Extreme Vertices Research Articles

Applicability of Extreme Vertices Design in the Compositional Optimization of 3D-Printed Lightweight High-Entropy-Alloy/B4C/ZrO2/Titanium Trihybrid Aero-Composite

Recent studies have shown the benefits of utilizing ceramic particles as reinforcement in metal alloys; nevertheless, certain drawbacks, including loss of ductility, embrittlement, and decreases in toughness, have been noted. For the objective of obtaining balanced performance, experts have suggested the addition of metal particles as supplement to the ceramic reinforcement. Consequently, high-performance metal hybrid composites have been developed. However, achieving the optimal mix for the reinforcement combination with regards to the optimal performance of developed composite remains a challenge. This research aimed to determine the optimal mixture of Al50Cu10Sn5Mg20Zn10Ti5 lightweight high-entropy alloy (LHEA), B4C, and ZrO2 for the fabrication of trihybrid titanium composites via direct laser deposition. A mixture design was involved in the experimental design, and experimental data were modeled and optimized to achieve the optimal performance of the trihybrid composite. The ANOVA, response surface plots, and ternary maps analyses of the experimental results revealed that various combinations of reinforcement particles displayed a variety of response trends. Moreover, the analysis showed that these reinforcements significantly contributed to the magnitudes and trends of the responses. The generated models were competent for predicting response, and the best formulation consisted of 8.4% LHEA, 1.2% B4C, and 2.4% ZrO2.

Investigations on wetting and structural behavior using CaF2-SiO2-CaO-22.5%TiO2 SMAW electrode coating for AUSC applications

This study investigates the structural behavior and high-temperature wettability of a CaF2-SiO2-CaO-22.5%TiO2 shielded metal arc welding electrode coating for advanced ultra-supercritical power plant applications. The wettability parameters were measured, including contact angle, spread area, adhesion energy, and surface tension. Extreme vertices mixture design approaches were used to develop 13 different electrode coatings. To determine the contact angle at solid/liquid interface, circular pellets were made from powder samples and heated inside the furnace at 1125°C at a constant heating rate. Young's and Boni's equations are used to calculate the surface tension value for 13 coated samples using the calculated contact angle. Adhesion energy for 13 coated samples is calculated using Dupre's equation. Phases and structural behavior of coating samples were measured by Fourier transform infrared spectroscopy and X-ray diffraction. The developed regression model estimates the impact of primary ingredients and their interaction on the calculated wettability characteristics. CaF2.SiO2, CaO.SiO2, and CaO.CaF2 binary mixture is the more favorable and substantially impacts contact angle, whereas ternary interactions of CaO.SiO2.CaF2 shows an opposite effect on contact angle. Coating numbers 2 and 10 give better wetting behavior and spread area due to the low value of contact angles. Individual ingredient shows an increasing effect on surface tension and adhesion energy. Ternary component of CaO.CaF2.SiO2 is favorable and shows an increasing impact on adhesion energy.

Investigation and modeling of the SMAW coating flux thermal properties using neural network and regression analysis

The present work aims to design and develop shielded metal arc welding electrode coating fluxes. The thermal properties of the electrode coating fluxes are studied. Ternary phase diagrams of CaF2−CaO−Al2O3 and SiO2−BaO−Al2O3 are used to determine the range of constituents. 27 flux mixture combinations were created using an extreme vertices design approach. The corrected optical basicity is estimated and utilized for the theoretical estimation of sulfide capacity and water vapor solubility. Thermogravimetric analysis, and differential scanning calorimetry analysis was performed to quantify the thermal response of the flux while heating. Thermogravimetry analysis shows variation of weight loss from 8.49% to 12.25% with the variation in flux composition. Calcite and witherite has positive influence on weight loss. Differential scanning calorimetry shows an overall change in enthalpy from −1076.73 to −7786 J/g. Hot disk analysis reveals fluorspar has a positive effect, whereas calcite has a negative effect on thermal conductivity. The effect of individual flux constituents and their interactions on thermal properties is discussed using regression analysis. The artificial neural network is used for predictive modeling, and the accuracy of its predictions is compared to regression analysis. In comparison to the regression, the model's mean square error improved by nearly 37% on average. The reduction in the mean absolute percentage error of the unseen test data suggests that the artificial neural network approach has better modeling capability.

Investigation of Thermophysical and Physicochemical Characteristics of Al2O3-SiO2- CaO - Na3AlF6 Flux for SMAW Electrode Coating

This study investigated the thermophysical, physicochemical, and electrical characteristics of electrode coatings developed for application in the weld joint of nuclear power plants (NPPs). The extreme vertices design technique has been used in this work to develop the Al2O3-SiO2-CaO-Na3AlF6-based Shielded metal arc welding (SMAW) electrodes. Twenty-six electrode coating compositions were formulated, and flux coatings were milled into a fine powder for further characterization. X-ray diffraction (XRD) technique was utilized to investigate the structure and phases of the coating composition, and the Fourier transform infrared (FTIR) analysis technique was employed to determine the nature of bonds. The coating's thermal characteristics, including conductivity, diffusivity, and specific heat, were evaluated using hot disk equipment. Enthalpy change and thermal stability of flux coating were determined using the Differential thermal analysis(DTA)/ differential scanning calorimetry (DSC) technique.. The precision inductance (L), capacitance (C), and resistance (R) (LCR) instrument was used further to examine the electrical characteristics of the flux coatings. In addition, a regression model has been developed for each coating property using statistical analysis and investigated a correlation between the properties and mineral interactions. Results reveal that the individual elements and their binary and tertiary interaction significantly influence the physicochemical, thermophysical, and electrical properties of the flux coatings.

Nanoemulgel formulation for topical delivery of plant glucosylceramide: Characterization and optimization

Plant sphingolipids (SPLs) are available as oral or topical skin care products in order to restore skin protective nature due to their chemical similarity with human skin ceramides (CERs). However, successful delivery of glucosylceramide (GlcCER) to the viable epidermis is challenging due to the skin barrier nature. The current study aimed to develop and characterize optimized nanoemulsion (NE) and nanoemulgel (NEG) formulations for topical delivery of lupin GlcCERs. The NE components were screened and pseudo-ternary phase diagrams were constructed at different hydrophilic-lipophilic balance (HLB) values of surfactant-co-surfactant mixture (Smix). Extreme vertices mixture design was developed to investigate the impact of percentage compositions of the independent variables; oil mixture (2–3%), Smix (15–18%) and aqueous component (79–83%) on the globule size of the NEs. Then, NEG was prepared from optimized 0.25% lupin GlcCER NE and Carbopol 980 gel. HLB values of 13.5 and 12 provided broader NE regions for Miglyol and isopropyl myristate, respectively. The analysis of variance of the quadratic model showed suitability of the model with R2 of 99.80 and non-significant lack of fit (F value = 17.06). The optimized percentage compositions of oil phase, Smix and aqueous phase were 2.15%, 16.39% and 81.46%, respectively, with predicted globule size of 23.96 nm. Accordingly, the optimized NE globule size, poly dispersity index and zeta potential were 23.93 ± 0.25 nm, 0.069 ± 0.017 and 23.95 ± 1.20 mV, respectively. The oil globules were spherical and distributed uniformly without aggregation. The NE exhibited Newtonian flow with a viscosity of 6.75 mPa s while NEGs showed non-Newtonian flow with shear thinning property. The amount of lupin GlcCER released and penetrated into each model membrane layer at different time point was in the order of NEs > basic cream > NEGs. After 180 min, 51%, 84% and 96% of lupin GlcCER was released and penetrated into the model membrane layers from NEG, basic cream and NEs, respectively. NEGs prolonged the release and slowed down the penetration of GlcCER into the multilayer membrane model which is crucial to limit its penetration into the epidermal skin layer. Therefore, NEGs could be considered as an option for the delivery of plant GlcCER into the upper part of the skin after further ex-vivo investigation as the study is the first of its kind.

The extreme vertices of the power graph of a group

For a fixed finite group G, the power graph of G was defined to be the simple graph Γ(G) whose vertex set V(Γ(G))=G, and edge set E(Γ(G))={xy: either x=yn or y=xn for some integer n}. In this paper the extreme vertices of the power graph of abelian groups, dihedral groups and dicyclic groups have been characterized.

Wettability studies of formulated SMAW electrode coating fluxes with regression analysis and neural network approach

The present work aims to formulate and investigate the SMAW electrode coating fluxes for pipeline steels. The wettability of the flux on steel has a significant influence on weld properties. Twenty-seven flux compositions are produced by the extreme vertices design approach. The contact angle, spread area, work of adhesion, and floatation coefficient at 1573 K are investigated for the SiO2−CaO−CaF2−BaO−Al2O3−TiO2 fluxes. The corrected optical basicity and surface tension of the fluxes are estimated. The XRD, FTIR, and UV–vis analysis techniques are employed to investigate the phases present in the flux and slag. The structural analysis of the melt is done by examining the powder of quenched slag. The corrected optical basicity is estimated, which is a global measure of oxygen species in the melt. Regression models are developed to study the effect of flux composition on the wettability properties. An artificial neural network method is used, and the MSE and MAPE values for the predicted result have been successfully lowered.

On the toll number of a graph

A tolled walk T between two different, non-adjacent vertices u , v in a graph G is a walk in which u and v have exactly one neighbor. A toll interval between u , v ∈ V ( G ) , T ( u , v ) , is the set of all vertices of G that lie in some tolled u , v -walk. A set S ⊆ V ( G ) is t -convex if T ( u , v ) ⊆ S for any u , v ∈ S . The size of a maximum proper t -convex set S ⊆ V ( G ) is called the t -convexity number of a graph G and is denoted by c t ( G ) . A vertex v ∈ V ( G ) is t -extreme if V ( G ) − { v } is a t -convex set of G . The toll number of G , t n ( G ) , is the smallest size of a set S with ⋃ u , v ∈ S T ( u , v ) = V ( G ) . In this paper we prove that t n ( G ) ≤ 6 in any prime graph G with diam ( G ) > 2 . Then we present the exact value of the toll number of a cograph which implies that in any cograph G , t n ( G ) can be computed in polynomial time. Cographs are used to present the existence of a graph G of diameter 2 in which the difference between t n ( G ) and the number of t -extreme vertices is arbitrary large. Then we consider graphs with extreme toll number and give a characterization of graphs G with t n ( G ) ∈ { 2 , | V ( G ) | − 1 , | V ( G ) | } . Finally we give a characterization of t -convex sets and prove that for a given k , deciding whether c t ( G ) ≥ k is NP-complete.

Optimization and Simulation of Saw Dust Ash Concrete Using Extreme Vertex Design Method

In this research study, a constrained simplex optimization method was adapted for the evaluation of green concrete’s mechanical property constituting of two-component mixture problem of cement and saw dust ash (SDA), which is a derivative from industrial residue. This experiential research will provide avenue for the recycle and incorporation of waste materials to achieve sustainability and control indiscriminate disposal of waste. The formulated components constrained were realized from the relevant literature studies to obtain the feasible planes in the simplex, and from this computation approach using I-optimality, the design mixture proportions and experimental runs were derived. The experimental results obtained from the laboratory experiments showed a maximum compressive strength of 31.13 N/mm2 with a ratio of 0.875 : 0.125 for cement and SDA, respectively, and a flexural strength of 9.49 N/mm2 with a ratio of 1 : 0 for cement and SDA, respectively; the results were observed to decline linearly with the further addition of SDA. The details generated from laboratory program were utilized for the development of the EVD model through fits statistical evaluation, ANOVA, diagnostic test and influence statistics, numerical optimization, and graphical statistical computations to analyze the datasets and locate the optimal levels of mixture ingredients using desirability function. A desirability score of 0.990 was derived at a mix ratio of 0.89 : 0.110 for the two components, cement and SDA, to produce a maximized compressive strength and a flexural strength of 31.102 N/mm2 and 9.384 N/mm2, respectively. Furthermore, the test of adequacy of the generated EVD model was carried out through simulation and statistical validation exercises using the F-test and student’s t-test, and the outcome signified a good correlation between the EVD model-simulated and actual values withpvalue >0.05.

Effect of the Addition of Soybean Residue (Okara) on the Physicochemical, Tribological, Instrumental, and Sensory Texture Properties of Extruded Snacks.

An extrusion process was used to improve the physical and textural characteristics of an extruded snack supplemented with soybean residue (okara). An extreme vertices mixture design with a constraint for okara flour (0–50%), mung bean flour (20–70%), and rice flour (20–80%) resulted in the production of eleven formulations. The color, radial expansion index (REI), bulk density, tribological behavior, and instrumental and sensory texture of the extruded snacks were evaluated. Increasing the quantity of okara resulted in an extrudate with a darker, redder color, decreased REI, increased bulk density, and decreased crispness. The tribological pattern of the snack was determined by its dominant composition (protein, starch, or fiber) in the flour mixture, which contributed to the stability of the lubricating film under rotational shear. A principal component analysis of sensory data captured a total of 81.9% variations in the first two dimensions. Texture appeal was inversely related to tooth packing (r = −0.646, p < 0.05). The optimized formulation for texture preference had an okara content of 19%, which was 104% crispier and 168% tougher than an okara content of 40%. This by-product of soybean milk processing can thus be used to develop gluten-free snacks with desirable physical characteristics and texture.

Rapid oral transmucosal delivery of zaleplon–lavender oil utilizing self-nanoemulsifying lyophilized tablets technology: development, optimization and pharmacokinetic evaluation

Based on the administration convenience, transmucosal buccal drug delivery allows special strength points over peroral routes for systemic delivery. It could achieve local or systemic effect and boost drugs’ bioavailability for agents with first pass metabolism. The current study aimed to manufacture and optimize a lavender oil–based nanoemulsion loaded with zaleplon and incorporate it into fast-disintegrating tablets to promote its dissolution and oral bioavailability via oral mucosa. Zaleplon-loaded nanoemulsions were devised with various levels of lavender oil (10% to 25%), the surfactant Sorbeth-20 (35% to 65%), and the co-surfactant HCO-60 (20% to 40%); the extreme vertices mixture statistical design was adopted. The droplet size and drug-loading efficiency were the evaluated. The optimal formulation was transformed into self-nanoemulsified lyophilized tablets (ZP-LV-SNELTs), which were tested for their uniformity of content, friability, and disintegration time with in-vitro release. Finally, the pharmacokinetic parameters of the ZP-LV-SNELTs were determined and compared with those of marketed formulations. The optimal nanoemulsion had a droplet size of 87 nm and drug-loading capacity of 185 mg/mL. ZP-LV-SNELTs exhibited acceptable friability and weight uniformity and a short disintegration time. The in-vitro release of ZP-LV-SNELTs was 17 times faster than that of the marketed tablet. Moreover, the optimal ZP-LV-SNELTs increased the bioavailability of zaleplon in rabbits by 1.6-fold compared with the commercial tablets. Hence, this investigation revealed that ZP-LV-SNELTs delivered zaleplon with enhanced solubility, a fast release, and boosted bioavailability thru oral mucosa which provided a favorable route for drug administration which is suggested to be clinically investigated in future studies

Formulation of the agro-waste mixture for multi-enzyme (pectinase, xylanase, and cellulase) production by mixture design method exploiting Streptomyces sp.

The demand for enzymes in different industries is continuously increasing, and the use of a pure form of carbon and nitrogen source for enzyme production is expensive. Thus, organic waste as a low-cost substrate is used to produce enzymes, mitigate the market demand, and reduce the production cost. Besides, this action helps in decreasing organic waste and finally pollution. This study aims to utilize agro-waste for maximum multi-enzyme production by Streptomyces sp. and to formulate the three agro-waste mixtures using a statistical approach; extreme vertices mixture design (EVMD). The study illustrated the bacterium produced a maximum of 4.24 ± 0.05 U/mL pectinase, 2.88 ± 0.05 U/mL polygalacturonase (PGase), 9.43 ± 0.16 U/mL xylanase, and 1.62 ± 0.09 U/mL cellulase by formulating the agro-waste mixture of orange peel, pomegranate peel, and pumpkin pulp+seeds. Also, the mixture of agro-waste enhanced enzyme production rather than the single feedstock, and the enzyme production depends on the agro-waste mixture.

Experimental investigation on SMAW electrode coatings developed using CaO–SiO2–CaF2–SrO based coating system

This research aims to provide a SMAW electrode coating developed using a CaO–SiO2–CaF2–SrO flux system for welding the components of an advanced ultra-supercritical power plant. The physicochemical and thermophysical characteristics of developed coatings were investigated. Twenty-one distinct electrode coating formulations were developed using the extreme vertices technique. Experiments for several thermophysical and physicochemical characteristics were carried out. The coating's qualities are critical for producing a strong weld that will last in the field. X-ray diffraction and Infrared spectroscopy were used to examine the structural behavior of the electrode coatings. Furthermore, the regression model was developed to explore the effect of coating compositions. The primary constituents and their interaction have an influential role in physicochemical and thermophysical characteristics. Individual and ternary mixtures significantly affect the density. CaO.SiO2.SrO and CaF2·SiO2·SrO is the most effective ternary mixture, which has an increasing effect on density. The weight loss of coating observed during thermogravimetric analysis is affected by individual constituents significantly. The ternary mixture CaO·CaF2·SiO2, CaO·CaF2·SrO, and CaF2·SiO2·SrO is the most favorable and has an increasing effect on weight loss. Individual constituents affect change in enthalpy significantly. The thermal properties of coating observed during hot disc are affected by binary and ternary mixture constituents. Binary mixture CaO·SiO2 is having an increasing effect on thermal conductivity. Binary mixture CaO·SrO and SrO containing ternary mixture have an increasing impact on thermal diffusivity. Ternary mixture constituents CaO·CaF2·SrO, CaF2·SiO2·SrO is the most effective and has an increasing effect on specific heat.

Topological aspects of extended Sierpiński structures with help of underlying networks

Sierpiński networks are the most studied networks of fractal nature with applications in various fields of science. A generalized Sierpiński network is obtained by copying the base network, resulting in the self-similar network. The extended Sierpiński networks are obtained by introducing a new vertex in a generalized Sierpiński network and attaching this vertex with the extreme vertices. Certain network invariants are used to find thermodynamic properties, physio-chemical properties, and biological activities of chemical compounds. These network invariants play a dynamic role in QSAR/QSPR study. In this paper, we discussed Zagreb indices and forgotten topological index for extended Sierpiński networks by using any base network H. Moreover, for the studied topological indices, we attained some bounds using different parameters i.e. order, size, maximum and minimum degrees of vertices in network H.

On the Connected Monophonic Number of a Graph

For a connected graph G of order at least two, a connected monophonic set of G is a monophonic set S such that the subgraph induced by S is connected. The minimum cardinality of a connected monophonic set of G is the connected monophonic number of G and is denoted by . The number of extreme vertices and cut-vertices of G is its extreme-cut order . A graph G is an extreme-cut connected monophonic graph if . Some interesting results on the extreme-cut connected monophonic graphs G are studied. For positive integers r, d and with r<d, there exists an extreme-cut connected monophonic graph G with monophonic radius r, monophonic diameter d and the connected monophonic number k. Also if p, d and k are positive integers such that and , then there exists an extreme-cut connected monophonic graph G of order p with monophonic diameter d and .

Physicochemical and thermophysical properties of CaO–TiO2–SiO2–Na3AlF6 system based electrode coating for AUSC power plant

The aim of this study is to investigate the physicochemical and thermophysical properties of CaO–TiO2–SiO2–Na3AlF6 based electrode coating developed for the welding of advanced ultra-supercritical (AUSC) thermal power plant components. The extreme vertices approach has been used to create twenty-six electrode coating compositions. Various physicochemical and thermophysical properties were characterized using experiments. The coating properties are essential in ensuring sound weld with desirable in-service performance. The developed coating's structural behavior was analyzed using Fourier transformation infrared spectroscopy (FTIR) and X-ray diffraction (XRD). In addition, regression analysis was carried out to evaluate the influence of coating constituents. Individual constituents and their interaction were found to have a prominent role in influencing the physicochemical and thermophysical properties.

Palm Olein Organogelation Using Mixtures of Soy Lecithin and Glyceryl Monostearate.

The present work investigated the interaction between soy lecithin (SL), glyceryl monostearate (GMS), and water in structuring palm olein (PO) to create an organogel having similar mechanical properties to commercial spread. Extreme vertices mixture design was used to optimize the composition of PO-based organogel. The resulting model showed a good fit to the predicted data with R2 ≥ 0.89. The optimum composition was 8% SL, 22% GMS, 28% water, and 42% PO (w/w) to produce a mean firmness of 1.91 N, spreadability of 15.28 N s−1, and oil binding capacity (OBC) of 83.83%. The OBC of optimized organogel was 10% higher than commercial spread product, and no significant difference was observed in the mechanical properties (p > 0.05). The microstructure, as well as the rheological and thermal properties of the optimized organogel were characterized. Fourier transform infrared analysis indicated that hydrogen bonding and van der Waals interactions were the key driving forces for organogelation. The mixture of SL and GMS favored the formation of β′ + β form crystals with a predominance of the β′ form. These results have important implications for the development of PO-based organogel as a potential fat replacer in the production of low-fat spread.

Quality assessment of baby wet wipes

A wet wipe is a commercial product made of a fibrous substrate impregnated with a lotion that often comes folded and individually wrapped for convenience. The present work relates to wet wipes’ composition to clean the baby’s body. Wet wipes were produced from two spunlace nonwoven fabrics consisting of polyester/viscose and a wetting solution. Objective performance evaluation was carried out to determine the efficiency of the wipes for manufacturing and end uses. The lotion formula comprising surfactants, a solubilizer, preservative compounds, perfumes, and mainly purified water is selected to deliver the intended benefits of a baby wet wipe. Besides, physical, mechanical characteristics, and moisture management parameters of the wet wipe fabrics were measured. Optimal lotion (oil–water emulsion) stirring conditions were illustrated using optical microscopy. Lotion foamability appears as an undesirable phenomenon upon the manufacturing of the wet wipe. A mixture design, an extreme vertices design, was used to study the influence of the compounds on the foam volume. The relative contribution of each compound in the lotion to generate bath foam was discussed. Because wet media are more effective than dry media for surface cleaning, the optimum wet pick-up ensuring the best wiping efficiency about of 83.2% was found to be about 3 g of lotion for 1 g of fabric. Assuming that a wipe sample could be performed in less than 3 min, it was also confirmed that the developed wipe remains effective with a moisture content of 242% and can be comparable with other commercial wipes.

Constrained vertex optimization and simulation of the unconfined compressive strength of geotextile reinforced soil for flexible pavement foundation construction

Extreme vertex design (EVD) provides an efficient approach to mixture experiment design whereby the factor level possesses multiple dependencies expressed through component constraints formulation. Consequently, the derived experimental points are within the center edges and vertices of the feasible constrained region. EVD was deployed for the modeling of the mechanical properties of the problematic clayey soil-geogrid blends. Geogrids are geosynthetic materials which possess an open mesh-like structure and are mostly used for soil stabilization. The geotextile materials present a geosynthetic and permeable layer to support the soil and foundation by improvement of its stiffness characteristics and at a cheaper cost to procure compared to other construction materials and possess unique light weight properties with greater strength improvement on the soil layer when used. Minitab 18 and Design Expert statistical software were utilized for the mixture design experiment computation; to fully explore the constrained region of the simplex, I-optimal designs with a special cubic design model were utilized to formulate the mixture component ratios at ten experimental runs. I-optimality and D-optimality of 0.39093 and 1747.474, respectively, were obtained with G-efficiency of 64.8%. The generated laboratory responses were taken together with the mixture ingredients' ratio and taken as the system database for the model development. Statistical influence and diagnostics tests carried out on the generated EVD model indicate a good correlation with the experimental results. Graphical and numerical optimizations were incorporated using a desirability functions that ranged from 0 to 1, which helped to arrive at the optimal combination of the mixture components. 0.2% of geogrid, 9.8% of water, and 90% of soil yielded the optimal solution with a response of 41.270 kN/m2 and a desirability score of 1.0. Model simulation was further carried out to test the model's applicability with the results compared with the actual results using student's t-test and analysis of variance. The statistical results showed p-value>.05 which indicates good correlation.

Artificial Intelligence Prediction Model for Swelling Potential of Soil and Quicklime Activated Rice Husk Ash Blend for Sustainable Construction

Artificial intelligence (AI) algorithms of adaptive neuro-fuzzy inference system or the adaptive network-based fuzzy inference system (ANFIS) has been deployed to predict the swelling potential (SP) of treated weak soil. The soil was treated with quicklime activated rice husk ash (QARHA) and the prediction efficiency was compared with the previous outcomes of this operation from literature. The need for effective utilization of construction materials to achieve sustainable designs and monitoring of the behavior of built environment is the motivation behind the deployment of artificial intelligence in geo-environmental research and field operations. The use of ANFIS is common in different fields of science and business to predict the best fits from several data points. The results of this modeling exercise conducted with 25 datasets from mixture experimental treatment of soft soil with QARHA has shown that ANFIS is a better tool compared to the individual algorithms of ANN and FL and even the other artificial intelligence tools like scheffe, ANOVA, regression and extreme vertices methods. With performance index of 88% and correlation of about 71% in the ANFIS testing and 17% and 99% respectively in the ANFIS training, ANFIS proved to be a more powerful tool in achieving a more sustainable material utilization in earthwork constructions, design and monitoring of geotechnical systems performance.