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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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The interdisciplinary role of space geodesy; Proceedings of the International Workshop, Erice, Italy, July 23-29, 1988

The current status of space geodesy and research plans for the 1990s are discussed in reviews and reports. Sections are devoted to the short-term and long-term dynamics of the solid earth, interactions between space geodesy and other disciplines and programs (geodynamics, earth structure, ocean physics, atmosphere and climate, planetary science, and fundamental physics), instrumentation, data analysis, reference coordinate systems, and education. Also provided are overviews of the French, ESA, and NASA geodetic research programs and descriptions of the Soviet Glonass navigation satellites, the WEGENER/MEDLAS observation program, and the Lageos II laser-ranging satellites. Diagrams, graphs, maps, and tables of numerical data are provided.

Mueller, Ivan I.

National Space Science Data Center and World Data Center A for Rockets and Satellites - Ionospheric data holdings and services

The activities and services of the National Space Science data Center (NSSDC) and the World Data Center A for Rockets and Satellites (WDC-A-R and S) are described with special emphasis on ionospheric physics. The present catalog/archive system is explained and future developments are indicated. In addition to the basic data acquisition, archiving, and dissemination functions, ongoing activities include the Central Online Data Directory (CODD), the Coordinated Data Analysis Workshopps (CDAW), the Space Physics Analysis Network (SPAN), advanced data management systems (CD/DIS, NCDS, PLDS), and publication of the NSSDC News, the SPACEWARN Bulletin, and several NSSD reports.

Bilitza, D.

Combining Data with Physical Knowledge for Uncertainty Quantification in Certification and Reliability Analysis

Unifying empirical data with predictive models can enable engineering cost-savings through certification by analysis and reliability-based design. Both concepts require rigorous uncertainty quantification (UQ) and robust understanding and treatment of relevant physics. Combining sampling-based UQ algorithms with high-fidelity simulations creates a computational bottleneck that is often alleviated through the use of machine learning (ML). ML can be used to create computationally efficient surrogates for simulations of complex or high-dimensional physical interactions (e.g., multi-phase interactions associated with melt pools in laser powder bed fusion or spatially-dependent material properties in functionally graded materials). However, negative side effects of ML may include a lack of interpretability and negative correlation between event rarity and simulation accuracy due to a lack of training data. As such, it is important to infuse ML algorithms with physics-based guardrails to provide confidence in their predictions. This talk will provide a brief review of recent NASA research at this intersection of physics-based simulation, ML, and UQ with a focus on certification and reliability analysis.

uncertainty quantification

Physics-guided dual implicit neural representations for source separation

Significant challenges exist in efficient data analysis of most advanced experimental and observational techniques because the collected signals often include unwanted contributions, such as background and signal distortions, that can obscure the physically relevant information of interest. To address this, we have developed a self-supervised machine-learning approach for source separation using a dual implicit neural representation framework that jointly trains two neural networks: one for approximating distortions of the physical signal of interest and the other for learning the effective background contribution. Our method learns directly from the raw data by minimizing a reconstruction-based loss function without requiring labeled data or pre-defined dictionaries. We demonstrate the effectiveness of our framework by considering a challenging case study involving large-scale simulated, as well as experimental, momentum-energy-dependent inelastic neutron scattering data in a four-dimensional parameter space, characterized by heterogeneous background contributions and unknown distortions to the target signal. The method is found to successfully separate physically meaningful signals from a complex or structured background even when the signal characteristics vary across all four dimensions of the parameter space. An analytical approach that informs the choice of the regularization parameter is presented. Our method offers a versatile framework for addressing source separation problems across diverse domains, ranging from superimposed signals in astronomical measurements to structural features in biomedical image reconstructions.

47 OTHER INSTRUMENTATION

From minimum-viable-products to full models: a step-wise development of diagnostic forward models in support of design, analysis and modelling on the ST40 tokamak

Like most magnetic confined fusion experiments, the ST40 tokamak started off with a small subset of diagnostics and gradually increased the diagnostic set to include more complex and comprehensive systems. To make the most of each operational phase, forward models of various diagnostics are used and developed to aid design, provide consistency-checks during commissioning, test analysis methods, and build workflows to constrain high-level parameters to inform interpretation, theory and modelling. For new models and new analysis workflows, minimum-viable-products are released early, and their complexity is increased in a step-wise manner, facilitating the support of all programme phases on multiple parallel applications, while enabling learning opportunities and feedback loops. In this contribution we review the philosophy, scope and architecture of the framework under development. We discuss the details of some forward models, with examples on how they are used to aid diagnostic design, to investigate analysis methodologies through synthetic data, and how they are embedded in experimental analysis workflows. We compare previously published experimental results with new, more advanced analysis workflows employing more recent, detailed models and new diagnostic data, providing confirmation of the published material from the 2021–22 experimental campaign.

integrated data analysis

An Integrated Data Analytics Platform

An Integrated Science Data Analytics Platform is an environment that enables the confluence of resources for scientific investigation. It harmonizes data, tools and computational resources which subsequently enable the research community to focus on the investigation rather than spending time on security, data preparation, management, etc. OceanWorks is a NASA technology integration project to establish a cloud-based Integrated Ocean Science Data Analytics Platform at NASA’s Physical Oceanography Distributed Active Archive Center (PO.DAAC) for big ocean science. It focuses on advancement and maturity by bringing together several NASA open-source, big data projects for parallel analytics, anomaly detection, in-situ to satellite data matchup, quality-screened data subsetting, search relevancy, and data discovery. Our communities are relying on data distributed through data centers such as the PO.DAAC, COAPS, NCAR, and many others to conduct their research. In typical investigations, scientists would engage in: search for data, evaluate the relevance of that data, download it, and then apply algorithms to identify trends. Such workflow cannot scale if the research involves a massive amount of data or multi-variate measurements. NASA’s Surface Water and Ocean Topography (SWOT) mission is expected to produce massive amount of observational data during its 3-year nominal mission. Collections like SWOT challenges all existing Earth Science data archival, distribution and analysis paradigms. In this paper, we will discuss how OceanWorks enhances the analysis of physical ocean data where the computation is done on an elastic cloud platform next to the archive to deliver fast, web-accessible services for working with oceanographic measurements.

Yang, Chaowei

The GLAS physical inversion method for analysis of HIRS2/MSU sounding data

Goddard Laboratory for Atmospheric Sciences has developed a method to derive atmospheric temperature profiles, sea or land surface temperatures, sea ice extent and snow cover, and cloud heights and fractional cloud, from HIRS2/MSU radiance data. Chapter 1 describes the physics used in the radiative transfer calculations and demonstrates the accuracy of the calculations. Chapter 2 describes the rapid transmittance algorithm used and demonstrates its accuracy. Chapter 3 describes the theory and application of the techniques used to analyze the satellite data. Chapter 4 shows results obtained for January 1979.

Susskind, J.

GaAs solar cell photoresponse modeling using PC-1D V2.1

Photoresponse data of high efficiency GaAs solar cells were analyzed using PC-1D V2.1. The approach required to use PC-1D for photoresponse data analysis, and the physical insights gained from performing the analysis are discussed. In particular, the effect of Al(x)Ga(1-x)As heteroface quality was modeled. Photoresponse or spectral quantum efficiency is an important tool in characterizing material quality and predicting cell performance. The strength of the photoresponse measurement lies in the ability to precisely fit the experimental data with a physical model. PC-1D provides a flexible platform for calculations based on these physical models.

Huber, D. A.

Results of a joint NOAA/NASA sounder simulation study

This paper presents the results of a joint NOAA and NASA sounder simulation study in which the accuracies of atmospheric temperature profiles and surface skin temperature measuremnents retrieved from two sounders were compared: (1) the currently used IR temperature sounder HIRS2 (High-resolution Infrared Radiation Sounder 2); and (2) the recently proposed high-spectral-resolution IR sounder AMTS (Advanced Moisture and Temperature Sounder). Simulations were conducted for both clear and partial cloud conditions. Data were analyzed at NASA using a physical inversion technique and at NOAA using a statistical technique. Results show significant improvement of AMTS compared to HIRS2 for both clear and cloudy conditions. The improvements are indicated by both methods of data analysis, but the physical retrievals outperform the statistical retrievals.

Phillips, N.

Laser fringe anemometry for aero engine components

Advances in flow measurement techniques in turbomachinery continue to be paced by the need to obtain detailed data for use in validating numerical predictions of the flowfield and for use in the development of empirical models for those flow features which cannot be readily modelled numerically. The use of laser anemometry in turbomachinery research has grown over the last 14 years in response to these needs. Based on past applications and current developments, this paper reviews the key issues which are involved when considering the application of laser anemometry to the measurement of turbomachinery flowfields. Aspects of laser fringe anemometer optical design which are applicable to turbomachinery research are briefly reviewed. Application problems which are common to both laser fringe anemometry (LFA) and laser transit anemometry (LTA) such as seed particle injection, optical access to the flowfield, and measurement of rotor rotational position are covered. The efficiency of various data acquisition schemes is analyzed and issues related to data integrity and error estimation are addressed. Real-time data analysis techniques aimed at capturing flow physics in real time are discussed. Finally, data reduction and analysis techniques are discussed and illustrated using examples taken from several LFA turbomachinery applications.

Strazisar, A. J.

Laser fringe anemometry for aero engine components

Advances in flow measurement techniques in turbomachinery continue to be paced by the need to obtain detailed data for use in validating numerical predictions of the flowfield and for use in the development of empirical models for those flow features which cannot be readily modelled numerically. The use of laser anemometry in turbomachinery research has grown over the last 14 years in response to these needs. Based on past applications and current developments, the key issues which are involved when considering the application of laser anemometry to the measurement of turbomachinery flowfields are discussed. Aspects of laser fringe anemometer optical design which are applicable to turbomachinery research are briefly reviewed. Application problems which are common to both laser fringe anemometry (LFA) and laser transit anemometry (LTA) such as seed particle injection, optical access to the flowfield, and measurement of rotor rotational position are covered. The efficiency of various data acquisition schemes is analyzed and issues related to data integrity and error estimation are addressed. Real-time data analysis techniques aimed at capturing flow physics in real time are discussed. Finally, data reduction and analysis techniques are discussed and illustrated using examples taken from several LFA turbomachinery applications.

Strazisar, Anthony J.

The GLAS physical inversion method for analysis of TIROS N data

The Goddard Laboratory for Atmospheric Sciences approach to temperature sounding from satellite observations is fundamentally different from that of NESS in that heavy reliance is placed on the ability to model accurately the instrumental response to atmospheric and surface conditions, while no use is made of statistical relationships between satellite observations and atmospheric temperature profiles. The method involves starting with a guess set of atmospheric and surface conditions from which expected brightness temperatures for the satellite observations are computed. Then, iterative relaxation of atmospheric and surface conditions is performed according to the difference between observed and computed brightness temperatures until sufficient agreement is reached. In the absence of sufficient agreement, no retrieval is produced for that location.

Susskind, J.

Hiding in plain sight: The prevalence and impact of trions and Fermi polarons in transient absorption spectroscopy experiments of 2D semiconductors

Transient absorption (TA) spectroscopy is one of the most popular experimental methods to measure the excited state lifetimes and charge carrier recombination mechanisms in two dimensional (2D) semiconductors. This fundamental information is essential for designing and optimizing the next generation of ultrathin and lightweight 2D semiconductor-based optoelectronic devices. However, the interpretation of TA spectroscopy data varies across the community. The community lacks a unifying physical explanation for how and why experimental variables such as incident light intensity, sample-substrate interactions, and/or applied bias affect TA spectral data. This Perspective (1) compares the physical chemistry TA literature to nanomaterial physics literature from a historical perspective, (2) reviews multiple physical explanations that the TA community developed to explain spectral features and experimental trends, (3) provides a unifying explanation for how and why trions—and, more generally, Fermi polarons—contribute to TA spectra, and (4) quantifies the extent to which various physical interpretations and data analysis procedures yield different timescales and mechanisms for the same set of experimental results. We highlight the importance of considering trions/Fermi polarons in TA measurements and their implications for advancing our understanding of 2D material properties.

2D materials

Data and Modeling of Dendrites Subject to A Step Change in Pressure (TDSE)

There is considerable interest in dendritic solidification because of the influence dendrites have in the determination of microstructure, and thereby in the physical properties of cast metals and alloys. Current theories and models of dendritic growth generally couple diffusion effects in the melt with the physics of the interface. Data and subsequent analysis prior of the tip growth speed and radii of thermal succinonitrile dendrites in the near-convection free, on-orbit, free-fall environment demonstrate that these theories yield predictions that are reasonably in agreement with the results of experiment. However, data and analysis for assessing the interfacial physics component of theory are not sufficiently detailed or definitive. To study fundamental aspects of dendritic interface stability, we are measuring and modeling the kinetics and morphology of dendrites as they evolve from one well-defined steady state at a pre-set supercooling, through a transient stage, to a different well-defined steady state. More specifically, we subject succinonitrile dendrites, growing under steady-state conditions, to a rapid change in pressure. This leads to a rapid change in thermal driving force from the corresponding change in both the equilibrium melting temperature due to the Clapeyron effect, and a change in the far-field temperature due to adiabatic temperature changes in the bulk liquid and solid. Subsequently, we observe transformations from a well-characterized initial state into a new steady-state. Initial data reveal that the dendrite tip velocity changes almost as fast as the pressure charges, while the tip radius changes occur more slowly, taking from 10 60 seconds depending on the size of the step change and the final supercooling. Computer modeling of this process shows both agreements and disagreements with the experimental data. In making these observations and measurements, we are gaining new understandings of interfacial dynamics and state-selection physics.

Koss, Matthew B.

Plant canopy transpiration in bioregenerative life support systems - The link between mechanistic and empirical models

A model of water transpiration in a plant canopy that combines two approaches is presented. The first approach is to account for underlying physical processes, while the second is to empirically incorporate transpiration data now being generated at the Johnson Center Variable Pressure Growth Chamber. The two approaches, physical modeling and data analysis, make it possible to produce a model that is more robust than either the standard first-principles model or a straightforward empirical model. It is shown that the present transpiration model is able to efficiently capture the dynamic behavior of the plant canopy over the entire range of environmental parameters now envisioned to be important in an operating controlled ecological life support system (CELSS). Examples of the use of this model in assessing plant canopy dynamics and CELSS design options are also presented.

Sirko, Robert J.

Analysis of the Radiated Field in an Electromagnetic Reverberation Chamber as an Upset-Inducing Stimulus for Digital Systems

Preliminary data analysis for a physical fault injection experiment of a digital system exposed to High Intensity Radiated Fields (HIRF) in an electromagnetic reverberation chamber suggests a direct causal relation between the time profile of the field strength amplitude in the chamber and the severity of observed effects at the outputs of the radiated system. This report presents an analysis of the field strength modulation induced by the movement of the field stirrers in the reverberation chamber. The analysis is framed as a characterization of the discrete features of the field strength waveform responsible for the faults experienced by a radiated digital system. The results presented here will serve as a basis to refine the approach for a detailed analysis of HIRF-induced upsets observed during the radiation experiment. This work offers a novel perspective into the use of an electromagnetic reverberation chamber to generate upset-inducing stimuli for the study of fault effects in digital systems.

Torres-Pomales, Wilfredo