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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Crustal permeability generated through microearthquakes is constrained by seismic moment

We link changes in crustal permeability to informative features of microearthquakes (MEQs) using two field hydraulic stimulation experiments where both MEQs and permeability evolution are recorded simultaneously. The Bidirectional Long Short-Term Memory (Bi-LSTM) model effectively predicts permeability evolution and ultimate permeability increase. Our findings confirm the form of key features linking the MEQs to permeability, offering mechanistically consistent interpretations of this association. Transfer learning correctly predicts permeability evolution of one experiment from a model trained on an alternate dataset and locale, which further reinforces the innate interdependency of permeability-to-seismicity. Models representing permeability evolution on reactivated fractures in both shear and tension suggest scaling relationships in which changes in permeability (Δk) are linearly related to the seismic moment (M) of individual MEQs as Δk ∝ M. This scaling relation rationalizes our observation of the permeability-to-seismicity linkage, contributes to its predictive robustness and accentuates its potential in characterizing crustal permeability evolution using MEQs.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Geologic stress modulates fluid mixing at fracture intersections

Fracture intersections are critical links that enable flow and transport in subsurface fracture networks, and their behavior strongly influences fluid mixing in a network. Although all subsurface fractures are subjected to geological stress, we lack a fundamental understanding of how fracture intersection geometry evolves under stress and how these changes influence fluid mixing. Here, we combine 3D printing, 3D X-ray tomographic imaging, and 3D pore-scale numerical simulations to reveal stress-induced changes in intersection geometry and their impact on mixing. Mixing is found to be strongly affected by partial closure of an intersection under stress. As an intersection closes, the void area for fluid flow and diffusion decreases leading to substantial deviations between conventional mixing models and full pore-scale modeling. To address this, we propose a modified mixing model that accounts for intersection deformation, which is essential for accurate modeling of solute transport and mixing through fracture networks.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

In situ transmission electron microscopy observations of CaCO 3 crystallization onto polysaccharide-coated nanoparticles

Polysaccharides and proteoglycans are widely associated with the organic matrix at sites of CaCO 3 biomineralization, and previous studies indicate that these macromolecules may confer greater roles in mineral nucleation than previously recognized. This investigation uses in situ liquid-phase transmission electron microscopy (LP-TEM) to observe CaCO 3 nucleation onto aminated silica (SiO 2 –NH 3 + ) nanoparticles treated with a layer of chitosan (near-neutral derivative of chitin) or heparin (a carboxylated and highly sulfated glycosaminoglycan). In the absence of polysaccharides, few CaCO 3 particles formed and exhibited mobility. However, the SiO 2 –NH 3 + nanoparticles were enveloped in a region of higher mass density relative to the bulk solution, suggesting the development of a local solute-rich environment that surrounds the charged NH 3 + groups. The heparin- or chitosan-coated silica particles also exhibited regions of higher mass density around the nanoparticles. In the presence of these polysaccharide coatings, we observed the nucleation of abundant CaCO 3 particles whereby the polyanionic heparin promoted more nucleation than the weakly cationic chitosan. Many crystallites appeared to form at the polysaccharide–TEM cell membrane–solution interface, further indicating interfacial and macromolecule-specific control on crystallization. The combined results demonstrate that chitosan and heparin have an appreciable effect on the timing, size, and location of CaCO 3 nucleation compared to the polysaccharide-free nanoparticles.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Thermodynamics of calcium binding to heparin: Implications of solvation and water structuring for polysaccharide biofunctions

Heparan sulfates are found in all animal tissues and have essential roles in living systems. This family of biomacromolecules modulates binding to calcium ions (Ca 2+ ) in low free energy reactions that influence biochemical processes from cell signaling and anticoagulant efficacy to biomineralization. Despite their ubiquity, the thermodynamic basis for how heparans and similarly functionalized biomolecules regulate Ca 2+ interactions is not yet established. Using heparosan (Control) and heparins with different positions of sulfate groups, we quantify how SO 3 − and COO − content and SO 3 − position modulate Ca 2+ binding by isothermal titration calorimetry. The free energy of all heparin-Ca2+ interactions (ΔG rxn ) is dominated by entropic contributions due to favorable water release from polar, hydrophilic groups. Heparin with both sulfate esters (O-SO 3 − ) and sulfamides (N-SO 3 − ) has the strongest binding to Ca 2+ compared to heparosan and to heparin with only O-SO 3 − groups (~3X). By linking Ca 2+ binding thermodynamics to measurements of the interfacial energy for calcite (CaCO 3 ) crystallization onto polysaccharides, we show molecule-specific differences in nucleation rate can be explained by differences in water structuring during Ca 2+ interactions. A large entropic term (-TΔS rxn ) upon Ca 2+ –polysaccharide binding correlates with high interfacial energy to CaCO 3 nucleation. Combining our measurements with literature values indicates many Ca 2+ –polysaccharide interactions have a shared thermodynamic signature. The resulting enthalpy–entropy compensation relationship suggests these interactions are generally dominated by water restructuring involving few conformational changes, distinct from Ca 2+ –protein binding. Our findings quantify the thermodynamic origins of heparin-specific interactions with Ca 2+ and demonstrate the contributions of solvation and functional group position during biomacromolecule-mediated ion regulation.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Physics-informed neural networks for heterogeneous poroelastic media

This study presents a novel physics-informed neural network (PINN) framework for modeling poroelasticity in heterogeneous media with material interfaces. The approach introduces a composite neural network (CoNN) where separate neural networks predict displacement and pressure variables for each material. While sharing identical activation functions, these networks are independently trained for all other parameters. To address challenges posed by heterogeneous material interfaces, the CoNN is integrated with the Interface-PINNs (I-PINNs) framework (Sarma et al., Comput. Methods Appl. Mech. Eng. 429: 117135, 2024), allowing different activation functions across material interfaces. Further, this ensures accurate approximation of discontinuous solution fields and gradients. Performance and accuracy of this combined architecture were evaluated against the conventional PINNs approach, a single neural network (SNN) architecture, and the eXtended PINNs (XPINNs) framework through two one-dimensional benchmark examples with discontinuous material properties. The results show that the proposed CoNN with I-PINNs architecture achieves an RMSE that is two orders of magnitude better than the conventional PINNs approach and is at least 40 times faster than the SNN framework. Compared to XPINNs, the proposed method achieves an RMSE at least one order of magnitude better and is 40% faster.

42 ENGINEERING↗
DOE OSTI2024

The Scientific Impact of the Exascale Computing Project

The recent arrival of the Frontier Supercomputer at Oak Ridge National Laboratory officially marked the dawn of the exascale computing era. Its successful deployment coincided with the culmination of the U.S. Department of Energy Exascale Computing Project (ECP), an ambitious, complex, and risky research and development effort that integrated contributions from a broad and diverse subset of the high-performance computing community. The success of ECP will ultimately be judged by the scientific and engineering advances that it enabled. In conclusion, this Special Issue is focused on showcasing early successes in the use of exascale resources to enable breakthroughs in key areas of science in engineering.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Sub-Degree-Per-Hour MEMS Gyroscope for Measurement While Drilling at 300°C

The orientation module of MWD tool offers the critical drill bit orientation information, including azimuth, inclination and toolface in order to control the path of wellbore. Although high end navigation grade gyroscope can meet the accuracy requirement for azimuth finding, the requirements of cost, size and reliability under harsh environment have largely limited the deployment of gyroscopes in MWD tools. To overcome these constraints, GE Research has developed a low cost, MEMS based Multi-Ring Gyroscope (MRG) capable of azimuth-seeking in MWD applications at 300°C. The MRG prototype has been demonstrated to achieve angular random walk (ARW) better than 0.003 deg/rt(hr) and bias instability of 0.01 deg/hr, capable of meeting azimuth finding accuracy better than 0.25 deg. It has further been tested to remain fully operational at 300 °C.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Analysis of Gaps in Techno-Economic Analysis to Advance Heliostat Technologies for Concentrating Solar-Thermal Power

The Heliostat Consortium (HelioCon) was launched in 2021 to advance heliostat technology. One of its first efforts was to do a detailed analysis of gaps in technology and capabilities in the heliostat industry and complete a roadmap study describing high-priority gaps. HelioCon gathered gaps through a series of outreach activities with representatives and experts from industries and research institutes. Here, this paper discusses the gap analysis for the techno-economic analysis (TEA) topic. One of the main objectives of the TEA topic is to relate the cost and performance of heliostats and heliostat components to the overall system performance. In this study, we limit the scope of this topic to the heliostat field, tower, and receiver and do not consider downstream applications or uses of thermal energy. We conducted a thorough review of existing models and compiled a list of the state of the art in open-source tools currently available to researchers. We collected an initial list of gaps for the TEA of heliostats from industry developers and experts. Each gap is briefly described, and the heliostat development cycle stages that the gap impacts are indicated. We ranked the initial list of TEA gaps into tiers depending on their potential impact. For TEA, most of the gaps identified are related to developing models or data. Strictly speaking, none of these gaps are essential for heliostat development, but all would aid in the heliostat development process.

14 SOLAR ENERGY↗
DOE OSTI2021

The spatial and temporal evolution of the Portland and Tualatin forearc basins, Oregon, USA

The Portland and Tualatin basins are part of the Salish-Puget-Willamette Lowland, a 900-km-long, forearc depression lying between the volcanic arc and the Coast Ranges of the Cascadia convergent margin. Such inland seaways are characteristic of warm, young slab subduction. We analyzed the basins to better understand their evolution and relation to Coast Range history and to provide an improved tectonic framework for the Portland metropolitan area. We model three key horizons in the basins: (1) the top of the Columbia River Basalt Group (CRBG), (2) the bottom of the CRBG, and (3) the top of Eocene basement. Isochore maps constrain basin depocenters during (1) Pleistocene to mid-Miocene time (0–15 Ma), (2) CRBG (15.5–16.5 Ma), and (3) early Miocene to late Eocene (ca. 17–35 Ma) time. Results show that the Portland and Tualatin basins have distinct mid-Miocene to Quaternary depocenters but were one continuous basin from the Eocene until mid-Miocene time. A NW-striking gravity low coincident with the NW-striking, fault-bounded Portland Hills anticline is interpreted as an older graben coincident with observed thickening of CRBG flows and underlying sedimentary rocks. Neogene transpression in the forearc structurally inverted the Sylvan-Oatfield and Portland Hills normal faults as high-angle dextral-reverse faults, separating the Portland and Tualatin basins. An eastward shift of the forearc basin depocenter and ten-fold decrease in accommodation space provide temporal constraints on the emergence of the Coast Range to the west. Clockwise rotation and northward transport of the forearc is deforming the basins and producing local earthquakes beneath the metropolitan area.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Review—Effects of Solution and Alloy Composition on Critical Crevice Temperature

Critical temperature for localized corrosion can be a good design parameter because localized corrosion is not likely to occur below that temperature. The critical temperature depends on alloy composition, microstructure, and environment chemistry (including its redox potential). This paper reviews the literature on critical temperature for localized corrosion, expressed either as Critical Pitting Temperature (CPT) or Critical Crevice Temperature (CCT). A history of various testing methods is presented. Different approaches for modeling the temperature of transition to active pit growth are reviewed, including probabilistic aspects of critical temperature. A semi-empirical, electrolyte-based, model is described that can be useful in predicting CCT in service environments that differ from standard laboratory test environments. The model predictions are compared to experimental data for various alloys. The effect of solvent on CCT/CPT is described briefly and future avenues of research are recommended.

02 PETROLEUM↗
DOE OSTI2021

Characterization of Nanoscale Pores in Tight Gas Sandstones Using Complex Techniques: A Case Study of a Linxing Tight Gas Sandstone Reservoir

Pore structures with rich nanopores and permeability in tight gas reservoirs are poorly understood up to date. Advanced techniques are needed to be employed to accurately characterize pore structures, especially tiny pores which include micron and nanopores. In this study, various experimental techniques such as scanning electron microscopy (SEM), nuclear magnetic resonance (NMR) T 2 , nitrogen adsorption method, and NMR cryoporometry (NMRC) are combined to interrogate the complex pore systems of the tight gas reservoir in the Linxing formation, Ordos Basin, China. Results show that tight gas sandstones are primarily comprised of residual interparticle and clay-dominated pores. Clay and quartz are two dominate minerals while pyrite occupies a nontrivial amount as well. The permeability of tight gas sandstones is very low, exhibiting an extremely poor positive correlation with porosity. While pore types and relative pore contents are more influential factors on the permeability, accurate characterization of pore size distribution is critical for the permeability of tight gas sandstones. Therefore, complementary characterization methods are carried out, indicating that neither small pores with radii < 100 nm (around peak 1 in NMR T 2 distribution) nor large pores with radii > 5 μ m (around peak 3 in NMR T 2 distribution) control the permeability by analyzing the connectivity of the pores in various size ranges, but rather pores averaging approximately 350 ± X nm (around peak 2 in NMR T 2 distribution) have sufficient connectivity to host and transmit hydrocarbons. The pore size of tight gas sandstones is dominated by the clay-rich mineral assemblage. The study shows that the NMRC technique can be a very promising method, especially when referred to as a promising “roadmap” on how to interrogate tight formations such as the tight gas sands or even shale especially for the nanopore characterization.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

EGS Collab Experiment 1: DNA tracer data on transport through porous media

This submission contains DNA tracer data that supports the analysis and conclusions of the publication, "DNA tracer transport through porous media -The effect of DNA length and adsorption." https://doi.org/10.1029/2020WR028382. This experiment used DNA as an artificial reservoir tracer. Groundwater tracing is an effective way to identify fluid flow pathways and estimate hydrogeologic properties, which are important premises for building reliable hydrological models for transport predictions or contamination mitigations. The objective of this study was to understand the effect of DNA length (i.e., number of base pairs for dsDNA) and adsorption on DNA transport.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assisted computational framework is presented to identify High-Temperature Reservoir Thermal Energy Storage (HT-RTES) site with optimal performance metrics by combining physics-based simulation with stochastic hydrogeologic formation and thermal energy storage operation parameters, artificial neural network regression of the simulation data, and genetic algorithm-enabled multi-objective optimization. A doublet well configuration with a layered (aquitard-aquifer-aquitard) generic reservoir is simulated for cases of continuous operation and seasonal-cycle operation scenarios. Neural network-based surrogate models are developed for the two scenarios and applied to generate the Pareto fronts of the HT-RTES performance for four potential HT-RTES sites. The developed Pareto optimal solutions indicate the performance of HT-RTES is operation-scenario (i.e., fluid cycle) and reservoir-site dependent, and the performance metrics have competing effects for a given site and a given fluid cycle. The developed neural network models can be applied to identify suitable sites for HT-RTES, and the proposed framework sheds light on the design of resilient HT-RTES systems. All the simulations and the neural network model were done by Idaho National Laboratory. A detailed description of the work was reported in publication linked below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Utah FORGE: Fault Reactivation Through Fluid Injection Induced Seismicity Laboratory Experiments

Included are results from shear reactivation experiments on laboratory faults pre-loaded close to failure and reactivated by the injection of fluid into the fault. The sample comprises a single-inclined-fracture (SIF) transecting a cylindrical sample of Westerly granite. All experiments are conducted at ambient temperature and follow a similar protocol: (i) application of confining stresses (3MPa) on the fault fully saturated with DI water, (ii) shear-mobilization through the increase of axial loading at a constant displacement rate until a post-peak steady-state condition is reached, (iii) reduction of axial loading and related shear stress to a prescribed fraction of the peak steady-state frictional strength (typically 60% to 90%, representing intermediate to high magnitudes) and (iv), fault reactivation triggered by a stepwise increase of pore pressure on the fault in 0.1 MPa increments held constant for 1-5 minutes. Mechanical data from three ISCO pumps connected to a Temco pressure vessel measure axial, confining, and fault-related parameters, including fluid pressure (kPa), fluid flow rate (mL/min), and axial displacement (mm). See included code for initial data analysis and visualization for select experiments. Resource names represent experiment numbers found in the "Read Me" file, which describes each experimental setup and parameters.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Utah FORGE: Pump and Probe Test on an Intact Westerly Granite Sample

This dataset contains results from a pump and probe experiment conducted on an intact Westerly Granite sample with a diameter of 1 inch and a height of 1 3/8 inches. The experiment was performed within an aluminum triaxial pressure vessel (TEMCO) to investigate the non-linear acoustic parameters of the sample under varying axial pressures. The confining pressure was maintained at 4 MPa, while the axial pressure was incrementally increased from 1 MPa to 17 MPa before being reduced back to 1 MPa. 5 dynamic pressure oscillations of 0.5 MPa were applied over a 10 minute interval. The dataset includes pump controller data, linear variable differential transformer (LVDT) measurements, and acoustic data. The pump controller data tracks the confining and axial pressures, flow rates, and pump volumes. LVDT measurements provide detailed records of the axial displacement of the cell piston. Additionally, acoustic data captured by s-wave transducers is archived in a compressed file.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Utah FORGE: Pump and Probe Test on a Mated Fracture Westerly Granite Sample

This dataset contains results from a pump and probe experiment conducted on a mated fracture Westerly Granite sample with a diameter of 1 inch and a height of 2 7/8 inches. The experiment was performed within an aluminum triaxial pressure vessel (TEMCO) to investigate the non-linear acoustic parameters of the sample under varying axial pressures. The confining pressure was maintained at 4 MPa, while the axial pressure was incrementally reduced from 17 MPa to 1 MPa in 1 MPa steps. 5 dynamic pressure oscillations of 0.5 MPa were applied over a 10 minute interval. The dataset includes pump controller data, linear variable differential transformer (LVDT) measurements, and acoustic data. The pump controller data tracks the confining and axial pressures, flow rates, and pump volumes. LVDT measurements provide detailed records of the axial displacement of the cell piston. Additionally, acoustic data captured by s-wave transducers is archived in a compressed file.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Multiple Holocene Earthquakes on the Gales Creek Fault, Northwest Oregon Fore-Arc

Several potentially hazardous northwest–striking faults in and around the Portland basin, within the fore-arc of Cascadia, are classified as Quaternary active by the U.S. Geological Survey, but little is known about their Holocene activity. We present new earthquake–timing constraints on the Gales Creek fault (GCF), a 73 km long, northwest–trending fault with youthful geomorphic expression located about 35 km west of Portland. We excavated a paleoseismic trench across the GCF in the populated northern Willamette Valley and document three surface-rupturing earthquakes from stratigraphic and structural relationships. Radiocarbon samples from offset stratigraphy constrain these earthquakes to have occurred ~1000, ~4200, and ~8800 calibrated years before the present. The penultimate earthquake back–tilted a buried soil into the hillslope creating accommodation space that was infilled by a colluvial deposit. The most recent earthquake faulted and formed a fissure within the penultimate colluvial deposit. Our results suggest that the GCF has a recurrence interval of ~4000 yr, and if the full 73 km length were to rupture, it would result in an M w 7.1–7.4 earthquake, providing a significant seismic hazard for the greater Portland metropolitan area.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Variability in Performance of a Machine Learning Seismicity Catalog: Central Italy, 2016–2017

Machine learning (ML) catalogs contain many more earthquakes than routine catalogs, but their performance in phase picking and earthquake detection has not been fully evaluated. We develop station‐level detection probabilities using logistic regression and combine them across a seismic network to compute spatial magnitude‐of‐completeness fields. We apply this approach to two catalogs from the 2016–2017 Central Italy sequence that were constructed from the same seismic network, one routine and one ML‐based. At the station level, the ML picker increases detection sensitivity by identifying smaller magnitude events and detecting earthquakes at greater distances. Spatially, the magnitude of completeness decreases substantially, with median values shifting from 1.6 to 0.5 for P waves and from 1.7 to 0.5 for S waves. However, the ML catalog also shows greater variability in station‐level performance than the routine catalog. These results demonstrate that ML‐based improvements in detectability are widespread but spatially nonuniform, highlighting their benefits, their limitations, and the potential for further improvements.

15 GEOTHERMAL ENERGY↗