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At least 1,135 records · Page 63

Yttrium Hydride Post-Irradiation Examination Plan

Micro nuclear reactors are expected to use metal hydride moderators to ensure thier compact design for the flexible operational purposes. Department of Energy’s Microreactor program therefore aims to provide infrasture and qualification bed for the development of micro nuclear reactors. Because micro nuclear reactors must be compact to offer a flexible operational purposes, metal hydrides are expected to be used as neutron moderator materials due to their high hydrogen number density. Los Alamos National Laboratory (LANL) directed by the DOE to provide a qualified fabrication techniques of metals hydride, especially the yttrium hydride (YHx) which provides advantages over other metal hydride candiates. Qualification of YHx involves fabrication, property, and performance pillars, which must be met for the deployment of microreactors. In the support of the qualification process metal hydride, LANL has developed fabrication techniques based in direct hydriding and powder compacting. For both manufacturing techniques, fresh material properties of metal hydrides have been reported in the literature. To establish the performance limits and the qualification parameters, an irradiation campaign has been initated at Idaho National Laboratory (INL). The irradation campaign aims to investigate the critical irradiated YHx properties as a function of neutron fluence and temperaute. The first phase of the irradiation campaign includes the effect of the operating temperature under neutron irradiation which provides initial data on the metal hydrides and informs the manufacturing processes. So that, drop-in irradations in Advanced Test Reactor (ATR) has been designed. This document depicts the post-irradation examination (PIE) plan of the ATR irradiated YHx. Objective of the PIE plan is to serve as a qualification basis for YHx as a neutron moderator material by understanding the impacts irradiation has on the physical and thermophysical properties; to establish a link between fabrication and the irradiated YHx properties; to institute a PIE strategy for other solid-state neutron moderator candidates, and; to inform micro nuclear reactor fuel performance and safety codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Detection and Quantitation of Hydrogen Emissions Role and Status of Detection Technology

Hydrogen is a critical strategy to decarbonize energy and manufacturing industries. Hydrogen is nontoxic and can be handled safely, but potential for secondary greenhouse impacts. Hydrogen releases arise from a variety of mechanisms (process, design features, "leaks") that contribute to total hydrogen releases. Detection methodologies will be critical to detect and quantify hydrogen emissions. Detection is to be integrated with advanced analytics (AI) and behavior modelling to effectively identify, quantify, and source locate hydrogen releases. Modelling of emissions will contribute to facility safety and reliability. DOE is committed to develop the tools to model and mitigate the impact of hydrogen releases which include: Support modeling to elucidate released hydrogen degradation; Support the development of tools for emissions quantitation; and Support engineering advancements to minimize hydrogen losses along the value chain (including process, design features, and leaks).

detection↗

Development of MCNP Training Modules for Safeguards Practitioners [Abstract]

The Monte-Carlo N-Particle (MCNP) software developed at LANL is the most widely used neutron transport code in the world. It is an essential tool for a variety of applications including detector development and design, nuclear fuel burnup simulation, criticality safety, and nondestructive assay system optimization. For this reason, it is indispensable within the safeguards and materials control & accountability (MC&A) communities. Multiple MCNP training courses have been created and taught over the last several decades by the MCNP development team at LANL, however there are no existing courses that cover specialized topics considered fundamental to NDA and safeguards models. To fill this gap, the MCNP team and Safeguards Science and Technology group at LANL have co-created a set of training modules customized to meet the specialized needs of the safeguards and MC&A communities. The basic modules cover concepts such as NDA system optimization, He-specific and other capture tallies, and tools for improved theoretical understanding. An advanced module was also created to cover topics including variance reduction for active interrogation simulations, use of the LANL MCNPTools post-processor, PTRAC (particle tracking) and list-mode data simulations, and fuel burnup simulations. The training modules teach to the latest and most state-of-the-art MCNP features and tools released by the development team at LANL and are intended to be taught jointly by the developers and safeguards experts. Ultimately, we hope that creation of these modules will serve to capture and convey the safeguards modeling and MCNP expertise at LANL, and that we will be able to share the modules more broadly with the MC&A and safeguards communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Celestial Quantum Error Correction. Part II. From qudits to celestial CFT

A holographic CFT description of asymptotically flat spacetimes inherits vacuum degeneracies and IR divergences from its gravitational dual. We devise a Quantum Error Correcting (QEC) framework to encode both effects as correctable fluctuations on the CFT dual. The framework is physically motivated by embedding a chain of qudits in the so-called Klein spacetime and then taking a continuum 𝑁 → ∞ limit. At finite 𝑁 the qudit chain 1) enjoys a discrete version of celestial symmetries and 2) supports a Gottesman-Kitaev-Preskill (GKP) code. The limit results in hard states with quantized BMS hair in the celestial torus forming the logical subspace, robust under errors induced by soft radiation. Technically, the construction leverages the recently studied 𝑤 1+∞ hierarchy of soft currents and its realization from a sigma model in twistor space.

79 ASTRONOMY AND ASTROPHYSICS↗

Advancing our understanding of instabilities in high-energy-density systems through the study of benchmark datasets with advanced modeling tools

Numerous types of pulsed power driven inertial confinement fusion (ICF) and high energy density (HED) systems rely on implosion stability to achieve desired temperatures, pressures, and densities. Sandia National Laboratories Pulsed Power Sciences Center’s main ICF platform, Magnetized Liner Inertial Fusion (MagLIF), suffers from implosion instabilities which limit attainable fuel conditions and can compromise fuel confinement. This Truman Fellowship research primarily focused on computationally exploring (a) methods for improving our understanding of hydrodynamic and magnetohydrodynamic instabilities that form during cylindrical liner implosions, (b) methods for mitigating implosion instabilities, particularly those that degrade performance of MagLIF targets, and (c) novel MagLIF target designs intended to improve target performance primarily via enhanced implosion stability. Several multi-dimensional computational tools were used, including the magnetohydrodynamics code ALEGRA, the radiation-magnetohydrodynamics code HYDRA, and the magnetohydrodynamics code KRAKEN. This research succeeded in executing and analyzing simulations of automagnetizing liner implosions, shockless MagLIF implosions, dynamic screw pinch driven cylindrical liner implosions, and cylindrically convergent HED instability studies. The methods and tools explored and developed in this Truman Fellowship research have been published in several peer-reviewed journal articles and will serve as useful contributions to the fields of pulsed power science and engineering, particularly pertaining to pulsed power ICF and HED science.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Equilibrium Core Model for Micro Pebble Bed Reactors Using OpenMC

Estimating the equilibrium state for pebble bed reactors (PBRs) presents complex challenges as it requires simultaneous consideration of changes in the pebbles’ movement as well as their fuel compositions. Whereas traditional approaches use multigroup diffusion codes for neutronics calculations of PBRs’ equilibrium state, the double-heterogeneity of PBRs complicates neutron cross-section generation. Continuous-energy Monte Carlo (MC) methods are better suited for detailed PBR analysis because of their natural handling of double-heterogeneity, but they demand substantially more computational resources. Here, this study introduces a novel method for efficiently estimating the equilibrium state in small and micro PBRs with reduced computational cost. The method is anticipated to accelerate the processes of core design and performing parametric studies for utilizing advanced fuel and structural materials. The HTR-10 reactor design was used for validating the method’s predictions and evaluating its computational efficiency. When compared to reference calculation values from the literature, criticality (k-effective) was predicted to be approximately within the margin of error of the MC transport calculation, average core power density (in megawatts per cubic meter) was predicted within 2.5% relative error, and maximum thermal flux (10 13 n/cm 2 .s −1 ) was predicted within 1.8% relative error. The calculated inventory of fission products and fuel composition in the equilibrium core were within 15% and 16.6%, respectively, when compared to reported values from the literature. The difference is attributed to variance in the considered values of the core temperature, which was found to significantly affect the depletion analyses.

Equilibrium core↗

Fully Bayesian Analysis With Model Inadequacy Correction For Nuclear Graphite Property Models With Hierarchical Variance Structure

Nuclear-grade graphites are extensively utilized in the core designs of various advanced nuclear reactors. Within the reactor environment, graphite is subjected to prolonged exposure to extreme conditions, including high temperatures, radiation, and potentially molten salt and oxygen. Such exposure can induce several degradation mechanisms in graphite, such as nonuniform volumetric strains caused by irradiation and thermal expansion, leading to stresses that may compromise the performance of graphite components. Assessing component integrity, forecasting component performance over the reactor's lifespan, and developing design standards necessitate robust tools for predicting fracture initiation and propagation in graphite structural components within nuclear reactors. This code enables the Bayesian calibration of properties for nuclear-grade graphites. Using a hierarchical Bayesian approach, multiple experimental data sources are combined to develop Gaussian process models for the properties. Using the Kennedy O'Hagan framework, the uncertainties due inadequacies in the model and the inherent spread in the experimental data are quantified.

Dhulipala, Som Lakshmi NarasimhaLakshmi Narasimha ↗

The Design of a High Charge Polarized Preinjector for the Electron-Ion Collider

The design of the electron pre-injector of the Electron-Ion Collider (EIC) project to generate 4 x 7 nC bunch has been advancing to meet the requirements for injection into the Rapid Cycling Synchrotron (RCS). The major challenges are high charge transport and achieving small energy spread from 3 GHz traveling-wave plate(TWP). The designed preinjector includes the polarized electron source, bunching section, TWP Linac, zigzag phase space manipulation and spin rotator. In this report, we will discuss the RF frequency selection and the way to reduce energy spread down to 0.2% by longitudinal phase space manipulate. We will also report the results of beamline simulation using space charge code and the conceptual design of spin rotator.

Wang, E.↗

An Advanced Machine Learning and Artificial Intelligence System for Demonstrating Radiation Regulatory Compliance in DOE Accelerator Facilities

In this Phase II proposal, Applied Research LLC (ARLLC), Thomas Jefferson National Accelerator Facility (Jefferson Lab), and Old Dominion University (ODU) propose the combination of domain knowledge (beam characteristics, fixed structural shielding, earthen burden (the soil and foliage added to the dome of the experimental halls as additional shielding), etc.), machine learning (ML) and/or artificial intelligence (AI) to correlate a variety of multi-modal onsite signals and the radiation fields seen in accessible areas of the accelerator site and the site boundary. The ML/AI will consider the complex influence of environmental parameters affecting the radon contribution of the measurements, focusing on actual data obtained from Jefferson Lab. In Phase I, the coded beam and location data were fed into a deep learning model to predict doses at several designated locations in Jefferson Lab’s facility. Moreover, a dense radiation map was generated using only a sparse collection of the samples in a facility. In Phase II, we will develop a software prototype containing a radiation prediction algorithm, dense radiation map algorithms, and background noise prediction algorithms, with actual data used to evaluate the prototype. This work will provide a framework for evaluation of radiation measurement results around the site based on learned responses. In addition, the proposed approach allows more granular mapping of radiation levels. Better understanding and communication of these levels is related to the overall approach in keeping doses to personnel ALARA.

43 PARTICLE ACCELERATORS↗

Nonnuclear Experimental Capabilities to Support Design, Development, and Demonstration of Microreactors

This work provides a summary of selected experimental capabilities being developed to support nonnuclear testing and demonstration of technology in support of microreactors under the U.S. Department of Energy’s (DOE’s) Microreactor Program. Major capabilities include the Single Primary Heat Extraction and Removal Emulator (SPHERE) and the Microreactor Agile Non-nuclear Experimental Test Bed (MAGNET). The SPHERE facility allows for controlled testing of the steady-state and transient heat rejection capabilities of a single heat pipe using electrical heaters that simulate nuclear heating. The facility is capable of monitoring axial temperature profiles along the heat pipe and surrounding test articles during startup, steady-state operation, and transients. Instrumentation includes noncontact infrared thermal imaging, surface thermocouples, spatially distributed fiber optic temperature and strain sensors, electrical power meters, and a water-cooled, gas-gap calorimeter for quantifying heat rejection from the heat pipe. The facility can be operated under both vacuum and inert-gas conditions. The MAGNET facility is a large-scale, 250-kW electrically heated microreactor test bed to enable nonnuclear experimental evaluation of a variety of microreactor concepts. It can be supplied to electrically heat a scaled section of a microreactor and further test the capabilities of heat rejection systems. The initial MAGNET experiments will support technology maturation and reduce uncertainty and risk associated with the design, operation, and deployment of monolithic heat pipe–based reactors. However, this test bed can broadly be applied to multiple microreactor concepts to evaluate a wide range of thermal-hydraulic and structural phenomena such as interface coupling with power conversion units and other collocated systems. MAGNET can evaluate integral thermomechanical effects during electrical heating of an array of heat pipes in a larger test article. Examples of initial testing will include thermal stresses in the monolith and the impact of debonding of a heat pipe from the core block and how that failure could impact surrounding heat pipes, i.e., understanding the potential for cascading failure. This work also discusses some modeling capabilities that can support experiment design, analysis, and interpretation, including the heat pipe code Sockeye and a comparison of thermal-structural simulations performed using ABAQUS and STAR-CCM+.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Effects of radial transport on divertor power and particle flux widths under different operational regimes in EAST

Here, a study of the effects of radial transport on the outer divertor particle and power flux widths (λ js and λ q ) is carried out using plasmas under different operational regimes in the Experimental Advanced Superconducting Tokamak (EAST). In the EAST experiments, the λ js values measured during the grassy intra- and inter-ELM phases are similar, and the averaged value of λ js during grassy ELMy discharges is found to be smaller than that of the intra-ELM phase of type-I ELMy discharges but larger than that of the inter-ELM phase of type-I ELMy discharges. Simulations of scans of the radial particle and heat transport coefficients, D and χ e , performed using the BOUT++ transport code show that both λq and λjs increase with D and χe, especially when D or χ e is larger than a threshold value, indicating that background turbulence starts to matter in the determination of λ q and λ js when D or χ e surpasses the threshold value. A comparison between the simulation of the D scan and the experimental results shows that the different values of λ js obtained under different plasma operational regimes are probably due to the different intensities of background turbulence, which is beyond the scope of Goldston's heuristic drift-based model as reported by Goldston et al (2012 Nucl. Fusion 52 013009), since their model was derived by assuming that turbulent transport does not exceed a certain level. The ratio of λ js to λ q is greatly affected by the radial transport; however, simulations carried out using Scrape-off Layer Plasma Simulation (SOLPS) show that divertor geometry and plasma density have big influences on λ js , and thus could also affect the ratio of λ js to λ q .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data Files for Runoff Evaluation in an Earth System Land Model for Permafrost Regions

Modeling of hydrological runoff is essential for accurately capturing spatiotemporal feedbacks within the land–atmosphere system, particularly in sensitive regions such as permafrost landscapes. However, substantial uncertainties persist in the terrestrial runoff parameterization schemes used in Earth system and land surface models. This is particularly true in permafrost regions, where landscape heterogeneity is high and reliable observational data are scarce.This data set includes all files that were produced and applied in the paper Runoff Evaluation in an Earth System Land Model for Permafrost Regions [Xiang et al. in review]. The paper is in review as of July 1 2025 in Geoscientific Model Development (GMD). In this study, we evaluate the performance of runoff parameterization schemes in the Energy Exascale Earth System Model (E3SM) land model (ELM). Our proposed framework leverages simulation results from the Advanced Terrestrial Simulator (ATS), which is a physics-rich integrated surface/subsurface hydrologic model that has been successfully evaluated previously in Arctic tundra regions. We used ATS to simulate runoff from 22 representative hillslopes in the Sagavanirktok River basin, located on the North Slope of Alaska, then compared the output with ELM’s parameterized representation of total runoff. This dataset contains 2 figure image files (*.png, *jpg) that describe the study site and methods, as well as folders (Figure*.zip) that contain the associated data files (*.csv, *.dat) and python code notebooks (*.ipynb) for figures 3-7 in the paper. Jupyter notebook (*.ipynb) files that produce the figure files using the associated data files will run within a python environment configured with Jupyter Lab or Notebook packages.

54 ENVIRONMENTAL SCIENCES↗

Modeling Continuous Online Refueling with SCALE 6.3.1 and Serpent-2 in the EIRENE Novel Molten Salt Reactor Design

The Molten Salt Reactor (MSR) is a Generation IV advanced fission reactor design in which the coolant, and in some cases the fuel itself, is in the form of liquid molten alkali-halide salts with a fluoride or chloride ionic base. In liquid-fueled MSRs, reactor refueling may be performed online, where fresh fuel salt is added to the core during operation without the need for shutdown periods. Refueling for these reactor designs is typically modeled using either a batch or continuous refueling approach, both of which can be simulated with the SCALE 6.3.1 and Serpent-2 code systems. However, the specific manner in which they are implemented can vary depending upon the desired rate of refueling, whether the refueling rate is constant or variable, and consideration of salt drainage for systems where the in-core salt volume is kept constant. In a novel MSR fuel cycle concept termed the “Sourdough” fuel cycle, fuel salt is allowed to “grow” within the core, with excess salt either being transferred to an external holding tank to maintain a constant core volume or diverted to an upper plenum within the core to allow for volume growth. In this work, continuous refueling was modeled in a thermal-spectrum, LEU-fueled, small MSR design operating with the Sourdough fuel cycle using the SCALE 6.3.1 and Serpent-2 codes. Two different continuous refueling approaches were simulated, with the performance of each being compared to determine which is most suitable for use with the Sourdough fuel cycle concept.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Advancements in Multiphysics Microdepletion Analysis of an eVinci TM -like Microreactor Leveraging OpenMC-CRAB Workflow

Nuclear microreactors (MRs) are a class of nuclear reactor technology, characterized by reduced dimensions, modular design, and reduced power output in contrast to conventional Light Water Reactors (LWRs). MRs are proposed for supplying electricity and eventual process heat to remote locations, such as military installations and disaster-affected areas. Current research work sponsored by the US Department of Energy Microreactor Program (MRP) is devoted to the development of novel modeling and simulation tools to better support MR vendors and regulatory bodies. Notably, the NRC is projected to utilize the CRAB multiphysics software driver for executing both design and beyond-design-basis accident analyses. Furthermore, the NRC has been utilizing the MELCOR code to calculate mechanistic source terms during accidents. Since MELCOR relies on isotopic inventory and reactor temperature/power profiles under accident conditions, which theoretically can be derived from CRAB, the goal is to establish a comprehensive CRAB-MELCOR computational framework. Past work was focused on testing and demonstrating CRAB's capability to generate results that can be used to inform mechanistic source term calculations in MELCOR. In particular, a computational workflow leveraging OpenMC-generated microscopic cross sections and CRAB was first applied to perform multiphysics microscopic depletion calculation followed by an accident scenario for a stylized microreactor problem. In fiscal year 2024, the research work has been focused on applying the OpenMC-CRAB workflow, which was first tested in fiscal year 2023, to a realistic 3D heat-pipe cooled MR problem representative of the eVinci TM design. The latter computational problem was developed with inputs from WEC to conserve selected neutronic and thermal characteristics of the eVinci TM design without releasing proprietary data. The results of this simulation, encompassing isotopic inventory, power density distribution, and kinetic parameters, will inform both MELCOR and the WEC-developed FATE code for mechanistic source terms calculations. The results from the two codes will then be compared for code verification purposes. This report contains the design characteristics of the realist heat pipe cooled microreactor developed as a use-case for the verification exercise, and the current results for the multiphysics microscopic depletion performed with the OpenMC-CRAB workflow. The results include eigenvalue as a function of time, power distribution at EOL, in addition to nuclides inventory's time evolution and spatial distribution. Finally, we report improvements to the workflow efficiency achieved through a collaboration with the NEAMS programs. Through this collaborative effort, we were able to strongly decrease the computational time for the multiphysics microdepletion calculation (i.e., from 17.4 hours to 5.7 hours on 280 processors) in addition to simplifying the interface to generate isotopics spatial distribution utilizable by FATE and MELCOR. Future work, including the improvement of the current microscopic cross-sections' library and the simulation of an accident scenario at EOL, is also discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

High-fidelity parallel entangling gates on a neutral-atom quantum computer

The ability to perform entangling quantum operations with low error rates in a scalable fashion is a central element of useful quantum information processing. Neutral-atom arrays have recently emerged as a promising quantum computing platform, featuring coherent control over hundreds of qubits and any-to-any gate connectivity in a flexible, dynamically reconfigurable architecture. The main outstanding challenge has been to reduce errors in entangling operations mediated through Rydberg interactions. Here we report the realization of two-qubit entangling gates with 99.5% fidelity on up to 60 atoms in parallel, surpassing the surface-code threshold for error correction. Our method uses fast, single-pulse gates based on optimal control, atomic dark states to reduce scattering and improvements to Rydberg excitation and atom cooling. We benchmark fidelity using several methods based on repeated gate applications, characterize the physical error sources and outline future improvements. Finally, we generalize our method to design entangling gates involving a higher number of qubits, which we demonstrate by realizing low-error three-qubit gates. By enabling high-fidelity operation in a scalable, highly connected system, these advances lay the groundwork for large-scale implementation of quantum algorithms, error-corrected circuits and digital simulations.

97 MATHEMATICS AND COMPUTING↗

A WISER way for simulating the performance of gratings

Soft X-ray monochromators for synchrotron radiation sources have been continuously developed over the years, improving energy resolution and stability. Great effort has been made in improving the surface quality of the optics involved, reaching values permitting diffraction-limited images. Still, one problem has not been solved, nor fully understood, yet: groove placing errors. Nowadays, these are one of the major factors responsible for resolving the power reduction of diffraction-gratings-based X-ray monochromators. Despite decades of use of gratings, there is not yet a universally established method for predicting and simulating the effect of groove placing errors on monochromator performance. This is especially important in the new scenario of high-coherent X-ray sources, i.e. diffraction-limited storage rings and free-electron lasers. To address this problem, in this article an approach based on WISER (Wavefront propagatIon Simulation codE libRary) is presented. WISER is a physical optics simulation package, also available in the user-friendly Orange Synchrotron Radiation Suite – OASYS. Even though it was originally conceived to assess the focusing performance of X-ray mirrors in the presence of height defects, it perfectly simulates the performance of a periodic (or quasi-periodic) structure like a diffraction grating. In this article, the way to use WISER and its application to a specific case, e.g. the design of a monochromator for the upgrade of a beamline at the Advanced Light Source, are shown. A simple rule for estimating how well the grooves are placed on a grating, based on calculation of the Strehl ratio, is also presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Hydrologic Model Data for the East Fork Poplar Creek Watershed Simulated with the Advanced Terrestrial Simulator (ATS): Streamflow and Network Expansion–Contraction Dynamics

This dataset supports hydrologic modeling and stream network expansion–contraction analysis for the East Fork Poplar Creek (EFPC) Watershed in Tennessee. It includes a Jupyter notebook for model setup, model configuration files, simulation outputs, and derived products used to evaluate model performance and investigate stream dynamics under varying hydrologic conditions. The dataset was generated using the Watershed Workflow Python package and the Advanced Terrestrial Simulator (ATS), enabling integrated surface–subsurface hydrologic simulations using a stream-aligned mesh. Outputs include high-resolution time series of streamflow, active network length, water table depth, and related hydrologic variables. Also included are spatially explicit stream persistency indices and classifications of reaches as perennial or non-perennial. These data facilitate reproducibility and support further research on stream intermittency and variability in network extent.The model data archive is organized in following directories:1) model_setup_inputsContains the Watershed Workflow Jupyter notebooks (accessed through any open source code editor), selected input datasets, and resulting ATS input files, including XML files (access through any open source code editor), computational mesh (.exo files can be viewed using Paraview), and meteorological forcing files (.h5 files can be accessed through h5py python package and HDFView open source software). 2) model_outputsIncludes ATS simulation outputs relevant to this study. Time series of spatially integrated or averaged variables (e.g., streamflow, water table depth) are provided as CSV files. Select spatial fields (e.g., ponded depth and water table depth) are saved as pickled Python objects to reduce file size, and can be accessed through pickle package in Python. Key geometry objects from Watershed Workflow—such as the surface mesh and river tree—are also included to support analysis of streamflow persistency and expansion–contraction dynamics. These files can also be accessed through Watershed Workflow Python package.3) model_evaluationProvides observed streamflow time series and field survey-based flow regime classifications used to evaluate model performance. Jupyter notebooks for processing ATS outputs and comparing model predictions with observations to build confidence in the model prior to scientific analysis are also included.4) Q_L_relationshipsContains workflows for generating time series of discharge, active network length, and related hydrologic variables used in the stream network expansion–contraction analysis. Includes routines for delineating baseflow-dominated periods. For each catchment, notebooks and processed data (as pickled DataFrames accessed through Pandas Python package) are provided. 5) figure_scriptsProvides the Jupyter notebooks used to generate the figures presented in the paper.

54 ENVIRONMENTAL SCIENCES↗

Advanced Laboratory and Field Arrays: Technical Report for Performance Enhancement for Marine Energy Converter (MEC) Arrays (Task 5)

Task 5 consisted of two parts, wave energy converter (WEC) arrays and current energy converter (CEC) arrays. The two parts of the project were executed independently, and this report covers only the work on WECs. In this part of the task, the team characterized the behavior of and developed control schemes for wave energy converter (WEC) arrays that improved performance (i.e., maximized aggregate power generation and reduced the levelized cost of energy) over baseline, non-coordinated control approaches. Specifically, for WEC arrays: the team developed optimal layouts of arrays that considered the effect of WEC placement within an array on coordinated array control with real-time estimation schemes. The numerical codes developed through this task were made available to users for array design. These tools utilized existing commercial software as well as software developed within the project team.

13 HYDRO ENERGY↗