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At least 559 records · Page 31

All sources NASA NTRS DOE OSTI

DOE OSTI2022

A machining digital twin for hybrid manufacturing

Hybrid manufacturing consisting of metal additively manufactured preforms and computer numerical control (CNC) machining has been established to be an effective method for high material use rates. However, hybrid manufacturing introduces unique challenges. Near-net shape designs are typically selected, which result in a smaller margin for part placement within the stock and stringent requirements for work coordinate system identification. Additionally, less stock material reduces the preform stiffness, which limits the material removal rates during machining. This paper demonstrates a digital twin for CNC machining of a wire arc additively manufactured preform that implements: 1) structured light scanning for stock model identification and tool path generation; 2) a fused filament fabrication apparatus to attach temporary fiducials and scan targets to the preform that enable coordinate system definition for both the CAM and CNC machine; 3) preform and tool tip frequency response function measurements to enable stable milling parameter selection; and 4) post-manufacturing measurements of geometry, surface finish, and structural dynamics to confirm designer intent. These efforts define key components of the machining digital twin for hybrid manufacturing.

36 MATERIALS SCIENCE↗

NASA NTRS1977

F-8 DFBW sensor failure identification using analytic redundancy

The structure of a sensor failure detection and identification system designed for the NASA F-8 DFBW aircraft is outlined. The system is for use in a dual-redundant environment, and it takes maximal advantage of all functional relationships among the sensed variables. The identification logic uses the quality sequential probability ratio, which provides a useful on-line measure of confidence in the various forms of analytic redundancy. Preliminary simulation results indicate good behavior of the analytic decision statistic, based on the sequential probability ratio test.

Deckert, J. C.↗

NASA NTRS1986

COFS 1: Beam dynamics and control technology overview

The Control of Flexible Structures (COFS) 1 Project provides the invaluable opportunity to test, validate, and measure the effectiveness of theories, structural concepts, control systems, and flight certification processes for future missions through a research program focusing on multiple issues in large flexible structures, dynamics, and controls. The COFS 1 Project consists of a series of ground and flight activities building progressively from modeling and dynamic characterization of large space systems to the more complex issues of flexible-body control. The program objectives are to: determine the degree to which theory and ground testing can predict flight performance of next-generation low-frequency structures; evaluate structural fidelity of representative next-generation large deployable precision structure; assess math modeling requirements for large lightweight complex systems on which ground test results are questionable; determine degree to which scale model analysis and tests can be correlated to full-scale performance; evaluate system identification and state estimation algorithms on complex lightweight structures in the space environment; evaluate and verify controls/structures modeling capability; evaluate control laws and control systems; and evaluate damping effects in micro-g environment.

Allen, John L.↗

NASA NTRS1978

Dynamic response and input identification of MDOF structures subjected to coupled random vector inputs

A method of random dynamic analysis is presented which is based on the classical approach applied to a discretized structure. The method assumes that the system identification is available in the form of natural modes and frequencies. These modes and frequencies can be found from either available solutions or approximately from finite element programs. A computer program has been developed to perform the computations required in the analysis. All computations are performed with transformed modal variables, which results in significant economy since the number of modal degrees of freedom is almost always less than the number of physical degrees of freedom. The program computes the response to force and base inputs which are statistically coupled. A method is also presented for predicting one of the inputs if the second input and the acceleration response at a point on the structure are known. Finally, results are presented for the random response of a rectangular plate subjected to a random pressure and a random base input. The inputs are considered individually and with various degrees of statistical coupling.

Ocallahan, J. C.↗

DOE OSTI2022

Advanced Sensor Deployment for Distribution System State Estimation and Fault Identification: Preprint

Distribution systems are currently facing steep operational challenges as a result of the rapidly increasing integration of renewables and other distributed energy resources (DERs)at both the primary and secondary circuit levels. Distribution utilities and system operators have traditionally had some visibility of their primary circuits using low-frequency supervisory control and data acquisition systems, and they have had very poor if not zero visibility of the secondary circuits where the presence of DERs is constantly increasing. Therefore, this paper presents simulation studies to demonstrate the benefits of an advanced, high-fidelity sensor technology, called as the Meta-Alert System (MAS), developed by Electrical Grid Monitoring Ltd. (EGM), on the distribution grid. First, a reliable model of the EGM sensors is developed, and then two use cases - distribution system state estimation (DSSE) and fault identification - are simulated to evaluate the performance of the MAS technology. Simulation results on the Electric Power Research Institute J1feeder demonstrate that the MAS can effectively participate in system-level DSSE programs and can detect and locate faults faster than traditional distribution protection schemes.

distribution system monitoring↗

NASA NTRSDate not supplied

The Feasibility of Motion Tracking Camera System for Magnetic Suspension Wind Tunnel Tests

The Entry Systems Modeling (ESM) Program at NASA has actively participated in the re-development of the Magnetic Suspension Balance System (MSBS) at the six-inch subsonic wind tunnel at NASA Langley Research Center. This initiative aims to enhance the MSBS system's capabilities, enabling the testing of stingless entry vehicle models at supersonic speeds. To achieve this, control algorithms are required to ensure magnetic levitation control and stability for models during free-oscillation dynamic responses. Currently, the system relies on electromagnetic position sensors to provide real-time 3 degrees of freedom in a rigid body. While this approach has proven successful for subsonic speeds, expanding testing under higher pressure conditions may necessitate the incorporation of real-time roll and pitch measurements to quantify the dynamic stability characteristics of the models in free-oscillation. In collaboration with Old Dominion University, the team at NASA Langley Research Center proposes the implementation of a motion-tracking camera system. This system will provide real-time five degrees of freedom output, which will be utilized within a closed feedback control system and a two-step system identification model to isolate aerodynamic forces from their corresponding magnetic forces. The motion-tracking cameras will offer precise and accurate control over the levitation system, facilitating precise and repeatable experiments within the wind tunnel. The real-time feedback provided by the cameras enables prompt adjustments to ensure the maintenance of stable levitation throughout the testing process.

Entry Systems Modeling↗

NASA NTRSDate not supplied

The Feasibility of Motion Tracking Camera System for Magnetic Suspension Wind Tunnel Tests

Entry Systems Modeling↗

NASA NTRS1993

An application of the Observer/Kalman Filter Identification (OKID) technique to Hubble flight data

The objective of the current research is to identify vibration parameters, including frequencies, damping ratio and uncertainty characteristics, of the Hubble Space Telescope from flight data using an advanced system identification technique. The Observer/Kalman Filter Identification (OKID) technique is used to identify the vibration parameters. The OKID was recently developed by the researchers in the Spacecraft Dynamics Branch at NASA Langley Research Center.

Juang, Jer-Nan↗

DOE OSTI2022

Wavelet and Deep-Learning-Based Approach for Generation System Problematic Parameters Identification and Calibration

Accurate models of generation systems are critical for maintaining reliable and secure grid operations. In this paper, a novel and systematic approach is proposed to identify and calibrate the generation system problematic parameters using continuous wavelet transform (CWT) and advanced deep-learning technology. The phasor measurement unit (PMU) data are used through “event playback” to check whether the parameter calibration is required, and if yes, a group of suspicious parameters will be identified as the primary problematic parameter candidates (PPCs). These primary PPCs are randomly perturbed to generate the event playback simulation data, which are used by the CWT and convolutional neural networks (CNNs) to further narrow down the primary PPCs into a smaller set of candidates. Then, the identified candidates are perturbed again to generate massive event playback simulation data for training a parameter calibration neural network. Here, we designed a multi-output neural network structure to find the mappings between the perturbed parameters and the simulation data using both CNN and long short-term memory (LSTM) models. Finally, the well-trained and tested CNN-LSTM model is used to estimate the accurate value of the suspicious parameters with actual PMU measurements. The proposed CNN-LSTM network can accurately and reliably estimate the generation-system problematic parameters, and has better performance when compared to other machine-learning methods, such as the multilayer perceptron network and the conditional variational autoencoder method. The accuracy and effectiveness of the proposed approach have been validated through simulation and real-world data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Data-Enabled Predictive Control for Building HVAC Systems

Model predictive control is widely used as a control technology for the computation of optimal control inputs of building heating, ventilating, and air conditioning (HVAC) systems. However, both the benefits and widespread adoption of model predictive control (MPC) are hindered by the effort of model creation, calibration, and accuracy of the predictions. In this paper, we apply the data-enabled predictive control (DeePC) algorithm for designing controls for building HVAC systems. The algorithm solely depends on input/output data from the system to predict future state trajectories without the need for system identification. The algorithm relies on the idea that a vector space of all input–output trajectories of a discrete-time linear time-invariant (LTI) system is spanned by time-shifts of a single measured trajectory, given the input signal is persistently exciting. Closed-loop simulations using EnergyPlus are performed to demonstrate the approach. The simulated building modeled in EnergyPlus is a modified commercial large office prototype building served by an air handling unit-variable air volume HVAC system. Temperature setpoints of zones are used as control variables to minimize the HVAC energy cost of the building considering a time-of-use electricity rate structure. Furthermore, sensitivity analysis is conducted to gain insights into the effect of parameter tuning on DeePC performance. Simulation results are used to illustrate the performance of the algorithm and compare the algorithm with model-based MPC and occupancy-based setpoint controller. Overall, DeePC achieves similar performance compared to MPC for lower engineering effort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1990

Investigation of Air Transportation Technology at Ohio University, 1989-1990

The activities of the participants in the Joint University Program (JUP) at Ohio University are briefly surveyed. During 1989 to 1990, five topics received emphasis. A spectrum-efficient weather data uplink system was designed, constructed, and flight tested. An integrated Global Positioning System/Inertial Navigation System (GPS/INS) study continued, utilizing the Redundant strapdown Inertial Measurement Unit (IMU) on loan from NASA. The Ridge Regression theory was refined and applied to air navigation scenarios. System Identification theory was applied to GPS data to point the way to better understanding of the effects of Selective Availability on civilian users of this navigation system. An analysis of thought-related (electroencephalographic) signals for application to control of computer systems that could have significance in aiding paraplegics or for hands-off systems control in industrial or air traffic control areas was carried out.

Lilley, Robert W.↗

NASA NTRS2003

The 2002 NASA Faculty Fellowship Program Research Reports

Contents include the following: System Identification of X-33. Neural Network Advanced Ceramic Technology for Space Applications at NASA MSFC. Developing a MATLAB-Based Tool for Visualization and Transformation. Subsurface Stress Fields in Single Crystal (Anisotropic). Contacts Our Space Future: A Challenge to the Conceptual Artist Concept Art for Presentation and Education. Identification and Characterization of Extremophile Microorganisms. Significant to Astrobiology. Mathematical Investigation of Gamma Ray and Neutron. Absorption Grid Patterns for Homeland Defense-Related Fourier Imaging Systems. The Potential of Microwave Radiation for Processing Martian Soil. Fuzzy Logic Trajectory Design and Guidance for Terminal Area.

Bland, J.↗

NASA NTRS1988

Time domain identification of element matrices

Accurate mathematical models are clearly an important part of the design, modification, control, and damage assessment of large space structures. A critical part of model determination of any type of structure is the use of system identification (SI), a process for using measured excitation and response data to improve the form of a mathematical model or the values of the parameters in it. The reasons for using SI are manifold, but most of them involve uncertainties in either the form of or the parameters in the mathematical model. Some of the more common uncertainties are the following: the nature of the damping, the characteristics of sloppy or sticky joints, inelastic material properties, and parameters in a reduced Degree-of-Freedom (DOF) model. This paper contains a description of the SI algorithm followed by two illustrations: one in which all parameters in a shear building model are determined using pull back and quick release data, and another in which an equivalent reduced DOF model is obtained for a two story frame.

Matzen, Vernon C.↗

DOE OSTI2021

Signal Preconditioning to Minimize Impulse Response Contribution

A study was performed to identify a method to minimize the effect of a linear time-invariant (LTI) system impulse response on an input. Three methods were studied: Wiener filter, the N4SID algorithm and transfer function estimation, the latter two using functions from MATLAB’s System Identification Toolbox. Although all three methods were able estimate an unknown forward impulse response given an input/output time series pair, only the Wiener filter was able to estimate a system inverse which satisfactorily solved the problem using a cosine similarity measure.

42 ENGINEERING↗

NASA NTRS1984

Isotopic composition of primary cosmic rays H-Fe for ISEE-C

The high energy cosmic ray instrument built for the International Sun-Earth Explorer is described. Some aspects of that system are critically renewed so that the experience gained in the design, construction and operation of this experiment can serve as a guide in designing future cosmic ray particle identification systems.

Heckman, H. H.↗

NASA NTRS1988

Identification of large space structures on orbit : A survey

The Task Committee on Methods for Identification of Large Structures in Space was founded in Jul. 1984. The charter of the committee was to prepare a state-of-the-art report on methods of system identification applicable to large space structures (LSS). Funding to support preparation of the report was received in Aug. 1985 from the Air Force Rocket Propulsion Laboratory (now the Air Force Astronautics Laboratory), in the form of a contract to the ASCE. The report was completed, and published by AFRPL in Sep. 1986. The Task Committee consisted of ten members, including ASCE and AFRPL representatives. The membership represented Government, Industry, and Universities, and consisted of electrical, mechanical, and civil engineers, with backgrounds in Structural Dynamics, Optimization, and Controls. An effort was made to use consistent terminology and notation throughout the report which would be compatible with the terminology used in both the structures and controls communities.

Denman, Eugene E.↗

NASA NTRS1999

Alterations in Cardiovascular Regulation and Function During Long-Term Simulated Microgravity

The Cardiovascular Alterations Team is conducting studies of hemodynamic regulation and susceptibility to arrhythmias resulting from sixteen days of simulated microgravity exposure. In these studies very intensive measurements are made during a short duration of bed rest. In this collaborative effort are making many of the same measurements, however much less frequently, on subjects who are exposed to a much longer duration of 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 addition, numerous reports from the past 30 years suggest that the incidence of ventricular arrhythmias among astronauts is increased during space flight. However, the effects of space flight and the associated physiologic stresses on cardiac conduction processes are not known, and an increase in cardiac susceptibility to arrhythmias has never been quantified. In this project we are applying the most powerful technologies available to determine, in a ground-based study of long duration space flight, the mechanisms by which space flight affects cardiovascular function, and then on the basis of an understanding of these mechanisms to develop rational and specific countermeasures. To this end we are conducting a collaborative project with the Bone Demineralization/Calcium Metabolism Team of the National Space Biomedical Research Institute (NSBRI). The Bone Team is conducting bed rest studies in human subjects lasting 17 weeks, which provides a unique opportunity to study the effects of long duration microgravity exposure on the human cardiovascular system. We are applying a number of powerful new methods to these long term bed rest subjects, including cardiovascular system identification (CSI), microvolt level T wave alternans analysis, and cardiac magnetic resonance imaging to assess non-invasively the effects of simulated long duration space flight on the cardiovascular system.

Cohen, Richard J.↗

NASA NTRS1977

Microbe Detector

The AutoMicrobic System (AMS) represents years of intensive research and development by McDonnell Douglas Corp. that originated with a NASA study aimed at development of a fully automated microbial detection and identification system for spacecraft use. A urine specimen is placed into the system, where it is subjected to different freeze-dried microbe nutrients for the nine most common pathogens. An electro-optical scanner studies each specimen once an hour through a 4-to-13 hour cycle, operating automatically. Changes in cell growths on each culture are monitored by computer. The presence of pathogens is indicated when growth reaches a predetermined level. The system also enumerates the pathogens and specifies the type. Developed initially to handle urine testing, AMS soon is expected to allow analyses of blood, spinal fluid, and other body fluids. An additional capability under development is "susceptibility testing," or the determination of which microbe-killing agents-such as penicillin or other antibiotics-would be most effective in eliminating the pathogens. The whole process of detecting, identifying, and enumerating the pathogens and determining susceptibility is accomplished in less half the time required for the manual procedure. The AMS minimizes human error, reduces technician time , and increases laboratory output.

Source record↗