Operating Conditions Research Articles

Design and Application of Parameter Self-tuning Regulator for DC Motor based on Neural Network

This study introduces a cutting-edge approach to regulating DC motors, featuring a unique combination of Artificial Neural Networks (ANN) and Long Short-Term Memory (LSTM) networks. This innovative system capitalizes on the adaptive learning capabilities of ANNs to dynamically fine-tune the control parameters of DC motors. This adaptability ensures optimal motor performance across diverse operational conditions, addressing the challenges posed by fluctuating loads and varying speed requirements. The integration of LSTM networks into this framework adds a layer of predictive functionality, allowing the system to anticipate future motor states. Such foresight enables the regulator to make proactive adjustments, significantly enhancing its responsiveness to changes in operational demands. The dual application of ANN’s adaptive control mechanisms and LSTM’s predictive capabilities is particularly effective in overcoming the non-linearity and variability that are typical challenges in DC motor control. This synergy ensures that the motor operates efficiently, stably, and with a quick response time, even under varying and unpredictable conditions. The practical application of this advanced regulator in real-world scenarios has shown marked improvements in motor performance. These enhancements are evident in the increased efficiency, stability, and responsiveness of the motors, making them more suitable for a wide range of industrial applications. This study marks a notable progression in the field of DC motor control technology. By integrating advanced machine learning techniques, it offers a solution that is not only more efficient and reliable but also adaptable to the evolving demands of industrial environments. The innovative combination of ANN and LSTM networks in this regulator design paves the way for smarter, more responsive, and efficient motor control systems, potentially transforming how motors are managed in various industrial applications.

Experimental results on a chiller using a CO2-DME mixture

CO2-DME (Carbon Dioxide-Dimethyl Ether) mixtures raised our interest in the last year as they promise to increase the COP with respect to pure CO2 while maintaining GWP = 1. The mixture can be non-flammable, as far as the percentage of DME is low. This study presents experimental findings obtained from a chiller system utilizing CO2-DME mixtures as the working fluid. The experimental investigation aims to analyse the performance and behaviour of the chiller under varying operating conditions. Key parameters, such as coefficient of performance, cooling capacity, and thermodynamic behaviour are examined to assess the suitability and efficacy of the CO2-DME mixture in chiller applications. The experimental results shed light on the thermodynamic characteristics and operational considerations of the chiller system, providing valuable insights into the potential of CO2-DME mixtures for environmentally friendly, safe and energy-efficient cooling technologies. The experimental findings indicate a maximum increase in COP of 15% for a mixture comprising 10% DME, with a condensation temperature of 35°C. Furthermore, the cooling capacity is reduced only by 7% in the worst case.

Optimization of material properties and performance of flexible thermoelectric generators with/without graphene

With the advancement of energy harvesting methods, the power level consumed by electronic circuits and sensors has been reduced so that self-sufficiency in power can be achieved, and the use of flexible thermoelectric generators to supply electrical energy is one of these methods. In this study, the manufacture of flexible thermoelectric generators is successfully developed and verified using a numerical method. The process follows the sandwich method of the conventional thermoelectric module and utilizes two different elastomers (polydimethylsiloxane and Eco-Flex) and thin copper sheets. Among the nine cases designed by the Taguchi method, the maximum tensile strength of the elastomer is 0.967 MPa, stemming from the operation conditions of 6 min stirring time, 85 °C heating temperature, and 3 h heating time. This strength is substantially higher than those of the other eight cases. The open-circuit voltage of the manufactured flexible thermoelectric generator with an internal resistance of 1.5 Ω is 0.011 V. The output power under a temperature difference of 75 °C is 11 μW. After blending graphene into polydimethylsiloxane, the elastomer’s thermal conductivity at 370 K rises by 9.6 folds. This results in the output power being lifted to 0.0515 W (75 °C temperature difference), accounting for an amplification of 4,681 times. Numerical simulations are also performed to aid in figuring out the detailed performance of the flexible thermoelectric generator. The errors between numerical simulations and experiments are between 4.6 % and 5.2 %, showing the reliability of the numerical predictions. The fabricated flexible thermoelectric generators can be practically used for green power generation by harvesting industrial low-temperature waste heat and biothermal energy, potentially driving sensors on industrial devices, the human body, and animals.

Dynamic modeling and analysis of compressed air energy storage for multi-scenario regulation requirements

Compressed air energy storage (CAES) technology has received widespread attention due to its advantages of large scale, low cost and less pollution. However, only mechanical and thermal dynamics are considered in the current dynamic models of the CAES system. The modeling approaches are relatively homogeneous. CAES power stations have gradually increased the demand for auxiliary services such as frequency modulation mode and voltage regulation mode in addition to the peak regulation mode. Therefore, it is urgent to pay attention to the dynamic response characteristics at shorter time scales. Due to the lack of an accurate and complete dynamic model of the CAES system for multi-scenario adaptation requirements, the development of system optimization design and control technology has been severely limited. The paper establishes a dynamic model of advanced adiabatic compressed air energy storage (AA-CAES) considering multi-timescale dynamic characteristics, interaction of variable operating conditions and multivariate coordinated control. The simulation data is compared with the measured data of the peak regulation, frequency regulation and voltage regulation scenarios of the Jintan Salt Cave CAES (JTSC-CAES). The results show that the deviation of the dynamic model is <7 %, which verifies the validity and accuracy of the proposed AA-CAES dynamic model. The established model and research results provide the theoretical model foundation for dynamic characteristic research, system design and optimization control of the JTSC-CAES.

Performance of anhydrous ethanol and gasoline blends on a SI engine: Decoupling evaporation enthalpy and knock resistance

Blending bioethanol with gasoline is recognized as a rapid solution for mitigating nonrenewable carbon dioxide emissions. This approach proves particularly meaningful in markets where the production of this biofuel aligns with sustainable practices. Understanding the alterations in the combustion process holds significance within these markets, contributing to informed decision-making and fostering environmentally conscious practices. In this context, it is widely known that highly ethanol blended fuels can provide benefits regarding suppression of knocking combustion in spark ignited engines if the quality of the base-fuel is not deteriorated to maintain octane ratings. However, the results of engine knocking investigations can be affected by two effects simultaneously. Firstly, ethanol has a beneficial effect on knock suppression due to its high enthalpy of evaporation compared to gasoline, which results in inner mixture cooling especially with direct injection. Secondly, ethanol can have beneficial effects on knock suppression by its decreased self-ignition tendency. This paper provides the set-up and results of an adapted engine testing procedure to diminish the effects of evaporation enthalpy during the knocking investigations of different highly ethanol blended fuels. The presented testing procedure at a single-cylinder research engine includes three technical steps: (1) the engine is equipped with a port fuel injection in stoichiometric operation for all tested fuels; (2) the engine is operated with constant speed of 1500 rpm and constant spark timing of 33° firing top dead center; (3) the engine is operated with fuel individual settings for the intake manifold gas pressure and intake manifold gas temperature. These parameters are adjusted to test all fuels with similar in-cylinder conditions at spark timing. The differing heating values of the fuels obviously result in differing engine loads. However, the presented testing procedure is aimed to achieve comparable in-cylinder conditions at spark timing without the effect of evaporation enthalpy. The novelty of the study lies in its adapted engine testing procedure that mitigates the cross-effects of fuel properties and operational conditions to isolate the true influences on knock occurrence. The paper provides a comprehensive description of the theoretical backgrounds, experimental set-up and post-processing procedures and also shows the results of the first measurement campaign.

Experimental study on how the settings of plasma affect its effectiveness of suppression of thermoacoustic oscillations in a Rijke tube

Thermoacoustic instabilities, frequent in a wide range of combustors, arise from the intricate coupling between the flame’s unsteady heat release and the combustor acoustic. The application of plasma, characterized by its substantial local energy addition and radical generation, has demonstrated potential in disrupting this coupling and thereby mitigating thermoacoustic oscillations. Notably, open-loop control using discharge plasma has been successfully implemented to suppress self-excited oscillations in a Rijke tube setup. Considering the broader context of a complex system that integrates both thermoacoustic systems and discharge plasma, experiments were done to see its performance in stability under different arrangement and discharge repetition rates of discharge plasma. These experimental investigations identified critical operating conditions essential for complete suppression: (A) the optimal location of discharge actuations, and (B) the minimum energy required for complete suppression. Moreover, the impact of discharge plasma, particularly when tuned to the eigenfrequencies of oscillations within the thermoacoustic system, was thoroughly examined. The insights gained from these successful suppression trials are instrumental in guiding the strategic design of both physical arrangement and electrical configurations for the control of combustion instabilities via discharge plasma. Furthermore, through the photographing of the swinging arcs and their thermal disturbances by high-speed camera and high-speed schlieren, the characteristics of arcs’ thermal disturbances and the reasons affecting its suppression effectiveness were determined.

An advanced high dimensional model representation approach for internal combustion engine modeling and optimization

This work introduces an efficient data-driven approach for engine performance modeling and optimization. A highly accurate and robust high-dimensional model representation (HDMR) surrogate model is developed based on the dataset generated from a coupled KIVA4-CHEMKIN Ⅱ software. The HDMR model is integrated with a multi-objective optimization algorithm, enabling the automatic identification of optimal combustion strategies. Results suggest that the constructed HDMR model is able to accurately predict the engine performance and exhaust gas emissions with negligible CPU costs. Moreover, the model effectively identifies optimal engine operating conditions, leading to enhanced fuel efficiency.

Static and Dynamic Stress of the Combined Rotor with Curvic Couplings Considering the Rough Three-Dimensional Interface at Extreme Operating Conditions

The curvic coupling, as one of the common connecting structures for gas turbine combined rotors, is more susceptible to various dynamic and static loads at extreme operating conditions. But, traditional combined rotor models tend to neglect the influence of the connection structure, especially failing to consider the contribution of the curvic coupling interfaces. To address this problem, this paper establishes a solid geometric model of the combined rotor with curvic couplings considering the rough three-dimensional interfaces. The effectiveness of the proposed model method is indirectly verified through the compression tests and modal tests. Subsequently, combined with finite element calculations, the mechanical properties of the rotor with curvic couplings considering the rough interface are analyzed under static and dynamic load conditions. The results indicate that the roughness of the interface significantly affects the deformation of the contact surface under static load, but its impact on the overall deformation of the rotor is relatively insignificant. The dynamic stress at the interface exhibits periodic variations at the resonance speed. At the maximum operating speed, the dynamic stress is influenced by the magnitude of imbalance. The aforementioned methods and conclusions provide a reference for the design research and engineering application of combined rotors.

Effect of argon and nitrogen environments on the structure and properties of protective cermet coatings based on titanium borides obtained by electric arc surfacing

The aim of this work was to enhance the mechanical and tribological properties of an alpha titanium substrate by forming a protective cermet coating on its surface. In this study, protective cermet coatings based on titanium borides were prepared by electric arc surfacing in a protective environment. Two types of protective environment were investigated during the surfacing process: (i) inert (argon) and (ii) reactive (nitrogen). The characteristic zones of the deposited layer were established depending on the environment used, and the coating-substrate transition zone was thoroughly examined. It was demonstrated that the formation of the transition zone results from the mutual diffusion of the molten material of the electrode material and the substrate. For the first time, the formation of TiB2-TiN eutectic in the form of whiskers 4-20 μm wide and 100-300 μm long distributed in the matrix of the Ti(B,N)x solid solution was established when forming a protective cermet coating in a nitrogen environment. The presence of this TiB2-TiN eutectic led to a significant increase in the hardness of the coating, up to 4.4 times, from 350 to 1530 HV. Tribological tests of surfacing coatings were conducted, and both 2D and 3D profiles of the wear grooves are presented, providing insight into the wear mechanism. It was found that the wear resistance of the cermet coating obtained in a nitrogen environment increased by 5.2 times, while in an argon environment it increased by 3.1 times as compared to the substrate without the protective cermet coating. The results indicate the potential of the developed protective cermet coatings for use in abrasive operating conditions.

Impact of Model Knowledge on Acoustic Emission Source Localization Accuracy

Reliable and precise damage localization in mechanical structures is of high importance in the context of structural health monitoring (SHM). The acoustic emission (AE) method has already shown its excellent suitability for damage localization. However, low signal-to-noise ratios (SNRs) are often prevalent in SHM, thus an increase in localization accuracy and robustness is still in demand. The present study faces this task through the integration of various model knowledge for AE source localization. The basis of the presented algorithm is the consideration of the dispersive behavior of elastic waves in thin-walled structures. The continuous wavelet transform (CWT) is used to obtain time-frequency representations of the signals, where frequency-dependent values for time-of-arrival (TOA) are extracted. Furthermore, the algorithm incorporates the knowledge that all sensors receive signals with the same time and location of origin, as well as the slightly different sensitivity of the theoretically equal sensors. The final localization results are achieved by a two parameter grid search optimization. The algorithm is experimentally tested on a large aluminum plate with four piezoelectric wafer active sensors (PWASs) arranged in an array of 100 mm × 100 mm. The mean localization error of pencil lead breaks at ten different positions within the sensor array is used as an accuracy measure. It is shown that as more of the described model knowledge is incorporated into the localization, the accuracy increases. With the final algorithm, the mean localization error is more than halved compared to AE localization based on classical TOA estimation. Although the experiment described is conducted under laboratory conditions, the remarkable increase in accuracy suggests that AE source localization may be successful even at low SNR as typical for operational conditions.

A Novel Fault Feature Selection and Diagnosis Method for Rotating Machinery with SI-IR2CMSE and SSGMM-SR

Abstract In the field of fault diagnosis, machine learning is highly valued for its broad applicability and efficiency. Feature extraction and feature selection are key steps in the application of machine learning, and the performance of fault diagnosis methods relies heavily on the effective execution of these two steps. For this reason, this paper aims to enhance the performance of fault diagnosis methods by improving these two aspects. Firstly, to address the non-linearity and non-stationarity of rotating machinery vibration signals under variable operation conditions, this paper proposes an improved rapid refined composite multiscale sample entropy (IR2CMSE) feature extraction method. In addition, this paper decomposes the vibration signals with improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and extracts the sensitive intrinsic modal functions’ (IMFs') IR2CMSE values (SI-IR2CMSE) as the initial feature vector, which more accurately reveals the intrinsic time-scale characteristics of the vibration signals. Secondly, to address the problem of over-reliance on sample labels in most feature selection methods, this paper proposes a semi-supervised Gaussian mixing model with sparse regularization (SSGMM-SR) feature selection model. The model does not require complete fault labels and can automatically identify important features. Finally, validation with two rotating machinery fault datasets shows that the method proposed in this study exhibits high diagnostic accuracy and stability across multiple classifiers.&amp;#xD;

Evaluating the effectiveness of the modified multi-scale multi-physics coupled model for solid oxide fuel cells: A comparative analysis

A multi-scale multi-physics coupling numerical model serves as an effective tool to study the performance and improve the efficiency of solid oxide fuel cells (SOFCs) and provides the theory and data support for optimizing SOFC structure and operational strategy. To improve the accuracy and reliability of the model, this work established a modified simulation model that considers the effect of operational, structural, and physical parameters of SOFCs. First, the electrochemical kinetics equation, multi-component diffusion lattice Boltzmann (LB) model, and heat transfer LB model are modified by incorporating the reaction gas molar fraction, gas mixture concentration, temperature, and other parameters. Second, a regional hierarchical modeling strategy is proposed, and the multi-scale coupling model is modified by coupling mass and heat transfer. Third, considering the effect of carbon monoxide molar fraction, temperature difference, concentration change and porosity on electrochemical, mass, and heat transfer processes, the effectiveness of modification model is analyzed and validated. Results demonstrate that the modified model considerably improves the numerical simulation to handle the complex operational conditions of SOFCs. The modified model's predictions show better accuracy compared with experimental data, while maintaining consistency with the trends predicted by the original numerical models.

Efficient removal of ammonia from aqueous solution using coal-based carbon membrane via electrochemical oxidation in the present of chloride ion

To tackle the escalating issue of ammonia nitrogen water pollution, developing efficient removal technologies holds paramount significance. In this work, an electrochemical membrane reactor (EMR) was constructed for the decontamination of ammonia nitrogen wastewater using the coal-based carbon membrane (CCM) as the flow-through anode. The removal efficiency and degradation mechanism of ammonia nitrogen by EMR during the treatment were investigated. It was found that, under applied voltage and in the presence of chloride ions, the CCM exhibited excellent chlorine evolution performance, and as a result, the EMR had excellent ammonia nitrogen removal efficiency. The removal of ammonia nitrogen by the flow-through EMR was following the pseudo-first-order kinetics. Analysis revealed that various operating parameters, including applied voltage, chloride ion concentration, flow rate, pH value, and initial ammonia concentration, all significantly influenced the ammonia nitrogen treatment performance of EMR. At optimal operation conditions (feed concentration of 30mg/L, applied voltage of 2.8V, NaCl concentration of 0.1mol/L and flow rate of 2ml/min), the EMR achieved a removal rate of 100% for ammonia nitrogen with a low energy consumption (EC) of 0.0380kW•h/g-NH4-N. The degradation mechanism analysis revealed that the primary means of ammonia removal relied on indirect oxidation mediated by OCl·, which was generated by the oxidation of Cl- on the surface of CCM within the solution under the influence of the electric field. Furthermore, the EMR demonstrated good applicability across various water matrices. In conclusion, the EMR holds considerable potential for the decontamination of ammonia nitrogen-containing wastewater.

Fault location method for new distribution networks based on waveform matching of time–frequency travelling waves

AbstractSome existing fault location methods for distribution networks rely too much on the local wave head information of the time or frequency domain signals, making it difficult to adapt to the increasingly complex structure and operating conditions of the distribution network after the new energy access. For improvement, the travelling wave (TW) time and frequency ranges that can effectively avoid waveform distortion caused by new energy access are analysed. The one‐to‐one matching relationship between the TW waveforms in these ranges and the fault positions is revealed. A fault TW time–frequency matrix with specific time and frequency windows is constructed, and a new distribution network fault location method is proposed based on the matching technique of waveform features, which realises the accurate fault location by exploring the proportionality between the cumulative trend of the matrix energy amplitude deviation and the fault point position. Simulation test results show that the proposed method is not affected by the complex structure of distribution networks such as new energy access and overhead‐cable line mixing on fault location and flexibly transforms the fault location problem into a time–frequency TW waveform matching problem, which improves the accuracy and robustness of the fault location for new distribution networks to a degree.

Diffusive nature of different gases in graphite: Implications for gas separation membrane technology

Graphite membranes have gained attention in membrane technology for gas separation due to their high stiffness, strength, and stability in corrosive and high-temperature environments. Graphite exists naturally in geologic media and can also be prepared by synthetic processes. In- situ hydrogen (H2) production in petroleum reservoirs or H2 storage in depleted gas reservoirs results in contamination with CH4 and CO2. To address the separation challenge at the surface, a sustainable downhole wellbore membrane must be available to separate H2, leaving behind CO2 and other gases to improve operational economics. Currently, there are no studies in the literature on the self-diffusivity of gases (CO2, H2, and CH4) in graphite as a function of pore size. To overcome time constraints in diffusivity experiments, this work utilized mathematical models and molecular simulations to delineate the self-diffusivity of gases in graphite of different pore sizes.To acknowledge subsurface operational conditions during in situ hydrogen production, we considered a temperature of 360 K and a wide pressure spectrum from 2 MPa to 20 MPa. In this study, we explored the diffusive nature of H2, CH4, and CO2 gases in different nanopore-sized graphite using analytical and molecular simulation approaches. We validated the results by presenting unrestricted case density calculations. First, effective diffusivity was calculated using the mean free pore path, followed by gas adsorption at high pressures (10–20 MPa) and a temperature of 350 K. The study utilized theoretical models and molecular dynamics (MD) simulations to determine the self-diffusivity of gases in graphite systems with various structures.

Enhancing Selective NH4+ Recovery from Wastewater Using Modified Zeolite-Based Flow Electrode Capacitive Deionization

Despite flow-electrode capacitive deionization (FCDI) is an emerging technology for desalination, contaminant removal, and resource recovery, the application of conventional FCDI in wastewater treatment is hindered by the electrode selectivity and material costs. In this study, we synthesized a low-cost ammonium (NH4+) adsorption electrode material by modifying zeolite using ethylenediaminetetraacetic acid disodium salt (EDTA-2Na). The flow electrode prepared by the mixture of EDTA-zeolite and carbon black exhibits a high selectivity and adsorption capacity for the recovery of NH4+ from wastewater. The NH4+ in wastewater passes through the ion exchange membrane and is rapidly adsorbed by the modified zeolite through ion exchange, while Na+ is retained in the electrolyte. The decrease in NH4+ concentration and the increase in Na+ concentration in the catholyte lead to a significant change in ion concentration gradient across the membrane. Consequently, the transmembrane selectivity between NH4+ and Na+ reached 3.46. We validated the feasibility of NH4+ recovery using FCDI with food waste fermentation supernatant. Under optimal operating conditions, 99.15% of the NH4+ in the fermentation supernatant was removed, and 95.92% of the NH4+ in the electrolyte was stored in the EDTA-zeolite. By gravitational settling, the NH4+-rich modified zeolite was separated from carbon black and could be utilized as nitrogen fertilizer. Meanwhile, the mixture of carbon black and brine was used to prepare a fresh electrode suspension. In brief, the FCDI system exhibits a satisfying NH4+ recovery performance and demonstrates a sustainable wastewater resource recovery strategy.

Ultra-stable counter flow diverging minichannel heat sink with integrated microstructures for superior cooling performance

Efficient thermal management of miniaturized electronic devices is quite challenging nowadays. It requires dissipation of very high heat flux without considerable elevation of surface temperature. To address this issue, this study proposes the counter flow diverging minichannel heat sink in a compact size of 3 cm2. Additionally, two innovative microstructures have been developed and integrated into the bottom surface of the proposed minichannel heat sink: one with gradient micro pin-fins and another combining gradient microcavities with micro pin-fins. Comprehensive flow boiling experiments are conducted under various operating conditions to identify the best configuration with the most appropriate operating condition to dissipate the highest heat flux with minimal pressure drop and stable two-phase flow patterns. The current study reveals that the synergistic effects of gradient micro pin-fins and optimized gradient microcavities achieve a very high heat flux of 746.14 W/cm2 and a two-phase heat transfer coefficient of 28.18 W/cm2K under the limitation of wall temperature lower than 132 °C. Additionally, it maintains an exceptionally low pressure drop of 2.35 kPa with stable two-phase flow patterns under a mass flux of 600 kg/m2s and a degree of subcooling of 40 °C. Compared to the bare surface, counter flow diverging minichannels with gradient micro pin-fins and optimized gradient microcavities show excellent enhancements of 201.12 % in the effective heat flux and 124 % in the two-phase heat transfer coefficient, suggesting it is the best design in the present study for advanced cooling applications.

Evaluation and Upscaling of Impregnated La0.20Sr0.25Ca0.45TiO3 Fuel Electrodes for Solid Oxide Electrolysis Cells

Recent research into Rh and Ce0.80Gd0.20O1.90-impregnated La0.20Sr0.25Ca0.45TiO3 fuel electrodes for solid oxide fuel cells has demonstrated the high-stability of these material sets to a variety of harsh operating conditions at small scales (1 cm2 active area button cells), as well as commercial scales (100 cm2 cells) in short stacks (5 cells) and full micro-combined heat and power systems (60 cells). In this work, the authors present a comprehensive evaluation of the ability of these novel titanate-based materials to function as fuel electrodes in solid oxide electrolysis cells (SOECs). Short-term and durability testing of button cell scale SOECs highlighted the limited stability of lanthanum strontium manganite-based air electrodes, under CO2 and steam electrolysis conditions, with lanthanum strontium cobaltite ferrite-based air electrodes offering improved degradation characteristics. Upscaling of this optimized cell chemistry to a 16 cm2 active area SOEC and testing under CO2, CO2/H2O and H2O electrolysis conditions demonstrated encouraging performance over a period of ∼600 h, with stable co-electrolysis performance at ∼−7.5 A at 1.47 V for the first 100 h.

3D simulation estimation and experimental validation of droplet generation in CFD-based flow-focusing microfluidic chips

Abstract Microdroplets generated using microfluidic techniques offer significant advantages over those generated using conventional methods, including high accuracy and excellent monodispersity. However, there remains a paucity of literature regarding the influence of fluid operating conditions and physical properties on droplet generation, specifically in relation to size and frequency, using computational fluid dynamics (CFD) techniques. In this study, we present a simplified microfluidic chip capable of flexibly adjusting the structure and size of the microchannels based on specific requirements. Subsequently, three-dimensional (3D) numerical simulations of this chip were conducted using CFD techniques and fitted a dimensionless model to estimate the droplet generation size and frequency through multivariate nonlinear regression methods. The experimental validation results demonstrated a strong correlation between the fitted data and the experimental observations, with size differences not exceeding 8% and good monodispersity, indicated by a coefficient of variation (CV) of less than 2.4%. This study provides valuable insights and a reference for future research.

Experimental study of the performance of a water-to-water heat pump equipped with a liquid receiver with different charge levels

This paper presents an experimental investigation of the effects of a decreasing refrigerant charge on the performance and operating conditions of an R513A water-to-water heat pump equipped with a liquid receiver, an electronic expansion valve, and a vapour accumulator at the compressor inlet. The mass of the refrigerant inside the machine is progressively extracted to simulate refrigerant leakages occurring during the normal operation or in case of failures. The results show that the subcooling is the parameter mostly affected by a refrigerant charge variation since it rapidly collapses to 0 K with the charge reduction. Furthermore, it is possible to identify three different zones in which almost all the properties analyzed (COP, heating capacity, operating pressures and expansion valve opening) exhibit peculiar trends with the charge decrease: subcooling sensitivity zone, constant parameters zone, and compressor failure risk zone. The extension of these zones is determined by the size of the liquid receiver which is installed in the system and, for the heat pump under consideration, is between 100% and 95% of the initial charge for the first zone, between 95% and 40% for the second zone, and below 40% for the third zone.