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DOE OSTI2022

Position Papers for the ASCR Workshop on the Management and Storage of Scientific Data

The purpose of this workshop is to identify priority research directions in the area of data management for high-performance and scientific computing above and beyond HPC’s traditional "the parallel file system is the data-management system" model. Supporting the breadth of the DOE mission, including the explosion of AI uses and the growing needs of experimental and observational science, motivates revisiting our assumptions about data management. There are many facets of this topic to explore including: (1) Interfaces for accessing data that resides on traditional persistent storage as well as memory devices; (2) Storage-system architecture design that supports scientific workflows on varied hierarchical storage and networking devices; (3) Devising metadata management infrastructure to support FAIR principles (Findability, Accessibility, Interoperability, and Reusability); (4) Capturing provenance information about scientific data; (5) Utilizing AI to learn I/O patterns of emerging workloads for efficient data management; (6) Providing data management support for AI and complex workflows; and (7) Understanding the overlap between traditional storage systems and I/O (SSIO) efforts and data management. While the program committee has identified these topics as important areas for discussion, we welcome position papers from the community that propose additional topics of interest for discussion at the workshop. The workshop agenda will include breakout sessions for discussing these and selected topic areas to inform priority research directions for data management for high-performance and scientific computing.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Report for the ASCR Workshop on the Management and Storage of Scientific Data

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1997

Case Study of an Object-Oriented System: EOSDIS

Mission to Planet Earth (MTPE) is a long-term NASA research mission to study the processes leading to global climate change. The Earth Observing System (EOS) is a NASA campaign of satellite observatories that are a major component of MTPE. The EOS Data and Information System (EOSDIS) is another component of MTPE that will provide the Earth science community with easy, affordable, and reliable access to Earth science data. EOSDIS is a distributed system, with major facilities at six Distributed Active Archive Centers (DAACS) located throughout the United States. The EOSDIS software architecture is being designed to receive, process, and archive several terabytes of science data on a daily basis. Thousands of science users and perhaps several hundred thousands of non-science users are expected to access the system. While there are many segments in EOSDIS (e.g., flight operations, network) this case study discusses the development of the science data processing segment (SDPS). We briefly review the architecture of the system, the goals of the SDPS, and the development progress to date. This study highlights key software development challenges, experiences integrating COTS, and the difficulties of managing a complex system development effort.

Behnke, Jeanne↗

NASA NTRS2019

Gravitational-Wave Astronomy in the 2020s and Beyond: A View Across the Gravitational Wave Spectrum

One of the most notable developments since the 2010 Decadal Survey is the addition of gravitationalwaves (GW) to the astronomers' suite of tools for understanding the Universe. LIGO's2015 detection of gravitational waves (Abbott et al. 2016) from the merger of a pair of black holesroughly 30 times the mass of our Sun garnered tremendous excitement from both the public andthe scientific community and raised interesting questions as to the origin of such systems. To datea total of 11 confirmed detections have been announced, including the first GW signals from themerger of neutron stars in 2017 seen by LIGO and Virgo (Abbott et al. 2017). That event wasassociated with a gamma ray burst; the subsequent kilonovae and afterglow was perhaps the mostthoroughly-observed astronomical event of all time (Abbott et al. 2017b). In the coming decades,with continued investment, the ground-based network will continue to improve in both the numberand sensitivity of detectors at high frequencies, pulsar timing arrays such as NANOGrav willuncover stochastic sources of gravitational waves and then single sources at low frequencies, andLISA will begin to probe the mid-frequency band from space. In this white paper, we presenta broad outline of the scientific impact of these facilities in the coming decade and the 2030s,emphasizing the ways in which

Shoemaker, David↗

DOE OSTI2022

What are mycorrhizal traits?

Traits are inherent properties of organisms, but how are they defined for organismal networks such as mycorrhizal symbioses? Mycorrhizal symbioses are complex and diverse belowground symbioses between plants and fungi that have proved challenging to fit into a unified and coherent trait framework. Here we propose an inclusive mycorrhizal trait framework that classifies traits as morphological, physiological, and phenological features that have functional implications for the symbiosis. We further classify mycorrhizal traits by location – plant, fungus, or the symbiosis – which highlights new questions in trait-based mycorrhizal ecology designed to charge and challenge the scientific community. This new framework is an opportunity for researchers to interrogate their data to identify novel insights and gaps in our understanding of mycorrhizal symbioses.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

End-to-End Workflow for Machine-Learning-Based Qubit Readout With QICK and hls4ml

In this article, we present an end-to-end workflow for superconducting qubit readout that embeds codesigned neural networks into the quantum instrumentation control kit (QICK). Capitalizing on the custom firmware and software of the QICK platform, which is built on Xilinx radiofrequency system-on-chip field-programmable gate arrays (FPGAs), we aim to leverage machine learning (ML) to address critical challenges in qubit readout accuracy and scalability. The workflow utilizes the hls4ml package and employs quantization-aware training to translate ML models into hardware-efficient FPGA implementations via user-friendly Python application programming interfaces. We experimentally demonstrate the design, optimization, and integration of an ML algorithm for single transmon qubit readout, achieving 96% single-shot fidelity with a latency of 32.25 ns and less than 16% FPGA lookup table resource utilization. Our results offer the community an accessible workflow to advance ML-driven readout and adaptive control in quantum information processing applications.

42 ENGINEERING↗

DOE OSTI2019

Spatial and temporal variation in river corridor exchange across a 5th-order mountain stream network

Although most field and modeling studies of river corridor exchange have been conducted at scales ranging from tens to hundreds of meters, results of these studies are used to predict their ecological and hydrological influences at the scale of river networks. Further complicating prediction, exchanges are expected to vary with hydrologic forcing and the local geomorphic setting. While we desire predictive power, we lack a complete spatiotemporal relationship relating discharge to the variation in geologic setting and hydrologic forcing that is expected across a river basin. Indeed, the conceptual model of Wondzell (2011) predicts systematic variation in river corridor exchange as a function of (1) variation in baseflow over time at a fixed location, (2) variation in discharge with location in the river network, and (3) local geomorphic setting. To test this conceptual model we conducted more than 60 solute tracer studies including a synoptic campaign in the 5th-order river network of the H. J. Andrews Experimental Forest (Oregon, USA) and replicate-in-time experiments in four watersheds. We interpret the data using a series of metrics describing river corridor exchange and solute transport, testing for consistent direction and magnitude of relationships relating these metrics to discharge and local geomorphic setting. We confirmed systematic decrease in river corridor exchange space through the river networks, from headwaters to the larger main stem. However, we did not find systematic variation with changes in discharge through time or with local geomorphic setting. While interpretation of our results is complicated by problems with the analytical methods, the results are sufficiently robust for us to conclude that space-for-time and time-for-space substitutions are not appropriate in our study system. Finally, we suggest two strategies that will improve the interpretability of tracer test results and help the hyporheic community develop robust datasets that will enable comparisons across multiple sites and/or discharge conditions.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1991

An overview of the NASA electronic components information management system

The NASA Parts Project Office (NPPO) comprehensive data system to support all NASA Electric, Electronic, and Electromechanical (EEE) parts management and technical data requirements is described. A phase delivery approach is adopted, comprising four principal phases. Phases 1 and 2 support Space Station Freedom (SSF) and use a centralized architecture with all data and processing kept on a mainframe computer. Phases 3 and 4 support all NASA centers and projects and implement a distributed system architecture, in which data and processing are shared among networked database servers. The Phase 1 system, which became operational in February of 1990, implements a core set of functions. Phase 2, scheduled for release in 1991, adds functions to the Phase 1 system. Phase 3, to be prototyped beginning in 1991 and delivered in 1992, introduces a distributed system, separate from the Phase 1 and 2 system, with a refined semantic data model. Phase 4 extends the data model and functionality of the Phase 3 system to provide support for the NASA design community, including integration with Computer Aided Design (CAD) environments. Phase 4 is scheduled for prototyping in 1992 to 93 and delivery in 1994.

Kramer, G.↗

NASA NTRS2000

Global Interoperability of High Definition Video Streams Via ACTS and Intelsat

In 1993, a proposal at the Japan.-U.S. Cooperation in Space Program Workshop lead to a subsequent series of satellite communications experiments and demonstrations, under the title of Trans-Pacific High Data Rate Satellite Communications Experiments. The first of which is a joint collaboration between government and industry teams in the United States and Japan that successfully demonstrated distributed high definition video (HDV) post-production on a global scale using a combination of high data rate satellites and terrestrial fiber optic asynchronous transfer mode (ATM) networks. The HDV experiment is the first GIBN experiment to establish a dual-hop broadband satellite link for the transmission of digital HDV over ATM. This paper describes the team's effort in using the NASA Advanced Communications Technology Satellite (ACTS) at rates up to OC-3 (155 Mbps) between Los Angeles and Honolulu, and using Intelsat at rates up to DS-3 (45 Mbps) between Kapolei and Tokyo, with which HDV source material was transmitted between Sony Pictures High Definition Center (SPHDC) in Los Angeles and Sony Visual Communication Center (VCC) in Shinagawa, Tokyo. The global-scale connection also used terrestrial networks in Japan, the States of Hawaii and California. The 1.2 Gbps digital HDV stream was compressed down to 22.5 Mbps using a proprietary Mitsubishi MPEG-2 codec that was ATM AAL-5 compatible. The codec: employed four-way parallel processing. Improved versions of the codec are now commercially available. The successful post-production activity performed in Tokyo with a HDV clip transmitted from Los Angeles was predicated on the seamless interoperation of all the equipment between the sites, and was an exciting example in deploying a global-scale information infrastructure involving a combination of broadband satellites and terrestrial fiber optic networks. Correlation of atmospheric effects with cell loss, codec drop-out, and picture quality were made. Current efforts in the Trans-Pacific series plan to examine the use of Internet Protocol (IP)-related technologies over such an infrastructure. The use of IP allows the general public to be an integral part of the exciting activities, helps to examine issues in constructing the solar-system internet, and affords an opportunity to tap the research results from the (reliable) multicast and distributed systems communities. The current Trans- Pacific projects, including remote astronomy and digital library (visible human) are briefly described.

Hsu, Eddie↗

NASA NTRS2004

The LATEST Project: Operational Assessment of Total Lightning Data in the U.S.

A government, university, and industry alliance has joined forces to transition total lightning observations from ground-based research networks and NASA satellites (LIS/TRMM) to improve the short range prediction of severe weather. This interest builds on the desire of the U.S Weather Research Program to foster a national Nowcasting Test Bed, with this specific transition activity initiated through the NASA short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL. A kick-off national workshop sponsored by the SPoRT Center was held in Huntsville April 1-2 to identify the common goals and objectives of the research and operational community, and to assign roles and responsibilities within the alliance. The workshop agenda, presentations, and summary are available at the SPoRT Center Web site ( h h under the "Meetings" tab. The next national workshop is planned for 2005 in Dallas, TX. The NASA North Alabama regional Lightning Mapping Array &MA) has been operational in the Huntsville area for 3 years, and has continuously sampled a variety of severe weather systems during that period. A gridded version of the LMA total lightning data is currently being supplied to National Weather Service offices in Huntsville, Nashville and Birmingham through the NWS AWES decision support system, for the purposes of assessing the utility of the data in the nowcasting of severe weather such as tornadoes, damaging straight line winds, flash flooding and other weather hazards (lightning induced forest fires, microbursts). While the raw LMA data have been useful to NWS forecasters, even greater utility would be realized if higher-order data products could be supplied through AWIPS along with the gridded data over a larger domain. In 2003-2004 additional LMA systems have been deployed across the southern US. from Florida to New Mexico, providing an opportunity for more than 20 NWS forecast offices to evaluate the incremental value of total lightning data in the warning decision making process.

Goodman, Steven↗

NASA NTRS2008

Systematic Independent Validation of Inner Heliospheric Models

This presentation is the first in a series which will provide independent validation of community models of the outer corona and inner heliosphere. In this work we establish a set of measures to be used in validating this group of models. We use these procedures to generate a comprehensive set of results from the Wang- Sheeley-Arge (WSA) model which will be used as a baseline, or reference, against which to compare all other models. We also run a test of the validation procedures by applying them to a small set of results produced by the ENLIL Magnetohydrodynamic (MHD) model. In future presentations we will validate other models currently hosted by the Community Coordinated Modeling Center(CCMC), including a comprehensive validation of the ENLIL model. The Wang-Sheeley-Arge (WSA) model is widely used to model the Solar wind, and is used by a number of agencies to predict Solar wind conditions at Earth as much as four days into the future. Because it is so important to both the research and space weather forecasting communities, it is essential that its performance be measured systematically, and independently. In this paper we offer just such an independent and systematic validation. We report skill scores for the model's predictions of wind speed and IMF polarity for a large set of Carrington rotations. The model was run in all its routinely used configurations. It ingests line of sight magnetograms. For this study we generated model results for monthly magnetograms from the National Solar Observatory (SOLIS), Mount Wilson Observatory and the GONG network, spanning the Carrington rotation range from 1650 to 2068. We compare the influence of the different magnetogram sources, performance at quiet and active times, and estimate the effect of different empirical wind speed tunings. We also consider the ability of the WSA model to identify sharp transitions in wind speed from slow to fast wind. These results will serve as a baseline against which to compare future versions of the model

MacNeice, P. J.↗

NASA NTRS2020

UAS Service Supplier Network Performance

This report summarizes the performance of Unmanned Aircraft System (UAS) Service Suppliers (USS) in the Technical Capability Level 4 (TCL4) flight test performed by NASA and its partners in support of the UAS Traffic Management (UTM) concept. TCL4 is the final in a series of TCL demonstrations of a traffic management system for small UAS (sUAS). All demonstrations have been executed in collaboration with industry partners. The [FAA 2018] UTM Concept of Operations document describes UTM as:...the manner in which the FAA will support operations for predominantly sUAS operating in low altitude airspace. UTM utilizes industry’s ability to supply services under FAA’s regulatory authority where these services do not currently exist. It is a community-based traffic management system, where the Operators are responsible for the coordination, execution, and management of operations, with rules of the road established by FAA. UTM is designed to support the demand and expectations for a broad spectrum of operations with ever-increasing complexity and risk. UTM should be considered a collection of services rather than a monolithic application. The following section describes the architecture at a high level. For further insight, the FAA’s concept document [FAA 2018] or NASA’s earlier concept publication [NASA 2016] should be consulted.

Rios, Joseph L.↗

DOE OSTI2021

Quantifying microbial control of soil organic matter dynamics at macrosystem scales

Soil organic matter (SOM) stocks, decomposition and persistence are largely the product of controls that act locally. Yet the controls are shaped and interact at multiple spatiotemporal scales, from which macrosystem patterns in SOM emerge. Theory on SOM turnover recognizes the resulting spatial and temporal conditionality in the effect sizes of controls that play out across macrosystems, and couples them through evolutionary and community assembly processes. For example, climate history shapes plant functional traits, which in turn interact with contemporary climate to influence SOM dynamics. Selection and assembly also shape the functional traits of soil decomposer communities, but it is less clear how in turn these traits influence temporal macrosystem patterns in SOM turnover. Here, we review evidence that establishes the expectation that selection and assembly should generate decomposer communities across macrosystems that have distinct functional effects on SOM dynamics. Representation of this knowledge in soil biogeochemical models affects the magnitude and direction of projected SOM responses under global change. Yet there is high uncertainty and low confidence in these projections. To address these issues, we make the case that a coordinated set of empirical practices are required which necessitate (1) greater use of statistical approaches in biogeochemistry that are suited to causative inference; (2) long-term, macrosystem-scale, observational and experimental networks to reveal conditionality in effect sizes, and embedded correlation, in controls on SOM turnover; and (3) use of multiple measurement grains to capture local- and macroscale variation in controls and outcomes, to avoid obscuring causative understanding through data aggregation. Here, when employed together, along with process-based models to synthesize knowledge and guide further empirical work, we believe these practices will rapidly advance understanding of microbial controls on SOM and improve carbon cycle projections that guide policies on climate adaptation and mitigation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Envisioning the Future Renewable and Resilient Energy Grids—A Power Grid Revolution Enabled by Renewables, Energy Storage, and Energy Electronics

Today’s power grids are facing tremendous challenges because of the ever-increasing power demand, system complexity, infrastructure cost, knowledge base, and policy and regulatory issues to achieve supply–demand power balance and resiliency with respect to more frequent extreme weather events and cyberattacks. It is particularly challenging when the transition toward 100% intermittent renewable energy sources is considered. Many countries are calling for building up more transmission and distribution lines to increase power delivery capacities. This article is an attempt to answer two urgent questions: Is more transmission and distribution infrastructure really needed to meet the increasing power demand? What kind of future grid infrastructure should we envision and build? This article attempts to answer these questions and proposes the concept of community-centric asynchronous renewable and resilient energy grids. By clearly differentiating the concepts of grid resilience and reliability, the importance of building resilient power electronics’ devices and robust system-level control algorithms to achieve 100% renewable energy integrated resilient grids is presented. To identify the shortcomings and propose advancements, power electronics’ technologies are categorized using the proposed concepts of natural source frequencies (NSf), energy storage, direct energy conversion/control and fault protection (DeCaFp), and high-efficiency energy consumption and buffering (heECaB) technology. The ability of networked microgrids to greatly reduce power outages and power system restoration time is demonstrated by leveraging robust decentralized and centralized control algorithms, identified through a comprehensive literature review. Future research areas are proposed to further enhance grid stability, controllability, cybersecurity, and protection against faults in the presence of 100% renewable sources by leveraging the advanced capabilities of NSf, DeCaFp, and heECaB devices and system-level control algorithms.

14 SOLAR ENERGY↗

DOE OSTI2022

Model-Form Epistemic Uncertainty Quantification for Modeling with Differential Equations: Application to Epidemiology

Modeling real-world phenomena to any degree of accuracy is a challenge that the scientific research community has navigated since its foundation. Lack of information and limited computational and observational resources necessitate modeling assumptions which, when invalid, lead to model-form error (MFE). The work reported herein explored a novel method to represent model-form uncertainty (MFU) that combines Bayesian statistics with the emerging field of universal differential equations (UDEs). The fundamental principle behind UDEs is simple: use known equational forms that govern a dynamical system when you have them; then incorporate data-driven approaches – in this case neural networks (NNs) – embedded within the governing equations to learn the interacting terms that were underrepresented. Utilizing epidemiology as our motivating exemplar, this report will highlight the challenges of modeling novel infectious diseases while introducing ways to incorporate NN approximations to MFE. Prior to embarking on a Bayesian calibration, we first explored methods to augment the standard (non-Bayesian) UDE training procedure to account for uncertainty and increase robustness of training. In addition, it is often the case that uncertainty in observations is significant; this may be due to randomness or lack of precision in the measurement process. This uncertainty typically manifests as “noisy” observations which deviate from a true underlying signal. To account for such variability, the NN approximation to MFE is endowed with a probabilistic representation and is updated using available observational data in a Bayesian framework. By representing the MFU explicitly and deploying an embedded, data-driven model, this approach enables an agile, expressive, and interpretable method for representing MFU. In this report we will provide evidence that Bayesian UDEs show promise as a novel framework for any science-based, data-driven MFU representation; while emphasizing that significant advances must be made in the calibration of Bayesian NNs to ensure a robust calibration procedure.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Supporting Growth of a Skilled Workforce in the Building Energy Efficiency Industry (Final Technical Report)

The Interstate Renewable Energy Council (IREC), having worked for well over a decade to develop national networks and best practices focused on attracting and training high quality workers for the clean energy industries, sought to address shortfalls in skilled workers who build, retrofit, operate, and maintain energy efficient buildings. Through this project, IREC created and promoted a Green Buildings Career Map (GBCM)—a career awareness and recruitment tool—that seeks to boost the nationwide growth of workers entering the energy efficiency (EE) industry. Working with a team of subject matter experts and our partner organizations—Building Performance Association (BPA), Building Performance Institute (BPI), Community Action Partnership (CAP), and the National Institute of Building Sciences (NIBS)—IREC produced an interactive, engaging career map to attract and motivate individuals into pursuing careers in energy efficiency, and in support of the Weatherization Assistance Program. The GBCM was designed for a broad audience including educators, career advisors, employers, policymakers, workforce professionals, and jobseekers who may otherwise have little or no awareness of the exciting and rewarding opportunities within targeted industry sectors. Most individuals seeking careers do not know about the breadth of careers awaiting them in the built environment and the same is true for most career and guidance counselors, educators, and parents. The GBCM provides this broad audience with a vision of the myriad jobs that could lead to a long-standing career in energy efficiency. The GBCM describes diverse occupations across the EE industry, charts possible progression between those occupations, and identifies the training, skills, and credentials necessary to do them well.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Assessing the limitations of commercial sensors and models for supporting marine carbon dioxide removal monitoring: a case study

Several unknowns remain surrounding marine Carbon Dioxide Removal (mCDR) monitoring, reporting, and verification (MRV) practices and capabilities. Current in-situ sensor technology is limited (primarily pH and pCO 2 ), requiring calculations and assumptions to estimate changes in carbonate chemistry parameters, including total alkalinity (TA). Considering that cost, energy consumption, and accuracy of commercial sensors can vary by orders of magnitude, understanding how well existing sensors perform in an mCDR context is important for this emerging community. Likewise, documenting sensor limitations and how relatively simple models can optimize sensor deployments will improve MRV efforts and support protocol development. Here we (1) compare performance a variety of commercially available sensors in a blind mesocosm experiment simulating ocean alkalinity enhancement (OAE), and how sensor performance impacted carbonate chemistry estimates; (2) evaluate if sensors can distinguish the OAE signal from natural variability during a small scale OAE field test in Sequim Bay, WA, USA, and (3) use an idealized ocean biogeochemistry model to explore optimal sensor network design based on (1) and (2). Our mesocosm results indicate that correctly constraining pH uncertainty will be critical for accurate TA estimates with current sensor technology compared to the less impactful variation caused by uncertainty in pCO 2 (pH data that are presented throughout are reported on the total scale (pH T ) unless otherwise noted). Our pilot field test demonstrated that sensors were capable of distinguishing mCDR signatures from natural variability under optimal real-world conditions. Idealized modeling simulations of the field test showed that a range of sparse and dense (3 to 100) sensors sampling areas of detectable increases will underestimate the net change in surface pH by at least 35–55%, at both realistic and highly elevated alkalinity input levels. We also highlight the limitations of current sensing technology for MRV, and the importance of ocean biogeochemistry models as critical tools for predicting when and where mCDR signals will be detectable using available sensors. Overall, our findings suggest that commercially available pCO 2 sensors and some pH sensors will form an important backbone for mCDR MRV tasks, though complete MRV characterization will require these data to be used in combination with other tools.

OAE↗

NASA NTRS2012

Understanding Group/Party Affiliation Using Social Networks and Agent-Based Modeling

The dynamics of group affiliation and group dispersion is a concept that is most often studied in order for political candidates to better understand the most efficient way to conduct their campaigns. While political campaigning in the United States is a very hot topic that most politicians analyze and study, the concept of group/party affiliation presents its own area of study that producers very interesting results. One tool for examining party affiliation on a large scale is agent-based modeling (ABM), a paradigm in the modeling and simulation (M&S) field perfectly suited for aggregating individual behaviors to observe large swaths of a population. For this study agent based modeling was used in order to look at a community of agents and determine what factors can affect the group/party affiliation patterns that are present. In the agent-based model that was used for this experiment many factors were present but two main factors were used to determine the results. The results of this study show that it is possible to use agent-based modeling to explore group/party affiliation and construct a model that can mimic real world events. More importantly, the model in the study allows for the results found in a smaller community to be translated into larger experiments to determine if the results will remain present on a much larger scale.

Campbell, Kenyth↗