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At least 217 records · Page 12

Theoretical estimate of the effect of thermal agitation on ribosome motion generated by stochastic microswimming

The effect of thermal agitation on ribosome motion is evaluated through the Péclet number, assuming that the ribosome is self-propelled along the mRNA during protein synthesis by a swimming stroke consisting of a cycle of stochastically-generated ribosome configurations involving its two subunits. The ribosome velocity probability distribution function is obtained, giving an approximately normal distribution. Its mean and variance together with an estimate of the in vivo free diffusion coefficient of the ribosome and using only configuration changes of small size, give a Péclet number similar to motor proteins and microorganisms. These results suggest the feasibility of the stochastic microswimming hypothesis to explain ribosome motion. - Highlights: • Hypothesis: the ribosome swims along the mRNA during protein synthesis. • How can withstand the thermal agitation of the particles in the surrounding fluid? • The Péclet number Pe is calculated estimating the in vivo diffusion coefficient. • With small size deformations the ribosome has speeds similar to motor proteins. • Similar Pe values for the ribosome and the motor proteins mean feasible hypothesis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

5 kHz thermometry in a swirl-stabilized gas turbine model combustor using chirped probe pulse femtosecond CARS. Part 2. Analysis of swirl flame dynamics

We have performed a detailed analysis of the temperature field in a turbulent swirl flame operating with a self-excited thermo-acoustic instability. The temperature field was measured using 5 kHz chirped-probe-pulse (CPP) femtosecond (fs) coherent anti-Stokes Raman scattering (CARS). The measurements are described in detail in the part 1 companion article. In this paper, part 2, a detailed analysis of the time-resolved temperature measurements and simultaneous pressure measurements is performed to provide insight into the dynamics and structure of the swirl-stabilized flame. Here this work is the first to capture the dynamics of the flame, flow, and coupled flow-flame processes using high-fidelity, spatially- and temporally-resolved thermometry in a flame of practical relevance. The time-averaged contour plot of the temperature field indicates that the flame is very flat and stabilizes approximately 10 mm downstream of the burner face. In this region, there are very significant temperature fluctuations indicating a very high level of unsteadiness. The temperature probability distribution functions (PDFs) are clearly bimodal in this region near the injector face. A Fourier analysis of the temperature time series revealed multiple coherent oscillatory modes. The strongest oscillation was found to be coherent and in-phase with an acoustic resonance at 314 Hz, as expected from the Rayleigh criteria for the unstable flame. An analysis of the phase-conditioned average temperature fields clearly shows an axial pumping of low-temperature reactants, which are consumed after a convective delay and result in a spike in the global heat-release rate. Continued analysis also revealed a 438 Hz oscillation that was found to correspond with the dynamics of convective transport by a helical precessing vortex core (PVC). The structure of the PVC, and its interaction with the flame, were studied based on the presence of this characteristic frequency in the power spectral densities computed throughout the flow. The precision and time-resolution of the CPP fsCARS measurements was also sufficient to enable computation of the integral time-scales as well as the PDFs of the temporal temperature gradients. A sample of state space trajectories were used to provide insight into the nature of coupling between the narrowband acoustic resonance and the broadband spectrum of turbulent flame processes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Direct numerical simulations of turbulent premixed cool flames: Global and local flame dynamics analysis

The cool flame dynamics, especially in turbulent flows, is of great interest for both practical application and fundamental research. Here, in this study, a series of direct numerical simulations of turbulent premixed n-C 7 H 16 /O 2 /O 3 /N 2 cool flames are performed, with the focus on the influence of turbulence intensity (u'/S L , where S L is the laminar flame speed) on the flame structure as well as the global and local cool flame dynamics. It is found that the cool flame front is considerably wrinkled by turbulence at high u'/S L , leading to significantly thickened turbulent cool flame brush and largely altered local reactivity compared with the reference laminar flame. However, the turbulent flame structure in the temperature space is found to be insensitive to u'/S L . Besides, with increasing u'/S L , the normalized turbulent cool flame speed (S L /S L ) is monotonically increased, attributed to substantial augmentation on the flame surface area (A T /A L ), while the stretching factor (I 0 ) remains almost constant and is smaller than 1. The underlying mechanisms for such variations are revealed through local flame dynamics analysis. Specifically, the local flame displacement speed S d is found to be strongly negatively correlated with flame curvature; meanwhile, such negative correlation and the probability distribution function (PDF) of flame curvature are barely influenced by u'/S L , leading to a weak dependence of I 0 on u'/S L . In contrast, the PDF of the tangential strain rate is found to span a much wider range and shift to the positive side as u'/S L increases, suggesting that the enhanced tangential strain rate is the main cause for the increase in surface area of the turbulent premixed cool flame. Finally, the influence of equivalence ratio on above findings is found to be insignificant, indicating that although the local reactivity of turbulent premixed cool flames is altered due to the differential diffusion, the resultant flame- stretch interaction is insensitive to the equivalence ratio. This study presents some unique cool flame dynamics that are distinct from hot flames, which can help improve the understanding and modeling of turbulent cool flames.

Cool flames↗

Computing the QRPA level density with the finite amplitude method

Here, we describe a new algorithm to calculate the vibrational nuclear level density of an atomic nucleus. Fictitious perturbation operators that probe the response of the system are generated by drawing their matrix elements from some probability distribution function. We use the Finite Amplitude Method to explicitly compute the response for each such sample. With the help of the Kernel Polynomial Method, we build an estimator of the vibrational level density and provide the upper bound of the relative error in the limit of infinitely many random samples. The new algorithm can give accurate estimates of the vibrational level density. Since it is based on drawing multiple samples of perturbation operators, its computational implementation is naturally parallel and scales like the number of available processing units.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Model-based Dynamic Control of Speculative Forays in Parallel Computation

In simulations running in parallel, the processors would have to synchronize with other processors to maintain correct global order of computations. This can be done either by blocking computation until correct order is guaranteed, or by \textit{speculatively} proceeding with the best guess (based on local information) and later correcting errors if/as necessary. Since the gainful lengths of speculative forays depend on the dynamics of the application software and hardware at runtime, an online control system is necessary to dynamically choose and/or switch between the blocking and speculative strategies. In this paper, we formulate the reversible speculative computing in large-scale parallel computing as a dynamic linear feedback control (optimization) system model and evaluate its performance in terms of time and cost savings as compared to the traditional (forward) computing. We illustrate with an exact analogy in the form of vehicular travel under dynamic, delayed route information. The objective is to assist in making the optimal decision on what computational approach is to be chosen, by predicting the amount of time and cost savings (or losing) under different environments represented by different parameters and probability distribution functions. We consider the cases of Gaussian, exponential and log-normal distribution functions. The control system is intended for incorporating into speculative parallel applications such as optimistic parallel discrete event simulations to decide at runtime when and to what extent speculative execution can be performed gainfully.

Perumalla, Kalyan↗

Hydrodynamic and magnetohydrodynamic simulations of wire turbulence

In this paper, we report on simulations of laboratory experiments in which magnetized supersonic flows are driven through a wire mesh. The goal of the study was to investigate the ability of such a configuration to generate supersonic, MHD turbulence. We first report on the morphological structures that develop in both magnetized and non-magnetized cases. We then analyze the flow using a variety of statistical measures, including power spectra and probability distribution functions of the density. Using these results we estimate the sonic mach number in the flows downstream of the wire mesh. Finally, we find the initially hypersonic (M s = 20) planar shock through the wire mesh does lead to downstream turbulent conditions. However, in both magnetized and non-magnetized cases, the resultant turbulence was marginally supersonic to transonic (M s ~1), and highly anisotropic in structure.

(Magnetohydrodynamics) MHD↗

Results from single-shock Marble experiments studying thermonuclear burn in the presence of heterogeneous mix on the National Ignition Facility

The Marble campaign on the National Ignition Facility investigates the effect of heterogeneous mix on thermonuclear burn for comparison to a probability distribution function (PDF) burn model. Marble utilizes plastic capsules filled with deuterated plastic foam and a fill gas containing tritium. As the capsules implode, the deuterium in the foam mixes with the tritium gas, and DT neutrons are produced as the shocks compress and heat the mixture. The yield of DT neutrons is dependent on the uniformity of the mix, with more heterogeneous mix producing fewer neutrons. In Marble, the heterogeneity of the mix is controlled by varying the diameter of voids introduced into the foam. The first NIF Marble campaign has been executed in which the Marble capsules were indirectly driven with a single strong shock using NIF hohlraums. The experiments produce a low-convergence, high-ion-temperature implosion. The ratio of DT to DD neutron yield is largely consistent with uniform atomic mix for fine-pore foam, and increases slightly with void diameter, contrary to 1D simulations using the PDF burn model. Recent 3D high-resolution simulations of similar experiments performed on the Omega Laser Facility suggest an explanation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A probabilistic creep model incorporating test condition, initial damage, and material property uncertainty

Uncertainty is prevalent in the creep resistance of alloys, where at elevated temperature and low pressure, rupture can range across logarithmic decades. In this study, a probabilistic continuum-damage-mechanics (CDM)-based model is derived to capture the uncertainty of creep resistance. To meet this objective, creep data for alloy 304 Stainless Steel is gathered. A constitutive model, “Sinh”, is calibrated deterministically to determine the statistical variability of the material properties. Three sources of uncertainty are injected into the model: test condition (stress and temperature), initial damage, and material properties. Probabilistic simulations are carried out by (a) calibrating probability distribution functions (pdfs) for each source of uncertainty (b) randomly sampling the pdfs using Monte Carlo methods and (c) executing simulations to replicate the uncertain creep behavior. A sensitivity analysis is performed to evaluate the relative effect of each source of uncertainty. In full probabilistic simulations, the cumulative uncertainty of creep behavior is evaluated. The probabilistic model accurately predicts the creep deformation and rupture of the available experiments. The probabilistic model is validated for interpolation but lacks extrapolation ability. Several future works are proposed to further improve the model.

36 MATERIALS SCIENCE↗

Quantitative Ultrasonic Nakagami Imaging of Neck Fibrosis After Head and Neck Radiation Therapy

Purpose: To investigate the feasibility of ultrasound Nakagami imaging to quantitatively assess radiation-induced neck fibrosis, a common sequela of radiation therapy (RT) to the head and neck. Methods and Materials: In a pilot study, 40 study participants were enrolled and classified into 3 subgroups: (1) a control group of 12 healthy volunteers; (2) an asymptomatic group of 11 patients who had received intensity modulated RT for head and neck cancer and had experienced no neck fibrosis; and (3) a symptomatic group of 17 post-RT patients with neck fibrosis. Each study participant underwent 1 ultrasound study in which scans were performed in the longitudinal orientation of the bilateral neck. Three Nakagami parameters were calculated to quantify radiation-induced tissue injury: Nakagami probability distribution function, shape, and scaling parameters. Physician-based assessments of the neck fibrosis were performed according to the Radiation Therapy Oncology Group late morbidity scoring scheme, and patient-based fibrosis assessments were rated based on symptoms such as pain and stiffness. Results: Major discrepancies existed between physician-based and patient-based assessments of radiation-induced fibrosis. Significant differences in all Nakagami parameters were observed between the control group and 2 post-RT groups. Moreover, significant differences in Nakagami shape and scaling parameters were observed among asymptomatic and symptomatic groups. Compared with the control group, the average Nakagami shape parameter value increased by 32.1% (P<.001), and the average Nakagami scaling parameter increased by 55.7% (P<.001) for the asymptomatic group, whereas the Nakagami shape parameter increased by 74.1% (P<.001) and the Nakagami scaling parameter increased by 83.5% (P<.001) for the symptomatic group. Conclusions: Ultrasonic Nakagami imaging is a potential quantitative tool to characterize radiation-induced asymptomatic and symptomatic neck fibrosis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

A full-angle Monte-Carlo scattering technique including cumulative and single-event Rutherford scattering in plasmas [Theory of cumulative large-angle collisions in plasmas]

Here, we describe and justify a full-angle scattering (FAS) method to faithfully reproduce the accumulated differential angular Rutherford scattering probability distribution function (pdf) of particles in a plasma. The FAS method splits the scattering events into two regions. At small angles it is described by cumulative scattering events resulting, via the central limit theorem, in a Gaussian-like pdf; at larger angles it is described by single-event scatters and retains a pdf that follows the form of the Rutherford differential cross-section. The FAS method is verified using discrete Monte-Carlo scattering simulations run at small timesteps to include each individual scattering event. We identify the FAS regime of interest as where the ratio of temporal/spatial scale-of-interest to slowing-down time/length is from 10 -3 to 0.3–0.7; the upper limit corresponds to Coulomb logarithm of 20–2, respectively. Two test problems, high-velocity interpenetrating plasma flows and keV-temperature ion equilibration, are used to highlight systems where including FAS is important to capture relevant physics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A statistical analysis of the elastic distortion and dislocation density fields in deformed crystals

The statistical properties of the elastic distortion fields of dislocations in deforming crystals are investigated using the method of discrete dislocation dynamics to simulate dislocation structures and dislocation density evolution under tensile loading. Probability distribution functions (PDF) and pair correlation functions (PCF) of the simulated internal elastic strains and lattice rotations are generated for tensile strain levels up to 0.85%. The PDFs of simulated lattice rotation are compared with sub-micrometer resolution three-dimensional X-ray microscopy measurements of rotation magnitudes and deformation length scales in 1.0% and 2.3% compression strained Cu single crystals to explore the linkage between experiment and the theoretical analysis. The statistical properties of the deformation simulations are analyzed through determinations of the Nye and Kr ner dislocation density tensors. The significance of the magnitudes and the length scales of the elastic strain and the rotation parts of dislocation density tensors are demonstrated, and their relevance to understanding the fundamental aspects of deformation is discussed.

3D X-ray microscopy↗

Discrete Thermodynamics

Here, we consider the dependence of velocity probability distribution functions on the finite size of a thermodynamic system. We are motivated by applications to computational fluid dynamics, hence discrete thermodynamics. We then begin by describing a coarsening process that represents geometric renormalization. Then, based only on the requirements of conservation, we demonstrate that the pervasive assumption of local thermodynamic equilibrium is not form invariant. We develop a perturbative correction that restores form invariance to second-order in a small parameter associated with macroscopic gradients. Finally, we interpret the corrections in terms of unresolved kinetic energy and discuss the implications of our results both in theory and as applied to numerical simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Bayesian inference of in-medium baryon-baryon scattering cross sections from HADES proton flow data

Within a Bayesian statistical framework using a Gaussian Process emulator for an isospin-dependent Boltzmann-Uehling-Uhlenbeck (IBUU) transport model simulator of heavy-ion reactions at intermediate energies, we infer from the HADES proton flow data the posterior probability distribution functions of in-medium baryon-baryon scattering cross section modification factor X with respect to free-space and the corresponding incompressibility K of nuclear matter as well as their correlation function. In conclusion, the mean value of X is found to be $X$ = $1.32_ {+0.28} ^ {-0.40} $ at 68% confidence level assuming the nuclear incompressibility K will not exceed 400 MeV, providing circumstantial evidence for enhanced baryon-braryon scattering cross sections in hot and dense nuclear matter.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Controlling extrapolations of nuclear properties with feature selection

Predictions of nuclear properties far from measured data are inherently inaccurate because of uncertainties in our knowledge of nuclear forces and in our treatment of quantum many-body effects in strongly-interacting systems. While the model bias can be directly calculated when experimental data is available, only an estimate can be made in the absence of such measurements. Current approaches to compute the estimated bias quickly lose predictive power when their input variables are taken far from the training region, resulting in uncontrolled uncertainties in applications such as nucleosynthesis simulations. In this letter, we present a novel technique to identify the input variables of machine learning algorithms that can provide robust estimates of model bias. Our process is based on selecting input variables, or features, based on their probability distribution functions across the entire nuclear chart. We illustrate our approach on the problem of quantifying the model bias in nuclear binding energies calculated with Density Functional Theory (DFT). We prove that building model biases with only Z and N as features leads to highly unreliable extrapolations. Conversely, we show that proper feature selection can systematically improve theoretical predictions without increasing uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A data-driven method for modelling dissipation rates in stratified turbulence

We present a deep probabilistic convolutional neural network (PCNN) model for predicting local values of small-scale mixing properties in stratified turbulent flows, namely the dissipation rates of turbulent kinetic energy and density variance, $\varepsilon$ and $\chi$ . Inputs to the PCNN are vertical columns of velocity and density gradients, motivated by data typically available from microstructure profilers in the ocean. The architecture is designed to enable the model to capture several characteristic features of stratified turbulence, in particular the dependence of small-scale isotropy on the buoyancy Reynolds number $Re_b:=\varepsilon /(\nu N^2)$ , where $\nu$ is the kinematic viscosity and $N$ is the background buoyancy frequency, the correlation between suitably locally averaged density gradients and turbulence intensity and the importance of capturing the tails of the probability distribution functions of values of dissipation. Empirically modified versions of commonly used isotropic models for $\varepsilon$ and $\chi$ that depend only on vertical derivatives of density and velocity are proposed based on the asymptotic regimes $Re_b\ll 1$ and $Re_b\gg 1$ , and serve as an instructive benchmark for comparison with the data-driven approach. When trained and tested on a simulation of stratified decaying turbulence which accesses a range of turbulent regimes (associated with differing values of $Re_b$ ), the PCNN outperforms assumptions of isotropy significantly as $Re_b$ decreases, and additionally demonstrates improvements over the fitted empirical models. A differential sensitivity analysis of the PCNN facilitates a comparison with the theoretical models and provides a physical interpretation of the features enabling it to make improved predictions.

42 ENGINEERING↗

Single-Molecule Kinetics of Styrene Hydrogenation on Silica-Supported Vanadium: The Role of Disorder for Single-Atom Catalysts

We report a theoretical approach for the study of supported atom catalysis is developed based on recent advances in the study of single-molecule kinetics. This view is particularly useful in exhibiting the role of disorder in single-atom and single-site catalysts on amorphous supports. The distribution of passage times (or waiting times) through a complex catalytic network originating from a set of coupled active sites is described by a probability distribution function (PDF), f(t), that reflects the local environment of the reaction center. An efficient algorithm is developed based on the linear algebra of the Markov transition matrix that produces f(t) or its moments. The kinetics of the hydrogenation reaction of styrene on an organovanadium(III) catalyst supported on amorphous silica is studied. A kinetic model consisting of three intertwined catalytic cycles emanating from three chemically distinct active sites is proposed to describe the chemistry. Density functional theory (DFT) calculations are employed to determine the free energy barriers of the reactions, which are used to construct the rate coefficient matrix. The disorder induced by the amorphous support material is divided into a low-dimensional short-range component reflecting the covalent structures near the reaction center and a weaker long-range component modeling the bulk randomness. The results are computed and analyzed for a wide range of concentration values and disorder scenarios. The unusual structure in the f(t) PDF is found to occur for certain cases that reveal the contribution of multiple catalytic pathways acting in concert.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aircraft Observations of Turbulence in Cloudy and Cloud-Free Boundary Layers Over the Western North Atlantic Ocean From ACTIVATE and Implications for the Earth System Model Evaluation and Development

This study examines boundary layer turbulence derived from high temporal resolution meteorological measurements from 40 research flights over the western North Atlantic Ocean during the 2020 deployments of ACTIVATE. Frequency distributions of various turbulent quantities reveal stronger turbulence during the winter deployment than in summer and for cloud‐topped than in cloud‐free boundary layers during the summer deployment. Maximum turbulence kinetic energy (TKE) is most often within cloud from observations in winter and summer, whereas it is mostly below cloud in both seasons by a global model turbulence parameterization. Further, bivariate frequency distributions are consistent with the bivariate Gaussian probability distribution functions assumed for the closure of higher‐order turbulence/shallow convection parameterizations used by some global models. Turbulence simulated by the Community Atmosphere Model version 6 and the Energy Exascale Earth System Model Atmosphere Model version 2 using such parameterizations is not as strong as observed, with more TKE going into vertical wind perturbations rather than into zonal wind perturbations as observed, suggesting that the treatment of turbulence in Earth system models still needs to be further improved.

54 ENVIRONMENTAL SCIENCES↗

A New Hybrid Mass-Flux/High-Order Turbulence Closure for Ocean Vertical Mixing

While various parameterizations of vertical turbulent fluxes at different levels of complexity have been proposed, each has its own limitations. For example, simple first-order closure schemes such as the K-Profile Parameterization (KPP) lack energetic constraints; two-equation models $k-ε$ like directly solve an equation for the turbulent kinetic energy but do not account for non-diffusive fluxes, and high-order closures that include the high-order transport terms are computationally expensive. To address these, we extend the Assumed-Distribution Higher-Order Closure (ADC) framework originally proposed for the atmospheric boundary layer and apply it to the ocean surface boundary layer. By assuming a probability distribution function relationship between the vertical velocity and tracers, all second-order and higher-order moments are exactly constructed and turbulence closure is achieved in the ADC scheme. In addition, this ADC parameterization has full energetic constraints and includes non-diffusive fluxes without the computational cost of a full higher-order closure scheme. We have tested the ADC scheme against a combination of large eddy simulation (LES), KPP, and $k-ε$ for surface buoyancy-driven convective mixing and found that the ADC scheme is robust with different vertical resolutions and compares well to the LES results.

54 ENVIRONMENTAL SCIENCES↗