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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Infrastructure inequality is a characteristic of urbanization

Urbanization can challenge sustainable development if it produces unequal outcomes. Infrastructure is an important urbanization dimension, providing services to support diverse urban activities. However, it can lock in unequal outcomes due to its durable nature. This paper studies inequalities in infrastructure distributions to derive insights into the structure and characteristics of unequal outcomes associated with urbanization. We analyzed infrastructure inequalities in two emerging economies in the Global South: India and South Africa. We developed and applied an inequality measure to understand the structure of inequality in infrastructure provisioning (based on census data) and infrastructure availability (based on satellite nighttime lights [NTLs] data). Consistent with differences in economic inequality, results show greater inequalities in South Africa than in India and greater urban inequalities than rural inequalities. Nevertheless, inequalities in urban infrastructure provisioning and infrastructure availability increase from finer to coarser spatial scales. NTL-based inequality measurements additionally show that inequalities are more concentrated at coarse spatial scales in India than in South Africa. Finally, results show that urban inequalities in infrastructure provisioning covary with urbanization levels conceptualized as a multidimensional phenomenon, including demographic, economic, and infrastructural dimensions. Similarly, inequalities in urban infrastructure availability increase monotonically with infrastructure development levels and urban population size. Together, these findings underscore infrastructure inequalities as a feature of urbanization and suggest that understanding urban inequalities requires applying an inequality lens to urbanization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Scientific machine learning for modeling and simulating complex fluids

The formulation of rheological constitutive equations—models that relate internal stresses and deformations in complex fluids—is a critical step in the engineering of systems involving soft materials. While data-driven models provide accessible alternatives to expensive first-principles models and less accurate empirical models in many engineering disciplines, the development of similar models for complex fluids has lagged. The diversity of techniques for characterizing non-Newtonian fluid dynamics creates a challenge for classical machine learning approaches, which require uniformly structured training data. Consequently, early machine-learning based constitutive equations have not been portable between different deformation protocols or mechanical observables. Here, we present a data-driven framework that resolves such issues, allowing rheologists to construct learnable models that incorporate essential physical information, while remaining agnostic to details regarding particular experimental protocols or flow kinematics. These scientific machine learning models incorporate a universal approximator within a materially objective tensorial constitutive framework. By construction, these models respect physical constraints, such as frame-invariance and tensor symmetry, required by continuum mechanics. We demonstrate that this framework facilitates the rapid discovery of accurate constitutive equations from limited data and that the learned models may be used to describe more kinematically complex flows. This inherent flexibility admits the application of these “digital fluid twins” to a range of material systems and engineering problems. We illustrate this flexibility by deploying a trained model within a multidimensional computational fluid dynamics simulation—a task that is not achievable using any previously developed data-driven rheological equation of state.

Science & Technology - Other Topics↗
DOE OSTI2024

Probing the dynamics and bottleneck of the key atmospheric SO 2 oxidation reaction by the hydroxyl radical

SO 2 (Sulfur dioxide) is the major precursor to the production of sulfuric acid (H 2 SO 4 ), contributing to acid rain and atmospheric aerosols. Sulfuric acid formed from SO 2 generates light-reflecting sulfate aerosol particles in the atmosphere. This property has prompted recent geoengineering proposals to inject sulfuric acid or its precursors into the Earth’s atmosphere to increase the planetary albedo to counteract global warming. SO 2 oxidation in the atmosphere by the hydroxyl radical HO to form HOSO 2 is a key rate-limiting step in the mechanism for forming acid rain. However, the dynamics of the HO + SO 2 → HOSO 2 reaction and its slow rate in the atmosphere are poorly understood to date. Herein, we use photoelectron spectroscopy of cryogenically cooled HOSO 2 – anion to access the neutral HOSO 2 radical near the transition state of the HO + SO 2 reaction. Spectroscopic and dynamic calculations are conducted on the first ab initio-based full-dimensional potential energy surface to interpret the photoelectron spectra of HOSO 2 – and to probe the dynamics of the HO + SO 2 reaction. In addition to the finding of a unique pre-reaction complex (HO⋯SO 2 ) directly connected to the transition state, dynamic calculations reveal that the accessible phase space for the HO + SO 2 → HOSO 2 reaction is extremely narrow, forming a key reaction bottleneck and slowing the reaction rate in the atmosphere, despite the low reaction barrier. This study underlines the importance of understanding the full multidimensional potential energy surface to elucidate the dynamics of complex bimolecular reactions involving polyatomic reactants.

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

Command of three-dimensional solitary waves via photopatterning

Multidimensional solitons are prevalent in numerous research fields. In orientationally ordered soft matter system, three-dimensional director solitons exemplify the localized distortion of molecular orientation. However, their precise manipulation remains challenging due to unpredictable and uncontrolled generation. Here, we utilize preimposed programmable photopatterning in nematics to control the kinetics of director solitons. This enables both unidirectional and bidirectional generation at specific locations and times, confinement within micron-scaled patterns of diverse shapes, and directed propagation along predefined trajectories. A focused dynamical model provides insight into the origins of these solitons and aligns closely with experimental observations, underscoring the pivotal role of anchoring conditions in soliton manipulation. Our findings pave the way for diverse fundamental research avenues and promising applications, including microcargo transportation and optical information processing.

Science & Technology - Other Topics↗
DOE OSTI2014

Ischemia in tumors induces early and sustained phosphorylation changes in stress kinase pathways but does not affect global protein levels

Advances in quantitative mass spectrometry (MS)-based proteomics have sparked efforts to characterize the proteomes of tumor samples to provide complementary and unique information inaccessible by genomics. Tumor samples are usually not accrued with proteomic characterization in mind, raising concerns regarding effects of undocumented sample ischemia on protein abundance and phosphosite stoichiometry. Here we report the effects of cold ischemia time on clinical ovarian cancer samples and patient-derived basal and luminal breast cancer xenografts. Tumor tissues were excised and collected prior to vascular ligation, subjected to accurately defined ischemia times up to 60 min, and analyzed by quantitative proteomics and phosphoproteomics using isobaric tags and high-performance, multidimensional LC-MS/MS. No significant changes were detected at the protein level in each tumor type after 60 minutes of ischemia, and the majority of the >25,000 phosphosites detected were also stable. However, large, reproducible increases and decreases in protein phosphorylation at specific sites were observed in up to 24% of the phosphoproteome starting as early as 5 minutes post-excision. Early and sustained activation of stress response, transcriptional regulation and cell death pathways were observed in common across tumor types. Tissue-specific changes in phosphosite stability were also observed suggesting idiosyncratic effects of ischemia in particular lineages. Our study provides insights into the information that may be obtained by proteomic characterization of tumor samples after undocumented periods of ischemia, and suggests caution especially in interpreting activation of stress pathways in such samples as they may reflect sample handling rather than tumor physiology.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2022

Characterizing Tradeoffs in Memory, Accuracy, and Speed for Chemistry Tabulation Techniques

Chemistry tabulation is a common approach in practical simulations of turbulent combustion at engineering scales. Linear interpolants have traditionally been used for accessing precomputed multidimensional tables but suffer from large memory requirements and discontinuous derivatives. Higher-degree interpolants address some of these restrictions but are similarly limited to relatively low-dimensional tabulation. Artificial neural networks (ANNs) can be used to overcome these limitations but cannot guarantee the same accuracy as interpolants and introduce challenges in reproducibility and reliable training. These challenges are enhanced as the physics complexity to be represented within the tabulation increases. Here, we assess the efficiency, accuracy, and memory requirements of Lagrange polynomials, tensor product B-splines, and ANNs as tabulation strategies. We analyze results in the context of nonadiabatic flamelet modeling where higher dimension counts are necessary. While ANNs do not require structuring of data, providing benefits for complex physics representation, interpolation approaches often rely on some structuring of the table. Interpolation using structured table inputs that are not directly related to the variables transported in a simulation can incur additional query costs. This is demonstrated in the present implementation of heat losses. We show that ANNs, despite being difficult to train and reproduce, can be advantageous for high-dimensional, unstructured datasets relevant to nonadiabatic flamelet models. Furthermore we demonstrate that Lagrange polynomials show significant speedup for similar accuracy compared to B-splines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Coupling of CTF and RELAP5-3D Within an Enhanced Fidelity Nuclear Power Plant Simulator

A robust and accurate multiphysics engineering simulator is being developed to model the core behavior and system response of pressurized water reactors. This simulator relies on the NESTLE and CTF computer codes to model the neutronics and thermal hydraulics (TH), respectively, inside the core on a nodal scale and on the Reactor Excursion and Leak Analysis Program—Three Dimensional (RELAP5-3D) to model the entire nuclear steam supply system. The RELAP5-3D model includes highly detailed nodalization and multidimensional flow modeling throughout the vessel. Previously, pin-resolved data generated via the Virtual Environment for Reactor Analysis core simulator were used to improve the accuracy of the NESTLE core predictions. The engineering simulator being developed as part of this work uses the 3KEYMASTER platform to couple the enhanced NESTLE model to a nodal-fidelity CTF model to balance run time with accuracy; NESTLE provides node-dependent powers to CTF, and CTF provides node-dependent coolant densities and fuel temperatures to NESTLE.An overlapping domain approach is used for the core TH in which RELAP5-3D provides core boundary conditions based on the system response and CTF provides a node-dependent coolant heating rate to the RELAP5-3D core solution. In the preliminary TH demonstration discussed in this paper, CTF and RELAP5-3D provided similar steady-state core predictions, indicating the hydraulic compatibility between the codes, as well as reasonable and expected behavior under hypothetical transient conditions. This provides an initial step in ongoing efforts toward a robust, multiscale TH/neutronics engineering simulator capability.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

ROM-Based Surrogate Systems Modeling of EBR-II

We report the System Analysis Module (SAM), developed and maintained by Argonne National Laboratory, is designed to provide whole-plant transient safety analysis capabilities for a number of advanced non-light water reactors, including sodium-cooled fast reactor (SFR), lead-cooled fast reactor (LFR), and molten salt reactor (MSR)/fluoride-salt-cooled high-temperature reactor (FHR) designs. SAM is primarily constructed as a systems-level analysis tool, with the potential to incorporate reduced order models from three-dimensional computational fluid dynamics (CFD) simulations to improve characterization of complex, multidimensional physics. It is recognized that the computational expense associated with CFD can be intractable for various engineering analyses, such as uncertainty quantification, inference, and design optimization. This paper explores the reducibility of a SAM model using recent advances in randomized linear algebra techniques, which attempt to find recurring patterns in the various realizations generated by a model after randomly perturbing all its input parameters. The reduction is described in terms of fewer degrees of freedom (DOFs), referred to as the active DOFs, for the model variables such as input model parameters and model responses. The results indicate that there is significant room for additional reduction that may be leveraged for additional computational gains when employing SAM for engineering-intensive analyses that require repeated model executions. Different from physics-based reduction approaches, the proposed approach allows one to estimate upper bounds on the reduction errors, which are rigorously developed in this work. Finally, different methods for surrogate model construction, such as regression and neural network-based training, are employed to correlate the input and output active DOFs, which are related back to the original variables using matrix-based linear transformations.

42 ENGINEERING↗
DOE OSTI2016

Measurement of Size-dependent Dynamic Shape Factors of Quartz Particles in Two Flow Regimes

Understanding and modeling the behavior of quartz dust particles, commonly found in the atmosphere, requires knowledge of many relevant particles properties, including particle shape. This study uses a single particle mass spectrometer, a differential mobility analyzer, and an aerosol particle mass analyzer to measure quartz aerosol particles mobility, aerodynamic, and volume equivalent diameters, mass, composition, effective density, and dynamic shape factor as a function of particle size, in both the free molecular and transition flow regimes. The results clearly demonstrate that dynamic shape factors can vary significantly as a function of particle size. For the quartz samples studied here, the dynamic shape factors increase with size, indicating that larger particles are significantly more aspherical than smaller particles. In addition, dynamic shape factors measured in the free-molecular (χv) and transition (χt) flow regimes can be significantly different, and these differences vary with the size of the quartz particles. For quartz, χv of small (d < 200 nm) particles is 1.25, while χv of larger particles (d ~ 440 nm) is 1.6, with a continuously increasing trend with particle size. In contrast χt, of small particles starts at 1.1 increasing slowly to 1.34 for 550 nm diameter particles. The multidimensional particle characterization approach used here goes beyond determination of average properties for each size, to provide additional information about how the particle dynamic shape factor may vary even for particles with the same mass and volume equivalent diameter.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2019

Thermal conductivity of energetic materials

Here, thermal conductivity has been confirmed for a variety of energetic materials (EMs) using finite element analysis (FEA) and cookoff data from the Sandia Instrumented Thermal Ignition (SITI) experiment. Materials studied include melt-cast, pressed, and low-density explosives. The low-density explosives were either prills or powders with some experiments run at pour density (not pressed). We have viewed several of our thermal conductivities with those in the literature as well as investigated contact resistance between the confining aluminum and explosive, multidimensional heat transfer effects, and uncertainty in the thermocouple bead positions. We have determined that contact resistance is minimal in the SITI experiment, the heat transfer along the midplane is one-dimensional, and that uncertainty in the thermocouple location is greatest near the heated boundary. Our values of thermal conductivity can be used with kinetic mechanisms to accurately predict thermal profiles and energy dissipation during the cookoff of explosives.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A spectral deferred correction strategy for low Mach number reacting flows subject to electric fields

We propose an algorithm for low Mach number reacting flows subjected to electric field that includes the chemical production and transport of charged species. This work is an extension of a multi-implicit spectral deferred correction (MISDC) algorithm designed to advance the conservation equations in time at scales associated with advective transport. The fast and nontrivial interactions of electrons with the electric field are treated implicitly using a Jacobian-Free Newton Krylov approach for which a preconditioning strategy is developed. Within the MISDC framework, this enables a close and stable coupling of diffusion, reactions and dielectric relaxation terms with advective transport and is shown to exhibit second-order convergence in space and time. The algorithm is then applied to a series of steady and unsteady problems to demonstrate its capability and stability. Although developed in a one-dimensional case, the algorithmic ingredients are carefully designed to be amenable to multidimensional applications.

42 ENGINEERING↗
DOE OSTI2018

Rapid constriction of the selectivity filter underlies C-type inactivation in the KcsA potassium channel

C-type inactivation is a time-dependent process observed in many K+ channels whereby prolonged activation by an external stimulus leads to a reduction in ionic conduction. While C-type inactivation is thought to be a result of a constriction of the selectivity filter, the local dynamics of the process remain elusive. Here, we use molecular dynamics (MD) simulations of the KcsA channel to elucidate the nature of kinetically delayed activation/inactivation gating coupling. Microsecond-scale MD simulations based on the truncated form of the KcsA channel (C-terminal domain deleted) provide a first glimpse of the onset of C-type inactivation. We observe over multiple trajectories that the selectivity filter consistently undergoes a spontaneous and rapid (within 1–2 µs) transition to a constricted conformation when the intracellular activation gate is fully open, but remains in the conductive conformation when the activation gate is closed or partially open. Multidimensional umbrella sampling potential of mean force calculations and nonequilibrium voltage-driven simulations further confirm these observations. Electrophysiological measurements show that the truncated form of the KcsA channel inactivates faster and greater than full-length KcsA, which is consistent with truncated KcsA opening to a greater degree because of the absence of the C-terminal domain restraint. Together, these results imply that the observed kinetics underlying activation/inactivation gating reflect a rapid conductive-to-constricted transition of the selectivity filter that is allosterically controlled by the slow opening of the intracellular gate.

Li, Jing↗
DOE OSTI2013

ASYMMETRIC EJECTA DISTRIBUTION IN SN 1006

We present the results from deep X-ray observations ({approx}400 ks in total) of SN 1006 with Suzaku. The thermal spectrum from the entire supernova remnant (SNR) exhibits prominent emission lines of O, Ne, Mg, Si, S, Ar, Ca, and Fe. The observed abundance pattern in the ejecta components is in good agreement with that predicted by a standard model of Type Ia supernovae (SNe). The spatially resolved analysis reveals that the distribution of the O-burning and incomplete Si-burning products (Si, S, and Ar) is asymmetric, while that of the C-burning products (O, Ne, and Mg) is relatively uniform in the SNR interior. The peak position of the former is clearly shifted by 5' ({approx}3.2 pc at the distance of 2.2 kpc) to the southeast (SE) from the SNR's geometric center. Using the SNR age of {approx}1000 yr, we constrain that the velocity asymmetry (in projection) of the ejecta is {approx}3100 km s{sup -1}. The Fe abundance is also significantly higher in the SE region than in the northwest. Given that the non-uniformity is observed only in the heavier elements (Si through Fe), we argue that SN 1006 originates from an asymmetric explosion, as is expected from recent multidimensional simulations of Type Ia SNe, although we cannot eliminate the possibility that inhomogeneous ambient medium had induced the apparent non-uniformity. Possible evidence for the Cr-K-shell line and line broadening in the Fe-K-shell emission is also found.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

THE POST-MERGER MAGNETIZED EVOLUTION OF WHITE DWARF BINARIES: THE DOUBLE-DEGENERATE CHANNEL OF SUB-CHANDRASEKHAR TYPE Ia SUPERNOVAE AND THE FORMATION OF MAGNETIZED WHITE DWARFS

Type Ia supernovae (SNe Ia) play a crucial role as standardizable cosmological candles, though the nature of their progenitors is a subject of active investigation. Recent observational and theoretical work has pointed to merging white dwarf binaries, referred to as the double-degenerate channel, as the possible progenitor systems for some SNe Ia. Additionally, recent theoretical work suggests that mergers which fail to detonate may produce magnetized, rapidly rotating white dwarfs. In this paper, we present the first multidimensional simulations of the post-merger evolution of white dwarf binaries to include the effect of the magnetic field. In these systems, the two white dwarfs complete a final merger on a dynamical timescale, and are tidally disrupted, producing a rapidly rotating white dwarf merger surrounded by a hot corona and a thick, differentially rotating disk. The disk is strongly susceptible to the magnetorotational instability (MRI), and we demonstrate that this leads to the rapid growth of an initially dynamically weak magnetic field in the disk, the spin-down of the white dwarf merger, and to the subsequent central ignition of the white dwarf merger. Additionally, these magnetized models exhibit new features not present in prior hydrodynamic studies of white dwarf mergers, including the development of MRI turbulence in the hot disk, magnetized outflows carrying a significant fraction of the disk mass, and the magnetization of the white dwarf merger to field strengths {approx}2 Multiplication-Sign 10{sup 8} G. We discuss the impact of our findings on the origins, circumstellar media, and observed properties of SNe Ia and magnetized white dwarfs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

GRID-BASED EXPLORATION OF COSMOLOGICAL PARAMETER SPACE WITH SNAKE

We present a fully parallelized grid-based parameter estimation algorithm for investigating multidimensional likelihoods called Snake, and apply it to cosmological parameter estimation. The basic idea is to map out the likelihood grid-cell by grid-cell according to decreasing likelihood, and stop when a certain threshold has been reached. This approach improves vastly on the 'curse of dimensionality' problem plaguing standard grid-based parameter estimation simply by disregarding grid cells with negligible likelihood. The main advantages of this method compared to standard Metropolis-Hastings Markov Chain Monte Carlo methods include (1) trivial extraction of arbitrary conditional distributions; (2) direct access to Bayesian evidences; (3) better sampling of the tails of the distribution; and (4) nearly perfect parallelization scaling. The main disadvantage is, as in the case of brute-force grid-based evaluation, a dependency on the number of parameters, N{sub par}. One of the main goals of the present paper is to determine how large N{sub par} can be, while still maintaining reasonable computational efficiency; we find that N{sub par} = 12 is well within the capabilities of the method. The performance of the code is tested by comparing cosmological parameters estimated using Snake and the WMAP-7 data with those obtained using CosmoMC, the current standard code in the field. We find fully consistent results, with similar computational expenses, but shorter wall time due to the perfect parallelization scheme.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Pair instability supernovae of very massive population III stars

Numerical studies of primordial star formation suggest that the first stars in the universe may have been very massive. Stellar models indicate that non-rotating Population III stars with initial masses of 140-260 M {sub ☉} die as highly energetic pair-instability supernovae. We present new two-dimensional simulations of primordial pair-instability supernovae done with the CASTRO code. Our simulations begin at earlier times than previous multidimensional models, at the onset of core contraction, to capture any dynamical instabilities that may be seeded by core contraction and explosive burning. Such instabilities could enhance explosive yields by mixing hot ash with fuel, thereby accelerating nuclear burning, and affect the spectra of the supernova by dredging up heavy elements from greater depths in the star at early times. Our grid of models includes both blue supergiants and red supergiants over the range in progenitor mass expected for these events. We find that fluid instabilities driven by oxygen and helium burning arise at the upper and lower boundaries of the oxygen shell ∼20-100 s after core bounce. Instabilities driven by burning freeze out after the SN shock exits the helium core. As the shock later propagates through the hydrogen envelope, a strong reverse shock forms that drives the growth of Rayleigh-Taylor instabilities. In red supergiant progenitors, the amplitudes of these instabilities are sufficient to mix the supernova ejecta.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

The quantum interference effects in the SC II 4247 Å line of the second solar spectrum

The Sc II 4247 Å line formed in the chromosphere is one of the lines well known, like the Na I D{sub 2} and Ba II D{sub 2}, for its prominent triple-peak structure in Q/I and the underlying quantum interference effects governing it. In this paper, we try to study the nature of this triple-peak structure using the theory of F-state interference including the effects of partial frequency redistribution (PRD) and radiative transfer (RT). We compare our results with the observations taken in a quiet region near the solar limb. In spite of accounting for PRD and RT effects, it has not been possible to reproduce the observed triple-peak structure in Q/I. While the two wing PRD peaks (on either side of central peak) and the near wing continuum can be reproduced, the central peak is completely suppressed by the enhanced depolarization resulting from the hyperfine structure splitting. This suppression remains for all the tested widely different one-dimensional model atmospheres or for any multi-component combinations of them. While multidimensional RT effects may improve the fit to the intensity profiles, they do not appear capable of explaining the enigmatic central Q/I peak. This leads us to suspect that some aspect of quantum physics is missing.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Signatures of a companion star in type Ia supernovae

Although type Ia supernovae (SNe Ia) have been used as precise cosmological distance indicators, their progenitor systems remain unresolved. One of the key questions is whether there is a nondegenerate companion star at the time of a thermonuclear explosion of a white dwarf. In this paper, we investigate whether an interaction between the SN ejecta and the companion star may result in observable footprints around the maximum brightness and thereafter, by performing multidimensional radiation transfer simulations based on hydrodynamic simulations of the interaction. We find that such systems result in variations in various observational characteristics due to different viewing directions, and the predicted behaviors (redder and fainter for the companion direction) are the opposite of what were suggested by the previous study. The variations are generally modest and within observed scatters. However, the model predicts trends between some observables different from those observationally derived, so a large sample of SNe Ia with small calibration errors may be used to constrain the existence of such a companion star. The variations in different colors in optical band passes can be mimicked by external extinctions, so such an effect could be a source of scatter in the peak luminosity and derived distance. After the peak, hydrogen-rich materials expelled from the companion will manifest themselves in hydrogen lines, but Hα is extremely difficult to identify. Alternatively, we find that P{sub β} in postmaximum near-infrared spectra can potentially provide a powerful diagnostic.

79 ASTRONOMY AND ASTROPHYSICS↗