Time-Domain Analysis of Sensor-to-Sensor Transmissibility Operators with Application to Fault Detection.

In some applications, multiple measurements are available, but the driving input that gives rise to those outputs may be unknown. This raises the question as to whether it is possible to model the response of a subset of sensors based on the response of the remaining sensors without knowledge of the driving input. To address this issue, we develop time-domain sensor-to-sensor models that account for nonzero initial conditions. The sensor-to-sensor model is in the form of a transmissibility operator, that is, a rational function of the differentiation operator. What is essential in defining the transmissibility operator is that it must be independent of both the initial condition and inputs of the underlying system, which is assumed to be time-invariant. The development is carried out for both single-input, single-output and multi-input, multi-output transmissibility operators. These time-domain sensor-to-sensor models can be used for diagnostics and output prediction. We show that transmissibility operators may be unstable, noncausal, and of unknown order. Therefore, to facilitate system identification, we consider a class of models that can approximate transmissibility operators with these properties. This class of models consists of noncausal finite impulse response models based on a truncated Laurent expansion. These models are shown to approximate the Laurent expansion inside the annulus between the asymptotically stable pole of largest modulus and the unstable pole of smallest modulus. By delaying the measured pseudo output relative to the measured pseudo input, the identified finite impulse response model is a noncausal approximation of the transmissibility operator. The causal (backward-shift) part of the Laurent expansion is asymptotically stable since all of its poles are zero, while the noncausal (forward-shift) part of the Laurent expansion captures the unstable and noncausal components of the transmissibility operator. This dissertation also develops a time-domain framework for both single-input, single-output and multi-input, multi-output transmissibilities that account for nonzero initial conditions for both force-driven and displacement-driven structures. We show that motion transmissibilities in force-driven and displacement-driven structures are equal when the locations of the forces and prescribed displacements are identical.PhDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113623/1/khaledfj_1.pd

Time-domain analysis of sensor-to-sensor transmissibility operators

a b s t r a c t In some applications, multiple measurements are available, but the driving input that gives rise to those outputs may be unknown. This raises the question as to whether it is possible to model the response of a subset of sensors based on the response of the remaining sensors without knowledge of the driving input. To address this issue, we develop time-domain sensor-to-sensor models that account for nonzero initial conditions. The sensor-to-sensor model is in the form of a transmissibility operator that is a rational function of the differentiation operator. The development is carried out for both SISO and MIMO transmissibility operators. These time-domain sensor-to-sensor models can be used for diagnostics and output prediction

The influence of whole-body vibration and postural support on activity interference in standing rail passengers

Travel time has generally been regarded as an unproductive period, representing a means-to-an-end in order to engage in activities at specific destinations. Rapid developments in mobile technology have provided people with innovative ways to multi-task and engage in meaningful activities while travelling. Rail transportation specifically, offers passengers advantages over other means of transportation as there is no need to focus on driving tasks. Due to the increase in passenger numbers and limited seating availability in train carriages, over one third of rail passengers are required to stand while travelling (DfT, 2013). The vibration to which rail passengers are exposed has been shown to interfere with the performance of activities and for standing passengers, it is often necessary to use postural supports such as holding on to grab rails or leaning on walls in order to maintain stability. The overall aim of the research is to evaluate the influence of whole-body vibration (WBV) exposure and standing posture on the performance of manual control tasks and the associated subjective workloads experienced by rail passengers. The use of supports, such as a backrest in seated postures, has been found to influence the response of the human body to WBV exposure, yet no reported studies have investigated the effects of postural supports on the response of the body in standing postures. Understanding how the body is affected in these conditions would increase the current state of knowledge on the biomechanical responses of the human body to vibration exposure and provide improved representation of standing postures within vibration standards (for example, ISO2631-4 (2001)) and guidelines for device interface design. A field study, using direct observation, was conducted to assess the behaviour of standing rail passengers and determine the characteristics of typical vibration exposures. This information provided the basis for the design of four subsequent laboratory studies. The main investigations of the laboratory studies were the influence of WBV exposure on objective performance measures, such as task completion time and error rate, and subjective workloads (for example, NASA TLX) for a range of manual control tasks. One of these laboratory studies evaluated the influence of various postural supports (for example, backrests) on the biomechanical responses of standing individuals. Measurements obtained during the field investigation indicated that the vibration exposures did not exceed the EU Physical Agents Exposure Action Value (EAV) and therefore posed little risk of injury. Vibration magnitudes in the horizontal directions (x- and y-axes) were higher than in the vertical direction (z-axis) and it was necessary for standing passengers to alter behaviours and use supports in order to maintain stability while travelling. The results of the laboratory studies indicated that in conditions where decrements in task performance occurred, the extent to which performance was degraded increased progressively with increases in vibration magnitude. There were conditions (for example, in the continuous control task and the Overhead Handle supported posture in the serial control task) where vibration exposure showed no significant influence on performance measures. This suggested that individuals were able to adapt and compensate for the added stress of vibration exposure in order to maintain performance levels however, this occurred at the expense of mental workload. The workload experienced by the participants increased with corresponding increases in magnitude. Vibration frequency-dependent effects in performance and workload were found to match the biomechanical responses (apparent mass and transmissibility) of the human body and resemble the frequency weightings described in the standards (ISO2631-1 (1997)). During the serial control task, the postures which demonstrated the greatest decrements to performance (for example, Lean Shoulder and Lean Back ) corresponded to the same postures that showed the greatest influence on the biomechanical responses of the body. It was concluded therefore, that measurements of the biomechanical responses to WBV could be used to offer predictions for the likelihood of activity interference. Consideration should however, be given to the applicability of this research before these results can be generalised to wider contexts. Further validation is recommended for future work to include different conditions in order to substantiate the findings of this research

Epidemic processes in complex networks

In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.Comment: 62 pages, 15 figures, final versio

Numerical reservoir characterization using dimensionless scale numbers with application in upscaling

Dimensionless space provides a tool for analyzing the behavior of complex systems described by mathematical relationships. The limited application of dimensionless variables in numerical reservoir simulation and experimental design motivated the development of a complete set of dimensionless scaling groups. Inspectional analysis yielded 8 dimensionless groups completely describing the flow system. Further analysis of fluid interaction reduced the number of dimensionless groups to 7. The newly developed dimensionless equations and groups were used for analytical and numerical reservoir characterization, quantifying the behavior of differential and difference equations employed in fluid flow in three-dimensional porous media. The behavior of the dimensionless scaling is demonstrated for breakthrough time in an immiscible displacement in three dimensions. Numerical simulations were designed in dimensionless space and converted to dimensional space using several approaches. The resulting estimates of stability limits, numerical dispersion, and regime boundaries were in excellent agreement. The application of the dimensionless groups to upscaling was investigated using designed reservoir simulations to estimate dimensionless regions corresponding to different flow regimes. Analytical development, simulation runs and literature data were in good agreement. This application demonstrates the potential benefits of the proposed dimensionless groups for upscaling, sensitivity analysis, stability analysis, and reservoir characterization

Aeronautical engineering: A continuing bibliography with indexes (supplement 268)

This bibliography lists 406 reports, articles, and other documents introduced into the NASA scientific and technical information system in July, 1991. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

A unified metaheuristic and system-theoretic framework for petroleum reservoir management

With phenomenal rise in world population as well as robust economic growth in China, India and other emerging economies; the global demand for energy continues to grow in monumental proportions. Owing to its wide end-use capabilities, petroleum is without doubt, the world’s number one energy resource. The present demand for oil and credible future forecasts – which point to the fact that the demand is expected to increase in the coming decades – make it imperative that the E&P industry must device means to improve the present low recovery factor of hydrocarbon reservoirs. Efficiently tailored model-based optimization, estimation and control techniques within the ambit of a closed-loop reservoir management framework can play a significant role in achieving this objective. In this thesis, some fundamental reservoir engineering problems such as field development planning, production scheduling and control are formulated into different optimization problems. In this regard, field development optimization identifies the well placements that best maximizes hydrocarbon recovery, while production optimization identifies reservoir well-settings that maximizes total oil recovery or asset value, and finally, the implementation of a predictive controller algorithm which computes corrected well controls that minimizes the difference between actual outputs and simulated (or optimal) reference trajectory. We employ either deterministic or metaheuristic optimization algorithms, such that the choice of algorithm is purely based on the peculiarity of the underlying optimization problem. Altogether, we present a unified metaheuristic and system-theoretic framework for petroleum reservoir management. The proposed framework is essentially a closed-loop reservoir management approach with four key elements, namely: a new metaheuristic technique for field development optimization, a gradient-based adjoint formulation for well rates control, an effective predictive control strategy for tracking the gradient-based optimal production trajectory and an efficient model-updating (or history matching) – where well production data are used to systematically recalibrate reservoir model parameters in order to minimize the mismatch between actual and simulated measurements. Central to all of these problems is the use of white-box reservoir models which are employed in the well placement optimization and production settings optimization. However, a simple data-driven black-box model which results from the linearization of an identified nonlinear model is employed in the predictive controller algorithm. The benefits and efficiency of the approach in our work is demonstrated through the maximization of the NPV of waterflooded reservoir models that are subject to production and geological uncertainty. Our procedure provides an improvement in the NPV, and importantly, the predictive control algorithm ensures that this improved NPV are attainable as nearly as possible in practice