Chemical Engineering Numerical Analysis with R: Peng-Robinson Equation of State
Journal Title: Journal of Data Science and Intelligent Systems - Year 2023, Vol 1, Issue 1
Abstract
Likely, many text on MATLAB, C++, FORTRAN and Python programming languages exist in chemical engineering libraries, discussing their applications for chemical engineering numerical analysis. R programming language, which has been in existence for more than 40 years is just evolving as a language of choice for data analytics in science and engineering. Here, it is shown that, numerical analysis with equations of state (EOS), especially the Peng-Robinson EOS, typically taught in undergraduate chemical engineering introductory courses can be solved with a developed or existing R source codes. Out of several other mathematical methods, including Fixed-point iteration, Regula-Falsi, Bisection and their modified/hybrid methods recently developed, only Secant and Newton’s method algorithm were followed to solve a sample problem by writing an R program. Although sufficient, in-depth study of the R language using some recommended manuals in this work can be a guide in implementing a solution with R for other numerical methods, for the same problem, as well as several other existing analytical and statistical chemical engineering problems out there.
Authors and Affiliations
Abdulhalim Musa Abubakar, Ahmed Elshahhat, Simisani Ndaba, Adegoke Taiwo Mobolaji, Balasubramanian Thiagarajan, E. M. Mansour
Random Forest Ensemble Machine Learning Model for Early Detection and Prediction of Weight Category
The number of insurgents in our nation today is significantly rising each day, and the majority of those affected are living as internally displaced persons (IDP) in various IDP camps. These people experience a variety o...
The Evolving Landscape of Oil and Gas Chemicals: Convergence of Artificial Intelligence and Chemical-Enhanced Oil Recovery in the Energy Transition Toward Sustainable Energy Systems and Net-Zero Emissions
Chemical-enhanced oil recovery (EOR) is a field of study that can gain significantly from artificial intelligence (AI), addressing uncertainties such as mobility control, interfacial tension reduction, wettability altera...
Identification of Damage in a Wind Turbine Blade Using Mechanical Measurements and Artificial Neural Networks
Due to the stochastic nature of environmental loadings, a lot of interest is paid in the discovery of possible damages to the involved equipment in modern industry. In wind turbines' blades, the development of a smart st...
3D-STCNN: Spatiotemporal Convolutional Neural Network Based on EEG 3D Features for Detecting Driving Fatigue
Fatigue driving has become one of the main causes of traffic accidents, and driving fatigue detection based on electroencephalogram (EEG) can effectively evaluate the driver's mental state and avoid the occurrence of tra...
Feature Selection, Clustering, and IoMT on Biomedical Engineering for COVID-19 Pandemic: A Comprehensive Review
In this era, feature clustering is a prominent technique in data mining. Feature clustering has also huge applications in biomedical research for multiple purposes including grouping, feature reduction, and many more. Th...