Optimal Injection Research Articles

An Analysis Model for Predicting Windage Power Loss of Aviation Spiral Bevel Gears Under Optimal Injection Jet Layout

With the increasing rotating speed of aviation spiral bevel gears, the load-independent windage power loss caused by hydrodynamic behavior has a greater impact on transmission efficiency. An analytical model is established to predict the windage power loss of spiral bevel gears with oil injection lubrication. The improved model regards the total windage losses as the sum of oil–gas dragging effects on the tooth flank, toe/heel, circular cone surface, circumference of the teeth, and tooth root. Then the numerical method and analytical method are combined to calculate windage losses. A multi-objective NSGA-II optimization algorithm is used to optimize the jet layout parameters. The rationality and accuracy of this model are verified by comparing the calculation results of an example with data sets of existing experimental findings and computational fluid dynamics (CFD) simulation results. The calculation results show that compared with the tooth profile assumption method in the existing literature, the improved calculation formula of windage dragging effect on tooth flank can better reflect the influence of oil injection lubrication layout parameters on windage loss and make the windage loss calculation more accurate. Finally, the influence of gear body parameters, working conditions parameters, geometric parameters, and injection lubrication layout parameters on the windage loss is examined. This research provides a theoretical basis and methodological guidance for optimization design of reducing windage power loss.

Optimal Injection Distance in Ultrasonic Water Flow Cleaning

Cleaning tests with ultrasound-superposed water jets are performed to explore the optimal injection distance from the jet nozzle to a glass plate spin-coated with small silica particles (as a cleaning sample). The cleaning performance is evaluated based on particle removal efficiency (PRE) that is calculated using the haze method. Visualization of the water jet and liquid film flow over the cleaning target shows that the jet flow with short injection distance tends to be in a steady state, while the water jet shape instability grows for long injection distance, leading to atomization of the jet. The cleaning tests with varying the injection distance suggest that there exists an optimal injection distance at which the PRE becomes maximal.

A new hybrid rate optimization method to enhance oil recovery from Brugge field using streamline-driven injection efficiencies

BackgroundOptimization of waterflooding projects traditionally focuses on optimizing rate control of injector/producer wells to enhance recovered oil from reservoirs. In such projects, a complex, constrained, multi-variable problem is optimized to enhance the oil recovery performance of reservoirs. MethodsStreamline-based rate optimization has been applied as a robust method to find the optimal water injection strategy. The present study aims to optimize injector/producer wells rates using streamline-driven injection efficiencies. A heuristic algorithm (the so-called weights algorithm) was used in previous works. This study proposes a new hybrid particle swarm optimization (PSO)-weights method. The weights algorithm oil recovery results are dependent on the initial guesses to start searching the domain. PSO global search ability provides a proper set of initial guesses for the weights algorithm. Significant findingsThe hybrid method is implemented to optimize two reservoir models. First, the PSO-weights algorithm is applied on a 2-D homogenous model with 13 wells; after optimization, injectors/producers’ computed rate converged to known optimal rates. Second, the proposed algorithm has been tested to optimize the Brugge field and successfully afforded it quickly. The field oil production rate (FOPR) and the total field oil production (FOPT) results indicate an improvement in oil production. In addition, less trapped oil in saturation contours in different reservoir layers is reported.

Ultrastable emissive perovskite nanocomposite via dual protection of polymer-grafted TS-1 zeolite for backlight display application

Instability of all-inorganic perovskite quantum dots (PQDs) driven by the inherent ionic nature poses a grand challenge towards their long-term stability in optoelectronic devices. Herein, we report the crafting of a highly stable dual-protected CsPbBr3 perovskite nanocomposite by capitalizing on the encapsulation of a hydrophobic Styrene-Divinylbenzene (St-Dvb) copolymer grafted hierarchical titanium silicalite-1 (TS-1) zeolite shell. Firstly, an optimal hot injection method was used to accommodate CsPbBr3 PQDs into hierarchical TS-1 zeolite. After the modification of terminated Si-OH groups on the surface of TS-1 by phenyltriethoxysilane (PTES), a subsequent polymerization of St and Dvb was implemented using azobisisobutyronitrile (AIBN) as initiator to result in the highly emissive CsPbBr3-TS@St-Dvb nanocomposite, exhibiting outstanding luminescent stability against heat, polar solvents, and UV light irradiation. The as-prepared CsPbBr3-TS@St-Dvb nanocomposite also showed strongly suppressed anion exchange and high compatibility in polymer matrix, enabling improved applicability for versatile lighting and optical display applications. Ultimately, a white light-emitting diode (WLED) composed of green-emitting CsPbBr3-TS@St-Dvb and red-emitting K2SiF6:Mn4+ phosphor onto a commercial blue InGaN LED chip with wide color gamut and excellent stability is demonstrated. This work highlights a judiciously-designed and hard-soft dual-protected strategy to produce ultrastable perovskite nanomaterials with high brightness and durability for backlight display application.

Evaluation of Foam Gel Compound Profile Control and Flooding Technology in Low-Permeability Reservoirs

In the waterflooding development of fractured ultra-low permeability reservoirs, the heterogeneity is becoming increasingly serious. The development of large fracture channels leads to serious water channelling and low recovery, and the effect of conventional profile control is not ideal. This paper proposed gel foam composite profile control and flooding technology to solve the above problems. Herein, the new intelligent gel and foaming agent systems were optimized through laboratory experiments, and their performance was evaluated. The new intelligent gel system has the characteristics of low viscosity, easy preparation, good injection, slow cross-linking, high strength, and long-term effectiveness. The injection parameters were optimized, and the indoor injection scheme was formulated, that is, the optimal injection volumes of gel and foam slugs were 0.3 and 0.6 PV, respectively. The injection sequence of composite slugs was to inject gel slugs first, then foam slugs. The injection mode of air foam slugs was multiple rounds of small slug injection. The final recovery rate in the indoor dual tube oil displacement experiment reached 35.01%, increasing by 23.69%. Furthermore, an oil output increase of 899 t and an average water cut decrease of 5% were acquired in the oil field test. It shows that the injection scheme can effectively improve oil recovery. The gel foam compound profile control and flooding technology herein has good adaptability in similar reservoirs and has good promotion prospects.

Study on Nitrogen Injection Fire Prevention and Extinguishing Technology in Spontaneous Combustion Gob Based on Gob-Side Entry Retaining.

Under the gob-side entry retaining mining mode with roof cutting and pressure relief (GERRC), the gob and retained roadway section are interconnected to create an open area. Owing to the increased airflow, the coal remnants in the gob are more prone to spontaneous combustion. This study aimed to investigate the distribution of oxygen concentration within a gob and identify optimal parameters for nitrogen injection. The engineering context was the "110 method" introduced in the 1201 working face of the South Five mining area at Daxing. Computational fluid dynamics simulation software was used to analyze the effects of various nitrogen injection treatment parameters on the overall performance of the gob, including their impact on oxygen distribution. The simulation results showed that air leakage within the gob primarily originates from the working face adjacent to the intake roadway, as well as gaps within the retained roadway. The increased air leakage causes the high O2 concentration range in the gob to expand, and the retained roadway section is connected to an area with a high concentration of oxygen near the working face, which increases the risk of residual coal spontaneous combustion. The results show that the optimal nitrogen injection conditions for inerting and reducing the risk of spontaneous combustion within the gob require an injection quantity of 500 m3/h, with the injection point located at a depth of 60 m. With these parameters, the range of the oxidation zone was significantly reduced. To monitor the O2 concentration and temperature change curves in the gob during the project implementation, a bundle tube monitoring system was used, considering the actual mining situation. By varying the nitrogen injection spacing and quantity, we found that injecting nitrogen at a spacing of 30 m and at a quantity of 500 m3/h effectively placed most areas of the gob in the suffocation zone, reducing the risk of spontaneous combustion of residual coal. The accuracy of the simulation was verified. The study offers valuable insights into improving safety in coal mines and reducing spontaneous combustion incidents, providing important reference significance for fire prevention and control.

Anatomical Considerations for the Injection of Botulinum Neurotoxin in Shoulder and Arm Contouring.

The utilization of botulinum neurotoxin in the field of body contouring is on the rise. Body contouring procedures typically focus on specific muscle groups such as the superior trapezius, deltoid, and lateral head of the triceps brachii. The authors propose identifying optimal injection sites for botulinum neurotoxin to achieve desired aesthetic contouring of the shoulders and arms. The authors conducted a modified Sihler's staining method on specimens of the superior trapezius, deltoid, and lateral head of the triceps brachii muscles, totaling 16, 14, and 16 specimens, respectively. The neural distribution exhibited the most extensive branching patterns within the horizontal section (between 1/5 and 2/5) and the vertical section (between 2/4 and 4/4) of the superior trapezius muscle. In the deltoid muscle, the areas between the anterior and posterior deltoid bellies, specifically within the range of the horizontal 1/3 to 2/3 lines, showed significant intramuscular arborization. Furthermore, the middle deltoid muscle displayed arborization patterns between 2/3 and the axillary line. Regarding the triceps brachii muscle, the lateral heads demonstrated arborization between 4/10 and 7/10. The authors recommend targeting these regions, where maximum arborization occurs, as the optimal and safest points for injecting botulinum toxin.

Evaluation of hydrogen injection and oxygen enrichment strategies in an ammonia-hydrogen dual-fuel engine under high compression ratio

Ammonia with low reactivity still faces some challenges as the main fuel for engines. Hydrogen and oxygen, as two combustion improvers, are expected to solve ammonia’s reluctance to combust. To date, the application of oxygen enrichment strategies in ammonia-hydrogen dual-fuel engines is very rare, which motivates this study. The main objective of this investigation is to explore optimal hydrogen injection strategies and evaluate the effectiveness of oxygen enrichment strategies for the engine. Optimizing hydrogen injection parameters can vary the ammonia-hydrogen premixing degree, thus improving the flame kernel formation and flame propagation velocity. This is supported by the shortened CA0-90, lowered cyclic variation, and elevated thermal efficiency and power. Oxygen-enriched strategies enhance the heat release process and mitigate the negative effects of ammonia on the ignition process, which reduces cyclic variation and prominently increases power. However, the elevated oxygen concentration may increase the adiabatic flame temperature of the mixture and thus heat transfer loss, which decreases brake thermal efficiency. Moreover, a hypothesis that an ammonia-hydrogen engine may be employed in a hybrid power system in the future is proposed. The results of this work can be used as raw data for developing a hybrid power system.

Heat Transfer Included Simulation of Carbonate Rock Acidizing Using Two-Scale Continuum Model with Varying Rock Physics Curves

Summary Matrix acidizing is the commonly used method to enhance permeability of a damaged zone around the well. Acid injection will dissolve the rock, creating narrow, high-permeability channels, called wormholes, to bypass the damaged zone. The pattern of wormhole generation indicates the efficiency of the well stimulation process. Although the injection rate has the most important role in this process, there are other factors such as rock properties, presence of an immiscible phase, and temperature variation that could also affect the dissolution pattern. A few studies have considered the simultaneous effects of all phenomena involved in the acidizing process. We have developed a two-phase heat transfer model coupled with a two-scale continuum model considering capillary and gravity forces for the first time, to simulate the wormhole dissolution pattern. It could be used to analyze the dissolution phenomenon of carbonate rock. A new two-phase relative permeability model is implemented to take the effect of dissolution on relative permeability curves into account. The influence of acid-rock temperature difference, reaction heat, nonisothermal condition, phase saturation, formation porosity, intrinsic permeability and heterogeneity on dissolution pattern, and number of injected pore volumes (PVs) before acid breakthrough is investigated in the developed model. The simulation results show that both optimum injection rate and required PV of acid to breakthrough are strongly dependent on acid and rock temperatures. High formation temperature increases both the optimum injection rate and the optimum number of injected PVs before breakthrough. Injection of acid at lower temperatures will decrease both the optimum injection rate and the optimum number of injected PVs to break through. Simulation results show that the optimum number of injected PVs to break through is 8% higher when reaction heat is considered. Formation properties and degree of heterogeneity influence the number of required injected PVs to breakthrough. Low porosity formations with high heterogeneity correspond to the lowest number of injected PVs to breakthrough. The results indicated that formations with higher permeability will have a higher optimum number of injected PVs to break through and an optimum injection rate. Simulated results show that increasing the initial water saturation will increase the volume of acid to breakthrough. Variation in initial water saturation has a minor effect on wormhole shape, but it does not change the dissolution regime.

Intelligent Optimization of Gas Flooding Based on Multi-Objective Approach for Efficient Reservoir Management

The efficient development of oil reservoirs mainly depends on the comprehensive optimization of the subsurface fluid flow process. As an intelligent analysis technique, artificial intelligence provides a novel solution to multi-objective optimization (MOO) problems. In this study, an intelligent agent model based on the Transformer framework with the assistance of the multi-objective particle swarm optimization (MOPSO) algorithm has been utilized to optimize the gas flooding injection–production parameters in a well pattern in the Middle East. Firstly, 10 types of surveillance data covering 12 years from the target reservoir were gathered to provide a data foundation for model training and analysis. The prediction performance of the Transformer model reflected its higher accuracy compared to traditional reservoir numerical simulation (RNS) and other intelligent methods. The production prediction results based on the Transformer model were 21, 12, and 4 percentage points higher than those of RNS, bagging, and the bi-directional gated recurrent unit (Bi-GRU) in terms of accuracy, and it showed similar trends in the gas–oil ratio (GOR) prediction results. Secondly, the Pareto-based MOPSO algorithm was utilized to fulfil the two contradictory objectives of maximizing oil production and minimizing GOR simultaneously. After 10,000 iterations, the optimal injection–production parameters were proposed based on the generated Pareto frontier. To validate the feasibility and superiority of the developed approach, the development effects of three injection–production schemes were predicted in the intelligent agent model. In the next 400 days of production, the cumulative oil production increased by 25.3% compared to the average distribution method and 12.7% compared to the reservoir engineering method, while GOR was reduced by 27.1% and 15.3%, respectively. The results show that MOPSO results in a strategy that more appropriately optimizes oil production and GOR compared to some previous efforts published in the literature. The injection–production parameter optimization method based on the intelligent agent model and MOPSO algorithm can help decision makers to update the conservative development strategy and improve the development effect.

Anatomical proposal of local anesthesia injection for median nerve block in treating hyperhidrosis with botulinum neurotoxin.

Hyperhidrosis, causing excessive sweat, can be treated with Botulinum neurotoxin injection. Botulinum toxin, an effective and safe treatment for hyperhidrosis, unfortunately involves significant pain due to multiple injections. This study aims to propose a more efficient and less painful approach to nerve blocks for relief, by identifying optimal injection points to block the median nerve, thereby enhancing palmar hyperhidrosis treatment. This study, involving 52 Korean cadaver arms (mean age 73.5years), measured the location of the median nerve relative to the transverse line at the pisiform level to establish better nerve block injection sites. In between the extensor carpi radialis and palmaris longus, the median nerve was located at an average distance of 47.39 ± 6.43mm and 29.39 ± 6.43mm from the transverse line at the pisiform level. To minimize discomfort preceding the botulinum neurotoxin injection, we recommend the optimal injection site for local anesthesia to be located 4cm distal to the transverse line of the pisiform, within the tendons of the palmaris longus and flexor carpi radialis muscles.

Optimization of Indocyanine Green for Intraoperative Fluorescent Image-Guided Localization of Lung Cancer; Analysis Based on Solid Component of Lung Nodule.

ICG fluorescence imaging has been used to detect lung cancer; however, there is no consensus regarding the optimization of the indocyanine green (ICG) injection method. The aim of this study was to determine the optimal dose and timing of ICG for lung cancer detection using animal models and to evaluate the feasibility of ICG fluorescence in lung cancer patients. In a preclinical study, twenty C57BL/6 mice with footpad cancer and thirty-three rabbits with VX2 lung cancer were used. These animals received an intravenous injection of ICG at 0.5, 1, 2, or 5 mg/kg, and the cancers were detected using a fluorescent imaging system after 3, 6, 12, and 24 h. In a clinical study, fifty-one patients diagnosed with lung cancer and scheduled to undergo surgery were included. Fluorescent images of lung cancer were obtained, and the fluorescent signal was quantified. Based on a preclinical study, the optimal injection method for lung cancer detection was 2 mg/kg ICG 12 h before surgery. Among the 51 patients, ICG successfully detected 37 of 39 cases with a consolidation-to-tumor (C/T) ratio of >50% (TNR: 3.3 ± 1.2), while it failed in 12 cases with a C/T ratio ≤ 50% and 2 cases with anthracosis. ICG injection at 2 mg/kg, 12 h before surgery was optimal for lung cancer detection. Lung cancers with the C/T ratio > 50% were successfully detected using ICG with a detection rate of 95%, but not with the C/T ratio ≤ 50%. Therefore, further research is needed to develop fluorescent agents targeting lung cancer.

A novel method for preventing technical challenge during drilled cuttings/produced water reinjection: An injection rate management tool

Drilled cuttings reinjection (DCRI) is arguably the most cost-effective technique for disposing of drilling wastes, especially under the zero-discharge policy. However, there are many failed operations due to technical issues related to surface pumps and annular pressure. Currently, there is no sophisticated model for predicting an optimum injection rate that prevents technical failure during DCRI. The practice of using an arbitrary rate is not based on sound engineering principles and may be unable to prevent annular or pump failure. This is because operators do not relate the injection rate to the Maximum Allowable Surface Pressure (MASP) and/or the Maximum Allowable Annular Surface Pressure (MAASP). Due to these limitations, operators seek to find new methods to handle DCRI through the annulus. Thus, this study was carried out to derive a model systematically for the optimum injection rate to prevent technical challenges during DCRI. The components combined include the mechanical energy balance (MEB) and the model for hydraulic horsepower (HHP). The MEB between the wellhead and the annulus was used to derive a model for the annular pressure. Mechanical equilibrium between the STP and the MASP was used to generate another equation, based on the HHP. Then, the new expression was substituted into the annular pressure model. Lastly, the optimum rate was derived based on mathematical principles. The results applied to Well B of the Niger Delta showed a value (2.95 Bbl/min or 675.37 m3/day) that is consistent with the existing field database, and outperformed other related models for flow rate. Simulation results showed that the annular size (78.8%), rheological parameters (12.4%), and MASP (2.9%) were the main factors that affected the optimum injection rate. Thus, we can apply a higher injection rate in larger annuli compared to smaller ones, and to maintain annular pressure simply ensure uniform annulus devoid of erosion/thermal effects.

Optimal performance of water-oil axial jet pump in an egyptian offshore oil field

The jet pump is an artificial lift employed when the reservoir pressure declines and the well deviation increases. The use of computer well models for optimizing the oil well output has proven to be a successful strategy, and has helped increasing the efficiency and production of numerous wells. The objective of this study was to use a production optimization technique that achieves some improvements, and recommend approaches toward increasing the oil well production. The effects of the motive fluid flow rate and pressure on the oil production rate were investigated to determine the optimal injection rate and pressure on the performance of the deep well water-oil axial jet-pump. Additionally, the effects of the well-head pressure, water cut, and roughness of tubing on oil production of this jet pump type were investigated. The results revealed that the impact on the oil lift performance is significant. The oil production increased by 19.43%, and the optimal economic value for the injection rate and pressure for the GA-1A well are 744.44 BFPD and 2722.22 psig, respectively. In summary, increasing the tubing roughness decreased the well's total liquid production. Thus, maintaining the well integrity is a very important factor because not doing so can lower the productivity by up to 20%–25%.

Three‐dimensional simulation of the acidizing process under different influencing factors in fractured carbonate reservoirs

AbstractMatrix acidizing is widely used to enhance oil/gas production in the exploitation of carbonate reservoirs. In this work, a three‐dimensional (3D) hydro‐chemical‐thermal (H‐C‐T)‐coupled model was presented to improve the understanding of the acidizing process. The influence of different influencing factors was analyzed, especially the coupling effect of natural fractures and in situ stress. With the increase in acid injection concentration, the minimum pore volume of acid required for breakthrough (PVBT) decreases. The optimal injection rate and the minimum PVBT increase with increasing initial reservoir temperature. With the increasing initial reservoir permeability, the minimum PVBT increases. With the increasing initial reservoir pore diameter and specific surface area, the minimum PVBT and the optimal acid injection rate increase. When the fracture direction is perpendicular to the direction of the maximum principal stress, the fracture apertures decrease with the increase of the maximum principal stress, which leads to an increase in PVBT and wider paths of wormholes. Lastly, the present H‐C‐T‐coupled model was applied in the context of Tahe reservoir exploitation, which shows that optimizing the acid injection rate is able to enhance the connection between wellbores and natural caves.

Application of the closed loop industrial internet of things (IIoT)‐based control system in enhancing the oil recovery factor and the oil production

AbstractA non‐linear large scale stochastic optimisation model for enhancing the oil production and the recovery factor of the offshore oil reservoirs is proposed. The model aims at minimising the miss‐match between mathematical model and the actual dynamic behaviour of the reservoir and the exploitation time, while maximising the oil production and the recovery factor. The model involves the three dimension (3D) oil reservoirs equipped with a few vertical injection and production wells. The limited number of wells is one of the major features of the common oil reservoirs in the middle‐east region. The proposed model consists of the primarily mathematical model of the 3D reservoir, a model update algorithm and a large scale constrained non‐linear optimisation algorithm. The input to this model is the daily production rate of the oil, natural gas and water produced from the oil reservoir and the output is the optimal injection rate to be injected to the injection wells in order to maximise the oil production and the recovery factor. In order to evaluate the performance of this model, the authors apply this model on part of one of the Iran's offshore oil reservoirs and study the performance improvement due to the proposed model and compare its performance with the performance of the available Improved Oil Recovery (IOR) technique. It is illustrated that the proposed model can increase the oil production from the reservoir up to 47.96% and reduce the exploitation period up to 66.66% compared with those of the available technique.

Botulinum toxin in the management of parkinsonian disorders

Many studies have shown that botulinum toxin (BoNT) can be an option to treat motor and non-motor symptoms in Parkinson's disease (PD) and parkinsonian syndromes. The advantages of BoNT compared to oral medications include localized action and low incidence of systemic side effects, which is important in treating neurodegenerative disease. Motor symptoms that can be treated with BoNT include blepharospasm, apraxia of eyelid opening, tremor, cervical dystonia and limb dystonia. Other indications with less evidence include camptocormia, freezing of gait and dyskinesia. Non-motor symptoms that may improve with BoNT include sialorrhea, pain, overreactive bladder, dysphagia and constipation. However, the current evidence for use of BoNT in parkinsonism is mostly based on open-label studies and there are few randomized, controlled trials. BoNT can be a valuable tool to treat certain symptoms of PD and parkinsonian syndromes to improve the patient's quality of life. However, many of the uses are not supported by high quality studies and further studies are needed to provide further evidence of efficacy, define the optimal injection protocols such as doses and muscle selection.

Injection parameter design to improve the high-speed gear heat dissipation: CFD simulation and regression orthogonal experiment

A heat dissipation model of high-speed helical gears based on Computational Fluid Dynamics (CFD) is proposed under injection lubrication. Gear heat dissipation is investigated by static and dynamic heat flow coupling. The oil injection lubrication test is designed to measure tooth temperature by an infrared thermal imager. The results show that owing to the gear centrifugal force, the oil splash, and the blocking effect of the high-speed airflow, the average temperature first decreases and then increases, and the temperature difference increases first and then decreases with the increase in injection angle, distance, and velocity. The average temperature and temperature difference are remarkably affected by the injection velocity and distance, respectively. The optimal injection angle, distance, and velocity predicted by the regression orthogonal method are 9.212°, 54.514 mm and 35.561 m/s, respectively. Infrared thermometry experiments show that the optimal injection parameters enhance the gear heat emission by 6.93%. These findings provide support for the heat dissipation study and injection system design for aerospace gears.

Deep reinforcement learning to discover multi-fuel injection strategies for compression ignition engines

Over the past several decades, regulation of compression ignition engine emissions has become increasingly stringent as concern about the environmental and health implications of these emissions has grown. These changing constraints have led to a series of new, alternative fuel injection strategies that aim to maintain power output while reducing in-cylinder generated emissions by operating in the low-temperature combustion (LTC) regime. These advanced injection strategies are created and retuned for individual combinations of engine geometry, fuel, and emissions constraints. Deep reinforcement learning has been shown to be an effective alternative to traditional optimization approaches for highly combinatorial control problems, such as discovering the optimal injection schedules for compression ignition engines. In this study, we deploy a previously presented deep reinforcement learning framework to iteratively optimize a series of engine geometries over a range of increasingly strict NO x emissions regulations. We then examine the resulting injection schedules. We discuss the potential for using this deep reinforcement learning framework for fuel selection screening and for discovering unique injection strategies for different engine geometries and future emissions standards.

Performance Analysis of Transcritical CO2 Quasi-Secondary Compression Cycle with Ejector Based on Pinch Point

To investigate the performance of transcritical CO2 quasi-secondary compression cycle with ejector (TCIEJ) for heat pump water heaters, the thermodynamic model of TCIEJ is established based on the pinch point, and TCEX, TCEJ, and TCI are selected as comparisons. The effects of changing high pressure and ambient temperature on the heating COP and compressor exhaust temperature are analyzed, and the influence of cooling water inlet and outlet temperature and vapor injection pressure on TCIEJ is further analyzed. The results show that there are optimal high pressures that make the heating COP of the four heat pump cycles reach the maximum value, of which TCIEJ has the best performance. At an ambient temperature of −15 °C, the maximum heating COP of TCIEJ increased by about 20.5%, 14.9%, and 7.9% compared with TCEX, TCEJ, and TCI. With the increase in ambient temperature, the optimal high pressure continues to increase, and the corresponding maximum heating COP gradually increases. Selecting the geometric mean of high pressure and evaporation pressure as the optimal vapor injection pressure for TCIEJ, the error is small compared to the actual optimal vapor injection pressure. With the increase in ambient temperature and cooling water outlet temperature, the optimal high pressure of TCIEJ continues to increase, and the correlation formula of optimal high pressure is fitted according to the simulation results.