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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.

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At least 433 records · Page 24

32.9% Efficient Tandem Solar Cell with Strain-Balanced GaInAs/GaAsP Quantum Wells

We demonstrate single and dual junction solar cells with up to 80 strain-balanced GaInAs/GaAsP quantum wells (QWs), in order to extend the range of photon absorption. The net average stress in the quantum well layers is =12 MPa, despite coherent stresses in the individual layers that are 35-70 times greater. The GaAs-QW cell has a certified efficiency of (27.2 ± 0.2)% at one-sun; the GaInP/GaAs-QW tandem has a certified record one-sun efficiency of (32.9 ± 0.5)%. We will discuss the architecture of the devices, the physics behind the high performance, and pathways to further improvement.

III-V↗

In situ investigation of phosphonate retarder interaction in oil well cements at elevated temperature and pressure conditions

In this paper, the effect of a high-performance retarding additive in oil well cements was investigated under elevated temperature (165°C) and pressure (1000 psi) conditions via in situ synchrotron-based X-ray diffraction (XRD) and quasielastic neutron scattering (QENS) techniques. Under these temperature and pressure conditions, crystalline calcium silicate hydrates (C–S–H) are formed through the cement hydration process. From in situ XRD experiments, the retardation effect was observed by a change in the rate of the appearance of 11 Å tobermorites as well as a change in the rate of the α-C 2 SH generation and depletion. QENS analysis revealed that the retardation effect was related to the non-conversion of free water to chemical and constrained water components. A high presence of free water components was attributed to a decrease in 11Å tobermorites along with slower consumption of the quartz and portlandite phases. Furthermore, QENS results infer that the water molecules experienced confinement in the restricted pore spaces. The retarder inhibited this initial water confinement by slowing the bulk diffusion of free water in the confined region.

36 MATERIALS SCIENCE↗

Temperature uncertainty modelling with proxy structural data as geostatistical constraints for well siting: an example applied to Granite Springs Valley, NV, USA

Utilizing existing temperature and structural geology information around Granite Springs Valley, Nevada, we build 3D stochastic temperature models with the aims of evaluating the 3D uncertainty of temperature and choosing between candidate exploration well locations. The data used to support the modelling are measured temperatures and structural proxies from 3D geologic modelling (distance to fault, distance to fault intersections and terminations, Coulomb stress change and dilation tendency), the latter considered ‘secondary’ data. Two stochastic geostatistical techniques are explored for incorporating the structural proxies: cosimulation and local varying mean. With both the cosimulation and local varying mean methods, many equally-likely temperature models (i.e. realizations) are produced, from which temperature probability profiles are calculated at candidate well locations. To aid in choosing between the candidate locations, two quantities summarize the temperature probabilities: V prior and entropy. V prior quantifies the likelihood for economic temperatures at each candidate location, whereas entropy identifies where new information has the most potential to reduce uncertainty. In general, the cosimulation realizations have smoother spatial structure, and extrapolate high temperatures at candidate locations that are located along the direction of the longest spatial correlation, which are down dip from existing temperature logs. The smooth realizations result in tight temperature probability profiles that are easier to interpret, but they have unrealistic temperature reversals in some locations because of the dipping ellipsoid shape created and that the cosimulation technique does not enforce a conductive geothermal gradient as a baseline (i.e. linearly increasing temperature with depth). The local varying mean results produce realizations with more realistic geothermal gradients, with temperatures increasing downward since a depth-temperature relationship is included. However, because they have much noisier spatial nature compared to cosimulation, it is harder to interpret the temperature probability profiles. The different local varying mean results allow the geologist to determine which proxy (e.g. dilation v. distance to fault termination) should be used given the specific geothermal system. In general, V prior from local varying mean results identify locations that are close to high values for the structural proxies: areas with higher probabilities for higher temperatures. The entropy results identify where uncertainty is greatest and therefore new drilling information could be most useful. Though these techniques provide useful information, even when applied to areas of sparse data, our comparison of these two techniques demonstrates the need for new geothermal geostatistics techniques that combine the advantages of these two methods and that are tailored to the spatial uncertainty issues inherent in geothermal exploration.

15 GEOTHERMAL ENERGY↗

Oregon Direct Use Geothermal Well Data

This excel file provides direct use geothermal data for various wells located in Oregon. Data includes well name, location, heating application, temperature and flow of fluid, capacity, energy use, and load factor. The data is from the State of Oregon Department of Geology and Mineral Industries (linked below), where additional data downloads and metadata may be found.

15 GEOTHERMAL ENERGY↗

Utah FORGE: Phase 1a Tensor Strainmeter Data for the April, 2022 Stimulation of Well 16A(78)-32

Data from two Tensor Optical Fiber Strainmeters that were operational during Stages 1, 2, and 3 of the April, 2022 stimulation of well 16A(78)-32. Each csv file contains data from each stimulation stage (stage1, stage2, stage3) for both Phase 1a strainmeter installations (FS01, formerly FS-C, and FS02, formerly FS1-2) in human-readable comma-separated value text files. There are two header lines in each file describing the data contained in that column along with their units, respectively. Data have been decimated from 2 to 1 Hz to match the Pason data found in the linked GDR dataset below (16A78-32 Stimulation Pason Data). These files contain the time series spanning the same time interval as the Pason data as well as ambient data for 5 hours before the stimulation and 5 hours following shut in. The station locations were chosen based on their proximity to the borehole seismometers owned and operated by the University of Utah. See README.txt for more information.

15 GEOTHERMAL ENERGY↗

Utah FORGE 1-2409: Zonal Isolation Solution for Geothermal Wells - Workshop Presentation

This is a presentation on the Zonal Isolation Solution for Geothermal Wells project by PetroQuip Energy Services, presented by VP of operations Robert Coon. The project's objective was to design and develop a multi-stage system for zonally isolating fluids inside and outside of geothermal well casings. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 7, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

Utah FORGE 1-2551: Multi-Stage Fracturing System and Well Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores - Workshop Presentation and Report

Included here are a presentation recording, slides, and report on the Multi-Stage Fracturing System and Well Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores project by Colorado School of Mines, presented by Dr. William W. Fleckenstein. One goal of the project is to develop and demonstrate the use of low-cost, rapid multistage fracture stimulation technology with cemented casing frac sleeves that eliminates packers used in both conventional stimulation and injection flow control. The second goal is to develop and demonstrate the devices to effectively detect and control the flow of heat-carrier fluid solely from a long-reach injector through the network of induced and existing fractures and produced from an open-hole long-reach well to improve heat recovery. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 7, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

Utah FORGE: Well 16B(78)-32 DTS, RFS DSS Strain, and Absolute Strain Circulation Test Fiber Optic Data - August 2024

This dataset contains processed fiber optic measurements collected during the extended cross-well circulation test at the Utah FORGE site in August 2024. The data was acquired from the 16B(78)-32 well using distributed fiber optic sensing (DFOS) technology, including distributed temperature sensing (DTS) on multimode fiber and distributed strain sensing (DSS) measurements on single-mode fiber. The dataset includes Brillouin absolute strain, Rayleigh frequency shift (RFS) DSS strain change, RFS DSS strain change rate, and temperature (DTS) data, all stored in HDF5 format. Time coordinates are provided in UTC, and depth measurements are given in measured depth relative to the rotary kelly bushing (MD RKB) in feet. The spatial sampling on the RFS DSS strain data and the Brillouin Absolute Total Strain data is 20 cm and the spatial sampling on the DTS data is 1m. The dataset is accompanied by a report from Neubrex, which provides further documentation.

15 GEOTHERMAL ENERGY↗

Evaluating Compliance Inspection Data to Understand Emissions from Marginal Conventional Oil & Gas Wells in New York State

It is estimated that over half (~66%) of active oil and gas wells are marginally productive, producing less than 15 barrels of oil equivalent per day. This presentation showcases an evaluation of New York State compliance inspection reports and discusses the current capabilities of machine learning to identify high-risk MCWs that could be targeted during methane emission reduction efforts and future model deployments. Findings are valuable to the New York Department of Environmental Conservation and other state oil and gas regulatory agencies seeking to prioritize the spending of Methane Emission Reduction Program funds to plug marginal conventional wells with emissions.

compliance inspection data↗

Harnessing Machine Learning and Data Fusion for Accurate Undocumented Well Identification in Satellite Images

This study utilizes satellite data to detect undocumented oil and gas wells, which pose significant environmental concerns, including greenhouse gas emissions. Three key findings emerge from the study. Firstly, the problem of imbalanced data is addressed by recommending oversampling techniques like Rotation–GaussianBlur–Solarization data augmentation (RGS), the Synthetic Minority Over-Sampling Technique (SMOTE), or ADASYN (an extension of SMOTE) over undersampling techniques. The performance of borderline SMOTE is less effective than that of the rest of the oversampling techniques, as its performance relies heavily on the quality and distribution of data near the decision boundary. Secondly, incorporating pre-trained models trained on large-scale datasets enhances the models’ generalization ability, with models trained on one county’s dataset demonstrating high overall accuracy, recall, and F1 scores that can be extended to other areas. This transferability of models allows for wider application. Lastly, including persistent homology (PH) as an additional input improves performance for in-distribution testing but may affect the model’s generalization for out-of-distribution testing. A careful consideration of PH’s impact on overall performance and generalizability is recommended. Overall, this study provides a robust approach to identifying undocumented oil and gas wells, contributing to the acceleration of a net-zero economy and supporting environmental sustainability efforts.

SMOTE↗

Quantum Well Infrared Photodetectors for low background application

QWIPs operate by photoexcitation of electrons between ground and first excited state subbands of multi-quantum wells (MQWs) which are artificially fabricated by placing thin layers of two dfferent, high-bandgap semiconductor materials alternately. The bandgap discontinuity of two materials creates quantized subbands in the potential wells associated with conduction bands.

infrared focal plane arrays quantum wells↗

ACES Preliminary Results Supporting Selection of SARP Well-Clear Definitions

The UAS in the NAS project is studying the minimum operational performance standards for unmanned aerial systems (UAS's) detect-and-avoid (DAA) system in order to operate in the National Airspace System. The DoD's Science and research Panel Well-Clear Workshop is investigating the time and spatial boundary at which an UAS violates well-clear. NASA is supporting this effort through use of its Airspace Concept Evaluation System (ACES) simulation platform. This presentation reviews how the simulation was used to support this work, lessons learned during the experiment, and introduces preliminary results.

well-clear↗

Market Survey 2020: Commercial Clinical Decision Support Systems and Wellness Tools

For long-duration, deep space exploration missions, current methods for managing and supporting crew health and medical conditions will be unsuitable. Communication and data transmission lags will necessitate the use of a sophisticated clinical decision support system (CDSS) that will tailor diagnosis and treatment guidance that is context-sensitive for anticipated astronaut health, wellness, and medical conditions. A variety of clinical decision support (CDS) and wellness tools (WT) are currently available in the commercial market and a broad-brush survey of this market can provide an initial impression of the current state of the art which, in turn, can inform the roadmap of NASA deep space CDSS development and associated requirements. Such a survey was undertaken during the first six months of 2020 using directed convenience sampling to obtain information provided by vendors on their websites; both commercially available CDS and WT (such as those used to track and monitor nutrition, exercise, and sleep) were included. Areas assessed were item type (e.g., software/application, device); primary purpose of the item (e.g., diagnostic support, nutrition tracking); additional purposes (if any); reported features, capabilities, and functionality; setting of use (e.g., inpatient, outpatient); intended user (e.g., clinician, patient); location and sources of data/information used or produced by the item; integration with patient electronic health record (EHR); compliance with interoperability ontologies and standards (e.g., Health Level 7 [HL7], Systematized Nomenclature of Medicine – Clinical Terminology [SNOMED-CT]); and whether the item is knowledge-based (derived from research findings) or non-knowledge-based (derived through artificial intelligence, machine learning, advanced probability and statistics), among others. Ninety-seven (97) vendor websites describing 196 CDS and 73 WT (269 total) were reviewed and coded. The primary purpose of the majority of CDS reviewed is diagnosis or diagnosis/treatment/drug decision support—targeted for clinician use— and the primary purpose of the majority of WT reviewed is the monitoring of different health metrics, most often through the use of a biosensor device (e.g., blood pressure)—targeted for patient use. Very few CDS or WT appear to comply with major international interoperability standards or can be integrated with a patient’s EHR data. None consider contextual factors, such as conditions of the physical environment (e.g., CO2 levels). The majority of CDS and WT reviewed are non-knowledge, cloud- or web-based applications or software. Forty-three (43) major findings were identified and the implications those findings have for NASA will be discussed. Example major findings include: CDS-WT capabilities range from diagnosis to treatment applications, CDS-WT may be wearable or non-wearable and are technologically advanced and only a few CDS-WT tools referenced compliance to ensure interoperability, among other findings. Recommendations will also be offered that will help to address ExMC Gap, Medical-701: Enhance medical capabilities within an exploration medical system.

market survey↗

High Performance InGaAs/GaAs Quantum Well Infrared Photodetectors

By increasing the quantum well barrier width, incorporating spacer layers between the contacts and the multi quantum well region, and optimizing the materials growth parameters, we have dramatically reduced the dark current by many orders of magnitude and thereby significantly increased the detectivity.

spacer↗

32.9% Efficient Tandem Solar Cell with Strain-Balanced GaInAs/GaAsP Quantum Wells: Preprint

We demonstrate single and dual junction solar cells with up to 80 strain-balanced GaInAs/GaAsP quantum wells (QWs), in order to extend the range of photon absorption. The net average stress in the quantum well layers is =12 MPa, despite coherent stresses in the individual layers that are 35-70 times greater. The GaAs-QW cell has a certified efficiency of (27.2 ± 0.2)% at one-sun; the GaInP/GaAs-QW tandem has a certified record one-sun efficiency of (32.9 ± 0.5)%. We will discuss the architecture of the devices, the physics behind the high performance, and pathways to further improvement.

GaAsP↗

Utah FORGE: Updated Seismic Event Catalogue from the April, 2022 Stimulation of Well 16A(78)-32

These are revised catalogs, related to the April, 2022 well 16A(78)-32 stimulation (phases 1,2, & 3), provided by Geo Energie Suisse (GES) that include additional events at the start of Stage 1 and some tidying up of some locations. These catalogs also include events for additional events that were auto-located to provide a larger dataset for statistical analyses, like b-value calculations. The actual auto-locations have been removed to prevent spurious location plots being created. Times are recorded in UTC (Coordinate Universal Time), and the coordinate reference system is UTM Zone 12N, NAD83.

15 GEOTHERMAL ENERGY↗