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Results for “Predictive Data analytics”

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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Analytical study of vortex flaps on highly swept delta wings

This paper highlights some current results from ongoing analytical studies of vortex flaps on highly swept delta wings. A brief discussion of the vortex flow analysis tools is given along with comparisons of the theories to vortex flap force and pressure data. Theoretical trends in surface pressure distribution for both angle-of-attack variation and flap deflection are correctly predicted by Free Vortex Sheet theory. Also shown are some interesting calculations for attached-flow and vortex-flow flap hinge moments that indicate flaps utilizing vortex flow may generate less hinge moment than attached flow flaps. Finally, trailing-edge flap effects on leading-edge flap thrust potential are investigated and theory-experiment comparisons made.

Frink, N. T.↗
NASA NTRS1987

Analytical flutter investigation of a composite propfan model

A theoretical model and an associated computer program for predicting subsonic bending-torsion flutter in propfans are presented. The model is based on two-dimensional unsteady cascade strip theory and three-dimensional steady and unsteady lifting surface aerodynamic theory in conjunction with a finite element structural model for the blade. The analytical results compare well with published experimental data. Additional parametric studies are also presented illustrating the effects on flutter speed of steady aeroelastic deformations, blade setting angle, rotational speed, number of blades, structural damping, and number of modes.

Kaza, K. R. V.↗
NASA NTRS1987

Analytical flutter investigation of a composite propfan model

A theoretical model and an associated computer program for predicting subsonic bending-torsion flutter in propfans are presented. The model is based on two-dimensional unsteady cascade strip theory and three-dimensional steady and unsteady lifting surface aerodynamic theory in conjunction with a finite element structural model for the blade. The analytical results compare well with published experimental data. Additional parametric studies are also presented illustrating the effects on flutter speed of steady aeroelastic deformations, blade setting angle, rotational speed, number of blades, structural damping, and number of modes.

Kaza, K. R. V.↗
NASA NTRS1990

Turbulence modeling: Near-wall turbulence and effects of rotation on turbulence

Many Reynolds averaged Navier-Stokes solvers use closure models in conjunction with 'the law of the wall', rather than deal with a thin, viscous sublayer near the wall. This work is motivated by the need for better models to compute near wall turbulent flow. The authors use direct numerical simulation of fully developed channel flow and one of three dimensional turbulent boundary layer flow to develop new models. These direct numerical simulations provide detailed data that experimentalists have not been able to measure directly. Another objective of the work is to examine analytically the effects of rotation on turbulence, using Rapid Distortion Theory (RDT). This work was motivated by the observation that the pressure strain models in all current second order closure models are unable to predict the effects of rotation on turbulence.

Shih, T.-H.↗
NASA NTRS2020

Laboratory Studies of Astronomical Ices: Reaction Chemistry and Spectroscopy

In this article, we will describe the work of the Cosmic Ice Laboratory at NASA’s Goddard Space Flight Center to characterize the composition of and to understand the chemistry occurring in icy bodies in the Solar System and beyond. Our work has touched on a wide range of extraterrestrial environments including icy interstellar grains, small bodies such as comets and asteroids, and planets and moons. We are especially interested in the chemical and physical changes that occur in ices as a result of thermal changes or exposure to radiation. To this end, we conduct experiments designed to simulate cold extraterrestrial environments and measure physical properties of single- and multi-component ices. We expose ices to radiation (e.g., MeV protons or keV-MeV electrons) or high-energy photons (e.g., UV) to initiate physical and chemical changes. We conduct experiments using cryo-vacuum chambers equipped with analytical tools and radiation sources to make most of our measurements, including the collection of all spectroscopic data,in situ. When possible and appropriate, we also collect reaction products for further ex situ analysis. The work of the Cosmic Ice Lab provides critical data to astrochemists and others seeking to understand observations, make predictions, and plan future space missions.

Christopher K Materese↗
DOE OSTI2021

Experiment Based Superposition Thermal Modeling of Laser Powder Bed Fusion

This paper evaluates experiment-based superposition thermal modeling for Laser Powder Bed Fusion (LPBF) with a pulsed laser. An analytical pulsed laser thermal model establishes the modeling procedure. The framework inverts a powder bed’s single pulse temperature response from experimental spatiotemporal Short-Wave Infrared (SWIR) camera data. Superimposing this response along a scan path simulates multi-pulse LPBF. Results show the experimentally informed superposition model rapidly and accurately predicts a layer’s temperature history. The model has applications in correction of thermally driven LPBF errors and in-situ part qualification.

Lough, Cody↗
DOE OSTI2020

Probabilistic Groundwater Modeling of the RDX Plume at Los Alamos National Laboratory to Support Risk Assessment - 20359

A plume of the contaminant hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) with concentrations greater than the New Mexico tap water drinking standard (9.66 ppb) is present in the regional aquifer near the southwestern boundary of Los Alamos National Laboratory (LANL). A risk assessment is performed for exposure to regional aquifer groundwater, with long-term predictions of RDX concentrations provided by a calibrated, probabilistic, numerical fate and transport model. The structure of the model is hierarchical, with the RDX Regional Aquifer (RA) groundwater model acting as the primary tool for analysis of downgradient RDX concentrations. The RA model is deeply informed by the conceptual site model (CSM) and is calibrated using site RDX concentration data and hydraulic head measurements, along with other analyses. The model is calibrated using data through December 2019. Where data are scarce other lines of evidence are used to inform inputs, including the multiphase RDX Vadose Zone (VZ) model and Pipe and Disk analytical screening tool. Model inputs are described with informative prior distributions using a robust approach to development that incorporates all available lines of evidence for every parameter used as an input to the RA model. Calibration is performed using a classical nonlinear optimization routine, which is then used to initialize a Bayesian calibration. The Bayesian calibration constrains the uncertainty in the classical calibration, ultimately providing posterior distributions for all model parameters. The challenges of the calibration include high-dimensional parameter space, including spatially heterogeneous hydraulic conductivities, comparatively sparse data, and low RDX concentrations. Posterior parameter distributions developed in the calibration process are then used for stochastic predictive model runs into the future. The result of the forward runs is spatially and temporally explicit estimates of head and concentration with uncertainty at all points in space and time. The probabilistic modeling approach presented here includes innovative computational and statistical methods that leverage high-performance computing (HPC) resources. It makes use of prior modeling work performed at the chromium plume site in the central LANL area, with extensive updates. The risk assessment will ultimately be used to support decision-making at the site, using multiple appropriately weighted sources of information, as well as uncertainty, sensitivity, and value-of-information analyses. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1977

An experimental and analytical investigation of proprotor whirl flutter

The results of an experimental parametric investigation of whirl flutter are presented for a model consisting of a windmilling propeller-rotor, or proprotor, having blades with offset flapping hinges mounted on a rigid pylon with flexibility in pitch and yaw. The investigation was motivated by the need to establish a large data base from which to assess the predictability of whirl flutter for a proprotor since some question has been raised as to whether flutter in the forward whirl mode could be predicted with confidence. To provide the necessary data base, the parametric study included variation in the pylon pitch and yaw stiffnesses, flapping hinge offset, and blade kinematic pitch-flap coupling over a large range of advance ratios. Cases of forward whirl flutter and of backward whirl flutter are documented. Measured whirl flutter characteristics were shown to be in good agreement with predictions from two different linear stability analyses which employed simple, two dimensional, quasi-steady aerodynamics for the blade loading. On the basis of these results, it appears that proprotor whirl flutter, both forward and backward, can be predicted.

Kvaternik, R. G.↗
DOE OSTI2020

Model Development for Multi-Component Fuel Vaporization and Flash Boiling

The objectives of this project are to improve the multi-component fuel droplet and film vaporization models used in internal combustion engine simulation, and to develop a comprehensive model to predict the characteristics of multi-component flash boiling spray. This work explores two approaches to fuel composition treatment for modeling multi-component fuel vaporization: one based on discretization and surrogates, and the other based on continuous thermodynamic distribution of fuel properties. The experimental data collected for model validation are done under three fuel form factors: droplet, spray, and thin film. The study on sprays also include experimentation under non-flash and flash boiling conditions, a phenomenon that enhances fuel vaporization. The main goals of this work are: Design and develop a multi-component fuel droplet and wall film vaporization model using both discrete and continuous thermodynamics methods. Design and develop an analytical model for multi-component flash boiling. Integrate the multi-component droplet and film model into multi-dimensional engine calculations to predict the fuel vaporization process under engine operation condition. Conduct multi-component droplet and fuel film vaporization experiments in a non-combusting chamber to verify the proposed vaporization models. Characterize flash boiling phenomena of multi-component fuel sprays by optical and laser diagnostic techniques. This report will detail the experimental setup and the numerical basis for developing a model to achieve the main goals listed above. Key features of observed multi-component fuel vaporization will be summarized at the end of each experimental sections, and corresponding model performance evaluation will be presented at the end of each model development section.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Waveform processing using neural network algorithms on the front-end electronics

In a multi-channel radiation detector readout system, waveform sampling, digitization, and raw data transmission to the data acquisition system constitute a conventional processing chain. The deposited energy on the sensor is estimated by extracting peak amplitudes, area under pulse envelopes from the raw data, and starting times of signals or time of arrivals. However, such quantities can be estimated using machine learning algorithms on the front-end Application-Specific Integrated Circuits (ASICs), often termed as “edge computing”. Edge computation offers enormous benefits, especially when the analytical forms are not fully known or the registered waveform suffers from noise and imperfections of practical implementations. In this work, we aim to predict peak amplitude from a single waveform snippet whose rising and falling edges containing only 3 to 4 samples. We thoroughly studied two well-accepted neural network algorithms, Multi-Layer Perceptron (MLP) and Convolutional Neural Network (CNN) by varying their model sizes. Further, to better fit front-end electronics, neural network model reduction techniques, such as network pruning methods and variable-bit quantization approaches, were also studied. By combining pruning and quantization, our best performing model has the size of 1.5 KB, reduced from 16.6 KB of its full model counterpart. It can reach mean absolute error of 0.034 comparing to that of a naive baseline of 0.135. Such parameter-efficient and predictive neural network models established feasibility and practicality of their deployment on front-end ASICs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Use of Rig Parameter Data in Bit Constraint Models for Improved Drilling Performance at The Geysers

Surface parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. However, these measurements are of reduced value without a standard to aid in evaluation and decision making. A method is demonstrated whereby drill bit constraint models are used to interpret drilling response parameters. Drill rig parameter data for well GDC-36 at the Geysers Geothermal Field Power were acquired by Geysers Power Company and drilling contractor Kenai Drilling using Pason US DataHub and evaluated. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) along with other model constraints in computational algorithms. The method is used to evaluate overall bit performance, monitor bit integrity, and detect the presence of drillstring vibrations and other conditions contributing to bit failure; comparisons are made to observations of bit wear and damage. The method will be applied in real-time to improve decision-making on subsequent wells and has applicability to development of advanced analytics on future geothermal wells using real-time electronic drilling recorder (EDR) data for improved performance and reduced drilling costs.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Joint galaxy–galaxy lensing and clustering constraints on galaxy formation

ABSTRACT We compare predictions for galaxy–galaxy lensing profiles and clustering from the Henriques et al. public version of the Munich semi-analytical model (SAM) of galaxy formation and the IllustrisTNG suite, primarily TNG300, with observations from KiDS + GAMA and SDSS-DR7 using four different selection functions for the lenses (stellar mass, stellar mass and group membership, stellar mass and isolation criteria, and stellar mass and colour). We find that this version of the SAM does not agree well with the current data for stellar mass-only lenses with $M_\ast \gt 10^{11}\, \mathrm{ M}_\odot$. By decreasing the merger time for satellite galaxies as well as reducing the radio-mode active galactic nucleus accretion efficiency in the SAM, we obtain better agreement, both for the lensing and the clustering, at the high-mass end. We show that the new model is consistent with the signals for central galaxies presented in Velliscig et al. Turning to the hydrodynamical simulation, TNG300 produces good lensing predictions, both for stellar mass-only (χ2 = 1.81 compared to χ2 = 7.79 for the SAM) and locally brightest galaxy samples (χ2 = 3.80 compared to χ2 = 5.01). With added dust corrections to the colours it matches the SDSS clustering signal well for red low-mass galaxies. We find that both the SAMs and TNG300 predict $\sim 50\, {{\ \rm per\ cent}}$ excessive lensing signals for intermediate-mass red galaxies with 10.2 < log10M*[M⊙] < 11.2 at $r \approx 0.6\, h^{-1}\, \text{Mpc}$, which require further theoretical development.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1977

Assessment of existing analytic methods for prediction of high angle-of-attack loads on delta wings at supersonic speeds

An assessment of the applicability of four loading prediction methods to high angle-of-attack conditions for simplified wing-body configurations is provided. The methods are: The tangent wedge approximation, the linear theory methods of Middleton and Woodward, and a shock-fitting finite-difference technique. Estimates obtained by these methods were compared with experimental pressure data on delta wings to examine the effects of Mach number, camber, sweep angle, and angle of attack. Results indicate that all of the methods provided reasonable estimates at moderate angles of attack. At these moderate angles of attack, the methods of Middleton and Woodward provided good estimates at Mach numbers higher than those usually associated with linear theory. Only the finite-difference method provided reasonable load estimates at high angles of attack.

Landrum, E. J.↗
DOE OSTI2024

Deconvoluting XPS Spectra of La-Containing Perovskites from First-Principles

Perovskite-based oxides are used in electrochemical CO 2 and H 2 O reduction in electrochemical cells due to their compositional versatility, redox properties and stability. However limited knowledge exists on the mechanisms driving these processes. Toward this understanding, herein we probe the core level binding energy shifts of water-derived adspecies (H, O, OH, H 2 O) as well as the adsorption of CO 2 on LaCoO 3 and LaNiO 3 and we correlate the simulated peaks with experimental Temperature Programmed X-ray Photoelectron Spectroscopy (TPXPS) results. We find the strong adsorption of such chemical species can affect the antiferromagnetic ordering of LaNiO 3 . The adsorption of such adspecies is further quantified through Bader and differential charge analyses. We find the higher O 1s core level binding energy peak for both LaCoO 3 and LaNiO 3 corresponds to adsorption of water-related species and CO 2 , while the lower energy peak is due to lattice oxygen. We further correlate these DFT-based core level O 1s binding energies with the TPXPS measurements to quantify the decrease of the O 1s contribution due to desorption of adsorbates and the apparent increase of the lattice oxygen (both bulk and surface) with temperature. Finally, we quantify the influence of adsorbates on the La 4d, Co 2p and the Ni 3p core level binding energy shifts. This work demonstrates how theoretically generated XPS data can be utilized to predict species-specific binding energy shifts to assist in the deconvolution of the experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Description of quantum interference using mixed quantum/classical theory of inelastic scattering

Manifestation of the quantum interference effect in the oscillation of scattering cross section is explored using the N 2 + O system as a case study. Calculations are carried out for two electronic PESs of the system, for various initial rotational states of N 2 , in a broad range of N 2 + O collision energies and using three theoretical methods: two versions of the approximate mixed quantum/classical theory (MQCT and AT-MQCT) and the accurate full-quantum coupled-channel method (implemented in MOLSCAT). A good agreement between different methods is observed, especially at high energies. Elastic scattering cross-sections oscillate as a function of collision energy, which is the result of quantum interference. The effects of initial rotational excitation and of the PES properties are studied in detail. For the final (thermally averaged) cross sections, both MOLSCAT and MQCT calculations predict a rather regular pattern of quantum oscillations that persist through a broad range of collision energies and expand into the low-energy regime where quantum scattering resonances are common. The difference between cross sections predicted by MQCT and MOLSCAT decreases from ~8% at low energies to ~2% at high energies. Finally, experimental data available at high collision energies are well reproduced.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Radiation Effects Model for Ultra-Thin Silicon Solar Cells

This work is focused on investigation of radiation effects in Ultra-Thin Silicon solar cells with a particular emphasis on electron irradiation. The study is motivated by the application of these solar cells, developed by Solestial, Inc., for powering space missions, including those led by NASA, the Department Of Defence (DOD), and commercial satellite missions. Our research encompasses both experimental and theoretical approaches, addressing unique challenges posed by ultra-thin solar cell technology that deviates from the traditional models. From the experimental point of view, the test structures were irradiated with 1 MeV electrons up to the fluence of 1E+15 e/cm$^{2}$. Radiation effects due to accumulated electron dose were noticed as a drop in open-circuit voltage (Voc). An analytical expression for modeling the Voc characteristic of the UT-Si cell after exposure to electron irradiation was formulated and subsequently compared with experimental data. The theoretical foundation of the proposed approach builds upon the Non-Ionising Energy Loss (NIEL) concept, a fundamental parameter in addressing radiation damage modelling and survivability predictions.

Fedoseyev, Alex↗