Sensing Dense Particulate Materials
Sensing Dense Particulate Materials
批准号:
EP/V012436/1
负责人:
Artur Gower
金额:
$29.68万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Thousands of years ago, early Mesopotamian people discovered that a mixture of mud and straw creates strong durable buildings, what we call today a composite material. Composites are far better than the sum of their parts, for example they can be stronger and cheaper. Similar experiments with mixing fluids and gases led to the discovery of complex fluids. Composites, complex fluids, and powders can all be examples of particulate materials. These materials led to advances in food science and healthcare (emulsions, colloids, powders); automobile, aerospace, and construction (composites, cement), among many others.Although these materials are highly valuable, we do not have accurate and simple ways to measure their structure. This is due to their complex microstructure, which is a random mix of different types of particles. However, measuring is the first step to automation and perfecting any product.When using a powder for a chemical reaction, or producing an emulsion, the particles will constantly change size and properties. To automate these processes, we need to monitor the particle properties. In many cases the particle properties are simply unknown. For example, the pores (which are a type of particle) in bones. Measuring these pores would help diagnose and treat osteoporosis.The end goal is to develop new sensing methods for dense particulates using ultrasound. To achieve this the first step is to understand how a sound wave reflects from these materials? To develop new sensing methods requires a team with engineers and mathematicians working together to develop: the maths of sound waves, consider how these sensors will be installed in industry, and use machine learning to deal with the complex microstructure of particulate materials.
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A model to validate effective waves in random particulate media: spherical symmetry
验证随机颗粒介质中有效波的模型:球对称性
DOI:
10.1098/rspa.2023.0444
发表时间:
2023
期刊:
Mathematical, Physical and Engineering Sciences
影响因子:
--
作者:
[Gower A]
通讯作者:
Gower A
A unified framework for linear thermo-visco-elastic wave propagation including the effects of stress-relaxation
线性热粘弹性波传播的统一框架,包括应力松弛的影响
DOI:
10.1098/rspa.2022.0193
发表时间:
2022
期刊:
Mathematical, Physical and Engineering Sciences
影响因子:
--
作者:
[García Neefjes E]
通讯作者:
García Neefjes E
DOI:
10.1088/1367-2630/abdfee
发表时间:
2021
期刊:
New Journal of Physics
影响因子:
3.3
作者:
[Gower A]
通讯作者:
Gower A
Supplementary material from A unified framework for linear thermo-visco-elastic wave propagation including the effects of stress-relaxation
补充材料来自线性热粘弹性波传播的统一框架,包括应力松弛的影响
DOI:
10.6084/m9.figshare.20704074
发表时间:
2022
期刊:
影响因子:
--
作者:
[García Neefjes E]
通讯作者:
García Neefjes E
国内基金
海外基金
基于多模态融合Dense-Fusion深度学习网络预测原发性胃肠道间质瘤术后复发风险及靶向治疗获益性的研究
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批准号:--
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项目类别:面上项目
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资助金额:52万元
-
批准年份:2022
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负责人:陈韬
-
依托单位:
The formation and evolution of planetary systems in dense star clusters
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批准号:11043007
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项目类别:专项基金项目
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资助金额:10.0万元
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批准年份:2010
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负责人:柯文采
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依托单位: