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At least 1,405 records · Page 78

Artificial intelligence-based predictive modeling for imaging neutral particle analyzers on the DIII-D tokamak

The Imaging Neutral Particle Analyzer (INPA) at DIII-D is a diagnostic system used to accurately resolve the energy and spatial distributions of fast ions in fusion plasmas. A novel artificial intelligence (AI) technique named INPA-net is based on Reservoir Computing Networks and developed here to predict active and passive signals produced by charge-exchange reactions from injected and edge-cold neutrals, respectively, in magnetically confined fusion plasmas. This model is trained using a set of 21 time domain signals between 0 s to 3.35 s that includes injected beam and thermal plasma information, and 6444 real 2D experimental images of the INPA in 12 plasma discharges at DIII-D. The trained neural network is able to forecast experimental images in real-time. The model achieves an R-squared value of 0.91, which is higher than the 0.83 value achieved by a simple linear regression model. This improvement highlights the model's enhanced predictive accuracy for measured images from the validation set. This AI approach is valuable due to its rapid response times and potential for integration into real-time plasma control systems. A version of this model capable of generating syntehic images would be useful for the real-time monitoring of fast-ion transport. A comprehensive sensitivity study reveals that INPA-net maintains high performance even with variations in the input parameters, indicating the model's robustness and reliability. While developed for the INPA, the underlying architecture is adaptable and may be applied to various 2D imaging diagnostics in fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Q 10 of in situ microbial soil respiration varies with mean annual temperature, precipitation, pH, and plant cover: a meta-analysis and spatial prediction of Q 10

The temperature sensitivity of soil microbial respiration, commonly quantified using the Q 10 coefficient, is a key parameter in carbon cycle models. Uncovering how environmental factors affect in situ Q 10 values can therefore provide critical insight into potential shifts in global carbon stocks under climate change. We collected data from previously published field experiments that measured soil microbial respiration across a range of temperatures. We hypothesized that the Q 10 coefficient of in situ soil microbial respiration would vary based on environmental factors including mean annual temperature (MAT), mean annual precipitation (MAP), plant cover type, pH, soil C:N, and latitude. Linear regression revealed that Q 10 correlates negatively with MAT and MAP and positively with pH and absolute latitude. Additionally, average Q 10 varied significantly across different plant cover types; it was highest in mountain grasslands and lowest in tropical moist forests. Variation in microbial Q 10 across environmental factors may arise from underlying mechanisms such as enzyme kinetics, substrate availability and complexity, and microbial adaptation. To capture patterns in Q 10 more comprehensively, we developed a multiple linear regression model of Q 10 based on the most individually significant environmental drivers and applied it to public datasets to generate a global map of predicted Q 10 . Q 10 was higher in high-latitude and high-altitude regions, where large permafrost carbon stores are vulnerable to thawing and decomposition. We also compared fits between the Q 10 equation and a model produced from macromolecular rate theory (MMRT). We found that the MMRT model had the superior fit and may be better suited to model temperature sensitivity of complex biological reactions. Overall, our results emphasize that relationships between microbial Q 10 and environmental variables should be accounted for in climate models. Incorporating these variations in the Q 10 parameter, rather than using a fixed value, will help predict whether CO 2 emissions will be buffered or exacerbated by soil microbial respiration under climate change.

54 ENVIRONMENTAL SCIENCES↗

Innovative use of Cr(VI) plume depictions and pump-and-treat capture analysis to estimate risks of contaminant discharge to surface water at Hanford reactor areas - 15315

The Hanford Site nuclear reactor operations required large quantities of high-quality cooling water, which was treated with chemicals including sodium dichromate dihydrate for corrosion control. Cooling water leakage, as well as intentional discharge of cooling water to ground during upset conditions, produced extensive groundwater recharge mounds consisting largely of contaminated cooling water and resulted in wide distribution of hexavalent chromium (Cr[VI]) contamination in the unconfined aquifer. The 2013 Cr(VI) groundwater plumes in the 100 Areas cover approximately 6 km{sup 2} (1500 acres), primarily in the 100-HR-3 and 100-KR-4 groundwater operable units (OUs). The Columbia River is a groundwater discharge boundary; where the plumes are adjacent to the Columbia River there remains a potential to discharge Cr(VI) to the river at concentrations above water quality criteria. The pump-and-treat systems along the River Corridor are operating with two main goals: 1) protection of the Columbia River, and 2) recovery of contaminant mass. An evaluation of the effectiveness of the pump-and-treat systems was needed to determine if the Columbia River was protected from contamination, and also to determine where additional system modifications may be needed. In response to this need, a technique for assessing the river protection was developed which takes into consideration seasonal migration of the plume and hydraulic performance of the operating well fields. Groundwater contaminant plume maps are generated across the Hanford Site on an annual basis. The assessment technique overlays the annual plume and the capture efficiency maps for the various pump and treat systems. The river protection analysis technique was prepared for use at the Hanford site and is described in detail in M.J. Tonkin, 2013. Interpolated capture frequency maps, based on mapping dynamic water level observed in observation wells and derived water levels in the vicinity of extraction and injection wells, are developed initially. Second, simulated capture frequency maps are developed, based on transport modelling results. Both interpolated and simulated capture frequency maps are based on operation of the systems over a full year. These two capture maps are then overlaid on the plume distribution maps for inspection of the relative orientation of the contaminant plumes with the capture frequency. To quantify the relative degree of protection of the river from discharges of Cr(VI) (and conversely, the degree of threat) at any particular location, a systematic method of evaluating and mapping the plume/capture relationship was developed. By comparing the spatial relationship between contaminant plumes and hydraulic capture frequency, an index of relative protectiveness is developed and the results posted on the combined plume/capture plan view map. Areas exhibiting lesser degrees of river protection are identified for remedial process optimization actions to control plumes and prevent continuing discharge of Cr(VI) to the river. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Feasibility of FDEM cross-dipole and TDEM loop sources for monitoring CO 2 at the Kemper CarbonSAFE site

Electromagnetics has been shown to be a viable tool to monitor CO 2 plumes embedded in saline reservoirs. However, the majority of studies focus on measuring the electric field, which requires cumbersome equipment in the field and it is difficult to install permanent measurement stations. Magnetic field receivers offer an opportunity to reduce the form factor of the survey and increase the mobility by utilizing upcoming technologies, such as drones. We explore the use of frequency-domain electric dipole sources, and timedomain loops with a focus on measuring the secondary magnetic field at the surface for a conceptual injection scenario based on the Kemper CarbonSAFE site. We find that electric dipole sources give a response above the sensitivity of current sensor technology and, therefore, be a viable tool for CO 2 monitoring. The time domain loop source does provide fields that are useful for determining the location of the CO 2 plume, however the field magnitude is below the sensitivity of the current generation of instruments. To explore the use of a potential borehole receiver we generate a map of the magnetic field at depth to explore potential borehole placement for monitoring efforts. Finally, we limit the spatial extent of the electric dipole survey to a single parcel of land to help understand how the fields change with survey geometry. We find that the shape of the secondary fields change slightly with the small transmitter, but are still measurable provided that the cultural noise at the site is low. Thus, we conclude that at the Kemper site a frequency-domain cross-dipole source with magnetometer receivers is suitable to monitor the expansion of the CO 2 plume in the saline reservoir, even with a limited transmitter footprint on the surface.

58 GEOSCIENCES↗

Alternating Direction Decomposition with Strong Bounding and Convexification (ADDSBC) for Solving Security Constrained AC Unit Commitment Problems

This project aims to develop efficient and robust computational methods for solving the security-constrained unit commitment and alternating current optimal power flow problem (SC-UC-ACOPF). The SC-UC-ACOPF problem is at the center of the short-term operation of the U.S. Power Grid. It is solved every week, every day, and every 10 minutes to plan for the optimal action of electricity generation and consumption by minimizing the generation cost and maintaining power system reliability against potential disruptions of equipment failures. In mathematical terms, SC-UC-ACOPF is a challenging large-scale mixed-integer nonlinear optimization model. This means that the decisions involve both discrete variables, e.g. the turning on and off of generators and switching of transmission lines and transformers, and continuous decisions, e.g. the amount of energy generated by each generator and the power flows in the power grid. The physics of the power flow is described by nonlinear equations involving real and reactive power and bus voltages. Another key feature is the large number of contingencies, i.e. the system needs to stay reliable in face of failure of any one equipment, such as transmission lines and generators. The U.S. power grids are extremely complicated and large scale with more than 5,000 generators, 50,000 buses, and 100,000 high-voltage transmission lines, making the SC-UC-ACOPF a very large-scale computation challenge. The research developed in this project aims to solve the SC-UC-ACOPF problems in the three timescales, i.e. weekly, daily, and every 10-min. The proposed computational methods are built on a principled algorithmic approach of decomposition and penalization. More specifically, the algorithm develops spatial and temporal decomposition by exploiting the strong temporal coupling and weak spatial coupling of the UC problem and the complementary feature, i.e. weak temporal coupling and strong spatial coupling of the ACOPF problem. The algorithm also leverages recent progresses in strong convex relaxation of ACOPF. A unique feature of the proposed approach is that it generates a valid, global upper bound on the optimal maximum profit. In this way, a global optimality gap is available to measure the quality of the solution. To further speed up computation, the research team has developed a plethora of effective heuristics to strengthen the iterative penalty-based decomposition framework. For instance, a heuristic is developed to construct inner approximations of the time coupling constraints within the time decoupled problems. Contingencies are pre-screened and low-rank matrix computation is exploited to find the almost unique solution to each contingency. A novel heuristic for line switching is proposed and tested with positive impacts on instances where line switching is beneficial. Taking a systematic approach and carefully handling every detail of the problem pays off. The TIM-GO’s performance throughout the trials and the final event was stellar. TIM-GO garnered the second highest total prize money and is ranked in the top three positions across all categories of comparison.

97 MATHEMATICS AND COMPUTING↗

STEADY STATE MODELING OF THE MINIMUM CRITICAL CORE OF THE TRANSIENT REACTOR TEST FACILITY

With the advent of next generation reactor systems and new fuel designs, the U.S. Department of Energy (DOE) has identified the need for the resumption of transient testing of nuclear fuels. The DOE has decided that the Transient Reactor Test Facility (TREAT) at Idaho National Laboratory (INL) is best suited for future testing. TREAT is a thermal neutron spectrum, air-cooled, nuclear test facility that is designed to test nuclear fuels in transient scenarios. These specific scenarios range from simple temperature transients to full fuel melt accidents. DOE has expressed a desire to develop a simulation capability that will accurately model the experiments before they are irradiated at the facility. It is the aim for this capability to have an emphasis on effective and safe operation while minimizing experimental time and cost. The multi physics platform MOOSE has been selected as the framework for this project. The goals for this work are to identify the fundamental neutronics properties of TREAT and to develop an accurate steady state model for future multiphysics transient simulations. In order to minimize computational cost, the effect of spatial homogenization and angular discretization are investigated. It was found that significant anisotropy is present in TREAT assemblies and to capture this effect, explicit modeling of cooling channels and inter-element gaps is necessary. For this modeling scheme, single element calculations at 293 K gave power distributions with a root mean square difference of 0.076% from those of reference SERPENT calculations. The minimum critical core configuration with identical gap and channel treatment at 293 K resulted in a root mean square, total core, radial power distribution 2.423% different than those of reference SERPENT solutions.

Critical↗

A Numerical Tool for the Design of Enhanced Geothermal Reservoirs based on Modeling of Thermo-Hydro-Mechanical Processes and Explicit Representation of 3D Discrete Fracture Networks

This project has developed a coupled thermo-hydro-mechanical numerical modeling tool for prediction of energy production from Enhanced Geothermal Reservoirs (EGS). The tool is unique because it can explicitly represent thousands of pre-existing natural fractures. The capabilities developed in this project were built on the already existing expertise of Itasca arising from thirty years of research and development in discrete element modeling of fractured rocks. A thermal module suitable for analysis of different heat transfer mechanisms in fractured rocks percolated by fluids was developed and coupled with the already existing hydro-mechanical calculation in 3DEC, a commercial software for analysis of jointed rock based on the discrete element method (DEM). The heat transfer module simulates heat conduction, heat advection by moving fluid in rock fractures, and convective heat exchange at the fracture walls between the rock and the moving fluid. Techniques for spatial discretization of heat transfer in EGS-type problems were evaluated, and a boundary layer meshing approach was developed. Also, given the significant differences in time scale of physical processes involved, temporal integration schemes for coupled advection-diffusion processes and coupled thermal-hydro-mechanical processes were developed by taking advantage of both implicit and explicit time integration and also optimizing the coupling intervals. These improvements were necessary for modeling EGS reservoirs. Also, the DFN capacities in 3DEC were extended to include a larger number of fractures. Research was carried out on approaches to simplify the DFN so that the model can meet computational demands, while preserving thermo-hydro-mechanical characteristics of the DFN. The developed modules were coupled with the already existing capabilities of 3DEC. The results were presented as a submitted conference paper (Riahi et al., 2018a). A series of benchmark and test examples showed the developed capabilities. Finally, the developed tool was tested for a large-scale reservoir model for longer periods of injection and production. The thermal draw-down curves were generated and presented. The project successfully met all the milestones laid out in the proposal. Results demonstrated the feasibility of developing a fast and reliable software for the EGS community to use for assessment and prediction of reservoir performance. Some of its applications include assessment of stimulated volume and produced temperature and power. It can also be used for improved engineering, design and optimization of EGS reservoirs as well as other unconventional resources such as shale gas. Finally, the 3D analysis presented in this study showed that simulating EGS reservoirs with tens of thousands of fractures is feasible, and confirmed that the developed tool can serve toward meeting the goals and objectives of Geothermal Technologies Office in overcoming technical barriers associated with commercial EGS development.

15 GEOTHERMAL ENERGY↗

INTERSTELLAR PICKUP ION ACCELERATION IN THE TURBULENT MAGNETIC FIELD AT THE SOLAR WIND TERMINATION SHOCK USING A FOCUSED TRANSPORT APPROACH

We study the physics of locally born interstellar pickup proton acceleration at the nearly perpendicular solar wind termination shock (SWTS) in the presence of a random magnetic field spiral angle using a focused transport model. Guided by Voyager 2 observations, the spiral angle is modeled with a q -Gaussian distribution. The spiral angle fluctuations, which are used to generate the perpendicular diffusion of pickup protons across the SWTS, play a key role in enabling efficient injection and rapid diffusive shock acceleration (DSA) when these particles follow field lines. Our simulations suggest that variation of both the shape ( q -value) and the standard deviation ( σ -value) of the q -Gaussian distribution significantly affect the injection speed, pitch-angle anisotropy, radial distribution, and the efficiency of the DSA of pickup protons at the SWTS. For example, increasing q and especially reducing σ enhances the DSA rate.

79 ASTRONOMY AND ASTROPHYSICS↗

Simulating the absorption spectra of helium clusters (N = 70, 150, 231, 300) using a charge transfer correction to superposition of fragment single excitations

Simulations of the n = 2 absorption spectra of HeN(N = 70, 150, 231, 300) clusters are reported, with nuclear configurations sampled by path integral molecular dynamics. The electronic structure is treated by a new approach, ALMO-CIS+CT, which is a formulation of configuration interaction singles (CIS) based on absolutely localized molecular orbitals (ALMOs). The method generalizes the previously reported ALMO-CIS model [K. D. Closser et al. J. Chem. Theory Comput. 11, 5791 (2015)] to include spatially localized charge transfer (CT) effects. It is designed to recover large numbers of excited states in atomic and molecular clusters, such as the entire n = 2 Rydberg band in helium clusters. ALMO-CIS+CT is shown to recover most of the error caused by neglecting charge transfer in ALMO-CIS and has comparable accuracy to standard CIS for helium clusters. For the n = 2 band, CT stabilizes states towards the blue edge by up to 0.5 eV. ALMO-CIS+CT retains the formal cubic scaling of ALMO-CIS with respect to system size. With improvements to the implementation over that originally reported for ALMO-CIS, ALMO-CIS+CT is able to treat helium clusters with hundreds of atoms using modest computing resources. Here, a detailed simulation of the absorption spectra associated with the 2s and 2p bands of helium clusters up to 300 atoms is reported, using path integral molecular dynamics with a spherical boundary condition to generate atomic configurations at 3 K. The main features of experimentally reported fluorescence excitation spectra for helium clusters are reproduced.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TH-AB-209-07: High Resolution X-Ray-Induced Acoustic Computed Tomography

Purpose: X-ray radiographic absorption imaging is an invaluable tool in medical diagnostics, biology and materials science. However, the use of conventional CT is limited by two factors: the detection sensitivity to weak absorption material and the radiation dose from CT scanning. The purpose of this study is to explore X-ray induced acoustic computed tomography (XACT), a new imaging modality, which combines X-ray absorption contrast and high ultrasonic resolution to address these challenges. Methods: First, theoretical models was built to analyze the XACT sensitivity to X-ray absorption and calculate the minimal radiation dose in XACT imaging. Then, an XACT system comprised of an ultrashort X-ray pulse, a low noise ultrasound detector and a signal acquisition system was built to evaluate the X-ray induced acoustic signal generation. A piece of chicken bone and a phantom with two golden fiducial markers were exposed to 270 kVp X-ray source with 60 ns exposure time, and the X-ray induced acoustic signal was received by a 2.25MHz ultrasound transducer in 200 positions. XACT images were reconstructed by a filtered back-projection algorithm. Results: The theoretical analysis shows that X-ray induced acoustic signals have 100% relative sensitivity to X-ray absorption, but not to X-ray scattering. Applying this innovative technology to breast imaging, we can reduce radiation dose by a factor of 50 compared with newly FDA approved breast CT. The reconstructed images of chicken bone and golden fiducial marker phantom reveal that the spatial resolution of the built XACT system is 350µm. Conclusion: In XACT, the imaging sensitivity to X-ray absorption is improved and the imaging dose is dramatically reduced by using ultrashort pulsed X-ray. Taking advantage of the high ultrasonic resolution, we can also perform 3D imaging with a single X-ray pulse. This new modality has the potential to revolutionize x-ray imaging applications in medicine and biology.

60 APPLIED LIFE SCIENCES↗

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

Abstract This data plan outlines the structure and content of datasets generated and utilized in the research presented in the manuscript abstract. Groundwater overdraft has led to serious water supply issues in the US West. Most western states manage groundwater use through a permitting system, but California has only recently begun to restrict groundwater use statewide with the 2014 passage of groundwater restrictions which target the elimination of groundwater overdraft practices by 2042. With groundwater extraction curtailed, crop production in the US West (a $95 billion industry annually) will be affected, and appropriate response strategies will be needed to ensure minimal disruption to food production and the regional economy. In this paper, we explore the adoption of alternative adaptive responses: (a) deficit irrigation; (b) switching to less water-intensive crops; (c) changing the extent of irrigated land (including fallowing); and (d) geographically shifting crop production. Employing an integrated modeling approach, we explicitly capture the interactions and feedbacks between local hydrology, changes in crop yields, crop and land use decision-making, changes in crop prices, and regional shifts in crop production. We find that the optimal adaptive response is spatially heterogeneous and comprises a portfolio of strategies. Southwestern states and California will be the most impacted by groundwater restrictions. The optimal responses in these states are to both adopt deficit irrigation strategies and reduce a portion of their irrigated croplands, resulting in a shift in crop production to northwestern states with a larger supply of water. The datasets detailed in this repository represent the output from these integrated models, specifically designed to support the analysis and visualization presented in the manuscript and supplemental information. These datasets, used in conjunction with the scripts available at our associated GitHub repository (https://github.com/pches/Femeena_etal_How_can_crop_production_adapt), enable the reproduction of figures and facilitate a comprehensive understanding of the optimal adaptive strategies in agriculture for mitigating water stress under varying groundwater extraction scenarios, as outlined in the abstract.

DNDCe↗

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

Abstract This data plan outlines the structure and content of datasets generated and utilized in the research presented in the manuscript abstract. Groundwater overdraft has led to serious water supply issues in the US West. Most western states manage groundwater use through a permitting system, but California has only recently begun to restrict groundwater use statewide with the 2014 passage of groundwater restrictions which target the elimination of groundwater overdraft practices by 2042. With groundwater extraction curtailed, crop production in the US West (a $95 billion industry annually) will be affected, and appropriate response strategies will be needed to ensure minimal disruption to food production and the regional economy. In this paper, we explore the adoption of alternative adaptive responses: (a) deficit irrigation; (b) switching to less water-intensive crops; (c) changing the extent of irrigated land (including fallowing); and (d) geographically shifting crop production. Employing an integrated modeling approach, we explicitly capture the interactions and feedbacks between local hydrology, changes in crop yields, crop and land use decision-making, changes in crop prices, and regional shifts in crop production. We find that the optimal adaptive response is spatially heterogeneous and comprises a portfolio of strategies. Southwestern states and California will be the most impacted by groundwater restrictions. The optimal responses in these states are to both adopt deficit irrigation strategies and reduce a portion of their irrigated croplands, resulting in a shift in crop production to northwestern states with a larger supply of water. The datasets detailed in this repository represent the output from these integrated models, specifically designed to support the analysis and visualization presented in the manuscript and supplemental information. These datasets, used in conjunction with the scripts available at our associated GitHub repository (https://github.com/pches/Femeena_etal_How_can_crop_production_adapt), enable the reproduction of figures and facilitate a comprehensive understanding of the optimal adaptive strategies in agriculture for mitigating water stress under varying groundwater extraction scenarios, as outlined in the abstract.

DNDCe↗

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

Abstract This data plan outlines the structure and content of datasets generated and utilized in the research presented in the manuscript abstract. Groundwater overdraft has led to serious water supply issues in the US West. Most western states manage groundwater use through a permitting system, but California has only recently begun to restrict groundwater use statewide with the 2014 passage of groundwater restrictions which target the elimination of groundwater overdraft practices by 2042. With groundwater extraction curtailed, crop production in the US West (a $95 billion industry annually) will be affected, and appropriate response strategies will be needed to ensure minimal disruption to food production and the regional economy. In this paper, we explore the adoption of alternative adaptive responses: (a) deficit irrigation; (b) switching to less water-intensive crops; (c) changing the extent of irrigated land (including fallowing); and (d) geographically shifting crop production. Employing an integrated modeling approach, we explicitly capture the interactions and feedbacks between local hydrology, changes in crop yields, crop and land use decision-making, changes in crop prices, and regional shifts in crop production. We find that the optimal adaptive response is spatially heterogeneous and comprises a portfolio of strategies. Southwestern states and California will be the most impacted by groundwater restrictions. The optimal responses in these states are to both adopt deficit irrigation strategies and reduce a portion of their irrigated croplands, resulting in a shift in crop production to northwestern states with a larger supply of water. The datasets detailed in this repository represent the output from these integrated models, specifically designed to support the analysis and visualization presented in the manuscript and supplemental information. These datasets, used in conjunction with the scripts available at our associated GitHub repository (https://github.com/pches/Femeena_etal_How_can_crop_production_adapt), enable the reproduction of figures and facilitate a comprehensive understanding of the optimal adaptive strategies in agriculture for mitigating water stress under varying groundwater extraction scenarios, as outlined in the abstract.

DNDCe↗

Genomes to ecosystem function: Targeting critical knowledge gaps in methanogenesis and translation to updated global biogeochemical models

Natural freshwater temperate wetland systems currently represent the largest natural source of atmospheric methane, but are relatively understudied using systems biology tools (e.g. meta-omics) compared to other high producing methane systems (e.g. peat, tropical, or reconstructed wetlands). Using field investigations at the NOAA operated sentinel site on Lake Erie, methane producing activities and responses to geochemical conditions will be determined along seasonal and spatial gradients (Objective 1). Here, a combination of high-throughput activity and gas measurements, combined with high-resolution systems biology and analytical methods, will provide in depth knowledge of the microbiological, chemical, and physical constraints on methane production in wetlands. Using laboratory microcosms, the formation of anoxic microsites and their capacity to facilitate methane production in wetland soils will be simulated (Objective 2). This objective will validate the findings from the field investigations, offering a more controlled environment for teasing out the role of different yet interrelated variables. Lastly, these field and laboratory data will be used for multi-scale, process-level evaluation of an ecosystem biogeochemical model that accommodates these newly identified processes and parameterizes representation of these processes along relevant environmental gradients (Objective 3).This research will identify multiple interacting geochemical, ecological, and metabolic constraints that are poorly understood, oversimplified, or missing in global biogeochemical methane models. This proposal targets the role of oxygen limitation on methane processes in soil domains, to improve reactive transport models of microbial carbon cycling across terrestrial-aquatic soils and generate data on nutrient cycling activities in Great Lake wetlands. This information could provide new insights into the microbial controllers of Lake Erie eutrophication.

59 BASIC BIOLOGICAL SCIENCES↗

CORONAL MAGNETOGRAPHY OF A SIMULATED SOLAR ACTIVE REGION FROM MICROWAVE IMAGING SPECTROPOLARIMETRY

We have simulated the Expanded Owens Valley Solar Array (EOVSA) radio images generated at multiple frequencies from a model solar active region, embedded in a realistic solar disk model, and explored the resulting data cube for different spectral analysis schemes to evaluate the potential for realizing one of EOVSA’s most important scientific goals—coronal magnetography. In this paper, we focus on modeling the gyroresonance and free–free emission from an on-disk solar active region model with realistic complexities in electron density, temperature and magnetic field distribution. We compare the magnetic field parameters extrapolated from the image data cube along each line of sight after folding through the EOVSA instrumental profile with the original (unfolded) parameters used in the model. We find that even the most easily automated, image-based analysis approach (Level-0) provides reasonable quantitative results, although they are affected by systematic effects due to finite sampling in the Fourier (UV) plane. Finally, we note the potential for errors due to misidentified harmonics of the gyrofrequency, and discuss the prospects for applying a more sophisticated spectrally based analysis scheme (Level-1) to resolve the issue in cases where improved UV coverage and spatial resolution are available.

79 ASTRONOMY AND ASTROPHYSICS↗

Understanding the Drivers of Atlantic Multidecadal Variability using a Stochastic Model Hierarchy

The relative importance of ocean and atmospheric dynamics in generating Atlantic Multidecadal Variability (AMV) remains an open question. Comparisons between climate models with SLAB and fully-dynamic (FULL) ocean components are often used to explore this question, but cannot reveal how individual ocean processes generate these differences. We build a hierarchy of physically interpretable stochastic models to investigate the contribution of two upper-ocean processes to AMV: the role of seasonal variation and mixed-layer entrainment. This interpretability arises from the stochastic model’s simplified representation of sea surface temperature (SST), considering only the local upper ocean response to white-noise atmospheric forcing and its impact on surface heat exchange. We focus on understanding differences between SLAB and FULL non-eddy resolving pre-industrial control simulations of the Community Earth System Model 1 (CESM), and estimate the stochastic model parameters from each respective simulation. Despite its simplicity, the stochastic model reproduces temporal characteristics of SST variability in the SPG, including reemergence, seasonal-to-interannual persistence and power spectra. Furthermore, unrealistically persistent SST of the CESM-SLAB ocean simulation is reproduced in the equivalent stochastic model configuration where the mixed-layer depth (MLD) is constant. The stochastic model also reveals that vertical entrainment primarily damps SST variability, thus explaining why SLAB exhibits larger SST variance than FULL. Here, the stochastic model driven by temporally stochastic, spatially coherent forcing patterns reproduces the canonical AMV pattern. However, the amplitude of low-frequency variability remains underestimated, suggesting a role for ocean dynamics beyond entrainment.

54 ENVIRONMENTAL SCIENCES↗

Boundary layer description of directional polymer crystallisation

Nearly fifty years ago Lovinger and Gryte suggested that the directional crystallization of a polymer was analogous to the quiescent isothermal crystallization experiment but at a supercooling where the crystal growth velocity was equal to the velocity of the moving front. Our experiments showed that this equivalence holds in a detailed manner at low directional velocities. To understand the underlying physics of these situations, we modeled the motion of a crystallization front in a liquid where the left side boundary is suddenly lowered below the melting point (Stefan's problem) but with the modification that the crystallization kinetics follow a version of the Avrami model. Our numerical results surprisingly showed that the results of the polymer analog track with the Stefan results which were derived for a simple liquid that crystallizes completely at its melting point; in particular, the position of the crystal growth-front evolved with time exactly as in the Stefan problem. The numerical solution also showed that the temperature in the immediate vicinity of the growth-front decreased with increasing front velocity, which is in line with Lovinger and Gryte's ansatz. To provide a clear theoretical understanding of these numerical results we derive a boundary layer solution to the governing coupled differential equations of the polymer problem. The analytical results are in agreement with our observations from experiments and numerical computations but show that this equivalence between the small molecule and polymer analog only holds in the limit where the crystallization enthalpy is much larger than the rate at which heat is conducted away in the polymer. In particular, in the context of the temperature profile, the enthalpy generated by the crystallisation process which is spread out over a narrow spatial region can be approximated as a point source whose location and temperature correspond to the Lovinger–Gryte ansatz.

36 MATERIALS SCIENCE↗

Measurement of Kinetic Parameters by Oscillated Experiments

The availability of reliable values of the kinetic parameters (effective delayed neutron fraction {beta} and effective mean neutron generation time {Lambda}) is important for reactor kinetic analyses and for reactivity monitoring when adopting the point kinetic approach. The kinetic parameters may be obtained either by simulations (Monte Carlo or deterministic) of the system or by direct measurements. Several methods have been proposed for the direct experimental determination of the kinetic parameters, e.g. control rod drops and noise analysis approaches, e.g. In this work, the problem of the determination of kinetic parameters in subcritical systems is tackled. The system is subjected to an oscillated source and the value of the ratio {beta}/{Lambda} is related to a measurable quantity when the system response reaches an equilibrium condition. In the analysis presented, a pure frequency is considered: when analyzing more complicated source periodic behaviours, a Fourier analysis can allow to isolate the contributions of individual frequencies. The phase difference between the oscillating source and the system response is adopted as the experimental observable. The method for the interpretation of the measurements is based on the standard point kinetic model. The response of the system is obtained by localized neutron detectors and, therefore, spatial and spectral effects may also affect the results. This drawback needs some further discussion and will be considered in the future work. The phase shift between the source signal and the system response may be analytically retrieved by Laplace transforming the point kinetic equations in the presence of an oscillated source. An explicit formula relates the phase shift to the ratio {beta}/{Lambda} and to the frequency of the source. Based on this relationship, the ratio {beta}/{Lambda} can be determined. To validate the technique, the experimental data are simulated by a numerical code solving the time-dependent diffusion equations for a source-driven system. The work allows to assess the possibility of the technique and its limits of applicability. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗