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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 145 records · Page 8

Preliminary Characterization and Evaluation on FFF Manufactured 316H and ODS Steels

The Advanced Materials and Manufacturing Technology (AMMT) program develops cross-cutting technologies in support of a broad range of nuclear reactor technologies and maintains U.S. leadership in materials and manufacturing technologies for nuclear energy applications. The overarching vision of AMMT is to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. Solid-state advanced manufacturing techniques can overcome some of the challenges in liquid-based additive manufacturing (AM) processes and should therefore be considered in material design and manufacturing as well. The work presented in this report forms part of a study on solid-state AM techniques of 316 stainless steels (SS) and oxide dispersion strengthened (ODS) steel components and supports the vision and goals of the AMMT program relevant to accelerate the development and deployment of advanced manufacturing processes. Achieving this can provide a safety improvement through larger safety margins, economic benefit for higher efficiency during operation, and a cost reduction through more effective manufacturing processes and less waste. This study provides preliminary information on development of the fused-filament fabrication (FFF) process using different powder types to demonstrate the sensitivity, and therefore the characterization of these sample components. The full solid-state manufacturing feasibility study will be completed and reported in a final feasibility evaluation during 2025. The study investigation used two 14YWT ODS powder batches, which provided information and the effect of different powder morphologies on manufacturability. The two 316SS powders demonstrated the effect of powder size on the manufacturability using FFF. Two product forms, namely a honeycomb structure and flat samples, were manufactured to demonstrate the flexibility of product form.

36 MATERIALS SCIENCE↗

Neptunium (V) Solubility in WIPP Brine: Presence and Absence of WIPP-Relevant Organic and Inorganic Ligands

The oxidation state and solubility of neptunium (Np) in 5 M NaCl and high ionic strength synthetic WIPP (Waste Isolation Pilot Plant) brines were systematically investigated as a function of pCH+ (7-11) in the presence and absence of WIPP-relevant organic ligands, including EDTA (Ethylenediaminetetraacetic acid), oxalate, citrate, and acetate, as well as inorganic ligands such as borate and carbonate at a temperature of 23 ± 2°C. This study was conducted through long-term batch solubility experiments spanning approximately 950 days, using an undersaturation approach. A comprehensive set of experimental and spectroscopic techniques, including UV-VIS-NIR spectroscopy and Np L III -edge X-ray Absorption Spectroscopy (XAS), was employed to identify the solubility-controlling Np solid phases and the predominant aqueous Np species present in the samples.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Novel duplex vapor-electrochemical method for silicon solar cells

Silicon obtained by the SiF4-Na reaction was analyzed by spark source mass spectrometry (SSMS). Silicon samples prepared from induction melted powder were evaluated for electrical properties using four point probe conductivity and thermoelectric methods. SiF4-Na reaction under P sub SiF4 greater than 1 atmosphere. The amount of silicon produced was increased from 25 g per batch (in the glass reactor) to greater than 70 g per batch in the stainless steel reactor. The study of the effects of reaction variables such as P sub SiF4 and maximum temperature attained on the particle size of silicon powder showed that the silicon particle size tends to grow larger with increasing pressure of the SiF4 gas in the reaction system.

Kapur, V. K.↗

A simple, analytic 3-dimensional downburst model based on boundary layer stagnation flow

A simple downburst model is developed for use in batch and real-time piloted simulation studies of guidance strategies for terminal area transport aircraft operations in wind shear conditions. The model represents an axisymmetric stagnation point flow, based on velocity profiles from the Terminal Area Simulation System (TASS) model developed by Proctor and satisfies the mass continuity equation in cylindrical coordinates. Altitude dependence, including boundary layer effects near the ground, closely matches real-world measurements, as do the increase, peak, and decay of outflow and downflow with increasing distance from the downburst center. Equations for horizontal and vertical winds were derived, and found to be infinitely differentiable, with no singular points existent in the flow field. In addition, a simple relationship exists among the ratio of maximum horizontal to vertical velocities, the downdraft radius, depth of outflow, and altitude of maximum outflow. In use, a microburst can be modeled by specifying four characteristic parameters, velocity components in the x, y and z directions, and the corresponding nine partial derivatives are obtained easily from the velocity equations.

Oseguera, Rosa M.↗

Active Galactic Nuclei, Quasars, BL Lac Objects and X-Ray Background

The XMM COSMOS survey is producing the large surface density of X-ray sources anticipated. The first batch of approx. 200 sources is being studied in relation to the large scale structure derived from deep optical/near-IR imaging from Subaru and CFHT. The photometric redshifts from the opt/IR imaging program allow a first look at structure vs. redshift, identifying high z clusters. A consortium of SAO, U. Arizona and the Carnegie Institute of Washington (Pasadena) has started a large program using the 6.5meter Magellan telescopes in Chile with the prime objective of identifying the XMM X-ray sources in the COSMOS field. The first series of observing runs using the new IMACS multi-slit spectrograph on Magellan will take place in January and February of 2005. Some 300 spectra per field will be taken, including 70%-80% of the XMM sources in each field. The four first fields cover the center of the COSMOS field. A VLT consortium is set to obtain bulk redshifts of the field galaxies. The added accuracy of the spectroscopic redshifts over the photo-z's will allow much lower density structures to be seen, voids and filaments. The association of X-ray selected AGNs, and quasars with these filaments, is a major motivation for our studies. Comparison to the deep VLA radio data now becoming available is about to begin.

Mushotzky, Richard↗

Effective kinetics driven by dynamic concentration gradients under coupled transport and reaction

Biogeochemical reaction kinetics are generally established from batch reactors where concentrations are uniform. In natural systems, many biogeochemical processes are characterized by spatially and temporally variable concentration gradients that often occur at scales which are not resolved by field measurements or biogeochemical and reactive transport models. Yet, it is not clear how these sub-scale chemical gradients affect reaction kinetics compared to batch kinetics. Here we investigate this question by studying the paradigmatic case of localized pulses of solute reacting with a solid or a dissolved species in excess. Additionally, we consider non-linear biogeochemical reactions, representative of mineral dissolution, adsorption and redox reactions, which we quantify using simplified power-law kinetics. The combined effect of diffusion and reaction leads to effective kinetics that differ quantitatively and qualitatively from the batch kinetics. Depending on the nonlinearity (reaction order) of the local kinetics, these effects lead to either enhancement or decrease of the overall reaction rate, and result in a rich variety of reaction dynamics. We derive analytical results for the effective kinetics, which are validated by comparison to direct numerical simulations for a broad range of Damköhler numbers and reaction order. Our findings provide new insights into the interpretation of imperfectly mixed lab experiments, the effective kinetics of field systems characterized by intermittent reactant release and the integration of sub-scale concentration gradients in reactive transport models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Study of an Unrefined Humate Solution as a Possible Attenuation-based Remedy for Uranium Contamination in Acidic Groundwater - 20351

The Savannah River Site (SRS), joined the environmental cleanup program in 1981 after the Cold War, and was designated as a hazardous waste management facility. About 1.8 billion gallons of acid wastes were disposed into the F/H Area Seepage Basin that included many radionuclides and dissolved metals, resulting in highly contaminated groundwater plumes with pH of 3 - 5.5. The acidity of the plumes contributes to the mobility of several constituents of concern (COC) such as H-3, U-238, I-129, and Sr-90 for the F-Area plume and H-3, Sr-90 and mercury for the H-Area plume. An active treatment (pump-and-treat and re-injection) system was constructed and put in place in 1997 to address the removal of metals and radionuclides from the contaminated groundwater. As remediation projects advanced, active treatments were transitioned to more passive or enhanced-passive approaches such as the subsurface barrier with base injection system, which has been controlling the mobility of contaminants. However, new and more efficient attenuation-based remedies are always sought. Several studies have proposed that humic substances can be used to remediate sites contaminated with heavy metals by creating a permeable reactive barrier. Humic substances (HS) are major components of soil organic matter. HS are polyfunctional organic macromolecules formed by the chemo-microbiological decomposition of biomass or dead organic matter. These substances are usually divided into three main fractions: humin (insoluble at all pH values), humic acid (soluble at pH greater than 3.5), and fulvic acid (soluble at all pH values). Humic substances are major components of the soil at SRS and, in addition, are also helpful in the removal process of uranium. This research focuses on uranium (VI), which is a key contaminant of concern in the F-Area groundwater plume. The interaction of uranium with sediment in the presence or absence of humic substances involves complex mechanisms that are not yet well understood. The interaction of U(VI) with humic substances can affect the adsorption of U on sediment, altering its mobility in the subsurface. The objective of this study is to study the mobility of uranium in the presence of humic acid and to determine if sediments amended by humic acid can enhance the sorption of heavy metals onto sediments. In this research, experiments were conducted using background (clean) F-Area aquifer sediments to understand and predict uranium mobility. A blended material, humate, containing both humic and fulvic acids and a chemically modified humate (KW15 modified humic or mod-HA) was studied as a possible amendment for uranium remediation in SRS groundwater. Batch experiments were conducted in triplicates using 20 ml of aqueous suspension in DI water containing SRS sediment and mod-HA and studied the effect of pH, kinetics of humate sorption onto SRS sediment and also studied the sorption of uranium onto mod-HA amended SRS sediment. Results indicate that mod-HA amended sediment increases uranium removal significantly. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Recovery of postconsumer mechanically recycled polymers

Mechanical recycling plays a key role in reducing landfill bound plastics that pollute our environment. This process converts plastic waste into marketable pellets by sorting, cleaning, grinding into flakes, compounding in the molten state, and ultimately pelletizing. A primary restriction for the widescale usage of mechanical recycling is the highly variable quality and mechanical properties of the plastic waste feedstock. Degradation can occur during the plastic life cycle with the consumer, during the mechanical processing itself, or during the complex sorting process required to produce the feedstock. This study explores how rheological characterization can mitigate the batch-to-batch variability and identify a potential application for each batch. Shear and extensional rheology of “application-specific” virgin high-density polyethylene (HDPE) and virgin polypropylene (PP) was used as the control for this categorization process. Recycled HDPE and PP from three different streams were then measured and compared to the results from the control study. Rheological measurements proved to be very effective at providing sufficient differentiation to categorize the recycled polymer as suitable for different applications such as injection molding, blow molding, or thermoforming. Finally, the usage of an additional step to sort the recycled polymers by their initial use application was found to achieve a remarkably consistent recovery of application-specific material properties. Furthermore, this secondary sorting could provide significant added value for mechanically recycled polymers.

Differential scanning calorimetry↗

Solidification cracking of refractory alloys: a computational and machine learning study to investigate composition-dependence for improved weldability and additive manufacturability

Large-batch numerical, CALculation of PHAse Diagrams (CALPHAD)-based solidification cracking calculations are performed and then analyzed with machine learning methods to generate models that relate chemistry of refractory alloys to cracking susceptibility. Kou’s solidification cracking index is used to study the refractory alloys including O, N, C binary mixtures with Mo, Ta, Nb, and W, the molybdenum-based TZM, Niobium-based C103, and Tantalum-based T111 and Ta-10 W, as well as hypothetical refractory ternary alloys. Findings strongly validate Kou’s Crack Susceptibility Index (CSI) against Varestraint test data for Nb- and Ta-based alloys, establishing CSI thresholds where refractory alloys with CSI < 15,000 K are likely weldable, CSI > 15,000 K are prone to cracking, and CSI > 25,000 K are likely unweldable (or unprintable). Furthermore, interstitial elements C, N, and O significantly increase crack susceptibility, with some existing material specifications coinciding with peak cracking susceptibility concentrations. Finally, machine learning-derived elemental potency factors enable rapid prediction of CSI from alloy chemistry for C103, TZM, Ta-10 W, and T-111 alloys. These results provide practical guidance for feedstock selection, powder reuse limits, and alloy specification amendments for welding and additive manufacturing applications.

36 MATERIALS SCIENCE↗

Reductive amination cascades in cell‐free and resting whole cell formats for valorization of lignin deconstruction products

Abstract The selective introduction of amine groups within deconstruction products of lignin could provide an avenue for valorizing waste biomass while achieving a green synthesis of industrially relevant building blocks from sustainable sources. Here, we built and characterized enzyme cascades that create aldehydes and subsequently primary amines from diverse lignin‐derived carboxylic acids using a carboxylic acid reductase (CAR) and an ω‐transaminase (TA). Unlike previous studies that have paired CAR and TA enzymes, here we examine multiple homologs of each of these enzymes and a broader set of candidate substrates. In addition, we compare the performance of these systems in cell‐free and resting whole‐cell biocatalysis formats using the conversion of vanillate to vanillyl amine as model chemistry. We also demonstrate that resting whole cells can be recycled for multiple batch reactions. We used the knowledge gained from this study to produce several amines from carboxylic acid precursors using one‐pot biocatalytic reactions, several of which we report for the first time. These results expand our knowledge of these industrially relevant enzyme families to new substrates and contexts for environmentally friendly and potentially low‐cost synthesis of diverse aryl aldehydes and amines.

Biotechnology & Applied Microbiology↗

A direct transcription-based multiple shooting formulation for dynamic optimization

The growing need for fast and efficient solution techniques for solving dynamic optimization problems is driven by a broad spectrum of applications in scheduling and control. We suggest a novel framework for dynamic optimization that utilizes a multiple shooting “backbone” with discrete rather than continuous subproblems, thereby eliminating need for repeated time-integration. A Lagrangian relaxation (LR)-based decomposition scheme is proposed, which dualizes the state continuity requirements between subproblems and enables parallel solution of the problem. We demonstrate the applicability of our method on two case studies: the Van der Pol oscillator and a batch reactor.

42 ENGINEERING↗

A dimensionless number for high-throughput design of multi-principal element alloys in directed energy deposition

The present study demonstrates the development of a dimensionless number to predict the build height in the additive manufacturing technique of directed energy deposition (DED). The build height can also be used to estimate the dendrite arm spacing and, thus, the cooling rate in the fabrication of samples. A baseline sample, 316L stainless steel, was used to fit the build height to the dimensionless number. A range of process parameters, including laser power, laser feed rate, powder flow rate, layer thickness, and hatch spacing, were varied. Based upon dendrite arm spacing, the estimated cooling rate varied between 102 and 104 K/s. Using the fitted relationship for the stainless steel, high-throughput (HT) processing of multi-principal element alloys (MPEAs) was performed. For this study, HT is the ability to fabricate a batch of 25 bulk samples (∼1 cm3) with different compositions within a 5-h period with ±10 at. % accuracy. A range of compositions using in situ alloying of elemental powders in the Fe–Ni–Cr–Mo system were made. The MPEAs' build height followed the same relationship to the dimensionless number as the 316L alloy. The dimensionless number predicts both macro and meso-scale features in HT processing, thus offering a design tool for choosing process parameters in DED additive manufacturing. Also, the ability to control or increase cooling rates can enhance the ability to promote metastability as well as control meso-scale chemical distributions of alloy samples.

Islam, Zahabul (ORCID:0000000169613209)↗

Towards Low-Overhead Resilience for Data Parallel Deep Learning

Data parallel techniques have been widely adopted both in academia and industry as a tool to enable scalable training of deep learning models. At scale, DL training jobs can fail due to software or hardware bugs, may need to be preempted or terminated due to unexpected events, or may perform suboptimally because they were misconfigured. Under such circumstances, there is a need to recover and/or reconfigure data-parallel DL training jobs on-the-fly, while minimizing the impact on the accuracy of the DNN model and the runtime overhead. In this regard, state-of-art techniques adopted by the HPC community mostly rely on checkpoint-restart, which inevitably leads to loss of progress, thus increasing the runtime overhead. In this paper we explore alternative techniques that exploit the properties of modern deep learning frameworks (overlapping of gradient averaging and weight updates with local gradient computations through pipeline parallelism) to reduce the overhead of resilience/elasticity. To this end we introduce a failure simulation framework and two resilience strategies (immediate mini-batch rollback and lossy forward recovery), which we study compared with checkpoint-restart approaches in a variety of settings in order to understand the trade-offs between the accuracy loss of the DNN model and the runtime overhead.

data-parallel training↗

Plutonium Retention by Crystalline Silicotitanate under Hyperalkaline Conditions Relevant to Tank-Side Cesium-Removal at the Hanford Site

Crystalline silicotitanate (CST) is used in Hanford’s Tank-Side Cesium-Removal (TSCR) process to selectively remove Cs-137 from highly caustic, nitrate-rich tank supernatants. Recent testing with actual waste samples suggests that CST can also retain measurable plutonium (Pu), which could affect radiological classification and disposal pathways for spent CST. To quantify this behavior, Pu partitioning to CST was studied under Hanford-relevant conditions using batch-contact experiments in a representative simulant (2 M NaNO3, 0.7 M NaOH). Isotherm data were measured and distribution ratios calculated, with Cs+ uptake used as benchmark. Under low-carbonate conditions, Pu was retained strongly by CST in systems initially contacted with either PuO2 nanoparticles (Pu(IV)) or aqueous Pu(VI), with distribution ratios of ~2,200–3,700 mL/g, generally exceeding those for Cs+ (~400–1,000 mL/g). Increasing carbonate concentration strongly reduced PuO2 nanoparticle retention; at [Na2CO3] = 1 M, distribution ratios decreased by up to one order of magnitude to roughly 100–300 mL/g. Electron microscopy suggests that Pu retention involves a combination of mechanisms such as PuO2 NP aggregation induced by CST leachate components, and association with CST bead surfaces.

Neumann, J.↗

Viscous characteristics analysis

Program considers combustion and diffusive effects in analysis of supersonic, combustion-flow fields with imbedded subsonic regions. Effects of finite-rate chemistry, mixing, and wave propagation are linked together. Program handles up to 20 simultaneous shock waves. Some chemistry terms are computed for seven-species, eight-mechanism, hydrogen-and-air reaction scheme. Program is aid for supersonic-combustor development studies and is written in FORTRAN IV for batch execution on CYBER 175.

Jenkins, R. V.↗

An Empirical State Error Covariance Matrix Orbit Determination Example

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. First, consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. Then it follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix of the estimate will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully include all of the errors in the state estimate. The empirical error covariance matrix is determined from a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm. It is a formally correct, empirical state error covariance matrix obtained through use of the average form of the weighted measurement residual variance performance index rather than the usual total weighted residual form. Based on its formulation, this matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty and whether the source is anticipated or not. It is expected that the empirical error covariance matrix will give a better, statistical representation of the state error in poorly modeled systems or when sensor performance is suspect. In its most straight forward form, the technique only requires supplemental calculations to be added to existing batch estimation algorithms. In the current problem being studied a truth model making use of gravity with spherical, J2 and J4 terms plus a standard exponential type atmosphere with simple diurnal and random walk components is used. The ability of the empirical state error covariance matrix to account for errors is investigated under four scenarios during orbit estimation. These scenarios are: exact modeling under known measurement errors, exact modeling under corrupted measurement errors, inexact modeling under known measurement errors, and inexact modeling under corrupted measurement errors. For this problem a simple analog of a distributed space surveillance network is used. The sensors in this network make only range measurements and with simple normally distributed measurement errors. The sensors are assumed to have full horizon to horizon viewing at any azimuth. For definiteness, an orbit at the approximate altitude and inclination of the International Space Station is used for the study. The comparison analyses of the data involve only total vectors. No investigation of specific orbital elements is undertaken. The total vector analyses will look at the chisquare values of the error in the difference between the estimated state and the true modeled state using both the empirical and theoretical error covariance matrices for each of scenario.

Frisbee, Joseph H., Jr.↗

UAS Integration in the NAS Flight Test 6: Full Mission Results

Recent standards development efforts for the integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS) such as those in RTCA Inc. Special Committee 228 (SC-228) have focused on relatively large UAS transitioning to and from Class A airspace. In an effort to expand the range of vehicle classes that can access the NAS, the NASA UAS Integration in the NAS project has investigated Low Size, Weight, and Power (Low SWaP) technologies that would allow smaller UAS to detect-and-avoid (DAA) traffic. Through batch and human in the loop (HITL) simulation studies, the UAS Integration in the NAS DAA subproject have identified candidate performance standards that would contribute to enabling extended Low SWaP, UAS operations under 10,000 feet. These candidate performance standards include minimum field of regard (FOR) values for Low SWaP air surveillance sensors as well as a DAA well-clear (DWC) definition which can be applied to non-cooperative traffic to reduce the required maneuver initiation range. To test the assumptions of the project’s simulation studies and validate the candidate performance standards, a live flight research event was executed at NASA Armstrong Flight Research Center. The UAS Integration in the NAS Project Flight Test 6 Full Mission sought to characterize UAS pilot responses to traffic conflicts using a representative Low SWAP DAA system in an operational NAS environment. To achieve this, live, virtual and constructive distributed environment (LVC-DE) elements were combined to simulate a sector of Oakland center airspace and induce encounters with a live, manned aircraft. A Navmar Applied Sciences Tigershark XP was used as the UAS ownship and was integrated into the test architecture to enable it to be controlled from a Vigilant Spirit Control Station (VSCS) research ground control station. Qualified UAS pilots were recruited to act as subject pilots under test (SPUT) to control the Tigershark XP in a simulated mission while coordinating with a participating air traffic controller in simulated airspace. The intruder speed, intruder equipage and encounter geometry were varied between six scripted encounters per SPUT. Various metrics were collected including pilot reaction time from the onset of DAA alert, ATC coordination rate, probability and severity of losses of DAA well clear, and subjective ratings of system acceptability. The implications of these results on the development of standards for Low SWAP DAA systems will be discussed.

UAV↗

Statistical Analysis of Recent Go Around Flight Data to Study and Evaluate Skilled Pilot Monitoring

A statistical analysis was performed on a batch of recent go-around flight data of a few major US airlines spanning a one year period. The statistical analysis investigates a few select relevant aspects of these go arounds, such as initiation altitude and altitude change, aircraft configuration, deviation from the flightpath, and energy state. These data show that only one third of the landings are aborted below 400ft, but the majority of the go arounds occur at significantly higher altitudes. Current go-around training is specifically focused on the final approach and landing phase at low altitudes and low speeds. The results of this study will support the development of a broader set of relevant scenarios for an FAA simulator experiment to study and evaluate the skills of the pilots who monitor this wide spectrum of diverse go-around conditions, with the ultimate goal to help improve pilot go-around training and technologies.

go around↗