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Inserts on ball-separator ring of ball bearings provide continuous film of lubricant on ball surfaces. Inserts are machined or molded. Small inserts in ball pockets provide steady supply of lubricant. Technique is utilized on equipment for which maintenance is often poor and lubrication interval is uncertain, such as household appliances, automobiles, and marine engines.
Attention is given to Space Shuttle Main Engine (SSME) life extension and logistical systems that support launch and ground operations. The operations and maintenance tasks involved in this aspect of SSME development include turnaround requirements, ground support equipment, and control documentation. A discussion is presented on the spare parts provisioning system, which emphasizes the source of decision-making data and encompasses the hardware tracking system, usage data from ground testing and launch operations, and current and projected life limits. The life extension test program leads the launch program, offering comfortable life limit margins. Planned overhauls for the extension of useful hardware life beyond the 55-mission requirement, a turnabout improvement program, and a continuous training program contribute to launch cost reductions, reliable operations, and long life.
Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.
A Lunar Optical UV-IR Synthesis Array (LOUISA) proposed to take advantage of the characteristics of the lunar environment requires appropriate advances in technology. These technologies are in the areas of contamination/interference control, test and evaluation, manufacturing, construction, autonomous operations and maintenance, power and heating/cooling, stable precision structures, optics, parabolic antennas, and communications/control. LOUISA needs to be engineered to operate for long periods with minimal intervention by humans or robots. What is essential for LOUISA operation is enforcement of a systems engineering approach that makes compatible all lunar operations associated with habitation, resource development, and science.
Software Engineering is a knowledge intensive activity that involves defining, designing, developing, and maintaining software systems. In order to build effective systems to support Software Engineering activities, Artificial Intelligence techniques are needed. The application of Artificial Intelligence technology to Software Engineering is called Knowledge-based Software Engineering (KBSE). The goal of KBSE is to change the software life cycle such that software maintenance and evolution occur by modifying the specifications and then rederiving the implementation rather than by directly modifying the implementation. The use of domain knowledge in developing KBSE systems is crucial. Our work is mainly related to one area of KBSE that is called automatic specification acquisition. One example is the WATSON prototype on which our current work is based. WATSON is an automatic programming system for formalizing specifications for telephone switching software mainly restricted to POTS, i.e., plain old telephone service. Our current approach differentiates itself from other approaches in two antagonistic ways. On the one hand, we address a large and complex real-world problem instead of a 'toy domain' as in many research prototypes. On the other hand, to allow such scaling, we had to relax the ambitious goal of complete automatic programming, to the easier task of automatic testing.
The Lyndon B. Johnson Space Center Automation and Robotics Division has developed a simulation tool for use in evaluating the feasibility and effectiveness of proposed candidate mission concepts, such as the First Lunar Outpost design reference missions. The tool helps in defining requirements for such missions at the beginning of the definition activities and can be applied iteratively thereafter on a short cycle basis as changes are made to the mission definition. The simulation is applicable to the amount and capabilities of automation and robotics; number and skills of crew; amount of engineering work, science, and in-space materials utilization to be accomplished; impact of provision for maintenance and repair; and flight schedules and manifests. The simulation accounts for supply and demand of resources to accomplish tasks and accounts for elapsed time in carrying out mission processes and tasks.
The complexity of the Space Shuttle Main Engine (SSME), combined with mounting requirements to reduce operations costs have increased demands for accurate tracking, maintenance, and projections of SSME assets. The SSME Logistics Team is developing an integrated asset management process. This PC-based tool provides a user-friendly asset database for daily decision making, plus a variable-input hardware usage simulation with complex logic yielding output that addresses essential asset management issues. Cycle times on critical tasks are significantly reduced. Associated costs have decreased as asset data quality and decision-making capability has increased.
Although forces outside our control shape our industry, turbomachine sealing research, design, and customer agendas established in 1978 by Ludwig, Campbell, and Smith in terms of specific fuel consumption and performance remain as objectives today. Advances have been made because failures of the space shuttle main engine turbomachinery ushered in a new understanding of sealing in high-power-density systems. Further, it has been shown that changes in sealing, especially for high-pressure rotors, dramatically change the performance of the entire engine or turbomachine. Maintaining seal leakages and secondary flows within engine design specifications remains the most efficient and cost effective way to enhance performance and minimize maintenance costs. This three-part review summarizes experiences, ideas, successes, and failures by NASA and the U.S. aerospace industry in secondary flow management in advanced turbomachinery. Part 1 presents system sealing, part 2 system rotordynamics, and part 3 modeling, with some overlap of each part.
In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.
Advanced technical features of the electronic integrated propulsion control system (IPCS) and flight evaluation tests of IPCS (F-111E with TF30-P-9 engines as test vehicle) are described. Nine baseline flight tests and 15 IPCS flight tests were conducted. Instrumentation, data acquisition and data processing systems, software maintenance procedures, flight test procedures, flight safety criteria, flight test results, and ground and flight testing of the aircraft system are described. Advantages conferred by IPCS include: faster accelerations (both gas generator and afterburner performance), better thrust and flight control, reduced flight idle thrust, reduced engine ground trim, extended service ceiling, automatic stall detection, and stall recovery detection.
Information on knowledge-based systems (KBS) is given in viewgraph form. Information is given on KBS standardization needs, the knowledge engineering process, program management, software and hardware issues, and chronic problem areas.
The Software Engineering Laboratory (SEL) is currently engaged in a Methodology and Metrics program for the Information Systems Center (ISC) at Goddard Space Flight Center (GSFC). This paper addresses the Methodology portion of the program. The purpose of the Methodology effort is to assist a software team lead in selecting and tailoring a software development or maintenance process for a specific GSFC project. It is intended that this process will also be compliant with both ISO 9001 and the Software Engineering Institute's Capability Maturity Model (CMM). Under the Methodology program, we have defined four standard ISO-compliant software processes for the ISC, and three tailoring criteria that team leads can use to categorize their projects. The team lead would select a process and appropriate tailoring factors, from which a software process tailored to the specific project could be generated. Our objective in the Methodology program is to present software process information in a structured fashion, to make it easy for a team lead to characterize the type of software engineering to be performed, and to apply tailoring parameters to search for an appropriate software process description. This will enable the team lead to follow a proven, effective software process and also satisfy NASA's requirement for compliance with ISO 9001 and the anticipated requirement for CMM assessment. This work is also intended to support the deployment of sound software processes across the ISC.
The process for selecting materials for use in oxygen or oxygen-enriched environments is one that continues to be investigated by many industries due to the importance to those industries of oxygen systems. There are several excellent resources available to assist oxygen systems design engineers and end-users, with the most comprehensive being ASTM MNL-36, Safe Use of Oxygen and Oxygen Systems: Handbook for Design, Operation and Maintenance, 2nd Edition. ASTM also makes available several standards for oxygen systems. However, the ASTM publications are extremely detailed, and typically designed for professionals who already possess a working knowledge of oxygen systems. No notable resource exists, whether an ASTM or other organizational publication, which can be used to educate engineers or technicians who have no prior knowledge of the nuances of oxygen system design and safety. This paper will fill the void for information needed by organizations that design or operate oxygen systems. The information in this paper is not new information, but is a concise and easily understood summary of selecting materials for oxygen systems. This paper will serve well as an employee s first introduction to oxygen system materials selection, and probably the employee s first introduction to ASTM.
No abstract available
Detecting rotating engine component malfunctions and structural anomalies is increasingly becoming a crucial key feature that will help boost safety and lower maintenance cost. However, achievement of such technology, which can be referred to as a health monitoring remains somewhat challenging to implement. This is mostly due to presence of scattered loading conditions, crack sizes, component geometry and material properties that hinders the simplicity of imposing such application. Different approaches are being considered to assist in developing other means of health monitoring or nondestructive techniques to detect hidden flaws and mini cracks before any catastrophic events occur. These methods extend further to assess material discontinuities and other defects that have matured to the level where a failure is very likely. This paper is focused on presenting data obtained from spin test experiments of a turbine engine like rotor disk and their correlation to the development of a structural health monitoring and fault detection system. The data collected includes blade tip clearance, blade tip timing measurements and shaft displacements. The experimental results are collected at rotational speeds up to 10,000 Rpm and tests are conducted at the NASA Glenn Research Center s Rotordynamics Laboratory via a high precision spin system. Additionally, this study offers a closer glance at a selective online evaluation of a rotating disk using advanced capacitive, microwave and eddy current sensor technology.
We present the initiation of a community-driven framework for the integration of accelerator digital twins into control systems: Twinac. Few facilities have fully integrated accelerator digital twins like at Cornell’s CHESS. Many facilities have active research to employ surrogate models to aid in operational decisions like at Argonne’s ALS, MSU’s FRIB, SLAC’s LCLS-II, and Fermilab’s FAST/IOTA, PIP-II, and main complex. To lower the barrier to entry for all accelerator facilities to build and benefit from a digital twin of their own accelerators, we propose the following software framework. Twinac will provide the capability to compose one’s own digital twin using reusable components engineered at other facilities. With this model in place, Twinac will also support tools for (1) predictive maintenance systems; (2) discovery of correlated but uncontrolled environmental factors, like seasonal temperature variations causing performance changes on power supplies, magnets, etc.; and (3) prototyping and updating sophisticated optimization and controls algorithms. The Twinac framework will enable sharing and simplified deployment of modeled components and control algorithms at all facilities. With an inter-facility team to build and support the Twinac framework, it will be easy to publish and try out the latest advancements at one’s own facility.
The operating requirements established by NASA for the SSME were considerably more demanding than those for earlier rocket engines used in the military launch vehicles or Apollo program. The SSME, in order to achieve the high performance, low weight, long life, reusable objectives, embodied technical demands far in excess of its predecessor rocket engines. The requirements dictated the use of high combustion pressure and the staged combustion cycle which maximizes performance through total use of all propellants in the main combustion process. This approach presented a myriad of technical challenges for maximization of performance within attainable state of the art capabilities for operating pressures, operating temperatures and rotating machinery efficiencies. Controlling uniformity of the high pressure turbomachinery turbine temperature environment was a key challenge for thrust level and life capability demanding innovative engineering. New approaches in the design of the components were necessary to accommodate the multiple use, minimum maintenance objectives. Included were the use of line replaceable units to facilitate field maintenance automatic checkout and internal inspection capabilities.
A study was conducted to define characteristics of a Regenerative Fuel Cell System (RFCS) for low earth orbit Space Station missions. The RFCS's were defined and characterized based on both an alkaline electrolyte fuel cell integrated with an alkaline electrolyte water electrolyzer and an alkaline electrolyte fuel cell integrated with an acid solid polymer electrolyte (SPE) water electrolyzer. The study defined the operating characteristics of the systems including system weight, volume, and efficiency. A maintenance philosophy was defined and the implications of system reliability requirements and modularization were determined. Finally, an Engineering Model System was defined and a program to develop and demonstrate the EMS and pacing technology items that should be developed in parallel with the EMS were identified. The specific weight of an optimized RFCS operating at 140 F was defined as a function of system efficiency for a range of module sizes. An EMS operating at a nominal temperature of 180 F and capable of delivery of 10 kW at an overall efficiency of 55.4 percent is described. A program to develop the EMS is described including a technology development effort for pacing technology items.