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At least 55 records · Page 3

Robustness of the Stochastic Parameterization of Subgrid-Scale Wind Variability in Sea Surface Fluxes

Abstract High-resolution numerical models have been used to develop statistical models of the enhancement of sea surface fluxes resulting from spatial variability of sea surface wind. In particular, studies have shown that flux enhancement is not a deterministic function of the resolved state. Previous studies focused on single geographical areas or used a single high-resolution numerical model. This study extends the development of such statistical models by considering six different high-resolution models, four different geographical regions, and three different 10-day periods, allowing for a systematic investigation of the robustness of both the deterministic and stochastic parts of the data-driven parameterization. Results indicate that the deterministic part, based on regressing the unresolved normalized flux onto resolved-scale normalized flux and precipitation, is broadly robust across different models, regions, and time periods. The statistical features of the stochastic part of the model (spatial and temporal autocorrelation and parameters of a Gaussian process fit to the regression residual) are also found to be robust and not strongly sensitive to the underlying model, modeled geographical region, or time period studied. Best-fit Gaussian process parameters display robust spatial heterogeneity across models, indicating potential for improvements to the statistical model. These results illustrate the potential for the development of a generic, explicitly stochastic parameterization of sea surface flux enhancements dependent on wind variability.

Endo, Kota↗

Bayesian Spatial Models for Projecting Corn Yields

Climate change is predicted to impact corn yields. Previous studies analyzing these impacts differ in data and modeling approaches and, consequently, corn yield projections. We analyze the impacts of climate change on corn yields using two statistical models with different approaches for dealing with county-level effects. The first model, which is novel to modeling corn yields, uses a computationally efficient spatial basis function approach. We use a Bayesian framework to incorporate both parametric and climate model structural uncertainty. We find that the statistical models have similar predictive abilities, but the spatial basis function model is faster and hence potentially a useful tool for crop yield projections. We also explore how different gridded temperature datasets affect the statistical model fit and performance. Compared to the dataset with only weather station data, we find that the dataset composed of satellite and weather station data results in a model with a magnified relationship between temperature and corn yields. For all statistical models, we observe a relationship between temperature and corn yields that is broadly similar to previous studies. We use downscaled and bias-corrected CMIP5 climate model projections to obtain detrended corn yield projections for 2020–2049 and 2069–2098. In both periods, we project a decrease in the mean corn yield production, reinforcing the findings of other studies. However, the magnitude of the decrease and the associated uncertainties we obtain differ from previous studies.

54 ENVIRONMENTAL SCIENCES↗

Attribution of heterogeneous stress distributions in low-grain polycrystals under conditions leading to damage

In high-purity polycrystalline metallic materials, voids tend to favor grain boundaries as nucleation sites due to the elevated stress states produced by granular interactions and the weakened grain boundary from the relative atomic disorder. To quantify the key factors of this elevated stress state, simple compression of a small multi-grain cylinder of body-centered cubic tantalum was simulated using a single crystal plasticity model that incorporates non-Schmid effects. Four increasingly complex synthetic microstructures were created to tractably incorporate grain boundary interactions, and a statistically significant number of combinations were performed by varying the initial crystallographic orientations of the microstructure. Most of these simulations produce the maximum von Mises stress on a grain boundary and less frequently at the multi-grain junctions. To build a statistical model for the maximum von Mises stress at the grain boundary, physically based features that could contribute to the elevated stress state were selected. Then, a learning algorithm based on information theory was used to identify which of these features contributed the most information to the data set. The identified features include a grain’s propensity to accommodate both elastic and plastic deformations and their directional components. The misalignment of the direction of each grain’s mechanical response was found to be strongly correlated to the magnitude of the stress near the grain boundary. For all of the synthetic microstructures, the statistical models produce a residual distribution that is nearly Gaussian with a variance of, at most, 10% of the prior distribution. The successful performance of the statistical model implies the correct identification of the physical features that cause severe stress localization in polycrystalline materials. The statistical models constructed here can be used to formulate a physically motivated void nucleation model which is sensitive to a microstructure’s propensity to produce elevated stress states. As a result, these statistical models also enable the design of material microstructures, in which the crystallographic orientation is chosen to resist void nucleation.

36 MATERIALS SCIENCE↗

A Stochastic Reduced-Order Model for Statistical Microstructure Descriptors Evolution

Integrated computational materials engineering (ICME) models have been a crucial building block for modern materials development, relieving heavy reliance on experiments and significantly accelerating the materials design process. However, ICME models are also computationally expensive, particularly with respect to time integration for dynamics, which hinders the ability to study statistical ensembles and thermodynamic properties of large systems for long time scales. To alleviate the computational bottleneck, we propose to model the evolution of statistical microstructure descriptors as a continuous-time stochastic process using a non-linear Langevin equation, where the probability density function (PDF) of the statistical microstructure descriptors, which are also the quantities of interests (QoIs), is modeled by the Fokker–Planck equation. In this work, we discuss how to calibrate the drift and diffusion terms of the Fokker–Planck equation from the theoretical and computational perspectives. The calibrated Fokker–Planck equation can be used as a stochastic reduced-order model to simulate the microstructure evolution of statistical microstructure descriptors PDF. Considering statistical microstructure descriptors in the microstructure evolution as QoIs, we demonstrate our proposed methodology in three integrated computational materials engineering (ICME) models: kinetic Monte Carlo, phase field, and molecular dynamics simulations.

97 MATHEMATICS AND COMPUTING↗

Energy dependence of light hypernuclei production in heavy-ion collisions from a coalescence and statistical-thermal model perspective

A comparison of light hypernuclei production, from Ultra-relativistic Quantum Molecular Dynamics (UrQMD)+coalescence and the thermal model, in heavy ion collisions over a wide range of beam energies and system sizes is presented. We find that both approaches provide generally similar results, with differences in specific details. Especially the ratios of hypertriton to Λ are affected by both the source radius Δr of the coalescence procedure as well as canonical effects. On the other hand, the double ratio S 3 is almost independent of canonical effects, which is in contrast to coalescence. Thus, both the beam energy dependence and centrality dependence of S 3 can be used to constrain the hypertriton source radius. To do so the currently available data are not yet sufficient. Elliptic flow is shown to be unaffected by the source size of the nuclei and an almost perfect mass scaling of the elliptic flow is observed. Furthermore, our predictions further suggest that the existence of the H-dibaryon(ΛΛ) seems ruled out by ALICE data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Statistical generic design of glass and optimization: Selective review on oxide glasses

Designing a single glass composition for a multidimensional property space is challenging, and the difficulty increases with the number of design criteria. Traditionally, the task is accomplished using multiple statistical models that describe the relationships between composition (C) and property (P) values, i.e., C-P models. Recently, the structure (S)-property (P) statistical modeling has emerged as a complementary approach. The S-P modeling approach has also been shown to be a preferred method for modeling glass properties, particularly when a small data set is available, such as in single-component studies, or when strong nonlinearities exist between composition and properties. The combined model package, C-S-P, implements the concept of generic glass design, i.e., designing glass for performance by first selecting a specific or optimized set of glass network structural groups using S-P models and then transferring the designed structures (genes) to a particular composition using C-S models. This article reviews a set of supporting cases from the previous C-S-P modeling studies of phosphate, silicate, and borosilicate glasses, which are relevant for many critical commercial applications. The methodology for developing the statistical C-S-P database is presented, enabling the application of P?S?C to achieve a generic glass design and optimization, targeting multiple design criteria for both performance and processing properties simultaneously.

Network structure↗

Direct cross section measurement of 102 Pd ⁢(𝛾,𝑝) and 102 Pd ⁢(𝛾,𝛼) for the astrophysical 𝑝 process

Background: A handful of neutron-deficient stable nuclei, known as the “p nuclei,” cannot be produced through astrophysical neutron capture processes. Instead, some of these nuclei are proposed to be produced by 𝛾-induced reactions on existing r- and s-process seeds. The specific astrophysical site or sites are not yet identified, however, with uncertainties in the cross sections of these 𝛾-induced reactions playing a role. Databases of reaction rates for astrophysical simulations often rely on theoretical statistical model calculations, such as Hauser-Feshbach, for rates where no experimental information is known. However, reasonable variations in the choice of parametrizations of various nuclear properties can create order-of-magnitude variations in the final predicted cross sections and reaction rates, which are then propagated through the models to the predicted final abundances. Purpose: To better constrain these statistical model calculations and ultimately reduce the uncertainties from the nuclear physics on our understanding of the p nuclei, a measurement of the cross sections of 𝛾-induced reactions on the p-nucleus 102 Pd was undertaken. This work represents the first measurement of its kind, using segmented silicon detectors to measure prompt charged particle emission from 𝛾-induced reactions. Methods: Quasimonoenergetic gamma beams from the High Intensity 𝛾 Source facility bombarded an enriched 102 Pd target. A segmented silicon array was arranged to detect the particles emitted from (𝛾,𝑝) and (𝛾,𝛼) reactions. Results: Reaction cross sections were deduced at multiple 𝛾-beam energies between 10 and 19 MeV, and compared to statistical model calculations using talys-1.96. The 102 Pd ⁢(𝛾,𝑝)⁢ 101 Rh reaction cross section was reasonably well reproduced by a subset of photon strength functions and level densities, though the strength to the ground state of 101 Rh was underestimated at higher incident gamma energies. The 102 Pd ⁢(𝛾,𝛼)⁢ 98 Ru was in general overpredicted by the various alpha-nucleus optical model potentials. Conclusions: While the theoretical cross sections used to model the (𝛾,𝑝) reactions for the p process may be reasonable, a more careful approach is needed in the case of (𝛾,𝛼). Further work to probe gamma-induced reaction cross sections at and near the p nuclei is warranted.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Thermonuclear 28 P(p, γ ) 29 S reaction rate and astrophysical implication in ONe nova explosion

An accurate 28 P(p, γ) 29 S reaction rate is crucial to defining the nucleosynthesis products of explosive hydrogen burning in ONe novae. Using the recently released nuclear mass of 29 S, together with a shell model and a direct capture calculation, we reanalyzed the 28 P(p, γ) 29 S thermonuclear reaction rate and its astrophysical implication. We focus on improving the astrophysical rate for 28 P(p, γ) 29 S based on the newest nuclear mass data. Our goal is to explore the impact of the new rate and associated uncertainties on the nova nucleosynthesis. We evaluated this reaction rate via the sum of the isolated resonance contribution instead of the previously used Hauser-Feshbach statistical model. The corresponding rate uncertainty at different energies was derived using a Monte Carlo method. Nova nucleosynthesis is computed with the 1D hydrodynamic code SHIVA. The contribution from the capture on the first excited state at 105.64 keV in 28 P is taken into account for the first time. We find that the capture rate on the first excited state in 28 P is up to more than 12 times larger than the ground-state capture rate in the temperature region of 2.5 × 10 7 K to 4 × 10 8 K, resulting in the total 28 P(p, γ) 29 S reaction rate being enhanced by a factor of up to 1.4 at ~1 × 10 9 K. In addition, the rate uncertainty has been quantified for the first time. It is found that the new rate is smaller than the previous statistical model rates, but it still agrees with them within uncertainties for nova temperatures. The statistical model appears to be roughly valid for the rate estimation of this reaction in the nova nucleosynthesis scenario. Using the 1D hydrodynamic code SHIVA, we performed the nucleosynthesis calculations in a nova explosion to investigate the impact of the new rates of 28 P(p, γ) 29 S. Our calculations show that the nova abundance pattern is only marginally affected if we use our new rates with respect to the same simulations but statistical model rates. Finally, the isotopes whose abundance is most influenced by the present 28 P(p, γ) 29 S uncertainty are 28 Si, 33,34 S, 35,37 Cl, and 36 Ar, with relative abundance changes at the level of only 3% to 4%.

Astronomy & Astrophysics↗

Improved thermonuclear rate of 42 Ti( p , γ ) 43 V and its astrophysical implication in the rp process

Context. Accurate 42 Ti(p,γ) 43 V reaction rates are crucial for understanding the nucleosynthesis path of the rapid capture process (rp process) that occurs in X-ray bursts. Aims. We aim to improve the thermonuclear rates of 42 Ti(p,γ) 43 V based on more complete resonance information and a more accurate direct component, together with the recently released nuclear masses data. We also explore the impact of the newly obtained rates on the rp process. Methods. We reevaluated the reaction rate of 42 Ti(p,γ) 43 V by the sum of the isolated resonance contribution instead of the Hauser-Feshbach statistical model. We used a Monte Carlo method to derive the associated uncertainties of new rates. The nucleosynthesis simulations were performed via the NuGrid post-processing code ppn. Results. The new rates differ from previous estimations due to the use of a series of updated resonance parameters and a direct S factor. Compared with the previous results from the Hauser-Feshbach statistical model, which assumes compound nucleus 43 V with a sufficiently high-level density in the energy region of astrophysical interest, large differences exist over the entire temperature region of rp-process interest, up to two orders of magnitude. We consistently calculated the photodisintegration rate using our new nuclear masses via the detailed balance principle, and found the discrepancies among the different reverse rates are much larger than those for the forward rate, up to ten orders of magnitude at the temperature of 10 8 K. Using a trajectory with a peak temperature of 1.95×10 9 K, we performed the rp-process nucleosynthesis simulations to investigate the impact of the new rates. Our calculations show that the adoption of the new forward and reverse rates result in abundance variations for Sc and Ca of 128% and 49%, respectively, compared to the variations for the statistical model rates. On the other hand, the overall abundance pattern is not significantly affected. The results of using new rates also confirm that the rp-process path does not bypass the isotope 43 V. Conclusions. Our study found that the Hauser-Feshbach statistical model is inappropriate to the reaction rate evaluation for 42 Ti(p,γ) 43 V. The adoption of the new rates confirms that the reaction path of 42 Ti(p,γ) 43 V(p,γ) 44 Cr(β + ) 44 V is a key branch of the rp process in X-ray bursts.

79 ASTRONOMY AND ASTROPHYSICS↗

Cross-section measurement of the 82 Kr ($p,γ$) 83 Rb reaction in inverse kinematics

The total cross section of the 82 Kr(p,γ) 83 Rb reaction was measured for the first time at effective center-of-mass energies between 2.4 and 3.0 MeV, within the relevant Gamow window for the astrophysical γ process. The experiment took place at the National Superconducting Cyclotron Laboratory at Michigan State University using the ReA facility. A 82 Kr beam was directed onto a hydrogen gas cell located at the center of the Summing NaI(Tl) (SuN) detector. Here, the obtained spectra were analyzed using the γ-summing technique and the extracted cross section was compared to standard statistical model calculations using the non-smoker and talys codes. The comparison indicates that standard statistical model calculations tend to overproduce the cross section of the 82 Kr(p,γ) 83 Rb reaction relative to the experimentally measured values. Furthermore, the experimental data were used to provide additional constraints on the nuclear level density and the γ-ray strength function used in the statistical model calculations.

59 ≤ A ≤ 89↗

Extrapolation of the Rainflow-Counted Load Ranges for Fatigue Assessment of the Wind Turbine's Blades

Wind turbine design standards recommend the use of statistical modeling coupled with extrapolation of the short-term load data to long-term periods for fatigue reliability assessment. However, statistical error and computational expense can limit the accuracy of such approaches. In the case of wind turbine blades, the errors are more significant because of the high material fatigue exponent that makes the damage estimations more sensitive to variations. In addition, due to different excitation sources, the flapwise load range histogram is not unimodal, and thus its statistical modeling is complex. In the present work, we provide three methods for statistical modeling of the flapwise bending moment ranges including a novel approach based on frequency-based separation of the modes. The first two methods are simplified approaches for modeling the most crucial load ranges using unimodal distributions and the third method involves multimodal distribution fitting. The research is based on 3600 10-minute aeroelastic simulations of DTU 10MW case study wind turbine from which a benchmark damage equivalent load (DEL) is calculated. The DEL calculated by each of the three proposed methods is compared to this reference. The results show that the conventional approach based on using 6 seeds as well as using mixture models fitted on the limited data lead to under-conservative results with errors up to 23%. On the other hand, the simplified unimodal approaches provided in this work can provide conservative estimations of the fatigue damage with mean values 5% and 12% higher than the benchmark. However, the variability of the DEL estimates is higher when using unimodal extrapolation of the load ranges, and the data can be conservative by 17.5%. The proposed unimodal fits suggested for modeling and extrapolation of the blade's load ranges provide less errors relatively and most importantly conservative DEL estimations while maintaining computational efficiency.

blade fatigue↗

Statistical mechanical model for crack growth

Analytic relations that describe crack growth are vital for modeling experiments and building a theoretical understanding of fracture. Upon constructing an idealized model system for the crack and applying the principles of statistical thermodynamics, it is possible to formulate the rate of thermally activated crack growth as a function of load, but the result is analytically intractable. In this report an asymptotically correct theory is used to obtain analytic approximations of the crack growth rate from the fundamental theoretical formulation. These crack growth rate relations are compared to those that exist in the literature and are validated with respect to Monte Carlo calculations and experiments. The success of this approach is encouraging for future modeling endeavors that might consider more complicated fracture mechanisms, such as inhomogeneity or a reactive environment.

36 MATERIALS SCIENCE↗

coh3

CoH3 (CoH ver.3) is an optical model, exciton pre-equilibrium, and Hauser-Feshbach statistical model code, which calculates nuclear reaction cross sections for medium to heavy targets in the keV to MeV energy region. This program is written in standard C++, divided into approximately 200 source and header files. CoH solves the Schroedinger equation for optical potentials defined in the code, and calculates differential elastic scattering, reaction, and total cross sections, for neutron, proton, deuteron, triton, 3He, and alpha-particle. Deformed optical potentials are solved with the coupled-channels method, in which the ground state rotational band members, or vibrational phonon states are coupled. The optical model gives particle transmission coefficients that are fed into the statistical model calculations. CoH includes the pre-equilibrium model (exciton model), the direct/semidirect capture model, and the multi-stage Hauser-Feshbach statistical decay with width fluctuation correction based on the Gaussian orthogonal ensemble. For weakly coupled levels, the DWBA (distorted wave Born approximation) method is used to calculate the direct inelastic scattering process to the excited states.

Kawano, Toshihiko↗

β -delayed neutron emissions from N > 50 gallium isotopes

β-delayed γ-neutron spectroscopy has been performed on the decay of A = 84 to 87 gallium isotopes at the RI-beam Factory at the RIKEN Nishina Center using a high-efficiency array of 3 He neutron counters (BRIKEN). β-2n-γ events were measured in the decays of all of the four isotopes for the first time, which is direct evidence for populating the excited states of two-neutron daughter nuclei. Detailed decay schemes with the γ branching ratios were obtained for these isotopes, and the neutron emission probabilities (P xn ) were updated from the previous study. Hauser-Feshbach statistical model calculations were performed to understand the experimental branching ratios. We found that the P 1n and P 2n values are sensitive to the nuclear level densities of 1n daughter nuclei and showed that the statistical model reproduced the P 2n /P 1n ratio better when experimental levels plus shell-model level densities fit by the Gilbert-Cameron formula were used as the level-density input. We also showed the neutron and γ branching ratios are sensitive to the ground-state spin of the parent nucleus. Our statistical model analysis suggested J ≤ 3 for the unknown ground-state spin of the odd-odd nucleus 86 Ga, from the I γ (4 + → 2 + )/I γ (2 + → 0 + ) ratio of 84 Ga and the P 2n /P 1n ratio. In conclusion, these results show the necessity of detailed understanding of the decay scheme, including data from neutron spectroscopy, in addition to γ measurements of the multineutron emitters.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

First Direct Measurement Constraining the Ar 34 ( α , p ) K 37 Reaction Cross Section for Mixed Hydrogen and Helium Burning in Accreting Neutron Stars

The rate of the final step in the astrophysical αp process, the 34 Ar(α,p) 37 K reaction, suffers from large uncertainties due to a lack of experimental data, despite having a considerable impact on the observable light curves of x-ray bursts and the composition of the ashes of hydrogen and helium burning on accreting neutron stars. Here, we present the first direct measurement constraining the 34Ar(α,p)37K reaction cross section, using the Jet Experiments in Nuclear Structure and Astrophysics gas jet target. The combined cross section for the 34 Ar,Cl(α,p) 37 K,Ar reaction is found to agree well with Hauser-Feshbach predictions. The 34 Ar(α,2p) 36 Ar cross section, which can be exclusively attributed to the 34 Ar beam component, also agrees to within the typical uncertainties quoted for statistical models. This indicates the applicability of the statistical model for predicting astrophysical (α,p) reaction rates in this part of the αp process, in contrast to earlier findings from indirect reaction studies indicating orders-of-magnitude discrepancies. This removes a significant uncertainty in models of hydrogen and helium burning on accreting neutron stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Understanding the fusion yield dependencies in OMEGA DT-layered implosion experiments using a physics-based statistical mapping model

Improving the performance of inertial confinement fusion implosions requires physics models that can accurately predict the response to changes in the experimental inputs. Good predictive capability has been demonstrated for the fusion yield using a statistical mapping of simulated outcomes to experimental data [Gopalaswamy et al., Nature 565(771), 581–586 (2019)]. In this paper, a physics-based statistical mapping approach is used to extract and quantify all the major sources of degradation of fusion yield for direct-drive implosions on the OMEGA laser. Here, the yield is found to be dependent on the age of the deuterium tritium fill, the ℓ = 1 asymmetry in the implosion core, the laser beam-to-target size ratio, and parameters related to the hydrodynamic stability. A controlled set of experiments were carried out where only the target fill age was varied while keeping all other parameters constant. The measurements were found to be in excellent agreement with the fill age dependency inferred using the mapping model. In addition, a new implosion design was created, guided by the statistical mapping model by optimizing the trade-offs between increased laser energy coupling at larger target size and the degradations caused by the laser beam-to-target size ratio and hydrodynamic instabilities. When experimentally performed, an increased fusion yield was demonstrated in targets with larger diameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Differentiable Preisach Modeling for Characterization and Optimization of Particle Accelerator Systems with Hysteresis

Future improvements in particle accelerator performance are predicated on increasingly accurate online modeling of accelerators. Hysteresis effects in magnetic, mechanical, and material components of accelerators are often neglected in online accelerator models used to inform control algorithms, even though reproducibility errors from systems exhibiting hysteresis are not negligible in high precision accelerators. Here, we combine the classical Preisach model of hysteresis with machine learning techniques to efficiently create nonparametric, high-fidelity models of arbitrary systems exhibiting hysteresis. We experimentally demonstrate how these methods can be used in situ, where a hysteresis model of an accelerator magnet is combined with a Bayesian statistical model of the beam response, allowing characterization of magnetic hysteresis solely from beam-based measurements. Finally, we explore how using these joint hysteresis-Bayesian statistical models allows us to overcome optimization performance limitations that arise when hysteresis effects are ignored.

43 PARTICLE ACCELERATORS↗

Soil carbon storage capacity of drylands under altered fire regimes

The determinants of fire-driven changes in soil organic carbon (SOC) across broad environmental gradients remains unclear, especially in global drylands. Here we combined datasets and field sampling of fire-manipulation experiments to evaluate where and why fire changes SOC and compared our statistical model to simulations from ecosystem models. Drier ecosystems experienced larger relative changes in SOC than humid ecosystems—in some cases exceeding losses from plant biomass pools—primarily explained by high fire-driven declines in tree biomass inputs in dry ecosystems. Many ecosystem models underestimated the SOC changes in drier ecosystems. Upscaling our statistical model predicted that soils in savannah–grassland regions may have gained 0.64 PgC due to net-declines in burned area over the past approximately two decades. Consequently, ongoing declines in fire frequencies have probably created an extensive carbon sink in the soils of global drylands that may have been underestimated by ecosystem models.

54 ENVIRONMENTAL SCIENCES↗