In this paper, we present an internally developed sensing system featuring an integrated 6 degrees-of-freedom (6 DoF) accelerometer designed to provide a rapid and remarkably simple solution for measuring low frequency vibrations — such as flow-induced vibrations — or other movements of solid structures in educational, research, and industrial applications. Given its highly compact form factor, the device supports wireless communication and onboard data logging to a memory card. Since neither power supply nor data transmission requires a wired connection, it is also suitable for analyzing the motion of untethered, freely moving bodies. According to its modular architecture, the sensor can be fitted with custom housings tailored to diverse geometric constraints and produced rapidly using SLA 3D printing technology. In addition to outlining the design considerations, we detail the device's construction and capabilities, then validate its performance by comparing measurement results from a simple autonomous chaotic mechanical system experiment with a vision-based measurement method.
Geothermal energy represents a reliable and low-carbon resource with significant potential for both heat and electricity generation, particularly in regions characterized by medium-temperature reservoirs such as the Pannonian Basin. However, the efficient utilization of these resources requires an integrated approach that simultaneously considers subsurface geological conditions and surface-level constraints. This study presents a comprehensive methodology for the first-order evaluation of geothermal resources for combined heat and power production. The approach integrates geological risk assessment, based on Common Risk Segment (CRS) and Composite Common Risk Segment (CCRS) mapping, with a GIS-based multi-criteria analysis of environmental, technical, and socio-economic factors. The methodology is applied to a case study in southwestern Hungary (B & oacute;ly region), where potential locations for new geothermal doublets are identified and evaluated. Preliminary reservoir simulations indicate that the selected doublets can provide up to 4.2 MWth thermal capacity over several decades. The integration of geothermal heat into district heating systems, combined with electricity generation using Organic Rankine Cycle (ORC) technology, enables efficient cascading utilization of the resource. Under representative conditions, the system can supply a substantial share of local heat demand while producing several GWh of electricity annually. Another case study of an existing well near Szarvas (southeastern Hungary) was also presented. The results demonstrate that medium-temperature geothermal resources can support decentralized energy systems and contribute to improved energy security, resource efficiency, and decarbonization.
In sheet metal forming processes such as deep drawing, planar anisotropy plays a crucial role in determining the final geometry. The formability of sheet metals depends on their anisotropic behavior; therefore, anisotropy can be a limitation of forming. Accurate finite element modeling of sheet metal forming processes requires a robust description of anisotropic behavior. The standardized approach for determining anisotropy is tensile testing at different angles relative to the sheet metal's rolling direction. Biaxial behavior is also important for the yield function of the materials. Although several methods are available for determining biaxial properties, the disk compression test is relatively simple and easy to perform and, therefore, a favorable method in an industrial environment. The goal of the present study is to determine the biaxial anisotropy coefficient of LDX2205 duplex stainless steel (DSS). Although the proper lubrication and the appropriate test methodology are unknown, a comparison is needed to define the methods and lubricants for further investigations. The tests were conducted with three lubricants to identify the most reliable one: a high-contact-pressure grease, a graphite-containing grease, and PTFE sheets. Based on measurements, the greatest deformation occurred when PTFE sheets were applied; therefore, further tests were performed using these sheets. Three series of compression tests were performed: a fully compressed series, a gradually compressed series, and a load-driven series. The investigations were carried out to examine the influence of the different methods on the parameter. Microhardness tests were conducted on the as-delivery-conditioned material and on the compressed material.
The impact of vibration phenomena on gas turbine operation and production quality can significantly reduce their service life. Balancing the rotating elements of these machines is a valuable method for reducing production losses and avoiding the need for total machine dismantling. In this study, a gas turbine type MS3002 with two rotors was examined on-site to minimize the phenomenon of unbalance and provide correction angles at the rotor level. This balancing process enabled the control and improvement of the mass distribution of the rotor to maintain efforts and vibrations caused by unbalance within acceptable limits while ensuring the optimal operation of the turbine. The results demonstrate the importance of balancing techniques in extending the service life of gas turbines and maintaining optimal performance.
The tribological behavior of metal-polymer friction pairs depends to a large extent on their surface roughness. In this study, we analyze the friction of C45 (1.0503) steel and polypropylene homopolymer (PPH) in terms of the surface roughness characteristics of the material pair subjected to friction. The results of the friction experiments described in the article showed that during the friction process, the investigated roughness parameters of the steel specimen (Ra-average surface roughness, Rz-roughness height or tenpoint height, Rp-maximum peak height, Rv-maximum valley depth) remained essentially unchanged, while the same roughness parameters of the polymer surface significantly changed and adapted to the roughness characteristics of the steel. Ellipsometric measurements also confirmed the presence of a 20-30 nm thick polymer transition film on the steel surface, and there were parts of steel on the polymer surface as well. The obtained results indicate that in the case of metal-polymer friction pairs, the change in surface roughness is asymmetric (the surface roughness of the harder material shapes the softer surface). In contrast, material transfer is bidirectional. These must be taken into account in friction modeling and wear prediction.
This study examines dry sliding friction between a hydrogenated amorphous carbon (a-C:H) diamond-like carbon (DLC) coating and a polypropylene homopolymer (PPH). The coating was deposited on a quenched and tempered 42CrMo4 steel specimen (39 +/- 1 HRC). Friction tests were performed at three sliding speeds (v = 5, 50, and 500 mm/min) and three surface pressures (p = 2, 4, and 6 MPa). From the recorded friction-force curves, the static friction coefficient (p0) was taken as the peak value at the onset of motion, while the dynamic friction coefficient (pdyn) was evaluated in the near steady-state (gross sliding) region. Both p0 and pdyn increased with sliding speed: p0 rose from about 0.24 to 0.33 and pdyn from about 0.22 to 0.32 in the investigated range. Surface pressure had a smaller effect: p0 showed no clear pressure trend, whereas pdyn increased with pressure at a given speed. A two-factor analysis confirms that sliding speed is the dominant factor for both p0 and pdyn, and it also indicates a weak non-linear speed dependence in this parameter range. Overall, the friction coefficient of the PPH-DLC pair remained approximately within 0.20-0.35 for v = 5-500 mm/min and p = 2-6 MPa.
Particularly in the transportation sector, waste heat originating from ultra-low-temperature sources (25-80 degrees C) represents a significant but largely untapped energy resource. With conventional heat recovery solutions, this type of heat loss is either not or only poorly exploitable. Therefore, thermally regenerative electrochemical cycles offer a promising solution, as they can directly convert lowtemperature thermal energy into electricity. In this research, the dynamic behavior of a system using iron- and iodine-based redox pairs was investigated. In the model, the temporal variations of reactant concentrations were simulated over a 24-hour period, along with the electromotive force. Based on our results, the system's electromotive force closely follows the concentration changes, which means that the regeneration process can be effectively controlled solely based on voltage. This enables the optimization of pump operation using voltage as the input parameter for pump control, avoiding unnecessary pump cycling. The method may be particularly promising for dynamic applications in vehicles, where concentration measurement is difficult to implement.
This work examines the influence of a heat source/sink and dissipation on the MHD laminar flow of Williamson fluid over a nonlinear elastic sheet in a porous medium. The effects of non-linear radiation and Joule heating are also considered. The fluid's conductivity and viscosity are assumed to vary with temperature, enabling the study of heat and mass transfer phenomena. Suitable similarity variables are employed to transfer the resultant system of PDEs into a system of non-linear ODEs. The system is numerically solved utilizing the shooting approach in combination with the 4th-order Runge-Kutta method in MATLAB. The findings are validated through comparison with prior research, demonstrating a high level of agreement. The influence of various flow parameters on heat distribution and the flow field is analyzed and illustrated through diagrams. Additionally, the friction coefficient and Nusselt number are computed numerically for a range of selected parameters and presented in tables. Key findings reveal that the velocity profile decreases with an increase in the viscosity parameter, while temperature rises with a higher viscosity parameter. Moreover, the Nusselt number decreases with an increase in the Williamson, viscosity, and Eckert parameters, while it increased with the suction parameter. The findings may have significant applications in various industrial and scientific fields, particularly in paints and coating, oil drilling, and blood circulation.
This paper quantifies uncertainty and identifies the key drivers of simulated energy use in a representative archetype of the Hungarian residential building stock. It specifically examines the impact of standardized occupancy inputs compared to those based on surveys and stochastic methods. A DesignBuilder model of a typical detached house is parameterized using data from Energy Performance Certificates (EPCs) that detail the building's envelope and system characteristics. Additionally, occupantrelated parameters such as setpoints, ventilation, domestic hot water (DHW), and internal gains are derived from a comprehensive national survey and relevant literature. To analyze uncertainty propagation and conduct a global sensitivity analysis, Latin Hypercube Sampling is applied across multiple scenarios: a typical meteorological year, two actual years, and a future climatechange scenario, with and without space cooling. Furthermore, an alternative scenario using a 2050 primary energy conversion factor is evaluated. The results indicate that the heating setpoint temperature is consistently the most influential factor for EPBDbased primary energy usage. Other significant contributors, depending on weather conditions and cooling assumptions, include ventilation rates, heating system efficiency, and parameters related to domestic hot water. Overheating hours are primarily affected by factors such as night ventilation, shading, and internal gains. The findings reveal that using standardized assumptions for occupancy can skew both heating and cooling outcomes. Additionally, assumptions regarding climate and primary energy factors can alter the relative significance of key parameters. The proposed workflow enhances the robustness of building-stock assessments and underscores the value of improving input data quality.
This paper presents the high-resolution reconstruction of a human mandible and lower dentition based on real CT data. The primary goal was to create a continuous spline-based computer model that provides a robust foundation for analyzing the tooth-bone interface. Special emphasis was placed on the realistic integration of teeth into the mandible, enabling the model to be divided into distinct biological layers. The resulting geometry is fully prepared for numerical simulations, where individual solid parts can be assigned specific material properties, allowing more accurate finite element analysis of the mechanical behavior of different regions.
Convolution and deconvolution are essential in image processing for enhancement, analysis, and feature extraction. Convolution is widely used for filtering and edge detection, while deconvolution restores blurred images by recovering hidden details. These techniques are particularly important in space research, where high spatial resolution is coupled with 12-16-bit ADC, and optical quality is often degraded by stray light, making data interpretation challenging. Additionally, high-resolution images with large spatial dimensions and a high number of pixels, commonly encountered in space research, require significant computational resources, leading to slow processing times. Our research focuses on optimizing convolution and deconvolution techniques using CUDA technology to accelerate processing. We developed a custom CUDA-based stray light removal method, achieving performance comparable to a previous C++ implementation while significantly reducing processing time through parallelization, resulting in an approximately 83% reduction in execution time and a runtime below half a second. For deconvolution, we implemented multiple algorithms in MATLAB and CUDA environments, including Wiener filtering, Richardson- Lucy deconvolution, relevant regularization methods, and blind deconvolution. The Richardson-Lucy method, due to its iterative nature, is computationally intensive, which motivated its CUDA implementation. Leveraging GPU parallelization, we achieved substantial speed improvements - specifically, more than a 52% reduction in execution time - while maintaining result quality. This paper proposes multiple deconvolution solutions for various image processing tasks and demonstrates the effectiveness and applicability of parallel programming in image enhancement algorithms. These contributions are particularly valuable for large-scale images and real-time applications.
As a result of the rapid expansion of photovoltaic (PV) systems in Europe, system operators are faced with challenges caused by deviations between scheduled and actual power generation more and more often, which increases their balancing requirements and operational costs. Ensuring schedule compliance has thus become a critical issue for integrating PV into modern electricity networks. This study introduces and evaluates a novel schedule-oriented control mechanism for dual-axis PV systems, based on a patented concept. Unlike conventional sun-tracking strategies that maximize irradiance capture, the proposed method intentionally adjusts module orientation to minimize deviations from day-ahead and intraday schedules. This represents an innovative shift from generation-maximizing to grid-supportive control, directly addressing system-level balancing needs. The control logic, implemented in Python, was evaluated on Hungarian datasets combining measured and simulated time series, and all analyses were carried out in a simulation environment, with field validation planned in future work. Results show that while the mechanism reduces annual energy yield by around 7% (1164 MWh to 1080 MWh per 1 MWp system), it achieves a >90% reduction in downward regulation requirements (from 8.0% to 0.8% of annual output). Upward regulation requirements decreased only marginally, as these cannot be effectively influenced by control interventions. The results demonstrate that the proposed control mechanism substantially improves schedule compliance while incurring only minor energy yield losses, offering a cost-effective solution for large-scale PV integration.
The investigation of floating body motions is a frequently visited topic in the areas of wave energy converters and coastal engineering. In fluvial conditions, the design process of floating platforms and the forecast of ice jamming events are also parts of relevant applications. Apparently, the two-way coupling of the fluid and floating body forces is often a fundamental requirement in such applications leading to computationally expensive studies. In cases of open surface flow modeling, where the water depth is sufficiently small compared to the horizontal extensions of a water body, the depth-averaged shallow water equations (SWE) offer an efficient alternative of the 3D Navier-Stokes equations. Utilizing the benefits of the SWEs, we aim to reduce the 3D problem of floating body motions to the 2D shallow water framework utilizing the smoothed particle hydrodynamic (SPH) method. However, the task is not straightforward due to the explicit nature of the SWE-SPH model. As an additional constraint, the presence of a floating object determines the local water depth, which is otherwise purely driven by the equation of motion and continuity. In our model, this constraint is defined by an additional penalty term in the equation of motion to accurately predict the water depth as well as the forces acting on the floating object. As a result, a two-way coupled fluid structure interaction model is established. The proposed method is easy to be implemented and offers an efficient alternative approach to the fully resolved computations, with a reasonable loss of accuracy.
Phased microphone array measurements combined with beamforming signal processing is a widely used approach for localizing and quantifying noise sources, which can be used for turbomachinery applications. Among the various array configurations, uniform circular arrays (UCAs) are frequently employed for rotating sources due to their geometric simplicity and the practical advantage that they can be installed around a free jet or a duct without disturbing the flow. The present article investigates this array design with the aim of providing guidelines for planning proper measurement setups. Particular attention is given to two interdependent parameters: the array diameter and the measurement distance. For a simplified turbomachinery test case, a suitable measurement range is defined within the parameter plane spanned by these variables. The lower and upper bounds of this range are established through the constraints of achieving sufficient spatial resolution and avoiding spatial aliasing, for the estimation of which straightforward formulas are derived herein. Furthermore, it is shown that the parameter plane defined by array diameter and measurement distance can be regarded as the extrusion of one of its cross-sections along specific curves, referred to herein as self-similar curves, as the beamforming maps along these curves are self-similar. This property is advantageous, as conclusions can easily be drawn for the entire parameter space under investigation by carrying out a few simple calculations that utilize the formulas derived herein.
Climate change is the most significant environmental challenge facing the world today. The EU is implementing various strategies to create a legislative and proposal framework for its Member States, promoting environmental sustainability through the European Green Deal. The EU aims to make Europe the first climate-neutral continent, requiring significant reductions in greenhouse gas (GHG) emissions from the energy sector, including initiatives under the Clean Energy Transition prioritizing renewable fuels. Besides weather-dependent renewables – aligned with waste management regulations – waste-based fuels like recycled carbon fuels (RCFs) can also aid the transition when the 70% GHG emission saving criterion is fulfilled, which is highly dependent on the accuracy of the input data. Digitalization will help higher renewable energy integration, but the extensive use of data requires preserving high privacy, safety, and security standards. Systematic literature research identified blockchain-based systems as an appropriate choice for advanced data collection. Data from a Hungarian municipal solid waste sorting facility was used to investigate the effect of data accuracy on GHG emission saving results of a RCF, comparing the EU regulated calculation method and the holistic life cycle assessment (LCA) method suitable for analyzing complex systems, complemented with a sensitivity analysis. Results showed that the GHG emission saving increases by 4.5 percent points using LCA compared to the EU regulated method. The sensitivity analysis proved the necessity of accurate data as a 1% change of input parameters resulted in a maximum two-fold relative change in GHG emission savings.
Titanium-based alloys are widely applied in the aerospace industry thanks to their excellent strength-to-weight ratio, good corrosion resistance and thermal stability. In this study, a Ti-6Al-2Cr-2Ni alloy was elaborated by Spark Plasma Sintering (SPS), a technique derived from powder metallurgy that enables rapid, controlled densification. Sintering was carried out at 1000 °C under 30 MPa for 8 minutes in an inert atmosphere. A thermal annealing treatment at 550 °C was then applied to optimize microstructure and mechanical properties. Microstructural characterization by scanning electron microscopy (SEM), combined with EDS elemental analysis, revealed a significant reduction in porosity and progressive homogenization of the alloying elements after treatment. X-ray diffraction (XRD) confirmed the presence of a majority of α-Ti phase, associated with intermetallic compounds. Mechanically, Vickers microhardness measurements showed an increase in hardness after annealing, while instrumented indentation enabled Young's modulus to be reliably determined. These results indicate that the Ti-6Al-2Cr-2Ni alloy developed by SPS is a promising alternative to standard alloys such as Ti-6Al-4V, offering improved microstructural controllability, interesting mechanical properties and thermal optimization potential for advanced aerospace applications.
The present paper employs the 3D finite element method to investigate the elastic-plastic behavior of repaired cracks in welded structures reinforced with bonded composite patches. The analysis is based on the J-integral, an important parameter for crack tip characterization. Two different patch configurations are considered: single and double symmetric patches. The effect of patch thickness, adhesive properties and the mechanical behavior of weld-metal on the J-integral variation are systematically evaluated. The results revealed that the double symmetric patch configuration excels over a single patch in terms of improving repair efficiency. Additionally, it is found that the mechanical behavior of weld-metal plays a crucial role in determining the performance of the reinforced welded structures.
Reinforced metal matrix syntactic foams (rMMSFs) were produced by liquid-state, low-pressure vacuum infiltration. Technical purity Al99.5 aluminum alloy was used as the matrix material, and ceramic hollow spheres (CHSs) with Ø2.24±0.13 mm diameter were applied as a filler material. The matrix was reinforced by 0.6 nominal size SiC with seven different volume fractions of the reinforcing material relative to the matrix material’s volume: 0 vol%, 5 vol%, 10 vol%, 15 vol%, 20 vol%, 25 vol%, and 30 vol%, respectively. The samples were investigated structurally and mechanically. Based on the microscopic investigation, the liquid-state, low-pressure vacuum infiltration was found to be a good production method of the rMMSFs; no traces of reactions between the components had been found. Based on the results of the standardized compressive test, the specific compressive strength and specific structural stiffness of rMMSFs were significantly increased for each reinforcement volume fraction, and even a 63.2±8.1% improvement can be achieved in the specific compressive strength compared to the unreinforced (UR) samples. The specific plateau strength and the specific energy absorption were improved with a 15 vol% or above reinforcement volume fraction compared to the UR foams. The decrement was caused by the stress-concentrating particles, and this effect could only be equalized by higher reinforcement content. The failure modes of the MMSFs were dependent on the dual composite properties of rMMSFs. The failure of the reinforced samples was indicated by plastic collapse followed by the appearance of a cleavage band and its widening.
This study addresses the improvement of part cooling in FFF 3D printing, using the Creality Ender 3 V2 as a case study. The stock cooling system directs airflow from a single side, which leads to uneven cooling and reduced surface quality. To overcome this limitation, both a reference redesign and a generative design approach were investigated. The development involved flow domain optimization with Autodesk Fusion's Generative Design module, followed by CFD simulations in Ansys CFX. Results indicate that generative design can enhance cooling performance and enable more effective two-sided airflow. At the same time, challenges remain in achieving uniform outlet velocity distribution, as flow separation effects may occur. Overall, the study demonstrates the potential of generative design as an innovative tool for accelerating fluid dynamics design processes, while highlighting the need for further refinement and experimental validation.
It is well established in the literature that the precipitation of different carbide types and intermetallic phases in stainless steels can lead to drastic consequences in their mechanical and corrosion behavior. Chromium carbide particles precipitate at grain boundaries, creating chromium depletion zones that expose the stainless steel to high corrosion penetration in harmful working atmospheres. The aim of this work is to evaluate the effect of electrolytically charged hydrogen on the mechanical behavior of heat treated AISI 316L austenitic stainless steel samples. To achieve a homogeneous distribution of carbides, specific heat treatments were conducted before tensile tests. Subsequently, a group of heat-treated samples were hydrogen-charged. After tensile tests carried out at high (0.003 s−1) and low (0.000003 s−1) strain rates, the resulting fracture surfaces exhibited mixed behavior in hydrogen-charged samples, i.e., ductile-brittle, in comparison with the ductile morphology obtained in uncharged ones. Additionally, in hydrogenated samples, cracks were associated with fine chromium carbides. Coincidentally, there was a ductility loss in hydrogen-charged samples, which was not observed in uncharged ones. In order to identify hydrogen-carbide interactions, combined studies of Differential Scanning Calorimetry (DSC) and a selective metallographic technique made it possible to identify grain boundaries and carbides/matrix interfaces as the main hydrogen traps. Finally, regarding strain rate effects on mechanical properties, it could be stated that when the strain rate decreases, the embrittlement effect of hydrogen is more explicitly manifested in conjunction with a microstructure sensitized by heat treatments and revealed by the mixed mode of fracture in hydrogen-charged samples.
