Flow patterns in upward two-phase flow in small diameter tubes

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 22/11/2006.Two-phase flow in small tubes and channels is becoming a common phenomenon in industrial processes. However, the study of two-phase flow regimes in small tubes is still at its infancy. The previous studies are reviewed and discussed in the literature section. The problems and inconsistencies encountered in the earlier studies are presented and discussed. The experimental facility is introduced in the chapters that follow. They include a section on the design of the experimental system and the test sections, the selection of the experimental parameters and the introduction of the purposely-developed programs to control the experiments and collect and process the data. The methodology of the calibration and the uncertainty analysis, the problems encountered and their solutions and the single-phase validation experiments are also described. In this project we studied the effect of tube diameter and fluid flow parameters on flow patterns in small tubes using R134a as the working fluid. The tested tube diameters were 1.10, 2.01, 2.88 and 4.26 mm; the fluid pressures were 6, 10 and 14 bar; the liquid and gas superficial velocities covered a range of 0.04-5.0 m/s and 0.01-10.0 m/s respectively. The observed flow patterns included bubbly, dispersed bubble, confined bubble, slug, chum, annular and mist flow. Twelve integrated flow maps are sketched in this report. The obtained results were compared with earlier experiments by other workers and with existing models, with obvious differences in the prediction of the transition boundaries. A set of new models and correlations were developed, based on the new data for boiling R134a presented in this thesis, to predict the effect of tube diameter and fluid properties on the transition boundaries. Some also agreed with the limited data available from earlier studies for adiabatic air-water flow in small to normal size tubes.London South Bank Universit

Transient identification and interpretation of real-time pressure data from modern well surveillance systems

Permanent downhole gauges (PDG) that are installed in modern wells are capable of recording pressure and temperature data during well operations. These data in combination with flow rate measurements may be utilized for Pressure Transient Analysis (PTA) or its time-lapse version - time-lapse PTA. Unlike traditional PTA which would mainly interpret data from shut-in periods, time-lapse PTA is applied to sequential pressure transients and both flowing and shut-in periods to evaluate well-reservoir parameters that may vary with time. A PTA workflow may be divided into several steps. In this study, we mainly focus on the step of transient identification based on pressure measurements, which is crucial for time-lapse PTA and keeps being a challenge especially when the data are very noisy. Another step - denoising is also carried out and discussed in the part of computational experiments. Previous work in the area of the transient identification has been studied before developing and testing of own algorithms to address this problem. Seven approaches have been reviewed, compared and summarized in the thesis. In this master thesis, the transient identification problem is considered as a two-stage process consisting of two identification tasks: 1) splitting the data set into shut-in and flowing periods; 2) task 1 + detecting multi-rate break points in flowing periods. Three methods based on pressure derivative, tangent of pressure data and pattern recognition were proposed and studied and a workflow to implement these methods was designed. Through a number of computational experiments, the derivative-based method provided the best result for the task 1, while tangent-based method - best results for the task 2. In the comparison section, we discussed the results of testing of these methods taking an insight into performance of the break-point detection in the different tasks. The thesis is finalized by establishing an easy-to-use web application, where the users could experiment with different methods using own data sets. The web app provides a friendly user interface to upload and test different data sets and download results of the break-point detection

Flight Data Validation of an Icing Accretion Estimation Scheme using Super-twisting Observers

This paper develops a generalised multivariable super-twisting observer for a class of nonlinear systems in which the unmeasured variables linked to the known state dependent matrix function appear multiplicatively. A sufficient condition is given to guarantee that the reconstruction errors associated with the unmeasurable variables converge to zero in finite time. This approach is then used to address the aircraft icing accretion estimation problem despite unreliable sensor measurement. The efficacy of the approach has been evaluated via real flight data recorded under natural icing conditions. Results show that the observer has the capability to estimate the change of the drag coefficient induced by icing accretion and to reconstruct the unreliable pitch rate sensor measurement simultaneously

Application of model-based LPV actuator fault estimation for an industrial benchmark

To bridge the gap between model-based fault diagnosis theory and the industry practice, a linear parameter varying H_/H∞ fault estimation approach is applied to a high fidelity nonlinear aircraft benchmark, to deal with the various actuator fault detection scenarios which can result in the abnormal aircraft configuration. To facilitate the industry calculating the computational load of the fault estimation approach, the design is fully coded using the flight control computer software library. Furthermore, the robustness performance of the fault estimation approach is evaluated using the parametric simulation and the Monte Carlo campaign supported by a functioning engineering simulator despite the aerodynamic database uncertainties and measurements errors over a wide range of the flight envelope

Wind Preview-Based Model Predictive Control of Multi-Rotor UAVs Using LiDAR

Autonomous outdoor operations of Unmanned Aerial Vehicles (UAVs), such as quadrotors, expose the aircraft to wind gusts causing a significant reduction in their position-holding performance. This vulnerability becomes more critical during the automated docking of these vehicles to outdoor charging stations. Utilising real-time wind preview information for the gust rejection control of UAVs has become more feasible due to the advancement of remote wind sensing technology such as LiDAR. This work proposes the use of a wind-preview-based Model Predictive Controller (MPC) to utilise remote wind measurements from a LiDAR for disturbance rejection. Here a ground-based LiDAR unit is used to predict the incoming wind disturbance at the takeoff and landing site of an autonomous quadrotor UAV. This preview information is then utilised by an MPC to provide the optimal compensation over the defined horizon. Simulations were conducted with LiDAR data gathered from field tests to verify the efficacy of the proposed system and to test the robustness of the wind-preview-based control. The results show a favourable improvement in the aircraft response to wind gusts with the addition of wind preview to the MPC; An 80% improvement in its position-holding performance combined with reduced rotational rates and peak rotational angles signifying a less aggressive approach to increased performance when compared with only feedback based MPC disturbance rejection. System robustness tests demonstrated a 1.75 s or 120% margin in the gust preview’s timing or strength respectively before adverse performance impact. The addition of wind-preview to an MPC has been shown to increase the gust rejection of UAVs over standard feedback-based MPC thus enabling their precision landing onto docking stations in the presence of wind gusts

Flight data validation of an icing accretion estimation scheme using super-twisting observers

This paper develops a generalised multivariable super-twisting observer for a class of nonlinear systems in which the unmeasured variables linked to the known state dependent matrix function appear multiplicatively. A sufficient condition is given to guarantee that the reconstruction errors associated with the unmeasurable variables converge to zero in finite time. This approach is then used to address the aircraft icing accretion estimation problem despite unreliable sensor measurement. The efficacy of the approach has been evaluated via real flight data recorded under natural icing conditions. Results show that the observer has the capability to estimate the change of the drag coefficient induced by icing accretion and to reconstruct the unreliable pitch rate sensor measurement simultaneously

Sliding mode observers for a class of LPV systems

In this paper, a new framework for the synthesis of a class of sliding mode observers for affine linear parameter varying (LPV) systems is proposed. The sliding mode observer is synthesized by selecting the design freedom via LMIs. Posing the problem from a small gain perspective allows existing numerical techniques from the literature to be used for the purpose of synthesizing the observer gains. In particular, the framework allows affine parameterdependent Lyapunov functions to be considered for analyzing the stability of the state estimation error dynamics, to help reduce design conservatism. Initially a variable structure observer formulation is proposed, but by imposing further constraints on the LMIs, a stable sliding mode is introduced, which can force and maintain the output estimation error to be zero in finite time. The efficacy of the scheme is demonstrated using an LPV model of the short period dynamics of an aircraft and demonstrates simultaneous asymptotic estimation of the states and disturbances

Multistage Output-lifting Eigenstructure Assignment: A Multirate Ball and Plate Example

By exploiting both the left and the right allowable subspaces in consecutive stages, this paper extends a recently-developed output-lifting eigenstructure assignment approach into a multistage eigenstructure assignment scheme. In this scheme, design degrees of freedom, enlarged via output-lifting, are further exploited to improve eigenvector assignment. To mitigate the inherent conflicts between the theoretical development of eigenstructure assignment and inherent physical system characteristics, the paper also clearly demonstrates how to derive an ideal eigenstructure, particularly the desired eigenvectors, to distribute and decouple the natural modes among appropriate states or outputs, based upon an example: a novel multirate Ball and Plate system. The design and simulation results show the efficacy of the scheme

Flow patterns in upward two-phase flow in small diameter tubes

Two-phase flow in small tubes and channels is becoming a common phenomenon in industrial processes. However, the study of two-phase flow regimes in small tubes is still at its infancy. The previous studies are reviewed and discussed in the literature section. The problems and inconsistencies encountered in the earlier studies are presented and discussed. The experimental facility is introduced in the chapters that follow. They include a section on the design of the experimental system and the test sections, the selection of the experimental parameters and the introduction of the purposely-developed programs to control the experiments and collect and process the data. The methodology of the calibration and the uncertainty analysis, the problems encountered and their solutions and the single-phase validation experiments are also described. In this project we studied the effect of tube diameter and fluid flow parameters on flow patterns in small tubes using R134a as the working fluid. The tested tube diameters were 1.10, 2.01, 2.88 and 4.26 mm; the fluid pressures were 6, 10 and 14 bar; the liquid and gas superficial velocities covered a range of 0.04-5.0 m/s and 0.01-10.0 m/s respectively. The observed flow patterns included bubbly, dispersed bubble, confined bubble, slug, chum, annular and mist flow. Twelve integrated flow maps are sketched in this report. The obtained results were compared with earlier experiments by other workers and with existing models, with obvious differences in the prediction of the transition boundaries. A set of new models and correlations were developed, based on the new data for boiling R134a presented in this thesis, to predict the effect of tube diameter and fluid properties on the transition boundaries. Some also agreed with the limited data available from earlier studies for adiabatic air-water flow in small to normal size tubes.EThOS - Electronic Theses Online ServiceLondon South Bank UniversityGBUnited Kingdo

Flight evaluation of an LPV sliding mode observer for sensor FTC

This brief develops a sliding mode sensor fault-tolerant control scheme for a class of linear parameter varying (LPV) systems. It incorporates a sliding mode observer that reconstructs the unknown sensor faults based on only the system inputs and outputs. The reconstructed sensor faults are used to compensate for the corrupted sensor measurements before they are used in the feedback controller. Provided accurate fault estimates can be computed; near nominal control performance can be retained without any controller reconfiguration. Furthermore, the closed-loop stability of the fault-tolerant control (FTC) scheme, involving both a sliding mode controller and a sliding mode observer, is rigorously analyzed. The proposed scheme is validated using the Japan Aerospace Exploration Agency's Multipurpose Aviation Laboratory (MuPAL-α) research aircraft. These flight tests represent the first validation tests of a sliding mode sensor FTC scheme on a full-scale aircraft