Current trends in the development of technologies for comprehensive optimization of fuel systems in thermodynamic power equipment within smart home infrastructure reflect the integrative conceptual proposals of the specialist Artem Aleksanian, whose management and control approaches incorporate elements of artificial intelligence and artificial neural networks, while monitoring systems rely on fundamental principles of electromagnetic resonance spectroscopy. In recent years, extensive efforts by researchers and industrial practitioners have focused on identifying and selecting the most practical and efficient technical solutions aimed at optimizing the preparation and supply of fuel mixtures to the combustion chambers of thermodynamic equipment used in smart home systems. Experimental testing was conducted on diesel engines, boilers, diesel generators, gas turbines, and other types of thermodynamic equipment forming fuel supersystems and subsystems of smart home and smart industrial infrastructures. Alongside these developments, fully automated operational modes based on contactless monitoring and control systems utilizing electromagnetic resonance spectroscopy have emerged, resulting in an integrative synthesis of technical effectiveness aligned with the capabilities and interests of investment partners.

The rapid growth in the installation of new energy poses challenges to the stability of the power grid due to its volatility and intermittency. Coal-fired power plants have come to play an important role in flexible peak power regulation. Considering that the burner is the core of a pulverized coal boiler, this study proposes the application of reverse injection pulverized coal combustion technology to power plant burners to achieve better ignition and combustion stability. The results of numerical simulations combined with experimental verification indicate that for a single ignition stabilizer, recirculation zones can be formed on both sides of the primary pulverized coal pipe at the front cone, and a high-temperature flame is ejected at high speed at the outlet. As the secondary air temperature increases from 373 K to 533 K, the axial length of the high-temperature recirculation zone increases, corresponding to an increase in the average outlet flame temperature from 1510 K to 1672 K. Under different loads of the main pulverized coal burner, the high-temperature flame ejected from the stabilizer can quickly encounter and mix with the surrounding main pulverized coal airflow, thereby igniting it rapidly. This process establishes a high-temperature flame zone within the two-stage combustion chamber, demonstrating strong adaptability to load fluctuations. As the burner load decreases, the outlet airflow velocity decreases significantly and the high-speed zone area shrinks, and the two adjacent high-temperature zones initially formed at the outlet gradually merge into a larger high-temperature zone. Simultaneously, the upward deflection of the jet at the outlet weakens.

The persistent operation of rotating detonation engines (RDEs) is severely constrained by intense combustion chamber vibrations and excessive noise emissions. Existing research on engine noise has been predominantly confined to experimental investigations of noise generation mechanisms and sound pressure levels, leaving critical gaps in predictive modeling. To address this, this study employs a numerical methodology for analyzing transient flow fields within the combustion chamber, enabling systematic characterization of vibration-coupled noise phenomena. Leveraging this computational approach, we elucidate the spectral and directivity features of vibration-induced noise. Subsequently, parametric studies identify key factors governing vibrational and acoustic responses. The results demonstrate strong agreement between simulated noise profiles and prior experimental data, confirming the model's predictive capability. Notably, the acoustic radiation exhibits pronounced directionality, with dominant emissions concentrated in specific azimuthal orientations. Furthermore, the parametric analysis yields actionable insights for structural optimization, including recommendations for chamber design parameters. These findings provide a theoretical foundation for mitigating vibration and its resultant acoustic emissions, thereby supporting future advancements in the performance and durability of RDEs.

Enhancing the operability of next-generation combustion devices with emerging fuels at near-limit conditions requires the development of innovative ignition strategies. To address this need, a new modular plasma-coupled rapid compression machine (PRCM) featuring a mono-piston, single-stroke configuration was developed to support auto-ignition, conventional spark-ignition, and non-equilibrium plasma-assisted ignition studies within a single experimental platform. The PRCM attains end-of-compression pressures up to 70bar and temperatures up to 1200K, enabling systematic investigation of ignition phenomenon and the effects of non-equilibrium plasmas on fuel reactivity at regimes inaccessible to previous platforms. A high-voltage pulse generator delivers up to 20kV pulses at repetition rates up to 100kHz, producing kilohertz repetitive nanosecond pulsed (KRNP) discharges at elevated pressures in the combustion chamber. Integrated diagnostics include high-speed pressure transducers and optical access to enable time-resolved measurements of ignition delay, burn rate, and kernel and plasma morphology to probe for plasma-combustion coupling. Initial benchmarking with methane and n-butane mixtures demonstrated good agreement with auto-ignition data from the literature, validating the PRCM's functionality and measurement fidelity. Preliminary KRNP studies at 10bar revealed a nearly 20% increase in burn rate compared to conventional spark ignition for n-butane, highlighting the efficacy of pulsed plasma in enhancing fuel reactivity and ignition kernels. This novel experimental facility offers a versatile, high-fidelity platform for investigating the fundamental processes by which non-equilibrium plasmas initiate, control, and accelerate combustion. These insights are expected to guide the design of optimized plasma-based ignition strategies for advanced air-breathing propulsion and power systems.

Simulation of particulate flows in combustion chambers of solid rocket motors with multiscale model

Characterization of a LOX/natural gas liquid-centered swirl coaxial injector element in an optically accessible combustion chamber

Design and optimization of injector heads for combustion chamber of small-scale liquid-fuel rocket engine

Thermal–mechanical coupling analysis of ceramic heat insulation tiles in gas turbine combustion chambers

Utilization of catalytically cracked waste transformer oil in compression ignition engines: Effects of combustion chamber geometry on efficiency and emission characteristics

To investigate the influence of initial instability waves on the secondary atomization of a rotating conical liquid sheet, this study adopted a numerical simulation method. By varying the initial velocity of the liquid sheet to simulate the initial instability waves, the effects of sinusoidal fluctuating velocities under different frequencies and amplitudes on secondary atomization were investigated. The research demonstrates that the characteristic parameters of secondary atomization undergo regular changes with increases in the frequency and amplitude of the initial velocity fluctuations of the liquid sheet. Furthermore, the direction of these changes (increase or decrease) periodically reverses depending on the axial position or the moment of observation. The initial velocity fluctuations of the liquid sheet form ring-shaped droplet-dense regions along the axis of the spray field. Variations in frequency and amplitude lead to changes in the droplet number distribution within each droplet-dense region, as well as alterations in the droplet distribution on the inner and outer sides of the spray cone in the radial direction. In addition, the influence of the velocity fluctuation frequency on the secondary atomization characteristics and the spatial distribution characteristics of the droplets is significantly greater than that of the amplitude. This study provides insights for regulating the droplet size and spatial distribution characteristics of the spray field, contributing to reliable prediction and control methods for the design of high-performance advanced combustion chamber nozzles.

This study employs CFD simulations carried on ANSYS Fluent 2022 R1 (ANSYS Inc., Canonsburg, PA, USA), to address the design, development, and thermodynamic analysis of a biomass burner, based on mass and energy balances, combustion efficiency, flame temperature, and thermodynamic properties. The prototype incorporates a flow deflector located before the combustion chamber. This component improves the air-fuel mixture to maximise thermal efficiency and minimise pollutant emissions. The burner is specifically designed to use sawdust as fuel and is intended for industrial applications such as heating or drying processes. The integration of the flow deflector results in uniform, complete combustion, achieving 90% thermal efficiency and an adjustable thermal power output of 0–100 kW. Compared to conventional burners, this design reduces CO emissions by 20% and NOx emissions by 15%, demonstrating significant environmental improvements. The design methodology is based on mass and energy balance equations to evaluate combustion efficiency as a function of the stoichiometric ratio, along with experimental testing. These experimental tests were conducted using an ECOM (America Ltd., Nashua, NH, USA) gas analyser and anemometer. The internal temperature was monitored with a K-type thermocouple (Omega Engineering Inc., Norwalk, CT, USA). The results confirmed the positive influence of the structural design on thermal performance. The proposed burner aims to maximise heat generation in the combustion chamber, offering an innovative alternative for biomass combustion systems.

This study presents a finite element method (FEM) analysis of the connecting rod - piston assembly used in internal combustion engines. The study includes static, modal, and harmonic response analyses to evaluate the structural integrity and dynamic behavior of the assembly under realistic operating conditions. The static analysis investigates the distribution of stresses and deformations under the maximum pressure in the combustion chamber, verifying the strength and stiffness of the components, while the modal analysis determines the natural frequencies and mode shapes, which are essential for avoiding resonance phenomena. The harmonic response analysis evaluates the dynamic behavior under periodic excitations, highlighting critical frequencies where vibrational amplification may occur. The results show that the assembly has adequate structural stiffness, stable dynamic behavior with natural frequencies outside the engine’s operational range, as well as effective damping properties, ensuring durability and reliability. This integrated FEM approach provides a solid foundation for optimizing the design and performance of engine components subjected to complex loads.

With the increasing power output of aero-engines, combustor hot-gas mass flow rate and temperature continue to rise, posing more severe challenges to combustor structural cooling design. To enhance the film-cooling performance of the Z-profile feature in a reverse-flow combustor, this study performs a multi-parameter numerical optimization by integrating computational fluid dynamics (CFD), a radial basis function neural network (RBFNN), and a genetic algorithm (GA). The hole inclination angle, hole pitch, row spacing, and the distance between the first-row holes and the hot-side wall are selected as design variables, and the area-averaged adiabatic film-cooling effectiveness over a critical downstream region is adopted as the optimization objective. The RBFNN surrogate model trained on 750 CFD samples exhibits high predictive accuracy (correlation coefficient (R > 0.999)). The GA converges after approximately 50 generations and identifies an optimal configuration (Opt C). Numerical results indicate that Opt C produces more favorable vortex organization and near-wall flow characteristics, thereby achieving superior cooling performance in the target region; its average adiabatic film-cooling effectiveness is improved by 7.01% and 9.64% relative to the reference configurations Ref D and Ref E, respectively.

An increase in global energy demand results in coal dependance which contributes to greenhouse gas emissions. Poultry litter is a potential substitute, but its poor physicochemical and combustion properties reduce its combustion efficiency; hence, demineralization and pyrolysis to biochar value-adds. The study analyzed the characterization of biochar derived from demineralized PL and selected the best-suited combustion technology. The PL was mechanically fractioned (4 mm) and leached in deionized water and pyrolyzed (300 ℃; 15 min). The biochar physicochemical properties improved the higher heating value (22.31 MJ kg-1) and reduced the Ash Content (18.63 %) compared with undemineralized biochar. Increase in TGA/DTG heating rate shifted the reaction region to high temperature (58.57–548.93 ℃) reducing the ease of ignition and combustion. The biochar has high fouling and slag tendency, and the fluidized bed combustion chamber was the preferred chamber technology. Mass of air at 7.83 kg kg-1 fuel is required to combust the biochar and produce 3.26 kg kg-1 fuel of flue gas. Flue gas produced with 25 % excess air produced a higher enthalpy than stoichiometric conditions, attaining a thermal efficiency of 86.20 %. Demineralized PL biochar exhibits excellent physicochemical and combustion properties making it an ideal fuel candidacy.

It has long been known that inlet port geometry plays a crucial role in regulating in-cylinder flow processes, significantly affecting combustion efficiency and engine emissions. This paper elucidates the effects of an intake port geometry modification, specifically the implementation of a novel moving deflector to intensify tangential intake flow, on fluid flow patterns, combustion stage, and exhaust emissions in a spark-ignited internal combustion engine. The analysis was performed using multi-dimensional numerical modeling of reactive flow, where the numerical domain was extended to the complete intake system to explicitly encompass the modification. The numerical model was validated against experimental data, showing excellent agreement, with differences in peak in-cylinder pressure and peak rate of heat release (RHR) kept below 3% and the moment of peak pressure being nearly identical to the experimental results. During the induction stroke, the effects of implemented modification through intensification of intake jet were clearly legible, pursued by deflection of smaller side vortices in the vicinity of the bottom dead-center. During compression, the attenuation of the effects of the earlier established macro flow was encountered and some negative effects of the increased intake jet were elucidated. During combustion the existence of “flame dominated fluid flow” controlled primarily by turbulence diffusion was encountered. Negative effects on exhaust emissions were elucidated as well. As the combustion process in spark ignition internal combustion engines is primarily controlled by turbulent diffusion, proper identification of influential types of organized flows is a challenging but very important task. The advantages offered by the application of numerical modeling in these situations are clear.

This LPG gas-fueled metal heating furnace is designed to support heat treatment and metal smelting processes in small to medium-scale industries. With dimensions of 50 × 90 × 67 cm, this furnace is equipped with a 3600 RPM Sumura burner and blower to improve combustion efficiency and even heat distribution. The wall structure consists of SK32 firebrick, a fireproof blanket, caliboard, and an iron plate as outer protection. This layered insulation system aims to contain the heat in the combustion chamber so that it does not propagate out excessively. Tests showed that the combustion chamber temperature (T6) reached 1023°C in 60 minutes. The temperature decreases gradually from the inner to the outer layers: T5 (SK32 brick) 832°C, T4 (outer brick) 69°C, T3 (fiber blanket) 49°C, T2 (clapboard) 45°C, and T1 (iron plate) 43°C. The total heat transfer by conduction was recorded at 20.671 kW. These results show that the layered insulation design is effective in maintaining thermal efficiency and improving user safety. This furnace design has great potential to be applied in metal heat treatment activities by small industry players because it is energy efficient, easy to control, and economical. This research also opens up further development opportunities, such as the integration of an automatic control system and optimization of the shape of the combustion chamber.

Biogas, a promising fuel for present and future generations, is produced from the anaerobic digestion of organic waste generated by the condominium itself. Therefore, this work aims to evaluate the exergoeconomic performance of a biogas cogeneration unit designed to meet the electrical and thermal energy demands of a residential condominium in the city of Teresina, Piauí, Northeast Brazil. The cogeneration unit consists of an internal combustion engine (ICE) coupled to an electric generator (genset) to produce electricity, and a heat exchanger that recovers part of the exhaust-gas heat to heat water. The analysis was conducted based on the concepts of Thermodynamics and Exergoeconomics, using the SPECO (Specific Exergy Costing) methodology to define the exergetic costs of the system. The novelty of the work lies in applying the SPECO exergoeconomic analysis to a small-scale biogas cogeneration unit fueled by residential organic waste. The achieved electricity production was 167.40 kW, and the heat transfer rate at the exchange rate was 51.55 kW. The results revealed that the exergy destroyed in the internal combustion chamber (ICE) was 223.65 kW, whereas that in the heat exchanger was significantly higher at 45.67 kW. The exergy efficiency of the ICE reached 39.19%, and the heat exchanger efficiency was around 9%. In financial terms, the cost of exergy destroyed in the ICEC was USD/h 135, but in the heat exchanger, it was dramatically higher at USD/h 158.40. The cost of producing hot water (product) was considered extremely high (USD/GJ 38.98). The relative difference parameter in the heat exchanger also has a value much higher than expected (10.240). This is because the product’s cost (USD/GJ 38.98) is well above the cost of fuel (USD/GJ 3.468). This study concludes that the cogeneration unit is more justifiable by the savings generated through thermal energy production than by electricity production alone, since the cogeneration system significantly enhances performance, raising both the energetic and exergetic efficiencies to 55% and 48%, respectively, thereby confirming the added value of the simultaneous utilization of heat and power.

Abstract The optimization of gas turbine combustion chamber design has gained significant importance due to the complexity of combustion processes, temperature distribution, and pollutant emissions. To optimize three key geometric parameters of the combustion chamber simultaneously, a hybrid approach that combines numerical modeling, artificial neural networks (ANNs), and a modified multi-objective genetic algorithm (NSGA-II) is proposed. The reduction of non-volatile particulate matter (nvPM) emissions is regarded as one of the most critical pollution concerns, even though gaseous pollutants such as CO and NOx are also important. To simulate the combustion chamber in the initial phase, a chemical reactor network (CRN) is employed, followed by training the ANN with results from the numerical model. The modified NSGA-II multi-objective genetic algorithm is used to simultaneously optimize the previously mentioned parameters to enhance combustion and thermal performance while minimizing pollutant emissions, particularly nvPM. To identify the optimal final solution, TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) applies multi-criteria decision-making. As a result of this approach, CO emissions are reduced by 7.1%, NOx by 4.9%, and nvPM emissions by 16% simultaneously, compared to the initial values. This method can lead to the development of gas turbine combustion chambers with higher efficiency and lower emissions.

This paper presents new results of computational experiments to study the influence of various methods of fuel input (straight flow and vortex with a flow deflection angle of the pulverized coal stream) across the firing systems on combustion processes utilizing the BKZ-75 boiler combustion chamber case of the Shakhtinskaya TPP (Kazakhstan), fluidized combusting Karaganda coal with high ash content. According to the results of computational combustion modeling, the following results were derived: the total velocity vector distributions, spatial distributions of temperature, and concentrations of carbon oxides and nitrogen dioxide (NO₂) within the full volume through the combustion zone and at the chamber’s discharge. It has been appeared that the vortex strategy of providing the discuss blend makes it conceivable to enhance the method in the combustion of high-ash coal, as in this case there's an increment in temperature within the center of the burn and a lower temperature observed at the combustion zone outlet, which features a noteworthy effect on the chemical forms of the arrangement of reaction products formed during combustion. When employing vortex burner devices, the concentration levels at the combustion outlet zone for carbon monoxide (CO) decrease by about 15 %, and for nitrogen dioxide (NO2) by roughly 20 % relative to direct‑flow burner devices. The comes about gotten make it conceivable to create proposals for the advancement of ideal strategies for managing flame structure and combustion dynamics of a pulverized coal burn to extend the productivity of vitality offices and decrease emanations of hurtful substances into the environment.

Gas turbines are essential for high-power energy generation, but growing demands to reduce NOₓ and CO₂ emissions make traditional combustion chamber design increasingly complex and costly. This work proposes a new modeling paradigm that combines high-fidelity Computational Fluid Dynamics using neural network learning to accelerate emission prediction. A Computational Fluid Dynamics model was developed using the Reynolds-averaged Navier-Stokes equations with the k–ε turbulence model and a non-premixed Probability Density Function approach to simulate turbulent methane combustion. NOₓ emissions were calculated post-simulation using the Zeldovich mechanism. Model validation included varying fuel flow, excess air ratio, and wall heat loss. To speed up evaluations, a multilayer perceptron neural network was trained on Computational Fluid Dynamics results to predict NOₓ and CO₂ emissions based on key inputs (fuel rate, air excess, temperature, pressure, cooling). The model achieved high accuracy with a coefficient of determination (R^2) of 0.998 for NOₓ and 0.956 for CO₂ on an independent test set. Results showed good agreement with both experimental data and a Network of ideal reactors model using detailed kinetic scheme of methane combustion - Mech 3.0. This neural network serves as a fast surrogate model for emissions assessment, enabling rapid optimization of low-emission combustor designs. The approach is suitable for digital twins and combustion control systems and is adaptable to alternative fuels like hydrogen and ammonia.