Thermomechanical characterization and modeling of fast-curing polyurethane adhesives

Thermomechanical characterization and modeling of fast-curing polyurethane adhesives
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快速固化聚氨酯粘合剂的热机械表征和建模

DOI:
10.1007/s00161-019-00788-w
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发表时间:
2020
影响因子:
2.6
通讯作者:
Stammen
Stammen
中科院分区:
工程技术3区
文献类型:
--
作者:
Jennrich;Johlitz;Dilger;Stammen

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在轻量化设计和现代混合技术的背景下,结构和软粘合剂在工业应用中的重要性正在增加。因此,本文研究了一种相对柔软的聚氨酯胶粘剂,其特征在于在室温下表现出非线性粘弹性行为,并承受大变形。它非常适合在动态负载下的应用,可以补偿由不同热膨胀系数的材料产生的间隙变化。从理论上讲,所研究的单组分聚氨酯胶粘剂可以通过热固化或通过湿度固化,从而产生相同的机械特性。比较两种固化反应,湿固化比热固化慢得多。后者可以通过温度来控制,温度可以通过加热速率高达。然而,与金属相比,聚氨酯以小得多的速率传导热量,这导致粘合剂层内的高温度梯度。本文重点研究了一种快速固化聚氨酯胶粘剂的建模,考虑了热固化引起的密度和热机械材料性能的变化。因此,需要在整个热固化过程中观察材料特性,从未固化的流体到固化的橡胶材料。从长远来看,对材料行为的准确预测将最终促进固化过程的优化。
In the context of lightweight design and modern hybrid technologies, the importance of structural and soft adhesives in industrial applications is increasing. Therefore, this paper examines a relatively soft polyurethane adhesive characterized by showing nonlinear viscoelastic behavior at room temperature and enduring large deformations. It is well suited for applications under dynamic loadings and can compensate gap changes generated by materials with different thermal expansion coefficients. Theoretically, the examined one-component polyurethane adhesive can be cured either thermally or through humidity, resulting in the same mechanical characteristics. Comparing both curing reactions, humidity curing is much slower than thermal curing. The latter can be controlled through the temperature, which may be applied through heating rates of up to. However, in comparison with metals polyurethane conducts the heat with a much smaller rate which results in high temperature gradients within the adhesive layer. This paper focuses on the modeling of a fast-curing polyurethane adhesive under consideration of the changes in density and thermomechanical material properties induced by thermal curing. Therefore, the material properties need to be observed throughout the thermal curing process, from the uncured fluid to the cured rubber material. In the long term, the accurate prediction of the materials behavior will ultimately facilitate the optimization of the curing process.
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