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At least 1,171 records · Page 65

A Genome-Based Model to Predict the Virulence of Pseudomonas aeruginosa Isolates

ABSTRACT: Variation in the genome of Pseudomonas aeruginosa , an important pathogen, can have dramatic impacts on the bacterium’s ability to cause disease. We therefore asked whether it was possible to predict the virulence of P. aeruginosa isolates based on their genomic content. We applied a machine learning approach to a genetically and phenotypically diverse collection of 115 clinical P. aeruginosa isolates using genomic information and corresponding virulence phenotypes in a mouse model of bacteremia. We defined the accessory genome of these isolates through the presence or absence of accessory genomic elements (AGEs), sequences present in some strains but not others. Machine learning models trained using AGEs were predictive of virulence, with a mean nested cross-validation accuracy of 75% using the random forest algorithm. However, individual AGEs did not have a large influence on the algorithm’s performance, suggesting instead that virulence predictions are derived from a diffuse genomic signature. These results were validated with an independent test set of 25 P. aeruginosa isolates whose virulence was predicted with 72% accuracy. Machine learning models trained using core genome single-nucleotide variants and whole-genome k-mers also predicted virulence. Our findings are a proof of concept for the use of bacterial genomes to predict pathogenicity in P. aeruginosa and highlight the potential of this approach for predicting patient outcomes. IMPORTANCE Pseudomonas aeruginosa is a clinically important Gram-negative opportunistic pathogen. P. aeruginosa shows a large degree of genomic heterogeneity both through variation in sequences found throughout the species (core genome) and through the presence or absence of sequences in different isolates (accessory genome). P. aeruginosa isolates also differ markedly in their ability to cause disease. In this study, we used machine learning to predict the virulence level of P. aeruginosa isolates in a mouse bacteremia model based on genomic content. We show that both the accessory and core genomes are predictive of virulence. This study provides a machine learning framework to investigate relationships between bacterial genomes and complex phenotypes such as virulence.

59 BASIC BIOLOGICAL SCIENCES↗

Traffic safety analysis and model updating for freeways using Bayesian method

Freeway crash prediction models are the basic of traffic safety research, yet crash occurrence and the influencing factors change over time. In order to make sure the implemented safety models fit the current traffic environment, this study conducts a comparative analysis of 2017 and 2020 datasets collected from freeways in Suzhou, China. Herein, considering the spatial correlation among analysis units and the hierarchical data structure, a Bayesian conditional autoregressive negative binomial (CAR-NB) model and a Bayesian hierarchical CAR-NB (HCAR-NB) model were used to explore the safety influencing factors, and a traditional NB model was developed for further comparison. To update the HCAR-NB model from 2017 to 2020, Bayesian inference with informative priors was used to improve its goodness of fit and efficiency. Preliminary results showed that 1) the HCAR-NB model outperformed the NB model and CAR-NB model in prediction accuracy, and 2) the number of crashes was significantly correlated with average speed, speed variance, road segment length, number of lanes, and presence of ramps. The potential for safety improvement (PSI) method was applied to the modeling results to identify hotspots for the two years. The results confirmed that the hotspots spatiotemporally shifted among the freeways. The proposed crash prediction model and updating method are expected to assist implementation of informed countermeasures for freeway safety improvement.

97 MATHEMATICS AND COMPUTING↗

Active and Widespread Halogen Chemistry in the Tropical and Subtropical Free Troposphere

Halogens in the troposphere are increasingly recognized as playing an important role for atmospheric chemistry, and possibly climate. Bromine and iodine react catalytically to destroy ozone (O3), oxidize mercury, and modify oxidative capacity that is relevant for the lifetime of greenhouse gases. Most of the tropospheric O3 and methane (CH4) loss occurs at tropical latitudes. Here we report simultaneous measurements of vertical profiles of bromine oxide (BrO) and iodine oxide (IO) in the tropical and subtropical free troposphere (10degN to 40degS), and show that these halogens are responsible for 34% of the column-integrated loss of tropospheric O3. The observed BrO concentrations increase strongly with altitude (approx.3.4 pptv at 13.5 km), and are 2-4 times higher than predicted in the tropical free troposphere. BrO resembles model predictions more closely in stratospheric air. The largest model low bias is observed in the lower tropical transition layer (TTL) over the tropical eastern Pacific Ocean, and may reflect a missing inorganic bromine source supplying an additional 2.5-6.4 pptv total inorganic bromine (Bry), or model overestimated Bry wet scavenging. Our results highlight the importance of heterogeneous chemistry on ice clouds, and imply an additional Bry source from the debromination of sea salt residue in the lower TTL. The observed levels of bromine oxidize mercury up to 3.5 times faster than models predict, possibly increasing mercury deposition to the ocean. The halogen-catalyzed loss of tropospheric O3 needs to be considered when estimating past and future ozone radiative effects.

Wang, Siyuan↗

The measurement, modelling and prediction of traction forces in a rocket propellant

Traction tests were performed on RPI, a common kerosene-based rocket propellant. Traction data on this fluid are required for purposes of turbopump bearing design, using such codes as SHABERTH. To obtain the traction data, an existing twin disk machine was used, operating under the side slip mode and using elliptical contacts. The resulting traction curves were reduced to fundamental fluid property parameters using the Johnson and Tevaarwerk traction model. Theoretical traction predictions were performed by back substitution of the fundamental properties into the traction model. Comparison of the predicted with the measured curves gives a high degree of confidence in the correctness of the traction model.

Tevaarwerk, J. L.↗

Static Loads Testing of a High Aspect Ratio Tow-Steered Wingbox

Static loads testing was performed on a 39-foot, high-aspect-ratio wingbox comprising carbon fiber tow-steered wing skins that were tailored for aircraft fuel efficiency under aeroelastic loads. The test article was designated the Passive Aeroelastic Tailored (PAT) wing. To date, the PAT wing, which has an aspect ratio of 13.5, is the largest wingbox designed and built to employ variably oriented carbon fibers along the span of the wing. During testing, distributed point loads were applied to the wingbox to simulate both -1g and 2.5g maneuver loads. To determine the wingbox’s flexural axis location, individual point loads were applied. The global response of the wing (displacement and rotation measurements) showed similar trends compared to the finite element model predictions, though discrepancies of up to 17% were observed when comparing actual values between model and test. It was concluded that the boundary conditions and nonstructural features of the wingbox were the likely cause of the inconsistencies. The local response of the wingbox (strain measurements), which was much less affected by factors unrelated to tow-steering, exhibited good agreement with the model predictions, validating the modelling techniques employed for tow-steered composites.

Tow-steered composites↗

Computational model for predicting the performance of fluid-powered longiudinal piston modules and motors.

A Matlab-based computational model line code has been developed for predicting the performance of fluid-powered longitudinal piston modules and motors. A system of equations has been developed based upon applying the conservation of mass to a control volume defined by a reciprocating piston. The method results in a differential equation that predicts the pressure gradient in the control volume as a function of rotor rotation angle. The model uses an integration scheme to predict the pressure state in the control volume. The orifice equation is used to predict the flowrate in and out of the control volume. From the resulting solution the torque and speed characteristics of the motor configuration can be predicted, optimized, or tailored for a specific requirement.SAND2019-13983 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Taylor, Michael↗

Role of ion temperature anisotropy in multistage refilling of the outer plasmasphere

The refilling processes predicted by the ion temperature anisotropy (TAN) model and those of a model based on the assumption of temperature isotropy (TISO) are compared. It is noted that the TISO model predicts that a flux tube with L = 4 undergoes a substantial refilling in about 12 hours after a severe depletion, while the TAN model predicts much longer refilling time divided in two stages, with the supersonic flows from the conjugate ionospheres in the early stage, lasting over a few hours. The plasma in the flux tube develops an anisotropy causing a downward force, which balances the upward electric and pressure forces on ions keeping the flux tube depleted. The second stage starts when the temperature anisotropy begins to relax due to Coulomb collisions at high altitudes and is characterized by a subsonic flow.

Singh, Nagendra↗

Application of an Erosion Wear Model to Predict Wear of Hammer Milling Components

A workable analytical erosion model that relates critical hammermill process parameters (hammermill geometry and rotational speed) to critical material attributes of inorganic mineral species in feedstock (density, size, and aspect ratio) and substrate (hardness, toughness, and fatigue ductility) was applied to model wear (more specifically, change in the shape of hammers) in hammer milling operations. Results of the model were compared to experimental observations of the shape of hammers used in the INL Stage 1 Vermeer hammermill. Results showed good agreement between predicted and measured shape of the hammer, and that a quality-by-design (QbD) approach can be developed to predict component reliability based on scientific engineering principles in lieu of trial-and-error approaches.

36 MATERIALS SCIENCE↗

A Reduced Model for Prediction of Thermal and Rotational Effects on Turbine Tip Clearance

This paper describes a dynamic model that was developed to predict changes in turbine tip clearance the radial distance between the end of a turbine blade and the abradable tip seal. The clearance is estimated by using a first principles approach to model the thermal and mechanical effects of engine operating conditions on the turbine sub-components. These effects are summed to determine the resulting clearance. The model is demonstrated via a ground idle to maximum power transient and a lapse-rate takeoff transient. Results show the model demonstrates the expected pinch point behavior. The paper concludes by identifying knowledge gaps and suggesting additional research to improve the model.

Kypuros, Javier A.↗

Modeling and Prediction of the Noise from Non-Axisymmetric Jets

The new source model was combined with the original sound propagation model developed for rectangular jets to produce a new version of the rectangular jet noise prediction code. This code was validated using a set of rectangular nozzles whose geometries were specified by NASA. Nozzles of aspect ratios two, four and eight were studied at jet exit Mach numbers of 0.5, 0.7 and 0.9, for a total of nine cases. Reynolds-averaged Navier-Stokes solutions for these jets were provided to the contactor for use as input to the code. Quantitative comparisons of the predicted azimuthal and polar directivity of the acoustic spectrum were made with experimental data provided by NASA. The results of these comparisons, along with a documentation of the propagation and source models, were reported in a journal article publication (Ref. 4). The complete set of computer codes and computational modules that make up the prediction scheme, along with a user's guide describing their use and example test cases, was provided to NASA as a deliverable of this task. The use of conformal mapping, along with simplified modeling of the mean flow field, for noise propagation modeling was explored for other nozzle geometries, to support the task milestone of developing methods which are applicable to other geometries and flow conditions of interest to NASA. A model to represent twin round jets using this approach was formulated and implemented. A general approach to solving the equations governing sound propagation in a locally parallel nonaxisymmetric jet was developed and implemented, in aid of the tasks and milestones charged with selecting more exact numerical methods for modeling sound propagation, and developing methods that have application to other nozzle geometries. The method is based on expansion of both the mean-flowdependent coefficients in the governing equation and the Green's function in series of orthogonal functions. The method was coded and tested on two analytically prescribed mean flows which were meant to represent noise reduction concepts being considered by NASA. Testing (Ref. 5) showed that the method was feasible for the types of mean flows of interest in jet noise applications. Subsequently, this method was further developed to allow use of mean flow profiles obtained from a Reynolds-averaged Navier-Stokes (RANS) solution of the flow. Preliminary testing of the generalized code was among the last tasks completed under this contract. The stringent noise-reduction goals of NASA's Fundamental Aeronautics Program suggest that, in addition to potentially complex exhaust nozzle geometries, next generation aircraft will also involve tighter integration of the engine with the airframe. Therefore, noise generated and propagated by jet flows in the vicinity of solid surfaces is expected to be quite significant, and reduced-order noise prediction tools will be needed that can deal with such geometries. One important source of noise is that generated by the interaction of a turbulent jet with the edge of a solid surface (edge noise). Such noise is generated, for example, by the passing of the engine exhaust over a shielding surface, such as a wing. Work under this task supported an effort to develop a RANS-based prediction code for edge noise based on an extension of the classical Rapid Distortion Theory (RDT) to transversely sheared base flows (Refs. 6 and 7). The RDT-based theoretical analysis was applied to the generic problem of a turbulent jet interacting with the trailing edge of a flat plate. A code was written to evaluate the formula derived for the spectrum of the noise produced by this interaction and results were compared with data taken at NASA Glenn for a variety of jet/plate configurations and flow conditions (Ref. 8). A longer-term goal of this task was to work toward the development of a high-fidelity model of sound propagation in spatially developing non-axisymmetric jets using direct numerical methods for solving the relevant equations. Working with NASA Glenn Acoustics Branch personnel, numerical methods and boundary conditions appropriate for use in a high-resolution calculation of the full equations governing sound propagation in a steady base flow were identified. Computer codes were then written (by NASA) and tested (by OAI) for an increasingly complex set of flow conditions to validate the methods. The NASA-supplied codes were ported to the High-End Computing resources of the NASA Advanced Supercomputing facility for testing and validation against analytical (where possible) and independent numerical solutions. The cases which were completed during the course of this contract were solutions of the two-dimensional linearized Euler equations with no mean flow, a uniform mean flow and a nonuniform mean flow representative of a parallel flow jet.

Leib, Stewart J.↗

Planetary atmosphere modeling and predictions

The capability to generate spacecraft frequency predictions which include the refractive bending effects induced during signal passage through a planetary atmosphere is a pivotal element of the DSN Radio Science System. This article describes the current implementation effort to develop planetary atmosphere modeling and prediction capability.

Berman, A. L.↗

Modeling Chemo-Mechanics with Electrolyte Infiltration to Quantify Degradation of Cathode Particles

One of the main goals in modeling lithium-ion batteries is to improve/predict longevity and resilience of new chemistries. To that end, this talk investigates the formation of stress-induced fracture within polycrystalline cathode particles and the impact on capacity loss. Physically based cathode aging dynamics is simulated in a 3D, continuum-level chemo-mechanical model. The model captures anisotropic Li diffusion within a single polycrystalline particle comprised of hundreds to thousands of randomly oriented grains. A recent addition to this model includes electrolyte infiltration, which occurs when the electrolyte seeps into surface cracks within the particle. The model predicts that particle fracture is primarily due to non-ideal grain interactions with slight dependence on high-rate charge demands. Essentially, when neighboring grains are misaligned, they expand a different rates relative to one another leading to high stresses and ultimately the formation of intraparticle cracks. The model predicts that small particles with large grains develop significantly less damage than larger particles with small grains. Finally, the model predicts most of the chemo-mechanical damage accumulates in the first charge after formation. This chemo-mechanical "damage saturation" effect indicates that initial particle fracture occurs within the first few cycles, while long-term cathode degradation is not solely chemo-mechanically induced. The principle contribution of this research is the use of an anisotropic chemo-mechanical model to test how particle geometry affect capacity fade, which predicts that particle size has a stronger effect on capacity fade than grain size and ultimately that small particles with large grains have the least capacity fade.

cathode↗

Model Based Predictive Control for Frequency Support in Multi-port Autonomous Reconfigurable Solar Plants

Primary frequency support functionality can be an added advantage for any new grid integrated power electronics resource. With increased penetration of power electronics resources, inertial and primary frequency response capabilities are decreasing. In this research paper, an advanced model-based predictive control (MBPC) algorithm for providing frequency support to a new topology of integrated photovoltaic(PV), batterybased energy storage systems (ESS), and high-voltage direct current (HV dc) systems called multi-port autonomus reconfigurable solar (MARS) plants is based on the synchronverter-based control. The simulation of MARS-HV dc system with proposed control strategy is simulated and validated for MARS connected to low short circuit ratio (SCR) grids in PSCAD/EMTDC simulation environment. The control algorithm proposed showcases better performance in terms of frequency nadir improvement and frequency steady state improvemnt with respect to no frequency control.

Marthi, Phani Ratna Vanamali↗

A statistical model to predict ignition probability

Ignition capability is a critical design constraint for aeronautical gas turbines. However the current trend toward overall lean burn is detrimental to the engine ignition and relight and the ignition system must be adapted to ensure a fast and reliable light-round in all circumstances. As ignition is a stochastic phenomenon, the optimization of an ignition system requires to build ignition probability maps, which is difficult and costly with either experiment or numerical simulation as both require many tests. Here, this work proposes a model to predict the ignition probability map, knowing only flow statistics in non-reacting conditions, i.e., with only one test. The originality of the model is to construct statistics of the flame kernel trajectory, which are then combined with local flow indicators to evaluate the ignition probability at the considered sparking location. Application to a swirled burner operated in premixed, non-premixed and spray combustion modes illustrates the model concepts and demonstrates its ability to recover the experimental ignition map with good accuracy.

42 ENGINEERING↗

A Hybrid CFD/Engineering Model for Predicting Plume Induced Erosion and Cratering

The Descent Interpolated Gas-Granular Erosion Model (DIGGEM) is a hybrid computational fluid dynamics (CFD) / engineering model calibrated with flight data from Apollo. It is used for the prediction of plume induced viscous erosion and cratering during the descent of landing vehicles. The model assumes a functional relationship between local shear stress and eroded mass flux. It is used along with a suite of other tools to predict complex plume induced environments for Human Landing System (HLS) and Commercial Lunar Payload Services (CLPSS) vehicles.

PSI↗

Multi-Parameter Yield Zone Model for Predicting Spectrum Crack Growth

A systematic technique is presented for modeling crack growth load interaction effects due to spectrum loading. The Multi-Parameter Yield Zone (MPYZ) model accounts for crack growth retardation, acceleration, and underload effects. The load interactions are attributed to the residual stress intensity due to the plastic deformation at the crack tip. Fatigue crack growth was predicted and compared with test data for a variety of spectrum loadings.

Johnson, W. S.↗

The Implications of ACTS Technology on the Requirements of Rain Attenuation Modeling for Communication System Specification and Analysis at 30/20 GHz and Beyond

The advent of the use of the Ka-Band for space communications, coupled with the introduction of digital modulation techniques as well as multiple-beam methodology for satellites, has deemed it necessary to reassess the plethora of rain attenuation prediction models in use. The Advanced Communication Technology Satellite (ACTS) Project, undertaken by the National Aeronautics and Space Administration in 1983, offered such challenges to rain attenuation prediction modeling. Up to 1983, no such single modeling formalism existed that could fill such requirements. Not even the work done by the NASA Propagation Experimenters (NAPEX) Group had envisioned such requirements, so no dynamic Ka-Band data existed from which one could draw conclusions. In this paper, the basic rudiments of what has become to be known as the 'ACTS Rain Attenuation Prediction Model' will be presented. The concept of rain fade mitigation control availability will be introduced. A new evaluation is then presented for the performance of satellite communication systems, in particular, those to be operating within the Ka-Band and above, that will necessarily employ some type of dynamic rain fade mitigation procedure.

Manning, Robert M.↗

Durability/life of fiber composites in hygrothermomechanical environments

Statistical analysis and multiple regression were used to determine and quantify the significant hygrothermomechanical variables which influence the tensile durability/life (cycle loading, fatigue) of boron-fiber/epoxy-matrix (B/E) and high-modulus-fiber/epoxy-matrix (HMS/E) composites. The use of the multiple regression analysis reduced the variables from fifteen, assumed initially, to six or less with a probability of greater than 0.999. The reduced variables were used to derive predictive models for compression and intralaminar shear durability/life of B/E and HMS/E composites assuming isoparametric fatigue behavior. The predictive models were subsequently generalized to predict the durability/life of graphite/fiber-r generalized model is of simple form, predicts conservative values compared with measured data and should be adequate for use in preliminary designs. Previously announced in STAR as N82-14287

Chamis, C. C.↗