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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Limitation on two-photon temporal correlation

We show theoretically that two-photon correlation time for a biphoton, a pair of entangled photons generated in the process of parametric down conversion, is limited by the inverse frequency width of the single-photon spectrum, which is limited by the dispersion of the nonlinear material used for the pair generation. The dispersion is determined by the transparency window of the material, which provides the ultimate limitation for the twophoton correlation time. We discuss several experimental approaches enabling realization of such a limiting case.

Maleki, Lute↗
NASA NTRS2004

Recent Advances in Synthesis and Characterization of SWCNTs Produced by Laser Oven Process

Results from the parametric study of the two-laser oven process indicated possible improvements with flow conditions and laser characteristics. Higher flow rates, lower operating pressures coupled with changes in flow tube material are found to improve the nanotube yields. The collected nanotube material is analyzed using a combination of characterization techniques including SEM, TEM, TGA, Raman and UV-VIS-NIR to estimate the purity of the samples. In-situ diagnostics of the laser oven process is now extended to include the surface temperature of the target material. Spectral emission from the target surface is compared with black body type emission to estimate the temperature. The surface temperature seemed to correlate well with the ablation rate as well as the quality of the SWCNTs. Recent changes in improving the production rate by rastering the target and using cw laser will be presented.

Aepalli, Sivaram↗
NASA NTRS2004

Recent Advances in Synthesis and Characterization of SWCNTs produced by laser oven process

Results from the parametric study of the two-laser oven process indicated possible improvements with flow conditions and laser characteristics (ref. 1). Higher flow rates, lower operating pressures coupled with changes in flow tube material are found to improve the nanotube yields. The collected nanotube material is analyzed using a combination of characterization techniques including SEM, TEM, TGA, Raman and UV-VIS-NIR to estimate the purity of the samples. Insitu diagnostics of the laser oven process is now extended to include the surface temperature of the target material. Spectral emission from the target surface is compared with black body type emission to estimate the temperature. The surface temperature seemed to correlate well with the ablation rate as well as the quality of the SWCNTs. Recent changes in improving the production rate by rastering the target and using cw laser will be presented.

Arepalli, Sivaram↗
DOE OSTI2023

Parametric study of an acid baking process for rare earth element recovery from a bituminous-coal source

Acid baking treatment is widely used to extract rare earth elements (REEs) from refractory rare earth bearing minerals such as monazite and xenotime. Since these REE minerals have been identified in coal-based sources, a parametric study was conducted to evaluate the impact and optimize the parametric values associated with the acid-baking process when treating a bituminous coal source. The parameters studied using a three-level statistical experimental program were acid baking time, acid solution concentration, baking temperature, and acid solution-to-solids ratio and each were found to significantly impact REE and contaminant element recovery. An increase in baking temperature up to around 250°C improved the light and heavy REE recovery values by more than 50 absolute percentage points relative to performances achieved when direct leaching. Acid baking was needed to dehydroxylate the clays and liberate the REE minerals, which allowed access for the acid to solubilize the REEs. Acid concentration of the solution used for acid baking was studied as a means of minimizing the amount of acid needed to achieve a target REE recovery. However, thermo-gravimetric and differential scanning calorimetry analysis (TGA-DSC) of sulfuric acid under oxidizing atmosphere revealed that the addition of water decreased the evaporation temperature, which explains the lower REE recovery values obtained when using lower acid concentrations. Using pure sulfuric acid at an acid-to-solid ratio of 0.8:1 resulted in recovery values of around 70% for both LREEs and HREEs. The decomposition reaction time was relatively quick with 65% of the TREEs recovered within the first 10 minutes. Water leaching experiments performed on the acid-baked products under a temperature of 25°C instead of 75°C revealed an increase in REE recovery by 10 absolute percentage points, which was likely due to the high solubility of REE-sulfates at room temperatures.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Determining processing behaviour of pure Cu in laser powder bed fusion using direct micro-calorimetry

We report copper is challenging to process by laser powder bed fusion (LPBF) given its high reflectivity at common infrared laser diode wavelengths and high thermal conductivity. Successful deposition of copper in a predictable and repeatable fashion relies on understanding the development of the keyhole melting regime, as well as heating, melting, boiling and vapour formation behaviour when interacting with a laser beam within an LPBF environment. In this study, in situ optical absorptivity measurements are used to clarify the complex physics of the laser material interaction. Absorptivity of laser energy is measured using direct micro-calorimetry and compared to melt pool depth in correlation to processing parameters. The measured absorptivity for a 100 μm layer thickness of powder was found to be approximately four times higher than that of the bare polished discs. It was also shown that high laser power above 500 W and scan speed up to 150 mm/s are appropriate for effective melting of the powder layer, with these parameters overcoming the threshold required to achieve keyhole melting. This is explained by multiple reflections withing the powder particles and the lower thermal conductivity of packed powder in comparison to bare discs. Melt pool formation was found to be highly unstable and an explosive behavior was observed when in the keyhole regime, caused by high fluctuations in absorptivity values. This work demonstrates calorimetry can be used to monitor melting behaviour in a real-time fashion during processing for this challenging to process material, thereby avoiding unnecessary parametric optimisation. In addition, the parametric window for optimum processing revealed here can inform future work.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A parametric approach to identify synergistic domains of process intensification for reactive separation

Process intensification aims to combine multiple tasks within multi-functional units to drastically improve economic, energy or sustainability metrics of a chemical process. Limited work exists to systematically identify the synergistic domains where intensification outperforms its nonintensified counterpart. In this work, we computationally derive the synergistic domains of a reactive separation system. Specifically, we first postulate general models for both intensified and nonintensified systems. We use these models to generate data to train a ReLU-type artifical neural network (ANN). Further, the trained ReLU-NN model is formulated as a multi-parametric mixed-integer linear program (mp-MILP), and the critical regions of this mp-MILP define the synergistic feasible domains of intensification. We have derived these synergistic domains of vapor–liquid equilibrium (VLE)-based reactive separation for several industrial applications. These synergistic domains enable quick screening of properties that favor intensification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Out-of-distribution detection with non-parametric density estimation for models predicting processing history of uranium ore concentrates

The rapid advancement in machine learning (ML) and computer vision (CV) coincides with the growth of interest in deploying these ML/CV models in numerous fields from medicine to social science. Similar to those areas, we have witnessed a great number of works in materials science employing ML/CV models – neural networks in particular – in their studies in recent years. These models have proven to obtain accurate performance in various tasks. However, these models struggle to attain a similar performance when encountering test samples coming from a distribution that is different from the training set. More importantly, they fail without providing any warning to the users. Therefore, we propose a framework for detecting out-of-distribution (OOD) samples to alert users when a human intervention might be necessary in this work. Specifically, we explore the use of a non-parametric density estimation method to detect OOD samples. Here, we assess OOD detection capability of the proposed framework on ML models developed for categorizing precipitation routes of U 3 O 8 when encountering OOD datasets that contain samples (1) undergone different imaging acquisition process, (2) undergone different material synthesis process, and (3) different materials than ID set. Through those experiments, we achieve an average area under the receiver operating characteristic (AUROC) of at least 91% on average in detecting OOD samples. With minimal overhead cost and superior performance, the proposed framework enables a reliable and safe system when deploying in real-world scenarios.

Convolutional neural networks↗
DOE OSTI2024

Stimulated emission tomography for efficient characterization of spatial entanglement

Stimulated-emission tomography (SET) is an excellent tool for characterizing the process of spontaneous parametric down conversion (SPDC), which is commonly used to create pairs of entangled photons for use in quantum information protocols. The use of stimulated emission increases the average number of detected photons by several orders of magnitude compared to the spontaneous process. In a SET measurement, the parametric down conversion is seeded by an intense signal field prepared with specified mode properties rather than by broadband multimodal vacuum fluctuations, as is the case for the spontaneous process. The SET process generates an intense idler field in a mode that is the complex conjugate to the signal mode. In this work we use SET to estimate the joint spatial mode distribution (JSMD) in the Laguerre-Gaussian (LG) basis of the two photons of an entangled photon pair. The pair is produced by parametric down conversion in a beta barium borate (BBO) crystal with type-II phase matching pumped at a wavelength of 405 nm along with a 780 nm seed signal beam prepared in a variety of LG modes to generate an 842 nm idler beam of which the spatial mode distribution is measured. We observe strong idler production and good agreement with the theoretical prediction of its spatial mode distribution. Our experimental procedure should enable the efficient determination of the photon-pair wavefunctions produced by low-brightness SPDC sources and the characterization of high-dimensional entangled-photon pairs. Published by the American Physical Society 2024

Xu, Yang (ORCID:0009000954547320)↗
DOE OSTI2022

Process-oriented stochastic perturbations applied to the parametrization of turbulence and shallow convection for ensemble prediction

Weather forecasting nowadays often requires some estimation of uncertainties associated with the output of meteorological models, in order to better inform decision making, especially in the context of intense weather events. Ensemble prediction systems provide such information through sets of possible scenarios which are designed to represent various uncertainty sources, including model uncertainties. A wide variety of methods have been proposed to estimate model uncertainties, among which perturbation methods targeting uncertain processes are a promising research field. Here, we focus on the representation of small-scale variability by process-oriented perturbation schemes applied to two key physical processes, namely turbulence and shallow convection. The perturbations are applied to a single-column version of the convection-permitting AROME model, in three idealized boundary-layer cases. Large-eddy simulations (LESs) of the same cases serve as a reference for the subgrid variability that has to be represented, and the results are also compared to those given by the Stochastically Perturbed Parametrization Tendencies (SPPT) method, which is a method commonly used by weather forecast centres to represent model uncertainty. The spread produced by our process-oriented perturbations of turbulence and shallow convection does not represent all the small-scale variability implied by the LESs for temperature and humidity. However, it is of a similar order of magnitude for the wind, thanks to perturbations generated by the stochastic turbulence scheme. The dispersion is structurally different from what is obtained with SPPT. It is non-negligible in the lower levels, where SPPT perturbations are usually suppressed because of numerical instabilities, indicating a possible complementarity between the schemes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Elliptic Volume Grid Generation for Viscous CFD Parametric Design Studies

This paper presents a robust method for the generation of zonal volume grids of design parametrics for aerodynamic configurations. The process utilizes simple algebraic techniques with parametric splines coupled with elliptic volume grid generation to generate isolated zonal grids for changes in body configuration needed to perform parametric design studies. Speed of the algorithm is maximized through the algebraic methods and reduced number of grid points to be regenerated for each design parametric without sacrificing grid quality and continuity within the volume domain. The method is directly applicable to grid reusability, because it modifies existing ow adapted volume grids and enables the user to restart the CFD solution process with an established flow field. Use of this zonal approach reduces computer usage time to create new volume grids for design parametric studies by an order of magnitude, as compared to current methods which require the regeneration of an entire volume grid. A sample configuration of a proposed Single Stage-to-Orbit Vehicle is used to illustrate an application of this method.

Alter, Stephen J.↗
DOE OSTI2023

Degree-preserving graph dynamics: a versatile process to construct random networks

Real-world networks evolve over time via the addition or removal of vertices and edges. In current network evolution models, vertex degree varies or grows arbitrarily. A recently introduced degree-preserving network growth (DPG) family of models preserves vertex degree, resulting in structures significantly different from and more diverse than previous models. Despite its degree preserving property, the DPG model is able to replicate the output of several well-known real-world network growth models. Simulations showed that many real-world networks can also be constructed from small seed graphs via the DPG process. Here, we start the development of a rigorous mathematical theory underlying the DPG family of network growth models. We prove that the degree sequence of the output of some of the well-known, real-world network growth models can be reconstructed via the DPG process, using proper parametrization. We also show that the general problem of deciding whether a simple graph can be obtained via the DPG process from a small seed (DPG feasibility) is, however, NP-complete. In conclusion, it is an intriguing open problem to uncover whether there is a structural reason behind the DPG-constructability of real-world networks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2000

Parametric Cost Modeling of Space Missions Using the Develop New Projects (DMP) Implementation Process

This paper presents an overview of a parametric cost model that has been built at JPL to estimate costs of future, deep space, robotic science missions. Due to the recent dramatic changes in JPL business practices brought about by an internal reengineering effort known as develop new products (DNP), high-level historic cost data is no longer considered analogous to future missions. Therefore, the historic data is of little value in forecasting costs for projects developed using the DNP process. This has lead to the development of an approach for obtaining expert opinion and also for combining actual data with expert opinion to provide a cost database for future missions. In addition, the DNP cost model has a maximum of objective cost drivers which reduces the likelihood of model input error. Version 2 is now under development which expands the model capabilities, links it more tightly with key design technical parameters, and is grounded in more rigorous statistical techniques. The challenges faced in building this model will be discussed, as well as it's background, development approach, status, validation, and future plans.

Rosenberg, Leigh↗
NASA NTRS2017

Parametric Structural Model for a Mars Entry Concept

This paper outlines the process of developing a parametric model for a vehicle that can withstand Earth launch and Mars entry conditions. This model allows the user to change a variety of parameters ranging from dimensions and meshing to materials and atmospheric entry angles to perform finite element analysis on the model for the specified load cases. While this work focuses on an aeroshell for Earth launch aboard the Space Launch System (SLS) and Mars entry, the model can be applied to different vehicles and destinations. This specific project derived from the need to deliver large payloads to Mars efficiently, safely, and cheaply. Doing so requires minimizing the structural mass of the body as much as possible. The code developed for this project allows for dozens of cases to be run with the single click of a button. The end result of the parametric model gives the user a sense of how the body reacts under different loading cases so that it can be optimized for its purpose. The data are reported in this paper and can provide engineers with a good understanding of the model and valuable information for improving the design of the vehicle. In addition, conclusions show that the frequency analysis drives the design and suggestions are made to reduce the significance of normal modes in the design.

Lane, Brittney M.↗
NASA NTRS1985

The speed of wave-wave interactions in the atmosphere

Resonant wave-wave interactions are considered. Studies of the interaction coefficient show that rapid transfer of wave action can take place in the disjoined parts of the spectrum for three processes, namely: elastic scattering, parametric subharmonic instability and induced diffusion. Of the three processes, the vertical shear plays a role in two. The vertical shear of a moderate scale interacts through elastic scattering to make the spectrum vertically symmetric. On the other hand, the vertical shear of a large scale interacts through induced diffusion and is responsible for diffusion in k sub z space. When interacting with a vertical shear, it is known that the vertical shear acts as a catalyst and is not involved in energy transfer. Consequently, in both elastic scattering and induced diffusion, the vertical shear does not gain or lose energy. Through parametric subharmonic instability the more energetic large-scale waves are feeding energy into moderate and small scale waves of an elevation angle of 60 deg or larger.

Yeh, K. C.↗
NASA NTRS1992

Nondestructive measurement of intensity of optical fields using spontaneous parametric down conversion

Results of nondestructive measurements of intensity (photons per mode) of light from different sources are discussed. The procedure of measurement does not destroy the state of the optical field. The method is based on using the second order nonlinearity of crystal media lacking a center of symmetry and the nonclassical properties of the process of Spontaneous Parametric Down Conversion (SPDC).

Penin, A. N.↗
DOE OSTI2023

Attention-Augmented Parametric Kernel Graph Neural Network (APKGNN) for Node Classification

We present a new graph neural network, the Attention-based Parametric-Kernel augmented Graph Neural Network (APKGNN), developed for node classification tasks. Despite extensive work on modeling multi-faceted relationships between connected nodes of a graph, the effect of attention on edge features mapped to relationships has not yet been analyzed through learning representation. This study derives such an attention vector by first calculating node features corresponding to endpoints of an edge and then aggregating these with extracted local intrinsic patches of a given graph to generate augmented local patch vectors. This process uses a parametric kernel based on Gaussian mixture models (GMMs) to embed local neighborhoods of the graph in local patches. The patch vectors then convolve with the above node features to produce an updated node representation. We show that this new learning representation (APKGNN) achieves higher node classification accuracy on tasks - both standard benchmarks (Cora, PubMed, Citeseer) and new experimental short text corpora where nodes correspond to text documents and words. This implementation of the GNN convolution layer outperforms state-of-the-art (SOTA) algorithms, achieving higher training, validation, and test accuracy by a significant margin on three standard benchmark data sets under both SOTA experimental settings and those for new testbeds.

Bose, Avishek↗
NASA NTRS1987

Effect of wave localization on plasma instabilities

The Anderson model of wave localization in random media is involved to study the effect of solar wind density turbulence on plasma processes associated with the solar type III radio burst. ISEE-3 satellite data indicate that a possible model for the type III process is the parametric decay of Langmuir waves excited by solar flare electron streams into daughter electromagnetic and ion acoustic waves. The threshold for this instability, however, is much higher than observed Langmuir wave levels because of rapid wave convection of the transverse electromagnetic daughter wave in the case where the solar wind is assumed homogeneous. Langmuir and transverse waves near critical density satisfy the Ioffe-Reigel criteria for wave localization in the solar wind with observed density fluctuations -1 percent. Numerical simulations of wave propagation in random media confirm the localization length predictions of Escande and Souillard for stationary density fluctations. For mobile density fluctuations localized wave packets spread at the propagation velocity of the density fluctuations rather than the group velocity of the waves. Computer simulations using a linearized hybrid code show that an electron beam will excite localized Langmuir waves in a plasma with density turbulence. An action principle approach is used to develop a theory of non-linear wave processes when waves are localized. A theory of resonant particles diffusion by localized waves is developed to explain the saturation of the beam-plasma instability. It is argued that localization of electromagnetic waves will allow the instability threshold to be exceeded for the parametric decay discussed above.

Levedahl, William Kirk↗