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NASA NTRS1999

Autonomous Command Operations of the WIRE Spacecraft

This paper presents operational innovations which will be introduced on NASA's Wide Field Infrared Explorer (WIRE) mission. These innovations include an end-to-end design architecture for an autonomous commanding capability for the uplink of command loads during unattended station contacts. The WIRE mission is the fifth and final mission of NASA's Goddard Space Flight Center Small Explorer (SMEX) series to be launched in March of 1999. Its primary mission is the targeting of deep space fields using an ultra-cooled infrared telescope. Due to its mission design WIRE command loads are large (approximately 40 Kbytes per 24 hours) and must be performed daily. To reduce the cost of mission operations support that would be required in order to uplink command loads, the WIRE Flight Operations Team has implemented all autonomous command loading capability. This capability allows completely unattended operations over a typical two-day weekend period. The key factors driving design and implementation of this capability were: 1) integration with already existing ground system autonomous capabilities and systems, 2) the desire to evolve autonomous operations capabilities based upon previous SMEX operations experience - specifically the TRACE mission, 3) integration with ground station operations - both autonomous and man-tended, 4) low cost and quick implementation, and 5) end-to-end system robustness. A trade-off study was performed to examine these factors in light of the low-cost, higher-risk SMEX mission philosophy. The study concluded that a STOL (Spacecraft Test and Operations Language) based script, highly integrated with other scripts used to perform autonomous operations, was best suited given the budget and goals of the mission. Each of these factors is discussed in addition to use of the TRACE mission as a testbed for autonomous commanding prior to implementation on WIRE. The capabilities implemented on the WIRE mission are an example of a low-cost, robust, and efficient method for autonomous command loading when implemented with other autonomous features of the ground system. They call be used as a design and implementation template by other missions interested in evolving toward autonomous and lower cost operations. Additionally, the WIRE spacecraft will be used as an operational testbed upon completion of its nominal mission later in 1999. One idea being studied is advanced on-board modeling. Advanced on-board modeling techniques will be used to more efficiently display the spacecraft state. This health and safety information could be used by engineers on the ground or could be used by tile spacecraft for its own assessments. Additionally, this same state information could also be input into the event-driven scheduling system, as the scheduling system will need to assess the spacecraft state before undertaking a new activity. Advanced modeling techniques are being evaluated for a number of NASA missions including The Next Generation Space Telescope (NGST), which is scheduled to launch in 2007.

Walyus, Keith↗
NASA NTRS1999

New Mission Concepts for Astrophysics Large Area X-Ray Spectroscopy Mission

Work at SAO was performed under the overall direction of Dr. Harvey Tananbaum, the Principal Investigator for the program. Dr. Jay Bookbinder was responsible for day to day program coordination at SAO and liaison with GSFC. Dr. Nicholas E. White served as GSFC Technical Officer for the Grant. The effort was directed at formulating the general characteristics and scientific requirements of the contemplated mission. While funding and therefore effort was limited, nonetheless SAO was involved in a broad range of activities. These activities were defined by our SAO proposal to GSFC that were subsequently accepted and funded by this Grant. The main activities were: Support of mission studies. Support the development of science requirements. and Performance of selected engineering studies and trades. During this period, an integrated GSFC/SAO management team began to form and work together. Jean F. Grady was appointed Project Formulation Manager at GSFC and assumed the overall management direction of the project including coordination of work performed under the grant.

Tananbaum, Harvey↗
NASA NTRS1999

Current Status of Airwatch-OWL Optics

The current status of the OWL (Obstacle Warning Ladar) Optical Design is discussed, and the results of a trade-off study are presented.

Lamb, David J.↗
NASA NTRS2002

Automation Tools for Finite Element Analysis of Adhesively Bonded Joints

This article presents two new automation creation tools that obtain stresses and strains (Shear and peel) in adhesively bonded joints. For a given adhesively bonded joint Finite Element model, in which the adhesive is characterised using springs, these automation tools read the corresponding input and output files, use the spring forces and deformations to obtain the adhesive stresses and strains, sort the stresses and strains in descending order, and generate plot files for 3D visualisation of the stress and strain fields. Grids (nodes) and elements can be numbered in any order that is convenient for the user. Using the automation tools, trade-off studies, which are needed for design of adhesively bonded joints, can be performed very quickly.

Tahmasebi, Farhad↗
NASA NTRS2003

Method for Constructing Composite Response Surfaces by Combining Neural Networks with other Interpolation or Estimation Techniques

A method and system for design optimization that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The present invention employs a unique strategy called parameter-based partitioning of the given design space. In the design procedure, a sequence of composite response surfaces based on both neural networks and polynomial fits is used to traverse the design space to identify an optimal solution. The composite response surface has both the power of neural networks and the economy of low-order polynomials (in terms of the number of simulations needed and the network training requirements). The present invention handles design problems with many more parameters than would be possible using neural networks alone and permits a designer to rapidly perform a variety of trade-off studies before arriving at the final design.

Rai, Man Mohan↗
NASA NTRS2004

Terrestrial Environment (Climatic) Criteria Handbook For Use in Aerospace Vehicle Development

An update of the NASA 'Terrestrial Environment (Climatic) Criteria Handbook for Use in Aerospace Vehicle Development' (NASA-HDBK-1001) is currently in the final process of completion for release in late-2004 or early 2005. The current version of the Handbook was approved by the NASA Chief Engineer in 2000 as a NASA Preferred Technical Standard. However, it was based on natural environment criteria developed mostly in the early 1990's. Therefore, a task was approved to completely update the Handbook in order to reflect the current state-of-the-art in the various terrestrial environmental climatic criteria areas. The technical areas include: Winds, atmospheric constituents, thermodynamic parameters/models/extremes, humidity, electricity, precipitation/fog/icing, cloud phenomena/cover, diffusion/toxic release, severe weather/tornado/hurricane, solar/thermal radiation, geologic hazards, and sea state. A summary of this extensive update will be presented along with some key examples of the new contents. Earlier versions of this publication have been extensively used by the aerospace community, especially program managers and design engineers for required natural terrestrial environment inputs to use in mission planning, development studies and trades, plus by those concerned with terrestrial environment descriptions for the major test ranges within the United States.

Johnson, Dale↗
NASA NTRS2006

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

Rai, Man Mohan↗
NASA NTRS2006

Simulation Modeling and Performance Evaluation of Space Networks

In space exploration missions, the coordinated use of spacecraft as communication relays increases the efficiency of the endeavors. To conduct trade-off studies of the performance and resource usage of different communication protocols and network designs, JPL designed a comprehensive extendable tool, the Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE). The design and development of MACHETE began in 2000 and is constantly evolving. Currently, MACHETE contains Consultative Committee for Space Data Systems (CCSDS) protocol standards such as Proximity-1, Advanced Orbiting Systems (AOS), Packet Telemetry/Telecommand, Space Communications Protocol Specification (SCPS), and the CCSDS File Delivery Protocol (CFDP). MACHETE uses the Aerospace Corporation s Satellite Orbital Analysis Program (SOAP) to generate the orbital geometry information and contact opportunities. Matlab scripts provide the link characteristics. At the core of MACHETE is a discrete event simulator, QualNet. Delay Tolerant Networking (DTN) is an end-to-end architecture providing communication in and/or through highly stressed networking environments. Stressed networking environments include those with intermittent connectivity, large and/or variable delays, and high bit error rates. To provide its services, the DTN protocols reside at the application layer of the constituent internets, forming a store-and-forward overlay network. The key capabilities of the bundling protocols include custody-based reliability, ability to cope with intermittent connectivity, ability to take advantage of scheduled and opportunistic connectivity, and late binding of names to addresses. In this presentation, we report on the addition of MACHETE models needed to support DTN, namely: the Bundle Protocol (BP) model. To illustrate the use of MACHETE with the additional DTN model, we provide an example simulation to benchmark its performance. We demonstrate the use of the DTN protocol and discuss statistics gathered concerning the total time needed to simulate numerous bundle transmissions

network protocols↗
NASA NTRS2009

Using Covariance Analysis to Assess Pointing Performance

A Pointing Covariance Analysis Tool (PCAT) has been developed for evaluating the expected performance of the pointing control system for NASA s Space Interferometry Mission (SIM). The SIM pointing control system is very complex, consisting of multiple feedback and feedforward loops, and operating with multiple latencies and data rates. The SIM pointing problem is particularly challenging due to the effects of thermomechanical drifts in concert with the long camera exposures needed to image dim stars. Other pointing error sources include sensor noises, mechanical vibrations, and errors in the feedforward signals. PCAT models the effects of finite camera exposures and all other error sources using linear system elements. This allows the pointing analysis to be performed using linear covariance analysis. PCAT propagates the error covariance using a Lyapunov equation associated with time-varying discrete and continuous-time system matrices. Unlike Monte Carlo analysis, which could involve thousands of computational runs for a single assessment, the PCAT analysis performs the same assessment in a single run. This capability facilitates the analysis of parametric studies, design trades, and "what-if" scenarios for quickly evaluating and optimizing the control system architecture and design.

Bayard, David↗
NASA NTRS2009

Understanding the Scalability of Bayesian Network Inference using Clique Tree Growth Curves

Bayesian networks (BNs) are used to represent and efficiently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to perform computation in BNs is clique tree clustering and propagation. In this approach, BN computation consists of propagation in a clique tree compiled from a Bayesian network. There is a lack of understanding of how clique tree computation time, and BN computation time in more general, depends on variations in BN size and structure. On the one hand, complexity results tell us that many interesting BN queries are NP-hard or worse to answer, and it is not hard to find application BNs where the clique tree approach in practice cannot be used. On the other hand, it is well-known that tree-structured BNs can be used to answer probabilistic queries in polynomial time. In this article, we develop an approach to characterizing clique tree growth as a function of parameters that can be computed in polynomial time from BNs, specifically: (i) the ratio of the number of a BN's non-root nodes to the number of root nodes, or (ii) the expected number of moral edges in their moral graphs. Our approach is based on combining analytical and experimental results. Analytically, we partition the set of cliques in a clique tree into different sets, and introduce a growth curve for each set. For the special case of bipartite BNs, we consequently have two growth curves, a mixed clique growth curve and a root clique growth curve. In experiments, we systematically increase the degree of the root nodes in bipartite Bayesian networks, and find that root clique growth is well-approximated by Gompertz growth curves. It is believed that this research improves the understanding of the scaling behavior of clique tree clustering, provides a foundation for benchmarking and developing improved BN inference and machine learning algorithms, and presents an aid for analytical trade-off studies of clique tree clustering using growth curves.

Mengshoel, Ole Jakob↗
NASA NTRS2004

A Decision Support Framework for Feasibility Analysis of International Space Station (ISS) Research Capability Enhancing Options

The assembly and operation of the ISS has generated significant challenges that have ultimately impacted resources available to the program's primary mission: research. To address this, program personnel routinely perform trade-off studies on alternative options to enhance research. The approach, content level of analysis and resulting outputs of these studies vary due to many factors, however, complicating the Program Manager's job of selecting the best option. To address this, the program requested a framework be developed to evaluate multiple research-enhancing options in a thorough, disciplined and repeatable manner, and to identify the best option on the basis of cost, benefit and risk. The resulting framework consisted of a systematic methodology and a decision-support toolset. The framework provides quantifiable and repeatable means for ranking research-enhancing options for the complex and multiple-constraint domain of the space research laboratory. This paper describes the development, verification and validation of this framework and provides observations on its operational use.

Ortiz, James N.↗
NASA NTRS2012

Influence of Alternative Engine Concepts on LCTR2 Sizing and Mission Profile

The Large Civil Tiltrotor (LCTR) was developed as part of the NASA Heavy Lift Rotorcraft Systems Investigation in order to establish a consistent basis for evaluating the benefits of advanced technology for large tiltrotors. The concept has since evolved into the second-generation LCTR2, designed to carry 90 passengers for 1,000 nm at 300 knots, with vertical takeoff and landing. This paper examines the impact of advanced propulsion system concepts on LCTR2 sizing. Two concepts were studied: an advanced, single-speed engine with a conventional power turbine layout (Advanced Conventional Engine, or ACE), and a variable-speed power turbine engine (VSPT). The ACE is the lighter engine, but requires a multi-speed (shifting) gearbox, whereas the VSPT uses a lighter, fixed-ratio gearbox. The NASA Design and Analysis of Rotorcraft (NDARC) design code was used to study the trades between rotor and engine efficiency and weight. Rotor performance was determined by Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics (CAMRAD II), and engine performance was estimated with the Numerical Propulsion System Simulation (NPSS). Design trades for the ACE vs. VSPT are presented in terms of vehicle weight empty for variations in mission altitude and range; the effect of different One Engine Inoperative (OEI) criteria are also examined. Because of its strong effect on gearbox weight and on both rotor and engine efficiency, rotor speed was chosen as the reference design variable for comparing design trades. The two propulsion concepts had nearly identical vehicle weights and mission fuel consumption, and their relative advantages varied little with cruise altitude, mission range, or OEI criteria; high cruise altitude and low cruise tip speed were beneficial for both concepts.

Acree, C. W., Jr.↗
NASA NTRS2012

Approach to an Affordable and Productive Space Transportation System

This paper describes an approach for creating space transportation architectures that are affordable, productive, and sustainable. The architectural scope includes both flight and ground system elements, and focuses on their compatibility to achieve a technical solution that is operationally productive, and also affordable throughout its life cycle. Previous papers by the authors and other members of the Space Propulsion Synergy Team (SPST) focused on space flight system engineering methods, along with operationally efficient propulsion system concepts and technologies. This paper follows up previous work by using a structured process to derive examples of conceptual architectures that integrate a number of advanced concepts and technologies. The examples are not intended to provide a near-term alternative architecture to displace current near-term design and development activity. Rather, the examples demonstrate an approach that promotes early investments in advanced system concept studies and trades (flight and ground), as well as in advanced technologies with the goal of enabling highly affordable, productive flight and ground space transportation systems.

McCleskey, Carey M.↗
NASA NTRS2014

Is a Space Laundry Needed for Exploration?

Future human space exploration missions will lengthen to years, and keeping crews clothed without a huge resupply burden is an important consideration for habitation systems. A space laundry system could be the solution; however, the resources it uses must be accounted for and must win out over the very reliable practice of bringing along enough spare underwear. Through NASA's Logistics Reduction and Repurposing project, trade off studies have been conducted to compare current space clothing systems, life extension of that clothing, traditional water based clothes washing and other sanitizing techniques. The best clothing system of course depends on the mission and assumptions, but in general, analysis results indicate that washing clothes on space missions will start to pay off as mission durations push past a year.

Ewert, Michael K.↗
NASA NTRS2015

Will Astronauts Wash Clothes on the Way to Mars?

Future human space exploration missions will lengthen to years, and keeping crews clothed without a huge resupply burden is an important consideration for habitation systems. A space laundry system could be the solution; however, the resources it uses must be accounted for and must win out over the reliable practice of simply bringing along enough spare underwear. NASA has conducted trade-off studies through its Logistics Reduction Project to compare current space clothing systems, life extension of that clothing, traditional water-based clothes washing, and other sanitizing techniques. The best clothing system depends on the mission and assumptions but, in general, analysis results indicate that washing clothes on space missions will start to pay off as mission durations approach a year.

Ewert, Michael K.↗
NASA NTRS2010

Risk Identification and Visualization in a Concurrent Engineering Team Environment

Incorporating risk assessment into the dynamic environment of a concurrent engineering team requires rapid response and adaptation. Generating consistent risk lists with inputs from all the relevant subsystems and presenting the results clearly to the stakeholders in a concurrent engineering environment is difficult because of the speed with which decisions are made. In this paper we describe the various approaches and techniques that have been explored for the point designs of JPL's Team X and the Trade Space Studies of the Rapid Mission Architecture Team. The paper will also focus on the issues of the misuse of categorical and ordinal data that keep arising within current engineering risk approaches and also in the applied risk literature.

Risk Scoring↗