Pressure measured from the cardiovascular system is widely used to diagnose disease. Pressure reconstruction methods are increasingly of interest with the development of 4D flow magnetic resonance imaging (MRI) which noninvasively measures time-resolved velocity fields in-vivo. However, several error sources and limitations inherent to in...
Estimating the probability density function (PDF) of the random motion of particles has many applications. For example, measuring diffusion, rheology, temperature, Reynolds stresses in turbulent flows, and uncertainty in velocity measurements. Current methods based on cross-correlation (CC) of image ensembles estimate an assumed Gaussian PDF's...
Autoinjectors are drug delivery medical devices for self-administered injection of biopharmaceuticals. Even though the working principle of single-spring-actuated autoinjectors is similar, differences in device design can affect the functionality and performance. From an engineering point of view, this study investigates the performance differences of two...
For cancer to metastasize, tumor cells must invade the local tissue and grow and proliferate once they arrive. Tumor cell heterogeneity, the presence of multiple types of cancer cells within a tumor, can increase cell proliferation and invasion through interactions, increasing the potential for metastasis....
This article presents a method for three-dimensional confocal microscopy to study the kinematics of nanometer-sized molecules and particles that are of great interest to a wide range of biological systems and cellular mechanics but have heretofore been obscured by limitations in measurement technology. The correlation-based...
PIV uncertainty quantification is important for comparison with CFD simulations and engineering design, but is challenging due to the complex non-linear measurement chain which involves a large number of parameters. Multiple assessments show that none of the current methods can reliably predict the actual uncertainty...
We propose an improved density integration methodology for Background Oriented Schlieren (BOS) measurements that overcomes the noise sensitivity of the commonly used Poisson solver. The method employs a weighted least-squares (WLS) optimization of the 2D integration of the density gradient field by solving an over-determined...
We present an uncertainty quantification methodology for density estimation from Background-Oriented Schlieren (BOS) measurements, in order to provide local, instantaneous, a posteriori uncertainty bounds on each density measurement in the field of view. Displacement uncertainty quantification algorithms from cross-correlation-based particle image velocimetry are used to...
We present a ray tracing image generation methodology for rendering realistic images of particle image velocimetry (PIV) and background oriented schlieren (BOS) experiments in the presence of density/refractive index gradients. This methodology enables the simulation of experiments for experimental design, error, and uncertainty analysis. Images...
Background-Oriented Schlieren (BOS) is used to measure fluid density from the apparent distortion of a target dot pattern. Here, we propose a new displacement estimation methodology based on tracking individual dots on the pattern as opposed to conventional cross-correlation algorithms. As dot patterns used in...