Pattern Size Research Articles

Experimental study of fluid displacement and viscous fingering in fractured porous media: effect of viscosity ratio

Abstract Viscous fingering instability has been analyzed through empirical studies using miscible flow displacement in fractured porous media. While significant research has been conducted on viscous fingering, limited information is available regarding its behavior in fractured porous structures. The experiments were conducted in rectangular porous models with fractures oriented at $${0}^\circ $$ 0 ∘ , $${45}^\circ $$ 45 ∘ , and $${90}^\circ $$ 90 ∘ , to investigate how fracture orientation influences fluid displacement, where both channeling and fingering mechanisms play significant roles. This paper, which is the second part of a previous study, places particular emphasis on the impact of the viscosity ratio, a crucial parameter in determining the complexity of the fingering patterns. Quantitative parameters such as sweep efficiency, tip location, and breakthrough time were evaluated and analyzed using image processing techniques. The results indicate that increasing the viscosity ratio leads to more complex finger formations. Additionally, as the injection rate increases, the size of the finger patterns slightly increases, while the channeling effect becomes less pronounced. Notably, fractures aligned at $${0}^\circ $$ 0 ∘ had the most significant impact on the rate of sweep efficiency and tip location, increasing the tip velocity of the fingers by up to 90%.

Parameter estimation for cellular automata

Abstract Self-organizing complex systems can be modeled using cellular automaton models. However, the parametrization of these models is crucial and significantly determines the resulting structural pattern. In this research, we introduce and successfully apply a sound statistical method to estimate these parameters. The decisive difference to earlier applications of such approaches is that, in our case, both the CA rules and the resulting patterns are discrete. The method is based on constructing Gaussian likelihoods using characteristics of the structures, such as the mean particle size. We show that our approach is robust for the method parameters, domain size of patterns, or CA iterations.

The Prevalence of Tear Patterns and Their Effects on Tendon Healing After Arthroscopic Surgery in Patients With Full-Thickness Rotator Cuff Tears.

To achieve successful anatomic rotator cuff repair with minimal tension, both the tear pattern and tear size should be considered. However, little information is available concerning the frequency of tear patterns and their effects on tendon healing. To evaluate the distribution of tear patterns in full-thickness rotator cuff tears and whether these patterns affect tendon healing after arthroscopic repair. Case-control study; Level of evidence, 3. Between 2014 and 2021, patients who underwent arthroscopic surgery for symptomatic full-thickness rotator cuff tears with a minimum 2-year follow-up with postoperative magnetic resonance imaging or ultrasound were retrospectively reviewed. After the debridement of degenerative tendon tissue during arthroscopic surgery, the tear pattern was classified as crescent, U, or anterior or posterior L shaped. Intergroup differences in clinical and radiological characteristics were analyzed. In the subgroup analysis, patients were divided into 2 subgroups: small-to-medium or large-to-massive tears. Among the 1037 patients with a full-thickness rotator cuff tear, the most common tear pattern was crescent shaped (39.6%), followed by posterior L, U, and anterior L shaped (26.0%, 21.4%, and 12.9%, respectively). In the subgroup analysis, 713 patients (68.8%) had small-to-medium tears, while 324 (31.2%) had large-to-massive tears. The proportion of large-to-massive tears was significantly higher for the anterior L-shaped tear pattern than for the other tear patterns (24.8%, 28.8%, 52.2%, and 32.6% for crescent, U, and anterior and posterior L shaped, respectively; P < .001). The anterior L-shaped tear pattern had a significantly higher retear rate than the other tear patterns in small-to-medium tears (7.8%, 13.0%, 28.0%, and 10.6% for crescent, U, and anterior and posterior L shaped, respectively; P < .001). The rate of revision surgery because of a symptomatic retear within 2 years after primary surgery was significantly higher for the anterior L-shaped tear pattern than for the other tear patterns (3.8%, 7.5%, 21.6%, and 0.0% for crescent, U, and anterior and posterior L shaped, respectively; P = .002). The prevalence of tear patterns varied depending on the tear size. In small-to-medium tears, the anterior L-shaped tear pattern had the lowest incidence among the tear patterns; however, it had a significantly higher retear rate. Furthermore, the anterior L-shaped tear pattern had a higher incidence of retears requiring early revision surgery than the other tear patterns.

Efficient and Effective Detection of Repeated Pattern from Fronto-Parallel Images with Unknown Visual Contents

The effective detection of repeated patterns from inputs of unknown fronto-parallel images is an important computer vision task that supports many real-world applications, such as image retrieval, synthesis, and texture analysis. A repeated pattern is defined as the smallest unit capable of tiling the entire image, representing its primary structural and visual information. In this paper, a hybrid method is proposed, overcoming the drawbacks of both traditional and existing deep learning-based approaches. The new method leverages deep features from a pre-trained Convolutional Neural Network (CNN) to estimate initial repeated pattern sizes and refines them using a dynamic autocorrelation algorithm. Comprehensive experiments are conducted on a new dataset of fronto-parallel textile images as well as another set of real-world non-textile images to demonstrate the superiority of the proposed method. The accuracy of the proposed method is 67.3%, which represents 20% higher than the baseline method, and the time cost is only 11% of the baseline. The proposed method has been applied and contributed to textile design, and it can be adapted to other applications.

Tolerable patterning in nanoimprint lithography by one-pass breakthrough etching of residual layer and spin-on-glass

Abstract In nanoimprint lithography (NIL), a residual layer inherently exists under the NIL resist features and must be removed in later etching steps. The subsequent etching process, known as breakthrough etching, leads to variations in the device pattern sizes and disrupts process integration because of NIL resist pattern loss. It was reported previously that the residual layer thickness (RLT) should be less than half the feature height (FH) for subsequent high-precision etching. In this work, we develop a one-pass etching process using an atomic-scale cycle stepped etching technique that passes through the residual layer to the spin-on-glass and demonstrate that the process can maintain the pattern width, regardless of RLT variations within the 12–32 nm thickness range. Even in the case of a 32-nm-thick RLT corresponding to 76% of the feature height (0.76 FH), good electrical performances were obtained without electrical failures in the half-pitch 26 nm line-and-space W-damascene interconnect patterns.

Hybrid structure design of expanded steel mesh to enhance the tensile performance of fiber‐reinforced composites

AbstractMetal hybrid structures with fiber‐reinforced composites optimize strength, weight, toughness, and durability while minimizing cracks and retaining structural integrity. The present investigation evaluates the tensile performance of hybrid composites manufactured from expanded steel wire meshes and fiber‐reinforced epoxy versus pure glass fiber (GE). Hybrid specimens were fabricated with steel mesh of varying pattern sizes inserted at two different positions within the composites and exposed to two loading layouts. The results indicated that replacing GE layers with steel mesh decreased specimen density by 6.25% while increasing ductility and energy absorption. Medium‐size mesh provided the most effective performance, enhancing tensile strength, peak load, energy absorption, and stiffness by an average of 18.9% over other sizes. The outer layer configuration was superior to the inner layer, improving peak strength, failure strain, stiffness, and absorbed energy by up to 25.6%. Moreover, vertical loading boosted overall performance by an average of 28.5% compared with horizontal loading. The SO2 configuration was selected via Grey Relational Analysis to be the most effective arrangement.Highlights Insight into the impact of using expanded steel mesh in GE composites. Analyzing the effect of mesh size and laminating order on tensile performance. Effect of loading layouts on the overall performance of the hybrid composites. Examining damage morphologies to assess the interlayers interaction. Superior results in terms of peak load, failure strain, and toughness.

Nickel oxide nanoflowers based resistive sensors for detecting methyl salicylate and linalool

Abstract Crop health monitoring is crucial for early detection of biotic stress, which can significantly impact crop yield and quality. This work reports detection of two volatile organic compounds (VOCs) - methyl salicylate and linalool which have promising utility in agriculture including indication of biotic stresses in crops. NiO nanoflowers were synthesized using a solvothermal method. The polycrystalline nature of the metal oxide was confirmed using X-ray diffractometer pattern and crystallite size was found to be 16.8 nm. The bandgap of the NiO nanoflowers were found to be 3.47 eV when using UV-Visible spectrometer. The morphology of the nanomaterial was confirmed using field emission scanning electron microscope. Brunauer–Emmett–Teller confirmed the surface area of NiO to be 39.6 m2 g−1. X-ray photoelectron spectroscopy confirms the successful synthesis of nickel oxide (NiO) with distinct Ni 2p peaks at 855.5 eV and 873.3 eV, along with O 1s lattice oxygen at 529.6 eV. Satellite peaks at 861 eV and 879 eV further validate the Ni(II) oxidation state, indicating a well-defined crystalline structure. The NiO nanoflower was seen to exhibit temperature modulated dual selectivity as it exhibited the highest response to linalool at 300 °C whereas for methyl salicylate the optimum sensing temperature was found to be 250 °C. The response of NiO was found to be varying from 5.2–40% towards 5–40 ppm of linalool at 300 °C and between 2.5–13.5% towards 10–40 ppm of methyl salicylate at 250 °C. The response times and recovery times of the sensor varied from 260 s to 160 s and 170 s to 650 s, respectively for 5 to 40 ppm of linalool. For 10 to 40 ppm methyl salicylate, the response times and recovery times ranged from 280 s to 230 s and 220 s to 1203 s, respectively. The sensor was found to be highly selective towards linalool at 300 °C but the response of NiO was found to be comparable for both methyl salicylate and linalool at 250 °C. A simple algorithm based on steady state responses of the sensor at 250 and 300 °C could be developed for accurate prediction of both the VOCs.

Status and ecology of forest antelopes and other large mammals in the Ngoyla Faunal Reserve, Cameroon

Abstract Ungulates have undergone major declines in Central and West African forests as a result of bushmeat trade and habitat loss. Monitoring forest ungulate status is a critical conservation need. We undertook a systematic camera-trap survey of the Ngoyla Faunal Reserve within the ∼11,000 km2 Dja-Ngoyla Complex, part of the critical TRIDOM forest landscape in Central Africa. We deployed cameras at 36 sites over 2,734 camera-trap days. We recorded 3,307 independent detections of 12 species of forest ungulates. The Peters’ duiker and blue duiker were the most abundant, accounting for 71 % of all ungulate detections, both with occupancy &gt;85 %. The black-fronted duiker and white-bellied duiker were relatively widespread but rare. There were very few detections of Bates’ pygmy antelope, sitatunga, forest buffalo, and bongo. These findings are similar to our baseline population estimates of ungulates in the neighbouring Dja World Heritage site. Our study provides further evidence of ecological partitioning among the more abundant duikers based on activity pattern and body size. The Dja-Ngoyla Complex is integral to the 178,000 km2 TRIDOM conservation landscape. The landscape is a global conservation priority for securing the future of great apes, forest elephant, a community of forest ungulates, and other threatened species in the region.

A systematic review and meta-analysis of eyespot anti-predator mechanisms.

Eyespot patterns have evolved in many prey species. These patterns were traditionally explained by the eye mimicry hypothesis, which proposes that eyespots resembling vertebrate eyes function as predator avoidance. However, it is possible that eyespots do not mimic eyes: according to the conspicuousness hypothesis, eyespots are just one form of vivid signals where only conspicuousness matters. They might work simply through neophobia or unfamiliarity, without necessarily implying aposematism or the unprofitability to potential predators. To test these hypotheses and explore factors influencing predators' responses, we conducted a meta-analysis with 33 empirical papers that focused on bird responses to both real lepidopterans and artificial targets with conspicuous patterns (i.e. eyespots and non-eyespots). Supporting the latter hypothesis, the results showed no clear difference in predator avoidance efficacy between eyespots and non-eyespots. When comparing geometric pattern characteristics, bigger pattern sizes and smaller numbers of patterns were more effective in preventing avian predation. This finding indicates that single concentric patterns have stronger deterring effects than paired ones. Taken together, our study supports the conspicuousness hypothesis more than the eye mimicry hypothesis. Due to the number and species coverage of published studies so far, the generalisability of our conclusion may be limited. The findings highlight that pattern conspicuousness is key to eliciting avian avoidance responses, shedding a different light on this classic example of signal evolution.

Some morphometric traits of Rita rita from Southern Punjab, Pakistan

In this research work, forty five (45) specimens of Rita rita inhabiting River Chenab, one of the five rivers of the Punjab Province, were evaluated to observe morphometric and proximate composition of the fish specimens. To analyze the influence of biological factors, condition factor was determined based on body constituents using regression equations. Various morphometric characters i.e. total length (TL), standard length (SL), fork length (FL), head length (HL), head width (HW), body girth (BG), body depth (BD), dorsal fin length (DFL), pectoral fin length (PtFL), pelvic fin length (PvFL), anal fin length (AFL), dorsal fin base (DFB), anal fin base (AFB), caudal fin length (CFL), and caudal fin width (CFW) were measured to know their correlation with the size and types of growth pattern. Morphometric analysis showed isometric growth pattern of the fish in the current study.

Optimum selection of nature-inspired texture pattern for cutting tool surface using an integrated multi-criteria decision-making approach: a comparative analysis

Purpose This paper aims to focus on the selection of an appropriate nature-inspired texture pattern for cutting tool tribological surface. The selection process uses the recognized skin textures of different snakes scrolling on highly rough and projected surface conditions to analyze suitability of texture based on the texture geometry and machining conditions. The work also aims to propose a texture pattern selection process to incorporate on cutting tool tribological surface. Design/methodology/approach The selection of alternative nature-inspired texture patterns based on the texture pattern geometry and machining properties leads to a multi-criteria decision-making problem. Thirteen criteria are considered for selecting an appropriate texture pattern among 14 alternatives, i.e. nature-inspired texture patterns. In the present work, an integrated analytical hierarchy process (AHP)-TOPSIS, AHP-multi-objective optimization on the basis of ratio analysis (MOORA) and AHP-Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) approaches have been proposed for the selection of an appropriate nature-inspired texture pattern. AHP is used for the formulation of decision-making matrix and criteria weight calculations and ranking of alternatives is done by three methods. Spearman’s correlation compared and found positive relations between rank assigned by methods. Experimental validation is done in Lathe for selected texture effects. Findings The texture parameters C-1 (Width of texture) and C-2 (Depth of texture) are found significant, while T-2 (Blended Krait) and T-6 (Banded Racer-1) texture is found optimal to generate on cutting tool surface. Research limitations/implications Only some nature-inspired texture patterns have been recognized before the selection; an infinite number of textures are available in nature. The size of the texture pattern is difficult to identify by the selection process because each texture pattern may have different effects on tribological surfaces. Practical implications The proposed selection methodology of nature-inspired texture patterns will help identify optimal texture geometry for specific tribological applications. The nature-inspired texture patterned tool has a significant impact on the cutting force and temperature due to its tribological effect on the cutting tool surface; it decreases the power required for machining. The machining characteristics like roughness are found to decrease by using nature-inspired texture patterned tools. Social implications Various nature-inspire texture studies to generate specific effects on the tribological surfaces may be started study for the surface of aircraft, ships, bearings, etc. Small and big fabrication industries may benefit by decreasing the cost of machining using nature-inspired texture-patterned tools. Research society will pay attention to nature’s inspiration. Originality/value Novel snake-skin-inspired texture patterns are recognized and hybrid MCDM methods are proposed to select optimal texture pattern. Proposed method used single time normalization to effectively rank the alternatives. The insights gained from this research can be extrapolated to address similar challenges in selecting nature-inspired textures for various applications. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0163/

Enhanced Electromagnetic Wave Absorption in Hexaferrite/LSMO Bilayers: Optimization of Structural Design Using a High Frequency Software Simulation

In this study, the electromagnetic (EM) wave absorption properties of a two-layered structure composed of La0.7Sr0.3MnO3-epoxy (10 wt.%) (LSMO) and SrFe9.5Co1.25Ti1.25O19-epoxy (10 wt.%) (SFCTO), both exhibiting distinct high-frequency magnetic and dielectric properties, were investigated using a High Frequency Simulation Software (HFSS) simulation tool. LSMO had a high dielectric constant (ε' &gt;30) within the measurement range (0.1-18 GHz), indicating that dielectric loss mechanisms primarily contribute to EM wave absorption. In contrast, SFCTO is a material capable of significantly absorbing EM waves near 10 GHz due to ferromagnetic resonance (FMR). The simulations were validated by comparing the measured and simulated reflection losses (RL) of an unpatterned LSMO/SFCTO bilayer. The RL spectra were examined by varying the layer thickness and pattern size in three configurations: a continuous LSMO/SFCTO structure, a cross-patterned LSMO on SFCTO, and a square-patterned LSMO on SFCTO. In the continuous LSMO/SFCTO structure, tunable absorption frequency bands were achieved by adjusting the layer thickness. However, it was difficult to achieve broadband absorption due to the reflective characteristics of the high dielectric LSMO layer. The cross-patterned LSMO structure on SFCTO demonstrated broader bandwidth absorption, with layer thickness being more influential than pattern width. The square-patterned LSMO on SFCTO exhibited the best broadband EM wave absorption (max Δf = 7.39 GHz). These results suggest that broader absorption is achievable by partially covering the high-dielectric layer with patterns on a hexaferrite sheet.

Pattern size relative to oil droplet size effect on oil fouling in nanofiltration

Membrane fouling is a major issue in many membrane applications. There are numerous methods used in attempt to mitigate membrane fouling, with one method being membrane surface patterning. However, it is still unclear how the ratio of foulant size to pattern size affects membrane fouling. In this study, we investigated constant foulant size while varying the pattern size on the membrane surface to be smaller than (300-nm), equal to (10-μm), and larger than (50-μm) the foulant (10-μm) on polyamide nanofiltration membranes. These membranes were compared to a commercial nanofiltration membrane and a control flat synthesized membrane. The membranes were tested with water, 2000 ppm Na2SO4, and three cycles of a n-dodecane (as oil) brine solution in a dead-end cell to assess the fouling resistance and flux recovery ability of each polyamide membrane type. From the fouling experiments, it was determined that none of the pattern sizes significantly affect the flux recovery ratio, but smaller than and larger than patterns decreased the fouling rate on the polyamide membranes by a small margin.

Prediction of visual outcomes using virtual implantation of a trifocal intraocular lens in presbyopic lens exchange patients.

To assess the reliability of a novel virtual IOL implantation device to predict the outcomes of a trifocal IOL. Clinical sites in Spain and Germany. Prospective multicenter study. Preoperative measurements obtained by the virtual implantation of AT LISA tri 839MP IOL (Carl Zeiss Meditec AG, Jena, Germany) with VirtIOL device (10Lens S.L.U., Terrassa, Spain) were compared to postoperative (month 3) outcomes following the IOL implantation. Evaluated metrics were defocus curve, contrast sensitivity (both in photopic conditions), and visual phenomena (visual angle size of burst and annular pattern) in mesopic conditions. The study included 45 presbyopic non-cataract patients (mean age 56.16±5.03 years). VirtIOL device reasonably predicted the shape of the defocus curve, especially in the intermediate vision range, but underestimated postoperative visual acuities mainly at the defocus range between +1.0D and -3.5D. The difference between predicted and achieved visual acuity was -0.11±0.13 logMAR (p<0.001) for 0.0D defocus and -0.16±0.15D logMAR (p<0.001) for -2.50D defocus. The shape of the contrast sensitivity curve was almost identical for predicted and achieved measurements, but the device underestimated the values by ≈0.3 logCS units for each spatial frequency. Visual phenomena were similar between the predicted and achieved outcome (predicted vs. achieved: burst pattern 2.65±0.97° vs. 2.74°±0.95°, p=0.63; annular pattern: 0.88±0.42° vs. 0.93±0.49°, p=0.59). The device reasonably predicted the pattern of measured variables. Visual acuity/contrast sensitivity reduction might be attributed to viewing the objects through a more complex optical system and would need to be accounted for in clinical studies.

Estimation of Trip-based Generation Models and Calibration of Mode Choice Models for the American Travel Behavior

Background The National Household Travel Survey (NHTS) is the primary national dataset for analyzing personal and household travel trends. It covers daily non-commercial travel across all modes and details information on travelers, their households, and their vehicles. Materials and Methods The NHTS includes critical data for calibrating travel demand models, such as vehicle details (number and type), individual demographic characteristics (age, gender, employment), and household demographics (income, ownership status, size, race). In this study, we utilized the 2017 NHTS summary statistics to estimate individual trip generation models, differentiating between weekdays and weekends. By comparing factors influencing daily person trips during these periods, we aimed to discern distinctions between the two models. Additionally, we calibrated a mode choice model to understand the impact of trip purpose, duration, household income, and the ratio of available vehicles to household size on the chosen mode. Our analysis focused on identifying and quantifying the factors influencing travel behavior, providing insights into how various variables affect the number of trips and mode choices. Results The results indicated variations between weekday and weekend models, with the presence of non-workers and individuals' education levels emerging as crucial factors for weekday travel. Conversely, the existence of children, household income level, and personal yearly miles driven were identified as significant factors affecting weekend travel. Additionally, common characteristics such as household size and urban residence were substantial in both models. The Multinomial regression analysis investigated the correlations between individual, household, activity, and trip characteristics and the modes of transportation selected by travelers. The most significant factors influencing an individual's mode choice are household income, the ratio of available vehicles to household size, and activity purpose. Discussion The study compared weekday and weekend travel behavior using trip-based generation models. Weekday travel was significantly influenced by non-workers and education levels, while weekend travel was more affected by factors like the presence of children, household income, and annual kilometers traveled. Both models emphasized the role of household size and urban residence in shaping travel patterns. The research also examined transportation mode choice, with validation confirming the high accuracy and robustness of the mode choice model in predicting travel behavior. Conclusions The study findings are valuable to transportation planners, policymakers, and urban mobility experts aiming to enhance the efficiency and effectiveness of transportation systems. By offering a detailed understanding of individual and household travel patterns, the research enables data-driven interventions that support policy decisions, such as optimizing transit routes, enhancing infrastructure for active transportation, and managing congestion.

Deep Learning for Time Series Anomaly Detection: A Survey

Time series anomaly detection is important for a wide range of research fields and applications, including financial markets, economics, earth sciences, manufacturing, and healthcare. The presence of anomalies can indicate novel or unexpected events, such as production faults, system defects, and heart palpitations, and is therefore of particular interest. The large size and complexity of patterns in time series data have led researchers to develop specialised deep learning models for detecting anomalous patterns. This survey provides a structured and comprehensive overview of state-of-the-art deep learning for time series anomaly detection. It provides a taxonomy based on anomaly detection strategies and deep learning models. Aside from describing the basic anomaly detection techniques in each category, their advantages and limitations are also discussed. Furthermore, this study includes examples of deep anomaly detection in time series across various application domains in recent years. Finally, it summarises open issues in research and challenges faced while adopting deep anomaly detection models to time series data.

Designing of Inverted F Antenna and Utilizing of Blockchain in Vehicle Systems

Raed Daraghma, Eman Daraghmi, Yousef Daraghmi, Hacene FoThis paper is the first to integrate a blockchain system to improve the manufacturing efficiency and reliability of 5G F Inverted antennas. The recommended antenna is constructed from a single side of a premium aluminum conductor, the width of the radiator is 0.564 mm, the thickness of the conductor is 0.77 mm ground plane is 29.3 x 29.3 mm2 dimension. The antenna is designed to work at a frequency of 5.9 GHz, therefore it can be used for vehicle applications. It is designed to be inserted as an integrated antenna into an IOT device and is composed of Microstrip F shapes. Therefore, a rectangular Microstrip patch F antenna was built and its performance was examined in this work. 5.9 GHz is the antenna's resonance frequency range, which is suitable for vehicle applications. The simulation software for this work was Computer Simulation Technology (CST) software. Antenna performance was compared concerning gain, bandwidth, and return on loss. By enhancing the production efficiency and reliability of 5G Inverted F antennas, our study sets a new benchmark for the integration of blockchain and smart contract technologies, paving the way for ground-breaking advancements in manufacturing techniques. The relevance of creating an inverted F antenna for the Vehicle Systems environment is increased by this research. Typically, rod antennas are found in automobiles. However, the Vehicle Systems industry's requirements for meeting the demands of human resources with a variety of applications at different frequencies are not met by the rod antenna now in use. Because of their important characteristics, which include wideband matching, omnidirectional pattern, high efficiency, and compact size, microstrip patch Inverted F antennas are highly favored in the Vehicle Systems industry. uchal

Surfactant-Polymer Slug Optimization, Injection Rate &amp; Pattern Size Determination Using The Cmg Simulator In The Mj Well

The MJ well is one of the oldest in the Central Sumatra field. This field was originally produced in 1952, with a reserve of 4.5 MMSTB. This explains why EOR studies are needed to increase the production of oil. The MJ well can be injected with surfactant-polymer based on the EOR screening criteria. Surfactant performance mechanisms can minimise IFT and displacement, however, polymers can limit mobility by increasing the viscosity of formation water and sweep efficiency. It is preferable to use reservoir modelling before applying surfactant-polymer to a well. Surfactant-polymer simulation, specifically CMG software, is used in this research. Several simulations were run using sensitivity such as slug SP, injection rate, and pattern size to determine the best approach for use in the MJ well. Surfactant injection was performed after a year of applying a water flood followed by injection of surfactant-polymer with several slug variations, namely 0.2 PV, 0.3 PV, 0.4 PV, 0.5 PV, and 0.6 PV at varied injection rates. 1600 BPD, 2300 BPD, and 3000 BPD, as well as many well-pattern variations, including a 5-spot pattern, a 7-spot pattern, and a 9-spot pattern. Based on the simulation, optimal results are obtained at a slug of 0.6 PV, an injection rate of 3000 BPD, and a 5-Spot well pattern with a total amount of oil of 2,023,700 bbl and a recovery factor of 81.67%.

Experimental study on grid-patterned low thermal conductivity coatings for fast chill-down of flat plate in liquid nitrogen pool

This study investigates a fast chill-down technology utilizing grid-patterned low-thermal-conductivity (low-k) coatings. Experiments were conducted on the transient pool boiling of liquid nitrogen on stainless steel plates under various conditions: bare, partially coated, and fully coated surfaces with coating thicknesses ranging from 50 to 200 μm. Fully coated surfaces exhibited a 52–58 % shorter chill-down time owing to the rapid transition from film to transition boiling. However, these surfaces reduced thermal performance in the nucleate boiling regime owing to the added thermal resistance of the low-k coating. To address this, a partially coated surface with a grid-patterned design was proposed and examined for various pattern sizes of d = 2.5, 5, and 10 mm. The rapid regime transition was most effectively facilitated when the pattern size was comparable to the wavelength determined by the Taylor instability. In the nucleate boiling regime, thermal performance improved as the pattern size approached the capillary length. Consequently, the chill-down time for the partially coated surface with d = 2.5 mm was reduced by 79 %, owing to both the rapid regime transition and improved performance throughout the entire process. Finally, the grid-patterned coatings showed a twofold increase in coating effectiveness (∼4.8) compared to the fully coated surfaces (∼2.4). This study establishes a new design guideline for low-k coatings, optimizing cooling performance across all boiling regimes.

The Dietary Pattern Concerning Non-alcoholic Fatty Liver: An Umbrella Review and Meta-analyses of Observational Studies and Intervention Trials

Context: Non-alcoholic fatty liver disease (NAFLD) has been extensively studied in recent years, but the optimal dietary patterns for improving this condition remain unclear. Evidence Acquisition: Therefore, this umbrella review aimed to summarize the available evidence from meta-analyses on the relationship between various dietary patterns and NAFLD. Results: Two independent researchers identified published meta-analyses of interventional and observational studies that investigated the relationship between dietary patterns and NAFLD by searching electronic databases up until March 2023 and extracting relevant information. The pooled effect size of dietary patterns on NAFLD was evaluated using the standard mean difference (SMD) with a 95% confidence interval (CI). Fourteen meta-analyses met the inclusion criteria. Conclusions: All NAFLD-related outcomes, including hepatic steatosis, Fatty Liver Index (FLI), liver stiffness, and liver enzymes, were significantly affected by a calorie-restricted diet. Similarly, following the Mediterranean diet had beneficial effects on improving these outcomes. The findings support the role of a calorie-restricted diet and a Mediterranean diet in improving NAFLD, alongside the treatment protocol for these patients.