利用共振微泡实现声空化：时域分析
Acoustic Cavitation using Resonating Micro-Bubbles. Analysis in the Time-Domain
AI总结：
本文用时域积分方程与渐近分析证明，低密度、低体积模量微泡可表现为 Dirac 型点状散射体并产生 Minnaert 共振，从而调控近场压力以服务声空化。
摘要：
我们研究存在微泡时的时域声波传播。该微泡的特征在于其质量密度和体积模量与背景真空相比都非常小。目标是估算在非常靠近微泡（距离与微泡半径成比例）处产生的压力大小。我们表明，在这一很小距离处，主导场类似于由点状障碍物产生的波，该障碍物在形式上被建模为支撑在微泡位置处的 Dirac 型非均匀性，并以微泡与背景材料之间的对比度作为散射系数。由此得出结论，我们可以调节微泡的材料属性，使其附近的压力达到所需大小。这种设计可能有助于实现声空化，因为在声空化中需要足够但不过量的压力来消除不需要的异常。数学分析采用时域积分方程和渐近分析技术完成。这里一个众所周知的特征是，微泡与背景之间的对比尺度会在时谐区域产生共振（主要是 Minnaert 共振）。这些临界尺度以及所产生的共振也反映在声波的时域估算中。特别是，只有借助此类共振微泡，才可能在微泡位置附近达到所需的压力大小。
英文摘要：
We study the time-domain acoustic wave propagation in the presence of a micro-bubble. This micro-bubble is characterized by a mass density and bulk modulus which are both very small as compared to the ones of the background vacuum. The goal is to estimate the amount of pressure that is created very near (at a distance proportional to the radius of the bubble) to the bubble. We show that, at that small distance, the dominating field is reminiscent to the wave created by a point-like obstacle modeled formally by a Dirac-like heterogeneity with support at the location of the bubble and the contrast between the bubble and background material as the scattering coefficient. As a conclusion, we can tune the bubbles material properties so that the pressure near it reaches a desired amount. Such design might be useful in the purpose of acoustic cavitation where one needs enough, but not too much, pressure to eliminate unwanted anomalies. The mathematical analysis is done using time-domain integral equations and asymptotic analysis techniques. A well known feature here is that the contrasting scales between the bubble and the background generate resonances (mainly the Minnaert one) in the time-harmonic regime. Such critical scales, and the generated resonances, are also reflected in the time-domain estimation of the acoustic wave. In particular, reaching the desired amount of pressure near the location of the bubble is possible only with such resonating bubbles.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
