Daniel Mora-Melia

Dr. Daniel Mora-Melia

Departamento de Ingeniería y Gestión de la Construcción, Universidad de Talca, Curicó 3340000, Chile
orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 July 2014 in Journal of Water Resources Planning and Management
Verified
Journal Article
Closed access
AMAngela Marchi
Angela Marchi
Elad SalomonsElad Salomons
Elad Salomons
Avi OstfeldAvi Ostfeld
Avi Ostfeld
ZKZoran Kapelan
Zoran Kapelan
ASAngus R. Simpson
Angus R. Simpson
MAMasoud Asadzadeh
Masoud Asadzadeh
The Battle of the Water Networks II (BWN-II) is the latest of a series of competitions related to the design and operation of water distribution systems (WDSs) undertaken within the Water Distribution Systems Analysis (WDSA) Symposium series. The BWN-II problem specification involved a broadly defined design and operation problem for an existing network that has to be upgraded for increased future demands, and the addition of a new development area. The design decisions involved addition of new and parallel pipes, storage, operational controls for pumps and valves, and sizing of backup power supply. Design criteria involved hydraulic, water quality, reliability, and environmental performance measures. Fourteen teams participated in the Battle and presented their results at the 14th Water Distribution Systems Analysis (WDSA 2012) conference in Adelaide, Australia, September 2012. This paper summarizes the approaches used by the participants and the results they obtained. Given the complexity of the BWN-II problem and the innovative methods required to deal with the multi-objective, high dimensional and computationally demanding nature of the problem, this paper represents a snap-shot of state of the art methods for the design and operation of water distribution systems. A general finding of this paper is that there is benefit in using a combination of heuristic engineering experience and sophisticated optimization algorithms when tackling complex real-world water distribution system design problems.Angela Marchi...Angus R. Simpson, Aaron C. Zecchin, Holger R. Maier...Christopher Stokes, Wenyan Wu, Graeme C. Dandy...et al

1 November 2016 in Computers & Operations Research
Verified
Journal Article
Open access
JGJimmy H. Gutiérrez
Jimmy H. Gutiérrez
CACésar A. Astudillo
César A. Astudillo
PBPablo Ballesteros-Perez
Pablo Ballesteros-Perez
DMDaniel Mora-Melia
Daniel Mora-Melia
ACAlfredo Candia-Véjar
Alfredo Candia-Véjar
The Team Formation problem (TFP) has become a well-known problem in the OR literature over the last few years. In this problem, the allocation of multiple individuals that match a required set of skills as a group must be chosen to maximise one or several social positive attributes.Specifically, the aim of the current research is two-fold. First, two new dimensions of the TFP are added by considering multiple projects and fractions of people's dedication. This new problem is named the Multiple Team Formation Problem (MTFP).Second, an optimisation model consisting in a quadratic objective function, linear constraints and integer variables is proposed for the problem. The optimisation model is solved by three algorithms: a Constraint Programming approach provided by a commercial solver, a Local Search heuristic and a Variable Neighbourhood Search metaheuristic. These three algorithms constitute the first attempt to solve the MTFP, being a variable neighbourhood local search metaheuristic the most efficient in almost all cases.Applications of this problem commonly appear in real-life situations, particularly with the current and ongoing development of social network analysis. Therefore, this work opens multiple paths for future research

1 April 2015 in Applied Clay Science
Verified
Journal Article
Closed access
Pedro MuñozPedro Muñoz
Pedro Muñoz
MOMaría Pilar M. Ortiz
María Pilar M. Ortiz
MGManuel Antonio M. Giró
Manuel Antonio M. Giró
DMDaniel Mora-Melia
Daniel Mora-Melia
JRJorge H. Rehbein
Jorge H. Rehbein

21 April 2019 in Urban Water Journal
Verified
Journal Article
Closed access
Vicente S. Fuertes-MiquelVicente S. Fuertes-Miquel
Vicente S. Fuertes-Miquel
Oscar Coronado-HernándezOscar Coronado-Hernández
Oscar Coronado-Hernández
DMDaniel Mora-Melia
Daniel Mora-Melia
PIPedro L. Iglesias-Rey
Pedro L. Iglesias-Rey
Filling and emptying processes are common maneuvers while operating, controlling and managing water pipeline systems. Currently, these operations are executed following recommendations from technical manuals and pipe manufacturers; however, these recommendations have a lack of understanding about the behavior of these processes. The application of mathematical models considering transient flows with entrapped air pockets is necessary because a rapid filling operation can cause pressure surges due to air pocket compressions, while an uncontrolled emptying operation can generate troughs of sub-atmospheric pressure caused by air pocket expansion. Depending on pipe and installation conditions, either situation can produce a rupture of pipe systems. Recently, reliable mathematical models have been developed by different researchers. This paper reviews and compares various mathematical models to simulate these processes. Water columns can be analyzed using a rigid water column model, an elastic water model, or 2D/3D CFD models; air–water interfaces using a piston-flow model or more complex models; air pockets through a polytropic model; and air valves using an isentropic nozzle flow or similar approaches. This work can be used as a starting point for planning filling and emptying operations in pressurized pipelines. Uncertainties of mathematical models of two-phases flow concerning to a non-variable friction factor, a polytropic coefficient, an air pocket sizes and an air valve behavior are identified.

1 December 2017 in Automation in Construction
Verified
Journal Article
Open access
PBPablo Ballesteros-Perez
Pablo Ballesteros-Perez
YRYonatan Alexis Rojas-Céspedes
Yonatan Alexis Rojas-Céspedes
WHWill Hughes
Will Hughes
SKShabnam Kabiri
Shabnam Kabiri
EPEugenio Pellicer
Eugenio Pellicer
MCMaría Luisa del Campo_Hitschfeld
María Luisa del Campo_Hitschfeld

8 August 2015 in Water Resources Management
Verified
Journal Article
Open access
PDF file
DMDaniel Mora-Melia
Daniel Mora-Melia
PIPedro L. Iglesias-Rey
Pedro L. Iglesias-Rey
F. Javier Martínez-SolanoF. Javier Martínez-Solano
F. Javier Martínez-Solano
PBPablo Ballesteros-Perez
Pablo Ballesteros-Perez
The pipe sizing of water networks via evolutionary algorithms is of great interest because it allows the selection of alternative economical solutions that meet a set of design requirements. However, available evolutionary methods are numerous, and methodologies to compare the performance of these methods beyond obtaining a minimal solution for a given problem are currently lacking. A methodology to compare algorithms based on an efficiency rate (E) is presented here and applied to the pipe-sizing problem of four medium-sized benchmark networks (Hanoi, New York Tunnel, GoYang and R-9 Joao Pessoa). E numerically determines the performance of a given algorithm while also considering the quality of the obtained solution and the required computational effort. From the wide range of available evolutionary algorithms, four algorithms were selected to implement the methodology: a PseudoGenetic Algorithm (PGA), Particle Swarm Optimization (PSO), a Harmony Search and a modified Shuffled Frog Leaping Algorithm (SFLA). After more than 500,000 simulations, a statistical analysis was performed based on the specific parameters each algorithm requires to operate, and finally, E was analyzed for each network and algorithm. The efficiency measure indicated that PGA is the most efficient algorithm for problems of greater complexity and that HS is the most efficient algorithm for less complex problems. However, the main contribution of this work is that the proposed efficiency ratio provides a neutral strategy to compare optimization algorithms and may be useful in the future to select the most appropriate algorithm for different types of optimization problems.