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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

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↗
DOE OSTI2017

Optimization principles and the figure of merit for triboelectric generators

Energy harvesting with triboelectric nanogenerators is a burgeoning field, with a growing portfolio of creative application schemes attracting much interest. Although power generation capabilities and its optimization are one of the most important subjects, a satisfactory elemental model that illustrates the basic principles and sets the optimization guideline remains elusive. We use a simple model to clarify how the energy generation mechanism is electrostatic induction but with a time-varying character that makes the optimal matching for power generation more restrictive. By combining multiple parameters into dimensionless variables, we pinpoint the optimum condition with only two independent parameters, leading to predictions of the maximum limit of power density, which allows us to derive the triboelectric material and device figure of merit. We reveal the importance of optimizing device capacitance, not only load resistance, and minimizing the impact of parasitic capacitance. Optimized capacitances can lead to an overall increase in power density of more than 10 times.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The Onset of Nucleate Boiling Prediction in a Mini Channel with the Eulerian Multiphase Flow

The prediction of boiling incipience is a critical issue for a reactor. Vapor lock causes operating instability and undesirable temperature rise, especially for small channels. This study uses the Eulerian multiphase flow boiling model to predict the onset of nucleate boiling in a millimeter scale rectangular channel. Two wall boiling models, namely the RPI (Rensselaer Polytechnic Institute) and the non-equilibrium sub cooled model are applied. Computational fluid dynamics is employed for this study to investigate the impact of operating conditions like liquid flow rate, operating pressure, heat flux, velocity profile, turbulence model, and inlet liquid temperature. Here, the effect of fundamental boiling parameters on the surface wall temperature and vapor volume fraction is also studied. The parameters under consideration are the bubble departure diameter, bubble departure frequency, nucleate site density, quenching time period, and interface heat transfer coefficients. A series of CFD calculations is conducted by varying the considered variables systematically in a wide range of flow conditions covering laminar, transition, and turbulent flows. The sub-component heat fluxes like the liquid convective, the vapor convective, the evaporative, and the quenching terms are monitored to infer the boiling dynamics in the transition region from the single-phase flow to the nucleate boiling zone. It is found that the CFD approach to detecting the boiling incipience point agrees reasonably with available experimental data. However, its limitations, like inaccuracy for lower flow rates and early transition to boiling flow, are also noticed due to the nature of the considered RPI model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Variation of Ionizing Continuum: The Main Driver of Broad Absorption Line Variability

We present a statistical analysis of the variability of broad absorption lines (BALs) in quasars using the large multi-epoch spectroscopic data set of the Sloan Digital Sky Survey Data Release 12 (SDSS DR12). We divide the sample into two groups according to the pattern of the variation of C iv BAL with respect to that of a continuum: the equivalent widths (EW) of the BAL decreases (increases) when the continuum brightens (dims) as group T1; and the variation of the EW and the continuum in the opposite relation of group T2. We find that T2 has significantly (P{sub T}<10{sup −6}, Students T Test) higher EW ratios (R) of Si iv to C iv BAL than T1. Our result agrees with the prediction of photoionization models that C{sup +3} column density increases (decreases) if there is a (or no) C{sup +3} ionization front, while R decreases with the incident continuum. We show that BAL variabilities in at least 80% of quasars are driven by the variation of an ionizing continuum, while other models that predict uncorrelated BAL and continuum variability contribute less than 20%. Considering large uncertainty in the continuum flux calibration, the latter fraction may be much smaller. When the sample is binned into different time intervals between the two observations, we find significant difference in the distribution of R between T1 and T2 in all time-bins down to ΔT<6 days, suggesting that the BAL outflow in a fraction of quasars has a recombination timescale of only a few days.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

PolyMat: an efficient Matlab code for multi-material topology optimization

We introduce a Matlab implementation of topology optimization for compliance minimization on unstructured polygonal finite element meshes that efficiently accommodates many materials and many volume constraints. Leveraging the modular structure of the educational code, PolyTop, we extend it to the multi-material version, PolyMat, with only a few modifications. First, a design variable for each candidate material is defined in each finite element. Next, we couple a Discrete Material Optimization interpolation with the existing penalization and introduce a new parameter such that we can employ continuation and smoothly transition from a convex problem without any penalization to a non-convex problem in which material mixing and intermediate densities are penalized. Mixing that remains due to the density filter operation is eliminated via continuation on the filter radius. To accommodate flexibility in the volume constraint definition, the constraint function is modified to compute multiple volume constraints and the design variable update is modified in accordance with the Zhang-Paulino-Ramos Jr. (ZPR) update scheme, which updates the design variables associated with each constraint independently. The formulation allows for volume constraints controlling any subset of the design variables, i.e., they can be defined globally or locally for any subset of the candidate materials. Borrowing ideas for mesh generation on complex domains from PolyMesher, we conclude which design variables are associated with each local constraint of arbitrary geometry. A number of examples are presented to demonstrate the many material capability, the flexibility of the volume constraint definition, the ease with which we can accommodate passive regions, and how we may use local constraints to break symmetries or achieve graded geometries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Influence of fixed charge concentration and water uptake on ion sorption in AMPS/PEGDA membranes

Water content and charge density strongly influence ion sorption in charged membranes. However, isolating the individual effect of each parameter on ion sorption can be difficult due to experimental challenges associated with independently controlling these two variables during membrane synthesis. This frustrates development and validation of fundamental models and structure/property relationships. In this study, three series of uncharged and negatively charged hydrogel membranes were prepared using poly(ethylene glycol) diacrylate (PEGDA) as a cross-linker and 2-acrylamido-2-methylpropanesulfonic acid (AMPS) as an ionic monomer. Here, water content and charge density were controlled by varying AMPS content and PEGDA chain length. Ion sorption in these materials was measured using aqueous NaCl solutions at concentrations ranging from 0.01 to 1.0 M. At constant charge density, salt sorption increased as water content increased. At fixed water content, salt sorption decreased as charge density increased. Salt sorption in membranes with the highest water content and charge density was predicted using the Donnan/Manning model, which accounts for solution and membrane phase thermodynamic non-idealities. However, this approach could not predict sorption in weakly charged and uncharged membranes, presumably due to additional membrane phase thermodynamic non-idealities associated with ion solvation and uncharged polymer segments.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Direct Demonstration of Unified Brønsted-Evans-Polanyi Relationships for Proton-Coupled Electron Transfer Reactions on Transition Metal Surfaces

Brønsted-Evans-Polanyi (BEP) relationships, which relate elementary reaction barriers to reaction thermodynamics, have long been discussed in electrochemical science, but demonstration of their existence in heterogeneous electrocatalysis, across many different catalyst surfaces and voltages, is lacking. In this contribution, the BEP model is demonstrated to describe both multiple catalyst surfaces and variable voltages in electrochemical environments. For proton-coupled electron transfer (PCET) to surface nitrogen (N*) and nitric oxide (NO*), reaction energies and activation barriers are calculated using Density Functional Theory (DFT) on a parallel plate capacitor model at three different potentials and for nine different transition metal surfaces. Linear BEP relations that describe all potentials and catalyst surfaces are obtained for these elementary reactions, and the slopes of the correlations are shown to be directly related to the fractional coordinate of the transition states (FCTS) of the reactions. The results, which are explained in terms of Marcus Theory, prove a direct equivalence between unified BEP coefficients, describing both variable catalyst surfaces and voltages, and electrochemical symmetry factors and provide a straightforward means of estimating this quantify for PCET reactions on transition metal surfaces. The resulting relationships, in turn, could lead to predictions of electrocatalytic reactivity trends of enhanced accuracy and efficiency.

Electrochemistry↗
DOE OSTI2020

Characterizing Variability in Lignocellulosic Biomass: A Review

Feedstock variability is a significant barrier to the scale-up and commercialization of lignocellulosic biofuel technologies. Variability in feedstock characteristics and behavior creates numerous challenges to the biorefining industry by affecting continuous operation and biofuels yields. Recently, feedstock variability is understood and explained largely on the basis of chemical composition. Physical and mechanical properties and behavior of lignocellulosic feedstock in various unit operations, studied through advanced analytical methods, can further explain variability. Such studies will enable us in developing processes and designing equipment to improve operation and conversion performance. In this perspective, we review several advanced analytical methods that measure density, moisture content, thermal properties, flowability, grindability, rheology properties, and micromorphological characteristics. We also discuss the correlations and interactions among these properties that reflect the complexity of lignocellulosic biomass as a feedstock and the associated quality metrics and logistics of supplying consistent quality feedstock to a biorefinery. We further examine methods that have not traditionally been used to characterize lignocellulosic feedstocks but have the potential to bridge the gap in our explanation of feedstock variability.

09 BIOMASS FUELS↗
DOE OSTI2024

Efficient particle control in systems with large density gradients

Simulations of large density gradients present a number of challenges for direct Monte Carlo methods, since they lead to too few particles in dilute regions and prohibitively many in the dense regions. Here, we propose a particle control methodology that gives the user more control of the number of particles per cell by introducing a variable weight for each particle. The proposed scheme is based on the stochastic weighted particle method, requires only small modifications to DSMC, and exactly conserves mass, momentum, and energy. In validation tests of systems with density ratios of order 102-104, we observe 101-102 times less variance in the dilute region compared to a DSMC solution with the same number of system particles, while introducing a moderate additional computational cost.

DSMC↗
DOE OSTI2024

Ensemble variational Fokker-Planck methods for data assimilation

Particle flow filters solve Bayesian inference problems by smoothly transforming a set of particles into samples from the posterior distribution. Particles move in state space under the flow of an McKean-Vlasov-Itˆo process. This work introduces the Variational Fokker-Planck (VFP) framework for data assimilation, a general approach that includes previously known particle flow filters as special cases. The McKean-Vlasov-Itˆo process that transforms particles is defined via an optimal drift that depends on the selected diffusion term. It is established that the underlying probability density - sampled by the ensemble of particles - converges to the Bayesian posterior probability density. For a finite number of particles the optimal drift contains a regularization term that nudges particles toward becoming independent random variables. Based on this analysis, we derive computationally-feasible approximate regularization approaches that penalize the mutual information between pairs of particles, and avoid particle collapse. Moreover, the diffusion plays a role akin to a particle rejuvenation approach that aims to alleviate particle collapse. The VFP framework is very flexible. Different assumptions on prior and intermediate probability distributions can be used to implement the optimal drift, and localization and covariance shrinkage can be applied to alleviate the curse of dimensionality. A robust implicit-explicit method is discussed for the efficient integration of stiff McKean- Vlasov-Itˆo processes. Here, the effectiveness of the VFP framework is demonstrated on three progressively more challenging test problems, namely the Lorenz ’63, Lorenz ’96 and the quasi-geostrophic equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Pursuing Heteroleptic Ligand Design Principles for Photoactive Fe Complexes with Ultrafast X-ray Emission and Variable-Temperature Optical Spectroscopies

Understanding the key parameters that govern the photophysical and photochemical properties of transition metal complexes is essential for the development of efficient photosensitizers for photocatalytic applications. Achieving this objective necessitates clear and detailed investigations of their electronic excited states, for which time-resolved metal Kβ X-ray emission spectroscopy (XES) has proven highly effective. Here, we present a time-resolved Fe Kβ XES study of a heteroleptic Fe(II) polypyridyl carbene complex, [Fe(phen) 2 (C 4 H 10 N 4 )] 2+ (1; phen = 1,10-phenanthroline), utilizing both the valence-to-core and Kβ mainline spectral regions, complemented by variable-temperature transient optical absorption (VT-TA) spectroscopy. Detailed analysis of the time-resolved Kβ XES data, supported by density functional theory (DFT) calculations and an Eyring analysis of the VT-TA data, reveals parallel excited state relaxation dynamics that support an assignment of the long-lived excited state to a triplet metal-centered state. Placing these results in the context of prior studies of heteroleptic Fe(II) polypyridyl cyanide complexes motivated a series of DFT calculations to investigate the effects of ligand structural flexibility and arrangement. These calculations reinforce the experimentally derived conclusion that constraining structural flexibility with multidentate ligands significantly impacts the excited state relaxation dynamics. Furthermore, our study emphasizes that the arrangement of strong field ligands in heteroleptic complexes substantially affects the energy of Jahn–Teller active triplet metal-centered states in low-spin d 6 metal complexes. Together, these findings provide synthetic design principles for extending metal-to-ligand charge transfer excited state lifetimes of heteroleptic Fe complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Analytical noise bias correction for precise weak lensing shear inference

Noise bias is a significant source of systematic error in weak gravitational lensing measurements that must be corrected to satisfy the stringent standards of modern imaging surveys in the era of precision cosmology. This paper reviews the analytical noise bias correction method and provides analytical derivations demonstrating that we can recover shear to its second order using the ‘renoising’ noise bias correction approach introduced by METACALIBRATION. We implement this analytical noise bias correction within the AnaCal shear estimation framework and propose several enhancements to the noise bias correction algorithm. We evaluate the improved AnaCal using simulations designed to replicate Rubin Legacy Survey of Space and Time (LSST) imaging data. These simulations feature semi-realistic galaxies and stars, complete with representative distributions of magnitudes and Galactic spatial density. We conduct tests under various observational challenges, including cosmic rays, defective CCD columns, bright star saturation, bleed trails, and spatially variable point spread functions. Our results indicate a multiplicative bias in weak lensing shear recovery of less than a few tenths of a per cent, meeting LSST Dark Energy Science Collaboration requirements without requiring calibration from external image simulations. Additionally, our algorithm achieves rapid processing, handling one galaxy in less than a millisecond.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Automated Design-for-Reliability of a Power Electronics Module

The design of a power electronics module is a multiphysics problem and involves electrical, thermal, and reliability targets and constraints. Although the electrical and thermal design consider multiple aspects such as materials, geometry, and energy losses, reliability design is often limited to the selection of the attachment materials and electrical interconnect types. In this paper, we incorporate reliability metrics in the design phase by investigating the impact of package geometry on the thermomechanical behavior of the die-attachment material. To this end, we conducted thermal and power cycling simulations of a commercial six-pack power module with silicon carbide devices to compute junction temperature and strain energy density per cycle, respectively. We performed multiple simulations with different geometric dimensions and established a correlation between input features and output variables using subspace-based dimension reduction. The machine learning-based dimension reduction method serves as a surrogate model, which can be employed to identify the optimal module design from a thermal and reliability standpoint.

design-for-reliability↗
DOE OSTI2023

The Coastal Carbon Library and Atlas: Open source soil data and tools supporting blue carbon research and policy

Abstract Quantifying carbon fluxes into and out of coastal soils is critical to meeting greenhouse gas reduction and coastal resiliency goals. Numerous ‘blue carbon’ studies have generated, or benefitted from, synthetic datasets. However, the community those efforts inspired does not have a centralized, standardized database of disaggregated data used to estimate carbon stocks and fluxes. In this paper, we describe a data structure designed to standardize data reporting, maximize reuse, and maintain a chain of credit from synthesis to original source. We introduce version 1.0.0. of the Coastal Carbon Library, a global database of 6723 soil profiles representing blue carbon‐storing systems including marshes, mangroves, tidal freshwater forests, and seagrasses. We also present the Coastal Carbon Atlas, an R‐shiny application that can be used to visualize, query, and download portions of the Coastal Carbon Library. The majority (4815) of entries in the database can be used for carbon stock assessments without the need for interpolating missing soil variables, 533 are available for estimating carbon burial rate, and 326 are useful for fitting dynamic soil formation models. Organic matter density significantly varied by habitat with tidal freshwater forests having the highest density, and seagrasses having the lowest. Future work could involve expansion of the synthesis to include more deep stock assessments, increasing the representation of data outside of the U.S., and increasing the amount of data available for mangroves and seagrasses, especially carbon burial rate data. We present proposed best practices for blue carbon data including an emphasis on disaggregation, data publication, dataset documentation, and use of standardized vocabulary and templates whenever appropriate. To conclude, the Coastal Carbon Library and Atlas serve as a general example of a grassroots F.A.I.R. (Findable, Accessible, Interoperable, and Reusable) data effort demonstrating how data producers can coordinate to develop tools relevant to policy and decision‐making.

Holmquist, James R.↗
DOE OSTI2017

The SCEC Unified Community Velocity Model Software Framework

Crustal seismic-velocity models and datasets play a key role in regional 3D numerical earthquake ground-motion simulation, full waveform tomography, and modern physics-based probabilistic earthquake-hazard analysis, as well as in other related fields, including geophysics and earthquake engineering. Most of these models and datasets, often collectively identified as Community Velocity Models (CVMs), synthesize information from multiple sources and are delivered to users in variable formats, including computer applications that allow for interactive querying of material properties, namely P- and S-wave velocities and density ρ. Computational users often require massive and repetitive access to velocity models and datasets, and such access is often unpractical and difficult due to a lack of standardized methods and procedures. To overcome these issues and to facilitate access by the community to these models, the Southern California Earthquake Center developed the Unified CVM (UCVM) software framework, an open-source collection of tools that enables users to access one or more seismic-velocity models, while providing a standard query interface. Here, we describe the research challenges that motivated the development of UCVM, its software design, development approach, and basic capabilities, as well as a few examples of seismic-modeling applications that use UCVM.

Geochemistry & Geophysics↗
DOE OSTI2017

Two Small Transiting Planets and a Possible Third Body Orbiting HD 106315

The masses, atmospheric makeups, spin–orbit alignments, and system architectures of extrasolar planets can be best studied when the planets orbit bright stars. We report the discovery of three bodies orbiting HD 106315, a bright (V = 8.97 mag) F5 dwarf targeted by our K2 survey for transiting exoplanets. Two small transiting planets are found to have radii 2.23{sub −0.25}{sup +0.30} R{sub ⊕} and 3.95{sub −0.39}{sup +0.42} R{sub ⊕} and orbital periods 9.55 days and 21.06 days, respectively. A radial velocity (RV) trend of 0.3 ± 0.1 m s{sup −1} day{sup −1} indicates the likely presence of a third body orbiting HD 106315 with period ≳160 days and mass ≳45 M {sub ⊕}. Transits of this object would have depths ≳0.1% and are definitively ruled out. Although the star has v sin i = 13.2 km s{sup −1}, it exhibits a short-timescale RV variability of just 6.4 m s{sup −1}. Thus, it is a good target for RV measurements of the mass and density of the inner two planets and the outer object’s orbit and mass. Furthermore, the combination of RV noise and moderate v sin i makes HD 106315 a valuable laboratory for studying the spin–orbit alignment of small planets through the Rossiter–McLaughlin effect. Space-based atmospheric characterization of the two transiting planets via transit and eclipse spectroscopy should also be feasible. This discovery demonstrates again the power of K2 to find compelling exoplanets worthy of future study.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

right-sized dimple evaluator

The code (aka computer program written as a Matlab script) uses a unique set of n independent equations to solve for n turbulence variables. The code requires the input of a characteristic dimension, a characteristic fluid velocity, the fluid dynamic viscosity, and the fluid density. Most importantly, the code estimates the size of three key turbulent eddies: Kolmogorov, Taylor, and integral. Based on the eddy sizes, dimples dimensions are prescribed such that the key eddies (principally Taylor, and sometimes Kolmogorov), can be generated by the dimple rim and flow unimpeded through the dimple’s concave cavity. It is hypothesized that turbulent eddies are generated by the dimple rim at the dimple-surface interface. The newly-generated eddies in turn entrain the movement of surrounding regions of fluid, creating more mixing. The eddies also generate lift near the wall surrounding the dimple, as they accelerate and reduce pressure in the regions near and at the dimple cavity, thereby minimizing the fluid drag.

Rodriguez, Sal↗
DOE OSTI2019

Modeling Variable-Impedance, Magnetically Insulated, Transmission Lines

Coupling generator current to electron-beam loads and dynamic-inductance loads (z pinches) is greatly improved with low-inductance vacuum transmission lines. Typically, magnetically insulated transmission lines (MITLs) utilize nearly constant impedance geometries where the minimum impedance (anode-cathode gap) is limited by electron loss during the setup of magnetic insulation. Constant-impedance MITL designs are not optimized for low inductance (Zτ) when given a constraint on vacuum electron flow. We describe the design and the modeling of MITLs that have a nonconstant impedance. The baseline variable-impedance MITL designs are based on equilibrium vacuum-electron flow models [1] that are incorporated into the Screamer circuit code [2]. Such designs satisfy the MITL limits in the areal density of the loss current and have magnetically insulated flow that is stable everywhere along the MITL. Different MITL designs are then modeled analytically and with a 2-D particle-in-cell computer code in order to quantify subtle electron losses driven by changes to the vacuum impedance as a function of distance along the transmission line. We present a variable-impedance MITL design that delivers more current with a lower inductance than found in constant-impedance MITL designs.

47 OTHER INSTRUMENTATION↗