Modeling of a Heat-Induced Buckling of Plates Using the Mesh-free Method

In the process of engineering design of structural shapes, the flat plate analysis results can be generalized to predict behaviors of complete structural shapes. In this case, the purpose of this project is to analyze a thin flat plate under conductive heat transfer and to simulate the temperature distribution, thermal stresses, total displacements, and buckling deformations. The current approach in these cases has been using the Finite Element Method (FEM), whose basis is the construction of a conforming mesh. In contrast, this project uses the mesh-free Scan Solve Method. This method eliminates the meshing limitation using a non-conforming mesh. I implemented this modeling process developing numerical algorithms and software tools to model thermally induced buckling. In addition, convergence analysis was achieved, and the results were compared with FEM. In conclusion, the results demonstrate that the method gives similar solutions to FEM in quality, but it is computationally less time consuming.

Simulating Everglades National Park hydrology and phosphorus transport under existing and future scenarios using numerical modeling

The Florida Everglades has a long history of anthropogenic changes which have impacted the quantity and quality of water entering the system. Since the construction of Tamiami Trail in the 1920's, overland flow to the Florida Everglades has decreased significantly, impacting ecosystems from the wetlands to the estuary. The MIKE Marsh Model of Everglades National Park (M3ENP) is a numerical model, which simulates Everglades National Park (ENP) hydrology using MIKE SHE/MIKE 11software. This model has been developed to determine the parameters that effect Everglades hydrology and understand the impact of specific flow changes on the hydrology of the system. As part of the effort to return flows to the historical levels, several changes to the existing water management infrastructure have been implemented or are in the design phase. Bridge construction scenarios were programed into the M3ENP model to review the effect of these structural changes and evaluate the potential impacts on water levels and hydroperiods in the receiving Northeast Shark Slough ecosystem. These scenarios have shown critical water level increases in an area which has been in decline due to low water levels. Results from this work may help guide future decisions for restoration designs. Excess phosphorus entering Everglades National Park in South Florida may promote the growth of more phosphorus-opportunistic species and alter the food chain from the bottom up. Two phosphorus transport methods were developed into the M3ENP hydrodynamic model to determine the factors affecting phosphorus transport and the impact of bridge construction on water quality. Results showed that while phosphorus concentrations in surface waters decreased overall, some areas within ENP interior may experience an increase in phosphorus loading which the addition of bridges to Tamiami Trail. Finally, phosphorus data and modeled water level data was used to evaluate the spectral response of Everglades vegetation to increasing phosphorus availability using Landsat imagery.

Projecting Changes in the Distribution and Productivity of Living Marine Resources: A Critical Review of the Suite of Modeling Approaches used in the Large European Project VECTORS

We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

Projecting Changes in the Distribution and Productivity of Living Marine Resources: A Critical Review of the Suite of Modeling Approaches used in the Large European Project VECTORS

We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

Avoiding Overfitting in Inverse Modeling of Chloride Migration in Concrete

Inverse analysis for reactive transport of chlorides through concrete in the presence of electric field is presented. The model is solved using MATLAB’s built-in solvers “pdepe.m” and “ode15s.m”. The results from the model are compared with experimental measurements from accelerated migration test and a function representing the lack of fit is formed. This function is optimised with respect to varying amount of key parameters defining the model. Levenberg-Marquardt trust-region optimisation approach is employed. The paper presents a method by which the degree of inter-dependency between parameters and sensitivity (significance) of each parameter towards model predictions can be studied on models with or without clearly defined governing equations. Eigen value analysis of the Hessian matrix was employed to investigate and avoid over-parametrisation in inverse analysis. We investigated simultaneous fitting of parameters for diffusivity, chloride binding as defined by Freundlich isotherm (thermodynamic) and binding rate (kinetic parameter). Fitting of more than 2 parameters, simultaneously, demonstrates a high degree of parameter inter-dependency. This finding is significant as mathematical models for representing chloride transport rely on several parameters for each mode of transport (i.e., diffusivity, binding, etc.), which combined may lead to unreliable simultaneous estimation of parameters.

Quantifying and Modeling the Influence of Forest on the Magnitude and Duration of Mountain Snow Storage in the Pacific Northwest, USA

Thesis (Ph.D.)--University of Washington, 2016-08

Glutathione Transferases as Detoxification Agents: Structural and Functional Studies

Glutathione transferases (GSTs) are a diverse family of enzymes that catalyze the glutathione-dependent detoxification of toxic compounds. GSTs are responsible for the conjugation of the tripeptide glutathione (GSH) to a wide range of electrophilic substrates. These include industrial pollutants, drugs, genotoxic carcinogen metabolites, antibiotics, insecticides and herbicides. In light of applications in biomedicine and biotechnology as cellular detoxification agents, detailed structural and functional studies of GSTs are required. Plant tau class GSTs play crucial catalytic and non-catalytic roles in cellular xenobiotic detoxification process in agronomically important crops. The abundant existence of GSTs in Glycine max and their ability to provide resistance to abiotic and biotic stresses such as herbicide tolerance is of great interest in agriculture because they provide effective and suitable tools for selective weed control. Structural and catalytic studies on tau class GST isoenzymes from Glycine max (GmGSTU10-10, GmGSTU chimeric clone 14 (Sh14), and GmGSTU2-2) were performed. Crystal structures of GmGSTU10-10 in complex with glutathione sulfenic acid (GSOH) and Sh14 in complex with S-(p-nitrobenzyl)-glutathione (Nb-GSH) were determined by molecular replacement at 1.6 Å and 1.75 Å, respectively. Major structural variations that affect substrate recognition and catalytic mechanism were revealed in the upper part of helix H4 and helix H9 of GmGSTU10-10. Structural analysis of Sh14 showed that the Trp114Cys point mutation is responsible for the enhanced catalytic activity of the enzyme. Furthermore, two salt bridges that trigger an allosteric effect between the H-sites were identified at the dimer interface between Glu66 and Lys104. The 3D structure of GmGSTU2-2 was predicted using homology modeling. Structural and phylogenetic analysis suggested GmGSTU2-2 shares residues that are crucial for the catalytic activity of other tau class GSTs–Phe10, Trp11, Ser13, Arg20, Tyr30, Leu37, Lys40, Lys53, Ile54, Glu66 and Ser67. This indicates that the catalytic and ligand binding site in GmGSTU2-2 are well-conserved. Nevertheless, at the ligandin binding site a significant variation was observed. Tyr32 is replaced by Ser32 in GmGSTU2-2 and thismay affect the ligand recognition and binding properties of GmGSTU2-2. Moreover, docking studies revealed important amino acid residues in the hydrophobic binding site that can affect the substrate specificity of the enzyme. Phe10, Pro12, Phe15, Leu37, Phe107, Trp114, Trp163, Phe208, Ile212, and Phe216 could form the hydrophobic ligand binding site and bind fluorodifen. Additionally, side chains of Arg111 and Lys215 could stabilize the binding through hydrogen bonds with the –NO2 groups of fluorodifen. GST gene family from the pathogenic soil bacterium Agrobacterium tumefaciens C58 was characterized and eight GST-like proteins in A. tumefaciens (AtuGSTs) were identified. Phylogenetic analysis revealed that four members of AtuGSTs belong to a previously recognized bacterial beta GST class and one member to theta class. Nevertheless, three AtuGSTs do not belong to any previously known GST classes. The 3D structures of AtuGSTs were predicted using homology modeling. Comparative structural and sequence analysis of the AtuGSTs showed local sequence and structural characteristics between different GST isoenzymes and classes. Interactions at the G-site are conserved, however, significant variations were seen at the active site and the H5b helix at the C-terminal domain. H5b contributes to the formation of the hydrophobic ligand binding site and is responsible for recognition of the electrophilic moiety of the xenobiotic. It is noted that the position of H5b varies among models, thus providing different specificities. Moreover, AtuGSTs appear to form functional dimers through diverse modes. AtuGST1, AtuGST3, AtuGST4 and AtuGST8 use hydrophobic ‘lock–and–key’-like motifs whereas the dimer interface of AtuGST2, AtuGST5, AtuGST6 and AtuGST7 is dominated by polar interactions. These results suggested that AtuGSTs could be involved in a broad range of biological functions including stress tolerance and detoxification of toxic compounds.

THE IMPACT OF UPPER-LEVEL PROCESSES ON THE INTENSITY AND STRUCTURAL CHANGES OF HURRICANE SANDY (2012)

The first part of this study examines the relative roles of frontogenesis and tropopause undulation in determining the intensity and structural changes of Hurricane Sandy (2012) using a high-resolution cloud-resolving model. A 138-h simulation reproduces Sandy’s four distinct development stages: (i) rapid intensification, (ii) weakening, (iii) steady maximum surface wind but with large continued sea-level pressure (SLP) falls, and (iv) re-intensification. Results show typical correlations between intensity changes, sea-surface temperature and vertical wind shear during the first two stages. The large SLP falls during the last two stages are mostly caused by Sandy’s moving northward into lower-tropopause regions associated with an eastward-propagating midlatitude trough, where the associated lower-stratospheric warm air wraps into the storm and its surrounding areas. The steady maximum surface wind occurs because of the widespread SLP falls with weak pressure gradients lacking significant inward advection of absolute angular momentum (AAM). Meanwhile, there is a continuous frontogenesis in the outer region during the last three stages. Cyclonic inward advection of AAM along each frontal rainband accounts for the continued expansion of the tropical-storm-force wind and structural changes, while deep convection in the eyewall and merging of the final two survived frontal rainbands generate a spiraling jet in Sandy’s northwestern quadrant, leading to its re-intensification prior to landfall. The physical, kinematic and dynamic aspects of an upper-level outflow layer and its possible impact on the re-intensification of Sandy are examined in the second part of this study. Above the outflow layer isentropes are tilted downward with radius as a result of the development of deep convection and an approaching upper-level trough, causing weak subsidence. Its maximum outward radial velocity is located above the cloud top, so the outflow channel experiences cloud-induced long-wave cooling. Because Sandy has two distinct convective regions (an eyewall and a frontal rainband), it has multiple outflow layers, with the eyewall’s outflow layer located above that of the frontal rainband. During the re-intensification stage, the eyewall’s outflow layer interacts with a jet stream ahead of the upper-level trough axis. Because of the presence of inertial instability on the anticyclonic side of the jet stream and symmetric instability in the inner region of the outflow layer, Sandy’s secondary circulation intensifies. Its re-intensification ceases when these instabilities disappear. The relationship between the intensity of the secondary circulation and dynamic instabilities of the outflow layer suggests that the re-intensification occurs in response to these instabilities. Additionally, it is verified that the long-wave cooling in the outflow layer helps induce symmetric instability by reducing static stability.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

MULTISCALE MODELING OF LIQUID CRYSTALLINE/NANOTUBE COMPOSITES

The objective of this research is to synthesize structural composites designed with particular areas defined with custom modulus, strength and toughness values in order to improve the overall mechanical behavior of the composite. Such composites are defined and referred to as 3D-designer composites. These composites will be formed from liquid crystalline polymers and carbon nanotubes. The fabrication process is a variation of rapid prototyping process, which is a layered, additive-manufacturing approach. Composites formed using this process can be custom designed by apt modeling methods for superior performance in advanced applications. The focus of this research is on enhancement of Young's modulus in order to make the final composite stiffer. Strength and toughness of the final composite with respect to various applications is also discussed. We have taken into consideration the mechanical properties of final composite at different fiber volume content as well as at different orientations and lengths of the fibers. The orientation of the LC monomers is supposed to be carried out using electric or magnetic fields. A computer program is modeled incorporating the Mori-Tanaka modeling scheme to generate the stiffness matrix of the final composite. The final properties are then deduced from the stiffness matrix using composite micromechanics. Eshelby's tensor, required to calculate the stiffness tensor using Mori-Tanaka method, is calculated using a numerical scheme that determines the components of the Eshelby's tensor (Gavazzi and Lagoudas 1990). The numerical integration is solved using Gaussian Quadrature scheme and is worked out using MATLAB as well. . MATLAB provides a good deal of commands and algorithms that can be used efficiently to elaborate the continuum of the formula to its extents. Graphs are plotted using different combinations of results and parameters involved in finding these results

ADVANCED COMPUTATIONAL MODELING OF THE INTERNAL STRUCTURE OF SMART WIND-TURBINE BLADES

Implementation of stable aeroelastic models with the ability to capture the complex features of Multi concept smartblades is a prime step in reducing the uncertainties that come along with blade dynamics. The numerical simulations of fluid structure interaction can thus be used to test a realistic scenarios comprising of full-scale blades at a reasonably low computational cost. A code which was a combination of two advanced numerical models was designed and was run with the help of paralell HPC supercomputer platform. The first model was based on a variation of dimensional reduction technique proposed by Hodges and Yu. This model was the one to record the structural response of heterogenous composite blades. This technique reduces the geometrical complexities of the heterogenous blade section into a stiffness matrix for an equivalent beam. This derived equivalent 1-D strain energy matrix is similar to the actual 3-D strain energy matrix in an asymptotic sense. As this 1-D matrix helps in accurately modeling the blade structure as a 1-D finite element problem, this substantially redues the computational effort and subsequently the computational cost that are required to model the structural dynamics at each step. Second model comprises of implementation of the Blade Element Momentum Theory. In this approach we map all the velocities and the forces with the help of orthogonal matrices that help in capturing the large deformations and the effects of rotations in calculating the aerodynamic forces. This ultimately helps us to take into account the complex flexo torsional deformations. In this thesis we have succesfully tested these computayinal tools developed by MTU’s research team lead by for the aero elastic analysis of wind-turbine blades. The validation in this thesis is majorly based on several experiments done on NREL-5MW blade, as this is widely accepted as a benchmark blade in the wind industry. Along with the use of this innovative model the internal blade structure was also changed to add up to the existing benefits of the already advanced numerical models.

Structural Health Monitoring Inside Concrete and Grout Using the Wireless Identification and Sensing Platform (WISP)

This research investigates the implementation of battery-less RFID sensing platforms inside lossy media, such as, concrete and grout. Both concrete and novel grouts can be used for nuclear plant decommissioning as part of the U.S. Department of Energy’s (DOE’s) cleanup projects. Our research examines the following: (1) material characterization, (2) analytical modeling of transmission and propagation losses inside lossy media, (3) maximum operational range of RFID wireless sensors embedded inside concrete and grout, and (4) best positioning of antennas for achieving longer communication range between RFID antennas and wireless sensors. Our research uses the battery-less Wireless Identification and Sensing Platform (WISP) which can be used to monitor temperature, and humidity inside complex materials. By using a commercial Agilent open-ended coaxial probe (HP8570B), the measurements of the dielectric permittivity of concrete and grout are performed. Subsequently, the measured complex permittivity is used to formulate analytical Debye models. Also, the transmission and propagation losses of a uniform plane wave inside grout are calculated. Our results show that wireless sensors will perform better in concrete than grout. In addition, the maximum axial and radial ranges for WISP are experimentally determined. Our work illustrates the feasibility of battery-less wireless sensors that are embedded inside concrete and grout. Also, our work provides information that can be used to optimize the power management, sampling rate, and antenna design of such sensors.

Challenges in imaging and predictive modeling of rhizosphere processes

Background Plant-soil interaction is central to human food production and ecosystem function. Thus, it is essential to not only understand, but also to develop predictive mathematical models which can be used to assess how climate and soil management practices will affect these interactions. Scope In this paper we review the current developments in structural and chemical imaging of rhizosphere processes within the context of multiscale mathematical image based modeling. We outline areas that need more research and areas which would benefit from more detailed understanding. Conclusions We conclude that the combination of structural and chemical imaging with modeling is an incredibly powerful tool which is fundamental for understanding how plant roots interact with soil. We emphasize the need for more researchers to be attracted to this area that is so fertile for future discoveries. Finally, model building must go hand in hand with experiments. In particular, there is a real need to integrate rhizosphere structural and chemical imaging with modeling for better understanding of the rhizosphere processes leading to models which explicitly account for pore scale processes.

Diachronic and Synchronic Indexing: Modeling Conceptual Change in Indexing Languages

This paper outlines a model of conceptual change in indexing languages. Findings from this modeling effort point to three ways meaning and relationships are established and then change in an indexing language. These ways: structural, terminological, and textual point to ways indexing language metadata can aid in managing conceptual change in indexing languages.

Advanced numerical modeling of masonry vaulted structures based on BIM parametric geometry generation

Vaults are an architectural element which during construction history have been built with a great variety of different materials, shapes, and sizes. The shape of these structural elements was often dependent by the necessity to cover complex spaces, by the needed loading capacity, or by architectural aesthetics. Within this complex scenario masonry patterns generates also different effects on loading capacity, load percolation and stiffness of the structure. These effects were been extensively investigated, both with empirical observations and with modern numerical methods. While most of them focus on analyzing the load bearing capacity or the texture effect on vaulted structures, the aim of this analysis is to investigate on the effects of the variation of a single structural characteristic on the load percolation in the vault. Moreover, an additional purpose of the work is related to the coding of a parametrical model aiming at generating different masonry vaulted structures. Nevertheless, proposed script can generate different typology of vaulted structure basing on some structural characteristics, such as the span and the length to cover and the dimensions of the blocks.