Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Matrix Models”

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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Pulse-level noisy quantum circuits with QuTiP

The study of the impact of noise on quantum circuits is especially relevant to guide the progress of Noisy Intermediate-Scale Quantum (NISQ) computing. In this paper, we address the pulse-level simulation of noisy quantum circuits with the Quantum Toolbox in Python (QuTiP). We introduce new tools in qutip-qip, QuTiP's quantum information processing package. These tools simulate quantum circuits at the pulse level, leveraging QuTiP's quantum dynamics solvers and control optimization features. We show how quantum circuits can be compiled on simulated processors, with control pulses acting on a target Hamiltonian that describes the unitary evolution of the physical qubits. Various types of noise can be introduced based on the physical model, e.g., by simulating the Lindblad density-matrix dynamics or Monte Carlo quantum trajectories. In particular, the user can define environment-induced decoherence at the processor level and include noise simulation at the level of control pulses. We illustrate how the Deutsch-Jozsa algorithm is compiled and executed on a superconducting-qubit-based processor, on a spin-chain-based processor and using control optimization algorithms. We also show how to easily reproduce experimental results on cross-talk noise in an ion-based processor, and how a Ramsey experiment can be modeled with Lindblad dynamics. Finally, we illustrate how to integrate these features with other software frameworks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Hydrolytic Aging in Rubber-Like Materials: A Micro-Mechanical Approach to Modeling

Abstract The effect of hydrolytic aging on mechanical responses of Rubber likes materials, in particular, Mullins effect and the permanent set has been modeled. Hydrolytic aging is considered as the result of the competition between two phenomena (1) chain scission and (2) cross-link scission/reformation. Both phenomena were modeled and thus, the strain energy of the polymer matrix is written with respect to three independent mechanisms; i) the shrinking original matrix which has not been attacked by water, ii) conversion of the first network to a new network due to the reduction of the crosslinks, and iii) energy loss from network degradation due to water attacks to ester groups. The model is validated with respect to a set of experimental data. Besides accuracy, the simplicity and few numbers of fitting parameters make the model a good choice for further implementations.

Bahrololoumi, Amir↗
DOE OSTI2015

Multiporosity flow in fractured low-permeability rocks: Extension to shale hydrocarbon reservoirs

We presented a multiporosity extension of classical double and triple-porosity fractured rock flow models for slightly compressible fluids. The multiporosity model is an adaptation of the multirate solute transport model of Haggerty and Gorelick (1995) to viscous flow in fractured rock reservoirs. It is a generalization of both pseudo steady state and transient interporosity flow double-porosity models. The model includes a fracture continuum and an overlapping distribution of multiple rock matrix continua, whose fracture-matrix exchange coefficients are specified through a discrete probability mass function. Semianalytical cylindrically symmetric solutions to the multiporosity mathematical model are developed using the Laplace transform to illustrate its behavior. Furthermore, the multiporosity model presented here is conceptually simple, yet flexible enough to simulate common conceptualizations of double and triple-porosity flow. This combination of generality and simplicity makes the multiporosity model a good choice for flow modelling in low-permeability fractured rocks.

58 GEOSCIENCES↗
DOE OSTI2015

“Full Model” Nuclear Data and Covariance Evaluation Process Using TALYS, Total Monte Carlo and Backward-forward Monte Carlo

The “Full model” evaluation process, that is used in CEA DAM DIF to evaluate nuclear data in the continuum region, makes extended use of nuclear models implemented in the TALYS code to account for experimental data (both differential and integral) by varying the parameters of these models until a satisfactory description of these experimental data is reached. For the evaluation of the covariance data associated with this evaluated data, the Backward-forward Monte Carlo (BFMC) method was devised in such a way that it mirrors the process of the “Full model” evaluation method. When coupled with the Total Monte Carlo method via the T6 system developed by NRG Petten, the BFMC method allows to make use of integral experiments to constrain the distribution of model parameters, and hence the distribution of derived observables and their covariance matrix. Together, TALYS, TMC, BFMC, and T6, constitute a powerful integrated tool for nuclear data evaluation, that allows for evaluation of nuclear data and the associated covariance matrix, all at once, making good use of all the available experimental information to drive the distribution of the model parameters and the derived observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Simulation of Deuterium Oxidation in a Room with a Fire

A series of experiments where deuterium was released in trace amounts into a room with a fire were performed at Sandia National Laboratories. This report describes the corresponding effort to model the test series using SIERRA/FUEGO. The objective of this modeling effort was to produce a simulation test matrix that can be utilized to help interpret the corresponding experiments and be used to assess the credibility of using the SIERRA/FUEGO simulations as a surrogate for real tritium reaction data for mock fire and release studies. The simulations assessed multiple configurations of fire size and location and overall found that there was low conversion of deuterium to oxidized deuterium. There are some notable differences between the simulation predictions and the experimental results, such as the simulations generally predicting higher amounts of deuterium conversion compared to the experiment. A strategy to address modeling uncertainties and unknowns is also given in this report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Embedding PbS Quantum Dots (QDs) in Pb-Halide Perovskite Matrices: QD Surface Chemistry and Antisolvent Effects on QD Dispersion and Confinement Properties

Hybrid materials of metal chalcogenide colloidal quantum dots (QDs) embedded in metal halide perovskites (MHPs) have led to composites with synergistic properties. Here, we investigate how QD size, surface chemistry, and MHP film formation methods affect the resulting optoelectronic properties of QD/MHP “dot-in-matrix” systems. We monitor the QD absorption and photoluminescence throughout synthesis, ligand exchange, and transfer into the MHP ink, and we characterize the final QD/MHP films via electron microscopy and transient absorption. In addition, we are the first to globally map how PbS QDs are distributed on the micrometer scale within these dot-in-matrix systems, using three-dimensional (3D) tomography time-of-flight secondary ion mass spectrometry. The surface chemistry imparted during synthesis directly affects the optical properties of the dot-in-matrix composites. Pb-halide passivation leads to QD/MHP dot-in-matrix samples with optical properties that are well-described by a theoretical model, based on a Type I finite-barrier heterostructure between the PbS QD and the MHP matrix. Samples without Pb-halide passivation show complicated size-dependent behavior, indicating a transition from a Type I heterostructure between the PbS QD wells and MHP barriers for small-sized QDs to PbS QDs that are electronically decoupled from the MHP matrix for larger QDs. Furthermore, the choice in perovskite antisolvent crystallization method leads to a difference in the spatial QD distribution within the perovskite matrix, differences in carrier lifetime, and photoluminescence shifts of up to 180 meV for PbS in methylammonium lead iodide. This work establishes an understanding of such emerging synergistic systems relevant for technologies such as photovoltaics, infrared emitters and detectors, and other unexplored technological applications.

92 SC - Basic Energy Sciences (BES) (SC-22)↗
DOE OSTI2019

Broken mirror symmetry, incommensurate spin correlations, and B 2 g nematic order in iron pnictides

Motivated by recent experiments in the extremely hole doped iron pnictide compounds AFe 2 As 2 (A = K, Rb, Cs), we consider spin-driven nematic order for incommensurate magnetic fluctuations. We classify the nematic order parameters by broken mirror symmetries of the tetragonal D 4h point group, and use this scheme to construct a general Ginzburg-Landau theory that links the nematic order to spatial pattern of magnetic fluctuations. Our analysis points to incommensurate (q,q) magnetic fluctuations as underlying a B 2 g nematic order in AFe 2 As 2 . We substantiate this idea by microscopic calculations based on three-sublattice (2π/3,2π/3) spin correlations in an extended bilinear-biquadratic Heisenberg model. Our classification scheme provides symmetry-based understanding for quasidegeneracy of several nematic channels. The proposed mechanism resolves recently emerged experimental puzzles. Furthermore, we suggest ways to further test it in future experiments and discuss the implications of our results for iron-based high temperature superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Image Characterization of Reactions Generated by an Aeroengine Micromixing Injector for Lean Direct Injection of Hydrogen and Hydrogen/Natural Gas Blend

An aeroengine micromixing injector, originally designed for lean direct injection of jet fuel, was adapted to work with hydrogen, natural gas, and any blend in between. The ultimate goal of the design was to achieve low NOx emissions when operated on pure hydrogen; to better characterize its performance, flame imaging diagnostics was implemented. Three types of cameras mounted parallel to the injector base and pointing towards the quartz combustor cylinder with the same angle were operated simultaneously: Nikon D90, Dynacolor FB-N9-U, and Phantom v7.1, to capture the visible spectrum, OH* chemiluminescence, and dynamic behavior of the flames, respectively. The current work also includes the overlapping of visible spectrum and OH* chemiluminescence, as an effort to qualitatively define the heat release over the flame area, i.e., UV over visible domain. Additionally, a z-type schlieren configuration was employed to reinforce the presence of some small-scale details occurring near the injector outlet ports. Using the airbox pressure drop, preheat temperature, fuel composition and flame temperature as the factors of study, a Box Behnken model was designed yielding into a 16-points matrix for the operability region, at atmospheric pressure. The main responses were extracted from the OH* images, because of its correlation with the flame heat release, these being the flame area and its average brightness, the heat release area and its center of gravity and leading edge. To assess the importance of the main factors and their interactions, an analysis of variance (ANOVA) was performed for each response, considering as significant each contributor with a p-value below 0.05. For these five responses it was found that all four main factors need to be included into the model (most of them because its own significance, others to ensure the model hierarchy), as well as some common interactions as the preheat and flame temperatures or pressure drop and fuel composition, and quadratic terms from fuel composition or flame temperature. Three of the five models presented R2 and coefficient of variance (C.V.) indicators around 0.97 and 5%, respectively; the leading edge ANOVA yielded into R2=0.78 and C.V.=18.88%; and the heat release area showed R2=0.91 and C.V.=24.13%. Lastly, the confinement ratio effect of the combustor over the flame structure was quantified, for three different conditions: the original 80 mm inner diameter and 200 mm length cylinder was compared against a shorter 150 mm tube (same inner diameter) and a narrower 47 mm inner diameter one (same 200 mm length). The length had a smaller effect than the inner diameter, even though both factors were not strong enough to make a significant deviation on most of the flame parameters: the difference was within the repeatability margin of error for the brightness, flame area, and center of gravity and leading edge of the heat release area.

Imaging diagnostics, flame characterization, OH* c↗
DOE OSTI2024

Quantum Melting of Generalized Wigner Crystals in Transition Metal Dichalcogenide Moiré Systems

The generalized Wigner crystal (GWC) is a novel quantum phase of matter driven by further-range interaction at fractional fillings of a lattice. The role of further-range interaction as the driver for the incompressible state is akin to the Wigner crystal. On the other hand, the significant role of commensurate filling is akin to the Mott insulator. Recent progress in simulator platforms presents unprecedented opportunities to investigate quantum melting in the strongly interacting regime through synergy between theory and experiments. However, the earlier theory literature presents diverging predictions. We study the quantum freezing of GWC through large-scale density matrix renormalization group simulations of a triangular lattice extended Hubbard model. We find a single first-order phase transition between the Fermi liquid and the √3×√3 GWC state. Furthermore, the GWC state shows long-range antiferromagnetic 120° Néel order. Our results present the simplest answers to the question of the quantum phase transition into the GWC phase and the properties of the GWC phase.

Density matrix renormalization group↗
DOE OSTI2018

Failure strength predictions for closed-cell polyvinyl chloride foams

This paper describes an effort to model mechanical strength of closed-cell polyvinyl chloride foams under static loading. The study presented here is a continuation of an earlier study to model elastic stiffness of closed-cell polyvinyl chloride foams as effective transversely isotropic materials. An engineering approach is used in the study and governing equations are developed for predicting the strength of polyvinyl chloride foams. To account for foam microstructure and cell-shape anisotropy on foam strength, a unit cell representation of the polyvinyl chloride foam microstructure is used to derive equations to assess tensile and shear strengths of polyvinyl chloride foams. The differential stretching of polyvinyl chloride foam cell walls (in the rise direction and in the in-plane directions) on the strength of the foam-matrix polymer is also taken into account in modeling the mechanical strength of polyvinyl chloride closed-cell foams. The behavior of closed-cell polyvinyl chloride foams under compression is different from that under tension. In the paper, the equations for predicting compressive strength of closed-cell polyvinyl chloride foams are based on an approximate theory developed in an earlier study of compressive strength of unidirectional composites. The validity of the foam strength predictive equations, derived in the paper, is first demonstrated through comparison of the predictions with the results on Divinycell H (DIAB) foams obtained from a systematic in-house test program. A comparison is also carried out between the strength predictions and the test results published by two polyvinyl chloride foam manufacturers for different density polyvinyl chloride foams. Good agreements are found for all the different density foams studied.

Lo, King H.↗
DOE OSTI2014

Recent results and persisting problems in modeling flow induced coalescence

The contribution summarizes recent results of description of the flow induced coalescence in immiscible polymer blends and addresses problems that call for which solving. The theory of coalescence based on the switch between equations for matrix drainage between spherical or deformed droplets provides a good agreement with more complicated modeling and available experimental data for probability, P{sub c}, that the collision of droplets will be followed by their fusion. A new equation for description of the matrix drainage between deformed droplets, applicable to the whole range of viscosity ratios, p, of the droplets and matrixes, is proposed. The theory facilitates to consider the effect of the matrix elasticity on coalescence. P{sub c} decreases with the matrix relaxation time but this decrease is not pronounced for relaxation times typical of most commercial polymers. Modeling of the flow induced coalescence in concentrated systems is needed for prediction of the dependence of coalescence rate on volume fraction of droplets. The effect of the droplet anisometry on P{sub c} should be studied for better understanding the coalescence in flow field with high and moderate deformation rates. A reliable description of coalescence in mixing and processing devices requires proper modeling of complex flow fields.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Analysis of Unpolarised p+p¿ Photoproduction with the GlueX Experiment

This thesis presents measurements of spin-density matrix elements in unpolarised p+p? photoproduction on a proton target. The dominant resonance contribution to the dipion system is the r(770) meson. Due to the large production cross section for this resonance, a valid comparison can be made between the obtained final results and r(770) spin-density matrix elements measured previously with other experiments. The measurement was performed over the 3:0 ? 11:6 GeV beam energy regime, which is a more extensive energy range than has ever been studied previously for the r(770). Results were obtained by analysing data from the GlueX experiment based at Jefferson Lab. Extended maximum likelihood fits were applied to extract three spin-density matrix elements using Markov chain Monte Carlo based parameter estimations. This was performed using various binning configurations to probe the energy, mass, and four-momentum transfer dependence of the determined physics observables. Spin-density matrix elements are shown to be consistent with the model of s-channel helicity conservation at low ?t. The effects of pomeron and f2 exchanges are clearly visible in the energy dependence of the measured observables. These observations provide valuable insights into the relative strengths of both processes as a function of the photon energy, and may enable theorists to disentangle the f2=P coupling ratio. Spin-density matrix elements are seen to be highly dependent on the reconstructed resonance mass. This observation is likely to be a result of non-resonant S-wave background processes, and emphasises the need for a more detailed model of the p+p? angular distribution that considers all of the competing angular momentum components that contribute to the measured final state. The statistical precision of measurements performed for this thesis surpass what was achievable in previous studies of the r(770) by several orders of magnitude. Studies of the energy and four-momentum transfer dependence, and insights into the effects of non r(770) background contributions provide valuable input for production models. This will help inform the choice of wave-sets used for partial wave analyses, supporting GlueX in its search for exotic hybrid meson states.

Fitches, James↗
DOE OSTI2021

A Python Library for Radiance Matrix-based Simulation Control and EnergyPlus Integration

Radiance matrix-based methods enable efficient parametric simulations, allowing users to vary sky conditions, fenestration systems, and other model parameters at a minimal cost to computation. However, the steep learning curve and complex workflow hinder the widespread adoption of matrix-based methods. The frads Python library with a series of command-line tools was developed to automate the entire matrix-based simulation process, lowering entry barriers and reducing human error. Co-simulation between EnergyPlus and Radiance was also enabled using the Python library from EnergyPlus. Key Innovations • Command-line based automation of Radiance matrix-based simulation methods • Python library facilitates broader adoption of Radiance matrix-based simulation methods • Radiance EnergyPlus run-time integration enabling the modeling of advanced control systems Practical Implications The frads library, with associated command-line tools, provides practitioners with the capability to easily adopt and use Radiance matrix-based simulation methods for various daylighting, solar control, and energy-related evaluations. Frads' current form is designed for 1) users familiar with a command-line interface and 2) software developers to integrate the matrix-based methods into existing software packages.

Wang, Taoning↗
DOE OSTI2018

Half-filled Landau levels: A continuum and sign-free regularization for three-dimensional quantum critical points

In this paper, we explore a method for regulating 2+1D quantum critical points in which the ultraviolet cutoff is provided by the finite density of states of particles in a magnetic field rather than by a lattice. Such Landau-level quantization allows for numerical computations on arbitrary manifolds, like spheres, without introducing lattice defects. In particular, when half-filling a Landau level with $N = 4$ electron flavors, with appropriate interaction anisotropies in flavor space, we obtain a fully continuum regularization of the $\mathrm{O}(5)$ nonlinear sigma model with a topological term, which has been conjectured to flow to a deconfined quantum critical point. We demonstrate that this model can be solved by both infinite density-matrix renormalization group (DMRG) calculations and sign-free determinantal quantum Monte Carlo. DMRG calculations estimate the scaling dimension of the $\mathrm{O}(5)$ vector operator to be in the range $\mathrm{Δ_V}$ ~ $0.55-0.7$, depending on the stiffness of the nonlinear sigma model. Future Monte Carlo simulations will be required to determine whether this dependence is a finite-size effect or further evidence for a weak first-order transition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Apparent permeability prediction of organic shale with generalized lattice Boltzmann model considering surface diffusion effect

Gas flow in shale is associated with both organic matter (OM) and inorganic matter (IOM) which contain nano-pores ranging in size from a few to hundreds of nano-meters. In addition to the non-continuum effect which leads to an apparent permeability of gas higher than the intrinsic permeability, the surface diffusion of adsorbed gas in organic pores also can influence the apparent permeability through its own transport mechanism. In this study, a generalized lattice Boltzmann model (GLBM) is employed for gas flow through the reconstructed shale matrix consisting of OM and IOM. The Expectation–Maximization (EM) algorithm is used to assign the pore size distribution to each component, and the dusty gas model (DGM) and generalized Maxwell–Stefan model (GMS) are adopted to calculate the apparent permeability accounting for multiple transport mechanisms including viscous flow, Knudsen diffusion and surface diffusion. Effects of pore radius and pressure on permeability of both IOM and OM as well as effects of Langmuir parameters on OM are investigated. The effect of total organic content and distribution on the apparent permeability of the reconstructed shale matrix at different surface diffusivity is also studied. It is found that the influence of pore size and pressure on the apparent permeability of organic matter is affected by the surface diffusion of adsorbed gas. Furthermore, surface diffusion plays a significant role in determining apparent permeability and the velocity distribution of shale matrix.

02 PETROLEUM↗
DOE OSTI2021

GIS Resource Compilation Map Package - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups include: new/revised datasets (paleo-geothermal features, geochemistry, geophysics, heat flow, slip and dilation, potential structures, geothermal power plants, positive and negative test sites), machine learning model input grids, machine learning models (Artificial Neural Network (ANN), Extreme Learning Machine (ELM), Bayesian Neural Network (BNN), Principal Component Analysis (PCA/PCAk), Non-negative Matrix Factorization (NMF/NMFk) - supervised and unsupervised), original NV Play Fairway data and models, and NV cultural/reference data. See layer descriptions for additional metadata. Smaller GIS resource packages (by category) can be found in the related datasets section of this submission. A submission linking the full codebase for generating machine learning output models is available through the "Related Datasets" link on this page, and contains results beyond the top picks present in this compilation.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Quark-flavor symmetries and their violation in quantum chromodynamics

In Quantum Chromodynamics, the hadrons consisting of light (u, d, s) and heavy (c, b) quarks are subject to approximate flavor symmetries, providing the basis for powerful effective theories. I will briefly overview the origin of these symmetries and the scale of their violation. The current precision tests of Standard Model in the electroweak decays of hadrons demand an accurate quantitative account of flavor-symmetry violation effects. I will discuss the continuum (non-lattice) QCD calculation of these effects in hadronic matrix elements, taking as an example the decay constants of heavy–light hadrons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Mutual information prediction for strongly correlated systems

We have trained a new machine-learning (ML) model which predicts mutual information (MI) for strongly correlated systems. This is a complex quantity, which is much more difficult to predict than one-site entropies, but carries important information about the correlation structure inside electronic systems. In this work, we replaced the expensive density matrix renormalization group (DMRG) calculations by newly trained ML model for prediction of the mutual information. We show the performance of the model on two important tasks: (a) to determine the correlation structure and (b) to determine ordering of orbitals for accurate DMRG calculations. In conclusion, the results are compared with the MI obtained from accurate DMRG calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗