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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Simplified data reduction methods for the ECT test for mode 3 interlaminar fracture toughness

Simplified expressions for the parameter controlling the load point compliance and strain energy release rate were obtained for the Edge Crack Torsion (ECT) specimen for mode 3 interlaminar fracture toughness. Data reduction methods for mode 3 toughness based on the present analysis are proposed. The effect of the transverse shear modulus, G(sub 23), on mode 3 interlaminar fracture toughness characterization was evaluated. Parameters influenced by the transverse shear modulus were identified. Analytical results indicate that a higher value of G(sub 23) results in a low load point compliance and lower mode 3 toughness estimation. The effect of G(sub 23) on the mode 3 toughness using the ECT specimen is negligible when an appropriate initial delamination length is chosen. A conservative estimation of mode 3 toughness can be obtained by assuming G(sub 23) = G(sub 12) for any initial delamination length.

Li, Jian↗
NASA NTRS2017

LPV Modeling of a Flexible Wing Aircraft Using Modal Alignment and Adaptive Gridding Methods

One of the earliest approaches in gain-scheduling control is the gridding based approach, in which a set of local linear time-invariant models are obtained at various gridded points corresponding to the varying parameters within the flight envelop. In order to ensure smooth and effective Linear Parameter-Varying control, aligning all the flexible modes within each local model and maintaining small number of representative local models over the gridded parameter space are crucial. In addition, since the flexible structural models tend to have large dimensions, a tractable model reduction process is necessary. In this paper, the notion of s-shifted H2- and H Infinity-norm are introduced and used as a metric to measure the model mismatch. A new modal alignment algorithm is developed which utilizes the defined metric for aligning all the local models over the entire gridded parameter space. Furthermore, an Adaptive Grid Step Size Determination algorithm is developed to minimize the number of local models required to represent the gridded parameter space. For model reduction, we propose to utilize the concept of Composite Modal Cost Analysis, through which the collective contribution of each flexible mode is computed and ranked. Therefore, a reduced-order model is constructed by retaining only those modes with significant contribution. The NASA Generic Transport Model operating at various flight speeds is studied for verification purpose, and the analysis and simulation results demonstrate the effectiveness of the proposed modeling approach.

LPV Modeling↗
DOE OSTI2020

The Energy Modeling Forum (EMF)-30 Study on Short-Lived Climate Forcers: Introduction and Overview

The Energy Modeling Forum (EMF)-30 inter-comparison study on short-lived climate forcers (SLCFs) focuses on black carbon (BC) and methane, two of the most important warming SLCFs. The potential impact on climate change of methane and BC-focused emission reductions in the transport and residential sectors were quantified using nine integrated assessment models and a simple climate model. These SLCF reductions reduced global temperatures by 0.18–0.26 °C in 2050 across the models for central climate parameters, with methane being the dominant contributor. The incremental impact of SLCF-focused reductions is much smaller when combined with a broader climate policy. Individual modeling groups examined the health benefits of air pollutant reductions, climate policy co-benefits, and quantified market impacts from air pollutant damages. Model structure and set-up impact on results are discussed along with areas for future work.

Smith, Steven J.↗
DOE OSTI2022

A Reinforcement Learning Approach to Parameter Selection for Distributed Optimal Power Flow

With the increasing penetration of distributed energy resources, distributed optimization algorithms have attracted significant attention for power systems applications due to their potential for superior scalability, privacy, and robustness to a single point-of-failure. The Alternating Direction Method of Multipliers (ADMM) is a popular distributed optimization algorithm; however, its convergence performance is highly dependent on the selection of penalty parameters, which are usually chosen heuristically. In this work, we use reinforcement learning (RL) to develop an adaptive penalty parameter selection policy for alternating current optimal power flow (ACOPF) problem solved via ADMM with the goal of minimizing the number of iterations until convergence. We train our RL policy using deep Q-learning and show that this policy can result in significantly accelerated convergence (up to a 59% reduction in the number of iterations compared to existing, curvatureinformed penalty parameter selection methods). Furthermore, we show that our RL policy demonstrates promise for generalizability, performing well under unseen loading schemes as well as under unseen losses of lines and generators (up to a 50% reduction in iterations). This work thus provides a proof-of-concept for using RL for parameter selection in ADMM for power systems applications.

alternating current optimal power flow↗
DOE OSTI2024

Quantitative analysis of three-dimensional fatigue crack path selection in Mg alloy WE43 using high-energy X-ray diffraction microscopy

Fatigue short-cracks in Mg alloys display complex growth behavior due to high plastic anisotropy and crack path dependence on local microstructural features. In this study, the three-dimensional crystallography of short-crack paths in Mg alloy WE43 was characterized by mapping near-field high-energy X-ray diffraction microscopy (HEDM) reconstructed grain maps to high-resolution X-ray CT reconstructions of the fracture surfaces in the crack initiation and short-crack growth regions of six ultrasonic fatigue specimens. Crack–grain–boundary intersections were analyzed at 81 locations across the six crack paths. The basal intragranular, non-basal intragranular, or intergranular character of short-crack growth following each boundary intersection was correlated to crystallographic and geometric parameters of the trailing and leading grains, three-dimensional grain boundary plane, and advancing crack front. The results indicate that crack paths are dependent on the combined crystallographic and geometric character of the local microstructure, and crack path prediction can be improved by use of dimensionality reduction on subsets of high-linear-correlation microstructural parameters.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Maximum life spiral bevel reduction design

Optimization is applied to the design of a spiral bevel gear reduction for maximum life at a given size. A modified feasible directions search algorithm permits a wide variety of inequality constraints and exact design requirements to be met with low sensitivity to initial values. Gear tooth bending strength and minimum contact ratio under load are included in the active constraints. The optimal design of the spiral bevel gear reduction includes the selection of bearing and shaft proportions in addition to gear mesh parameters. System life is maximized subject to a fixed backcone distance of the spiral bevel gear set for a specified speed reduction, shaft angle, input torque, and power. Design examples show the influence of the bearing lives on the gear parameters in the optimal configurations. For a fixed back-cone distance, optimal designs with larger shaft angles have larger service lives.

Savage, M.↗
DOE OSTI2023

Methane Emissions Produced by Pneumatic Devices and Produced Water Tanks on Natural Gas Wellsites

In recent years, more scrutiny has been placed on the release of greenhouse gasses (GHGs) by the oil and gas industry in North America as climate concerns increase. In the coming years, stricter regulations proposed by the Environmental Protection Agency (EPA) concerning the release of GHGs will further direct attention to GHG emissions quantification, modeling, and overall reduction. Active natural gas wellsites employ production equipment that routinely emits methane during normal operation. Production equipment often includes, but is not limited to, gas production units (GPUs), pneumatic controllers (PCs) and actuators powered by produced natural gas, and produced water storage tanks. This work details direct methane emission measurements taken at active natural gas wellsites originating from intermittent pneumatic controllers and produced water storage tanks. Efforts to model methane flows originating from these sources are also detailed, and those results are compared to direct measurement. The direct methane emissions measurement campaign collected flow data from two active dry wellsites in the Marcellus shale region. These measurement campaigns captured, in total, several weeks of continuous data from these sites. Data included multiple pneumatic device vent flowrate channels, a single channel monitoring total emissions vented from the produced water storage tanks, and corresponding site weather data. Periodic composition measurements were taken from flows vented from produced water tanks. Computational modeling efforts attempted to mimic a given site’s methane emissions behavior given limited input parameters. Direct measurement data and simulation data yielded, through reduction and analysis, apparent methane emissions factors, statistics on pneumatic device actuation events, important relationships between GPU parameters and pneumatic device actuation events, produced water storage tank vent flows and flow compositions, and parameters most contributing to the magnitude and frequency of these fugitive methane emissions. Measurements, considering data from a 72hr period, produced PC emissions factors from 0.008 to 0.03 SCFH per device with an average device emitting 0.026 SCFH at the first site. The second site produced PC emissions factors spanning from 0.05 to 25.47 SCFH with an average device emitting 1.93 SCFH not including the 25.47 SCFH device, which was assumed to be malfunctioning. Two unique water tank emission measurements were made, 618 g CH4 per hour and 32.6 g CH4 per hour. On a water basis, the water tank emissions factors were 0.66 and 0.042 kg CH4 per bbl of water, respectively.

03 NATURAL GAS↗
DOE OSTI2021

A Discussion of Strength Reduction Factor Development for Thermal Aging Effect on Nuclear Structural Alloys

In consideration of structural alloy property deterioration during long-term exposure to elevated temperatures, the yield and ultimate tensile strength reduction factors are provided in the Boiler and Pressure Vessel Code Section III for nuclear reactor component design and operation analysis. Because the Gen IV reactor requirement of 40 ~ 60 years of service life makes it difficult to acquire such long exposure test data for developing the reduction factors, they must be derived from test data with relatively short exposure by predictive methods considered to be reasonably reliable. A novel approach with a physically-based model has recently been proposed for application to development of reduction factors for 9Cr-1Mo-V. In the model, contributors to the tensile strength are first identified and related to definite microstructural features of the alloy, then some physically-based methods are employed to simulate the microstructural evolution, and finally the model is assembled with test-data-calibrated parameters to generate the yield and ultimate tensile strength reduction factors covering elevated temperature exposure for up to 57 years. The approach is undoubtedly a trailblazing development that will, if proven reliable, lead to a paradigm shift in predicting thermal aging behavior of many other alloys. Its debut application to Section III, however, concerns nuclear safety and naturally warrants objective, impartial, and thorough technical scrutiny. In the present paper, the novel and conventional approaches are discussed. Necessary improvements to the novel approach are recommended for its application to nuclear structural component design and analysis, and for its potential expanded use to other alloys.

Ren, Weiju↗
NASA NTRS2012

Sensitivity of Mission Energy Consumption to Turboelectric Distributed Propulsion Design Assumptions on the N3-X Hybrid Wing Body Aircraft

In a previous study by the authors it was shown that the N3-X, a 300 passenger hybrid wing body (HWB) aircraft with a turboelectric distributed propulsion (TeDP) system, was able to meet the NASA Subsonic Fixed Wing (SFW) project goal for N+3 generation aircraft of at least a 60% reduction in total energy consumption as compared to the best in class current generation aircraft. This previous study combined technology assumptions that represented the highest anticipated values that could be matured to technology readiness level (TRL) 4-6 by 2030. This paper presents the results of a sensitivity analysis of the total mission energy consumption to reductions in each key technology assumption. Of the parameters examined, the mission total energy consumption was most sensitive to changes to total pressure loss in the propulsor inlet. The baseline inlet internal pressure loss is assumed to be an optimistic 0.5%. An inlet pressure loss of 3% increases the total energy consumption 9%. However changes to reduce inlet pressure loss can result in additional distortion to the fan which can reduce fan efficiency or vice versa. It is very important that the inlet and fan be analyzed and optimized as a single unit. The turboshaft hot section is assumed to be made of ceramic matrix composite (CMC) with a 3000 F maximum material temperature. Reducing the maximum material temperature to 2700 F increases the mission energy consumption by only 1.5%. Thus achieving a 3000 F temperature in CMCs is important but not central to achieving the energy consumption objective of the N3-X/TeDP. A key parameter in the efficiency of superconducting motors and generators is the size of the superconducting filaments in the stator. The size of the superconducting filaments in the baseline model is assumed to be 10 microns. A 40 micron filament, which represents current technology, results in a 200% increase in AC losses in the motor and generator stators. This analysis shows that for a system with 40 micron filaments the higher stator losses plus the added weight and power of larger cryocoolers results in a 4% increase in mission energy consumption. If liquid hydrogen is used to cool the superconductors the 40 micron fibers results in a 200% increase in hydrogen required for cooling. Each pound of hydrogen used as fuel displaces 3 pounds of jet fuel. For the N3-X on the reference mission the additional hydrogen due to the increase stator losses reduces the total fuel weight 10%. The lighter fuel load and attendant vehicle resizing reduces the total energy consumption more than the higher stator losses increase it. As a result with hydrogen cooling there is a slight reduction in mission energy consumption with increasing stator losses. This counter intuitive result highlights the need to consider the full system impact of changes rather than just at the component or subsystem level.

Felder, James L.↗
DOE OSTI2023

Comparing the cooling effectiveness of operationalisable urban surface combination scenarios for summer heat mitigation

Extreme summer heat in cities exacerbates the vulnerability of urban communities to heatwaves. Vegetative and reflective urban surfaces can help reduce urban heat. This study investigated the impacts of urban trees, green roofs and cool roofs on heat mitigation during average and extreme summer conditions in temperate oceanic Melbourne, Australia. We simulated the city climate using ‘The Air Pollution Model’ (TAPM) at a 1 km spatial resolution over 10 years, which according to our review of the literature, was the most prolonged period for simulation in Melbourne. During a widespread heatwave event, some of the tested scenarios with combined surface parameters could reduce the extreme values of the energy budget components- sensible heat, latent heat, and storage heat fluxes up to seasonal averages compared to the existing situation for Melbourne (control). The scenario with the highest (reasonable maximum) ground-level vegetation, green roofs, and cool roofs could reduce air temperatures up to 2.4 °C. The simulations suggest that a combined strategy with vegetative and high-albedo surfaces will deliver higher effectiveness with maximum cooling benefits and cost-effectiveness than individual strategies in cities. These results suggest the importance of collaborative strategic planning of urban surfaces to make cities healthier, sustainable, and liveable.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Effectively Using Remote I/O For Work Composition in Distributed Workflows

Distributed scientific workflows are becoming more important with the interest in incorporating AI into their loops. A critical programming and performance question is how to compose workflow tasks when data is produced on one system but must be consumed on another. Since the dominant technique is composition with remote I/O, this paper explores its performance expectations. We describe BigFlowSim, a workflow I/O simulator that captures key implementation choices for remote I/O, including intensity, reuse, locality, access pattern, and data movement.With BigFlowSim, we generate a synthetic benchmark. We quantify the effects of each parameter with a performance sensitivity study. We explain trends in terms of data movement reduction and show that, under certain conditions, it is possible to establish a total order among most parameters. We apply these insights to a high energy physics workflow, Belle II Monte Carlo and simulate several I/O optimizations. Speedups range from 5% to 2×, without changing compute time.

Friese, Ryan D.↗
DOE OSTI2025

Constraining Systematics for Future Sterile Neutrino Analysis at NOvA Experiment

In this article, we report an approach used to constrain the impact of cross-section systematic parameters in the future sterile neutrino analysis at the NOvA experiment. NOvA is a long-baseline neutrino experiment built to investigate the intricate properties of neutrinos, with the principal emphasis on active three-flavor neutrino mixing phenomena. Besides that, NOvA also explores exotic oscillations, including sterile neutrino search. Uncertainties on the neutrino flux, cross-section, and detector systematic parameters significantly contribute, complicating the disentanglement of genuine physics events from background noise. We present the impact of systematic reduction via near detector neutral current sample splitting and its implications on oscillation parameters, leveraging results primarily from Monte Carlo simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1985

The design and implementation of cost-effective algorithms for direct solution of banded linear systems on the vector processor system 32 supercomputer

The problem of solving banded linear systems by direct (non-iterative) techniques on the Vector Processor System (VPS) 32 supercomputer is considered. Two efficient direct methods for solving banded linear systems on the VPS 32 are described. The vector cyclic reduction (VCR) algorithm is discussed in detail. The performance of the VCR on a three parameter model problem is also illustrated. The VCR is an adaptation of the conventional point cyclic reduction algorithm. The second direct method is the Customized Reduction of Augmented Triangles' (CRAT). CRAT has the dominant characteristics of an efficient VPS 32 algorithm. CRAT is tailored to the pipeline architecture of the VPS 32 and as a consequence the algorithm is implicitly vectorizable.

Samba, A. S.↗
DOE OSTI2020

Laminar drag reduction in microchannels with liquid infused textured surfaces

Liquid infused surfaces (LIS) achieve non-wetting properties through asperity structures containing pockets of a lubricating liquid rather than air. Although studies have demonstrated several potential applications of LIS, the effect of liquid infused texture on the flow of liquid in microchannels has not been systematically addressed. The present work focuses on the effect of liquid-infused texture geometry and the infused liquid properties on the flow characteristics of a bulk fluid in rectangular and round microchannel geometries. Considering four different textured geometries of transverse ridges, longitudinal ridges, in-lined square posts and staggered squares, a detailed parametric study is presented to assess the resulting drag reduction and friction factor, expressed in terms of the Poiseuille number, on the flow in microchannels. The effect of geometrical parameters is investigated for different asperity solid fraction (Φ s ), asperity height (h s ) and channel thickness (H) or tube diameter (D), while the effect of the infused fluid is studied in terms of a ratio of its viscosity relative to the viscosity of the flowing bulk fluid. Based on the results of the parametric study an extension of the conventional Moody diagram for non-wetting surfaces is developed. Finally, a design of experiments study is conducted to relate the drag reduction and Poiseuille number to the various governing parameters, using which conditions that maximize drag reduction are identified.

42 ENGINEERING↗
DOE OSTI2021

Neural network-based order parameter for phase transitions and its applications in high-entropy alloys

Phase transition is one of the most important phenomena in nature and plays a central role in materials design. All phase transitions are characterized by suitable order parameters, including the order–disorder phase transition. However, finding a representative order parameter for complex systems is non-trivial, such as for high-entropy alloys. Given the strength of dimensionality reduction of a variational autoencoder (VAE), we introduce a VAE-based order parameter. Here, we propose that the Manhattan distance in the VAE latent space can serve as a generic order parameter for order–disorder phase transitions. The physical properties of our order parameter are quantitatively interpreted and demonstrated by multiple refractory high-entropy alloys. Using this order parameter, a generally applicable alloy design concept is proposed by mimicking the natural mixing process of elements. Our physically interpretable VAE-based order parameter provides a computational technique for understanding chemical ordering in alloys, which can facilitate the development of rational alloy design strategies.

36 MATERIALS SCIENCE↗
NASA NTRS2005

Launch Vehicle Propulsion Design with Multiple Selection Criteria

The approach and techniques described herein define an optimization and evaluation approach for a liquid hydrogen/liquid oxygen single-stage-to-orbit system. The method uses Monte Carlo simulations, genetic algorithm solvers, a propulsion thermo-chemical code, power series regression curves for historical data, and statistical models in order to optimize a vehicle system. The system, including parameters for engine chamber pressure, area ratio, and oxidizer/fuel ratio, was modeled and optimized to determine the best design for seven separate design weight and cost cases by varying design and technology parameters. Significant model results show that a 53% increase in Design, Development, Test and Evaluation cost results in a 67% reduction in Gross Liftoff Weight. Other key findings show the sensitivity of propulsion parameters, technology factors, and cost factors and how these parameters differ when cost and weight are optimized separately. Each of the three key propulsion parameters; chamber pressure, area ratio, and oxidizer/fuel ratio, are optimized in the seven design cases and results are plotted to show impacts to engine mass and overall vehicle mass.

Shelton, Joey D.↗
DOE OSTI2020

Fractal Model for Drag Reduction on Multiscale Nonwetting Rough Surfaces

Rough surfaces in contact with a flow of fluid exhibit alternating no-slip and free shear boundary conditions at the solid–liquid and air–liquid interfaces, respectively, thereby potentially offering drag reduction benefits. The balance between the dynamic pressure in the flow and the restoring capillary pressure in the interasperity spaces determines the stability of the Cassie state of wettability and is a function of the relative extent of no-slip and free shear regions per unit surface area. In the present study, using a fractal representation of rough surface topography, an analytical model is developed to quantify the stability of the Cassie state of wettability as well as drag reduction and the friction factor for laminar flow in a rectangular channel between nonwetting multiscale rough surfaces. A systematic study is conducted to quantify the effects of fractal parameters of the surfaces and the flow Reynolds number on drag reduction and the friction factor. The studies are used to develop friction factor curves extending the classical Moody diagram to hydrophobic and superhydrophobic surfaces. On the basis of the studies, regime maps are derived for estimating the extent of drag reduction offered by hydrophobic and superhydrophobic surfaces, revealing that superhydrophobic surfaces do not always offer the best drag reduction performance. The application of the fractal model to practical topographies of nonwetting surfaces of copper, aluminum, and zinc oxide fabricated via electrodeposition and etching is also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗