scholarly journals Optimization of Acid and Steam Explosion Pretreatment of Cogon Grass for Improved Cellulose Enzymatic Saccharification

2019 ◽  
Vol 21 (2) ◽  
pp. 143
Author(s):  
J.P. Rivadeneira ◽  
M.E. Flavier ◽  
F.R.P. Nayve, Jr.
Keyword(s):  
Optimum Condition ◽  
Response Surface ◽  
Experimental Verification ◽  
Steam Explosion ◽  
Colorimetric Method ◽  
Enzymatic Saccharification ◽  
Reducing Sugar ◽  
Surface Model ◽  
Solid Liquid ◽  
Explosion Condition

Acid-impregnation and its combination with steam explosion were evaluated and optimized using Response Surface Methodology. At 10% solid-liquid ratio, cogon was impregnated with diluted H2SO4 solution (0 to 3%, w/w) at different ranges of temperature (40 to 120 °C) and varied time (0 to 130 min). Impregnated samples were then subjected to enzymatic saccharification using 60 FPU/g Accelerase 1500™. After enzymatic saccharification, the concentration of reducing sugar released was measured using Dinitrosalicylic (DNS) Colorimetric Method. Based on the results, Response Surface Model (RSM) showed that the optimum condition, predicting 7.18% Reducing Sugar Yield (RSY), was impregnation of cogon using 1.9% H2SO4 at 91.8 °C for 56 min. Experimental verification of optimum condition, done in triplicates, showed 6.35 + 0.05% RSY. Acid-impregnated cogon was subjected to steam explosion to improve saccharifiability. Factors varied were temperature (137 to 222 °C) and exposure time (17 to 582 s). Steam-exploded samples were saccharified and RSY was determined. RSM indicated that the best steam explosion condition, predicting 7.91% RSY, was 179 °C and 500 s. Experimental verification of optimum condition showed 8.78 + 0.02% RSY. Using RSY as basis, steam explosion improved saccharifiability of H2SO4-impregnated cogon by 38%, thus, increasing production of reducing sugars for potential bioethanol production.

Optimization of Ultrasound Extraction of Nitrite Nitrogen in Sediment by Response Surface Methodology

2014 ◽  
Vol 955-959 ◽  
pp. 1466-1470 ◽  
Author(s):  
Dan Liu ◽  
Fang Yu ◽  
Wei Tan ◽  
Gui Zhen Li ◽  
Min Yang ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Optimum Condition ◽  
Response Surface ◽  
Process Condition ◽  
Extraction Time ◽  
Ultrasonic Power ◽  
Liquid Ratio ◽  
Ultrasound Extraction ◽  
Nitrite Nitrogen ◽  
Solid Liquid

Response surface methodology based on single factors was used to optimize the process condition for extraction of nitrite nitrogen in sediment . The results indicated that the extraction amount of nitrite nitrogen was 9.5μg /g under the optimum condition of extraction time of 44min, ultrasonic power of 280W, solid-liquid ratio of 1:19,which was closed to the predicated yield of 9.3μg/g. The process can be used for the extraction of nitrite nitrogen in sediments.

scholarly journals Parametric Analysis on Landing Gear Strut Friction of Light Aircraft for Touchdown Performance

2021 ◽  
Vol 11 (12) ◽  
pp. 5445
Author(s):  
Shengyong Gan ◽  
Xingbo Fang ◽  
Xiaohui Wei
Keyword(s):  
Response Surface ◽  
Energy Absorption ◽  
Landing Gear ◽  
Surface Model ◽  
Absorption Properties ◽  
Surface Method ◽  
Design Variables ◽  
Landing Impact ◽  
Landing Response ◽  
Parametric Studies

The aim of this paper is to obtain the strut friction–touchdown performance relation for designing the parameters involving the strut friction of the landing gear in a light aircraft. The numerical model of the landing gear is validated by drop test of single half-axle landing gear, which is used to obtain the energy absorption properties of strut friction in the landing process. Parametric studies are conducted using the response surface method. Based on the design of the experiment results and response surface functions, the sensitivity analysis of the design variables is implemented. Furthermore, a multi-objective optimization is carried out for good touchdown performance. The results show that the proportion of energy absorption of friction load accounts for more than 35% of the total landing impact energy. The response surface model characterizes well for the landing response, with a minimum fitting accuracy of 99.52%. The most sensitive variables for the four landing responses are the lower bearing width and the wheel moment of inertia. Moreover, the max overloading of sprung mass in LC-1 decreases by 4.84% after design optimization, which illustrates that the method of analysis and optimization on the strut friction of landing gear is efficient for improving the aircraft touchdown performance.

scholarly journals Optimization of oxalic acid pre-treatment and enzymatic saccharification in Typha latifolia for production of reducing sugar

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Sunil Kodishetty Ramaiah ◽  
Girisha Shringala Thimappa ◽  
Lokesh Kyathasandra Nataraj ◽  
Proteek Dasgupta
Keyword(s):  
Oxalic Acid ◽  
Enzymatic Saccharification ◽  
Typha Latifolia ◽  
Reducing Sugar ◽  
Pre Treatment

An Adaptive Response Surface Method Using Bayesian Metric and Model Bias Correction Function

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Lei Shi ◽  
Ren-Jye Yang ◽  
Ping Zhu
Keyword(s):  
Response Surface ◽  
Bias Correction ◽  
Adaptive Response ◽  
Large Scale ◽  
Correction Method ◽  
Data Uncertainty ◽  
Correction Function ◽  
Surface Model ◽  
Model Bias ◽  
Adaptive Response Surface Method

The Bayesian metric was used to select the best available response surface in the literature. One of the major drawbacks of this method is the lack of a rigorous method to quantify data uncertainty, which is required as an input. In addition, the accuracy of any response surface is inherently unpredictable. This paper employs the Gaussian process based model bias correction method to quantify the data uncertainty and subsequently improve the accuracy of a response surface model. An adaptive response surface updating algorithm is then proposed for a large-scale problem to select the best response surface. The proposed methodology is demonstrated by a mathematical example and then applied to a vehicle design problem.

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