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All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Design and Preliminary Testing of a High Performance Antiproton Trap (HiPAT)

Antimatter represents the pinnacle of energy density, offering the potential to enhance current fusion/fission concepts enabling various classes of deep space missions. Current production rates are sufficient to support proof-of-concept evaluation of many key technologies associated with antimatter-derived propulsion. Storage has been identified as a key enabling technology for all antimatter-related operations, and as such is the current focus of this NASA-MSFC effort to design and fabricate a portable device capable of holding up to 10(exp 12) particles. Hardware has been assembled and initial tests are underway to evaluate the trap behavior using electron gun generated, positive hydrogen ions. Ions have been stored for tens of minutes, limited by observed interaction with background gas. Additionally, radio frequency manipulation is being tested to increase lifetime by stabilizing the stored particles, potentially reducing their interaction with background gas, easing requirements on ultimate trap vacuum and precision mechanical alignment.

Martin, James↗
DOE OSTI2023

Insights into Methodologies and Stochastic Optimization of Thermal Energy Storage-Coupled Advanced Reactor Systems: A Comparison of Methods for Accessing Long-Term Sub-System Sizing Adequacy

This paper investigates the potential of coupling Thermal Energy Storage (TES) with Advanced Reactors (ARs) to address uncertainties posed by climate change in deep decarbonized power systems. The TES Use-case Team at Idaho National Laboratory (INL) has examined the potential of storing thermal energy from ARs during low demand periods and optimizing discharge during peak-priced hours, in both steady-state and transient conditions. Building on this groundwork, this study bridges the gaps in optimal sizing of the sub-system of TES-coupled AR systems using Risk Analysis Virtual Environment (RAVEN) and Holistic Energy Resource Optimization Network (HERON), INL?s framework for grid optimization. By applying this framework, we present statistically-robust optimal charge, discharge including balance of plant (BOP), and storage sizing for the High-Temperature Gas-Cooled Reactor (HTGR) with 203 MWth output. To this end, we generated synthetic price samples for 30 years using 2018 ? 2021 real-time market data from ERCOT, PJM and MISO. Our results reveals that the TES-coupled HTGR system is highly effective in maximizing revenue from electricity sales. We observed a substantial increase of 40 % in ERCOT and a noteworthy 15 % increase in PJM and MISO when compared to the conventional BOP without TES. This improvement is achieved through regionally-tailored sub-system sizing, which ranges from 398 to 416 MWth for the discharge system and 610 to 1029 MWth for the TES. We find that the average electricity price directly impacts the overall economics, while price volatility influences storage size. Additional sensitivity analyses were performed to access the impact of key assumptions on system economics and sizing, differentiating the optimization window (i.e., 24 ? 219 hours of chronological observations) and by imposing storage continuity condition in tracking TES cycles. We observed that at the 120-hour of the optimization window, a reasonable balance between computation time and accuracy was achieved. Our analysis also highlights the significance of conducting multi-day cycle analysis (> 120-hour) for TES to capture interaction between electricity prices and storage dynamics, providing a comprehensive understanding of TES behavior that AR developers should integrate into their plant designs.

25 ENERGY STORAGE↗
DOE OSTI2025

Anomalous electroweak physics unraveled via evidential deep learning

The ever-growing ecosystem of beyond standard model (BSM) calculations and parametrizations has motivated the development of systematic methods for making quantitative cross-comparisons over the wide range of possible models, especially with controllable uncertainties. In this setting, the language of uncertainty quantification (UQ) furnishes useful metrics for assessing statistical overlaps and discrepancies among BSM and related models. In this study, we leverage recent machine learning (ML) developments in evidential deep learning (EDL) for UQ to separate data (aleatoric) and knowledge (epistemic) uncertainties in a model-discrimination setting. We construct several potentially BSM-motivated scenarios for the anomalous electroweak interaction (AEWI) of neutrinos with nucleons in deep inelastic scattering ( v DIS). These scenarios are then quantitatively mapped, as a demonstration, alongside Monte Carlo replicas of the CT18 PDFs used to calculate the $\varDelta \chi ^{2}$ statistic for a typical multi-GeV v DIS experiment, CDHSW. Our framework effectively highlights areas of model agreement and provides a classification of out-of-distribution (OOD) samples. By offering the opportunity to quantitatively understand model overlaps, the approach presented in this work can help facilitate efficient BSM model exploration and exclusion for future New Physics searches.

AI↗
DOE OSTI2024

How well are hazards associated with derechos reproduced in regional climate simulations?

Abstract. A 15-member ensemble of convection-permitting regional simulations of the fast-moving and destructive derecho of 29–30 June 2012 that impacted the northeastern urban corridor of the USA is presented. This event generated 1100 reports of damaging winds, generated significant wind gusts over an extensive area of up to 500 000 km2, caused several fatalities, and resulted in widespread loss of electrical power. Extreme events such as this are increasingly being used within pseudo-global-warming experiments to examine the sensitivity of historical, societally important events to global climate non-stationarity and how they may evolve as a result of changing thermodynamic and dynamic contexts. As such it is important to examine the fidelity with which such events are described in hindcast experiments. The regional simulations presented herein are performed using the Weather Research and Forecasting (WRF) model. The resulting ensemble is used to explore simulation fidelity relative to observations for wind gust magnitudes, spatial scales of convection (as is manifest in high composite reflectivity, cREF), and both rainfall and hail production as a function of model configuration (microphysics parameterization, lateral boundary conditions (LBCs), start date, use of nudging, compiler choice, damping, and number of vertical levels). We also examine the degree to which each ensemble member differs with respect to key mesoscale drivers of convective systems (e.g., convective available potential energy and vertical wind shear) and critical manifestations of deep convection, e.g., vertical velocities, cold-pool generation, and how those properties relate to the correct characterization of the associated atmospheric hazards (wind gusts and hail). Use of a double-moment, seven-class scheme with number concentrations for all species (including hail and graupel) results in the greatest fidelity of model-simulated wind gusts and convective structure to the observations of this event. All ensemble members, however, fail to capture the intensity of the event in terms of the spatial extent of convection and the production of high near-surface wind gusts. We further show very high sensitivity to the LBCs employed and specifically that simulation fidelity is higher for simulations nested within ERA-Interim compared to ERA5. Excess convective available potential energy (CAPE) in all ensemble members after the derecho passage leads to excess production of convective cells, wind gusts, cREF > 40 dBZ, and precipitation during a frontal passage on the subsequent day. This event proved very challenging to forecast in real time and to reproduce in the 15-member hindcast simulation ensemble presented here. Future work could examine if simulations with other initial and lateral boundary conditions can achieve greater fidelity.

Shepherd, Tristan (ORCID:0000000186276419)↗
NASA NTRS2011

Qualifications of Bonding Process of Temperature Sensors to Deep-Space Missions

A process has been examined for bonding a platinum resistance thermometer (PRT) onto potential aerospace materials such as flat aluminum surfaces and a flexible copper tube to simulate coaxial cables for flight applications. Primarily, PRTs were inserted into a silver-plated copper braid to avoid stresses on the sensor while the sensor was attached with the braid to the base material for long-duration, deep-space missions. A1-1145/graphite composite (planar substrate) and copper tube have been used in this study to assess the reliability of PRT bonding materials. A flexible copper tube was chosen to simulate the coaxial cable to attach PRTs. The substrate materials were cleaned with acetone wipes to remove oils and contaminants. Later, the surface was also cleaned with ethyl alcohol and was air-dried. The materials were gently abraded and then were cleaned again the same way as previously mentioned. Initially, shielded (silver plated copper braid) PRT (type X) test articles were fabricated and cleaned. The base antenna material was pretreated and shielded, and CV-2566 NuSil silicone was used to attach the shielded PRT to the base material. The test articles were cured at room temperature and humidity for seven days. The resistance of the PRTs was continuously monitored during the thermal cycling, and the test articles were inspected prior to, at various intermediate steps during, and at the end of the thermal cycling as well. All of the PRTs survived three times the expected mission life for the JUNO project. No adhesion problems were observed in the PRT sensor area, or under the shielded PRT. Furthermore, the PRT resistance accurately tracked the thermal cycling of the chamber.

Ramesham, Rajeshuni↗
DOE OSTI2021

DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks

Abstract Background Due to the complexity of the biological systems, the prediction of the potential DNA binding sites for transcription factors remains a difficult problem in computational biology. Genomic DNA sequences and experimental results from parallel sequencing provide available information about the affinity and accessibility of genome and are commonly used features in binding sites prediction. The attention mechanism in deep learning has shown its capability to learn long-range dependencies from sequential data, such as sentences and voices. Until now, no study has applied this approach in binding site inference from massively parallel sequencing data. The successful applications of attention mechanism in similar input contexts motivate us to build and test new methods that can accurately determine the binding sites of transcription factors. Results In this study, we propose a novel tool (named DeepGRN) for transcription factors binding site prediction based on the combination of two components: single attention module and pairwise attention module. The performance of our methods is evaluated on the ENCODE-DREAM in vivo Transcription Factor Binding Site Prediction Challenge datasets. The results show that DeepGRN achieves higher unified scores in 6 of 13 targets than any of the top four methods in the DREAM challenge. We also demonstrate that the attention weights learned by the model are correlated with potential informative inputs, such as DNase-Seq coverage and motifs, which provide possible explanations for the predictive improvements in DeepGRN. Conclusions DeepGRN can automatically and effectively predict transcription factor binding sites from DNA sequences and DNase-Seq coverage. Furthermore, the visualization techniques we developed for the attention modules help to interpret how critical patterns from different types of input features are recognized by our model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2007

Broken-Plane Maneuver Applications for Earth to Mars Trajectories

Optimization techniques are critical when investigating Earth to Mars trajectories since they have the potential of reducing the total (delta)V of a mission. A deep space maneuver (DSM) executed during the cruise may improve a trajectory by reducing the total mission V. Nonetheless, DSMs not only may improve trajectory performance (from an energetic point of view) but also open up new families of trajectories that would satisfy very specific mission requirements not achievable with ballistic trajectories. In the following pages, various specific examples showing the potential advantages of the usage of broken plane maneuvers will be introduced. These examples correspond to possible scenarios for Earth to Mars trajectories during the next decade (2010-2020).

Abilleira, Fernando↗
DOE OSTI2017

Dynamic Radioisotope Power System Development for Space Explorations

Dynamic power conversion offers the potential to produce radioisotope power systems (RPS) that generate higher power outputs and utilize the Pu-238 radioisotope more efficiently than Radioisotope Thermoelectric Generators (RTG). Additionally, dynamic systems also offer the potential of producing generators with significantly reduced power degradation over the course of deep space missions so that more power will be available at the end of the mission when it is needed for both powering the science and transmitting the results. The development of dynamic generators involves addressing technical issues not typically associated with traditional thermoelectric generators. Developing long-life, robust and reliable dynamic conversion technology is challenging yet essential to building a suitable generator. Considerations include working within existing handling infrastructure where possible so that development costs can be kept low and integrating dynamic generators into spacecraft, which may be more complex than integration of static systems. Methods of interfacing to and controlling a dynamic generator must be considered and new potential failure modes must be taken into account. This paper will address some of the key issues of dynamic RPS design, development and adaption.Dynamic power conversion offers the potential to produce Radioisotope Power Systems (RPS) that generate higher power outputs and utilize the available heat source plutonium fuel more efficiently than Radioisotope Thermoelectric Generators. Additionally, dynamic systems offer the potential of producing generators with significantly reduced power degradation over the course of deep space missions so that more power would be available at the end of the mission, when it is needed most for both powering science instruments and transmitting the resulting data. The development of dynamic generators involves addressing technical issues not typically associated with traditional thermoelectric generators. Developing long-life, robust, and reliable dynamic conversion technology is challenging yet essential to building a suitable flight-ready generator. Considerations include working within existing hardware-handling infrastructure, where possible, so that development costs can be kept low, and integrating dynamic generators into spacecraft, which may be more complex than integration of static thermoelectric systems. Methods of interfacing to and controlling a dynamic generator must also be considered, and new potential failure modes must be taken into account. This paper will address some of the key issues of dynamic RPS design, development, and adaption.

Qualls, A L↗
DOE OSTI2025

Anomaly Detection in Seismic Data with Deep Learning: Application for Instrument Failure Detection and Forecasting

Seismic data quality assessment (QA) is the first and one of the most important steps before conducting any further data analysis. Traditional methods involve checking various metrics, such as spike detection and power spectral density, by setting strict thresholds or comparing data against synthetic benchmarks. However, these approaches often rely on pre-existing knowledge and assumptions about data anomalies, leading to potential misclassification of unusual cases. Here, in this study, we propose a deep autoencoder model, an unsupervised learning approach that evaluates data quality without making assumptions about normal and anomalous data, which can be used to identify deviations in recorded data that may indicate nascent instrument failure. We test the model with the U.S. International Monitoring System (IMS) seismic stations and demonstrate the capability of detecting anomalies on a monthly scale. This could prompt station operators to examine potential problems early, allowing sufficient time for instrument maintenance to prevent data outages. In addition, we use a new manually selected testing dataset to compare our model performance against two supervised machine learning (ML) approaches and a standard QA package, as baseline models. When applied to the dataset containing known data anomalies, performance of the supervised and unsupervised ML approaches is similar, with an accuracy of 88.1% for our model compared to ∼90% for the supervised ML approach and 78.2% for the standard QA package. Our model outperforms the baseline models when applied to new stations, where new types of data anomalies can be station-specific and not included in the training dataset. Finally, we show model transferability by training the model with data from the Global Seismograph Network only and applying it to the IMS network data. The results suggest that our model is generalizable and can be applied to new stations with good accuracy.

Lin, Jiun-Ting [Lawrence Livermore National Labora↗
DOE OSTI2021

Low-Level Mesoscale and Cloud-Scale Interactions Promoting Deep Convection Initiation

Data from scanning radars, radiosondes, and vertical profilers deployed during three field campaigns are analyzed to study interactions between cloud-scale updrafts associated with initiating deep moist convection and the surrounding environment. Three cases are analyzed in which the radar networks permitted dual-Doppler wind retrievals in clear air preceding and during the onset of surface precipitation. These observations capture the evolution of (i) the mesoscale and boundary layer flow, and (ii) low-level updrafts associated with deep moist convection initiation (CI) events yielding sustained or short-lived precipitating storms. The elimination of convective inhibition did not distinguish between sustained and unsustained CI events, though the vertical distribution of convective available potential energy may have played a role. The clearest signal differentiating the initiation of sustained versus unsustained precipitating deep convection was the depth of the low-level horizontal wind convergence associated with the mesoscale flow feature triggering CI, a sharp surface wind shift boundary, or orographic upslope flow. The depth of the boundary layer relative to the height of the LFC failed to be a consistent indicator of CI potential. Widths of the earliest detectable low-level updrafts associated with sustained precipitating deep convection were ~3–5 km, larger than updrafts associated with surrounding boundary layer turbulence (~1–3 km wide). It is hypothesized that updrafts of this larger size are important for initiating cells to survive the destructive effects of buoyancy dilution via entrainment.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Supporting Development for the Stirling Radioisotope Generator and Advanced Stirling Technology Development at NASA Glenn

A high-efficiency, 110-W(sub e) (watts electric) Stirling Radioisotope Generator (SRG110) for possible use on future NASA Space Science missions is being developed by the Department of Energy, Lockheed Martin, Stirling Technology Company (STC), and NASA Glenn Research Center (GRC). Potential mission use includes providing spacecraft onboard electric power for deep space missions and power for unmanned Mars rovers. GRC is conducting an in-house supporting technology project to assist in SRG110 development. One-, three-, and six-month heater head structural benchmark tests have been completed in support of a heater head life assessment. Testing is underway to evaluate the key epoxy bond of the permanent magnets to the linear alternator stator lamination stack. GRC has completed over 10,000 hours of extended duration testing of the Stirling convertors for the SRG110, and a three-year test of two Stirling convertors in a thermal vacuum environment will be starting shortly. GRC is also developing advanced technology for Stirling convertors, aimed at substantially improving the specific power and efficiency of the convertor and the overall generator. Sunpower, Inc. has begun the development of a lightweight Stirling convertor, under a NASA Research Announcement (NRA) award, that has the potential to double the system specific power to about 8 W(sub e) per kilogram. GRC has performed random vibration testing of a lowerpower version of this convertor to evaluate robustness for surviving launch vibrations. STC has also completed the initial design of a lightweight convertor. Status of the development of a multi-dimensional computational fluid dynamics code and high-temperature materials work on advanced superalloys, refractory metal alloys, and ceramics are also discussed.

Thieme, Lanny G.↗
NASA NTRS2005

Supporting Development for the Stirling Radioisotope Generator and Advanced Stirling Technology Development at NASA Glenn Research Center

A high-efficiency, 110-We (watts electric) Stirling Radioisotope Generator (SRG110) for possible use on future NASA Space Science missions is being developed by the Department of Energy, Lockheed Martin, Stirling Technology Company (STC), and NASA Glenn Research Center (GRC). Potential mission use includes providing spacecraft onboard electric power for deep space missions and power for unmanned Mars rovers. GRC is conducting an in-house supporting technology project to assist in SRG110 development. One-, three-, and six-month heater head structural benchmark tests have been completed in support of a heater head life assessment. Testing is underway to evaluate the key epoxy bond of the permanent magnets to the linear alternator stator lamination stack. GRC has completed over 10,000 hours of extended duration testing of the Stirling convertors for the SRG110, and a three-year test of two Stirling convertors in a thermal vacuum environment will be starting shortly. GRC is also developing advanced technology for Stirling convertors, aimed at substantially improving the specific power and efficiency of the convertor and the overall generator. Sunpower, Inc. has begun the development of a lightweight Stirling convertor, under a NASA Research Announcement (NRA) award, that has the potential to double the system specific power to about 8 We/kg. GRC has performed random vibration testing of a lower-power version of this convertor to evaluate robustness for surviving launch vibrations. STC has also completed the initial design of a lightweight convertor. Status of the development of a multi-dimensional computational fluid dynamics code and high-temperature materials work on advanced superalloys, refractory metal alloys, and ceramics are also discussed.

Thieme, Lanny G.↗
NASA NTRS2016

Auto-Gopher-2 - Wireline Deep Sampler Driven by Percussive Piezoelectric Actuator and Rotary EM Motors

Two of the key purposes of future NASA’s solar system exploration of planetary bodies are the search for potentially preserved bio-signatures and for habitable regions. To address these objectives, a biologically inspired wireline deep rotary-percussive drill, called Auto-Gopher, has been developed. This drill employs a piezoelectric-actuated percussive mechanism for generating impulsive stresses and breaking formations, and an electric motor to rotate the bit to break material and remove the cuttings. Initially, the drill was designed as percussive mechanism for sampling ice and was demonstrated in 2005 at Lake Vida, Antarctica, reaching about 2 meters depth. The lessons learned suggested there is a need to augment the percussive action with bit rotation in order to maximize the penetration rate. The first generation implementation of the rotary augmentation was focused on the demonstration of this capability. In 2012, during the 3-day field test, the drill reached a 3-meter deep in gypsum. A separate mechanism was used to break and remove the cores. The average drilling power consumption was in the range of 100-150 Watts, while the rate of penetration was approximately 2.4 meters per hour. Currently under development is the second-generation drill, called Auto-Gopher-2. The drill will be fully autonomous. In this paper, the capabilities that are being integrated into the Auto-Gopher-2 are described and discussed.

Auto-Gopher Drill↗
NASA NTRSDate not supplied

Feasibility and Performance Analysis of Magnetohydrodynamics Control for Aerocapture at Neptune

NASA’s most recent Decadal Survey posed a mission to one of the Ice Giants as the top priorityfor flagship missionsin the organization’s future. However, current technologieslimit the amount of scientific payload available for future Uranian and Neptunian missions due to the need for fuel for orbit insertion maneuvers. Thus, to maximize the scientific potential of futuremissions, atmospheric aerocapture has been heavily researched. While atmospheric aerocapture simulations have proven enabling for capturing around Neptune, its deep atmospheric pass requiresan aeroshell with thermal protection systems(TPS).Magnetohydrodynamically-controlled aerocapture serves as a potential solution to both fully-propulsive orbit insertion and atmospheric aerocapture. Through NASA Langley’s high-fidelity flight dynamics simulation, the Program to Optimize Simulated Trajectories II, both the atmospheric and magnetohydrodynamic aerocapture methods were simulated and compared for identical missions to Neptune. After applying a guidance algorithm for both methods, the results showed that magnetohydrodynamics has not only the control authority to successfully capture around Neptune, but also the unique advantage of a shallower atmospheric pass which decreases the maximum heat load and the required TPS mass.

Danny N Nguyen↗
DOE OSTI2022

A resilient network recovery framework against cascading failures with deep graph learning

Because of the increasing importance and dependencies of infrastructure networks and the potential for massive cascading failures in real-world network systems, maintenance optimization to effectively reduce system performance loss caused by diverse disruptions is of significant interest among researchers and practitioners. In this work, a new recovery framework was developed to rapidly identify important system components for maintenance to improve network resilience against cascading failures. Here this work provides distinct advantages to determine an optimal maintenance priority by combining real-time network structure importance with other maintenance prioritization based on customer preference. This approach adopts structural graph embedding and deep reinforcement learning to extract real-time network topology information (such as minimum vertex cover) to update the maintenance priority during the recovery process. Based on the case studies on synthetic networks and a US airport network, the proposed recovery framework with real-time network topology awareness shows better performance than other maintenance prioritization strategies regarding resilience enhancement. This work improves the understanding of how the changing network structure influences maintenance effects. It also provides insights of the practical usefulness of advanced deep learning on helping optimal maintenance prioritization to effectively reduce the intensity and extent of cascading failures.

42 ENGINEERING↗
NASA NTRS2007

Mars Radiation Risk Assessment and Shielding Design for Long-term Exposure to Ionizing Space Radiation

NASA is now focused on the agency's vision for space exploration encompassing a broad range of human and robotic missions including missions to Moon, Mars and beyond. As a result, there is a focus on long duration space missions. NASA is committed to the safety of the missions and the crew, and there is an overwhelming emphasis on the reliability issues for space missions and the habitat. The cost-effective design of the spacecraft demands a very stringent requirement on the optimization process. Exposure from the hazards of severe space radiation in deep space and/or long duration missions is a critical design constraint and a potential 'show stopper'. Thus, protection from the hazards of severe space radiation is of paramount importance to the agency's vision. It is envisioned to have long duration human presence on the Moon for deep space exploration. The exposures from ionizing radiation - galactic cosmic radiation and solar particle events - and optimized shield design for a swing-by and a long duration Mars mission have been investigated. It is found that the technology of today is inadequate for safe human missions to Mars, and revolutionary technologies need to be developed for long duration and/or deep space missions. The study will provide a guideline for radiation exposure and protection for long duration missions and career astronauts and their safety.

Tripathi, Ram K.↗
DOE OSTI2022

Experimental Evaluation of Thermal Storage Performance of a Dual-Purpose Underground Thermal Battery

A geothermal heat pump (GHP) system is an energy-efficient building heating and cooling technology with great potential for reducing energy consumption and decarbonization. However, applications of GHP are still limited due to the high cost, of which 30% is related to the cost of installing the conventional vertical bore ground heat exchangers, which are usually installed in boreholes 60 meters deep. A dual-purpose underground thermal battery (DPUTB) has been developed to offer a low-cost ground heat exchanger with a built-in thermal storage capacity. The DPUTB innovatively integrates a shallow-bore ground heat exchanger (the outer tank), which can be installed in a borehole less than 6 m deep, with thermal energy storage (TES) (the inner tank). DPUTB has the potential to reduce the cost of a ground source heat pump system while allowing shifting the electric demand of the building served by the GHP system from peak to off-peak hours of the electric grid by charging and discharging the thermal storage. A lab-scale (1:125 in volume) DPUTB prototype was built. Phase change material (PCM) was added to increase the thermal storage capacity and maintain the supply water temperature from the TES within the desired range for direct cooling operation during the discharge period. As PCMs are critical to the TES performance of the DPUTB, this study compared the influence of different PCMs (including salt hydrate and organic PCMs) on the discharge performance of the DPUTB. The thermal State of Charge (SoC) of the DPUTB was used to compare the performance resulting from using different PCMs. Test results indicate that the organic PCM (Methyl Laurate) outperforms salt-hydrate PCMs due to a lower melting temperature and a narrower melting temperature range during the phase change process. The results of this study provide a guide for PCM selection and the optimal design of DPUTB.

Wang, Lingshi↗
DOE OSTI2014

Spectral SP: A New Approach to Mapping Reservoir Flow and Permeability

Our objectives for the current project were to develop an innovative inversion and analysis procedure for magnetotelluric field data and time variable self-potentials that will enable us to map not only the subsurface resistivity structure of a geothermal prospect but to also delineate the permeability distribution within the field. Hence, the ultimate objective were to provide better targeting information for exploratory and development drilling of a geothermal prospect. Field data were collected and analyzed from the Kilauea Summit, Kilauea East Rift Zone, and the Humuula Saddle between Mauna Loa and Mauna Kea volcanoes. All of these areas were known or suspected to have geothermal activity of varying intensities. Our results provided evidence for significant long-term coordinated changes in spontaneous potential that could be associated with subsurface flows, significant interferences were encountered that arose from surface environmental changes (rainfall, temperature) that rendered it nearly impossible to unequivocally distinguish between deep fluid flow changes and environmental effects. Further, the analysis of the inferred spontaneous potential changes in the context of depth of the signals, and hence, permeability horizons, were unable to be completed in the time available.

15 GEOTHERMAL ENERGY↗