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At least 991 records · Page 55

Resource Prospector (RP) - Early Prototyping and Development

The Resource Prospector (RP) is an In-Situ Resource Utilization (ISRU) technology demonstration mission under study by the NASA Human Exploration and Operations Mission Directorate's (HEOMD) Advanced Exploration Systems (AES) Division. The mission, currently planned to launch in 2020, will demonstrate extraction of oxygen from lunar regolith to validate ISRU capability. The mission will address key Strategic Knowledge Gaps (SKGs) for robotic and human exploration to the Moon, Near Earth Asteroids (NEAs), and ultimately Mars, as well as meet the strategic goals of the Global Exploration Roadmap (GER), offered by the International Space Exploration Coordination Group (ISECG). In this roadmap, the use of local resources is specifically addressed relating to human exploration. RP will provide knowledge to inform the selection of future mission destinations, support the development of exploration systems, and reduce the risk associated with human exploration. Expanding human presence beyond low-Earth orbit to asteroids and Mars will require the maximum possible use of local materials, so-called in-situ resources. The moon presents a unique destination to conduct robotic investigations that advance ISRU capabilities, as well as providing significant exploration and science value. Lunar regolith contains useful resources such as oxygen, water, silicon, and light metals, like aluminum and titanium. Oxygen can be separated from the regolith for life support (breathable air), or used to create rocket propellant (oxidizer). Regolith can be used to protect against radiation exposure, be processed into solar cells, or used to manufacture construction materials such as bricks and glass. RP will characterize the constituents and distribution of water and other volatiles at the poles of the Moon, enabling innovative uses of local resources, in addition to validating ISRU capabilities. This capability, as well as a deeper understanding of regolith, will be valuable in the exploration of near-Earth asteroids (NEAs) and Mars. In order to reduce risk and explore system designs, the RP project is attempting two-fold approaches to development as it looks towards flight. We continue to explore flight planning, requirements, and interfaces definition by using Engineering Test Units (ETUs), looking towards lunar deployment, while also using fiscal year 2015 to develop, build and test an earth-terrestrial prototype rover and payload system. This terrestrial prototype, called "RP15", is built to both inform the system design, and to be a partnership advocacy tool for this unique mission. RP15 must be affordable within the resource and time constraints of fiscal year 2015, while working to the following Needs, Goals, and Objectives provided by HEOMD/AES: 1. Demonstrate rover mobility in a 1g environment 2. The Surface Segment (prototype rover + payload system) shall represent the flight system concept with as much fidelity as affordable (limited by cost and schedule) - Surface Segment shall be the approximate size/dimension/footprint -Surface Segment shall package all the expected devices (instruments, systems, etc.), even if some facets are mocked-up due to time/cost constraints -Overall Surface Segment fidelity negotiable to make achievable 3. Priority should be given to illustrating mission functionality over support functionality, which exists solely to support mission functionality This paper will provide an overview of RP project developments, including the design and build, capturing the development and initial integrated testing of RP15 in relevant environments.

Lunar↗

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

The currently planned schedule for advanced Environmental Control and Life Support System (ECLSS) development and test activities to support human exploration missions is unlikely to generate sufficient data to enable statistically-supportable, precise Orbital Replacement Unit (ORU) failure rate estimates to meet existing crew safety expectations. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches –namely regular resupply and rapid abort capabilities –will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of International Space Station (ISS) ECLSS operations, a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass. A Bayesian estimation approach, such as the one currently implemented by the ISS Program, can reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, any inaccuracy in theseprior estimates currently hasa strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Reliability↗

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

The currently planned schedule for advanced Environmental Control and Life Support System (ECLSS) development and test activities to support human exploration missions is unlikely to generate sufficient data to enable statistically-supportable, precise Orbital Replacement Unit (ORU) failure rate estimates to meet existing crew safety expectations. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches –namely regular resupply and rapid abort capabilities –will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of International Space Station (ISS) ECLSS operations, a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass. A Bayesian estimation approach, such as the one currently implemented by the ISS Program, can reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, any inaccuracy in theseprior estimates currently hasa strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Reliability↗

Multi-Mission Automated Task Invocation Subsystem

Multi-Mission Automated Task Invocation Subsystem (MATIS) is software that establishes a distributed data-processing framework for automated generation of instrument data products from a spacecraft mission. Each mission may set up a set of MATIS servers for processing its data products. MATIS embodies lessons learned in experience with prior instrument- data-product-generation software. MATIS is an event-driven workflow manager that interprets project-specific, user-defined rules for managing processes. It executes programs in response to specific events under specific conditions according to the rules. Because requirements of different missions are too diverse to be satisfied by one program, MATIS accommodates plug-in programs. MATIS is flexible in that users can control such processing parameters as how many pipelines to run and on which computing machines to run them. MATIS has a fail-safe capability. At each step, MATIS captures and retains pertinent information needed to complete the step and start the next step. In the event of a restart, this information is retrieved so that processing can be resumed appropriately. At this writing, it is planned to develop a graphical user interface (GUI) for monitoring and controlling a product generation engine in MATIS. The GUI would enable users to schedule multiple processes and manage the data products produced in the processes. Although MATIS was initially designed for instrument data product generation,

Cheng, Cecilia S.↗

Recent Developments in Security-Constrained AC Optimal Power Flow: Overview of Challenge 1 in the ARPA-E Grid Optimization Competition

In “Recent Developments in Security-Constrained AC Optimal Power Flow: Overview of Challenge 1 in the ARPA-E Grid Optimization Competition,” we review the state of the art in practical algorithms for scheduling power-systems operations in the short term and the results of the recent competition organized by the U.S. Advanced Research Projects Agency–Energy. We explain the mixed-integer nonlinear formulation used in the competition for nonspecialists in electrical engineering, the context and organization of the competition, and the performance of competitors. We find that the collective approaches and results of competitors provide support for efforts to move nonlinear optimization techniques into industrial applications, as they have proven to be a robust and efficient alternative to current linear approximation techniques.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Geoscience Laser Altimeter System (GLAS) for the ICESAT Mission

The Laser In space Technology Experiment, Shuttle Laser Altimeter and the Mars Observer Laser Altimeter have demonstrated accurate measurements of atmospheric backscatter and Surface heights from space. The recent MOLA measurements of the Mars surface have 40 cm vertical resolution and have reduced the global uncertainty in Mars topography from a few km to about 5 m. The Geoscience Laser Altimeter System (GLAS) is a next generation lidar for Earth orbit being developed as part of NASA's Icesat Mission. The GLAS design combines a 10 cm precision surface lidar with a sensitive dual wavelength cloud and aerosol lidar. GLAS will precisely measure the heights of the Earth's polar ice sheets, establish a grid of accurate height profiles of the Earth's land topography, and profile the vertical backscatter of clouds and aerosols on a global scale. GLAS is being developed to fly on a small dedicated spacecraft in a polar orbit with a 590 630 km altitude at inclination of 94 degrees. GLAS is scheduled to launch in the summer 2001 and to operate continuously for a minimum of 3 years with a goal of 5 years. The primary mission for GLAS is to measure the seasonal and annual changes in the heights of the Greenland and Antarctic ice sheets. GLAS will continuously measure the vertical distance from orbit to the Earth's surface with 1064 nm pulses from a ND:YAG laser at a 40 Hz rate. Each 5 nsec wide laser pulse is used to produce a single range measurement, and the laser spots have 66 m diameter and about 170 m center-center spacings. When over land GLAS will profile the heights of the topography and vegetation. The GLAS receiver uses a 1 m diameter telescope and a Si APD detector. The detector signal is sampled by an all digital receiver which records each surface echo waveform with I nsec resolution and a stored echo record lengths of either 200, 400, or 600 samples. Analysis of the echo waveforms within the instrument permits discrimination between cloud and surface echoes. Ground based echo analysis permits precise ranging, determining the roughness or slopes of the surface as well as the vertical distributions of vegetation illuminated by the laser. Accurate knowledge of the laser beam's pointing angle is needed to prevent height biases when over sloped surfaces. For surfaces with 2 deg. slopes, knowledge of pointing angle of the beam's centroid to about 8 urad is needed to achieve 10 cm height accuracy. GLAS uses a stellar reference system (SRS) to determine the pointing angle of each laser firing relative to inertial space. The SRS uses a high precision star camera oriented toward local zenith and a gyroscope to determine the inertial orientation of the SRS optical bench. The far field pattern of each laser is measured pulse relative to the star camera with a laser reference system (LRS). Optically measuring each laser far field pattern relative to the orientation of the star camera and gyroscope permits the precise pointing angle of each laser pulse to be determined. GLAS will also determine the vertical distributions of clouds and aerosols by measuring the vertical profile of laser energy backscattered by the atmosphere at both 1064 and 532 nm. The 1064 nm measurements use the Si APD detector and profile the height and vertical structure of thicker clouds. The measurements at 532 nm use new highly sensitive photon counting, detectors, and measure the height distributions of very thin Clouds and aerosol layers. With averaging these can be used to determine the height of the planetary boundary layer. The instrument design and expected performance will be discussed.

Abshire, James B.↗

Building a Propulsion Experiment Project Management Environment

What do you get when you cross rocket scientists with computer geeks? It is an interactive, distributed computing web of tools and services providing a more productive environment for propulsion research and development. The Rocket Engine Advancement Program 2 (REAP2) project involves researchers at several institutions collaborating on propulsion experiments and modeling. In an effort to facilitate these collaborations among researchers at different locations and with different specializations, researchers at the Information Technology and Systems Center,' University of Alabama in Huntsville, are creating a prototype web-based interactive information system in support of propulsion research. This system, to be based on experience gained in creating similar systems for NASA Earth science field experiment campaigns such as the Convection and Moisture Experiments (CAMEX), will assist in the planning and analysis of model and experiment results across REAP2 participants. The initial version of the Propulsion Experiment Project Management Environment (PExPM) consists of a controlled-access web portal facilitating the drafting and sharing of working documents and publications. Interactive tools for building and searching an annotated bibliography of publications related to REAP2 research topics have been created to help organize and maintain the results of literature searches. Also work is underway, with some initial prototypes in place, for interactive project management tools allowing project managers to schedule experiment activities, track status and report on results. This paper describes current successes, plans, and expected challenges for this project.

Keiser, Ken↗

Atikokan Digital Twin: Machine learning in a biomass energy system

The Atikokan Generating Station, operated by Ontario Power Generation, has a 200 MW, biomass-fired tower boiler that operates on a dispatch schedule with a five-minute cycle. The boiler is generally operated in the range of 40–100 MW using two of five burner levels. In order to optimize boiler performance, we propose the implementation of a unique digital twin. Our digital twin abstraction couples Bayesian inference from science-based models and from observations (machine learning) with decision theory to predict operating-variable set points that optimize the physical asset (the boiler) in the presence of uncertainty (artificial intelligence). We focus this paper on the continuous Bayesian machine learning part of the Atikokan Digital Twin; we discuss decision theory in a companion paper. We identify and learn about 12 operational, model, and measured-output parameters and their uncertainties from high-fidelity, science-based simulations of the Atikokan boiler and from the observed measurements at the power plant. Since the goal of the Atikokan Digital Twin is to implement it online in real time, we require fast function evaluations for the quantities of interest extracted from the simulations in the Bayesian analysis. We use Gaussian process regression/interpolation to create accurate, robust surrogate models. We define the Bayesian priors and likelihood function and solve for the posterior distributions of the 12 parameters. Here we then propagate these distributions (i.e., parameters with uncertainty) into the predicted distributions of 790 quantities of interest to learn about the relative importance of various sources of error including experimental, model, and operating-parameter errors.

09 BIOMASS FUELS↗

Comparison of Deterministic and Statistical Models for Water Quality Compliance Forecasting in the San Joaquin River Basin, California

Model selection for water quality forecasting depends on many factors including analyst expertise and cost, stakeholder involvement and expected performance. Water quality forecasting in arid river basins is especially challenging given the importance of protecting beneficial uses in these environments and the livelihood of agricultural communities. In the agriculture-dominated San Joaquin River Basin of California, real-time salinity management (RTSM) is a state-sanctioned program that helps to maximize allowable salt export while protecting existing basin beneficial uses of water supply. The RTSM strategy supplants the federal total maximum daily load (TMDL) approach that could impose fines associated with exceedances of monthly and annual salt load allocations of up to $1 million per year based on average year hydrology and salt load export limits. The essential components of the current program include the establishment of telemetered sensor networks, a web-based information system for sharing data, a basin-scale salt load assimilative capacity forecasting model and institutional entities tasked with performing weekly forecasts of river salt assimilative capacity and scheduling west-side drainage export of salt loads. Web-based information portals have been developed to share model input data and salt assimilative capacity forecasts together with increasing stakeholder awareness and involvement in water quality resource management activities in the river basin. Two modeling approaches have been developed simultaneously. The first relies on a statistical analysis of the relationship between flow and salt concentration at three compliance monitoring sites and the use of these regression relationships for forecasting. The second salt load forecasting approach is a customized application of the Watershed Analysis Risk Management Framework (WARMF), a watershed water quality simulation model that has been configured to estimate daily river salt assimilative capacity and to provide decision support for real-time salinity management at the watershed level. Analysis of the results from both model-based forecasting approaches over a period of five years shows that the regression-based forecasting model, run daily Monday to Friday each week, provided marginally better performance. However, the regression-based forecasting model assumes the same general relationship between flow and salinity which breaks down during extreme weather events such as droughts when water allocation cutbacks among stakeholders are not evenly distributed across the basin. A recent test case shows the utility of both models in dealing with an exceedance event at one compliance monitoring site recently introduced in 2020.

54 ENVIRONMENTAL SCIENCES↗

The Search for Chiral Asymmetry as a Potential Biosignature in Samples from Mars

The search for evidence of extraterrestrial life in our solar system has been guided by our under-standing of terrestrial biology and its associated biosignatures. The observed homochirality in all life on Earth, that is, the predominance of “left-handed” or L-amino acids and “right-handed” or D-sugars, is a unique property of life that is crucial for molecular recognition, enzymatic function, information storage and structure, and is thought to be a prerequisite for the origin or early evolution of life. Therefore, the detection of L- or D-excesses of chiral amino acids or sugars could be a powerful indicator of extant or extinct life on Mars or other habitable environments in our solar system. However, studies of primitive meteorites have revealed that they contain extraterrestrial amino acids and sugar acids with large enantiomeric excesses (60% and higher) that resulted from non-biological processes [1], complicating the use of chiral asymmetry by itself as a definitive biosignature. The exploration of habitable environments on Mars, including an assessment of the preservation potential for complex organics of either abiotic or biological origin, is an objective of both current and future Mars missions. Now with the unambiguous detection of indigenous organic matter in sedimentary rocks by the Sample Analysis at Mars (SAM) instrument suite on Mars [2-5], NASA’s Curiosity rover has found evidence of the preservation of potential chemical biosignatures in the martian near surface. Although amino acids have not yet been identified by in situ measurements on Mars [5], indigenous achiral amino acids have been identified in one martian meteorite [6]. It is expected that amino acid racemization would be very slow and any chiral or isotopic signatures from an extinct martian biota could be preserved for billions of years, given the extremely cold and dry surface conditions [7]. The ESA/Roscosmos ExoMars mission scheduled for launch next year includes the Rosalind Franklin rover designed to acquire samples from a depth of ~2 m and deliver them to a suite of instruments, including the Mars Organic Molecule Analyzer (MOMA). The MOMA instrument contains a wet chemistry experiment designed specifically for the detection of amino acids and measurement of their enantiomeric compositions [8]. The complexity and limited duration of spaceflight operations, and the known analytical challenges associated with in situ extraction and characterization of trace reduced organic com-pounds in ancient rocks, make it challenging to determine the origins of martian organic matter found to date. Coordinated state-of-the-art laboratory measurements of returned samples from Mars that include spatially resolved chemical, mineralogical, bulk and molecule-specific isotopic, and enantiomeric measurements will be required to firmly establish whether the complex organic matter detected on Mars derives from bio-tic or abiotic processes. Ultimately, Mars Sample Return of rock cores collected by NASA’s Perseverance rover may be our best chance of identifying chemical biosignatures, including any chiral amino acid asymmetry resulting from a past or present martian biota, if one ever existed on Mars. Here we review our current knowledge of the distributions, and enantiomeric and isotopic com-positions of amino acids found in meteorites compared to terrestrial biochemistry. We also propose a set of measurement criteria that should be used to help establish the sources of any amino acids detected in samples returned from Mars using state-of-the-art gas and liquid chromatography mass spectrometry techniques [1].

D P Glavin↗

Feedback on the Electric Emergency Incident and Disturbance Report, OE-417

The US Department of Energy (DOE) Office of Electricity (OE) mandates requirements for reporting electric emergencies and disruptions in the United States. Specific electric power industry organizations (such as balancing authorities, reliability coordinators, some generating entities, and electric utilities) report this information through the OE-417 Electric Emergency Incident and Disturbance Report via Form OE-417. Entities are required to submit Form OE-417 when at least one of the qualifying 26 criteria is met pursuant to Section 13(b) of the Federal Energy Administration Act of 1974 (Public Law 93-275). Entities are required to report, within 6 hours of the incident, loss of electric service to 50,000 customers or more for 1 hour or longer. The deadline for submitting Form OE-417 depends on the nature of the incident. An updated Form OE-417 Schedule 1 and all of Schedule 2 are both due within 72 hours of the incident to provide complete disruption information. Additionally, a Final Report must be filed within 72 hours of the incident, unless an interim update has been provided. If the incident meets specific criteria, the form must be filed within one hour, six hours, or by the later of 24 hours after the recognition of the incident or by the end of the next business day.1 The ability of DOE to respond quickly to energy emergencies that could affect the nation’s infrastructure and help alleviate or prevent further disruptions depends on the industry’s prompt and complete submission of information. This report summarizes current issues with Form OE-417 and the reporting process and presents recommendations for improvements.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Forecasting Lightning at Kennedy Space Center/Cape Canaveral Air Force Station, Florida

The Applied Meteorology Unit (AMU) developed a set of statistical forecast equations that provide a probability of lightning occurrence on Kennedy Space Center (KSC) I Cape Canaveral Air Force Station (CCAFS) for the day during the warm season (May September). The 45th Weather Squadron (45 WS) forecasters at CCAFS in Florida include a probability of lightning occurrence in their daily 24-hour and weekly planning forecasts, which are briefed at 1100 UTC (0700 EDT). This information is used for general scheduling of operations at CCAFS and KSC. Forecasters at the Spaceflight Meteorology Group also make thunderstorm forecasts for the KSC/CCAFS area during Shuttle flight operations. Much of the current lightning probability forecast at both groups is based on a subjective analysis of model and observational data. The objective tool currently available is the Neumann-Pfeffer Thunderstorm Index (NPTI, Neumann 1971), developed specifically for the KSCICCAFS area over 30 years ago. However, recent studies have shown that 1-day persistence provides a better forecast than the NPTI, indicating that the NPTI needed to be upgraded or replaced. Because they require a tool that provides a reliable estimate of the daily thunderstorm probability forecast, the 45 WS forecasters requested that the AMU develop a new lightning probability forecast tool using recent data and more sophisticated techniques now possible through more computing power than that available over 30 years ago. The equation development incorporated results from two research projects that investigated causes of lightning occurrence near KSCICCAFS and over the Florida peninsula. One proved that logistic regression outperformed the linear regression method used in NPTI, even when the same predictors were used. The other study found relationships between large scale flow regimes and spatial lightning distributions over Florida. Lightning, probabilities based on these flow regimes were used as candidate predictors in the equation development. Fifteen years (1 989-2003) of warm season data were used to develop the forecast equations. The data sources included a local network of cloud-to-ground lightning sensors called the Cloud-to-Ground Lightning Surveillance System (CGLSS), 1200 UTC Florida synoptic soundings, and the 1000 UTC CCAFS sounding. Data from CGLSS were used to determine lightning occurrence for each day. The 1200 UTC soundings were used to calculate the synoptic-scale flow regimes and the 1000 UTC soundings were used to calculate local stability parameters, which were used as candidate predictors of lightning occurrence. Five logistic regression forecast equations were created through careful selection and elimination of the candidate predictors. The resulting equations contain five to six predictors each. Results from four performance tests indicated that the equations showed an increase in skill over several standard forecasting methods, good reliability, an ability to distinguish between non-lightning and lightning days, and good accuracy measures and skill scores. Given the overall good performance the 45 WS requested that the equations be transitioned to operations and added to the current set of tools used to determine the daily lightning probability of occurrence.

Lambert, Winfred↗

Research, Development and Fabrication of Lithium Solar Cells

This report continues studies on cells made with low temperature (<400degC) single-cycle, lithium diffusion schedules. Measurements of concentration of lithium at the back surface showed that C(sub S) changes with time consisting of a build-up to a maximum value (above 10(exp 17) cm(exp -3)) with gradual decrease at longer diffusion times. Using the estimated C(sub S) values, theoretical lithium profiles were calculated. The calculated concentration near the PN junction was higher than those measured by the capacitance voltage (C-V) technique. The calculated concentration gradients were one-seventh of those measured by C-V methods. Both the concentration and its gradient were proportional to C(sub S). Estimates of C(sub S) obtained by extrapolating from C-V measured values of concentration and gradient near the PN junction, showed a decrease in C(sub S) for longer diffusion times. This fact supported the trend observed in Shipment C-13, where,, at longer times, the spread in values of V(sub oc), lithium concentration, and gradient became greater. The general conclusion was that the I-V characteristics were well controlled, with good cell output, but for longer diffusion times the lithium concentration gradient could have wider spread. The work described has led to greater insight into the lithium distribution dependence on the surface conditions. The surface conditions could be changed by varying the method used to apply lithium. Vacuum evaporation of lithium shows promise, and another exhaustive test of this method is in progress. Shipment C-13 is summarized, and the succeeding lots (C-14, C-15) are described. It is felt that improved monitoring of cell properties is at hand, and that the control of cell fabrication processes has advanced to where the effects of subtle differences in lithium distribution can now be seen. Evaluation is continuing on the best method to scale up the fabrication steps. A different sequence of fabrication is planned for Shipments C-14 and C-15.

Iles, Peter A.↗

Using the cFS Command and Data Dictionary (CCDD) to Automate Software Development on Habulous

Final paper is attached. The NASA developed Core Flight System (cFS) is a reusable software architecture that has been used on multiple spaceflight missions. By using this framework, missions are able to reuse code from other missions, as well as leverage deployment onto similar computer architectures (i.e. not "reinvent the wheel" on each new mission). The success in the cFS concept can be seen in the large number of projects using cFS at FSW-2018. The Habulous project is an Earth-based testbed, used for hardware and software that may one day be used on a future space habitat unit, with many participating groups from various NASA centers and aerospace organizations around the country. The distributed nature of the various teams mean that defining (and following) an interface definition is critical on the project. Additionally, since various groups use various types of computer hardware (32/64-bit, big/little endian, Linux/VxWorks/Windows) many additional complications exist in interfacing all the various components into a final integrated system. cFS is used on the majority the flight software (FSW) in running in Habulous. But some subsystems have elected to not use cFS, and use a software bridge (called SBN_lib) to interact with the other cFS nodes in Habulous. In order to most efficiently develop the FSW, a central database is used to define and store each message sent by cFS. A Command and Data Dictionary (CDD) is something nearly universal on spacecraft, but as a team we worked to develop the CDD before the SW development was complete, and not treat it like "as built" documentation. To manage the CDD, the cFS Command and Data Dictionary (CCDD) tool was chosen (available from NASA as open source software). The CCDD tool has successfully been used to automate/autocode a large amount of software used on Habulous, as we are hoping to use it to define even more items in the future (time-triggered Ethernet (TTE) network maps, CPU scheduling). Additionally, Habulous has been exploring the use of cFS on wildly heterogeneous CPUs, and how to coordinate all those various machines using/extending the software bus – network (SBN) application in cFS, as well as TTE to coordinate message passing between various synchronized machines. The major topics to be covered in the presentation are: (1) Updating to the CCSDS_v2 extended headers (and using CPU# as subsystem ID). (2) Managing all the message identification numbers for each cFS message sent/received on any of the various CPUs. (3) Using the CCDD information to automatically generate the C-header files that define the structure for all software bus (SB) commands/telemetry messages. (4) Using the CCDD to automatically generate XML Telemetry and Command Exchange (XTCE) files, which streams display production/integration/testing in a web based display architecture (5) Extending/customizing SBN to pass messages among computers on multiple networks. (6) Using "Protobetter" inside SBN to manage different endian-ness/architectures. (7) Using SBN_lib to allow non-cFS node to communicate with cFS nodes. (8) Developing TTE network and schedule tables for all the various CPUs to use.

Hirsh, Robert L.↗

[Exploring Aeronautics]

This summer I have been working with the N.A.S.A. Project at Cuyahoga Community College (Tri-C) under the title of Exploring Aeronautics Project Leader. The class that I have worked with is comprised of students that will enter the eighth grade in the fall of 2004. The program primarily focuses upon math proficiency and individualized class projects. My duties have encompassed both realms. During the first 2-3 weeks of my internship, I worked at NASA Glenn Research Center (GRC) researching, organizing, and compiling information for weekly Scholastic Challenges and the Super Scholastic Challenge. I was able to complete an overview of Scholastic Challenge and staff responsibilities regarding the competition; a proposal for an interactive learning system, Quizdom; a schedule for challenge equipment, as well as a schedule listing submission deadlines for the staff. Also included in my tasks, during these first 2-3 weeks, were assisting Tammy Allen and Candice Thomas with the student application review and interview processes for student applicants. For the student and parent orientation, I was assigned publications and other varying tasks to complete before the start of the program. Upon the commencement of the program, I changed location from NASA GRC to Tri-C Metro Campus, where student classes for the Cleveland site are held. During the duration of the program, I work with the instructor for the Exploring Aeronautics class, kkkk, assisting in classroom management, daily attendance, curriculum, project building, and other tasks as needed. These tasks include the conducting of the weekly competition, known as Scholastic Challenge. As a Project Leader, I am also responsible for one subject area of the Scholastic Challenge aspect of the N.A.S.A. Project curriculum. Each week I have to prepare a mission that the participants will take home the following Monday and at least 10 questions that will be included in the pool of questions used for the Scholastic Challenge competition on Thursdays. For at least one of these competitions, I must compile all mission and question information submitted by the staff, distribute missions to the students, and enter questions into Jeopardy formatted PowerPoint presentation. Unique to the N.A.S.A. Project are its Saturday sessions and opportunities for field trips. As a Project Leader, I am required to attend all field trips and Saturday sessions held for participants and their parent(s)/guardian(s). The Saturday sessions do not require my assistance because they are facilitated by a contracting company, Imhotep. This leaves my duties to observation unless instructed otherwise.

Robinson, Brandi↗

Modeling and Optimizing Pumped Storage in a Multi-stage Large Scale Electricity Market under Portfolio Evolution

To leverage the fast-ramping capability of resources to provide great value to the grid, electricity system operators such as the Midcontinent Independent System Operator (MISO) continue to evolve their approaches for integrating energy storage resources, including pumpedstorage hydro (PSH), into the electricity markets. However, new challenges arise in modeling and optimizing these energy-limited resources across multiple market clearing processes and planning studies with uncertainties and imperfect information. For instance, current market practices of PSH owners specifying pumping/generating hours can result in sub-optimal generation dispatch. Letting grid operators optimize PSH with the consideration of multiple operating modes and energy limitation constraints can potentially bring economic benefits to both the system and the PSH owners. However, in multi-stage clearing process of electricity markets, utilizing the PSH flexibility to deal with realized uncertainties can cause deviation in the multi-stage scheduling processes. The resulting financial risks from the schedule deviation may not be acceptable to PSH owners. In addition, to effectively utilize this energy limited resource, the state of charge (SOC) constraints of PSH needs to be continuously optimized and the marginal cost of deviation need to reflect the expected cost to purchase or sell energy at future times to compensate for deviations. This project aims to develop a prototype enhanced PSH model and improved price signals in the multi-stage market clearing process with proper consideration of the unique characteristics of PSH, in order to better align underlying PSH capabilities with evolving grid needs, particularly including the needs for more frequent and larger cycling to manage variability and uncertainty from renewables.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Data-Driven Method for Adaptive Reserve Requirement Estimation via Probabilistic Net Load Forecasting

The University of Colorado Boulder Boulder, CO, 80309, USA With the increasing penetration of renewable energy, power systems are subject to more uncertainty. This makes power system reserve scheduling more challenging. Most of the current reserve requirement determination methods calculate reserve requirements based on historical data, which does not consider the real-time or future system uncertainty. In this paper, a data-driven method is developed to determine the non-spinning reserve requirement (NSRR) in the Electric Reliability Council of Texas (ERCOT) system. The method follows the procedure of the current ERCOT method while adaptively determining the NSRR based on probabilistic net load forecasts. Case studies with two years of ERCOT data show that the developed method significantly reduces the NSRR by introducing an adaptive temporal resolution and update rate. Sensitivity analysis with different forecasting and percentile thresholds indicates the flexibility of the developed method.

non-spinning reserve↗

Statistical Treatment of Earth Observing System Pyroshock Separation Test Data

The Earth Observing System (EOS) AM-1 spacecraft for NASA's Mission to Planet Earth is scheduled to be launched on an Atlas IIAS vehicle in June of 1998. One concern is that the instruments on the EOS spacecraft are sensitive to the shock-induced vibration produced when the spacecraft separates from the launch vehicle. By employing unique statistical analysis to the available ground test shock data, the NASA Lewis Research Center found that shock-induced vibrations would not be as great as the previously specified levels of Lockheed Martin. The EOS pyroshock separation testing, which was completed in 1997, produced a large quantity of accelerometer data to characterize the shock response levels at the launch vehicle/spacecraft interface. Thirteen pyroshock separation firings of the EOS and payload adapter configuration yielded 78 total measurements at the interface. The multiple firings were necessary to qualify the newly developed Lockheed Martin six-hardpoint separation system. Because of the unusually large amount of data acquired, Lewis developed a statistical methodology to predict the maximum expected shock levels at the interface between the EOS spacecraft and the launch vehicle. Then, this methodology, which is based on six shear plate accelerometer measurements per test firing at the spacecraft/launch vehicle interface, was used to determine the shock endurance specification for EOS. Each pyroshock separation test of the EOS spacecraft simulator produced its own set of interface accelerometer data. Probability distributions, histograms, the median, and higher order moments (skew and kurtosis) were analyzed. The data were found to be lognormally distributed, which is consistent with NASA pyroshock standards. Each set of lognormally transformed test data produced was analyzed to determine if the data should be combined statistically. Statistical testing of the data's standard deviations and means (F and t testing, respectively) determined if data sets were significantly different at a 95-percent confidence level. If two data sets were found to be significantly different, these families of data were not combined for statistical purposes. This methodology produced three separate statistical data families of shear plate data. For each population, a P99.1/50 (probability/confidence) per-separation-nut firing level was calculated. By using the binomial distribution, Lewis researchers determined that this pernut firing level was equivalent to a P95/50 per-flight confidence level. The overall envelope of the per-flight P95/50 levels led to Lewis' recommended EOS interface shock endurance specification. A similar methodology was used to develop Lewis' recommended EOS mission assurance levels. The available test data for the EOS mission are significantly larger than for a normal mission, thus increasing the confidence level in the calculated expected shock environment. Lewis significantly affected the EOS mission by properly employing statistical analysis to the data. This analysis prevented a costly requalification of the spacecraft's instruments, which otherwise would have been exposed to significantly higher test levels.

McNelis, Anne M.↗