UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.
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Item CFD INVESTIGATION OF A PULSE JET MIXED VESSEL WITH RANS, LES, AND LBM SIMULATION MODELS(2023) Kim, Jung; Calabrese, Richard V.; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Pulse Jet Mixed (PJM) vessels are used to process nuclear waste due to their maintenance free operation. In this study we model the turbulent velocity field in water during normal PJM operation to gain insight into vessel operations and to evolve a modeling strategy for process design and operator training. Three transient simulation models, developed using Large Eddy Simulation (LES), unsteady Reynolds-Averaged Navier-Stokes (RANS), and Lattice Boltzmann Method (LBM) techniques, are compared to velocity measurements acquired for 3 test scenarios at 3 locations in a pilot scale vessel at the US DOE National Energy Technology Laboratory (NETL). The LES and RANS simulations are performed in ANSYS Fluent, and the LBM simulations in M-STAR.The LES model well predicts the experimental data provided that the operational pressure profile within the individual pulse tubes is considered. While the RANS model failed to predict the data and exhibited significant differences from LES with respect to turbulence quantities, it is a useful comparison tool that can quickly predict averaged flow parameters. The LBM model’s rigid grid system is deemed unsuitable, as currently configured, for the NETL PJM vessel’s wide range of length scales and curved boundaries, resulting in the longest simulation time and least accurate velocity predictions. Predicted velocity and turbulence metrics are explored to better understand the strengths and failures of the three models. Because the LES model produced the most accurate predictions, it is exploited to generate animations and still images on various 2D planes that depict extremely complex flow patterns throughout the vessel with numerous local jets and mixing layer vortices The study concludes with recommendations for future research to improve the model development and validation strategy.Item COMPUTATIONAL FLUID DYNAMICS ANALYSIS OF SPATIALLY-RESOLVED SPRAY SCANNING SYSTEM (4S) SPRAY PATTERNS(2023) Bors, Jeffrey; Trouve, Arnaud C; Fire Protection Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In computational fluid dynamics (CFD) fire models, sprinkler sprays are represented in complex numerical simulations using Lagrangian particles. These CFD sprays are typically characterized using a combination of experimental data, literature correlations, and estimation. The Spatially-Resolved Spray Scanning System (4S) machine provides high resolution data to characterize sprays for use in CFD analysis, however a quantitative analysis on the effect of this high resolution data with FDS in realistic fire scenarios has not been completed before. 4S spray data is analyzed and compared to a basic spray estimated from literature correlations with and without the presence of fire to analyze trends. In all environments, the basic nozzle overestimated water flux closer to the center of the nozzle and underestimated water flux farther from the center. Differences between the basic and 4S nozzle ranged from 1% to 240% in the enclosure fire scenario. Investigation into the differences showed the polar water distribution to be the most impactful parameter provided by the 4S. Local azimuthal trends were shown to be significant, but non-impactful in the enclosure fire simulation. Global azimuthal trends were apparent but not significant.Item A STUDY OF THE FIRE DYNAMICS SIMULATOR (FDS)- CREATING LIFE-LIKE MOVIES AND STUDYING THE ACCURACY OF THE LAGRANGIAN PARTICLE MODEL(2022) Hussain, Zishanul Haque; Trouve, Arnaud; Fire Protection Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Fire Dynamic Simulator (FDS) is a computational fluid dynamics (CFD) model of firedrivenfluid flow. It was first released publicly in February 2000. Using SmokeView or Pyrosim to view the results of FDS simulations provides a powerful non-immersive virtual reality experience. It can be used in fire engineering, fire safety training, and fire investigation. By providing a more engaging and interactive user experience, nonimmersive VR can help improve understanding and develop effective fire safety and prevention strategies. On the other hand, FDS is a powerful tool for modeling the physics of fire behavior in buildings and other structures. It has been shown to produce accurate descriptions of fire behavior under a variety of different conditions. This study touches on very divergent, yet very critical, aspects of the applications of FDS. First, generating life-like simulations of fire and smoke characterized by different growth rates and surroundings (a non-immersive virtual reality application). Human behaviour experiments at Morgan State University will use the simulation videos to assess the accuracy of human estimates of fire growth rates and understand how situational factors impact human response. The second part of the study focuses on the Lagrangian particle representation of water droplets in FDS simulations of fire suppression. This study id is going to look at the fire suppression model in which fire suppression is defined by surface wetting or the mass of water falling in the fire surface. The Lagrangian liquid water droplets tracked by FDS represent a larger number of actual droplets. The number of ‘super drops’ can affect the accuracy of the simulations. The particle insertion rate has a default value and controls the mass of the 'super drop'. FDS allows altering the particle insertion rate and hence the mass of the 'super drop. The goal is to find out how changing particle injection rate and mesh grid size impacts the accuracy of the simulation of water sprays.Item Feasibility Analysis of Coupling FDS Modeling with Machine Learning for Situational Awareness in Aircraft Hangars(2022) Davis, Alison Marie; Milke, James A; Fire Protection Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Situational awareness is a critical factor in maintaining the safety of firefighters and can be largely improved in buildings using distributed sensors that provide real-time data. A two-phase approach is used to increase situational awareness in aircraft hangars. Phase I consists of modeling a hangar with an open door in Fire Dynamics Simulator (FDS), with a high density of smoke, temperature, CO and CO2 sensors located at the ceiling. Fuels of interest including Douglas fir, polyethylene, paper, JP-8, and propane are modeled in six potential fire locations, with five locations along the centerline of the hangar and one in the corner of the hangar. Additionally, wind and beams at the ceiling are added to the simulation to determine the impact on the products of combustion that the sensors pick up. Phase II uses the data acquired from the FDS simulations to inform and build machine learning models that utilize supervised learning techniques to identify the location of the fire, the magnitude of the fire and the composition of the fuel that is burning. It is determined that temperature and smoke are the key products of combustion needed for these analyses. The location of the fire is identified within a circular area with a 5 m radius by using temperature measurements, thus reducing the amount of input data needed for the machine learning models. The magnitude of the fire is predicted using temperature as inputs to a heat release rate (HRR) model using a fully connected, three-layer, feed forward neural network. The composition of the fuel is predicted using a linear support vector machine that supports multi-class classification, using products of temperature and smoke obscuration as inputs. The location model is 80% accurate, the HRR model is 85% accurate and the fuel composition model varies between 62% and 91% accuracy depending on the classification goals. These results prove the feasibility of machine learning applications in an aircraft hangar setting.Item IDENTIFYING SMOKE DETECTION BIASES WITHIN DIFFERING ROOM CONFIGURATIONS FOR ZONE AND COMPUTATIONAL FLUID DYNAMIC MODELS(2022) Lee, Adam; Milke, James A; Fire Protection Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This research project aims to identify room configuration conditions in which FDS, a CFD model, and CFAST, a zone model, may differ in detector activation time. A total of four configurations, with varying aspect ratios, were explored. Additionally, a range of four ceiling heights were also modeled. Furthermore, a total of three statistically significant models were developed to relate the differences between detection times within CFAST and FDS. It was found that FDS and CFAST discrepancies were a result of the compartment volume to doorway area ratios. Larger volumes compared to the doorway area resulted in better agreement between FDS and CFAST. Additionally, for larger ceilings in FDS, larger variability in activation times were present. Furthermore, for higher ceilings, FDSs’ ability to account for thermal buoyancy within the smoke plume resulted in quicker activation within FDS.Item Development of a laminar-turbulent transition model and blended time-marching schemes for rotorcraft CFD application(2021) Lee, Bumseok; Baeder, James; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This work focuses on improving rotorcraft Computational Fluid Dynamic (CFD) simulations through the incorporation of an appropriate Galilean invariant transition model suitable for rotating flows and a blended implicit time-marching scheme to reduce unphysical early tip-vortex breakdown. A correlation-based Galilean invariant transition model is coupled to the Spalart-Allmaras (S-A) turbulence model. The transition model is derived from Menter's 1-eq transition model and reformulated to incorporate with the S-A turbulence model. A constant freestream turbulence is applied for local correlations to account for wind tunnel test conditions in CFD simulations. Convergence of the model is improved for implicit time methods by applying the positivity in the implicit operators. The model is extended with two crossflow transition models, one proposed by Langtry et al. and the other one by Menter and Smirnov. The extended model has capability to predict the natural transition, bypass transition, separation-induced transition, and cross flow transition. Calibrations of the transition model are performed based on results of plate cases, and a new set of the model constants are proposed. The model is validated against various 2-D airfoils and 3-D cases. Accuracy and robustness of the transition model is demonstrated with comparisons with experimental data. For a 3-D hovering rotor case, the transition model shows similar trends with other CFD for integrated quantities, but without nonphysical behaviors in transition locations. The wake breakdown of a hovering rotor in CFD simulations is investigated with a focus on the effect of time marching. Several factors are tested such as 1) time step sizes, 2) temporal accuracy of time-marching schemes (BDF2 and BDF1), and 3) adding temporal damping to the BDF2 scheme. For this purpose, a blended formulation of the BDF2 and BDF1 schemes is derived with a temporal damping variable. Numerical studies are performed for NASA Langley's PSP hovering rotor, and results are compared such as wake structures, integrated rotor performance, and FFT analysis of the thrust coefficient. The results show that adding a small amount of temporal damping to the BDF2 scheme makes the integrated rotor performance settled down and reduces unphysical secondary vortex braid instability in wake structure. It is shown that the blended BDF scheme with a temporal damping can be used as an engineering solution of the wake structure breakdown in CFD rotor simulations without significant loss of temporal accuracy.Item Feasibility Analysis and FDS Modeling of Water Mist Fire Suppression Systems for Protection of Aircraft Hangars(2021) Steranka, Karolyn; Milke, James; Fire Protection Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Concern about PFAS containing foam fire suppression agents’ negative environmental impact motivated the U.S. Air Force to perform a two-phase feasibility analysis of water mist systems for protection of aircraft hangars. Phase I involved a feasibility analysis of COTS water mist technologies based on manufacturer specifications, literature, and previous test data. Phase I identified seven manufacturers who have developed systems with potential for successful protection of aircraft hangars. Phase II used FDS to model two low pressure and one high pressure system identified in Phase I. Phase II completed an analysis and validation simulations of the Lagrangian particle, extinction, and evaporation model in FDS. Following validation simulations each nozzle was tested in a full-scale hangar configuration for protection of a JP-8 spill fire. The results found the high-pressure mist system was able to extinguish the fire and earlier activation times lead to less damage to the aircraft and hangar compartment.Item Effect of Interactional Aerodynamics on Computational Aeroacoustics of Sikorsky's Notional X2 Platform(2020) Bahr, Ian; Baeder, James; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)An in-house acoustics code, ACUM, was used in conjunction with full vehicle CFD/CSD coupling to create a computational aeroacoustic framework to investigate the effect of aerodynamic interactions on the acoustic prediction of a compound coaxial helicopter. The full vehicle CFD/CSD was accomplished by using a high- fidelity computational fluid dynamics framework, HPCMP CREATETM-AV Helios, combined with an in-house computational structural dynamics solver to simulate the helicopter in steady forward flight. A notional X2TD helicopter consisting of a coaxial rotor, airframe, and pusher propeller was used and split into three simulation cases: isolated coaxial and propeller, airframe and full helicopter configuration to investigate each component’s effect on the others noise as well as the total noise. The primary impact on the acoustic prediction was the inclusion of the airframe in the CFD simulation as it affected both coaxial rotors as well as the propeller. It was found that the propeller and coaxial rotors had a negligible impact on each other.Item CFD/CSD STUDY OF INTERACTIONAL AERODYNAMICS OF A COAXIAL COMPOUND HELICOPTER IN HIGH-SPEED FORWARD FLIGHT(2020) Klimchenko, Vera; Baeder, James; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This work presents a computational study of the aerodynamic interactions that arise between the components of a high-speed lift-offset coaxial compound helicopter in forward flight. The objective of this study is to develop a computational methodology that would enable fundamental understanding of the complex aeromechanics of a modern lift-offset coaxial compound rotorcraft configuration in it's entirety. The modeling of a helicopter is a coupled aeroelastic problem, in which the aerodynamics is highly dependent on the structural dynamics, and vice versa. Therefore, the prediction of the rotorcraft airloads and blade deformations must be performed with sufficient fidelity to accurately model both aspects of the problem. A high-fidelity computational fluid dynamics framework, HPCMP CREATE$^{TM}$-AV Helios, was used in conjunction with an in-house comprehensive analysis solver, to simulate a lift-offset coaxial compound helicopter in forward flight. A notional X2TD helicopter consisting of a lift-offset coaxial rotor, airframe and an aft-mounted propeller, was modeled in this work. An in-house comprehensive analysis solver, PRASADUM, performed trim calculations and the structural modeling using low order aerodynamics. Conventionally, the comprehensive analysis rotor airloads that are computed from the built-in low order aerodynamic models, would be corrected with the high-fidelity CFD airloads using delta coupling procedure. In this study, the conventional rotor delta coupling methodology was used to study the interactional aerodynamics of a coaxial rotor system in forward flight at a range of flight speeds (50 knots to 225 knots). This study also focused on extending this methodology to perform high-fidelity airloads corrections for airframe and the propeller. The low order rotor, airframe and propeller aerodynamic loads were corrected with the high-fidelity CFD airloads, using a full vehicle loose delta coupling methodology. The two CFD/CSD coupling approaches, rotor and full vehicle, were compared. The results showed that correcting the low fidelity CSD airframe airloads with high-fidelity CFD airloads affects the rotor trim solution. The converged trim state from the full vehicle delta coupling procedure was utilized to study the fundamental interactional aerodynamics between various components of the coaxial compound helicopter. The CFD simulations were performed for isolated helicopter components and component combinations.Item ADVANCED MODELING AND REFRIGERANT FLOW PATH OPTIMIZATION FOR AIR-TO-REFRIGERANT HEAT EXCHANGERS WITH GENERALIZED GEOMETRIES(2019) Li, Zhenning; Radermacher, Reinhard K; Aute, Vikrant C; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Air-to-refrigerant heat exchangers are key components of the heating, ventilation, air-conditioning and refrigeration systems. The evolving simulation and manufacturing capabilities have given engineers new opportunities in pursuing complex and cost-efficient heat exchanger designs. Advanced heat exchanger modeling tools are desired to adapt to the industrial transition from conventional refrigerants to low Global Warming Potential (low-GWP) refrigerants. This research presents an advanced heat exchanger performance prediction model which distinguishes itself as a cutting-edge simulation tool in the literature to have capabilities, such as to (i) model heat exchangers with variable tube shape and topology, (ii) improved numerical stability, (iv) multiple dehumidification models to improve evaporator prediction, and (v) CFD-based predictions for airflow maldistribution. Meanwhile, HX performance is significantly influenced by the refrigerant flow path arrangements. The refrigerant flow path is optimized for various reasons such as to (i) mitigate the impact of airflow maldistribution, (ii) reduce material/cost, (iii) balance refrigerant state at the outlet of each circuit, and (iv) ensure overall stable performance under a variety of operating conditions. This problem is particularly challenging due to the large design space which increases faster than n factorial with the increase in the number of tubes. This research presents an integer permutation based Genetic Algorithm (GA) to optimize the refrigerant flow path of air-to-refrigerant heat exchangers. The algorithm has novel features such as to (i) integrate with hybrid initialization approaches to maintain the diversity and feasibility of initial individuals, (ii) use effective chromosome representations and GA operators to guarantee the chromosome (genotype) can be mapped to valid heat exchanger designs (phenotype), and (iii) incorporate real-world manufacturability constraints to ensure the optimal designs are manufacturable with the available tooling. Case studies have demonstrated that the optimal designs obtained from this algorithm can improve performance of heat exchangers under airflow maldistribution, reduce defrost energy and assure stable heat exchanger performance under cooling and heating modes in reversible heat pump applications. Comparison with other algorithms in literature shows that the proposed algorithm exhibits higher quality optimal solutions than other algorithms.