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At least 109 records · Page 6

Machine Learning Calabi–Yau Metrics

We apply machine learning to the problem of finding numerical Calabi–Yau metrics. Building on Donaldson's algorithm for calculating balanced metrics on Kähler manifolds, we combine conventional curve fitting and machine-learning techniques to numerically approximate Ricci-flat metrics. We show that machine learning is able to predict the Calabi–Yau metric and quantities associated with it, such as its determinant, having seen only a small sample of training data. Using this in conjunction with a straightforward curve fitting routine, we demonstrate that it is possible to find highly accurate numerical metrics much more quickly than by using Donaldson's algorithm alone, with our new machine-learning algorithm decreasing the time required by between one and two orders of magnitude.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

p -adic reconstruction of rational functions in multiloop amplitudes

Numerical reconstruction techniques are widely employed in the calculation of multiloop scattering amplitudes. In recent years, it has been observed that the rational functions in multiloop calculations greatly simplify under partial fractioning. In this article, we present a technique to reconstruct rational functions directly in partial-fractioned form, by evaluating the functions at special integer points chosen for their properties under a p -adic metric. As an application, we apply this technique to reconstruct the largest rational function in the integration-by-parts reduction of one of the rank-5 integrals appearing in two-loop five-point full-color massless amplitude calculations in quantum chromodynamics. The number of required numerical probes (per prime field) is found to be around 25 times smaller than in conventional techniques, and the obtained result is 130 times smaller. The reconstructed result displays signs of additional structure that could be used to further reduce its size and the number of required probes. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Atomistic modeling of radiation damage in crystalline materials

This review discusses atomistic modeling techniques used to simulate radiation damage in crystalline materials. Radiation damage due to energetic particles results in the formation of defects. The subsequent evolution of these defects over multiple length and time scales requiring numerous simulations techniques to model the gamut of behaviors. This work focuses attention on current and new methodologies at the atomistic scale regarding the mechanisms of defect formation at the primary damage state.

36 MATERIALS SCIENCE↗

Super‐Droplet Method to Simulate Lagrangian Microphysics of Nuclear Fallout in a Homogeneous Cloud

Abstract Nuclear detonations produce hazardous local and global particles or fallout. Predicting fallout size, chemical components, and location is necessary to inform officials and determine immediate guidance for the public. However, existing nuclear detonation fallout models prescribe the particle size distributions based on limited observations. In this work, we apply the super‐droplet method, which is a numerical modeling technique developed for cloud microphysics, to simulate size distributions of particles in a mushroom cloud formed post‐detonation of a nuclear device. We model fallout formation and evolution with homogeneous nucleation and condensation of a single species and a Monte Carlo coagulation algorithm. We verify the numerical methods representing coagulation and condensation processes against analytical test problems. Additionally, we explore several scenarios for the integral system mass and yield in equivalent kilotons (kt) of TNT (trinitrotoluene). The fallout size distribution median diameter d pg follows a scaling law based on the integral system mass m v 0 kg and yield Y kt: nm. We test the effect of cloud turbulence, enhanced nucleation and growth, and vapor volatility with a sensitivity study. The range in median diameter predictions for simulations of historical tests performed over the Pacific encompass the measurements of particles sampled from the cloud caps. Predicted median particle size ranges up to 217, 123, 86, and 35 nm for historical tests with yields of 0.2, 0.7, 2, and 10 Mt, respectively. This work can be expanded in many different directions to build a more predictive model for fallout formation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Nuclear Responses with Neural-Network Quantum States

We introduce a variational Monte Carlo framework that combines neural-network quantum states with the Lorentz integral transform technique to compute the dynamical properties of self-bound quantum many-body systems in continuous Hilbert spaces. While broadly applicable to various quantum systems, including atoms and molecules, in this initial application we focus on the photoabsorption cross section of light nuclei, where benchmarks against numerically exact techniques are available. Our accurate theoretical predictions are complemented by robust uncertainty quantification, enabling meaningful comparisons with experiments. Here, we demonstrate that a relatively simple nuclear Hamiltonian—based on a leading-order pionless EFT expansion and known to accurately reproduce ground-state energies of nuclei with 𝐴 ≤ 40—also provides a reliable description of the photoabsorption cross section.

Ab initio calculations↗

Nuclear responses with neural-network quantum states

We introduce a variational Monte Carlo framework that combines neural-network quantum states with the Lorentz integral transform technique to compute the dynamical properties of self-bound quantum many-body systems in continuous Hilbert spaces. While broadly applicable to various quantum systems, including atoms and molecules, in this initial application we focus on the photoabsorption cross section of light nuclei, where benchmarks against numerically exact techniques are available. Our accurate theoretical predictions are complemented by robust uncertainty quantification, enabling meaningful comparisons with experiments. We demonstrate that a simple nuclear Hamiltonian, based on a leading-order pionless effective field theory expansion and known to accurately reproduce the ground-state energies of nuclei with $A\leq 20$ nucleons also provides a reliable description of the photoabsorption cross section.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

SonicPy: a suite of programs for ultrasound pulse-echo data acquisition and analysis

Sound speed and elastic constants measurements in solids and liquids are commonly performed using the ultrasound pulse-echo technique. Recent advances have expanded the use of this technique at numerous high pressure synchrotron beamlines and offline laboratories. However, the increased experimental throughput has revealed many limitations in existing software for handling the rapid measurement and the subsequent data-reduction. Here, we report the development of a collection of computer programs for sound speed measurements using the ultrasound pulse-echo technique, compatible with stepped multi-frequency, as well as broadband-pulse, couplant-corrected methods. The programs provide a highly interactive graphical interface, enable efficient measurement, exploration and near real-time analysis of the ultrasound data, and contain features useful for working with samples under high pressure and/or high temperature. The included analysis programs can alleviate the time required for data reduction from hours to less than a minute, allowing users to make timely and informed decisions regarding the appropriate experimental parameters.

97 MATHEMATICS AND COMPUTING↗

Calibrating the Classical Hardness of the Quantum Approximate Optimization Algorithm

The trading of fidelity for scale enables approximate classical simulators such as matrix product states (MPSs) to run quantum circuits beyond exact methods. A control parameter, the so-called bond dimension $\mathcal{χ}$ for MPSs, governs the allocated computational resources and the output fidelity. Here, we characterize the fidelity for the quantum approximate optimization algorithm by the expectation value of the cost function that it seeks to minimize and find that it follows a scaling law $\mathscr{F}$(ln $\mathcal{χ}$/N), where N is the number of qubits. With ln $\mathcal{χ}$ amounting to the entanglement that a MPS can encode, we show that the relevant variable for investigating the fidelity is the entanglement per qubit. Importantly, our results calibrate the classical computational power required to achieve the desired fidelity and benchmark the performance of quantum hardware in a realistic setup. For instance, we quantify the hardness of performing better classically than a noisy superconducting quantum processor by readily matching its output to the scaling function. Moreover, we relate the global fidelity to that of individual operations and establish its relationship with $\mathcal{χ}$ and N. We sharpen the requirements for noisy quantum computers to outperform classical techniques at running a quantum optimization algorithm in speed, size, and fidelity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Analytic and numerical bootstrap of CFTs with $O(m)\times O(n)$ global symmetry in 3D

Motivated by applications to critical phenomena and open theoretical questions, we study conformal field theories with O(m)\times O(n) O ( m ) × O ( n ) global symmetry in d=3 d = 3 spacetime dimensions. We use both analytic and numerical bootstrap techniques. Using the analytic bootstrap, we calculate anomalous dimensions and OPE coefficients as power series in \varepsilon=4-d ε = 4 − d and in 1/n 1 / n , with a method that generalizes to arbitrary global symmetry. Whenever comparison is possible, our results agree with earlier results obtained with diagrammatic methods in the literature. Using the numerical bootstrap, we obtain a wide variety of operator dimension bounds, and we find several islands (isolated allowed regions) in parameter space for O(2)\times O(n) O ( 2 ) × O ( n ) theories for various values of n n . Some of these islands can be attributed to fixed points predicted by perturbative methods like the \varepsilon ε and large- n n expansions, while others appear to arise due to fixed points that have been claimed to exist in resummations of perturbative beta functions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Electronic density response of warm dense matter

Matter at extreme temperatures and pressures—commonly known as warm dense matter (WDM)—is ubiquitous throughout our Universe and occurs in astrophysical objects such as giant planet interiors and brown dwarfs. Moreover, WDM is very important for technological applications such as inertial confinement fusion and is realized in the laboratory using different techniques. A particularly important property for the understanding of WDM is given by its electronic density response to an external perturbation. Such response properties are probed in x-ray Thomson scattering (XRTS) experiments and are central for the theoretical description of WDM. In this work, we give an overview of a number of recent developments in this field. To this end, we summarize the relevant theoretical background, covering the regime of linear response theory and nonlinear effects, the fully dynamic response and its static, time-independent limit, and the connection between density response properties and imaginary-time correlation functions (ITCF). In addition, we introduce the most important numerical simulation techniques, including path-integral Monte Carlo simulations and different thermal density functional theory (DFT) approaches. From a practical perspective, we present a variety of simulation results for different density response properties, covering the archetypal model of the uniform electron gas and realistic WDM systems such as hydrogen. Moreover, we show how the concept of ITCFs can be used to infer the temperature from XRTS measurements of arbitrary complex systems without the need for any models or approximations. Finally, we outline a strategy for future developments based on the close interplay between simulations and experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Tuning of strong nonlinearity in radio-frequency superconducting-quantum-interference-device meta-atoms

Strong nonlinearity of a self-resonant radio-frequency (rf) superconducting-quantum-interference-device (SQUID) meta-atom is explored via intermodulation (IM) measurements. Previous work in zero dc magnetic flux showed a sharp onset of IM response as the frequency sweeps through the resonance. A second onset at higher frequency was also observed, creating a prominent gap in the IM response. By extending those measurements to nonzero dc flux, different dynamics are revealed, including dc flux tunability of the aforementioned gaps and enhanced IM response near geometric resonance of the rf SQUID. These features observed experimentally are understood and analyzed theoretically through a combination of a steady-state analytical modeling and a full numerical treatment of the rf SQUID dynamics. The latter in addition predicts the presence of chaos in narrow parameter regimes. Here, the understanding of intermodulation in rf SQUID metamaterials is important for producing low-noise amplification of microwave signals and tunable filters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Critical points of the random cluster model with Newman–Ziff sampling

Here, we present a method for computing transition points of the random cluster model using a generalization of the Newman–Ziff algorithm, a celebrated technique in numerical percolation, to the random cluster model. The new method is straightforward to implement and works for real cluster weight q > 0. Furthermore, results for an arbitrary number of values of q can be found at once within a single simulation. Because the algorithm used to sweep through bond configurations is identical to that of Newman and Ziff, which was conceived for percolation, the method loses accuracy for large lattices when q > 1. However, by sampling the critical polynomial, accurate estimates of critical points in two dimensions can be found using relatively small lattice sizes, which we demonstrate here by computing critical points for non-integer values of q on the square lattice, to compare with the exact solution, and on the unsolved non-planar square matching lattice. The latter results would be much more difficult to obtain using other techniques.

97 MATHEMATICS AND COMPUTING↗

The Application of Differential Scanning Calorimetry to Investigate Precipitation Behavior in Nickel-Base Superalloys Under Continuous Cooling and Heating Conditions

In this study, a suite of experimental tools and fast-acting, numerical-simulation techniques was used to quantify the precipitation behavior of three nickel-base superalloys: IN-100, LSHR, and 718. Experimental methods comprised differential scanning calorimetry (DSC) to establish the specific heat as a function of temperature and selected direct-resistance heating trials (using a Gleeble ® machine) to obtain samples for microstructural analysis. For the DSC experiments, each alloy was cooled at a prescribed constant rate (between 5 and 20 K/min) after an initial soak/equilibration in the high-temperature, single-phase (supersolvus) temperature regime. On-heating DSC trials beginning at ambient temperature were also performed on alloy 718 in three different starting conditions: super- δ -solvus solution treated and water quenched (denoted as ST), solution treated and aged (STA), and solution treated and overaged (STOA). DSC results, revealing the thermal signatures associated with the kinetics of precipitation of γ ' (IN-100, LSHR) or γ ' and γ " (718), were interpreted using a previously-developed fast-acting routine that treats concurrent nucleation, growth, coarsening, and dissolution. For these simulations, special attention was paid to various thermo-kinetic input parameters including equilibrium solvus-approach curves, bulk free energies of transformation, matrix-precipitate interface energies, and effective diffusivities. For the γ - γ ' superalloys (IN-100 and LSHR), estimates of precipitate volume fraction as a function of temperature from the specific-heat data revealed semi-quantitative agreement with simulation predictions. For the γ - γ '- γ " superalloy (718), simulation predictions of precipitate volume fractions were converted to specific heat as a function of temperature and showed semi-quantitative agreement with the direct measurements.

36 MATERIALS SCIENCE↗

CFD modeling of turbulent air flow in self-heated gyroid TPMS structures: Thermal-hydraulic performance and validation

The application of mathematically derived geometries, such as triply periodic minimal surface (TPMS) lattices, has garnered significant interest across various fields, including the nuclear sector, due to their superior thermal-hydraulic characteristics for heat transfer compared to traditional plain or finned tubes. Here, this study validates a computational fluid dynamics (CFD) model, evaluates different turbulence models and CFD model settings, and performs uncertainty quantification to provide a comprehensive analysis. Despite extensive research on CFD modeling of TPMS lattices, such as gyroid and diamond geometries, there is a notable lack of publicly available literature providing comprehensive details on numerical analysis aspects, including convergence and methodological best practices. This study embarks on a benchmark analysis of a gyroid geometry to evaluate its thermal-hydraulic performance under turbulent flow conditions and scrutinize various CFD model configurations. The main contributions of this work include validating the CFD model, assessing and comparing different turbulence models, and enhancing pressure drop and temperature prediction capabilities. The results aim to support the development of methodologies needed to benchmark and enhance numerical analysis techniques for TPMS lattices. This work seeks to complement the existing body of knowledge, support the development of TPMS reactor concepts, and improve best practices for CFD modeling of TPMS lattices, ultimately advancing methodologies to support future applications in this domain.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Shock compression behavior of stainless steel 316L octet-truss lattice structures

Lattice structures offer desirable mechanical properties for applications of energy absorption and impact mitigation but limited research has been carried out on their shock compression behavior. In this work, the shock compression behavior of stainless steel 316L (SS316L) octet-truss lattice structures was investigated through experimental techniques and numerical simulations. Plate impact experiments with high-speed imaging were conducted at impact velocities of 270 – 390 m/s on lattice specimens with 5x5x10 unit cell geometries additively manufactured (AM) using direct metal laser sintering. High-speed imaging together with digital image correlation was used to extract full-field measurements and define a two-wave structure consisting of an elastic wave and planar compaction (shock) wave which propagated along the impact direction. A linear shock velocity versus particle velocity relation was found to approximate the measurements with a unit slope and a linear fit constant equal to the crushing speed. Furthermore, the shock velocity versus particle velocity relation, full-field measurements, and elastic limit together with the Eulerian form of the Rankine-Hugoniot jump conditions were used to find relations for the stress and internal energy behind the shock. Stress behind the shock increased with relative density and particle velocity, and specific internal energy converged to a single curve similar to that of bulk AM SS316L. Explicit finite element analysis using the Johnson-Cook constitutive model demonstrated similar shock behavior observed in experiments and a linear shock velocity versus particle velocity relation and corresponding Hugoniot calculations were found to be in agreement with experimental results. Numerical simulations confirmed negligible effects of exterior versus interior measurements and further validated the application of one-dimensional shock theory.

42 ENGINEERING↗

Direct Mapping of Polyclonal Epitopes in Serum by HDX-MS

Elucidating the interactions that drive antigen recognition is central to understanding antibody-mediated protection and is vital for the rational design of immunogens. Often, structural knowledge of epitopes targeted by antibodies is derived from isolated studies of monoclonal antibodies, for which numerous structural techniques exist. In contrast, there are very few approaches capable of mapping the full scope of antigen surfaces targeted by polyclonal sera through the course of a natural antibody response. Here, in this study, we develop an approach using immobilized antigen coupled to hydrogen/deuterium exchange with mass spectrometry (HDX-MS) to probe epitope targeting in the context of the fully native serum environment. Using the well-characterized Staphylococcal enterotoxin B (SEB) as a model system, we show that complex combinations of epitopes can be detected and subtle differences across different anti-sera can be discerned. This work reveals new insight into how neutralizing antibodies and antisera target SEB, and more importantly, establishes a novel method for directly mapping the epitope landscape of polyclonal sera.

antigens↗