Mixture experiments and their applications in welding flux design

Adeyeye, Ademola David; Oyawale, F. A.

doi:10.1590/s1678-58782008000400008

Cited by 24 publications

(29 citation statements)

References 27 publications

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“…Published literature suggests that factorial design is not suitable for welding flux formulation because welding flux is a mixture of ingredients and the final properties of the flux depend on the relative proportions of the ingredients in the mixture 11 . Experiments where the input factors are the ingredients/components of a mixture and the properties (response variables) are functions of the proportions of the ingredients are known as mixture experiment.…”

Section: Description Of the Combined Xvertd And Mp Methodologymentioning

confidence: 99%

“…Experimental optimization approach is therefore very slow and costly and as a result lags behind the development of new materials. The consequence is that rapid deployment of new materials is hampered 1,11 . In addition, the welding flux developed from such methods has a random character and often far from optimal because the best among the experimental flux formulations is usually selected as the optimum flux for the given metal under the given welding conditions 2,12 .…”

Section: Introductionmentioning

confidence: 99%

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Weld-metal property optimization from flux ingredients through mixture experiments and mathematical programming approach

Adeyeye

Oyawale

2009

Mat. Res.

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This paper presents a new methodology for weld-metal properties optimization from welding flux ingredients. The methodology integrates statistical design of mixture experiment with mathematical programming optimization technique. The mixture experiment is responsible for the modeling of the weld-metal properties as a function of welding flux levels while mathematical programming optimizes the model. Data and confirmed models from the literature were used to perform optimization on the responses. The maximum values possible with the prevailing conditions for acicular ferrite, charpy impact toughness and silicon transfer are 51.2%, 29 J and 0.231% respectively while the minimum oxygen content possible is 249 ppm. The new methodology is able to eliminate the limitations associated with the traditional experimental optimization methodology for flux formulation.

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Section: Description Of the Combined Xvertd And Mp Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Weld-metal property optimization from flux ingredients through mixture experiments and mathematical programming approach

Adeyeye

Oyawale

2009

Mat. Res.

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“…These fluxes were prepared by varying the composition of four flux constituents CaO, Al 2 O 3 , CaF 2 and MgO and keeping SiO 2 , TiO 2 , MnO and bentonite as constant (Table 1). The most suitable method for constrained mixtures design, extreme vertices design first suggested by Anderson and McLean, 16 Cornell 17 and Adeyeye and Oyawale 18 was used for flux formulation. Design of experiment (DOE) technique mentioned here was also used previously by Jindal et al 19 with same limits of flux constituents and same design table 17 to determine mechanical properties and H 2 content.…”

Section: Plan Of Experimentationmentioning

confidence: 99%

Prediction of element transfer due to flux and optimization of chemical composition and mechanical properties in high-strength low-alloy steel weld

Jindal

Chhibber

Mehta

2014

Proceedings of the Institution of Mechanical Engineers, Part B:

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The transfer of elements C, Si, Mn, P and S from slag into the weld metal or from weld metal into the slag and microhardness has been studied using formulated fluxes. The fluxes have been formulated using extreme vertices design with an aim to develop mathematical models for change in element content and mechanical properties versus flux constituents for submerged arc welding of high-strength low-alloy steel. It is found that CaO is the most significant flux constituent and Al2O3 is the second most significant constituent among individual mixtures. CaO·MgO and CaO·Al2O3 among binary mixtures have significant effect on element transfer and microhardness. Developed mathematical models have been checked for adequacy using t-test and analysis of variance (F-test). Flux mixtures’ composition has been provided for optimum chemical composition and mechanical properties. One of the optimum flux mixture with composition, CaO 11.61, Al2O3 12.33, CaF2 15.00 and MgO 39.06, would be providing desirable chemical composition and mechanical properties.

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“…In the standard mixture designs, the proportions of the ingredients can vary between 0 and 1 and must sum up to unity. (Cornell, 2002;Adeyeye, 2008).…”

Section: Experimental Design and Statistical Analysismentioning

confidence: 99%

Applying design of experiments (DOE) to flavonoid extraction from Passiflora alata and P. edulis

Noriega

Mafud

Souza

et al. 2012

Rev. bras. farmacogn.

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Abstract:The Passifloraceae family is extensively used in native Brazilian folk medicine to treat a wide variety of diseases. The problem of flavonoid extraction from Passiflora was treated by application of design of experiments (DOE), as an experiment with mixture including one categorical process variable. The components of the binary mixture were: ethanol (component A) and water (component B); the categorical process variable: extraction method (factor C) was varied at two levels: (+1) maceration and (-1) percolation. ANOVA suggested a cubic model for P. edulis extraction and a quadratic model for P. alata. These results indicate that the proportion of components A and B in the mixture is the main factor involved in significantly increasing flavonoid extraction. In regard to the extraction methods, no important differences were observed, which indicates that these two traditional extraction methods could be effectively used to extract flavonoids from both medicinal plants. The evaluation of antioxidant activity of the extract by ORAC method showed that P. edulis displays twice as much antioxidant activity as P. alata. Considering that maceration is a simple, rapid and environmentally friendly extraction method, in this study, the optimized conditions for flavonoid extraction from these Passiflora species is maceration with 75% ethanol for P. edulis and 50% ethanol for P. alata.

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Mixture experiments and their applications in welding flux design

Cited by 24 publications

References 27 publications

Weld-metal property optimization from flux ingredients through mixture experiments and mathematical programming approach

Weld-metal property optimization from flux ingredients through mixture experiments and mathematical programming approach

Prediction of element transfer due to flux and optimization of chemical composition and mechanical properties in high-strength low-alloy steel weld

Applying design of experiments (DOE) to flavonoid extraction from Passiflora alata and P. edulis

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