The cured-in-place pipe (CIPP) method is currently the most frequently used approach for the renovation of piping without digging; this technology is suitable for pipes made from all types of material. The authors of this paper examined how chemical substances and increased temperature change samples of CIPP with vinyl-ester resin taken from a simulated installation. Changes were observed at several levels: visually via a digital optical microscope, through changes of short-term bending properties and by observation of the activity of the sample structure by means of acoustic emission (AE). Interdependencies among the observed parameters were examined, specifically, the cumulative number of hits (cnt)/deflection and flexural properties/mechanic wave velocity. The test results prove that after three weeks of immersion in a simulated aggressive environment that mirrors what may happen to CIPP in real conditions, short-term mechanical properties change. This is also proven by the results of the AE measurements. For clarity, the results include images from a digital optical microscope. In addition, this paper proves that CIPP samples have good resistance to the action of organic and inorganic acids and to increased temperatures. After three weeks of exposure to a temperature of 100 °C the CIPP flexural properties of the samples had even improved.

This study investigates the relationships between the hydration kinetics of waterglass-activated slag and the development of its physical-mechanical properties, as well as its color change. To modify the calorimetric response of alkali-activated slag, hexylene glycol was selected from various alcohols for in-depth experiments. In presence of hexylene glycol, the formation of initial reaction products was restricted to the slag surface, which drastically slowed down the further consumption of dissolved species and slag dissolution and consequently delayed the bulk hydration of the waterglass-activated slag by several days. This allowed to show that the corresponding calorimetric peak is directly related to the rapid evolution of the microstructure and physical-mechanical parameters and to the onset of a blue/green color change recorded as a time-lapse video. Workability loss was correlated with the first half of the second calorimetric peak, while the most rapid increase in strengths and autogenous shrinkage was related to the third calorimetric peak. Ultrasonic pulse velocity increased considerably during both the second and third calorimetric peak. Despite the modified morphology of the initial reaction products, the prolonged induction period, and the slightly reduced degree of hydration induced by hexylene glycol, the overall mechanism of alkaline activation remained unchanged in the long-term perspective. It was hypothesized that the main issue of the use of organic admixtures in alkali-activated systems is the destabilizing effect of these admixtures on soluble silicates introduced into the system with an activator.

Historical buildings and monuments are largely made of brickwork. These buildings form the historical and artistic character of cities, and how we look after them is a reflection of our society. When assessing ceramic products, great emphasis is placed on their mechanical properties, whilst their durability is often neglected. However, the durability or resistance to weathering of masonry elements is just as important as their mechanical properties. Therefore, this work deals with predicting the durability of solid-fired bricks before they are used when reconstructing monuments and historical buildings. Durability prediction is assessed by identifying defects in the material’s internal structure. These faults may not be visible on the element’s surface and are difficult to detect. For this purpose, non-destructive electroacoustic methods, such as the resonant pulse method or the ultrasonic pulse method, were used. Based on an analysis of the initial and residual mechanical properties after freezing cycles, four durability classes of solid-fired bricks were determined. This work aimed to find a way to predict the durability (lifetime) of an anonymous solid-fired brick, expressed in terms of the number of freeze cycles the brick would last, based on non-destructive measurements.

This article presents research on the behavior of cement-bonded particleboards under mechanical stress caused by the static load. The composition of the boards was modified using alternative raw materials–dust (DU) forming during the processing of cement-fibre boards and particle mixture (PM) generated in the production of cement-bonded particleboards. The particleboards (1-year-old) were subjected to an adverse environment (100 to 250 frost cycles). Mechanical parameters were tested, and the development of defects during static load of the boards by bending was analyzed using acoustic emission. Particleboards with modified compositions are slightly more resistant to adverse environments. The results of the acoustic emission showed the different types of defects occurring under stress by bending. Standard-composition particleboards showed defects located mainly under the cylindrical stress-test head. The modified boards showed larger location distribution of the occurring defects that were also concentrated further away from the cylindrical stress head. The energy during the occurrence of defects was higher in the modified boards in the location of weight application than in the reference boards.

The impact-echo diagnostic method is a well-known nondestructive pulse compression test method, which can be relatively easily used for the testing of concrete and reinforced concrete elements. The evaluation of the measurement with this method is based on the analysis of the signal itself in the time and frequency domains. This allows acquisition of information on the velocity of the mechanical wave, the resonant frequency of the specimen or on the presence of internal defects. The ability to interpret these measurements depends on the experience of the diagnostic technician. The advent of classification algorithms in the field of machine learning has brought an increasing number of applications where the entire interpretation phase can be considerably simplified with the help of classification models. However, this automated evaluation procedure must be provided with the information of whether the signal acquired by the test equipment has actually been measured under optimally set conditions. This paper proposes a procedure for the mutual comparison of different measuring setups with a variable tip type, hammer handle and impact force. These three variables were used for a series of measurements which were subsequently compared with each other using multi-criteria evaluation. This offers a tool for the evaluation of measured data and their filtering. As an output of the designed method, each measurement is marked by a score value, which represents how well the acquired signal fit the weight demands for each observed feature of the signal. The method allows the adjustment of selected demands for a specific application by means of set thresholds. This approach enables the understanding of characteristics of the signal in the automated pre-processing of measured data, where computing power is limited. Thus, this solution is potentially suitable for remote long-term observations with sensor arrays or for acoustic emission signals pre-processing.

Sewage and water networks are crucial infrastructures of modern urban society. The uninterrupted functionality of these networks is paramount, necessitating regular maintenance and rehabilitation. In densely populated urban areas, trenchless methods, particularly those employing cured-in-place pipe technology, have emerged as the most cost-efficient approach for network rehabilitation. Common diagnostic methods for assessing pipe conditions, whether original or retrofitted with-cured-in-place pipes, typically include camera examination or laser scans, and are limited in material characterization. This study introduces three innovative methods for characterizing critical aspects of pipe conditions. The impact-echo method, ground-penetrating radar, and impedance spectroscopy address the challenges posed by polymer liners and offer enhanced accuracy in defect detection. These methods enable the characterization of delamination, identification of caverns behind cured-in-place pipes, and evaluation of overall pipe health. A machine learning algorithm using deep learning on images acquired from impact-echo signals using continuous wavelet transformation is presented to characterize defects. The aim is to compare traditional machine learning and deep learning methods to characterize selected pipe defects. The measurement conducted with ground-penetrating radar is depicted, employing a heuristic algorithm to estimate caverns behind the tested polymer composites. This study also presents results obtained through impedance spectroscopy, employed to characterize the delamination of polymer liners caused by uneven curing. A comparative analysis of these methods is conducted, assessing the accuracy by comparing the known positions of defects with their predicted characteristics based on laboratory measurements.