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At least 217 records · Page 12

Report of the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science

This report summarizes insights from the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science, which convened more than 40 experts from national laboratories, academia, industry, and community organizations to chart a path toward more powerful, sustainable, and collaborative scientific software ecosystems. To address urgent challenges at the intersection of high-performance computing (HPC), AI, and scientific software, participants envisioned agile, robust ecosystems built through socio-technical co-design—the intentional integration of social and technical components as interdependent parts of a unified strategy. This approach combines advances in AI, HPC, and software with new models for cross-disciplinary collaboration, training, and workforce development. Key recommendations include building modular, trustworthy AI-enabled scientific software systems; enabling scientific teams to integrate AI systems into their workflows while preserving human creativity, trust, and scientific rigor; and creating innovative training pipelines that keep pace with rapid technological change. Pilot projects were identified as near-term catalysts, with initial priorities focused on hybrid AI/HPC infrastructure, cross-disciplinary collaboration and pedagogy, responsible AI guidelines, and prototyping of public-private partnerships. This report presents a vision of next-generation ecosystems for scientific computing where AI, software, hardware, and human expertise are interwoven to drive discovery, expand access, strengthen the workforce, and accelerate scientific progress.

97 MATHEMATICS AND COMPUTING↗

Report of the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science

Scientific computing is undergoing rapid transformation as advances in artificial intelligence, heterogeneous computing, automation, and data-intensive research reshape not only computational tools but also the institutions, workforce models, and collaborative practices that support scientific discovery. This report synthesizes insights from the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing, the second in a three-year series focused on strengthening scientific computing ecosystems through socio-technical co-design. Workshop discussions identified four interdependent strategic themes: software ecosystems for AI-enabled scientific discovery; trust, validation, and traceability; human-AI teaming and paradigm shifts; and workforce, pedagogy, and governance. The report translates these themes into eight priorities for community action spanning shared research infrastructure, trust and traceability, user experience, human-AI teaming, workforce development, cross-sector coordination, stewardship and sustainability, and evaluation of scientific value. Together, these priorities outline directions for building scientific computing ecosystems that remain trustworthy, sustainable, innovative, and resilient as AI assumes a growing role in scientific work.

AI↗

Human Automation Teaming: Lessons Learned and Future Directions

Full autonomy seems to be the goal for system developers in almost every area of the economy. However, as we move from automated systems to autonomous systems, designers have needed to insert humans to oversee automation that has traditionally been brittle or incomplete. This creates its own problems as the operator is usually out of the loop when the automation hands over problems that it cannot handle. To better handle these situations, it has been proposed that we develop human automation teams that have shared goals and objectives to support task performance. This paper will describe an initial model of Human Automation Teaming (HAT) which has three elements: transparency, bi-directional communications, and human-directed execution. Transparency in our model is a method for giving insight into the reasoning behind automated recommendations and actions, bi-directional communication allows the operator to communicate directly with the automation, and finally the automation defers execution to the human. The model was implemented through a number of features on an electronic flight bag (EFB) which are described in the paper. The EFB was installed in a mid-fidelity flight simulator and used by 12 airline pilots to support diversion decisions during off-nominal flight scenarios. Pilots reported that working with the HAT automation made diversion decisions easier and reduced their workload. They also reported that the information provided about diversion airports was similar to what they would receive from ground dispatch, thus making coordination with dispatch easier and less time consuming. These HAT features engender more trust in the automation when appropriate, and less when not, allowing improved supervision of automated functions by flight crews.

Human-Autonomy Teaming↗

Problem Complexity and LLM: H-M Team Reliability in Challenging Environments

In traditional human-machine operations, the functional decomposition of actions and responsibilities among various agents is assigned a priori. For instance, in current air traffic operations, although assisted by software, human pilots have the ultimate control of aircraft. Multiagent human-machine and machine-machine systems will face problems of varying and potentially unpredicted complexity in future challenging scenarios of planetary, en route, and orbital activities. Hence, it is important to enable dynamic transfer of decision-making to appropriate team members, human or machine, depending on which agent is best equipped to solve that specific problem on a time budget. In this paper, we consider aspects of problem-solving and its modeling that affect the outcomes of decision-making as a function of solution quality and the likelihood of solving the problem on a required time budget. We focus on Large Language Models (LLM) as potential machine teammates and conclude that practical, predictive modeling of their performance, at the current stage of their development, is infeasible. Simple examples help us illustrate that current LLM will require fundamental advancements to provide reliable support in team decision-making, especially in safety-critical and time-critical domains. The study is not meant to diminish the value of the remarkable capabilities of LLM, but rather to gain a better understanding of the technology’s appropriate use and the needed additions.

function allocation↗

Dynamic Charging Rendezvous and Motion Planning for a Multi-AGV Team Including a Mobile Charging Host

Teams of automated battery-powered electric vehicles have the potential to execute complex mission tasks in off-road environments for agriculture, military, and other applications. Limited onboard energy reserves hinder their adoption in large-scale resource-constrained environments, where recharging is a necessity. It may be infeasible to install a network of static charging stations in off-road environments. For this reason, dedicated mobile host vehicles with charging capabilities are proposed as a means to increase range and capabilities of the multivehicle team. Here, in this study, we consider an ad hoc planning framework, where results from a high-confidence trajectory planner are leveraged to plan charging rendezvous between a host and other worker vehicles in a receding horizon fashion to provide high confidence that energy reserves will not be prematurely exhausted. The core problem is posed so as to minimize the impact of recharging on the mission in terms of task delays, overall energy utilization, and costs of fast charging. Through extensive Monte Carlo simulations of an off-road mission, we show a decrease in task delays without substantial increases in energy needs by updating the charging rendezvous plan during the mission. However, if updates are made too often, model mismatch may cause unnecessary cycling and mission failure.

Energy constraints↗

Towards Exascale Astrophysics of Mergers and Supernovae (TEAMS)

The TEAMS project brought together cutting-edge simulations, theoretical insights, and collaborative efforts to deepen our understanding of some of the universe’s most extreme phenomena—supernovae, neutron star mergers, and the powerful signals they emit. Using one of the largest suites of 3D supernova simulations ever conducted, researchers uncovered new insights into how massive stars explode, how those explosions vary by stellar mass, and what conditions lead to the birth of neutron stars or black holes. They also studied the radiation and gravitational wave signals emitted during these events, revealing how future observations can be used to uncover what happens deep inside collapsing stars. The team developed improved tools for modeling how light and neutrinos behave in such explosive environments, enabling more accurate predictions of what astronomers might observe. Work also explored how the chemical composition and geometry of kilonovae—the visible explosions that follow neutron star mergers—influence their signals and can reveal the origins of heavy elements like gold. These efforts not only advanced scientific knowledge, but also trained a new generation of researchers at the intersection of astrophysics, computational science, and nuclear theory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Fermilab 2025 Summer Internship: Repairing Pre-Amplifiers with Mu2e Electronics Installation Team

The author spent nine weeks over summer 2025 working on the tracker electronics installation team for the Mu2e experiment. One of her main responsibilities was repairing high voltage (HV) and calibration (Cal) pre-amplifiers (pre-amps). During installation, the fragile wires connecting the two sockets to the pre-amp board must be bent, often leading to breakage. During production, the sockets and wires were initially soldered to the board at UC Berkely, then the whole pre-amp was coated in parylene before transport to Fermilab. The interns were able to expedite the repairs, and thus whole installation process, by using an alternative method on-site with epoxy. Another task they were responsible for, not included in the original project specifications, was attaching copper clips to specific vias on the Cals to reduce noise. The talk will give listeners insight into the daily problem-solving required by the novel technologies in the Mu2e project. The author would like to acknowledge her fellow Monmouth College undergraduate interns, Lizzie Durfee and Gianna Maughan, advisor and PI of the DOE RENEW Grant Dr. Christopher G. Fasano, and the Mu2e team lead by co-spokesperson Dr. Bob Bernstein and tracker L2 manager Dr. Brendan Kiburg.

de Zwart, Bronte [Monmouth Coll.]↗

Setting Priorities: A Process Improvement Study to Achieve Greater Team Efficiency.

This report details a comprehensive process improvement study designed to optimize team efficiency and strategic focus within an Identity and Access Management (IAM) technical unit at Los Alamos National Laboratory (LANL). Faced with a high volume of operational support and a fragmented project landscape, the team experienced "capacity fatigue" and delivery times extending into years.

99 GENERAL AND MISCELLANEOUS↗

Astronomical activities of the Apollo orbital science photographic team

A partial accounting of Apollo Orbital Science Photographic Team (APST) work is presented as reported by one of its members who provided scientific recommendations for, guidance in, and reviews of photography in astronomy. Background on the formation of the team and its functions and management are discussed. It is concluded that the APST clearly performed the overall objective for which it was established - to improve the scientific value of the Apollo lunar missions. Specific reasons for this success are given.

Mercer, R. D.↗

Viking lander: Creating the science teams

The teams of scientists and the contractors involved in designing and fabricating the Viking lander spacecraft for Mars exploration are discussed. The requirements established for each member of the research teams are enumerated and the personnel selection process is described. Two instruments for the lander, a gas chromatograph-mass spectrometer and a biology life detection instrument, are addressed in terms of costs, design, planning, and subcontractors. The challenges and ultimate success of the research management efforts are related in detail.

Source record↗

An experimental paradigm for team decision processes

The study of distributed information processing and decision making is presently hampered by two factors: (1) The inherent complexity of the mathematical formulation of decentralized problems has prevented the development of models that could be used to predict performance in a distributed environment; and (2) The lack of comprehensive scientific empirical data on human team decision making has hindered the development of significant descriptive models. As a part of a comprehensive effort to find a new framework for multihuman decision making problems, a novel experimental research paradigm was developed involving human terms in decision making tasks. Attempts to construct parts of an integrated model with ideas from queueing networks, team theory, distributed estimation and decentralized resource management are described.

Serfaty, D.↗

Aeroelastic modeling for the FIT team F/A-18 simulation

Some details of the aeroelastic modeling of the F/A-18 aircraft done for the Functional Integration Technology (FIT) team's research in integrated dynamics modeling and how these are combined with the FIT team's integrated dynamics model are described. Also described are mean axis corrections to elastic modes, the addition of nonlinear inertial coupling terms into the equations of motion, and the calculation of internal loads time histories using the integrated dynamics model in a batch simulation program. A video tape made of a loads time history animation was included as a part of the oral presentation. Also discussed is work done in one of the areas of unsteady aerodynamic modeling identified as needing improvement, specifically, in correction factor methodologies for improving the accuracy of stability derivatives calculated with a doublet lattice code.

Zeiler, Thomas A.↗

Aeroelastic modeling for the FIT (Functional Integration Technology) team F/A-18 simulation

As part of Langley Research Center's commitment to developing multidisciplinary integration methods to improve aerospace systems, the Functional Integration Technology (FIT) team was established to perform dynamics integration research using an existing aircraft configuration, the F/A-18. An essential part of this effort has been the development of a comprehensive simulation modeling capability that includes structural, control, and propulsion dynamics as well as steady and unsteady aerodynamics. The structural and unsteady aerodynamics contributions come from an aeroelastic mode. Some details of the aeroelastic modeling done for the Functional Integration Technology (FIT) team research are presented. Particular attention is given to work done in the area of correction factors to unsteady aerodynamics data.

Zeiler, Thomas A.↗

Possible misinterpretation of lunar cratering record in Voyager team analyses of outer planet satellites

While interpreting outer planetary satellites, the Voyager imaging team repeatedly referred to a lunar frontside highland calibration curve. It was assumed that it is unmodified and not in steady state equilibrium, but rather records all impacts that have occurred. It was also assumed that it records the size distribution of an early population of impactors, called Population I, evidence for which was found on various satellites. New evidence is reported that the Voyager team interpretation of this population is wrong, a conclusion that seriously affects the cratering histories reported for outer planet satellites.

Hartmann, William K.↗

Making intelligent systems team players: Overview for designers

This report is a guide and companion to the NASA Technical Memorandum 104738, 'Making Intelligent Systems Team Players,' Volumes 1 and 2. The first two volumes of this Technical Memorandum provide comprehensive guidance to designers of intelligent systems for real-time fault management of space systems, with the objective of achieving more effective human interaction. This report provides an analysis of the material discussed in the Technical Memorandum. It clarifies what it means for an intelligent system to be a team player, and how such systems are designed. It identifies significant intelligent system design problems and their impacts on reliability and usability. Where common design practice is not effective in solving these problems, we make recommendations for these situations. In this report, we summarize the main points in the Technical Memorandum and identify where to look for further information.

Malin, Jane T.↗

A status of the activities of the NASA. Marshall Space Flight Center Combustion Devices Technology Team

The Consortium for Computational Fluid Dynamics (CFD) Applications in Propulsion Technology was established to focus on computational fluid dynamics applications in propulsion. Specific areas of effort include developing the CFD technology required to address rocket propulsion issues, validating the technology, and applying the validated technology to design problems. The Combustion Devices Technology Team was formed to implement the above objectives in the broad area of combustion driven flows. In an effort to bring CFD to bear in the design environment, the team has focused its efforts on the Space Transportation Main Engine nozzle. The main emphasis has been on the film cooling scheme used to cool the nozzle wall. Benchmark problems have been chosen to validate CFD film cooling capabilities. CFD simulations of the subscale nozzle have been made. Also, CFD predictions of the base flow resulting from this type of nozzle have been made. The status of these calculations is presented along with future plans. Information is given in viewgraph form.

Tucker, Kevin↗

Turbine Technology Team - An overview of current and planned activities relevant to the National Launch System (NLS)

The current status of the activities and future plans of the Turbine Technology Team of the Consortium for Computational Fluid Dynamics is reviewed. The activities of the Turbine Team focus on developing and enhancing codes and models, obtaining data for code validation and general understanding of flows through turbines, and developing and analyzing the aerodynamic designs of turbines suitable for use in the Space Transportation Main Engine fuel and oxidizer turbopumps. Future work will include the experimental evaluation of the oxidizer turbine configuration, the development, analysis, and experimental verification of concepts to control secondary and tip losses, and the aerodynamic design, analysis, and experimental evaluation of turbine volutes.

Griffin, Lisa W.↗