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This slide presentation reports on findings from analyzing a NASA COCOMO 81 dataset with 93 records. The current tool is called COSEEKMO, using a methodology can be applied to any set of cost models and data. The effort was part of a research initiative funded by the NASA Office of Safety and Mission and Assurance (OSMA) aimed at improving software reliability.
In a commercially hosted operational mode, a scientific instrument or operational device is attached to a spacecraft but operates independently from the spacecraft s primary mission. Despite the expected benefits of this arrangement, there are few examples of hosted payload programs actually being executed by government organizations. The lack of hosted payload programs is largely driven by programmatic challenges, both real and perceived, rather than by technical challenges. Partly for these reasons, NASA has not sponsored a hosted payload program, in spite of the benefits and visible community interest in doing so. In the interest of increasing the use of hosted payloads across the space community, this paper seeks to alleviate concerns about hosted payloads by identifying these programmatic challenges and presenting ways in which they can be avoided or mitigated. Despite the challenges, several recent hosted payload programs have been successfully completed or are currently in progress. This paper presents an assessment of these programs, with a focus on acquisition, costs, schedules, risks, and other programmatic aspects. The hosted payloads included in this study are the Federal Aviation Administration's Wide Area Augmentation System (WAAS) payloads, United States Coast Guard's Automatic Identification System (AIS) demonstration payload, Department of Defense's IP Router In Space (IRIS) demonstration payload, the United States Air Force's Commercially Hosted Infrared Payload (CHIRP), and the Australian Defence Force's Ultra High Frequency (UHF) payload. General descriptions of each of these programs are presented along with issues that have been encountered and lessons learned from those experiences. A set of recommended approaches for future hosted payload programs is presented, with a focus on addressing risks or potential problem areas through smart and flexible contracting up front. This set of lessons and recommendations is broadly applicable to future hosted payload programs, whether they are technology demonstrations, communications systems, or operational sensors. Additionally, we present a basic cost model for commercial access to space for hosted payloads as a function of payload mass
As the space business rapidly evolves to accommodate a lower cost model of development and operation via concepts such as commercial space and small spacecraft (aka, CubeSats), traditional EEE parts screening and qualification methods are being scrutinized under a risk-reward trade space. In this presentation, two basic concepts will be the overarching theme: 1) The movement from complete risk aversion EEE parts methods to managing and or accepting risk via alternate approaches; and, 2) A discussion of over-design focusing on both electrical design performance and bounding margins.
The NASA Systems Engineering Research Consortium was formed at the end of 2010 to study the approaches to producing elegant systems on a consistent basis. This has been a transformative study looking at the engineering and organizational basis of systems engineering. The consortium has engaged in a variety of research topics to determine the path to elegant systems. In the second year of the consortium, a systems engineering framework emerged which structured the approach to systems engineering and guided our research. This led in the third year to set of systems engineering postulates that the consortium is continuing to refine. The consortium has conducted several research projects that have contributed significantly to the understanding of systems engineering. The consortium has surveyed the application of the NASA 17 systems engineering processes, explored the physics and statistics of systems integration, and considered organizational aspects of systems engineering discipline integration. The systems integration methods have included system exergy analysis, Akaike Information Criteria (AIC), State Variable Analysis, Multidisciplinary Coupling Analysis (MCA), Multidisciplinary Design Optimization (MDO), System Cost Modelling, System Robustness, and Value Modelling. Organizational studies have included the variability of processes in change evaluations, margin management within the organization, information theory of board structures, social categorization of unintended consequences, and initial looks at applying cognitive science to systems engineering. Consortium members have also studied the bidirectional influence of policy and law with systems engineering.
The NASA Systems Engineering Research Consortium was formed at the end of 2010 to study the approaches to producing elegant systems on a consistent basis. This has been a transformative study looking at the engineering and organizational basis of systems engineering. The consortium has engaged in a variety of research topics to determine the path to elegant systems. In the second year of the consortium, a systems engineering framework emerged which structured the approach to systems engineering and guided our research. This led in the third year to set of systems engineering postulates that the consortium is continuing to refine. The consortium has conducted several research projects that have contributed significantly to the understanding of systems engineering. The consortium has surveyed the application of the NASA 17 systems engineering processes, explored the physics and statistics of systems integration, and considered organizational aspects of systems engineering discipline integration. The systems integration methods have included system energy analysis, Akaike Information Criteria (AIC), State Variable Analysis, Multidisciplinary Coupling Analysis (MCA), Multidisciplinary Design Optimization (MDO), System Cost Modeling, System Robustness, and Value Modeling. Organizational studies have included the variability of processes in change evaluations, margin management within the organization, information theory of board structures, social categorization of unintended consequences, and initial looks at applying cognitive science to systems engineering. Consortium members have also studied the bidirectional influence of policy and law with systems engineering.
As the space business rapidly evolves to accommodate a lower cost model of development and operation via concepts such as commercial space and small spacecraft (aka, CubeSats), traditional EEE parts screening and qualification methods are being scrutinized under a risk-reward trade space. In this presentation, two basic concepts will be the overarching theme: 1) The movement from complete risk aversion EEE parts methods to managing and/or accepting risk via alternate approaches; and, 2) A discussion of over-design focusing on both electrical design performance and bounding margins.
This paper details the adaptation of specific 'knowledge production' methods to implement a first of its kind, grassroots event that provokes a cultural change in how the NASA Ames civil servant community engages in the creation and selection of innovative ideas. Historically, selection of innovative proposals at NASA Ames Research Center is done at the highest levels of management, isolating the views and perspectives of the larger civil servant community. Additionally, NASA innovation programs are typically open to technical organizations and do not engage non-technical organizations to bring forward innovative processes/business practices. Finally, collaboration on innovative ideas and associated solutions tend to be isolated to organizational silos. In this environment, not all Ames employees feel empowered to innovate and opportunities for employee collaboration are limited. In order to address these issues, the 'innovation contest' method was adapted to create the NASA Ames Innovation Fair, a unique, grassroots innovation opportunity for the civil servant community. The Innovation Fair consisted of a physical event with a virtual component. The physical event provided innovators the opportunity to collaborate and pitch their innovations to the NASA Ames community. The civil servant community then voted for the projects that they viewed as innovative and would contribute to NASA's core mission, making this event a truly grassroots effort. The Innovation Fair website provided a location for additional knowledge sharing, discussion, and voting. On March 3rd, 2016, the 'First Annual NASA Ames Innovation Fair' was held with 49 innovators and more than 300 participants collaborating and/or voting for the best innovations. Based on the voting results, seven projects were awarded seed funding for projects ranging from innovative cost models to innovations in aerospace technology. Surveys of both innovators and Fair participants show the Innovation Fair was successful in fostering cross-organizational collaborations, soliciting participation of non-technical innovations, and increasing employee engagement in influencing the future of NASA Ames Research Center. The grassroots component of the Innovation Fair has been bench marked by the agency as a solid foundation for increasing employee engagement in the development of game changing aerospace technology and processes in support of NASA's mission.
As the space business rapidly evolves to accommodate a lower cost model of development and operation via concepts such as commercial space and small spacecraft (aka, CubeSats and swarms), traditional EEE parts screening and qualification methods are being scrutinized under a risk-reward trade space. In this presentation, two basic concepts will be discussed: (1) The movement from complete risk aversion EEE parts methods to managing and/or accepting risk via alternate approaches; and, (2) A discussion of emerging assurance methods to reduce overdesign as well emerging model based mission assurance (MBMA) concepts. center dot Example scenarios will be described as well as consideration for trading traditional versus alternate methods.
NASA ESDIS has been moving a variety of data ingest, distribution, and science data processing applications into a cloud environment over the last 2 years. As expected, there have been a number of challenges in migrating primarily on-premises applications into a cloud-based environment, related to architecture and taking advantage of cloud-based services. What was not expected is a number of issues that were beyond purely technical application re-architectures. We ran into surprising network policy limitations, billing challenges in a government-based cost model, and difficulty in obtaining certificates in an NASA security-compliant manner. On the other hand, this approach has allowed us to move a number of applications from local hosting to the cloud in a matter of hours (yes, hours!!), and our CMR application now services 95% of granule searches and an astonishing 99% of all collection searches in under a second. And most surprising of all, well, you'll just have to wait and see the realization that caught our entire team off guard!
As the space business rapidly evolves to accommodate a lower cost model of development and operation via concepts such as commercial space and small spacecraft (aka, CubeSats), traditional EEE parts screening and qualification methods are being scrutinized under a risk-reward trade space. In this presentation, two basic concepts will be the overarching theme: 1) The movement from complete risk aversion EEE parts methods to managing andor accepting risk via alternate approaches; and, 2) A discussion of over-design focusing on both electrical design performance and bounding margins.
Future Mars missions will require the ability to land increasingly heavy systems with high precision, possibly at high altitude landing sites. A key obstacle in landing systems with high ballistic coefficient is Mars’ very thin atmosphere, approximately one hundred times less dense than Earth’s atmosphere. As a result, hypersonic deceleration occurs slowly throughout atmospheric entry and additional deceleration methods are required before landing. Previous landers up to and including MSL relied on Viking-heritage technologies including a Disk-Gap-Band (DGB) supersonic parachute and a blunt body aeroshell. Safe and effective deployment of a DGB parachute can be accomplished only within prescribed bounds on dynamic pressure and Mach number.2 In addition to the restrictive constraint this imposes on the entry trajectory, there is a concern that for a parachute to effectively slow an entry vehicle with a high ballistic coefficient, its diameter must be large enough to impose certification costs, modeling uncertainty, or mission risk that could be unacceptable. This has prompted investigation into alternative mission concepts based on use of supersonic retropropulsion (SRP) without a parachute. This work investigates SRP as an enabling technology for Mars EDL of high ballistic coefficient vehicles.
This presentation is an overview OF EOSDIS and motivation for commercial cloud and will discuss components of the Earthdata cloud, AWS accounts metric, account structure architecture and cloud resource and cost model.
Cloud Computing has become the ubiquitous approach to our Big Data challenge. However, one will quickly discover that moving (a.k.a. forklifting) existing on-premise data analytics solutions to the Cloud doesn’t always translate to costing saving and performance boost. The Cloud’s elasticity, its availability, and its wide selection of computing options and selections of costing models making Cloud an attractive environment to tackle our Big Data challenge. The fact is Cloud, on its own, is not the silver bullet to our daunting challenge need for analyze and derive scientific inferences through vast collections of multi-sensor measurements. We would like to have all scientific data in one easy to access environment, but getting the world of scientific data in one analytic system is immensely difficult to achieve. This paper describes the data analytics web architecture NASA is developing by infusing instances of Integrated Data Analytics systems next to the data. The goal is to minimize unnecessary data movement through collection of data access and analytics webservices for researchers to interact with and analyze measurements without have to download data to their local computer. These services are RESTful and provisioned by the data centers with the help from subject matter and science experts. These services encapsulate the physical computing infrastructure, which could local computing cluster, on-premise or public Cloud environment.
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 cost processes and methods, how they are being used to expand our data frontiers and cost modelling capabilities, and how this enables the ability to estimate early and estimate often.
With challenges related to testing highly complex integrated circuits as well as entire systems continuing to grow, the use of higher energy heavy ions for single-event effects (SEE) testing becomes a critical technical need. This presentation, however, focuses only partially on the technical side with the main emphasis on the economics of using a high-energy heavy ion beam and comparing via notional cost models for testing.
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.
Software Cost Estimation Model program, SOFTCOST, developed to provide consistent automated resource-and-schedule mathematical model more formalized than guesswork model. Combines several software-cost models found in open literature into one comprehensive set of algorithms compensating for nearly 50 implementation factors relative to size of task, inherited baseline, organizational and system environment, and difficulty of task. Produces mean and variance estimates of software size, implementation productivity, recommended staff level, probable duration, amount of computer resources required, and amount and cost of software documentation. Written in Microsoft BASIC.
The Collaborative Modeling for Parametric Assessment of Space Systems (COMPASS) team at Glenn Research Center has performed integrated system analysis of conceptual spacecraft mission designs since 2006 using a multidisciplinary concurrent engineering process. The set of completed designs was archived in a database, to allow for the study of relationships between design parameters. Although COMPASS uses a parametric spacecraft costing model, this research investigated the possibility of using a top-down approach to rapidly estimate the overall vehicle costs. This paper presents the relationships between significant design variables, including breakdowns of dry mass, wet mass, and cost. It also develops a model for a broad estimate of these parameters through basic mission characteristics, including the target location distance, the payload mass, the duration, the delta-v requirement, and the type of mission, propulsion, and electrical power. Finally, this paper examines the accuracy of this model in regards to past COMPASS designs, with an assessment of outlying spacecraft, and compares the results to historical data of completed NASA missions.