DSpace@RPI (Rensselaer Polytechnic Institute)
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A study of the flow physics on a swept wing and the application of steady blowing to separation control
No full textAugust 2022School of EngineeringAn experimental study was conducted to understand the effect of steady blowing from segmented jets along the leading edge of a 30° swept wing with an aspect ratio of approximately 4, with a twist of approximately −2.5° between the root and the tip at a chord-based Reynolds number of 260, 000. The objective of the steady blowing is to control the separation that starts at the leading edge of the wing to increase the lift produced by the wing at higher angles of attack and delay the unstable pitch break experienced by the full SWiFT wing so that a higher stable maximum lift can be generated. Hot wire anemometry was used to calibrate the jets on the model. Pressure transducers were used to set the momentum coefficient of each jet. Loads were collected for a range of angles of attack. At select angles of attack, videos of tufts were recorded. At an angle of attack of 19°, stereo particle image velocimetry was performed. Without steady blowing, the wing experiences partial separation in the middle of the span at an angle of attack of approximately 17°, which extends to the tip of the wing at 19°. At 19° a horn-shaped vortex extending from the mid-span to the tip of the wing which merged with the wing tip vortex was observed. The lift curve slope agreed well with two predictions based on theory and on the vortex lattice method. Steady blowing reduces the extent of separation on the wing and delays separation of the flow over the entire wing to higher angles of attack. The steady blowing also moved the focus point (at which the horn vortex is originated from) observed in the near-surface streamlines and disrupted the formation of the horn vortex. Blowing from a single jet located outboard of mid-span reattaches the flow on the wing between the tip and the blowing location. Blowing from additional jets between the tip and this jet does not have a significant effect on the behavior of the flow, which indicates that a single jet acts as a fluidic fence which obstructs the spanwise flow that contributes to the separation at the tip. This effect is limited to jets closer to the tip because blowing from single jets closer to the root of the wing does not have the same effect. For both the case with three outer jets and with the single jet actuated, the horn vortex was present inboard of the blowing location, but was disrupted by the presence of the jet and did not travel all the way to the wingtip. Unlike the case with all of the jets actuated; however, the location of the focus did not move and the horn vortex began to form at the same location as observed on the baseline case.M
Neural modeling of efficient coding in primate mt and mstd
No full textDecember 2021School of Humanities, Arts, and Social SciencesI conducted two studies that explore the implications of the efficient coding hypothesis on neural mechanisms in primate MT and MSTd. The efficient coding hypothesis holds that neuronal populations, particularly those in perceptual areas, have sparse, hierarchical coding schemes that efficiently encode stimuli. In the first study, I introduced a self-tuning mechanism for capturing rapid adaptation to changing visual stimuli within a population of neurons. Model MT speed cell tuning curve parameters were continually updated to optimally encode a time-varying distribution of recently detected stimulus values. In two simulation experiments, I found this dynamic tuning yielded more accurate, lower latency heading estimates from downstream model MSTd cells compared to a static tuning. The second study investigated how simulated, complex stimuli affected model cell sensitivities derived via an efficient coding framework. Model cell sensitivities were derived using nonnegative matrix factorization (NMF) of an MT-like population coding of optic flow speed and direction. A previous study (Beyeler et al., 2016) found that basis vectors derived in this manner matched the results from neurophysiological studies of area MSTd in macaques. This prior work used simple, planar dot-environments which lacked a varied environmental structure and thus many visual features that affect the flow field generated by self-motion. I replicated portions of this prior work, then used the same methods and analyses to generate and evaluate the results for alternative stimuli from more naturalistic settings with higher spatial resolution. I found that model units derived with NMF used a coding schema similar to that found in primate MSTd, confirming the original result with more complex stimuli.Ph
Dielectric conduction mechanisms pre- and post- intrinsic breakdown
No full textMay 2021School of EngineeringDielectric breakdown is the phenomenon where an insulator degrades and its leakage current increases significantly. A lightning strike between the cloud and ground is the most common example of a dielectric breakdown event. The time-dependent dielectric breakdown (TDDB) occurring at the interconnect level in an integrated circuit has become an increasingly serious reliability issue as devices get smaller. Numerous closed-form lifetime acceleration models have been proposed to extrapolate the lifetime measurements obtained under high temperature and high-field testing conditions to the lifetime under working conditions. A charge transport model was developed to simulate and achieve a better understanding of TDDB. The charge transport model (CT model) is a one-dimensional dynamic model, that consists of a set of non-linear partial differential equations (PDEs) which replicate electronic conduction through the dielectric. The dielectric breakdown phenomenon, however, is not necessarily a reliability issue. It has positive effects and can be exploited for device operation. Resistive random access memory (ReRAM) is one example of devices that exploit breakdown phenomena. In this study, the aforementioned CT model is modified and extended to also simulate the post-breakdown region. A linear post-breakdown region appears automatically following the abrupt change in current under a ramped voltage stress. The breakdown event has a strong correlation with percolation theory. Intrinsic dielectric breakdown is driven by defects (traps) in the material and occurs only when the local trap concentration reaches a percolation threshold. The percolation threshold is found to be 0.03 for the studied system. The completion of the percolation path indicates the first breakdown event often called the soft breakdown point. The occurrence of hard breakdown, or final failure, is attributed to the saturation in the number of intrinsically generated defects in the dielectric material. The saturation value for each dielectric system can be obtained from the fitting parameters extracted from the CT model. The industrial definition of the time-to-failure (TTF) may result in a premature breakdown especially when a high constant voltage stress is applied. The dynamic process underlying formation of the percolation path is visualized by the trap distribution evolution in the model. The percolation path always originates near the anode and terminates near the cathode, though the trap distribution evolution varies with the stressing methods. The weakest link during the percolation path formation and also the most possible location of the filament rupture during the RESET process for ReRAM devices is found to be the cathode/dielectric interface when a ramped voltage stress or a high constant voltage is applied; however, under a low constant voltage stress, the weakest link migrates from the center of the dielectric to the cathode/dielectric interface upon the formation of the conductive pathway. A relationship between the abruptness of the current increase at the failure point and the unevenness of the trap distribution when the percolation path starts forming is found, which will be verified with future plans including pre-implantation of traps near the anode or increasing the ramp rate during the forming process. A less abrupt current increase during the forming or SET process is favored by 3D crossbar structures and by multilevel cell ReRAM devices. The percolation path formation can be manually controlled by switching offthe trap generation in the CT model. A transition from an insulator region to a metallic-like region is observed based on the temperature dependence simulation results with the controlled breakdown. The post-breakdown conductance is found to be linearly dependent on the current limit, the current level when the trap generation is stopped, which agrees with the experimental results on multi-level cell ReRAM devices where the SET state conductivity has a linear relationship with the preset current compliance. To precisely describe how electrons move through the percolation path, trap-trap tunneling is proposed and these electrons are treated exactly the same as drifting in the CT model. A Superlattice model and a Nasyrov-Gritsenko (N-G) model are discussed and compared as alternative mechanisms. The Superlattice model is able to predict a linear I-V characteristic only with an unrealistic Fermi level at the cathode. The N-G model was adapted for the trap-trap tunneling current calculation with a formed percolation path by the CT model and the post-breakdown linear I-V characteristic can be realized. However, the weak temperature dependence of the post-breakdown region can be only realized when the optical excitation energy is preset really close to the trap depth from the conduction band. Future work on the temperature dependence of the post- intrinsic hard breakdown and also on the possibility and requirement for the optical excitation energy to be abnormally small may help decide whether N-G model should be adapted.Ph
Metal ion adsorption using silk fibroin-coated polypropylene filters
No full textMay 2022School of EngineeringHeavy metals from industrial manufacturing wastewater can contaminate ground and surface water sources. Current wastewater treatment methods to remove these metals involve liquid separation processes which are energy intensive and expensive. Removal of these heavy metals though adsorption processes provides an alternative processing method which is less labor and energy intensive. In this thesis, adsorption of Cu (II) and Zn (II) metal ions were investigated using silk fibroin-coated nonwoven polypropylene filters. As a strong biopolymer that can be utilized as a coating for any substrate, silk fibroin contains electron-rich functional groups that serve as potential active sites for metal cation adsorption. Batch adsorption studies were conducted for the initial metal ion concentration and time effects on adsorption for a metal ion concentration range of 200-2400 ppm in aqueous solution. Filter adsorption followed a Langmuir model, with uncoated filter adsorption capacities changing from 67.5 to 50.8 mg/g and 66.8 to 83.5 mg/g for silk fibroin coated filters with Cu (II) and Zn (II) adsorption, respectively. Silk-coated filters exhibit an adsorption efficiency below 10% for copper and zinc, suggesting this silk fibroin coating requires further functionalization to remove metals down to the ppb range concentration required for wastewater discharge into the environment.M
Taxonomy generation to insert out of vocabulary terms and hypernym-hyponym pair induction
No full textAn approach to induction of unknown terms into a term taxonomy graph may be provided. The approach may include analyzing a domain specific corpus to generate a term taxonomy graph using a term taxonomy graph generation model with a term knowledge base and determining which terms within the domain specific corpus are out of vocabulary (OOV) terms. The approach may also analyze the terms in the domain specific corpus with a semantic representation model to generate feature vectors of the OOV terms and terms known within the generated term taxonomy graph. The approach may determine if an OOV can be a hyponym of a term within the term taxonomy graph based on the feature vectors and insert the OOV term into the graph at the appropriate location
Characterization of glycan-protein interactions in SARS-CoV-2 and Parkinson's disease
No full textAugust 2022School of ScienceABSTRACT. Heparan sulfate (HS) acts as a co-receptor of angiotensin-converting enzyme 2 (ACE2) by interacting with severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) spike glycoprotein (SGP), facilitating host cell entry of SARS-CoV-2 virus. Heparin, a highly sulfated version of heparan sulfate (HS), interacts with a variety of proteins playing key roles in many physiological and pathological processes. In this study, SARS-CoV-2 SGP receptor binding domain (RBD) of wild type (WT), Delta and Omicron variants were expressed in Expi293F cells and used in the kinetic and structural analysis on their interactions with heparin. Surface plasmon resonance (SPR) analysis showed the binding kinetics of SGP RBD from WT and Delta variants were very similar while Omicron variant SGP showed a much higher association rate. The SGP from Delta and Omicron showed higher affinity (KD) to heparin than the WT SGP. Competition SPR studies using heparin oligosaccharides indicated that optimal binding of SGP RBDs to heparin requires chain length greater than 18. Chemically modified heparin derivatives all showed reduced interactions in competition assays suggesting that all the sulfo groups in the heparin polysaccharide were critical for binding SGP RBDs with heparin. These interactions with heparin are pH sensitive. Acidic pH (pH 6.5, 5.5, 4.5) greatly increased the binding of WT and Delta SGP RBDs to heparin, while acidic pH only slightly reduced the binding of Omicron SGP RBD to heparin compared to binding at pH 7.3. In contrast, basic pH (pH 8.5) greatly reduced the binding of Omicron SGP RBDs to heparin, with much less effects on WT or Delta. The pH dependence indicates different charged residues were present at the Omicron SGP-heparin interface. Detailed kinetic and structural analysis of the interactions of SARS-CoV-2 SGP RBDs with heparin provides important information for designing anti-SARS-CoV-2 molecules.Heparan sulfate on neuronal surface also plays important roles in the prion-like spread of -synuclein (aS) pathology in Parkinson’s disease (PD). Using similar SPR methods employed in heparin-SPG studies, we show that aS binds heparin with 0.4 M affinity, and that N-sulfation is the most important sulfation pattern for heparin-aS interaction. In addition, glycan chain length plays a crucial role in heparin-aS interaction, with a minimal chain length of 16 saccharide units required for optimal interaction. NMR has been used to characterize the binding sites in aS. Based on chemical shift perturbation and peak intensity change, C-terminal acidic tail is minimally involved while the non amyloid component (NAC) domain is the most important region for heparin binding. K81, K59 and K61, within the imperfect KTKEGV repeats, likely provide the crucial positive charges for interaction with heparin. Detailed SPR and NMR provide novel insights towards molecular mechanisms and therapeutic intervention of PD.Ph
Modeling interfaces in polymer nanodielectrics
No full textDecember 2021School of EngineeringAb initio design of polymer nanocomposite materials for high breakdown strength requires prediction of trap states at the polymer–filler interface. Systematic first-principles calculations of realistic interfaces can be challenging, particularly for amorphous polymers and fillers that necessitate the calculation of ensembles of large unit cells with hundreds of atoms. We present a computational approach for automatically generating reasonable structures for amorphous polymer–filler interfaces, combining classical molecular dynamics and Monte Carlo simulations. We identify trap states by analyzing the localization of electronic eigenstates calculated using density functional theory on ensembles of interface structures, clearly distinguishing shallow trap states from delocalized band-edge states. Nanofillers in polymer nanocomposites are functionalized to improve dielectric performance in both direct and indirect ways. For comprehensive design of polymer nanodielectrics, we include coupling agents with functional groups to our automated scheme of generating interface structure. In our initial study, we create ensembles of interfaces with three functional groups - thiophene, terthiophene, ferrocene. Analyzing their eigenstates reveals distinct distribution of hole and electron traps in energy and space dimension dictated by the chemistry of functional groups. Apart from interface engineering, dispersion of nanofillers is an important factor in determining dielectric breakdown strength. Since simulating dielectric breakdown is challenging, we calculate electron mobility and calibrate experimentally measured dielectric breakdown strength. We use trap state information from either experiments to develop a Monte Carlo electron hopping model to simulate electron trajectories through a microstructure under a given electric field. We find a logarithmic relation between electron mobility and dielectric breakdown strength. A combination of ab initio, classical molecular dynamics and Monte Carlo methods applied in investigating amorphous interfaces of polymer nanodielectrics can be extended to other areas too. Understanding electrochemical interfaces is an equally-complex problem.Controlling electrochemical reactivity requires a detailed understanding of the charging behavior and thermodynamics of the electrochemical interface. Experiments can independently probe the overall charge response of the electrochemical double layer by capacitance measurements, and the thermodynamics of the inner layer with potential of maximum entropy (PME) measurements. Relating these properties by computational modeling of the electrochemical interface has so far been challenging due to the low accuracy of classical molecular dynamics (MD) for capacitance and the limited time and length scales of \emph{ab initio} MD (AIMD). Here, we combine large ensembles of long-time-scale classical MD simulations with charge response from electronic DFT to predict the potential-dependent capacitance of a family of ideal aqueous electrochemical interfaces with different peak capacitances. We calculate two charge-based benchmarks which indicate an asymmetric response of interfacial water that is stronger for negatively charged electrodes, while the difference between CME and CMC illustrates the richness in behavior of even the ideal electrochemical interface.Ph
Hemp decortication by a mastication process
No full textAugust 2019School of EngineeringThe goal of this Master’s Thesis research was to design, fabricate and test a mechanical decortication system for unretted bast fiber plant stalks with a particular focus on hemp. To preserve hemp fiber quality and maximize the hurd removal, a new decortication concept based on the teeth structure and chewing process (mastication) of herbivores (e.g., elephant) has been designed and developed as an improvement of current methods. With this new concept, a set of tools crushes hemp stalks under control conditions to induce effective fiber/hurd detachment during crushing cycles. Compression tests were performed to investigate the deformation behavior and corresponding acoustic response of hemp stalks during mastication. An apparatus was designed, fabricated and tested to run experiments that demonstrate the process and assess parameter sensitivities. Finally, the effect of process parameters on decortication quality was investigated, and parameter combinations that yielded the best result were identified.M
Building and Analyzing the Brazilian Legal Knowledge Graph
No full textArtificial Intelligence has proven to be effective in streamlining processes in several domains. The Brazilian judiciary, specifically, has a very large number of cases, above the work capacity of the courts, generating urgency in the creation of methods that mainly support the access and manipulation of unstructured data. This paper presents the construction of a Knowledge Graph of the Brazilian Legislation using Semantic Web standards that allows an understanding of how Brazilian laws interact with each other. The Knowledge Graph was quantitatively evaluated using complex network analysis and it was found to be useful to support experts in understanding the Brazilian legislation by detecting special nodes, namely the “bridge-like nodes”, that play an important role in the structure of the graph
Formal verification of decentralized coordination in autonomous multi-agent aerospace systems
No full textMay 2022School of ScienceAs autonomous vehicular technologies such as self-driving cars and uncrewed aircraft systems (UAS) evolve to become more accessible and cost-efficient, autonomous multi-agentsystems, that comprise of such entities, will become ubiquitous in the near future. The close
operational proximity between such autonomous agents will warrant the need for multi-agent
coordination to ensure safe operations. In this thesis, we adopt a formal methods-based approach to investigate multi-agent coordination for safety-critical autonomous multi-agent
systems. We explore algorithms that can be used for decentralized multi-agent coordination among autonomous mobile agents by communicating over asynchronous vehicle-to-vehicle (V2V) networks that can be prone to agent failures. In particular, we study two
types of distributed algorithms that are useful for decentralized coordination — consensus, which can be used by autonomous agents to agree on a set of compatible operations;
and knowledge propagation, which can be used to ensure sufficient situational awareness
in autonomous multi-agent systems. We develop the first machine-checked proof of eventual progress for the Synod consensus algorithm, that does not assume a unique leader. To
consider agent failures while reasoning about progress, we introduce a novel Failure-Aware
Actor Model (FAM). We then propose a formally verified Two-Phase Acknowledge Protocol (TAP) for knowledge propagation that can establish a safe state of knowledge suitable for
autonomous vehicular operations. The non-deterministic and dynamic operating conditions
of distributed algorithms deployed over asynchronous V2V networks make it challenging to
provide appropriate formal guarantees for the algorithms. To address this, we introduce probabilistic correctness properties that can be developed by stochastically modeling the systems.
We present a formal proof library that can be used for reasoning about probabilistic properties of distributed algorithms deployed over V2V networks. We also propose a Dynamic
Data-Driven Applications Systems (DDDAS)-based approach for the runtime verification of
distributed algorithms. This approach uses parameterized proofs, which can be instantiated
at runtime, and progress envelopes, which can divide the operational state space into distinct regions where a proof of progress may or may not hold. To motivate our verification
of decentralized coordination, we introduce an autonomous air traffic management (ATM)
technique for multi-aircraft systems called Decentralized Admission Control (DAC).Ph