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At least 343 records · Page 19

A measurement system for large, complex software programs

This paper describes measurement systems required to forecast, measure, and control activities for large, complex software development and support programs. Initial software cost and quality analysis provides the foundation for meaningful management decisions as a project evolves. In modeling the cost and quality of software systems, the relationship between the functionality, quality, cost, and schedule of the product must be considered. This explicit relationship is dictated by the criticality of the software being developed. This balance between cost and quality is a viable software engineering trade-off throughout the life cycle. Therefore, the ability to accurately estimate the cost and quality of software systems is essential to providing reliable software on time and within budget. Software cost models relate the product error rate to the percent of the project labor that is required for independent verification and validation. The criticality of the software determines which cost model is used to estimate the labor required to develop the software. Software quality models yield an expected error discovery rate based on the software size, criticality, software development environment, and the level of competence of the project and developers with respect to the processes being employed.

Rone, Kyle Y.↗

Engineering and fabrication cost considerations for cryogenic wind tunnel models

Design and fabrication cost drivers for cryogenic transonic wind tunnel models are defined. The major cost factors for wind tunnel models are model complexity, tolerances, surface finishes, materials, material validation, and model inspection. The cryogenic temperatures require the use of materials with relatively high fracture toughness but at the same time high strength. Some of these materials are very difficult to machine, requiring extensive machine hours which can add significantly to the manufacturing costs. Some additional engineering costs are incurred to certify the materials through mechanical tests and nondestructive evaluation techniques, which are not normally required with conventional models. When instrumentation such as accelerometers and electronically scanned pressure modules is required, temperature control of these devices needs to be incorporated into the design, which requires added effort. Additional thermal analyses and subsystem tests may be necessary, which also adds to the design costs. The largest driver to the design costs is potentially the additional static and dynamic analyses required to insure structural integrity of the model and support system.

Boykin, R. M., Jr.↗

The application of simulation modeling to the cost and performance ranking of solar thermal power plants

Small solar thermal power systems (up to 10 MWe in size) were tested. The solar thermal power plant ranking study was performed to aid in experiment activity and support decisions for the selection of the most appropriate technological approach. The cost and performance were determined for insolation conditions by utilizing the Solar Energy Simulation computer code (SESII). This model optimizes the size of the collector field and energy storage subsystem for given engine generator and energy transport characteristics. The development of the simulation tool, its operation, and the results achieved from the analysis are discussed.

Rosenberg, L. S.↗

Costs and benefits

Two models of cost benefit analysis are illustrated and the application of these models to assessing the economic scope of space applications programs was discussed. Four major areas cited as improvable through space derived information - food supply and distribution, energy sources, mineral reserves, and communication and navigation were - discussed. Specific illustrations are given for agriculture and maritime traffic.

Source record↗

Software for Tracking Costs of Mars Projects

The Mars Cost Tracking Model is a computer program that administers a system set up for tracking the costs of future NASA projects that pertain to Mars. Previously, no such tracking system existed, and documentation was written in a variety of formats and scattered in various places. It was difficult to justify costs or even track the history of costs of a spacecraft mission to Mars. The present software enables users to maintain all cost-model definitions, documentation, and justifications of cost estimates in one computer system that is accessible via the Internet. The software provides sign-off safeguards to ensure the reliability of information entered into the system. This system may eventually be used to track the costs of projects other than only those that pertain to Mars.

Wong, Alvin↗

Advanced space power requirements and techniques. Task 1: Mission projections and requirements. Volume 3: Appendices

Contents: (1) general study guidelines and assumptions; (2) launch vehicle performance and cost assumptions; (3) satellite programs 1959 to 1979; (4) initiative mission and design characteristics; (5) satellite listing; (6) spacecraft design model; (7) spacecraft cost model; (8) mission cost model; and (9) nominal and optimistic budget program cost summaries.

Wolfe, M. G.↗

Business Intelligence Modeling in Launch Operations

This technology project is to advance an integrated Planning and Management Simulation Model for evaluation of risks, costs, and reliability of launch systems from Earth to Orbit for Space Exploration. The approach builds on research done in the NASA ARC/KSC developed Virtual Test Bed (VTB) to integrate architectural, operations process, and mission simulations for the purpose of evaluating enterprise level strategies to reduce cost, improve systems operability, and reduce mission risks. The objectives are to understand the interdependency of architecture and process on recurring launch cost of operations, provide management a tool for assessing systems safety and dependability versus cost, and leverage lessons learned and empirical models from Shuttle and International Space Station to validate models applied to Exploration. The systems-of-systems concept is built to balance the conflicting objectives of safety, reliability, and process strategy in order to achieve long term sustainability. A planning and analysis test bed is needed for evaluation of enterprise level options and strategies for transit and launch systems as well as surface and orbital systems. This environment can also support agency simulation .based acquisition process objectives. The technology development approach is based on the collaborative effort set forth in the VTB's integrating operations. process models, systems and environment models, and cost models as a comprehensive disciplined enterprise analysis environment. Significant emphasis is being placed on adapting root cause from existing Shuttle operations to exploration. Technical challenges include cost model validation, integration of parametric models with discrete event process and systems simulations. and large-scale simulation integration. The enterprise architecture is required for coherent integration of systems models. It will also require a plan for evolution over the life of the program. The proposed technology will produce long-term benefits in support of the NASA objectives for simulation based acquisition, will improve the ability to assess architectural options verses safety/risk for future exploration systems, and will facilitate incorporation of operability as a systems design consideration, reducing overall life cycle cost for future systems. The future of business intelligence of space exploration will focus on the intelligent system-of-systems real-time enterprise. In present business intelligence, a number of technologies that are most relevant to space exploration are experiencing the greatest change. Emerging patterns of set of processes rather than organizational units leading to end-to-end automation is becoming a major objective of enterprise information technology. The cost element is a leading factor of future exploration systems.

Bardina, Jorge E.↗

The application of simulation modeling to the cost and performance ranking of solar thermal power plants

A computer simulation code was employed to evaluate several generic types of solar power systems (up to 10 MWe). Details of the simulation methodology, and the solar plant concepts are given along with cost and performance results. The Solar Energy Simulation computer code (SESII) was used, which optimizes the size of the collector field and energy storage subsystem for given engine-generator and energy-transport characteristics. Nine plant types were examined which employed combinations of different technology options, such as: distributed or central receivers with one- or two-axis tracking or no tracking; point- or line-focusing concentrator; central or distributed power conversion; Rankin, Brayton, or Stirling thermodynamic cycles; and thermal or electrical storage. Optimal cost curves were plotted as a function of levelized busbar energy cost and annualized plant capacity. Point-focusing distributed receiver systems were found to be most efficient (17-26 percent).

Rosenberg, L. S.↗

Flexible space structure model reduction by modal cost analysis

It is noted that reduced models and reduced controllers for flexible space structures are obtained by retaining those modes which make the greatest contribution to quadratic control objectives. Attention is given to the relative importance of damping, frequency and mode shapes in the mode truncation decisions for the following control objectives: attitude control, vibration suppression and figure control. It is also shown that using Modal Cost Analysis (MCA) on the closed loop modes of the optimally controlled system allows the construction of reduced control policies which feedback only those closed loop coordinates which are most critical to the quadratic control performance criterion. In this manner, the modes which need to be controlled are deduced from truncations of the optimal controller.

Skelton, R. E.↗

Pros, Cons, and Alternatives to Weight Based Cost Estimating

Many cost estimating tools use weight as a major parameter in projecting the cost. This is often combined with modifying factors such as complexity, technical maturity of design, environment of operation, etc. to increase the fidelity of the estimate. For a set of conceptual designs, all meeting the same requirements, increased weight can be a major driver in increased cost. However, once a design is fixed, increased weight generally decreases cost, while decreased weight generally increases cost - and the relationship is not linear. Alternative approaches to estimating cost without using weight (except perhaps for materials costs) have been attempted to try to produce a tool usable throughout the design process - from concept studies through development. This paper will address the pros and cons of using weight based models for cost estimating, using liquid rocket engines as the example. It will then examine approaches that minimize the imp~ct of weight based cost estimating. The Rocket Engine- Cost Model (RECM) is an attribute based model developed internally by Pratt & Whitney Rocketdyne for NASA. RECM will be presented primarily to show a successful method to use design and programmatic parameters instead of weight to estimate both design and development costs and production costs. An operations model developed by KSC, the Launch and Landing Effects Ground Operations model (LLEGO), will also be discussed.

Joyner, Claude R.↗

Atmospheric corrosion model and monitor for low cost solar arrays

An atmospheric corrosion model and corrosion monitoring system has been developed for low cost solar arrays (LSA). The corrosion model predicts that corrosion rate is the product of the surface condensation probability of water vapor and the diffusion controlled corrosion current. This corrosion model is verified by simultaneous monitoring of weather conditions and corrosion rates at the solar array test site at Mead, Nebraska.

Kaelble, D. H.↗

Estimating the Life Cycle Cost of Space Systems

A space system's Life Cycle Cost (LCC) includes design and development, launch and emplacement, and operations and maintenance. Each of these cost factors is usually estimated separately. NASA uses three different parametric models for the design and development cost of crewed space systems; the commercial PRICE-H space hardware cost model, the NASA-Air Force Cost Model (NAFCOM), and the Advanced Missions Cost Model (AMCM). System mass is an important parameter in all three models. System mass also determines the launch and emplacement cost, which directly depends on the cost per kilogram to launch mass to Low Earth Orbit (LEO). The launch and emplacement cost is the cost to launch to LEO the system itself and also the rockets, propellant, and lander needed to emplace it. The ratio of the total launch mass to payload mass depends on the mission scenario and destination. The operations and maintenance costs include any material and spares provided, the ground control crew, and sustaining engineering. The Mission Operations Cost Model (MOCM) estimates these costs as a percentage of the system development cost per year.

Life cycle cost↗

Cost Analysis In A Multi-Mission Operations Environment

Spacecraft control centers have evolved from dedicated, single-mission or single missiontype support to multi-mission, service-oriented support for operating a variety of mission types. At the same time, available money for projects is shrinking and competition for new missions is increasing. These factors drive the need for an accurate and flexible model to support estimating service costs for new or extended missions; the cost model in turn drives the need for an accurate and efficient approach to service cost analysis. The National Aeronautics and Space Administration (NASA) Huntsville Operations Support Center (HOSC) at Marshall Space Flight Center (MSFC) provides operations services to a variety of customers around the world. HOSC customers range from launch vehicle test flights; to International Space Station (ISS) payloads; to small, short duration missions; and has included long duration flagship missions. The HOSC recently completed a detailed analysis of service costs as part of the development of a complete service cost model. The cost analysis process required the team to address a number of issues. One of the primary issues involves the difficulty of reverse engineering individual mission costs in a highly efficient multimission environment, along with a related issue of the value of detailed metrics or data to the cost model versus the cost of obtaining accurate data. Another concern is the difficulty of balancing costs between missions of different types and size and extrapolating costs to different mission types. The cost analysis also had to address issues relating to providing shared, cloud-like services in a government environment, and then assigning an uncertainty or risk factor to cost estimates that are based on current technology, but will be executed using future technology. Finally the cost analysis needed to consider how to validate the resulting cost models taking into account the non-homogeneous nature of the available cost data and the decreasing flight rate. This paper presents the issues encountered during the HOSC cost analysis process, and the associated lessons learned. These lessons can be used when planning for a new multi-mission operations center or in the transformation from a dedicated control center to multi-center operations, as an aid in defining processes that support future cost analysis and estimation. The lessons can also be used by mature serviceoriented, multi-mission control centers to streamline or refine their cost analysis process.

Newhouse, M.↗

Cost Analysis in a Multi-Mission Operations Environment

Spacecraft control centers have evolved from dedicated, single-mission or single mission-type support to multi-mission, service-oriented support for operating a variety of mission types. At the same time, available money for projects is shrinking and competition for new missions is increasing. These factors drive the need for an accurate and flexible model to support estimating service costs for new or extended missions; the cost model in turn drives the need for an accurate and efficient approach to service cost analysis. The National Aeronautics and Space Administration (NASA) Huntsville Operations Support Center (HOSC) at Marshall Space Flight Center (MSFC) provides operations services to a variety of customers around the world. HOSC customers range from launch vehicle test flights; to International Space Station (ISS) payloads; to small, short duration missions; and has included long duration flagship missions. The HOSC recently completed a detailed analysis of service costs as part of the development of a complete service cost model. The cost analysis process required the team to address a number of issues. One of the primary issues involves the difficulty of reverse engineering individual mission costs in a highly efficient multi-mission environment, along with a related issue of the value of detailed metrics or data to the cost model versus the cost of obtaining accurate data. Another concern is the difficulty of balancing costs between missions of different types and size and extrapolating costs to different mission types. The cost analysis also had to address issues relating to providing shared, cloud-like services in a government environment, and then assigning an uncertainty or risk factor to cost estimates that are based on current technology, but will be executed using future technology. Finally the cost analysis needed to consider how to validate the resulting cost models taking into account the non-homogeneous nature of the available cost data and the decreasing flight rate. This paper presents the issues encountered during the HOSC cost analysis process, and the associated lessons learned. These lessons can be used when planning for a new multi-mission operations center or in the transformation from a dedicated control center to multi-center operations, as an aid in defining processes that support future cost analysis and estimation. The lessons can also be used by mature service-oriented, multi-mission control centers to streamline or refine their cost analysis process.

Felton, Larry↗

The cost of doing a cost estimate

A model for estimating the cost required to do a cost estimate for Deep Space Network (DSN) projects that range from $0.1 to $100 million is presented. The cost of the cost estimate in thousands of dollars, C(sub E), is found to be approximately given by C(sub E) = K(/C(sub p)/(sup 0.35)) where C(sub p) is the cost of the project being estimated in millions of dollars and K is a constant depending on the accuracy of the estimate. For an order-of-magnitude estimate, K = 24; for a budget estimate, K = 60; and for a definitive estimate, K = 115. That is, for a specific project, the cost of doing a budget estimate is about 2.5 times as much as that for an order-of-magnitude estimate, and a definitive estimate costs about twice as much as a budget estimate. Use of this model should help provide the level of resources required for doing cost estimates and, as a result, provide insights towards more accurate estimates with less potential for cost overruns.

Remer, Donald S.↗