Analysis of pelletizing from corn cob waste.
M T Miranda1, F J Sepúlveda1, J I Arranz1
1Industrial Engineering School, University of Extremadura, Av. Elvas s/n, Badajoz 06006, Spain.
Journal of Environmental Management
|September 22, 2018
Summary
Corn cob waste can be pelletized into high-quality biofuels for domestic use. This study analyzed the pelletizing process, finding satisfactory fuel properties and improved productivity with increased energy consumption.
Area of Science:
- Agricultural Science
- Biomass Energy
- Materials Science
Background:
- The growing biomass market necessitates exploring new biofuel sources.
- Agricultural wastes like corn cobs show potential but require processing for domestic use.
- Densification is crucial for enhancing the fuel quality of corn cob waste.
Purpose of the Study:
- To conduct a technical and energy analysis of corn cob waste pelletizing.
- To investigate the relationships between moisture, bulk density, and mechanical durability.
- To assess the influence of these variables on energy consumption and productivity.
Main Methods:
- Pelletizing corn cob waste in a semi-industrial pelletizer.
- Analyzing technical parameters like moisture, bulk density, and mechanical durability.
- Evaluating the energy consumption and productivity of the pelletization process.
Main Results:
- Manufactured corn cob pellets met most quality specifications.
- Pellets exhibited higher mechanical durability compared to similar products.
- Increased production led to higher energy consumption, improving the productivity ratio.
Conclusions:
- Corn cob waste can be successfully pelletized into high-quality biofuels.
- The pelletizing process is technically and energetically viable for domestic fuel applications.
- Optimizing the process can lead to enhanced fuel quality and efficient production.
More Related Videos
Related Concept Videos
Qualitative Analysis
24.4K
For solutions containing mixtures of different cations, the identity of each cation can be determined by qualitative analysis. This technique involves a series of selective precipitations with different chemical reagents, each reaction producing a characteristic precipitate for a specific group of cations. Metal ions within a group are further separated by varying the pH, heating the mixture to redissolve a precipitate, or adding other reagents to form complex ions.
For instance, group IV...
For instance, group IV...
24.4K
Dimensional Analysis
64.7K
Dimensional analysis, also known as the factor label method, is a versatile approach for mathematical operations. The main principle behind this approach is: the units of quantities must be subjected to the same mathematical operations as their associated numbers. This method can be applied to computations ranging from simple unit conversions to more complex and multi-step calculations involving several different quantities and their units.
Conversion Factors and Dimensional Analysis
The unit...
Conversion Factors and Dimensional Analysis
The unit...
64.7K
Dimensional Analysis
679
Dimensional analysis is a valuable technique in fluid mechanics for simplifying complex problems by reducing them into dimensionless groups. These groups capture the essential relationships between the variables involved, allowing researchers and engineers to analyze fluid flow without dealing with each variable individually. This approach reduces the number of independent variables, allowing for easier analysis and better understanding of physical phenomena.
In fluid mechanics, dimensional...
In fluid mechanics, dimensional...
679
Dimensional Analysis
2.2K
Dimensional analysis is a powerful tool that is used in physics and engineering to understand and predict the behavior of physical systems. The basic idea behind dimensional analysis is to express physical quantities in terms of fundamental dimensions such as the mass, length, and time. Derived dimensions like the velocity, acceleration, and force are derived from the combinations of these fundamental dimensions.
Dimensional analysis allows us to analyze and compare physical quantities on a...
Dimensional analysis allows us to analyze and compare physical quantities on a...
2.2K
Pedigree Analysis
89.5K
Overview
89.5K
Epistasis Analysis
5.8K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
5.8K


