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This report provides a brief description of the Field System (FS) for non-users. The Field System (FS) is a suite of programs that provides the coordinating control of VLBI data acquisition at many stations. The basic features of the FS and experiment operations are described. Areas for future development axe listed.
We have utilized an extensive set of independent British Airways flight data recording wind vector and temperature observations (the Global Aircraft Data Set [GADS] archive) in three ways: (a) as an independent check of operational analyses; (b) as an analysis observing system experiment (OSE) as if the GADS observations were available in real time; and (c) as the corresponding forecast simulation experiment applicable to future operational forecasts. Using a 31 day sample (0000 UTC 20 December 2000 through 0000 UTC 20 January 2000) from Winter 2000, we conclude that over the data-dense continental U. S. analyzed jet streaks are too weak by -2% to -5%. Over nearby data-sparse regions of Canada, analyzed jet streaks are too weak by -5% to -9%. The second range provides a limit on the accuracy of current jet streak analyses over the portions of the -85% of the earth's surface that are poorly covered by non-satellite observations. The -5% to -9% range is relevant for the pre-third generation satellite (AIRS, IASI, GIFTS) era.
The JPL Optical Communications Telescope Laboratory (OCTL) is a 200 sq-m located at 2.2.km altitude in Wrightwood California and houses a state-of-the-art 1-m telescope. The OCTL team is involved in the development of operational strategies for ground-to-space laser beam propagation for future NASA optical communications missions. Strategies include safe beam propagation through navigable air space, line of sight optical attenuation monitoring, adaptive optics, and multi-beam scintillation mitigation. This paper presents the results of recent operations at the OCTL facility including telescope characterization data and laser beam propagation experiments to Earth-orbiting retro-reflecting satellites; experiments that validate the telescope's tracking and blind-pointing performance and safe laser beam transmission procedures for propagating through navigable airspace.
This paper presents a series of optical measurement techniques that were developed for use during large-scale fabrication and testing of nozzle components. A thorough understanding of hardware throughout the fabrication cycle and hotfire testing is critical to meet component design intent. Regeneratively cooled nozzles and associated tooling require tight control of tolerances during the fabrication process to ensure optimal performance. Additionally, changes in geometry during testing can affect performance of the nozzle and mating components. Structured light scanning and digital image correlation techniques were used to collect data during the fabrication and test of nozzles, in addition to other engine components. This data was used to analyze deformations data during machining, heat treatment, assembly and testing operations. A series of feasibility experiments were conducted for these techniques that led to use on full scale nozzles during the J-2X upper stage engine program in addition to other engine development programs. This paper discusses the methods and results of these measurement techniques throughout the nozzle life cycle and application to other components.
Flights often experience large delays when they are routed around weather. Multi-flight common route advisories provide delay recovery by suggesting time-saving re-routes for groups of flights whose current weather-avoidance routes have become outdated because the weather has dissipated and/or moved away. A laboratory evaluation of these advisories was conducted by four subject matter experts having extensive experience in traffic flow management operations. These experts provided a total of 120 data points in the airspace of Houston Center. The multi-flight common route tool provides time-saving route change advisories taking into account flight plans, wind fields, and the spatio-temporal evolution of predicted convective weather. It is not designed to account for complex operational factors such as non-standard sector traversal and interactions with local traffic management initiatives; hence a relatively low percentage (37%) of advisories generated by the tool were rated as acceptable. However, a high percentage (81%) of advisories were rated as acceptable after the subject matter experts used the tool's user interface to make route modifications that accounted for relevant operational factors not considered by the tool. The workload associated with using the tool, as measured by the NASA Task Load Index, was quite low (1.1 on a scale of 0 to 10). The results of this evaluation make a good case for human-automation teaming to design operationally valid weather re-routes for delay recovery.
Flights often experience large delays when they are routed around weather. Multi-flight common route advisories provide delay recovery by suggesting time-saving re-routes for groups of flights whose current weather-avoidance routes have become outdated because the weather has dissipated and/or moved away. A laboratory evaluation of these advisories was conducted by four subject matter experts having extensive experience in traffic flow management operations. These experts provided a total of 120 data points in the airspace of Houston Center. The multi-flight common route tool provides time-saving route change advisories taking into account flight plans, wind fields, and the spatio-temporal evolution of predicted convective weather. It is not designed to account for complex operational factors such as non-standard sector traversal and interactions with local traffic management initiatives; hence a relatively low percentage (37%) of advisories generated by the tool were rated as acceptable. However, a high percentage (81%) of advisories were rated as acceptable after the subject matter experts used the tool's user interface to make route modifications that accounted for relevant operational factors not considered by the tool. The workload associated with using the tool, as measured by the NASA Task Load Index, was quite low (1.1 on a scale of 0 to 10). The results of this evaluation make a good case for human-automation teaming to design operationally valid weather re-routes for delay recovery.
Historically, a two-step procedure for estimation of Universal Time and polar motion from observations was adopted: night averages from individual observatories formed a raw non-equidistant time series that was edited for outliers, smoothed, and formed the final data product. This approach was by inertia used for processing modern space geodesy observations. I will present an alternative one-step approach and its application for processing a dataset of VLBI observations since 1990.0 through present. The essence of this approach is to represent the Earth orientation parameters in a form of an expansion into basic functions and estimate of the expansion coefficients directly from observations. A further extension of this approach is to assimilate not only space geodesy data, but atmospheric and ocean angular momentum from assimilation numerical weather models and their forecasts. That makes a smooth bridge between Earth rotation estimation and prediction. I will talk about my experience of running data analysis in such a way on a semi-operational basis, present results, and discuss advantages and disadvantages of this approach.
This paper documents the development and validation of a dynamic primary cooling and thermal storage system simulation testbed. The system simulation testbed, sIBAL, is based on the Intelligent Building Agents Laboratory (IBAL) at the National Institute of Standards and Technology (NIST), which is a research infrastructure and testbed for the development, evaluation, and demonstration of intelligent control algorithms. The sIBAL testbed developed in this project will serve as a virtual twin of the real facility for future control algorithm development. The details of the methodologies used to develop and validate the simulation testbed, which replicates the dynamic behaviors of the primary cooling and ice storage system in the IBAL facility, are presented. The simulation testbed was developed in TRNSYS using built-in component models and MATLAB functions to replicate the two water-cooled chillers, a thermal storage tank, pumps, valves and other components for four different operation modes. Experiments on IBAL components were designed and executed to generate experimental data for model development and verification of the simulation platform. The validation of the simulation results was carried out in two phases: 1) independent component simulations for the chillers and thermal storage tank, and 2) a combined testbed simulation of the entire hydronic system. Comparison of simulation results to the experimental data obtained from the IBAL facility showed errors within 1 °C for the temperatures outputs of both the chiller and the thermal storage model. The error is within an acceptable range for further intelligent control algorithms development. The findings from the study are summarized and presented along with areas where additional research is needed. In addition, data filtering procedures and model refinement measures utilized to improve the accuracy and accelerate the computation time of the simulation are presented.
This paper identifies general and specific quantitative and qualitative results from a study of actual operational experiences while processing 185 science, applications, and commercial payloads for the first five years of STS operations at NASA's Kennedy Space Center (KSC). All the non-DOD payloads from STS-2 through STS-33 were part of the study. The emphasis was placed on various program planning and events that affected KSC processing, payload experiences and improvements, payload hardware condition after arrival, services to customers, and the impact of STS operations and delays. From these initial considerations, operational drivers were identified, data for selected processing measurements collected and analyzed, processing criteria and options determined, and STS payload results and conclusions reached. The study showed a significant reduction in time and effort needed by STS customers and KSC to process a wide variety of payload configurations, although even the simplest payloads required more processing resources and time than were initially assumed.
The High Energy Astrophysics Costing Tool (HEACT) is a combined Expert System/Numerical Simulation to evaluate sensors and experiments proposed for space platforms in order to determine their expected performance and to assess the amount and quality of scientific information likely to be gathered by such experiments. The end product of this tool will be both a cost estimate for the experiment package as deployed and also an estimate of the amount of new scientific knowledge (both new data and reductions in the uncertainties of previous measurements) which would result from the actual deployment and operation of that experiment package. The numerical simulation part of HEACT will contain components to: (1) calculate the high energy signatures of both actual and proposed classes of astrophysical objects, and (2) model the response and resolution of the candidate sensors for observing those objects. The rule based part of the HEACT will be based on knowledge in the areas of experiment design, instrument selection, and system integration developed from experience with existing high energy astrophysics observatories, both orbiting and lofted by rockets or balloons. This paper presents mainly results from the design of the rule-based part of HEACT. It focuses on the structure of the rules and the structures used to represent the knowledge related to the design and integration of such experiments. Methods for integrating the results from numerical simulations into the expert system will also be discussed.
The DSN command system provided the capability to enter commands in a computer at the deep space stations for transmission to the spacecraft. The high-rate telemetry system operated at 16,200 bits/sec. This system will permit return to DSS 14 of full-resolution television pictures from the spacecraft tape recorder, plus the other science experiment data, during the two playback periods of each Goldstone pass planned for each corresponding orbit. Other features included 4800 bits/sec modem high-speed data lines from all deep space stations to Space Flight Operations Facility (SFOF) and the Goddard Space Flight Center, as well as 50,000 bits/sec wideband data lines from DSS 14 to the SFOF, thus providing the capability for data flow of two 16,200 bits/sec high-rate telemetry data streams in real time. The TDS performed prelaunch training and testing and provided support for the Mariner Mars 1971/Mission Operations System training and testing. The facilities of the ETR, DSS 71, and stations of the MSFN provided flight support coverage at launch and during the near-earth phase. The DSSs 12, 14, 41, and 51 of the DSN provided the deep space phase support from 30 May 1971 through 4 June 1971.
Long-baseline atom interferometer (LBAI) experiments offer unprecedented sensitivity to ultralight scalar dark matter (DM) [1], however reconstruction of a putative DM signal with traditional frequency-domain analysis requires ``perfect data (i.e., regularly-sampled with no missing samples). In a real LBAI experiment, there will undoubtedly be imperfections in the data leading to downtime. This downtime can arise from operational considerations (e.g., maintenance), the operational environment (motion of people and animals [2] or elevators), and robustness of the experimental apparatus (e.g., bad atom launches). In this work, we investigate the impact of various downtime models on the overall DM sensitivity of such an experiment. We compare the sensitivity for each downtime model as determined by a ``compound FFT analysis to a baseline no-downtime case. We also show how much sensitivity can be regained by moving to a Lomb-Scargle frequency analysis, as in [2]. Furthermore, we demonstrate reconstruction of the DM wave s phase as well as its frequency. [1] D. Antypas, et al, ``New Horizons: Scalar and Vector Ultralight Dark Matter (2022). arXiv:2203.14915 [2] J. Carlton and C. McCabe, ``From RATs to riches: mitigating anthropogenic and synanthropic noise in atom interferometer searches for ultra-light dark matter (2023). arXiv:2308.101731
Tropical tropospheric ozone fields from two different experiments performed with an off-line ozone assimilation system developed in NASA's Data Assimilation Office (DAO) are examined. Assimilated ozone fields from the two experiments are compared with the collocated ozone profiles from the Southern Hemispheric Additional Ozonesondes (SHADOZ) network. Results are presented for 1998. The ozone assimilation system includes a chemistry-transport model, which uses analyzed winds from the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The two experiments use wind fields from different versions of GEOS DAS: an operational version of the GEOS-2 system and a prototype of the GEOS-4 system. While both versions of the DAS utilize the Physical-space Statistical Analysis System and use comparable observations, they use entirely different general circulation models and data insertion techniques. The shape of the annual-mean vertical profile of the assimilated ozone fields is sensitive to the meteorological analyses, with the GEOS-4-based ozone being closest to the observations. This indicates that the resolved transport in GEOS-4 is more realistic than in GEOS-2. Remaining uncertainties include quantification of the representation of sub-grid-scale processes in the transport calculations, which plays an important role in the locations and seasons where convection dominates the transport.
Online reconstruction is key for monitoring purposes and real time analysis in High Energy and Nuclear Physics experiments. A necessary component of reconstruction algorithms is particle identification that combines information left by a particle passing through several detector components to identify the particle’s type. Of particular interest to electro-production Nuclear Physics experiments such as CLAS12 is electron identification which is used to trigger data recording. A machine learning approach was developed for CLAS12 to reconstruct and identify electrons by combining raw signals at the data acquisition level from several detector components. Here, this approach achieves an electron identification purity above 75% whilst retaining an efficiency close to 100%. The machine learning tools are capable of running at high rates exceeding the data acquisition rates and will allow electron reconstruction in real-time. This work enhances online analyses and monitoring and can contribute to improved triggering at CLAS12. This machine learning driven approach will also be crucial for experiments aiming to transition to streaming readout operations where online reconstruction will be a key component of the data taking paradigm.
To achieve ambitious decarbonization goals it is critical that buildings operate to their full potential. Commercial HVAC systems, however, experience a wide range of operational faults, adversely affecting energy consumption, occupant comfort, and maintenance costs. Analytical tools such as fault detection & diagnostics (FDD) software identify and help diagnose these types of sensing, mechanical, or control-related faults. While significant energy savings has been documented for FDD, along with limited-scale studies on technical capabilities, there is a lack of empirical data on faults being reported by FDD tools. With FDD deployment accelerating significantly over the past decade there is an opportunity to gather and analyze data on commercial HVAC operational problems at an unprecedented scale. Such data could address many questions such as: [a] What faults are most commonly reported?; and [b] How does fault reporting vary by time of year and other possible drivers? A recent study into FDD fault reporting amassed the largest U.S. dataset of commercial HVAC air-side fault records, drawn from multi-year monitoring across over 60,000 pieces of HVAC equipment. The results of this study provide granular data on fault reporting for over 90 unique fault types. In this paper we provide an overview of the research process and highlight key findings and lessons learned. This study presents an extraordinary level of detail on FDD fault reporting characteristics across many climate zones and building types. Armed with these new insights, commercial building industry stakeholders can make better informed decisions when designing, configuring, and operating commercial HVAC systems.
Following is an overview of the Chemical Steam Generator system selected to provide vacuum conditions for a new altitude test facility, the A-3 Test Stand at Stennis Space Center (SSC) in Bay St. Louis, MS. A-3 will serve as NASA s primary facility for altitude testing of the J-2X rocket engine, to be used as the primary propulsion device for the upper stages of the Ares launch vehicles. The Chemical Steam Generators (CSGs) will produce vacuum conditions in the test cell through the production and subsequent supersonic ejection of steam into a diffuser downstream of the J-2X engine nozzle exit. The Chemical Steam Generators chosen have a rich heritage of operation at rocket engine altitude test facilities since the days of the Apollo program and are still in use at NASA White Sands Test Facility (WSTF) in New Mexico. The generators at WSTF have been modified to a degree, but are still very close to the heritage design. The intent for the A-3 implementation is to maintain this heritage design as much as possible, making minimal updates only where necessary to substitute for obsolete parts and to increase reliability. Reliability improvements are especially desired because the proposed system will require 27 generators, which is nine times the largest system installed in the 1960s. Improvements were suggested by the original design firm, Reaction Motors, by NASA SSC and NASA WSTF engineers, and by the A-3 test stand design contractor, Jacobs Technology, Inc. (JTI). This paper describes the range of improvements made to the design to date, starting with the heritage generator and the minor modifications made over time at WSTF, to the modernized configuration which will be used at A-3. The paper will discuss NASA s investment in modifications to SSC s E-2 test facility fire a full-scale Chemical Steam Generator in advance of the larger steam system installation at A-3. Risk mitigation testing will be performed in early 2009 at this test facility to verify that the CSGs operate as expected. The generator which will undergo this testing is of the most recent A-3 configuration, and will be instrumented far in excess of what is normally required for operation. The extra data will allow for easier troubleshooting and more complete knowledge of expected generator performance. In addition, the early testing will give SSC personnel experience in operating the CSG systems, which will expedite the process of installation and activation at A-3. Each Chemical Steam Generator is supported by a complement of valves, instruments, and flow control devices, with the entire assembly called a "module." The generators will be installed in groups of three, historically called "units". A module is so called because of its modular ability to be replaced or serviced without disturbing the other two modules installed on the same unit. A module is pictured in Figure 1, shown with its generator secured by white bands in its shipping (vs. installed) configuration. The heritage system at WSTF is composed of a single unit (three generator modules), pictured in Figure 2 as it was installed in 1965. In contrast, A-3 will have nine units operating in parallel to achieve vacuum conditions appropriate for testing the J-2X engine. Each of the combustors operates in two modes and achieves the so-called "full-steam" mode after all three of its stages ignite. Ignition of the first stage is achieved by exciting a spark plug; the second stage and main stage are lit by the flame front of the previous stage. The main stage burns approximately 97% of the total propellant flow and uses the heat energy to vaporize water into superheated steam. While the main stage remains unlit, the combustor is in so-called "idle" mode. In the WSTF system, this idle mode is not optimized for water usage, and does not need to be, as the water is pumped from a large reservoir. The water supply at A-3 will be contained in tanks with finite volume, so water optimization is preferred for the modnized configuration. Multiple solutions for this issue have been proposed, with the leading concept being a change to the operational definition of "idle mode," with the generator running in a lower heat flux condition.
The Midcourse Space Experiment (MSX) satellite, sponsored by BMDO, is intended to gather broad-band phenomenology data on missiles, plumes, naturally occurring earthlimb backgrounds and deep space backgrounds. In addition the MSX will be used to conduct functional demonstrations of space-based space surveillance. The JHU/Applied Physics Laboratory (APL), located in Laurel, MD, is the integrator and operator of the MSX satellite. APL will conduct all operations related to the MSX and is charged with the detailed operations planning required to implement all of the experiments run on the MSX except the space surveillance experiments. The non-surveillance operations are generally amenable to being defined months ahead of time and being scheduled on a monthly basis. Lincoln Laboratory, Massachusetts Institute of Technology (LL), located in Lexington, MA, is the provider of one of the principle MSX instruments, the Space-Based Visible (SBV) sensor, and the agency charged with implementing the space surveillance demonstrations on the MSX. The planning timelines for the space surveillance demonstrations are fundamentally different from those for the other experiments. They are generally amenable to being scheduled on a monthly basis, but the specific experiment sequence and pointing must be refined shortly before execution. This allocation of responsibilities to different organizations implies the need for a joint mission planning system for conducting space surveillance demonstrations. This paper details the iterative, joint planning system, based on passing responsibility for generating MSX commands for surveillance operations from APL to LL for specific scheduled operations. The joint planning system, including the generation of a budget for spacecraft resources to be used for surveillance events, has been successfully demonstrated during ground testing of the MSX and is being validated for MSX launch within the year. The planning system developed for the MSX forms a model possibly applicable to developing distributed mission planning systems for other multi-use satellites.
Abstract Machine learning (ML) has become critical for post-acquisition data analysis in (scanning) transmission electron microscopy, (S)TEM, imaging and spectroscopy. An emerging trend is the transition to real-time analysis and closed-loop microscope operation. The effective use of ML in electron microscopy now requires the development of strategies for microscopy-centric experiment workflow design and optimization. Here, we discuss the associated challenges with the transition to active ML, including sequential data analysis and out-of-distribution drift effects, the requirements for edge operation, local and cloud data storage, and theory in the loop operations. Specifically, we discuss the relative contributions of human scientists and ML agents in the ideation, orchestration, and execution of experimental workflows, as well as the need to develop universal hyper languages that can apply across multiple platforms. These considerations will collectively inform the operationalization of ML in next-generation experimentation.