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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Evolution of Pore Structure and Permeability of Rocks Under Hydrothermal Conditions (Final Report)

The physical and transport properties of porous rocks can be altered by a variety of diagenetic, metamorphic, and tectonic processes, and the changes that result are of critical importance to such industrial applications as resource recovery, carbon dioxide sequestration, and waste isolation in geologic formations. The associated interrelationships between rocks, pore fluids and deformation are also key to understanding many natural processes, including dynamic metamorphism, fault mechanics, fault stability and pressure solution creep. In this project, we investigated the changes of permeability and pore geometry owing to inelastic deformation by solution-transfer, brittle fracturing and dislocation creep. In particular, we studied the coupling between pore fluids and deformation in fluid-filled quartz, calcite, mudstones and ultramafic rocks and examine the effects of coupled mechanical and chemical processes on the evolution of porosity and permeability under hydrothermal conditions. The investigations used a combination of techniques, that included triaxial laboratory experiments; uniaxial compressive loading with in situ observations of microstructure; permeability under hydrostatic compression; observations of microstructure using optical and electron microscopes, and micro-CT imaging; and numerical calculations. Laboratory experiments were designed to provide mechanical and transport data under conditions that isolate the particular mechanisms responsible for the changes. The data obtained were used to quantify changes in surface roughness, porosity, pore dimensions and their spatial fluctuations. The results of the experiments and data from image analyses were compared to the results of network, finite-difference and other numerical models to verify the validity of experimentally established relations between permeability and other rock properties. A bibliography for the period from 2015-2019 is appended below. New results obtained in the final year and the unfunded extension period are detailed below.

58 GEOSCIENCES↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Cold-atom quantum simulator for string and hadron dynamics in non-Abelian lattice gauge theory

We propose an analog quantum simulator for simulating real-time dynamics of (1+1)-dimensional non-Abelian gauge theory well within the existing capacity of ultracold-atom experiments. The scheme calls for the realization of a two-state ultracold fermionic system in a one-dimensional bipartite lattice, and the observation of subsequent tunneling dynamics. Being based on the loop string hadron formalism of SU(2) lattice gauge theory, this simulation technique is completely SU(2) invariant and simulates accurate dynamics of physical phenomena such as string breaking and/or pair production. The scheme is scalable and particularly effective in simulating the theory in the weak-coupling regime, and also a bulk limit of the theory in the strong-coupling regime up to certain approximations. This paper also presents a numerical benchmark comparison of the exact spectrum and real-time dynamics of lattice gauge theory to that of the atomic Hamiltonian with an experimentally realizable range of parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Systematic mapping of the conformational landscape and dynamism of soluble fibrinogen

Background: Fibrinogen is a soluble, multisubunit, and multidomain dimeric protein, which, upon its proteolytic cleavage by thrombin, is converted to insoluble fibrin, initiating polymerization that substantially contributes to clot growth. Fibrinogen contains numerous, transiently accessible “cryptic” epitopes for hemostatic and immunologic proteins, suggesting that fibrinogen exhibits conformational flexibility, which may play functional roles in its temporal and spatial interactions. Hitherto, there have been limited integrative approaches characterizing the solution structure and internal flexibility of fibrinogen. Methods: Here, utilizing a multipronged, biophysical approach involving 2 solution-based techniques, temperature-dependent hydrogen-deuterium exchange mass spectrometry and small angle X-ray scattering, corroborated by negative stain electron microscopy, we present a holistic, conformationally dynamic model of human fibrinogen in solution. Results: Our data reveal 4 major and distinct conformations of fibrinogen accommodated by a high degree of internal protein flexibility along its central scaffold. We propose that the fibrinogen structure in the solution consists of a complex, conformational landscape with multiple local minima. This is further supported by the location of numerous point mutations that are linked to dysfibrinogenemia and posttranslational modifications, residing near the identified fibrinogen flexions. Conclusion: Further, this work provides a molecular basis for the structural “dynamism” of fibrinogen that is expected to influence the broad swath of its functionally diverse macromolecular interactions and fine-tune the structural and mechanical properties of blood clots.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Recursive Use of the Short-Time Fast Fourier Transform for Signature Analysis in Continuous Processes

Although a nuclear reactor is a hostile environment for sensing and electrical communications, the reactor core is amenable to acoustic communication. An acoustic measurement infrastructure (AMI) has been installed in the Advanced Test Reactor (ATR) to record acoustic signals that can capture its different operating regimes. AMI uses coolant pumps as continuous signal sources, coolant and structural components as transmission lines, and accelerometers to capture system motion. A recursive signal processing technique based on the short-time fast Fourier transform (STFFT) for continuous processes provides unique signatures for diagnostic and prognostic analyses from the system motion data. Here this article presents a recursive STFFT methodology that processes acoustic signals from continuous industrial processes. The article first discusses the initial STFFT use with simulated data to elucidate the basic principles necessary to understand and interpret the STFFT results from actual pump vibration data. Each repetitive use of the STFFT on pump vibration data using the results from the prior STFFT processing will generate additional complimentary time-frequency-based signatures. These signatures are generated by the coolant pumps operating under different process conditions. After each use of the STFFT, the resulting signatures provide exemplary examples of the diversity and intuitive nature of recursively using the STFFT. This article focuses on recursively using the STFFT to provide numerous complimentary and diverse signatures that will ultimately be inputs for machine learning algorithms that provide predictive data analytics. The intuitive nature of the information and signatures from recursive STFFT processing will also bring intuitive interpretation capabilities to machine learning and predictive data analytic techniques.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models

Visualization and analysis of multivariate data and their uncertainty are top research challenges in data visualization. Constructing fiber surfaces is a popular technique for multivariate data visualization that generalizes the idea of level-set visualization for univariate data to multivariate data. Here, in this paper, we present a statistical framework to quantify positional probabilities of fibers extracted from uncertain bivariate fields. Specifically, we extend the state-of-the-art Gaussian models of uncertainty for bivariate data to other parametric distributions (e.g., uniform and Epanechnikov) and more general nonparametric probability distributions (e.g., histograms and kernel density estimation) and derive corresponding spatial probabilities of fibers. In our proposed framework, we leverage Green's theorem for closed-form computation of fiber probabilities when bivariate data are assumed to have independent parametric and nonparametric noise. Additionally, we present a nonparametric approach combined with numerical integration to study the positional probability of fibers when bivariate data are assumed to have correlated noise. For uncertainty analysis, we visualize the derived probability volumes for fibers via volume rendering and extracting level sets based on probability thresholds. We present the utility of our proposed techniques via experiments on synthetic and simulation datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Subvoxel Control of Fiber Orientation via Multidirectional Shearing in 3D Printing

Anisotropy, the characteristic of materials exhibiting different properties based on their direction, is widespread in nature. Conventional manufacturing techniques often fall short in recreating such complex anisotropy. While 3D printing allows for precise fiber deposition in anisotropic composites, previous studies have only achieved bulk reorientation of fibers at the voxel level in two dimensions. This limits the replication of localized 3D anisotropies found in natural materials. To address this, a novel 3D printing technique is presented that enables subvoxel control of fiber orientation in all three directions using multidirectional shearing via nozzle rotation and inclination. The fiber orientation control in these experimental tests is driven by a numerical model, enabling a fully digital approach to program microstructures within a strand. This programmability is demonstrated through mechanical and thermal tests, illustrating a localized and controllable response to external stimuli. Achieving such complex anisotropy holds potential across several fields, including wearables and biomedical implants, lightweight composite structures, and energy storage technologies such as batteries and supercapacitors.

3D printing↗
DOE OSTI2025

Lines of Bound States in the Continuum in Monodisperse Microsphere Structures

Incorporating epitaxially grown active semiconductor media into self-assembled microsphere crystals has remained a major challenge as the curved geometry of the spheres is incompatible with conventional planar growth and patterning techniques. As a result, active photonic devices based on such self-assembled structures, which have other desirable properties such as enabling the rapid assembly of large area systems, have been elusive. Here, we numerically demonstrate an alternative route to creating high-Q resonances in microsphere-based nanophotonic assemblies compatible with standard optical gain materials. We show that close-packed layers of monodisperse microspheres can exhibit symmetry bandgaps, regardless of their layer stacking order. Thus, this microsphere environment can be used to create lines of bound states in the continuum (BICs) of an embedded slab made of active material. Using a realistic ZnS@SiO 2 (core-shell) architecture and sphere diameters compatible with scalable colloidal assembly, we predict sharp spectral features in angle-resolved transmission that trace these lines of BICs and persist in the presence of some fabrication disorder. Altogether, in enabling the integration of unpatterned epitaxial gain slabs with large-area colloidal microsphere assemblies, this approach opens a practical path toward active, dynamically reconfigurable photonic devices that leverage BIC physics for narrow-linewidth lasing and enhanced light–matter interactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

High-Order Mesh hr-adaptivity for Surface Fitting to Implicit Geometries

We present an ℎ𝑟-adaptivity framework for morphing a given mesh to fit a target surface prescribed as the zero isocontour of a discrete function. In this framework, high-order meshing is posed as a variational minimization problem that depends on the mesh quality prescribed via the target matrix optimization paradigm (TMOP) and position of a subset of mesh nodes with respect to the target surface. The proposed formulation ensures that the variational problem is converged and mesh quality degradation near the surface is limited, even when the mesh topology is incompatible with the target surface. Additionally, a mesh subset-based approach and ℎ-refinement is introduced to efficiently increase fitting accuracy while reducing the computational cost of the mesh morphing problem. The ℎ𝑟-adaptivity technique extends to different element types in two- and three-dimensions, and can be used in existing finite element and spectral element frameworks to obtain high-order body-fitted meshes. Various numerical experiments demonstrate the robustness and accuracy of the fitting approach for problems of practical interest such as Lagrangian hydrodynamics and topology optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Prediction of dynamic behavior of a system undergoing an exchange of components using a transmission simulator method

In systems with modular design, it is of interest to perform component exchanges to upgrade components and explore new system configurations. If the dynamics of the components are known, then dynamic substructuring can be used to obtain a prediction of system performance for the new configuration. The transmission simulator method is a substructuring technique that utilizes an additional fixture to apply an elastic boundary condition to a test article such that an appropriate dynamic response can be obtained for a given substructuring application, and the technique has been used widely for performing coupling and decoupling operations. Here, in this work, a modified transmission simulator method is proposed that allows a direct exchange of components to be performed. In a numerical demonstration, the proposed method is shown to accurately predict the dynamics of an assembly that has undergone a component exchange in which the exchanged components have different material properties and different geometric properties. This approach can be applied to dynamic qualification frameworks in which structures undergo modifications or upgrades rather than complete redesigns.

Component exchange↗
DOE OSTI2025

Polariton spectra under the collective coupling regime. I. Efficient simulation of linear spectra and quantum dynamics

We outline two general theoretical techniques to simulate polariton quantum dynamics and optical spectra under the collective coupling regimes described by a Holstein–Tavis–Cummings (HTC) model Hamiltonian. The first one takes advantage of sparsity of the HTC Hamiltonian, which allows one to reduce the cost of acting polariton Hamiltonian onto a state vector to the linear order of the number of states, instead of the quadratic order. The second one is applying the well-known Chebyshev series expansion approach for quantum dynamics propagation and to simulate the polariton dynamics in the HTC system; this approach allows us to use a much larger time step for propagation and only requires a few recursive operations of the polariton Hamiltonian acting on state vectors. These two theoretical approaches are general and can be applied to any trajectory-based non-adiabatic quantum dynamics methods. We apply these two techniques with our previously developed Lindblad-partially linearized density matrix approach to simulate the linear absorption spectra of the HTC model system, with both inhomogeneous site energy disorders and dipolar orientational disorders. Our numerical results agree well with the previous analytic and numerical work.

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

Probing the edge states of Chern insulators using microwave impedance microscopy

Microwave impedance microscopy (MIM) has been utilized to directly visualize topological edge states in many quantum materials. While the microwave response for conventional metals and insulators can be accurately quantified using simple lumped-element circuits, whose applicability to more exotic quantum systems remain limited. In this work, we present a general theoretical framework of the MIM response of arbitrary quantum materials. Applying it to topological edge states in a Chern insulator predicts an enhanced MIM response at the crystal boundaries due to collective edge magnetoplasmon (EMP) excitations. The unique resonance frequency of these plasmonic modes allows one to disentangle the signatures of topological versus trivial edge states. To benchmark our analytical predictions, we experimentally probe the MIM response of quantum anomalous Hall edge states in a Cr-doped (Bi,Sb) 2 Te 3 topological insulator and perform numerical simulations using a classical formulation of the EMP modes based on this realistic tip-sample geometry, both of which yield results consistent with our theoretical picture. Here we also show how the technique of MIM can be used to quantitatively extract the topological invariant of a Chern insulator and shed light on the microscopic nature of dissipation along the crystal boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2021

On-chip optical levitation with a metalens in vacuum

Optical levitation of dielectric particles in vacuum is a powerful technique for precision measurements, testing fundamental physics, and quantum information science. Conventional optical tweezers require bulky optical components for trapping and detection. Here, we design and fabricate an ultrathin dielectric metalens with a high numerical aperture of 0.88 at 1064 nm in vacuum. It consists of 500-nm-thick silicon nano-antennas, which are compatible with an ultrahigh vacuum. We demonstrate optical levitation of nanoparticles in vacuum with a single metalens. The trapping frequency can be tuned by changing the laser power and polarization. We also transfer a levitated nanoparticle between two separated optical tweezers. Optical levitation with an ultrathin metalens in vacuum provides opportunities for a wide range of applications including on-chip sensing. Such metalenses will also be useful for trapping ultracold atoms and molecules.

Shen, Kunhong↗
DOE OSTI2024

Characterization of Oscillatory Response of Light-Weight Wind Turbine Rotors under Controlled Gust Pulses

Given the industry-wide trend of continual increases in the size of utility-scale wind turbines, a point will come where reductions will need to be made in terms of the weight of the turbine’s blades to ensure they can be as long as needed without sacrificing structural stability. One such technique that may be considered is to decrease the material used for the shell and spar cap. While this will solve the weight issue, it creates a new one entirely—less material for the shell and spar cap will in turn create blades that are more flexible than what is currently used. This article aims to investigate how the oscillatory response of light-weight wind turbine rotors is affected by these flexibility changes. The object of our study is the Sandia National Lab National Rotor Testbed (SNL-NRT) wind turbine, which the authors investigated in the course of a research project supported by SNL. Using a reduced-order characterization (ROC) technique based on controlled gust pulses, introduced by the authors in a previous work, the aeroelastic dynamics of the NRT’s original baseline blade design and several of its flexible variations were studied via numerical simulations employing the CODEF multiphysics suite. Results for this characterization are presented and analyzed, including a generalization of the ROC of the SNL-NRT oscillatory dynamics to larger machines with geometrical similarity. The latter will prove to be valuable in terms of extrapolating results from the present investigation and other ongoing studies to the scale of current and future commercial machines.

Ponta, Fernando (ORCID:0000000321032864)↗
DOE OSTI2024

Convergence Analysis for an Online Data-Driven Feedback Control Algorithm

This paper presents convergence analysis of a novel data-driven feedback control algorithm designed for generating online controls based on partial noisy observational data. The algorithm comprises a particle filter-enabled state estimation component, estimating the controlled system’s state via indirect observations, alongside an efficient stochastic maximum principle-type optimal control solver. By integrating weak convergence techniques for the particle filter with convergence analysis for the stochastic maximum principle control solver, we derive a weak convergence result for the optimization procedure in search of optimal data-driven feedback control. Numerical experiments are performed to validate the theoretical findings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Modeling of a 1/20th Scaled-down Gas Reactor Using MOOSE-based Application Pronghorn

University of Idaho (UI) designed and built a 1/20th scaled-down HTGR system to examine the mixing and venting of helium and reactor cavity air after a loss-of-coolant, also known as LOCA, due to a break in the reactor pressure vessel. Computational fluid dynamics (CFD) models of the system were developed, but their computational cost is high for modeling long transient accident scenarios. The objective of the project is to develop a simulation of the scaled-down system using the MOOSE-based application Pronghorn. A numerical approach is needed to have a better understanding of the physics phenomena that takes place following a LOCA event, and it can guide plant designers to design parameters for the development of mitigation techniques. This scenario is applicable to all HTR designs including the pebble bed reactor concept.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗