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Team Structures and Processes in the Design of Space Missions
We consider team dynamics a component of the engineering design process for space missions and explore the possibility of improvements in management of team dynamics to gain additional efficiencies.
Flight Dynamics Mission Support and Quality Assurance Process
This paper summarizes the method of the Computer Sciences Corporation Flight Dynamics Operation (FDO) quality assurance approach to support the National Aeronautics and Space Administration Goddard Space Flight Center Flight Dynamics Support Branch. Historically, a strong need has existed for developing systematic quality assurance using methods that account for the unique nature and environment of satellite Flight Dynamics mission support. Over the past few years FDO has developed and implemented proactive quality assurance processes applied to each of the six phases of the Flight Dynamics mission support life cycle: systems and operations concept, system requirements and specifications, software development support, operations planing and training, launch support, and on-orbit mission operations. Rather than performing quality assurance as a final step after work is completed, quality assurance has been built in as work progresses in the form of process assurance. Process assurance activities occur throughout the Flight Dynamics mission support life cycle. The FDO Product Assurance Office developed process checklists for prephase process reviews, mission team orientations, in-progress reviews, and end-of-phase audits. This paper will outline the evolving history of FDO quality assurance approaches, discuss the tailoring of Computer Science Corporations's process assurance cycle procedures, describe some of the quality assurance approaches that have been or are being developed, and present some of the successful results.
Balancing Science Objectives and Operational Constraints: A Mission Planner's Challenge
The Air Force minute sensor technology integration (MSTI-3) satellite's primary mission is to characterize Earth's atmospheric background clutter. MSTI-3 will use three cameras for data collection, a mid-wave infrared imager, a short wave infrared imager, and a visible imaging spectrometer. Mission science objectives call for the collection of over 2 million images within the one year mission life. In addition, operational constraints limit camera usage to four operations of twenty minutes per day, with no more than 10,000 data and calibrating images collected per day. To balance the operational constraints and science objectives, the mission planning team has designed a planning process to e event schedules and sensor operation timelines. Each set of constraints, including spacecraft performance capabilities, the camera filters, the geographical regions, and the spacecraft-Sun-Earth geometries of interest, and remote tracking station deconflictions has been accounted for in this methodology. To aid in this process, the mission planning team is building a series of tools from commercial off-the-shelf software. These include the mission manifest which builds a daily schedule of events, and the MSTI Scene Simulator which helps build geometrically correct scans. These tools provide an efficient, responsive, and highly flexible architecture that maximizes data collection while minimizing mission planning time.
Team Efficiencies Within a Model-Driven Design Process
(Smith & Koenig 1998) formulated a model-based design process describing a triad of people, process, and technology (PPT) within an aerospace culture.
How to Quickly Import CAD Geometry into Thermal Desktop
There are several groups at JPL (Jet Propulsion Laboratory) that are committed to concurrent design efforts, two are featured here. Center for Space Mission Architecture and Design (CSMAD) enables the practical application of advanced process technologies in JPL's mission architecture process. Team I functions as an incubator for projects that are in the Discovery, and even pre-Discovery proposal stages. JPL's concurrent design environment is to a large extent centered on the CAD (Computer Aided Design) file. During concurrent design sessions CAD geometry is ported to other more specialized engineering design packages.
Spitzer Space Telescope Sequencing Operations Software, Strategies, and Lessons Learned
The Space Infrared Telescope Facility (SIRTF) was launched in August, 2003, and renamed to the Spitzer Space Telescope in 2004. Two years of observing the universe in the wavelength range from 3 to 180 microns has yielded enormous scientific discoveries. Since this magnificent observatory has a limited lifetime, maximizing science viewing efficiency (ie, maximizing time spent executing activities directly related to science observations) was the key operational objective. The strategy employed for maximizing science viewing efficiency was to optimize spacecraft flexibility, adaptability, and use of observation time. The selected approach involved implementation of a multi-engine sequencing architecture coupled with nondeterministic spacecraft and science execution times. This approach, though effective, added much complexity to uplink operations and sequence development. The Jet Propulsion Laboratory (JPL) manages Spitzer s operations. As part of the uplink process, Spitzer s Mission Sequence Team (MST) was tasked with processing observatory inputs from the Spitzer Science Center (SSC) into efficiently integrated, constraint-checked, and modeled review and command products which accommodated the complexity of non-deterministic spacecraft and science event executions without increasing operations costs. The MST developed processes, scripts, and participated in the adaptation of multi-mission core software to enable rapid processing of complex sequences. The MST was also tasked with developing a Downlink Keyword File (DKF) which could instruct Deep Space Network (DSN) stations on how and when to configure themselves to receive Spitzer science data. As MST and uplink operations developed, important lessons were learned that should be applied to future missions, especially those missions which employ command-intensive operations via a multi-engine sequence architecture.
Orbiter data reduction complex data processing requirements for the OFT mission evaluation team (level C)
This document addresses requirements for post-test data reduction in support of the Orbital Flight Tests (OFT) mission evaluation team, specifically those which are planned to be implemented in the ODRC (Orbiter Data Reduction Complex). Only those requirements which have been previously baselined by the Data Systems and Analysis Directorate configuration control board are included. This document serves as the control document between Institutional Data Systems Division and the Integration Division for OFT mission evaluation data processing requirements, and shall be the basis for detailed design of ODRC data processing systems.
Exploring the Science Trade Space with the JPL Innovation Foundry A-Team
The JPL Innovation Foundry has established a new approach for exploring, developing, and evaluating early concepts with a group called the Architecture Team (A-Team). The A-Team combines innovative collaborative methods and facilitated sessions with subject matter experts and analysis tools to help mature mission concepts. Science, implementation, and programmatic elements are all considered during an ATeam study. In these studies, Concept Maturity Levels (CML) are used to group methods. These levels include idea generation and capture (CML 1), initial feasibility assessment (CML 2), and trade space exploration (CML 3). Methods used for exploring the science objectives, feasibility, and scope will be described including use of a new technique for understanding the most compelling science, called a Science Return Diagram (SRD). In the process of developing the SRD, gradients in the science trade space are uncovered along with their implications for implementation and mission architecture. Special attention is paid towards developing complete investigations, establishing a series of logical claims that lead to the natural selection of a measurement approach. Over 20 science-focused A-Team studies have used these techniques to help science teams refine their mission objectives, make implementation decisions and reveal the mission concept’s most compelling science. This paper will describe the A-Team process for exploring the mission concept's science trade space and the Science Return Diagram technique.In June of 2011 a new collaborative engineering approach forearly concept formulation began in the JPL InnovationFoundry [1], six months later becoming the “A-Team” [2].Responding to a need for exploring mission architecturelevel trades [3], the A-Team precedes Team X [4,5] in asequence of concurrent engineering teams at JPL that can beused to mature a concept from a “cocktail napkin” level ideato a complete mission point design. The A-Team efficientlyexplores the science, implementation, and programmatictrade space in early concept formulation. Small, facilitatedgroups of experts generate innovative ideas, quantitativelyassess feasibility, and discover key sensitivities in the tradespace through collaborative analysis and use of advancedmethods and tools. The A-Team process builds off theexperience within JPL and other recent approaches to earlyconcept formulation [6] including best practices of the JPLInnovation Foundry, Project Systems Engineering &Formulation Section, Team Eureka and the Rapid MissionArchitecture Team[7].The A-Team is a focal point for innovative formulationapproaches and people within JPL. It relies on a largebackground of study resources, creative thinkers and “greybeard” scrutinizers, advanced tools, and subject matterexperts with both breadth and depth in experience andexpertise that are all available at JPL. The A-Team isdesigned to be a rapid and efficient process takingapproximately 6 weeks (the entire process can be as short asjust a few days or as long as up to three months) and costingthe equivalent of a work-month of a full-time employee orless. Studies begin with detailed planning and client reviewfollowed by study sessions, analysis work, and reporting.The staffing on each study is customized to the study goalsand objectives, and it is addressed early in the A-Teamprocess. Sessions are generally half-day or whole-day eventsand conducted over a series of days with focused agendas thatare moderated by a trained facilitator. Preliminary results andknowledge capture are available within hours of each session,and a final report is generally available two weeks later.One of the biggest challenges facing early conceptdevelopment is understanding the gradient in science returnversus various available mission scenarios and payload options. Often times, major areas of scientific inquiry havealready been prioritized by science groups, including throughthe National Research Council’s Decadal Studies inAstronomy, Planetary, and Earth Science. Yet science teamscontinue to struggle, especially in competitive missionsolicitations, to capture the right amount of scope that’sachievable within the cost constraints of the opportunity.Often the desire to completely and comprehensively study ascience area in just one mission (after all, true missionopportunities are rare) drives teams to take on too much,providing requirements that are unachievable within theresources of the opportunity without inducing unacceptableimplementation risk. Alternatively, science teams can seekto reduce risk by using an established instrument, but havenot thought through the traceability and key aspects of thescience question to justify its use. Both scenarios lead to badassumptions at the beginning of the concept development thatcan then ripple through implementation option choices,potentially preventing what would have been a good scienceinvestigation from being selected.The purpose of this paper is first to provide some additionalbackground and summary of the A-Team process, tools,people, and facilities. We then focus on the A-Teammethodology for overcoming the barriers of defining thescience scope well at the early concept development stage.This includes understanding the science story andtraceability, and then examining the gradient in science returnversus key characteristics of observables, developing theright payload and mission requirement specification throughexamining the science and implementation trade space.
Essentials for Team Based Rehearsals and the Differences Between Earth Orbiting and Deep Space Missions
The mission readiness environment is where spacecraft and ground systems converge to form the entire as built flight system for the final phase of operationally-themed testing. For most space missions, this phase starts between nine to twelve months prior to the planned launch. In the mission readiness environment, the goal is to perform sufficient testing to exercise the flight teams and systems through all mission phases in order to demonstrate that all elements are ready to support. As part of the maturation process, a mission rehearsal program is introduced to focus on team processes within the final flight system, in a more realistic operational environment. The overall goal for a mission rehearsal program is to: 1) ensure all flight system elements are able to meet mission objectives as a cohesive team; 2) reduce the risk in space based operations due to deficiencies in people, processes, procedures, or systems; and 3) instill confidence in the teams that will execute these first time flight activities. A good rehearsal program ensures critical events are exercised, discovers team or flight system nuances whose impact were previously unknown, and provides a real-time environment in which to interact with the various teams and systems. For flight team members, the rehearsal program provides experience and training in the event of planned (or unplanned) flight contingencies. To preserve the essence for team based rehearsals, this paper will explore the important elements necessary for a successful rehearsal program, document differences driven by Earth Orbiting (Aqua, Aura, Suomi-National Polar-orbiting Partnership (NPP)) and Deep Space missions (New Horizons, Mars Atmosphere and Volatile EvolutioN (MAVEN)) and discuss common challenges to both mission types. In addition, large scale program considerations and enhancements or additional steps for developing a rehearsal program will also be considered. For NASA missions, the mission rehearsal phase is a key milestone for predicting and ensuring on-orbit success.
Reinventing the Design Process: Teams and Models
The future of space mission designing will be dramatically different from the past. Formerly, performance-driven paradigms emphasized data return with cost and schedule being secondary issues.
Applying Strategic Visualization(Registered Trademark) to Lunar and Planetary Mission Design
NASA teams, such as the NASA Exploration Team (NEXT), utilize advanced computational visualization processes to develop mission designs and architectures for lunar and planetary missions. One such process, Strategic Visualization (trademark), is a tool used extensively to help mission designers visualize various design alternatives and present them to other participants of their team. The participants, which may include NASA, industry, and the academic community, are distributed within a virtual network. Consequently, computer animation and other digital techniques provide an efficient means to communicate top-level technical information among team members. Today,Strategic Visualization(trademark) is used extensively both in the mission design process within the technical community, and to communicate the value of space exploration to the general public. Movies and digital images have been generated and shown on nationally broadcast television and the Internet, as well as in magazines and digital media. In our presentation will show excerpts of a computer-generated animation depicting the reference Earth/Moon L1 Libration Point Gateway architecture. The Gateway serves as a staging corridor for human expeditions to the lunar poles and other surface locations. Also shown are crew transfer systems and current reference lunar excursion vehicles as well as the Human and robotic construction of an inflatable telescope array for deployment to the Sun/Earth Libration Point.
Advantages of Brahms for Specifying and Implementing a Multiagent Human-Robotic Exploration System
We have developed a model-based, distributed architecture that integrates diverse components in a system designed for lunar and planetary surface operations: an astronaut's space suit, cameras, all-terrain vehicles, robotic assistant, crew in a local habitat, and mission support team. Software processes ('agents') implemented in the Brahms language, run on multiple, mobile platforms. These mobile agents interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. The Brahms-based mobile agent architecture (MAA) uses a novel combination of agent types so the software agents may understand and facilitate communications between people and between system components. A state-of-the-art spoken dialogue interface is integrated with Brahms models, supporting a speech-driven field observation record and rover command system. An important aspect of the methodology involves first simulating the entire system in Brahms, then configuring the agents into a runtime system Thus, Brahms provides a language, engine, and system builder's toolkit for specifying and implementing multiagent systems.
Mobile Agents: A Distributed Voice-Commanded Sensory and Robotic System for Surface EVA Assistance
A model-based, distributed architecture integrates diverse components in a system designed for lunar and planetary surface operations: spacesuit biosensors, cameras, GPS, and a robotic assistant. The system transmits data and assists communication between the extra-vehicular activity (EVA) astronauts, the crew in a local habitat, and a remote mission support team. Software processes ("agents"), implemented in a system called Brahms, run on multiple, mobile platforms, including the spacesuit backpacks, all-terrain vehicles, and robot. These "mobile agents" interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. Different types of agents relate platforms to each other ("proxy agents"), devices to software ("comm agents"), and people to the system ("personal agents"). A state-of-the-art spoken dialogue interface enables people to communicate with their personal agents, supporting a speech-driven navigation and scheduling tool, field observation record, and rover command system. An important aspect of the engineering methodology involves first simulating the entire hardware and software system in Brahms, and then configuring the agents into a runtime system. Design of mobile agent functionality has been based on ethnographic observation of scientists working in Mars analog settings in the High Canadian Arctic on Devon Island and the southeast Utah desert. The Mobile Agents system is developed iteratively in the context of use, with people doing authentic work. This paper provides a brief introduction to the architecture and emphasizes the method of empirical requirements analysis, through which observation, modeling, design, and testing are integrated in simulated EVA operations.
Orbiter Return-To-Flight Entry Aeroheating
The Columbia accident on February 1, 2003 began an unprecedented level of effort within the hypersonic aerothermodynamic community to support the Space Shuttle Program. During the approximately six month time frame of the primary Columbia Accident Investigation Board activity, many technical disciplines were involved in a concerted effort to reconstruct the last moments of the Columbia and her crew, and understand the critical events that led to that loss. Significant contributions to the CAIB activity were made by the hypersonic aerothermodynamic community(REF CAIB) in understanding the re-entry environments that led to the propagation of an ascent foam induced wing leading edge damage to a subsequent breech of the wing spar of Columbia, and the subsequent breakup of the vehicle. A core of the NASA hypersonic aerothermodynamics team that was involved in the CAIB investigation has been combined with the United Space Alliance and Boeing Orbiter engineering team in order to position the Space Shuttle Program with a process to perform in-flight Thermal Protection System damage assessments. This damage assessment process is now part of the baselined plan for Shuttle support, and is a direct out-growth of the Columbia accident and NASAs response. Multiple re-entry aeroheating tools are involved in this damage assessment process, many of which have been developed during the Return To Flight activity. In addition, because these aeroheating tools are part of an overall damage assessment process that also involves the thermal and stress analyses community, in addition to a much broader mission support team, an integrated process for performing the damage assessment activities has been developed by the Space Shuttle Program and the Orbiter engineering community. Several subsets of activity in the Orbiter aeroheating communities support to the Return To Flight effort have been described in previous publications (CFD?, Cavity Heating? Any BLT? Grid Generation?). This work will provide a description of the integrated process utilized to perform Orbiter tile damage assessment, and in particular will seek to provide a description of the integrated aeroheating tools utilized to perform these assessments. Individual aeroheating tools will be described which provide the nominal re-entry heating environment characterization for the Orbiter, the heating environments for tile damage, heating effects due to exposed Thermal Protection System substrates, the application of Computational Fluid Dynamics for the description of tile cavity heating, and boundary layer transition prediction. This paper is meant to provide an overall view of the integrated aeroheating assessment process for tile damage assessment as one of a sequence of papers on the development of the boundary layer transition prediction capability in support of Space Shuttle Return To Flight efforts.
Using Simulation for Launch Team Training and Evaluation
This document describes some of the histor y and uses of simulation systems and processes for the training and evaluation of Launch Processing, Mission Control, and Mission Management teams. It documents some of the types of simulations that are used at Kennedy Space Center (KSC) today and that could be utilized (and possibly enhanced) for future launch vehicles. This article is intended to provide an initial baseline for further research into simulation for launch team training in the near future.
Automation and Process Improvement Enables a Small Team to Operate a Low Thrust Mission in Orbit Around the Asteroid Vesta
NASA's Dawn mission to the asteroid Vesta and dwarf planet Ceres launched September 27, 2007 and arrived at Vesta in July of 2011. This mission uses ion propulsion to achieve the necessary delta-V to reach and maneuver at Vesta and Ceres. This paper will show how the evolution of ground system automation and process improvement allowed a relatively small engineering team to transition from cruise operations to asteroid operations while maintaining robust processes. The cruise to Vesta phase lasted almost 4 years and consisted of activities that were built with software tools, but each tool was open loop and required engineers to review the output to ensure consistency. Additionally, this same time period was characterized by the evolution from manually retrieved and reviewed data products to automatically generated data products and data value checking. Furthermore, the team originally took about three to four weeks to design and build about four weeks of spacecraft activities, with spacecraft contacts only once a week. Operations around the asteroid Vesta increased the tempo dramatically by transitioning from one contact a week to three or four contacts a week, to fourteen contacts a week (every 12 hours). This was accompanied by a similar increase in activity complexity as well as very fast turn around activity design and build cycles. The design process became more automated and the tools became closed loop, allowing the team to build more activities without sacrificing rigor. Additionally, these activities were dependent on the results of flight system performance, so more automation was added to analyze the flight data and provide results in a timely fashion to feed the design cycle. All of this automation and process improvement enabled up the engineers to focus on other aspects of spacecraft operations, including spacecraft health monitoring and anomaly resolution.
Reinventing The Design Process: Teams and Models
The future of space mission designing will be dramatically different from the past. Formerly, performance-driven paradigms emphasized data return with cost and schedule being secondary issues. Now and in the future, costs are capped and schedules fixed-these two variables must be treated as independent in the design process. Accordingly, JPL has redesigned its design process. At the conceptual level, design times have been reduced by properly defining the required design depth, improving the linkages between tools, and managing team dynamics. In implementation-phase design, system requirements will be held in crosscutting models, linked to subsystem design tools through a central database that captures the design and supplies needed configuration management and control. Mission goals will then be captured in timelining software that drives the models, testing their capability to execute the goals. Metrics are used to measure and control both processes and to ensure that design parameters converge through the design process within schedule constraints. This methodology manages margins controlled by acceptable risk levels. Thus, teams can evolve risk tolerance (and cost) as they would any engineering parameter. This new approach allows more design freedom for a longer time, which tends to encourage revolutionary and unexpected improvements in design.