A neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine

In order to properly utilize the available fuel and oxidizer of a liquid propellant rocket engine, the mixture ratio is closed loop controlled during main stage (65 percent - 109 percent power) operation. However, because of the lack of flight-capable instrumentation for measuring mixture ratio, the value of mixture ratio in the control loop is estimated using available sensor measurements such as the combustion chamber pressure and the volumetric flow, and the temperature and pressure at the exit duct on the low pressure fuel pump. This estimation scheme has two limitations. First, the estimation formula is based on an empirical curve fitting which is accurate only within a narrow operating range. Second, the mixture ratio estimate relies on a few sensor measurements and loss of any of these measurements will make the estimate invalid. In this paper, we propose a neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine. The estimator is an extension of a previously developed neural network based sensor failure detection and recovery algorithm (sensor validation). This neural network uses an auto associative structure which utilizes the redundant information of dissimilar sensors to detect inconsistent measurements. Two approaches have been identified for synthesizing mixture ratio from measurement data using a neural network. The first approach uses an auto associative neural network for sensor validation which is modified to include the mixture ratio as an additional output. The second uses a new network for the mixture ratio estimation in addition to the sensor validation network. Although mixture ratio is not directly measured in flight, it is generally available in simulation and in test bed firing data from facility measurements of fuel and oxidizer volumetric flows. The pros and cons of these two approaches will be discussed in terms of robustness to sensor failures and accuracy of the estimate during typical transients using simulation data

A Newman-Penrose Calculator for Instanton Metrics

We present a Maple11+GRTensorII based symbolic calculator for instanton metrics using Newman-Penrose formalism. Gravitational instantons are exact solutions of Einstein's vacuum field equations with Euclidean signature. The Newman-Penrose formalism, which supplies a toolbox for studying the exact solutions of Einstein's field equations, was adopted to the instanton case and our code translates it for the computational use.Comment: 13 pages. Matches the published version. The web page of the codes is changed as https://github.com/tbirkandan/NPInstanto

Implementation of an intelligent control system

A laboratory testbed facility which was constructed at NASA LeRC for the development of an Intelligent Control System (ICS) for reusable rocket engines is described. The framework of the ICS consists of a hierarchy of various control and diagnostic functions. The traditional high speed, closed-loop controller resides at the lowest level of the ICS hierarchy. Above this level resides the diagnostic functions which identify engine faults. The ICS top level consists of the coordination function which manages the interaction between an expert system and a traditional control system. The purpose of the testbed is to demonstrate the feasibility of the OCS concept by implementing the ICS as the primary controller in a simulation of the Space Shuttle Main Engine (SSME). The functions of the ICS which are implemented in the testbed are as follows: an SSME dynamic simulation with selected fault mode models, a reconfigurable controller, a neural network for sensor validation, a model-based failure detection algorithm, a rule based failure detection algorithm, a diagnostic expert system, an intelligent coordinator, and a user interface which provides a graphical representation of the event occurring within the testbed. The diverse nature of the ICS has led to the development of a distributed architecture consisting of specialized hardware and software for the implementation of the various functions. This testbed is made up of five different computer systems. These individual computers are discussed along with the schemes used to implement the various ICS components. The communication between computers and the timing and synchronization between components are also addressed

Telematics for community portal development.

Community portals emanate from information and communication technology (ICT) applied to community networking, enabling citizens to access information and services on-line. These telematic portal systems are now deployed globally, facilitating information services to geographic and virtual communities. The context of this research study is one of community portals deployed by UK government local authorities for citizen service interactions. To date there have been few studies that holistically and longitudinally examine the subject of community portals. The 5 year research exercise has been undertaken as a qualitative study using an interpretivist approach and methodology derived > from context-process analysis. The approach was influenced by Mumford’s writings on ‘people and technology' and Schuler’s early work on community network development in the USA. Data collection was undertaken using a national survey questionnaire and qualitative techniques including interviews and mini-case studies. Findings of the research include a new categorisation of community portals into two distinctive types of Civic and Civil portal. Theoretical outcomes include an improved understanding of the methodological, technical, and social dimensions of portal development and deployment. The implications for management include an exposition of the issues involved in community portal development and the important need for citizen engagement in the process. A case study of Blackpool, (and mini case studies of five civic / civil portals), point to lack of collaboration between central and local government portal architects and developers

Integrated health monitoring and controls for rocket engines

Current research in intelligent control systems at the Lewis Research Center is described in the context of a functional framework. The framework is applicable to a variety of reusable space propulsion systems for existing and future launch vehicles. It provides a 'road map' technology development to enable enhanced engine performance with increased reliability, durability, and maintainability. The framework hierarchy consists of a mission coordination level, a propulsion system coordination level, and an engine control level. Each level is described in the context of the Space Shuttle Main Engine. The concept of integrating diagnostics with control is discussed within the context of the functional framework. A distributed real time simulation testbed is used to realize and evaluate the functionalities in closed loop

Implementation of a model based fault detection and diagnosis for actuation faults of the Space Shuttle main engine

In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the space shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the space shuttle main engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults

Including children with chronic health conditions in early childhood education and care settings

This article sheds light on how chronic health conditions impact upon concepts of inclusion in children’s early childhood education and care in England; it draws upon findings from a small-scale research project which highlights the need to consider health, in particular, the impact of chronic health conditions on early childhood education and care. The study was conducted in two stages: Stage 1 involved a postal questionnaire to 60 early childhood settings and Stage 2 included interviews with 6 practitioners in 4 settings, interviews with parents and observations of a child (called DJ) in his setting over the course of a year. The findings from this study indicate that in an attempt to be inclusive, practitioners may be unintentionally exclusive in their practice. The data suggest that this may be as a consequence of practitioners having different understandings and definitions of what is meant by the term inclusion, leading to confusion about the aims of inclusion. The findings indicate that there is a need to identify what effective pedagogy is for children with chronic health conditions, as well as a need to redefine inclusion in relation to their needs