Fault detecting experiments for sequential circuits.
Experiment design to determine if sequential switching is operating according to state table description
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Experiment design to determine if sequential switching is operating according to state table description
Modern distributed hybrid and electric propulsion aircraft, including vertical, short, and conventional takeoff and landing configurations, exhibit significant aero-propulsive complexity and a large number of interacting test factors. This paper presents the development and evaluation of experiment designs for aero-propulsive characterization of distributed propulsion aircraft. Five different foundational response surface designs are evaluated to inform the development of two sequential design approaches tailored to complex aircraft aerodynamic characterization experiments. The first approach, which builds on sequential face-centered central composite designs, has been used previously to develop aero-propulsive models for complex aircraft using wind tunnel testing. The second approach is a new design strategy leveraging a regular I-optimal and nested I-optimal design that was developed for this study. The two sequential design strategies are compared for experiments with a large number of test factors using pre-experiment design evaluation metrics, as well as modeling results obtained from simulated wind tunnel data for the NASA LA-8 aircraft. The design evaluation metrics show that the sequential I-optimal base design has higher statistical power, lower correlation among candidate regressors, lower prediction variance, and more precise parameter estimates. The simulated wind tunnel experiments conducted using each design reveal that the sequential I-optimal base design has better predictive capability with fewer test points. The experiment design and evaluation procedures are described in detail to inform future aerodynamic characterization experiments for complex aircraft.
Current inventory management techniques for consumables and supplies aboard space vehicles are burdensome and time consuming. Inventory of food, clothing, and supplies are taken periodically by manually scanning the barcodes on each item. The inaccuracy of reading barcodes and the excessive amount of time it takes for the astronauts to perform this function would be better spent doing scientific experiments. Therefore, there is a need for an alternative method of inventory control by NASA astronauts. Radio Frequency Identification (RFID) is an automatic data capture technology that has potential to create a more effective and user-friendly inventory management system (IMS). In this paper we introduce a Design for Six Sigma Research (DFSS-R) methodology that allows for reliability testing of RFID systems. The research methodology uses a modified sequential design of experiments process to test and evaluate the quality of commercially available RFID technology. The results from the experimentation are compared to the requirements provided by NASA to evaluate the feasibility of using passive Generation 2 RFID technology to improve inventory control aboard crew exploration vehicles.
Comparsion of two approaches to problem of sequential design of experiments
A sequential adaptive experimental design procedure for a related problem is studied. It is assumed that a finite set of potential linear models relating certain controlled variables to an observed variable is postulated, and that exactly one of these models is correct. The problem is to sequentially design most informative experiments so that the correct model equation can be determined with as little experimentation as possible. Discussion includes: structure of the linear models; prerequisite distribution theory; entropy functions and the Kullback-Leibler information function; the sequential decision procedure; and computer simulation results. An example of application is given.
Tables are given for the numbers of center points to be used with blocked sequential designs of composite response surface experiments as used in empirical optimum seeking. The star point radii for exact orthogonal blocking is presented. The center point options varied from a lower limit of one to an upper limit equal to the numbers proposed by Box and Hunter for approximate rotatability and uniform variance, and exact orthogonal blocking. Some operating characteristics of the proposed options are described.
Tables are given for the numbers of center points to be used with blocked sequential designs of composite response surface experiments as used in empirical optimum seeking. The tables also give the star point radii for exact orthogonal blocking. The center point options vary from a lower limit of one to an upper limit equal to the numbers proposed by Box and Hunter for approximate rotatability and uniform variance, and exact orthogonal blocking. Some operating characteristics of the proposed options are described.
Rapid modeling and efficient testing methods are important in a number of aerospace applications. In this study efficient testing strategies were evaluated in a wind tunnel test environment and combined to suggest a promising approach for both ground-based and flight-based experiments. Benefits of using Design of Experiment techniques, well established in scientific, military, and manufacturing applications are evaluated in combination with newly developing methods for global nonlinear modeling. The nonlinear modeling methods, referred to as Learn-to-Fly methods, utilize fuzzy logic and multivariate orthogonal function techniques that have been successfully demonstrated in flight test. The blended approach presented has a focus on experiment design and identifies a sequential testing process with clearly defined completion metrics that produce increased testing efficiency.
Validating a concept of operation for a complex, safety-critical system (like the National Airspace System) is challenging because of the high dimensionality of the controllable parameters and the infinite number of states of the system. In this paper, we use statistical modeling techniques to explore the behavior of a conflict detection and resolution algorithm designed for the terminal airspace. These techniques predict the robustness of the system simulation to both nominal and off-nominal behaviors within the overall airspace. They also can be used to evaluate the output of the simulation against recorded airspace data. Additionally, the techniques carry with them a mathematical value of the worth of each prediction-a statistical uncertainty for any robustness estimate. Uncertainty Quantification (UQ) is the process of quantitative characterization and ultimately a reduction of uncertainties in complex systems. UQ is important for understanding the influence of uncertainties on the behavior of a system and therefore is valuable for design, analysis, and verification and validation. In this paper, we apply advanced statistical modeling methodologies and techniques on an advanced air traffic management system, namely the Terminal Tactical Separation Assured Flight Environment (T-TSAFE). We show initial results for a parameter analysis and safety boundary (envelope) detection in the high-dimensional parameter space. For our boundary analysis, we developed a new sequential approach based upon the design of computer experiments, allowing us to incorporate knowledge from domain experts into our modeling and to determine the most likely boundary shapes and its parameters. We carried out the analysis on system parameters and describe an initial approach that will allow us to include time-series inputs, such as the radar track data, into the analysis
A description is given of the FIFE (First ISLSCP Field Experiment) information system, which was developed to serve FIFE investigators as a tool for designing the experiment and for organizing and manipulating the complex data set. Fulfilling these functions on an experiment-driven timeline led to abandoning the classical sequential development paradigm of software engineering in favor of a more responsive and broadly based approach. The design, development, and operation of the information system supporting the experiment had to be flexible and under direct day-to-day control of scientist/users. Because of the organization around scientific requirements, the system was able to incorporate diverse data types in a systematic way as they became available, to add scientific rigor by identifying data gaps at an early stage, and to provide real-time quality assurance. These factors are important for designing and building future databases and long-term information systems to support interdisciplinary scientific research.
This paper deals with an analysis of psychophysical detection experiments designed to assess the limit of a human observer's level of sensitivity. A mathematical theory or the detection process is introduced that, in contrast to previous theories, provides an analysis of the sequential effects observed in psychophysical data. Two variations of the detection task are considered: information feedback and no-information feedback. In the feedback situation the subject is given information concerning the correctness of his responses, whereas in the no-feedback situation he is not. Data from a visual detection experiment with no-information feedback, and from an auditory detection experiment with information feedback are analyzed in terms of the theory. Finally, some general results are derived concerning the relationship between performance in the feedback situation and the no-feedback situation.
Computer simulation experiments design for industrial systems, considering variance techniques, multiple ranking procedures, sequential sampling and spectral analysis
This articles considers computer experiments where levels for continuous factors are selected in sequential order with the level selected for one factor directly a ecting the range of possible levels for the nested factor, and so on for a nite number of factors. In addition, we assume the nested relationships between the factors have no closed form solution. In this paper, we propose an approach for constructing a multi-layer nested factor design, or multi-NFD for short. This space- lling design approach takes advan- tage of the maximin criterion and can be analyzed using a standard Gaussian process model. While the multi-NFD approach can be adapted for future computer experi- ments involving factor relationships of this type, we present results from a particular aerospace computer simulation study.
NASA is working to develop an integrated set of advanced technologies to enable efficient arrival operations in high-density terminal airspace for the Next Generation Air Transportation System. This integrated arrival solution is being validated and verified in laboratories and transitioned to a field prototype for an operational demonstration at a major U.S. airport. Within NASA, this is a collaborative effort between Ames and Langley Research Centers involving a multi-year iterative experimentation process. Designing and analyzing a series of sequential batch computer simulations and human-in-the-loop experiments across multiple facilities and simulation environments involves a number of statistical challenges. Experiments conducted in separate laboratories typically have different limitations and constraints, and can take different approaches with respect to the fundamental principles of statistical design of experiments. This often makes it difficult to compare results from multiple experiments and incorporate findings into the next experiment in the series. A statistical engineering approach is being employed within this project to support risk-informed decision making and maximize the knowledge gained within the available resources. This presentation describes a statistical engineering case study from NASA, highlights statistical challenges, and discusses areas where existing statistical methodology is adapted and extended.
The Critical Point Facility (CPF) is an ESA multiuser facility designed for microgravity research onboard Spacelab. It has been conceived and built to offer investigators opportunities to conduct research on critical point phenomena in microgravity. This facility provides the high precision and stability temperature standards required in this field of research. It has been primarily designed for the purpose of optical investigations of transparent fluids. During a Spacelab mission, the CPF automatically processes several thermostats sequentially, each thermostat corresponding to an experiment. The CPF is now integrated in Spacelab at Kennedy Space Center, in preparation for the International Microgravity Lab. mission. The CPF was designed to submit transparent fluids to an adequate, user defined thermal scenario, and to monitor their behavior by using thermal and optical means. Because they are strongly affected by gravity, a good understanding of critical phenomena in fluids can only be gained in low gravity conditions. Fluids at the critical point become compressed under their own weight. The role played by gravity in the formation of interfaces between distinct phases is not clearly understood.
The design and rationale of an advanced labeled release experiment based on single addition of soil and multiple sequential additions of media into each of four test chambers are outlined. The feasibility for multiple addition tests was established and various details of the methodology were studied. The four chamber battery of tests include: (1) determination of the effect of various atmospheric gases and selection of that gas which produces an optimum response; (2) determination of the effect of incubation temperature and selection of the optimum temperature for performing Martian biochemical tests; (3) sterile soil is dosed with a battery of C-14 labeled substrates and subjected to experimental temperature range; and (4) determination of the possible inhibitory effects of water on Martian organisms is performed initially by dosing with 0.01 ml and 0.5 ml of medium, respectively. A series of specifically labeled substrates are then added to obtain patterns in metabolic 14CO2 (C-14)O2 evolution.
The general problem studied is that of segmenting or partitioning programs for distribution across a multiprocessor system. Efficient partitioning and the assignment of program elements are of great importance since the time consumed in this overhead activity may easily dominate the computation, effectively eliminating any gains made by the use of the parallelism. In this study, the partitioning of sequentially structured programs (written in FORTRAN) is evaluated. Heuristics, developed for similar applications are examined. Finally, a model for queueing networks with finite queues is developed which may be used to analyze multiprocessor system architectures with a shared memory approach to the problem of partitioning. The properties of sequentially written programs form obstacles to large scale (at the procedure or subroutine level) parallelization. Data dependencies of even the minutest nature, reflecting the sequential development of the program, severely limit parallelism. The design of heuristic algorithms is tied to the experience gained in the parallel splitting. Parallelism obtained through the physical separation of data has seen some success, especially at the data element level. Data parallelism on a grander scale requires models that accurately reflect the effects of blocking caused by finite queues. A model for the approximation of the performance of finite queueing networks is developed. This model makes use of the decomposition approach combined with the efficiency of product form solutions.
The experiments described in this paper are part of a larger joint MIT/NASA research effort and focus on the development of a methodology for designing and evaluating integrated interfaces for highly dexterous and multifunctional telerobot. Specifically, a telerobotic workstation is being designed for an Extravehicular Activity (EVA) anthropomorphic space station telerobot called Robonaut. Previous researchers have designed telerobotic workstations based upon performance of discrete subsets of tasks (for example, peg-in-hole, tracking, etc.) without regard for transitions that operators go through between tasks performed sequentially in the context of larger integrated tasks. The experiments presented here took an integrated approach to describing teleoperator performance and assessed how subjects operating a full-immersion telerobot perform during fine position and gross position tasks. In addition, a Robonaut simulation was also developed as part of this research effort, and experimentally tested against Robonaut itself to determine its utility. Results show that subject performance of teleoperated tasks using both Robonaut and the simulation are virtually identical, with no significant difference between the two. These results indicate that the simulation can be utilized as both a Robonaut training tool, and as a powerful design platform for telepresence displays and aids.