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At least 271 records · Page 15

Factor analytic reduction of the carotid-cardiac baroreflex parameters

An accepted method for measuring the responsiveness of the carotid-cardiac baroreflex to arterial pressure changes is to artificially stimulate the baroreceptors in the neck. This is accomplished by using a pressurized neck cuff which constricts and distends the carotid artery and subsequently stimulates the baroreceptors. Nine physiological responses to this type of stimulation are quantified and used as indicators of the baroreflex. Thirty male humans between the ages 27 and 46 underwent the carotid-cardiac baroreflex test. The data for the nine response parameters were analyzed by principle component factor analysis. The results of this analysis indicated that 93 percent of the total variance across all nine parameters could be explained in four dimensions. Examination of the factor loadings following an orthogonal rotation of the principle components indicated four well defined dimensions. The first two dimensions reflected location points for R-R interval and carotid distending pressure respectively. The third dimension was composed of measures reflecting the gain of the reflex. The fourth dimension was the ratio of the resting R-R interval to R-R interval during simulated hypertension. The data suggests that the analysis of all nine baroreflex parameters is redundant.

Ludwig, David A.↗

Roles of mineral matter in biomass processing to biofuels

Abstract Minerals in biomass have a significant impact on both biofuel quality and yield. This is especially true for current thermochemical biomass conversion processes. However, the roles of plant minerals in biochemical conversion have not been studied extensively, even though they are generally considered to lower the sugar yield because they reduce the feedstock proportion of carbohydrates. A successful strategic solution is thus necessary to overcome the challenges caused by the minerals in biomass, which include (1) decreased quality of biomass feedstocks; (2) reduction of process efficiency; and (3) reduction of the product quality and quantity from biomass conversion. This review summarizes the roles of plant minerals in a biorefinery, focusing on these key challenges. The discussion covers many issues related to plant minerals in biofuel production, including their sources, functions, and distribution in plant biomass, methods of characterizing them, their influence in a biorefinery, and the strategic handling required to manage their occurrence in biomass, based on reported studies. It could inspire better strategies to deal with the variance of mineral content in biomass feedstocks to increase process efficiency and reduce costs while supporting the concept of a circular bioeconomy. © 2023 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗

Visual Instance-aware Prompt Tuning

Visual Prompt Tuning (VPT) has emerged as a parameter-efficient fine-tuning paradigm for vision transformers, with conventional approaches utilizing dataset-level prompts that remain the same across all input instances. We observe that this strategy results in sub-optimal performance due to high variance in downstream datasets. To address this challenge, we propose Visual Instance-aware Prompt Tuning (ViaPT), which generates instance-aware prompts based on each individual input and fuses them with dataset-level prompts, leveraging Principal Component Analysis (PCA) to retain important prompting information. Moreover, we reveal that VPT-Deep and VPT-Shallow represent two corner cases based on a conceptual understanding, in which they fail to effectively capture instance-specific information, while random dimension reduction on prompts only yields performance between the two extremes. Instead, ViaPT overcomes these limitations by balancing dataset-level and instance-level knowledge, while reducing the amount of learnable parameters compared to VPT-Deep. Extensive experiments across 34 diverse datasets demonstrate that our method consistently outperforms state-of-the-art baselines, establishing a new paradigm for analyzing and optimizing visual prompts for vision transformers.

Xiao, Xi [ORNL] (ORCID:0009000009316982)↗

Low-Pressure Long-Term Xenon Storage for Electric Propulsion

This Phase 2 effort demonstrated an alternative Xe storage and regulation system using activated carbon (AC) as a secondary storage media (ACSFR). This regulator system is nonmechanical, simple, inexpensive, and lighter. The ACSFR system isolates the thruster from the compressed gas tank, and allows independent multiple setpoint thruster operation. The flow using an ACSFR can also be throttled by applying increments in electrical power. Primary storage of Xe by AC is not superior to compressed gas storage with regard to weight, but AC storage can provide volume reduction, lower pressures in space, and potentially in situ Xe purification. With partial fill designs, a primary AC storage vessel for Xe could also eliminate problems with two-phase storage and regulate pressure. AC could also be utilized in long-term large quantity storage of Xe serving as a compact capture site for boil-off. Several Xe delivery ACSFR protocols between 2 and 45 sccm, and 15 min to 7 hr, were tested with an average flow variance of 1.2 percent, average power requirements of 5 W, and repeatability s of about 0.4 percent. Power requirements are affected by ACSFR bed sizing and flow rate/ duration design points, and these flow variances can be reduced by optimizing PID controller parameters.

Back, Dwight D.↗

Ground-to-Ground Optical Communications Demonstration

A bidirectional horizontal-path optical link was demonstrated between Strawberry Peak (SP), Lake Arrowhead, California, and the JPL Table Mountain Facility (TMF), Wrightwood, California, during June and November of 1998. The 0.6-m telescope at TMF was used to broadcast a 4-beam 780-nm beacon to SP. The JPL-patented Optical Communications Demonstrator (OCD) at SP received the beacon, performed ne tracking to compensate for the atmosphere-induced beacon motion and retransmitted a 844-nm communications laser beam modulated at 40 to 500 Mb/s back to TMF. Characteristics of the horizontal-path atmospheric channel as well as performance of the optical communications link were evaluated. The normalized variance of the irradiance fluctuations or scintillation index delta2/I at either end was determined. At TMF where a single 844-nm beam was received by a 0.6-m aperture, the measured delta2/I covered a wide range from 0.07 to 1.08. A single 780-nm beam delta2/I measured at SP using a 0.09-m aperture yielded values ranging from 0.66 to 1.03, while a combination of four beams reduced the scintillation index due to incoherent averaging to 0.22 to 0.40. This reduction reduced the dynamic range of the fluctuations from 17 to 21 dB to 13 to 14 dB as compared with the OCD tracking sensor dynamic range of 10 dB. Predictions of these values also were made based on existing theories and are compared. Generally speaking, the theoretical bounds were reasonable. Discussions on the probability density function (PDF) of the intensity fluctuations are presented and compared with the measurements made. The lognormal PDF was found to agree for the weak scintillation regime as expected. The present measurements support evidence presented by earlier measurements made using the same horizontal path, which suggests that the aperture averaging effect is better than theoretically predicted.

Biswas, A.↗

Effect of Flight on Turbulence Statistics and Noise Sources in a Round Turbulent Jet

Turbulence statistics relevant to noise modeling and prediction are computed in a near-sonic, unheated round jet in the presence of a flight stream using Large Eddy Simulation. The Naval Research Laboratory’s Jet Engine Noise REduction (JENRE) code is used to obtain unsteady flow solutions which are post-processed for single- and two-point, space-time statistical quantities, including the nominal noise sources from an acoustic analogy formulation. Jets subject to three different flight-stream speeds, along with a baseline static case, are considered. The impact of flight-stream speed on mean flow and turbulence profiles and the amplitudes, length and time scales of Reynolds-stress auto co-variances are determined and scalings for representing the flight stream effect are explored. The implications for source modeling in jet mixing noise predictions within an acoustic analogy formulation are discussed.

Jet noise, flight effects, aircraft noise↗

Effect of Flight on Turbulence Statistics and Noise Sources in a Round Turbulent Jet

Turbulence statistics relevant to noise modeling and prediction are computed in a series near-sonic, unheated round jets in the presence of a flight stream using Large Eddy Simulation. The Naval Research Laboratory’s Jet Engine Noise REduction (JENRE®) code is used to obtain unsteady flow solutions which are post-processed for single- and two-point, space-time statistical quantities, including the nominal noise sources from an acoustic analogy formulation. Jets subject to three different flight-stream speeds, along with a baseline static case, are considered. The impact of flight-stream speed on mean flow and turbulence profiles and the amplitudes, length and time scales of Reynolds-stress auto co-variances are determined and scalings for representing the flight-stream effect are explored. The implications for source modeling in jet mixing noise predictions within an acoustic analogy formulation are discussed.

Jet noise↗

Effect of Flight on Turbulence Statistics and Noise Sources in a Round Turbulent Jet

Turbulence statistics relevant to noise modeling and prediction are computed in a series near-sonic, unheated round jets in the presence of a flight stream using Large Eddy Simulation. The Naval Research Laboratory’s Jet Engine Noise REduction (JENRE) code is used to obtain unsteady flow solutions which are post-processed for single- and two-point, space-time statistical quantities, including the nominal noise sources from an acoustic analogy formulation. Jets subject to three different flight-stream speeds, along with a baseline static case, are considered. The impact of flight-stream speed on mean flow and turbulence profiles and the amplitudes, length and time scales of Reynolds-stress auto co-variances are determined and scalings for representing the flight-stream effect are explored. The implications for source modeling in jet mixing noise predictions within an acoustic analogy formulation are discussed.

Jet noise↗

Detailed modeling of the video signal and optimal readout of charge-coupled devices

This paper provides a practical design methodology to calculate an optimal filter for noise reduction in the readout of charge-coupled devices (CCDs) taking into account the charge transfer and feedthroughs due to capacitive coupling in the CCD. A detailed analysis of the dynamics of the video signal and charge transfer is presented, including the circuital modeling of the output stage of the CCD and the dynamics of the electronics in the video chain before the analog-to-digital (AD) converter. This model is used to compute an optimal filter that minimizes the variance of the pixel noise and uses the samples of the charge transfer, before the charge is fully settled. This is necessary to enhance the performance of previous results that also use optimal filters but do not use the transition samples, while also reducing the pixel readout time, resulting in faster readouts. As a proof of concept for the optimal filter, we present in this paper novel experimental results using a Skipper CCD, which has a floating sense node that allows to measure the charge packet an arbitrary number of times. However, this technique can be applied to any CCD that has a readout system that digitally samples the video signal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Direct simulation of compressible turbulence in a shear flow

Compressibility effects on the turbulence in homogeneous shear flow are investigated. The growth of the turbulent kinetic energy was found to decrease with increasing Mach number: a phenomenon which is similar to the reduction of turbulent velocity intensities observed in experiments on supersonic free shear layers. An examination of the turbulent energy budget shows that both the compressible dissipation and the pressure-dilatation contribute to the decrease in the growth of kinetic energy. The pressure-dilatation is predominantly negative in homogeneous shear flow, in contrast to its predominantly positive behavior in isotropic turbulence. The different signs of the pressure-dilatation are explained by theoretical consideration of the equations for the pressure variance and density variance. Previously, the following results were obtained for isotropic turbulence: (1) the normalized compressible dissipation is of O(M(sub t)(exp 2)); and (2) there is approximate equipartition between the kinetic and potential energies associated with the fluctuating compressible mode. Both of these results were substantiated in the case of homogeneous shear. The dilatation field is significantly more skewed and intermittent than the vorticity field. Strong compressions seem to be more likely than strong expansions.

Sarkar, S.↗

Direct simulation of compressible turbulence in a shear flow

The purpose of this study is to investigate compressibility effects on the turbulence in homogeneous shear flow. It is found that the growth of the turbulent kinetic energy decreases with increasing Mach number, a phenomenon similar to the reduction of turbulent velocity intensities observed in experiments on supersonic free shear layers. An examination of the turbulent energy budget shows that both the compressible dissipation and the pressure-dilatation contribute to the decrease in the growth of kinetic energy. The pressure-dilatation is predominantly negative in homogeneous shear flow, in contrast to its predominantly positive behavior in isotropic turbulence. The different signs of the pressure-dilatation are explained by theoretical consideration of the equations for the pressure variance and density variance.

Sarkar, S.↗

A 3-D Navier-Stokes CFD study of turbojet/ramjet nozzle plume interactions at Mach 3.0 and comparison with data

Advanced airbreathing propulsion systems used in Mach 4-6 mission scenarios, usually consist of a single integrated turboramjet or as in this study, a turbojet housed in an upper bay with a separate ramjet housed in a lower bay. As the engines transition from turbojet to ramjet, there is an operational envelope where both engines operate simultaneously. One nozzle concept under consideration has a common nozzle, where the plumes from the turbojet and ramjet interact with one another as they expand to ambient conditions. In this paper, the two plumes interact at the end of a common 2-D cowl, when they both reach an approximate Mach 3.0 condition and then jointly expand to Mach 3.6 at the common nozzle exit plane. At this condition, the turbojet engine operated at a higher NPR than the ramjet, where the turbojet overpowers the ramjet plume, deflecting it approximately 12 degrees downward and in turn the turbojet plume is deflected 6 degrees upward. In the process, shocks were formed at the deflections and a shear layer formed at the confluence of the two jets. This particular case was experimentally tested and the data used to compare with the PARC3D code with k-kl two equation turbulence model. The 2-D and 3-D centerline CFD solutions are in good agreement, but as the CFD solutions approach the outer sidewall, a slight variance occurs. The outer wall boundary layers are thin and do not present much of an interaction, however, where the confluence interaction shocks interact with the thin boundary layer on the outer wall, strong vortices run down each shock causing substantial disturbances in the boundary layer. These disturbances amplify somewhat as they propagate downstream axially from the confluence point. The nozzle coefficient (CFG) is reduced 1/2 percent as a result of this sidewall interaction, from 0.9850 to 0.9807. This three-dimensional reduction is in better agreement with the experimental value of 0.9790.

Chang, Ing↗

Uncertainty Reduction using Bayesian Inference and Sensitivity Analysis: A Sequential Approach to the NASA Langley Uncertainty Quantification Challenge

This paper presents a computational framework for uncertainty characterization and propagation, and sensitivity analysis under the presence of aleatory and epistemic un- certainty, and develops a rigorous methodology for efficient refinement of epistemic un- certainty by identifying important epistemic variables that significantly affect the overall performance of an engineering system. The proposed methodology is illustrated using the NASA Langley Uncertainty Quantification Challenge (NASA-LUQC) problem that deals with uncertainty analysis of a generic transport model (GTM). First, Bayesian inference is used to infer subsystem-level epistemic quantities using the subsystem-level model and corresponding data. Second, tools of variance-based global sensitivity analysis are used to identify four important epistemic variables (this limitation specified in the NASA-LUQC is reflective of practical engineering situations where not all epistemic variables can be refined due to time/budget constraints) that significantly affect system-level performance. The most significant contribution of this paper is the development of the sequential refine- ment methodology, where epistemic variables for refinement are not identified all-at-once. Instead, only one variable is first identified, and then, Bayesian inference and global sensi- tivity calculations are repeated to identify the next important variable. This procedure is continued until all 4 variables are identified and the refinement in the system-level perfor- mance is computed. The advantages of the proposed sequential refinement methodology over the all-at-once uncertainty refinement approach are explained, and then applied to the NASA Langley Uncertainty Quantification Challenge problem.

Uncertainty↗

A Vertically Resolved Analysis of Radiative Feedbacks on Moist Static Energy Variance in Tropical Cyclones

Abstract A vertically resolved moist static energy (MSE) variance budget framework is used to diagnose processes associated with the development of tropical cyclones (TCs) in a general circulation model (GCM) under realistic boundary conditions. Previous studies have shown that interactions between radiation and MSE promote TC development. Here, we examine the vertical contributions of radiation and its interactions with MSE by performing several mechanism-denial experiments in which synoptic-scale radiative interactions are suppressed either in the boundary layer or in the free troposphere. Partly suppressing radiative interactions results in a reduction in global TC frequency. However, the magnitude of reduction and structure of the feedback depend on the intensity and structure of the TCs in these mechanism-denial experiments, indicating that both the magnitude and the vertical location of radiative interactions can impact global TC frequency. Using instantaneous 6-hourly outputs, an explicit computation reveals distinct spatial patterns of the advection term: the vertical component is positive in the mid- to upper troposphere, which reflects an upward transport of MSE by deep convection, whereas the horizontal component is positive in the boundary layer. These results illustrate the impact of the vertical distribution of radiative interactions and vertically varied contribution of the advection term in the development of TCs.

Meteorology & Atmospheric Sciences↗

Sensitivity analysis of thermal contact conductance modeling to inform MiniFuel irradiation capsule designs

The MiniFuel irradiation platform has been developed by Oak Ridge National Laboratory as a flexible, high-throughput separate effects testing capability within the High Flux Isotope Reactor (HFIR). Finite element thermal models are relied upon to design MiniFuel experiments to achieve a specific time-averaged irradiation temperature for experimental objectives. A previous study identified that uncertainty in the component heat generation rates and thermal contact conductance (TCC) model are the most significant contributors to predicted fuel temperature variance. To address both sources of uncertainty, this work performs sensitivity analysis on the TCC model to identify high-impact, high-uncertainty parameters that contribute to fuel temperature variance. The TCC model is analyzed in increasing detail, first using a standalone Python code, then again after coupling Python to the BISON fuel performance code. Furthermore, the parameters with the largest contributions to fuel temperature variance which can be reduced through design changes are identified as the initial subcapsule gas pressure, contact pressure between the fuel and dish, and the effective surface roughness of the interface. A set of design recommendations for future capsule designs has been established and applied to reduce the previously quantified average fuel temperature uncertainty ranges of ± 40 °C in the HFIR vertical experiment facilities (VXF) and ± 80 °C in the removable beryllium (RB) reflector to approximately ± 32 °C and ± 53 °C, respectively. This equates to a 21 % and 33 % reduction in the uncertainty range of the average fuel temperature for VXF and RB, respectively.

BISON↗

An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change

Abstract. This study investigated the computational benefits of using multi-fidelity statistical estimation (MFSE) algorithms to quantify uncertainty in the mass change of Humboldt Glacier, Greenland, between 2007 and 2100 using a single climate change scenario. The goal of this study was to determine whether MFSE can use multiple models of varying cost and accuracy to reduce the computational cost of estimating the mean and variance of the projected mass change of a glacier. The problem size and complexity were chosen to reflect the challenges posed by future continental-scale studies while still facilitating a computationally feasible investigation of MFSE methods. When quantifying uncertainty introduced by a high-dimensional parameterization of the basal friction field, MFSE was able to reduce the mean-squared error in the estimates of the statistics by well over an order of magnitude when compared to a single-fidelity approach that only used the highest-fidelity model. This significant reduction in computational cost was achieved despite the low-fidelity models used being incapable of capturing the local features of the ice-flow fields predicted by the high-fidelity model. The MFSE algorithms were able to effectively leverage the high correlation between each model's predictions of mass change, which all responded similarly to perturbations in the model inputs. Consequently, our results suggest that MFSE could be highly useful for reducing the cost of computing continental-scale probabilistic projections of sea-level rise due to ice-sheet mass change.

54 ENVIRONMENTAL SCIENCES↗

Understanding Growth Dynamics and Yield Prediction of Sorghum Using High Temporal Resolution UAV Imagery Time Series and Machine Learning

Unmanned aerial vehicles (UAV) carrying multispectral cameras are increasingly being used for high-throughput phenotyping (HTP) of above-ground traits of crops to study genetic diversity, resource use efficiency and responses to abiotic or biotic stresses. There is significant unexplored potential for repeated data collection through a field season to reveal information on the rates of growth and provide predictions of the final yield. Generating such information early in the season would create opportunities for more efficient in-depth phenotyping and germplasm selection. This study tested the use of high-resolution time-series imagery (5 or 10 sampling dates) to understand the relationships between growth dynamics, temporal resolution and end-of-season above-ground biomass (AGB) in 869 diverse accessions of highly productive (mean AGB = 23.4 Mg/Ha), photoperiod sensitive sorghum. Canopy surface height (CSM), ground cover (GC), and five common spectral indices were considered as features of the crop phenotype. Spline curve fitting was used to integrate data from single flights into continuous time courses. Random Forest was used to predict end-of-season AGB from aerial imagery, and to identify the most informative variables driving predictions. Improved prediction of end-of-season AGB (RMSE reduction of 0.24 Mg/Ha) was achieved earlier in the growing season (10 to 20 days) by leveraging early- and mid-season measurement of the rate of change of geometric and spectral features. Early in the season, dynamic traits describing the rates of change of CSM and GC predicted end-of-season AGB best. Late in the season, CSM on a given date was the most influential predictor of end-of-season AGB. The power to predict end-of-season AGB was greatest at 50 days after planting, accounting for 63% of variance across this very diverse germplasm collection with modest error (RMSE 1.8 Mg/ha). End-of-season AGB could be predicted equally well when spline fitting was performed on data collected from five flights versus 10 flights over the growing season. This demonstrates a more valuable and efficient approach to using UAVs for HTP, while also proposing strategies to add further value.

54 ENVIRONMENTAL SCIENCES↗

LANDSAT-D thematic mapper image dimensionality reduction and geometric correction accuracy

When principal component analysis of a subscene of a section of the Sacramento River showed lower correlation among the TM spectral components that were observed for the MSS spectral components, principal component analysis was applied to a LANDSAT 2 MSS subscene of the same area for comparison purposes. Correlation coefficient matrices indicate the pairwise similarity and correlation of the data for the spectral components. The principal components transformation matrix, indicates the weights applied to the original components to generate the transformed components. The first two TM components can be described as visible and near infrared. For the MSS data, the first transformed component is roughly the average of the four original components. The second transformed component is roughly the difference between the visible and infrared components. Tables show that 97.0% of the variance in an MSS image is contained in only two transformed components.

Ford, G. E.↗