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At least 307 records · Page 17

Impact of Radial Reflector Fidelity on Neutronics and Vessel Fluence Simulations

The Consortium for Advanced Simulation of Light Water Reactors is developing the Virtual Environment for Reactor Applications (VERA), and the MPACT code, which is the primary deterministic neutron transport solver in VERA, provides sub-pin level flux and power distributions as part of full-scale cycle depletion and analysis. In such calculations, an important aspect is the radial reflector treatment. To improve the fidelity of the radial reflector treatment, MPACT was extended to approximate the modeling of the reactor’s structural components such as the core shroud, barrel, neutron pads, and vessel. This work explores several modeling configurations with varying levels of fidelity and computational burden and assesses the importance of modeling fidelity on the eigenvalue and pin power distribution. Two two-dimensional (2-D) problems were analyzed to assess the impact on eigenvalue and pin power distributions with low-fidelity, coarse square cell reflector representations: (1) a Watts Bar Nuclear Plant Unit 1 (WBN1) quarter-core slice with depletion and (2) an AP1000 quarter-core slice. In this work, the analyses showed that the effect on eigenvalue is fairly small, but the effect on pin power is more pronounced, especially locally in the assemblies closest to the periphery, where the maximum pin power difference is nearly 3.5% in the AP1000 case. Two additional 2-D problems were used to assess the comparison between the low-fidelity coarse square cell treatment and a high-fidelity geometric representation that uses subpin material specification: (1) the same WBN1 quarter-core slice and (2) a representative model of the NuScale small modular reactor (SMR), which features a solid reflector design with moderator holes. These results demonstrate that even a coarse, low-fidelity representation adequately captures the necessary simulation characteristics. Last, these capabilities were applied to the 2-D WBN1 quarter-core depletion to assess the impact on vessel fluence using VeraShift. From adjoint calculations, pins along the periphery were observed to be of highest importance for fluence calculation, so the impact of the reflector representation in MPACT could theoretically substantially affect the predicted result. However, it was observed that the change in pin powers along the periphery minimally impacts the maximum vessel fluence with a difference within the statistical uncertainty but provides terrific insight on the sensitivity of the peripheral pins.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Relativistic levels of mesic atoms

We revisit the derivation of the covariant two-body scalar-fermion equation with a Coulomb interaction, presented in a previous paper. We show that it can be given the formal aspect of a Dirac equation, but for the fact that the eigenvalue is also contained in one of the coefficients and thus it is not linearly included. The discussion of the boundary value problem is therefore different, although some properties of the Dirac equation can be recovered in an approximation bringing back to the concept of reduced mass. We discuss a mixed analytic-numerical method of solution which allows to obtain very accurate results and we calculate the lowest levels, states and QED corrections for pionic and kaonic atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Sampling electronic structure quadratic unconstrained binary optimization problems (QUBOs) with Ocean and Mukai solvers

The most advanced D-Wave Advantage quantum annealer has 5000+ qubits, however, every qubit is connected to a small number of neighbors. As such, implementation of a fully-connected graph results in an order of magnitude reduction in qubit count. To compensate for the reduced number of qubits, one has to rely on special heuristic software such as qbsolv, the purpose of which is to decompose a large quadratic unconstrained binary optimization (QUBO) problem into smaller pieces that fit onto a quantum annealer. In this work, we compare the performance of the open-source qbsolv which is a part of the D-Wave Ocean tools and a new Mukai QUBO solver from Quantum Computing Inc. (QCI). The comparison is done for solving the electronic structure problem and is implemented in a classical mode (Tabu search techniques). The Quantum Annealer Eigensolver is used to map the electronic structure eigenvalue-eigenvector equation to a QUBO problem, solvable on a D-Wave annealer. We find that the Mukai QUBO solver outperforms the Ocean qbsolv with one to two orders of magnitude more accurate energies for all calculations done in the present work, both the ground and excited state calculations. This work stimulates the further development of software to assist in the utilization of modern quantum annealers.

97 MATHEMATICS AND COMPUTING↗

Verification of the pin power reconstruction method in NESTLE

NESTLE is a 3D nodal core simulator that solves the few group neutron diffusion equation using the nodal expansion method (NEM) for the steady state (eigenvalue or fixed-source), adjoint (eigenvalue), and transient (eigenvalue or fixed-source) problems. NESTLE has been in use for over 25 years and has been continuously improved and developed. NESTLE can be used to model either Cartesian geometries (for use with typical PWR, BWR fuel assemblies) or hexagonal geometries (for use with VVER and other triangularly pitched fuel assemblies). As part of NESTLE's ongoing verification and validation process, several computational comparisons have been made to quantify the discrepancies in NESTLE's hexagonal pin power reconstruction method. In this paper, we present the results of these code-to-code comparisons and find that the root mean squared (RMS) error in pin power is comparable to other nodal codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A variational eigenvalue solver on a photonic quantum processor

Quantum computers promise to efficiently solve important problems that are intractable on a conventional computer. For quantum systems, where the physical dimension grows exponentially, finding the eigenvalues of certain operators is one such intractable problem and remains a fundamental challenge. The quantum phase estimation algorithm efficiently finds the eigenvalue of a given eigenvector but requires fully coherent evolution. Here we present an alternative approach that greatly reduces the requirements for coherent evolution and combine this method with a new approach to state preparation based on ansa¨tze and classical optimization. We implement the algorithm by combining a highly reconfigurable photonic quantum processor with a conventional computer. We experimentally demonstrate the feasibility of this approach with an example from quantum chemistry—calculating the ground-state molecular energy for He–H þ . The proposed approach drastically reduces the coherence time requirements, enhancing the potential of quantum resources available today and in the near future.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Elastic waves trapped by a homogeneous anisotropic semicylinder

It is established that the problem of elastic oscillations of a homogeneous anisotropic semicylinder (console) with traction-free lateral surface (Neumann boundary condition) has no eigenvalues when the console is clamped at one end (Dirichlet boundary condition). If the end is free, under additional requirements of elastic and geometric symmetry, simple sufficient conditions are found for the existence of an eigenvalue embedded in the continuous spectrum and generating a trapped elastic wave, that is, one which decays at infinity at an exponential rate. The results are obtained by generalizing the methods developed for scalar problems, which however require substantial modification for the vector problem in elasticity theory. Examples are given and open questions are stated. Bibliography: 53 titles.

97 MATHEMATICS AND COMPUTING↗

Universal Method of Modeling Linear Stationary Physical Fields

The aim of this paper is to develop a method, described earlier, of solving quantum-mechanical problems into a universal numerical method of modeling fields of various physical nature. This method is based on reducing the initial equation of mathematical physics describing a given physical field to a simpler inhomogeneous equation with a known fundamental solution. This equation is then transformed into an inhomogeneous integral equation with a kernel expressed in terms of the known fundamental solution. The obtained integral equation with boundary conditions is solved numerically. To confirm the efficiency of the proposed numerical method, a two-dimensional and a three-dimensional boundary value problem with known solutions have been solved. Another important illustration of the efficiency of the proposed method is the solution of quantum-mechanical problems for one-dimensional and two-dimensional quantum oscillators. It is shown that the considered method allows one to find the energy eigenvalues and the eigenfunctions with acceptable accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Topology optimization of 3D photonic crystals with complete bandgaps

The design of photonic crystals with complete bandgaps has recently received considerable research focus for numerous reasons. This work leverages well-known nonlinear programming techniques to alleviate the non-smoothness caused by degenerate eigenvalues such that topology optimization problems can be solved with the open-source IPOPT software. A fully-vectorial plane wave expansion technique is used with an iterative eigensolver to efficiently predict dispersion properties of candidate structures. Nonlinear programming is employed to solve the inverse problem of designing three-dimensional periodic structures that exhibit complete two-dimensional (2D) and three-dimensional (3D) photonic bandgaps. Mesh refinement is performed to alleviate the large computational burden of designing and analyzing photonic crystals, and a periodic density filter is implemented to impose a minimum feature size for manufacturability considerations.

97 MATHEMATICS AND COMPUTING↗

Verification of High-Fidelity Neutronics Code PROTEUS for C5G7 Benchmark Problems

Under the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the 3D whole core transport code PROTEUS has been developed at Argonne National Laboratory to perform the detailed 3D transport calculation for various reactor types including irregular or complex geometric reactors. PROTEUS includes two distinct transport solvers: SN and MOC. Among them, the MOC solver based on the extruded geometry, thus named MOCEX, can produce the faithful 3-D transport solutions by employing the rigorous and robust 2D/3D MOC formulation. This formulation overcomes the drawbacks of a full 3D MOC method requiring enormous memory and computational resources and resolves the instability issues of the 2D/1D method as well. The solution of MOCEX converges to that of a Monte Carlo code as the discretization of angle, space and energy is refined, unlike the 2D/1D method. As a verification and validation (V and V) effort of PROTEUS-MOCEX, this paper presents verification test results using the well-known 3D C5G7 benchmark problems by solving and comparing eigenvalues and pin powers with MCNP solutions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Creation of problem-dependent Doppler-broadened cross sections in the KENO Monte Carlo code

In this paper, we introduce a quick method for improving the accuracy of Monte Carlo simulations by generating one- and two-dimensional cross sections at a user-defined temperature before performing transport calculations. A finite difference method is used to Doppler-broaden cross sections to the desired temperature, and unit-base interpolation is done to generate the probability distributions for double differential two-dimensional thermal moderator cross sections at any arbitrarily user-defined temperature. The accuracy of these methods is tested using a variety of contrived problems. In addition, various benchmarks at elevated temperatures are modeled, and results are compared with benchmark results. Lastly, the problem-dependent cross sections are observed to produce eigenvalue estimates that are closer to the benchmark results than those without the problem-dependent cross sections.

42 ENGINEERING↗

Exact and Model Exchange-Correlation Potentials for Open-Shell Systems

The conventional approaches to the inverse density functional theory problem typically assume nondegeneracy of the Kohn–Sham (KS) eigenvalues, greatly hindering their use in open-shell systems. Here, we present a generalization of the inverse density functional theory problem that can seamlessly admit degenerate KS eigenvalues. Additionally, we allow for fractional occupancy of the Kohn–Sham orbitals to also handle noninteracting ensemble-v-representable densities, as opposed to just noninteracting pure-v-representable densities. We present the exact exchange-correlation (XC) potentials for six open-shell systems–four atoms (Li, C, N, and O) and two molecules (CN and CH 2 )–using accurate ground-state densities from configuration interaction calculations. We compare these exact XC potentials with model XC potentials obtained using nonlocal (B3LYP, SCAN0) and local/semilocal (SCAN, PBE, PW92) XC functionals. Although the relative errors in the densities obtained from these DFT functionals are of $O$(10 –3 to 10 –2 ), the relative errors in the model XC potentials remain substantially large–$O$(10 –1 to 10 0 ).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of a New Fixed-source Sensitivity Tally Capability in the MCNP® code [Abstract]

The development of a new fixed-source sensitivity tally capability is currently underway in the MCNP code. In recent research and development efforts that utilize machine learning to both seek problematic nuclear data as well as design experiments optimized to improve the nuclear data, the adjoint-weighted k-eigenvalue sensitivity tally capabilities have been heavily essential. In this paper, the motivation to expand the sensitivity tally capabilities beyond k-eigenvalues toward diverse fixed-source problems along with preliminary results and verification will be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Distributed Link Removal Using Local Estimation of Network Topology

In this paper, we consider the problem of network structure manipulation in the absence of information on the global network topology. In particular, the problem of removing some of links is investigated in order to slow or stop the spread of disease in a network while preserving its connectivity. Existing methods solve this combinatorial problem in a centralized manner and they require the global information of network structure. In this paper, we propose a distributed design algorithm to compute a suboptimal solution to this problem efficiently by mimicking gradient based method, namely by iteratively removing one or multiple links at a time from the network. Specifically, using matrix perturbation analysis we formulate an optimization problem involving the eigenvector associated with the largest eigenvalue of the adjacency matrix and whose solution is equal to a suboptimal solution to the original problem. This strategy also enables us to overcome the combinatorial issue of the problem. Distributed algorithms to estimate the eigenvector and to verify network’s connectivity are then proposed which facilitate us to solve the new optimization problem. In addition, topological insights into the proposed algorithm and optimality of its solution are also discussed. Lastly, the proposed distributed design method is demonstrated and evaluated via several numerical examples.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Cliffed Cape Does Not Trap Water Waves in the Sea of Constant Depth

The water wave problem is considered for a class of semi-infinite domains each having its shore shaped as a cliffed cape. In particular, the free surface of a water domain is supposed to be an infinite sector whose vertex angle is greater than π, whereas the water layer lying under the free surface is of constant depth. Under these assumptions it is shown that there are no trapped mode solutions of the problem for all values of a non-dimensional spectral parameter; in other words, no point eigenvalues are embedded in the continuous spectrum of the problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Model Order Reduction Algorithm for Estimating the Absorption Spectrum

The ab initio description of the spectral interior of the absorption spectrum poses both a theoretical and computational challenge for modern electronic structure theory. Due to the often spectrally dense character of this domain in the quantum propagator’s eigenspectrum for medium-to-large sized systems, traditional approaches based on the partial diagonalization of the propagator often encounter oscillatory and stagnating convergence. Electronic structure methods which solve the molecular response problem through the solution of spectrally shifted linear systems, such as the complex polarization propagator, offer an alternative approach which is agnostic to the underlying spectral density or domain location. This generality comes at a seemingly high computational cost associated with solving a large linear system for each spectral shift in some discretization of the spectral domain of interest. In this work, we present a novel, adaptive solution to this high computational overhead based on model order reduction techniques via interpolation. Model order reduction reduces the computational complexity of mathematical models and is ubiquitous in the simulation of dynamical systems and control theory. The efficiency and effectiveness of the proposed algorithm in the ab initio prediction of X-ray absorption spectra is demonstrated using a test set of challenging water clusters which are spectrally dense in the neighborhood of the oxygen K-edge. On the basis of a single, user defined tolerance we automatically determine the order of the reduced models and approximate the absorption spectrum up to the given tolerance. We also illustrate that, for the systems studied, the automatically determined model order increases logarithmically with the problem dimension, compared to a linear increase of the number of eigenvalues within the energy window. Furthermore, we observed that the computational cost of the proposed algorithm only scales quadratically with respect to the problem dimension.

IDREAM, K-Edge, theoretical, computational, electr↗

Laplace Transform–Based Quantum Eigenvalue Transformation via Linear Combination of Hamiltonian Simulation

Eigenvalue transformations, which include solving time-dependent differential equations as a special case, have a wide range of applications in scientific and engineering computation. While quantum algorithms for singular value transformations are well studied, eigenvalue transformations are distinct, especially for nonnormal matrices. Here, we propose an efficient quantum algorithm for performing a class of eigenvalue transformations that can be expressed as a certain type of matrix Laplace transformation. This allows us to significantly extend the recently developed linear combination of Hamiltonian simulation method [D. An, J.-P. Liu, and L. Lin, Phys. Rev. Lett., 131 (2023), 150603; D. An, A. M. Childs, and L. Lin, Commun. Math. Phys. 407, 19 (2026)] to represent a wider class of eigenvalue transformations, such as powers of the matrix inverse, 𝐴 −𝑘 , and the exponential of the matrix inverse, 𝑒 −𝐴 −1 . The latter can be interpreted as the solution of a mass-matrix differential equation of the form form 𝐴⁢𝑢′⁡⁡(𝑡) =−𝑢⁡(𝑡). We demonstrate that our eigenvalue transformation approach can solve this problem without explicitly inverting 𝐴, thereby reducing the computational complexity.

Laplace transform↗

Efficient phase-factor evaluation in quantum signal processing

Quantum signal processing (QSP) is a powerful quantum algorithm to exactly implement matrix polynomials on quantum computers. Asymptotic analysis of quantum algorithms based on QSP has shown that asymptotically optimal results can in principle be obtained for a range of tasks, such as Hamiltonian simulation and the quantum linear system problem. A further benefit of QSP is that it uses a minimal number of ancilla qubits, which facilitates its implementation on near-to-intermediate term quantum architectures. However, there is so far no classically stable algorithm allowing computation of the phase factors that are needed to build QSP circuits. Existing methods require the use of variable precision arithmetic and can only be applied to polynomials of a relatively low degree. We present here an optimization-based method that can accurately compute the phase factors using standard double precision arithmetic operations. We demonstrate the performance of this approach with applications to Hamiltonian simulation, eigenvalue filtering, and quantum linear system problems. Furthermore, our numerical results show that the optimization algorithm can find phase factors to accurately approximate polynomials of a degree larger than 10000 with errors below 10 -12 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗