As a by-product of wastewater treatment, sewage sludge can be used for natural, agricultural, or energy purposes. One method of preparing sludge for management and use is solar drying. To intensify the drying process, natural additives can be used to alter the structure of the sludge and accelerate the evaporation of water. This research aimed to evaluate the influences of different organic additives in sewage sludge mixtures on the physicochemical and energy parameters of briquettes. This research was carried out without thermal boosting in a 4 × 2.5 × 2 m plastic tunnel. The tunnel was equipped with three drying stations and control and measuring equipment. In two test series, sludge additives in the form of straw and lignocellulosic materials, sawdust, bark, woodchips, and walnut shells, were used. Briquettes were made from the resulting mixtures and then subjected to physical and chemical analyses. This research showed high variability in the contents of trace elements, nitrogen, and sulphur in relation to an increase in the amount of sludge in the briquettes, which, for the briquettes made from sewage sludge, was nearly twice as high as for the briquettes made from the mixtures. The results of the flue gas analysis for the briquettes with sawdust and wood chip additives were very similar. The briquettes made from sewage sludge with lignocellulosic materials (bark and wood chips) had fuel properties similar to woody biomass, with a calorific value and heat of combustion of 15–16 MJ/kg. Fibrous additives (straw) significantly increased the strength parameters of the briquettes, by more than 50% of the value. The compositions and properties of the mixtures affected the following briquetting parameters: temperature and compressive force. The briquettes made from sewage sludge and additives can be classified according to ISO 21640 as SRFs (solid recovered fuels). In most of the results, the net calorific value (NCV) was 3 to 4; the chlorine content (CL) was 2 to 1; and the mercury content (Hg) was 1. The sewage sludge mixtures facilitated the agricultural and energy use of the briquettes.

The article discusses an example of the use of graph search algorithms with trace of water analysis and aggregation of failures in the occurrence of a large number of failures in the Water Supply System (WSS). In the event of a catastrophic situation, based on the Water Distribution System (WDS) network model, information about detected failures, the condition and location of valves, the number of repair teams, criticality analysis, the coefficient of prioritization of individual network elements, and selected objective function, the algorithm proposes the order of repairing the failures should be analyzed. The approach proposed by the authors of the article assumes the selection of the following objective function: minimizing the time of lack of access to drinking water (with or without prioritization) and minimizing failure repair time (with or without failure aggregation). The algorithm was tested on three different water networks (small, medium, and large numbers of nodes) and three different scenarios (different numbers of failures and valves in the water network) for each selected water network. The results were compared to a valve designation approach for closure using an adjacency matrix and a Strategic Valve Management Model (SVMM).

This study demonstrates the use of the differential evolution method for optimizing multi-source water supply systems. The objective was to identify a water-supply scenario that minimizes the total water-supply costs in multiple sources network. The analysis assumed varying water-production costs at each source, with control implemented through the adjustment of valve settings at the network inlets. For the research, open-source tools such as EPANET, the WNTR library, and Python’s scipy.optimize package, were utilized. The analyses were conducted on two water distribution networks. The first was a simplified network with three water sources, designed to validate the simulation environment and perform initial assessments of the optimization algorithms, whereas the second was a complex model representing a real water distribution network. Analyses were conducted for the latter assuming three, four, five, and six sources. For both networks, multiple pricing scenarios were evaluated to explore how different conditions impact the performance of the algorithm. The results show that near-optimal solutions can be achieved with significantly reduced computation times. The differences in objective function values between the brute force and differential evolution (DE) methods were no greater than 0.2%, while the computation time for DE was substantially shorter. These findings highlight DE scalability, efficiency, and potential for real-world applications, promoting cost-effective and accessible optimization in engineering practice.

This paper presents a simulation-based method for classifying failures in water distribution systems according to their impact on network operation. The method combines hydraulic simulation, element criticality assessment, flow-path analysis, valve-isolation analysis, and repair-time estimation...