scholarly journals Parameter estimation in distributed hydrological modelling: comparison of global and local optimisation techniques

2007 ◽  
Vol 38 (4-5) ◽  
pp. 451-476 ◽  
Author(s):  
R.-S. Blasone ◽  
H. Madsen ◽  
Dan Rosbjerg
Keyword(s):  
Computational Time ◽  
Fully Integrated ◽  
Distributed Models ◽  
Shuffled Complex Evolution ◽  
Model Response ◽  
Physically Based ◽  
Gradient Based ◽  
Complex Models ◽  
Global And Local ◽  
Local Optimisation

Much research has been spent in the last three decades in developing more effective and efficient automatic calibration procedures and in demonstrating their applicability to hydrological problems. Several problems have emerged when applying these procedures to calibration of conceptual rainfall–runoff and groundwater (GW) models, such as computational time, large number of calibration parameters, parameter identifiability, model response surface complexity, handling of multiple objectives and parameter equifinality. All these are expected to be much more severe for more complex models, for which comprehensive calibration studies have not so far been conducted. The scope of this paper is to investigate the performance of a global and a local optimisation technique, respectively, the Shuffled Complex Evolution algorithm and the gradient-based Gauss–Marquard–Levenberg algorithm, in calibration of physically based distributed models of different complexity. The models considered are a steady-state GW model, a transient GW model and a fully integrated model of the same catchment. The calibration is conducted in a multi-objective framework where two different aspects of the model response, the simulated runoff and the groundwater elevation are aggregated and simultaneously optimised. Different aggregated objective functions are used to give different weights to the calibration criteria. The results of the calibration procedures are compared in terms of effectiveness and efficiency and demonstrate the different performance of the methods. Moreover, a combination of the global and local techniques is investigated as an attempt to exploit the advantages of both procedures, while overcoming their drawbacks.

Overview of Path-Planning and Obstacle Avoidance Algorithms for UAVs: A Comparative Study

2018 ◽  
Vol 06 (02) ◽  
pp. 95-118 ◽  
Author(s):  
Mohammadreza Radmanesh ◽  
Manish Kumar ◽  
Paul H. Guentert ◽  
Mohammad Sarim
Keyword(s):  
Path Planning ◽  
Comparative Study ◽  
Operating Conditions ◽  
Computational Time ◽  
Safe Operation ◽  
Sense And Avoid ◽  
Planning Algorithms ◽  
And Control ◽  
Global And Local ◽  
Further Development

Unmanned aerial vehicles (UAVs) have recently attracted the attention of researchers due to their numerous potential civilian applications. However, current robot navigation technologies need further development for efficient application to various scenarios. One key issue is the “Sense and Avoid” capability, currently of immense interest to researchers. Such a capability is required for safe operation of UAVs in civilian domain. For autonomous decision making and control of UAVs, several path-planning and navigation algorithms have been proposed. This is a challenging task to be carried out in a 3D environment, especially while accounting for sensor noise, uncertainties in operating conditions, and real-time applicability. Heuristic and non-heuristic or exact techniques are the two solution methodologies that categorize path-planning algorithms. The aim of this paper is to carry out a comprehensive and comparative study of existing UAV path-planning algorithms for both methods. Three different obstacle scenarios test the performance of each algorithm. We have compared the computational time and solution optimality, and tested each algorithm with variations in the availability of global and local obstacle information.

scholarly journals Surrogate Models Applied to Optimized Organic Rankine Cycles

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8456
Author(s):  
Icaro Figueiredo Vilasboas ◽  
Victor Gabriel Sousa Fagundes dos Santos ◽  
Armando Sá Ribeiro Júnior ◽  
Julio Augusto Mendes da Silva
Keyword(s):  
Polynomial Regression ◽  
Surrogate Models ◽  
Industrial Plant ◽  
Computational Time ◽  
Working Fluid ◽  
Or Efficiency ◽  
Specific Cost ◽  
Complex Models ◽  
Organic Rankine Cycles ◽  
Main Components

Global optimization of industrial plant configurations using organic Rankine cycles (ORC) to recover heat is becoming attractive nowadays. This kind of optimization requires structural and parametric decisions to be made; the number of variables is usually high, and some of them generate disruptive responses. Surrogate models can be developed to replace the main components of the complex models reducing the computational requirements. This paper aims to create, evaluate, and compare surrogates built to replace a complex thermodynamic-economic code used to indicate the specific cost (US$/kWe) and efficiency of optimized ORCs. The ORCs are optimized under different heat sources conditions in respect to their operational state, configuration, working fluid and thermal fluid, aiming at a minimal specific cost. The costs of 1449.05, 1045.24, and 638.80 US$/kWe and energy efficiencies of 11.1%, 10.9%, and 10.4% were found for 100, 1000, and 50,000 kWt of heat transfer rate at average temperature of 345 °C. The R-square varied from 0.96 to 0.99 while the number of results with error lower than 5% varied from 88% to 75% depending on the surrogate model (random forest or polynomial regression) and output (specific cost or efficiency). The computational time was reduced in more than 99.9% for all surrogates indicated.

Three-Dimensional Elastic Analysis of a Structure with Holes Using Accelerated Coupling-Matrix-Free Iterative s-Version FEM

2018 ◽  
Vol 15 (05) ◽  
pp. 1850036 ◽  
Author(s):  
Yasunori Yusa ◽  
Hiroshi Okada ◽  
Yosuke Yumoto
Keyword(s):  
Search Algorithm ◽  
Three Dimensional ◽  
Convergence Acceleration ◽  
Computational Time ◽  
Elastic Analysis ◽  
Coupling Matrix ◽  
Acceleration Techniques ◽  
Key Techniques ◽  
Global And Local ◽  
Matrix Free

Some improvements of the coupling-matrix-free iterative s-version finite element method (FEM) to shorten its computational time are proposed. Then, the proposed method is applied to three-dimensional stress concentration problems. For sufficiently small computational time for practical use, two key techniques are introduced. First, the iteration is accelerated drastically by using the proposed convergence acceleration techniques. Secondly, stress transfers between global and local meshes are accelerated considerably by a bucket search algorithm. The proposed method was more than one hundred times faster than the straightforward algorithm of the coupling-matrix-free iterative s-version FEM.

scholarly journals Calibration of physically based models: back to basics?

2003 ◽  
Vol 5 (4) ◽  
pp. 233-244 ◽  
Author(s):  
Vincent Guinot ◽  
Philippe Gourbesville
Keyword(s):  
Hydrological Model ◽  
Flash Flood ◽  
Model Parameters ◽  
Model Structure ◽  
Ungauged Catchments ◽  
Model Response ◽  
Physically Based ◽  
Physically Based Models ◽  
Extreme Hydrological Events ◽  
Main Factor

The modelling of extreme hydrological events often suffers from a lack of available data. Physically based models are the best available modelling option in such situations, as they can in principle provide answers about the behaviour of ungauged catchments provided that the geometry and the forcings are known with sufficient accuracy. The need for calibration is therefore limited. In some situations, calibration (seen as adjusting the model parameters so that they fit the calculation as closely to the measurements as possible) is impossible. This paper presents such a situation. The MIKE SHE physically based hydrological model is used to model a flash flood over a medium-sized catchment of the Mediterranean Alps (2820 km2). An examination of a number of modelling alternatives shows that the main factor of uncertainty in the model response is the model structure (what are the dominant processes). The second most important factor is the accuracy with which the catchment geometry is represented in the model. The model results exhibit very little sensitivity to the model parameters, and therefore calibration of these parameters is found to be useless.

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 Comparison of Two Software Tools for Damage Identification: Gradient-Based vs. Case-Based Approach

2005 ◽  
Vol 293-294 ◽  
pp. 103-110
Author(s):  
Przemysław Kołakowski ◽  
Luis E. Mujica ◽  
Josep Vehí
Keyword(s):  
Damage Identification ◽  
Element Model ◽  
Identification Problem ◽  
Optimization Method ◽  
Software Tools ◽  
Similarity Criteria ◽  
Computational Time ◽  
Case Based Reasoning ◽  
Gradient Based ◽  
Case Based

Two alternative software tools for damage identification are presented. The first tool, developed on the basis of the Virtual Distortion Method (VDM), takes advantage of an analytical formulation of the damage identification problem. Consequently, gradient-based optimization method is applied to solve the resulting dynamic inverse problem in time domain. Finite element model of the structure is necessary for the VDM approach. The second tool utilizes the Case-Based Reasoning (CBR) for damage identification. This method consists in i) extracting principal features of the response signal by wavelet transform, ii) creating a base of representative damage cases, iii) organizing and training the base by neural networks, and finally iv) retrieving and adapting a new case (possible damage) by similarity criteria. Basic description of both approaches is given. A comparison of numerical effectiveness, in terms of accuracy and computational time, is provided for a simple beam structure. Advantages and weaknesses of each approach are highlighted.

Fluid Dynamic Design Optimization of the Intake of a Small Turbojet

2006 ◽  
Author(s):  
Riccardo Amirante ◽  
Luciano A. Catalano ◽  
Andrea Dadone ◽  
Vito S. E. Daloiso ◽  
Dario Manodoro
Keyword(s):  
Design Optimization ◽  
Electricity Generation ◽  
Fluid Dynamic ◽  
Optimization Procedure ◽  
Black Box ◽  
High Load ◽  
Computational Time ◽  
Design Criteria ◽  
Dynamic Design ◽  
Gradient Based

This paper proposes an efficient gradient-based optimization procedure for black-box simulation codes and its application to the fluid-dynamic design optimization of the intake of a small-size turbojet, at high load and zero flight speed. Two simplified design criteria have been considered, which avoid to simulate the flow in any turbojet components other than the intake itself. Both design optimizations have been completed in a computational time corresponding to that required by eight flow analyses and have provided almost coincident optimal profiles for the intake. The flow fields computed with the original and the optimal profiles are compared to demonstrate the flow pattern improvements that can be theoretically achieved. Finally, the original and the optimal profiles have been mounted on the same small-size turbojet and experimentally tested, to assess the resulting improvements in terms of overall performances. All numerical and experimental results can be obviously extended to the intake of a microturbine for electricity generation.

Sensitivity analysis and auto-calibration of an integral dynamic model for river water quality

2002 ◽  
Vol 45 (9) ◽  
pp. 325-332 ◽  
Author(s):  
A. van Griensven ◽  
A. Francos ◽  
W. Bauwens
Keyword(s):  
Sensitivity Analysis ◽  
Assessment Tool ◽  
Calibration Procedure ◽  
Distributed Model ◽  
Shuffled Complex Evolution ◽  
Physically Based ◽  
High Pollution ◽  
Individual Variables ◽  
Weighting Problem ◽  
The One

ESWAT – Extended Soil and Water Assessment Tool – was developed to allow for an integral modelling of the water quantity and quality processes in river basins. ESWAT is a physically based, semi-distributed model, with a moderate-to-large number of parameters and input and output variables (depending on the desegregation scheme). An auto-calibration procedure was implemented for the optimisation of the process parameters. The procedure is based on a new approach for multi-objective calibration and incorporates the algorithms of the Shuffled Complex Evolution Method. The optimisation uses a global optimisation criterion, whereby several output variables can be taken into account simultaneously. A statistical method enables the aggregation of the objective functions for individual variables, hereby avoiding the weighting problem. To select the important parameters for the optimisation, a sensitivity analysis precedes the calibration. The latter analysis is based on the One-factor-At-a-Time (OAT) design approach. The sensitivity analysis and the calibration procedure are applied to the river Dender in Belgium. The river is characterised by high pollution loads and long residence times in summer periods.

Constrained multi-objective aerofoil design using a multi-level optimisation strategy

2015 ◽  
Vol 119 (1217) ◽  
pp. 833-854
Author(s):  
L. Cameron ◽  
J. Early ◽  
R. McRoberts ◽  
M. Price
Keyword(s):  
Leading Edge ◽  
Boundary Layer Transition ◽  
Layer Transition ◽  
Multi Objective ◽  
Trade Offs ◽  
Novel Approach ◽  
Design Variables ◽  
Business Jet ◽  
Global And Local ◽  
Local Optimisation

AbstractA novel approach for the multi-objective design optimisation of aerofoil profiles is presented. The proposed method aims to exploit the relative strengths of global and local optimisation algorithms, whilst using surrogate models to limit the number of computationally expensive CFD simulations required. The local search stage utilises a re-parameterisation scheme that increases the flexibility of the geometry description by iteratively increasing the number of design variables, enabling superior designs to be generated with minimal user intervention. Capability of the algorithm is demonstrated via the conceptual design of aerofoil sections for use on a lightweight laminar flow business jet. The design case is formulated to account for take-off performance while reducing sensitivity to leading edge contamination. The algorithm successfully manipulates boundary layer transition location to provide a potential set of aerofoils that represent the trade-offs between drag at cruise and climb conditions in the presence of a challenging constraint set. Variations in the underlying flow physics between Pareto-optimal aerofoils are examined to aid understanding of the mechanisms that drive the trade-offs in objective functions.

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