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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25

Control and data acquisition upgrades for NSTX-U

The extensive NSTX Upgrade (NSTX-U) Project includes major components which allow a doubling of the toroidal field strength to 1 T, of the Neutral Beam heating power to 12 MW, and the plasma current to 2 MA, and substantial structural enhancements to withstand the increased electromagnetic loads. The maximum pulse length will go from 1.5 to 5 s. The larger and more complex forces on the coils will be protected by a Digital Coil Protection System, which requires demanding real-time data input rates, calculations and responses. The amount of conventional digitized data for a given pulse is expected to increase from 2.5 to 5 GB per second of pulse. 2-D Fast Camera data is expected to go from 2.5 GB/pulse to 10, and another 2 GB/pulse is expected from new IR cameras. Our network capacity will be increased by a factor of 10, with 10 Gb/s fibers used for the major trunks. 32-core Linux systems will be used for several functions, including between-shot data processing, MDSplus data serving, between-shot EFIT analysis, real-time processing, and for a new capability, between-shot TRANSP. As a result, improvements to the MDSplus events subsystem will be made through the use of both UDP and TCP/IP based methods and the addition of a dedicated “event server”.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The pervasive impact of critical fluctuations in liquid–liquid extraction organic phases

Liquid-liquid extraction is an essential chemical separation technique where polar solutes are extracted from an aqueous phase into a nonpolar organic solvent by amphiphilic extractant molecules. A fundamental limitation to the efficiency of this important technology is third phase formation, wherein the organic phase splits upon sufficient loading of polar solutes. The nanoscale drivers of phase splitting are challenging to understand in the complex hierarchically structured organic phases. In this study, we demonstrate that the organic phase structure and phase behavior are fundamentally connected in a way than can be understood with critical phenomena theory. For a series of binary mixtures of trialkyl phosphate extractants with linear alkane diluents, we combine small angle x-ray scattering and molecular dynamics simulations to demonstrate how the organic phase mesostructure over a wide range of compositions is dominated by critical concentration fluctuations associated with the critical point of the third phase formation phase transition. These findings reconcile many longstanding inconsistencies in the literature where small angle scattering features, also consistent with such critical fluctuations, were interpreted as reverse micellar-like particles. Altogether, this study shows how the organic phase mesostructure and phase behavior are intrinsically linked, deepening our understanding of both and providing a new framework for using molecular structure and thermodynamic variables to control mesostructure and phase behavior in liquid-liquid extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phasor-Based Adaptive Control of a Test-Feeder Distribution Network

Control in the power distribution system is needed to match the generation of electricity (that is, supply) with the demand for power (that is, load) at all times while maintaining a high level of power quality [1] (see "Summary"). The complexity of controlling the electric distribution system increases when distributed intermittent energy sources, such as solar photovoltaics (PVs), displace large-scale dispatchable generation [2]-[10]. Furthermore, if the supply from distributed resources exceeds the time-varying demand across a feeder, then the feeder-level voltage will increase. In extreme cases, large voltage increases will trigger the disconnection of distributed generation to protect electrical equipment and ensure customer safety. Consequently, coordinating renewable energy sources that are distributed throughout the distribution system-to match real-time demand across an entire power network-brings the additional challenge of maintaining a high level of supply reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

MoorDyn V2: New Capabilities in Mooring System Components and Load Cases

MoorDyn, an open-source mooring dynamics model, is being expanded with capabilities for additional mooring system features and load cases. As floating wind turbine technology matures, mooring systems are becoming more sophisticated and more complex scenarios need to be considered in the design process. Mooring systems may have synthetic line materials, ballast/buoyancy bodies along the lines, or interconnections between platforms. Failure modes may involve multiple cascading line failures that depend on mooring system dynamics. Features recently added to MoorDyn aim to address these emerging needs. MoorDyn’s linear elasticity model has been supplemented to support user-defined stress-strain curves, which can be adjusted to represent synthetic mooring materials. Rigid six-degree-of-freedom bodies in the mooring system can now be modeled using two new model objects. “Rod” objects provide an option for rigid cylindrical bodies. They use the existing Morison equation-based hydrodynamics model and can be connected to mooring lines at either end. “Body” objects provide a generic six-degree-of-freedom rigid-body representation based on a lumped-parameter model of translational and rotational properties. Rod objects can be added to Body objects and mooring lines can be attached at any location, allowing a wide variety of submerged structures to be integrated into the mooring system. Lastly, a means of dynamically simulating mooring line failures has been implemented. These new features, currently in the C++ version of MoorDyn, are described and then demonstrated on a two-turbine shared-mooring array. A qualitative view of the results suggests the new features are functioning as expected.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

Improving High-Energy Particle Detectors with Machine Learning

Microseconds after the Big Bang, the universe existed in a state called the quark-gluon plasma (QGP). To experimentally study its properties, the QGP is recreated in high-energy nuclear collisions at the LHC, and the particles produced from the QGP are reconstructed from their energy deposition in the ATLAS calorimeter. This requires both classifying the particles and calibrating their deposited energy. The objective of this project is to improve the reconstruction by using machine learning techniques, where the energy depositions of clusters of cells, formed by ATLAS topo-clustering methods, are treated as three-dimensional images when inputted to neural networks. This approach significantly improves the calibration of deposited energies when cross-validating while training, and models trained on idealized data predict the calibrated energies of particles in more complex data sets well. Additionally, implementation of a data generator using uproot allows the program to load input data into memory as needed while training or predicting, significantly reducing the amount of memory used. The data generator also allows for use of multiprocessing to speed up training and evaluating. This work illustrates that using machine learning methods for both classification and calibration has the potential to significantly improve particle reconstruction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Overview of Proposed Summer Project [Slides]

The following are visual aids developed to assist in initial discussion with an intern about their proposed Summer 2021 project. Project Goal: Develop a user friendly code to assess pressure load on a geometry of interest to understand the rigid body effects, and compare to more complex approaches

97 MATHEMATICS AND COMPUTING↗

Reactor Physics Simulations of the High Flux Isotope Reactor Permanent Beryllium Reflector Number 5 Design

This study evaluates reactor physics aspects of the proposed High Flux Isotope Reactor (HFIR) permanent beryllium reflector number 5 design. HFIR is a pressurized, light water–cooled, and beryllium reflected research reactor that operates at 85 MW for cycle lengths of approximately 24 to 26 days. A new permanent reflector design is highly desirable for increased versatility in irradiation experiments, to arrange the vertical experiment facilities (VXFs) to minimize their impact on neutron scattering if loaded with neutronabsorbing experiments, to enhance reflector thermal-structural-hydraulic performance, and to simplify the complex fabrication process. The current number 4 and concept number 5 reflectors have 22 and 28 VXFs, respectively, and are modeled and analyzed in this study with the MCNP5 and SCALE 6.1.3 nuclear simulation codes.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Explainable and Differentiable Reinforcement Learning for Multi-objective Optimization in Particle Accelerators

Operating particle accelerators involves optimizing multiple goals simultaneously, which can be challenging due to trade-offs among objectives. While evolutionary algorithms like the genetic algorithm (GA) have been used for various Multi-Objective Optimization (MOO) tasks, they are not inherently suited for complex control problems. This talk highlights two variations of Reinforcement Learning (RL) for concurrently optimizing heat load and trip rates at the Continuous Electron Beam Accelerator Facility (CEBAF). The problem involves strict constraints on individual states, actions, and overall energy requirements of the beam. First, this talk highlights how differentiability can be harnessed through a Deep Differentiable Reinforcement Learning (DDRL) approach to address MOO issues within particle accelerators. We examine the DDRL method alongside Model Free Reinforcement Learning (MFRL), GA, and Bayesian Optimization (BO). The performance of these methods is assessed by generating a Pareto-front for two objectives. Our findings indicate that DDRL excels in handling high-dimensional problems more effectively than MFRL, BO, and GA. Next, we will show integration of explainable physics-based constraints into RL algorithms to enhance trans- parency and trust in decision-making processes by enabling users to verify that agents adhere to established physical principles. This surrogate function can be modeled using neural networks or sparse dictionary mod- els. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment provided but the surrogate model. In addi- tion, we find that the introduction of a mathematical functional dictionary based surrogate model enables our reinforcement learning algorithms to reliably converge for difficult high-dimensional accelerator controls environments.

Rajput, Kishansingh [Thomas Jefferson National Acc↗

Simulation of the Multi-Wake Evolution of Two Sandia National Labs/National Rotor Testbed Turbines Operating in a Tandem Layout

The future of wind power systems deployment is in the form of wind farms comprised of scores of such large turbines, most likely at offshore locations. Individual turbines have grown in span from a few tens of meters to today’s large turbines with rotor diameters that dwarf even the largest commercial aircraft. These massive dynamical systems present unique challenges at scales unparalleled in prior applications of wind science research. Fundamental to this effort is the understanding of the wind turbine wake and its evolution. Furthermore, the optimization of the entire wind farm depends on the evolution of the wakes of different turbines and their interactions within the wind farm. In this article, we use the capabilities of the Common ODE Framework (CODEF) model for the analysis of the effects of wake–rotor and wake-to-wake interactions between two turbines situated in a tandem layout fully and partially aligned with the incoming wind. These experiments were conducted in the context of a research project supported by the National Rotor Testbed (NRT) program of Sandia National Labs (SNL). Results are presented for a layout which emulates the turbine interspace and relative turbine emplacement found at SNL’s Scaled Wind Technologies Facility (SWiFT), located in Lubbock, Texas. The evolution of the twin-wake interaction generates a very rich series of secondary transitions in the vortex structure of the combined wake. These ultimately affect the wake’s axial velocity patterns, altering the position, number, intensity, and shape of localized velocity-deficit zones in the wake’s cross-section. This complex distribution of axial velocity patterns has the capacity to substantially affect the power output, peak loads, fatigue damage, and aeroelastic stability of turbines located in subsequent rows downstream on the farm.

Baruah, Apurva (ORCID:0000000252354068)↗

Environmental Durability Assessment and Development of Subcomponent Test Methods for Advanced Materials in Marine Energy Applications

Marine energy developers are beginning to rely more heavily on advanced composite materials for their load-bearing structures. Understanding how these materials respond and degrade in harsh marine environments is a complex problem. Much research has been performed at smaller laboratory scales to understand the fundamental physical and chemical degradation mechanisms, but little structural testing research has been performed at larger scales to understand how these physical and chemical interactions scale and how they should be accounted for in the design process. The Advanced Materials project is a multilaboratory research collaboration that addresses these issues with the intention of reducing risks and barriers to marine energy developers wanting to adopt advanced composite materials. The National Laboratory of the Rockies has been playing a leading role in developing larger-scale testing infrastructure and test methods to validate complex numerical degradation models and standardize testing procedures to do so. This paper reviews past structural testing activities, how they have grown into current research activities, and how they will continue to evolve to directly address industry needs. This paper covers key research areas - large-scale water absorption and subsequent structural validation testing, qualification of bolted and adhesive connections, and combined submerged fatigue testing at increasing scales. It provides insights into the complex requirements for testing infrastructure and test method development to effectively qualify materials and certify marine energy structures for harsh marine environments. This research program paves the way for better guidance and standardization within the industry when adopting advanced composite materials.

16 TIDAL AND WAVE POWER↗

MoorDyn V2: New Capabilities in Mooring System Components and Load Cases: Preprint

MoorDyn, an open-source mooring dynamics model, is being expanded with capabilities for additional mooring system features and load cases. As floating wind turbine technology matures, mooring systems are becoming more sophisticated and more complex scenarios need to be considered in the design process. Mooring systems may have synthetic line materials, ballast/buoyancy bodies along the lines, or interconnections between platforms. Failure modes may involve multiple cascading line failures that depend on mooring system dynamics. Features recently added to MoorDyn aim to address these emerging needs. MoorDyn’s linear elasticity model has been supplemented to support user-defined stress-strain curves, which can be adjusted to represent synthetic mooring materials. Rigid six-degree-of-freedom bodies in the mooring system can now be modeled using two new model objects. “Rod” objects provide an option for rigid cylindrical bodies. They use the existing Morison equation-based hydrodynamics model and can be connected to mooring lines at either end. “Body” objects provide a generic six-degree-of-freedom rigid-body representation based on a lumped-parameter model of translational and rotational properties. Rod objects can be added to Body objects and mooring lines can be attached at any location, allowing a wide variety of submerged structures to be integrated into the mooring system. Lastly, a means of dynamically simulating mooring line failures has been implemented. These new features, currently in the C++ version of MoorDyn, are described and then demonstrated on a two-turbine shared-mooring array. A qualitative view of the results suggests the new features are functioning as expected.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

Environmental Durability Assessment and Development of Subcomponent Test Methods for Advanced Materials in Marine Energy Applications: Preprint

Marine energy developers are beginning to rely more heavily on advanced composite materials for their load bearing structures. Understanding how these materials respond and degrade in harsh marine environments is a complex problem. Much research has been performed at smaller laboratory scales to understand the fundamental physical and chemical degradation mechanisms, but little structural testing research has been performed at larger scales to understand how these physical and chemical interactions scale and how they should be accounted for in the design process. The Advanced Materials project is a multilaboratory research collaboration that has been addressing these issues with the intention of reducing risks and barriers to marine energy developers wanting to adopt advanced composite materials. The National Laboratory of the Rockies has been playing a leading role in developing larger scale testing infrastructure and test methods to validate complex numerical degradation models and standardize testing procedures to do so. This paper provides a review of past structural testing activities and how they have grown into current research activities and will continue to evolve into the future to directly address industry needs. This paper covers key research areas large-scale water absorption and subsequent structural validation testing, qualification of bolted and adhesive connections, and conducting combined submerged fatigue testing at increasing scales. This paper provides insights into the complex requirements for testing infrastructure and test method development to effectively qualify materials and certify marine energy structures for harsh marine environments. This research program paves the way for better guidance and standardization within the industry when adopting advanced composite materials.

16 TIDAL AND WAVE POWER↗

A Multi-Phase Modeling Framework Suitable for Dynamic Applications

Under dynamic loading conditions and the associated extreme conditions many metals will undergo phase transformations. The change in crystal structure associated with solid–solid phase transformations can significantly alter the subsequent mechanical response of the material. For the interpretation of experiments involving dynamic loading it is beneficial to have a modeling framework that captures key features of the material response while remaining relatively simple. We introduce a candidate framework and apply it to the metal tin to highlight a range of behaviors that are captured by the model. We also discuss potential extensions to capture additional behaviors that could be important for certain materials and loading scenarios. The model is useful for analysis of results from dynamic experiments and offers a point of departure for more complex model formulations.

36 MATERIALS SCIENCE↗

Design Features of the Neutral Particle Diagnostic System for the ITER Tokamak

The control of the deuterium–tritium (DT) fuel isotopic ratio has to ensure the best performance of the ITER thermonuclear fusion reactor. The diagnostic system described in this paper allows the measurement of this ratio analyzing the hydrogen isotope fluxes (performing neutral particle analysis (NPA)). The development and supply of the NPA diagnostics for ITER was delegated to the Russian Federation. The diagnostics is being developed at the Ioffe Institute. The system consists of two analyzers, viz., LENPA (Low Energy Neutral Particle Analyzer) with 10–200 keV energy range and HENPA (High Energy Neutral Particle Analyzer) with 0.1–4.0MeV energy range. Simultaneous operation of both analyzers in different energy ranges enables researchers to measure the DT fuel ratio both in the central burning plasma (thermonuclear burn zone) and at the edge as well. When developing the diagnostic complex, it was necessary to account for the impact of several factors: high levels of neutron and gamma radiation, the direct vacuum connection to the ITER vessel, implying high tritium containment, strict requirements on reliability of all units and mechanisms, and the limited space available for accommodation of the diagnostic hardware at the ITER tokamak. The paper describes the design of the diagnostic complex and the engineering solutions that make it possible to conduct measurements under tokamak reactor conditions. The proposed engineering solutions provide a safe—with respect to thermal and mechanical loads—common vacuum channel for hydrogen isotope atoms to pass to the analyzers; ensure efficient shielding of the analyzers from the ITER stray magnetic field (up to 1 kG); provide the remote control of the NPA diagnostic complex, in particular, connection/disconnection of the NPA vacuum beamline from the ITER vessel; meet the ITER radiation safety requirements; and ensure measurements of the fuel isotopic ratio under high levels of neutron and gamma radiation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Low and High LET Degradation Studies of Metal-Loaded Organic Phase Ligands in the ALSEP Process

Organic solutions comprising the Actinide Lanthanide Separation Process (ALSEP) solvent consisting of 0.5 M 2-ethylhexyl phosphonic acid mono-2-ethylhexyl ester (HEH[EHP]) and 0.05 M N,N,N’,N’-tetra(2-ethylhexyl)diglycolamide (T2EHDGA) in n-dodecane were subjected to low LET and high LET irradiation before and after equilibration with an aqueous phase of 3 M HNO 3 . Degradation dose constants revealed greater ligand degradation due to gamma irradiation than alpha irradiation for both ligands. Furthermore, equilibration with nitric acid did not have a significant impact on ligand degradation for either irradiation source. Identified degradation products were similar for both gamma and alpha irradiation and occurred mostly through the rupture of the N–C carbonyl and C–O ether bonds for T2EHDGA and the C–Oether bond in HEH[EHP]. Acid contact appears to alter the degradation pathway by favoring the formation of higher molecular weight recombination products. Furthermore, mixed T2EHDGA-HEH[EHP]-NO 3 complexes were formed with Nd(III) after extraction from 3 M HNO 3 , and low LET gamma irradiation of the Nd(III) loaded organic solution produced similar degradation products as the organic solution absent of Nd(III). Interestingly, and likely due to the greater radiolytic susceptibility of T2EHDGA than HEH[EHP], a HEH[EHP]-Nd(III) complex appears to form as the T2EHDGA degrades with increasing absorbed dose.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Groundwater flowpath characteristics drive variability in per- and polyfluoroalkyl substances (PFAS) loading across a stream-wetland system

Groundwater dependent ecosystems in areas with industrial and military land use are at risk of direct exposure to a wide range of contaminants, including PFAS chemicals. Glaciated terrain often has mixed high and low permeability sediments coupled with groundwater flow-through lake features. These hydrogeologic attributes create highly complex ‘source to seep’ dynamics that make spatiotemporal contaminant transport patterns difficult to predict. We investigated one such system in detail using a suite of heat-tracing and chemical methods. Numerous (n=57) preferential groundwater discharge zones (vertical flux rates ranging 0.2 to 3.2 m/d) were identified across the upper Quashnet River stream-wetland system in Mashpee, MA, USA, adjacent to an Air Force Base with several known PFAS source areas. Surface-water and groundwater samples were collected and analyzed (n=145) for precursors and terminal PFAS compounds between March and September 2022. Samples were collected at identified seeps along the Quashnet River (n=59), from wells upgradient from the stream-wetland system (n= 44), from contributing flow-through kettle lakes (n=8), and at multiple locations along the Quashnet River (n=34). Samples from seeps and wells had measured PFAS concentrations ranging from non-detect to approximate 3,500 ng/L (mean= 1,650 ng/L), and a range of deuterium excess values (3.2 to 15.9 per mil) indicative of varying degrees of groundwater-lake interaction prior to emergence at the discharge zones. Groundwater-lake interaction along flowpaths that sourced the sampled seeps was farther supported by significant correlations (p < 0.01) between deuterium excess and %PFAS precursors, and between %PFAS precursors and multiple terminal PFAS compounds (e.g., PFPeS, PFBS, PFHxS). However, some sampled seeps contributing groundwater to the stream-wetland system had much higher total PFAS concentrations (>1000 ng/L) than the upgradient kettle lakes, despite showing lake (evaporative) isotopic signatures, indicating the potential for groundwater flowpath convergence at wetland discharge zones and the influence of lakebed PFAS precursor reactions. PFAS compounds and water isotopic composition at sampled multilevel groundwater wells, rivers, lakes, and seeps suggest that a complex mixture of source groundwater and flowpath characteristics are responsible for diverse observed PFAS mixtures at preferential discharge zones across the stream-wetland system. Further, total PFAS loading patterns to the Quashnet River via groundwater discharge remained remarkably similar from winter to summer to fall conditions, despite a regional dry period in late summer 2022 with the upper river channel completely drying. This work addresses gaps in the existing PFAS literature by demonstrating the importance of subsurface fate and transport on PFAS compound concentrations in controlling contaminant mass loading in preferential groundwater discharge zones and presents a transferrable field toolkit for efficient characterization of spatially preferential PFAS transport dynamics.

Contaminant transport↗

Probing the Energetics of Molecule–Material Interactions at Interfaces and in Nanopores

During the past decades, advances in interfacial chemistries at the molecular level are shaping our world by playing crucial roles in balancing global scale energy crisis and critical environmental concerns. However, systematic investigations into the binding energies, site distribution and their correlation with the molecular-level surface assemblages and structures at interfaces and in nanopores are rarely documented. In this review, we summarize a set of systematic calorimetric studies on surface energetics we performed during the last decade. These studies demonstrate how thermochemistry can reveal crucial energetic insights into a series of molecule – material interactions relevant to a number of applications, including carbon capture and sequestration, energy production, sustainable chemical processing, catalysis, and nanogeoscience. Calorimetric methodologies developed and applied include direct gas adsorption calorimetry, nearroom temperature solvent immersion/solution calorimetry and high temperature oxide melt solution calorimetry. Using these highly unique techniques, we reveal the thermodynamic complexity of carbon dioxide capture on metal – organic framework (MOF) sorbents with built-in and grafted nucleophilic functional groups (-OH and -NH2). These studies suggest that carbon dioxide adsorption on functionalized MOFs is a complex process involving multiple thermodynamic factors, as reflected by changes in surface phase and structure, chemical bonding and degree of disorder with varying temperature and gas loading. The fundamental insights obtained may help optimize the design, synthesis and application of MOF-based carbon dioxide sorbents for carbon capture and sequestration. In parallel, we also explore the energetics of interaction and competition between small molecules (water, carbon dioxide, methane, simple and complex organics) and inorganic materials (calcite, silica, zirconia, zeolites, mesoporous frameworks, alumina, and uranium), at interfaces and in nanopores. Combined with spectroscopic, diffraction, electron microscopic and computational techniques, the energetics of gas/liquid – solid interactions can be correlated with specific bonds, molecular configurations and nanostructures. Although the energetics evolves continuously from weak association to strong bonding to classical capping, distinct regions of rapidly changing stepwise energetics often separate the different regimes. These phenomena are closely related to the properties of inorganic material surfaces (hydrophobicity and acidity/basicity), the framework architectures, and the chemical nature of adsorbate molecules. These direct thermodynamic insights reinforce our understanding of complex small molecule – inorganic material interactions important to multiple disciplines of chemical engineering, materials science, nanogeoscience and environmental technology, including heterogeneous catalysis, molecular separation, material design and synthesis, biomineralization, contaminant and nutrient transport, carbonate formation, and water – organic competitions on material/mineral surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uncertainty characterization in a coupled human-natural system: Modeling agricultural adaptation in the Great Lakes Region

The Great Lakes Region's water quality and ecological health are threatened by the export of nutrients from agricultural lands, which causes eutrophication, hypoxia, and destructive algal blooms. The intensification of hydrologic cycles brought about by climate change is expected to exacerbate nutrient loading in the region, and, at the same time, agricultural adaptation to changing conditions is also expected to affect loading through shifting amounts and timing of fertilization. Quantifying these future effects and their interactions necessitates modeling both the human and natural processes as a coupled system, by pairing land use and agricultural management with hydrologic modeling. At the same time, compounding uncertainties arising from the complex interactions in both systems significantly limit our predictive understanding of the region's impacts. This study utilizes the Soil and Water Assessment Tool (SWAT), developed for simulating the impact of various farmer decisions on watershed functions in Western Lake Erie watersheds, and an under-development agent-based model (ABM) for agricultural management decisions. The aim of this study is to use global sensitivity analysis on the coupled ABM and SWAT models to quantify how uncertainty in both models interactively affects nutrient loading. To do so, we will conduct Sobol sensitivity analysis experiments at different levels of coupling assumptions to quantify how various uncertain factors (e.g., soil moisture and crop choice) and their interactions affect our estimates of nutrient loading. The results of this analysis will allow us to quantify how complex interactions and dependencies between both systems amplify the effect of uncertainties. Insights gained from this study will have broader implications for modeling the adaptive co-evolution of human and natural systems under climate change and can inform effective management of nutrient loading in the Great Lakes Region.

Climate Change↗