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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Initial Systems-Level Assessment of a Distributed Direct Air Capture System Concept at the Urban-scale (UrbanDAC)

Direct Air Capture (DAC) systems offer a promising solution for mitigating global carbon emissions by directly removing ambient carbon dioxide (CO 2 ) from the atmosphere. While future DAC facilities are typically envisioned as being large and centralized, small-scale systems present an alternative approach with advantages such as adaptability and lower uptake costs. By harnessing waste heat from the built environment, such small-scale systems become distributed DAC at the urban scale (UrbanDAC) that benefit from existing urban infrastructure, while presenting challenges such as identifying eligible buildings and sustainable transportation and storage of captured CO 2 . Collaborating with engineering experts and developers of a DAC unit that can be co-located with cooling towers of existing commercial buildings, this study explores the systems-level implications of UrbanDAC using a geographically explicit multi-decision criteria analysis (MCDA) framework. By considering various infrastructure and environmental factors, network analysis and geospatial techniques are applied to identify optimal building candidates for distributed DAC units within Knoxville, Tennessee, USA, as a representative mid-size city. The selected outputs of the MCDA are used to explore a scenario that assumes a CO 2 collection and transport route for 20 high-ranking candidate buildings; total carbon emissions, EV energy consumption, and net carbon dioxide removal (CDR) are then calculated. Results suggest that the spatial variation of optimal candidates between thriving commercial areas is an important planning consideration. Examining the feasibility of UrbanDAC at an urban planning level provides valuable insights into the barriers and enabling conditions for CDR in cities, where the vast majority of CO 2 emissions are produced, and supports decision-making processes for the implementation of decarbonization initiatives. Through this initial assessment, this research acts as a pilot study for an emerging technology that highlights the importance of distributed DAC technologies in addressing climate change and emphasizes the need for further research and exploration in this domain.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1980

Laser-fluorescence measurement of marine algae

Progress in remote sensing of algae by laser-induced fluorescence is subject of comprehensive report. Existing single-wavelength and four-wavelength systems are reviewed, and new expression for power received by airborne sensor is derived. Result differs by as much as factor of 10 from those previously reported. Detailed error analysis evluates factors affecting accuracy of laser-fluorosensor systems.

Browell, E. V.↗
NASA NTRSDate not supplied

Implementing Geometric Surface Imperfections into Sandwich Composite Cylinder Finite Element Method Models

The buckling responses of certain cylindrical shell structures are extremely sensitive to geometric surface imperfections. The NASA Engineering and Safety Center (NESC) Shell Buckling Knockdown Factor Project (SBKF) is conducting research to develop analysis-based buckling design recommendations. Experiments are used to verify the analysis-based factors, but the sensitivity of the test articles to geometric imperfections requires implementing as-manufactured imperfections into high-fidelity finite element method models. Data collection methods such as structured light scanning are used for all geometric surface data used in this work. Common preprocessing and visualization steps used in SBKF are discussed, and steps on how surface scans are prepared for implementation into a finite element model is described. The Python Tool for Implementing Geometric Imperfections in Reduced Structures (Py_TIGIRS), written specifically for the use with SBKF, is briefly described and uses eight functions to extract, modify, and write geometric imperfections into Abaqus input files. Results of the pre-processing methods and results from Py_TIGIRS are provided and compared for Composite Test Article (CTA) 8.2B. Excellent agreement between the visualized scan data and the FEM-extracted geometry is demonstrated. A brief example of why geometric surface imperfections are significant in nonlinear numerical analyses for thin cylinders in axial compression is provided as motivation to use tools such as Py_TIGIRS. Future development of Py_TIGIRS including expansion to structures of arbitrary geometry is planned.

Sandwich structures↗
NASA NTRSDate not supplied

Implementing Geometric Surface Imperfections into Sandwich Composite Cylinder Finite Element Method Models

The buckling responses of certain cylindrical shell structures are extremely sensitive to geometric imperfections. The NASA Engineering and Safety Center (NESC) Shell Buckling Knockdown Factor Project (SBKF) is conducting research to develop analysis-based buckling design recommendations. Experiments are used to verify the analysis-based factors, but the sensitivity of the test articles to geometric imperfections requires implementing as-manufactured imperfections into high-fidelity finite element method (FEM) models. Geometry measurement methods such as structured light scanning are used for all geometric surface data used in this work. Common preprocessing and visualization steps used in SBKF are discussed, and steps of how surface scans are prepared for implementation into a finite element model is described. The Python Tool for Implementing Geometric Imperfections in Reduced Structures (Py_TIGIRS), written specifically for the use with SBKF, is briefly described and uses eight functions to extract, modify, and write geometric imperfections into Abaqus input files. Results of the preprocessing methods and results from Py_TIGIRS are provided and compared for Composite Test Articles (CTA) 8.2, 8.2B, and 8.3. Excellent agreement between the visualized scan data and the FEM-extracted geometry is demonstrated. A brief example of why geometric surface imperfections are significant in nonlinear numerical analyses for thin cylinders in axial compression is provided as motivation to use tools such as Py_TIGIRS. Future developments of Py_TIGIRS including expansion to structures of arbitrary geometry is planned.

Geometric imperfections↗
NASA NTRSDate not supplied

Implementing Geometric Surface Imperfections into Sandwich Composite Cylinder Finite Element Method Models

The buckling responses of certain cylindrical shell structures are extremely sensitive to geometric imperfections. The NASA Engineering and Safety Center (NESC) Shell Buckling Knockdown Factor Project (SBKF) is conducting research to develop analysis-based buckling design recommendations. Experiments are used to verify the analysis-based factors, but the sensitivity of the test articles to geometric imperfections requires implementing as-manufactured imperfections into high-fidelity finite element method (FEM) models. Geometry measurement methods such as structured light scanning are used for all geometric surface data used in this work. Common preprocessing and visualization steps used in SBKF are discussed, and steps of how surface scans are prepared for implementation into a finite element model is described. The Python Tool for Implementing Geometric Imperfections in Reduced Structures (Py_TIGIRS), written specifically for the use with SBKF, is briefly described and uses eight functions to extract, modify, and write geometric imperfections into Abaqus input files. Results of the preprocessing methods and results from Py_TIGIRS are provided and compared for Composite Test Articles (CTA) 8.2, 8.2B, and 8.3. Excellent agreement between the visualized scan data and the FEM-extracted geometry is demonstrated. A brief example of why geometric surface imperfections are significant in nonlinear numerical analyses for thin cylinders in axial compression is provided as motivation to use tools such as Py_TIGIRS. Future developments of Py_TIGIRS including expansion to structures of arbitrary geometry is planned.

Geometric imperfections↗
NASA NTRS1984

Quick Look Analysis of TM Data of the Washington, District of Columbia Area

A fixed factor analysis-of-variance (ANOVA) approach was used to quantify the impact of each TM sensor characteristic (spectral, spatial, and radiometric resolutions) on classification accuracy. All assessments were made relative to MSS sensor characteristics, and the impact of each characteristic was assessed individually, and in all possible combinations. Thematic Mapper data acquired over the Washington, D.C. area on November 2, 1982 were utilized to conduct the experiment. The following results were obtained: the reduction of quantization level from eight bits to six bits caused a decrease in overall accuracy (7%); the use of only three bands (TM 2, 3 and 4) covering the isible and near infrared portion of the spectrum caused a decrease in overall accuracy (7%); and the decrease in spatial resolution resulted in an increase in overall accuracy (4%). Results indicate that the increased radiometric and spectral resolution of the TM instrument do provide increased information content. The result of the spatial resolution degradation is somewhat misleading, in that the result is more a function of spatial resolution.

Williams, D. L.↗
NASA NTRS1994

Human factors issues and approaches in the spatial layout of a space station control room, including the use of virtual reality as a design analysis tool

Human Factors Engineering support was provided for the 30% design review of the late Space Station Freedom Payload Control Area (PCA). The PCA was to be the payload operations control room, analogous to the Spacelab Payload Operations Control Center (POCC). This effort began with a systematic collection and refinement of the relevant requirements driving the spatial layout of the consoles and PCA. This information was used as input for specialized human factors analytical tools and techniques in the design and design analysis activities. Design concepts and configuration options were developed and reviewed using sketches, 2-D Computer-Aided Design (CAD) drawings, and immersive Virtual Reality (VR) mockups.

Hale, Joseph P., II↗
NASA NTRS1978

Filtering and error analysis via the UDU super T covariance factorization

Kalman filter algorithms based on the UDU super T covariance factorization are discussed, with special attention given to algorithm implementation efficiency. A U-D-factored covariance error-analysis algorithm is formulated, and its efficiency and numerical stability are demonstrated in a representative orbit determination problem. The numerical results are compared with those obtained using covariance error-analysis formulas, and the comparison highlights the numerical superiority of the present algorithm. A byproduct of the U-D analysis is a highly efficient algorithm mechanization of the arbitrary gain covariance update formula.

Thornton, C. L.↗
NASA NTRS2013

Simple Sensitivity Analysis for Orion GNC

The performance of Orion flight software, especially its GNC software, is being analyzed by running Monte Carlo simulations of Orion spacecraft flights. The simulated performance is analyzed for conformance with flight requirements, expressed as performance constraints. Flight requirements include guidance (e.g. touchdown distance from target) and control (e.g., control saturation) as well as performance (e.g., heat load constraints). The Monte Carlo simulations disperse hundreds of simulation input variables, for everything from mass properties to date of launch.We describe in this paper a sensitivity analysis tool (Critical Factors Tool or CFT) developed to find the input variables or pairs of variables which by themselves significantly influence satisfaction of requirements or significantly affect key performance metrics (e.g., touchdown distance from target). Knowing these factors can inform robustness analysis, can inform where engineering resources are most needed, and could even affect operations. The contributions of this paper include the introduction of novel sensitivity measures, such as estimating success probability, and a technique for determining whether pairs of factors are interacting dependently or independently. The tool found that input variables such as moments, mass, thrust dispersions, and date of launch were found to be significant factors for success of various requirements. Examples are shown in this paper as well as a summary and physics discussion of EFT-1 driving factors that the tool found.

Monte Carlo Simulation↗
NASA NTRS1988

Entrance and exit region friction factor models for annular seal analysis

The Mach number definition and boundary conditions in Nelson's nominally-centered, annular gas seal analysis are revised. A method is described for determining the wall shear stress characteristics of an annular gas seal experimentally. Two friction factor models are developed for annular seal analysis; one model is based on flat-plate flow theory; the other uses empirical entrance and exit region friction factors. The friction factor predictions of the models are compared to experimental results. Each friction model is used in an annular gas seal analysis. The seal characteristics predicted by the two seal analyses are compared to experimental results and to the predictions of Nelson's analysis. The comparisons are for smooth-rotor seals with smooth and honeycomb stators. The comparisons show that the analysis which uses empirical entrance and exit region shear stress models predicts the static and stability characteristics of annular gas seals better than the other analyses. The analyses predict direct stiffness poorly.

Elrod, David Alan↗
NASA NTRS2013

Simple Sensitivity Analysis for Orion Guidance Navigation and Control

The performance of Orion flight software, especially its GNC software, is being analyzed by running Monte Carlo simulations of Orion spacecraft flights. The simulated performance is analyzed for conformance with flight requirements, expressed as performance constraints. Flight requirements include guidance (e.g. touchdown distance from target) and control (e.g., control saturation) as well as performance (e.g., heat load constraints). The Monte Carlo simulations disperse hundreds of simulation input variables, for everything from mass properties to date of launch. We describe in this paper a sensitivity analysis tool ("Critical Factors Tool" or CFT) developed to find the input variables or pairs of variables which by themselves significantly influence satisfaction of requirements or significantly affect key performance metrics (e.g., touchdown distance from target). Knowing these factors can inform robustness analysis, can inform where engineering resources are most needed, and could even affect operations. The contributions of this paper include the introduction of novel sensitivity measures, such as estimating success probability, and a technique for determining whether pairs of factors are interacting dependently or independently. The tool found that input variables such as moments, mass, thrust dispersions, and date of launch were found to be significant factors for success of various requirements. Examples are shown in this paper as well as a summary and physics discussion of EFT-1 driving factors that the tool found.

Pressburger, Tom↗
DOE OSTI2021

Analysis Report for Determination of pH Correction Factors for Brines under AP-157 Rev.1

This Analysis Report (AR) documents the determination of pH correction factors for the observed pH readings. The correction factor converts the observed pH reading recorded from the brines used in geochemical studies in support of the Waste Isolation Pilot Plant (WIPP) to a corrected pH value. The data analysis in this AR falls under AP-157 Rev. 1 Analysis Plan for Determination of pH Correction Factors in Brines (Kirkes et al, 2021). Measurement of pH in some solutions can be challenging due to numerous factors such as high ionic strength, elevated or lowered temperature, complex matrix composition, etc. (Knauss et al., 1990; and Rai et al., 1995). The measured pH can be corrected by applying the correction factor, empirically obtained from a specific test solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Factors Influencing Electric Bike Share Ridership: Analysis of Park City, Utah

In recent years, bike share programs have become more popular as they contribute to the move toward sustainable mobility in cities. Electric bike sharing, however, remains in the early stages of development. In contrast to traditional bikes, electric bicycles (e-bikes) provide an extra boost via an electric pedal-assist motor, thereby making it much easier to travel around a city with a hilly terrain, such as Park City, Utah. The Summit Bike Share system in Park City is the nation’s first fully electric bike share system (e-BSS). Based on an analysis of historical trip data of Summit Bike Share, this paper presents the system’s performance experience and evaluates user characteristics and travel behavior. A Poisson regression analysis is performed to investigate the factors that influence the e-bike share usage of this e-BSS. The regression results reveal that weather factors, including temperature and wind speed, significantly affect e-bike share usage. It was also found that weekends, summer months, high population density, proximity to public transit centers, recreational centers, and bike trails positively affect the demand for e-bikes. The findings of this paper can help the operators of Summit Bike Share to better understand their users and their e-BSS, while also providing a guide for other e-bike projects currently in the planning stages.

Engineering↗
NASA NTRS1993

Orthopyroxenes as recorders of diogenite petrogenesis: Major and minor element systematics

As a part of our research to better understand magmatic processes in the Eucrite Parent Body, we have initiated an ambitious program of study of major, minor and trace elements in orthopyroxene from diogenites. This paper reports preliminary results for major and minor elements in orthopyroxenes for a suite of 13 diogenites: Aioun El Atrouss, ALH 84001, ALH A 77256, EET 87530, Ellemeet, Garland, Ibbenburen, Johnstown, Manegoan, peckelsheim, Roda, Shalka, and Tatahouine. A companion paper by Shearer et al. reports new trace element data for ALH 84001, ALH A 77256, Ibbenburen, and Tatahouine. We have presently collected over 800 high quality pyroxene microprobe analyses for Si, Al, Ca, Na, Mn, Fe, Mg, Cr, and Ti. The chemical systematics observed for these orthopyroxenes reflect original magmatic mineral/melt partitioning plus later trapped liquid/mineral equilibration, subsolids, exsolution, and mineral/mineral metamorphic reactions. We have therefore avoided, at this point, any attempt to use statistical analysis to group (e.g. factor or cluster analysis) these orthopyroxenes chemically.

Papike, J. J.↗
NASA NTRS2016

Statistical Analysis of Instantaneous Frequency Scaling Factor as Derived From Optical Disdrometer Measurements At KQ Bands

The rain rate data and statistics of a location are often used in conjunction with models to predict rain attenuation. However, the true attenuation is a function not only of rain rate, but also of the drop size distribution (DSD). Generally, models utilize an average drop size distribution (Laws and Parsons or Marshall and Palmer. However, individual rain events may deviate from these models significantly if their DSD is not well approximated by the average. Therefore, characterizing the relationship between the DSD and attenuation is valuable in improving modeled predictions of rain attenuation statistics. The DSD may also be used to derive the instantaneous frequency scaling factor and thus validate frequency scaling models. Since June of 2014, NASA Glenn Research Center (GRC) and the Politecnico di Milano (POLIMI) have jointly conducted a propagation study in Milan, Italy utilizing the 20 and 40 GHz beacon signals of the Alphasat TDP#5 Aldo Paraboni payload. The Ka- and Q-band beacon receivers provide a direct measurement of the signal attenuation while concurrent weather instrumentation provides measurements of the atmospheric conditions at the receiver. Among these instruments is a Thies Clima Laser Precipitation Monitor (optical disdrometer) which yields droplet size distributions (DSD); this DSD information can be used to derive a scaling factor that scales the measured 20 GHz data to expected 40 GHz attenuation. Given the capability to both predict and directly observe 40 GHz attenuation, this site is uniquely situated to assess and characterize such predictions. Previous work using this data has examined the relationship between the measured drop-size distribution and the measured attenuation of the link]. The focus of this paper now turns to a deeper analysis of the scaling factor, including the prediction error as a function of attenuation level, correlation between the scaling factor and the rain rate, and the temporal variability of the drop size distribution both within a given rain event and across different varieties of rain events. Index Terms-drop size distribution, frequency scaling, propagation losses, radiowave propagation.

Statistics↗