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At least 415 records · Page 23

Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) Field Campaign Report

Cumulus convection is an important component in the atmospheric radiation budget and hydrologic cycle over the southern Great Plains and over many regions of the world, particularly during the summertime growing season when intense turbulence induced by surface radiation couples the land surface to clouds. Current convective cloud parameterizations contain uncertainties resulting in part from insufficient coincident data that couples cloud macrophysical and microphysical properties to inhomogeneities in land surface, boundary layer, and aerosol properties. The Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign was designed to provide a detailed set of measurements that are needed to obtain a more complete understanding of the lifecycle of shallow clouds by coupling cloud macrophysical and microphysical properties to land surface properties, ecosystems, and aerosols. Some of the land-atmosphere-cloud interactions that can be studied using HI-SCALE data are shown in Figure 1. HI-SCALE consisted of two 4-week intensive operation periods (IOPs), one in the spring (April 24-May 21) and the other in the late summer (August 28-September 24) of 2016, to take advantage of different stages of the plant lifecycle, the distribution of “greenness” for various types of vegetation in the vicinity of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains (SGP) site, and aerosol properties that vary during the growing season. As expected, satellite measurements indicated that the Normalized Difference Vegetation Index (NDVI) was much “greener” in the vicinity of the SGP site during the spring IOP than the late summer IOP as a result of winter wheat maturing in the spring and being harvested in the early summer. As shown in Figure 2, temperatures were cooler than average and soil moisture was high during the spring IOP, while temperatures were warmer than average and soil moisture was low during the late summer IOP. These factors likely influence the occurrence and lifecycle of shallow clouds. Most of the instrumentation was deployed on the ARM Aerial Facility (AAF) Gulfstream 1 (G-1) aircraft, including those that measure atmospheric turbulence, cloud water content and drop size distributions, aerosol precursor gases, aerosol chemical composition and size distributions, and cloud condensation nuclei (CCN) concentrations. The specific instrumentation is listed in Table 1. The team of scientists participating in the G-1 flights were from Pacific Northwest National Laboratory (PNNL), Brookhaven National Laboratory (BNL), and the University of Washington. Routine ARM aerosol measurements made at the surface were supplemented with aerosol microphysical properties measurements, with support from the DOE Environmental Molecular Sciences Laboratory (EMSL) User Facility and the Atmospheric System Radiation (ASR) program. This included deploying a scanning mobility particle sizer (SMPS) to measure aerosol size distribution, a proton transfer reaction-mass spectrometer (PTR-MS) to measure volatile organic compounds, an aerosol mass spectrometer (AMS) to measure bulk aerosol composition, and the single-particle laser ablation time-of-flight mass spectrometer (SPLAT II) to measure single-particle aerosol composition at the SGP site Guest Instrumentation Facility. In this way, characterization of aerosol properties at the surface and on the G-1 were consistent. In addition, the HI-SCALE: Nanoparticle Composition and Precursors add-on campaign was conducted during the second IOP in which several state-of-the-science chemical ionization mass spectrometers were deployed to measure nanoparticle composition and precursors. Scientists participating in the surface measurements were from PNNL, BNL, University California–Irvine, Augsberg College, Colorado University, Aerodyne Inc., and Aerosol Dynamics Inc.

54 ENVIRONMENTAL SCIENCES↗

Atmospheric Radiation Measurement Climate Research Facility Operations Quarterly Report July 1-September 30, 2016

Individual datastreams from instrumentation at the Atmospheric Radiation Measurement (ARM) Climate Research Facility fixed and mobile research sites are collected and routed to the Data Management Facility (DMF) for processing in near-real time. Instrument and processed data are then delivered approximately daily to the ARM Data Archive, where they are made freely available to the research community. For each instrument, ARM calculates the ratio of the actual number of processed data records received daily at the ARM Data Archive to the expected number of data records. The results are tabulated by 1) individual datastream, site, and month for the current year, and 2) site and fiscal year dating back to 1998. The U.S. Department of Energy requires national user facilities to report time-based operating data. The requirements involve the: Actual hours of operation (ACTUAL) – 24 hours per day, 92 days or 2208 hours for this quarter Estimated maximum operation or uptime target (TARGET) Variance (VARIANCE), which is equal to (1 – [ACTUAL/TARGET]) TARGET and VARIANCE numbers account for unplanned downtime. Differences in TARGET performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure TARGET for each instrument or datastream. Data availability reported here refers to the average of the individual, continuous datastreams received by the ARM Data Archive. Therefore, data availability is directly related to individual instrument uptime expressed in hours. Data not at the ARM Data Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Missing data caused by scheduled downtime are not included in the metrics. Thus, the average percentage of data in the ARM Data Archive represents the average percentage of the time the instruments were operating for the quarter.

Southern Great Plains, North Slope of Alaska, East↗

Atmospheric Radiation Measurement Climate Research Facility Operations Quarterly Report April 1-June 30, 2016

Individual datastreams from instrumentation at the Atmospheric Radiation Measurement (ARM) Climate Research Facility fixed and mobile research sites are collected and routed to the Data Management Facility (DMF) for processing in near-real time. Instrument and processed data are then delivered approximately daily to the ARM Data Archive, where they are made freely available to the research community. For each instrument, ARM calculates the ratio of the actual number of processed data records received daily at the ARM Data Archive to the expected number of data records. The results are tabulated by 1) individual datastream, site, and month for the current year, and 2) site and fiscal year dating back to 1998. The U.S. Department of Energy requires national user facilities to report time-based operating data. The requirements involve the: Actual hours of operation (ACTUAL) – 24 hours per day, 91 days or 2184 hours for this quarter Estimated maximum operation or uptime target (TARGET) Variance (VARIANCE), which is equal to (1 – [ACTUAL/TARGET]) TARGET and VARIANCE numbers account for unplanned downtime. Differences in TARGET performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure TARGET for each instrument or datastream. Data availability reported here refers to the average of the individual, continuous datastreams received by the ARM Data Archive. Therefore, data availability is directly related to individual instrument uptime expressed in hours. Data not at the ARM Data Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Missing data caused by scheduled downtime are not included in the metrics. Thus, the average percentage of data in the ARM Data Archive represents the average percentage of the time the instruments were operating for the quarter.

North Slope of Alaska, Eastern North Atlantic, Sou↗

Development of Magnesium Diboride Superconducting Coils for Nuclear Physics Application

The primary objective of this project is to develop an affordable magnet technology at 10-25K and then take it to a level that it can be considered mature enough to be used in a real Nuclear Physics accelerator system. We believe that because of the lower cost of magnesium diboride (MgB2) as compared to the other HTS, it offers the best such chance. Once successfully demonstrated, this exciting and innovative technology could potentially revolutionize the field the same way the conventional superconducting NbTi magnets did several decades ago. MgB2 magnets could reduce the cost of ownership (capital +operation) while enhancing performance. Another innovation is the overall cooling scheme where the exhaust gas of an existing superconducting magnet cools the inner tube which conduction cools the MgB2 coils. In several instances during the upgrade of existing facilities or designing new facilities in the Nuclear Physics or High Energy Physics communities, it is found that magnets made neither with copper coils nor with conventional superconducting NbTi coils offer an acceptable solution. Whereas copper coils limit the performance of the machine and consume large amount of power, NbTi require 4 K cryogenic facilities. This is particularly applicable in those Nuclear Physics machines where the magnetic field requirements are rather modest. One such case has been found in the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory (BNL) where an e-lens system is under construction to increase RHIC luminosity. In this case, magnesium diboride (MgB2) operating at 10-25 K seems to offer an exciting and practical solution. The main objective in Phase II is to demonstrate the reliability and robustness of the MgB2 coil technology, so that it is ready for use in RHIC and other user facilities. We will do this by fabricating several MgB2 coils and by conducting an exhaustive series of lifetime cycle tests. The tests will involve about a thousand ramp-up and ramp-down cycles, about 20 over current or thermal-excursions hitting the quench limit and about 10 thermal cycles. Phase II will begin with a design modeling effort of the MgB2 coils for the e-lens system with enough detail so that the magnetic, thermal and stress requirements can be understood for the fabrication and testing of representative MgB2 coils. After the technology is proven in Phase II for reliability, we will propose to use this in Phase III to upgrade RHIC e-lens system for improved luminosity performance and expect that more applications will follow in other accelerator and medical facilities.

99 GENERAL AND MISCELLANEOUS↗

The Compelling Need for a Mid-Scale Stellarator Facility

In the pursuit of the goal of commercial fusion as an abundant and safe source of energy, the stellarator is a leading concept with compelling attractiveness and demonstrated performance. A new mid-size stellarator is needed to retire risks and innovate towards a high performance, economically attractive, stellarator Fusion Pilot Plant. In this presentation we, as a community of US researchers from Universities, National Laboratories, and Private Industry, involved in studying the stellarator concept, lay out the programmatic and technical motivation for a new and modern mid-size stellarator research facility. A new mid-scale stellarator is needed to realize the potential predicted by a solid body of theory and simulation along with advances in computational tools for optimization and non-linear turbulence modeling. Notably, it is possible to combine the advantages of the stellarator (steady state, no current drive, no disruptions) with the good confinement regularly achieved in tokamaks. The top priorities for experimental work, and the motivation for a mid-scale stellarator experiment are: turbulence control, non-resonant divertor, MHD stability at large beta, confinement of fast particles, and coil simplification. A new mid-size quasi-symmetric stellarator, built as a user facility, would complement existing research at Wendelstein 7-X and LHD and strongly augment private industry. It would provide a program of innovative research, concept validation, theoretical advancement, and workforce development. Growing support and interest for stellarators by the fusion community and private industry affirms this rationale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The UARS and open data concept and analysis study

Alternative concepts for a common design for the UARS and OPEN Central Data Handling Facility (CDHF) are offered. Costs for alternative implementations of the UARS designs are presented, showing that the system design does not restrict the implementation to a single manufacturer. Processing demands on the alternative UARS CDHF implementations are then discussed. With this information at hand together with estimates for OPEN processing demands, it is shown that any shortfall in system capability for OPEN support can be remedied by either component upgrades or array processing attachments rather than a system redesign. In addition to a common system design, it is shown that there is significant potential for common software design, especially in the areas of data management software and non-user-unique production software. Archiving the CDHF data are discussed. Following that, cost examples for several modes of communications between the CDHF and Remote User Facilities are presented. Technology application is discussed.

Mittal, M.↗

Advances of the FRIB project

The Facility for Rare Isotope Beams (FRIB) Project has entered the phase of beam commissioning starting from the room-temperature front end and the superconducting linac segment of first 15 cryomodules. With the newly commissioned helium refrigeration system supplying 4.5K liquid helium to the quarter-wave resonators and solenoids, the FRIB accelerator team achieved the sectional key performance parameters as designed ahead of schedule accelerating heavy ion beams above 20MeV/u energy. Thus, FRIB accelerator becomes world’s highest-energy heavy ion linear accelerator. We also validated machine protection and personnel protection systems that will be crucial to the next phase of commissioning. FRIB is on track towards a national user facility at the power frontier with a beam power two orders of magnitude higher than operating heavy ion facilities. Here, this paper summarizes the status of accelerator design, technology development, construction, commissioning as well as path to operations and upgrades.

43 PARTICLE ACCELERATORS↗

The Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) Activity for Continental Shallow Convection

The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility recently initiated the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) activity focused on shallow convection at ARM’s Southern Great Plains (SGP) atmospheric observatory in Oklahoma. LASSO is designed to overcome an oft-shared difficulty of bridging the gap from point-based measurements to scales relevant for model parameterization development, and it provides an approach to add value to observations through modeling. LASSO is envisioned to be useful to modelers, theoreticians, and observationalists needing information relevant to cloud processes. LASSO does so by combining a suite of observations, LES inputs and outputs, diagnostics, and skill scores into data bundles that are freely available, and by simplifying user access to the data to speed scientific inquiry. The combination of relevant observations with observationally constrained LES output provides detail that gives context to the observations by showing physically consistent connections between processes based on the simulated state. A unique approach for LASSO is the generation of a library of cases for days with shallow convection combined with an ensemble of LES for each case. The library enables researchers to move beyond the single-case-study approach typical of LES research. The ensemble members are produced using a selection of different large-scale forcing sources and spatial scales. Since large-scale forcing is one of the most uncertain aspects of generating the LES, the ensemble informs users about potential uncertainty for each date and increases the probability of having an accurate forcing for each case.

54 ENVIRONMENTAL SCIENCES↗

Enhancing Discoverability and Management of Atmospheric Data at Scale: Solutions from the ARM Data Center

The Atmospheric Radiation Measurement (ARM) is a multi-laboratory and multi-institutional U.S. Department of Energy (DOE) Office of Science National User Facility. The ARM Data Center (ADC), located at Oak Ridge National Laboratory, collects, archives, and shares vast atmospheric data crucial for climate research. The ADC manages over 7 PB of data from 460 instruments worldwide, processing it into more than 11,000 diverse data products using the Network Common Data Form (NetCDF) for machine-independent accessibility. The primary challenge addressed in this paper is the efficient management and distribution of vast and diverse datasets essential for the climate research community, enhancing accessibility through advanced tools like Data Discovery. The ADC has developed advanced infrastructure and software architecture to handle the continuous influx of heterogeneous data to enhance data discoverability, resulting in increased scientific collaboration. In 2023, users from over 34 countries downloaded and utilized ARM data, resulting in 1,455 publications. The ADC’s efforts have significantly improved the discoverability and usability of atmospheric data, fostering extensive scientific research and collaboration. This paper details the solutions implemented by the ADC team for efficient data discovery and distribution, and it demonstrates ARM’s capability of staging processed data for scientific analysis.

Shah, Chirag [ORNL] (ORCID:0000000203145737)↗

Bioenergy Feedstock Library Annual Summary Report

The Bioenergy Feedstock Library (BFL), part of the Biomass Feedstock National User Facility (BFNUF) located at INL, is a physical sample repository and a web-accessible electronic database. The BFL stores physical and chemical characteristics of biomass and waste carbon sources for energy use as well as samples generated from across U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) funded projects. The objective of this Bioenergy Feedstock Library Annual Summary Report for 2022 is to focus on the (1) publicly available analytical data and equipment tracked through the BFNUF, (2) physical samples available for request, (3) sample and data archival progress from recent BETO-funded projects, and (4) publicly available data sets created upon request from BETO, INL projects, or outside entities. This report highlights key statistics from FY22 and available data and information important for INL, BFL users, academics, and industry.

09 BIOMASS FUELS↗

Structure, dynamics and stability of water/scCO 2 /mineral interfaces from ab initio molecular dynamics simulations

Here, the interface between a solid and a complex multi-component liquid forms a unique reaction environment whose structure and composition can significantly deviate from either bulk or liquid phase and is poorly understood due the innate difficulty to obtain molecular level information. Feldspar minerals, as typified by the Ca-end member Anorthite, serve as prototypical model systems to assess the reactivity and ion mobility at solid/water-bearing supercritical fluid (WBSF) interfaces due to recent X-ray based measurements that provide information on water-film formation, and cation vacancies at these surfaces. Using density functional theory based molecular dynamics, which allows the evaluation of reactivity and condensed phase dynamics on equal footing, we report on the structure and dynamics of water nucleation and surface aggregation, carbonation and Ca mobilization under geologic carbon sequestration scenarios (T = 323 K and P = 90 bar). We find that water has a strong enthalpic preference for aggregation on a Ca-rich, O-terminated anorthite (001) surface, but entropy strongly hinders the film formation at very low water concentrations. Carbonation reactions readily occur at electron-rich terminal Oxygen sites adjacent to cation vacancies, when in contact with supercritical CO 2 . Cation vacancies of this type can form readily in the presence of a water layer that allows for facile and enthalpicly favorable Ca 2+ extraction and solvation. Apart from providing unprecedented molecular level detail of a complex three component (mineral, water and scCO 2 ) system), this work highlights the ability of modern capabilities of AIMD methods to begin to qualitatively and quantitatively address structure and reactivity at solid-liquid interfaces of high chemical complexity. This work was supported by the US Department of Energy, Office of Fossil Energy (M.-S. L., B. P. M. and V.-A. G.) and the Office of Basic Energy Science, Division of Chemical Sciences, Geosciences and Biosciences (R.R.), and performed at the Pacific Northwest National Laboratory (PNNL). PNNL is a multi-program national laboratory operated for DOE by Battelle. Computational resources were provided by PNNL’s Platform for Institutional Computing (PIC), the W. R. Wiley Environmental Molecular Science Laboratory (EMSL), a national scientific user facility sponsored by the Department of Energy’s Office of Biological and Environmental Research located at PNNL and the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bioenergy Feedstock Library 2023 Annual Summary Report

The Bioenergy Feedstock Library (BFL), part of the Biomass Feedstock National User Facility (BFNUF) located at INL, is a physical sample repository and a web-accessible electronic database. The BFL stores physical and chemical characteristics of biomass and waste carbon sources for energy use as well as samples generated from across U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) and U.S. Department of Agriculture funded projects. The objective of this Bioenergy Feedstock Library Annual Summary Report for 2023 is to focus on the updates to (1) publicly available analytical data and equipment tracked through the BFNUF, (2) physical samples available for request, (3) sample and data archival progress from recent BETO-funded projects, and (4) publicly available datasets created upon request from BETO, INL projects, or outside entities compared to the 2022 Bioenergy Feedstock Library Annual Summary Report. This report highlights key statistics and available data and information important for INL, BFL users, academics, and industry.

09 BIOMASS FUELS↗

EPCAPE Radar b1 Data Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility recently deployed its First ARM Mobile Facility (AMF1) to La Jolla, California as part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) campaign. Some of the goals behind EPCAPE were to characterize the diurnal and seasonal cycles of stratocumulus clouds and to investigate the cloud-aerosol-radiation interactions and feedbacks in the area. The deployment of the AMF1 for a full year from 15 February 2023 to 14 February 2024 aided in addressing these scientific questions. While AMF1 collected data year-round, enhanced measurements were taken during two intensive operational periods (IOPs). The first IOP occurred from April to June and focused on the chemistry of low clouds (EPCAPE_Chem), while the second IOP occurred from July to September and was focused on the radiation of high clouds (EPCAPE_Radiation). Several cloud radars were deployed with AMF1 to collect valuable data on cloud properties that will help users address key science objectives. As in past ARM campaigns, a1-level radar data is extensively analyzed and calibration techniques are performed to generate b1-level data (Matthews et al. 2023, Feng et al. 2024). Radar data at the b1-level are of the highest quality and thus can be used to examine scientific questions. The status of the a1-level data and the a1-to-b1 process for the EPCAPE radars is subsequently detailed in this document.

54 ENVIRONMENTAL SCIENCES↗

BASIN-3D Data Integration for Selected ARM Data Field Campaign Report

The purpose of this data services request was to demonstrate integration of the Atmospheric Radiation Measurement (ARM) User Facility’s “met” datastreams with time series data from other earth science data sources using the BASIN-3D data synthesis software tool. BASIN-3D is an open-source Python library that enables researchers to integrate data across configured public and private data sources. It provides a common query language for researchers to request measurement locations and time series data based on specified locations, variables, time period, statistics, aggregation, and data quality. BASIN-3D acquires the data that match the query from each configured data source and translates the results into harmonized vocabularies, thus reducing researchers' data-wrangling effort. In addition, because the queries are executed on demand, researchers can easily regenerate their synthesized data sets as new data and/or data updates become available, eliminating one-off data products. BASIN-3D can output data using a variety of different data structures for end-user applications including Python pandas data frames and hdf5 output formats.

54 ENVIRONMENTAL SCIENCES↗

A Facile Approach Using MgCl2 to Formulate High Performance Mg2+ Electrolytes for Rechargeable Mg Batteries

Rechargeable Mg batteries have been regarded as a viable battery technology for grid scale energy storage and transportation applications. However, the limited performance of Mg2+ electrolytes has been a primary technical hurdle to develop high energy density rechargeable Mg batteries. In this study, MgCl2 is demonstrated as a non-nucleophilic and cheap Mg2+ source in combining with Al Lewis acids (AlCl3, AlPh3 and AlEtCl2) to formulate a series of Mg2+ electrolytes characteristic of high oxidation stability (up to 3.4 V vs Mg), sulfur compatibility and electrochemical reversibility (up to 100% coulombic efficiency). Three electrolyte systems (MgCl2-AlCl3, MgCl2-AlPh3, and MgCl2-AlEtCl2) were prepared free of purification and fully characterized by multinuclear NMR (27Al{1H} and 25Mg{1H}) spectroscopies, single crystal X-ray diffraction, and electrochemical analysis. The reaction mechanism of MgCl2 and the Al Lewis acids in THF is discussed to highlight the formation of the electrochemically active [(µ-Cl)3Mg2(THF)6]+ monocation in these electrolytes. We are grateful for the financial support from the Pacific Northwest National Laboratory (PNNL)-Laboratory Directed Research and Development (LDRD) program for developing magnesium battery technology. The XRD and SEM data were collected at the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the DOE’s Office of Biological and Environmental Research and located at PNNL. PNNL is a multiprogram laboratory operated by Battelle Memorial Institute for the Department of Energy under Contract DE-AC05-76RL01830.

electrolytes↗

Bioenergy Feedstock Library Annual Summary Report 2024

The Bioenergy Feedstock Library (BFL), part of the Biomass Feedstock National User Facility (BFNUF) located at Idaho National Laboratory (INL), is a physical sample repository and a web-accessible electronic database. The BFL stores physical and chemical characteristics of biomass and waste carbon sources for energy use, as well as samples generated from U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) and U.S. Department of Agriculture-funded projects. The objective of this Bioenergy Feedstock Library Annual Summary Report for 2024, similar to the 2023 Annual Summary Report , is to focus on the updates to: (1) publicly available analytical data and equipment tracked through the BFNUF, (2) significant increases in the physical samples available for request, (3) sample and data archival progress from recent BETO-funded projects, and (4) publicly available data sets created upon request from BETO, INL projects, or outside entities compared to the previous annual summary reports. This report highlights key statistics and available data and information important for INL, BFL users, academics, and industry.

09 BIOMASS FUELS↗

Enabling real-time adaptation of machine learning models at x-ray Free Electron Laser facilities with high-speed training optimized computational hardware

The emergence of novel computational hardware is enabling a new paradigm for rapid machine learning model training. For the Department of Energy’s major research facilities, this developing technology will enable a highly adaptive approach to experimental sciences. In this manuscript we present the per-epoch and end-to-end training times for an example of a streaming diagnostic that is planned for the upcoming high-repetition rate x-ray Free Electron Laser, the Linac Coherent Light Source-II. We explore the parameter space of batch size and data parallel training across multiple Graphics Processing Units and Reconfigurable Dataflow Units. We show the landscape of training times with a goal of full model retraining in under 15 min. Although a full from scratch retraining of a model may not be required in all cases, we nevertheless present an example of the application of emerging computational hardware for adapting machine learning models to changing environments in real-time, during streaming data acquisition, at the rates expected for the data fire hoses of accelerator-based user facilities.

97 MATHEMATICS AND COMPUTING↗

The Life Cycle Application of Intelligent Software Modeling for the First Materials Science Research Rack

Marshall Space Flight Center (MSFC) has been funding development of intelligent software models to benefit payload ground operations for nearly a decade. Experience gained from simulator development and real-time monitoring and control is being applied to engineering design, testing, and operation of the First Material Science Research Rack (MSRR-1). MSRR-1 is the first rack in a suite of three racks comprising the Materials Science Research Facility (MSRF) which will operate on the International Space Station (ISS). The MSRF will accommodate advanced microgravity investigations in areas such as the fields of solidification of metals and alloys, thermo-physical properties of polymers, crystal growth studies of semiconductor materials, and research in ceramics and glasses. The MSRR-1 is a joint venture between NASA and the European Space Agency (ESA) to study the behavior of different materials during high temperature processing in a low gravity environment. The planned MSRR-1 mission duration is five (5) years on-orbit and the total design life is ten (IO) years. The MSRR-1 launch is scheduled on the third Utilization Flight (UF-3) to ISS, currently in February of 2003). The objective of MSRR-1 is to provide an early capability on the ISS to conduct material science, materials technology, and space product research investigations in microgravity. It will provide a modular, multi-user facility for microgravity research in materials crystal growth and solidification. An intelligent software model of MSRR-1 is under development and will serve multiple purposes to support the engineering analysis, testing, training, and operational phases of the MSRR-1 life cycle development. The G2 real-time expert system software environment developed by Gensym Corporation was selected as the intelligent system shell for this development work based on past experience gained and the effectiveness of the programming environment. Our approach of multi- uses of the simulation model and its intuitive graphics capabilities is providing a concurrent engineering environment for rapid prototyping and development. Operational schematics of the MSRR-1 electrical, thermal control, vacuum access, and gas supply systems, and furnace inserts are represented graphically in the environment. Logic to represent first order engineering calculations is coded into the knowledge base to simulate the operational behavior of the MSRR-1 systems. An example of engineering data provided includes electrical currents, voltages, operational power, temperatures, thermal fluid flow rates. pressures, and component status indications. These type of data are calculated and displayed at appropriate instrumentation points, and the schematics are animated to reflect the simulated operational status of the MSRR-1. The software control functions are also simulated to represent appropriate operational behavior based on automated control and response to commands received by the crew or ground controllers. The first benefit of this simulation environment is being realized in the high fidelity engineering analysis results from the electrical power system G2 model. Secondly, the MSRR-1 simulation model will be embedded with a hardware mock-up of the MSRR-1 to provide crew training on MSRR-1 integrated payload operations. G2 gateway code will output the simulated instrumentation values, termed as telemetry, in a flight-like data stream so that the crew has realistic and accurate simulated MSRR-1 data on the flight displays which will be designed for crew use. The simulation will also respond appropriately to crew or ground initiated commands, which will be part of normal facility operations. A third use of the G2 model is being planned; the MSRR-1 simulation will be integrated with additional software code as part of the test configuration of the primary onboard computer, or Master Controller, for MSRR-1. We will take advantage of the G2 capability to simulate the flight like data stream to test flight software responses and behavior. A fourth use of the G2 model will be to train the Ground Support Personnel that will monitor the MSRR-1 systems and payloads while they are operating aboard the ISS. The intuitive, schematic based environment will provide an excellent foundation for personnel to understand the integrated configuration and operation of the MSRR-1, and the anticipated telemetry feedback based on operational modes of the equipment. Expert monitoring features will be enhanced to provide a smart monitoring environment for the operators. These features include: (1) Animated, intuitive schematic-based displays which reflect telemetry values, (1) Real-time plotting of simulated or incoming sensor values, (3) High/Low exception monitoring for analog data, (4) Expected state monitoring for discrete data, (5) Data trending, (6) Automated malfunction procedure execution to diagnose problems, (7) Look ahead capability to planned MSRR-1 activities in the onboard timeline. And finally, the logic to calculate telemetry values will be deactivated, and the same environment will interface to the incoming data for the real-time telemetry stream to schematically represent the onboard hardware configuration. G2 will be the foundation for the real-time monitoring and control environment. In summary, our MSRR-1 simulation model spans many elements of the life cycle development of this project: Engineering Analysis, Test and Checkout, Training of Crew and Ground Personnel, and Real-time monitoring and control. By utilizing the unique features afforded by an expert system development environment, we have been able to synergize a powerful tool capable of addressing our project needs at every phase of project development.

Rice, Amanda↗