Decontamination and Waste Treatment Facility (DWTF) Final Environmental Assessment (EA) B1 PDF Download
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Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
The purpose of this study has been to evaluate the adequacy of present and proposed decontamination and waste treatment facilities (DWTF) at LLNL, to determine the cost effectiveness for proposed improvements, and possible alternatives for accomplishing these improvements. To the extent possible, we have also looked at some of the proposed environmental compliance and cleanup (ECC) projects.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
This EA evaluates the proposed action to decontaminate and decommission GA's hot cell facility in northern San Diego, CA. This facility has been used for DOE and commercial nuclear R & D for> 30 years. About 30,000 cubic feet of decontamination debris and up to 50,000 cubic feet of contaminated soil are to be removed. Low-level radioactive waste would be shipped for disposal. It was determined that the proposal does not constitute a major federal action significantly affecting the human environment according to NEPA; therefore, a finding of no significant impact is made, and an environmental impact statement is not required.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
To provide a centralized decontamination and waste treatment facility (DWTF) at LLNL, the construction of a new installation has been planned. Objectives for this new facility were to replace obsolete, structurally and environmentally sub-marginal liquid and solid waste process facilities and decontamination facility and to bring these facilities into compliance with existing federal, state and local regulations as well as DOE orders. In a previous study, SAIC conducted a preliminary review and evaluation of existing facilities at LLNL and cost effectiveness of the proposed DWTF. This document reports on a detailed review of specific aspects of the proposed DWTF.
Author: Steven S. Skiena Publisher: Springer ISBN: 3319554441 Category : Computers Languages : en Pages : 445
Book Description
This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)