ERI: Dielectric Mixing Models for Coarse Aggregate

ERI：粗骨料的介电混合模型

• 批准号: 2301588
• 负责人: Aaron Rubin
• 金额: $ 14.93万
• 依托单位: Smith College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2301588&HistoricalAwards=false
• 关键词: ERI; Dielectric; Mixing; Models; Coarse

This Engineering Research Initiation (ERI) award supports research that will focus on improving dielectric mixing models used to estimate the relative permittivity of coarse aggregate mixes. Dielectric mixing models relate the physical characteristics of soil or aggregate (the water, air, and solid particles) to the bulk relative permittivity (bulk electrical material property) captured by ground penetrating radar (GPR). These dielectric mixing models in turn are what allow engineers to estimate properties such as water content, saturation, density, or object depth from GPR data. The research will investigate the effect of particle gradation on relative permittivity measurements by creating a high-quality open data set of relative permittivity measurements on gradations ranging from smaller particles to larger particles which will close an existing gap in the literature. From these data a new dielectric mixing model suitable for coarse aggregate will be created. In addition, the funding will allow for Smith College students to work with the Girls Inc Eureka! program which will have the synergistic benefit of putting Smith College students in a mentoring role to middle school and high school girls in engineering and STEM. Simultaneously, it is anticipated that the Eureka! program students will be inspired by the college-aged women in engineering. In order to achieve the goal of producing an improved dielectric mixing model for coarse aggregates, large box tests (approximately 1 cubic meter in scale) will be conducted to produce a data set to develop a new dielectric mixing model. These box tests will consider a variety of materials with particle sizes ranging from sand-silt mixtures (which existing models should model well) up to cobble-gravel mixtures (which existing models are anticipated to model poorly). Specimens will be tested under dry, saturated, and partially saturated conditions. The work has three main objectives. The first objective is to establish the repeatability of common practices for specimen preparation and methods that produce the highest quality specimens. The second objective will be to create the data set of relative permittivity values covering a wide range of aggregate gradations, density, and water content. The third objective is to create and verify the dielectric mixing model suitable for coarse aggregates.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该工程研究启动 (ERI) 奖项支持的研究重点是改进用于估计粗骨料混合物相对介电常数的介电混合模型。介电混合模型将土壤或骨料（水、空气和固体颗粒）的物理特性与探地雷达 (GPR) 捕获的体积相对介电常数（体积电材料特性）联系起来。这些介电混合模型又使工程师能够根据探地雷达数据估计含水量、饱和度、密度或物体深度等属性。该研究将通过创建一个高质量的开放数据集来研究颗粒分级对相对介电常数测量的影响，该数据集对从小颗粒到较大颗粒的分级范围进行相对介电常数测量，这将弥补文献中现有的空白。根据这些数据，将创建适用于粗骨料的新介电混合模型。此外，这笔资金还将允许史密斯学院的学生与 Girls Inc Eureka! 合作。该计划将产生协同效益，让史密斯学院的学生在工程和 STEM 领域为初中和高中女生提供指导。同时，预计尤里卡！项目学生将受到工程领域大学年龄女性的启发。为了实现改进粗骨料介电混合模型的目标，将进行大箱试验（规模约为1立方米）以产生数据集以开发新的介电混合模型。这些箱式测试将考虑各种颗粒尺寸的材料，从沙子-淤泥混合物（现有模型应该能够很好地模拟）到卵石-砾石混合物（预计现有模型模拟效果很差）。样品将在干燥、饱和和部分饱和的条件下进行测试。这项工作有三个主要目标。第一个目标是建立样本制备常见做法和生产最高质量样本的方法的可重复性。第二个目标是创建涵盖各种骨料级配、密度和含水量的相对介电常数值的数据集。第三个目标是创建和验证适用于粗骨料的介电混合模型。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。