Indian Institute of Science Bangalore
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Characterization and Modelling of Switching Dynamics of SiC MOSFETs
No full textSilicon Carbide MOSFETs (SiC MOSFETs) fall into the class of wide band gap (WBG) power devices. These devices are commercially available in the voltage range of 600-3300V and superior over the state of the art Si insulated gate bipolar junction transistors (IGBTs) due to their better electrical and thermal performances.
In power electronic converters, semiconductor devices operate as switches. They can be turned on or off using a control signal. Unlike ideal switches, practical devices require a finite amount of time to transit between on and off states. This is termed as switching transient. Non-zero finite product of voltage and current during switching transient results in switching loss. Characterization and modelling of switching dynamics help gain insight into the switching process and estimate switching loss. It is useful over experimental measurement techniques like double pulse test (DPT) or calorimetric measurements in the early stages of power converter design. Estimated loss through the switching transient model can be used to determine switching frequency and selection of power devices. Also, switching dynamics is strongly impacted by the device and circuit parasitics. Insight into the switching process helps in the proper design of gate driver and power circuit layout.
Superior material properties of SiC MOSFET leads to smaller die size compared to the state of the art Si-based power devices. It results in faster switching transients and lower switching loss. However, it excites device and circuit parasitics that may lead to prolonged oscillation, high device stress, spurious turn on and EMI-related issues Etc. So, the benefit of using SiC MOSFET as power devices come with numerous design challenges resulting in slow commercial adaptation. It is predicted that the overall market share of WBG devices (SiC and GaN together) will be roughly 10% of the total market for power semiconductors by 2025.
To overcome the design challenges and fully utilize the benefits of fast switching SiC MOSFETs, a better understanding of dynamics is essential. However, the switching dynamics of SiC MOSFET is different compared to its Si counterpart. This is due to the highly non-linear device characteristics. Also, the fast switching transient of SiC MOSFET excites the circuit parasitics and makes the switching dynamics highly involved. This work focuses on characterization and
modelling of switching transient of SiC MOSFET.
Simulation and analytical modelling approaches are used to model the switching dynamics and estimate switching loss. The behavioural modelling approach is a widely used simulation based approach (i.e., Spice simulation) and it can capture the switching transient with sufficient accuracy. This approach uses lumped parameter model (circuit model) of the device and external circuit and can be simulated in circuit simulator like MATLAB/Simulinkr. This implies numerical solution of a set of coupled non-linear differential equations. On the other hand, analytical modelling approach is based on the simplified approximate solution of a set of coupled non-linear differential equations obtained from the behavioural model. In order to obtain the approximate solution, the entire switching process is divided into different modes with clearly defined transition conditions. Different approximations are used in each mode to arrive at analytical closed-form solutions or reduced order coupled non-linear differential equations. This model is computationally efficient and can be implemented easily in freely available programming platforms such as C or Python. Also, the parameters required for analytical models can be obtained from the device datasheet. This modelling approach is beneficial for the converter design when switching loss and junction temperature need to be evaluated over several operating points for many available devices from different manufacturers
Minimizing latency in data acquisition, distributed processing, storage and retrieval
No full textAchieving low latency is of utmost importance in applications demanding real-time sensing
and control as in cyber-physical systems. In this thesis, we explore three different facets of
ensuring low latency in such systems. First part of this manuscript considers the design of
an encoder-decoder system to facilitate real-time tracking of a physical process modelled as a
first order auto-regressive process. Samples from a high-dimensional first-order auto-regressive
process generated by an independently and identically distributed random innovation sequence
are observed by a sender which can communicate only finitely many bits per unit time to a
receiver. The receiver seeks to form an estimate of the process value at every time instant in
real-time. We consider a time-slotted communication model in a slow-sampling regime where
multiple communication slots occur between two sampling instants. We propose a successive
update scheme which uses communication between sampling instants to refine estimates of the
latest sample and study the following question: Is it better to collect communication of multiple
slots to send better refined estimates, making the receiver wait more for every refinement, or to
be fast but loose and send new information in every communication opportunity? We show that
the fast but loose successive update scheme with ideal spherical codes is universally optimal
asymptotically for a large dimension. However, most practical quantization codes for fixed
dimensions do not meet the ideal performance required for this optimality, and they typically
will have a bias in the form of a fixed additive error. Interestingly, our analysis shows that the
fast but loose scheme is not an optimal choice in the presence of such errors, and a judiciously
chosen frequency of updates outperforms it.
Next part considers designing load balancing policies that ensures low latency without needing
extra overhead in terms of server-side feedback or coordination among the servers. Dispatching
policies such as the join shortest queue (JSQ), join smallest work (JSW) and their power
of two variants are used in load balancing systems where the instantaneous queue length or
workload information at all queues or a subset of them can be queried. In situations where the
dispatcher has an associated memory, one can minimize this query overhead by maintaining a
list of idle servers to which jobs can be dispatched. Recent alternative approaches that do not require querying such information include the cancel on start and cancel on complete based
replication policies. The downside of such policies however is that the servers must communicate
the start or completion of each service to the dispatcher and must allow cancellation
of redundant copies. In practice, the requirements of query messaging, memory, and replica
cancellation pose challenges in their implementation and their advantages are not clear. We
consider load balancing policies that do not query load information, do not have a memory,
and do not cancel replicas. Surprisingly, we were able to identify operating regimes where such
policies have better performance when compared to policies that utilize server feedback information.
Our policies allow the dispatcher to append a timer to each job or its replica. A job
or a replica is discarded if its timer expires before it starts getting served. We analyze several
variants of this policy which are novel, simple to implement, and also have remarkably good
performance, despite no feedback from servers to the dispatcher.
Finally, we consider the setting of a distributed storage system where a single file is subdivided
into smaller fragments of same size which are then replicated with a common replication
factor across servers of identical cache size. An incoming file download request is sent to all
the servers, and the download is completed whenever the request gathers all the fragments. At
each server, we are interested in determining the set of fragments to be stored, and the sequence
in which fragments should be accessed, such that the mean file download time for a request
is minimized. We model the fragment download time as an exponential random variable independent
and identically distributed for all fragments across all servers, and show that the mean
file download time can be lower bounded in terms of the expected number of useful servers
summed over all distinct fragment downloads. We present deterministic storage schemes that
attempt to maximize the number of useful servers. We show that finding the optimal sequence
of accessing the fragments is a Markov decision problem, whose complexity grows exponentially
with the number of fragments. We propose heuristic algorithms that determine the sequence
of access to the fragments which are empirically shown to perform well
Design and Characterisation of Rotating Gliding Arc Reactor for Dilute Hydrocarbon Conversion Applications: Experiments and Simulations Studies
No full textIn recent years, non-thermal plasma technology is becoming popular for chemical applications involving conversion/abatement/decomposition of compounds of interest. The specialty of non-thermal plasmas is to activate chemical processes at atmospheric conditions, which are thermodynamically limited. However, plasma reactors for chemical conversion are still on the laboratory scale (flow rates of the order of a few mL·min-1) and pose scale-up challenges. The challenges mainly arise due to the strong interaction between the plasma and gas, whose interaction behavior is not fully understood. The rotating gliding arc (RGA) plasma reactor is well adapted to scale up for high flow rate applications. The reactor has a tangential entry of the treatment gas, creating a swirl flow that rotates the arc formed between two diverging electrodes. The complex behavior of the rotating gliding arc poses challenges in quantifying the plasma parameters governing the chemistry, such as reduced electric field, gas temperature, electron temperature, and discharge size. Nevertheless, to meet the growing scale of the demand for sustainable energy and chemistry, it is necessary to investigate the performance and behavior of plasma reactors (characterization) with large throughputs. This dissertation: First part proposes a new electrode configuration for the rotating gliding arc plasma reactor that facilitates scaling up of plasma volume without the need to scale up the reactor size. The flow regime (laminar, transitional, and turbulent) in the electrode region is characterized for flow rates between 5 SL·min-1 and 50 SL·min-1 for multiple tangential entries, using the Reynolds number defined based on the tangential velocity. The defined Reynolds number is found to have a linear relationship with the arc’s rotation; the arc rotation and gas rotation are comparable. The second part validates the applicability of a method to estimate the reduced electric field, using a multi–diagnostic approach and collisional-radiative modeling. Image processing techniques are developed to estimate the length and diameter of the rotating arc. In the third part, the reactor’s electrical, optical, morphological, and chemical characteristics are investigated at transitional (5 SL·min-1) and highly turbulent (50 SL·min-1) flow regimes, using nitrogen as a plasma-forming gas. When changed from transitional to turbulent flow, operation mode transitioned from glow to spark due to frequent reignition events; the average reduced electric field and electron temperature raises (38→92 Td, 0.84→2.2 eV); plasma’s gas temperature is slightly cooled (2973→2807 K). The G–factor (molecules generated per 100 eV of energy input) of the chemically active singlet and triplet metastable states of N2 increases by a factor of 20 and 65, respectively—indicating increased energy efficiency, a promising feature for chemical applications. This result is further confirmed by a dilute toluene stream (112±10 ppmV) conversion experiment, which shows a three-fold increase in the energy efficiency achieving 3.0±0.2 g·kWh-1 at a highly turbulent flow. The final part investigates the decomposition of dilute methane (1% by volume) in a nitrogen stream. When changed from transitional (5 SL·min-1) to turbulent (50 SL·min-1) flow, the operation mode changes from glow to spark type; the average electric field, plasma’s gas temperature, and electron temperature raises (106→156 V·mm-1 , 3681→3911 K, and 1.62→2.12 eV). The energy efficiency in decomposing CH4 increases by a factor of 3.9 (16.1→61.9 g·kWh-1). Chemical kinetics simulation shows that the reactions induced by H, CH, and CH3 (key–species) are the first three dominants in CH4 consumption yet differ by their contribution values for both the flow regimes. The rate of the dominant CH4 consuming reactions increases by 80–148% involving electron and singlet state of N2 and decreases by 34–93% involving CH, CH3, and triplet state of N2. The electron–impact processes generate at least 50% more key–species and metastables for every 100 eV of input energy, explaining the increased energy efficiency at turbulent flow. These observations clearly show that the flow regime does influence plasma chemistry. This work highlights the significance of the flow regime, which is often overlooked by the plasma community. From the application point of view, based on this work, it is demonstrated that the developed RGA reactor is suitable to decompose dilute hydrocarbons with energy-efficient operation at high flow rates—a promising feature for upscaling. The understandings evolved in this work will help optimize the reactor for improved conversion/decomposition efficiency
Cerium Oxide-based Degradable Polymer Nanocomposites for Bone Tissue Engineering
No full textThe incidences of bone-related disorders is growing steeply worldwide because of acute trauma, diseases related to aging, and obesity. Bone has a natural regenerative capacity to repair and regenerate fractures and small defects. However, surgical intervention is required in the case of large bone defects and non-union fractures. Conventionally, substitutes such as bone grafts are used to treat the aforementioned bone defects. Drawbacks associated with bone grafts, such as low donor availability, immune rejection, multiple surgeries, etc., have created a huge demand for bone tissue substitute development. Bone tissue engineering aims to fabricate a scaffold that closely mimics the bone tissue microenvironment and thus stimulates bone regeneration and integration with the host tissue. Over the years, studies have shown that degradable polymer nanocomposites provide a better combination of properties to scaffolds over polymer alone. Also, it has been reported that oxidative stress can hamper the bone repair process. With its unique redox properties, cerium oxide (ceria) is increasingly being studied in biomedical applications but its potential in orthopedic applications is minimally explored. Ceria can be used to fabricate multifunctional polymer nanocomposites. Thus, ceria-based composite scaffolds could be developed and investigated as scaffolds that potentially offer multifunctional benefits for bone tissue engineering.
This thesis comprises seven chapters. Chapter 1 briefly introduces the concept of bone tissue engineering, polymer nanocomposites, oxidative stress in bone repair, and the unique properties of ceria. The chapter further outlines the literature review on the use of degradable polymeric nanocomposites for bone tissue engineering. Furthermore, the applications of ceria nanoparticles in the biomedical field are discussed with special attention to the antioxidant property that offers protection against oxidative stress in several degenerative disorders.
Chapters 2, 3, and 4 focus on synthesizing olive oil-based degradable polymer nanocomposites. Chapter 2 describes a combinatorial approach to prepare a library of polyesteramides from olive oil with tuneable properties. Polyesteramides are polymers with ester groups that provide degradability, whereas amide groups offer thermo-mechanical properties. The degradation, mechanical, and release properties were tailored by varying the chain length of the diacid, curing time, and stoichiometric ratio of reactants. Further, the fabrication of ceria-infused nanocomposites prepared by compression molding is also discussed in this chapter. The synthesized polymers and nanocomposite were cytocompatible in nature. And the release studies confirmed that the composites could be used as delivery platforms, including for ceria nanoparticles.
Chapter 3 explains the synthesis of slower degrading polyurethanes compared to polyesteramides from olive oil that are better suited for engineering tissue scaffolds. Polyurethanes are widely used in biomedical applications based on their various physicochemical p= roperties and biocompatibility. Two different polyurethanes were synthesized from olive oil, optionally incorporating polyethylene glycol (PEG). Improvement in degradation while the reduction in the mechanical properties of polyurethanes was observed after adding PEG. The synthesized polyurethanes can be fabricated into various 2D substrates and 3D scaffolds by compression molding and particulate leaching techniques. Further, the cytocompatibility and osteogenesis studies were performed, which are presented in this chapter. The result showed both the polyurethanes were cytocompatible and supported osteogenesis. Thus, this chapter deals with olive oil-based polyurethanes as a promising biomaterial for developing scaffolds with tailored degradation and mechanical properties for tissue regeneration.
Chapter 4 describes the synthesis of hybrid nanoparticles containing ceria nanoparticles anchored to the graphene sheets using a hydrothermal process and its advantage in improving the bioactivity of olive oil-based polyurethane. The hybrid particles afford good dispersion and reduced agglomeration in contrast to ceria nanoparticles. The various nanocomposites were prepared by in situ polymerization process incorporating hybrid, graphene oxide, or ceria nanoparticles. All the composites showed minimal toxicity to preosteoblasts. Hybrid particle-infused nanocomposites demonstrated improved radical scavenging potential and osteogenic differentiation ability over other nanocomposites and neat polyurethane. Thus, the collaborative effect of graphene and ceria in hybrid particles provides multifunctional properties to olive oil-based polyurethanes for potential application in bone tissue regeneration.
Chapters 5 and 6 demonstrate the use of known degradable polymers such as polylactic acid (PLA) and polycaprolactone (PCL) to fabricate multifunctional composite scaffolds containing ceria for bone tissue engineering. Chapter 5 explains a strategy to surface decorate 3D printed PLA scaffold with ceria and its advantage in bone regeneration. The 3D porous PLA scaffold was fabricated using a fused filament fabrication-based method. A facile polyethylene imine-citric acid conjugation was used to the functionalized scaffold with ceria. The surface functionalization was nontoxic and helped protect human mesenchymal stem cells from oxidative stress. Further, the decorated scaffold exhibited improved osteogenic and antibacterial potential than unfunctionalized scaffolds. Thus, the current chapter display a simple method of surface decoration of 3D printed PLA scaffolds with ceria offering a viable route for improvement of its bioactivity for bone tissue engineering.
Chapter 6 describes the fabrication of ceria-infused PCL nanofibrous scaffolds and its benefit in bone tissue engineering in the older population. The older population has a greater number of senescent cells, which are responsible for delayed bone regeneration. Senescent cells are identified with the cell cycle arrest and oxidative microenvironment. Senescence was induced by exposing preosteoblasts to ionizing radiations. The potential to scavenge free radicles showed that the strategy of ceria incorporation in nanofibrous scaffolds could reduce the oxidative stress level in senescent and non-senescent cells. Ceria-infused fibers rescued the decreased osteogenic potential caused due to senescence. Thus, the addition of ceria nanoparticles provides multifunctional properties to nanofibers which could be used in bone regeneration in the geriatric population.
Chapter 7 summarizes the key outcomes of the different studies performed here. The future scope and extension of this work are also discussed in this chapter.
In conclusion, the current thesis focuses on enhancing the osteogenic activity along with the antioxidant potential of scaffolds. This was accomplished by developing ceria containing multifunctional degradable polymer nanocomposite for bone tissue regeneration
Experimental Investigation of Novel High Shear Injector at Elevated Pressure Conditions: Hydrodynamics, Spray and Combustion Characterization
No full textThe stringent pollution and emission norms due to the present climate change and global warming have pushed industries to meet these norms and cut down their emission levels. In the same pipeline, the aviation industries do not remain untouched. The emissions from aircraft engines burning fossil fuel, NOx, CO, unburnt hydrocarbon, etc., affect the atmosphere's upper layer temperature and air quality. These increasing number of air-transport demands and strict emission norms have forced the aviation industry to develop a next-generation aero-engine that can burn fossil fuel more efficiently and meet the emission norms.
Liquid fuel is a major power source for most power-generating units, such as land-based and air-based gas turbine combustors, rocket engines, industrial burners etc. The high energy density per unit volume for liquid fuel makes it a better candidate than gaseous fuel for an air-breathing engine/combustor. The extraction of power from the liquid fuel involves various stages such as fuel injection, its atomization in smaller droplets, oxidizer and fuel droplet mixing and then ignition of this fuel-oxidizer mixture.
The fuel injection process and technique are key to enhancing the gas turbine combustion performance and reducing the emission levels to meet the pollution norms in upcoming eras of aviation transport. However, optimization of the fuel injection system remains a key challenge, especially in liquid-powered gas turbine engines. Modern-day aircraft combustors utilize high shear fuel injectors that consist of multiple arrangements of swirlers along with a concentric fuel nozzle that generates coflowing swirling air to enhance atomization quality and get a homogeneous level of fuel-air reactant mixture prior to combustion.
The key observations of the current work are discussed in four parts. In the first part, we have designed, developed and characterized the performance of a new class of high shear injector (HSI). The benchmark to evaluate the performance of HSI are Spray flow field, Droplet size distribution, and droplet dispersion across a wide range of air-to-liquid mass ratios (ALR; 4-14). In the first part of the study, the influence of the injector’s geometrical features over the time-averaged and dynamical spray characteristics are examined using high fidelity laser-diagnostics technique (high-speed PIV). These features are swirl numbers (SN_Prim), airflow split-ratio(γ), area ratio(Δ), flare angle(θ) and relative flow orientation of primary and secondary swirlers (co and counter-rotation). A Simplex pressure-swirl fuel nozzle is mounted at the center of the injector to deliver the liquid. The non-dimensional length scales (radial; W/Df and axial; L/Df) are used to distinguish the test cases. W/Df and L/Df are governed by nearby swirl number SN5 for both counter and co-rotation swirl configuration. Here, SN5 is the experimental swirl number calculated 5mm from the exit. The length scales, W/Df and L/Df, are more sensitive to the split-ratio of primary and secondary swirlers, flare angle, and it’s mixing length. The spray droplet size and spatial uniformity are insensitive to the test variables. Further, dominant dynamic spatial modes changes with a change in W/Df of the recirculation zone and the oscillation frequency of the most dominating modes shifts to a lower value with increasing W/Df.
Simplex pressure-swirl fuel nozzle and dual orifice fuel nozzle are commonly used for fuel delivery at the center of the fuel injector/atomizer in the present-day gas turbine combustor. However, these fuel-nozzle have limitations such as hollow-cone liquid sheets collapsing at higher pressure, prone to plugging of narrow passages with contaminations over time, and high delivery pressure requirement.
The second part of the work addresses these issues by replacing the same with a discrete liquid-jet fuel nozzle with a simple orifice design and low injection pressure. The performance of a high shear injector with a discrete liquid – jet mounted at the center is evaluated and compared to the performance achieved with a high shear injector using a simplex pressure-swirl fuel nozzle. The comparison shows the potential of a discrete liquid -jet fuel nozzle to replace the simplex pressure-swirl fuel nozzle with the proper design of high shear injector. The injectors have excellent atomization capability along with superior azimuthal distribution of spray. The Sauter-Mean Diameters (SMD) across all the test cases are in the range of 9-30µm,15-37µm, 15-50µm and 23-75µm at ALR 14.1, 9.44, 7.08, and 4.72 respectively. Further, the Std. Deviation of azimuthal spatial uniformity in an azimuthal plane is below 6 percent of the mean.
A high shear injector consists of multiple swirler that produce swirl flow, and swirl flow is generally characterized by swirl number (SN). Above particular SN, the swirl flow creates a negative axial pressure gradient at the central axis which manifests a vortex breakdown bubble (VBB), also called the recirculation zone or central toroidal recirculation zone (CTRZ). The CTRZ help to stabilize the flame inside the gas turbine combustor. However, the onset of the vortex breakdown bubble is associated with a self-excited instability known as precessing vortex core oscillation. The PVC oscillation in a swirl flow-based combustor aids the thermoacoustic instability, resulting in severe hardware damage and poor emission characteristic of the engine.
The third part of the work addresses the suppression of PVC oscillation to avoid the thermoacoustic -instability by modifying the fuel nozzle mounted at the center of the injector. A dummy cylindrical post is attached to the fuel nozzle that acts as the centerbody. The work shows the intermittent or absolute suppression of PVC oscillation with proper design of centerbody and variation of flow Reynold number. The diameters of the centerbody considered are Dc = 7;9 and 11mm. The results further demonstrate the suppression of loud whistle-like acoustic sound with the suppression of PVC oscillations in the flow.
Considering the current global warming scenario and emission norms, the fourth part of the work addresses the soot formation study using Laser-induced Incandesce Imaging (LII) in a turbulent non-premixed ethylene swirl flame at a constant global equivalence ratio, ∅global=0.55 in a high shear injector. First, the impact of the split-ratio of primary and secondary swirler on soot formation is estimated at the given Reynolds number and pressure conditions for constant ∅global, which shows that a 60/40 swirl cup produces lower soot than a 40/60 swirl cup. Further, at constant pressure and ∅global=0.55, soot volume fraction reduces from ~4 ppm to ~0.8 ppm by increasing the Reynolds number from Re~5000 to Re~ 15000, and at Re ~20000, no soot is observed. At constant exit bulk velocity and constant ∅global=0.55, the soot volume fraction scales-up with pressure as p2.1 on log-log plots. Further, pressure increment increases the soot formation at a constant Re number. Overall, it is observed that pressure endorses soot formation. In addition, a large formation of soot particles is majorly observed in the annual jet’s region of the swirl flow field
Classical Approach to Understanding the Impact Dynamics of Hollow Droplets
No full textCompound droplets are utilized in applications ranging from the preparation of emulsion to
biological cell printing and additive manufacturing. Here, we report on the impact dynamics of
a compound hollow droplet on a solid substrate. Contrary to the impact of simple droplets and
compound droplets with liquids of similar densities, the compound droplet with an
encapsulated air bubble demonstrates the formation of a counterjet in addition to the lamella.
Here, we experimentally investigate the influence of the size of the air bubble, liquid viscosity,
and height of impact on the evolution of counterjet and the spreading characteristics of the
lamella. For a given hollow droplet, the volume of the counterjet is observed to depend on the
volume of air and liquid in the droplet and is independent of the viscosity of the liquid and
impact velocity of the droplet. We observe that the spread characteristics, counterintuitively,
do not vary significantly compared to that of a simple droplet having an identical liquid volume
as the hollow droplet. We propose a model to predict the maximum spread during the impact
of a hollow droplet on a substrate based on the energy interaction between the spreading liquid
and the liquid in the counterjet during the impact process. Furthermore, the maximum spread
diameter during the impact of a HD obtained using the model developed is in excellent
agreement with that observed in experiments
Direct Methods for Optimal Ascent Guidance
No full textAn ascent guidance algorithm determines the thrust vector that allows the spacecraft to
reach the desired orbit. Generally, optimal ascent guidance algorithms try to reach the
orbit while minimizing mission time or fuel. A renewed interest in new-generation space
missions necessitates the development of optimal ascent guidance algorithms that are
efficient in time and control and can accommodate ever-changing mission constraints.
These guidance algorithms will pave the way for future autonomous space exploration.
The first part of this thesis develops an ascent guidance algorithm that guides a
spacecraft from a known initial position to an orbit of known apogee and perigee in
minimum time. The algorithm follows an iterative approach that reduces the terminal
error over successive iterations while keeping the control inputs within bounds. Every
iteration consists of a model-predicting phase in which the initial conditions and system
dynamics are used to calculate the error at the end of guidance. It is followed by an
optimization phase that helps us to minimize time and accommodate path constraints.
Numerical simulations are carried out using a point mass model of a spacecraft. The
initial guess for control that is required for simulations is generated using an existing
polynomial guidance method. Next, we study the algorithm's behavior for different guess
inputs of the thrust and the final time. Further analysis is carried out by varying the
learning parameter and initial position of the spacecraft. Finally, we do a comparative
study of the algorithm with commercially available optimal control solvers. Simulation results show faster convergence of the proposed minimum-time algorithm compared to
other optimal control software.
Another essential and desirable characteristic of a guidance algorithm is lower control
effort spent in achieving the mission objective. In the second part of this thesis, we
augment the cost function of the algorithm with a weighted running cost on the control
effort. The weights of the running cost allow us to tune the algorithm to achieve a
balance between the mission time and the control effort invested in guidance. Numerical
simulations are carried out to analyze algorithm behavior for different initial conditions
and by steadily increasing the weight of the running cost. As the main result, we observe
that the control effort can be reduced signi ficantly with a correspondingly small trade-off
in mission time
An electromagnetically actuated mesoscale ball and socket joint for applications in 3-D metrology and electrical characterization
No full textMicro-robotics is concerned with development of robotic systems to manipulate micro-meter
sized objects. To develop functional micro-robotic manipulators, it is necessary to develop
joints that possess large motion range and move in a precise manner. This thesis is devoted
to the design, evaluation and applications of an active meso-scale ball and socket joint that
possesses these properties. The joint employs magnetic actuation for purposes of rotation of
the ball. Dither-based excitation is employed during rotation to eliminate the effect of static
friction. After rotation, the dither signal is switched off and the joint is firmly held in its new
orientation.
In the first part of the thesis, the design of the ball and socket joint would be described, followed
by its dynamic modelling. The dynamic model is developed by taking into consideration the
different magnetic and mechanical forces experienced by the ball. Subsequently, the overall
model is employed to perform simulations that validate the feasibility of the proposed actuation
strategy.
The second part of the thesis discusses the fabrication and evaluation of the joint. In particular,
the development of the joint and integration of a conductive tip to it would be first described.
Subsequently, the experimental setup and measurement strategy for characterization of the
ball’s rotation will be discussed. The experimental results demonstrate large rotation range, of
about 70◦, for the joint with negligible hysteresis and low cross-axis rotation of about 8%.
The third part of the thesis describes two applications of the developed ball and socket joint. In
the first application, the joint was employed to develop a probe for a Coordinate Measurement
Machine (CMM). The entire CMM system was also developed subsequently and employed for
performing 3-D metrology. In particular, the instrument has been demonstrated to simultaneously
access the vertical faces and the horizontal floor of a cuboidal corner and to reconstruct its geometry. In the second application, the electrically conductive nature of the tip of the CMM
probe has been demonstrated to enable it to detect conductive surfaces. These results showcase
the potential of the probe to be employed in 3-D Kelvin Probe Force Microscopy (KPFM)
Influence of surface topography on wear and debris morphology of polymers
No full textThe artificial knee and hip joints comprise a polymer-metal tribological system where soft polymers slide against hard metallic surfaces. When a polymer slides on it, the micro hard asperities remove the polymers in the form of debris. Numerous investigations discovered that the shapes and sizes of polymer debris have a major impact on the functionality and life of the artificial knee and hip joints.
The counter surface topography is one of the various parameters influencing debris morphology. Hence, researchers created various surface topographies on metallic surfaces and studied their influence on debris morphology. However, debris generation is a complex process. It depends on various interrelated processes such as deformation mechanisms, adhesion, transfer film formation and debris entrapment.
Friction is the source of stress, causing deformation and wear. Friction has two components: the ploughing component and the adhesion component. One or both components participate in the wear and debris generation. The researchers previously found a relationship between surface topography and the two components of friction. However, previous research is lacking or ambiguous in describing how the wear rate and debris morphology are linked with the counter surface topography.
Hence, this thesis tries to correlate surface topography and wear and debris morphology. The two friction components are used to explain the obtained correlation. The explanation may contribute to understanding the basic wear and debris generation mechanisms.
For the present study, various kinds of surface topography with varying roughness were created on SS316L steel plates. Wear experiments of various polymers with different physical and mechanical properties were performed against the prepared surface topographies. The wear rate was calculated from the LVDT data. The adhesion and ploughing components of friction were calculated from the friction data of the wear experiments under dry and lubricated conditions. The size and aspect ratio of the generated debris were measured using digital image analysis software. The underlying wear and debris generation mechanisms were analysed by examining the worn pin surface and the sliding tracks using a Scanning Electron Microscope. The major underlying mechanisms were ploughing, adhesion, plastic deformation, debris trapping, and debris rolling.
The experimental results show that the roughness does not affect the wear rate, debris size, or aspect ratio. However, surface topography significantly affects the wear rate, debris size, and debris aspect ratio. The results are explained by analysing the variation of adhesion and ploughing components with the surface topographies. The ploughing component finds to be varied with surface topography. However, the adhesion component finds to remain independent of the kinds of surface topography. The results conclude that the ploughing component of friction primarily dictates the wear rate with a proportional relationship. However, the adhesion component of friction primarily dictates the transfer film formation, debris entrapment and its rolling. This provides a reducing effect on effective wear.
The debris morphology results show that, in the absence of the adhesion, debris size has a proportional relationship with the ploughing component. The size of the debris has an inverse relationship with the ploughing component of friction when adhesion is present. The ploughing and adhesion together generate smaller debris than ploughing alone. The results also conclude that the aspect ratio of debris has a proportional relationship with the ploughing component of friction. However, the adhesion and ploughing together produce debris with a larger aspect ratio than ploughing alone produces
Towards Robust and Scalable Video Surveillance: Cross-modal and Domain Generalizable Person Re-identification
No full textWith rapid technological advances, one can easily find video surveillance systems deployed in public places such as malls, airports etc. as well as across private residential areas. These systems play a critical role in ensuring safety and security against criminal/anomalous activities. ‘Person Re-Identification’ (re-ID) is a key component of such a system and is well-studied in modern computer vision literature. The task of person re-ID is typically posed as an instance retrieval problem in a large wide-area network of cameras with non-overlapping field-of-views (FoV). When presented with an image of a person of interest (query) as observed in any given camera, the goal is to retrieve all image instances of the target with the same identity from all other cameras (gallery) in the network. Despite the extensive research in this area, there is still a gap between the efficacy of the existing re-ID frameworks under laboratory setting and their real-world deployability - thus necessitating the development of practical solutions for person re-ID. In this thesis, we explore two such research directions to build robust and scalable person re-ID models.
The first part of the thesis proposes a solution for the challenging and open problem of Visible-Thermal Person Re-ID (VT Re-ID). In this cross-modal retrieval problem, the query image of a target (in dark/low-light conditions) is captured using a thermal imaging camera and the re-ID system needs to search and retrieve observations corresponding to the same identity from the gallery set, which is composed of visible spectrum images of various targets captured using standard RGB cameras in well-lit environment. Such a system has major applications in night-time surveillance and enables round-the-clock monitoring of the places of interest. Existing cross-modal re-ID methods align the modalities via adversarial learning or complex feature extraction modules that heavily rely on domain knowledge. We propose a simple but effective framework, MMD-ReID, to explicitly reduce the modality gap. MMD-ReID takes inspiration from ‘Maximum Mean Discrepancy’ (MMD), a statistical tool that determines the distance between two distributions. Our method uses a novel margin-based formulation to match class-conditional feature distributions of the visible and thermal samples to minimize intra-class distances while maintaining feature discriminability across identities. Extensive experiments show that our method outperforms state-of-the-art approaches by significant margins.
The second part of the thesis attempts to solve a more challenging problem of Domain Generalization (DG) in person re-ID. Most existing re-ID models are trained and tested on the same dataset and perform poorly when evaluated on a new dataset (domain) without any explicit fine-tuning using annotated data samples from the latter. Recent multi-source DG methods use meta-learning approaches, which are prone to overfitting on the seen domains. To overcome this, we propose a novel strategy based on a supervised contrastive learning framework for learning domain-agnostic features. Our method attempts to model domain variations by creating hallucinated ‘positive’ samples that realistically mimic the perturbations one expects from domain-shift. We empirically show that by using our proposed pool of perturbation strategies, we are able to learn better generalizable features, thereby achieving state-of-the-art performance across unseen domains. We also hypothesize that training on a related, auxiliary task that is preserved across domains can help in learning robust features. With attribute prediction as the chosen auxiliary task, we experimentally show that such training indeed leads to a better generalization of the learnt model