Lublin University of Technology

With the growing share of distributed energy sources and energy storage, the problem of high-voltage line overloads is becoming one of the key challenges of modern power systems. This paper proposes a method to eliminate transmission line overloads by coordinating power changes among selected generation units, loads, and energy storage units, with network reconfiguration as needed. A key element of the proposed approach is identifying the controllable elements most strongly associated with overload patterns in post-contingency scenarios. These elements were identified using statistical correlation coefficients describing the relationship between line loading levels and the power generated, consumed, or stored at individual buses. Correlation analysis was used to determine a subset of candidate elements most relevant to the observed overload patterns, thereby reducing the dimension of the control problem. The proposed approach enables effective overload reduction while simultaneously reducing the problem's dimensionality. The results indicate that it can be a useful tool supporting network management under conditions of high generation and load variability.

A troubling trend has emerged in recent literature on points of zero charge (PZC). Only a minority of newly published studies report reliable PZC values obtained from properly designed experiments, whereas many present apparent PZC derived from flawed methodologies. These erroneous values are widely cited, increasing the likelihood that readers - including AI-based systems - encounter incorrect data rather than rigorously determined results. This highlights the need for critical reviews that compile only well-established PZC values. This review provides updated isoelectric point (IEP) data from properly conducted electrokinetic or electroacoustic measurements and PZC values of metal oxides determined as common intersection points of surface charge versus pH curves measured at different ionic strengths. The compilation includes studies from 2023 to 2025 as well as earlier overlooked papers, and compares recent data with previously established values. Most new results concern well-studied materials such as alumina, silica, titania, and iron (hydr)oxides, while reliable data for less-documented materials remain limited.

X-ray diffraction and Mössbauer spectroscopy were applied to monitor the process of alloy formation during synthesis of Co2FeAl compound via mechanical alloying method. After 20 h of milling, the bcc solid solution was obtained, with an average crystallite size 23 nm, mean level of lattice strains 0.75

This paper presents a non-invasive diagnostic approach for Electric Parking Brake (EPB) modules based on recurrence quantification analysis (RQA) of piezoelectric vibration data. Vibration signals were collected from sensors mounted on the motor, planetary gearbox, and pinion under five predefined fault conditions: missing gear in the lower row of the planetary gearbox, missing gear in the upper row, tooth damage in the planetary gear, partially cut timing belt, and incorrect gear installation. Each failure mode was tested repeatedly to obtain statistically reliable datasets for non-linear time-series and recurrence-based analysis. The following RQA quantificators were computed: Determinism (DET), Laminarity (LAM), maximal diagonal line length ( L_max ), and mean diagonal line length (L) were calculated to characterize the underlying dynamic behavior. Additional recurrence quantificators describing laminar states—Trapping Time (TT) and maximal vertical line length ( V_max ) were used to capture transient stability and synchronization effects. The results show that these RQA quantificators are highly sensitive to mechanical faults, especially within the gearbox, enabling effective fault localization and differentiation between failure types. The missing-gear condition resulted in increased values of DET, LAM, and L_max , reflecting more regular and structured recurrence patterns, while incorrect pinion installation produced more irregular and weakly correlated responses. Statistical analyses confirmed that the observed differences between fault conditions were significant, not only within experimental groups, but also between individual RQA quantificators, highlighting their diagnostic discriminative capability. The proposed method allows efficient fault detection without disassembling the EPB unit, thus reducing remanufacturing costs and downtime. Overall, the study demonstrates that recurrence-based diagnostics provide a robust and interpretable framework for real-time condition monitoring and fault prediction.

The hot deformation behavior and dynamic recrystallization (DRX) mechanisms of as-cast NiCr19Fe19Nb5 alloy were investigated via isothermal compression tests using a Gleeble-3500 simulator at 950-1150 degrees C and strain rates of 0.01-10 s-1. Flow stress data were corrected for friction and adiabatic heating effects to develop a strain-compensated Arrhenius constitutive model, yielding an activation energy of 528.6 kJ/mol. Processing maps based on the dynamic material model identified optimal hot-working domains at 950-1020 degrees C/0.01 s-1 and 1020-1150 degrees C/0.01-0.1 s-1. Microstructural characterization via EBSD and TEM revealed that elevated temperatures and lower strain rates promote the transition of low-angle to high-angle grain boundaries. Discontinuous DRX (DDRX) was identified as the dominant softening mechanism, characterized by necklace structures and grain boundary bulging. Additionally, subgrain-rotation-induced continuous DRX (CDRX) and twin-induced DRX (TDRX) were observed as auxiliary mechanisms, with TDRX providing supplementary nucleation sites at twin boundaries during early deformation stages. These findings deepen the understanding of deformation mechanisms in NiCr19Fe19Nb5 alloy and offer valuable guidance for optimizing hot-working processes and achieving high-quality manufacturing of Ni-based superalloy components.