Surrogate modelling for reliability assessment of cutting tools

Currently, cutting tool life for machining operations is correlated to process parameters through the widely applied Taylor functions. The latter are valuable expressions in established practice however their generalised nature does not allow accurate prediction of the tool’s service life or optimization of the manufacturing process due to effects of uncertainties in various input variables. These variables should be treated in a stochastic way in order to avoid employment of safety factors for quantification of uncertainty. This paper documents a procedure that allows derivation of analytical expressions for cutting tools performance employing advanced approximation methods and concepts of reliability analysis. Due to the complexity of manufacturing processes surrogate modelling (SM) methods are applied, starting from a few sample points obtained through lab or soft experiments and extending them to models able to predict/estimate the values of control values/indicators as a function of the key design variables, often referred to as limit states

Reliability assessment of cutting tool life based on surrogate approximation methods

A novel reliability estimation approach to the cutting tools based on advanced approximation methods is proposed. Methods such as the stochastic response surface and surrogate modeling are tested, starting from a few sample points obtained through fundamental experiments and extending them to models able to estimate the tool wear as a function of the key process parameters. Subsequently, different reliability analysis methods are employed such as Monte Carlo simulations and first- and second-order reliability methods. In the present study, these reliability analysis methods are assessed for estimating the reliability of cutting tools. The results show that the proposed method is an efficient method for assessing the reliability of the cutting tool based on the minimum number of experimental results. Experimental verification for the case of high-speed turning confirms the findings of the present study for cutting tools under flank wear

Failure mode identification and end of life scenarios of offshore wind turbines: a review

In 2007, the EU established challenging goals for all Member States with the aim of obtaining 20% of their energy consumption from renewables, and offshore wind is expected to be among the renewable energy sources contributing highly towards achieving this target. Currently wind turbines are designed for a 25-year service life with the possibility of operational extension. Extending their efficient operation and increasing the overall electricity production will significantly increase the return on investment (ROI) and decrease the levelized cost of electricity (LCOE), considering that Capital Expenditure (CAPEX) will be distributed over a larger production output. The aim of this paper is to perform a detailed failure mode identification throughout the service life of offshore wind turbines and review the three most relevant end of life (EOL) scenarios: life extension, repowering and decommissioning. Life extension is considered the most desirable EOL scenario due to its profitability. It is believed that combining good inspection, operations and maintenance (O&M) strategies with the most up to date structural health monitoring and condition monitoring systems for detecting previously identified failure modes, will make life extension feasible. Nevertheless, for the cases where it is not feasible, other options such as repowering or decommissioning must be explored

External grind-hardening forces modelling and experimentation

Grind hardening process utilizes the heat generated in the grinding area for the surface heat treatment of the workpiece. The workpiece surface is heated above the austenitizing temperature by using large values of depth of cut and low workpiece feed speeds. However, such process parameter combinations result in high process forces that inhibit the broad application of grind hardening to smaller grinding machines. In the present paper, modelling and predicting of the process forces as a function of the process parameters are presented. The theoretical predictions present good agreement with experimental results. The results of the study can be used for the prediction of the grind hardening process forces and, therefore, optimize the process parameters so as to be used with every size grinding machine

Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm

Offshore Wind has become the most profitable renewable energy source due to the remarkable development it has experienced in Europe over the last decade. In this paper, a review of Structural Health Monitoring Systems (SHMS) for offshore wind turbines (OWT) has been carried out considering the topic as a Statistical Pattern Recognition problem. Therefore, each one of the stages of this paradigm has been reviewed focusing on OWT application. These stages are: Operational Evaluation; Data Acquisition, Normalization and Cleansing; Feature Extraction and Information Condensation; and Statistical Model Development. It is expected that optimizing each stage, SHMS can contribute to the development of efficient Condition-Based Maintenance Strategies. Optimizing this strategy will help reduce labor costs of OWTs׳ inspection, avoid unnecessary maintenance, identify design weaknesses before failure, improve the availability of power production while preventing wind turbines׳ overloading, therefore, maximizing the investments׳ return. In the forthcoming years, a growing interest in SHM technologies for OWT is expected, enhancing the potential of offshore wind farm deployments further offshore. Increasing efficiency in operational management will contribute towards achieving UK׳s 2020 and 2050 targets, through ultimately reducing the Levelised Cost of Energy (LCOE)

Determination of stress concentration factors in offshore wind welded structures through a hybrid experimental and numerical approach

Offshore wind turbine (OWT) monopile support structures generally consist of steel cans connected together through circumferential welding joints. One critical factor to evaluate the localised increase in stresses is the stress concentration factor (SCF) which depends on the welding quality. The complex welding profiles in OWT monopiles makes the accurate calculation of SCF quite challenging. In this work, an innovative approach for the calculation of SCFs in offshore welded structures is proposed based on combined 3D (three-dimensional) laser scanning technology (LST) and 3D finite element analysis (FEA). The precise geometry of the welded specimens is captured using 3D LST, and then imported into a finite element software to perform 3D FEA modelling to accurately calculate SCFs. A 2D (two-dimensional) FEA model of a typical offshore welded structure with ideal geometry is also developed in this work. In addition to numerically calculate SCFs, the 2D FEA model is further combined with non-linear RSM (response surface method) to derive analytical equations, expressing SCFs of offshore welded structures in terms of key welding parameters. Both LST-FEA3D and RSM-FEA2D models are applied to calculate SCFs in large-scale S-N fatigue welded specimens. The results indicate that the LST-FEA3D approach is capable of capturing the variation of SCFs along the width of the welded specimens and identifying the critical points where fatigue crack is most likely to initiate; and the RSM-FEA2D is valuable and efficient in deriving analytical parametric equations for SCFs

Thermodynamic performance of heat exchangers in a free piston Stirling engine

There is an increasing request in energy recovery systems that are more efficient, environmentally friendly and economical. The free piston Stirling engine has been investigated due to its structural simplicity and high efficiency, coupled with its cogeneration ability. This study presents the numerical investigation of quasi-steady model of a gamma type free piston Stirling engine (FPSE), including the thermodynamic analysis of the heat exchangers. Advanced thermodynamic models are employed to derive the initial set of operational parameters of the FPSE due to the coupling of the piston’s (displacer and piston) dynamics and the working process. The proximity effect of the heater and cooler on the regenerator effectiveness in relation to the heat losses, output power, net work and thermal efficiency of the FPSE are also observed and presented in this study. It can be observed that at temperatures of 541.3 °C and 49.8 °C of the heater and cooler, respectively, with heater volume of 0.004 m3, regenerator volume of 0.003 m3 and cooler volume of 0.005 m3, the FPSE produced an output performance of 996.7 W with a thermal efficiency of 23% at a frequency of 30 Hz. This approach can be employed to design effective high performance FPSE due to their complexity and also predict a satisfactory performance

A comparative study of multiple-criteria decision-making methods under stochastic inputs

This paper presents an application and extension of multiple-criteria decision-making (MCDM) methods to account for stochastic input variables. More in particular, a comparative study is carried out among well-known and widely-applied methods in MCDM, when applied to the reference problem of the selection of wind turbine support structures for a given deployment location. Along with data from industrial experts, six deterministic MCDM methods are studied, so as to determine the best alternative among the available options, assessed against selected criteria with a view toward assigning confidence levels to each option. Following an overview of the literature around MCDM problems, the best practice implementation of each method is presented aiming to assist stakeholders and decision-makers to support decisions in real-world applications, where many and often conflicting criteria are present within uncertain environments. The outcomes of this research highlight that more sophisticated methods, such as technique for the order of preference by similarity to the ideal solution (TOPSIS) and Preference Ranking Organization method for enrichment evaluation (PROMETHEE), better predict the optimum design alternative

A multi-objective optimisation approach applied to offshore wind farm location selection

This paper compares the three state-of-the-art algorithms when applied to a real-world case of the wind energy sector. Optimum locations are suggested for a wind farm by considering only Round 3 zones around the UK. The problem comprises of some of the most important techno-economic life cycle cost-related factors, which are modelled using the physical aspects of each wind farm location (i.e., the wind speed, distance from the ports, and water depth), the wind turbine size, and the number of turbines. The model is linked to NSGA II, NSGA III, and SPEA 2 algorithms, to conduct an optimisation search. The performance of these three algorithms is demonstrated and analysed, so as to assess their effectiveness in the investment decision-making process in the wind sector, more importantly, for Round 3 zones. The results are subject to the specifics of the underlying life cycle cost model

Effect of the number of blades and solidity on the performance of a vertical axis wind turbine

Two, three and four bladed phgr-shape Vertical Axis Wind Turbines are simulated using a free-wake vortex model. Two versions of the three and four bladed turbines are considered, one having the same chord length as the two-bladed turbine and the other having the same solidity as the two-bladed turbine. Results of the two-bladed turbine are validated against published experimental data of power coefficient and instantaneous torque. The effect of solidity on the power coefficient is presented and the instantaneous torque, thrust and lateral force of the two-, three- and four-bladed turbines are compared for the same solidity. It is found that increasing the number of blades from two to three significantly reduces the torque, thrust and lateral force ripples. Adding a fourth blade further reduces the ripples except for the torque at low tip speed ratio. This work aims to help choosing the number of blades during the design phase of a vertical axis wind turbine