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34. Experimental and Statistical Analysis of Iron Powder for Green Heat Production.

Author

Sohrabi, Mohammadmahdi, Ghobadian, Barat, Najafi, Gholamhassan, Prasidha, Willie, Baigmohammadi, Mohammadreza, and de Goey, Philip

Abstract

In the current investigation, a novel methodology was employed to assess iron powder as a recyclable and sustainable energy carrier. Concurrently, an examination of the modeling of iron powder ignition and the ensuing heat output from the burner was undertaken. The flame temperature was determined by examining the light intensity emitted by the particles as they melted, which is directly related to the particle's cross-sectional area. An account of the characterization of the experimental procedure, validation, and calibration is presented. Through measurements, distinct one-to-one correlations have been established between the scales of flame combustion and the temperatures of particles of varying sizes of iron. Additionally, a theoretical model for the combustion of expanding particles, particularly iron, within the diffusion-limited regime has been rigorously developed. This model delves into the spectra acquired from particle flames within the burner, utilizing Partial Least Squares Regression (PLSR) and Principal Component Analysis (PCA). This study investigates the use of optical fiber spectroscopy to predict flame temperature and assess iron powder size. The aim was to investigate how different sizes of iron powder affect flame temperature and to create calibration models for non-destructive prediction. The study shows that smaller particles had an average temperature of 1381 °C while larger particles reach up to 1842 °C, demonstrating the significant impact of particle size on combustion efficiency. The results were confirmed using advanced statistical methods, including PLSR and PCA, with PCA effectively differentiating between particle sizes and PLSR achieving an R2 value of 0.90 for the 30 µm particles. [ABSTRACT FROM AUTHOR]

Published
2024
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47. Application of the Box-Behnken Design for Optimizing Biodiesel Output from Castor Oil: Analysis and Characterization.

Author

Rezaei, Sheyda, Mohtasebi, Seyed Saeid, Ghobadian, Barat, Nouri, Behzad, and Namdari, Majid

Subjects
CASTOR oil, KINEMATIC viscosity, POTASSIUM hydroxide, GAS chromatography, REGRESSION analysis
Abstract

This study specifically examines the process of producing and analyzing biodiesel made from castor oil using base-catalyzed transesterification. The catalyst used in this process is potassium hydroxide (KOH), and the methanol (CH3OH) used has a purity of 99.9%. The biodiesel obtained was analyzed extensively to assess its quality. The characterization techniques employed were Gas Chromatography (GC) for compositional analysis, Flash Point measurement for safety assessment, Kinematic Viscosity evaluation for flow properties, and Density determination for mass-volume relationships. To perform a statistical analysis, the Response Surface Method (RSM) was employed to determine the optimal conditions that would yield the highest rate of biodiesel production among the potential solutions. This study focused on three key variables affecting the transesterification process: ultrasonic duty cycle (using a 24 kHz ultrasonic method varying the duty cycle from 20% to 100%), ultrasonic amplitude (varying from 20% to 100%), and reaction time (spanning from 10 to 15 minutes). This investigation achieved a biodiesel yield of 88.38% using a 60% ultrasonic amplitude, a single ultrasonic cycle, and a 15-minute reaction time. The regression model developed can be used to predict biodiesel's percentage conversion. [ABSTRACT FROM AUTHOR]

Published
2024
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