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Stennis Space Center Verification & Validation Capabilities

Scientists within NASA s Applied Sciences Directorate have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site enables the in-flight characterization of satellite and airborne high spatial and moderate resolution remote sensing systems and their products. The smaller scale of the newer high resolution remote sensing systems allows scientists to characterize geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active lidar systems. SSC employs geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment, and thermal calibration ponds to characterize remote sensing data products. The SSC Instrument Validation Lab is a key component of the V&V capability and is used to calibrate field instrumentation and to provide National Institute of Standards and Technology traceability. This poster presents a description of the SSC characterization capabilities and examples of calibration data.

Pagnutti, Mary↗

CarbonSAFE East Sub-Basin Site Feasibility Plan Subtask 4.5 – Topical Report: DOE-FE0029445-12

Regional industrial facilities were considered for potential commercial-scale [50 million metric tons (55 tons) or more] geological storage in a CO 2 source and storage network study for the CarbonSAFE Illinois East Sub-Basin region (DOE-FE0029445-9). The study area has a number of potential geologic sequestration targets, including three significant deep saline reservoirs with corresponding seals, and potential enhanced oil recovery (CO 2 -EOR) opportunities (Figure 1). Recent geological research has focused on a high porosity, arkosic zone within the Lower Mt. Simon Sandstone as a prospective storage resource play in the region. This report summarizes the regional geology of the East Sub-Basin and discusses considerations leading from pre-feasibility work into the Wabash CarbonSAFE feasibility project (DE-FE0031626), recently underway in conjunction with the Wabash Valley Resources (WVR) ammonia plant retrofit taking place at the former US DOE Integrated Gasification Combined Cycle (IGCC) plant located near Terre Haute, Indiana. As part of the feasibility study, geological and site characterization work will address data gaps and risks outlined in Table 1 and will aid continued steps toward commercial-scale CCS at the WVR site. The feasibility plan discussed here draws upon regional assessment work in the East Sub-Basin as it pertains to risk and data needs to characterize the WVR site, highlights plans for data acquisition to support characterization efforts, and offers insight into the legal and permitting landscape surrounding CCS in the state of Indiana.

01 COAL, LIGNITE, AND PEAT↗

Initial Development of A Digital Twin Model for an Electrified Aircraft Propulsion Emulation Rig

In support of aviation fuel burn and emission reduction goals, NASA is pursing high-payoff research investments that promise to transform aviation. This includes investments in Electrified Aircraft Propulsion (EAP), which relies on the generation, storage, transmission, and use of electrical power for producing thrust and optimizing propulsion system efficiency. Multiple technology challenges must be addressed to unlock the full potential of EAP. This includes advances in propulsion controls, which will be vital for ensuring coordinated efficient operation of the complex integrated subsystems that comprise EAP architectures. To support EAP controls research, the NASA Glenn Research Center has developed the Hybrid Propulsion Emulation Rig (HyPER). The HyPER laboratory hardware includes shaft-mounted electric machines, power converters, power supplies, power distribution cables, and an energy storage device that can be reconfigured to represent a variety of EAP architectures. It also includes an integrated real-time computer system that hosts developed EAP control software and turbomachinery simulations. This enables the electrical system and rotating shafts of EAP designs to be implemented in actual hardware and integrated with turbomachinery simulations and system-level EAP control logic implemented in software. In this form, the HyPER laboratory provides a partially simulated, partially hardware-in-the-loop test environment enabling the initial development and evaluation of EAP control technology. A prerequisite for the development of EAP control designs is the availability of a system model that accurately reflects the operation of the electrical system hardware. To support this need, a digital twin model of the HyPER electrical system hardware is under development. This model is being coded in the MATLAB Simulink environment and uses the NASA-developed Electrical Modeling and Thermal Analysis Toolbox (EMTAT) to construct a digital twin framework. EMTAT contains generic electrical component building blocks that are simulated at turbomachinery timescales. Associated inputs and outputs allow the blocks to be combined to model complete electrical systems. The EMTAT blocks also contain adjustable internal maps and parameters that can be set to reflect the operation of a specific electrical component. For the HyPER digital twin, the settings of these EMTAT block internal maps and parameters is determined through machine learning approaches applied to characterization run data collected from the laboratory. During characterization runs the laboratory electrical system hardware is subjected to a full range of torque, speed, and power settings. Acquired data is then used to estimate EMTAT block parameters using a variety of machine learning techniques. The resulting digital twin model is found to match the operation of actual HyPER hardware with an accuracy suitable for control development purposes. It also holds promise for other applications including modeling the performance of HyPER laboratory reconfigurations and model-based anomaly detection. Planned follow-on work to automate post-processing of acquired laboratory data to update the HyPER digital twin model will also be presented and discussed.

Electrified Aircraft Propulsion↗

MSD CoP Webinar: AI and Extreme Events - Overcoming Data Challenges for Improved Characterization of Climate Extremes

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Artificial Intelligence (AI) models require large volumes of data for training and testing. Data requirements present challenges for using AI to explore extreme events with limited observational data. This webinar will showcase two innovative methods developed by part of the European Climate Intelligence (CLINT) project to overcome data challenges and harness AI to improve our understanding of climate extremes. Dr. Ascenso will present his research on data augmentation methods to improve estimates of tropical cyclones using satellite data. His presentation will review established methods for data augmentation and explore opportunities and challenges for using generative AI to generate images of extreme, life-threatening tropical cyclones. Next, Dr. Plesiat will present his research on deep learning techniques to overcome limited observational data sets. His presentation will illustrate deep learning methods to develop AI reconstructions of four climate indices across Europe. Presenters : Dr. Guido Ascenso (post-doctoral researcher, Politecnico di Milano); Dr. Étienne Plésiat (German Climate Computing Centre - DKRZ) Moderator(s): Stefano Galelli (MSD CoP WG Co-Lead), David Gold (MSD CoP WG Co-Lead), Jillian Sturtevant (MSD CoP WG Communications Officer), Matteo Giuliani (Politecnico di Milano, MSD CoP WG Member, Moderator and Organizer) This webinar was held on: October 11, 2024 from 11AM - 1PM ET

AI↗

Multitemporal and Multiscaled Fractal Analysis of Landsat Satellite Data Using the Image Characterization and Modeling System (ICAMS)

The Image Characterization And Modeling System (ICAMS) is a public domain software package that is designed to provide scientists with innovative spatial analytical tools to visualize, measure, and characterize landscape patterns so that environmental conditions or processes can be assessed and monitored more effectively. In this study ICAMS has been used to evaluate how changes in fractal dimension, as a landscape characterization index, and resolution, are related to differences in Landsat images collected at different dates for the same area. Landsat Thematic Mapper (TM) data obtained in May and August 1993 over a portion of the Great Basin Desert in eastern Nevada were used for analysis. These data represent contrasting periods of peak "green-up" and "dry-down" for the study area. The TM data sets were converted into Normalized Difference Vegetation Index (NDVI) images to expedite analysis of differences in fractal dimension between the two dates. These NDVI images were also resampled to resolutions of 60, 120, 240, 480, and 960 meters from the original 30 meter pixel size, to permit an assessment of how fractal dimension varies with spatial resolution. Tests of fractal dimension for two dates at various pixel resolutions show that the D values in the August image become increasingly more complex as pixel size increases to 480 meters. The D values in the May image show an even more complex relationship to pixel size than that expressed in the August image. Fractal dimension for a difference image computed for the May and August dates increase with pixel size up to a resolution of 120 meters, and then decline with increasing pixel size. This means that the greatest complexity in the difference images occur around a resolution of 120 meters, which is analogous to the operational domain of changes in vegetation and snow cover that constitute differences between the two dates.

Quattrochi, Dale A.↗

U-rich U-Mo Solidus, Liquidus, Enthalpy, and Thermal Diffusivity

Several material properties have been studied as a function of composition as part of the USHPRR effort to use U-10Mo for LEU monolithic fuel foils, with special attention to areas where simulation outcomes can be improved. The liquidus and solidus phase boundaries are important for engineering design of processing parameters and for predicting the degree of microsegregation within initial castings. The numerous phase diagram constructions available in the literature differ significantly in their solid/liquid boundary definitions, therefore, an experimental strategy was employed in order to resolve some of the discord. That strategy focuses not on proving any singular point, but instead to provide data with highly characterized uncertainty. The data presented here is the most consistent with the U-rich liquidus and solidus boundaries provided by H. Okamoto (2012), Berche et al. (2011), and Mardon et al. (1959). The recently suggested change in the peritectic reaction temperature (to 1302 K) suggested by Berchè and adopted by Okamoto is also supported, but with lower confidence. The enthalpy of fusion is a basic characteristic of the solidification reaction property for which is required for both research-oriented predictions of behavior and development of applied design strategies for casting engineering. It has been determined that an admixture model for the heat of fusion between U BCC and Mo BCC is a reasonable assumption within the composition region of interest, though limitations of the measurement accuracy impacts the ability to support any trends more detailed than this baseline behavior. A limited number of thermal diffusivity measurements were also performed into the gamma region to provide additional information for solidification modeling and simulations as well as a check on the component properties of thermal conductivity, density, and heat capacity.

36 MATERIALS SCIENCE↗

Landsat image data quality studies

Preliminary results of the Landsat-4 Image Data Quality Analysis (LIDQA) program to characterize the data obtained using the Thematic Mapper (TM) instrument on board the Landsat-4 and Landsat-5 satellites are reported. TM design specifications were compared to the obtained data with respect to four criteria, including spatial resolution; geometric fidelity; information content; and image relativity to Multispectral Scanner (MSS) data. The overall performance of the TM was rated excellent despite minor instabilities and radiometric anomalies in the data. Spatial performance of the TM exceeded design specifications in terms of both image sharpness and geometric accuracy, and the image utility of the TM data was at least twice as high as MSS data. The separability of alfalfa and sugar beet fields in a TM image is demonstrated.

Schueler, C. F.↗

Intelligent multi-sensor integrations

Growth in the intelligence of space systems requires the use and integration of data from multiple sensors. Generic tools are being developed for extracting and integrating information obtained from multiple sources. The full spectrum is addressed for issues ranging from data acquisition, to characterization of sensor data, to adaptive systems for utilizing the data. In particular, there are three major aspects to the project, multisensor processing, an adaptive approach to object recognition, and distributed sensor system integration.

Volz, Richard A.↗

Investigation of Iso-octane Ignition and Validation of a Multizone Modeling Method in an Ignition Quality Tester

An ignition quality tester was used to characterize the autoignition delay times of iso-octane. The experimental data were characterized between temperatures of 653 and 996 K, pressures of 1.0 and 1.5 MPa, and global equivalence ratios of 0.7 and 1.05. A clear negative temperature coefficient behavior was seen at both pressures in the experimental data. These data were used to characterize the effectiveness of three modeling methods: a single-zone homogeneous batch reactor, a multizone engine model, and a three-dimensional computational fluid dynamics (CFD) model. A detailed 874 species iso-octane ignition mechanism (Mehl, M.; Curran, H. J.; Pitz, W. J.; Westbrook, C. K.Chemical kinetic modeling of component mixtures relevant to gasoline. Proceedings of the European Combustion Meeting; Vienna, Austria, April 14-17, 2009) was reduced to 89 species for use in these models, and the predictions of the reduced mechanism were consistent with ignition delay times predicted by the detailed chemical mechanism across a broad range of temperatures, pressures, and equivalence ratios. The CFD model was also run without chemistry to characterize the extent of mixing of fuel and air in the chamber. The calculations predicted that the main part of the combustion chamber was fairly well-mixed at longer times (> ~30 ms), suggesting that the simpler models might be applicable in this quasi-homogeneous region. The multizone predictions, where the combustion chamber was divided into 20 zones of temperature and equivalence ratio, were quite close to the coupled CFD-kinetics results, but the calculation time was ~11 times faster than the coupled CFD-kinetics model. Although the coupled CFD-kinetics model captured the observed negative temperature coefficient behavior and pressure dependence, discrepancies remain between the predictions and the observed ignition time delays, suggesting improvements are still needed in the kinetic mechanism and/or the CFD model. This approach suggests a combined modeling approach, wherein the CFD calculations (without chemistry) can be used to examine the sensitivity of various model inputs to in-cylinder temperature and equivalence ratios. In conclusion, these values can be used as inputs to the multizone model to examine the impact on ignition delay. Additionally, the speed of the multizone model also makes it feasible to quickly test more detailed kinetic mechanisms for comparison to experimental data and sensitivity analysis.

33 ADVANCED PROPULSION SYSTEMS↗

Replication Data for: Automated Detection and Characterization of Surface Restructuring Events in Bimetallic Catalysts

The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The accurate assessment of small-angle X-ray scattering data

Small-angle X-ray scattering (SAXS) has grown in popularity in recent times with the advent of bright synchrotron X-ray sources, powerful computational resources and algorithms enabling the calculation of increasingly complex models. However, the lack of standardized data-quality metrics presents difficulties for the growing user community in accurately assessing the quality of experimental SAXS data. Here, a series of metrics to quantitatively describe SAXS data in an objective manner using statistical evaluations are defined. These metrics are applied to identify the effects of radiation damage, concentration dependence and interparticle interactions on SAXS data from a set of 27 previously described targets for which high-resolution structures have been determined via X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. Studies show that these metrics are sufficient to characterize SAXS data quality on a small sample set with statistical rigor and sensitivity similar to or better than manual analysis. The development of data-quality analysis strategies such as these initial efforts is needed to enable the accurate and unbiased assessment of SAXS data quality.

36 MATERIALS SCIENCE↗

Applying mobile technology to data collection for environmental characterization and remediation, beyond the science - 15453

The rapid advancements of our time bring us new methods of analysis that enhance the accuracy and sensitivity of measurement, improving the science used to solve problems and meet our objectives. What is often overlooked in our industry are the technology advancements that can dramatically improve the speed, accuracy and completeness by which those data can be collected, communicated, managed and reported. In addition, in the time used to generate and collect the analytical data, the technology collects, manages and reports other process data that can be used to better manage and facilitate our business process improving efficiency and communications as well as providing the information needed to track and manage cost and schedule. Good information management practices, including the use of innovative technology solutions like mobile data collection, are the drivers for project implementation. However, experience has highlighted key success factors that will maximize the level of success and benefit realized by the project. These factors include: -A comprehensive, working knowledge of operational objectives; - Detailed, documented process and data work-flows; - Effective technology selection and/or development (right tool for the job); - Complete integration of the technology into day to day work practice accomplished through effective training and implementation planning. Once this formula is in place, and executed consistently, it can be applied to any environmental investigation and/or remediation scenario. The proof is in the calculated return on investment and captured lessons learned for each project. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Characterization and classification of sea ice in polarimetric SAR data

A more detailed characterization of the apparent thin ice types in the multifrequency, multipolarization synthetic aperture radar (SAR) dataset acquired during a campaign for validation of the DMSP SSM/I radiometer ice products is given. The emphasis is on providing a more detailed characterization of the signatures of apparent thin ice types observed in this data and the utility of these signatures for ice type classification purposes. The statistical characteristics of these signatures and their dependence on system calibration are summarized. Implications of these observations for sea ice scattering models are briefly discussed.

Kwok, R.↗

Fractal Characterization of Multitemporal Remote Sensing Data

Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the capture, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust software and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISs. Scale is fundamental to the characterization of geo-spatial data as represented in GISs, but we have relatively little insight on how to measure the effects of scale in representing data that are acquired in different formats and exist in varying spatial, temporal and radiometric configurations. Moreover, the complexities associated with the integration of multiscaled data sets in a multitude of formats are exacerbated by the confusion of what the term "scale" is from a multidisciplinary perspective. "Scale" takes on significantly different meanings depending upon one's disciplinary background and spatial perspective which lead to substantial confusion in the input, manipulation, analysis, and output operations. Hence, we must begin to look at the universality of scale and begin to develop the theory, methods, and techniques necessary to advance knowledge on the "Science of Scale' across all disciplines that use GISs.

Quattrochi, Dale A.↗

Fractal Characterization of Multitemporal Remote Sensing Data

Scale is an 'innate' concept in geographical information systems (GIS). It is recognized as something that is intrinsic to the capture, storage, manipulation, analysis, modelling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GIS becomes more sophisticated as a product of more robust software and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GIS. Scale is fundamental to the characterization of geo-spatial data as represented in GIS, but we have relatively little insight on how to measure the effects of scale in representing data that are acquired in different formats and exist in varying spatial, temporal and radiometric configurations. Moreover, the complexities associated with the integration of multi-scaled data sets in a multitude of formats are exacerbated by the confusion of what the term 'scale' means from a multidisciplinary perspective. 'Scale' takes on significantly different meanings depending upon one's disciplinary background and spatial perspective, which can lead to substantial confusion in the input, manipulation, analysis, and output operations. Hence, we must begin to look at the universality of scale and begin to develop the theory, methods and techniques necessary to advance knowledge on the 'Science of scale' across all disciplines that use GIS.

Quattrochi, Dale A.↗

Performance Characterization of Digital Optical Data Transfer Systems for Use in the Space Radiation Environment

Radiation effects in photonic and microelectronic components can impact the performance of high-speed digital optical data link in a variety of ways. This segment of the short course focuses on radiation effects in digital optical data links operating in the MHz to GHz regime. (Some of the information is applicable to frequencies above and below this regime) The three basic component level effects that should be considered are Total Ionizing Dose (TID), Displacement Damage Dose (DDD) and Single Event Effects (SEE). In some cases the system performance degradation can be quantified from component level tests, while in others a more holistic characterization approach must be taken. In Section 2.0 of this segment of the Short Course we will give a brief overview of the space radiation environment follow by a summary of the basic space radiation effects important for microelectronics and photonics listed above. The last part of this section will give an example of a typical mission radiation environment requirements. Section 3.0 gives an overview of intra-satellite digital optical data link systems. It contains a discussion of the digital optical data link and it's components. Also, we discuss some of the important system performance metrics that are impacted by radiation effects degradation of optical and optoelectronic component performance. Section 4.0 discusses radiation effects in optical and optoelectronic components. While each component effect will be discussed, the focus of this section is on degradation of passive optical components and SEE in photodiodes (other mechanisms are covered in segment II of this short course entitled "Photonic Devices with Complex and Multiple Failure Modes"). Section 5.0 will focus on optical data link system response to the space radiation environment. System level SEE ground testing will be discussed. Then we give a discussion of system level assessment of data link performance when operating in the space radiation environment.

Reed, Robert A.↗

A survey of solar protons and alpha differential spectra between 1 and greater than 400 MeV/nucleon

Attempts to systematically measure and fit a large sample of flare spectra from IMP 7 and 8 satellite data to determine the spectral forms that characterize the data and the range of spectral slopes are reported. Proton spectra are constructed covering the range 0.9 to over 400 MeV, and alpha fluxes from 1.4-80 MeV/nucleon. The event spectra are composed of fluxes measured at different times at each energy, and fitting procedures were employed such as a power law in kinetic energy, an exponential in rigidity, an exponential in energy, and a Bessel function of momentum/nucleon. Best fits were obtained with the exponential in rigidity and the Bessel function, with the Bessel function having a better numerical accuracy for all 21 proton spectra considered.

Mcguire, R. E.↗

Evaluation of spacecraft product assurance requirements and flight performance history

The Jet Propulsion Laboratory (JPL) has undertaken a task to relate long duration, space flight hardware performance to specific product assurance requirements established during the hardware development process. This paper describes the approach that JPL is using to correlate in-flight and ground test hardware failures to critical product assurance practices implemented on a given flight project. The first step in this effort has been to collect, and convert into a convenient format, in-flight problem, failure, and anomaly data. A characterization of a subset of this anomaly data base, focusing on anomaly causes, time dependence, and subsystem affected is presented.

Gonzalez, Charles C.↗