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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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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Quantifying uncertainty in machine learning for nuclear binding energy

Techniques from artificial intelligence and machine learning are increasingly employed in nuclear theory; however, the uncertainties that arise from the complex parameter manifold encoded by the neural networks are often overlooked. Epistemic uncertainties arising from training the same network multiple times for an ensemble of initial weight sets offer a first insight into the confidence of machine learning predictions, but they often come with a high computational cost. Instead, we apply a single-model uncertainty quantification method called Δ-UQ that gives epistemic uncertainties with one-time training. Here, we demonstrate our approach on a two-feature model of nuclear binding energies per nucleon with proton and neutron number pairs as inputs. We show that Δ-UQ can produce reliable and self-consistent epistemic uncertainty estimates and can be used to assess the degree of confidence in predictions made with deep neural networks.

Huang, Mengyao [Lawrence Livermore National Labora↗
DOE OSTI2024

Enhancing Solar Power Forecasting with Regularized Constrained Quantile Regression Averaging and Bootstrapping Techniques

Probabilistic solar power forecasting (SPF) plays an essential role in optimizing power-grid operations by quantifying the forecast uncertainty. To improve the accuracy and robustness of probabilistic SPF, this paper introduces the regularized constrained quantile regression averaging (rCQRA) method to combine outputs from multiple PSPF models. In addition, a bootstrapping method was used to quantify model uncertainty, providing insights into the reliability and significance of each ensemble component. To evaluate its efficacy, the proposed rCQRA method is used to integrate four PSPF methods. The resulting SPF models are trained and validated using a real-world six-year dataset from a rooftop solar plant in the USA. The performance of the proposed rCQRA method is evaluated and compared with two benchmark methods under three categories of weather conditions. It is shown that the rCQRA method has superior performance in its forecast reliability, sharpness, and accuracy.

Ensemble learning, probabilistic solar power forec↗
DOE OSTI2025

Understanding drivers and uncertainty in projected African precipitation

We investigate the drivers of projected summer precipitation changes and their uncertainties across Africa in the second half of the 21st century under the SSP2-4.5 and SSP5-8.5 scenarios using CMIP6 models. Our results reveal distinct regional precipitation changes, particularly under SSP5-8.5, with robust increases of 75%, 24%, and 17% over the Sahara, South Eastern Africa, and South Central Africa, respectively, and a decline of up to 5% over West Southern Africa (WSAF). In most regions, precipitation increases are driven by enhanced vertical thermodynamic processes associated with temperature-induced moisture increases and enhanced moisture convergence. In contrast, the WSAF decrease is associated with vertical dynamic processes driven by a weakening of the Hadley circulation’s ascending branch. Model uncertainty accounts for over 85% of total projection uncertainty across all regions and is largely due to subgrid-scale parameterizations. Overall, this study enhances our understanding of climate change impacts on African precipitation.

Taguela, Thierry N↗
NASA NTRS1984

An on-line equivalent system identification scheme for adaptive control

A prime obstacle to the widespread use of adaptive control is the degradation of performance and possible instability resulting from the presence of unmodeled dynamics. The approach taken is to explicitly include the unstructured model uncertainty in the output error identification algorithm. The order of the compensator is successively increased by including identified modes. During this model building stage, heuristic rules are used to test for convergence prior to designing compensators. Additionally, the recursive identification algorithm as extended to multi-input, multi-output systems. Enhancements were also made to reduce the computational burden of an algorithm for obtaining minimal state space realizations from the inexact, multivariate transfer functions which result from the identification process. A number of potential adaptive control applications for this approach are illustrated using computer simulations. Results indicated that when speed of adaptation and plant stability are not critical, the proposed schemes converge to enhance system performance.

Sliwa, S. M.↗
NASA NTRS1994

MME-based attitude dynamics identification and estimation for SAMPEX

A method is described for obtaining optimal attitude estimation algorithms for spacecraft lacking attitude rate measurement devices (rate gyros), and then demonstrated using actual flight data from the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) spacecraft. SAMPEX does not have on-board rate sensing, and relies on sun sensors and a three-axis magnetometer for attitude determination. Problems arise since typical attitude estimation is accomplished by filtering measurements of both attitude and attitude rates. Rates are nearly always sampled much more densely than are attitudes. Thus, the absence/loss of rate data normally reduces both the total amount of data available and the sampling density (in time) by a substantial fraction. As a result, the sensitivity of the estimates to model uncertainty and to measurement noise increases. In order to maintain accuracy in the attitude estimates, there is increased need for accurate models of the rotational dynamics. The proposed approach is based on the minimum model error (MME) optimal estimation strategy, which has been successfully applied to estimation of poorly modeled dynamic systems which are relatively sparsely and/or noisily measured. The MME estimates may be used to construct accurate models of the system dynamics (i.e. perform system model identification). Thus, an MME-based approach directly addresses the problems created by absence of attitude rate measurements.

Depena, Juan↗
NASA NTRS2001

A forward model-based validation of cardiovascular system identification

We present a theoretical evaluation of a cardiovascular system identification method that we previously developed for the analysis of beat-to-beat fluctuations in noninvasively measured heart rate, arterial blood pressure, and instantaneous lung volume. The method provides a dynamical characterization of the important autonomic and mechanical mechanisms responsible for coupling the fluctuations (inverse modeling). To carry out the evaluation, we developed a computational model of the cardiovascular system capable of generating realistic beat-to-beat variability (forward modeling). We applied the method to data generated from the forward model and compared the resulting estimated dynamics with the actual dynamics of the forward model, which were either precisely known or easily determined. We found that the estimated dynamics corresponded to the actual dynamics and that this correspondence was robust to forward model uncertainty. We also demonstrated the sensitivity of the method in detecting small changes in parameters characterizing autonomic function in the forward model. These results provide confidence in the performance of the cardiovascular system identification method when applied to experimental data.

NASA Discipline Cardiopulmonary↗
NASA NTRS2014

Validation of the 5th and 95th Percentile Hybrid III Anthropomorphic Test Device Finite Element Model

NASA spacecraft design requirements for occupant protection are a combination of the Brinkley criteria and injury metrics extracted from anthropomorphic test devices (ATD's). For the ATD injury metrics, the requirements specify the use of the 5th percentile female Hybrid III and the 95th percentile male Hybrid III. Furthermore, each of these ATD's is required to be fitted with an articulating pelvis and a straight spine. The articulating pelvis is necessary for the ATD to fit into spacecraft seats, while the straight spine is required as injury metrics for vertical accelerations are better defined for this configuration. The requirements require that physical testing be performed with both ATD's to demonstrate compliance. Before compliance testing can be conducted, extensive modeling and simulation are required to determine appropriate test conditions, simulate conditions not feasible for testing, and assess design features to better ensure compliance testing is successful. While finite element (FE) models are currently available for many of the physical ATD's, currently there are no complete models for either the 5th percentile female or the 95th percentile male Hybrid III with a straight spine and articulating pelvis. The purpose of this work is to assess the accuracy of the existing Livermore Software Technology Corporation's FE models of the 5th and 95th percentile ATD's. To perform this assessment, a series of tests will be performed at Wright Patterson Air Force Research Lab using their horizontal impact accelerator sled test facility. The ATD's will be placed in the Orion seat with a modified-advanced-crew-escape-system (MACES) pressure suit and helmet, and driven with loadings similar to what is expected for the actual Orion vehicle during landing, launch abort, and chute deployment. Test data will be compared to analytical predictions and modelling uncertainty factors will be determined for each injury metric. Additionally, the test data will be used to further improve the FE model, particularly in the areas of the ATD neck components, harness, and suit and helmet effects.

Lawrence, C.↗
NASA NTRS1982

Geoid height-age relation from Seasat altimeter profiles across the Mendocino Fracture Zone

Twenty-eight Seasat altimeter profiles crossing the Mendocino Fracture Zone are used together with seafloor ages determined from magnetic lineations to estimate the change in oceanic geoid height with age, between ages of 15 and 135 m.y. An unbiased estimate of the overall geoid offset along each profile is determined from a least-squares fit of the along-track derivative of the geoid to the geoid slope predicted from a simple two-layer gravitational edge effect model. Uncertainties based upon the statistical properties of each profile are also determined. A geoid slope-age relation is constructed by normalizing the geoid offsets and uncertainties by the age offsets. The results are in agreement with geoid slope-age relations determined from symmetrically spreading ridges (Sandwell and Schubert, 1980). However, the fracture zone estimates have smaller uncertainties and show less scatter. A comparison of these results with the geoid slope-age prediction of the boundary layer cooling model shows that the thermal structure begins to deviate from this model at an early age (20-40 m.y.). A plate cooling model with a thickness of 125 km is most compatible with the geoid slope-age estimates, although significant deviations occur; these may indicate that the lithospheric thermal structure is not entirely age dependent.

Sandwell, D. T.↗
NASA NTRS1985

On the geographical correlation of orbit error

The orbit accuracies needed to support the global crustal dynamics project and recent satellite altimeter missions have placed unique demands on the data analysis and orbit analysis systems. These demands include accurate and well distributed observations, improved computational techniques and substantial enhancements in the force models which represent the satellite's motion. For example, the satellite altimeter mission (TOPEX), whose objectives will be: (1) to measure the time variable ocean surface topography, and (2) to demonstrate the ability to map the general ocean circulation, requires that the radial component of the satellite's orbit be known with an rms accuracy of 13 cm for the three year mission lifetime. The primary force model uncertainty which limits the contemporary orbit computation accuracy is the inaccuracy in the values assigned to the spherical harmonic coefficients used to model the Earth's gravity field.

Tapley, B. D.↗
NASA NTRS1995

Use of nonlinear identification in robust attitude and attitude rate estimation for SAMPEX

A method is described for obtaining optimal attitude estimation/identification algorithms for spacecraft lacking attitude rate measurement devices (rate gyros), and then demonstrated using actual flight data from the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) spacecraft. SAMPEX does not have on-board rate sensing, and relies on sun sensors and a three-axis magnetometer for attitude determination. The absence of rate data normally reduces both the total amount of data available and the sampling density (in time) by a substantial fraction. In addition, attitude data is occasionally unavailable (for example, during sun occultation). As a result, the sensitivity of the estimates to model uncertainty and to measurement noise increases. In order to maintain accuracy in the attitude estimates, there is an increased need for accurate models of the rotational dynamics. The Minimum Model Error(MME)/Least Square Correlation(LSC) algorithm accurately identifies an improved model for SAMPEX to be used during periods of complete data loss or extreme noise. The model correction is determined by estimating only one orbit(the identification pass) just prior to the assumed data loss(the prediction pass). The MME estimator correctly predicted the states during the identification phase, but more importantly determines the necessary model correction trajectory, d(t). The LSC algorithm is then used to find this trajectory's functional form, H(x(t)). The results show significant improvement of the new corrected model's attitude estimates as compared to the original uncorrected model's estimates. The possible functional form of the correction term is limited at this point in the study to functions strictly of the estimated states. The results, however, strongly suggest that functions based on the relative position of the satellite may also be possible candidates for future consideration.

Mook, D. Joseph↗
NASA NTRS2010

A Near-Term Concept for Trajectory Based Operations with Air/Ground Data Link Communication

An operating concept and required system components for trajectory-based operations with air/ground data link for today's en route and transition airspace is proposed. Controllers are fully responsible for separation as they are today, and no new aircraft equipage is required. Trajectory automation computes integrated solutions to problems like metering, weather avoidance, traffic conflicts and the desire to find and fly more time/fuel efficient flight trajectories. A common ground-based system supports all levels of aircraft equipage and performance including those equipped and not equipped for data link. User interface functions for the radar controller's display make trajectory-based clearance advisories easy to visualize, modify if necessary, and implement. Laboratory simulations (without human operators) were conducted to test integrated operation of selected system components with uncertainty modeling. Results are based on 102 hours of Fort Worth Center traffic recordings involving over 37,000 individual flights. The presence of uncertainty had a marginal effect (5%) on minimum-delay conflict resolution performance, and windfavorable routes had no effect on detection and resolution metrics. Flight plan amendments and clearances were substantially reduced compared to today s operations. Top-of-descent prediction errors are the largest cause of failure indicating that better descent predictions are needed to reliably achieve fuel-efficient descent profiles in medium to heavy traffic. Improved conflict detections for climbing flights could enable substantially more continuous climbs to cruise altitude. Unlike today s Conflict Alert, tactical automation must alert when an altitude amendment is entered, but before the aircraft starts the maneuver. In every other failure case tactical automation prevented losses of separation. A real-time prototype trajectory trajectory-automation system is running now and could be made ready for operational testing at an en route Center in 1-2 years.

McNally, David↗
NASA NTRS2011

Ares I-X Flight Test Validation of Control Design Tools in the Frequency-Domain

A major motivation of the Ares I-X flight test program was to Design for Data, in order to maximize the usefulness of the data recorded in support of Ares I modeling and validation of design and analysis tools. The Design for Data effort was intended to enable good post-flight characterizations of the flight control system, the vehicle structural dynamics, and also the aerodynamic characteristics of the vehicle. To extract the necessary data from the system during flight, a set of small predetermined Programmed Test Inputs (PTIs) was injected directly into the TVC signal. These PTIs were designed to excite the necessary vehicle dynamics while exhibiting a minimal impact on loads. The method is similar to common approaches in aircraft flight test programs, but with unique launch vehicle challenges due to rapidly changing states, short duration of flight, a tight flight envelope, and an inability to repeat any test. This paper documents the validation effort of the stability analysis tools to the flight data which was performed by comparing the post-flight calculated frequency response of the vehicle to the frequency response calculated by the stability analysis tools used to design and analyze the preflight models during the control design effort. The comparison between flight day frequency response and stability tool analysis for flight of the simulated vehicle shows good agreement and provides a high level of confidence in the stability analysis tools for use in any future program. This is true for both a nominal model as well as for dispersed analysis, which shows that the flight day frequency response is enveloped by the vehicle s preflight uncertainty models.

Johnson, Matthew↗
NASA NTRS2016

Improved Analysis of GW150914 Using a Fully Spin-Precessing Waveform Model

This paper presents updated estimates of source parameters for GW150914, a binary black-hole coalescence event detected by the Laser Interferometer Gravitational-wave Observatory (LIGO) in 2015 [Abbott et al. Phys. Rev. Lett. 116, 061102 (2016).]. Abbott et al. [Phys. Rev. Lett. 116, 241102 (2016).] presented parameter estimation of the source using a 13-dimensional, phenomenological precessing-spin model (precessing IMRPhenom) and an 11-dimensional nonprecessing effective-one-body (EOB) model calibrated to numerical-relativity simulations, which forces spin alignment (nonprecessing EOBNR). Here, we present new results that include a 15-dimensional precessing-spin waveform model (precessing EOBNR) developed within the EOB formalism. We find good agreement with the parameters estimated previously [Abbott et al. Phys. Rev. Lett. 116, 241102 (2016).], and we quote updated component masses of 35(+5)(-3) solar M; and 30(+3)(-4) solar M; (where errors correspond to 90 symmetric credible intervals). We also present slightly tighter constraints on the dimensionless spin magnitudes of the two black holes, with a primary spin estimate is less than 0.65 and a secondary spin estimate is less than 0.75 at 90% probability. Abbott et al. [Phys. Rev. Lett. 116, 241102 (2016).] estimated the systematic parameter-extraction errors due to waveform-model uncertainty by combining the posterior probability densities of precessing IMRPhenom and nonprecessing EOBNR. Here, we find that the two precessing-spin models are in closer agreement, suggesting that these systematic errors are smaller than previously quoted.

Abbott, B. P.↗
DOE OSTI2021

Deep Reinforcement Scheduling of Energy Storage Systems for Real-time Voltage Regulation in Unbalanced LV Networks with High PV Penetration

The ever-growing higher penetration of distributed energy resources (DERs) in low-voltage (LV) distribution systems brings both opportunities and challenges to voltage support and regulation. This paper proposes a deep reinforcement learning (DRL)-based scheduling scheme of energy storage systems (ESSs) to mitigate system voltage deviations in unbalanced LV distribution networks. The ESS-based voltage regulation problem is formulated as a multi-stage quadratic stochastic program, with the objective of minimizing the expected total daily voltage regulation cost while satisfying operational constraints. While existing voltage regulation methods are mostly focused on onetime- step control, this paper explores a day-horizon systemwide voltage regulation problem. In other words, the size of action and state spaces are extremely high-dimensional and need to be delicately handled. Furthermore, in order to overcome the difficulty of modeling uncertainties and develop a realtime solution, a learn-to-schedule feedback control framework is proposed by adapting the problem to a model-free DRL setting. The proposed algorithm is tested on a customized 6-bus system and a modified IEEE 34-bus system. Simulation results validate the effectiveness and near-optimality of voltage regulation by ESS in comparison with a deterministic quadratic program solution.

Wang, Shengyi↗
NASA NTRS1981

Practical robustness measures in multivariable control system analysis

The robustness of the stability of multivariable linear time invariant feedback control systems with respect to model uncertainty is considered using frequency domain criteria. Available robustness tests are unified under a common framework based on the nature and structure of model errors. These results are derived using a multivariable version of Nyquist's stability theorem in which the minimum singular value of the return difference transfer matrix is shown to be the multivariable generalization of the distance to the critical point on a single input, single output Nyquist diagram. Using the return difference transfer matrix, a very general robustness theorem is presented from which all of the robustness tests dealing with specific model errors may be derived. The robustness tests that explicitly utilized model error structure are able to guarantee feedback system stability in the face of model errors of larger magnitude than those robustness tests that do not. The robustness of linear quadratic Gaussian control systems are analyzed.

Lehtomaki, N. A.↗
NASA NTRS2015

Assessing Disparities of Dengue Virus Transmission Risk across the US-Mexican Border Using a Climate Driven Vector-Epidemiological Model

Dengue fever is a mosquito‐borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Although transmission regularly occurs along the border region in Mexico, dengue virus transmission in bordering Arizona has not occurred. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input and Daymet for temperature and supplemental precipitation input, we modeled dengue transmission along a US‐Mexico transect using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Model runs were performed for 5 cities in Sonora, Mexico and southern Arizona. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. For cities with reported dengue case data, the top model simulations that best reproduced dengue case numbers were retained and their parameter values were extracted for comparison. These parameter values were used to run simulations in areas where dengue virus transmission does not occur or where dengue fever case data was unavailable. Additional model runs were performed to reveal how changes in climate or parameter values could alter transmission risk along the transect. The relative influence of climate variability and model parameters on dengue virus transmission is assessed to help public health workers prepare location specific infection prevention strategies.

Morin, Cory↗
DOE OSTI2021

Estimating uncertainty: A Bayesian approach to modelling photosynthesis in C3 leaves

The Farquhar-von Caemmerer-Berry (FvCB) model is extensively used to model pho-tosynthesis from gas exchange measurements. Since its publication, many methods have been developed to measure, or more accurately estimate, parameters of this model. Here, we have created a tool that uses Bayesian statistics to fit photosyn-thetic parameters using concurrent gas exchange and chlorophyll fluorescence mea-surements whilst evaluating the reliability of the parameter estimation. We have tested this tool on synthetic data and experimental data from rice leaves. Our results indicate that reliable parameter estimation can be achieved whilst only keeping one parameter, Km, that is, Michaelis constant for CO2 by Rubisco, prefixed. Additionally, we show that including detailed low CO2 measurements at low light levels increases reliability and suggests this as a new standard measurement protocol. By providing an estimated distribution of parameter values, the tool can be used to evaluate the quality of data from gas exchange and chlorophyll fluorescence measurement proto-cols. Compared to earlier model fitting methods, the use of a Bayesian statistics-based tool minimizes human interaction during fitting, reducing the subjectivity which is essential to most existing tools. A user friendly, interactive Bayesian tool script is provided.

Bayesian statistics, leaf photosynthesis, mesophyl↗
DOE OSTI2026

A Joint Search for Muon Neutrino Disappearance with the Short-Baseline Neutrino Program Using the SPINE Deep Learning-Based Reconstruction Package

We present the status of a joint search for muon neutrino disappearance in the Booster Neutrino Beam at Fermilab using the Short-Baseline Neutrino (SBN) Program's two-detector configuration, SBND and ICARUS. Charged-current interactions consistent with muon neutrinos and containing only a muon and at least one proton in the final state are reconstructed and selected using the SPINE deep learning-based particle reconstruction package. To exploit proton multiplicity information and enhance sensitivity to modeling effects, the selected sample is partitioned into exclusive channels with exactly one reconstructed proton and with more than one reconstructed proton. Comprehensive systematic uncertainties from the neutrino flux, interaction, and detector response are incorporated into the analysis, and the coverage of these systematic uncertainty models is validated using data from both detectors, including checks of near-far consistency in key kinematic and topology-sensitive observables. This analysis is intended for inclusion in SBN's first oscillation result.

Mueller, Justin [Fermilab]↗