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Kuan Chong Ting - One of the best experts on this subject based on the ideXlab platform.
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Systems Informatics for Biomass Feedstock Production Engineering
2009 Reno Nevada June 21 - June 24 2009, 2020Co-Authors: Konstantinos Domdouzis, Yogendra R Shastri, Ming-che Hu, Luis F Rodriguez, Alan Christopher Hansen, Kuan Chong TingAbstract:Biomass Feedstock Production is a significant part of the supply chain of bioenergy. It consists of an integrative framework of chemical and biological processes as well as technical operations. The introduction of systems informatics facilitates the flow of information between these processes and operations through the use of specific techniques such as knowledge management, concurrent science and engineering, software engineering, and decision support. These techniques are integrated in the Production of biomass Feedstock through an information system. The core element of this information system is a database system. The handling of the data of the database system occurs through a number of graphical user interfaces. The design of these graphical user interfaces is based on the use of metadata which correspond to the attributes of the tasks, subtasks, and technological equipments of the respective stages of the biomass Feedstock Production. Furthermore, these interfaces allow the initiation of a number of operations, such as optimization, simulation, analysis of experimental data, and collection of information in real time, with parallel use of a number of software packages specialized for each stage of the biomass Feedstock Production. This paper describes the development of the framework for this information system for biomass Feedstock Production.
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Development of an Application Programming Interface (API) for Biomass Feedstock Production Engineering
2010 Pittsburgh Pennsylvania June 20 - June 23 2010, 2020Co-Authors: Konstantinos Domdouzis, Luis F Rodriguez, Alan Christopher Hansen, Kuan Chong TingAbstract:Biomass Feedstock Production is an integral element of bioenergy Production. The amount of useful information distributed among various stages of biomass Feedstock Production is large while there is increased complexity in the relationship between the generated data. A systems informatics infrastructure is therefore considered necessary in order for the people involved in biomass Feedstock Production to be able to access the generated data, exchange data amongst each other, and also manipulate them. The ultimate goal of this infrastructure is the provision of effective procedures for decision making in a concurrent way. Specifically, all the stages of biomass Feedstock Production should be able to handle data simultaneously. Furthermore, any knowledge associated with the infrastructure must be managed efficiently and this can be achieved by the use of the appropriate software engineering techniques. The use of such techniques allows the identification of the requirements for the biomass Feedstock Production supply chains and the design of an efficient informatics platform based on these requirements. This paper aims to introduce the application programming interface (API) which is the core element of the informatics infrastructure developed for the biomass Feedstock Production. The API is connected to a database containing data related to each stage of biomass Feedstock Production. The API provides a number of capabilities to its users, such as the access to and visualization of both existing data and simulation results for analysis purposes, the provision of a metadata-based database search engine, the identification of hidden relationships between data through the use of data clustering algorithms, and the identification of the strength of these relationships through the use of rule-based techniques. Furthermore, the capabilities of the API will expand to the field of artificial intelligence and especially artificial neural networks and genetic algorithms for the realization of predictions and optimization. Regression analysis is another technique which will be provided by the API to facilitate the exploration of optimal values of data which affect other data related to biomass Feedstock Production to be explored.
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A novel computational approach to solve complex optimization problems involving multiple stakeholders in biomass Feedstock Production
2010 Pittsburgh Pennsylvania June 20 - June 23 2010, 2020Co-Authors: Yogendra Shastri, Luis F Rodriguez, Alan Christopher Hansen, Kuan Chong TingAbstract:Biomass Feedstock Production is an important component of the biomass based energy sector. Seasonal and distributed collection of low energy density material creates unique challenges, and optimization of the complete value chain is critical for cost-competitiveness. BioFeed is a mixed integer linear programming (MILP) model that has been developed and successfully applied to optimize biomass Feedstock Production of bioenergy crops. It integrates the individual farm design and operating decision with the transportation logistics issues to analyze them as a single system. However, this integration leads to a model that is computationally demanding, leading to large simulation times for simplified case studies. Given these challenges, and in wake of the future model extensions, this work proposes a new computational approach that reduces computational demand, maintains result accuracy, provides modeling flexibility and enables future model enhancements. The new approach, named the Decomposition and Distributed Computing (DDC) approach, first decomposes the model into two separate optimization models: a Production model, focusing on on-farm activities such as harvesting, and a provision model, incorporating the post-Production activities such as transportation logistics. An iterative scheme based on the concepts from agent based modeling is adapted to solve the Production and provision problems iteratively until convergence has been reached. The computational features of the approach are further enhanced by enabling distributed computing of the individual farm optimization models. Simulation studies comparing the performance of the DDC approach with the rigorous MILP solution approach illustrate an order of magnitude reduction in computational time using the proposed DDC approach. Moreover, the solution obtained using the DDC approach is within 5% of the MILP solution. This approach can be a valuable tool to solve complex supply chain optimization problems in other sectors where similar challenges are encountered.
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Engineering Solutions for Biomass Feedstock Production - Pre-harvest Crop Monitoring System
2009 Reno Nevada June 21 - June 24 2009, 2020Co-Authors: Tofael Ahamed, Lei Tian, Yuliang Zhang, Qin Zhang, Tony E Grift, Kuan Chong TingAbstract:This work is a part of the integrated research of engineering solution for biomass Feedstock Production. The goal of this task is to monitor energy crops at the pre-harvest condition using near-real-time remote sensing method. To achieve this elusive goal, the stand alone tower camera platform has been developed to monitor energy crops during plant growing season. A high resolution multispectral camera with a variable lens and pan tilt device are used to capture RGB and CIR images. The system is installed on top of a 38 meter height tower in the field of energy crops. A stand-alone control algorithm has been developed to control the camera gain and exposure time in different natural illumination conditions. The sensing system is remotely controlled using wireless networking. The challenges of this task are the site-specific management; explore the potential of identify the optimum harvesting time (window) and increase the quality assurance of different biomass Feedstock. The field layout has been designed to monitor crop growth conditions. The biomass yield and energy content are to be compared using remote sensing models. The correlation with agronomic databases and remote sensing spectral data will be evaluated for the validation and modification of sensing and data processing system.
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Concurrent science, engineering and technology (ConSEnT) for biomass Feedstock Production decision support
2011 Louisville Kentucky August 7 - August 10 2011, 2020Co-Authors: Yung Chen Liao, Yogendra Shastri, Luis F Rodriguez, Alan Christopher Hansen, Kuan Chong TingAbstract:Concurrent Science, Engineering, and Technology (ConSEnT) approach was used to develop and implement a web-based environment for supporting decision making on the planning, design, management, and operation of biomass Feedstock Production and provision systems. ConSEnT is suitable for integrating and utilizing computational resources, such as databases, models, and user interfaces, in a real-time fashion to share information and results of analysis. This web-based decision support system, BPSys, is programmed in Java and integrates the functions provided from various software packages, Apache Http Server, Apache Tomcat, Drupal, MySQL database, and JFreeChart. The graphical user interface (GUI) of BPSys is a Java applet embedded in a web page executed on users’ local machines and works as a front end. The GUI provides users easy access to biomass Production scenario building tools, simulation/optimization models, and various forms of analyses and output from the models. This decision support system allows researchers and users to contribute and test the latest information about biomass Production systems in a concurrent fashion. BPSys users can logon to this system anywhere via web browsers and select different scenarios, retrieve latest attributes from the database, modify attributes, execute latest models and save results through the GUI.
Yogendra Shastri - One of the best experts on this subject based on the ideXlab platform.
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Concurrent science, engineering and technology (ConSEnT) for biomass Feedstock Production decision support
2011 Louisville Kentucky August 7 - August 10 2011, 2020Co-Authors: Yung Chen Liao, Yogendra Shastri, Luis F Rodriguez, Alan Christopher Hansen, Kuan Chong TingAbstract:Concurrent Science, Engineering, and Technology (ConSEnT) approach was used to develop and implement a web-based environment for supporting decision making on the planning, design, management, and operation of biomass Feedstock Production and provision systems. ConSEnT is suitable for integrating and utilizing computational resources, such as databases, models, and user interfaces, in a real-time fashion to share information and results of analysis. This web-based decision support system, BPSys, is programmed in Java and integrates the functions provided from various software packages, Apache Http Server, Apache Tomcat, Drupal, MySQL database, and JFreeChart. The graphical user interface (GUI) of BPSys is a Java applet embedded in a web page executed on users’ local machines and works as a front end. The GUI provides users easy access to biomass Production scenario building tools, simulation/optimization models, and various forms of analyses and output from the models. This decision support system allows researchers and users to contribute and test the latest information about biomass Production systems in a concurrent fashion. BPSys users can logon to this system anywhere via web browsers and select different scenarios, retrieve latest attributes from the database, modify attributes, execute latest models and save results through the GUI.
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A novel computational approach to solve complex optimization problems involving multiple stakeholders in biomass Feedstock Production
2010 Pittsburgh Pennsylvania June 20 - June 23 2010, 2020Co-Authors: Yogendra Shastri, Luis F Rodriguez, Alan Christopher Hansen, Kuan Chong TingAbstract:Biomass Feedstock Production is an important component of the biomass based energy sector. Seasonal and distributed collection of low energy density material creates unique challenges, and optimization of the complete value chain is critical for cost-competitiveness. BioFeed is a mixed integer linear programming (MILP) model that has been developed and successfully applied to optimize biomass Feedstock Production of bioenergy crops. It integrates the individual farm design and operating decision with the transportation logistics issues to analyze them as a single system. However, this integration leads to a model that is computationally demanding, leading to large simulation times for simplified case studies. Given these challenges, and in wake of the future model extensions, this work proposes a new computational approach that reduces computational demand, maintains result accuracy, provides modeling flexibility and enables future model enhancements. The new approach, named the Decomposition and Distributed Computing (DDC) approach, first decomposes the model into two separate optimization models: a Production model, focusing on on-farm activities such as harvesting, and a provision model, incorporating the post-Production activities such as transportation logistics. An iterative scheme based on the concepts from agent based modeling is adapted to solve the Production and provision problems iteratively until convergence has been reached. The computational features of the approach are further enhanced by enabling distributed computing of the individual farm optimization models. Simulation studies comparing the performance of the DDC approach with the rigorous MILP solution approach illustrate an order of magnitude reduction in computational time using the proposed DDC approach. Moreover, the solution obtained using the DDC approach is within 5% of the MILP solution. This approach can be a valuable tool to solve complex supply chain optimization problems in other sectors where similar challenges are encountered.
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Biomass Feedstock Production and Provision: Overview, Current Status, and Challenges
Engineering and Science of Biomass Feedstock Production and Provision, 2014Co-Authors: Yogendra Shastri, Kuan Chong TingAbstract:Biomass-based renewable energy will play a critical role in meeting the future global energy demands. Lignocellulosic biomass, such as agricultural residue, perennial grasses, and woody biomass, will constitute a major portion of the Feedstock for these biomass-based energy systems. However, successful transition to this second-generation bioenergy system will require cost-efficient, reliable, and sustainable biomass Feedstock Production and provision (BFPP). The BFPP system includes the operations of agronomic Production of energy crops and physical processing and handling/delivery of biomass, as well as other enabling logistics. On the technical side, biological, physical, and chemical sciences need to be integrated with engineering and technology to ensure effective and efficient Production of biomass Feedstock. However, low energy and bulk densities, seasonal availability, and distributed supply create unique challenges for BFPP. Lack of experience and established standards provide additional challenges for large-scale Production and provision of energy crops. The aim of this book is to summarize the current state of knowledge, identify research gaps, and provide future research directions on the topic of BFPP. Towards that end, the goal of this chapter is to set the foundation for the subsequent chapters that focus on specific components within this system. This BFPP system and its components are briefly described, current status and challenges are identified, and the research needs are highlighted. A typical Production system based on current understanding and technological availability is also described. The chapter, therefore, provides an introduction to the advanced chapters that appear subsequently in the book.
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Systems informatics and analysis of biomass Feedstock Production.
pertanika journal of science and technology, 2013Co-Authors: Yogendra Shastri, Luis F Rodriguez, Alan Christopher Hansen, Kuan Chong TingAbstract:Sustainable biomass Feedstock Production is critical for the success of a regional bioenergy system. Low energy and mass densities, seasonal availability, distributed supply, and lack of an established value chain for the Feedstock create unique challenges that require an integrated systems approach. We have, therefore, developed a Concurrent Science, Engineering and Technology (ConSEnT) platform integrating informatics, modelling and analysis, as well as decision support for biomass Feedstock Production. An optimization model (BioFeed) and an agent-based model, which are supported by an informatics database and made accessible through a web-based decision support system, have been developed. This article summarizes the recent advances in this subject area by our research team.
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Impact of probability of working day on planning and operation of biomass Feedstock Production systems
Biofuels Bioproducts and Biorefining, 2012Co-Authors: Yogendra Shastri, Luis F Rodriguez, Alan Christopher Hansen, Kuan Chong TingAbstract:Unfavorable weather can significantly impact the Production and provision of agriculture-based biomass Feedstocks such as Miscanthus and switchgrass. This work quantified the impact of regional weather on the Feedstock Production systems using the BioFeed modeling framework. Weather effects were incorporated in BioFeed by including the probability of working day (pwd) parameter in the model, which defined the fraction of days in a specific period such as two weeks that were suitable for field operations. Model simulations were conducted for Miscanthus and switchgrass for values of pwd between 20 and 100% and intended biorefinery capacities between 1000 and 5000 Mg d−1; and the impact on total cost and farm machinery requirements was quantified. Results indicated that using Production and provision systems designed assuming 100% pwd for lower pwd values increased the cost exponentially by up to 64% for Miscanthus and 85% for switchgrass. It also decreased the supportable biorefinery capacity for the collection region by up to 60%. If the systems were instead optimized for specific values of pwd, the original biorefinery capacity was maintained and the total cost increase was less than 5%. The resulting optimal systems required up to 40% higher investment in farm machinery. For Illinois, Production systems designed for regional pwd values required a 34% increase in farm machinery investment for Miscanthus while only a 12% increase for switchgrass. Initiating Miscanthus harvesting in November instead of January reduced the farm machinery investment increase to 17%, which suggests that such an alternative should be rigorously evaluated. © 2012 Society of Chemical Industry and John Wiley & Sons, Ltd
Conrad Savy - One of the best experts on this subject based on the ideXlab platform.
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Tools and methodologies to support more sustainable biofuel Feedstock Production
Journal of Industrial Microbiology and Biotechnology, 2011Co-Authors: Christine Dragisic, Lucio Bede, Bambi Semroc, Erica Ashkenazi, Miroslav Honzák, Adriano Paglia, Tim Killeen, Conrad SavyAbstract:Increasingly, government regulations, voluntary standards, and company guidelines require that biofuel Production complies with sustainability criteria. For some stakeholders, however, compliance with these criteria may seem complex, costly, or unfeasible. What existing tools, then, might facilitate compliance with a variety of biofuel-related sustainability criteria? This paper presents four existing tools and methodologies that can help stakeholders assess (and mitigate) potential risks associated with Feedstock Production, and can thus facilitate compliance with requirements under different requirement systems. These include the Integrated Biodiversity Assessment Tool (IBAT), the ARtificial Intelligence for Ecosystem Services (ARIES) tool, the Responsible Cultivation Areas (RCA) methodology, and the related Biofuels + Forest Carbon (Biofuel + FC) methodology.
Seth W Snyder - One of the best experts on this subject based on the ideXlab platform.
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a novel framework to classify marginal land for sustainable biomass Feedstock Production
Journal of Environmental Quality, 2011Co-Authors: Gayathri Gopalakrishnan, Cristina M Negri, Seth W SnyderAbstract:: To achieve food and energy security, sustainable bioenergy has become an important goal for many countries. The use of marginal lands to produce energy crops is one strategy for achieving this goal, but what is marginal land? Current definitions generally focus on a single criterion, primarily agroeconomic profitability. Herein, we present a framework that incorporates multiple criteria including profitability of current land use, soil health indicators (erosion, flooding, drainage, or high slopes), and environmental degradation resulting from contamination of surface water or groundwater resources. We tested this framework for classifying marginal land in the state of Nebraska and estimated the potential for using marginal land to produce biofuel crops. Our results indicate that approximately 1.6 million ha, or 4 million acres, of land (approximately 8% of total land area) could be classified as marginal on the basis of at least two criteria. Second-generation lignocellulosic bioenergy crops such as switchgrass ( Panicum virgatum L.), miscanthus (Miscanthus giganteus), native prairie grasses, and short-rotation woody crops could be grown on this land in redesigned landscapes that meet energy and environmental needs, without significant impacts on food or feed Production. Calculating tradeoffs between the economics of redesigned landscapes and current practices at the field scale is the next step for determining functional designs for integrating biofuel Feedstock Production into current land management practices.
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Biofuels, Land, and Water: A Systems Approach to Sustainability
Environmental Science & Technology, 2009Co-Authors: Gayathri Gopalakrishnan, May Wu, Seth W Snyder, M. Cristina Negri, Michael Wang, Lorraine LafreniereAbstract:There is a strong societal need to evaluate and understand the sustainability of biofuels, especially because of the significant increases in Production mandated by many countries, including the United States. Sustainability will be a strong factor in the regulatory environment and investments in biofuels. Biomass Feedstock Production is an important contributor to environmental, social, and economic impacts from biofuels. This study presents a systems approach where the agricultural, energy, and environmental sectors are considered as components of a single system, and environmental liabilities are used as recoverable resources for biomass Feedstock Production. We focus on efficient use of land and water resources. We conducted a spatial analysis evaluating marginal land and degraded water resources to improve Feedstock productivity with concomitant environmental restoration for the state of Nebraska. Results indicate that utilizing marginal land resources such as riparian and roadway buffer strips, brow...
Kyoung S Ro - One of the best experts on this subject based on the ideXlab platform.
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the potential impacts of biomass Feedstock Production on water resource availability
Bioresource Technology, 2010Co-Authors: K C Stone, P G Hunt, Keri B Cantrell, Kyoung S RoAbstract:Biofuels are a major topic of global interest and technology development. Whereas bioenergy crop Production is highly dependent on water, bioenergy development requires effective allocation and management of water. The objectives of this investigation were to assess the bioenergy Production relative to the impacts on water resource related factors: (1) climate and weather impact on water supplies for biomass Production; (2) water use for major bioenergy crop Production; and (3) potential alternatives to improve water supplies for bioenergy. Shifts to alternative bioenergy crops with greater water demand may produce unintended consequences for both water resources and energy Feedstocks. Sugarcane and corn require 458 and 2036 m 3 water/m 3 ethanol produced, respectively. The water requirements for corn grain Production to meet the US-DOE Billion-Ton Vision may increase approximately 6-fold from 8.6 to 50.1 km 3 . Furthermore, climate change is impacting water resources throughout the world. In the western US, runoff from snowmelt is occurring earlier altering the timing of water availability. Weather extremes, both drought and flooding, have occurred more frequently over the last 30 years than the previous 100 years. All of these weather events impact bioenergy crop Production. These events may be partially mitigated by alternative water management systems that offer potential for more effective water use and conservation. A few potential alternatives include controlled drainage and new next-generation livestock waste treatment systems. Controlled drainage can increase water available to plants and simultaneously improve water quality. New livestock waste treatments systems offer the potential to utilize treated wastewater to produce bioenergy crops. New technologies for cellulosic biomass conversion via thermochemical conversion offer the potential for using more diverse Feedstocks with dramatically reduced water requirements. The development of bioenergy Feedstocks in the US and throughout the world should carefully consider water resource limitations and their critical connections to ecosystem integrity and sustainability of human food. Published by Elsevier Ltd.
