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219 records · Page 13

Simulation of Spent Nuclear Fuel loading into a Final Waste Repository

Previous work towards studying repository loading have used: - spent nuclear fuel (SNF) with an average burnup composition; - a lumped capacitance thermal model for calculating temperature in a Cyclus repository model. The goal of this work is to improve on the repository models and use U.S. historical SNF inventory data in simulations to more accurately study the loading of a waste repository. These goals will be achieved by: - using UNF-ST-and-DARDS Unified Database (UDB) that has historic assembly-specific data (e.g, isotopic composition, heat) in Cyclus simulations; - implementing a more accurate thermal model within a Cyclus repository model. Objectives: - Create a Cyclus spent fuel conditioning model that packages spent fuel bundles into packages which have user-defined properties. - Create a Cyclus medium-fidelity repository model that gives accurate time and spatial dependent temperature values and loads the repository based on a user-selected loading strategy. Cyclus is an agent-based extensible framework for modeling flow of material through user-defined nuclear fuel cycles. In Cyclus, each facility in the fuel cycle is modeled individually and the facilities interact with one another as independent agents. The spent fuel conditioning model accepts spent fuel bundles and puts them into a cylindrical waste package. In the spent fuel conditioning model, the user can define variables: For each layer, radius, thermal conductivity, thermal diffusivity; For each package, Number of spent fuel bundles, Radius and height. The waste repository model accepts waste packages and emplaces them into available positions within the waste repository based on a thermal criteria. The thermal criteria is a temperature limit at the interface between the waste package surface and the host geology, that is set based on the repository's host geology. In the waste repository model, the user can define the variables: Capacity, Distance between waste packages, Distance between drifts, Repository host geology, Loading Strategy. After the addition of new waste packages at each time step, the waste repository model recalculates the temperature at each location in the repository. If the addition of this new package causes its temperature to exceed the thermal limit, it will be placed back into the buffer. A thermal model that relies on a transient 'outside' model and quasi-steady-state 'inside' model is used to accurately determine the temperature in the repository. The 'outside' model assumes a homogenous medium with the Engineered Barrier System (EBS) replaced by the geologic medium. Temperature solutions for the central waste package, adjacent point and line sources are superimposed to calculate the temperature at specific points in the repository. The central drift consists of one finite line source which represents the central waste package. The central drift also consists of point sources that represent neighboring waste packages in the central drift. The neighboring drifts are represented by infinite line sources. The 'inside' model is considered to be at a quasi-steady-state condition because EBS has a relatively low thermal mass compared to the infinite geologic medium. The steady state calculation is performed at each time step with the heat source and interface temperature as boundary conditions. Future Work: Run Cyclus simulations with U.S. historical SNF inventory data, the spent fuel conditioning and repository models to study how waste package acceptance strategies impact repository loading.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

National Modeling of Geothermal District Energy Systems with Ambient-Temperature Loops Using dGeo: Preprint

Geothermal district energy systems (DES) with ambient-temperature loops, also known as thermal energy networks, are one option for decarbonizing space heating and cooling loads. Geothermal fifth-generation DES include an "ambient" temperature thermal loop that connects heat pumps at each building with thermal balancing sources such as geothermal borehole fields. Heating and cooling are provided via a water-source heat pump at each end-user. This project seeks to analyze the nationwide potential for ambient-temperature loop districts by creating a new module within the Distributed Geothermal Market Demand Model (dGeo). dGeo is an agent-based modeling tool for distributed geothermal resources; it can investigate potential on a nationwide or statewide scale using geospatial data for all 50 states and thermal demands for existing buildings. This process allows for high-level estimates of technical and economic potential for ambient-temperature loop districts across the United States. Using GHEDesigner, a lookup table was created to size borehole fields for different thermal loads and ground conditions experienced across the country. A cost and financing structure, along with incentives, were applied. Cost estimates include costs for the distribution network, borehole field installation and operation, and circulation pump operation, while savings are calculated based on agent energy bills. This newly developed module can be used for assessing which areas of the country have the highest potential for agent benefits from ambient-temperature loop installation and assess the impact of different costing and pricing future scenarios. While the code is still under development and nationwide simulations are ongoing, initial results for two states are provided. Future work includes expanding the module to consider mixed residential and commercial districts and considering multiple costing scenarios.

ambient temperature loop↗

BEAM CORE: A Flexible Ecosystem for Freight, Demographics, and Vehicle Analysis

The Behavior, Energy, Autonomy, and Mobility Comprehensive Regional Evaluator (BEAM CORE) is an open-source, modular ecosystem of highly refined, agent-based modeling tools developed by Lawrence Berkeley National Laboratory and the National Laboratory of the Rockies. Organizations such as metropolitan planning organizations, agencies, and companies can use BEAM CORE to analyze freight movement and optimize logistics solutions, assess the impacts of emerging freight technologies or e-commerce trends, model dynamic population growth and evolution, and understand the drivers and impacts of electric vehicle adoption across households in a given region. Users can choose from a flexible suite of modeling modules according to their needs and priorities. The modules integrate with travel demand models to support enhanced analysis of diverse scenarios involving freight movement, vehicle technologies, and other key factors relevant to regional planning.

33 ADVANCED PROPULSION SYSTEMS↗