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DOE OSTI2024

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 4: Utah FORGE Well 78B-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 3: Utah FORGE Well 56-32

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 1: Summary of Utah FORGE Wells 16A(78)-32, 56-32, 78B-32 and 16B(78)-32

15 GEOTHERMAL ENERGY↗

DOE OSTI2026

California Bridge to the EIC: Building a Diverse Workforce for Nuclear Physics Research at the Electron Ion Collider

The California Bridge to the Electron Ion Collider traineeship program established an integrated workforce development effort connecting University of California campuses, California State University Minority Serving Institutions, and DOE national laboratories. The program expanded participation in nuclear physics research among students from underrepresented and socioeconomically disadvantaged backgrounds while strengthening collaborative activities aligned with the future Electron Ion Collider. During the award period, trainees conducted experimental, theoretical, and computational research, participated in consortium meetings and national laboratory collaborations, and received structured mentoring and professional development. The program achieved strong outcomes in graduate school placement, STEM career transitions, and sustained engagement with DOE Nuclear Physics research.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2020

CACTI Radar b1 Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility deployed a large number of instruments to a region nearby the Sierra de Córdobas mountains in Argentina as part of the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign (1). During this campaign, four radars were installed at a site outside of Villa Yacanto as shown in Figure 1. As part of a post-campaign effort to improve the usability of these data, a significant activity was undertaken towards the calibration, correction, and improvement of the data quality of these radar datastreams. This process in ARM nomenclature is referred to as generating a “b1” datastream. While these “b1” standards may imply different corrections or standards for various ARM instruments, for radars it refers to a datastream that has been calibrated (and cross-calibrated), including a serious effort to deliver the highest-quality (well-characterized) data possible. This report details (i) the status/quality of the original “a1” (raw) data, (ii) the corrections and calibrations that are applied to generate these b1 datastreams, (iii) the details of the applied algorithms and how radar offset/calibration numbers were determined for the eventual corrections, and (iv) the new and flexible plug-in-based processing system designed during CACTI for radar b1 activities (current, future) that interfaces with ARM’s Data Integrator (ADI) and high-performance computing (HPC) system.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Remote Instrumentation and Data Acquisition

This poster outlines the development and implementation of a remote data acquisition system for waveform analysis using a Rohde & Schwarz oscilloscope. The project involved capturing waveform data, and transferring it to a local machine for visualization and analysis. The core logic was developed in C++ with a focus on object oriented programming and the use of polymorphism so the main application can interact with any instrument without knowing its exact type, simplifying the overall logic and making it easier to add or swap out components without changing the rest of the codebase.. The system issues Standard Commands for Programmable Instruments (SCPI) via a socket connection and parses the oscilloscope s ASCII waveform data. The C++ application was containerized using Docker for ease of portability, and reproducibility. Emphasis was placed on secure networking practices, error handling, and effective data capture. The report describes the technical steps taken, challenges encountered, and future work, providing insight into the practical integration of hardware interfacing with remote computational environments.

Parikh, Jaymil [Illinois U., Urbana]↗

DOE OSTI2026

Lithium–Divertor Interactions and Helium/Hydrogen Trapping in Lithiated Metals (Final Technical Report)

The goal of this project was to develop a fundamental understanding of helium and hydrogen behavior in lithium, both in bulk and at interfaces with tungsten, in order to inform the design of lithium based plasma facing components for fusion devices. Over the course of the award, the project produced the first comprehensive, peer reviewed dataset describing helium energetics, migration behaviors, and defect interactions in lithium. The research demonstrated that helium behaves in ways not previously observed in any other body centered cubic (BCC) metal: its interstitial configurations are more stable than substitutional ones, and its migration barriers are extraordinarily low, in some cases more than an order of magnitude below those in tungsten or iron. These discoveries reveal that helium in lithium diffuses so rapidly that its transport may be dominated by translational motion rather than the vibrationally activated mechanisms that underpin conventional solid state diffusion. This work lays a scientific foundation for understanding gas retention, bubble formation, and wall evolution in lithium based fusion environments and provides new computational tools, most notably a newly developed Li–He interatomic potential, for advancing future modeling efforts.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Status on Genetic Resistance to Rice Blast Disease in the Post-Genomic Era

Rice blast, caused by Magnaporthe oryzae, is a major threat to global rice production, necessitating the development of resistant cultivars through genetic improvement. Breakthroughs in rice genomics, including the complete genome sequencing of japonica and indica subspecies and the availability of various sequence-based molecular markers, have greatly advanced the genetic analysis of blast resistance. To date, approximately 122 blast-resistance genes have been identified, with 39 of these genes cloned and molecularly characterized. The application of these findings in marker-assisted selection (MAS) has significantly improved rice breeding, allowing for the efficient integration of multiple resistance genes into elite cultivars, enhancing both the durability and spectrum of resistance. Pangenomic studies, along with AI-driven tools like AlphaFold2, RoseTTAFold, and AlphaFold3, have further accelerated the identification and functional characterization of resistance genes, expediting the breeding process. Future rice blast disease management will depend on leveraging these advanced genomic and computational technologies. Emphasis should be placed on enhancing computational tools for the large-scale screening of resistance genes and utilizing gene editing technologies such as CRISPR-Cas9 for functional validation and targeted resistance enhancement and deployment. These approaches will be crucial for advancing rice blast resistance, ensuring food security, and promoting agricultural sustainability.

Pedrozo, Rodrigo↗

DOE OSTI2015

Century-scale simulations of the response of the West Antarctic Ice Sheet to a warming climate

Abstract. We use the BISICLES adaptive mesh ice sheet model to carry out one, two, and three century simulations of the fast-flowing ice streams of the West Antarctic Ice Sheet, deploying sub-kilometer resolution around the grounding line since coarser resolution results in substantial underestimation of the response. Each of the simulations begins with a geometry and velocity close to present-day observations, and evolves according to variation in meteoric ice accumulation rates and oceanic ice shelf melt rates. Future changes in accumulation and melt rates range from no change, through anomalies computed by atmosphere and ocean models driven by the E1 and A1B emissions scenarios, to spatially uniform melt rate anomalies that remove most of the ice shelves over a few centuries. We find that variation in the resulting ice dynamics is dominated by the choice of initial conditions and ice shelf melt rate and mesh resolution, although ice accumulation affects the net change in volume above flotation to a similar degree. Given sufficient melt rates, we compute grounding line retreat over hundreds of kilometers in every major ice stream, but the ocean models do not predict such melt rates outside of the Amundsen Sea Embayment until after 2100. Within the Amundsen Sea Embayment the largest single source of variability is the onset of sustained retreat in Thwaites Glacier, which can triple the rate of eustatic sea level rise.

Cornford, S. L. (ORCID:000000031844274X)↗

DOE OSTI2016

Report for Oregon State University Reporting Period: June 2016 to June 2017

The goal of this project is to develop an eddy resolving ocean model (POP) with tides coupled to a sea ice model (CICE) within the Regional Arctic System Model (RASM) to investigate the importance of ocean tides and mesoscale eddies in arctic climate simulations and quantify biases associated with these processes and how their relative contribution may improve decadal to centennial arctic climate predictions. Ocean, sea ice and coupled arctic climate response to these small scale processes will be evaluated with regard to their influence on mass, momentum and property exchange between oceans, shelf-basin, ice-ocean, and ocean-atmosphere. The project will facilitate the future routine inclusion of polar tides and eddies in Earth System Models when computing power allows. As such, the proposed research addresses the science in support of the BER’s Climate and Environmental Sciences Division Long Term Measure as it will improve the ocean and sea ice model components as well as the fully coupled RASM and Community Earth System Model (CESM) and it will make them more accurate and computationally efficient.

58 GEOSCIENCES↗

DOE OSTI2018

DESIGN AND EXPERIMENTAL STUDY OF A HIGH PRESSURE AND SUPERCRITICAL METHANE-OXYGEN BURNER

Directly heated supercritical oxy-fuel power cycles have potential to offer a higher thermal efficiency and lower pollutant emissions compared to existing power cycles. Recent thermodynamic analysis of the cycle performed by several groups including the UTEP-Air Liquide research team show that combustion in the vicinity of 300 bar pressure and 1000-1400 K temperature allows for relatively high system efficiencies while operating within the limit of practical combustor materials. However, the realization of directly heated supercritical power cycle requires combustion systems be designed to operate in supercritical conditions and at temperature far below the blowout limit of conventional flames (above 1500 K), where not only the thermodynamic properties but also the combustion properties and kinetics are unexplored. To minimize these knowledge gaps, some intermediate pressure ranges (up to 20 bar) are experimented and modeled using a CFD simulation tool. The knowledge obtained from the high pressure test will assist in understanding the combustion chamber pressurization mechanism, ignition and flame behavior at the elevated pressure. This is a systematic first step in testing at higher pressures of 100 and 300 bar pressures. The primary objective of this dissertation is to perform qualitative analysis on oxy-methane combustion at high pressure (< 20 bar) and compare to CFD model for future scale up to supercritical condition. For modeling of the system, a commercial computational fluid dynamics simulation tool, ANSYS Fluent, is used. The inlet conditions for the CFD analysis are obtained from the experiments. The geometry used for the study is same as the test apparatus and operates at the same power ratings. The expertise gained from this experimental study is important to accurately and safely design combustors at elevated pressures up to 300bar. A high pressure methane-oxygen fuel burner and combustor have been developed to accommodate oxycombustion environment. A detailed CFD analysis is conducted to understand the flame length and cooling phenomenon inside the combustor first at pressures up to 20 bar to compare to experiments then at supercritical pressure. The first part of the dissertation compares CFD results with high pressure burner experiments at pressures up to 20 bar. The test is conducted for 30 s within 150 kW – 250 kW thermal power inputs. Afterwards, based on the simulation results a cooling system is proposed for steady state high pressure combustion experiments. It is observed from the experimental study that the proposed pressurization mechanism able to pressurize the vessel up to 20 bar. It is also determined that the current combustor can operate up to 20 bar for short term. The steady state CFD simulation demonstrates that a cooling system must be incorporated for continuous operation. Additionally, the study focuses on the ignition delay due to added diluent during the combustion process. It is observed that as the carbon dioxide recirculation ratio increases the ignition delay time increases. Later part of the dissertation provides a preliminary guideline for developing a laboratory scale supercritical oxy combustor. The employment of supercritical fluid in gas turbine is fairly a new concept. Hence, there are many questions that need to be answered. During this dissertation study an investigation is performed to understand the impact of equation of state in the supercritical combustion simulation. Finally, a CFD model for developing supercritical oxy-methane burner and the combustor, incorporating real gas model, is presented. Although Lee-Kesler equation of state provides better accuracy than Peng Robinson, due to the computational time Peng Robinson equation of state is used for the simulation. It is found that existing knowledge is not enough to simulate combustion at supercritical phase. Detailed combustion chemistry at the supercritical condition must be developed and should be incorporated to accurately replicate the combustion phenomenon.

Chowdhury, ASM Arifur Rahim↗

DOE OSTI2016

Experimental Data and Analysis for a New Irradiation Facility

A new experimental facility is being developed for materials irradiation and testing at the Oak Ridge National Laboratory (ORNL) High Flux Isotope Reactor (HFIR). Details of this facility have been presented before. A prototype of this facility, the Thermosyphon Test Loop (TSTL), has been built, and experimental data have been obtained and analyzed. The purpose of the tests was to establish a safe operating envelope for actual fueled experiments in a HFIR experimental facility. Both steady-state and transient experiments were conducted. The data will also be used to validate computer simulations of the thermosyphon so that those codes can be used for future safety-basis calculations. This paper presents a summary of the TSTL experimental data and analysis. A report with all the data and analyses will be published in the near future. Experimental data from 51 tests in the TSTL have been obtained. This extensive set of high quality data can be used to benchmark codes with boiling and condensing phenomena. This new proposed irradiation facility allows materials to be irradiated without concern for HFIR coolant contamination (from specimen failures) as it uses a separate coolant, that is isolated (except thermally) from the HFIR primary coolant. (authors)

42 ENGINEERING↗

DOE OSTI2024

Studying Wind Loading on CSP Collectors to Improve Performance and Reliability

Electricity generation through Concentrating Solar-thermal Power (CSP) adds the advantage of thermal energy storage and heat production. CSP collector costs constitute nearly one-third of total plant costs. Managing wind loading, especially dynamic wind loading caused by the turbulent wind flow, is a significant design challenge. Traditional collector designs rely on wind tunnel experiments and numerical simulations, which do not fully capture dynamic effects. Here, we provide an overview of NREL's activities on wind loading on CSP collectors, aiming to improve their reliability and cost-efficiency. We present insights from field measurements at operational parabolic trough and power-tower CSP plants. Over two years, we measured turbulent wind fields and resulting structural loads in a parabolic trough plant, revealing wind, turbulence, and collector field interactions. Similar measurements are ongoing at the Crescent Dunes heliostat field. These campaigns show how atmospheric turbulence, wind direction, and collector orientation affect dynamic wind loading. Upwind collector structures can generate turbulent structures, causing fluctuating loads at downstream collectors, impacting fatigue lifetime and optical efficiency. Preliminary results indicate that interior collectors experience higher turning moments than those at the edges, suggesting higher drive wear. At Crescent Dunes, we use instrumented heliostats at the field's edge and interior to study the translation of turbulent wind to dynamic structural loads. The campaign is still ongoing, and we will present first findings. Another focus of our work is tying the experimental wind loading findings to optical performance of the collectors, using simulation tools. For example, we derive torsional errors of the parabolic troughs - the angular offset from the sun position along a collector row. This error is impacted by wind-induced mirror deformations. Future work will focus on continuing the measurement efforts and combining them with computational fluid dynamic simulations. By providing detailed field measurements and validated models, our efforts aim to enhance understanding of wind loading on CSP collectors, improving their structural integrity and optical performance.

CSP↗

DOE OSTI2019

MULTIDIMENSIONAL NUMERICAL SIMULATIONS OF REACTING FLOW IN A NON-PREMIXED ROTATING DETONATION ENGINE

Over the last two decades, detonation based propulsion has received a great deal of attention as a potential means to achieve significant improvement in the performance of air-breathing and rocket engines. Detonative combustion mode is particularly interesting due to the resulting pressure gain from reactants to products, faster heat release, decreased entropy generation, more available work and higher thrust compared to conventional deflagrative combustion. Rotating detonation engine (RDE) is one such novel combustor concept. Realistic RDE configurations utilize separate fuel and air injection schemes, hence are not perfectly premixed. Moreover, RDE performance is governed by a large number of design parameters and operating conditions. In this context, computational fluid dynamics (CFD) has the potential to enhance the understanding of RDE combustion and aid future development/optimization of this technology. In the present work, a CFD model was developed to simulate a representative non-premixed RDE combustor. Unsteady Reynolds-Averaged Navier-Stokes (RANS) simulations were performed for the full combustor geometry (including the separate fuel and air injection ports), with hydrogen as fuel and air as the oxidizer. Adaptive mesh refinement (AMR) was incorporated to achieve a trade-off between model accuracy and computational expense. A finite-rate chemistry model along with a 10-species detailed kinetic mechanism was employed to describe the H2-Air combustion chemistry. Two operating conditions were simulated, corresponding to the same global equivalence ratio of unity but different fuel and air mass flow rates. For both conditions, the capability of the model to capture the essential detonation wave dynamics was assessed. A validation study was performed against experimental data available on detonation wave frequency/height, reactant fill height, oblique shock angle, axial pressure distribution in the channel, and fuel/air plenum pressure. The CFD model predicted the sensitivity of these wave characteristics to the operating conditions with good accuracy, both qualitatively and quantitatively. The present CFD model offers a potential capability to perform rapid design space exploration and/or performance optimization studies for realistic full-scale RDE configurations.

Pal, Pinaki↗

DOE OSTI2025

Futureproofing through 2035 for the AI and HPC Power Density Trend

HPC and AI are businesses necessitating growth for providing performance improvement with increased power and cooling. As HPC and AI computers and their supporting facilities approach utility scale with a frequency of technology innovation outpacing utility and construction timelines, understanding and designing for this trend has become critical. This paper will provide historical trend data for facilities and compute racks, relate power trend data to cooling technology capabilities, and reason through constraints impacting anticipated future power densities to aid the reader in futureproofing a facility’s power and cooling systems through the mid-2030’s.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Error mitigation in variational quantum eigensolvers using tailored probabilistic machine learning

Quantum computing technology has the potential to revolutionize the simulation of materials and molecules in the near future. A primary challenge in achieving near-term quantum advantage is effectively mitigating the noise effects inherent in current quantum processing units (QPUs). This challenge is also decisive in the context of quantum-classical hybrid schemes employing variational quantum eigensolvers (VQEs) that have attracted significant interest in recent years. In this paper, we present a method that employs parametric Gaussian process regression (GPR) within an active learning framework to mitigate noise in quantum computations, focusing on VQEs. Our approach, grounded in probabilistic machine learning, exploits a custom prior based on the VQE ansatz to capture the underlying correlations between VQE outputs for different variational parameters, thereby enhancing both accuracy and efficiency. We demonstrate the effectiveness of our method on a two-site Anderson impurity model and a eight-site Heisenberg model, using the IBM open-source quantum computing framework, Qiskit, showcasing substantial improvements in the accuracy of VQE outputs while reducing the number of direct QPU energy evaluations. This paper contributes to the ongoing efforts in quantum-error mitigation and optimization, bringing us a step closer to realizing the potential of quantum computing in quantum matter simulations. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Realizing our vision of the future [Slides]

Abstract not provided.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service

Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗