A. James Clark School of Engineering

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The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

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    MONTE CARLO SIMULATIONS OF BRILLOUIN SCATTERING IN TURBID MEDIA
    (2023) Lashley, Stephanie; Chembo, Yanne K; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Brillouin microscopy is a non-invasive, label-free optical elastography method for measuring mechanical properties of cells. It provides information on the longitudinal modulus and viscosity of a medium, which can be indicators of traumatic brain injury, cancerous tumors, or fibrosis. All optical techniques face difficulties imaging turbid media, and Monte Carlo simulations are considered the gold-standard to model these scenarios. Brillouin microscopy adds a unique challenge to this problem due to the angular dependence of the scattering event. This thesis extends a traditional Monte Carlo simulation software by adding the capability to simulate Brillouin scattering in turbid media, which provides a method to test strategies to mitigate the effects of multiple elastic scattering without the time and cost associated with physical experiments. Experimental results have shown potential methods to alleviate the problems caused by multiple elastic scattering, and this thesis will verify the simulation results against the experimental findings.
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    A MULTISCALE MODEL FOR AN ATOMIC LAYER DEPOSITION PROCESS
    (2010) Dwivedi, Vivek Hari; Adomaitis, Raymond A; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Atomic layer deposition (ALD) is a deposition technique suitable for the con- trolled growth of thin films. During ALD, precursor gasses are supplied to the reactor in an alternating sequence producing individual atomic layers through self- limiting reactions. Thin films are grown conformally with atomic layer control over surfaces with topographical features. A very promising material system for ALD growth is aluminum oxide. Alu- minum oxide is highly desirable for both its physical and electronic characteristics. Aluminum oxide has a very high band gap (~ 9 ev) and a high dielectric constant (k ~ 9). The choice of precursors for aluminum oxide atomic layer deposition vary from aluminum halide, alkyl, and alkoxides for aluminum-containing molecules; for oxygen-containing molecules choices include oxygen, water, hydrogen peroxide and ozone. For this work a multiscale simulation is presented where aluminum oxide is deposited inside anodic aluminum oxide (AAO) pores for the purposes of tuning the pore diameter. Controlling the pore diameter is an import step in the conversion of AAO into nanostructered catalytic membranes (NCM). Shrinking the pore size to a desired radius allows for the control of the residence time for molecules entering the pore and a method for molecular filtration. Furthermore pore diameter control would allow for the optimization of precursor doses making this a green process. Inherently, the ALD of AAO is characterized by a slow and a faster time scale where film growth is on the order of minutes and hours and surface reactions are near instantaneous. Likewise there are two length scales: film thickness and composition on the order of nanometers and pore length on the order of microns. The surface growth is modeled in terms of a lattice Monte Carlo simulation while the diffusion of the precursor gas along the length of the pore is modeled as a Knudsen diffusion based transport model.
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    Modeling and validation of dosimetry measurement assumptions within the Armed Forces Radiobiology Research Institute TRIGA Mark F reactor and associated exposure facilities using Monte Carlo techniques
    (2009) Hall, Donald Edward; Modarres, Mohammad; Al-Sheikhly, Mohamad; Nuclear Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The TRIGA Mark F reactor at the Armed Forces Radiobiology Research Institute in Bethesda Maryland is a 1 megawatt steady state reactor which can also be operated in pulse mode at a power of up to 2500 megawatts. It is characterized by a moveable core and two large exposure rooms, rather than a thermal column or beam ports, as found in most research reactors. A detailed model of the reactor and the associated exposure facilities was developed using the Monte Carlo N-Particle (MCNP) and Monte Carlo N-Particle Extended (MCNPX) software programs. The model was benchmarked against operational data from the reactor, to include total core excess reactivity, control rod worths, and nominal fuel element worths. The model was then used to model burnup within individual fuel elements within the core to determine the effect of core movement within the reactor pool on individual element burnup. Movement of the core with respect to the two exposure rooms was modeled to determine the effect of movement of the core on the radiation fields and gamma and neutron fluxes within the exposure rooms. Additionally, the model was used to demonstrate the effectiveness of gadolinium paint used within the exposure rooms to reduce thermal neutron production and subsequent Ar41 production within the exposure rooms. The model showed a good approximation to measured benchmark data across all applied metrics, and additionally provided confirmation of data on dose rates within the exposure rooms. It also showed that, while there was some variation of burnup within individual fuel elements based on core position within the reactor pool, the overall effect was negligible for effective fuel management within the core. Finally, the model demonstrated explicitly that the use of gadolinium paint within the exposure rooms was, and remains, an effective way of reducing the thermal flux, and subsequent Ar-41 production within the exposure rooms. It also demonstrated that the gadolinium paint also resulted in a much steeper neutron flux gradient within the exposure rooms than would have been obtained had neutrons been allowed to thermalize within the wood walls lining the rooms and then reenter the exposure facilities.
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    IN-SITU MEASUREMENT OF EPITHELIAL TISSUE OPTICAL PROPERTIES: DEVELOPMENT AND IMPLEMENTATION OF DIFFUSE REFLECTANCE SPECTROSCOPY TECHNIQUES
    (2009) Wang, Quanzeng; Wang, Nam Sun; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Cancer is a severe threat to human health. Early detection is considered the best way to increase the chance for survival. While the traditional cancer detection method, biopsy, is invasive, noninvasive optical diagnostic techniques are revolutionizing the way that cancer is diagnosed. Reflectance spectroscopy is one of these optical spectroscopy techniques showing promise as a diagnostic tool for pre-cancer detection. When a neoplasia occurs in tissue, morphologic and biochemical changes happen in the tissue, which in turn results in the change of optical properties and reflectance spectroscopy. Therefore, a pre-cancer can be detected by extracting optical properties from reflectance spectroscopy. This dissertation described the construction of a fiberoptic based reflectance system and the development of a series of modeling studies. This research is aimed at establishing an improved understanding of the optical properties of mucosal tissues by analyzing reflectance signals at different wavelengths. The ultimate goal is to reveal the potential of reflectance-based optical diagnosis of pre-cancer. The research is detailed in Chapter 3 through Chapter 5. Although related with each other, each chapter was designed to become a journal paper ultimately. In Chapter 3, a multi-wavelength, fiberoptic system was constructed, evaluated and implemented to determine internal tissue optical properties at ultraviolet A and visible wavelengths. A condensed Monte Carlo model was deployed to simulate light-tissue interaction and generate spatially distributed reflectance data. These data were used to train an inverse neural network model to extract tissue optical properties from reflectance. Optical properties of porcine mucosal and liver tissues were finally measured. In Chapter 4, the condensed Monte Carlo method was extended so that it can rapidly simulate reflectance from a single illumination-detection fiber thus enabling the calculation of large data sets. The model was implemented to study spectral reflectance changes due to breast cancer. The effect of adding an illumination-detection fiber to a linear array fiber for optical property determination was also evaluated. In Chapter 5, an investigation of extracting the optical properties from two-layer tissues was performed. The relationship between spatially-resolved reflectance distributions and optical properties in two-layer tissue was investigated. Based on all the aforementioned studies, spatially resolved reflectance system coupled with condensed Monte Carlo and neural network models was found to be objective and appear to be sensitive and accurate in quantitatively assessing optical property change of mucosal tissues.
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    Integrated Methodology for Thermal-Hydraulics Uncertainty Analysis (IMTHUA)
    (2007-01-25) Pour-Gol-Mohamad, Mohammad; Modarres, Mohammad; Mosleh, Ali; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This dissertation describes a new integrated uncertainty analysis methodology for "best estimate" thermal hydraulics (TH) codes such as RELAP5. The main thrust of the methodology is to utilize all available types of data and information in an effective way to identify important sources of uncertainty and to assess the magnitude of their impact on the uncertainty of the TH code output measures. The proposed methodology is fully quantitative and uses the Bayesian approach for quantifying the uncertainties in the predictions of TH codes. The methodology also uses the data and information for a more informed and evidence-based ranking and selection of TH phenomena through a modified PIRT method. The modification considers importance of various TH phenomena as well as their uncertainty importance. In identifying and assessing uncertainties, the proposed methodology treats the TH code as a white box, thus explicitly treating internal sub-model uncertainties, and propagation of such model uncertainties through the code structure as well as various input parameters. A The TH code output is further corrected through a Bayesian updating with available experimental data from integrated test facilities. It utilizes the data directly or indirectly related to the code output to account implicitly for missed/screened out sources of uncertainties. The proposed methodology uses an efficient Monte Carlo sampling technique for the propagation of uncertainty using modified Wilks sampling criteria. The methodology is demonstrated on the LOFT facility for 200% cold leg LBLOCA transient scenario.