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DOE OSTI2025

Assessing the suitability of sites near Pine Island Glacier for subglacial bedrock drilling aimed at detecting Holocene retreat–readvance

Abstract. Unambiguous identification of past episodes of ice sheet thinning below the modern surface and grounding line retreat inboard of present requires recovery and exposure dating of subglacial bedrock. Such efforts are needed to understand the significance and potential future reversibility of ongoing and projected change in Antarctica. Here we evaluate the suitability for subglacial bedrock drilling of sites in the Hudson Mountains, which are located in the Amundsen Sea sector of West Antarctica. We use an ice sheet model and field data – geological observations, glaciological observations and bedrock samples from nunataks, and ground-penetrating radar from subglacial ridges – to rate each site against four key criteria: (i) presence of ridges extending below the ice sheet, (ii) likelihood of increased exposure of those ridges if the grounding line was inboard of present, (iii) suitability of bedrock for drilling and geochemical analysis, and (iv) accessibility for aircraft and drilling operations. Our results demonstrate that although no site in the Hudson Mountains is perfect for this study when assessed against all criteria, the accessibility, N–S orientation and basaltic bedrock lithology of Winkie Nunatak's southernmost ridge (74.86° S, 99.77° W) make it a feasible site both for drilling and subsequent cosmogenic nuclide analysis. Furthermore, the ridge is strewn with glacial erratics at all elevations, providing valuable constraints on its early Holocene deglacial history. Based on our experiences during this study, we conclude with a series of recommendations for assessing site suitability for future bedrock drilling campaigns. We emphasise the importance of consulting a range of expertise prior to drilling and ensuring that sufficient field reconnaissance is undertaken (including obtaining detailed grids of radar survey data and bedrock samples).

58 GEOSCIENCES↗

DOE OSTI2024

DASSH-F: Subchannel Based Thermal Analysis

The DASSH thermal analysis code is designed to rapidly allow a reactor design engineer to obtain flow rates requirements that satisfy peak temperature constraints in the domain. The advantage of using DASSH over a hand calculation is that it has a more rigorous treatment of the pin power distribution and coolant heat transfer within an assembly and between assemblies. The advantage of using DASSH over a conventional 3D subchannel code or a computational fluid dynamics code (CFD) is that it can obtain the desired solution in a matter of minutes in serial with minor computer memory needs. The DASSH methodology is virtually identical to SUPERENERGY-2 with additional functionalities taken from follow on work to SUPERENERGY-2 done at ANL in the 1980s. DASSH today is an integral component of the Argonne Fast Reactor analysis suite for reactor design work. DASSH obtains the power distribution from a coupled neutron-gamma heating calculation in GAMSOR (including DIF3D) at each time point of a companion fuel cycle analysis calculation with REBUS. The domain in DASSH assumes a hexagonal grid typical for fast reactors with much of the geometry information taken from the DIF3D model. DASSH assumes the assemblies that are loaded into each grid position are ducted to control the coolant flow. Considerable detail is given on the subchannel formulation of DASSH in this document. Much of the formulation and design of the code builds upon research done by previous authors with little new investigation. Thus the decisions made in developing the subchannel model used in DASSH have their origins over 50 years ago. Much of the heat transfer methodology in DASSH is built upon correlations for both the coolant mixing and heat transfer coefficients for pins and ducts. DASSH is thus not a rigorous treatment of a given problem, but a rapid assessment of the temperature field that has known limitations with respect to an experimental measurement or CFD calculation. The DASSH input and output are detailed along with usage of the software. The DASSH output provides tables of evaluated material properties and key coolant and pin temperature results. DASSH can create Python scripts that generate domain summary pictures. DASSH can also generate assembly temperature maps and VTK output files which allow the DASSH solution to be visualized. As the primary purpose of the DASSH software is to compute the coolant and fuel pin temperature distribution for a given model of a reactor, much of the output focus is giving the user quick summary tables needed to assess the performance of a given orifice flow specification. The present version of DASSH has a crude orifice search capability and an efficient orifice flow search capability. The flow search tries to meet user specified constraints for 1) peak 2-sigma clad midwall temperature, 2) peak coolant temperature, and 3) desired bulk outlet temperature. There are many development shortcomings in DASSH detailed in this document, but this version is functional for modern analysis needs. This document serves as the manual for the Fortran based DASSH software that was developed to replace the Python version of DASSH developed as part of the VTR program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Compactly‐Supported Nonstationary Kernels for Computing Exact Gaussian Processes on Big Data

The Gaussian process (GP) is a widely used method for analyzing large-scale data sets, including spatio-temporal measurements of nonlinear processes that are now commonplace in the environmental sciences. Traditional implementations of GPs involve stationary kernels (also termed covariance functions) that limit their flexibility, and exact methods for inference that prevent application to data sets with more than about 10,000 points. Modern approaches to address stationarity assumptions generally fail to accommodate large data sets, while all attempts to address scalability focus on approximating the Gaussian likelihood, which can involve subjectivity and lead to inaccuracies. In this work, we explicitly derive an alternative kernel that can discover and encode both sparsity and nonstationarity. We embed the kernel within a fully Bayesian GP model and leverage high-performance computing resources to enable the analysis of massive data sets. We demonstrate the favorable performance of our novel kernel relative to existing exact and approximate GP methods across a variety of synthetic data examples. Furthermore, we conduct space–time prediction based on more than 1 million measurements of daily maximum temperature and verify that our results outperform state-of-the-art methods in the Earth sciences. More broadly, having access to exact GPs that use ultra-scalable, sparsity-discovering, nonstationary kernels allows GP methods to truly compete with a wide variety of machine learning methods.

Gaussian processes↗

DOE OSTI2025

ZIPPER: Zonal isolation with plug and perf in enhanced reservoirs (Final Technical Report)

Modern multistage hydraulic stimulation treatments in cased wellbores require an effective method of isolating stages between treatments. A commonly used method in the oil and gas industry, plug and perf, is not currently viable for Enhanced Geothermal Systems (EGS) due to limitations of a critical component of the system – the ball drop (flow through) frac plug. Commercially available ball drop frac plugs do not meet the temperature or wellbore diameter requirements needed for use in EGS stimulations. For example, one particular drillable bridge and frac plug line from a large tool developer is only rated to 175 °C, while another is only available up to casing sizes of 5 ½” and rated up to 204 °C. We developed, prototyped, and field tested an upgraded ball drop frac plug to meet the requirements of EGS stimulations, including high-temperature (225+ °C), differential pressure (6000+ psi), and wellbore diameters ranging from 6 5/8” to 10 5/8”. We focused on designs and materials to optimize drillability, a key cost driver in plug and perf systems. The primary objective was to upgrade a drillable frac plug (currently rated to a temperature of 175°C and a pressure of 10,000 psi in 7” casing) to withstand temperatures of 225+°C. The upgraded frac plug was tested in the laboratory as well as in a field trial at a geothermal field. Engineering design and fabrication of the new plug was completed in 2019. Lab testing, validation, and qualification of the plug was completed in 2020. Ultimately the plug was successfully run during a multistage stimulation treatment in a fully horizontal EGS well in 2022. Prior to this project, a ball-drop, flow-through stimulation plug had never been used in a geothermal well. At the conclusion of this project, three different types of zonal isolation plugs were evaluated under full-scale operating conditions across 16 stimulation treatment stages in a first-of-a-kind EGS project called Project Red. This trial included the newly designed high-temperature, large-diameter plug. The plugs met all of 5 the technical requirements for commercial viability. Project Red has since been fully commissioned and is generating electricity on the Nevada grid - the first EGS project to successfully deliver power to the grid in the US.

15 GEOTHERMAL ENERGY↗