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At least 739 records · Page 41

All sources NASA NTRS DOE OSTI

DOE OSTI2011

Transient groundwater chemistry near a river: Effects on U(VI) transport in laboratory column experiments

In the 300 Area of a U(VI)-contaminated aquifer at Hanford, Washington, USA, inorganic carbon and major cations, which have large impacts on U(VI) transport, change on an hourly and seasonal basis near the Columbia River. Batch and column experiments were conducted to investigate the factors controlling U(VI) adsorption/desorption by changing chemical conditions over time. Low alkalinity and low Ca concentrations (Columbia River water) enhanced adsorption and reduced aqueous concentrations. Conversely, high alkalinity and high Ca concentrations (Hanford groundwater) reduced adsorption and increased aqueous concentrations of U(VI). An equilibrium surface complexation model calibrated using laboratory batch experiments accounted for the decrease in U(VI) adsorption observed with increasing (bi)carbonate concentrations and other aqueous chemical conditions. In the column experiment, alternating pulses of river and groundwater caused swings in aqueous U(VI) concentration. A multispecies multirate surface complexation reactive transport model simulated most of the major U(VI) changes in two column experiments. The modeling results also indicated that U(VI) transport in the studied sediment could be simulated by using a single kinetic rate without loss of accuracy in the simulations. Moreover, the capability of the model to predict U(VI) transport in Hanford groundwater under transient chemical conditions depends significantly on the knowledge of real-time change of local groundwater chemistry.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Predicting soils and environmental impacts associated with switchgrass for bioenergy production: a DAYCENT modeling approach

Abstract Switchgrass ( Panicum virgatum L.) production has the potential to improve soils and the environment. However, little is known about the long‐term future assessment of soil and environmental impacts associated with switchgrass production. In this study, soil organic carbon (SOC), soil nitrate ( ), water‐filled pore space (WFPS), carbon dioxide (CO 2 ) and nitrous oxide (N 2 O) fluxes, and biomass yield from switchgrass field were predicted using DAYCENT models for 2016 through 2050. Measured data for model calibration and validation at this study site managed with nitrogen fertilization rates (N rates) (low, 0 kg N ha −1 ; medium, 56 kg N ha −1 ; and high, 112 kg N ha −1 ) and landscape positions (shoulder and footslope) for switchgrass production were collected from the previously published studies. Modeling results showed that the N fertilization can enhance SOC and soil NO 3 − , but increase soil N 2 O and CO 2 fluxes. In this study, medium N fertilization was the optimum rate for enhancing switchgrass yield and reducing negative impact on the environment. Footslope position can be beneficial for improving SOC, , and yield, but contribute higher greenhouse gas (GHG) emissions compared to those of the shoulder. An increase in temperature and decrease in precipitation (climate scenarios) may reduce soil , WFPS, and N 2 O flux. Switchgrass production can improve and maintain SOC and , and reduce N 2 O and CO 2 fluxes over the predicted years. These findings indicate that switchgrass could be a sustainable bioenergy crop on marginally yielding lands for improving soils without significant negative impacts on the environment in the long run.

09 BIOMASS FUELS↗

NASA NTRS2003

Modeling and Control of Airport Queueing Dynamics under Severe Flow Restrictions

Based on field observations and interviews with controllers at BOS and EWR, we identify the closure of local departure fixes as the most severe class of airport departure restrictions. A set of simple queueing dynamics and traffic rules are developed to model departure traffic under such restrictions. The validity of the proposed model is tested via Monte Carlo simulation against 10 hours of actual operations data collected during a case-study at EWR on June 29,2000. In general, the model successfully reproduces the aggregate departure congestion. An analysis of the average error over 40 simulation runs indicates that flow-rate restrictions also significantly impact departure traffic; work is underway to capture these effects. Several applications and what-if scenarios are discussed for future evaluation using the calibrated model.

Carr, Francis↗

NASA NTRS2010

Using Leaf Chlorophyll to Parameterize Light-Use-Efficiency Within a Thermal-Based Carbon, Water and Energy Exchange Model

Chlorophylls absorb photosynthetically active radiation and thus function as vital pigments for photosynthesis, which makes leaf chlorophyll content (C(sub ab) useful for monitoring vegetation productivity and an important indicator of the overall plant physiological condition. This study investigates the utility of integrating remotely sensed estimates of C(sub ab) into a thermal-based Two-Source Energy Balance (TSEB) model that estimates land-surface CO2 and energy fluxes using an analytical, light-use-efficiency (LUE) based model of canopy resistance. The LUE model component computes canopy-scale carbon assimilation and transpiration fluxes and incorporates LUE modifications from a nominal (species-dependent) value (LUE(sub n)) in response to short term variations in environmental conditions, However LUE(sub n) may need adjustment on a daily timescale to accommodate changes in plant phenology, physiological condition and nutrient status. Day to day variations in LUE(sub n) were assessed for a heterogeneous corn crop field in Maryland, U,S.A. through model calibration with eddy covariance CO2 flux tower observations. The optimized daily LUE(sub n) values were then compared to estimates of C(sub ab) integrated from gridded maps of chlorophyll content weighted over the tower flux source area. The time continuous maps of daily C(sub ab) over the study field were generated by focusing in-situ measurements with retrievals generated with an integrated radiative transfer modeling tool (accurate to within +/-10%) using at-sensor radiances in green, red and near-infrared wavelengths acquired with an aircraft imaging system. The resultant daily changes in C(sub ab) within the tower flux source area generally correlated well with corresponding changes in daily calibrated LUE(sub n) derived from the tower flux data, and hourly water, energy and carbon flux estimation accuracies from TSEB were significantly improved when using C(sub ab) for delineating spatio-temporal variations in LUE(sub n). The results demonstrate the synergy between thermal infrared and shortwave reflective wavebands in producing valuable remote sensing data for operational monitoring of carbon and water fluxes.

Houlborg, Rasmus↗

DOE OSTI2022

Big Hill Geomechanical Analysis Using M-D Viscoplastic Material Model

The integrity of wellbores at the interbed between the caprock and salt is a serious concern in the Big Hill site. For the remediation and life extension of wellbores, more accurate predictions from the global model are needed. The Big Hill global model is improved using the M-D viscoplastic contact surface model and the mesh containing the interbed layer with contact surfaces between the salt and caprock layers, and fault blocks in overburden and caprock layers. The model calibration has been performed based on the cavern volumetric closures obtained from the Caveman calculations. The results agree well from 1991 to the early 2000s. The difference starts to widen after that, it might be because of frequent fluid movement and raw water injection. Therefore, the predictions from this improved model could be used to examine the structural integrity of caverns in Big Hill salt dome.

42 ENGINEERING↗

NASA NTRS2010

Experiment and Modeling of Simultaneous Creep, Plasticity and Transformation of High Temperature Shape Memory Alloys During Cyclic Actuation

The present work is focused on studying the cycling actuation behavior of HTSMAs undergoing simultaneous creep and transformation. For the thermomechanical testing, a high temperature test setup was assembled on a MTS frame with the capability to test up to temperatures of 600 C. Constant stress thermal cycling tests were conducted to establish the actuation characteristics and the phase diagram for the chosen HTSMA. Additionally, creep tests were conducted at constant stress levels at different test temperatures to characterize the creep behavior of the alloy over the operational range. A thermodynamic constitutive model is developed and extended to take into account a) the effect of multiple thermal cycling on the generation of plastic strains due to transformation (TRIP strains) and b) both primary and secondary creep effects. The model calibration is based on the test results. The creep tests and the uniaxial tests are used to identify the viscoplastic behavior of the material. The parameters for the SMA properties, regarding the transformation and transformation induced plastic strain evolutions, are obtained from the material phase diagram and the thermomechanical tests. The model is validated by predicting the material behavior at different thermomechanical test conditions.

Kumar, Parikshith K.↗

DOE OSTI2016

Impact of High Performance Computing on the Detailed Simulation of Subsurface Flow and Contaminant Transport Using eSTOMP - 16341

The ability to model subsurface processes at the field-scale is essential to site closure and remedial action decisions. Field-scale models often require high-performance computing to meet the computational demands associated with complex systems, model calibration, and uncertainty quantification. eSTOMP, a parallel version of STOMP, is an analytical tool that meets the need for investigating coupled processes in the subsurface involving regional multi-fluid flow and biogeochemistry. The scalability of eSTOMP makes it ideal for simulating contaminant and geochemical reactive transport when long run times result from execution of a serial code. To demonstrate the impact of high-performance computation on subsurface analyses, the application of eSTOMP is presented for two sites. The first site involves uranium surface complexation within a highly dynamic, variably saturated flow field. The use of this model in conjunction with continued field monitoring is expected to provide a rigorous basis for developing operational strategies for field remediation and for defining defensible remediation endpoints. The second site involves the long-term dissolution of low-level radioactive glass emplaced within a near-surface repository. The waste form release rate is evaluated by modeling the basic physical and chemical processes that are known to control the waste form dissolution behavior, including pH and composition of the fluid contacting the glass. Simulations demonstrate that glass dissolution rates vary both in time and as a function of position within the disposal system, and that a 'leach rate' or radionuclide release rate parameter can only be estimated after identifying these impacts in a dynamic system. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Biogeochemistry simulations for the Salt Marsh Accretion Response to Temperature eXperiment (SMARTX)

Coastal ecosystems have been largely ignored in Earth system models but are important zones for carbon and nutrient processing. Interactions between water, microbes, soil, sediments, and vegetation are important for mechanistic representation of coastal processes and ecosystem function. To investigate the role of these feedbacks, we used a reactive transport model (PFLOTRAN) that has the capability to be connected to the Energy Exascale Earth System Model (E3SM). PFLOTRAN was used to incorporate redox reactions and track chemical species important for coastal ecosystems as well as define simple representations of vegetation dynamics. Our goal was to incorporate oxygen flux, salinity, pH, sulfur cycling, and methane production along with plant-mediated transport of gases and tidal flux. Using porewater profile and incubation data for model calibration and evaluation, we were able to create depth-resolved biogeochemical soil profiles for saltmarsh habitat and use this updated representation to simulate direct and indirect effects of elevated CO2 and temperature on subsurface biogeochemical cycling. We found that simply changing the partial pressure of CO2 or increasing temperature in the model did not fully reproduce observed changes in the porewater profile, but the inclusion of plant or microbial responses to CO2 and temperature manipulations was more accurate in representing porewater concentrations. This indicates the importance of characterizing tightly coupled vegetation-subsurface processes for developing predictive understanding and the need for measurement of plant-soil interactions on the same time scale to understand how hotspots or moments are generated.Included in this data package are PFLOTRAN input (PFLOTRAN input files and chemical database) files for simulating single column biogeochemistry, root, and tide interactions at the Global Change Research Wetland (Kirkpatrick Marsh; Edgewater, MD). The biogeochemical network includes soil organic matter decomposition, nitrogen, iron, and sulfur cycling, and methanogenesis. Reduced species can be oxidized and plant processes include oxygen and nutrient priming, methane release, and nutrient uptake.Inputs:TAI_database.dat - geochemical database for reactions, more information on database structure and variables can be found here https://www.pflotran.org/documentation/user_guide/cards/pages/geochemical_database.htmlswamp.in - input file for biogeochemical network in PFLOTRANswamp_eCO2.in - input file for biogeochemical network in PFLOTRAN with input gas partial pressures/concentrations adjusted for elevated CO2 treatmentsOutputs:swamp_obs_0.tec - hourly porewater concentrations from from multiple depths in the soil columnswamp_eCO2_obs_0.tec - hourly porewater concentrations from multiple depths in the soil column for elevated CO2 treatmentsPFLOTRAN code access: https://github.com/fmyuan/pflotran-elm-interface.git

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Sequential Bayesian Experimental Design for Calibration of Expensive Simulation Models

Simulation models of critical systems often have parameters that need to be calibrated using observed data. For expensive simulation models, calibration is done using an emulator of the simulation model built on simulation output at different parameter settings. Using intelligent and adaptive selection of parameters to build the emulator can drastically improve the efficiency of the calibration process. The article proposes a sequential framework with a novel criterion for parameter selection that targets learning the posterior density of the parameters. The emergent behavior from this criterion is that exploration happens by selecting parameters in uncertain posterior regions while simultaneously exploitation happens by selecting parameters in regions of high posterior density. Furthermore, the advantages of the proposed method are illustrated using several simulation experiments and a nuclear physics reaction model.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

CALIBRATING STELLAR POPULATION MODELS WITH MAGELLANIC CLOUD STAR CLUSTERS

Stellar population models are commonly calculated using star clusters as calibrators for those evolutionary stages that depend on free parameters. However, discrepancies exist among different models, even if similar sets of calibration clusters are used. With the aim of understanding these discrepancies, and of improving the calibration procedure, we consider a set of 43 Magellanic Cloud (MC) clusters, taking age and photometric information from the literature. We carefully assign ages to each cluster based on up-to-date determinations, ensuring that these are as homogeneous as possible. To cope with statistical fluctuations, we stack the clusters in five age bins, deriving for each of them integrated luminosities and colors. We find that clusters become abruptly red in optical and optical-infrared colors as they age from {approx}0.6 to {approx}1 Gyr, which we interpret as due to the development of a well-populated thermally pulsing asymptotic giant branch (TP-AGB). We argue that other studies missed this detection because of coarser age binnings. Maraston and Girardi et al. models predict the presence of a populated TP-AGB at {approx}0.6 Gyr, with a correspondingly very red integrated color, at variance with the data; Bruzual and Charlot and Conroy models run within the error bars at all ages. The discrepancy between the synthetic colors of Maraston models and the average colors of MC clusters results from the now obsolete age scale adopted. Finally, our finding that the TP-AGB phase appears to develop between {approx}0.6 and 1 Gyr is dependent on the adopted age scale for the clusters and may have important implications for stellar evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Developing a Redox Network for Coastal Saltmarsh Systems in the PFLOTRAN Reaction Model

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Special Analysis: Impact of Updated GSA Flow Model on E-Area Low-Level Waste Facility Groundwater Performance

In March 2018, the Savannah River National Laboratory (SRNL) notified Solid Waste Management (SWM) of new information that could potentially impact groundwater (GW) disposal limits and possibly require temporary protective measures (Crowley 2018). GW flow directions in the E-Area Low-Level Waste Facility (LLWF) Slit Trenches (STs), Engineered Trenches (ETs), and the Low Activity Waste Vault (LAWV) have notably changed in the new 2018 General Separations Area (GSA) flow model (Flach 2018a). The 2018 GSA flow model had been updated using 20 years of new hydrologic field data and model calibration methods that employed mathematical optimization software. It was later determined that the primary reason for the change in GW flow directions was due to the influence of low permeability caps that had been placed over the Old Burial Grounds and the Low Level Radioactive Waste Disposal Facility (LLRWDF). Updated flow directions in the model produce a higher degree of plume overlap for disposal units (DU’s) in the southeastern portion of E-Area than had been predicted in the 2008 E-Area LLWF Performance Assessment (PA). SWM and SRNL outlined the scope for this Special Analysis (SA) and proposed a set of interim measures (IM’s) to protect trench operations from exceeding Performance Objectives (PO’s) during the preparation of this SA, both of which were approved by the SWM Performance Assessment Review Committee (PARC) (Mooneyhan 2018).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2007

NASA Shuttle Orbiter Reinforced Carbon Carbon (RCC) Crack Repair Arc-Jet Testing

This NASA study demonstrates the capability for testing NOAX-repaired RCC crack models in high temperature environments representative of Shuttle Orbiter during reentry. Analysis methods have provided correlation of test data with flight predictions. NOAX repair material for RCC is flown on every STS flight in the event such a repair is needed. Two final test reports are being generated on arc-jet results (both calibration model runs and repaired models runs).

Clark, ShawnDella↗

DOE OSTI2014

Dynamical model for the toroidal sporadic meteors

More than a decade of radar operations by the Canadian Meteor Orbit Radar have allowed both young and moderately old streams to be distinguished from the dispersed sporadic background component. The latter has been categorized according to broad radiant regions visible to Earth-based observers into three broad classes: the helion and anti-helion source, the north and south apex sources, and the north and south toroidal sources (and a related arc structure). The first two are populated mainly by dust released from Jupiter-family comets and new comets. Proper modeling of the toroidal sources has not to date been accomplished. Here, we develop a steady-state model for the toroidal source of the sporadic meteoroid complex, compare our model with the available radar measurements, and investigate a contribution of dust particles from our model to the whole population of sporadic meteoroids. We find that the long-term stable part of the toroidal particles is mainly fed by dust released by Halley type (long period) comets (HTCs). Our synthetic model reproduces most of the observed features of the toroidal particles, including the most troublesome low-eccentricity component, which is due to a combination of two effects: particles' ability to decouple from Jupiter and circularize by the Poynting-Robertson effect, and large collision probability for orbits similar to that of the Earth. Our calibrated model also allows us to estimate the total mass of the HTC-released dust in space and check the flux necessary to maintain the cloud in a steady state.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2010

Error handling strategies in multiphase inverse modeling

Parameter estimation by inverse modeling involves the repeated evaluation of a function of residuals. These residuals represent both errors in the model and errors in the data. In practical applications of inverse modeling of multiphase flow and transport, the error structure of the final residuals often significantly deviates from the statistical assumptions that underlie standard maximum likelihood estimation using the least-squares method. Large random or systematic errors are likely to lead to convergence problems, biased parameter estimates, misleading uncertainty measures, or poor predictive capabilities of the calibrated model. The multiphase inverse modeling code iTOUGH2 supports strategies that identify and mitigate the impact of systematic or non-normal error structures. We discuss these approaches and provide an overview of the error handling features implemented in iTOUGH2.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Leveraging High-resolution Molecular Composition of Soil Organic Matter to Enhance Carbon Cycling Modeling

Soils store more carbon than the atmosphere and vegetation combined, yet Earth system models still struggle to predict how this vast reservoir will respond to environmental change. A central limitation is that most soil biogeochemical models represent organic matter using bulk conceptual pools or chemically homogeneous fractions, preventing direct use of rapidly expanding molecular-scale datasets. Here we develop and test a new soil decomposition framework that explicitly integrates high-resolution information on organic matter composition. First, we construct a molecularly informed litter decomposition module in which plant inputs are partitioned into five functional compound classes—carbohydrates, proteins, lignin-like aromatics, lipids, and carbonyls—using a molecular mixing model calibrated to solid-state 13 C Nuclear Magnetic Resonance (NMR) spectra. Class-specific kinetics, lignin-dependent physical protection, and substrate-driven microbial carbon use efficiency allow the module to capture metabolic tradeoffs associated with enzyme production and nutrient limitation. We then embed this litter module within a microbially explicit whole-soil model that tracks the transformation of these compound classes through particulate organic matter, dissolved organic matter, mineral-associated organic matter, and microbial biomass. High-resolution Fourier Transform Ion Cyclotron Resonance mass spectrometry (FTICR-MS) data are used to link internal pools to measurable soil organic matter fractions and to constrain key process parameters. Applications at soil-core and ecosystem scales demonstrate that the new model reproduces observed soil respiration dynamics while providing mechanistic attribution of CO 2 fluxes to specific chemical classes and pools. Compared to existing frameworks such as the Community Land Model soil biogeochemistry module and the Millennial model, our approach maintains competitive predictive skill while substantially improving interpretability and opportunities for data–model integration. This work illustrates a viable pathway for leveraging molecular-scale observations to reduce structural uncertainty in soil carbon–climate feedback projections.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Solidification dynamics in metal additive manufacturing: analysis of model assumptions

Solidification characteristics in the meltpool drive the process-microstructure relationship which helps dictate the material properties of as-built parts in additive manufacturing; therefore, being able to accurately and quickly simulate the size, shape, and solidification characteristics in the melt pool is of great interest to the field. In this study, we investigate various important physical phenomena (dynamic material properties, fluid-flow, radiation and vaporization) which can either be included or neglected in a continuum finite volume model (FVM) and their effect on the solidification conditions. Additionally, since the simplest form of such a model (conduction only) has an analytic solution which is much faster, its viability is also considered. Since the inclusion of some of these physical phenomena will inherently change the net energy input as well as the amount of energy needed to achieve melting of a control volume, each set of included phenomena had an effective absorption efficiency which was calibrated to closely match the dimensions of the melt pool to that of the ground truth data. The ground truth data for this study was defined to be the output of the FVM which included all the physical phenomena (OF). This study then goes on to compare the effects on solidification conditions each of these calibrated models has. It was found that most of the change in solidification conditions comes from the inclusion of latent heat. A posterior correlation factor (PCF) is then introduced to enable an analytic model to predict similar solidification conditions to OF model.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Inversion for Eigenvalues and Modes Using Sierra-SD and ROL.

In this report we formulate eigenvalue-based methods for model calibration using a PDE-constrained optimization framework. We derive the abstract optimization operators from first principles and implement these methods using Sierra-SD and the Rapid Optimization Library (ROL). To demon- strate this approach, we use experimental measurements and an inverse solution to compute the joint and elastic foam properties of a low-fidelity unit (LFU) model.

42 ENGINEERING↗