| publications-4531 |
article |
2003 |
Nauges, CΓ©line and Nauges, CΓ©line and Thomas, Alban and Thomas, Alban |
Long-run Study of Residential Water Consumption |
Environmental and Resource Economics |
10.1007/978-94-015-9984-9_3 |
|
|
|
The estimation of dynamic models and themeasure of long-run effects arerare in residential water demand studies. Weshow in this paper that a dynamicmodel of water consumption can be derived froma structural optimisation programsolved by local communities. Thisnonlinear model is estimated on asample of French municipalities and is foundasymptotically equivalent to a dynamic panel data model that is linear in theparameters. The latter includes anoriginal error-component structure that allowsfor a flexible heterogeneity pattern, including both the usual idiosyncraticeffect, and an additional individualeffect affected by a multiplicative time-varyingparameter. As usual GMM estimators for panel data are not consistent inthis case, we propose a new GMMprocedure that yields consistent and efficientestimates of short- and long-runprice elasticities (respectively β’0.26 andβ’0.40). |
|
|
|
|
| publications-4532 |
article |
2005 |
Bristow, Elizabeth and Brumbelow, Kelly |
Delay between Sensing and Response in Water Contamination Events |
|
10.1061/40792(173)305 |
|
|
|
Determining the consequences of a water contamination event is an important concern in the field of water systems security. Morbidity and mortality resulting from such a contamination are influenced in part by the amount of contaminated water consumed and the time between consumption and medical treatment. Water quality sensors in the water distribution network may shorten this time and help the users avoid the contaminant's adverse effects by alerting authorities to unusual water quality parameters; otherwise, the authorities may first suspect contamination when the victims begin seeking treatment. Once the irregular water quality parameters have been detected, some time may still elapse before all users stop consuming the contaminated water. Modeling this additional delay is the focus of this paper. This delay has been divided into five independent, sequential processes. The first phase is the amount of time required to transmit the sensed or measured contaminant concentrations to the local authorities. The second process includes the authorities' efforts to verify that there is a genuine contamination event. The third stage includes any measures that the authorities take in preparation to alerting the public to the threat including agency coordination, drafting announcements, contacting media, and printing flyers. The fourth phase of the delay is the time required to transmit the news of the contamination to the public. The final period encompasses the time elapsed while the system users, after being informed of the contamination, decide whether or not to comply with instructions on how to avoid the adverse effects. Probability distributions are constructed for the duration of each phase of the delay based on data collected from historical water contamination events and other disasters and characteristics of typical sensor networks. The entire response process is modeled using a Monte Carlo approach to determine probability distributions of response delay. |
|
|
|
|
| publications-4533 |
article |
2005 |
Gutzler, David S. and Gutzler, David S. and Nims, Joshua S. and Nims, Joshua S. |
Interannual Variability of Water Demand and Summer Climate in Albuquerque, New Mexico |
Journal of Applied Meteorology |
10.1175/jam2298.1 |
|
|
|
Abstract The effects of interannual climate variability on water demand in Albuquerque, New Mexico, are assessed. This city provides an ideal setting for examining the effects of climate on urban water demand, because at present the municipal water supply is derived entirely from groundwater, making supply insensitive to short-term climate variability. There is little correlation between interannual variability of climate and total water demandβ€”a result that is consistent with several previous studies. However, summertime residential demand, which composes about one-quarter of total annual demand in Albuquerque, is significantly correlated with summer-season precipitation and average daily maximum temperature. Furthermore, regressions derived from year-to-year changes in these variables are shown to isolate the climatic modulation of residential water demand effectively. Over 60\% of the variance of year-to-year changes in summer residential demand is accounted for by interannual temperature and precipitat... |
|
|
|
|
| publications-4534 |
article |
2005 |
Kapelan, Zoran and Kapelan, Zoran and Savić, Dragan and Savic, Dragan and Walters, Godfrey A. and Walters, Godfrey A. |
Multiobjective design of water distribution systems under uncertainty |
Water Resources Research |
10.1029/2004wr003787 |
|
|
|
[1]The water distribution system (WDS) design problem is defined here as a multiobjective optimization problem under uncertainty. The two objectives are (1) minimize the total WDS design cost and (2) maximize WDS robustness. The WDS robustness is defined as the probability of simultaneously satisfying minimum pressure head constraints at all nodes in the network. Decision variables are the alternative design options for each pipe in the network. The sources of uncertainty are future water consumption and pipe roughness coefficients. Uncertain variables are modeled using probability density functions (PDFs) assigned in the problem formulation phase. The corresponding PDFs of the analyzed nodal heads are calculated using the Latin hypercube sampling technique. The optimal design problem is solved using the newly developed RNSGAII method based on the nondominated sorting genetic algorithm II (NSGAII). In RNSGAII a small number of samples are used for each fitness evaluation, leading to significant computational savings when compared to the full sampling approach. Chromosome fitness is defined here in the same way as in the NSGAII optimization methodology. The new methodology is tested on several cases, all based on the New York tunnels reinforcement problem. The results obtained demonstrate that the new methodology is capable of identifying robust Pareto optimal solutions despite significantly reduced computational effort. |
|
|
|
|
| publications-4535 |
article |
2005 |
Turner, Andrea and Turner, Andrea and White, Saxon William and White, Stuart and Beatty, Kate E. and Beatty, K. and Gregory, A. and Gregory, A. |
Results of the largest residential demand management program in Australia |
Water Science & Technology: Water Supply |
10.2166/ws.2005.0106 |
|
|
|
This paper provides details and the results of an evaluation study carried out on the largest residential demand management program in Australia, the Sydney Water Corporation (SWC) β€Every Drop Counts’ (EDC) residential retrofit program. The evaluation measured the water savings of program participants and compared them to a control group. Savings of 20.9 Β± 2.5 kilolitres per household per annum (kL/hh/a) were found from statistical analysis of water meter readings of the sample of single residential households analysed. These individual savings effectively provide SWC with a potential total saving of 3,344 Β± 400 megalitres per annum (ML/a) for the single residential houses retrofitted alone, i.e. 80\% of the 200,000 households retrofitted to date. The evaluation identified that no β€decay’ in average savings were found over the maximum four year period assessed. Other factors evaluated during the study included: analysis of individual water efficiency measures; comparison of savings with other evaluations; and savings related to occupancy ratio, geographical grouping, income category and defined socioeconomic categories. |
|
|
|
|
| publications-4536 |
article |
2007 |
Kim, S.H. and Kim, Sanghyun and Choi, Sung-Hwan and Choi, S.H. and Choi, S.H. and Choi, Soo-Han and Koo, Jaβ€Yong and Koo, Jayong and Choi, Se Yeon and Choi, Sun-A and Choi, Suingil and Choi, Suingil and Hyun, In-Hwan and Hyun, Inhwan |
Trend analysis of domestic water consumption depending upon social, cultural, economic parameters |
Water Science & Technology: Water Supply |
10.2166/ws.2007.097 |
|
|
|
Designs of water distribution systems and water resources planning and management can be obtained from a comprehensive investigation and analysis of water consumption data in real life systems. Water consumption patterns for domestic purposes were monitored at 145 households over a three-year period. Electric flow meters were installed at the ends of all of the household water taps. Water consumption patterns were analyzed to configure the water demand trends for social and cultural factors. Economic factors such as monthly income and the area of the floor plan were investigated to determine the impact of resident wealth on the patterns of water consumption. Water use data collected by a public water resources management firm in Korea, Kwater, had been filtered using both physical and probabilistic criteria to improve the credibility of the analysis. Both the Mann-Kendall and Spearman's Rho tests were used to perform the trend analysis. Distinct factors in the patterns of water consumption can be determined to cause both increasing and decreasing trends in water use. Analysis of this data provides the basis of parameter configuration for a reasonable design of a domestic water-demand prediction model. |
|
|
|
|
| publications-4537 |
article |
2009 |
Kang, Doosun and Kang, Doosun and Pasha, M. Fayzul K. and Pasha, M. F K and Lansey, Kevin and Lansey, Kevin E |
Approximate methods for uncertainty analysis of water distribution systems |
Urban Water Journal |
10.1080/15730620802566844 |
|
|
|
Monte Carlo simulation (MCS) has been commonly applied for uncertainty analysis of model predictions. However, when modelling a water distribution system under unsteady conditions, the computational demand of MCS is quite high even for a reasonably sized system. The aim of this study is to evaluate alternative approximation schemes and examine their ability to predict model prediction uncertainty with less computational effort. Here, MCS is compared with a point estimation method, the first-order second-moment (FOSM) method, and a quasi-MCS method, Latin hypercube sampling (LHS). Hydraulic and water quality simulations are performed using EPANET and the evaluated model outputs are nodal pressure, water age and chlorine concentration. Six input parameters, pipe diameter and roughness coefficient, nodal spatial and temporal demands and bulk and wall decay coefficients, are considered. To examine the effect of the magnitude of input uncertainty on model output, three uncertainty levels are evaluated. The stu... |
|
|
|
|
| publications-4538 |
article |
2010 |
Mounce, S. R. and Mounce, Stephen R. and Boxall, Joby and Boxall, Joby and Machell, John and Machell, John |
Development and Verification of an Online Artificial Intelligence System for Detection of Bursts and Other Abnormal Flows |
Journal of Water Resources Planning and Management |
10.1061/(asce)wr.1943-5452.0000030 |
|
|
|
Water lost through leakage from water distribution networks is often appreciable. As pressure increases on water resources, there is a growing emphasis for water service providers to minimize this loss. The objective of the work presented in this paper was to assess the online application and resulting benefits of an artificial intelligence system for detection of leaks/bursts at district meter area (DMA) level. An artificial neural network model, a mixture density network, was trained using a continually updated historic database that constructed a probability density model of the future flow profile. A fuzzy inference system was used for classification; it compared latest observed flow values with predicted flows over time windows such that in the event of abnormal flow conditions alerts are generated. From the probability density functions of predicted flows, the fuzzy inference system provides confidence intervals associated with each detection, these confidence values provide useful information for f... |
|
|
|
|
| publications-4539 |
article |
2017 |
Cai, Yi and Starly, Binil and Cai, Yi and Cohen, Paul H. and Starly, Binil and Cohen, Paul H. and Lee, Yuanβ€Shin and Lee, Yuan-Shin |
Sensor Data and Information Fusion to Construct Digital-twins Virtual Machine Tools for Cyber-physical Manufacturing |
Procedia Manufacturing |
10.1016/j.promfg.2017.07.094 |
|
|
|
Abstract This paper presents sensor data integration and information fusion to build β€_x009c_digital-twinsβ€_x009d_ virtual machine tools for cyber-physical manufacturing. Virtual machine tools are useful for simulating machine tools’ capabilities in a safe and cost-effective way, but it is challenging to accurately emulate the behavior of the physical tools. When a physical machine tool breaks down or malfunctions, engineers can always go back to check the digital traces of the β€_x009c_digital-twinsβ€_x009d_ virtual machine for diagnosis and prognosis. This paper presents an integration of manufacturing data and sensory data into developing β€_x009c_digital-twinsβ€_x009d_ virtual machine tools to improve their accountability and capabilities for cyber-physical manufacturing. The sensory data are used to extract the machining characteristics profiles of a digital-twins machine tool, with which the tool can better reflect the actual status of its physical counterpart in its various applications. In this paper, techniques are discussed for deploying sensors to capture machine-specific features, and analytical techniques of data and information fusion are presented for modeling and developing β€_x009c_digital-twinsβ€_x009d_ virtual machine tools. Example of developing the digital-twins of a 3-axis vertical milling machine is presented to demonstrate the concept of modeling and building a digital-twins virtual machine tool for cyber-physical manufacturing. The presented technique can be used as a building block for cyber-physic manufacturing development. |
|
|
|
|
| publications-4540 |
article |
1987 |
LeChevallier, Mark W. and LeChevallier, M W and Babcock, T M and Babcock, T M and Lee, R G and Lee, R G |
Examination and characterization of distribution system biofilms. |
Applied and Environmental Microbiology |
10.1128/aem.53.12.2714-2724.1987 |
|
|
|
Investigations concerning the role of distribution system biofilms on water quality were conducted at a drinking water utility in New Jersey. The utility experienced long-term bacteriological problems in the distribution system, while treatment plant effluents were uniformly negative for coliform bacteria. Results of a monitoring program showed increased coliform levels as the water moved from the treatment plant through the distribution system. Increased coliform densities could not be accounted for by growth of the cells in the water column alone. Identification of coliform bacteria showed that species diversity increased as water flowed through the study area. All materials in the distribution system had high densities of heterotrophic plate count bacteria, while high levels of coliforms were detected only in iron tubercles. Coliform bacteria with the same biochemical profile were found both in distribution system biofilms and in the water column. Assimilable organic carbon determinations showed that carbon levels declined as water flowed through the study area. Maintenance of a 1.0-mg/liter free chlorine residual was insufficient to control coliform occurrences. Flushing and pigging the study area was not an effective control for coliform occurrences in that section. Because coliform bacteria growing in distribution system biofilms may mask the presence of indicator organisms resulting from a true breakdown of treatment barriers, the report recommends that efforts continue to find methods to control growth of coliform bacteria in pipeline biofilms. |
|
|
|
|
