Doctor of Philosophy

dissertationA polytype of wollastonite, 2M-wollastonite, that breaks into acicular particles under external forces is being synthesized through two different processes, namely a Partial Melting and Recrystallization Process (PMR Process) and a Flux Growth Process (FG Process). The PMR Process combines the advantages of the solid state reaction and liquid phase reaction methods by creating a partially melted phase to maintain the original shape of the compacts of raw materials while melted regions form locally within the compacts, providing a favorable environment for the growth of alpha-wollastonite in the first step. The target crystal, 2M-wollastonite, nucleates and grows during the subsequent recrystallization stage. Using this process, effects of additives on the preparation of acicular wollastonite particles were investigated. It was found that B2O3 is one of the melting point depressing additives that can lower the melting point of the raw mixtures significantly in a small amount. Li2O is one of the catalytic additives that promote the formation of acicular wollastonite particles. The FG Process completely melt the raw mixtures in a suitable crucible at temperatures above 1400oC, and then lets the melt solidify under a favorable cooling rate to allow the nucleation and growth of 2M-wollastotnite during this stage. It takes advantage of the heat transfer properties of the melt-crucible-furnace wall (MCF) system; a vertical temperature gradient is achieved to provide sites for the preferable nucleation of 2M-wollatonite crystals at the top melt surface. The solidified products contain nearly pure 2M-wollastonite crystals as the major component and an amorphous glass phase as the minor part. Both the PMR and FG processes yielded high-aspect-ratio (HAR) particles. The crystals grown by the PMR process were small in size but large in number, and they grew randomly in the final products. The crystals grown by the FG process were aligned and they formed cellular and dendritic patterns. Such a growth behavior offers additional benefits for producing HAR wollastonite particles. When the two processes were compared, the FG process surpasses the PMR process in terms of efficiency. Modeling and simulation work was done on the FG process that presented cellular and dendritic growth. Based on experimental studies, an empirical model was proposed that modified the existing models on predicting cellular and dendritic growth on a SiO2-CaO-B2O3-Li2O ceramic alloy under high temperature unsteady-state heat transfer. Using this new model, the growth rate and primary arm spacing were predicted well compared with experimental observations. Besides, the average growth front, solidification volume fraction, and mean aspect ratio were also simulated. The simulation work helped to understand and predict the growth of wollastonite crystals in a significant way

The Fidelity of Measurement-Based Quantum Computation under a Boson Environment

We investigate the fidelity of the measurement-based quantum computation (MBQC) when it is coupled with boson environment, by measuring cluster state fidelity and gate fidelity. Two different schemes of cluster state preparation are studied. In the Controlled-Z (CZ) creation scheme, cluster states are prepared by entangling all qubits in $|+\rangle$ state with CZ gates on all neighboring sites. The fidelity shows an oscillation pattern over time evolution. The influence of environment temperature is evaluated, and suggestions are given to enhance the performance of MBQC realized in this way. In the Hamiltonian creation scheme, cluster states are made by cooling a system with cluster Hamiltonians, of which ground states are cluster states. The fidelity sudden drop phenomenon is discovered. When the coupling is below a threshold, MBQC systems are highly robust against the noise. Our main environment model is the one with a single collective bosonic mode.Comment: 13 pages, 16 figure

3,4-Bis(4-meth­oxy­phen­yl)-2,5-dihydro-1H-pyrrole-2,5-dione

In the title compound, C18H15NO4, the benzene rings form quite different dihedral angles [16.07 (1) and 59.50 (1)°] with the central pyrrole ring, indicating a twisted mol­ecule. Conjugation is indicated between the five- and six-membered rings by the lengths of the C—C bonds which link them [1.462 (3) and 1.477 (3) Å]. The most prominent feature of the crystal packing is the formation of inversion dimers via eight-membered {⋯HNCO}2 synthons

Evaluating Wind-driven Natural Ventilation Potential for Early Building Design

Natural ventilation is widely applied in buildings considering its potential of improving indoor air quality and saving building energy costs. However, to evaluate its viability and determine the ventilation rates quickly and relatively accurately during early design stage is challenging. This paper explores a fast and accurate evaluation approach in the form of empirical equations to estimate the ventilation rate and potential of wind-driven natural ventilation. By using computational fluid dynamics (CFD) with results validated for both cross and single natural ventilation strategies, this study conducted a series of simulations to determine critical ventilation coefficients for the empirical equations as functions of wind direction, speed and building height. The proposed evaluation approach could help architects and engineers to evaluate the viability of natural ventilation during early building design. This approach was also demonstrated to evaluate the potential of natural ventilation in 65 cities of North America so a series of natural ventilation potential maps were generated for a better understanding of natural ventilation potential in different climates and for the climate-conscious design of buildings in North America

Eco-development of oil and gas industry: CCUS-EOR technology

The current status and development prospects of CCUS-EOR technology development are sorted out from the perspective of ecological development. A good foundation is laid to promote the world low-carbon development pattern and the development of CCUS-EOR technology in oil-rich, low-permeability reservoirs. By analyzing the differences between China and the United States regarding the technology level, application scale, and production effect, the development gaps between different countries in terms of CO2 burial for enhanced oil and gas recovery are derived. In response to these gaps, recommendations for responsive technology research and supporting infrastructure construction are proposed, which are of reference significance for advancing the development of large-scale CCUS technology for all of humanity

Fourier neural operator for real-time simulation of 3D dynamic urban microclimate

Global urbanization has underscored the significance of urban microclimates for human comfort, health, and building/urban energy efficiency. They profoundly influence building design and urban planning as major environmental impacts. Understanding local microclimates is essential for cities to prepare for climate change and effectively implement resilience measures. However, analyzing urban microclimates requires considering a complex array of outdoor parameters within computational domains at the city scale over a longer period than indoors. As a result, numerical methods like Computational Fluid Dynamics (CFD) become computationally expensive when evaluating the impact of urban microclimates. The rise of deep learning techniques has opened new opportunities for accelerating the modeling of complex non-linear interactions and system dynamics. Recently, the Fourier Neural Operator (FNO) has been shown to be very promising in accelerating solving the Partial Differential Equations (PDEs) and modeling fluid dynamic systems. In this work, we apply the FNO network for real-time three-dimensional (3D) urban wind field simulation. The training and testing data are generated from CFD simulation of the urban area, based on the semi-Lagrangian approach and fractional stepping method to simulate urban microclimate features for modeling large-scale urban problems. Numerical experiments show that the FNO model can accurately reconstruct the instantaneous spatial velocity field. We further evaluate the trained FNO model on unseen data with different wind directions, and the results show that the FNO model can generalize well on different wind directions. More importantly, the FNO approach can make predictions within milliseconds on the graphics processing unit, making real-time simulation of 3D dynamic urban microclimate possible

Metamodel Development for Predicting Hygrothermal Performance of Wood-Frame Wall under Rain Leakage

In recent years, stochastic modeling has been increasingly applied to investigate the uncertainties of input parameters in hygrothermal simulation and the moisture damage risks of building envelopes. Generally, stochastic modeling requires hundreds or even thousands of simulations to take into account the uncertainties of input parameters, which is computationally intensive and timeconsuming. This paper aims to apply polynomial and neural network metamodel as a substitute for the traditional hygrothermal model, to predict the hygrothermal performance of building envelopes. In the previous study carried out by the authors, stochastic simulations have been performed based on the traditional hygrothermal model, to investigate the hygrothermal performance of wood-frame walls under different rain leakage levels. The material properties and rain deposition factors were considered as stochastic variables, and stochastic simulations were performed under three rain leakage scenarios: 1%, 0.5% and 0.1% of wind-driven rain. In this paper, the stochastic inputs (the hygric material properties and rain deposition factor) and outputs (the maximum moisture content and mold growth index over a 5-year period of the simulation) of a conventional 2×6 wood-frame wall are used to develop the metamodels through polynomial regression and neural network methods. The metamodels are developed for each rain leakage scenario, and the stochastic data of the three rain leakage scenarios are aggregated together to train another metamodel. It is found that the metamodels generally perform well to predict the maximum moisture content and mold growth index. The metamodels for low rain leakage scenarios are better than those for high rain leakage scenarios and the neural network metamodel is more accurate than polynomial metamodel for high rain leakage scenarios, i.e. 1% of rain leakage

Parametric study of air curtain door aerodynamics performance based on experiments and numerical simulations

Air curtains have been widely used to reduce infiltration through door openings and save heating/cooling energy in different types of buildings. Previous studies have found that there exist three aerodynamics conditions: optimum condition (OC), inflow break-through (IB), and outflow break-through (OB) conditions, which are important for categorizing air curtain performance subject to such key parameters including supply speed and angle, and presence of a person during an actual operation. However, few studies have focused on the effects of these parameters on air curtain performance in terms of resisting infiltration and reducing exfiltration. This research presents a parametric study of air curtain performance based on reduced-scale experiments and full-scale numerical simulations. It was found that increasing air curtain supply angle improves air curtain performance when it is operated under the OC and IB conditions but creates excessive exfiltration under the OB condition. Increasing supply speed of air curtain generally improves the air curtain performance whereas this improvement deteriorates with the increase of supply angle under the OB condition. The presence of person, either directly under or below the air curtain, almost has no effect on the infiltration/exfiltration during the OC condition. Moreover, the person in the doorway can block airflow from both directions, contributing to less infiltration under the IB condition and less exfiltration under the OB condition than without the person. This study provides valuable insights into air curtain aerodynamics performance under different operational conditions and key contributing parameters