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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 451 records · Page 25

Development of an Expert System for Representing Procedural Knowledge

A high level of automation is of paramount importance in most space operations. It is critical for unmanned missions and greatly increases the effectiveness of manned missions. However, although many functions can be automated by using advanced engineering techniques, others require complex reasoning, sensing, and manipulatory capabilities that go beyond this technology. Automation of fault diagnosis and malfunction handling is a case in point. The military have long been interested in this problem, and have developed automatic test equipment to aid in the maintenance of complex military hardware. These systems are all based on conventional software and engineering techniques. However, the effectiveness of such test equipment is severely limited. The equipment is inflexible and unresponsive to the skill level of the technicians using it. The diagnostic procedures cannot be matched to the exigencies of the current situation nor can they cope with reconfiguration or modification of the items under test. The diagnosis cannot be guided by useful advice from technicians and, when a fault cannot be isolated, no explanation is given as to the cause of failure. Because these systems perform a prescribed sequence of tests, they cannot utilize knowledge of a particular situation to focus attention on more likely trouble spots. Consequently, real-time performance is highly unsatisfactory. Furthermore, the cost of developing test software is substantial and time to maturation is excessive. Significant advances in artificial intelligence (AI) have recently led to the development of powerful and flexible reasoning systems, known as expert or knowledge-based systems. We have devised a powerful and theoretically sound scheme for representing and reasoning about procedural knowledge.

Georgeff, Michael P.↗

Parametric Transformation Analysis

Because twisted coronal features are important proxies for predicting solar eruptive events, and, yet not clearly understood, we present new results to resolve the complex, non-potential magnetic field configurations of active regions. This research uses free-form deformation mathematics to generate the associated coronal magnetic field. We use a parametric representation of the magnetic field lines such that the field lines can be manipulated to match the structure of EUV and SXR coronal loops. The objective is to derive sigmoidal magnetic field solutions which allows the beta greater than 1 regions to be included, aligned and non-aligned electric currents to be calculated, and the Lorentz force to be determined. The advantage of our technique is that the solution is independent of the unknown upper and side boundary conditions, allows non-vanishing magnetic forces, and provides a global magnetic field solution, which contains high- and low-beta regimes and is consistent with all the coronal images of the region. We show that the mathematical description is unique and physical.

Gary, G. Allan↗

Human Factors in Training

Future space missions will be significantly longer than current Shuttle missions and new systems will be more complex than current systems. Increasing communication delays between crews and Earth-based support means that astronauts need to be prepared to handle the unexpected on their own. As crews become more autonomous, their potential span of control and required expertise must grow to match their autonomy. It is not possible to train for every eventuality ahead of time on the ground, or to maintain trained skills across long intervals of disuse. To adequately prepare NASA personnel for these challenges, new training approaches, methodologies, and tools are required. This research project aims at developing these training capabilities. Training efforts in FY07 strongly focused on crew medical training, but also began exploring how Space Flight Resource Management training for Mission Operations Directorate (MOD) Flight Controllers could be integrated with systems training for optimal Mission Control Center operations. Beginning in January 2008, the training research effort will include team training prototypes and tools. The Training Task addresses Program risks that lie at the intersection of the following three risks identified by the Project: 1) Risk associated with poor task design; 2) Risk of error due to inadequate information; 3) Risk associated with reduced safety and efficiency due to poor human factors design.

Barshi, Immanuel↗

Human Factors in Training

Future space missions will be significantly longer than current shuttle missions and new systems will be more complex than current systems. Increasing communication delays between crews and Earth-based support means that astronauts need to be prepared to handle the unexpected on their own. As crews become more autonomous, their potential span of control and required expertise must grow to match their autonomy. It is not possible to train for every eventuality ahead of time on the ground, or to maintain trained skills across long intervals of disuse. To adequately prepare NASA personnel for these challenges, new training approaches, methodologies, and tools are required. This research project aims at developing these training capabilities. By researching established training principles, examining future needs, and by using current practices in space flight training as test beds, both in Flight Controller and Crew Medical domains, this research project is mitigating program risks and generating templates and requirements to meet future training needs. Training efforts in Fiscal Year 08 (FY08) strongly focused on crew medical training, but also began exploring how Space Flight Resource Management training for Mission Operations Directorate (MOD) Flight Controllers could be integrated with systems training for optimal Mission Control Center (MCC) operations. The Training Task addresses Program risks that lie at the intersection of the following three risks identified by the Project: (1) Risk associated with poor task design (2) Risk of error due to inadequate information (3) Risk associated with reduced safety and efficiency due to poor human factors design

Barshi, Immanuel↗

Human Factors in Training

Future space missions will be significantly longer than current shuttle missions and new systems will be more complex than current systems. Increasing communication delays between crews and Earth-based support means that astronauts need to be prepared to handle the unexpected on their own. As crews become more autonomous, their potential span of control and required expertise must grow to match their autonomy. It is not possible to train for every eventuality ahead of time on the ground, or to maintain trained skills across long intervals of disuse. To adequately prepare NASA personnel for these challenges, new training approaches, methodologies, and tools are required. This research project aims at developing these training capabilities. By researching established training principles, examining future needs, and by using current practices in space flight training as test beds, both in Flight Controller and Crew Medical domains, this research project is mitigating program risks and generating templates and requirements to meet future training needs. Training efforts in Fiscal Year 09 (FY09) strongly focused on crew medical training, but also began exploring how Space Flight Resource Management training for Mission Operations Directorate (MOD) Flight Controllers could be integrated with systems training for optimal Mission Control Center (MCC) operations. The Training Task addresses Program risks that lie at the intersection of the following three risks identified by the Project: 1) Risk associated with poor task design; 2) Risk of error due to inadequate information; and 3) Risk associated with reduced safety and efficiency due to poor human factors design.

Barshi, Immanuel↗

Self-regulating behavior of hybrid membrane systems as demonstrated in an element-scale forward osmosis-reverse osmosis hybrid system

Hybrid membrane systems can be difficult to design due to the requisite flow rate matching between up- and downstream unit operations. In this work, we use a forward osmosis-reverse osmosis (FO-RO) hybrid system to demonstrate how some membrane systems can exhibit self-regulating behavior due to osmotic coupling. This can reduce the need for complex control systems for flow balancing. We show this behavior using a module-scale test bed that can mimic the behavior of larger scale operations. The system shows permeate flow rate near-convergence between the FO and RO modules after startup or when perturbed by a change in RO module pressure. The behavior of this hybrid system demonstrates that some membrane operations can exploit osmotic interdependence, rather than expensive control systems, to achieve steady state operation.

Debottlenecking↗

Dara: Automated Multiple-Hypothesis Phase Identification and Refinement from Powder X-ray Diffraction

Powder X-ray diffraction (XRD) is a foundational technique for characterizing crystalline materials. However, the reliable interpretation of XRD patterns, particularly in multiphase systems, remains a manual and expertise-demanding task. As a characterization method that only provides structural information, multiple reference phases can often be fit to a single pattern, leading to potential misinterpretation when alternative solutions are overlooked. To ease humans’ efforts and address the challenge, we introduce Dara (data-driven automated Rietveld analysis), a framework designed to automate the robust identification and refinement of multiple phases from powder XRD data. Dara performs an exhaustive tree search over all plausible phase combinations within a given chemical space and validates each hypothesis using the BGMN Rietveld refinement routine. Key features include structural database filtering, automatic clustering of isostructural phases during tree expansion, and peak-matching-based scoring to identify promising phases for refinement. When ambiguity exists, Dara generates multiple hypothesis which can then be decided between by human experts or with further characterization tools. By enhancing the reliability and accuracy of phase identification, Dara enables scalable analysis of realistic complex XRD patterns and provides a foundation for integration into multimodal characterization workflows, moving toward fully self-driving materials discovery.

Biological databases↗

Generalized analytical and numerical modeling of optical second harmonic generation in anisotropic crystals and complex heterostructures using #SHAARP package

Optical second harmonic generation (SHG) is a nonlinear optical effect widely used for nonlinear optical microscopy and laser frequency conversion. The closed-form analytical solution of the nonlinear optical responses is essential for evaluating the optical responses of new materials whose optical properties are unknown a priori. Many approximations have therefore been employed in the existing analytical approaches, such as slowly varying approximation, weak reflection of the nonlinear polarization, transparent medium, high crystallographic symmetry, Kleinman symmetry, easy crystal orientation along a high-symmetry direction, phase matching conditions and negligible interference among nonlinear waves, which may lead to large errors in the reported material properties. To avoid these approximations, here we have developed an open-source package named Second Harmonic Analysis of Anisotropic Rotational Polarimetry (#SHAARP) for single interface (si) and in multilayers (ml) for homogeneous crystals. The reliability and accuracy are established by experimentally benchmarking with both the SHG polarimetry and Maker fringes predicted from the package using standard materials. SHAARP.si and SHAARP.ml are available through GitHub https://github.com/Rui-Zu/SHAARP and https://github.com/bzw133/SHAARP.ml, respectively.

complex systems↗

Low-energy electrodynamics and a hidden Fermi liquid in the heavy-fermion compound CeCoIn 5

We present time-domain THz spectroscopy of thin films of the heavy-fermion superconductor CeCoIn 5 . Below the ≈40 K Kondo coherence temperature, a narrow Drude-like peak forms, as a result of the 𝑓-orbital–conduction-electron hybridization and the formation of the heavy-fermion state. The complex optical conductivity is analyzed through a Drude model and extended Drude model analysis. Via the extended Drude model analysis, we measure the frequency-dependent scattering rate (1/𝜏) and effective mass (𝑚*/𝑚 𝑏 ). This scattering rate shows a linear dependence on temperature, which matches the dependence of the resistivity as expected. Nevertheless, the width of the low-frequency Drude peak itself that is set by the renormalized quasiparticle scattering rate (1/𝜏*=𝑚 𝑏 /𝑚*⁢𝜏) shows a 𝑇 2 dependence. This is the scattering rate that characterizes the relaxation time of the renormalized quasiparticles. In conclusion, this gives evidence for a Fermi liquid state, which in conventional transport experiments is hidden by the strong temperature dependent mass.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Three-dimensional superlattice engineering with block copolymer epitaxy

Three-dimensional (3D) structures at the nanometer length scale play a crucial role in modern devices, but their fabrication using traditional top-down approaches is complex and expensive. Analogous to atomic lattices, block copolymers (BCPs) spontaneously form a rich variety of 3D nanostructures and have the potential to substantially simplify 3D nanofabrication. Here, we show that the 3D superlattice formed by BCP micelles can be controlled by lithographically defined 2D templates matching a crystallographic plane in the 3D superlattice. Using scanning transmission electron microscopy tomography, we demonstrate precise control over the lattice symmetry and orientation. Excellent ordering and substrate registration can be achieved, propagating through 284-nanometer-thick films. BCP epitaxy also showed exceptional lattice tunability, with a continuous Bain transformation from a body-centered cubic to a face-centered cubic lattice. Lattice stability was mediated by molecular packing frustration, and surface-induced lattice reconstruction was observed, leading to the formation of a unique honeycomb lattice.

42 ENGINEERING↗

Statistically Resolved Planetary Boundary Layer Height Diurnal Variability Using Spaceborne Lidar Data

The Planetary Boundary Layer Height (PBLH) significantly impacts weather, climate, and air quality. Understanding the global diurnal variation of the PBLH is particularly challenging due to the necessity of extensive observations and suitable retrieval algorithms that can adapt to diverse thermodynamic and dynamic conditions. This study utilized data from the Cloud-Aerosol Transport System (CATS) to analyze the diurnal variation of PBLH in both continental and marine regions. By leveraging CATS data and a modified version of the Different Thermo-Dynamics Stability (DTDS) algorithm, along with machine learning denoising, the study determined the diurnal variation of the PBLH in continental mid-latitude and marine regions. The CATS DTDS-PBLH closely matches ground-based lidar and radiosonde measurements at the continental sites, with correlation coefficients above 0.6 and well-aligned diurnal variability, although slightly overestimated at nighttime. In contrast, PBLH at the marine site was consistently overestimated due to the viewing geometry of CATS and complex cloud structures. The study emphasizes the importance of integrating meteorological data with lidar signals for accurate and robust PBLH estimations, which are essential for effective boundary layer assessment from satellite observations.

54 ENVIRONMENTAL SCIENCES↗

Ch3MS-RF: a random forest model for chemical characterization and improved quantification of unidentified atmospheric organics detected by chromatography–mass spectrometry techniques

Abstract. The chemical composition of ambient organic aerosols plays a critical role in driving their climate and health-relevant properties and holds important clues to the sources and formation mechanisms of secondary aerosol material. In most ambient atmospheric environments, this composition remains incompletely characterized, with the number of identifiable species consistently outnumbered by those that have no mass spectral matches in the literature or the National Institute of Standards and Technology/National Institutes of Health/Environmental Protection Agency (NIST/NIH/EPA) mass spectral databases, making them nearly impossible to definitively identify. This creates significant challenges in utilizing the full analytical capabilities of techniques which separate and generate spectra for complex environmental samples. In this work, we develop the use of machine learning techniques to quantify and characterize novel, or unidentifiable, organic material. This work introduces Ch3MS-RF (Chemical Characterization by Chromatography–Mass Spectrometry Random Forest Modeling), an open-source, R-based software tool, for efficient machine-learning-enabled characterization of compounds separated in chromatography–mass spectrometry applications but not identifiable by comparison to mass spectral databases. A random forest model is trained and tested on a known 130 component representative external standard to predict the response factors of novel environmental organics based on position in volatility–polarity space and mass spectrum, enabling the reproducible, efficient, and optimized quantification of novel environmental species. Quantification accuracy on a reserved 20 % test set randomly split from the external standard compound list indicates that random forest modeling significantly outperforms the commonly used methods in both precision and accuracy, with a median response factor percent error of −2 %, for modeled response factors, compared to > 15 %, for typically used proxy assignment-based methods. Chemical properties modeling, evaluated on the same reserved 20 % test set and an extrapolation set of species identified in ambient organic aerosol samples collected in the Amazon rainforest, also demonstrate robust performance. Extrapolation set property prediction mean absolute errors for carbon number, oxygen to carbon ratio (O : C), average carbon oxidation state (OSc‾), and vapor pressure are 1.8, 0.15, 0.25, and 1.0 (log(atm)), respectively. Extrapolation set out-of-sample R2 for all properties modeled are above 0.75, with the exception of vapor pressure. While predictive performance for vapor pressure is less robust compared to the other chemical properties modeled, random-forest-based modeling was significantly more accurate than other commonly used methods of vapor pressure prediction, decreasing the mean vapor pressure prediction error to 0.24 (log(atm)) from 0.55 (log(atm)) (chromatography-based vapor pressure prediction) and 1.2 (log(atm)) (chemical formula-based vapor pressure prediction). The random forest model significantly advances an untargeted analysis of the full scope of chemical speciation yielded by two-dimensional gas chromatography (GCxGC-MS) techniques and can be applied to gas chromatography coupled with electron ionization mass spectrometry (GC-MS) as well. It enables the accurate estimation of key chemical properties commonly utilized in the atmospheric chemistry community, which may be used to more efficiently identify important tracers for further individual analysis and to characterize compound populations uniquely formed under specific ambient conditions.

54 ENVIRONMENTAL SCIENCES↗

Quiet Supersonic Wind Tunnel Development

The ability to control the extent of laminar flow on swept wings at supersonic speeds may be a critical element in developing the enabling technology for a High Speed Civil Transport (HSCT). Laminar boundary layers are less resistive to forward flight than their turbulent counterparts, thus the farther downstream that transition from laminar to turbulent flow in the wing boundary layer is extended can be of significant economic impact. Due to the complex processes involved experimental studies of boundary layer stability and transition are needed, and these are performed in "quiet" wind tunnels capable of simulating the low-disturbance environment of free flight. At Ames, a wind tunnel has been built to operate at flow conditions which match those of the HSCT laminar flow flight demonstration 'aircraft, the F-16XL, i.e. at a Mach number of 1.6 and a Reynolds number range of 1 to 3 million per foot. This will allow detailed studies of the attachment line and crossflow on the leading edge area of the highly swept wing. Also, use of suction as a means of control of transition due to crossflow and attachment line instabilities can be studied. Topics covered include: test operating conditions required; design requirements to efficiently make use of the existing infrastructure; development of an injector drive system using a small pilot facility; plenum chamber design; use of computational tools for tunnel and model design; and early operational results.

King, Lyndell S.↗

The Statistical Consulting Center for Astronomy (SCCA)

The process by which raw astronomical data acquisition is transformed into scientifically meaningful results and interpretation typically involves many statistical steps. Traditional astronomy limits itself to a narrow range of old and familiar statistical methods: means and standard deviations; least-squares methods like chi(sup 2) minimization; and simple nonparametric procedures such as the Kolmogorov-Smirnov tests. These tools are often inadequate for the complex problems and datasets under investigations, and recent years have witnessed an increased usage of maximum-likelihood, survival analysis, multivariate analysis, wavelet and advanced time-series methods. The Statistical Consulting Center for Astronomy (SCCA) assisted astronomers with the use of sophisticated tools, and to match these tools with specific problems. The SCCA operated with two professors of statistics and a professor of astronomy working together. Questions were received by e-mail, and were discussed in detail with the questioner. Summaries of those questions and answers leading to new approaches were posted on the Web (www.state.psu.edu/ mga/SCCA). In addition to serving individual astronomers, the SCCA established a Web site for general use that provides hypertext links to selected on-line public-domain statistical software and services. The StatCodes site (www.astro.psu.edu/statcodes) provides over 200 links in the areas of: Bayesian statistics; censored and truncated data; correlation and regression, density estimation and smoothing, general statistics packages and information; image analysis; interactive Web tools; multivariate analysis; multivariate clustering and classification; nonparametric analysis; software written by astronomers; spatial statistics; statistical distributions; time series analysis; and visualization tools. StatCodes has received a remarkable high and constant hit rate of 250 hits/week (over 10,000/year) since its inception in mid-1997. It is of interest to scientists both within and outside of astronomy. The most popular sections are multivariate techniques, image analysis, and time series analysis. Hundreds of copies of the ASURV, SLOPES and CENS-TAU codes developed by SCCA scientists were also downloaded from the StatCodes site. In addition to formal SCCA duties, SCCA scientists continued a variety of related activities in astrostatistics, including refereeing of statistically oriented papers submitted to the Astrophysical Journal, talks in meetings including Feigelson's talk to science journalists entitled "The reemergence of astrostatistics" at the American Association for the Advancement of Science meeting, and published papers of astrostatistical content.

Akritas, Michael↗

Absorption and scattering properties of the Martian dust in the solar wavelengths

A new wavelength-dependent model of the single-scattering properties of the Martian dust is presented. The model encompasses the solar wavelengths (0.3 to 4.3 micrometers at 0.02 micrometer resolution) and does not assume a particular mineralogical composition of the particles. We use the particle size distribution, shape, and single-scattering properties at Viking Lander wavelengths presented by Pollack et al. [1995]. We expand the wavelength range of the aerosol model by assuming that the atmospheric dust complex index of refraction is the same as that of dust particles in the bright surface geologic units. The new wavelength-dependent model is compared to observations taken by the Viking Orbiter Infrared Thermal Mapper solar channel instrument during two dust storms. The model accurately matches afternoon observations and some morning observations. Some of the early morning observations are much brighter than the model results. The increased reflectance can be ascribed to the formation of a water ice shell around the dust particles, thus creating the water ice clouds which Colburn et al. [1989], among others, have predicted.

Atmosphere/analysis↗

Conceptual design of the modular detector and readout system for the CMB-S4 survey experiment

We present the conceptual design of the modular detector and readout system for the Cosmic Microwave Background – Stage four (CMB-S4) ground-based survey experiment. CMB-S4 will map the cosmic microwave background (CMB) and the millimeter-wave sky to unprecedented sensitivity, using 500,000 superconducting detectors observing from Chile and Antarctica to map over 60% of the sky. The fundamental building block of the detector and readout system is a detector module package operated at 100 mK, which is connected to a readout and amplification chain that carries signals out to room temperature. It uses arrays of feedhorn-coupled orthomode transducers (OMT) that collect optical power from the sky onto dc-voltage-biased transition-edge sensor (TES) bolometers. The resulting current signal in the TESs is then amplified by a two-stage cryogenic Superconducting Quantum Interference Device (SQUID) system with a time-division multiplexer to reduce wire count, and matching room-temperature electronics to condition and transmit signals to the data acquisition system. Sensitivity and systematics requirements are being developed for the detector and readout system over wide range of observing bands (20 to 300 GHz) and optical powers to accomplish CMB-S4’s science goals. While the design incorporates the successes of previous generations of CMB instruments, CMB-S4 requires an order of magnitude more detectors than any prior experiment. This requires fabrication of complex superconducting circuits on over 10 m2 of silicon, as well as significant amounts of precision wiring, assembly and cryogenic testing

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Synthesis of results for Brine Availability Test in Salt (BATS) DECOVALEX-2023 Task E

In the 2023 phase of the international collaborative DECOVALEX modeling project, Task E focused on understanding thermal, hydrological, and mechanical (THM) processes related to predicting brine migration in the excavation damaged zone around a heated excavation in salt. Salt is attractive as a disposal medium for radioactive waste because it is self-healing and is essentially impermeable and non-porous in the far field. Investigation of the short-term, near-field behavior is important for radioactive waste disposal because this early period strongly controls the amount of inflowing brine. Brine leads to corrosion of waste forms and waste packages, and possible dissolution of radionuclides with brine transport being a potential transport vector to the accessible environment.The Task was divided into steps. Step 0 included matching unheated brine inflow data from boreholes at the Waste Isolation Pilot Plant (WIPP) and matching temperature observations during a Brine Availability Test in Salt (BATS) heater test. Step 1 included validation of models against a thermo-poroelastic analytical solution, and two-phase flow around an excavation. Finally, Step 2 required all the individual components covered in steps 0 and 1 to come together to match observed brine inflow behavior during the same BATS heater test.There were a range of approaches from the teams, from mechanistic to prescriptive. Given the uncertainties in the problem, some teams used one- or two-dimensional models of the processes, while other teams included more geometrical complexity in three-dimensional models. Task E was a learning experience for the teams involved, and feedback from the modeling teams has led to changes in follow-on BATS experiments at WIPP. The primary Task E lessons learned were the impact of hydrologic initialization methods (wetting up vs. drying down), the difference between confined and unconfined thermal expansion, and the large changes in permeability associated with heating and cooling.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Ethanol as a Renewable Building Block for Fuels and Chemicals

Three factors, i) the ethanol “blend wall”, which limits its market as a transportation fuel, ii) advances in production efficiency, and iii) feedstock diversification, could lead to excess ethanol at competitive prices. Those factors have already motivated a search for value-added derivatives (e.g., distillate fuels, olefins, and asymmetric amines). Siting small, low cost, flexible conversion facilities to process ethanol at or near the fermentation plant could encourage the growth of an enterprise. Decreasing the barriers to entry, matching supply and demand, and enhancing access to production incentives are enabling success factors. This review discusses the process chemistries that might be employed by such ethanol conversion facilities based on market prices. Finally, how these technologies might benefit from process intensification, and without the requirement of complex processing or large pressures or temperature gradients typically employed in conventional, large scale facilities.

09 BIOMASS FUELS↗