Visualization Experiments Research Articles

Experimental and numerical study on the offshore adaptability of new FLH2 floating hydrogen liquefaction production storage and offloading unit

With the development of hydrogen production technology from offshore wind power and natural gas, the deep-sea energy interconnection system using hydrogen energy as the medium is constantly improving. The floating hydrogen liquefaction production storage and offloading unit (LH2-FPSO, FLH2) is an effective method for large-scale utilization of offshore hydrogen energy. By filling the heat exchanger with ortho-parahydrogen conversion catalyst, a new porous medium heat exchange channel is formed. Integrating the spiral wound heat exchanger with the ortho-parahydrogen catalytic conversion reactor can reduce the deck area of FLH2 process system and lower the investment cost of floating hydrogen liquefaction device. The performance of FLH2 can be influenced by the offshore wave and typhoon. In this paper, the methods of floating cryogenic visualization experiment, theoretical analysis and numerical simulation are conducted to study the coupled flow and heat transfer mechanism of working fluid applied in FLH2 under offshore conditions. The results show that the sea state has little influence on the ortho-parahydrogen conversion and cooling process of hydrogen in the porous heat exchange tube. The complex flow and heat transfer challenges brought by the integrated process of new floating hydrogen liquefaction and ortho-parahydrogen conversion have been overcome. With the effect of co-current shear of gas-phase mixed refrigerant, a large dry area will not appear on the outer wall surface of porous tube under offshore conditions. The FLH2 process system shows good adaptability at sea.

Bayesian Nonparametric Multivariate Mixture of Autoregressive Processes with Application to Brain Signals

One of neuroscience’s goals is to study the interactions between different brain regions during rest and while performing specific cognitive tasks. Multivariate Bayesian autoregressive decomposition (MBMARD) is proposed as an intuitive and novel Bayesian non-parametric model to represent high-dimensional signals as a low-dimensional mixture of univariate uncorrelated latent oscillations. Each latent oscillation captures a specific underlying oscillatory activity and, hence, is modeled as a unique second-order autoregressive process due to a compelling property, namely, that its spectral density’s shape is characterized by a unique frequency peak and bandwidth, parameterized by a location and a scale parameter. The posterior distributions of the latent oscillation parameters are computed using a Metropolis-within-Gibbs algorithm. One of the advantages of the MBMARD model is its higher robustness against misspecification, compared with standard models. The main scientific questions addressed by the MBMARD model relate to the effects of long-term alcohol abuse on memory. These effects were examined by analyzing the electroencephalogram records of alcoholic and non-alcoholic subjects performing a visual recognition experiment. The MBMARD model yielded novel and interesting findings, including the identification of subject-specific clusters of low- and high-frequency oscillations in different brain regions.

Heating-induced release of trapped bubbles from dead-end pore throats filled with nonvolatile liquid

The release of trapped bubbles from dead-end pore throats filled with nonvolatile liquid has widespread applications in gas–liquid reactors, radiators, foam flooding, ceramic sintering, and droplet microcarriers. As conventional pressure-driven flow cannot induce the transport of bubbles in dead-end pores, this paper explores the possibility of using heating to control the release of bubbles from dead-end pore throats. Visualization experiments of the microfluidics within a dead-end pore throat structure are conducted to address the release process of bubbles during heating. An increase in temperature causes dissolved gas in the solution to be transferred to the bubble, which enhances the bubble pressure and enables the bubble to pass through the pore throat. We analyze the effects of the initial bubble radius and initial temperature on the critical temperature Tcr at which the bubble passes through the pore throat. A larger initial radius does not necessarily make it more difficult for the bubble to pass through the throat, but there is a critical radius above which any increase in radius produces a lower value of Tcr. A theoretical model considering diffusion mass transfer, capillary forces, and corner film flows is developed, and this model is found to be in good agreement with the experimental results. Finally, we obtain three dimensionless numbers that can be used to predict Tcr. Our work provides guidance for the effective regulation of diffusive growth and the heating-induced release of bubbles from dead-end pore throats.

Heterogeneous Domain Adaptation Framework for Logging Lithofacies Identification

Summary Reservoir lithofacies type is an important indicator of reservoir quality and oiliness, and understanding lithofacies type can help geologists and engineers make informed decisions about exploration and development activities. The use of well-log data to establish machine learning models for lithofacies identification has gained popularity; however, the assumption that data are independent identical distribution followed by these models is often unrealistic. Additionally, there is a possible incompatibility between the training and test data in terms of feature space dimensions. We propose the heterogeneous domain adaptation framework for logging lithofacies identification (HDAFLI) to address these problems. The framework comprises three main contributions: (i) The denoising autoencoder feature mapping (DAFM) module is adopted to resolve the incompatibility issue in feature space between training and test data. The connection between training and test data can be effectively established to improve the performance and generalization ability. (ii) The transferability and discriminative joint probability distribution adaptive (TDJPDA) module addresses the issue of data distribution differences. It improves the transferability of training and test data by minimizing the maximum mean difference (MMD) of the joint probabilities of the source and target domains and enhances their discriminative ability by maximizing the joint probability MMD of different lithofacies categories. (iii) Bayesian optimization is used to optimize hyperparameters in the light gradient boosting machine (LightGBM) model for high computational efficiency in determining the best accuracy. We selected well-logging data from eight wells in the Pearl River Mouth Basin of the South China Sea to design four tasks and compared HDAFLI with various baseline machine learning algorithms and baseline domain adaptive algorithms. The results show that HDAFLI has the highest average accuracy among the four tasks. It is 19.76% and 8.94% higher than the best-performing baseline machine learning algorithm and baseline domain adaptive method among the comparison algorithms, respectively. For HDAFLI, we also conducted ablation experiments, time cost and convergence performance analysis, parameter sensitivity experiments, and feature visualization experiments. The results of ablation experiments show that the three modules of HDAFLI all play an active role, working together to achieve the best results. In addition, HDAFLI has a reasonable time cost, can become stable after several iterations, and has good convergence performance. The results of parameter sensitivity experiments confirm that the accuracy of HDAFLI does not change significantly with changes in hyperparameters, which is robust. The results of feature visualization experiments show that the data of the training set and the test set are concentrated together to a certain extent, which indicates that HDAFLI has completed the task of data distribution alignment very well. The findings of this study can help for a better understanding of how to address the challenge of reservoir lithofacies identification through a heterogeneous domain adaptation framework. By solving the problem of feature space incompatibility and data distribution difference between training data and test data, the application of HDAFLI provides geologists and engineers with more accurate lithofacies classification tools. This study has practical application value for reservoir quality assessment, oiliness prediction, and exploration and development decision-making.

Stereolithography of ceramic scaffolds for bone tissue regeneration: Influence of hydroxyapatite/silica ratio on mechanical properties

In this paper, the results obtained in the development of ceramic resin feedstock for stereolithography are shown. Hydroxyapatite and silica are used as source of ceramic. Hydroxyapatite is extracted from bovine bone, which enhances bioactivity of ceramic scaffold. The influence of hydroxyapatite amount in polymer-based slurry on the viscosity and printability of feedstock is explored. Hydroxyapatite and silica containing scaffolds are successfully obtained by stereolithography. Influence of hydroxyapatite/silica ratio on the bioactivity, biodegradability and mechanical properties of the scaffolds is also studied. It was observed that higher concentrations of hydroxyapatite led to improved mechanical strength of the scuffolds but increased viscosity of the slurry, affecting printability. Cell viability assays and cell visualization experiments indicated that the scaffolds not cause significant cell toxicity.

A Visualization Experiment on Icing Characteristics of a Saline Water Droplet on the Surface of an Aluminum Plate

When the offshore device, such as an offshore wind turbine, works in winter, ice accretion often occurs on the blade surface, which affects the working performance. To explore the icing characteristics on a microscale, the freezing characteristics of a water droplet with salinity were tested in the present study. A self-developed icing device was used to record the icing process of a water droplet, and a water droplet with a volume of 5 μL was tested under different salinities and temperatures. The effects of salinity and temperature on the profile of the iced water droplet, such as the height and contact diameter, were analyzed. As the temperature was constant, along with the increase in salinity, the height of the iced water droplet first increased and then decreased, and the contact diameter decreased. The maximum height of the iced water droplet was 1.21 mm, and the minimum contact diameter was 3.67 mm. With the increase in salinity, the icing time of the water droplet increased, yet a minor effect occurred under low temperatures such as −18 °C. Based on the experimental results, the profile of the iced water droplet was fitted using the polynomial method, with a coefficient of determination (R2) higher than 0.99. Then the mathematical model of the volume of the iced water droplet was established. The volume of the iced water droplet decreased along with temperature and increased along with salinity. The largest volume was 4.1 mm3. The research findings provide a foundation for exploring the offshore device icing characteristics in depth.

Experimental Study on the Evolution Law of the Mechanical and Pore Characteristic Parameters of Set Cement under High- and Ultra-High-Temperature Treatments

Cement has been widely used as a structural material in many underground projects, and these projects often face high- or ultra-high-temperature environments, leading to the deterioration of the mechanical, porosity, and permeability properties of set cement, thereby increasing the risk of instability of underground structures. In response to this, two new temperature-resistant cement slurry systems were designed. Experiments were conducted on the changes in porosity and permeability of set cement after thermal treatment using low-field nuclear magnetic resonance technology (NMR), visual studies of pore and crack development were carried out using the argon-ion polishing field emission scanning electron microscopy (FE-SEM) and computed tomography (CT) methods. The research results show that as the thermal treatment temperature continued to rise, the compressive strength first increased (25 °C–200 °C) and then decreased (200 °C–600 °C). The porosity of the set cement first decreased (25 °C–115 °C) and then increased (115 °C–600 °C), and the penetration first slowly increased (25 °C–400 °C) and then rapidly increased (400 °C–600 °C). Visualization experiments were conducted on micro-cracks and the pore distribution of the set cement under high- and ultra-high-temperatures, which proved the evolution law of these characteristic parameters. The research results have vital reference significance for the protection of the structural stability of cement components when encountering high-temperature environments.

A multi-modal feature fusion classification model based on distance matching and discriminative representation learning for differentiation of high-grade glioma from solitary brain metastasis

To explore the performance of a new multimodal feature fusion classification model based on distance matching and discriminative representation learning for differentiating high-grade glioma (HGG) from solitary brain metastasis (SBM). We collected multi-parametric magnetic resonance imaging (MRI) data from 61 patients with HGG and 60 with SBM, and delineated regions of interest (ROI) on T1WI, T2WI, T2-weighted fluid attenuated inversion recovery (T2_FLAIR) and post-contrast enhancement T1WI (CE_T1WI) images. The radiomics features were extracted from each sequence using Pyradiomics and fused using a multimodal feature fusion classification model based on distance matching and discriminative representation learning to obtain a classification model. The discriminative performance of the classification model for differentiating HGG from SBM was evaluated using five-fold cross-validation with metrics of specificity, sensitivity, accuracy, and the area under the ROC curve (AUC) and quantitatively compared with other feature fusion models. Visual experiments were conducted to examine the fused features obtained by the proposed model to validate its feasibility and effectiveness. The five-fold cross-validation results showed that the proposed multimodal feature fusion classification model had a specificity of 0.871, a sensitivity of 0.817, an accuracy of 0.843, and an AUC of 0.930 for distinguishing HGG from SBM. This feature fusion method exhibited excellent discriminative performance in the visual experiments. The proposed multimodal feature fusion classification model has an excellent ability for differentiating HGG from SBM with significant advantages over other feature fusion classification models in discrimination and classification tasks between HGG and SBM.

Content policy and access limitations on commercial neural networks as an incentive to artivism

This article employs a case‐study method to investigate the artivism neural network community concentrated on Twitter (since renamed X), which has been ideologically influenced by the content policy and limitations of OpenAI. Today, many young artists using machine learning technologies in their artworks (Midjourney, Stable Diffusion, Kandinsky) note that despite significant progress in the field of neural network generators of image through prompts present in museums and exhibitions of contemporary digital art, a significant number of artworks are still made chiefly using outdated text-to-image algorithms created in 2021. These neural networks continue to be popular in art to this day. The reasons for the sustainability of such practices can be found in the soft ideological conflict between artists and OpenAI in 2021. At that time, neural networks had not yet become mainstream, and the dominant theme was deep fakes, which became the basis for a comprehensive discussion about the possibilities and consequences of implementing AI algorithms in modern society. A series of scandals related to the work of neural networks alerted businesses, which feared the reputational costs of neural network errors and biases. At the same time, the existing discourse on freedom of speech, thought, and self-expression in contemporary art has led to ideological conflict, as the creators have introduced constraints on tools of artistic expression. Previously, the actions of artists were not moderated by technical means. Thus, the community did not accept this state of affairs, and as a result of cooperation and “collective intelligence” created, on the GitHub and Google Colab platforms, their own algorithms with open code, with which everyone could carry out their visual experiments. Artists face the ideological question of fighting globalism and anti-progress in art to be outside the system but to riot against it. This process led to a division of artistic practises in neural network art, outlined by media artist Ryan Murdock as a gateway to text-guided visual art by the hacker effort of 2021 or the modern generation of algorithm text-to-images (after 2022).

Analysis of thermal storage behavior of composite phase change materials embedded with gradient-designed TPMS thermal conductivity enhancers: A numerical and experimental study

Phase change materials (PCMs) exhibit considerable potential for utilization in energy storage and temperature regulation applications, primarily attributed to their notable latent heat capacity. Nevertheless, the intrinsically limited thermal conductivity of PCMs necessitates the use of thermal conductivity enhancers (TCEs) that possess adjustable features to compensate for greater heat storage efficiency. Porous structures with flexible design freedom have garnered growing interest in contrast to traditional random foams, owing to their significantly larger surface areas and fully interconnected pore networks. This study fabricated three polar form-designed triply periodic minimal surfaces (TPMS) porous structures using selective laser melting (SLM) based on various radial density gradients, namely the uniform density, the linear gradient, and the Boltzmann gradient. The TPMS porous structures were incorporated as TCEs within a paraffin matrix to form composite TPMS-PCMs. The melting behavior of composite TPMS-PCMs during the charging process was investigated by employing both visual experiments and numerical methods. A thorough analysis was undertaken regarding the progression of solid-liquid phase interfaces, temperature distribution, convection distribution, and heat storage rate to elucidate the mechanisms that contribute to enhanced heat transfer. The findings indicate that the configuration of the density gradient has a notable impact on the melting behavior of composite TPMS-PCMs by tuning heat transfer paths. The heat storage rate of the linear gradient case is the highest among the three, reaching 12.1 W, 1.6 times that of the uniform density case, and twice that of the Boltzmann gradient case. Although the Boltzmann gradient case has the lowest heat storage rate, it demonstrates exceptional performance in terms of temperature uniformity. The average temperature gradient along the radius during melting is 348.6 °C/m, which is only 59% observed in the linear gradient case and 56% in the uniform density case. These findings substantiate the effectiveness of the radial gradient density design in the control of the thermal storage process of composite TPMS-PCMs. They serve as a reference for optimizing thermal storage and temperature control systems that rely on latent heat storage in the future.

Flow pattern-based heat transfer analysis of microchannel flow boiling: An experimental investigation

The present study investigates the flow boiling heat transfer and flow pattern of R245fa in a smooth, horizontal microchannel with an inner diameter of 1 mm. The experiments cover a range of mass flux from 300 to 700 kg/m2s and heat fluxes varying between 10 and 94 kW/m2, with corresponding saturation temperature of 23–54 °C. Heat transfer experiment results indicate that the local heat transfer coefficient (HTC) presents two distinct variation trends under different heat and mass flux conditions. In addition, the heat flux is positively correlated with the local HTC at each measure point. Visualization experiment results show that annular flow forms at low vapor quality and significantly influences heat transfer as the primary flow pattern. The flow boiling heat transfer of R245fa in the 1 mm microchannel can be characterized by three regimes: bubble/slug regime, liquid film evaporation regime, and intermittent dryout regime. Thin liquid film evaporation and intermittent dryout during annular flow predominately contribute to heat transfer. Finally, the experimental HTC is compared with five different predictive methods, revealing that the three-zone model proposed by Thome et al. [46] holds immense potential for estimating the local HTC in the microchannel.

The effect of baffles on vertical wall PCM to enhance natural convection

The objective of this study is to enhance convective heat transfer within phase change materials (PCM) using baffles on a vertical wall. PCMs have major drawbacks of low thermal conductivity, high viscosity, and limited natural convection. To address these issues, we investigated a passive approach to enhance natural convection with baffles. The new approach is to arrange multiple baffles with gaps on the opposite side of the heated vertical wall. This placement can minimize vertical temperature difference by blending upward-flowing hot liquid PCM with downward-flowing cold liquid PCM across the gaps and also increase circulating velocity by shortening path of circulation cell through sections divided by baffles. Visualization experiments of shadowgraphy and particle image velocimetry (PIV) were conducted to compare the case with baffle (WB) against the case without baffle (NB). The presence of the baffles lowered the average temperature difference in the horizontal direction by 40%. The WB case reduced the temperature difference in the vertical direction by 50%, compared with the NB case. Furthermore, comparison of the WB with NB showed that at the heat power levels of (4, 6, and 8) W, the convection coefficient increased by up to (28, 34, and 27)%, respectively. Therefore, by changing the internal flow pattern, the baffles on the vertical wall improved convective heat transfer performance.

Unsteady assessment and alleviation of inter-blade vortex in Francis turbine

Inter-blade vortex refers to a specific type vortex cavitation observed in Francis turbines under partial loads and its adverse impact is widely recognized as a crucial factor that limits the safety and stability of hydraulic turbines. The present study endeavors to examine the spatiotemporal evolution attributes of inter-blade vortex and its contribution to the generation of unstable pressure fluctuations. To achieve this, a comprehensive investigation is conducted using a reduced-scale Francis model turbine with low head, combining numerical investigations and visualization experiments. The study demonstrates that the vapor volume associated with the inter-blade vortex experiences periodic pulsation, with a frequency proximate to the rotational frequency of the runner. Within the turbine runner, cavitation exhibits a dynamic cycle of incipience, growth, expansion, and localized collapse. The most remarkable cavitation disintegration occurs at the convergence point of the trailing edge of the runner blade and the band, wherein the most pronounced amplitude of pressure fluctuation is also discerned. In addition, this research establishes a direct correlation between pressure fluctuations and vapor volume, revealing that the acceleration of the vapor volume is accountable for the occurrence of pressure fluctuations with heightened magnitude. Furthermore, an optimization campaign successfully reduces the cavitation volume by 88.58% and 78.99% at two specific points of interest, resulting in the nearly complete elimination of high-amplitude pressure pulsations. Building upon these findings, data mining techniques are implemented to identify that the blade profile at a spanwise height of 0.75 significantly influences the enhancement of turbine hydraulic performance. Additionally, it has been ascertained that the design parameter governing the geometric placement of the blade trailing edge plays a pivotal role in reducing the intensity of the inter-blade vortex. This study yields invaluable insights into the underlying mechanism of unsteady phenomena induced by inter-blade vortex and formulates a hydraulic optimization approach capable of enhancing the operating stability of the Francis turbine.

A project-based learning (PBL) on gas dynamic concepts using hydraulic analogy technique

This article suggests the hydraulic analogy technique as a cost-effective approach for flow visualization in fluid mechanics, particularly in dealing with challenges related to supersonic flow, such as shock waves and flow past wedges. The project-based learning approach is adopted to engage students in the study effectively. This active learning method allows students to actively participate in research activities, from setting project goals to designing and executing experiments. The article highlights the positive impact of project-based learning on students’ learning outcomes through internal and external evaluations. The study shows that project-based learning enhances technical competence and encourages a lifelong passion for learning. The cost-effectiveness of the hydraulic analogy method inspires neighbouring academic institutions to consider similar approaches, further promoting the use of practical and affordable solutions for flow visualization experiments.

Experimental and theoretical study on liquid-vapor behavior characteristics near CHF

Liquid-vapor behavior characteristics near CHF conditions are investigated through flow visualization experiments and theoretical analysis. The detailed liquid-vapor behavior near CHF is captured by high-speed camera in this paper. With the increase of heat flux, the periodic vapor layer occurs due to numerous large bubble coalescence. A three-layer structure is observed close to CHF conditions, i.e., liquid film, vapor layer, and liquid core. The physical triggering mechanism of CHF is the complete evaporation at the liquid film wave trough position close to the end of the heating rod. Furthermore, based on the separated flow model and instability analysis, respective prediction models for essential liquid-vapor characteristics, including thickness of vapor layer, interfacial wavelength, and the maximum thickness of liquid film, are developed. The predicted results are in good prediction performance with MAE of 16.9 %, 12.8 %, and 26.1 % compared to experimental results, respectively. The relevant research in this paper provides an important foundation for further development of the mechanistic CHF model.

Investigation of thermo-hydrodynamic characteristics in micro-oscillating heat pipe by alternatively-arranged ratchet microchannels

In this study, three flat-plate micro-oscillating heat pipes (FPMOHPs) with different alternatively-arranged ratchet microchannels were designed and fabricated. Then, a combined visualization and thermal experiment was conducted to examine the regulation of thermo-hydrodynamic characteristics in the FPMOHPs by the alternatively-arranged ratchet microchannels, via the comparison with a traditional FPMOHP with completely uniform microchannel. The detailed fluid flow motions and corresponding temperature oscillations as well as thermal performance of the FPMOHPs were illustrated and analyzed to clarify the advantages of this microchannel design. It is indicated that the oscillating frequency and velocity of the fluid are diminished by the ratchet microchannels because of the higher flowing resistance. However, the ratchet microchannels can trigger the stronger flow disturbance, leading to the ascending “wave-like” annular flow broken into the dispersive slugs or bubbles with irregular shape. Among the three different ratchet microchannels, the asymmetric ratchet structure with the larger contraction-expansion ratio near the inlet of the fluid can trigger more intense boiling in the evaporator, which also energizes the downward flow from the condenser. Furthermore, the additional actions on the bubbles/slugs caused by the Laplace pressure jump in three different ratchet microchannels play distinct roles in upward and downward bubble/slug flow, i.e., driving force or resistance force or little role, which determine the most favorable ratchet structure for the fluid flow and heat transfer in the FPMOHPs. In general, the positive effects of the enhanced boiling and the stronger fluid flow disturbance caused by the ratchet microchannel dominates the negative effect of growing flow resistance, leading to the enhanced convective heat transfer. Therefore, the equivalent thermal conductivity can be improved up to 33.8 % on average as compared to the traditional FPMOHP with completely uniform rectangular channel.

Supporting the Development of Students’ Scientific Literacy

ABSTRACT Science teachers are increasingly encouraged to critically engage their students with scientific knowledge and expertise, with the expectation that such instructional practices will support the development of scientific literacy (SL). Drawing on Bildung framework, this qualitative study was conducted in Tanzania to explore how science teachers’ classroom practices facilitate the development of students’ SL. Data were collected through semi-structured interviews and non-participant classroom observations with science teachers and students from six secondary schools. The study has identified five instructional practices that were used to support students’ development of SL, namely guided reading, code-switching, educational print and visual aids, science experiments, and science projects. While there is evidence that the instructional practices used provided opportunities for students to contribute their thinking, experience and understanding to the science learning, the instructional practices were mostly print-based, paper-based and teacher-led, resulting in little engagement in active scientific thinking and literacy learning. Overall, the knowledge base developed by this study is of practical use to science teachers and educators in making decisions about appropriate instructional practices and what should be the regular focus of pre-service teacher education and professional development programs.

Research on the Influence of Heterogeneity and Viscosity on the Fluid Intrusion Mechanism of the Water Flooding Process Based on the Microscopic Visualization Experiment.

The flow law of immiscible fluids in porous media plays an important role in the development of oil and gas fields. In the process of water flooding reservoir development, when the water phase displaces the oil phase, a fluid with higher viscosity, as a fluid with lower viscosity, the oil-water interface will always be unstable, resulting in different fingering effects. After water flooding, the distribution law of oil and water in the reservoir is mainly affected by the fluid intrusion mechanism. Due to the difference of capillary force, viscous force, and other microscopic forces, the fluid intrusion mechanism is mainly divided into two types: viscous fingering and capillary fingering. At the same time, due to the influence of reservoir heterogeneity, the fingering effect in the process of water displacement in porous media will be influenced to a certain extent. Based on the two-dimensional microscopic visualization experiment, this paper extracted the variance of the static parameter G in the capillary number calculation method of the two-dimensional microscopic model to represent the heterogeneity and conducted displacement experiments with different viscosities and flow rates to study the influence of the flow rate, viscosity, and heterogeneity on the results of water flooding. The experiments found that as for the influence of flow velocity, with the increase of flow velocity, that is, with the increase of capillary number, the recovery degree decreases first and then increases. As for the influence of viscosity, from a numerical point of view, the displacement efficiency and conformance coefficient of the low-viscosity group are higher than those of the high-viscosity group. From the trend, with the increase of the capillary number, the displacement efficiency of both the low-viscosity and high-viscosity groups increases, while the conformance coefficient decreases first and then increases, indicating that capillary fingering and viscous fingering can occur in different viscosity reservoirs. As for the influence of heterogeneity, the conformance coefficient of the water flooding decreases with the increase of heterogeneity, and the viscous pointing trend caused by heterogeneity is stronger, resulting in an uneven water injection sweep and higher oil displacement efficiency within the swept area. It can be seen from the fluid intrusion mechanism diagram that with the increase of heterogeneity, the viscous fingering trend becomes more obvious; with the increase of viscosity, the fluid intrusion mechanism boundary moves down and the viscous fingering trend becomes more obvious.

A Chola Sex Party: Anal And Concha Art

This piece explores the visual art and performance of Wynnie Mynerva (1992–), interpreting their aesthetic use of violence and sadism. My reading of Wynnie’s work articulates cholanness in relation to Blackness, unearthing the colonial etymology of “cholo.” I argue that the body of chola women is at very center of the “abigarrado cholo sex,” a sexual/reproductive system of extraction of labor and pleasure. Wynnie’s visual experimentation toys with castration and revenge, and with the non-generative pleasures of anal sex and anti-natalism. To think through the contemporary uses of chola, I use the work of Black feminist scholars in the US and the Caribbean, establishing hemispheric connections with Latin American feminist scholars and activists.

Analysis of low-speed blade coating flows

From industrial-scale production to small-scale fabrication of functional films, the blade coating method is used widely to apply a uniform thin liquid film on a moving substrate. However, conventional hydrodynamic models are inadequate for laboratory-scale low-speed blade coating, where capillary forces dominate. In this study, the low-speed blade coating of non-evaporative Newtonian fluids was investigated in experimental, computational and analytical approaches. The transient free boundary problem was solved utilizing a two-dimensional finite element method, and a simple viscocapillary model was developed to describe the viscous stress and capillary forces within the puddle, and predict the thickness of the wet film as a function of the speed of the substrate. Comparing the predicted film thickness with the computational results, and a flow visualization experiment of blade coating with silicone oil, respectively, confirmed the model's validity. The study indicates that the proposed model may be a useful tool for optimizing laboratory coating processes, as it provides a greater understanding of the low-speed blade coating system on a laboratory scale.