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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Precipitation characteristic changes due to global warming in a high‐resolution (16 km) ECMWF simulation

Changes in precipitation amount, intensity and frequency in response to global warming are examined using global high‐resolution (16 km) climate model simulations based on the European Centre for Medium‐range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) conducted under Project Athena. Our study shows the increases of zonal‐mean total precipitation in all latitudes except the northern subtropics (15°–30°N) and southern subtropics‐to‐midlatitudes (30°–40°S). The probability distribution function (PDF) changes in different latitudes suggest a higher occurrence of light precipitation (LP; ≤1 mm/day) and heavy precipitation (HP; ≥30 mm/day) at the expense of moderate precipitation reduction (MP; 1–30 mm/day) from Tropics to midlatitudes, but an increase in all categories of precipitation in polar regions. On the other hand, the PDF change with global warming in different precipitation climatological zones presents another image. For all regions and seasons examined, there is an HP increase at the cost of MP, but LP varies. The reduced MP in richer precipitation zones resides in the PDF peak intensities, which linearly increase with the precipitation climatology zones. In particular in the Tropics (20°S to 20°N), the precipitation PDF has a flatter distribution (i.e. HP and LP increases with MP reduction) except for the Sahara Desert. In the primary precipitation zones in the subtropics (20°–40°) of both hemispheres, precipitation over land switches toward higher intensity (HP increases, but MP and LP decrease) in both winter and summer, while precipitation over ocean in both seasons shows a flattening trend in the intensity distribution. For the major precipitation zones of the mid‐to‐high latitude belt (40°–70°), PDF of precipitation tends to be flatter over ocean in summer, but switches toward higher intensities over land in both summer and winter, as well as over ocean in winter.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

The Impact of Nuclear Reaction Rate Uncertainties on the Evolution of Core-collapse Supernova Progenitors

We review properties of core-collapse supernova progenitors with respect to the composite uncertainties in the thermonuclear reaction rates by coupling the probability density functions of the reaction rates provided by the STARLIB reaction rate library with MESA stellar models. We evolve 1000 models of 15${M}_{\odot }$ from the pre-main sequence to core O-depletion at solar and subsolar metallicities for a total of 2000 Monte Carlo stellar models. For each stellar model, we independently and simultaneously sample 665 thermonuclear reaction rates and use them in a MESA in situ reaction network that follows 127 isotopes from 1 H to 64 Zn. With this framework we survey the core mass, burning lifetime, composition, and structural properties at five different evolutionary epochs. At each epoch we measure the probability distribution function of the variations of each property and calculate Spearman rank-order correlation coefficients for each sampled reaction rate to identify which reaction rate has the largest impact on the variations on each property. We find that uncertainties in the reaction rates of ${}^{14}{\rm{N}}{({\rm{p}},\gamma )}^{15}{\rm{O}}$, triple-α, ${}^{12}{\rm{C}}{(\alpha ,\gamma )}^{16}{\rm{O}}$, 12 C( 12 C,p) 23 Na, 12 C( 16 O, p) 27 Al, 16 O( 16 O,n) 31 S, 16 O( 16 O, p) 31 P, and 16 O( 16 O,α) 28 Si dominate the variations of the properties surveyed. We find that variations induced by uncertainties in nuclear reaction rates grow with each passing phase of evolution, and at core H-, He-depletion they are of comparable magnitude to the variations induced by choices of mass resolution and network resolution. Yet, at core C-, Ne-, and O-depletion, the reaction rate uncertainties can dominate the variation, causing uncertainty in various properties of the stellar model in the evolution toward iron core-collapse.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Response Surface Modeling Tool Suite, Version 1.x

The Response Surface Modeling (RSM) Tool Suite is a collection of three codes used to generate an empirical interpolation function for a collection of drag coefficient calculations computed with Test Particle Monte Carlo (TPMC) simulations. The first code, "Automated RSM", automates the generation of a drag coefficient RSM for a particular object to a single command. "Automated RSM" first creates a Latin Hypercube Sample (LHS) of 1,000 ensemble members to explore the global parameter space. For each ensemble member, a TPMC simulation is performed and the object drag coefficient is computed. In the next step of the "Automated RSM" code, a Gaussian process is used to fit the TPMC simulations. In the final step, Markov Chain Monte Carlo (MCMC) is used to evaluate the non-analytic probability distribution function from the Gaussian process. The second code, "RSM Area", creates a look-up table for the projected area of the object based on input limits on the minimum and maximum allowed pitch and yaw angles and pitch and yaw angle intervals. The projected area from the look-up table is used to compute the ballistic coefficient of the object based on its pitch and yaw angle. An accurate ballistic coefficient is crucial in accurately computing the drag on an object. The third code, "RSM Cd", uses the RSM generated by the "Automated RSM" code and the projected area look-up table generated by the "RSM Area" code to accurately compute the drag coefficient and ballistic coefficient of the object. The user can modify the object velocity, object surface temperature, the translational temperature of the gas, the species concentrations of the gas, and the pitch and yaw angles of the object. Together, these codes allow for the accurate derivation of an object's drag coefficient and ballistic coefficient under any conditions with only knowledge of the object's geometry and mass.

Walker, Andrew↗
DOE OSTI2016

Response Surface Modeling Tool Suite, Version 1.x

The Response Surface Modeling (RSM) Tool Suite is a collection of three codes used to generate an empirical interpolation function for a collection of drag coefficient calculations computed with Test Particle Monte Carlo (TPMC) simulations. The first code, "Automated RSM", automates the generation of a drag coefficient RSM for a particular object to a single command. "Automated RSM" first creates a Latin Hypercube Sample (LHS) of 1,000 ensemble members to explore the global parameter space. For each ensemble member, a TPMC simulation is performed and the object drag coefficient is computed. In the next step of the "Automated RSM" code, a Gaussian process is used to fit the TPMC simulations. In the final step, Markov Chain Monte Carlo (MCMC) is used to evaluate the non-analytic probability distribution function from the Gaussian process. The second code, "RSM Area", creates a look-up table for the projected area of the object based on input limits on the minimum and maximum allowed pitch and yaw angles and pitch and yaw angle intervals. The projected area from the look-up table is used to compute the ballistic coefficient of the object based on its pitch and yaw angle. An accurate ballistic coefficient is crucial in accurately computing the drag on an object. The third code, "RSM Cd", uses the RSM generated by the "Automated RSM" code and the projected area look-up table generated by the "RSM Area" code to accurately compute the drag coefficient and ballistic coefficient of the object. The user can modify the object velocity, object surface temperature, the translational temperature of the gas, the species concentrations of the gas, and the pitch and yaw angles of the object. Together, these codes allow for the accurate derivation of an object's drag coefficient and ballistic coefficient under any conditions with only knowledge of the object's geometry and mass.

Walker, Andrew↗
DOE OSTI2016

Environmental dependence of the galaxy stellar mass function in the Dark Energy Survey Science Verification Data

Measurements of the galaxy stellar mass function are crucial to understand the formation of galaxies in the Universe. In a hierarchical clustering paradigm it is plausible that there is a connection between the properties of galaxies and their environments. Evidence for environmental trends has been established in the local Universe. The Dark Energy Survey (DES) provides large photometric datasets that enable further investigation of the assembly of mass. In this study we use ~3.2 million galaxies from the (South Pole Telescope) SPT-East field in the DES science verification (SV) dataset. From grizY photometry we derive galaxy stellar masses and absolute magnitudes, and determine the errors on these properties using Monte-Carlo simulations using the full photometric redshift probability distributions. We compute galaxy environments using a fixed conical aperture for a range of scales. We construct galaxy environment probability distribution functions and investigate the dependence of the environment errors on the aperture parameters. We compute the environment components of the galaxy stellar mass function for the redshift range 0.15 < z < 1.05. For z < 0.75 we find that the fraction of massive galaxies is larger in high density environment than in low density environments. We show that the low density and high density components converge with increasing redshift up to z ~ 1.0 where the shapes of the mass function components are indistinguishable. As a result, our study shows how high density structures build up around massive galaxies through cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The Information Length Concept Applied to Plasma Turbulence

A methodology to study statistical properties of anomalous transport in fusion plasma is investigated. Three time traces generated by the full-f gyrokinetic code GKNET are analyzed for this purpose. The time traces consist of heat flux as a function of the radial position, which is studied in a novel manner using statistical methods. The simulation data exhibit transport processes with both medium and long correlation length along the radius. A typical example of a phenomenon with long correlation length is avalanches. In order to investigate the evolution of the turbulent state, two basic configurations are studied, one flux-driven and one gradient-driven with decaying turbulence. The information length concept in tandem with Boltzmann–Gibbs and Tsallis entropy is used in the investigation. It is found that the dynamical states in both flux-driven and gradient-driven cases are surprisingly similar, but the Tsallis entropy reveals differences between them. This indicates that the types of probability distribution function are nevertheless quite different since the higher moments are significantly different.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2010

PROJECTED CENTRAL DARK MATTER FRACTIONS AND DENSITIES IN MASSIVE EARLY-TYPE GALAXIES FROM THE SLOAN DIGITAL SKY SURVEY

We investigate in massive early-type galaxies the variation of their two-dimensional central fraction of dark over total mass and dark matter density as a function of stellar mass, central stellar velocity dispersion, effective radius, and central surface stellar mass density. We use a sample of approximately 1.7 x 10{sup 5} galaxies from the Sloan Digital Sky Survey Data Release Seven (SDSS DR7) at redshift smaller than 0.33. We apply conservative photometric and spectroscopic cuts on the SDSS DR7 and the MPA/JHU value-added galaxy catalogs, to select galaxies with physical properties similar to those of the lenses studied in the Sloan Lens ACS Survey. The values of the galaxy stellar and total mass projected inside a cylinder of radius equal to the effective radius are obtained, respectively, by fitting the SDSS multicolor photometry with stellar population synthesis models, under the assumption of a Chabrier stellar initial mass function (IMF), and adopting a one-component isothermal total mass model with effective velocity dispersion approximated by the central stellar velocity dispersion. The plausibility of an isothermal model to represent the galaxy total mass distribution is supported by independent gravitational lensing and stellar-dynamical analyses performed in the lens subsample, which is found here to represent nicely the entire galaxy sample. We find that within the effective radius the stellar mass estimates differ from the total ones by only a relatively constant proportionality factor. In detail, we observe that the values of the projected fraction of dark over total mass and the logarithmic values of the central surface dark matter density (measured in M{sub sun} kpc{sup -2}) have almost Gaussian probability distribution functions, with median values of 0.64{sup +0.08}{sub -0.11} and 9.1{sup +0.2}{sub -0.2}, respectively. We discuss the observed correlations between these quantities and other galaxy global parameters and show that our results disfavor an interpretation of the tilt of the fundamental plane in terms of differences in the galaxy dark matter content and give useful information on the possible variations of the galaxy stellar IMF and dark matter density profile. Finally, we provide some observational evidence on the likely significant contribution of dry minor mergers, feedback from active galactic nuclei, and/or coalescence of binary black holes on the formation and evolution of massive early-type galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

HIGH STAR FORMATION RATES IN TURBULENT ATOMIC-DOMINATED GAS IN THE INTERACTING GALAXIES IC 2163 AND NGC 2207

CO observations of the interacting galaxies IC 2163 and NGC 2207 are combined with HI, H α , and 24 μ m observations to study the star formation rate (SFR) surface density as a function of the gas surface density. More than half of the high-SFR regions are HI dominated. When compared to other galaxies, these HI-dominated regions have excess SFRs relative to their molecular gas surface densities but normal SFRs relative to their total gas surface densities. The HI-dominated regions are mostly located in the outer part of NGC 2207 where the HI velocity dispersion is high, 40–50 km s{sup −1}. We suggest that the star-forming clouds in these regions have envelopes at lower densities than normal, making them predominantly atomic, and cores at higher densities than normal because of the high turbulent Mach numbers. This is consistent with theoretical predictions of a flattening in the density probability distribution function for compressive, high Mach number turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Empirical radius formulas for canonical neutron stars from bidirectionally selecting features of equations of state in extended Bayesian analyses of observational data

Significant advancement in Bayesian inference of nuclear equation of state (EOS) from gravitational wave and x-ray observations of neutron stars (NSs) has been made by the nuclear astrophysics community especially since GW170817. By extending the traditional Bayesian analysis which normally ends at presenting the marginalized posterior probability distribution functions (PDFs) of individual EOS parameters and their correlations (or sometimes only the Pearson correlation coefficients which are only reliably useful when the variables are linearly correlated while they are actually often not), we search for a data-driven and robust empirical formula for the radius 𝑅 1.4 of canonical NSs in terms of the characteristic EOS parameters (features). We also identify the single most important but currently poorly known EOS parameter for determining the 𝑅 1.4 . Using three regression-model-building methodologies: bidirectional stepwise feature selection, least absolute shrinkage selection operator (LASSO) regression, and neural network regression on a large set of posterior EOSs and the corresponding 𝑅 1.4 values inferred from earlier comprehensive Bayesian analyses of NS observational data, we systematically and rigorously develop the most probable 𝑅 1.4 formulas with varying statistical accuracy and technical complexity. Here, the most important EOS parameters for determining 𝑅 1.4 are found consistently in each of the feature selection processes to be (in order of decreasing importance): curvature 𝐾 sym , slope 𝐿, skewness 𝐽 sym of nuclear symmetry energy, skewness 𝐽 0 , incompressibility 𝐾 0 of symmetric nuclear matter, and the magnitude 𝐸 sym ⁡(𝜌 0 ) of symmetry energy at the saturation density 𝜌 0 of nuclear matter.

Bayesian methods↗
DOE OSTI2020

Elucidating plasma dynamics in Hasegawa–Wakatani turbulence by information geometry

In this work, the impact of adiabatic electrons on drift-wave turbulence, modeled by the Hasegawa–Wakatani equations, is studied using information length. Information length is a novel theoretical method for measuring distances between statistical states represented by different probability distribution functions (PDFs) along the path of a system and represents the total number of statistically different states that a system evolves through in time. Specifically, the time-dependent PDFs of turbulent fluctuations for a given adiabatic index $A$ are computed. The changes in fluctuation statistics are then quantified in time by using information length. The numerical results provide time traces exhibiting intermittent plasma dynamics, and such behavior is identified by a rapid change in the information length. The effects of $A$ are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Disentangling the physics of the attractive Hubbard model as a fully interacting model of fermions via the accessible and symmetry-resolved entanglement entropies

The complicated ways in which electrons interact in many-body systems such as molecules and materials have long been viewed through the lens of local electron correlation and associated correlation functions. However, quantum information science has demonstrated that more global diagnostics of quantum states like the entanglement entropy can provide a complementary and clarifying lens on electronic behavior. One particularly useful measure that can be used to distinguish between quantum and classical sources of entanglement is the accessible entanglement, the entanglement available as a quantum resource for systems subject to conservation laws, such as fixed particle number, due to superselection rules. In this work, we introduce an algorithm and demonstrate how to compute accessible and symmetry-resolved entanglements for interacting fermion systems. This is accomplished by combining an incremental version of the swap algorithm with a recursive auxiliary field quantum Monte Carlo algorithm recently developed by the authors. We apply these tools to study the pairing and charge density waves exhibited in the paradigmatic attractive Hubbard model via entanglement. We find that the particle and spin symmetry-resolved entanglements and their related full probability distribution functions show very clear—and unique—signatures of the underlying electronic behavior even when those features are less pronounced in conventional correlation functions. Altogether, this work provides a systematic means of characterizing the entanglement within quantum systems that can grant a deeper understanding of the complicated electronic behavior that underlies quantum phase transitions and crossovers in many-body systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Bayesian inverse modeling of the atmospheric transport and emissions of a controlled tracer release from a nuclear power plant

Probability distribution functions (PDFs) of model inputs that affect the transport and dispersion of a trace gas released from a coastal California nuclear power plant are quantified using ensemble simulations, machine-learning algorithms, and Bayesian inversion. The PDFs are constrained by observations of tracer concentrations and account for uncertainty in meteorology, transport, diffusion, and emissions. Meteorological uncertainty is calculated using an ensemble of simulations of the Weather Research and Forecasting (WRF) model that samples five categories of model inputs (initialization time, boundary layer physics, land surface model, nudging options, and reanalysis data). The WRF output is used to drive tens of thousands of FLEXPART dispersion simulations that sample a uniform distribution of six emissions inputs. Machine-learning algorithms are trained on the ensemble data and used to quantify the sources of ensemble variability and to infer, via inverse modeling, the values of the 11 model inputs most consistent with tracer measurements. We find a substantial ensemble spread in tracer concentrations (factors of 10 to 10 3 ), most of which is due to changing emissions inputs (about 80%), though the cumulative effects of meteorological variations are not negligible. The performance of the inverse method is verified using synthetic observations generated from arbitrarily selected simulations. When applied to measurements from a controlled tracer release experiment, the inverse method satisfactorily determines the location, start time, duration and amount. In a 2 km × 2 km area of possible locations, the actual location is determined to within 200m. The start time is determined to within 5min out of 2h, and the duration to within 50min out of 4h. Over a range of release amounts of 10 to 1000kg, the estimated amount exceeds the actual amount of 146kg by only 32kg. The inversion also estimates probabilities of different WRF configurations. In conclusion, to best match the tracer observations, the highest-probability cases in WRF are associated with using a late initialization time and specific reanalysis data products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Toward reconciling the influence of atmospheric aerosols and greenhouse gases on light precipitation changes in Eastern China

The attribution of the widely observed shifted precipitation extremes to different forcing agents represents a critical issue for understanding of changes in the hydrological cycle. To compare aerosol and greenhouse-gas effects on the historical trends of precipitation intensity, we performed AMIP-style NCAR/DOE CAM5 model simulations from 1950-2005 with and without anthropogenic aerosol forcings. Precipitation rates at every time step in CAM5 are used to construct precipitation probability distribution functions. By contrasting the two sets of experiments, we found that the global warming induced by the accumulating greenhouse gases is responsible for the changes in precipitation intensity at the global scale. However, regionally over the Eastern China, the drastic increase in anthropogenic aerosols primarily accounts for the observed light precipitation suppression since the 1950s. Here, compared with aerosol radiative effects, aerosol microphysical effect has a predominant role in determining the historical trends of precipitation intensity in Eastern China.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Assessment of marine boundary layer cloud simulations in the CAM with CLUBB and updated microphysics scheme based on ARM observations from the Azores

To assess marine boundary layer (MBL) cloud simulations in three versions of the Community Atmosphere Model (CAM), three sets of short-term global hindcasts are performed and compared to Atmospheric Radiation Measurement Program (ARM) observations on Graciosa Island in the Azores from June 2009 to December 2010. Here, the three versions consist of CAM5.3 with default schemes (CAM5.3), CAM5.3 with Cloud Layers Unified By Binormals (CLUBB-MG1), and CAM5.3 with CLUBB and updated microphysics scheme (CLUBB-MG2). Our results show that relative to CAM5.3 default schemes, simulations with CLUBB better represent MBL cloud base height, the height of the major cloud layer, and the daily cloud cover variability. CLUBB also better simulates the relationship of cloud fraction to cloud liquid water path (LWP) most likely due to CLUBB's consistent treatment of these variables through a probability distribution function (PDF) approach. Subcloud evaporation of precipitation is substantially enhanced in simulations with CLUBB-MG2 and is more realistic based on the limited observational estimate. Despite these improvements, all model versions underestimate MBL cloud cover. CLUBB-MG2 reduces biases in in-cloud LWP (clouds are not too bright) but there are still too few of MBL clouds due to an underestimate in the frequency of overcast scenes. Thus, combining CLUBB with MG2 scheme better simulates MBL cloud processes, but because biases remain in MBL cloud cover CLUBB-MG2 does not improve the simulation of the surface shortwave cloud radiative effect (CRE SW ).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Simulation of Precipitation Extremes Using a Stochastic Convective Parameterization in the NCAR CAM5 Under Different Resolutions

With the incorporation of the Plant-Craig stochastic deep convection scheme into the Zhang-McFarlane deterministic parameterization in the Community Atmospheric Model version 5 (CAM5), its impact on extreme precipitation at different resolutions (2°, 1°, and 0.5°) is investigated. CAM5 with the stochastic deep convection scheme (experiment (EXP)) simulates the precipitation extreme indices better than the standard version (control). At 2° and 1° resolutions, EXP increases high percentile (>99th) daily precipitation over the United States, Europe, and China, resulting in a better agreement with observations. However, at 0.5° resolution, due to enhanced grid-scale precipitation with increasing resolution, EXP overestimates extreme precipitation over southeastern U.S. and eastern Europe. The reduced biases in EXP at each resolution benefit from a broader probability distribution function of convective precipitation intensity simulated. Among EXP simulations at different resolutions, if the spatial averaging area over which input quantities used in convective closure are spatially averaged in the stochastic convection scheme is comparable, the modeled convective precipitation intensity decreases with increasing resolution, when gridded to the same resolution, while the total precipitation is not sensitive to model resolution, exhibiting some degree of scale-awareness. Sensitivity tests show that for the same resolution, increasing the size of spatial averaging area decreases convective precipitation but increases the grid-scale precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Global hourly land surface air temperature datasets: inter‐comparison and climate change

ABSTRACT The land surface air temperature ( LSAT ) is one of the fundamental parameters to represent heat transfer and to modulate the moisture cycle between land and atmosphere. Here, we quantify the spatiotemporal characteristics of four newly developed hourly temperature products by merging reanalysis with in situ data Climatic Research Unit ( CRU ). Overall, LSATs from different hourly products are consistent with each other, and their differences are generally smaller in magnitude than biases between hourly products and monthly averaged daily maximum and minimum temperature data from CRU . While the true monthly mean (using hourly values) and the monthly mean (of daily maximum and minimum temperatures) and their seasonality [as represented by the (July–January) differences] differ, their trends agree with each other very well. The polar amplification ratio of average temperature trend north of 65°N to that over global land (excluding Greenland and Antarctica) is also similar among different products, with the annual ratio of around 1.7. The ratio in summer (June–August) is always smaller than the annual value for different periods among all products. Based on the probability distribution functions from the monthly anomalies of different variables, the coldest tenth percentile of temperature in each decade overall increases with time, while the warmest tenth percentile does not vary much from 1950–1979, followed by a rapid increase from 1980–2009. These results and additional sensitivity tests suggest that the 4‐h LSAT products can be widely used for climate analysis, model evaluation, and offline land surface modelling from 1948–2009.

Wang, Aihui↗
DOE OSTI2023

The neutron number probability distribution in coupled lumped assemblies

Here, the validity of the gamma distribution in describing the neutron number probability distribution function for both isolated and coupled multiplying assemblies when constrained to reproduce the true mean and variance is investigated in lumped geometry by numerical comparison with kinetic Monte Carlo simulations. The mean and variance are obtained from numerical solution of moment equations constructed from the relevant forward Master equation with assembly coupling coefficients obtained from a view factor method. Numerical results for a two-group, two coupled assemblies model, with static and dynamic reactivity insertion, show that except for subcritical assemblies, the gamma distribution well-approximates the number distribution. Differences in the fast and thermal neutron population shapes are explained in terms of effective source strengths due to downscatter and coupling.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

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↗