Mihaela Constantin

Reverse-flow cyclone preselection is often performed with nominal semi-empirical closure values, although swirl and turbulence corrections are family-dependent. This study develops a scenario-based robust geometric screening framework for fixed-throughput reverse-flow cyclones using a family-calibrated reduced-order model for cut size and grade efficiency, combined with a fixed-Eu pressure drop. The design variables are the inlet-area ratio, vortex-finder diameter ratio, and effective residence-height ratio. Closure uncertainty is represented by 27 combinations of the swirl-intensity coefficient, turbulence-correction coefficient, and turbulence intensity. Deterministic and robust Pareto fronts are compared in the pressure-drop–corrected-cut-size plane (Δp,d_50,t), and worst-case grade-efficiency indicators are evaluated for 2 and 5 μm particles. The results show that closure uncertainty substantially penalizes nominal fine-particle predictions: across the robust Pareto set, the worst-case corrected cut size is 1.79–1.93 times the nominal value. Within the original design window, the reduced-order screen identifies a balanced candidate near ϕ_in ≈ 0.10, D_e/D = 0.40, and H_eff/D = 6, with lower predicted nominal and worst-case corrected cut sizes than the baseline at unchanged fixed-Eu pressure drop estimate. The selected geometries are not independently validated in the present study and should be treated as candidates for subsequent high-fidelity assessment. Design-grid refinement and extended-bounds, hydraulic, and logistic-slope sensitivity audits show that the numerical screening results are stable within the adopted formulation but remain conditioned by its closure assumptions.

The decarbonization of energy systems has intensified interest in hydrogen-enriched natural gas (H₂NG) as a transitional fuel for combined heat and power (CHP) units and micro-CHP systems. This review consolidates experimental and numerical studies that explore the energy, environmental, and techno-economic implications of H₂NG blends in CHP applications. Research conducted over the last decade highlights that enriching natural gas with hydrogen extends the flammability limits, enhances combustion stability, and reduces CO₂ and CO emissions, while maintaining or improving electrical efficiency. However, these benefits are accompanied by higher NO_x formation under stoichiometric conditions, which can be mitigated by operating under lean-burn regimes. The review further examines hybrid solutions that integrate electrolyzers, photovoltaic systems, and oxygen-enriched combustion to improve system flexibility and sustainability. The findings consistently show that moderate hydrogen fractions (5–20% vol.) provide optimal trade-offs between efficiency gains and emission control, supporting the role of H₂NG as an intermediate step toward fully hydrogen-powered CHP technologies. Technical challenges related to ignition control, thermal recovery efficiency, and infrastructure adaptation are also discussed, along with emerging strategies for techno-economic optimization. This comprehensive assessment contributes to understanding how hydrogen blending can accelerate the transition to low-carbon, distributed energy systems.

Cyclone separators remain widely used for gas–solid separation, yet analytical prediction of cut size and pressure drop remains challenging. This study presents an explicit semi-empirical model for the cut size (d₅₀) of reverse-flow cyclones based on the radial particle equation of motion in cylindrical coordinates, with d₅₀ obtained by equating radial migration time and residence time. A closed-form solution is derived in the Stokes regime, whereas non-Stokes behavior is handled numerically through the Schiller–Naumann drag correction. Turbulence is incorporated through a phenomenological correction, and the grade–efficiency curve is represented by a logistic relation. The model was implemented in MATLAB R2025a and applied in a parametric study covering inlet velocity, particle density, cyclone diameter, and gas viscosity. A Euler-type pressure drop relation was included to examine the separation–energy trade-off. Validation on the Kim et al. benchmark using one calibration point per cyclone family and six independent verification cases yielded a mean absolute percentage error of 13.5% and a root mean square error of 0.22 μm for d₅₀; the paired pressure drop check gave a 2.8% mean absolute percentage error. A complementary benchmark based on Wang et al. using 15 cm 1D3D and 2D2D cyclones under actual-air and standard-air conditions further supported the family-calibrated use of the model. A separate scale-up test showed that constant swirl intensity similarity is not transferable across large diameter changes. The formulation provides a transparent reduced-order tool for preliminary design and sensitivity analysis.

This study presents a combined numerical and experimental investigation of transient multiphase compressible flow inside a profiled-rotor rotary volumetric compressor. While most existing studies rely on high-fidelity CFD approaches, a low-order thermodynamic chamber-based model implemented in MATLAB Release 2023a is proposed to predict the temporal evolution of pressure, temperature, and vapor volume fraction during the compression cycle. The model is based on mass and energy conservation applied to variable-volume control chambers and incorporates a simplified cavitation criterion derived from local pressure relative to saturation vapor pressure. An open-loop experimental test bench was developed to measure air mass flow rate, suction and discharge pressures, temperatures, torque, and shaft power under controlled operating conditions. These measurements are used to validate the numerical predictions. The results show good agreement between measured and simulated pressure levels and global performance indicators, with deviations quantified using mean absolute percentage error values remaining below 5% over the investigated operating range. The numerical analysis further reveals the occurrence of localized low-pressure zones during the suction phase, indicating incipient cavitation or microbubble formation at specific rotor positions. The proposed modeling approach provides a computationally efficient alternative to full CFD simulations and enables rapid parametric analysis of rotor geometry and operating conditions. The cavitation formulation does not aim to resolve detailed bubble dynamics or erosion mechanisms, but rather to identify cavitation tendency based on thermodynamic pressure thresholds.

This paper presents the development and experimental validation of a rotary volumetric pump with profiled rotors designed for domestic water supply systems. The proposed solution integrates an electric drive system coupled with frequency control to improve hydraulic and energy performance. A constructive concept, mathematical modeling, and an experimental prototype were developed at the National University of Science and Technology POLITEHNICA of Bucharest. Comparative studies with conventional centrifugal pumps highlight significant improvements in energy efficiency, lower power demand, and the ability to convey viscous fluids or suspensions without performance degradation. Experimental installations equipped with sensors and monitoring instruments confirmed theoretical predictions, demonstrating that integrating electrically driven rotary volumetric pumps can reduce operational energy consumption and increase reliability in civil building services. These results underline the potential contribution of the proposed pump to sustainable energy management in water distribution systems.

Cyclone separators are widely used for gas–solid separation due to their robustness and low operating cost. This study focuses on the experimental validation of a single cyclone configuration and the development of a MATLAB-based numerical framework. The model employs a Euler–Lagrange approach to capture centrifugal, drag, and gravitational forces acting on spherical polyethylene particles (D = 5 mm). Laboratory-scale measurements of airflow, pressure drop, and separation efficiency showed strong agreement with the numerical model (deviation < 6%), confirming its reliability for the single cyclone case. Beyond this validated framework, exploratory simulations were carried out for series and parallel cyclone configurations to provide predictive insights into possible design trade-offs. Unlike high-fidelity CFD–DEM models, which are computationally intensive and allow detailed turbulence and particle–particle interactions, the present MATLAB model is simplified but transparent and fast to implement. Its originality lies in demonstrating a low-cost, experimentally calibrated tool that can support preliminary design decisions. The multi-cyclone results should be interpreted as predictive trends, as no direct experimental validation was possible within the present setup. These findings offer preliminary guidance for balancing efficiency, energy demand, and throughput in applied mechanics of multiphase flow systems.

This study presents the design, modeling, and multi-platform simulation of NEPTUNE-R, a solar-powered autonomous hydro-robot developed for sustainable water purification and oxygenation. Mechanical design was performed in Fusion 360, trajectory optimization in MATLAB R2024a, and dynamic motion analysis in Roblox Studio, creating a reproducible digital twin environment. The proposed path-planning strategies—Boustrophedon and Archimedean spiral—achieved full surface coverage across various lake geometries, with an average efficiency of 97.4% ± 1.2% and a 12% reduction in energy consumption compared to conventional linear patterns. The integrated Euler-based force model ensured stability and maneuverability under ideal hydrodynamic conditions. The modular architecture of NEPTUNE-R enables scalable implementation of photovoltaic panels and microbubble-based oxygenation systems. The results confirm the feasibility of an accessible, zero-emission platform for aquatic ecosystem restoration and contribute directly to Sustainable Development Goals (SDGs) 6, 7, and 14 by promoting clean water, renewable energy, and life below water. Future work will involve prototype testing and experimental calibration to validate the numerical findings under real environmental conditions.

This paper presents a detailed thermodynamic and mathematical modeling study of the oxygenation processes in stationary water bodies, focusing on improving oxygen transfer efficiency, an essential factor in sustaining aquatic ecosystem health. The study employed mathematical models implemented in MATLAB R2024a to simulate the influence of temperature, bubble size, and mass transfer parameters. Key parameters, such as dissolved oxygen concentration, volumetric mass transfer coefficient (ak_L), and water temperature, were evaluated under different operational scenarios. The oxygenation system was powered by solar energy and included rotating fine-bubble generators mounted on a floating platform. Mathematical modeling carried out in MATLAB validated the theoretical models, showing how environmental factors such as temperature and bubble size influence oxygen dissolution. Initial experimental data, including dissolved oxygen levels (C₀ = 3.12 mg/dm³), saturation concentrations at various temperatures (Cs = 8.3 mg/dm³ at 24 °C; Cs = 7.3 mg/dm³ at 30 °C), and a mass transfer coefficient of ak_L = 0.09 s⁻¹, were used to support the model accuracy. The results highlight the potential of digitally controlled energy-efficient aeration technologies for applications in lake restoration, aquaculture, and sustainable water management. This paper introduces a coupled approach to oxygen transfer and temperature evolution validated experimentally, which has rarely been detailed in the literature. The novelty of this study lies in the combined thermodynamic modeling and exergy–entropy analysis along with real-time tracking, showing the relevance of energy-optimized, digitally monitored oxygenation platforms powered by solar energy.

The transition towards a sustainable and renewable energy future is essential to mitigate climate change and reduce greenhouse gas emissions. Small–medium combined heat and power (CHP) systems are increasingly popular for distributed energy generation, as they offer improved energy efficiency and reduced emissions compared to traditional power generation systems. This article reviews recent research articles related to small–medium CHP systems, including their role in renewable energy systems, use of biofuels, steam injection, diagnostics, and carbon capture. Throughout the research, the high potential of coastal regions has been observed and studied as a solid base for the later development of CHP systems. Based on the reviewed literature, the highest potential solutions are proposed to be further investigated as an efficient, economical solution for generating electricity and heat for various small-scale applications.

This paper presents the mathematical modeling of the oxygen transfer process using partial differential equations (PDEs). This process is crucial in various environmental and engineering applications, such as wastewater treatment, aeration systems, and natural water bodies, in order to maintain water quality. The authors solved the typical PDE for describing the change in oxygen concentration over time and present the developed model of the differential equation with the term “source”, indicating that the model could be used to optimize oxygen transfer in various environmental and engineering applications, contributing to improved water quality and system efficiency.