Pump Parameters Research Articles

Experimental and Simulation Investigations of Proppant Transport and Distribution Between Perforation Clusters in a Horizontal Well

Summary Multistage hydraulic fracturing is widely used to stimulate tight reservoirs by means of plug and perforation technology. The proppant distribution between perforation clusters significantly impacts fracture conductivity and well productivity. Uneven slurry distribution is often the norm rather than the exception. Proppant transport behaviors and distribution characteristics are still poorly understood in a horizontal wellbore with clusters, especially at field scales. The objective is to propose an innovative and feasible method to quantitatively evaluate the distribution uniformity of proppant between clusters. In this work, we systematically investigate proppant migration and placement by means of laboratory tests and numerical simulation. Computational fluid dynamics (CFD) and the discrete element method (DEM) are coupled to analyze proppant-fluid flow. The experimental observation and results validate the numerical model and calibrate critical parameters. The transport efficiency (E) and normalized standard deviation (NSD) are used to evaluate proppant distribution. The effects of nine parameters on the E and NSD are investigated at field ranges. The calibrated CFD-DEM model is accurate in studying proppant distribution between multiple clusters. The toe bias is the primary distribution between clusters because of the large inertia originating from high injection rates. Fluid distribution and perforation configuration are critical factors that significantly change the toe bias at the cluster level. Fluid redistribution changes proppant distribution toward the heel. The inline up pattern has the best uniformity, followed by the 180° up-down pattern. The secondary characteristic is bottom-biased within a cluster. Increasing fluid viscosity, using small and light proppants, and pumping high-concentration slurry can improve proppant distribution. The slurry diversion into perforations is hardly changed unless external conditions change. The combination of high-concentration slurry and a large bed quickly induces premature screenout at the toe-side cluster, especially when injecting large and high-density particles. Slurry redistributes toward the heel if the toe-side cluster is blocked. The investigation provides a rational and feasible method for operators to understand proppant transport between clusters and optimize pumping parameters under field situations.

Development of a pump-jet piezoelectric swimmer with acoustic radiation actuation

The acoustofluidic actuation produced by piezoelectric transducer is capable of propelling micro underwater robots forward, yet the motion pattern is relatively simplistic. To solve this problem, a pump-jet swimmer with a combination of the underwater acoustic radiation effect is proposed in this work. The absorption and discharge of internal piezoelectric pump provide the linear forward power, and turning is achieved under the acoustic propulsive force of the external dual piezoelectric actuators. The working mode and optimal driving frequency of the piezoelectric actuators are determined through finite element simulation and mechanical vibration characteristic tests. And the key dimensional parameters of the piezoelectric pump are optimized in the light of the output flow measurements. Finally, a prototype with the size of Ф3.1 cm × 12 cm is fabricated for underwater driving performance experiments, which demonstrated well functions in straight swimming, turning, and loading. The swimmer with 20 g of additional load achieves a maximum speed of 105 mm s−1at the voltage of 180 Vp-p, it also completes the obstacle avoidance in water along a certain path. The rationality of this conceived actuation mechanism is preliminarily verified, which shows a potential for fixed-point transportation in the complex underwater situations.

Impact of the HeartMate 3 Pump Speed Modulation Algorithm on Derived Pump Parameters and Measured Haemodynamic Variables

Impact of the HeartMate 3 Pump Speed Modulation Algorithm on Derived Pump Parameters and Measured Haemodynamic Variables

ГИДРАВЛИЧЕСКИЙ РАСЧЕТ СИСТЕМЫ ПОДАЧИ ПЛАВЛЕНОГО СЫРА КУЛАЧКОВЫМ НАСОСОМ

The purpose of the study is to develop a calculation method for a continuous supply system for highly viscous food masses, taking into account the characteristics of the pipeline, cam pump and rheological parameters of the pumped food liquid. The paper considered a system for supplying processed cheese with rheological parameters at temperatures from 55 to 95 °C. As a result of hydraulic calculations using published data, it was found that 1) calculation of the effective dynamic viscosity μE using the Ostwald formula with the found parameter values yields results very close to the experimental data obtained from open sources; 2) the dependence of the expended power N on the pressure is linear, on the rotor speed n is parabolic, and on the dimensionless dynamic viscosity coefficient μ is power-law; 3) the dimensionless dynamic viscosity coefficient μ has different effects on the productivity Q and the power N: for large values of μ, the effect on Q decreases, while on N, on the contrary, it increases;4) with the growth of viscosity of the pumped liquid, the energy efficiency of the cam pump first improves (the hydraulic efficiency of the pump η increases, the specific energy consumption indicator E decreases), and then begins to deteriorate. The characteristic of the process pipeline (dependence of the required pressure on the flow rate of pumped processed cheese) with a given length L, local resistances, static pressure PC for three values of the internal diameter is constructed. A method is proposed that allows determining the operating parameters of the liquid food supply system at the operating point, taking into account the influence of its viscosity (using the example of pumping processed cheese).

A Working Conditions Warning Method for Sucker Rod Wells Based on Temporal Sequence Prediction

The warning of the potential faults occurring in the future in a sucker rod well can help technicians adjust production strategies in time. It is of great significance for safety during well production. In this paper, the key characteristic parameters of dynamometer cards were predicted by a temporal neural network to implement the warning of different working conditions which might result in failures. First, a one-dimensional damped-wave equation was used to eliminate the dynamic loads’ effect of surface dynamometer cards by converting them into down-hole dynamometer cards. Based on the down-hole dynamometer cards, the characteristic parameters were extracted, including the load change, the position of the valve opening and closing point, the dynamometer card area, and so on. The mapping relationship between the characteristic parameters and working conditions (classification model) was obtained by the Xgboost algorithm. Meanwhile, the noise in these parameters was reduced by wavelet transformation, and the rationality of the results was verified. Second, the Encoder–Decoder and multi-head attention structures were used to set up the time series prediction model. Then, the characteristic parameters were predicted in a sequence-to-sequence way by using historical characteristic parameters, date, and pumping parameters as input. At last, by inputting the predicted results into the classification model, a working conditions warning method was created. The results showed that noise reduction improved the prediction accuracy significantly. The prediction relative error of most characteristic parameters was less than 15% after noise reduction. In most working conditions, their F1 values were more than 85%. Most Recall values could be restored to over 90% of those calculated by real parameters, indicating few false negative cases. In general, the warning method proposed in this paper can predict faulty working conditions that may occur in the future in a timely manner.

Toward Ultra-High-Quality-Factor Wireless Masing Magnetic Resonance Sensing.

It has recently been shown that a bolus of hyperpolarized nuclear spins can yield stimulated emission signals similar in nature to maser signals, potentially enabling new ways of sensing hyperpolarized contrast media, including most notably [1-13C]pyruvate that is under evaluation in over 50 clinical trials for metabolic imaging of cancer. The stimulated NMR signal emissions lasting for minutes do not require radio-frequency excitation, offering unprecedented advantages compared to conventional MR sensing. However, creating nuclear spin maser emission is challenging in practice due to stringent fundamental requirements, making practical in vivo applications hardly possible using conventional passive MR detectors. Here, we demonstrate the utility of a wireless NMR maser detector, the quality factor of which was enhanced 22-fold (to 1,670) via parametric pumping. This active-feedback technique breaks the intrinsic fundamental limit of NMR detector circuit quality factor. We show the use of parametric pumping to reduce the threshold requirement for inducing nuclear spin masing at 300 MHz resonance frequency in a preclinical MRI scanner. Indeed, stimulated emission from hyperpolarized protons was obtained under highly unfavorable conditions of low magnetic field homogeneity (T2* of 3 ms). Greater gains of the quality factor of the MR detector (up to 1 million) were also demonstrated.

Toward Ultra‐High‐Quality‐Factor Wireless Masing Magnetic Resonance Sensing

AbstractIt has recently been shown that a bolus of hyperpolarized nuclear spins can yield stimulated emission signals similar in nature to maser signals, potentially enabling new ways of sensing hyperpolarized contrast media, including most notably [1‐13C]pyruvate that is under evaluation in over 50 clinical trials for metabolic imaging of cancer. The stimulated NMR signal emissions lasting for minutes do not require radio‐frequency excitation, offering unprecedented advantages compared to conventional MR sensing. However, creating nuclear spin maser emission is challenging in practice due to stringent fundamental requirements, making practical in vivo applications hardly possible using conventional passive MR detectors. Here, we demonstrate the utility of a wireless NMR maser detector, the quality factor of which was enhanced 22‐fold (to 1,670) via parametric pumping. This active‐feedback technique breaks the intrinsic fundamental limit of NMR detector circuit quality factor. We show the use of parametric pumping to reduce the threshold requirement for inducing nuclear spin masing at 300 MHz resonance frequency in a preclinical MRI scanner. Indeed, stimulated emission from hyperpolarized protons was obtained under highly unfavorable conditions of low magnetic field homogeneity (T2* of 3 ms). Greater gains of the quality factor of the MR detector (up to 1 million) were also demonstrated.

A Health Monitoring Model for Circulation Water Pumps in a Nuclear Power Plant Based on Graph Neural Network Observer.

The health monitoring of CRF (circulation water) pumps is essential for prognostics and management in nuclear power plants. However, the operational status of CRF pumps can vary due to environmental factors and human intervention, and the interrelationships between monitoring parameters are often complex. Consequently, the existing methods face challenges in effectively assessing the health status of CRF pumps. In this study, we propose a health monitoring model for CRF pumps utilizing a meta graph transformer (MGT) observer. Initially, the meta graph transformer, a temporal-spatial graph learning model, is employed to predict trends across the various monitoring parameters of the CRF pump. Subsequently, a fault observer is constructed to generate early warnings of potential faults. The proposed model was validated using real data from CRF pumps in a nuclear power plant. The results demonstrate that the average Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) of normal predictions were reduced to 1.2385, 0.5614, and 2.6554, respectively. These findings indicate that our model achieves higher prediction accuracy compared to the existing methods and can provide fault warnings at least one week in advance.

Performance and economic study of a novel high-efficiency PEMFC vehicle thermal management system applied for cold conditions

This paper proposes three different heating management systems, sysse (self priming thermal management system), syslow (low temperature thermal management system), and syssp (split flow thermal management system), which are mainly composed of PEMFC and heat pump subsystems. Simulations were conducted to compare the comprehensive performance of these systems under cold startup and cold operating conditions, and analyzed the effect of different factors on these three system. The results show that under the influence of cell stack parameters, compared to sysse and syslow, the syssp has an average power consumption reduction of 29.95 % and 20.94 %, with a maximum power reduction of 31.46 % and 27.61 %, the average range power increases by 35.09 % and 23.58 %, with a maximum range power increase of 107.53 % and 75.57 %, the average COPPEMFC (Coefficient of Performance of heating Proton Exchange Membrane Fuel Cell) increases by 0.56 and 0.37. Under the influence of heat pump parameters, the evaporating temperature has a larger impact on the performance gains of the syssp, while condensing temperature has a greater effect on power consumption, range power, and COP variations. Compared to sysse and syslow, the syssp can recover costs as quickly as 3.12 and 3.68 years.

Application of CFD Simulation to the Design of an Innovative Drying Chamber

Drying and sanitising equipment has been very common in industrial plants since the pandemic. These are devices that consume significant amounts of energy. The best solution is to use a drying chamber equipped with a heat pump, which allows partial recovery of the energy. In the design of the drying chamber, the drying time is important, which depends both on the parameters of the heat pump itself, and the geometry and airflow of the drying chamber. The geometry and airflow supply should be arranged to ensure a uniform distribution of velocity throughout the drying area. For this purpose, the use of CFD simulations has been proposed. A model was developed in ANSYS/FLUENT where all model parameters, including the optimal mesh density, turbulence models, etc., were determined. The model was verified on the experimental results of the basic design of the chamber. Then an innovative design was proposed that was modelled and optimised in terms of the distribution of the inlet’s perforation. The final design was made, and, at the same time, the simulation’s results were verified by measuring the velocity of airflow in the new design. Together with the optimisation of the heat pump, this made it possible to reduce the drying time by 50%, with a simultaneous reduction in the energy consumed.

Test and analysis of energy characteristics of large vertical submersible pumps

The efficiency of the pump device is an important parameter to judge the overall dynamic performance of the pumping station. The commonly used method at home and abroad is to carry out model tests of the pump device. The performance parameters of the prototype pump and pump device are obtained by the similarity conversion formula. However, at present, there are not many device model tests for large vertical submersible pumps. Taking a large vertical submersible mixed-flow pumping station in China as an example, research predicted the performance of the pump device through a model test and a submersible pump prototype test. The results show that the model test of the large vertical submersible mixed-flow pump device has a maximum efficiency of approximately 77.8%, and the prototype test conversion device has a maximum efficiency of approximately 80.33%. The device model test and the pump factory prototype test results are compared. It is found that the performance parameters of the pump measured by the prototype test are in good agreement with the device model test under the design conditions, and there is a certain error when the deviation from the design conditions is significant. The device model test and the factory test of the pump are indispensable in the large-scale road of submersible pumps, and a large number of tests are needed to sum up the experience.

Study on the Influence of Working Characteristics of Centripetal Pump Based on VOF/Mixture Model

Aviation fuel contamination can seriously affect aircraft flight safety, and the centripetal pump is the core component of aviation fuel purification equipment. The performance of centripetal pumps is highly demanded for purification equipment. The operating parameters of centripetal pumps significantly affect the internal flow characteristics, which affects the performance of centripetal pumps. However, the flow characteristics of a centripetal pump influenced by the operating parameters have not yet been elaborated upon. In this research, a three-dimensional numerical simulation of the air-fuel two-phase flow field inside a centripetal pump was carried out using the VOF/Mixture model to investigate the effects of three relatively independent physical quantities, namely, fuel flow, outlet fuel discharge pressure, and rotational speed, on the operating characteristics of the centripetal pump. The flow law inside the flow channel of a centripetal pump was analyzed based on a rotating fluid pressure model, the free liquid surface radius of air-fuel, and the total pressure recovery coefficient. It was found that centripetal pumps have a steady working state and an unsteady working state. In a steady working state, the proportion of separated zones in the flow channel of the centripetal pump is small, the flow coefficient C of the flow channel is greater than 1, and the total pressure recovery coefficient of the centripetal pump is high. In an unsteady working state, the separation zone in the flow channel of the centripetal pump accounts for a large proportion, the flow channel flow coefficient C is less than 1, and the total pressure recovery coefficient of the centripetal pump is low. An unsteady working state can easily occur in small flow, high-speed conditions. By analyzing the working state and flow characteristics of the centripetal pump, the mechanism of the influence of the flow, outlet fuel discharge pressure, and rotational speed on the working state of the centripetal pump is revealed, which provides a basis for the stable operation of the centripetal pump.

Assessing the physicochemical properties of surface/groundwater of Sudhnoti district, Azad Jammu and Kashmir: Impacts on lindane degradation by photocatalysis

Since polluted water deteriorates the health of human beings and other animals, healthy society and environmental sustainability demand for clean and safe water. The presence of contaminants, and imbalance of common physicochemical parameters significantly disturb the quality of water. Taking the importance of clean and safe water into account, this study investigated fourteen physicochemical parameters of hand pump and open well water (main drinking water sources) from fifteen places of district Sudhnoti, Azad Jammu and Kashmir (AJK). The mean values of pH, electrical conductivity (EC), alkalinity, hardness and total dissolved solids (TDS) were 7.6, 349.9 μS/cm, 144, 152 and 190 mg/L, respectively. The mean concentration of Na+, K+, Ca2+, Mg2+, HCO3−, Cl−, SO42− and NO3− was found to be 9.5, 0.96, 9.9, 44.2, 144, 16.8, 8.1 and 6.67 mg/L, respectively. The turbidity as well as the concentration of CO32− was found below the detectable level in all water samples tested. Interestingly, all the studied physicochemical parameters had lower values than the maximum permissible level recommended by the world health organization (WHO) for drinking water. Eventually, the impacts of the studied physicochemical parameters, particularly anions and cation, on the efficiency of water treatment technology for real field application were discussed. The results revealed that physicochemical parameters of the groundwater of Sudhnoti, AJK had a slight effect on the degradation efficiency of one of the most widely used pesticides, lindane, in water by using ultraviolet–visible titanium oxide/hydrogen peroxide (UV–Vis)/TiO2/H2O2) and ultraviolet–visible/titanium oxide persulfate photocatalysis. Of note, the quality of hand pump and open well water which are the main drinking water sources of district Sudhnoti, AJK was found to be fit for drinking and other domestic purposes as well as for the ecosystem.

Clinical decision support system based on artificial intelligence for adjusting insulin pump parameters in children with type 1 diabetes mellitus

BACKGROUND: Widely available diabetes devices (continuous glucose monitoring, insulin pump etc.) generate large amount of data and development of an advanced clinical decision support system (CDSS), able to automatically evaluate and optimize insulin therapy, is relevant.AIM: Development of a mathematical model and an CDSS based on it to optimize insulin therapy in children with type 1 diabetes (T1D) and assessment of the agreement between the recommendations of the CDSS and the physician on insulin pump (IP) parameters: basal profile (BP), carbohydrate ratio (CR), correction factor (СF).MATERIALS AND METHODS: Data from 504 children with T1DM were analyzed over the period of 7875 days. The data included glucose, insulin, food, sex, age, height, weight, diabetes duration and HbA1c. We constructed recurrent neural network (RNN) to predict glucose concentration for 30-120 minutes, an algorithm for optimizing IP settings using prediction results. Next, a software product was developed — a CDSS. To assess the agreement of the recommendations of the CDSS and physicians, retrospective data from 40 remote telemedicine consultations of 40 patients with T1D (median age 11.6 years [7; 15]) were used and 960 points of possible adjustments were analyzed. Three degrees of agreement have been introduced: complete agreement, partial agreement, and complete disagreement. The magnitude of the adjustments was also analyzed.RESULTS: The accuracy of glycemic predictions was better or comparable with other similar models. The assessment of agreement for BP, CR and CF, according to the Kappa index, showed slight and weak agreement. The frequency of complete agreement between recommendations for adjusting the ongoing IP therapy between the CDSS and physicians is 37.5–53.8%, and complete inconsistency is 4.5–17.4%. From a clinical point of view, consistency in the frequency of occurrence of the indicator is more important. There were no differences in median IP settings between the CDSS and physicians.CONCLUSION: The CDSS has an acceptable accuracy of glycemic predictions. The CDSS and physicians provide comparable recommendations regarding CSII parameters.

A microfluidic manipulation platform based on droplet mixing technology

A microfluidic manipulation platform, utilizing droplet mixing technology in conjunction with piezoelectric actuation, has been constructed. This integration facilitates the realization of efficient and controllable mixing within micro-mixing chips. It boasts rapid droplet generation capabilities and enables precise control over droplet movement and internal mixing dynamics by modulating the operational parameters of the piezo pump. The pump itself offers a broad spectrum of output flow rates and pressures, ensuring ample power for the micro-mixing chip’s dispersed phase input. The platform’s actuation method combines active pressure and acoustic actuation. The efficacy of the platform is substantiated through numerical simulations and experimental validation. Furthermore, an optimization strategy employing support vector regression coupled with a particle swarm algorithm has been introduced for the micro-mixing chip. This method accurately forecasts data trends with minimal error margins. Notably, the micro-mixing chip’s mixing efficiency significantly increases, particularly at lower Reynolds numbers. Experimental findings indicate that the platform’s droplet mixing efficiency exceeds 95 %, rendering it a potent lab-on-a-chip solution for applications in bio-medicine, fine chemistry, and other fields.

Optimal refrigerant selection and parameter analysis of a wastewater heat pump using CO2 zeotropic mixtures

Heat pump technology can effectively recover waste heat from low-grade wastewater, which is crucial for energy conservation and carbon emission reduction in buildings. In this study, zeotropic mixtures were used to recover heat from low-grade wastewater and produce high-temperature water in a heat pump. The deep recovery of waste heat was realized by using a CO2 zeotropic mixture with a large glide temperature. Furthermore, this method ensures an excellent temperature matching between the heat transfer fluids and effectively reduces irreversible losses. To obtain an optimal zeotropic mixture, a method based on heuristic screening of the optimal CO2 zeotropic mixture was proposed. Furthermore, a model of a CO2 zeotropic mixture heat pump was established and experimentally validated. Based on the validated model, a sensitivity analysis of the various operating parameters of the heat pump was conducted. The results show that the zeotropic mixture CO2/R1234yf with a mass fraction of 0.17/0.83 is selected as the optimal refrigerant for the heat pump with the coefficient of performance, exergy efficiency and volumetric heating capacity of 7.46, 0.37, and 7978 kJ⋅m−3, respectively. The sensitivity analysis of operating parameters shows that the inlet temperature of hot water has more crucial influence on the coefficient of performance and exergy efficiency than various operating parameters, with sensitivity coefficients of −0.3868 and 0.2157, respectively. The volumetric heating capacity and system total exergy destruction per heating capacity unit are most sensitive to the flow rate of wastewater and hot water, with sensitivity coefficients of 0.1121 and −0.4985, respectively. These results provide a foundation for the design and optimization of a CO2 zeotropic mixture heat pump system.

Teaching Families How to Manage Diabetic Emergencies Using Their Children as Patient Simulators

Objectives The aims of the study are to develop an insulin pump simulation curriculum using patients as simulators, to evaluate its effectiveness on knowledge, attitudes, and skills necessary for families to manage diabetic emergencies, and to identify ongoing gaps in care. Methods Our simulation curriculum developed using Kerns, consisted of 4 stations. A prospective simulation study was conducted at a pediatric tertiary care hospital with a convenience sample of children with type 1 diabetes on the insulin pump program and their families using patients as simulators and their parents as participants. The curriculum's success with developing competent skills was assessed using Kirkpatrick's 4-level evaluation model. Data from satisfaction questionnaires, performance gaps in emergency management, and postsimulation knowledge questionnaires were analyzed to identify ongoing gaps in care using a mixed methods approach. Results Among 70 families (169 participants), satisfaction was high (3.7–4.0/4.0) and confidence was increased (mean score 12 ± 0.03/12). Recurrent performance gaps across scenarios were found: misunderstandings about residual insulin during hypoglycemia (35%) and severe hypoglycemia with altered level of consciousness (22%), and failure to identify causes in 13% of simple and 11% of severe hypoglycemia scenarios and overtreating hypoglycemia with glucagon in a conscious patient in 14% of simple hypoglycemia scenarios. Postsimulation knowledge questionnaires revealed improvements in knowledge/management of simple hypoglycemia (mean score 87%), poor knowledge of pump parameters (mean score 56%), excellent knowledge of manipulating pump parameters to prevent emergencies (mean score 100%), and poor knowledge of basal rate concepts (mean score 19%). Conclusions Simulation using patient simulators improved management skills and confidence of families facing diabetic emergencies. Ongoing gaps in care were identified and used to enhance the current curriculum. Integrating simulation into insulin pump curricula can enhance patient self-care, safety, and be generalizable to other chronic-care patient-education programs. Future work should evaluate the impact of this curriculum on real-life events and patient outcomes.

Influence of blade wrap angle on internal flow and wear performance of solid-liquid two-phase centrifugal pump with semi-open impeller

Blade wrap angle is one of the main parameters of centrifugal pump, which has an important influence on the internal flow characteristic and pump performance. In this work, five impeller models with different blade wrap angles (85°, 95°, 105°, 115°, and 125°) are established on the condition of other impeller parameters remain unchanged, whose external characteristic, internal flow, and wear were analyzed by numerical simulation method. The results show that the influence of blade wrap angle on efficiency is more significant than head, has a certain effect on the internal flow field of the centrifugal pumps and effects the wear position of pressure surface. With the increasing of blade wrap angle, the pump efficiency increases companied by the pump head decreases slightly, the area of higher speed at the outlet of the impeller tends to decrease, the higher speed wake area at the end of the blade pressure surface breaks and shrinks, the vortex in the impeller passage is fewer and smaller, the turbulent kinetic energy and morphology of vortex inside the pump decreases gradually, and the wear rate of the flow passage components shows a pattern of first decreasing and then increasing.

Effect of Blade Thickening Law on the Internal Flow Field and Hydraulic Performance of Double Suction Pumps for Yellow River Pumping

Abstract The thickness of the blades is a fundamental parameter of the impeller and has a substantial impact on the performance of the pump. With the other geometric parameters of a centrifugal pump fixed, six kinds of impellers with different blade thickness were designed. Numerical simulations of the pumps were performed with Fluent under six different operating conditions based on the RNG k-epsilon equation and the SIMPLE algorithm. The hydraulic performance of the pump and its external characteristics were analysed based on the internal flow field to understand the relationship between blade thickness and performance. The results have showed that the hydraulic performance of the pump increases with the backward movement of the maximum thickness of the blade; Under the same sand concentration, the efficiency increases slightly with the increase of blade thickness within a certain range;With the increase of blade thickness, the turbulent kinetic energy loss of the pump under design operating conditions increases continuously; The thickening rules of schemes A1 and B can improve the hydraulic performance of the pump and the transport capacity of the sediment laden two-phase flow. That is, on the premise of meeting the structural strength of the blades, selecting a reasonable blade thickness can ensure that the double suction pump has good hydraulic performance.

Parametric interaction of laser cavity-solitons with an external CW pump

We study the interaction of a laser cavity-soliton microcomb with an externally coupled, co-propagating tunable CW pump, observing parametric Kerr interactions which lead to the formation of both a cross-phase modulation and a four-wave mixing replica of the laser cavity-soliton. We compare and explain the dependence of the microcomb spectra from both the cavity-soliton and pump parameters, demonstrating the ability to adjust the microcomb externally without breaking or interfering with the soliton state. The parametric nature of the process agrees with numerical simulations. The parametric extended state maintains the typical robustness of laser-cavity solitons.