Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Subsurface data models”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Saildrone Baja Field Campaign: A Comparison of Surface Meteorology with GEOS Products

The Saildrone Baja field campaign was an international effort to collect measurements across the air-sea interface for a 62-day period between April 11-June 11, 2018. The field campaign was executed using a saildrone, an unmanned surface vehicle (USV) carrying a comprehensive suite of instruments to measure meteorological, ocean surface, and subsurface data. We use these data to validate near-surface meteorology and ocean surface temperature fields in theGlobal Earth Observing System (GEOS). This is the first study using Saildrone data to validate GEOS products. As these USV platforms become more prevalent, they could be used to improve model representation of the air-sea interface variables.

Akella, Santha↗
DOE OSTI2024

Machine Learning-Driven Quantification of CO2 Plume Dynamics at Illinois Basin Decatur Project Sites Using Microseismic Data

This study utilizes machine learning to quantify CO2 plume extents by analyzing microseismic data from the Illinois Basin Decatur Project (IBDP). Leveraging a unique dataset of well logs, microseismic records, and CO2 injection metrics, this work aims to predict the temporal evolution of subsurface CO2 saturation plumes. The findings illustrate that machine learning can predict plume dynamics, revealing vertical clustering of microseismic events over distinct time periods within certain proximities to the injection well, consistent with an invasion percolation model. The buoyant CO2 plume partially trapped within sandstone intervals periodically breaches localized barriers or baffles, which act as leaky seals and impede vertical migration until buoyancy overcomes gravity and capillary forces, leading to breakthroughs along vertical zones of weakness. Between different unsupervised clustering techniques, K-Means and DBSCAN were applied and analyzed in detail, where K-means outperformed DBSCAN in this specific study by indicating the combination of the highest Silhouette Score and the lowest Davies–Bouldin Index. The predictive capability of machine learning models in quantifying CO2 saturation plume extension is significant for real-time monitoring and management of CO2 sequestration sites. The models exhibit high accuracy, validated against physical models and injection data from the IBDP, reinforcing the viability of CO2 geological sequestration as a climate change mitigation strategy and enhancing advanced tools for safe management of these operations.

Iyegbekedo, Ikponmwosa↗
DOE OSTI2023

Data, figures, animations, and scripts associated with the manuscript "Integrated Effects of Site Hydrology and Vegetation on Exchange Fluxes and Carbon Cycling at the Coastal Terrestrial Aquatic Interface"

This package contains the data, figures, animations, and scripts used in "Integrated Effects of Site Hydrology and Vegetation on Exchange Fluxes and Carbon Cycling at the Coastal Terrestrial Aquatic Interface" (Li et al., 2023). This study examines the interactions between soil, vegetation and hydrologic conditions in coastal areas, with a focus on the Chesapeake Bay region. The researchers used a mechanistic model called ATS-PFLOTRAN to explore how these interactions affect exchange process in different regions and the carbon/nitrogen cycle across the terrestrial-aquatic interface (TAI). Simulation scenarios isolate the effects of control factors and reaction constants derived from laboratory experiments. The results show a carbon cycle "hot zone" in coastal wetlands and in the transition zone between wetlands and uplands. Transpiration enhances fluxes between the surface and subsurface domains and increases dissolved oxygen in TAI. The decomposition of leaf-derived organic carbon provides an additional source of carbon for aerobic respiration and denitrification in the TAI. Microbial activity plays a key role in controlling redox conditions and their variability. This modeling study improves the understanding of complex TAI interactions and facilitates the representation of coastal ecosystems in larger-scale Earth system models.Several files can be found from this data package.1. Readme,md: This file describe the Title, Target Journal, Target submission date, Co-author, Science Questions, Hypotheses, Key words, Key message, Model and Data, Repo Structure. The user can read this file first and then go to details.2. mesh.zip: This file contains the mesh file for simulation cases. 3. Figure.zip: This file contains figures used in the manuscript . 4. animation.zip: This file contains animations used in the manuscript . 5. Data.zip: This file contains all required input data, such as concentration and flow boundaries. Also, it contains the DEM and processes results on area fraction. 6. Simulation_setup_and_results.zip: This file contains setup of cases used in the manuscript . The result files are too large, if you need that data, please contact to the Author. 7. notebooks.zip: This file contains the Jupyter notebooks for performing sensitivity analysis and other pre-process and post-process analyses.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Improving Ocean Reanalyses and ENSO Forecasts By Assimilation of Rain Corrected Satellite Sea Surface Salinity Using the GMAO S2S Forecast System

During the past years, we have seen that the La Nina to El Nino transition has had a significant global socio-economic impact and so has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of satellite altimetry and subsurface temperature and salinity from (mostly) Argo help to improve the initialization of the thermocline, while satellite Sea Surface Temperature (SST) aids in constraining surface heat-fluxes, leading to improved subseasonal to seasonal forecasts of the coupled system. However, few studies have focused on improving the fresh-water flux and near-surface density and mixing through assimilation of satellite sea surface salinity (SSS). For expediency, the few ocean models that do assimilate SSS bias-correct the satellite SSS data to normalize towards the near-surface Argo data. However, in rainy regions, where buoyant water sits as a fresh lens at the surface, this assumption is likely inadequate. In previous work, we have shown that adjusting SSS data to bulk salinity (Sb) using the Rain Impact Model (RIM) of Santos-Garcia et al., 2014 has improved the near-surface density and mixed layer depth, leading to deeper thermocline and improved the NINO3.4 SST forecasts. Now we utilize the Soil Moisture/Ocean Salinity, Rain Corrected (SMOS_RC) SSS product provided by the Centre Aval de Traitement des données SMOS (CATDS CPDC) to represent the Sb more accurately at first model layer (in our case 5 m). Rather than using a diffusivity model as with RIM, SMOS_RC relies on an observed relationship between the spatial heterogeneity of SMOS SSS and instantaneous rain rate (RR) (Supply et al., 2020). In order to test the impact of SMOS_RC versus SMOS, we compare two reanalyses over the period 2014 to 2021. For both reanalysis experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF scheme (Penny et al., 2013). One reanalysis additionally assimilates SMOS SSS data as is (i.e., with the fresh bias), and a separate reanalysis is performed assimilating the SMOS_RC data. We assess the impact for near-surface and subsurface dynamics within ocean reanalyses by validating against observations and explore how SSS assimilation (SMOS versus SMOS_RC) impacts dynamical ENSO forecasts using the NASA GMAO Sub-seasonal to Seasonal coupled forecast system (GEOS S2S-3, Molod et al., 2020, Hackert et al., 2023). We will show that improved SSS estimates and near-surface density and mixing led to more accurate coupled air/sea interaction and better ENSO forecasts.

Eric Hackert↗
DOE OSTI2021

Stratigraphic Identification with Airborne Electromagnetic Methods at the Hanford Site, Washington

Stratigraphic units can influence the fate and transport of subsurface contaminants within groundwater. Units having coarse-grained sediments act as preferential flow pathways, and therefore can accelerate the transport of contaminants to reach human and ecological receptors. At legacy waste sites, detailed knowledge of subsurface stratigraphy can be used for effective monitoring and remediation planning to help minimize risk to human health and the environment. Airborne electromagnetic (AEM) methods can non-invasively provide information on kilometer-scale or larger subsurface stratigraphic features and fill informational gaps in directly sampled data from sparsely located boreholes. In this paper, we present inversion results of a 412 line-km frequency-domain AEM survey to delineate subsurface stratigraphic features at the Hanford Site, located in southeastern Washington State. The inversion was performed using a massively parallel 3D electromagnetic modeling and inversion code, where the modeling is based on solving frequency-domain Maxwell’s equations using an unstructured-mesh finite-element method and the inversion employs a Gauss-Newton optimization scheme. The results are compared to an underlying geologic framework model (GFM), built by interpolating contact depths of stratigraphic units interpreted from site borehole datasets. In areas with good borehole coverage, the inversion results show a good match with the GFM to a depth of about 60 m. Outside of these areas, the inversion results exhibit inconsistencies from the assumptions made to create the GFM, demonstrating that the AEM survey results can be used to improve the understanding of the geological conceptual model.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Recent advances in integrated hydrologic models: Integration of new domains

Over the past several decades, hydrologic models have advanced from independent models of the surface and subsurface to integrated models that can capture the terrestrial hydrologic cycle within one framework. In recent years, these coupled frameworks have seen the inclusion of biogeochemical processes, ecohydrology, sedimentation and erosion, cold region hydrology, anthropogenic activities, and atmospheric processes. This expansion is the result of increased computational, data, and modeling capabilities and capacities, as well as improved understanding of the processes that drive these integrated systems. Here, in this study, we review these recent advances to integrate new processes and systems into existing terrestrial hydrologic models and highlight the significant challenges and opportunities that remain. We identify that with so many models currently available and in development, selecting the most appropriate model is difficult, and we suggest a path for new or novice modelers to find the most appropriate code based on their needs. In addition, data required to parameterize and calibrate these models can often constrain their applicability and usefulness. However, advances in environmental sensors and measurement technology, in addition to data assimilation of non-traditional data (e.g. remote sensing, qualitative data) are providing new ways of addressing this issue. As we expand hydrologic models to integrate more processes and systems, our computational demands also increase. Recent and emerging advances in computational platforms, including cloud and quantum computing, in addition to the use of machine learning to capture some processes, will continue to support the use of increasingly larger and more complex, process-based models. Finally, we highlight that it is critical to develop state-of-the-science models that are accessible to all model users, not just those applied for research and development. We encourage continued development of diverse modeling platforms, considering the user needs, data availability, and computational resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

From Micro-environments to Macroscopic Effects: How the Alkaline Hydrogen Evolution Reaction Drives Cu Cathodic Corrosion

Cathodic corrosion of copper (Cu) has posed a significant challenge for over a century, impeding various technological progresses such as electrochemical conversion of CO 2 (eCO 2 RR) into fuels and other value-added carbon products. Here, in this study, employing a combined Density Functional Theory (DFT) and kinetic Monte Carlo (kMC) simulation approach, we delve into the atomistic level mechanism driving this phenomenon in Cu. Our hypothesis posits the pivotal role of alkaline hydrogen evolution reaction (HER) in facilitating cathodic corrosion in Cu. We rigorously develop a pH-dependent hydroxide (OH) adsorption mechanism and calculate the equilibrium OH coverage (𝜃 OH ) at varying pH levels, the thermodynamic stability of subsurface oxygen (O sub ), as well as the Cu-vacancy mediated diffusion of subsurface oxygens (O sub ). Through comprehensive analysis, we establish correlation among various microenvironments, including oxygen diffusion in subsurface layers, pH-dependent OH adsorption, and Cu dissolution into the electrolyte as (Cu-OH) complexes. Furthermore, our investigation explores the correlation between surface coordination environment of active sites and cathodic corrosion of Cu. Finally, by integrating DFT-derived thermodynamic data into a kMC model, we successfully predict the formation of experimentally observed corrosion pits on Cu-surfaces. This combined approach not only advances our fundamental understanding of Cu cathodic corrosion but also offers insights crucial for developing effective corrosion mitigation strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Surface Meteorology at Teller Mile 47 Watershed, Seward Peninsula, Alaska, Ongoing from 2018

Meteorological data are currently being collected at one location at the Teller Mile 47 (TL_MM47) Research Basin Site, Seward Peninsula (N64 58' 36.918", W166 12' 32.67", 67 meters above sea level). The site was installed and initial measurements started in September 2018 and it has operated continuously since then. The meteorological station is co-located with a continuous snow depth sensor and two soil pits for subsurface temperature and moisture measurements. These data are being collected to better understand the energy dynamics above the active layer and permafrost. They complement in-situ snow and soil measurements also at this location. The data could also be used as supporting measurements for other research and modeling activities. There are 35 comma separated value format (*.csv) files provided, where each file contains the full data for an individual parameter (e.g. air temperature at 1.5 meters above the ground surface (teller_m47_air_temperature_150cm_ags_Avg.csv) or soil temperature 20 centimeters below ground surface (teller_m47_dry_soil_pit_temperature_20cmbgs_Avg.csv)) plus the time in Universal Coordinated Time (UTC) and Alaska Standard Time (UTC time minus nine hours). The site was installed and initial measurements started in September 2018. It has been operated continuously since. Primary data gaps are due to battery failure or sensor failure. These data are being collected to better understand the surface energy dynamics above the active layer and permafrost. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy?s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy?s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

A cool anomaly off northern California - An investigation using IR imagery and in situ data

The OPTOMA (Ocean Prediction Through Observation, Modeling and Analysis) program is developing an ocean descriptive-predictive system for four-dimensional data assimilation. It is presently concerned with the mesoscale variability in the California Current System (CCS). The present paper has the objective to assess the relationship of surface temperature structure to subsurface temperature structure and flow fields. Surface temperature anomalies are related to the mesoscale horizontal advective and subsurface mass fields. The cool anomaly off northern California in summer 1982 is discussed, taking into account the temperature structure along transects, T-S variations and inferred water masses, variation of horizontal temperature patterns with depth, and synoptic information from IR data.

Rienecker, M. M.↗
DOE OSTI2021

Widespread deep seismicity in the Delaware Basin, Texas, is mainly driven by shallow wastewater injection

Significance The Delaware Basin, western Texas, has experienced a surge in the number of earthquakes. We investigate basin-wide earthquake, hydrogeologic, industrial, and geodetic data spanning 1993–2020 to identify the reasons for the increase. We use these data and models to quantify the stress changes from wastewater injection and hydrocarbon extraction. We demonstrate that the basin-wide seismicity is dominated by the stresses caused by shallow injection that are transmitted vertically by deforming the underlying crust. We analyze both injection and production data to understand how subsurface properties control earthquake locations and timings. We suggest that injecting wastewater into porous formations will minimize seismic hazard. We establish a framework explaining why earthquakes sometimes occur and sometimes do not occur within human activity-impacted areas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Deep Image Prior Enabled Full Waveform Inversion (Final Technical Report)

MS Student Naveen Gupta worked on the problem of full waveform inversion (FWI) using neural networks as shown in Figure 1. Our goal was to learn a neural network to represent the subsurface velocity model, which when fed into the FWI module (implemented using a numerical forward model of wave equations) produces amplitude estimates that match with ground-truth observations of amplitude. We used neural networks to solve the inverse problem of estimating velocity distributions for a given seismic amplitude data such that, once trained, our neural network model can generate a distribution of velocity profiles for different random vectors fed as inputs to the neural network model.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2000

The Geologic History of Mars: An Astrobiology Perspective

Fourteen SNC meteorites contain information which must be incorporated with recent spaceflight data for developing Mars' geologic history. SNCs have crystallization ages of 4500 to 160 m.y. Tle oldest meteorite ALH84001 contains information on the Noachian period of Mars' history. There are no meteorites from the Hesperian period and the remaining 13 meteorites fall into two age groups within the Amazonian: The nakhlites around 1300 m.y. and the shergottites between 800-160 m.y. Oxygen isotopic analysis of Martian samples shows two distinct O2 reservoirs throughout Martian history indicating late additions of volatiles and a lack of plate tectonics prior to 3.9 Gy. Evidence for percolation of aqueous brines through impact-produced fractures in the rocky surface is contained in the 3.9 Gy-old ALH84001 carbonate deposits. These carbonates precipitated at approx. 100 C. At this time life had already evolved on Earth. Early Mars could have hosted life similar to the bacteria that inhabited early Earth. Potential microorganisms could have been transported into fractures by carbonate-bearing waters and their remains could have become incorporated into the precipitated carbonate. Since Mars had a weak magnetic field at this time, it can be hypothesized that some of the Martian microorganisms may have been similar to terrestrial magnetotactic bacteria. Over geologic time episodic cratering, and tectonic events have occurred on Mars along with the periodic release of subsurface waters which may have produced clays within SNC meteorites. The geochemical data contained within SNC meteorites complements previous observational data and the recent Mars Global Surveyor data to provide a geological and environmental history which spans almost the entire lifespan on Mars. One of the outstanding features of this model is the possible creation of an early (about 4 Gy) volatile reservoir distinct from the outgassed Mars volatiles, and the persistence of this reservoir throughout most, if not all of subsequent Mars' history. Within the framework of this history a potential scenario for a possible record of living organisms is provided by suggestive structures and organic signatures trapped within secondary mineral deposits and alteration features of some SNC meteorites. Tracing the differences in oxygen isotopic compositions within Martian components allows us to gain insight in the history of Mars.

Gibson, Everett K.↗
NASA NTRS2002

Technical Challenges of Drilling on Mars

In the last year, NASA's Mars science advisory committee (MEPAG: Mars Exploration Payload Advisory Group) has formally recommended that deep drilling be undertaken as a priority investigation to meet astrobiology and geology goals. This proposed new dimension in Mars exploration has come about for several reasons. Firstly, geophysical models of the martian subsurface environment indicate that we may well find liquid water (in the form of brines) under ground-ice at depths of several kilometers near the equator. On Earth we invariably find life forms associated with any environmental niche that supports liquid water. New data from the Mars Global Surveyor have shown that the most recent volcanism on Mars is very young so we cannot rule out contemporary volcanism -- in which case subsurface temperatures consistent with having water in its liquid phase may be found at relatively shallow depths. Secondly, in recent decades we have learned to our surprise that the Earth's subsurface (microbial) biosphere extends to depths of many kilometers and this discovery provides the basis for planning to explore the martian subsurface in search of ancient or even extant microbial life forms. We know (from Viking measurements) that all the biogenic elements (C, H, O, N, P, S) are available on Mars. What we therefore hope to learn is whether or not the evolution of life is inevitable given the necessary ingredients and, by implication, whether the Universe may be teeming with life. The feasibility of drilling deep into the surface of Mars has been the subject of increasing attention within NASA (and more recently among some of its international partners) for several years and this led to a broad-based feasibility study carried out by the Los Alamos National Laboratory and, subsequently, to the development of several hardware prototypes. This paper is intended to provide a general survey of that activity.

Briggs, Geoffrey↗
NASA NTRS2014

Real-Time Science Operations to Support a Lunar Polar Volatiles Rover Mission

Future human exploration of the Moon will likely rely on in situ resource utilization (ISRU) to enable long duration lunar missions. Prior to utilizing ISRU on the Moon, the natural resources (in this case lunar volatiles) must be identified and characterized, and ISRU demonstrated on the lunar surface. To enable future uses of ISRU, NASA and the CSA are developing a lunar rover payload that can (1) locate near subsurface volatiles, (2) excavate and analyze samples of the volatile-bearing regolith, and (3) demonstrate the form, extractability and usefulness of the materials. Such investigations are important both for ISRU purposes and for understanding the scientific nature of these intriguing lunar volatile deposits. Temperature models and orbital data suggest near surface volatile concentrations may exist at briefly lit lunar polar locations outside persistently shadowed regions. A lunar rover could be remotely operated at some of these locations for the approx. 2-14 days of expected sunlight at relatively low cost. Due to the limited operational time available, both science and rover operations decisions must be made in real time, requiring immediate situational awareness, data analysis, and decision support tools. Given these constraints, such a mission requires a new concept of operations. In this paper we outline the results and lessons learned from an analog field campaign in July 2012 which tested operations for a lunar polar rover concept. A rover was operated in the analog environment of Hawaii by an off-site Flight Control Center, a rover navigation center in Canada, a Science Backroom at NASA Ames Research Center in California, and support teams at NASA Johnson Space Center in Texas and NASA Kennedy Space Center in Florida. We find that this type of mission requires highly efficient, real time, remotely operated rover operations to enable low cost, scientifically relevant exploration of the distribution and nature of lunar polar volatiles. The field demonstration illustrated the need for science operations personnel in constant communications with the flight mission operators and the Science Backroom to provide immediate and continual science support and validation throughout the mission. Specific data analysis tools are also required to enable immediate data monitoring, visualization, and decision making. The field campaign demonstrated that this novel methodology of real-time science operations is possible and applicable to providing important new insights regarding lunar polar volatiles for both science and exploration.

Moon; Volatiles; Rover; Missions↗
NASA NTRS1993

Evaluation of a distributed catchment scale water balance model

The validity of some of the simplifying assumptions in a conceptual water balance model is investigated by comparing simulation results from the conceptual model with simulation results from a three-dimensional physically based numerical model and with field observations. We examine, in particular, assumptions and simplifications related to water table dynamics, vertical soil moisture and pressure head distributions, and subsurface flow contributions to stream discharge. The conceptual model relies on a topographic index to predict saturation excess runoff and on Philip's infiltration equation to predict infiltration excess runoff. The numerical model solves the three-dimensional Richards equation describing flow in variably saturated porous media, and handles seepage face boundaries, infiltration excess and saturation excess runoff production, and soil driven and atmosphere driven surface fluxes. The study catchments (a 7.2 sq km catchment and a 0.64 sq km subcatchment) are located in the North Appalachian ridge and valley region of eastern Pennsylvania. Hydrologic data collected during the MACHYDRO 90 field experiment are used to calibrate the models and to evaluate simulation results. It is found that water table dynamics as predicted by the conceptual model are close to the observations in a shallow water well and therefore, that a linear relationship between a topographic index and the local water table depth is found to be a reasonable assumption for catchment scale modeling. However, the hydraulic equilibrium assumption is not valid for the upper 100 cm layer of the unsaturated zone and a conceptual model that incorporates a root zone is suggested. Furthermore, theoretical subsurface flow characteristics from the conceptual model are found to be different from field observations, numerical simulation results, and theoretical baseflow recession characteristics based on Boussinesq's groundwater equation.

Troch, Peter A.↗
DOE OSTI2023

The influence of physical and algorithmic factors on simulated far-field waveforms and source–time functions of underground explosions using unsupervised machine learning

SUMMARY Characterizing explosion sources and differentiating between earthquake and underground explosions using distributed seismic networks becomes non-trivial when explosions are detonated in cavities or heterogeneous ground material. Moreover, there is little understanding of how changes in subsurface physical properties affect the far-field waveforms we record and use to infer information about the source. Simulations of underground explosions and the resultant ground motions can be a powerful tool to systematically explore how different subsurface properties affect far-field waveform features, but there are added variables that arise from how we choose to model the explosions that can confound interpretation. To assess how both subsurface properties and algorithmic choices affect the seismic wavefield and the estimated source functions, we ran a series of 2-D axisymmetric non-linear numerical explosion experiments and wave propagation simulations that explore a wide array of parameters. We then inverted the synthetic far-field waveform data using a linear inversion scheme to estimate source–time functions (STFs) for each simulation case. We applied principal component analysis (PCA), an unsupervised machine learning method, to both the far-field waveforms and STFs to identify the most important factors that control variance in the waveform data and differences between cases. For the far-field waveforms, the largest variance occurs in the shallower radial receiver channels in the 0–50 Hz frequency band. For the STFs, both peak amplitude and rise times across different frequencies contribute to the variance. We find that the ground equation of state (i.e. lithology and rheology) and the explosion emplacement conditions (i.e. tamped versus cavity) have the greatest effect on the variance of the far-field waveforms and STFs, with the ground yield strength and fracture pressure being secondary factors. Differences in the PCA results between the far-field waveforms and STFs could possibly be due to near-field non-linearities of the source that are not accounted for in the estimation of STFs and could be associated with yield strength, fracture pressure, cavity radius and cavity shape parameters. Other algorithmic parameters are found to be less important and cause less variance in both the far-field waveforms and STFs, meaning algorithmic choices in how we model explosions are less important, which is encouraging for the further use of explosion simulations to study how physical Earth properties affect seismic waveform features and estimated STFs.

58 GEOSCIENCES↗
DOE OSTI2025

Integration and Demonstration of Monitoring, Modeling, and Prediction of DV-1 Amendment Performance at the Bench Scale: DV-1 Amendment Demonstration

During fiscal years 2024 and 2025, the U.S. Department of Energy’s Hanford Field Office commissioned Pacific Northwest National Laboratory to conduct applied research aimed at reducing the cost, time, and uncertainty associated with in situ treatment of vadose zone contaminants at the Hanford Site. This report outlines the integration of three key research efforts into a meso-scale demonstration designed to advance field-scale solutions that aim to (1) optimize the delivery of chemical amendments to contaminated soils, (2) reduce uncertainty in amendment delivery performance assessment using advanced monitoring techniques, and (3) provide real-time insights into when and where amendment-induced precipitation reactions occur in the subsurface. To achieve these objectives, the tank-scale (~ 1 cubic meter) Geophysical Imaging of Flow and Transport (GIFT) system was developed. GIFT enables experimental testing of amendment delivery while incorporating automated multi-modal monitoring approaches, including pressure measurements, direct fluid sampling, and remote time-lapse geophysical imaging. The data generated from these monitoring techniques will serve as inputs for a generative artificial-intelligence-driven digital twin – a numerical simulation model designed to honor observed data while quantifying uncertainty in simulation accuracy. Using this simulator, researchers will refine an amendment injection strategy to maximize delivery efficiency within a low-permeability soil zone. Monitoring data will be interpreted through simulated outputs to enhance understanding of the injection process. The efficacy of this integrated approach will be evaluated through direct sampling at the conclusion of the experiment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

GEOPHIRES Simulations for Deep Direct Use (DDU) Projects

This folder contains the GEOPHIRES codes and input files for running the base case scenarios for the six deep direct-use (DDU) projects. The six DDU projects took place during 2017-2020 and were funded by the U.S. Department of Energy Geothermal Technologies Office. They investigated the potential of geothermal deep direct-use at six locations across the country. The projects were conducted by Cornell University, West Virginia University (WVU), University of Illinois (U of IL), Sandia National Laboratory (SNL), Portland State University (PSU), and National Renewable Energy Laboratory (NREL). Four projects (Cornell, WVU, U of IL, SNL) investigated geothermal for direct heating of a local campus or community, the project by PSU considered seasonal subsurface storage of solar heating, and the NREL project investigated geothermal heating for turbine inlet cooling using absorption chillers. To allow comparison of techno-economic results across the six DDU projects, GEOPHIRES simulations were set up and conducted for each project. The GEOPHIRES code was modified for each project to simulate the local application and incorporate project-specific assumptions and results such as reservoir production temperature or financing conditions. The base case input file is included which simulates the base case conditions assumed by each project team. The levelized cost of heat (LCOH) is calculated and matches the base case LCOH reported by the project teams.

15 GEOTHERMAL ENERGY↗