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At least 631 records · Page 35

Spatial Variability of Winds and HRRR–NCEP Model Error Statistics at Three Doppler-Lidar Sites in the Wind-Energy Generation Region of the Columbia River Basin

Annually and seasonally averaged wind profiles from three Doppler lidars were gathered from sites in the Columbia River basin of east-central Oregon and Washington, a major region of wind-energy production, for the Second Wind Forecast Improvement Project (WFIP2) experiment. The profile data are used to quantify the spatial variability of wind flows in this area of complex terrain, to assess the HRRR-NCEP model's ability to capture spatial and temporal variability of wind profiles, and to evaluate model errors. Annually averaged measured wind speed differences over the 70-km extent of the lidar measurements reached 1 m s -1 within the wind-turbine rotor layer, and 2 m s -1 for 200-500 m AGL. Stronger wind speeds in the lowest 500 m occurred at sites higher in elevation, farther from the river, and farther west - closer to the Cascade Mountain barrier. Validating against the lidar data, the HRRR model underestimated strong wind speeds (>12 m s -1 ) and, consequently, their frequency of occurrence, especially at the two lowest-elevation sites, producing annual low biases in rotor-layer wind speed of 0.5 m s -1 . The RMSE between measured and modeled winds at all sites was about 3 m s -1 and did not degrade significantly with forecast lead time. The nature of the model errors was different for different seasons. Furthermore, although the three sites were located in the same basin terrain, the nature of the model errors was different at each site. Thus, if only one of the sites had been instrumented, different conclusions would have been drawn as to the major sources of model error, depending on where the measurements were made.

17 WIND ENERGY↗

Impacts of Light Use Efficiency and fPAR Parameterization on Gross Primary Production Modeling

This study examines the impact of parameterization of two variables, light use efficiency (LUE) and the fraction of absorbed photosynthetically active radiation (fPAR or fAPAR), on gross primary production(GPP) modeling. Carbon sequestration by terrestrial plants is a key factor to a comprehensive under-standing of the carbon budget at global scale. In this context, accurate measurements and estimates of GPP will allow us to achieve improved carbon monitoring and to quantitatively assess impacts from cli-mate changes and human activities. Spaceborne remote sensing observations can provide a variety of land surface parameterizations for modeling photosynthetic activities at various spatial and temporal scales. This study utilizes a simple GPP model based on LUE concept and different land surface parameterizations to evaluate the model and monitor GPP. Two maize-soybean rotation fields in Nebraska, USA and the Bartlett Experimental Forest in New Hampshire, USA were selected for study. Tower-based eddy-covariance carbon exchange and PAR measurements were collected from the FLUXNET Synthesis Dataset. For the model parameterization, we utilized different values of LUE and the fPAR derived from various algorithms. We adapted the approach and parameters from the MODIS MOD17 Biome Properties Look-Up Table (BPLUT) to derive LUE. We also used a site-specific analytic approach with tower-based Net Ecosystem Exchange (NEE) and PAR to estimate maximum potential LUE (LUEmax) to derive LUE. For the fPAR parameter, the MODIS MOD15A2 fPAR product was used. We also utilized fAPAR chl, a parameter accounting for the fAPAR linked to the chlorophyll-containing canopy fraction. fAPAR chl was obtained by inversion of a radiative transfer model, which used the MODIS-based reflectances in bands 1-7 produced by Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. fAPAR chl exhibited seasonal dynamics more similar with the flux tower based GPP than MOD15A2 fPAR, especially in the spring and fall at the agricultural sites. When using the MODIS MOD17-based parameters to estimate LUE, fAPAR chl generated better agreements with GPP (r2= 0.79-0.91) than MOD15A2 fPAR (r2= 0.57-0.84).However, underestimations of GPP were also observed, especially for the crop fields. When applying the site-specific LUE max value to estimate in situ LUE, the magnitude of estimated GPP was closer to in situ GPP; this method produced a slight overestimation for the MOD15A2 fPAR at the Bartlett forest. This study highlights the importance of accurate land surface parameterizations to achieve reliable carbon monitoring capabilities from remote sensing information.

grossprimary↗

History of Thermally Processed Solids in the Protoplanetary Disk: Reconciling Theoretical Models and Meteoritical Evidence

In this talk we assess theoretical models of the radial, temporal, and thermal evolution of nebula solids, and their ultimate accretion into planetesimals such as we see today, using meteorite evidence as a guide. Each class of chondrites contains a characteristic suite of chondrules and CAIs that may have formed over a period of several Myr during which planetesimals were accreting in the disk. Details of the various models for transient melting of chondrules and igneous CAIs will be left to others. However, high-temperature processes of different kinds evaporation, alteration, etc did affect these constituents and their environment over this time span. Here we describe evolutionary scenarios consistent with a large time gap between CAI and chondrule formation and the presence of distinctive suites of chondrules and CAIs in each chondrite class. Particle-gas dynamical processes transport particles of all relevant sizes (microns to many meters) within the nebula and affect their evolution in a variety of important ways. Turbulent radial diffusion spreads particles radially down their concentration gradients - as one example, it can prevent CAIs from being lost into the sun on several Myr timescales [1]. Vertical diffusion spreads the dense midplane particle layer, determining its volume density, which in turn affects the particle growth rate and even the dominant growth process [2-4]. Turbulent concentration selects aerodynamically sorted particles for orders-of-magnitude density enhancement, and is applicable to porous, fluffy particles of appropriate size as well as to solid chondrules [5]. Inward radial drift under gas drag brings a surprisingly large amount of material to regions where it evaporates; these evaporation fronts cause significant chemical modification of the nebula gas over a wide range of radii [6]. Radial transport by stellar winds can be important for small particles [7].

Cuzzi, J. N.↗

Laser-to-hot-electron conversion limitations in relativistic laser matter interactions due to multi-picosecond dynamics

High-energy short-pulse lasers are pushing the limits of plasma-based particle acceleration, x-ray generation, and high-harmonic generation by creating strong electromagnetic fields at the laser focus where electrons are being accelerated to relativistic velocities. Understanding the relativistic electron dynamics is key for an accurate interpretation of measurements. We present a unified and self-consistent modeling approach in quantitative agreement with measurements and differing trends across multiple target types acquired from two separate laser systems, which differ only in their nanosecond to picosecond-scale rising edge. Insights from high-fidelity modeling of laser-plasma interaction demonstrate that the ps-scale, orders of magnitude weaker rising edge of the main pulse measurably alters target evolution and relativistic electron generation compared to idealized pulse shapes. This can lead for instance to the experimentally observed difference between 45 MeV and 75 MeV maximum energy protons for two nominally identical laser shots, due to ps-scale prepulse variations. Our results indicate that the realistic inclusion of temporal laser pulse profiles in modeling efforts is required if predictive capability and extrapolation are sought for future target and laser designs or for other relativistic laser ion acceleration schemes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

SU-E-J-273: Simulation of the Radiation Response of Hypoxic Tumors

Purpose: In radiotherapy, it is important to predict the response of tumour to irradiation prior to the treatment. Mathematical modelling of tumour control probability (TCP) based on the dose distribution, medical imaging and other biological information may help to improve this prediction and to optimize the treatment plan. The aim of this work is to develop an image based 3D multiscale radiobiological model, which describes the growth and the response to radiotherapy of hypoxic tumors. Methods: The computer model is based on voxels, containing tumour, normal (including capillary) and dead cells. Killing of tumour cells due to irradiation is calculated by the Linear Quadratic Model (extended for hypoxia), and the proliferation and resorption of cells are modelled by exponential laws. The initial shape of the tumours is taken from CT images and the initial vascular and cell density information from PET and/or MR images. Including the fractionation regime and the physical dose distribution of the radiation treatment, the model simulates the spatial-temporal evolution of the tumor. Additionally, the dose distribution may be biologically optimized. Results: The model describes the appearance of hypoxia during tumour growth and the reoxygenation processes during radiotherapy. Among other parameters, the TCP is calculated for different dose distributions. The results are in accordance with published results. Conclusion: The simulation model may contribute to the understanding of the influence of biological parameters on tumor response during treatment, and specifically on TCP. It may be used to implement dose-painting approaches. Experimental and clinical validation is needed. This study is supported by a grant from the Ministry of Education of Chile, Programa Mece Educacion Superior (2)

60 APPLIED LIFE SCIENCES↗

Carbon Calculator for Land Use Change from Biofuels Production (CCLUB). Users' Manual and Technical Documentation

The Carbon Calculator for Land Use Change from Biofuels Production (CCLUB) calculates carbon emissions from land use change (LUC) for four different ethanol production pathways including corn grain ethanol and cellulosic ethanol from corn stover, miscanthus, and switchgrass. This document discusses the version of CCLUB released May 31, 2012 which includes corn, as did the previous CCLUB version, and three cellulosic feedstocks: corn stover, miscanthus, and switchgrass. CCLUB calculations are based upon two data sets: land change areas and above- and below-ground carbon content. Table 1 identifies where these data are stored and used within the CCLUB model, which is built in MS Excel. Land change area data is from Purdue University's Global Trade Analysis Project (GTAP) model, a computable general equilibrium (CGE) economic model. Section 2 describes the GTAP data CCLUB uses and how these data were modified to reflect shrubland transitions. Feedstock- and spatially-explicit below-ground carbon content data for the United States were generated with a surrogate model for CENTURY's soil organic carbon sub-model (Kwon and Hudson 2010) as described in Section 3. CENTURY is a soil organic matter model developed by Parton et al. (1987). The previous CCLUB version used more coarse domestic carbon emission factors. Above-ground non-soil carbon content data for forest ecosystems was sourced from the USDA/NCIAS Carbon Online Estimator (COLE) as explained in Section 4. We discuss emission factors used for calculation of international greenhouse gas (GHG) emissions in Section 5. Temporal issues associated with modeling LUC emissions are the topic of Section 6. Finally, in Section 7 we provide a step-by-step guide to using CCLUB and obtaining results.

09 BIOMASS FUELS↗

Generic Argillite/Shale Disposal Reference Case

Radioactive waste disposal in a deep subsurface repository hosted in clay/shale/argillite is a subject of widespread interest given the desirable isolation properties, geochemically reduced conditions, and widespread geologic occurrence of this rock type (Hansen 2010; Bianchi et al. 2013). Bianchi et al. (2013) provides a description of diffusion in a clay-hosted repository based on single-phase flow and full saturation using parametric data from documented studies in Europe (e.g., ANDRA 2005). The predominance of diffusive transport and sorption phenomena in this clay media are key attributes to impede radionuclide mobility making clay rock formations target sites for disposal of high-level radioactive waste. The reports by Hansen et al. (2010) and those from numerous studies in clay-hosted underground research laboratories (URLs) in Belgium, France and Switzerland outline the extensive scientific knowledge obtained to assess long-term clay/shale/argillite repository isolation performance of nuclear waste. In the past several years under the UFDC, various kinds of models have been developed for argillite repository to demonstrate the model capability, understand the spatial and temporal alteration of the repository, and evaluate different scenarios. These models include the coupled Thermal-Hydrological-Mechanical (THM) and Thermal-Hydrological-Mechanical-Chemical (THMC) models (e.g. Liu et al. 2013; Rutqvist et al. 2014a, Zheng et al. 2014a) that focus on THMC processes in the Engineered Barrier System (EBS) bentonite and argillite host hock, the large scale hydrogeologic model (Bianchi et al. 2014) that investigates the hydraulic connection between an emplacement drift and surrounding hydrogeological units, and Disposal Systems Evaluation Framework (DSEF) models (Greenberg et al. 2013) that evaluate thermal evolution in the host rock approximated as a thermal conduction process to facilitate the analysis of design options. However, the assumptions and the properties (parameters) used in these models are different, which not only make inter-model comparisons difficult, but also compromise the applicability of the lessons learned from one model to another model. The establishment of a reference case would therefore be helpful to set up a baseline for model development. A generic salt repository reference case was developed in Freeze et al. (2013) and the generic argillite repository reference case is presented in this report. The definition of a reference case requires the characterization of the waste inventory, waste form, waste package, repository layout, EBS backfill, host rock, and biosphere. This report mainly documents the processes in EBS bentonite and host rock that are potentially important for performance assessment and properties that are needed to describe these processes, with brief description other components such as waste inventory, waste form, waste package, repository layout, aquifer, and biosphere. A thorough description of the generic argillite repository reference case will be given in Jové Colon et al. (2014).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Systems and methods for modeling water quality

A system, method, device and computer-readable medium for creating an ensemble model of water quality. The ensemble model is generated by determining a set of optimal component models for spectral regions of a body of water, and combining the optimal models. The optimal models can be based on remote sensing data, including satellite imagery. A K-fold partition approach or a global approach can be used to determine the optimal component models, and the optimal component models can be combined through spectral space partition rules to generate an ensemble model of water quality. The ensemble model not only has improved water quality prediction ability, but also has strong spatial and temporal extensibility. The spatial and temporal extensibility of the ensemble model is fundamentally important and desirable for long-term and large-scale remote sensing monitoring and assessment of water quality.

Liu, Hongxing↗

Hydrogeologic modeling and the development of preliminary remediation goals for the Guterl Specialty Steel Site, New York - 15431

The Former Guterl Specialty Steel Corporation Site (Guterl Site) is located 32 kilometers (20 miles) northeast of Buffalo, New York, in Lockport, Niagara County, New York. Between 1948 and 1952, up to 15,875 metric tons (35 million pounds) of natural uranium metal (U) were processed at the Guterl Site. The resulting milling dust, shavings, thermal scale, and associated on-site land disposal contaminated both the facility and soils. These combined manufacturing and disposal processes promoted the development of a large-scale uranium plume in the groundwater underlying the site. Site soils are anthropogenic fill and re-worked, glacially-derived sediments that vary between 0.6 meters (m) and 3 meters (2.0 to 10.0 feet [ft]) in thickness. These soils blanket a highly permeable weathered and fractured zone in the upper Lockport Dolostone bedrock. Aerial recharge through the thin soils flushes soluble constituents to groundwater, as exemplified by variations in specific conductivity and groundwater levels in the bedrock during precipitation events. Seasonally higher groundwater levels also promote contact with uranium contamination in deeper soil, thus complicating the transport characteristics of the site (e.g., oxidizing metallic uranium in the soil that increases leach rates). The Seasonal Soil (SESOIL) compartment model was used to simulate a series of site soil conditions and predict the leaching of uranium to groundwater. The SESOIL input included physical soil characteristics, uranium profiles common in five soil areas, climate data, and an assumed oxidation-state (or chemical valence) for metallic uranium in the soil. The iterative modeling process evaluated site-specific variables to achieve a final deterministic set of input that was applied to the five soil areas. The leaching simulations estimated time-dependent influx rates for uranium, which were input to a numerical groundwater flow (MODFLOW) and transport (MT3DMS) model. The combined modeling effort produced spatially and temporally variable transport conditions that were simulated over a 1,000-year period. The leaching models predicted a preliminary remediation goal (PRG) for uranium of 11 milligrams per kilogram (mg/kg) that is protective of groundwater. However, this low uranium PRG has field implementation concerns, so a modified direct-exposure PRG of 70 mg/kg was developed and evaluated in the flow and transport model. The primary difference in the PRGs is the longevity and location of the uranium plume, which will affect the remedial costs and potential stakeholder acceptance. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species–season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds.

59 BASIC BIOLOGICAL SCIENCES↗

Standing waves observed at the dayside magnetopause

Energetic (greater than 24 keV) ion distributions are used in remotely sounding an ion trapping boundary at the dayside magnetopause for two inbound crossings of ISEE-2 on days 347 and 312, 1977, at 0830 and 1100 LT. Applying single particle trajectory models to the observed temporal relationships between trapping boundary distance and orientation parameters, it is concluded that longitudinal standing waves occur on the boundary, having typical wavelengths of 1500-3000 km, amplitudes of 500 km, and periods of 200-400 sec. The standing wave nodes move along the node axis with velocities ranging from 1.5 to 6 km/sec. The data are found to be inconsistent with models of traveling waves moving tailward along the boundary.

Fahnenstiel, S. C.↗

Towards an A-train Aerosol Assimilation System: Assimilation of MODIS Aerosol Optical Thickness Retrievals into a Global Aerosol Transport and Radiation Model

To understand the role of atmospheric aerosols in Earth's climate system we ideally require a global, three-dimensional, and temporally continuous system of measurements. The view of aerosols provided by a single polar-orbiting satellite instrument (e.g., MODIS), while providing the greatest spatial coverage of any measurement system available, can offer only a single relevant observation per day of a particular location. Furthermore, the quantitative interpretation of those observations is subject to considerable uncertainty because of we do not know the aerosol optical properties or vertical profiles well enough. Ground-based and in situ measurements can provide missing detail about aerosol vertical and optical properties, but lack the spatial (and sometimes temporal) coverage desired. Chemical transport models treating the aerosol lifecycle complement this picture by providing three-dimensional, global, and continuous aerosol fields, but suffer from poor constraints on their initial conditions (e.g., the aerosol source, sink, and transformation mechanisms). Here we present a global, three- dimensional aerosol transport model and assimilation system. The model assimilates the MODIS aerosol optical thickness product to constrain its aerosol distributions and burdens. We provide an analysis of the model aerosol distributions as constrained by ground-based sun photometer measurements and aerosol products from other satellite measurements.

Colarco, P.↗

Recovery Act: An Integrated Experimental and Numerical Study: Developing a Reaction Transport Model that Couples Chemical Reactions of Mineral Dissolution/Precipitation with Spatial and Temporal Flow Variations.

A total of 12 publications and 23 abstracts were produced as a result of this study. In particular, the compilation of a thermodynamic database utilizing consistent, current thermodynamic data is a major step toward accurately modeling multi-phase fluid interactions with solids. Existing databases designed for aqueous fluids did not mesh well with existing solid phase databases. Addition of a second liquid phase (CO2) magnifies the inconsistencies between aqueous and solid thermodynamic databases. Overall, the combination of high temperature and pressure lab studies (task 1), using a purpose built apparatus, and solid characterization (task 2), using XRCT and more developed technologies, allowed observation of dissolution and precipitation processes under CO2 reservoir conditions. These observations were combined with results from PIV experiments on multi-phase fluids (task 3) in typical flow path geometries. The results of the tasks 1, 2, and 3 were compiled and integrated into numerical models utilizing Lattice-Boltzmann simulations (task 4) to realistically model the physical processes and were ultimately folded into TOUGH2 code for reservoir scale modeling (task 5). Compilation of the thermodynamic database assisted comparisons to PIV experiments (Task 3) and greatly improved Lattice Boltzmann (Task 4) and TOUGH2 simulations (Task 5). PIV (Task 3) and experimental apparatus (Task 1) have identified problem areas in TOUGHREACT code. Additional lab experiments and coding work has been integrated into an improved numerical modeling code.

15 GEOTHERMAL ENERGY↗

Improved Satellite Retrievals of NO2 and SO2 over the Canadian Oil Sands and Comparisons with Surface Measurements

Satellite remote sensing is increasingly being used to monitor air quality over localized sources such as the Canadian oil sands. Following an initial study, significantly low biases have been identified in current NO2 and SO2 retrieval products from the Ozone Monitoring Instrument (OMI) satellite sensor over this location resulting from a combination of its rapid development and small spatial scale. Air mass factors (AMFs) used to convert line-of-sight "slant" columns to vertical columns were re-calculated for this region based on updated and higher resolution input information including absorber profiles from a regional-scale (15 km × 15 km resolution) air quality model, higher spatial and temporal resolution surface reflectivity, and an improved treatment of snow. The overall impact of these new Environment Canada (EC) AMFs led to substantial increases in the peak NO2 and SO2 average vertical column density (VCD), occurring over an area of intensive surface mining, by factors of 2 and 1.4, respectively, relative to estimates made with previous AMFs. Comparisons are made with long-term averages of NO2 and SO2 (2005-2011) from in situ surface monitors by using the air quality model to map the OMI VCDs to surface concentrations. This new OMI-EC product is able to capture the spatial distribution of the in situ instruments (slopes of 0.65 to 1.0, correlation coefficients of greater than 0.9). The concentration absolute values from surface network observations were in reasonable agreement, with OMI-EC NO2 and SO2 biased low by roughly 30%. Several complications were addressed including correction for the interference effect in the surface NO2 instruments and smoothing and clear-sky biases in the OMI measurements. Overall these results highlight the importance of using input information that accounts for the spatial and temporal variability of the location of interest when performing retrievals.

surface concentration↗

Spatio-Temporal Surrogates for Interaction of a Jet with High Explosives: Part II - Clustering Extremely High-Dimensional Grid-Based Data

Building an accurate surrogate model for the spatio-temporal outputs of a computer simulation is a challenging task. A simple approach to improve the accuracy of the surrogate is to cluster the outputs based on similarity and build a separate surrogate model for each cluster. This clustering is relatively straightforward when the output at each time step is of moderate size. However, when the spatial domain is represented by a large number of grid points, numbering in the millions, the clustering of the data becomes more challenging. In this report, we consider output data from simulations of a jet interacting with high explosives. These data are available on spatial domains of different sizes, at grid points that vary in their spatial coordinates, and in a format that distributes the output across multiple files at each time step of the simulation. We first describe how we bring these data into a consistent format prior to clustering. Borrowing the idea of random projections from data mining, we reduce the dimension of our data by a factor of thousand, making it possible to use the iterative k-means method for clustering. We show how we can use the randomness of both the random projections, and the choice of initial centroids in k-means clustering, to determine the number of clusters in our data set. Our approach makes clustering of extremely high dimensional data tractable, generating meaningful cluster assignments for our problem, despite the approximation introduced in the random projections.

97 MATHEMATICS AND COMPUTING↗

Gas Generator Feedline Orifice Sizing Methodology: Effects of Unsteadiness and Non-Axisymmetric Flow

Engine LH2 and LO2 gas generator feed assemblies were modeled with computational fluid dynamics (CFD) methods at 100% rated power level, using on-center square- and round-edge orifices. The purpose of the orifices is to regulate the flow of fuel and oxidizer to the gas generator, enabling optimal power supply to the turbine and pump assemblies. The unsteady Reynolds-Averaged Navier-Stokes equations were solved on unstructured grids at second-order spatial and temporal accuracy. The LO2 model was validated against published experimental data and semi-empirical relationships for thin-plate orifices over a range of Reynolds numbers. Predictions for the LO2 square- and round-edge orifices precisely match experiment and semi-empirical formulas, despite complex feedline geometry whereby a portion of the flow from the engine main feedlines travels at a right-angle through a smaller-diameter pipe containing the orifice. Predictions for LH2 square- and round-edge orifice designs match experiment and semi-empirical formulas to varying degrees depending on the semi-empirical formula being evaluated. LO2 mass flow rate through the square-edge orifice is predicted to be 25 percent less than the flow rate budgeted in the original engine balance, which was subsequently modified. LH2 mass flow rate through the square-edge orifice is predicted to be 5 percent greater than the flow rate budgeted in the engine balance. Since CFD predictions for LO2 and LH2 square-edge orifice pressure loss coefficients, K, both agree with published data, the equation for K has been used to define a procedure for orifice sizing.

Rothermel, Jeffry↗

Ectomycorrhizal effects on decomposition are highly dependent on fungal traits, climate, and litter properties: A model-based assessment. Dataset.

To simulate the effects of mycorrhizal fungi on soil organic matter cycling, we incorporated mycorrhizal processes into the Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment (CORPSE) model to develop a new soil model Myco-CORPSE. The new model was calibrated and evaluated against soil measurements taken at temperate forests in New Hampshire (NH) and Georgia (GA). A series of scenario analysis were also conducted to explore the conditions under which ectomycorrhizal (ECM) N acquisition processes can induce different soil C accumulation in ECM systems compared to arbuscular (AM) systems.In this data package, we included:-The Python codes of the standard Myco-CORPSE model we developed: "Standard Myco_CORPSE python codes.zip". The main program is the "gradient_sim.py" which calculates the bulk soil microbes and CN content along a user defined gradient of clay, soil temperature, soil moisture and mycorrhizal dominance, and relies on two subprograms "CORPSE_deriv.py" and "CORPSE_integrate.py". "CORPSE_deriv.py" calculated the changes in all simulated soil stock within every time step and "CORPSE_integrate.py" integrate the changes in all simulated soil stock within simulated time period. The program "Plot.py" is used to plot the major outputs produced by the main program "gradient_sim.py".-The modified Python codes of Myco-CORPSE models with site-level environmental inputs (in NH and GA) used to conduct simulations in NH and GA sites: "NH_GA model simulations.zip". -The Python codes used to evaluate the Myco-CORPSE simulation outputs in NH and GA sites against site-level measurements: "Plot NH_GA simulation against measurements.zip". It includes both the evaluation Python code, the model outputs on NH and GA sites, and the measured soil properties in both sites.-The modified Python codes of Myco-CORPSE models "Scenario analysis_model simulations.zip" that is used to conduct scenario analysis of how different litter properties, mycorrhizal fungal traits, climate, and seasonal variation in temperature and vegetation phenology impact the mycorrhizal effects on soil CN properties. The sub file folder "Scenario analysis_litter traits" contains the codes for scenario analysis of different litter properties; The sub file folder "Scenario analysis_ECM types" contains the codes for scenario analysis of different ECM fungal traits; The sub file folder "Scenario analysis_climate&seasonality" contains the codes for scenario analysis of different climate and seasonalities;-"Scenario analysis_model results and plotting codes.zip" contains all the output files from the the scenario analysis of Myco-CORPSE model as described above and the plotting codes used to the generate the heatmaps and scatterplots shown in the manuscript "Ectomycorrhizal effects on decomposition are highly dependent on fungal traits, climate, and litter properties: A model-based assessment"The majority of the model outputs did not have specific geographic information or temporal coverage because the analysis we conducted are mainly hypothetical model simulations. We only provided geographic description, coordinates and temporal coverage for those soil measurements which we used for model evaluations (included in the "Plot NH_GA simulation against measurements.zip").

54 ENVIRONMENTAL SCIENCES↗

HCl in rocket exhaust clouds - Atmospheric dispersion, acid aerosol characteristics, and acid rain deposition

Both measurements and model calculations of the temporal dispersion of peak HCl (g + aq) concentration in Titan III exhaust clouds are found to be well characterized by one-term power-law decay expressions. The respective coefficients and decay exponents, however, are found to vary widely with meteorology. The HCl (g), HCl (g + aq), dewpoint, and temperature-pressure-altitude data for Titan III exhaust clouds are consistent with accurately calculated HCl/H2O vapor-liquid compositions for a model quasi-equilibrated flat surface aqueous aerosol. Some cloud evolution characteristics are also defined. Rapid and extensive condensation of aqueous acid clearly occurs during the first three min of cloud rise. Condensation is found to be intensified by the initial entrainment of relatively moist ambient air from lower levels, that is, from levels below eventual cloud stabilization. It is pointed out that if subsequent dilution air at stabilization altitude is significantly drier, a state of maximum condensation soon occurs, followed by an aerosol evaporation phase.

Pellett, G. L.↗