scholarly journals Urban Drainage Network Rehabilitation Considering Storm Tank Installation and Pipe Substitution

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 515 ◽  
Author(s):  
Ulrich Ngamalieu-Nengoue ◽  
Pedro Iglesias-Rey ◽  
F. Martínez-Solano ◽  
Daniel Mora-Meliá ◽  
Juan Saldarriaga Valderrama
Keyword(s):  
Cost Optimization ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Optimization Method ◽  
Drainage Network ◽  
Storm Water Management Model ◽  
Drainage Networks ◽  
Combined Use ◽  
The City ◽  
Swmm Model

The drainage networks of our cities are currently experiencing a growing increase in runoff flows, caused mainly by the waterproofing of the soil and the effects of climate change. Consequently, networks originally designed correctly must endure floods with frequencies much higher than those considered in the design phase. The solution of such a problem is to improve the network. There are several ways to rehabilitate a network: conduit substitution as a former method or current methods such as storm tank installation or combined use of conduit substitution and storm tank installation. To find an optimal solution, deterministic or heuristic optimization methods are used. In this paper, a methodology for the rehabilitation of these drainage networks based on the combined use of the installation of storm tanks and the substitution of some conduits of the system is presented. For this, a cost-optimization method and a pseudo-genetic heuristic algorithm, whose efficiency has been validated in other fields, are applied. The Storm Water Management Model (SWMM) model for hydraulic analysis of drainage and sanitation networks is used. The methodology has been applied to a sector of the drainage network of the city of Bogota in Colombia, showing how the combined use of storm tanks and conduits leads to lower cost rehabilitation solutions.

scholarly journals Inclusion of Hydraulic Controls in Rehabilitation Models of Drainage Networks to Control Floods

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 514
Author(s):  
Leonardo Bayas-Jiménez ◽  
F. Javier Martínez-Solano ◽  
Pedro L. Iglesias-Rey ◽  
Daniel Mora-Melia ◽  
Vicente S. Fuertes-Miquel
Keyword(s):  
Genetic Algorithm ◽  
Drainage System ◽  
Optimal Solution ◽  
Hydraulic Control ◽  
Drainage Systems ◽  
Storm Water Management Model ◽  
Drainage Networks ◽  
Extreme Rain ◽  
Rain Events ◽  
The Cost

A problem for drainage systems managers is the increase in extreme rain events that are increasing in various parts of the world. Their occurrence produces hydraulic overload in the drainage system and consequently floods. Adapting the existing infrastructure to be able to receive extreme rains without generating consequences for cities’ inhabitants has become a necessity. This research shows a new way to improve drainage systems with minimal investment costs, using for this purpose a novel methodology that considers the inclusion of hydraulic control elements in the network, the installation of storm tanks and the replacement of pipes. The presented methodology uses the Storm Water Management Model for the hydraulic analysis of the network and a modified Genetic Algorithm to optimize the network. In this algorithm, called the Pseudo-Genetic Algorithm, the coding of the chromosomes is integral and has been used in previous studies of hydraulic optimization. This work evaluates the cost of the required infrastructure and the damage caused by floods to find the optimal solution. The main conclusion of this study is that the inclusion of hydraulic controls can reduce the cost of network rehabilitation and decrease flood levels.

Design Optimization Method for MR-Brake Actuators

2011 ◽  
Author(s):  
Ozan G. Erol ◽  
Hakan Gurocak ◽  
Berk Gonenc
Keyword(s):  
Optimal Solution ◽  
Volume Ratio ◽  
Optimization Methods ◽  
Search Space ◽  
Optimization Method ◽  
Friction Torque ◽  
Element Analysis ◽  
Taguchi Design Of Experiments ◽  
Variable Friction ◽  
Electronically Controllable

MR-brakes work by varying viscosity of a magnetorheological (MR) fluid inside the brake. This electronically controllable viscosity leads to variable friction torque generated by the actuator. A properly designed MR-brake can have a high torque-to-volume ratio which is quite desirable for an actuator. However, designing an MR-brake is a complex process as there are many parameters involved in the design which can affect the size and torque output significantly. The contribution of this study is a new design approach that combines the Taguchi design of experiments method with parameterized finite element analysis for optimization. Unlike the typical multivariate optimization methods, this approach can identify the dominant parameters of the design and allows the designer to only explore their interactions during the optimization process. This unique feature reduces the size of the search space and the time it takes to find an optimal solution. It normally takes about a week to design an MR-brake manually. Our interactive method allows the designer to finish the design in about two minutes. In this paper, we first present the details of the MR-brake design problem. This is followed by the details of our new approach. Next, we show how to design an MR-brake using this method. Prototype of a new brake was fabricated. Results of experiments with the prototype brake are very encouraging and are in close agreement with the theoretical performance predictions.

Research for Combined Drainage Networks in Chuanfang River Basin of Kunming City Based on SWMM

2012 ◽  
Vol 170-173 ◽  
pp. 2380-2385
Author(s):  
Xiao Min Zhu ◽  
Bing Huang ◽  
Shu Dong Wang ◽  
Jin Long Zheng ◽  
Bo Yao ◽  
...  
Keyword(s):  
River Basin ◽  
Drainage System ◽  
Sewage Water ◽  
Management Model ◽  
Peak Time ◽  
Drainage Network ◽  
Efficiency Coefficient ◽  
Storm Water Management Model ◽  
Drainage Networks ◽  
Water Base

A model for simulating combined drainage networks in Chuangfang river basin of Kunming City based on the Storm Water Management Model was established. The type and period of using water base on residential area, marketplace, school area, and guesthouse area Kunming city were introduced into the model, and their infection for drainage system was research. The results show that simulation results of two outlets flow have coherence with monitoring data based two typical rainfall in Kunming, the Nash-Sutcliffe efficiency coefficient is 0.71-0.82. And the model can be using analyze ‘bottleneck’ nodes and restricting conduits, simulating the running status of drainage network of combined drainage at raining and draining peak time of sewage water. The research provide strong technical support for rebuild drainage network in Kunming or other city.

scholarly journals Compensatory alternatives for flooding control in urban areas with tidal influence in Recife - PE

RBRH ◽  
2017 ◽  
Vol 22 (0) ◽  
Author(s):  
Marcos Antonio Barbosa da Silva Junior ◽  
◽  
Simone Rosa da Silva ◽  
Jaime Joaquim da Silva Pereira Cabral ◽  
Keyword(s):  
Urban Areas ◽  
Drainage System ◽  
Infiltration Rate ◽  
Urban Drainage ◽  
Drainage Network ◽  
Storm Water Management Model ◽  
Recurrence Period ◽  
Detention Tank ◽  
Swmm Model ◽  
Two Alternatives

ABSTRACT This paper presents a study of compensatory alternatives in urban drainage, using SWMM model (Storm Water Management Model), for the critical point of flooding in an urban area and vulnerable to tide fluctuations, located in Recife. For this, we used the registered information of the micro-drainage network and defined the parameters and variables required for modeling, such as: the subareas of contribution to the drainage system, indicating the percentage of soil waterproofing, equivalent width, slope, and infiltration rate; project rain; and tide curve. Two alternatives were simulated after the model has been calibrated. The first, which is an adaptation of the drainage network, presented maximum reductions in the volume of flooding of 37% for the events with recurrence period of two years and of 58% for five years of recurrence. The second, based on the deployment of a detention tank in the existing network, presented satisfactory results for the event of two years and reduced approximately 38% for events of five years. The results showed that there was a reduction in the area of flooding for the conditions simulated. However, the first alternative would not solve the local flooding problems, it would only attenuate and would increase the overload of the drainage pipes downstream of the modified system, while the second alternative could solve the problem of flooding, with the occurrence of an event of two years.

S-Metaheuristics Approach to Solve Traveling Salesman Problem

Jurnal METRIS ◽  
2020 ◽  
Vol 21 (02) ◽  
pp. 111-115
Author(s):  
Agung Chandra ◽  
Aulia Naro
Keyword(s):  
State Of The Art ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Optimization Method ◽  
Complex Problem ◽  
Traveling Salesman ◽  
Solution Technique ◽  
Metaheuristic Algorithm ◽  
Shortest Distance ◽  
Single Solution

Metaheuristic algorithm is a state of the art optimization method which suitable for solving large and complex problem. Single solution technique – Smetaheuristic is one of metaheuristic algorithm that search near optimal solution and known as exploitation based. The research conducted to seek a better solution for deliverying goods to 29 destinations by comparing two well known optimization methods that can produce the shortest distance: Simulated Annealing (SA) and Tabu Search (TS). The result shows that TS – 107 KM has a shorter distance than SA – 119 KM. Exploration based method should be conducted for next research to produce information in which one is a better method

Comparative Study of Different Optimization Algorithms Used for Obtaining Diesel-Biodiesel Blends

2019 ◽  
Vol 70 (6) ◽  
pp. 1893-1896
Author(s):  
Stefan Sandru ◽  
Ion Onutu
Keyword(s):  
Artificial Intelligence ◽  
Genetic Algorithms ◽  
Linear Programming ◽  
Classical Method ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Optimization Method ◽  
Biodiesel Blends ◽  
Dual Simplex ◽  
Linear Programming Problems

The purpose of this paper is to compare two different optimization methods, used in acquiring diesel-biodiesel blends. There were used five types of samples in order to enable the optimization of the final blend: there were chosen two types of hydrofined diesel fuel and there were synthesized three original types of biodiesel. The first optimization method used, dual simplex, is a classical method being used in solving linear programming problems. The second optimization method, the genetic algorithms, falls in the type of artificial intelligence algorithms, being an evolutionary method used when the problem requires searching an optimal solution in a great variety of valid solutions.

scholarly journals Architectural Models Enabled Dynamic Optimization for System-of-Systems Evolution

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Zhemei Fang ◽  
Xiaozhou Zhou ◽  
Ani Song
Keyword(s):  
Dynamic Optimization ◽  
Systems Engineering ◽  
Conceptual Models ◽  
Mathematical Optimization ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Optimization Method ◽  
System Of Systems ◽  
Architectural Representation ◽  
Architecture Framework

System of Systems (SoS) is designed to deliver value to participant stakeholders in a dynamic and uncertain environment where new systems are added and current systems are removed continuously and on their own volition. This requires effective evolution management at the SoS architectural level with adequate support of process, methods, and tools. This paper follows the principle of Model-Based Systems Engineering (MBSE) and develops a holistic framework integrating MBSE conceptual representations and approximate dynamic programming (ADP) to support the SoS evolution. The conceptual models provide a common architectural representation to improve communication between various decision makers while the dynamic optimization method suggests evolution planning decisions from the analytical perspective. The Department of Defense Architecture Framework (DoDAF) models using Systems Modeling Language (SysML) are used as MBSE artifacts to connect with ADP modeling elements through DoDAF metamodels to increase information traceability and reduce unnecessary information loss. Using a surface warfare SoS as an example, this paper demonstrates and explains the procedures of developing DoDAF models, mapping DoDAF models to ADP elements, formulating ADP formulation, and generating evolutionary decisions. The effectiveness of using ADP in supporting evolution to achieve a near-optimal solution that can maximize the SoS capability over time is illustrated by comparing ADP solution to other alternative solutions. The entire framework also sheds light on bridging the DoDAF-based conceptual models and other mathematical optimization methods.

scholarly journals The Hybrid Invasive Weed Optimization-Shuffled Frog-leaping Algorithm Applied to Optimal Design of Frame Structures

2019 ◽  
Author(s):  
Ali Kaveh ◽  
Siamak Talatahari ◽  
Nima Khodadadi
Keyword(s):  
Optimization Algorithm ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Optimization Method ◽  
Population Based ◽  
Frame Structures ◽  
Invasive Weed Optimization ◽  
Shuffled Frog Leaping Algorithm ◽  
Invasive Weed ◽  
Shuffled Frog Leaping

In this article, an efficient hybrid optimization algorithm based on invasive weed optimization algorithm and shuffled frog-leaping algorithm is utilized for optimum design of skeletal frame structures. The shuffled frog-leaping algorithm is a population-based cooperative search metaphor inspired by natural memetic, and the invasive weed optimization algorithm is an optimization method based on dynamic growth of weeds colony. In the proposed algorithm, shuffled frog-leaping algorithm works to find optimal solution region rapidly, and invasive weed optimization performs the global search. Different benchmark frame structures are optimized using the new hybrid algorithm. Three design examples are tested using the new method. This algorithm converges to better or at least the same solutions compared the utilized methods with a smaller number of analyses. The outcomes are compared to those obtained previously using other recently developed meta-heuristic optimization methods.

scholarly journals Mobile Phone Usage Detection by ANN Trained with a Metaheuristic Algorithm †

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3110 ◽  
Author(s):  
Efrain Mendez ◽  
Alexandro Ortiz ◽  
Pedro Ponce ◽  
Juan Acosta ◽  
Arturo Molina
Keyword(s):  
Mobile Phone ◽  
Logic Gate ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Optimization Method ◽  
Computational Effort ◽  
Training Process ◽  
Nano Sensors ◽  
Mobile Phone Usage ◽  
Smart Mobile Phone

Artificial neural networks (ANN) are widely used to classify high non-linear systems by using a set of input/output data. Moreover, they are trained using several optimization methodologies and this paper presents a novel algorithm for training ANN through an earthquake optimization method. Usually, gradient optimization method is implemented for the training process, with perhaps the large number of iterations leading to slow convergence, and not always achieving the optimal solution. Since metaheuristic optimization methods deal with searching for weight values in a broad optimization space, the training computational effort is reduced and ensures an optimal solution. This work shows an efficient training process that is a suitable solution for detection of mobile phone usage while driving. The main advantage of training ANN using the Earthquake Algorithm (EA) lies in its versatility to search in a fine or aggressive way, which extends its field of application. Additionally, a basic example of a linear classification is illustrated using the proposal-training method, so the number of applications could be expanded to nano-sensors, such as reversible logic circuit synthesis in which a genetic algorithm had been implemented. The fine search is important for the studied logic gate emulation due to the small searching areas for the linear separation, also demonstrating the convergence capabilities of the algorithm. Experimental results validate the proposed method for smart mobile phone applications that also can be applied for optimization applications.

Research on Engineering Project Time-Cost Optimization Based on Particle Swarm Optimization

2011 ◽  
Vol 55-57 ◽  
pp. 1683-1686
Author(s):  
Ting Wang ◽  
Li Feng Li
Keyword(s):  
Particle Swarm Optimization ◽  
Programming Model ◽  
Cost Optimization ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Optimization Method ◽  
Time Cost ◽  
Engineering Project ◽  
Swarm Optimization ◽  
Nonlinear Relation

In order to reasonably reduce the cost of project, and reduce the duration of project, the engineering project time–cost must be optimized. The paper concludes the project time - cost optimal solution, by establishing programming model of project time–cost nonlinear relation, and using particle swarm optimization algorithm to achieve progress optimization. And using an example shows that this optimization method is the feasibility and practicability in solving engineering project time–cost of nonlinear optimization.

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