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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Design Exploration of a Slotted-Wing Common Research Model

A knowledge-based aerodynamic design method, Constrained Direct Iterative Surface Cur-vature (CDISC), has been leveraged for the computational design exploration of a Common Research Model with Reduced-Sweep and Slotted Wings (CRMRS-SW). Cruise-slotted-wing airfoils include a slot near the trailing edge of a main airfoil component to introduce stream air to the low-momentum, upper-surface boundary layer on a flap airfoil component with the goal of allowing for a more aft loading, relative to supercritical airfoils, without shock-induced separation. Ultimately, the cruise slotted wing is a passive technology that allows for an in-crease in the drag divergence Mach number and/or an increase in aerodynamic efficiency at agiven cruise condition. These aerodynamic benefits may be realized at the vehicle level through a trade space that includes the following design options: increasing cruise Mach number, in-creasing wing thickness, decreasing wing sweep, increasing lift coefficient and/or decreasing drag coefficient. The present study aimed to evaluate the slotted-wing concept’s potential as adrag-saving technology in application to a single-aisle transonic transport aircraft at a given cruise condition. The CDISC design method was used to develop a better understanding of the slotted-wing design variables that have a significant impact on the variability in aircraft drag and leverage this newly-developed knowledge to quantify the aerodynamic performance benefits enabled by the cruise slotted wing.

Brett R. Hiller↗
DOE OSTI2025

Environmental Thermodynamic Effects on Future Changes of Mesoscale Convective Systems and Isolated Deep Convection Over the US: A Case Study

Mesoscale convective systems (MCSs) and isolated deep convection (IDC) significantly influence local weather conditions and the hydrological cycle across the United States. Their future changes under warming is critical to the society. However, the exact impacts of thermodynamic environmental changes on them are difficult to resolve using climate model simulations which integrate both dynamic and thermodynamic factors. This study explores a theoretical modeling approach to isolate environmental thermodynamic effects on their future changes through a case study. For a 50-day period during the 2020 summer, a pair of convection-permitting model simulations indicate contrasting changes in MCSs and IDC between inland and coastal regions under pseudo global warming. Driven by the thermodynamic environments of these simulations, a single-column parcel model indicates a decrease in the frequency of IDC occurrences, along with increases in duration and precipitation amount under warming, attributable to rising most unstable convective available potential energy (MUCAPE), convective inhibition (MUCIN), and precipitable water (PW). A multi-column parcel model reveals contrasting changes in the frequency and mean area of MCSs between inland and coastal regions, underscoring the increase in mean MUCIN over inland regions and increases in mean MUCAPE and PW over coastal regions. The increase in mean MCS area over inland regions is linked to the interplay between accelerated gust fronts and enhanced subsidence strength, which is further traced to the unchanged mean MUCIN but increased mean MUCAPE in large-scale environments. In conclusion, these case study results suggest a major role of thermodynamic environmental changes in controlling characteristics of MCSs and IDC under warming.

Mesoscale convective system↗
NASA NTRS2018

LAVA Simulations for the 3rd AIAA CFD High Lift Prediction Workshop with Body Fitted Grids

In response to the 3rd AIAA CFD High Lift Prediction Workshop, the workshop cases were analyzed using Reynolds-averaged Navier-Stokes flow solvers within the Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework. For the workshop cases the advantages and limitations of both overset-structured an unstructured polyhedral meshes were assessed. The workshop included 3 cases: a 2D airfoil validation case, a mesh convergence study using the High Lift Common Research Model, and a nacelle/pylon integration study using the JAXA (Japan Aerospace Exploration Agency) Standard Model. The 2D airfoil case from the workshop is used to verify the implementation of the Spalart-Allmaras turbulence model along with some of its variants within the solver. The High Lift Common Research Model case is used to assess solver performance and accuracy at varying mesh resolutions, as well as identify the minimum mesh fidelity required for LAVA on this class of problem. The JAXA Standard Model case is used to assess the solver's sensitivity to the turbulence model and to compare the structured and unstructured mesh paradigms. These workshop cases have helped establish best practices for high lift flow configurations for the LAVA solver.

LAVA↗
NASA NTRS2018

Multifidelity Uncertainty Quantification of a Commercial Supersonic Transport

The objective of this work was to develop a multifidelity uncertainty quantification approach for efficient analysis of a commercial supersonic transport concept. An approach based on point-collocation, non-intrusive polynomial chaos was formulated in which a low-fidelity model could be corrected using multiple higher-fidelity models. The formulation and methodology also allows for the addition of uncertainty sources not present in the lower fidelity models. To demonstrate the applicability and potential computational savings of the multifidelity polynomial chaos approach, two model problems were explored. The first was a supersonic airfoil with three levels of modeling fidelity, each capturing a gradual increase in modeling of the underlying flow physics. As much as 50% computational cost reduction was observed using the mutlifidelity approach, while predicting nearly the same amount of uncertainty in drag. The second problem was a commercial supersonic transport. This model had three levels of fidelity that included two different modeling approaches and the addition of physics between the fidelity levels. Results of this analysis yielded nearly a 70% computational savings to predict a comparable amount of uncertainty in ground noise. Both problems illustrate the applicability and significant computational savings of the multifidelity method for efficient and accurate uncertainty quantification.

Thomas K. West IV↗
DOE OSTI2025

professor

Professor is a tool to help you study complicated physical phenomena by providing tools to 1) fit machine learning models to 2D image arrays from simulations and 2) interactively explore these machine learning models in real time. Professor is most useful when studying ensembles of simulations. A typically workflow would look like: 1. A user is interested in how parameters A, B, C, & D influence some complicated physics 2. User setups up parameterized simulations to study ABCD and the results of these simulations to be image arrays (a 2d matrix of float32 values) 3. User runs an ensemble of simulations studying ABCD creating a dataset of image arrays 4. User runs `prof-trainer` to fit a machine learning model to learn the mapping from [A,B,C,D] to the image arrays 5. User then uses `prov-vis` to interactively explore the machine learning model in real time, gaining their insight into how those parameters influence the physics 6. Go profess your idea about ABCD!

Collis, HenryH [Lawrence Livermore National Labora↗
NASA NTRS2020

Exploring the Limits of the Data-Model-Theory Synergy: “Hot” MW Transitions for Rovibrational IR Studies

In order to further improve the accuracy of rovibrational IR line lists generated from the “Best Theory +Reliable High-resolution Experiment” (BTRHE) strategy from 0.01-0.05 cm-1, or 300-1500 MHz, to ~10 MHz, we explore the current limits of the Data-Model-Theory synergy by examining the accuracy and consistency of existing data, then propose that “hot” bands in microwave (MW) spectra is the solution we need for future enhancements. The Ames SO2 J=0-20 rovibrational energy levels computed on the semi-empirically refined Ames-2 potential energy surface (PES) are fit to the Effective Hamiltonian (EH) model regularly used in the experimental infrared (IR) analysis for SO2 isotopologues. In the fitted EH(Ames) model, the rotational constants A/B/C and all 5 quartic centrifugal distortion constants display clear, systematic, and consistent patterns along the vibrational state energy or quanta. Such consistent patterns may facilitate the vibrational assignments for MW hot bands and extract more information from high temperature MW spectra. Some EH(Expt) analyses were carried out with the lowest order Coriolis Coupling term, C1. Their constants should not be directly compared with other EH(Expt) and EH(Ames) results. After excluding them, our  = EH(Ames)- EH(Expt) analyses for 5 isotopologues (626, 636, 646, 628 and 828) indicates some loss of accuracy and consistency starting from vibrational states as low as 22 or 1000 cm-1. Some EH parameters, e.g. K, may have relative deviations as large as 50-100% and totally lose any recognizable patterns. This simply means that current EH(Expt) models do not have the system-wide consistency we need to further refine the EH(Ames) and Ames rovibrational IR line lists. A large part of such defects are probably inherited from the limited precision of experimental line positions, i.e. 1E-3 ~ 1E-4 cm-1, or 3-30 MHz. This is confirmed in a series of truncation tests using the Ames data. Although the EH(Ames) consistency may help identify unreliable rovibrational EH(Expt) parameters, and make reliable predictions for minor isotopologues and unobserved vibrational bands, we believe only the highly accurate “hot” MW transitions can provide real enhancements for EH(Expt) accuracy and consistency. “Hot” MW spectra should play a more significant role in the future synergy of Data, Model, and Theory in the field of rovibrational IR studies.

Xinchuan Huang↗
DOE OSTI2024

GCAM–GLORY v1.0: representing global reservoir water storage in a multi-sector human–Earth system model

Abstract. Reservoirs play a significant role in modifying the spatiotemporal availability of surface water to meet multi-sector human demands, despite representing a relatively small fraction of the global water budget. Yet the integrated modeling frameworks that explore the interactions among climate, land, energy, water, and socioeconomic systems at a global scale often contain limited representations of water storage dynamics that incorporate feedbacks from other systems. In this study, we implement a representation of water storage in the Global Change Analysis Model (GCAM) to enable the exploration of the future role (e.g., expansion) of reservoir water storage globally in meeting demands for, and evolving in response to interactions with, the climate, land, and energy systems. GCAM represents 235 global water basins, operates at 5-year time steps, and uses supply curves to capture economic competition among renewable water (now including reservoirs), non-renewable groundwater, and desalination. Our approach consists of developing the GLObal Reservoir Yield (GLORY) model, which uses a linear programming (LP)-based optimization algorithm and dynamically linking GLORY with GCAM. The new coupled GCAM–GLORY approach improves the representation of reservoir water storage in GCAM in several ways. First, the GLORY model identifies the cost of supplying increasing levels of water supply from reservoir storage by considering regional physical and economic factors, such as evolving monthly reservoir inflows and demands, and the leveled cost of constructing additional reservoir storage capacity. Second, by passing those costs to GCAM, GLORY enables the exploration of future regional reservoir expansion pathways and their response to climate and socioeconomic drivers. To guide the model toward reasonable reservoir expansion pathways, GLORY applies a diverse array of feasibility constraints related to protected land, population, water sources, and cropland. Finally, the GLORY–GCAM feedback loop allows evolving water demands from GCAM to inform GLORY, resulting in an updated supply curve at each time step, thus enabling GCAM to establish a more meaningful economic value of water. This study improves our understanding of the sensitivity of reservoir water supply to multiple physical and economic dimensions, such as sub-annual variations in climate conditions and human water demands, especially for basins experiencing socioeconomic droughts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Exploration of an oculometer-based model of pilot workload

Potential relationships between eye behavior and pilot workload are discussed. A Honeywell Mark IIA oculometer was used to obtain the eye data in a fixed base transport aircraft simulation facility. The data were analyzed to determine those parameters of eye behavior which were related to changes in level of task difficulty of the simulated manual approach and landing on instruments. A number of trends and relationships between eye variables and pilot ratings were found. A preliminary equation was written based on the results of a stepwise linear regression. High variability in time spent on various instruments was related to differences in scanning strategy among pilots. A more detailed analysis of individual runs by individual pilots was performed to investigate the source of this variability more closely. Results indicated a high degree of intra-pilot variability in instrument scanning. No consistent workload related trends were found. Pupil diameter which had demonstrated a strong relationship to task difficulty was extensively re-exmained.

Krebs, M. J.↗
NASA NTRS1993

Walkway friction: Experiment and analysis

The objectives are to explore the utility and the limitations of the Amontons-Coulomb friction model and to explore design of experiments issues which underlie competent testing.

Marpet, Mark I.↗
NASA NTRS2006

Managing Analysis Models in the Design Process

Design of large, complex space systems depends on significant model-based support for exploration of the design space. Integrated models predict system performance in mission-relevant terms given design descriptions and multiple physics-based numerical models. Both the design activities and the modeling activities warrant explicit process definitions and active process management to protect the project from excessive risk. Software and systems engineering processes have been formalized and similar formal process activities are under development for design engineering and integrated modeling. JPL is establishing a modeling process to define development and application of such system-level models.

design↗
NASA NTRS2021

FORECASTING WHEAT YIELD USING REMOTE SENSING: THE ARYA FORECASTING SYSTEM

In this study we present a model to forecast wheat yield based on the evolution of the Difference Vegetation Index (DVI)and the Growing Degree Days (GDD), presented in Franch et al. (2015), but adapted to Franch et al. (2019) model. Additionally, we explore how the Land Surface Temperature (LST) can be included into the model and if this parameter adds any value to the model when combined with the optical information. This study is applied toMODIS data at 1km resolution to monitor the national and state level yield of winter wheat in the United States and Ukraine from 2001 to 2019.

B. Franch↗