Flow Rate Conditions Research Articles

Study on the Unsteady Flow Characteristics of a Pump Turbine in Pump Mode

Extensive research has been conducted on the performance of pump turbines, particularly focused on understanding the generation mechanism of S-shaped characteristics. However, there has been a lack of research on unsteady flow characteristics in hump characteristics with small guide vane openings. This study focuses on the hump characteristics of a pump turbine in pump mode. The unsteady numerical simulation method is used along with experimental testing to examine the internal flow characteristics and induced pressure fluctuations under pump operating conditions. The results indicate that flow separation occurs in the impeller when the flow rate decreases to the valley operating condition, and recirculation flow occurs near the impeller inlet at the partial flow rate. Moreover, the unstable flow on the positive slope exhibits a low-frequency characteristic of 0.15fn. The pressure fluctuation from the hub to shroud areas of the guide vane region diminishes sequentially. Notably, distinct vortex structures emerge at the draft tube cone section under the valley operating condition. These structures extend toward the elbow section of the draft tube as the flow rate decreases. This phenomenon generates low-frequency pressure fluctuation originating from the primary frequency of the vortex and dean vortex on the surface, located at 0.4 D of the draft tube under conditions of low flow rate.

Laser Perforated Dual-Scale Porous Electrodes Considering the Interdigitated Flow Field for Vanadium Redox Flow Battery

The conflict between the specific surface area and hydraulic permeability of carbon-based porous electrodes limits the further improvement of redox flow battery (RFB) system performance. Dual-scale electrode design is a feasible approach to overcome this contradiction. In this study, we prepared dual-scale electrodes by perforating graphite felts using an infrared laser. Based on the symmetry of the interdigitated flow field structure, we proposed three dual-scale structure designs with different combinations of large and small pores and tested their performance on a vanadium redox flow battery (VRFB) single cell. The results showed that the design with perforations under the center of the rib could increase the maximum power density by approximately 2.4 times compared to the original electrode. Furthermore, to investigate the effect of the large pores formed by laser perforation on the local electrolyte velocity, active species concentration, and reaction rate distribution, we proposed a pore-network model and investigated the influence of different combinations of large and small pores and different operating conditions on overall performance through numerical simulation. The results showed that the optimal combination of large and small pores is related to the flow rate and other operating conditions, and that setting large pores under the rib near the outlet channel is expected to provide more performance gains in VRFBs equipped with interdigitated flow fields under typical operating flow rates.

Study on the modes transformation and emission characteristics of Ionic Liquid Electrospray Thrusters

Ionic Liquid Electrospray Thrusters (ILETs) exhibit distinct emission characteristics when operating in different emission mode under different conditions, which can significantly impact their performance. Therefore, to optimize the performance of ILETs and make them suitable for a wide range of space missions, it is necessary to investigate the emission mode characteristics of ILETs. In this study, the ionic liquid 1-Ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (EMI-Im) was used to conduct experiments at varying supply voltage and flow rate conditions. The emitted current was measured and the liquid surface was imaged using a high-speed camera. The emission mode was estimated using algebraic calculations. Experimental results revealed that ILETs operate in the Ion-droplet Mixed mode at low flow rates, while the emission mode transforms into the Droplet mode as the flow rate increases. Similarly, as the supply voltage increases, the emission mode transforms from the Droplet mode to the Ion-droplet Mixed mode. The liquid surface height decreased with the supply voltage increase in each mode, and it increased with the flow rate in the Droplet mode. Notably, the liquid surface height in the Ion-droplet Mixed mode was similar to that in the Droplet mode at the lowest flow rate. Furthermore, the ion ratio significantly affected the thrust and specific impulse of ILETs.

Exploring the thermal performance of a solar air heater with a V-corrugated and shot-blasted absorber plate comprising nano-enhanced phase change materials

This research aims to carry out an experimental investigation into the performance of a solar air heater using phase change materials in combination with V-corrugated absorber plates and shot blasting. This shot blasting approach is applied to interrupt the boundary layer thickness of the absorber plate material it will increase the absorbance of the material. This study incorporates the analysis of four distinct absorber plates namely (i) V-Corrugated Plate (ii) V-Corrugated with shot blasting, incorporating PCM (iii) V-Corrugated with shot blasting, including NEPCM (0.6 %) (iv) V-Corrugated with shot blasting, including NEPCM (0.9 %). In this study, Paraffin wax was selected as the base PCM, and MWCNT dispersed into base PCM with different weight fractions. The nano-enhanced phase change material with a concentration of 0.9 wt% examined that the latent heat of melting and solidification experienced a significant augmentation. This enhancement resulted in a maximum increase of 12.5 % for melting and 8.2 % solidification was attained at 0.9 % of MWCNTs compared with paraffin wax. The average exergy efficiencies of V-corrugated plate attains an efficiency of 1.023 %, V-corrugated with PCM records 1.357 %, V-corrugated with 0.6 % NEPCM attains 1.698 %, and V-corrugated with 0.9 % NEPCM attains the highest efficiency at 2.167 %. The significant enhancement in exergy efficiency observed in NEPCM configurations with volume fractions of 0.6 % and 0.9 % is primarily attributed to two key factors namely enhanced thermal conductivity and improved heat transfer properties. The maximum sustainability index for the V-corrugated design with 0.9 % NEPCM falls within the range of 1.014 to 1.037. The average “Nu” value of 27.5 was achieved under the conditions of a mass flow rate of 0.02 kg/s and the addition of 0.9 % MWCNTs dispersed in paraffin wax.

Characteristics of cavitating flows in cryogenic pump units in a combined cycle power system based on liquefied natural gas and solar energy

The cavitation of cryogenic pump units is an important cause for the low cold energy recovery efficiency and low utilization efficiency of solar energy in combined cycle power systems based on liquefied natural gas (LNG) and solar energy. Through numerical simulation of cavitation in cryogenic pump units, the research established the correlation mechanism between cavitation evolution and energy characteristics. By using the transport-based cavitation model considering the thermomechanical effect of cryogenic media, a novel numerical simulation model for two-phase flows during cryogenic cavitation was developed. In addition, the numerical model of cavitation was verified to be reliable. The cavitation performance of the two-stage LNG submerged pump in cryogenic pump units was studied under multiple conditions. In addition, the evolution of cavitating flow regimes under conditions of different flow rates and its influences on flow patterns of various flow passage components were investigated by combining analysis on temperature changes and flow fields. The entropy production diagnostic model (EPDM) was also adopted to discuss the distribution of the irreversible entropy production rate (EPR) in the evolution process of cavitation. Results show that the interfacial EPR that characterizes the phase-transition intensity after inception of cavitation exerts significant influences. Analysis of influencing mechanisms of changes in temperature, changes in flow fields, and distribution characteristics of energy consumption can provide a theoretical basis for further optimization.

Hydrothermal Conversion of Microalgae Slurry in a Continuous Solar Collector with Static Mixer for Heat Transfer Enhancement

The continuous solar collector is a promising heater and reactor for the hydrothermal liquefaction (HTL) of microalgae biomass. To enhance the heat transfer and hydrothermal conversion of microalgae slurry in solar-driven reactors, a static mixer is inserted in the flow channel of the solar collector. A numerical model combining CFD and HTL reactions of microalgae biomass is proposed. Six composition equations of protein, carbohydrates, lipids, biocrude, aqueous phase and biogas were proposed, while corresponding HTL kinetics were utilized to simulate the conversion rate of the reactants and products. The effects of the twist ratio of the static mixer (3–10), flow rate (30–80 L/h) and solar intensity (650, 750, 850 W/m2) on the flow resistance, heat transfer and organics formation of microalgae slurry were investigated. The swirl flow caused by the static mixer with a twist ratio of three increased the convective heat transfer coefficient (97 W·m−2·K−1) by 2.06 times, while the production rate of biocrude (0.074 g·L−1·s−1) increased by 2.05 times at 50 L/h and 750 W/m2. This investigation gives guidance for utilizing static mixers in solar-driven reactors to optimize the heat transfer and HTL of microalgae biomass with solar heat sources.

Deep Reinforcement Learning Framework-Based Flow Rate Rejection Control of Soft Magnetic Miniature Robots.

Soft magnetic miniature robots (SMMRs) have potential biomedical applications due to their flexible size and mobility to access confined environments. However, navigating the robot to a goal site with precise control performance and high repeatability in unstructured environments, especially in flow rate conditions, still remains a challenge. In this study, drawing inspiration from the control requirements of drug delivery and release to the goal lesion site in the presence of dynamic biofluids, we propose a flow rate rejection control strategy based on a deep reinforcement learning (DRL) framework to actuate an SMMR to achieve goal-reaching and hovering in fluidic tubes. To this end, an SMMR is first fabricated, which can be operated by an external magnetic field to realize its desired functionalities. Subsequently, a simulator is constructed based on neural networks to map the relationship between the applied magnetic field and robot locomotion states. With minimal prior knowledge about the environment and dynamics, a gated recurrent unit (GRU)-based DRL algorithm is formulated by considering the designed history state-action and estimated flow rates. In addition, the randomization technique is applied during training to distill the general control policy for the physical SMMR. The results of numerical simulations and experiments are illustrated to demonstrate the robustness and efficacy of the presented control framework. Finally, in-depth analyses and discussions indicate the potentiality of DRL for soft magnetic robots in biomedical applications.

Machine Learning Model for Predicting the Performance of Activated Carbon Column for the Removal of Volatile Organic Compounds (VOCs)

Objectives : In this study, a performance prediction model for a pilot-scale VOC adsorption column was developed using ANN algorithm. We compared the prediction accuracy of the mathematical models (Thomas model and Yan model) and the multiple linear regression model with that of ANN. This study showed the applicability of the ANN model for predicting the performance of activated carbon columns.Methods : The adsorption module contained 79.8 kg/module of wood-based activated carbon. The gas with 800 ppm-THC of toluene flowed downward from the top at about 5,700 m<sup>3</sup>/h. The breakthrough point was taken as 200 ppm-THC, the same as VOC emission regulation. The desorption was carried out using 130 m<sup>3</sup>/h of hot gas flowing upwards with reduced pressure (-150 to -200 mbar) and high heat (170℃). Adsorption and desorption cycles were conducted 6 times using 3 batches of activated carbon modules. Thomas model, Yan model, multiple linear regression model, and ANN model were developed to predict the breakthrough of <i>C<sub>out</sub>/C<sub>in</sub></i> .Results and Discussion : The Thomas model and the Yan model provided the R<sup>2</sup> values of 0.25 and 0.28, respectively, for predicting the <i>C<sub>out</sub>/C<sub>in</sub></i> of all adsorption module batches and cycles, and the prediction accuracies were low. This could be because these two models do not consider temperature and pressure change operating conditions in the models. Also, the prediction accuracy of <i>C<sub>out</sub>/C<sub>in</sub></i> was low when the initial inlet concentration and flow rate conditions were different for each batch. The multiple linear regression model considers all operating factors in the model, but the prediction accuracy of <i>C<sub>out</sub>/C<sub>in</sub></i> was low as R<sup>2</sup> of 0.45. On the other hand, the ANN model predicted the <i>C<sub>out</sub>/C<sub>in</sub></i> with R<sup>2</sup> higher than 0.97 for all adsorption module batches. In particular, even with the non-ideal data, the ANN model derived a breakthrough of <i>C<sub>out</sub>/C<sub>in</sub></i> close to the experimental value.Conclusion : The ANN model provided high prediction performance for the breakthrough of <i>C<sub>out</sub>/C<sub>in</sub></i> even under non-ideal operation conditions and was expected to be helpful for actual THC adsorption column operation. The accuracy of the ANN model will be further improved if data are accumulated under various conditions.

Analysis of two-phase gas-liquid flow in an Electric Submersible Pump using A CFD approach

This study comprehensively analyzes a mixed-flow Electric Submersible Pump's (ESP) performance under challenging conditions of low flow rates and high gas fractions. The research leverages a computational model built on the Eulerian-Eulerian methodology, adeptly solving the 3D incompressible Navier-Stokes equations for each phase. To ensure an encompassing depiction of the flow dynamics within the ESP, the model considers critical parameters such as the bubble diameter and interphase forces, including drag, lift, and virtual mass force.Key findings reveal that the ESP's performance deteriorates markedly under the studied conditions. One of the primary influencers is the phenomenon of gas locking, where gas accumulation within the impeller hampers the consistent flow of liquid, thereby degrading the pump's efficiency. In addition, the model delineated the occurrence of the surging phenomenon across diverse gas volume fractions and rotational speeds, which further exacerbates the reduction in the ESP's performance. Intriguingly, the bubble diameter was identified as a decisive factor, especially at minuscule flow rates. Large bubble diameters instigate the formation of gas pockets on the suction side of the vane, culminating in a segregated flow pattern and further declining pump efficiency.On the other hand, the drag force is the primary interaction force between phases of gas-liquid flow. Other interfacial forces, such as lift and virtual mass force, change the pump's performance but do not affect the gas flow and distribution patterns for a one-stage configuration. Results show that the Schiller-Neuman drag coefficient offers a better fit than the Bozano-Dente coefficient.Conclusively, the study underscores the indispensable role of nuanced computational models in elucidating the intricate flow dynamics within ESPs, especially under conditions fraught with operational challenges. The insights gleaned enrich our understanding of ESP performance dynamics and provide a roadmap for designing more resilient and efficient pumping systems in the future.

Developing a Computational Fluid Dynamics-Finite Element Method Model to Analyze Thermal-Mechanical Stresses in a Heavy-Duty Medium-Speed Diesel Engine Piston During Warm-Up

Abstract Pistons play a vital role in internal combustion engines, affecting both performance and reliability, and are subjected to intense thermal-mechanical loads that have become more challenging due to improved engine efficiency and power. This study examines the thermal and mechanical stress experienced by a piston in a heavy-duty medium-speed diesel engine during warm-up. The heavy-duty diesel engines are typically used in heavy trucks, locomotives, and ships. A combination of computational fluid dynamics, finite element method, and matlab was used to consider factors such as oil temperature and flowrate, coolant temperature, component temperature, and boundary conditions during engine transient conditions. The results highlight the significant variations in the thermal and mechanical stress on the piston, particularly in the piston head under different warming-up conditions. It is noted that the variation in oil temperature is a crucial factor affecting the thermal stress on the piston. Low oil temperature can result in reduced heat exchange coefficient and inadequate cooling of the piston due to low flowrate of the cooling oil. During engine warm-up, both thermal and combined stresses reach maximum values and then decrease when the engine reaches stable operating conditions. By selecting appropriate warming-up modes, the quality of the warm-up process and the strength and longevity of the engine could be improved. This study also provides useful insights for technicians to prevent critical conditions that may damage the piston and reduce its strength and lifespan.

Research on optimization scheme for boiling heat transfer models of mini-channels casing-pipes once-through steam generator

The mini-channels casing-pipes once-through steam generator(MCOTSG) is used for a certain type of small modular reactor. The boiling heat transfer model is crucial to the accuracy of simulating the heat transfer process on the secondary loop of MCOTSG. In this paper, the heat transfer tubes of MCOTSG are taken as the research object. The thermal–hydraulic model of primary and secondary loops is established based on the RELAP5 program. Then the different nucleate boiling heat transfer models are calibrated and analyzed based on the experimental results of the steady state under low flow rate conditions. On this basis, the secondary loop heat transfer characteristics and the overall operating characteristics of OTSG under the transient state of feedwater flow rate reduction are simulated. The results of the steady state and transient state analysis show that the revised model that the Bertsch correlation is used to correct the Chen correlation performs the best in terms of computational stability and computational accuracy. The results of the study can provide a basis for the safety analysis and optimal design of MCOTSG and small modular reactor under low flow rate conditions.

Natural circulation oscillation in a seawater loop during startup

Aiming to improve nuclear safety by using seawater as an alternative emergency coolant during an accident, the knowledge of two-phase flow instabilities and heat transfer performances of seawater is needed. Startup experiments from the quiescent state at room temperature of 20–23 °C are carried out by raising heating power with 3.5 wt% artificial seawater in a natural circulation loop. De-ionized water is adopted as well for the comparative study. In this paper, a type of natural circulation oscillation at the modified heat fluxes of 383.70–530.62 kW/m2 and 404.05–594.97 kW/m2, respectively, for seawater and de-ionized water, with intermittent inlet mass flow rates is exclusively investigated, as a part of the experimental studies of two-phase flow instabilities during the startup of a natural circulation loop. Visualizations of two-phase flow behaviors at the power of 2206 W in seawater reveal the unique bubble foam regimes at the outlet of the heated section, tiny bubbles at the inlet of the riser, and the possible elongated slug bubbles at the central region of the riser.The natural circulation oscillations for two fluids are characterized by four distinct stages in sequence: calm state (stage 1), accumulations of foam/slug bubbles in seawater/de-ionized water (stage 2), propagations of foam/slug bubbles in seawater/de-ionized water (stage 3), and restorations (stage 4). The same period for stages 1, 3, and 4 for both fluids are 25 s, 4 s, and 5 s, respectively. For stage 2, the period measured as 12.5 s in seawater is significantly shorter than that recorded as 45 s in de-ionized water, leading to earlier systematic natural circulation rates. It is possibly caused by the much stronger accumulation effect of tiny bubbles in the riser, resulting in vast buoyant forces by draining more liquid out of the riser. The intermittent peak inlet mass flow rates of 0.017 kg/s and 0.023 kg/s are recorded, respectively, for seawater and de-ionized water. It would not induce a pressure drop increase over the riser while cause a very high pressure drop oscillation of 4.67 kPa in de-ionized water. Slower circulation rates induce smaller wall temperature drops of 3.6 °C in seawater than that of 5.2 °C in de-ionized water. Under zero flow rate conditions, the wall temperatures are mainly kept at 117–119 °C, accompanied by bubble foam without ruptures in seawater, while that are about 115 °C with slug bubbles due to bubble coalescences in de-ionized water. It demonstrates that the immobile foam may deteriorate the heat transfer under pool-like conditions.

Understanding the effects of inhaler resistance on particle deposition behaviour – A computational modelling study

Background and objectiveUnderstanding the impact of inhaler resistance on particle transport and deposition in the human upper airway is essential for optimizing inhaler designs, thereby contributing to the enhancement of the therapeutic efficacy of inhaled drug delivery. This study demonstrates the potential effects of inhaler resistance on particle deposition characteristics in an anatomically realistic human oropharynx and the United States Pharmacopeia (USP) throat using computational fluid dynamics (CFD). MethodMagnetic resonance (MR) imaging was performed on a healthy volunteer biting on a small mockup inhaler mouthpiece. Three-dimensional geometry of the oropharynx and mouthpiece were reconstructed from the MR images. CFD simulations coupled with discrete phase modelling were conducted. Inhaled polydisperse particles under two different transient flow profiles with peak inspiratory flow rates (PIFR) of 30 L/min and 60 L/min were investigated. The effect of inhaler mouthpiece resistance was modelled as a porous medium by varying the initial resistance (Ri) and viscous resistance (Rv). Three resistance values, 0.02 kPa0.5minL−1, 0.035 kPa0.5minL−1 and 0.05 kPa0.5 minL−1, were simulated. The inhaler outlet velocity was set to be consistent across all models for both flow rate conditions to enable a meaningful comparison of models with different inhaler resistances. ResultThe results from this study demonstrate that investigating the effect of inhaler resistance by solely relying on the USP throat model may yield misleading results. For the geometrically realistic oropharyngeal model, both the pressure and kinetic energy profiles at the mid-sagittal plane of the airway change dramatically when connected to a higher-resistance inhaler. In addition, the geometrically realistic oropharyngeal model appears to have a resistance threshold. When this threshold is surpassed, significant changes in flow dynamics become evident, which is not observed in the USP throat model. Furthermore, this study also reveals that the impact of inhaler resistance in a geometrically realistic throat model extends beyond the oral cavity and affects particle deposition downstream of the oral cavity, including the oropharynx region. ConclusionResults from this study suggest that key mechanisms underpinning the working principles of inhaler resistance are intricately connected to their complex interaction with the pharynx geometry, which affects the local pressure, local variation in velocity and kinetic energy profile in the airway.

Effects of Injector Configuration on the Detonation Characteristics and Propulsion Performance of Rotating Detonation Engine (RDE)

Fuel injection and mixing affect the characteristics of detonation initiation and propagation, as well as the propulsion performance of rotating detonation engine (RDE). A study on the injector is carried out in the present investigation. A rectangular-shaped hole-type fuel injector (RHFI) and slit-type fuel injector (SFI) were designed and compared experimentally at equivalent conditions. The investigation of the detonation propagation modes and the analysis of propulsion performance were carried out using fast Fourier transform (FFT), short-time Fourier transform (STFT), and unwrapped image post-processing. Under 50, 75, and 100 g/s flow rate conditions at an equivalence ratio of 1.0 ± 0.05, the RHFI has relatively stable detonation propagation characteristics, higher thrust, and specific impulse performance. Additionally, the results of the experiment indicate that the number of detonation waves affects performance.

A flow-rate-aware data-driven model of vanadium redox flow battery based on gated recurrent unit neural network

The vanadium redox flow battery (VRB) system involves complex multi-physical and multi-timescale interactions, where the electrolyte flow rate plays a pivotal role in both static and dynamic performance. Traditionally, fixed flow rates have been employed for operational convenience. However, in today’s highly dynamic energy market environment, adjusting flow rates based on operating conditions can provide significant advantages for improving VRB energy conversion efficiency and cost-effectiveness. Unfortunately, incorporating the electrolyte flow rate into conventional multi-physical models is overly complex for VRB management and control systems, as real-time operations demand low-computational and low-complexity models for onboard functionalities. This paper introduces a novel data-driven approach that integrates flow rates into VRB modeling, enhancing data processing capabilities and prediction accuracy of VRB behaviors. The proposed model adopts a gated recurrent unit (GRU) neural network as its fundamental framework, exhibiting exceptional proficiency in capturing VRB’s nonlinear voltage segments. The GRU network structure is carefully designed to optimize the predictive ability of the model, with flow rate considered as a crucial input parameter to account for its influence on VRB behavior. Model refinement involves analyzing well-designed simulation results obtained during VRB operations under various flow rates. Laboratory experiments were also designed and conducted, covering different conditions of currents and flow rates to validate the proposed data-driven modeling method. Comparative analyses were performed against several state-of-the-art algorithms, including equivalent circuit models and other data-driven models, demonstrating the superiority of the proposed GRU-based VRB model considering flow rates. Thanks to the GRU’s outstanding capability in processing time series data, the proposed model delivers impressively accurate terminal voltage predictions with a low error margin of no more than 0.023 V (1.3%) under wide operating ranges. These results indicate the efficacy and robustness of the proposed approach, highlighting the novelty and significance of accounting for flow rates in accurate VRB modeling for management and control system design.

Numerical Simulation Method for Flash Evaporation with Circulating Water Based on a Modified Lee Model

Flash evaporation processes are widely adopted in the desalination, food processing, waste heat recovery and other industries for heat extraction or product separation. In this paper, a pressure-driven phase transition model is developed by improving the Lee model and combined with the VOF (Volume of Fluid) method to numerically simulate the flash evaporation process. In this modified Lee phase transition model, the driving force for the rates of the local phase transition is calculated using the local temperature and static pressure magnitude. Numerical simulations are carried out in a water-circulating flash chamber and compared with the experimental results to obtain the values of the time relaxation parameters. And the non-equilibrium fraction of the outlet water can be effectively obtained under different conditions of flow rate, inlet temperature and initial liquid level height. The time relaxation factor takes values from 0.195 to 0.43 (Pout,v = 19.9 kPa) and from 0.31 to 0.92 (Pout,v = 31.2 kPa) with increasing superheat. In addition, the model can effectively represent the evolution of the unstable flow flash evaporation from the initial rapid boiling state to dynamic equilibrium.

Method Provides Real-Time Anomaly Detection for Drilling-Fluid Properties

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 212443, “Real-Time Anomaly-Detection Methodology for Drilling-Fluid Properties,” by Moacyr N.B. Filho, Thalles P. Mello, and Cláudia M. Scheid, Federal Rural University of Rio de Janeiro, et al. The paper has not been peer reviewed. _ Online drilling-fluid-measurement technologies have become an essential tool for drilling automation. While online density measurements are widespread, the availability of rheology measurements is increasing quickly, and additional properties are central to ongoing field trials. The complete paper presents the concept of supervisory and advisory systems dedicated to support the detection of abnormal events and to provide guidelines for fluid treatment. Introduction The Laboratory of Fluid Flow of the Federal Rural University of Rio de Janeiro and Petrobras developed a flow loop for the proposal and validation of online sensors for the measurement of drilling-fluid properties. In previous work, the authors described the development of a set of online sensors to measure fluid properties with control of operational conditions of temperature, pressure, and fluid flow rate. Following previous research, this study proposes a new method using a technique based purely on data to diagnose and detect deviations in drilling-fluid properties. The method proposed applies principal component analysis (PCA) for detecting anomalies in drilling fluids. Method PCA-Based Anomaly-Detection Technique. This method consists of the linear transformation of the space of monitored variables, which generates a new space of variables called principal components, in which each principal component is a linear combination of the process variable. This allows the new space of variables to be linearly independent—that is, the principal components are linearly independent, allowing the calculation of process monitoring statistics. The ability to detect anomalies in drilling-fluid properties is necessary to train the system in the normal state of operation. The training based on the normal state of operation was performed through the calculation of the principal-component matrix and the selection of the reduced principal-component matrix. Once the process model was trained, the monitoring of new samples was performed with the help of two statistical tools that described the health of the process operation: T² and Q statistics. The T² statistic measures variations in the main space. T² only detects variation in the subspace of the first principal components larger than those attributed to the dynamics of the process. The Q statistic denotes the change of events not explained by the principal-component model. It is a measure of the difference, or residual, between a sample and its projection on the model. The failure-detection procedure based on the use of PCA consisted of continuous assessments of whether process statistics were within or outside an acceptable range. A method previously proposed in the literature used control systems based on fuzzy logic to monitor properties of drilling fluids and propose corrections, which are performed automatically by an experimental unit containing actuators for additions of drilling agents as thickeners and viscosifiers. The application of fuzzy logic depends on inference rules, which must be provided to the system by the programmer. This is a limitation of corrective systems based on fuzzy logic.

Drag Reduction and Thermal Protection of the Combination of Aero Disk, Lateral Jet, and Rear Jet for Hypersonic Vehicle

This study proposes a combined scheme based on a spike-aero-disk, a lateral jet, and a rear jet to enhance hypersonic vehicles’ drag reduction and thermal protection performance. Numerical simulations were conducted using CFD methods to validate the scheme’s capabilities. The results demonstrate a significant improvement in drag reduction and thermal protection compared to the basic scheme with only a spike-aero disk. Furthermore, under the same mass flow rate conditions, the combined scheme with an extra rear jet is compared to a scheme with a spike-aero-disk-lateral jet, revealing a reduction of approximately 23.4% in the peak Stanton number, indicating a remarkable enhancement in drag reduction and thermal protection performance. The simulation results show that the use of lateral jet and rear jet improves the overall thermal protection ability and drag reduction ability of the vehicle.

Study on Unsteady Flow Characteristics of Cooling Water Pump for Nuclear Power Plant Equipment under Low Flow Rate Conditions

During the operation of cooling water pumps, it is necessary to operate them under conditions of low flow rate. In order to improve the unstable performance of the cooling water pump under low flow rate conditions. Taking the cooling water pump as the research object, the internal flow and pressure pulsation characteristics of the cooling water pump under 0.4Q to 0.6Q conditions were investigated, and the influence of different operating conditions on the performance and vibration of the cooling water pump was analyzed. The ANSYS CFX 2022 software and the SST k-ω turbulence model were used to perform a three-dimensional numerical simulation of the cooling water pump. After analyzing the simulation results, the velocity and pressure cloud and streamline diagram within the semi-spiral suction casing and impeller were obtained. The internal flow state of the cooling water pump was then analyzed in detail under low flow rate conditions. At the same time, a series of monitoring points were set up within the impeller, and the pressure pulsation within the impeller was analyzed using the frequency domain diagram and the radial force polar coordinate diagram. The results show that at flow rates between 0.4Q and 0.6Q, a certain amount of vortex has been generated in the suction casing, which affects the flow state when entering the impeller. Furthermore, significant vortices have been generated in the middle and back part of the blade and mainly concentrated in the pump cover of the mid-open pump. At the same time, when in low flow rate conditions, the primary frequency of pressure pulsation is mainly the axial frequency, with three times the axial frequency and blade frequency following. The amplitude of the pressure surface (PS) of the blade is greater than that of the suction surface (SS) and increases as the flow rate decreases. The internal radial force corresponds with the result of pressure pulsation and exhibits a certain pattern. This study outlines the coolant pump’s internal flow and pressure pulsation characteristics under low-flow conditions. It proposes a solution to stabilize the cooling water pump at low flow rates and provides theoretical guidance for optimizing its design.

Influence of noise masking on leak pinpointing: Experimental analysis on a laboratory test rig for leak noise correlation.

The efficient management of water distribution networks requires the detection and mitigation of leaks that result in significant water losses, economic costs, and potential health hazards. This experimental study focuses on the optimal frequency range for accurately locating a water leak in a distribution network using the noise correlation approach while mitigating the influence of background noise associated with water consumption from users. Through laboratory experimental tests, a digital bandpass filter was defined in order to pre-process signals and to improve cross-correlation analysis within the pertinent frequency range. This was done by characterising the frequency content of leak-induced noise, noise masking resulting from water consumption, and background noise. The analysed signals were recorded using hydrophones installed within the pipes of a laboratory test rig under different conditions of water flow rate. The spectra analysis assessed the influence of varying water flow rates on the acoustic sound field within the pipeline system. Additionally, the results of the analysis made it possible to discriminate clearly between noise generated by leaks and noise attributed to water consumption. This distinction is useful for implementing suitable filters, and also to establish a threshold ratio of leak flow rate to water consumption flow rate for effective pre-filtering. This study aims to establish a methodological framework that can effectively differentiate between acoustic signals stemming from leaks and noise generated by other sources within the system, to improve leak location accuracy through the noise correlation approach.