Million tons of waste are produced annually in mining and processing of dimension stone in Iran. In most cases, the waste is released in nature that would cause environmental hazards. In this work, Artificial stone slabs were manufactured by combination of coarse waste and sludge powder of stone cutting factories. The results show that the manufactured stone slabs have physical and mechanical specifications according to Iranian national standards for building stone. With increasing the amount of resin in the composition, the flexural and tensile strength were increased and the compressive strength and water absorption coefficient were decreased. The slabs produced from granite waste compare to the slabs produced from marble waste had better physical and mechanical specifications. At the optimum condition, with the aim of using more waste, with a composition of 90% marble waste and 10% resin, Artificial stone slabs were produced which have compressive strength about 143 MPa, flexural strength of 21 MPa, tensile strength of 25 MPa, water absorption coefficient 1% and density equal to 2. 32 g/cm3.

In this work, the waste stone sludge obtained from the granite and marble stone processing factories was used for the manufacture of Artificial stones using vibratory compaction in a vacuum environment. The results obtained showed that water absorption and density increased, and the flexure, compressive, and tensile strengths decreased with increase in the content of the waste stone sludge. These results also demonstrated that by combining 50% of stone sludge, 12% of ground quartz, 25% of waste glass, and 13% of resin at a compaction pressure of 12 MPa, a vibration frequency of 30 Hz, and vacuum conditions at 50 mm Hg, Artificial stone slabs with a water absorption less than 0.64, a density less than 2.68, a flexure strength more than 45 MPa, a compressive strength more than 90 MPa, and a tensile strength more than 35 MPa can be obtained. The Artificial stone slabs obtained in this research work had good density and water absorption, and flexure, compressive, and tensile strengths compared to the natural stones, and thus they can be regarded as the ideal construction materials for covering walls or paving floors.

This study aimed to develop and optimize Artificial stone mix designs incorporating microsilica using Artificial neural networks (ANNs) and metaheuristic optimization algorithms. Initially, 10 base mix designs were prepared and tested based on previous experience and literature. The test results were used to train an ANN model. The trained ANN was then optimized using SA-EVPS and EVPS algorithms to maximize 28-day compressive strength, with aggregate gradation as the optimization variable. The optimized mixes were produced and tested experimentally, revealing some discrepancies with the ANN predictions. The ANN was retrained using the original and new experimental data, and the optimization process was repeated iteratively until an acceptable agreement was achieved between predicted and measured strengths. This approach demonstrates the potential of combining ANNs and metaheuristic algorithms to efficiently optimize Artificial stone mix designs, reducing the need for extensive physical testing.

In this paper, factors affecting the mechanical properties of polymeric granite Artificial stone have been investigated. Epoxy resin and three types of additives called Poly ether ether ketone, Silicon rubber, and Nanoclay have been used to make the Artificial stone. Unlike previous research on resin alone, this study has been conducted on Artificial stone and samples made using these materials. These samples are compared with the control sample and the sample with optimal mechanical characteristics. The method of making Artificial stone is that crushed stone blend with resin, and is molded into molds that are defined according to the American Association of Materials and Testing. Samples were made with two percentages of 7. 5 and 15 percent to determine the optimum amount of additive. After curing, the sample is subjected to testing. The results obtained from these experiments for Artificial stone show that the addition of polyether ether ketone to epoxy resin compressive strength by more than 30%. 7. 5wt% of Nanoclay increases more than 6% in compressive strength in epoxy resin. Therefore, the amount of 7. 5% by weight of the additive has been selected as the optimum percentage and only this percent is considered in the manufacture of flexural and tensile strength samples. Adding Silicon rubber to the epoxy resin, increases the flexural strength by 7%. Contrary to expectation, Nanoclay reduces flexural strength significantly. By examining the results of the tensile test, it was determined that the addition of silicon to the epoxy resin increased the resistance to 46%. It is concluded that the addition of silicon rubber has been effective in increasing the compressive strength and in increasing the flexural and tensile strength and adding polyether ether ketone.

Artificial stone is a mixture of natural aggregate and additives such as industrial gums (resin), cement and other polymer materials. In this research, Artificial stone with additives and two resins (vinyl ester and polyester resin) in order to determine the strength and type of use, mixing plan, 84% rock, 10% resin and 6% additive completely manually without the need Vacuum and pressure system was built. Artificial rocks made with additives (glass fiber, carbon fiber, plastic), and three granite granite stones (Alamut, Sefid Tekab and Nehbandan) are used to determine the physical and engineering characteristics (Brazilian Test, Point Load Test, Uniaxial Compression Test and Ultra Sonic Test) have been tested. Based on experiments, Artificial stones made of precious stones, a resin of wilin ester, glass fibers, have the highest compressive strength of single axis and borehole. However, carbon-fiber samples have a tensile strength of 28% compared to glass fiber-reinforced glass samples. The samples made with plastic have the least porosity between the samples of synthetic stones. According to the above results, in environments affected by pressures, high-strength reinforced rocks (glass-fibered samples), in tensile-induced environments; high tensile strength Artificial rocks (samples made With carbon fiber) and on sidewalks made of synthetic stones made of plastic due to low porosity.

Background and Aim: Discoloration is among the most common problems of composite restorations. Color change over time compromises the main advantage of composite resins namely their high esthetics. In such cases, the restoration needs to be replaced. .The aim of this in-vitro study was to evaluate the effect of accelerated Artificial aging (AAA) on the color stability of three composite resins (Filtek Z250, Filtek Z250XT, and Filtek Supreme). Materials and Methods: In this experimental study, 7 composite specimens with equal dimensions were fabricated of each composite resin. The initial color of specimens was measured using a spectroradiometer according to the CIE L*a*b* system. The specimens were then submitted to AAA for 384h and underwent color assessment again. Before and after aging, the surface roughness of one specimen from each group was determined by Atomic Force Microscopy (AFM). The obtained color parameters were analyzed by one-way ANOVA and Tukey’s test. Results: The color change of Filtek Z250 was significantly lower than that of Filtek Z250XT and Filtek Supreme (P≤0.05). No statistically significant differences were found between Z250XT and Supreme in this respect (P>0.05 ). Conclusion: All composite resins showed color change above the clinically acceptable threshold. Z250 microhybrid composite was more color stable than nano-composites (Z250XT and Supreme). AAA increased the surface roughness in all groups but it was within the clinically acceptable range.

Nowadays, estimating the ampere consumption and achievement of the optimum condition from the perspective of energy consumption is one of the most important steps in reducing the production costs. In this research, we tried to develop an accurate model for estimating the ampere consumption using the Artificial neural networks (ANN).In the first step, experimental studies were carried out on 7 carbonate rock samples in different conditions at particular feed rates (100, 200, 300 and 400) and depth of cut (15, 22, 30 and 35mm) using a fully instrumented laboratory rig that is able to change the machine parameters and to measure the ampere consumption. In the next step, a retro-propagation neural network was designed for modelling the sawing process to predict the ampere consumption. The input network consists of two parts: machine, work piece characteristics and the output of neural network was ampere consumption. This research evaluated the competencies of neural networks to estimate the ampere consumption in sawing process. The correlation coefficient between measured and predicted data in training and testing data is 0.95 and 0.97, respectively. The Root Mean Square Error (RMSE) for train and test data is 1.2 and 0.7, respectively. The results of this study show that the ANNs can be used to estimate the ampere consumption with high ability and low error for industrial applications. Moreover, the cost of sawing machine ampere consumption can be accurately estimated using this neural model from some important physical and mechanical properties of rock.

Introduction: Artificial stone is a type of building material that consists of natural aggregates, binders, such as cement or polymeric resin and some additives. The aggregates used for the production of the Artificial stone are generally supplied from the wastes and scraps of quarries and industrial stone manufactories. Accordingly, the produced rock has a significant economic value. The mixing design includes more than 80% of natural aggregates and less than 20% additives and binders, such as various types of polymer resin or cement. Due to the fact that Artificial stones are designed purposefully and according to engineering patterns, so the stone has different designs and colors and thus can meet the diversity of consumer desire and is an appropriate alternative for natural stones in the building industry. Due to a large number of various rock mines and industrial workshops in Iran, it has the ability to produce Artificial stones...

Introduction: Discoloration is one of the most common reasons for replacement of resin composites. The purpose of this study was to compare the color stability of three Methacrylate-based Resin Composites (Filtek Z250, Filtek Z250x, Filtek Z350xt) with Silorane-based Resin Composites (Filtek P90) after Accelerated Artificial Aging (AAA).Materials & Methods: In this in vitro study 56 composite discs were prepared (N=14). CIE L*a*b* parameters of each specimen were measured by a reflectance spectrophotometer after 24h and 384 h of AAA. Then Color change (DE) of each composite was calculated. Data were analyzed by one way ANOVA, Tukey and paired t-test at the significance level of 0.05.Results: DE values of Filtek Z250, Filtek Z250x, Filtek Z350xt and Filtek P90 were 7.77, 5.86, 8.95 and 8, respectively. One way ANOVA demonstrated a significant difference between DE values of composites (P˂0.001). Tukey’s test revealed that DE value of Filtek Z250xt was significantly lower than those of other composites (P˂0.05).Conclusion: Silorane and methacrylate based composites showed a color change more than the clinically acceptable level (DE˃3.3) after AAA. Filtek Z250xt showed the lowest color change and other composites showed relatively similar color change.