Optimal Flow Rate Research Articles

A Neural Network approach to optimize flow rate for Micro-Bubble Drag Reduction

To reduce the resistance of ships, many scholars have focused on micro-bubble drag reduction (MBDR) technology. However, The implementation of MBDR on ships is challenging due to the numerous factors and complex coupling relationships involved in the gas–liquid two-phase flow at the ship’s bottom. This paper aims to apply neural network algorithm on MBDR technology to real ships to achieve energy savings and emission reductions. A test platform was constructed, and the Micro-Bubble Flow Rate of the test model at the lowest drag resistance was collected to form a sample database. Using the database as a sample, the mathematical model is trained by the neural network algorithm, and optimized by the genetic algorithm through a number of iterations, the Optimal Micro-Bubbles Flow Rate (OMFR) is predicted for each status. This paper is of great significance to the application of MBDR technology on real ships. Using neural network algorithm to form the mathematics model from the data samples of unconstrained self-propulsion tests. The OMFR obtained through the iterative process of the genetic algorithm, can reduce the ship resistance, thereby achieving energy savings and emission reductions.

Increasing the operating time of hollow fiber membrane bundles used for water ultrafiltration

In order to increase the interval between cleanings of a hollow fiber membrane bundle (HFMB) used for water ultrafiltration, a numerical study and an experimental test were conducted. The relation between the water flow rate and shear stress along the hollow fiber membrane wires (HFMW) was studied for three geometries. Three angles (α = 900,450,00) for the intake flow pipe (di = 25 mm) against the horizontal axis of a cylinder (Dc = 100 mm; L = 600 mm) containing one hollow fiber membrane wire (dw = 1 mm) were chosen for the numerical investigation; five different water flow rates (Q = 8…16 l/min) were considered. The values for the shear stresses along one membrane wire placed along the cylinder's central axis were computed. The findings show that the best geome1try for enhanced shear stress is obtained for α = 00. For this geometry a mean value of 1.1 Pa for the shear stress was obtain along the first 1/3 of the membrane wire at a minimum flow rate of Q = 8 l/min. Higher values for water flow rates do raise shear stress but increased energy consumption is needed. The tests were carried out on a HFMB with molecular weight cut-off (MWCO) of 0.097 μm, that was put in a glass cylinder with a horizontal axis, for μ = 900, μ = 00, and Q = 8 l/min. The results confirmed the conclusions of the numerical study i.e. the filtering capacity of the membrane was maintained higher by 6-6.5% for α = 00 comparing to α = 900 due to shear stress increase. For the flow rate of Q = 12 l/min the filtering capacity of the membrane did not increased. The study confirmed the hypothesis that for certain geometries there could be settle down optimum flow rates to minimize energy consumption during membrane operation but comprehensive research is needed.

Predicting the Impact of Polysulfone Dialyzers and Binder Dialysate Flow Rate on Bilirubin Removal.

Liver failure is the 12th leading cause of death worldwide. Protein-bound toxins such as bilirubin are responsible for many complications of the disease. Binder dialysis systems use albumin or another binding molecule in dialysate and detoxifying sorbent columns to remove these toxins. Systems like the molecular adsorbent recirculating system and BioLogic-DT have existed since the 1990s, but survival benefits in randomized controlled trials have not been consistent. New binder dialysis systems, including open albumin dialysis and the Advanced Multi-Organ Replacement system, are being developed. Optimal conditions for binder dialysis have not been established. We developed and validated a computational model of bound solute dialysis. It predicted the impact of changing between two test setups using different polysulfone dialyzers (F3 and F6HPS). We then predicted the impact of varying the dialysate flow rate on toxin removal. We found that bilirubin removal declines with dialysate flow rate. This can be explained through a linear decline in free bilirubin membrane permeability. Our model quantifies this decline through a single parameter (polysulfone dialyzers). Validation for additional dialyzers and flow rates will be needed. This model will benefit clinical trials by predicting optimal dialyzer and flow rate conditions. Accounting for toxin adsorption onto the dialyzer membrane may improve results further.

Numerical investigation and thermal optimization of low-inductance ring-shaped film capacitors with integrated cooling structure for electric vehicle

The advancement of motor controllers for electric vehicles is increasingly focusing on higher power density, efficiency, and miniaturization. Consequently, there is a growing demand for film capacitors that offer not only lower stray inductances but also enhanced high-temperature resistance capabilities. While existing research dedicated to mitigating the stray inductances of film capacitors, studies that address both the capacitors’ stray inductances and the thermal managements remain relatively scarce. Therefore, this paper proposes for the first time a low-inductance ring-shaped capacitor, utilizing an integrated cooling structure to reduce the capacitor’s thermal resistance and enhance its high-temperature tolerance. Firstly, the stray inductances and heat dissipation performances of both ring-shaped and conventional square-shaped capacitors, each with identical capacitances, are compared using Q3D and FLUENT simulations, the results demonstrate that the ring-shaped capacitor exhibits lower stray inductance and superior heat dissipation performance. Then an integrated cooling structure is proposed for the ring-shaped capacitor with the aim of diminishing its thermal resistance and augmenting its tolerance to high temperature. Utilizing FLUENT conjugate heat transfer simulation, the impacts of key factors within the cooling structure such as inlet flow rate, inlet temperature, and ambient temperature on the capacitor’s maximum temperatures are investigated, and the optimal inlet flow rate and inlet temperature are determined by multi-objective optimization. The findings reveal that increasing the inlet flow rate reduces the maximum temperature, although the cooling effect becomes less significant at higher flow rates, leading to increased energy consumption and operating costs. Moreover, the ambient temperature has the largest impact on the capacitor temperature, followed by the inlet temperature. The optimized integrated cooling structure achieves approximately a 73.93% reduction in thermal resistance and lowers the maximum temperature of the ring-shaped capacitor by about 72.24%.

Optimizing Microfluidic Channel Design with High-Performance Materials for Safe Neonatal Drug Delivery.

Designing the microfluidic channel for neonatal drug delivery requires proper considerations to enhance the efficiency and safety of drug substances when used in neonates. Thus, this research aims to evaluate high-performance materials and optimize the channel design by modeling and simulation using COMSOL multiphysics in order to deliver an optimum flow rate between 0. 3 and 1 mL/hr. Some of the materials used in the study included PDMS, glass, COC, PMMA, PC, TPE, and hydrogels, and the evaluation criterion involved biocompatibility, mechanical properties, chemical resistance, and ease of fabrication. The simulation was carried out in the COMSOL multiphysics platform and demonstrated the fog fluid behavior in different channel geometries, including laminar flow and turbulence. The study then used systematic changes in design parameters with the aim of establishing the best implementation models that can improve the efficiency and reliability of the drug delivery system. The comparison was based mostly on each material and its appropriateness in microfluidic usage, primarily in neonatal drug delivery. The biocompatibility of the developed materials was verified using the literature analysis and adherence to the ISO 10993 standard, thus providing safety for the use of neonatal devices. Tensile strength was included to check the strength of each material to withstand its operation conditions. Chemical resistance was also tested in order to determine the compatibility of the materials with various drugs, and the possibility of fabrication was also taken into consideration to identify appropriate materials that could be used in the rapid manufacturing of the product. The results we obtained show that PDMS, due to its flexibility and simplicity in simulation coupled with more efficient channel designs which have been extracted from COMSOL, present a feasible solution to neonatal drug delivery. The present comparative study serves as a guide on the choice of materials and design of microfluidic devices to help achieve safer and enhanced drug delivery systems suitable for the delicate reception of fragile neonates.

Influence of MIG Welding Process Parameters on the Strength of Bimetal Joints: Study of Gas Flow Rate and Macrofractures

Bimetal joints are often used in various industries, such as automotive, power generation, electronics, and manufacturing. This is because bimetal joints allow the joining of two types of metal with different properties. Welding two different types of metal can pose its own challenges, such as the difficulty of controlling welding parameters so that the results are optimal for both types of metal, as well as differences in the thermal and mechanical properties of the two metals. This has led to extensive research on bimetal plate connections. Based on this background, this research aims to determine the effect of variations in flow rate and current strength on the tensile strength of robotic welding bimetal welded joints, as well as determine the results of macro photos of fractures resulting from tensile tests for each variation. The research was carried out experimentally where each variation was repeated with data 3 times. Based on the results and discussion, it is known that the optimal gas flow rate in general is 20 l/min, where the tensile strength reaches 353.1442 MPa–455.5458 MPa. At this flow rate, the dominant fracture occurs in the base metal and is ductile, which indicates good plastic deformation. On the other hand, gas flow that is too low or too high causes joint defects and reduces the tensile strength. Meanwhile, other welding parameters, namely variations in welding current, affect tensile strength. At a gas flow of 10 l/min, increasing the current to 180 A produces the highest tensile strength of 449.4357 MPa with ductile fracture characteristics. However, at a current of 120 A there is a significant decrease due to overheating, especially at higher gas flows such as 20 l/min and 30 l/min, which results in brittle fracture in the heat-affected zone (HAZ). The results of this research contribute to the understanding of the influence of welding parameters on the tensile strength and fracture characteristics of bimetallic joints. This research can be a reference for the development of more efficient and reliable welding processes in various industries, such as automotive, power generation and manufacturing, which require bimetallic joints with optimal quality.

An efficient low-grade thermal energy dual-driven elastocaloric cooling system: Thermodynamic cycle analysis, economic and sustainability assessment

Elastocaloric cooling is regarded as the most promising emerging refrigeration technology, with heat driven elastocaloric cycles at the forefront of research. However, existing systems often have actuators with a mass of 4–20 times that of the refrigerant, resulting in bulky structures and low thermodynamic efficiency. Enhancing system compactness and efficiency has thus become a critical research challenge. This study proposes an innovative low-grade thermal energy dual-driven elastocaloric cooling system, achieving a 1:1 mass ratio (mActuator/mRefrigerant) between the actuator and refrigerant, significantly improving system compactness and coefficient of performance while effectively reducing costs. A three-dimensional numerical and geometric model was developed to analyze the thermodynamic cycle, examining the effects of material, operational, and geometric parameters on cooling performance, and a “category-wise optimization” strategy was employed to determine optimal parameter combinations. The cost and environmental impacts of the new system were evaluated and compared with vapor-compression air conditioning. Results show that the difference in transformation temperatures between austenite and martensite phases significantly impacts cooling performance. Optimal flow rates and cycling frequencies are essential to avoid performance loss. Considering the coefficient of performance and heat transfer, a 1:1 mass ratio is optimal for geometric parameters. The system achieves a maximum coefficient of performance of 0.158, exceeding the existing two schemes by more than 2 times and 7 times, with a maximum temperature rise of 13.1 K. The proposed system is economically feasible and environmentally friendly, providing valuable theoretical foundations and technical solutions for developing sustainable alternative refrigeration technologies.

A novel 3D opto-electro-thermal coupling numerical model for photovoltaic/thermal systems

Photovoltaic/thermal (PV/T) systems offer a promising solution for enhancing energy conversion performance by capturing waste heat and reducing the operating temperature of photovoltaic cells. The performance of these PV/T systems could be further optimized by numerical simulation. However, currently reported PV/T models utilize simplified models and and fail to consider the electro-thermal coupling in local areas of solar cells, thereby inadequately representing the underlying physical mechanisms. To address this issue, a novel opto-electro-thermal coupling numerical model of perovskite PV/T systems based on drift–diffusion equations is developed in this work. This model enables the investigation of the energy conversion mechanism of optical, electrical and thermal energy at grid cell level. Building on the developed model, the energy conversion performance at system level under various operational conditions is analyzed via a modified weighted total efficiency evaluation indicator. The results indicate that: the total efficiency is significantly compromised by elevated environmental temperature, with an efficiency loss of 8.45 % observed when the temperature increases by 40 °C. Meanwhile, as irradiation intensity rises, the efficiency gained from utilizing waste heat would become increasingly significant in PV/T systems. More importantly, the optimal flow rate for various irradiation intensities is also derived. This work could offer theoretical guidance for investigating more comprehensive energy conversion mechanisms and optimizing energy conversion performance for PV/T systems.

Nozzle structure optimisation in a photovoltaic irrigation system

AbstractOn the basis of the significant impact of the sprinkler nozzle structure in photovoltaic irrigation systems, the nozzle parameters are optimised to improve sprinkler adaptability and irrigation uniformity under different light intensities. An experimental test and numerical simulation were conducted to analyse the influence of nozzles with distinct parameters on the spray irrigation effect. Taking the irrigation uniformity coefficient as the optimisation goal and the nozzle outlet shape, outlet area and straight flow channel length as the optimisation variables, an orthogonal experimental design was employed, and the optimal solution was obtained via range analysis. The experimental results indicate that the sprinkler performs best when the outlet shape is circular, the nozzle outlet area is 7 mm2 and the flow channel length is 2 mm. The optimal nozzle characteristics were tested and compared with those of the original design, and numerical simulation was used to demonstrate the optimised internal flow mechanism. The results demonstrate that the optimised flow rate and spray range are improved, and the working pressure and rotation period are significantly reduced, enabling the system to adapt to a more extensive range of light intensities. The radial water distribution structure is better, and the combined application rate and uniformity coefficient are also significantly improved. In addition, the sprinkler outlet speed is more consistent, and the area of the high‐speed zone in the spray plate increases, which is conducive to reducing energy loss and enhancing sprinkler irrigation uniformity.

A new approach to cooling photovoltaic panels: Electrospray cooling

In recent years, rise in carbon emissions has increased the focus on renewable energy. Solar energy systems are widely used for energy production due to their easy applicability and being an unlimited resource. There are factors affecting the efficiency of these systems. One of the most prominent of these is temperature. Enabling thermal control of the solar panels not only increases their electrical efficiency but also extends their economic life. In this study, electrospray cooling, which is not found to be used in the literature for cooling PV panels, was analyzed. Electrospray cooling performance in PV panels was examined for different flow rates and irradiance values using water as the coolant fluid. As a result, it was determined that the optimum flow rate was 80 ml/h water flow rate, and the panel temperature at this flow rate was reduced from approximately 77 °C–32.2 °C at 1200 W/m2 radiation. The output power obtained increased by 56.6 % at optimum flow rate and radiation. Compared to the studies in which PV panels were cooled by spray, it was found that electrospray requires approximately 1.5–137 times less water.

Thermodynamic Approach to Optimal Water Management for Fuel Cell Electric Vehicles

A systematic, multicomponent model has been developed to investigate optimal water management for fuel cell electric vehicles. The water management strategies focus on manipulating thermodynamic states to provide the adequate requirements of fuel cells. A pseudo-2D fuel cell water transfer model, a shell and tube type membrane humidifier model, and a centrifugal compressor model are mathematically developed and solved using MATLAB to achieve an integrated thermodynamic approach based on system piping and instrumental diagrams(P&ID). Each component model is validated using published experimental data with good agreement. In the air supply system, the required humidity at the fuel cell channel inlets is theoretically predicted under low heating value operating fuel cells. Subsequently, the optimal mass flow rate of the compressor is suggested to cover a wide range of conditions. Additionally, the recirculated gas is bypassed to control the humidification levels of the humidifier based on the required humidity at the fuel cell channel inlets. The results show the thermodynamic states within system in accordance with the optimal operation conditions of the component. This systematic approach presents significant algorithms for optimizing water distributions in vehicular fuel cell systems.

Design, optimization, simulation, and implementation of a 3D printed soft robotic peristaltic pump

Abstract This study presents an innovative approach to fluidic pumping using soft robotics, designed to circulate fluid through soft conduits for delicate environments like blood streams where traditional peristaltic pumps may not be feasible. A novel soft robotic peristaltic pump is optimized and implemented, featuring 3D printed ring-shaped actuators and a PDMS pipe housing a Newtonian fluid. The design includes a three-stage actuator ring structure, actuated sequentially for peristaltic motion. A parametric finite element model predicts the required pressure, and the Mooney-Rivlin 5 Parameters hyper-elastic material model ensures accurate material properties. Optimization uses response surface analysis in Minitab and MATLAB Simulink Simscape simulations to achieve maximum flow rate with minimal power and pressure. Experimental validation confirms the simulations, achieving an optimal flow rate of 0.27 ml s−1 at a 450 ms cycle, with minor discrepancies due to friction and measurement errors. This study demonstrates the scalability of linearly sequenced soft squeeze actuators into an effective pump, validated by both simulation and experiments. Future applications include medical devices addressing deep venous thrombosis, with further research exploring control theory for optimization and comparing performance with conventional pumps to enhance practical applicability.

The Effect of O2 Flow Rate on Nanostructured TiO2 Thin Films Prepared by Reactive DC Magnetron Sputtering with OAD Technique

In this project, we explored how different oxygen flow rates influenced the creation of TiO2 nanostructures in thin films using magnetron sputtering preparation with oblique angle deposition (OAD) technique. The experiment involved oxygen flow rates of 20, 40, 60, 80 and 100 sccm along with a constant argon flow at 20 sccm. Morphological analysis by FE-SEM was performed to determine film thickness and deposition rate. In a subsequent stage, thin films thickness was confirmed to be 100 nm. After coating, specimens were annealed at 300°C for 2 h using various O2 flow rates. FE-SEM revealed morphological changes, GIXRD to explore crystal structures, and UV-Vis spectrophotometry to measure light transmittance. The results showed an optimal oxygen flow rate at 60 sccm, with annealed specimens exhibiting anatase structure and promising light transmittance of 73-83%.

ESTIMATION OF THE CLEANING TIME OF THE BOTTOM-HOLE ZONE OF WELLS IN CONDITIONS OF UNCERTAINTY

The aim of the work is to analyze changes in the maximum optimal flow rates of wells operating various groups of productive formations of the Volga-Ural oil and gas province under conditions of uncertainty of geological and field data. The relevance of the work is due to the deterioration of the structure of residual oil reserves and the need for the most efficient extraction of liquid hydrocarbon resources, optimization of design methods for various treatments of the bottomhole formation zone. Using geological and statistical modeling systems, the timing of cleaning the bottomhole zones of wells from drilling products was determined at the time they reached their maximum optimal flow rate in conditions of deposits confined to various stratigraphic horizons, and appropriate models of changes in productivity coefficients were constructed. The factors influencing the recovery time of the real properties of the reservoir at the point of opening it by the well, which, among other things, determines the profitability of the process of selecting residual oil reserves, have been established. Among them, the most relevant and necessary for the implementation of an integrated approach to computer support procedures for the development of oil fields are the productivity of wells, fracturing of formations, their proximity to a particular tectonic-stratigraphic complex, geological, physical and physico-chemical properties of formations and their saturating fluids. For the deposits of the Famensk tier of deposits of the Volga-Ural oil and gas province, a multiple decrease in the time of removal of reaction products after hydrochloric acid exposure at objects with low fracturing has been established. At the same time, additional processing of the bottomhole formation zone within areas with high drilling density does not affect the total cleaning time of the bottomhole zone of wells. Stimulation of the removal of drilling mud filtrate and additional products of formation reactions by injection of hydrochloric acid compositions under certain conditions can lead to a decrease in the actual productivity of wells due to the introduction of less developed and dead-end cracks into the drainage process. The existence of the specifics of the procedure for cleaning the bottomhole formation zone depending on the geological and physical parameters of productive formations is substantiated and various patterns of changes in the productivity coefficient depending on the time of wells reaching the maximum optimal flow rate are revealed. The results obtained make it possible to make informed technological decisions to improve the efficiency of oil production, including in conditions of uncertainty, which may be caused by the lack of the necessary volume of hydrodynamic studies of wells.

Application of Nano Bubble Aeration Technology in Domestic Wastewater Treatment: Optimization of Gas Flow and Reaction Time

Nano bubble aeration is an emerging technology with significant potential in wastewater treatment, particularly for removing suspended solids and organic matter. This study investigates the application of nano bubble aeration in the treatment of domestic wastewater, focusing on the reduction of chemical oxygen demand (COD) and total suspended solids (TSS). Nano bubbles, with diameters ranging from tens of nanometers to a few micrometers, exhibit slower rising velocities and prolonged stability in water due to their negatively charged surfaces. Various nano bubble air flow rates were tested over 90-minute intervals to determine the optimal treatment conditions. The results indicate that a flow rate of 2 liters per minute achieves the highest treatment efficiency, reducing COD by 84.73% and TSS by 77.51%. Increasing the flow rate beyond this level showed minimal improvement, demonstrating that 2 liters per minute is the optimal flow rate for efficient wastewater treatment using nano bubble aeration. This research highlights the advantages of nano bubble technology in enhancing the treatment efficiency of suspended solids and organic matter in wastewater.

Enhancing Transfection Efficacy in Glioma Cells: A Comparison of Microfluidic versus Manual Polypropylenimine Dendriplex Formation.

Gene therapy is a promising therapeutic approach for treating various disorders by introducing modified nucleic acids to correct cellular dysfunctions or introduce new functions. Despite significant advancements in the field, the effective delivery of nucleic acids remains a challenge, due to biological barriers and the immune system's ability to target and destroy these molecules. Due to their branched structure and ability to condense negatively charged nucleic acids, cationic dendrimers have shown potential in overcoming these challenges. Despite this, standardized scalable production methods are still lacking. This study investigates the use of microfluidics to formulate generation 3-diaminobutyric polypropylenimine (DAB) dendriplexes and compares their characteristics and in vitro gene delivery efficacy to those prepared using conventional manual mixing. DAB dendriplexes were produced by both microfluidic and manual approaches and characterized. Their cellular uptake and gene expression were evaluated on C6 glioma cancer cells in vitro. Dendriplexes formed using microfluidics at the optimal flow rate and ratio demonstrated enhanced DNA condensation over time, achieving up to 97% condensation at 24hours. Both preparation methods produced positively charged dendriplexes, indicating stable formulations. However, dendriplexes prepared through hand mixing resulted in smaller particle sizes, significantly higher cellular uptake and gene expression efficacy compared to those prepared by microfluidics. Nonetheless, microfluidic preparation offers the advantage of standardized and scalable production, which is essential for future applications. This study highlights the potential of microfluidic technology to improve precision and scalability in gene delivery, paving the way for future advancements in gene therapy. Our findings suggest that, with further optimization, microfluidic systems could provide superior control over dendriplex formation, expanding their potential use in gene therapy applications.

Adaptive jet flow control for performance improvement via coupling stator-blade with rotor-tip injections in a transonic compressor

With the increase in the blade load of modern compressors for aircraft engines and gas turbines, flow separation is always generated in stator and rotor blade passages. This not only deteriorates the compressor efficiency but also blocks the flow path that may induce instability such as stall or surge. In order to tackle these issues, an adaptive jet flow control system coupling stator-blade with rotor-tip injections is proposed, and the goal of this paper is to investigate its effects on the aerodynamic performance of an in-house 1.5 stage transonic compressor. The developed flow control system integrates a jet configuration on the stator-blade surface and on the rotor casing surface respectively. The first step to construct this system is designing the jet configurations, and the Coanda effect is adopted to achieve wall-attachment injection. Second, the flow control system is intended to execute real-time monitoring on the operating condition of the compressor and can inject air with appropriate mass flow rate to eliminate flow separation and rotating stall. To do this, an optimal injection mass flow rate prediction model is established via a back propagation neural network algorithm. It aids to ensure an adaptive jet mass flow rate control during the compressor operation. Then, the effectiveness of the adaptive jet flow control system is evaluated using numerical simulations, and the influence mechanism of the injection mass flow on flow fields and aerodynamic performance is analyzed. Results indicate that compared to the prototype compressor, the compressor with adaptive stator-blade and rotor-tip injections can significantly increase efficiency and improve stability margin.

Optical and stress properties of ZrO2/SiO2 and TiO2/SiO2 anti-reflective coatings deposited by ion-beam-assisted deposition on a flexible substrate

Dielectric films of ZrO2,TiO2, and SiO2 were deposited on flexible polycarbonate (PC) and polyethylene terephthalate (PET) substrates by using ion-beam-assisted deposition (IBAD). Each layer had a thickness ranging from 30 to 210 nm. The optical and anisotropic stress properties were investigated. Two anti-reflective coatings (ARCs), ZrO2/SiO2 and TiO2/SiO2, were selected and deposited on the PET flexible substrate. The anisotropic stresses of the single layer and ARCs were measured using a phase-shifting moiré interferometer. Experimental results showed that the optimal oxygen flow rates for the ZrO2,TiO2, and SiO2 films deposited with IBAD were 10, 10, and 15 sccm, respectively. The refractive index (n) was TiO2(2.37)>ZrO2(2.05)>SiO2(1.46), and the extinction coefficient (k) for all samples was below 10−3. The thermal expansion coefficient of the PC substrate was three times that of the PET substrate, and the high-refraction ZrO2 and TiO2 single-layer films presented cracks and distortions on the PC substrate. Only the low-refractive-index SiO2 sample did not present cracks. The three dielectric films did not crack or distort when deposited on the PET substrate. The anisotropic stress analysis provided the maximum principal and shear stresses for the three dielectric films on the PET substrate. Therefore, the maximum principal stress of the 210 nm single-layer film on a PET substrate is TiO2>ZrO2>SiO2. It was also discovered that the principal stress of the AR multilayer film is significantly decreased due to the damping stacking effect (DSE) of the high- and low-refractive-index materials, ZrO2/SiO2 ARC (−297.3MPa)>TiO2/SiO2ARC(−132.6MPa). Thus, the high packing density of TiO2 gives a better DSE than ZrO2.

Comparative Numerical and Experimental Analyses of Conical Solar Collector and Spot Fresnel Concentrator

This paper aims to compare the thermal performances of the conical solar collector (CSC) system and the spot Fresnel lens system (SFL) using water and CuO nanofluid as the working fluids. The studied CFD models for both systems were validated using experimental data. At an optimal flow rate of 6 L/min, the SFL system showed higher optical and thermal performance in comparison with that of the CSC system. In the case of the SFL system, the availability of a greater amount of solar energy per unit collector area caused an increase in thermal energy. Moreover, in the case of the CSC system, the non-uniform distribution of solar flux on the absorber’s outer surface leads to an increase in temperature gradient and heat losses. As a heating medium, the CuO nanofluid outperformed the water in terms of higher thermal conductivity and heat capacity. The average thermal efficiencies of 64.7% and 61.2% were achieved using SFL with and without CuO nanofluid, respectively, which were 2.4% and 0.5% higher than those of the CSC with and without nanofluid. CFD simulations show a 2.80% deviation for SFL and 2.92% for CSC, indicating acceptable accuracy compared to experimental data.

Developing a neural network model to predict the optimal minimum flow rate for effective hole cleaning

The object of the study is effective well cleaning during drilling. The subject of the study is the development of a machine learning model based on a neural network for predicting the optimal minimum drilling fluid flow rate. The challenge is the need to improve well cleaning efficiency to prevent stuck pipes and the associated downtime and costs. During the study, a neural network model was developed and tested to predict the minimum flow rate for cleaning wells. The model was trained and tested on data showing its high accuracy and reliability. The mean square error (MSE) reached 0.019169 for LSTM and 0.0828 for GRU, indicating the accuracy of the predictions. Neural network architectures such as Long-Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) were used to efficiently process time series of data and consider long-term dependencies. The results are explained using advanced neural network architectures and machine learning algorithms, which made it possible to achieve good accuracy of predictions. These architectures enable efficient model training on large amounts of data, allowing complex dependencies and influencing factors to be considered. Distinctive features of the results include good accuracy of predictions and the ability to use the model in real-world conditions. The model demonstrates good performance and reliability in predicting the minimum flow rate. The results of the study can be used to optimize the processes of well drilling. Practical applications include using the model to predict the optimal minimum flow rate in various conditions, which will reduce the risks of stuck pipes and increase the efficiency of drilling operations. The model can be integrated into existing monitoring and control systems for drilling processes to improve their performance