Effect of Termination of Long-term Free Air CO2 Enrichment on Physiology and Carbon Allocation in a Loblolly Pine Dominated Forest

This dissertation examined the response to termination of CO2 enrichment of a forest ecosystem exposed to long-term elevated atmospheric CO2 condition, and aimed at investigating responses and their underlying mechanisms of two important factors of carbon cycle in the ecosystem, stomatal conductance and soil respiration. Because the contribution of understory vegetation to the entire ecosystem grew with time, we first investigated the effect of elevated CO2 on understory vegetation. Potential growth enhancing effect of elevated CO2 were not observed, and light seemed to be a limiting factor. Secondly, we examined the importance of aerodynamic conductance to determine canopy conductance, and found that its effect can be negligible. Responses of stomatal conductance and soil respiration were assessed using Bayesian state space model. In two years after the termination of CO2 enrichment, stomatal conductance in formerly elevated CO2 returned to ambient level, while soil respiration became smaller than ambient level and did not recovered to ambient in two years.

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.

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.

Major ion chemistry of snow cores along a transect in central Dronning Maud Land, Antarctica

Among the large variety of particulates in the atmosphere, calcic mineral dust particles have highly reactive surfaces that undergo heterogeneous reactions with nitrogen oxides contiguously. The association between Ca2+, an important proxy indicator of mineral dust and NO3-, a dominant anion in the Antarctic snow pack was analysed. A total of 41 snow cores (~ 1 m each) that represent snow deposited during 2008-2009 were studied along coastal-inland transects from two different regions - the Princess Elizabeth Land (PEL) and central Dronning Maud Land (cDML) in East Antarctica. Correlation statistics showed a strong association (at 99 % significance level) between NO3- and Ca2+ at the near-coastal sections of both PEL (r = 0.72) and cDML (r = 0.76) transects. Similarly, a strong association between these ions was also observed in snow deposits at the inland sections of PEL (r = 0.8) and cDML (r = 0.85). Such systematic associations between Ca2+ and NO3- is attributed to the interaction between calcic mineral dust and nitrogen oxides in the atmosphere, leading to the possible formation of calcium nitrate (Ca(NO3)2). Forward and back trajectory analyses using HYSPLIT model v. 4 revealed that Southern South America (SSA) was an important dust emitting source to the study region, aided by the westerlies. Particle size distribution showed that over 90 % of the dust was in the range < 4 µm, indicating that these dust particles reached the Antarctic region via long range transport from the SSA region. We propose that the association between Ca2+ and NO3- occurs during the long range transport due to the formation of Ca(NO3)2. The Ca(NO3)2 thus formed in the atmosphere undergo deposition over Antarctica under the influence of anticyclonic polar easterlies. However, influence of local dust sources from the nunataks in cDML evidently mask such association in the mountainous region. The study indicates that the input of dust-bound NO3- may contribute a significant fraction of the total NO3- deposited in Antarctic snow.

Age determinaton and age model of sediments from the Bay of Biscay

Continuous high-resolution mass accumulation rates (MAR) and X-ray fluorescence (XRF) measurements from marine sediment records in the Bay of Biscay (NE Atlantic) have allowed the determination of the timing and the amplitude of the 'Fleuve Manche' (Channel River) discharges during glacial stages MIS 10, MIS 8, MIS 6 and MIS 4-2. These results have yielded detailed insight into the Middle and Late Pleistocene glaciations in Europe and the drainage network of the western and central European rivers over the last 350 kyr. This study provides clear evidence that the 'Fleuve Manche' connected the southern North Sea basin with the Bay of Biscay during each glacial period and reveals that 'Fleuve Manche' activity during the glaciations MIS 10 and MIS 8 was significantly less than during MIS 6 and MIS 2. We correlate the significant 'Fleuve Manche' activity, detected during MIS 6 and MIS 2, with the extensive Saalian (Drenthe Substage) and the Weichselian glaciations, respectively, confirming that the major Elsterian glaciation precedes the glacial MIS 10. In detail, massive 'Fleuve Manche' discharges occurred at ca 155 ka (mid-MIS 6) and during Termination I, while no significant discharges are found during Termination II. It is assumed that a substantial retreat of the European ice sheet at ca 155 kyr, followed by the formation of ice-free conditions between the British Isles and Scandinavia until Termination II, allowed meltwater to flow northwards through the North Sea basin during the second part of the MIS 6. We assume that this glacial pattern corresponds to the Warthe Substage glacial maximum, therefore indicating that the data presented here equates to the Drenthe and the Warthe glacial advances at ca 175-160 ka and ca 150-140 ka, respectively. Finally, the correlation of our records with ODP site 980 reveals that massive 'Fleuve Manche' discharges, related to partial or complete melting of the European ice masses, were synchronous with strong decreases in both the rate of deep-water formation and the strength of the Atlantic thermohaline circulation. 'Fleuve Manche' discharges over the last 350 kyr probably participated, with other meltwater sources, in the collapse of the thermohaline circulation by freshening the northern Atlantic surface water.

Antarctic free-air and complete Bouguer gravity anomaly grid

Gravity surveying is challenging in Antarctica because of its hostile environment and inaccessibility. Nevertheless, many ground-based, airborne and shipborne gravity campaigns have been completed by the geophysical and geodetic communities since the 1980s. We present the first modern Antarctic-wide gravity data compilation derived from 13 million data points covering an area of 10 million km**2, which corresponds to 73% coverage of the continent. The remove-compute-restore technique was applied for gridding, which facilitated levelling of the different gravity datasets with respect to an Earth Gravity Model derived from satellite data alone. The resulting free-air and Bouguer gravity anomaly grids of 10 km resolution are publicly available. These grids will enable new high-resolution combined Earth Gravity Models to be derived and represent a major step forward towards solving the geodetic polar data gap problem. They provide a new tool to investigate continental-scale lithospheric structure and geological evolution of Antarctica.

Seawater carbonate chemistry and growth rate during experiments with phylotypes of Symbiodinium (Dinophyceae), 2011

We investigated the effect of elevated partial pressure of CO2 (pCO2) on the photosynthesis and growth of four phylotypes (ITS2 types A1, A13, A2, and B1) from the genus Symbiodinium, a diverse dinoflagellate group that is important, both free-living and in symbiosis, for the viability of cnidarians and is thus a potentially important model dinoflagellate group. The response of Symbiodinium to an elevated pCO2 was phylotype-specific. Phylotypes A1 and B1 were largely unaffected by a doubling in pCO2 in contrast, the growth rate of A13 and the photosynthetic capacity of A2 both increased by ~ 60%. In no case was there an effect of ocean acidification (OA) upon respiration (dark- or light-dependent) for any of the phylotypes examined. Our observations suggest that OA might preferentially select among free-living populations of Symbiodinium, with implications for future symbioses that rely on algal acquisition from the environment (i.e., horizontal transmission). Furthermore, the carbon environment within the host could differentially affect the physiology of different Symbiodinium phylotypes. The range of responses we observed also highlights that the choice of species is an important consideration in OA research and that further investigation across phylogenetic diversity, for both the direction of effect and the underlying mechanism(s) involved, is warranted.

Using multifractals to evaluate oceanographic model skill

We are in an era of unprecedented data volumes generated from observations and model simulations. This is particularly true from satellite Earth Observations (EO) and global scale oceanographic models. This presents us with an opportunity to evaluate large scale oceanographic model outputs using EO data. Previous work on model skill evaluation has led to a plethora of metrics. The paper defines two new model skill evaluation metrics. The metrics are based on the theory of universal multifractals and their purpose is to measure the structural similarity between the model predictions and the EO data. The two metrics have the following advantages over the standard techniques: a) they are scale-free, b) they carry important part of information about how model represents different oceanographic drivers. Those two metrics are then used in the paper to evaluate the performance of the FVCOM model in the shelf seas around the south-west coast of the UK.

Using multifractals to evaluate oceanographic model skill

We are in an era of unprecedented data volumes generated from observations and model simulations. This is particularly true from satellite Earth Observations (EO) and global scale oceanographic models. This presents us with an opportunity to evaluate large scale oceanographic model outputs using EO data. Previous work on model skill evaluation has led to a plethora of metrics. The paper defines two new model skill evaluation metrics. The metrics are based on the theory of universal multifractals and their purpose is to measure the structural similarity between the model predictions and the EO data. The two metrics have the following advantages over the standard techniques: a) they are scale-free, b) they carry important part of information about how model represents different oceanographic drivers. Those two metrics are then used in the paper to evaluate the performance of the FVCOM model in the shelf seas around the south-west coast of the UK.

Development of the Oxide Ion Conductor Na0.5Bi0.5TiO3 (NBT) for Solid Oxide Cells

Na0.5Bi0.5TiO3 (NBT) is a well-known lead-free piezoelectric material with potential to replace lead zirconate titanate (PZT),1 however high leakage conductivity for the material has been widely reported.2 Through a combination of Impedance Spectroscopy (IS), O2- ion transference (EMF) number experiments and O18 tracer diffusion measurements, combined with Time-of-flight Secondary Ion Mass Spectrometry (TOFSIMS), it was identified that this leakage conductivity was due to oxygen ion conductivity. The volatilization of bismuth during synthesis, causing oxygen vacancies, is believed to be responsible for the leakage conductivity.3 The oxide-ion conductivity, when doped with magnesium, exceeds that of yttria-stabilized zirconia (YSZ) at ~500 °C,3 making it a potential electrolyte material for Intermediate Temperature Solid Oxide Cells (ITSOCs). Figure 1 shows the comparison of bulk oxide ion conductivity between 2 at.% Mg-doped NBT and other known oxide ion conductors.

As part of the UK wide £5.7m 4CU project, research has concentrated on trying to develop NBT for use in Intermediate Temperature Solid Oxide Cells (ITSOCS). With the aim of achieving mixed ionic and electronic conduction, transition metals were chemically doped on to the Ti-site. A range of experimental techniques was used to characterize the materials aimed at investigating both conductivity and material structure (Scanning Electron Microscopy (SEM), IS, X-ray Photoelectron Spectroscopy (XPS) and X-ray Absorption Spectroscopy (XAS)). The potential for NBT as an ITSOC material, as well as the challenges of developing the material, will be discussed.

(1) Takenaka T. et al. Jpn. J. Appl. Phys 1999, 30, 2236.

(2) Hiruma Y. et al. J. Appl. Phys 2009, 105, 084112.

(3) Li. M. et al. Nature Materials 2013, 13, 31.

Feature recognition & tool path generation for 5 axis step-nc machining of free form / irregular contoured surfaces

This research paper presents a five step algorithm to generate tool paths for machining Free form / Irregular Contoured Surface(s) (FICS) by adopting STEP-NC (AP-238) format. In the first step, a parametrized CAD model with FICS is created or imported in UG-NX6.0 CAD package. The second step recognizes the features and calculates a Closeness Index (CI) by comparing them with the B-Splines / Bezier surfaces. The third step utilizes the CI and extracts the necessary data to formulate the blending functions for identified features. In the fourth step Z-level 5 axis tool paths are generated by adopting flat and ball end mill cutters. Finally, in the fifth step, tool paths are integrated with STEP-NC format and validated. All these steps are discussed and explained through a validated industrial component.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.

New Method Based on the UNIFAC–VISCO Model for the Estimation of Ionic Liquids Viscosity Using the Experimental Data Recommended by Mathematical Gnostics

The viscosity of ionic liquids (ILs) has been modeled as a function of temperature and at atmospheric pressure using a new method based on the UNIFAC–VISCO method. This model extends the calculations previously reported by our group (see Zhao et al. J. Chem. Eng. Data 2016, 61, 2160–2169) which used 154 experimental viscosity data points of 25 ionic liquids for regression of a set of binary interaction parameters and ion Vogel–Fulcher–Tammann (VFT) parameters. Discrepancies in the experimental data of the same IL affect the quality of the correlation and thus the development of the predictive method. In this work, mathematical gnostics was used to analyze the experimental data from different sources and recommend one set of reliable data for each IL. These recommended data (totally 819 data points) for 70 ILs were correlated using this model to obtain an extended set of binary interaction parameters and ion VFT parameters, with a regression accuracy of 1.4%. In addition, 966 experimental viscosity data points for 11 binary mixtures of ILs were collected from literature to establish this model. All the binary data consist of 128 training data points used for the optimization of binary interaction parameters and 838 test data points used for the comparison of the pure evaluated values. The relative average absolute deviation (RAAD) for training and test is 2.9% and 3.9%, respectively.