Using Ultra Violet Light to Produce Layered Fiber Reinforced Materials Derived from Biological Sources
使用紫外线生产生物源层状纤维增强材料
基本信息
- 批准号:1537756
- 负责人:
- 金额:$ 35万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-08-15 至 2019-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The goal of this project is to study ultra violet (UV) processing as a viable pathway towards a sustainable method of manufacturing layered fiber reinforced materials derived from biological sources for structural applications. A key challenge in the processing of these biobased composite materials is that traditional thermal curing approaches cannot be employed since the constituent natural fibers, which are primarily made of cellulose and hemicellulose, start to degrade with prolonged exposure to high temperatures. UV curing is a fast, low temperature photopolymerization process that uses significantly less energy than thermal curing. If successful, the study will enable a cost-effective and greener process for making high-strength thick laminates that are highly critical for lightweighting automotive and aerospace structures. Lightweighting is tied to achieving improvements in fuel-efficiency and reducing pollution. The PIs will engage graduate and undergraduate students in this interdisciplinary research project and train them in understanding the integral role of process modeling, experimentation, optimization, and control in advanced sustainable manufacturing. The PIs will also leverage collaborations and interactions with industrial partners to broadly influence industrial practices for processing biobased composites.The specific technical objectives of the project are to, first, extract physically motivated and experimentally verified process models for UV processing of biobased composites, and then apply them in new layering, scale-up optimization and process control schemes for building thick structural parts with these materials. The basic phenomena to be characterized by the modeling and experimental efforts include: 1) the nature of the attenuation of UV intensity as it passes through the biobased resin and fiber systems, and 2) the nature of the coupled evolution of the spatially distributed cure and temperature state. The project will also investigate the potential of a stepped-concurrent curing and layering scheme that will exploit knowledge of the cure kinetics, thermal evolution and UV attenuation in these materials. The project will apply a new hybrid modeling perspective that treats the addition of layers as discrete events on the otherwise continuous physical processes involved in curing. This perspective will help generalize the scale-up optimization of the scheme with the goal of building ever-thicker parts of highest cure quality with minimal time/energy needs. The project will also address process robustness considerations via uncertainty handling in the scale-up optimization as well as with online feedback compensation.
该项目的目标是研究紫外线(UV)加工作为一种可行的途径,以可持续的方式制造用于结构应用的生物源层状纤维增强材料。这些生物基复合材料加工中的一个关键挑战是无法采用传统的热固化方法,因为主要由纤维素和半纤维素组成的天然纤维会随着长时间暴露在高温下而开始降解。 UV 固化是一种快速、低温光聚合过程,其使用的能量比热固化少得多。如果成功,该研究将为制造高强度厚层压板提供一种经济有效且更环保的工艺,这对于汽车和航空航天结构的轻量化至关重要。轻量化与提高燃油效率和减少污染息息相关。 PI 将让研究生和本科生参与这个跨学科研究项目,并培训他们了解流程建模、实验、优化和控制在先进可持续制造中的不可或缺的作用。 PI还将利用与工业合作伙伴的合作和互动,广泛影响生物基复合材料加工的工业实践。该项目的具体技术目标是,首先,提取生物基复合材料紫外加工的物理驱动和实验验证的工艺模型,然后将其应用于新的分层、放大优化和工艺控制方案中,以使用这些材料构建厚结构零件。建模和实验工作所表征的基本现象包括:1)紫外线强度穿过生物基树脂和纤维系统时衰减的本质,2)空间分布的固化和温度状态耦合演化的本质。该项目还将研究逐步并发固化和分层方案的潜力,该方案将利用这些材料的固化动力学、热演化和紫外线衰减知识。该项目将应用新的混合建模视角,将层的添加视为固化过程中涉及的连续物理过程的离散事件。这种观点将有助于推广该方案的放大优化,目标是用最少的时间/能源需求构建具有最高固化质量的更厚部件。该项目还将通过放大优化中的不确定性处理以及在线反馈补偿来解决工艺稳健性问题。
项目成果
期刊论文数量(0)
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Estimation and coordinated control for distributed parameter processes with a moving radiant actuator
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10.1016/j.jprocont.2010.04.005 - 发表时间:
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- DOI:
10.1016/j.est.2025.117056 - 发表时间:
2025-09-01 - 期刊:
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Deep reinforcement learning-based energy management system enhancement using digital twin for electric vehicles
- DOI:
10.1016/j.energy.2024.133384 - 发表时间:
2024-12-15 - 期刊:
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Yiming Ye;Bin Xu;Hanchen Wang;Jiangfeng Zhang;Benjamin Lawler;Beshah Ayalew - 通讯作者:
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Continual hybrid model learning for lithium-ion batteries
用于锂离子电池的持续混合模型学习
- DOI:
10.1016/j.est.2024.115105 - 发表时间:
2025-02-15 - 期刊:
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Probabilistic constraint tightening techniques for trajectory planning with predictive control
- DOI:
10.1016/j.jfranklin.2022.06.005 - 发表时间:
2022-08-01 - 期刊:
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Nathan Goulet;Qian Wang;Beshah Ayalew - 通讯作者:
Beshah Ayalew
Beshah Ayalew的其他文献
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{{ truncateString('Beshah Ayalew', 18)}}的其他基金
CAREER: Control of Processes Actuated with Mobile Radiant Sources
职业:控制移动辐射源驱动的过程
- 批准号:
1055254 - 财政年份:2011
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
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