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NASA NTRS1977

Study of the luminosity function for field galaxies

Nine determinations of the luminosity function (LF) for field galaxies are adjusted, analyzed, and compared. Adjustments are made for differences in definitions as well as in assumptions regarding magnitude systems, the Hubble constant, and galactic absorption. Eight of the nine adjusted determinations are found to be in fairly good agreement, and the discrepancy in the ninth is attributed to incompleteness effects. A large-scale normalization of the LF is performed using the method and some integral counts of Gott and Turner (1976); the large-scale mean LF of (mostly field) galaxies is found to be about 2.3 times less than a previously derived 'local' LF. The large-scale luminosity density in space arising from sources within the B(0) isophotes of galaxies is evaluated, and a value of 86 million (H/50) suns per cu Mpc is obtained for a galactic absorption coefficient of 0.25 magnitude. It is noted that the true large-scale luminosity density is probably within a factor of 1.6 of the reported value.

Felten, J. E.↗

NASA NTRS2018

Medical Data Architecture Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.

medical data architecture↗

NASA NTRS2018

Medical Data Architecture (MDA) Project Status

medical data architecture↗

DOE OSTI2024

GraphAide: Advanced Graph-Assisted Query and Reasoning System

Curating knowledge from multiple siloed sources that contain both structured and unstructured data is a major challenge in many real-world applications. Pattern matching and querying represent fundamental tasks in modern data analytics that leverage this curated knowledge. The development of such applications necessitates overcoming several research challenges, including data extraction, named entity recognition, data modeling, and designing query interfaces. Moreover, the explainability of these functionalities is critical for their broader adoption. The emergence of Large Language Models (LLMs) has accelerated the development lifecycle of new capabilities. Nonetheless, there is an ongoing need for domain-specific tools tailored to user activities. The creation of digital assistants has gained considerable traction in recent years, with LLMs offering a promising avenue to develop such assistants utilizing domain-specific knowledge and assumptions. In this context, we introduce an advanced query and reasoning system, GraphAide, which constructs a knowledge graph (KG) from diverse sources and allows to query and reason over the resulting KG. GraphAide harnesses both the KG and LLMs to rapidly develop domain-specific digital assistants. It integrates design patterns from retrieval augmented generation (RAG) and the semantic web to create an agentic LLM application. GraphAide underscores the potential for streamlined and efficient development of specialized digital assistants, thereby enhancing their applicability across various domains.

Purohit, Sumit [BATTELLE (PACIFIC NW LAB)] (ORCID:↗

DOE OSTI2024

SMART Deliverable 6.1.2a: Application of the ORION tool to the IBDP Carbon Storage Site

Forecasting and managing potential induced seismic activity is one of the challenges facing commercialscale geologic carbon sequestration (GCS), as well as other geologic energy extraction and byproduct disposal technologies. Historically, the process to develop robust, science-based forecasts of induced seismicity has required an integrated effort from experts in seismology, geomechanics, and reservoir engineering to manage data, develop and evaluate models of subsurface processes, and to calibrate and interpret the results from a range of models to understand site behavior relative to prescribed standards and in the context of uncertainty in geologic characterization data, forecasting models, and operational scenario uncertainty. The Operational Forecasting of Induced Seismicity (ORION) toolkit is an open-source, observation-based forecasting toolkit that is being co-developed by two U.S. DOE-funded initiatives: the National Risk Assessment Partnership (NRAP) and the Scienceinformed Machine Learning for Accelerating Real Time Decisions in Subsurface Applications (SMART) Initiative. ORION is designed to provide functionality to support decision making about seismic hazard analysis and risk management for GCS stakeholders ranging from the public to site operators to expert seismologists. The tool, which is written as open-source code in the Python programming language, is composed of a desktop graphical user interface (GUI) and an underlying forecasting engine. The forecasting engine uses available reservoir properties, well and fluid injection scenario details, and observed seismic catalog data as inputs to produce a set of temporal and spatio-temporal seismic forecasts.

58 GEOSCIENCES↗

DOE OSTI2024

Quadrature Based Neural Network Learning of Stochastic Hamiltonian Systems

Hamiltonian Neural Networks (HNNs) provide structure-preserving learning of Hamiltonian systems. In this paper, we extend HNNs to structure-preserving inversion of stochastic Hamiltonian systems (SHSs) from observational data. We propose the quadrature-based models according to the integral form of the SHSs’ solutions, where we denoise the loss-by-moment calculations of the solutions. The integral pattern of the models transforms the source of the essential learning error from the discrepancy between the modified Hamiltonian and the true Hamiltonian in the classical HNN models into that between the integrals and their quadrature approximations. This transforms the challenging task of deriving the relation between the modified and the true Hamiltonians from the (stochastic) Hamilton–Jacobi PDEs, into the one that only requires invoking results from the numerical quadrature theory. Meanwhile, denoising via moments calculations gives a simpler data fitting method than, e.g., via probability density fitting, which may imply better generalization ability in certain circumstances. Numerical experiments validate the proposed learning strategy on several concrete Hamiltonian systems. The experimental results show that both the learned Hamiltonian function and the predicted solution of our quadrature-based model are more accurate than that of the corrected symplectic HNN method on a harmonic oscillator, and the three-point Gaussian quadrature-based model produces higher accuracy in long-time prediction than the Kramers–Moyal method and the numerics-informed likelihood method on the stochastic Kubo oscillator as well as other two stochastic systems with non-polynomial Hamiltonian functions. Moreover, the Hamiltonian learning error εH arising from the Gaussian quadrature-based model is lower than that from Simpson’s quadrature-based model. These demonstrate the superiority of our approach in learning accuracy and long-time prediction ability compared to certain existing methods and exhibit its potential to improve learning accuracy via applying precise quadrature formulae.

Mathematics↗

NASA NTRS1990

An integrated approach to system design, reliability, and diagnosis

The requirement for ultradependability of computer systems in future avionics and space applications necessitates a top-down, integrated systems engineering approach for design, implementation, testing, and operation. The functional analyses of hardware and software systems must be combined by models that are flexible enough to represent their interactions and behavior. The information contained in these models must be accessible throughout all phases of the system life cycle in order to maintain consistency and accuracy in design and operational decisions. One approach being taken by researchers at Ames Research Center is the creation of an object-oriented environment that integrates information about system components required in the reliability evaluation with behavioral information useful for diagnostic algorithms. Procedures have been developed at Ames that perform reliability evaluations during design and failure diagnoses during system operation. These procedures utilize information from a central source, structured as object-oriented fault trees. Fault trees were selected because they are a flexible model widely used in aerospace applications and because they give a concise, structured representation of system behavior. The utility of this integrated environment for aerospace applications in light of our experiences during its development and use is described. The techniques for reliability evaluation and failure diagnosis are discussed, and current extensions of the environment and areas requiring further development are summarized.

Patterson-Hine, F. A.↗

NASA NTRS1993

An almost 'perfectly' diffuse, 'perfect' reflector for far-infrared reflectance calibration

Specular and diffuse reflectance measurements made near normal incidence of two very rough, solid aluminum surfaces are presented for the wavelength range from 2.2 to 512 microns. The diffuse measurements made at nonspecular angles by two different detectors indicate that between 33 and 201 microns the reflectance of one surface is nearly Lambertian (isotropic) with a bidirectional reflectance distribution function (BRDF) value within 32 percent of the theoretical value of (1/pi)/sr for a perfectly diffuse, perfect reflector. Photometric reflectance spectra at the specular angle show that between 6.9 and 100 microns the specular BRDF of these surfaces is within 5 percent of the theoretical value of (1/pi)/sr. At longer wavelengths of 235, 320, and 512 microns the specular reflectance rapidly departs from that of a perfectly diffuse, perfect reflector. The two samples studied have rms surface roughnesses of 44 and 60 microns. A durable metal surface with these near perfect reflectance characteristics can be advantageously used in the FIR as a black-body source, the interior surface of an integrating sphere, and most especially as an absolute calibration standard. BRDF measurements at 40 deg incidence, though still highly diffuse, show a significant departure from Lambertian reflectance.

Smith, Sheldon M.↗

NASA NTRS2005

International Space Station Electric Power System Performance Code-SPACE

The System Power Analysis for Capability Evaluation (SPACE) software analyzes and predicts the minute-by-minute state of the International Space Station (ISS) electrical power system (EPS) for upcoming missions as well as EPS power generation capacity as a function of ISS configuration and orbital conditions. In order to complete the Certification of Flight Readiness (CoFR) process in which the mission is certified for flight each ISS System must thoroughly assess every proposed mission to verify that the system will support the planned mission operations; SPACE is the sole tool used to conduct these assessments for the power system capability. SPACE is an integrated power system model that incorporates a variety of modules tied together with integration routines and graphical output. The modules include orbit mechanics, solar array pointing/shadowing/thermal and electrical, battery performance, and power management and distribution performance. These modules are tightly integrated within a flexible architecture featuring data-file-driven configurations, source- or load-driven operation, and event scripting. SPACE also predicts the amount of power available for a given system configuration, spacecraft orientation, solar-array-pointing conditions, orbit, and the like. In the source-driven mode, the model must assure that energy balance is achieved, meaning that energy removed from the batteries must be restored (or balanced) each and every orbit. This entails an optimization scheme to ensure that energy balance is maintained without violating any other constraints.

Hojnicki, Jeffrey↗

DOE OSTI2020

An automatically curated first-principles database of ferroelectrics

Ferroelectric materials have technological applications in information storage and electronic devices. The ferroelectric polar phase can be controlled with external fields, chemical substitution and size-effects in bulk and ultrathin film form, providing a platform for future technologies and for exploratory research. In this work, we integrate spin-polarized density functional theory (DFT) calculations, crystal structure databases, symmetry tools, workflow software, and a custom analysis toolkit to build a library of known, previously-proposed, and newly-proposed ferroelectric materials. With our automated workflow, we screen over 67,000 candidate materials from the Materials Project database to generate a dataset of 255 ferroelectric candidates, and propose 126 new ferroelectric materials. We benchmark our results against experimental data and previous first-principles results. The data provided includes atomic structures, output files, and DFT values of band gaps, energies, and the spontaneous polarization for each ferroelectric candidate. Finally, we contribute our workflow and analysis code to the open-source python packages atomate and pymatgen so others can conduct analogous symmetry driven searches for ferroelectrics and related phenomena.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Phased Array Characterization of Slat Noise Radiation from a High-Lift Common Research Model

A test campaign was conducted in the open-jet test section of the NASA Langley 14- by 22-Foot Subsonic Tunnel on a 10%-scale, semispan version of a High-Lift Common Research Model (CRM-HL) incorporating a leading-edge slat, trailing-edge flap and removable high-fidelity main landing gear. Far field acoustic measurements were obtained on baseline and acoustically treated model configurations using a traversing 97-microphone phased array that viewed the pressure side of the airframe. A modified version of the DAMAS deconvolution method incorporating corrections for shear layer acoustic wave decorrelation was employed to determine the locations and strengths of relevant noise sources along the span of the slat and in the vicinity of the flap edges and landing gear. The main goal of the test campaign was to use the array data to evaluate the effectiveness of various slat noise reduction concepts. It was found that slat-gap fillers produced significant broadband noise reduction for all Mach numbers and airfoil angles of attack that were investigated. Mach number scaling revealed an approximate velocity to the sixth power relationship for the slat noise at higher frequencies. Directivity measurements obtained from integration of DAMAS pressure-squared values over defined geometric zones around the model showed that baseline slat noise radiation approximated a dipole as a function of polar emission angle, becoming approximately omnidirectional with the introduction of the slat-gap filler. The test campaign clearly demonstrated the noise reduction benefits that can be obtained by applying appropriate treatments to leading edge slats on commercial transport-class aircraft.

William M Humphreys, Jr.↗

NASA NTRSDate not supplied

New Features of the NEQAIR Radiation Code

The longest-lived code for predicting shock layer radiation, NEQAIR, is now in its 5th decade of service. Substantial changes to the code have been made over the previous decade, the most recent report of which was at the 5th Workshop on Radiation in High Temperature Gases in 2014, for the version referred to as NEQAIR14. This paper will review some of the improvements made to the NEQAIR code since then, which is now at v15.2. Some of these features are discussed briefly below. NEQAIR15 and subsequent versions have enabled parallel evaluation of multiple lines of sight. This is accomplished by utilizing the HDF5 file format and placing multiple lines into a single file, LOS.h5, which is used for both input and output. This approach enables straightforward parallel execution both over the number of lines of sight and the number of points per line. For large problems, runtime reduces linearly with the number of nodes deployed since each line is processed independently by a subset of MPI ranks. Three applications of the multi-line solver are discussed. The first has to do with performing loosely coupled radiation-flowfield solutions. In this case the computed absorption and emission coefficients are used to evaluate the total energy absorbed or emitted at each point, allowing evaluation of the volumetric source term in the flowfield. The second computation is for obtaining heat flux from nonuniform flows, which require integration over spherical co-ordinates. These are of particular interest for evaluating radiation on the vehicle backshell. This 3D option improves the angular integration scheme and allows adaptive line selection that together reduce the number of lines required by about an order of magnitude. The final application is for remote observation, which is essentially the 3D integration problem over a small solid angle. For all three of these computations, data can be stored in the HDF5 file which allows a NEQAIR run to be restarted when it times out, or to add atmospheric absorption or instrument scan functions. An additional level of parallelism is enabled in NEQAIR15.2 using GPU routines. The GPU parallelism has realized up to 8x speed-up when running on a single core but diminishes as CPU parallelism is increased. For running multi-line simulations, it may be easier to reserve a large number of CPU nodes than to obtain the number of GPU nodes required for similar performance. A GUI, known as NEQTPY, allows for reading and creating input files, running NEQAIR, and displaying results. A significant feature of NEQTPY is the ability to perform spectral fits to data. The fits can operate on a single line spectrum (radiance vs. wavelength) or a 3D input file with multiple columns of data. Other new features include improved constants, additional species, more detailed non-Boltzmann modelling, advanced user controls, the ability to read and calculate spectra from HITRAN datafiles, photodissociation and photoionization cross-sections. A “fast” automatic grid option may reduce the size and time of spectral calculations while still maintaining good accuracy for total heat flux.

Brett A Cruden↗

DOE OSTI2021

Selective cobalt and nickel electrodeposition for lithium-ion battery recycling through integrated electrolyte and interface control

Abstract Molecularly-selective metal separations are key to sustainable recycling of Li-ion battery electrodes. However, metals with close reduction potentials present a fundamental challenge for selective electrodeposition, especially for critical elements such as cobalt and nickel. Here, we demonstrate the synergistic combination of electrolyte control and interfacial design to achieve molecular selectivity for cobalt and nickel during potential-dependent electrodeposition. Concentrated chloride allows for the speciation control via distinct formation of anionic cobalt chloride complex (CoCl 4 2- ), while maintaining nickel in the cationic form ([Ni(H 2 O) 5 Cl] + ). Furthermore, functionalizing electrodes with a positively charged polyelectrolyte (i.e., poly(diallyldimethylammonium) chloride) changes the mobility of CoCl 4 2- by electrostatic stabilization, which tunes cobalt selectivity depending on the polyelectrolyte loading. This strategy is applied for the multicomponent metal recovery from commercially-sourced lithium nickel manganese cobalt oxide electrodes. We report a final purity of 96.4 ± 3.1% and 94.1 ± 2.3% for cobalt and nickel, respectively. Based on a technoeconomic analysis, we identify the limiting costs arising from the background electrolyte, and provide a promising outlook of selective electrodeposition as an efficient separation approach for battery recycling.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Tunable structure and reinforcement of polyvinyl alcohol (PVA) hydrogels using fungal chitin particles

Polysaccharides, including chitin, are one of the most abundant biopolymers in nature and are increasingly recognized as a sustainable alternative to petroleum-derived plastics and synthetic fillers in polymer composites. Traditionally sourced from crustacean shells, chitin offers mechanical strength and biocompatibility with limitations also in processability and functionality. Fungal-derived chitin material represents a promising alternative, with advantages including scalable fermentation on low-cost substrates, absence of shellfish allergens, and tunable molecular architectures that vary by species, developmental stage, and growth environment. Here, in this study, we systematically examined chitinous materials obtained from taxonomically and functionally distinct fungi, Laccaria bicolor, Trichoderma reesei and Rhizopus oryzae, to assess their structural, chemical, and morphological properties as reinforcement agents in polymer composites. Mild alkaline pretreatment was employed to obtain mycelium chitin particles, thereby improving accessibility to chitin and co-occurring β-D-glucans while maintaining microparticle integrity. Comprehensive FTIR and solid-state NMR analyses revealed species-specific differences in chemical composition and microstructure, with R. oryzae exhibiting a unique spectral signature. These fungal-derived chitin were then incorporated into poly(vinyl alcohol) (PVA) hydrogels, where they acted as reinforcing fillers without the need for additional chemical crosslinkers. Comparative evaluation of hydrogel properties demonstrated that fungal chitin significantly enhanced mechanical performance, with all mycelium fillers mitigating the water weakening in PVA hydrogels. R. oryzae-derived composites tripled the hydrogel tensile strength while the submicron fibrous morphology in L. bicolor contributes to over 45 % tensile improvement in dry PVA composites. Our findings highlight the potential of fungal biomass as a tunable, sustainable platform for producing chitin-based reinforcing agents.

Chitin↗

DOE OSTI2019

Infrared studies of gas phase and surface processes of the enhancement of catalytic methane decomposition by low temperature plasma

Catalyst enhancement by atmospheric pressure plasma is a recently emerging field of research that embodies a complex system of reactive species and how they interact with surfaces. In this work we use an atmospheric pressure plasma jet integrated with a nickel on Al 2 O 3 /SiO 2 support catalyst material to decompose methane gas by partial oxidation reaction. We use Fourier-transform Infrared spectroscopy (FTIR) analysis of the gas phase post reaction to measure the loss of methane and the production of CO, CO 2 , and H 2 O and diffuse reflectance Fourier-transform Infrared spectroscopy (DRIFTs) in situ analysis of the catalyst surface as a function of both catalyst temperature and plasma operating parameters. We find reduction of methane by both plasma alone, catalyst alone, and an increase when both plasma and catalyst were simultaneously used. The production of CO appears to be due primarily to the plasma source as it only appears above 2.5 W plasma dissipated power and decreases as catalyst temperature increases. CO 2 production is enhanced by having the catalyst at high temperature and H 2 O production depends on both plasma power and temperature. Using DRIFTs we find that both heating and plasma treatment remove absorbed water on the surface of the catalyst. Plasma treatment alone however leads to the formation of CO and another IR spectral feature at 1590 cm -1 , which may be attributed to carboxylate groups, bonded to the catalyst surface. These species exhibit a regime of plasma treatment where they are formed on the surface and where they are significantly removed from the catalyst surface. We see the formation of a new spectral feature at 995 cm -1 and discuss the behavior and possible origins of this feature. Furthermore, this research highlights the potential for plasma regeneration of catalyst materials as well as showing enhancement of the catalytic behavior under low temperature plasma treatment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Fidelity Comparison of Time-Bin and Fock State Encoding in Hybrid Quantum Systems Under Channel and Transduction Effects

Future quantum networks are expected to integrate a heterogeneous combination of quantum systems, owing to the diverse advantages offered by different physical platforms in terms of scalability, coherence times, and interfacing capabilities. Within the context of this emerging quantum communication paradigm, this paper presents an analytical comparison of two photonic encoding schemes—time-bin and Fock state (single rail)—in hybrid quantum systems where flying qubits are entangled with stationary matter qubits. We evaluate their resilience against fiber channel and quantum transduction effects by calculating the fidelity of the final states relative to their ideal forms. Employing the characteristic function approach, we derive analytical fidelity expressions and investigate their dependence on parameters such as transmissivity, noise levels, fiber length, and source generation success probability. Additionally, we simulate the scenario with a dedicated QuTiP software implementation to verify the validity of the theoretical models. Our findings reveal that due to its inherent single-mode structure, the Fock state encoding consistently outperforms time-bin encoding in fidelity, as this structure significantly minimizes susceptibility to losses compared to the two-mode nature of the time-bin scheme. This analysis offers valuable insights for future hybrid quantum communication and information processing applications.

Fiorini, Francesco [Pisa U.]↗

NASA NTRS1983

H I Lyman-alpha in the sun - The effects of partial redistribution in the line wings

A form for the Lyman-alpha redistribution function that is modified to include the effects of collisional coupling between different energy states is presented. It is noted that this extends the work of Yelnik et al. (1981) and Roussel-Dupre(1982). By separating the source function into its primary components at all heights, the formation of Lyman-alpha radiation is investigated in detail. Frequencies in the line wing can be mapped back in such a way that the heights of formation for a change in lambda of plus or minus 0.5-6 A span the entire solar chromosphere. The usefulness of the Lyman-alpha wing as an atmospheric probe, however, is limited by long thermalization lengths, which result from almost coherent scattering outside of the Doppler core. When the line profiles calculated from the chromospheric models of Vernazza et al. (1981) are compared with the quiet-sun observations of Roussel-Dupre, agreement is found in integrated core intensities and in the line wing shape and normalized center-to-limb behavior. The calculated wing intensities, however, are a factor of four too small.

Roussel-Dupre, D.↗

NASA NTRS2001

Project Integration Architecture: Architectural Overview

The Project Integration Architecture (PIA) implements a flexible, object-oriented, wrapping architecture which encapsulates all of the information associated with engineering applications. The architecture allows the progress of a project to be tracked and documented in its entirety. By being a single, self-revealing architecture, the ability to develop single tools, for example a single graphical user interface, to span all applications is enabled. Additionally, by bringing all of the information sources and sinks of a project into a single architectural space, the ability to transport information between those applications becomes possible, Object-encapsulation further allows information to become in a sense self-aware, knowing things such as its own dimensionality and providing functionality appropriate to its kind.

Jones, William Henry↗