22,117 research outputs found

    Optimization for Explainable Modeling

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    Whether it is the signaling mechanisms behind immune cells or the change in animal populations, mechanistic models such as agent based models or systems of differential equations that define explicit causal mechanisms are used to validate hypothesises and thereby understand physical systems. To quantitatively and qualitatively validate a mechanistic model, experimental data is used to fit and estimate parameters within these models, thereby providing interpretable and explainable quantitative values. Parameter estimation tasks for mechanistic models can be extremely challenging for a variety of reasons, especially for single-cell systems. One, measurements of protein abundances can vary many orders of magnitude and often the number of model parameters exceeds that of the data. Two, mechanistic simulations can often be computationally expensive where parameter estimation can range from hours to days, and even more when fine-tuning an optimization algorithm. Through building a framework BioNetGMMFit, we show that we can readily account for the large variances within single-cell models using generalized method of moments, and through leveraging deep learning in surrogate modeling, we show that we can reduce the computational time complexity in parameter estimation.No embargoAcademic Major: Computer Science and Engineerin

    Vortex flow of downwind sails

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    This paper sets out to investigate the vortex flow of spinnaker yacht sails, which are low-aspect-ratio highly-cambered wings used to sail downwind. We tested three model-scale sails with the same sections but different twists over a range of angles of attack in a water tunnel at a Reynolds number of 21 000. We measured the forces with a balance and the velocity field with particle image velocimetry. The sails experience massively separated three-dimensional flow and leading-edge vortices convect at half of the free stream velocity in a turbulent shear layer. Despite the massive flow separation, the twist of the sail does not change the lift curve slope, in agreement with strip theory. As the angle of attack and the twist vary, flow reattachment might occur in the time-average sense, but this does not necessarily result in a higher lift to drag ratio as the vorticity field is marginally affected. Finally, we investigated the effect of secondary vorticity, vortex stretching and diffusion on the vorticity fluxes. Overall, these results provide new insights on the vortex flow and associated force generation mechanism of wings with massively separated flo

    Numerical study on wind profiles change trend of upright reticulation barriers under different configuration models

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    To explore how to lay the same specifications to maximize the protection benefits of mechanical sand barriers is an essential issue in the actual production process. We used the Reynolds-Averaged Navier-Stokes (RANS) method and the shear stress transport (SST) K-ε turbulence model to study the windbreak efficiency of sand barriers with different structures. Among them, the structure of the sand barriers includes rhombus 60° (cTnI = 60°, R60°), rhombus 90° (cTnI = 90°, R90°), rhombus 120° (cTnI = 120°, R120°) and parallel straight line (belt). The sand barrier was set to a porous jump model, where the surface permeability a was 2.6 × 108, and the inertial resistance coefficient c2 was 9,400. The wind velocity field results showed that the sand barrier’s blocking effect on wind velocity decreases with the increase in height. The leading edge of the 120° obstacle has the strongest weakening effect on the inlet wind speed. The minimum wind speed (0.97 m/s to 1.41 m/s) occurs near the sand barrier, and the vortex appears on both sides of the node, and the wind speed increases. The order of the blocking effect of different angles on airflow is as follows: 120° > 90°> brand >60°. Under R120° conditions, the wind speed is reduced by more than 60% at 0.05 m and 0.1 m height behind the barrier compared to the initial wind speed. This will be conducive to the design and control engineering planning of the laying angle of the gauze sand barrier in the main wind direction

    Physics-informed Neural Network Combined with Characteristic-Based Split for Solving Navier-Stokes Equations

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    In this paper, physics-informed neural network (PINN) based on characteristic-based split (CBS) is proposed, which can be used to solve the time-dependent Navier-Stokes equations (N-S equations). In this method, The output parameters and corresponding losses are separated, so the weights between output parameters are not considered. Not all partial derivatives participate in gradient backpropagation, and the remaining terms will be reused.Therefore, compared with traditional PINN, this method is a rapid version. Here, labeled data, physical constraints and network outputs are regarded as priori information, and the residuals of the N-S equations are regarded as posteriori information. So this method can deal with both data-driven and data-free problems. As a result, it can solve the special form of compressible N-S equations -- -Shallow-Water equations, and incompressible N-S equations. As boundary conditions are known, this method only needs the flow field information at a certain time to restore the past and future flow field information. We solve the progress of a solitary wave onto a shelving beach and the dispersion of the hot water in the flow, which show this method's potential in the marine engineering. We also use incompressible equations with exact solutions to prove this method's correctness and universality. We find that PINN needs more strict boundary conditions to solve the N-S equation, because it has no computational boundary compared with the finite element method

    Investigation of Submergence Depth and Wave-Induced Effects on the Performance of a Fully Passive Energy Harvesting Flapping Foil Operating Beneath the Free Surface

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    This paper investigates the performance of a fully passive flapping foil device for energy harvesting in a free surface flow. The study uses numerical simulations to examine the effects of varying submergence depths and the impact of monochromatic waves on the foil's performance. The results show that the fully passive flapping foil device can achieve high efficiency for submergence depths between 4 and 9 chords, with an "optimum" submergence depth where the flapping foil performance is maximised. The performance was found to be correlated with the resonant frequency of the heaving motion and its proximity to the damped natural frequency. The effects of regular waves on the foil's performance were also investigated, showing that waves with a frequency close to that of the natural frequency of the flapping foil aided energy harvesting. Overall, this study provides insights that could be useful for future design improvements for fully passive flapping foil devices for energy harvesting operating near the free surface

    Aero-thermal analysis of a laminar separation bubble subjected to varying free-stream turbulence: Large Eddy Simulation

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    A quantitative analysis illustrating salient features of a Laminar Separation Bubble (LSB), its transition forming coherent structures, and associated heat transfer has been performed on a flat plate for varying free stream turbulence (fst) between 1.2% to 10.3%. A well-resolved Large Eddy Simulation (LES) developed in-house is used for the purpose. Flow separation has been induced by imposing an adverse pressure gradient on the upper boundary of a Cartesian domain. Isotropic perturbations are introduced at the inlet to mimic grid turbulence. With an increase of fst, an upstream shift in the mean reattachment point has been observed while the onset of separation remains almost invariant, shrinking the bubble length significantly. The transition of the shear layer is triggered by the Kelvin-Helmholtz (K-H) instability for fst of less than 3.3%, while Klebanoff modes (Kmodes) dictate the flow transition at fst greater than 6.5%. Further, a mixed mode, i.e., both K-H and K-modes, contribute to the flow transition at a moderate level of fst, lying between 3.3% and 6.5%. Thus, the roll-up of the shear layer appears in the second half of the bubble shedding large-scale vortices that keep their identity far downstream at low fst levels. On the contrary, the streamwise streaks via K-modes prior to the separation are found to interact with the LSB, resulting in an earlier breakdown of the shear layer with abundant small-scale vortices downstream at the moderate to high fst levels. However, higher surface-normal heat flux is associated with large-scale energetic coherent vortices

    Evolutionary Multi-Objective Aerodynamic Design Optimization Using CFD Simulation Incorporating Deep Neural Network

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    An evolutionary multi-objective aerodynamic design optimization method using the computational fluid dynamics (CFD) simulations incorporating deep neural network (DNN) to reduce the required computational time is proposed. In this approach, the DNN infers the flow field from the grid data of a design and the CFD simulation starts from the inferred flow field to obtain the steady-state flow field with a smaller number of time integration steps. To show the effectiveness of the proposed method, a multi-objective aerodynamic airfoil design optimization is demonstrated. The results indicate that the computational time for design optimization is suppressed to 57.9% under 96 cores processor conditions

    Effects of wind turbine rotor positioning on tornado induced loads

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    This study investigates the loads induced by a large-scale tornado simulation on a horizontal axis wind turbine (HAWT) to assess the influence of three-dimensional flows with respect to the HAWT position. The loads were analyzed under two rotor operational conditions, idling and parked, at five radial distances. Subsequently, experimental validation of the numerical code HIW-TUR was conducted by evaluating the induced moments for various yaw and pitch angles. The experimental results demonstrated that the bending moment was the most important in terms of magnitude and variation with respect to the HAWT position. Furthermore, The HIW-TUR code accurately identified the magnitude and HAWT configuration that leads to the maximum mean moments induced by the tornado. It was proved that by varying the yaw angle of the rotor plane and blade orientation to parallel to the tornado tangential component, the overall loads could be reduced to the minimum values

    Curriculum Subcommittee Agenda, April 7, 2022

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    Approval of 3 March 2022 Minutes Program Proposals Semester Course Approval Reviews https://usu.curriculog.com/ Other Business New Curriculum Subcommittee Chair appointment. Acceptance of membership for 2022-2023 academic year. Program Proposals Request from the Department of Plants, Soils and Climate in the College of Agriculture and Applied Sciences to offer a new specialization (Bioinformatics and Computational Biology) to the MS and PhD degrees of Plant Science. Request from the Department of Theatre Arts in the Caine College of the Arts to change the name of the Theatre Arts Theatre Education Certification Option BFA to Theatre Arts Education BFA. Request from the Department of Mechanical and Aerospace Engineering in the College of Engineering to create a Center for the Design and Manufacturing of Advanced Materials (CDMAM). Request from the Department of Data Analytics and Information Systems in the Jon M. Huntsman School of Business to create a new post-baccalaureate certificate in Cybersecurity. Request from the Department of Data Analytics and Information Systems in the Jon M. Huntsman School of Business to create a new post-baccalaureate certificate in Data Analytics. Request from the Department of Data Analytics and Information Systems in the Jon M. Huntsman School of Business to create a new post-baccalaureate certificate in Data Engineering. Request from the Department of Data Analytics and Information Systems in the Jon M. Huntsman School of Business to create a new post-baccalaureate certificate in Data Technologies. Request from the Department of Data Analytics and Information Systems in the Jon M. Huntsman School of Business to restructure the existing Master of Management Information Systems program to require completion of two stackable post-baccalaureate certificates (24 credits) along with six credits of information technology strategy or management courses. Request from the Department of Data Analytics and Information Systems in the Jon M. Huntsman School of Business to create a new post-baccalaureate certificate in Web Development
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