Parallel Computing in Water Network Analysis and Leakage Minimization

[EN] In this paper a parallel computing based software demonstrator for the simulation and leakage minimization of water networks is presented. This demonstrator, based on the EPANET package, tackles three different types of problems making use of parallel computing. First, the solution of the hydraulic problem is treated by means of the gradient method. The key point in the parallelization of the method is the solution of the underlying linear systems, which is carried out by means of a multifrontal Choleski method. Second, the water quality simulation problem is approached by using the discrete volume element method. The application of parallel computing is based on dividing the water network in several parts using the multilevel recursive bisection graph partitioning algorithm. Finally, the problem of leakage minimization using pressure reducing valves is approached. This results in the formulation of an optimization problem for each time step, which is solved by means of sequential quadratic programming. Because these subproblems are independent of each other, they can be solved in parallel.The writers wish to acknowledge the financial support provided by the ESPRIT program of the European Commission (HIPERWATER, ESPRIT project 24003), by the CICYT TIC96-1062-C03-01 project, and also by research staff training grants from the Spanish government and the autonomous government of the Comunidad Valenciana in Spain.Alonso Ábalos, JM.; Alvarruiz Bermejo, F.; Guerrero López, D.; Hernández García, V.; Ruiz Martínez, PA.; Vidal Maciá, AM.; Martínez Alzamora, F.... (2000). Parallel Computing in Water Network Analysis and Leakage Minimization. Journal of Water Resources Planning and Management. 126(4):251-260. https://doi.org/10.1061/(ASCE)0733-9496(2000)126:4(251)S251260126

Pattern Recognition and Clustering of Transient Pressure Signals for Burst Location

[EN] A large volume of the water produced for public supply is lost in the systems between sources and consumers. An important-in many cases the greatest-fraction of these losses are physical losses, mainly related to leaks and bursts in pipes and in consumer connections. Fast detection and location of bursts plays an important role in the design of operation strategies for water loss control, since this helps reduce the volume lost from the instant the event occurs until its effective repair (run time). The transient pressure signals caused by bursts contain important information about their location and magnitude, and stamp on any of these events a specific "hydraulic signature". The present work proposes and evaluates three methods to disaggregate transient signals, which are used afterwards to train artificial neural networks (ANNs) to identify burst locations and calculate the leaked flow. In addition, a clustering process is also used to group similar signals, and then train specific ANNs for each group, thus improving both the computational efficiency and the location accuracy. The proposed methods are applied to two real distribution networks, and the results show good accuracy in burst location and characterization.Manzi, D.; Brentan, BM.; Meirelles, G.; Izquierdo Sebastián, J.; Luvizotto Jr., E. (2019). Pattern Recognition and Clustering of Transient Pressure Signals for Burst Location. Water. 11(11):1-13. https://doi.org/10.3390/w11112279S1131111Creaco, E., & Walski, T. (2017). Economic Analysis of Pressure Control for Leakage and Pipe Burst Reduction. Journal of Water Resources Planning and Management, 143(12), 04017074. doi:10.1061/(asce)wr.1943-5452.0000846Campisano, A., Creaco, E., & Modica, C. (2010). RTC of Valves for Leakage Reduction in Water Supply Networks. Journal of Water Resources Planning and Management, 136(1), 138-141. doi:10.1061/(asce)0733-9496(2010)136:1(138)Campisano, A., Modica, C., Reitano, S., Ugarelli, R., & Bagherian, S. (2016). Field-Oriented Methodology for Real-Time Pressure Control to Reduce Leakage in Water Distribution Networks. Journal of Water Resources Planning and Management, 142(12), 04016057. doi:10.1061/(asce)wr.1943-5452.0000697Vítkovský, J. P., Simpson, A. R., & Lambert, M. F. (2000). Leak Detection and Calibration Using Transients and Genetic Algorithms. Journal of Water Resources Planning and Management, 126(4), 262-265. doi:10.1061/(asce)0733-9496(2000)126:4(262)Pérez, R., Puig, V., Pascual, J., Quevedo, J., Landeros, E., & Peralta, A. (2011). Methodology for leakage isolation using pressure sensitivity analysis in water distribution networks. Control Engineering Practice, 19(10), 1157-1167. doi:10.1016/j.conengprac.2011.06.004Jung, D., & Kim, J. (2017). Robust Meter Network for Water Distribution Pipe Burst Detection. Water, 9(11), 820. doi:10.3390/w9110820Colombo, A. F., Lee, P., & Karney, B. W. (2009). A selective literature review of transient-based leak detection methods. Journal of Hydro-environment Research, 2(4), 212-227. doi:10.1016/j.jher.2009.02.003Choi, D., Kim, S.-W., Choi, M.-A., & Geem, Z. (2016). Adaptive Kalman Filter Based on Adjustable Sampling Interval in Burst Detection for Water Distribution System. Water, 8(4), 142. doi:10.3390/w8040142Christodoulou, S. E., Kourti, E., & Agathokleous, A. (2016). Waterloss Detection in Water Distribution Networks using Wavelet Change-Point Detection. Water Resources Management, 31(3), 979-994. doi:10.1007/s11269-016-1558-5Guo, X., Yang, K., & Guo, Y. (2012). Leak detection in pipelines by exclusively frequency domain method. Science China Technological Sciences, 55(3), 743-752. doi:10.1007/s11431-011-4707-3Holloway, M. B., & Hanif Chaudhry, M. (1985). Stability and accuracy of waterhammer analysis. Advances in Water Resources, 8(3), 121-128. doi:10.1016/0309-1708(85)90052-1Sanz, G., Pérez, R., Kapelan, Z., & Savic, D. (2016). Leak Detection and Localization through Demand Components Calibration. Journal of Water Resources Planning and Management, 142(2), 04015057. doi:10.1061/(asce)wr.1943-5452.0000592Zhang, Q., Wu, Z. Y., Zhao, M., Qi, J., Huang, Y., & Zhao, H. (2016). Leakage Zone Identification in Large-Scale Water Distribution Systems Using Multiclass Support Vector Machines. Journal of Water Resources Planning and Management, 142(11), 04016042. doi:10.1061/(asce)wr.1943-5452.0000661Mounce, S. R., & Machell, J. (2006). Burst detection using hydraulic data from water distribution systems with artificial neural networks. Urban Water Journal, 3(1), 21-31. doi:10.1080/15730620600578538Covas, D., Ramos, H., & de Almeida, A. B. (2005). Standing Wave Difference Method for Leak Detection in Pipeline Systems. Journal of Hydraulic Engineering, 131(12), 1106-1116. doi:10.1061/(asce)0733-9429(2005)131:12(1106)Liggett, J. A., & Chen, L. (1994). Inverse Transient Analysis in Pipe Networks. Journal of Hydraulic Engineering, 120(8), 934-955. doi:10.1061/(asce)0733-9429(1994)120:8(934)Caputo, A. C., & Pelagagge, P. M. (2002). An inverse approach for piping networks monitoring. Journal of Loss Prevention in the Process Industries, 15(6), 497-505. doi:10.1016/s0950-4230(02)00036-0Van Zyl, J. E. (2014). Theoretical Modeling of Pressure and Leakage in Water Distribution Systems. Procedia Engineering, 89, 273-277. doi:10.1016/j.proeng.2014.11.187Izquierdo, J., & Iglesias, P. . (2004). Mathematical modelling of hydraulic transients in complex systems. Mathematical and Computer Modelling, 39(4-5), 529-540. doi:10.1016/s0895-7177(04)90524-9Lin, J., Keogh, E., Wei, L., & Lonardi, S. (2007). Experiencing SAX: a novel symbolic representation of time series. Data Mining and Knowledge Discovery, 15(2), 107-144. doi:10.1007/s10618-007-0064-zNavarrete-López, C., Herrera, M., Brentan, B., Luvizotto, E., & Izquierdo, J. (2019). Enhanced Water Demand Analysis via Symbolic Approximation within an Epidemiology-Based Forecasting Framework. Water, 11(2), 246. doi:10.3390/w11020246Meirelles, G., Manzi, D., Brentan, B., Goulart, T., & Luvizotto, E. (2017). Calibration Model for Water Distribution Network Using Pressures Estimated by Artificial Neural Networks. Water Resources Management, 31(13), 4339-4351. doi:10.1007/s11269-017-1750-2Adamowski, J., & Chan, H. F. (2011). A wavelet neural network conjunction model for groundwater level forecasting. Journal of Hydrology, 407(1-4), 28-40. doi:10.1016/j.jhydrol.2011.06.013Brentan, B., Meirelles, G., Luvizotto, E., & Izquierdo, J. (2018). Hybrid SOM+ k -Means clustering to improve planning, operation and management in water distribution systems. Environmental Modelling & Software, 106, 77-88. doi:10.1016/j.envsoft.2018.02.013Calinski, T., & Harabasz, J. (1974). A dendrite method for cluster analysis. Communications in Statistics - Theory and Methods, 3(1), 1-27. doi:10.1080/0361092740882710

Information Systems Skills Differences between High-Wage and Low-Wage Regions: Implications for Global Sourcing

Developing Information Systems (IS) skills for a company’s workforce has always been challenging, but global sourcing growth has caused the determination of needed IS skills to be more complex. The increased use of outsourcing to an IS service provider and from high-wage regions to low-wage regions has affected what IS skills are required globally and how to distribute the workforce to meet these needs. To understand what skills are needed in locations that seek and those that provide outsourcing, we surveyed IS service provider managers in global locations. Results from 126 reporting units provide empirical evidence that provider units in low-wage regions value technical skills more than those in high-wage regions. Despite the emphasis on commodity skills in low-wage areas, high- and low-wage providers value project management skills. Low-wage regions note global and virtual teamwork more than high-wage regions do. The mix of skills and the variation by region have implications for domestic and offshore sourcing. Service providers can vary their staffing models in global regions which has consequences for recruiting, corporate training, and curriculum

Phishing – the threat of internet banking

The attractiveness of Internet banking, the dynamics and the integration with e-business is still growing. The current use of electronic banking is defined by cyberspace and abused in the form of cyber terrorism as well. Therefore it is in the interest of all banks to focus on minimizing the real attacks. This article analyzes and compares the current possibilities against so-called phishing and identifies the area of the safe use of Internet banking in terms of the current potential threats in this area

The last five years of Big Data Research in Economics, Econometrics and Finance: Identification and conceptual analysis

Today, the Big Data term has a multidimensional approach where five main characteristics stand out: volume, velocity, veracity, value and variety. It has changed from being an emerging theme to a growing research area. In this respect, this study analyses the literature on Big Data in the Economics, Econometrics and Finance field. To do that, 1.034 publications from 2015 to 2019 were evaluated using SciMAT as a bibliometric and network analysis software. SciMAT offers a complete approach of the field and evaluates the most cited and productive authors, countries and subject areas related to Big Data. Lastly, a science map is performed to understand the intellectual structure and the main research lines (themes)

Integrating case study and survey research methods: An example in information systems

The case for combining research methods generally, and more specifically that for combining qualitative and quantitative methods, is strong. Yet, research designs that extensively integrate both fieldwork (e.g. case studies) and survey research are rare. More¬over, some journals tend tacitly to specialize by methodology thereby encouraging purity of method. The multi-method model of research while not new, has not been appreciated. In this respect it is useful to articulate and describe its usage through example. By reference to a recently completed study of IS consultant engagement success factors this paper presents an analysis of the benefits of integrating case study and survey research methods. The emphasis is on the qualitative case study method and how it can compliment more quantitative survey research. Benefits are demonstrated through specific examples from the reference study.</i

Abstract State Machines 1988-1998: Commented ASM Bibliography

An annotated bibliography of papers which deal with or use Abstract State Machines (ASMs), as of January 1998.Comment: Also maintained as a BibTeX file at http://www.eecs.umich.edu/gasm

An overview of Mirjam and WeaveC

In this chapter, we elaborate on the design of an industrial-strength aspectoriented programming language and weaver for large-scale software development. First, we present an analysis on the requirements of a general purpose aspect-oriented language that can handle crosscutting concerns in ASML software. We also outline a strategy on working with aspects in large-scale software development processes. In our design, we both re-use existing aspect-oriented language abstractions and propose new ones to address the issues that we identified in our analysis. The quality of the code ensured by the realized language and weaver has a positive impact both on maintenance effort and lead-time in the first line software development process. As evidence, we present a short evaluation of the language and weaver as applied today in the software development process of ASML