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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

High frequency flow-structural interaction in dense subsonic fluids

Prediction of the detailed dynamic behavior in rocket propellant feed systems and engines and other such high-energy fluid systems requires precise analysis to assure structural performance. Designs sometimes require placement of bluff bodies in a flow passage. Additionally, there are flexibilities in ducts, liners, and piping systems. A design handbook and interactive data base have been developed for assessing flow/structural interactions to be used as a tool in design and development, to evaluate applicable geometries before problems develop, or to eliminate or minimize problems with existing hardware. This is a compilation of analytical/empirical data and techniques to evaluate detailed dynamic characteristics of both the fluid and structures. These techniques have direct applicability to rocket engine internal flow passages, hot gas drive systems, and vehicle propellant feed systems. Organization of the handbook is by basic geometries for estimating Strouhal numbers, added mass effects, mode shapes for various end constraints, critical onset flow conditions, and possible structural response amplitudes. Emphasis is on dense fluids and high structural loading potential for fatigue at low subsonic flow speeds where high-frequency excitations are possible. Avoidance and corrective measure illustrations are presented together with analytical curve fits for predictions compiled from a comprehensive data base.

Liu, Baw-Lin↗
DOE OSTI2020

Towards Trust-Augmented Visual Analytics for Data-Driven Energy Modeling

The promise of data-driven predictive modeling is being increasingly realized in various science and engineering disciplines, where experts are used to the more conventional, simulation-driven modeling practices. However, trust remains a bottleneck for greater adoption of machine learning-based models for domain experts, who might not be necessarily trained in data science. In this paper, we focus on the building energy domain, where physics-based simulations are being complemented or replaced by machine learning-based methods for forecasting energy supply and demand at various spatio-temporal scales. We study the trust problem in close collaboration with energy scientists and engineers and describe how visual analytics can be leveraged for alleviating this trust bottleneck for stakeholders with varying degrees of expertise and analytics goals in this domain.

Kandakatla, Akshith R.↗
DOE OSTI2020

Updates to Relevance Vector Machine: Multiclass Classification, Variable Selection, and Proof-of-Concept Application to Safeguards Fresh Fuel Verification using List-Mode Neutron Collar Data

To expand the capabilities of safeguards authorities to verify the integrity of fresh fuel assemblies, Oak Ridge National Laboratory has retrofit the existing electronics of the JCC-71 uranium neutron coincidence collar, which contains 18 3 He neutron detectors and an external 241 AmLi(α, n) neutron interrogation source arranged to surround a fresh nuclear fuel assembly. The new electronics system allows analysts to record list-mode neutron multiplicity data in addition to the singles and doubles rates that are currently measured. Based on previous proof-of-concept research, analysis of these new data will identify off-normal fuel configurations in an assembly and characterize or localize the specific partial fuel defects. The purpose of this report it to document the analysis algorithm development and then to demonstrate its capability for the safeguards verification of fresh fuel assemblies using list mode neutron collar data. To analyze the complex list-mode data collected with the upgraded uranium neutron collar, multivariate classification algorithms are being developed using a novel classification method, the relevance vector machine. This approach may be applied to multiclass problems to estimate the probability that test data belongs to one of many possible classes of data. In addition, our method identifies the most useful variables/channels for making predictions, which illuminates the basis for the model’s predictions, and this interpretability is largely unique among data analytics methods. Variable selection occurs during model training and parameter tuning and does not need any external hyperparameter tuning routines. Finally, we apply the modified relevance vector machine to a simulated dataset of list-mode neutron collar data generated with the radiation transport code MCNP. The method can correctly identify off-normal fuel configurations, categorize the data according to four fuel defect scenarios, and rank the channels in the data according to prediction utility. For nuclear safeguards applications, it is concluded that this method has the potential to increase the sensitivity and reliability to detect missing fuel rods from a standard 17 x 17 Pressurized Water Reactor (PWR) fresh fuel assembly. Within this analysis, “off-normal” (i.e., missing fuel rods) were correctly classified in 17 simulated test scenarios with one quarter (25%) of the fresh fuel rods missing using a training data set of 58 simulated measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants: 2nd Annual Report

For economic reasons, the nuclear industry is witnessing premature closure of nuclear power plants, despite excellent safety records. Operations and Maintenance (O&M) activities are some of the largest costs in operating legacy light-water plants. By reducing O&M costs, nuclear energy can become more economically competitive with other energy sources. This can be achieved by leveraging machine-learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose potential faults within the system. Improved accuracy of the models can lead to a reduction in unnecessary maintenance, thus reducing costs associated with parts, labor, and unnecessary planned, forced, or extended outages. To address these challenges, the goal of this project is to perform research and development in the area of digital monitoring, i.e., the application of advanced sensor technologies (particularly wireless sensor technologies) and data science based analytic capabilities, to advance online monitoring and predictive maintenance in nuclear plants and improve plant performance (efficiency gain and economic competitiveness). This report summarizes the fiscal year 2020 research progress encompassing (1) different wireless vibration sensor and data indicators used to assess the health of a plant asset; (2) development of diagnostic models for fault detection; and (3) development of prognostic models for estimating the health of the system up to 7 days ahead.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1992

Interval prediction in structural dynamic analysis

Methods for assessing the predictive accuracy of structural dynamic models are examined with attention given to the effects of modal mass, stiffness, and damping uncertainties. The methods are based on a nondeterministic analysis called 'interval prediction' in which interval variables are used to describe parameters and responses that are unknown. Statistical databases for generic modeling uncertainties are derived from experimental data and incorporated analytically to evaluate responses. Covariance matrices of modal mass, stiffness, and damping parameters are propagated numerically in models of large space structures by means of three methods. The test data tend to fall within the predicted intervals of uncertainty determined by the statistical databases. The present findings demonstrate the suitability of using data from previously analyzed and tested space structures for assessing the predictive accuracy of an analytical model.

Hasselman, Timothy K.↗
NASA NTRS1993

Interpretation of lunar and planetary electromagnetic scattering using the full wave solutions

Bistatic radar experiments carried out during the Apollo 14, 15, and 16 missions provide a very useful data set with which to compare theoretical models and experimental data. Vesecky, et al. report that their model for near grazing angles compares favorably with experimental data. However, for angles of incidence around 80 degrees, all the analytical models considered by Vesecky, et al. predict values for the quasi-specular cross sections that are about half the corresponding values taken from the Apollo 16 data. In this work, questions raised by this discrepancy between the reported analytical and experimental results are addressed. The unified full wave solutions are shown to be in good agreement with the bistatic radar taken during Apollo 14 and 16 missions. Using the full wave approach, the quasi-specular contributions to the scattered field from the large scale surface roughness as well as the diffuse Bragg-like scattering from the small scale surface roughness are accounted for in a unified self-consistent manner. Since the full wave computer codes for the scattering cross sections contain ground truth data only, it is shown how it can be reliably used to predict the rough surface parameters of planets based on the measured data.

Bahar, E.↗
NASA NTRS1988

Turbofan forced mixer lobe flow modeling. 1: Experimental and analytical assessment

A joint analytical and experimental investigation of three-dimensional flowfield development within the lobe region of turbofan forced mixer nozzles is described. The objective was to develop a method for predicting the lobe exit flowfield. In the analytical approach, a linearized inviscid aerodynamical theory was used for representing the axial and secondary flows within the three-dimensional convoluted mixer lobes and three-dimensional boundary layer analysis was applied thereafter to account for viscous effects. The experimental phase of the program employed three planar mixer lobe models having different waveform shapes and lobe heights for which detailed measurements were made of the three-dimensional velocity field and total pressure field at the lobe exit plane. Velocity data was obtained using Laser Doppler Velocimetry (LDV) and total pressure probing and hot wire anemometry were employed to define exit plane total pressure and boundary layer development. Comparison of data and analysis was performed to assess analytical model prediction accuracy. As a result of this study a planar mixed geometry analysis was developed. A principal conclusion is that the global mixer lobe flowfield is inviscid and can be predicted from an inviscid analysis and Kutta condition.

Barber, T.↗
DOE OSTI2022

Physics-Informed and Data-Driven Prediction of Residual Stress in Three-Dimensional Machining

Efficient and reliable prediction of machining-induced residual stress (RS) is a key requirement for truly integrated computational materials engineering (ICME). Currently available process modeling approaches, including empirical, analytical, and numerical methodologies lack predictive power and require substantial calibration and validation data. Moreover, most model-based approaches consider only two-dimensional (2D) (i.e., orthogonal), cutting processes. Meanwhile, industrial processes such as milling, turning, and drilling are inherently three-dimensional (3D). The present work attempts to bridge the gap between 2D and 3D through careful consideration of the process physics, including geometric, kinematic, and size-effect constraints to realize robust prediction of how RS develops in 3D machining. Using a novel in-situ experimental technique and digital image correlation (DIC) to determine equivalent Hertzian contact widths, contact pressures, and friction coefficients, the proposed methodology leverages a discretized conversion algorithm that includes multi-pass shakedown effects. This paper presents a semi-analytical model to predict machining-induced RS in 3D turning operations, which are used representatively for 3D processes more generally. Rather than follow a ‘brute force’ 3D FEM approach or conduct countless experiments to train a purely data-driven machine learning algorithm, the proposed approach builds on previous 2D modeling work. Through careful consideration of the process physics, including complex geometry/kinematic considerations of 3D turning, the authors demonstrated an experimentally calibrated approach, as well as validation based on published RS data. Model predictions and previously published measurement data of RS depth profiles for turning of Inconel 718 were compared for a range of process parameters. Correlation between the proposed 3D model and validation data was found to be within the margin of experimental error for most conditions. The proposed model appears to capture the overall behavior of 3D RS depth profiles with acceptable accuracy, particularly the key metrics of near-surface stress, peak stress magnitude and location, as well as overall stress profile depth. This report presents a physics-informed, data-driven approach for efficient calibration of a 2D model for machining-induced RS through DIC analysis of in-situ characterized subsurface displacement fields.

42 ENGINEERING↗
NASA NTRS2019

Challenges in Qualification of Thermal Protection Systems in Extreme Entry Environments

Planetary entry vehicles employ ablative TPS materials to shield the aeroshell from entry aeroheating environments. To ensure mission success, it must be demonstrated that the heat shield system, including local features such as seams, does not fail at conditions that are suitably margined beyond those expected in flight. Furthermore, its thermal response must be predictable, with acceptable fidelity, by computational tools used in heat shield design. Mission assurance is accomplished through a combination of ground testing and material response modelling. A material's robustness to failure is verified through arcjet testing while its thermal response is predicted by analytical tools that are verified against experimental data. Due to limitations in flight-like ground testing capability and lack of validated high-fidelity computational models, qualification of heat shield materials is often achieved by piecing together evidence from multiple ground tests and analytical simulations, none of which fully bound the flight conditions and vehicle configuration. Extreme heating environments (>2000 W/sq. cm heat flux and >2 atm pressure), experienced during entries at Venus, Saturn and Ice Giants, further stretch the current testing and modelling capabilities for applicable TPS materials. Fully-dense Carbon Phenolic was the material of choice for these applications; however, since heritage raw materials are no longer available, future uses of re-created Carbon Phenolic will require re-qualification. To address this sustainability challenge, NASA is developing a new dual-layer material based on 3D weaving technology called Heat shield for Extreme Entry Environments (HEEET). Regardless of TPS material, extreme environments pose additional certification challenges beyond what has been typical in recent NASA missions. Scope of this presentation: This presentation will give an overview of challenges faced in verifying TPS performance at extreme heating conditions. Examples include: (1) Bounding aeroheating parameters (heat flux, pressure, shear and enthalpy) in ground facilities. How to certify TPS if environments can't be bounded or aeroheating parameters can't be simultaneously achieved. (2) Higher uncertainties in ground test environments (facility calibration and analytical predictions) at extreme conditions. (3) Testing in flows similar to planetary atmosphere composition (H2/He for Gas and Ice Giants). (4) Test sample size limitations for qualifying seam designs. (5) Lack of computational tools capable of simulating all significant aspects of TPS performance (including initiation and propagation of failures). This presentation will provide recommendations on how the EDL community can address these challenges and mitigate some of the risks involved in flying TPS materials at extreme conditions. Examples include: (1) Dedicated activity to understanding TPS failure modes. Develop computational tools capable of modelling fluid interaction with material's thermostructural response. Validate these tools through failure testing. A better understanding of failure mechanisms may eliminate the need to fully bound all aeroheating parameters in ground testing. (2) Enhancements to current testing facilities to simulate flight-like ablation mechanism (ex. testing in Nitrogen at Ames Interaction Heating Facility to limit oxidation in favor of more sublimation). (3) Improved characterization of test conditions with new diagnostic methods and determination of environment uncertainty through rigorous statistical analysis of available data. (4) Design margin policies that are directly tied to uncertainties in ground test environments and modelling fidelity

Mahzari, Milad↗
DOE OSTI2021

Secondary porosity prediction in complex carbonate reefs using 3D CT scan image analysis and machine learning

Development and preservation of carbonate porosity and permeability are critical to characterizing reservoirs. However, secondary porosity, such as vugs and fractures, are difficult to identify and require collection of expensive wireline tools or core sampling. Wireline logs and cores have traditionally been used to identify the presence of secondary porosity but fail to quantify the contribution to total reservoir porosity. Additionally, advanced wireline logs and core are not readily available for most wells. Dual energy CT scans were collected on whole core from the A-1 Carbonate and Brown Niagaran formations drawn from six wells in northern Michigan. 3D analysis techniques were applied to identify and isolate secondary porosity features. A series of machine learning and data analytics techniques were applied to the dataset to predict secondary porosity features on basic wireline logs. The predictive model successfully predicted secondary porosity with high confidence.

02 PETROLEUM↗
NASA NTRS1979

Measurements of reactive gaseous rocket injector admittances

The paper describes the results of an experimental study of the quantitative determination of the capabilities of the combustion processes associated with coaxial gaseous propellant rocket injectors to drive combustor pressure oscillations. The data, obtained by employing the modified impedance tube technique with compressed air as the oxidizer and acetylene gas as the fuel, describe the frequency dependence of the admittance of the combined injector-combustion process. The measured data are compared with the predictions of the Feiler and Heidmann analytical model utilizing different values for the characteristic combustion time tau sub b. The values of tau sub b which result in a best fit between the measured and predicted data are indicated for different equivalence ratios. It is shown that for the coaxial injector investigated in this study the tau sub b varies between 0.7 and 1.2 msec for equivalence ratios in the range of 0.57 to 1.31. In addition, the experimental data indicate that the tested injector system could drive combustion instabilities over a frequency range that is in qualitative agreement with the predictions of the Feiler and Heidmann model.

Janardan, B. A.↗
NASA NTRS1978

Engine component improvement: JT8D and JT9D performance improvements

A feasibility analysis screening method for predicting the airline acceptance of a proposed engine performance improvement modification was developed. Technical information derived from available test data and analytical models is used along with conceptual/preliminary designs to establish the predicted performance improvement, weight and installation characteristics, the cost for new production and retrofit, maintenance cost and qualitative characteristics of the performance improvement concepts being evaluated. These results are used to arrive at the payback period, which is the time required for an airline to recover the investment cost of concept implementation, and to predict the amount of fuel saved by a performance improvement concept. The assumptions used to calculate the payback period and fuel saved are discussed. A summary of the results when the screening method is applied is presented for several representative JT8D and JT9D performance improvement concepts. An example of the input information used to develop the summary results is shown.

Gaffin, W. O.↗
NASA NTRS2014

Preparing Earth Data Scientists for 'The Sexiest Job of the 21st Century'

What Exactly do Earth Data Scientists do, and What do They Need to Know, to do It? There is not one simple answer, but there are many complex answers. Data Science, and data analytics, are new and nebulas, and takes on different characteristics depending on: The subject matter being analyzed, the maturity of the research, and whether the employed subject specific analytics is descriptive, diagnostic, discoveritive, predictive, or prescriptive, in nature. In addition, in a, thus far, business driven paradigm shift, university curriculums teaching data analytics pertaining to Earth science have, as a whole, lagged behind, andor have varied in approach.This presentation attempts to breakdown and identify the many activities that Earth Data Scientists, as a profession, encounter, as well as provide case studies of specific Earth Data Scientist and data analytics efforts. I will also address the educational preparation, that best equips future Earth Data Scientists, needed to further Earth science heterogeneous data research and applications analysis. The goal of this presentation is to describe the actual need for Earth Data Scientists and the practical skills to perform Earth science data analytics, thus hoping to initiate discussion addressing a baseline set of needed expertise for educating future Earth Data Scientists.

data analytics↗
NASA NTRS1989

An Experimental Method for Measuring Water Droplet Impingement Efficiency on Two- and Three-dimensional Bodies

An experimental method was developed to determine the droplet impingement characteristics on 2-D and 3-D bodies. The experimental results provide the essential droplet impingement data required to validate water droplet trajectory codes, which are used in the analysis of aircraft icing. A body, whose water droplet impingement characteristics are required, is covered at strategic locations by thin strips of moisture absorbing (blotter) paper, and is exposed to an air stream containing a water dye solution spray cloud. Water droplet impingement data are extracted from the dyed blotter strips by measuring the optical reflectance of the dye deposit on the strips, using an automated reflectometer. Models tested include a 4-inch diameter cylinder, a NACA 652015 airfoil section, a MS(1)-0317 supercritical airfoil section, three simulated ice shapes, an axisymmetric inlet and a Boeing 737-300 inlet model. Detailed descriptions of the dye tracer technique, instrumentation, data reduction method and the results obtained are presented. Analytical predictions of collection efficiency characteristics for most test configurations are included for comparison.

Trajectory code validation↗
NASA NTRS1977

Assessment of analytical techniques for predicting solid propellant exhaust plumes and plume impingement environments

An analysis of experimental nozzle, exhaust plume, and exhaust plume impingement data is presented. The data were obtained for subscale solid propellant motors with propellant Al loadings of 2, 10 and 15% exhausting to simulated altitudes of 50,000, 100,000 and 112,000 ft. Analytical predictions were made using a fully coupled two-phase method of characteristics numerical solution and a technique for defining thermal and pressure environments experienced by bodies immersed in two-phase exhaust plumes.

Tevepaugh, J. A.↗
NASA NTRS1992

Pressurization of cryogens: A review of current technology and its applicability to low-gravity conditions

A review of technology, history, and current status for pressurized expulsion of cryogenic tankage is presented. Use of tank pressurization to expel cryogenic fluids will continue to be studied for future spacecraft applications over a range of operating conditions in the low-gravity environment. The review examines experimental test results and analytical model development for quiescent and agitated conditions in normal-gravity, followed by a discussion of pressurization and expulsion in low-gravity. Validated, 1-D, finite difference codes exist for the prediction of pressurant mass requirements within the range of quiescent normal-gravity test data. To date, the effects of liquid sloshing have been characterized by tests in normal-gravity, but analytical models capable of predicting pressurant gas requirements remain unavailable. Efforts to develop multidimensional modeling capabilities in both normal and low-gravity have recently occurred. Low-gravity cryogenic fluid transfer experiments are needed to obtain low-gravity pressurized expulsion data. This data is required to guide analytical model development and to verify code performance.

Vandresar, N. T.↗
NASA NTRS1992

Pressurization of cryogens - A review of current technology and its applicability to low-gravity conditions

A review of technology, history, and current status for pressurized expulsion of cryogenic tankage is presented. Use of tank pressurization to expel cryogenic fluid will continue to be studied for future spacecraft applications over a range of operating conditions in the low-gravity environment. The review examines experimental test results and analytical model development for quiescent and agitated conditions in normal-gravity followed by a discussion of pressurization and expulsion in low-gravity. Validated, 1-D, finite difference codes exist for the prediction of pressurant mass requirements within the range of quiescent normal-gravity test data. To date, the effects of liquid sloshing have been characterized by tests in normal-gravity, but analytical models capable of predicting pressurant gas requirements remain unavailable. Efforts to develop multidimensional modeling capabilities in both normal and low-gravity have recently occurred. Low-gravity cryogenic fluid transfer experiments are needed to obtain low-gravity pressurized expulsion data. This data is required to guide analytical model development and to verify code performance.

Van Dresar, N. T.↗
NASA NTRS2011

HIFiRE Direct-Connect Rig (HDCR) Phase I Scramjet Test Results from the NASA Langley Arc-Heated Scramjet Test Facility

A series of hydrocarbon-fueled direct-connect scramjet ground tests has been completed in the NASA Langley Arc-Heated Scramjet Test Facility (AHSTF) at simulated Mach 8 flight conditions. These experiments were part of an initial test phase to support Flight 2 of the Hypersonic International Flight Research Experimentation (HIFiRE) Program. In this flight experiment, a hydrocarbon-fueled scramjet is intended to demonstrate transition from dual-mode to scramjet-mode operation and verify the scramjet performance prediction and design tools A performance goal is the achievement of a combusted fuel equivalence ratio greater than 0.7 while in scramjet mode. The ground test rig, designated the HIFiRE Direct Connect Rig (HDCR), is a full-scale, heat sink test article that duplicates both the flowpath lines and a majority of the instrumentation layout of the isolator and combustor portion of the flight test hardware. The primary objectives of the HDCR Phase I tests were to verify the operability of the HIFiRE isolator/combustor across the simulated Mach 6-8 flight regime and to establish a fuel distribution schedule to ensure a successful mode transition. Both of these objectives were achieved prior to the HiFIRE Flight 2 payload Critical Design Review. Mach 8 ground test results are presented in this report, including flowpath surface pressure distributions that demonstrate the operation of the flowpath in scramjet-mode over a small range of test conditions around the nominal Mach 8 simulation, as well as over a range of fuel equivalence ratios. Flowpath analysis using ground test data is presented elsewhere; however, limited comparisons with analytical predictions suggest that both scramjet-mode operation and the combustion performance objective are achieved at Mach 8 conditions.

Cabell, Karen↗