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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Low Speed Aerodynamics of the X-38 CRV

This project was performed in support of the engineering development of the NASA X-38 Crew Return Vehicle (CRV)system. Wind tunnel experiments were used to visualize various aerodynamic phenomena encountered by the CRV during the final stages of descent and landing. Scale models of the CRV were used to visualize vortex structures above and below the vehicle, and in its wake, and to quantify their trajectories. The effect of flaperon deflection on these structures was studied. The structure and dynamics of the CRV's wake during the drag parachute deployment stage were measured. Regions of high vorticity were identified using surveys conducted in several planes using a vortex meter. Periodic shedding of the vortex sheets from the sides of the CRV was observed using laser sheet videography as the CRV reached high angles of attack during the quasi-steady pitch-up prior to parafoil deployment. Using spectral analysis of hot-film anemometer data, the Strouhal number of these wake fluctuations was found to be 0.14 based on the model span. Phenomena encountered in flight test during parafoil operation were captured in scale-model tests, and a video photogrammetry technique was implemented to obtain parafoil surface shapes during flight in the tunnel. Forces on the parafoil were resolved using tension gages on individual lines. The temporal evolution of the phenomenon of leading edge collapse was captured. Laser velocimetry was used to demonstrate measurement of the porosity of the parafoil surface. From these measurements, several physical explanations have been developed for phenomena observed at various stages of the X-38 development program. Quantitative measurement capabilities have also been demonstrated for continued refinement of the aerodynamic technologies employed in the X-38 project. Detailed results from these studies are given in an AIAA Paper, two slide presentations, and other material which are given on a Web-based archival resource. This is the Digital Library of the Georgia Tech Experimental Aerodynamics Group.

Komerath, N. M.↗
NASA NTRS2011

Design of the Next Generation Aircraft Noise Prediction Program: ANOPP2

The requirements, constraints, and design of NASA's next generation Aircraft NOise Prediction Program (ANOPP2) are introduced. Similar to its predecessor (ANOPP), ANOPP2 provides the U.S. Government with an independent aircraft system noise prediction capability that can be used as a stand-alone program or within larger trade studies that include performance, emissions, and fuel burn. The ANOPP2 framework is designed to facilitate the combination of acoustic approaches of varying fidelity for the analysis of noise from conventional and unconventional aircraft. ANOPP2 integrates noise prediction and propagation methods, including those found in ANOPP, into a unified system that is compatible for use within general aircraft analysis software. The design of the system is described in terms of its functionality and capability to perform predictions accounting for distributed sources, installation effects, and propagation through a non-uniform atmosphere including refraction and the influence of terrain. The philosophy of mixed fidelity noise prediction through the use of nested Ffowcs Williams and Hawkings surfaces is presented and specific issues associated with its implementation are identified. Demonstrations for a conventional twin-aisle and an unconventional hybrid wing body aircraft configuration are presented to show the feasibility and capabilities of the system. Isolated model-scale jet noise predictions are also presented using high-fidelity and reduced order models, further demonstrating ANOPP2's ability to provide predictions for model-scale test configurations.

Lopes, Leonard V., Dr.↗
DOE OSTI2022

A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling

Mechanistic models of how single cells respond to different perturbations can help integrate disparate big data sets or predict response to varied drug combinations. However, the construction and simulation of such models have proved challenging. Here, we developed a python-based model creation and simulation pipeline that converts a few structured text files into an SBML standard and is high-performance- and cloud-computing ready. We applied this pipeline to our large-scale, mechanistic pan-cancer signaling model (named SPARCED) and demonstrate it by adding an IFNγ pathway submodel. We then investigated whether a putative crosstalk mechanism could be consistent with experimental observations from the LINCS MCF10A Data Cube that IFNγ acts as an anti-proliferative factor. The analyses suggested this observation can be explained by IFNγ-induced SOCS1 sequestering activated EGF receptors. This work forms a foundational recipe for increased mechanistic model-based data integration on a single-cell level, an important building block for clinically-predictive mechanistic models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Dual frequency comb spectroscopy of solid fuel pyrolysis and combustion: Quantifying the influence of moisture content in Douglas fir

As the fire research community develops multi-scale models to predict the spread of wildland fires, there is a need for well-controlled, small-scale experiments which provide benchmark data and fundamental understanding of the effects of key parameters on the combustion of wildland fuels. Here, we implement a unique suite of non-intrusive, quantitative diagnostics that simultaneously measure mass loss, surface temperature, in situ gas temperature and water vapor concentration, including the first implementation of dual frequency comb spectroscopy for the study of solid fuels. As a demonstration, we examine the effect of fuel moisture content on the burning of Douglas fir wood samples that are ignited under constant radiative heat flux from a cone calorimeter to provide benchmark data for multi-scale models. Peak flame temperatures 3 mm above the sample surface measured with the dual frequency comb laser spectrometer are in excess of 1200 K. The flame temperature decreases by over 150 K as fuel moisture content increases from 0.7% to 40%. This work demonstrates a platform for simultaneous, quantitative measurements of well-controlled small-scale experiments which provide benchmark data for the development of advanced modeling and simulations capable of capturing the complex physics present in wildland fire systems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Effect of High-Fidelity Ice Accretion Simulations on the Performance of a Full-Scale Airfoil Model

The simulation of ice accretion on a wing or other surface is often required for aerodynamic evaluation, particularly at small scale or low-Reynolds number. While there are commonly accepted practices for ice simulation, there are no established and validated guidelines. The purpose of this article is to report the results of an experimental study establishing a high-fidelity, full-scale, iced-airfoil aerodynamic performance database. This research was conducted as a part of a larger program with the goal of developing subscale aerodynamic simulation methods for iced airfoils. Airfoil performance testing was carried out at the ONERA F1 pressurized wind tunnel using a 72-in. (1828.8-mm) chord NACA 23012 airfoil over a Reynolds number range of 4.5x10(exp 6) to 16.0 10(exp 6) and a Mach number range of 0.10 to 0.28. The high-fidelity, ice-casting simulations had a significant impact on the aerodynamic performance. A spanwise-ridge ice shape resulted in a maximum lift coefficient of 0.56 compared to the clean value of 1.85 at Re = 15.9x10(exp 6) and M = 0.20. Two roughness and streamwise shapes yielded maximum lift values in the range of 1.09 to 1.28, which was a relatively small variation compared to the differences in the ice geometry. The stalling characteristics of the two roughness and one streamwise ice simulation maintained the abrupt leading-edge stall type of the clean NACA 23012 airfoil, despite the significant decrease in maximum lift. Changes in Reynolds and Mach number over the large range tested had little effect on the iced-airfoil performance.

Broeren, Andy P.↗
DOE OSTI2023

Systems Engineering of Rhodococcus opacus to Enable Production of Drop-in Fuels from Lignocellulose

Production of drop-in fuels from lignocellulose using Rhodococcus opacus PD630 (hereafter R. opacus) is a challenging goal. During the grant period we have pushed the field forward significantly in several areas of research. Towards the end goal of accelerating the adoption of R. opacus in biofuel production, during the grant period we have expanded the phenotypic characterization of R. opacus grown in single aromatic (model lignocellulosic) compounds or their mixtures, modeling the growth conditions in lignocellulosic biomass. Harnessing the power of adaptive evolution, we produced evolved R. opacus isolates with superior lignin valorization capabilities and identified differentially expressed genes and pathways after adaptation. We used next generation multi-omic techniques such as genomic, transcriptomic, and metabolomic analyses, to identify the catabolic pathways used by R. opacus to degrade aromatic compounds and funnel these degradation products into central metabolism, as well as the aromatic transport genes required for increased tolerance and utilization. Taking this information one step further, we identified endogenous transcription factors and regulatory mechanisms important for degradation of five model aromatic compounds. To accurately estimate R. opacus growth and consumption on model lignin compounds we pioneered the use of novel extraction procedures prior to GC-MS analysis. Alongside 13 C-metabolic flux analysis, we have elucidated the metabolic routes preferred by Rhodococcus opacus during aromatic compound degradation. Finally, we used in tandem lipidomics and high-resolution mass spectrometry to identify the modulation of mycolic acids and phospholipid membrane composition modification as a strategy for aromatic tolerance in R. opacus. Being a non-model organism, R. opacus lacks the breadth of tools and technical foundation which drive biofuel research in more well-understood microbes such as Escherichia coli. To reduce this burden for use, we designed and produced new tools for genomic manipulation and engineering in R. opacus. These engineering breakthroughs support efficient genomic editing, enabling gene overexpression, repression, and genetic alteration. Using these tools, we have generated synthetically engineered strains with increased lipogenesis and growth, both positive traits required for increased lignin valorization. Optimizing engineered strains for biofuel production from lignocellulose requires extremely sophisticated synthetic rewiring of metabolism. To facilitate systems-level reorganization of metabolism in R. opacus, we created a genome-scale model that accurately predicts metabolic flux and growth rates on the aromatic compound phenol. Lignin requires extensive pre-treatment before biological degradation by R. opacus. Towards an eventual goal of degrading real-world lignin, we developed new depolymerization processes to generate lignin breakdown products (LBP). We optimized LBP storage and composition analysis techniques, enabling accurate prediction of specific LBP compound integration into cell wall components. Overall, through the work funded by this grant we generated 20 manuscripts (17 published, 3 in review/preparation), methods for increased accuracy in metabolomics of aromatic compounds, multiple genetic tools for altering the R. opacus genome, genome scale models for predicting flux through metabolic pathways, as well as multi-omic data for community use. The work funded by this grant has increased the knowledge of aromatic degradation in bacteria and advanced our efforts to optimize R. opacus for lignin valorization.

09 BIOMASS FUELS↗
DOE OSTI2020

HPC-enabled computation of demand models at scale

The purpose of this project is to examine the energy impact of urban-scale traffic for the Los Angeles Basin by developing and implementing a scalable traffic assignment model. An energy optimization function will be posed and when integrated into the optimization code for travel assignment it can be mathematically proven to converge. The energy optimization function can then be compared to the typical travel time optimization that is traditionally used in traffic assignment models. The analysis will begin with static traffic assignment models with the routing for all origin and destinations computed in parallel on high performance computing facilities. Convergence of the numerical methods rely on the solution of convex programs (or extensions of these). This step will mostly consist of demonstrating the ability to parallelize the Frank Wolfe algorithm on various platforms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1991

Numerical simulations of turbulent thermal convection with differential rotation

The solar nebula, from which the planets in our solar system formed, featured a disk of gas and dust grains in rapid, differential rotation, and at some stage was likely to have been unstable to thermal convection. This situation is suspected by many to lead to significant turbulent Reynolds stress production and angular momentum transport in such systems, and estimates of transport rates have been attempted from unsubstantiated phenomenological models. In order to determine the circumstances and physical conditions under which our own planetary system formed and to explain recent observations of young stellar systems, it is necessary to develop realistic models of heat and angular momentum transport for such flows. Developing an understanding of complicated flows featuring thermal convection, rotation, and shear is also of wide interest in stellar astrophysics and in planetary and terrestrial atmospheric studies. The ultimate objective is to develop workable models based on the numerical simulations for constructing global solar nebula models; viz., relatively simple prescriptions for heat and angular momentum fluxes from given system parameters (e.g., ratios of rotation, shear, and convective lapse rates) are characterized, quantified, and developed. Toward this end, our program has been to attempt to understand the behavior of the direct numerical simulations of Boussinesq convection, which, despite the complexity of the results, is still an overly simplified approximation to the real system and should be more amenable to analysis. These results are also intended to be tested against turbulence models, especially those designed for atmospheric boundary layers, and may provide a basis for subgrid-scale models. In order to make the numerical simulations more realistic with regard to the solar nebula problem, a fully compressible code that will allow incorporation of large density stratifications and realistic thermodynamic and radiative properties is developed. In order to explore the properties of these flows at the very high values of Re found in natural systems and the very low values of Pr found in most astrophysical contexts, we will need to employ large-eddy simulations for which we want to determine the most appropriate subgrid-scale model to incorporate.

Cabot, William H.↗
NASA NTRS1976

Acoustics and aerodynamics of over-the-wing thrust reversers

As part of the Quiet Clean Short-Haul Experimental Engine Program, model tests were conducted to determine the effects of thrust reverser geometric parameters on noise and reverse thrust. The acoustic tests used a 1/6 scale model thrust reverser while the aerodynamic performance tests used a 1/12 scale model reverser. Parameters which were varied in both tests include blocker spacing, blocker height, lip angle, and lip length. The impact of these parameters on peak sideline noise and reverse thrust performance is discussed.

Stimpert, D. L.↗
DOE OSTI2024

Experimental validation of a Kalman observer using linearized OpenFAST and a fully instrumented 1:70 model

Abstract To enable real‐time monitoring and control strategies for floating offshore wind turbines, accurate information about the state of the system is needed. This paper details the application of a Kalman filter to the UMaine VolturnUS‐S floating wind platform to provide accurate state estimates in real time using minimal system measurements. The midfidelity nonlinear simulation tool OpenFAST was used to generate the underlying linear state‐space model for the Kalman filter. This linear model and its limitations are demonstrated through comparison with experimental data collected on a 1:70 froude‐scaled model of the floating platform and tower. Using a selection of five measurements from the real system, a Kalman filter was developed to provide estimates for the remaining system states and measurements. These estimates were then validated against the experimental values collected from testing of the scale model. Validation of the Kalman filter produced accurate estimates of surge, heave, and tower base bending moment, measurements of which were not available to the Kalman filter. Performance of the Kalman filter was tested and validated over a range of sea conditions from rated wind speed to storm events and demonstrated robustness in the Kalman filter to maintain accuracy across all operating conditions despite significant error in the underlying linear model for extreme conditions.

17 WIND ENERGY↗
DOE OSTI2023

Scaling of Floods With Geomorphologic Characteristics and Precipitation Variability Across the Conterminous United States

Abstract Accurate flood risk assessment requires a comprehensive understanding of flood sensitivity to regional drivers and climate factors. This paper presents the scaling of floods (duration, peak, volume) with geomorphologic characteristics of the basin (i.e., drainage area, slope, elevation) and precipitation patterns (rainfall accumulation, variability). Long‐term daily streamflow observations over the 20th and early 21st centuries from Hydro‐Climatic Data Network streamgages across the conterminous United States are used to create a flood event database based on their flood stage information. Antecedent daily rainfall accumulation and variability corresponding to these floods are computed using Global Historical Climatology Network daily data set. Two Bayesian scaling models are developed, and the spatial organization of scaling exponents is investigated. The baseline model quantifies the scaling of floods to geomorphologic characteristics. The dynamic model quantifies the scaling of floods to antecedent precipitation distribution which is further conditioned on geomorphologic characteristics. Results show that small and low‐elevation basins have a stronger response to antecedent rainfall distribution in amplifying flood peaks, while high‐elevation steeper basins have a lower response for flood duration and volume. The dynamic models demonstrate that there are significant variations in the flood scaling rates, with the largest rates up to 40% and 4.5% for flood duration, 64% and 44% for peak, and 98% and 40% for volume found across the Northeast, Coastal Southeast, and Northwest with intensifying rainfall accumulation and variability, respectively. This study advances flood predictions by better informing the flood attributes in the context of dynamical land‐atmosphere perturbations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

On the transferability of residence time distributions in two 10-km long river sections with similar hydromorphic units

Quantifying hydrologic exchange fluxes (HEFs) at the stream-groundwater interface and their residence time distributions (RTDs) in the subsurface are important for managing the water quality and ecosystem health in dynamic river corridors. However, direct simulating high-spatial resolution HEFs and RTDs can be time-consuming, especially for watershed-scale modeling. Efficient surrogate models linking RTDs to hydromorphic units (HUs) can be alternatives for simulating RTDs in large-scale models. A common concern of these surrogate models, though, is the transferability of the relationship between the RTDs and HUs from one river corridor to another. To address this issue, this work evaluates the HEFs and resulting RTD-HU relationships for two 10-km long river corridors along the Columbia River leveraging a one-way coupled three-dimensional transient surface-subsurface water transport modeling framework we previously developed. Applying such a framework at the two river corridors with similar HUs allows for quantitative comparisons of HEFs and RTDs using both statistical tests and machine learning classification models. Finally, our comparison shows that the similarity and transferability of the RTD-HU relationship is very low for the two investigated river sections, which suggests that devising a general algorithm to estimate RTDs based solely on surface water hydrodynamics and short-distance river channel topography data, as well as HU classification, might be nearly impossible.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Multi-scale planning model for robust urban drought response

Increasingly severe droughts are straining municipal water resources and jeopardizing urban water security, but uncertainty in their duration, frequency, and intensity challenges drought planning and response. We develop the Drought Resilient Interscale Portfolio Planning model (DRIPP) to generate optimal planning responses to urban drought. DRIPP is a generalizable multi-scale framework for optimizing dynamic planning strategies of long-term infrastructure deployment and short-term drought response. It integrates climate and hydrological variability with high-fidelity representations of urban water distribution, available technology options, and demand reduction measures to yield robust and cost-effective water supply portfolios that are location-specific. We apply DRIPP in Santa Barbara, California to assess how least cost water supply portfolios vary under different drought scenarios and identify portfolios that are robust across drought scenarios. In Santa Barbara, we find that drought intensity, not duration or frequency, drives cost increases, reliability risk, and regret of overbuilding infrastructure. Under uncertain drought conditions, a diversified technology portfolio that includes both rapidly deployable, decentralized technologies alongside larger centralized technologies minimizes water supply cost while maintaining high robustness to climate uncertainty.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Aeroacoustic Simulations of the High-Lift Common Research Model and Validation with Experiment

Aerodynamic and acoustic data from unsteady numerical simulations of the High-Lift Common Research Model are compared with experimental measurements from an open-jet wind tunnel test of a 10\-scale model. Time-averaged surface pressure data is in good agreement for all of the configurations evaluated during the test. Unsteady surface pressure spectra from the leading-edge slat and the nose of the main element are presented, demonstrating that the highest levels are associated with the wakes of slat brackets. At these locations the simulations and experiment match reasonably well at low enough frequencies (f < 10 kHz based on the model scale) before excessive numerical dissipation leads to a rapid roll off in the predicted frequency spectra. The agreement is inconsistent at other locations on the slat and main-element surfaces, where the pressure fluctuation levels are lower. Noise predictions using a synthetic microphone array are compared with equivalent experimental results, and the changes in levels predicted between three configurations are similar to those measured. However, some details of the noise predictions are inconsistent with the experiment, and the use of solid- instead of porous-surface data for the acoustic processing of the simulations likely contributes to the discrepancies. All of the simulations were completed before the test, and, despite some shortcomings, they provided valuable insight into the aeroacoustic performance of the model that greatly aided test planning and execution. Hence, the post-test comparisons presented here allow an assessment of the predictive methodology in the context of a realistic high-lift configuration.

High-lift↗
NASA NTRS1994

Design of scaled down structural models

In the aircraft industry, full scale and large component testing is a very necessary, time consuming, and expensive process. It is essential to find ways by which this process can be minimized without loss of reliability. One possible alternative is the use of scaled down models in testing and use of the model test results in order to predict the behavior of the larger system, referred to herein as prototype. This viewgraph presentation provides justifications and motivation for the research study, and it describes the necessary conditions (similarity conditions) for two structural systems to be structurally similar with similar behavioral response. Similarity conditions provide the relationship between a scaled down model and its prototype. Thus, scaled down models can be used to predict the behavior of the prototype by extrapolating their experimental data. Since satisfying all similarity conditions simultaneously is in most cases impractical, distorted models with partial similarity can be employed. Establishment of similarity conditions, based on the direct use of the governing equations, is discussed and their use in the design of models is presented. Examples include the use of models for the analysis of cylindrical bending of orthotropic laminated beam plates, of buckling of symmetric laminated rectangular plates subjected to uniform uniaxial compression and shear, applied individually, and of vibrational response of the same rectangular plates. Extensions and future tasks are also described.

Simitses, George J.↗
DOE OSTI2025

High‐Resolution National‐Scale Water Modeling Is Enhanced by Multiscale Differentiable Physics‐Informed Machine Learning

Abstract The National Water Model (NWM) is a key tool for flood forecasting, planning, and water management. Key challenges facing the NWM include calibration and parameter regionalization when confronted with big data. We present two novel versions of high‐resolution (∼37 km 2 ) differentiable models (a type of hybrid model): one with implicit, unit‐hydrograph‐style routing and another with explicit Muskingum‐Cunge routing in the river network. The former predicts streamflow at basin outlets whereas the latter presents a discretized product that seamlessly covers rivers in the conterminous United States (CONUS). Both versions use neural networks to provide a multiscale parameterization and process‐based equations to provide a structural backbone, which were trained simultaneously (“end‐to‐end”) on 2,807 basins across the CONUS and evaluated on 4,997 basins. Both versions show great potential to elevate future NWM performance for extensively calibrated as well as ungauged sites: the median daily Nash‐Sutcliffe efficiency of all 4,997 basins is improved to around 0.68 from 0.48 of NWM3.0. As they resolve spatial heterogeneity, both versions greatly improved simulations in the western CONUS and also in the Prairie Pothole Region, a long‐standing modeling challenge. The Muskingum‐Cunge version further improved performance for basins >10,000 km 2 . Overall, our results show how neural‐network‐based parameterizations can improve NWM performance for providing operational flood predictions while maintaining interpretability and multivariate outputs. The modeling system supports the Basic Model Interface (BMI), which allows seamless integration with the next‐generation NWM. We also provide a CONUS‐scale hydrologic data set for further evaluation and use.

Song, Yalan [Civil and Environmental Engineering T↗