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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Machine learning to identify geologic factors associated with production in geothermal fields: A casestudy using 3D geologic data, Brady geothermal field, Nevada

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in the Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fluid flow pathways are relatively rare in the subsurface but are critical components of hydrothermal systems like Brady and many other types of fluid flow systems in fractured rock. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of fourteen 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate the macro-scale faults and a local step-over in the fault system preferentially occur along with production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate 1) the specific geologic controls on the Brady hydrothermal system and 2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Ground Motion Models (GMMs) Improvements Using Earthquake Simulations on High Performance Computers

A computationally efficient simulation platform was developed that can provide representative synthetic ground motions from crustal earthquakes in the Stable Continental Regions of Central and Eastern US (CEUS), using 3D modeling and high-performance computing. The main objective was to use synthetic ground motion to provide constrains to refinements of exiting ergodic Ground Motion Models (GMMs), for large magnitude earthquakes and near-fault distances, for which these models are less reliable. Physics-based broadband (0-5Hz) ground motion simulations were used to estimate the near-fault ground motion amplitudes and within event and between-event variabilities associated with fault rupture characteristics. As part of a strategy for selecting a reginal velocity model and validation of developed rupture modeling technique, ground motions from the moment magnitude Mw5.0 November 7, 2016, Cushing Oklahoma, and Mw5.8 September 3, 2016, Pawnee Oklahoma earthquakes were simulated. In our simulations we used a 3D regional velocity model that was based on Saikia’s 1D velocity model. Saikia’s model demonstrated better performance in modelling high frequency regional wave propagation for CEUS region. The proposed 3D model includes lateral variations added to the 1D background model using the stochastic scheme of Pitarka and Mellors. Comparisons of the simulations with recordings of both earthquakes demonstrated the reliability of our deterministic simulation approach while emphasizing the importance of including small-scale variability in the regional velocity model needed to reproduce the observed high-frequency wave scattering effects. As part of validation analysis, comparisons with different GMMs for a Mw6.5 earthquake in the CESUS region resulted in a very good match between the simulated and empirical ground motion models. Initial investigations of within-event and between-event ground motion variabilities for Mw6.5 scenario earthquakes on a strike-slip fault, suggest that they are strongly related to spatial slip and slip rate variations, average rupture velocity, rupture area and rupture initiation location. For certain scenarios we found that the ground motion variability observed at near-fault distances (< 5 km) also persists at longer distances. Regardless of the rupture scenario, the simulated ground motion tends to fully saturate at short distances and for all periods. The near-fault saturation has to do with the attenuation of waves propagating along the fault and local rupture radiation pattern that also contribute to stronger ground motion variation at such distances. Analysis of effects of rupture initiation location suggest that the peak ground motion (PGV) and spectral acceleration (SA) can be quite variable due to rupture directivity effects. Such effects are stronger at periods longer than 1s. The effect of the 1D velocity models and surface topography on simulated ground motion were investigated by comparing three component synthetic seismograms computed at selected sites. Effect of surface topography was considered using the ratio between spectral accelerations simulated for two 1D models with flat surface topography and realistic model with surface topography. Overall, the topography slightly amplifies (by ~30%) the ground motion amplitude in the frequency range 1-3Hz. The effect of topography is more visible in the surface and coda waves portion of the seismograms.

58 GEOSCIENCES↗
NASA NTRS1973

New aspects on the tectonic of the Alps and the Apennines revealed by ERTS-1 data

An analysis of the tectonic situation in the Alps and Apennine Mountains based on ERTS-1 imagery is presented. It is stated that the ERTS-1 imagery reveals connections between shearing systems of more than regional importance which could not be determined previously. The tracing of locally known fault distances by ERTS-1 imagery is discussed.

Bodechtel, J.↗
NASA NTRS2001

Impact Cratering Calculations

This research is computational /theoretical and complements the Caltech experimental program. We have developed an understanding of the basic physical processes and produced computational models and implemented these into Eulerian and Lagrangian finite element codes. The key issues we have addressed include the conditions required for: faulting (strain localization), elastic moduli weakening, dynamic weakening (layering elastic instabilities and fluidization), bulking (creation of porosity at zero pressure) and compaction of pores, frictional melting (creation of pseudotachylytes), partial and selective devolatilization of materials (e.g. CaCO3, water/ice mixtures), and debris flows.

Ahrens, Thomas J.↗
DOE OSTI2017

Robust Online Monitoring for Calibration Assessment of Transmitters and Instrumentation

Robust online monitoring (OLM) technologies are expected to enable the extension or elimination of periodic sensor calibration intervals in operating and new reactors. These advances in OLM technologies will improve the safety and reliability of current and planned nuclear power systems through improved accuracy and increased reliability of sensors used to monitor key parameters. In this article, we discuss an overview of research being performed within the Nuclear Energy Enabling Technologies (NEET)/Advanced Sensors and Instrumentation (ASI) program, for the development of OLM algorithms to use sensor outputs and, in combination with other available information, 1) determine whether one or more sensors are out of calibration or failing and 2) replace a failing sensor with reliable, accurate sensor outputs. Algorithm development is focused on the following OLM functions: • Signal validation • Virtual sensing • Sensor response-time assessment These algorithms incorporate, at their base, a Gaussian Process-based uncertainty quantification (UQ) method. Various plant models (using kernel regression, GP, or hierarchical models) may be used to predict sensor responses under various plant conditions. These predicted responses can then be applied in fault detection (sensor output and response time) and in computing the correct value (virtual sensing) of a failing physical sensor. The methods being evaluated in this work can compute confidence levels along with the predicted sensor responses, and as a result, may have the potential for compensating for sensor drift in real-time (online recalibration). Evaluation was conducted using data from multiple sources (laboratory flow loops and plant data). Ongoing research in this project is focused on further evaluation of the algorithms, optimization for accuracy and computational efficiency, and integration into a suite of tools for robust OLM that are applicable to monitoring sensor calibration state in nuclear power plants.

fault detection↗
DOE OSTI2017

ROBUST ONLINE MONITORING FOR CALIBRATION ASSESSMENT OF TRANSMITTERS AND INSTRUMENTATION

Robust online monitoring (OLM) technologies are expected to enable the extension or elimination of periodic sensor calibration intervals in operating and new reactors. Specifically, the next generation of OLM technology is expected to include newly developed advanced algorithms that improve monitoring of sensor/system performance and enable the use of plant data to derive information that currently cannot be measured. These advances in OLM technologies will improve the safety and reliability of current and planned nuclear power systems through improved accuracy and increased reliability of sensors used to monitor key parameters. In this paper, we discuss an overview of research being performed within the Nuclear Energy Enabling Technologies (NEET)/Advanced Sensors and Instrumentation (ASI) program, for the development of OLM algorithms to use sensor outputs and, in combination with other available information, 1) determine whether one or more sensors are out of calibration or failing and 2) replace a failing sensor with reliable, accurate sensor outputs. Algorithm development is focused on the following OLM functions: • Signal validation – fault detection and selection of acceptance criteria • Virtual sensing – signal value prediction and acceptance criteria • Response-time assessment – fault detection and acceptance criteria selection A GP-based uncertainty quantification (UQ) method previously developed for UQ in OLM, was adapted for use in sensor-fault detection and virtual sensing. For signal validation, the various components to the OLM residual (which is computed using an AAKR model) were explicitly defined and modeled using a GP. Evaluation was conducted using flow loop data from multiple sources. Results using experimental data from laboratory-scale flow loops indicate that the approach, while capable of detecting sensor drift, may be incapable of discriminating between sensor drift and model inadequacy. This may be due to a simplification applied in the initial modeling, where the sensor degradation is assumed to be stationary. In the case of virtual sensors, the GP model was used in a predictive mode to estimate the correct sensor reading for sensors that may have failed. Results have indicated the viability of using this approach for virtual sensing. However, the GP model has proven to be computationally expensive, and so alternative algorithms for virtual sensing are being evaluated. Finally, automated approaches to performing noise analysis for extracting sensor response time were developed. Evaluation of this technique using laboratory-scale data indicates that it compares well with manual techniques previously used for noise analysis. Moreover, the automated and manual approaches for noise analysis also compare well with the current “gold standard”, hydraulic ramp testing, for response time monitoring. Ongoing research in this project is focused on further evaluation of the algorithms, optimization for accuracy and computational efficiency, and integration into a suite of tools for robust OLM that are applicable to monitoring sensor calibration state in nuclear power plants.

calibration interval extension↗
DOE OSTI2024

Convolutional Neural Network-Based Protection-Zone Classification of Faults in Distribution Feeders with Photovoltaics.

Fault detection and isolation is critical for reliable operation of distribution systems. The ride-through requirements for the distributed energy resources (DER), mandated by the IEEE 1547-2018 standard, makes it challenging to use undervoltage (UV) conditions for fault detection. In addition, with low fault current contribution from these inverter-based DERs, the time-overcurrent relays are also less effective. Thus motivated, this paper presents a learning-based approach for fault detection and localization. A convolutional neural network (CNN)-based model is proposed which uses local voltage and current waveforms from DER locations and feeder substations, for training a zonal classifier. The classifier can be adopted into any relay-like device for discriminating between faults originating from different protection zones. The performance of the proposed approach was tested on publicly available test feeders with distributed photovoltaics (PVs).

Fault localization, convolutional neural networks,↗
DOE OSTI2014

Blackcomb: Hardware-Software Co-design for Non-Volatile Memory in Exascale Systems

Summary of technical results of Blackcomb Memory Devices We explored various different memory technologies (STTRAM, PCRAM, FeRAM, and ReRAM). The progress can be classified into three categories, below. Modeling and Tool Releases Various modeling tools have been developed over the last decade to help in the design of SRAM or DRAM-based memory hierarchies. To explore new design opportunities that NVM technologies can bring to the designers, we have developed similar high-level models for NVM, including PCRAMsim [Dong 2009], NVSim [Dong 2012], and NVMain [Poremba 2012]. NVSim is a circuit-level model for NVM performance, energy, and area estimation, which supports various NVM technologies, including STT-RAM, PCRAM, ReRAM, and legacy NAND Flash. NVSim is successfully validated against industrial NVM prototypes, and it is expected to help boost architecture-level NVM-related studies. On the other side, NVMain is a cycle accurate main memory simulator designed to simulate emerging nonvolatile memories at the architectural level. We have released these models as open source tools and provided contiguous support to them. We also proposed PS3-RAM, which is a fast, portable and scalable statistical STT-RAM reliability analysis model [Wen 2012]. Design Space Exploration and Optimization With the support of these models, we explore different device/circuit optimization techniques. For example, in [Niu 2012a] we studied the power reduction technique for the application of ECC scheme in ReRAM designs and proposed to use ECC code to relax the BER (Bit Error Rate) requirement of a single memory to improve the write energy consumption and latency for both 1T1R and cross-point ReRAM designs. In [Xu 2011], we proposed a methodology to design STT-RAM for different optimization goals such as read performance, write performance and write energy by leveraging the trade-off between write current and write time of MTJ. We also studied the tradeoffs in building a reliable crosspoint ReRAM array [Niu 2012b]. We have conducted an in depth analysis of the circuit and system level design implications of multi-layer cross-point Resistive RAM (MLCReRAM) from performance, power and reliability perspectives [Xu 2013]. The objective of this study is to understand the design trade-offs of this technology with respect to the MLC Phase Change Memory (MLCPCM).Our MLC ReRAM design at the circuit and system levels indicates that different resistance allocation schemes, programming strategies, peripheral designs, and material selections profoundly affect the area, latency, power, and reliability of MLC ReRAM. Based on this analysis, we conduct two case studies: first we compare MLC ReRAM design against MLC phase-change memory (PCM) and multi-layer cross-point ReRAM design, and point out why multi-level ReRAM is appealing; second we further explore the design space for MLC ReRAM. Architecture and Application We explored hybrid checkpointing using phase-change memory for future exascale systems [Dong 2011] and showed that the use of nonvolatile memory for local checkpointing significantly increases the number of faults covered by local checkpoints and reduces the probability of a global failure in the middle of a global checkpoint to less than 1%. We also proposed a technique called i2WAP to mitigate the write variations in NVM-based last-level cache for the improvement of the NVM lifetime [Wang 2013]. Our wear leveling technique attempts to work around the limitations of write endurance by arranging data access so that write operations can be distributed evenly across all the storage cells. During our intensive research on fault-tolerant NVM design, we found that ECC cannot effectively tolerate hard errors from limited write endurance and process imperfection. Therefore, we devised a novel Point and Discard (PAD) architecture in in [ 2012] as a hard-error-tolerant architecture for ReRAM-based Last Level Caches. PAD improves the lifetime of ReRAM caches by 1.6X-440X under different process variations without performance overhead in the system's early life. We have investigated the applicability of NVM for persistent memory design [Zhao 2013]. New byte addressable NVM enables fast persistent memory that allows in-memory persistent data objects to be updated with much higher throughput. Despite the significant improvement, the performance of these designs is only 50% of the native system with no persistence support, due to the logging or copy-on-write mechanisms used to update the persistent memory. A challenge in this approach is therefore how to efficiently enable atomic, consistent, and durable updates to ensure data persistence that survives application and/or system failures. We have designed a persistent memory system, called Klin, that can provide performance as close as that of the native system. The Klin design adopts a non-volatile cache and a non-volatile main memory for constructing a multi-versioned durable memory system, enabling atomic updates without logging or copy-on-write. Our evaluation shows that the proposed Kiln mechanism can achieve up to 2X of performance improvement to NVRAM-based persistent memory employing write-ahead logging. In addition, our design has numerous practical advantages: a simple and intuitive abstract interface, microarchitecture-level optimizations, fast recovery from failures, and no redundant writes to slow non-volatile storage media. The work was published in MICRO 2013 and received Best Paper Honorable Mentioned Award.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Rotation of stress and blocks in the Lake Mead, Nevada, Fault System

The combined effects of stress field rotation and material rotation were found in the Lake Mead, Nevada Fault System (LMFS). Fault inversion results imply an apparent 60 deg clockwise (CW) rotation of the stress field since mid-Miocene time. In contrast, structural data from the Great Basin suggest only a 30 deg CW stress field rotation. By incorporating paleomagnetic declination anomalies, it is inferred that slip on faults caused a local 30 deg counterclockwise rotation of blocks and faults in the Lake Mead area, so that the inferred 60 deg CW rotation of the stress field in the LMFS is actually only 30 deg.

Ron, Hagai↗
NASA NTRS1990

Stress field rotation or block rotation: An example from the Lake Mead fault system

The Coulomb criterion, as applied by Anderson (1951), has been widely used as the basis for inferring paleostresses from in situ fault slip data, assuming that faults are optimally oriented relative to the tectonic stress direction. Consequently if stress direction is fixed during deformation so must be the faults. Freund (1974) has shown that faults, when arranged in sets, must generally rotate as they slip. Nur et al., (1986) showed how sufficiently large rotations require the development of new sets of faults which are more favorably oriented to the principal direction of stress. This leads to the appearance of multiple fault sets in which older faults are offset by younger ones, both having the same sense of slip. Consequently correct paleostress analysis must include the possible effect of fault and material rotation, in addition to stress field rotation. The combined effects of stress field rotation and material rotation were investigated in the Lake Meade Fault System (LMFS) especially in the Hoover Dam area. Fault inversion results imply an apparent 60 degrees clockwise (CW) rotation of the stress field since mid-Miocene time. In contrast structural data from the rest of the Great Basin suggest only a 30 degrees CW stress field rotation. By incorporating paleomagnetic and seismic evidence, the 30 degrees discrepancy can be neatly resolved. Based on paleomagnetic declination anomalies, it is inferred that slip on NW trending right lateral faults caused a local 30 degrees counter-clockwise (CCW) rotation of blocks and faults in the Lake Mead area. Consequently the inferred 60 degrees CW rotation of the stress field in the LMFS consists of an actual 30 degrees CW rotation of the stress field (as for the entire Great Basin) plus a local 30 degrees CCW material rotation of the LMFS fault blocks.

Ron, Hagai↗
NASA NTRS1985

Low-angle normal faults-low differential stress at mid crustal levels

A simple model for frictional slip on pre-existing faults that considers the local stress state near the fault and the effect of non-hydrostatic fluid pressures predicts that low-angle normal faulting is restricted to areas of the crust characterized by low differential stress and nearly lithostatic fluid pressures. The model considers frictional slip on a cohesionless low-angle normal fault governed by the failure criterion tau = mu sub f (sigma (*) sub n) =mu sub f (sigma sub n - P sub f) where tau and sigma sub n are the shear and normal stresses across the fault plane, mu sub f is the static coefficient of friction, and P sub f is the pore fluid pressure. As a first approximation, the model considers a vertical greatest principal compressive stress, sigma sub 1. It is apparent that if slip on low-angle normal faults is governed by the avove frictional failure criterion, slip on the low-angle normal fault occurs only if the least effective principal stress, sigma (*) sub 3 = sigma sub 3 - P sub f, is tensile, whenever tan superscrip -1(mu sub f d, where d is the dip of the fault. If detachment faulting occurs at any significant depth in the crust, P sub f sigma sub 3 is required. In light of this conclusion I allow P sub f to vary as necessary to allow slip on the low-angle normal fault.

Power, W. L.↗
NASA NTRS2004

Geologic Evolution of the Martian Dichotomy in the Ismenius Area of Mars and Implications for Plains Magnetization

The origin of the Martian dichotomy, which divides highlands from lowlands, is unknown. We examine a section of the dichotomy ( 50 - 90E) defined by steep scarps and normal faults. Stratigraphy and age relationships preclude the formation of the 2.5 km high boundary via erosion. The abrupt disappearance of topographic knobs similar to 300 - 500 km to the northeast is interpreted as a buried fault. Alignment of the buried fault with grabens, stratigraphy, and age determinations using crater counts indicate that the lowland bench is down faulted highlands crust. The estimated local strain (3.5%) and fault pattern are broadly consistent with gravitational relaxation of a plateau boundary. Magnetic and gravity anomalies occur on either side of the buried fault. Admittance analysis indicates isostatic compensation. Although nonunique, a model with a 10 km thick intracrustal block under the lowland bench, a 20 km thick block under the plains, and an excess density of 200 kg/m(3) provides a good fit to the isostatic anomaly. A good fit to a profile of the magnetic field perpendicular to the dichotomy is produced using uniformly polarized intracrustal blocks 10 - 20 km thick, an intensity of 6 Am/m, a field inclination of -30 degrees, and gaps aligned with the isostatic anomalies. One interpretation is that high-density intrusions demagnetized the crust after dynamo cessation and that low-lying magnetized areas could be down faulted highlands crust. Another model (inclination of 30 degrees) has magnetized crust beneath the isostatic anomalies, separated by gaps. The gaps could result from hydrothermal alteration of the crust along fault zones.

faulting↗
DOE OSTI2024

Modular DC circuit breaker with integrated energy storage for future DC networks

A T-breaker is an all-in-one solution for dc microgrid fault protection, power flow control, and power quality improvement. A T-breaker features a modular multilevel “T” structure with integrated energy storage devices. The two horizontal arms of the T-breaker realize fault current breaking, load voltage compensation, and power flow control; and the vertical arm of the T-breaker realizes shunt compensation. The configuration provides excellent voltage scalability and relaxes the requirements on the switching signal synchronization during fault transients. The local energy storage in sub-modules eases the fault energy dissipation requirement placed on the traditionally-adopted surge arrestors. The modular multilevel structure also offers immense control flexibility for all types of targeted functions of the provided T-breaker.

Wang, Jin↗
NASA NTRS1998

The Surface Displacement Field of the November 8, 1997, Mw7.6 Manyi (Tibet) Earthquake Observed with ERS InSAR Data

ERS2 radar data acquired before and after the Mw7.6, Manyi (Tibet) earthquake of November 8, 1997, provide geodetic information about the surface displacement produced by the earthquake in two ways. (1) The sub-pixel geometric adjustment of the before and after images provides a two dimensional offset field with a resolution of approx, 1m in both the range (radar line of sight) and azimuth (satellite track) directions. Comparison of offsets in azimuth and range indicates that the displacement along the fault is essentially strike-slip and in a left-lateral sense. The offset map reveals a relatively smooth and straight, N78E surface rupture that exceeds 150 km in length, consistent with the EW plane of the Harvard CMT solution. The rupture follows the trace of a quaternary fault visible on satellite imagery (Tapponnier and Molnar, 1978; Wan Der Woerd, pers. comm.). (2) Interferometric processing of the SAR data provides a range displacement map with a precision of a few millimeters. The slip distribution along the rupture reconstructed from the range change map is a bell-shaped curve in the 100-km long central section of the fault with smaller, local maxima near both ends. The curve shows that the fault slip exceeds 2.2 m in range, or 6.2 in strike-slip, along a 30-km long section of the fault and remains above 1 m in range, approx. 3 m strike-slip, along most of its length. Preliminary forward modeling of the central section of the rupture, assuming a uniform slip distribution with depth, indicates that the slip occur-red essentially between 0 and the depth of 10 km, consistent with a relatively shallow event (Velasco et al., 1998).

Peltzer, G.↗
DOE OSTI2014

Recombination dynamics of a localized exciton bound at basal stacking faults within the m-plane ZnO film

We investigated the carrier dynamics near basal stacking faults (BSFs) in m-plane ZnO epitaxial film. The behaviors of the type-II quantum wells related to the BSFs are verified through time-resolved and time-integrated photoluminescence. The decay time of the emission of BSFs is observed to have a higher power law value and longer decay time than the emission of the donor-bound excitons. The spectral-dependent decay times reveal a phenomenon of carriers migrating among band tail states, which are related to the spatial distribution of the type-II quantum wells formed by the BSFs. A high density of excited carriers leads to a band bending effect, which in turn causes a blue-shift of the emission peak of BSFs with a broadened distribution of band tail states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1986

North American-Pacific relative plate motion in southern California from interferometry

VLBI measurements of baselines crossing the San Andreas fault zone in southern California have provided observational constraints on rates of elastic tectonic strain accumulation. The single site located near this fault (the JPL site) moves in a direction concordant with the Pacific plate motion vector but at approximately half the net rate relative to North America. This motion agrees approximately in amount with geologically determined displacement rates on the San Andreas fault alone but not with the local strike of the fault. When considered together with complementary geodetic data, these results suggest a complex relation between the short-term accumulation of elastic strain and its permanent accommodation on existing faults.

Lyzenga, G. A.↗
DOE OSTI2021

Machine learning to identify geologic factors associated with production in geothermal fields: a case-study using 3D geologic data, Brady geothermal field, Nevada

Abstract In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fluid-flow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fluid-flow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k -means clustering (NMF k ), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes.

58 GEOSCIENCES↗