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This dataset consists of an Excel spreadsheet detailing the fracture picks from a reinterpretation of the formation micro-imaging (FMI) log from Utah FORGE well 16A(78)-32. The provided information details fracture location, geometry, and type. Also included here is a link to the original raw and processed FMI logs, as well as other data from the 2021 well logging.
Recent innovations are producing a multitude of advanced commercial satellite communications (COMSATCOM) systems that could deliver massive amounts of SATCOM capacity at a fraction of current cost while also offering reliability and availability that is critical to achieving mission success for orbiting assets. Recognizing the alignment of commercial capabilities with the National Aeronautics and Space Administration's (NASA) diverse mission requirements, the agency is proactively engaging industry to formulate strategies leading towards a NASA communications architecture that includes advanced commercial capabilities. To fully leverage the expanded space resources, NASA must also address the integration of commercial waveforms into its space terminals. In pursuit of similar goals, the United States Department of Defense (DoD) is leading the standardization of the flexible modem interface (FMI) to address service integration for their tactical terminals in pursuit of a DoD Wideband SATCOM Enterprise.This paper describes how NASA is adapting this FMI standard to work with the Space Telecommunications Radio System (STRS) software-defined radio (SDR) framework to address the challenging size, weight, and power resource requirements for terminals in space. A full adaptation would include waveform compatibility with modular baseband processing, frequency compatibility with a wideband front end, and radiated beam control with an electronically steerable antenna to enable multi-provider commercial service capability in a feasible package for space terminals. Security is also a key aspect to be addressed for this integration since data will flow through commercial networks, commercial service providers have their own security mechanisms, and space terminals must be able to securely load proprietary software and firmware needed to access the commercial networks on demand. Success of this effort means commercial partners will be able to allow network-compliant implementations to be hosted on STRS-compliant SDRs in space for reliable and capable network access.
PICA and HEEET/3MDCP are proven and capable TPS solutions that are needed for the majority of future SMD-PSD missions. FMI has been a critical partner in the development of both PICA and HEEET as FMI's manufacturing capabilities are essential for the large-scale processing of PICA, HEEET and 3MDCP TPS materials in support of countless past and future NASA missions acrosss the solar system.
The Functional Mock-up Interface - Machine Learning Center is a tool to interface the Python-Tensorflow library with building simulation models, to develop and train machine learning-based controls. In particular, this framework allows the use of reinforcement learning through the standardized Functional Mock-up Interface, an open industry standard for co-simulation. First application was the development of a controller for dynamic façade and heating ventilation and air conditioning (HVAC) systems.
To meet the rising demand for an Advanced Air Mobility (i.e. urban and rural unmanned aircraft systems) ecosystem, NASA Aeronautics Research Mission Directorate (ARMD) is hosting a series of simulations and flight tests under the High Density Vertiplex sub-project (HDV). HDV aims to develop an integrated automation architecture to support terminal area flight operations. The HDV simulations and flight tests address safety, integration, and operational challenges, while integrated systems and software demonstrate design readiness, robustness, and interoperability. During the initial HDV simulation in 2021, a prototype traffic management tool developed by NASA called Fleet Management Interface (FMI) was tested. FMI was designed to introduce an advanced level of human-automation interaction to aid both Ground Control Station Operators (GCSOs) and Fleet Managers (FMs) in remotely managing flights under their ownership. In a human-in-the-loop simulation, a usability study was conducted with FMI to identify optimal approaches for displaying information for human operators using subjective measures of usability, workload, situation awareness, risk, and trust, along with qualitative feedback. This study consisted of task analysis in which GCSO and FM subjects used an Urban Air Mobility (UAM) environment to develop and execute a plan for two different traffic scenarios of remotely controlled vehicles. In each scenario, a controlled vehicle completed a takeoff, active flight, and landing sequence while automated traffic flew in the background at a rate of 20 operations per hour. In the first scenario, the controlled vehicle flew a nominal route with takeoff and landing at the same vertiport. In the second scenario, the controlled vehicle started on the nominal route, then diverted to an unplanned location mid-flight. Results showed that self-reported performance, usability, trust, and situation awareness ratings of FMI were moderately to strongly high. There were small differences between scenarios, with Scenario 2 being perceived as more unstable, complex, variable, risky, and potentially harmful than Scenario 1. Furthermore, participants described improvements that could be made to create a better user experience. For example, users would like greater configurability of the interface based on their personal information requirements, and they would like the opportunity to review routes before assigning them. The results from this study will inform future development of the FMI with the end goal of creating a reference automation tool for airspace management procedures in AAM. The FMI could be introduced as a potential way to reduce dependency on traditional air navigation services through increased automation in high density vertiplex environments.
To meet the rising demand for an Advanced Air Mobility (AAM) (i.e. urban and rural unmanned aircraft systems) ecosystem, the NASA Aeronautics Research Mission Directorate (ARMD) is hosting a series of simulations and flight tests under the High Density Vertiplex sub-project (HDV) to prototype and study the effectiveness AAM capabilities under various operational contexts. HDV aims to develop an integrated automation architecture to support terminal area flight operations. The HDV simulations and flight tests address safety, integration, and operational challenges, while integrated systems and software demonstrate design readiness, robustness, and interoperability. During the initial HDV simulation in 2021, a prototype traffic management tool developed by NASA called the Fleet Management Interface (FMI) was tested. FMI was designed to introduce an advanced level of human-automation interaction to aid both Ground Control Station Operators (GCSOs) and Fleet Managers (FMs) in remotely managing flights under their ownership. In a human-in-the-loop simulation, a usability study was conducted with the FMI to identify optimal approaches for displaying information to human operators using subjective measures of usability, workload, situation awareness, risk, and trust, along with qualitative feedback. This study consisted of task analysis in which GCSO and FM subjects used an Urban Air Mobility (UAM) environment to develop and execute a plan for two different traffic scenarios of remotely controlled vehicles. In each scenario, a remotely controlled vehicle completed a takeoff, active flight, and landing sequence while simulated traffic flew in the background at a rate of 20 operations per hour. In the first scenario, the controlled vehicle flew a nominal route with takeoff and landing at the same vertiport. In the second scenario, the controlled vehicle started on the nominal route, then diverted to an unplanned location mid-flight. Results showed that self- reported performance, usability, trust, and situation awareness ratings of FMI were moderately to strongly high. There were small differences between scenarios, with Scenario 2 being perceived as more unstable, complex, variable, risky, and potentially harmful than Scenario 1. Furthermore, participants described improvements that could be made to create a better user experience. For example, users suggested customizable interfaces to accommodate information display preferences, and the ability to review routes before assigning them. The results from this study will inform future development of the FMI with the end goal of creating a reference automation tool for airspace management procedures in AAM. The FMI could serve to reduce dependency on traditional air navigation services through increased automation in high density vertiplex environments.
The CyDER project aimed at developing an open-source, modular and scalable co-simulation platform for power grids with large shares of Distributed Energy Resources (DERs). The project partners are the Lawrence Berkeley National Lab (LBNL), Lawrence Livermore National Lab (LLNL), PG&E, SolarCity, and ChargePoint. The prime recipient is LBNL; SolarCity and ChargePoint were partners for the project’s first two years. Increased DER integration introduces a number of challenges in power grid operation including a more dynamic interaction between the transmission grid and distribution grids, and increased modeling complexity. Although specialized software exists to precisely model different components of the power system, it is far from trivial to integrate all various models and perform a holistic simulation. Instead of replicating all models in a common simulation program, a commonly accepted approach to tackle this model diversity is to couple third-party simulators and models through a co-simulation platform that coordinates information exchange among the various components. Following this line of research, this project’s objective was to develop a co-simulation platform based on a widely accepted industrial standard called Functional Mockup Interface (FMI). Within this process, the project developed models compliant with the FMI standard, called Functional Mockup Units (FMUs), and used them to perform various operational and planning power system analyses. Relying and building upon an industrial standard is the main differentiation of this project compared with previous or parallel efforts in the co-simulation area. Particular emphasis was put on delivering software utilities to facilitate setting up and running co-simulations by end-users. Furthermore, a strong aspect of this project is demonstrating that co-simulation techniques can be used to perform Hardware-in-the-Loop (HIL) simulations that couple software components (e.g., simulated models) with hardware components (e.g., real devices such PV systems and batteries). The long-term goal of CyDER project is to help establish FMI as a powerful standard for co-simulation and promote adoption by electric utilities and other interested stakeholders. The main accomplishments of the project include the development of several FMUs including distribution and transmission grid models, PV inverters with Volt/Var/Watt controllers, batteries, and predictive optimal controllers. Additionally, a unique software package was developed, called SimulatorToFMU, which is capable of exporting any Python-driven simulator or Python script as an FMU. This is an important contribution towards establishing FMI as one of the main co-simulation standards, because more and more third-party programs for sub-system modeling and simulation are delivered with Python APIs. The CyDER platform was used to perform PV hosting capacity analyses in real utility feeders with and without smart inverter controls, battery storage, and EV charging. Smart inverter controls include conventional Volt/Var/Watt controls for reactive power support and active power curtailment, but also predictive controls that optimize the charging and discharging profile of the battery connected on the DC side in order to minimize the customer’s economic benefit. Finally, an important result of this project is delivering an experimental setup that consists of residential-scale PV inverters with battery storage, a real-time grid simulator with an ideal voltage source as grid emulator, and micro Phasor Measurement Units (PMUs). All these components and additional software modules are coupled to one another using the FMI standard and can be co-simulated with the CyDER platform.
It is very important to know how much rain and snow falls around the world for uses that range from crop forecasting to disaster response, drought monitoring to flood forecasting, and weather analysis to climate research. Precipitation is usually measured with rain gauges, but rain gauges don t exist in areas that are sparsely populated, which tends to be a good portion of the globe. To overcome this, meteorologists use satellite data to estimate global precipitation. However, it is difficult to estimate rain and especially snow in cold climates using most current satellites. The satellite sensors are often "confused" by a snowy or frozen surface and therefore cannot distinguish precipitation. One commonly used satellite-based precipitation data set, the Global Precipitation Climatology Project (GPCP) data, overcomes this frozen-surface problem through the innovative use of two sources of satellite data, the Television Infrared Observation Satellite Operational Vertical Sounder (TOVS) and the Atmospheric Infrared Sounder (AIRS). Though the GPCP estimates are generally considered a very reliable source of precipitation, it has been difficult to assess the quality of these estimates in cold climates due to the lack of gauges. Recently, the Finnish Meteorological Institute (FMI) has provided a 12-year span of high-quality daily rain gauge observations, covering all of Finland, that can be used to compare with the GPCP data to determine how well the satellites estimate cold-climate precipitation. Comparison of the monthly GPCP satellite-based estimates and the FMI gauge observations shows remarkably good agreement, with the GPCP estimates being 6% lower in the amount of precipitation than the FMI observations. Furthermore, the month-to-month correlation between the GPCP and FMI is very high at 0.95 (1.0 is perfect). The daily GPCP estimates replicate the FMI daily occurrences of precipitation with a correlation of 0.55 in the summer and 0.45 in the winter. The winter result indicates the GPCP estimates have skill in "seeing" snowfall, which is the most challenging situation. Thus, the GPCP data set successfully overcomes a current limitation in satellite meteorology, namely the estimation of cold-climate precipitation. The success of the GPCP data set bodes well for future missions, whose instrumentation is specifically designed to give even more information for addressing cold-climate precipitation.
An in-memory coupling between the sub-channel thermal hydraulics code COBRA-TF (CTF), which is included in the Virtual Environment for Reactor Applications (VERA), and the systems code Transient Simulation Framework of Reconfigurable Models (TRANSFORM) was developed in this work. Data exchange is accomplished by using the Functional Mock-Up Interface (FMI), an open standard for coupling dynamic systems models together. The FMI-based coupling necessitated the development of a novel FORTRAN wrapper for communicating with Functional Mock-Up Units. This wrapper will facilitate future FMI-based code couplings with other FORTRAN-based programs. CTF-TRANSFORM is exercised on a simplified Molten Salt Reactor Experiment (MSRE) model in steady-state and transient configurations. The coupled CTF-TRANSFORM model is shown to predict core temperature deltas similar to those available in historical MSRE operational data and is shown to be robust to fast power transients.The coupling paves the way to performing sensitivity and design studies impossible with VERA/CTF alone, in which secondary and tertiary loop operating conditions and design parameters may be perturbed and their impact on the core operating conditions studied.
This dataset contains drilling core data from well 16B(78)-32, including PDF documents with flattened core images annotated by feature type and core interval, as well as spreadsheets detailing feature morphologies by depth, planar feature measurements, and planar feature orientations rotated to in situ conditions. Core was recovered from three intervals, one per stimulation stage, in the crystalline rocks affected by the stimulation of well 16A(78)-32. Seven core runs were conducted, yielding 135.8 feet of recovered core. Features in the core were categorized into planar fractures, semi-planar fractures, unbroken mineralized fractures, rough fractures, curviplanar fractures, concave-convex surfaces, and planar compositional features such as mylonite or dike-like structures. Planar features were measured while the core was positioned horizontally, with the core axis aligned to a downhole azimuth of 42 degrees. Planar core measurements from stimulations 2 and 3 that could be confidently correlated with FMI data were rotated to in situ orientations. This was done by rotating the planes along vertical and horizontal axes to match the azimuth and inclination data recorded in the directional survey of well 16B(78)-32, as well as applying an axial rotation to resemble the fracture orientations observed in the FMI log at corresponding depths. Coherent sets of planar fracture measurements were made by aligning the core within each 3-foot section of the dissected core barrel, and between adjacent 3-foot sections within a core run by matching rock fabrics, saw cuts and/or tool marks. Where coherent fracture measurements could not be made within a core run, data sets are denoted by a subscript (i.e. 2-Ta and 2-Tb both come from tangent core run number 2).
Ferromagnetic insulating (FMI) double perovskite oxides (DPOs) A2BB′O6 with near-room-temperature Curie temperatures are promising candidates for ambient-temperature spintronics applications. To realize their potential, epitaxial stabilization of DPO films and understanding the effect of multiple broken symmetries across the film/substrate interface are crucial. This study investigates ultrathin films of the FMI Nd2NiMnO6 grown on SrTiO3 (STO) and NdGaO3 (NGO) substrates. By comparing growth on these substrates, we examine the influence of polarity and structural symmetry mismatches, which are absent in the NGO system. The interface exhibits immeasurable resistance in both cases. Using synchrotron x-ray diffraction, we show that films have three octahedral rotational domains because of the structural symmetry mismatch with the STO substrate. Furthermore, our coherent Bragg rod analysis of specular x-ray diffraction reveals a significant modification of the out-of-plane lattice parameter within a few unit cells at the film/substrate interface and the surface. This arises from polarity compensation and surface symmetry breaking, respectively. These structural alterations influence the Mn orbital symmetry, a dependence that we further confirm through x-ray linear dichroism measurements. Since the ferromagnetism in insulating DPOs is mediated by orbital-dependent superexchange interactions [Phys. Rev. Lett. 100, 186402 (2008)0031-900710.1103/PhysRevLett.100.186402], our study provides a framework for understanding the evolution of magnetism in ultrathin geometry.
The on-orbit calibration of the optics, structure, and control systems of the CSI Focus Mission Interferometer (FMI) is described. The calibration involves the estimation and propagation of both positional and rotational parameters and the propagation of both positional and rotational parameters at the nanometer/nanoradian level. It is shown that, given a nanometer class metrology system to monitor positional changes of critical optical elements, this calibration procedure should enable the FMI to perform 50 picoradian astrometry. The same Kalman filter that implements the initializing calibration of the interferometer baselines and internal pathlengths will also participate in the astrometric measurements of stellar positions.
Report discusses calibration and operation of conceptual Focus Mission Interferometer (FMI), consisting of component instruments mounted at widely separated locations on large truss structure in orbit 1,400 km above Earth. Includes six telescopes in linear array. Outputs combined in pairlike fashion so FMI operates as three distinct two-telescope interferometers. Accurate enough for submilliarcsecond astrometry.
The CSI program at JPL is chartered to develop the structures and control technology needed for sub-micron level stabilization of future optical space systems. The extreme dimensional stability required for such systems derives from the need to maintain the alignment and figure of critical optical elements to a small fraction (typically 1/20th to 1/50th) of the wavelength of detected radiation. The wavelength is about 0.5 micron for visible light and 0.1 micron for ultra-violet light. This lambda/50 requirement is common to a broad class of optical systems including filled aperture telescopes (with monolithic or segmented primary mirrors), sparse aperture telescopes, and optical interferometers. The challenge for CSI arises when such systems become large, with spatially distributed optical elements mounted on a lightweight, flexible structure. In order to better understand the requirements for micro-precision CSI technology, a representative future optical system was identified and developed as an analytical testbed for CSI concepts and approaches. An optical interferometer was selected as a stressing example of the relevant mission class. The system that emerged was termed the Focus Mission Interferometer (FMI). This paper will describe the multi-layer control architecture used to address the FMI's nanometer level stabilization requirements. In addition the paper will discuss on-going and planned experimental work aimed at demonstrating that multi-layer CSI can work in practice in the relevant performance regime.
The application of the 2D-video disdrometer to measure fall speed and snow size distribution and to derive liquid equivalent snow rate, mean density-size and reflectivity-snow rate power law is described. Inversion of the methodology proposed by Böhm provides the pathway to use measured fall speed, area ratio and '3D' size measurement to estimate the mass of each particle. Four snow cases from the Light Precipitation Validation Experiment are analyzed with supporting data from other instruments such as Precipitation Occurrence Sensor System (POSS), Snow Video Imager (SVI), a network of seven snow gauges and three scanning C9 band radars. The radar-based snow accumulations using the 2DVD-derived Ze-SR relation are in good agreement with a network of seven snow gauges and outperform the accumulations derived from a climatological Ze-SR relation used by the Finnish Meteorological Institute (FMI). The normalized bias between radar-derived and gauge accumulation is reduced from 96% when using the fixed FMI relation to 28% when using the Ze-SR relations based on 2DVD data. The normalized standard error is also reduced significantly from 66% to 31%. For two of the days with widely different coefficients of the Ze-SR power law, the reflectivity structure showed significant differences in spatial variability. Liquid water path estimates from radiometric data also showed significant differences between the two cases. Examination of SVI particle images at the measurement site corroborated these differences in terms of unrimed versus rimed snow particles. The findings reported herein support the application of Böhm's methodology for deriving the mean density-size and Ze-SR power laws using data from 2D-video disdrometer.
Two satellites are currently monitoring surface soil moisture (SM) using L-band observations: SMOS (Soil Moisture and Ocean Salinity), a joint ESA (European Space Agency), CNES (Centre national d'tudes spatiales), and CDTI (the Spanish government agency with responsibility for space) satellite launched on November 2, 2009 and SMAP (Soil Moisture Active Passive), a National Aeronautics and Space Administration (NASA) satellite successfully launched in January 2015. In this study, we used a multilinear regression approach to retrieve SM from SMAP data to create a global dataset of SM, which is consistent with SM data retrieved from SMOS. This was achieved by calibrating coefficients of the regression model using the CATDS (Centre Aval de Traitement des Donnes) SMOS Level 3 SM and the horizontally and vertically polarized brightness temperatures (TB) at 40 deg incidence angle, over the 2013 - 2014 period. Next, this model was applied to SMAP L3 TB data from Apr 2015 to Jul 2016. The retrieved SM from SMAP (referred to here as SMAP_Reg) was compared to: (i) the operational SMAP L3 SM (SMAP_SCA), retrieved using the baseline Single Channel retrieval Algorithm (SCA); and (ii) the operational SMOSL3 SM, derived from the multiangular inversion of the L-MEB model (L-MEB algorithm) (SMOSL3). This inter-comparison was made against in situ soil moisture measurements from more than 400 sites spread over the globe, which are used here as a reference soil moisture dataset. The in situ observations were obtained from the International Soil Moisture Network (ISMN; https:ismn.geo.tuwien.ac.at) in North of America (PBO_H2O, SCAN, SNOTEL, iRON, and USCRN), in Australia (Oznet), Africa (DAHRA), and in Europe (REMEDHUS, SMOSMANIA, FMI, and RSMN). The agreement was analyzed in terms of four classical statistical criteria: Root Mean Squared Error (RMSE),Bias, Unbiased RMSE (UnbRMSE), and correlation coefficient (R). Results of the comparison of these various products with in situ observations show that the performance of both SMAP products i.e. SMAP_SCA and SMAP_Reg is 48 similar and marginally better to that of the SMOSL3 product particularly over the PBO_H2O, SCAN, and USCRN sites. However, SMOSL3 SM was closer to the in situ observations over the DAHRA and Oznet sites. We found that the correlation between all three datasets and in situ measurements is best (R 0.80) over the Oznet sites and worst (R 0.58) over the SNOTEL sites for SMAP_SCA and over the DAHRA and SMOSMANIA sites (R 0.51 and R 0.45 for SMAP_Reg and SMOSL3, respectively). The Bias values showed that all products are generally dry, except over RSMN, DAHRA, and Oznet (and FMI for SMAP_SCA). Finally, our analysis provided interesting insights that can be useful to improve the consistency between SMAP and SMOS datasets.
Among the challenges faced by the Entry Descent and Landing (EDL) community have been: the lack of a matured forebody heatshield thermal protection system (TPS) capable of meeting the demanding entry environments for the high priority in-situ science missions identified in the decadal survey at Venus, Saturn and the Ice Giants, and the continued sustainment of thermal protection systems/materials. In response to the identified shortfall in TPS technologies capable of extreme entry environments NASA's Space Technology Mission Directorate (STMD) and Science Mission Directorate (SMD) initiated the Heatshield for Extreme Entry Environment Technology (HEEET) project which has matured a 3D-Woven TPS to Technology Readiness Level 6 and which is ready for infusion into these high priority missions. During the development of HEEET long term sustainability was a key consideration. However existing TPS also continue to face sustainability issues. Phenolic Impregnated Carbon Ablator (PICA) has been/is being utilized by many SMD Missions (Stardust, Mars Science Laboratory, OSIRIS-Rex, Mars 2020, Dragonfly) and is under consideration for others including Mars Sample Return, so maintaining PICA for the long term is a priority for NASA. This presentation will discuss raw material sustainability challenges faced by PICA and the efforts by NASA to work with Fiber Materials Inc (FMI) to resolve these challenges with a more sustainable supply chain. In addition, NASA is working with FMI to increase the manufacturing scale for single piece PICA heatshields and to expand the aerothermal performance envelop maturing PICA for larger sized heatshield and more aggressive entry environments. This presentation will also identify challenges and limitations with these systems, particularly around understanding failure modes in these materials and systems and how understanding these may allow use of these systems in environments that are difficult to achieve in ground based testing.
Challenges faced by the Entry Descent and Landing (EDL) community include the lack of a matured forebody heatshield thermal protection system (TPS) capable of meeting the demanding entry environments for the high priority in-situ science missions identified in the decadal survey at Venus, Saturn and the Ice Giants, and the continued sustainment of thermal protection systems/materials. In response to the identified shortfall in TPS technologies capable of extreme entry environments NASA's Space Technology Mission Directorate (STMD) and Science Mission Directorate (SMD) initiated the Heatshield for Extreme Entry Environment Technology (HEEET) project which has matured a 3D-Woven TPS to Technology Readiness Level 6 and which is ready for infusion into these high priority missions. During the development of HEEET long term sustainability was a key consideration. However existing TPS also continue to face sustainability issues. Phenolic Impregnated Carbon Ablator (PICA) has been/is being utilized by many SMD Missions (Stardust, Mars Science Laboratory, OSIRIS-Rex, Mars 2020, Dragonfly) and is under consideration for others including Mars Sample Return, so maintaining PICA for the long term is a priority for NASA. This presentation will discuss raw material sustainability challenges faced by PICA and the efforts by NASA to work with Fiber Materials Inc (FMI) to resolve these challenges with a more sustainable supply chain. In addition, NASA is working with FMI to increase the manufacturing scale for single piece PICA heatshields and to expand the aerothermal performance envelop maturing PICA for larger sized heatshield and more aggressive entry environments. This presentation will also identify challenges and limitations with these systems, particularly around understanding failure modes in these materials and systems and how understanding these may allow use of these systems in environments that are difficult to achieve in ground based testing