Search NASA⌕ Search

SEARCH · Search NASA

Results for “Process parameters”

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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Simplified Vicarious Radiometric Calibration

A measurement-based radiance estimation approach for vicarious radiometric calibration of spaceborne multispectral remote sensing systems has been developed. This simplified process eliminates the use of radiative transfer codes and reduces the number of atmospheric assumptions required to perform sensor calibrations. Like prior approaches, the simplified method involves the collection of ground truth data coincident with the overpass of the remote sensing system being calibrated, but this approach differs from the prior techniques in both the nature of the data collected and the manner in which the data are processed. In traditional vicarious radiometric calibration, ground truth data are gathered using ground-viewing spectroradiometers and one or more sun photometer( s), among other instruments, located at a ground target area. The measured data from the ground-based instruments are used in radiative transfer models to estimate the top-of-atmosphere (TOA) target radiances at the time of satellite overpass. These TOA radiances are compared with the satellite sensor readings to radiometrically calibrate the sensor. Traditional vicarious radiometric calibration methods require that an atmospheric model be defined such that the ground-based observations of solar transmission and diffuse-to-global ratios are in close agreement with the radiative transfer code estimation of these parameters. This process is labor-intensive and complex, and can be prone to errors. The errors can be compounded because of approximations in the model and inaccurate assumptions about the radiative coupling between the atmosphere and the terrain. The errors can increase the uncertainty of the TOA radiance estimates used to perform the radiometric calibration. In comparison, the simplified approach does not use atmospheric radiative transfer models and involves fewer assumptions concerning the radiative transfer properties of the atmosphere. This new technique uses two neighboring uniform ground target areas having different reflectance values. The target areas can be natural or artificial and must be large enough to minimize adjacent-pixel contamination effects. The radiative coupling between the atmosphere and the terrain needs to be approximately the same for the two targets. This condition can be met for relatively uniform backgrounds when the distance between the targets is within a few hundred meters. For each target area, the radiance leaving the ground in the direction of the satellite is measured with a radiometrically calibrated spectroradiometer. Using the radiance measurements from the two targets, atmospheric adjacency and atmospheric scattering effects can be subtracted, thereby eliminating many assumptions about the atmosphere and the radiative interaction between the atmosphere and the terrain. In addition, the radiometrically calibrated spectroradiometer can be used with a known reflectance target to estimate atmospheric transmission and diffuse- to-global ratios without the need for ancillary sun photometers. Several comparisons between the simplified method and traditional techniques were found to agree within a few percent. Hence, the simplified method reduces the overall complexity of performing vicarious calibrations and can serve as a method for validating traditional radiative transfer models

Stanley, Thomas↗
DOE OSTI2020

Predicting the influence of particle size on the glass transition temperature and viscosity of secondary organic material

Abstract Atmospheric aerosols can assume liquid, amorphous semi-solid or glassy, and crystalline phase states. Particle phase state plays a critical role in understanding and predicting aerosol impacts on human health, visibility, cloud formation, and climate. Melting point depression increases with decreasing particle diameter and is predicted by the Gibbs–Thompson relationship. This work reviews existing data on the melting point depression to constrain a simple parameterization of the process. The parameter $$\xi $$ ξ describes the degree to which particle size lowers the melting point and is found to vary between 300 and 1800 K nm for a wide range of particle compositions. The parameterization is used together with existing frameworks for modeling the temperature and RH dependence of viscosity to predict the influence of particle size on the glass transition temperature and viscosity of secondary organic aerosol formed from the oxidation of $$\alpha $$ α -pinene. Literature data are broadly consistent with the predictions. The model predicts a sharp decrease in viscosity for particles less than 100 nm in diameter. It is computationally efficient and suitable for inclusion in models to evaluate the potential influence of the phase change on atmospheric processes. New experimental data of the size-dependence of particle viscosity for atmospheric aerosol mimics are needed to thoroughly validate the predictions.

36 MATERIALS SCIENCE↗
NASA NTRS2021

The Use of Astronomy VLBA Campaign MOJAVE for Geodesy

We investigated the suitability of the astronomical 15 GHz VLBA observing program MOJAVE-5 for estimation of geodetic parameters, such as station coordinates and Earth orientation parameters. We processed contemporary geodetic dual-band RV and CN experiments observed at 2.3 GHz and 8.6 GHz starting on September 2016 through July 2020 as reference dataset. We showed that the baseline length repeatability from MOJAVE-5 experiments is only a factor of 1.5 greater than from the dedicated geodetic dataset and still below 1 ppb. The wrms of the difference of estimated EOP with respect to the reference IERS C04 time series are a factor of 1.3 to 1.8 worse. We isolated three major differences between the datasets in terms their possible impact on the geodetic results, i.e. the scheduling approach, treatment of the ionospheric delay, and selection of target radio sources. We showed that the major factor causing discrepancies in the estimated geodetic parameters is the different scheduling approach of the datasets. We conclude that systematic errors in MOJAVE-5 dataset are low enough for these data to be used as an excellent testbed for further investigations on the radio source structure effects in geodesy and astrometry.

Hana Krasna↗
NASA NTRS1974

Evaluation of importance of lateral acceleration derivatives in extraction of lateral-directional derivatives at high angles of attack

A theoretical investigation was conducted to determine the importance of the lateral acceleration (beta) derivatives in the extraction of lateral-directional stability derivatives for swept wing airplanes at high angles of attack. Representative values of lateral acceleration derivatives in yaw and roll (Cn beta and Cl beta) were used in a computer program to generate representative flight motions at several angles of attack and altitudes. The computer-generated motions were then subjected to a parameter identification process based on a modified Newton-Raphson method. Two identification techniques were evaluated, one which included the beta derivatives and one which neglected them. The results of the study indicate that omission of the beta derivatives from mathematical models used in the derivative-extraction techniques can produce erroneous values for the lateral-directional stability derivatives particularly at high angles of attack, where the beta derivatives are large. The largest errors occur in the dynamic derivatives, but large errors may also occur in the static derivatives for cases in which the beta derivatives have large effects on the flight motions of the airplane. In addition, the resulting identified mathematical models provide poor motion prediction as well as erroneous predictions of dynamic modal characteristics. These results strongly indicate that the effects of beta derivatives should be considered in any attempt to extract lateral-directional aerodynamic parameters at high angles of attack.

Nguyen, L. T.↗
NASA NTRS2016

High Temperature Thermoplastic Additive Manufacturing Using Low-Cost, Open-Source Hardware

Additive manufacturing (or 3D printing) via Fused Filament Fabrication (FFF), also known as Fused Deposition Modeling (FDM), is a process where material is placed in specific locations layer-by-layer to create a complete part. Printers designed for FFF build parts by extruding a thermoplastic filament from a nozzle in a predetermined path. Originally developed for commercial printers, 3D printing via FFF has become accessible to a much larger community of users since the introduction of Reprap printers. These low-cost, desktop machines are typically used to print prototype parts or novelty items. As the adoption of desktop sized 3D printers broadens, there is increased demand for these machines to produce functional parts that can withstand harsher conditions such as high temperature and mechanical loads. Materials meeting these requirements tend to possess better mechanical properties and higher glass transition temperatures (Tg), thus requiring printers with high temperature printing capability. This report outlines the problems and solutions, and includes a detailed description of the machine design, printing parameters, and processes specific to high temperature thermoplastic 3D printing.

Gardner, John M.↗
DOE OSTI2021

Effect of hatch spacing and laser power on microstructure, texture, and thermomechanical properties of laser powder bed fusion (L-PBF) additively manufactured NiTi

This study systematically evaluates the effects of laser powder bed fusion additive manufacturing (L-PBF-AM) parameters (hatch spacing and laser power) on the thermomechanical behavior and microstructure of Ni 50.8 Ti 49.2 shape memory alloy. The samples were fabricated with hatch spacings from 40 to 240 µm and laser powers of 50 and 100 W at a constant scanning speed of 125 mm/s, resulting in parts with volumetric energy density levels from 55 to 666 J/mm 3 and two sets of linear energy densities of 0.4 and 0.8 J/mm. The results showed a reduced melt pool size and discontinuity of scan tracks with decreased laser power. Additionally, the porosity level was increased with larger hatch spacing and lower laser power. More notably, the transformation temperatures increased, and the critical stress, recoverable strain, and functional stability of samples improved with lower hatch spacing, where the recovery ratio of up to 90% was observed, regardless of the employed laser power. This study also discussed the relationship between the fabrication process and texture formation in the L-PBF-AM process. In conclusion, the advantage of L-PBF-AM was revealed in tailoring the microstructure from highly textured samples in [1 1 1] or [0 0 1] direction when hatch spacing lower than laser beam focused was employed, to the appearance of equiaxed solidification front with island grains and random orientations.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

COSPAR Workshop Series on Refining Planetary Protection Requirements for Human Missions to Mars

COSPAR and its space agency partners are supporting a multi-year stepwise process devel-oping needed approaches to address planetary protection requirements for human missions beyond Earth orbit. The objective is to support incremental development from the current qualitative COSPAR planetary protection “Principles and Guidelines for Human Missions to Mars” to quantitative implementable planetary protection requirements for such future mis-sions. The workshops and meetings in this series have involved participants from NASA, ESA, JAXA and other national space agencies, as well as the scientific/technical community, and commercial/private enterprise stakeholders, based around three main topic areas: Microbial and Human Health Monitoring; Spacecraft Technology and Operations, and; Natural Trans-port of Contamination at Mars. This presentation provides a status update on the findings of the COSPAR Meetings on this topic to date. First, the identification and prioritization of knowledge gaps will be summarized. Next, where a knowledge gap is to be addressed by new measurements, example descriptions of measurements needed to close the knowledge gaps (and instruments necessary to make those measurements) will be discussed. Where the knowledge gaps closure is based on Agency policy decisions, the scope of the decision-making parameters and process will be described. Lastly, the presentation will consider how the findings of the study series can be integrated into current and future space agency and COSPAR activities.

J. Andy Spry↗
DOE OSTI2018

Binary interaction parameters from reacting mixture data. Supercritical biodiesel process with CO 2 as cosolvent

A method is presented for the calculation of binary interaction parameters from reacting mixture data. The process studied is the supercritical methanol transesterification of triolein with CO 2 as cosolvent. The reaction proceeds through 3 reversible reactions in series, on a solid catalyst (Nafion(R) SAC-13), for which the kinetics is known. To describe the reactor performance, the kinetic constants and the binary interaction parameters for the Peng-Robinson equation of state, are necessary, and were included in the reactor model. Previously published view-cell observations and thermodynamic calculations indicate that no condensation occurs in the reactor. Kinetic and thermodynamic parameters were determined by a global optimisation procedure. From the rate constants obtained, the process exhibits some reversibility, despite the excess of methanol used. Our methodology allows to obtain the binary interaction coefficients for the intermediate reaction species (dioleins and monooleins) that were unavailable so far. The method is sensitive to the errors in the measured concentrations.

09 BIOMASS FUELS↗
DOE OSTI2020

Achieving High Alignment of Conjugated Polymers by Controlled Dip-Coating

Realizing high polymer chain orientation and ordered thin-film microstructures is beneficial for efficient charge transport of conjugated polymers. However, achieving a high alignment degree remains a challenge due to the sensitive nature of polymers to the processing conditions. By simply varying concentrations during a dip-coating method, the component of polymer aggregates that adopt the planar backbones is enlarged and the ensuing assembly process is promoted. Herein, highly oriented polymer thin films of an isoindigo-based conjugated polymer (PII-2T) are prepared to enhance polymer orientation resulting in a drastic booming in carrier mobilities of organic field-effect-transistors (OFETs). The maximum mobility from aligned polymer films increases by up to 8.3 cm 2 V -1 s -1 , which is tenfold beyond the value evaluated from the unaligned direction or traditional spin-coated samples. The enhanced orientation can also reduce the adverse effects of the contact resistance and facilitate charge transport in transistors. This work demonstrates that the highly aligned conjugated polymer films can be approached by the dip-coating method while offers a latent cornerstone toward understanding the critical role of processing-related parameters in determining morphology of solution-coated thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Amorphization of Pseudocapacitive T−Nb 2 O 5 Accelerates Lithium Diffusivity as Revealed Using Tunable Isomorphic Architectures

Abstract Intercalation pseudocapacitance can combine capacitor‐like power densities with battery‐like energy densities. Such surface‐limited behavior requires rapid diffusion where amorphization can increase solid‐state diffusivity. Here intercalation pseudocapacitive materials with tailored extents of amorphization in T‐Nb 2 O 5 are first reported. Amorphization was characterized with WAXS, XPS, XAFS, and EPR which suggested a peroxide‐rich (O 2 2− ) surface that was consistent with DFT predictions. A series of tunable isomorphic architectures enabled comparisons while independently varying transport parameters. Through process of elimination, solid‐state lithium diffusion was identified as the dominant diffusive‐constraint dictating the maximum voltage sweep rate for surface‐limited kinetics ( v SLT ), termed the Surface‐Limited Threshold (SLT). The v SLT increased with amorphization however stable cycling required crystalline T‐Nb 2 O 5 . A current‐response model using series‐impedances well‐matched these observations. This perspective revealed that amorphization of T‐Nb 2 O 5 enhanced solid‐state diffusion by 12.2 % and increased surface‐limitations by 17.0 % (stable samples). This approach enabled retaining 95 % lithiation capacity at ∼800 mV s −1 (1,600 C‐rate equivalent).

25 ENERGY STORAGE↗
DOE OSTI2023

Sensitivity analysis of an automated fault detection algorithm for residential air-conditioning systems

The state of the art of fault detection and diagnosis (FDD) for residential air-conditioning systems is expensive and not yet amenable to widespread implementation. FDD for homes can significantly reduce utility costs, and increase the lifespan of the equipment. The cost barriers currently, however, make FDD for homes economically unviable for large scale implementation. In prior work, we offered a solution to reduce FDD costs by proposing an automated fault detection algorithm to serve as a screening step before more expensive FDD tests can be conducted. The algorithm uses only the home thermostat and local weather information to identify thermodynamic parameters and detect high-impact air-conditioning faults, including those that occur during equipment installation. We had tested the algorithm on a single EnergyPlus™ model of a home in Orlando, Florida. The thermodynamic parameter identification process is highly nonconvex involving several local optimal solutions. In this paper we propose a novel method to select the best model for fault detection from among the list of local optimal solutions to make the algorithm more robust to homes of different construction, without which the fault detection process would be infeasible. Another unique contribution of the paper is implementing the solution on real-world data. We also bring the algorithm closer to market by testing it on real-world data. We implement the algorithm on data obtained from experiments conducted by the Florida Solar Energy Center (FSEC) on a laboratory home equipped with a heat pump where faults were intentionally added for a period of seven months. The algorithm successfully detected an undercharge fault with 70.6% accuracy, concurrent duct leakage and undercharge faults with 85.2% accuracy, and duct leakage faults with 69.1% accuracy. A sensitivity analysis is also performed on EnergyPlus models of nine types of homes that vary in construction to demonstrate the robustness of the algorithm. Finally, the algorithm achieves an average accuracy of 71% for no-fault condition, 77% for 40% undercharge fault, and 76% for duct-leak fault.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Microwave-enhanced catalytic ammonia synthesis under moderate pressure and temperature

In this study, an alternative approach based on microwave-enhanced ammonia synthesis for Haber-Bosch process was carried out under moderate pressure of 0.1–0.65 MPa and temperature range of 280–400 °C over a stable CsRu/CeO 2 catalyst. The ammonia production rate is significantly improved under microwave conditions. At 0.65 MPa and 320 °C, maximum ammonia production rate was achieved at H 2 /N 2 ratio of 1/1. Stable performance was obtained in a 6-cycles of startup-shutdown operation for cumulative on-line time of 80 h. The work demonstrates the potential of microwave catalytic technology for the distributed ammonia synthesis using renewable power having intermittent nature of energy supply.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Methodology for physics-informed generation of synthetic neutron time-of-flight measurement data

Accurate neutron cross section data are a vital input to the simulation of nuclear systems for a wide range of applications from energy production to national security. The evaluation of experimental data is a key step in producing accurate cross sections. There is a widely recognized lack of reproducibility in the evaluation process due to its artisanal nature and therefore there is a call for improvement within the nuclear data community. This can be realized by automating/standardizing viable parts of the process, namely, parameter estimation by fitting theoretical models to experimental data. This automation effort could greatly benefit from a synthetic data resource. This work leverages problem-specific physics, Monte Carlo sampling, and a general methodology for data synthesis to generate unlimited, labelled experimental cross-section data that is statistically indistinguishable to the observed data. Heuristic and, where applicable, rigorous statistical comparisons to observed data support this claim. The demonstration is based on/limited to transmission measurements at Rensselaer Polytechnic Institute (RPI) and energy-differential cross sections in the resolved resonance region (RRR). An open-source software is published alongside this article that executes the complete methodology to produce high-utility synthetic datasets. The goal of this work is to provide an approach and corresponding tool that will allow the evaluation community to begin exploring more data-driven, ML-based solutions to long-standing challenges in the field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

An inverse approach to solving zone air infiltration rate and people count using indoor environmental sensor data

Physics-based simulation of energy use in buildings is typically widely used in building design and performance rating, controls design and operations. However, various challenges exist in the modeling process. Model parameters such as people count and air infiltration rate are usually highly uncertain, yet they have significant impacts on the simulation accuracy. With the increasing availability and affordability of sensors and meters in buildings, a large amount of measured data has been collected including indoor environmental parameters, such as room air dry-bulb temperature, humidity ratio, and CO 2 concentration levels. Fusing these sensor data with traditional energy modeling poses new opportunities to improve simulation accuracy. This study develops a set of physics-based inverse algorithms which can solve the highly uncertain and hard-to-measure building parameters such as zone-level people count and air infiltration rate. A simulation-based case study is conducted to verify the inverse algorithms implemented in EnergyPlus covering various sensor measurement scenarios and different modeling use cases. The developed inverse models can solve the zone people count and air infiltration at sub-hourly resolution using the measured zone air temperature, humidity and/or CO 2 concentration given other easy-to-measure model parameters are known.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Characterization of CO 2 storage and enhanced oil recovery in residual oil zones

Residual oil zones (ROZs) are reservoirs in which oil is swept over geologic time period and exists at residual saturation. The oil in such reservoirs cannot be commercially exploited using conventional oil recovery methods as the oil exists at residual oil saturation. Instead, enhanced oil recovery methods such as CO 2 injection are required. Recently, ROZs have been increasingly studied as potential CO 2 storage targets. In spite of increased interest in ROZs, there are significant gaps in the knowledge of parameters and processes that impact CO 2 storage and oil recovery. In this work, we identify key geologic and operational characteristics that affect CO 2 storage capacity and oil recovery potential by performing Monte Carlo simulations and sensitivity analysis. In addition to CO 2 storage capacity, we also characterize the long-term CO 2 fate in ROZs. The distinction of CO 2 storage in ROZs from conventional oil reservoirs and saline aquifers are also characterized. Furthermore, predictive models based on machine learning techniques are developed to estimate CO 2 storage and oil production potentials for ROZs. The applicability of the predictive models is demonstrated for five ROZs in the Permian Basin.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Fatigue of additive manufactured Ti-6Al-4V, Part I: The effects of powder feedstock, manufacturing, and post-process conditions on the resulting microstructure and defects

Additive manufacturing provides an appealing means to process titanium alloy parts with new levels of conformability, complexity, and weight reduction. However, due to the heating/cooling rates and heat transfer associated with directed energy source material processing, the as-built AM parts contain unique material and microstructural features. In order to confidently manufacture fatigue critical additive manufactured (AM) Ti-6Al-4V parts, a better understanding of the interrelationships between powder feedstock, AM processes, structure of the processed parts, their resulting mechanical properties, and their performance under realistic loadings is necessary. Part I of this two-part collection focuses on the powder-process-structure relationships and how powder feedstock, manufacturing, and post-processing conditions can affect the microstructure and defect features that ultimately contribute to the fatigue performance of Ti-6Al-4V parts. The material and physical phenomena inherent to the AM process of Ti-6Al-4V are discussed in detail and related to the phase composition/structure, grain morphology, surface characteristics, defect size/distribution, and post-process treatments available for AM parts. This investigation is the foundation for the structure-performance relationships that will be covered in detail in Part II.

36 MATERIALS SCIENCE↗