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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Computational Fluid Dynamics (CFD) Simulations of Taylor Bubbles in Vertical and Inclined Pipes with Upward and Downward Liquid Flow

Summary Two-phase flow is a common occurrence in pipes of oil and gas developments. Current predictive tools are based on the mechanistic two-fluid model, which requires the use of closure relations to predict integral flow parameters such as liquid holdup (or void fraction) and pressure gradient. However, these closure relations carry the highest uncertainties in the model. In particular, significant discrepancies have been found between experimental data and closure relations for the Taylor bubble velocity in slug flow, which has been determined to strongly affect the mechanistic model predictions (Lizarraga-García 2016). In this work, we study the behavior of Taylor bubbles in vertical and inclined pipes with upward and downward flow using a validated 3D computational fluid dynamics (CFD) approach with level set method implemented in a commercial code. A total of 56 cases are simulated, covering a wide range of fluid properties, pipe diameters, and inclination angles: Eo ∈ [10, 700]; Mo ∈ [1×10–6, 5×103]; ReSL ∈ [–40, 10]; θ ∈ [5°, 90°]. For bubbles in vertical upward flows, the simulated distribution parameter, C0, is successfully compared with an existing model. However, the C0 values of downward and inclined slug flows where the bubble becomes asymmetric are shown to be significantly different from their respective vertical upward flow values, and no current model exists for the fluids simulated here. The main contributions of this work are (1) the relatively large 3D numerical database generated for this type of flow, (2) the study of the asymmetric nature of inclined and some vertical downward slug flows, and (3) the analysis of its impact on the distribution parameter, C0.

Engineering↗
NASA NTRS1994

Computational control of flexible aerospace systems

The main objective of this project is to establish a distributed parameter modeling technique for structural analysis, parameter estimation, vibration suppression and control synthesis of large flexible aerospace structures. This report concentrates on the research outputs produced in the last two years. The main accomplishments can be summarized as follows. A new version of the PDEMOD Code had been completed based on several incomplete versions. The verification of the code had been conducted by comparing the results with those examples for which the exact theoretical solutions can be obtained. The theoretical background of the package and the verification examples has been reported in a technical paper submitted to the Joint Applied Mechanics & Material Conference, ASME. A brief USER'S MANUAL had been compiled, which includes three parts: (1) Input data preparation; (2) Explanation of the Subroutines; and (3) Specification of control variables. Meanwhile, a theoretical investigation of the NASA MSFC two-dimensional ground-based manipulator facility by using distributed parameter modeling technique has been conducted. A new mathematical treatment for dynamic analysis and control of large flexible manipulator systems has been conceived, which may provide an embryonic form of a more sophisticated mathematical model for future modified versions of the PDEMOD Codes.

Sharpe, Lonnie, Jr.↗
NASA NTRS1991

Combined structures-controls optimization of lattice trusses

The role that distributed parameter model can play in CSI is demonstrated, in particular in combined structures controls optimization problems of importance in preliminary design. Closed form solutions can be obtained for performance criteria such as rms attitude error, making possible analytical solutions of the optimization problem. This is in contrast to the need for numerical computer solution involving the inversion of large matrices in traditional finite element model (FEM) use. Another advantage of the analytic solution is that it can provide much needed insight into phenomena that can otherwise be obscured or difficult to discern from numerical computer results. As a compromise in level of complexity between a toy lab model and a real space structure, the lattice truss used in the EPS (Earth Pointing Satellite) was chosen. The optimization problem chosen is a generic one: of minimizing the structure mass subject to a specified stability margin and to a specified upper bond on the rms attitude error, using a co-located controller and sensors. Standard FEM treating each bar as a truss element is used, while the continuum model is anisotropic Timoshenko beam model. Performance criteria are derived for each model, except that for the distributed parameter model, explicit closed form solutions was obtained. Numerical results obtained by the two model show complete agreement.

Balakrishnan, A. V.↗
DOE OSTI2020

Statistical Characteristics of Raindrop Size Distributions and Parameters in Central China during the Meiyu Seasons

The rain parameters measured by the laser OTT Parsivel raindrop disdrometer (Parsivel), the two-dimensional video disdrometer (2DVD) and DZZ5 tipping-bucket rain gauge (RG) during the Integrative Monsoon Frontal Rainfall Experiment (IMFRE) in summer 2018 are compared. The total rain amounts observed by Parsivel, 2DVD, and RG during IMFRE are 178.07 mm, 176.76 mm and 182.5 mm, while their total rainy hours are 113, 113 and 90. The mean Dm (mass-weighted mean diameter) and liquid water content values derived from Parsivel and 2DVD are 0.9 mm and 1.02 mm, and 0.247 g m-3 and 0.223 g m-3, respectively, and Parsivel is more sensitive to small raindrops (< 1 mm) than 2DVD. The raindrop spectra measured by Parsivel and 2DVD have excellent agreement for both convective rain (CR) and stratiform rain (SR) within a range of Dm from 1 to 3.5 mm. The rain samples from six Parsivel sites over the middle reaches of the Yangtze River during the 2016–2018 meiyu seasons have been collected and processed. The frequency occurrences for rain rates (RR) < 5 and > 10 mm h-1 are 83.9% and 7.4%, respectively, but they contribute 30.5% and 52.1 % of the total accumulated rainfall. Comparing the results with those over the lower reaches, the RR and total accumulated rainfall over the middle reaches are greater, especially for heavy rainfall. The rain drop size distributions (DSDs) in this study are wider and have higher number concentration than those from the lower reaches.

Raindrop size distribution, Meiyu front, disdromet↗
DOE OSTI2020

Optimal Estimation Retrievals and Their Uncertainties: What Every Atmospheric Scientist Should Know

Remote sensing instruments are heavily used to provide observations for both the operational and research communities. These sensors do not provide direct observations of the desired atmospheric variables, but instead, retrieval algorithms are necessary to convert the indirect observations into the variable of interest. It is critical to be aware of the underlying assumptions made by many retrieval algorithms, including that the retrieval problem is often ill posed and that there are various sources of uncertainty that need to be treated properly. In short, the retrieval challenge is to invert a set of noisy observations to obtain estimates of atmospheric quantities. The problem is often complicated by imperfect forward models, by imperfect prior knowledge, and by the existence of nonunique solutions. Optimal estimation (OE) is a widely used physical retrieval method that combines measurements, prior information, and the corresponding uncertainties based on Bayes’s theorem to find an optimal solution for the atmospheric state. Furthermore, OE also allows the relative contributions of the different sources of error to the uncertainty in the final retrieved atmospheric state to be understood. Here, we provide a novel Python library to illustrate the use of OE for inverse problems in the atmospheric sciences. We introduce two example problems: how to retrieve drop size distribution parameters from radar observations and how to retrieve the temperature profile from ground-based microwave sensors. Using these examples, we discuss common pitfalls, how the various error sources impact the retrieval, and how the quality of the retrieval results can be quantified.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Driving Parameters for Distributed and Centralized Air Transportation Architectures

This report considers the problem of intersecting aircraft flows under decentralized conflict avoidance rules. Using an Eulerian standpoint (aircraft flow through a fixed control volume), new air traffic control models and scenarios are defined that enable the study of long-term airspace stability problems. Considering a class of two intersecting aircraft flows, it is shown that airspace stability, defined both in terms of safety and performance, is preserved under decentralized conflict resolution algorithms. Performance bounds are derived for the aircraft flow problem under different maneuver models. Besides analytical approaches, numerical examples are presented to test the theoretical results, as well as to generate some insight about the structure of the traffic flow after resolution. Considering more than two intersecting aircraft flows, simulations indicate that flow stability may not be guaranteed under simple conflict avoidance rules. Finally, a comparison is made with centralized strategies to conflict resolution.

Feron, Eric↗
NASA NTRS2001

Properties of Air Traffic Conflicts for Free and Structured Routing

This paper analyzes the properties of air traffic conflicts in a future free routing system against those in the current structured routing system. Simulation of en route air traffic operations (above 18,000 ft) over the contiguous United States for a 24-hour period, constructed with initial conditions from actual air traffic data, were conducted using the Future ATM Concepts Evaluation Tool (FACET). Free routes were modeled as great circle (direct) routes from origin to destination, and structured routes were derived from actual flight plans along the current system of air routes. The conflict properties analyzed in this study include: (1) Total number of conflicts; (2) Distributions of key conflict parameters; and, (3) Categorization of conflicts into independent conflicts and two types of interacting conflicts. Preliminary results (for Denver Center traffic) indicate that conflict properties in a free routing system are different from those in the current structured routing system. In particular, a free routing system has significantly fewer conflicts, involving a correspondingly smaller number of aircraft, compared to the current structured routing system. Additionally, the conflict parameter distributions indicate that free routing conflicts are less intrusive than structured routing conflicts, and would therefore require small trajectory deviations for resolution.

Bilimoria, Karl D.↗
NASA NTRS2017

Global Distribution and Parameter Dependences of Gravity Wave Activity in the Martian Upper Thermosphere Derived from MAVEN NGIMS Observations

Wavelike perturbations in the Martian upper thermosphere observed by the Neutral Gas Ion Mass Spectrometer (NGIMS) onboard the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft have been analyzed. The amplitudes of small-scale perturbations with apparent wavelengths between approx. 100 and approx. 500 km in the Ar density around the exobase show a clear dependence on temperature (T(sub 0)) of the upper thermosphere. The average amplitude of the perturbations is approx. 10% on the dayside and approx. 20% on the nightside, which is about 2 and 10 times larger than those observed in the Venusian upper thermosphere and in the low-latitude region of Earths upper thermosphere, respectively. The amplitudes are inversely proportional to T(sub 0), suggesting saturation due to convective instability in the Martian upper thermosphere. After removing the dependence on T(sub 0), dependences of the average amplitude on the geographic latitude and longitude and solar wind parameters are found to be not larger than a few percent. These results suggest that the amplitudes of small-scale perturbations are mainly determined by convective breaking saturation in the upper thermosphere on Mars, unlike those on Venus and Earth.

Thermosphere↗
NASA NTRS1967

Effect of Propellant Feed System Coupling and Hydraulic Parameters on Analysis of Chugging

A digital distributed parameter model was used to study the effects of propellant-feed- system coupling and various hydraulic parameters on the analytical prediction of chugging instabilities. Coupling between the combustion chamber and feed system was controlled by varying the compliance of the injector-dome region. The coupling with the feed system above the pump was varied by changing the amount of cavitation compliance at the pump inlet. The stability limits and chugging frequencies proved to be strongly dependent on the degree of feed-system coupling. The maximum stability condition occurred with intermediate coupling. Under conditions of a high degree of feed-system-combustor coupling, the stability limits and chugging frequencies were primarily dependent on the feed-system characteristics; the responses were characterized by beating patterns. For the system analyzed, the pump suction line had little effect on the stability limits or chugging frequencies. Beating, present under the condition of near zero injector -dome compliance, was eliminated when the suction line was decoupled by employing a sufficiently high value of pump-inlet compliance. Under conditions of maximum feed-system coupling, the magnitude and distribution of line losses in the discharge line had a significant effect on the stability limits but had negligible effect on the chugging frequency and beating characteristics. Also, the length of the discharge line greatly affected the stability limits, chugging frequency, and beating characteristics. The length of the suction line, however, had little effect on the stability limits and chugging frequency but did influence the beating pattern. A resistive-shunt device attached to the pump discharge line to suppress chugging was investigated. The analysis showed that the device was effective under conditions of high feed-system coupling.

CHUGGING↗
DOE OSTI2024

A Bayesian Multi-fidelity Neural Network to Predict Nonlinear Frequency Backbone Curves

The use of structural mechanics models during the design process often leads to the development of models of varying fidelity. Often low-fidelity models are efficient to simulate but lack accuracy, while the high-fidelity counterparts are accurate with less efficiency. Here, this paper presents a multi-fidelity surrogate modeling approach that combines the accuracy of a high-fidelity finite element model with the efficiency of a low-fidelity model to train an even faster surrogate model that parameterizes the design space of interest. The objective of these models is to predict the nonlinear frequency backbone curves of the Tribomechadynamics Research Challenge benchmark structure which exhibits simultaneous nonlinearities from frictional contact and geometric nonlinearity. The surrogate model consists of an ensemble of neural networks that learn the mapping between low and high-fidelity data through nonlinear transformations. Bayesian neural networks are used to assess the surrogate model's uncertainty. Once trained, the multi-fidelity neural network is used to perform sensitivity analysis to assess the influence of the design parameters on the predicted backbone curves. Additionally, Bayesian calibration is performed to update the input parameter distributions to correlate the model parameters to the collection of experimentally measured backbone curves.

42 ENGINEERING↗
NASA NTRS1991

Bremsstrahlung x rays from Jovian auroral electrons

In a recent paper by D. D. Barbosa, it is argued that electron bremsstrahlung is the most likely source of the auroral x-ray emissions that have been observed at Jupiter. Barbosa bases his argument on observational and theoretical studies of the production of secondary electrons in the Earth's aurora. It is argued here that Barbosa's interpretation is flawed because it ignors the constraint that the primary electron distribution parameters place on the parameters for the secondary electron distribution. As a result, Barbosa's postulated secondary electron fluxes are over three orders of magnitude greater than the theory of auroral electrons permits.

Waite, J. Hunter, Jr.↗
NASA NTRS2012

Microwave Properties of Ice-Phase Hydrometeors for Radar and Radiometers: Sensitivity to Model Assumptions

A simplied framework is presented for assessing the qualitative sensitivities of computed microwave properties, satellite brightness temperatures, and radar reflectivities to assumptions concerning the physical properties of ice-phase hydrometeors. Properties considered included the shape parameter of a gamma size distribution andthe melted-equivalent mass median diameter D0, the particle density, dielectric mixing formula, and the choice of complex index of refraction for ice. We examine these properties at selected radiometer frequencies of 18.7, 36.5, 89.0, and 150.0 GHz; and radar frequencies at 2.8, 13.4, 35.6, and 94.0 GHz consistent with existing and planned remote sensing instruments. Passive and active microwave observables of ice particles arefound to be extremely sensitive to the melted-equivalent mass median diameter D0 ofthe size distribution. Similar large sensitivities are found for variations in the ice vol-ume fraction whenever the geometric mass median diameter exceeds approximately 1/8th of the wavelength. At 94 GHz the two-way path integrated attenuation is potentially large for dense compact particles. The distribution parameter mu has a relatively weak effect on any observable: less than 1-2 K in brightness temperature and up to 2.7 dB difference in the effective radar reflectivity. Reversal of the roles of ice and air in the MaxwellGarnett dielectric mixing formula leads to a signicant change in both microwave brightness temperature (10 K) and radar reflectivity (2 dB). The choice of Warren (1984) or Warren and Brandt (2008) for the complex index of refraction of ice can produce a 3%-4% change in the brightness temperature depression.

Microwave properties↗
DOE OSTI2024

Quantifying Drivers of Methane Hydrobiogeochemistry in a Tidal River Floodplain System

The influence of coastal ecosystems on global greenhouse gas (GHG) budgets and their response to increasing inundation and salinization remains poorly constrained. In this study, we have integrated an uncertainty quantification (UQ) and ensemble machine learning (ML) framework to identify and rank the most influential processes, properties, and conditions controlling methane behavior in a freshwater floodplain responding to recently restored seawater inundation. Our unique multivariate, multiyear, and multi-site dataset comprises tidal creek and floodplain porewater observations encompassing water level, salinity, pH, temperature, dissolved oxygen (DO), dissolved organic carbon (DOC), total dissolved nitrogen (TDN), partial pressure of carbon dioxide (pCO 2 ), nitrous oxide (pN 2 O), methane (pCH 4 ), and the stable isotopic composition of methane (δ 13 CH 4 ). Additionally, we incorporated topographical data, soil porosity, hydraulic conductivity, and water retention parameters for UQ analysis using a previously developed 3D variably saturated flow and transport floodplain model for a physical mechanistic understanding of factors influencing groundwater levels and salinity and, therefore, CH 4 . Principal component analysis revealed that groundwater level and salinity are the most significant predictors of overall biogeochemical variability. The ensemble ML models and UQ analyses identified DO, water level, salinity, and temperature as the most influential factors for porewater methane levels and indicated that approximately 80% of the total variability in hourly water levels and around 60% of the total variability in hourly salinity can be explained by permeability, creek water level, and two van Genuchten water retention function parameters: the air-entry suction parameter α and the pore size distribution parameter m. These findings provide insights on the physicochemical factors in methane behavior in coastal ecosystems and their representation in local- to global-scale Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quadrupole Effects in the Photoionisation of Sodium 3s in the Vicinity of the Dipole Cooper Minimum

A procedure to obtain relativistic expressions for photoionisation angular distribution parameters using the helicity formulation is discussed for open-shell atoms. Electric dipole and quadrupole transition matrix elements were considered in the present work, to study the photoionisation dynamics of the 3s electron of the sodium atom in the vicinity of the dipole Cooper minimum. We studied dipole–quadrupole interference effects on the photoelectron angular distribution in the region of the dipole Cooper minimum. Interference with quadrupole transitions was found to alter the photoelectron angular distribution, even at rather low photon energies. The initial ground and final ionised state discrete wavefunctions of the atom were obtained in the present work using GRASP, and we employed RATIP with discrete wavefunctions, to construct continuum wavefunctions and to calculate transition amplitudes, total cross-sections and angular distribution asymmetry parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

A Bayesian Approach to the Eagar–Tsai Model for Melt Pool Geometry Prediction with Implications in Additive Manufacturing of Metals

Here, this paper focuses on improving the melt pool geometry predictions and quantifying uncertainties using an adapted version of the Eagar–Tsai (E–T) model that incorporates temperature-dependent properties of the material as well as powder conditions. Additionally, Bayesian inference is employed to predict distributions for the E–T model input parameters of laser absorptivity and powder bed porosity by incorporating experimental results into the analysis. Monte Carlo uncertainty propagation is then used with these parameter distributions to estimate the melt pool depth and associated uncertainty. Our results for the 316L stainless steel suggest that both the absorptivity and powder bed porosity are strongly influenced by the laser power. In contrast, the scanning speed has only a marginal effect on both the absorptivity and powder bed porosity. We constructed a printability map using the Bayesian E–T model based on power-dependent input parameter values to demonstrate the merit of the approach. The Bayesian approach improved the accuracy in predicting the keyhole regions in the laser power-scan speed parameter space for the 316L stainless steel. Although applied to a specific adaptation of the E–T model, the method put forth can be extended to quantify uncertainties in other numerical models as well as in the estimation of unknown parameters.

316L Stainless Steel (SS).↗
DOE OSTI2021

Application of Sequential Design of Experiments (SDoE) to Large Pilot-Scale Solvent-Based CO2 Capture Process at Technology Centre Mongstad (TCM)

The United States Department of Energy’s Carbon Capture Simulation for Industry Impact (CCSI2) program has developed a framework for sequential design of experiments (SDoE) that aims to maximize knowledge gained from budget- and schedule-limited pilot scale testing. SDoE was applied to the planning and execution of campaigns for testing CO2 capture systems at pilot-scale in order to optimally allocate resources available for the testing. In this methodology, a stochastic process model is developed by quantifying the parametric uncertainty in submodels of interest; for a solvent-based CO2 capture system, these may include physical properties and equipment performance submodels (e.g., mass transfer, interfacial area). This uncertainty is propagated through the full process model, over variable operating conditions, for estimating the resulting uncertainty in key model outputs (e.g., percentage of CO2 capture, solvent regeneration energy requirement). In developing a data collection plan, the predicted output uncertainty is incorporated into an algorithm that seeks simultaneously to select process operating conditions for which the predicted uncertainty is relatively high and to ensure that the entire space of operation is well represented. This test plan is then used to guide operation of the pilot plant at varying steady-state conditions, with resulting process data incorporated into the existing model using Bayesian inference to refine parameter distributions. The updated stochastic model, with reduced parametric uncertainty from data collected, is then used to guide additional data collection, thus the sequential nature of the experimental design. The SDoE process was implemented at the pilot test unit (12 MWe in scale) at Norway’s Technology Centre Mongstad (TCM) in a summer 2018 test campaign with aqueous monoethanolamine (MEA). During the test campaign, the varied operating conditions included the flowrates of circulated solvent, flue gas, and reboiler steam and the CO2 concentration in the flue gas. The process data were used to update probability distributions of mass transfer and interfacial area parameters of a stochastic process model developed by the CCSI2 team. Two iterations of the SDoE process were executed, resulting in the uncertainty in model predicted CO2 capture percentage decreasing by an average of 58.0 ± 4.7% over the full input space of interest. This work demonstrates the potential of the SDoE process for model refinement through reduction in process model parametric uncertainty, and ultimately risk in scale-up, in CO2 capture technology performance.

carbon capture↗