VTechWorks Repository :: Browsing by Author "Pitchumani, Ranga"

Browsing by Author "Pitchumani, Ranga"

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The Adhesion Strength of a Plasma Sprayed Silicon Bond Coating on a Silicon Carbide Ceramic Matrix Composite
Scherbarth, Austin Daniel (Virginia Tech, 2020-10-19)
Silicon-based ceramics and ceramic matrix composites (CMCs), such as silicon carbide (SiC) fiber reinforced SiC, are promising candidates for hot section components in next generation turbine engines. Environmental barrier coatings (EBCs) are essential for implementing these components as they insulate and protect the substrate from reaction with water vapor in the engine environment. EBCs are typically deposited via atmospheric plasma spraying (APS) and preparing the component surfaces through cleaning and roughening prior to coating is a vital step to ensure sufficient coating adhesion. The adhesion of a plasma sprayed coating to the underlying component is one of the most important properties as the component will not be protected if the coating is not well adhered. Surface roughening of metallic components via grit blasting is well documented and understood, but much less is known about preparing ceramic and ceramic composite surfaces for thermal spray coating. Silicon coatings are often used as a bond coating between SiC-based components and EBC top layers, but the adhesion strength of plasma sprayed Si on these substrates, Si splat formation and the factors that affect coating formation and adhesion have not been well studied. The effects of automated grit blasting process parameters on surface roughness and material loss of a reaction bonded SiC (rb SiC) composite were evaluated. Surface roughness before and after grit blasting was evaluated with a confocal laser scanning microscope. The differences and advantages of automated grit blasting compared to manual grit blasting were observed. Most notably was the level of control at high nozzle traverse speeds resulting in reduction of material loss and consistency of roughening. At high nozzle traverse speeds, the amount of material loss decreased greatly with a small effect on induced surface roughness. The degree of grit blasting induced roughness and material loss was found to be largely dependent on the nature of the composite matrix and reinforcement, as well as blast nozzle traverse speed. A statistical model was developed to predict the substrate thickness loss and induced average roughness based on nozzle traverse speed and blast pressure for automated grit blasting. Additionally, laser ablation was used to create controlled, regularly patterned surface texture on rb SiC substrates to further investigate the role of texture parameters in Si coating adhesion. Si was plasma sprayed onto rb SiC substrates to deposit both thick coatings to evaluate adhesion strength and single splats to study splat formation. Surface roughness/texture, substrate preheat temperature and mean Si particle size were varied in plasma spray coating experiments to observe their role in coating adhesion strength. Si adhesion strength was found to be related to all three factors and a statistical model was developed to predict adhesion strength based on them. Substrate preheat temperature had a significant effect on both Si adhesion strength and Si splat formation on rb SiC. Single splat formation during plasma spraying of Si on SiC was simulated with software called SimDrop. Simulations of Si droplet impact, spreading and solidification during plasma spraying on smooth and textured SiC surfaces were used to investigate the effects of relevant process parameters on splat formation. Experimentally observed Si splats on smooth substrates at different temperatures during deposition were matched with simulated splats with the same spraying parameters. A change in thermal contact resistance with changing substrate preheat temperature was confirmed by the simulation results. The role of surface texture parameters for a regularly patterned surface texture in splat formation was demonstrated through simulation. This dissertation investigates methods of roughening and preparing a SiC composite substrate for plasma spray coating, as well as factors which affect the adhesion strength and splat formation of plasma sprayed Si through experiments and simulation. The observations made provide valuable insight for understanding and optimizing the manufacturing processes utilized to deposit strongly adhered coatings onto SiC-based composites. In addition, areas of interest in this field for future study and further investigation are introduced and suggested.
Analysis and Optimization of a Novel Hexagonal Waveguide Concentrator for Solar Thermal Applications
Kant, Karunesh; Nithyanandam, Karthik; Pitchumani, Ranga (MDPI, 2021-04-12)
This paper analyzes a novel, cost-effective planar waveguide solar concentrator design that is inspired by cellular hexagonal structures in nature with the benefits of facile installation and low operation and maintenance cost. A coupled thermal and optical analysis of solar irradiation through an ideal hexagonal waveguide concentrator integrated with a linear receiver is presented, along with a cost analysis methodology, to establish the upper limit of performance. The techno-economic model, coupled with numerical optimization, is used to determine designs that maximized power density and minimized the cost of heat in the temperature range of 100–250 °C, which constitutes more than half of the industrial process heat demand. Depending on the incident solar irradiation and the application temperature, the cost of heat for the optimal design configuration ranged between 0.1–0.27 $/W and 0.075–0.18 $/W for waveguide made of ZK7 glass and polycarbonate, respectively. A techno-economic analysis showed the potential of the technology to achieve cost as low as 80 $/m² and 61 $/m² for waveguide made of ZK7 glass and polycarbonate material, respectively, which is less than half the cost of state-of-the-art parabolic trough concentrators. Overall, the hexagonal waveguide solar concentrator technology shows immense potential for decarbonizing the industrial process heat and thermal desalination sectors.
Analysis of Interfacial Processes on Non-Wetting Surfaces
Hatte, Sandeep Shankarrao (Virginia Tech, 2022-10-04)
Non-wetting surfaces mainly categorized into superhydrophobic (SHS), lubricant-infused (LIS) and solid-infused surfaces (SIS), by virtue of their superior water repellant properties have wide applications in several energy and environmental systems. In this dissertation, the role of non-wetting surfaces toward the enhancement of condensation effectiveness is analyzed by taking into consideration the tube side and shell side individual interfacial energy transport processes namely, drag reduction, convection heat transfer enhancement, fouling mitigation and dropwise condensation heat transfer. First, an analytical solution is developed for effective slip length and, in turn, drag reduction and friction factor on structured non-wetting surfaces. Secondly, by combining the solution for effective slip length on structured non-wetting surfaces and the fractal characterization of generic multiscale rough surfaces, a theoretical analysis of drag reduction, friction factor, and convection heat transfer enhancement is conducted for scalable non-wetting surfaces. Next, fractal representation of rough surfaces is used to theoretical derive the dropwise condensation heat transfer performance on SHS and novel SIS surfaces. The aspect of dynamic fouling mitigation properties of non-wetting surfaces is explored by conducting systematic experiments. Using Taguchi design of experiments, this work for the first time presents a closed formed relationship of fouling mitigation quantified in terms of asymptotic fouling resistance with Reynolds number, foulant concentration and viscosity of the infusion material that represents the different surface types in a unified manner. Furthermore, it was observed that LIS and SIS offer excellent fouling mitigation compared to SHS and conventional smooth surfaces, however only SIS owing to the presence of solid-like infusion materials is observed to be robust for practical applications.
Antimicrobial Properties of Graphite and Coal-Derived Graphene Oxides as an Advanced Coating for Titanium Implants
Jankus, Daniel James (Virginia Tech, 2021-04-27)
Prosthetic joint infection (PJI) poses a significant risk to implanted patients, requiring multiple surgeries with high rates of reinfection. The primary cause of such infections is otherwise innocuous bacterial species present on the skin that have survived sterilization protocols. Antibiotic drugs have significantly reduced efficacy due to the lack of vasculature in the newly implanted site, allowing microbes to form biofilms with even greater resistance. Graphene oxide (GO) is known to have good biocompatibility while providing drugless antimicrobial properties. The focus of this study is on the development and characterization of a robust coating for titanium alloy implants to promote bone regeneration while inhibiting microbial biofilm adhesion to the implant surface. The novelty of this study is the use of proprietary coal-derived graphene oxide (c-GO) in a biomedical application. c-GO has been demonstrated to have a greater number of functional oxygen groups to promote cell adhesion, while also maintaining thinner layers than possible with graphite exfoliation methods. As an alternative to powerful antimicrobial drugs, it was hypothesized that an advanced coating of graphene-oxide would provide a defensive, passively antimicrobial layer to a titanium implant. While GO is typically quite expensive, the newly developed process provides an economical and environmentally friendly method of producing GO from coal (c-GO). The result is a coating that is inexpensive and capable of halving the biofilm formation of MRSA on titanium-alloy surgical screws in addition to providing improved bone cell adhesion and hard tissue compatibility.
Benchmarking of the RAPID Eigenvalue Algorithm using the ICSBEP Handbook
Butler, James Michael (Virginia Tech, 2019-09-17)
The purpose of this thesis is to examine the accuracy of the RAPID (Real-Time Analysis for Particle Transport and In-situ Detection) eigenvalue algorithm based on a few problems from the ICSBEP (International Criticality Safety Benchmark Evaluation Project) Handbook. RAPID is developed based on the MRT (Multi-Stage Response-Function Transport) methodology and it uses the fission matrix (FM) method for performing eigenvalue calculations. RAPID has already been benchmarked based on several real-world problems including spent fuel pools and casks, and reactor cores. This thesis examines the accuracy of the RAPID eigenvalue algorithm for modeling the physics of problems with unique geometric configurations. Four problems were selected from the ICSBEP Handbook; these problems differ by their unique configurations which can effectively examine the capability of the RAPID code system. For each problem, a reference Serpent Monte Carlo calculation has been performed. Using the same Serpent model in the pRAPID (pre- and post-processing for RAPID) utility code, a series of fixed-source Serpent calculations are performed to determine spatially-dependent FM coefficients. RAPID calculations are performed using these FM coefficients to obtain the axially-dependent, pin-wise fission density distribution and system eigenvalue for each problem. It is demonstrated that the eigenvalues calculated by RAPID and Serpent agree with the experimental data within the given experimental uncertainty. Further, the detailed 3-D pin-wise fission density distribution obtained by RAPID agrees with the reference prediction by Serpent which itself has converged to less than 1% weighted uncertainty. While achieving accurate results, RAPID calculations are significantly faster than the reference Serpent calculations, with a calculation time speed-up of between 4x and 34x demonstrated in this thesis. In addition to examining the accuracy of the RAPID algorithm, this thesis provides useful information on the use of the FM method for simulation of nuclear systems.
Computational and Machine Learning-Reinforced Modeling and Design of Materials under Uncertainty
Hasan, Md Mahmudul (Virginia Tech, 2023-07-05)
The component-level performance of materials is fundamentally determined by the underlying microstructural features. Therefore, designing high-performance materials using multi-scale models plays a significant role to improve the predictability, reliability, proper functioning, and longevity of components for a wide range of applications in the fields of aerospace, electronics, energy, and structural engineering. This thesis aims to develop new methodologies to design microstructures under inherent material uncertainty by incorporating machine learning techniques. To achieve this objective, the study addresses gradient-based and machine learning-driven design optimization methods to enhance homogenized linear and non-linear properties of polycrystalline microstructures. However, variations arising from the thermo-mechanical processing of materials affect microstructural features and properties by propagating over multiple length scales. To quantify this inherent microstructural uncertainty, this study introduces a linear programming-based analytical method. When this analytical uncertainty quantification formulation is not applicable (e.g., uncertainty propagation on non-linear properties), a machine learning-based inverse design approach is presented to quantify the microstructural uncertainty. Example design problems are discussed for different polycrystalline systems (e.g., Titanium, Aluminium, and Galfenol). Though conventional machine learning performs well when used for designing microstructures or modeling material properties, its predictions may still fail to satisfy design constraints associated with the physics of the system. Therefore, the physics-informed neural network (PINN) is developed to incorporate problem physics in the machine learning formulation. In this study, a PINN model is built and integrated into materials design to study the deformation processes of Copper and a Titanium-Aluminum alloy.
D-Q Frame Impedance Based Small-signal Stability Analysis of PV Inverters in Distribution Grids
Tang, Ye (Virginia Tech, 2021-01-18)
With development of renewable energies worldwide, power system is seeing higher penetration of Utility-scale photovoltaic (PV) farms at distributed level as well as transmission level. Power electronics converters present negative incremental impedance characteristics at their input while under regulated output control, which brings in the possibility of system instability. Recent evidence suggests that large-scale penetration of PV inverters increases the probability of instability. While IEEE standard 1547 newest version requires PV inverters to have reactive power control, there have been few investigations into the small-signal stability impact of PV inverters on distribution systems especially with reactive power control. In addition, the existing studies either use the conventional way of state space equations and eigenvalues or use time-domain simulation methodology, which are based on the assumptions that detailed models of the grid and the PV inverters are accessible. Different from the previous literatures, this research employs Generalized Nyquist Criterion (GNC) method based on measured impedances in d-q frames at connection interfaces. GNC method has the advantage that interconnection stability can be judged without knowing the grid and PV generator model details. This work first demonstrates the advantage of volt-var droop mode control among all different local reactive power control modes for PV inverters in the aspects of static impact on grid voltage profiles and power loss in a 12kV test-bed distribution system. Then it is discovered that d-q frame impedance of PV inverter under volt-var droop mode control shows a significant difference from other reactive power control modes. The d-q frame impedance derived from the small-signal model of PV generator is validated by both MATLAB simulation results and hardware experiments. Based on the d-q frame impedances, GNC is utilized to analyze the stability connection of a single PV farm and multiple PVs into the grid. GNC stability assessment results match with time-domain simulations and reveal the stability problem related to volt-var droop mode control. Furthermore, considering the unbalance of the distribution system, a new impedance model in d-q frame is proposed to capture both the dynamics of PV inverter operating in unbalanced points and the dynamics of three-phase unbalanced grid. The new impedance model is a combination of positive-negative sequence impedance and conventional d-q frame impedance. A procedure is designed for the measurement of the extended d-q frame impedance and the GNC application to predict small-signal stability of the unbalanced grid, which are justified by both time domain simulation and hardware experiments.
Detailed Heat Transfer Measurements of Various Rib Turbulator Shapes at Very High Reynolds Numbers Using Steady-state Liquid Crystal Thermography
Zhang, Mingyang (Virginia Tech, 2018-01-18)
In order to protect gas turbine blades from hot gases exiting the combustor, several intricate external and internal cooling concepts are employed. High pressure stage gas turbine blades feature serpentine passages where rib turbulators are installed to enhance heat transfer between the relatively colder air bled off from the compressor and the hot internal walls. Most of the prior studies have been restricted to Reynolds number of 90000 and several studies have been carried out to determine geometrically optimized parameters for achieving high levels of heat transfer in this range of Reynolds number. However, for land-based power generation gas turbines, the Reynolds numbers are significantly high and vary between 105 and 106. Present study is targeted towards these high Reynolds numbers where traditional rib turbulator shapes and prescribed optimum geometrical parameters have been investigated experimentally. A steady-state liquid crystal thermography technique is employed for measurement of detailed heat transfer coefficient. Five different rib configurations, viz., 45 deg., V-shaped, inverse V-shaped, W-shaped and M-shaped have been investigated for Reynolds numbers ranging from 150,000 to 400,000. The ribs were installed on two opposite walls of a straight duct with aspect ratio of unity. For very high Reynolds numbers, the heat transfer enhancement levels for different rib shapes varied between 1.3 and 1.7 and the thermal hydraulic performance was found to be less than unity.
Experimental Investigations on Non-Wetting Surfaces
Stoddard, Ryan Manse (Virginia Tech, 2021-05-24)
Superhydrophobic (SHS) and lubricant-infused surfaces (LIS) exhibit exceptional non-wetting characteristics that make them attractive for energy production applications including steam condensation and fouling mitigation. The dissertation work focuses on application of non-wetting surfaces to energy production using a systematic approach examining each component of surface fabrication in three functional areas. First, SHS and LIS are fabricated using robust, scalable methods and tested for durability in heated, wet conditions and under high-energy water jet impingement. Clear performance differences are shown based on surface texturing, functionalizing agent, and infused lubricant. Second, SHS and LIS are applied to tube exteriors and evaluated for their ability to produce sustained dropwise condensation in a typical power plant condenser environment. The surfaces are shown to produce heat transfer coefficients up to 7-10 times that of film-wise condensation, with condenser effectiveness of 0.92 or better compared to effectiveness of about 0.6 in conventional condensers. Third, LIS on the interior of tubes are assessed in accelerated mineral fouling conditions. LIS are shown to mitigate calcium sulfate and calcium carbonate fouling under laminar conditions. The results of the study bear profound benefits to reducing the levelized cost of condensers and water uptake in thermoelectric power plants, that currently consume about 50% of the total water use in the U.S.
Investigations on Air-cooled Air Gap Membrane Distillation and Radial Waveguides for Desalination
Narayan, Aditya (Virginia Tech, 2017-08-30)
This thesis presents investigations on air-cooled air gap membrane distillation for desalination and the application of radial waveguides based on total internal reflection for solar thermal desalination. Using an air-cooled design for an air gap membrane distillation (AGMD) process may result in significantly lower energy requirements for desalination. Experiments were conducted on AGMD module to study the effect of air gap, support mesh conductivity and hydrophobicity, condensing surface hydrophobicity. A novel modular design was used in which modules could be used in a series configuration to increase the flux value for the distillate. The output from the series configuration was found to have about three times the production from a single pass water-cooled system with the same temperature difference between the saline and clear water streams. The results also indicated that the mesh conductivity had a favorable effect on the flux value whereas the hydrophobicity of the mesh had no significant effect. The hydrophobicity of the condensing surface was favorable on two accounts: first, it led to an increase in the flux of the distillate at temperatures below 60 °C and second, the temperature difference of the saline feed when it enters and leaves the module is lower which can lead to energy savings and higher yields when used in a series configuration. The second part of the thesis considers use of low-cost radial waveguides to collect and concentrate solar energy for use in thermal desalination processes. The optical-waveguide-based solar energy concentrators are based on total internal reflection and minimize/eliminate moving parts, tracking structures and cost. The use of optical waveguides for thermal desalination is explored using an analytical closed-form solution for the coupled optical and thermal transport of solar irradiation through a radial planar waveguide concentrator integrated with a central receiver. The analytical model is verified against and supported by computational optical ray tracing simulations. The effects of various design and operating parameters are systematically investigated on the system performance, which is quantified in terms of net thermal power delivered, aperture area required and collection efficiency. Design constraints like thermal stress, maximum continuous operation temperature and structural constraints have been considered to identify realistic waveguide configurations which are suitable for real world applications. The study provides realistic estimates for the performance achievable with radial planar waveguide concentrator-receiver configuration. In addition to this, a cost analysis has been conducted to determine the preferred design configurations that minimize the cost per unit area of the planar waveguide concentrator coupled to the receiver. Considering applications to thermal desalination which is a low temperature application, optimal design configuration of waveguide concentrator-receiver system is identified that result in the minimum levelized cost of power (LCOP).
Investigations on Latent Thermal Energy Storage for Concentrating Solar Power
Nithyanandam, Karthik (Virginia Tech, 2013-06-10)
Thermal energy storage (TES) in a concentrating solar power (CSP) plant allows for continuous operation even during times when solar radiation is not available, thus providing a reliable output to the grid. Energy can be stored either as sensible heat or latent heat, of which latent heat storage is advantageous due to its high volumetric energy density and the high Rankine cycle efficiency owing to the isothermal operation of latent thermal energy storage (LTES) system. Storing heat in the form of latent heat of fusion of a phase change material (PCM), in addition to sensible heat, significantly increases the energy density, thus potentially reducing the storage size and cost. However, a major technical barrier to the use of latent thermal energy of PCM is the high thermal resistance to energy transfer due to the intrinsically low thermal conductivity of PCMs, which is a particularly acute constraint during the energy discharge. Secondly, for integration of TES in CSP plants, it is imperative that the cyclic exergetic efficiency be high, among other requirements, to ensure that the energy extracted from the system is at the maximum possible temperature to achieve higher cycle conversion efficiency in the power block. The first objective is addressed through computational modeling and simulation to quantify the effectiveness of two different approaches to reduce the thermal resistance of PCM in a LTES, viz. (a) developing innovative, inexpensive and passive heat transfer devices that efficiently transfer large amount of energy between the PCM and heat transfer fluid (HTF) and (b) increase the heat transfer area of interaction between the HTF and PCM by incorporating the PCM mixture in small capsules using suitable encapsulation techniques. The second portion of the research focuses on numerical modeling of large scale latent thermal storage systems integrated to a CSP plant with the aforementioned enhancement techniques and cascaded with more than one PCM to maximize the exergetic efficiency. Based on systematic parametric analysis on the various performance metrics of the two types of LTES, feasible operating regimes and design parameters are identified to meet the U.S. Department of Energy SunShot Initiative requirements including storage cost < $15/kWht and exergetic efficiency > 95%, for a minimum storage capacity of 14 h, in order to reduce subsidy-free levelized cost of electricity (LCE) of CSP plants from 21¢/kWh (2010 baseline) to 6¢/kWh, to be on par with the LCE associated with fossil fuel plants.
Investigations on Multiscale Fractal-textured Superhydrophobic and Solar Selective Coatings
Jain, Rahul (Virginia Tech, 2017-08-21)
Functional coatings produced using scalable and cost-effective processes such as electrodeposition and etching lead to the creation of random roughness at multiple length scales on the surface. The first part of thesis work aims at developing a fundamental mathematical understanding of multiscale coatings by presenting a fractal model to describe wettability on such surfaces. These surfaces are described with a fractal asperity model based on the Weierstrass-Mandelbrot function. Using this description, a model is presented to evaluate the apparent contact angle in different wetting regimes. Experimental validation of the model predictions is presented on various hydrophobic and superhydrophobic surfaces generated on several materials under different processing conditions. Superhydrophobic surfaces have myriad industrial applications, yet their practical utilization has been severely limited by their poor mechanical durability and longevity. Toward addressing this gap, the second and third parts of this thesis work present low cost, facile processes to fabricate superhydrophobic copper and zinc-based coatings via electrodeposition. Additionally, systematic studies are presented on coatings fabricated under different processing conditions to demonstrate excellent durability, mechanical and underwater stability, and corrosion resistance. The presented processes can be scaled to larger, durable coatings with controllable wettability for diverse applications. Apart from their use as superhydrophobic surfaces, the application of multiscale coatings in photo-thermal conversion systems as solar selective coatings is explored in the final part of this thesis. The effects of scale-independent fractal parameters of the coating surfaces and heat treatment are systematically explored with respect to their optical properties of absorptance, emittance, and figure of merit (FOM).
Investigations on Solar Powered Direct Contact Membrane Distillation
Deshpande, Jaydeep Sanjeev (Virginia Tech, 2016-06-20)
Desalination is one of the proposed methods to meet the ever increasing water demands. It can be subdivided into two broad categories, thermal based desalination and electricity based desalination. Multi-effect Distillation (MED), Multi-Stage Flashing (MSF), Membrane Distillation (MD) fall under former and Reverse Osmosis (RO), Electro-Dialysis (ED) fall under later. MD offers an attractive solution for seawater as well as brackish water distillation. It shows highly pure yields, theoretically 100% pure. The overall construction of a MD unit is way simpler than any other desalination systems. MD is a thermally driven diffusion process where desalination takes places in the form of water vapor transport across the membrane. It has low second law efficiency due to parasitic heat losses. The objective of the first part of the investigation is to thoroughly analyze a Direct Contact Membrane Distillation (DCMD) system from the view point of yield and exergy. The insights from exergy analysis are used in a design study, which is used for performance optimization. The first part concludes with a design procedure and design windows for large scale DCMD construction. In the second part of the investigation, focus is moved to waveguide solar energy collector. The idea behind an ideal waveguide is to reduce the complexity of modeling solar energy collection. The mathematical model provided in this analysis can be extended to a family of non-imaging optics in solar energy and serves as a benchmarking analysis tool. A waveguide is suitable for low temperature operations due to limitations on maximum continuous temperature of operation. Thus, it becomes an ideal solution for DCMD applications. A levelized cost analysis is presented for a waveguide powered DCMD plant of a 30,000 capacity. A combination of waveguide and DCMD shows levelized cost of water at $1.80/m³, which is found to be lower than previously reported solar desalination water costs.
Investigations on Void Formation in Composite Molding Processes and Structural Damping in Fiber-Reinforced Composites with Nanoscale Reinforcements
DeValve, Caleb Joshua (Virginia Tech, 2013-03-18)
Fiber-reinforced composites (FRCs) offer a stronger and lighter weight alternative to traditional materials used in engineering components such as wind turbine blades and rotorcraft structures. Composites for these applications are often fabricated using liquid molding techniques, such as injection molding or resin transfer molding. One significant issue during these processing methods is void formation due to incomplete wet-out of the resin within the fiber preform, resulting in discontinuous material properties and localized failure zones in the material. A fundamental understanding of the resin evolution during processing is essential to designing processing conditions for void-free filling, which is the first objective of the dissertation. Secondly, FRCs used in rotorcraft experience severe vibrational loads during service, and improved damping characteristics of the composite structure are desirable. To this end, a second goal is to explore the use of matrix-embedded nanoscale reinforcements to augment the inherent damping capabilities in FRCs. The first objective is addressed through a computational modeling and simulation of the infiltrating dual-scale resin flow through the micro-architectures of woven fibrous preforms, accounting for the capillary effects within the fiber bundles. An analytical model is developed for the longitudinal permeability of flow through fibrous bundles and applied to simulations which provide detailed predictions of local air entrapment locations as the resin permeates the preform. Generalized design plots are presented for predicting the void content and processing time in terms of the Capillary and Reynolds Numbers governing the molding process. The second portion of the research investigates the damping enhancement provided to FRC's in static and rotational configurations by different types and weight fractions of matrix-embedded carbon nanotubes (CNTs) in high fiber volume fraction composites. The damping is measured using dynamic mechanical analysis (DMA) and modal analysis techniques, and the results show that the addition of CNTs can increase the material damping by up to 130%. Numerical simulations are conducted to explore the CNT vibration damping effects in rotating composite structures, and demonstrate that the vibration settling times and the maximum displacement amplitudes of the different structures may be reduced by up to 72% and 50%, respectively, with the addition of CNTs.
Machine Learning based Methods to Improve Power System Operation under High Renewable Pennetration
Bhavsar, Sujal Pradipkumar (Virginia Tech, 2022-09-19)
In an attempt to thwart global warming in a concerted way, more than 130 countries have committed to becoming carbon neutral around 2050. In the United States, the Biden ad- ministration has called for 100% clean energy by 2035. It is estimated that in order to meet that target, the energy production from solar and wind should increase to 50-70% from the current 11% share. Under higher penetration of solar and wind, the intermittency of the energy source poses critical problems in forecasting, uncertainty quantification, reserve man- agement, unit commitment, and economic dispatch, and presents unique challenges to the distribution system, including predicting solar adoption by the user as well as forecasting end-use load profiles. While these problems are complex, advances in machine learning and artificial intelligence provide opportunities for novel paradigms for addressing the challenges. The overall aim of the dissertation is to harness data-driven and model-based techniques and develop computationally efficient tools for improved power systems operation under high re- newables penetration in the next-generation electric grid. Some of the salient contributions of this work are the reduction in the number of uncertain scenarios by 99%; dramatic reduc- tion in the computational overhead to simulate stochastic unit commitment and economic dispatch on a single-node electric-grid system to merely 10 seconds from 24 hours; reduc- tion in the total monthly operating cost of two-stage stochastic economic dispatch by an average of 5%, and reduction in average overall reserve due to intermittency in renewables by 50%; and improvement in the existing end-use load prediction and rooftop PV adopter identification tools by a considerable margin.
Multiscale Modeling and Uncertainty Quantification of Multiphase Flow and Mass Transfer Processes
Donato, Adam Armido (Virginia Tech, 2015-01-10)
Most engineering systems have some degree of uncertainty in their input and operating parameters. The interaction of these parameters leads to the uncertain nature of the system performance and outputs. In order to quantify this uncertainty in a computational model, it is necessary to include the full range of uncertainty in the model. Currently, there are two major technical barriers to achieving this: (1) in many situations -particularly those involving multiscale phenomena-the stochastic nature of input parameters is not well defined, and is usually approximated by limited experimental data or heuristics; (2) incorporating the full range of uncertainty across all uncertain input and operating parameters via conventional techniques often results in an inordinate number of computational scenarios to be performed, thereby limiting uncertainty analysis to simple or approximate computational models. This first objective is addressed through combining molecular and macroscale modeling where the molecular modeling is used to quantify the stochastic distribution of parameters that are typically approximated. Specifically, an adsorption separation process is used to demonstrate this computational technique. In this demonstration, stochastic molecular modeling results are validated against a diverse range of experimental data sets. The stochastic molecular-level results are then shown to have a significant role on the macro-scale performance of adsorption systems. The second portion of this research is focused on reducing the computational burden of performing an uncertainty analysis on practical engineering systems. The state of the art for uncertainty analysis relies on the construction of a meta-model (also known as a surrogate model or reduced order model) which can then be sampled stochastically at a relatively minimal computational burden. Unfortunately these meta-models can be very computationally expensive to construct, and the complexity of construction can scale exponentially with the number of relevant uncertain input parameters. In an effort to dramatically reduce this effort, a novel methodology "QUICKER (Quantifying Uncertainty In Computational Knowledge Engineering Rapidly)" has been developed. Instead of building a meta-model, QUICKER focuses exclusively on the output distributions, which are always one-dimensional. By focusing on one-dimensional distributions instead of the multiple dimensions analyzed via meta-models, QUICKER is able to handle systems with far more uncertain inputs.
Numerical and Experimental Design of High Performance Heat Exchanger System for A Thermoelectric Power Generator for Implementation in Automobile Exhaust Gas Waste Heat Recovery
Pandit, Jaideep (Virginia Tech, 2014-05-07)
The effects of greenhouse gases have seen a significant rise in recent years due to the use of fossil fuels like gasoline and diesel. Conversion of the energy stored in these fossil fuels to mechanical work is an extremely inefficient process which results in a high amount of energy rejected in the form of waste heat. Thermoelectric materials are able to harness this waste heat energy and convert it to electrical power. Thermoelectric devices work on the principle of the Seebeck effect, which states that if two junctions of dissimilar materials are at different temperatures, an electrical potential is developed across them. Even though these devices have small efficiencies, they are still an extremely effective way of converting low grade waste heat to usable electrical power. These devices have the added advantage of having no moving parts (solid state) which contributes to a long life of the device without needing much maintenance. The performance of thermoelectric generators is dependent on a non-dimensional figure of merit, ZT. Extensive research, both past and ongoing, is focused on improving the thermoelectric generator's (TEG's) performance by improving this figure of merit, ZT, by way of controlling the material properties. This research is usually incremental and the high performance materials developed can be cost prohibitive. The focus of this study has been to improve the performance of thermoelectric generator by way of improving the heat transfer from the exhaust gases to the TEG and also the heat transfer from TEG to the coolant. Apart from the figure of merit ZT, the performance of the TEG is also a function of the temperature difference across it, By improving the heat transfer between the TEG and the working fluid, a higher temperature gradient can be achieved across it, resulting in higher heat flux and improved efficiency from the system. This area has been largely neglected as a source of improvement in past research and has immense potential to be a low cost performance enhancer in such systems. Improvements made through this avenue, also have the advantage of being applicable regardless of the material in the system. Thus these high performance heat exchangers can be coupled with high performance materials to supplement the gains made by improved figure of merits. The heat exchanger designs developed and studied in this work have taken into account several considerations, like pressure drop, varying engine speeds, location of the system along the fuel path, system stability etc. A comprehensive treatment is presented here which includes 3D conjugate heat transfer modeling with RANS based turbulence models on such a system. Various heat transfer enhancement features are implemented in the system and studied numerically as well as experimentally. The entire system is also studied experimentally in a scaled down setup which provided data for validation of numerical studies. With the help of measured and calculated data like temperature, ZT etc, predictions are also presented about key metrics of system performance.
Numerical Modeling and Prediction of Bubbling Fluidized Beds
England, Jonas Andrew (Virginia Tech, 2011-04-27)
Numerical modeling and prediction techniques are used to determine pressure drop, minimum fluidization velocity and segregation for bubbling fluidized beds. The computational fluid dynamics (CFD) code Multiphase Flow with Interphase eXchange (MFIX) is used to study a two-stage reactor geometry with a binary mixture. MFIX is demonstrated to accurately predict pressure drop versus inlet gas velocity for binary mixtures. A new method is developed to predict the pressure drop versus inlet gas velocity and minimum fluidization velocity for multi-component fluidized beds. The mass accounting in the stationary system (MASS) method accounts for the changing bed composition during the fluidization process by using a novel definition for the mass fractions of the bed not yet fluidized. Published experimental data for pressure drop from single-, binary- and ternary-component fluidized bed systems are compared to MFIX simulations and the MASS method, with good agreement between all three approaches. Minimum fluidization velocities predicted using correlations in the literature were compared with the experimental data, MFIX, and the MASS method. The predicted minimum fluidization velocity from the MASS method provided very good results with an average relative error of ±4%. The MASS method is shown to accurately predict when complex multi-component systems of granular material will fluidize. The MASS method and MFIX are also used to explore the occurrence and extent of segregation in multi-component systems. The MASS method and MFIX are both shown to accurately predict the occurrence and extent of segregation in multi-component systems.
On-line Nonlinear Characterization of Anisotropic Materials
Pan, Jan Wei (Virginia Tech, 2010-12-20)
This dissertation proposes a new framework to characterize the nonlinear behavior of anisotropic materials in an on-line manner. The proposed framework applies recursive estimation and a multi-linear model to characterize the nonlinear behavior of anisotropic materials on-line using full-field strains, which are capable of capturing the multi-axial information of anisotropic materials. A stochastic method is developed to characterize the linear behavior of anisotropic materials under the influence of full-field strain measurement noise. This method first derives stochastic equations based on the formulas of energy-based characterization that utilizes the principle of ener-gy conservation, and then recursively estimates elastic constants at every acquisition of measure-ment using a Kalman filter (KF). Since the measurement model is expressed nonlinearly, the KF utilizes a Kalman gain, which is newly derived in this dissertation through variance minimization, to achieve optimal characterization. The aforementioned method, namely stochastic linear characteri-zation in this dissertation, becomes a basis of the multi-linear characterization method. This method utilizes a multi-linear model, which is defined by partitions, to characterize the nonlinear constitu-tive relations. The multi-linear characterization scales up the number of estimates and identifies the coefficients of each linear partition using the previously derived KF. The recursive updates in measurements not only removes uncertainty through sensor measurements, but also enables the on-line capability of the nonlinear characterization of anisotropic materials. A series of numerical and experimental studies were performed to demonstrate the performance of the proposed framework in characterizing the nonlinear behavior of anisotropic materials. The validity and applicability of the proposed framework were confirmed by the comparison with the known values of the characterized constitutive relations. It was found that the proposed framework identified elastic constants that were in good agreement with known values irrespective of the spec-imen geometry. The results of the multi-linear characterization method were well correlated with known nonlinear stress-strain relations and concluded that the proposed framework is capable of characterizing adequate nonlinear behavior on-line.
Studies on Corrosion, Fouling and Durability of Advanced Functional Nonwetting Surfaces
Mousavi, Seyed Mohammad Ali (Virginia Tech, 2021-11-30)
Superhydrophobic and lubricant-infused porous surfaces are two classes of non-wetting surfaces that are inspired by the adaptation of natural surfaces such as lotus leaves, pond skater legs, butterfly wings, and Nepenthes pitcher plant. This dissertation focuses on fabrication and in depth study of bioinspired functional metallic surfaces for applications such as power plant condensers and marine applications. Toward that, first, facile and scalable methods are developed for the fabrication of superhydrophobic surfaces (SHS) and lubricant-infused surfaces (LIS). Second, the corrosion inhibition mechanism of SHS was systematically studied and modeled via electrochemical methods to elucidate the role of superhydrophobicity and other parameters on corrosion inhibition. The anti-corrosion properties of SHS and LIS were systematically studied over a range of temperatures (23°C–90°C) to simulate an actual condenser environment. Moreover, the environment of application often involves using harsh cleaning chemicals. The fabricated non-wetting surfaces were examined over a wide range of acidity and basicity (pH=1 to pH=14). Third, the durability of SHS and LIS is systematically assessed using a set of testing protocols including water impingement tests, scratch wear tests, and accelerated chemical corrosion tests. Considering that industrial environments of application are often turbulent, in addition to static long term corrosion tests, long term dynamic durability was studied in a simulated turbulent condition. Fourth, the performance of the fabricated nonwetting surfaces was systematically studied against calcium sulfate scaling in turbulent conditions and different temperatures. An analytical relationship based on the Hill-Langmuir model is proposed for the prediction of fouling on nonwetting and conventional surfaces alike in dynamic conditions. Overall 1048 individual samples were studied via over 3000 measurements in this dissertation to establish a comprehensive fundamental knowledge base on fabrication and anti fouling characteristics of metallic nonwetting surfaces, which profoundly helps to design appropriate surfaces and fabrication methods based on the use environment.

Browsing by Author "Pitchumani, Ranga"

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