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Among the various types of polymeric materials, geosynthetics deserve special attention. A geosynthetic is a product made from synthetic polymers that is embedded in soils for various purposes. There are some basic functions of geosynthetics, namely, erosion control, filtration, drainage, separation, reinforcement, containment, barrier, and protection. Geosynthetics for erosion control are very effective in preventing or limiting soil loss by water erosion on slopes or river/channel banks. Where the current line runs through the undercut area of the slope, the curvature of the arch is increased. If this phenomenon is undesirable, the meander arch should be protected from erosion processes. The combination of geosynthetics provides the best resistance to erosion. In addition to external erosion, internal erosion of soils is also a negative phenomenon. Internal erosion refers to any process by which soil particles are eroded from within or beneath a water-retaining structure. Geosynthetics, particularly geotextiles, are used to prevent internal erosion of soils in contact with the filters. Therefore, the main objective of this review paper is to address the many ways in which geosynthetics are used for erosion control (internal and external). Many examples of hydrotechnical and civil engineering applications of geosynthetics will be presented. [ABSTRACT FROM AUTHOR]

Implementing rain garden (RG) designs is widespread worldwide to reduce peak flow rates, promote stormwater infiltration, and treat pollutants. However, inadequate RG design degrades its hydrological behaviour, requiring the development and validation of an appropriate hydrological model for the design and analysis of structures. This study aimed to improve a hydrological infiltration model based on Darcy's law by taking into account the height of the water column (HWC) at the surface of the RG and the filtration coefficients of soil materials. The model was tested by simulating the hydrological characteristics of a rain garden based on a single rain event of critical intensity (36 mm/h). Using the validated model, design curves were obtained that predict the performance of the RG as a function of the main design parameters of the structure: water column height, ratio of catchment area to structure area, layer thickness, and soil filtration coefficient. The hydrological efficiency of the RG was evaluated in terms of the time of complete saturation, filling of the structure with water, and determining the change in HWC caused by changes in the parameters. The filtration coefficient and thickness of the upper and intermediate infiltration layers of the RG are the main parameters that affect the depth of saturation of the layers of the structure and the HWC on the surface. The model is not very sensitive to the model parameters related to the lower gravel layer. If the top layer's thickness increases by 10 cm, it takes longer to fill the structure with water, and the HWC on the surface reaches 0.341 m. The rain garden's performance improves when the filtration coefficient of the top layer is 7.0 cm/h. Complete saturation and filling of the structure with rainwater do not occur within 7200 s, and the water column reaches a height of 0.342 m at this filtration coefficient. However, the rain garden's effectiveness decreases if the filtration coefficient of the upper and intermediate layers exceeds 15 cm/h and 25 cm/h, respectively, or if the catchment area to RG area ratio decreases to values below 15. The modelling results confirm that considering the HWC in RG hydrological models is essential for designing structures to minimise the risk of overflow during intense rainfall events. [ABSTRACT FROM AUTHOR]

This paper examines the effectiveness of sustainable warehouse design with regard to fire regulations and costs. When designing industrial facilities, the high risk of fire during their subsequent operation must be considered. Therefore, in this article, the variant analysis in terms of cost and technological, sustainable solutions for the investment in the "design and build" system were subjected to fire protection installation systems for three variants with different fire zones. During the modelling, the impact of the fire zone on the spread of smoke, temperature changes at a selected point above the fire source, and visibility were examined. Numerical analyses showed differences in the degree of smoke spread for variants I, II, and III without any relevant impact on the effectiveness of evacuation. The division of the hall into a larger number of fire zones reduces the effects of a potential fire. This study highlights that the cost of the investment is vastly influenced by the conditions of fire protection and evacuation. [ABSTRACT FROM AUTHOR]

Almost every civil engineering project involves heavy construction equipment to create earthworks. This in turn is connected with carbon dioxide emissions, which are hazardous to the environment, especially in densely populated areas. Strict control and regulation of emissions from construction equipment has already been introduced in Hong Kong. This paper presents the results of several years of field research on the performance of construction equipment (excavators). The comparative analysis concerns the data obtained during a field survey in relation to the outlays proposed in the catalogues of material outlays commonly used in Poland (KNR catalogues.) The presented problem fills in the gaps in research on the performance of construction equipment. The results of the study clearly show the discrepancy between theoretical data from the KNR and the actual use of construction equipment during the construction of underground sanitary networks. Apart from the excessive consumption of diesel fuel, sequentially increased CO2 emissions occur. The presented research results allow for the development of an innovative method for the optimal use of heavy construction equipment, thus reducing CO2 emissions. This study is a continuation of a pilot study conducted by the staff of the Institute of Civil Engineering, Warsaw University of Life Science. [ABSTRACT FROM AUTHOR]

The properties and behavior of soils depend on many factors. The interaction of individual factors is difficult to determine by traditional statistical methods due to their interdependence. The paper presents a procedure of creating an artificial neural network (ANN) model to determine the value of the damping ratio (D) of clay soils. The main purpose of this paper is to compare the appropriateness of ANN model application with empirical formulas described in the literature. The ANN model was developed using a series of laboratory tests of the damping ratio performed in the Resonance Column. Predicted values of the damping ratio of clay soils obtained from the ANN model are characterized by high convergence (coefficient of determination R2 = 0.976). In comparison with other published empirical formulas, the ANN model showed an improvement in the prediction accuracy. What is more, ANN models proved to be more flexible compared to formulas and relationships with a predetermined structure, and they were well suited to modeling the complex behavior of most geotechnical engineering materials, which, by their very nature, exhibit extreme variability. In conclusion, ANNs have the potential to predict the damping ratio (D) of clay soils and can do much better than traditional statistical techniques. [ABSTRACT FROM AUTHOR]

The paper presents a method of application of an ANN (Artificial Neural Network) to predict the permeability coefficient k in sandy soils: FSa, MSa, CSa. To develop an ANN the results of permeability coefficients from pumping and consolidation tests were applied. The proposed ANN with an architecture 6-8-1 predicts the value of permeability coefficient k based on the following parameters: soil type, relative density ID, void ratio e and effective soil diameter d10. The mean relative error and single maximum value of the relative error for the proposed ANN are following: Mean RE = ±4%, Max RE = 7.59%. The use of the ANN to predict the soil permeability coefficient allows the reduction of the costs and time needed to conduct laboratory or field tests to determine this parameter. [ABSTRACT FROM AUTHOR]

This paper presents a method describing the application of artificial neural networks to evaluate the change in undrained shear strength in cohesive soils due to principal stress rotation. For analysis, the results of torsional shear hollow cylinder (TSHC) tests were used. An artificial neural network with an architecture of 7–6–1 was able to predict the real value of normalized undrained shear strength, τfu/σ’v, based on soil type, over-consolidation ratio (OCR), plasticity index, IP, and the angle of principal stress rotation, α, with an average relative error of around ±3%, and a single maximum value of relative error around 6%. [ABSTRACT FROM AUTHOR]

Exceeding the approved budget is often an integral part of the implementation of construction projects, especially those where unforeseen threats may occur. Therefore, each construction investment should contain elements of risk forecasting, mainly in terms of the cost of its implementation. Only a small number of institutions apply effective cost control methods, taking into account the specifics of a given industry. Especially small construction companies that participate in the structure of the implementation of large construction projects as subcontractors. The article presents a method by which it is possible to determine, with certain probability, the final cost of railway construction investments carried out in Poland. The method was based on a reliable database of risk factors published in sources. In this article, the main presumptions of the original method are presented, which take into account the impact of potential, previously recognized, risks specific to railway investments, and enable project managers to relate them to the conditions where the implementation of a specific object is planned. The authors assumed that such a relatively simple method, supported by a suitable computational program, would encourage teams that plan to implement railway projects to use it and increase the credibility of their schedules. [ABSTRACT FROM AUTHOR]