Mountain Scholar :: Browsing by Author "Gao, Xinfeng, committee member"

Browsing by Author "Gao, Xinfeng, committee member"

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Open Access
A computational and experimental study on combustion processes in natural gas/diesel dual fuel engines
(Colorado State University. Libraries, 2015) Hockett, Andrew, author; Marchese, Anthony J., advisor; Hampson, Greg, committee member; Olsen, Daniel B., committee member; Gao, Xinfeng, committee member; Young, Peter, committee member
Natural gas/diesel dual fuel engines offer a path towards meeting current and future emissions standards with lower fuel cost. However, numerous technical challenges remain that require a greater understanding of the in-cylinder combustion physics. For example, due to the high compression ratio of diesel engines, substitution of natural gas for diesel fuel at high load is often limited by engine knock and pre-ignition. Additionally, increasing the natural gas percentage in a dual fuel engine often results in decreasing maximum load. These problems limit the substitution percentage of natural gas in high compression ratio diesel engines and therefore reduce the fuel cost savings. Furthermore, when operating at part load dual fuel engines can suffer from excessive emissions of unburned natural gas. Computational fluid dynamics (CFD) is a multi-dimensional modeling tool that can provide new information about the in-cylinder combustion processes causing these issues. In this work a multi-dimensional CFD model has been developed for dual fuel natural gas/diesel combustion and validated across a wide range of engine loads, natural gas substitution percentages, and natural gas compositions. The model utilizes reduced chemical kinetics and a RANS based turbulence model. A new reduced chemical kinetic mechanism consisting of 141 species and 709 reactions was generated from multiple detailed mechanisms, and has been validated against ignition delay, laminar flame speed, diesel spray experiments, and dual fuel engine experiments using two different natural gas compositions. Engine experiments were conducted using a GM 1.9 liter turbocharged 4-cylinder common rail diesel engine, which was modified to accommodate port injection of natural gas and propane. A combination of experiments and simulations were used to explore the performance limitations of the light duty dual fuel engine including natural gas substitution percentage limits due to fast combustion or engine knock, pre-ignition, emissions, and maximum load. In particular, comparisons between detailed computations and experimental engine data resulted in an explanation of combustion phenomena leading to engine knock in dual fuel engines. In addition to conventional dual fuel operation, a low temperature combustion strategy known as reactivity controlled compression ignition (RCCI) was explored using experiments and computations. RCCI uses early diesel injection to create a reactivity gradient leading to staged auto-ignition from the highest reactivity region to the lowest. Natural gas/diesel RCCI has proven to yield high efficiency and low emissions at moderate load, but has not been realized at the high loads possible in conventional diesel engines. Previous attempts to model natural gas/diesel RCCI using a RANS based turbulence model and a single component diesel fuel surrogate have shown much larger combustion rates than seen in experimental heat release rate profiles, because the reactivity gradient of real diesel fuel is not well captured. To obtain better agreement with experiments, a reduced dual fuel mechanism was constructed using a two component diesel surrogate. A sensitivity study was then performed on various model parameters resulting in improved agreement with experimental pressure and heat release rate.
Open Access
A numerical model for the determination of biomass ignition from a hotspot
(Colorado State University. Libraries, 2015) McArdle, Patrick, author; Williams, John, advisor; Gao, Xinfeng, committee member; Shipman, Patrick, committee member
The determination of biomass ignition from an inert spherical hotspot using a fourth-order finite-volume method is presented. The transient ignition-combustion system is modeled by two coupled reaction-diffusion equations. One equation governs the heating characteristics of the biomass while the other governs the mass loss of the biomass. The combustion assumes a one-step, 1st-order Arrhenius reaction. This work is motivated and funded by the Department of Defense Legacy Program to create a munition specific fire danger rating system. Improving fire danger rating systems on military lands would minimize the economic and environmental impact of soldiers training on protected habitats. A better understanding of these ignition characteristics would also improve current fire spread models. Our result shows that given the ignition criteria derived from a simplified non-dimensional model and specifying critical values found by Gol'dshleger et al., an ignition probability can be established by varying the biomass properties based on moisture content. Following the procedure developed in this thesis, the computed ignition probabilities correlate well with experimental ignition data that was obtained at the Center for Environmental Management of Military Lands. Moreover, numerically solving the coupled reaction-diffusion system provides additional insight into more realistic ignition criteria involving mass loss. The numerical solution suggests more sources of heat loss, in addition to convection, must be considered for a more realistic ignition model.
Open Access
Alternative heart assistance pump
(Colorado State University. Libraries, 2021) Sharifi, Alireza, author; Bark, David, advisor; James, Susan, advisor; Scansen, Brian, committee member; Popat, Ketul, committee member; Gao, Xinfeng, committee member
On average, the human heart beats around 115,000, and pumps around 2,000 gallons of blood daily. This essential organ may undergo systolic or diastolic dysfunction in which the heart cannot properly contract or relax, respectively. To help hearts pump effectively should these types of failures occur, ventricular assist devices (VAD) are implemented as a temporary or permanent solution. The most common VAD is the left ventricular assist device (LVAD) which supports the left ventricle in pumping the oxygen-rich blood from the heart to the aorta, and ultimately to the rest of the body. Although current VADs are an important treatment for advanced heart failure, generally VADS come with many complications and issues after implantation. These complications include incidents of hemolysis (tearing of the blood cells), thrombosis (clotting of the blood), bleeding (especially in the gastrointestinal tract), and infection at the driveline site. Specifically, the current continuous flow pumps are associated with a much higher incidence of gastrointestinal bleeding, myocardial perfusion, kidney problems, among others, compared with the earlier generation pulsatile pumps. However, the presence of several moving mechanical components made the pulsatile pumps less durable, bulky, and prone to malfunction, ultimately leading to favor toward continuous flow designs. The goal of the present study is to develop a novel heart assist pump, overcoming drawbacks to current commercially available pumps, by improving hemodynamic (blood flow) performance, pulsatility, and eliminating bleeding disorders. Our design will overcome the current pumps which suffer from non-physiological flow, and blood damage. The impact of this work goes beyond heart assist devices and would be applicable to other blood pumps. The fundamental biological and physical principles of designing a blood pump will be reviewed in chapter one. In addition, recent studies on current LVADs and the motivation behind these studies will also be discussed. Then, the idea of using a contractive tubular heart as an alternative pump will be presented in chapter two. To understand the pumping mechanism of the tubular heart, a detailed study on the embryonic heart is presented in this chapter. Subsequently, the effect of flow forces on blood cells will be studied in chapter 3. Moreover, the relation between flow regime and bleeding disorders have been studied in the same chapter. A discussion of our design, including the pump design, testing set up, experimental results will be presented in chapter 4. Finally, the limitations of the present study and future work will be presented in chapter 5.
Open Access
Biomechanical analysis of aortic valve calcification and post-procedural paravalvular leak
(Colorado State University. Libraries, 2016) Zebhi, Banafsheh, author; Dasi, Lakshmi Prasad, advisor; Orton, Christopher, committee member; Gao, Xinfeng, committee member
Cardiovascular disease is a leading cause of death accounted for 17.3 million people annually. Aortic valve calcification (AVC) and stenosis are the most common diseases among valvular heart diseases. Severe AVC and stenosis will need the standard surgical aortic valve replacement (SAVR) or transcatheter aortic valve replacement (TAVR) for patients who are at high risk for open heart surgery. Post-procedural paravalvular leak (PVL) is a common complication which occurs around the implanted stent in a significant population of patients who undergo valve replacement, requiring significant interventions. The overarching hypothesis of this research is that anatomic characteristics of patients’ native aortic valve play an important role in both calcification processes and post-procedural PVL occurrence. This hypothesis is studied through two specific Aims. Aim 1 was designed to determine what anatomic and biological parameters as well as hemodynamic factors are associated with severity of aortic valve calcification. In this aim, patient-specific geometric characteristics were extracted using 3D image reconstruction of patient CT data, and their relation with cusp specific calcification was evaluated using multiple regression analysis. The results of this analysis indicated that severity of calcification is significantly correlated with coronary calcification as well as the size of sinus of valsava and sinotubular junction (all p-values<0.05). In Aim 2, we investigated the relationship among patients’ calcification level and anatomic parameters of their native aortic valve as well as the risk of post-procedural PVL occurrence. Using a logistic regression analysis model we show that large calcification deposition (p-value<0.001) and large ratio of sinus of valsava to annulus (p-value<0.02) of native aortic valve can predict probability of post-procedural PVL occurrence. The overall significance of this study is that bioengineering analysis of pre-procedural CT data can be utilized towards better TAVR planning as well as basic understanding of the pathogenesis of AVC.
Open Access
Biomechanical analysis of hypoplastic left heart syndrome and calcific aortic stenosis: a statistical and computational study
(Colorado State University. Libraries, 2021) Zebhi, Banafsheh, author; Bark, David, advisor; Gao, Xinfeng, committee member; Wang, Zhijie, committee member; Scansen, Brian, committee member
Cardiovascular diseases are a leading cause of death in the United States. In this dissertation, a congenital heart disease (CHD) and a valvular disease are discussed. CHDs occur in ~5% of live births. Structural CHDs can be complex and difficult to treat, such as hypoplastic left heart syndrome (HLHS) in which the left ventricle is generally underdeveloped, representing ~9% of all congenital heart diseases. Calcific aortic stenosis is one of the most common valvular diseases in which valves thicken and stiffen, and in some cases nodular deposits form, limiting valve function that may result in flow regurgitation and outflow obstruction. The overarching hypothesis of this research is that patient-specific heart geometry and valve characteristics are linked to cardiovascular diseases and may play an important role in regulating hemodynamics within the heart. This hypothesis is studied through three specific aims. In specific aim 1, a computational fluid dynamics study was developed to quantify the hemodynamic characteristics within the right ventricles of healthy fetuses and fetuses with HLHS, using 4D patient-specific ultrasound scans. In these simulations, we find that the HLHS right ventricle exhibits a greater cardiac output than normal; yet, hemodynamics are relatively similar between normal and HLHS right ventricles. Overall, this study provides detailed quantitative flow patterns for HLHS, which has the potential to guide future prevention and therapeutic interventions, while more immediately providing additional functional detail to cardiologists to aid in decision making. The specific aim 2 is a comprehensive review in which we highlight underlying molecular mechanisms of acquired aortic stenosis calcification in relation to hemodynamics, complications related to the disease, diagnostic methods, and evolving treatment practices for calcific aortic stenosis and, bioprosthetic or native aortic scallop intentional laceration (BASILICA) procedure to free coronary arteries from obstruction. In specific aim 3, we use statistical trends and relationships to identify the role of patient-specific aortic valve characteristics in post-BASILICA coronary obstruction. The findings of this study shows that in addition to direct anatomical measurements of the aortic valve, the aspect ratios of the anatomical features are important in determining the cause of post-BASILICA coronary obstruction. The overall significance of this dissertation is that computational and statistical analysis of patient's specific flow hemodynamics and geometric characteristics can provide more insight into the cardiovascular disease and treatment approaches which can ultimately assist surgeons with procedural planning.
Open Access
Characterizing fuel reactivity in advanced internal combustion engines
(Colorado State University. Libraries, 2014) Baumgardner, Marc E., author; Marchese, Anthony J., advisor; Reardon, Ken, committee member; Olsen, Daniel, committee member; Gao, Xinfeng, committee member
The urgent need to increase efficiency and reduce exhaust emissions from internal combustion engines has resulted in an increased interest in alternative combustion modes. Premixed or partially premixed compression ignition modes, such as homogeneous-charge compression ignition (HCCI), reactivity-controlled compression ignition (RCCI) and multi-zone stratified compression ignition (MSCI) have been a particular focus because of their potential to deliver enhanced fuel efficiency and meet exhaust emissions mandates without the addition of costly after-treatment technologies. For HCCI and other single fuel, partially premixed compression ignition schemes such as MSCI, many studies have shown that fuels with characteristics intermediate between gasoline and diesel fuel are necessary. Many researchers have shown, however, that existing industry metrics such as Octane Number and Cetane Number are insufficient to represent fuel ignition characteristics for advanced engine combustion modes. In light of the poor performance of traditional metrics, new methods have been proposed to try and better characterize, order, and rank fuels used in HCCI operation. However, studies have since shown that when a broad array of fuels are considered, these recent metrics fail to adequately define a characteristic HCCI fuel index. Described in this work is an analysis of fuel reactivity in traditional and advanced internal combustion engines. Firstly, conventional engine regimes are broken down to their basic components, providing a framework for investigating the context of fuel reactivity. This analysis allows a novel equation to be formulated which links the historic metrics of Octane Number and Cetane Number. As part of this analysis a parameter, the knock length, is developed which explains the underlying principles of the Research and Motor Octane Number scales and further shows why some fuels test differently in these two methods. The knock length is also used to investigate unusual behavior observed in Methane Number reference fuels data - behavior which traditional concepts such as ignition delay and flame speed are unable to explain on their own. Secondly, this work focuses on the application of fuels such as bio-derived alcohols (ethanol and butanol) and fatty acid methyl esters in traditional and advanced combustion applications. Reactivity differences between alcohol and petroleum fuels are described and explained. Lastly, a new metric, the HCCI Number, is developed which allows the prediction of combustion timing in HCCI engines, and is highly amenable toward the development of bench-top laboratory apparatuses to facilitate practical adoption by fuel manufactures. Data from 23 different fuel blends tested in Cooperative Fuel Research (CFR) engines, a Fuel Ignition Tester, and a HCCI engine provide the experimental support for the theory presented herein. Additionally, a new chemical-kinetic mechanism is developed and used to describe combustion of n-butanol/n-heptane fuel mixtures in both conventional and advanced combustion applications (HCCI). Computational modeling is also used to examine the experiments presented herein: single and multi-zone (CHEMKIN) as well as system-level (GT Power) and multi-dimensional (CONVERGE) modeling approaches are developed and discussed. For the HCCI experiments conducted herein, an engine test-bed that allows HCCI examination across a wide array of conditions was also designed and fabricated. In summary, it is hoped that with better understanding of how fuels react in current and future engines, researchers can achieve the control necessary to bring higher performance engines to market and help the world take one step closer to addressing some of the pressing environmental and humanitarian issues at hand.
Embargo
Development of a prediction model for windborne debris damage assessment of coast communities under hurricanes
(Colorado State University. Libraries, 2023) Dong, Yue, author; Guo, Yanlin, advisor; van de Lindt, John W., committee member; Ellingwood, Bruce R., committee member; Gao, Xinfeng, committee member
Urban high-rise building envelopes may suffer severe damage induced by windborne debris during hurricanes. Breaches in urban building envelopes may lead to cascading building content loss due to rain intrusion and building functionality loss for long periods of time, thus disrupting the resilience of urban coastal communities. Such a societal disruption may become worse due to the rapid growth of population and development of economy in coastal communities. Objective of this dissertation is to develop an efficient prediction model for assessing windborne debris damage to building envelopes and apply it to the hurricane scenarios identified through a de-aggregation process to enable risk-informed resilience assessment of coastal communities for windborne debris impact. A set of scenario hurricanes corresponding to a stipulated return period (RP) for resilience assessment of coastal communities for debris impact is systematically identified using the de-aggregation approach proposed in this dissertation. The existing building envelope damage assessment models for urban high/mid-rise buildings often neglect the geometry of building clusters or simply assume a homogeneous configuration, which can introduce errors and uncertainties for urban building clusters with varying geometries and layouts. This dissertation proposes a new fragility modeling approach for urban buildings envelopes, which explicitly considers geometric configurations of urban buildings, to improve the accuracy of risk assessment for urban buildings. Estimating the urban wind field that drives the debris flight is critical for constructing fragilities for debris damage. The traditional tools for simulating urban wind fields, such as wind tunnel tests and Computational Fluid Dynamic (CFD), are usually expensive or time-consuming for complex urban environments and cannot offer an efficient prediction of the urban wind field that is sufficient for risk assessment at a community level. Therefore, an efficient machine learning (ML) based prediction model of wind fields around building clusters is proposed using conditional Generative Adversarial Networks (cGANs). Uncertainty analysis is conducted on the models and parameters involved in this procedure of debris damage assessment. The uncertainty in the final prediction of windborne debris damage is evaluated through uncertainty propagation among models and parameters. Sensitivity analysis with some critical factors is also conducted to identify the dominant contributors to the uncertainty in the estimation of debris damage. In the end, windborne debris damage on building envelopes in virtual communities under synthetic hurricanes scenarios is investigated to illustrate the damage assessment procedure for windborne debris impact at the community level.
Open Access
Effect of large-scale anisotropy on the small-scale structure of turbulence
(Colorado State University. Libraries, 2014) Morshed, Khandakar Niaz, author; Dasi, Lakshmi Prasad, advisor; Kirkpatrick, Allan, committee member; Gao, Xinfeng, committee member; Venayagamoorthy, Subhas Karan, committee member
Even though the small-scale structure of turbulence has been hypothesized to be locally isotropic with universal properties, numerous studies document the departure from local isotropy and universality in the presence of strong mean shear (or large-scale anisotropy). The goal of this work is to elucidate the effects of strong shear on the small-scale structure with emphasis on the physical mechanism through which mean shear deviates local structure from isotropy. Two dimensional time-resolved particle image velocimetry (PIV) experiments were performed in a stationary turbulent flow past a backward facing step at Reynolds numbers 13600 and 5500 based on the maximum velocity and step height. Large-scale anisotropic properties of the flow along with local turbulence characteristics were quantified in detail. Special points of interest distributed within the measurement domain for varying large-scale anisotropic characteristics were probed to analyze small-scale structure. Results show that velocity structure functions and their scaling exponents systematically align with the principal directions of deformation of the mean flow field. Furthermore, the probability density function (PDF) of the instantaneous dissipative scales indicate a potentially universal mechanism of how mean shear affects the distribution of dissipative scales captured through a local Reynolds number based on mean shear and dissipation rate. PDFs of the instantaneous dissipative scales in all directions demonstrate that mean shear strength and local principal axis directions dictate the behavior of structure functions, correlation functions, thereby influencing the dissipative scale PDFs in a directionally dependent manner.
Open Access
Four-stroke, internal combustion engine performance modeling
(Colorado State University. Libraries, 2017) Wagner, Richard C., author; Kirkpatrick, Allan, advisor; Gao, Xinfeng, committee member; Robinson, R. Steve, committee member
In this thesis, two models of four-stroke, internal combustion engines are created and compared. The first model predicts the intake and exhaust processes using isentropic flow equations augmented by discharge coefficients. The second model predicts the intake and exhaust processes using a compressible, time-accurate, Quasi-One-Dimensional (Q1D) approach. Both models employ the same heat release and reduced-order modeling of the cylinder charge. Both include friction and cylinder loss models so that the predicted performance values can be compared to measurements. The results indicate that the isentropic-based model neglects important fluid mechanics and returns inaccurate results. The Q1D flow model, combined with the reduced-order model of the cylinder charge, is able to capture the dominant intake and exhaust fluid mechanics and produces results that compare well with measurement. Fluid friction, convective heat transfer, piston ring and skirt friction and temperature-varying specific heats in the working fluids are all shown to be significant factors in engine performance predictions. Charge blowby is shown to play a lesser role.
Open Access
FTIR spectroscopy of methyl butanoate-air and propane-air low pressure flat flames
(Colorado State University. Libraries, 2012) Naber, Kristen Ann, author; Marchese, Anthony, advisor; Catton, Kimberly, committee member; Gao, Xinfeng, committee member
The combustion of fatty acid methyl esters (FAME) in diesel engines has been shown to produce lower emissions of carbon monoxide (CO), unburned hydrocarbons, greenhouse carbon dioxide (CO2), and particulate matter than petroleum based fuels. However, most diesel engine studies have shown that emission of oxides of nitrogen (NOx) typically increase for methyl ester fuels in comparison to petroleum based fuels. Many theories have been proposed to explain these NOx increases from FAME combustion but a general consensus has emerged toward two primary mechanisms: (1) the increased bulk modulus of biodiesel results in earlier fuel injection into the cylinder and/or (2) the presence of oxygen in the fuel results in a leaner (but still rich) premixed autoignition zone thereby increasing the local flame temperature during the premixed burn phase. It is well known that NOx is produced during the combustion of hydrocarbons in air from three different mechanisms: prompt NOx, thermal NOx, and via fuel bound nitrogen. Both of the mechanisms that have been proposed to explain the observed NOx increases from the combustion of FAME in diesel engines are related to the thermal NOx production route. However, no quantitative data exist on local in-cylinder temperatures and associated in-cylinder NO production during the premixed autoignition phase to experimentally verify these hypotheses. The present work is aimed at developing an experimental approach to examine a third hypothesis that suggests that the chemical structure of methyl esters results in an increase in prompt NOx in comparison to non-oxygenated hydrocarbons. This new hypothesis has the potential to be verified by conducting experiments with steady, laminar flames. Accordingly, in the present study, low pressure, flat flame burner experiments were conducted, which enabled direct temperature measurements using a thermocouple and direct species sampling using a quartz microprobe. The fuels used in the flame experiments were propane (C3H8) and methyl butanoate (C5H10O2), a small methyl ester fuel whose chemical kinetic mechanism has been the subject of substantial research in the past decade. The gas samples were directed to an FTIR spectrometer for analysis of various species including NO, CO, and CO2. Equivalence ratios of φ = 0.8, 1.0, and 1.2 were examined for both fuels. Temperatures were obtained using coated Pt-Pt/13%Rh type R thermocouples and were corrected for radiation losses. In addition to the experiments, laminar flame modeling studies were conducted using CHEMKIN for the both fuel types at each equivalence ratio using existing detailed chemical kinetic mechanisms to predict temperature and species concentrations. Because no methyl butanoate mechanisms containing detailed NOx chemistry exist, the propane/NOx chemical kinetic mechanism of Konnov and was combined with a detailed methyl butanoate mechanism Gail and coworkers. Experimental and modeling results show that nitric oxide production in the steady, premixed laminar methyl butanoate flames did not differ substantially from that produced in similar propane flames. Results were inconclusive on which nitric oxide formation mechanisms contributed to the overall measured concentrations.
Open Access
Links between atmospheric cloud radiative effects and tropical circulations
(Colorado State University. Libraries, 2021) Needham, Michael R., author; Randall, David A., advisor; Hurrell, James W., committee member; Gao, Xinfeng, committee member
Atmospheric cloud radiative effects (ACRE) quantify the radiative heating or cooling due to clouds within the atmosphere. In this study, a framework is developed with which to analyze the ways that ACRE impact large-scale circulations in humid and dry regions of the tropics. The frame-work is applied to a set of simulations from a global atmospheric model configured with uniform tropical sea surface temperatures, following the protocol of the Radiative Convective Equilibrium Model Intercomparison Project. It is found that humid regions export energy and import moisture, and that ACRE in extremely humid regions are strong enough to change the sign of the net radiation tendency. This net heating drives a feedback in which large-scale ascent moistens the troposphere by lifting latent energy from near the surface. Moisture at these higher levels then forms clouds which in turn reinforce the ACRE, continuing the process. The relevance of this feedback to the germinal study of Riehl and Malkus (1958) is discussed. Additionally, the analysis method reveals a simple relationship between cloud radiative effects and column relative humidity in the idealized model. The same relationship is also observed in cloud radiative effects calculated from satellite observations. This suggests a simple way to estimate the cloud radiative effect at the top of the atmosphere. The estimated cloud radiative effect may be useful in estimating the ACRE, which is harder to infer from measurements using previous methods. The estimation shows some skill at estimating the cloud radiative effect in humid regions across the tropics on time scales of one month or longer. The method is found to be extremely effective at estimating observed cloud radiative effects in the equatorial west Pacific. Weaknesses of the estimation method in relation to marine stratus clouds are discussed.
Open Access
New insights into flow over sharp-crested and pivot weirs using computational fluid dynamics
(Colorado State University. Libraries, 2021) Sinclair, Joseph, author; Venayagamoorthy, Subhas Karan, advisor; Gates, Timothy K., advisor; Gao, Xinfeng, committee member
Irrigation for agriculture is the highest use of fresh water in the world. Efficient and equitable access and distribution of this water is vital to survival of the Earth's population. Open channels are the most common means of conveying water for agricultural irrigation and hydraulic structures are often used in these open channels to regulate and measure flow to achieve desired conditions. Sharp-crested weirs are one of the most popular of these structures and pivot weirs are quickly becoming a more widely used hydraulic structure. The purpose of this study was to reexamine both types of weirs to better understand how they operate for flow regulation and measurement and to provide insights into the flow structure around the weir. Computational fluid dynamics, or CFD, was the primary tool used, with a commercial code called FLOW-3D being the specific software selected. Prior to investigating the weirs, preliminary studies were carried out to identify the best-practices in building an open-channel and hydraulic flow simulation in FLOW-3D. It was found that because FLOW-3D has no method of specifying developed flow prior to entering the model domain, additional care had to be taken to develop flow within the computational domain. The upstream length in the models was often extended to give the simulated flow more time and distance to develop. Additionally, the first-cell height had to be within a certain dimension to produce accurate velocity profiles due to the use of the logarithmic law of the wall boundary condition to solve for velocity in the first cell. Finally, a study analyzing the effects of the simulated downstream distance after a free-flowing sharp-crested weir revealed that the downstream distance has no effect on upstream flow. The sharp-crested weir parametric study analyzed velocity and pressure profiles over the crest, several calculated discharge coefficients, and turbulence flow structures upstream of the weir using high-resolution two-dimensional simulations. Three distinct operating regimes were identified based on the profiles over the crest as well as plots of the discharge coefficient against h/P where h is the upstream potentiometric head above the weir crest and P is the height of the crest above the channel bed. The first regime, the high-acceleration regime, occurs when h/P < 0.6. Flow accelerates greatly near the weir crest which results in negative pressure. The discharge coefficient has a negative linear trend with h/P in this regime. The next region occurs where 0.6 < h/P < 2.0 and is called the ideal-operating regime. In this regime, flow is not experiencing acceleration or inundation and better maintains the assumptions used in deriving the classical rating equation. The discharge coefficient is relatively constant in this case and a single value can be used with minimal error for all flow rates within this range. The final regime, the weir-inundated regime, is where h/P > 2.0. The weir is often submerged here and the effect of the weir on the flow is diminished due to the high depth of flow. Turbulence patterns upstream of the weir appear to have a relationship to the Reynolds number, Re, of the flow with eddies reaching a minimum size at a Re = 70,000. The region of smallest eddy size correlated to the ideal-operating regime, again lending to the hypothesis that flow is more efficiently controlled within this regime. Six flow rates at five different gate angles (27°, 47°, 57°, 72°, and 90°) were tested for the pivot weir study. After analysis of the h/P values and discharge coefficients, it was found that the flow rates bounding the ideal-operating regime shift lower in magnitude as the gate angle decreases. Each angle also has an associated relatively constant discharge coefficient in its ideal-operating regime, meaning a single coefficient value may be used with minimal error. Comparison of the average discharge coefficient for each angle revealed a minimum value at 72° and a maximum value at 27°. The fraction of the total upstream mechanical energy head comprised of the velocity head was found to increase as gate angle decreased. Visual contours of velocity and pressure depicted how the flow changes as it approaches weirs of varying angles, with the recirculation zone moving from upstream of the weir to solely downstream of the weir for angles below 47°. Plots of the non-dimensional pressure and velocity profiles over the weir crest revealed that velocity over the crest increases as the inclination angle decreases. At the 47° weir, the flow acceleration created a region of negative relative pressure close to the weir. These results highlight how flow over both the sharp-crested weir and pivot weir varies considerably. Thus, caution must be exercised in using empirical discharge coefficients for a broad range of h/P value.
Open Access
Novel laser ignition technique using dual-pulse pre-ionization
(Colorado State University. Libraries, 2017) Dumitrache, Ciprian, author; Yalin, Azer P., advisor; Marchese, Anthony J., advisor; Gao, Xinfeng, committee member; Kirkpatrick, Allan T., committee member; Van Orden, Alan, committee member
Recent advances in the development of compact high power laser sources and fiber optic delivery of giant pulses have generated a renewed interest in laser ignition. The non-intrusive nature of laser ignition gives it a set of unique characteristics over the well-established capacitive discharge devices (or spark plugs) that are currently used as ignition sources in engines. Overall, the use of laser ignition has been shown to have a positive impact on engine operation leading to a reduction in NOx emission, fuel saving and an increased operational envelope of current engines. Conventionally, laser ignition is achieved by tightly focusing a high-power q-switched laser pulse until the optical intensity at the focus is high enough to breakdown the gas molecules. This leads to the formation of a spark that serves as the ignition source in engines. However, there are certain disadvantages associated with this ignition method. This ionization approach is energetically inefficient as the medium is transparent to the laser radiation until the laser intensity is high enough to cause gas breakdown. As a consequence, very high energies are required for ignition (about an order of magnitude higher energy than capacitive plugs at stoichiometric conditions). Additionally, the fluid flow induced during the plasma recombination generates high vorticity leading to high rates of flame stretching. In this work, we are addressing some of the aforementioned disadvantages of laser ignition by developing a novel approach based on a dual-pulse pre-ionization scheme. The new technique works by decoupling the effect of the two ionization mechanisms governing plasma formation: multiphoton ionization (MPI) and electron avalanche ionization (EAI). An UV nanosecond pulse (λ=266 nm) is used to generate initial ionization through MPI. This is followed by an overlapped NIR nanosecond pulse (λ=1064 nm) that adds energy into the pre-ionized mixture into a controlled manner until the gas temperature is suitable for combustion (T=2000-3000 K). This technique is demonstrated by attempting ignition of various mixtures of propane-air and it is shown to have distinct advantages when compared to the classical approach: lower ignition energy for given stoichiometry than conventional laser ignition (~20% lower), extension of the lean limit (~15% leaner) and improvement in combustion efficiency. Moreover, it is demonstrated that careful alignment of the two pulses influences the fluid dynamics of the early flame kernel growth. This finding has a number of implications for practical uses as it demonstrates that the flame kernel dynamics can be tailored using various combinations of laser pulses and opens the door for implementing such a technique to applications such as: flame holding and flame stabilization in high speed flow combustors (such as ramjet and scramjet engines), reducing flame stretching in highly turbulent combustion devices and increasing combustion efficiency for stationary natural gas engines. As such, the work presented in this dissertation should be of interest to a broad audience including those interested in combustion research, engine operation, chemically reacting flows, plasma dynamics and laser diagnostics.
Open Access
Numerical algorithms for two-fluid, weakly-compressible flows
(Colorado State University. Libraries, 2024) Brodin, Erik, author; Guzik, Stephen, advisor; Colella, Phillip, advisor; Gao, Xinfeng, committee member; Troxell, Wade, committee member; Bangerth, Wolfgang, committee member
A multifluid numerical method is developed for flows of two fluids in a single domain at low Mach numbers. An all-speed formulation of the Navier-Stokes equations governs the dynamics of both fluids and the level-set method defines the interface between them and the domain of each fluid. The algorithm represents velocity and pressure as single valued throughout the whole domain, and fluid dependent variables, density and bulk modulus, only in the domain of their respective fluid. The all-speed equations are not subject to the divergence-free velocity constraint through use of a redundant velocity equation, and are evolved in time using an implicit-explicit additive Runge-Kutta method resulting in a time step constrained only by the bulk fluid velocity. Each fluid is evolved conservatively with respect to the moving interface between them. Due to errors in the evolution in the interface, perturbations in the volume of each fluid, and thereby the density, can develop. A thermodynamically consistent correction is made to the position of the interface to reduce these unphysical perturbations. The algorithm developed here includes three novel contributions: (i) the use of a multifluid all-speed algorithm with a level-set method for evolution of the solution in time, (ii) a multifluid algorithm using the level-set to capture the interface in the weakly compressible regime that is thermodynamically consistent, and (iii) an initialization method for sharp corners in the level-set. Numerical tests have demonstrated that the algorithm exhibits the expected low Mach number behavior, achieves second order-accuracy, and ensures fluid volumes are bounded and convergent.
Open Access
Quasidimensional modeling of reacting fuel sprays using detailed chemical kinetics
(Colorado State University. Libraries, 2016) Dobos, Aron Peter, author; Kirkpatrick, Allan T., advisor; Marchese, Anthony, committee member; Gao, Xinfeng, committee member; Venayagamoorthy, Karan, committee member
Since its invention in the late 1800s, the internal combustion engine has been indispensable to society for motive transport at all scales worldwide. Despite growing concern about the environmental damage caused by the pervasive use of these engines, no compelling alternative has yet emerged that matches the internal combustion engine's robustness, versatility, and high power-to-weight ratio. Consequently, as requirements on engine designs continue to increase to meet new emissions and efficiency standards, there is a strong need for computationally efficient and accurate predictive modeling of complex engine combustion processes. This work presents an efficient approach to direct injection engine combustion simulation that uses detailed chemical kinetics with a quasidimensional fuel spray model. Instead of a full multidimensional approach that solves continuity, momentum, energy, and chemistry equations simultaneously over a fine grid, the spatial information is greatly reduced and modeled phenomenologically. The model discretizes the fuel spray into independent parcels that entrain air from the surroundings and account for liquid fuel vaporization. Gas phase species concentrations and heat release in each parcel are calculated by detailed chemical kinetic mechanisms for the fuel under consideration. Comparisons of predicted pressure, heat release, and emissions with data from diesel engine experiments show good agreement overall, and suggest that spray combustion processes can be modeled without calibration of empirical constants at a significantly lower computational cost than with standard multidimensional tools. The new combustion model is also used to investigate spray structure and emissions trends for biodiesel fuels in a compression ignition engine. Results underscore the complex relationships among operational parameters, fuel chemistry, and NOx emissions, and provide further evidence of a link between stoichiometry near the flame lift-off length and formation of NOx. In addition, fuel molecular structure is demonstrated to be a significant factor in NOx emissions, but more robust chemical kinetic mechanisms and soot models for biodiesel are likely needed for improved predictive accuracy in modeling alternative fuels.
Open Access
Randomized hierarchical semi-separable structures for parallel direct double-higher-order method of moments
(Colorado State University. Libraries, 2017) Moin, Nabeel, author; Notaros, Branislav, advisor; Pezeshki, Ali, committee member; Gao, Xinfeng, committee member
As technology grows more and more rapidly, the need for large-scale electromagnetics modelling arises. This includes software that can handle very large problems and simulate them quickly. The goal of this research is to introduce some randomized techniques to existing methods to increase the speed and efficiency of Computational Electromagnetics (CEM) simulations. A particularly effective existing method is the Surface Integral Equation (SIE) formulation of the Method of Moments (MoM) using Double Higher Order (DHO) modelling. The advantage of this method is that it can typically model geometries with fewer unknowns, but the disadvantage is that the system matrix is fully dense. In order to counter this drawback, we utilize Hierarchical Semi-separable Structures (HSS), a data-sparse representation that expresses the off-diagonal blocks of the matrix in terms of low rank approximations. This improves both the speed and memory efficiency of the DHO-MoM-SIE. Of the three steps of HSS (construction, factorization, and solving), the one with the most computational cost is construction, with a complexity of O(rN2), where N is the size of the matrix and r is maximum rank of the off-diagonal blocks. This step can be improved by constructing the HSS form with Randomized Sampling (RS). If a vector can be applied to the system matrix in O(N1.5) time, which we accomplish by means of the Fast Multipole Method (FMM) then the HSS construction time is reduced to O(r2 N1.5). This work presents the theory of the above methods. Numerical validation will also be presented.
Open Access
Soft and shape morphing robots driven by twisted-and-coiled actuators
(Colorado State University. Libraries, 2022) Sun, Jiefeng, author; Zhao, Jianguo, advisor; Maciejewski, Anthony, committee member; Gao, Xinfeng, committee member; Yourdkhani, Mostafa, committee member
Soft robots are a new type of robot with deformable bodies and muscle-like actuation, which are fundamentally different from traditional robots with rigid links and motor-based actuators. Owing to their elasticity, soft robots outperform rigid ones in safety, maneuverability, and adaptability. With their advantages, many soft robots have been developed for manipulation and locomotion in recent years. To enable their unique capabilities, soft robots require a key component—the actuator. Many different actuators have been used, including the conventional pneumatic-driven and cable-driven methods, as well as several novel approaches proposed recently such as combustion, dielectric elastomers, chemical reactions, liquid–vapor transition, liquid crystal elastomer, and shape memory alloy. Besides existing actuation approaches, another promising actuator for soft robots is the twisted-and-coiled actuator (TCA). Compared with existing actuation methods, TCAs exhibit several unique characteristics: like large energy density and being directly actuated by electricity with a small voltage. All of these characteristics will potentially enable small-scale and untethered soft robots that in general are difficult to be accomplished by pneumatic and tendon-driven methods. Further, unlike shape memory alloys, TCAs are intrinsically soft, making it possible to embed them in any shape inside a soft body to generate versatile motion. To better actuate soft robots with TCAs, we introduce a novel fabrication technique of contraction TCAs that will have uniform initial gaps between neighboring coils. In this case, they can contract larger than 48% without a preload, termed free stroke. We also characterize such a TCA and compare it with self-coiled TCAs. Besides the free stroke property, the TCA can also be directly used as a sensor that provides its displacement information. To better design, optimize, and control TCAs for various applications, we developed a physics-based model based on TCAs' physical parameters as opposed to system identification methods, since such physics-based models are expected to be a general model for different types of TCAs (self-coiled, free-stroke, conical) We demonstrate soft robots with programmable motions by placing TCAs in different shapes inside a soft body. Specifically, we embed TCAs in a curved U shape, a helical shape, and straight shapes in parallel to enable three different motions: two-dimensional bending, twisting, and three-dimensional bending. We also combine the three motions to demonstrate a completely soft robotic arm that mimics a human forearm. A model is also developed to simulate the TCA-driven soft robots. The framework can model 1) the complicated routes of multiple TCAs in a soft body and 2) the coupling effect between the soft body and the TCAs during their actuation process. When not actuated, a TCA in the soft body is an antagonistic elastic element that restrains the magnitude of the motion and increases the stiffness of the robot. By stacking several modules together, we simulate the sequential motion of a soft robotics arm with three-dimensional bending, twisting, and grasping motion. The presented modeling and simulation approach will facilitate the design, optimization, and control of soft robots driven by TCAs or other types of artificial muscles. Finally, we design shape morphing robots that can morph the shape of their bodies to adapt to a different environment. These robots can be built with shape-morphing modules. A shape-morphing module has a variable stiffness element that allows it to switch between soft and rigid states. While it is in a soft state, it can morph to different configurations driven by TCAs. We demonstrate robots built with these modules can morph to different shapes that facilitate grasping and locomotion.
Open Access
Surrogate modeling for efficient analysis and design of engineering systems
(Colorado State University. Libraries, 2021) Li, Min, author; Jia, Gaofeng, advisor; Ellingwood, Bruce, committee member; van de Lindt, John, committee member; Gao, Xinfeng, committee member
Surrogate models, trained using a data-driven approach, have been extensively used to approximate the input/output relationship for expensive high-fidelity models (e.g., large-scale physical experiments and high-resolution computationally expensive numerical simulations). The computational efficiency of surrogate models is greatly increased compared with the high-fidelity models. Once trained, the original high-fidelity models can be replaced by the surrogate models to facilitate efficient subsequent analysis and design of engineering systems. The quality of surrogate based analysis and design of engineering systems relies largely on the prediction accuracy of the constructed surrogate model. To ensure the prediction accuracy, the training data should be adequate in terms of the size of the training data and their sampling. Unfortunately, constrained by limited computational budgets, typically it is challenging to obtain a lot of training data by running high-fidelity models. Furthermore, significant challenge arises in obtaining sufficient training data for problems with high-dimensional model inputs due to the well-known curse of dimensionality. In order to build surrogate models with high prediction accuracy and generalization performance while using as less computational resources as possible, this dissertation proposes several advanced strategies and examines their performances within several practical engineering applications. The fundamental idea of the proposed strategies is to embed extra knowledge about the high-fidelity models in the surrogate model by enriching the training data (e.g., leverage additional low-fidelity data, or censored/bounded data) and enhancing model assumption (e.g., explicitly incorporate prior knowledge about the physics of the problem, or explore low-dimensional latent structures/features), which reduces the required size of high-fidelity training data and meanwhile effectively boosts the prediction accuracy of the established surrogate model. Among different surrogate models, Gaussian process models have been gaining popularity due to its flexibility in modeling complex functions and ability to provide closed-form predictive distributions. Therefore, the strategies are developed in the context of Gaussian process model, but the ideas are expected to be applicable to other types of surrogate models. In particular, this dissertation (i) develops a physics-constrained Gaussian process model to efficiently incorporate our prior knowledge about physical constraints/characteristics of the input/output relationship by designing specific kernels, (ii) proposes a general multi-fidelity Gaussian process model capable of integrating training data with different level of accuracy (i.e., both high-fidelity data and low-fidelity data) and completeness (i.e., both accurate data and censored data), and (iii) develops an efficient surrogate modeling approach for problems with high-dimensional binary model inputs by integrating dimension reduction technique and Gaussian process model, and investigates its application in design optimization problems. The excellent performance of the proposed strategies are then validated through analysis and design of several different engineering systems, including (i) calculating hydrodynamic characteristics of wave energy converters (WECs) in an array, (ii) predicting the deformation capacity of reinforced concrete columns under cyclic loading, and (iii) optimizing topology of periodic structures.
Open Access
Towards automatic compilation for energy efficient iterative stencil computations
(Colorado State University. Libraries, 2016) Zou, Yun, author; Rajopadhye, Sanjay, advisor; Strout, Michelle M., committee member; Anderson, Chuck W., committee member; Gao, Xinfeng, committee member
Today, energy has become a critical concern in all aspects of computing. In this thesis, we address the energy efficiency of an important class of programs called "Stencil Computations", which occur frequently in a wide variety of scientific applications. We target the compute intensive stencil computations, and seek to automatically produce codes that minimize energy consumption. Two main energy consumption contributors are addressed in our work -- dynamic memory energy and static energy -- which are proportional to the number of off-chip memory accesses and execution time separately. We first target the dynamic energy consumption, and propose an energy-efficient tiling and parallelization strategy called Flattened Multi-Pass Parallelization (FMPP), it seeks to minimize the total number of off-chip memory accesses without sacrificing execution time. Our strategy uses two-level tiling, which first partitions the iteration space into "passes", and then tiles the passes and executes the passes in a "non-synchronized" or overlapped fashion. Producing such codes are beyond the capability of current tiled code generators, because the schedules used are polynomials, thus are more general than multidimensional schedules. We present a parametric tiled code generation algorithm for FMPP strategy for the programs with parallelogram shaped iteration space. Then, we seek to reduce the static energy consumption by further improving the performance of generated code. We found that existing production compilers fail to vectorize the parametric tiled code efficiently, which is critical to the compiled program's performance. We propose a compilation method for parametrically tiled stencil computations that systematically vectorizes the loops with short vector intrinsics. Our method targets the non-boundary full tiles, trades register loads of register reorganization operations, enables vector register reuse within and across vectorized computations, and incorporates temporary buffering and memory padding to align memory accesses. We developed a semi-automatic code generation framework to support our memory efficient strategy and compilation method for vectorization. Our framework allows a number of optimization choices to be configured (e.g., the trade-off of data reorganization instructions and the number of aligned loads, tiling and parallelization strategy etc). We evaluate our strategy on several modern Intel architectures with a set of stencil benchmarks. Our experimental results shown that our energy efficient tiling and parallelization strategy is able to significantly reduce the dynamic memory energy consumption on different platforms, by about a 74% (resp. 75% and 67%) reduction on an 8-core Xeon E5-2650 v2 (resp. 6-core Xeon E5-2620 v2 and 6-core Xeon E5-2620 v3). This leads to a reduction in the total energy consumption of the program by 2% to 14%. Our vectorized code also shows significant performance improvement over existing compilers. We get an average of 34% performance improvement for Jacobi 1D on all the platforms, and up to 40% performance improvement for some 2D stencils. With the savings in both static energy and dynamic memory energy, we are able to reduce the total energy consumption by 20% in average for 2D stencils on the Xeon E5-2620~v3 platform. The tuning space for our experiment is fairly large (including both optimization choices and tile sizes), and exhaustively searching the whole space is extremely time-consuming. In our work, we also take the first step for building an autotuner for our framework. We propose to use Artificial Neural Networks to assist the tuning process, and present a study of performance tuning with the assistance of neural networks. Our results show that the use of an Artificial Neural Network has a great potential to accurately predict the performance, and can help reduce the search space significantly.
Open Access
Volumetric efficiency modeling of a four stroke IC engine
(Colorado State University. Libraries, 2017) Yin, Shumei, author; Kirkpatrick, Allan T., advisor; Cheney, Margaret, committee member; Gao, Xinfeng, committee member
Volumetric efficiency, one of the most important engine performance parameters, is influenced by several engine parameters such as valve timing, valve lift, intake and exhaust runner length, and intake and exhaust pressure. To explore how these parameters impact volumetric efficiency, a 1D unsteady thermal fluid analysis is performed to determine the instantaneous cylinder pressure and the mass flow rate through the intake and exhaust valves during the intake and exhaust processes. In addition to a MATLAB implementation, a GT-Power model is also developed for validation. A synthetic intake pressure pulse is then added to the model to explore the engine intake tuning effect. The results predict a volumetric efficiency increase by about $9\%$ when this pulse enters the cylinder near bottom dead center (BDC). The prediction is consistent with an acoustic model predicting that the maximum volumetric efficiency is reached when the natural frequency of the intake system equals the frequency of the intake process. The GT-Power model is also used to validate the relationship between the engine speed and intake runner length for optimal volumetric efficiency. The results from GT-Power do not agree with the Helmholtz model very well. Finally, the effect of the intake valve timing, valve lift and intake and exhaust pressure on volumetric efficiency are also determined.