Fakhruldin Mohd Hashim

Use of fuzzy systems and bat algorithm for exergy modeling in a gas turbine generator

Exergy analysis plays a major role in thermal systems. Using exergy, apart from finding components for further improvement, fault detection and diagnosis can be conducted. This paper demonstrates the use of fuzzy systems for capturing exergy destruction variations in the main components of an industrial gas turbine. The models cover part load operating conditions. The fuzzy models are trained applying locally linear model tree algorithm followed by a meta-heuristic nature inspired algorithm called bat algorithm. The data for model training and validation are generated using semi-empirical models developed by the authors. However, the inputs to the model are kept the same as the inputs as experienced by a real gas turbine generator. The comparison between actual data from a different day and the prediction by the proposed method showed a match that is close enough to be considered as reliable. The models could be used for performance optimization and condition monitoring.

Analysis of Journal Bearing with Double-Layer Porous Lubricant Film: Influence of Surface Porous Layer Configuration

This article presents an analysis of a long journal bearing with a double-layer porous lubricant film using couple stress and Newtonian fluids. The porous layer with infinite permeability analyzed in this study simulates the surface layer. The Brinkman model was utilized to model the flow in the porous region. The effects of couple stresses were analyzed based on Stokes microcontinuum theory. A double-layer porous lubricant film configuration, with a low-permeability porous layer on top of a high-permeability bearing adherent porous layer, improved the journal bearing performance characteristics. A surface porous layered lubricant film configuration increased the load-carrying capacity and reduced the coefficient of friction in a journal bearing.

Wavelet analysis and auto-associative neural network based fault detection and diagnosis in an industrial gas turbine

This work presents a Fault Detection and Diagnosis (FDD) system that uses a combination of discrete wavelet transform and auto-associative neural network. The neural network is trained by Levenberg-Marquardt (LM) algorithm. As a case study, it considers a 5.2MW Siemens Taurus 60S industrial gas turbine. The work is unique in the sense that it addresses the signals in the gas path, generator coils, lubrication system, and vibration sensors. Real data are used to train and corroborate the models. In order to test validity of the FDD system, we used abrupt and incipient faults generated by implanting controlled bias to the normal signals. Results show that the proposed method could detect a 10% bias with an average true detection higher than 95% while the diagnoses performance is in the range of 96 to 100%. Since it is designed and tested based on real data, it can be considered competent for practical use.

A framework for function‐based conceptual design support system

Purpose – The purpose of this paper is to describe the framework of conceptual design support tool (CDST) developed to assist designers during conceptual design process. The premise of the study is that, by combining human creativity with computer capabilities, it is possible to perform conceptual design process more efficiently than solely manual design. The study aims to show how conceptual design knowledge can be captured from experienced designers and kept in the computer system for later use and how the developed tool assists designers by handling some of the repetitive and time‐consuming tasks.Design/methodology/approach – A conceptual design process model, which integrates systematic design approach with knowledge‐based system, is proposed. Based on this model, a CDST, which consists of function library, alternative concepts database, different modules for conceptual design activities, and a knowledge‐based system is developed. The alternative concepts database is built based on design reuse philos...

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.

Numerical investigation of gas separation in T-junction

T-junctions are commonly used in distributing two-phase flow by piping networks especially in oil and gas industries. Understanding the behavior of two-phase flow through a T-junction is very important as it has significant effect on the operation, maintenance and efficiency of the components downstream from the junction. The objective of this paper is to determine the effect of ratio of side arm to main arm diameters, initial inlet gas saturation and gas density variation on passive separation performance in T-junction. Via computational fluid dynamics tool, preliminary investigation found that separation efficiency is proportional to diameter ratio in between 0.5-0.75. Beyond diameter ratio 0.75, there is a flattening of separation efficiency. The change of fraction of gas taken off is inversely proportional to initial inlet gas saturation and the trend is almost inversely linear for diameter ratio 0.5. Beyond that, the relationship between initial inlet gas saturation and separation efficiency exhibits...

A prediction model for the natural gas hydrate formation pressure into transmission line

ABSTRACT Gas hydrate is a major challenge in deepwater hydrocarbon transmission lines. It can lead to safety hazards in production and flow assurance in the transportation system of hydrocarbons. The authors propose a mathematical prediction model for hydrate formation pressure conditions based on exponential function and intelligent optimization. The intelligent optimization approach namely genetic algorithm (GA), particle swarm optimization (PSO) and grey wolf optimizer (GWO) were used to search the best value of coefficients that give a minimum error in prediction of pressure conditions during hydrate formation in the deepwater pipeline. The proposed approach was tested on the four experimental data of with and without inhibitor and nitrogen in the mixture of gases. The proposed approach of hydrate formation pressure conditions prediction model will be helpful in finding hydrate formation pressure in deepwater methane gas pipeline.

Maintainability analysis of an offshore gas compression train system, a case study

Purpose – This paper aims to propose a practical method of performing maintainability analysis of an offshore system at operation phase having some improvement trend.Design/methodology/approach – The analysis follows a systematically developed method of analyzing maintenance data, identifying critical factors affecting system performance, and developing suitable downtime distribution model with some applications of statistical analysis techniques and expert opinion.Findings – Improvement in spare part logistics is found significant in reducing downtime thus should be well feedback to design and plant engineers so that it can be incorporated in new offshore system. The downtime models developed based on the steady state analysis and expert input are found to be practical for prediction of the system maintainability performance.Research limitations/implications – The analysis focuses on the downtime which includes the repair, logistics and administrative delay time. At the operation phase, plant personnel a...

A Knowledge-Based Conceptual Design Support System

Conceptual design process is considered as the most critical and important phase of product design process. It is the stage where product’s fundamental features are determined, large proportion of the lifecycle cost of the product is committed, and other major decisions are made, which have significant impact on the downstream design and related manufacturing processes. It is also a knowledge intensive process where diverse knowledge and several years of experience are put together to design quality and cost effective products. Unfortunately, computer support systems for this phase are lagging behind compared to the currently available commercial computer aided design (CAD) tools for the later stage of design. This paper proposes a knowledge-based conceptual design support system in which design concepts from existing products and previous experiences are captured and used to design future products. The conceptual design support system will assist designers during the conceptual design process by generating concepts on a morphology chart and handling some of the repetitive tasks. In addition, the generated concepts may inspire designers to generate new concepts. The design support system addresses the key features of conceptual design process such as functional analysis, concept generation and concept evaluation with aid of the production rules within the knowledge-based system.

Stability evaluation of three-layered journal bearing with slip/partial slip

Purpose This paper aims to present stability of a three-layered journal bearing considering magnitude of the layers’ thicknesses and viscosities with slip/partial slip on the bearing surface. Design/methodology/approach Modified Reynolds equation based on one-dimensional analysis is derived for a three-layered journal bearing with slip/partial slip. Dynamic coefficients are derived based on infinitesimal perturbation method. Linearized stability analysis is presented taking into account slip/partial slip on bearing surface; thicknesses and viscosities of bearing surface layer; and core layer and journal surface layer. Findings Results of threshold speed and critical whirl frequency ratio coefficients (Cω, CΩ), stiffness (Kij for i = x,y) and damping (Bij for i = x, y) coefficients and threshold speed (ωs) and critical whirl frequency ratio (Ωs) are presented. The bearing surface is analyzed for slip (total surface with slip) and partial slip (partial surface with slip). The slip-on bearing surface reduces stability, while partial slip improves bearing stability. The threshold speed coefficient (Cω) decreases with slip on bearing surface. The threshold speed (ωs) and critical whirl frequency ratio (Ωs) are influenced by the variation of threshold speed coefficient (Cω) and critical whirl frequency ratio coefficient (CΩ), respectively. A three-layered journal bearing with partial slip and thick high viscosity bearing surface layer results in higher threshold speed coefficient and has a potential to improve stability of journal bearing. The analyses indicate that optimal angular extent of partial slip region (θs) enhances the stability of journal bearing. Originality/value The paper presents parametric study of stability coefficients (Cω and CΩ) and evaluation of threshold speed (ωs) and critical whirl frequency ratio (Ωs) of a three-layered journal bearing with slip/partial slip.