Search NASA⌕ Search

SEARCH · Search NASA

Results for “downstream modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Moving beyond post hoc explainable artificial intelligence: a perspective paper on lessons learned from dynamical climate modeling

AI models are criticized as being black boxes, potentially subjecting climate science to greater uncertainty. Explainable artificial intelligence (XAI) has been proposed to probe AI models and increase trust. In this review and perspective paper, we suggest that, in addition to using XAI methods, AI researchers in climate science can learn from past successes in the development of physics-based dynamical climate models. Dynamical models are complex but have gained trust because their successes and failures can sometimes be attributed to specific components or sub-models, such as when model bias is explained by pointing to a particular parameterization. We propose three types of understanding as a basis to evaluate trust in dynamical and AI models alike: (1) instrumental understanding, which is obtained when a model has passed a functional test; (2) statistical understanding, obtained when researchers can make sense of the modeling results using statistical techniques to identify input–output relationships; and (3) component-level understanding, which refers to modelers' ability to point to specific model components or parts in the model architecture as the culprit for erratic model behaviors or as the crucial reason why the model functions well. We demonstrate how component-level understanding has been sought and achieved via climate model intercomparison projects over the past several decades. Such component-level understanding routinely leads to model improvements and may also serve as a template for thinking about AI-driven climate science. Currently, XAI methods can help explain the behaviors of AI models by focusing on the mapping between input and output, thereby increasing the statistical understanding of AI models. Yet, to further increase our understanding of AI models, we will have to build AI models that have interpretable components amenable to component-level understanding. We give recent examples from the AI climate science literature to highlight some recent, albeit limited, successes in achieving component-level understanding and thereby explaining model behavior. The merit of such interpretable AI models is that they serve as a stronger basis for trust in climate modeling and, by extension, downstream uses of climate model data.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

Inviscid to turbulent transition of trailing vortices

The characteristics of the plateau region in the vortex system which trails from a lifting wing are discussed. The decay of the vortex due to viscous or turbulent shear is very slow in the plateau so that the maximum tangential speed in the vortices remains nearly constant for some distance downstream of roll-up and then begins to decrease, becoming inversely proportional to the square root of the distance downstream. Mathematical models are developed to analyze the structure of the plateau area. Solutions are obtained for both constant and variable eddy viscosity models.

Iversen, J. D.↗
NASA NTRS1993

Laser velocimeter measurements of the flow field generated by a forward-swept propfan during flutter

Results are presented from an investigation to measure the flow field generated by a forward-swept propfan operating in flutter at a low forward velocity. For comparison to the flutter condition, flow field data are also presented for a slightly reduced rotational speed just below flutter. The forward-swept propfan was tested as the front rotor of a counterrotating pusher propeller. A laser Doppler velocimeter (LDV) was used to measure the velocity field in planes normal to the model centerline downstream of the rotor and in planes of constant radius within the blade passages at each operating condition. The mean time-averaged flow about the blades did not change drastically as the propfan rotational speed was increased from the stable operating point to the flutter condition. No regions of flow separation could be identified in the data plots of the mean intrablade flow field. The relative flow about the blades remained subsonic during flutter operation. The blades were found to have a higher than expected tip loading at both operating conditions. This is thought to have been caused by the outer blade sections twisting under load to higher than expected effective blade angles. This high tip loading resulted in strong vortices and a very nonuniform flow downstream of the tips of the forward-swept blades. This high tip loading may also have caused the blade flutter.

Podboy, Gary G.↗
NASA NTRS1993

Laser velocimeter measurements of the flow field generated by a forward-swept propfan during flutter

Results are presented from an investigation to measure the flow field generated by a forward-swept propfan operating in flutter at a low forward velocity. For comparison to the flutter condition, flow field data are also presented for a slightly reduced rotational speed just below flutter. The forward-swept propfan was tested as the front rotor of a counterrotating pusher propeller. A laser Doppler velocimeter (LDV) was used to measure the velocity field in planes normal to the model centerline downstream of the rotor and in planes of constant radius within the blade passages at each operating condition. A comparison of the data taken at the two different operating conditions indicated that the mean, time-averaged flow about the blades did not change drastically as the propfan rotational speed was increased from the stable operating point to the flutter condition. No regions of flow separation could be identified in the data plots of the mean intrablade flow field. The data also indicate that the relative flow about the blades remained subsonic during flutter operation. The blades were found to have a higher than expected tip loading at both operating conditions. This is thought to have been caused by the outer blade sections twisting under load to higher than expected effective blade angles. This high tip loading resulted in strong vortices and a very nonuniform flow downstream of the tips of the forward-swept blades. This high tip loading may also have caused the blade flutter.

Podboy, Gary G.↗
NASA NTRS1999

Aeroacoustic Resonance with Convergent-Divergent Nozzles

Convergent-divergent nozzles, when run at off-design conditions, often undergo flow resonance accompanied by the emission of a tone. Apart from screech occurring at higher operating pressures, resonance is also common at lower Mach numbers near transonic as well as subsonic conditions. With data from six nozzles of different size and design Mach number, the present paper documents the characteristics of the latter phenomenon that is morphologically quite different from conventional screech. The resonance is due to a feedback loop internal to the nozzle and is apparently driven by unsteady laminar boundary layer separation near the throat of the nozzle. Appropriate boundary layer tripping prior to the throat is found to eliminate or alter most of the tones. The Helmholtz number of the resonance, based on the throat-to-exit length, is found to attain a value of approximately 0.15 at M(sub j)=1 for all nozzles. However, its variation with M(sub j) may be different and depend on the nozzle geometry. With nozzles having larger throat-to-exit angle of divergence, the frequency is found to increase, in some cases having stage jumps to lower frequencies, with increasing operating pressure. With nozzles having smaller angle of divergence, the frequency variation exhibits an increase followed by a decrease involving one prominent stage occurring around transonic (M(sub j)= 1) condition. While the mechanisms remain far from completely clear, a model involving downstream propagating aerodynamic disturbance together with acoustic feedback explains the overall frequency characteristics for most cases.

Zaman, K. B. M. Q.↗
NASA NTRS2022

A Scaled Model Study of the PSL Facility for Alleviating Low-Frequency Howl

This report documents results from a scaled model experimental study of howl occurring in the Propulsion Systems Laboratory (PSL)during engine tests. The aim is to understand the sources of the howling noise and find possible remedies. It is shown that a jet discharged into the model of the duct gives rise to high levels of low frequency noise which occurs apparently due to excitation of duct acoustic modes randomly excited by the jet. A wire-mesh screen placed at the end of the duct model immediately downstream of the jet nozzle is shown to alleviate such noise significantly. Based on these results, an end treatment for the duct in the PSL facility is recommended.

engine test↗
NASA NTRS1978

Prediction of orbiter RSI tile gap heating ratios from NASA/Ames double wedge model test

In-depth gap heating ratios for Orbiter RSI tile sidewalls were predicted based on near steady state temperature measurements obtained from double wedge model tests. An analysis was performed to derive gap heating ratios which would result in the best fit of test data; provide an assessment of open gap response, and supply the definition of gap filler requirements on the Orbiter. A comparison was made of these heating ratios with previously derived ratios in order to verify the extrapolation of the wing glove data to Orbiter flight conditions. The analysis was performed with the Rockwell TPS Multidimensional Heat Conduction Program for a 3-D, 2.0-inch thick flat RSI tile with 255 nodal points. The data from 14 tests was used to correlate with the analysis. The results show that the best-fit heating ratios at the station farthest upstream on the model for most gap depths were less than the extrapolated values of the wing glove model heating ratios. For the station farthest downstream on the model, the baseline heating ratios adequately predicted or over-predicted the test data.

Source record↗
NASA NTRS1992

The effect of entrance radius and film injection on wall heating in scramjet nozzles

An experimental study has been performed with a scramjet combustor and nozzle model to determine the effect of nozzle radii on relaminarization, and the effectiveness of film injection in reducing wall heat flux. The nozzle model was installed downstream of a swept-ramp scramjet combustor model, operated at Mach 2.7 with vitiated air, simulating Mach 6-7 flight enthalpies. Results from tests conducted with three nozzle radii, varying in curvature from a sharp Prandtl-Meyer expansion to a radius of two scramjet combustor exit heights, showed little or no effect on the downstream wall heat flux, which is not in agreement with both subsonic and supersonic relaminarization correlations in the available literature. In contrast, film injection upstream of all three radii produced reductions of 70 percent in the entire nozzle model heating rate, for the nominal film-to-free stream pressure matched condition. Results from film injection, with and without pressure gradient, but without wall curvature, show that the gradients appear to stabilize the film, with the resulting reductions in wall heat transfer rates apparent far downstream of the point of injection.

Baker, N. R.↗
DOE OSTI2016

Wabash Valley Integrated Gasification Combined Cycle, Coal to Fischer Tropsch Jet Fuel Conversion Study

This reports examines the feasibility of converting the existing Wabash Integrated Gasification Combined Cycle (IGCC) plant into a liquid fuel facility, with the goal of maximizing jet fuel production. The fuels produced are required to be in compliance with Section 526 of the Energy Independence and Security Act of 2007 (EISA 2007 §526) lifecycle greenhouse gas (GHG) emissions requirements, so lifecycle GHG emissions from the fuel must be equal to or better than conventional fuels. Retrofitting an existing gasification facility reduces the technical risk and capital costs associated with a coal to liquids project, leading to a higher probability of implementation and more competitive liquid fuel prices. The existing combustion turbine will continue to operate on low cost natural gas and low carbon fuel gas from the gasification facility. The gasification technology utilized at Wabash is the E-Gas™ Technology and has been in commercial operation since 1995. In order to minimize capital costs, the study maximizes reuse of existing equipment with minimal modifications. Plant data and process models were used to develop process data for downstream units. Process modeling was utilized for the syngas conditioning, acid gas removal, CO 2 compression and utility units. Syngas conversion to Fischer Tropsch (FT) liquids and upgrading of the liquids was modeled and designed by Johnson Matthey Davy Technologies (JM Davy). In order to maintain the GHG emission profile below that of conventional fuels, the CO 2 from the process must be captured and exported for sequestration or enhanced oil recovery. In addition the power utilized for the plant’s auxiliary loads had to be supplied by a low carbon fuel source. Since the process produces a fuel gas with sufficient energy content to power the plant’s loads, this fuel gas was converted to hydrogen and exported to the existing gas turbine for low carbon power production. Utilizing low carbon fuel gas and process steam in the existing combined cycle power plant provides sufficient power for all plant loads. The lifecycle GHG profile of the produced jet fuel is 95% of conventional jet fuel. Without converting the fuel gas to a low carbon fuel gas, the emissions would be 108% of conventional jet fuel and without any GHG mitigation, the profile would be 206%. Oil prices greater than $120 per barrel are required to reach a targeted internal rate of return on equity (IRROE) of 12%. Although capital expenditure is much less than if a greenfield facility was built, the relatively small size of the plant, assumed coal price, and the CTL risk profile used in the economic assumptions lead to a high cost of production. Assuming more favorable factors, the economic oil price could be reduced to $78 per barrel with GHG mitigation and $55 per barrel with no GHG mitigation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Algal Biomass Conversion to Fuels via Combined Algae Processing (CAP): 2022 State of Technology and Future Research

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office (BETO). It allows for the impact of research progress (both directly achieved in-house at NREL and furnished by partner organizations) to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked toward out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae SOT benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) consortium efforts and driven by data furnished by Arizona State University's (ASU's) Arizona Center for Algae Technology and Innovation (AzCATI) test bed site. The CAP model is primarily based on experimental efforts conducted under NREL research and development projects, with some process parameters provided by partner organizations. Assumptions regarding the wet storage of algae use data provided by Idaho National Laboratory (INL), while parts of the polyurethane production process leverage BETO-funded research from collaborators at Algenesis and the University of California, San Diego (UCSD). This report focuses on back-end conversion of algal biomass through the CAP pathway, highlighting the 2022 updates to minimum fuel selling price (MFSP). This update incorporates improvements to fermentation performance for two biological pathways through carboxylic acid and 2,3-butanediol (BDO) intermediates, as demonstrated through parallel research on the biochemical conversion of corn stover. Improvements are applied to the glucose fraction of the biomass only, while parameters regarding the conversion of the mannose fraction (not a significant component in corn stover) are maintained consistently with prior CAP SOTs. Additional parameters are also updated to reflect the most current understanding of each pathway, including an increase in the catalyst loading requirement in the ketonization step of the acids pathway and a decrease in the fermentation productivity in the BDO pathway. Additionally, the biomass feedstock costs (minimum biomass selling price [MBSP]), yields, and seasonal variability from the upstream cultivation SOT model were also incorporated into downstream Aspen Plus CAP models.

09 BIOMASS FUELS↗
NASA NTRS2013

MPST Software: grl_pef_check

This innovation is a tool used to verify and validate spacecraft sequences at the predicted events file (PEF) level for the GRAIL (Gravity Recovery and Interior Laboratory, see http://www.nasa. gov/mission_pages/grail/main/index. html) mission as part of the Multi-Mission Planning and Sequencing Team (MPST) operations process to reduce the possibility for errors. This tool is used to catch any sequence related errors or issues immediately after the seqgen modeling to streamline downstream processes. This script verifies and validates the seqgen modeling for the GRAIL MPST process. A PEF is provided as input, and dozens of checks are performed on it to verify and validate the command products including command content, command ordering, flight-rule violations, modeling boundary consistency, resource limits, and ground commanding consistency. By performing as many checks as early in the process as possible, grl_pef_check streamlines the MPST task of generating GRAIL command and modeled products on an aggressive schedule. By enumerating each check being performed, and clearly stating the criteria and assumptions made at each step, grl_pef_check can be used as a manual checklist as well as an automated tool. This helper script was written with a focus on enabling the user with the information they need in order to evaluate a sequence quickly and efficiently, while still keeping them informed and active in the overall sequencing process. grl_pef_check verifies and validates the modeling and sequence content prior to investing any more effort into the build. There are dozens of various items in the modeling run that need to be checked, which is a time-consuming and errorprone task. Currently, no software exists that provides this functionality. Compared to a manual process, this script reduces human error and saves considerable man-hours by automating and streamlining the mission planning and sequencing task for the GRAIL mission.

Call, Jared A.↗
NASA NTRS2010

Wake Measurement Downstream of a Hybrid Wing Body Model with Blown Flaps

Flow-field measurements were obtained in the wake of a full-span Hybrid Wing Body model with internally blown flaps. The test was performed at the NASA Langley 14 x 22 Foot Subsonic Tunnel at low speeds. Off-body measurements were obtained with a 7-hole probe rake survey system. Three model configurations were investigated. At 0deg angle of attack the surveys were completed with 0deg and 60deg flap deflections. At 10deg angle of attack the wake surveys were completed with a slat and a 60deg flap deflection. The 7-hole probe results further quantified two known swirling regions (downstream of the outboard flap edge and the inboard/outboard flap juncture) for the 60deg flap cases with blowing. Flowfield results and the general trends are very similar for the two blowing cases at nozzle pressure ratios of 1.37 and 1.56. High downwash velocities correlated with the enhanced lift for the 60deg flap cases with blowing. Jet-induced effects are the largest at the most inboard station for all (three) velocity components due in part to the larger inboard slot height. The experimental data are being used to improve computational tools for high-lift wings with integrated powered-lift technologies.

Lin, John C.↗
NASA NTRSDate not supplied

Revolutionizing Earth Science with Generalized AI Models

Foundation Models (FM) are generalized Artificial Intelligence (AI) models that are designed to replace a task or an application-specific model and can be used for many downstream applications. These FM can be built on any sequence data and are trained utilizing self-supervised approaches. The obstacle of creating a sizable labeled dataset for training is removed by using self-supervised learning. Most FM employ transformer design that takes advantage of the idea of self-attention, allowing the network to represent the impact of distant data points on one another in space and time. The FM models show emergent qualities that are induced from the data. FM can become a valuable tool for Earth science researchers. Due to the size of these models, downstream applications built fine-tuning these FM perform better and exhibit greater accuracy than models created from scratch. FM significantly lowers the entry barrier in terms of both the time and effort required to develop various downstream applications. For some scientific datasets, such as optical remote sensing data, FM can speed up processes like classification, object detection and prediction. By eliminating the training data bottleneck and maximizing the usage of science data, FM can make it simpler to integrate AI into scientific research. Initial results for three different FMs will be presented.

Rahul Ramachandran↗
DOE OSTI2016

A computational fluid dynamics modeling study of guide walls for downstream fish passage

A partial-depth, impermeable guidance structure (or guide wall) for downstream fish passage is typically constructed as a series of panels attached to a floating boom and anchored across a water body (e.g. river channel, reservoir, or power canal). The downstream terminus of the wall is generally located nearby to a fish bypass structure. If guidance is successful, the fish will avoid entrainment in a dangerous intake structure (i.e. turbine intakes) while passing from the headpond to the tailwater of a hydroelectric facility through a safer passage route (i.e. the bypass). The goal of this study is to determine the combination of guide wall design parameters that will most likely increase the chance of surface-oriented fish being successfully guided to the bypass. To evaluate the flow field immediately upstream of a guide wall, a parameterized computational fluid dynamics model of an idealized power canal was constructed in © ANSYS Fluent v 14.5 (ANSYS Inc., 2012). The design parameters investigated were the angle and depth of the guide wall and the average approach velocity in the power canal. Results call attention to the importance of the downward to sweeping flow ratio and demonstrate how a change in guide wall depth and angle can affect this important hydraulic cue to out-migrating fish. The key findings indicate that a guide wall set at a small angle (15° is the minimum in this study) and deep enough such that sweeping flow dominant conditions prevail within the expected vertical distribution of fish approaching the structure will produce hydraulic conditions that are more likely to result in effective passage.

42 ENGINEERING↗
NASA NTRSDate not supplied

Harnessing Large Language Models for Scientific Endeavors

The rapid proliferation of Large Language Models (LLMs) such as GPT, Bard, and Llama has revolutionized various sectors, including the scientific community. These models, with their potential to automate and augment tasks, are increasingly being recognized as both a valuable asset and a potential challenge in the realm of scientific research and data management. However, the current LLMs, primarily trained on general corpora, exhibit a limited understanding of scientific concepts and terminologies due to the lack of scientific corpus in their training data. Recognizing this gap, several groups are now advocating for the development of LLMs specifically tailored for scientific applications. A notable initiative in this direction is the Large Language Model effort initiated by NASA's CSDO. This endeavor aims to align LLM efforts across NASA’s Science Mission Directorate, develop a science-specific corpus and validation test set for model training, and create an encoder-only model for various downstream tasks. Moreover, the initiative also plans to develop a decoder-only model to explore the potential benefits and risks associated with a generative LLM for science. Lastly, the project aims to create a science evaluation suite, encompassing various categories of downstream scientific tasks, to serve as a benchmark for assessing the value of any LLM for future use. This presentation will provide an overview and current status of this ongoing initiative, highlighting its potential to reshape the use of LLMs in the scientific domain.

Rahul Ramachandran↗
NASA NTRS1971

A model for analysis of the temperature field downstream of a heated jet injected into an isothermal crossflow at an angle of 90 deg

The temperature distribution downstream of a heated jet entering an isothermal crossflow at an angle of 90 deg is predicted using two conduction models with energy sources above the point of injection, in one case a point source and in the second a line source. The models use effective turbulent diffusivities that are determined empirically from previous measurements. Temperatures predicted by the models are compared to experimental results.

Eriksen, V. L.↗
NASA NTRS2024

AI Foundation Model for Heliophysics: Applications, Design, and Implementation

Deep learning-based methods have been widely researched in the areas of language and vision, demonstrating their capacity to understand long sequences of data and their usefulness in numerous helio-physics applications. Foundation models (FMs), which are pre-trained on a large-scale datasets, form the basis fora variety of downstream tasks. These models, especially those based on trans-formers in vision and language, show exceptional potential for adapting to a wide range of downstream applications. In this paper, we provide our perspective on the criteria for designing a FM for heliophysic and associated challenges and applications using the Solar Dynamics Observatory (SDO) dataset. We believe that this is the first study to design a foundation model in the domain of heliophysics.

Sujit Roy↗