Alkali-activated materials are gaining much interest due to their outstanding performance, including their great resistance to chemical corrosion, good thermal characteristics, and ability to valorise industrial waste materials. Reusing waste glasses in creating alkali-activated materials appears to be a viable option for more effective solid waste utilisation and lower-cost products. However, very little research has been conducted on the suitability of waste glass as a prime precursor for alkali activation. This study examines the reuse of seven different types of waste glasses in the creation of geopolymeric and cementitious concretes as sustainable building materials, focusing in particular on how using waste glasses as the raw material in alkali-activated materials affects the durability, microstructures, hydration products, and fresh and hardened properties in comparison with using traditional raw materials. The impacts of several vital parameters, including the employment of a chemical activator, gel formation, post-fabrication curing procedures, and the distribution of source materials, are carefully considered. This review will offer insight into an in-depth understanding of the manufacturing and performance in promising applications of alkali-activated waste glass in light of future uses. The current study aims to provide a contemporary review of the chemical and structural properties of glasses and the state of research on the utilisation of waste glasses in the creation of alkali-activated materials. Full article

The corrosion resistance properties of a new type of environmentally-friendly organic inhibitor containing amino ketone molecules are presented in this paper. To evaluate the prevention effect of the inhibitor on corrosion of reinforcement, the electrochemical characteristics of steels in the simulated concrete pore solution (SPS) were investigated under varied conditions of the relevant parameters, including concentrations of the inhibitor and NaCl, pH value, and temperature. The inhibition efficiency of the material was characterized through electrochemical impedance spectroscopy (EIS), potentiodynamic polarization, and the weight loss of steels. The results reveal a significant improvement in the corrosion resistance of steels with the inhibitor. A maximum resistance value of 89.07% was achieved at an inhibitor concentration of 4%. Moreover, the new organic inhibitor exhibited good corrosion protection capability for steels under different NaCl concentrations. Its inhibition efficiency was determined to be 65.62, 80.06, and 66.30% at NaCl concentrations of 2, 3.5 and 5%, respectively. On the other hand, it was found that an alkaline environment was favorable for an enhanced corrosion prevention effect, and an optimal pH value of 11.3 was observed in this work. Besides, the inhibition efficiencies at different temperatures showed a trend of 25 > 35 > 40 > 20 > 30 °C, with a maximum value of 81.32% at 25 °C. The above results suggest that the new organic material has high potential to be used as an eco-friendly and long-term durable inhibitor for steel corrosion prevention under complex conditions. Full article

The automobile industry relies primarily on spot welding operations, particularly resistance spot welding (RSW). The performance and durability of the resistance spot-welded joints are significantly impacted by the welding quality outputs, such as the shear force, nugget diameter, failure mode, and the hardness of the welded joints. In light of this, the present study sought to determine how the aforementioned welding quality outputs of 0.5 and 1 mm thick austenitic stainless steel AISI 304 were affected by RSW parameters, such as welding current, welding time, pressure, holding time, squeezing time, and pulse welding. In order to guarantee precise evaluation and experimental analysis, it is essential that they are supported by a numerical model using an intelligent model. The primary objective of this research is to develop and enhance an intelligent model employing artificial neural network (ANN) models. This model aims to provide deeper knowledge of how the RSW parameters affect the quality of optimum joint behavior. The proposed neural network (NN) models were executed using different ANN structures with various training and transfer functions based on the feedforward backpropagation approach to find the optimal model. The performance of the ANN models was evaluated in accordance with validation metrics, like the mean squared error (MSE) and correlation coefficient (R²). Assessing the experimental findings revealed the maximum shear force and nugget diameter emerged to be 8.6 kN and 5.4 mm for the case of 1–1 mm, 3.298 kN and 4.1 mm for the case of 0.5–0.5 mm, and 4.031 kN and 4.9 mm for the case of 0.5–1 mm. Based on the results of the Pareto charts generated by the Minitab program, the most important parameter for the 1–1 mm case was the welding current; for the 0.5–0.5 mm case, it was pulse welding; and for the 0.5–1 mm case, it was holding time. When looking at the hardness results, it is clear that the nugget zone is much higher than the heat-affected zone (HZ) and base metal (BM) in all three cases. The ANN models showed that the one-output shear force model gave the best prediction, relating to the highest R and the lowest MSE compared to the one-output nugget diameter model and two-output structure. However, the Levenberg–Marquardt backpropagation (Trainlm) training function with the log sigmoid transfer function recorded the best prediction results of both ANN structures. Full article

Existing research in metasurface design was based on trial-and-error high-intensity iterations and requires deep acoustic expertise from the researcher, which severely hampered the development of the metasurface field. Using deep learning enabled the fast and accurate design of hypersurfaces. Based on this, in this paper, an integrated learning approach was first utilized to construct a model of the forward mapping relationship between the hypersurface physical structure parameters and the acoustic field, which was intended to be used for data enhancement. Then a dual-feature fusion model (DFCNN) based on a convolutional neural network was proposed, in which the first feature was the high-dimensional nonlinear features extracted using a data-driven approach, and the second feature was the physical feature information of the acoustic field mined using the model. A convolutional neural network was used for feature fusion. A genetic algorithm was used for network parameter optimization. Finally, generalization ability verification was performed to prove the validity of the network model. The results showed that 90% of the integrated learning models had an error of less than 3 dB between the real and predicted sound field data, and 93% of the DFCNN models could achieve an error of less than 5 dB in the local sound field intensity. Full article

The manufacturing process for wrought Ti alloys with the hexagonal close-packed (HCP) structure introduces a complicated microstructure with abundant intra- and inter-grain boundaries, which greatly influence performance. In the hexagonal close-packed (HCP) structure, two types of grain boundaries are commonly observed between grains with ~90° misorientation: the basal/prismatic boundary (BPB) and the coherent twin boundary (CTB). The mechanical response of the BPB and CTB under external loading was studied through molecular dynamic simulations of HCP-Ti. The results revealed that CTB undergoes transformation into BPB through the accumulation of twin boundary (TB) steps and subsequent emission of Shockley partial dislocations. When the total mismatch vector is close to the Burgers vector of a Shockley partial dislocation, BPB emits partial dislocations and further grows along the stacking faults. When a pair of CTBs are close to each other, severe boundary distortion occurs, facilitating the emission and absorption of partial dislocations, which further assists the CTB-BPB transformation. The present results thus help to explain the frequent observation of coexisting CTB and BPB in HCP alloys and further contribute to the understanding of their microstructure and property regulation. Full article

A batch of ZnO thin films, pure and doped with molybdenum (up to 2 mol %), were prepared using the spray pyrolysis technique on glass and silicon substrates. The effect of molybdenum concentration on the morphology, structure and optical properties of the films was investigated. X-ray diffraction (XRD) results show a wurtzite polycrystalline crystal structure. The average crystallite size increases from 30 to 80 nm with increasing molybdenum content. Scanning electron microscopy (SEM) images demonstrate a smooth and homogeneous surface with densely spaced nanocrystalline grains. The number of nuclei increases, growing over the entire surface of the substrate with uniform grains, when the molybdenum concentration is increased to 2 mol %. The estimated root mean square (RMS) roughness values for the undoped and doped with 1 mol % and 2 mol % of ZnO thin films, defined by atomic force microscopy (AFM), are 6.12, 23.54 and 23.83 nm, respectively. The increase in Mo concentration contributes to the increase in film transmittance. Full article

The positive effects of deep rolling on fatigue strength—reduced surface roughness, work hardening and compressive residual stress—in the near-surface region are achieved by controlled high plasticisation of the treated material. However, excessive and/or repeated plasticising poses a risk of damage to the machined component. This paper investigates the damage caused by deep rolling of a railway axle. Two sections of the axle are experimentally deep rolled repeatedly at different feed rates until damage is detected. For comparative analysis, these experiments are numerically analysed and the damage is assessed using the strain-based damage calculation. The results are compared and a damage sum of ~120% is evaluated for both tests, thus developing a reliable and conservative assessment method. The single deep rolling treatment at a feed rate of 0.25 mm causes damage of 6.1%, and at a feed rate of 0.5 mm, damage of 4.7%. The developed and experimentally validated evaluation method allows for investigating the limits of applicability of different deep rolling parameters. The influence of the deep rolling force and feed rate and a proposed optimisation with multiple deep rolling with reduced deep rolling forces are investigated. Full article

In the field of lithium-ion batteries, the challenges posed by the low melting point and inadequate wettability of conventional polyolefin separators have increased the focus on ceramic-coated separators. This study introduces a highly efficient and stable boehmite/polydopamine/polyethylene (AlOOH-PDA-PE) separator. It is crafted by covalently attaching functionalized nanosized boehmite (γ-AlOOH) whiskers onto polyethylene (PE) surfaces. The presence of a covalent bond increases the stability at the interface, while amino groups on the surface of the separator enhance the infiltration of the electrolyte and facilitate the diffusion of lithium ions. The PE-PDA-AlOOH separator, when used in lithium-ion batteries, achieves a discharge capacity of 126 mAh g⁻¹ at 5 C and retains 97.1% capacity after 400 cycles, indicating superior cycling stability due to its covalently bonded ceramic surface. Thus, covalent interface modification is a promising strategy to prevent delamination of ceramic coatings in separators. Full article

Stress distribution and its magnitude during loading heavily influence the osseointegration of dental implants. Currently, no high-resolution, three-dimensional method of directly measuring these biomechanical processes in the peri-implant bone is available. The aim of this study was to measure the influence of different implant materials on stress distribution in the peri-implant bone. Using the three-dimensional ARAMIS camera system, surface strain in the peri-implant bone area was compared under simulated masticatory forces of 300 N in axial and non-axial directions for titanium implants and zirconia implants. The investigated titanium implants led to a more homogeneous stress distribution than the investigated zirconia implants. Non-axial forces led to greater surface strain on the peri-implant bone than axial forces. Thus, the implant material, implant system, and direction of force could have a significant influence on biomechanical processes and osseointegration within the peri-implant bone. Full article

In this article, the practical issues connected with guided wave measurement are studied: (1) the influence of gluing of PZT plate actuators (NAC2013) on generated elastic wave propagation, (2) the repeatability of PZT transducers attachment, and (3) the assessment of the possibility of comparing the results of Laser Doppler Vibrometry (LDV) measurement performed on different 2D samples. The consideration of these questions is crucial in the context of the assessment of the possibility of the application of the guided wave phenomenon to structural health-monitoring systems, e.g., in civil engineering. In the examination, laboratory tests on the web of steel I-section specimens were conducted. The size and shape of the specimens were developed in such a way that they were similar to the elements typically used in civil engineering structures. It was proved that the highest amplitude of the generated wave was obtained when the exciters were glued using wax. The repeatability and durability of this connection type were the weakest. Due to this reason, it was not suitable for practical use outside the laboratory. The permanent glue application gave a stable connection between the exciter and the specimen, but the generated signal had the lowest amplitude. In the paper, the new procedure dedicated to objective analysis and comparison of the elastic waves propagating on the surface of different specimens was proposed. In this procedure, the genetic algorithms help with the determination of a new coordinate system, in which the assessment of the quality of wave propagation in different directions is possible. Full article

The application of a two-phase ejector allows for the mixing of liquid and gas and provides effective heat transfer between phases. The aim of the study is a numerical investigation of the performance of a water-driven, condensing two-phase ejector. The research was performed using CFD methods, which can provide an opportunity to analyze this complex phenomenon in 2D or 3D. The 2D axisymmetric model was developed using CFD software Siemens StarCCM+ 2022.1.1. The Reynolds-Averaged Navier–Stokes (RANS) approach with the Realisable k-ε turbulence model was applied. The multiphase flow was calculated using the mixture model. The boiling/condensation model, where the condensation rate is limited by thermal diffusion, was applied to take into account direct contact condensation. Based on the mass balance calculations and developed pressure and steam volume fraction distributions, the ejector performance was analyzed for various boundary conditions. The influence of the suction pressure (range between 0.812 and 0.90) and the steam mass flow rate (range between 10 g/s and 25 g/s) is presented to investigate the steam condensation phenomenon inside the ejector condenser. The provided mixture of inert gas (CO₂) with steam (H₂O) in the ejector condenser was investigated also. The weakening of the steam condensation process by adding CO₂ gas was observed, but it is still possible to achieve effective condensation despite the presence of inert gas. Full article

The demand for different energy goods and services is a fundamental component in a country’s economic structure for development. Understanding it is vital in designing economic policies, such as taxes, that can improve the welfare of the population. A comprehension of the distributional effects of elasticities and the application of them to simulate household responses to price changes, as well as a calculation of the welfare impacts on poor and rich households in Mexico, should inform policy design. This paper uses the Household Income and Expenditure Survey (ENIGH) from 1996 to 2018 to estimate the demand of Mexican households for fuels, specifically electricity, liquefied petroleum gas, and gasoline. A Quasi Ideal Quadratic Demand System (QUAIDS) is employed to analyse the effects of removing energy subsidies and introducing a carbon tax. The results indicate that welfare losses would be regressive concerning electricity price increases, while changes in gasoline prices would be progressive. Redistributing the tax revenues accrued by removing energy subsidies and imposing the carbon tax would have more progressive effects on the economy of Mexican households, with welfare gains of up to 350% for the poorest households in the case of electricity consumption taxes. Full article

In a renewable-energy-penetrated power system (RPPS), inverter-based resources (IBRs) pose serious challenges to power system stability due to their completely different dynamic characteristics compared with conventional generators; thus, it is necessary to study the dynamic interactions between IBRs and power systems. Although many research efforts have been dedicated to this topic from both power electronics and power system researchers, some research from the power electronics field treats the external power system as a voltage source with an impedance, therefore ignoring the dynamic characteristics of a power system, while most of the research from the power system field applies simulation-based methods, for which it is difficult to directly interpret the interaction mechanism of IBRs and external system dynamics. Thus, none of these studies can explore the accurate dynamic interaction mechanism between IBRs and power systems, leading to performance degradation of IBR-integrated power systems. Our study takes into account the dynamic characteristics of both IBRs and the external power system, resulting in the development of a new open-loop transfer function for RPPSs. Based on this formulation, it is observed that under certain operating conditions, the dynamic interactions between the inverter and the power system help enhance IBR-penetrated power system stability compared with the case for which the external power system is controlled as a voltage source. The study also reveals how the inverter (phase-locked loop, control parameters, etc.), external power system (network strength) and penetration ratio in an IBR-penetrated power system affect the dynamic interactions between IBRs and the external power system using the proposed quantified interaction indices. Full article

As offline control photovoltaic (PV) plants are not equipped with online communication and remote control systems, they cannot adjust their power in real-time. Therefore, in a distribution network saturated with offline control PVs, the distribution system operator (DSO) should schedule the distributed energy resources (DERs) considering the uncertainty of renewable energy to prevent curtailment due to overvoltage. This paper presents a day-ahead network operation strategy using a mobile energy storage system (MESS) and offline control PVs to minimize power curtailment. The MESS model efficiently considers the transportation time and power loss of the MESS, and models various operating modes, such as the charging, discharging, idle, and moving modes. The optimization problem is formulated based on mixed-integer linear programming (MILP) considering the spatial and temporal operation constraints of MESSs and is performed using chanced constrained optimal power flow (CC-OPF). The upper limits for offline control PVs are set based on the probabilistic approach, thus mitigating overvoltage due to forecasting errors. The proposed operation strategy was tested in the IEEE 33-node distribution system coupled with a 15-node transportation system. The test results show the effectiveness of the proposed method for minimizing curtailment in offline control PVs. Full article

The work is devoted to the development of a method for neural network approximation of helicopter turboshaft engine parameters, which is the basis for researching engine energy characteristics to improve efficiency, reliability, and flight safety. It is proposed to use a three-layer direct propagation neural network with linear neurons in the output layer for training in which the scale conjugate gradient algorithm is modified by introducing a moment coefficient into the analytical expression. This modification helps in calculating new model parameters to avoid falling into a local minimum. The dependence of the energy released during helicopter turboshaft engine compressor rotation on the gas-generator rotor r.p.m. was obtained. This enables the determination of the optimal gas-generator rotor r.p.m. region for a specific type of helicopter turboshaft engine. The optimal ratio of energy consumption and compressor operating efficiency is achieved, thereby ensuring helicopter turboshaft engines’ optimal performance and reliability. Experimental data support the high efficiency of using a three-layer feed-forward neural network with linear neurons in the output layer, trained using a modified scale conjugate gradient algorithm, for approximating parameters of helicopter turboshaft engines compared to the analogues. Specifically, this method better predicts the relations between the energy release during compressor rotation and gas-generator rotor r.p.m. The efficiency coefficient of the proposed method was 0.994, which exceeded that of the closest analogue (0.914) by 1.09 times. Full article

In Poland and other countries in Central Europe, residential buildings from the second half of the 20th century dominate, which have recently undergone deep thermomodernisation. Research on the retrofitting of residential buildings has focused mainly on energy efficiency, with only a few studies on indoor air quality. The aim of this study was to present a comparative analysis of the impact of five ventilation scenarios (three natural and two mechanical) on CO₂ concentration and energy demand for heating and ventilation in residential spaces of a multi-family building located in Poland. The analyses were based on the results of building performance co-simulation using the EnergyPlus and CONTAM programs carried out under dynamic conditions with a 5 min time step for the entire heating season. The calculations took into account the instantaneous occupancy variability of twenty apartments. In the buildings equipped with new tight windows, the natural ventilation system provided extremely low air exchange (on average 0.1 h⁻¹) and poor indoor air quality (average CO₂ concentration at the level of 2500 ppm). Opening windows to ventilate the rooms generated a multiple increase (up to 8 times) in heating demand during these periods, but average CO₂ concentration was on the level of 930 ppm. The use of mechanical ventilation was profitable both in terms of energy savings (at the level of 50%) and improvement in the indoor air. Full article

Carbon geological storage (CGS) is one of the key processes in carbon capture and storage (CCS) technologies, which are used to reduce CO₂ emissions and achieve carbon-neutrality and net-zero emissions in developing countries. In Thailand, the Mae Moh basin is a potential site for implementing CGS due to the presence of a structural trap that can seal the CO₂ storage formation. However, the cost of CGS projects needs to be subsidized by selling carbon credits in order to reach the project breakeven. Therefore, this paper estimates the economic components of a CGS project in the Mae Moh basin by designing the well completion and operating parameters for CO₂ injection. The capital costs and operating costs of the process components were calculated, and the minimum carbon credit cost required to cover the total costs of the CGS project was determined. The results indicate that the designed system proposes an operating gas injection rate of 1.454 MMscf/day, which is equivalent to 29,530 tCO₂e per year per well. Additionally, the minimum carbon credit cost was estimated to be USD 70.77 per tCO₂e in order to achieve breakeven for the best case CGS project, which was found to be much higher than the current market price of carbon credit in Thailand, at around USD 3.5 per tCO₂e. To enhance the economic prospects of this area, it is imperative to promote a policy of improving the cost of carbon credit for CGS projects in Thailand. Full article

Heavy metals in flue gas desulfurization (FGD) gypsum from coal-fired power plants are at risk of releaching during the processes of stockpiling and resource utilization. In this study, the effects of organosulfur chelators dithiocarbamate (DTC) and trisodium trithiocyanate-15 (TMT-15) on the solidification characteristics of heavy metals in desulphurized gypsum under different mass fractions, pH values, water contents and reaction times were investigated. The chemical composition and morphology were analyzed by inductively coupled plasma atomic emission spectrometer (ICP-AES) and scanning electron microscope (SEM). The experiments showed that both DTC and TMT-15 were effective at stabilizing the heavy metals in the FGD gypsum, with more than a 50% curing effect for all the heavy metals except Pb. DTC showed a better stabilization for Pb, Hg, Cu, Zn, and Cr, and TMT-15 showed a better curing effect for Cd. The solidified gypsum had good heavy metal stability in low-water-content environments. Increasing the mass fraction, reaction time, and pH decreased the heavy metal leaching, and the mass fraction had the greatest effect on the total heavy metal leaching concentration, followed by the reaction time and pH value. Full article

Spent coffee grounds (SCGs) constitute the main solid residue of the coffee brewing process. SCGs are generated in significant amounts daily, worldwide. The effective management of this waste through biological processes is still an unresolved problem. In this study, the application of hydrodynamic cavitation (HC) as a pre-treatment method for improving the biodegradability of SCGs suspended in municipal wastewater was proposed. An orifice plate with a conical concentric hole having inlet/outlet diameter of 3/10 mm was applied as the cavitation inducer. Three inlet pressures were chosen: 3, 5 and 7 bar. The effects in time intervals of 0, 5, 10, 20, 30 and 45 min were evaluated. The application of HC led to enhanced biodegradability for each case. The results of multi-criteria decision indicated that the most efficient combination in terms of biodegradability and energy usage was obtained at the pressure of 5 bar and duration of 20 or 30 min, depending on the adopted weights. The improvements of DOC/TOC (dissolved organic carbon/total organic carbon) ratio were 57% and 71%, as compared to the untreated samples. The release of caffeine was found at pressures of 5 and 7 bar. However, at 5 bar, this effect was noticed for the longest times, 30 and 45 min, respectively. Full article

Since the beginning of the 20th century, many studies have focused on the possibility of considering the sky as a body characterized by an apparent temperature, and several correlations to quantify the apparent sky temperature have been proposed. However, the different models were obtained for specific meteorological conditions and through measurements at specific sites. The available models do not cover all locations in the world, although the evaluation of the sky temperature is fundamental for estimating the net radiative heat transfer between surfaces and the sky. Here, experimental data logged from a regional micrometeorological network (in Italy, within the Lazio region) were processed and used to identify an empirical model for the estimation of the sky temperature in the Mediterranean area. Data relating to atmospheric infrared radiation were used to compute the sky temperature, aiming at identifying a direct correlation with the ambient temperature. Climatic data acquired during 2022 were processed. The proposed correlations were compared with other models available in the literature, including the standard ISO 13790. This study proposes an annual-based direct correlation in its initial phase, demonstrating a superior fit to the measured data compared to well-known direct empirical models from the literature. Subsequently, quarterly-based correlations are introduced further in a secondary phase of the work to improve the model’s adaptation to experimental observations. The results reveal that quarterly-based correlations improve goodness-of-fit indexes compared to annual-based and well-known direct empirical correlations. Finally, a detached building was modeled via a dynamic code to highlight the influence of different correlations on annual energy needs. Full article

Numerical calculations of the innovative flue gas recirculation (FGR) system through an inactive coal pulverizer for a 40% load of the OP 650 boiler at the Jaworzno III Power Plant were carried out. The research was conducted to determine the effect of FGR on the formation of NO_x, CO emissions, and low-NO_x waterwall corrosion. Using numerical modelling, the influence of the place of injection of recirculated flue gas on the formation of NO_x was also investigated. The tests were carried out based on data from the boiler monitoring system and calculation results using a 0-dimensional model. Modelling of the FGR was performed for five variants. FGR equalized the temperature in the furnace, eliminating temperature peaks in the burner belt. Moreover, FGR did not increase the CO content in the flue gas and reduced the O₂ concentration in the area zone of pulverized coal combustion. For FGR systems, the emission of NO_x below 200 mg/m³_n for 6% O₂ in dry flue gas was kept. This proves that the recirculation helps to meet the BAT (best available techniques) requirements for NO_x emissions. It has also been shown that FGR does not pose a risk of low-NO_x corrosion in the next 20 years. Full article

The efficient design of Permanent Magnet Synchronous Motors (PMSMs) is crucial for their operational performance. A key design parameter, cogging torque, is significantly influenced by various structural parameters of the motor, complicating the optimization of motor structures. This paper proposes an optimization method for PMSM structures based on heuristic optimization algorithms, named the Permanent Magnet Synchronous Motor Self-Optimization Lift Algorithm (PMSM-SLA). Initially, a dataset capturing the efficiency of motors under various structural parameter scenarios is created using finite element simulation methods. Building on this dataset, a batch optimization solution aimed at PMSM structure optimization was introduced to identify the set of structural parameters that maximize motor efficiency. The approach presented in this study enhances the efficiency of optimizing PMSM structures, overcoming the limitations of traditional trial-and-error methods and supporting the industrial application of PMSM structural design. Full article