New Configurations of the Fuzzy Fractional Differential Boussinesq Model with Application in Ocean Engineering and Their Analysis in Statistical Theory

The fractional-order Boussinesq equations(FBSQe)are investigated in this work to see if they can effectively improve the situation where the shallow water equation cannot directly handle the dispersion wave.The fuzzy forms of analytical FBSQe solutions are first derived using the Adomian decomposition method.It also occurs on the sea floor as opposed to at the functionality.A set of dynamical partial differential equations(PDEs)in this article exemplify an unconfined aquifer flow implication.Thismethodology can accurately simulate climatological intrinsic waves,so the ripples are spread across a large demographic zone.The Aboodh transform merged with the mechanism of Adomian decomposition is implemented to obtain the fuzzified FBSQe in R,R^(n) and(2nth)-order involving generalized Hukuhara differentiability.According to the system parameter,we classify the qualitative features of the Aboodh transform in the fuzzified Caputo and Atangana-Baleanu-Caputo fractional derivative formulations,which are addressed in detail.The illustrations depict a comparison analysis between the both fractional operators under gH-differentiability,as well as the appropriate attributes for the fractional-order and unpredictability factorsσ∈[0,1].A statistical experiment is conducted between the findings of both fractional derivatives to prevent changing the hypothesis after the results are known.Based on the suggested analyses,hydrodynamic technicians,as irrigation or aquifer quality experts,may be capable of obtaining an appropriate storage intensity amount,including an unpredictability threshold.

The Toxic Effects of Strong Chlorin Disinfectant on Mangroves and Emission Thresholds

In this study, based on the simulated discharge results of chemical disinfectants, hypocotyl germination concentration gradient pre-test and concentration gradient determination experiment were set up respectively. Laboratory cultivation was conducted to compare and analyze the root germination and germination indexes, three mangrove hypocotyls of Kandelia candel (Linn.) Druce, Ceriopstagal C.B. Rob. and Bruguiera sexangula var. Rhynchopetalas’ efficiency of cumulative root germination, cumulative germination and the cumulative expansion of the second pair of leaves, one-way analysis of variance was used to obtain the tolerance threshold of three mangrove hypocotyls to strong chlorin disinfectant. The study determined that the by-products of strong chlorin disinfectant, the toxic threshold concentrations of Kandelia candel (Linn.) Druce, Ceriopstagal C.B. Rob. and Bruguiera sexangula var. rhynchopetala are close to 0.55 mg/L, 0.55 mg/L and 0.25 mg/L, respectively. This concentration range is lower than the average concentration of 1.183 mg/L of active chlorine emitted from strong chlorine concentrate during pond clearing in high-level shrimp ponds, indicating that transient emissions of strong chlorine concentrate during pond clearing can have a toxic effect on mangrove plants. The strength of tolerance of the embryonic axes of the three mangrove species to effective chlorine contamination was, Ceriopstagal C.B. Rob. stronger than Bruguiera sexangula var. rhynchopetala, and Kandelia candel (Linn.) Druce is the weakest.

The default mode network is affected in the early stage of simian immunodeficiency virus infection:a longitudinal study

Acquired immune deficiency syndrome infection can lead to cognitive dysfunction represented by changes in the default mode network.Most recent studies have been cross-sectional and thus have not revealed dynamic changes in the default mode network following acquired immune deficiency syndrome infection and antiretroviral therapy.Specifically,when brain imaging data at only one time point are analyzed,determining the duration at which the default mode network is the most effective following antiretroviral therapy after the occurrence of acquired immune deficiency syndrome.However,because infection times and other factors are often uncertain,longitudinal studies cannot be conducted directly in the clinic.Therefore,in this study,we performed a longitudinal study on the dynamic changes in the default mode network over time in a rhesus monkey model of simian immunodeficiency virus infection.We found marked changes in default mode network connectivity in 11 pairs of regions of interest at baseline and 10 days and 4 weeks after virus inoculation.Significant interactions between treatment and time were observed in the default mode network connectivity of regions of interest pairs area 31/V6.R and area 8/frontal eye field(FEF).L,area 8/FEF.L and caudal temporal parietal occipital area(TPOC).R,and area 31/V6.R and TPOC.L.ART administered 4 weeks after infection not only interrupted the progress of simian immunodeficiency virus infection but also preserved brain function to a large extent.These findings suggest that the default mode network is affected in the early stage of simian immunodeficiency virus infection and that it may serve as a potential biomarker for early changes in brain function and an objective indicator for making early clinical intervention decisions.

Influence of tool material and rotational speed on mechanical properties of friction stir welded AZ31B magnesium alloy

In this investigation,the effect of friction stir welding(FSW)parameters such as tool material rotational speed,and welding speed on the mechanical properties of tensile strength,hardness and impact energy of magnesium alloy AZ31B was studied.The experiments were carried out as per Taguchi parametric design concepts and an L9 orthogonal array was used to study the influence of various combinations of process parameters.Statistical optimization technique,ANOVA,was used to determine the optimum levels and to find the significance of each process parameter.The results indicate that rotational speed(RS)and traverse speed(TS)are the most significant factors,followed by tool material(TM),in deciding the mechanical properties of friction stir processed magnesium alloy.In addition,mathematical models were developed to establish relationship between different process variables and mechanical properties.

Influence of tool pin profile and rotational speed on the formation of friction stir welding zone in AZ31 magnesium alloy

In this investigation,the effect of friction stir welding(FSW)parameters such as tool pin profiles,rotational speed and welding speed on the mechanical properties of tensile strength,hardness and impact energy of magnesium alloy AZ31 was studied.The experiments were carried out as per Taguchi parametric design concepts and an L9 orthogonal array was used to study the influence of various combinations of process parameters.Statistical optimization technique,ANOVA,was used to determine the optimum levels and to find the significance of each process parameter.The results indicate that rotational speed(RS)and transverse speed(TS)are the most significant factors,followed by tool pin profile(PF),in deciding the mechanical properties of friction stir welded magnesium alloy.In addition,mathematical models were developed to establish relationship between different process variables and mechanical properties.

Decomposition Method of Genetic Correlation Coefficient Based on NC Ⅱ Mating Design

There are different degrees of correlation between crop traits. The phenotypic correlation is decomposed into genetic and environmental correlation in quantitative genetics. In this paper,according to stochastic model of variance and covariance analysis,we calculate different genetic components,bring up a decomposition method of genetic correlation coefficient based on NC II mating design,and use examples to show analytic steps and interpret results.

The Effects of Water Recycling on Flotation at a North American Concentrator—Part 1

Water chemistry and its impact on mineral processing operations are not well understood and often not adequately monitored. CanmetMINING, as part of its water management research program, has been involved in a project initiated to identify opportunities for improving water recovery, water treatment, and recycling in the mining and mineral processing operations. One of the main objectives of this work is to evaluate and assess water chemistry and identify factors that impact mineral recovery, concentrate grade, and metal extraction efficiencies in order to understand and mitigate negative impacts of water recycling and improve process efficiency. In collaboration with a North American concentrator, CanmetMINING has been involved in assessing the water chemistry in the mill and evaluating water recycling options for select process streams to reduce fresh water intake and maximize recycling. The overall goal of the project is to investigate options for water recycling (increase the thickener overflow recirculation from thickener overflow tank) without affecting nickel and copper metallurgy. The results of the sampling campaigns showed that the water chemistry of the streams was fairly consistent throughout the year with no significant seasonal variations. The laboratory tests illustrated that when higher quantities of thickener overflow from thickener overflow were used, the nickel + copper grade versus nickel recovery curves shifted towards lower values. These observations were observed for the plant water samples obtained in April, June and August 2019.

Development of Empirical Models for the Estimation of CBR Value of Soil from Their Index Properties: A Case Study of the Ogbia-Nembe Road in Niger Delta Region of Nigeria

This study developed empirical-mathematical models to predict the California Bearing Ratio (CBR) using soil index properties in Ogbia-Nembe road in the Niger Delta region of Nigeria. The determination of CBR of soil is a laborious operation that requires a longer time and materials leading to increased cost and schedule;this can be reduced by adopting an empirical-mathematical model that can predict the CBR using other simpler soil index properties such as Plastic Limit (PL), the Liquid Limit (LL), the Plasticity Index (PI) and the Moisture Content (MC), which are less laborious and take lesser time to obtain. Thirteen models were developed to understand the relationship between these soil index properties: the independent variable and the California Bearing Ratio (CBR): the dependent variable;Six linear, Six quadratic and One multiple linear regression models were developed for this relationship. Analysis of variance (ANOVA) on the thirteen models showed that the Optimum Moisture Content (OMC) and the Maximum Dry Density (MDD) are better independent variables for the prediction of the CBR value of Ogbia-Nembe soil generating a quadratic model and a multiple linear regression model having a better coefficient of determination R2 = 0.96 and 0.94 respectively, mean square error (MSE) of 0.74 and 1.152 respectively with Root mean square errors of 0.861 and 1.073 accordingly. These models were used to predict the CBR of the soil. The CBR values predicted by the model were further compared with those of the actual experimental test and found to be relatively consistent with minimal variance. This establishes that CBR of any soil can be predicted from the Index Property of the soil and this is more economical and takes lesser time and can be universally adopted for soil investigation.

Off-Line Quality Control in Bioproducts Processing: A Case Study in Greece

In the present article we study the production of grape molasses. Data drawn from a specified biolaboratory, are properly analyzed in order to detect factors that affect significantly the Brix value and the volatile acidity of the final product. The ground that is used for planting and a variety of grapes have been taken into account. Off-line statistical quality control techniques have been employed and the outcomes are displayed and discussed in detail.

Statistical Method for Block in Replication Design and Its SAS Program

Large-scale genetic population used for genetic breeding researches covers a large area in the field experiment,and the effect of local control would be gradually weakened.The block in replication(BIR)design is suitable for large population,which is applied to the field experiment of genetic population.The statistical methods of analysis of variance(ANOVA)and heritability estimation in single and multiple environments were derived and implemented using the statistical analysis system(SAS)program for the analysis of BIR.As a work example,a comparison of statistical analysis between BIR design and the completely random block(CRB)design were conducted for the protein content from a panel containing 455 soybean germplasms.The results indicated the different estimates of average heritability in multiple environments.The research results provided technical support for the application of BIR design in genetics and breeding studies.

Optimization for aerodynamic performance of double serpentine nozzles with spanwise offsets using Taguchi-based CFD analysis

Serpentine nozzles are widely used in combat aircraft to realize strong stealth characteristics.Based on the layout characteristics within a confined space,a series of double serpentine nozzles with spanwise offsets are established.Using computational fluid dynamics and Taguchi method,the influence mechanisms of the Distribution of Area(DA),Distributions of Centerline for the first and second‘S’sections in the Vertical direction(DCV1 and DCV2),and Distribution of Centerline in the Spanwise direction(DCS)are analyzed.The impact of these factors on the total pressure recovery coefficient can be ranked as DA>DCV2>DCS>DCV1,whereas their impacts on the discharge coefficient and axial thrust coefficient can be ranked as DCV2>DCS>DA>DCV1.Considering the statistical significance of these factors,a nozzle in which DA changes rapidly at the exit and DCV1,DCV2,and DCS change rapidly at the entrance gives the best aerodynamic performance.Compared to the worst configuration,the total pressure recovery coefficient,discharge coefficient,and axial thrust coefficient are improved by 1.6%,3.5%and 3.6%,respectively.DA influences the gas flow acceleration in the entire serpentine channel,resulting in different wall shear stress and friction losses.The various centerline distributions influence the gas flow acceleration effects and form complex wave structures in the constantarea extension section,resulting in different local and friction losses.

Thermal optimization of MHD nanofluid over a wedge by using response surface methodology:Sensitivity analysis

It is well documented that heat transfer is enhanced with addition of nanosized particles in fluid.But,in a mechanical system there are variety of factors influences the heat transfer.Some factors are significant while others are not.In this paper,authors will discuss sensitivity of different input parameters such as Le,Nt and Nb on output responses𝑁Nu_(x)and Sh_(x).To achieve this goal,the problem is modeled using basic conservation laws.The formulated model is a set of PDEs,which are converted to set of non-linear ODEs by using similarity transformation.Then these ODEs are solved numerically by using MATLAB built in package bvp4c and compared the numerical results with existing work and found good results.Sensitivity analysis is performed by employing RSM to determine the relationship between the input parameters such that 0.1≤Le≤1,0.1≤Nt≤1 and 0.1≤Nb≤1 and the output responses(Nu_(x)and Sh_(x)).ANOVA tables are generated by using RSM.By using the ANOVA tables the correlations between input parameters and output response are developed.To check the validity of correlated equations,the residuals are plotted graphically and show best correlations between input parameters and output responses.The high values of R^(2)=98.65 and AdjR^(2)=97.43 for Nu_(x)and R^(2)=97.83 and AdjR^(2)=95.88 for Sh_(x)demonstrates the high validity of ANOVA results to perform sensitivity analysis.Finally,we have conducted a sensitivity analysis of the responses and came to the important results that Nt and Nb is most sensitive to Nusselt number and Sherwood number respectively.

Modeling and analysis of pelletization process based on a multi-hole pelletizing device

A multi-hole pelletizing device(MPD)was proposed to simulate the granular extrusion process of animal feed due to its cheap,fast,and controllable features.The compression mechanism was analyzed and discussed according to the compression force-time curve.This study applied response surface methodology(RSM)with a central composite design(CCD)to develop predictive models for the compression force Fout and the pellet properties which includes pellet densityρp,pellet moisture content Mcp,and pellet tensile strength Dp based on the MPD.The effects of feedstock moisture content Mcf(10%-18%w.b.),feedstock particle size Sf(8 meshes-24 meshes),die temperature Td(70°C-110°C)and compression speed Vc(5 mm/min to 25 mm/min)were investigated.Response surface models developed for the compression force and pellet properties have adequately described the pelleting process(R^(2)>0.95).The results showed the significant effects of all factors and most of the squared and interaction terms on the compression force and pellet physical properties.It can be concluded from the present study that moisture content and die temperature,followed by compression speed and feedstock particle size are the interacting process factors influencing compression force and pellet properties.

Modeling, analysis, and optimization of dimensional accuracy of FDM-fabricated parts using definitive screening design and deep learning feedforward artificial neural network

Additive manufacturing(AM)technologies such as fused deposition modeling(FDM)rely on the quality of manufactured products and the process capability.Currently,the dimensional accuracy and stability of any AM process is essential for ensuring that customer specifications are satisfied at the highest standard,and variations are controlled without significantly affecting the functioning of processes,machines,and product structures.This study aims to investigate the effects of FDM fabrication conditions on the dimensional accuracy of cylindrical parts.In this study,a new class of experimental design techniques for integrated second-order definitive screening design(DSD)and an artificial neural network(ANN)are proposed for designing experiments to evaluate and predict the effects of six important operating variables.By determining the optimum fabrication conditions to obtain better dimensional accuracies for cylindrical parts,the time consumption and number of complex experiments are reduced considerably in this study.The optimum fabrication conditions generated through a second-order DSD are verified with experimental measurements.The results indicate that the slice thickness,part print direction,and number of perimeters significantly affect the percentage of length difference,whereas the percentage of diameter difference is significantly affected by the raster-to-raster air gap,bead width,number of perimeters,and part print direction.Furthermore,the results demonstrate that a second-order DSD integrated with an ANN is a more attractive and promising methodology for AM applications.

Strain rate analyses during elliptical vibration cutting of Inconel 718 using finite element analysis,Taguchi method,and ANOVA

The high strain rate in metal cutting significantly affects the mechanical properties of the work piece by altering its properties.This study outlines the material strain rates during elliptical vibration cutting.The finite element analysis,Taguchi method,and analysis of variance(ANOVA)were employed to analyze the effects and contributions of cutting and vibration process parameters(feed rate,rake angle,tangential amplitude,and frequency of vibration)on the variation of strain rates during machining of Inconel 718.Taguchi signal-to-noise analysis on an L18(2^1×3^3)orthogonal array was used to determine the optimum parametric combination for the maximum strain rate,and ANOVA was applied to evaluate the significance of control parameter factors on the strain rate.The results of the finite element analysis under different conditions illustrated that the feed rate and rake angle were negatively related to the strain rate,whereas the tangential amplitude and frequency had a positive response.Furthermore,ANOVA results indicated that the effect of the feed rate,tool rake angle,vibration frequency,and tangential amplitude on the strain rate were all statistically significant,with a reliability level of 95%.Of these,the dominant parameter affecting the strain rate was the feed rate,with a percentage contribution of 40.36%.The estimation of the optimum strain rate and confirmation tests proved that the Taguchi method could successfully optimize the working conditions to obtain the desired maximum strain rate.

SIMULATION, ANALYSIS AND OPTIMIZATION OF CONTAINER TERMINALS PROCESSES

The freight logistics includes all the processes needed to supply industry,retailers and wholesalers and final customers with goods.Such processes generate a flow of goods that,in the global supply chain,mainly relies on the activities carried out within worldwide container terminals.In this paper,the authors present a simulation model of a real container terminal.After some preliminary analyses,the simulation model is first used with Design of Experiments and Analysis of Variance to investigate the effects of different resources allocations(i.e.,number of forklifts and tractors)and some parameters(i.e.,inter-arrival times,container unloading time)on the container terminal performances in terms of total number of handled containers per day.Then,based on the results achieved through the Design of Experiments and Analysis of Variance,the simulation model is used with genetic algorithms to carry out a range allocation optimization on berth assignment to incoming ships and number of tractors serving each quay crane.The aim of the optimization is the minimization of the average time spent by each ship in the port area(decreasing,as consequence,costs and increasing service level provided to final customers).

Effects of soil and water conservation practices on soil physicochemical properties in Gumara watershed, Upper Blue Nile Basin, Ethiopia

Background:Soil erosion is among the foremost causes of declining soil resources in Ethiopia,which in turn affect agricultural productivity.To limit this problem,for the last two decades in Gumara watershed,soil and water conservation measures have been practiced through free labor community mass-mobilization.However,their effect on soil fertility has not been evaluated.This study investigated the impact of implemented soil and water conservation measures on fertility improvement in the Gumara watershed.Both composite and core soil samples were taken from upstream,midstream,and downstream adjacent conserved and non-conserved cultivated and grazing plots.Selected soil fertility indicators were analyzed using standard laboratory procedures.Results:Soil and water conservation practices have resulted in a statistically significantly higher mean values of total nitrogen,exchangeable Na+and Mg2+at p<0.01,and of soil organic carbon and organic matter at p<0.05 in the watershed.The clay content,soil reaction,cation exchange capacity,and exchangeable K+showed nonsignificant,but higher mean values in conserved plots.Furthermore,the effects of conservation practices on soil properties were found more effective in cultivated land uses as compared to that of grazing land uses.This is because conservation treatments had significant effects on organic carbon,total nitrogen,exchangeable Na+and Mg2+in cultivated land uses but only on exchangeable Na+in grazing land uses.The interaction effect of treatments and land uses did not reach a statistically significant result for any of the soil properties considered in this study.Conclusion:Conservation measures have important implications for improving soil fertility in the Gumara watershed.Therefore,proper guidance and follow-up,use of agro-forestry and grass strips,and maintenance are required for the watershed’s sustainability and good soil conditions.

Numerical investigation and optimisation of heat transfer performance in a vertical sinter cooling packed bed using Taguchi and ANOVA methods

The Taguchi and analysis of variance (ANOVA) methods were applied to investigate the effects of the structural and operational parameters on the heat transfer performance of a vertical sinter cooling packed bed. The analysed parameters were the gas flow rate, the air inlet temperature, the sinter inlet temperature, the cooling bed diameter and the cooling bed height, all of which contain three levels. The purpose was to improve the heat transfer performance of a vertical sinter cooling bed. A numerical analysis model was established to assess the heat transfer performance with respect to the varying parameters and their different levels. This mathematical model was validated by using data from practical industrial processes. The Taguchi method for the L27 (35) orthogonal design experiment was selected to evaluate the impacts of the design parameters on the heat transfer performance and to acquire the optimum combination of parameters. The analysis of variance was applied to assess the impact weights and the order of significance of the design parameters. The results show that the sinter inlet temperature and cooling bed diameter have great influences and impact the exergy of the wasted heat recovery by 61.65% and 23.31%, respectively. However, the gas flow rate and the air inlet temperature have small effects on the response. Furthermore, the air and sinter inlet temperatures have the most significant impacts on the efficiency of heat transfer by 68.83% and 23.31%, respectively. The optimal parameter combination (A1B1C3D3E3) was obtained, and the optimal results were validated by confirmation tests.

Experimental investigation and prediction of tribological behavior of unidirectional short castor oil fiber reinforced epoxy composites

The present study aims at introducing a newly developed natural fiber called castor oil fiber,termed ricinus communis,as a possible reinforcement in tribo-composites.Unidirectional short castor oil fiber reinforced epoxy resin composites of different fiber lengths with 40%volume fraction were fabricated using hand layup technique.Dry sliding wear tests were performed on a pin-on-disc tribometer based on full factorial design of experiments(DoE)at four fiber lengths(5,10,15,and 20 mm),three normal loads(15,30,and 45 N),and three sliding distances(1,000,2,000,and 3,000 m).The effect of individual parameters on the amount of wear,interfacial temperature,and coefficient of friction was studied using analysis of variance(ANOVA).The composite with 5 mm fiber length provided the best tribological properties than 10,15,and 20 mm fiber length composites.The worn surfaces were analyzed under scanning electron microscope.Also,the tribological behavior of the composites was predicted using regression,artificial neural network(ANN)-single hidden layer,and ANN-multi hidden layer models.The confirmatory test results show the reliability of predicted models.ANN with multi hidden layers are found to predict the tribological performance accurately and then followed by ANN with single hidden layer and regression model.

Analytical study of friction coefficients of pomegranate seed as essential parameters in design of post-harvest equipment

Friction coefficients(static friction coefficient(SFC)and dynamic friction coefficient(DFC))of pomegranate seed on different structural surfaces(glass,aluminum,plywood,galvanized steel and rubber)as affected by moisture content(4-21.9%(d.b.))and sliding velocity(1.4-16(cm/s))were investigated.Analysis of variance(ANOVA)was performed to determine the effect of main treatments and their interactions on SFC and DFC.Significance of single or multiple effect of the main treatments with five levels was assessed using Duncan’s multiple range test(DMRT).To predict SFC and DFC,multiple linear regression(MLR)modeling technique was applied for each type of structural surface.The goodness of fit of each MLR model was evaluated using statistical parameters:coefficient of determination,root mean square error and mean relative deviation modulus.Results showed that the minimum and maximum SFC or DFC were in minimum and maximum moisture content on glass and rubber surface,respectively.ANOVA table indicated the significant effect of main treatments and their interactions on SFC and DFC at significance level of 1%(P<0.01).According to DMRT results,SFC linearly increased as moisture content increased and DFC increased also linearly as individual or simultaneous increment of moisture content and sliding velocity occurred,for all experimental conditions.According to the obtained statistical parameters,both SFC and DFC were properly predicted by means of MLR modeling technique.