Second-Order Polynomial Model to Solve the Least-Cost Lumber Grade Mix Problem

2010 ◽  
Vol 60 (1) ◽  
pp. 69-77 ◽  
Author(s):  
Urs Buehlmann ◽  
Xiaoqiu Zuo ◽  
R. Edward Thomas
Keyword(s):  
Second Order ◽  
Polynomial Model ◽  
Order Polynomial ◽  
Lumber Grade

An Extended Second Order Polynomial Model for Hydraulic Fluid Density

2013 ◽  
Author(s):  
J.-P. Karjalainen ◽  
R. Karjalainen ◽  
K. Huhtala
Keyword(s):  
Power Transmission ◽  
Second Order ◽  
Polynomial Model ◽  
Hydraulic Fluid ◽  
Wide Range ◽  
Fuel Oils ◽  
Hydraulic Fluids ◽  
Order Polynomial ◽  
Temperature Ranges ◽  
Fluid Characteristics

In this paper, a second order polynomial model for predicting the pressure-temperature behaviour of the density of any hydraulic fluid is presented. The model is an extension of the previously published model by the same authors for more moderate operating temperatures. Nevertheless, for a user the extension will not add any more complexity to the model. Even at a wider operating range, the density model can still always be parameterized without any unknown variables, once the standard fluid characteristics are available. It is shown that compared to the measured values the maximum modelling error is well within 1% at the studied pressure range of up to 1500 bar, and at the studied temperature ranges overall covering from +20 to +130°C, with all the studied fluids. This study includes 10 highly different hydraulic fluids used in various fluid power applications as power transmission fluids or fuel oils. The studied fluids have a density range from 827 to 997.2 kg/m3, and an ISO VG range from 2.6 to 1187. Also the studied base fluids cover a wide range. Moreover, the studied fluids contain different additives or not even additives at all (crude oils). Neither the base fluid nor the additives will be discovered to affect the received modelling accuracy.

Optimized Formulation of APN Toothpaste with Biochemical Materials Using Response Surface Methodology

2013 ◽  
Vol 676 ◽  
pp. 108-113
Author(s):  
Ting Kong ◽  
Chao Yan Zhang ◽  
Bin Bao ◽  
Long Sha ◽  
Zhen Wang ◽  
...  
Keyword(s):  
Experimental Data ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Panax Notoginseng ◽  
Second Order ◽  
Polynomial Model ◽  
Composite Score ◽  
Optimum Formulation ◽  
Order Polynomial ◽  
Addition Amount

Response surface methodology(RSM) was used to optimize the formulation of one toothpaste with aglycone extracted from Panax notoginseng(APN). Biochemical materials are important components in toothpastes. The addition amount of APN, thickener, different ratios of humectant and friction agent were selected as three factors for the design. Our results showed that the experimental data could be adequately fitted into a second-order polynomial model. Addition amount of thickener and humectant : friction agent had a significant effect on the composite score. The optimum formulation for preparing APN toothpaste was predicted to be: APN, 0.12%; thickener, 1.58%; humectant : friction agent, 1.01.

scholarly journals Using a Second-Order Polynomial Model to Determine The Optimum Vinasse/Grape Marc Ratio For In-Vessel Composting

2004 ◽  
Vol 12 (3) ◽  
pp. 273-279 ◽  
Author(s):  
M.J. Díaz ◽  
E. Madejón ◽  
F. Cabrera ◽  
L. Jiménez ◽  
M. De Bertoldi
Keyword(s):  
Second Order ◽  
Polynomial Model ◽  
Grape Marc ◽  
Order Polynomial

scholarly journals Accuracy evaluation of 2D geometric correction models: Iraq as a case study

2018 ◽  
Vol 162 ◽  
pp. 03015
Author(s):  
Abdul Razzak Ziboon ◽  
Israa Mohammed
Keyword(s):  
Mathematical Models ◽  
Two Dimensions ◽  
Second Order ◽  
Polynomial Model ◽  
Accuracy Evaluation ◽  
Geometric Correction ◽  
Flat Area ◽  
First Order ◽  
High Resolution Satellite Images ◽  
Order Polynomial

One of the most important preprocessing methods for remote sensing data and geometrical distrortion is the geometric correction. In this research, several mathematical models were used in two dimensions case and were compared to each other to determine the accuracy of each mathematical model when used in three different regions with different terrains. Three high-resolution satellite images of the QuickBird satellite (a flat area, a hilly area and a mountain area) of Iraq have been used in this work. The flat area is chosen in Baghdad, while the hilly and mountain areas are chosen in Irbil in the north of Iraq. In this research, the mathematical models used are the first and second order polynomials, as well as the projective transform. All of these models were applied to all different topographic areas and their accuracy was assessed based on the Matlab program. The results of the models in the three areas studied indicate that the best precision is achieved with the second order polynomial model, while the worst precision is obtained with the first order polynomial model. On the other hand, the precision of the projective transformation is almost similar to the precision of the first order polynomial.

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