کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1732130 | 1521458 | 2015 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Orthogonal test design to optimize products and to characterize heavy oil via biomass hydrothermal treatment
ترجمه فارسی عنوان
طراحی تست ارتوگنال برای بهینه سازی محصولات و برای توصیف روغن سنگین از طریق درمان گرمابی زیست توده
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کلمات کلیدی
ارتودنسی، هیدروترمال نی کتان، روغن سنگین،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی (عمومی)
چکیده انگلیسی
The key parameters for biomass hydrothermal treatment were optimized for product distribution in this study on the basis of a L16 (45) orthogonal experiment design. Results showed that biomass species, particle size, and hydrothermal temperature significantly affected heavy oil yield. By contrast, the effect of biomass concentration was negligible. The maximum heavy oil yield was 28.00 wt.% at the optimal condition (biomass species, pine sawdust; 250 °C; 80-150 mesh; 15 min; 10 g/110 g). In addition, cotton straw yielded the most liquid in the agricultural straws, although ash content was low. The influences of temperature, residence time, catalysts, and the size of cotton straw particles on product distribution were investigated as well. The results of analysis with GC-MS (gas chromatography-mass spectroscopy) indicated that the liquid product contained organic components, namely, acids, esters, aldehydes, ketones, and phenols. Among these components, acids, esters, phenols, and their derivatives were dominant. The addition of catalysts increased oil yield and also affected the oil components. Specifically, acids and ketones were reduced and the pH value of the oil increased. As a result, its quality improved to a certain extent. This research provides a reference for biomass hydrothermal treatment.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy - Volume 88, August 2015, Pages 139-148
Journal: Energy - Volume 88, August 2015, Pages 139-148
نویسندگان
Ying Gao, Bo Yu, Xianhua Wang, Qiaoxia Yuan, Haiping Yang, Hanping Chen, Shihong Zhang,