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.

这个工程研究启动（ERI）奖支持的研究，将重点放在改善介电混合模型用于估计粗骨料混合物的相对介电常数。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）捕获的体相对介电常数（体电材料特性）联系起来。这些介电混合模型反过来又使工程师能够从GPR数据中估计诸如含水量、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的相对介电常数测量的梯度范围从较小的颗粒到较大的颗粒，这将关闭现有的差距在文献中的颗粒级配对相对介电常数测量的影响。从这些数据中，一个新的介电混合模型适用于粗骨料将被创建。此外，这笔资金将允许史密斯学院的学生与女孩公司尤里卡！该计划将具有协同效益，使史密斯学院的学生在指导作用，以初中和高中女生在工程和干。同时，预计尤里卡！该项目的学生将受到工程专业大学年龄女性的启发。为了实现产生用于粗骨料的改进的介电混合模型的目标，将进行大箱测试（大约1立方米规模）以产生数据集，从而开发新的介电混合模型。这些箱形试验将考虑颗粒大小从砂-粉土混合物（现有模型应能很好地模拟）到鹅卵石-砾石混合物（现有模型预计模拟效果不佳）的各种材料。将在干燥、饱和和部分饱和条件下对样本进行试验。这项工作有三个主要目标。第一个目标是建立标本制备的常规做法和方法的可重复性，以产生最高质量的标本。第二个目标将是创建一个相对介电常数值的数据集，涵盖了广泛的骨料级配，密度和含水量。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知识价值和更广泛的影响审查标准进行评估，被认为值得支持。