Leaks in resource transmission pipelines is a growing concern for the water transmission industry. This creates a need to prevent the threat of leaks and minimize their damages through extensive research in leak detection technology. This research work provides a thorough investigation into the history of leak detection in pipelines by surveying the web of knowledge database and visualizing the outputs using visualization software VOSviewer and CiteNetExplorer. The analysis of the web of knowledge output presents a set of the ten most used keywords in the field of leak detection in pipelines that are further described and analyzed. Additionally, in-depth analysis of a randomly selected sample of papers was conducted to draw a sense of the progress in the industry over the past four decades. This article also defines a novel approach to define the leak detection phases, i.e., the identify-localize-pinpoint approach. Furthermore, two classes of leak detection systems are identified, static leak detection systems and dynamic leak detection systems. The two systems are defined as well as their differentiative capabilities. Finally, this article provides a summary of popular leak detection technologies to provide a broad sense of understanding for the leak detection field of research.

Water mains, especially old pipelines, are consistently threatened by the formation of leaks. Leaks inherit increased direct and indirect costs and impacts on various levels such as the economic field and the environmental level. Recently, financially capable municipalities are testing acoustic early detection systems that utilize wireless noise loggers. Noise loggers would be distributed throughout the water network to detect any anomalies in the network. Loggers provide early detection via recording and analyzing acoustic signals within the network. The city of Montreal adopted one of the leak detection projects in this domain and had reported that the main issue that hinders the installed system is false alarms. False alarms consume municipality resources and funds inefficiently. Therefore, this paper aims to present a novel approach to utilize more than one data analysis and classification technique to ameliorate the leak identification process. In this research, acoustic leak signals were analyzed using Fourier Transform, and the multiple frequency bandwidths were determined. Three models were developed to identify the state of the leak using Naïve Bayes (NB), Deep Learning (DL), and Decision Tree (DT) Algorithms. Each of the developed models has an accuracy ranging between 84% to 89%. An aggregator approach was developed to cultivate the collective approaches developed into one single answer. Through aggregation, the accuracy of leak detection improved from 89% at its best to 100%. The design, implementation approach and results are displayed in this paper. Using this method helps municipalities minimize and alleviate the costs of uncertain leak verifications and efficiently allocate their resources.

Paving blocks might encounter diverse environmental conditions during their lifespan. The durability of paving blocks is determined by their capacity to endure various exposure conditions. Synthetic fibers have been used in mortar and concrete to improve their properties. This research investigates the influence of including banana fiber (BF) on the physical and mechanical characteristics of mortar. Five different mortar mixes were developed, with varying amounts of BF ranging from 0 to 2% by volume. Testing included ultrasonic pulse velocity, compressive strength, flexural strength, total water absorption, and sorptivity. Specimens were cured for up to 90 days. The results indicate that using 0.5% BF resulted in an improvement in compressive and flexural strength compared to the control mix. There was an increase in total water absorption and the water absorption coefficient in the presence of fibers. There appeared to be good correlations between the compressive strength and the other properties examined.

Over the last decades, concrete has been excessively prone to cracks resulting from shrinkage. These dimensional changes can be affected by the incorporation of supplementary cementitious materials. This work used olive waste ash (OWA), which could substantially tackle this problem and achieve sustainability goals. For this issue, five cement paste mixes were prepared by replacing cement with OWA at different percentages varying from 0 to 20% by weight with a constant increment of 5%. The water-to-cement ratio was 0.45 for all mixes. Compressive strength and flexural strength were investigated at 7, 28, and 90 days. In addition, three shrinkage tests (drying, autogenous, and chemical) and expansion tests were also conducted for each mix and measured during 90 days of curing. The experimental findings indicated that there was a loss in compressive and flexural strength in the existence of OWA. Among all mixes containing OWA, the samples incorporating 10% OWA exhibited maximum strength values. Furthermore, the chemical and autogenous shrinkage decreased with the incorporation of OWA. However, the drying shrinkage decreased at lower levels of substitutions and increased at higher replacement levels. In addition, there was a growth in expansion rates for up to 10% of OWA content, followed by a decrease at higher levels (beyond 10%). Additionally, correlations between these volumetric stability tests were performed. It was shown that a positive linear correlation existed between chemical shrinkage and autogenous and drying shrinkage; however, there was a negative relationship between chemical shrinkage and expansion.