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At least 19 records

Kennedy Space Center Orion Processing Team Planning for Ground Operations

Topics in this presentation are: Constellation Ares I/Orion/Ground Ops Elements Orion Ground Operations Flow Orion Operations Planning Process and Toolset Overview, including: 1 Orion Concept of Operations by Phase 2 Ops Analysis Capabilities Overview 3 Operations Planning Evolution 4 Functional Flow Block Diagrams 5 Operations Timeline Development 6 Discrete Event Simulation (DES) Modeling 7 Ground Operations Planning Document Database (GOPDb) Using Operations Planning Tools for Operability Improvements includes: 1 Kaizen/Lean Events 2 Mockups 3 Human Factors Analysis

Letchworth, Gary↗

Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) for Transportation Hubs (Final Report)

This report summarizes the work performed under the award number EE0008524. The project develops the Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) platform as the next-generation transportation solution based on autonomous electric vehicles (AEV) serving passenger trips from and to urban transportation hubs, to substantially reduce transportation energy consumption. Extensive data collection and analyses were first conducted to understand the demand patterns and energy consumption of hub-based on-road trips. Then, a data-driven framework that consists of an analytical module and a simulation module was proposed. For the analytical module, five planning + operation tools were developed to support the planning and energy-efficient operations of urban AEV services: the charging station planning that robotically allocates charging supplies based on the stationary charging demand distribution; the transit planning and demand adaptive scheduling model that efficiently generates\ candidate transit routes from hubs to other places and dynamically adjusts the transit time table to fit the current demand; the online energy-efficient routing that learns the energy-optimal paths from observations of link-level energy consumption in real-time; the hub-based ridesharing that matches trip requests together with account for the uncertainty of future trip demand and vehicle supply; and finally, the integrated demand prediction and anomaly detection pipeline that leverages the flight/train time table and support other planning/operation tools. To demonstrate the performance of these tools, a scalable high-performance agent-based simulator was built. We divided the urban space into multiple service zones where each zone was considered as an agent for passenger generation and vehicle charging. Two types of AEV agents were coded to model two types of mobility services: AEV taxi and AEV transit. For the AEV taxi, the team implemented the functions of pickup/drop-off passengers, energy-efficient routing, ridesharing, fleet rebalancing, and recharging. For the AEV bus, the team implemented the functions of demand-adaptive route scheduling, passenger boarding, and recharging. A high-performance computing framework was introduced to receive various profiling information (such as link energy updates, vehicle speed) from the simulator instances and communicate the operational commands back to the instances. The numerical experiments show that each of the proposed operational algorithms can reduce energy consumption and improve system efficiency. Furthermore, there exists the need to collectively consider multiple planning + operational strategies as multiple strategies can influence each other in terms of performance impacts. Recommendations for future work related to AEV planning and simulation are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Enhancing Cassini Operations & Science Planning Tools

The Cassini team uses a variety of software utilities as they manage and coordinate their mission to Saturn. Most of these tools have been unchanged for many years, and although stability is a virtue for long-lived space missions, there are some less-fragile tools that could greatly benefit from modern improvements. This report shall describe three such upgrades, including their architectural differences and their overall impact. Emphasis is placed on the motivation and rationale behind architectural choices rather than the final product, so as to illuminate the lessons learned and discoveries made.These three enhancements included developing a strategy for migrating Science Planning utilities to a new execution model, rewriting the team's internal portal for ease of use and maintenance, and developing a web-based agenda application for tracking the sequence of files being transmitted to the Cassini spacecraft. Of this set, the first two have been fully completed, while the agenda application is currently in the early prototype stage.

science planning↗

Preparing General Mission Analysis Tool for Operational Maneuver Planning of the Advanced Composition Explorer Mission

The General Mission Analysis Tool (GMAT) is an open-source space mission design, analysis and trajectory optimization tool. GMAT is developed by a team of NASA, private industry, public and private contributors. GMAT is designed to model, optimize and estimate spacecraft trajectories in flight regimes ranging from low Earth orbit to lunar applications, interplanetary trajectories and other deep space missions. GMAT has also been flight qualified to support operational maneuver planning for the Advanced Composition Explorer (ACE) mission. ACE was launched in August, 1997 and is orbiting the Sun-Earth L1 libration point. The primary science objective of ACE is to study the composition of both the solar wind and the galactic cosmic rays. Operational orbit determination, maneuver operations and product generation for ACE are conducted by NASA Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF). This paper discusses the entire engineering lifecycle and major operational certification milestones that GMAT successfully completed to obtain operational certification for the ACE mission. Operational certification milestones such as gathering of the requirements for ACE operational maneuver planning, gap analysis, test plans and procedures development, system design, pre-shadow operations, training to FDF ACE maneuver planners, shadow operations, Test Readiness Review (TRR) and finally Operational Readiness Review (ORR) are discussed. These efforts have demonstrated that GMAT is flight quality software ready to support ACE mission operations in the FDF.

mission design↗

Evaluation of Crew-Centric Onboard Mission Operations Planning and Execution Tool: Year 2

Currently, mission planning for the International Space Station (ISS) is largely affected by ground operators in mission control. The task of creating a week-long mission plan for ISS crew takes dozens of people multiple days to complete, and is often created far in advance of its execution. As such, re-planning or adapting to changing real-time constraints or emergent issues is similarly taxing. As we design for future mission operations concepts to other planets or areas with limited connectivity to Earth, more of these ground-based tasks will need to be handled autonomously by the crew onboard.There is a need for a highly usable (including low training time) tool that enables efficient self-scheduling and execution within a single package. The ISS Program has identified Playbook as a potential option. It already has high crew acceptance as a plan viewer from previous analogs and can now support a crew self-scheduling assessment on ISS or on another mission. The goals of this work, a collaboration between the Human Research Program and the ISS Program, are to inform the design of systems for more autonomous crew operations and provide a platform for research on crew autonomy for future deep space missions. Our second year of the research effort have included new insights on the crew self-scheduling sessions performed by the crew through use on the HERA (Human Exploration Research Analog) and NEEMO (NASA Extreme Environment Mission Operations) analogs. Use on the NEEMO analog involved two self-scheduling strategies where the crew planned and executed two days of EVAs (Extra-Vehicular Activities). On HERA year two represented the first HERA campaign where we were able to perform research tasks. This involved selected flexible activities that the crew could schedule, mock timelines where the crew completed more complex planning exercises, usability evaluation of the crew self-scheduling features, and more insights into the limit of plan complexity that the crew could effectively self-schedule. In parallel we have added in new features and functionality in the Playbook tool based off of our insights from crew self-scheduling in the NASA analogs. In particular this year we have added in the ability for the crew to add, edit, and remove their own activities in the Playbook tool, expanding the type of planning and re-planning possible in the tool and opening up the ability for more free form plan creation. The ability to group and manipulate groups of activities from the plan task list was also added, allowing crew members to add predefined sets of activities onto their mission timeline. In addition we also added a way for crew members to roll back changes in their plan, in order to allow an undo like capability. These features expand and complement the initial self-scheduling features added in year one with the goal of making crew autonomous planning more efficient. As part of this work we have also finished developing the first version of our Playbook Data Analysis Tool, a research tool built to interpret and analyze the unobtrusively collected data obtained during the NASA analog missions through Playbook. This data which includes user click interaction as well as plan change information, through the Playbook Data Analysis Tool, allows us to playback this information as if a video camera was mounted over the crewmember's tablet. While the primary purpose of this tool is to allow usability analysis of crew self-scheduling sessions used on the NASA analog, since the data collected is structured, the tool can automatically derive metrics that would be traditionally tedious to achieve without manual analysis of video playback. We will demonstrate and discuss the ability for future derived metrics to be added to the tool. In addition to the current data and results gathered in year two we will also discuss the preparation and goals of our International Space Station (ISS) onboard technology demonstration with Playbook. This technology demonstration will be preformed as part of the CAST payload starting in late 2016.

onboard planning↗

Multi Sector Planning Tools for Trajectory-Based Operations

This paper discusses a suite of multi sector planning tools for trajectory-based operations that were developed and evaluated in the Airspace Operations Laboratory (AOL) at the NASA Ames Research Center. The toolset included tools for traffic load and complexity assessment as well as trajectory planning and coordination. The situation assessment tools included an integrated suite of interactive traffic displays, load tables, load graphs, and dynamic aircraft filters. The planning toolset allowed for single and multi aircraft trajectory planning and data communication-based coordination of trajectories between operators. Also newly introduced was a real-time computation of sector complexity into the toolset that operators could use in lieu of aircraft count to better estimate and manage sector workload, especially in situations with convective weather. The tools were used during a joint NASA/FAA multi sector planner simulation in the AOL in 2009 that had multiple objectives with the assessment of the effectiveness of the tools being one of them. Current air traffic control operators who were experienced as area supervisors and traffic management coordinators used the tools throughout the simulation and provided their usefulness and usability ratings in post simulation questionnaires. This paper presents these subjective assessments as well as the actual usage data that was collected during the simulation. The toolset was rated very useful and usable overall. Many elements received high scores by the operators and were used frequently and successfully. Other functions were not used at all, but various requests for new functions and capabilities were received that could be added to the toolset.

Prevot, Thomas↗

Using RSVP for analyzing state and previous activities for the Mars Exploration Rovers

Current developments in immersive environments for mission planning include several tools which make up a system for performing and rehearsing missions. This system, known as the Rover Sequencing and Visualization Program (RSVP), includes tools for planning long range sorties for highly autonomous rovers, tools for planning operations with robotic arms, and advanced tools for visualizing telemetry from remote spacecraft and landers. One of the keys to successful planning of rover activities is knowing what the rover has accomplished to date and understanding the current rover state. RSVP builds on the lessons learned and the heritage of the Mars Pathfinder mission This paper will discuss the tools and methodologies present in the RSVP suite for examining rover state, reviewing previous activities, visually comparing telemetered results to rehearsed results, and reviewing science and engineering imagery. In addition we will present how this tool suite was used on the Mars Exploration Rovers (MER) project to explore the surface of Mars.

Mars Exploration Rover (MER)↗

Connecting Projects to Complete the In Situ Resource Utilization Paradigm

Terrain Identify specifics such as slope, rockiness, traction parameters Identify what part of ISRU needs each Physical Geotechnical Hardness, density, cohesion, etc. Identify what part of ISRU needs each (e.g., excavation needs to know hardness, density; soil processing needs to know density, cohesion; etc.)Mineral Identify specifics Identify what part of ISRU needs each Volatile Identify specifics Identify what part of ISRU needs each Atmosphere Identify specifics Identify what part of ISRU needs each Environment Identify specifics Identify what part of ISRU needs each Resource Characterization What: Develop an instrument suite to locate and evaluate the physical, mineral, and volatile resources at the lunar poles Neutron Spectrometer Near Infrared (IR) to locate subsurface hydrogen surface water Near IR for mineral identification Auger drill for sample removal down to 1 m Oven with Gas Chromatograph Mass Spectrometer to quantify volatiles present ISRU relevance: Water volatile resource characterization and subsurface material access removal Site Evaluation Resource Mapping What: Develop and utilize new data products and tools for evaluating potential exploration sites for selection and overlay mission data to map terrain, environment, and resource information e.g., New techniques applied to generate Digital Elevation Map (DEMs) at native scale of images (1mpxl)ISRU relevance: Resource mapping and estimation with terrain and environment information is needed for extraction planning Mission Planning and Operations What: Develop and utilize tools and procedures for planning mission operations and real time changes Planning tools include detailed engineering models (e.g., power and data) of surface segment systems allows evaluation of designs ISRU relevance: Allows for iterative engineering as a function of environment and hardware performance.

Paradigm↗

Innovative Development of a Cross-Center Timeline Planning Tool

The Payload Operations Integration Center (POIC) at Marshall Space Flight Center (MSFC) supports planning, coordination and scheduling of science activities for the International Space Station (ISS) in coordination with other NASA centers, international partners, and payload developers. The ability to efficiently plan and re-plan in response to change is critical to the flight planning teams. With the achievement of supporting a fourth crew member aboard the ISS and an increasing amount of payload science activities, came the need for a dynamic, more efficient way of building timeline planning reports that could be readily updated as fast as payload science plans could change. This paper addresses software architecture considerations in the successful cross-center development of an automated planning tool with multiple data sources. It also discusses the practical implementation of a time-boxed, hybrid Agile Software Development (ASD) approach to deliver customer-driven value despite changing requirements with respect to low-Earth orbit operational planning activities. The goal of this paper is to open discussion with members of the international community and trade effective strategies for cross-center architectural and customer-developer driven collaborations, to support increasing utilization of planning and conducting science activities in space.

Pedoto, Ramon W.↗

OPSMODEL, an or-orbit operations simulation modeling tool for Space Station

The 'OPSMODEL' operations-analysis and planning tool simulates on-orbit crew operations for the NASA Space Station, furnishing a quantitative measure of the effectiveness of crew activities in various alternative Station configurations while supporting engineering and cost analyses. OPSMODEL is entirely data-driven; the top-down modeling structure of the software allows the user to control both the content and the complexity level of model definition during data base population. Illustrative simulation samples are given.

Davis, William T.↗

NASA Planning for Orion Multi-Purpose Crew Vehicle Ground Operations

The NASA Orion Ground Processing Team was originally formed by the Kennedy Space Center (KSC) Constellation (Cx) Project Office's Orion Division to define, refine and mature pre-launch and post-landing ground operations for the Orion human spacecraft. The multidisciplined KSC Orion team consisted of KSC civil servant, SAIC, Productivity Apex, Inc. and Boeing-CAPPS engineers, project managers and safety engineers, as well as engineers from Constellation's Orion Project and Lockheed Martin Orion Prime contractor. The team evaluated the Orion design configurations as the spacecraft concept matured between Systems Design Review (SDR), Systems Requirement Review (SRR) and Preliminary Design Review (PDR). The team functionally decomposed prelaunch and post-landing steps at three levels' of detail, or tiers, beginning with functional flow block diagrams (FFBDs). The third tier FFBDs were used to build logic networks and nominal timelines. Orion ground support equipment (GSE) was identified and mapped to each step. This information was subsequently used in developing lower level operations steps in a Ground Operations Planning Document PDR product. Subject matter experts for each spacecraft and GSE subsystem were used to define 5th - 95th percentile processing times for each FFBD step, using the Delphi Method. Discrete event simulations used this information and the logic network to provide processing timeline confidence intervals for launch rate assessments. The team also used the capabilities of the KSC Visualization Lab, the FFBDs and knowledge of the spacecraft, GSE and facilities to build visualizations of Orion pre-launch and postlanding processing at KSC. Visualizations were a powerful tool for communicating planned operations within the KSC community (i.e., Ground Systems design team), and externally to the Orion Project, Lockheed Martin spacecraft designers and other Constellation Program stakeholders during the SRR to PDR timeframe. Other operations planning tools included Kaizen/Lean events, mockups and human factors analysis. The majority of products developed by this team are applicable as KSC prepares 21st Century Ground Systems for the Orion Multi-Purpose Crew Vehicle and Space Launch System.

Letchworth, Gary↗

DEEP Solar: Data DrivEn Modeling and Analytics for Enhanced System Layer ImPlementation

Realizing the SETO 2030 mission of reducing solar energy costs to 3-5 c/kWh will require innovative enabling research on effective, cost-efficient integration of local PV within distribution systems. However, the intermittent and variable nature of PVs compels operators to impose conservative hosting capacity constraints. Given the extremely high variability of (intermittent and unpredictable) solar energy generation, relaxing the capacity constraints (which are currently around 15%) and achieving 100% or greater integration of renewables will require a fundamental transformation of the power grid via the utilization of exponentially larger amounts of AMI enabled fine-grained data. To address the challenges in increasing the penetration of renewable energy based DERs, this project envisions an Enhanced System Layer (ESL) at the distribution network level that is reliable, cost-effective and scalable to millions of Distributed Energy Resources (DERs)/devices. This includes developing: 1) Transformative and highly scalable machine learning based predictive analytics tools that plug into distribution system planning and provide real-time situational awareness at the distribution level for short and long-term operational planning. The tools will be built using novel data-driven energy models of millions of active nodes with AMI, 2) Adaptive stochastic analysis and optimization algorithms for real-time grid operations, 3) Dynamic Scenario Analysis using parallel Cloudenabled implementations with < 1 minute computational cycle times.

14 SOLAR ENERGY↗

Innovative Development of a Cross-Center Timeline Planning Tool

The Payload Operations Integration Center (POIC) at Marshall Space Flight Center (MSFC) is the United States focal point to support operations controllers and payload developers conducting payload science operations for the National Aeronautics and Space Administration (NASA) aboard the International Space Station (ISS). Some of the key functions are planning, coordination and scheduling of science activities. This effort occurs in coordination with other NASA centers, international partners, and payload developers. The ability to efficiently plan and re-plan in response to change is critical to the flight planning teams. Additionally, in Fall 2017, NASA will increase its ability to perform payload science operations aboard the ISS with a fourth crew member. In order to support this, there will be an increasing need to quickly plan and schedule more activities. In the past, it was cumbersome and time-consuming to consolidate copious amounts of planning and change request data from various sources. Planners would summarize information from the Johnson Space Center (JSC) Operations Planning Timeline Integration System (OPTIMIS) and manually integrate it with other data in order to produce a Timeline Planning Summary (TPS). This lengthy process of updating static documents while planning and re-planning was cumbersome, introduced human error, and was inflexible to last minute changes. There was a need for a dynamic, more efficient, less erroneous, and more concise way of building a report that could be readily updated as fast as payload science plans change.

Pedoto, Ramon W.↗

Exploring the Future Energy Value of Long-Duration Energy Storage

Long-duration energy storage is commonly viewed as a key technology for providing flexibility to the grid and broader energy systems over a multidecadal time frame. However, prior work has typically used present-day grid infrastructures to characterize the relationship between the duration and arbitrage value of storage in electricity markets. This study leverages established National Renewable Energy Laboratory grid planning and operations tools, analysis, and data to execute a price-taker model of an energy storage system for several 8760 h price series representative of current and future contiguous United States grid infrastructures with varying shares of variable renewable energy (VRE). We find that the total value of energy storage typically increases with VRE shares, but any increase in the relative value of longer storage durations over time depends on the region and grid mix. Some regions see incremental value increasing notably, up to 20–40 h in 2050, while others do not. The negative effect of lower roundtrip efficiency on value is also found to be scenario-dependent, with the energy value in higher VRE scenarios being less sensitive to roundtrip efficiency and more supportive of longer storage durations. Long-duration storage value and deployment potential are a function of evolving electricity sector infrastructure, markets, and policy, making it critical to consistently revisit potential long-duration storage contributions to the grid.

14 SOLAR ENERGY↗

Maintaining consistency between planning hierarchies: Techniques and applications

In many planning and scheduling environments, it is desirable to be able to view and manipulate plans at different levels of abstraction, allowing the users the option of viewing and manipulating either a very detailed representation of the plan or a high-level more abstract version of the plan. Generating a detailed plan from a more abstract plan requires domain-specific planning/scheduling knowledge; the reverse process of generating a high-level plan from a detailed plan Reverse Plan Maintenance, or RPM) requires having the system remember the actions it took based on its domain-specific knowledge and its reasons for taking those actions. This reverse plan maintenance process is described as implemented in a specific planning and scheduling tool, The Mission Operations Planning Assistant (MOPA), as well as the applications of RPM to other planning and scheduling problems; emphasizing the knowledge that is needed to maintain the correspondence between the different hierarchical planning levels.

Zoch, David R.↗

NASA's Autonomous Formation Flying Technology Demonstration, Earth Observing-1(EO-1)

NASA's first autonomous formation flying mission, the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft, recently completed its principal goal of demonstrating advanced formation control technology. This paper provides an overview of the evolution of an onboard system that was developed originally as a ground mission planning and operations tool. We discuss the Goddard Space Flight Center s formation flying algorithm, the onboard flight design and its implementation, the interface and functionality of the onboard system, and the implementation of a Kalman filter based GPS data smoother. A number of safeguards that allow the incremental phasing in of autonomy and alleviate the potential for mission-impacting anomalies from the on- board autonomous system are discussed. A comparison of the maneuvers planned onboard using the EO-1 autonomous control system to those from the operational ground-based maneuver planning system is presented to quantify our success. The maneuvers discussed encompass reactionary and routine formation maintenance. Definitive orbital data is presented that verifies all formation flying requirements.

Folta, David↗

Identification of pressure points in modern power systems using transfer entropy

Power shortages disrupt daily life, economic activity, and essential services. In modern power systems, weather is an increasingly important driver of reliability: high temperatures raise demand and limit transmission capacity, and calm or cloudy periods reduce wind and solar supply. Using a data-driven analysis, this study identifies grid infrastructure whose operating patterns help predict power shortages. The results show that reliability risks often emerge from interacting stresses across generation, transmission, and demand, rather than from single bottlenecks. By clarifying how system stress propagates through the grid, this diagnostic perspective helps explain why shortages occur under specific conditions and can complement traditional planning and operational tools to support adaptive reliability strategies, targeted monitoring, and coordinated infrastructure investments.

power systems↗

Development of a health monitoring framework: Application to a supercritical pulverized coal-fired boiler

In this study, this work details the development of a physics-based equipment health monitoring framework for a supercritical boiler, using first-principles models to estimate the remaining useful life (RUL) of its components. The framework accounts for fatigue and creep life consumption, generating spatio-temporal variations in mechanical and thermal stress. Analysis of the stress profile throughout the boiler highlights the finishing superheater inlet steam header as a vulnerable location susceptible to damage from cycling operation. The framework also yields quantified uncertainty in the RUL projection for specific locations, accounting for uncertainties in material properties and boiler operation. Results indicate that operational uncertainties (e.g., seasonal variation and operational strategy) and material properties (e.g., rupture time coefficients, Young’s modulus, yield strength, and coefficient of thermal expansion) significantly impact the RUL of the finishing superheater inlet steam header. Additionally, case studies demonstrate the use of the health monitoring framework as a predictive tool for operational planning under uncertainty, including scenarios with and without updates on the operation of the boiler.

20 FOSSIL-FUELED POWER PLANTS↗