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At least 235 records · Page 13

Accurate Holdup Calculations with Predictive Modeling & Data Integration

In facilities that process special nuclear material (SNM) it is important to account accurately for the fissile material that enters and leaves the plant. Although there are many stages and processes through which materials must be traced and measured, the focus of this project is material that is “held-up” in equipment, pipes, and ducts during normal operation and that can accumulate over time into significant quantities. Accurately estimating the holdup is essential for proper SNM accounting (vis-à-vis nuclear non-proliferation), criticality and radiation safety, waste management, and efficient plant operation. Usually it is not possible to directly measure the holdup quantity and location, so these must be inferred from measured radiation fields, primarily gamma and less frequently neutrons. Current methods to quantify holdup, i.e. Generalized Geometry Holdup (GGH), primarily rely on simple source configurations and crude radiation transport models aided by ad hoc correction factors. This project seeks an alternate method of performing measurement-based holdup calculations using a predictive model that employs state-of-the-art radiation transport codes capable of accurately simulating such situations. Inverse and data assimilation methods use the forward transport model to search for a source configuration that best matches the measured data and simultaneously provide an estimate of the level of confidence in the correctness of such configuration. In this work the holdup problem is re-interpreted as an inverse problem that is under-determined, hence may permit multiple solutions. A probabilistic approach is applied to solving the resulting inverse problem. This approach rates possible solutions according to their plausibility given the measurements and initial information. This is accomplished through the use of Bayes’ Theorem that resolves the issue of multiple solutions by giving an estimate of the probability of observing each possible solution. To use Bayes’ Theorem, one must have a model y(x) that maps the state variables x (the solution in this case) to the measurements y. In this case, the unknown state variables are the configuration and composition of the heldup SNM. The measurements are the detector readings. Thus, the natural model is neutral-particle radiation transport where a wealth of computational tools exists for performing these simulations accurately and efficiently. The combination of predictive model and Bayesian inference forms the Data Integration with Modeled Predictions (DIMP) method that serves as foundation for this project. The cost functional describing the model-to-data misfit is computed via a norm created by the inverse of the covariance matrix of the model parameters and responses. Since the model y(x) for the holdup problem is nonlinear, a nonlinear optimization on Q is conducted via Newton-type iterative methods to find the optimal values of the model parameters x. This project comprised a collaboration between NC State University (NCSU), the University of South Carolina (USC), and Oak Ridge National Laboratory (ORNL). The project was originally proposed in seven main tasks with an eighth contingency task to be performed if time and funding permitted; in fact time did not permit commencement of the contingency task and it was not performed. The remaining tasks involved holdup analysis with gamma detection strategies and separately with neutrons based on coincidence counting. Early in the project, and upon consultation with experts in coincidence counting it became evident that this approach is not viable for holdup applications and this task was replaced with an alternative, but valuable investigation that was carried out by the USC partner. Nevertheless, the experimental 4 measurements at ORNL of both gamma and neutron sources for the purpose of constructing Detector Response Functions (DRFs) with the associated uncertainties were indeed completed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Fermilab Booster loss modelling and rebalancing using Bayesian methods

Fermilab Booster is being upgraded for the PIP-II project to support 20Hz ramp rate at higher intensities. Loss trip limits determine the achievable peak power. To meet PIP-II requirements, losses need to be halved as compared to current levels. Losses primarily occur at injection and transition crossing, with both gradually increasing and threshold-like intensity-dependent behaviors. The existing simulation models are not yet good enough for quantitative loss predictions. In practice, it will be necessary to tune up the Booster using iterative methods and operator intuition. In this paper we present an effort to systematically model Booster losses using active learning (Bayesian exploration) techniques, and subsequently to rebalance them for higher trip limit margins. We first created several sets of spatially and temporally isolated orbit and optics knobs, and trained Gaussian process models for each beam loss monitor as well as beam current. This is a complex task due to safety and timing requirements – we discuss mitigations such as uncertainty constraints and approximate fitting. Once models are stable, we perform large-scale single and multi-objective tuning using scalarized objectives made up of critical beam loss locations. Our results demonstrate significant rebalancing of losses, increasing trip margins, as well as an overall improvement in beam transmission efficiency. We are exploring how to combine existing simulations with experimental data and automate the collection procedure so that more advanced surrogate models can be created over time.

Kuklev, Nikita [Fermilab]↗

Interpolative Separable Density Fitting Decomposition for Accelerating Hybrid Density Functional Calculations with Applications to Defects in Silicon

We present a new efficient way to perform hybrid density functional theory (DFT)-based electronic structure calculations. The new method uses an interpolative separable density fitting (ISDF) procedure to construct a set of numerical auxiliary basis vectors and a compact approximation of the matrix consisting of products of occupied orbitals represented in a large basis set such as the planewave basis. Such an approximation allows us to reduce the number of Poisson solves from O ($N$ $^{2}_{ϵ}$) to O ( N ϵ ) when we apply the exchange operator to occupied orbitals in an iterative method for solving the Kohn–Sham equations, where Ne is the number of electrons in the system to be studied. We show that the ISDF procedure can be carried out in O ($N$ $^{3}_{ϵ}$) operations, with a much smaller preconstant compared to methods used in existing approaches. When combined with the recently developed adaptively compressed exchange (ACE) operator formalism, which reduces the number of times the exchange operator needs to be updated, the resulting ACE-ISDF method significantly reduces the computational cost associated with the exchange operator by nearly 2 orders of magnitude compared to existing approaches for a large silicon system with 1000 atoms. We demonstrate that the ACE-ISDF method can produce accurate energies and forces for insulating and metallic systems and that it is possible to obtain converged hybrid functional calculation results for a 1000-atom bulk silicon within 10 min on 2000 computational cores. We also show that ACE-ISDF can scale to 8192 computational cores for a 4096-atom bulk silicon system. We use the ACE-ISDF method to geometrically optimize a 1000-atom silicon system with a vacancy defect using the HSE06 functional and computes its electronic structure. Here, we find that that the computed energy gap from the HSE06 functional is much closer to the experimental value compared to that produced by semilocal functionals in the DFT calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Score-based denoising for atomic structure identification

We propose an effective method for removing thermal vibrations that complicate the task of analyzing complex dynamics in atomistic simulation of condensed matter. Our method iteratively subtracts thermal noises or perturbations in atomic positions using a denoising score function trained on synthetically noised but otherwise perfect crystal lattices. The resulting denoised structures clearly reveal underlying crystal order while retaining disorder associated with crystal defects. Purely geometric, agnostic to interatomic potentials, and trained without inputs from explicit simulations, our denoiser can be applied to simulation data generated from vastly different interatomic interactions. The denoiser is shown to improve existing classification methods, such as common neighbor analysis and polyhedral template matching, reaching perfect classification accuracy on a recent benchmark dataset of thermally perturbed structures up to the melting point. Demonstrated here in a wide variety of atomistic simulation contexts, the denoiser is general, robust, and readily extendable to delineate order from disorder in structurally and chemically complex materials.

36 MATERIALS SCIENCE↗

An FFT-based approach for Bloch wave analysis: application to polycrystals

A method based on the Fast Fourier Transform is proposed to obtain the dispersion relation of acoustic waves in heterogeneous periodic media with arbitrary microstructures. The microstructure is explicitly considered using a voxelized Representative Volume Element (RVE). The dispersion diagram is obtained solving an eigenvalue problem for Bloch waves in Fourier space. To this aim, two linear operators representing stiffness and mass are defined through the use of differential operators in Fourier space. The smallest eigenvalues are obtained using the implicitly restarted Lanczos and the subspace iteration methods, and the required inverse of the stiffness operator is done using the conjugate gradient with a preconditioner. The method is used to study the propagation of acoustic waves in elastic polycrystals, showing the strong effect of crystal anistropy and polycrystaline texture on the propagation. It is shown that the method combines the simplicity of classical Fourier series analysis with the versatility of Finite Elements to account for complex geometries proving an efficient and general approach which allows the use of large RVEs in 3D.

97 MATHEMATICS AND COMPUTING↗

Microscopic Theory of Nuclear Fission: A Review

This paper reviews how nuclear fission is described within nuclear density functional theory. A distinction should be made between spontaneous fission, where half-lives are the main observables and quantum tunnelling the essential concept, and induced fission, where the focus is on fragment properties and explicitly time-dependent approaches are often invoked. Overall, the cornerstone of the density functional theory approach to fission is the energy density functional formalism. The basic tenets of this method, including some well-known tools such as the Hartree–Fock–Bogoliubov (HFB) theory, effective two-body nuclear potentials such as the Skyrme and Gogny force, finite-temperature extensions and beyond mean-field corrections, are presented succinctly. The energy density functional approach is often combined with the hypothesis that the time-scale of the large amplitude collective motion driving the system to fission is slow compared to typical time-scales of nucleons inside the nucleus. In practice, this hypothesis of adiabaticity is implemented by introducing (a few) collective variables and mapping out the many-body Schrödinger equation into a collective Schrödinger-like equation for the nuclear wave-packet. The region of the collective space where the system transitions from one nucleus to two (or more) fragments defines what are called the scission configurations. The inertia tensor that enters the kinetic energy term of the collective Schrödinger-like equation is one of the most essential ingredients of the theory, since it includes the response of the system to small changes in the collective variables. For this reason, the two main approximations used to compute this inertia tensor, the adiabatic time-dependent HFB and the generator coordinate method, are presented in detail, both in their general formulation and in their most common approximations. The collective inertia tensor enters also the Wentzel–Kramers–Brillouin (WKB) formula used to extract spontaneous fission half-lives from multi-dimensional quantum tunnelling probabilities (For the sake of completeness, other approaches to tunnelling based on functional integrals are also briefly discussed, although there are very few applications.) It is also an important component of some of the time-dependent methods that have been used in fission studies. Concerning the latter, both the semi-classical approaches to time-dependent nuclear dynamics and more microscopic theories involving explicit quantum-many-body methods are presented. One of the hallmarks of the microscopic theory of fission is the tremendous amount of computing needed for practical applications. In particular, the successful implementation of the theories presented in this article requires a very precise numerical resolution of the HFB equations for large values of the collective variables. This aspect is often overlooked, and several sections are devoted to discussing the resolution of the HFB equations, especially in the context of very deformed nuclear shapes. In particular, the numerical precision and iterative methods employed to obtain the HFB solution are documented in detail. Finally, a selection of the most recent and representative results obtained for both spontaneous and induced fission is presented, with the goal of emphasizing the coherence of the microscopic approaches employed. In conclusion, although impressive progress has been achieved over the last two decades to understand fission microscopically, much work remains to be done. Several possible lines of research are outlined in the conclusion.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

An FFT-based micromechanical model for gradient enhanced brittle fracture

Damage models incorporated within FFT-based micromechanical methods have received much attention recently because of the need to better understand and predict brittle and ductile fracture. An important aspect of a damage model is non-local regularization, which removes the mesh dependence of the predictions that otherwise become physically unacceptable upon grid refinement. In this work, the Helmholtz-type equation for non-local gradient regularization of a damage model on a distorted grid is solved using an FFT-based approach. Further, the resulting system of equations is solved using the Jacobi iterative method. The model is applied to simulate brittle fracture of an intermetallic. The influence of the time and space discretization, the length-scale parameter, and intermetallic crystallographic orientation on crack evolution is studied.

36 MATERIALS SCIENCE↗

Random Phase Approximation Correlation Energy Using Real-Space Density Functional Perturbation Theory

We present a real-space method for computing the random phase approximation (RPA) correlation energy within Kohn–Sham density functional theory, leveraging the low-rank nature of the frequency-dependent density response operator. In particular, we employ a cubic-scaling formalism based on density functional perturbation theory that circumvents the calculation of the response function matrix, instead relying on the ability to compute its product with a vector through the solution of the associated Sternheimer linear systems. We develop a large-scale parallel implementation of this formalism using the subspace iteration method in conjunction with the spectral quadrature method while employing the Kronecker product-based method for the application of the Coulomb operator and the conjugate orthogonal conjugate gradient method for the solution of the linear systems. We demonstrate convergence with respect to key parameters and verify the method’s accuracy by comparing with plane-wave results. We show that the framework achieves good strong scaling to many thousands of processors, reducing the time to solution for a lithium hydride system with 128 electrons to around 150 s on 4608 processors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Meshless discretization of the discrete-ordinates transport equation with integration based on Voronoi cells

The time-dependent, gray, linear radiation transport equation is discretized using the meshless local Petrov-Galerkin method with reproducing kernels. The integration is performed using a Voronoi tessellation, which creates a partition of unity that only depends on the position and extent of the kernels. The resolution of the integration automatically follows the particles and requires no manual adjustment. The discretization includes streamline-upwind Petrov-Galerkin stabilization to prevent oscillations and improve numerical conditioning. The angular quadrature is selectively refineable to increase angular resolution in chosen directions. The time discretization is done using backward Euler. The transport solve for each direction and the solve for the scattering source are both done using Krylov iterative methods. The results indicate first-order convergence in time and second-order convergence in space for linear reproducing kernels.

97 MATHEMATICS AND COMPUTING↗

Three-dimensional Skyrme Hartree-Fock-Bogoliubov solver in coordinate-space representation

The coordinate-space representation of the Hartree-Fock-Bogoliubov theory is the method of choice to study weakly bound nuclei whose properties are affected by the quasiparticle continuum space. To describe such systems, we developed a three-dimensional Skyrme-Hartree-Fock-Bogoliubov solver HFBFFT based on the existing, highly optimized and parallelized Skyrme-Hartree-Fock code Sky3D. The code does not impose any self-consistent spatial symmetries such as mirror inversions or parity. The underlying equations are solved in HFBFFT directly in the canonical basis using the fast Fourier transform. To remedy the problems with pairing collapse, we implemented the soft energy cutoff and pairing annealing. The convergence of HFB solutions was improved by a sub-iteration method. The Hermiticity violation of differential operators brought by Fourier-transform-based differentiation has also been solved. Furthermore, the accuracy and performance of HFBFFT were tested by benchmarking it against other HFB codes, both spherical and deformed, for a set of nuclei, both well-bound and weakly-bound.

3D coordinate-space representation↗

Synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON): A statistical model based iterative image reconstruction method to eliminate limited-view artifacts and to mitigate the temporal-average artifacts in time-resolved CT

Purpose: In x-ray computed tomography (CT), a violation of the Tuy data sufficiency condition leads to limited-view artifacts. In some applications, it is desirable to use data corresponding to a narrow temporal window to reconstruct images with reduced temporal-average artifacts. However, the need to reduce temporal-average artifacts in practice may result in a violation of the Tuy condition and thus undesirable limited-view artifacts. In this paper, the authors present a new iterative reconstruction method, synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON), to eliminate limited-view artifacts using data acquired within an ultranarrow temporal window that severely violates the Tuy condition. Methods: In time-resolved contrast enhanced CT acquisitions, image contrast dynamically changes during data acquisition. Each image reconstructed from data acquired in a given temporal window represents one time frame and can be denoted as an image vector. Conventionally, each individual time frame is reconstructed independently. In this paper, all image frames are grouped into a spatial–temporal image matrix and are reconstructed together. Rather than the spatial and/or temporal smoothing regularizers commonly used in iterative image reconstruction, the nuclear norm of the spatial–temporal image matrix is used in SMART-RECON to regularize the reconstruction of all image time frames. This regularizer exploits the low-dimensional structure of the spatial–temporal image matrix to mitigate limited-view artifacts when an ultranarrow temporal window is desired in some applications to reduce temporal-average artifacts. Both numerical simulations in two dimensional image slices with known ground truth and in vivo human subject data acquired in a contrast enhanced cone beam CT exam have been used to validate the proposed SMART-RECON algorithm and to demonstrate the initial performance of the algorithm. Reconstruction errors and temporal fidelity of the reconstructed images were quantified using the relative root mean square error (rRMSE) and the universal quality index (UQI) in numerical simulations. The performance of the SMART-RECON algorithm was compared with that of the prior image constrained compressed sensing (PICCS) reconstruction quantitatively in simulations and qualitatively in human subject exam. Results: In numerical simulations, the 240{sup ∘} short scan angular span was divided into four consecutive 60{sup ∘} angular subsectors. SMART-RECON enables four high temporal fidelity images without limited-view artifacts. The average rRMSE is 16% and UQIs are 0.96 and 0.95 for the two local regions of interest, respectively. In contrast, the corresponding average rRMSE and UQIs are 25%, 0.78, and 0.81, respectively, for the PICCS reconstruction. Note that only one filtered backprojection image can be reconstructed from the same data set with an average rRMSE and UQIs are 45%, 0.71, and 0.79, respectively, to benchmark reconstruction accuracies. For in vivo contrast enhanced cone beam CT data acquired from a short scan angular span of 200{sup ∘}, three 66{sup ∘} angular subsectors were used in SMART-RECON. The results demonstrated clear contrast difference in three SMART-RECON reconstructed image volumes without limited-view artifacts. In contrast, for the same angular sectors, PICCS cannot reconstruct images without limited-view artifacts and with clear contrast difference in three reconstructed image volumes. Conclusions: In time-resolved CT, the proposed SMART-RECON method provides a new method to eliminate limited-view artifacts using data acquired in an ultranarrow temporal window, which corresponds to approximately 60{sup ∘} angular subsectors.

60 APPLIED LIFE SCIENCES↗

Nonperturbative analysis of field theories quantized on the light cone (Final Scientific Report for ER41087)

The primary focus of the work was the development of methods for the nonperturbative solution of quantum chromodynamics (QCD) in a form that yields wave functions for the eigenstates, from which hadronic properties can be computed. The principal approach was to use a light-front Hamiltonian formulation. In light-front coordinates, t+z/c plays the role of time, with t the ordinary time, z a space direction, and c the speed of light. This leads to a relativistic formulation that retains useful characteristics of nonrelativistic treatments. A bound state of many constituents can be represented by wave functions that define probabilities for each possible arrangement of internal momenta. These functions satisfy integral equations that can be approximated numerically to yield a matrix representation. The matrix problem can be solved by iterative methods. The approximate wave functions can then be used to compute properties of the bound state. Methods have been developed for model theories and gauge theories, including quantum electrodynamics and theories that are supersymmetric. The work has required the development of new numerical algorithms and computer codes for singular integral equations and eigenvalue problems. A key aspect of the work is the construction of practical procedures for nonperturbative regularization and renormalization. Two methods of regularization have been studied. One is the addition of heavy Pauli--Villars (PV) particles to the Lagrangian, with their metrics and couplings tuned to provide the necessary cancellations in the regularization. The other method of regularization is the addition of supersymmetric partners, to extend a theory to a supersymmetric form. The supersymmetric theories were solved by the supersymmetric discrete light-cone quantization (SDLCQ) method. The most significant accomplishments of the project were the SDLCQ calculation of direct evidence for a Maldacena duality conjecture, construction of a practical light-front quantization for QED in an arbitrary covariant gauge, and invention of the light-front coupled-cluster method, designed to eliminate the need for Fock-space truncations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Pre-commercial Demonstration of Direct Non-iterative State Estimator for Operational Use of Synchrophasor Management Systems

The objective of this project was to demonstrate functionality and performance of a Direct Non-iterative State Estimator (DNSE) integrated with NYPA’s Energy Management System (EMS) and with enhanced Real Time Dynamics Monitoring System (RTDMS) synchrophasor platform from Electric Power Group (EPG). DNSE is designed to overcome a major obstacle to operational use of Synchro-Phasor Management Systems (SPMS) by providing to synchrophasor management systems (SPMS) applications a consistent and a complete synchrophasor data foundation in the same way that a traditional EMS State Estimator (SE) provides to EMS applications. Specifically, DNSE is designed to use synchrophasor measurements collected by a central PDC, Supervisory Control and Data Acquisition (SCADA) measurements, and Energy Management System (EMS) network model, to obtain the complete state of the utility’s operating model at rates that are close to the synchrophasor data rates. In this way, the system is comprehensive in that it does not only cover the part of the network that is “visible” via synchrophasors, but also the part that is only “visible” through the SCADA measurements. Visualization needs associated with the use of DNSE results are fulfilled through suitably enhanced Real Time Dynamics Monitoring System (RTDMS), with the enhancements implemented by EPG. This project had the following goals in mind: To advance the deployment of commercial grade DNSE software application that relies on synchrophasor and SCADA data ; Apply DNSE at other utilities, to address a generic and fundamental need for “clean” operational data for synchrophasor applications; Provide means for “live” estimated data access by control system operators; Enhance potential for situational awareness through full system operational model coverage; Sub-second execution rate of the Direct Non-iterative State Estimator, eventually at a near-phasor data rate execution speed, i.e. < 0.1 sec. Anticipated benefits from this projects are: Enhanced reliability and improvements in the economic efficiency of bulk power system planning and operations; Providing “clean” data to other synchrophasor applications; Enhancement of situational awareness by providing the full operational model updated at near synchrophasor rate; A production-grade software tool that incorporate synchrophasor and SCADA data; Provides a basis for development of next generation monitoring and control applications, based on both SCADA and PMU data. Quanta Technology (QT) team worked in collaboration with Electric Power Group (EPG) whose team has enhanced its commercial Real Time Dynamics Monitoring System (RTDMS) to accommodate the requirements posed by DNSE application. EPG also provided its ePDC and Model-less Data Conditioning (PDVC) software for integration with DNSE+. QT developed the system requirements for DNSE; developed system architecture and defined interfaces between internal DNSE components. The core DNSE algorithm with all surrounding interfaces was named DNSE+. Since the DNSE development was done in a simulated system environment, QT used its PMU simulator that was enhanced during this project for development and factory acceptance testing (FAT). SCADA data in this stage was simulated by commercial PSS/e software. The output of DNSE are estimates of System states in C37.118-2 format, sent to RTDMS for further processing and display. As the number of these states is large, it was necessary to expand the C37.111-2 standard to accommodate large data sets. This enhancement was implemented in RTDMS. The demonstration of pre-production DNSE technology was done at NYPA using streaming field data from NYPA PMUs and from its RTUs through their SCADA system. NYPA provided ICCP interface as well as Common Information Model (CIM). The relevance of the DNSE+ application is that it provides state estimation of the power system based on hybrid set of data, consisting of both available PMU data and SCADA measurements. As this is a direct, non-iterative method of calculation of the system states, if does not suffer from convergence issues which is potential problem for conventional state estimators. Also, it can take any available PMU measurements, so it does not need to have a high percentage of PMU coverage needed in the case of Linear State Estimator. As the DNSE calculates synchrophasors of the system states (both phase and absolute value) as sub-second rate, this application can provide a basis for development of next generation of applications based both on SCADA and PMU data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Distributionally Robust Partially Observable Markov Decision Process with Moment-Based Ambiguity

In this paper, we consider a distributionally robust partially observable Markov decision process (DR-POMDP), where the distribution of the transition-observation probabilities is unknown at the beginning of each decision period, but their realizations can be inferred using side information at the end of each period after an action being taken. We build an ambiguity set of the joint distribution using bounded moments via conic constraints and seek an optimal policy to maximize the worst-case (minimum) reward for any distribution in the set. We show that the value function of DR-POMDP is piecewise linear convex with respect to the belief state and propose a heuristic search value iteration method for obtaining lower and upper bounds of the value function. We conduct numerical studies and demonstrate the computational performance of our approach via testing instances of a dynamic epidemic control problem. Our results show that DR-POMDP can produce more robust policies under misspecified distributions of transition-observation probabilities as compared to POMDP but has less costly solutions than robust POMDP. The DR-POMDP policies are also insensitive to varying parameter in the ambiguity set and to noise added to the true transition-observation probability values obtained at the end of each decision period.

97 MATHEMATICS AND COMPUTING↗

ESTABLISHING ROCK OUTCROP TIME SERIES AT VARIOUS DEPTHS IN A NONLINEAR SOIL COLUMN

Nonlinear soil-structure interaction (NLSSI) analysis methods are currently being developed at Idaho National Laboratory (INL). Appendix B in ASCE 4 (2016) includes a framework for performing NLSSI analysis. For NLSSI analysis to be widely implemented in industry, it is important to demonstrate that accurate response in a dynamically loaded, nonlinear soil column can be produced. In performing NLSSI analysis, one approach is to consider vertically propagating shear and compressive waves that pass through a nonlinear soil column and into a structure. Using finite element techniques, the structure can be placed in a finite volume of nonlinear soil with a rock outcrop seismic time series applied to the bottom of the nonlinear soil. The necessary depth of the nonlinear soil mesh is dependent on the vertical soil stiffness when the model is in static and dynamic equilibrium. Run time, and therefore size of the meshed soil domain, is an important consideration when developing the NLSSI model. An approach is presented in this paper that establishes compatible rock outcrop seismic time series for reduced nonlinear soil mesh depths. To apply the approach, an example is developed using a reasonable soil column with a reasonable top-of-soil response spectrum. The approach is an iterative method which is applied in two steps. The first step is used to establish a reasonable rock outcrop time series at the highest depth considered. The second step is used to establish compatible rock outcrop time series at shallower depths.

42 ENGINEERING↗

Ordering of Trotterization: Impact on Errors in Quantum Simulation of Electronic Structure

Trotter–Suzuki decompositions are frequently used in the quantum simulation of quantum chemistry. They transform the evolution operator into a form implementable on a quantum device, while incurring an error—the Trotter error. The Trotter error can be made arbitrarily small by increasing the Trotter number. However, this increases the length of the quantum circuits required, which may be impractical. It is therefore desirable to find methods of reducing the Trotter error through alternate means. The Trotter error is dependent on the order in which individual term unitaries are applied. Due to the factorial growth in the number of possible orderings with respect to the number of terms, finding an optimal strategy for ordering Trotter sequences is difficult. In this paper, we propose three ordering strategies, and assess their impact on the Trotter error incurred. Initially, we exhaustively examine the possible orderings for molecular hydrogen in a STO-3G basis. We demonstrate how the optimal ordering scheme depends on the compatibility graph of the Hamiltonian, and show how it varies with increasing bond length. We then use 44 molecular Hamiltonians to evaluate two strategies based on coloring their incompatibility graphs, while considering the properties of the obtained colorings. We find that the Trotter error for most systems involving heavy atoms, using a reference magnitude ordering, is less than 1 kcal/mol. Relative to this, the difference between ordering schemes can be substantial, being approximately on the order of millihartrees. The coloring-based ordering schemes are reasonably promising—particularly for systems involving heavy atoms—however further work is required to increase dependence on the magnitude of terms. Finally, we consider ordering strategies based on the norm of the Trotter error operator, including an iterative method for generating the new error operator terms added upon insertion of a term into an ordered Hamiltonian.

97 MATHEMATICS AND COMPUTING↗

Application of HRGS for forensic characterization of uranium oxides, pure uranium metals and uranium alloys

A nondestructive iterative method for uranium-bearing material characterization with HRGS developed earlier in (J. appl. Rad. Isotopes, 166 (2020) 109433) is applied to determine matrix densities and uranium isotope masses of a variety of uranium materials, namely uranium ore, UO 2 and U 3 O 8 powders, fuel elements in the form of UO2 microspheres, uranium metal and uranium alloys. It is shown that U 3 O 8 powders with uranium mass fraction of about 84% can be distinguished from the powders of UO 2 with uranium mass fraction of about 87%; uranium products in the form of liquid or loose powder with matrix density of 0.5-2.0 g/cm 3 can be distinguished from uranium products in the form of compacted fuel elements with matrix density of 6.0-10.0 g/cm 3 and from pure metal uranium and uranium alloys with matrix density of 14.0- 19.0 g/cm 3 . In fuel microspheres based on UO2 the uranium mass fraction 88.02% measured by HRGS is consistent, within the measurement uncertainties, with the results of isotope dilution mass spectrometry 87.76±0.64 % and also is confirmed by X-ray diffraction technique. The uranium mass fraction of the uranium ore estimated as 0.08% by HRGS is consistent, within the measurement uncertainties, with the value 0.09±0.01% determined with WDXRF. Densities of two different uranium metal samples, estimated as 18.42 g/cm 3 and 19.33 g/cm 3 by HRGS are consistent with values 18.24±0.55 g/cm 3 and 18.86±0.59 g/cm 3 , respectively, obtained by the gas pycnometry technique.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Adaptive Variational Quantum Imaginary Time Evolution Approach for Ground State Preparation

Abstract An adaptive variational quantum imaginary time evolution (AVQITE) approach is introduced that yields efficient representations of ground states for interacting Hamiltonians on near‐term quantum computers. It is based on McLachlan's variational principle applied to imaginary time evolution of variational wave functions. The variational parameters evolve deterministically according to equations of motions that minimize the difference to the exact imaginary time evolution, which is quantified by the McLachlan distance. Rather than working with a fixed variational ansatz, where the McLachlan distance is constrained by the quality of the ansatz, the AVQITE method iteratively expands the ansatz along the dynamical path to keep the McLachlan distance below a chosen threshold. This ensures the state is able to follow the quantum imaginary time evolution path in the system Hilbert space rather than in a restricted variational manifold set by a predefined fixed ansatz. AVQITE is used to prepare ground states of H 4 , H 2 O, and BeH 2 molecules, where it yields compact variational ansätze and ground state energies within chemical accuracy. Polynomial scaling of circuit depth with system size is shown through a set of AVQITE calculations of quantum spin models. Finally, quantum Lanczos calculations are demonstrated alongside AVQITE without additional quantum resource costs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗