Anisotropic Extension of a Model for Materials with Ferroelectric to Antiferroelectric Phase Transformation.
Abstract not provided.
Carleton, James↗
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Results for “model extension”
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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A dynamical model of lithosphere extension and sedimentary basin formation
The effect of convection-induced stresses at the base of the continental lithosphere on surface and extensional deviatoric stresses is investigated. The biaxial strain in the continental lithosphere is controlled by power law creep in the upper and lower crust, brittle failure, and the Dorn plasticity law. The relationship between the lithosphere stress distribution and Moho temperatures is examined. The extension factors, basin subsidence, heat flow, and sediment loading of the lithosphere are studied.
Houseman, G.↗
Extension of convection modeling into the high-latitude ionosphere - Some theoretical difficulties
The Rice Convection Model (RCM) is extended and merged with empirical models so as to cover the entire high-latitude ionosphere with the aim of providing precipitation and electric field inputs for ionosphere and thermosphere modelers and producing a model in which the boundaries of the precipitation and electric field patterns maintain physically consistent relationships to each other. The computed auroral electron energy flux, plotted as a function of latitude, exhibited an exaggerated two-peak structure. When no floor was placed under the precipitation rate, the minimum between the two peaks was much too deep to be consistent with typical observations. The regions of excessively weak precipitation map to equatorial distances of 15-35 RE and thus to the regions of the plasma sheet that were not included in previous self-consistent convection calculations.
Wolf, R. A.↗
NASA's nuclear thermal propulsion technology project
The nonnuclear subsystem technologies required for incorporating nuclear thermal propulsion (NTP) into space-exploration missions are discussed. Of particular interest to planned missions are such technologies as materials, instrumentation and controls, turbomachinery, CFD modeling, nozzle extension designs and models, and analyses of exhaust plumes. NASA studies are described and/or proposed for refractory metals and alloys, robotic NTP controls, and turbopump materials candidates. Alternative nozzle concepts such as aerospikes and truncated plugs are proposed, and numerical simulations are set forth for studying heavy molecules and the backstreaming of highly reactive free-radical hydrogen in the exhaust plume. The critical technologies described in the paper are central to the development of NTP, and NTP has the potential to facilitate a range of space exploration activities.
Peecook, Keith M.↗
Enhancement and Extension of Porosity Model in the FDNS-500 Code to Provide Enhanced Simulations of Rocket Engine Components
In the past, the design of rocket engines has primarily relied on the cold flow/hot fire test, and the empirical correlations developed based on the database from previous designs. However, it is very costly to fabricate and test various hardware designs during the design cycle, whereas the empirical model becomes unreliable in designing the advanced rocket engine where its operating conditions exceed the range of the database. The main goal of the 2nd Generation Reusable Launching Vehicle (GEN-II RLV) is to reduce the cost per payload and to extend the life of the hardware, which poses a great challenge to the rocket engine design. Hence, understanding the flow characteristics in each engine components is thus critical to the engine design. In the last few decades, the methodology of computational fluid dynamics (CFD) has been advanced to be a mature tool of analyzing various engine components. Therefore, it is important for the CFD design tool to be able to properly simulate the hot flow environment near the liquid injector, and thus to accurately predict the heat load to the injector faceplate. However, to date it is still not feasible to conduct CFD simulations of the detailed flowfield with very complicated geometries such as fluid flow and heat transfer in an injector assembly and through a porous plate, which requires gigantic computer memories and power to resolve the detailed geometry. The rigimesh (a sintered metal material), utilized to reduce the heat load to the faceplate, is one of the design concepts for the injector faceplate of the GEN-II RLV. In addition, the injector assembly is designed to distribute propellants into the combustion chamber of the liquid rocket engine. A porosity mode thus becomes a necessity for the CFD code in order to efficiently simulate the flow and heat transfer in these porous media, and maintain good accuracy in describing the flow fields. Currently, the FDNS (Finite Difference Navier-Stakes) code is one of the CFD codes which are most widely used by research engineers at NASA Marshall Space Flight Center (MSFC) to simulate various flow problems related to rocket engines. The objective of this research work during the 10-week summer faculty fellowship program was to 1) debug the framework of the porosity model in the current FDNS code, and 2) validate the porosity model by simulating flows through various porous media such as tube banks and porous plate.
Cheng, Gary↗
The Long-stable Hard State of XTE J1752-223 and the Disk Truncation Dilemma
The degree to which the thin accretion disks of black hole X-ray binaries are truncated during hard spectral states remains a contentious open question in black hole astrophysics. During its singular observed outburst in 2009–2010, the black hole X-ray binary XTE J1752−223 spent ∼1 month in a long-stable hard spectral state at a luminosity of ∼0.02–0.1 L Edd . It was observed with 56 RXTE pointings during this period, with simultaneous Swift-XRT daily coverage during the first 10 days of the RXTE observations. While reflection modeling has been extensively explored in the analysis of these data, there is disagreement surrounding the geometry of the accretion disk and corona implied by the reflection features. We reexamine the combined, high signal-to-noise, simultaneous Swift and RXTE observations, and perform extensive reflection modeling with the latest relxill suite of reflection models, including newer high disk density models. We show that reflection modeling requires that the disk be within ∼5 R ISCO during the hard spectral state, while weaker constraints from the thermal disk emission imply higher truncation (Rin = 6–80 R ISCO ). We also explore more complex coronal continuum models, allowing for two Comptonization components instead of one, and show that the reflection features still require only a mildly truncated disk. Finally we present a full comparison of our results to previous constraints found from analyses of the same data set.
Accretion↗
Hierarchic plate and shell models based on p-extension
Formulations of finite element models for beams, arches, plates and shells based on the principle of virtual work was studied. The focus is on computer implementation of hierarchic sequences of finite element models suitable for numerical solution of a large variety of practical problems which may concurrently contain thin and thick plates and shells, stiffeners, and regions where three dimensional representation is required. The approximate solutions corresponding to the hierarchic sequence of models converge to the exact solution of the fully three dimensional model. The stopping criterion is based on: (1) estimation of the relative error in energy norm; (2) equilibrium tests, and (3) observation of the convergence of quantities of interest.
Szabo, Barna A.↗
MRAC with Time-Varying Reference Model from Convex Combination
An extension of model reference adaptive control is presented that accommodates use of a time-varying reference model. Specifically, the reference model is taken to be a time-varying convex combination of two linear, time-invariant models. The design is intended to act as a way to smoothly transition between two different reference models without resorting to a scheduled switch. It also provides the ability to use an interpolated reference model when the plant is operating between design points. The time variation of the combination must satisfy some requirements to ensure stability but is otherwise user choice. Subject to these requirements, bounded tracking error behavior is demonstrated via Lyapunov stability analysis for the single-input, single-output, output feedback case. Tracking error convergence is asymptotic when time variation ceases. The proposed design is demonstrated in simulation of a numerical model.
Hashemi, Kelley E.↗
A multiscale recurrent neural network model for predicting energy production from geothermal reservoirs
Optimization of energy production from geothermal reservoirs requires reliable prediction of energy production performance under alternative operation and development scenarios. Traditionally, reservoir simulation models are used for the evaluation and screening of alternative production and development plans. However, simulation models require extensive data collection and modeling efforts and are time-consuming to build, run, and update. Data-driven predictive models, on the other hand, can serve as efficient prediction tools that can be used for decision support and management of daily operations and surveillance activities. Data-driven models become particularly attractive when a reservoir simulation model for a field does not exist and/or is difficult to build. Machine learning (ML)-based data-driven models that have recently become popular in several fields exploit statistical patterns and relations in training data to generate predictions. As such, they tend to perform better in interpolation problems (that is, prediction within the training data range) than when they are used to extrapolate beyond the training data. Production data from geothermal reservoirs tend to exhibit short-term variabilities as well as long-term trends, such as monotonically declining production temperatures. Capturing both short-term features and long-term trends with ML-based models is not trivial. We evaluate the use of recurrent neural networks (RNN) for the prediction of energy production from geothermal reservoirs. RNN is a class of ML architectures that are used to represent and predict sequential/dynamic data. Thus, it can be challenging to apply RNN to problems where long-term trends must be captured and extrapolation beyond the training data range is needed. We introduce the multiscale RNN architecture to extend the application of RNN to detect and predict both short-term variabilities and long-term trends in geothermal data. The developed architecture consists of a long-term component to only capture low-frequency data patterns, and a short-term component to detect features with higher frequency and more nonlinearity. The final prediction is obtained by combining the long-term and short-term predictions. Both synthetic and field data are used to evaluate the presented multiscale RNN model. The prediction performance of the multiscale RNN is compared against those obtained from the regular RNN and the autoregressive (AR) model. The results suggest that the multiscale architecture improves the long-term prediction performance of the regular RNN and enhances its robustness against noise.
15 GEOTHERMAL ENERGY↗
A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach
Deep learning (DL) models are extensively used as surrogate models for high-fidelity simulations of multiphase fluid flow in porous media at large scales, enabling fast forecasts of the spatial–temporal evolution of three-dimensional (3D) state variables in geological carbon storage (GCS). However, training these models in high-dimensional space remains computationally demanding and prone to overfitting because of limited training data. This paper presents a novel workflow to address these challenges by integrating dimension reduction (DR) methods. Here, the proposed workflow employed pre-trained DR models to extract the latent variables of geological models and state variables and utilized the multi-layer perceptron (MLP) for constructing mapping functions between the input and output variables in latent spaces. Subsequently, the pre-trained reconstruction models converted the MLP-predicted latent state variables to their original high-dimensional form. Furthermore, we proposed a novel strategy for the DR and reconstruction of 3D saturation fields to account for the unique data characteristics of sparsity, nonuniformity, and discontinuity. The proposed strategy applied PCA and inverse PCA for 2D average saturation fields and developed a DL-based 3D reconstruction model, leveraging three 2D average saturation fields as input to produce a 3D saturation field as output. The pre-training of DR and reconstruction models and training of MLP models were conducted on 84 Gulf of Mexico (GoM) simulations and evaluated on 12 testing simulations. Each simulation contained 720 monthly time steps, with the first 360 months as the injection period and the rest as the post-injection period. The proposed workflow, incorporating DR and DL models, accurately predicts the normalized 3D pressure fields, achieving mean square error (MSE) of 2.92 × 10 -7 compared to the ground truth obtained from a full-physics simulator. Furthermore, the proposed strategy outperformed PCA and convolutional autoencoder (CAE) models on 3D saturation fields, resulting in minor workflow prediction errors with an MSE of 2.93 × 10 -5 . The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales, and enables a speedup of 160 times compared to the full-physics simulator, facilitating improved decision-making and risk assessment for large-scale GCS management in real-time scenarios.
3D reconstruction model↗
Relating the radar backscattering coefficient to leaf-area index
The relationship between the radar backscattering coefficient of a vegetation canopy, sigma(0) sub can, and the canopy's leaf area index (LAI) is examined. The relationship is established through the development of a model for corn and sorghum and another for wheat. Both models are extensions of the cloud model of Attema and Ulaby (1978). Analysis of experimental data measured at 8.6, 13.0, 17.0, and 35.6 GHz indicates that most of the temporal variations of sigma(0) sub can can be accounted for through variations in green LAI alone, if the latter is greater than 0.5.
Ulaby, F. T.↗
Relating the microwave backscattering coefficient to leaf area index
This paper examines the relationship between the microwave backscattering coefficient of a vegetation canopy, sigma (can, 0) and the canopy's leaf area index (LAI). The relationship is established through the development of one model for corn and sorghum and another for wheat. Both models are extensions of the cloud model of Attema and Ulaby (1978). Analysis of experimental data measured at 8.6, 13.0, 17.0, and 35.6 GHz indicates that most of the temporal variations of sigma (can, 0) can be accounted for through variations in green LAI alone, if the latter is greater than 0.5.
Ulaby, F. T.↗
X-ray Reflected Spectra from Accretion Disk Models. III. A Complete Grid of Ionized Reflection Calculations
We present a new and complete library of synthetic spectra for modeling the component of emission that is reflected from an illuminated accretion disk. The spectra were computed using an updated version of our code xillver that incorporates new routines and a richer atomic data base. We offer in the form of a table model an extensive grid of reflection models that cover a wide range of parameters. Each individual model is characterized by the photon index Gamma of the illuminating radiation, the ionization parameter zeta at the surface of the disk (i.e., the ratio of the X-ray flux to the gas density), and the iron abundance A(sub Fe) relative to the solar value. The ranges of the parameters covered are: 1.2 <= Gamma <= 3.4, 1 <= zeta <= 104, and 0.5 <= A(sub Fe) <= 10. These ranges capture the physical conditions typically inferred from observations of active galactic nuclei, and also stellar-mass black holes in the hard state. This library is intended for use when the thermal disk flux is faint compared to the incident power-law flux. The models are expected to provide an accurate description of the Fe K emission line, which is the crucial spectral feature used to measure black hole spin. A total of 720 reflection spectra are provided in a single FITS file suitable for the analysis of X-ray observations via the atable model in xspec. Detailed comparisons with previous reflection models illustrate the improvements incorporated in this version of xillver.
X-ray↗
Responses of summer mesoscale convective systems to irrigation over the North China Plain based on convection-permitting model simulations
Extensive irrigation activities in the North China Plain (NCP) significantly influence regional weather and climate. However, previous studies focusing on the NCP were primarily based on coarse-resolution models, which are unable to explicitly resolve convection systems, causing large uncertainty in precipitation simulations. In this study, a convection-permitting model coupled with a dynamic irrigation scheme is utilized to investigate the impacts of irrigation on summertime mesoscale convective systems (MCSs) over the NCP. Sensitivity experiments with irrigation off and on are conducted for 5 summers and an MCS identification and tracking algorithm is applied to both satellite observations and model simulations. We find that incorporating irrigation in the model increases MCS precipitation, which agrees more with observations. The probability distributions of MCS lifetime, area, propagation speed, and intensity are all better simulated with irrigation. Irrigation increases the occurrence frequency of MCSs throughout the entire day. The nighttime increase is partly because of more frequent local initiation of MCS developed from isolated deep convection, while the daytime increase is mainly attributed to the changes in MCSs initiating elsewhere and then propagating to the NCP. On average, irrigation induces additional moisture that is more thermodynamically favorable for precipitation, but this effect is partially offset by the weakened ascending air motion primarily caused by irrigation surface cooling. Compared to weak MCS precipitation events, strong MCS precipitation events experience greater enhancement in precipitation intensity when including irrigation because the offset effect from the change in large-scale ascending air motion is insignificant. In addition, irrigation makes the variation of MCS precipitation intensity more correlated with the variation in ascending motion but less correlated with that in atmospheric moisture. Our results suggest the pronounced impacts of irrigation on MCSs over the NCP which should be included in numerical models to improve regional precipitation simulation and prediction.
54 ENVIRONMENTAL SCIENCES↗
What can formal methods offer to digital flight control systems design
Formal methods research begins to produce methods which will enable mathematic modeling of the physical behavior of digital hardware and software systems. The development of these methods directly supports the NASA mission of increasing the scope and effectiveness of flight system modeling capabilities. The conventional, continuous mathematics that is used extensively in modeling flight systems is not adequate for accurate modeling of digital systems. Therefore, the current practice of digital flight control system design has not had the benefits of extensive mathematical modeling which are common in other parts of flight system engineering. Formal methods research shows that by using discrete mathematics, very accurate modeling of digital systems is possible. These discrete modeling methods will bring the traditional benefits of modeling to digital hardware and hardware design. Sound reasoning about accurate mathematical models of flight control systems can be an important part of reducing risk of unsafe flight control.
Good, Donald I.↗
Thermal Model Development for Ares I-X
Thermal analysis for the Ares I-X vehicle has involved extensive thermal model integration, since thermal models of vehicle elements came from several different NASA and industry organizations. Many valuable lessons were learned in terms of model integration and validation. Modeling practices such as submodel, analysis group and symbol naming were standardized to facilitate the later model integration. Upfront coordination of coordinate systems, timelines, units, symbols and case scenarios was very helpful in minimizing integration rework. A process for model integration was developed that included pre-integration runs and basic checks of both models, and a step-by-step process to efficiently integrate one model into another. Extensive use of model logic was used to create scenarios and timelines for avionics and air flow activation. Efficient methods of model restart between case scenarios were developed. Standardization of software version and even compiler version between organizations was found to be essential. An automated method for applying aeroheating to the full integrated vehicle model, including submodels developed by other organizations, was developed.
Amundsen, Ruth M.↗
Mars Sulfate Formation Sourced in Sulfide-Enriched Subsurface Fluids: The Rio Tinto Model
The extensive evidence for sulfate deposits on Mars provided by analyses of MER and Mars Express data shows that the sulfur played an essential role in the geochemical cycles of the planet, including reservoirs in the atmosphere, hydro-sphere and geosphere. Overall the data are consistent with a fluvial/lacustrine-evaporative origin of at least some of the sulfate deposits, with mineral precipitation through oversaturation of salty acidic fluids enriched in sulfates. This scenario requires reservoirs of sulfur and associated cations, as well as an acidic and oxidizing hydrochemistry which could be provided by surface and subsurface catching of meteoric waters resulting in the presence of sulfur-bearing gases and steam photochemistry. In this work we suggest a new scenario for the extensive generation of sulfates in Mars based on the observation of seasonal changes in the redox and pH of subsurface waters enriched in sulfur that supply the acidic Mars process analog of Rio Tinto. This model considers the long-term subsurface storage of sulfur during most of Noachian and its release from the late Noachian to Hesperian time through weathering by meteoric fluids that would acidify and oxidize the sulfur bearing compounds stored in the subsurface.
Fernandez-Remolar, D. C.↗
Core-corona hadronization model and muon puzzle in extensive air showers
The discrepancy between models and measurements concerning the muon content in air showers produced by ultra-high energy cosmic rays, the so-called muon puzzle, remains unsolved. String fragmentation models currently used in hadronic interactions fail to reproduce the observations, while recent measurements at the LHC hint towards the existence of production mechanisms, such as collective statistical hadronization, which lead to an increase in the muon production after a hadronic interaction. The core-corona model of heavy ions implements both production mechanisms, where the large-density region of interaction (core) hadronizes statistically, while the low-density (corona) hadronizes following string fragmentation. In this contribution, we present a modification of the CONEX framework to implement the core-corona model in air shower simulations. We demonstrate a significant impact of the core effect, as observed at the LHC, on the muon content in air showers produced by ultra-high energy cosmic rays.
79 ASTRONOMY AND ASTROPHYSICS↗