Developing Environmentally Sustainable and Cost-Effective Geopolymer Concrete with Improved Characteristics

Improving the efficiency and quality of construction mainly depends on the cost of building materials, which is about 55–65% of total capital-construction costs. The study aimed to obtain geopolymer fine-grained concrete with improved quality characteristics that meet the construction field’s sustainable development criteria and that have environmental friendliness, economic efficiency, and advantages over competing analogues. The dependences of strength characteristics on various compositions of geopolymer concrete were obtained. It was found that the most effective activator is a composition of NaOH and Na2SiO3 with a ratio of 1:2. The increase in the indicators of the obtained geopolymer concrete from the developed composition (4A) in relation to the base control (1X) was 17% in terms of compressive strength and 24% in tensile strength in bending. Polynomial equations were obtained showing the dependence of the change in the strength characteristics of geopolymer concrete on the individual influence of each of the activators. A significant effect of the composition of the alkaline activator on the strength characteristics of geopolymer fine-grained concrete was noted. The optimal temperature range of heat treatment of geopolymer concrete samples, contributing to the positive kinetics of compressive strength gain at the age of 28 days, was determined. The main technological and recipe parameters for obtaining geopolymers with the desired properties, which meet the ecology requirements and are efficient from the point of view of economics, were determined

High-Performance Concrete Nanomodified with Recycled Rice Straw Biochar

The development of new and improvement of existing technologies based on the use of waste products from various industries or recyclable materials is a current trend in the construction industry. Including in the composition of binders and concrete by-products of industry, reducing the proportion of Portland cement, it is crucial to maintain and improve the resulting products’ mechanical characteristics and life cycle. The main aim of the study was to investigate the influence of biochar additive on the microstructure and properties of the concrete and obtain the composition with improved characteristics due to nanomodification of rice straw recycled biochar. An environmentally friendly technology for concrete manufacture was obtained, using agricultural waste, rice straw, as its components, developing a composition of concrete nanomodified with processed rice straw biochar, identifying the dependences of concrete properties on their nanomodification with processed rice straw coal. It has been established that the most effective dosage is the addition of rice straw biochar in the amount of 6% by weight of cement. The improvement in the properties of concrete was expressed in the increase in its physical and mechanical characteristics and changes in deformability according to the results of the analysis of the stress-strain diagrams. The increase in strength characteristics ranged from 17% to 25%. The modulus of elasticity increased to 14%. The deformation characteristics decreased from 12% to 24%. Introducing a finely dispersed additive of rice straw biochar modified by the electromagnetic method leads to a decrease in cement consumption by up to 10%

Modeling of Flow Heat Transfer Processes and Aerodynamics in the Cabins of Vehicles

Ensuring comfortable climatic conditions for operators in the cabin of technological machines is an important scientific and technical task affecting operator health. This article implements numerical and analytical modeling of the thermal state of the vehicle cabin, considering external airflow and internal ventilation. A method for calculating the heat transfer coefficients of a multilayer cabin wall for internal and external air under conditions of forced convective heat exchange is proposed. The cabin is located in the external aerodynamic flow to consider the speed and direction of the wind, as well as the speed of traffic. Inside the cabin, the operation of the climate system is modeled as an incoming flow of a given temperature and flow rate. The fields of velocities, pressures, and temperatures are calculated by the method of computer hydrodynamics for the averaged Navier–Stokes equations and the energy equation using the turbulence model. To verify the model, the values of the obtained heat transfer coefficients were compared with three applied theories obtained from experimental data based on dimensionless complexes for averaged velocities and calculated by a numerical method. It is shown that the use of numerical simulation considering the external air domain makes it possible to obtain more accurate results from 5% to 75% compared to applied theories, particularly in areas with large velocity gradients. This method makes it possible to get more accurate values of the heat transfer coefficients than for averaged velocities

Numerical Simulation of Heat Transfer and Spread of Virus Particles in the Car Interior

The epidemic caused by the coronavirus infection SARS-CoV-2 at the beginning of 2022 affected approximately 500 million people in all countries. The source of infection is the particles of the virus, which, when breathing, talking, and coughing, are released with the respiratory droplets and aerosol dust of an infected person. Actions aimed at combating and minimizing the consequences of coronavirus infection led to taking measures in scientific areas to investigate the processes of the spread of viral particles in the air, in ventilation, and air conditioning systems of premises and transport, filtration through masks, the effect of partitions, face shields, etc. The article presents a mathematical model of the spread of viral particles in technological transport. Air intake diverters and the operator’s respiratory tract are the sources of the virus. The Euler–Lagrange approach was used to simulate liquid droplets in a flow. Here, the liquid phase is considered as a continuous medium using Navier–Stokes equations, the continuity equation, the energy equation, and the diffusion equation. Accounting for diffusion makes it possible to explicitly model air humidity and is necessary to consider the evaporation of droplets (changes in the mass and size of particles containing the virus). Liquid droplets are modeled using the discrete-phase model (DPM), in which each particle is tracked in a Lagrange coordinate system. The DPM method is effective, since the volume fraction of particles is small relative to the total volume of the medium, and the interaction of particles with each other can be neglected. In this case, the discrete and continuous phases are interconnected through the source terms in the equations. The averaged RANS equations are solved numerically using the k-ω turbulence model in the Ansys Fluent package. The task was solved in a static form and in the time domain. For a non-stationary problem, the stabilization time of the variables is found. The simulation results are obtained in the form of fields of pressures, velocities, temperatures and air densities, and the field of propagation of particles containing the virus. Various regimes were studied at various free flow rates and initial velocities of droplets with viral particles. The results of trajectories and velocities of particles, and particle concentrations depending on time, size, and on the evaporability of particles are obtained

Modeling of Flow Heat Transfer Processes and Aerodynamics in the Cabins of Vehicles

Ensuring comfortable climatic conditions for operators in the cabin of technological machines is an important scientific and technical task affecting operator health. This article implements numerical and analytical modeling of the thermal state of the vehicle cabin, considering external airflow and internal ventilation. A method for calculating the heat transfer coefficients of a multilayer cabin wall for internal and external air under conditions of forced convective heat exchange is proposed. The cabin is located in the external aerodynamic flow to consider the speed and direction of the wind, as well as the speed of traffic. Inside the cabin, the operation of the climate system is modeled as an incoming flow of a given temperature and flow rate. The fields of velocities, pressures, and temperatures are calculated by the method of computer hydrodynamics for the averaged Navier–Stokes equations and the energy equation using the turbulence model. To verify the model, the values of the obtained heat transfer coefficients were compared with three applied theories obtained from experimental data based on dimensionless complexes for averaged velocities and calculated by a numerical method. It is shown that the use of numerical simulation considering the external air domain makes it possible to obtain more accurate results from 5% to 75% compared to applied theories, particularly in areas with large velocity gradients. This method makes it possible to get more accurate values of the heat transfer coefficients than for averaged velocities

Numerical Simulation of Heat Transfer and Spread of Virus Particles in the Car Interior

The epidemic caused by the coronavirus infection SARS-CoV-2 at the beginning of 2022 affected approximately 500 million people in all countries. The source of infection is the particles of the virus, which, when breathing, talking, and coughing, are released with the respiratory droplets and aerosol dust of an infected person. Actions aimed at combating and minimizing the consequences of coronavirus infection led to taking measures in scientific areas to investigate the processes of the spread of viral particles in the air, in ventilation, and air conditioning systems of premises and transport, filtration through masks, the effect of partitions, face shields, etc. The article presents a mathematical model of the spread of viral particles in technological transport. Air intake diverters and the operator’s respiratory tract are the sources of the virus. The Euler–Lagrange approach was used to simulate liquid droplets in a flow. Here, the liquid phase is considered as a continuous medium using Navier–Stokes equations, the continuity equation, the energy equation, and the diffusion equation. Accounting for diffusion makes it possible to explicitly model air humidity and is necessary to consider the evaporation of droplets (changes in the mass and size of particles containing the virus). Liquid droplets are modeled using the discrete-phase model (DPM), in which each particle is tracked in a Lagrange coordinate system. The DPM method is effective, since the volume fraction of particles is small relative to the total volume of the medium, and the interaction of particles with each other can be neglected. In this case, the discrete and continuous phases are interconnected through the source terms in the equations. The averaged RANS equations are solved numerically using the k-ω turbulence model in the Ansys Fluent package. The task was solved in a static form and in the time domain. For a non-stationary problem, the stabilization time of the variables is found. The simulation results are obtained in the form of fields of pressures, velocities, temperatures and air densities, and the field of propagation of particles containing the virus. Various regimes were studied at various free flow rates and initial velocities of droplets with viral particles. The results of trajectories and velocities of particles, and particle concentrations depending on time, size, and on the evaporability of particles are obtained

Prediction of Mechanical Properties of Highly Functional Lightweight Fiber-Reinforced Concrete Based on Deep Neural Network and Ensemble Regression Trees Methods

Currently, one of the topical areas of application of artificial intelligence methods in industrial production is neural networks, which allow for predicting the performance properties of products and structures that depend on the characteristics of the initial components and process parameters. The purpose of the study was to develop and train a neural network and an ensemble model to predict the mechanical properties of lightweight fiber-reinforced concrete using the accumulated empirical database and data from construction industry enterprises, and to improve production processes in the construction industry. The study applied deep learning and an ensemble of regression trees. The empirical base is the result of testing a series of experimental compositions of fiber-reinforced concrete. The predicted properties are cubic compressive strength, prismatic compressive strength, flexural tensile strength, and axial tensile strength. The quantitative picture of the accuracy of the applied methods for strength characteristics varies for the deep neural network method from 0.15 to 0.73 (MAE), from 0.17 to 0.89 (RMSE), and from 0.98% to 6.62% (MAPE), and for the ensemble of regression trees, from 0.11 to 0.62 (MAE), from 0.15 to 0.80 (RMSE), and from 1.30% to 3.4% (MAPE). Both methods have shown high efficiency in relation to such a hard-to-predict material as concrete, which is so heterogeneous in structure and depends on many factors. The value of the developed models lies in the possibility of obtaining additional useful information in the process of preparing highly functional lightweight fiber-reinforced concrete without additional experiments

Reinforced Concrete Columns with Local Prestressing Rebars: A Calculation Theory and an Experimental Study

Local prestressing of reinforcement can be effective for slender reinforced concrete columns with large longitudinal force eccentricities. This article deals with columns with prestressed reinforcement on the side opposite to the eccentricity of the longitudinal force. Prestressing is created with the help of turnbuckles. The aim of the work is to develop a model for determining the stress–strain state of columns with local prestress and its experimental verification. The article presents the derivation of a resolving equation for the increment of deflection, which considers the non-linearity of the concrete and reinforcement work, the presence of creep and shrinkage of concrete. The solution of the resulting equation was performed numerically by the finite difference method in a MATLAB environment. Experimental studies were carried out according to the hinged support scheme for eight eccentrically compressed samples, four of which had been prestressed. Experiments and numerical modeling of columns with local prestressing showed a significant increase in crack resistance (by 1.3–2.5 times) and bearing capacity (by 12.5–30%) compared to similar structures without prestressing

Theoretical and Experimental Substantiation of the Efficiency of Combined-Reinforced Glass Fiber Polymer Composite Concrete Elements in Bending

An essential problem of current construction engineering is the search for ways to obtain lightweight building structures with improved characteristics. The relevant way is the use of polymer composite reinforcement and concrete with high classes and prime characteristics. The purpose of this work is the theoretical and experimental substantiation of the effectiveness of combined-reinforced glass fiber polymer composite concrete (GFPCC) bending elements, and new recipe, technological and design solutions. We theoretically and experimentally substantiated the effectiveness of GFPCC bending elements from the point of view of three aspects: prescription, technological and constructive. An improvement in the structure and characteristics of glass fiber-reinforced concrete and GFPCC bending elements of a new type has been proven: the compressive strength of glass fiber-reinforced concrete has been increased up to 20%, and the efficiency of GFPCC bending elements is comparable to the concrete bending elements with steel reinforcement of class A1000 and higher. An improvement in the performance of the design due to the synergistic effect of fiber reinforcement of bending elements in combination with polymer composite reinforcement with rods was revealed. The synergistic effect with optimal recipe and technological parameters is due to the combined effect of dispersed fiber, which strengthens concrete at the micro level, and polymer composite reinforcement, which significantly increases the bearing capacity of the element at the macro level. Analytical dependences of the type of functions of the characteristics of bent concrete structures on the arguments—the parameters of the combined reinforcement with fiber and polymer composite reinforcement—are proposed. The synergistic effect of such a development is described, a new controlled significant coefficient of synergistic efficiency of combined reinforcement is proposed. From an economic point of view, the cost of the developed elements has been reduced and is economically more profitable (up to 300%)