Actual Operating Conditions Research Articles

ATKB-PID: an adaptive control method for micro tension under complex hot rolling conditions

At present, the parameters of the controllers in hot rolling roughing microtension control systems are not adaptively adjustable to variations in working conditions, which compromises both width accuracy and production stability. To address this issue, this paper introduces an ATKB-PID adaptive micro tension control method. This method incorporates a linear attention layer and utilizes a K-Nearest Neighbors (KNN) algorithm to predict the optimal learning rate and inertia coefficient under actual operating conditions. Furthermore, an objective function is tailored to production indices to enhance model performance. Comparative experiments with both established and recently introduced controllers demonstrate that the proposed ATKB-PID method exhibits a smaller steady-state error and quicker adjustment time. The ATKB-PID control method is well-suited for the complex and dynamic microtension control demands in thermal roughing processes, showing promising application potential.

Exogenous C6-HSL enhanced the cometabolic removal of sulfadiazine by an enriched ammonia oxidizing bacteria culture.

The removal of antibiotics in wastewater treatment plants (WWTPs) is generally insufficient. Studies have proved that ammonia-oxidizing bacteria (AOB) are capable of degrading antibiotics through cometabolism. However, the actual operating conditions in WWTPs are generally unfavorable for AOB to fully reach its cometabolic potential. Studies have demonstrated that exogenous N-acyl homoserine lactones (AHLs) can enhance the treatment efficiency of wastewater treatment microorganisms by regulating their quorum sensing system. However, few studies have reported the effect of exogenous AHLs on the cometabolic removal of antibiotics by AOB. In this study, a typical AHL, N-hexanoyl-L-homoserine lactone (C6-HSL), was selected to explore its effects on the cometabolic removal of a typical antibiotic, sulfadiazine (SDZ), by an enriched AOB culture and the microbial responses of the culture during the process. The results showed that the exposure to SDZ (0.1-10mg/L) led to the decrease in ammonia oxidation rate, the concentrations of intracellular adenosine triphosphate and ammonia oxygenase (AMO) and the abundances of amoA gene and AOB, while more extracellular polymeric substances (EPS) were secreted to resist the adverse effects brought by SDZ. With the simultaneous addition of SDZ (1 and 10mg/L) and exogenous C6-HSL (1μM), it was found that C6-HSL significantly enhanced the removal efficiency and rate of SDZ by the enriched AOB culture. By promoting EPS secretion, strengthening energy metabolism, promoting AMO synthesis, increasing AOB and amoA gene abundances and altering microbial community structure, C6-HSL restored the microbial activity and alleviated the pressure on microorganisms induced by SDZ. It is expected that this study could provide a new strategy for enhancing antibiotics removal in wastewater.

Digital upgrade of drainage detention devices for forced retention.

Current urban challenges related to local urban flooding require effective preventive measures. This applies particularly to various methods of stormwater retention, including forced retention, and solutions that enable cooperation between small individual retention systems and drainage systems. Therefore, this study presents the results of research on the hydraulic efficiency of controllable systems, which combine the features of an on-site tank with the solutions of network tanks to increase the retention of stormwater in drainage systems. The study had two main objectives: first, to investigate the potential for improving the hydraulic efficiency of retention devices operating within forced retention systems through the implementation of real-time control, and second, to assess the impact of hydraulic parameters characterizing flow in the system on the efficiency of the studied types of devices. The operation of three hydraulic systems in terms of forced retention was verified: a classic linear system, a forced retention system subjected to digitisation through real-time control implementation and a forced retention system devoid of control elements. The study was conducted under laboratory conditions that simulate actual operational conditions. The results demonstrate that a retention system based on real-time control can increase the correct operation time by up to 50%. The efficiency relative to linear objects for the retention system based on real-time control ranged from 50% to 241.67%, whereas a system lacking control elements showed an increase of 66.67%-136.64%. Additionally, this study demonstrated a significant impact of the stormwater fill level in forced retention devices on their hydraulic efficiency. The results indicate the potential to increase the efficiency of various retention solutions through the application of a properly selected and optimised control system.

ANALYSIS OF THE THERMAL-KINETIC-FLUID-DYNAMIC PROFILE OF A SLAB REHEATING FURNACE USING CFD-DYNAMIC MESH

In this work, the actual operating conditions of a walking beam and direct flame reheating furnace for conventional steel slabs in continuous motion were numerically simulated. The fluid dynamics, heat transfer, chemical species and combustion were solved in a coupled way using a continuous readaptation of the computational domain by means of a dynamic mesh. The results were validated by means of temperature measurements averaged over 24 hours of plant operation with 16 thermocouples, resulting in an average error of 2.56%. With the reduction in flow rates in the range of 70-85% and a decrease in load of ?66.5% there was an overheating in the furnace of up to 33% in excess. The use of dynamic meshes allowed the oxide growth rate to be studied showing that, the higher the temperatures and residence times in the furnace, the higher the oxidation rate of the slab. Keywords: Reheating Furnace, CFD, Slab, Dynamic Mesh.

Development and assessment of a novel single-drive variable angle spraying machine

Traditional sprayers are limited to applying spray mixture solely to the upper surfaces of crops. To overcome this limitation, a variable angle spraying machine (VASM) was designed using a linkage system. This machine enables the adjustment of both the spray position and angle through a single input signal, facilitating multi-directional spraying from the top to the bottom of crops. By utilizing ADAMS simulation, the relationship between input signal and output angle of spraying connecting rod was analyzed. The study employs a control variable experimental methodology alongside multiple comparison analysis to investigate various experimental factors, specifically nozzle sweep time (t), spray pump pressure (p), and distance from measurement position to surface (l). The average coverage rate observed in the top, side, and bottom orientations during actual operational conditions serves as the primary evaluation index for experimental analysis. The experimental results indicate that the VASM can achieve comprehensive spraying of crops, effectively covering both the leaf surface and the leaf underside. As the l value increases, the downward spray coverage rate (DSC) gradually rises, while the sideways spray coverage rate (SSC) gradually declines. The upward spray coverage rate (USC) initially decreases before increasing. It was observed that the DSC is lower than both the USC and the SSC due to the influence of gravity, particularly in the surface and middle layers of crops. The VASM can significantly enhance coverage of the underside and inner layers of crop leaves, thereby achieving the objectives of reducing pesticide waste and minimizing environmental pollution.

Formation of a set of parameters for assessing the technical condition of autonomous power plants

Abstract. Problem. The object of study is the problem of creating a relatively simple diagnostic model of a diesel engine for an autonomous power plant in terms of the number of required input parameters. Goal.The aim of the study is to develop a diesel engine diagnostic system for an autonomous power plant. Methodology. To achieve this goal, the following tasks were solved: - to develop a method for synthesising a diagnostic graph model of a diesel engine for an autonomous power plant; - to propose a method for selecting the initial parameters of the diagnostic graph model of a diesel engine.The subject of the study is the relationship between the selected set of input parameters of the diagnostic model of a diesel engine and the adequacy of the response of the resulting model to real emergency situations. Results. As a result of the study, a methodology for synthesising a diagnostic graph model of a diesel engine of an autonomous power plant has been developed. The resulting model allows monitoring the performance of a diesel engine and adjusting the relevant parameters to achieve the required operating state or localise an emergency. Originality. The proposed method of synthesis of a diagnostic graph model of a diesel engine of an autonomous power plant, based on the use of the graph theory method, allows obtaining results that correspond to the actual state of operation of a diesel engine of a power plant with relative simplicity of use. This is achieved by using specially selected groups of diesel power control parameters as diagnostic parameters of the graph model. These indicators are available for measurement without significant dismantling and installation work, the use of complex measuring instruments, but can be measured during routine maintenance and operation. A methodology for selecting the output parameters of a diagnostic graph model of a diesel engine is proposed, which includes the process of forming the minimum required sample of parameters of diesel engine operation. Practical value. The following parameters have been selected as parameters for assessing the technical condition of power plant diesel engines and functionally related systems and circuits: power plant capacity; diesel crankshaft rotation frequency; fuel consumption; and a group of thermal parameters. This minimum required set of system state parameters makes it possible to link the diagnostic scheme for the studied technical condition of power plant diesel engines with their operational performance

Experimental Determination of the Equivalent Moment of Inertia and Stresses of Aluminium Profiles with Thermal Breaks

This paper presents the results of experimental tests and computer simulations on the stiffness of composite aluminium mullions used in unitised façades. The elements analysed were subjected to bending in order to simulate the actual operating conditions of aluminium façades subjected to significant wind pressure or suction loads. The basic mechanical and physical properties of the materials from which the analysed type of aluminium façade is made (Aluminium EN AW-6060 in the T66 temper and polyamide PA66 25GF), the test method, and the results obtained are described. As a result of the tests, equivalent moments of inertia of the composite profile (aluminium profile with the thermal break) were determined, which are strongly dependent on the strength of the connection between the individual elements, the asymmetry of the cross-section, and the properties of the thermal break. Strain measurements carried out using FBG (Fiber Bragg Grating) strain sensors installed in the profiles under tests allowed for determining the actual stress values of the aluminium profiles under consideration. The results obtained were compared to theoretical (numerical) values, indicating discrepancies at higher load values. The methodology presented in this article is to be used to monitor the deformation of the aluminium façade mullions of HRB (High-Rise Buildings).

Modern methods of identifying the hazards of destruction of buildings, structures and constructions in real operating conditions

The problem of identifying the hazards of buildings, constructions and structural elements destruction in the conditions of actual operation arises from the need to ensure the safety of people and property. This problem is especially relevantin connection with the constant increase in the volume of construction and operation of building objects of various functional purposes.The importance of identifying the hazards of the destruction of operated objects is to identify potential threats of destruction in advance and to take appropriate measures to localize them This challenge requires an integrated approach, encompassing continuous monitoring of the technical condition, assessment of actual operating conditions, analysis of design resistance of structural elements, and the development of suitable strategies for maintenance, strengthening or replacement of structures, carrying out repair and restoration work or reconstruction.Destruction hazards can arise for various reasons and can induce a serious threat to life, human health, and property integrity.Some of the main factors that can lead to failure include: aging and physical wear; natural rheological processes (material degradation) and changes in design and operating conditions. In addition, the danger may increase due to natural disasters, such as earthquakes, floods, hurricanes, etc. Potential threats of destruction are hidden defects and damages caused by design errors, non-compliance of structural elements with technical conditions, poor-quality construction and installation (repair) work, which ultimately increases the level of danger of destruction during operation.It should be noted that during the building object operation, deficiencies in technical operation, changes in the design conditions of normal operation, violations of regulatory conditions and the system of planned preventive repairs can lead to the accumulation of problems that can cause destruction over time.Studying methods to identify hazards, conducting a detailed analysis of the causes and mechanisms of emergencies, and implementing appropriate measures based on these findings are crucial for the continuous improvement of destruction prevention strategies.Research methods for identifying hazards of operated building objects destruction, detailed analysis of the causes and mechanisms of emergency situations, and implementation of appropriate measures based on the data obtained allow for continuous improvement of the destruction prevention strategy.

Capacity Prognostics of Marine Lithium-Ion Batteries Based on ICPO-Bi-LSTM Under Dynamic Operating Conditions

An accurate prognosis of the marine lithium-ion battery capacity is significant in guiding electric ships’ optimal operation and maintenance. Under real-world operating conditions, lithium-ion batteries are exposed to various external factors, making accurate capacity prognostication a complex challenge. The paper develops a marine lithium-ion battery capacity prognostic method based on ICPO-Bi-LSTM under dynamic operating conditions to address this. First, the battery is simulated according to the actual operating conditions of an all-electric ferry, and in each charge/discharge cycle, the sum, mean, and standard deviation of each parameter (current, voltage, energy, and power) during battery charging, as well as the voltage difference before and after the simulated operating conditions, are calculated to extract a series of features that capture the complex nonlinear degradation tendency of the battery, and then a correlation analysis is performed on the extracted features to select the optimal feature set. Next, to address the challenge of determining the neural network’s hyperparameters, an improved crested porcupine optimization algorithm is proposed to identify the optimal hyperparameters for the model. Finally, to prevent the interference of test data during model training, which could lead to evaluation errors, the training dataset is used for parameter fitting, the validation dataset for hyperparameter adjustment, and the test dataset for the model performance evaluation. The experimental results demonstrate that the proposed method achieves high accuracy and robustness in capacity prognostics of lithium-ion batteries across various operating conditions and types.

Research on the Measurement of AC Resistance of Overhead Transmission Lines Considering Actual Operating Conditions

The presence of alternating current (AC) resistance in overhead conductors contributes to additional energy losses during electrical energy transmission and affects the current-carrying capacity of the lines. However, a standardized measurement method for AC resistance remains unavailable. This paper presents the design of an experimental platform for measuring the AC resistance of conductors using an electrical measurement approach in conjunction with the least squares method. In the experiments, data were collected for four conductors, including current, AC resistance, and temperature. The study analyzes the relationships among the AC resistance of the conductors, their temperature, and the AC/DC resistance ratio as the current varies. The results from measuring the AC/DC resistance ratio indicate that the platform is effective for AC resistance measurement and can serve as a valuable reference for evaluating the AC losses of existing line conductors.

Research on Power Smoothing Control of Grid-Connected High Proportion New Energy Power Systems

With the increasing share of renewable energy in power systems, the construction of an integrated "source-grid-load-storage" system in regions rich in renewable energy and areas with concentrated loads has become an effective way to promote large-scale local consumption of renewable energy. However, under scenarios of high renewable energy integration, the lack of synchronous inertia support in the integrated system poses severe challenges to system frequency stability. Therefore, it is crucial to deeply explore the frequency regulation potential of each component in the "source-grid-load-storage" system. This paper studies the frequency response characteristics of new energy power stations and the demand-side response mechanism. Based on the actual operating conditions of the system and expected fault scenarios, reasonable virtual inertia time constants are set, and a frequency response model of the "source-grid-load-storage" integrated system is established. Furthermore, a new optimized power command is proposed, which combines a moving average filtering algorithm to smooth wind power output fluctuations. Finally, an optimized energy storage configuration method considering resource coordinated operation is studied. The research in this paper provides theoretical support and reference for improving system frequency stability and promoting renewable energy consumption under high renewable energy integration scenarios.

CYCLIC LOW-THERMAL AGING OF DISSIMILAR AUSTENITIC STEEL WELDS USED IN NUCLEAR POWER PLANTS

The nuclear power plants in Eastern Europe face problems with supplies of spare parts manufactured according to the same Russian standards as the originals. Therefore, the dissimilar welds of original Russian steel 08Ch18N10T and substitutive 1.4541 were made and analyzed to consider the possibility of original steel replacement during the repairs. Two different filler wires were applied. The welds were subjected to cyclic thermal loading corresponding to the actual operating conditions of a nuclear unit, and their microstructure and mechanical properties were compared to the as-welded joints. An increase in weld metal microhardness induced by aging was found when the filler with higher C and Cr content was used. Although this could indicate possible ferrite decomposition, the detected changes in mechanical properties corresponded to the changes in homogeneous welds of the original steel. The strength requirements for the steel used in nuclear power plant devices were still matched.

Application of the non-circular sprocket in the timing chain drive system

As a fundamental component of hybrid vehicles, the timing chain drive system significantly improves fuel economy while minimizing transmission error. A non-circular sprocket is used in a timing chain drive system to improve the dynamics characteristics of the system. In the scheme to reduce the crankshaft speed fluctuation, the relationship between the transmission ratio and the camshaft rotation angle is determined by analyzing simulation and experimental results. The mathematical relationship between the transmission ratio and the pitch curve of the non-circular sprocket is deduced. The pitch curve and phase angle of the non-circular sprocket are calculated. Combined with the self-constructed dynamics model of the hydraulic tensioner, a complete three-dimensional timing chain drive system simulation model is established based on the recursive algorithm and Hertz contact theory. The non-circular sprocket is installed into the system at the initial mounting angle. Dynamics simulations are carried out taking into account actual operating conditions. The simulation results prove that the use of a non-circular crankshaft sprocket can effectively reduce speed fluctuation of the camshaft sprocket, transmission error, and maximum chain tension when the crankshaft speed fluctuates regularly. This research proposes and validates a method to improve the dynamics characteristics of the system.

Security Situation Assessment for Terminal Area Control System Operation Based on BN-ISSA-ELM

Performing an operational safety situation evaluation of the terminal area control system is crucial for enhancing safety management and ensuring operational safety in the terminal area. We use a combination active–passive risk source identification method to thoroughly identify the safety features of the terminal area control system, and then establish a related indicator system. After that, the system’s secondary and primary indicators are used as input and output vectors for an Extreme Learning Machine (ELM). This creates an ISSA-ELM-based risk probability prediction model for the primary indicators, which gives us the predicted values of the primary indicator risks. Bayesian theory merges the output results to determine the overall safety status of the terminal area control system. The evaluation results indicate a distinct correlation between the secondary and primary indicators in a terminal area of North China. The ELM, which has been improved by the Sparrow Search Algorithm (ISSA), correctly displays this mapping and predicts the operational risks. The improved model is able to make predictions that are more than 80% accurate. A comparison of the model’s evaluation results with the actual operational conditions during the same period demonstrates consistency, suggesting that this method may consistently evaluate the operational safety status of the terminal area control system.

Surrogate modeling of pantograph-catenary system interactions

The smooth interaction between the pantograph and the catenary is crucial for the operational safety of railway vehicles. Coupled dynamic models of the pantograph–catenary system (PCS) constructed based on physical principles are important tools for analyzing their interactions; however, these models rely on accurate system parameters (such as stiffness, damping, and mass). Under actual operating conditions, the system parameters of the PCS exhibit time-varying characteristics and are difficult to measure, making it challenging for dynamic models to accurately represent the system’s behavior. Data-driven intelligent algorithms, with powerful feature extraction and nonlinear fitting capabilities, provide new approaches for solving system response prediction and state identification problems of the PCS. However, excessive reliance on large amounts of data for training may lead to poor generalization ability and pose challenges to model robustness, such as sensitivity to input noise or outliers. To address these issues, this paper proposes a surrogate model for the interaction of the PCS by integrating physical information with deep neural networks. The model introduces a novel neural operator that combines Transformers and convolutions (Convs), capable of capturing complex mapping relationships among various parameters within the dynamic model of the PCS in the frequency domain. A residual network incorporating physical information is designed to simulate the intricate correlations among system parameters. Additionally, a dynamic weighting balance algorithm is proposed to adjust the losses of different physical equations dynamically, ensuring the balance of physical information during training. The proposed model effectively performs response prediction and state identification of the PCS. It demonstrates excellent performance on both simulation and real-world data, providing new insights and methodologies for studying PCS interactions.

SOC Estimation of a Lithium-Ion Battery at Low Temperatures Based on a CNN-Transformer and SRUKF

As environmental regulations become stricter, the advantages of pure electric vehicles over fuel vehicles are becoming more and more significant. Due to the uncertainty of the actual operating conditions of the vehicle, accurate estimation of the state-of-charge (SOC) of the power battery under multi-temperature scenarios plays an important role in guaranteeing the safety, economy, and reliability of electric vehicles. In this paper, a SOC estimation method based on the fusion of convolutional neural network-transformer (CNN-Transformer) and square root unscented Kalman filter (SRUKF) for lithium-ion batteries in low-temperature scenarios is proposed. First, the CNN-Transformer base model is established. Then, the SRUKF algorithm is used to update the state of the Coulomb counting method results based on the base model results. Finally, ensemble learning theory is applied to estimate SOC in multi-temperature scenarios. Data is obtained from laboratory conditions at −20 °C, −7 °C, and 0 °C. The experimental results show that the SOC estimation method proposed in this study is stable in terms of the root mean square error (RMSE) being between 2.69% and 4.22%. The proposed base model is also compared with the long short-term memory (LSTM) network and gated recurrent unit (GRU) network to demonstrate its relative advantages.

Fast search for toxic gas leakage on offshore platforms based on deep learning methods

In the context of addressing dangerous gas leakage on offshore platforms, the prompt identification of leakage sources is paramount for implementing targeted emergency measures. This paper introduces a rapid leakage source location method leveraging a preexisting database on gas leakage and dispersion consequences, coupled with a deep learning approach. Initially, latin hypercube sampling (LHS) and computational fluid dynamics (CFD) are employed to simulate the consequences of gas leakage and dispersion on offshore platforms. Subsequently, a neural network model, specifically a long short-term memory (LSTM) model, is trained using concentration data. This trained model facilitates the rapid localization of the leakage source based on real-time detector data. Furthermore, optimization of the model is conducted through an analysis of various hyperparameters. Finally, the efficacy of the proposed methodology is demonstrated through a comparison between predicted results and actual operating conditions. This approach enables swift and precise identification of leakage sources during incidents, thereby facilitating a more efficient emergency response.

Optimization of electromagnetic vibration for integrated electric drive systems based on electric vehicle driving cycle considering energy consumption

To reduce the vibration of the integrated electric drive system (IEDS) in actual operation condition and enhance vehicle comfort, the method is proposed to characterize the working characteristics of the IEDS in the electric vehicle driving cycle (EVDC) that can reflect the daily travel conditions of electric vehicles by using representative points. Then, based on the representative points, the multi-objective optimization method was proposed to optimize the electromagnetic force harmonics and motor loss of the electric drive system under complex operating conditions. This method utilizes particle swarm optimization algorithm to obtain the Pareto solution set of the optimization objectives, and uses weighted sum method (WSM) to determine the best-balanced solution. The optimization results show that the multi-objective optimization method proposed in this paper reduces the electromagnetic harmonic as the optimization objective by more than 13 %. Additionally, it expands the high-efficiency region of the IEDS, reducing the energy consumption of the vehicle by 4.7 % in the EVDC, thereby decreasing vehicle energy consumption and improving vehicle comfort.

Electric Vehicle Battery Lifespan Diagnosis Technology Based on Resistance Trends Under Real-World Operating Conditions

As part of global efforts towards low-carbon green growth for a sustainable future, the rapid adoption of electric vehicles is underway worldwide. Consequently, the importance of battery-related technology is increasing, and research on battery lifespan and fault diagnosis has emerged as a crucial topic. However, due to environmental and temporal constraints, lifespan diagnosis technology based on accelerated laboratory tests and equivalent circuit modeling faces challenges in accurately reflecting the diverse environmental factors such as degradation under actual driving conditions. Therefore, this study monitors data from electric vehicles in actual operation to analyze the driving patterns of users. Based on these patterns, charging and discharging experiments were conducted on 18650 cylindrical batteries to investigate their characteristics under real-world conditions. The degradation characteristics under actual operating conditions were then trained in an AI model and scaled up to electric vehicle batteries to analyze the accuracy of the AI model. This approach aims to provide insights into electric vehicle battery pack lifespan diagnosis technology.

The Effect of Pt Catalysts with Controlled Hydrophilicity on the Surface on the Dispersibility of Ionomers and Durability in Polymer Electrolyte Fuel Cells

Polymer electrolyte fuel cells (PEFCs) are attracting attention as a promising system that can generate electricity without emitting greenhouse gases such as CO2. In recent years, there has been growing interest in the use of FCVs for Heavy duty commercial vehicles(HDV) due to the relationship between cruising range, vehicle size, and fuel costs, and many manufacturers are actively pursuing development. HDV require high power density and a cruising range of over 1 million km on a single charge, and achieving this requires a large amount of platinum catalyst, so striking a balance between performance and durability is important1. The distribution of ionomers on the surface of the catalyst and within the catalyst layer is an important topic for improving performance, and has been clarified through extensive research, including the mechanism of activity reduction due to adsorption poisoning of Pt by sulfonic acid functional groups2,3 and the adsorption and occupation of Pt by ionomers deposited in the pores or on the outer surface of the support4,5. In order to discuss the dispersion of the ionomer on the catalyst surface, it is necessary to consider the balance of the surface conditions of the platinum and carbon support surface. We evaluated the effect of differences in hydrophilicity on the dispersion of ionomers by chemical treatment of the catalyst surface to give differences in hydrophilicity derived from the balance of functional groups and Pt oxides. Furthermore, assuming use under actual operating conditions, the impact of the hydrophilicity of the catalyst on durability was evaluated using water-generating load cycle durability test6.We prepared a reference catalyst of 50% Pt/Ketjen EC300J (K-1), and then prepared K-2 and K-3 with different hydrophilicities using two different surface treatment methods.K-2 was found to have excessive hydrophilicity, while K-3 had moderate hydrophilicity. Through surface treatment, we found that there were differences in the amount of hydrophilic functional groups and the amount of Pt oxide. In addition, we observed the dispersibility of the ionomers using a low-accelerate-voltage TEM, and found differences in the dispersibility of the ionomer layer on the catalyst surface and the pore blockage within the catalyst layer depending on the hydrophilicity. We achieved high dispersibility of the ionomers by appropriately controlling the hydrophilicity, as in K-3. In addition, the Pt utilization ratio (U Pt) was measured using electrochemical measurements. K-3showed a high U Pt with moderate hydrophilicity. In addition, in water-generating load cycle durability test, K-3 with moderate hydrophilicity showed high durability.Based on this, it is expected that the surface condition of the catalyst can be appropriately controlled to promote improvements in the MEA structure, its performance, and durability. s durability. Acknowledgement This work was partially based on results obtained from a project, JPNP20003,commissioned by the New Energy and Industrial Technology Development Organization (NEDO). References 1)D. A. Cullen, et al., Nat. Energy, 6, 462−474(2021).2)K. Kodama, et al., ECS Trans., 58, 363−368(2013).3)K. Kodama, et al., ACS Catal., 8 , 694−700(2018).4)Y. C. Park, et al., J. Power Sources, 315, 179−191(2016).5)A. Kobayashi, et al., ACS Appl. Energy Mater., 4, 2307−2317(2021).6)C. Takei, et al., J. Power Sources, 324, 729−737(2016). Figure 1