scholarly journals Using Optimisation Meta-Heuristics for the Roughness Estimation Problem in River Flow Analysis

2021 ◽  
Vol 11 (22) ◽  
pp. 10575
Author(s):  
Antonio Agresta ◽  
Marco Baioletti ◽  
Chiara Biscarini ◽  
Fabio Caraffini ◽  
Alfredo Milani ◽  
...  
Keyword(s):  
Cross Sections ◽  
Computational Models ◽  
River Flow ◽  
Heuristic Algorithms ◽  
Flow Analysis ◽  
Differential Evolution Algorithm ◽  
Optimal Estimation ◽  
Evolution Strategy ◽  
Computational Time ◽  
Roughness Coefficient

Climate change threats make it difficult to perform reliable and quick predictions on floods forecasting. This gives rise to the need of having advanced methods, e.g., computational intelligence tools, to improve upon the results from flooding events simulations and, in turn, design best practices for riverbed maintenance. In this context, being able to accurately estimate the roughness coefficient, also known as Manning’s n coefficient, plays an important role when computational models are employed. In this piece of research, we propose an optimal approach for the estimation of ‘n’. First, an objective function is designed for measuring the quality of ‘candidate’ Manning’s coefficients relative to specif cross-sections of a river. Second, such function is optimised to return coefficients having the highest quality as possible. Five well-known meta-heuristic algorithms are employed to achieve this goal, these being a classic Evolution Strategy, a Differential Evolution algorithm, the popular Covariance Matrix Adaptation Evolution Strategy, a classic Particle Swarm Optimisation and a Bayesian Optimisation framework. We report results on two real-world case studies based on the Italian rivers ‘Paglia’ and ‘Aniene’. A comparative analysis between the employed optimisation algorithms is performed and discussed both empirically and statistically. From the hydrodynamic point of view, the experimental results are satisfactory and produced within significantly less computational time in comparison to classic methods. This shows the suitability of the proposed approach for optimal estimation of the roughness coefficient and, in turn, for designing optimised hydrological models.

scholarly journals Development of RiverBox—An ArcGIS Toolbox for River Bathymetry Reconstruction

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1266 ◽  
Author(s):  
Tomasz Dysarz
Keyword(s):  
Cross Sections ◽  
River Flow ◽  
Computational Time ◽  
Fully Integrated ◽  
River Bed ◽  
Develop Software ◽  
Scripting Language ◽  
Gis Environment ◽  
Elevation Model ◽  
Model Preparation

The main purpose of the present research is to develop software for reconstruction of the river bed on the basis of sparse cross-section measurements. The tools prepared should support the process of hydrodynamic model preparation for simulation of river flow. Considering the formats of available data and the requirements of modern modeling techniques, the prepared software is fully integrated with the GIS environment. The scripting language Python 2.7 implemented in ArcGIS 10.5.1 was chosen for this purpose. Two study cases were selected to validate and test the prepared procedures. These are stream reaches in Poland. The first is located on the Warta river, and the second on the Ner river. The data necessary for the whole procedure are: a digital elevation model, measurements of the cross-sections in the form of points, and two polyline layers representing an arbitrary river centerline and river banks. In the presented research the concept of a channel-oriented coordinate system is applied. The elevations are linearly interpolated along the longitudinal and transversal directions. The interpolation along the channel is implemented in three computational schemes linking different tools available in ArcGIS and ArcToolbox. A simplified comparison of memory usage and computational time is presented. The scheme linking longitudinal and spatial interpolation algorithms seems to be the most advantageous.

scholarly journals Patterns of Difference between Physical and 1-D Calibrated Effective Roughness Parameters in Mountain Rivers

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3202
Author(s):  
Sebastián Cedillo ◽  
Esteban Sánchez-Cordero ◽  
Luis Timbe ◽  
Esteban Samaniego ◽  
Andrés Alvarado
Keyword(s):  
Cross Sections ◽  
River Flow ◽  
Selection Process ◽  
Roughness Parameter ◽  
Field Measurements ◽  
Accurate Estimation ◽  
Roughness Coefficient ◽  
Mountain Rivers ◽  
Effective Roughness ◽  
The Difference

Due to the presence of boulders and different morphologies, mountain rivers contain various resistance sources. To correctly simulate river flow using 1-D hydrodynamic models, an accurate estimation of the flow resistance is required. In this article, a comparison between the physical roughness parameter (PRP) and effective roughness coefficient (ERC) is presented for three of the most typical morphological configurations in mountain rivers: cascade, step-pool, and plane-bed. The PRP and its variation were obtained through multiple measurements of field variables and an uncertainty analysis, while the ERC range was derived with a GLUE procedure implemented in HEC-RAS, a 1-D hydrodynamic model. In the GLUE experiments, two modes of the Representative Friction Slope Method (RFSM) between two cross-sections were tested, including the variation in the roughness parameter. The results revealed that the RFSM effect was limited to low flows in cascade and step-pool. Moreover, when HEC-RAS selected the RSFM, only acceptable results were presented for plane-bed. The difference between ERC and PRP depended on the flow magnitude and the morphology, and as shown in this study, when the flow increased, the ERC and PRP ranges approached each other and even overlapped in cascade and step-pool. This research aimed to improve the roughness value selection process in a 1-D model given the importance of this parameter in the predictability of the results. In addition, a comparison was presented between the results obtained with the numerical model and the values calculated with the field measurements

Comparison of Meta-heuristic Algorithms on Benchmark Functions

2019 ◽  
Vol 2 (3) ◽  
pp. 508-517
Author(s):  
FerdaNur Arıcı ◽  
Ersin Kaya
Keyword(s):  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Differential Evolution Algorithm ◽  
Population Based ◽  
Time Interval ◽  
Bee Colony ◽  
Different Characteristics

Optimization is a process to search the most suitable solution for a problem within an acceptable time interval. The algorithms that solve the optimization problems are called as optimization algorithms. In the literature, there are many optimization algorithms with different characteristics. The optimization algorithms can exhibit different behaviors depending on the size, characteristics and complexity of the optimization problem. In this study, six well-known population based optimization algorithms (artificial algae algorithm - AAA, artificial bee colony algorithm - ABC, differential evolution algorithm - DE, genetic algorithm - GA, gravitational search algorithm - GSA and particle swarm optimization - PSO) were used. These six algorithms were performed on the CEC’17 test functions. According to the experimental results, the algorithms were compared and performances of the algorithms were evaluated.

scholarly journals AN ATHEROSCLEROTIC CORONARY ARTERY PHANTOM FOR PARTICLE IMAGE VELOCIMETRY

2011 ◽  
Author(s):  
Jean Brunette ◽  
Rosaire Mongrain ◽  
Rosaire Mongrain ◽  
Adrian Ranga ◽  
Adrian Ranga ◽  
...  
Keyword(s):  
Experimental Data ◽  
Particle Image Velocimetry ◽  
Heart Attack ◽  
Computational Models ◽  
Particle Image ◽  
Flow Analysis ◽  
Novel Technique ◽  
Image Velocimetry ◽  
Inflammatory Processes ◽  
Injection Molded

Myocardial infarction, also known as a heart attack, is the single leading cause of death in North America. It results from the rupture of an atherosclerotic plaque, which occurs in response to both mechanical stress and inflammatory processes. In order to validate computational models of atherosclerotic coronary arteries, a novel technique for molding realistic compliant phantom featuring injection-molded inclusions and multiple layers has been developed. This transparent phantom allows for particle image velocimetry (PIV) flow analysis and can supply experimental data to validate computational fluid dynamics algorithms and hypothesis.

scholarly journals Improving ozone profile retrieval from spaceborne UV backscatter spectrometers using convergence behaviour diagnostics

2010 ◽  
Vol 3 (6) ◽  
pp. 1555-1568 ◽  
Author(s):  
B. Mijling ◽  
O. N. E. Tuinder ◽  
R. F. van Oss ◽  
R. J. van der A
Keyword(s):  
Cross Sections ◽  
A Priori ◽  
Computation Time ◽  
External Input ◽  
Computational Time ◽  
Ozone Profile ◽  
Global Performance ◽  
Convergence Behaviour ◽  
Low Cloud ◽  
Average Computation Time

Abstract. The Ozone Profile Algorithm (OPERA), developed at KNMI, retrieves the vertical ozone distribution from nadir spectral satellite measurements of back scattered sunlight in the ultraviolet and visible wavelength range. To produce consistent global datasets the algorithm needs to have good global performance, while short computation time facilitates the use of the algorithm in near real time applications. To test the global performance of the algorithm we look at the convergence behaviour as diagnostic tool of the ozone profile retrievals from the GOME instrument (on board ERS-2) for February and October 1998. In this way, we uncover different classes of retrieval problems, related to the South Atlantic Anomaly, low cloud fractions over deserts, desert dust outflow over the ocean, and the intertropical convergence zone. The influence of the first guess and the external input data including the ozone cross-sections and the ozone climatologies on the retrieval performance is also investigated. By using a priori ozone profiles which are selected on the expected total ozone column, retrieval problems due to anomalous ozone distributions (such as in the ozone hole) can be avoided. By applying the algorithm adaptations the convergence statistics improve considerably, not only increasing the number of successful retrievals, but also reducing the average computation time, due to less iteration steps per retrieval. For February 1998, non-convergence was brought down from 10.7% to 2.1%, while the mean number of iteration steps (which dominates the computational time) dropped 26% from 5.11 to 3.79.

AFM-Based Nanoindentation Process: A Comparative Study

2012 ◽  
Author(s):  
Rapeepan Promyoo ◽  
Hazim El-Mounayri ◽  
Kody Varahramyan
Keyword(s):  
Md Simulation ◽  
Computational Models ◽  
Surface Deformation ◽  
Experimental Results ◽  
Computational Time ◽  
Machined Surface ◽  
Indentation Force ◽  
Subsurface Deformation ◽  
Different Types ◽  
Copper Aluminum

Atomic force microscopy (AFM) has been widely used for nanomachining and fabrication of micro/nanodevices. This paper describes the development and validation of computational models for AFM-based nanomachining. Molecular Dynamics (MD) technique is used to model and simulate mechanical indentation at the nanoscale for different types of materials, including gold, copper, aluminum, and silicon. The simulation allows for the prediction of indentation forces at the interface between an indenter and a substrate. The effects of tip materials on machined surface are investigated. The material deformation and indentation geometry are extracted based on the final locations of the atoms, which have been displaced by the rigid tool. In addition to the modeling, an AFM was used to conduct actual indentation at the nanoscale, and provide measurements to which the MD simulation predictions can be compared. The MD simulation results show that surface and subsurface deformation found in the case of gold, copper and aluminum have the same pattern. However, aluminum has more surface deformation than other materials. Two different types of indenter tips including diamond and silicon tips were used in the model. More surface and subsurface deformation can be observed for the case of nanoindentation with diamond tip. The indentation forces at various depths of indentation were obtained. It can be concluded that indentation force increases as depth of indentation increases. Due to limitations on computational time, the quantitative values of the indentation force obtained from MD simulation are not comparable to the experimental results. However, the increasing trends of indentation force are the same for both simulation and experimental results.

scholarly journals Comparison of Solvers Performance for Load Flow Analysis

2019 ◽  
Vol 3 (1) ◽  
pp. 26 ◽  
Author(s):  
Vishnu Sidaarth Suresh
Keyword(s):  
Steady State ◽  
Power System ◽  
Reactive Power ◽  
Flow Analysis ◽  
Steady State Solution ◽  
Load Flow ◽  
State Solution ◽  
Computational Time ◽  
Load Flow Analysis ◽  
Active And Reactive Power

Load flow studies are carried out in order to find a steady state solution of a power system network. It is done to continuously monitor the system and decide upon future expansion of the system. The parameters of the system monitored are voltage magnitude, voltage angle, active and reactive power. This paper presents techniques used in order to obtain such parameters for a standard IEEE – 30 bus and IEEE-57 bus network and makes a comparison into the differences with regard to computational time and effectiveness of each solver

scholarly journals Manning’s roughness coefficient for the Doce River

RBRH ◽  
2018 ◽  
Vol 23 (0) ◽  
Author(s):  
Emmanuel Kennedy da Costa Teixeira ◽  
Márcia Maria Lara Pinto Coelho ◽  
Eber José de Andrade Pinto ◽  
Jéssica Guimarães Diniz ◽  
Aloysio Portugal Maia Saliba
Keyword(s):  
River Flow ◽  
Hydraulic Modeling ◽  
Roughness Coefficient ◽  
Local Approach ◽  
Water Courses ◽  
Time Variations ◽  
The Subject ◽  
Manning’S Roughness Coefficient ◽  
Doce River ◽  
Water Depths

ABSTRACT The Manning’s roughness coefficient is used for various hydraulic modeling. However, the decision on what value to adopt is a complex task, especially when dealing with natural water courses due to the various factors that affect this coefficient. For this reason, most of the studies carried out on the subject adopt a local approach, such as this proposal for the Doce River. Due to the regional importance of this river in Brazil, the objective of this article was to estimate the roughness coefficient of Manning along the river, in order to aid in hydraulic simulations, as well as to discuss the uncertainties and variations associated with this value. For this purpose, information on flow rates and water depths were collected at river flow stations along the river. With this information, the coefficients were calculated using the Manning equation, using the software Canal, and their space-time variations were observed. In addition, it was observed that the uncertainties in flow and depth measurements affect the value of the Manning coefficient in the case studied.

scholarly journals Effective Heuristic Algorithms Solving the Jobshop Scheduling Problem with Release Dates

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1221
Author(s):  
Tao Ren ◽  
Yan Zhang ◽  
Shuenn-Ren Cheng ◽  
Chin-Chia Wu ◽  
Meng Zhang ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Large Scale ◽  
Manufacturing Industry ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Optimal Schedule ◽  
Differential Evolution Algorithm ◽  
Developed Countries ◽  
Productivity Level ◽  
Jobshop Scheduling

Manufacturing industry reflects a country’s productivity level and occupies an important share in the national economy of developed countries in the world. Jobshop scheduling (JSS) model originates from modern manufacturing, in which a number of tasks are executed individually on a series of processors following their preset processing routes. This study addresses a JSS problem with the criterion of minimizing total quadratic completion time (TQCT), where each task is available at its own release date. Constructive heuristic and meta-heuristic algorithms are introduced to handle different scale instances as the problem is NP-hard. Given that the shortest-processing-time (SPT)-based heuristic and dense scheduling rule are effective for the TQCT criterion and the JSS problem, respectively, an innovative heuristic combining SPT and dense scheduling rule is put forward to provide feasible solutions for large-scale instances. A preemptive single-machine-based lower bound is designed to estimate the optimal schedule and reveal the performance of the heuristic. Differential evolution algorithm is a global search algorithm on the basis of population, which has the advantages of simple structure, strong robustness, fast convergence, and easy implementation. Therefore, a hybrid discrete differential evolution (HDDE) algorithm is presented to obtain near-optimal solutions for medium-scale instances, where multi-point insertion and a local search scheme enhance the quality of final solutions. The superiority of the HDDE algorithm is highlighted by contrast experiments with population-based meta-heuristics, i.e., ant colony optimization (ACO), particle swarm optimization (PSO) and genetic algorithm (GA). Average gaps 45.62, 63.38 and 188.46 between HDDE with ACO, PSO and GA, respectively, are demonstrated by the numerical results with benchmark data, which reveals the domination of the proposed HDDE algorithm.

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