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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2005

Assessing the Relative Risk of Aerocapture Using Probabalistic Risk Assessment

A recent study performed for the Aerocapture Technology Area in the In-Space Propulsion Technology Projects Office at the Marshall Space Flight Center investigated the relative risk of various capture techniques for Mars missions. Aerocapture has been proposed as a possible capture technique for future Mars missions but has been perceived by many in the community as a higher risk option as compared to aerobraking and propulsive capture. By performing a probabilistic risk assessment on aerocapture, aerobraking and propulsive capture, a comparison was made to uncover the projected relative risks of these three maneuvers. For mission planners, this knowledge will allow them to decide if the mass savings provided by aerocapture warrant any incremental risk exposure. The study focuses on a Mars Sample Return mission currently under investigation at the Jet Propulsion Laboratory (JPL). In each case (propulsive, aerobraking and aerocapture), the Earth return vehicle is inserted into Martian orbit by one of the three techniques being investigated. A baseline spacecraft was established through initial sizing exercises performed by JPL's Team X. While Team X design results provided the baseline and common thread between the spacecraft, in each case the Team X results were supplemented by historical data as needed. Propulsion, thermal protection, guidance, navigation and control, software, solar arrays, navigation and targeting and atmospheric prediction were investigated. A qualitative assessment of human reliability was also included. Results show that different risk drivers contribute significantly to each capture technique. For aerocapture, the significant drivers include propulsion system failures and atmospheric prediction errors. Software and guidance hardware contribute the most to aerobraking risk. Propulsive capture risk is mainly driven by anomalous solar array degradation and propulsion system failures. While each subsystem contributes differently to the risk of each technique, results show that there exists little relative difference in the reliability of these capture techniques although uncertainty for the aerocapture estimates remains high given the lack of in-space demonstration.

Percy, Thomas K.↗
NASA NTRS2013

Domain-Specific Languages and Diagram Customization for a Concurrent Engineering Environment

A major open question for advocates of Model-Based Systems Engineering (MBSE) is the question of how system and subsystem engineers will work together. The Systems Modeling Language (SysML), like any language intended for a large audience, is in tension between the desires for simplicity and for expressiveness. In order to be more expressive, many specialized language elements may be introduced, which will unfortunately make a complete understanding of the language a more daunting task. While this may be acceptable for systems modelers, it will increase the challenge of including subsystem engineers in the modeling effort. One possible answer to this situation is the use of Domain-Specific Languages (DSL), which are fully supported by the Unified Modeling Language (UML). SysML is in fact a DSL for systems engineering. The expressive power of a DSL can be enhanced through the use of diagram customization. Various domains have already developed their own schematic vocabularies. Within the space engineering community, two excellent examples are the propulsion and telecommunication subsystems. A return to simple box-and-line diagrams (e.g., the SysML Internal Block Diagram) are in many ways a step backward. In order allow subsystem engineers to contribute directly to the model, it is necessary to make a system modeling tool at least approximate in accessibility to drawing tools like Microsoft PowerPoint and Visio. The challenge is made more extreme in a concurrent engineering environment, where designs must often be drafted in an hour or two. In the case of the Jet Propulsion Laboratory's Team X concurrent design team, a subsystem is specified using a combination of PowerPoint for drawing and Excel for calculation. A pilot has been undertaken in order to meld the drawing portion and the production of master equipment lists (MELs) via a SysML authoring tool, MagicDraw. Team X currently interacts with its customers in a process of sharing presentations. There are several inefficiencies that arise from this situation. The first is that a customer team must wait two weeks to a month (which is 2-4 times the duration of most Team X studies themselves) for a finalized, detailed design description. Another is that this information must be re-entered by hand into the set of engineering artifacts and design tools that the mission concept team uses after a study is complete. Further, there is no persistent connection to Team X or institutionally shared formulation design tools and data after a given study, again reducing the direct reuse of designs created in a Team X study. This paper presents the underpinnings of subsystem DSLs as they were developed for this pilot. This includes specialized semantics for different domains as well as the process by which major categories of objects were derived in support of defining the DSLs. The feedback given to us by the domain experts on usability, along with a pilot study with the partial inclusion of these tools is also discussed.

Cole, Bjorn↗
NASA NTRS2010

Identification and Classification of Common Risks in Space Science Missions

Due to the highly constrained schedules and budgets that NASA missions must contend with, the identification and management of cost, schedule and risks in the earliest stages of the lifecycle is critical. At the Jet Propulsion Laboratory (JPL) it is the concurrent engineering teams that first address these items in a systematic manner. Foremost of these concurrent engineering teams is Team X. Started in 1995, Team X has carried out over 1000 studies, dramatically reducing the time and cost involved, and has been the model for other concurrent engineering teams both within NASA and throughout the larger aerospace community. The ability to do integrated risk identification and assessment was first introduced into Team X in 2001. Since that time the mission risks identified in each study have been kept in a database. In this paper we will describe how the Team X risk process is evolving highlighting the strengths and weaknesses of the different approaches. The paper will especially focus on the identification and classification of common risks that have arisen during Team X studies of space based science missions.

Risk Identification↗
NASA NTRS2016

JPL's Foundry Furnace: Web-Based Concurrent Engineering for Formulation

The Jet Propulsion Laboratory’s Innovation Foundry is an enterprise tasked with shepherding space mission concepts through the formulation lifecycle. It oversees a number of “virtual teams” for the various stages of formulation. Among these is Team X, which has had considerable success over its more than 20-year history. In a Team X study, domain experts (including engineers devoted to the various spacecraft subsystems) work concurrently and collaboratively over several days to arrive at a feasible point design with a reasonable cost estimate. They use a set of linked Excel workbooks, each developed and approved by a responsible “line organization” within JPL. This toolset has served Team X well over the years, and has evolved since its inception. At the same time, the Innovation Foundry’s portfolio of formulation teams has expanded, and so has the scope of the design challenges they face. The A-Team runs workshop-like architecture studies to focus science investigations, generate mission concepts, assess feasibility, and explore trade spaces. Team Xc performs rapid point design in the style of Team X, but for CubeSats and small spacecraft, using a different toolset. Proposal teams further mature concepts to the point where they can be proposed. Recognizing the importance of trade space modeling combined with new IT services for providing and integrating data, JPL is developing the Foundry Furnace web-based software infrastructure. It will support A-Team, Team Xc, and Team X, providing study management, a catalog of hardware components, a library of re-usable analyses, and a design environment. It is a modernization of JPL’s concurrent engineering infrastructure, embracing the core concepts of Model-Based Systems Engineering, and built with modern software design philosophies.

Murphy, Jonathan↗
NASA NTRS2005

The NASA Exploration Design Team; Blueprint for a New Design Paradigm

NASA has chosen JPL to deliver a NASA-wide rapid-response real-time collaborative design team to perform rapid execution of program, system, mission, and technology trade studies. This team will draw on the expertise of all NASA centers and external partners necessary. The NASA Exploration Design Team (NEDT) will be led by NASA Headquarters, with field centers and partners added according to the needs of each study. Through real-time distributed collaboration we will effectively bring all NASA field centers directly inside Headquarters. JPL's Team X pioneered the technique of real time collaborative design 8 years ago. Since its inception, Team X has performed over 600 mission studies and has reduced per-study cost by a factor of 5 and per-study duration by a factor of 10 compared to conventional design processes. The Team X concept has spread to other NASA centers, industry, academia, and international partners. In this paper, we discuss the extension of the JPL Team X process to the NASA-wide collaborative design team. We discuss the architecture for such a process and elaborate on the implementation challenges of this process. We further discuss our current ideas on how to address these challenges.

Team X↗
NASA NTRS2021

Lessons Learned in Remote Participant Concurrent Engineering Concept Development Studies

Team-X was born from a need to perform rapid space mission design for principal investigator-led competed proposals in the mid-1990s. Throughout the last 25 years, Team-X at the Jet Propulsion Laboratory has expanded its application of the collaborative, concurrent study approach into every facet necessary to win competed proposals. The COVID-19 pandemic of 2020 created an immediate and new constraint on these studies – the need to conduct them with remote participants, both on the client side requesting the study, but also on the provider side producing the study. This paper provides lessons learned from dozens of design studies run by Team-X at the Jet Propulsion Laboratory during the COVID-19 pandemic. These lessons span all aspects of the information infrastructure: the people, processes, procedures, methods, tools, and “facilities”. These lessons learned will have applicability post-pandemic, as they have shown how best to incorporate participants, both on the provider side, and on the client side, who cannot travel or otherwise be co-located during collaborative, concurrent study sessions.

Nash, Alfred↗
NASA NTRSDate not supplied

VERNE: Revealing the Mysteries and Histories of Venus

Introduction: The three Venus missions that were recently selected for upcoming flight (VERITAS, DAVINCI+, and EnVision) will be incredibly valuable to our understanding of Venus’ history, geology, and atmosphere. However, even once completed, key gaps in our knowledge of Venus, and more generally the formation and active processes on rocky, Earth-like planets, will still persist. Remaining questions include 1) how global intrinsic magnetic fields might be maintained on rocky worlds, and how they could then go extinct, and 2) what role atmospheric sulfur chemistry plays in climates of Earth-like planets, which is an increasingly timely subject as Earth’s own atmospheric sulfur content is climbing due to human activity. These questions require in-situ observations from Venus’ cloud deck, at the altitudes at which the UV absorber exists. The Venus Environment Research and Novel Exploration (VERNE) mission will address these questions with an aerial platform that will drift around the equatorial region of the planet for 9 days. VERNE will collect data to determine the identity of the mysterious UV absorber, while also taking magnetic field measurements over the tesserae, the regions on Venus that are most likely to retain remanent crustal magnetization, in order to understand the potential role of a past intrinsically-generated global magnetic field on Venus. Mission Objectives: The two major science objectives that drive the VERNE mission are: 1) Determine the identity of the Venusian unknown ultraviolet absorber(s). First observed approximately a century ago [1], the composition of Venus’ ultraviolet (UV) absorber is one of the oldest mysteries in Venus atmospheric chemistry [2,3]. While several candidate UV absorbers (mostly sulfur species) have been proposed, no consensus has been reached on its composition and its specific interactions with the atmosphere. Determining the identity of the UV absorber will aid climate models by showing how and where incident solar energy is absorbed by the atmosphere and make progress towards understanding the chemical and energetic processes taking place above Venus’ upper cloud deck [4]. 2) Determine if Venus retains evidence of a past, internally-generated magnetic field. While Venus does not currently have an intrinsically-generated magnetic field, evidence for the existence of a past field on Venus and a timeline of its decay will fill in a more holistic picture of the evolution of Venus’ geological record and atmosphere. As the oldest geologic units on the surface, Venus’ tesserae may still have remanent crustal magnetization signatures within the rocky composition [5]. In any case, the signatures detected will provide insight into Venus’ past geological and core dynamo activity. Mission Summary: VERNE includes a 3-part flight system made up of 1) an entry system with a HEEET (Heatshield for Extreme Entry Environment Technology) aeroshell, 2) an orbiter for data relay, and 3) an in-situ balloon and gondola. After entry into Venus’ atmosphere, the balloon will be deployed within the upper cloud deck, at an altitude of 62 km, over a tesserae region. The in-situ data collection will last for the duration of 2 full circumnavigations of the planet, which will take ~9 days. Instrumentation Suite: The four instruments that comprise VERNE’s instrument payload will enable the identification of the unknown UV absorber and the detection of remanent crustal magnetization if it exists in the tesserae. The proposed instrument suite cycle during mission operations is shown in Fig. 1. The four instruments are described below: 1) Adams (ion neutral mass spectrometer) has a range of 18-257 AMU and will detect and distinguish the mixing ratios of O₂, H₂O, H₂SO₄, S, S₂, S₃, S₄, S₅, S₆, S₇, S₈, SO, SO₂, OSSO, SO₃, Cl₂, FeCl₃ and other trace sulfur and organic species. The spatial (longitudinal) and temporal (day/night) variations will be observed throughout 2 circumnavigations with a sample cadence of 12 minutes. 2) Shelley (nephelometer) will determine the size distribution of the aerosols (0.4 to 36 um) in the atmosphere. With a size resolution of <0.7 um, it can determine which mode of H2SO4 is present and characterize the large (>30 um) organic particles previously detected by the Venera and Galileo missions [6,7]. 3) Herbert (UV imager) will measure UV radiance at 283 nm (the wavelength of SO2 absorption) and 365 nm (the unknown part of the absorber). UV images will be taken concurrently with the INMS and nephelometer to correlate UV absorption with abundances of the UV absorber species. 4) Vonnegut (magnetometer) has a range of >600 nT and a precision and accuracy of 1 nT. If magnetized by a past field, the crust may have retained a magnetization of up to 3 A/m2 [5]. With a noise floor of 10 nT, the magnetometer will be able to detect RCM from an altitude of 62 km, even if the thickness of the magnetized crust is just 1 km (Fig. 2). Mission Concept Design: VERNE will be launched with a mass of 3300 kg in an intermediate-high performance class vehicle with a 4-m fairing. The 475-day mission includes 466 days for the cruise, coasting, and orbit initialization phases before entry, descent, and balloon deployment. During the 9-day science phase, the aerial platform will make 2 circumnavigations of the planet at an altitude of 62 km. The INMS and the nephelometer will acquire data for 2 hours during the daytime and nighttime during each circumnavigation, while the UV imager will be on for the duration of the daytime, and the magnetometer will be operational throughout the entirety of the science phase. Data will be stored and processed with the JPL-designed Sphinx command and data handling system. Data will be sent from the balloon to the orbiter using an S-band relay link, stored on the orbiter, and then forwarded to Earth where it will be received by the DSN. Conclusion: VERNE will fill key gaps in our understanding of the history and ongoing processes related to the geology and atmosphere of Venus and rocky worlds in general. Even with adequate flight system contingencies and expected costs below the $900M New Frontiers cost cap, VERNE is not without its risks and challenges. Further trade spaces to explore include 1) using solely battery power vs. including solar panels to increase the mission duration and 2) investigating the use of lightweight materials and 3D-printed structures to reduce the gondola mass, among others. Acknowledgments: We would like to thank the JPL Planetary Science Summer School, especially our mentors Troy Hudson, Karl Mitchell, and Leslie Lowes, as well as our Team-X study lead Al Nash and the members of Team-X. We’d additionally like to thank our review panel for asking insightful questions and providing valuable feedback. References: [1] Ross, F. E. (1928) Astrophysical J., 68, 57-92. [2] Rossow, W. B. et al. (1980) J. Geophysical Research, 85, 8107-8128. [3] Pinto, J. P. et al. (2021) Nature Communications, 12, 175. [4] Titov, D. V. et al. (2007) Cosmic Research, 21, 401. [5] O’Rourke, J. et al. (2019) Geophysical Research Lett., 46, 5768–5777. [6] Limaye, S. S. et al. (2018) Astrobiology, 18(9), 1181-1198. [7] Grinspoon, D. H. et al. (2013) Planetary and Space Sci., 41(7), 515-542. [8] Parker, R. L. (2003) J. Geophysical Research, 108, 5006. *The cost information contained in this document is of a budgetary and planning nature and is intended for informational purposes only. It does not constitute a commitment on the part of JPL and/or Caltech.

H Alpert↗
NASA NTRS2008

Dilute Aperture Visible Nulling Coronagraph Imaging (DAViNCI)

The presentation focuses on instrument and mission overview, science case, Team X study, and technology status. Topics include DAViNCI study milestones, number of targets versus inner working angle, planet orbit and IWA, combiner/nuller instrument, DAViNCI Team X costs, technology status and near future plans, and deep laser null 1.23 x 10(exp -7) suppression. Summary points are: dilute aperture concept advantages, lower cost than a comparable 7-8m coronagraph working at 2 lambda/D, technology progress prior to 2008 was seriously limited by available funding but showed 1e-y suppression (2006) of laser light needed for 1e-9 to approximately 1e-10 contrast, and current technology effort is off to a fast date with a demonstration of less than 100pm wavefront measurement in Nov 08.

coronagraphs↗
DOE OSTI2024

Taking the MPI standard and the open MPI library to exascale

The Open MPI for Exascale (OMPI-X) project was one of two in the Exascale Computing Project (ECP) focused on advancing the MPI ecosystem. The OMPI-X team worked with other MPI Forum members to champion several important features for inclusion in the MPI 4.0, 4.1, and upcoming 5.0 MPI standard versions, in support of the needs of exascale applications and systems. The team also worked with the larger Open MPI community to bring implementations of these new features and other enhancements into Open MPI, one of the leading open-source implementations of the MPI interface. Here, this paper describes the motivation for the work of the OMPI-X project in the context of exascale computing needs, the nature of the resulting new capabilities in the MPI standard, and how they were implemented in the Open MPI library. Features include improved support for “MPI + X” programming models through partitioned communications and support for user-level threading, sessions, fault tolerance through the user-level fault mitigation (ULFM) and Reinit models, and other features. We also discuss enhancements to Open MPI providing improved performance and scalability for existing features, such as collective operations, one-sided operations, support for the Slingshot-11 interconnect of the initial exascale systems, and how the OMPI-X team worked to improve quality assurance for the Open MPI library, particularly on platforms of interest to the Department of Energy community.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

COMPASS Final Report: Lunar Relay Satellite (LRS)

The Lunar Relay Satellite (LRS) COllaborative Modeling and Parametric Assessment of Space Systems (COMPASS) session was tasked to design a satellite to orbit in an elliptical lunar polar orbit to provide relay communications between lunar South Pole assets and the Earth. The design included a complete master equipment list, power requirement list, configuration design, and brief risk assessment and cost analysis. The LRS is a half-TDRSS sized box spacecraft, which provides communications and navigation relay between lunar outposts (via Lunar Communications Terminals (LCT)) or Sortie parties (with user radios) and large ground antennas on Earth. The LRS consists of a spacecraft containing all the communications and avionics equipment designed by NASA Jet Propulsion Laboratory s (JPL) Team X to perform the relay between lunar-based assets and the Earth. The satellite design is a standard box truss spacecraft design with a thermal control system, 1.7 m solar arrays for 1 kWe power, a 1 m diameter Ka/S band dish which provides relay communications with the LCT, and a Q-band dish for communications to/from the Earth based assets. While JPL's Team X and Goddard Space Flight Center s (GSFC) I M Design Center (IMDC) have completed two other LRS designs, this NASA Glenn Research Center (GRC) COMPASS LRS design sits between them in terms of physical size and capabilities.

Oleson, Steven R.↗
NASA NTRS2022

Gaussian Process Regression Method for Costing SmallSat Bus Capabilities

NASA is responding to the growing interest in, andcapabilities of, small satellites for science applications with an increasingnumber and frequency of Announcements of Opportunityfor small satellite space missions. Estimating the probabilitythat these mission concepts will fit within the small cost capsof these opportunities is largely driven by the probability thatone of the burgeoning number of small satellite providers will beable to meet the payload’s accommodation requirements withinthe budget for the spacecraft. JPL has collected a databasecontaining technical specifications and cost of commerciallyavailable Smallsat buses across various vendors. The primarypurpose of the database is for use in JPL’s Team X architecturestudies to inform cost estimates of a spacecraft bus which fitsthe customer’s technical requirements for their payload andmission. Customer needs are often unique and don’t alignperfectly with an off-the-shelf commercial spacecraft bus, whichmotivates the need to develop a cost model across the continuoustechnical parameter space.Al’s Bus Cost Distribution Estimator (ABCDE) uses Gaussianprocess regression (GPR) to predict commercial Smallsat spacecraftbus cost based on a subset of a customer’s technicalrequirements (payload mass, payload power, delta V, pointingcontrol, and downlink rate). GPR is implemented in ABCDE asa Bayesian method which fits an implied multivariate regressionon the technical parameters and uses kriging to intentionally“overfit” the residuals. Overfitting the residuals allows costestimates to collapse in uncertainty closer to the data pointswhile maintaining larger uncertainty intervals in regions of parameterspace with fewer data records. The data used to fit thismodel is sensitive and represents cost estimates for off-the-shelfcommercial buses. GPR simultaneously protects the sensitivityof the database and uses the sparse nature of the database toaccount for uncertainty in cost in a useful way. For a givenset of customer technical requirements, the tool provides a costestimate distribution, the percentiles of which can be interpretedas a confidence level of finding a commercial bus under a specifiedcost cap. ABCDE dramatically pushes the boundaries ofspacecraft cost estimation models due to its Bayesian methodology(accounting for the maximum uncertainty in the underlyingregression), the mathematically advanced kriging methodology,and the novelty of its application in Team X architecture tradestudies.

Austin, Alex↗
NASA NTRS2020

Estimate Early and Estimate Often: How Your Concurrent Engineering Design Team Can Bootstrap Your Organizations Programmatic Capabilities

What do you do when it is necessary to generate reasonable cost estimates at the earliest Concept Maturity Levels and you have never flown any similar missions before? This paper describes the current and future Team X and A-Team cost processes and methods, how they are being used to expand our data frontiers, cost modelling capabilities and how this enables the ability to estimate early and estimate often.

Hihn, Jairus↗
NASA NTRS1998

New Approach to Concept Feasibility and Design Studies for Astrophysics Missions

JPL has assembled a team of multidisciplinary experts with corporate knowledge of space mission and instrument development. The advanced Concept Design Team, known as Team X, provides interactive design trades including cost as a design parameter, and advanced visualization for pre-Phase A Studies.

Concept Feasibility Design Studies Team X Astrophy↗
NASA NTRS2007

Mission Options Scoping Tool for Mars Orbiters: Mass Cost Calculator (MC2)

Prior to developing the details of an advanced mission study, the mission architecture trade space is typically explored to assess the scope of feasible options. This paper describes the main features of an Excel-based tool, called the Mass-Cost-Calculator (MC2 ), which is used to perform rapid, high-level mass and cost options analyses of Mars orbiter missions. MC2 consists of a combination of databases, analytical solutions, and parametric relationships to enable quick evaluation of new mission concepts and comparison of multiple architecture options. The tool's outputs provide program management and planning teams with answers to "what if" queries, as well as an understanding of the driving mission elements, during the pre-project planning phase. These outputs have been validated against the outputs generated by the Advanced Projects Design Team (Team X) at NASA's Jet Propulsion Laboratory (JPL). The architecture of the tool allows for future expansion to other orbiters beyond Mars, and to non-orbiter missions, such as those involving fly-by spacecraft, probes, landers, rovers, or other mission elements.

orbiters↗
NASA NTRS2016

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.

Ziemer, John K.↗
NASA NTRS2018

How Do You Go From a Concept Idea to a NASA Selected Mission? Formulating the Psyche Discovery Mission with JPL's Concurrent Engineering Teams

JPL’s Office of Formulation provides continuity of support and access to domain subject matter experts, as Principal Investigators mature their mission concepts from “cocktail napkin” ideas to Preliminary Design Reviews [1]. Using NASA’s Psyche mission as a case study, we describe JPL’s concurrent engineering A-Team and Team X support to the Psyche competed concept study team in the areas of 1) Initial Feasibility, 2) Trade Space Exploration, 3) Spacecraft Point Design and Cost Estimate, 4) Science, Technical, Management, and Cost Review, and 5) Strategy and Communication Development. NASA’s Psyche Discovery-class mission started as a grassroots idea from Principal Investigator L.T. ElkinsTanton. Is there a compelling Discovery mission to visit the interior of a body for the first time, by sending a mission to an iron metal asteroid? In less than five years the Psyche concept was selected as a mission under NASA’s Discovery Program. While Psyche had a dedicated concept development team [2], they utilized JPL’s concurrent engineering teams, methods, analysis tools, and subject matter experts throughout their mission concept formulation lifecycle

Ziemer, John↗
NASA NTRS2018

How Do You Go From a Concept Idea to a NASA Selected Mission? Formulating the Psyche Discovery Mission with JPL's Concurrent Engineering Teams

JPL’s Office of Formulation provides continuity of support and access to domain subject matter experts, as Principal Investigators mature their mission concepts from “cocktail napkin” ideas to Preliminary Design Reviews [1]. Using NASA’s Psyche mission as a case study, we will describe JPL’s concurrent engineering ATeam and Team X support to the Psyche competed concept study team in the areas of 1) Science Feasibility, 2) Trade Space Exploration, 3) Spacecraft Point Design and Cost Estimate, 4) Science, Technical, Management, and Cost Review, and 5) Strategy and Communication Development. NASA’s Psyche Discovery class mission started as a grassroots idea in our A-Team facility, and in less than five years was selected as a mission under NASA’s Discovery Program. While Psyche had a dedicated concept development team [2], they utilized JPL’s concurrent engineering teams, methods, analysis tools, and experts throughout their mission concept lifecycle.

Ziemer, John↗