Methodology for the Optimization of Bolting Sequences for Wind Generator Flanges

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Mikel Abasolo ◽  
Josu Aguirrebeitia ◽  
Rafael Avilés ◽  
Igor Fernández de Bustos
Keyword(s):  
Pressure Vessel ◽  
Computational Cost ◽  
Elastic Interaction ◽  
Optimization Methods ◽  
Bolted Joints ◽  
Wind Generator ◽  
Contact Surfaces ◽  
Number Of Passes ◽  
Low Computational Cost

In bolted joints, bolts are tightened to a uniform preload in order to improve their operational behavior. This preload is not easy to achieve due to several phenomena that occur during the tightening sequence; in the case of wind generator bolted joints, which present a gap between the contact surfaces of the flanges, the elastic interaction is by far the most prejudicial of them. As a consequence, the tightening sequence is very costly, typically consisting on a large number of passes. Based on a metamodel created in previous work, this work presents methodology for the optimization of the tightening sequence, which consists on calculating the load to be applied to each bolt so as to achieve the target uniform preload at the end of the sequence in only one pass or two at the most. This methodology is based on optimization methods used for pressure vessel bolted joints has provided satisfactory results (validated via FE analyses) with a very low computational cost.

A Tetraparametric Metamodel for the Simulation and Optimization of Bolting Sequences for Wind Generator Flanges

2010 ◽  
Author(s):  
Mikel Abasolo ◽  
Josu Aguirrebeitia ◽  
Rafael Avile´s ◽  
Igor Fernandez de Bustos
Keyword(s):  
Computational Cost ◽  
Nonlinear Behavior ◽  
Elastic Interaction ◽  
Bolted Joints ◽  
Experimental Measurements ◽  
Assembly Process ◽  
Simulation And Optimization ◽  
Wind Generator ◽  
Bolt Preload ◽  
Contact Surfaces

In the bolted joints of wind generator flanges there is a gap between the contact surfaces of the flanges. This involves a nonlinear behavior of the system during the tightening sequence of the joint. This phenomenom, in addition with the elastic interaction, makes it difficult to achieve a uniform bolt preload at the end of the assembly process. This work presents a methodology which, based on a metamodel created for such purpose, enables the optimization of the tightening sequence; i.e. it calculates the load to be applied to each bolt in order to achieve a desired uniform preload at the end of the tightening sequence. This optimization is done with a minimum computational cost, avoiding costly experimental measurements or nonlinear FE simulations. Besides, the methodology also takes into account that the load for any bolt must be below its yield point, and therefore calculates a two-pass sequence if necessary.

A Tetraparametric Metamodel for the Analysis and Design of Bolting Sequences for Wind Generator Flanges

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Mikel Abasolo ◽  
Josu Aguirrebeitia ◽  
Rafael Avilés ◽  
Igor Fernández de Bustos
Keyword(s):  
Finite Element ◽  
Computational Cost ◽  
Elastic Interaction ◽  
Bolted Joints ◽  
Experimental Measurements ◽  
Fe Model ◽  
Analysis And Design ◽  
Linear Elastic ◽  
Wind Generator ◽  
Contact Surfaces

This paper presents a metamodel that enables estimation of the elastic interaction that occurs in the bolted joints of a wind generator tower during the tightening sequence. In this kind of joint, there is a gap between the contact surfaces of the flanges. The metamodel is composed of four parameters, which are enough to simulate the response of the flange under the tightening loads of the bolts. Even though the behavior of the joint is nonlinear because of the gap, the parameters are obtained from two simple linear elastic analyses of a finite element (FE) model of the flange. The corresponding loss of load in the bolts has been estimated for various sequences with minimum computational cost. Thus, there is no need for costly experimental measurements or nonlinear FE simulations.

Optimized Bolt Tightening Sequences in Bolted Joints Using Superelement FE Modeling Technique

2018 ◽  
Author(s):  
Ibai Coria ◽  
Iñigo Martín ◽  
Hakim Bouzid ◽  
Iker Heras ◽  
Josu Aguirrebeitia
Keyword(s):  
Elastic Interaction ◽  
Bolted Joints ◽  
Fe Modeling ◽  
Bolted Joint ◽  
Assembly Time ◽  
Load Variations ◽  
Computational Costs ◽  
Bolt Preload ◽  
Optimization Methodology ◽  
Number Of Passes

A lot of effort is put to achieve bolt preload uniformity during the assembly process of offshore bolted joint connections resulting in potentially high economic costs and project delays. The complexity of this operation is due to the effect of the elastic interaction between the different joint elements which causes load variations of adjacent bolts whenever a bolt is tightened. As a consequence, it is difficult to achieve a uniform target load in the bolts. In order to avoid this phenomenon, tightening sequences of a large number of passes are usually carried out until a uniform target load is achieved. This solution is neither practical nor efficient when treating hundreds or even thousands of bolted joints due to the large assembly time needed. Several methods were developed to study the effect of the elastic interaction and minimize the assembly time. These methods usually predict the loss of load of every bolt during the tightening sequence, and thus calculate the tightening loads that will provide a uniform final load at the end of the sequence. As a result, an optimized tightening sequence is achieved, which provides a uniform final load distribution in only one or two tightening passes. However, several complex and costly analyses are previously necessary for such purpose. Based on these traditional methods, this paper presents a new and more efficient optimization methodology to achieve assembly bolt load uniformity. The method is based on the use of superelement technique and is capable of producing similar results with computational costs reduced by 30 times as compared to the more conventional Finite Element (FE) modeling. The results were satisfactorily validated with the latter as well as with tests conducted on a NPS 4 class 900 bolted joint.

scholarly journals Computing Expectiles Using k-Nearest Neighbours Approach

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 645
Author(s):  
Muhammad Farooq ◽  
Sehrish Sarfraz ◽  
Christophe Chesneau ◽  
Mahmood Ul Hassan ◽  
Muhammad Ali Raza ◽  
...  
Keyword(s):  
Computational Cost ◽  
Real Life ◽  
Distance Measures ◽  
Computational Time ◽  
High Dimensional ◽  
Test Error ◽  
Nearest Neighbours ◽  
Comparable Performance ◽  
Asymmetric Least Squares ◽  
Low Computational Cost

Expectiles have gained considerable attention in recent years due to wide applications in many areas. In this study, the k-nearest neighbours approach, together with the asymmetric least squares loss function, called ex-kNN, is proposed for computing expectiles. Firstly, the effect of various distance measures on ex-kNN in terms of test error and computational time is evaluated. It is found that Canberra, Lorentzian, and Soergel distance measures lead to minimum test error, whereas Euclidean, Canberra, and Average of (L1,L∞) lead to a low computational cost. Secondly, the performance of ex-kNN is compared with existing packages er-boost and ex-svm for computing expectiles that are based on nine real life examples. Depending on the nature of data, the ex-kNN showed two to 10 times better performance than er-boost and comparable performance with ex-svm regarding test error. Computationally, the ex-kNN is found two to five times faster than ex-svm and much faster than er-boost, particularly, in the case of high dimensional data.

scholarly journals Directional TGV-Based Image Restoration under Poisson Noise

2021 ◽  
Vol 7 (6) ◽  
pp. 99
Author(s):  
Daniela di Serafino ◽  
Germana Landi ◽  
Marco Viola
Keyword(s):  
Computed Tomography ◽  
Image Restoration ◽  
Gaussian Noise ◽  
Computational Cost ◽  
Data Fitting ◽  
Poisson Noise ◽  
Glass Fibres ◽  
Leibler Divergence ◽  
Generalized Variation ◽  
Low Computational Cost

We are interested in the restoration of noisy and blurry images where the texture mainly follows a single direction (i.e., directional images). Problems of this type arise, for example, in microscopy or computed tomography for carbon or glass fibres. In order to deal with these problems, the Directional Total Generalized Variation (DTGV) was developed by Kongskov et al. in 2017 and 2019, in the case of impulse and Gaussian noise. In this article we focus on images corrupted by Poisson noise, extending the DTGV regularization to image restoration models where the data fitting term is the generalized Kullback–Leibler divergence. We also propose a technique for the identification of the main texture direction, which improves upon the techniques used in the aforementioned work about DTGV. We solve the problem by an ADMM algorithm with proven convergence and subproblems that can be solved exactly at a low computational cost. Numerical results on both phantom and real images demonstrate the effectiveness of our approach.

scholarly journals An optimal and low computational cost fractional Newton-type method for solving nonlinear equations

2021 ◽  
pp. 107650
Author(s):  
Giro Candelario ◽  
Alicia Cordero ◽  
Juan R. Torregrosa ◽  
María P. Vassileva
Keyword(s):  
Nonlinear Equations ◽  
Computational Cost ◽  
Type Method ◽  
Low Computational Cost

Low-Computational Cost Estimation Algorithm for Adaptive Optics Systems*

2011 ◽  
Vol 44 (1) ◽  
pp. 5573-5578
Author(s):  
M. Abbas Turki ◽  
D. Esqueda Merino ◽  
K. Kasper ◽  
C. Durieu
Keyword(s):  
Adaptive Optics ◽  
Cost Estimation ◽  
Computational Cost ◽  
Estimation Algorithm ◽  
Low Computational Cost

scholarly journals Status Estimation and In-Process Connection of Kanbans Using BLE Beacons and LPWA Network to Implement Intra-Traceability for the Kanban System

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5038
Author(s):  
Kosuke Shima ◽  
Masahiro Yamaguchi ◽  
Takumi Yoshida ◽  
Takanobu Otsuka
Keyword(s):  
Inventory Management ◽  
Low Cost ◽  
Computational Cost ◽  
Low Energy ◽  
Manufacturing Strategy ◽  
Implementation Cost ◽  
Measurement Systems ◽  
Process Route ◽  
Kanban System ◽  
Low Computational Cost

IoT-based measurement systems for manufacturing have been widely implemented. As components that can be implemented at low cost, BLE beacons have been used in several systems developed in previous research. In this work, we focus on the Kanban system, which is a measure used in manufacturing strategy. The Kanban system emphasizes inventory management and is used to produce only required amounts. In the Kanban system, the Kanban cards are rotated through the factory along with the products, and when the products change to a different process route, the Kanban card is removed from the products and the products are assigned to another Kanban. For this reason, a single Kanban cannot trace products from plan to completion. In this work, we propose a system that uses a Bluetooth low energy (BLE) beacon to connect Kanbans in different routes but assigned to the same products. The proposed method estimates the beacon status of whether the Kanban is inside or outside a postbox, which can then be computed by a micro controller at low computational cost. In addition, the system connects the Kanbans using the beacons as paired connection targets. In an experiment, we confirmed that the system connected 70% of the beacons accurately. We also confirmed that the system could connect the Kanbans at a small implementation cost.

scholarly journals Fast Image Registration for Spacecraft Autonomous Navigation Using Natural Landmarks

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Yun-Hua Wu ◽  
Lin-Lin Ge ◽  
Feng Wang ◽  
Bing Hua ◽  
Zhi-Ming Chen ◽  
...  
Keyword(s):  
Image Registration ◽  
Autonomous Navigation ◽  
Computational Cost ◽  
Segmentation Algorithm ◽  
Speeded Up Robust Features ◽  
Speed Up ◽  
Random Sample Consensus ◽  
Invariant Properties ◽  
Low Computational Cost ◽  
Ransac Algorithm

In order to satisfy the real-time requirement of spacecraft autonomous navigation using natural landmarks, a novel algorithm called CSA-SURF (chessboard segmentation algorithm and speeded up robust features) is proposed to improve the speed without loss of repeatability performance of image registration progress. It is a combination of chessboard segmentation algorithm and SURF. Here, SURF is used to extract the features from satellite images because of its scale- and rotation-invariant properties and low computational cost. CSA is based on image segmentation technology, aiming to find representative blocks, which will be allocated to different tasks to speed up the image registration progress. To illustrate the advantages of the proposed algorithm, PCA-SURF, which is the combination of principle component analysis and SURF, is also analyzed in this paper for comparison. Furthermore, random sample consensus (RANSAC) algorithm is applied to eliminate the false matches for further accuracy improvement. The simulation results show that the proposed strategy obtains good results, especially in scaling and rotation variation. Besides, CSA-SURF decreased 50% of the time in extraction and 90% of the time in matching without losing the repeatability performance by comparing with SURF algorithm. The proposed method has been demonstrated as an alternative way for image registration of spacecraft autonomous navigation using natural landmarks.

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