Walking in old age and development of metabolic syndrome: the health, aging, and body composition study.

BACKGROUND: The specific health benefits of meeting physical activity guidelines are unclear in older adults. We examined the association between meeting, not meeting, or change in status of meeting physical activity guidelines through walking and the 5-year incidence of metabolic syndrome in older adults. METHODS: A total of 1,863 Health, Aging, and Body Composition (Health ABC) Study participants aged 70-79 were followed for 5 years (1997-1998 to 2002-2003). Four walking groups were created based on self-report during years 1 and 6: Sustained low (Year 1, <150 min/week, and year 6, <150 min/week), decreased (year 1, >150 min/week, and year 6, <150 min/week), increased (year 1, <150 min/week, and year 6, >150 min/week), and sustained high (year 1, >150 min/week, and year 6, >150 min/week). Based on the Adult Treatment Panel III (ATP III) panel guidelines, the metabolic syndrome criterion was having three of five factors: Large waist circumference, elevated blood pressure, triglycerides, blood glucose, and low high-density lipoprotein (HDL) levels. RESULTS: Compared to the sustained low group, the sustained high group had a 39% reduction in odds of incident metabolic syndrome [adjusted odds ratio (OR) = 0.61; 95% confidence interval (CI), 0.40-0.93], and a significantly lower likelihood of developing the number of metabolic syndrome risk factors that the sustained low group developed over 5 years (beta = -0.16, P = 0.04). CONCLUSIONS: Meeting or exceeding the physical activity guidelines via walking significantly reduced the odds of incident metabolic syndrome and onset of new metabolic syndrome components in older adults. This protective association was found only in individuals who sustained high levels of walking for physical activity.

Body image and body satisfaction differ by race in overweight postpartum mothers.

BACKGROUND: Body image (BI) and body satisfaction may be important in understanding weight loss behaviors, particularly during the postpartum period. We assessed these constructs among African American and white overweight postpartum women. METHODS: The sample included 162 women (73 African American and 89 white) in the intervention arm 6 months into the Active Mothers Postpartum (AMP) Study, a nutritional and physical activity weight loss intervention. BIs, self-reported using the Stunkard figure rating scale, were compared assessing mean values by race. Body satisfaction was measured using body discrepancy (BD), calculated as perceived current image minus ideal image (BD<0: desire to be heavier; BD>0: desire to be lighter). BD was assessed by race for: BD(Ideal) (current image minus the ideal image) and BD(Ideal Mother) (current image minus ideal mother image). RESULTS: Compared with white women, African American women were younger and were less likely to report being married, having any college education, or residing in households with annual incomes >$30,000 (all p < 0.01). They also had a higher mean body mass index (BMI) (p = 0.04), although perceived current BI did not differ by race (p = 0.21). African Americans had higher mean ideal (p = 0.07) and ideal mother (p = 0.001) BIs compared with whites. African Americans' mean BDs (adjusting for age, BMI, education, income, marital status, and interaction terms) were significantly lower than those of whites, indicating greater body satisfaction among African Americans (BD(Ideal): 1.7 vs. 2.3, p = 0.005; BD(Ideal Mother): 1.1 vs. 1.8, p = 0.0002). CONCLUSIONS: Racial differences exist in postpartum weight, ideal images, and body satisfaction. Healthcare providers should consider tailored messaging that accounts for these racially different perceptions and factors when designing weight loss programs for overweight mothers.

Elucidating solvent contributions to solution reactions with ab initio QM/MM methods.

Computer simulations of reaction processes in solution in general rely on the definition of a reaction coordinate and the determination of the thermodynamic changes of the system along the reaction coordinate. The reaction coordinate often is constituted of characteristic geometrical properties of the reactive solute species, while the contributions of solvent molecules are implicitly included in the thermodynamics of the solute degrees of freedoms. However, solvent dynamics can provide the driving force for the reaction process, and in such cases explicit description of the solvent contribution in the free energy of the reaction process becomes necessary. We report here a method that can be used to analyze the solvent contributions to the reaction activation free energies from the combined QM/MM minimum free-energy path simulations. The method was applied to the self-exchange S(N)2 reaction of CH(3)Cl + Cl(-), showing that the importance of solvent-solute interactions to the reaction process. The results were further discussed in the context of coupling between solvent and solute molecules in reaction processes.

Comparison of pattern detection methods in microarray time series of the segmentation clock.

While genome-wide gene expression data are generated at an increasing rate, the repertoire of approaches for pattern discovery in these data is still limited. Identifying subtle patterns of interest in large amounts of data (tens of thousands of profiles) associated with a certain level of noise remains a challenge. A microarray time series was recently generated to study the transcriptional program of the mouse segmentation clock, a biological oscillator associated with the periodic formation of the segments of the body axis. A method related to Fourier analysis, the Lomb-Scargle periodogram, was used to detect periodic profiles in the dataset, leading to the identification of a novel set of cyclic genes associated with the segmentation clock. Here, we applied to the same microarray time series dataset four distinct mathematical methods to identify significant patterns in gene expression profiles. These methods are called: Phase consistency, Address reduction, Cyclohedron test and Stable persistence, and are based on different conceptual frameworks that are either hypothesis- or data-driven. Some of the methods, unlike Fourier transforms, are not dependent on the assumption of periodicity of the pattern of interest. Remarkably, these methods identified blindly the expression profiles of known cyclic genes as the most significant patterns in the dataset. Many candidate genes predicted by more than one approach appeared to be true positive cyclic genes and will be of particular interest for future research. In addition, these methods predicted novel candidate cyclic genes that were consistent with previous biological knowledge and experimental validation in mouse embryos. Our results demonstrate the utility of these novel pattern detection strategies, notably for detection of periodic profiles, and suggest that combining several distinct mathematical approaches to analyze microarray datasets is a valuable strategy for identifying genes that exhibit novel, interesting transcriptional patterns.

Field methods for capture and measurement of three monkey species in Costa Rica.

A total of 54 free-ranging monkeys were captured and marked in Santa Rosa National Park, Costa Rica, during May 1985, and an additional 17 were captured during March 1986. The animals were darted using a blowpipe or a CO2 gun. The drugs used were Ketaset, Sernylan and Telazol. Ketaset was effective for Cebus capucinus but unsuccessful for Alouatta palliata and Ateles geoffroyi. Sernylan was successful for A. geoffroyi and A. palliata but is no longer commercially available. Telazol proved to be an excellent alternative capture drug for both A. palliata and A. geoffroyi.

Adaptive stereotactic body radiation therapy planning for lung cancer.

PURPOSE: To investigate the dosimetric effects of adaptive planning on lung stereotactic body radiation therapy (SBRT). METHODS AND MATERIALS: Forty of 66 consecutive lung SBRT patients were selected for a retrospective adaptive planning study. CBCT images acquired at each fraction were used for treatment planning. Adaptive plans were created using the same planning parameters as the original CT-based plan, with the goal to achieve comparable comformality index (CI). For each patient, 2 cumulative plans, nonadaptive plan (PNON) and adaptive plan (PADP), were generated and compared for the following organs-at-risks (OARs): cord, esophagus, chest wall, and the lungs. Dosimetric comparison was performed between PNON and PADP for all 40 patients. Correlations were evaluated between changes in dosimetric metrics induced by adaptive planning and potential impacting factors, including tumor-to-OAR distances (dT-OAR), initial internal target volume (ITV1), ITV change (ΔITV), and effective ITV diameter change (ΔdITV). RESULTS: 34 (85%) patients showed ITV decrease and 6 (15%) patients showed ITV increase throughout the course of lung SBRT. Percentage ITV change ranged from -59.6% to 13.0%, with a mean (±SD) of -21.0% (±21.4%). On average of all patients, PADP resulted in significantly (P=0 to .045) lower values for all dosimetric metrics. ΔdITV/dT-OAR was found to correlate with changes in dose to 5 cc (ΔD5cc) of esophagus (r=0.61) and dose to 30 cc (ΔD30cc) of chest wall (r=0.81). Stronger correlations between ΔdITV/dT-OAR and ΔD30cc of chest wall were discovered for peripheral (r=0.81) and central (r=0.84) tumors, respectively. CONCLUSIONS: Dosimetric effects of adaptive lung SBRT planning depend upon target volume changes and tumor-to-OAR distances. Adaptive lung SBRT can potentially reduce dose to adjacent OARs if patients present large tumor volume shrinkage during the treatment.

Mainland size variation informs predictive models of exceptional insular body size change in rodents.

The tendency for island populations of mammalian taxa to diverge in body size from their mainland counterparts consistently in particular directions is both impressive for its regularity and, especially among rodents, troublesome for its exceptions. However, previous studies have largely ignored mainland body size variation, treating size differences of any magnitude as equally noteworthy. Here, we use distributions of mainland population body sizes to identify island populations as 'extremely' big or small, and we compare traits of extreme populations and their islands with those of island populations more typical in body size. We find that although insular rodents vary in the directions of body size change, 'extreme' populations tend towards gigantism. With classification tree methods, we develop a predictive model, which points to resource limitations as major drivers in the few cases of insular dwarfism. Highly successful in classifying our dataset, our model also successfully predicts change in untested cases.

Monte Carlo Analysis and Physics Characterization of a Novel Nanoparticle Detector for Medical and Micro-dosimetry Applications

The outcomes for both (i) radiation therapy and (ii) preclinical small animal radio- biology studies are dependent on the delivery of a known quantity of radiation to a specific and intentional location. Adverse effects can result from these procedures if the dose to the target is too high or low, and can also result from an incorrect spatial distribution in which nearby normal healthy tissue can be undesirably damaged by poor radiation delivery techniques. Thus, in mice and humans alike, the spatial dose distributions from radiation sources should be well characterized in terms of the absolute dose quantity, and with pin-point accuracy. When dealing with the steep spatial dose gradients consequential to either (i) high dose rate (HDR) brachytherapy or (ii) within the small organs and tissue inhomogeneities of mice, obtaining accurate and highly precise dose results can be very challenging, considering commercially available radiation detection tools, such as ion chambers, are often too large for in-vivo use.

In this dissertation two tools are developed and applied for both clinical and preclinical radiation measurement. The first tool is a novel radiation detector for acquiring physical measurements, fabricated from an inorganic nano-crystalline scintillator that has been fixed on an optical fiber terminus. This dosimeter allows for the measurement of point doses to sub-millimeter resolution, and has the ability to be placed in-vivo in humans and small animals. Real-time data is displayed to the user to provide instant quality assurance and dose-rate information. The second tool utilizes an open source Monte Carlo particle transport code, and was applied for small animal dosimetry studies to calculate organ doses and recommend new techniques of dose prescription in mice, as well as to characterize dose to the murine bone marrow compartment with micron-scale resolution.

Hardware design changes were implemented to reduce the overall fiber diameter to <0.9 mm for the nano-crystalline scintillator based fiber optic detector (NanoFOD) system. Lower limits of device sensitivity were found to be approximately 0.05 cGy/s. Herein, this detector was demonstrated to perform quality assurance of clinical 192Ir HDR brachytherapy procedures, providing comparable dose measurements as thermo-luminescent dosimeters and accuracy within 20% of the treatment planning software (TPS) for 27 treatments conducted, with an inter-quartile range ratio to the TPS dose value of (1.02-0.94=0.08). After removing contaminant signals (Cerenkov and diode background), calibration of the detector enabled accurate dose measurements for vaginal applicator brachytherapy procedures. For 192Ir use, energy response changed by a factor of 2.25 over the SDD values of 3 to 9 cm; however a cap made of 0.2 mm thickness silver reduced energy dependence to a factor of 1.25 over the same SDD range, but had the consequence of reducing overall sensitivity by 33%.

For preclinical measurements, dose accuracy of the NanoFOD was within 1.3% of MOSFET measured dose values in a cylindrical mouse phantom at 225 kV for x-ray irradiation at angles of 0, 90, 180, and 270˝. The NanoFOD exhibited small changes in angular sensitivity, with a coefficient of variation (COV) of 3.6% at 120 kV and 1% at 225 kV. When the NanoFOD was placed alongside a MOSFET in the liver of a sacrificed mouse and treatment was delivered at 225 kV with 0.3 mm Cu filter, the dose difference was only 1.09% with use of the 4x4 cm collimator, and -0.03% with no collimation. Additionally, the NanoFOD utilized a scintillator of 11 µm thickness to measure small x-ray fields for microbeam radiation therapy (MRT) applications, and achieved 2.7% dose accuracy of the microbeam peak in comparison to radiochromic film. Modest differences between the full-width at half maximum measured lateral dimension of the MRT system were observed between the NanoFOD (420 µm) and radiochromic film (320 µm), but these differences have been explained mostly as an artifact due to the geometry used and volumetric effects in the scintillator material. Characterization of the energy dependence for the yttrium-oxide based scintillator material was performed in the range of 40-320 kV (2 mm Al filtration), and the maximum device sensitivity was achieved at 100 kV. Tissue maximum ratio data measurements were carried out on a small animal x-ray irradiator system at 320 kV and demonstrated an average difference of 0.9% as compared to a MOSFET dosimeter in the range of 2.5 to 33 cm depth in tissue equivalent plastic blocks. Irradiation of the NanoFOD fiber and scintillator material on a 137Cs gamma irradiator to 1600 Gy did not produce any measurable change in light output, suggesting that the NanoFOD system may be re-used without the need for replacement or recalibration over its lifetime.

For small animal irradiator systems, researchers can deliver a given dose to a target organ by controlling exposure time. Currently, researchers calculate this exposure time by dividing the total dose that they wish to deliver by a single provided dose rate value. This method is independent of the target organ. Studies conducted here used Monte Carlo particle transport codes to justify a new method of dose prescription in mice, that considers organ specific doses. Monte Carlo simulations were performed in the Geant4 Application for Tomographic Emission (GATE) toolkit using a MOBY mouse whole-body phantom. The non-homogeneous phantom was comprised of 256x256x800 voxels of size 0.145x0.145x0.145 mm3. Differences of up to 20-30% in dose to soft-tissue target organs was demonstrated, and methods for alleviating these errors were suggested during whole body radiation of mice by utilizing organ specific and x-ray tube filter specific dose rates for all irradiations.

Monte Carlo analysis was used on 1 µm resolution CT images of a mouse femur and a mouse vertebra to calculate the dose gradients within the bone marrow (BM) compartment of mice based on different radiation beam qualities relevant to x-ray and isotope type irradiators. Results and findings indicated that soft x-ray beams (160 kV at 0.62 mm Cu HVL and 320 kV at 1 mm Cu HVL) lead to substantially higher dose to BM within close proximity to mineral bone (within about 60 µm) as compared to hard x-ray beams (320 kV at 4 mm Cu HVL) and isotope based gamma irradiators (137Cs). The average dose increases to the BM in the vertebra for these four aforementioned radiation beam qualities were found to be 31%, 17%, 8%, and 1%, respectively. Both in-vitro and in-vivo experimental studies confirmed these simulation results, demonstrating that the 320 kV, 1 mm Cu HVL beam caused statistically significant increased killing to the BM cells at 6 Gy dose levels in comparison to both the 320 kV, 4 mm Cu HVL and the 662 keV, 137Cs beams.

The effects of curcumin (diferuloylmethane) on body composition of patients with advanced pancreatic cancer.

BACKGROUND: Curcumin is a natural product that is often explored by patients with cancer. Weight loss due to fat and muscle depletion is a hallmark of pancreatic cancer and is associated with worse outcomes. Studies of curcumin's effects on muscularity show conflicting results in animal models. METHODS AND RESULTS: Retrospective matched 1:2 case-control study to evaluate the effects of curcumin on body composition (determined by computerized tomography) of 66 patients with advanced pancreatic cancer (22 treated,44 controls). Average age (SEM) was 63(1.8) years, 30/66(45%) women, median number of prior therapies was 2, median (IQR) time from advanced pancreatic cancer diagnosis to baseline image was 7(2-13.5) months (p>0.2, all variables). All patients lost weight (3.3% and 1.3%, treated vs. control, p=0.13). Treated patients lost more muscle (median [IQR] percent change -4.8[-9.1,-0.1] vs. -0.05%[-4.2, 2.6] in controls,p<0.001) and fat (median [IQR] percent change -6.8%[-15,-0.6] vs. -4.0%[-7.6, 1.3] in controls,p=0.04). Subcutaneous fat was more affected in the treated patients. Sarcopenic patients treated with curcumin(n=15) had survival of 169(115-223) days vs. 299(229-369) sarcopenic controls(p=0.024). No survival difference was found amongst non-sarcopenic patients. CONCLUSIONS: Patients with advanced pancreatic cancer treated with curcumin showed significantly greater loss of subcutaneous fat and muscle than matched untreated controls.

Surgical Procedure Characteristics and Risk of Sharps-Related Blood and Body Fluid Exposure.

OBJECTIVE To use a unique multicomponent administrative data set assembled at a large academic teaching hospital to examine the risk of percutaneous blood and body fluid (BBF) exposures occurring in operating rooms. DESIGN A 10-year retrospective cohort design. SETTING A single large academic teaching hospital. PARTICIPANTS All surgical procedures (n=333,073) performed in 2001-2010 as well as 2,113 reported BBF exposures were analyzed. METHODS Crude exposure rates were calculated; Poisson regression was used to analyze risk factors and account for procedure duration. BBF exposures involving suture needles were examined separately from those involving other device types to examine possible differences in risk factors. RESULTS The overall rate of reported BBF exposures was 6.3 per 1,000 surgical procedures (2.9 per 1,000 surgical hours). BBF exposure rates increased with estimated patient blood loss (17.7 exposures per 1,000 procedures with 501-1,000 cc blood loss and 26.4 exposures per 1,000 procedures with >1,000 cc blood loss), number of personnel working in the surgical field during the procedure (34.4 exposures per 1,000 procedures having ≥15 personnel ever in the field), and procedure duration (14.3 exposures per 1,000 procedures lasting 4 to <6 hours, 27.1 exposures per 1,000 procedures lasting ≥6 hours). Regression results showed associations were generally stronger for suture needle-related exposures. CONCLUSIONS Results largely support other studies found in the literature. However, additional research should investigate differences in risk factors for BBF exposures associated with suture needles and those associated with all other device types. Infect. Control Hosp. Epidemiol. 2015;37(1):80-87.

Prospective Estimation of Radiation Dose and Image Quality for Optimized CT Performance

X-ray computed tomography (CT) is a non-invasive medical imaging technique that generates cross-sectional images by acquiring attenuation-based projection measurements at multiple angles. Since its first introduction in the 1970s, substantial technical improvements have led to the expanding use of CT in clinical examinations. CT has become an indispensable imaging modality for the diagnosis of a wide array of diseases in both pediatric and adult populations [1, 2]. Currently, approximately 272 million CT examinations are performed annually worldwide, with nearly 85 million of these in the United States alone [3]. Although this trend has decelerated in recent years, CT usage is still expected to increase mainly due to advanced technologies such as multi-energy [4], photon counting [5], and cone-beam CT [6].

Despite the significant clinical benefits, concerns have been raised regarding the population-based radiation dose associated with CT examinations [7]. From 1980 to 2006, the effective dose from medical diagnostic procedures rose six-fold, with CT contributing to almost half of the total dose from medical exposure [8]. For each patient, the risk associated with a single CT examination is likely to be minimal. However, the relatively large population-based radiation level has led to enormous efforts among the community to manage and optimize the CT dose.

As promoted by the international campaigns Image Gently and Image Wisely, exposure to CT radiation should be appropriate and safe [9, 10]. It is thus a responsibility to optimize the amount of radiation dose for CT examinations. The key for dose optimization is to determine the minimum amount of radiation dose that achieves the targeted image quality [11]. Based on such principle, dose optimization would significantly benefit from effective metrics to characterize radiation dose and image quality for a CT exam. Moreover, if accurate predictions of the radiation dose and image quality were possible before the initiation of the exam, it would be feasible to personalize it by adjusting the scanning parameters to achieve a desired level of image quality. The purpose of this thesis is to design and validate models to quantify patient-specific radiation dose prospectively and task-based image quality. The dual aim of the study is to implement the theoretical models into clinical practice by developing an organ-based dose monitoring system and an image-based noise addition software for protocol optimization.

More specifically, Chapter 3 aims to develop an organ dose-prediction method for CT examinations of the body under constant tube current condition. The study effectively modeled the anatomical diversity and complexity using a large number of patient models with representative age, size, and gender distribution. The dependence of organ dose coefficients on patient size and scanner models was further evaluated. Distinct from prior work, these studies use the largest number of patient models to date with representative age, weight percentile, and body mass index (BMI) range.

With effective quantification of organ dose under constant tube current condition, Chapter 4 aims to extend the organ dose prediction system to tube current modulated (TCM) CT examinations. The prediction, applied to chest and abdominopelvic exams, was achieved by combining a convolution-based estimation technique that quantifies the radiation field, a TCM scheme that emulates modulation profiles from major CT vendors, and a library of computational phantoms with representative sizes, ages, and genders. The prospective quantification model is validated by comparing the predicted organ dose with the dose estimated based on Monte Carlo simulations with TCM function explicitly modeled.

Chapter 5 aims to implement the organ dose-estimation framework in clinical practice to develop an organ dose-monitoring program based on a commercial software (Dose Watch, GE Healthcare, Waukesha, WI). In the first phase of the study we focused on body CT examinations, and so the patient’s major body landmark information was extracted from the patient scout image in order to match clinical patients against a computational phantom in the library. The organ dose coefficients were estimated based on CT protocol and patient size as reported in Chapter 3. The exam CTDIvol, DLP, and TCM profiles were extracted and used to quantify the radiation field using the convolution technique proposed in Chapter 4.

With effective methods to predict and monitor organ dose, Chapters 6 aims to develop and validate improved measurement techniques for image quality assessment. Chapter 6 outlines the method that was developed to assess and predict quantum noise in clinical body CT images. Compared with previous phantom-based studies, this study accurately assessed the quantum noise in clinical images and further validated the correspondence between phantom-based measurements and the expected clinical image quality as a function of patient size and scanner attributes.

Chapter 7 aims to develop a practical strategy to generate hybrid CT images and assess the impact of dose reduction on diagnostic confidence for the diagnosis of acute pancreatitis. The general strategy is (1) to simulate synthetic CT images at multiple reduced-dose levels from clinical datasets using an image-based noise addition technique; (2) to develop quantitative and observer-based methods to validate the realism of simulated low-dose images; (3) to perform multi-reader observer studies on the low-dose image series to assess the impact of dose reduction on the diagnostic confidence for multiple diagnostic tasks; and (4) to determine the dose operating point for clinical CT examinations based on the minimum diagnostic performance to achieve protocol optimization.

Chapter 8 concludes the thesis with a summary of accomplished work and a discussion about future research.

Application of Numerical Methods to Study Arrangement and Fracture of Lithium-Ion Microstructure

The focus of this work is to develop and employ numerical methods that provide characterization of granular microstructures, dynamic fragmentation of brittle materials, and dynamic fracture of three-dimensional bodies.

We first propose the fabric tensor formalism to describe the structure and evolution of lithium-ion electrode microstructure during the calendaring process. Fabric tensors are directional measures of particulate assemblies based on inter-particle connectivity, relating to the structural and transport properties of the electrode. Applying this technique to X-ray computed tomography of cathode microstructure, we show that fabric tensors capture the evolution of the inter-particle contact distribution and are therefore good measures for the internal state of and electronic transport within the electrode.

We then shift focus to the development and analysis of fracture models within finite element simulations. A difficult problem to characterize in the realm of fracture modeling is that of fragmentation, wherein brittle materials subjected to a uniform tensile loading break apart into a large number of smaller pieces. We explore the effect of numerical precision in the results of dynamic fragmentation simulations using the cohesive element approach on a one-dimensional domain. By introducing random and non-random field variations, we discern that round-off error plays a significant role in establishing a mesh-convergent solution for uniform fragmentation problems. Further, by using differing magnitudes of randomized material properties and mesh discretizations, we find that employing randomness can improve convergence behavior and provide a computational savings.

The Thick Level-Set model is implemented to describe brittle media undergoing dynamic fragmentation as an alternative to the cohesive element approach. This non-local damage model features a level-set function that defines the extent and severity of degradation and uses a length scale to limit the damage gradient. In terms of energy dissipated by fracture and mean fragment size, we find that the proposed model reproduces the rate-dependent observations of analytical approaches, cohesive element simulations, and experimental studies.

Lastly, the Thick Level-Set model is implemented in three dimensions to describe the dynamic failure of brittle media, such as the active material particles in the battery cathode during manufacturing. The proposed model matches expected behavior from physical experiments, analytical approaches, and numerical models, and mesh convergence is established. We find that the use of an asymmetrical damage model to represent tensile damage is important to producing the expected results for brittle fracture problems.

The impact of this work is that designers of lithium-ion battery components can employ the numerical methods presented herein to analyze the evolving electrode microstructure during manufacturing, operational, and extraordinary loadings. This allows for enhanced designs and manufacturing methods that advance the state of battery technology. Further, these numerical tools have applicability in a broad range of fields, from geotechnical analysis to ice-sheet modeling to armor design to hydraulic fracturing.

A New Method for Modeling Free Surface Flows and Fluid-structure Interaction with Ocean Applications

The computational modeling of ocean waves and ocean-faring devices poses numerous challenges. Among these are the need to stably and accurately represent both the fluid-fluid interface between water and air as well as the fluid-structure interfaces arising between solid devices and one or more fluids. As techniques are developed to stably and accurately balance the interactions between fluid and structural solvers at these boundaries, a similarly pressing challenge is the development of algorithms that are massively scalable and capable of performing large-scale three-dimensional simulations on reasonable time scales. This dissertation introduces two separate methods for approaching this problem, with the first focusing on the development of sophisticated fluid-fluid interface representations and the second focusing primarily on scalability and extensibility to higher-order methods.

We begin by introducing the narrow-band gradient-augmented level set method (GALSM) for incompressible multiphase Navier-Stokes flow. This is the first use of the high-order GALSM for a fluid flow application, and its reliability and accuracy in modeling ocean environments is tested extensively. The method demonstrates numerous advantages over the traditional level set method, among these a heightened conservation of fluid volume and the representation of subgrid structures.

Next, we present a finite-volume algorithm for solving the incompressible Euler equations in two and three dimensions in the presence of a flow-driven free surface and a dynamic rigid body. In this development, the chief concerns are efficiency, scalability, and extensibility (to higher-order and truly conservative methods). These priorities informed a number of important choices: The air phase is substituted by a pressure boundary condition in order to greatly reduce the size of the computational domain, a cut-cell finite-volume approach is chosen in order to minimize fluid volume loss and open the door to higher-order methods, and adaptive mesh refinement (AMR) is employed to focus computational effort and make large-scale 3D simulations possible. This algorithm is shown to produce robust and accurate results that are well-suited for the study of ocean waves and the development of wave energy conversion (WEC) devices.