Applied Sciences

This study provides a computational and experimental assessment of the parametric reliability of friction pairs in brake devices for lifting and transport technology. The computational and experimental method for assessing the parametric reliability of various friction units in lifting and transport equipment, based on operational and experimental research data with their permissible dynamic and thermal load of disc-drum and band-shoe brake devices, was developed to evaluate the influence of coupled dynamic and thermal loads on brake friction pair reliability. The operational parameters of the band-shoe brake, considered as a multi-pair friction system, were classified into four functional groups. The external operational parameters of their materials are determined, and the relationship between dynamic and thermal processes, phenomena and effects is established. A new quantitative indicator, the relative coefficient of parameter (RCP), was introduced to characterize the stochastic variability in friction pair performance and to assess parametric reliability. The meaning of parametric reliability for friction pairs is revealed with the subsequent classification of parameters that fit into the structural diagram of its computational and experimental assessment. Based on reliability conditions, the optimal thickness of the transverse or longitudinal section of the metal friction element has been determined, ensuring it does not exceed the permissible level of thermal stress. Experimental investigations of drilling rig winch brakes demonstrated that the RCP values ranged from 0.008 to 0.051 depending on operating conditions. The proposed probabilistic model enables the optimization of metal friction element dimensions while maintaining thermal stresses below critical levels.

The growing penetration of variable renewable energy (VRE) is increasing the frequency of very low and negative prices, although these events also depend on demand, transmission capacity, price-regime persistence and flexibility resources. This study examines which pre-auction and diagnostic variables are associated with negative day-ahead prices across European bidding zones, and whether these relationships remain stable over time and transferable across markets. More than 736,000 observations from 12 bidding zones in 2019–2025 were analysed, with sample coverage varying by data completeness. A gate-closure-audited Extreme Gradient Boosting (XGBoost) model achieved moderate risk-ranking performance and positive probabilistic skill in 2024–2025. The strongest pre-auction signals were completed-auction price history, calendar features and structural load relationships. Leave-one-market-out validation showed partial and heterogeneous transferability, supporting local calibration. A separate diagnostic layer revealed market-specific, non-linear associations involving VRE forecasts, residual load and cross-border exchange. Negative prices are therefore interpreted as screening signals for market configurations potentially associated with limited surplus absorption, rather than direct evidence of a flexibility shortfall. The framework separates operational pre-auction prediction from later market diagnosis and provides a reproducible basis for local early-warning applications. All SHAP, ALE and scenario results are interpreted as predictive associations and model diagnostics, not as causal effects or direct measures of physical flexibility.

This paper investigates the thermal characteristics of machine tools under the influence of multiple heat sources and proposes an active temperature control method. The study was conducted under steady-state conditions with a constant feed rate of 10 m/min and no cutting load. First, finite element simulations are performed to analyze the thermal characteristics of the machine tool subjected to internal heat sources, yielding the corresponding temperature and deformation fields. Second, within the tested temperature range, the thermal characteristics are examined with respect to the layout of temperature control devices, and the best-performing layout schemes for the bed and column are determined. Subsequently, the thermal error resulting from the coupling effect of multiple temperature control devices is studied, and an active control strategy is proposed to obtain the best layout configuration within the tested range. Finally, experiments are conducted using a multi-loop differential active temperature control system, and the validity of the proposed method is verified through comparison between simulation and experimental results. The findings demonstrate that the proposed active control method effectively reduces thermal deformation in machine tool structures.