Results for “RuN” — Page 81

NASA NTRSDate not supplied

High-Enthalpy Testing to Validate Simulation of an Aerosol Capture Probe

AERACEPT (Aerosol Rapid Analysis Combined Entry Probe/sonde Technology) is a developing technology enabling in-situ aerosol particle sampling and analysis in a small spacecraft mission envelope. It integrates a passive aerosol sample collection system into a probe’s thermal protection system (TPS) to remove the need for heat shield separation and active descent control (parachutes, gliders, etc.). AERACEPT is being validated against the requirements of the Nephele mission concept, which targets the middle and lower Venus cloud layers. The proposed technology employs 3D Carbon-Carbon (3D-CC) at the probe’s nose to withstand the extreme environments encountered in a Venus entry without producing pyrolysis gases that would contaminate the mission sample collection. Any shape change of this 3D-CC sample inlet will affect airflow through the sampling system, thereby impacting aerosol sample collection bias and efficiency. Accurate prediction of the nose’s material response during entry is there-fore of fundamental importance to the development and practical use of this technology. As a result, the AERACEPT project is planning a test campaign in the newly built PlasmatronX facility with a novel “Open Iso-Q” test article to validate state-of-the-art material response tools for a simulated Venus entry. The PlasmatronX is a 350 kW inductively-coupled plasma facility developed and run by the Center for Hypersonics and Entry Systems Studies at the University of Illinois at Urbana-Champaign. The facility can support ground testing for a variety of planetary destinations by simulating entry conditions in Nitrogen, Air, and Carbon Dioxide. To best simulate the Venus atmosphere and match flight-like recession, the planned AERACEPT test campaign will use Carbon Dioxide as its test gas. AERACEPT has designed two test articles for this campaign: 1) a standard test article whose curved surface approximates a constant applied heat flux (“Closed Iso-Q” model) and 2) a novel inlet test article with a through-hole at the stagnation point (“Open Iso-Q” model). Both article types consist of a 3D-CC sample bonded to a graphite fixture. All articles will be laser scanned before and after testing to estimate shape change and recession, and the “Closed Iso-Q” articles will be instrumented with thermocouples to provide temperature histories. The test article temperatures and inlet shape change will be compared against simulations run with the Porous material Analysis Toolbox based on OpenFOAM (PATO) to validate the AERACEPT 3D-CC material response model. Due to the high thermal conductivity of 3D-CC, multidimensional effects have a large influence on the test article temperature and the standard 1-D material response tools are not sufficient for test planning. The test campaign features (e.g. article design, run duration, heat fluxes) are therefore informed by a series of 3-D simulations using state-of-the-art material response tools such as PATO. The test campaign is scheduled for spring of 2024. Expected results include 1) Key drivers of selected test conditions (e.g. matching mission flight atmosphere & recession), 2) Simulation results that informed test article design, 3) Acquired test data such as recession measurements, temperature histories, and photos, and 4) Comparisons between test results and simulation predictions.

AERACEPT↗

NASA NTRSDate not supplied

Tracking Magnetic Perturbations, dB/dt and Geomagnetic Indices for Geospace Storms on a Routine Basis at the CCMC

The first comprehensive assessment of geospace model skill to specify magnetic perturbations (delta-B) on the ground and their time derivative (dB/dt) was performed at the Community Coordinated Modeling Center starting in 2010. This study resulted in the addition of the Space Weather Modling Framework to the suite of operational models run by the NOAA Space Weather Prediction Center (SWPC). Since then, magnetic pertubations have been made available on a larger scale for Run-on-Request simulations in geospace at the CCMC. We will demonstrate recent additions to the suite of analysis tools and model results including magnetic perturbations at more stations and on a grid of positions from both, original model outputs (SWMF using preset run configurations) and post-processed calculations using CalcDeltaB and their analysis and visualization using the open-source Kamodo data access and analysis suite and the Comprehensive Assessment of Models and Events using Library tools (CAMEL) application.

Lutz Rastaetter↗

NASA NTRSDate not supplied

Evaluating the Trustworthiness of Deep Neural Networks in Deployment – A Comparative Study (Replicability Study)

As deep neural networks (DNNs) are increasingly used in safety critical applications, there is a growing concern for their trustworthiness. Even highly trained, high-performant networks are not 100% accurate. However, it is very difficult to predict their behaviour during deployment without ground truth. In this paper, we provide a comparative and replicability study on recent approaches that have been proposed to evaluate the trustworthiness of DNNs. We find that it is very difficult to run and reproduce the results for these approaches on their replication packages, and it is even more difficult to run the tools on artifacts other than their own. Further, it is difficult to compare the effectiveness of the tools, due to lack of clearly defined evaluation metrics. Our results indicate that more effort is needed in our research community to obtain sound techniques for evaluating the trustworthiness of neural networks in safety-critical domains. To this end, we contribute an evaluation framework that incorporates the considered approaches and enables evaluation on common benchmarks, using common metrics. Using this framework, we run a comparative study of the three approaches.

Trustworthy AI↗

NASA NTRSDate not supplied

Open Science Practices at the Community Coordinated Modeling Center

Open Science is defined as “the principle and practice of making research products and processes available to all, while respecting diverse cultures, maintaining security and privacy, and fostering collaborations, reproducibility, and equity” by Federal Agencies. The CCMC has been practicing open science based on FAIR (Findable, Accessible, Interoperable and Reusable) principle by providing access to the state-of -the art space science and space weather models to users around the world through various simulation services such as Runs-on-Request, Instant Runs, Real time runs on iSWA system. The CCMC also provides a wide range of tools and framework to help users easily utilize modeled data. One of the tools is the official NASA open-sourced software called Kamodo. Kamodo allows users to work with complex space weather models and data with little or no coding experience. Additionally, to support transparent model validation efforts, the CCMC is providing an integrated and flexible framework called CAMEL. CAMEL allows users to seamlessly compare model outputs with observational data sets. Currently, we are working on a user-friendly database of the papers and research that used CCMC services, so that the future users will have open access to previously performed research by other users and its details. In this presentation, we will show the open tools and resources provided by the CCMC. Furthermore, we will share our new efforts to support open data and open science results.

Ja Soon Shim↗

NASA NTRSDate not supplied

High-Enthalpy Testing to Validate Simulation of an Aerosol Capture Probe

AERACEPT (Aerosol Rapid Analysis Combined Entry Probe/sonde Technology) is a developing technology enabling in-situ aerosol particle sampling and analysis in a small spacecraft mission envelope. It integrates a passive aerosol sample collection system into a probe’s thermal protection system (TPS) to remove the need for heat shield separation and active descent control (parachutes, gliders, etc.). AERACEPT is being validated against the requirements of the Nephele mission concept, which targets the middle and lower Venus cloud layers. The proposed technology employs 3D Carbon-Carbon (3D-CC) at the probe’s nose to withstand the extreme environments encountered in a Venus entry without producing pyrolysis gases that would contaminate the mission sample collection. Any shape change of this 3D-CC sample inlet will affect airflow through the sampling system, thereby impacting aerosol sample collection bias and efficiency. Accurate prediction of the nose’s material response during entry is there-fore of fundamental importance to the development and practical use of this technology. As a result, the AERACEPT project is planning a test campaign in the newly built PlasmatronX facility with a novel “Open Iso-Q” test article to validate state-of-the-art material response tools for a simulated Venus entry. The PlasmatronX is a 350 kW inductively-coupled plasma facility developed and run by the Center for Hypersonics and Entry Systems Studies at the University of Illinois at Urbana-Champaign. The facility can support ground testing for a variety of planetary destinations by simulating entry conditions in Nitrogen, Air, and Carbon Dioxide. To best simulate the Venus atmosphere and match flight-like recession, the planned AERACEPT test campaign will use Carbon Dioxide as its test gas. AERACEPT has designed two test articles for this campaign: 1) a standard test article whose curved surface approximates a constant applied heat flux (“Closed Iso-Q” model) and 2) a novel inlet test article with a through-hole at the stagnation point (“Open Iso-Q” model). Both article types consist of a 3D-CC sample bonded to a graphite fixture. All articles will be laser scanned before and after testing to estimate shape change and recession, and the “Closed Iso-Q” articles will be instrumented with thermocouples to provide temperature histories. The test article temperatures and inlet shape change will be compared against simulations run with the Porous material Analysis Toolbox based on OpenFOAM (PATO) to validate the AERACEPT 3D-CC material response model. Due to the high thermal conductivity of 3D-CC, multidimensional effects have a large influence on the test article temperature and the standard 1-D material response tools are not sufficient for test planning. The test campaign features (e.g. article design, run duration, heat fluxes) are therefore informed by a series of 3-D simulations using state-of-the-art material response tools such as PATO. The test campaign is scheduled for spring of 2024. Expected results include 1) Key drivers of selected test conditions (e.g. matching mission flight atmosphere & recession), 2) Simulation results that informed test article design, 3) Acquired test data such as recession measurements, temperature histories, and photos, and 4) Comparisons between test results and simulation predictions.

AERACEPT↗

NASA NTRSDate not supplied

In-Situ Ice Adhesion Testing using the Deformed Skin Adhesion Test

There exists a plethora of ice adhesion testing methods such as centrifuge-based methods, push/pull methods, and lap joint shear tests. However, these methods often cannot be done in-situ during an icing spray and require researcher handling/preparation prior to testing. Additionally, many of these methods test ice accretions that are not representative of the ice shapes that grow on airframes which can have unintended consequences such as edge or corner stress concentrations. In order to mitigate the issues present with other ice adhesion tests a novel, hands-free, in-situ test method imbedded into the leading edge of the airfoil has been developed and tested in the NASA Glenn Research Center Icing Research Tunnel. The mechanics of the new test method are discussed with finite element simulations being used to highlight the fundamental mechanics of this test method. The testing procedures used during the experimental test campaign are discussed along with the icing cloud test matrix. Analysis of the force-displacement results highlights the repeatability of the test method with regards to both sample behavior across several days of testing and different ice shapes. The results from first run of the day showed a significant discrepancy from subsequent runs and differential image analysis was used to determine differences in the interfacial bonding states between runs.

Ice Adhesion↗

NASA NTRSDate not supplied

Alternate Methods of Model Reduction to Avoid Dynamic Modal Truncation Error

Loads analysis is traditionally performed using dynamically reduced models, which provides the benefit to reduce run time. If the reduced model frequency cutoff is not chosen appropriately, the model will lack the dynamic content required to fully represent the response of the non-reduced model. Standard guidance for reduced model frequency content, provided in NASA-STD-5002, is to solve fixed base modes up to a minimum of 1.5x the model frequency content of interest and to employ static modal truncation methods such as residual vectors, the mode acceleration method, and the residual flexibility method to account for the truncated flexibility of the missing modes. Fixed base modes require the selection of a set of degrees of freedom to be constrained which, if not properly selected, may affect the accuracy of the reduced model by excluding some of the dynamic characteristic of the full model. In this case, the standard NASA guidance would be insufficient, but it may not be readily apparent that a portion of the reduced model response is missing. This error was encountered during an independent verification and validation (IV&V) effort, where it was observed that the resulting dynamic response was lower than the inline analysis. In this specific case, despite following the standard NASA model reduction guidelines in the selection of the frequency cutoff, the inline model still did not fully capture the necessary dynamic content. As part of the IV&V, an alternate reduction methodology was employed using an unconstrained mode acceleration method. The original model initially performed a constrained reduction to twice the frequency content of interest before doing a free-free run, employing the mode acceleration method to account for the truncated modes. In contrast in the IV&V, the unconstrained model reduced directly to the needed frequency content of the free-free run, avoiding any interactions between constraints and dynamic content. To verify the model, the original reduction methodology was used to generate a series of Hurty-Craig-Bampton reductions, each with a higher frequency cutoff than the previous. The results were shown to converge once the frequency cutoff increased past eight times the frequency content of interest. At the same frequency cutoff, the results of the Hurty-Craig-Bampton model converged with the results of the unconstrained mode acceleration model. This comparative study provided confidence that the results of the unconstrained modal acceleration reduced model were correct and that the Hurty-Craig-Bampton needed to increase its frequency cutoff to fully capture the dynamic response.

Erin Simmons↗

NASA NTRSDate not supplied

Alternate Methods of Model Reduction to Avoid Dynamic Modal Truncation Error

Loads analysis is traditionally performed using dynamically reduced models, which provides the benefit to reduce run time. If the reduced model frequency cutoff is not chosen appropriately, the model will lack the dynamic content required to fully represent the response of the non-reduced model. Standard guidance for reduced model frequency content, provided in NASA-STD-5002, is to solve fixed base modes up to a minimum of 1.5x the model frequency content of interest and to employ static modal truncation methods such as residual vectors, the mode acceleration method, and the residual flexibility method to account for the truncated flexibility of the missing modes. Fixed base modes require the selection of a set of degrees of freedom to be constrained which, if not properly selected, may affect the accuracy of the reduced model by excluding some of the dynamic characteristic of the full model. In this case, the standard NASA guidance would be insufficient, but it may not be readily apparent that a portion of the reduced model response is missing. This error was encountered during an independent verification and validation (IV&V) effort, where it was observed that the resulting dynamic response was lower than the inline analysis. In this specific case, despite following the standard NASA model reduction guidelines in the selection of the frequency cutoff, the inline model still did not fully capture the necessary dynamic content. As part of the IV&V, an alternate reduction methodology was employed using an unconstrained mode acceleration method. The original model initially performed a constrained reduction to twice the frequency content of interest before doing a free-free run, employing the mode acceleration method to account for the truncated modes. In contrast in the IV&V, the unconstrained model reduced directly to the needed frequency content of the free-free run, avoiding any interactions between constraints and dynamic content. To verify the model, the original reduction methodology was used to generate a series of Hurty-Craig-Bampton reductions, each with a higher frequency cutoff than the previous. The results were shown to converge once the frequency cutoff increased past eight times the frequency content of interest. At the same frequency cutoff, the results of the Hurty-Craig-Bampton model converged with the results of the unconstrained mode acceleration model. This comparative study provided confidence that the results of the unconstrained modal acceleration reduced model were correct and that the Hurty-Craig-Bampton needed to increase its frequency cutoff to fully capture the dynamic response.

Erin Simmons↗

NASA NTRSDate not supplied

In-Situ Ice Adhesion Testing using the Deformed Skin Adhesion Test

There exists a plethora of ice adhesion testing methods such as centrifuge-based methods, push/pull methods, and lap joint shear tests. However, these methods often cannot be done in-situ during an icing spray and require researcher handling/preparation prior to testing. Additionally, many of these methods test ice accretions that are not representative of the ice shapes that grow on airframes which can have unintended consequences such as edge or corner stress concentrations. In order to mitigate the issues present with other ice adhesion tests a novel, hands-free, in-situ test method imbedded into the leading edge of the airfoil has been developed and tested in the NASA Glenn Research Center Icing Research Tunnel. The mechanics of the new test method are discussed with finite element simulations being used to highlight the fundamental mechanics of this test method. The testing procedures used during the experimental test campaign are discussed along with the icing cloud test matrix. Analysis of the force-displacement results highlights the repeatability of the test method with regards to both sample behavior across several days of testing and different ice shapes. The results from first run of the day showed a significant discrepancy from subsequent runs and differential image analysis was used to determine differences in the interfacial bonding states between runs.

Ice Adhesion↗

NASA NTRSDate not supplied

In-Depth Modeling and Simulation Analysis of Artemis Missions Using the Impact Probabilistic Risk Assessment Tool

BACKGROUND The Artemis campaign is a Moon exploration program with a series of six planned missions, five of which will be crewed. These five crewed missions will contain a single mission segment (space flight), or multiple mission segments involving space flight (Orion), lunar landing (LTV) and/or space habitat (Gateway). Each crewed segment faces the risk of unique medical conditions, necessitating medical sets/kits tailored to those specificities. To support and enable a data-driven and evidence-based decision-making process through out a mission’s life cycle, a software tool called IMPACT was developed. Using probabilistic risk assessment (PRA) methodologies, IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a novel tool built for analyzing the possibility of encountering complex medical risks during space flight, and for identifying the medical resources and capabilities needed to treat those potential at-risk medical conditions. IMPACT achieves this by performing hundreds of thousands of Monte Carlo simulations of missions to build aggregate pictures of medical risk. During an extended simulation modeling phase, IMPACT generated analytical results for medical risks, and the medical resources and capabilities to address those risks, for every segment of every crewed Artemis mission. This presentation will highlight the reliability, consistency and validity of IMPACT’s computational modeling techniques and will showcase the library of analytical outcomes generated for the Artemis missions. OVERVIEW During the early stages of IMPACT’s design, architecture and technical requirements collection, “scenarios” (use cases) - achievement goals required for acceptance testing, were identified by stakeholders. IMPACT successfully completed the scenario testing requirements and undertook an extensive operational run phase utilizing a wide range of input combinations with a goal of delivering a cohesive, trustworthy, reliable, vast, and diverse body of evidence. The intent of these modeling runs was to validate consistency in output, ensure solidity of executable operations and to streamline processes by identifying areas requiring efficiency improvements. Using the many missions of Artemis, IMPACT ran variations of operational runs to assess the output for acceptable, as well as unusual characteristics. This rigorous long-term “shakedown” analysis was implemented to help build a collective body of evidence to aid in securing a high level of confidence, reliability, and validity in the output, whether from the applicational components of IMPACT, or the entirety of the operational process. ANTICIPATED ANALYSIS AND CONCLUSION This presentation will discuss the various categories of input criteria; the comparisons in the application of these input criteria to various Artemis missions; the preparation and collection of the body of evidence, and reliability of the computational modeling techniques. This paper serves as an initial analytical overview of IMPACT’s probabilistic risk assessment (PRA) medical risk outputs covering Artemis missions and is not intended to be deemed the official medical response for the Artemis campaign.

Crew Composition↗

NASA NTRSDate not supplied

Big Data Challenges at CCMC

Like other research centers, the Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) at NASA Goddard Space Flight Center (GSFC) is also experiencing the big data challenges. CCMC hosts over 80 space weather models for Runs On Request (ROR), Continuous Runs and Instant Runs simulation services for the research community. In addition, CCMC has started to support simulation output onboarding in response to the Open Science initiative. Overall, we have accumulated over petabytes of simulation output data and are rapidly growing. In this presentation, we will discuss our data and storage challenges. We will present our attempts to address our challenges and any associated lessons learned. CCMC uses Apache Airflow to ensure data transfer is consistent. We will give a brief overview on how we leverage Apache Airflow to enhance our environment.

space weather↗

NASA NTRSDate not supplied

NASA 5.2%-Scale Semispan High Lift Common Research Model Wind Tunnel Test at the 14- by 22-Foot Subsonic Tunnel

A wind tunnel test of the NASA 5.2%-scale Semispan High Lift Common Research Model (CRM-HL) was conducted at the 14- by 22-Foot Subsonic Tunnel (14x22) in the fall of 2022. The main purpose of the test was a model checkout before shipping it overseas. The model was shipped to Germany in the spring of 2023, and the team wanted to be sure that instrumentation in the model was working, all of the model parts fit together well, and model changes could be done smoothly, as designed while installed in a wind tunnel. Force and moment and pressure data were collected during the test, and while these data were a secondary objective, they can be used for for tunnel-to-tunnel verification of the model, and for database supplementation for the NASA CRM-HL ecosystem. The test was run from August 15, 2022 through September 8, 2022. Eight configurations were tested at Mach 0.2 and 0.26, over an alpha range from -4deg to +24deg. All of the configurations that were tested accomplished testing of all model parts. This test campaign was a unique opportunity to test a complicated model design in a wind tunnel that is less expensive to test in and has easier model access than the tunnel that it was designed to run in. The test was invaluable in providing lessons learned about building up and running the model, and the model was returned to the model manufacturer from December 2022 to February 2023 for updates to make model changes easier, to make design fixes on the model, and to do clean up work on the model.

CRM-HL↗

NASA NTRS1967

WSTF Transporting of Spare Altitude Chamber from LM Site to CSM Site

Transporting of Spare Altitude Chamber from Lunar Module (LM) Site to Command Service Module (CSM) Site. The video is broken into three parts: - Part 1: Run time of 21 min., 21 sec.; color; no sound - Part 2: Run time of 17 min., 14 sec.; color; no sound - Part 3: Run time of 18 min., 41 sec.; color, no sound All videos are in the mp4 format.

Heavy Equipment↗

NASA NTRSDate not supplied

Big Data Challenges at the Community Coordinated Modeling Center (CCMC)

Like other research centers, the Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) at NASA Goddard Space Flight Center (GSFC) is also experiencing the big data challenges. CCMC hosts over 80 space weather models for Runs On Request (ROR), Continuous Runs and Instant Runs simulation services for the research community. In addition, CCMC has started to support simulation output onboarding in response to the Open Science initiative. Overall, we have accumulated over petabytes of simulation output data and are rapidly growing. In this presentation, we will discuss our data and storage challenges. We will present our attempts to address our challenges and any associated lessons learned. CCMC uses Apache Airflow to ensure data transfer is consistent. We will give a brief overview on how we leverage Apache Airflow to enhance our environment.

space weather↗

NASA NTRSDate not supplied

NASA 5.2%-Scale Semispan High Lift Common Research Model Wind Tunnel Test at the 14- by 22-Foot Subsonic Tunnel

A wind tunnel test of the NASA 5.2%-scale Semispan High Lift Common Research Model (CRM-HL) was conducted at the 14- by 22-Foot Subsonic Tunnel (14x22) in the fall of 2022. The main purpose of the test was a model checkout before shipping it overseas. The model was shipped to Germany in the spring of 2023, and the team wanted to be sure that instrumentation in the model was working, all of the model parts fit together well, and model changes could be done smoothly, as designed while installed in a wind tunnel. Force and moment and pressure data were collected during the test, and while these data were a secondary objective, they can be used for for tunnel-to-tunnel verification of the model, and for database supplementation for the NASA CRM-HL ecosystem. The test was run from August 15, 2022 through September 8, 2022. Eight configurations were tested at Mach 0.2 and 0.26, over an alpha range from -4deg to +24deg. All of the configurations that were tested accomplished testing of all model parts. This test campaign was a unique opportunity to test a complicated model design in a wind tunnel that is less expensive to test in and has easier model access than the tunnel that it was designed to run in. The test was invaluable in providing lessons learned about building up and running the model, and the model was returned to the model manufacturer from December 2022 to February 2023 for updates to make model changes easier, to make design fixes on the model, and to do clean up work on the model.

Semispan↗

NASA NTRS2025

Single Integrated Flux Files to Account for Spacecraft Attitude Motion in Meteoroid Risk Assessments Using the NASA MEM3 and Bumper Codes

Spacecraft meteoroid risk assessments can be performed using NASA’s Meteoroid Engineering Model 3 (MEM3) and the Bumper risk assessment code. The MEM3 meteoroid flux is highly directional in heliocentric space. To represent the directionality, MEM3 outputs the flux in commonly used coordinate frames. For example, if a spacecraft attitude is fixed in the orbital tangential frame, a single Bumper run using the MEM3 flux file in the body-fixed frame can be performed. Cases exist in which the spacecraft does not remain fixed in one of these frames during a mission. This could be handled by performing a series of Bumper runs at points along the trajectory. For each trajectory point, the spacecraft has to be rotated into the frame in which the MEM3 flux file is defined. Another option presented here is to generate a single integrated flux (SIF) file. A SIF file is an average over a trajectory of the time varying MEM3 flux files rotated from their native frame into the spacecraft bus frame. A SIF file enables accounting for spacecraft rotation (coupled with flux variation over the trajectory) in a single Bumper run. An example of an application of SIF files is the meteoroid risk assessment for the Mars Sample Return (MSR) campaign Capture Containment and Return System (CCRS). This report discusses how SIF files were generated for the CCRS risk assessment and presents metrics on the accuracy of the impinging fluence that is generated when using the files. The results show a maximum difference per element in a finite element model within 1 percent for seven of the eight examined cases, with the outlier being less than 2 percent. The results also show that the maximum standard deviation of differences across all elements is within 0.275 percent. The maximum difference in the total fluence across all the elements is 0.0463 percent. The maximum difference in the mean fluence across all the elements is 0.0407 percent.

Meteoroids↗

DOE OSTI2020

RECENT RESULTS AND OPPORTUNITIES AT THE IOTA FACILITY

The Integrable Optics Test Accelerator (IOTA) was recently commissioned as part of the Fermilab Accelerator Science and Technology (FAST) facility. The IOTA ring was briefly operated with electrons at 47 MeV followed by a 6-months run with 100 MeV electrons. The main goal of the first runwas to study beam dynamics in the integrable lattices with elliptical nonlinear magnets and in the quasi-integrable case with profiled octupole channel. The flexibility of the IOTA ring allowed a wide range of complementary studies, such as experiments with a single electron; studies of fluctuations in undulator radiation and operation with low emittance beams. Over the next year the proton injector will be installed and two runs carried out. One run will be dedicated to the refinement of nonlinear experiments and another will be dedicated to the proof-of-principle demonstration of Optical Stochastic Cooling.

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗