Saint Petersburg Mining University (Russian: Санкт-Петербургский горный университет), is Russia's oldest technical university, and one of the oldest technical colleges in Europe. It was founded on October 21, 1773, by Empress Catherine the Great, who realised an idea proposed by Peter the Great and Mikhail Lomonosov for training engineers for the mining and metals industries. Having a strong engineering profession was seen by many Russian rulers as a vital means of maintaining Russia's status as a great power. As historian Alfred J. Rieber wrote, "The marriage of technology and central state power had a natural attraction for Peter the Great and his successors, particularly Paul I, Alexander I and Nicholas I". All three had had a military education and seen the achievements of the engineers of revolutionary and imperial France, who had reconstructed the great highways, unified the waterways and erected buildings throughout Europe in a more lasting tribute to the French than all of Napoleon's victories.Though located in St. Petersburg, the university is on a federal rather than local level, and has partnerships with global oil, gas and mining companies and governments. Its museum is home to one of the world's finest collections of gem and mineral samples and the university building is a Neoclassical masterpiece by Andrey Voronikhin.
Many companies in the mining industry include decarbonization of production among their key strategic goals as part of their internal sustainability strategy. This need is driven by a number of factors: stricter regulation in the area of carbon footprint (introduction of carbon taxes, emissions quotas, reporting requirements); sustained growth in demand for electricity and rising market prices; economic feasibility—the need to optimize operating costs and improve energy efficiency. This study provides a comprehensive technical and economic justification for implementing a hybrid power supply system—combining a solar power plant (SPP) and a gas engine power plant (GPP)—at Solidcore Resources’ Varvarinsky hub in Kazakhstan. The methodology includes modeling the energy balance of the real asset (156.9 GWh of annual energy consumption), calculating the output of a 22.6 MW SPP based on local GHI/PR/η parameters, forming and determining the adaptability coefficient Kₐ (proportion of PV in total monthly electricity generation), conducting an economic assessment (NPV, payback period, sensitivity), and inventorying CO2 emissions under Scope 1–2. The SPP provides approximately 41.3 GWh of electricity generation per year, with an average annual Ka = 0.263; the 40 MW installed capacity of the gas piston power plant covers the residual demand, forming a stable daily and seasonal balance. The project demonstrates a positive NPV (After Tax) = USD 23.65 million with an estimated payback period of 10 years, while the cost of energy in extraction and processing is reduced by almost three times, and the total reduction in CO2 emissions will be 51%. Thus, hybridization of energy supply systems is a practical compromise between reliability and decarbonization. Determining the adaptability coefficient Ka allows the flexibility of the system to be taken into account, shows how effectively the new energy system uses renewable energy sources, and can be used to optimize the operation of the energy system to achieve the company’s internal sustainable development goals.
The quantity of waste produced by the food industry is on the rise annually. Among the most prevalent types of waste classified as Class I hazardous substances, posing a significant threat to the environment, is used cooking oils, necessitating proper disposal methods. Concurrently, the combustion of petroleum resources generates substantial greenhouse gas emissions, acting as a primary driver of global warming and associated climatic disruptions. To address the issues mentioned above, food industry waste has been processed into biodiesel fuel. The production involved transformation of sunflower and waste cooking oils with ethanol, with the reaction duration incrementally adjusted between 2 and 7 h in 30 min intervals to determine its effect on biofuel yield. The analysis revealed a pronounced disparity in ester yield between the feedstocks, with the primary component derived from sunflower oil exhibiting a yield 5,81% lower than that obtained from waste oil. For the waste oil substrate, the total ester yield varied from 77.45% (at a 3 h reaction duration) to a maximum of 95.49% (observed at 6.5 h). The temporal evolution of ester release demonstrated a complex, non-monotonic trend, characterized by periodic oscillations superimposed upon a parabolic profile. The confidence interval for the temporal yield data was determined to be ±10%.
Non-intrusive load monitoring (NILM) can provide actionable feedback for demand response (DR) when direct measurements of device states are unavailable. We propose a reproducible, engineering-oriented pipeline for detecting ON/OFF states of end-use load groups from an aggregated active power time series. The method uses robust hysteresis-based labeling with adaptive thresholds derived from the median and median absolute deviation, followed by compact feature engineering restricted to global active power (GAP). After removing collinear features (|r| > 0.98), permutation importance is used to retain informative predictors. Probabilistic binary classifiers (LGBM, Histogram-based Gradient Boosting, XGBoost, and CatBoost) are trained for each target load, and the decision threshold is optimized via F-beta to balance missed events and false alarms. A post-processing stage stabilizes predictions by smoothing probabilities and suppressing spurious triggers. Model quality is assessed with both sample-wise metrics and event-based metrics that credit the correct detection of switching intervals within a time tolerance. Experiments on the open "Individual Household Electric Power Consumption" dataset (1-min resolution, 2007-2010) demonstrate that lightweight gradient boosting models, particularly LGBM, deliver reliable and interpretable state estimates suitable for practical DR integration and edge deployment.
The study develops and implements a methodology for prioritizing power units (PUs) of captive power plants (CPPs) to support the development of maintenance and repair (M&R) programs considering their actual technical condition (TC) and reliability indicators. The proposed approach is based on the joint assessment of the technical condition index (TCI), the consumed technical resource (CTR), and the risk level (RL) of the PUs. To describe the statistical patterns of failures, a two-parameter Weibull distribution is applied, while the temporal change in the TCI is approximated by a linear relationship that accounts for differences between actual and nominal operating conditions. The CTR is defined as an integral characteristic reflecting the deviation between the actual and nominal TCI degradation functions. The RL is evaluated as a function of the probability of failure and the consequences of PU failure. Based on these individual indicators, an integrated priority index is formed to provide an unambiguous ranking of PUs. The methodology was implemented using actual operational data from a fleet of PUs of an energy company. The results demonstrate that using the TCI alone does not fully reflect the actual TC of the PUs, whereas the combined consideration of TC, CTR, and RL enables a more justified formation of M&R programs. The practical significance of the study lies in the possibility of applying the developed methodology for reliability management of PUs at CPPs under resource constraints.
The influence of iron on the flotation activity of ethoxylated phosphoric acid esters with different structures and sodium oleate in the enrichment of phosphate ores has been investigated. It was found that the presence of iron reduces the contact angle of apatite wetting by 15.26-27.42 degrees. The greatest reduction in hydrophobicity (Delta theta = 27.42 degrees) is observed for aromatic ethoxyphosphate Ar-EP-6. Aliphatic ethoxylates (EP-6 and EP-10) exhibit the least sensitivity to iron, maintaining high flotation activity (apatite recovery degree up to 70 %). Flotation test results show that aliphatic ethoxyphosphates have higher flotation activity compared to their aromatic analogs and traditional collectors, which can be explained by the specific structure of molecular aggregates in the adsorption layer. At a concentration of Fe3 + = 5.31 x 10-4 M in the aqueous phase suspension, apatite flotation is almost completely suppressed for all collectors. The obtained data can be used to optimize reagent regimes during the processing of complex phosphate ores.
