Description and Use of SCALE Sampler Parametric Capability for Engineering Analysis and Optimization [Slides]
Abstract not provided.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
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Cambium 2022 Scenario Descriptions and Documentation
The National Renewable Energy Laboratory’s (NREL’s) Cambium data sets are annually released sets of simulated hourly emission, cost, and operational data for a range of modeled futures of the U.S. electric sector with metrics designed to be useful for long-term decision making. The 2022 Cambium data set is the third annual release. The data sets are a companion product to NREL’s Standard Scenarios, which are likewise released annually and are a set of projections of how the U.S. electric sector could evolve across a suite of different potential futures, but covering more scenarios with less temporal granularity. In this documentation, we describe Cambium 2022’s scenarios (Section 3), define the metrics (Section 5), and document the Cambium-specific methods for calculating those metrics (Section 6).
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Preliminary IHLW Formulation Algorithm Description
This report documents the initial algorithm that could be used by the Waste Treatment and Immobilization Plant (WTP) in batching high-level waste (HLW) and glass-forming chemicals (GFCs) in the HLW melter feed preparation vessel (MFPV) (HFP-VSL-00001 and -00005). Not all Hanford tank waste can be accommodated by the models developed for this report and significant expansion of the model boundaries could be achievable to reduce the WTP mission life and total canister production count. The immobilized HLW (IHLW) must meet a series of constraints to be acceptable for disposal in the Monitored Geologic Repository, which are contained in the Specification 1 of the Contract (DOE 2000), the Waste Acceptance Product Specifications (WAPS, DOE 1996), and the Waste Acceptance System Requirements Document (WASRD, DOE 2007). The IHLW Waste Form Compliance Plan (WCP, 24590-HLW-PL-RT-07-0001, Rev 3) specifies that the formulation algorithm will be developed and used to comply with the constraints associated with glass composition and properties. This report is not an engineering calculation, does not provide design input, and is not an engineering study. Algorithm inputs include the chemical analyses of the blended HLW in the HLW blend vessel (HBV) (HLP-VSL-00028, the volume and composition of the MFPV heel, the volume and composition of the MFPV after waste addition, the volume and composition of MFPV batch after GFC addition, the compositions of individual GFCs, and the mass of glass in each canister. In addition to these inputs, uncertainties in the HLW composition and processing parameters are included in the algorithm. Using the above inputs, the algorithm calculates the following outputs: 1) the volume of HLW to be transferred from the HBV to the MFPV, 2) the mass of each GFC for addition to the MFPV, 3) the composition of the glass that will be produced along with uncertainties, and 4) the predicted properties, with associated uncertainties, of the resulting IHLW. The algorithm uses the property-composition models to calculate properties with associated uncertainties and compares them with various constraints to ensure that a processable feed is formulated and a compliant IHLW is produced. The GFC additions are determined using an optimization approach to provide high confidence that the HLW glass will meet all product quality requirements and key processing constraints. For most HLW batches there are many possible glass compositions that meet all constraints. In these cases, the glass composition is optimized for a series of target component concentrations and target property values. The algorithm also incorporates process measurement and product quality uncertainties, based on the work of Piepel et al. (2005). Estimates of the various process and measurement uncertainties that affect glass compositions and predicted glass properties have been previously reported (Piepel et al. 2005, 2006) and the impacts of these estimated uncertainties on the IHLW composition envelope that meets product quality and processing-related properties with sufficient confidence were evaluated. The details of work performed to date to develop this initial GFC addition and batching algorithm are summarized in Sections 4 and 5. An example data set is used to illustrate the calculations of the algorithm summarized in Section 6. Finally, in Section 7, there is a statement of the required work to achieve a final operational IHLW formulation control algorithm. This report is not an engineering calculation, does not provide design input, and is not an engineering study.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Requirements Description of the REBUS Software for the Versatile Test Reactor
This report presents the modeling and simulation capabilities of Argonne National Laboratory’s fuel cycle analysis code, the REactor BUrnup System (REBUS), that will be relied on for the VTR project. These capabilities will then be used to establish the set of REBUS verification tasks necessary to verify REBUS for usage on the VTR project. A similar path was followed for the DIF3D software where its’ requirements and verification tasks were established. REBUS has been maintained by Argonne since the early 1960s to support its reactor design mission. That software transitioned from the original REBUS to REBUS-2 in the mid 1970s and to REBUS-3 in the mid 1980s. Since then REBUS has gone through many revisions to the current REBUS-11. Note that this version numbering is consistent with the progression of DIF3D, the base flux solver that REBUS is built upon. The name REBUS refers to a pictorial based puzzle as the original developers were inspired by having to track thousands of unique fuel assemblies as they are inserted into the reactor, depleted, shuffled, discharged, and reprocessed.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Specifications of EBR-II Neutron Radiography Method Description and Digitization Approach
All neutron radiography (NRAD) images of fuel pins in Argonne’s collection were originally generated using the NRAD imaging facility established in the Hot Fuel Examination Facility (HFEF) at Idaho National Laboratory (INL). The NRAD reactor facility was built in 1977 and has been operating since. The reactor is a TRIGA-type reactor operating at a power level of 250 kWth to provide a neutron source for radiography imaging. The reactor is equipped with two beam tubes (i.e., east beam tube and north beam tube) to guide the neutron beams to two radiography stations. The east radiography station is directly under the HFEF main cell and is dedicated for specimens already in the HFEF hot cell. The north radiography station is outside of the main HFEF hot cell and allows NRAD imaging of non-irradiated items. The NRAD images of EBR-II irradiated metallic fuel pins were taken in the east radiography station. Thermal neutrons have the capability to transmit through most materials and are ideal for NRAD imaging. However, because of their high thermal neutron absorption cross-section, fissile materials (e.g., highly-enriched nuclear fuels) may not be as transmissible to thermal neutrons. This is also the case for oversize specimens with extraneous thickness. Epithermal neutron imaging is therefore used as a complement to thermal neutron NRAD imaging. At HFEF’s NRAD facility, both thermal and epithermal neutrons can be used for NRAD imaging. Irradiated nuclear fuels emit high levels of γ radiation that can easily darken X-ray films, so direct exposure NRAD cannot be used to image them. Instead, an indirect NRAD imaging method was developed at HFEF’s NRAD facility. In this method, foils made of materials that can be activated by neutrons (i.e., with large neutron absorption cross section) are used to collect transmitted neutron signals. Then the activated foils are then placed against X-ray films and enclosed in a vacuum cassette so that the γ decay from the activated foils can produce images on the X-ray films. Then, general X-ray film processing procedures are used to digitize and store the images. By using different foil materials, different energy neutrons can be used for NRAD imaging. At the HFEF NRAD station, two types of films are commonly used: dysprosium (Dy) foils with thickness of 130 microns are used to capture thermal neutron signal, while indium (In) foils with thickness of 130 microns are used to capture epithermal neutron signal. A cadmium or gadolinium foil is put before the indium foil to work as a thermal neutron filter. The thermal and epithermal NRAD images can be taken simultaneously by using a Dy/Cd/In sandwiched foil combination. The typical NRAD exposure time is approximately 20 minutes. Then the exposed foils are transferred to film vacuum cassettes. The vacuum ensures that there is no gap between the foil and the film. The foil-to-film exposure time is at least three half-lives of the corresponding radioisotopes, which are 3 hours for In and 7.5 hours for Dy, respectively. Exposed films are processed using an automatic film processor to produce completed NRAD images.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Effects of spin-orbit coupling and very large supercells on the description of acceptors in CdTe
Predicting accurate shallow donor and acceptor levels in semiconductors has been quite challenging using periodic boundary conditions as implemented in current density functional theory codes. The reason is that the wave functions associated with the shallow centers are quite extended and are not fully contained in the supercell (typically with a few hundred atoms) so impurities in the periodically repeated image cells interact with each other. Errors of ~0.1 eV are expected, and these are of the same order of magnitude as the ionization energies themselves. In the case of acceptors in CdTe, this problem is exacerbated by the strong spin-orbit coupling that split the Te-related states at the top of the valence band, making the calculations at least 8 times more expensive. CdTe is an important solar-cell material with record high efficiency of 22%. One of the main limiting factors to increasing the efficiency towards the theoretical limit of ~30% is the often reported very low hole concentration. Pushing to the limit of computational capability by using very large supercells with spin-orbit coupling we report the results of hybrid functional calculations of group-V acceptors in CdTe. We show that extrapolation to the dilute limit leads to an interpretation of the experimental data that is qualitatively different from previous DFT and hybrid functional calculation reports. We find that the group-V impurities indeed behave as shallow acceptors and that the corresponding compensating AX-centers are unstable and do not limit p-type doping. We address the differences between our results and previous theoretical predictions and show that our calculated ionization energies predict hole concentrations that are in excellent agreement with recent temperature-dependent Hall measurements on high-quality single-crystal samples.
14 SOLAR ENERGY↗
FECM/NETL CO 2 Transport Cost Model (2023): Description and User’s Manual
The FECM/NETL CO 2 Transport Cost Model (CO 2 _T_COM) is an Excel spreadsheet model that calculates the cost of transporting CO 2 from the beginning to the end of a pipeline. This document provides two main functions. First, the document describes the equations and algorithms that are used by the model to calculate technical quantities (such as the minimum inner pipe diameter needed to transport a user-specified CO 2 mass flow rate a specified distance) and engineering-economic quantities (such as capital costs, operating costs and cash flows). Second, the document is a user’s manual for the model that describes the procedures the user must follow to run the model. The document also describes input variables and output variables (i.e., results) for the model. The model can be accessed at this URL: https://www.netl.doe.gov/energy-analysis/details?id=d3086f60-278d-4e97-a649-8e4d5ce5e93c
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
805 Stepped Plan Project Description
The 805 MHz system utilizes 1.25 MW class klystron amplifiers. The Solid-State Amplifier (SSA) technology has been utilized in the SC accelerator technology, but more powerful sources are needed for use in the NC accelerator facilities such as LASNCE. The SSA topologies that are widely used need to be scaled and tested for reliability and operation in a high impact accelerator facility, such as the 805 MHz SCCL in Los Alamos. Operational experience with high power SSA needs to be assessed prior to installation of an SSA unit at LANSCE. The RFE group at LANSCE is looking for collaboration in the development of the Solid-State Amplifier.
43 PARTICLE ACCELERATORS↗
Description of SIS-AOP Result Format V1.0
Single Image SICD-Based Automatic Object Processing (SIS-AOP) is an automatic object identification tool for SAR imagery. It ingests a SAR image in standard SICD format, and it will run a suite of algorithms to cue possible vehicle detections, cull those detections and then ultimately label them either as detections only or possible expound to give a class-level ID or a vehicle-type ID. The SIS-AOP results are given in an XML (Extensible Markup Language) output format. This document defines the elements in the SISAOPR XML output format.
97 MATHEMATICS AND COMPUTING↗
Atomic structure description of interface disorder in Si/SiGe thin-film heterostructures .
Abstract not provided.
Bussmann, Ezra↗
Another Set of Python Tools for Visualizing and Manipulating Small-Angle Neutron Scattering Data: Descriptions and Examples
The GP-SANS, Bio-SANS and EQ-SANS instruments at ORNL utilize drtsans for data reduction. drtsans is built on Python, and it can be run using python scripts and Jupyter notebooks. The flexibility afforded by Python makes it possible to incorporate additional actions into the scripts used for data reduction, such as analysis and visualization. Here, a new set of tools for visualizing and manipulating SANS data that can be incorporated into the data reduction scripts for the ORNL SANS instruments, or employed during post–processing, is presented that expands the capabilities of the two previously-released tool sets.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Cambium 2023 Scenario Descriptions and Documentation
The National Renewable Energy Laboratory's (NREL's) Cambium data sets are annually released sets of simulated hourly emission, cost, and operational data for a range of modeled futures of the U.S. electric sector with metrics designed to be useful for long-term decision- making. The 2023 Cambium data set is the fourth annual release. The data sets are a companion product to NREL's Standard Scenarios, which are likewise released annually and are a set of projections of how the U.S. electric sector could evolve across a suite of different potential futures, but covering more scenarios with less temporal granularity (Gagnon et al. 2024). Information about Cambium and related publications can be found at https://www.nrel.gov/analysis/cambium.html, and the Cambium data sets can be viewed and downloaded at https://scenarioviewer.nrel.gov/. In this documentation, we describe Cambium 2023's scenarios, define the metrics, and document the Cambium-specific methods for calculating those metrics.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Requirements Description of VARPOW
This report presents the modeling and simulation capabilities of Argonne National Laboratory’s VARPOW code [1] that is used in present reactor analysis activities. These capabilities will then be used to establish the set of VARPOW verification tasks necessary to verify VARPOW for usage on commercial projects. A similar approach was taken for the PERSENT, REBUS and DIF3D software packages. The VARPOW program is a post-processing utility program for DIF3D, specifically DIF3DVARIANT. As covered in [1], the VARPOW program was built to provide input for follow-on steady state thermal-hydraulic analysis. Its primary purpose is to act as the interface between DASSH and DIF3D-VARIANT. The outputs from VARPOW are contained in three output files: Output.VARPOW, VariantMonoExponents.out, and MaterialPower.out.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Requirements Description of EvaluateFlux
This report presents the modeling and simulation capabilities of Argonne National Laboratory’s EvaluateFlux code [1] that is used in present reactor analysis activities. These capabilities will then be used to establish the set of EvaluateFlux verification tasks necessary to verify EvaluateFlux for usage on commercial projects. A similar approach was taken for the PERSENT, REBUS and DIF3D software packages. The EvaluateFlux program is a post-processing utility program for DIF3D, specifically DIF3D-VARIANT. As covered in [1], the EvaluateFlux program was built to allow users to obtain flux and power traverses through the domain. Its primary purpose was to facilitate foil analysis by evaluating the flux solution from DIF3D-VARIANT and combining it with foil cross section data. The outputs from EvaluateFlux are contained in four possible output files: FluxAndRegionRR.out, IsotopeMicroRR.out, LabeledRegionRR.out, and IsotopeMacroRR.out. Each file is focused on using the flux evaluate and cross section data in a different manner and all are covered in this verification process.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
FECM/NETL Hydrogen Pipeline Cost Model (2024): Description and User’s Manual
The FECM/NETL Hydrogen Pipeline Cost Model (H2_P_COM) estimates costs for transporting gaseous hydrogen in a pipeline from a source, such as a hydrogen production facility, to a final destination which may be a user of the hydrogen or a distribution center where hydrogen in the pipeline is diverted to multiple end users. This document provides two main functions. First, the document describes the equations and algorithms that are used by the model to calculate technical quantities (such as the minimum inner pipe diameter needed to transport a user-specified H 2 mass flow rate a specified distance) and engineering-economic quantities (such as capital costs, operating costs, and cash flows). Second, the document is a user’s manual for the model that describes the procedures the user must follow to run the model. The model can be accessed at this URL: https://www.netl.doe.gov/energy-analysis/details?id=db897190-8e26-40b1-9535-ee78ac934193
08 HYDROGEN↗
Response to Questionnaire of Grid Control Architecture Description Document: Mission Innovation, Innovation Challenge 1. Task 5 – New Grid Control Architectures. Subtask 5.1 – Collection of Available New Grid Control Architectures
As part of Task 5 (New Grid Control Architectures) of Mission Innovation, Innovation Challenge 1, a questionnaire was provided to all countries participating in the project. In this document, PNNL has responded to the questionnaire with information regarding new grid control architectures being proposed or developed in the US. Ron Melton sent the report to all participants.
24 POWER TRANSMISSION AND DISTRIBUTION↗
A Physics-Informed Deep Learning Description of Knudsen Layer Reactivity Reduction
A physics-informed neural network (PINN) is used to evaluate the fast ion distribution in the hot spot of an inertial confinement fusion target. The use of tailored input and output layers to the neural network is shown to enable a PINN to learn the parametric solution to the Vlasov–Fokker–Planck equation in the absence of any synthetic or experimental data. As an explicit demonstration of the approach, the specific problem of Knudsen layer fusion yield reduction is treated. Here, the predictions from the Vlasov–Fokker–Planck PINN are used to provide a non-perturbative solution of the fast ion tail in the vicinity of the hot spot, thus allowing the spatial profile of the fusion reactivity to be evaluated for a range of collisionalities and hot spot conditions. Excellent agreement is found between the predictions of the Vlasov–Fokker–Planck PINN and the results from traditional numerical solvers with respect to both the energy and spatial distribution of fast ions and the fusion reactivity profile, demonstrating that the Vlasov–Fokker–Planck PINN provides an accurate and efficient means of determining the impact of Knudsen layer yield reduction across a broad range of plasma conditions.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗