Rethinking CycleGAN: Improving Quality of GANs for Unpaired Image-to-Image Translation

An unpaired image-to-image (I2I) translation technique seeks to find a mapping between two domains of data in a fully unsupervised manner. While the initial solutions to the I2I problem were provided by the generative adversarial neural networks (GANs), currently, diffusion models (DM) hold the state-of-the-art status on the I2I translation benchmarks in terms of FID. Yet, they suffer from some limitations, such as not using data from the source domain during the training, or maintaining consistency of the source and translated images only via simple pixel-wise errors. This work revisits the classic CycleGAN model and equips it with recent advancements in model architectures and model training procedures. The revised model is shown to significantly outperform other advanced GAN- and DM-based competitors on a variety of benchmarks. In the case of Male2Female translation of CelebA, the model achieves over 40% improvement in FID score compared to the state-of-the-art results. This work also demonstrates the ineffectiveness of the pixel-wise I2I translation faithfulness metrics and suggests their revision. The code and trained models are available at https://github.com/LS4GAN/uvcgan

Implementation of ACTS into sPHENIX track reconstruction

sPHENIX is a high energy nuclear physics experiment under construction at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory (BNL). The primary physics goals of sPHENIX are to study the quark-gluon-plasma, as well as the partonic structure of protons and nuclei, by measuring jets, their substructure, and heavy flavor hadrons in $p$$+$$p$, $p$+Au, and Au+Au collisions. sPHENIX will collect approximately 300 PB of data over three run periods, to be analyzed using available computing resources at BNL; thus, performing track reconstruction in a timely manner is a challenge due to the high occupancy of heavy ion collision events. The sPHENIX experiment has recently implemented the A Common Tracking Software (ACTS) track reconstruction toolkit with the goal of reconstructing tracks with high efficiency and within a computational budget of 5 seconds per minimum bias event. This paper reports the performance status of ACTS as the default track fitting tool within sPHENIX, including discussion of the first implementation of a time projection chamber geometry within ACTS

Experimental and Numerical Investigations on the Flow Characteristics within Hydrodynamic Entrance Regions in Microchannels

Flow characteristics within entrance regions in microchannels are important due to their effect on heat and mass transfer. However, relevant research is limited and some conclusions are controversial. In order to reveal flow characteristics within entrance regions and to provide empiric correlation estimating hydrodynamic entrance length, experimental and numerical investigations were conducted in microchannels with square cross-sections. The inlet configuration was elaborately designed in a more common pattern for microdevices to diminish errors caused by separation flow near the inlet and fabrication faults so that conclusions which were more applicable to microchannels could be drawn. Three different microchannels with hydraulic diameters of 100 μm, 150 μm, and 200 μm were investigated with Reynolds (Re) number ranging from 0.5 to 50. For the experiment, deionized water was chosen as the working fluid and microscopic particle image velocimetry (micro-PIV) was adopted to record and analyze velocity profiles. For numerical simulation, the test-sections were modeled and incompressible laminar Navier–Stokes equations were solved with commercial software. Strong agreement was achieved between the experimental data and the simulated data. According to the results of both the experiments and the simulations, new correlations were proposed to estimate entrance length. Re numbers ranging from 12.5 to 15 was considered as the transition region where the relationship between entrance length and Re number converted. For the microchannels and the Reynolds number range investigated compared with correlations for conventional channels, noticeable deviation was observed for lower Re numbers (Re < 12.5) and strong agreement was found for higher Re numbers (Re > 15)

Experimental Investigation of the Flow and Heat Transfer Characteristics in Microchannel Heat Exchangers with Reentrant Cavities

The application of microchannel heat exchangers is of great significance in industrial fields due to their advantages of miniaturized scale, large surface-area-to-volume ratio, and high heat transfer rate. In this study, microchannel heat exchangers with and without fan-shaped reentrant cavities were designed and manufactured, and experiments were conducted to investigate the flow and heat-transfer characteristics. The impact rising from the radius of reentrant cavities, as well as the Reynolds number on the heat transfer and the pressure drop, is also analyzed. The results indicate that, compared with straight microchannels, microchannels with reentrant cavities could enhance the heat transfer and, more importantly, reduce the pressure drop at the same time. For the ranges of parameters studied, increasing the radius of reentrant cavities could augment the effect of pressure-drop reduction, while the corresponding variation of heat transfer is complicated. It is considered that adding reentrant cavities in microchannel heat exchangers is an ideal approach to improve performance

Flow Characteristics of the Entrance Region with Roughness Effect within Rectangular Microchannels

We conducted systematic numerical investigations of the flow characteristics within the entrance region of rectangular microchannels. The effects of the geometrical aspect ratio and roughness on entrance lengths were analyzed. The incompressible laminar Navier–Stokes equations were solved using finite volume method (FVM). In the simulation, hydraulic diameters ( D h ) ranging from 50 to 200 µm were studied, and aspect ratios of 1, 1.25, 1.5, 1.75, and 2 were considered as well. The working fluid was set as water, and the Reynolds number ranged from 0.5 to 100. The results showed a good agreement with the conducted experiment. Correlations are proposed to predict the entrance lengths of microchannels with respect to different aspect ratios. Compared with other correlations, these new correlations are more reliable because a more practical inlet condition was considered in our investigations. Instead of considering the influence of the width and height of the microchannels, in our investigation we proved that the critical role is played by the aspect ratio, representing the combination of the aforementioned parameters. Furthermore, the existence of rough elements obviously shortens the entrance region, and this effect became more pronounced with increasing relative roughness and Reynolds number. A similar effect could be seen by shortening the roughness spacing. An asymmetric distribution of rough elements decreased the entrance length compared with a symmetric distribution, which can be extrapolated to other irregularly distributed forms

Numerical Investigation on the Optimum Thermal Design of the Shape and Geometric Parameters of Microchannel Heat Exchangers with Cavities

Due to the large surface-area-to-volume ratio, microchannel heat exchangers have a higher heat transfer rate compared with traditional scale heat exchangers. In this study, the optimum microchannel cavity with high heat transfer and low flow resistance is designed to further improve microchannel exchangers’ thermal performance. A three-dimensional laminar flow model, consisting of Navier–Stokes equations and an energy conservation equation is solved and the conjugate heat transfer between the silicon basement and deionized water is taken into consideration. The impact of the shape, aspect ratio, size and spacing of the cavity on the thermal performance of microchannel exchangers are numerically investigated, respectively. The results indicated that the cavity on the sidewall can enhance heat transfer and reduce flow resistance simultaneously, and cavities with a relatively small expansion angle and streamlined edge could enhance thermal performance the most. Based on the conclusions, a new cavity shape is proposed, and the simulation results verify its excellent thermal performance as expected. Furthermore, investigation is performed to figure out the optimum design of the new cavity and the optimal geometric parameters of the cavity under different flow conditions have been obtained in principle for microchannel exchangers’ design

Unsupervised Domain Transfer for Science: Exploring Deep Learning Methods for Translation between LArTPC Detector Simulations with Differing Response Models

Deep learning (DL) techniques have broad applications in science, especially in seeking to streamline the pathway to potential solutions and discoveries. Frequently, however, DL models are trained on the results of simulation yet applied to real experimental data. As such, any systematic differences between the simulated and real data may degrade the model's performance -- an effect known as "domain shift." This work studies a toy model of the systematic differences between simulated and real data. It presents a fully unsupervised, task-agnostic method to reduce differences between two systematically different samples. The method is based on the recent advances in unpaired image-to-image translation techniques and is validated on two sets of samples of simulated Liquid Argon Time Projection Chamber (LArTPC) detector events, created to illustrate common systematic differences between the simulated and real data in a controlled way. LArTPC-based detectors represent the next-generation particle detectors, producing unique high-resolution particle track data. This work open-sources the generated LArTPC data set, called Simple Liquid-Argon Track Samples (or SLATS), allowing researchers from diverse domains to study the LArTPC-like data for the first time. The code and trained models are available at https://github.com/LS4GAN/uvcgan4slats

Powder filling and sintering of 3D in-chip solenoid coils with high aspect ratio structure

In this study, a 3D coil embedded in a silicon substrate including densely distributed through-silicon vias (TSVs) was fabricated via a rapid metal powder sintering process. The filling and sintering methods for microdevices were evaluated, and the effects of powder types were compared. The parameters influencing the properties and processing speed were analyzed. The results showed that the pre-alloyed powder exhibited the best uniformity and stability when the experiment used two or more types of powders to avoid the segregation effect. The smaller the particle diameter, the better the inductive performance will be. The entire structure can be sintered near the melting point of the alloy, and increasing the temperature increases strength, while resulting in low resistivity. Finally, an 800-µm-high coil was fabricated. This process does not need surface metallization and seed layer formation. The forming process involves only sintering instead of slowly growing copper with a tiny current. Therefore, this process has advantages, such as a process time of 7 h, corresponding to an 84% reduction compared to current electroplating processes (45 h), and a 543% efficiency improvement. Thus, this process is more efficient, controllable, stable, and suitable for mass production of devices with flexible dimensions. ©2020 Keywords: through-silicon-vias (TSVs); three-dimensional (3D) solenoid coils; microelectromechanical system (MEMS); powder filling; metal powder sinteringNational Natural Science Foundation of China (grant no. 51906008)National Natural Science Foundation of China (grant no. 51822602

Investigating the Flow Characteristics of Superhydrophobic U-Shaped Microchannels

Hydrophobicity has been widely reported for its superior behavior in drag reduction, self-cleaning, and anti-corrosion in many areas. Especially in engineering design, the research of the unique property of the slip flow with complex flow patterns is essential for practical applications. In this paper, the flow characteristics of a superhydrophobic U-shaped microchannel are systematically investigated, as the curved part is a fundamental component in microfluids. A slip model is established based on theoretical and experimental solutions. Various types of U-shaped microchannels, radii of curvature, and contact angles are studied with a wide range of Reynolds numbers from 0 to 300. We propose a velocity distribution to examine the non-uniformity of slip velocity on the cross-section. This imbalance is improved with an increase in the apparent contact angle and flow rate, and a decrease in the radius of curvature. The secondary flow and vortices generated by the centrifugal force are enhanced, and their positions are changed due to the slippery boundary. The results show a considerable drag reduction from 10% to 40% with different contact angles. The variation of curvature does not have a decisive impact on the final performance when the surface wettability maintains a steady state. Our research elucidates the physical principle of the slip model in curved channels, showing extensive applications of hydrophobicity in the design of complex microchips and the optimization strategy of heat transfer systems

A Review on the Application of Cobalt-Based Nanomaterials in Supercapacitors

Among many electrode materials, cobalt-based nanomaterials are widely used in supercapacitors because of their high natural abundance, good electrical conductivity, and high specific capacitance. However, there are still some difficulties to overcome, including poor structural stability and low power density. This paper summarizes the research progress of cobalt-based nanomaterials (cobalt oxide, cobalt hydroxide, cobalt-containing ternary metal oxides, etc.) as electrode materials for supercapacitors in recent years and discusses the preparation methods and properties of the materials. Notably, the focus of this paper is on the strategies to improve the electrochemical properties of these materials. We show that the performance of cobalt-based nanomaterials can be improved by designing their morphologies and, among the many morphologies, the mesoporous structure plays a major role. This is because mesoporous structures can mitigate volume changes and improve the performance of pseudo capacitance. This review is dedicated to the study of several cobalt-based nanomaterials in supercapacitors, and we hope that future scholars will make new breakthroughs in morphology design