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Renewable Energy Atlas of the United States

The Renewable Energy Atlas (Atlas) of the United States is a compilation of geospatial data focused on renewable energy resources, federal land ownership, and base map reference information. It is designed for the U.S. Department of Agriculture Forest Service (USFS) and other federal land management agencies to evaluate existing and proposed renewable energy projects. Much of the content of the Atlas was compiled at Argonne National Laboratory (Argonne) to support recent and current energy-related Environmental Impact Statements and studies, including the following projects: (1) West-wide Energy Corridor Programmatic Environmental Impact Statement (PEIS) (BLM 2008); (2) Draft PEIS for Solar Energy Development in Six Southwestern States (DOE/BLM 2010); (3) Supplement to the Draft PEIS for Solar Energy Development in Six Southwestern States (DOE/BLM 2011); (4) Upper Great Plains Wind Energy PEIS (WAPA/USFWS 2012, in progress); and (5) Energy Transport Corridors: The Potential Role of Federal Lands in States Identified by the Energy Policy Act of 2005, Section 368(b) (in progress). This report explains how to add the Atlas to your computer and install the associated software; describes each of the components of the Atlas; lists the Geographic Information System (GIS) database content and sources; and provides a brief introduction to the major renewable energy technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Fuel Cycle Research & Development Technical Monthly-March 2012

Several MPACT BCPs were executed in February, reflecting the shift in MPACT priorities directed late last year. Work continued on the FY2014 IPL, also bringing it in line with the new priorities. Preparations were made for the March MPACT Working Group meeting, in conjunction with Savannah River which is hosting the meeting. Steps were taken to initiate a new project with the World Institute for Nuclear Security, including discussions with WINS staff and preliminary work on the required procurement documentation. Several hardware issues were worked through. The newest detector array is working at LANL. A thorough analysis of previously collected Pu sample data using recently developed analysis code with improved spectral energy calibrations was completed. We now have a significantly better understanding of measurement uncertainties.

08 HYDROGEN↗

Predictive Maturity of Multi-Scale Simulation Models for Fuel Performance

The project proposed to provide a Predictive Maturity Framework with its companion metrics that (1) introduce a formalized, quantitative means to communicate information between interested parties, (2) provide scientifically dependable means to claim completion of Validation and Uncertainty Quantification (VU) activities, and (3) guide the decision makers in the allocation of Nuclear Energy’s resources for code development and physical experiments. The project team proposed to develop this framework based on two complimentary criteria: (1) the extent of experimental evidence available for the calibration of simulation models and (2) the sophistication of the physics incorporated in simulation models. The proposed framework is capable of quantifying the interaction between the required number of physical experiments and degree of physics sophistication. The project team has developed this framework and implemented it with a multi-scale model for simulating creep of a core reactor cladding. The multi-scale model is composed of the viscoplastic self-consistent (VPSC) code at the meso-scale, which represents the visco-plastic behavior and changing properties of a highly anisotropic material and a Finite Element (FE) code at the macro-scale to represent the elastic behavior and apply the loading. The framework developed takes advantage of the transparency provided by partitioned analysis, where independent constituent codes are coupled in an iterative manner. This transparency allows model developers to better understand and remedy the source of biases and uncertainties, whether they stem from the constituents or the coupling interface by exploiting separate-effect experiments conducted within the constituent domain and integral-effect experiments conducted within the full-system domain. The project team has implemented this procedure with the multi- scale VPSC-FE model and demonstrated its ability to improve the predictive capability of the model. Within this framework, the project team has focused on optimizing resource allocation for improving numerical models through further code development and experimentation. Related to further code development, we have developed a code prioritization index (CPI) for coupled numerical models. CPI is implemented to effectively improve the predictive capability of the coupled model by increasing the sophistication of constituent codes. In relation to designing new experiments, we investigated the information gained by the addition of each new experiment used for calibration and bias correction of a simulation model. Additionally, the variability of ‘information gain’ through the design domain has been investigated in order to identify the experiment settings where maximum information gain occurs and thus guide the experimenters in the selection of the experiment settings. This idea was extended to evaluate the information gain from each experiment can be improved by intelligently selecting the experiments, leading to the development of the Batch Sequential Design (BSD) technique. Additionally, we evaluated the importance of sufficiently exploring the domain of applicability in experiment-based validation of high-consequence modeling and simulation by developing a new metric to quantify coverage. This metric has also been incorporated into the design of new experiments. Finally, we have proposed a data-aware calibration approach for the calibration of numerical models. This new method considers the complexity of a numerical model (the number of parameters to be calibrated, parameter uncertainty, and form of the model) and seeks to identify the number of experiments necessary to calibrate the model based on the level of sophistication of the physics. The final component in the project team’s work to improve model calibration and validation methods is the incorporation of robustness to non-probabilistic uncertainty in the input parameters. This is an improvement to model validation and uncertainty quantification stemming beyond the originally proposed scope of the project. We have introduced a new metric for incorporating the concept of robustness into experiment-based validation of numerical models. This project has accounted for the graduation of two Ph.D. students (Kendra Van Buren and Josh Hegenderfer) and two M.S. students (Matthew Egeberg and Parker Shields). One of the doctoral students is now working in the nuclear engineering field and the other one is a post-doctoral fellow at the Los Alamos National Laboratory. Additionally, two more Ph.D. students (Garrison Stevens and Tunc Kulaksiz) who are working towards graduation have been supported by this project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Transport-reaction model for defect and carrier behavior within displacement cascades in gallium arsenide

A model is presented for recombination of charge carriers at displacement damage in gallium arsenide, which includes clustering of the defects in atomic displacement cascades produced by neutron or ion irradiation. The carrier recombination model is based on an atomistic description of capture and emission of carriers by the defects with time evolution resulting from the migration and reaction of the defects. The physics and equations on which the model is based are presented, along with details of the numerical methods used for their solution. The model uses a continuum description of diffusion, field-drift and reaction of carriers and defects within a representative spherically symmetric cluster. The initial radial defect profiles within the cluster were chosen through pair-correlation-function analysis of the spatial distribution of defects obtained from the binary-collision code MARLOWE, using recoil energies for fission neutrons. Charging of the defects can produce high electric fields within the cluster which may influence transport and reaction of carriers and defects, and which may enhance carrier recombination through band-to-trap tunneling. Properties of the defects are discussed and values for their parameters are given, many of which were obtained from density functional theory. The model provides a basis for predicting the transient response of III-V heterojunction bipolar transistors to pulsed neutron irradiation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Comparison of Monte Carlo and Deterministic Solvers for keff and Sensitivity Calculations

Verification and validation of our solutions for calculating the neutron reactivity for nuclear materials is a key issue to address for many applications, including criticality safety, research reactors, power reactors, and nuclear security. Neutronics codes solve variations of the Boltzmann transport equation. The two main variants are Monte Carlo versus deterministic solutions, e.g. the MCNP [1] versus PARTISN [2] codes, respectively. There have been many studies over the decades that examined the accuracy of such solvers and the general conclusion is that when the problems are well-posed, either solver can produce accurate results. However, the devil is always in the details. The current study examines the issue of self-shielding and the stress it puts on deterministic solvers. Most Monte Carlo neutronics codes use continuous-energy descriptions of the neutron interaction data that are not subject to this effect. The issue of self-shielding occurs because of the discretisation of data used by the deterministic solutions. Multigroup data used in these solvers are the average cross section and scattering parameters over an energy range. Resonances in cross sections can occur that change the likelihood of interaction by one to three orders of magnitude over a small energy range. Self-shielding is the numerical effect that the average cross section in groups with strong resonances can be strongly affected as neutrons within that material are preferentially absorbed or scattered out of the resonance energies. This affects both the average cross section and the scattering matrix.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Windows and Envelope R&D Opportunities Workshop

BTO's Emerging Technologies program held a two-day workshop on “Windows and Envelope R&D Opportunities” on May 31 and June 1, 2017 at the Illinois Institute of Technology in Chicago, Illinois. A broad range of about 100 experts from industry, academia, national laboratories, and government participated, contributing their ideas, insights, and perspectives. Their feedback is intended to help inform and augment BTO’s research and development activities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Energy Savings Analysis: 2018 IECC for Residential Buildings

DOE and Pacific Northwest National Laboratory (PNNL) conducted a technical analysis to determine energy savings for the 2018 IECC residential provisions relative to the previous edition, the 2015 IECC. This report documents the methodology used to conduct the analysis and summarizes the results and findings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

MCNP ® Code V.6.3.0 Release Notes

The Monte Carlo N-Particle ® (MCNP ® ) code is a general-purpose, continuous-energy, generalized geometry, time-dependent, radiation transport code developed by the MCNP development team. The MCNP calculations provide predictive capabilities that can replace expensive or impossible-to perform experiments. Specific application problems include simulations of experimental diagnostics, intrinsic radiation, radiation detection and measurement, criticality safety, nuclear threat reduction and response, radiation health protection, nuclear weapons effects, and nuclear forensics. This MCNP code, version 6.3.0, follows the MCNP6.2.0 version. Since the release of MCNP6.2.0, many changes have been made to the MCNP code. These changes include new or improved features, a new build system, code enhancement and modernization, and bug fixes. The MCNP code, version 6.3.0, theory and user input information is documented in MCNP ® Code Version 6.3.0 Theory & User Manual, the build guidance for various platforms is documented in MCNP ® Code Version 6.3.0 Build Guide, and the verification and validation testing for various application benchmark test suites is documented in MCNP ® Code Version 6.3.0 Verification & Validation Testing.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Write-up on the analytical formalism for DTL Synchrotron and Betatron frequencies estimates

Appendix A contains tables of the DTL tanks geometry, generated using PARMILA code with input parameters of initial and final energy, accelerating gradient, synchronouse phase, and using DTLfish code (part of the SUPERFISH/POISSON package of codes). Details of the design and generation od the DTL geometry will be presented in a separate report. After generation of the DTL geometry and initial beam dynamics simulations, the analytic estimates of the synchrotron and betatron oscillations, as well as presence of the parametric resonance of first order were done. In present report the analytic background of those estimates, as well as the results of these are presented.

43 PARTICLE ACCELERATORS↗

Dust Formation and Destruction in Core Collapse Supernovae Explosions [Dissertation]

Dust is a crucial component of the Interstellar Medium (ISM) and an important driver in many astrophysical processes. Dust formed from evolved stars increases the metallicity of the ISM, enriching it with heavier elements. Dust makes up the source material of collapsing clouds in the ISM leading to stellar and galactic formation. The stabilization of these systems are aided by dust through absorption and scattering of excess energy. As stellar systems evolve and undergo supernova and mass loss events, enriched dust is produced, further enhancing the metallicity of the ISM. However, despite the importance of dust, the processes that produce dust are not well understood. Core-Collapse Supernovae are one source of dust. Dying massive stars explode, sending their constituent material into the Interstellar Medium, which as the ejecta expands and cools, material condenses and nucleates forming dust grains. I investigate the formation, survivability, and properties of dust. In Chapter 2, dust grain nucleation in CCSNe is discussed. A revised formulation of Kinetic Nucleation Theory (KNT) is used to track the nucleation and growth of dust grains in the ejecta. The affects of the progenitor system on the amount and type of dust is explored, showing a strong dependence on explosion energy. I discuss the code and methods used to model dust nucleation and destruction in Chapter 3. The sputtering and erosion of dust grains in CCSNe shocks are explored in Chapter 4. The erosion and survival of this nucleated dust is modeled through thermal and non-thermal sputtering by the surrounding gas and shocks. The optical properties and scattering of light by surviving dust grains is modeled by Mie scattering in Chapter 5. A discussion of observations of dust in variable star systems and supernovae is outlined in Chapter 6.

79 ASTRONOMY AND ASTROPHYSICS↗

Simulating Muon Capture with MARLEY

Core-collapse supernovae are intense sources of tens-of-MeV neutrinos. Each explosion releases about 1058 neutrinos in a burst lasting tens of seconds. As neutrinos are weakly interacting, they escape more easily compared to photons, allowing them to be observed before the light signal. Understanding low-energy neutrino interactions with argon will be critical for future supernova measurements with the Deep Underground Neutrino Experiment (DUNE). Interpreting future DUNE supernova neutrino data will require a high-quality model of O(10 MeV) neutrino interactions, but the dominant charged-current cross section has never been measured at these low energies for an argon target. We exploit the theoretical similarities between muon capture, which has been measured, and antineutrino scattering to test MARLEY (Model of Argon Reaction Low Energy Yields), the simulation code used by DUNE to model supernova neutrino reactions. I implemented C++ code to add a muon capture mode to MARLEY and compared the predictions of the new simulation to measured isotope branching ratios of the residual nuclei. The preliminary branching ratios predicted by MARLEY running in muon capture mode demonstrate promising baseline performance when compared to experimental data and are expected to improve with further model adjustments.

Wong, Baker Louie↗

Gearbox Reliability Collaborative: Gearbox Inspection Metadata

NREL has developed a software application called GearFacts that will be distributed to Database Collaborative participants to capture failure information when gearboxes are rebuilt. This publication names and describes each field used in GearFacts and can be used as a reference to the software's design.

17 WIND ENERGY↗

Optimizing Laser-accelerated Ion Beams for a Collimated Neutron Source

High-flux neutrons for imaging and materials analysis applications have typically been provided by accelerator- and reactor-based neutron sources. A novel approach is to use ultraintense (>1018W/cm2) lasers to generate picosecond, collimated neutrons from a dual target configuration. In this article, the production capabilities of present and upcoming laser facilities are estimated while independently maximizing neutron yields and minimizing beam divergence. A Monte-Carlo code calculates angular and energy distributions of neutrons generated by D-D fusion events occurring within a deuterated target for a given incident beam of D+ ions. Tailoring of the incident distribution via laser parameters and microlens focusing modifies the emerging neutrons. Projected neutron yields and distributions are compared to conventional sources, yielding comparable on-target fluxes per discharge, shorter time resolution, larger neutron energies and greater collimation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fault detection in PV systems

A practical fault detection approach for PV systems intended for online implementation is developed. The fault detection model here is built using artificial neural network. initially the photovoltaic system is simulated using MATLAB software and output power is collected for various combinations of irradiance and temperature. Data is first collected for normal operating condition and then four types of faults are simulated and data are collected for faulty conditions. Four faults are considered here and they are: Line to Line faults with a small voltage difference, Line to line faults with a large voltage difference, degradation fault and open-circuit fault. This data is then used to train the neural network and to develop the fault detection model. The fault detection model takes irradiance, temperature and power as the input and accurately gives the type of fault in the PV system as the output. This system is a generalized one as any PV module datasheet can be used to simulate the Photovoltaic system and also this fault detection system can be implemented online with the use of data acquisition system.

14 SOLAR ENERGY↗

Benchmarking of three DWM-based wake models at below-rated wind speeds

Wind turbine wake models are essential tools for predicting power losses and structural loads in wind farms. Among these, the dynamic wake meandering (DWM) model, included as a recommended approach in the International Electrotechnical Commission design standard, is a widely used engineering-fidelity method that balances accuracy and computational cost. This study compares the performance of three DWM-based wake model implementations (from the Technical University of Denmark, the National Renewable Energy Laboratory, and the Institute for Energy Technology) under below-rated wind speed conditions. Model predictions of wake flow, power output, and structural loads for a four-turbine row are evaluated across different ambient turbulence levels and wind-direction misalignments and compared against high-fidelity large-eddy simulation results. All three models captured the overall wake evolution and mean turbine performance with reasonable accuracy; their predicted time-averaged thrust and power were typically within 5 %–10 % of the large-eddy simulation benchmark. However, notable differences emerged in wake structure and unsteady load predictions, with discrepancies increasing for turbines further downstream. These differences highlight the importance of modelling choices such as wake summation and turbulence treatment, which strongly influence power-deficit and fatigue-load predictions. Comparison with large-eddy simulations reveals each approach's strengths and weaknesses, indicating where improvements are needed. Overall, the findings point to specific refinements for DWM models to improve their fidelity, ultimately enabling more robust wake predictions for wind farm design and operation.

17 WIND ENERGY↗

Spatiotemporal evolution of runaway electrons from synchrotron images in Alcator C-Mod

In the Alcator C-Mod tokamak, relativistic runaway electron (RE) generation can occur during the flattop current phase of low density, diverted plasma discharges. Due to the high toroidal magnetic field (B0 = 5.4 T), RE synchrotron radiation is measured by a wide-view camera in the visible wavelength range (~400-900 nm). In this paper, a statistical analysis of over one thousand camera images is performed to investigate the plasma conditions under which synchrotron emission is observed in C-Mod. In addition, the spatiotemporal evolution of REs during one particular discharge is explored in detail via a thorough analysis of the distortion-corrected synchrotron images. To accurately predict RE energies, the kinetic solver CODE [Landreman et al 2014 Comput. Phys. Commun. 185 847-855] is used to evolve the electron momentum-space distribution at six locations throughout the plasma: the magnetic axis and flux surfaces q = 1, 4/3, 3/2, 2, and 3. These results, along with the experimentally-measured magnetic topology and camera geometry, are input into the synthetic diagnostic SOFT [Hoppe et al 2018 Nucl. Fusion 58 026032] to simulate synchrotron emission and detection. Interesting spatial structure near the surface q = 2 is found to coincide with the onset of a locked mode and increased MHD activity. Furthermore, the RE density profile evolution is fit by comparing experimental to synthetic images, providing important insight into RE spatiotemporal dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗