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Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters最新文献

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Equivalent Energy Absorption (EEA) - A Methodology for Improved Automotive Crash & Safety Design 等效能量吸收(EEA)——一种改进汽车碰撞与安全设计的方法
Pub Date : 2021-11-01 DOI: 10.1115/imece2021-70137
Peddi Sai Rama Narayana, R. Prakash, S. Gunti, Kanugula Raghu
Safety norms across the world are becoming more and more stringent posing new challenges to achieve lightweight vehicle structures. Structures made of Advanced/Ultra high strength steels (AHSS) play a vital role in meeting the vehicle safety targets, by absorbing large amounts of impact energy, as well as by withstanding higher impact loads that occur due to vehicle collisions. Safety simulations usually take longer solution times due to their complexity and nonlinear nature. Engineers often encounter with a problem of quick evaluation of safety performance by using different grades of materials to optimize the weight & cost. In this paper, a new methodology - Equivalent Energy Absorption (EEA) has been proposed to do a quick trade-off study on performance vs weight for various thickness and material combinations. A relationship is established between the gauge and grade of a component to derive an equivalent safety performance so that engineers can make quick decisions by conducting minimal number of simulations. a simple rectangular crush box was considered for study to assess the Energy Absorption (EA) with various material and thickness combinations. A Design of Experiments (DOE) study was done using simulations with many numbers of material grades and gauges to construct a 3D Response Surface between gauge, grade & EA parameters to understand the relationship between each of these parameters. A case study has been discussed in the paper about application of this methodology on a vehicle to evaluate its safety performance. It has been found that more than 80% evaluation time is reduced by using this methodology.
世界各国的安全标准越来越严格,为实现汽车结构的轻量化提出了新的挑战。由先进/超高强度钢(AHSS)制成的结构通过吸收大量的冲击能量,以及承受由于车辆碰撞而产生的更高的冲击载荷,在满足车辆安全目标方面发挥着至关重要的作用。安全仿真由于其复杂性和非线性特性,通常需要较长的求解时间。工程师经常遇到的问题是,如何通过使用不同等级的材料来优化重量和成本来快速评估安全性能。在本文中,提出了一种新的方法-等效能量吸收(EEA),用于快速权衡各种厚度和材料组合的性能与重量。建立了元件的规格和等级之间的关系,以获得等效的安全性能,以便工程师可以通过进行最少数量的模拟来快速做出决策。以一个简单的矩形挤压箱为研究对象,研究了不同材料和厚度组合的吸能性能。实验设计(DOE)研究使用大量材料等级和量具进行模拟,构建量具、等级和EA参数之间的3D响应面,以了解这些参数之间的关系。本文以某汽车为例,讨论了该方法在汽车安全性能评价中的应用。研究发现,使用该方法可减少80%以上的评估时间。
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引用次数: 1
Fatigue Crack Growth Prognosis With the Particle Filter and On-Line Guided Wave Structural Monitoring Data 基于粒子滤波和在线导波结构监测数据的疲劳裂纹扩展预测
Pub Date : 2021-11-01 DOI: 10.1115/imece2021-73504
Jian Chen, S. Yuan, Lei Qiu, Yuanqiang Ren
Prognostics and health management (PHM) techniques have been widely studied in recent years to increase reliability, availability, safety, and reducing maintenance costs of safe-critical systems, like aircraft and power plants. In these systems, fatigue cracking is still one of the most widespread problems affecting structural safety. However, it is difficult to determine the structure’s fatigue life of an individual system due to uncertainties arising from various sources such as intrinsic material properties, loading, and environmental factors. Even fatigue lives of the same specimens under laboratory tests have large dispersion. To deal with this problem, this paper introduces a fatigue crack growth prognosis method with the particle filter (PF) and on-line guided wave structural health monitoring (SHM) data. The guided wave-based SHM technique is adopted for on-line monitoring the presence and size of the fatigue crack. Besides, the monitored data is sequentially combined for correcting a physical fatigue crack growth model within the PF algorithm. Finally, the data of the fatigue tests of the hole-edge crack is used for demonstrating the proposed method.
近年来,预测和健康管理(PHM)技术得到了广泛的研究,以提高飞机和发电厂等安全关键系统的可靠性、可用性、安全性和降低维护成本。在这些体系中,疲劳开裂仍然是影响结构安全的最普遍问题之一。然而,由于各种来源的不确定性,如材料的固有特性、载荷和环境因素,很难确定单个系统的结构疲劳寿命。即使在实验室试验中,同一试样的疲劳寿命也存在较大的离散性。针对这一问题,提出了一种基于粒子滤波(PF)和在线导波结构健康监测(SHM)数据的疲劳裂纹扩展预测方法。采用基于导波的SHM技术对疲劳裂纹的存在和尺寸进行在线监测。此外,将监测数据按顺序组合,在PF算法中修正物理疲劳裂纹扩展模型。最后,用孔边裂纹的疲劳试验数据对所提出的方法进行了验证。
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引用次数: 0
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Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters
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