Let us suppose a situation in which it is necessary to check the car before going on a journey, a situation in which breakdowns appear but also mysteriously disappear, a situation where solving problems with the vehicle is only possible by looking at the data obtained by reading sensors, routine vehicle checking (insight into data irregularity), "real-time" monitoring of car condition…The main goal of this paper is the early detection of erroneous readings of vehicle airflow systems in real time and constant monitoring of the subject vehicle, by coupling and using trained models based on machine learning tools of artificial intelligence and using "Infinity" device.

One of the most important tasks of managing the construction process is to achieve the highest possible productivity. The productivity that can be achieved on a construction site depends on a number of influencing factors and on the type of work that is executed. Concrete works are a crucial activity when constructing high-rise buildings built in the RC frame structural system. Therefore, it is very important to adequately manage the concreting process in order to meet the set deadlines and reduce costs. This paper presents an approach for predicting the productivity of the concreting process based on the conducted quantitative research, by recording the concreting process on construction sites of buildings in Niš, Serbia. The concreting of reinforced concrete columns and walls on seven construction sites was recorded for 20 months. The total amount of fresh concrete that is built into the elements is 848 m3 and the total duration is 114 h of work. Factors that can affect productivity have been identified and, by applying the multiple linear regression and simulation methods and techniques and using the discrete event method and the agent-based method, models have been developed to predict the productivity of the concreting of reinforced concrete columns and walls. An analysis of the developed models was performed, and a comparative presentation was provided.

Steel-timber composite structures have numerous advantages compared to steel only and timber only structures. One of the most important parts of a composite structure is the composite connection. Object of this research was a steel-CLT composite connection consisting of a steel profile, a cross-laminated timber (CLT) panel and a bolt with nut and washer. Aim of the research was to develop an efficient finite element (FE) model of a bolted steel-CLT composite connection and to validate it experimentally. The research process consisted of several steps: experimental testing of the considered connection using asymmetrical push-out test, numerical modelling and analysis of the connection using Finite Element Method (FEM), validation of the numerical model using experimental results, and parametric study of the proposed numerical model. For numerical analysis, an innovative method for timber modelling has been proposed. The comparison between the experimental and numerical research results demonstrated that the proposed numerical model was convenient for practical application in structure analyses. The parametric study showed that, in some cases, atypical failure modes of the connection occurred. Based on registered behavior, a recommendation is given to calculate the load capacity of the connection integrally, taking into account both the primary (Johansen’s) and the secondary (rope effect) part of the connection strength, instead partially, as proposed by EN standards.

Supply of Ready Mixed Concrete (RMC) is a common process of concrete works on any structure. There is often a need to supply one or more construction sites simultaneously from multiple concrete plants. This paper presents a new simulation model of RMC supply and delivery from three concrete plants to three construction sites. The model is dynamic, easily managed, and adjustable and it allows proper estimation of the cost and time required to solve the problem of RMC supply. Model verification was performed using a case study of concrete supply to construction sites in the city of Niš, Serbia. The case study is based on real parameters obtained from specific concrete plants and construction sites. The results of the simulation experiment with varying number of mixers indicate that there is a significant influence of vehicle number and volume on idling costs. Based on the model analysis in the case study, scenario 10 (minimum total idling cost is 14,09 €) is recommended as the optimal combination of truck mixers for the considered case study. The simulation results indicate that the selection of an adequate combination can significantly reduce the costs of idling, for both the mixer and the pump, which leads to minimal idling time and, consequently, to timely pouring of concrete without reducing its quality.