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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Life Cycle Cost Analysis of Prestressed Concrete Poles Subjected to Wind, Surges, and Waves

Prestressed concrete (PC) poles are becoming popular choices to support coastal power transmission systems. However, the existing literature does not offer a detailed analysis of the effectiveness of PC poles in terms of long-term vulnerabilities and the direct and indirect costs. This is due to (1) lack of fragility models for PC poles and (2) lack of probabilistic wind, storm surge, and wave models in coastal settings. In this study, we address these gaps through a series of Monte Carlo simulations to estimate fragility of PC poles as a function of age and hazard (wind, surges, and waves) intensity, and the development of a probabilistic hazard model based on 10,000 years of synthetic tropical cyclone data. The probabilistic hazard model is used in conjunction with high-resolution hydrodynamic models to generate realizations of coastal wind, storm surges, and waves for the Louisiana and Mississippi coasts. A comprehensive life cycle cost analysis for a service life of 70 years considering direct and indirect losses is conducted to compare the performance of a transmission line located in Pascagoula, Mississippi, when wood poles are replaced by PC poles. Results showed that aging has a minor effect on the reliability of PC poles, highlighting the advantages of replacing wood poles with PC poles, especially in coastal areas. In addition, PC poles are significantly more cost-effective compared with wood poles over their life cycle, leading to an estimated saving of $11.55 million (68.17% reduction). The results of this study provide key insight to inform decision-making processes to keep the coastal power grids resilient and cost-effective against future storm hazards.

natural disasters↗
DOE OSTI2022

Initial Investigation of Coupled Electron-Photon Transport with SCEPTRE and RAPTURE (Rev.1.1)

The SCEPTRE1 code models coupled photon and electron transport in material media using discrete ordinates methods. The code can use different solvers in 1D and 3D in parallel, promising users the ability to run problems that are significant both in physics and computational scale. One capability that is perhaps unique at this time in the NNSA complex is SCEPTRE’s coupled photon– electron transport physics in a discrete ordinates approach. For example, incident x–rays can generate a significant electron population, whose transport can be simulated within the same code. In this context, fully–coupled means that photons can produce electrons and electrons can produce photons; uncoupled or no–coupling means photons do not produce electrons. Partial–coupling, an intermediate option in which photons can produce electrons but electrons do not produce photons, is not considered in the present work. The MCNP code can treat this physics with a Monte Carlo approach. MCNP should be viewed as complementary to SCEPTRE in both computational method (Monte Carlo versus discrete ordinates) as well as data libraries. SCEPTRE and MCNP should provide important checks on each other, especially from complementary modeling frameworks of a S n (discrete ordinates) mesh based method versus Monte Carlo particle based method. In order to learn more about SCEPTRE, and how it might inform engineering work at the Laboratory, we used it to carry out a set of initial studies. This was a series of 1D simulations of photon beams hitting Aluminum slabs. Our studies mainly used SCEPTRE directly, and made little use of the closely associated RAPTURE code (more on this below). The goals of these studies were first, to familiarize ourselves with operating the code, and second, to begin to assess the importance of coupled electron–photon transport. To support these studies, we began to develop a set of scripts to initialize inputs, run tools, process outputs, and plot results. An initial version of these scripts has been committed to the Lightning workflow repository. This memo relates the results of those studies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Sensitivity of nEXO to 136 Xe charged-current interactions: Background-free searches for solar neutrinos and fermionic dark matter

We study the sensitivity of nEXO to solar neutrino charged-current interactions, 𝜈 𝑒 + 136 Xe → 136 Cs*+𝑒 − , as well as analogous interactions predicted by models of fermionic dark matter. Due to the recently observed low-lying isomeric states of 136 Cs, these interactions will create a time-delayed coincident signal observable in the scintillation channel. Here we develop a detailed Monte Carlo simulation of scintillation emission, propagation, and detection in the nEXO detector to model these signals under different assumptions about the timing resolution of the photosensor readout. We show this correlated signal can be used to achieve background discrimination on the order of 10 −9 , enabling nEXO to make background-free measurements of solar neutrinos above the reaction threshold of 0.668 MeV. We project that nEXO could measure the flux of neutrinos from the carbon-nitrogen-oxygen cycle with a statistical uncertainty of 25%, thus contributing a novel and competitive measurement toward addressing the solar metallicity problem. Additionally, nEXO could measure the mean energy of the 7 Be neutrinos with a precision of 𝜎 ≤ 1.5 keV and could determine the survival probability of 7 Be and pep solar 𝜈𝑒 with precision comparable to the state of the art. These quantities are sensitive to the Sun’s core temperature and to nonstandard neutrino interactions, respectively. Here, the strong background suppression would allow nEXO to search for charged-current interactions of fermionic dark matter in the mass range 𝑚 𝜒 = 0.668–7 MeV with a sensitivity up to three orders of magnitude better than current limits.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Pulse-level noisy quantum circuits with QuTiP

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

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

The Anatomy of an Unusual Edge-on Protoplanetary Disk. I. Dust Settling in a Cold Disk

As the earliest stage of planet formation, massive, optically thick, and gas-rich protoplanetary disks provide key insights into the physics of star and planet formation. When viewed edge-on, high-resolution images offer a unique opportunity to study both the radial and vertical structures of these disks and relate this to vertical settling, radial drift, grain growth, and changes in the midplane temperatures. In this work, we present multi-epoch Hubble Space Telescope and Keck scattered light images, and an Atacama Large Millimeter/submillimeter Array 1.3 mm continuum map for the remarkably flat edge-on protoplanetary disk SSTC2DJ163131.2–242627, a young solar-type star in ρ Ophiuchus. We model the 0.8 μm and 1.3 mm images in separate Markov Chain Monte Carlo (MCMC) runs to investigate the geometry and dust properties of the disk using the MCFOST radiative transfer code. In scattered light, we are sensitive to the smaller dust grains in the surface layers of the disk, while the submillimeter dust continuum observations probe larger grains closer to the disk midplane. An MCMC run combining both data sets using a covariance-based log-likelihood estimation was marginally successful, implying insufficient complexity in our disk model. The disk is well characterized by a flared disk model with an exponentially tapered outer edge viewed nearly edge-on, though some degree of dust settling is required to reproduce the vertically thin profile and lack of apparent flaring. A colder than expected disk midplane, evidence for dust settling, and residual radial substructures all point to a more complex radial density profile to be probed with future, higher-resolution observations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Complex paths around the sign problem

The Monte Carlo evaluation of path integrals is one of a few general purpose methods to approach strongly coupled systems. It is used in all branches of physics, from QCD and nuclear physics to the correlated electron systems. However, many systems of great importance (dense matter inside neutron stars, the repulsive Hubbard model away from half filling, and dynamical and nonequilibrium observables) are not amenable to the Monte Carlo method as it currently stands due to the so-called sign problem. Here, a new set of ideas recently developed to tackle the sign problem based on the complexification of field space and the Picard-Lefshetz theory accompanying it is reviewed. The mathematical ideas underpinning this approach, as well as the algorithms developed thus far, are described together with nontrivial examples where the method has already been proved successful. Directions of future work, including the burgeoning use of machine learning techniques, are delineated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Constrained Bayesian Optimization of Criticality Experiments [Slides]

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. We demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for criticality safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗
DOE OSTI2020

Constrained Bayesian optimization of criticality experiments

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. Furthermore, we demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for criticality safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗
DOE OSTI2020

Constrained Bayesian Optimization of Criticality Experiments at LLNL [Slides]

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. We demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for critical ity safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗
DOE OSTI2022

Layered CAD/CSG geometry for spatially complex radiation transport scenarios

Many spatially complex fission, fusion, and national security Monte Carlo (MC) radiation transport scenarios involve combining computer-aided design (CAD) models with constructive solid geometry (CSG) models. A layered geometry method has been implemented in the Shift MC code to address this need. With layered geometry, multiple CAD and/or CSG models can be clipped, translated, rotated, and placed in overlapping layers to form transport-ready geometries. Here, the utility of this method is demonstrated with two problems: (1) a fixed-source simulation with a layered geometry consisting of a LiDAR-generated CAD model of the Combined Arms Collective Training Facility urban environment overlaid with CSG models of a mock hotel and a detector apparatus, and (2) a k-eigenvalue calculation using a layered geometry model of the Transformational Challenge Reactor consisting of CAD fuel elements placed in a CSG core. Tallied particle flux distributions match expectations, but tracking robustness must be improved prior to general-purpose use.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

CHUWD-H v1.0: a comprehensive historical hourly weather database for U.S. urban energy system modeling

Reliable and continuous meteorological data are crucial for modeling the responses of energy systems and their components to weather and climate conditions, particularly in densely populated urban areas. However, existing long-term datasets often suffer from spatial and temporal gaps and inconsistencies, posing great challenges for detailed urban energy system modeling and cross-city comparison under realistic weather conditions. Here we introduce the Historical Comprehensive Hourly Urban Weather Database (CHUWD-H) v1.0, a 23-year (1998-2020) gap-free and quality-controlled hourly weather dataset covering 550 weather station locations across all urban areas in the contiguous United States. CHUWD-H v1.0 synthesizes hourly weather observations from stations with outputs from a physics-based solar radiation model and a reanalysis dataset through a multi-step gap filling approach. A 10-fold Monte Carlo cross-validation suggests that the accuracy of this gap filling approach surpasses that of conventional gap filling methods. Designed primarily for urban energy system modeling, CHUWD-H v1.0 should also support historical urban meteorological and climate studies, including the validation and evaluation of urban climate modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Unraveling small-scale defects in irradiated ThO 2 using kinetic Monte Carlo simulations

Point defects and their clusters generated through irradiation can have significant impact on the physical and mechanical properties of materials. However, direct experimental visualization of these small-scale defects using high-resolution scanning transmission electron microscopy remains a challenging task. In this study, using thorium dioxide (ThO 2 ) with the fluorite structure as a model system, we demonstrate the use of ab initio basin-hopping simulations in synergy with object kinetic Monte Carlo simulations as a powerful tool for identifying small defect complexes in irradiated materials. In addition to providing quantitative insights into defect evolution in ThO 2 under irradiation, our study reveals an unexpected role of bound anti-Schottky defect clusters in mediating defect transport. Remarkably, despite their poor thermal stability against dissociation at high temperatures, the transient formation of bound anti-Schottky defects under irradiation and their subsequent migration provide the dominant mechanism for the growth of large interstitial loops that have been experimentally observed in ThO 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2021

Slope-Aspect Induced Climate Differences Influence How Water Is Exchanged Between the Land and Atmosphere

Cross-slope climate differences in the midlatitudes are ecologically important, and impact vegetation-mediated water balance between the earth surface and the atmosphere. We made high-resolution in situ observations of air temperature, relative humidity, soil moisture, insolation, and sap velocity observations on 14 Pacific madrone trees (Arbutus menziesii) spanning adjacent north and south slopes at the University of California's Angelo Coast Range Reserve. To understand the cross-slope response of sap velocity, a proxy for transpiration, to microclimate, we modeled the sap velocity on each slope using a transpiration model driven by ambient environment and parameterized with a Markov Chain Monte Carlo parameter estimation process. The results show that trees on opposing slopes do not follow a shared pattern of physiological response to transpiration drivers. This means that the observed sap velocity differences are not due entirely to observed microclimate differences, but also due to population-level physiological differences, which indicates acclimation to inhabited microclimate. While our present data set and analytical tools do not identify mechanisms of acclimation, we speculate that differing proportions of sun-adapted and shade-adapted leaves, differences in stomatal regulation, and cross-slope root zone moisture differences could explain some of the observed and modeled differences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Orbital structure of the effective pairing interaction in the high-temperature superconducting cuprates

The nature of the effective interaction responsible for pairing in the high-temperature superconducting cuprates remains unsettled. This question has been studied extensively using the simplified single-band Hubbard model, which does not explicitly consider the orbital degrees of freedom of the relevant CuO 2 planes. Here, we use a dynamical cluster quantum Monte Carlo approximation to study the orbital structure of the pairing interaction in the three-band Hubbard model, which treats the orbital degrees of freedom explicitly. We find that the interaction predominately acts between neighboring copper orbitals, but with significant additional weight appearing on the surrounding bonding molecular oxygen orbitals. By explicitly comparing these results to those from the simpler single-band Hubbard model, our study provides strong support for the single-band framework for describing superconductivity in the cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Multimodal parameter spaces of a complex multi-channel neuron model

One of the most common types of models that helps us to understand neuron behavior is based on the Hodgkin–Huxley ion channel formulation (HH model). A major challenge with inferring parameters in HH models is non-uniqueness: many different sets of ion channel parameter values produce similar outputs for the same input stimulus. Such phenomena result in an objective function that exhibits multiple modes (i.e., multiple local minima). This non-uniqueness of local optimality poses challenges for parameter estimation with many algorithmic optimization techniques. HH models additionally have severe non-linearities resulting in further challenges for inferring parameters in an algorithmic fashion. To address these challenges with a tractable method in high-dimensional parameter spaces, we propose using a particular Markov chain Monte Carlo (MCMC) algorithm, which has the advantage of inferring parameters in a Bayesian framework. The Bayesian approach is designed to be suitable for multimodal solutions to inverse problems. We introduce and demonstrate the method using a three-channel HH model. We then focus on the inference of nine parameters in an eight-channel HH model, which we analyze in detail. We explore how the MCMC algorithm can uncover complex relationships between inferred parameters using five injected current levels. The MCMC method provides as a result a nine-dimensional posterior distribution, which we analyze visually with solution maps or landscapes of the possible parameter sets. The visualized solution maps show new complex structures of the multimodal posteriors, and they allow for selection of locally and globally optimal value sets, and they visually expose parameter sensitivities and regions of higher model robustness. We envision these solution maps as enabling experimentalists to improve the design of future experiments, increase scientific productivity and improve on model structure and ideation when the MCMC algorithm is applied to experimental data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Multiplicity-dependent jet modification from di-hadron correlations in pp collisions at $ \sqrt{s} $ = 13 TeV

Short-range correlations between charged particles are studied via two-particle angular correlations in pp collisions at $\sqrt{s}$ = 13 TeV. The correlation functions are measured as a function of the relative azimuthal angle ∆φ and the pseudorapidity separation ∆η for pairs of primary charged particles within the pseudorapidity interval |η| < 0.9 and the transverse-momentum range 1 < p T < 8 GeV/c. Near-side (|∆φ| < 1.3) peak widths are extracted from a generalised Gaussian fitted over the correlations in full pseudorapidity separation (|∆η| < 1.8), while the per-trigger associated near-side yields are extracted for the short-range correlations (|∆η| < 1.3). Both are evaluated as a function of charged-particle multiplicity obtained by two different event activity estimators. The width of the near-side peak decreases with increasing multiplicity, and this trend is reproduced qualitatively by the Monte Carlo event generators PYTHIA 8, AMPT, and EPOS. However, the models overestimate the width in the low transverse-momentum region (p T < 3 GeV/c). The per-trigger associated near-side yield increases with increasing multiplicity. Although this trend is also captured qualitatively by the considered event generators, the yield is mostly overestimated by the models in the considered kinematic range. The measurement of the shape and yield of the short-range correlation peak can help us understand the interplay between jet fragmentation and event activity, quantify the narrowing trend of the near-side peak as a function of transverse momentum and multiplicity selections in pp collisions, and search for final-state jet modification in small collision systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

TRANSLATE - a Monte Carlo simulation of electron transport in liquid argon

Here, the microphysics of electron and photon propagation in liquid argon is a key component of detector design and calibrations needed to construct and perform measurements within a wide range of particle physics experiments. As experiments grow in scale and complexity, and as the precision of their intended measurements increases, the development of tools to investigate important microphysics effects impacting such detectors becomes necessary. In this paper we present a new time-domain Monte Carlo simulation of electron transport in liquid argon. The simulation models the TRANSport in Liquid Argon of near-Thermal Electrons (TRANSLATE) with the aim of providing a multi-purpose software package for the study and optimization of detector environments, with a particular focus on ongoing and next generation liquid argon neutrino experiments utilizing the time projection chamber technology. TRANSLATE builds on previous work of Wojcik and Tachiya, amongst others, introducing additional processes, including ionization, thus modeling the full range of drift electron scattering interactions. The simulation is validated by benchmarking its performance with swarm parameters from data collected in experimental setups operating in gas and liquid.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

A Cartesian-diffusion Langevin method for hybrid kinetic-fluid Coulomb scattering in particle-in-cell plasma simulations

A novel, drag-diffusion Langevin method of hybrid, kinetic-fluid Coulomb scattering in plasmas is presented. Unlike previous methods, the frictional drag is always applied in the simulation frame of reference. The velocity-space diffusion is performed in the stationary-fluid frame of reference when anisotropic, and in the laboratory frame when isotropic. While the general method is mass-ratio independent, we focus on interactions of kinetic-ions and fluid-electrons to show first-order modifications to the electron velocity distribution function that are an important correction for the accurate calculation of electric resistivity. Inclusion of sub-cycling and a limit to the maximum collision frequency is shown to allow for arbitrarily large timesteps without numerical failure. Here the Langevin method is compared with a grid-based binary method and found to require a much less restrictive timestep in cases of ion–electron slowing and temperature equilibration; this finding differs from previous work and is dependent on the mass ratio.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗