Results for “input estimation” — Page 98

NASA NTRS1989

Measurements of short-term thermal responses of coniferous forest canopies using thermal scanner data

Thermal Infrared Multispectral Scanner (TIMS) data were collected over a coniferous forest in western Oregon. Concurrent radiosonde measurements of atmospheric profiles of air temperature and moisture provided inputs to LOWTRAN6 for atmospheric radiance corrections of the TIMS data. Surface temperature differences measured by the TIMS over time between flight lines were combined with surface radiative energy balance estimates to develop thermal response numbers (TRN). These numbers characterized the thermal response of the diffent surface types. Barren surfaces had the lowest TRN, whereas the forested surfaces had the highest.

Luvall, J. C.↗

NASA NTRS1991

The AFIT gross motion control project

The objective of the Gross Motion Control project is to study alternative control approaches that will provide payload invariant high speed trajectory tracking for nonrepetitive motions in free space. The research has concentrated on modifications to the model-based control structure. Development and evaluation is being actively pursued of both adaptive primary (inner loop) and robust secondary (output loop) controllers. In-house developments are compared and contrasted to the techniques proposed by other researchers. The case study for the evaluation is the first three links of a PUMA-560. Incorporating the principals of multiple model adaptive estimation, artificial neural networks, and Lyapunov theory into the model based paradigm has shown the potential for enhanced tracking. Secondary controllers based on Quantitative Feedback Theory, or augmented with auxiliary inputs, significantly improve the robustness to payload variations and unmodeled drive system dynamics. An overview is presented of the different concepts under investigation and a sample is provided of the latest experimental results.

Leahy, M. B., Jr.↗

NASA NTRS1992

Identification and feedback control in structures with piezoceramic actuators

In this lecture we give fundamental well-posedness results for a variational formulation of a class of damped second order partial differential equations with unbounded input or control coefficients. Included as special cases in this class are structures with piezoceramic actuators. We consider approximation techniques leading to computational methods in the context of both parameter estimation and feedback control problems for these systems. Rigorous convergence results for parameter estimates and feedback gains are discussed.

Banks, H. T.↗

NASA NTRS1992

Reversible thermodynamic cycle for AMTEC power conversion

The thermodynamic cycle appropriate to an AMTEC (alkali metal thermal-to-electric converter) cell is discussed for both liquid- and vapor-fed modes of operation, under the assumption that all processes can be performed reversibly. In the liquid-fed mode, the reversible efficiency is greater than 89.6 percent of Carnot efficiency for heat input and rejection temperatures (900-1300 K and 400-800 K, respectively) typical of practical devices. Vapor-fed cells can approach the efficiency of liquid-fed cells. Quantitative estimates confirm that the efficiency is insensitive to either the work required to pressurize the sodium liquid or the details of the state changes associated with cooling the low pressure sodium gas to the heat rejection temperature.

Vining, Cronin B.↗

NASA NTRS1996

Piloted Parameter Identification Flight Test Maneuvers for Closed Loop Modeling of the F-18 High Alpha Research Vehicle (HARV)

Flight test maneuvers are specified for the F-18 High Alpha Research Vehicle (HARV). The maneuvers were designed for closed loop parameter identification purposes, specifically for longitudinal and lateral linear model parameter estimation at 5, 20, 30, 45, and 60 degrees angle of attack, using the NASA 1A control law. Each maneuver is to be realized by the pilot applying square wave inputs to specific pilot station controls. Maneuver descriptions and complete specifications of the time/amplitude points defining each input are included, along with plots of the input time histories.

Morelli, Eugene A.↗

NASA NTRS1996

An efficient approach to ARMA modeling of biological systems with multiple inputs and delays

This paper presents a new approach to AutoRegressive Moving Average (ARMA or ARX) modeling which automatically seeks the best model order to represent investigated linear, time invariant systems using their input/output data. The algorithm seeks the ARMA parameterization which accounts for variability in the output of the system due to input activity and contains the fewest number of parameters required to do so. The unique characteristics of the proposed system identification algorithm are its simplicity and efficiency in handling systems with delays and multiple inputs. We present results of applying the algorithm to simulated data and experimental biological data In addition, a technique for assessing the error associated with the impulse responses calculated from estimated ARMA parameterizations is presented. The mapping from ARMA coefficients to impulse response estimates is nonlinear, which complicates any effort to construct confidence bounds for the obtained impulse responses. Here a method for obtaining a linearization of this mapping is derived, which leads to a simple procedure to approximate the confidence bounds.

Non-NASA Center↗

NASA NTRS2005

Shuttle Rudder/Speed Brake Power Drive Unit (PDU) Gear Scuffing Tests With Flight Gears

Scuffing-like damage has been found on the tooth surfaces of gears 5 and 6 of the NASA space shuttle rudder/speed brake power drive unit (PDU) number 2 after the occurrence of a transient back-driving event in flight. Tests were conducted using a pair of unused spare flight gears in a bench test at operating conditions up to 2866 rpm and 1144 in.-lb at the input ring gear and 14,000 rpm and 234 in.-lb at the output pinion gear, corresponding to a power level of 52 hp. This test condition exceeds the maximum estimated conditions expected in a backdriving event thought to produce the scuffing damage. Some wear marks were produced, but they were much less severe than the scuffing damaged produced during shuttle flight. Failure to produce scuff damage like that found on the shuttle may be due to geometrical variations between the scuffed gears and the gears tested herein, more severe operating conditions during the flight that produced the scuff than estimated, the order of the test procedures, the use of new hydraulic oil, differences between the dynamic response of the flight gearbox and the bench-test gearbox, or a combination of these. This report documents the test gears, apparatus, and procedures, summarizes the test results, and includes a discussion of the findings, conclusions, and recommendations.

Proctor, Margaret P.↗

NASA NTRS2014

A Formal Approach to Empirical Dynamic Model Optimization and Validation

A framework was developed for the optimization and validation of empirical dynamic models subject to an arbitrary set of validation criteria. The validation requirements imposed upon the model, which may involve several sets of input-output data and arbitrary specifications in time and frequency domains, are used to determine if model predictions are within admissible error limits. The parameters of the empirical model are estimated by finding the parameter realization for which the smallest of the margins of requirement compliance is as large as possible. The uncertainty in the value of this estimate is characterized by studying the set of model parameters yielding predictions that comply with all the requirements. Strategies are presented for bounding this set, studying its dependence on admissible prediction error set by the analyst, and evaluating the sensitivity of the model predictions to parameter variations. This information is instrumental in characterizing uncertainty models used for evaluating the dynamic model at operating conditions differing from those used for its identification and validation. A practical example based on the short period dynamics of the F-16 is used for illustration.

Crespo, Luis G↗

NASA NTRS2015

Modelling Freshwater Resources at the Global Scale: Challenges and Prospects

Quantification of spatially and temporally resolved water flows and water storage variations for all land areas of the globe is required to assess water resources, water scarcity and flood hazards, and to understand the Earth system. This quantification is done with the help of global hydrological models (GHMs). What are the challenges and prospects in the development and application of GHMs? Seven important challenges are presented. (1) Data scarcity makes quantification of human water use difficult even though significant progress has been achieved in the last decade. (2) Uncertainty of meteorological input data strongly affects model outputs. (3) The reaction of vegetation to changing climate and CO2 concentrations is uncertain and not taken into account in most GHMs that serve to estimate climate change impacts. (4) Reasons for discrepant responses of GHMs to changing climate have yet to be identified. (5) More accurate estimates of monthly time series of water availability and use are needed to provide good indicators of water scarcity. (6) Integration of gradient-based groundwater modelling into GHMs is necessary for a better simulation of groundwater-surface water interactions and capillary rise. (7) Detection and attribution of human interference with freshwater systems by using GHMs are constrained by data of insufficient quality but also GHM uncertainty itself. Regarding prospects for progress, we propose to decrease the uncertainty of GHM output by making better use of in situ and remotely sensed observations of output variables such as river discharge or total water storage variations by multi-criteria validation, calibration or data assimilation. Finally, we present an initiative that works towards the vision of hyper resolution global hydrological modelling where GHM outputs would be provided at a 1-km resolution with reasonable accuracy.

Global hydrological model↗

NASA NTRSDate not supplied

Parallelized Quadrupole Simulations of Thermographic Responses of Composites

Thermography has been shown to be a viable technique for inspection of composites. Model inversion of the thermography data requires a fast method for performing the forward problem. Viable numerical methods for the thermal response forward problem are finite element, finite difference and the quadrupole method. Normally both the finite element and finite difference methods solve for the thermal response in the time domain which limits one’s ability to increase the speed of the simulation by parallelization. In contrast, the quadrupole method solves for the Laplace transform of the thermal response. One of the features of the Laplace transform methodology is the solution at any discrete time is independent of the solution at all other times. Therefore, it is easy to separate into a set of independent calculations with each of the times of interest being performed in parallel. Additionally, the numeric inversion of the Laplace transform typically involves numerically solving for the Laplace transform at multiple Laplace frequencies. Each of those solutions are also independent of solutions at other frequencies and can be calculated in parallel. By parallelization of this method, it is possible to perform the simulations of three-dimensional configurations in seconds. When the input stimulus for thermal response is a delta function heat flux (a reasonable approximation for flash heating), the thermal response is smooth. For this case, it is possible to accurately estimate the thermal response at any time within a given time interval from a set of simulations separated by exponentially increasing time steps. From these simulations, it is possible to accurately interpolate to find the response at intermediate times by a spline interpolation of the logarithm of time versus logarithm of temperature. The thermal response with exponential time stepping is shown to produce values for the thermal response which are within 1% of values within the time interval. The simulations are compared to finite element simulations of the same inspection configurations. The simulations are also compared to the thermographic measurements on composites where shape and depth of the delaminations are obtained from other inspection methods.

Thermography↗

NASA NTRSDate not supplied

Parallelized Quadrupole Simulations of Thermographic Responses of Composites

Thermography has been shown to be a viable technique for inspection of composites. Model inversion of the thermography data requires a fast method for performing the forward problem. Viable numerical methods for the thermal response forward problem are finite element, finite difference and the quadrupole method. Normally both the finite element and finite difference methods solve for the thermal response in the time domain which limits one’s ability to increase the speed of the simulation by parallelization. In contrast, the quadrupole method solves for the Laplace transform of the thermal response. One of the features of the Laplace transform methodology is the solution at any discrete time is independent of the solution at all other times. Therefore, it is easy to separate into a set of independent calculations with each of the times of interest being performed in parallel. Additionally, the numeric inversion of the Laplace transform typically involves numerically solving for the Laplace transform at multiple Laplace frequencies. Each of those solutions are also independent of solutions at other frequencies and can be calculated in parallel. By parallelization of this method, it is possible to perform the simulations of three-dimensional configurations in seconds. When the input stimulus for thermal response is a delta function heat flux (a reasonable approximation for flash heating), the thermal response is smooth. For this case, it is possible to accurately estimate the thermal response at any time within a given time interval from a set of simulations separated by exponentially increasing time steps. From these simulations, it is possible to accurately interpolate to find the response at intermediate times by a spline interpolation of the logarithm of time versus logarithm of temperature. The thermal response with exponential time stepping is shown to produce values for the thermal response which are within 1% of values within the time interval. The simulations are compared to finite element simulations of the same inspection configurations. The simulations are also compared to the thermographic measurements on composites where shape and depth of the delaminations are obtained from other inspection methods.

Thermography↗

NASA NTRSDate not supplied

Recent Developments in the Assimilation of Microwave and Radar Observations Into NWP Models

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗

NASA NTRSDate not supplied

Enhancing CRTM All-Sky Simulations and Implementation of A New Active Sensor Module

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗

NASA NTRSDate not supplied

CRTM Microwave Cloud Scattering Lookup Tables and Radar Simulator

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗

NASA NTRS1961

Flight-Path Characteristics for Decelerating From Supercircular Speed

Characteristics of the following six flight paths for decelerating from a supercircular speed are developed in closed form: constant angle of attack, constant net acceleration, constant altitude" constant free-stream Reynolds number, and "modulated roll." The vehicles were required to remain in or near the atmosphere, and to stay within the aerodynamic capabilities of a vehicle with a maximum lift-drag ratio of 1.0 and within a maximum net acceleration G of 10 g's. The local Reynolds number for all the flight paths for a vehicle with a gross weight of 10,000 pounds and a 600 swept wing was found to be about 0.7 x 10(exp 6). With the assumption of a laminar boundary layer, the heating of the vehicle is studied as a function of type of flight path, initial G load, and initial velocity. The following heating parameters were considered: the distribution of the heating rate over the vehicle, the distribution of the heat per square foot over the vehicle, and the total heat input to the vehicle. The constant G load path at limiting G was found to give the lowest total heat input for a given initial velocity. For a vehicle with a maximum lift-drag ratio of 1.0 and a flight path with a maximum G of 10 g's, entry velocities of twice circular appear thermo- dynamically feasible, and entries at velocities of 2.8 times circular are aerodynamically possible. The predominant heating (about 85 percent) occurs at the leading edge of the vehicle. The total ablated weight for a 10,000-pound-gross-weight vehicle decelerating from an initial velocity of twice circular velocity is estimated to be 5 percent of gross weight. Modifying the constant G load flight path by a constant-angle-of-attack segment through a flight- to circular-velocity ratio of 1.0 gives essentially a "point landing" capability but also results in an increased total heat input to the vehicle.

Luidens, Roger W.↗

NASA NTRS2018

Systems and Methods for Transfer Function Estimation Using Membership Functions

An apparatus, method, and computer program that can learn a linear or non-linear transfer function are disclosed. In one embodiment, for example, a computer-implemented method may include creating a plurality of combinations for at least one input, and calculating an output for the plurality of combinations. The method may also include calculating an error based on the calculated output.

Krasowski, Michael J↗

DOE OSTI2024

Training quantum neural networks using the quantum information bottleneck method

Abstract We provide in this paper a concrete method for training a quantum neural network to maximize the relevant information about a property that is transmitted through the network. This is significant because it gives an operationally well founded quantity to optimize when training autoencoders for problems where the inputs and outputs are fully quantum. We provide a rigorous algorithm for computing the value of the quantum information bottleneck quantity within error ε that requires O ( log 2 ⁡ ( 1 / ϵ ) + 1 / δ 2 ) queries to a purification of the input density operator if its spectrum is supported on { 0 } ⋃ [ δ , 1 − δ ] for δ > 0 and the kernels of the relevant density matrices are disjoint. We further provide algorithms for estimating the derivatives of the QIB function, showing that quantum neural networks can be trained efficiently using the QIB quantity given that the number of gradient steps required is polynomial.

Çatlı, Ahmet Burak (ORCID:0000000152294141)↗

DOE OSTI2022

Performance of New Near-Real-Time PERSIANN Product (PDIR-Now) for Atmospheric River Events over the Russian River Basin, California

Most heavy precipitation events and extreme flooding over the U.S. Pacific coast can be linked to prevalent atmospheric river (AR) conditions. Thus, reliable quantitative precipitation estimation with a rich spatiotemporal resolution is vital for water management and early warning systems of flooding and landslides over these regions. At the same time, high-quality near-real-time measurements of AR precipitation remain challenging due to the complex topographic features of land surface and meteorological conditions of the region: specifically, orographic features occlude radar measurements while infrared-based algorithms face challenges, differentiating between both cold brightband (BB) precipitation and the warmer nonbrightband (NBB) precipitation. It should be noted that the latter precipitation is characterized by greater orographic enhancement. In this study, we evaluate the performance of a recently developed near-real-time satellite precipitation algorithm: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) Dynamic Infrared–Rain Rate-Now (PDIR-Now). This model is primarily dependent on infrared information from geostationary satellites as input; consequently, PDIR-Now has the advantage of short data latency, 15–60-min delay between observation to precipitation product delivery. The performance of PDIR-Now is analyzed with a focus on AR-related events for cases dominated by NBB and BB precipitation over the Russian River basin. In our investigations, we utilize S-band (3-GHz) precipitation profilers with Joss/Parsivel disdrometer measurements at the Middletown and Santa Rosa stations to classify BB and NBB precipitation events. In general, our analysis shows that PDIR-Now is more skillful in retrieving precipitation rates over both BB and NBB events across the topologically complex study area as compared to PERSIANN-Cloud Classification System (CCS). Also, we discuss the performance of well-known operational near-real-time precipitation products from 2017 to 2019. Conventional categorical and volumetric categorical indices, as well as continuous statistical metrics, are used to show the differences between various high-resolution precipitation products such as Multi-Radar Multi-Sensor (MRMS).

54 ENVIRONMENTAL SCIENCES↗