Operational Instability Research Articles

Transient Analysis of Flow Unsteadiness And Machine Instabilities In a Centrifugal Compressor at Surge and Second Quadrant Operation

Abstract Instabilities in turbomachinery operation originate from intrinsic flow unsteadiness, sudden variations of operating conditions, and interactions with the surrounding system, affecting both system stability and machine reliability. The flow unsteadiness, presenting a characteristic behaviour, requires a deep understanding of the underlying flow fundamentals, a careful analysis using advanced experimental methods and a clear distinction on how the system might lead to instabilities. The identified approach addresses deep surge and second quadrant characterization. The analysis presented here benefits from the responsiveness and flexibility of the experimental test rig, fine tuning of the system layout, the instrumentation installation, and the transient tests procedure. The main focus area is the time-frequency analysis of flow and pressure signals at transients, thus providing a proper reconstruction of flow mechanisms and instability evolution. Valuable techniques include: short-time fast Fourier transform, wavelet analysis, and Wigner-Ville distribution; coherence between flow and pressure, to trace waves propagation, is considered too. These, presented outlining their strengths and weaknesses, are evaluated considering real time field applicability with regards to computational resources too. The experimental campaigns and data processing are presented, with a test matrix covering a wide range of parameters, including system layout and surge volume size, rotational speeds, flow rates ranging from nominal point to full second quadrant operation. These data are vital for system modeling validation for a full compressor-system digital twin. Results indicate the importance of ensuring reliable data acquisition and analysis, with adequate instrumentation range, accuracy, synchronization, responsiveness and positioning.

Threshold Voltage Recovery Time Measurement Technique Post VTH Instability in Normally-Off p-Gate GaN High Electron Mobility Transistors

In this study, we propose a simple measurement technique to quantitatively measure the time taken by threshold voltage of normally-off p-GaN AlGaN/GaN HEMTs to recover from a nominal operational gate stress-induced instability. The proposed technique eliminates the requirement to perform a full transfer characteristic sweep post-stress, thereby eliminating the measurement-induced instability effect, often colluding precise recovery time measurement. The rate of recovery and extracted recovery times hold significance in empirically correlating the location of traps in the p-GaN or AlGaN barrier region causing VTH instability. The gate of the HEMT is stressed at nominal operational drive voltages 1.5 V, 2 V, and 4 V for various time intervals from 500 μs to 100 s, and the time taken for the drain current to recover to prestress levels measured at near-threshold voltage (~1.1 VTH) is measured as the threshold voltage recovery time. With increasing gate stress voltages, 2DEG gets trapped at relatively deeper trap energy levels at the AlGaN/GaN interface requiring more emission time during the process of recovery, mandating larger recovery times. At higher stress voltage of 4 V, the Schottky gate leakage current is high enough enabling injected holes to cross the AlGaN barrier and counter-compensate for the deeply trapped 2DEG, requiring relatively the same recovery times as lower stress voltages where the gate leakage is negligibly small. With increasing stress time, the amount of 2DEG trapped increases, requiring more recovery time to de-trap and beyond a certain time, saturation of the trap density occurs causing the recovery time to plateau.

Suppressing Ion Migration in MAPbI3 Polycrystalline Wafer with BMIMBF4 Ionic Liquid for X‐ray Detection and Imaging

Abstract3D lead‐halide perovskite wafers, recognized for their superior photoelectronic properties and robust fabrication, are promising candidates for advanced X‐ray detectors. However, severe ion migration in 3D perovskite wafers leads to dark current baseline drift and long‐term operational instability, hindering their further development. Herein, 3D MAPbI3 polycrystalline wafers with suppressed ion migration are prepared using the ionic liquid 1‐butyl‐3‐methylimidazolium tetrafluoroborate (BMIMBF4) and systematically investigated for X‐ray detection. The BMIMBF4‐passivated MAPbI3 wafers exhibit a low defect trap density (ntrap) of 9.45 × 109 cm−3, a high ion activation energy (Ea) of 0.51 eV, a notable iodide ion migration energy barrier of 0.65 eV, and a decreased dark current drift (Idrift) of 3.56 × 10−4 nA cm−1 s−1 V−1. The optimized MAPbI3 wafer‐based detectors exhibit a high sensitivity of 12088.8 µC Gyair−1 cm−2, a low detection limit (LoD) of 107.8 nGyair s−1, and strong operational stability in X‐ray detection. Moreover, these detectors demonstrate outstanding X‐ray imaging capabilities, achieving a high spatial resolution of 5.17 lp mm−1. Consequently, the utilization of ionic liquids with pseudo‐halide anions and polarized electron density distribution provides an innovative strategy for passivating 3D perovskite, advancing the field of powder‐pressed perovskite wafer X‐ray detection.

Novel bioaugmentation process to enhance anaerobic digestion of municipal sewage sludge

The imperative shift to a circular economy, driven by population growth, urbanization, and economic development, highlights the importance of recovering resources from waste streams. Anaerobic digestion (AD) is promising for stabilizing organic wastes and producing renewable methane-rich biogas. However, AD faces challenges, including operational instability, fatty acids accumulation, ammonium inhibition, and low yields. This study investigates the applicability of a novel Ydro Process® bioaugmentation on municipal sewage sludge anaerobic digestion. The process led to pre-hydrolysis of sewage sludge, as evidenced by an increase in volatile fatty acids (VFA), from 134 mg HAc/L in raw TWAS to 997 mg HAc/L in augmented sludge and improved soluble chemical oxygen demand (SCOD) yields. Additionally, the viscosity decreased by 41 % in the Ydro Process® bioaugmented sludge. Biogas production significantly increased from 732 mL/day to 1338 mL/day during semi-continuous digestion, with methane yield rising from 116 mL/g TCODadded to 218 mL/g TCODadded. Microbial analysis revealed an enhanced population of hydrogenotrophic methanogens.

Chemically‐Modified 2D Covalent Organic Framework as an HTL Dopant for High‐Performance, Stable, and Sustainable Perovskite Solar Cells and Modules

AbstractDespite significant advances in perovskite solar cells (PeSCs), the operational instability and susceptibility to Pb leakage of PeSCs severely limit their widespread application. To address these issues, this study investigates the effect of doping the Spiro‐OMeTAD hole‐transporting layer (HTL) with a chemically‐modified 2D conjugated covalent organic framework (Tp‐Azo‐COF) on the photovoltaic performance and stability of PeSCs. Enriched with abundant carbonyl (C═O) groups and azo (N═N) nodes, Tp‐Azo‐COF has excellent chelation and adsorption capabilities, and experimental results confirm that Tp‐Azo‐COF effectively decreases Pb leakage and Li‐ion migration, improving the environmental safety and operational stability of PeSCs. The optimized PeSCs (0.12 cm2) exhibit an efficiency of 24.25%, a new benchmark for COF‐modified devices, and maintain robust performance in large‐area modules (18 cm2) with an efficiency of 21.96%. Under accelerated aging tests, including continuous light irradiation at maximum power point tracking for 980 h, the module demonstrated exceptional durability, with near‐100% efficiency retention. The COF doping strategy developed in this study significantly enhances operational stability and minimizes Pb leakage in PeSCs, paving the way for the sustainable, large‐scale deployment of perovskite photovoltaics.

Effect of sediment erosion on pressure pulsations in a large Pelton turbine

AbstractPelton turbines functioning in sandy river environments often encounter difficulties due to the swift movement of sediment particles, leading to erosion and damage to overflow components. These challenges can result in operational instability, particularly noticeable in large turbines. Pressure pulsation is crucial for turbine stability, and alterations in overflow component profiles caused by sediment erosion can worsen pressure pulsations. This study utilizes numerical simulations to analyze turbine pressure pulsations based on surface profile changes of runner buckets after 2 and 4 years of sediment erosion in a single 500 MW large‐scale Pelton turbine. Our findings reveal that erosion leads to a gradual decrease in pressure pulsation along the bucket's splitting edge from the notch to the root. After 4 years of erosion and wear, the relative pressure pulsation amplitude in the root region increased by more than 530%. Additionally, changes occur in the thickness of the water film in the erosion area on the working surface, disrupting the flow pattern and generating more vortices. This occurrence intensifies the relative pressure pulsation amplitude and reduces bucket stability. The study findings highlight the significant impact of sediment erosion on Pelton turbine pressure pulsation, posing a considerable risk to the unit's operational stability and safety.

Numerical modeling of alkali metal heat pipes

Heat pipe cooled reactors passively transfer heat from the core to the energy conversion system through alkali metal heat pipes. Further studies of the heat transfer characteristics of alkali metal heat pipes are needed to develop heat pipe cooled reactors. This work used a two-dimensional heat and mass transfer model of an alkali metal heat pipe. The flow field was validated against CFD predictions which showed that the model has less than 10 % errors in the velocity distribution and less than 5 % errors in the pressure distribution. A comparison of the predictions with experimental data in the literature indicated that the predicted wall temperature error was within 30 °C. This model was then used to analyze four factors that affect heat transfer in sodium heat pipes. The simulations show that higher heat fluxes shorten the startup time by approximately 70 % but significantly increase the operating temperature. The heat flux distribution significantly affects the evaporator temperature distribution. The heat transfer boundary condition on the condenser’s outer surface mainly affects the operating temperature and startup time. Increasing the heat pipe length-to-diameter ratio with a fixed heat flux increases the operating temperature with the increase proportional to the heat flux. This model provides accurate simulations of sodium heat pipes for various heat transfer boundary conditions. The simulations provide a reference for the selection of working conditions for heat pipe operation instability experiments.

Energy performance and pressure fluctuation in multi-stage centrifugal pump with floating impellers under various axial oscillation frequencies

A novel multi-stage centrifugal pump with floating impellers is gaining traction in energy systems because it easily links stages in series for varying high head requirements. However, the axial oscillation frequency of the floating impeller introduces uncertainties in the pump's energy performance and pressure fluctuation. To address these issues, a comprehensive analysis of multi-stage centrifugal pumps was conducted, utilizing a computational fluid dynamics simulation method that incorporats dynamic mesh and multiple reference frame techniques, validated through three experimental trials. The findings show that average head coefficient and average efficiency are not significantly affected by the axial oscillation of impeller, but that pressure fluctuations, efficiency, and head coefficient all show periodic variations that are connected to the frequency of impeller oscillation. The amplitude of variations in the head coefficient and efficiency could increase by as much as 112.3 % and 172.4 %, respectively, under the influence of impeller oscillations, thereby heightening the instability of pump operation. Trigonometric functions for the energy performance during impeller oscillations are proposed to facilitate rapid assessment of pump stability. This study offers valuable insights into the unsteady characteristics of novel multi-stage centrifugal pumps and serves as a reference for further understanding their dynamic behavior.

Experimental study on combustion instability characteristics in a pre-chamber natural gas engine under lean burn conditions

Pre-chamber jet ignition is a key technology for future high-efficiency natural gas (NG) engines. It can achieve fast and stable combustion through excellent ignition performance. However, there are still some challenges, such as high combustion instability near the lean burn limit and the narrow engine operating range. Therefore, this paper investigates the combustion instability of a pre-chamber NG engine under ultra-diluted conditions by experimental method. At two engine loads, experiments are carried out with different jet ignition intensity schemes to study the effect of jet ignition intensity on the cyclic combustion variations. Then, the combustion instability characteristics of the pre-chamber NG engine are studied by cyclic variation analysis and phase space reconstruction. The results show that with the increase in the jet ignition intensity, the cyclic combustion variations decrease, and the cyclic variation coefficient of the indicated mean effective pressure decreases to below 2%. The lean burn limit of the pre-chamber natural gas engine is extended to an excess air ratio of 2.0. The operation instability of the pre-chamber NG engine is mainly due to cyclic variations in the ignition and combustion process. The nonlinear dynamic analysis shows that the combustion process in the lean burn pre-chamber NG engine behaves with chaotic characteristics under the operating conditions of low jet ignition intensity. As the jet ignition intensity increases, the combustion stability is improved and the cycle-to-cycle variations change from fairly deterministic to more stochastic behavior. The chaotic characteristics of the combustion process become weaker. In conclusion, it is of great importance to generate stable and high ignition intensity jets for reducing combustion instability and improving combustion efficiency in lean burn pre-chamber NG engines.

Ion Migration in Metal Halide Perovskites: Characterization Protocols and Physicochemical Mechanisms.

Metal halide perovskites (MHPs) have demonstrated considerable promise for a range of photoelectronic applications owing to their prominent photophysical properties. However, MHPs suffer from remarkable ion migration under illumination and bias voltage, which generally poses operational instability of MHP-based devices and restricts their practicality. While numerous chemical strategies have been proposed for manipulating ion migration dynamics, the relevant mechanistic research relatively lags behind, which is nevertheless imperative for guiding ion migration engineering. In this perspective, we first review the well-established experimental techniques for characterizing ion migration in MHP films and photovoltaic devices. For the sake of gaining insights into the underlying mechanism, we also present a series of physical models that elucidate the dynamics of ion migration and the coupling interaction between ions and charge carriers in MHP photovoltaics. Finally, we identify several crucial areas for future investigation, with the aim of advancing both the fundamental and applied research on high-efficiency and high-stability MHP materials and devices.

Optimization of a Novel Engineered Ecosystem Integrating Carbon, Nitrogen, Phosphorus, and Sulfur Biotransformation for Saline Wastewater Treatment Using an Interpretable Machine Learning Approach.

The denitrifying sulfur (S) conversion-associated enhanced biological phosphorus removal (DS-EBPR) process for treating saline wastewater is characterized by its unique microbial ecology that integrates carbon (C), nitrogen (N), phosphorus (P), and S biotransformation. However, operational instability arises due to the numerous parameters and intricates bacterial interactions. This study introduces a two-stage interpretable machine learning approach to predict S conversion-driven P removal efficiency and optimize DS-EBPR process. Stage one utilized the XGBoost regression model, achieving an R2 value of 0.948 for predicting sulfate reduction (SR) intensity from anaerobic parameters with feature engineering. Stage two involved the CatBoost classification and regression model integrating anoxic parameters with the predicted SR values for predicting P removal, reaching an accuracy of 94% and an R2 value of 0.93, respectively. This study identified key environmental factors, including SR intensity (20-45 mg S/L), influent P concentration (<9.0 mg P/L), mixed liquor volatile suspended solids (MLVSS)/mixed liquor suspended solids (MLSS) ratio (0.55-0.72), influent C/S ratio (0.5-1.0), anoxic reaction time (5-6 h), and MLSS concentration (>6.50 g/L). A user-friendly graphic interface was developed to facilitate easier optimization and control. This approach streamlines the determination of optimal conditions for enhancing P removal in the DS-EBPR process.

Rancang Bangun Prototipe Pengisian Air Expansion Tank Berbasis IoT

The shipping industry faces challenges in reducing environmental impact and increasing operational efficiency. Among them are the expansion tanks on ship engines which play an important role in maintaining the pressure and water quality of the engine cooling system, which is still run manually on some ships. This can result in the risk of engine damage due to overheating or unstable pressure. Manual water filling that requires crew supervision can cause operational instability. This research designed a prototype of an automatic water filling system for expansion tanks, using microcontroller-based automation technology and an Internet of things system to make monitoring easier. This system aims to increase efficiency and reduce the risk of engine damage, thereby supporting the sustainability of ship operations in the future. In the trials that have been carried out, this tool is able to operate the expansion tank filling automatically and efficiently. The distance sensor used has high accuracy with a largest error of 1.6%, and an average error of 0.01%. Integration with the Internet of Things system can run well and reliably with 100% success and latency of 0.5 – 1 second. The system's overall success rate is 80%. So the system can be used in real working conditions

The Influence of Pump-Turbine Specific Speed on Hydraulic Transient Processes

The main porpose of this paper is to perform and present at transient process analysis on the influence of different specific speeds (nq) of the three-model pump-turbines that may implemented at the hydropower pump storage plant (HPSP) Bajina Basta, Serbia. The intention is to analyze the operation regimes along the S-shaped characteristic curve, which creates difficulties in calculations during the load-rejection process. These problems are manifested by an unusual increase in water pressure, followed by an increase in machine vibrations, thus threatening the stability of machine operation. The subject of this research is the four-quadrant (4Q) characteristic curves, presented in the form of Suter curves (the head and momentum parameters (Wh and Wm), in dependence of angle (θ)) for different wicket gate openings, of the three pump-turbine models with different specific speeds (nq = 27, nq = 38 and nq = 50). These 4Q characteristics are used as input data for numerical code developed to calculate the simultaneous load rejection of both pump-turbines. The numerical code is based on the method of characteristics and applied to the test case at HPSP. This is especially relevant when dealing with characteristic S-shaped curves that may lead to serious instability in operation during the transient process. The calculation results show changes in the pressure, speed of rotation and discharge of the machine operation regimes, but the important findings are reflected in further application of the results to determine the parametric flow and speed (Q11 and n11) trajectories of the operating points, where the unstable behavior of a pump-turbine operating in turbine mode is presented and periodically the trajectories also pass through the reverse pump zone.

ANALYSIS OF ROUTING PROTOCOLS CHARACTERISTICS IN AD-HOC NETWORK

Background. Wireless ad-hoc networks are becoming increasingly prevalence in remote areas, in extreme environments, even in military operations, and in scenarios where setting up infrastructure networks is not possible. Research of ad-hoc routing protocols problems allows improving the efficiency of their operation in conditions of high variability in packet loss or instability of network operation when the speed of users changes. Objective. The purpose of the paper is analysis of packet loss dependency from a network operation time, study of a user speed influence on a network efficiency, and research of network operation efficiency with different routing protocols. Methods. The method of routing protocols efficiency evaluation is the simulation of their operation in an ad-hoc network on a test data set and research of a network indicators dependency in time under different loads and changing mobility of users. Results. The conducted research demonstrated that user’s mobility at different speeds significantly affects the network operation as a whole. The instability of users' positions leads to a significant increase in route search time and packet transmission time. Among researched GPSR, DSDV, and AODV protocols, the latter proved to be the best because it has the lowest percentage of data loss and the lowest average time of message send and receive operations. Conclusions. The work is dedicated to the actual problem of developing and setting parameters of ad-hoc network. Received research results indicate the need to choose the optimal routing protocol depending on specific application conditions, such as user movement speed and network stability. The proposed solutions can be the first stage of complex processing of packets in the mobile network and justify the choice of AODV protocol as a basis for further improvement.

Power Transformer On-Load Capacity-Regulating Control and Optimization Based on Load Forecasting and Hesitant Fuzzy Control

The operational stability of a power transformer exerts an extremely important impact on the power symmetry, balance, and security of power systems. When the grid load fluctuates greatly, if the load factor of the transformer cannot be maintained within a reasonable range, it leads to increased instability in grid operation. Adjusting the transformer capacity based on load changes is of great significance. The existing control methods for on-load capacity-regulating (OLCR) transformers have low timeliness, and the daily switching frequency of the capacity-regulating switch is not controlled. To ensure the safe and stable operation of transformers, this paper proposes a control method for OLCR transformers based on load prediction and fuzzy control. Firstly, the operating principle of OLCR transformers is analyzed, and a multi-strategy enhanced dung beetle optimizer (MSDBO) combined with a CNN−LSTM model is proposed for load forecasting. On this basis, the daily switching frequency of the capacity-regulating transformer is introduced, and hesitant fuzzy control is used to select the optimal capacity-regulating strategy relying on three factors: loss, economy, and switching frequency. Finally, simulation models are constructed using the MATLAB/SIMULINK platform and simulation analysis is conducted to verify the effectiveness and superiority of the proposed control method. For the three scenarios in this paper, the method reduces daily power loss by 28.5% to 56.3% and daily operating costs by 25.4% to 50.8%. The method used in this paper can sacrifice 3.5% to 9.2% of the loss reduction capability in exchange for reducing the number of switch operations by 28.6% to 57.1%, significantly extending the lifespan of the switches and thereby increasing the operational lifespan of the transformer.

Co-precipitation synthesis of carbonic anhydrase-embedded magnetic zeolitic imidazolate framework-8 nanocomposite enzyme for enzymatic CO2 conversion and utilization in facilitating uranium extraction

Carbonic anhydrase (CA)-mediated carbon conversion and utilization (CCU) technology is recognized as an eco-friendly and cost-effective strategy for carbon reduction. However, the broader application of this technology is significantly constrained by the operational instability and challenging recyclability of free CA. Fortunately, nano-integrated biocatalysis has emerged as an effective solution to these challenges. In this study, we immobilized CA for the first time as a CA-embedded ferriferous oxide-zeolite imidazolium framework-8 (Fe3O4@ZIF-8@CA) nanocomposite enzyme through a one-pot co-precipitation strategy, integrating both the in-situ growth of ZIF-8 around the Fe3O4 core and the immobilization of CA within a single step. Subsequently, this nanocomposite was employed as a nano-integrated biocatalyst to facilitate an innovative CCU pathway. This pathway leverages bicarbonate, produced from the enzymatic hydration of carbon dioxide (CO2), as a substantive uranyl complexing agent to facilitate the neutral leaching of sandstone uranium ore. Systematic characterization techniques, including SEM, TEM, XRD, FTIR, TGA, CLSM, and MPMS, confirmed that Fe3O4@ZIF-8@CA, which possesses a core–shell structure and excellent magnetic responsiveness, has been successfully synthesized. Enzymatic assays revealed that Fe3O4@ZIF-8@CA retains approximately 79% of the activity compared to its free counterparts while demonstrating significantly enhanced thermal and storage stability. The outcome of CO2 hydration conversion for facilitating uranium extraction indicated that, compared with the non-enzymatic reaction group, the bicarbonate yield increased up to 1.5 times, and the uranium extraction efficiency was nearly 10% higher in the Fe3O4@ZIF-8@CA-mediated reaction group. These findings suggest that Fe3O4@ZIF-8@CA possesses excellent catalytic properties for CO2 hydration and can achieve multiplied decarbonization by mediating this innovative CCU pathway. Furthermore, Fe3O4@ZIF-8@CA demonstrated superb reusability and durability, experiencing no significant degradation in its catalytic performance after eight consecutive hydration regeneration cycles. Our research is anticipated to be a viable option for advancing the goals of carbon neutrality and sustainable development.

Analyzing meteorological parameters using Pearson correlation coefficient and implementing machine learning models for solar energy prediction in Kuching, Sarawak

Solar energy is one of the clean renewable energy sources that can offset the rising consumption of fossil fuels. However, the meteorological parameters, such as solar irradiance, ambient and solar module temperatures, relative humidity, etc., constantly change, and so does the solar power generation. Such variations cause instability in the power grid operation due to injecting an unpredicted amount of power. Hence, solar energy prediction models capable of learning from past weather data and predicting future energy generation are highly desired for grid operation and planning. The objective of this study is to determine the suitable meteorological parameters for the solar energy prediction model based on the Pearson correlation coefficient and to implement them in different machine learning models. It is found in this study that five meteorological parameters, namely Air temperature, cloud opacity, global tilted irradiance, relative humidity, and zenith angle, correlate highly with solar energy generation. Later, based on the correlations, four machine-learning models were implemented to predict the solar power for Kuching, Sarawak. The accuracy of the models is measured through standard matrices such as root mean square error, mean square error, mean absolute error, and R-squared value.

Designing of phenothiazine dioxide based donor molecules with improved photovoltaic parameters for efficient perovskite solar cells

Perovskite solar cells are the emerging photovoltaics devices due to their high efficiency because of broad range light absorption and better charge carrier and separation properties. However, in the past few decades their material degradation and instability in the device operation accompanying low power conversion efficiency were the major drawbacks. To address these shortcomings, here we designed five Phenothiazine based novel hole-transporting molecules of d-Pi-A type with improved photovoltaic parameters for efficient perovskite solar devices. Detailed DFT calculation analysis with MPW1PW91 functions and 6–31 G basis set were performed for all molecules. Structural geometrical analysis along with density of states and transition density matrix analysis were extensively performed. Their electronic properties including HOMO and LUMO energies including energy gap, electron affinity, and ionization potential were also explored to elucidate the charge transfer characteristics. The lower values of reorganization in relation to reference molecules show that all designed molecules are better hole-transporters for perovskite building blocks. Lastly the devices photovoltaic parameter calculations for all the designed systems revealed that their Fill factor (FF), VOC and resultant power conversion efficiencies were significantly improved (18.63–22.81 % than its reference counterpart with PCE of 16.7 %) demonstrating their great potential for the future efficient PSCs devices.

Lower boundary capacity estimations of frequency-selective communication channels with PAM-n-signals achievable using resolution time theory

The issue of ensuring high specific capacity of promising wire telecommunication systems is one of the key problems of the last decade. At the same time, despite the existing spectrally efficient modulation methods that are used in existing communication systems, the majority of leading researchers associate further solution of this issue with the transition to the mode of information transmission at a rate "Faster-than-Nyquist" rate (FTN), in which the information receiving about the channel symbol occurs with pronounced intersymbol interference. In turn, this causes difficulties in the practical implementation of the receiver when using optimal signal processing algorithms with nonpolynomial computational complexity, and in the case of suboptimal demodulation methods implementing various types of channel equalization, due to conceptual limitations cannot provide a wide coverage of speeds in this mode. In this regard, the study of an alternative approach to processing signals with multi-position PAM-n-signals on the output of baseband frequency-selective channels (FSC) is relevant. The object of this paper is the study of the possibilities offered by the theory of resolution time for baseband FSC of the, in which information is transmitted using the PAM-n-signal, in the FTN mode. A modified mathematical model of FSC is presented, thanks to which analytical expressions are obtained for estimating the specific capacity in terms of the low bound capacity estimation introduced by Sh. Shamai, expressions for estimating the BER, including the case under the action of destabilizing factors on the symbol synchronization system. Auxiliary capacity estimations and rules for calculating the conditions for achieving them are introduced, convenient for engineering analysis. By means of numerical simulating for the most typical conditions inherent in wired FSC, which are modeled in this work by Chebyshev filters with ripple level of 3 dB and Butterworth filters, it is shown that in the FSN mode with a S/N ratio of no more than 40 dB and instability of the symbol synchronization system operation of 2.5% of the channel symbol duration with a bit error probability of 10–12, it is possible to expect a specific capacity of 5.7–8 bits/Hz*s. It is shown that these results are achieved by using hybrid forms of partial pulses. Recommendations for choosing a partial pulse shape are presented, their main properties are studied from the point of view of their engineering application.

P-702 Centrifugal Pump Damage Analysis Insights and Implications

Centrifugal pumps are widely used in industries for fluid transfer, operating on the rotation of an impeller driven by a prime mover. However, sudden performance drops and operational instability pose significant challenges, impacting overall system efficiency. Predictive maintenance relies on vibration analysis to assess rotating equipment condition, with vibration patterns indicating potential issues such as cavitation and corrosion. Prolonged cavitation leads to erosion of channel wall surfaces, resulting in structural damage. This study aims to address the knowledge gap in understanding the relationship between pump vibration, cavitation, and corrosion. Through comprehensive vibration analysis and examination of pump performance, our research identifies the mechanisms driving pump degradation. The findings highlight the critical role of predictive maintenance in mitigating pump failures and optimizing system performance. Highlights : Vibration analysis crucial for predictive maintenance: Identifying early signs of pump deterioration. Cavitation-induced erosion: Understanding the impact of prolonged cavitation on pump performance. Importance of proactive maintenance: Mitigating pump failures and optimizing system efficiency. Keywords : Centrifugal pumps, Vibration analysis, Cavitation, Corrosion, Predictive maintenance