Properties Of Construction Materials Research Articles

Elucidating Rheological Properties of Cementitious Materials Containing Fly Ash and Nanosilica by Machine Learning

Researching the rheology contributes to enhancing the physical and mechanical properties of concrete and promoting material sustainability. Despite the challenges posed by numerous factors influencing viscosity, leveraging machine learning in the era of big data emerges as a viable solution for predicting the general properties of construction materials. This study aims to create models to forecast the rheological properties of cementitious materials containing fly ash and nanosilica. Four models—Random Forest, XGBoost, ANN, and RNN (Stacked LSTM)—are employed to predict and assess shear rate versus shear stress and shear rate versus apparent viscosity curves. Through hyperparameter adjustments, RNN (Stacked LSTM) exhibits excellent performance, achieving a coefficient of determination (R2) of 0.9582 and 0.9257 for the two curves, demonstrating superior statistical parameters and fitting effects. The RNN (Stacked LSTM) exhibited a better generalization ability, suggesting it will be more reliable for future prediction in cementitious material viscosity.

FoCa – Free of Carbon Architecture –an educational and informational online platform supporting the decarbonization of the construction sector in Poland and Turkey

Wrocław University of Science and Technology, in consortium with the Polish Association of Ecological Buildings (PLGBC), the Institute of Building Technology (ITB) and research and scientific units from Turkey, started the international project FoCA – Free of Carbon Architecture. Its aim is to create a publicly available tool – an interactive internet platform providing information on the environmental properties of construction materials and products available in Poland and Turkey. The platform allows users to compare and evaluate the environmental impact of selected building materials. As part of the platform's development, information is collected about building materials or products available on local markets, in the form of data describing their selected environmental impacts (GWPfossil, GWPbiogenic, GWPtotal, TRPE, TNRPE, WD). The platform allows to compare building materials and perform analyzes for conceptual building designs. In addition, producers of building materials can also benefit from the project because they will receive information about the environmental properties of some of their products. The platform will be available in the second half of 2024.

Identification of Alternations in the Structure of Historical Masonry Walls Using the GPR Method Accompanied with Architectural Survey in the Former Piast Gymnasium in Brzeg

Widely used in civil engineering, GPR (ground penetrating radar) is increasingly being used to survey historic structures. However, there are still no conclusive directives on the use of GPR in the identification and diagnosis of masonry structures. The current state of the art allows only on the example of individual case studies, to draw conclusions about the effectiveness of the use of this tool. One such area, where the effective use of GPR has been experimentally confirmed, is the historic architectural survey of a heritage buildings. Due to diversity in the dielectric properties of individual construction materials, it is possible to observe on radargrams the change of electromagnetic wave patterns by materials from different phases. Traditional approach require extensive excavation efforts or core drilling, which may not always be acceptable for conservation reasons. Hence the GPR method could be interesting, non – destructive option for identification and diagnosis of historical masonry walls. The authors used the architectural survey and accompanying excavations at the former Piast Gymnasium in Brzeg to conduct a survey campaign using the GPR method. The brick walls of the building's nave have been scanned. The nave have undergone numerous alterations over hundreds of years. The GPR data has been subjected to adequate post-processing and then correlated with architectural surveys and validated on the basis of available excavations at the site. The authors highlight that GPR surveys, when combined with architectural investigations, offer a less invasive approach to examining historic structures, thereby mitigating the need for problematic excavation work.

Energy audit based identification of energy efficiency improvement opportunities for existing houses

Energy efficiency in the building has two dimensions; efficient use of energy resources and energy conservation. Energy-efficient houses play a critical role in energy conservation and achieving sustainable built environment goals. The energy efficiency of a house depends on its building envelope (design, orientation, and energy properties of construction material) and operational characteristics appliance efficiency, energy consumption patterns). Rather than merely ensuring new houses are energy-efficient, it is vital to energy retrofit existing houses. Energy audits can assist in evaluating the energy efficiency of existing houses and identify improvement measures. The main objectives of this study were to identify efficiency improvement opportunities through an energy audit of houses and apartments in Karachi. A detailed energy audit checklist was prepared using literature, standards, expert review, and code requirements. Data was collected through physical and owner-assisted virtual audits of 58 houses in six districts of Karachi. Architectural plans, information about doors, windows, air ducts, thermal images, historical data, and material properties were collected. Audit tools included; an anemometer and thermal imagining camera during physical audits. Android applications were used during owner-assisted audits. Data were analyzed for developing descriptive graphs, U and R-values, Pareto charts, and district-wise mapping of energy properties of the material. As a result, energy improvement opportunities were proposed. These are focused on building envelope aspects, including; window orientation, minimizing air infiltration, and using heatresistant paint. Improvement measures were confirmed through thermal imaging of selected buildings.

Characteristics of Circulating Fluidized Bed Combustion (CFBC) Ash as Carbon Dioxide Storage Medium and Development of Construction Materials by Recycling Carbonated Ash.

This study validates the attributes of the mineral carbonation process employing circulating fluidized bed combustion (CFBC) ash, which is generated from thermal power plants, as a medium for carbon storage. Furthermore, an examination was conducted on the properties of construction materials produced through the recycling of carbonated circulating fluidized bed combustion (CFBC) ash. The carbonation characteristics of circulating fluidized bed combustion (CFBC) ash were investigated by analyzing the impact of CO2 flow rate and solid content. Experiments were conducted to investigate the use of it as a concrete admixture by replacing cement at varying percentages ranging from 0% to 20% by weight. The stability and setting time were subsequently measured. To produce foam concrete, specimens were fabricated by substituting 0 to 30 wt% of the cement. Characteristics of the unhardened slurry, such as density, flow, and settlement depth, were measured, while characteristics after hardening, including density, compressive strength, and thermal conductivity, were also assessed. The findings of our research study validated that the carbonation rate of CFBC ash in the slurry exhibited distinct characteristics compared to the reaction in the solid-gas system. Manufactured carbonated circulating fluidized bed combustion (CFBC) ash, when used as a recycled concrete mixture, improved the initial strength of cement mortar by 5 to 12% based on the 7-day strength. In addition, it replaced 25 wt% of cement in the production of foam concrete, showing a density of 0.58 g/cm3, and the 28-day strength was 2.1 MPa, meeting the density standard of 0.6 grade foam concrete.

Machine learning models for predicting the compressive strength of agro-waste stabilized bricks for sustainable buildings

Excessive consumption of time and resources are the major challenges of conducting laboratory experiments to determine the mechanical properties of building/construction materials. There is a need to explore various prediction models for mechanical properties of construction materials. This study is aimed at using machine learning models to predict the compressive strength of stabilized bricks for sustainable buildings. Data for the independent variables generated from laboratory experiments were used for the compressive strength prediction. Several machine learning models were explored using Lazy Predict Python library. Extreme Gradient Boosting Regressor with the coefficient of determination (R2) score of 99.45% and root mean square error of 0.06 outperformed all the tested models. SHAP (SHapley Additive exPlanations) analysis was used to show the distribution of the impacts of the features on the predicted compressive strength. The SHAP analysis results showed that higher percentages of the stabilizers (with reference to 0%, 2%, 4%, and 6% of stabilizers) have a positive impact on the prediction of compressive strength of stabilized bricks. In addition, higher water content, lower lateritic soil contents, lower cube sizes and curing at higher values of temperature favoured the prediction of compressive strength of stabilized bricks. The proposed model can be adapted by civil engineers and researchers for the prediction of the compressive strength of agro-waste stabilized construction materials. The implication of this study will save the time and resources required by the construction professionals to obtain the compressive strength agro-waste stabilized bricks during the production of bricks for sustainable construction applications.

Inverse problem method application in building physics numerical optimization: new insight into ideal envelope properties determination

ABSTRACT Building thermal design optimization is pivotal for energy efficiency and built environment improvement. The optimal thermophysical properties for building walls remain ambiguous. This ambiguity stems from the constraints of traditional building physics, which: (1) disjoins the enhancement of wall thermal performance from the building service system management; and (2) relies on the forward method that fails to identify the ideal variable thermophysical property, the solution to which is inherently a function. This study elucidates the optimal temperature-dependent volumetric specific heat ( ρ c p ( t ) ) and thermal conductivity ( k ( t ) ) through the inverse problem and variation method. Illustrative example indicates that the optimal ρ c p ( t ) closely resembles a combination of two ‘ δ ’ functions, while the optimal k ( t ) mirrors a square wave function. Utilizing these ideal thermophysical properties, the building energy consumption can be significantly reduced by 77.1% with the optimized ρ c p ( t ) and 79.9% with the optimized k ( t ) . The ideal thermophysical properties for active buildings differ significantly from those recommended for passive buildings, underscoring that minimal energy consumption does not necessarily imply minimal discomfort. Therefore, the thermophysical properties of active and passive buildings should be optimized distinctly. This research offers valuable insights for defining ideal thermophysical properties of active building walls and construction materials.

Recycling and reuse of waste banded iron formation as fine aggregate in the production of lightweight foamed concrete: Fresh-state, mechanical, thermal, microstructure and durability properties assessment

This study investigates the possibility of using BIFs as sustainable fine aggregates to produce lightweight foam concrete (LWFC) by replacing sand with 5, 10, 15, 20, and 25 % banded iron formations (BIFs). The fresh concrete properties, such as slump flow, density, and setting time, as well as its mechanical properties, including compressive strength, splitting strength, and flexural strength, were investigated. The thermal conductivity, specific heat, porosity, gas permeability, pore distribution, and sorptivity were measured to determine durability and thermal performance. Microstructural analysis of the mixes was performed using SEM, energy-dispersive X-ray spectroscopy (EDX), and mapping. The results recommended a 10 % replacement ratio to achieve an increased compressive strength ratio of 55.88 % compared to the control mix at 7 days (d). The strength at later ages increased compared to that of the control mix by 33.9 %, 30 %, 42.48 %, and 42.4 % at 14, 28, 56, and 180 d, respectively. In addition, the flexure increased by 42.7 % at 7 d, 49.6 % at 14 d, and 45.6 % at 28 d compared to the control mix. In addition, the UPV also increased gradually from 2757 to 3699 km/s with increase in BIFs content. Furthermore, the porosity decreased at 7 d, 14 d, 28 d, and 90 d. Moreover, chloride penetration decreased by 2.5 %, where an improvement in thermal conductivity was achieved with BIFs to 0.342 W/mK compared to that of the control mix. In addition, a reduction in the specific heat of the material from 1042 J/kg K to 1007 J/kg K was observed. SEM showed a better arrangement of pores when BIFs were utilized compared with that of control mix without BIFs. In conclusion, the incorporation of waste BIFs as fine aggregates in lightweight foam concrete demonstrates a promising potential for enhancing the mechanical and thermal properties of construction materials, paving the way for durable building materials in the construction industry.

A comparative analysis of simulation approaches for predicting permeability and compressive strength in pervious concrete

Porous concrete plays a crucial role in addressing various environmental challenges and mitigating the impacts of climate change. It proves effective in reducing issues such as flooding, heat phenomena in the earth, and groundwater decline. Typically devoid of sand content, porous concrete’s key attributes lie in its permeability and compressive strength. Accurate prediction of these properties is essential for cost and time savings, ensuring precise proportions of materials in the concrete mixture. This article explores different models, including the linear model (LR), nonlinear model (NLR), and Artificial Neural Network (ANN), to predict and estimate permeability and compressive strength in porous concrete. The analysis incorporates 139 samples from various papers and experimental studies, utilizing significant parameters and variables like water-to-cement ratio, coarse aggregate content, cement content, porosity, and curing time as input variables. Statistical assessments, such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Scatter Index (SI), OBJ value, and coefficient of determination (R2), are employed to assess model performance. The results reveal that the ANN model outperforms other models in forecasting permeability and compressive strength of porous concrete. The SI and OBJ value of the ANN model are lower than those of all other models, indicating superior performance. The robust performance of the ANN model has significant implications for construction applications, ensuring precise material proportions and contributing to the durability of porous concrete structures. The success of the ANN model suggests avenues for refinement, including architecture adjustments and dataset expansion. These findings offer valuable insights into the ongoing efforts to optimize simulation techniques for predicting key properties of construction materials. On the other hand, the use of these models to optimize concrete mix design not only enhances efficiency but also significantly conserves raw materials and reduces energy consumption. These advancements contribute to lowering carbon emissions and promoting sustainable practices in the construction industry.

Estimating the energy consumption for residential buildings in semiarid and arid desert climate using artificial intelligence

This research aims to develop predictive models to estimate building energy accurately. Three commonly used artificial intelligence techniques were chosen to develop a new building energy estimation model. The chosen techniques are Genetic Programming (GP), Artificial Neural Network (ANN), and Evolutionary Polynomial Regression (EPR). Sixteen energy efficiency measures were collected and used in designing and evaluating the proposed models, which include building dimensions, orientation, envelope construction materials properties, window-to-wall ratio, heating and cooling set points, and glass properties. The performance of the developed models was evaluated in terms of the RMS, R2, and MAPE. The results showed that the EPR model is the most accurate and practical model with an error percent of 2%. Additionally, the energy consumption was found to be mainly governed by three factors which dominate 87% of the impact; which are building size, Solar Heating Glass Coefficient (SHGC), and the target inside temperature in summer.

Риск-ориентированный анализ безопасности и защищенности промышленных объектов на основе характеристик прочности и ресурса

The concept of computation and experimental determination of safety and protectability of industrial facilities on parameters of risk of initiation of refusals, accidents and disasters taking into account possibility of regular and emergency situations is considered. The scientifically substantiated, normalized and controlled parameters of risks estimated by criteria of strength, life-time and survivability are its basis. Risks at the same time are estimated on probabilities of initiation of emergency situations and losses accompanying them at their interdependence. It is shown that generally safety is defined by ability of installations not to pass into emergency and catastrophic states with drawing significant damages to the person, a technosphere and environment; the risk is defined by probability of initiation on installation of adverse situations and possible losses from these situations; protectability is defined by ability of installation to resist to initiation and an evolution of adverse situations (refusals, accidents, disasters) in regular and emergency conditions. The new perspective direction for maintenance of conditions of safe service of industrial facilities is that which initially forms the level of their protectability, and this protectability is defined by the formed and acceptable risks. In this case the solution of basic problems of protectability, safety and risk has to be guided surely by the solution of problems of strength, a life-time, survivability in their direct interaction This circumstance is based on a quantitative estimation of conditions of service damages accumulation and on the analysis of conditions of transition from regular to the damaged and limit states of installation taking into account criteria of strength, fatigue life and survivability. The solution of practical problems of maintenance of strength, life-time and safety within of strength, life-time and risk-focused design assumes determination of nominal and local stresses from service loadings in the most loaded zones with use of characteristics of mechanical properties of constructional materials. In the paper it is put and solved the new scientific and almost important problem about risk-focused definition, maintenance, increase and a standartization of complex safety and protectability of technosphere installations by criteria of the acceptable and controlled risks.

Laboratory studies on the mechanical properties of sulphur-based construction material at simulated Martian temperatures

Mars is the next destination for further exploration and the hypothetical establishment of humanity's frontier. However, the planet offers very harsh environmental conditions particularly the very cold temperature in the Martian environment. Knowing that the sulphur-based construction material is perceived as one of the ideal Martian construction materials based on the identified abundant source of sulphur on Mars, its behaviour when subjected to the very cold Martian temperature is yet to be fully clarified. Therefore, this study intends to investigate the behaviour of the Martian sulphur-based construction material subjected to the simulated very cold Martian temperature whilst being compared with the simulated hot Martian temperature. Two mixture compositions of 50/50 and 60/40 comprising of sulphur and Mojave Mars simulant 1 (MMS-1) respectively were fabricated in this study characterising the simulated Martian temperature. The workability at 50 % and 60 % sulphur content was initially investigated. Subsequently, the overall mechanical properties characterising the sulphur content and simulated Martian temperature were investigated via unconfined compression, three-point bending and tensile splitting tests. Necessary factors that influence the overall mechanical properties including the internal structure and microstructural characteristics were also performed via ultrasonic pulse velocity (UPV) and scanning electron microscopy (SEM) respectively. X-ray diffraction (XRD) was also conducted to identify the chemical composition of the end product. The comparisons between this study and other previous related studies within the state-of-the-art Martian sulphur-based construction materials were also outlined. Prospects for future construction on Mars are also presented. It was found that the 60 % sulphur content exhibited higher workability due to the high amount of unreactive sulphur. The 50 % sulphur content recorded the optimal overall mechanical properties under the simulated hot and very cold Martian temperatures. The simulated very cold Martian temperature triggered non-uniform interparticle distribution and larger cavities thus dramatically reducing its overall strength and triggering higher volumetric inconsistency. The very brittle nature of unreactive crystallised sulphur binder at excessive thickness particularly at 60 % sulphur content in between filler particles also triggered volumetric inconsistency which further worsened at the simulated very cold Martian temperature. The iron sulphate hydrate found was almost in agreement with the related works and another new compound, potassium calcium magnesium sulphate was identified as well. The overall mechanical properties are comparable with the other previous related studies and the residual strength when subjected to the simulated very cold Martian temperature remains adequate in the Martian environment of low gravity. The 60 % sulphur content is suggested for structural elements built internally whereas the 50 % sulphur content demonstrated a high potential in adapting to the harsh Martian environmental conditions. The findings of this study hoped to act as the initial outlook on how such Martian sulphur-based construction material would react upon fabrication on Mars.

Influence of Subsoil and Building Material Properties on Mine-Induced Soil–Structure Interaction Effect

Soil–structure interaction (SSI) refers to the dynamic interaction between a structure and the surrounding soil on which it rests. The behavior of the soil can significantly affect the response of the building structure. In the context of civil engineering and structural analysis, SSI becomes particularly important when considering the response of structures to dynamic loads such as earthquakes or so-called paraseismic loads, e.g., mining tremors. Several factors contribute to SSI. Soil and building structure material properties, foundation type, and loading conditions are the most important parameters. The article concerns SSI in the case of mining rock bursts in Poland. The influence of changes in site material conditions and building material properties on the SSI phenomenon was investigated. A few variants of different properties of typical construction materials (brick, reinforced concrete, and cellular concrete) in the case of selected representative building structure were considered. The subsoil material properties from the wide range were also taken into account. Numerical three-dimensional finite element method (FEM) analysis was applied. The adopted models of the soil-structure system were verified by data from in situ experimental vibration measurements. A significant influence of the subgrade material and the building structure material on the SSI was demonstrated.

Soft computing techniques for analysing the mechanical properties of egg shell powder-based concrete

The construction industry is increasingly focused on sustainability to reduce environmental impact. Researchers are actively exploring alternative materials to replace clinker-based binders. This study specifically investigates the use of eggshell powder (ESP) as a sustainable substitute in construction. Portland slag cement (PSC) is partially replaced by ESP in concrete production for this purpose. To assess the effectiveness of ESP in enhancing binder properties, the study analyses experimental data for compressive and flexural strength. Artificial Neural Network (ANN) modelling is employed for this analysis to predict material performance. The model undergoes training and testing using input data to ensure accuracy and reliability. The success of the study is demonstrated by high R2 values, with 0,9915 for compressive strength and 0,9921 for flexural strength, indicating that the ANN model closely matches actual material performance. Additionally, error analysis confirms the model's remarkable accuracy in predicting real-world results. Furthermore, the research highlights the exceptional potential of the developed ANN model, which can effectively predict the mechanical properties of construction materials containing ESP.

Nanotechnology and its impact on achieving sustainable architecture in Egypt

Considering the significant growth of the global population, several severe issues have emerged, including pollution, economic challenges, and environmental problems. To tackle these ecological issues, many construction experts are actively seeking new flexible techniques. Among these, Nano-technology stands out as a crucial field aiming to enhance the efficiency of the built environment and play a vital role in addressing future challenges. This study aims to examine the effectiveness of integrating Nano-technology techniques in construction to harness the acquired properties of materials and their impact on the interior thermal environment. The paper is divided into three main parts, each providing a detailed and scientific depiction of the study. The first part begins by shedding light on the concept of sustainability in architecture and the evaluation of sustainable buildings. Additionally, it explores the definition of Nano-technology and its substantial impact on the field of architecture by discussing various architectural terms associated with Nano-technology. The emergence of Nano-architecture is seen as a significant advancement in scientific research, representing a fusion between architecture and Nano-technology. Moving on to the second part of the thesis, it focuses on how Nano-technology techniques influence the work of architects. Nowadays, architects consider the properties of construction materials, construction methods, and energy consumption. These factors are essential in achieving an ideal design that is defined as sustainable. The second part also examines the effect of Nano-technology on the thermal environment, analyzing both national and international projects that have implemented this technique.

Impact of earth variability and implementation processes on hydromechanical and microstructure properties of sustainable construction materials

The suitability criteria for soils used in earth construction is investigated. Four soils collected from earth heritage buildings sites were studied. Cylindrical fibred and non-fibred specimen were produced using cob and adobe techniques. An experiment campaign was carried out to after drying and conditioning the specimen to study the implementation process effect, geotechnical properties and mineralogical composition influence on the hydromechanical and microstructural behavior of the specimens. The hydromechanical parameters like dry bulk density, unconfined compressive strength (UCS), Young's modulus (E) and suction of the specimen produced were studied. The pore volume and specific surface area were also determined using the BET technique. The collective impact of implementation process, geotechnical properties and mineralogical composition of the soils on the hydromechanical strength (UCS and Suction) and microstructure (pore volume, Specific surface area (SSA)) of laboratory produced cob and adobe specimens was studied. A statistical analysis was conducted using the principal component analysis to analyse the complexity of the interactions among the parameters. The analysis showed that aside the geotechnical properties of a soil, the implementation process and mineralogical composition of a soil also have high influence on the hydromechanical strength and microstructure of the earth specimen produced.

Properties of Sustainable Earth Construction Materials: A State-of-the-Art Review

As a significant symbol of human civilization advancement, earth construction not only inherits traditional architectural culture but also enjoys worldwide popularity and widespread usage throughout China due to its economic and environmentally friendly nature, as well as its moisture absorption and heat storage advantages. Consequently, earth construction has garnered considerable attention from international scholars. This paper compiles relevant data to review the developmental trajectory of earth construction, while conducting an in-depth analysis of the performance characteristics of earthen materials. Furthermore, it provides a comprehensive overview of the impact of three modification methods on the mechanical and durability properties of earthen materials, along with a discussion on the research concerning the thermal and moisture performance of these materials. Simultaneously, discussions were held on the relevant research findings and potential directions for the development of earthen materials. Finally, conclusions were drawn, suggesting a comprehensive utilization of their thermal and moisture performance, emphasizing the enhancement of their mechanical and durability performance. Additionally, attention was urged towards the economic and ecological aspects during the construction and maintenance phases of earth construction. These recommendations aim to facilitate the sustainable development and widespread application of earthen materials in the future.

Preparation and performance of acrylic mortar repair material modified suitably by nano-fiber and nano-particle in low-temperature for high-strength gain applications in construction

Nano-particles and nano-fibers have a marked effect on the physico-mechanical properties of polymeric mortar. In this study, to further enhance the mechanical properties of acrylic repair materials used in extreme environments (−25 °C or even lower), we added nano-particles (SiC, Al2O3, B4C, Si3N4, Fe2O3, SiO2), nano-fibers (CFs, MW-CNTs), nano-sheets (GNP, MOS2) and one homemade three-dimensional (3D) nano-fibers SiC–OH@APTES-g-CFs-COOH, respectively, to the polymeric mortar. We investigated how the dimensionality, content and type affect the compressive strength and flexural strength of the acrylic mortar repair materials. Acrylic mortar specimens were prepared by mixing methyl methacrylate binder, aggregates, initiator, accelerator and different nano-particles in a standard cement mixer, which is placed in standard molds of 40mm × 40mm × 160 mm and kept in −25 °C. Compressive and flexural strength of the acrylic mortar repair materials were determined at 1h, 1d and 10d of curing. The carbon fibers were treated with γ-aminopropyltriethoxysilane (APTES), and the 3D nano-fibers SiC–OH@APTES-g-CFs-COOH were prepared. The Scanning electron microscopy (SEM) analysis indicated that a large number of SiC were uniformly and densely distributed on the surface of CFs. The mechanical strength results showed that almost all contents of nano-materials of any dimension used in this article could enhance the mechanical strength of the specimens. Notably, when 0.05 wt% SiC–OH@APTES-g-CFs-COOH was added, the compressive strength and flexural strength values of acrylic mortar specimens at 10d were improved by 41.16 % and 52.28 % than those of control specimens. The incorporation of 3D nano-fibers formed a mechanical engagement with the aggregates, which increased the contact area between the aggregates and 3D nano-fibers and the thickness of the contact layer inside the specimen, thus effectively transferring the stress when the specimen was subjected to the load, and enhance the interfacial properties between the substrate and the nanofillers. Among the explored nano-particles, the addition of Si3N4 could significantly improve the compressive and flexural strength of acrylic mortar. Compared with the control specimen, the compressive strength can be improved by 44.6 % and the flexural strength of acrylic mortar specimens can be improved by 76.2 % when the addition of Si3N4 was 0.3 % by weight. This article demonstrated the availability of nano-powders for improving the mechanical properties of polymeric mortar construction materials.

Artificial Intelligence and Applications in Structural and Material Engineering

The integration of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) has become a vital tool attributed to Structural and Material Engineering and developed the way engineers approach design analysis and optimization. This paper explores the principal models of ML and DL, such as the generative adversarial network (GAN) and the artificial neural networks (ANN) and, and discusses their impacts on the applications of material design, structure damage detection (SDD), and archtecture design. It indicates that the high-quality of database is the essential key to training the model. Thus, the data preprocessing is required for expanding the data source and improving the quality of data. In material design process, ML and DL models reduce the time to predict the properties of construction materials, which makes SDD realistic as well. For architecture design, GAN is used to generate image data, such as drawing of the floor plan and this could be helpful to reduce the labor resources. However, some challenges of ML and DL are found while applying the algorithms to real-life applications. For example, sufficient data is needed to train the DL models and the ethic aspect is also a concern when thinking of AI.

Enhancing the mechanical and thermal insulation properties of clay-based construction materials with neutral carbon footprint through the use of Doum fibers

The construction industry is currently experiencing robust global growth. With the advancement of technology, real estate development is evolving through the adoption of new strategies. The present study aims to identify the optimal formulation for unfired bricks made from clay and Doum fibers sourced from the Taounate region in Morocco. To achieve this, six brick samples were produced with varying amounts of Doum fibers (0 %, 1 %, 5 %, 7 %, 10 %, and 12 %), and their performance was assessed through tests for bulk density, linear shrinkage, compressive strength, and thermal conductivity. The results indicate that the resulting bricks are lightweight, with a bulk density not exceeding 1.75 g/cm3, in accordance with the NM EN 772-16 standard. Furthermore, there was a notable reduction in linear shrinkage, reaching up to 80 %. The reference brick without fiber additions exhibited a shrinkage of 5.86 %, whereas the brick containing a high fiber content of 12 % demonstrated a linear shrinkage of 1.12 %. The strength of the brick decreases with increasing fiber content, but the thermal insulation properties improve significantly. Considering these variations, the optimal enhancement in thermal and mechanical performance was determined to be 41.5 % in terms of compressive strength and thermal conductivity, corresponding to a 10 % inclusion of Doum fibers. The optimal brick is classified as EB6 according to the German standard DIN 18945 (2013–08), with a thermal conductivity of 0.31 W/m.K and a compressive strength of 8.26 MPa, rendering it suitable for use in earth construction. This study also concludes that the production cost for the optimal brick is half that of the conventional bricks available in the building materials market. This holds promising implications for the future of harnessing local natural resources in the field of eco-construction, as it positively impacts the economy and environment of the region.