- Mechanical and Optical Resonators
- Advanced MEMS and NEMS Technologies
- Force Microscopy Techniques and Applications
- Neural Networks and Applications
- Fault Detection and Control Systems
- Model Reduction and Neural Networks
- COVID-19 epidemiological studies
- Energy Load and Power Forecasting
- Acoustic Wave Resonator Technologies
- Fluid Dynamics Simulations and Interactions
- Ship Hydrodynamics and Maneuverability
- Mathematical and Theoretical Epidemiology and Ecology Models
- Probabilistic and Robust Engineering Design
- SARS-CoV-2 and COVID-19 Research
- Engineering Diagnostics and Reliability
- Advanced Measurement and Detection Methods
- Quantum chaos and dynamical systems
- Control and Dynamics of Mobile Robots
- Gear and Bearing Dynamics Analysis
- Hydraulic and Pneumatic Systems
- Evolution and Genetic Dynamics
- Control Systems and Identification
- Advanced Sensor and Control Systems
- Machine Fault Diagnosis Techniques
- Magnetic Bearings and Levitation Dynamics
Villanova University
2022-2024
Dynamic Systems (United States)
2022-2024
Technion – Israel Institute of Technology
2019
Indian Institute of Technology Hyderabad
2014-2016
Accurate models are essential for design, performance prediction, control, and diagnostics in complex engineering systems. Physics-based excel during the design phase but often become outdated system deployment due to changing operational conditions, unknown interactions, excitations, parametric drift. While data-based can capture current state of systems, they face significant challenges, including excessive data dependence, limited generalizability inability predict dependence. This has...
Understanding the coupling of different modal frequencies and their tuning mechanisms has become essential to design multi-frequency MEMS devices. In this work, we fabricate a beam with fixed boundaries separated from two side electrodes bottom electrode. Subsequently, perform experiments obtain frequency variation in-plane out-of-plane mechanical modes microbeam respect both DC bias laser heating. We show that coincide at certain bias, which in turn can also be varied due temperature....
An accurate computation of electrical force is significant in analyzing the performance microelectromechanical systems and nanoelectromechanical systems. Many analytical empirical models are available for computing forces, especially, a single set parallel plates. In general, these forces computed based on direct electric field between overlapping areas plates fringing effects. Most models, which effect, consider only trivial cases this paper, we propose different obtained from numerical...
Microelectromechanical system (MEMS) and Nanoelectromechanical (NEMS) are mostly actuated by direct forcing due to electrostatic excitation. In general, the consists of two main components, first is which based on parallel plate capacitance another fringing effects. As size beam its cross section reduces from microscale nanoscale, effect diminishes because overlapping area also reduces. Consequently, force remains only viable factor excite beams electrostatically. this paper, we present...
Microelectromechanical system (MEMS) based arrays have been employed to increase the bandwidth and sensitivity of many sensors actuators. In this paper, we present an approximate model demonstrate tuning in-plane out-of-plane frequencies MEMS consisting fixed–fixed beams. Subsequently, apply Galerkin's method with single mode obtain reduced-order static dynamic equations. Corresponding a given direct current (DC) voltage, first solve equations then corresponding from equation for beam...
Abstract This study concerns hybrid modeling of a multidimensional coupled nonlinear system. The underlying basis for the model is derived from Hamiltonian mechanics capitalizing on broad utility and efficiency energy-based reasoning in high-dimensional systems. essentially an artificial neural network with computational graph that modified conventional networks few significant ways. first modification includes incorporating intermediate scalar function representing learned data. second...
Abstract This study concerns hybrid modeling of a multidimensional coupled nonlinear system. The underlying basis for the model is derived from Hamiltonian mechanics capitalizing on broad utility and efficiency energy-based reasoning in high-dimensional systems. essentially an artificial neural network with computational graph that modified conventional networks few significant ways. first modification includes incorporating intermediate scalar function representing learned data. second...
In this paper, we develop a fault identification approach for electro-hydraulic servo actuators based on injecting pre-defined diagnostic signal into the system and then extracting fault-related features from phase space topology. Next, build regression models using an artificial neural network, which maps feature to identify faults represented by system’s parameters. The performance of proposed is evaluated when degradation permanent armature occurs. effect parametric dynamics studied...
We propose simple approximate expressions for capacitance and electrostatic force fixed-fixed beam-based MEMS/NEMS devices subjected to direct fringing field effects. The configuration that are considered study beam bottom electrode, side a combination of beam, electrode electrode. evaluated based on the numerical result obtained using FEA analysis in COMSOL software. accuracy proposed formulae is compared with available literature. this paper valid wide operating range they can also be used...
With the rapid advancement of industrial systems and unavoidable complications interconnectedness in systems, diagnostics machinery are achieving paramount importance. Accurate estimation health condition becomes more challenging due to inherent nonlinearity, complexity, uncertainty observations. Nonlinear dynamic analysis has proven be a powerful tool for providing information about system that can used diagnostic applications. The current study particularly focuses on crack depth using...
Abstract This paper is concerned with nonlinear modeling and analysis of the COVID-19 pandemic. We are especially interested in two current topics: effect vaccination universally observed oscillations infections. use a Susceptible, Infected, & Immune model incorporating dynamic transmission rate policy. The US data provides starting point for analyzing stability, bifurcations dynamics general. Further parametric reveals saddle-node bifurcation under imperfect leading to occurrence...
Abstract The dynamics of surface vehicles such as boats and ships, when modeled a rigid body, is complex it strongly nonlinear involves six degrees freedom. We are particularly interested in the steering decoupled from pitching rolling basis our research on unmanned autonomy. Steering has been traditionally using linear Nomoto model, which however does poor job capturing real phenomena. On other hand, there exists somewhat simplified three degree freedom model derived by Abkowitz, which,...

 The current study concerns diagnostics of a one-stage gear- box based on the integration physics and machine learn- ing. A physics-based model this system is developed, then nonlinear dynamic analysis performed. accuracy validated by comparing fundamental phenomena observed in synthetic experimental data. To address problem data are generated for faulty healthy conditions. Further, physics-informed features extracted from phase space system. It shown that these highly informative...