International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

In this study, gelatin-SiO2 hybrid coatings were prepared on glass substrates using an acid-catalyzed sol-gel method. The deposited layers were subjected to thermal treatment at 50°C, 150°C, and 250°C to evaluate the effect of temperature on their structure and optical properties. Spectroscopic investigations in the UV-VIS-NIR range show that the hybrid coatings enhance optical transmittance and reduce reflective losses compared to uncoated glass. The best optical performance was observed for the sample thermally treated at 150 °C (GS 150), where an optimal balance between the organic (gelatin) and inorganic (SiO2) phases was achieved, resulting in maximum transmittance and minimal light reflection. At lower treatment temperatures (50°C), the coating exhibited higher porosity but lower structural stability, whereas at higher temperatures (250°C), partial thermal degradation of the gelatin phase led to layer densification and a slight reduction in the antireflective effect. These results demonstrate that gelatin can be successfully used as a biopolymer component to control the microstructure and optical properties of sol-gel hybrid coatings. Improving optical transmittance and reducing reflective losses of glass surfaces is crucial for enhancing photovoltaic module efficiency, as it allows a greater amount of solar radiation to reach the active layer of solar cells.

This study develops a machine learning framework for predicting the mechanical properties of 6xxx series Al-Mg-Si alloys (6061, 6063, 6082) across seven temper conditions. A hybrid dataset of 860 real measurement-based and 4,200 Monte Carlo augmented samples was generated from a literature-mined dataset. Random Forest (RF), Gradient Boosting (GBR), and Multilayer Perceptron (MLP) models were evaluated via 5-fold cross-validation (CV). RF achieved the best or comparable accuracy: coefficient of determination R² = 0.80 (ultimate tensile strength), 0.92 (yield strength), and 0.83 (elongation). Feature importance analysis showed that alloy type and temper encodings dominated predictions (>90% combined), while individual compositional features contributed <3% a result partly attributable to the augmentation strategy, which decoupled measured compositions from their corresponding property values. Learning curve analysis confirmed model convergence above 2,000 samples.

Contactless techniques for evaluating pressing shapes, as part of the Industry 4.0 framework, are increasingly adopted in industry. Springback assessment is critical for verifying the final geometry of automotive body panels. Although 2D photogrammetric methods have been in use for over a decade, 3D optical surface-scanning systems are now preferred due to their superior accuracy. This study evaluates cylindrical pressings with flat and hemispherical bottoms, fabricated from 1.6 mm thick DP800 dual-phase steel. Thickness distribution was measured using the GOM Scan 1 device. Experimental results were compared against numerical simulations performed in PamStamp software, employing the Vegter Lite yield criterion and Krupkowski hardening law. Real cups (50 mm diameter) were deep-drawn from 90 mm blanks on an Erichsen 145-60 testing machine, with plastic foil lubrication. The thickness profiles obtained from scanned data were directly compared with simulation predictions to assess model accuracy and springback behaviour.

Modern geospatial systems increasingly require search that is both where-aware and meaning-aware. Traditional spatial indexes (e.g., R-tree, Quad/Oct-tree, S2/Geohash) excel at geometric predicates and topological filtering, yet fall short when users ask semantic questions (“ports similar to Rotterdam,” “neighborhoods with transit-oriented development like X”). In parallel, embedding models for text and imagery enable powerful semantic retrieval but typically ignore spatial topology, containment, and scale.
This paper introduces a hybrid spatial–vector search architecture that unifies spatial predicates with embedding similarity for GIS-scale data. The proposed approach involves: (i) a two-stage retrieval process that initially prunes candidates using spatial cells (such as R-tree or S2 indexing) before ranking results with approximate nearest neighbour (ANN) search over embeddings (for example, HNSW or IVF methods); (ii) cell-aware vector indexes that co-partition embeddings according to space-filling curves, thereby reducing cross-cell probes; (iii) a cost-based query planner designed to jointly optimise spatial selectivity and vector recall; and (iv) a multi-modal Retrieval-Augmented Generation (RAG) layer, which integrates map features, textual data, and remote-sensing image embeddings to produce grounded responses. Evaluation is conducted on public geo-text and satellite imagery datasets, with results reported on latency/recall trade-offs, spatial bias effects, and robustness across heterogeneous scales and coordinate reference systems.
Results demonstrate that hybrid indexing delivers more than tenfold lower latency at fixed recall compared to vector-only baselines for spatially selective queries, while maintaining geometric correctness through predicate pushdown. Integration pathways with mainstream GIS and spatial SQL systems (such as PostGIS combined with pgvector) are explored, and ongoing challenges are identified in areas including geodesic distance metrics, CRS normalization, privacy, and reproducible benchmarking. These findings provide a practical blueprint for AI-empowered geospatial search that addresses both the spatial characteristics of locations and the semantic aspects of meaning.

Explosively welded materials exhibit heterogeneous microstructures and variable mechanical properties, making local analysis crucial for the evaluation of joint integrity. Nanoindentation effectively assesses interface properties but typically relies on a series of analytical calculations. This paper proposes a machine learning approach to predict hardness directly from measured load-displacement curves. A neural network model captures nonlinear relationships in indentation data, demonstrating high accuracy against reference measurements across heterogeneous microstructure. This data-driven method offers a scalable solution for rapid, reliable property assessment in complex engineering materials.

Spectroscopic ellipsometry was applied to study the optical properties of Ti–6Al–4V alloy before and after anodization in acetic acid electrolyte. The main findings can be summarized as follows: The ellipsometric spectra of the uncoated alloy were successfully modeled using a multi-Lorentz oscillator approach with MSE values of 20–26, and surface roughness ranging from 17 to 52 nm. Anodized surfaces exhibited distinct interference features, confirming the formation of a transparent oxide layer. The optical modeling revealed increased surface roughness and modified optical constants due to the formation of a TiO₂ -based film with amorphous–anatase character. The applied ellipsometric methodology proved reliable for evaluating the thickness and optical properties of anodic oxide films on titanium alloys. These results form the basis for future quantitative analysis of anodic oxide thickness and refractive index as functions of anodizing parameters, which is important for optimizing the surface properties of titanium alloys in biomedical, protective, and optical applications.

This study presents the design, modeling, and construction of a compact gas turbine prototype. The main goal is to combine theoretical thermodynamic analysis with practical mechanical realization, enabling visualization and study of the performance of a microgas turbine system for educational and research purposes. The design phase was carried out in SolidWorks, where each turbine component, including the compressor, combustion chamber, turbine, etc., were individually modeled to ensure dimensional accuracy and fit during assembly. The 3D model served as the basis for the production and assembly of the real parts of the prototype, built with machined metal components and mounted on a customized steel frame. The combustion and exhaust system was designed to ensure controlled fuel flow and safe ignition conditions, while the shaft was supported on precision bearings to minimize vibration and friction losses. The physical realization, combined with CAD modeling and thermodynamic cycle analysis, provides an excellent platform for studying the thermodynamics of the Brayton cycle, energy conversion efficiency, and heat transfer mechanisms in compact turbines. The study shows that interdisciplinary collaboration between mechanical design, thermodynamics, and practical realization can lead to the construction of a functional prototype for educational and research purposes, which can serve as a basis for experimental testing and further developments in the field of gas microturbines. Future work will include the integration of sensors for real-time data collection and the comparison of experimental performance with theoretical predictions.

Two-dimensional (2D) materials such as graphene and tungsten disulfide (WS₂ ) are promising candidates for gas sensors due to their unique electrical and surface properties. Graphene exhibits high conductivity and mechanical strength, while its oxidized or functionalized forms enhance chemical reactivity and gas adsorption. WS₂ , a semiconducting transition metal dichalcogenide, shows strong surface interactions with gases, enabling sensitive detection even at room temperature.
In this work, graphene and WS₂ thin films were characterized to evaluate surface morphology, uniformity, and structural quality. Graphene films were prepared by chemical vapor deposition (CVD) and transferred onto SiO₂ /Si substrates, while WS₂ films with thicknesses of 20 nm and 50 nm were obtained via CVD and sputtering. Surface analysis using scanning electron microscopy (SEM) and 3D laser microscopy revealed that graphene films are highly uniform and smooth, whereas WS₂ films exhibit thickness-dependent surface roughness and texture. These findings provide insights into the relationship between film morphology and gas sensing performance, highlighting the potential of both materials for sensor applications.

In today’s global industrial environment, the need for sustainable, efficient, and energy-saving solutions for energy supply is more significant than ever and every enterprise that has adopted the policy of a green and low-carbon economy must seek such solutions. Enterprises must analyze their largest energy consumers and look for alternative options for generating and using “green energy”. Photovoltaic systems are among the most common solutions, but their dependence on weather conditions requires integration with energy storage systems. This report presents a model and analysis of an integrated hybrid photovoltaic system with battery storage, designed to provide electricity for energy-intensive production processes under the conditions of the Bulgarian climate and electricity market.

In roll-to-roll systems like wet wipe production, the synchronous and smooth unwinding of the web material with constant tension is critical for product quality and production efficiency. Traditional constant belt braking mechanisms cause tension issues due to varying bobbin diameter and friction-induced heating, leading to web undulations, stretching, and breaks in sensitive materials such as wetlace. To overcome these operational challenges, an automatically controlled braking and accumulator system has been developed. The system instantly measures product tension by monitoring web position using a laser ruler and dynamically adjusts the pneumatic brake force via a high-frequency PID algorithm updated every 5 milliseconds. Furthermore, a constant pressure pneumatic piston acts as an accumulator, balancing the web’s vertical movements and dampening instantaneous tension variations. This system, compliant with Industry 4.0 principles and based on real-time feedback, solves critical tension control problems, ensures continuity in product quality, and establishes a new concept that is a pioneering example in the global market.

This article examines the stiffness calculations for a wing pre-twisted relative to its spar. Such wings can be used in experimental aircraft to study changes in their aerodynamic properties during flight testing at various twist angles. Such variable-geometry wings require comprehensive investigation using strength of materials and elasticity theory. This problem is fundamental to the structural mechanics of aircraft.

A survey of the prevailing trends in the field of quartz ceramics has been carried out. The article examines the main technological stages characteristic of the synthesis of quartz ceramics and the production of various product categories. The main technological stages characteristic of the synthesis of quartz ceramics and the production of various categories of products have been presented. The technological conditions applicable to the processing of raw materials, the preparation of suspensions with optimal characteristics, the molding of blanks and the heat treatment of semi-finished products have been examined. The role and influence of various technological factors in the formation of the structural characteristics and operational indicators of the products have been analyzed.