Effect of water current on underwater glider velocity and range

An autonomous underwater glider speed and range is influenced by water currents. This is compounded by a weak actuation system for controlling its movement. In this work, the effects of water currents on the speed and range of an underwater glider at steady state glide conditions are investigated. Extensive numerical simulations have been performed to determine the speed and range of a glider with and without water current at different net buoyancies. The results show that the effect of water current on the glider speed and range depends on the current relative motion and direction. In the presence of water current, for a given glide angle, glide speed can be increased by increasing the net buoyancy of the glider

A review on the Application of Empirical Models to Hydrate Formation Prediction

In deepwater hydrocarbon transportation pipeline, the production may decrease and operational cost and time are increasing due to the growth rate of hydrate. The pressure of deepwater pipeline is comparatively high, so it is entirely possible to form the hydrate formation conditions and pose a major operational and safety challenge. This work provides a review on empirical models for hydrate formation prediction in deepwater gas pipeline. The correlation and empirical models are presented with the hydrate formation temperature described as a function of pressure and gas gravity. This study could possibly provide a milestone for predicting PVT and heat transfer effects on hydrate formation in deepwater pipeline

Adaptive Teleoperation System with Neural Network-Based Multiple Model Control

This paper presents an adaptive teleoperation which is robust to time-delay and environmental uncertainties while assuring the transparent performance. A novel theoretical framework and algorithms for the teleoperation system have been built up with neural network-based multiple model control and time forward state observer. Conditions for stability and transparency performance are also identified. Simulations show that the system is stable and in good performance

A functional approach to redesign

This paper describes a methodology to assist in the identification of possible conceptual design variants during redesign. The approach is based on functional reasoning and involves: (1) the structural and functional analysis of an existing design; (2) the production of abstract representations of functions and design entities using conceptual graphs; and (3) design interrogation based on a functional tree approach. The research reported in this paper also focuses on the definition and the representation of elementary mechanical functions. Extended Backus-Naur Form (EBNF) notations are used to structure in a computable form, the relevant information (or design knowledge) conceptualised in either the conceptual graphs or the functional trees. EBNF syntax is also used to formulate rules which aid the partial automation of the reasoning process. The EBNF notations can be mapped to any programming language. A diaphragm valve is used as a case study to demonstrate the approach

Failure Mode and Effect Analysis of Subsea Multiphase Pump Equipment

Finding oil and gas reserves in deep/harsh environment with challenging reservoir and field conditions, subsea multiphase pumping benefits has found its way to provide solutions to these issues. Challenges such as failure issues that are still surging the industry and with the current practice of information hiding, this issues becomes even more difficult to tackle. Although, there are some joint industry projects which are only accessible to its members, still there is a need to have a clear understanding of these equipment groups so as to know which issues to focus attention on. A failure mode and effect analysis (FMEA) is a potential first aid in understanding this equipment groups. A survey questionnaire/interview was conducted with the oil and gas operating company and equipment manufacturer based on the literature review. The results indicates that these equipment’s group are similar with its onshore counterpart, but the difference is the robustness built into the equipment internal subsystems for subsea applications. The results from the manufacturer perspectives indicates that Helico-axial multiphase pump have a mean time to failure of more than 10 years, twin-screw and electrical submersible pumps are still struggling with a mean time to failure of less than 5 years

Theoretical background and the flow fields in downhole liquid-liquid hydrocyclone (LLHC)

Hydrocyclone system for downhole oil-water separation provides an effective technique of enhancing the economic viability of higher water-cut wells while at the same time reducing the risk of environmental pollution. This paper describes the hydrodynamics of the liquid-liquid hydrocyclones and the flow fields within it are paramount for achieving successful separation process. Some of the important hydrodynamic flow phenomenon within the liquid-liquid hydrocyclone and how they influence the separation efficiency of water/oil was analyzed through analytical solution. The properties of the liquids were based on Bayan offshore field measured properties. The results indicated that there are two swirling zones separated by stagnant flow field. The inner is the light liquid zone, while the outer is the heavy liquid zone

Development of ANN Model for the Prediction of VIV Fatigue Damage of Top-tensioned Riser

Marine riser experiences vortex-induced vibration (VIV) caused by current, leading to fatigue damage if VIV is not considered in design of riser. Estimation of VIV fatigue damage is essential in designing feasible and operable riser. A simplified approach for predicting fatigue damage is required to reduce the computation time to analyze the fatigue damage. This study aims to explore the applicability of artificial neural network (ANN) approach in developing top-tensioned riser fatigue damage prediction model. A total of 2100 riser model is generated with different combination of four main input parameters: riser outer diameter, wall thickness, top tension and uniform current velocity. The modal analysis is performed using OrcaFlex and VIV fatigue damage of the riser is computed using SHEAR7. The four input parameters and corresponding fatigue damage results make up the database for training a 2-layer neural network. Weight and bias values acquired from the training of ANN are used to develop the VIV fatigue damage prediction model of the riser. The results show ANN approach is suitable for prediction of the riser fatigue damage due to VIV. The proposed approach requires further refinements and extension to more input features to improve the accuracy and usefulness of the developed prediction model