Topology Optimization of Fixed-Geometry Fluid Diodes

2015 ◽  
Vol 137 (8) ◽  
Author(s):  
Sen Lin ◽  
Longyu Zhao ◽  
James K. Guest ◽  
Timothy P. Weihs ◽  
Zhenyu Liu
Keyword(s):  
Topology Optimization ◽  
Reverse Flow ◽  
Flow Behavior ◽  
Projection Methods ◽  
Reverse Direction ◽  
Minimum Length ◽  
Penalty Term ◽  
Forward Flow ◽  
Dependent Flow ◽  
Minimum Length Scale

This paper proposes using topology optimization to design fixed-geometry fluid diodes that allow easy passage of fluid flowing in one direction while inhibiting flow in the reverse direction. Fixed-geometry diodes do not use movable mechanical parts or deformations, but rather utilize inertial forces of the fluid to achieve this flow behavior. Diode performance is measured by diodicity, defined as the ratio of pressure drop of reverse flow and forward flow, or equivalently the ratio of dissipation of reverse and forward flow. Diodicity can then be maximized by minimizing forward dissipation while maximizing reverse dissipation. While significant research has been conducted in topology optimization of fluids for minimizing dissipation, maximizing dissipation introduces challenges in the form of small, mesh dependent flow channels and that artificial flow in solid region becomes (numerically) desirable. These challenges are circumvented herein using projection methods for controlling the minimum length scale of channels and by introducing an additional penalty term on flow through intermediate porosities. Several solutions are presented, one of which is fabricated by 3D printing and experimentally tested to demonstrate the diodelike behavior.

scholarly journals Brain-wide mapping of water flow perception in zebrafish

2020 ◽  
Author(s):  
Gilles Vanwalleghem ◽  
Kevin Schuster ◽  
Michael A. Taylor ◽  
Itia A. Favre-Bulle ◽  
Ethan K. Scott
Keyword(s):  
Water Flow ◽  
Lateral Line ◽  
Reverse Flow ◽  
Forward Direction ◽  
Brain Regions ◽  
Reverse Direction ◽  
Departure Point ◽  
Forward Flow ◽  
Larval Zebrafish ◽  
The Brain

AbstractInformation about water flow, detected by lateral line organs, is critical to the behavior and survival of fish and amphibians. While certain specific aspects of water flow processing have been revealed through electrophysiology, we lack a comprehensive description of the neurons that respond to water flow and the network that they form. Here, we use brain-wide calcium imaging in combination with microfluidic stimulation to map out, at cellular resolution, all neurons involved in perceiving and processing water flow information in larval zebrafish. We find a diverse array of neurons responding to forward flow, reverse flow, or both. Early in this pathway, in the lateral line ganglia, these are almost exclusively neurons responding to the simple presence of forward or reverse flow, but later processing includes neurons responding specifically to flow onset, representing the accumulated volume of flow during a stimulus, or encoding the speed of the flow. The neurons reporting on these more nuanced details are located across numerous brain regions, including some not previously implicated in water flow processing. A graph theory-based analysis of the brain-wide water flow network shows that a majority of this processing is dedicated to forward flow detection, and this is reinforced by our finding that details like flow velocity and the total volume of accumulated flow are only encoded for the simulated forward direction. The results represent the first brain-wide description of processing for this important modality, and provide a departure point for more detailed studies of the flow of information through this network.Significance statementIn aquatic animals, the lateral line is important for detecting water flow stimuli, but the brain networks that interpret this information remain mysterious. Here, we have imaged the activity of individual neurons across the entire brains of larval zebrafish, revealing all response types and their brain locations as water flow processing occurs. We find some neurons that respond to the simple presence of water flow, and others that are attuned to the flow’s direction, speed, duration, or the accumulated volume of water that has passed during the stimulus. With this information, we modeled the underlying network, describing a system that is nuanced in its processing of water flow simulating forward motion but rudimentary in processing flow in the reverse direction.

Casting and Milling Restrictions in Topology Optimization via Projection-Based Algorithms

2012 ◽  
Author(s):  
James K. Guest ◽  
Mu Zhu
Keyword(s):  
Topology Optimization ◽  
Continuation Methods ◽  
Minimum Length ◽  
Manufacturing Constraints ◽  
Element Space ◽  
Structure Topology ◽  
Design Variables ◽  
Unstructured Meshing ◽  
Independent Design ◽  
Minimum Length Scale

Projection-based algorithms are arising as a powerful tool for continuum topology optimization. They use independent design variables that are projected onto element space to create structure topology. The projection functions are designed so that geometric properties, such as the minimum length scale of features, are naturally achieved. They therefore offer an efficient means for imposing geometry-related design specifications and/or manufacturing constraints. This paper presents recent advances in projection-based algorithms, including topology optimization under manufacturing constraints related to milling and casting processes. The new advancements leverage the logic of recently proposed algorithms for Heaviside projection, including eliminating continuation methods on projection parameters and potential for using multiple design variables to achieve active projection of each phase used in design. The primary advantages of such an approach are that manufacturing restrictions are achieved naturally, without need for additional constraints, and that sensitivity calculations are efficient and straightforward. The primary drawback of the approach is that the so-called neighborhood maps require storage for efficient processing when using unstructured meshing.

The Sensitivity of Counterweighted Swing Check Valve Performance to Counterweight Location

2003 ◽  
Author(s):  
L. I. Ezekoye
Keyword(s):  
Flow Resistance ◽  
Reverse Flow ◽  
Check Valve ◽  
Fast Response ◽  
Water Hammer ◽  
Flow Reversal ◽  
Reverse Direction ◽  
Valve Closure ◽  
Forward Flow ◽  
Opening And Closing

Check valves are used to minimize flow reversal. In general, the two primary design objectives of installing a check valve in a system include quick opening in forward flow and fast closure in reverse flow. The fast response requirements in both opening and closing directions are challenging. In the opening direction, the concern is to minimize forward flow resistance and, in the reverse direction, the objective is to minimize flow reversal and avoid water hammer. Check valve manufacturers have often used counterweights to permit quick opening or quick closing. The drawback of forward flow counterweight check valves is that in the flow reverse direction, the counterweights may retard valve closure. The location of the counterweight could further complicate the performance of the check valve. Misaligning the counterweight can also affect check valve performance. The use of quick closing counterweights present similar challenges. This paper examines the interaction of counterweight location and alignment on the performance of check valves.

Gradient-Based Multi-Component Topology Optimization for Additive Manufacturing (MTO-A)

2017 ◽  
Author(s):  
Yuqing Zhou ◽  
Kazuhiro Saitou
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Simultaneous Optimization ◽  
Minimum Length ◽  
Manufacturing Constraints ◽  
Component Level ◽  
Component Size ◽  
Design Variables ◽  
Gradient Based ◽  
Minimum Length Scale

Topology optimization for additive manufacturing has been limited to the component-level designs with the component size smaller than the printer’s build volume. To enable the design of structures larger than the printer’s build volume, this paper presents a gradient-based multi-component topology optimization framework for structures assembled from components built by additive manufacturing. Constraints on component geometry for additive manufacturing are incorporated in the density-based topology optimization, with additional design variables specifying fractional component membership. For each component, constraints on build size, enclosed voids, overhangs, and the minimum length scale are imposed during the simultaneous optimization of overall base topology and component partitioning. The preliminary result on a minimum compliance structure shows promising advantages over the conventional monolithic topology optimization. Manufacturing constraints previously applied to monolithic topology optimization gain new interpretations when applied to multi-component assemblies, which can unlock richer design space for topology exploration.

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