A Generalized Polynomial Chaos-Based Approach to Analyze the Impacts of Process Deviations on MEMS Beams [PDF]
Sensors, 2017 A microstructure beam is one of the fundamental elements in MEMS devices like cantilever sensors, RF/optical switches, varactors, resonators, etc.
Lili Gao, Zai-Fa Zhou, Qing-An Huang
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Full-cycle prediction of crack healing in self-healing concrete using generalized polynomial chaos expansion [PDF]
Communications EngineeringThe crack healing capacity of self-healing concrete is crucial for enhancing structural durability, especially in aggressive environments where the dynamic progression of healing depth directly influences service life.
Changhao Fu +6 more
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Generalized Polynomial Chaos Expansion for Fast and Accurate Uncertainty Quantification in Geomechanical Modelling [PDF]
Algorithms, 2020 Geomechanical modelling of the processes associated to the exploitation of subsurface resources, such as land subsidence or triggered/induced seismicity, is a common practice of major interest.
Claudia Zoccarato +3 more
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Modeling of fractional order DPG model insight global warming and pollution effect on desertification for control mechanism [PDF]
Scientific ReportsThis study presents a novel fractional-order mathematical model that investigates the dynamic interplay between dust pollutants, plant biomass, and global warming, referred to as the DPG system.
Muhammad Farman +6 more
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Results in Physics, 2023 The paper mainly studies the traveling wave solutions, phase portrait and chaotic pattern of the generalized fractional stochastic Schrödinger equations forced by multiplicative Brownian motion. By using the polynomial complete discrimination method, the
Da Shi, Zhao Li, Tianyong Han
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Polynomials and General Degree-Based Topological Indices of Generalized Sierpinski Networks
Complexity, 2021 Sierpinski networks are networks of fractal nature having several applications in computer science, music, chemistry, and mathematics. These networks are commonly used in chaos, fractals, recursive sequences, and complex systems.
Chengmei Fan +4 more
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Uncertainty Quantification of GEKO Model Coefficients on Compressible Flows
International Journal of Aerospace Engineering, 2021 In the present work, supersonic flows over an axisymmetric base and a 24-deg compression ramp are investigated using the generalized k-ω (GEKO) model implemented in the commercial software, ANSYS FLUENT.
Yeong-Ki Jung +2 more
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An Efficient Polynomial Chaos Expansion Method for Uncertainty Quantification in Dynamic Systems
Applied Mechanics, 2021 Uncertainty is a common feature in first-principles models that are widely used in various engineering problems. Uncertainty quantification (UQ) has become an essential procedure to improve the accuracy and reliability of model predictions.
Jeongeun Son, Yuncheng Du
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Computation, 2022 In this work, generalized polynomial chaos (gPC) expansion for land surface model parameter estimation is evaluated. We perform inverse modeling and compute the posterior distribution of the critical hydrological parameters that are subject to great ...
Georgios Karagiannis +3 more
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Robustness Analysis of the Collective Nonlinear Dynamics of a Periodic Coupled Pendulums Chain
Applied Sciences, 2017 Perfect structural periodicity is disturbed in presence of imperfections. The present paper is based on a realistic modeling of imperfections, using uncertainties, to investigate the robustness of the collective nonlinear dynamics of a periodic coupled ...
Khaoula Chikhaoui +3 more
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