An integrated AHP-PROMETHEE II ranking method to evaluate the resilience of sewer networks considering urban flood and ground collapse risks.

The aim of this study is to present criteria to evaluate the resilience of sewer networks related to ground collapse and urban flooding likely to occur in a specific region and then to determine the ranks of the sewer networks resilience of the selected regions to show the applicability of the analytic hierarchy process (AHP) and the Preference Ranking Organization Method for Enriching Evaluations (PROMETHEE II) method. Fourteen evaluation criteria representing resistance, reliability, redundancy, and response and recovery are presented and their weights are estimated by the AHP by asking questionnaires to 10 sewer experts, leading to the result that the sub-criteria of reliability showed the highest importance, followed by the length ratio of good pipelines (under resistance) and adequacy of the flow capacity of the bypass pipelines (under redundancy). Four separate small blocks of drainage areas (total area of 3.57 km2; sewer length of 50.6 km) in Seoul are chosen for the case study. Using appropriate preference functions and thresholds for each evaluation criterion for PROMETHEE II application yields the resilience rankings of four blocks as Block III > Block IV > Block I > Block II. A sensitivity analysis was also carried out by changing the weights.

Sustainability assessment of retrofitting alternatives for large and old wastewater treatment plants in Seoul.

Old wastewater treatment plants (WWTPs) must be upgraded to alleviate the problems associated with aging and reduce their total environmental impacts. To enhance the environmental sustainability in retrofitting large and old WWTPs, the decision-making process for selecting the most appropriate alternative is complicated. In this study, evaluation criteria were proposed to select the most sustainable alternatives for mid- to long-term retrofitting plans for a large WWTP with the treatment capacity of 1.6 M m3/d, which is initially built in 1987. An analytic hierarchy process was applied to estimate the weights of each criterion. Fourteen experts evaluated the relative importance of criteria through pairwise comparisons. In order to assess the current retrofitting opinions, three retrofitting alternatives were constructed: A focused on energy sufficiency; B expanded the bioreactor capacity and enhancement of the facility for incinerating the sludge leaving the anaerobic digestor; C emphasized the treatment of contaminants of emerging concerns (CECs). A achieved the highest score (0.623) owing to the environmental benefits associated with recycling and first flush stormwater treatment. C exhibited the second highest score (0.612) as the focus on CECs removal. B corresponded to the lowest sustainability (0.426), with the lowest scores pertaining to effective land use and first flush stormwater treatment.

Evaluation of sewer network resilience index under the perspective of ground collapse prevention.

Generally, when evaluating the resilience of infrastructure, the four properties of resilience (robustness, rapidity, resources, and redundancy, 4Rs) are widely considered. However, there is little research on the resilience assessment of sewer networks. Therefore, to establish a framework to evaluate sewer network resilience under the perspective of urban ground collapse prevention, this study considers the 13 second-level detailed indicators corresponding to the four first-level indicators (4Rs) based on literature reviews and experts' opinions. An analytic hierarchy process (AHP) is used to obtain relative weights of each indicator and a weighted sum method (WSM) is used to evaluate the sewer network resilience index (SRI). The evaluation system is applied to eight small blocks of selected drainage areas in Seoul, South Korea, and the SRI of eight small blocks are computed. This study could help the sewer management department to make decisions and manage sewer network assets that enhance the resilience of the sewer networks.

Non-Target Structural Displacement Measurement Using Reference Frame-Based Deepflow.

Displacement is crucial for structural health monitoring, although it is very challenging to measure under field conditions. Most existing displacement measurement methods are costly, labor-intensive, and insufficiently accurate for measuring small dynamic displacements. Computer vision (CV)-based methods incorporate optical devices with advanced image processing algorithms to accurately, cost-effectively, and remotely measure structural displacement with easy installation. However, non-target-based CV methods are still limited by insufficient feature points, incorrect feature point detection, occlusion, and drift induced by tracking error accumulation. This paper presents a reference frame-based Deepflow algorithm integrated with masking and signal filtering for non-target-based displacement measurements. The proposed method allows the user to select points of interest for images with a low gradient for displacement tracking and directly calculate displacement without drift accumulated by measurement error. The proposed method is experimentally validated on a cantilevered beam under ambient and occluded test conditions. The accuracy of the proposed method is compared with that of a reference laser displacement sensor for validation. The significant advantage of the proposed method is its flexibility in extracting structural displacement in any region on structures that do not have distinct natural features.