Operating Conditions Research Articles

Effects of propeller cavitation on ship propulsion performance in off-design operating conditions

The propeller cavitation is closely related with its hydrodynamic performance. When the propeller works in the cavitating flow, the propeller hydrodynamic performance, in terms of thrust and torque coefficients, is reduced due to the propeller cavitation. When the high-speed and high-power ship sails in adverse sea, the varying loads on propeller will cause severer cavitation on propeller. The reduction in propulsion performance caused by cavitation will further affect the propulsion system, impacting the ship sailing performance and safety. The VP1304 propeller cavitation CFD simulation are conducted to validate the CFD method. Furthermore, the influence of propeller advance ratio and cavitation numbers on the performance of low-speed high-power series propeller in cavitating flow are studied and illustrated. This influence of cavitation has also been transferred to the propulsion system and this process are calculated by the ship propulsion system numerical model. Additionally, the sailing performance of ship propulsion system under off-design conditions, where the cavitation is more likely to occur, has been investigated in this article. Under severe heavy load conditions, it can even result in a complete loss of propulsion capability, posing significant risks. Therefore, it is necessary to further optimize control strategies for the propulsion system to mitigate the hazards caused by cavitation.

Preprocessing Text Data for the Doc2Vec Model in the Automatic Classification of Tickets in Support Centers of Software Providers

Leading software providers typically implement customer technical support functions, which are crucial for promoting and enhancing the competitiveness of their products and services in global markets. The high volume and heterogeneity of support tickets (functional, temporal, linguistic, etc.) highlight the importance of efficient classification systems. Effective classification optimizes the distribution of these tickets among support center specialists and automates their processing using an established knowledge base. However, classifying these tickets is a loosely formalized task. For companies that have accumulated substantial data on customer requests, automating classification through machine learning methods and natural language processing models, such as Word2Vec, FastText, BERT, and GPT, becomes feasible. It is generally accepted that classification effectiveness primarily depends on the model employed. Nevertheless, the quality of these models is significantly influenced by the nature of the training data. Literature review of the reveals significant research interest in methods for the automatic classification of tickets specifically tailored to the operational conditions of software provider support centers. However, there is a noticeable gap in the literature regarding the impact of data preprocessing on the quality of these models. The article aims to clarify the techniques of data preprocessing and analyze their impact on the effectiveness of text classification, considering the specificity of software provider support centers. This study examines the stages of the automatic classification process for tickets, accounting for the unique characteristics of the data (customer text requests). A relevant set of specified methodological and instrumental tools was developed and tested using open data from a global software provider (DevExpress). The testing involved a database of 165,000 tickets. The study's results indicate that preprocessing can improve classification metrics such as F-measure, Precision, and Recall from 77% to 79%. Additionally, preprocessing significantly reduces the dimensionality of text data (by 48.2%) and increases model training speed (by 26.5%) without loss of accuracy, ensuring cost-efficiency and operational efficiency in the use of computational resources.

Effect of Residual Cuts on Deactivation of Hierarchical Y Zeolite-Based Catalysts during Co-Processing of Vacuum Gas Oil (VGO) with Atmospheric Residue (ATR)

The influence of residual cuts on the deactivation of hierarchical Y zeolite-based catalysts during the co-processing of vacuum gas oil (VGO) with atmospheric residue (ATR) was investigated. The experiments were conducted in a laboratory-scale MAT-type reactor. The conversion of VGO, ATR, and their 70:30 (mass basis) mixture was examined using two composite catalysts: Cat.Y.0.00 and Cat.Y.0.20. The operating conditions closely resembled those of the commercial catalytic cracking process (550 °C and contact times of 10 to 50 s). When ATR was processed individually, the conversion remained below 50 wt%. However, significant improvements in conversion rates were achieved and catalyst deactivation was mitigated when ATR was co-processed with VGO. Notably, the BET surface area and average mesopore volume were adversely impacted by ATR, which also led to the accumulation of high levels of metals and nitrogen on the spent catalyst, detrimentally affecting its acidic and structural properties. Moreover, substantial coke deposition occurred during ATR cracking. The soluble and insoluble coke analysis revealed H/C ratio values of up to 0.36, indicative of polycondensed coke structures with more than ten aromatic rings. The nature of the coke was confirmed through TPO and FTIR analyses. Interestingly, the CatY.0.20 catalyst exhibited less activity loss, retaining superior acid and structural properties. Co-processing Colombian atmospheric residue with ATR loadings of 30 wt% (higher than the typical 20 wt%) in catalysts formulated with hierarchical zeolites presents a promising alternative for commercial applications. This research opens avenues for optimizing catalytic cracking processes.

Synchronous Decomposition Match-Reassigning Transform and Its Application in Planetary Gearbox Fault Diagnosis

Abstract Under time-varying operating conditions, the instantaneous frequency (IF) of the vibration signal of the planetary gearbox exhibits non-stationary time-varying closely spaced characteristics as well as non-proportional and non-synchronous characteristics, making it difficult for traditional time-frequency analysis (TFA) methods to accurately identify its fault features and obtain accurate time-frequency representations (TFR). To address this challenge, this paper proposes a TFA method based on Synchronous Decomposition Match-Reassigning Transform (SDMRT). Firstly, the successive variational mode decomposition (SVMD) is used to adaptively separate non-synchronous frequency components in the original vibration signal. Then, the chirp rate (CR) describing the signal harmonic structure is used to synchronously match each frequency component, obtaining the TFR corresponding to each component. Next, all TFRs are merged to obtain a complete TFA result. Finally, Finally, the energy spread is re-aggregated to the ridge of the IF using the reassignment principle, resulting in a new frequency estimation operator called the Synchronous Decomposition Match-Reassigning Operator (SDMRO). SDMRT can adaptively separate non-proportional and non-synchronous IFs and achieve precise matching of time-varying closely spaced IFs, thereby completing the TFR of the vibration signal generated by the planetary gearbox. By analyzing simulated signals and measured vibration signals from planetary gearboxes, the method proposed in this paper is significantly superior to other TFA methods, thereby validating the effectiveness and superiority of SDMRT.

Review Paper for SOC Estimation Techniques: Challenges and Future Areas for Improvement

This paper explores the advancements and challenges in State of Charge (SOC) estimation techniques for lithium-ion batteries, particularly within the context of electric vehicles (EVs) and renewable energy systems. As the global demand for sustainable energy solutions grows, accurate SOC estimation becomes essential for optimizing battery performance, enhancing safety, and extending battery life. The paper categorizes various SOC estimation methods into three primary approaches: direct measurement techniques, model-based methods, and data-driven algorithms. Direct measurement techniques, such as Coulomb counting and Open Circuit Voltage (OCV), are straightforward but often lack precision under dynamic conditions. Model-based methods, including Equivalent Circuit Models (ECM) and electrochemical models, provide detailed insights into battery behavior but can be computationally intensive. In contrast, data-driven approaches utilizing machine learning algorithms exhibit promising adaptability and accuracy, albeit relying heavily on large datasets. Despite these advancements, several limitations persist. Current SOC estimation methods are hindered by their dependence on accurate battery models and quality data, which can degrade over time. Furthermore, hybrid methods, which combine strengths from various techniques, introduce complexity and demand substantial computational resources. The integration of SOC estimation techniques in EV applications poses additional challenges due to varying operational conditions, necessitating efficient processing of real-time data from multiple sensors. Emerging trends in Battery Management Systems (BMS) are also examined, highlighting the role of AI and machine learning in improving real-time SOC computations and predictive capabilities. Cloud-based BMS systems are identified as a significant development for remote monitoring and control, enhancing the overall reliability of battery systems. This paper aims to provide a comprehensive overview of SOC estimation techniques, identify ongoing challenges, and suggest future research directions to enhance the effectiveness of battery management strategies in the evolving landscape of energy systems. DOI: https://doi.org/10.52783/pst.906

Development of a Mathematical Model of a Highly Maneuverable Robot for Simulation of Robots with Different Types of Designs

The article presents the results of developing a mathematical model and simulation modeling of a three-wheeled highly maneuverable mobile robot. A mathematical model of the robot in the state space has been developed. The possibility of using this robot with rotary modules for analyzing and testing control algorithms for robots of various designs has been considered. The relevance of the study is justified by the high costs of creating physical models of robots for experimental verification of control algorithms. The proposed three-wheeled mobile robot with rotary modules, where each wheel is simultaneously both a driving and a steering wheel, allows reducing these costs, while maintaining the ability to simulate part of the real operating conditions. Simplified diagrams of the robot are given, the main parameters and equations characterizing the change in linear and angular velocity are described. Particular attention is paid to modeling various types of robot drives: automotive type and with a differential drive. In the discrete state space, equations describing the dynamics of the robot were presented, which allows them to be used in software products for modeling. The results of simulation modeling obtained in the SimInTech software environment confirm the effectiveness of the proposed model. The analysis of the obtained results showed that the use of a three-wheeled robot with rotary modules allows successfully simulating the behavior of robots with other types of drives and creating conditions close to real ones for testing control algorithms. The proposed model can be used to improve the quality of design and testing of control algorithms in robotics, while reducing the costs of creating physical models of robots, as well as in the educational process.

Optimisation of synchronisation control parameters for enhanced bilateral teleoperation system

Abstract Bilateral teleoperation systems encounter challenges in achieving synchronisation between master and slave robots due to communication time delays. This paper addresses the instability caused by these delays and proposes a solution through advanced control algorithms. Nonlinear optimisation algorithms might only sometimes deliver solutions in the allotted time, particularly when handling complicated, high-dimensional issues or when optimisation iterations are extensive. The study first develops a comprehensive mathematical model encompassing the dynamics and communication intricacies of both master and slave sides in teleoperation. By recognising the limitations of existing proportional-derivative controllers in compensating for communication errors, a sequential quadratic programming-proportional-integral-derivative (SQP-PID) controller is introduced. This controller accumulates and rectifies synchronisation delay errors, ensuring precise control without steady-state deviations. The proposed SQP-PID controller stands out for its ability to handle steady-state errors effectively, offering swift response and maintaining stability. Leveraging the SQP optimisation algorithm, it intelligently tunes the parameters, minimising synchronisation errors. The approach capitalises on the simplicity, performance, and robustness of the SQP-PID controller, providing a promising avenue for enhancing bilateral teleoperation systems’ accuracy and stability, maintaining initial discrepancy with a best fitness value of 0.98 % in varied operating conditions.

The degradation mechanism of high power S-band AlGaN/GaN HEMTs under high temperature

Abstract The RF degradation mechanism under high temperature of high power GaN-based high electron mobility transistors (HEMTs) are proposed in this paper. The saturated output power (Psat), power added efficiency (PAE) and gain of the HEMTs deteriorated obviously under large power dissipation operation conditions which contribute to the elevate of junction temperature (Tj). The high Tj caused the negative shift of threshold voltage and the reduction of electron mobility, meanwhile, promoting trapping effects of the devices. As a result, the Psat and PAE of high power HEMTs (Psat = 152 W) decreased 0.76 dB and 8.3% which is more serious than low power HEMTs (Psat = 20 W) with Psat and PAE reducing 0.16 dB and 3.1% as elevating the operation temperature from 25 to 150 oC. By increasing the gate-to-drain distance from 1.625 to 2.175 μm, the stability of drain current and HTRB reliability are improved. It demonstrates that the trapping effect can be suppressed by decreasing the electric field under the gate, therefore, the RF output characteristics are boosted by 1.2 W, 1 dB and 2.6% for the device with gate width of 11.52 mm.

Blood trauma in veno-venous extracorporeal membrane oxygenation: low pump pressures and low circuit resistance matter

BackgroundVeno-venous extracorporeal membrane oxygenation (VV ECMO) has become standard of care in patients with the most severe forms of acute respiratory distress syndrome. However, hemolysis and bleeding are one of the most frequent side effects, affecting mortality. Despite the widespread use of VV ECMO, current protocols lack detailed, in-vivo data-based recommendations for safe ECMO pump operating conditions. This study aims to comprehensively analyze the impact of VV ECMO pump operating conditions on hemolysis by combining in-silico modeling and clinical data analysis.MethodsWe combined data from 580 patients treated with VV ECMO in conjunction with numerical predictions of hemolysis using computational fluid dynamics and reduced order modeling of the Rotaflow (Getinge) and DP3 (Xenios) pumps. Blood trauma parameters across 94,779 pump operating points were associated with numerical predictions of shear induced hemolysis.ResultsMinimal hemolysis was observed at low pump pressures and low circuit resistance across all flow rates, whereas high pump pressures and circuit resistance consistently precipitated substantial hemolysis, irrespective of flow rate. However, the lower the flow rate, the more pronounced the influence of circuit resistance on hemolysis became. Numerical models validated against clinical data demonstrated a strong association (Spearman’s r = 0.8) between simulated and observed hemolysis, irrespective of the pump type.ConclusionsIntegrating in-silico predictions with clinical data provided a novel approach in understanding and potentially reducing blood trauma in VV ECMO. This study further demonstrated that a key factor in lowering side effects of ECMO support is the maintenance of low circuit resistance, including oxygenators with the lowest possible resistance, the shortest feasible circuit tubing, and cannulae with an optimal diameter.

Remaining Useful Life of the Rolling Bearings Prediction Method Based on Transfer Learning Integrated with CNN-GRU-MHA

To accurately predict the remaining useful life (RUL) of rolling bearings under limited data and fluctuating load conditions, we propose a new method for constructing health indicators (HI) and a transfer learning prediction framework, which integrates Convolutional Neural Networks (CNN), Gated Recurrent Units (GRU), and Multi-head attention (MHA). Firstly, we combined Convolutional Neural Networks (CNN) with Gated Recurrent Units (GRU) to fully extract temporal and spatial features from vibration signals. Then, the Multi-head attention mechanism (MHA) was added for weighted processing to improve the expression ability of the model. Finally, a new method for constructing Health indicators (HIs) was proposed in which the noise reduction and normalized vibration signals were taken as a HI, the L1 regularization method was added to avoid overfitting, and the model-based transfer learning method was used to realize the RUL prediction of bearings under small samples and variable load conditions. Experiments were conducted using the PHM2012 dataset from the FEMTO-ST research institute and XJTU-SY dataset. Three sets of 12 migration experiments were conducted under three different operating conditions on the PHM2012 dataset. The results show that the average RMSE of the proposed method was 0.0443, indicating high prediction accuracy under variable loads and small sample conditions. Three different operating conditions and two sets of four migration experiments were conducted on the XJTU-SY dataset, and the results show that the average RMSE of the proposed method was 0.0693, verifying the good generalization of the model under variable load conditions. In summary, the proposed HI construction method and prediction framework can effectively reduce the differences between features, with high stability and good generalizability.

Semiconductor optical amplifiers as an optical arbitrary waveform generator for high-energy laser systems

A simple and straightforward technique is presented as a novel temporally controllable front-end for nanosecond very-high energy laser systems. It is based on an original utilization of a semiconductor optical amplifier (SOA) used as an intensity modulator. The essential characteristics of the component are analyzed in order to evaluate potential limitations. Various parameters of interest for standard operation are displayed, demonstrating its usability and its effectiveness. We demonstrate arbitrary and controllable pulse temporal profiles with duration ranging from 1 nanosecond to 100 nanoseconds and a temporal precision of 1.1 ns. A high extinction ratio is also achieved ensuring a modulation contrast up to 53 dB. The SOA is then integrated into an existing operating system in an ultra-compact, reliable all-fibered system. It is used to seed a 2*200 J laser system, exhibiting excellent performance, and validating its usability under operation conditions without any detrimental effects.

The Reconstruction of Bi2Te4O11 Nanorods for Efficient and pH-universal Electrochemical CO2 Reduction.

The electrochemical CO2 reduction reaction (CO2RR) to generate chemical fuels such as formate presents a promising route to a carbon-neutral future. However, its practical application is hindered by the competing CO production and hydrogen evolution reaction (HER), as well as the lack of pH-universal catalysts. Here, Te-modified Bi nanorods (Te-Bi NRs) were synthesized through in situ reconstruction of Bi2Te4O11 NRs under the CO2RR condition. Our study illustrates that the complex reconstruction process of Bi2Te4O11 NRs during CO2RR could be decoupled into three distinct steps, i.e., the destruction of Bi2Te4O11, the formation of Te/Bi phases, and the dissolution of Te. The thus-obtained Te-Bi NRs exhibit remarkably high performance in CO2RR towards formate production, showing high activity, selectivity, and stability across all pH conditions (acidic, neutral, and alkaline). In a flow cell reactor under neutral, alkaline, or acidic conditions, the catalysts achieved HCOOH Faradaic efficiencies of up to 94.3 %, 96.4 %, and 91.0 %, respectively, at a high current density of 300 mA cm-2. Density functional theory calculations, along with operando spectral measurements, reveal that Te manipulates the Bi sites to an electron-deficient state, enhancing the adsorption strength of the *OCHO intermediate, and significantly suppressing the competing HER and CO production. This study highlights the substantial influence of catalyst reconstruction under operational conditions and offers insights into designing highly active and stable electrocatalysts towards CO2RR.

Electronic Structure Modulating of W 18 O 49 Nanospheres by Niobium Doping for Efficient Hydrogen Evolution Reaction.

Developing efficient electrocatalysts to reduce HER overpotential is vital to enhance hydrogen production efficiency and minimize energy consumption. Adjusting the electronic structure of transition metal oxides via elemental doping is a potent strategy to improve the effectiveness of electrocatalysts for hydrogen evolution. In this work, we synthesized a set of niobium-doped tungsten oxides (Nbx-W18O49) under anoxic conditions using a straightforward "one-pot" solvothermal approach. After doping Nb, the oxygen vacancy content inside W18O49was increased, which induced a synergistic effect with the active sites of tungsten. In acidic environments, the hydrogen evolution activity of the Nb0.6-W18O49electrocatalyst is secondonly by 20 wt% Pt/C. It attains a current density of -10 mA cm-2at an overpotential of 102 mV. By comparison with W18O49, Nb0.4-W18O49and Nb0.5-W18O49, Nb0.6-W18O49demonstrates a reduced charge transfer resistance, which significantly enhances its conductivity and the speed of electron movement across interfaces. Coupled with this feature are notably faster HER kinetics. Additionally, it exhibits excellent stability, meaning it maintains its performance and structural integrity over prolonged periods and under various operational conditions. This article provides a new perspective for discovering inexpensive and efficient hydrogen evolution electrocatalyst materials.

An investigation on tribology performance of Abutilon Indicum fibre reinforced polymer composites

This research work investigates the tribological characteristics of Abutilon Indicum Fiber (AIF) reinforced composites with epoxy as the binding agent. The Abutilon Indicum fiber reinforced composites were manufactured by compression molding technique. These composites were fabricated by varying the fiber volume fraction ranging from 5%, 10%, 15% and 20% respectively and considering the fiber length as a fixed factor due to its short length. This research paper illustrates the effects of different fiber volume fractions (5,10,15 and 20%) on the tribological properties such as Specific wear rate (SWR) and Coefficient of friction (µ) of Abutilon Indicum fiber reinforced composites. Sliding wear tests were carried out under dry environment conditions with pin-on-disc wear testing machine. The experiments were performed for each composite with different combinations of testing parameters, sliding loads (10, 20 and 30 N); sliding distances (1,2 and 3 km); sliding speeds (1,2 and 3 m/s). Shore D hardness of 78.22 is determined to be higher for 15% volume fraction of AIF composites. Results conclude that the addition of AIFs in these composites enhanced the tribological performance with good wear resistance in relation with the pure epoxy-based composites with 15% volume fraction of AIFs displaying best results with higher resistance to wear at various operating conditions. Composites produced with 20% volume fraction displays the effects of fiber agglomeration which in turn has an inverse effect on hardness; limits the wear resistance with higher friction and wear rate and such results agree well with the wear debris, pits and contact patches in micrographs. Optimal fiber volume fraction of 15% was suggested in fabrication of composites for usage of AIFs as friction material.

Fault domain separation networks: A cross-domain diagnostic method for variable operating conditions in the elevator guidance system

High-speed elevators play a critical role in vertical transportation. However, they may exhibit different working conditions under varying operating conditions, posing challenges for fault diagnosis. We propose a model named fault domain separation networks (FDSN) to tackle the cross-domain diagnostic problem of guidance system by leveraging transfer learning techniques. FDSN comprises three distinct modules that extract invariant fault features and variable operating condition features, and use orthogonal loss function for feature decoupling, achieving effective feature allocation, and mitigating the impact of variable operating conditions on fault diagnosis. To evaluate and demonstrate the efficacy of FDSN, a high-speed elevator platform is constructed, and fault vibration data under various working conditions are simulated to form a comprehensive dataset. The proposed FDSN achieved an average diagnostic accuracy of 92.7% in cross-domain diagnostic tasks, outperforming other comparative methods and demonstrating the remarkable superiority.

ОСОБЛИВОСТІ ВПРОВАДЖЕННЯ МОНІТОРИНГУ ПЕРСОНАЛУ НА СУЧАСНИХ ПІДПРИЄМСТВАХ

Businesses related to various niches and industries use employee monitoring to protect themselves from potential risks of data leakage and other external threats. Employee monitoring is a new strategy in today's business that is central to improving productivity and operational efficiency. The application of scientific methods of monitoring and analyzing the activities of employees in real time allows organizations to achieve a high level of accountability, optimal allocation of resources and making informed management decisions. Such a monitoring system contributes to the rise and development of the enterprise, creating a more productive and motivated work environment. The article examines the peculiarities of the implementation of employee monitoring as an important tool for ensuring the efficient operation of the enterprise, maintaining labor discipline and rational use of resources. Separate forms of monitoring that are used in practice are considered. Attention is focused on the legal aspects of the monitoring process, compliance with the needs of both employers and employees, in particular, taking into account the rights and privacy of the latter. In the modern conditions of business operation and development, employers have an interest in the most efficient use of their staff's working time. Time control is one way to achieve this. Controlling working hours can be efficient and beneficial for a company, but it can also raise certain ethical and legal issues. It is important that this control is carried out in compliance with all relevant legal requirements and taking into account the rights and interests of employees. Therefore, the employer must develop and implement internal regulatory documents that regulate monitoring procedures, as well as ensure that employees are informed about their rights and obligations in this process. This will avoid conflicts and ensure the legal purity of monitoring, maintaining a balance between the needs of the enterprise and the rights of employees. The choice of personnel monitoring and tracking tools is not limited to technical aspects, but includes the creation of a culture of trust and openness in the relationship between the employer and employees.

An Efficient Time‐Sensitive Networking Traffic Scheduling Method for Train Communication Network

As a critical system of rail train, the train communication network (TCN) is an integrated central platform that is used to realize the train operation control, condition monitoring, and data transmission. With the development of train intelligence, the scale of data flow in TCN continues to expand, and the control data and monitoring data must be real‐time transmitted to ensure the safe and reliable operation of the train. Time‐sensitive network (TSN) can be applied as the next‐generation TCN solution, which provides end‐to‐end data transmission with extremely low delay and high reliability based on Ethernet. For the application of TSN technology in TCN, a single frame simple scheduling method is proposed to effectively reduce the worst end‐to‐end delay of the entire network, which improve the real‐time performance of TSN‐based TCN. The network topology and data flow characteristics in TCN are analyzed, a series of scheduling constraints are constructed, and the satisfiability modulo theories (SMT) is used to obtain a gate control list (GCL) to ensure the real‐time performance of time‐trigger streams. Finally, the TCN simulation model is established using OMnet++ software, the experiment results show that the proposed method can effectively reduce the overall delay and jitter, and meet the real‐time requirement of TCN. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Increasing Vitamin K2 Synthesis in Bacillus subtilis by Controlling the Expression of MenD and Stabilizing MenA.

As an indispensable member of the family of lipid vitamins, vitamin K2 (MK-7) plays an important role in blood coagulation, cardiovascular health, and kidney health. Microbial fermentation is favored due to its high utilization rate of raw materials, simple operation, and moderate conditions. However, the biosynthesis pathway of vitamin K2 in microorganisms is highly complex, which hinders its industrial production in microbial cell factories. One of the major challenges is the stable expression and deregulation of key enzymes in the vitamin K2 biosynthesis pathway, which remains unclear and has undergone little investigation. In this study, 2-succinyl-5-enolpyruvyl-6-hydroxy-3-cyclohexene-1-carboxylic-acid synthase (MenD) and 1,4-dihydroxy-2-naphthoate polyprenyltransferase (MenA) were identified as pivotal enzymes in the biosynthesis of vitamin K2. To investigate the catalytic efficiency of MenD in the biosynthesis pathway of vitamin K2, structure-based mutation design and site-directed mutagenesis were performed. Three mutation sites were identified in MenD: A115Y, R96 M, and R323M, which improve the expression level and protein stability. Meanwhile, the MenA mutant T290M, which exhibits improved protein stability, was obtained by modifying its hydrophobic stacking structure. Finally, an engineered strain noted ZQ13 that combinatorially overexpressed MenD (A115Y) and MenA (T290M) mutants was constructed and achieved 338.37 mg/L vitamin K2 production in a 3-L fermenter.

Scaling design and similarity analysis of a floating nuclear power plant

In the process of developing floating reactor systems, their operation in the marine environment needs to be simulated to ensure the reliability of the safe design of nuclear reactors. Scaling test is a potential option for computer model validation by virtue of its low cost and flexibility. This study first gives the similarity law for dynamic tests of the reactor system in high-temperature environments by dimensional analysis. Then we focus on analyzing the jamming phenomenon that may occur during the similarity design process and provides a solution for realizing the contact state of the prototype in the scaled model. This study also analyzes the dynamic response of a floating reactor system under extreme operating conditions by combining numerical simulations and scaling tests. By comparing the response results predicted by the scaled model with the prototype response, it is further demonstrated that the feasibility of scaling test as an alternative to full-size test to provide a reference for realizing low-cost, accurate and safe design for reactor system.

The Impact of Flow-Thermal Characteristics in Ship-Board Solid Oxide Fuel Cells

Hydrogen is increasingly recognized as a clean and reliable energy vector for decarbonization in the future. In the marine sector, marine solid oxide fuel cells (SOFCs) that employ hydrogen as an energy source have already been developed. In this study, a multi-channel plate-anode-loaded SOFC was taken as the research object. A three-dimensional steady-state computational fluid dynamics (CFD) model for anode-supported SOFC was established, which is based on the mass conservation, energy conservation, momentum conservation, electrochemical reactions, and charge transport equations, including detailed geometric shapes, model boundary condition settings, and the numerical methods employed. The polarization curves calculated from the numerical simulation were compared with experimental results from the literature to verify the model’s accuracy. The curved model was applied by enlarging the flow channels or adding blocks. Numerical calculations were employed to obtain the current density, temperature distribution, and component concentration distribution under the operating conditions of the SOFC. Subsequently, the distribution patterns of various physical parameters during the SOFC operation were analyzed. Compared to the classical model, the temperature of the curved model was reduced by 1.3%, and the velocities of the cathode and anode were increased by 4.9% and 5.0%, respectively, with a 2.42% enhancement in performance. The findings of this study provide robust support for research into and the application of marine SOFCs, and offer they insights into how we may achieving “dual carbon” goals.