Performance Modeling for Sewer Networks

In spite of the pressing need to preserve sewer networks, sewer pipelines and manholes are prone to deterioration and hence to collapse. According to the American Society of Civil Engineers (ASCE) (2017), the sewer network’s grade of the United States (US) is grade “D+”, making it one of the worst infrastructure assets in the US. In addition, the Canadian Infrastructure Report Card (CIRC) (2016) states that more than half of their linear wastewater assets’ physical condition were ranked between very poor to good states, with a total replacement value of $47-billion. Despite the enormous studies conducted in this field, many of the efforts lack a comprehensive assessment of sewer components, leading to misjudged rehabilitation decision plans and continued asset deterioration. Improved cost-effective models that optimize sewer rehabilitation plans, given the scarcity of resources, are clearly needed. Accordingly, the paramount objective of this research is to design a decision-support system that optimizes the maintenance, rehabilitation and replacement (MRR) decisions of sewer pipelines and manholes. The first phase of the research is to identify several defects that impact the condition of sewer components and to model the erosion void defect utilizing fuzzy expert system. The model provided accuracy, true positive rate and precision values of 83 The research establishes an approach to aggregate the condition indexes of all pipelines and manholes in the network through a criticality model to supply the overall network performance index. Accordingly, the economic factors are deemed the most important ones compared to environmental and public factors. An informative optimized model that integrates the outputs of the previously developed models is designed through the Particle Swarm Optimization (PSO) approach to maximize the sewer network performance and minimize the total costs. Different trade-off solutions are then established by varying the weights of the objective functions and considering the defined constraints. The best network performance improvement attained is 1.47 with a total cost of$1.39- million. The comprehensive sewer network assessment performed in this research will improve current practices in sewer networks management, thereby reducing sewer network failures and avoiding catastrophic sinkholes

Automated Sewer Inspection Analysis and Condition Assessment

Underground infrastructure serves an essential need for the society. Huge number of facilities is dedicated to facilitate the well-being’s needs. Sewer infrastructure, one of the facilities, plays a major role in maintaining healthier environment. Its main duty is to transfer sewage material to treatment plants or any designated disposal area. Therefore, providing well performing sewer systems is essential to avoid any breakdown. Nevertheless, sewer pipelines’ condition in North America is deteriorating. In fact, studies have shown that 30% of municipal infrastructure in Canada is in either fair or very poor condition. As a result, there is a significant requirement for inspection and rehabilitation. Many municipalities utilize Closed Circuit Television (CCTV) inspection technique in inspecting sewer pipelines. However, this technique suffers from significant subjective and imprecise conclusions. Hence, studying, analyzing and applying different sewer inspection technologies and designing a condition assessment model are necessary to reduce subjectivity and errors and produce accurate and reliable results. This research aims to develop an automated tool to quantify: deformation, settled deposits, infiltration and surface damage sewer defects. The automated approach is dependent upon using image processing techniques and several models to analyze output data from 2D laser profiler, sonar and electroscan. Other than using ASTM F1216 formula, the research suggests applying the roundness factor in quantifying the deformation defect. The research develops a condition assessment model, based on the aforementioned defects, to arrive to an aggregated index suggesting the condition of sewer pipelines. Multi Attribute Utility Theory (MAUT) approach is used for each defect. The research also suggests a methodology to evaluate the surface damage defect of sewer pipelines for reinforced concrete, vitrified clay and ductile iron sewer pipeline materials. An interface, using MATLAB, was developed to implement the designed quantification algorithms and the MAUT model on real case studies. After implementing and validating the two deformation quantification methods, the Mean Absolute Error (MAE) utilizing the ASTM F1216 was 4.27%, while the MAE using the roundness factor was 4.83%. The maximum difference percentage was found to be 40.06%; however, the minimum difference percentage was 0.59%. The average difference percentage for all the cases was calculated as 16.67%. Later, the MAUT model was validated with actual case studies. Three rounding types (rounding to nearest number, rounding up and down) were tested to change the aggregated index, containing decimals, to a whole number. Mean Absolute Error (MAE) was utilized to compare the rounding types. In all case studies, rounding up type produced the lowest MAE values. When rounding up the computed index in case study 1, the MAE for Concordia Sewer Protocol (CSP), Water Research Centre (WRc) and New Zealand were 0.33, 0.33 and 0.42, respectively. This research shall encourage subject matters to utilize technologies, other than or beside CCTV, to conclude sound results. The developed automated user interface shall reduce inaccuracy and subjectivity through the application of robust image processing algorithms. After extending this research in including several sewer’s components and defects, the condition assessment model shall aid asset managers to allocate their maintenance and rehabilitation budgets

A Human Evacuation System for Smart Cities

The evacuation procedure is an unexpected process and can happen at any moment. In this paper, the human evacuation system based on wireless sensor networks is proposed to guide firefighters, security people, and people involved in rescuing and evacuating humans during disastrous conditions or evacuation processes. The functional system designed and implemented in this paper will detect whether the place is emptied from people or not. Also, to make sure places are safe and there is no risk to forget anyone in case any disaster occurred. The system will be used in a fire disaster, instead of the fireman entering the dangerous place to clear the place, the system will detect who is inside, and the alarm will start ringing, and he will be able to see from the tablet where is the person exactly to help him without risking his life. The interacting system can also be used during school days, for example, at the end of the day to clear the building before closing the school or even during break time, where students are not allowed to stay in classes for safety reasons. This system will make sure that no student is left in the class. Furthermore, this functional system can also be used in malls at the end of the day before closing to ensure that the mall is empty and no one is inside. It will save time and provides safety for people

A practical guide to managing hypertension, hyperlipidemia, and hyperglycemia in patients with chronic myeloid leukemia

Tyrosine kinase inhibitors (TKIs) have significantly improved the prognosis of chronic myeloid leukemia (CML) since their approval. Although safe in general, TKIs carry concerns about cardiovascular adverse events. Hypertension, diabetes, and dyslipidemia are among the most common baseline comorbidities among CML patients. Guidelines for the management of the existing comorbidities or those related to TKI therapy are lacking. This paper will review hypertension, hyperglycemia and hyperlipidemia reported in CML patients or associated with TKI therapy and then propose a simple guide on their management

A practical guide to managing cardiopulmonary toxicities of tyrosine kinase inhibitors in chronic myeloid leukemia

Tyrosine kinase inhibitors (TKIs) have revolutionized the treatment of chronic myeloid leukemia (CML) but their use was associated with a range of serious cardiopulmonary toxicities including vascular adverse events, QT prolongation, heart failure, pleural effusion, and pulmonary arterial hypertension. Dedicated clinical management guidelines for TKI-induced toxicities are not available. This review aims to discuss TKI-associated cardiopulmonary toxicities and proposes a practical guide for their management

Condition assessment of sewer pipelines using multi attribute utility theory (MAUT)

Many municipalities rely on the interpretation of Closed Circuit Television (CCTV) inspection reports to arrive to a condition assessment grade for the inspected sewer pipelines. The grades stand as a key for decision makers in their maintenance and rehabilitation plans. The paper will propose a condition assessment for sewer pipelines using Multi Attribute Utility Theory (MAUT). The condition assessment model utilizes MAUT to generate utility functions for four sewer pipeline defects: deformation, settled deposits, infiltration and surface damage. Minimum and maximum values were adopted, where applicable, from the Water Research center (WRc) to build the utility functions. The grades are changed to 0 to 10 utility scale to plot the points considered. The deformation defect utility curve was polynomial of degree two and the coefficient of correlation (R2) was exactly 1. However, the settled deposits defect utility curve was polynomial of degree three with R2 of 0.9993. The proposed model aims to provide information for asset managers about the severity of some sewer defects existing in sewer pipelines. In addition, it reinforces their plans for rehabilitation and maintenance by suggesting the existing condition of the sewer pipelines.Scopu

Integrated Reliability Assessment Model for Drinking Water Networks: A Case Study of the City of London, Canada

Water distribution networks (WDNs) are complex interconnected networks that require extensive planning and maintenance to ensure good quality water is delivered to all consumers. The main task of WDNs is to provide consumers with a minimum acceptable level of supply (in terms of pressure, availability, and water quality) at all times under a range of operating conditions. However, the water infrastructure in North America signifies an urgent need of upgrading the aging and deteriorating distribution systems if they are to continue to provide consumers with reliable and safe water supplies. In this context, this research is proposing a new reliability model for assessing the mechanical/structural as well as hydraulic conditions of a WDN to identify failure-prone components and prioritize their renewal. The developed model provides a systematic and practical methodology to calculate the mechanical/structural reliability of the pipe and its accessories (valves, hydrants, and so on) through the consideration of historical failures of components. The research deployed pressure-dependent demand analysis to determine the hydraulic reliability of the network in meeting the pressure requirements and overall hydraulics of the network. The minimum-cut-set theory was implemented in both reliability assessments, and the outputs of the two models were integrated to provide a representative reliability of the network. A sensitivity analysis was followed to study the change in segments' attributes on the mechanical/structural and hydraulic reliabilities. The approach was implemented on the City of London, Canada, network (north and south) to test its applicability. The developed model is expected to assist decision makers in integrating the failure records with the hydraulic simulation to plan for optimum intervention actions. 2022 American Society of Civil Engineers.Scopu

Prediction of Breaks in Municipal Drinking Water Linear Assets

Improper asset management practices increase the probability of water main failures due to inactive intervention actions. The annual number of breaks of each pipe segment is known as one of the most important criteria for the condition assessment of water pipelines. This metric is also considered one of the major performance measures in levels of service (LoS) studies. In an effort to maximize the benefits of historical data, this research utilized the evolutionary polynomial regression (EPR) method in determining the best mathematical expression for predicting water pipeline failures. The prediction model was trained and tested on the city of Montreal water network. After determining the best independent variables through the best subset regression, pipelines were clustered based on their attributes (length, diameter, age, and material). The majority of the models provided high R2 values, but the highest performing model's R2 was 89.35%. Further, a sensitivity analysis was also performed and showed that the most sensitive parameter was the diameter, and the most sensitive material type to age was ferrous material. The tools and stages performed in this research showed promising results in predicting the expected water main failures using four different asset attributes. Therefore, this research can be implemented in asset management best practices and in LoS performance measures to predict the number of water pipeline failures. To further improve the prediction model, additional explanatory variables could be considered along with leveraging multiple artificial intelligence tools. 2020 American Society of Civil Engineers.Scopu

Optimized maintenance model for wastewater treatment plants

Wastewater treatment plants (WWTPs) are facing significant deterioration due to aging and improper maintenance. Statistics Canada reported that 22% and 14% of the wastewater treatment plants in Alberta and Ontario, respectively, are in poor and very poor conditions. Because of the non-capital and capital improvement requirements for any WWTP, intervention decision-making tools are paramount. The objectives of this research were to develop an integrated condition rating model for the WWTP and an optimized maintenance, rehabilitation, and replacement (MR&R) intervention model. The condition assessment model was applied on case studies and the indices supplied by the operators were used to compare the results of model through the mean absolute error (MAE) calculation, which was minimal. To optimize the intervention decisions for various units of the WWTP, the binary integer programming was used. These models are expected to enhance the evaluation of WWTPs and facilitate intervention plans based on an optimized methodology.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author