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The paper investigates experimentally the influence of infill density, infill pattern, layer height, wall number, printing orientation, and material color on the impact strength of 3D-printed PLA (polylactic acid) samples by using the Charpy test method. The used printing method is FDM (Fused Deposition Modeling) performed on a desktop printer. For each parameter changed in the study, five separate unnotched specimens were produced and tested, and the average impact strength value was taken into account. The filament rolls went through a drying process before printing and were then stored in a low-humidity environment filled with desiccant in order to minimize the effect of absorbed humidity in the filament during the experiments. The conditioning and testing of samples were performed according to the EN ISO 179-1 standard. Dimensional accuracy, print times, and filament consumption were also estimated in the study. The results revealed that the infill density, infill pattern, and wall number have a larger influence on the impact energy absorbed by the samples in comparison to the layer height, printing orientation, and the PLA filament color. The best optimization of the studied mechanical property was obtained by increasing the infill percentage and the number of walls. Applying different PLA colors has a slight effect on the impact strength, yet it should be taken into consideration when designing 3D-printed products that are intended to withstand impact. Moreover, it was found out that the studied parameters have an insignificant effect on the dimensional accuracy of the produced samples.
This paper presents an evaluation of the performance characteristics of lawnmowers powered by gasoline engines and electric motors. Particular emphasis is placed on usability, reduced maintenance requirements, noise emission levels, and environmental sustainability. A custom electric lawnmower was constructed for the purposes of this study, involving the selection and integration of suitable motors, batteries, and auxiliary components. A comparative analysis was subsequently conducted between the conventional gasoline-powered lawnmower and the electrically powered prototype. Measurements of operational duration and efficiency indicated notable improvements in mowing time and maintenance-related costs. The findings underscore the potential advantages of transitioning to electric propulsion technologies, both from the perspective of sustainable development and environmental responsibility, as well as in terms of operational convenience.
Recently, interest has grown in using alternatives to cement and aggregates to improve concrete and reduce its environmental impact. This study explores the use of cherry pit waste (CPW) as a partial substitute for coarse aggregates in self-compacting concrete (SCC) at varying rates (0–25%). Rheological, compressive strength, and ultrasonic pulse velocity tests were conducted. The results showed that CPWs reduce flowability but increase cohesion. The 5% CPW mix achieved the highest compressive strength. All the mixes remained acceptable, with classifications from SF3 to SF1. Due to CPWs’ lower density, both wet and dry weights decreased, making this a viable lightweight concrete option.
The current space law does not clarify the asteroid mining problem enough. This paper presents a techno-economic analysis to show how legal certainty impacts the profitability and overall investment in asteroid mining projects. Our analysis reveals that clear legal frameworks reduce perceived investment risk significantly. We have introduced a financial model that demonstrates how different legal scenarios, specifically those offering clear frameworks and benefit-sharing mechanisms, lead to positive Net Present Values. We thereby encourage fair resource distribution and opportunities within a regulated system, as an environment with high legal uncertainty results in negative Net Present Values, and show significant financial risk.
This paper explores the evolution of royalty payments from the extraction of reserved mineral resources in the Czech Republic between 1992 and 2025, with a particular focus on their allocation for the reclamation of environmentally affected areas. It presents the legislative framework governing these payments, including Acts No. 44/1988 Coll., No. 61/1988 Coll., and No. 280/2009 Coll., as well as Government Regulation No. 354/2023 Coll., which collectively define the obligations of mining companies regarding royalty payments. The study addresses the adjustment of royalty rates in response to current economic conditions to ensure sustainable financing of environmental projects. It also emphasizes the importance of continuous evaluation of the regulatory system to maintain a balance between the economic capacity of extractive industries and the protection of the environment.
This paper examines the application of Artificial Intelligence (AI) to protect satellite communication networks, focusing on the identification and prevention of cyber threats. With the rapid development of the commercial space sector, the importance of effective cyber defense has grown due to the increasing dependence of global infrastructure on satellite technologies. The study applies a structured comparative analysis of AI methods across three main satellite architectures: geostationary (GEO), low Earth orbit (LEO), and hybrid systems. The methodology is based on guiding research question and evaluates representative AI algorithms in the context of specific threat scenarios, including jamming, spoofing, DDoS attacks, and signal interception. Real-world cases such as the KA-SAT AcidRain attack and reported Starlink jamming in Ukraine, as well as experimental demonstrations of RL-based anti-jamming and GNN/DQN routing, are used to provide evidence of practical applicability. The results highlight both the potential and limitations of AI solutions, showing measurable improvements in detection accuracy, throughput, latency reduction, and resilience under interference. Architectural approaches for integrating AI into satellite security are presented, and their effectiveness, trade-offs, and deployment feasibility are discussed.
Progressive collapse is a critical structural phenomenon where local damage triggers a chain reaction and potentially leads to disproportionate failure of the entire system. In this study, the progressive collapse behavior of multi-story reinforced concrete (RC) structures is investigated using numerical analysis methods. This situation poses a serious danger, especially for high-risk types of structures. In the study, the effect on the collapse tendency is evaluated by considering different structural models. Numerical analyses are performed using a nonlinear finite element method. This study offers a general exploration of the progressive collapse behavior of multi-story RC frames, focusing on robustness evaluation under various structural scenarios. The aim of this study is to improve the understanding of structural responses and to support the development of safer, more durable design strategies.
This paper investigates the influence of design parameters on fluid leakage in axial piston pumps. Particular emphasis is placed on the analysis of operating clearances, sealing surfaces, and geometric relationships that affect volumetric efficiency and system reliability. Through a systematic review of 32 relevant sources, key components contributing to both internal and external leakage are identified, along with approaches for their optimization through material selection, microgeometry, tolerances, and thermodynamic conditions. Modern methods for diagnostics and leakage prediction are also considered, including the application of artificial intelligence and numerical simulations. The findings of this review may serve as a basis for improving the design and maintenance of axial pumps, with the aim of increasing efficiency and reducing losses.
The present paper investigates the dynamic behavior of an unbalanced rotor mounted in a balancing machine. Differential equations of motion are derived without linearization using Lagrange equations of the second kind to determine the nonlinear nature of the system. This study proposes a method for using differential equations in balancing to determine important parameters, such as the coordinates of the center of mass and the products of inertia of the rotor. An analysis of the interactions between the periodicities of the individual terms in the differential equations is carried out in order to eliminate terms with difficult-to-determine moments of inertia.
This study investigates the flow around Kline-Fogleman (KF) airfoils using Particle Image Velocimetry (PIV) in a wind tunnel at Reynolds number Re = 6.8 × 104. Three configurations are tested: a clean NACA 0015 airfoil and two modified versions with a step on either the pressure or suction side. Velocity fields are used to calculate lift via the Kutta-Joukowski theorem. Results show that the KF airfoil with a step on the pressure side achieves a 14.8% higher maximum lift coefficient and delayed stall. In contrast, placing the step on the suction side reduces maximum lift by 4%. The KF airfoil with pressure-side step shows potential for low Reynolds number applications where higher lift and larger stall angles are required.
Artificial intelligence is increasingly being applied not only in the economy but also across various social sectors. As a result, research into maintenance activities is justified, particularly in the context of complex corporate systems. These systems often involve significant investments in fixed assets and advanced technologies, which implies high maintenance costs. Therefore, maintenance should be considered both in the formulation and implementation of business strategies. The research hypothesis proposes that the application of artificial intelligence can enhance business and production processes, particularly by optimizing maintenance and reducing costs. Accordingly, maintenance should be integrated into the broader business strategy as a key implementation process. To ensure effective application, all available AI capabilities should be thoroughly explored. Through analysis and discussion, the advantages of using artificial intelligence in maintenance are to be identified, ultimately leading to the validation of the hypothesis. Given the rapid development of information technology especially, this topic offers significant potential for further research.
The distributor valve is one of the most important components in the pneumatic braking system of trains. It performs the functions of filling and releasing the brake cylinder. The distributor valve most widely used on Bulgarian railways operates in two positions, respectively, in “freight train” mode (G) and in “passenger train mode” (P). The difference between them is determined by the different times for filling and emptying the brake cylinder. These times affect the moment of engagement of the braking system of each wagon in the train composition. This has a significant impact on the longitudinal forces obtained in the couplers. This paper is dedicated to the analysis of the influence of the distributor valve position on the longitudinal forces. A simulation study of the longitudinal behavior of a train set was carried out in Simulink®, which consists of a locomotive and 43 freight wagons attached to it, with 80 t gross mass of each wagon. The railway cars are linked by elastic elements with nonlinear characteristics. The results represent the distribution of longitudinal forces in time. They are used for the investigation of the longitudinal dynamics of the train, with the aim of improving the running-dynamic qualities of the train during braking.
Knowing the structure and composition of soil is of great importance in numerous scientific and technical fields. For this reason, numerous measuring techniques for measuring soil structure and composition are in use. Despite progress and the introduction of new measuring techniques for determining the structure and composition of soil, galvanic methods are still widely used today. This paper provides a brief review of galvanic methods for measuring soil structure and composition. Special emphasis is given to the Wenner method. This paper presents the modelling of Wenner’s method and soil using the finite element method. For this purpose, a common two-layer soil model was chosen. For more advanced modelling and analysis, the two-layer soil model is extended by adding local soil heterogeneity. The influence of local soil heterogeneity, which can be expected during practical measurements, was analyzed.
Side flaps are critical structural components of flat freight wagons, directly affecting cargo safety during transportation and playing an essential role in loading and unloading operations. Over the years, their reliability has been well established, with standardized designs available in UIC technical datasheets. Despite this standardization, the introduction of newly manufactured or redesigned components necessitates technological validation through Finite Element Method (FEM) simulations and/or physical testing. This requirement holds irrespective of whether the component in question adheres to existing standards or is a novel development. This study presents the creation and application of computational models for the structural sizing and strength assessment of side flaps for flat wagons. The models are verified through a series of physical tests conducted by a research team at the Technical University of Sofia.
The global energy landscape is transitioning towards cleaner solutions, with hydrogen emerging as a key energy source. To unlock hydrogen’s potential, it is crucial to prioritize the development of a more efficient, cost-effective, and environmentally friendly production process. Enhancing the efficiency and scalability of these technologies will not only reduce their environmental impact but also accelerate the adoption of hydrogen as a viable alternative energy solution, fostering a cleaner and more sustainable future. This paper presents a study on simulating a heat recovery system in an alkaline electrolyser consisting of 30 cells, which integrates a plate heat exchanger to preheat the water entering the system, and assessing how it affects efficiency. The study uses a thermal model, employing the concept of lumped thermal capacitance, to analyze the impact of the heat recovery system utilization on the overall performance of the electrolyser. MATLAB/Simulink was used to simulate and provide a detailed visualization of how recovery systems affect the electrolyser’s efficiency. The results of the simulations confirmed that incorporating a heat recovery system significantly improves the efficiency of alkaline electrolysers up to 8%. The study provides a promising outlook for the future of hydrogen production, emphasizing the potential of waste heat recovery systems to make green hydrogen production more viable and sustainable.
Brake squeal is an undesirable high-frequency noise caused by vibrations induced by friction in disc brake systems. The noise is strongly affected by temperature, as this influences the material properties of the friction pair and the dynamic behaviour of the brake components. This study investigates the effect of temperature changes on the squeal characteristics of a disc brake system under different operating conditions. Experiments are carried out using a laboratory-scale test setup comprising a rotating disc, pneumatically actuated callipers, and precise measurement equipment. A series of test combinations is performed by systematically varying three parameters: disc surface temperature (40, 55, 70, 85, 100 °C), brake pressure (4.0 bar), and disc rotational speed (50, 100, 150, 200 rpm). Acceleration data are acquired using an accelerometer mounted directly on the calliper, while sound pressure data are measured with a fixed-position microphone located 0.5 m from the disc surface. The collected data are analyzed in the time and frequency domain to identify squeal events and their dominant frequencies. The effect of temperature on brake squeal noise and vibration varies with operating conditions, showing different patterns at low and high disc speed at constant brake pressure. This highlights the importance of considering both thermal and mechanical factors together when addressing brake squeal.
Seismic performance evaluation of existing buildings is essential for defining effective mitigation strategies in earthquake-prone regions. This study investigates the seismic performance of low-rise unreinforced masonry (URM) residential buildings located in several cities in the Albanian territory. Material properties were obtained from experimental tests conducted on representative samples and subsequently adopted in the development of analytical models. Three-dimensional finite element models were generated based on the collected geometric data and experimentally determined material characteristics. Nonlinear static (pushover) analyses were carried out to assess the seismic capacity and identify the potential failure mechanisms of the buildings. The numerical results showed significant variation in performance depending on the building typology, with some cases reaching the near-collapse limit state under design-level earthquakes. The capacity curves and performance points obtained from the models demonstrate the pronounced influence of construction techniques, boundary conditions, and material properties on the seismic response. The results indicated that URM residential buildings exhibit distinctive seismic performance characteristics influenced by their construction techniques and material properties. Based on the findings, recommendations for retrofit strategies are proposed to enhance the seismic resilience of such structures.
This article investigates the behavior of an electromagnetic field passing through a composite material—a multilayered structure. The material consists of a dielectric material polymethyl methacrylate (acrylic, plexiglass) to which one or more layers of conductive paint are applied to attenuate the field strength. This field attenuation is possible precisely because of the chemical structure of the paint, which contains carbon-based particles and is therefore very successful in its purpose. Research was carried out with the stated aim—simulations and confirmation by measurements—to investigate the attenuation of the EM field when passing through a multi-layered structure.
The present literature review identifies substantial research and applied potential in the combined utilization of internationally recognized information security standards, Bayesian networks, and AI-based assistants to enhance cyber resilience in Unmanned Aerial Systems (UAS) operations within the specific category defined by the SORA (Specific Operations Risk Assessment) methodology. The analysis reveals that while the existing literature individually addresses key components such as ISO/IEC 27001, NIST SP 800-53, MITRE ATT&CK, Bayesian models, and AI techniques, integrated methodologies that unify these elements into a comprehensive and operationally applicable framework are lacking. Particularly underrepresented is the connection to the Cyber Safety Extension of SORA, as well as the synergistic application of quantitative analysis and automation through intelligent systems. The review concludes that a systematic effort is required to develop a holistic framework that reflects the dynamic regulatory demands, operational environments, and contemporary threats facing drone technologies.
