data Pre-Processor, Structural System Identification, Damage Detection Criterion, and Computer Visualization. The function of the system is to detect damage as it is incurred by the engine structures. The scientific principle to identify damage is to utilize the changes in the vibrational properties between the pre-damaged and post-damaged structures. The vibrational properties of the pre-damaged structure can be obtained based on an analytic computer model of the structure. Thus, as the first stage of the whole research plan, we currently focus on the first module - Structural Modeling. Three computer software packages are selected, and will be integrated for this purpose. They are PhotoModeler-Pro, AutoCAD-R14, and MSC/NASTRAN. AutoCAD is the most popular PC-CAD system currently available in the market. For our purpose, it plays like an interface to generate structural models of any particular engine parts or assembly, which is then passed to MSC/NASTRAN for extracting structural dynamic properties. Although AutoCAD is a powerful structural modeling tool, the complexity of engine components requires a further improvement in structural modeling techniques. We are working on a so-called "scanning and mapping" technique, which is a relatively new technique. The basic idea is to producing a full and accurate 3D structural model by tracing on multiple overlapping photographs taken from different angles. There is no need to input point positions, angles, distances or axes. Photographs can be taken by any types of cameras with different lenses. With the integration of such a modeling technique, the capability of structural modeling will be enhanced. The prototypes of any complex structural components will be produced by PhotoModeler first based on existing similar components, then passed to AutoCAD for modification and correction of any discrepancies seen in the Photomodeler version of the 3Dmodel. These three software packages are fully compatible. The DXF file can be used to transfer drawings among those packages. To begin this entire process, we are using a small replica of an actual engine blade as a test object. This paper introduces the accomplishment of our recent work.

Amos, Courtney L.↗
NASA NTRS1997

Flutter Boundary Identification From Simulation Time Histories

While there has been much recent progress in simulating nonlinear aeroelastic systems, and in predicting many of the aeroelastic phenomena of concern in transport aircraft design (i.e. transonic flutter buckets), the utility of a simulation in generating an understanding of the flutter behavior is limited. This is due in part to the high cost of generating these simulations; and the implied limitation on the number of conditions that can be analyzed, but there are also some difficulties introduced by the very nature of a simulation. Flutter engineers have traditionally worked in the frequency domain, and are accustomed to describing the flutter behavior of an airplane in terms of its V-G and V-F (or Q-G and Q-F) plots and flutter mode shapes. While the V-G and V-F plots give information about how the dynamic response of an airplane changes as the airspeed is increased, the simulation only gives information about one isolated condition (Mach, airspeed, altitude, etc.). Therefore, where a traditional flutter analysis can let the engineer determine an airspeed at which an airplane becomes unstable, while a simulation only serves as a binary check: either the airplane is fluttering at this condition, or it is not. In this document, a new technique is described in which system identification is used to easily extract modal frequencies and damping ratios from simulation time histories, and shows how the identified parameters can be used to determine the variation in frequency and dampin,o ratio as the airspeed is changed. This technique not only provides the flutter engineer with added insight into the aeroelastic behavior of the airplane, but it allows calculation of flutter mode shapes, and allows estimation of flutter boundaries while minimizing the number of simulations required.

Baker, Myles↗
DOE OSTI2024

Power System Frequency Dynamics Modeling, State Estimation, and Control using Neural Ordinary Differential Equations (NODEs) and Soft Actor-Critic (SAC) Machine Learning Approaches

With the global energy transition of the electric power system, grid control, supervision, and protection is becoming more challenging. With the increasing integration of renewable energy sources (RES), the system dynamics are changing, causing traditional power system dynamic modeling with swing equation-based modeling approaches to fail. Additionally, the converter-dominated power grid is decreasing the system inertia, making the power system more fragile to the frequency swings. This paper first investigates and compares the application of a model-based Kalman filter state estimation approach with (i) a model-free machine learning approach --- neural ordinary differential equations (NODEs) --- and (ii) a data-driven system identification (SysId) approach to model and infer critical state values of the power system frequency dynamics. Then a model predictive control (MPC) framework is compared to a model-free Soft Actor-Critic (SAC) reinforcement learning (RL) control algorithm in providing efficient fast frequency response (FFR) to the power system frequency dynamics. The approaches are compared in terms of their performance goals as well as their per-timestep computational efficiency. Furthermore, the comparative study for state estimation shows that for the model-free requirement, both NODEs and SysId can provide accurate state estimates; however, with increasing model complexity, NODEs can be a better choice for model identification. Similarly, the results from the FFR comparative study show that the SAC RL-based FFR, once trained, outperforms MPC with better control signals and faster computation time, making the SAC RL-based FFR better option for providing FFR to the power system.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1985

Parameter identification in distributed systems

This paper describes a method for the identification of the parameters entering into the equations of motion of distributed systems. Because the motion of distributed systems is described in terms of partial differential equations, these parameters are in general continuous functions of the spatial variables. For vibrating systems, these parameters ordinarily represent the mass, stiffness and damping distributions. In this paper, these distributions are expanded in terms of finite series of known functions of the spatial variables multiplied by undetermined coefficients. It is assumed that the nature of the equations of motion is known and that a limited number of eigenvalues and eigenfunctions is identified in advance. Use is then made of the least squares method, in conjunction with the eigenfunctions' orthogonality, to compute the undetermined coefficients, thus identifying the system distributed parameters. A method for the identification of the eigensolution is also presented. The procedure for the identification of the eigensolution and of the system parameters is demonstrated via a numerical example.

Baruh, H.↗
NASA NTRSDate not supplied

Frequency Domain Quasi Maximum Likelihood Identification of Low Order Aeroservoelastic Models from Flight-Test Data

Background and Motivation - Low Order Equivalent System (LOES) - From handling qualities analysis - Traditionally simplifying complex control law and plant - More easily understood form - Extend LOES to a complex model due to aeroelasticity - Maximum likelihood (Filter Error) System Identification - Z = H_loes (U + W) + V - There are a lot of parameters - Estimate noise parameters - Extra outputs mean extra parameters to estimate - Usually assume noise model to simplify - Output Error and Equation Error - Results in biased estimates of the parameters - Sensing flexible aircraft have many outputs - Quasi maximum likelihood exploits redundancy of outputs

Jeffrey Ouellette↗
DOE OSTI2024

A Data-driven approach to Determining the Fidelity in the Hardware-in-the-loop Systems using Subspace Identification Method

One of the major questions in any Hardware-in-the-loop (HiL) simulation is to understand the fidelity of the HiL simulation itself which is most often indicated qualitatively as either high or low instead of quantifying it. Being cognizant of the level of fidelity forms the crux to assess the validity and credibility of the HiL simulation. In this work, we address this issue by developing a systematic, data-driven approach to assess the fidelity of any HiL simulation, and more specifically, the fidelity of the interface between the simulator and hardware in an HiL simulation. Applying a subspace identification method, a linear system representing the interface is obtained from the time-series data captured between the hardware and simulator in the HiL simulation. Finally, the fidelity is defined based on this linear system properties. The proposed data-driven fidelity quantification framework is illustrated on the IEEE 123 node feeder system running on HYPERSIM and interacting with virtual protection relays.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Restructurable Controls

Restructurable control system theory, robust reconfiguration for high reliability and survivability for advanced aircraft, restructurable controls problem definition and research, experimentation, system identification methods applied to aircraft, a self-repairing digital flight control system, and state-of-the-art theory application are addressed.

R. J. Montoya↗
NASA NTRS1991

Pattern-recognition techniques applied to performance monitoring of the DSS 13 34-meter antenna control assembly

The results of applying pattern recognition techniques to diagnose fault conditions in the pointing system of one of the Deep Space network's large antennas, the DSS 13 34-meter structure, are discussed. A previous article described an experiment whereby a neural network technique was used to identify fault classes by using data obtained from a simulation model of the Deep Space Network (DSN) 70-meter antenna system. Described here is the extension of these classification techniques to the analysis of real data from the field. The general architecture and philosophy of an autonomous monitoring paradigm is described and classification results are discussed and analyzed in this context. Key features of this approach include a probabilistic time-varying context model, the effective integration of signal processing and system identification techniques with pattern recognition algorithms, and the ability to calibrate the system given limited amounts of training data. Reported here are recognition accuracies in the 97 to 98 percent range for the particular fault classes included in the experiments.

Mellstrom, J. A.↗
NASA NTRS1992

Identification of the Space Shuttle Main Engine dynamic models from firing data

A multi-input multi-output system identification technique is used to obtain linearized point models of the Space Shuttle Main Engine (SSME) at five different operating conditions (power levels) from the engine firing data. This study demonstrates that the open-loop dynamics of the SSME can be successfully modeled from the engine firing data. The identified linear models may be used for fault detection studies and control system design and development.

Saravanan, N.↗
NASA NTRSDate not supplied

Handling Qualities Considerations in Control Allocation for Multicopters

Due to multicopters’ role in advanced air mobility, there has been an increasing interest in handling qualities. This paper investigates the effect of control allocation of multicopters on handling qualities. Typically, multicopter aircraft are trimmed with equal speed on each rotor. The force generated by each rotor can be modeled, where thrust and torque of the rotor are related to the square of the rotor speed. The dynamic equations indicate that trimming pairs of motors at different RPM results in an increase of control effectiveness in the associated axis, improving bandwidth and disturbance rejection. A tradeoff occurs where power usage is no longer optimized, but handling qualities are improved in that control axis. A blade element model for multicopter, RMAC, was used to simulate how this off-nominal control allocation would affect the dynamics of a multicopter. System identification flight tests were used to validate the trends seen in RMAC. Control systems were optimized to provide improved disturbance rejection bandwidth in the axis associated with increased rotational speed. Unmanned mission task elements were performed in flight test, showing improved tracking in the lateral axis by using off-nominal mixing to increase trim speed on the rolling motors.

Handling Qualities↗
NASA NTRS2022

Adaptive Force Control for Small Celestial Body Sampling

An adaptive force control algorithm for small celestial body sampling for a variety of surface properties is developed. The control algorithm consists of an adaptive controller combined with feedback linearization. When a spacecraft makes contact with the surface, it must maintain a desired contact force in order to capture a sample. The properties of the surface are unknown or uncertain before contact with the surface is made. The adaptive controller performs system identification online to create an input-output model of the feedback linearized system. From the input-output model a block observable canonical form is realized and the control input is determined by model predictive control (MPC) to maintain a desired contact force in spite of the unknown surface properties. The approach is applied to a variety of surface properties with linear and nonlinear contact models.

Quadrelli, Marco M↗
DOE OSTI2013

Model Identification for Optimal Diesel Emissions Control

In this paper we develop a model based con- troller for diesel emission reduction using system identification methods. Specifically, our method minimizes the downstream readings from a production NOx sensor while injecting a minimal amount of urea upstream. Based on the linear quadratic estimator we derive the closed form solution to a cost function that accounts for the case some of the system inputs are not controllable. Our cost function can also be tuned to trade-off between input usage and output optimization. Our approach performs better than a production controller in simulation. Our NOx conversion efficiency was 92.7% while the production controller achieved 92.4%. For NH3 conversion, our efficiency was 98.7% compared to 88.5% for the production controller.

Stevens, Andrew J.↗
NASA NTRS1983

A study of helicopter gust response alleviation by automatic control

Two control schemes designed to alleviate gust-induced vibration are analytically investigated for a helicopter with four articulated blades. One is an individual blade pitch control scheme. The other is an adaptive blade pitch control algorithm based on linear optimal control theory. In both controllers, control inputs to alleviate gust response are superimposed on the conventional control inputs required to maintain the trim condition. A sinusoidal vertical gust model and a step gust model are used. The individual blade pitch control, in this research, is composed of sensors and a pitch control actuator for each blade. Each sensor can detect flapwise (or lead-lag or torsionwise) deflection of the respective blade. The acturator controls the blade pitch angle for gust alleviation. Theoretical calculations to predict the performance of this feedback system have been conducted by means of the harmonic method. The adaptive blade pitch control system is composed of a set of measurements (oscillatory hub forces and moments), an identification system using a Kalman filter, and a control system based on the minimization of the quadratic performance function.

Saito, S.↗
NASA NTRS1999

Cardiovascular Deconditioning in Humans: Alteration in Cardiovascular Regulation and Function During Simulated Microgravity

Alterations in cardiovascular regulation and function that occur during and after space flight have been reported. These alterations are manifested, for example, by reduced orthostatic tolerance upon reentry to the earth's gravity from space. However, the precise physiologic mechanisms responsible for these alterations remain to be fully elucidated. Perhaps, as a result, effective countermeasures have yet to be developed. In this project we apply a powerful, new method - cardiovascular system identification (CSI) - for the study of the effects of space flight on the cardiovascular system so that effective countermeasures can be developed. CSI involves the mathematical analysis of second-to-second fluctuations in non-invasively measured heart rate, arterial blood pressure (ABP), and instantaneous lung volume (ILV - respiratory activity) in order to characterize quantitatively the physiologic mechanisms responsible for the couplings between these signals. Through the characterization of all the physiologic mechanisms coupling these signals, CSI provides a model of the closed-loop cardiovascular regulatory state in an individual subject. The model includes quantitative descriptions of the heart rate baroreflex, autonomic function, as well as other important physiologic mechanisms. We are in the process of incorporating beat-to-beat fluctuations of stroke volume into the CSI technique in order to quantify additional physiologic mechanisms such as those involved in control of peripheral vascular resistance and alterations in cardiac contractility. We apply CSI in conjunction with the two general protocols of the Human Studies Core project. The first protocol involves ground-based, human head down tilt bed rest to simulate microgravity and acute stressors - upright tilt, standing and bicycle exercise - to provide orthostatic and exercise challenges. The second protocol is intended to be the same as the first but with the addition of sleep deprivation to determine whether this contributes to cardiovascular alterations. In these studies, we focus on the basic physiologic mechanisms responsible for the alterations in cardiovascular regulation and function during the simulated microgravity in order to formulate hypotheses regarding what countermeasures are likely to be most effective. Compared to our original proposal, the protocol we are using has been slightly modified to lengthen the bed rest period to 16 days and streamline the data collection. These modifications provide us data on a longer bed rest period and have enabled us to increase our subject throughput. Based on review of our preliminary data we have decided to test a countermeasure which is applied the very end of the bed rest period. We will use the same bed rest protocol to test this countermeasure. We anticipate completing the baseline data collection in our first protocol plus testing of the countermeasure in an additional eight subjects, at which time we plan to initiate the second protocol which includes sleep deprivation. In future studies, we plan to apply CSI to test other potential countermeasures in conjunction with the same bed rest, sleep deprivation and acute stressor models. We also anticipate applying CSI for studying astronauts before and after space flight and ultimately, during space flight. The application of CSI is providing information relevant to the development and evaluation of effective countermeasures allowing humans to adapt appropriately upon re-exposure to a gravity field, and to live and work for longer periods of time in microgravity.

Cohen, Richard↗
NASA NTRS2000

A Historical Perspective on Dynamics Testing at the Langley Research Center

The experience and advancement of Structural dynamics testing for space system applications at the Langley Research Center of the National Aeronautics and Space Administration (NASA) over the past four decades is reviewed. This experience began in the 1960's with the development of a technology base using a variety of physical models to explore dynamic phenomena and to develop reliable analytical modeling capability for space systems. It continued through the 1970's and 80's with the development of rapid, computer-aided test techniques, the testing of low-natural frequency, gravity-sensitive systems, the testing of integrated structures with active flexible motion control, and orbital flight measurements, It extended into the 1990's where advanced computerized system identification methods were developed for estimating the dynamic states of complex, lightweight, flexible aerospace systems, The scope of discussion in this paper includes ground and flight tests and summarizes lessons learned in both successes and failures.

Horta, Lucas G.↗