The Experts below are selected from a list of 951 Experts worldwide ranked by ideXlab platform
Kun-hsing Liu - One of the best experts on this subject based on the ideXlab platform.
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resource and waste stream modeling and visualization as decision support tools for sustainable materials management
Journal of Cleaner Production, 2017Co-Authors: Pi Cheng Chen, Kun-hsing LiuAbstract:Abstract Sustainable Materials Management requires the knowledge of complex material flow system. However, it's difficult for the policy maker and industries to know the flows for the lack of the expertise to implement material flow analysis. Facing this issue, we designed a web-based tool to generate interactive Sankey Diagrams for developing strategies to sustainably manage resource and waste flows through a complex economy. By examining the opportunities across a material's lifecycle, this tool supports sustainable materials management, which is important in reducing environmental pressures and the demand for resource extraction. Three applications were developed for (1) tracking resource flows along supply chains, (2) identifying economic activities that cause waste generation, and (3) tracing the material footprints for a sector. To finish the applications, we integrated a comprehensive resource and waste database with several input–output analysis based material flow models. For easy recognition of the key flows and activities, Sankey Diagrams can be generated using a data-visualization technology. This article demonstrates the material management practices that can be discovered with the information of the flow system from the applications. Examine the flow paths of resources, several practices for sand and gravels are formulated based on the key activities in processing or using the material. Overviewing the driving forces of industrial wastes, we also pinpoint the practices to reduce the generation of coal ash. Tracking the resource footprints of economic activities, we highlight that the construction sector can use the cement made from blast furnace slag as to reduce the footprint. Also, we explain how this approach facilitates the coordination of government's interagency actions and the engagement of private sectors.
Jonathan M. Cullen - One of the best experts on this subject based on the ideXlab platform.
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Control data, Sankey Diagrams, and exergy: Assessing the resource efficiency of industrial plants
Applied Energy, 2018Co-Authors: Ana Gonzalez Hernandez, Richard C. Lupton, Chris Williams, Jonathan M. CullenAbstract:This research is funded by Emerson Electric co. This study was supported by Tata Steel UK.
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From control data to real-time resource maps in a steel-making plant
Energy Procedia, 2017Co-Authors: Ana Gonzalez Hernandez, Richard C. Lupton, Chris Williams, Jonathan M. CullenAbstract:Abstract This study measures the resource efficiency of a basic oxygen steelmaking plant and develops visual maps of its resource use using raw energy and material data extracted directly from the control system. Resource efficiency is measured in units of exergy and resource flows are visualised in Sankey Diagrams. Both the metric and the visuals are computed in close-to-real time scales, and are presented on a daily basis over a period of two weeks. Results show the highest level of resource efficiency (73.8%, Day 11) occurs not when energy intensity is greatest (Day 14) but instead when both energy intensity and material yields are high. Combining energy and materials into a single metric – resource efficiency – is shown to provide plant managers with a clearer picture of where interventions might deliver the greatest efficiency gains and redefines the concept of best practice.
Richard C. Lupton - One of the best experts on this subject based on the ideXlab platform.
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Code supporting "Control data, Sankey Diagrams, and exergy:: Assessing the resource efficiency of industrial plants
2019Co-Authors: Ana Gonzalez Hernandez, Richard C. LuptonAbstract:This folder contains the Python code that was used to process the resource flow data of a basic oxygen steelmaking plant owned by Tata Steel.
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Control data, Sankey Diagrams, and exergy: Assessing the resource efficiency of industrial plants
Applied Energy, 2018Co-Authors: Ana Gonzalez Hernandez, Richard C. Lupton, Chris Williams, Jonathan M. CullenAbstract:This research is funded by Emerson Electric co. This study was supported by Tata Steel UK.
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Hybrid Sankey Diagrams: Visual analysis of multidimensional data for understanding resource use
Resources Conservation and Recycling, 2017Co-Authors: Richard C. Lupton, Julian M. AllwoodAbstract:Abstract Sankey Diagrams are used to visualise flows of materials and energy in many applications, to aid understanding of losses and inefficiencies, to map out production processes, and to give a sense of scale across a system. As available data and models become increasingly complex and detailed, new types of visualisation may be needed. For example, when looking for opportunities to reduce steel scrap through supply chain integration, it is not enough to consider simply flows of “steel” — the alloy, thickness, coating and forming history of the metal can be critical. This paper combines data-visualisation techniques with the traditional Sankey diagram to propose a new type of “hybrid” Sankey diagram, which is better able to visualise these different aspects of flows. There is more than one way to visualise a dataset as a Sankey diagram, and different ways are appropriate in different situations. To facilitate this, a systematic method is presented for generating different hybrid Sankey Diagrams from a dataset, with an accompanying open-source Python implementation. A common data structure for flow data is defined, through which this method can be used to generate Sankey Diagrams from different data sources such as material flow analysis, life-cycle inventories, or directly measured data. The approach is introduced with a series of visual examples, and applied to a real database of global steel flows.
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From control data to real-time resource maps in a steel-making plant
Energy Procedia, 2017Co-Authors: Ana Gonzalez Hernandez, Richard C. Lupton, Chris Williams, Jonathan M. CullenAbstract:Abstract This study measures the resource efficiency of a basic oxygen steelmaking plant and develops visual maps of its resource use using raw energy and material data extracted directly from the control system. Resource efficiency is measured in units of exergy and resource flows are visualised in Sankey Diagrams. Both the metric and the visuals are computed in close-to-real time scales, and are presented on a daily basis over a period of two weeks. Results show the highest level of resource efficiency (73.8%, Day 11) occurs not when energy intensity is greatest (Day 14) but instead when both energy intensity and material yields are high. Combining energy and materials into a single metric – resource efficiency – is shown to provide plant managers with a clearer picture of where interventions might deliver the greatest efficiency gains and redefines the concept of best practice.
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Research data supporting “Hybrid Sankey Diagrams: visual analysis of multidimensional data for understanding resource use”
2016Co-Authors: Richard C. Lupton, Julian M. AllwoodAbstract:This data includes two example databases from the paper "Hybrid Sankey Diagrams: visual analysis of multidimensional data for understanding resource use": the made-up fruit flows, and real global steel flow data from Cullen et al. (2012). It also includes the Sankey Diagram Definitions to reproduce the Diagrams in the paper. The code to reproduce the figures is written in Python in the form of Jupyter notebooks. A conda environment file is included to easily set up the necessary Python packages to run the notebooks. All files are included in the "examples.zip" file. The notebook files are also uploaded standalone so they can be linked to nbviewer.
Thomas E. Graedel - One of the best experts on this subject based on the ideXlab platform.
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Material Flow Analysis from Origin to Evolution.
Environmental science & technology, 2019Co-Authors: Thomas E. GraedelAbstract:Material flow analysis (MFA), a central methodology of industrial ecology, quantifies the ways in which the materials that enable modern society are used, reused, and lost. Sankey Diagrams, termed ...
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Uncovering the end uses of the rare earth elements.
Science of The Total Environment, 2013Co-Authors: Thomas E. GraedelAbstract:The rare earth elements (REE) are a group of fifteen elements with unique properties that make them indispensable for a wide variety of emerging and conventional established technologies. However, quantitative knowledge of REE remains sparse, despite the current heightened interest in future availability of the resources. Mining is heavily concentrated in China, whose monopoly position and potential restriction of exports render primary supply vulnerable to short term disruption. We have drawn upon the published literature and unpublished materials in different languages to derive the first quantitative annual domestic production by end use of individual rare earth elements from 1995 to 2007. The information is illustrated in Sankey Diagrams for the years 1995 and 2007. Other years are available in the supporting information. Comparing 1995 and 2007, the production of the rare earth elements in China, Japan, and the US changed dramatically in quantities and structure. The information can provide a solid foundation for industries, academic institutions and governments to make decisions and develop strategies.
Pi Cheng Chen - One of the best experts on this subject based on the ideXlab platform.
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resource and waste stream modeling and visualization as decision support tools for sustainable materials management
Journal of Cleaner Production, 2017Co-Authors: Pi Cheng Chen, Kun-hsing LiuAbstract:Abstract Sustainable Materials Management requires the knowledge of complex material flow system. However, it's difficult for the policy maker and industries to know the flows for the lack of the expertise to implement material flow analysis. Facing this issue, we designed a web-based tool to generate interactive Sankey Diagrams for developing strategies to sustainably manage resource and waste flows through a complex economy. By examining the opportunities across a material's lifecycle, this tool supports sustainable materials management, which is important in reducing environmental pressures and the demand for resource extraction. Three applications were developed for (1) tracking resource flows along supply chains, (2) identifying economic activities that cause waste generation, and (3) tracing the material footprints for a sector. To finish the applications, we integrated a comprehensive resource and waste database with several input–output analysis based material flow models. For easy recognition of the key flows and activities, Sankey Diagrams can be generated using a data-visualization technology. This article demonstrates the material management practices that can be discovered with the information of the flow system from the applications. Examine the flow paths of resources, several practices for sand and gravels are formulated based on the key activities in processing or using the material. Overviewing the driving forces of industrial wastes, we also pinpoint the practices to reduce the generation of coal ash. Tracking the resource footprints of economic activities, we highlight that the construction sector can use the cement made from blast furnace slag as to reduce the footprint. Also, we explain how this approach facilitates the coordination of government's interagency actions and the engagement of private sectors.
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identifying the drivers of environmental risk through a model integrating substance flow and input output analysis
Ecological Economics, 2014Co-Authors: Pi Cheng Chen, Douglas Crawfordbrown, Chi Hui ChangAbstract:Abstract In addition to risk assessment, effective environmental risk management requires information indicating sources and driving forces of risks. Systematic substance flow analysis can indicate critical emissions and potential strategies of risk reduction by mapping the flows of toxic substances throughout the economic system. This research developed an integrated modeling framework for examining the connections between driving forces and environmental risk. Three methodologies, including substance flow modeling, input–output model, and environmental risk assessment, were integrated into the framework. We built a model of lead flow system integrating four risk chain modules, which are corresponding to the Driver, Presser, State, and Impact component of DPSIR environmental management framework. Thus, risk can be backtraced to its exposure pathways, emission sources, and driving forces. In the results, Sankey Diagrams are presented to highlight the sources and driving forces of the lead flow system. Among the driving forces, unit change in the demand on computer products is associated with the most significant change in risk of lead. Backtracing the contributions of the causes along the risk chain, the sectors of electronic product and computer product had driven the electronic supply chain which contributes the greatest to risk of lead by discharging into water body.
