37 research outputs found

    End-of-life vehicle recycling : state of the art of resource recovery from shredder residue.

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    Each year, more than 25 million vehicles reach the end of their service life throughout the world, and this number is rising rapidly because the number of vehicles on the roads is rapidly increasing. In the United States, more than 95% of the 10-15 million scrapped vehicles annually enter a comprehensive recycling infrastructure that includes auto parts recyclers/dismantlers, remanufacturers, and material recyclers (shredders). Today, over 75% of automotive materials, primarily the metals, are profitably recycled via (1) parts reuse and parts and components remanufacturing and (2) ultimately by the scrap processing (shredding) industry. The process by which the scrap processors recover metal scrap from automobiles involves shredding the obsolete automobile hulks, along with other obsolete metal-containing products (such as white goods, industrial scrap, and demolition debris), and recovering the metals from the shredded material. The single largest source of recycled ferrous scrap for the iron and steel industry is obsolete automobiles. The non-metallic fraction that remains after the metals are recovered from the shredded materials - commonly called shredder residue - constitutes about 25% of the weight of the vehicle, and it is disposed of in landfills. This practice is not environmentally friendly, wastes valuable resources, and may become uneconomical. Therefore, it is not sustainable. Over the past 15-20 years, a significant amount of research and development has been undertaken to enhance the recycle rate of end-of-life vehicles, including enhancing dismantling techniques and improving remanufacturing operations. However, most of the effort has been focused on developing technology to separate and recover non-metallic materials, such as polymers, from shredder residue. To make future vehicles more energy efficient, more lightweighting materials - primarily polymers, polymer composites, high-strength steels, and aluminum - will be used in manufacturing these vehicles. Many of these materials increase the percentage of shredder residue that must be disposed of, compared with the percentage of metals that are recovered. In addition, the number of hybrid vehicles and electric vehicles on the road is rapidly increasing. This trend will also introduce new materials for disposal at the end of their useful lives, including batteries. Therefore, as the complexity of automotive materials and systems increases, new technologies will be required to sustain and maximize the ultimate recycling of these materials and systems. Argonne National Laboratory (Argonne), the Vehicle Recycling Partnership, LLC. (VRP) of the United States Council for Automotive Research, LLC. (USCAR), and the American Chemistry Council-Plastics Division (ACC-PD) are working to develop technology for recovering materials from end-of-life vehicles, including separating and recovering polymers and residual metals from shredder residue. Several other organizations worldwide are also working on developing technology for recycling materials from shredder residue. Without a commercially viable shredder industry, our nation and the world will most likely face greater environmental challenges and a decreased supply of quality scrap, and thereby be forced to turn to primary ores for the production of finished metals. This will result in increased energy consumption and increased damage to the environment, including increased greenhouse gas emissions. The recycling of polymers, other organics, and residual metals in shredder residue saves the equivalent of over 23 million barrels of oil annually. This results in a 12-million-ton reduction in greenhouse gas emissions. This document presents a review of the state-of-the-art in the recycling of automotive materials

    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    Retrieval of passages for information reduction

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    Information Retrieval (IR) typically retrieves entire documents in response to a user\u27s information need. However, many times a user would prefer to examine smaller portions of a document. One example of this is when building a frame-based representation of a text. The user would like to read all and only those portions of the text that are about predefined important features. This research addresses the problem of automatically locating text about these features, where the important features are those defined for use by a case-based reasoning (CBR) system in the form of features and values or slots and fillers. To locate important text pieces we gathered a small set of excerpts , textual segments, when creating the original case-base representations. Each segment contains the local context for a particular feature within a document. We used these excerpts to generate queries that retrieve relevant passages. By locating passages for display to the user, we winnow a text down to sets of several sentences, greatly reducing the time and effort expended searching through each text for important features
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