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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Delta Method Application for the Correlation of IR Detector Thermal Parasitic Loads with Statistically Accurate Results

The Linear Etalon Imaging Spectral Array (LEISA) is a cryogenic IR detector that is passively cooled below 110K. LEISA is part of the L’Ralph instrument, which is going on the Lucy mission, with planned flyby’s of the Trojan asteroids around 5.5 AU. One of the primary thermal challenges is to successfully quantify each significant parasitic heat flow value with statistical certainty.Simulation of flight-like thermal environments and correlation of thermal models is an important part of this challenge, which can be critical for thermally sensitive systems such as cryogenic detectors that are passively cooled. It is common practice during TVAC to achieve several thermal balance points and then to correlate several design variables in order to achieve the closest match to all balance points tested. This approach lends itself to high levels of uncertainty in the correlated values due to the cumulative effect of absolute temperature uncertainty and differences between the sensors used for the measurement. Accuracy can be improved with the use of more accurate sensors, by calibrating all sensors with respect to each other, and by using Zero-Q methodologies, all of which add cost and complexity to the test.The Delta Method uses the difference in temperature caused by the changes in the boundary conditions to calculate heat flows and/or thermal resistances across temperature differentials. This eliminates the problem of high uncertainties with absolute temperature measurements, and yields statistically accurate results down to the sensor resolution of 1mK at < 100K, by taking the sensor’s calibration errors out of the equation. During testing, this method relies on parametric variations around an initial balance point, by varying the boundary conditions of the different parasitic heat sources. The Delta Method, as well as its application on the LEISA thermal test, will be discussed in detail.

Daniel G. Bae↗
NASA NTRS1978

Delta method, an empirical drag buildup technique

An empirical drag correlation technique was developed from analysis of 19 subsonic and supersonic military aircraft and 15 advanced or supercritical airfoil configurations which can be applied in conceptual and advanced aircraft design activities. The Delta Method may be used for estimating the clean wing drag polar for cruise and maneuver conditions up to buffet onset, and to approximately Mach 2.0. This technique incorporates a unique capability of predicting the off-design performance of advanced or supercritical airfoil sections. The buffet onset limit may also be estimated. The method is applicable to wind tunnel models as well as to full scale configurations. This technique has been converted into a computer code for use on the IBM 360 and CDC 7600 computer facilities at NASA AMES. Results obtained using this method to predict known aircraft characteristics are good and agreement can be obtained within a degree of accuracy judged to be sufficient for the initial processes of preliminary design.

Feagin, R. C.↗
NASA NTRS1975

Dynamic delta method for trace gas analysis

Method has been developed in which measurements are made only over viscous flow range, eliminating fractionation before the molecular leak and problems due to surface elution.

Wood, G. M.↗
NASA NTRS2018

New Treatment of Strongly Anisotropic Scattering Phase Functions: The Delta-M+ Method

The treatment of strongly anisotropic scattering phase functions is still a challenge for accurate radiance computations. The new delta-M+ method resolves this problem by introducing a reliable, fast, accurate, and easy-to-use Legendre expansion of the scattering phase function with modified moments. Delta-M+ is an upgrade of the widely used delta-M method that truncates the forward scattering peak with a Dirac delta function, where the ‘‘+’’ symbol indicates that it essentially matches moments beyond the first M terms. Compared with the original delta-M method, delta-M+ has the same computational efficiency, but for radiance computations, the accuracy and stability have been increased dramatically.

Lin, Zhenyi↗
DOE OSTI2022

Robust and scalable uncertainty estimation with conformal prediction for machine-learned interatomic potentials

Abstract Uncertainty quantification (UQ) is important to machine learning (ML) force fields to assess the level of confidence during prediction, as ML models are not inherently physical and can therefore yield catastrophically incorrect predictions. Established a-posteriori UQ methods, including ensemble methods, the dropout method, the delta method, and various heuristic distance metrics, have limitations such as being computationally challenging for large models due to model re-training. In addition, the uncertainty estimates are often not rigorously calibrated. In this work, we propose combining the distribution-free UQ method, known as conformal prediction (CP), with the distances in the neural network’s latent space to estimate the uncertainty of energies predicted by neural network force fields. We evaluate this method (CP+latent) along with other UQ methods on two essential aspects, calibration, and sharpness, and find this method to be both calibrated and sharp under the assumption of independent and identically-distributed (i.i.d.) data. We show that the method is relatively insensitive to hyperparameters selected, and test the limitations of the method when the i.i.d. assumption is violated. Finally, we demonstrate that this method can be readily applied to trained neural network force fields with traditional and graph neural network architectures to obtain estimates of uncertainty with low computational costs on a training dataset of 1 million images to showcase its scalability and portability. Incorporating the CP method with latent distances offers a calibrated, sharp and efficient strategy to estimate the uncertainty of neural network force fields. In addition, the CP approach can also function as a promising strategy for calibrating uncertainty estimated by other approaches.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2016

Uncertainty Estimates of Psychoacoustic Thresholds Obtained from Group Tests

Adaptive psychoacoustic test methods, in which the next signal level depends on the response to the previous signal, are the most efficient for determining psychoacoustic thresholds of individual subjects. In many tests conducted in the NASA psychoacoustic labs, the goal is to determine thresholds representative of the general population. To do this economically, non-adaptive testing methods are used in which three or four subjects are tested at the same time with predetermined signal levels. This approach requires us to identify techniques for assessing the uncertainty in resulting group-average psychoacoustic thresholds. In this presentation we examine the Delta Method of frequentist statistics, the Generalized Linear Model (GLM), the Nonparametric Bootstrap, a frequentist method, and Markov Chain Monte Carlo Posterior Estimation and a Bayesian approach. Each technique is exercised on a manufactured, theoretical dataset and then on datasets from two psychoacoustics facilities at NASA. The Delta Method is the simplest to implement and accurate for the cases studied. The GLM is found to be the least robust, and the Bootstrap takes the longest to calculate. The Bayesian Posterior Estimate is the most versatile technique examined because it allows the inclusion of prior information.

Rathsam, Jonathan↗
NASA NTRS1987

Engineering calculations for the Delta S method of solving the orbital allotment problem

The method of calculating single-entry separation requirements for pairs of satellites is extended to include the interference on the top link as well as on the down link. Several heuristic models for analyzing the effects of shaped-beam antenna designs on required satellite separations are introduced and demonstrated with gain contour plots. The calculation of aggregate interference is extended to include the effects of up-link interference. The relationship between the single-entry C/I requirements, used in determining satellite separation constraints for various optimization procedures, and the aggregate C/I values of the resulting solutions is discussed.

Kohnhorst, P. A.↗
DOE OSTI2022

Machine Learning with Gradient-Based Optimization of Nuclear Waste Vitrification with Uncertainties and Constraints

Gekko is an optimization suite in Python that solves optimization problems involving mixed-integer, nonlinear, and differential equations. The purpose of this study is to integrate common Machine Learning (ML) algorithms such as Gaussian Process Regression (GPR), support vector regression (SVR), and artificial neural network (ANN) models into Gekko to solve data based optimization problems. Uncertainty quantification (UQ) is used alongside ML for better decision making. These methods include ensemble methods, model-specific methods, conformal predictions, and the delta method. An optimization problem involving nuclear waste vitrification is presented to demonstrate the benefit of ML in this field. ML models are compared against the current partial quadratic mixture (PQM) model in an optimization problem in Gekko. GPR with conformal uncertainty was chosen as the best substitute model as it had a lower mean squared error of 0.0025 compared to 0.018 and more confidently predicted a higher waste loading of 37.5 wt% compared to 34 wt%. The example problem shows that these tools can be used in similar industry settings where easier use and better performance is needed over classical approaches. Future works with these tools include expanding them with other regression models and UQ methods, and exploration into other optimization problems or dynamic control.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Response of hypoxia to future climate change is sensitive to methodological assumptions

Climate-induced changes in hypoxia are among the most serious threats facing estuaries, which are among the most productive ecosystems on Earth. Future projections of estuarine hypoxia typically involve long-term multi-decadal continuous simulations or more computationally efficient time slice and delta methods that are restricted to short historical and future periods. We make a first comparison of these three methods by applying a linked terrestrial–estuarine model to the Chesapeake Bay, a large coastal-plain estuary in the eastern United States. Results show that the time slice approach accurately captures the behavior of the continuous approach, indicating a minimal impact of model memory. However, increases in mean annual hypoxic volume by the mid-twenty-first century simulated by the delta approach (+ 19%) are approximately twice as large as the time slice and continuous experiments (+ 9% and + 11%, respectively), indicating an important impact of changes in climate variability. Our findings suggest that system memory and projected changes in climate variability, as well as simulation length and natural variability of system hypoxia, should be considered when deciding to apply the more computationally efficient delta and time slice methods.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Confidence Intervals for Laboratory Sonic Boom Annoyance Tests

Commercial supersonic flight is currently forbidden over land because sonic booms have historically caused unacceptable annoyance levels in overflown communities. NASA is providing data and expertise to noise regulators as they consider relaxing the ban for future quiet supersonic aircraft. One deliverable NASA will provide is a predictive model for indoor annoyance to aid in setting an acceptable quiet sonic boom threshold. A laboratory study was conducted to determine how indoor vibrations caused by sonic booms affect annoyance judgments. The test method required finding the point of subjective equality (PSE) between sonic boom signals that cause vibrations and signals not causing vibrations played at various amplitudes. This presentation focuses on a few statistical techniques for estimating the interval around the PSE. The techniques examined are the Delta Method, Parametric and Nonparametric Bootstrapping, and Bayesian Posterior Estimation.

Rathsam, Jonathan↗
NASA NTRS1987

Dual laser gyro test program

This paper addresses the results of a comparative test evaluation of two similar-sized but otherwise dissimilar ring laser gyroscopes (RLG's). Both units were tested side by side, with the input axes (IA's) parallel, on the same test table. This report describes the rationale and design factors considered important to the test objectives. Emphasis was placed upon the evaluation of the scale factor (SF) linearity, drift rate stability (short term and long term), and derived rate. Conclusions drawn were (1) that dual operation had an observable but insignificant effect on the test results, (2) that the benefits of dual operation outweighed the additional design and analysis efforts required at the outset of the program, and (3) that the performance characteristics of the two test articles were significantly different. The differences between the two test articles (1) led to suggestions which could direct one vendor toward obtaining improved performance and (2) resulted in the creation of a conceptually new method (DELTA TIME-COUNT histogram) for quickly assessing the quality of laser gyros (or any digital sensor device for that matter).

Jones, Malcolm E.↗
NASA NTRS1993

Instrumentation for Measurement of Gas Permeability of Polymeric Membranes

A mass spectrometric 'Dynamic Delta' method for the measurement of gas permeability of polymeric membranes has been developed. The method is universally applicable for measurement of the permeability of any gas through polymeric membrane materials. The usual large sample size of more than 100 square centimeters required for other methods is not necessary for this new method which requires a size less than one square centimeter. The new method should fulfill requirements and find applicability for industrial materials such as food packaging, contact lenses and other commercial materials where gas permeability or permselectivity properties are important.

Upchurch, Billy T.↗