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Dive into the research topics where Neal Yancey is active.

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Featured researches published by Neal Yancey.


Biofuels | 2013

Impact of mixed feedstocks and feedstock densification on ionic liquid pretreatment efficiency

Jian Shi; Vicki S. Thompson; Neal Yancey; Vitalie Stavila; Blake A. Simmons; Seema Singh

Background: Lignocellulosic biorefineries must be able to efficiently process the regional feedstocks that are available at cost-competitive prices year round. These feedstocks typically have low energy densities and vary significantly in composition. One potential solution to these issues is blending and/or densifying the feedstocks in order to create a uniform feedstock. Results & discussion: We have mixed four feedstocks – switchgrass, lodgepole pine, corn stover and eucalyptus – in flour and pellet form, and processed them using the ionic liquid 1-ethyl-3-methylimidazolium acetate. Sugar yields from both the mixed flour and pelletized feedstocks reach 90% within 24 h of saccharification. Conclusion: Mixed feedstocks, in either flour or pellet form, are efficiently processed using this pretreatment process, and demonstrate that this approach has significant potential.


2011 ASABE Annual International Meeting,Louisville, Kentucky,08/07/2011,08/10/2011 | 2011

A Review on Biomass Classification and Composition, Co-firing Issues and Pretreatment Methods

Jaya Shankar Tumuluru; Christopher T. Wright; Richard D. Boardman; Neal Yancey; Shahab Sokhansanj

Presently, around the globe, there is a significant interest in using biomass for power generation as power generation from coal continues to raise environmental concerns. Using just biomass for power generation can bring a lot of environmental benefits. However the constraints of using biomass alone can include high investments costs for biomass feed systems and also uncertainty in the security of the feedstock supply due to seasonal variations, and in most countries, limited infrastructure for biomass supply. Alternatively, co-firing biomass along with coal offers advantages like a) reducing the issues related to biomass quality and buffers the system when there is insufficient feedstock quantity and b) costs of adapting the existing coal power plants will be lower than building new systems dedicated only to biomass. However, with the above said advantages there exists some technical constrains including low heating and energy density values, low bulk density, lower grindability index, higher moisture and ash content. In order to successfully cofire biomass with coal, biomass feedstock specifications need to be established to direct pretreatment options that may include increasing the energy density, bulk density, stability during storage and grindability. Impacts on particle transport systems, flame stability, pollutant formation and boiler tube fouling/corrosion must also be minimized by setting feedstock specifications including composition and blend ratios if necessary. Some of these limitations can be overcome by using preprocessing methods. This paper discusses the impact of feedstock preprocessing methods like sizing, baling, pelletizing, briquetting, washing/leaching, torrefaction, torrefaction and pelletization and steam explosion in attainment of optimum feedstock characteristics to successfully cofire biomass with coal.


Biofuels | 2013

Optimizing hammer mill performance through screen selection and hammer design

Neal Yancey; Christopher T. Wright; Tyler L. Westover

Background: Mechanical preprocessing, which includes particle-size reduction and mechanical separation, is one of the primary operations in the feedstock supply system for a lignocellulosic biorefinery. It is the means by which raw biomass from the field or forest is mechanically transformed into an on-spec feedstock with characteristics better suited for the fuel conversion process. Results: This work provides a general overview of the objectives and methodologies of mechanical preprocessing and then presents experimental results illustrating improved size reduction via optimization of hammer mill configuration, improved size reduction via pneumatic-assisted hammer milling and improved control of particle size and particle-size distribution through proper selection of grinder process parameters. Conclusion: Optimal grinder configuration for maximal process throughput and efficiency is strongly dependent on feedstock type and properties, such as moisture content. Tests conducted using a HG200 hammer grinder indicate that tip speed, screen size and optimizing hammer geometry can increase grinder throughput as much as 400%.


ASABE Annual International Meeting,Louisville, KY,08/05/2011,08/07/2011 | 2011

Optimization of Preprocessing and Densification of Sorghum Stover at Full-scale Operation

Neal Yancey; Christopher T. Wright; Craig C. Conner; Jaya Shankar Tumuluru

Transportation can be a prohibitive cost in bringing biomass to a preprocessing location or biofuel refinery. One alternative to transporting biomass in baled or loose format to a preprocessing location is to utilize a mobile preprocessing system that can be relocated to the places where biomass is stored and used to preprocess and densify the biomass, which is then shipped to the refinery as needed. Idaho National Laboratory (INL) has a full-scale process demonstration unit (PDU) that includes a Stage 1 grinder, hammer mill, drier, pellet mill, and cooler with the associated conveyance system components. Testing at bench and pilot scales has been conducted to determine effects of moisture on preprocessing, crop varieties on preprocessing efficiency, and product quality. INL’s PDU provides an opportunity to test the conclusions made at the bench and pilot scales on full industrial-scale systems. Each PDU component is operated from a central operating station where data is collected to determine power consumption rates for each step in the process. The power for each electrical motor in the system is monitored from the control station for problems and to determine optimal conditions for system performance. The data can then be evaluated to determine how changes in biomass input parameters (for example, moisture and crop type), mechanical changes (i.e., screen size, biomass drying, pellet size, grinding speed, etc.), or other variations affect the power consumption of the system. Sorgum, in four-foot round bales, was tested in the system using a series of six different screen sizes, including 3/16 in., 1 in., 2 in., 3 in., 4 in., and 6 in. The effect on power consumption, product quality, and production rate were measured to determine optimal conditions.


Archive | 2014

Feedstock Supply System Design and Economics for Conversion of Lignocellulosic Biomass to Hydrocarbon Fuels Conversion Pathway: Fast Pyrolysis and Hydrotreating Bio-Oil Pathway "The 2017 Design Case"

Kevin L. Kenney; Kara G. Cafferty; Jacob J. Jacobson; Ian J. Bonner; Garold L. Gresham; J. Richard Hess; William A. Smith; David N. Thompson; Vicki S. Thompson; Jaya Shankar Tumuluru; Neal Yancey

The U.S. Department of Energy promotes the production of liquid fuels from lignocellulosic biomass feedstocks by funding fundamental and applied research that advances the state of technology in biomass sustainable supply, logistics, conversion, and overall system sustainability. As part of its involvement in this program, Idaho National Laboratory (INL) investigates the feedstock logistics economics and sustainability of these fuels. Between 2000 and 2012, INL quantified and the economics and sustainability of moving biomass from the field or stand to the throat of the conversion process using conventional equipment and processes. All previous work to 2012 was designed to improve the efficiency and decrease costs under conventional supply systems. The 2012 programmatic target was to demonstrate a biomass logistics cost of


2010 Pittsburgh, Pennsylvania, June 20 - June 23, 2010 | 2010

Modifications to Fixed Cutter Grinders for Improved Capacity and Efficiency

Neal Yancey; Christopher T. Wright; Craig C. Conner

55/dry Ton for woody biomass delivered to fast pyrolysis conversion facility. The goal was achieved by applying field and process demonstration unit-scale data from harvest, collection, storage, preprocessing, handling, and transportation operations into INL’s biomass logistics model.


2017 Resilience Week (RWS) | 2017

Data driven decision support for reliable biomass feedstock preprocessing

Daniel L. Marino; Kasun Amarasinghe; Matthew O. Anderson; Neal Yancey; Quang Nguyen; Kevin L. Kenney; Milos Manic

Preprocessing is a critical operation in the biomass feedstock assembly system of a lignocellulosic biorefinery. Preprocessing is typically accomplished using industrial grinders to grind, chop, or otherwise size-reduce biomass materials into a suitable feedstock for conversion to biofuels and bioproducts. Various components of commercial preprocessing equipment capable of handling large-format material (such as large square bales) can be modified or altered to change the overall productivity and efficiency of the process. Many factors affect machine capacity and efficiency and the physical characteristics of preprocessed biomass. Ultimately, grinder capacity and efficiency can be enhanced by selecting hammer and screen configurations that optimize grinder performance-based mass flow and energy consumption. Variations in grinder capacity and efficiency were evaluated by altering the type, number, and orientation of the hammer; the screen type and size; and the rotational drum speed of the grinder. Fuel use and grinder capacity were compared with each modification made to the grinder system and the original design of the horizontal grinder test platform. Modifications evaluated in this study resulted in a significant increase in grinder capacity and efficiency.


international conference on human system interactions | 2017

Dynamic user interfaces for control systems

Patrick Sivils; Kasun Amarasinghe; Matthew O. Anderson; Neal Yancey; Quang Nguyen; Kevin L. Kenney; Milos Manic

Biomass feedstock preprocessing through comminution is an essential first step in biofuel production. Chemical, physical and mechanical variability in feedstock prevents the preprocessing plants from assuming constant control parameters. Constant control parameters can lead to suboptimal capability and reliability. However, adapting the control parameters to account for the variabilities is not a trivial task. This paper presents a framework for adapting control parameters through data driven methodologies. The framework named PDU- RS is a decision support system for human in the loop control. PDU-RS is implemented on the Biofuels National User Facility Preprocessing Process Demonstration Unit (PDU), operated by the Idaho National Laboratory (INL) in Idaho Falls, Idaho. PDU-RS aims at ensuring reliability in the overall operations of the PDU while maximizing throughput. Presented implementation of the PDU-RS uses Gaussian Processes (GP) for knowledge extraction from data. This paper elaborates on the PDU-RS and presents the experimental results of implementing the PDU-RS on the real Biomass PDU. The experimental results demonstrated that the PDU-RS is able to produce significantly higher throughputs while ensuring higher reliability when compared to the traditional control methodology used with the system.


Journal of Biobased Materials and Bioenergy | 2013

Drying, grinding and pelletization studies on raw and formulated biomass feedstock's for bioenergy applications.

Neal Yancey; Jaya Shankar Tumuluru; Christopher T. Wright

Control systems monitor and command other devices, systems, and software within an infrastructure. Typically, control systems employ human-in-the-loop control for critical decision making and response. These end-users require easy access to accurate, actionable and relevant data to ensure quick and effective decision making. This work presents a framework for creating dynamic visual interfaces for improved situational awareness. The proposed framework determines the relevance of available information pieces and then applies the derived relevance scores to a visualization so that the most relevant and important information are emphasized to the end-users. In the presented work, a priori expert knowledge is encoded in the system through the use of Fuzzy Logic (FL) and the resulting FL inference system assigns scores to information pieces based on system state information and user defined relevance. These scores can then be used to organize and display the relevant data given the current situation and end-user roles. The proposed FL based scoring system was implemented on a real world control system dataset and we demonstrate how the information visualization is dynamically adapted to improve situational awareness. Further, we discuss potential methods the relevance scores can be incorporated into real world visualizations to increase the situational awareness in control systems.


Bioenergy Research | 2015

Scale-Up of Ionic Liquid-Based Fractionation of Single and Mixed Feedstocks

Chenlin Li; Deepti Tanjore; Wei He; Jessica Wong; James Gardner; Vicki S. Thompson; Neal Yancey; Kenneth L. Sale; Blake A. Simmons; Seema Singh

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Kevin L. Kenney

Idaho National Laboratory

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Blake A. Simmons

Lawrence Berkeley National Laboratory

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Ian J. Bonner

Idaho National Laboratory

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J. Richard Hess

Idaho National Laboratory

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