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NASA NTRS2017

Using the Coronal Evolution to Successfully Forward Model CMEs' In Situ Magnetic Profiles

Predicting the effects of a coronal mass ejection (CME) impact requires knowing if impact will occur, which part of the CME impacts, and its magnetic properties. We explore the relation between CME deflections and rotations, which change the position and orientation of a CME, and the resulting magnetic profiles at 1 AU. For 45 STEREO-era, Earth-impacting CMEs, we determine the solar source of each CME, reconstruct its coronal position and orientation, and perform a ForeCAT (Forecasting a CME's Altered Trajectory) simulation of the coronal deï¬‚ection and rotation. From the reconstructed and modeled CME deflections and rotations, we determine the solar cycle variation and correlations with CME properties. We assume no evolution between the outer corona and 1 AU and use the ForeCAT results to drive the ForeCAT In situ Data Observer (FIDO) in situ magnetic field model, allowing for comparisons with ACE and Wind observations. We do not attempt to reproduce the arrival time. On average FIDO reproduces the in situ magnetic field for each vector component with an error equivalent to 35 percent of the average total magnetic field strength when the total modeled magnetic field is scaled to match the average observed value. Random walk best fits distinguish between ForeCAT's ability to determine FIDO's input parameters and the limitations of the simple flux rope model. These best fits reduce the average error to 30 percent.The FIDO results are sensitive to changes of order a degree in the CME latitude, longitude, and tilt, suggesting that accurate space weather predictions require accurate measurements of a CME's position and orientation.

Kay, C.↗

NASA NTRS2017

Single Degree-of-Freedom Modeling of SLS Liquid Hydrogen Pre-Valve Flow Guide to Enable Rapid Transient Analysis

A unique single degree-of-freedom approximation technique has been developed to enable rapid application of a temporally-defined multi-spectral semi-narrow-band loading for generation of realistic stress/cycle values compared to a resonant analysis. The technique uses the harmonic analysis at resonance of a high-fidelity finite element model to produce a transfer function, which is then used to calibrate the response of the SDOF model. A standard numerical ordinary differential equation solver is then used to obtain the temporal response, and its histogram is used in a fatigue/fracture model. This technique is related to other SDOF methods used widely in industry, such as Miles' Equation and the Shock Response Spectra, but it is unique in that it produces a realistic time history of the response. The most obvious error in the process, which is the effect of closely-spaced modes, was also assessed using the parallel application of several SDOF models, and the error is shown to be small. The application of this unique and tractable reduced-order methodology has enabled the SLS program to avoid substantial cost and schedule penalties if a redesign or change of material were required. It has also enabled quick analysis of a number of other structures undergoing the same or similar excitation fields, and quick assessment when the excitation and structural configuration has been altered due to design changes in the system.

Brown, Andrew M.↗

NASA NTRS1994

Parameterization of bulk condensation in numerical cloud models

The accuracy of the moist saturation adjustment scheme has been evaluated using a three-dimensional explicit microphysical cloud model. It was found that the error in saturation adjustment depends strongly on the Cloud Condensation Nucleii (CCN) concentration in the ambient atmosphere. The scheme provides rather accurate results in the case where a sufficiently large number of CCN (on the order of several hundred per cubic centimeter) is available. However, under conditions typical of marine stratocumulus cloud layers with low CCN concentration, the error in the amounts of condensed water vapor and released latent heat may be as large as 40%-50%. A revision of the saturation adjustment scheme is devised that employs the CCN concentration, dynamical supersaturation, and cloud water content as additional variables in the calculation of the condensation rate. The revised condensation model reduced the error in maximum updraft and cloud water content in the climatically significant case of marine stratocumulus cloud layers by an order of magnitude.

Kogan, Yefim L.↗

NASA NTRS2012

Progress Toward Affordable High Fidelity Combustion Simulations Using Filtered Density Functions for Hypersonic Flows in Complex Geometries

Significant progress has been made in the development of subgrid scale (SGS) closures based on a filtered density function (FDF) for large eddy simulations (LES) of turbulent reacting flows. The FDF is the counterpart of the probability density function (PDF) method, which has proven effective in Reynolds averaged simulations (RAS). However, while systematic progress is being made advancing the FDF models for relatively simple flows and lab-scale flames, the application of these methods in complex geometries and high speed, wall-bounded flows with shocks remains a challenge. The key difficulties are the significant computational cost associated with solving the FDF transport equation and numerically stiff finite rate chemistry. For LES/FDF methods to make a more significant impact in practical applications a pragmatic approach must be taken that significantly reduces the computational cost while maintaining high modeling fidelity. An example of one such ongoing effort is at the NASA Langley Research Center, where the first generation FDF models, namely the scalar filtered mass density function (SFMDF) are being implemented into VULCAN, a production-quality RAS and LES solver widely used for design of high speed propulsion flowpaths. This effort leverages internal and external collaborations to reduce the overall computational cost of high fidelity simulations in VULCAN by: implementing high order methods that allow reduction in the total number of computational cells without loss in accuracy; implementing first generation of high fidelity scalar PDF/FDF models applicable to high-speed compressible flows; coupling RAS/PDF and LES/FDF into a hybrid framework to efficiently and accurately model the effects of combustion in the vicinity of the walls; developing efficient Lagrangian particle tracking algorithms to support robust solutions of the FDF equations for high speed flows; and utilizing finite rate chemistry parametrization, such as flamelet models, to reduce the number of transported reactive species and remove numerical stiffness. This paper briefly introduces the SFMDF model (highlighting key benefits and challenges), and discusses particle tracking for flows with shocks, the hybrid coupled RAS/PDF and LES/FDF model, flamelet generated manifolds (FGM) model, and the Irregularly Portioned Lagrangian Monte Carlo Finite Difference (IPLMCFD) methodology for scalable simulation of high-speed reacting compressible flows.

Drozda, Tomasz G.↗

NASA NTRSDate not supplied

Multi-Party Flight Trajectory Negotiation for Upper Class E Traffic Management

A new operational concept has been proposed in Upper Class E airspace at or above 60,000 feet (Flight Level / FL600), which will allow operators of diverse vehicle characteristics to cooperatively manage and share their operational intents with neighboring operators to avoid conflict. There is a consensus in the community that negotiation for strategic deconfliction is needed, but there are no specific guidelines for how the negotiation should be conducted. There is a need for a structured and cooperative way to resolve the conflict between a wide variety of aircraft projected to be operating in Upper Class E for the negotiation to be carried out routinely. The use of negotiation models are a promising solution that can resolve conflict risks during flight in real-time while taking into account the uncertainty of future vehicle positions and dynamic business considerations. A two-party negotiation model has been researched, but as the traffic demand grows, there is a higher likelihood of conflict involving multiple aircraft that would require a method to handle multi-party conflict. This paper proposes a cooperative multi-party negotiation model inspired by game theory concepts for application to flight trajectory negotiation in Upper Class E traffic management. This model can be applied in flight with operators communicating directly after a potential conflict is detected. Some of the model’s benefits include allowing business costs to be private to operators, allowing operators to collaborate together to find conflict-free flight trajectories, and being compatible with different aircraft and operation types. This model provides a structured procedure for conflict resolution that can handle conflict involving multiple parties, assuming each operator is willing to take on a small cost to themselves in order to reduce the total cost to the group.

Upper Class E Traffic Management (ETM)↗

DOE OSTI2025

Preferential adsorption of noble gases in zeolitic tuff with variable saturation: A modeling study of counter-intuitive diffusive-adsorptive behavior

Noble gas transport through geologic media has important applications in the prediction and characterization of measured gas signatures related to underground nuclear explosions (UNEs). Retarding processes such as adsorption can cause significant species fractionation of radionuclide gases, which has implications for measured and predicted signatures used to distinguish radioxenon originating from civilian nuclear facilities or from UNEs. Accounting for the effects of variable water saturation in geologic media on tracer transport is one of the most challenging aspects of modeling gas transport because there is no unifying relationship for the associated tortuosity changes between different rock types, and reactive transport processes such as adsorption that are affected by the presence of water likewise behave differently between gas species. In this study, we perform numerical diffusive-adsorptive transport simulations to estimate gas transport parameters associated with bench-scale laboratory diffusion cell experiments measuring breakthrough in zeolitic and non-zeolitic rocks for a gaseous mixture of xenon, krypton, and SF 6 at varying degrees of water saturation (S w ). Counter-intuitive transport behavior was observed in the zeolitic rock experiments whereby breakthrough concentrations were significantly higher when the core was partially saturated (S w = 17 %) than under dry (S w = 0 %) conditions. Breakthrough of xenon was especially retarded in the dry core – likely due to comparatively high affinity of xenon for zeolitic adsorption sites – and estimated effective diffusion coefficients for all gases were approximately an order of magnitude lower than what is predicted by porosity-tortuosity models. We propose the counter-intuitive behavior observed is because water infiltration of zeolite nanopores reduces both the adsorptive capacity of the rock and the tortuosity of connected flow paths. We developed a two-site competitive kinetic Langmuir adsorption reaction for the porous media transport simulator in order to constrain transport parameters within zeolitic tuff, where differential adsorption to zeolite and non-zeolite pores was observed. We determined that liquid saturation-dependent diffusive-adsorptive transport is affected by subtle and at times competing processes that are specific to different gases, which have a significant overall influence on effective transport parameters.

58 GEOSCIENCES↗

DOE OSTI2023

Chemical compression and ferroic orders in La substituted BiFe O 3

Chemical compression effects on the ferroic orders in La substituted BiFeO 3 are studied by atomic pair distribution function analysis and structure modeling. While rhombohedral BiFeO 3 exhibits ferroelectricity and antiferromagnetism (AF) with a cycloidal Fe spin arrangement leading to zero magnetization, La substituted BiFeO 3 exhibits a reduced lattice polarization, strengthened AF order, and an apparently suppressed spin cycloid leading to nonzero magnetization. Furthermore, the observed changes in the ferroic orders arise from the chemical compression induced changes in the octahedral rotation and ferroelectric displacement of Bi atoms, which appear as lattice degrees of freedom entangling the electronic and magnetic orders in BiFeO 3 .

36 MATERIALS SCIENCE↗

DOE OSTI2016

Assessing the effects of noise abatement measures on health risks: A case study in Istanbul

In recent decades, noise pollution caused by industrialization and increased motorization has become a major concern around the world because of its adverse effects on human well-being. Therefore, transportation agencies have been implementing noise abatement measures in order to reduce road traffic noise. However, limited attention is given to noise in environmental assessment of road transportation systems. This paper presents a framework for a health impact assessment model for road transportation noise emissions. The model allows noise impacts to be addressed with the health effects of air pollutant and greenhouse gas emissions from road transportation. The health damages assessed in the model include annoyance, sleep disturbance, and cardiovascular disease in terms of acute myocardial infarction. The model was applied in a case study in Istanbul in order to evaluate the change in health risks from the implementation of noise abatement strategies. The noise abatement strategies evaluated include altering pavement surfaces in order to absorb noise and introducing speed limits. It was shown that significant improvements in health risks can be achieved using open graded pavement surfaces and introducing speed limits on highways. - Highlights: • Transportation noise has a significant effect on health. • Noise should be included in the environmental assessment of transportation systems. • Traffic noise abatement measures include noise reducing pavements and speed limits. • Noise abatement measures help reduce the health risks of transportation noise. • Speed limit reduction on uncongested roads is an effective way to reduce health risks.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Jet Noise Modeling Using an Acoustic Analogy: From Theoretical Formulation to Practical Noise Predictions

In this presentation an overview of the development of an acoustic analogy formulation, and its implementation into a reduced-order prediction method for turbulent jet mixing noise, will be given. The definition and rationale of an acoustic analogy approach to the prediction of flow-generated noise will be provided. A high-level description of the mathematical processes involved will be outlined in the context of a particular formulation developed at NASA Glenn Research Center. The modelling approximations needed to implement the general theoretical formulation into a practical noise prediction tool will be discussed. Sample results obtained using a noise prediction code based on the NASA Glenn formulation, and comparisons with experimental data, will be presented for a series of turbulent jet test cases. A view on the prospects for continued use of acoustic analogy-based methods for the prediction of flow-generated noise and the assessment of noise-reduction technologies will conclude the presentation.

Jet noise↗

DOE OSTI2021

The curled wake model: a three-dimensional and extremely fast steady-state wake solver for wind plant flows

Abstract. Wind turbine wake models typically require approximations, such as wake superposition and deflection models, to accurately describe wake physics. However, capturing the phenomena of interest, such as the curled wake and interaction of multiple wakes, in wind power plant flows comes with an increased computational cost. To address this, we propose a new hybrid method that uses analytical solutions with an approximate form of the Reynolds-averaged Navier–Stokes equations to solve the time-averaged flow over a wind plant. We compare results from the solver to supervisory control and data acquisition data from the Lillgrund wind plant obtaining wake model predictions which are generally within 1 standard deviation of the mean power data. We perform simulations of flow over the Columbia River Gorge to demonstrate the capabilities of the model in complex terrain. We also apply the solver to a case with wake steering, which agreed well with large-eddy simulations. This new solver reduces the time – and therefore the related cost – it takes to simulate a steady-state wind plant flow (on the order of seconds using one core). Because the model is computationally efficient, it can also be used for different applications including wake steering for wind power plants and layout optimization.

17 WIND ENERGY↗

NASA NTRS2010

Predicting Tropical Cyclogenesis with a Global Mesoscale Model: Hierarchical Multiscale Interactions During the Formation of Tropical Cyclone Nargis(2008)

Very severe cyclonic storm Nargis devastated Burma (Myanmar) in May 2008, caused tremendous damage and numerous fatalities, and became one of the 10 deadliest tropical cyclones (TCs) of all time. To increase the warning time in order to save lives and reduce economic damage, it is important to extend the lead time in the prediction of TCs like Nargis. As recent advances in high-resolution global models and supercomputing technology have shown the potential for improving TC track and intensity forecasts, the ability of a global mesoscale model to predict TC genesis in the Indian Ocean is examined in this study with the aim of improving simulations of TC climate. High-resolution global simulations with real data show that the initial formation and intensity variations of TC Nargis can be realistically predicted up to 5 days in advance. Preliminary analysis suggests that improved representations of the following environmental conditions and their hierarchical multiscale interactions were the key to achieving this lead time: (1) a westerly wind burst and equatorial trough, (2) an enhanced monsoon circulation with a zero wind shear line, (3) good upper-level outflow with anti-cyclonic wind shear between 200 and 850 hPa, and (4) low-level moisture convergence.

Shen, B.-W.↗

NASA NTRS1991

A Markov model reduction technique for fault tolerant processor reliability analysis

A fault tolerant processor (FTP) plays a key role in many high performance, safety-critical control system applications. Realistic modeling of an FTP is crucial to gaining a high degree of confidence in the reliability and safety analysis of such a system. While fidelity is clearly a major consideration, a practical model must also be kept to a moderate size to allow its incorporation into the overall system model. This paper presents a systematic reduction technique that starts from a complex, detailed model of a triple, redundant FTP and produces a low order approximation of very high accuracy. The existence of two distinct time scales represents the key to the success of the technique. No eigenvalue solution or coordinate transformation are needed. The reduced model captures all the important features of the detailed model, is amenable to an analytical solution and provides insight into the reconfiguration behavior of an FTP.

Schor, Andrei L.↗

NASA NTRS1975

A multilevel control system for the large space telescope

A multilevel scheme was proposed for control of Large Space Telescope (LST) modeled by a three-axis-six-order nonlinear equation. Local controllers were used on the subsystem level to stabilize motions corresponding to the three axes. Global controllers were applied to reduce (and sometimes nullify) the interactions among the subsystems. A multilevel optimization method was developed whereby local quadratic optimizations were performed on the subsystem level, and global control was again used to reduce (nullify) the effect of interactions. The multilevel stabilization and optimization methods are presented as general tools for design and then used in the design of the LST Control System. The methods are entirely computerized, so that they can accommodate higher order LST models with both conceptual and numerical advantages over standard straightforward design techniques.

D D Siljak↗

DOE OSTI2023

Influence of aluminum incorporation and aqueous conditions on metal ion release of high-Ni transition metal oxide nanomaterials

Developing a materials perspective of how to control the degradation and negative impact of complex metal oxides requires an integrated understanding of how these nanomaterials transform in the environment and interact with biological systems. Doping with aluminum is known to stabilize oxide materials, but has not been assessed cohesively from synthesis to environmental fate and biological impact. In the present study, the influence of aluminum doping on metal ion release from transition metal oxides was investigated by comparing aqueous transformations of lithium nickel cobalt aluminum oxide (LiNi 0.82 Co 0.15 Al 0.03 O 2 ; NCA) and lithium nickel cobalt oxide (LiNi 0.80 Co 0.20 O 2 ; NC) nanoparticles and by calculating the energetics of metal release using a density functional theory (DFT) and thermodynamics method. Two model environmental organisms were used to assess biological impact, and metal ion release was compared for NCA and NC nanoparticles incubated in their respective growth media: moderately hard reconstituted water (MHRW) for the freshwater invertebrate Daphnia magna (D. magna) and minimal growth medium for the Gram-negative bacterium Shewanella oneidensis MR-1 (S. oneidensis). Further, the amount of metal ions released was reduced for NCA compared to NC in MHRW, which correlated to changes in the modeled energetics of release upon Al substitution in the lattice. In minimal medium, metal ion release was approximately an order of magnitude higher compared to MHRW and was similar to the stoichiometry of the bulk nanoparticles for both NCA and NC. Interpretation of the release profiles and modeling indicated that the increase in total metal ion release and the reduced influence of Al doping arises from lactate complexation of metal ions in solution. The relative biological impacts of NC and NCA exposure for both S. oneidensis and D. magna were consistent with the metal release trends observed for minimal medium and MHRW, respectively. Together, these results demonstrate how a combined experimental and computational approach provides valuable insight into the aqueous transformations and biological impacts of complex metal oxide nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1975

Noise reduction studies for the Cessna model 337 (0-2) airplane

A study was undertaken to determine the noise reduction potential of the 0-2 airplane in order to reduce its aural detection distance. Static and flyover noise measurements were made to document the noise signature of the unmodified airplane. The results show that significant reductions in aural detection distance can be achieved by the combination of propeller geometry changes and the addition of engine exhaust mufflers. The best results were estimated for the aircraft equipped with a six-blade propeller operating at 3/4 engine speed in combination with a 3.49 cubic foot exhaust muffler installed on each engine. Detection distance for the modified aircraft is estimated to be reduced from about 4-1/4 miles to about 1-1/2 miles when the aircraft is operating at an altitude of 1,000 ft over grassy terrain. Reducing the altitude to 300 ft over a leafy jungle ground cover should reduce the aural detection distance to 0.9 miles. Reduced aural detection distances were also indicated for a modification utilizing a direct-drive six-blade propeller of reduced radius along with smaller exhaust mufflers.

Hilton, D. A.↗

DOE OSTI2015

Using Advanced Modeling to Accelerate the Scale-Up of Carbon Capture Technologies

Carbon capture and storage (CCS) is one of many approaches that are critical for significantly reducing domestic and global CO2 emissions. The U.S. Department of Energy’s Clean Coal Technology Program Plan envisions 2nd generation CO2 capture technologies ready for demonstration-scale testing around 2020 with the goal of enabling commercial deployment by 2025 [1]. Third generation technologies have a similarly aggressive timeline. A major challenge is that the development and scale-up of new technologies in the energy sector historically takes up to 15 years to move from the laboratory to pre-deployment and another 20 to 30 years for widespread industrial scale deployment. In order to help meet the goals of the DOE carbon capture program, the Carbon Capture Simulation Initiative (CCSI) was launched in early 2011 to develop, demonstrate, and deploy advanced computational tools and validated multi-scale models to reduce the time required to develop and scale up new carbon capture technologies. The CCSI Toolset (1) enables promising concepts to be more quickly identified through rapid computational screening of processes and devices, (2) reduces the time to design and troubleshoot new devices and processes by using optimization techniques to focus development on the best overall process conditions and by using detailed device-scale models to better understand and improve the internal behavior of complex equipment, and (3) provides quantitative predictions of device and process performance during scale up based on rigorously validated smaller scale simulations that take into account model and parameter uncertainty[2]. This article focuses on essential elements related to the development and validation of multi-scale models in order to help minimize risk and maximize learning as new technologies progress from pilot to demonstration scale.

Miller, David↗

DOE OSTI2019

Application of deep artificial neural networks to multi-dimensional flamelet libraries and spray flames

The “curse of dimensionality” has limited the applicability and expansion of tabulated combustion models. While the tabulated flamelet model and other multi-dimensional manifold approaches have shown predictive capability, the associated tabulation involves the storage of large lookup tables, requiring large memory as well as multi-dimensional interpolation subroutines, all implemented during runtime. As such, this work investigates the use of deep artificial neural networks to replace lookup tables in order to reduce the memory footprint and increase the computational speed of tabulated flamelets and related approaches. Specifically, different strategic approaches to training the artificial neural network models are explored and a grouped multi-target artificial neural network is introduced, which takes advantage of the ability of artificial neural networks to map an input space to multiple targets by classifying the species based on their correlation to one another. The grouped multi-target artificial neural network approach is validated by applying it to an n-dodecane spray flame using conditions of the Spray A flame from the Engine Combustion Network and comparing global flame characteristics for different ambient conditions using a well-established large-eddy simulation framework. The same framework is then extended to the simulations of methyl decanoate combustion in a compression ignition engine. The validation studies show that the grouped multi-target artificial neural networks are able to accurately capture flame liftoff, autoignition, two-stage heat release and other quantitative trends over a range of conditions. The use of neural networks in conjunction with the grouping mechanism as performed in the grouped multi-target artificial neural network produces a significant reduction in the memory footprint and computational costs for the code and, thus, widens the operating envelope for higher fidelity engine simulations with detailed mechanisms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

DiaMonD: An Integrated Multifaceted Approach to Mathematics at the Interfaces of Data, Models, and Decisions

The major goal of the project was to invent, analyze, implement, and apply new algorithms to speed up the computational simulation of complex systems in settings in which multiple simulations are needed. The main efforts we undertook are as follows: 1. Develop novel reduced order methods to reduce the costs of simulations, especially in settings (e.g., UQ, inference, optimization and control) for which numerous simulation are needed and also for nonlocal problems (e.g., fractional derivative, anomalous diffusion, nonlocal mechanics) for which lack of sparsity results in more expensive full-order simulation than encountered in partial differential equations settings; rigorous analyses as well as computational tests were carried out, 2. Develop multifidelity methods based on the usage of a variety of models having different fidelities and different costs to accelerate simulations again in settings where numerous simulations are needed or are especially expensive; rigorous analyses as well as computational tests were carried out, 3. Develop ensemble methods to reduced the costs of simulations again in settings where numerous simulations are needed or are especially expensive; rigorous analyses as well as computational tests were carried out, and 4. Analyze a model for Richardson pair dispersion in turbulent flows and develop discretization methods for the efficient and accurate approximations of the solution of the model; rigorous analyses as well as computational tests were carried out.

97 MATHEMATICS AND COMPUTING↗