Smart composite wind turbine blades - a pilot study

Wind energy is seen as a viable alternative energy option to meet future energy demands. The blades of wind turbines have been long recognised as the most critical component of the wind turbine system. The turbine blades interact with the wind flow to turn the wind turbine, in effect acting s a tool to extract the wind energy and turn it into electrical energy. As the wind industry continues to explore new technologies, the turbine blade is a key aspect of better wind turbine designs. Harnessing greater wind power requires larger swept areas. Increasing the length of the turbine blades increases the swept area of a wind turbine, thereby improving the production of wind energy. However, longer turbine blades significantly add to the weight of the turbine, and they also suffer from larger bending deflections due to flapwise loads. The flapwise bending deflections not only result in a lower performance of electrical power generation but also increase in material degradation due to high fatigue loads and can significantly shorten the longevity for the turbine blade. To overcome this excessive flapwise deflection, it is proposed that shape memory alloy (SMA) wires be used to return the turbine blade back to its optimal operational shape. The work presented here details the analytical and experimental work that was carried out to minimise blade flapping deflection using SMA. This study proposes a way to overcome the wind blade deflection using shape memory alloy (SMA) wires. A �finite element model has been developed for the simulation of the deflection response of a horizontal axis wind turbine blade using an SMA wire arrangement. The model was developed on the commercial finite element ABAQUSR, and focused on design and analysis, to predict the structural response. Experimental work was carried out to investigate the feasibility of the model based on a plate-like structure. An Artificial Neural Network (ANN) was used to predict the performance of the smart wind turbine blades. From this study, the model of a smart wind turbine, incorporating SMA wires, was determined to be capable of recovering from large deflections. The coefficient of performance of the smart wind turbine blade was also determined to be higher than the coefficient for a conventional turbine blade. The results showed that by increasing the number of SMA wires, the actuation provided is sufficient to recover from signifi�cant blade deflection resulting in a signifi�cant increase in the lift produced by the blade. It was determined that the coefficient of performance for turbine blades with SMA wires is 0.45 compared to 0.42 for turbine blades without SMA. These fi�ndings will be a signifi�cant achievement in the development of a smart wind turbine blade. It is expected that the use of smart wind turbine blades, incorporating SMA in their design, will not only increase the power output of the wind turbine but also prolong the lifetime of the turbine blade itself through a reduction of the bending deflections

Design and analysis of a smart composite beam for small wind turbine blade construction

Wind energy is seen as a viable alternative energy option for future energy demand. The blades of wind turbines are generally regarded as the most critical component of the wind turbine system. Ultimately, the blades act as the prime mover of the whole system which interacts with the wind flow during the production of energy. During wind turbine operation the wind loading cause the deflection of the wind turbine blade which can be significant and affect the turbine efficiency. Such a deflection in wind blade not only will result in lower performance in electrical power generation but also increase of material degradation due high fatigue life and can significantly shorten the longevity for the wind turbine material. In harnessing stiffness of the blade will contribute massive weight factor and consequently excessive bending moment. To overcome this excessive deflection due to wind loading on the blade, it is feasible to use shape memory alloy (SMA) wires which has ability take the blade back to its optimal operational shape

Heating Value Evaluation of Palm Oil Waste

The aim of this project is to evaluate the heating value of palm oil waste (POW).It is also concerned with the theory and method for determining heating value.The POW have high moisture contents (MC) which may affect the heating value.Therefore,this study also investigates the relationship between higher heating value (HHV) and MC. Calorimetry is the science of measuring heat based on the change in temperature that occurs during energy exchange between a reaction system and its environment.This exchange in energy can be measured using a thermally insulated container known as a bomb calorimeter. The experimentation part of this project mainly comprises on the calibration of the experimental set-up and arrangement and secondly the determination of POW’S HHV at full dry condition, as well as for different MC.Before conducting the tests on POW samples,the calibration test must be carried out firstly to identify whether the equivalent value of energy obtained is recommended by the manufacturer.Then, the remaining experiments will be proceeded further to satisfy the scope of the study. The POW which was fresh fibre and shell samples were collected from the Sri Ulu Langat, Dengkil, Selangor. The statistical analysis of t-test was applied to see whether all heating values of POW show significantly different between one to each other at fully dry.To verify all data sampling for POW at different MC,the Anova one-way test was used to see whether the heating values varied with the moisture contents.It is clearly being observed that higher heating value (HHV) is a function of moisture contents (MC). As conclusion,the aim of the study to evaluate the heating values of POW has been achieve

Improving quality management methods in manufacturing SMEs: a conceptual framework

The purpose of this paper is to deliver a critical review of quality management process improvement methods, determine the critical success factors to Lean Six Sigma implementation in manufacturing SMEs and design the conceptual execution framework to Lean Six Sigma implementation successfully in manufacturing SMEs. A variety of methods are available for implementation in quality management process improvement. In this paper four of the well-known methods have been briefly described including Total quality management (TQM), Lean Manufacturing, Six Sigma and Lean Six Sigma (LSS). The previous studies showed that all the four methods have some barriers and challenges that requires an elimination, Lean Six Sigma which is a combination of both Lean Manufacturing and Six Sigma is considered as the most updated method with less barriers in implementing quality management process in manufacturing SMEs

The impact of maintenance policies on some items of ISO (9001-2000): a survey study in industrial companies in Iraq

The influence of maintenance policy on the industrial sector is highly important, where there is a significant correlation between maintenance policies and some of the items related to international standard (ISO 9001- 2000) such as infrastructure, work environment, control of the production and service operations, and the adjustment of the measurement and monitoring tools. The aim of this study is to provide the intellectual and workable framework that relies on the arguments of researchers and those interested in the fields of management, production and engineering operations to highlight the role of maintenance policies in contributing to the achievement of quality. The industrial and governmental sectors were selected in the province of Nineveh as an arena to do the field work. The sample of the study comprises of six governmental and industrial companies. Questionnaires are used as the main tool for data collection. The study shows the need for sites with appropriate physical working conditions of temperature, humidity, and ventilation to do work in order to ensure the quality of performance through the maintenance policies

Development of artificial neural network model in predicting performance of the smart wind turbine blade

This paper demonstrates the applicability of artificial neural networks (ANNs) that use multiple bck-propagation networks (MBP) and a non-linear autoregressive exogenous model (NARX) for predicting the deflection of a smart wind turbine blade specimen. A neural network model has been developed to perform the deflection with respect to the number of wires required as the output parameter, and parameters such as load, current, time taken and deflection as the input parameters. The network has been trained with experimental data obtained from experimental work. The various stages involved in the development of a genetic algorithm based neural network model are addressed in detail in this paper

RSM approach for modeling and optimization of designing parameters for inclined fins of solar air heater

In the present study, a simulation and response surface methodology (RSM) combined approach has been applied to investigate the thermal and thermo-hydraulic performance parameter (THPP) of solar air heater (SAH) with inclined fins. CFD based software (ANSYS Fluent v16.1) is used to simulate the SAH. RNG k-Ɛ turbulence model was selected to carry out a two-dimensional simulation modeling. Moreover, RSM is applied to analyze the results of finite volume method and to optimize the process parameters of SAH. A numerical model describing the heat transfer characteristics of SAH having inclined fins has been developed and employed to study the effects of various design of fins on the average Nusselt number, fiction factor as well as THPP. The study covered different length of fin in the range of 1.5–2.5 mm, different slant angle (α) of fin in the range of 30°–60°, different pitch (P) of fin in the range of 15–25 mm, and a range of 4000–24,000 for the Reynolds numbers. Based on results of the model, the optimized values of design parameters for the optimal operation of SAH to provide the optimal THPP of 1.928 were found to be; length of fin = 1.52 mm, the pitch of fin = 19.04 mm, slant angle = 49° and Reynolds number at 18243.5. According to the optimized values of design parameters, the enhancement ratio of Nusselt number and friction factor were found to be 2.53 and 2.22, respectively. Finally, the thermal performance of the proposed inclined fin in terms of THPP was compared to other roughness geometries, such as circle (THPP = 1.65), square-sectioned (THPP = 1.80) and L-shaped (THPP = 1.90). Accordingly, a better THPP of 1.928 was observed for the current study

Optimization and selection of maintenance policies in an electrical gas turbine generator based on the hybrid reliability-centered maintenance (RCM) model

The electrical generation industry is looking for techniques to precisely determine the proper maintenance policy and schedule of their assets. Reliability-centered maintenance (RCM) is a methodology for choosing what maintenance activities have to be performed to keep the asset working within its designed function. Current developments in RCM models are struggling to solve the drawbacks of traditional RCM with regards to optimization and strategy selection; for instance, traditional RCM handles each failure mode individually with a simple yes or no safety question in which question has the possibility of major error and missing the effect of a combinational failure mode. Hence, in the present study, a hybrid RCM model was proposed to fill these gaps and find the optimal maintenance policies and scheduling by a combination of hybrid linguistic-failure mode and effect analysis (HL-FMEA), the co-evolutionary multi-objective particle swarm optimization (CMPSO) algorithm, an analytic network process (ANP), and developed maintenance decision tree (DMDT). To demonstrate the effectiveness and efficiencies of the proposed RCM model, a case study on the maintenance of an electrical generator was conducted at a Yemeni oil and gas processing plant. The results confirm that, compared with previous studies, the proposed model gave the optimal maintenance policies and scheduling for the electrical generator in a well-structured plan, economically and effectively

Development of a hybrid AHP and Dempster-Shafer theory of evidence for project risk assessment problem

In this paper, a new hybrid AHP and Dempster-Shafer Theory of Evidence is presented for solving the problem of choosing the best project among a list of available alternatives while uncertain risk factors are taken into account. The aim is to minimize overall risks. For this purpose, four groups of risk factors, including Properties, Operational and Technological, Financial, Strategic risk factors, are considered. Then using an L2 4 Taguchi method, several experiments with various dimensions have been designed and solved by the proposed algorithm. The outcomes are then analyzed using the Validating Index (VI), Reduced Risk Indicator (R.R.I%), and Solving time. The findings indicated that, compared to the classic AHP, the results of the proposed hybrid method were different in most cases due to uncertainty of risk factors. It was observed that the method could be safely used for selecting project problems in real industries

Microcontroller based DC energy logger for off-grid PV system application

This paper presents the development of a microcontroller-based DC energy power logger using the low-cost ATmega328 microcontroller to measure the PV system DC voltage and current, while at the same time logging the measured data over time to calculate the generated energy in kWh. An existing 1 kWp off-grid 24V DC PV System has been applied as the testbed for the prototype logger where its voltage sensor can sense the voltage PV array output range between 0-50V using a voltage divider sensor circuit. For current measurement, 50A ACS756 hall effect sensor were adopted for precise sensing of the PV array current output. The data was recorded and stored in comma-separated values (CSV) text format which is accessible using MS Excel. LCD displayed the real time voltage, current, power and time lapsed of the logging duration. Measured data were compared with standard digital multimeter for calibration. This energy logger's stand-alone feature is very suitable for off-grid PV System application beside its high accuracy performance for V & I measurement