The primary issues restricting fast-growing wood utilization in buildings are its low dimensional stability and lack of strength grading. Thermal treatment has been shown to improve wood dimensional ...stability while decreasing certain mechanical parameters. This study was aimed to optimize the thermal treatment for fast-growing poplar wood to determine its impact on the wood strength class from the perspective of structural applications. Seven temperature levels between 20 and 210 °C and 2 h heating duration were used to thermally treat fast-growing poplar wood, which was then subsequently investigated for chemical composition and color change, as well as mechanical properties, such as parallel-to-grain bending, tensile, compressive (fc,0), shear strength (fv), modulus of elasticity (M0), and perpendicular-to-grain tensile strength. In addition, characteristic values were derived to provide an initial indication of design values. Thermal treatment resulted in hemicelluloses degradation, which darkened the color and reduced strength according to chemical composition and infrared spectroscopic analyses. In general, mechanical properties decreased with temperature, except for fc,0 and M0, which increased with temperature (≤180 °C) and followed by a decrease at ≥ 190 °C. The strength class of heat-treated wood depended on the smaller values of M0 and fv. M0 determined the strength class of native and heated wood to be ≤ 180 °C and fv at ≥ 190 °C. Thermal treatment in the region of 170–180 °C was a practical approach to improving wood properties in view of their structural use. Results of this study provided a basis for developing a design guide for structural uses of thermally-treated poplar wood.
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•Variations in mechanical properties were attributed to thermal degradation of chemical composition.•The strength class of heated wood exposed to a broad variety of temperatures was determined.•The 170–180 °C was recommended to be used in treating poplar wood in view of structural applications.
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•The effect of cement strength class on the compressive strength of cement mortar is examined.•ANN model accurately predicted compressive strength of cement mortar.•The results ...between ANN model and experiments results show a good agreement.•The performance of ANN model show improved with cement strength class considered.
An artificial neural network (ANN) study is presented to predict the compressive strength (Fc) of mortar mixtures containing different cement strength classes of CME 32.5, 42.5, and 52.5MPa. For this purpose, 54 mixtures considering six water/cement ratios (W/C) (0.25, 0.3, 0.35, 0.4, 0.45, and 0.5) and three sand/cement ratios (S/C) (2.5, 2.75, and 3) along with the abovementioned three types of cement strength classes have been constructed, and the results for a total of 810 specimens have been obtained. A comparative investigation was performed on two conditions of with and without considering the cement strength class as an input parameter in developed ANN-I and ANN-II models in order to obtain the optimum state.
The comparison of the proposed idealized ANN model with two other existing models indicates good precision and accuracy of the developed ANN model in predicting the compressive strength of the mortar and the deficiency of these existing models in situations where cement strength class is present as an input parameter.
•Workability of SCC decreases considerably by adding steel fibers.•Compressive strength loss in HS-SCC class was lower than that of MS-SCC class.•Flexural toughness enhances significantly when steel ...fibers were utilized.
Self-compacting concrete (SCC) is a highly-workable concrete that without any vibration or impact and under its own weight fills the formwork, and it also passes easily through small spaces between rebars. In this paper, the effect of steel fibers on rheological properties, compressive strength, splitting tensile strength, flexural strength, and flexural toughness of SCC specimens, using four different steel fiber volume fractions (0.5%,1%,1.5%,and 2%), were investigated. Two mix designs with strengths of 40MPa (medium strength) and 60MPa (high strength) were considered. Rheological properties were determined through slump flow time and diameter, L-box, and V-funnel flow time tests. Mechanical characteristics were obtained through compressive strength and splitting tensile strength tests with standard cylindrical specimens of 150×300mm, and flexural strength and flexural toughness tests were performed by using beams of 100×140×1200mm.
The results revealed that the workability of medium and high strength SCC classes is reduced by increasing the steel fiber volume fraction, and using high percentages of fibers led to decrease of other rheological characteristics that have been specified by EFNARC and ACI 237R. On the contrary, splitting tensile strength, flexural strength, and flexural toughness are increased by increasing the percentage of fibers; however compressive strength is decreased by increasing the percentage of fibers.
The primary aim of this work was to determine the effects of production parameters, such as wood species and timber strength classes, on some mechanical properties of cross-laminated timber (CLT) ...panels using artificial neural network (ANN) prediction models. Subsequently, using the models obtained from the analyses, the goal was to identify the optimum layer combinations of timber strength classes used in the middle and outer layers that would provide the highest mechanical properties for CLT panels. CLT panels made from spruce and alder timbers, as well as hybrid panels created from combinations of these two wood species, were produced. The strength classes of the timbers were determined non-destructively according to the TS EN 338 (2016) standard using an acoustic testing device. The bending strength and modulus of elasticity values of the CLT panels were determined destructively according to the TS EN 408 (2019) standard. According to ANN results, the optimum timber strength classes and layer combinations were determined for bending strength as C24-C27-C24 for spruce CLT, D18-D24-D18 for alder CLT, C30-D40-C30 and D18-C30-D18 for hybrid panels; and for modulus of elasticity, C22-C27-C22 for spruce, D35-D30-D35 for alder, C16-D24-C16, and D24-C24-D24 for hybrid panels.
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•The influence of CSC on the compressive strength of cement mortar is evaluated.•There is a good correlation between experimental and prediction results using GEP.•Considering CSC as ...an additional input parameter lead to more accurate prediction.
Gene expression programming (GEP) has been widely used to predict the properties of cementation materials. In this study, 54 mix designs including six water/cement (W/C) ratios of 0.25, 0.30, 0.35, 0.40, 0.45 and 0.50, three sand/cement (S/C) ratios of 2.50, 2.75, and 3.00 as well as three cement strength classes (CSC) of 32.5, 42.5 and 52.5 MPa were first constructed and then the compressive strength of 270 constructed samples with five different ages of 3, 7, 14, 21 and 28 days was measured. The compressive strength of cement mortar was then predicted using GEP and the results were utilized to investigate the roles of linking function and CSC on the performance of GEP models. The effect of CSC on the prediction of compressive strength of cement mortar was also evaluated by comparing the prediction results obtained from the proposed GEP in the current study considering CSC as an extra input parameter with the prediction results taken from existing GEP model from the literature without considering the CSC, where the input parameters were collected from three data sets of previous studies from the literature. The results showed that the GEP model with linking function of addition has a better performance than that with linking function of multiplication. The results also showed the strong potential of proposed GEP in predicting the compressive strength of cement mortar. Furthermore the results showed that considering the CSC as an additional input data increases the prediction accuracy of compressive strength.
•Effect of strength class on high-velocity bullet impact resistance is discussed.•Fibre type and dosage on penetration depth and crack inhibition are studied.•Coarse basalt aggregates with particle ...size up to 25 mm are applied in protective UHPFRC.•The size of aggregate size plays a significant role of depth of penetration.•Perforation limits of UHPFRC are derived for different bullet velocity.
This study investigates the influence of key parameters on in-service bullet impact resistance of ultra-high performance fibre reinforced concrete (UHPFRC), with the aim to provide design guidance for the engineering applications. The effects of steel fibre type and dosage, matrix strength, coarse basalt aggregates, and target thickness are researched by subjecting the UHPFRC to a 7.62 mm bullet shooting with velocities of 843–926 m/s. The results show that the UHPFRC, designed by using a particle packing model with compressive strength around 150 MPa, is appropriate to develop protective elements considering both anti-penetration performance and cost-efficiency. The 13 mm short straight steel fibres show better anti-penetration than the 30 mm hook-ended ones, and the optimum volume dosage is approximately 2% by considering both the penetration and crack inhibition. Introducing coarse basalt aggregates with the particle size up to 25 mm into UHPFRC reduces the powder consumption from 900 kg/m3 to 700 kg/m3, and results in slightly higher mechanical strength and significantly enhanced bullet impact resistance with 14.5% reduction of penetration depth. The safe thicknesses (perforation limit) of the designed UHPFRC slabs are approximately 85 mm and 95 mm to withstand the 7.62 × 51 mm NATO armor-piercing bullet impact under velocity 843 mm/s and 926 mm/s, respectively.
Thermal modification has been commonly perceived to improve wood dimensional stability, but decreases certain main mechanical properties. This research aimed to optimize thermal modification for ...poplar wood to determine its impacts on strength class for potential structural use. In this study, poplar wood was thermally modified at temperatures between 160 and 210 °C and 2 h duration, after which the chemical composition and mechanical properties were determined. The results showed thermal modification led to hemicelluloses degradation, which served as the main reason for strength reduction. The main mechanical properties of thermally-modified wood decreased with temperatures, except for compressive strength and modulus of elasticity, which increased with temperature (≤180 °C) and was followed by a reduction at ≥190 °C. The strength class of thermally-modified wood was dependent on the smaller value of modulus of elasticity and shear strength. Thermal modification at 180 °C was shown to be practical in improving wood properties for structural use.
•The cause of variations in heated poplar's strength was discovered.•Strength class of heated poplar at high temperatures was determined.•A suitable modification temperature was recommended in view of structural use.
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•Effect of cement fineness and amount of cement consumption were examined.•A MOANN-BBO model was developed to reliably predict by focusing on the CSC and C.•Performance indicators ...showed significant contribution of CSC and C.•Findings help reduce environmental impacts through reduction of cement.
The role of cement plants on negative environmental impacts is known. Therefore, investigating the type and amount of cement used in the mix design can significantly reduce the cement consumption and, consequently, reduce the pollution resulting from its excessive production. Also, despite the efforts by researchers to suggest the prediction model of mechanical properties of cementitious materials, there is no reliable model that simultaneously predicts them under freezing and thawing (FT) condition because of the lack of attention to the effective parameters. To fulfil these purposes, initially, an extensive experimental work considering 54 mix designs (810 specimens) was prepared, and the impact of cement fineness in the form of three cement strength classes (CSC 32.5, 42.5 and 52.5 MPa) and amount of cement consumption (Sand/Cement of 2.5, 2.75 and 3.0) on porosity, flexural (Ff) and compressive strength (Fc) under five different FT cycles (0, 50, 100, 150 and 200), and also cement paste texture by SEM and XRD analysis were investigated. Then, a new multi-objective model was developed based on hybrid artificial neural network (ANN) with biogeography-based optimization (BBO) to improve prediction accuracy.
Results demonstrated that specimens with fine cement (CSC 52.5 MPa) experienced decreasing the porosity up to 55% and increasing the load carrying capacity about 60% Ff and 80% Fc compared with coarse cement ones (CSC 32.5 MPa) at 200 FT cycles. Also, SEM images and XRD analysis illustrated that the finer cement can improve the homogeneity of the cement paste, and thereby it became denser texture. Comparison of results with previous studies confirmed the S/C of 2.75 as optimum proportion in mix design. Results of sensitivity analysis on models by performance indicators revealed that the best performance for MOANNII-BBO model compared with other models due to considering the CSC and amount of cement consumption as input parameters. Furthermore, the analysis of influencing input parameters indicated the sensitivity of 20% CSC and 18% amount of cement to the model performance. The findings of this work can bring notable benefits for the range of issues involved.
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