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Brown, Stephen

Publications and source records attributed to Brown, Stephen.

7 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis

Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. As a result, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Preliminary report on applications of machine learning techniques to the Nevada play fairway analysis

We are applying machine learning (ML) techniques, including training set augmentation and artificial neural networks, to mitigate key challenges in the Nevada play fairway project. The study area includes ~85 active geothermal systems as potential training sites and >12 geologic, geophysical, and geochemical features. The main goal is to develop an algorithmic approach to identify new geothermal systems in the Great Basin region. Major objectives include: 1) integrate ML techniques into the geothermal community; 2) develop open community datasets, whereby all play fairway and ML datasets and algorithms are publicly released and available for modification by various user groups; 3) identify data acquisition targets with high value for future work; 4) identify new signatures to detect blind geothermal systems; and 5) foster new capabilities for characterizing subsurface temperature and permeability. Initially, ML techniques are being applied to the same play fairway datasets and workflow. ML will then be applied to both enhanced and additional datasets, with modification of the PFA workflow to incorporate the new datasets. Finally, ML will be applied to define new workflows using the enhanced and additional datasets. An algorithmic approach that empirically learns to estimate weights of influence for diverse parameters can potentially scale and perform better than the play fairway analysis. Initial work on this project has involved 1) evaluating potential positive and negative training sites, 2) transformation of datasets into formats suitable for ML, and 3) initial development and testing of ML techniques.

58 GEOSCIENCES↗
DOE OSTI2022

Python Codebase and Jupyter Notebooks - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

Git archive containing Python modules and resources used to generate machine-learning models used in the "Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada" project. This software is licensed as free to use, modify, and distribute with attribution. Full license details are included within the archive. See "documentation.zip" for setup instructions and file trees annotated with module descriptions.

Brown, Stephen↗
NASA NTRS2017

Hydrogen Balmer Line Broadening in Solar and Stellar Flares

The broadening of the hydrogen lines during flares is thought to result from increased charge (electron, proton) density in the flare chromosphere. However, disagreements between theory and modeling prescriptions have precluded an accurate diagnostic of the degree of ionization and compression resulting from flare heating in the chromosphere. To resolve this issue, we have incorporated the unified theory of electric pressure broadening of the hydrogen lines into the non-LTE radiative-transfer code RH. This broadening prescription produces a much more realistic spectrum of the quiescent, A0 star Vega compared to the analytic approximations used as a damping parameter in the Voigt profiles. We test recent radiative-hydrodynamic (RHD) simulations of the atmospheric response to high nonthermal electron beam fluxes with the new broadening prescription and find that the Balmer lines are overbroadened at the densest times in the simulations. Adding many simultaneously heated and cooling model loops as a 'multithread' model improves the agreement with the observations. We revisit the three component phenomenological flare model of the YZ CMi Megaflare using recent and new RHD models. The evolution of the broadening, line flux ratios, and continuum flux ratios are well-reproduced by a multithread model with high-flux nonthermal electron beam heating, an extended decay phase model, and a 'hot spot' atmosphere heated by an ultra relativistic electron beam with reasonable filling factors: approximately 0.1%, 1%, and 0.1% of the visible stellar hemisphere, respectively. The new modeling motivates future work to understand the origin of the extended gradual phase emission.

Kowalski, Adam F.↗
NASA NTRS2010

Analysis of Possible Explosions at Kennedy Space Center Due to Spontaneous Ignition of Hypergolic Propellants

NASA's Constellation Program plan currently calls for the replacement of the Space Shuttle with the ARES I & V spacecraft and booster vehicles to send astronauts to the moon and beyond. Part of the ARES spacecraft is the Orion Crew Exploration Vehicle (CEV), which includes the Crew Module (CM) and Service Module (SM). The Orion CM's main propulsion system and supplies are provided by the SM. The SM is to be processed off line and moved to the Vehicle Assembly Building (V AB) for stacking to the first stage booster motors prior to ARES move to the launch pad. The new Constellation Program philosophy to process in this manner has created a major task for the KSC infrastructure in that conventional QD calculations are no longer viable because of the location of surrounding facilities near the VAB and the Multi Purpose Processing Facility (MPPF), where the SM will be serviced with nearly 18,000 pounds of hypergolic propellants. The Multi-Payload Processing Facility (MPPF) complex, constructed by NASA in 1994, is located just off E Avenue south of the Operations and Checkout (O&C) building in the Kennedy Space Center industrial area. The MPPF includes a high bay and a low bay. The MPPF high bay is 40.2 m (132 ft) long x 18.9 m (60 ft) wide with a ceiling height of 18.9 m (62 ft). The low bay is a 10.4 m (34 ft) long x 10.4 m (34 ft) wide processing area and has a ceiling height of6.1 m (20 ft). The MPPF is currently used to process non-hazardous payloads. Engineering Analysis Inc. (EAI), under contract with ASRC Aerospace, Inc. in conjunction with the Explosive Safety Office, NASA, Kennedy Space Center (KSC), has carried out an analysis of the effects of explosions at KSC in or near various facilities produced by the spontaneous ignition ofhypergolic fuel stored in the CEV SM. The facilities considered included (1) Vehicle Assembly Building (VAB) (2) Multi-Payload Processing Facility (MPPF) (3) Canister Rotation Facility (CRF) Subsequent discussion deals with the MPPF analysis. Figure 1 provides a view of the MPPF from the northwest. An interior view ofthe facility is shown in Figure 2. The study was concerned with both blast hazards and hazardous fragments which exceed existing safety standards, as described in Section 2.0. The analysis included both blast and fragmentation effects and was divided into three parts as follows: (1) blast (2) primary fragmentation (3) secondary fragmentation Blast effects are summarized in Section 3.0, primary fragmentation in Section 4.0, and secondary fragmentation (internal and external) in Section 5.0. Conclusions are provided in Section 6.0, while references cited are included in Section 7.0. A more detailed description of the entire study is available in a separate document.

Brown, Stephen↗