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Wayne Sharp

Researcher at University of Louisiana at Lafayette

Publications -  16
Citations -  288

Wayne Sharp is an academic researcher from University of Louisiana at Lafayette. The author has contributed to research in topics: Biogas & Anaerobic digestion. The author has an hindex of 4, co-authored 13 publications receiving 54 citations.

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Adsorption kinetic modeling using pseudo-first order and pseudo-second order rate laws: A review

TL;DR: In this paper, a new validation method was proposed and was then employed to re-examine previously published adsorption kinetic data to eliminate modeling biasness and eliminate model validation tools that cannot provide any kind of certainty on the validity of a model.
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A Review of Pretreatment Methods to Enhance Solids Reduction during Anaerobic Digestion of Municipal Wastewater Sludges and the Resulting Digester Performance: Implications to Future Urban Biorefineries

TL;DR: In this article, the authors present an assessment of various pretreatment methods to optimize the anaerobic digestion of waste sludges with a focus on maximizing both biosolids reduction and biogas quality.
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Microalgae Culturing To Produce Biobased Diesel Fuels: An Overview of the Basics, Challenges, and a Look toward a True Biorefinery Future

TL;DR: The concept has many positive aspects including positive aspects inclusive of be... as mentioned in this paper, and is envisioned by many experts to be one of the key future feedstocks for producing transportation fuels and other chemical products.
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Computational evaluation for effects of feedstock variations on the sensitivities of biochemical mechanism parameters in anaerobic digestion kinetic models

TL;DR: In this article, a computational approach for the exploration of the importance of biochemical mechanism parameters in anaerobic digestion models subjected to concentration variations of digestion feedstock components is presented, which consists of an algorithm integrating global sensitivity analysis (GSA), functional principal component analysis (FPCA), and rank-clustering techniques.
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A Methodology for Global Sensitivity Analysis of Activated Sludge Models: Case Study with Activated Sludge Model No. 3 (ASM3).

TL;DR: This work focused on the evaluation of the following key computational factors that may significantly influence the performance of the GSA-fPCA methodology: model parameter sampling range, model simulation period, basis functions system, and state of the system being modeled-batch or continuous activated sludge process.