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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Development of Waypoint Planning Tool in Response to NASA Field Campaign Challenges

Airborne real time observations are a major component of NASA's Earth Science research and satellite ground validation studies. For mission scientists, planning a research aircraft mission within the context of meeting the science objectives is a complex task because it requires real time situational awareness of the weather conditions that affect the aircraft track. Multiple aircrafts are often involved in NASA field campaigns. The coordination of the aircrafts with satellite overpasses, other airplanes and the constantly evolving, dynamic weather conditions often determines the success of the campaign. A flight planning tool is needed to provide situational awareness information to the mission scientists, and help them plan and modify the flight tracks. Scientists at the University of Alabama-Huntsville and the NASA Marshall Space Flight Center developed the Waypoint Planning Tool, an interactive software tool that enables scientists to develop their own flight plans (also known as waypoints) with point -and-click mouse capabilities on a digital map filled with real time raster and vector data. The development of this Waypoint Planning Tool demonstrates the significance of mission support in responding to the challenges presented during NASA field campaigns. Analysis during and after each campaign helped identify both issues and new requirements, and initiated the next wave of development. Currently the Waypoint Planning Tool has gone through three rounds of development and analysis processes. The development of this waypoint tool is directly affected by the technology advances on GIS/Mapping technologies. From the standalone Google Earth application and simple KML functionalities, to Google Earth Plugin and Java Web Start/Applet on web platform, and to the rising open source GIS tools with new JavaScript frameworks, the Waypoint Planning Tool has entered its third phase of technology advancement. The newly innovated, cross ]platform, modular designed JavaScript ]controlled Way Point Tool is planned to be integrated with NASA Airborne Science Mission Tool Suite. Adapting new technologies for the Waypoint Planning Tool ensures its success in helping scientists reach their mission objectives. This presentation will discuss the development processes of the Waypoint Planning Tool in responding to field campaign challenges, identify new information technologies, and describe the capabilities and features of the Waypoint Planning Tool with the real time aspect, interactive nature, and the resultant benefits to the airborne science community.

He, Matt↗
DOE OSTI2017

Toward a Visualization-Supported Workflow for Cyber Alert Management using Threat Models and Human-Centered Design

Cyber network analysts follow complex processes in their investigations of potential threats to their network. Much research is dedicated to providing automated tool support in the effort to make their tasks more efficient, accurate, and timely. This tool support comes in a variety of implementations from machine learning algorithms that monitor streams of data to visual analytic environments for exploring rich and noisy data sets. Cyber analysts, however, often speak of a need for tools which help them merge the data they already have and help them establish appropriate baselines against which to compare potential anomalies. Furthermore, existing threat models that cyber analysts regularly use to structure their investigation are not often leveraged in support tools. We report on our work with cyber analysts to understand they analytic process and how one such model, the MITRE ATT&CK Matrix [32], is used to structure their analytic thinking. We present our efforts to map specific data needed by analysts into the threat model to inform our eventual visualization designs. We examine data mapping for gaps where the threat model is under-supported by either data or tools. We discuss these gaps as potential design spaces for future research efforts. We also discuss the design of a prototype tool that combines machine-learning and visualization components to support cyber analysts working with this threat model.

Cyber Security↗
NASA NTRS2012

The Way Point Planning Tool: Real Time Flight Planning for Airborne Science

Airborne real time observation are a major component of NASA's Earth Science research and satellite ground validation studies. For mission scientist, planning a research aircraft mission within the context of meeting the science objective is a complex task because it requires real time situational awareness of the weather conditions that affect the aircraft track. Multiple aircraft are often involved in the NASA field campaigns the coordination of the aircraft with satellite overpasses, other airplanes and the constantly evolving dynamic weather conditions often determine the success of the campaign. A flight planning tool is needed to provide situational awareness information to the mission scientist and help them plan and modify the flight tracks successfully. Scientists at the University of Alabama Huntsville and the NASA Marshal Space Flight Center developed the Waypoint Planning Tool (WPT), an interactive software tool that enables scientist to develop their own flight plans (also known as waypoints), with point and click mouse capabilities on a digital map filled with time raster and vector data. The development of this Waypoint Planning Tool demonstrates the significance of mission support in responding to the challenges presented during NASA field campaigns. Analyses during and after each campaign helped identify both issues and new requirements, initiating the next wave of development. Currently the Waypoint Planning Tool has gone through three rounds of development and analysis processes. The development of this waypoint tool is directly affected by the technology advances on GIS/Mapping technologies. From the standalone Google Earth application and simple KML functionalities to the Google Earth Plugin and Java Web Start/Applet on web platform, as well as to the rising open source GIS tools with new JavaScript frameworks, the Waypoint planning Tool has entered its third phase of technology advancement. The newly innovated, cross-platform, modular designed JavaScript-controled Waypoint tool is planned to be integrated with the NASA Airborne Science Mission Tool Suite. Adapting new technologies for the Waypoint Planning Tool ensures its success in helping scientist reach their mission objectives. This presentation will discuss the development process of the Waypoint Planning Tool in responding to field campaign challenges, identifying new information technologies, and describing the capabilities and features of the Waypoint Planning Tool with the real time aspect, interactive nature, and the resultant benefits to the airborne science community.

He, Yubin↗
DOE OSTI2018

Deep data analysis via physically constrained linear unmixing: universal framework, domain examples, and a community-wide platform

Abstract Many spectral responses in materials science, physics, and chemistry experiments can be characterized as resulting from the superposition of a number of more basic individual spectra. In this context, unmixing is defined as the problem of determining the individual spectra, given measurements of multiple spectra that are spatially resolved across samples, as well as the determination of the corresponding abundance maps indicating the local weighting of each individual spectrum. Matrix factorization is a popular linear unmixing technique that considers that the mixture model between the individual spectra and the spatial maps is linear. Here, we present a tutorial paper targeted at domain scientists to introduce linear unmixing techniques, to facilitate greater understanding of spectroscopic imaging data. We detail a matrix factorization framework that can incorporate different domain information through various parameters of the matrix factorization method. We demonstrate many domain-specific examples to explain the expressivity of the matrix factorization framework and show how the appropriate use of domain-specific constraints such as non-negativity and sum-to-one abundance result in physically meaningful spectral decompositions that are more readily interpretable. Our aim is not only to explain the off-the-shelf available tools, but to add additional constraints when ready-made algorithms are unavailable for the task. All examples use the scalable open source implementation from https://github.com/ramkikannan/nmflibrary that can run from small laptops to supercomputers, creating a user-wide platform for rapid dissemination and adoption across scientific disciplines.

47 OTHER INSTRUMENTATION↗
NASA NTRS2007

Organization's Orderly Interest Exploration: Inception, Development and Insights of AIAA's Topics Database

Since 2003, AIAA's Computer Systems and Software Systems Technical Committees (TCs) have developed a database that aids technical committee management to map technical topics to their members. This Topics/Interest (T/I) database grew out of a collection of charts and spreadsheets maintained by the TCs. Since its inception, the tool has evolved into a multi-dimensional database whose dimensions include the importance, interest and expertise of TC members and whether or not a member and/or a TC is actively involved with the topic. In 2005, the database was expanded to include the TCs in AIAA s Information Systems Group and then expanded further to include all AIAA TCs. It was field tested at an AIAA Technical Activities Committee (TAC) Workshop in early 2006 through live access by over 80 users. Through the use of the topics database, TC and program committee (PC) members can accomplish relevant tasks such as: to identify topic experts (for Aerospace America articles or external contacts), to determine the interest of its members, to identify overlapping topics between diverse TCs and PCs, to guide new member drives and to reveal emerging topics. This paper will describe the origins, inception, initial development, field test and current version of the tool as well as elucidate the benefits and insights gained by using the database to aid the management of various TC functions. Suggestions will be provided to guide future development of the database for the purpose of providing dynamics and system level benefits to AIAA that currently do not exist in any technical organization.

Marshall, Jospeh R.↗
DOE OSTI2019

EGS Collab Earth Modeling: Integrated 3D Model of the Testbed

The EGS Collab project is conducting a series of stimulation and interwell flow tests in an intermediate scale (~10-20 m) testbed located on the 4850 level in the Sanford Underground Research Facility (SURF) in Lead, South Dakota. The testbed consists of eight ~200 ft (~60 m) HQ-diameter (9.6 cm) boreholes that are drilled into the Poorman Formation from the western rib of the West Access Drift. Of the eight boreholes, one borehole is used as an injection/stimulation well, another sub-parallel borehole located about 10 m away from the injection well is used as a production well, and rest of the other boreholes are used as monitoring wells. For 3D visualization of the testbed as well as to provide spatially accurate and consistent parameter data for geomechanical and geophysical process modeling tasks, we are using Leapfrog Software (Seequent Limited). For analysis of fractures and creation of conditioned stochastic discrete fracture network (CS-DFN) model of the testbed, we are using FracMan (Golder Associates Inc.). As of mid-May 2019, the EGS Collab Leapfrog database contains the general layout of the drifts/shafts at the 4850 and 4100 levels; generalized geologic framework model of a domain that spans both the 4850 and 4100 levels; the CS-DFN of the testbed; and layouts of the EGS Collab testbed boreholes, kISMET testbed boreholes, and other existing boreholes at the 4850 level. This information has been obtained from the SURF Vulcan database, detailed laser scan and point surveys of borehole collar locations, directional surveys of borehole trajectories, and mapping of features in the drifts, boreholes, and cores. Similarly, other types of data that have been incorporated into the Leapfrog database include static features of the testbed such as natural discontinuities (e.g., fractures, weeps), location of monitoring instruments, and stimulation notches. Baseline geophysical characterization results (e.g., seismic, ERT, temperature, etc.) are also imported into the Leapfrog database. The location and size of packers, various point-source signals detected during stimulation and flow tests (e.g., temperature anomalies, micro-earthquake events, etc.) are also compiled in the database. All feature locations are reported using the local Homestake Mine coordinate system. In this paper, we present some of the geostructural characteristics as well as the status of the testbed as represented by Leapfrog/FracMan database/visualizations.

15 GEOTHERMAL ENERGY↗
NASA NTRS1990

Acquisition plan for Digital Document Storage (DDS) prototype system

NASA Headquarters maintains a continuing interest in and commitment to exploring the use of new technology to support productivity improvements in meeting service requirements tasked to the NASA Scientific and Technical Information (STI) Facility, and to support cost effective approaches to the development and delivery of enhanced levels of service provided by the STI Facility. The DDS project has been pursued with this interest and commitment in mind. It is believed that DDS will provide improved archival blowback quality and service for ad hoc requests for paper copies of documents archived and serviced centrally at the STI Facility. It will also develop an operating capability to scan, digitize, store, and reproduce paper copies of 5000 NASA technical reports archived annually at the STI Facility and serviced to the user community. Additionally, it will provide NASA Headquarters and field installations with on-demand, remote, electronic retrieval of digitized, bilevel, bit mapped report images along with branched, nonsequential retrieval of report subparts.

Source record↗
NASA NTRSDate not supplied

Human-AI Collaboration Among Engineering and Design Professionals: Three Strategies of Generative AI Use

Designers are increasingly using Generative Artificial Intelligence (GenAI) in design processes; however, knowing how designers use GenAI--especially in professional design practice--is under-explored. This paper presents an ethnographic study of a design team at NASA that explores the natural variation of GenAI use across team members during a speculative design workflow. We aimed to uncover when, how, and why GenAI tools were or were not employed using ethnographic observations to map the team's speculative design process and follow-up interviews to provide deeper insights into team members' interactions (or lackthereof) with GenAI. Through inductive qualitative coding, our analysis revealed three strategies of GenAI use observed among professional engineers and designers--intimate co-design with GenAI, selective delegation to GenAI, and minimal use of GenAI--as well as factors that appeared to influence their decisions whether or not to use GenAI. This study proposes new theory in human-AI collaboration that sheds light on the strategies, rationale, and circumstances under which design professionals use GenAI. Future work that builds upon these insights include examining a larger sample size of engineering and design professionals in uncontrolled design process experiences and exploring the impact that design tasks, goals, and constraints have on a participants decision to leverage GenAI tools.

design practice↗
DOE OSTI2024

CIRCLEZ : Reliable photometric redshifts for active galactic nuclei computed solely using photometry from Legacy Survey Imaging for DESI

Photometric redshifts for galaxies hosting an accreting supermassive black hole in their center, known as active galactic nuclei (AGNs), are notoriously challenging. At present, they are most optimally computed via spectral energy distribution (SED) fittings, assuming that deep photometry for many wavelengths is available. However, for AGNs detected from all-sky surveys, the photometry is limited and provided by a range of instruments and studies. This makes the task of homogenizing the data challenging, presenting a dramatic drawback for the millions of AGNs that wide surveys such as SRG/eROSITA are poised to detect. This work aims to compute reliable photometric redshifts for X-ray-detected AGNs using only one dataset that covers a large area: the tenth data release of the Imaging Legacy Survey (LS10) for DESI. LS10 provides deep grizW1-W4 forced photometry within various apertures over the footprint of the eROSITA-DE survey, which avoids issues related to the cross-calibration of surveys. We present the results from CIRCLEZ, a machine-learning algorithm based on a fully connected neural network. CIRCLEZ is built on a training sample of 14 000 X-ray-detected AGNs and utilizes multi-aperture photometry, mapping the light distribution of the sources. The accuracy (σNMAD) and the fraction of outliers (η) reached in a test sample of 2913 AGNs are equal to 0.067 and 11.6%, respectively. The results are comparable to (or even better than) what was previously obtained for the same field, but with much less effort in this instance. We further tested the stability of the results by computing the photometric redshifts for the sources detected in CSC2 and Chandra-COSMOS Legacy, reaching a comparable accuracy as in eFEDS when limiting the magnitude of the counterparts to the depth of LS10. The method can be applied to fainter samples of AGNs using deeper optical data from future surveys (for example, LSST, Euclid), granting LS10-like information on the light distribution beyond the morphological type. Along with this paper, we have released an updated version of the photometric redshifts (including errors and probability distribution functions) for eROSITA/eFEDS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

SECARB-USA: Needs Assessment Framework for Storage Complexes (Task 2.1.b)

A team of SECARB storage experts examined 63 formations at 39 sites that were selected to represent the range of diversity of newly assessed, as well as well-advanced, storage prospects in the SECARB region. We inventoried the data needs triggered by the requirements to obtain a Class VI UIC storage permit, the data needs that results from the requirement to create geocellular fluid flow models to support that permit, and by pragmatic and best practice inputs such as public acceptance, regulatory readiness, and pore space leasing. We anchored both the needs inventory and the processes for and cost of meeting the needs with data from 9 sites in in the SECARB area that have advanced far in characterization. Results show that the total cost of characterization prior to obtaining a permit is convergent, because the permit and modeling requirements drive projects to obtain the same types of data for all cases. The high cost data that control cost are 1) drilling, coring, core-testing, logging, sampling and testing a characterization well and 2) collection of a 3-D seismic survey to map reservoir and confining system properties over the area of the plume or the area of elevated pressure. In 5 of our case study sites we determined that one or both of these costs could be avoided because the needs are met by available data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Automatic log analysis with NLP for the CMS workflow handling

The central Monte-Carlo production of the CMS experiment utilizes the WLCG infrastructure and manages daily thousands of tasks, each up to thousands of jobs. The distributed computing system is bound to sustain a certain rate of failures of various types, which are currently handled by computing operators a posteriori. Within the context of computing operations, and operation intelligence, we propose a Machine Learning technique to learn from the operators with a view to reduce the operational workload and delays. This work is in continuation of CMS work on operation intelligence to try and reach accurate predictions with Machine Learning. We present an approach to consider the log files of the workflows as regular text to leverage modern techniques from Natural Language Processing (NLP). In general, log files contain a substantial amount of text that is not human language. Therefore, different log parsing approaches are studied in order to map the log files’ words to high dimensional vectors. These vectors are then exploited as feature space to train a model that predicts the action that the operator has to take. This approach has the advantage that the information of the log files is extracted automatically and the format of the logs can be arbitrary. In this work the performance of the log file analysis with NLP is presented and compared to previous approaches.

Layer, Lukas↗
NASA NTRS1989

Large liquid rocket engine transient performance simulation system

Phase 1 of the Rocket Engine Transient Simulation (ROCETS) program consists of seven technical tasks: architecture; system requirements; component and submodel requirements; submodel implementation; component implementation; submodel testing and verification; and subsystem testing and verification. These tasks were completed. Phase 2 of ROCETS consists of two technical tasks: Technology Test Bed Engine (TTBE) model data generation; and system testing verification. During this period specific coding of the system processors was begun and the engineering representations of Phase 1 were expanded to produce a simple model of the TTBE. As the code was completed, some minor modifications to the system architecture centering on the global variable common, GLOBVAR, were necessary to increase processor efficiency. The engineering modules completed during Phase 2 are listed: INJTOO - main injector; MCHBOO - main chamber; NOZLOO - nozzle thrust calculations; PBRNOO - preburner; PIPE02 - compressible flow without inertia; PUMPOO - polytropic pump; ROTROO - rotor torque balance/speed derivative; and TURBOO - turbine. Detailed documentation of these modules is in the Appendix. In addition to the engineering modules, several submodules were also completed. These submodules include combustion properties, component performance characteristics (maps), and specific utilities. Specific coding was begun on the system configuration processor. All functions necessary for multiple module operation were completed but the SOLVER implementation is still under development. This system, the Verification Checkout Facility (VCF) allows interactive comparison of module results to store data as well as provides an intermediate checkout of the processor code. After validation using the VCF, the engineering modules and submodules were used to build a simple TTBE.

Mason, J. R.↗
NASA NTRS2021

Colorado Ecological Forecasting: Monitoring Post-fire Cheatgrass (Bromus tectorum) Distribution to Inform Management Planning

Cheatgrass (Bromus tectorum) is a species of concern across the western United States as it has the potential to outcompete native plant species, reduce biodiversity, and diminish nutrient availability for ungulates. Furthermore, because cheatgrass can quickly dominate disturbed landscapes it has the potential to exacerbate wildfire risk by increasing fuel loads. In 2020, the Cameron Peak fire burned more than 200,000 acres on the Arapaho and Roosevelt National Forests in Colorado. These issues are of imminent concern for our partners at the Forest Service (USFS), as they are tasked with wildfire risk and invasive species mitigation. Disturbances such as wildfires can substantially increase the rate and extent of cheatgrass spread. Current cheatgrass mitigation methods rely on field crews to physically locate cheatgrass on the landscape, which takes time, money, and extensive manpower. Here, we developed two Random Forest models within the Software for Assisted Habitat Modeling (SAHM) using remote sensing predictors derived from Sentinel-2 MultiSpectral Instrument (MSI) and Shuttle Radar Topography Mission (SRTM). The first model identified suitable cheatgrass habitat while the other detected cheatgrass presence during the 2021 growing season. Topographic variables were found to be the most important in driving the habitat suitability model. Cheatgrass detection was also found to be possible within a short timespan with limited imagery surrounding a phenological shift of the plant. Maps produced from these models provide natural resource managers the ability to implement early detection and rapid response to prevent the spread of cheatgrass to new locations.

DEVELOP Tech Paper↗
DOE OSTI2024

The Effect of the Prior and the Experimental Design on the Inference of the Precision Matrix in Gaussian Chain Graph Models

Here, we investigate whether (and how) experimental design could aid in the estimation of the precision matrix in a Gaussian chain graph model, especially the interplay between the design, the effect of the experiment and prior knowledge about the effect. Estimation of the precision matrix is a fundamental task to infer biological graphical structures like microbial networks. We compare the marginal posterior precision of the precision matrix under four priors: flat, conjugate Normal-Wishart, Normal-MGIG and a general independent. Under the flat and conjugate priors, the Laplace-approximated posterior precision is not a function of the design matrix rendering useless any efforts to find an optimal experimental design to infer the precision matrix. In contrast, the Normal-MGIG and general independent priors do allow for the search of optimal experimental designs, yet there is a sharp upper bound on the information that can be extracted from a given experiment. We confirm our theoretical findings via a simulation study comparing (i) the KL divergence between prior and posterior and (ii) the Stein’s loss difference of MAPs between random and no experiment. Our findings provide practical advice for domain scientists conducting experiments to better infer the precision matrix as a representation of a biological network.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Hybrid Oscillator-Qubit Quantum Processors: Instruction Set Architectures, Abstract Machine Models, and Applications

This tutorial offers a pedagogical guide to hybrid quantum processors that integrate discrete-variable (DV) qubits and continuous-variable (CV) oscillators. Aimed at computer scientists, engineers, and physicists, it provides an overview of the experimental, algorithmic, and architectural aspects of this novel and rapidly developing hardware model. Experimental realizations of this model include superconducting, trapped-ion, and neutral-atom platforms. By combining DV and CV components, hybrid oscillator-qubit processors enable a powerful new paradigm that offers complementary strengths for quantum control, error correction, computation, and simulation. Working toward the goal of a full-stack system connecting applications to CV-DV hardware, we define and formulate abstract machine models and instruction set architectures. These essential abstractions enable codesign of hardware and software, and resource estimation for exploring the potential of current and future hardware for computational and simulation tasks. Using these abstractions, we present both new and existing examples that illustrate the benefits of hybrid CV-DV processors relative to traditional DV-only hardware in computation as well as quantum simulation of physical models. Examples include algorithms for transferring states between DV and CV systems, performing the quantum Fourier transform, and simulation of lattice gauge theories. Relative to qubit-only hardware, the bosonic degrees of freedom natively available in hybrid architectures can substantially reduce the circuit complexity of simulations for physical models containing bosons. A key technique is the extension of quantum signal processing ideas to CV-DV systems. This work is intended to serve as a timely and comprehensive guide to this relatively unexplored yet promising approach to quantum computation and to provide a road map to guide future development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Upscaled diurnal cycles of land–atmosphere fluxes: a new global half-hourly data product

Interactions between the biosphere and the atmosphere can be well characterized by fluxes between the two. In particular, carbon and energy fluxes play a major role in understanding biogeochemical processes on an ecosystem level or global scale. However, the fluxes can only be measured at individual sites, e.g., by eddy covariance towers, and an upscaling of these local observations is required to analyze global patterns. Previous work focused on upscaling monthly, 8-day, or daily average values, and global maps for each flux have been provided accordingly. In this paper, we raise the upscaling of carbon and energy fluxes between land and atmosphere to the next level by increasing the temporal resolution to subdaily timescales. We provide continuous half-hourly fluxes for the period from 2001 to 2014 at 0.5° spatial resolution, which allows for analyzing diurnal cycles globally. The data set contains four fluxes: gross primary production (GPP), net ecosystem exchange (NEE), latent heat (LE), and sensible heat (H). We propose two prediction approaches for the diurnal cycles based on large-scale regression models and compare them in extensive cross-validation experiments using different sets of predictor variables. We analyze the results for a set of FLUXNET tower sites showing the suitability of our approaches for this upscaling task. Finally, we have selected one approach to calculate the global half-hourly data products based on predictor variables from remote sensing and meteorology at daily resolution as well as half-hourly potential radiation. In addition, we provide a derived product that only contains monthly average diurnal cycles, which is a lightweight version in terms of data storage that still allows studying the important characteristics of diurnal patterns globally. We recommend to primarily use these monthly average diurnal cycles, because they are less affected by the impacts of day-to-day variation, observation noise, and short-term fluctuations on subdaily timescales compared to the full half-hourly flux products. The global half-hourly data products are available at https://doi.org/10.17871/BACI.224 .

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Long-Term Ozone Variability and Trends from Reanalyses: Can It Be Done?

Stratospheric ozone concentrations have begun to show early signs of recovery following the implementation of the Montreal Protocol and its amendments as well as in response to decreasing upper-stratospheric temperatures. Secular trends in stratospheric ozone are modulated by considerable interannual variability and systematic changes in transport patterns that are expected under increasing concentrations of greenhouse gases, especially in the lower stratosphere. These factors necessitate the continued close monitoring of stratospheric ozone in upcoming decades, with a special focus on the lower stratosphere.As highly resolved data sets combining a plethora of observations with model simulations atmospheric reanalyses are, in principle, well suited for the task. All major reanalyses generate ozone output. However, significant spurious discontinuities that arise from step changes in the observing systems prevent a straightforward analysis of ozone trends and long-term variability. Building on our recent work, in this presentation we will demonstrate that trend detection is nonetheless possible using the ozone record from NASA's MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2) reanalysis bias-corrected using a chemistry model simulation as a transfer function. Next, we will outline several strategies to reduce artificial discontinuities in the ozone record in future NASA reanalyses. This discussion will be illustrated by an example of joint assimilation of bias-corrected ozone profiles from the Microwave Limb Sounder (MLS) on the Aura satellite (2004 to present) and the Ozone Mapping Profiler Suite Limb Profiler (OMPS-LP) sensors that are expected to operate on future NOAA platforms.

Wargan, Krzysztof↗
DOE OSTI2017

Determination of the Complete Spin Density Distribution in 13 C-Labeled Protein-Bound Radical Intermediates Using Advanced 2D Electron Paramagnetic Resonance Spectroscopy and Density Functional Theory

Determining the complete electron spin density distribution for protein-bound radicals, even with advanced pulsed electron paramagnetic resonance (EPR) methods, is a formidable task. Here we present a strategy to overcome this problem combining multifrequency HYSCORE and ENDOR measurements on site-specifically 13 C-labeled samples with DFT calculations on model systems. As a demonstration of this approach, pulsed EPR experiments are performed on the primary Q A and secondary Q B ubisemiquinones of the photosynthetic reaction center from Rhodobacter sphaeroides 13C-labeled at the ring and tail positions. Despite the large number of nuclei interacting with the unpaired electron in these samples, two-dimensional X- and Q-band HYSCORE and orientation selective Q-band ENDOR resolve and allow for a characterization of the eight expected 13 C resonances from significantly different hyperfine tensors for both semiquinones. From these results we construct, for the first time, the most complete experimentally determined maps of the s- and p π -orbital spin density distributions for any protein organic cofactor radical to date. This work lays a foundation for understanding the relationship between the electronic structure of semiquinones and their functional properties, and introduces new techniques for mapping out the spin density distribution that are readily applicable to other systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗