STUDY OF SENSITIVITY OF THE PARAMETERS OF A GENETIC ALGORITHM FOR DESIGN OF WATER DISTRIBUTION NETWORKS

The Genetic Algorithms (GAs) are a technique of optimization used for water distribution networks design. This work has been made with a modified pseudo genetic algorithm (PGA), whose main variation with a classical GA is a change in the codification of the chromosomes, which is made of numerical form instead of the binary codification. This variation entails a series of special characteristics in the codification and in the definition of the operations of mutation and crossover. Initially, the work displays the results of the PGA on a water network studied in the literature. The results show the kindness of the method. Also is made a statistical analysis of the obtained solutions. This analysis allows verifying the values of mutation and crossing probability more suitable for the proposed method. Finally, in the study of the analyzed water supply networks the concept of reliability in introduced. This concept is essential to understand the validity of the obtained results. The second part, starting with values optimized for the probability of crossing and mutation, the influence of the population size is analyzed in the final solutions on the network of Hanoi, widely studied in the bibliography. The aim is to find the most suitable configuration of the problem, so that good solutions are obtained in the less time

Exact skeletonization method in water distribution systems for hydraulic and quality models

[EN] A mathematical model is a powerful tool for simulating different scenarios that occur in a water distribution network without making physical experimentation. According to the objectives, a model can be classified into three categories: layout, design and operation. Furthermore, the level of detail is strongly related to the objective that the model tries to achieve. However, bigger amount of information does not mean better accuracy. For example, a fully detailed mathematical model of the network would lead to know every single connection. Usually, this information is so difficult to compile as imprecise. Therefore, one of the most important stages in elaborating a model consists of the model simplification, also known as skeletonization. During the works made for model skeletonization some assumptions are made. Most of the times, these assumptions may produce significant errors. Among the different techniques for network skeletonization, series pipe removal is one of the most used. It consists of replacing several adjacent pipes with a single one which must present the same head losses than the pipes being substituted. When there are no intermediate consumptions the problem has been effectively solved. The problem arises when a demand appears in one of the pipes being removed. It has been demonstrated that methods which assume constant roughness coefficients (either Hazen-Williams or Darcy equations) produce errors in the head losses. These errors may be even higher if travel time is included as a restriction, for example in water quality models. This paper reviews the most common techniques for serial pipes association. The error will be evaluated in both hydraulic and quality models. Finally, a method for exact substitution of serial pipes with intermediate demands is proposed. This method imposes two restrictions (head losses and travel time) and gives exact results when the flow direction is known. The method is tested with an example that highlights the results.This work was supported by the projects “OPERAGUA”, (Project DPI2009-13674, Spain) and by the Program Initiation into research (Project 11140128) of the Comisión Nacional de Invest. Científica y Tecnológica, Chile.Martínez-Solano, FJ.; Iglesias Rey, PL.; Mora Meliá, D.; Fuertes-Miquel, VS. (2017). Exact skeletonization method in water distribution systems for hydraulic and quality models. Procedia Engineering. 186:286-293. https://doi.org/10.1016/j.proeng.2017.03.246S28629318

Design of water distribution networks using a pseudo-genetic algorithm and sensitivity of genetic operators

[EN] Genetic algorithms (GA) are optimization techniques that are widely used in the design of water distribution networks. One of the main disadvantages of GA is positional bias, which degrades the quality of the solution. In this study, a modified pseudo-genetic algorithm (PGA) is presented. In a PGA, the coding of chromosomes is performed using integer coding; in a traditional GA, binary coding is utilized. Each decision variable is represented by only one gene. This variation entails a series of special characteristics in the definition of mutation and crossover operations. Some benchmark networks have been used to test the suitability of a PGA for designing water distribution networks. More than 50,000 simulations were conducted with different sets of parameters. A statistical analysis of the obtained solutions was also performed. Through this analysis, more suitable values of mutation and crossover probabilities were discovered for each case. The results demonstrate the validity of the method. Optimum solutions are not guaranteed in any heuristic method. Hence, the concept of a good solution is introduced. A good solution is a design solution that does not substantially exceed the optimal solution that is obtained from the simulations. This concept may be useful when the computational cost is critical. The main conclusion derived from this study is that a proper combination of population and crossover and mutation probabilities leads to a high probability that good solutions will be obtained[This work was supported by the project DPI2009-13674 (OPERAGUA) of the Direccion General de Investigacion y Gestion del Plan Nacional de I + D + I del Ministerio de Ciencia e Innovacion, Spain.Mora Meliá, D.; Iglesias Rey, PL.; Martínez-Solano, FJ.; Fuertes Miquel, VS. (2013). Design of water distribution networks using a pseudo-genetic algorithm and sensitivity of genetic operators. Water Resources Management. 27(12):4149-4162. https://doi.org/10.1007/s11269-013-0400-6S414941622712Alperovits E, Shamir U (1977) Design of optimal water distribution systems. Water Resour Res 13(6):885–900Balla M, Lingireddy S (2000) Distributed genetic algorithm model on network of personal computers. J Comput Civ Eng 14(3):199–205. doi: 10.1061/(ASCE)0887-3801(2000)14:3(199)Baños R, Gil C, Agulleiro JI, Reca J (2007) A memetic algorithm for water distribution network design. Advances in Soft Computing 39:279–289. doi: 10.1007/978-3-540-70706-6_26Cisty M (2010) Hybrid genetic algorithm and linear programming method for least-cost design of water distribution systems. Water Resour Manage 24(1):1–24. doi: 10.1007/s1269-009-9434-1Chung G, Lansey K (2008) Application of the shuffled frog leaping algorithm for the optimization of a general large-scale in a watersupply system. Water Resour Manage 23:797–823. doi: 10.1007/s11269-008-9300-6Cunha MC, Sousa J (1999) Water distribution network design optimization: simulated annealing approach. J Water Resour Plann Manage 125(4):215–221. doi: 10.1061/(ASCE)0733-9496(1999)125:4(215)Eusuff M, Lansey K (2003) Optimization of water distribution network design using the shuffled frog leaping algorithm. J Water Resour Plann Manage 129(3):210–225. doi: 10.1061/(ASCE)0733-9496(2003)129:3(210)Fujiwara O, Khang DB (1990) A two phase decomposition method for optimal design of looped water distribution network. Water Resour Res 26(4):539–549. doi: 10.1029/WR026i004p00539Geem ZW (2006) Optimal cost design of water distribution networks using harmony search. Eng Optimiz 38(3):259–277. doi: 10.1080/03052150500467430Goldberg DE, Kuo CH (1987) Genetic algorithms in pipeline optimization. J Comput Civil Eng 1(2):128–141. doi: 10.1061/(ASCE)0887-3801(1987)1:2(128)Goulter IC, Morgan DR (1985) An integrated approach to the layout and design of water distribution systems. Civil Eng Syst 2(2):104–113. doi: 10.1080/02630258508970389Halhal D, Walters GA, Ouazar D, Savic DA (1997) Water network rehabilitation with structured messy genetic algorithms. J Water Resour Plann Manage 123(3):137–147. doi: 10.1061/(ASCE)0733-9496(1997)123:3(137)Iglesias-Rey PL, Martínez-Solano FJ, Mora-Meliá D, Ribelles-Aguilar JV (2012) The battle water networks II: Combination of meta-heuristic techniques with the concept of setpoint function in water network optimization algorithms. In: Proc. 14th Water Distribution Systems Analysis symposium (WDSA), Engineers Australia, Adelaide, AustraliaJin YX, Cheng HZ, Yan J, Zhang L (2007) New discrete method for particle swarm optimization and its application in transmission network expansion planning. Electr Pow Syst Res 77(3–4):227–233. doi: 10.1016/j.epsr.2006.02.016Lansey KE, Mays LW (1989). Optimization model for design of water distribution systems. Reliability analysis of water distribution systems. In: L. R. Mays (ed) ASCE: Reston, VaLouati M, Benabdallah S, Lebdi F, Milutin D (2011) Application of a genetic algorithm for the optimization of a complex reservoir system in Tunisia. Water Resour Manage 25(10):2387–2404. doi: 10.1007/s11269-011-9814-1Matías A (2003) “Diseño de redes de distribución de agua contemplando la fiabilidad mediante Algoritmos Genéticos”. Ph.D. Thesis, Universidad Politécnica de Valencia, ValenciaNazif S, Karamouz M, Tabesh M, Moridi A (2010) Pressure management model for urban water distribution networks. Water Resour Manage 24(3):437–458. doi: 10.1007/s11269-009-9454-xPrasad DT, Park NS (2004) Multiobjective genetic algorithms for design of water distribution networks. J Water Resour Plann Manage 130(1):73–82. doi: 10.1061/(ASCE)0733-9496(2004)130:1(73)Reca J, Martinez J (2006) Genetic algorithms for the design of looped irrigation water distribution networks. Water Resour Res 42(5):W05416. doi: 10.1029/2005WR004383Reca J, Martinez J, Gil C, Baños R (2008) Application of several meta-heuristic techniques to the optimization of real looped water distribution networks. Water Resour Manage 22(10):1367–1379. doi: 10.1007/s11269-007-9230-8Rossman LA (2000) EPANET 2.0 User’s manual. EPA/600/R-00/057, 2000Savic DA, Walters GA (1997) Genetic algorithms for least-cost design of water distribution systems. J Water Resour Plann Manage 123(2):67–77. doi: 10.1061/(ASCE)0733-9496(1997)123:2(67)Su YL, Mays LW, Duan N, Lansey KE (1987) Reliability based optimization model for water distribution systems. J Hydraul Eng 113(12):1539–1556. doi: 10.1061/(ASCE)0733-9429(1987)113:12(1539)Tsai FTC, Katiyar V, Toy D, Goff RA (2008) Conjunctive management of large-scale pressurized water distribution and groundwater systems in semi-arid area with parallel genetic algorithm. Water Resour Manage 23(8):1497–1517. doi: 10.1007/s11269-008-9338-5Vairavamoorthy K, Ali M (2000) Optimal design of water distribution systems using genetic algorithms. Comput Aided Civ Infrastruc Eng 15(5):374–382. doi: 10.1111/0885-9507.00201Wang QJ (1991) The genetic algorithm and its application to calibrating conceptual rainfall-runoff models. Water Resour Res 27(9):2467–2471. doi: 10.1029/91WR0130

Computational Determination of Air Valves Capacity Using CFD Techniques

[EN] The analysis of transient flow is necessary to design adequate protection systems that support the oscillations of pressure produced in the operation of motor elements and regulation. Air valves are generally used in pressurized water pipes to manage the air inside them. Under certain circumstances, they can be used as an indirect control mechanism of the hydraulic transient. Unfortunately, one of the major limitations is the reliability of information provided by manufacturers and vendors, which is why experimental trials are usually used to characterize such devices. The realization of these tests is not simple since they require an enormous volume of previously stored air to be used in such experiments. Additionally, the costs are expensive. Consequently, it is necessary to develop models that represent the behaviour of these devices. Although computational fluid dynamics (CFD) techniques cannot completely replace measurements, the amount of experimentation and the overall cost can be reduced significantly. This work approaches the characterization of air valves using CFD techniques, including some experimental tests to calibrate and validate the results. A mesh convergence analysis was made. The results show how the CFD models are an efficient alternative to represent the behavior of air valves during the entry and exit of air to the system, implying a better knowledge of the system to improve it.This research was funded by the Program Fondecyt Regular, grant number 1180660.García-Todolí, S.; Iglesias Rey, PL.; Mora Melia, D.; Martínez-Solano, FJ.; Fuertes-Miquel, VS. (2018). Computational Determination of Air Valves Capacity Using CFD Techniques. Water. 10(10):1-16. https://doi.org/10.3390/w10101433S1161010Liou, C. P., & Hunt, W. A. (1996). Filling of Pipelines with Undulating Elevation Profiles. Journal of Hydraulic Engineering, 122(10), 534-539. doi:10.1061/(asce)0733-9429(1996)122:10(534)Zhou, F., Hicks, F. E., & Steffler, P. M. (2002). Transient Flow in a Rapidly Filling Horizontal Pipe Containing Trapped Air. Journal of Hydraulic Engineering, 128(6), 625-634. doi:10.1061/(asce)0733-9429(2002)128:6(625)Laanearu, J., Annus, I., Koppel, T., Bergant, A., Vučković, S., Hou, Q., … van’t Westende, J. M. C. (2012). Emptying of Large-Scale Pipeline by Pressurized Air. Journal of Hydraulic Engineering, 138(12), 1090-1100. doi:10.1061/(asce)hy.1943-7900.0000631Apollonio, C., Balacco, G., Fontana, N., Giugni, M., Marini, G., & Piccinni, A. (2016). Hydraulic Transients Caused by Air Expulsion During Rapid Filling of Undulating Pipelines. Water, 8(1), 25. doi:10.3390/w8010025Zhou, F., Hicks, F. E., & Steffler, P. M. (2002). Observations of Air–Water Interaction in a Rapidly Filling Horizontal Pipe. Journal of Hydraulic Engineering, 128(6), 635-639. doi:10.1061/(asce)0733-9429(2002)128:6(635)Vasconcelos, J. G., Wright, S. J., & Roe, P. L. (2006). Improved Simulation of Flow Regime Transition in Sewers: Two-Component Pressure Approach. Journal of Hydraulic Engineering, 132(6), 553-562. doi:10.1061/(asce)0733-9429(2006)132:6(553)Li, J., & McCorquodale, A. (1999). Modeling Mixed Flow in Storm Sewers. Journal of Hydraulic Engineering, 125(11), 1170-1180. doi:10.1061/(asce)0733-9429(1999)125:11(1170)Ramezani, L., Karney, B., & Malekpour, A. (2015). The Challenge of Air Valves: A Selective Critical Literature Review. Journal of Water Resources Planning and Management, 141(10), 04015017. doi:10.1061/(asce)wr.1943-5452.0000530Stephenson, D. (1997). Effects of Air Valves and Pipework on Water Hammer Pressures. Journal of Transportation Engineering, 123(2), 101-106. doi:10.1061/(asce)0733-947x(1997)123:2(101)Bianchi, A., Mambretti, S., & Pianta, P. (2007). Practical Formulas for the Dimensioning of Air Valves. Journal of Hydraulic Engineering, 133(10), 1177-1180. doi:10.1061/(asce)0733-9429(2007)133:10(1177)De Martino, G., Fontana, N., & Giugni, M. (2008). Transient Flow Caused by Air Expulsion through an Orifice. Journal of Hydraulic Engineering, 134(9), 1395-1399. doi:10.1061/(asce)0733-9429(2008)134:9(1395)Bhosekar, V. V., Jothiprakash, V., & Deolalikar, P. B. (2012). Orifice Spillway Aerator: Hydraulic Design. Journal of Hydraulic Engineering, 138(6), 563-572. doi:10.1061/(asce)hy.1943-7900.0000548Iglesias-Rey, P. L., Fuertes-Miquel, V. S., García-Mares, F. J., & Martínez-Solano, J. J. (2014). Comparative Study of Intake and Exhaust Air Flows of Different Commercial Air Valves. Procedia Engineering, 89, 1412-1419. doi:10.1016/j.proeng.2014.11.467Martins, N. M. C., Soares, A. K., Ramos, H. M., & Covas, D. I. C. (2016). CFD modeling of transient flow in pressurized pipes. Computers & Fluids, 126, 129-140. doi:10.1016/j.compfluid.2015.12.002Zhou, L., Liu, D., & Ou, C. (2011). Simulation of Flow Transients in a Water Filling Pipe Containing Entrapped Air Pocket with VOF Model. Engineering Applications of Computational Fluid Mechanics, 5(1), 127-140. doi:10.1080/19942060.2011.11015357Davis, J. A., & Stewart, M. (2002). Predicting Globe Control Valve Performance—Part I: CFD Modeling. Journal of Fluids Engineering, 124(3), 772-777. doi:10.1115/1.1490108Stephens, D., Johnson, M. C., & Sharp, Z. B. (2012). Design Considerations for Fixed-Cone Valve with Baffled Hood. Journal of Hydraulic Engineering, 138(2), 204-209. doi:10.1061/(asce)hy.1943-7900.0000496Romero-Gomez, P., Ho, C. K., & Choi, C. Y. (2008). Mixing at Cross Junctions in Water Distribution Systems. I: Numerical Study. Journal of Water Resources Planning and Management, 134(3), 285-294. doi:10.1061/(asce)0733-9496(2008)134:3(285)Austin, R. G., Waanders, B. van B., McKenna, S., & Choi, C. Y. (2008). Mixing at Cross Junctions in Water Distribution Systems. II: Experimental Study. Journal of Water Resources Planning and Management, 134(3), 295-302. doi:10.1061/(asce)0733-9496(2008)134:3(295)Ho, C. K. (2008). Solute Mixing Models for Water-Distribution Pipe Networks. Journal of Hydraulic Engineering, 134(9), 1236-1244. doi:10.1061/(asce)0733-9429(2008)134:9(1236)Huang, J., Weber, L. J., & Lai, Y. G. (2002). Three-Dimensional Numerical Study of Flows in Open-Channel Junctions. Journal of Hydraulic Engineering, 128(3), 268-280. doi:10.1061/(asce)0733-9429(2002)128:3(268)Weber, L. J., Schumate, E. D., & Mawer, N. (2001). Experiments on Flow at a 90° Open-Channel Junction. Journal of Hydraulic Engineering, 127(5), 340-350. doi:10.1061/(asce)0733-9429(2001)127:5(340)Chanel, P. G., & Doering, J. C. (2008). Assessment of spillway modeling using computational fluid dynamics. Canadian Journal of Civil Engineering, 35(12), 1481-1485. doi:10.1139/l08-094Li, S., Cain, S., Wosnik, M., Miller, C., Kocahan, H., & Wyckoff, R. (2011). Numerical Modeling of Probable Maximum Flood Flowing through a System of Spillways. Journal of Hydraulic Engineering, 137(1), 66-74. doi:10.1061/(asce)hy.1943-7900.0000279Castillo, L., García, J., & Carrillo, J. (2017). Influence of Rack Slope and Approaching Conditions in Bottom Intake Systems. Water, 9(1), 65. doi:10.3390/w9010065Regueiro-Picallo, M., Naves, J., Anta, J., Puertas, J., & Suárez, J. (2016). Experimental and Numerical Analysis of Egg-Shaped Sewer Pipes Flow Performance. Water, 8(12), 587. doi:10.3390/w812058

Observation of magnetic order in the double-layer system La2MCu2O6+δ (M=Ca,Sr)

Under the terms of the Creative Commons Attribution License 3.0 (CC-BY).-- et al.Measurements of the spin rotation and depolarization of implanted positive muons have revealed that La2SrCu2O6+δ, La2CaCu2O6+δ, and La1.9Y0.1CaCu2O6+δ, members of the double-layer perovskite family La2MCu2O6+δ (M=Ca,Sr), display magnetic ordering similar to that of La2−xSrxCuO4−y and YBa2Cu3Ox Their magnetic order parameters are remarkably close to those of the other layered cuprates. A superconducting minority phase has been detected in La2CaCu2O6+δ (δ≥0.02), with onset at ∼45 K and accompanied by a change in the muon-spin-precession signals from the majority antiferromagnetic phase, phenomena absent in La2SrCu2O6+δ. This behavior was attributed to mobility and local clustering of intercalated oxygen excess in the layer between the CuO2 planes.This work was supported by NSERC (Canada), DOE Grant No. DE-FG05-88ER45353, the CICYT and the MIDAS project (Spain), and the CEE.Peer Reviewe

Design of Pumping Stations Using a Multicriteria Analysis and the Application of the AHP Method

[EN] The pumping station are very important hydraulic system in urban water supply be-cause the pumps raise the water head ensuring the minimum pressure required in drinking water systems. In the design of a pumping station, one of the most important criteria is the number of pumps. However, in the traditional design this criterion is de-fined arbitrarily. The other criteria are defined from the number of pumps and can be produce a design not optimal. In addition, the traditional design does not consider the environment importance to choose the pumps. The objective of this paper is defining a new design methodology for pumping sta-tions. It has been developed using a multicriteria analysis in which nine criteria are evaluated. The application of the analytic hierarchy process (AHP) allows finding an optimal solution. These design criteria have been associated in three cluster factors: technical factors, environmental factors, and economic factors. The results obtained allow not only to validate the methodology, but also to offer a solution to the problem of determining the most suitable model and the number of pumps of a pumping sta-tion.Sánchez-Ferrer, DS.; Briceño-León, CX.; Iglesias Rey, PL.; Martínez-Solano, FJ.; Fuertes-Miquel, VS. (2021). Design of Pumping Stations Using a Multicriteria Analysis and the Application of the AHP Method. Sustainability. 13(11):1-22. https://doi.org/10.3390/su13115876S122131

High-pressure effects on the optical-absorption edge of CdIn2S4, MgIn2S4, and MnIn2S4 thiospinels

The effect of pressure on the optical-absorption edge of CdIn2S4, MgIn2S4, and MnIn2S4 thiospinels at room temperature is investigated up to 20 GPa. The pressure dependence of their band-gaps has been analyzed using the Urbach rule. We have found that, within the pressure-range of stability of the low-pressure spinel phase, the band-gap of CdIn2S4 and MgIn2S4 exhibits a linear blue-shift with pressure, whereas the band-gap of MnIn2S4 exhibits a pronounced non-linear shift. In addition, an abrupt decrease of the band-gap energies occurs in the three compounds at pressures of 10 GPa, 8.5 GPa, and 7.2 GPa, respectively. Beyond these pressures, the optical-absorption edge red-shifts upon compression for the three studied thiospinels. All these results are discussed in terms of the electronic structure of each compound and their reported structural changes.Comment: 18 pages, 3 figure

Numerical modelling of pipelines with air pockets and air valves

[EN] This work considers the behaviour of air inside pipes when the air is expelled through air valves. Generally, the air shows isothermal behaviour. Nevertheless, when the transient is very fast, it shows adiabatic behaviour. In a real installation, an intermediate evolution between these two extreme conditions occurs. Thus, it is verified that the results vary significantly depending on the hypothesis adopted. To determine the pressure of the air pocket, the most unfavourable hypothesis (isothermal behaviour) is typically adopted. Nevertheless, from the perspective of the water hammer that takes place when the water column arrives at the air valve and abruptly closes, the most unfavourable hypothesis is the opposite (adiabatic behaviour). In this case, the residual velocity with which the water arrives at the air valve is higher, and, consequently, the water hammer generated is greater.Fuertes Miquel, VS.; López Jiménez, PA.; Martínez-Solano, FJ.; López-Patiño, G. (2016). Numerical modelling of pipelines with air pockets and air valves. Canadian Journal of Civil Engineering. 43(12):1052-1061. doi:10.1139/cjce-2016-0209S10521061431

Comparative Study of Intake and Exhaust Air Flows of Different Commercial Air Valves

This work aims to study in detail the methods of experimental characterization of air valves. In the first part, different experimental techniques are compared to the measurements made in the Air Valves Test Bench built by Bermad CS at its factory in Evron (Israel). The second part deals with the study of a collection of commercial air valves from different manufacturers. Finally, the Wylie and Streeter discharge coefficient Cd for air valve characterization [1] has been obtained. The results have been also compared with a simplified proposed model representation of the air valve.Iglesias Rey, PL.; Fuertes-Miquel, VS.; García Mares, FJ.; Martínez-Solano, FJ. (2014). Comparative Study of Intake and Exhaust Air Flows of Different Commercial Air Valves. Procedia Engineering. 89:1412-1419. doi:10.1016/j.proeng.2014.11.467S141214198

Rigid Water Column Model for Simulating the Emptying Process in a Pipeline Using Pressurized Air

This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers[EN] This paper presents a mathematical model for analyzing the emptying process in a pipeline using pressurized air. The rigid water column model (RWCM) is used to analyze the transient phenomena that occur during the emptying of the pipeline. The air-water interface is also computed in the proposed model. The proposed model is applied along a 271.6-m-long PVC-steel pipeline with a 232-mm internal diameter. The boundary conditions are given by a high-pressure air tank at the upstream end and a manual butterfly valve at the downstream end. The solution was carried out in a computer modeling program. The results show that comparisons between both the computed and measured water flow oscillations and gauge pressures are very similar; hence, the model can effectively simulate the transient flow in this system. In addition, the results indicate that the proposed model can predict both the water flow and gauge pressure better than previous models.Funding for Oscar E. Coronado-Hernandez (doctoral student) was covered by Fundacion Centro de Estudios Interdisciplinarios Basicos y Aplicados (CEIBA)-Gobernacion de Bolivar (Colombia).Coronado-Hernández, OE.; Fuertes-Miquel, VS.; Iglesias Rey, PL.; Martínez-Solano, FJ. (2018). Rigid Water Column Model for Simulating the Emptying Process in a Pipeline Using Pressurized Air. Journal of Hydraulic Engineering. 144(4):1-7. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001446S17144