This article delivers a new Preisach model representing the correlation between the elastoplastic behavior of structural mild steel under axial monotonic and cyclic loading with damage. The newly formed model is based on the experimentally defined correlation between axial monotonic and cyclic behavior of structural mild steel. To examine the monotonic and cyclic behavior of structural mild steel and find fitting material properties for the model, monotonic and cyclic axial tensile tests are performed. Tests are executed on coupons of the commonly used European structural steel S275. The model represents a mathematical description of modified single-crystal material behavior under monotonic loading. Two different approaches were used to describe damage in the multilinear mechanical model. The excellent agreement with experimental results is achieved by infinitely linking many single-crystal elements in parallel, forming the polycrystalline model. This model provides a good solution for everyday engineering practice due to its geometric representation in the form of the Preisach triangle and the lower costs of monotonic tests used to define material properties compared to cyclic tests.

The construction of many buildings requires ready mixed concrete (RMC) delivery from concrete plants. It is common to supply multiple construction sites, simultaneously, from one or more concrete plants. In such cases, a crucial task is planning the appropriate delivery schedule to each construction site in order to minimize or avoid machinery idling. This paper presents the application of an original model developed in AnyLogic simulation software. The model is based on a hybrid approach, combining two simulation techniques: discrete event and agent-based simulation. This model addresses the supply chain problem, or transportation problem, and can solve the duration and cost of concrete delivery from up to three concrete plants to a maximum of three construction sites simultaneously. The model allows for cost optimization and several other analyses. The fleet of mixers included in the model can be adjusted before running the simulation through the OptionPlant excel file. This paper analyzes a case study based on real parameters obtained from a specific concrete plant and construction sites. Two construction sites and one concrete plant are considered. The costs of transportation, total costs, as well as pump and mixer penalty costs, are calculated. Different analyses and discussion based on conducted results are provided to improve the concrete delivery process.

The construction sector plays an important role in economic development but is highly sensitive to financial constraints during project implementation. While existing studies mainly focus on the sources of financing, less attention has been paid to the availability and timing of financial flows throughout the project lifecycle. Delays in financial disbursements and irregular payment schedules can disrupt construction activities, affect contractor liquidity, and lead to project delays and cost overruns. This paper provides a review of theoretical and empirical studies examining the connection between financing availability, payment timing, and construction project performance. By synthesizing insights from construction management, project finance, and public investment literature, the study highlights key mechanisms through which financing inefficiencies influence project delivery and identifies major gaps for future research.

This paper analyses the application of the Popovics, Eurocode 2 and Stojkovic models for describing the stress–strain curve of 3D printed concrete (3DPC) based on available experimental data. Based on RMSE criteria, it was determined that the Stojkovic model best approximates the experimental results. Functions describing the dependence of model parameters on concrete compressive strength were also proposed, contributing to more accurate numerical analysis of 3D printed structures.

Timber-concrete composite (TCC) systems have application for new floors and for upgrading and enhancing of existing timber floors in residential and office buildings. In order to develop the optimal maintenance programs of structures, it is essential to predict the performance of structures over their life-cycle. The long-term behavior of timber-concrete composite floors is influenced by a combination of various factors, including material properties, load distribution, moisture effects, temperature effects and durability considerations. Timber and concrete material in the composite system, exhibit different behaviors over time due to their inherent characteristics. Deterioration prediction models are used to estimate the future degradation and condition of various types of structures. The aim of this paper is to present two probabilistic models, random variable deterioration rate model and stochastic gamma process model, that will capture uncertainty and variability associated with the deterioration of TCC floor under the service load and to estimate its service life.