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Energy absorption and dissipation associated with mass activation and deactivation for open systems

机译:与开放系统的质量激活和停用相关的能量吸收和耗散

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Energy dissipation at the macroscopic scale, applied to large bodies, relies on using the average bulk or global properties. The normal procedure is to load/unload a uniaxial tensile specimen, and account for the difference of the area under the stress and strain curve, even though unloading does not occur in reality. The same procedure, however, is not feasible for treating the energy dissipation at the microscopic scale, applied to small bodies, where the space/time dependency of the local material properties plays a role. That is the transient character of the energy transfer between the specimen surface and surrounding can no longer be neglected. Moreover, there is no way to simulate microscopic unloading. Besides, the coupon test scheme of load/unload, an artifact, that has been used because of no other choice. Energy lost is an intrinsic process that defies empirical determination in the true sense. Incomplete homogeneous loading and/or unloading rate at all locations of the material gives rise to dissipation. This effect has been described by using the transitional function that entails multiscaling and segmentation for the simulation of material damage at the different scales. Segmented damage initiation/termination thresholds are invoked that may consist of, say pico- to nano-cracking and nano- to micro-cracking followed by micro- to macro-cracking and so on. The idealized "crack tip" is used to model the sink and source that can absorb and dissipate energy, respectively. The mass surrounding the crack tip is said to be activated by direct-absorption of energy and deactivated by self-dissipation of energy. The threshold for each scale range is assumed to depend on the square of the crack tip velocity (a) over dot(2) and mass densities M-down arrow up arrow and M-down arrow up arrow such that W = M(down arrow up arrow)a(down arrow up arrow)(2), and F = M(down arrow up arrow)a(down arrow up arrow)(2). The quantities W and F are referred to, respectively, as the direct-absorption and self-dissipation energy density. They fluctuate in time and determine whether the surrounding crack tip field of inhomogeneity is expanding or contracting. Singularity representation is used to capture the character of the crack tip field strength while scaling is reflected by the characteristic length. Demonstrated will be a pico/ nano/ micro/ macro fatigue cracking model of a 2024-T3 aluminum panel. Only the undamaged material properties are employed. Time degradation of the pi co/ nano/ micro/ macro material structure behavior is derived by using nine scale transitional physical parameters: three for the picoano range (mu*(pia), sigma*(pia), d*(pia)), three for the nanolmicro range (mu*(na/mi), sigma*(na/mi), d*(na/mi)) and three for the micro/macro range (mu*(mi/ma), sigma*(mi/ma), d*(mi/ma)). The subscripts pi, na, mi, and ma designate, respectively, pica, nano, micro, and macro. Only the ratios of two successive scale sensitive parameters need to be known. The time dependent physical parameters at the lower scale are implicit and needed only for analytical continuation. More specifically, the transitional character of picocracks, nanocracks, microcracks, and macrocracks; are determined from the specified life expectancy of time arrow according to pico -> nano -> micro -> macro with the respective singularity strength of lambda given by 1.25/1.00/0.75/0.50. Recall that lambda = 0.5 corresponds to the inverse square root r(-0.5) in fracture mechanics with r being the distance from the macrocrack tip. The microcrack, nanocrack, and picocrack tips are assigned with the singularities r(-0.75) and r(-1.00) and r(-1.25), respectively. The time of arrow in years will depend on the problem definition. Progressive damage is assumed to occur in the direction of pico -> nano -> micro -> macro. The same scheme is applied to the fatigue damage of a 2024-T3 panel with a total life time of 18.5(+) to 20 years that may be distributed over the p
机译:应用于大型物体的宏观尺度上的能量耗散依赖于使用平均体积或整体属性。正常程序是加载/卸载单轴拉伸试样,并考虑应力和应变曲线下面积的差异,即使实际上并没有发生卸载。然而,相同的方法对于处理微观尺度上的能量耗散是不可行的,这些能量耗散适用于小型物体,其中局部材料属性的时空依赖性起着作用。那就是样品表面与周围环境之间能量转移的瞬态特性将不再被忽略。而且,没有办法模拟微观卸载。此外,由于没有其他选择,因此使用了加载/卸载(工件)的优惠券测试方案。能量损失是一个内在的过程,在真实意义上无视经验的确定。在材料的所有位置上均一的不均匀加载和/或卸载速率会导致耗散。已经通过使用过渡函数描述了这种效果,该过渡函数需要多尺度和分段来模拟不同尺度下的材料损坏。调用分段的损坏开始/终止阈值,该阈值可能包括皮克级至纳米级裂纹和纳米级至微级裂纹,然后是微级至宏观级裂纹等。理想化的“裂纹尖端”用于分别模拟可以吸收和耗散能量的汇和源。据称,裂纹尖端周围的质量是通过直接吸收能量而激活的,而由于能量的自耗散而失活的。假定每个尺度范围的阈值取决于点(2)上裂纹尖端速度(a)的平方和质量密度M-向下箭头向上箭头和M-向下箭头向上箭头,从而W = M(向下箭头向上箭头)a(向下箭头向上箭头)(2),并且F = M(向下箭头向上箭头)a(向下箭头向上箭头)(2)。量W和F分别称为直接吸收和自耗散能量密度。它们随时间波动,并确定周围的非均匀裂纹尖端场是在扩展还是在收缩。奇异性表示用于捕获裂纹尖端场强的特征,而缩放则由特征长度反映出来。展示的是2024-T3铝面板的皮克/纳米/微/宏观疲劳裂纹模型。仅采用未损坏的材料特性。 pi co /纳米/微观/宏观材料结构行为的时间退化是通过使用九个标度过渡物理参数得出的:三个用于皮克/纳米范围(mu *(pi / na),sigma *(pi / na),d *(pi / na)),三个用于纳微米范围(mu *(na / mi),sigma *(na / mi),d *(na / mi)),三个用于微米/宏范围(mu *( mi / ma),sigma *(mi / ma),d *(mi / ma))。下标pi,na,mi和ma分别表示pica,nano,micro和macro。仅需要知道两个连续的比例敏感参数的比率。较低级别的时间相关物理参数是隐式的,仅在分析连续性时才需要。更具体地说,皮裂纹,纳米裂纹,微裂纹和宏观裂纹的过渡特性;是根据pico-> nano-> micro-> macro从时间箭头的指定预期寿命中确定的,λ的奇异强度分别为1.25 / 1.00 / 0.75 / 0.50。回想一下,λ= 0.5对应于断裂力学的平方根倒数r(-0.5),其中r是距大裂纹尖端的距离。微裂纹,纳米裂纹和皮裂纹尖端分别具有奇异性r(-0.75)和r(-1.00)和r(-1.25)。以年为单位的箭头时间取决于问题的定义。假定在pico-> nano-> micro-> macro方向上发生渐进式损坏。相同的方案适用于2024-T3面板的疲劳损伤,其总寿命为18.5(+)到20年,可以分配给p

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