JOURNAL OF ENGINEERING SCIENCE

APPLICATION OF FLUID-STRUCTURE INTERACTION SIMULATIONS IN THE OPTIMISATION CYCLE OF CENTRIFUGAL PUMP IMPELLERS

Viorel Bostan — 2026-04-05

The integration of fluid-structure interaction (FSI) simulations into the design cycle of centrifugal pump impellers is an important part of this methodology, ensuring the safe conduct of bench tests. This study evaluates the behaviour of the CH 100/32-11-1 pump impeller using a combined numerical workflow involving ANSYS CFX and Mechanical. After a thorough analysis of mesh convergence, the hydraulic loads obtained from Computational Fluid Dynamics (CFD) data were transferred to the structural domain for quantitative assessment of equivalent stresses and strains. The analysis shows that the maximum equivalent stress for the optimised geometry is 24.45 MPa, which is within the tensile strength limit of PA12, confirming the feasibility of manufacturing a functional prototype using a Selective Laser Sintering (SLS). A comparative assessment with respect to the CH 6.3/20-1.1-2 and CH 100/125-75-5 models shows a non-linear scaling of structural loads, with the latter demonstrating critical failure stresses (51.7 MPa) exceeding the material's strength limits. The results confirm that the Fluid-Structure Interaction (FSI) numerical model is an important filter in the preparation stage for prototyping turbomachinery components using additive technologies.

THEORETICAL PRINCIPLES GOVERNING ELECTROCHEMICAL IMPEDANCE SPECTROSCOPY IN NANOSTRUCTURED SEMICONDUCTOR ELECTRODES

Simon Busuioc — 2026-04-05

Electrochemical impedance spectroscopy (EIS) provides a powerful means of probing interfacial and charge-transport phenomena in semiconductor electrodes, yet interpretation becomes increasingly difficult when applied to nanostructured materials. Semiconductor nanowires, nanotubes, and porous films exhibit high surface areas, heterogeneous morphologies, and defect-rich interfaces, all of which modify their impedance response. Theoretical principles regarding EIS behavior in such systems are presented, beginning with semiconductor–electrolyte junction formation, space-charge layer development, band bending and the influence of surface states. Key elements of equivalentcircuit descriptions are examined, including double-layer capacitance, charge-transfer resistance and diffusion-related impedance contributions. Special emphasis is placed on constant-phase elements and distributed models required to capture non-ideal capacitive behavior characteristic of nanoscale electrodes. Common challenges in spectral interpretation, such as overlapping time constants, non-uniform current distribution and deviations from classical Randles-type responses, are summarized within a unified theoretical framework to support reliable modelling and analysis.

ADAPTIVE COMPUTING STRUCTURES FOR SERVICE-ORIENTED MULTI-AGENT SYSTEMS BASED ON KNOWLEDGE MODELS

Vadim Struna — 2026-04-05

This paper proposes an adaptive computing framework for service-oriented multiagent systems, based on knowledge models inspired by the hierarchical organization of the human brain. The approach integrates neurophysiological principles of conscious and subconscious processing with rigorous mathematical formalization and hardware-oriented architectural design. The conscious–subconscious interaction is modeled as a two-level computational hierarchy, in which subconscious processing is fast, parallel, adaptive, and high-dimensional, and conscious processing is deliberative, symbolic, and low-dimensional, being responsible for control, planning, and decision-making. An attention-based coupling mechanism controls the flow of information between the two levels, allowing for dynamic adaptation and efficient use of resources. Based on this model, a heterogeneous hardware architecture is proposed that maps subconscious processing to NPU/GPU accelerators, and conscious processing to CPU units. The framework is extended to multi-agent systems, in which each agent implements a conscious–subconscious hierarchy, and the emergent coordination is achieved through a collective conscious level. The approach supports distributed intelligence, scalability, and adaptive service composition.

MULTI-AGENT SYSTEM FOR PLANNING THE EDUCATIONAL CONTINGENT USING NEURAL NETWORKS

Radu Melnic — 2026-04-05

This paper is dedicated to the development and validation of an intelligent architecture for educational cohort planning, based on the integration of multi-agent systems with artificial neural networks. The research is motivated by the need to efficiently manage educational data flows characterized by high volume, temporal dynamics, and uncertainty, in the context of demographic and socio-economic changes. To this end, a formal model is proposed that describes agents’ decision-making dynamics, inter-agent coordination mechanisms, and the neural learning process used to predict key educational indicators. To validate the proposed solution, an experimental dataset covering the period 2020–2024 was used, reflecting the educational trajectory from high school graduation to the completion of undergraduate studies. The experimental results highlight stable convergence of the learning process, a reduction in prediction error, and the model’s ability to approximate nonlinear relationships between demographic and socio-economic factors and educational indicators. The multi-agent architecture enables efficient distribution of computational tasks, scalability, and adaptability to changes in the educational environment. The proposed solution provides robust decision support for educational management and may serve as an essential formal basis for the development of advanced intelligent systems for institutional planning.

A LAB-ORIENTED CURRICULUM MODEL FOR CLOUD-NATIVE SECURITY AUTOMATION: FROM IMAGE SCANNING TO RUNTIME POLICY ENFORCEMENT

Ludmila Peca — 2026-04-05

The accelerating adoption of cloud-native architectures has created a critical gap between academic cybersecurity training and operational industry demands. This paper applies a design-based research (DBR) methodology to propose a lab-oriented curriculum model for cloud-native security automation, structured around the complete build-deploy-run lifecycle. The model integrates progressive static and dynamic security controls aligned with Cloud Workload Protection Platform (CWPP) and Cloud-Native Application Protection Platform (CNAPP) industry practices. Four curriculum modules produce verifiable deliverables, namely scan reports, compliance checklists, runtime policies, and incident analyses, enabling objective competency assessment through a structured rubric. Preliminary validation with 22 master-level students achieved a module completion rate of 90% and an overall competency score of 78%, demonstrating significant improvement over theoryfocused approaches. The model offers a replicable framework for both academic programs and professional continuous education, contributing to reducing the global cybersecurity skills gap estimated at 4.76 million professionals worldwide as of 2024.

ASPECT-BASED SENTIMENT ANALYSIS USING N-GRAMS, THRESHOLD ADJUSTMENT, AND 3-D SENTIVALUES WITH A NAIVE BAYES ENSEMBLE

Musa Tanimu Karatu — 2026-04-05

Aspect-Based Sentiment Analysis (ABSA) supports fine-grained understanding of user opinions by identifying sentiment toward specific aspects. Nevertheless, many existing approaches either rely on rigid feature representations or adopt deep learning models that introduce high computational cost and limited interpretability, reducing their suitability for scalable soft computing systems. This study proposes a hybrid intelligence framework for ABSA that combines TF-IDF n-gram representations with three-dimensional lexicon-based sentiment values and a threshold-adjusted Naïve Bayes ensemble. Contextual information is captured using unigram, bigram, and trigram features, while semantic polarity, objectivity, and subjectivity scores derived from SentiWordNet provide complementary sentiment knowledge. A weighted fusion of Multinomial and Gaussian Naïve Bayes classifiers is employed, alongside adaptive threshold calibration to improve minority-class detection. Experiments on a large restaurant review dataset demonstrate that the proposed approach achieves an overall accuracy of 0.92 with strong macro-averaged and weighted F1-scores, outperforming multiple baseline and hybrid methods. Statistical significance is confirmed using the Wilcoxon signed-rank test. Computational complexity analysis shows linear scalability with respect to corpus size and document length. The results indicate that the proposed hybrid framework delivers an effective balance between accuracy, interpretability, and computational efficiency, making it suitable for scalable soft computing systems and resource-constrained sentiment analysis applications.

AVAILABILITY AND MAINTAINABILITY OF EQUIPMENT IN INTEGRATED TECHNOLOGICAL FLOWS FOR SOLID BIOFUEL PRODUCTION: A REVIEW

Teodor Marian — 2026-04-05

The transition toward renewable energy sources and the efficient valorization of agricultural residual biomass necessitate increased reliability and efficiency of integrated technological flows for solid biofuel production. The study is based on the hypothesis that the overall performance of the integrated technological flow is primarily determined by equipment located on the critical path and by the operational behavior of working components. The research aims to evaluate equipment availability and maintainability at system level and to identify the limiting links affecting process continuity. The methodology includes the analysis of reliability and maintenance indicators, correlation of availability with functional criticality, and the development of a synthetic technological vulnerability indicator to assess the global risk of unavailability. The results highlight the decisive influence of biomass properties and working component behavior on MTBF, MTTR, and overall availability, emphasizing the need for a systemic and differentiated maintenance approach to enhance system resilience. Furthermore, the findings indicate an uneven distribution of performance within the technological flow and identify densification stages as critical limiting links, followed by mechanical preparation and biomass generation and collection stages. The proposed integrative approach provides an innovative methodological framework for performance evaluation and maintenance prioritization, contributing to reduced unplanned downtime, optimized resource utilization, and improved resilience of solid biofuel production systems.

NUMERICAL MODELING OF HYDRODYNAMICS OF RIVER-TYPE AQUATIC SYSTEMS

Rodica Branişte — 2026-04-05

The prediction and monitoring of pollutants in riverine ecosystems are essential for environmental protection and public health. This study proposes a methodology for the numerical modeling of hydrodynamics in aquatic systems using ANSYS Fluent. The results highlight the capability of ANSYS Fluent to determine critical parameters required for subsequent simulations, enabling accurate assessment of pollutant concentration distributions.

TERRESTRIAL LASER SCANNING FOR 3D CADASTRE: A CASE STUDY OF ROAD INFRASTRUCTURE IN THE REPUBLIC OF MOLDOVA

Ana Vlasenco — 2026-04-05

Accelerated urban development and infrastructure expansion require the modernization of the cadastral system in the Republic of Moldova through the integration of the three-dimensional component. This article analyzes the possibility of implementing 3D cadastre, starting from the limitations of the current two-dimensional cadastre and the need for alignment with international standards, particularly ISO 19152 (LADM - Land Administration Domain Model). The case study focuses on the three-dimensional modeling of a complex infrastructural object – a road bridge in Criuleni district, located at the intersection of Hrușova, Ciopleni, and Goian villages. Using terrestrial laser scanning technology (Leica BLK360), high-precision spatial data were obtained (RMS <10 mm, density >800 points/m²), which were processed and integrated into a functional 3D model. The results demonstrate that three-dimensional modeling provides a more accurate representation of reality, facilitates engineering analysis, and enables correct description of overlapping objects or those with complex geometry. The article proposes a hybrid implementation model, in which the 2D cadastre remains the legal basis, while 3D models serve as technical and decision-making support. The conclusions highlight the need for developing a specific regulatory framework, standardizing data acquisition processes, and creating an integrated GIS (Geographic Information Systems) platform for efficient management of three-dimensional spatial information.

PHYSICOCHEMICAL, SENSORY AND TEXTURAL EVALUATION OF SUGAR BISCUITS SUPPLEMENTED WITH LENTIL FLOUR

Olga Boestean — 2026-04-05

Grain legumes are widely acknowledged as fundamental sources of dietary protein on a global scale. In particular, lentil proteins contribute not only essential amino acids to the human diet but also serve as a source of bioactive peptides with documented healthpromoting properties. The present study aimed to evaluate the impact of lentil flour (Lens culinaris) incorporation on the quality attributes, color, and textural properties of sugar biscuits. Lentils are highly valued due to their well-balanced nutritional composition. The analyzed red lentil variety exhibited a notable chemical profile, characterized by a protein content of 31.35 g/100 g, lipid content of 1.87 g/100 g, and dietary fiber content of 12.6 g/100 g. Sugar biscuits formulated with varying levels of lentil flour (1–15%) were assessed in terms of sensory characteristics, physicochemical properties, texture parameters, and color indices. Among the tested formulations, the sample containing 10% lentil flour achieved the highest overall evaluation score. Based on the obtained quality indicators, the biscuits can be considered safe for consumption, maintaining their key quality attributes over a storage period of up to 35 days under specified conditions. Consequently, these products may be recommended as part of the diet for diverse consumer groups.

EVALUATION OF THE IMPACT OF SEA BUCKTHORN POMACE ADDITION ON THE PHYSICOCHEMICAL AND QUALITY PROPERTIES OF MEAT SNACK PRODUCTS

Irina Dianu — 2026-04-05

The utilization of fruit-processing by-products is a practical approach to develop sustainable, value-added meat snacks. Sea buckthorn pomace, rich in colored and acidic compounds, is expected to influence dehydration behavior, appearance and storage stability of deshydrated meat products. The study was designed to investigate how different inclusion levels of sea buckthorn pomace powder (SBPP) - 0.75%, 1.25%, and 2.5% (w/w) - influence the quality and safety attributes of fermented and dehydrated meat snack products. The samples underwent fermentation at 25 ± 1 °C for a period of 12 hours, followed by dehydration at 50 ± 5 °C for 6 hours. Subsequent analyses comprised the assessment of key physicochemical parameters (moisture content, pH, and water activity), instrumental color measurement using the CIELab system, sensory profiling, determination of lipid oxidation through peroxide value, and evaluation of microbiological indicators. Increasing SBPP level decreased moisture (15.79% to 7.93%), water activity (0.455 c.u. to 0.358 c.u.) and pH (6.16 to 5.65), indicating enhanced shelf-stability. Color shifted toward a darker red-orange profile (L* 47.85 to 20.64; a* up to 27.09). Peroxide value remained low and unchanged (1.60 to 1.70 mEq O2/kg). Coliforms, moulds/yeasts and Salmonella were not detected. SBPP is therefore a clean-label ingredient enabling differentiated ripening-dehydrated meat snacks while supporting circular valorization of processing residues.