| publications-4251 |
article |
2009 |
Yang, Ethan and Yang, Yi-Chen E. and Cai, Ximing and Cai, Ximing and Stipanović, Dušan M. and Stipanović, Dušan M. |
A decentralized optimization algorithm for multiagent system-based watershed management |
Water Resources Research |
10.1029/2008wr007634 |
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[1]A watershed can be simulated as a multiagent system (MAS) composed of spatially distributed land and water users (agents) within a common defined environment. The watershed system is characterized by distributed decision processes at the agent level with a coordination mechanism organizing the interactions among individual decision processes at the system level. This paper presents a decentralized (distributed) optimization method known as constraint-based reasoning, which allows individual agents in an MAS to optimize their behaviors over various alternatives. The method incorporates the optimization of all agents' objectives through an interaction scheme, in which the ith agent optimizes its objective with a selected priority for collaboration and forwards the solution and consequences to all agents that interact with it. Agents are allowed to determine how important their own objectives are in comparison with the constraints, using a local interest factor (Ξ²i). A large Ξ²i value indicates a selfish agent who puts high priority on its own benefit and ignores collaboration requirements. This bottom-up problem-solving approach mimics real-world watershed management problems better than conventional β€_x009c_top-downβ€_x009d_ optimization methods in which it is assumed that individual agents will completely comply with any recommendations that the coordinator makes. The method is applied to a steady state hypothetical watershed with three off-stream human agents, one in-stream human agent (reservoir), and two ecological agents. |
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| publications-4252 |
article |
1985 |
Germanopoulos, George and Germanopoulos, George |
A technical note on the inclusion of pressure dependent demand and leakage terms in water supply network models |
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10.1080/02630258508970401 |
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Abstract This note suggests a technique for including pressure dependent demand and leakage terms in simulation models for water distribution systems. Empirical functions are used to relate consumer outflows and leakage losses to the network pressures and the inclusion of these functions in the mathematical formulation of the network analysis problem is described. An application to an existing distribution system is presented where it is shown that the extended network model proposed leads to more realistic simulation results when the network pressures are too low to provide specified consumer demands, or high enough to cause significant leakage losses. It is also found that the computational requirements of network analysis and simulation are not significantly affected by the inclusion of the additional terms. |
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| publications-4253 |
article |
2001 |
Tillman, T. and Tillman, T. and Larsen, Tove A. and Larsen, Tove A. and Pahlβ€Wostl, Claudia and Pahl-Wostl, C. and Gujer, Willi and Gujer, Willi |
Interaction analysis of stakeholders in water supply systems |
Water Science and Technology |
10.2166/wst.2001.0316 |
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An analysis of the characteristic goals, strategies and rules of behavior of relevant stakeholders allows the efficacy and potential risks of past and current engineering and management concepts to be estimated. The study is driven by the observable shift from security to cost-centered strategies by water utilities and the difficulties of balancing technical and financial needs in an uncertain future. Its benefits include a methodology with a twofold result. With the aid of domain knowledge from experts involved in a participatory process, the interactions of a subset of stakeholders are quantified and documented in a rule catalog. This leads to an improved understanding of their decision-making rules. An agent-based model comprising these stakeholders' rules of behavior in subsequently development. Once the model is validated with data sets from a real utility, multiple-scenario testing helps to explore different strategies and can be used to generate ideas for developing flexible management and design schemes. Despite the complexity of the system described, simple model rules which are repeated annually can replicate the general development of both capacity and cost-related parameters. Scenario simulations show the effects of different management strategies on key parameters such as capacity, water price and financial debt. |
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| publications-4254 |
article |
2001 |
Woo, Hyoung-Min and Woo, Hyoungmin and Yoon, Jae-Heung and Choi, Doo-Yong |
Optimal Monitoring Sites Based on Water Quality and Quantity in Water Distribution Systems |
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10.1061/40569(2001)397 |
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The optimal monitoring sites of water quality should reflect both the water quantity and quality, and be representatives of the water distribution system. In the previous research, only the water quantity was considered as a factor of monitoring importance. Even if the water quality as well as the water quantity was considered, the retention times in the system was used to estimate the water quality at the network nodes. However the retention times cannot well represent the water quality because of their nonlinear relationship. In this paper, we present a new method of determining the optimal monitoring sites, in which the water quality is incorporated into the optimization model with a different method for water distribution system from the previous researches. In the method, the water quality at the nodes is determined by using a simulation model EPANET rather than retention times. The method of minimal path enumeration with list processing is applied to constructing the coverage matrix and determining all the flow paths. With the coverage matrix, an integer programming problem is formulated and solved. The cases of steady-state simulation is analyzed by the newly developed method. For the extended period simulation, minimal set of covering algorithm is used to locate the optimal monitoring sites. Our method provides more reasonable monitoring sites than those of the previous methods for two sample distribution networks. |
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| publications-4255 |
article |
2006 |
Shastri, Yogendra and Diwekar, Urmila M. |
Sensor Placement in Water Networks: A Stochastic Programming Approach |
Journal of Water Resources Planning and Management |
10.1061/(asce)0733-9496(2006)132:3(192) |
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Placement of sensors in water distribution networks helps timely detection of contamination and reduces risk to the population. Identifying the optimal locations of these sensors is important from an economic perspective and has been previously attempted using the theory of optimization. This work extends that formulation by considering uncertainty in the network and describes a stochastic program- ming method that is capable of determining the optimal sensor location while accounting for demand uncertainties. The problem is formulated as a two stage stochastic programming problem with recourse. The solution to the problem is achieved by using a newly proposed algorithm aimed at efficiently solving stochastic nonlinear programming problems. This makes the problem solution computa- tionally tractable as compared to the traditional stochastic programming methods. The proposed formulation and solution methodology are tested on an example network to perform a comparative study with other formulations. The results show the importance of uncertainty consideration in decision making and highlight the advantages of the proposed stochastic programming approach. |
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| publications-4256 |
article |
2008 |
Huang, Jinhui Jeanne and McBean, Edward A. and James, William |
Multi-Objective Optimization for Monitoring Sensor Placement in Water Distribution Systems |
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10.1061/40941(247)113 |
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As water distribution systems are vulnerable to a variety of accidental or deliberate contaminant intrusion events, efficient in-situ water quality monitoring is important in providing a robust water supply. To identify optimal placements of monitoring sensors in water distribution systems, a multiple-objective optimization method employing genetic algorithms (GA) in conjunction with data mining, is developed. The proposed methodology is capable of identifying an optimal set of monitoring stations based on three objectives: detection delay time, detection probability, and the affected population prior to detection. To apply the method, a database which stores data for intrusion events at each node, and the classified consequences of these intrusions at each node, is prepared. The initial solutions for multi-objective optimization are obtained from the database based on sensor coverage criteria. Pareto ranking is performed during the GA optimization. The effectiveness of the proposed method is illustrated by applying the methodology to the two networks, Networks 1 and 2, provided by the Battle of the Water Sensor Networks design competition. The final results in application to Networks 1 and 2 are also provided. |
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| publications-4257 |
article |
2010 |
Polebitski, Austin and Polebitski, Austin and Palmer, Richard N. and Palmer, Richard N. |
Seasonal Residential Water Demand Forecasting for Census Tracts |
Journal of Water Resources Planning and Management |
10.1061/(asce)wr.1943-5452.0000003 |
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The paucity of readily available demographic, economic, and water consumption data at household levels has limited the application of disaggregate water demand models. This research develops regression-based water demand models capable of forecasting single-family residential water demands within individual census tracts at a bimonthly time-step. The regression models are estimated using 12 years of demographic, weather, economic, and metered bimonthly water consumption data associated with over 100 unique census tracts in Seattle, Washington. In general, the three regression methods perform well in replicating total single-family water consumption in the study region. Two regression models, a fixed effects model and a random effects model, provide better estimates of water demand within individual census tracts. Improved water demand forecasts at the spatial scale of census tracts provide policy makers and planners information useful for managing water resources. These proposed approaches allow examinati... |
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| publications-4258 |
article |
2012 |
Carragher, Byron James and Carragher, Byron James and Stewart, Rodney Anthony and Stewart, Rodney Anthony and Beal, Cara and Beal, Cara |
Quantifying the influence of residential water appliance efficiency on average day diurnal demand patterns at an end use level: A precursor to optimised water service infrastructure planning |
Resources Conservation and Recycling |
10.1016/j.resconrec.2012.02.008 |
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Abstract Residential water consumption reductions resulting from water efficiency measures has received much research attention in recent years; however, research into the contribution of such measures in reducing hourly water demand and subsequent benefits to urban water service infrastructure efficiency is still in its infancy. In an attempt to address this issue, this study examined the degree of influence that differing water stock (e.g. taps, shower heads, clothes washers) efficiency in 191 households, participating in an Australian smart metering study, had on average day (AD) diurnal consumption patterns. Sub-sample clusters used for analysis were formed by a weighted household water stock efficiency star rating classification method. Results showed a statistically significant reduction in AD peak hour water consumption in households with stock of a higher composite star rating. Paired comparison between households with a composite efficiency rating greater than or equal to (≥) three stars and those of a composite rating less than ( |
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| publications-4259 |
article |
2016 |
Boschert, Stefan and Boschert, Stefan and Rosen, Roland and Rosen, Roland |
Digital Twinβ€”The Simulation Aspect |
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10.1007/978-3-319-32156-1_5 |
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The vision of the Digital Twin itself refers to a comprehensive physical and functional description of a component, product or system, which includes more or less all information which could be useful in allβ€”the current and subsequentβ€”lifecycle phases. In this chapter we focus on the simulation aspects of the Digital Twin. Today, modelling and simulation is a standard process in system development, e.g. to support design tasks or to validate system properties. During operation and for service first simulation-based solutions are realized for optimized operations and failure prediction. In this sense, simulation merges the physical and virtual world in all life cycle phases. Current practice already enables the users (designer, SW/HW developers, test engineers, operators, maintenance personnel, etc) to master the complexity of mechatronic systems. |
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| publications-4260 |
article |
2018 |
Qi, Qinglin and Qi, Qinglin and Tao, Fei and Tao, Fei |
Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison |
IEEE Access |
10.1109/access.2018.2793265 |
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With the advances in new-generation information technologies, especially big data and digital twin, smart manufacturing is becoming the focus of global manufacturing transformation and upgrading. Intelligence comes from data. Integrated analysis for the manufacturing big data is beneficial to all aspects of manufacturing. Besides, the digital twin paves a way for the cyber-physical integration of manufacturing, which is an important bottleneck to achieve smart manufacturing. In this paper, the big data and digital twin in manufacturing are reviewed, including their concept as well as their applications in product design, production planning, manufacturing, and predictive maintenance. On this basis, the similarities and differences between big data and digital twin are compared from the general and data perspectives. Since the big data and digital twin can be complementary, how they can be integrated to promote smart manufacturing are discussed. |
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