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Artificial intelligence - NASA

Artificial Intelligence (AI) represents a vital common space support element needed to enable the civil space program and commercial space program to perform their missions successfully. It is pointed out that advances in AI stimulated by the Space Station Program could benefit the U.S. in many ways. A fundamental challenge for the civil space program is to meet the needs of the customers and users of space with facilities enabling maximum productivity and having low start-up costs, and low annual operating costs. An effective way to meet this challenge may involve a man-machine system in which artificial intelligence, robotics, and advanced automation are integrated into high reliability organizations. Attention is given to the benefits, NASA strategy for AI, candidate space station systems, the Space Station as a stepping stone, and the commercialization of space.

Erickson, J. D.↗

An expert system for choosing the best combination of options in a general purpose program for automated design synthesis

An expert system called EXADS has been developed to aid users of the Automated Design Synthesis (ADS) general purpose optimization program. ADS has approximately 100 combinations of strategy, optimizer, and one-dimensional search options from which to choose. It is difficult for a nonexpert to make this choice. This expert system aids the user in choosing the best combination of options based on the users knowledge of the problem and the expert knowledge stored in the knowledge base. The knowledge base is divided into three categories; constrained problems, unconstrained problems, and constrained problems being treated as unconstrained problems. The inference engine and rules are written in LISP, contains about 200 rules, and executes on DEC-VAX (with Franz-LISP) and IBM PC (with IQ-LISP) computers.

Rogers, J. L.↗

An evidential approach to model-based satellite diagnosis

The paper presents an approach to the implementation of an automated satellite diagnosis capability which emphasizes techniques offering flexibility in the application of diagnostic strategies. The system utilizes a structural and behavioral model of the satellite; it uses a form of spreading activation to perform the diagnostic procedures on the model. A Dempster-Shafer evidential framework was implemented, making it possible to integrate evidence from the multiple sources necessary for building useful systems.

Bickmore, Timothy W.↗

Distributed Optimization

We demonstrate a new framework for analyzing and controlling distributed systems, by solving constrained optimization problems with an algorithm based on that framework. The framework is ar. information-theoretic extension of conventional full-rationality game theory to allow bounded rational agents. The associated optimization algorithm is a game in which agents control the variables of the optimization problem. They do this by jointly minimizing a Lagrangian of (the probability distribution of) their joint state. The updating of the Lagrange parameters in that Lagrangian is a form of automated annealing, one that focuses the multi-agent system on the optimal pure strategy. We present computer experiments for the k-sat constraint satisfaction problem and for unconstrained minimization of NK functions.

Macready, William↗

Fault Management Techniques in Human Spaceflight Operations

This paper discusses human spaceflight fault management operations. Fault detection and response capabilities available in current US human spaceflight programs Space Shuttle and International Space Station are described while emphasizing system design impacts on operational techniques and constraints. Preflight and inflight processes along with products used to anticipate, mitigate and respond to failures are introduced. Examples of operational products used to support failure responses are presented. Possible improvements in the state of the art, as well as prioritization and success criteria for their implementation are proposed. This paper describes how the architecture of a command and control system impacts operations in areas such as the required fault response times, automated vs. manual fault responses, use of workarounds, etc. The architecture includes the use of redundancy at the system and software function level, software capabilities, use of intelligent or autonomous systems, number and severity of software defects, etc. This in turn drives which Caution and Warning (C&W) events should be annunciated, C&W event classification, operator display designs, crew training, flight control team training, and procedure development. Other factors impacting operations are the complexity of a system, skills needed to understand and operate a system, and the use of commonality vs. optimized solutions for software and responses. Fault detection, annunciation, safing responses, and recovery capabilities are explored using real examples to uncover underlying philosophies and constraints. These factors directly impact operations in that the crew and flight control team need to understand what happened, why it happened, what the system is doing, and what, if any, corrective actions they need to perform. If a fault results in multiple C&W events, or if several faults occur simultaneously, the root cause(s) of the fault(s), as well as their vehicle-wide impacts, must be determined in order to maintain situational awareness. This allows both automated and manual recovery operations to focus on the real cause of the fault(s). An appropriate balance must be struck between correcting the root cause failure and addressing the impacts of that fault on other vehicle components. Lastly, this paper presents a strategy for using lessons learned to improve the software, displays, and procedures in addition to determining what is a candidate for automation. Enabling technologies and techniques are identified to promote system evolution from one that requires manual fault responses to one that uses automation and autonomy where they are most effective. These considerations include the value in correcting software defects in a timely manner, automation of repetitive tasks, making time critical responses autonomous, etc. The paper recommends the appropriate use of intelligent systems to determine the root causes of faults and correctly identify separate unrelated faults.

O'Hagan, Brian↗

MATE: The multi-agent test environment

In this report we present the Multi-Agent Test Environment, MATE. MATE is a collection of experiment management tools for assisting in the design, testing, and evaluation of distributed problem-solvers. It provides the experimenter with an automated tool for executing and monitoring experiments choosing among rule bases, number of agents, communication strategies, and inference engines. Using MATE the experimenter can run a series of distributed problem-solving experiments without human intervention.

Mason, Cindy L.↗

Nonlinear rescaling of control values simplifies fuzzy control

Traditional control theory is well-developed mainly for linear control situations. In non-linear cases there is no general method of generating a good control, so we have to rely on the ability of the experts (operators) to control them. If we want to automate their control, we must acquire their knowledge and translate it into a precise control strategy. The experts' knowledge is usually represented in non-numeric terms, namely, in terms of uncertain statements of the type 'if the obstacle is straight ahead, the distance to it is small, and the velocity of the car is medium, press the brakes hard'. Fuzzy control is a methodology that translates such statements into precise formulas for control. The necessary first step of this strategy consists of assigning membership functions to all the terms that the expert uses in his rules (in our sample phrase these words are 'small', 'medium', and 'hard'). The appropriate choice of a membership function can drastically improve the quality of a fuzzy control. In the simplest cases, we can take the functions whose domains have equally spaced endpoints. Because of that, many software packages for fuzzy control are based on this choice of membership functions. This choice is not very efficient in more complicated cases. Therefore, methods have been developed that use neural networks or generic algorithms to 'tune' membership functions. But this tuning takes lots of time (for example, several thousands iterations are typical for neural networks). In some cases there are evident physical reasons why equally space domains do not work: e.g., if the control variable u is always positive (i.e., if we control temperature in a reactor), then negative values (that are generated by equal spacing) simply make no sense. In this case it sounds reasonable to choose another scale u' = f(u) to represent u, so that equal spacing will work fine for u'. In the present paper we formulate the problem of finding the best rescaling function, solve this problem, and show (on a real-life example) that after an optimal rescaling, the un-tuned fuzzy control can be as good as the best state-of-art traditional non-linear controls.

Vanlangingham, H.↗

Computer-controlled float zone crystal growth

A PC-based computer control system to automate a high-temperature float zone growth of titanium carbide is reported. The control strategy of the computer control system relies on the relations derived from a combination of empirical relations and results from detailed mathematical analysis of the physical transports of the entire float zone assembly. A system control computer program was written to establish real-time determination of the size of the molten zone from a thermal image, control parameters from established relationships, and collected processed data to achieve control objectives. We found that the developed computer control allows the growth process to be operated nearer the stability limit. Any slight variations in growth conditions can be corrected in time to avoid any instability growth, which otherwise cannot be adjusted via manual control.

Chan, Y. T.↗

Design for Verification: Enabling Verification of High Dependability Software-Intensive Systems

Strategies to achieve confidence that high-dependability applications are correctly implemented include testing and automated verification. Testing deals mainly with a limited number of expected execution paths. Verification usually attempts to deal with a larger number of possible execution paths. While the impact of architecture design on testing is well known, its impact on most verification methods is not as well understood. The Design for Verification approach considers verification from the application development perspective, in which system architecture is designed explicitly according to the application's key properties. The D4V-hypothesis is that the same general architecture and design principles that lead to good modularity, extensibility and complexity/functionality ratio can be adapted to overcome some of the constraints on verification tools, such as the production of hand-crafted models and the limits on dynamic and static analysis caused by state space explosion.

Mehlitz, Peter C.↗

IceVal DatAssistant: An Interactive, Automated Icing Data Management System

As with any scientific endeavor, the foundation of icing research at the NASA Glenn Research Center (GRC) is the data acquired during experimental testing. In the case of the GRC Icing Branch, an important part of this data consists of ice tracings taken following tests carried out in the GRC Icing Research Tunnel (IRT), as well as the associated operational and environmental conditions documented during these tests. Over the years, the large number of experimental runs completed has served to emphasize the need for a consistent strategy for managing this data. To address the situation, the Icing Branch has recently elected to implement the IceVal DatAssistant automated data management system. With the release of this system, all publicly available IRT-generated experimental ice shapes with complete and verifiable conditions have now been compiled into one electronically-searchable database. Simulation software results for the equivalent conditions, generated using the latest version of the LEWICE ice shape prediction code, are likewise included and are linked to the corresponding experimental runs. In addition to this comprehensive database, the IceVal system also includes a graphically-oriented database access utility, which provides reliable and easy access to all data contained in the database. In this paper, the issues surrounding historical icing data management practices are discussed, as well as the anticipated benefits to be achieved as a result of migrating to the new system. A detailed description of the software system features and database content is also provided; and, finally, known issues and plans for future work are presented.

Levinson, Laurie H.↗

Human exploration mission studies

The Office of Exploration has established a process whereby all NASA field centers and other NASA Headquarters offices participate in the formulation and analysis of a wide range of mission strategies. These strategies were manifested into specific scenarios or candidate case studies. The case studies provided a systematic approach into analyzing each mission element. First, each case study must address several major themes and rationale including: national pride and international prestige, advancement of scientific knowledge, a catalyst for technology, economic benefits, space enterprise, international cooperation, and education and excellence. Second, the set of candidate case studies are formulated to encompass the technology requirement limits in the life sciences, launch capabilities, space transfer, automation, and robotics in space operations, power, and propulsion. The first set of reference case studies identify three major strategies: human expeditions, science outposts, and evolutionary expansion. During the past year, four case studies were examined to explore these strategies. The expeditionary missions include the Human Expedition to Phobos and Human Expedition to Mars case studies. The Lunar Observatory and Lunar Outpost to Early Mars Evolution case studies examined the later two strategies. This set of case studies established the framework to perform detailed mission analysis and system engineering to define a host of concepts and requirements for various space systems and advanced technologies. The details of each mission are described and, specifically, the results affecting the advanced technologies required to accomplish each mission scenario are presented.

Cataldo, Robert L.↗

IceVal DatAssistant: An Interactive, Automated Icing Data Management System

As with any scientific endeavor, the foundation of icing research at the NASA Glenn Research Center (GRC) is the data acquired during experimental testing. In the case of the GRC Icing Branch, an important part of this data consists of ice tracings taken following tests carried out in the GRC Icing Research Tunnel (IRT), as well as the associated operational and environmental conditions during those tests. Over the years, the large number of experimental runs completed has served to emphasize the need for a consistent strategy to manage the resulting data. To address this situation, the Icing Branch has recently elected to implement the IceVal DatAssistant automated data management system. With the release of this system, all publicly available IRT-generated experimental ice shapes with complete and verifiable conditions have now been compiled into one electronically-searchable database; and simulation software results for the equivalent conditions, generated using the latest version of the LEWICE ice shape prediction code, are likewise included and linked to the corresponding experimental runs. In addition to this comprehensive database, the IceVal system also includes a graphically-oriented database access utility, which provides reliable and easy access to all data contained in the database. In this paper, the issues surrounding historical icing data management practices are discussed, as well as the anticipated benefits to be achieved as a result of migrating to the new system. A detailed description of the software system features and database content is also provided; and, finally, known issues and plans for future work are presented.

Levinson, Laurie H.↗

An expert system for choosing the best combination of options in a general-purpose program for automated design synthesis

An expert system was developed to aid a user of the Automated Design Synthesis (ADS) general-purpose optimization computer program in selecting the best combination of strategy, optimizer, and one-dimensional search options for solving a problem. There are approximately 100 such combinations available in ADS. The knowledge base contains over 200 rules, and is divided into three categories: constrained problems, unconstrained problems, and constrained problems treated as unconstrained problems. The inference engine is written in LISP and is available on DEC-VAX and IBM PC/XT computers.

Rogers, J. L., Jr.↗

Flying SATS Higher Volume Operations: Training, Lessons Learned, and Pilots' Experiences

Developments in aviation, including new surveillance technologies and quicker, more economical small aircraft, have been identified as driving factors in a potential expansion of the use of non-towered, non-radar airports. The Small Aircraft Transportation System (SATS) project has developed the Higher Volume Operations (HVO) concept that enables pilots to safely arrive and depart these airports in instrument conditions at an increased rate as compared to today's procedures. This is achieved by transferring some traffic management tasks to centralized, ground-based automation, while assigning others to participating pilots aided by on-board tools. This paper describes strategies and lessons learned while training pilots to fly these innovative operations. Pilot approaches to using the experimental displays and dynamic altering systems during training are discussed. Potential operational benefits as well as pit-falls and frustrations expressed by subjects while learning to fly these new procedures are presented. Generally, pilots were comfortable with the procedures and the training process, and expressed interest in its near-term implementation.

Conway, Sheila↗

Implementation of Combinatorial Optimization Techniques for Automated Fiber Placement Through Thickness Defect Stack-Up Minimization

The Computer Aided Process Planning (CAPP) module was developed to facilitate and accelerate the process planning workflow for Automated Fiber Placement (AFP). CAPP assists process planners in identifying optimal starting point locations and layup strategies for each ply of a laminate. Ply optimization operates on measurement and scoring of geometry-based defects such as gaps, overlaps, angle deviation, and steering. This paper expands on the established framework for analyzing defect stack-up through thickness of a laminate. Four different combinatorial optimization algorithms are implemented and evaluated: (1) genetic algorithm, (2) differential evolution, (3) particle swarm, and (4) greedy search. The algorithms identify the optimal combination of ply-level layup strategies, by scoring potential laminates on defect stacking, using two different objective functions. A final optimization approach is also presented which trades some performance for a large gain in efficiency. These approaches are compared to a randomized combination using a complex tool surface in a virtual case study. The result is a streamlined methodology for comparing different laminate-level manufacturing strategies and minimizing the through thickness defect stack up.

CAPP↗

Investigation of Physical Mechanisms for Jet Noise Reduction by Plug Nozzle Porosity

This paper presents the results of a computational study on porous-plug nozzles for their eventual application in reducing takeoff noise levels for supersonic civil transport. The study explores a wide range of porous-plug geometries, encompassing variations in hole size, plug length and porosity. Computational fluid dynamics (CFD) analyses are employed in concert with an advanced automated mesh refinement (AMR) scheme, Sketch-to-Solution (S2S), to investigate porous plug nozzle design strategies that may diminish shock strength, broad-band shock noise (BBSN), flow separation, and other undesirable characteristics associated with high takeoff noise levels. A selected subset of the porous-plug nozzles that were analyzed computationally were manufactured at subscale using stereolithography 3D printing. These nozzles were tested experimentally, obtaining far-field noise spectral data and schlieren flow visualization pictures. Detailed comparisons between CFD predictions and experimental results were conducted. These comparisons focus on gaining a better understanding of the underlying physical mechanisms responsible for noise reduction with the porous plugs relative to corresponding solid plugs.

computational fluid dynamics↗

Investigation of Physical Mechanisms for Jet Noise Reduction by Plug Nozzle Porosity

This paper presents the results of a computational study on porous-plug nozzles for their eventual application in reducing takeoff noise levels for supersonic civil transport. The study explores a wide range of porous-plug geometries, encompassing variations in hole size, plug length and porosity. Computational fluid dynamics (CFD) analyses are employed in concert with an advanced automated mesh refinement (AMR) scheme, Sketch-to-Solution (S2S), to investigate porous plug nozzle design strategies that may diminish shock strength, broad-band shock noise (BBSN), flow separation, and other undesirable characteristics associated with high takeoff noise levels. A selected subset of the porous-plug nozzles that were analyzed computationally were manufactured at subscale using stereolithography 3D printing. These nozzles were tested experimentally, obtaining far-field noise spectral data and schlieren flow visualization pictures. Detailed comparisons between CFD predictions and experimental results were conducted. These comparisons focus on gaining a better understanding of the underlying physical mechanisms responsible for noise reduction with the porous plugs relative to corresponding solid plugs.

Nozzles↗

Automated Scheduling of Federated Observations in the NOS Testbed

The advancement of remote and in-situ sensing technology, combined with the emergence of New Space ventures, is producing a variety of new measurements for Earth Science phenomena. New observation techniques must combine and leverage these federated systems. In developing this new paradigm, NASA’s Earth Science Technology Office is developing the New Observing Strategies (NOS) Testbed to validate and demonstrate new operations concepts. As a part of this effort, we have developed a planning and scheduling system to support automated retasking

Chien, Steve↗