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On-Site Disposition of Concrete During Decommissioning and Decontamination: A Data Quality Objective-Based Approach

机译:退役和净化过程中混凝土的现场处置:一种基于数据质量目标的方法

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On-site disposition of concrete derived during decommissioning and demolition (D&D) of buildings at industrial sites is a cost-effective, waste minimization alternative to off-site disposal. Because the concrete is to be left on-site it becomes part of the solid matrix of the site and is subject to the compositional constraints governing site soils. In addition, the concrete and its contained-in materials may be subject to physical constraints such as size and shape which do not apply to soils. When considering on-site disposition of concrete, the data quality objective (DQO) process should be used to determine the compositional and physical constraints on the concrete and for developing the characterization approach to determine whether those constraints have been met. The information inputs to the compositional and physical constraints on the concrete constitute the concrete acceptance criteria (CAC) which become the basis for developing decision rules - the yeso statements that unequivocally state the compositional and physical conditions under which concrete may be left on site.An important DQO boundary concept is concrete classification. The cost of concrete characterization can be minimized with a thorough data gap assessment by focusing resources on the concrete most in need of characterization. Concrete for which a yeso decision can be made with reasonable certainty based on a comparison of existing data to the CAC receives a lesser amount of characterization scrutiny than does concrete for which existing data is non-existent or ambiguous relative to the CAC.
机译:在工业场所对建筑物进行退役和拆除(D&D)时对混凝土进行现场处置是一种成本效益高,废物最少的替代方法。因为混凝土要留在现场,所以它成为场地固体基质的一部分,并受到控制场地土壤的成分限制。另外,混凝土及其包含的材料可能受到不适用于土壤的物理约束,例如尺寸和形状。在考虑现场处理混凝土时,应使用数据质量目标(DQO)过程来确定混凝土的成分和物理约束,并用于开发表征方法以确定这些约束是否得到满足。混凝土中成分和物理约束的信息输入构成了混凝土验收标准(CAC),这些标准成为制定决策规则的基础-是/否声明明确说明了可能在现场残留混凝土的成分和物理条件。 DQO边界的一个重要概念是具体分类。通过将资源集中在最需要表征的混凝土上,可以通过彻底的数据缺口评估将具体表征的成本降至最低。与现有数据相对于CAC而言不存在或模棱两可的混凝土相比,根据现有数据与CAC的比较可以合理确定地做出“是/否”决定的混凝土受到的特征检查较少。

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