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Results for “Inverse model calibration”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Model Calibration for Cancer Risk Projections According to Uncertain Data

This paper presents forward and inverse formulations for the calibration of computational models according to uncertain data. Uncertainty in the data might be caused by a poor metrology system, measurement noise, missing or uncontrollable input variables, or by the inability to directly measure the inputs and/or outputs of interest. The forward approach performs the calibration in the space of the model’s output thereby requiring repeated model simulations. Conversely, the inverse approach leverages an ensemble of solutions to an inverse problem in order to perform the calibration in the space of the model’s parameters. As such, the computational demands of the inverse approach are considerably lower. These strategies are applied to the calibration of a radiation model that in-forms cancer risk projections for future deep space missions.

uncertainty quantification↗

Calibration or inverse regression: Which is appropriate for crop surveys using LANDSAT data?

Calibration and inverse regression estimators of crop proportions are investigated where the auxiliary variable is obtained from binary classification of multivariate LANDSAT data. The appropriate model relating classifier proportions and ground observed proportions for a given crop type is the calibration model. Under this model the inverse regression estimator is superior to the calibration estimator in estimating the crop acreage or proportion for a region of interest.

Chhikara, R. S.↗

An Inverse Chance-constrained Approach to the Calibration of Robust Models

This paper proposes a strategy to calibrate computational models according to uncertain input-output data. To this end, uncertainty in the data is first quantified by creating adversarial data sets. Samples drawn from such sets are then mapped from the input-output space to the parameter space using an inverse mapping. This mapping minimizes the collective output spread of an ensemble of point predictions while satisfying a set of individual data-matching requirements. The distribution of the resulting parameter points, which often exhibits strong parameter dependencies, is then modeled using sliced-normals. The chance-constrained formulation used to learn this distribution enables the analyst to trade-off a greater likelihood for most of the data against a lower likelihood for some of the data thereby relaxing the conservatism of the calibrated model. This formulation not only neglects the worst-performing quantiles of each adversarial distribution but also eliminates the potentially serious effects that outliers might have on the resulting model. This calibration approach not only has a considerably lower computational cost than the standard forward approach but it also allows for the identification of suitable distribution classes, which in turn yield better calibrated models.

Calibration↗

An Analytical Calibration Approach for the Polarimetric Airborne C Band Radiometer

Passive microwave remote sensing is sensitive to the quantity and distribution of water in soil and vegetation. During summer 2000, the Microwave Geophysics Group a t the University of Michigan conducted the seventh Radiobrighness Energy Balance Experiment (REBEX-7) over a corn canopy in Michigan. Long time series of brightness temperatures, soil moisture and micrometeorology on the plot were taken. This paper addresses the calibration of the NASA GSFC polarimetric airborne C band microwave radiometer (ACMR) that participated in REBEX-7. These passive polarimeters are typically calibrated using an end-to-end approach based upon a standard artificial target or a well-known geophysical target. Analyzing the major internal functional subsystems offers a different perspective. The primary goal of this approach is to provide a transfer function that not only describes the system in its entire5 but also accounts for the contributions of each subsystem toward the final modified Stokes parameters. This approach does not assume that the radiometric system is linear as it does not take polarization isolation for granted, and it also serves as a realistic instrument simulator, a useful tool for future designs. The ACMR architecture can be partitioned into functional subsystems. The characteristics of each subsystem was extensively measured and the estimated parameters were imported into the overall dosed form system model. Inversion of the model yields a calibration for the modeled Stokes parameters with uncertainties of 0.2 K for the V and H polarizations and 2.4 K for the 3rd and 4th parameters. Application to the full Stokes parameters over a senescent cornfield is presented.

Pham, Hanh↗

Validation of SCIAMACHY and TOMS UV Radiances Using Ground and Space Observations

Verification of a stratospheric ozone recovery remains a high priority for environmental research and policy definition. Models predict an ozone recovery at a much lower rate than the measured depletion rate observed to date. Therefore improved precision of the satellite and ground ozone observing systems are required over the long term to verify its recovery. We show that validation of satellite radiances from space and from the ground can be a very effective means for correcting long term drifts of backscatter type satellite measurements and can be used to cross calibrate all B W instruments in orbit (TOMS, SBW/2, GOME, SCIAMACHY, OM, GOME-2, OMPS). This method bypasses the retrieval algorithms used for both satellite and ground based measurements that are normally used to validate and correct the satellite data. Radiance comparisons employ forward models and are inherently more accurate than inverse (retrieval) algorithms. This approach however requires well calibrated instruments and an accurate radiative transfer model that accounts for aerosols. TOMS and SCIAMACHY calibrations are checked to demonstrate this method and to demonstrate applicability for long term trends.

Hilsenrath, E.↗

Modeling Spectralon's Bidirectional Reflectance for In-Flight Calibration of Earth-Orbiting Sensors

This paper describes the results of a model inversion which was conducted using measured Spectralon BRDF data at several illumination angles. We can describe the bidirectional reflectance of the Spectralon and in paticular its slight anisotrophy with a physically-based model. The root mean square difference between the model and the observations is currently of the order of the noise in the data (+/-1%). It is expected that meaningful corrections to account for the anisotrophy of the Spectralon panels will be achieved in the next few years and will improve the calibration of the MISR instrument.

EOS↗

Oxygen and Fuel Jet Diffusion Flame Studies in Microgravity Motivated by Spacecraft Oxygen Storage Fire Safety

Owing to the absence of past work involving flames similar to the Mir fire namely oxygen-enhanced, inverse gas-jet diffusion flames in microgravity the objectives of this work are as follows: 1. Observe the effects of enhanced oxygen conditions on laminar jet diffusion flames with ethane fuel. 2. Consider both earth gravity and microgravity. 3. Examine both normal and inverse flames. 4. Compare the measured flame lengths and widths with calibrated predictions of several flame shape models. This study expands on the work of Hwang and Gore which emphasized radiative emissions from oxygen-enhanced inverse flames in earth gravity, and Sunderland et al. which emphasized the shapes of normal and inverse oxygen-enhanced gas-jet diffusion flames in microgravity.

Sunderland, P. B.↗

Calculating Nozzle Side Loads using Acceleration Measurements of Test-Based Models

As part of a NASA/MSFC research program to evaluate the effect of different nozzle contours on the well-known but poorly characterized "side load" phenomena, we attempt to back out the net force on a sub-scale nozzle during cold-flow testing using acceleration measurements. Because modeling the test facility dynamics is problematic, new techniques for creating a "pseudo-model" of the facility and nozzle directly from modal test results are applied. Extensive verification procedures were undertaken, resulting in a loading scale factor necessary for agreement between test and model based frequency response functions. Side loads are then obtained by applying a wide-band random load onto the system model, obtaining nozzle response PSD's, and iterating both the amplitude and frequency of the input until a good comparison of the response with the measured response PSD for a specific time point is obtained. The final calculated loading can be used to compare different nozzle profiles for assessment during rocket engine nozzle development and as a basis for accurate design of the nozzle and engine structure to withstand these loads. The techniques applied within this procedure have extensive applicability to timely and accurate characterization of all test fixtures used for modal test.A viewgraph presentation on a model-test based pseudo-model used to calculate side loads on rocket engine nozzles is included. The topics include: 1) Side Loads in Rocket Nozzles; 2) Present Side Loads Research at NASA/MSFC; 3) Structural Dynamic Model Generation; 4) Pseudo-Model Generation; 5) Implementation; 6) Calibration of Pseudo-Model Response; 7) Pseudo-Model Response Verification; 8) Inverse Force Determination; 9) Results; and 10) Recent Work.

Brown, Andrew M.↗

Flame Chemiluminescence Rate Constants for Quantitative Microgravity Combustion Diagnostics

Absolute excited state concentrations of OH(A), CH(A), and C2(d) were determined in three low pressure premixed methane-air flames. Two dimensional images of chemiluminescence from these states were recorded by a filtered CCD camera, processed by Abel inversion, and calibrated against Rayleigh scattering, Using a previously validated 1-D flame model with known chemistry and excited state quenching rate constants, rate constants are extracted for the reactions CH + O2 (goes to) OH(A) + CO and C2H + O (goes to) CH(A) + CO at flame temperatures. Variations of flame emission intensities with stoichiometry agree well with model predictions.

Luque, Jorge↗

The use of a helicopter mounted ranging scatterometer for estimation of extinction and scattering properties of forest canopies-II: Experimental results for high-density aspen

An analytic expression is derived that describes the backscatter power from a semi-infinite plane parallel homogeneous canopy as a function of distance from an airborne radar. This model is fitted to observed data for a high-density aspen canopy by a modification of a technique developed by Tyapkin (1960). This inversion of the model provides unbiased estimates of the canopy extinction and backscattering parameters. An active radar calibrator located underneath the canopy provides an independent method of determining the volume extinction coefficient. The results reported indicate that the coefficients change throughout the year. A comparison of these coefficients with Eom and Funk's (1984) disk model, using measured canopy properties, shows that at C-band frequency, only a part of the scattering and absorption can be attributed to the canopy leaves.

Pitts, David E.↗

Active microwaves

Research on the use of active microwaves in remote sensing, presented during plenary and poster sessions, is summarized. The main highlights are: calibration techniques are well understood; innovative modeling approaches have been developed which increase active microwave applications (segmentation prior to model inversion, use of ERS-1 scatterometer, simulations); polarization angle and frequency diversity improves characterization of ice sheets, vegetation, and determination of soil moisture (X band sensor study); SAR (Synthetic Aperture Radar) interferometry potential is emerging; use of multiple sensors/extended spectral signatures is important (increase emphasis).

Evans, D.↗

Improved Tracking of Targets by Cameras on a Mars Rover

A paper describes a method devised to increase the robustness and accuracy of tracking of targets by means of three stereoscopic pairs of video cameras on a Mars-rover-type exploratory robotic vehicle. Two of the camera pairs are mounted on a mast that can be adjusted in pan and tilt; the third camera pair is mounted on the main vehicle body. Elements of the method include a mast calibration, a camera-pointing algorithm, and a purely geometric technique for handing off tracking between different camera pairs at critical distances as the rover approaches a target of interest. The mast calibration is an extension of camera calibration in which the camera images of calibration targets at known positions are collected at various pan and tilt angles. In the camerapointing algorithm, pan and tilt angles are computed by a closed-form, non-iterative solution of inverse kinematics of the mast combined with mathematical models of the cameras. The purely geometric camera-handoff technique involves the use of stereoscopic views of a target of interest in conjunction with the mast calibration.

Kim, Won↗

The Prediction Properties of Inverse and Reverse Regression for the Simple Linear Calibration Problem

The calibration of measurement systems is a fundamental but under-studied problem within industrial statistics. The origins of this problem go back to basic chemical analysis based on NIST standards. In today's world these issues extend to mechanical, electrical, and materials engineering. Often, these new scenarios do not provide "gold standards" such as the standard weights provided by NIST. This paper considers the classic "forward regression followed by inverse regression" approach. In this approach the initial experiment treats the "standards" as the regressor and the observed values as the response to calibrate the instrument. The analyst then must invert the resulting regression model in order to use the instrument to make actual measurements in practice. This paper compares this classical approach to "reverse regression," which treats the standards as the response and the observed measurements as the regressor in the calibration experiment. Such an approach is intuitively appealing because it avoids the need for the inverse regression. However, it also violates some of the basic regression assumptions.

Parker, Peter A.↗

Robot geometry calibration

Autonomous robot task execution requires that the end effector of the robot be positioned accurately relative to a reference world-coordinate frame. The authors present a complete formulation to identify the actual robot geometric parameters. The method applies to any serial link manipulator with arbitrary order and combination of revolute and prismatic joints. A method is also presented to solve the inverse kinematic of the actual robot model which usually is not a so-called simple robot. Experimental results performed by utilizing a PUMA 560 with simple measurement hardware are presented. As a result of this calibration a precision move command is designed and integrated into a robot language, RCCL, and used in the NASA Telerobot Testbed.

Hayati, Samad↗

Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3

Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.

Source record↗

Improving NASA GEOS Atmospheric CO2 Simulations by Calibrating CASA Surface Fluxes with an Empirical Sink

With the adoption of the Paris climate accord, efforts to monitor and understand both anthropogenic and natural carbon sources and sinks are increasing across the world. Given their low latency and global coverage, satellite observations of atmospheric carbon dioxide (CO2) are poised to make important contributions to this field. The combination of satellite data and high resolution global models can be used to monitor changes in carbon fluxes and to evaluate the consistency of nationally reported emissions estimates in support of multiple stakeholder communities. However, a consistent challenge to such work has been the high latency of surface carbon flux estimates, which are often not available for a year or more. This presentation describes the construction of surface carbon flux estimates meant to improve the near real time simulation of atmospheric CO2 with NASA's Goddard Earth Observing System (GEOS) general circulation model. The surface flux estimates begin with a collection of bottom-up fluxes which incorporate satellite measurements in their construction, e.g. vegetation indices in the Carnegie-Ames-Stanford Approach (CASA) and nighttime lights in the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). From there, we take the additional step of using an empirical sink to calibrate terrestrial net biospheric exchange (NBE) to estimated values from atmospheric inversion systems. This approach removes a known, systematic bias in predicted atmospheric mixing ratios. Using these fluxes in a free running simulation, the model is able to reproduce in situ measurements with the same skill as when it uses gridded fluxes from a flux inversion system. Using these fluxes as a prior in an assimilation system, e.g. one incorporating retrievals of column CO2 from the Orbiting Carbon Observatory 2 (OCO-2), allows the analysis to capture variability in CO2 on scales that would be missed otherwise. This approach supports NASA's capability to forecast atmospheric CO2 up to two weeks in advance by leveraging a GEOS system used to produce quasi-operational weather analyses and forecasts, providing a valuable new tool to the carbon monitoring research and applications communities.

Weir, B.↗

Quantitative determination of stratospheric aerosol characteristics

The author has identified the following significant results. The multiplicative scale factor needed to calibrate the recorded intensity is obtained by fitting the measured curve against a brightness model. The model was converted to the multispectral band scanner signal. Inversion of this measured signature is shown as the profile of attenuation coefficients versus altitude. Because of Gaussian noise, data were not measured directly. Data were fit with two exponential curves, one covering the lower altitude and the other covering the higher altitude. A twenty point curve was derived by selecting a data point and plotting its value from each of twenty adjacent scans. Noise from the lower altitudes was found to be erratic.

Tingey, D. L.↗