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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A model for discrete fracture-clay rock interaction incorporating electrostatic effects on transport

Abstract A model based on the code CrunchClay is presented for a fracture-clay matrix system that takes electrostatic effects on transport into account. The electrostatic effects on transport include those associated with the development of a diffusion potential as captured by the Nernst-Planck equation, and the formation of a diffuse layer bordering negatively charged clay particles within which partial anion exclusion occurs. The model is based on a dual continuum formulation that accounts for diffuse layer and bulk water pore space, providing a more flexible framework than is found in the classical mean electrostatic potential models. The diffuse layer model is obtained by volume averaging ion concentrations in the Poisson-Boltzmann equation, but also includes the treatment of longitudinal transport within this continuum. The calculation of transport within the bulk and diffuse layer porosity is based on a new formulation for the Nernst-Planck equation that considers averaging of diffusion coefficients and accumulation factors at grid cell interfaces. Equations for function residuals and the associated Jacobian matrix are presented such that the system of nonlinear differential-algebraic equations can be solved with Newton’s method. As an example, we consider a 2D system with a single discrete fracture within which flow and advective transport occurs that is coupled to diffusion in the clay-rich matrix. The simulation results demonstrate the lack of retardation for anions (e.g., 36 Cl − ) of the contaminant plume within the fracture flow system because they are largely excluded from the charged clay rock, while the migration of cations (e.g., 90 Sr ++ ) is more strongly attenuated. The diffusive loss of divalent cations in particular from the fracture is accentuated by their accumulation in the diffuse layer within the clay-rich matrix.

58 GEOSCIENCES↗
DOE OSTI2023

Techno-economic and life cycle analyses for a supercritical biodiesel production process from waste cooking oil for a plant located in the Midwest United States

Existing literature lacks detailed techno-economic and environmental life cycle analyses (TEA-LCA) focused on supercritical biodiesel production pathways produced via waste products. Therefore, in this work, the TEA-LCA was conducted to generate supercritical biodiesel from waste cooking oil for plants located in the Midwest region of USA having annual production capacities of 10,600 and 128,000 t using Aspen Plus and GREET softwares. Here, two plant production capacities were chosen to capture the economies of scale impact on biodiesel manufacture cost. In the supercritical process, methanol and propane were used as a cosolvent to synthesize biodiesel from waste cooking oil (WCO) at 280 °C and 128 bar at a residence time of 8.4 min and a WCO conversion rate of 97%. Economic analysis revealed that the supercritical process was an economically attractive pathway with a 2-year payback period for the 10,600 t/year capacity along with a break-even selling price of $\$$ 2.42/gal of diesel. In case of the larger plant (128,000 t/year capacity), the payback period and the breakeven selling price were considerably lower at values of 0.4 years and $1.31/gal of diesel, respectively, due to economies of scale impact. The generated biodiesel from supercritical process for the both the plant capacities met European (EN14214) and US (ASTM D6751) fuel quality standards while the obtained commercially valuable side product, i.e., glycerol, adhered to a pharmaceutical grade of 99.7%. Cradle to gate life cycle analysis using GREET revealed that supercritical process possessed 17% lower CO2 emissions than alkali-catalyzed process and 4% lower CO2 emissions than the conventional diesel production process. Other biodiesel production pathways in the literature were also compared to the results of the TEA-LCA of supercritical biodiesel production pathway.

Biodiesel production↗
DOE OSTI2022

Modeling receptor flexibility in the structure-based design of KRAS G12C inhibitors

KRAS has long been referred to as an ‘undruggable’ target due to its high affinity for its cognate ligands (GDP and GTP) and its lack of readily exploited allosteric binding pockets. Recent progress in the development of covalent inhibitors of KRAS G12C has revealed that occupancy of an allosteric binding site located between the α3-helix and switch-II loop of KRAS G12C —sometimes referred to as the ‘switch-II pocket’—holds great potential in the design of direct inhibitors of KRAS G12C . In studying diverse switch-II pocket binders during the development of sotorasib (AMG 510), the first FDA-approved inhibitor of KRAS G12C , we found the dramatic conformational flexibility of the switch-II pocket posing significant challenges toward the structure-based design of inhibitors. Here, we present our computational approaches for dealing with receptor flexibility in the prediction of ligand binding pose and binding affinity. For binding pose prediction, we modified the covalent docking program CovDock to allow for protein conformational mobility. This new docking approach, termed as FlexCovDock, improves success rates from 55 to 89% for binding pose prediction on a dataset of 10 cross-docking cases and has been prospectively validated across diverse ligand chemotypes. For binding affinity prediction, we found standard free energy perturbation (FEP) methods could not adequately handle the significant conformational change of the switch-II loop. We developed a new computational strategy to accelerate conformational transitions through the use of targeted protein mutations. Using this methodology, the mean unsigned error (MUE) of binding affinity prediction were reduced from 1.44 to 0.89 kcal/mol on a set of 14 compounds. These approaches were of significant use in facilitating the structure-based design of KRAS G12C inhibitors and are anticipated to be of further use in the design of covalent (and noncovalent) inhibitors of other conformationally labile protein targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A deep learning framework for layer-wise porosity prediction in metal powder bed fusion using thermal signatures

Abstract Part quality manufactured by the laser powder bed fusion process is significantly affected by porosity. Existing works of process–property relationships for porosity prediction require many experiments or computationally expensive simulations without considering environmental variations. While efforts that adopt real-time monitoring sensors can only detect porosity after its occurrence rather than predicting it ahead of time. In this study, a novel porosity detection-prediction framework is proposed based on deep learning that predicts porosity in the next layer based on thermal signatures of the previous layers. The proposed framework is validated in terms of its ability to accurately predict lack of fusion porosity using computerized tomography (CT) scans, which achieves a F1-score of 0.75. The framework presented in this work can be effectively applied to quality control in additive manufacturing. As a function of the predicted porosity positions, laser process parameters in the next layer can be adjusted to avoid more part porosity in the future or the existing porosity could be filled. If the predicted part porosity is not acceptable regardless of laser parameters, the building process can be stopped to minimize the loss.

42 ENGINEERING↗
DOE OSTI2020

Synchrotron CT imaging of lattice structures with engineered defects

Understanding mechanical failure, crack propagation, and compressive behavior at the micrometer scale is essential for tailoring material properties for structural performance in cellular materials. Typically, modeling of traditional polymer foam materials is clouded by the lack of control in material morphology and its inherent stochastic structure. Additive manufacturing with sub-micrometer resolution provides a direct path for experimenters to specifically tailor structures needed by modelers to explicitly probe mechanical performance. Using laboratory-based 3D X-ray computed tomographic imaging (CT), the examination of deformation and damage provides a critical path to understand how these soft materials behave. Additionally, synchrotron CT yields realistic information at higher strain rates to directly validate the robustness of our finite element modeling. For this study, nanolithographic printing was employed to generate a series of engineered lattices with increasing levels of defects through the random removal of ligaments. These structures were mechanically tested and imaged with laboratory-based microCT. Additionally, synchrotron experiments were conducted in which the structures were imaged in 3D at 14 Hz during compression at a 0.4 s –1 strain rate. These 3D images show the changes in the structure as the ligaments bend, buckle and fracture in real time. This technique provides a robust framework for developing our methodologies and future exploration of engineered structures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Virtual diffraction simulations using the quasi-coarse-grained dynamics method to understand and interpret plasticity contributions during in situ shock experiments

The dynamic deformation response of metallic materials has contributions from dislocations, deformation twinning, and plastic deformation. The current state-of-art techniques can detail the complex mechanistic history of deformation modes under shock loading in real-time using in situ X-ray diffraction (XRD). However, the capability of these experiments to unravel plasticity contributions is challenging due to limitations in interpreting results and the lack of validation from atomistic simulations. Molecular dynamics (MD) simulations can successfully capture various deformation modes in metals and complement experiments using simulated diffractograms at various stages of evolution. However, the difference in length and time scales of MD simulations and experiments is a substantial obstacle in completing and interpreting in situ diffractograms. Therefore, the existing modeling methods require various approximations to model defect evolution and interaction at the mesoscales. However, while using approximations to correlate the peak broadening behavior to the density of dislocations or the shifts/splitting due to the presence of twins, the interpretations of the plasticity contributions from diffractograms are non-trivial, especially when multiple modes of deformation may be operating. This viewpoint discusses combining a mesoscale modeling method called quasi-coarse-grained dynamics and virtual XRD to characterize the plasticity contributions in BCC metals from slip, twinning, and phase transformation behavior. Furthermore, the combined approach shows promise in bridging the mesoscale gap between the capabilities of atomic-scale simulations and in situ experiments to characterize the dynamic deformation of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Rethinking radiation effects in materials science using the plasma-focused ion beam

This work demonstrates the viability of using a plasma-focused ion beam (PFIB) as a new platform to carry out radiation effects studies in solids. While materials subjected to irradiation in either nuclear reactors or energetic particle accelerators experience limitations with respect to inaccuracies in both flux measurements and lack of precise control of irradiation areas, we demonstrate a new irradiation technique that allows the exposure of a single specimen in multiple areas, at multiple doses, and in site-specific dependencies - all with flux variations on the order of only 1%. This versatile technique also allows materials to be exposed to significantly higher irradiation dose rates than conventional accelerators. To validate the new methodology, we selected the classical example of ion-beam-induced amorphization of pure single-crystal Si. By pioneering the use of the PFIB for radiation effects studies in materials science, we were able to exploit, in both micro- and nanometer-sized detail, the differences in electron image contrast arising from crystalline versus amorphous solid-state phases in classical semiconductors subjected to irradiation, thus providing new insights on amorphization mechanisms. This methodology opens new research frontiers at the fringe of materials science with promising applications beyond the scope of materials at extremes such as in nanopatterning, nanodevices and nanoarchitectonics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Lithium Divertor Targets and Walls for the ASTER Liquid Stellarator Reactor, Distributed Divertor

Stellarators may have advantages for certain liquid metal options as Plasma Facing Components (PFC) for divertor targets and first walls due to the wide range of possible magnetic configurations, which additionally are free of disruptions and fast field variations. In a previous work (V. Queral et al., IEEE Trans. Plasma Sci. 52, 2024), a concept of stellarator reactor (ASTER-CP) based on swirling Li-molten salts and liquid lithium floating on the molten salt as PFC was presented. The divertor matters were not studied then and, thus, they are being studied and experimentally tested now. The ASTER-CP reactor concept, the initial liquid metal experiments and potential concepts for the ASTER-CP divertor and first wall are reported. Concerning the experiments, several small scale experiments of galinstan in a small rotating cylinder under magnetic field have been produced, including one experiment with high viscosity galinstan-mixture for increased thickness of layer. An experiment of floating lithium on the molten salt LiCl-PbCl2 gave fast volatilization/decomposition of the molten salt. Particularly for divertors, the traditional free-flow, Capillary Porous Systems and ‘divertorlets’ have been studied for application to ASTER-CP. Surface waves (hot spots), lack of enough surface fluid turbulence and excessive fluid speed are the main issues found in fast free-flow. The perhaps original concept of Distributed Divertor and Equi-power Surface is tentatively proposed and studied, taking advantage of stellarator fields and low recycling regime.

distributed divertor↗
DOE OSTI2025

Experimental Realization of One-Dimensional Helium

Abstract As the spatial dimension is lowered, locally stabilizing interactions are reduced, leading to the emergence of strongly fluctuating phases of matter without classical analogues. Realizing 1D platforms has been elusive, due to their inherent lack of stability, with a few notable exceptions such as spin chains and ultracold low-density gasses. The inability of such systems to exhibit long range order is essential to their universal description in terms of the Tomonaga-Luttinger liquid theory. Here we report on the experimental observation of a one-dimensional quantum liquid of $$^4$$ 4 He using nanoengineering to confine it within a porous material preplated with a noble gas to enhance dimensional reduction. The resulting excitations of the confined $$^4$$ 4 He, confirmed by neutron scattering, are qualitatively different than three- and two-dimensional superfluid helium, and consistent with Quantum Monte Carlo calculations. The results can be analyzed in terms of a mobile impurity in an otherwise linear Luttinger liquid allowing for the extraction of the microscopic parameters describing the emergent quantum liquid.

Sokol, Paul E.↗
DOE OSTI2020

Stability Analysis of Interface Conditions for Ocean-Atmosphere Coupling

In this paper, we analyze the stability of different coupling strategies for multidomain PDEs that arise in general circulation models used in climate simulations. We focus on fully coupled ocean–atmosphere models that are needed to represent and understand the complicated interactions of these two systems, becoming increasingly important in climate change assessment in recent years. Numerical stability issues typically arise because of different time-stepping strategies applied to the coupled PDE system. In particular, the contributing factors include using large time steps, lack of accurate interface flux, and single-iteration coupling. We investigate the stability of the coupled ocean–atmosphere models for various interface conditions such as the Dirichlet–Neumann condition and the bulk interface condition, which is unique to climate modeling. By analyzing a simplified model, we demonstrate here how the parameterization of the bulk condition and other numerical and physical parameters affect the coupling stability and establish stability conditions for different coupling strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

An interlaboratory collaboration to determine consensus 231 Pa/ 235 U model ages of a uranium certified reference material for nuclear forensics

Application of the 231 Pa/ 235 U radiochronometer for nuclear forensic investigations is challenged by a lack of certified reference materials with 231 Pa/ 235 U model purification dates. The Japan Atomic Energy Agency, Los Alamos National Laboratory, and Lawrence Livermore National Laboratory completed an interlaboratory study measuring 231 Pa/ 235 U model ages of New Brunswick Laboratory CRM U100. Results from independent laboratories were combined to calculate a consensus 231 Pa/ 235 U model purification date for CRM U100 of March 26, 1959 ± 237 days. This 231 Pa/ 235 U consensus date for CRM U100 may be used by the nuclear forensic community for quality control of 231 Pa/ 235 U radiochronometry measurements of unknown materials.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

New measurements of gamma-ray energies and their absolute intensities from the decay of 231 Pa

Accurate nuclear data for the decay of 231 Pa is highly important for non-destructive analysis in the areas of radiochronometry and nuclear forensics. However, the evaluated nuclear data for this isotope is lacking; many previous measurements have large uncertainties and only two measurements are used to determine the absolute intensities. In this work, we present modern measurements of the major gamma-ray emissions from the decay of 231 Pa to 227 Ac including the energies and absolute intensities. For many of these measurements, the error envelopes have been significantly decreased compared to previous measurements, while remaining in good agreement. The absolute intensity of the 283 keV reference line was measured as 0.0163(2).

231Pa↗
DOE OSTI2024

Linkages between riverine flooding risk and economic damage over the continental United States

Economic damages from riverine flooding are expected to grow because of climate change. Yet, there are few 7 studies analyzing flooding damages in the U.S. that clearly measure the roles of hazard, exposure, and vulnerability 8 separately and locally. A lack of this knowledge prohibits spatially detailed predictions of future damages. By being 9 able to separate into these three risk factors, we provide all necessary inputs for uncertainty analysis of the flooding-10 damages forecasts that can incorporate new predictive scenarios for each component. To analyze the flooding risk 11 factors of non-coastal counties within the contiguous U.S. between 1999-2018, we gathered information on (1) 12 property and human damages from flooding, (2) maximum annual river discharge, (3) the number of housing units 13 and the years in which they were built, and (4) the incidence of flooding events. We used the method of trimmed 14 least absolute deviated and trimmed least square estimators to obtain the individual impact of hazard, exposure, and 15 vulnerability in the context of censored flooding damages for panel data. The resulting estimates indicate that 16 exposure has been the main driver of flooding risk for most counties in the U.S. Here, we use these estimates to describe 17 the main source of flooding risk for non-coastal counties for the 1999-2018 period.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Lagrangian dual method for two-stage robust optimization with binary uncertainties

This report presents a new exact method to calculate worst-case parameter realizations in two-stage robust optimization problems with categorical or binary-valued uncertain data. Traditional exact algorithms for these problems, notably Benders decomposition and column-and-constraint generation, compute worst-case parameter realizations by solving mixed-integer bilinear optimization subproblems. However, their numerical solution can be computationally expensive not only due to their resulting large size after reformulating the bilinear terms, but also because decision-independent bounds on their variables are typically unknown. We propose an alternative Lagrangian dual method that circumvents these difficulties and is readily integrated in either algorithm. We specialize the method to problems where the binary parameters switch on or off constraints as these are commonly encountered in applications, and discuss extensions to problems that lack relatively complete recourse and to those with integer recourse. Numerical experiments provide evidence of significant computational improvements over existing methods.

42 ENGINEERING↗
DOE OSTI2021

Lessons Learned in Employing Data Analytics to Predict Oxidation Kinetics and Spallation Behavior of High-Temperature NiCr-Based Alloys

Machine learning (ML) can offer many advantages in predicting material properties over traditional materials development methods based solely on limited experimental investigations or physical-based simulations with the capability to reduce development cost, risk, and time. However, so far, limited efforts have been made to predict alloy oxidation kinetics and spallation behavior via ML due to the lack of consistently measured and sufficient experimental data and the inherent complexity in oxidation behavior of multicomponent high-temperature alloys. A previous study reported the ability of ML to predict oxidation kinetics of NiCr-based alloys as a function of alloy composition and operating conditions. Here, the performance of a ML model in predicting rate constants and spallation probability was evaluated in light of the roles of the data distribution of the experimental dataset (data analytics), the alloy composition, the exposure environment and the chosen oxidation approach to extracting kinetic values from the measured mass changes (but using either a simple parabolic law or a statistical cyclic oxidation model). Potential strategies to improve the predictions and enhance the extrapolative capability of the previously trained model will be discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Identifying Regimes During Plasma Catalytic Ammonia Synthesis

Herein, we demonstrate that the performance of mesoporous silica SBA-15 and SBA-15-Ag during plasma ammonia synthesis depends on the plasma conditions. At high power, the mesoporous silica SBA-15 without Ag produces the largest amount of ammonia, but the addition of Ag provides a minor benefit at lower powers. Plasma conditions were analyzed through optical emission spectroscopy using N 2 , N 2 + , and NH molecular bands and H α line. Stark broadening of H α line was used to find electron density, and N 2 molecular bands were used to assess N 2 vibrational excitation, important for plasma nitrogen decomposition. At similar input conditions, reactors with SBA-15 have higher electron density and higher N 2 vibrational temperature. Consistent with higher electron density, SBA-15 reactors have stronger N 2 + emission intensity relative to the neutral N 2 . The addition of Ag results in higher N 2 rotational temperature, possibly due to localized heating. From the materials point of view, SBA-15 is a more robust catalyst with good surface area retention after plasma exposure due to the lack of local heating generated when a metal is in the structure. Furthermore, we identify two possible regimes during ammonia synthesis, a metal and a surface-plasma driven. At lower plasma densities, the addition of metal is beneficial, while at higher power and plasma density, the best performance is achieved without the aid of a metal catalyst.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Plasma Bubble Column Reactor: A High Throughput Reactor Design for Water Treatment

Plasma-based water treatment (PWT) is a promising technology that can degrade various emerging contaminants. However, PWT application on an industrially viable scale is hindered by the lack of an efficient reactor design that combines enhanced plasma-liquid contact with high liquid throughput. This work investigates the applicability of a bubble column gas-liquid contactor to PWT. A pulsed plasma bubble column reactor (PBCR) with a concentric rod-cylinder electrode configuration was used to correlate contaminant removal performance with the gas-liquid contact parameters of the bubble column. A surfactant, rhodamine B dye, and a nonsurfactant, caffeine, were used as model contaminants at µM concentration levels. The bubble column characteristics, i.e., gas holdup, bubble size distribution, and gas-liquid area, were measured as a function of superficial gas velocity using image-based methods. Degradation rates of both contaminants increased with gas flowrate. For caffeine, the increase was attributed to intensified bulk liquid mixing, while dye degradation increased due to the increased gas-liquid area. Ultimately, we show that bubble column contactors significantly improve the utilization of plasma-generated reactive species toward contaminant degradation by distributing them over a large contact area. As a result, a better match between the plasma species interfacial flux and the interfacial contaminant concentration leads to improved treatment energy efficiency. Furthermore, typical degradation energy efficiencies were ~10 g/kWh for caffeine and ~60 g/kWh for rhodamine B.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Dynamics of N 2 O in vicinity of plant residues: a microsensor approach

Plant residues decomposing within the soil matrix are known to serve as hotspots of N 2 O production. However, the lack of technical tools for microscale in-situ N 2 O measurements limits understanding of hotspot functioning. Our aim was to assess performance of microsensor technology for evaluating the temporal patterns of N 2 O production in immediate vicinity to decomposing plant residues. We incorporated intact switchgrass leaves and roots into soil matrix and monitored O 2 depletion and N 2 O production using electrochemical microsensors along with N 2 O emission from the soil. We also measured residue’s water absorption and b-glucosidase activity on the surface of the residue - the characteristics related to microenvironmental conditions and biological activity near the residue. N 2 O production in the vicinity of switchgrass residues began within 0–12 h after the wetting, reached peak at ~0.6 day and decreased by day 2. N 2 O was higher near leaf than near root residues due to greater leaf N contents and water absorption by the leaves. However, N 2 O production near the roots started sooner than near the leaves, in part due to high initial enzyme levels on root surfaces. Electrochemical microsensor is a useful tool for in-situ micro-scale N 2 O monitoring in immediate vicinity of soil incorporated plant residues. Monitoring provided valuable information on N 2 O production near leaves and roots, its temporal dynamic, and the factors affecting it. The N 2 O production from residues measured by microsensors was consistent with the N 2 O emission from the whole soil, demonstrating the validity of the microsensors for N 2 O hotspot studies.

59 BASIC BIOLOGICAL SCIENCES↗