Development of a continuum mechanics model of passive skeletal muscle

Skeletal muscle force evaluation is difficult to implement in a clinical setting. Muscle force is typically assessed through either manual muscle testing, isokinetic/isometric dynamometry, or electromyography (EMG). Manual muscle testing is a subjective evaluation of a patient’s ability to move voluntarily against gravity and to resist force applied by an examiner. Muscle testing using dynamometers adds accuracy by quantifying functional mechanical output of a limb. However, like manual muscle testing, dynamometry only provides estimates of the joint moment. EMG quantifies neuromuscular activation signals of individual muscles, and is used to infer muscle function. Despite the abundance of work performed to determine the degree to which EMG signals and muscle forces are related, the basic problem remains that EMG cannot provide a quantitative measurement of muscle force. Intramuscular pressure (IMP), the pressure applied by muscle fibers on interstitial fluid, has been considered as a correlate for muscle force. Numerous studies have shown that an approximately linear relationship exists between IMP and muscle force. A microsensor has recently been developed that is accurate, biocompatible, and appropriately sized for clinical use. While muscle force and pressure have been shown to be correlates, IMP has been shown to be non-uniform within the muscle. As it would not be practicable to experimentally evaluate how IMP is distributed, computational modeling may provide the means to fully evaluate IMP generation in muscles of various shapes and operating conditions. The work presented in this dissertation focuses on the development and validation of computational models of passive skeletal muscle and the evaluation of their performance for prediction of IMP. A transversly isotropic, hyperelastic, and nearly incompressible model will be evaluated along with a poroelastic model.

Assessments and Computational Simulations in Support of a Time-Varying Mass Flow Rate Measurement Technique for Pulsatile Gas Flow

This thesis covers the correction, and verification, development, and implementation of a computational fluid dynamics (CFD) model for an orifice plate meter. Past results were corrected and further expanded on with compressibility effects of acoustic waves being taken into account. One dynamic pressure difference transducer measures the time-varying differential pressure across the orifice meter. A dynamic absolute pressure measurement is also taken at the inlet of the orifice meter, along with a suitable temperature measurement of the mean flow gas. Together these three measurements allow for an incompressible CFD simulation (using a well-tested and robust model) for the cross-section independent time-varying mass flow rate through the orifice meter. The mean value of this incompressible mass flow rate is then corrected to match the mean of the measured flow rate( obtained from a Coriolis meter located up stream of the orifice meter). Even with the mean and compressibility corrections, significant differences in the measured mass flow rates at two orifice meters in a common flow stream were observed. This means that the compressibility effects associated with pulsatile gas flows is significant in the measurement of the time-varying mass flow rate. Future work (with the approach and initial runs covered here) will provide an indirect verification of the reported mass flow rate measurements.

DYNAMIC MODEL BASED STATE ESTIMATION IN A HEAVY DUTY DIESEL AFTERTREATMENT SYSTEM FOR ONBOARD DIAGNOSTICS AND CONTROLS

Estimating un-measurable states is an important component for onboard diagnostics (OBD) and control strategy development in diesel exhaust aftertreatment systems. This research focuses on the development of an Extended Kalman Filter (EKF) based state estimator for two of the main components in a diesel engine aftertreatment system: the Diesel Oxidation Catalyst (DOC) and the Selective Catalytic Reduction (SCR) catalyst. One of the key areas of interest is the performance of these estimators when the catalyzed particulate filter (CPF) is being actively regenerated. In this study, model reduction techniques were developed and used to develop reduced order models from the 1D models used to simulate the DOC and SCR. As a result of order reduction, the number of states in the estimator is reduced from 12 to 1 per element for the DOC and 12 to 2 per element for the SCR. The reduced order models were simulated on the experimental data and compared to the high fidelity model and the experimental data. The results show that the effect of eliminating the heat transfer and mass transfer coefficients are not significant on the performance of the reduced order models. This is shown by an insignificant change in the kinetic parameters between the reduced order and 1D model for simulating the experimental data. An EKF based estimator to estimate the internal states of the DOC and SCR was developed. The DOC and SCR estimators were simulated on the experimental data to show that the estimator provides improved estimation of states compared to a reduced order model. The results showed that using the temperature measurement at the DOC outlet improved the estimates of the CO , NO , NO2 and HC concentrations from the DOC. The SCR estimator was used to evaluate the effect of NH3 and NOX sensors on state estimation quality. Three sensor combinations of NOX sensor only, NH3 sensor only and both NOX and NH3 sensors were evaluated. The NOX only configuration had the worst performance, the NH3 sensor only configuration was in the middle and both the NOX and NH3 sensor combination provided the best performance.

Development of measurement and modeling techniques to quantify atmospheric deposition of persistent, bioaccumulative and toxic chemicals in the Great Lakes

Measurement and modeling techniques were developed to improve over-water gaseous air-water exchange measurements for persistent bioaccumulative and toxic chemicals (PBTs). Analytical methods were applied to atmospheric measurements of hexachlorobenzene (HCB), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs). Additionally, the sampling and analytical methods are well suited to study semivolatile organic compounds (SOCs) in air with applications related to secondary organic aerosol formation, urban, and indoor air quality. A novel gas-phase cleanup method is described for use with thermal desorption methods for analysis of atmospheric SOCs using multicapillary denuders. The cleanup selectively removed hydrogen-bonding chemicals from samples, including much of the background matrix of oxidized organic compounds in ambient air, and thereby improved precision and method detection limits for nonpolar analytes. A model is presented that predicts gas collection efficiency and particle collection artifact for SOCs in multicapillary denuders using polydimethylsiloxane (PDMS) sorbent. An approach is presented to estimate the equilibrium PDMS-gas partition coefficient (Kpdms) from an Abraham solvation parameter model for any SOC. A high flow rate (300 L min-1) multicapillary denuder was designed for measurement of trace atmospheric SOCs. Overall method precision and detection limits were determined using field duplicates and compared to the conventional high-volume sampler method. The high-flow denuder is an alternative to high-volume or passive samplers when separation of gas and particle-associated SOCs upstream of a filter and short sample collection time are advantageous. A Lagrangian internal boundary layer transport exchange (IBLTE) Model is described. The model predicts the near-surface variation in several quantities with fetch in coastal, offshore flow: 1) modification in potential temperature and gas mixing ratio, 2) surface fluxes of sensible heat, water vapor, and trace gases using the NOAA COARE Bulk Algorithm and Gas Transfer Model, 3) vertical gradients in potential temperature and mixing ratio. The model was applied to interpret micrometeorological measurements of air-water exchange flux of HCB and several PCB congeners in Lake Superior. The IBLTE Model can be applied to any scalar, including water vapor, carbon dioxide, dimethyl sulfide, and other scalar quantities of interest with respect to hydrology, climate, and ecosystem science.