Cortical control during walking is most pronounced when the person is perturbed. Although seated locomotor tasks such as cycling or recumbent stepping improve walking performance, the electrocortical correlates of perturbed seated tasks have not been studied in detail. The primary purpose of this research was to quantify cortical and muscular responses to mechanical perturbations during recumbent stepping. We also aimed to quantify possible differences between young and older adults' responses to perturbed stepping. A secondary aim of this research was to determine the accuracy of electroencephalography (EEG) source imaging to interpret the electrocortical findings adequately. We hypothesized that both young and older adults would adapt to the perturbations by reducing their movement errors and reducing the anterior cingulate electrocortical activity. We also hypothesized that older adults would co-contract their agonist and antagonist muscles more than young adults in response to perturbations. Such stronger co-contraction would indicate older adults would have weaker corticomuscular connectivity in response to perturbations than young adults. Seventeen young adults and eleven older adults completed four perturbed arms and leg stepping tasks. We perturbed the stepping with brief 200ms increased movement resistance using a controllable servomotor on our recumbent stepper. We asked subjects to step smoothly, use both arms and legs and follow the visual pacing cue set at 60 steps per minute. We recorded brain activity with high-density EEG with 128 electrodes, muscular activity with 16 electromyography (EMG) sensors, and stepping kinematics using the servomotor's encoder. We quantified temporal and spatial motor errors from the stepping kinematics data. We used a novel post-processing approach to reject noise from EEG and estimated the electrocortical sources using independent component analysis and the current dipole estimation technique. We then performed a series of time-frequency analyses on the group EEG source data. We quantified EMG co-contraction for each of the perturbed and recovery steps. Finally, we used direct Directed Transfer Fucnction to determine the corticomuscular connectivity time-locked to young and older adults' perturbations. Quantifying the accuracy of source estimation showed that recording the three-dimensional EEG electrode locations would provide accurate source estimation up to a single Brodmann area. We also found that recording the precise location of the fiducials, i.e., the anatomical landmarks used to place the EEG electrodes, is critical for a reliable source estimation process. Motor errors did not show a reduction of errors with more perturbation experience for both young and older adults. Young adults showed significant theta-band (3-8 Hz) electrocortical activity locked to the perturbations at the anterior cingulate cortex, supplementary motor areas, and posterior parietal cortex. These locked spectral fluctuations decreased with more perturbation experience for the right-side perturbations and varied with perturbation timing. Older adults showed significant electrocortical activity with a wider spread of electrocortical sources in the motor and posterior parietal cortices. Older adults demonstrated more co-contracted muscle pairs than young adults, and co-contraction did not decrease with more perturbation experience. The results show that brief perturbation during recumbent stepping does not create error-based adaptation with reduced motor errors tied to more perturbation experience. However, these perturbations cause prolonged modifications in the motor patterns even after the perturbations are removed. Modulating the perturbation timing can tune both cortical activities at specific brain areas and modify muscular co-contraction behavior in older adults.

Seismocardiography (SCG) is the measured chest surface vibrations resulting from cardiac activity. Although SCG can contain information that correlate with cardiac health, its utility may be limited by lack of understanding of the signal genesis and a variability that can mask subtle SCG changes. The current research utilized medical imaging reconstruction and finite element method (FEM) to simulate SCG by modeling the propagation of myocardial movements to the chest surface. FEM analysis provided a link between myocardial movements and the SCG signals measured at the chest surface and suggested that myocardial movement is a primary source of SCG. Increased understanding of the sources and propagation of SCG may help increase the utility of SCG as a cardiac monitoring tool. To reduce the variability of SCG measured in human subjects, unsupervised machine learning (ML) was implemented to group SCG beats into clusters with minimal intra-cluster heterogeneity. The clustering helped reduce the SCG variability and unveiled consistent relations with the respiratory phases and SCG morphology. This clustering reduced noise in calculating signal features and provided additional useful features. The study also analyzed longitudinal SCG from heart failure (HF) patients in order to predict HF readmission. Here, many time- and frequency-domain SCG features were extracted. Certain features showed good correlations with readmission. Using supervised ML algorithms, high classification accuracies (up to 100%) were achieved suggesting high SCG utility for monitoring HF patients and possibly other heart conditions. Effective monitoring followed by timely intervention can lead to improved patient management and reduced mortality.

Cardiovascular disease is one of the leading causes of mortality in the world. Early detection and intervention can significantly improve disease management and patient quality of life. Current methods of evaluating cardiac function often involve history and physical examination (including stethoscope auscultation), electrocardiograms (ECG), echocardiogram imaging, computed tomography, and various blood tests. Seismocardiographic signals (SCG) are the chest surface vibrations resulting from cardiomechanical activity. SCG may be recorded using accelerometers and can be used for monitoring and predicting cardiac health. SCG's potential utility may be impeded by its spatial, postural, respiratory, and longitudinal variability. In this dissertation, the SCG variability sources are documented, resulting in changes in signal features are quantified, and optimum posture and sensor placement are discussed. Understanding SCG variability can help account for signal variability and more precise quantification of prominent SCG features that may be predictive of cardiac health. In addition, non-invasive monitoring respiration is a useful patient monitoring signal that can be performed via direct measurement of airflow utilizing a mouthpiece. In some instances, direct access to breathing airflow may be impractical or undesirable, especially in an ambulatory setting, and alternative approaches are needed. The respiratory phase can be extracted noninvasively from physiological signals such as ECG or SCG. The current study extracted respiration from several physiological signals in healthy adults and compared it with direct respiration airflow measurements. In addition, respiratory phases were extracted from SCG signals of HF patients, and results from traditional signal processing techniques and machine learning approaches were compared. The study resulted in a better understanding of the sources of SCG variability and alternative approaches to respiratory phase detection. These findings can lead to the development of improved non-invasive, low-cost methods for the management of cardiopulmonary conditions, timely intervention, and improved quality of life of patients.

The United States government has set 2050 as the target for net-zero greenhouse gas emissions due to their increasing levels and the subsequent rise in global temperatures. To meet this target, there has been renewed interest in the combustion of high-energy biofuels that could combat these issues. Thus, the Department of Energy started the Co-Optimization of Fuels and Engines program to find bioderived blendstocks that can harmonize with current and future generation engines to increase power and efficiency, all while reducing overall emissions. As part of this program, it is crucial to understand the combustion of these fuels at the temperatures and pressures internal combustion engines operate at. Therefore, the oxidation and pyrolysis of several advanced biofuels—cyclopentanone, prenol, 1-pentene and trans-2 pentene, and methyl propyl ether—have been studied in a shock tube reactor to quantify some of their fundamental combustion properties. Measurements include ignition delay times and time-resolved species concentrations, including that of fuel decomposition and formation of intermediate species such as carbon monoxide and ethylene. These measurements are useful for validating and updating chemical kinetic mechanisms that provide the chemistry input into computational fluid dynamic codes. This study's measured data are compared to the predictions of the most recent literature chemical kinetic mechanisms for each fuel. When appropriate, sensitivity analyses were conducted to highlight reactions sensitive to the conducted measurements, and some reaction rate modifications were made.

Combination of topology and material could play an important role in giving rise to nontraditional behavior in mechanical structures and is a typical strategy in nature. Topology is concerned with the geometrical and spatial properties of the objects, which are preserved under continues mechanical deformation of the object such as stretching, bending, twisting, etc. In this work, we focus on structures based on fish scale inspired surface topology. The utilized idea for surface topology is a bioinspired design on the substrate of biological scale-covered systems. Scales are a path breaking evolutionary adaptation that accompanied vertebrate evolution for the past 500 million years. Fish scales are inherently lightweight with diverse shapes, sizes, materials, and distribution, and they provide remarkable architecture-material enhancement, typical of metamaterials. Here we provide a perspective on mechanical behavior of fish scale inspired structures and quantify the origins of some of their striking mechanical properties that include nonlinear and directional strain stiffening in both bending and twisting, dual nature of friction which combines both resistance as well as adding stiffness to motion. We will provide derivation of mathematical laws that govern structure-property relationships that can help guide design. The response of biomimetic scale under twisting, bending and combined load is tailorable through the geometric arrangement and orientation of the scales. Also, the analytical models have been validated by the finite element analysis. We outline and explain the progress in understanding the complexities of these structures in global and local deformation modes and conclude by offering future perspectives and challenges.

Biological structures have inspired synthetic materials with unparalleled performances such as ultra-lightweight design, tunable elasticity, camouflaging, and antifouling. Among biological structures, exoskeletal scales that cover the exterior surfaces of fishes, fur, and many reptiles. These exoskeletal scales had appeared in the earliest stages of evolution of complex multicellular life and continued their existence in spite of millions of years of evolutionary pressures. This makes them an attractive candidate for biomimicry to produce high performance multifunctional materials with applications to soft robotics, wearables, energy efficient smart skins, antifouling surfaces and on-demand tunable materials. Canonically speaking, biomimetic samples can be fabricated by partially embedding stiffer plate-like segments on softer substrates to create a bi-material system, with overlapping scales. The bending behavior of this system has been carried out using assumption of periodic engagement even after scales contact. This is true only under the most ideal loading conditions or if the scales are extremely dense akin to a continuum assumption on the scales. Here, we develop a rigorous theory with computational validation of key parameters which relaxes these restrictions. We also present an analytical study to demonstrate a bioinspired mechanical pathway to tailor the elasticity of cantilevered beams as an alternative to traditional functional gradation. In addition, we explore for the first time the dynamic behavior of these scales during oscillatory motion using analytical models, supported by finite element (FE) computations. Finally, inspired by the hypothesis that fur surfaces, which consist of plate-like topography, significantly change the initial stages of biofouling, we shed light on the fundamentals of this process by reducing the fur to a scale-covered elastica under flow with biomass suspensions. A FE coupled nonlinear deposition-large deflection model of the system is developed.

Monitoring intracranial pressure (ICP) is a standard diagnostic tool for various neurological conditions such as head injury, ruptured aneurysms, intracerebral and intracranial hemorrhage, and hydrocephalus. Currently, ICP monitoring relies on invasive pressure measurements. These include intraventricular catheter, subdural screw, epidural sensor, and lumbar puncture. Invasive methods pose the risk of infection and hemorrhage, are expensive, and require special clinical skills. A noninvasive method that is reliable, simple to use, low-cost, and provides easily interpretable results can help avoid the complications associated with the invasive methods. This study proposes a novel method for noninvasive ICP monitoring using tympanic membrane pulsation (TMp). ICP signals propagate through the cochlear aqueduct, cochlea, and middle ear bones to reach the tympanic membrane where it can be observed as a TMp signal. Therefore, TMp may provide useful information about ICP and possibly intracranial compliance. To investigate the utility of the proposed approach, TMp signals were acquired from 15 healthy subjects. Subjects performed specific maneuvers that are known to induce ICP changes. Maneuvers included head-down-tilt, head-up-tilt, and hyperventilation. A custom-made system utilizing a stethoscope headset and a pressure transducer was used to measure TMp signals. Morphological changes in the TMp waveform were observed when subjects underwent ICP changes. Waveform changes included rise-decay patterns and high-frequency components. The study results suggest that TMp waveform measurement and analysis may offer an inexpensive, non-invasive, accurate tool for the detection and monitoring of ICP. More studies are needed in larger sample sizes and patients with elevated ICP to further investigate the utility of the proposed method.

Unexpected main bearing failure on a wind turbine causes unscheduled maintenance and increased operation costs (mainly due to crane, parts, labor, and production loss). Unfortunately, historical data indicates that failure can happen far earlier than the component designed lives (due to manufacturing problems, for example). For the legacy fleet, which composes the majority of the installed basis, fatigue has become a major issue. Although bearing fatigue can be expressed with physics-informed models, they often inherent large uncertainties due to operation and unknown lubricant degradation mechanism. Apart from the unknown physics of failure, additional uncertainties associated with the grease that surrounds the bearing can be listed as the lack of fidelity in the observations due to visual inspections, and quality variation from one batch to the other. As opposed to detailed laboratory analysis, grease visual inspection can lead to large uncertainties in characterization of grease condition (although visual inspection can be cost and time effective). Eventually, a main bearing fatigue model that can quantify the model-form uncertainty (unknown grease degradation mechanism), observation uncertainty (visual inspections), and input uncertainty (grease quality variation), becomes a necessity for managing and optimizing maintenance of aging wind turbines. In this research, we investigate the effect of lubricant state on main bearing fatigue. After we demonstrate the importance of modeling grease, we propose a novel modeling approach that is hybrid and designed to merge physics-informed and data-driven layers within deep neural networks. The result is a cumulative damage model where the physics-informed layers are used to model the relatively well-understood physics (bearing fatigue damage accumulation) and the data-driven layers account for the hard to model components (i.e., grease degradation). In addition, we introduce a trainable classifier tailored for our application, to map continuous grease damage into discrete visual inspection rankings. Finally, we improve our model to estimate the variation due to lubricant quality, and provide probabilistic life estimations for the component.

Congenital Heart Disease (CHD) occurs in about 1\% (40,000) of newborn babies each year in the United States alone. About 10.9\% (960) of whom suffer from Hypoplastic Left Heart Syndrome (HLHS) - a subset of CHD where children are born with a single-ventricle (SV). A series of three surgeries are carried out to correct HLHS culminating in the Fontan procedure where venous flow returns passively to the lungs. The current configuration for the Fontan results in elevated Central Venous Pressure (CVP), inadequate ventricular preload, and elevated Pulmonary Vascular Resistance (PVR) leading to a barrage of disease. To alleviate these complications, a 'self-powered' Fontan is suggested where an Injection Jet Shunt (IJS) emanating from the aorta is anastomosed to each pulmonary artery. The IJS attempts to reduce the central venous pressure, increase preload, and aid in pulmonary arterial growth by entraining the flow with a high energy source provided by the aorta. Previous computational studies on this concept with rigid vessel walls show mild success, but not enough to be clinically relevant. It is hypothesized that vessel wall deformation may play an important role in enhancing the jet effect to provide a larger exit area for the flow to diffuse while also being more physiologically accurate. A multiscale 0D-3D tightly coupled Computational Fluid Dynamics (CFD) with Fluid-Structure Interaction (FSI) model is developed to investigate the efficacy of the proposed 'self-powered' Fontan modification. Several runs are made varying the PVR to investigate the sensitivity of IVC pressure on PVR. IVC pressure decreased by 2.41 mmHg while the rigid wall study decreased the IVC pressure by 2.88 mmHg. It is shown that IVC pressure is highly sensitive to changes in PVR and modifications to the Fontan procedure should target aiding pulmonary arterial growth as it is the main indicator of Fontan success.

The high heat transfer capabilities of impinging jets have led to their widespread use in industrial applications, such as gas turbine cooling. These impinging jets are usually manufactured on the walls of super-alloy metals and are influenced by being positioned with a confined setting. Studies have been shown to enhance the heat transfer of impinging jets by fluctuating the flow which will be analyzed in this project with two designs. The first design is a self-sustaining stationary fluidic oscillator that causes a sweeping motion jet to impinge on the surface. This is investigated using Particle Image Velocimetry (PIV) to study the flow field as well as copper- block heated surface to study the heat transfer. The second design involves pulsating the jet through a rotating disk that opens and closes the jet hole, providing a pulsing impingement on the surface. This is examined using hot-wire anemometry for understanding the fluid mechanics and copper-block heated surface to study the heat transfer. Both configurations are tested at a constant Reynolds number of 30,000 with the oscillator tested at normalized jet-to-surface spacings of 3, 4, 6 and the pulsing mechanism tested at jet-to-surface spacing of 3. The results for the fluidic oscillator indicate: Reynolds stress profiles of the jet demonstrated elevated levels of mixing for the fluidic oscillator; heat transfer enhancement was seen in some cases; a confined jet does worse than an unconfined case; and the oscillator's heat removal performed best at lower jet-to- surface spacings. The results for the pulsing mechanism indicate: lower frequencies displayed high turbulence right at the exit of the jet as well as the jet-to-surface spacing of 3; the duty cycle parameter strongly influences the heat transfer results; and heat transfer enhancement was seen for a variation of frequencies.