Trade-off prediction and circuit performance optimization using a second-order model

1992 ◽  
Vol 20 (3) ◽  
pp. 299-307
Author(s):  
Xiao Xiangming ◽  
Robert Spence
Keyword(s):  
Performance Optimization ◽  
Second Order ◽  
Order Model ◽  
Trade Off ◽  
Circuit Performance ◽  
Second Order Model

scholarly journals Performance Optimization, Prediction, and Adequacy by Response Surfaces Methodology with Allusion to DRF Technique

ISRN Textiles ◽  
2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Lokesh Shukla ◽  
Anita Nishkam
Keyword(s):  
Performance Optimization ◽  
Fiber Length ◽  
Response Surfaces ◽  
Second Order ◽  
Polynomial Model ◽  
Knitted Fabric ◽  
Order Model ◽  
Strand Spacing ◽  
Fabric Weight ◽  
Second Order Model

The RSM introduces statistically designed experiments for the purpose of making inferences from data. The second-order model is the most frequently used approximating polynomial model in RSM. The most common designs for the second-order model are the 3k factorial, Doehlert, Box-Behnken, and CCD. In this Box and Behnken design of three variables is selected as a representative of RSM and 70 : 30 polyester-wool DRF yarn knitted fabrics samples as a process representative. The survey reveals that second-order model is the most frequently used approximating polynomial model in RSM. The Box-Behnken is the most suited design for optimization and prediction of data in textile manufacturing and this model is well-suited for DRF technique yarn knitted fabric. The trend was as higher wool fiber length shows higher fabric weight, abrasion, and bursting strength, correlation of TM was not visible; however, role of strands spacing is found dominant in comparison to other variables; at 14 mm spacing it shows optimum behaviors. The optimum values were weight (gms/mt2) 206 at length 75 mm, TM 2.5 and 14 mm spacing, abrasion (cycles) 1325 at length 70 mm, TM 2.25 and 14 mm spacing, bursting (kg/cm2) 14.35 at length 70 mm, and TM 2.00 and 18 mm spacing. A selected variables, fiber length, TM, and strand spacing, have substantial influence. The adequacies of response surface equations are very high. The line trends of knitted fabric basic characteristics were almost the same for actual and predicted models. The difference (%) was in range of 1.21 to −1.45, 2.01 to −7.26, and 17.84 to −6.61, the accuracy (%) was in range of 101.45 to 98.79, 107.27 to 97.99, and 106.61 to 82.16, and the Discrepancy Factor (R-Factor) was noted to be 0.016, 0.002, and 0.229 for weight, abrasion, and bursting, respectively, between actual and predicted data. The L-estimation factors for actual and predicted data were that (i) the ratio were in range of 1.01 to 0.99, 1.02 to 0.93, and 1.22 to 0.94 for weight, abrasion, and bursting, respectively, (ii) the multiple-ratio was in range of 1.26 to 0.86, (iii) the ratio product was in range of 1.22 to 0.92, and (iv) the toting ratio was in range of 1.02 to 0.94.

Adsorption Kinetics of Pb2+ Ions Using Chitosan Nanoparticles

2013 ◽  
Vol 367 ◽  
pp. 45-49
Author(s):  
Ying Hong ◽  
Ze Hui Zhong ◽  
You Shi Liu
Keyword(s):  
Adsorption Kinetics ◽  
Chitosan Nanoparticles ◽  
Second Order ◽  
Isotherm Model ◽  
Order Model ◽  
Adsorption Characteristics ◽  
Pseudo Second Order ◽  
Kinetics Of ◽  
Second Order Model

Chitosan nanoparticles were prepared by crosslinkingusing TPP. SEM showed that chitosan nanoparticles were successfully obtained.The adsorption characteristics of chitosan nanoparticles were evaluated. Theresults demonstrated that chitosan nanoparticles were suitable for adsorbent toremoval Pb2+. The parameters for the adsorption of Pb2+by chitosan nanoparticles were also determined. It was shown that chitosannanoparticles were fit for Langmuir’s isotherm model and that the adsorptionkinetics of Pb2+ described by the pseudo-second-order model could bebest.

Polyaniline/ZnO nanocomposites for the removal of methyl orange dye from waste water

2018 ◽  
Vol 32 (19) ◽  
pp. 1840085 ◽  
Author(s):  
Neha V. Nerkar ◽  
Subhash B. Kondawar ◽  
Snehal Kargirwar Brahme ◽  
Yun Hae Kim
Keyword(s):  
Waste Water ◽  
Methyl Orange ◽  
Adsorption Mechanism ◽  
Second Order ◽  
Pure Pani ◽  
Time Interval ◽  
Order Model ◽  
Vis Spectroscopy ◽  
Pseudo Second Order ◽  
Second Order Model

In this paper, we report the safe removal of methyl orange (MO) dye from aqueous solution using chemical interaction of dye molecule with polyaniline/zinc oxide (PANI/ZnO) nanocomposite. PANI/ZnO nanocomposite has been prepared by in situ polymerization. PANI/ZnO nanocomposite was found to be the best promising candidate for adsorption of dyes due to more porosities compared to that of pure PANI. In the present investigation, PANI/ZnO nanocomposite was mixed in a solution of MO dye and used for adsorption process. Color removal was studied using UV-Vis spectroscopy and the spectra were recorded for specific time interval and validation of kinetic model has been applied. Absorbance of PANI/ZnO nanocomposite was found to be increased as compared to that of pure ZnO nanoparticles and pure PANI due to synergistic effect. Comparatively, the removal of dye was also found to be more by using PANI/ZnO nanocomposites. In order to evaluate kinetic mechanism the pseudo-first-order model, pseudo-second-order model and intraparticle diffusion models were verified by the linear equation analysis. Adsorption mechanism of pseudo-second-order model was systematically explained for removal of dye using PANI/ZnO nanocomposite. The results clearly demonstrated that the adsorption mechanism gives very novel and green method of removal of hazardous dyes from waste water.

scholarly journals Validating a second-order model for oil and gas projects’ investment climate scale

2017 ◽  
Vol 11 (1) ◽  
pp. 65-79 ◽  
Author(s):  
Abdulsalam Mas’ud ◽  
Nor Aziah Abd Manaf ◽  
Natrah Saad
Keyword(s):  
Goodness Of Fit ◽  
Oil And Gas ◽  
Second Order ◽  
Fit Indices ◽  
Investment Climate ◽  
Order Model ◽  
Content Type ◽  
Latent Construct ◽  
Climate Scale ◽  
Second Order Model

Purpose The investment climate is one of the key factors considered by foreign investors while deciding their investment destination. This paper aims to attempt at validating the second-order model of oil and gas projects’ investment climate. Examination of the relationship between the dimensions of oil and gas projects’ investment climate; strategy, participants/operating environment and risk/return; and the overall latent construct was conducted. The study also evaluates the goodness of fit of the second-order model using relevant fit indices. Design/methodology/approach Oil and gas experts in Malaysian marginal oil fields subsector were deployed, through whom responses were collected that formed the data set used in the analysis. Then, the data were used for confirmatory factor analysis, evaluation of the second-order model through path analysis and for model fit evaluation. Findings The finding revealed that the second-order model of oil and gas projects’ investment climate is valid and reliable. It also revealed that all the three dimensions, strategy, participants/operating environment and risk/return, have significant effects on the formation of the oil and gas projects’ investment climate. Finally, the goodness of fit of the second-order model satisfied the relevant fit indices. Research limitations/implications The findings present valuable insights to policymakers on the extent of the influence each of the dimensions has on the overall latent construct. The validity and reliability analysis suggests the measurements of the second-order model of oil and gas projects’ investment climate construct, and its dimensions are valid, reliable and fit for future empirical research. Thus, it calls for replication in other oil and gas settings. Originality/value The findings from the results of this study are pioneering. Extant literature falls short in attempting the validation of the second-order oil and gas projects’ investment climate scale, as well as relating each of the dimensions with the overall latent construct.

Sign in / Sign up

Export Citation Format

Share Document