Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Truncated distribution”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3

A fast approximation to supershell partition functions

A formula for supershell partition functions, which play a major role in the Super Transition Array approach to radiative-opacity calculations, is derived as a functional of the distribution of energies within the supershell. It consists in an alternative expansion for an arbitrary number of electrons or holes which also allows for quick approximate evaluations with truncated number of terms in the expansion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Cluster defects in gibbsite nanoplates grown at acidic to neutral pH

Gibbsite [α-Al(OH) 3 ] is the solubility limiting phase for aluminum across a wide pH range, and it is a common mineral phase with many industrial applications. The growth mechanism of this layered-structure material, however, remains incompletely understood. Synthesis of gibbsite at low to circumneutral pH yields nanoplates with substantial interlayer disorder. Here we examine defects in this material in detail, and the effects of recrystallization in highly alkaline sodium hydroxide solution at 80 °C. We employed a multimodal approach, including scanning electron microscopy, magic-angle spinning nuclear magnetic resonance (MAS-NMR), Raman and infrared spectroscopies, X-ray diffraction (XRD), and X-ray total scattering pair distribution function (XPDF) analysis to characterize the ageing of the nanoplates over several days. Additionally, XRD and XPDF indicate that gibbsite nanoplates precipitated at circumneutral pH contain dense, truncated sheets imparting a local difference in interlayer distance. These interlayer defects appear well described by flat Al 13 aluminum hydroxide nanoclusters nearly isostructural with gibbsite sheets present under synthesis conditions and trapped as interlayer inclusions during growth. Ageing at elevated temperature in alkaline solutions gradually improves crystallinity, showing a gradual increase in H-bonding between interlayer OH groups. Between 7 to 8 vol% of the initial gibbsite nanoparticles exhibit this defect, with the majority of differences disappearing after 2–4 hours of recrystallization in alkaline solution. The results not only identify the source of disorder in gibbsite formed under acidic/neutral conditions but also point to a possible cluster-mediated growth mechanism evident through inclusion of relict oligomers with gibbsite-like topology trapped in the interlayer spaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stochastic Ensemble Generation for Improved Characterization of Representing Geologic Variability in a Reservoir: IBDP Case Study for SMART Initiative

This document is a poster covering the findings from activities on training data generation, specifically geologic ensemble generation. The generated geologic realizations captured the range of possible permeability distributions of the subsurface at the Illinois Basin - Decatur Project (IBDP) site, based on available well log variabilities. The percentages of reservoirs and baffles in the injection zone and a truncation of baffle permeability led to more variance in the simulations. This will be used to build forward modeling, history matching, and optimization workflows. The geologic realizations were also ranked according to dynamic measures of hydraulic diffusivity, and simulations confirm a greater contrast between the reservoir and the baffles during injection.

stochastic ensemble generation↗

Analytic and numerical vibronic spectra from quasi-classical trajectory ensembles

The truncated Wigner approximation to quantum dynamics in phase space is explored in the context of computing vibronic line shapes for monomer linear optical spectra. We consider multiple model potential forms including a shifted harmonic oscillator with both equal and unequal frequencies on the ground and excited state potentials as well as a shifted Morse potential model. For the equal-frequency shifted harmonic oscillator model, we derive an analytic expression for the exact vibronic line shape that emphasizes the importance of using a quantum mechanical distribution of phase space initial conditions. For the unequal-frequency shifted harmonic oscillator model, we are no longer able to obtain an exact expression for the vibronic line shape in terms of independent deterministic classical trajectories. We show how one can rigorously account for corrections to the truncated Wigner approximation through nonlinear responses of the line shape function to momentum fluctuations along a classical trajectory and demonstrate the qualitative improvement in the resulting spectrum when the leading-order quantum correction is included. Finally, we numerically simulate absorption spectra of a highly anharmonic shifted Morse potential model. We find that, while finite quantization and the dissociation limit are captured with reasonable accuracy, there is a qualitative breakdown of the quasi-classical trajectory ensemble’s ability to describe the vibronic line shape when the relative shift in Morse potentials becomes large. The work presented here provides clarity on the origin of unphysical negative features known to contaminate absorption spectra computed with quasi-classical trajectory ensembles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Impala's horn applied to posterior samples of Ti-6Al-4V strength model parameters

We have generated strength model parameters for the Preston-Tonks-Wallace (PTW) model of plastic deformation based on a collection of Ti-6Al-4V alloy data and a Bayesian framework. This data collected from the literature includes different chemistries and processes. The experiments include quasistatic compression, Split Hopkinson Pressure Bar (SHPB) compression, and Taylor cylinders. Here we use posterior parameter distributions applied to a hypothetical impact referred to as the Impala's horn. The Impala's horn is like a Taylor cylinder, but modified to have a conical pro le that is truncated before coming to a point. The smaller diameter at the impact end results in higher calculated strain rates and strains than the same velocity impact with the traditional Taylor profile. The modified geometry exercises the behavior of the strength model outside the range of conditions found in the calibration data. Here we sort posterior strength models based on their flow stress at characteristic values for this hypothetical deformation. Then we compare the performance of these posterior models based on two simple observable final state properties of the Impala's horn.

36 MATERIALS SCIENCE↗

High Fidelity CFD Simulations Supporting the KP-FHR

Kairos Power, LLC, is developing its version of the Fluoride-cooled High-temperature Reactor, the KP-FHR. The design uses a pebble bed core with fluoride salt as a coolant. The pebbles used in the KP-FHR have a diameter of 4 cm, with a shell fuel region where TRISO particles are embedded. A Pebble bed core design is adopted by several Gen IV reactors, They boast many benefits, such as fuel integrity, highly efficient heat transfer, and passive safety. However, it is challenging to accurately predict temperature and flow inside a pebble bed. Traditional approaches use the porous media model, which regards the pebble bed as a continuous medium, but with different temperature fields representing different levels, such as the fluid temperature, pebble surface temperature, and pebble center temperature. Empirical heat transfer correlations are adopted to calculate the heat transfer coefficient between different phases. However, empirical correlations are usually validated with experimental data, which usually lacks detail inside the pebble bed. The available experimental data is also generally at a high Reynolds number, which falls outside of the conditions of KP-FHR. Explicit computational fluid dynamics (CFD) simulations of randomly packed pebble beds have only become feasible recently. This is thanks to the rapid development of computational power and scalable algorithms. In this work, we used the Spectral Element Method (SEM) CFD code NekRS to simulate the randomly packed pebble bed in a cylindrical container. NekRS, which is the GPU variant of Nek5000, but refactored to utilize the computational power of GPUs using the OCCA library to run on hybrid architecture high performance computing systems. It was initially developed with the libParamunal library, but truncated and tuned for large-scale turbulence simulation. As a result, the SEM reaches higher precision with the same degrees of freedom by using a high-order Lagrange polynomial basis distributed on Gauss-Lobatto-Legendre quadrature inside each element, compared to lower-order methods, such the Finite Volume Method and Finite Element Method. The report is divided into five parts. We start with a general discussion of the pebble bed reactor, along with a specific investigation into the KP-FHR. The second part presents the numerical methodology. In the third part, we study a modular pebble bed with 1741 pebbles in a container of 7 pebble-diameter radius. Beyond LES simulations done by NekRS, we also leveraged the thermal radiation model in OpenFOAM to study heat transfer under no-forced-flow scenarios. Then, in the fourth part we simulated a pebble bed similar to the size of the Hermes Test Reactor. The total number of pebbles is in these simulations is 34,374. The container radius is 14 pebble-diameters. Finally, the report concludes in part five, with a discussion of future work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Multimerization of Ebola GPΔmucin on protein nanoparticle vaccines has minimal effect on elicitation of neutralizing antibodies

Ebola virus (EBOV), a member of the Filoviridae family of viruses and a causative agent of Ebola Virus Disease (EVD), is a highly pathogenic virus that has caused over twenty outbreaks in Central and West Africa since its formal discovery in 1976. The only FDA-licensed vaccine against Ebola virus, rVSV-ZEBOV-GP (Ervebo®), is efficacious against infection following just one dose. However, since this vaccine contains a replicating virus, it requires ultra-low temperature storage which imparts considerable logistical challenges for distribution and access. Additional vaccine candidates could provide expanded protection to mitigate current and future outbreaks. Here, we designed and characterized two multimeric protein nanoparticle subunit vaccines displaying 8 or 20 copies of GPΔmucin, a truncated form of the EBOV surface protein GP. Single-dose immunization of mice with GPΔmucin nanoparticles revealed that neutralizing antibody levels were roughly equivalent to those observed in mice immunized with non-multimerized GPΔmucin trimers. These results suggest that some protein subunit antigens do not elicit enhanced antibody responses when displayed on multivalent scaffolds and can inform next-generation design of stable Ebola virus vaccine candidates.

60 APPLIED LIFE SCIENCES↗

Neutrino fast flavor oscillations with moments: Linear stability analysis and application to neutron star mergers

Providing an accurate modeling of neutrino physics in dense astrophysical environments such as binary neutron star mergers presents a challenge for hydrodynamic simulations. Nevertheless, understanding how flavor transformation can occur and affect the dynamics, the mass ejection, and the nucleosynthesis will need to be achieved in the future. Computationally expensive, large-scale simulations frequently evolve the first classical angular moments of the neutrino distributions. By promoting these quantities to matrices in flavor space, we develop a linear stability analysis of fast flavor oscillations using only the first two “quantum” moments, which notably requires generalizing the classical closure relations that appropriately truncate the hierarchy of moment equations in order to treat quantum flavor coherence. After showing the efficiency of this method on a well-understood test situation, we perform a systematic search of the occurrence of fast flavor instabilities in a neutron star merger simulation. Here, we discuss the successes and shortcomings of moment linear stability analysis, as this framework provides a time-efficient way to design and study better closure prescriptions in the future.

79 ASTRONOMY AND ASTROPHYSICS↗

Blanco DECam Bulge Survey (BDBS) Ⅳ: Metallicity distributions and bulge structure from 2.6 million red clump stars

We present photometric metallicity measurements for a sample of 2.6 million bulge red clump stars extracted from the Blanco DECam Bulge Survey (BDBS). Similar to previous studies, we find that the bulge exhibits a strong vertical metallicity gradient, and that at least two peaks in the metallicity distribution functions appear at b < -5°. We can discern a metal-poor ([Fe/H] ~ -0.3) and metal-rich ([Fe/H] ~+0.2) abundance distribution that each show clear systematic trends with latitude, and may be best understood by changes in the bulge’s star formation/enrichment processes. Both groups exhibit asymmetric tails, and as a result we argue that the proximity of a star to either peak in [Fe/H] space is not necessarily an affirmation of group membership. The metal-poor peak shifts to lower [Fe/H] values at larger distances from the plane while the metal-rich tail truncates. Close to the plane, the metal-rich tail appears broader along the minor axis than in off-axis fields. We also posit that the bulge has two metal-poor populations – one that belongs to the metal-poor tail of the low latitude and predominantly metal-rich group, and another belonging to the metal-poor group that dominates in the outer bulge. We detect the X-shape structure in fields with |Z| >0.7 kpc and for stars with [Fe/H] < -0.5. Stars with [Fe/H] > -0.5 may form a spheroidal or ‘thick bar’ distribution while those with [Fe/H] ≳ -0.1 are strongly concentrated near the plane.

79 ASTRONOMY AND ASTROPHYSICS↗

The role of SAXS and molecular simulations in 3D structure elucidation of a DNA aptamer against lung cancer

Aptamers are short, single-stranded DNA or RNA oligonucleotide molecules that function as synthetic analogs of antibodies and bind to a target molecule with high specificity. Aptamer affinity entirely depends on its tertiary structure and charge distribution. Therefore, length and structure optimization are essential for increasing aptamer specificity and affinity. Here, we present a general optimization procedure for finding the most populated atomistic structures of DNA aptamers. Based on the existed aptamer LC-18 for lung adenocarcinoma, a new truncated LC-18 (LC-18t) aptamer LC-18t was developed. A three-dimensional (3D) shape of LC-18t was reported based on small-angle X-ray scattering (SAXS) experiments and molecular modeling by fragment molecular orbital or molecular dynamic methods. Molecular simulations revealed an ensemble of possible aptamer conformations in solution that were in close agreement with measured SAXS data. The aptamer LC-18t had stronger binding to cancerous cells in lung tumor tissues and shared the binding site with the original larger aptamer. The suggested approach reveals 3D shapes of aptamers and helps in designing better affinity probes.

59 BASIC BIOLOGICAL SCIENCES↗

Regularized Differentiation for Bioburden Density Estimation in Planetary Protection

In this paper, we propose and investigate the performance of two novel shrinkage estimators for bioburden density estimation in planetary protection. The estimators are based on the regularized differentiation of a cumulative count of colony forming units collected throughout the data collecting session or the life cycle of the entire mission. The regularized differentiation recasts the problem of bioburden density estimation as a linear least squares problem. The least squares problem is then solved through regularization techniques, such as truncated singular value decomposition and penalized least squares. The regularization is necessary to avoid noise amplification during the differentiation of noisy data. The two regularization estimators are compared with four other commonly used estimators to simultaneously evaluate the means of multivariable independent Poisson distributions: the maximum likelihood, noninformative Bayes estimator with Jeffreys prior, Empirical Bayes using conjugate gamma-Poisson model with gamma parameters selected by method of moments, and the Clevenson-Zidek estimator. It is shown through computer-simulated data that the regularized differentiation based on ridge regression has the smallest mean-squared error among all estimators. The analysis of shrinkage mechanism implemented by regularized differentiation is performed, and it is shown that the regularized differentiation amounts to performing a weighted averaging of all the samples. The weights are determined by the regularization parameter automatically selected by the L-curve technique. Since the method of least squares makes no distributional assumptions about the data, it presents an attractive technique for bioburden density estimation when there are concerns about the misspecification of the distributional model. The paper concludes with the analysis of the bioburden data collected during InSight mission and directions for future work.

97 - MATHEMATICS AND COMPUTING↗

Small-amplitude Compressible Magnetohydrodynamic Turbulence Modulated by Collisionless Damping in Earth’s Magnetosheath: Observation Matches Theory

Plasma turbulence is a ubiquitous dynamical process that transfers energy across many spatial and temporal scales and affects energetic particle transport. Recent advances in the understanding of compressible magnetohydrodynamic (MHD) turbulence demonstrate the important role of damping in shaping energy distributions on small scales, yet its observational evidence is still lacking. This study provides the first observational evidence of substantial collisionless damping (CD) modulation on the small-amplitude compressible MHD turbulence cascade in Earth’s magnetosheath using four Cluster spacecraft. Based on an improved compressible MHD decomposition algorithm, turbulence is decomposed into three eigenmodes: incompressible Alfvén modes and compressible slow and fast (magnetosonic) modes. Our observations demonstrate that CD enhances the anisotropy of compressible MHD modes because CD has a strong dependence on wave propagation angle. The wavenumber distributions of slow modes are mainly stretched perpendicular to the background magnetic field (B 0 ) and weakly modulated by CD. In contrast, fast modes are subjected to a more significant CD modulation. Fast modes exhibit a weak, scale-independent anisotropy above the CD truncation scale. Below the CD truncation scale, the anisotropy of fast modes enhances as wavenumbers increase. As a result, fast-mode fractions in the total energy of compressible modes decrease with the increase of perpendicular wavenumber (to B 0 ) or wave propagation angle. Our findings reveal how the turbulence cascade is shaped by CD and its consequences for anisotropies in the space environment.

97 MATHEMATICS AND COMPUTING↗

Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors

A rational therapeutic strategy is urgently needed for combating SARS-CoV-2 infection. Viral infection initiates when the SARS-CoV-2 receptor-binding domain (RBD) binds to the ACE2 receptor, and thus, inhibiting RBD is a promising therapeutic for blocking viral entry. In this study, the structure of lead antiviral candidate binder (LCB1), which has three alpha-helices (H1, H2, and H3), is used as a template to design and simulate several miniprotein RBD inhibitors. LCB1 undergoes two modifications: structural modification by truncation of the H3 to reduce its size, followed by single and double amino acid substitutions to enhance its binding with RBD. We use molecular dynamics (MD) simulations supported by ab initio density functional theory (DFT) calculations. Complete binding profiles of all miniproteins with RBD have been determined. The MD investigations reveal that the H3 truncation results in a small inhibitor with a -1.5 kcal/mol tighter binding to RBD than original LCB1, while the best miniprotein with higher binding affinity involves D17R or E11V + D17R mutation. DFT calculations provide atomic-scale details on the role of hydrogen bonding and partial charge distribution in stabilizing the minibinder:RBD complex. This study provides insights into general principles for designing potential therapeutics for SARS-CoV-2.

60 APPLIED LIFE SCIENCES↗

Quantum efficiency enhancement in simulated nanostructured negative electron affinity GaAs photocathodes

We report nanostructured negative electron affinity GaAs photocathodes for a polarized electron source are studied using finite difference time domain optical simulation. The structures studied are nanosquare columns, truncated nanocones, and truncated nanopyramids. Mie-type resonances in the 700–800 nm waveband, suitable for generation of polarized electrons, are identified. At resonance wavelengths, the nanostructures can absorb up to 99% of the incident light. For nanosquare columns and truncated nanocones, the maximum quantum efficiency (QE) at 780 nm obtained from simulation is 27%, whereas for simulated nanopyramids, the QE is ~21%. The high photocathode quantum efficiency is due to the shift of Mie resonance toward the longer wavelength, leading to increased light absorption. The field profile distribution shows the excitation of dipole and quadrupole modes within the nanostructures at resonant frequencies. This leads to enhanced photoabsorption and photoelectron generation closer to emission surfaces than for a flat photocathode. The enhanced photoabsorption and reduced electron transport distance for the nanostructured photocathode enhance its QE compared to that for the flat surface wafer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Trivalent ion overcharging on electrified graphene

We report the structure of the electrical double layer (EDL) formed near graphene in aqueous environments strongly impacts its performance for a plethora of applications, including capacitive deionization. In particular, adsorption and organization of multivalent counterions near the graphene interface can promote nonclassical behaviors of EDL including overcharging followed by co-ion adsorption. In this paper, we characterize the EDL formed near an electrified graphene interface in dilute aqueous YCl 3 solution using in situ high resolution x-ray reflectivity (also known as crystal truncation rod) and resonant anomalous x-ray reflectivity (RAXR). These interface-specific techniques reveal the electron density profiles with molecular-scale resolution. We find that yttrium ions (Y 3+ ) readily adsorb to the negatively charged graphene surface to form an extended ion profile. This ion distribution resembles a classical diffuse layer but with a significantly high ion coverage, i.e., 1 Y 3+ per 11.4 ± 1.6 Å 2 , compared to the value calculated from the capacitance measured by cyclic voltammetry (1 Y 3+ per ~240 Å 2 ). Such overcharging can be explained by co-adsorption of chloride that effectively screens the excess positive charge. The adsorbed Y 3+ profile also shows a molecular-scale gap (≥ 5 Å) from the top graphene surfaces, which is attributed to the presence of intervening water molecules between the adsorbents and adsorbates as well as the lack of inner-sphere surface complexation on chemically inert graphene. We also demonstrate controlled adsorption by varying the applied potential and reveal consistent Y 3+ ion position with respect to the surface and increasing cation coverage with increasing the magnitude of the negative potential. This is the first experimental description of a model graphene-aqueous system with controlled potential and provides important insights into the application of graphene-based systems for enhanced and selective ion separations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

GPU-Accelerated Solution of the Bethe–Salpeter Equation for Large and Heterogeneous Systems

We present a massively parallel GPU-accelerated implementation of the Bethe–Salpeter equation (BSE) for the calculation of the vertical excitation energies (VEEs) and optical absorption spectra of condensed and molecular systems, starting from single-particle eigenvalues and eigenvectors obtained with density functional theory. The algorithms adopted here circumvent the slowly converging sums over empty and occupied states and the inversion of large dielectric matrices through a density matrix perturbation theory approach and a low-rank decomposition of the screened Coulomb interaction, respectively. Further computational savings are achieved by exploiting the nearsightedness of the density matrix of semiconductors and insulators to reduce the number of screened Coulomb integrals. We scale our calculations to thousands of GPUs with a hierarchical loop and data distribution strategy. The efficacy of our method is demonstrated by computing the VEEs of several spin defects in wide-band-gap materials, showing that supercells with up to 1000 atoms are necessary to obtain converged results. We discuss the validity of the common approximation that solves the BSE with truncated sums over empty and occupied states. In conclusion, we then apply our GW-BSE implementation to a diamond lattice with 1727 atoms to study the symmetry breaking of triplet states caused by the interaction of a point defect with an extended line defect.

Absorption spectra↗

Solving differential‐algebraic equations in power system dynamic analysis with quantum computing

Abstract Power system dynamics are generally modeled by high dimensional non‐linear differential‐algebraic equations (DAEs) given a large number of components forming the network. These DAEs' complexity can grow exponentially due to the increasing penetration of distributed energy resources, whereas their computation time becomes sensitive due to the increasing interconnection of the power grid with other energy systems. This paper demonstrates the use of quantum computing algorithms to solve DAEs for power system dynamic analysis. We leverage a symbolic programming framework to equivalently convert the power system's DAEs into ordinary differential equations (ODEs) using index reduction methods and then encode their data into qubits using amplitude encoding. The system non‐linearity is captured by Hamiltonian simulation with truncated Taylor expansion so that state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can solve the power system's DAEs accurately with a computational complexity polynomial in the logarithm of the system dimension. We also illustrate the use of recent advanced tools in scientific machine learning for implementing complex computing concepts, that is, Taylor expansion, DAEs/ODEs transformation, and quantum computing solver with abstract representation for power engineering applications.

computational complexity↗

Evaluation of data driven low-rank matrix factorization for accelerated solutions of the Vlasov equation

Low-rank methods have shown success in accelerating simulations of a collisionless plasma described by the Vlasov equation, but still rely on computationally costly linear algebra every time step. We propose a data-driven factorization method using artificial neural networks, specifically with convolutional layer architecture, that trains on existing simulation data. At inference time, the model outputs a low-rank decomposition of the distribution field of the charged particles, and we demonstrate that this step is faster than the standard linear algebra technique. Numerical experiments show that the method achieves comparable reconstruction accuracy for interpolation tasks, generalizing to unseen test data in a manner beyond just memorizing training data; patterns in factorization also inherently followed the same numerical trend as those within algebraic methods (e.g., truncated singular-value decomposition). However, when training on the first 70% of a time-series data and testing on the remaining 30%, the method fails to meaningfully extrapolate. Despite this limiting result, the technique may have benefits for simulations in a statistical steady-state or otherwise showing temporal stability. These results suggest that while the model offers a computationally efficient alternative for datasets with temporal stability, its current formulation is best suited for interpolation rather than for predicting future states in time-evolving systems. This study thus lays the groundwork for further refinement of neural network-based approaches to low-rank matrix factorization in high-dimensional plasma simulations.

97 MATHEMATICS AND COMPUTING↗