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In this report we consider a decision-making problem of selecting a strategy from a set of alternatives on the basis of incomplete information (e.g., a finite number of observations): the system can, however, gather additional information at some cost.
This slide presentation reviews the study to understand the changes in cost and schedule growth for NASA projects. A second goal was to determine the percentage of growth that was outside the control of the project. The study examined project documentation, conducted interviews with key project personnel, and allocated growth events to an Explanation of Change (EoC) tree to quantify the reasons for growth in the scheduled time. This briefing reviews the results of the study of the first 20 missions.
The concept of re-partitioning the airspace into a new set of sectors for allocating capacity rather than delaying flights to comply with the capacity constraints of a static set of sectors is being explored. The reduction in delay, a benefit, achieved by this concept needs to be greater than the cost of controllers and equipment needed for the additional sectors. Therefore, tradeoff studies are needed for benefits assessment of this concept.
Within the present budgetary environment, developing the technology that leads to an operationally efficient space transportation system with the required performance is a challenge. The present research focuses on a methodology to determine high payoff technology investment strategies. Research has been conducted at Langley Research Center in which design codes for the conceptual analysis of space transportation systems have been integrated in a multidisciplinary design optimization approach. The current study integrates trajectory, propulsion, weights and sizing, and cost disciplines where the effect of technology maturation on the development cost of a single stage to orbit reusable launch vehicle is examined. Results show that the technology investment prior to full-scale development has a significant economic payoff. The design optimization process is used to determine strategic allocations of limited technology funding to maximize the economic payoff.
Patterned after the Cassini Resource Exchange (CRE), Sholtz and Associates established the Automated Credit Exchange (ACE), an Internet-based concept that automates the auctioning of "pollution credits" in Southern California. An early challenge of the Jet Propulsion Laboratory's Cassini mission was allocating the spacecraft's resources. To support the decision-making process, the CRE was developed. The system removes the need for the science instrument manager to know the individual instruments' requirements for the spacecraft resources. Instead, by utilizing principles of exchange, the CRE induces the instrument teams to reveal their requirements. In doing so, they arrive at an efficient allocation of spacecraft resources by trading among themselves. A Southern California RECLAIM air pollution credit trading market has been set up using same bartering methods utilized in the Cassini mission in order to help companies keep pollution and costs down.
This paper investigates the trade-off between efficiency and habitability in lunar architectures. Five distinct lunar architectures are briefly presented and then critically examined in terms of spatial allocation and surface area to net and gross volume and in terms of four habitability criteria. Advantages and limitations of the basic concepts underlying each architecture are examined. A fundamental inverse relation is discovered between spatial efficiency (and thus cost containment) and habitability (and thus satisfaction and productivity). The most efficient architectures are described in detail, as are the most habitable architectures. This leads to a critical trade-off to be made in the design of any lunar architecture. Ways are suggested to integrate the concerns for efficiency with habitability.
The intersatellite links (ISL's) at geostationary orbit is currently a missing link in commercial satellite services. Prior studies have found that potential application of ISL's to domestic, regional, and global satellites will provide more cost-effective services than the non-ISL's systems (i.e., multiple-hop systems). In addition, ISL's can improve and expand the existing satellite services in several aspects. For example, ISL's can conserve the scarce spectrum allocated for fixed satellite services (FSS) by avoiding multiple hopping of the relay stations. ISL's can also conserve prime orbit slot by effectively expanding the geostationary arc. As a result of the coverage extension by using ISL's more users will have direct access to the satellite network, thus providing reduced signal propagation delay and improved signal quality. Given the potential benefits of ISL's system, it is of interest to determine the appropriate implementations for some potential ISL architectures. Summary of the selected ISL network architecture as supplied by NASA are listed. The projected high data rate requirements (greater than 400 Mbps) suggest that high frequency RF or optical implementations are natural approaches. Both RF and optical systems have their own merits and weaknesses which make the choice between them dependent on the specific application. Due to its relatively mature technology base, the implementation risk associated with RF (at least 32 GHz) is lower than that of the optical ISL's. However, the relatively large antenna size required by RF ISL's payload may cause real-estate problems on the host spacecraft. In addition, because of the frequency sharing (for duplex multiple channels communications) within the limited bandwidth allocated, RF ISL's are more susceptible to inter-system and inter-channel interferences. On the other hand, optical ISL's can offer interference-free transmission and compact sized payload. However, the extremely narrow beam widths (on the order of 10 micro-rad) associated with optical ISL's impose very stringent pointing, acquisition, and tracking requirements on the system. Even if the RF and optical systems are considered separately, questions still remain as to selection of RF frequency, direct versus coherent optical detection, etc. in implementing an ISL for a particular network architecture. These and other issues are studied.
This paper considers the decision-making problem of selecting a strategy from a set of alternatives on the basis of incomplete information (e.g., a finite number of observation). At any time the system can adopt a particular strategy or decide to gather additional information at some cost.
Multi Model Monte Carlo with Python (\mxmc {}) is a software package developed as a general capability for computing the statistics of outputs from an expensive, high-fidelity model by leveraging faster, low-fidelity models for speedup. Motivated by uncertainty propagation problems where classical Monte Carlo (MC) simulation is computationally intractable, various multi-model MC approaches have recently emerged that yield unbiased estimators with significantly reduced variance relative to MC for the same cost. These existing methods include multi-level Monte Carlo (MLMC), multi-fidelity Monte Carlo (MFMC), and approximate control variates (ACV). Given a fixed computational budget and a collection of models with varying cost/accuracy, each method seeks a sample allocation strategy across the models that results in an estimator with optimal variance reduction. \mxmc {} is a versatile tool that enables convenient access to many existing multi-model MC approaches within one modular and extensible package. With \mxmc {}, users can easily compare existing methods to determine the best choice for their particular problem, while developers have a basis for implementing and sharing new variance reduction approaches. This report introduces the \mxmc {} software, providing a summary of the problem-solving workflow for users as well as a brief overview of the code layout for developers.
The Collaborative Trajectory Options Program (CTOP) is a Traffic Management Initiative (TMI) intended to control the air traffic flow rates at multiple specified Flow Constrained Areas (FCAs), where demand exceeds capacity. CTOP allows flight operators to submit the desired Trajectory Options Set (TOS) for each affected flight with associated Relative Trajectory Cost (RTC) for each option. CTOP then creates a feasible schedule that complies with capacity constraints by assigning affected flights with routes and departure delays in such a way as to minimize the total cost while maintaining equity across flight operators. The current version of CTOP implements a Ration-by-Schedule (RBS) scheme, which assigns the best available options to flights based on a First-Scheduled-First-Served heuristic. In the present study, an alternative flight scheduling approach is developed based on linear optimization. Results suggest that such an approach can significantly reduce flight delays, in the deterministic case, while maintaining equity as defined using a Max-Min fairness scheme.
The Collaborative Trajectory Options Program (CTOP) is a Traffic Management Initiative (TMI) intended to control the air traffic flow rates at multiple specified Flow Constrained Areas (FCAs), where demand exceeds capacity. CTOP allows flight operators to submit the desired Trajectory Options Set (TOS) for each affected flight with associated Relative Trajectory Cost (RTC) for each option. CTOP then creates a feasible schedule that complies with capacity constraints by assigning affected flights with routes and departure delays in such a way as to minimize the total cost while maintaining equity across flight operators. The current version of CTOP implements a Ration-by-Schedule (RBS) scheme, which assigns the best available options to flights based on a First-Scheduled-First-Served heuristic. In the present study, an alternative flight scheduling approach is developed based on linear optimization. Results suggest that such an approach can significantly reduce flight delays, in the deterministic case, while maintaining equity as defined using a Max-Min fairness scheme.
The U.S. Vision for Space Exploration directs NASA to retire the Space Shuttle in 2010 and replace it with safe, reliable, and cost-effective space transportation systems for crew and cargo travel to the Moon, Mars, and beyond. Such emerging space transportation initiatives face massive organizational challenges, including building and nurturing an experienced, dedicated team with the right skills for the required tasks; allocating and tracking the fiscal capital invested in achieving technical progress against an integrated master schedule; and turning generated data into usehl knowledge that equips the team to design and develop superior products for customers and stakeholders. This paper discusses how NASA's Exploration Launch Projects Office, which is responsible for delivering these new launch vehicles, integrates these resources to create an engineering business environment that promotes mission success.
The U.S. Vision for Space Exploration directs NASA to retire the Space Shuttle in 2010 and replace it with safe, reliable, and cost-effective space transportation systems for crew and cargo travel to the Moon, Mars, and beyond. Such emerging space transportation initiatives face massive organizational challenges, including building and nurturing an experienced, dedicated team with the right skills for the required tasks; allocating and tracking the fiscal capital invested in achieving technical progress against an integrated master schedule; and turning generated data into useful knowledge that equips the team to design and develop superior products for customers and stakeholders. It has been more than 30 years since the Space Shuttle was designed; therefore, the current aerospace workforce has limited experience with developing new designs for human-rated spaceflight hardware. To accomplish these activities, NASA is using a wide range of state-of-the-art information technology tools that connect its diverse, decentralized teams and provide timely, accurate information for decision makers. In addition, business professionals are assisting technical managers with planning, tracking, and forecasting resource use against an integrated master schedule that horizontally and vertically interlinks hardware elements and milestone events. Furthermore, NASA is employing a wide variety of strategies to ensure that it has the motivated and qualified staff it needs for the tasks ahead. This paper discusses how NASA's Exploration Launch Projects Office, which is responsible for delivering these new launch vehicles, integrates its resources to create an engineering business environment that promotes mission success, which is defined by replacing the Space Shuttle by 2014 and returning to the Moon by 2020.
The Glenn Technical Library is a science and engineering library that primarily supports research activities at the Glenn Research Center, and provides selected services to researchers at all of the NASA research centers. Resources available in the library include books, journals, CD-ROMs, and access to various online sources, as well as live reference and inter-library loan services. The collection contains over 77,000 books, 800,000 research reports, and print or online access to over 1,400 journals. Currently the library operates within the Logistics and Technical Information Division, and is funded as an open-access resource within the GRC. Some of the research units at the GRC have recently requested that the library convert to a "pay-for-services" model, in which individual research units could fund only those journal subscriptions for which they have a specific need. Under this model, the library would always maintain a certain minimum level of pooled-expense services, including the ready reference and book collections, and inter-library loan services. Theoretically the "pay-for-services" model would encourage efficient financial allocation, and minimize the extent to which paid journal subscriptions go unused. However, this model also could potentially negate the benefits of group purchases for journal subscriptions and access. All of the major journal publishers offer package subscriptions that compare favorably in cost with the sum of individual subscription costs for a similar selection of titles. Furthermore, some of these subscription packages are "consortium" purchases that are funded collectively by the libraries at multiple NASA research centers; such consortia1 memberships would be difficult for the library to pay, if enough GRC research units were to withdraw their pooled contributions. cost of collectively-funded journal access with the cost of individual subscriptions. My primary task this summer is to create the cost dataset framework, and collect as much of the relevant data as possible. Hopefully this dataset will permit the research units at the GRC, and library administration as well, to make informed decisions about future library funding. Prior to the creation of the actual dataset, I established a comprehensive list of the library s print and online journal subscriptions. This list will be useful outside the context of the cost analysis project, as an addition to the library website. The cost analysis dataset s primary fields are: journal name, vendor, publisher, ISSN (International Standard Serial Number, to uniquely identify the titles), stand-alone price, and indication as to the presence of the journal in current GRC Technical Library consortium membership subscriptions. The dataset will hopefully facilitate comparisons between the stand-alone journal prices and the cost of shared journal subscriptions for groups of titles.
The issue of reducing the cost of phased array vehicle antennas through the use of a lens feeding arrangement instead of phase shifters at each element is addressed. In particular, the economic viability of a mobile satellite system (MSAT) is largely dependent on the efficient use of the allocated scarce spectrum and orbit as well as the satellite power. the type of vehicle antenna used will play a critical role in achieving this efficiency. A standard design approach for an electronically steered array uses phase shifters at each element to provide beam steering. A method for reducing the required number of phase shifters by using an R-KR lens feed network is outlined. The authors briefly discuss the phase shifter approach to beam steering, examine various lens feed techniques, and describe the R-KR lens approach. The lens feed network architecture is examined, a computer model for simulation of the array is presented, and the results of analysis of a suggested design for the MSAT application are given. In addition, satellite acquisition and tracking considerations are investigated.
In this paper we consider service placement problem for Data and Reasoning Fabric (DRF) enabled airspace operations assuming a fixed cloud/edge infrastructure with allocated computing, storage and power resources, where cloud/edge servers, and communication stations are in a wired connected network, while vehicles use a wireless network for communication. The objective is to automatically select the best location for the requested service execution, which achieves minimum cost while satisfying the user quality of service (QoS) and available resources constraints. To this end, we estimate for each potential location the response time, consumed energy and total cost; formulate an optimization problem for cost minimization given the users QoS constraints and network infrastructure limitations; and solve it using nonlinear programming tools. The approach is applied to trajectory re-planning use case to handle a no-fly zone contingency in real time.
In this paper we consider service migration problem for Data and Reasoning Fabric (DRF) enabled airspace operations assuming a fixed cloud/edge infrastructure with allocated computing, storage and power resources, where cloud/edge servers, and communication stations are in a wired connected network, while vehicles use a wireless network for communication. The objective is to automatically select the best location for the requested service execution, which achieves minimum cost while satisfying the user quality of service (QoS) and available resources constraints. To this end, estimates of the response time, consumed energy and total cost are defined for each potential compute location. A mixed-integer linear program is then formulated and solved to identify optimal compute locations given QoS constraints, network infrastructure limitations, with worst-case vehicle positioning. The approach is applied to trajectory re-planning use case to avoid a collision with an emergency vehicle in real time.
A finite element analysis emulator providing a basis for efficiently establishing an optimum computer implementation strategy when many calculations are involved is described. The SCOPE emulator determines computer resources required as a function of the structural model, structural load-deflection equation characteristics, the storage allocation plan, and computer hardware capabilities. Thereby, it provides data for trading analysis implementation options to arrive at a best strategy. The models contained in SCOPE lead to micro-operation computer counts of each finite element operation as well as overall computer resource cost estimates. Application of SCOPE to the Memphis-Arkansas bridge analysis provides measures of the accuracy of resource assessments. Data indicate that predictions are within 17.3 percent for calculation times and within 3.2 percent for peripheral storage resources for the ELAS code.