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At least 235 records · Page 13

All sources NASA NTRS DOE OSTI

NASA NTRS2016

Future Standardization of Space Telecommunications Radio System with Core Flight System

NASA Glenn Research Center (GRC) is integrating the NASA Space Telecommunications Radio System (STRS) Standard with the Core Flight System (cFS), an avionics software operating environment. The STRS standard provides a common, consistent framework to develop, qualify, operate and maintain complex, reconfigurable and reprogrammable radio systems. The cFS is a flexible, open architecture that features a plugand- play software executive called the Core Flight Executive (cFE), a reusable library of software components for flight and space missions and an integrated tool suite. Together, STRS and cFS create a development environment that allows for STRS compliant applications to reference the STRS application programmer interfaces (APIs) that use the cFS infrastructure. These APIs are used to standardize the communication protocols on NASAs space SDRs. The cFS-STRS Operating Environment (OE) is a portable cFS library, which adds the ability to run STRS applications on existing cFS platforms. The purpose of this paper is to discuss the cFS-STRS OE prototype, preliminary experimental results performed using the Advanced Space Radio Platform (ASRP), the GRC S‑ band Ground Station and the SCaN (Space Communication and Navigation) Testbed currently flying onboard the International Space Station (ISS). Additionally, this paper presents a demonstration of the Consultative Committee for Space Data Systems (CCSDS) Spacecraft Onboard Interface Services (SOIS) using electronic data sheets (EDS) inside cFE. This configuration allows for the data sheets to specify binary formats for data exchange between STRS applications. The integration of STRS with cFS leverages mission-proven platform functions and mitigates barriers to integration with future missions. This reduces flight software development time and the costs of software-defined radio (SDR) platforms. Furthermore, the combined benefits of STRS standardization with the flexibility of cFS provide an effective, reliable and modular framework to minimize software development efforts for spaceflight missions.

space communications↗

NASA NTRS2016

Future Standardization of Space Telecommunications Radio System with Core Flight System

NASA Glenn Research Center (GRC) is integrating the NASA Space Telecommunications Radio System (STRS) Standard with the Core Flight System (cFS). The STRS standard provides a common, consistent framework to develop, qualify, operate and maintain complex, reconfigurable and reprogrammable radio systems. The cFS is a flexible, open architecture that features a plug-and-play software executive called the Core Flight Executive (cFE), a reusable library of software components for flight and space missions and an integrated tool suite. Together, STRS and cFS create a development environment that allows for STRS compliant applications to reference the STRS APIs through the cFS infrastructure. These APis are used to standardize the communication protocols on NASAs space SDRs. The cFE-STRS Operating Environment (OE) is a portable cFS library, which adds the ability to run STRS applications on existing cFS platforms. The purpose of this paper is to discuss the cFE-STRS OE prototype, preliminary experimental results performed using the Advanced Space Radio Platform (ASRP), the GRC Sband Ground Station and the SCaN (Space Communication and Navigation) Testbed currently flying onboard the International Space Station. Additionally, this paper presents a demonstration of the Consultative Committee for Space Data Systems (CCSDS) Spacecraft Onboard Interface Services (SOIS) using electronic data sheets inside cFE. This configuration allows for the data sheets to specify binary formats for data exchange between STRS applications. The integration of STRS with cFS leverages mission-proven platform functions and mitigates barriers to integration with future missions. This reduces flight software development time and the costs of software-defined radio (SDR) platforms. Furthermore, the combined benefits of STRS standardization with the flexibility of cFS provide an effective, reliable and modular framework to minimize software development efforts for spaceflight missions.

space communications↗

DOE OSTI2025

Advancing ocean monitoring and knowledge for societal benefit: the urgency to expand Argo to OneArgo by 2030

The ocean plays an essential role in regulating Earth’s climate, influencing weather conditions, providing sustenance for large populations, moderating anthropogenic climate change, encompassing massive biodiversity, and sustaining the global economy. Human activities are changing the oceans, stressing ocean health, threatening the critical services the ocean provides to society, with significant consequences for human well-being and safety, and economic prosperity. Effective and sustainable monitoring of the physical, biogeochemical state and ecosystem structure of the ocean, to enable climate adaptation, carbon management and sustainable marine resource management is urgently needed. The Argo program, a cornerstone of the Global Ocean Observing System (GOOS), has revolutionized ocean observation by providing real-time, freely accessible global temperature and salinity data of the upper 2,000m of the ocean (Core Argo) using cost-effective simple robotics. For the past 25 years, Argo data have underpinned many ocean, climate and weather forecasting services, playing a fundamental role in safeguarding goods and lives. Argo data have enabled clearer assessments of ocean warming, sea level change and underlying driving processes, as well as scientific breakthroughs while supporting public awareness and education. Building on Argo’s success, OneArgo aims to greatly expand Argo’s capabilities by 2030, expanding to full-ocean depth, collecting biogeochemical parameters, and observing the rapidly changing polar regions. Providing a synergistic subsurface and global extension to several key space-based Earth Observation missions and GOOS components, OneArgo will enable biogeochemical and ecosystem forecasting and new long-term climate predictions for which the deep ocean is a key component. Driving forward a revolution in our understanding of marine ecosystems and the poorly-measured polar and deep oceans, OneArgo will be instrumental to assess sea level change, ocean carbon fluxes, acidification and deoxygenation. Emerging OneArgo applications include new views of ocean mixing, ocean bathymetry and sediment transport, and ecosystem resilience assessment. Implementing OneArgo requires about $100 million annually, a significant increase compared to present Argo funding. OneArgo is a strategic and cost-effective investment which will provide decision-makers, in both government and industry, with the critical knowledge needed to navigate the present and future environmental challenges, and safeguard both the ocean and human wellbeing for generations to come.

ARGO↗

DOE OSTI2022

Design and Analysis of a 200 kW Dynamic Wireless Charging System for Electric Vehicles

Dynamic wireless charging of electric vehicles can significantly alleviate or eliminate range anxiety while reducing the required on-board battery capacity. To achieve an electric vehicle charging balance with minimal infrastructure costs, power transfer levels around 200 kW are required. In this paper, a system architecture with a modularized power electronics and optimized power transfer couplers was adopted to enable efficient power transfer. A DC/DC converter was used for secondary-side charging control of the battery. The system performance was validated in an experimental setup at 120 kW with 91.31% efficiency from the DC input on the primary side to the vehicle battery.

Xue, Lincoln↗

DOE OSTI2023

Coexistent quantum channel characterization using quantum process tomography with spectrally resolved detection

The coexistence of classical and quantum signals over the same optical fiber is critical for quantum networks operating within the existing communications infrastructure. Here, we characterize the quantum channel that results from distributing approximate single-photon polarization-encoded qubits simultaneously with classical light of varying intensities through a 25 km fiber-optic channel. We use spectrally resolved quantum process tomography with a newly developed Bayesian reconstruction method to estimate the quantum channel from experimental data, both with and without classical noise. Furthermore, we show that the coexistent fiber-based quantum channel has high process fidelity with an ideal depolarizing channel if the noise is dominated by Raman scattering. These results aid future development of quantum repeater designs and quantum error-correcting codes which benefit from realistic channel error models.

Chapman, Joseph↗

NASA NTRSDate not supplied

The Nasa Facility for Astromaterials Research at the Johnson Space Center – A National Laboratory for Planetary Research.

The Astromaterials Research and Exploration Science (ARES) Division at the NASA Johnson Space Center has established the NASA Facility for Astromaterials Research (NFAR) through the NASA Planetary Science Enabling Facilities program. NFAR is designed to provide access to our unique combination of laboratories, instruments, infrastructure, and technical expertise for conducting broad-based world-class planetary research. NFAR enables direct access to both research and curation expertise, to facilitate specialized sample handling and analysis of astromaterials and planetary analog materials. NFAR users from institutions that historically have limited access to or lack in-house analytical or experimental facilities are particularly encouraged to apply. We issue three calls for user proposals each year due the last day of April, July, and November. We award NFAR research projects to users in a competitive peer-reviewed proposal process. NASA-funded research in active PSD R&A proposals is prioritized along with requests from early-career/next-generation scientists, under-represented minorities, and those PIs from minority serving institutions. There is no cost to use the analytical facility, but researchers are required to be in person for analyses. Proposals to use NFAR labs are limited to < 5 pages and focus on the scientific purpose of the investigation and its relevance to NASA PSD, the labs to be accessed, and the time needed for the investigation. More information can be found at: https://ares.jsc.nasa.gov/research/nasa-facility-astromaterials-research/.

J. Filiberto↗

NASA NTRSDate not supplied

The NASA Facility for Astromaterials Research at the Johnson Space Center – A National Laboratory for Planetary Research

The Astromaterials Research and Exploration Science (ARES) Division at the NASA Johnson Space Center has established the NASA Facility for Astromaterials Research (NFAR) through the NASA Planetary Science Enabling Facilities program. NFAR is designed to provide access to our unique combination of laboratories, instruments, infrastructure, and technical expertise for conducting broad-based world-class planetary research. NFAR enables direct access to both research and curation expertise, to facilitate specialized sample handling and analysis of astromaterials and planetary analog materials. NFAR users from institutions that historically have limited access to or lack in-house analytical or experimental facilities are particularly encouraged to apply. We award NFAR research projects to users in a competitive peer-reviewed proposal process. Proposals to use NFAR labs are limited to <5 pages and focus on the scientific purpose of the investigation and its relevance to NASA Planetary Science Division (PSD) objectives, the labs to be accessed, and the time needed for the investigation. There is no deadline for proposals, and proposals will be reviewed on a rolling basis. NASA-funded research in active PSD R&A proposals is prioritized along with requests from early-career/next-generation scientists, under-represented minorities, and to Principal Investigators from minority-serving institutions. More information on the NFAR labs and preparing and submitting a proposal can be found at: https://ares.jsc.nasa.gov/research/nasa-facility-astromaterials-research/.

E. Rampe↗

DOE OSTI2025

Dynamics and lipid membrane coupling of the RAS-RAF complex revealed via multiscale simulations

To gain molecular and mechanistic insights into initiation of the RAS-RAF signaling cascade, we developed and used a combination of multiscale simulation and experimental approaches. The influence and impact of the membrane on RAS and RAF proteins is a factor we are just beginning to understand and appreciate in more detail. Molecular simulation is an ideal methodology to further study this complicated relationship between the membrane and associated proteins. Our previous work using Multiscale Machine-learned Modeling Infrastructure investigated different lipid compositions solely around the KRAS4b protein and the interplay between protein behavior and these membrane environments. Multiscale Machine-learned Modeling Infrastructure uses machine learning to couple adjacent simulation scales and has been efficiently scaled across some of the world’s largest high-performance computers. Recently, we have expanded this multiresolution framework to include the all-atom simulation scale and to incorporate the RAF RBDCRD domains. Here, we present the overall analysis results from this new simulation campaign comprising a mixture of RAS and RAF RBDCRD proteins. Approximately 35,000 coarse-grained and 10,000 all-atom molecular dynamics simulations were completed, sampled from a variety of protein/lipid composition configurations that were generated from a micron-scale continuum simulation containing hundreds of copies of the proteins. Our studies suggest that orientations of the RAS-RBDCRD complex on the membrane occupy distinct configurational states, and the spatial patterns of lipid arrangements around these different protein states are unique to each state. The extent and size of lipid “fingerprints” imposed on the membrane by the RAS-RBDCRD protein complex are significantly larger than observed for just the RAS protein on its own. These protein complexes strongly associate, but we do not observe statistically significant preferred protein-protein orientations. These observations indicate that spatial colocalization of RAS-RBDCRD proteins in the same vicinity may be assisted by specific membrane environments, acting to increase the probability of signaling complex formation.

Carpenter, Timothy S. [Lawrence Livermore National↗

DOE OSTI2020

Hydrogen Risk Assessment Models (HyRAM) (Version 3.0 Technical Reference Manual)

The HyRAM software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM is designed to facilitate the use of state-of-the-art science and engineering models to conduct robust, repeatable assessments of hydrogen safety, hazards, and risk. HyRAM includes generic probabilities for hydrogen equipment failures, probabilistic models for the impact of heat flux on humans and structures, and computationally and experimentally validated first-order models of hydrogen release and flame physics. HyRAM integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, and characterizing hydrogen hazards (thermal effects from jet fires, overpressure effects from deflagrations), and assessing impact on people and structures. HyRAM is developed at Sandia National Laboratories for the U.S. Department of Energy to increase access to technical data about hydrogen safety and to enable the use of that data to support development and revision of national and international codes and standards. HyRAM is a research software in active development and thus the models and data may change. This report will be updated at appropriate developmental intervals. This document provides a description of the methodology and models contained in the HyRAM version 3.0. HyRAM 3.0 includes the new ability to model cryogenic hydrogen releases from liquid hydrogen systems, using a different property calculation method and different equations of state. Other changes include modifications to the ignition probability calculations, component leak frequency calculations, and addition of default impulse data.

08 HYDROGEN↗

NASA NTRS1990

Freedom is an international partnership

The NASA Space Station Freedom (SSF) project initiated in 1984 is a collaborative one among the U.S., Japan, Canada, and the 10 nations participating in ESA. The SSF partners have over the last six years defined user requirements, decided on the hardware to be manufactured, and constructed a framework for long-term cooperation. SSF will be composed of user elements furnished by the foreign partners and a U.S.-supplied infrastructure encompassing the truss assembly, electrical power system, and crew living quarters. The U.S. will also furnish a lab and a polar-orbit platform; ESA, a second lab and the coorbiting Free-Flying Laboratory, as well as a second polar platform. Japan's Japanese Experiment Module shall include an Exposed Facility and an Experimental Logistics module. Canada will contribute the Mobile Servicing System robotic assembler/maintainer for the whole of SFF.

Kohrs, Richard H.↗

DOE OSTI2022

Artificial Intelligence and Machine Learning for Bioenergy Research: Opportunities and Challenges

The integration of artificial intelligence and machine learning (AI/ML) with automated experimentation, genomics, biosystems design, and bioprocessing technologies is poised to revolutionize scientific investigation and, particularly, bioenergy research. To identify the opportunities and challenges in this emerging research area, the U.S. Department of Energy’s (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23–25, 2022. These interests have since been amplified in a September 2022 Executive Order, “Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure U.S. Bioeconomy,” to promote a whole-of government approach to biotechnology development (White House 2022). Approximately 50 scientists with various backgrounds and expertise from academia, industry, and DOE national laboratories met to discuss the opportunities and challenges of AI/ML for bioenergy research. Workshop participants were tasked with assessing the potential for AI/ML and laboratory automation to advance biological understanding and engineering in general. They particularly examined how integrating AI/ML tools with laboratory automation could accelerate biosystems design and optimize biomanufacturing. Discussions included the data and computational infrastructure needed to augment biosystems design applications and the expertise and workforce development efforts urgently required to shift integrated systems toward bioenergy research more broadly. Participants discussed many existing and future applications of AI/ML for biosystems design ranging from enzymes to plants and microbes, microbiomes, and bioprocess development. They also identified three key categories of scientific and technical opportunities and challenges: high-quality data, AI/ML algorithms, and laboratory automation. Several main takeaways emerged from the workshop: 1. Numerous AI/ML and automated experimentation applications exist for a variety of DOE mission needs in energy and the environment; 2. Exemplary research grand challenges for which AI/ML could provide solutions include: building microbes and microbial communities to specifications, developing closed-loop autonomous design and control for biosystems design, and advancing scale-up and automation; 3. Lack of sufficient high-quality, annotated data hinders the development of AI/ML applications; 4. New and improved AI/ML tools are needed, particularly those meeting the specific needs of the BER and BETO research communities; 5. Trade-offs in performance, cost, and reliability exist between deploying commercially available versus building custom-developed instrumentation and software for automated or autonomous experimentation; translation of manual to automated or autonomous methods is often a nontrivial endeavor; 6. Training a new generation of young scientists who can develop and apply AI/ML tools is needed to solve long-standing scientific challenges in bioenergy research. The integration of AI/ML tools and automated experimentation represents a new data-driven research paradigm complementary to the traditional hypothesis-driven research paradigm. This paradigm accelerates design and optimization of biological systems and processes for a variety of DOE mission needs in energy and the environment. The AMBER workshop broadly explored the potential of this new paradigm for bioenergy research, of particular interest to BER and BETO, and identified key challenges and opportunities that DOE can address in the coming years by leveraging its unique capabilities and resources.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Material processing, microstructure, and composite properties of low carbon Engineered Cementitious Composites (ECC)

Traditional PVA fiber-reinforced Engineered Cementitious Composites (ECC) show high tensile ductility and superior durability with tight crack width, but the high cost and embodied carbon can hinder its wider application in infrastructures. The objective of this study is to develop a better understanding of the fresh and hardened properties of an ECC that employs a lower embodied-carbon binder, Limestone Calcined Clay Cement (LC3), and lower-cost PP fiber that is widely available. Specifically, the interrelations between material processing, microstructure, and composite properties were studied experimentally. The results showed that ECC with high tensile ductility up to 9% tensile strain and tight crack width with 50 μm at 2% tensile strain can be achieved. It was found that a matrix paste with higher viscosity generally enhanced fiber dispersion uniformity and robustness in tensile strain-hardening. The paste viscosity is increased when OPC is replaced by LC3 and can be tuned with superplasticizer content. Larger maximum flaw size leads to lower first crack strength, beneficial for microcrack initiation and multiple cracking. This study generates fundamental knowledge linking processing-microstructure-performance of PP-LC3-ECC. This class of low embodied carbon ECC with tight crack width is expected to contribute to reducing the carbon footprint of the built environment.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Digital Twin for Chemical Science (DTCS) v0.01

Directly visualizing the trajectories of chemistry can unravel novel insights into the behavior of catalysts, gas phase reactions, photo-induced dynamics, and building blocks for quantum information processing. The ability of explicitly identifying, tracking, and tagging the exchange of matter, hence the annihilation and creation of new chemical species, can be best realized through a close coupling of theory and experiment. While the synchrotron-based characterization facilities propelled rapidly in its hardware, providing higher brightness, better resolution, and more precision, the software infrastructure is lagging. We developed DTCS (Digital Twin for Chemical Science) v.01, a central platform that faithfully mimics advanced instrumentations in Scientific User Facilities, by solving a variety of technical challenges in data acquisition, analysis, and model-driven interpretation. Rooted in physics and accelerated by AI, we validated this concept by direct comparison with precise experimental X-ray Photoelectron Spectroscopy (XPS) observations using a ubiquitous metal-water interfacial scenario, i.e., Ag/H2O as our main narrative. The DTCS v.01 input mirrors how the bench chemists work, with the output directly linked to the end station computer, thereby providing a user-friendly, knowledge-driven, and accessible user experience with mechanistic insights standardized in a way that are ready to be published, versioned, and transferred flexibly.

Qian, Jin↗

NASA NTRS2016

Experimenting Galileo on Board the International Space Station

The SCaN Testbed is an advanced integrated communications system and laboratory facility installed on the International Space Station (ISS) in 2012. The testbed incorporates a set of new generation of Software Defined Radio (SDR) technologies intended to allow researchers to develop, test, and demonstrate new communications, networking, and navigation capabilities in the actual environment of space. Qascom, in cooperation with ESA and NASA, is designing a Software Defined Radio GalileoGPS Receiver capable to provide accurate positioning and timing to be installed on the ISS SCaN Testbed. The GalileoGPS waveform will be operated in the JPL SDR that is constituted by several hardware components that can be used for experimentations in L-Band and S-Band. The JPL SDR includes an L-Band Dorne Margolin antenna mounted onto a choke ring. The antenna is connected to a radio front end capable to provide one bit samples for the three GNSS frequencies (L1, L2 and L5) at 38 MHz, exploiting the subharmonic sampling. The baseband processing is then performed by an ATMEL AT697 processor (100 MIPS) and two Virtex 2 FPGAs. The JPL SDR supports the STRS (Space Telecommunications Radio System) that provides common waveform software interfaces, methods of instantiation, operation, and testing among different compliant hardware and software products. The standard foresees the development of applications that are modular, portable, reconfigurable, and reusable. The developed waveform uses the STRS infrastructure-provided application program interfaces (APIs) and services to load, verify, execute, change parameters, terminate, or unload an application. The project is divided in three main phases. 1)Design and Development of the GalileoGPS waveform for the SCaN Testbed starting from Qascom existing GNSS SDR receiver. The baseline design is limited to the implementation of the single frequency Galileo and GPS L1E1 receiver even if as part of the activity it will be to assess the feasibility of a dual frequency implementation (L1E1+L5E5a) in the same SDR platform.2)Qualification and test the GalileoGPS waveform using ground systems available at the NASA Glenn Research Center. Experimenters can have access to two SCaN Testbed ground based systems for development and verification: the Experimenter Development System (EDS) that is intended to provide initial opportunity for software testing and basic functional validation and the Ground Integration Unit (GIU) that is a high fidelity version of the SCaN Testbed flight system and is therefore used for more controlled final development testing and verification testing.3)Perform in-orbit validation and experimentation: The experimentation phase will consists on the collection of raw measurements (pseudorange, Carrier phase, CN0) in space, assessment on the quality of the measurements and the receiver performances in terms of signal acquisition, tracking, etc. Finally computation of positioning in space (Position, Velocity and time) and assessment of its performance.(Complete abstract in attached document).

GPS↗

NASA NTRS2016

Experimenting Galileo on Board the International Space Station

Galileo↗

DOE OSTI2026

Comprehensive framework for assessing and optimizing existing research networks

Conservation, monitoring, and research networks, or collections of ecological research sites unified under a common mission of data collection or a research mission, are essential infrastructure for understanding large landscapes. However, most networks developed opportunistically over decades rather than through systematic design, creating potential limitations in the ability to address conservation challenges across entire regions. We developed a framework to evaluate how well an existing research network represents the environmental conditions its members study and devised an approach to rank sites of priority for strategic expansion. Our approach measures performance through environmental representativeness, geographic coverage, and adequacy for scientific inference and thus optimizes limited monitoring resources to maximize scientific impact. We demonstrated this approach with the U.S. Department of Agriculture (USDA) Forest Service Experimental Forests and Ranges Network (EFRN), a 79‐site network across the United States that grew opportunistically over a century. At the national scale, the network effectively captured high‐biomass forests important for carbon cycle research; 82% of forest biomass was in well‐represented areas. Some areas in Texas, Florida, the Rocky Mountains, and the West Coast had no relevant EFRN sites, which limits the ability to make regional inferences. A fundamental challenge for the EFRN was that sites improving regional extent coverage sometimes provided minimal national benefits, which can create conflicts between local and global priorities. Adding the highest‐ranked candidate site provided a relevant site for 17% of currently poorly represented 1‐km pixel cells nationally, but regional and national site rankings varied considerably due to nested spatial inference. This framework provides quantitative tools for strategic infrastructure decision‐making, ensures that limited monitoring resources maximize conservation impact, and can be applied broadly to address the widespread challenge of optimizing conservation and monitoring networks worldwide.

additional site↗

DOE OSTI2020

Cross-facility science with the Superfacility Project at LBNL

As data sets from DOE user science facilities grow in both size and complexity there is an urgent need for new capabilities to transfer, analyze and manage the data underlying scientific discoveries. LBNL's Superfacility project brings together experimental and observational research instruments with computational and network facilities at the National Energy Research Scientific Computing Center (NERSC) and the Energy Sciences Network (ESnet) with the goal of enabling user science. Here, we report on recent innovations in the Superfacility project, including advanced data management, API-based automation, real-Time interactive user interfaces, and supported infrastructure for 'edge' services.

Enders, B↗

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↗