scholarly journals Robust Estimation of Deformation from Observation Differences Using Some Evolutionary Optimisation Algorithms

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 159
Author(s):  
Mehmed Batilović ◽  
Radovan Đurović ◽  
Zoran Sušić ◽  
Željko Kanović ◽  
Zoran Cekić
Keyword(s):  
Robust Estimation ◽  
Displacement Vector ◽  
Traditional Approach ◽  
Deformation Analysis ◽  
Practical Usefulness ◽  
Evolutionary Optimisation ◽  
Global Optimal ◽  
Proposed Modification ◽  
Optimisation Techniques ◽  
Optimisation Algorithms

In this paper, an original modification of the generalised robust estimation of deformation from observation differences (GREDOD) method is presented with the application of two evolutionary optimisation algorithms, the genetic algorithm (GA) and generalised particle swarm optimisation (GPSO), in the procedure of robust estimation of the displacement vector. The iterative reweighted least-squares (IRLS) method is traditionally used to perform robust estimation of the displacement vector, i.e., to determine the optimal datum solution of the displacement vector. In order to overcome the main flaw of the IRLS method, namely, the inability to determine the global optimal datum solution of the displacement vector if displaced points appear in the set of datum network points, the application of the GA and GPSO algorithms, which are powerful global optimisation techniques, is proposed for the robust estimation of the displacement vector. A thorough and comprehensive experimental analysis of the proposed modification of the GREDOD method was conducted based on Monte Carlo simulations with the application of the mean success rate (MSR). A comparative analysis of the traditional approach using IRLS, the proposed modification based on the GA and GPSO algorithms and one recent modification of the iterative weighted similarity transformation (IWST) method based on evolutionary optimisation techniques is also presented. The obtained results confirmed the quality and practical usefulness of the presented modification of the GREDOD method, since it increased the overall efficiency by about 18% and can provide more reliable results for projects dealing with the deformation analysis of engineering facilities and parts of the Earth’s crust surface.

scholarly journals Multi-Mode Wave Energy Converter Design Optimisation Using an Improved Moth Flame Optimisation Algorithm

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3737
Author(s):  
Mehdi Neshat ◽  
Nataliia Sergiienko ◽  
Seyedali Mirjalili ◽  
Meysam Majidi Nezhad ◽  
Giuseppe Piras ◽  
...  
Keyword(s):  
Wave Energy ◽  
Wave Energy Converter ◽  
Total Power ◽  
Energy Converter ◽  
Wave Regime ◽  
Optimisation Algorithm ◽  
Wide Range ◽  
Evolutionary Optimisation ◽  
Optimisation Methods ◽  
Optimisation Algorithms

Ocean renewable wave power is one of the more encouraging inexhaustible energy sources, with the potential to be exploited for nearly 337 GW worldwide. However, compared with other sources of renewables, wave energy technologies have not been fully developed, and the produced energy price is not as competitive as that of wind or solar renewable technologies. In order to commercialise ocean wave technologies, a wide range of optimisation methodologies have been proposed in the last decade. However, evaluations and comparisons of the performance of state-of-the-art bio-inspired optimisation algorithms have not been contemplated for wave energy converters’ optimisation. In this work, we conduct a comprehensive investigation, evaluation and comparison of the optimisation of the geometry, tether angles and power take-off (PTO) settings of a wave energy converter (WEC) using bio-inspired swarm-evolutionary optimisation algorithms based on a sample wave regime at a site in the Mediterranean Sea, in the west of Sicily, Italy. An improved version of a recent optimisation algorithm, called the Moth–Flame Optimiser (MFO), is also proposed for this application area. The results demonstrated that the proposed MFO can outperform other optimisation methods in maximising the total power harnessed from a WEC.

A methodology for 7D warping and deformation monitoring using time-lapse seismic data

Geophysics ◽  
2006 ◽  
Vol 71 (4) ◽  
pp. O21-O31 ◽  
Author(s):  
Stephen A. Hall
Keyword(s):  
Displacement Vector ◽  
Strain Analysis ◽  
Time Lapse ◽  
Deformation Monitoring ◽  
Deformation Analysis ◽  
Local Effects ◽  
Image Match ◽  
Seismic Image ◽  
Vertical Displacements

A methodology is presented for vector analysis of the image displacements (warping) between successive 3D seismic image volumes that provides 7D analysis (including lateral and vertical displacements) of in situ subsurface deformation around hydrocarbon reservoirs. The key challenges are (1) assessment of just vertical shifts is insufficient, and vector displacements should be determined; (2) robust vertical displacements can usually be derived, but lateral shifts are less well defined because of the generally smooth data character in a horizontal/horizon plane; (3) subvoxel resolution is necessary for correct matching and deformation analysis; (4) velocity and strain effects are intrinsically combined in time-lapse seismic images; (5) separation of accumulated and local effects is necessary; (6) apparently coherent and smooth displacement fields do not necessarily provide good strain analysis; (7) warping is easily degraded by noise, and good cross-matching is a prerequisite. To address these challenges, a full 3D, local warp vector derivation methodology is proposed, which involves (1) constraint using prior estimates, (2) local refinement with subvoxel resolution, and (3) 3D and vectorial conditioning using a deformable mesh with sensitivity to image-match quality. The warping approach is extended to separate accumulated from local effects and to analyze in situ deformation based on the displacement vector volume. This is achieved by a finite-element approach to determine an elemental pseudostrain tensor field and an iterative procedure to separate the pseudostrain into velocity and strain components. The approach up to the strain analysis, is demonstrated using a real data example, which indicates the potential of the methodology (accumulated overburden effects are separated to reveal a local compaction signature in the reservoir), but realistic, quantitative values of strain have not yet been realized.

BUCKLING AND POST-BUCKLING OF ISOTROPIC AND COMPOSITE STIFFENED PANELS: A REVIEW ON OPTIMISATION (2000-2015)

2021 ◽  
Vol 158 (A3) ◽  
Author(s):  
X-Y Ni ◽  
B G Prusty ◽  
A K Hellier
Keyword(s):  
Critical Discussion ◽  
Loading Capacity ◽  
Light Weight ◽  
Structural Elements ◽  
Engineering Structures ◽  
Stiffened Panels ◽  
Post Buckling ◽  
Key Issues ◽  
Optimisation Techniques ◽  
Optimisation Algorithms

Stiffened panels made out of isotropic or anisotropic materials are being extensively used as structural elements for aircraft, maritime, and other structures. In order to maintain stiffness and strength with light weight, new design techniques must be employed when utilising these materials. Their stability, ultimate strength and loading capacity are the key issues pertaining to these engineering structures which have attracted a number of investigators to undertake in- depth research, either in an academic or actual engineering context. This paper presents a review of the optimisation techniques applied to buckling and post-buckling of stiffened panels. Papers published in the period from 2000 to May 2015 have been taken into consideration. The topic is addressed by identifying the most significant objectives, targets and issues, as well as the optimisation formulations, optimisation algorithms and models available. Finally a critical discussion, giving some practical advice and pointing out and post-buckling of stiffened panels, is provided. 

Optimisation meets the manager: a case study of the La Paz reservoir system

2003 ◽  
Vol 3 (1-2) ◽  
pp. 373-379
Author(s):  
M. Bender ◽  
M. Stanic ◽  
D. Luketina ◽  
D. Hranisavljevic
Keyword(s):  
Traditional Approach ◽  
Water Levels ◽  
La Paz ◽  
Reservoir System ◽  
Operating Rules ◽  
Dynamic Operating ◽  
Optimal Dynamic ◽  
Optimisation Techniques ◽  
Level Of Risk

Managers must usually apply operating rules to optimise the use of water resources in a sustainable manner. Ideally a manager needs a set of near-optimal dynamic operating rules that are consistent with the objectives and level of risk set by the manager. The traditional approach for a reservoir is to develop fixed (static) rule curves based upon a statistical analysis. However, improved dynamic rules can be derived using optimisation techniques such as genetic algorithms. Also, simulation methods can be used. Here we show how both methods can be applied to generate near-optimal dynamic operating rules for a reservoir system used for drinking water supply in La Paz, Bolivia. In particular, we show how simple practical operating rules can incorporate the level of risk set by the manager. Further, these rules advise how quickly water levels should be altered when they are too high or too low.

scholarly journals ANALISIS DEFORMASI GUNUNG API BATUR BERDASARKAN DATA PENGAMATAN GPS BERKALA TAHUN 2008, 2009, 2013, DAN 2015 DEFORMATION ANALYSIS OF BATUR VOLCANO BASED ON PERIODIC GPS OBSERVATIONS DATA IN 2008, 2009, 2013, AND 2015

2018 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Achmad Faris ◽  
Estu Kriswati ◽  
Irwan Meilano ◽  
Dina Anggreni Sarsito
Keyword(s):  
Volcanic Activity ◽  
Ground Deformation ◽  
Displacement Vector ◽  
Deformation Analysis ◽  
Gps Data ◽  
Deformation Pattern ◽  
The North ◽  
Strain Pattern ◽  
Batur Volcano ◽  
Gps Observations

ABSTRAKGunung Batur yang terletak di Kabupaten Bangli, Bali, terakhir meletus pada tahun 2000. Pada 2009 terjadi peningkatan aktivitas vulkanis di Gunug Batur walaupun tidak terjadi letusan. Penelitian ini bertujuan untuk mengetahui pola deformasi pada Gunung Batur serta keterkaitannya dengan peningkatan vulkanis pada tahun 2009. Analisis didasarkan pada pola vektor pergeseran dan pola regangan masing-masing titik pengamatan GPS berkala pada area Gunung Batur tahun 2008, 2009, 2013, dan 2015. Berdasarkan pengamatan GPS Oktober 2008-November 2009 pola deformasi menunjukkan adanya inflasi dengan pola vektor pergeseran titik pengamatan GPS dominan ke arah luar dari Gunung Batur, selain itu pola regangan memperlihatkan bahwa pada area bagian utara dan timurlaut Gunung Batur dominan terjadi ekstensi. Pada pengamatan GPS untuk periode November 2009-Februari 2013 pola deformasi menunjukkan adanya deflasi pada Gunung Batur dengan pola vektor pergeseran titik pengamatan GPS berarah menuju Gunung Batur dan pola regangan memperlihatkan bahwa pada area Gunung Batur terjadi kompresi. Kata Kunci: Gunung Batur, deflasi, deformasi, pergeseran, GPS, inflasi, regangan. ABSTRACTBatur volcano located in Bangli, Bali, last erupted in 2000. Increased in the volcanic activity occurred in 2009 but did not followed by eruption. This study aims to determine ground deformation pattern in Batur volcano and its association with the increased in volcanic activity in 2009 based on the pattern of displacement vector and strain using 2008-2015 campaign GPS data. During period of October 2008-November 2009, Batur Volcano experience inflation and strain pattern shows that the area of the north and northeast of Batur Volcano experienced extension. During November 2009-February 2013, Batur Volcano experienced deflation with GPS displacement directed towards Batur Volcano and a strain pattern of compression around Batur Volcano. Keywords: Batur Volcano, deflation, deformation, displacement, GPS, inflation, strain.

scholarly journals An Improved Pigeon-Inspired Optimisation Algorithm and Its Application in Parameter Inversion

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1291 ◽  
Author(s):  
Hanmin Liu ◽  
Xuesong Yan ◽  
Qinghua Wu
Keyword(s):  
Oil And Gas ◽  
Pso Algorithm ◽  
Elastic Parameter ◽  
Local Optimum ◽  
Oil And Gas Exploration ◽  
Avo Inversion ◽  
Parameter Inversion ◽  
Evolutionary Optimisation ◽  
Intelligent Optimisation ◽  
Optimisation Algorithms

Pre-stack amplitude variation with offset (AVO) elastic parameter inversion is a nonlinear, multi-solution optimisation problem. The techniques that combine intelligent optimisation algorithms and AVO inversion provide an effective identification method for oil and gas exploration. However, these techniques also have shortcomings in solving nonlinear geophysical inversion problems. The evolutionary optimisation algorithms have recognised disadvantages, such as the tendency of convergence to a local optimum resulting in poor local optimisation performance when dealing with multimodal search problems, decreasing diversity and leading to the prematurity of the population as the number of evolutionary iterations increases. The pre-stack AVO elastic parameter inversion is nonlinear with slow convergence, while the pigeon-inspired optimisation (PIO) algorithm has the advantage of fast convergence and better optimisation characteristics. In this study, based on the characteristics of the pre-stack AVO elastic parameter inversion problem, an improved PIO algorithm (IPIO) is proposed by introducing the particle swarm optimisation (PSO) algorithm, an inverse factor, and a Gaussian factor into the PIO algorithm. The experimental comparisons indicate that the proposed IPIO algorithm can achieve better inversion results.

scholarly journals F2S3: Robustified determination of 3D displacement vector fields using deep learning

2020 ◽  
Vol 14 (2) ◽  
pp. 177-189
Author(s):  
Zan Gojcic ◽  
Caifa Zhou ◽  
Andreas Wieser
Keyword(s):  
Displacement Vector ◽  
Point Clouds ◽  
Deformation Monitoring ◽  
Swiss Alps ◽  
Local Context ◽  
Deformation Analysis ◽  
Natural Scenes ◽  
Interest Points ◽  
Data Set ◽  
Cloud Data

AbstractAreal deformation monitoring based on point clouds can be a very valuable alternative to the established point-based monitoring techniques, especially for deformation monitoring of natural scenes. However, established deformation analysis approaches for point clouds do not necessarily expose the true 3D changes, because the correspondence between points is typically established naïvely. Recently, approaches to establish the correspondences in the feature space by using local feature descriptors that analyze the geometric peculiarities in the neighborhood of the interest points were proposed. However, the resulting correspondences are noisy and contain a large number of outliers. This impairs the direct applicability of these approaches for deformation monitoring. In this work, we propose Feature to Feature Supervoxel-based Spatial Smoothing (F2S3), a new deformation analysis method for point cloud data. In F2S3 we extend the recently proposed feature-based algorithms with a neural network based outlier detection, capable of classifying the putative pointwise correspondences into inliers and outliers based on the local context extracted from the supervoxels. We demonstrate the proposed method on two data sets, including a real case data set of a landslide located in the Swiss Alps. We show that while the traditional approaches, in this case, greatly underestimate the magnitude of the displacements, our method can correctly estimate the true 3D displacement vectors.

Sign in / Sign up

Export Citation Format

Share Document