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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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Nuclear material input accountancy with a representative sampling method
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Modeling and experimental validation of rotary riffling method for nuclear material input accountancy
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Intrinsic DNA Shape Accounts for Affinity Differences between Hox-Cofactor Binding Sites
Abstract not provided
Investigation of the changes in microstructure and transport properties of leached cement pastes accounting for mix composition
Ca-leaching of cement-based materials induces detrimental effects on properties related to long-term durability. A better understanding of leaching degradation in terms of alterations in mineralogy, microstructure, and transport properties is important for long-term assessments of concrete and reinforced concrete structures used in nuclear waste disposal systems or in hydro structures. However, the decalcification process is not easy to study because it is extremely slow. In this study, an ammonium nitrate (NH{sub 4}NO{sub 3}) solution of 6 mol/l was used to accelerate the leaching kinetics. The experiments were performed on cement paste samples with different water/powder (w/p) and limestone filler (LS) replacement ratios. Both the change of sample mass over time and the amount of calcium ion leached out were monitored during the test. Different post-analysis techniques including SEM/SEM-EDX, XRD/QXRD, MIP, ion chromatography, and N{sub 2}-adsorption were used to characterize the microstructural and mineralogical changes. The effect of accelerated leaching on transport properties was studied by measuring the changes in water permeability and diffusivity of dissolved gases. Results showed that the square-root-time law of degradation was applicable under accelerated conditions. Both higher w/p ratios and LS replacements increased the rate of leaching propagation; the former had a more significant effect. The accelerated leaching significantly altered the microstructure of the cement paste to a material with a higher specific surface area, increased total porosity and a shift to larger pore sizes. Those changes led to a significant increase in water permeability (one to two orders of magnitude) and diffusivity (less than one order) depending on degradation state.
A new phase field fracture model for brittle materials that accounts for elastic anisotropy
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Three-dimensional traction microscopy accounting for cell-induced matrix degradation
Tractions exerted by cells on the extracellular matrix (ECM) are critical in many important physiological and pathological processes such as embryonic morphogenesis, wound healing, and cancer metastasis. Three-dimensional Traction Microscopy (3DTM) is a tool to quantify cellular tractions by first measuring the displacement field in the ECM in response to these tractions, and then using this measurement to infer tractions. Most applications of 3DTM have assumed that the ECM has spatially-uniform mechanical properties, but cells secrete enzymes that can locally degrade the ECM. In this work, a novel computational method is developed to quantify both cellular tractions and ECM degradation. In particular, the ECM is modeled as a hyperelastic, Neo-Hookean solid, whose material parameters are corrupted by a single degradation parameter. The feasibility of determining both the traction and the degradation parameter is first demonstrated by showing the existence and uniqueness of the solution. An inverse problem is then formulated to determine the nodal values of the traction vector and the degradation parameter, with the objective of minimizing the difference between a predicted and measured displacement field, under the constraint that the predicted displacement field satisfies the equation of equilibrium. The inverse problem is solved by means of a gradient-based optimization approach, and the gradient is computed efficiently using appropriately derived adjoint fields. The computational method is validated in-silico using a geometrically realistic neuronal cell model and synthetic traction and degradation fields. It is found that the method accurately recovers both the traction and degradation fields. Moreover, it is found that neglecting ECM degradation can yield significant errors in traction measurements. Finally, our method can extend the range of context where tractions can be appropriately measured.
Uncertainty quantification of reaction mechanisms accounting for correlations introduced by rate rules and fitted Arrhenius parameters
We study correlations among uncertain Arrhenius rate parameters in a chemical model for hydrocarbon fuel-air combustion. We consider correlations induced by the use of rate rules for modeling reaction rate constants, as well as those resulting from fitting rate expressions to empirical measurements arriving at a joint probability density for all Arrhenius parameters. We focus on homogeneous ignition in a fuel-air mixture at constant-pressure. We also outline a general methodology for this analysis using polynomial chaos and Bayesian inference methods. Finally, we examine the uncertainties in both the Arrhenius parameters and in predicted ignition time, outlining the role of correlations, and considering both accuracy and computational efficiency.
Three-dimensional phase field sintering simulations accounting for the rigid-body motion of individual grains
Sintering is a widely used powder processing technique in industrial applications. During sintering, atoms migrate to decrease the energy of the system via two main mechanisms: coarsening and densification, both of which lead to significant morphological variation of the sintered microstructure. When simulating sintering dynamics, the phase-field method has been broadly utilized because of its convenience in tracking morphology evolution. When a large number of grains is involved, it is common to use the same order parameter to describe multiple grains that are not in direct contact with one another (in order to reduce the computational memory demands). However, with this treatment it is difficult to handle the rigid-body motion of individual grains during densification. In this work, an implementation scheme is introduced to overcome the challenge of calculating individual particle motion based on existing equations. It uses a grouping algorithm and sets a cutoff radius on each grain for calculating the particle velocity during densification. This method allows for the incorporation of the densification mechanism, which has been commonly ignored in previous work, into phase-field sintering models in three-dimensional simulations with a large number of particles/grains. Moreover, through combination with the smoothed boundary method, material properties of sintered microstructures, such as the effective diffusivity and Young’s modulus, can be calculated during the sintering processes.
Anisotropic thermal-conductivity degradation in the phase-field method accounting for crack directionality
Dynamic loads applied to metals may lead to brittle or ductile fracture depending on the imposed strain rates, material properties, and specimen geometry. With an increase in the applied velocity, brittle to ductile failure mode transition may also be observed. Furthermore, at high strain rates, ductile fracture may be preceded by shear bands, which are narrow bands of intense plastic deformation, typically accompanied by a significant rise in temperature. Reliable models are needed to predict the response of metals subject to dynamic loads. In particular, capturing the interplay between heat conduction and crack propagation using the phase-field fracture method is still an open research field. To accurately capture the heat transfer physics across crack surfaces, damage models degrading thermal-conductivity are necessary. While isotropic thermal-conductivity degradation models were proposed, they may lead to errors as they are indifferent to crack directionality. In our current work, a new anisotropic approach is proposed in which thermal-conductivity, which depends on the phase-field gradient, is degraded solely across the crack. Here, it is shown that this approach improves the near-field approximation of temperature and heat flux compared with isotropic degradation, when taking the discontinuous crack solutions as reference. Additionally, the anisotropic degradation approach is implemented in a unified dynamic fracture model and a couple of examples demonstrate the viability of this approach.
Taking into account greenhouse gas emissions of electric vehicles for transportation de-carbonization
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Accounting for adaptation and intensity in projecting heat wave-related mortality
Highlights: • We propose novel models for intensity of and adaptation to heat waves in projections of heat wave- mortality. • The modeling used a large national dataset and the projections used a rich set of climate models and scenarios. • Future heat wave-related mortality would be substantially overestimated, if adaptation were ignored. • The time trend of future heat wave-related mortality will vary substantially across climate regions. How adaptation and intensity of heat waves affect heat wave-related mortality is unclear, making health projections difficult.
Comparative estrogenicity of endogenous, environmental and dietary estrogens in pregnant women II: Total estrogenicity calculations accounting for competitive protein and receptor binding and potency
Evaluating the biological significance of human-relevant exposures to environmental estrogens involves assessing the individual and total estrogenicity of endogenous and exogenous estrogens found in serum, for example from biomonitoring studies. We developed a method for this assessment by integrating approaches for (i) measuring total hormone concentrations by mass spectrometry (Fleck et al., 2017), (ii) calculating hormone bioavailable concentrations in serum and, (iii) solving multiple equilibria between estrogenic ligands and receptors, and (iv) quantitatively describing key elements of estrogen potency. The approach was applied to endogenous (E1, E2,E3, E4), environmental (BPA), and dietary Genistein (GEN), Daidzein (DDZ) estrogens measured in the serum of thirty pregnant women. Fractional receptor occupancy (FRO) based estrogenicity was dominated by E1, E2 and E3 (ER-a, 94.4–99.2% (median: 97.3%), ER-ß, 82.7–97.7% (median: 92.8%), as was the total response (TR), which included ligand specific differences in recruitment of co-activator proteins (RCA). The median FRO for BPA was at least fve orders of magnitude lower than E1, E2 and E3, and three orders of magnitude lower than the fetal derived E4 and GEN and DDZ. BPA contributed less than 1/1000th of the normal daily variability in total serum estrogenicity in this cohort of pregnant women.
State-of-the-art of data collection, analytics, and future needs of transmission utilities worldwide to account for the continuous growth of sensing data
Nowadays, transmission system operators require higher degree of observability in real-time to gain situational awareness and improve the decision-making process to guarantee a safe and reliable operation. Digitalization of energy systems allows utilities to monitor the system dynamic performance in real-time at fast time scales. The use of such technologies has unlocked new opportunities to introduce new data driven algorithms for improving the stability assessment and control of the system. Motivated by these challenges, a group of experts have worked together to highlight and establish a baseline set of these common concerns, which can be used as motivation to propose innovative analytics and data-driven solutions. In this document, the results of a survey on 10 transmission system operators around the world are presented and it aims to understand the current practices of the participating companies, in terms of data acquisition, handling, storage, modelling and analytics. The overall objective of this document is to capture the actual needs from the interviewed utilities, thereby laying the groundwork for setting valid assumptions for the development of advanced algorithms in this field.
How green is my oil? A detailed look at greenhouse gas accounting for CO2-enhanced oil recovery (CO2-EOR) sites
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