Heuristic Optimization Model for the Optimal Layout and Pipe Design of Sewer Systems

Steele, Joshua C.; Mahoney, Kurt; Karovic, Omer; Mays, Larry W.

doi:10.1007/s11269-015-1191-8

Cited by 44 publications

(17 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Here random compressive sensing using particle swarm intelligence will be used because of its agnostic and universal nature. Previous investigations on CS showed that signals that can be compressed using classical deterministic methods can also be efficiently acquired from a small set of random measurements.…”

Section: Methodsmentioning

confidence: 99%

Compressive sensing based structural damage detection and localization using theoretical and metaheuristic statistics

Yao

Pakzad

Venkitasubramaniam

2016

Struct. Control Health Monit.

View full text Add to dashboard Cite

Accurate structural damage identification calls for dense sensor networks, which are becoming more feasible as the price of electronic sensing systems reduces. To transmit and process data from all nodes of a dense network is a computationally expensive BIG DATA problem; therefore scalable algorithms are needed so that inferences about the current state of the structure can be made efficiently. In this paper, an iterative spatial compressive sensing scheme for damage existence identification and localization is proposed and investigated. At each iteration, damage existence is identified from randomly collected sparse samples and damage localization is iteratively detected via sensing-processing cycles with metaheuristic sampling distribution updating. Specifically, simulated annealing and ant colony analogy are used for guidance in future selection of sensing locations. This framework is subsequently validated by numerical and experimental implementations for gusset plate crack identification. SHM systems [25,26], the transmission cost and energy consumption of centralized data processing becomes inhibitive as the sensor network expands in size [3,[27][28][29]. To overcome this obstacle, decentralized information extraction techniques and communication procedures have been proposed and tried in several studies [30][31][32][33], demonstrating increased energy efficiency and better flow of operation.In the meantime, options to compress the data for wireless transmission are also explored. This can be done by applying the off-the-shelf compression schemes via adaptive coding, and a number of studies that exploit the temporal information redundancy of structural monitoring signals for data condensation are also under way. Examples include compressive sensing from random selection [34][35][36], sparse matrix representation[37-39], bio-mimicry based signal interpretation [40], and wavelet analysis [41,42]. Such methods reduce the amount of data transmitted per node, yet the central station still needs to communicate directly/indirectly with all sensor nodes within network. But because damage is intrinsically a local phenomenon, even higher performance could be realized if within a dense network only a subset of sensors in the vicinity of possible damage communicates their data with the main repository given proper damage detection features and effective compressive data communication procedures.In this paper an iterative compact sensing framework on subset identification within dense sensor network for damage detection is introduced. It complements the existing temporal compressive sensing methods, where time histories are compressed at individual sensor nodes. In this scheme, damage existence is first identified via hypothesis testing on the determinant of sample correlation matrix, as a damage feature, among several random locations. Then damage is localized as the location where the maximum Damage Location Indicator (DLI) from iterative random sampling occurs. At each iteration damage indices are computed from the n...

show abstract

Section: Methodsmentioning

confidence: 99%

Compressive sensing based structural damage detection and localization using theoretical and metaheuristic statistics

Yao

Pakzad

Venkitasubramaniam

2016

Struct. Control Health Monit.

View full text Add to dashboard Cite

show abstract

“…Since the concept of optimal design for storm sewer networks was first proposed in the late 1960s [5,6], many researchers have concentrated on the optimal design of storm sewer systems, and various optimization techniques were applied to minimize construction costs whilst ensuring the reliability of sewer networks for their solution, such as linear programming [5,7,8], nonlinear programming [6,9], dynamic programming [10][11][12], genetic algorithm (GA) [13][14][15][16][17], cellular automata (CA) [18][19][20][21], ant colony optimization algorithm (ACOA) [22][23][24][25], rebirthing particle swarm optimization (PSO) algorithm [26], and more recently, simulated annealing (SA) [27,28]. The main goal in the optimal design of a storm sewer system is to find the combination of pipe diameters and pipe slopes which leads to the sewer system with the least cost, with the total cost of the sewer network as the objective function subject to proper constraints.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The cost discussed here consists of the cost of the sewer pipes and the cost of manholes. Steele summarized the average cost of pipes ranging in diameter from 0.3 to 2.1 m and the cost of manholes with different depths [28].…”

mentioning

confidence: 99%

A Novel SWMM Based Algorithm Application to Storm Sewer Network Design

Shao

Zhang

et al. 2017

Water

View full text Add to dashboard Cite

An automated algorithm based on the dynamic hydrological and hydraulic simulation modules in Storm Water Management Model (SWMM) was developed to aid the design of storm sewer networks, provided that a layout is given. Numerical performance of the proposed algorithm was compared with the existing design methods with two application cases. The automated computation process of the sewer network design was divided into two stages and solved iteratively, determining pipe diameter and pipe slope, respectively. In the first stage, starting with a set of initial values including pipe diameter, pipe cover depth, and ground elevation at manholes, the iteration was carried out from the downstream to the upstream while the pipe slopes of the network were assumed to be fixed and the diameter of each pipe segment was calculated. In the second stage, pipe diameters calculated from the first stage were fixed and the pipe slopes were calculated successively from the downstream pipe segment to the upstream pipe segment. Every time the diameter or slope of a pipe segment was adjusted, the pipe flow rate, velocity, and flow depth were obtained by running SWMM hydrological and hydraulic simulation modules. The iteration terminated once the combination scheme of pipe diameters and slopes met the design ordinance which requires the pipe flows full under gravity in a design return period. A real urban sewer system in a hilly city and a benchmark sewer network from the literature were tested to validate the proposed automated algorithm, and good performance was shown. The automated design results explicitly show that the proposed storm sewer design approach leads to a quality solution with reduced computational effort.

show abstract

“…Furthermore, a looped structure cannot be assessed with such steady-state methods. To overcome these limitations, many researchers have extensively focused on optimal design processes using various optimization techniques [4][5][6][7][8][9][10][11][12]. Since these optimization algorithms try to find the optimal combination of pipe diameters as well as slopes among numerous candidates to achieve a minimum-cost solution for the whole network, they are computationally very expensive.…”

Section: Introductionmentioning

confidence: 99%

Assessing Redundancy in Stormwater Structures Under Hydraulic Design

Hesarkazzazi

Hajibabaei

Reyes-Silva

et al. 2020

Water

View full text Add to dashboard Cite

As environmental change is happening at an unprecedented pace, a reliable and proper urban drainage design is required to alleviate the negative effects of unexpected extreme rainfall events occurring due to the natural and anthropogenic variations such as climate change and urbanization. Since structure/configuration of a stormwater network plays an imperative role in the design and hydraulic behavior of the system, the goal of this paper is to elaborate upon the significance of possessing redundancy (e.g., alternative flow paths as in loops) under simultaneous hydraulic design in stormwater pipe networks. In this work, an innovative approach based on complex network properties is introduced to systematically and successively reduce the number of loops and, therefore, the level of redundancy, from a given grid-like (street) network. A methodology based on hydrodynamic modelling is utilized to find the optimal design costs for all created structures while satisfying a number of hydraulic design constraints. As a general implication, when structures are subject to extreme precipitation events, the overall capability of looped configurations for discharging runoff more efficiently is higher compared to more branched ones. The reason is due to prevailing (additional) storage volume in the system and existing more alternative water flow paths in looped structures, as opposed to the branched ones in which only unique pathways for discharging peak runoff exist. However, the question arises where to best introduce extra paths in the network? By systematically addressing this question with complex network analysis, the influence of downstream loops was identified to be more significant than that of upstream loops. Findings, additionally, indicated that possessing loop and introducing extra capacity without determining appropriate additional pipes positions in the system (flow direction) can even exacerbate the efficiency of water discharge. Considering a reasonable and cost-effective budget, it would, therefore, be worthwhile to install loop-tree-integrated stormwater collection systems with additional pipes at specific locations, especially downstream, to boost the hydraulic reliability and minimize the damage imposed by the surface flooding upon the metropolitan area.

show abstract

Heuristic Optimization Model for the Optimal Layout and Pipe Design of Sewer Systems

Cited by 44 publications

References 25 publications

Compressive sensing based structural damage detection and localization using theoretical and metaheuristic statistics

Compressive sensing based structural damage detection and localization using theoretical and metaheuristic statistics

A Novel SWMM Based Algorithm Application to Storm Sewer Network Design

Assessing Redundancy in Stormwater Structures Under Hydraulic Design

Contact Info

Product

Resources

About