A Design Process Centric Application of State Space Modeling as a Function of Communications and Cognitive Skills Assessments.

Humans have a reliable basic probabilistic intuition. We utilize our probabilistic intuition in many day-to-day activities such as driving. In fact any interaction that occurs in the presence of other independent actors requires some probabilistic assessment. While we are good at sorting between rare and common events, determining if these events are statistical significant is always subject to scrutiny. Quite often the bounds of statistical significance are at ends with the ‘common sense’ expectation. While our probabilistic intuition is good for first moment effects such as driving a car, throwing a football and understanding simplistic mathematical models, our probabilistic intuition fails when we need to evaluate secondary effects such as high speed turns, playing golf or understanding complex mathematical models. When our probabilistic intuition is challenged misinterpretation of results and skewed perspectives of possible outcomes will occur. The work presented in this dissertation provides a mathematical formulation that will provide a guide to when our probabilistic intuition will be challenged. This dissertation will discuss the development of the Process Failure Estimation Technique (ProFET). A multitude of potential team parameters could have been selected, interpersonal communication effectiveness and cognitive skill assessments seemed the most obvious first steps. This is due to the prolific discussion on communication and the general acceptance of the cognitive testing as an indicator of performance potential. The teams skill set must be variable with respect to time in order to accomplish the required objectives of each phase of the design process. ProFET develops a metric for the design process that is sensitive to the team composition and structure. This metric is applied to a domain that is traditionally devoid of objective scoring. With the use of ProFET more informed decisions on team structure and composition can be made at critical junctions of the design process. Specifically, ProFET looks at how variability propagates through the design activities as opposed to attempting to quantify the actual values of design activities, which is the focus of the majority of other design research.PhDNaval Architecture and Marine EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116679/1/jdstrick_1.pd

Flow Imaging Using MRI: Quantification and Analysis

A complex and challenging problem in flow study is to obtain quantitative flow information in opaque systems, for example, blood flow in biological systems and flow channels in chemical reactors. In this regard, MRI is superior to the conventional optical flow imaging or ultrasonic Doppler imaging. However, for high speed flows, complex flow behaviors and turbulences make it difficult to image and analyze the flows. In MR flow imaging, MR tagging technique has demonstrated its ability to simultaneously visualize motion in a sequence of images. Moreover, a quantification method, namely HARmonic Phase (HARP) analysis, can extract a dense velocity field from tagged MR image sequence with minimal manual intervention. In this work, we developed and validated two new MRI methods for quantification of very rapid flows. First, HARP was integrated with a fast MRI imaging method called SEA (Single Echo Acquisition) to image and analyze high velocity flows. Second, an improved HARP method was developed to deal with tag fading and data noise in the raw MRI data. Specifically, a regularization method that incorporates the law of flow dynamics in the HARP analysis was developed. Finally, the methods were validated using results from the computational fluid dynamics (CFD) and the conventional optimal flow imaging based on particle image velocimetry (PIV). The results demonstrated the improvement from the quantification using solely the conventional HARP method

When Cardiac Biophysics Meets Groupwise Statistics: Complementary Modelling Approaches for Patient-Specific Medicine

This habilitation manuscript contains research on biophysical and statistical modeling of the heart, as well as interactions between these two approaches

When Cardiac Biophysics Meets Groupwise Statistics: Complementary Modelling Approaches for Patient-Specific Medicine

This habilitation manuscript contains research on biophysical and statistical modeling of the heart, as well as interactions between these two approaches