Modeling of fluid damping in resonant micro-mirrors with out-of-plane comb-drive actuation

Comb-drive micromirrors are becoming of interest for a broad range of light manipulation applications. Due to technical reasons, some of these applications require packaging of the micromirror’s optical module in ambient air. Furthermore, micromirrors for picoprojectors application are required to function at high frequencies in order to achieve high resolution images. Accordingly, a study of the energy dissipated due to the interaction between the moving parts of the micromirror and the surrounding air, leading to fluid damping, is an important issue. Even if air damping has been thoroughly studied, an extension to large air domain distortion linked to large tilting angles of torsional micromirrors is still partially missing. In such situations, the flow formation turns out to be far more complex than that assumed in analytical models. This task is here accomplished by adopting three-dimensional computational fluid dynamics models; specifically, two models, holding at different length scales, are adopted to attack the problem through an automated dynamic remeshing method. The time evolution of the torque required to compensate for the fluid damping term is computed for a-specific micromirror geometry

Exact Solutions of the Generalized Benjamin Equation and (3 + 1)- Dimensional Gkp Equation by the Extended Tanh Method

In this paper, the extended tanh method is used to construct exact solutions of the generalized Benjamin and (3 + 1)-dimensional gKP equation. This method is shown to be an efficient method for obtaining exact solutions of nonlinear partial differential equations. It can be applied to nonintegrable equations as well as to integrable ones

Modelling the COVID-19 pandemic in context : An international participatory approach

Funding RA is funded by the Bill and Melinda Gates Foundation (OPP1193472). LW is funded by the Li Ka Shing Foundation. CF is funded by grant #2017/26770-8, São Paulo Research Foundation (FAPESP). The CoMo Consortium has support from the Oxford University COVID-19 Research Response Fund (ref: 0009280). Scientific writing assistance and editorial support was provided by Adam Bodley, according to Good Publication Practice guidelines.Peer reviewedPublisher PD

Modeling double strand break susceptibility to interrogate structural variation in cancer

Abstract Background Structural variants (SVs) are known to play important roles in a variety of cancers, but their origins and functional consequences are still poorly understood. Many SVs are thought to emerge from errors in the repair processes following DNA double strand breaks (DSBs). Results We used experimentally quantified DSB frequencies in cell lines with matched chromatin and sequence features to derive the first quantitative genome-wide models of DSB susceptibility. These models are accurate and provide novel insights into the mutational mechanisms generating DSBs. Models trained in one cell type can be successfully applied to others, but a substantial proportion of DSBs appear to reflect cell type-specific processes. Using model predictions as a proxy for susceptibility to DSBs in tumors, many SV-enriched regions appear to be poorly explained by selectively neutral mutational bias alone. A substantial number of these regions show unexpectedly high SV breakpoint frequencies given their predicted susceptibility to mutation and are therefore credible targets of positive selection in tumors. These putatively positively selected SV hotspots are enriched for genes previously shown to be oncogenic. In contrast, several hundred regions across the genome show unexpectedly low levels of SVs, given their relatively high susceptibility to mutation. These novel coldspot regions appear to be subject to purifying selection in tumors and are enriched for active promoters and enhancers. Conclusions We conclude that models of DSB susceptibility offer a rigorous approach to the inference of SVs putatively subject to selection in tumors

Assessment of overetch and polysilicon film properties through on-chip tests

Due to the increasing demand of miniaturization of MEMS devices, the characteristic size (e.g. the width) of some mechanical components may become comparable to that of a silicon grain. Therefore, the relevant effective mechanical properties can vary significantly from one device to another. In this work, through on-chip tests we investigate the behavior of polysilicon films using standard electrostatic actuation/sensing. The outcomes of the experimental campaign are then compared to those obtained with an analytical reduced-order model of the moving structure, and to coupled electro-mechanical simulations accounting for the polycrystalline morphology of the silicon film. These two models are adopted to bilaterally bound the experimental data up to pull-in, and to assess the scattering induced by the random orientation of the crystal lattice of each grain in slender parts of the devices

Uncertainty quantification in polysilicon MEMS through on-chip testing and reduced-order modelling

In this paper, micro-scale uncertainties affecting the behaviour of microelectromechanical systems (MEMS) are investigated through a mixed numerical/experimental approach. An on-chip test device has been designed and fabricated using standard MEMS fabrication techniques, to deform a (microstructured) polysilicon beam. To interpret the experimental data and also the relevant scatterings in the system response, a high fidelity, parametric finite element (FE) model of the device is developed in ANSYS. Uncertainties in the parameters governing the polysilicon mechanical properties and the geometry of the movable structure are estimated through an inverse analysis. To systematically quantify the uncertainty levels within the realm of a cost-effective statistical analysis, a model order reduction technique based on a synergy of proper orthogonal decomposition (POD) and Kriging interpolation is proposed. The resulting reduced order model is finally fed into a transitional Markov chain Monte Carlo (TMCMC) algorithm for the estimation of the unknown parameters

Roundabout's Impact on Nearby Businesses

Abstract The objective of this study is to determine if installation of roundabouts in a business area or on business corridors can be good for the businesses as well as improve the traffic flow in that area. This objective is achieved by emphasizing on roundabouts located in Kansas cities, particularly Topeka, Kansas. The study concentrates on conducting survey of businesses around the roundabout corridors in different places in the US including Topeka (Kansas), Junction City (Kansas), Newton (Kansas), and Carmel (Indiana). The survey results indicated a positive impact of roundabouts on businesses and traffic movement. Further, as there is no before and after corridor data available for making definite conclusions, a business corridor in Topeka, Kansas is simulated using both SIDRA and VISSIM software to evaluate the impacts of converting several traditional intersections in the corridor to roundabouts. The results from the simulation tasks have showed substantial reductions in vehicle delay and queuing for most of the traffic movements. Therefore, it was concluded that roundabouts on businesses corridor have a positive impact on traffic flows and business

Fluid damping in compliant, comb-actuated torsional micromirrors

Fluid damping is studied for resonant torsional micromirrors, electrostatically actuated by comb fingers. A three-dimensional computational fluid dynamics (CFD) model of the air flow around the moving parts of the mirror is developed, coping with dynamic remeshing procedures to properly account for the large displacement setting required by the motion of the compliant structure. The time evolution of the damping torque contributions, due to shear at comb fingers and to drag over the surfaces of the micromirror plate, are computed. The relevant numerical estimation of the overall quality factor of the system is shown to compare well with available experimental results