339 research outputs found

    The dynamics of liquid slugs forced by a syringe pump

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    Microfluidic processes for chemical synthesis have become popular in recent years. The small scale of the chemical reactions promise greater control over reaction conditions and more timely creation of products. The small scale of microfluidics poses its own set of problems, however. At the microscale, the dominant fluid forces are viscous resistance and surface tension. The effects of viscosity and scale reduce the Reynolds number and make mixing difficult. Much work has been done to control mixing at the microscale. This problem is concerned with a different microfluidic problem: delivering reactants to the site of reaction. A common setup is to attach syringes full of reactant to a reaction chamber by narrow hydrophobic tubing. Using a stepper motor, a controlled dose of liquid may be injected into the tube. The hydrophobosity causes the dose to curve outward on the sides, becoming a "slug" of reactant with air in front and behind. The syringe at the rear is then switched for one full of air, and air pressure is used to drive the slug to the reaction site. If too much pressure is applied, the slug will arrive with a significant back pressure that will be relieved through bubbling in the reaction site. This causes the formation of a foam and is highly undesirable. We present a simple model based on Boyle’s law for the motion of a slug through a tube. We then extend this model for trains of slugs separated by air bubbles. Last, we consider the case of a flooded reaction site, where the forward air bubble must be pushed through the flooding liquid. In conclusion, we have determined the dynamics of a single slug moving towards an empty reaction chamber giving the final equilibrium position of the slug. A phase-plane analysis then determined a condition on the size of the slug needed to ensure that it comes to rest without oscillating about the equilibrium position. The effect of a flooded reaction chamber was then considered. In this case it is impossible to avoid bubbling due to the design of the device. We found that it is possible, however, to reduce the bubbling by minimising the back pressure behind the slug. Finally, the dynamics of multiple slugs with or without a flooded reaction chamber has been investigated

    GazeStereo3D: seamless disparity manipulations

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    Producing a high quality stereoscopic impression on current displays is a challenging task. The content has to be carefully prepared in order to maintain visual comfort, which typically affects the quality of depth reproduction. In this work, we show that this problem can be significantly alleviated when the eye fixation regions can be roughly estimated. We propose a new method for stereoscopic depth adjustment that utilizes eye tracking or other gaze prediction information. The key idea that distinguishes our approach from the previous work is to apply gradual depth adjustments at the eye fixation stage, so that they remain unnoticeable. To this end, we measure the limits imposed on the speed of disparity changes in various depth adjustment scenarios, and formulate a new model that can guide such seamless stereoscopic content processing. Based on this model, we propose a real-time controller that applies local manipulations to stereoscopic content to find the optimum between depth reproduction and visual comfort. We show that the controller is mostly immune to the limitations of low-cost eye tracking solutions. We also demonstrate benefits of our model in off-line applications, such as stereoscopic movie production, where skillful directors can reliably guide and predict viewers' attention or where attended image regions are identified during eye tracking sessions. We validate both our model and the controller in a series of user experiments. They show significant improvements in depth perception without sacrificing the visual quality when our techniques are applied

    Energy solutions to one-dimensional singular parabolic problems with BVBV data are viscosity solutions

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    We study one-dimensional very singular parabolic equations with periodic boundary conditions and initial data in BVBV, which is the energy space. We show existence of solutions in this energy space and then we prove that they are viscosity solutions in the sense of Giga-Giga.Comment: 15 page

    Neural Stress Fields for Reduced-order Elastoplasticity and Fracture

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    We propose a hybrid neural network and physics framework for reduced-order modeling of elastoplasticity and fracture. State-of-the-art scientific computing models like the Material Point Method (MPM) faithfully simulate large-deformation elastoplasticity and fracture mechanics. However, their long runtime and large memory consumption render them unsuitable for applications constrained by computation time and memory usage, e.g., virtual reality. To overcome these barriers, we propose a reduced-order framework. Our key innovation is training a low-dimensional manifold for the Kirchhoff stress field via an implicit neural representation. This low-dimensional neural stress field (NSF) enables efficient evaluations of stress values and, correspondingly, internal forces at arbitrary spatial locations. In addition, we also train neural deformation and affine fields to build low-dimensional manifolds for the deformation and affine momentum fields. These neural stress, deformation, and affine fields share the same low-dimensional latent space, which uniquely embeds the high-dimensional simulation state. After training, we run new simulations by evolving in this single latent space, which drastically reduces the computation time and memory consumption. Our general continuum-mechanics-based reduced-order framework is applicable to any phenomena governed by the elastodynamics equation. To showcase the versatility of our framework, we simulate a wide range of material behaviors, including elastica, sand, metal, non-Newtonian fluids, fracture, contact, and collision. We demonstrate dimension reduction by up to 100,000X and time savings by up to 10X

    Simit: A Language for Physical Simulation

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    Using existing programming tools, writing high-performance simulation code is labor intensive and requires sacrificing readability and portability. The alternative is to prototype simulations in a high-level language like Matlab, thereby sacrificing performance. The Matlab programming model naturally describes the behavior of an entire physical system using the language of linear algebra. However, simulations also manipulate individual geometric elements, which are best represented using linked data structures like meshes. Translating between the linked data structures and linear algebra comes at significant cost, both to the programmer and the machine. High-performance implementations avoid the cost by rephrasing the computation in terms of linked or index data structures, leaving the code complicated and monolithic, often increasing its size by an order of magnitude. In this paper, we present Simit, a new language for physical simulations that lets the programmer view the system both as a linked data structure in the form of a hypergraph, and as a set of global vectors, matrices and tensors depending on what is convenient at any given time. Simit provides a novel assembly construct that makes it conceptually easy and computationally efficient to move between the two abstractions. Using the information provided by the assembly construct, the compiler generates efficient in-place computation on the graph. We demonstrate that Simit is easy to use: a Simit program is typically shorter than a Matlab program; that it is high-performance: a Simit program running sequentially on a CPU performs comparably to hand-optimized simulations; and that it is portable: Simit programs can be compiled for GPUs with no change to the program, delivering 5-25x speedups over our optimized CPU code

    Video face replacement

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    We present a method for replacing facial performances in video. Our approach accounts for differences in identity, visual appearance, speech, and timing between source and target videos. Unlike prior work, it does not require substantial manual operation or complex acquisition hardware, only single-camera video. We use a 3D multilinear model to track the facial performance in both videos. Using the corresponding 3D geometry, we warp the source to the target face and retime the source to match the target performance. We then compute an optimal seam through the video volume that maintains temporal consistency in the final composite. We showcase the use of our method on a variety of examples and present the result of a user study that suggests our results are difficult to distinguish from real video footage.National Science Foundation (U.S.) (Grant PHY-0835713)National Science Foundation (U.S.) (Grant DMS-0739255

    Experimental and Computational Investigation of Subcritical Near-Nozzle Spray Structure and Primary Atomization in the Engine Combustion Network Spray D

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    [EN] In order to improve understanding of the primary atomization process for diesel-like sprays, a collaborative experimental and computational study was focused on the near-nozzle spray structure for the Engine Combustion Network (ECN) Spray D single-hole injector. These results were presented at the 5th Workshop of the ECN in Detroit, Michigan. Application of x-ray diagnostics to the Spray D standard cold condition enabled quantification of distributions of mass, phase interfacial area, and droplet size in the near-nozzle region from 0.1 to 14 mm from the nozzle exit. Using these data, several modeling frameworks, from Lagrangian-Eulerian to Eulerian-Eulerian and from Reynolds-Averaged Navier-Stokes (RANS) to Direct Numerical Simulation (DNS), were assessed in their ability to capture and explain experimentally observed spray details. Due to its computational efficiency, the Lagrangian-Eulerian approach was able to provide spray predictions across a broad range of conditions. In general, this "engineering-level" simulation was able to reproduce the details of the droplet size distribution throughout the spray after calibration of the spray breakup model constants against the experimental data. Complementary to this approach, higher-fidelity modeling techniques were able to provide detailed insight into the experimental trends. For example, interface-capturing multiphase simulations were able to capture the experimentally observed bimodal behavior in the transverse interfacial area distributions in the near-nozzle region. Further analysis of the spray predictions suggests that peaks in the interfacial area distribution may coincide with regions of finely atomized droplets, whereas local minima may coincide with regions of continuous liquid structures. The results from this study highlight the potential of x-ray diagnostics to reveal salient details of the near-nozzle spray structure and to guide improvements to existing primary atomization modeling approaches.Battistoni, M.; Magnotti, GM.; Genzale, CL.; Arienti, M.; Matusik, KE.; Duke, DJ.; Giraldo-Valderrama, JS.... (2018). Experimental and Computational Investigation of Subcritical Near-Nozzle Spray Structure and Primary Atomization in the Engine Combustion Network Spray D. SAE International Journal of Fuel and Lubricants. 11(4):337-352. https://doi.org/10.4271/2018-01-0277S33735211

    Human Resources and the Resource Based View of the Firm

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    The resource-based view (RBV) of the firm has influenced the field of strategic human resource management (SHRM) in a number of ways. This paper explores the impact of the RBV on the theoretical and empirical development of SHRM. It explores how the fields of strategy and SHRM are beginning to converge around a number of issues, and proposes a number of implications of this convergence

    A First Order Predicate Logic Formulation of the 3D Reconstruction Problem and its Solution Space

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    This paper defines the 3D reconstruction problem as the process of reconstructing a 3D scene from numerous 2D visual images of that scene. It is well known that this problem is ill-posed, and numerous constraints and assumptions are used in 3D reconstruction algorithms in order to reduce the solution space. Unfortunately, most constraints only work in a certain range of situations and often constraints are built into the most fundamental methods (e.g. Area Based Matching assumes that all the pixels in the window belong to the same object). This paper presents a novel formulation of the 3D reconstruction problem, using a voxel framework and first order logic equations, which does not contain any additional constraints or assumptions. Solving this formulation for a set of input images gives all the possible solutions for that set, rather than picking a solution that is deemed most likely. Using this formulation, this paper studies the problem of uniqueness in 3D reconstruction and how the solution space changes for different configurations of input images. It is found that it is not possible to guarantee a unique solution, no matter how many images are taken of the scene, their orientation or even how much color variation is in the scene itself. Results of using the formulation to reconstruct a few small voxel spaces are also presented. They show that the number of solutions is extremely large for even very small voxel spaces (5 x 5 voxel space gives 10 to 10(7) solutions). This shows the need for constraints to reduce the solution space to a reasonable size. Finally, it is noted that because of the discrete nature of the formulation, the solution space size can be easily calculated, making the formulation a useful tool to numerically evaluate the usefulness of any constraints that are added
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