# Browsing by Department "Civil and Environmental Engineering"

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Item Open Access A Class of Tetrahedral Finite Elements for Complex Geometry and Nonlinear Mechanics: A Variational Multiscale Approach(2019) Abboud, NabilIn this work, a stabilized finite element framework is developed to simulate small and large deformation solid mechanics problems involving complex geometries and complicated constitutive models. In particular, the focus is on solid dynamics problems involving nearly and fully incompressible materials. The work is divided into three main themes, the first is concerned with the development of stabilized finite element algorithms for hyperelastic materials, the second handles the case of viscoelastic materials, and the third focuses on algorithms for J2-plastic materials. For all three cases, problems in the small and large deformation regime are considered, and for the J2-plasticity case, both quasi-static and dynamic problems are examined.

Some of the key features of the algorithms developed in this work is the simplicity of their implementation into an existing finite element code, and their applicability to problems involving complicated geometries. The former is achieved by using a mixed formulation of the solid mechanics equations where the velocity and pressure unknowns are represented by linear shape functions, whereas the latter is realized by using triangular elements which offer numerous advantages compared to quadrilaterals, when meshing complicated geometries. To achieve the stability of the algorithm, a new approach is proposed in which the variational multiscale approach is applied to the mixed form of the solid mechanics equations written down as a first order system, whereby the pressure equation is cast in rate form.

Through a series of numerical simulations, it is shown that the stability properties of the proposed algorithm is invariant to the constitutive model and the time integrator used. By running convergence tests, the algorithm is shown to be second order accurate, in the $L^2$-nrom, for the displacements, velocities, and pressure. Finally, the robustness of the algorithm is showcased by considering realistic test cases involving complicated geometries and very large deformation.

Item Open Access A Combined Experimental and Modeling Approach Unraveling the Mechanics Behind Drying-induced Fractures in Soils(2023) Chen, RuoyuThis dissertation aims to understand the physics of geomaterial under different loading rates, employing a combination of experimental analysis and theoretical modeling. After obtaining a comprehensive understanding of geophysics, the objective shifts to exploring methods for enhancing the mechanical properties of materials to mitigate or prevent structural failures.

One particular focus in experimental studies is placed on understanding the phenomenon of desiccation, where the volumetric shrinkage rate of the geomaterial can be manipulated by adjusting atmospheric conditions. The experimental results from desiccation tests, supported by triaxial tests, reveal that the behavior of geomaterials is dependent on the loading rate, indicating a rate-dependent response. This observation highlights the need to consider viscoplasticity in the mechanical analysis of these geomaterials. Subsequently, a theoretical mathematical model incorporating viscoplasticity is utilized to describe the stress distribution within the geomaterial. By comparing the predicted locations and the number of stress singularities obtained from the model with the observed locations and the number of cracks in desiccation tests conducted under controlled atmospheric conditions, the effectiveness of the model in capturing the mechanical behavior of the geomaterial is assessed.

Once the mechanical behavior is understood and the corresponding theoretical model is validated, modifications in soil properties can be achieved through adjustments to viscosity. Initially, increasing the viscosity results in the formation of more cracks with narrower spacing. However, as viscosity continues to increase, it eventually leads to the complete prevention of failure. Desiccation experiments containing fluids with varying viscosities were conducted to validate the predicted failure pattern. The experimental results align with the theoretical predictions, providing confirmation of the anticipated behavior.

During desiccation tests conducted on amended soil samples, it was observed that crack development was mitigated, indicating that cracks initially appeared but remained suspended during the dehydration process. Due to the complexity of solving time-dependent partial differential equations with shifting boundary conditions, capillary experiments were introduced to provide insights into the force development within soil particles with the loss of water. The morphology and force development from capillary tests revealed distinct outcomes during dehydration: in the capillary system with distilled water and low viscosity fluid, a rapid force reduction (drop to zero) occurred as the capillary bridges broke, while the presence of high viscosity fluid resulted in a rebound followed by a high attraction force due to bonding formation in the capillary system.

In all, this dissertation offers a novel perspective on describing soil behavior and provides a micro-scale explanation of force development in soil dehydration.

Item Open Access A Computational Framework for Fracture Modeling in Coupled Field Problems(2018) Liu, YingjieThis dissertation proposes a family of computational frameworks for fracture modeling in coupled field problems. Fracture mechanics has been a topic of considerable interest for several decades due to the wide existence of fracture in different engineering structures and the important applications of fracture in multiple industries.

The present study first develops a continuum-discrete approach to model the fluid-driven fracture of granular media. This approach avoids remeshing by representing the particles as moving interfaces on a fixed background mesh. The effect of particle movement on the flow is characterized by a non-slip boundary condition. A boundary split scheme is proposed to ensure the coercivity of the method. The fluid-driven force on particles is represented by a boundary integral of the viscous drag force around the particles. The corresponding initial-boundary value problem is constructed for the invading fluid and is spatially discretized with the finite element method. A novel quadrature method is developed to handle partial elements that arise due to the mismatch between the mesh and the physical domain. The conditioning issue of partial elements is also addressed in the present study.

The present study also aims at developing a general and robust computational approach for the fracture modeling of conventional materials within coupled field problems. We follow the framework of a phase field regularization because of its strength in handling complex fracture patterns. The first application we consider is the fracture simulation of kidney stones during shock wave lithotripsy (SWL), an acoustic-solid-fracture coupling problem. The present study develops a novel computational framework for simulating SWL.

The propagation of acoustic pressure is modeled by a wave equation and the deformation of the phantom stone is modeled by the elasto-dynamics equations. The interactions between the acoustic wave and kidney stone is enforced via the continuity condition. The initialization and propagation of fracture within the stone is implicitly represented by the evolution of the phase field.

Traditional phase field is designed to model the brittle fracture of homogeneous materials. The present study develops a phase field framework to model fracture propagation in anisotropic and heterogeneous solids. The present model is distinguished from the traditional phase field approach by the fact that it converges to a cohesive type model instead of a Griffith model. A mathematically self-consistent strain energy density functional is proposed that is valid for any anisotropic linear elastic materials. Anisotropy in both the bulk moduli and the crack surface energy are characterized. The model employs multiple phase fields to capture the fracture behavior of the material with more than one preferential cleavage plane. The model develops a novel degradation function which relaxes the strong constraint between the regularization length l and the material properties. The convergence of the model with reducing l and the energy conservation properties of the framework are demonstrated through numerical examples. A robust adaptivity strategy is developed to increase the efficiency of the model. The present framework is applied to model fracture in heterogeneous and anisotropic materials. Coupled with a fine scale analysis, the present model is also used to model the fracture of functionally graded materials.

Item Open Access A Helicopter Observation Platform for Atmospheric Boundary Layer Studies(2009) Holder, Heidi EichingerSpatial variability of the Earth's surface has a considerable impact on the atmosphere at all scales and understanding the mechanisms involved in land-atmosphere interactions is hindered by the scarcity of appropriate observations. A measurement gap exists between traditional point sensors and large aircraft and satellite-based sensors in collecting measurements of atmospheric quantities. Point sensors are capable of making long time series of measurements, but cannot make measurements of spatial variability. Large aircraft and satellites make measurements over large spatial areas, but with poor spatial and temporal resolution. A helicopter-based platform can make measurements on scales relevant for towers, especially close to the Earth's surface, and can extend these measurements to account for spatial variability. Thus, the Duke University Helicopter Observation Platform (HOP) is designed to fill the existing measurement gap.

Because measurements must be made in such a way that they are as uncontaminated by the platform itself as much as is possible, it is necessary to quantify the aerodynamic envelope of the HOP. The results of an analytical analysis of the location of the main rotor wake at various airspeeds are shown. Similarly, the results of a numerical analysis using the commercial Computational Fluid Dynamics software Fluent are shown. The optimal flight speed for the sampling of turbulent fluxes is found to be around 30 m/s. At this airspeed, the sensors located in front of the nose of the HOP are in advance of the wake generated by the main rotor. This airspeed is also low enough that the region of high pressure due to the stagnation point on the nose of the HOP does not protrude far enough forward to affect the sensors. Measurements of differential pressures, variables and turbulent fluxes made while flying the HOP at different airspeeds support these results. No systematic effects of the platform are seen at airspeeds above about 10 m/s.

Processing of HOP data collected using the current set of sensors is discussed, including the novel use of the Empirical Mode Decomposition (EMD) to detrend and filter the data. The EMD separates the data into a finite number of Impirical Mode Functions (IMFs), each of which is unique and orthogonal. The basis is determined by the data itself, so that it need not be known a priori, and it is adaptive. The EMD is shown to be an ideal tool for the filtering and detrending of HOP data using data gathered during the Cloud and Land Surface Interaction Campaign (CLASIC).

The ability of the HOP to accurately measure atmospheric profiles of potential temperature is demonstrated. During experiments conducted in the marine boundary layer (MBL) and the convective boundary layer (CBL), HOP profiles are evaluated using profiles from an elastic backscatter lidar. The HOP and the lidar agree on the height of the boundary layer in both cases, and the HOP effectively locates other atmospheric structures.

Atmospheric sensible and latent heat fluxes, turbulence kinetic energy (TKE) and horizontal momentum fluxes are also measured, and the resulting information is used to provide context to tower-based data collected concurrently. A brief comparison made over homogeneous ocean conditions yields good results. A more exhaustive evaluation is made using short HOP flights made over an orchard during the Canopy Horizontal Turbulence Study (CHATS).

Item Open Access A Mean Field Approach to Watershed Hydrology(2016) Bartlett, Mark Stephan, JrSociety-induced changes to the environment are altering the effectiveness of existing management strategies for sustaining natural and agricultural ecosystem productivity. At the watershed scale, natural and agro-ecosystems represent complex spatiotemporal stochastic processes. In time, they respond to random rainfall events, evapotranspiration and other losses that are spatially variable because of heterogeneities in soil properties, root distributions, topography, and other factors. To quantify the environmental impact of anthropogenic activities, it is essential that we characterize the evolution of space and time patterns of ecosystem fluxes (e.g., energy, water, and nutrients). Such a characterization then provides a basis for assessing and managing future anthropogenic risks to the sustainability of ecosystem productivity.

To characterize the space and time evolution of watershed scale processes, this dissertation introduces a mean field approach to watershed hydrology. Mean field theory (also known as self-consistent field theory) is commonly used in statistical physics when modeling the space-time behavior of complex systems. The mean field theory approximates a complex multi-component system by considering a lumped (or average) effect of all individual components acting on a single component. Thus, the many body problem is reduced to a one body problem. For watershed hydrology, a mean field theory reduces the numerous point component effects to more tractable watershed averages resulting in a consistent method for linking the average watershed fluxes (evapotranspiration, runoff, etc.) to the local fluxes at each point.

The starting point for this work is a general point description of the soil moisture, rainfall, and runoff system. For this system, we find the joint PDF that describes the temporal variability of the soil water, rainfall, and runoff processes. Since this approach does not account for the spatial variability of runoff, we introduce a probabilistic storage (ProStor) framework for constructing a lumped (unit area) rainfall-runoff response from the spatial distribution of watershed storage. This framework provides a basis for unifying and extending common event-based hydrology models (e.g. Soil Conservation Service curve number (SCS-CN) method) with more modern semi-distributed models (e.g. Variable Infiltration Capacity (VIC) model, the Probability Distributed (PDM) model, and TOPMODEL). In each case, we obtain simple equations for the fractions of the different source areas of runoff, the spatial variability of runoff and soil moisture, and the average runoff value (i.e., the so-called runoff curve). Finally, we link the temporal and spatial descriptions with a mean field approach for watershed hydrology. By applying this mean field approach, we upscale the point description with the spatial distribution of soil moisture and parameterize the numerous local interactions related to lateral fluxes of soil water in terms of its average. With this approach, we then derive PDFs that represent the space and time distribution of soil water and associated watershed fluxes such as evapotranspiration and runoff.

Item Open Access A New Method for Modeling Free Surface Flows and Fluid-structure Interaction with Ocean Applications(2016) Lee, CurtisThe 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.

Item Open Access A Novel Integrated Biotrickling Filter -Anammox Bioreactor System for the Complete Treatment of Ammonia in Air with Nitrification and Denitrification(2020) Tang, LizhanAn integrated biotrickling filter (BTF)-Anammox bioreactor system was established for the complete treatment of ammonia. Shortcut nitrification process was successfully achieved in the biotrickling filter through free ammonia and free nitrous acid inhibition of nitrite oxidizing bacteria. During transients, while increasing nitrogen loading, free ammonia was the main factor that inhibited the activity of ammonia oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB). During steady state operation, free nitrous acid was mainly responsible for inhibition of NOB due to the accumulation of nitrite at relatively low pH. Ammonia removal by the BTF reached up to 50 gN m-3 h-1 with 100% removal at an inlet concentration of 403 ppm and a gas residence time of 20.8 s. Average removal of ammonia during stable operation was 95%. The anammox bioreactor could remove 75% of total nitrogen discharged by the BTF when the two reactors were connected. The possibility of operating in complete closed loop mode for the liquid was investigated. However, due to the limited activity of the Anammox bioreactor or the fact that this reactor was undersized, recycling the Anammox effluent back to BTF caused accumulation of nitrite in the system which further inhibited activity of Anammox and progressively caused failure of the system.

A conceptual model of both bioreactors was also developed to optimize the integrated system. The model was developed by including mass balances of nitrogen in the system and inhibition factors in microbial kinetics. Parameters such as hydraulic residence time (HRT), empty bed residence time (EBRT) and pH had significant impact on the partial nitritation process in the BTF. Model simulations also indicated that implementing a recycle for the Anammox bioreactor was needed to reduce the inhibitory effect of nitrite on the performance of the system.

Item Open Access A Python-Based Program for Estimating Biological Surface Acidity by Using a Non-Electrostatic Adsorption Model(2023) Li, HaotianThe objective of this research is to develop an open-source Python-based surface complexation modeling program to estimate the acidity of biological surface. Several computer software already exists with such function installed, such as ProtoFit and FITEQL. However, these programs lack capabilities in constraining fitting parameters, resulting in model fits that are not necessarily justified by the input data. Here, a new Python-based model algorithm was developed to estimate surface acidity and protonation constants for biological surfaces. The program was developed based on the algorithm of ProtoFit, and improved to allow for user-defined boundary conditions for model fitting parameters. This model was tested on potentiometric pH titration data for suspensions of Pseudomonas fluorescens and Bacillus subtilis bacterial cells and suspensions of colloidal particles (e.g., extracellular vesicles) that were isolated from cell cultures. Model testing was also performed for titration data collected for aqueous buffer solutions with known chemical species and concentration. The estimated surface acidities from Python script and ProtoFit are compared, and error analysis was conducted. Error analysis showed that the Python script modeled the titration data with lower curve-fitting error than models by ProtoFit, which suggests a better optimization performance in Python script. However, the model comparisons for the aqueous buffer titrations (for which acidity constants were known) did not showing such trend. We believe that is because experimental error is much larger than model error in our setups. Therefore, variance-based sensitivity analysis was further conducted on the Python script, and the result shows that the titrant concentration (N_tit) and adsorbent mass (M_ads) were two variables that contributed the most variance in our model output.

Item Open Access A Study in Laterally Restrained Buckled Beams for the use in a Vertical Isolation System(2021) McManus, Michael AllenLinear vibration isolation systems, used to reduce the transmissibility of vertical vibration, requires a vertical static displacement that increases with the square of the natural period of the isolation system. The static displacement of a vertical isolation system with a one second natural period is 0.25 m. The nonlinear stiffness of buckled beams loaded in the transverse direction can be designed to reduce the vertical static displacement requirement of vertical systems. This study presents an analysis of large displacement mechanics of slender beams that buckle against a constraint, and extracts the transverse constraint force via the Lagrange multiplier enforcing the constraint. The constraint prescribes a maximum allowable lateral displacement along the length of the beam and a specified longitudinal displacement at the mid span of the beam. No small curvature assumption is involved. Lateral and longitudinal displacements are parameterized in terms of Fourier coefficients. Coefficient values for constrained equilibria are found by minimizing the bending strain energy such that lateral and longitudinal constraints are satisfied. Because the full expression for curvature is used, this is a nonlinear constrained optimization problem.

Edge and mid-point horizontal constraint positions are varied to gain a better understanding of the constraint forces at each position. This modeling approach is then used to design a system of post-buckled leaf springs in order to meet vibration isolation requirements without over-stressing the springs. This process is discussed in detail along with the process and challenges associated with the physical model. Theoretical predictions are compared to laboratory scale measurements. Experimental results from the physical model are compared to the theoretical and numerical simulation results. The potential for rocking responses of the vertical isolation system are quantified via the modeling of the nonlinear dynamics of a platform supported by a system of springs and carrying a mass concentrated above the platform.

Item Open Access Aboveground Storage Tank Detection Using Faster R-CNN and High-Resolution Aerial Imagery(2021) Zhao, QianyuIn recent years, NaTech disasters, which are defined as the technological accidents caused by natural events, have led to huge losses all over the world. To reduce these losses, assessments of the vulnerabilities of industrial facilities are necessary. In this study, an effort was made to locate aboveground storage tanks from remotely sensed imagery. A dataset that identifies different types of tanks was generated. The data were acquired from the National Agriculture Imagery Program (NAIP) and tanks were labeled as closed roof tank, external floating roof tank, spherical tank, water treatment tank, or water tower according to their shapes. After collecting these data, the Faster R-CNN algorithm, an object detection architecture, was applied to test the performance of this algorithm on the prelabeled dataset. Results of testing indicate that the algorithm could well achieve the goal that having a high recall rate for all the classes of tanks. The precision and recall rates were 82.92% and 90.03% for closed roof tanks, 85.85% and 91.68% for external floating roof tanks, 34.81% and 60.26% for spherical tanks, 49.63% and 89.33% water treatment tanks, 9.43% and 38.46% for water towers. For spherical tanks and water towers, although having low precision and recall, the percentage of missed tanks was extremely low, which is 2.08% and 0 respectively. These results suggest that this aboveground storage tank dataset and the pretrained model generated from Faster R-CNN could be further used in future work for tank detection and vulnerability assessment.

Item Open Access ADAPTIVE LOCAL REDUCED BASIS METHOD FOR RISK-AVERSE PDE CONSTRAINED OPTIMIZATION AND INVERSE PROBLEMS(2018) Zou, ZilongMany physical systems are modeled using partial dierential equations (PDEs) with uncertain or random inputs. For such systems, naively propagating a xed number of samples of the input probability law (or an approximation thereof) through the PDE is often inadequate to accurately quantify the risk associated with critical system responses. In addition, to manage the risk associated with system response and devise risk-averse controls for such PDEs, one must obtain the numerical solution of a risk-averse PDE-constrained optimization problem, which requires substantial computational eorts resulting from the discretization of the underlying PDE in both the physical and stochastic dimensions.

Bayesian Inverse problem, where unknown system parameters need to be inferred from some noisy data of the system response, is another important class of problems that suffer from excessive computational cost due to the discretization of the underlying PDE. To accurately characterize the inverse solution and quantify its uncertainty, tremendous computational eorts are typically required to sample from the posterior distribution of the system parameters given the data. Surrogate approximation of the PDE model is an important technique to expedite the inference process and tractably solve such problems.

In this thesis, we develop a goal-oriented, adaptive sampling and local reduced basis approximation for PDEs with random inputs. The method, which we denote by local RB, determines a set of samples and an associated (implicit) Voronoi partition of the parameter domain on which we build local reduced basis approximations of the PDE solution. The local basis in a Voronoi cell is composed of the solutions at a xed number of closest samples as well as the gradient information in that cell. Thanks to the local nature of the method, computational cost of the approximation does not increase as more samples are included in the local RB model. We select the local RB samples in an adaptive and greedy manner using an a posteriori error indicator based on the residual of the approximation.

Additionally, we modify our adaptive sampling process using an error indicator that is specifically targeted for the approximation of coherent risk measures evaluated at quantities of interest depending on PDE solutions. This allow us to tailor our method to efficiently quantify the risk associated with the system responses. We then combine our local RB method with an inexact trust region method to eciently solve risk-averse optimization problems with PDE constraints. We propose a numerical framework for systematically constructing surrogate models for the trust-region subproblem and the objective function using local RB approximations.

Finally, we extend our local RB method to eciently approximate the Gibbs posterior distribution for inverse problems under uncertainty. The local RB method is employed to construct a cheap surrogate model for the loss function in the Gibbs posterior formula. To improve the accuracy of the surrogate approximation, we adopt a Sequential Monte Carlo framework to guide the progressive and adaptive construction of the local RB surrogate. The resulted method provides subjective and ecient inference of unknown system parameters under general distribution and noise assumptions.

We provide theoretical error bounds for our proposed local RB method and its extensions, and numerically demonstrate the performance of our methods through various examples.

Item Open Access Adsorption of Pharmaceutically Active Compounds (PhACs) by Powdered Activated Carbon from Natural Water --Influence of Natural Organic Matter (NOM)(2010) Gao, YaohuanPowdered Activated Carbon (PAC) adsorption was studied in order to determine the influence of natural organic matter (NOM) on the adsorption of two acidic pharmaceutically active compounds (PhACs), clofibric acid and ketoprofen. Suwannee River humic acids (SRHAs) was used as substitute of NOM in natural water. Batch adsorption experiments were conducted to obtain the single compound adsorption kinetics and adsorption isotherm with and without SRHAs in the system. Three main findings resulted from this study. First, the adsorption isotherms showed that the adsorption of clofibric acid was not significantly affected in the presence of SRHAs (5 ppm); however, the adsorption of ketoprofen markedly decreased with SRHAs in the solutions. Higher initial concentrations of clofibric acid than ketoprofen together with the compressed double layer theory helped explain the different behaviors that were observed. Furthermore, the more hydrophobic ketoprofen molecules may increase the possibility that this compound would adsorb less on the surface area which was covered by the more hydrophilic humic acids. Second, the adsorption kinetics of both compounds were not affected by the SRHAs, although more research may be needed, as it is possible that slight differences exist during the initial adsorption phase. Lastly, possible intermolecular forces were discussed and a sequence of importance is proposed for their role in the adsorption process as A). electrostatic forces; B). electron donor-acceptor interaction; C & D). H-bond and London Dispersion forces.

Item Open Access Advanced Aerogel Composites for Oil Remediation and Recovery(2016) Karatum, OsmanOil spills in marine environments often damage marine and coastal life if not remediated rapidly and efficiently. In spite of the strict enforcement of environmental legislations (i.e., Oil Pollution Act 1990) following the Exxon Valdez oil spill (June 1989; the second biggest oil spill in U.S. history), the Macondo well blowout disaster (April 2010) released 18 times more oil. Strikingly, the response methods used to contain and capture spilled oil after both accidents were nearly identical, note that more than two decades separate Exxon Valdez (1989) and Macondo well (2010) accidents.

The goal of this dissertation was to investigate new advanced materials (mechanically strong aerogel composite blankets-Cabot® Thermal Wrap™ (TW) and Aspen Aerogels® Spaceloft® (SL)), and their applications for oil capture and recovery to overcome the current material limitations in oil spill response methods. First, uptake of different solvents and oils were studied to answer the following question: do these blanket aerogel composites have competitive oil uptake compared to state-of-the-art oil sorbents (i.e., polyurethane foam-PUF)? In addition to their competitive mechanical strength (766, 380, 92 kPa for Spaceloft, Thermal Wrap, and PUF, respectively), our results showed that aerogel composites have three critical advantages over PUF: rapid (3-5 min.) and high (more than two times of PUF’s uptake) oil uptake, reusability (over 10 cycles), and oil recoverability (up to 60%) via mechanical extraction. Chemical-specific sorption experiments showed that the dominant uptake mechanism of aerogels is adsorption to the internal surface, with some contribution of absorption into the pore space.

Second, we investigated the potential environmental impacts (energy and chemical burdens) associated with manufacturing, use, and disposal of SL aerogel and PUF to remove the oil (i.e., 1 m3 oil) from a location (i.e., Macondo well). Different use (single and multiple use) and end of life (landfill, incinerator, and waste-to-energy) scenarios were assessed, and our results demonstrated that multiple use, and waste-to-energy choices minimize the energy and material use of SL aerogel. Nevertheless, using SL once and disposing via landfill still offers environmental and cost savings benefits relative to PUF, and so these benefits are preserved irrespective of the oil-spill-response operator choices.

To inform future aerogel manufacture, we investigated the different laboratory-scale aerogel fabrication technologies (rapid supercritical extraction (RSCE), CO2 supercritical extraction (CSCE), alcohol supercritical extraction (ASCE)). Our results from anticipatory LCA for laboratory-scaled aerogel fabrication demonstrated that RSCE method offers lower cumulative energy and ecotoxicity impacts compared to conventional aerogel fabrication methods (CSCE and ASCE).

The final objective of this study was to investigate different surface coating techniques to enhance oil recovery by modifying the existing aerogel surface chemistries to develop chemically responsive materials (switchable hydrophobicity in response to a CO2 stimulus). Our results showed that studied surface coating methods (drop casting, dip coating, and physical vapor deposition) were partially successful to modify surface with CO2 switchable chemical (tributylpentanamidine), likely because of the heterogeneous fiber structure of the aerogel blankets. A possible solution to these non-uniform coatings would be to include switchable chemical as a precursor during the gel preparation to chemically attach the switchable chemical to the pores of the aerogel.

Taken as a whole, the implications of this work are that mechanical deployment and recovery of aerogel composite blankets is a viable oil spill response strategy that can be deployed today. This will ultimately enable better oil uptake without the uptake of water, potential reuse of the collected oil, reduced material and energy burdens compared to competitive sorbents (e.g., PUF), and reduced occupational exposure to oiled sorbents. In addition, sorbent blankets and booms could be deployed in coastal and open-ocean settings, respectively, which was previously impossible.

Item Open Access Advancing the Representation of Land Surface Heterogeneity in Land Surface Models(2024) Torres Rojas, LauraDue to its profound influence on various environmental processes and phenomena, the correctrepresentation of landscape physical heterogeneity in models is vital for applications spanning a wide range of scales, from global climate prediction to field-scale hydrological forecasting. Land Surface Models (LSM), Earth System Models (ESMs), and satellite remote sensing provide spatially distributed fields of surface fluxes and states, making them critical scientific tools for understanding the impact of physical heterogeneity. Enhanced understanding of heterogeneity's spatial and temporal effect can significantly improve our comprehension of hydrological, energy, and biogeochemical cycles at multiple scales. Under this framework, the dissertation focuses on optimizing, evaluating, and improving heterogeneity representations for LSM and ESM applications. Chapter 2 introduces a novel multi-objective optimization approach to efficiently determine optimal heterogeneity representation configuration for LSMs while considering the spatial structure of the generated fields, the accuracy of the representation of hydrological processes, and the computational trackability of the resulting structure. Chapter 3 builds upon the spatial nature of this approach and presents the Empirical Spatio-Temporal Covariance Function (ESTCF), a tool based on geostatistics that allows to efficiently and effectively characterize the spatio-temporal patterns observed in remotely sensed fields and relate them to physical characteristics of the environment. Intending to use remote sensing elevation data to its maximum, Chapter 4 proposes strategies to improve the coupling between river networks and heterogeneity representations in LSMs. Experiments demonstrate the sensitivity of spatiotemporal patterns in the land surface to the heterogeneity representation. Finally, the tool developed in Chapter 2 and the heterogeneity representation proposed in Chapter 4 are combined in Chapter 5, where the spacetime covariance is used to evaluate LSM simulated spatio-temporal patterns of land surface temperature. The proposed method efficiently summarizes complex patterns and offers valuable insights into model strengths and weaknesses. Overall, this dissertation contributes to a stricter description and assessment of the landscape heterogeneity representation in LSMs and ESMs, providing a foundation for a more comprehensive model development.

Item Open Access Alterations of Endophytic Microbial Community Function in Spartina alterniflora as a Result of Crude Oil Exposure(2021) Addis, SamanthaThe 2010 Deepwater Horizon disaster remains one of the largest oil spills in history. This event caused significant damage to coastal ecosystems, the full extent of which has yet to be fully determined. Crude oil contains both toxic substances that are detrimental to microbes and compounds that may be used as food and energy resources by some microbial species. As a result, oil spills have the potential to cause significant shifts in microbial communities. In this study, we assessed the impact of oil contamination on the function of endophytic microbial communities associated with saltmarsh cordgrass (Spartina alterniflora). Soil samples were collected from two locations in coastal Louisiana, USA: one severely affected by contamination from the Deepwater Horizon oil spill and one relatively unaffected location. Spartina alterniflora seedlings were grown in both soil samples under greenhouse conditions, and GeoChip 5.0 was used to evaluate the endophytic microbial metatranscriptome shifts in response to host oil exposure. Microbial functional shifts were detected in functional categories related to metal homeostasis, organic remediation, and phosphorus utilization. These findings show that host oil exposure elicits multiple changes in metabolic response from their endophytic microbial communities, producing effects that may have the potential to impact host plant fitness.

Item Open Access America’s Evolving Relationship with Trees: A Statistical Analysis of Social, Economic, and Environmental Drivers of Forest Management(2021) Holt, JonathanIn the spirit of American individualism, the majority of the United States’ forested landscape is controlled by private landowners, who make autonomous decisions that impact a shared wealth of biodiversity and ecosystem services. It is important to understand not only the forest management decisions made by private landowners, but also the motivations that incentivize these consequential actions. Furthermore, it is useful to have the capacity to infer such insights using publicly available data, and by employing transparent, flexible, and scalable statistical frameworks. This dissertation seeks to elucidate the motivations and actions of private landowners in the United States using a variety of data sources, including Zillow home estimates, the American Community Survey, satellite remote sensing imagery, and the Forest Inventory and Analysis database, and by implementing interpretable modeling frameworks, such as the hedonic pricing method and structural equation modeling. I uncover nuanced insights about human-environmental systems, including (1) a positive feedback loop between affluence and tree-shading in metropolitan areas; (2) the dominance of normative pressures on forest owners’ harvest intentions; and (3) a causal link between invasive insects and the quantity and sizes of harvested trees. Understanding such relationships benefits policymakers, forest managers, and urban planners tasked with optimizing human-natural systems.

Item Open Access Ammonia Gas Removal Using a Biotrickling Filter Coupled with an Anammox Reactor(2018) Frei, LaurenAmmonia is an odorous gaseous compound emitted by a variety of industrial facilities. This study aimed to address the feasibility of ammonia gas removal using a biotrickling filter (BTF) coupled with an anammox bioreactor. In the BTF, the influent ammonia gas partitioned into the trickling water and was converted to nitrite via partial nitrification. The effluent liquid from the BTF, containing nitrite and ammonium concentrations, was fed into the anammox reactor where autotrophic denitrifying bacteria converted the ammonium and nitrite to dinitrogen gas. For the anammox reactor to operate efficiently, the influent ammonium and nitrite concentrations must be in a 1 to 1 molar ratio. To evaluate the feasibility of this system, a lab scale BTF and anammox reactor were constructed and operated and a conceptual model for this system was developed. To obtain a nitrite to ammonium ratio close to 1, it was found that the effluent pH from the BTF must be maintained below 7, and the loading rate could not exceed 8.7 g N/m3h. At this loading rate, complete ammonia gas removal occurred. A recycle rate of 1.4 times that of the influent was implemented in the BTF to increase performance and improve the nitrite to ammonium ratio. The addition of the recycle line achieved a nitrite of ammonium ratio of 0.97 at a pH value of 7.67. The anammox reactor achieved 88% removal of ammonium and nitrite at a loading rate of 10.5 g N /m3h. The fact that the BTF was able to achieve a 1 to 1 nitrite to ammonium ratio indicated that coupling of a BTF with the anammox reactor should be feasible. The mathematical model underpredicted effluent ammonium and nitrite concentrations in the BTF and greatly overpredicted the effluent concentrations from the anammox reactor. To improve the BTF model inhibition factors and oxygen supply need to be accounted for. Further development of the growth kinetics in the annamox model are necessary as well.

Item Open Access An efficient finite element method for embedded interface problems(2013) Annavarapu, ChandrasekharWe focus on developing a computationally efficient finite element method for interface problems. Finite element methods are severely constrained in their ability to resolve interfaces. Many of these limitations stem from their inability in independently representing interface geometry from the underlying discretization. We propose an approach that facilitates such an independent representation by embedding interfaces in the underlying finite element mesh. This embedding, however, raises stability concerns for existing algorithms used to enforce interfacial kinematic constraints. To address these stability concerns, we develop robust methods to enforce interfacial kinematics over embedded interfaces. We begin by examining embedded Dirichlet problems – a simpler class of embedded constraints. We develop both stable methods, based on Lagrange multipliers,and stabilized methods, based on Nitsche’s approach, for enforcing Dirichlet constraints over three-dimensional embedded surfaces and compare and contrast their performance. We then extend these methods to enforce perfectly-tied kinematics for elastodynamics with explicit time integration. In particular, we examine the coupled aspects of spatial and temporal stability for Nitsche’s approach.We address the incompatibility of Nitsche’s method for explicit time integration by (a) proposing a modified weighted stress variational form, and (b) proposing a novel mass-lumpingprocedure.We revisit Nitsche’s method and inspect the effect of this modified variational form on the interfacial quantities of interest. We establish that the performance of this method, with respect to recovery of interfacial quantities, is governed significantly by the choice for the various method parameters viz.stabilization and weighting. We establish a relationship between these parameters and propose an optimal choice for the weighting. We further extend this approach to handle non-linear,frictional sliding constraints at the interface. The naturally non-symmetric nature of these problems motivates us to omit the symmetry term arising in Nitsche’s method.We contrast the performance of the proposed approach with the more commonly used penalty method. Through several numerical examples, we show that with the pro-posed choice of weighting and stabilization parameters, Nitsche’s method achieves the right balance between accurate constraint enforcement and flux recovery - a balance hard to achieve with existing methods. Finally, we extend the proposed approach to intersecting interfaces and conduct numerical studies on problems with junctions and complex topologies.Item Open Access An Extended Rouse Model of Inertial Particles Settling in Turbulent Boundary Layers(2022) Zhang, YanThe settling of inertial particles in turbulence boundary layers plays an essential role in many meteorological, industrial and environmental processes, and is governed by multifarious mechanisms. First, turbulence alters the settling velocity of inertial particles through different effects, like preferential sweeping mechanism, loitering effect and vortex trapping. Second, the existence of a wall introduces extra effects that can influence particle settling, such as turbophoresis. The Rouse model was the most famous model in predicting particle settling in vertical wall-bounded settling. Nevertheless, it is only valid for inertia-less particles in the logarithmic region. A theory by Bragg et al., based on phase-space probability density theory, incorporates particle inertia into the Rouse model, and quantifies the contributions from the aforementioned mechanisms to the particle vertical velocity. The theory is valid for all particle Stokes numbers, yet it still lacks a closed form.In this work, one way to close the equations presented by Bragg et al. (the extended Rouse model) was examined. Using a central differencing scheme combined with an iterative method, the nonlinear second-order differential equation of the variance of vertical particle velocity was solved. The predictions of the variance of vertical particle velocity S and the particle concentration PDF ρ by the model were studied and compared to DNS. The comparison indicates that the extended Rouse model is able to predict many features of S and ρ, like the accumulation of particles close to the wall and turbophoretic drift. However, the quantitative agreement between the predictions by the model and DNS is poor. There are two probable reasons for the discrepancies between the predictions and DNS. First, the closure of the term in the equation may be a source of errors. Second, the lower boundary condition, whose validity is suspicious for particles with weak inertia, can be a reason for the discrepancies. In order to investigate the cause for the disagreement, three different boundary conditions (zero-gradient condition, asymptotic matching, iterative condition) were examined. The results indicate that the boundary conditions have a very limited influence on the predictions. As a result, the closure of the terms is more likely to be responsible for the discrepancies.

Item Open Access An Investigation into the Multiscale Nature of Turbulence and its Effect on Particle Transport(2022) Tom, JosinWe study the effect of the multiscale properties of turbulence on particle transport, specifically looking at the physical mechanisms by which different turbulent flow scales impact the settling speeds of particles in turbulent flows. The average settling speed of small heavy particles in turbulent flows is important for many environmental problems such as water droplets in clouds and atmospheric aerosols. The traditional explanation for enhanced particle settling speeds in turbulence for a one-way coupled (1WC) system is the preferential sweeping mechanism proposed by Maxey (1987, J. Fluid Mech.), which depends on the preferential sampling of the fluid velocity gradient field by the inertial particles. However, Maxey's analysis does not shed light on role of different turbulent flow scales contributing to the enhanced settling, partly since the theoretical analysis was restricted to particles with weak inertia.

In the first part of the work, we develop a new theoretical result, valid for particles of arbitrary inertia, that reveals the multiscale nature of the preferential sweeping mechanism. In particular, the analysis shows how the range of scales at which the preferential sweeping mechanism operates depends on particle inertia. This analysis is complemented by results from Direct Numerical Simulations (DNS) where we examine the role of different flow scales on the particle settling speeds by coarse-graining (filtering) the underlying flow. The results explain the dependence of the particle settling speeds on Reynolds number and show how the saturation of this dependence at sufficiently large Reynolds number depends upon particle inertia. We also explore how particles preferentially sample the fluid velocity gradients at various scales and show that while rapidly settling particles do not preferentially sample the fluid velocity gradients, they do preferentially sample the fluid velocity gradients coarse-grained at scales outside of the dissipation range.

Inspired by our finding that the effectiveness of the preferential sweeping mechanism depends on how particles interact with the strain and vorticity fields at different scales, we next shed light on the multiscale dynamics of turbulence by exploring the properties of the turbulent velocity gradients at different scales. We do this by analyzing the evolution equations for the filtered velocity gradient tensor (FVGT) in the strain-rate eigenframe. However, the pressure Hessian and viscous stress are unclosed in this frame of reference, requiring in-depth modelling. Using data from DNS of the forced Navier-Stokes equation, we consider the relative importance of local and non-local terms in the FVGT eigenframe equations across the scales using statistical analysis. We show that the anisotropic pressure Hessian (which is one of the unclosed terms) exhibits highly non-linear behavior at low values of normalized local gradients, with important modeling implications. We derive a generalization of the classical Lumley triangle that allows us to show that the pressure Hessian has a preference for two-component axisymmetric configurations at small scales, with a transition to a more isotropic state at larger scales. We also show that the current models fail to capture a number of subtle features observed in our results and provide useful guidelines for improving Lagrangian models of the FVGT.

In the final part of the work, we look at how two-way coupling (2WC) modifies the multiscale preferential sweeping mechanism. We comment on the the applicability of the theoretical analysis developed in the first part of the work for 2WC flows. Monchaux & Dejoan (2017, Phys. Rev. Fluids) showed using DNS that while for low particle loading the effect of 2WC on the global flow statistics is weak, 2WC enables the particles to drag the fluid in their vicinity down with them, significantly enhancing their settling, and they argued that two-way coupling suppresses the preferential sweeping mechanism. We explore this further by considering the impact of 2WC on the contribution made by eddies of different sizes on the particle settling. In agreement with Monchaux & Dejoan, we show that even for low loading, 2WC strongly enhances particle settling. However, contrary to their study, we show that preferential sweeping remains important in 2WC flows. In particular, for both 1WC and 2WC flows, the settling enhancement due to turbulence is dominated by contributions from particles in straining regions of the flow, but for the 2WC case, the particles also drag the fluid down with them, leading to an enhancement of their settling compared to the 1WC case. Overall, the novel results presented here not only augments the current understanding of the different physical mechanisms in producing enhanced settling speeds from a fundamental physics perspective, but can also be used to improve predictive capabilities in large-scale atmospheric modeling.