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At least 1,153 records · Page 64

Research study on stabilization and control: Modern sampled data control theory

A numerical analysis of spacecraft stability parameters was conducted. The analysis is based on a digital approximation by point by point state comparison. The technique used is that of approximating a continuous data system by a sampled data model by comparison of the states of the two systems. Application of the method to the digital redesign of the simplified one axis dynamics of the Skylab is presented.

Kuo, B. C.↗

A thermal control approach for a solar electric propulsion thrust subsystem

A thrust subsystem thermal control design is defined for a Solar Electric Propulsion System (SEPS) proposed for the comet Halley Flyby/comet Tempel 2 rendezvous mission. A 114 node analytic model, developed and coded on the systems improved numerical differencing analyzer program, was employed. A description of the resulting thrust subsystem thermal design is presented as well as a description of the analytic model and comparisons of the predicted temperature profiles for various SEPS thermal configurations that were generated using this model. It was concluded that: (1) a BIMOD engine system thermal design can be autonomous; (2) an independent thrust subsystem thermal design is feasible; (3) the interface module electronics temperatures can be controlled by a passive radiator and supplementary heaters; (4) maintaining heat pipes above the freezing point would require an additional 322 watts of supplementary heating power for the situation where no thrusters are operating; (5) insulation is required around the power processors, and between the interface module and the avionics module, as well as in those areas which may be subjected to solar heating; and (6) insulation behind the heat pipe radiators is not necessary.

Maloy, J. E.↗

Models of four highly obscured compact H II regions

Models are constructed for three stars in order to determine their properties and elemental abundances through comparisons of model predictions and observations. By comparing predicted line fluxes with those observed, it is noted that oxygen is apparently enhanced by a factor of 2 in W3A, and of 4 in G75.84 + 0.40A and G29.9 - 0.0. The first two cases are based on the premise that the O(++)-emitting regions are as clumped as those of S(++). The H II regions all need more than one main sequence star or one unusually large star to provide the observed radio luminosity.

Simpson, J. P.↗

Infrared emission from isolated dust clouds in the presence of very small dust grains

Models of the effects of small grain-generated temperature fluctuations on the IR spectrum and surface brightness of externally heated interstellar dust clouds are presently constructed on the basis of a continuum radiation transport computer code which encompasses the transient heating of small dust grains. The models assume a constant fractional abundance of large and small grains throughout the given cloud. A comparison of model results with IRAS observations indicates that the observed 12-25 micron band emissions are associated with about 10-A radius grains, while the 60-100 micron emission is primarily due to large grains which are heated under the equilibrium conditions.

Lis, Dariusz C.↗

Measurements on the shuttle of the LET spectra of galactic cosmic radiation and comparison with the radiation transport model

A new class of tissue-equivalent proportional counters has been flown on two space shuttle flights. These detectors and their associated electronics cover a lineal energy range from 0.4 to 1250 keV/microns with a multichannel analyzer resolution of 0.1 keV/microns from 0.4 to 20 keV/microns and 5 keV/microns from 20 to 1250 keV/microns. These detectors provide the most complete dynamic range and highest resolution of any technique currently in use. On one mission, one detector was mounted in the Shuttle payload bay and another older model in the mid-deck, thus providing information on the depth dependence of the lineal energy spectrum. A detailed comparison of the observed lineal energy and calculated LET spectra for galactic cosmic radiation shows that, although the radiation transport models provide a rather accurate description of the dose (+/- 15%) and equivalent dose (+/- 15%), the calculations significantly underestimate the frequency of events below about 100 keV/microns. This difference cannot be explained by the inclusion of the contribution of splash protons. The contribution of the secondary pions, kaons and electrons produced in the Shuttle shielding, if included in the radiation transport model, may explain these differences. There are also significant differences between the model predictions and observations above 140 keV/microns, particularly for 28.5 degrees inclination orbit.

NASA Discipline Radiation Health↗

Uncertainty Assessments of 2D and Axisymmetric Hypersonic Shock Wave - Turbulent Boundary Layer Interaction Simulations at Compression Corners

This paper is one of a series of five papers in a special session organized by the NASA Fundamental Aeronautics Program that addresses uncertainty assessments for CFD simulations in hypersonic flow. Simulations of a shock emanating from a compression corner and interacting with a fully developed turbulent boundary layer are evaluated herein. Mission relevant conditions at Mach 7 and Mach 14 are defined for a pre-compression ramp of a scramjet powered vehicle. Three compression angles are defined, the smallest to avoid separation losses and the largest to force a separated flow engaging more complicated flow physics. The Baldwin-Lomax and the Cebeci-Smith algebraic models, the one-equation Spalart-Allmaras model with the Catrix-Aupoix compressibility modification and two-equation models including Menter SST, Wilcox k-omega 98, and Wilcox k-omega 06 turbulence models are evaluated. Each model is fully defined herein to preclude any ambiguity regarding model implementation. Comparisons are made to existing experimental data and Van Driest theory to provide preliminary assessment of model form uncertainty. A set of coarse grained uncertainty metrics are defined to capture essential differences among turbulence models. Except for the inability of algebraic models to converge for some separated flows there is no clearly superior model as judged by these metrics. A preliminary metric for the numerical component of uncertainty in shock-turbulent-boundary-layer interactions at compression corners sufficiently steep to cause separation is defined as 55%. This value is a median of differences with experimental data averaged for peak pressure and heating and for extent of separation captured in new, grid-converged solutions presented here. This value is consistent with existing results in a literature review of hypersonic shock-turbulent-boundary-layer interactions by Roy and Blottner and with more recent computations of MacLean.

Gnoffo, Peter A.↗

Southeast Atmosphere Studies: Learning from Model-Observation Syntheses

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

atmospheric chemistry↗

Comparison of radiative-convective models with constant and pressure-dependent lapse rates

One of the most commonly used models for studying climatic processes is the convective adjustment radiation model. In current radiation models, stable temperature profiles are maintained with a convective adjustment in which the temperature lapse rate is set equal to a critical lapse rate whenever the computed lapse rates exceed the critical value. First introduced by Manabe and Strickler (1964), a variety of convective adjustment models are now in use. It is pointed out that on a global scale, moist adiabatic processes, and thus moist adiabatic lapse rates, approximate the atmospheric temperature profile. Comparisons of profiles from a one-dimensional-radiative-convective model have been made using the conventional 6.5 K/km as the critical lapse rate and the pressure-dependent moist adiabatic lapse rates. For a clear sky and a single effective cloud the surface temperatures are 1 to 3 K higher with the constant 6.5 K/km critical lapse rate.

Hummel, J. R.↗

Incorporation of aerosol into the COSPv2 satellite lidar simulator for climate model evaluation

Abstract. Atmospheric aerosol has substantial impacts on climate, air quality and biogeochemical cycles, and its concentrations are highly variable in space and time. A key variability to evaluate within models that simulate aerosol is the vertical distribution, which influences atmospheric heating profiles and aerosol–cloud interactions, to help constrain aerosol residence time and to better represent the magnitude of simulated impacts. To ensure a consistent comparison between modeled and observed vertical distribution of aerosol, we implemented an aerosol lidar simulator within the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package version 2 (COSPv2). We assessed the attenuated total backscattered (ATB) signal and the backscatter ratios (SRs) at 532 nm in the U.S. Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1). The simulator performs the computations at the same vertical resolution as the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), making use of aerosol optics from the E3SMv1 model as inputs and assuming that aerosol is uniformly distributed horizontally within each model grid box. The simulator applies a cloud masking and an aerosol detection threshold to obtain the ATB and SR profiles that would be observed above clouds by CALIOP with its aerosol detection capability. Our analysis shows that the aerosol distribution simulated at a seasonal timescale is generally in good agreement with observations. Over the Southern Ocean, however, the model does not produce the SR maximum as observed in the real world. Comparison between clear-sky and all-sky SRs shows little differences, indicating that the cloud screening by potentially incorrect model clouds does not affect the mean aerosol signal averaged over a season. This indicates that the differences between observed and simulated SR values are due not to sampling errors, but to deficiencies in the representation of aerosol in models. Finally, we highlight the need for future applications of lidar observations at multiple wavelengths to provide insights into aerosol properties and distribution and their representation in Earth system models.

54 ENVIRONMENTAL SCIENCES↗

Interactions Between the Amazonian Rainforest and Cumuli Clouds: A Large‐Eddy Simulation, High‐Resolution ECMWF, and Observational Intercomparison Study

Abstract The explicit coupling at meter and second scales of vegetation's responses to the atmospheric‐boundary layer dynamics drives a dynamic heterogeneity that influences canopy‐top fluxes and cloud formation. Focusing on a representative day during the Amazonian dry season, we investigate the diurnal cycle of energy, moisture and carbon dioxide at the canopy top, and the transition from clear to cloudy conditions. To this end, we compare results from a large‐eddy simulation technique, a high‐resolution global weather model, and a complete observational data set collected during the GoAmazon14/15 campaign. The overall model‐observation comparisons of radiation and canopy‐top fluxes, turbulence, and cloud dynamics are very satisfactory, with all the modeled variables lying within the standard deviation of the monthly aggregated observations. Our analysis indicates that the timing of the change in the daylight carbon exchange, from a sink to a source, remains uncertain and is probably related to the stomata closure caused by the increase in vapor pressure deficit during the afternoon. We demonstrate quantitatively that heat and moisture transport from the subcloud layer into the cloud layer are misrepresented by the global model, yielding low values of specific humidity and thermal instability above the cloud base. Finally, the numerical simulations and observational data are adequate settings for benchmarking more comprehensive studies of plant responses, microphysics, and radiation.

Vilà‐Guerau de Arellano, J.↗

Monitoring the Caustic Dissolution of Aluminum Alloy in a Radiochemical Hot Cell Using Raman Spectroscopy

Chemical processing of highly radioactive materials commonly takes place in heavily shielded hot cells. The remote, real-time monitoring of chemical processing streams via optical spectroscopic techniques in hot cells may be particularly useful. Here in this paper, we describe the implementation of Raman spectroscopy and chemometric analysis to monitor the dissolution of aluminum-clad targets containing irradiated aluminum–neptunium oxide cermet pellets in caustic solutions in a hot cell environment. Partial least squares regression analysis was used to generate calibration models to quantify the concentration of dissolved aluminum, nitrate, and hydroxide in solutions within the radiochemical hot cell. This work explored a systematic approach to optimize a matrix of calibration standards using a D-optimal experimental design. The Design of Experiments-based regression model, in comparison to more traditional analytical approaches, was found to be the more practical method for building calibration models, with fewer samples, to obtain informative analytical data from Raman spectra.

36 MATERIALS SCIENCE↗

PROcess Based Diagnostics PROBE

Many of the aspects of the climate system that are of the greatest interest (e.g., the sensitivity of the system to external forcings) are emergent properties that arise via the complex interplay between disparate processes. This is also true for climate models most diagnostics are not a function of an isolated portion of source code, but rather are affected by multiple components and procedures. Thus any model-observation mismatch is hard to attribute to any specific piece of code or imperfection in a specific model assumption. An alternative approach is to identify diagnostics that are more closely tied to specific processes -- implying that if a mismatch is found, it should be much easier to identify and address specific algorithmic choices that will improve the simulation. However, this approach requires looking at model output and observational data in a more sophisticated way than the more traditional production of monthly or annual mean quantities. The data must instead be filtered in time and space for examples of the specific process being targeted.We are developing a data analysis environment called PROcess-Based Explorer (PROBE) that seeks to enable efficient and systematic computation of process-based diagnostics on very large sets of data. In this environment, investigators can define arbitrarily complex filters and then seamlessly perform computations in parallel on the filtered output from their model. The same analysis can be performed on additional related data sets (e.g., reanalyses) thereby enabling routine comparisons between model and observational data. PROBE also incorporates workflow technology to automatically update computed diagnostics for subsequent executions of a model. In this presentation, we will discuss the design and current status of PROBE as well as share results from some preliminary use cases.

PROBE↗

An Ecosystem Simulation Model for Methane Production and Emission from Wetlands

Previous experimental studies suggest that methane emission from wetland is influenced by multiple interactive pathways of gas production and transport through soil and sediment layers to the atmosphere. The objective of this study is to evaluate a new simulation model of methane production and emission in wetland soils that was developed initially to help identify key processes that regulate methanogenesis and net flux of CH4 to the air, but which is designed ultimately for regional simulation using remotely sensed inputs for land cover characteristics. The foundation for these computer simulations is based on a well-documented model (CASA) of ecosystem production and carbon cycling in the terrestrial blaspheme. Modifications to represent flooded wetland soils and anaerobic decomposition include three new sub-models for: (1) layered soil temperature and water table depth (WTD) as a function of daily climate drivers, (2) CH4 production within the anoxic soil layer as a function of WTD and CO2 production under poorly drained conditions, and (3) CH4 gaseous transport pathways (molecular diffusion, ebullition, and plant vascular transport) as a function of WTD and ecosystem type. The model was applied and tested using climate and ecological data to characterize tundra wetland sites near Fairbanks, Alaska studied previously by Whalen and Reeburgh. Comparison of model predictions to measurements of soil temperature and thaw depth, water-table depth, and CH4 emissions over a two year period suggest that inter-site differences in soil physical conditions and methane fluxes could be reproduced accurately for selected periods. Day-to-day comparison of predicted emissions to measured CH4 flux rates reveals good agreement during the early part of the thaw season, but the model tends to underestimate production of CH4 during the months of July and August in both test years. Important seasonal effects, including that of falling WTD during these periods, are apparently overlooked in the model formulation. Nevertheless, reasonably close agreement was achieved between the model's mean daily and seasonal estimates of CH4 flux and observed emission rates for northern wetland ecosystems. Several features of the model are identified as crucial to more accurate prediction of wetland methane emission, including the capacity to incorporate influences of localized topographic and hydrologic features on site-specific soil temperature and WTD dynamics, and mechanistic simulation of methane emission transport pathways from within the soil profile.

Potter, C. S.↗

Inhomogeneous models of the Venus clouds containing sulfur

Based on the suggestion that elemental sulfur is responsible for the yellow color of Venus, calculations are compared at 3.4 microns of the reflectivity phase function of two sulfur containing inhomogeneous cloud models with that of a homogeneous model. Assuming reflectivity observations with 25% or less total error, comparison of the model calculations leads to a minimum detectable mass of sulfur equal to 7% of the mass of sulfuric acid for the inhomogeneous drop model. For the inhomogeneous cloud model the comparison leads to a minimum detectable mass of sulfur between 17% and 38% of the mass of the acid drops, depending upon the actual size of the large particles. It is concluded that moderately accurate 3.4 microns reflectivity observations are capable of detecting quite small amounts of elemental sulfur at the top of the Venus clouds.

Smith, S. M.↗

Cold Season QPF: Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

As operational numerical weather prediction is performed at increasingly finer spatial resolution, precipitation traditionally represented by sub-grid scale parameterization schemes is now being calculated explicitly through the use of single- or multi-moment, bulk water microphysics schemes. As computational resources grow, the real-time application of these schemes is becoming available to a broader audience, ranging from national meteorological centers to their component forecast offices. A need for improved quantitative precipitation forecasts has been highlighted by the United States Weather Research Program, which advised that gains in forecasting skill will draw upon improved simulations of clouds and cloud microphysical processes. Investments in space-borne remote sensing have produced the NASA A-Train of polar orbiting satellites, specially equipped to observe and catalog cloud properties. The NASA CloudSat instrument, a recent addition to the A-Train and the first 94 GHz radar system operated in space, provides a unique opportunity to compare observed cloud profiles to their modeled counterparts. Comparisons are available through the use of a radiative transfer model (QuickBeam), which simulates 94 GHz radar returns based on the microphysics of cloudy model profiles and the prescribed characteristics of their constituent hydrometeor classes. CloudSat observations of snowfall are presented for a case in the central United States, with comparisons made to precipitating clouds as simulated by the Weather Research and Forecasting Model and the Goddard single-moment microphysics scheme. An additional forecast cycle is performed with a temperature-based parameterization of the snow distribution slope parameter, with comparisons to CloudSat observations provided through the QuickBeam simulator.

Molthan, A. L.↗

A critical verification of beam and shell models of wind turbine blades

Ever-increasing wind turbine size has challenged predictive capabilities on several fronts. Here, to address part of the blade structural modeling uncertainty, a systematic model fidelity comparison study was conducted on commonly used finite elements. pyNuMAD was utilized to create beam, shell, and solid models of a 100 m long blade undergoing large static deflections. The solid model avoided the use of layered-solid elements by resolving core and facesheet layers. An unprecedented model with 73.7 million elements revealed insights that have never been possible from prior experimental and numerical studies. As compared to the solid element model, the tip deflection from the shell and beam model was found to be about 2% and 4.3% too low, respectively. The twist from the beam model was found to be about 5.6% too high, while the twist from shell model was 24% too low, though improvement was demonstrated with mesh refinement. The beam model adhesive stresses were more accurate than the shell model. Out-of-plane stresses were of great significance near geometric and material discontinuities, and neither the shell nor beam model captured these effects well. Failure predictions from beam, shell, or layered-solid models are unlikely to be reliable at trailing edges, adhesives, ply-drops, spar-cap boundaries.

17 WIND ENERGY↗

Assessing the behavioral realism of energy system models in light of the consumer adoption literature

Effective policymaking to achieve net zero greenhouse gas emissions demands an understanding of the complex drivers of, and barriers to, consumer adoption behavior via behaviorally realistic energy system models. Existing models tend to oversimplify by focusing on homogenized financial factors while neglecting consumer heterogeneity and non-monetary influences. This study develops and applies a comprehensive framework for evaluating the behavioral realism of consumer adoption models, informed by the adoption literature. It introduces a typology for factors influencing low-carbon technology adoption decisions: monetary and non-monetary factors relating to household characteristics, psychology, technological attributes, and contextual conditions. Next, reviews of the consumer adoption and decision-making literature identify the most influential adoption factor categories for distributed solar photovoltaics, electric vehicles, and air-source heat pumps. Finally, the extent to which a selection of energy system models accounts for these adoption factors is assessed. Existing models predominantly emphasize the economic aspects of technology, which are generally identified as the most important factors. Where the models fall short — in considering moderately important factor categories — sector-specific and agent-based models can offer more behaviorally realistic insights. This study sheds light on which types of factors are most important for consumer adoption decisions and investigates how well current models rise to the challenge of behavioral realism. The end-to-end analysis presented enables internally consistent comparisons across models and energy technologies. This research advances timely conversations on consumer adoption. It could inform more behaviorally realistic energy system modeling, and thereby more effective decarbonization policymaking.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Measurement of the angle between jet axes in Pb-Pb collisions at $\sqrt{s_{NN}}$ =5.02 TeV

This paper presents the first measurement of the angle between different jet axes (denoted as Δ⁢𝑅 axis ) in Pb-Pb collisions. The measurement is carried out in the 0–10 % most-central events at $\sqrt{s_{NN}}$ = 5.02 TeV. Jets are assembled by clustering charged particles at midrapidity using the anti-𝑘 T algorithm with resolution parameters 𝑅 = 0.2 and 0.4 and transverse momenta in the intervals 40 < 𝑝$^{ch jet}_{T}$ < 140 GeV/𝑐 and 80 < 𝑝$^{ch jet}_{T}$ < 140 GeV/𝑐, respectively. Measurements at these low transverse momenta enhance the sensitivity to quark-gluon plasma (QGP) effects. A comparison to models implementing various mechanisms of jet energy loss in the QGP suggests that the observed narrowing of the Pb-Pb distribution relative to 𝑝𝑝 can be explained if quark-initiated jets are more likely to emerge from the medium than gluon-initiated jets. These new measurements disfavor intrajet 𝑝 T broadening as implemented in a simple model calculation with the Baier-Dokshitzer-Mueller-Peigne-Schiff formalism for energy loss in the QGP. The comparison of Pb-Pb and 𝑝𝑝 collisions shows sensitivity to the angular scale at which the QGP can resolve two independent splittings, favoring mechanisms that incorporate incoherent energy loss.

Acharya, S. [LPC] (ORCID:0000000292135329)↗