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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Deep Learning for Modeling Enhanced Geothermal Systems

Enhanced Geothermal Systems (EGS) offer a vast potential to expand the use of geothermal energy. Heat is extracted from this engineered system by injecting cold water into a subsurface fractures, which are in contact with the hot dry rock, and pulled through the production wells. Creating EGS requires improving the natural permeability of hot crystalline rocks. To develop economically viable EGS reservoirs, significant technical barriers (e.g., better stimulation technologies without adequate water and/or permeability) and non-technical barriers (e.g., land access and permitting) must be overcome. In this short conference paper, we present a workflow to address a part of this challenge – “How to develop economically viable EGS using existing technologies?”. Our workflow called the GeoThermalCloud (GTC) for EGS, leverages recent advances in machine learning, deep learning, and cloud computing. This GTC framework is open-source and available at https://github.com/SmartTensors/GeoThermalCloud.jl. The GTC framework provides trained deep learning (DL) models to estimate the net present value of a given EGS design scenario. The Geothermal Design Tool (https://github.com/GeoDesignTool/GeoDT.git), a fast and simplified multi-physics solver, is used to develop a database for training DL models. The database consists of EGS design parameters (inputs to DL model) and their net present value (output of DL model) in uncertain geologic systems. The EGS design parameters for constructing this training database are based on Utah FORGE but include the options of more wells and deeper depths. The DL models are trained by ingesting the EGS design parameters and estimating the corresponding net present value. Such an emulation allows us to screen various EGS designs quickly and identify good development strategies by coupling them with optimization techniques. Our preliminary results show promise in DL emulation of net present value. However, a lot more work is needed to improve the predictive capability of DL models (i.e., extensive hyperparameter tuning is necessary). This will be the primary focus of our future work.

artificial neural networks, geothermal↗
DOE OSTI2023

A phase-field model for hydraulic fracture nucleation and propagation in porous media

Many geo-engineering applications, for example, enhanced geothermal systems, rely on hydraulic fracturing to enhance the permeability of natural formations and allow for sufficient fluid circulation. Over the past few decades, the phase-field method has grown in popularity as a valid approach to modeling hydraulic fracturing because of the ease of handling complex fracture propagation geometries. However, existing phase-field methods cannot appropriately capture nucleation of hydraulic fractures because their formulations are solely energy-based and do not explicitly take into account the strength of the material. Thus, in this work, we propose a novel phase-field formulation for hydraulic fracturing with the main goal of modeling fracture nucleation in porous media, for example, rocks. Built on the variational formulation of previous phase-field methods, the proposed model incorporates the material strength envelope for hydraulic fracture nucleation through two important steps: (i) an external driving force term, included in the damage evolution equation, that accounts for the material strength; (ii) a properly designed damage function that defines the fluid pressure contribution on the crack driving force. In conclusion, the comparison of numerical results for two-dimensional test cases with existing analytical solutions demonstrates that the proposed phase-field model can accurately model both nucleation and propagation of hydraulic fractures. Additionally, we present the simulation of hydraulic fracturing in a three-dimensional domain with various stress conditions to demonstrate the applicability of the method to realistic scenarios.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Recovery of Rare Earths, Precious Metals and other Critical Materials from Geothermal Waters with Advanced Sorbent Structures - CRADA 355 (Abstract)

The ability to recover valuable trace level minerals from geothermal brines using high-performance solid-phase sorbents will be explored and developed. A compressive range of sorbent materials will be screened for application to metal extraction from geothermal brines. Preferred sorbents from extraction of trace levels of rare earths (REs), precious metals (PMs), and other critical/strategically valuable materials (CMs) such as Zn, Mn, Te, Sc, Se and U from geothermal brines will be identified. For the preferred sorbents PNNL will determine the volumes they are capable of providing efficient extraction from. The thermal and chemical limits (including, acid, sulfur, salt) for performance of the preferred sorbent materials will be determined; with a target of at least 125°C and perhaps as high as 400° C. Sorbent form factors (including, packed bed, membrane, mats) that can function efficiently and be installed cost effectively in geothermal energy plants will be assessed for chemical and economic viability. Material regeneration and cyclic utilization will be demonstrated, targeting hundreds to thousands of cycles. Options for recovery and purification (including, selective separation of heavy REs) of collected materials will be explored. A techno-economic analysis (TEA) will be performed to assess the best approach to provide a value-added extraction process for geothermal energy systems. The sorbent materials and engineering analysis will be applicable to other industrial processes in which secondary recovery of valuable materials could provide economic benefit.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Thermal-Hydrological-Mechanical Modelling of Stockton University Reservoir Cooling System, Fine Scale Stress Test Modelling

Mesh, properties, initial conditions, injection/withdrawal rates for modelling thermal, hydrological, and mechanical effects of fluid injection to and withdrawal from ground for Stockton University reservoir cooling system (aquifer storage cooling system), Galloway, New Jersey, for unscheduled two hour injection at 133 % designed capacity, on fine scale grid, with some results. Second simulation of J.T. Smith, E. Sonnenthal, P. Dobson, P. Nico, and M. Worthington, 2021. Thermal-hydrological-mechanical modeling of Stockton University reservoir cooling system, Proceedings of the 46th Workshop on Geothermal Reservoir Engineering, Stanford University, SGP-TR-218, from which Figures 6-9, pertain.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Thermal-Hydrological-Mechanical Modelling of Stockton University Reservoir Cooling System, Large Scale Grid

Mesh, properties, initial conditions, injection/withdrawal rates for modeling thermal, hydrological, and mechanical effects of fluid injection to and withdrawal from ground for Stockton University reservoir cooling system (aquifer storage cooling system), Galloway, New Jersey, on large scale grid, with some results. First simulation of J.T. Smith, E. Sonnenthal, P. Dobson, P. Nico, and M. Worthington, 2021. Thermal-hydrological-mechanical modeling of Stockton University reservoir cooling system, Proceedings of the 46th Workshop on Geothermal Reservoir Engineering, Stanford University, SGP-TR-218, from which Figures 1-5 pertain.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Decovalex-2019 (Executive Summary)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. DECOVALEX was initially motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. Later it was realized that these processes also play a critical role in other subsurface engineering activities, such as subsurface CO 2 storage, enhanced geothermal systems, and unconventional oil and gas production through hydraulic fracturing. Research teams from many countries (e.g., Canada, China, Czech Republic, Finland, France, Germany, Japan, Republic of Korea, Spain, Sweden, Switzerland, Taiwan, United Kingdom, and the United States) various institutions have participated in the DECOVALEX Project over the years, providing a wide range of perspectives and solutions to these complex problems. These institutions represent radioactive waste management organizations, national research institutes, regulatory agencies, universities, as well as industry and consulting groups. The overall aim of DECOVALEX-2019 was to increase the understanding of various thermo-hydro-mechanical-chemical processes of importance for radionuclide release and transport from a repository to the biosphere and how they can be described and modelled using mathematical models. The scientific and technical objectives are: to increase the basic understanding of T-H-M-C coupled processes in fractured rocks (crystalline, sedimentary, argillaceous) and buffer materials; to investigate the predictive capabilities of different codes to field experiments and to perform verification of codes; to exchange experimental data, and improve the understanding of the constitutive behavior of crystalline and argillaceous rock masses and buffer materials; and to perform THMC calculations in a performance/safety assessment context.

58 GEOSCIENCES↗
DOE OSTI2020

DECOVALEX-2019 (Task E Final Report)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. DECOVALEX was initially motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. Later it was realized that these processes also play a critical role in other subsurface engineering activities, such as subsurface CO 2 storage, enhanced geothermal systems, and unconventional oil and gas production through hydraulic fracturing. Research teams from many countries (e.g., Canada, China, Czech Republic, Finland, France, Germany, Japan, Republic of Korea, Spain, Sweden, Switzerland, Taiwan, United Kingdom, and the United States) various institutions have participated in the DECOVALEX Project over the years, providing a wide range of perspectives and solutions to these complex problems. These institutions represent radioactive waste management organizations, national research institutes, regulatory agencies, universities, as well as industry and consulting groups. This document is the final report of Task E which was proposed and coordinated by Andra, the National Radioactive Waste Management Agency in France, presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. The purpose of Task E of the DECOVALEX-2019 project is to investigate upscaling THM modelling from small-scale experiments (some cubic meters) to full-scale experiments (some ten cubic meters) and finally to the scale of the waste repository (cubic kilometers). To achieve this aim, the data of two in-situ heating experiments performed by Andra (the French National Radioactive Waste Management Agency) in the Meuse/Haute-Marne Underground Research Laboratory (MHM URL) have formed the basis for the understanding of the THM behavior of the COx at different scales. The first experiment provided the reference values of the THM parameters by means of a calibration exercise and they were used for a blind prediction and an interpretative analysis of the second one.

58 GEOSCIENCES↗
DOE OSTI2026

A robust framework for frictional fault contact in geological formations using a stabilized augmented Lagrangian approach

Numerical simulations are essential to evaluate the performance and safety of engineered subsurface systems such as geological carbon storage sites, enhanced geothermal fields, and oil and gas reservoirs. A key challenge lies in accurately modeling the frictional contact behavior along fault surfaces. This problem involves inequality constraints that arise from the physics of frictional slip, requiring specialized numerical methods to handle the resulting highly nonlinear and path-dependent behavior. Here, in this work, we address this challenge using an Augmented Lagrangian Method (ALM) implemented via the Uzawa algorithm. The formulation employs mixed finite element spaces, combining low-order piecewise linear displacements within the 3D domain cells with piecewise constant tractions defined on the fault surfaces. Furthermore, to ensure stability and satisfy the inf-sup condition, the discrete displacement space is enriched with face bubble functions on both sides of the contact interfaces. This approach offers several advantages over other stabilization techniques that rely on additional terms, and it integrates naturally in the Uzawa framework.

58 GEOSCIENCES↗
DOE OSTI2026

Automated and Accelerated Continuum Model Development for Electrochemical Systems (Abbreviated Report)

Despite the availability of computational resources and advancements in numerical computing capabilities, the multiscale models core to understanding, predicting the behaviors of, and designing energy and environmental systems involving porous media are still 1.) developed through by-hand derivations and 2.) limited by many methodological assumptions employed during model derivation. As a result, the advancement of effective media models for engineering DOE mission-critical systems (e.g., batteries, flow batteries, electrolyzers, geothermal systems, subsurface chemical storage systems, etc.) is slow (i.e., it takes years for models to traverse from stages of “development” to “practical utilization”), hindering our ability to effectively optimize such systems and stay at the cutting-edge of the energy frontier. In this work, we aimed to address these limitations by 1.) automating and accelerating multiscale model derivation via symbolic computing and 2.) develop a novel multiscale modeling methodology for flow and transport through porous media that avoids the typical assumptions hindering previous models. As a result of our efforts, we 1.) developed a hybrid symbolic-numeric code called Fouriera for fully-automating the implementation of multiphysical and phase-field models via the Fourier spectral method for materials science research, and 2.) advanced a multiscale modeling methodology called The Method of Finite Averages that rigorously predicts the behaviors of flow and transport through heterogeneous porous media under the influence of non-local effects and strong advection. Ultimately, these deliverables provide strong foundations from which further efforts can advance multiscale modeling tools and capabilities that do not intrinsically rely on 1.) the speed and mathematical capabilities of humans, nor 2.) the methodological assumptions limiting current models.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Coalition for Community-Supported Affordable Geothermal Energy Systems (C2SAGES)

The C2SAGES project evaluated the feasibility of a community geothermal system for the planned Windy Ridge affordable housing development in Hinesburg, Vermont. Led by GTI Energy with Vermont Gas Systems, LN Consulting, NREL, and Frontier Energy, the work assessed technical design, energy performance, costs, business models, community engagement, maintenance, workforce development, and permitting. The proposed system was designed to serve 100% of the development’s heating, cooling, and domestic hot water loads. Compared with a baseline using air-source heat pumps and natural gas water heating, the geothermal system was estimated to reduce HVAC and domestic hot water energy use by about 45% to 48%, lower operating and maintenance costs, and reduce 30-year life-cycle costs by 37% for Phase 1 and 10% for Phase 2. Technical testing and modeling indicated that the Windy Ridge site is suitable for a community-scale geothermal system. The project also developed borehole field layouts, piping concepts, pump house designs, controls, maintenance plans, and supporting engineering drawings. The business model analysis found that first cost, ownership structure, and customer affordability remain major deployment challenges. Utility-led maintenance and operation were viewed favorably, but traditional utility cost-recovery models may require subsidy or revised financing structures to be practical for affordable housing. Community engagement highlighted the need for clear public education, transparent financing, reliable long-term maintenance, trained technicians, and the potential to pair geothermal systems with weatherization. Overall, the report concludes that community geothermal is technically feasible and offers meaningful energy, emissions, and life-cycle cost benefits, but broader deployment will depend on workable financing models and workforce readiness.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Thermal and Mechanical Energy Performance Analysis of Closed-loop Systems in Hot-Dry-Rock and Hot-Wet-Rock Reservoirs

To understand the potential and limitations for recovering thermal and mechanical energy from closed-loop geothermal systems a collaborative study is underway that will investigate an array of system configurations, working fluids, geothermal reservoir characteristics, operational periods, and heat transfer enhancements. Closed-loop geothermal systems are distinguished from hydrothermal or enhanced geothermal systems (EGS) in that the working fluid only circulates through drilled boreholes. Principal objectives of this study are to determine upper limits for thermal and mechanical energy recovery and optimal operational and configuration parameters for each scenario. Teams of scientists and engineers are applying a suite of numerical simulation and analytical tools to model the heat recovery from closed-loop geothermal systems, and then optimizing operational and configuration parameters to maximize the thermal and mechanical energy recovery. Results from the suite of numerical simulators and analytical tools, such as outlet and inlet states and temperature profiles in the geothermal reservoir over time are intercompared to increase confidence in the analysis. This paper documents the study findings for closed-loop systems in hot-dry-rock and hot-wet-rock reservoirs, where water is the working fluid. The characteristics of the hot-dry-rock reservoir were based on the U.S. Department of Energy's Utah Frontier Observatory for Research in Geothermal Energy (FORGE) site, near Milford Utah. Two objective functions are defined to optimize the operational and configuration parameters of the system, one each for the recovery of mechanical and thermal energy over the period of operation. For both objective functions, a surface plant thermal to mechanical energy conversion factor and an energy drilling cost is required. In keeping with the study objectives the surface plant conversion factor is determined from a second-law of thermodynamics analysis of a generic binary plant, and drilling costs are based on those from the Utah FORGE site and current national electrical costs.

closed-loop geothermal systems↗
DOE OSTI2021

Thermal and Mechanical Energy Performance Analysis of Closed-loop Systems in Hot-Dry-Rock and Hot-Wet-Rock Reservoirs

To understand the potential and limitations for recovering thermal and mechanical energy from closed-loop geothermal systems a collaborative study is underway that will investigate an array of system configurations, working fluids, geothermal reservoir characteristics, operational periods, and heat transfer enhancements. Closed-loop geothermal systems are distinguished from hydrothermal or enhanced geothermal systems (EGS) in that the working fluid only circulates through drilled boreholes. Principal objectives of this study are to determine upper limits for thermal and mechanical energy recovery and optimal operational and configuration parameters for each scenario. Teams of scientists and engineers are applying a suite of numerical simulation and analytical tools to model the heat recovery from closed-loop geothermal systems, and then optimizing operational and configuration parameters to maximize the thermal and mechanical energy recovery. Results from the suite of numerical simulators and analytical tools, such as outlet and inlet states and temperature profiles in the geothermal reservoir over time are intercompared to increase confidence in the analysis. This paper documents the study findings for closed-loop systems in hot-dry-rock and hot-wet-rock reservoirs, where water is the working fluid. The characteristics of the hot-dry-rock reservoir were based on the U.S. Department of Energy’s Utah Frontier Observatory for Research in Geothermal Energy (FORGE) site, near Milford Utah. Two objective functions are defined to optimize the operational and configuration parameters of the system, one each for the recovery of mechanical and thermal energy over the period of operation. For both objective functions, a surface plant thermal to mechanical energy conversion factor and an energy drilling cost is required. In keeping with the study objectives the surface plant conversion factor is determined from a second-law of thermodynamics analysis of a generic binary plant, and drilling costs are based on those from the Utah FORGE site and current national electrical costs.

Closed-loop geothermal systems, hot-dry-rock, hot-↗
DOE OSTI2021

A New Modeling Framework for Geothermal Operational Optimization with Machine Learning (GOOML)

Geothermal power plants are excellent resources for providing low carbon electricity generation with high reliability. However, many geothermal power plants could realize significant improvements in operational efficiency from the application of improved modeling software. Increased integration of digital twins into geothermal operations will not only enable engineers to better understand the complex interplay of components in larger systems but will also enable enhanced exploration of the operational space with the recent advances in artificial intelligence (AI) and machine learning (ML) tools. Such innovations in geothermal operational analysis have been deterred by several challenges, most notably, the challenge in applying idealized thermodynamic models to imperfect as-built systems with constant degradation of nominal performance. This paper presents GOOML: a new framework for Geothermal Operational Optimization with Machine Learning. By taking a hybrid data-driven thermodynamics approach, GOOML is able to accurately model the real-world performance characteristics of as-built geothermal systems. Further, GOOML can be readily integrated into the larger AI and ML ecosystem for true state-of-the-art optimization. This modeling framework has already been applied to several geothermal power plants and has provided reasonably accurate results in all cases. Therefore, we expect that the GOOML framework can be applied to any geothermal power plant around the world.

15 GEOTHERMAL ENERGY↗
NASA NTRS2012

Characterization of the Vectron PX-570 Crystal Oscillator for Use in Harsh Environments

Computing hardware, data-acquisition systems, communications systems, and many electronic control systems require well-controlled timing signals for proper and accurate operation. These signals are, in most cases, provided by circuits that employ crystal oscillators due to availability, cost, ease of operation, and accuracy. In some cases, the electronic systems are expected to survive and operate under harsh conditions that include exposure to extreme temperatures. These applications exist in terrestrial systems as well as in aerospace products. Well-logging, geothermal systems, and industrial process control are examples of ground-based applications, while distributed jet engine control in aircraft, space-based observatories (such as the James Webb Space Telescope), satellites, and lunar and planetary landers are typical environments where electronics are exposed to harsh operating conditions. To ensure these devices produce reliable results, the digital heartbeat from the oscillator must deliver a stable signal that is not affected by external temperature or other conditions. One such solution is a recently introduced commercial-off-the-shelf (COTS) oscillator, the PX-570 series from Vectron International. The oscillator was designed for high-temperature applications and as proof, the crystal oscillator was subjected to a wide suite of tests to determine its ruggedness for operation in harsh environments. The tests performed by Vectron included electrical characterization under wide range of temperature, accelerated life test/aging, shock and vibration, internal moisture analysis, ESD threshold, and latch-up testing. The parametric evaluation was performed on the oscillator's frequency, output signal rise and fall times, duty cycle, and supply current over the temperature range of -125 C to +230 C. The evaluations also determined the effects of thermal cycling and the oscillator's re-start capability at extreme hot and cold temperatures. These thermal cycling and restart tests were performed at the NASA Glenn Research Center. Overall, the crystal oscillator performed well and demonstrated very good frequency stability. This paper will discuss the test procedures and present details of the performance results.

Li, Jacob↗
DOE OSTI2024

Abstract for CRADA between National Energy Technology Laboratory and Shell International Exploration & Production, Inc

Introducing CO₂ into geothermal systems as a working fluid in reservoirs can enhance geothermal conductivity, production, and pressure maintenance. A cross-disciplinary interaction of geothermal reservoir stimulation and CO₂ utilization satisfies renewable energy demands and operations that support sustainable energy infrastructure. Challenges to implementing CO₂-stimulated geothermal enhancement (CS-GE) include (1) accurately characterizing and imaging CO₂-stimulated geothermal reservoirs; (2) quantitatively inferring CS-GE evolution under current and future engineered conditions for cost effective operations; and (3) monitoring resources by improving observational methods to advance the understanding of complex geothermal systems for sweep efficiency and, ultimately, cost effectiveness. NETL and Shell will collaborate under this CRADA to develop software to image key features, including CO₂-stimulated fracture imaging, CO₂ fluid sweep imaging and heat transfer and exchange imaging by leveraging available datasets and applying advanced Artificial Intelligence/Machine Learning (AI/ML), multi-level data analytics and data/information fusion to better understand the comprehensive mechanisms of CO₂-stimulated geothermal systems.

15 GEOTHERMAL ENERGY↗