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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↗

Monitoring robot actions for error detection and recovery

Reliability is a serious problem in computer controlled robot systems. Although robots serve successfully in relatively simple applications such as painting and spot welding, their potential in areas such as automated assembly is hampered by programming problems. A program for assembling parts may be logically correct, execute correctly on a simulator, and even execute correctly on a robot most of the time, yet still fail unexpectedly in the face of real world uncertainties. Recovery from such errors is far more complicated than recovery from simple controller errors, since even expected errors can often manifest themselves in unexpected ways. Here, a novel approach is presented for improving robot reliability. Instead of anticipating errors, researchers use knowledge-based programming techniques so that the robot can autonomously exploit knowledge about its task and environment to detect and recover from failures. They describe preliminary experiment of a system that they designed and constructed.

Gini, M.↗

Characterization of fluid physics effects on cardiovascular response to microgravity (G-572)

The recognition and understanding of cardiovascular adaptation to spaceflight has experienced substantial advancement in the last several years. In-flight echocardiographic measurements of astronaut cardiac function on the Space Shuttle have documented a 15 percent reduction in both left ventricular volume index and stroke volume with a compensatory increase in heart rate to maintain cardiac output. To date, the reduced cardiac size and stroke volume have been presumed to be the consequence of the reduction in circulating fluid volume following diuresis and other physiological processes to reduce blood volume within a few days after orbital insertion. However, no specific mechanism for the reduced stroke volume has been elucidated. The following investigation proposes the use of a hydraulic model of the cardiovascular system to examine the possibility that the observed reduction in stroke volume may, in part, be related to fluid physics effects on heart function. The automated model is being prepared to fly as a GAS payload. The experimental apparatus consists of a pneumatically actuated, elliptical artificial ventricle connected to a closed-loop, hydraulic circuit with compliance and resistance elements to create physiologic pressure and flow conditions. The ventricle is instrumented with high-fidelity, acceleration-insensitive, catheter-tip pressure transducers (Millar Instruments) in the apex and base to determine the instantaneous ventricular pressures and (delta)P(sub LV) across the left ventricle (LVP(sub apex)-LVP(sub base). The ventricle is also instrumented with a flow probe and pressure transducers immediately upstream of the inflow valve and downstream of the outflow valve. The experiment will be microprocessor controlled with analog signals stored on the FM data tape recorder. By varying the circulating fluid volume, ventricular function can be determined for varying preload pressures with fixed afterload pressure. Pilot experiments on board the NASA KC-135 aircraft have demonstrated proof-of-concept and provided early support for the proposed hypothesis. A review of the pilot experiments and developmental progress on the GAS version of this experiment will be presented.

Pantalos, George M.↗

Mild Normobaric Hypoxia Exposure for Human-Autonomy System Testing

An experiment investigated the impact of normobaric hypoxia induction on aircraft pilot performance to specifically evaluate the use of hypoxia as a method to induce mild cognitive impairment to explore human-autonomous systems integration opportunities. Results of this exploratory study show that the effect of 15,000 feet simulated altitude did not induce cognitive deficits as indicated by performance on written, computer-based, or simulated flight tasks. However, the subjective data demonstrated increased effort by the human test subject pilots to maintain equivalent performance in a flight simulation task. This study represents current research intended to add to the current knowledge of performance decrement and pilot workload assessment to improve automation support and increase aviation safety.

Stephens, Chad L.↗

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗

Understanding Crew Decision-Making in the Presence of Complexity: A Flight Simulation Experiment

Crew decision making and response have long been leading causal and contributing factors associated with aircraft accidents. Further, it is anticipated that future aircraft and operational environments will increase exposure to risks related to these factors if proactive steps are not taken to account for ever-increasing complexity. A flight simulation study was designed to collect data to help in understanding how complexity can, or may, be manifest. More specifically, an experimental apparatus was constructed that allowed for manipulation of information complexity and uncertainty, while also manipulating operational complexity and uncertainty. Through these manipulations, and the aid of experienced airline pilots, several issues have been discovered, related most prominently to the influence of information content, quality, and management. Flight crews were immersed in an environment that included new operational complexities suggested for the future air transportation system as well as new technological complexities (e.g. electronic flight bags, expanded data link services, synthetic and enhanced vision systems, and interval management automation). In addition, a set of off-nominal situations were emulated. These included, for example, adverse weather conditions, traffic deviations, equipment failures, poor data quality, communication errors, and unexpected clearances, or changes to flight plans. Each situation was based on one or more reference events from past accidents or incidents, or on a similar case that had been used in previous developmental tests or studies. Over the course of the study, 10 twopilot airline crews participated, completing over 230 flights. Each flight consisted of an approach beginning at 10,000 ft. Based on the recorded data and pilot and research observations, preliminary results are presented regarding decision-making issues in the presence of the operational and technological complexities encountered during the flights.

Young, Steven D.↗

Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research

Introduction The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped. Methods To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Results Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. Discussion We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Genetics & Heredity↗

Accelerating discoveries at DIII-D with the Integrated Research Infrastructure

DIII-D research is being accelerated by leveraging high performance computing (HPC) and data resources available through the National Energy Research Scientific Computing Center (NERSC) Superfacility initiative. As part of this initiative, a high-resolution, fully automated, whole discharge kinetic equilibrium reconstruction workflow was developed that runs at the NERSC for most DIII-D shots in under 20 min. This has eliminated a long-standing research barrier and opened the door to more sophisticated analyses, including plasma transport and stability. These capabilities would benefit from being automated and executed within the larger Department of Energy Advanced Scientific Computing Research program’s Integrated Research Infrastructure (IRI) framework. The goal of IRI is to empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation. For transport, we are looking at producing flux matched profiles and also using particle tracing to predict fast ion heat deposition from neutral beam injection before a shot takes place. Our starting point for evaluating plasma stability focuses on the pedestal limits that must be navigated to achieve better confinement. This information is meant to help operators run more effective experiments, so it needs to be available rapidly inside the DIII-D control room. So far this has been achieved by ensuring the data is available with existing tools, but as more novel results are produced new visualization tools must be developed. In addition, all of the high-quality data we have generated has been collected into databases that can unlock even deeper insights. This has already been leveraged for model and code validation studies as well as for developing AI/ML surrogates. The workflows developed for this project are intended to serve as prototypes that can be replicated on other experiments and can be run to provide timely and essential information for ITER, as well as next stage fusion power plants.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Generation and exploration of aggregation abstractions for scheduling and resource allocation

This paper presents research on the abstraction of computational theories for scheduling and resource allocation. The paper describes both theory and methods for the automated generation of aggregation abstractions and approximations in which detailed resource allocation constraints are replaced by constraints between aggregate demand and capacity. The interaction of aggregation abstraction generation with the more thoroughly investigated abstractions of weakening operator preconditions is briefly discussed. The purpose of generating abstract theories for aggregated demand and resources includes: answering queries about aggregate properties, such as gross feasibility; reducing computational costs by using the solution of aggregate problems to guide the solution of detailed problems; facilitating reformulating theories to approximate problems for which there are efficient problem-solving methods; and reducing computational costs of scheduling by providing more opportunities for variable and value-ordering heuristics to be effective. Experiments are being developed to characterize the properties of aggregations that make them cost effective. Both abstract and concrete theories are represented in a variant of first-order predicate calculus, which is a parameterized multi-sorted logic that facilitates specification of large problems. A particular problem is conceptually represented as a set of ground sentences that is consistent with a quantified theory.

Lowry, Michael R.↗

Drug providers’ perspectives on antibiotic misuse practices in eastern Ethiopia: a qualitative study

Objective Antibiotic misuse includes using them to treat colds and influenza, obtaining them without a prescription, not finishing the prescribed course and sharing them with others. Although drug providers are well positioned to advise clients on proper stewardship practices, antibiotic misuse continues to rise in Ethiopia. It necessitates an understanding of why drug providers failed to limit such risky behaviours. This study aimed to explore drug providers’ perspectives on antibiotic misuse practices in eastern Ethiopia. Setting The study was conducted in rural Haramaya district and Harar town, eastern Ethiopia. Design and participants An exploratory qualitative study was undertaken between March and June 2023, among the 15 drug providers. In-depth interviews were conducted using pilot-tested, semistructured questions. The interviews were transcribed verbatim, translated into English and analysed thematically. The analyses considered the entire dataset and field notes. Results The study identified self-medication pressures, non-prescribed dispensing motives, insufficient regulatory functions and a lack of specific antibiotic use policy as the key contributors to antibiotic misuse. We found previous usage experience, a desire to avoid extra costs and a lack of essential diagnostics and antibiotics in public institutions as the key drivers of non-prescribed antibiotic access from private drug suppliers. Non-prescribed antibiotic dispensing in pharmacies was driven by client satisfaction, financial gain, business survival and market competition from informal sellers. Antibiotic misuse in the setting has also been linked to traditional and ineffective dispensing audits, inadequate regulatory oversights and policy gaps. Conclusion This study highlights profits and oversimplified access to antibiotics as the main motivations for their misuse. It also identifies the traditional antibiotic dispensing audit as an inefficient regulatory operation. Hence, enforcing specific antibiotic usage policy guidance that entails an automated practice audit, a responsible office and insurance coverage for persons with financial limitations can help optimise antibiotic use while reducing resistance consequences.

General & Internal Medicine↗

An architecture and model for cognitive engineering simulation analysis - Application to advanced aviation automation

The process of designing crew stations for large-scale, complex automated systems is made difficult because of the flexibility of roles that the crew can assume, and by the rapid rate at which system designs become fixed. Modern cockpit automation frequently involves multiple layers of control and display technology in which human operators must exercise equipment in augmented, supervisory, and fully automated control modes. In this context, we maintain that effective human-centered design is dependent on adequate models of human/system performance in which representations of the equipment, the human operator(s), and the mission tasks are available to designers for manipulation and modification. The joint Army-NASA Aircrew/Aircraft Integration (A3I) Program, with its attendant Man-machine Integration Design and Analysis System (MIDAS), was initiated to meet this challenge. MIDAS provides designers with a test bed for analyzing human-system integration in an environment in which both cognitive human function and 'intelligent' machine function are described in similar terms. This distributed object-oriented simulation system, its architecture and assumptions, and our experiences from its application in advanced aviation crew stations are described.

Corker, Kevin M.↗

Automated Rendezvous and Capture System Development and Simulation for NASA

The United States does not have an Automated Rendezvous and Capture Docking (AR&C) capability and is reliant on manned control for rendezvous and docking of orbiting spacecraft. T h i s reliance on the labor intensive manned interface for control of rendezvous and docking vehicles has a significant impact on the cost of the operation of the International Space Station (ISS) and precludes the use of any U.S. expendable launch capabilities for Space Station resupply. The Marshall Space Flight Center (MSFC) has conducted pioneering research in the development of an automated rendezvous and capture (or docking) (AR&C) system for U.S. space vehicles. This A M C system was tested extensively using hardware-in-the-loop simulations in the Flight Robotics Laboratory, and a rendezvous sensor, the Video Guidance Sensor was developed and successfully flown on the Space Shuttle on flights STS-87 and STS-95, proving the concept of a video- based sensor. Further developments in sensor technology and vehicle and target configuration have lead to continued improvements and changes in AR&C system development and simulation. A new Advanced Video Guidance Sensor (AVGS) with target will be utilized as the primary navigation sensor on the Demonstration of Autonomous Rendezvous Technologies (DART) flight experiment in 2004. Realtime closed-loop simulations will be performed to validate the improved AR&C systems prior to flight.

Roe, Fred D.↗

Real-time three-dimensional color doppler evaluation of the flow convergence zone for quantification of mitral regurgitation: Validation experimental animal study and initial clinical experience

BACKGROUND: Pitfalls of the flow convergence (FC) method, including 2-dimensional imaging of the 3-dimensional (3D) geometry of the FC surface, can lead to erroneous quantification of mitral regurgitation (MR). This limitation may be mitigated by the use of real-time 3D color Doppler echocardiography (CE). Our objective was to validate a real-time 3D navigation method for MR quantification. METHODS: In 12 sheep with surgically induced chronic MR, 37 different hemodynamic conditions were studied with real-time 3DCE. Using real-time 3D navigation, the radius of the largest hemispherical FC zone was located and measured. MR volume was quantified according to the FC method after observing the shape of FC in 3D space. Aortic and mitral electromagnetic flow probes and meters were balanced against each other to determine reference MR volume. As an initial clinical application study, 22 patients with chronic MR were also studied with this real-time 3DCE-FC method. Left ventricular (LV) outflow tract automated cardiac flow measurement (Toshiba Corp, Tokyo, Japan) and real-time 3D LV stroke volume were used to quantify the reference MR volume (MR volume = 3DLV stroke volume - automated cardiac flow measurement). RESULTS: In the sheep model, a good correlation and agreement was seen between MR volume by real-time 3DCE and electromagnetic (y = 0.77x + 1.48, r = 0.87, P <.001, delta = -0.91 +/- 2.65 mL). In patients, real-time 3DCE-derived MR volume also showed a good correlation and agreement with the reference method (y = 0.89x - 0.38, r = 0.93, P <.001, delta = -4.8 +/- 7.6 mL). CONCLUSIONS: real-time 3DCE can capture the entire FC image, permitting geometrical recognition of the FC zone geometry and reliable MR quantification.

Validation Studies↗

Space flight manipulator technologies and requirements for the NASA Flight Telerobotic Servicer (FTS)

NASA Headquarters' Office of Advanced Concepts and Technology (OACT) joined efforts with Johnson Space Center's (JSC) Automation and Robotics Division and Langley Research Center's (LaRC) Information Systems Division to capture the technologies developed during the cancelled NASA Flight Telerobotic Servicer (FTS) program planned for use on Space Station Freedom. The recent FTS technology capture effort completed the build and testing of one flight qualifiable FTS manipulator, deliverable to JSC's Automation & Robotics Division for environmental testing. The many robotic technologies developed to meet the 30 year space environment design requirements are discussed in this paper. The manipulator properties were to allow positioning control to one thousandths of an inch, with zero actuator backlash over a temperature range of -50 to +95 C, and were to include impedance control and inertial decoupling. Safety and reliability requirements are discussed that were developed to allow a thirty year life in space with minimum maintenance. The system had to meet the safety requirements for hazardous payloads for operation in the shuttle payload bay during demonstration test flights prior to station use. A brief description is contained on an orbiter based robotic experiment and operational application using the dexterous FTS manipulator operating on the end of the shuttle remote manipulator systems (SRMS) from ground control.

Chladek, John T.↗

An Overview of SAL

To become practical for assurance, automated formal methods must be made more scalable, automatic, and cost-effective. Such an increase in scope, scale, automation, and utility can be derived from an emphasis on a systematic separation of concerns during verification. SAL (Symbolic Analysis Laboratory) attempts to address these issues. It is a framework for combining different tools to calculate properties of concurrent systems. The heart of SAL is a language, developed in collaboration with Stanford, Berkeley, and Verimag for specifying concurrent systems in a compositional way. Our instantiation of the SAL framework augments PVS with tools for abstraction, invariant generation, program analysis (such as slicing), theorem proving, and model checking to separate concerns as well as calculate properties (i.e., perform, symbolic analysis) of concurrent systems. We. describe the motivation, the language, the tools, their integration in SAL/PAS, and some preliminary experience of their use.

Bensalem, Saddek↗

Automated Antenna Design with Evolutionary Algorithms

Current methods of designing and optimizing antennas by hand are time and labor intensive, and limit complexity. Evolutionary design techniques can overcome these limitations by searching the design space and automatically finding effective solutions. In recent years, evolutionary algorithms have shown great promise in finding practical solutions in large, poorly understood design spaces. In particular, spacecraft antenna design has proven tractable to evolutionary design techniques. Researchers have been investigating evolutionary antenna design and optimization since the early 1990s, and the field has grown in recent years as computer speed has increased and electromagnetic simulators have improved. Two requirements-compliant antennas, one for ST5 and another for TDRS-C, have been automatically designed by evolutionary algorithms. The ST5 antenna is slated to fly this year, and a TDRS-C phased array element has been fabricated and tested. Such automated evolutionary design is enabled by medium-to-high quality simulators and fast modern computers to evaluate computer-generated designs. Evolutionary algorithms automate cut-and-try engineering, substituting automated search though millions of potential designs for intelligent search by engineers through a much smaller number of designs. For evolutionary design, the engineer chooses the evolutionary technique, parameters and the basic form of the antenna, e.g., single wire for ST5 and crossed-element Yagi for TDRS-C. Evolutionary algorithms then search for optimal configurations in the space defined by the engineer. NASA's Space Technology 5 (ST5) mission will launch three small spacecraft to test innovative concepts and technologies. Advanced evolutionary algorithms were used to automatically design antennas for ST5. The combination of wide beamwidth for a circularly-polarized wave and wide impedance bandwidth made for a challenging antenna design problem. From past experience in designing wire antennas, we chose to constrain the evolutionary design to a monopole wire antenna. The results of the runs produced requirements-compliant antennas that were subsequently fabricated and tested. The evolved antenna has a number of advantages with regard to power consumption, fabrication time and complexity, and performance. Lower power requirements result from achieving high gain across a wider range of elevation angles, thus allowing a broader range of angles over which maximum data throughput can be achieved. Since the evolved antenna does not require a phasing circuit, less design and fabrication work is required. In terms of overall work, the evolved antenna required approximately three person-months to design and fabricate whereas the conventional antenna required about five. Furthermore, when the mission was modified and new orbital parameters selected, a redesign of the antenna to new requirements was required. The evolutionary system was rapidly modified and a new antenna evolved in a few weeks. The evolved antenna was shown to be compliant to the ST5 mission requirements. It has an unusual organic looking structure, one that expert antenna designers would not likely produce. This antenna has been tested, baselined and is scheduled to fly this year. In addition to the ST5 antenna, our laboratory has evolved an S-band phased array antenna element design that meets the requirements for NASA's TDRS-C communications satellite scheduled for launch early next decade. A combination of fairly broad bandwidth, high efficiency and circular polarization at high gain made for another challenging design problem. We chose to constrain the evolutionary design to a crossed-element Yagi antenna. The specification called for two types of elements, one for receive only and one for transmit/receive. We were able to evolve a single element design that meets both specifications thereby simplifying the antenna and reducing testing and integration costs. The highest performance antenna found using a getic algorithm and stochastic hill-climbing has been fabricated and tested. Laboratory results correspond well with simulation. Aerospace component design is an expensive and important step in space development. Evolutionary design can make a significant contribution wherever sufficiently fast, accurate and capable software simulators are available. We have demonstrated successful real-world design in the spacecraft antenna domain; and there is good reason to believe that these results could be replicated in other design spaces.

Hornby, Gregory S.↗

Community Coordinated Modeling Center: Addressing Needs of Operational Space Weather Forecasting

Models are key elements of space weather forecasting. The Community Coordinated Modeling Center (CCMC, http://ccmc.gsfc.nasa.gov) hosts a broad range of state-of-the-art space weather models and enables access to complex models through an unmatched automated web-based runs-on-request system. Model output comparisons with observational data carried out by a large number of CCMC users open an unprecedented mechanism for extensive model testing and broad community feedback on model performance. The CCMC also evaluates model's prediction ability as an unbiased broker and supports operational model selections. The CCMC is organizing and leading a series of community-wide projects aiming to evaluate the current state of space weather modeling, to address challenges of model-data comparisons, and to define metrics for various user s needs and requirements. Many of CCMC models are continuously running in real-time. Over the years the CCMC acquired the unique experience in developing and maintaining real-time systems. CCMC staff expertise and trusted relations with model owners enable to keep up to date with rapid advances in model development. The information gleaned from the real-time calculations is tailored to specific mission needs. Model forecasts combined with data streams from NASA and other missions are integrated into an innovative configurable data analysis and dissemination system (http://iswa.gsfc.nasa.gov) that is accessible world-wide. The talk will review the latest progress and discuss opportunities for addressing operational space weather needs in innovative and collaborative ways.

Kuznetsova, M.↗

GUI Control System for the Mu2e Electrostatic Septum High Voltage at Fermilab

The Mu2e Experiment has stringent beam structure requirements; namely, its proton bunches with a time structure of 1.7 $\mu$s in the Fermilab Delivery Ring. This beam structure will be delivered using the Fermilab 8-GeV Booster, the 8-GeV Recycler Ring, and the Delivery Ring. The 1.7-$\mu$s period of the Delivery Ring will generate the required beam structure by means of a third order resonant extraction system operating on a single circulating bunch. The electrostatic septum (ESS) for this system is particularly challenging, requiring mechanical precision in a ultra high vacuum of 1 x 10$^-8$ Torr to generate 100 kV across 15 mm. This paper describes a graphical user interface that has been developed to automate the conditioning and commissioning process for the electrostatic septa. It is based on an interface to the Fermilab ACNET system using the ACSys Python Data Pool Manager (DPM) Client produced and maintained by Fermilab Accelerator Controls. Network interfacing between data pool managers made by the application and ACNET devices introduce an inherent (approximately 1 s) latency in throughput of the readouts. This delay is utilized to process and graph incoming data events of devices crucial to conditioning of a electrostatic septum (ESS). 'Ramping' and 'Monitoring' modes adjust settings of the power supply based on internal logic to efficaciously increase and maintain the high voltage (HV) in the ESS, easing the voltage setting on incidence of sparking or other possibly damaging events. A timestamped log file is produced as the application runs.

43 PARTICLE ACCELERATORS↗