Employment of Response Surface Methodology for Optimization of the Portland Cement Mechanical Resistance

For this workmixtureswere madewith three types ofPortland cement (CPII,CPIII, and CPIV), which were chosen because theyexhibit: good mechanical properties,lower heat ofhydrationgeneratedin the reaction, greater impermeability, greater resistance to environmentsaggressive.The objectwas to improve themechanical strengthofcementpasteswith the helpof experimental design. Ten different compositionswere prepared, which were tested forcompressivestrengthat 1 and14 days ofcuring. The results illustrated that the first day; the composition showed that the best result was composed of 50% of CP II and 50% of CP III. Already at 14 days, a paste made with 100% of CP III showed better results followed by composition made with 50%CP II and CP III 50%.

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Mechanical and Formability Evaluation of ST14 Alloys Welded by Friction Stir Welding

Shock and Vibration ◽

10.1155/2021/6269135 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Mahmoud Afshari ◽

Nima Fakhralmobasheri ◽

Mohammad Reza Samadi ◽

Amirhossein Alavi ◽

Hossein Norozi Foroushani

Keyword(s):

Mechanical Properties ◽

Response Surface Methodology ◽

Friction Stir Welding ◽

Experimental Design ◽

Response Surface ◽

Base Metal ◽

Tensile Failure ◽

Dome Height ◽

Experimental Conditions ◽

Friction Stir

Friction stir welding as one of the modern methods of solid-state welding of steel sheets and aluminum is a highly regarded industry. In these studies, the experimental design and response surface methodology were used. Optimization of experimental conditions and results which are compared with good agreement between the results was observed. The mechanical properties and ductility of welded plates under optimal conditions were studied. Microhardness testing, metallography, tensile testing, and limiting dome height were used to investigate the mechanical properties and formability limit diagram attached, respectively. The results showed that the heat-affected zone is very small and narrow and not easily distinguished from the base metal. In all tests, the failure of the dome height limit in the area was chaos. In all samples welded with the optimal parameters, tensile failure occurred in the base metal region. Turbulence in the region confirms the presence of WC particles. Experimental design and response surface methodology could introduce an optimal state, and the creation of common defects in the FSW process can prevent the binding strength of the guarantee. But due to the lack of proper stirring in the perturbation area in the samples welded with non-optimized parameters, the strength of the connection is not suitable, and samples were broken from the SZ region.

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Modeling and Sensitivity Analysis of the Forward Osmosis Process to Predict Membrane Flux Using a Novel Combination of Neural Network and Response Surface Methodology Techniques

Membranes ◽

10.3390/membranes11010070 ◽

2021 ◽

Vol 11 (1) ◽

pp. 70

Author(s):

Jasir Jawad ◽

Alaa H. Hawari ◽

Syed Javaid Zaidi

Keyword(s):

Response Surface Methodology ◽

Experimental Design ◽

Response Surface ◽

Forward Osmosis ◽

Feed Solution ◽

Operating Conditions ◽

Ann Model ◽

Membrane Flux ◽

Input Variables ◽

Rsm Model

The forward osmosis (FO) process is an emerging technology that has been considered as an alternative to desalination due to its low energy consumption and less severe reversible fouling. Artificial neural networks (ANNs) and response surface methodology (RSM) have become popular for the modeling and optimization of membrane processes. RSM requires the data on a specific experimental design whereas ANN does not. In this work, a combined ANN-RSM approach is presented to predict and optimize the membrane flux for the FO process. The ANN model, developed based on an experimental study, is used to predict the membrane flux for the experimental design in order to create the RSM model for optimization. A Box–Behnken design (BBD) is used to develop a response surface design where the ANN model evaluates the responses. The input variables were osmotic pressure difference, feed solution (FS) velocity, draw solution (DS) velocity, FS temperature, and DS temperature. The R2 obtained for the developed ANN and RSM model are 0.98036 and 0.9408, respectively. The weights of the ANN model and the response surface plots were used to optimize and study the influence of the operating conditions on the membrane flux.

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Experimental analysis of mechanical properties of graphene/kenaf/basalt reinforced hybrid nanocomposites using response surface methodology

Journal of the Brazilian Society of Mechanical Sciences and Engineering ◽

10.1007/s40430-021-02936-3 ◽

2021 ◽

Vol 43 (4) ◽

Author(s):

Jaber Mirzaei ◽

Abdolhossein Fereidoon ◽

Ahmad Ghasemi-Ghalebahman

Keyword(s):

Mechanical Properties ◽

Response Surface Methodology ◽

Response Surface ◽

Experimental Analysis ◽

Hybrid Nanocomposites

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Experimental study on mechanical properties of polypropylene nanocomposites reinforced with a hybrid graphene/PP-g-MA/kenaf fiber by response surface methodology

Journal of Elastomers & Plastics ◽

10.1177/00952443211015362 ◽

2021 ◽

pp. 009524432110153

Author(s):

Jaber Mirzaei ◽

Abdolhossein Fereidoon ◽

Ahmad Ghasemi-Ghalebahman

Keyword(s):

Mechanical Properties ◽

Response Surface Methodology ◽

Elastic Modulus ◽

Response Surface ◽

Graphene Nanosheets ◽

Hot Press ◽

Kenaf Fiber ◽

Polypropylene Nanocomposites ◽

Kenaf Fibers ◽

Internal Mixer

In this study, the mechanical properties of polypropylene (PP)-based nanocomposites reinforced with graphene nanosheets, kenaf fiber, and polypropylene-grafted maleic anhydride (PP-g-MA) were investigated. Response surface methodology (RSM) based on Box–Behnken design (BBD) was used as the experimental design. The blends fabricated in three levels of parameters include 0, 0.75, and 1.5 wt% graphene nanosheets, 0, 7.5, and 15 wt% kenaf fiber, and 0, 3, and 6 wt% PP-g-MA, prepared by an internal mixer and a hot press machine. The fiber length was 5 mm and was being constant for all samples. Tensile, flexural, and impact tests were conducted to determine the blend properties. The purpose of this research is to achieve the highest mechanical properties of the considered nanocomposite blend. The addition of graphene nanosheets to 1 wt% increased the tensile, flexural, and impact strengths by 16%, 24%, and 19%, respectively, and an addition up to 1.5 wt% reduced them. With further addition of graphene nanosheets until 1.5 wt%, the elastic modulus was increased by 70%. Adding the kenaf fiber up to 15 wt% increased the elastic modulus, tensile, flexural, and impact strength by 24%, 84%, 18%, and 11%, respectively. The addition of PP-g-MA has increased the adhesion, dispersion and compatibility of graphene nanosheets and kenaf fibers with matrix. With 6 wt% PP-g-MA, the tensile strength and elastic modulus were increased by 18% and 75%, respectively. The addition of PP-g-MA to 5 wt% increased the flexural and impact strengths by 10% and 5%, respectively. From the entire experimental data, the optimum values for elastic modulus, as well as, tensile, flexural, and impact strengths in the blends were obtained to be 4 GPa, 33.7896 MPa, 57.6306 MPa, and 100.1421 J/m, respectively. Finally, samples were studied by FE-SEM to check the dispersion of graphene nanosheets, PP-g-MA and kenaf fibers in the polymeric matrix.

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Predictive modeling and statistical analysis of mechanical properties OF heat treated Cu-10 %Ni alloy using response surface methodology

Materials Today Proceedings ◽

10.1016/j.matpr.2021.12.167 ◽

2021 ◽

Author(s):

C.C. Nwaeju ◽

F.O. Edoziuno ◽

E.E. Nnuka

Keyword(s):

Mechanical Properties ◽

Response Surface Methodology ◽

Statistical Analysis ◽

Response Surface ◽

Predictive Modeling ◽

Heat Treated ◽

Ni Alloy

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Optimization of mechanical properties of polypropylene/talc/graphene composites using response surface methodology

Polymer Testing ◽

10.1016/j.polymertesting.2016.06.012 ◽

2016 ◽

Vol 53 ◽

pp. 283-292 ◽

Cited By ~ 54

Author(s):

Faramarz Ashenai Ghasemi ◽

Ismail Ghasemi ◽

Saman Menbari ◽

Mohsen Ayaz ◽

Alireza Ashori

Keyword(s):

Mechanical Properties ◽

Response Surface Methodology ◽

Response Surface

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Process Parameter Optimization in Fused Deposition Modeling (FDM) Using Response Surface Methodology (RSM)

10.21203/rs.3.rs-122421/v1 ◽

2020 ◽

Author(s):

Muhammad Salman Mustafa ◽

Muhammad Qasim Zafar ◽

Muhammad Arslan Muneer ◽

Muhammad Arif ◽

Farrukh Arsalan Siddiqui ◽

...

Keyword(s):

Mechanical Properties ◽

Response Surface Methodology ◽

Impact Strength ◽

Response Surface ◽

Layer Thickness ◽

Fused Deposition Modeling ◽

Experimental Results ◽

Fused Deposition ◽

Deposition Modeling ◽

Printing Parameters

Abstract Fused Deposition Modeling (FDM) is a widely adopted additive manufacturing process to produce complex 3D structures and it is typically used in the fabrication of biodegradable materials e.g. PLA/PHA for biomedical applications. However, FDM as a fabrication process for such material needs to be optimized to enhance mechanical properties. In this study, dogbone and notched samples are printed with the FDM process to determine optimum values of printing parameters for superior mechanical properties. The effect of layer thickness, infill density, and print bed temperature on mechanical properties is investigated by applying response surface methodology (RSM). Optimum printing parameters are identified for tensile and impact strength and an empirical relation has been formulated with response surface methodology (RSM). Furthermore, the analysis of variance (ANOVA) was performed on the experimental results to determine the influence of the process parameters and their interactions. ANOVA results demonstrate that 44.7% infill density, 0.44 mm layer thickness, and 20C° printing temperatures are the optimum values of printing parameters owing to improved tensile and impact strength respectively. The experimental results were found in strong agreement with the predicted theoretical results.

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