In the current context of sustainability management and energy insecurity, amplified by the military instability determined by the war between Russia and Ukraine, and the increasingly frequent occurrence of a series of plausible scenarios for disasters or energy blackouts worldwide, this work is a real and applicable model for regional states that would like to critically analyze the situation of their energy security through identifying all the plausible risk scenarios targeting the energy critical infrastructures. The study has identified and assessed two of the most plausible risk scenarios (a natural disaster and a terrorist attack) in the case of a strategic power substation of 220 kV, 400 kV, or 750 kV undergoing a blackout effect. After having assessed the risks, the safety strategy for Romania’s national power system has been elaborated together with the safety strategy for the European Power system-ENTSO-E (European Network of Transmission System Operators for Electricity). The results of the study match other specialized works from different European countries and might represent a model for other types of energy safety risk assessments and for other types of critical infrastructures that are vital for the modern European society and for sustainability management.

Because of its specific nature, mining activity causes numerous negative impacts on the environment, both during the exploitation phase and after it has ended. An important source of income in the Jiu Valley is represented by the Lupeni Mining Exploitation. Like any mining activity, coal exploitation causes various negative effects on the environment. The subsidence phenomenon represents a significant issue associated with coal mining in the Jiu Valley. Underground extraction of mineral deposits induces displacement of the overburden strata. Such displacements result in ground subsidence and modifications of the surface topography. The larger the voids created following the exploitation of useful mineral deposits, the more they affect the surface of the land above the exploitation through sinking, displacement, deformation, and even cracks. Secondary deformations refer to post-mining surface movements induced by delayed rock mass adjustment, manifesting as ground collapse, localized subsoil failure, or uplift driven by groundwater rebound after drainage cessation. In this paper, we aim to study the subsidence phenomenon produced by coal mining at the Lupeni Mining Exploitation using the COMSOL simulation software and applying the Barcelona Basic Model (BBM) and Modified Cam-Clay (MCC) models. Following the simulation, the behavior of the rocks could be observed in order to improve prediction accuracy to support sustainable land management in post-mining areas.

In order to have a real picture of the exergetic performances of the compressors and highlight the contribution of each loss to the exergetic yield, we performed a series of experimental determinations “in site”, then based on a calculation model, we drew up the real hourly exergetic balances related to the KAESER compressor ESD 375. Based on the presented breviary, we approached a case study, used to justify energetically the feasibility of replacing old compressors, with many hours of operation, with compressors equipped with heat recuperators and compressed air dryers. In this way, the following were determined: the Carnot factor, the amount of heat given off, the exergy harnessed, the useful heat, the exergy supplied by the network, the increase in the efficiency of energy use, the annual operating time of the compressor, the annual energy economy, the production of GHG. In addition, the performed calculations have the role of justifying the installation of heat exchangers on compressors in pneumatic systems. In this work, the calculation breviary is presented on the basis of which the numerical calculation programs were made and then the effects of heat recovery in the two helical compressors with oil injection were quantified.

Road traffic injuries remain a central challenge for sustainable transport, public health, and mobility governance. The task of monitoring these injuries requires indicators that jointly capture harm severity, road and environmental context, and patterns of vehicle involvement at scale. Using harmonised English-language Romanian police crash exports (2023–2025), we build 92,790 records with 36 variables and estimate two complementary k-means typologies: a severity partition based on the fatality, injury, and vehicle-count fields (a register proxy for involvement, not vehicle-type attributes) and a context partition based on the road, environment, mechanism, and cause fields with one-hot encoding and TruncatedSVD. Reported tables and figures reproduce the archived MiniBatch pipeline for replication; for context, full-batch k-means clustering on the same embedding is the recommended default when cross-year prevalence stability is required (train–test TVD 0.039 versus 0.569 under MiniBatch). We report silhouette-guided choices ($k=6$ severity, $k=4$ context), cross-seed stability, feature ablations, and a 2023–2024 versus 2025 prevalence comparison. A Pearson ${\chi }^2$ test on severity × context labels reveals strong statistical significance, yet Cramér’s V remains small—statistical association with limited practical coupling, consistent with complementary rather than redundant partitions. Limitations include police-reported injury counts; a coarse vehicle proxy; weak context geometry; and large MiniBatch context drift, which binds inference to within-year descriptive profiling unless analysts refit the model, add version labels, or adopt full-batch context clustering. The contribution is an integrated, reproducible profiling and governance workflow for dashboards and follow-on modelling—not a fixed multi-year cluster taxonomy.