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DOE OSTI2022

A Statistical Interpolation Code for Ocean Analysis and Forecasting

Abstract We present a data assimilation package for use with ocean circulation models in analysis, forecasting, and system evaluation applications. The basic functionality of the package is centered on a multivariate linear statistical estimation for a given predicted/background ocean state, observations, and error statistics. Novel features of the package include support for multiple covariance models, and the solution of the least squares normal equations either using the covariance matrix or its inverse—the information matrix. The main focus of this paper, however, is on the solution of the analysis equations using the information matrix, which offers several advantages for solving large problems efficiently. Details of the parameterization of the inverse covariance using Markov random fields are provided and its relationship to finite-difference discretizations of diffusion equations are pointed out. The package can assimilate a variety of observation types from both remote sensing and in situ platforms. The performance of the data assimilation methodology implemented in the package is demonstrated with a yearlong global ocean hindcast with a 1/4° ocean model. The code is implemented in modern Fortran, supports distributed memory, shared memory, multicore architectures, and uses climate and forecasts compliant Network Common Data Form for input/output. The package is freely available with an open source license from www.tendral.com/tsis/ .

Srinivasan, Ashwanth↗

NASA NTRS1973

Analysis and modeling of a family of two-transistor parallel inverters

A family of five static dc-to-square-wave inverters, each employing a square-loop magnetic core in conjunction with two switching transistors, is analyzed using piecewise-linear models for the nonlinear characteristics of the transistors, diodes, and saturable-core devices. Four of the inverters are analyzed in detail for the first time. These analyses show that, by proper choice of a frame of reference, each of the five quite differently appearing inverter circuits can be described by a common equivalent circuit. This equivalent circuit consists of a five-segment nonlinear resistor, a nonlinear saturable reactor, and a linear capacitor. Thus, by proper interpretation and identification of the parameters in the different circuits, the results of a detailed solution for one of the inverter circuits provide similar information and insight into the local and global behavior of each inverter in the family.

Lee, F. C. Y.↗

NASA NTRS2007

The Plane-parallel Albedo Bias of Liquid Clouds from MODIS Observations

In our most advanced modeling tools for climate change prediction, namely General Circulation Models (GCMs), the schemes used to calculate the budget of solar and thermal radiation commonly assume that clouds are horizontally homogeneous at scales as large as a few hundred kilometers. However, this assumption, used for convenience, computational speed, and lack of knowledge on cloud small scale variability, leads to erroneous estimates of the radiation budget. This paper provides a global picture of the solar radiation errors at scales of approximately 100 km due to warm (liquid phase) clouds only. To achieve this, we use cloud retrievals from the instrument MODIS on the Terra and Aqua satellites, along with atmospheric and surface information, as input into a GCM-style radiative transfer algorithm. Since the MODIS product contains information on cloud variability below 100 km we can run the radiation algorithm both for the variable and the (assumed) homogeneous clouds. The difference between these calculations for reflected or transmitted solar radiation constitutes the bias that GCMs would commit if they were able to perfectly predict the properties of warm clouds, but then assumed they were homogeneous for radiation calculations. We find that the global average of this bias is approx.2-3 times larger in terms of energy than the additional amount of thermal energy that would be trapped if we were to double carbon dioxide from current concentrations. We should therefore make a greater effort to predict horizontal cloud variability in GCMs and account for its effects in radiation calculations.

Oreopoulos, Lazaros↗

NASA NTRS2019

Rethinking CO Antibiosignatures in the Search for Life Beyond the Solar System

Some atmospheric gases have been proposed as counter indicators to the presence of life on an exoplanet if remotely detectable at sufficient abundance (i.e., antibiosignatures), informing the search for biosignatures and potentially fingerprinting uninhabited habitats. However, the quantitative extent to which putative antibiosignatures could exist in the atmospheres of inhabited planets is not well understood. The most commonly referenced potential antibiosignature is CO, because it represents a source of free energy and reduced carbon that is readily exploited by life on Earth and is thus often assumed to accumulate only in the absence of life. Yet, biospheres actively produce CO through biomass burning, photooxidation processes, and release of gases that are photochemically converted into CO in the atmosphere. We demonstrate with a 1D ecosphere-atmosphere model that reducing biospheres can maintain CO levels of approximately 100 ppmv (parts per million by volume) even at low H2 fluxes due to the impact of hybrid photosynthetic ecosystems. Additionally, we show that photochemistry around M dwarf stars is particularly favorable for the buildup of CO, with plausible concentrations for inhabited, oxygen-rich planets extending from hundreds of ppm to several percent. Since CH4 buildup is also favored on these worlds, and because O2 and O3 are likely not detectable with the James Webb Space Telescope, the presence of high CO (greater than 100 ppmv) may discriminate between oxygen-rich and reducing biospheres with near-future transmission observations. These results suggest that spectroscopic detection of CO can be compatible with the presence of life and that a comprehensive contextual assessment is required to validate the significance of potential antibiosignatures.

Earth↗

NASA NTRSDate not supplied

Camera Calibration and Alignment Metrology at Johnson Space Center’s Electro-Optics Laboratory

It is increasingly common to see spacecraft equipped with cameras for the purpose of navigation. Images are either sent to Earth or processed autonomously on-board to provide information about the vehicle’s position, velocity, and/or attitude. These can be images of stars or celestial bodies for absolute navigation, or images of another spacecraft for relative navigation. While monocular cameras do not provide range information, the images they capture can be processed to determine bearing vectors to target objects within the camera’s field of view. For a camera to be effective in navigation, it must be carefully calibrated and aligned. This involves accurately modeling the optical effects that govern the projection of line-of-sight directions onto the camera’s pixels and determining the camera’s orientation relative to the spacecraft’s reference frame. Engineers at Johnson Space Center’s Electro-Optics Lab regularly perform camera inspection, calibration, and alignment metrology. This was done for the Orion Optical Navigation (OpNav) Camera, the Orion Docking Camera (DCAM), and for numerous cameras belonging to commercial partners. The nature of optical navigation means that cameras must be well-calibrated and their attitude well understood to provide high accuracy bearing measurements to the navigation filter. The stringent accuracy requirements for Orion could not have been met using traditional checkerboard camera calibration or by simply relying on design drawings. This paper details the hardware, software, techniques, and algorithms used by the EOL team to achieve this level of accuracy.

Paul D Mckee↗

NASA NTRSDate not supplied

Camera Calibration and Alignment Metrology at Johnson Space Center’s Electro-Optics Laboratory

Paul McKee↗

DOE OSTI2025

Standardized nomenclature for photovoltaic connectors

Photovoltaic (PV) systems rely on discrete connectors for the efficient and safe flow of power from module to module and from strings to combiner boxes and inverters. Despite their functional importance, no common nomenclature for PV connectors currently exists, resulting in confusion and miscommunication. Misunderstood terms like "MC4 compatible", "cross-mating", "intermating", "female", and "male" can lead to installation and maintenance errors and compromise system reliability. We believe a standardized terminology will reduce confusion, help support installation best practices, aid in maintenance and repair, inform next-generation designs, and provide a technical basis for improved codes and standards. To that end, we are proposing a standardized glossary for 4 mm PV connectors (the most common type of connector used in PV applications) based on, and validated by, a Sandia National Laboratories' investigation that included the following sources: 1) a comprehensive review of official documents from 20 connector manufacturers, including schematics, datasheets, installation manuals, and catalogs, as well as relevant patents; 2) two rounds of surveys distributed to stakeholders, including connector manufacturers, engineers, asset owners, test labs, and researchers; and 3) visual examination of 25 different models of 4 mm single-pole DC PV connectors to document variations in design and functionality. This work provides a foundation for establishing a clear and consistent terminology for PV connectors that will in turn enable progress toward greater reliability and collaboration across the industry.

14 SOLAR ENERGY↗

NASA NTRS1993

Martian particle size based on thermal inertia corrected for elevation-dependent atmospheric properties

Thermal inertia is commonly used to derive physical properties of the Martian surface. If the surface is composed of loosely consolidated grains, then the thermal conductivity derived from the inertia can theoretically be used to compute the particle size. However, one persistent difficulty associated with the interpretation of thermal inertia and the derivation of particle size from it has been the degree to which atmospheric properties affect both the radiation balance at the surface and the gas conductivity. These factors vary with atmospheric pressure so that derived thermal inertias and particle sizes are a function of elevation. By utilizing currently available thermal models and laboratory information, a fine component thermal inertia map was convolved with digital topography to produce particle size maps of the Martian surface corrected for these elevation-dependent effects. Such an approach is especially applicable for the highest elevations on Mars, where atmospheric back radiation and gas conductivity are low.

Bridges, N. T.↗

DOE OSTI2025

Learning robust parameter inference and density reconstruction in flyer plate impact experiments

Estimating physical parameters or material properties from experimental observations is a common objective in many areas of physics and material science. In many experiments, especially in shock physics, radiography is the primary means of observing the system of interest. However, radiography does not provide direct access to key state variables, such as density, which prevents the application of traditional parameter estimation approaches. Here we focus on flyer plate impact experiments on porous materials, and resolving the underlying parameterized equation of state (EoS) and crush porosity model parameters given radiographic observation(s). We use machine learning as a tool to demonstrate with high confidence that using only high impact velocity data does not provide sufficient information to accurately infer both EoS and crush model parameters, even with fully resolved density fields or a dynamic sequence of images. We thus propose an observable data set consisting of low and high impact velocity experiments/simulations that capture different regimes of compaction and shock propagation, and proceed to introduce a generative machine learning approach which produces a posterior distribution of physical parameters directly from radiographs. We demonstrate the effectiveness of the approach in estimating parameters from simulated flyer plate impact experiments, and show that the obtained estimates of EoS and crush model parameters can then be used in hydrodynamic simulations to obtain accurate and physically admissible density reconstructions. Finally, we examine the robustness of the approach to model mismatches, and find that the learned approach can provide useful parameter estimates in the presence of out-of-distribution radiographic noise and previously unseen physics, thereby promoting a potential breakthrough in estimating material properties from experimental radiographic images.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Three interaction energy scales in the single-layer high-$T_c$ cuprate HgBa 2 CuO 4+δ

The lamellar cuprate superconductors exhibit the highest ambient-pressure superconducting transition temperatures ($T_c$), and after more than three decades of extraordinary research activity, continue to pose formidable scientific challenges. A major experimental obstacle has been to distinguish universal phenomena from materials- or technique-dependent ones. Angle-resolved photoemission spectroscopy (ARPES) measures momentum-dependent single-particle electronic excitations and has been invaluable in the endeavor to determine the anisotropic momentum-space properties of the cuprates. HgBa 2 CuO 4+δ (Hg1201) is a single-CuO 2 -layer cuprate with a particularly high optimal Tc and a simple crystal structure, yet there exists little information from ARPES about the electronic properties of this model system. In this paper we present an ARPES study of doping-, temperature-, and momentum-dependent systematics of near-nodal dispersion anomalies in Hg1201. The data reveal a hierarchy of three distinct energy scales: a subgap low-energy kink, an intermediate-energy kink near 55 meV, and a peak-dip-hump structure. The first two features are attributed to the coupling of electrons to Ba-derived optical phonons and in-plane bond-stretching phonons, respectively. The nodal peak-dip-hump structure appears to have a common doping dependence in several single-layer cuprates and is interpreted as a manifestation of pseudogap physics at the node. These results establish several universal phenomena, both in terms of connecting multiple experimental techniques for a single material and in terms of connecting comparable spectral features in multiple structurally similar cuprates.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Development of an Assessment Methodology That Enables the Nuclear Industry to Evaluate Adoption of Advanced Automation

Nuclear power has a crucial role in providing safe, reliable, and economical carbon-free electricity for today and the future. For continued operation, many of the existing United States nuclear power plants will begin the subsequent license renewal process for extending their operating license periods. As plants extend their expected operating lifetimes, there is a significant opportunity to modernize. These plants have a much stronger business case with these extended mission periods to modernize and significantly enhance their economic viability in current and future energy markets by implementing digital technologies that support innovation, efficiency gains, and business-model transformation. Ensuring continued safety and reliability is crucial. Transformative digital technologies—including automation—that fundamentally change the concept of operation for the nuclear power plant operating model requires a critical focus on the human and technology integration element. Further, the nuclear industry has historically been reluctant to modernize due to having a risk adverse culture and lack of clarity for a transformative new state vision (Joe & Remer, 2019; Thomas et al., 2020). Common barriers include (1) the perceived value and return on investment (ROI) of digital technology, (2) the perceived risk associated with licensing, regulatory, and cybersecurity, and (3) insufficient guidance for performing digital modifications to power generation systems. This work presents a methodology to address these barriers and support the industry in adopting advanced automation and digital technology through developing a transformative vision and implementation strategy that will address the human and technology integration element. This research leverages previous LWRS Program and industry results. It draws specifically on previous LWRS Program research in the areas of advanced alarm systems, computer-based procedures, model informed decision support, and advanced human-system interface displays (e.g., overviews and task-based). The modernization methodology can be used to guide transformative thinking when integrating a set of vendor-specific capabilities to support a new concept of operations and a utility’s end-state vision. The results of this research are organized into six major sections: - Section 1 introduces the need for supporting large-scale digital modifications that will renew the technology base for extended operating life beyond 60 years - Section 2 describes the challenges that the nuclear industry is enduring with modernizing. - Section 3 summarizes the primary standards and guidance. - Section 4 presents earlier work from the LWRS Program regarding the development of a transformative conceptual design for an advanced control room of a hybrid plants. - Section 5 presents a methodology that is designed at addressing the challenges in the industry today in achieving a transformative new state vision and concept of operations. - Conclusions and next steps of this research are provided in Section 6.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRSDate not supplied

Extending CF Conventions to Enhance Data FAIRness for Atmospheric Composition Observations

The Hierarchical Data Format (HDF) and Network Common Data Form (NetCDF) are data file formats created to aid users in the creation or use of scientific data. These file formats are useful for handling large data volumes and hosting extensive metadata as global, group, or variable attributes and are popular with the modeling community. HDF and NetCDF files are widely used with atmospheric remote sensing data and have been used to support measurements from numerous field campaigns, from satellite to aircraft or ground and mobile based measurements. The files from airborne field studies, however, vary greatly in terms of the file structure and the amount and content of their metadata. Information relevant to the file that can be useful to the user such as the data producer, location where data was taken, variable descriptions, or information about the instrument might not be included in the file. Recently, the Measurements of Aerosols, Clouds, and their Interactions for Earth System Models (MACIE) group started a grassroots effort to develop a CF-based template for the HDF and NetCDF files for field studies, with the aim of making the data products more interoperable and usable. This template seeks to make the files more compliant to Climate and Forecast (CF) metadata conventions and to standardize the file structure and the global and variable attributes. The template would help to ensure that HDF and NetCDF files contain adequate metadata to better support their use for research, e.g., the modeling community, and to enhance the usability and interoperability of data for research communities at large. The draft template has been applied to recent field studies for various instruments and their merge files in support of the Atmosphere Observing System (AOS) project. The details of the revised template are to be presented, as well as examples of the implementation of these requirements for merge files and lidar observation data files and issues revealed during the implementation process.

Sean Leavor↗

DOE OSTI2020

System-level performance and degradation of 21 GWDC of utility-scale PV plants in the United States

We assess the performance of a fleet of 411 utility-scale (i.e., >5 MWAC and ground-mounted) photovoltaic (PV) projects totaling 21.1 GWDC (16.3 GWAC) of capacity, which achieved commercial operations in the United States from 2007 to 2016. This fleet of projects contributed more than 50% of all solar electricity generated in the United States in 2017. Using detailed information on individual project characteristics, in conjunction with modeled irradiance data, we assess the extent to which actual first-year performance has lived up to both modeled and stated expectations. We then analyze system-level performance degradation in subsequent years by employing a “fixed effects” regression model to statistically isolate the impact of age on system performance. We find that this fleet of utility-scale PV projects has generally lived up to ex ante expectations for first-year performance but that subsequent system-level degradation—found to be −1.3%/year (±0.2%)—has, on average, been worse than both ex ante expectations (commonly −0.5%/year) and results from past studies (ranging from −0.8%/year to −1.0%/year). We emphasize that −1.3%/year is a system-level estimate that captures more than just module degradation (e.g., including soiling, balance of plant degradation, and downtime for maintenance and/or other events). A side analysis of a variety of project characteristics suggests that system-level degradation rates tend to be of lower magnitude among newer projects and larger projects and at sites with lower long-term average temperatures.

14 SOLAR ENERGY↗

DOE OSTI2025

OC7 Phase I Definition Document

The Offshore Code Comparison Collaboration 7 (OC7) project is organized under the International Energy Agency Wind Technology Collaboration Programme Task 56 with an objective to evaluate and enhance the predictive accuracy of engineering-level modeling tools used in the design of offshore wind energy systems. Phase I of OC7 is focused on improving the models and modeling practices of hydrodynamic viscous loads on floating offshore wind turbine platforms. In alignment with this goal, Work Package 1.1 of OC7 Phase I is formulated to investigate the modeling of hydrodynamic viscous loads on several different geometric components commonly encountered with floating offshore wind platform designs, including cylindrical columns, heave plates, and rectangular pontoons. Work Package 1.1 also explores the dependence of hydrodynamic coefficients on the sea state to drive toward practical guidance on how these coefficients can be selected or adjusted for different conditions. This report outlines the motivation and objectives behind each subphase of OC7 Phase I, along with the necessary technical specifications and load case definitions to guide the project participants. It also serves as an important part of the project documentation for future modelers who would like to reproduce this work or make use of the data and information generated from the OC7 project.

17 WIND ENERGY↗

NASA NTRS1990

Triplets of galaxies: Their dynamics, evolution, and the origin of chaos in them

Recently Karachentsev's group at The Smithsonian Astrophysical Observatory (SAO) (6-meter Telescope Observatory) published a list of 84 triple systems of galaxies with their distances, radial (line of sight) velocities, and angular sizes (Karachentseva et al., 1988). This gives a new ground for studies of the dark matter problem which fills the gap between the large cosmic scales (White, 1987; Dekel and Rees, 1987, and Einasto et al., 1977) and the scale of individual galaxies (Erickson et al., 1987). The data on the typical velocity dispersions and linear dimension of the triplets indicate that they contain considerable amounts of dark matter (see also earlier work of Karachentseva et al., 1979). Numerical simulations show that the statistical characteristics of the Karachentsev triplets can be imitated by model ensembles of triple systems with dark matter masses M sub d = (1-3 x 10(exp 12) M sub O, which is almost ten times greater than the typical mass of stellar galaxies estimated by the standard mass-to-luminosity ration (Kiseleva and Chernin, 1988). Here, the authors report that important information can be drawn from the data on the visible configurations of these systems. The statistics of configurations provide an independent evidence for dark matter in the triplets; moreover, it enables one to argue that dark matter seems to be distributed over the whole volume of the typical triplet forming its common corona rather than concentrated within individual coronae (or haloes) of the member galaxies.

Chernin, Arthur D.↗

NASA NTRS2004

Parameter Estimation in Atmospheric Data Sets

In this study the structure tensor technique is used to estimate dynamical parameters in atmospheric data sets. The structure tensor is a common tool for estimating motion in image sequences. This technique can be extended to estimate other dynamical parameters such as diffusion constants or exponential decay rates. A general mathematical framework was developed for the direct estimation of the physical parameters that govern the underlying processes from image sequences. This estimation technique can be adapted to the specific physical problem under investigation, so it can be used in a variety of applications in trace gas, aerosol, and cloud remote sensing. As a test scenario this technique will be applied to modeled dust data. In this case vertically integrated dust concentrations were used to derive wind information. Those results can be compared to the wind vector fields which served as input to the model. Based on this analysis, a method to compute atmospheric data parameter fields will be presented. .

Wenig, Mark↗

NASA NTRS2015

Comparative Analysis of Static and Dynamic Probabilistic Risk Assessment

This study examines three different methodologies for producing loss-of-mission (LOM) and loss-of-crew (LOC) risks estimates for probabilistic risk assessments (PRA) of crewed spacecraft. The three bottom-up, component-based PRA approaches examined are a traditional static fault tree, a dynamic Monte Carlo simulation, and a fault tree hybrid that incorporates some dynamic elements. These approaches were used to model the reaction control system thruster pod of a generic crewed spacecraft and mission, and a comparative analysis of the methods is presented. The methodologies are assessed in terms of the process of modeling a system, the actionable information produced for the design team, and the overall fidelity of the quantitative risk evaluation generated. The system modeling process is compared in terms of the effort required to generate the initial model, update the model in response to design changes, and support mass-versus-risk trade studies. The results are compared by examining the top-level LOM/LOC estimates and the relative risk driver rankings at the failure mode level. The fidelity of each modeling methodology is discussed in terms of its capability to handle real-world system dynamics such as cold-sparing, changes in mission operations due to loss of redundancy, and common cause failure modes. The paper also discusses the applicability of each methodology to different phases of system development and shows that a single methodology may not be suitable for all of the many purposes of a spacecraft PRA. The fault tree hybrid approach is shown to be best suited to the needs of early assessments during conceptual design phases. As the design begins to mature, the level of detail represented in the risk model must go beyond redundancy and nominal mission operations to include dynamic, time- and state-dependent system responses as well as diverse system capabilities. This is best accomplished using the dynamic simulation approach, since these phenomena are not easily captured by static methods. Ultimately, once the design has been finalized and the goal of the PRA is to provide design validation and requirement verification, more traditional, static fault tree approaches may become as appropriate as the simulation method.

Mattenberger, Christopher J.↗

NASA NTRSDate not supplied

NASA Life Sciences Portal (NLSP): Supporting Scientific Transparency and Reproducibility

NASA’s Life Sciences Ports (NLSP) serves the scientific community by providing curated data from space life science experiment. The Human Research Program (HRP) with the help of NLSP is currently transforming their life sciences data archive systems and processes to improve compliance with the FAIR principles [1]. Some of these improvements will at the same time support the twin pillars of Open Science [2]: transparency of methods and reproducibility of results. Scientific transparency is marked by the easily intelligible communication of what has been investigated: what were the procedures for collecting sample and the characteristics of samples collected? what kinds of measurements were made, what were the environmental conditions of the measurements? What were the analysis techniques of the collected data? Reproducibility of the results and findings from the investigation requires a high level of transparency for all but the simplest investigations; the slightest deviation in communicating and replicating complex experimental procedures or data analyses can often yield quite different data and even findings, thwarting their validation. One of the ways the NLSP is aiming to improve the communication of scientific information is through the use of ontology-driven metadata. Ontologies are powerful, graph-based knowledge representation structures, which can be leveraged to increase data interoperability, the area of the FAIR principles in which many data systems most lack compliance. Over the past decade, there has been a concerted effort in the biomedical community to develop modular and narrowly focused domain and application-specific ontologies in a common, open-source framework, the Open Biological and Biomedical Ontology (OBO) Foundry [3]. The open sharing and modular nature of this effort promises huge increases in harmonized data sharing for systems that leverage these models. Which is in line with the FAIR Data Principles of Findability, Accessibility, Interoperability, and Reuse for scientific data management and stewardship. 1. Wilkinson, M.D., et al., The FAIR Guiding Principles for scientific data management and stewardship. Sci Data, 2016. 3: p. 160018. 2. National Academies of Sciences, E. and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. 2018, Washington, DC: The National Academies Press. 232. 3. Smith, B., et al., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol, 2007. 25(11): p. 1251-5.

Life Sciences data↗