AMMO: an automated multiple maneuver optimization system
An Automated Multiple Maneuver Optimization (AMMO) system is presented.
automated↗
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Results for “automated system optimization”
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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Reconciling Scientific Aspirations and Engineering Constraints for a Lunar Mission via Hyperdimensional Interpolation
Virtually every NASA space-exploration mission represents a compromise between the interests of two expert, dedicated, but very different communities: scientists, who want to go quickly to the places that interest them most and spend as much time there as possible conducting sophisticated experiments, and the engineers and designers charged with maximizing the probability that a given mission will be successful and cost-effective. Recent work at NASA's Jet Propulsion Laboratory (JPL) seeks to enhance communication between these two groups, and to help them reconcile their interests, by developing advanced modeling capabilities with which they can analyze the achievement of science goals and objectives against engineering design and operational constraints. The analyses conducted prior to this study have been point-design driven. Each analysis has been of one hypothetical case which addresses the question: Given a set of constraints, how much science can be done? But the constraints imposed by the architecture team-e.g., rover speed, time allowed for extravehicular activity (EVA), number of sites at which science experiments are to be conducted- are all in early development and carry a great deal of uncertainty. Variations can be incorporated into the analysis, and indeed that has been done in sensitivity studies designed to see which constraint variations have the greatest impact on results. But if a very large number of variations can be analyzed all at once, producing a table that includes virtually the entire trade space under consideration, then we have a tool that enables scientists and mission architects to ask the inverse question: For a given desired level of science (or any other objective), what is the range of constraints that would be needed? With this tool, mission architects could determine, for example, what combinations of rover speed, EVA duration, and other constraints produce the desired results. Further, this tool would help them identify which technology-improvement investments would be likely to produce the largest or most important return. However, the number of variations that need to be considered for such analysis quickly balloons to an unwieldy size. If three variations are considered for each of six constraints-a very modest example-there are a total of 243 variations to consider. If it takes 40 minutes to compute each variation, as it does with HURON, our automated optimization system, then it would take 162 hours or nearly 7 days of round-the-clock computing to calculate the results. Adding further constraints or variations exponentially increases the amount of time that is needed.
Weisbin, Charles R.↗
NASA Space Engineering Research Center for utilization of local planetary resources
Reports covering the period from 1 Nov. 1991 to 31 Oct. 1992 and documenting progress at the NASA Space Engineering Research Center are included. Topics covered include: (1) processing of propellants, volatiles, and metals; (2) production of structural and refractory materials; (3) system optimization discovery and characterization; (4) system automation and optimization; and (5) database development.
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An expert system for shuttle and satellite radar tracker scheduling
This expert system automates and optimizes radar tracker selection for shuttle missions. The expert system is written in the FORTRAN and C languages on an HP9000. It is portable to any UNIX machine having both ANSI-77 FORTRAN and C language compilers. It is a rule based expert system that selects tracking stations from the S-band and C-band radar stations and the TDRSS east and TDRSS west satellites under a variety of conditions. The expert system was prototyped on the Symbolics in the Automated Reasoning Tool (ART) and ZetaLisp. After the prototype demonstrated an acceptable automation of the process of selecting tracking stations to support the orbit determination requirements of Shuttle missions, the basic ART rules of the prototype were ported to the HP9000 computer using the CLIPS language. CLIPS is a forward-chaining rule-based expert system language written in C. Prior to the development of this expert system the selection process was a tedious manual process and expensive in terms of human resources. Manual tracking station selection required from 1 to 2 man weeks per mission; whereas the expert system can complete the selection process in about 2 hours.
Mitchell, Paul↗
ASTROS: A multidisciplinary automated structural design tool
ASTROS (Automated Structural Optimization System) is a finite-element-based multidisciplinary structural optimization procedure developed under Air Force sponsorship to perform automated preliminary structural design. The design task is the determination of the structural sizes that provide an optimal structure while satisfying numerous constraints from many disciplines. In addition to its automated design features, ASTROS provides a general transient and frequency response capability, as well as a special feature to perform a transient analysis of a vehicle subjected to a nuclear blast. The motivation for the development of a single multidisciplinary design tool is that such a tool can provide improved structural designs in less time than is currently needed. The role of such a tool is even more apparent as modern materials come into widespread use. Balancing conflicting requirements for the structure's strength and stiffness while exploiting the benefits of material anisotropy is perhaps an impossible task without assistance from an automated design tool. Finally, the use of a single tool can bring the design task into better focus among design team members, thereby improving their insight into the overall task.
Neill, D. J.↗
Linear Regression Model for Predictive Service Provider Selection
The increasing number of satellites in orbit has led to a growing reliance on third-party service providers for data transfer between Earth and space. Traditional approaches to managing satellite communications require human intervention, which becomes more burdensome with the escalating number of satellites. This research addresses the need for an efficient and automated system to optimize service provider selection for NASA space communication. Previous research has utilized human-operated approaches for service provider management. Our study fills a gap by developing a cognitive algorithm that automates and optimizes the selection process based on various parameters, such as data volume, priority, quality of service and cost. This novel solution reduces user burden, facilitates service management, and contributes to the development of cognitive spaceflight missions, ultimately supporting NASA’s research into Cognitive Communications technology. The algorithm design consists of three major steps: modeling data, developing a Link Selection Algorithm (LSA) based on a grading system, and applying machine learning using linear regression. The LSA evaluates providers based on user-defined constraints, considering factors such as delivery time, cost, and quality of service. We define a suitability metric which allows our algorithm to make a recommendation to a user regarding which commercial service providers to select. The addition of Linear Regression predicts the future suitability value. Our main findings demonstrate that the resulting algorithm can autonomously manage connections between satellites and providers, maximizing communication channel efficiency. This research has significant implications, as it not only addresses a pressing issue in satellite communication management but also advances the field of cognitive spaceflight missions.
Linear regression↗
NASA Space Engineering Research Center for Utilization of Local Planetary Resources
In the processing of propellants, volatiles, and metals subject area, the following topics are discussed: reduction of lunar regolith; reduction of carbon dioxide; and reduction of carbonaceous materials. Other areas addressed include: (1) production of structural and refractory materials; (2) resource discovery and characterization; (3) system automation and optimization; and (4) database development. The majority of these topics are discussed with respect to the development of lunar and mars bases. Some main topics of interest include: asteroid resources, lunar resources, mars resources, materials processing, construction materials, propellant production, oxygen production, and space-based oxygen production plants.
Ramohalli, Kumar↗
Influence of structural and aerodynamic modeling on optimization with flutter constraint
The influences of structural and aerodynamic modeling on multidisciplinary optimization in an aeroelastic environment are not well understood. Therefore, optimizations with flutter and frequency constraints were performed to investigate the effects these modeling factors have on various representative wings. To this end, the Automated Structural Optimization System (ASTROS) was used as a tool to minimize the weight of various fully built-up finite element wing models in subsonic and supersonic flow under given flutter and frequency constraints. First, the performance of the optimization module was tested against results from other codes on a straight and uniform wing widely used for optimization with flutter constraints. Then, fully built-up finite element models of various wings with different aspect ratios were investigated for the influence on the structural optimization for minimum weight of the following modeling factors: finite element selection, structural grid refinement; number of selected modes, retention of breathing modes; selection of reduced frequencies to be used in flutter analysis; aerodynamic panel size and placement; splining of the aerodynamic grid to the structural grid selection of extra points of the structural wing box for splining; and number of constraints to be retained. Knowledge of these influences as well as of the program behavior is important, since optimization can be made more efficient by the selection of reasonable initial models. Also, it was shown previously that modeling has an impact on the results of modal and aeroelastic analyses. Thus, if modeling errors can negatively affect the analyses, a minimum weight optimization can be jeopardized and result in an optimal design that is rather unreliable. In the following, selected results are presented and the influences of some modeling parameters on optimization are pointed out.
Striz, Alfred G.↗
Evolutionary Optimization of Yagi-Uda Antennas
Yagi-Uda antennas are known to be difficult to design and optimize due to their sensitivity at high gain, and the inclusion of numerous parasitic elements. We present a genetic algorithm-based automated antenna optimization system that uses a fixed Yagi-Uda topology and a byte-encoded antenna representation. The fitness calculation allows the implicit relationship between power gain and sidelobe/backlobe loss to emerge naturally, a technique that is less complex than previous approaches. The genetic operators used are also simpler. Our results include Yagi-Uda antennas that have excellent bandwidth and gain properties with very good impedance characteristics. Results exceeded previous Yagi-Uda antennas produced via evolutionary algorithms by at least 7.8% in mainlobe gain. We also present encouraging preliminary results where a coevolutionary genetic algorithm is used.
Lohn, Jason D.↗
Integrated design optimization research and development in an industrial environment
An overview is given of a design optimization project that is in progress at the GE Research and Development Center for the past few years. The objective of this project is to develop a methodology and a software system for design automation and optimization of structural/mechanical components and systems. The effort focuses on research and development issues and also on optimization applications that can be related to real-life industrial design problems. The overall technical approach is based on integration of numerical optimization techniques, finite element methods, CAE and software engineering, and artificial intelligence/expert systems (AI/ES) concepts. The role of each of these engineering technologies in the development of a unified design methodology is illustrated. A software system DESIGN-OPT has been developed for both size and shape optimization of structural components subjected to static as well as dynamic loadings. By integrating this software with an automatic mesh generator, a geometric modeler and an attribute specification computer code, a software module SHAPE-OPT has been developed for shape optimization. Details of these software packages together with their applications to some 2- and 3-dimensional design problems are described.
Kumar, V.↗
A high speed, automated solution for physical network or system parameters based on sensitivity analysis and hybrid computer optimization techniques
High speed automated network design method for optimum value determination of system parameters, using sensitivity analysis and hybrid computer optimization techniques
Beck, C. H.↗
Direct modeling parameter signature analysis and failure mode prediction of physical systems using hybrid computer optimization
High speed automated identification and design of dynamic systems, both linear and nonlinear, are discussed. Special emphasis is placed on developing hardware and techniques which are applicable to practical problems. The basic modeling experiment and new results are described. Using the improvements developed successful identification of several systems, including a physical example as well as simulated systems, was obtained. The advantages of parameter signature analysis over signal signature analysis in go-no go testing of operational systems were demonstrated. The feasibility of using these ideas in failure mode prediction in operating systems was also investigated. An improved digital controlled nonlinear function generator was developed, de-bugged, and completely documented.
Drake, R. L.↗
From Diagnosis to Action: An Automated Failure Advisor for Human Deep Space Missions
The major goal of current space system development at NASA is to enable human travel to deep space locations such as Mars and asteroids. At that distance, round trip communication with ground operators may take close to an hour, thus it becomes unfeasible to seek ground operator advice for problems that require immediate attention, either for crew safety or for activities that need to be performed at specific times for the attainment of scientific results. To achieve this goal, major reliance will need to be placed on automation systems capable of aiding the crew in detecting and diagnosing failures, assessing consequences of these failures, and providing guidance in repair activities that may be required. We report here on the most current step in the continuing development of such a system, and that is the addition of a Failure Response Advisor. In simple terms, we have a system in place the Advanced Caution and Warning System (ACAWS) to tell us what happened (failure diagnosis) and what happened because that happened (failure effects). The Failure Response Advisor will tell us what to do about it, how long until something must be done and why its important that something be done and will begin to approach the complex reasoning that is generally required for an optimal approach to automated system health management. This advice is based on the criticality and various timing elements, such as durations of activities and of component repairs, failure effects delay, and other factors. The failure advice is provided to operators (crew and mission controllers) together with the diagnostic and effects information. The operators also have the option to drill down for more information about the failure and the reasons for any suggested priorities.
spacecraft health maintenance↗
System modeling and structure optimization using hybrid computer techniques
Automated modeling and structure optimization of linear dynamic systems and circuits, using hybrid computer techniques and time-domain test data
Beck, C. H.↗
Ranking problems in multivariate normal (statistical) populations (first year work). Nonparametric ranging and selection procedures (second year work)
Optimal selection of automation systems under multivariate normal model in terms of reliability, feasibility, and economy
Rizvi, M. H.↗
Robotic Surgery
The Automated Endoscopic System for Optimal Positioning, or AESOP, was developed by Computer Motion, Inc. under a SBIR contract from the Jet Propulsion Lab. AESOP is a robotic endoscopic positioning system used to control the motion of a camera during endoscopic surgery. The camera, which is mounted at the end of a robotic arm, previously had to be held in place by the surgical staff. With AESOP the robotic arm can make more precise and consistent movements. AESOP is also voice controlled by the surgeon. It is hoped that this technology can be used in space repair missions which require precision beyond human dexterity. A new generation of the same technology entitled the ZEUS Robotic Surgical System can make endoscopic procedures even more successful. ZEUS allows the surgeon control various instruments in its robotic arms, allowing for the precision the procedure requires.
Source record↗
A Ground Systems Architecture Transition for A Distributed Operations System
The Marshall Space Flight Center (MSFC) Ground Systems Department (GSD) recently undertook an architecture change in the product line that serves the ISS program. As a result, the architecture tradeoffs between data system product lines that serve remote users versus those that serve control center flight control teams were explored extensively. This paper describes the resulting architecture that will be used in the ISS payloads program, and the resulting functional breakdown of the products that support that architecture. It also describes the lessons learned from the path that was followed, as a migration of products cause the need to reevaluate the allocation of functions across the architecture. The result is a set of innovative ground system solutions that is scalable so it can support facilities of wide-ranging sizes, from a small site up to large control centers. Effective use of system automation, custom components, design optimization for data management, data storage, data transmissions, and advanced local and wide area networking architectures, plus the effective use of Commercial-Off-The-Shelf (COTS) products, provides flexible Remote Ground System options that can be tailored to the needs of each user. This paper offers a description of the efficiency and effectiveness of the Ground Systems architectural options that have been implemented, and includes successful implementation examples and lessons learned.
Sellers, Donna↗