21 research outputs found
Cybersecurity in Smart Grids: Threats and Defence Mechanism
No full textThe increasing integration of digital technologies in modern smart grids has significantly improved the efficiency, reliability, and automation of energy distribution. However, this transformation has also introduced critical cybersecurity risks, making smart grids vulnerable to cyber threats such as malware attacks, Distributed Denial of Service (DDoS), and intrusion attempts. Traditional security mechanisms, while effective in conventional IT systems, struggle to protect smart grids due to their complex interconnection of operational technology (OT) and IT systems.
This thesis looks at cybersecurity challenges in smart grids by analyzing vulnerabilities in smartmeters, Supervisory Control and Data Acquisition (SCADA) systems, and communication networks. A detailed review of existing security approaches, including encryption, authentication protocols, anomaly detection, and intrusion detection systems, highlights their limitations in securing smart grid infrastructure.
To address these challenges, this research proposes a cybersecurity framework that combines three defense mechanisms:
(1) Digital Immune System – An AI-driven anomaly detection system that continuously learns from grid data to identify and neutralize threats in real time.
(2) Genetic Algorithms for Cyber Defense – A self-optimizing security mechanism that evolves security configurations to improve grid resilience.
(3) Decentralized AI Collectives – A distributed defense system where multiple AI agents collaborate to detect and mitigate cyberattacks without reliance on a central authority.
This integrated defense mechanism ensures real-time threat detection, automated response, and adaptive security evolution. The proposed approach is validated through simulations, demonstrating its effectiveness in mitigating cyber threats and improving the overall security of smart grid systems.
This research contributes to the field of enterprise and IT security by presenting a comprehensive, adaptive, and scalable cybersecurity solution tailored for smart grids
Learning, inference, and control for construction robots and spatiotemporal processes
No full textExpert operators of real world robots, especially constructions robots, develop expertise from years of training and experience. In the absence of such experts, these robots are operated by novice operators, and this adversely affects the productivity. On the other hand, safety concerns and the nature of the operating environment limits the possibility of automating these robots. This thesis proposes a solution by considering a problem setting in which the robot learns a policy from experts to train novice human operators. Formally, this is posed as the problem of learning instructional policy from demonstration, that maps the state of the robot to an instruction for a human operator. Existing methods learn policy from demonstration, however such policies do not relate to the human operator's action space and hence cannot be used to generate instructions for novice operators. We introduce action primitives that address this challenge of mapping continuous state action trajectories to human parse-able and executable instructions.
Construction tasks are complex as they consist of several subtasks with stochastic transitions. For such tasks, existing approaches learn policy for component subtask and then rely either on predefined decomposition or heuristics to generate policy for the entire task. To overcome this limitation, and to generate instructions for an entire construction task, this thesis proposes learning of a structured probabilistic model for instructional policy. This model utilizes hierarchy of Markov chains that incrementally captures the number of subtasks as well as their transitions. Switching between the subtasks is inferred using a likelihood rate based inference approach proposed in this thesis. Instructional policy model is tested based on a controlled group study involving 113 participants, who learn to perform the truck loading task on a hydraulic actuated scaled excavator robot.
Further this thesis investigates shared control design for construction robots. Existing work has established that shared control can improve cycle times in nominal conditions. However, these methods can be too slow to relinquish control in off-nominal cases, when the operator needs to deviate from the nominally optimal trajectory due to unforeseen obstacles or other uncertainties. With an objective to incorporate such capability, this thesis proposes a new shared control technique that utilizes the operator's intent to quickly relinquish control in off-nominal conditions. Theoretical results with performance guarantees and improved obstacle reaction time are presented. Proposed design has been experimentally validated on Zermelo's navigation problem. The last part of the thesis introduces kernel observer for learning and inference of large-scale stochastic phenomena with both spatial and temporal (spatiotemporal) evolution. This work considers the problem of estimating the latent state of a spatiotemporally evolving continuous function using very few sensor measurements. The model consists of a dynamical systems prior over temporal evolution of weights of a kernel model. Theoretical results provide sufficient conditions on the number and spatial location of sensors required to guarantee state recovery. A lower bound on the minimum number of sensors required to robustly infer the hidden states is also derived. Finally, theoretical results for randomly selecting sensing or sampling locations based on the predictive kernel observer model are presented. Our approach outperforms state-of-the-art kernel based machine learning methods in numerical experiments on real world datasets.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2020-08-01The student, Harshal Maske, accepted the attached license on 2018-06-14 at 15:57.The student, Harshal Maske, submitted this Dissertation for approval on 2018-06-14 at 16:13.This Dissertation was approved for publication on 2018-06-15 at 09:37.DSpace SAF Submission Ingestion Package generated from Vireo submission #12631 on 2018-09-27 at 11:15:58Made available in DSpace on 2018-09-27T16:30:12Z (GMT). No. of bitstreams: 3
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Previous issue date: 2018-06-15Embargo set by: Seth Robbins for item 107749
Lift date: 2020-09-27T16:30:34Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 107749
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Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 107749
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Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Only Restriction Lifted for Item 107749 on 2020-09-28T09:15:22Z
Modelling and Finite Element Simulation of a Surface Acoustic Wave Driven Linear Motor
No full textAbstractThe paper presents modeling and finite element simulation of a surface acoustic wave (SAW) linear motor. A SAW linear motor works on the principle of friction drive provided by SAW propagating on a piezoelectric stator. The SAW motor comprises of a cubical slider driven by Rayleigh wave generated on a piezoelectric substrate using an interdigital transducer (IDT) fabricated on the stator. In the study, a lithium niobate piezoelectric substrate is used as the stator on which aluminum IDTs are fabricated at the two edges and a cuboid slider is placed in the path of SAW propagation along with a preload. The characteristics such as displacement, velocity and forces acting on the slider for different amplitudes of wave excitations are studied. The slider in the SAW motor can move both in forward and reverse directions and the motor attains a saturated velocity with the continuous wave excitation
Simulation of Longitudinal Mode of Vibration in Piezoelectric Monolayer MoS2
No full textAbstractMonolayer molybdenum disulphide (MoS2) is one of the desired materials for the new age piezoelectric devices. The main objective of the paper is to present the finite element (FE) simulation of piezoelectric monolayer MoS2 in COMSOL Multiphysics software. A rectangular MoS2 sheet is simulated in fixed-fixed end and free-free end configuration. The eigenmode analysis is done and the eigen frequency is calculated. Due to the presence of one molecular layer and piezoelectric matrix the vibration should be in longitudinal mode. The longitudinal acoustic velocity is also calculated from the simulation and is verified analytically
Modeling and Simulation of a Piezoelectric Vibration Energy Harvester
No full textAbstractThe paper presents a lumped parameter model of a vibration energy harvester consisting of a bimorph piezoelectric cantilever with end mass. Stress on the piezoelectric material which is primarily accountable for the generation of electrical energy in the harvester is obtained along the beam length in terms of the end mass displacement. The model is applicable for parallel as well as series connection of the piezoelectric layers, and used to obtain resonant frequency, displacement of end mass and generated voltage across resistive load. Effect of load resistance on the resonant frequency and generated power is studied, and the results are verified with the finite element analysis in COMSOL Multiphysics
Design and Development of Membrane Electrode Assembly for Proton Exchange Membrane Fuel Cell
No full textabstract: This work aimed to characterize and optimize the variables that influence the Gas Diffusion Layer (GDL) preparation using design of experiment (DOE) approach. In the process of GDL preparation, the quantity of carbon support and Teflon were found to have significant influence on the Proton Exchange Membrane Fuel Cell (PEMFC). Characterization methods like surface roughness, wetting characteristics, microstructure surface morphology, pore size distribution, thermal conductivity of GDLs were examined using laser interferometer, Goniometer, SEM, porosimetry and thermal conductivity analyzer respectively. The GDLs were evaluated in single cell PEMFC under various operating conditions of temperature and relative humidity (RH) using air as oxidant. Electrodes were prepared with different PUREBLACK® and poly-tetrafluoroethylene (PTFE) content in the diffusion layer and maintaining catalytic layer with a Pt-loading (0.4 mg cm-2). In the study, a 73.16 wt.% level of PB and 34 wt.% level of PTFE was the optimal compositions for GDL at 70 °C for 70% RH under air atmosphere.
For most electrochemical processes the oxygen reduction is very vita reaction. Pt loading in the electrocatalyst contributes towards the total cost of electrochemical devices. Reducing the Pt loading in electrocatalysts with high efficiency is important for the development of fuel cell technologies. To this end, this thesis work reports the approach to lower down the Pt loading in electrocatalyst based on N-doped carbon nanotubes derived from Zeolitic Imidazolate Frameworks (ZIF-67) for oxygen reduction. This electrocatalyst perform with higher electrocatalytic activity and stability for oxygen reduction in fuel cell testing. The electrochemical properties are mainly due to the synergistic effect from N-doped carbon nanotubes derived from ZIF and Pt loading. The strategy with low Pt loading forecasts in emerging highly active and less expensive electrocatalysts in electrochemical energy devices.
This thesis focuses on: (i) methods to obtain greater power density by optimizing content of wet-proofing agent (PTFE) and fine-grained, hydrophobic, microporous layer (MPL); (ii) modeling full factorial analysis of PEMFC for evaluation with experimental results and predicting further improvements in performance; (iii) methods to obtain high levels of performance with low Pt loading electrodes based on N-doped carbon nanotubes derived from ZIF-67 and Pt.Dissertation/ThesisMasters Thesis Mechanical Engineering 201
DICLOFENAC INDUCED ANGIOEDEMA: A CASE REPORT
No full text Non-steroidal anti-inflammatory drugs (NSAIDs) are one of the most commonly prescribed groups of drugs for variety of indications. However, theyare associated with many potential adverse drug reactions. The detailed information of these reactions is necessary to decrease the morbidity andmortality associated with these reactions. Angioedema can be caused by many etiological factors including drugs. The NSAID induced angioedemaoccurs infrequently but sometimes it may prove fatal if not treated promptly. The angioedema due to NSAIDs use may be caused due to increase inproduction of Leukotriene due block in cyclooxygenase pathway. The mast cells and to lesser extent basophils plays a major role in pathogenesis ofangioedema. Early recognition and discontinuation of responsible NSAIDs should be done. Treatment with corticosteroids and antihistaminic is usefulin management of angioedema. The author reports a case of a patient with angioedema in association with use of Diclofenac.Keywords: Angioedema, Diclofenac, Non-steroidal anti-inflammatory drugs, Leukotrienes
HIGH RESOLUTION MICROWAVE SPECTROSCOPY OF THE ALLENE DERIVATIVES HCHCH, HCHCH, AND HCHCN
No full textAuthor Institution: Division of Engineering and Applied Sciences, Harvard; University, Cambridge, Massachusetts 02138 and Institute for; Theoretical Chemistry, Department of Chemistry and Biochemistry, The; University of Texas at Austin, Austin, Texas 78712; Harvard-Smithsonian Center for Astrophysics, Cambridge,; Massachusetts 02138 and Division of Engineering and Applied; Sciences, Harvard University, Cambridge, Massachusetts 02138Molecules of the form HCH--R (where R is a carbon chain) are of astrophysical interest in light of the recent centimeter-wave band detection of cyanoallene (HCHCN) towards TMC-1}, \underline{\textbf{637}}: L37-L40, (2006).}. The carbon chain molecules HCHCH, HCHCH, and HCHCN have been investigated between 5 and 41 GHz by Fourier transform microwave spectroscopy of a supersonic molecular beam. Accurate rotational and centrifugal distortion constants have been derived for all three molecules from their {\it a}- and {\it b}-type transitions, and owing to the high spectral resolution of this technique, nitrogen hyperfine structure has been resolved for HCHCN. Several C isotopic species have now been observed in natural abundance, suggesting that accurate determinations of experimental structures may be feasible. Because these molecules are structurally similar to known astronomical molecules and possess large dipole moments, they are good candidates for astronomical detection
ROTATIONAL SPECTROSCOPY OF HDO
No full textAuthor Institution: Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109The recent detection of HDO in Orion KL nderline{\textbf{521}}, (L20), 2010.} by the \emph{Herschel Space Observatory} provided a strong motivation to revisit the rotational spectrum in order to obtain more accurate calculations of transition frequencies. Rotational ransitions were recorded in the ~GHz frequency range. Analysis of the combined microwave and infrared data sets with an Euler series Hamiltonian nderline{\textbf{233}} (174), 2005.} has facilitated determination of a set of precise rotational constants to support precision velocity measurements. The new rotational data also provides a means of evaluating the performance of the MARVEL algorithm used in the recent review of all available HDO data nderline{\textbf{111}}(2160), 2010.}
