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At least 415 records · Page 23

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DOE OSTI2025

A theoretical kinetic study of ĊH 3 + ṄH 2 : From electronic structure to NH 3 /CH 4 combustion modelling implications

Carbon–nitrogen interaction reactions play an important role in governing the reactivity of ammonia blended fuels. However, there remains uncertainties regarding their detailed reaction pathways and rate constants, hampering the development of high-fidelity chemical kinetic models. In this study, the kinetics of ĊH 3 + ṄH 2 , a key C–N interaction reaction in ammonia/methane blend combustion have been investigated. The potential energy surface has been explored using the high-level ANL0F method, yielding highly accurate stationary point energies that agree with ATcT values within 0.1 kcal mol –1 . Variable reaction coordinate transition state theory is used to treat the barrierless association and decomposition reaction channels, based on directly sampled radical-radical interaction energies at the CASPT2-F12(2e,2o)/cc-pVTZ-F12 level of theory. The minimum transitional mode numbers of states obtained are then coupled with the RRKM/master equation to calculate temperature- and pressure-dependent rate constants. Our a priori calculations capture available experimental measurements from the literature very well. The calculated rate constants have been incorporated into an NH 3 /CH 4 chemical kinetic model currently under development at the University of Galway. The effect of the updated kinetic data for ĊH 3 + ṄH 2 on model predicted NH 3 /CH 4 fuel reactivity is elucidated.

ab initio↗

NASA NTRS2008

Similarity Metrics for Closed Loop Dynamic Systems

To what extent and in what ways can two closed-loop dynamic systems be said to be "similar?" This question arises in a wide range of dynamic systems modeling and control system design applications. For example, bounds on error models are fundamental to the controller optimization with modern control design methods. Metrics such as the structured singular value are direct measures of the degree to which properties such as stability or performance are maintained in the presence of specified uncertainties or variations in the plant model. Similarly, controls-related areas such as system identification, model reduction, and experimental model validation employ measures of similarity between multiple realizations of a dynamic system. Each area has its tools and approaches, with each tool more or less suited for one application or the other. Similarity in the context of closed-loop model validation via flight test is subtly different from error measures in the typical controls oriented application. Whereas similarity in a robust control context relates to plant variation and the attendant affect on stability and performance, in this context similarity metrics are sought that assess the relevance of a dynamic system test for the purpose of validating the stability and performance of a "similar" dynamic system. Similarity in the context of system identification is much more relevant than are robust control analogies in that errors between one dynamic system (the test article) and another (the nominal "design" model) are sought for the purpose of bounding the validity of a model for control design and analysis. Yet system identification typically involves open-loop plant models which are independent of the control system (with the exception of limited developments in closed-loop system identification which is nonetheless focused on obtaining open-loop plant models from closed-loop data). Moreover the objectives of system identification are not the same as a flight test and hence system identification error metrics are not directly relevant. In applications such as launch vehicles where the open loop plant is unstable it is similarity of the closed-loop system dynamics of a flight test that are relevant.

Whorton, Mark S.↗

NASA NTRS2002

Dynamic Stability of Uncertain Laminated Beams Under Subtangential Loads

Because of the inherent complexity of fiber-reinforced laminated composites, it can be challenging to manufacture composite structures according to their exact design specifications, resulting in unwanted material and geometric uncertainties. In this research, we focus on the deterministic and probabilistic stability analysis of laminated structures subject to subtangential loading, a combination of conservative and nonconservative tangential loads, using the dynamic criterion. Thus a shear-deformable laminated beam element, including warping effects, is derived to study the deterministic and probabilistic response of laminated beams. This twenty-one degrees of freedom element can be used for solving both static and dynamic problems. In the first-order shear deformable model used here we have employed a more accurate method to obtain the transverse shear correction factor. The dynamic version of the principle of virtual work for laminated composites is expressed in its nondimensional form and the element tangent stiffness and mass matrices are obtained using analytical integration The stability is studied by giving the structure a small disturbance about an equilibrium configuration, and observing if the resulting response remains small. In order to study the dynamic behavior by including uncertainties into the problem, three models were developed: Exact Monte Carlo Simulation, Sensitivity Based Monte Carlo Simulation, and Probabilistic FEA. These methods were integrated into the developed finite element analysis. Also, perturbation and sensitivity analysis have been used to study nonconservative problems, as well as to study the stability analysis, using the dynamic criterion.

Goyal, Vijay K.↗

NASA NTRS2006

Observing Ice in Clouds from Space

There are many satellite observations of cloud top properties and the liquid and rain content of clouds, however, we do not yet quantitatively understand the processes that control the water budget of the upper troposphere where ice is the predominant phase, and how these processes are linked to precipitation processes and the radiative energy budget. The ice in clouds in the upper troposphere either melts into rain or is detrained, and persists, as cirrus clouds affecting the hydrological and energy cycle, respectively. Fully modeling the Earth's climate and improving weather and climate forecasts requires accurate satellite measurements of various cloud properties at the temporal and spatial scales of cloud processes. These properties include cloud horizontal and vertical structure, cloud water content and some measure of particle sizes and shapes. The uncertainty in knowledge of these ice characteristics is reflected in the large discrepancies in model simulations of the upper tropospheric water budget. Model simulations are sensitive to the partition of ice between precipitation and outflow processes, i.e., to the parameterization of ice clouds and ice processes. One barrier to achieving accurate global ice cloud properties is the lack of adequate observations at millimeter and submillimeter wavelengths (183-874 GHz). Recent advances in instrumentation have allowed for the development and implementation of an airborne submillimeter-wave radiometer. The brightness temperatures at these frequencies are especially sensitive to cirrus ice particle sizes (because they are comparable to the wavelength). This allows for more accurate ice water path estimates when multiple channels are used to probe into the cloud layers. Further, submillimeter wavelengths offer simplicity in the retrieval algorithms because they do not probe into the liquid and near surface portions of clouds, thus requiring only one term of the radiative transfer equation (ice scattering) to relate brightness temperatures to ice. The next step is a satellite mission designed to acquire global Earth radiance measurements in the submillimeter-wave region, thus bridging the measurement gap between microwave sounders and shorter-wavelength infrared and visible sensors. This presentation provides scientific justification and an approach to measuring ice water path and particle size from a satellite platform that spans a range encompassing both the hydrologically active and radiatively active components of cloud systems.

Ackerman, S.↗

NASA NTRS1984

Composition, Structure and Evolution of Uranian and Neptunian Satellites

Large uncertainties in the current estimated densities of all of these satellites prevent detailed modeling or predictions. Nevertheless, current evidence suggests that at least Titania and Oberon might have anomalously high densities of 2-39 cm(-3), possibly requiring almost ice-free hydrated silicates or formation in a CO-rich environment, implying presence of CO-clathrate and a small ice/rock ratio. Trition and the four largest satellites of Uranus are massive enough to have undergone significant accretional heating and early differentiation; NH3-H2O volcanism; partial outgassing of CO, N2, Ch4; formation of dark surficial deposits of carbon-rich material obtained by UV irradiation of outgassed material; and, at least in the cases of Ariel and Triton, a possibility of weak ongoing icy volcanic activity. Triton may be the largest captured body in the solar system, with an unusual history and composition, including the possibility of substantial liquid or solid nitrogen obtained from either primordial NH3 photolysis or clathrate decomposition.

Stevenson, D. J.↗

DOE OSTI2020

Recent advances in the quantification of uncertainties in reaction theory

Uncertainty quantification has become increasingly more prominent in nuclear physics over the past several years. In few-body reaction theory, there are four main sources that contribute to the uncertainties in the calculated observables: the effective potentials, approximations made to the few-body problem, structure functions, and degrees of freedom left out of the model space. In this work, we illustrate some of the features that can be obtained when modern statistical tools are applied in the context of nuclear reactions. This work consists of a summary of the progress that has been made in quantifying theoretical uncertainties in this domain, focusing primarily on those uncertainties coming from the effective optical potential as well as their propagation within various reaction theories. We use, as the central example, reactions on the doubly-magic stable nucleus 40 Ca, namely neutron and proton elastic scattering and single-nucleon transfer 40 Ca(d,p) 41 Ca. First, we show different optimization schemes used to constrain the optical potential from differential cross sections and other experimental constraints; we then discuss how these uncertainties propagate to the transfer cross section, comparing two reaction theories. Finally, we finish by laying out our future plans.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

From noise to information: The transfer function formalism for uncertainty quantification in reconstructing the nuclear density

The neutron distribution of neutron-rich nuclei provides critical information on the structure of finite nuclei and neutron stars. Parity violating experiments—such as PREX and CREX—provide a clean and largely model-independent determination of neutron densities. Such experiments, however, are challenging and expensive, which is why sound statistical arguments are required to maximize the information gained. We introduce a new framework, the “transfer function formalism,” aimed at uncertainty quantification, model selection, and experimental design in the context of neutron densities. The transfer functions (TFs) are built analytically by expressing the linear response of the objective function (e.g., χ2) to small perturbations of the data. Using the TF formalism, we are able to analyze the expected overall uncertainty—quantified in terms of bias and variance—of the mean square radius and interior density of 48 Ca and 208 Pb. Using relativistic mean field models as a proxy for the weak-charge density—and assuming that a total of five measurements could be performed on the weak form factor of 48 Ca and 208 Pb—we identify the optimal models and experimental locations that minimize the uncertainty in the extraction of the radius and interior density. We also explore the use of the TF formalism to understand the influence of prior distributions for the model parameters, as well as the optimization of model hyperparameters not constrained by the data. Here,we establish how the choice of experimental locations and the model that is used can have a significant impact on the final uncertainties of the extracted quantities of interest. For challenging experiments such as CREX and PREX, a proper quantification of such uncertainties is critical. We have demonstrated how the TF formalism provides several advantages for this type of analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2002

Control Oriented Modeling and Validation of Aeroservoelastic Systems

Lightweight aircraft design emphasizes the reduction of structural weight to maximize aircraft efficiency and agility at the cost of increasing the likelihood of structural dynamic instabilities. To ensure flight safety, extensive flight testing and active structural servo control strategies are required to explore and expand the boundary of the flight envelope. Aeroservoelastic (ASE) models can provide online flight monitoring of dynamic instabilities to reduce flight time testing and increase flight safety. The success of ASE models is determined by the ability to take into account varying flight conditions and the possibility to perform flight monitoring under the presence of active structural servo control strategies. In this continued study, these aspects are addressed by developing specific methodologies and algorithms for control relevant robust identification and model validation of aeroservoelastic structures. The closed-loop model robust identification and model validation are based on a fractional model approach where the model uncertainties are characterized in a closed-loop relevant way.

Crowder, Marianne↗

NASA NTRS2002

Probabilistic Design Methodology and its Application to the Design of an Umbilical Retract Mechanism

A lot has been learned from past experience with structural and machine element failures. The understanding of failure modes and the application of an appropriate design analysis method can lead to improved structural and machine element safety as well as serviceability. To apply Probabilistic Design Methodology (PDM), all uncertainties are modeled as random variables with selected distribution types, means, and standard deviations. It is quite difficult to achieve a robust design without considering the randomness of the design parameters which is the case in the use of the Deterministic Design Approach. The US Navy has a fleet of submarine-launched ballistic missiles. An umbilical plug joins the missile to the submarine in order to provide electrical and cooling water connections. As the missile leaves the submarine, an umbilical retract mechanism retracts the umbilical plug clear of the advancing missile after disengagement during launch and retrains the plug in the retracted position. The design of the current retract mechanism in use was based on the deterministic approach which puts emphasis on factor of safety. A new umbilical retract mechanism that is simpler in design, lighter in weight, more reliable, easier to adjust, and more cost effective has become desirable since this will increase the performance and efficiency of the system. This paper reports on a recent project performed at Tennessee State University for the US Navy that involved the application of PDM to the design of an umbilical retract mechanism. This paper demonstrates how the use of PDM lead to the minimization of weight and cost, and the maximization of reliability and performance.

Onyebueke, Landon↗

NASA NTRS2012

The Influence of Boundary Layer Parameters on Interior Noise

Predictions of the wall pressure in the turbulent boundary of an aerospace vehicle can differ substantially from measurement due to phenomena that are not well understood. Characterizing the phenomena will require additional testing at considerable cost. Before expending scarce resources, it is desired to quantify the effect of the uncertainty in wall pressure predictions and measurements on structural response and acoustic radiation. A sensitivity analysis is performed on four parameters of the Corcos cross spectrum model: power spectrum, streamwise and cross stream coherence lengths and Mach number. It is found that at lower frequencies where high power levels and long coherence lengths exist, the radiated sound power prediction has up to 7 dB of uncertainty in power spectrum levels with streamwise and cross stream coherence lengths contributing equally to the total.

Palumbo, Daniel L.↗

DOE OSTI2026

Dark Matter Constraints from Small-Scale Cosmic Structure

Small-scale cosmic structure provides a powerful test of the fundamental nature of dark matter (DM). A wide range of DM models impact matter clustering on small scales, including warm, fuzzy, and (self-)interacting DM. In these scenarios, DM physics such as free-streaming, wave interference, and self/Standard Model interactions alter the abundance and internal structure of DM halos. Cosmological and astrophysical probes of nonlinear structure---including dwarf galaxies, strong lensing, the Lyman-$α$ forest, stellar streams, and high-redshift galaxies---are therefore sensitive to these effects. Here, we review DM constraints provided by small-scale structure, focusing on observables that probe scales smaller than $\sim 1~\mathrm{Mpc}$, which define the frontier of current measurements. We summarize how these constraints have been translated to limits on microphysical DM models, and we discuss key modeling uncertainties and observational systematics. Finally, we highlight the growing importance of probe combination and simulation-based inference for this field, and we overview upcoming observational facilities that will sharpen small-scale structure tests of DM physics.

Nadler, Ethan O. [UC, San Diego] (ORCID:0000000211↗

NASA NTRSDate not supplied

Arctic Amplification: Process Drivers and Sources of Uncertainty

Arctic amplification (AA) is a coupled atmosphere-sea ice-ocean process. This understanding has evolved from the early concept of AA, as a consequence of snow ice line progressions, through more than a century of research that has clarified the relevant processes and driving mechanisms of AA. The predictions made by early modeling studies, namely the fall/winter maximum, bottom-heavy structure, the prominence of surface albedo feedback, and the importance of stable stratification have withstood the scrutiny of multi-decadal observations and more complex models. Yet, the uncertainty in Arctic climate projections is larger than in any other region of the planet, making the assessment of high-impact, near-term regional changes difficult or impossible. Reducing this large spread in Arctic climate projections requires a quantitative process understanding. This presentation synthesizes current knowledge of AA and describes a set of recommendations to guide future research. It briefly reviews the history of AA science, summarizes observed Arctic changes, discusses modeling approaches and feedback diagnostics, and assesses the current understanding of the most relevant feedbacks to AA. These sections culminate in a conceptual model of the fundamental physical mechanisms causing AA and a collection of recommendations to accelerate progress towards reduced uncertainty in Arctic climate projections. Our conceptual model highlights the need to account for local feedback and remote process interactions within the context of the annual cycle to constrain projected AA.

Patrick C Taylor↗

DOE OSTI2023

Exploring density and strength variations in asteroid 16 Psyche’s composition with 3D hydrocode modeling of its deepest impact structure

Asteroid 16 Psyche is the largest metallic Main Belt Asteroid and is the subject of a forthcoming NASA mission. The composition of Psyche is still unknown and subject of recent debate. In particular, how much porosity is within Psyche, along with how much of Psyche consists of non-metallic versus metallic materials, are central questions to the issue of Psyche’s composition. If Psyche is indeed predominantly composed of metallic materials, it would need to have considerable porosity (~ 30%–50%) for a composition consistent with its expected bulk density (~ 3.7–4.1 g/cm). In this work, we vary the density and strength of Psyche by including uniform and layered fields of pseudo-microporosity, in addition to investigating the presence of macroscopic voids, i.e., spaces larger than the size of the simulation’s mesh cells, in rubble-pile configurations. Further, all configurations result in bulk densities within the uncertainties of measured values, however the strength of Psyche and the distribution of pseudo-pores are varied. Through 3D computational models of Psyche’s deepest impact structure, we show that Psyche’s composition is unlikely to contain only pseudo-microporosity. Rather, rubble pile structures, which include macroscopic voids, are shown to match the crater’s measured aspect ratio better than simulations of structures that included only pseudo-microporosity.

3D↗

DOE OSTI2020

ZPPR-15 Criticality Measurements

A reference critical configuration was established for each phase of the ZPPR-15 experimental program. The reference critical configuration for each phase corresponds to a configuration in which the measured excess reactivity was adjusted to a standard set of reporting conditions with an average reactor temperature of 293 K, a zero interface gap and all operational control rods parked 30 inches from the axial centerline of the core. The ZPPR staff published the measured excess reactivity and the statistical uncertainty in the measurement. In reality, the published uncertainty for each reference critical configuration is only a small component of the total uncertainty for that configuration. Additional uncertainties related measurement technique, configuration geometry and material compositions exist. The geometry and material composition uncertainties are the dominant uncertainties for ZPPR-15. A full uncertainty analysis was performed for each ZPPR-15 reference critical configuration. The significant uncertainties related to measurement technique, configuration geometry and material compositions were quantified, and a total uncertainty was derived for each reference critical configuration. The ZPPR-15 experimental records were used to create detailed as-built Monte Carlo models for the reference critical configurations established in ZPPR-15A loading 15, ZPPR-15B loading 88, ZPPR-15C loading 166 and ZPPR-15D loading 185. The as-built models neglect the small, non-uniform gap between matrix halves at full closure, any structures outside the matrix tubes and minor components, e.g., impurities, in some materials. The biases associated with the neglected items were quantified. The experimental value of keff and its associated uncertainty for each reference critical configuration were adjusted to account for biases introduced by items that are neglected in the as-built model for that configuration.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2015

Calibration of Predictor Models Using Multiple Validation Experiments

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Crespo, Luis G.↗

DOE OSTI2022

Data-driven based coordinated smart inverter control for distributed energy resources

Smart inverters (SI) for distributed energy resources (DER) are becoming popular since they have the ability to stabilize as well as restore the voltage and frequency of power systems. Aiming at establishing the mathematical models combined with SI control methods, multiple optimization methods are developed. However, the computational complexity of solving such a mathematical model with various uncertainties limits the real-time application of the SI control. To conquer this challenge, a data-driven-based SI control approach is developed to achieve coordinated control in the high penetration DER system. First, an optimization problem for maximizing the active power generation and minimizing the power loss is designed using the Volt/VAR control. To reduce the time consumption, the recurrent neural network (RNN) is proposed to model the relationship between the uncertainties and control actions during the offline site. The RNN with different sub-structures such as the long short-term memory cell and gated recurrent unit cell are included to enrich the diversity of features. In the last stage, different experiment comparisons, including multiple uncertainties maps and stateof- art machine learning methods, are conducted to verify the effectiveness of the proposed method based on the IEEE 123 bus power system. The results demonstrate that the proposed method can effectively achieve a rapid and coordinated control with a lower error rate.

Qiu, Wei↗

DOE OSTI2023

Nonparametric Inference for the Reproductive Rate in Generalized Compartmental Models

We develop a tractable nonparametric model for the time-varying reproductive rate of infectious diseases that combines the structure of a deterministic compartmental model and a stochastic model for incidence data. We use Bayesian inference to estimate, with uncertainty, the reproductive rate of the Coronavirus 2019 outbreak in the U.S. states of California, Florida, Michigan, New Mexico, New York, and Texas from January 2020 to March 2022. Employing the inferred reproductive rates, we estimate the posterior distribution of the time-varying reproduction numbers for each state. Compering the time-varying reproduction numbers across the states, we identify some epidemic waves, potentially driven from changes in human behavior and virus mutations.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1984

Radiation from accreting magnetized neutron stars

Some recent development on the understanding of accreting magnetized neutron stars are reviewed. A brief summary of the observations is given, on which current phenomenological models are based. The main part of this paper is a discussion of recent work by several groups on the radiative transfer problem in a strong magnetic field and its application to models of the structure and properties of self-consistent neutron star polar cap emission regions. The assumptions and uncertainties involved are discussed, recent progress is evaluated, and current and future problems are indicated.

Meszaros, P.↗