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Results for “parametric processes”

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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

High-voltage dc power processing thermal control and packaging techniques

The power processor operates in several modes, delivering up to 100 amperes of regulated electrical power, operating at input voltages to 375 volts with outputs controlled by an integral microprocessor. Several alternative packaging concepts are discussed and evaluated. High-voltage design applications, power stage interconnection and EMI considerations are also discussed. Preliminary thermal analyses were performed and the results presented for each conceptual approach with parametric study results given for the selected concept.

Chapter, J. J.↗
DOE OSTI2023

SDSS-IV MaNGA: The incidence of major mergers in type I and II AGN host galaxies in the DR15 sample

We present a study on the incidence of major mergers and their impact on the triggering of nuclear activity in 47 type I and 236 type II optically selected AGN from the MaNGA DR15 sample. From an estimate of non-parametric image predictors (Gini, M_20, concentration (C), asymmetry (A), clumpiness (S), Sérsic index (n), and shape asymmetry ()) using the SDSS images, in combination with a Linear Discriminant Analysis Method, we identified major mergers and merger stages. We reinforced our results by looking for bright tidal features in our post-processed SDSS and DESI legacy images. We find a statistically significant higher incidence of major mergers of 29 per cent ± 3 per cent in our type I+II AGN sample compared to 22 per cent ± 0.8 per cent for a non-AGN sample matched in redshift, stellar mass, colour, and morphological type, finding also a prevalence of post-coalescence (51 per cent ± 5 per cent) over pre-coalescence (23 per cent ± 6 per cent) merger stages. The levels of AGN activity among our massive major mergers are similar to those reported in other works using [O iii] tracers. However, similar levels are produced by our AGN-galaxies hosting stellar bars, suggesting that major mergers are important promoters of nuclear activity but are not the main nor the only mechanism behind the AGN triggering. The tidal strength parameter Q was considered at various scales looking for environmental differences that could affect our results on the merger incidence, finding non-significant differences. Finally, the H-H β diagram could be used as an empirical predictor for the flux coming from an AGN source, useful to correct photometric quantities in large AGN samples emerging from surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Modeling noise in global Mølmer-Sørensen interactions applied to quantum approximate optimization

Many-qubit Mølmer-Sørensen (MS) interactions applied to trapped ions offer unique capabilities for quantum information processing, with applications including quantum simulation and the quantum approximate optimization algorithm (QAOA). Here, we develop a physical model to describe many-qubit MS interactions under four sources of experimental noise: vibrational mode frequency fluctuations, laser power fluctuations, thermal initial vibrational states, and state preparation and measurement errors. The model parametrizes these errors from simple experimental measurements, without free parameters. Herein, we validate the model in comparison with experiments that implement sequences of MS interactions on two 171 Yb + ions. The model shows reasonable agreement after several MS interactions as quantified by the reduced chi-squared statistic $χ^{2}_{red}$≈2. As an application we examine MaxCut QAOA experiments on three and six ions. The experimental performance is quantified by approximation ratios that are 91% and 83% of the optimal theoretical values. Our model predicts $0.93^{+0.03}_{-0.02}$ and $0.95^{+0.04}_{-0.03}$, respectively, with disagreement in the latter value attributable to secondary noise sources beyond those considered in our analysis. With realistic experimental improvements to reduce measurement error and radial trap frequency variations, the model achieves approximation ratios that are 99% of the optimal. Incorporating these improvements into future experiments is expected to reveal new aspects of noise for future modeling and experimental improvements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Multichannel spectral estimation in acoustics: A state-space approach

Spectral estimation is a necessary methodology to analyze the frequency content of noisy data sets especially in acoustic applications. Many spectral techniques have evolved starting with the classical Fourier transform methods based on the well-known Wiener-Khintchine relationship relating the covariance-to-spectral density as a transform pair culminating with more elegant model-based parametric techniques that apply prior knowledge of the data to produce a high-resolution spectral estimate. Multichannel spectral representations are a class of both nonparametric, as well as parametric, estimators that provide improved spectral estimates. In any case, classical nonparametric multichannel techniques can provide reasonable estimates when coupled with peak-peaking methods as long as the signal levels are reasonably high. Furthermore, parametric multichannel methods can perform quite well in low signal level environments even when applying simple peak-picking techniques. In this paper, the performance of both nonparametric (periodogram) and parametric (state-space) multichannel spectral estimation methods are investigated when applied to both synthesized noisy structural vibration data as well as data obtained from a sounding rocket flight. It is demonstrated that for the multichannel problem, state-space techniques provide improved performance, offering a parametric alternative compared to classical methods.

42 ENGINEERING↗
DOE OSTI2021

Rheological Characterization of Biomass Feedstock for Alternative Energy Applications

With the increased necessity of alternative energy resources, bulk feedstock biomass materials were characterized with the purpose of replacing depleting energy supplies such as fossil fuels and other nonrenewable energy sources. Residual organic waste material (biomass) left over from agricultural processing and handling systems was recycled, and further investigated for renewable energy use. Understanding the scope of flowability for biomass material yielded more efficient, and economical crop harvesting, transporting, and storing method design for the agricultural industry. The effects of moisture on bulk solid flowability was investigated using a variety of parametric testing methods that measure basic flowability energy, and other properties such as compressibility and material resistance. In an industry where organic material is a wasteful byproduct, converting this biomass material into a new energy source and streamlining efficiently for innovative agricultural development supports a clean, renewable energy approach to everyday nonrenewable energy uses, such as oil, propane, and coal. As observed from the repeatable results from the investigated rheological material properties, biomass is an incredibly diverse material that requires modern engineering solutions to revolutionize biomass into a renewable energy source. Biomass will decarbonize petroleum (nonrenewable) derived fuels and chemicals, yielding recyclable carbon. This push to replace fossil fuels with recycled carbon is ideal because of the abundant, renewable, and otherwise agricultural waste of corn stover material. Decarburization, and reduction of C0 2 emissions reduces the effects of global warming.

09 BIOMASS FUELS↗
DOE OSTI2025

The Poisson tensor completion non-parametric differential entropy estimator

We introduce the Poisson tensor completion (PTC) estimator, a non-parametric differential entropy estimator. The PTC estimator leverages inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial Poisson process. The Poisson tensor decomposition leads to a completion of the intensity measure over all bins—including those containing few to no samples—and leads to our proposed PTC differential entropy estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values and so can be safely used directly in entropy estimation. Our estimator is the first tensor-based estimator that exploits the underlying spatial Poisson process related to the histogram explicitly when estimating the probability density with low-rank tensor decompositions for the purpose of tensor completion. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

42 ENGINEERING↗
DOE OSTI2023

Real-Time Krylov Theory for Quantum Computing Algorithms

Quantum computers provide new avenues to access ground and excited state properties of systems otherwise difficult to simulate on classical hardware. New approaches using subspaces generated by real-time evolution have shown efficiency in extracting eigenstate information, but the full capabilities of such approaches are still not understood. In recent work, we developed the variational quantum phase estimation (VQPE) method, a compact and efficient real-time algorithm to extract eigenvalues on quantum hardware. Here we build on that work by theoretically and numerically exploring a generalized Krylov scheme where the Krylov subspace is constructed through a parametrized real-time evolution, which applies to the VQPE algorithm as well as others. We establish an error bound that justifies the fast convergence of our spectral approximation. We also derive how the overlap with high energy eigenstates becomes suppressed from real-time subspace diagonalization and we visualize the process that shows the signature phase cancellations at specific eigenenergies. We investigate various algorithm implementations and consider performance when stochasticity is added to the target Hamiltonian in the form of spectral statistics. To demonstrate the practicality of such real-time evolution, we discuss its application to fundamental problems in quantum computation such as electronic structure predictions for strongly correlated systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1981

Development status of a preprototype water electrolysis subsystem

A preprototype water electrolysis subsystem was designed and fabricated for NASA's advanced regenerative life support program. A solid polymer is used for the cell electrolyte. The electrolysis module has 12 cells that can generate 5.5 kg/day of oxygen for the metabolic requirements of three crewmembers, for cabin leakage, and for the oxygen and hydrogen required for carbon dioxide collection and reduction processes. The subsystem can be operated at a pressure between 276 and 2760 kN/sq m and in a continuous constant-current, cyclic, or standby mode. A microprocessor is used to aid in operating the subsystem. Sensors and controls provide fault detection and automatic shutdown. The results of development, demonstration, and parametric testing are presented. Modifications to enhance operation in an integrated and manned test are described. Prospective improvements for the electrolysis subsystem are discussed.

Martin, R. B.↗
NASA NTRS1993

Lithium D-cell study

The purpose of this contract is to evaluate parametrically the effects of various factors including the electrolyte type, electrolyte concentration, depolarizer type, and cell configuration on lithium cell electrical performance and safety. This effort shall allow for the selection and optimization of cell design for future NASA applications while maintaining close ties with WGL's continuous improvements in manufacturing processes and lithium cell design. Taguchi experimental design techniques are employed in this task, and allow for a maximum amount of information to be obtained while requiring significantly less cells than if a full factorial design were employed. Acceptance testing for this task is modeled after the NASA Document EP5-83-025, Revision C, for cell weights, OCV's and load voltages. The performance attributes that are studied in this effort are fresh capacity and start-up characteristics evaluated at two rates and two temperatures, shelf-life characteristics including start-up and capacity retention, and iterative microcalorimetry measurements. Abuse testing includes forced over discharge at two rates with and without diode protection, temperature tolerance testing, and shorting tests at three rates with the measurement of heat generated during shorting conditions.

Size, P.↗
DOE OSTI2024

Confirming X-ray Parametric Down Conversion by Time-Energy Correlation

We present measurements of X-ray Parametric Down Conversion at the Advanced Photon Source synchrotron facility. Using an incoming pump beam at 22 keV, we observe the simultaneous, elastic emission of down-converted photon pairs generated in a diamond crystal. The pairs are detected using high count rate silicon drift detectors with low noise. Production by down-conversion is confirmed by measuring time-energy correlations in the detector signal, where photon pairs within an energy window ranging from 10 to 12 keV are only observed at short time differences. By systematically varying the crystal misalignment and detector positions, we obtain results that are consistent with the constant total of the down-converted signal. Our maximum rate of observed pairs was 130 /hour, corresponding to a conversion efficiency for the down-conversion process of 5.3±0.5×10 -13 .

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Physics-informed latent neural operator for real-time predictions of time-dependent parametric PDEs

Deep operator network (DeepONet) has shown significant promise as surrogate models for systems governed by partial differential equations (PDEs), enabling accurate mappings between infinite-dimensional function spaces. However, when applied to systems with high-dimensional input-output mappings arising from large numbers of spatial and temporal collocation points, these models often require heavily overparameterized networks, leading to long training times. Latent DeepONet addresses some of these challenges by introducing a two-step approach: first learning a reduced latent space using a separate model, followed by operator learning within this latent space. While efficient, this method is inherently data-driven and lacks mechanisms for incorporating physical laws, limiting its robustness and generalizability in data-scarce settings. Here, in this work, we propose PI-Latent-NO, a physics-informed latent neural operator framework that integrates governing physics directly into the learning process. Our architecture features two coupled DeepONets trained end-to-end: a Latent-DeepONet that learns a low-dimensional representation of the solution, and a Reconstruction-DeepONet that maps this latent representation back to the physical space. By embedding PDE constraints into the training via automatic differentiation, our method eliminates the need for labeled training data and ensures physics-consistent predictions. The proposed framework is both memory and compute-efficient, exhibiting near-constant scaling with problem size and demonstrating significant speedups over traditional physics-informed operator models. We validate our approach on a range of parametric PDEs, showcasing its accuracy, scalability, and suitability for real-time prediction in complex physical systems.

Latent representations↗
DOE OSTI2023

An Efficient Reactive Force Field without Explicit Coordination Dependence for Studying Caustic Aluminum Chemistry

Reactive force fields (RFFs) are an expedient approach to sample chemical reaction paths in complex systems, relative to density functional theory. However, there is continued need to improve efficiencies, specifically in systems that have slow transverse degrees of freedom, as in highly viscous and superconcentrated solutions. Here, we present an RFF that is differentiated from current models (e.g., ReaxFF) by omitting explicit dependence on the atom coordination and employing a small parameter set based on Lennard-Jones, Gaussian, and Stillinger–Weber potentials. In this study, the model was parametrized from AIMD simulation data and is used to model aluminate reactivity in sodium hydroxide solutions with extensive validation against experimental radial distribution functions, computed free energy profiles for oligomerization, and formation energies. In conclusion, the model enables simulation of early stage Al(OH) 3 nucleation which has significant relevance to industrial processing of aluminum and has a computational cost that is reduced by 1 order of magnitude relative to ReaxFF.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Image processing workflow yielding high contrast synchrotron nanoscale computed tomography data from Ni-YSZ electrodes

The operating lifetime of Ni-YSZ fuel electrodes used in solid oxide electrolysis cells and fuel cells (SOECs and SOFCs) is limited by Ni redistribution, one of the primary degradation mechanisms that must be overcome to extend the longevity and maximize the performance of SOECs and SOFCs. To achieve this, 3D microstructural data is needed to relate both initial performance and performance loss over time to microstructural properties and their evolution throughout operation under various conditions. However, 3D microstructure data remains relatively scarce within the literature due to multiple challenges in acquiring and analyzing such data reliably. This work presents a workflow for acquiring and processing synchrotron X-ray nanoscale computed tomography (nano-CT) data from Ni-YSZ electrodes. Parameters for each step in the nano-CT workflow are described up to the final result (a 3D reconstruction), with particular emphasis on image alignment using freely available software. Following the results of a parametric sweep of the image alignment step, high contrast, low signal-to-noise 3D nano-CT data is obtained with relatively short compute times. While the exact methods best suited to samples with different microstructural qualities, or similar Ni-YSZ nano-CT data obtained from other sources may deviate from the solution found herein, this work also generalizes the decision points and evaluation of each step to provide a starting point to adapt this workflow to other datasets.

08 HYDROGEN↗
NASA NTRS1994

Continuous hierarchical slope-aspect color display for parametric surfaces

A method for generating an image of a parametric surface, such as the aspect of terrain which maximizes color contrast to permit easy discrimination of the magnitude, ranges, intervals or classes of a surface parameter while making it easy for the user to visualize the form of the surface, such as a landscape. The four pole colors of the opponent process color theory are utilized to represent intervals or classes at 90 degree angles. The color perceived as having maximum measured luminance is selected to portray the color having an azimuth of an assumed light source and the color showing minimum measured luminance portrays the diametrically opposite azimuth. The 90 degree intermediate azimuths are portrayed by unique colors of intermediate measured luminance, such as red and green. Colors between these four pole colors are used which are perceived as mixtures or combinations of their bounding colors and are arranged progressively between their bounding colors to have perceived proportional mixtures of the bounding colors which are proportional to the interval's angular distance from its bounding colors.

Moellering, Harold J.↗
DOE OSTI2021

Aerosol emissions from water-lean solvents for post-combustion CO 2 capture

Advanced water-lean solvents (WLS) for post-combustion CO 2 capture have been gaining interest due to their ability to reduce the parasitic penalty from energy needed for solvent regeneration. Commercial implementation of these novel CO 2 capture technologies hinges on successful control of amine emissions. RTI conducted a parametric study of fundamental and operational variables influence on overall amine aerosol and vapor emissions from our water-lean solvent eCO 2 Sol™ using our 6-kW equivalent bench-scale gas absorption system. The parametric testing used a simulated flue gas with 15 % CO 2 , 2.3–4.2 % H 2 O, and 0–6 ppm sulfite (SO 3 ) to examine the impact of the presence of aerosols to the capture performance and amine emissions from the system. The SO 3 reacts with water in the flue gas to create H 2 SO 4 , which forms liquid aerosol droplets and provide nucleation sites for growth of aerosols. Scanning Mobility Particle Sizer and Aerodynamic Particle Sizer instruments monitored the aerosol particle size distribution. Parametric testing results suggested that the presence of the aerosols in the flue gas could increase the overall amine emissions by 10X compared to the baseline emissions from WLS’s vapor pressure. Principal component analysis (PCA) and projection to latent squares (PLS) developed models to predict the aerosol-based amine emissions from process data. The predictive PLS model had a correlation coefficient (Q 2 ) of 0.92 and could predict the aerosol-based emissions from the NAS process with ±15 % accuracy (average absolute deviation, AAD). The PLS regression model also identified key variables affecting aerosol-based emissions from WLS.

42 ENGINEERING↗
DOE OSTI2024

Phenomenology of TMD parton distributions in Drell-Yan and 𝑍 0 boson production in a hadron structure oriented approach

We present a first practical implementation of a recently proposed hadron structure oriented (HSO) approach to transverse momentum dependent (TMD) phenomenology applied to Drell-Yan-like processes, including lepton pair production at moderate 𝑄 2 and 𝑍 0 boson production. We compare and contrast general features of our methodology with other common practices and emphasize aspects that we view as improvements. Separately, we discuss the importance of treatments that preserve various theoretical properties of the nonperturbative parts of TMD parametrizations for future applications that have the extraction of hadron structure as a primary goal. These include the HSO’s preservation of a basic TMD parton-model-like framework even while accounting for full TMD factorization and evolution, explicit preservation of the integral relationship between TMD and collinear parton density functions, and the ability to meaningfully compare different theoretical models of nonperturbative TMD parton distributions. In our examples, we show that there is significant sensitivity at moderate 𝑄 2 to both the form of the nonperturbative transverse momentum dependence and the parametrization of collinear parton densities. However, we also find that evolving to 𝑄 2 =𝑀$^2_𝑍$, without fitting, results in a satisfactory postdiction of existing data for 𝑍0 production, nearly independently of the modeling of nonperturbative transverse momentum behavior. We argue that this demonstrates that moderate 𝑄 measurements should be given greater weight than high 𝑄 measurements in extractions of nonperturbative transverse momentum dependence. We also obtain new extractions of the nonperturbative Collins-Soper kernel within the HSO approach. We discuss its features and compare with some earlier extractions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1995

Steady State Temperature Profile in a Cylinder Heated by Microwaves

We have developed a new theory to calculate the steady state temperature profile in a cylindrical sample positioned along the entire axis of a cylindrical microwave cavity. Temperature profiles were computed for alumina rods of various radii contained in a cavity excited in one of the TM0n0 modes with n = 1, 2, or 3. Sample surface and center temperatures will be presented as a function of total sample absorbed power or electric field strength at the sample surface. An approach for attaining more uniform heating within the sample by reducing the magnitude of the inverted temperature profile using a concentric outer cylindrical tube will be discussed. Also, parametric studies will be reported for model calculations in which the total hemispherical emissivity was varied at boundaries of the sample and surrounding tube and at the cavity wall. The results will be discussed in the context of controlling both the average sample temperature and the temperature distribution in the sample during microwave processing.

steady-state↗