Combustion Process Research Articles (Page 1)

ABSTRACT This study investigates a 2-stroke hydrogen-oxygen-steam combustion process optimized for stationary hydrogen reconversion, i.e. converting stored hydrogen from electrolysis back into electricity. A quasi-dimensional combustion model incorporating gas dynamics, thermodynamics, wall heat transfer and a fractal-based combustion scheme was developed to simulate the full in-cylinder cycle. The model was validated against experimental data from a 4-stroke hydrogen engine to confirm its predictive capability. Parametric studies show that optimized valve timing, injection, and dilution yield 54 kW per 1.3 L cylinder and 54.6% indicated efficiency − 44% higher efficiency and 105% greater power density than a comparable 4-stroke engine.

A hybrid vibrational model is developed to study the thermal properties of ozone (O3), using the molecular Pöschl-Teller (MPT) oscillator to describe the symmetric stretch mode, while treating the remaining vibrational modes with harmonic oscillators. Analytical expressions derived from the total partition function are used to compute key thermodynamic quantities: Gibbs free energy (ΔG), entropy (S), enthalpy (ΔH), and heat capacity at constant pressure (Cp). Model predictions are evaluated over a wide temperature range (300-6000K) and compared against NASA Glenn polynomial estimates and NIST-JANAF reference data using the relative error in absolute percentage (REAP). The MPT model achieves mean REAP values of 0.107% for ΔG, 0.130% for S, 1.386% for ΔH, and 3.205% for Cp, demonstrating improved accuracy, especially at elevated temperatures. These results highlight the model's enhanced ability to capture anharmonic vibrational effects in ozone, with relevance to atmospheric chemistry, combustion processes, and high-temperature aerospace applications. The symmetric stretching vibration of O3 is modeled using the molecular Pöschl-Teller (MPT) oscillator, while the bending and antisymmetric stretch modes are treated as harmonic oscillators. Rotational and translational motions are modeled using classical statistical mechanics. Closed-form expressions for the partition function and derived thermodynamic quantities are obtained analytically and evaluated across the 300-6000K temperature range. Model performance is assessed using the relative error in absolute percentage (REAP) by comparing predictions with those from the NASA Glenn polynomial method and NIST-JANAF tabulations. All numerical evaluations and visualizations are performed using custom MATLAB scripts.

Abstract Carbon nanoparticles are synthesized by a controlled combustion process of Ghee (dairy-based fat) in a specially designed chamber. The carbon particles are deposited on quartz and silver substrates located at a height of 5mm from the tip to gain maximum yield. The X-ray Diffraction (XRD) pattern has confirmed the formation of a disordered layered structure leading to an amorphous phase. The surface morphology obtained using Field Emission- Scanning Electron Microscope (FE-SEM) and High Resolution-Transmission Electron Microscopy (HR-TEM) have revealed a homogeneous distribution of 50-60nm sized carbon nanoparticles. The disordered and graphitic nature of carbon nanoparticles is also evident from the values 0.85 and 0.92 obtained from the ratio of intensities corresponding to D and G bands of Raman active modes. The surface area of particles was determined to be 286.5 m2g-1 and 102.4 m2g-1 for silver and quartz susbstrate respectively, as determined by BET- measurements. The elemental analysis of nanoparticles carried out by X-ray photoelectron Spectroscopy (XPS), Energy Dispersive X-ray Spectroscopy (EDS), and Carbon-Hydrogen-Nitrogen (CHN) analysis has inferred that silver plays a role in synthesizing high-purity carbon nanoparticles with enhanced physical characteristics. The electrochemical studies were conducted on silver and quartz-derived carbon electrodes. As-prepared carbon nanoparticles deposited on a silver substrate (SS) are used in a successful demonstration of an Electric double-layer capacitor and in a three-electrode system, exhibiting capacitance values of 15 Fg-1 and 134 Fg-1 over 10,000 cycles and 2000 cycles, respectively. This investigation highlights low-temperature synthesis of hydrophobic carbon nanoparticles with a high surface area, utilizing a dairy-based bio-precursor and their application in successfully demonstrating an electric double-layer supercapacitor.

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.

Ducted fuel injection (DFI) is a promising technology that can modify the combustion process in compression ignition engines to mitigate soot formation. By guiding the spray through ducts, air entrainment is enhanced, promoting a more pronounced premixed combustion phase, reducing the diffusion flame, and consequently suppressing soot generation. While previous studies using constant-volume chambers and optical research engines have demonstrated the potential of DFI and the influence of injector geometry on emissions, few have implemented this approach directly in engines due to the substantial modifications required to the cylinder head. This study proposes and evaluates an alternative DFI configuration suitable for light-duty compression ignition engines, implemented without significant modifications to the engine head. Experiments were conducted in a single-cylinder research engine using a sleeve fitted to the injector, aligning the ducts with the nozzle holes. The limited space introduces constraints such as a trade-off between duct length and stand-off distance, and a duct length shorter than the theoretical liquid penetration length. Results show that the configuration with a 3.5 mm stand-off distance achieved up to a 70% reduction in soot emissions compared to the free-spray baseline, while shorter stand-off distances (2.5 and 3.0 mm) were less effective. Although DFI delays ignition, it enhances air entrainment and premixed combustion, ultimately accelerating the combustion process.

Abstract With increasing wildfire and crop residue burning, organic P in biomass burning smoke‐derived dissolved organic matters (BBS‐DOMs), as an important source of atmospheric P, plays a growingly crucial role in P cycling on the Earth's surface. However, the limited understanding of the molecular characteristics of this organic P hampers our ability to comprehend its environmental stability and cycling processes. To address this knowledge gap, this study synthesized various BBS‐DOMs and used FT‐ICR‐MS to analyze their molecular characteristics and potential environmental stabilities. Herein, CHOP compounds (the capital letters in these compound names indicate their elemental compositions) were the dominant organic P component in most BBS‐DOMs, followed by CHONP and CHONSP compounds. However, high content of N in biomass enabled CHONP compounds to become the primary component during the burning process. Furthermore, CHOP compounds exhibited higher polarity and aliphaticity, lower molecular mass and aromaticity than CHONP and CHONSP compounds. Among these compounds, CHOP compounds predominantly existed as hydrolysis‐available P (phosphate esters with three P‐O‐C/H groups), accounting for >76% of the total organic P. Differently, CHONP and CHONSP compounds exhibited comparable oxidation‐available P (containing P‐C bond or incompletely oxidized P) and hydrolysis‐available P levels. These findings suggested that CHOP compounds had a lower environmental stability and shorter turnover cycle than CHONP and CHONSP compounds. Additionally, the (cellulose + hemicellulose)/lignin ratio of biomass and the burning temperature co‐regulated the aromatic degree and available state of organic P compounds in BBS‐DOMs. This study provides critical molecular‐level insights into the biogeochemical process of atmospheric P from biomass burning.

Precise control of flue gas oxygen content is essential for stable and efficient operation in municipal solid waste incineration (MSWI) systems. However, the strong nonlinearity and time-varying characteristics of combustion processes often lead to poor performance of conventional proportional–integral–derivative (PID) and open-loop model-based control schemes. To overcome these limitations, this study proposes a hybrid intelligent closed-loop control framework that integrates the firefly algorithm (FA) and whale optimization algorithm (WOA) for adaptive tuning of control parameters under dynamic operating conditions. The proposed system comprises four coordinated modules—preset, oxygen content prediction, predictive compensation, and feedback compensation—forming an adaptive multi-layer control loop. Experimental validation was performed using real operational data from 2 × 600 t/d MSWI plant. When the operating conditions changed from stable to variable, the proposed method maintained the flue gas oxygen content at 7.78%, with an overshoot of 1.53%, a relative error of –0.094%, and a settling time of 90 s. In comparison, the MPC-based control achieved 7.75%, with an overshoot of 2.10%, relative error of –0.529%, and settling time of 100 s, while the existing plant control method achieved 7.85%, with an overshoot of 2.35%, relative error of 0.835%, and settling time of 180 s. These results indicate that the proposed FA–WOA hybrid control framework effectively improves response speed by 50%, reduces overshoot by 34.9%, and enhances control accuracy by over 80% compared with the conventional method. Moreover, the system eliminates manual adjustment and achieves stable combustion performance under fluctuating conditions, demonstrating its potential for intelligent oxygen control and automation in large-scale MSWI plants.

The gradual exhaustion of fossil fuel reserves, along with the adverse effects of their consumption on global climate, drives the need for research into alternative energy sources that can meet the growing demand in a sustainable and eco-friendly way. Among these, hydrogen stands out as one of the most promising options for the automotive sector, being the cleanest available fuel and capable of being produced from renewable resources. This paper reviews the existing literature on compression ignition engines operating in a dual-fuel configuration, where diesel serves as the ignition source and hydrogen is used to enhance the combustion process. The reviewed studies focus on engine systems with hydrogen injection into the intake manifold. The investigations analyzed the influence of hydrogen energy fraction on combustion characteristics, engine performance, combustion stability, and exhaust emissions in diesel/hydrogen dual-fuel engines operating under full or near-full-load conditions. The paper identifies the main challenges hindering the widespread and commercial application of hydrogen in diesel/hydrogen dual-fuel engines and discusses potential methods to overcome the existing barriers in this area.

In light of the urgent need to reduce greenhouse gas emissions, hydrogen has emerged as a promising alternative fuel for compression ignition engines. Considering the challenges of onboard hydrogen storage and transportation, micro hydrogen addition in marine diesel engines is a viable transitional fuel strategy. This study employs an externally heated constant volume combustion chamber (CVCC) to experimentally investigate hydrogen-diesel combustion under simulated top dead center (TDC) conditions. High-speed photography was utilized to capture the ignition and combustion processes across six injection strategies, systematically varying three key parameters: hydrogen fraction (1.5%–3% vol.), injection pressure (60–120 MPa), and fuel mass (11.27–21.51 mg). The results show that higher injection pressures advance ignition timing (IT) by improving atomization, but excessive pressure (120 MPa) causes spray-wall impingement, reducing combustion efficiency and soot production. Hydrogen addition exhibits a non-linear effect on IT – 1.5% H 2 delays ignition due to oxygen displacement, while 3% H 2 advances IT because hydrogen’s lower heat capacity enhances local temperatures. The 90 MPa condition demonstrates the largest flame area and highest heat release rate (HRR), indicating optimal combustion performance. Increased injection mass prolongs ignition delay and suppresses flame luminosity due to deteriorated air-fuel mixture quality. Hydrogen addition shows a linear influence on combustion intensity, with higher concentrations leading to stronger combustion intensity.

Osorno volcano (41.1° S, 72° W) is located in the Andean Southern Volcanic Zone. The volcano lies within a national park as part of the protected areas system. This setting provides an opportunity to compare soil microbial communities between sectors with (H) and without (NI) anthropogenic activities within a volcanic territory. To do so, we selected one of the most visited volcanoes in Chilean Patagonia to examine composition, diversity (taxonomic and phylogenetic), and co-presence and mutual exclusion interaction networks between members of volcanic soil bacterial communities. Soil DNA was extracted, and the 16S rRNA gene was analyzed by high-throughput DNA sequencing, followed by taxonomic identification. The most prevalent phylum across all sites (H and NI) was Pseudomonadota, followed by Acidobacteriota, Actinobacteriota, and Chloroflexota. Based on taxonomic and phylogenetic indices, we found that the diversity of bacteria was significantly less in the humanized area than in the non-intervened areas. Beta diversity analysis also revealed a clear separation between humanized and non-intervened soils. Additionally, a decrease in network connectivity was observed at NI sites. Our results provide clear evidence that anthropogenic factors, such as tourism, vehicle parking, and combustion processes, are key drivers shaping bacterial community structure in volcanic soils, with potential consequences for ecosystem health and the capacity to provide ecosystem services.

Light absorption and molecular composition of brown carbon in Nanjing, China: Large contribution of biomass burning and secondary formation.

Ca-ion storage enhancement of Ca-pillared vanadium oxide using a malonic-assisted solution combustion process and a novel aqueous AC//Ca(NO3)2//CaVO/C hybrid cell

Sintering and agglomeration mechanisms of Fe2O3-CaO-K2CO3 ternary system in biomass-fueled chemical looping combustion process: Experimental and molecular dynamics simulation study

The underwater explosion of aluminized explosives presents a prolonged combustion and energy release environment for aluminum powder, which significantly affects the dynamics of bubble expansion and contraction. Conventional bubble prediction models based on the detonation product equations of state (EOS) are therefore inadequate. This study employs Hexanitrohexaazaisowurtzitane (CL-20)-based aluminized explosives to perform underwater explosion experiments in a blast tank while varying aluminum content, particle size, and charge density. The bubble pulsation processes are recorded, revealing asymmetric behavior between expansion and contraction phases. A computational model for underwater explosion bubble loads of aluminized explosives is developed to quantify pulsation asymmetry. This is achieved by formulating the Jones–Wilkins–Lee–AlCombustion (JWL-AlC) EOS, which integrates aluminum combustion processes with the second-order Mach-accurate Lezzi–Prosperetti bubble dynamics equation. The results indicated that, compared to the ideal explosives, the aluminized explosives exhibit substantially shorter bubble expansion times relative to contraction times, demonstrating distinct temporal asymmetry. The proposed model shows strong agreement with experimental observations and effectively calculates the asymmetry characteristics of bubble pulsation. Within the tested ranges, increasing aluminum particle size exerts a negligible effect on bubble expansion and contraction durations. The inclusion of aluminum powder and higher charge density in the aluminized explosives extends both expansion and contraction durations simultaneously, while maintaining their asymmetric behavior.

Emissions and carbon isotopic signatures of polycyclic aromatic compounds (PAHs, OPAHs) produced by coking in China.

Influence of pre-injection of retardant fluid on the microscopic physicochemical structure of coal during the spontaneous combustion process

The influence of the secondary hydrogen injection strategy on the combustion process of jet ignition ammonia-hydrogen engines

Fabrication of a chitosan-based adhesive with high bonding performance and superior flame retardancy via embedding carbon dots to enhance its cohesion.

ABSTRACT In the study, the effect of Na2CO3 addition on the combustion process of Umutbaca coal and its ash composition was investigated. It was understood that valuable components such as Na2SiO3 and Na2SiO5 could be obtained through this reaction at 725°C. To better understand the combustion process, TG-DTG/DTA analysis, XRD, XRF, SEM-EDS, FTIR, and BET analyses were used to identify and characterize the ash produced from coal combustion with Na2CO3. The kinetics analysis parameters were obtained by Ortega method. It has been understood that the Na2CO3 addition to Umutbaca coal has a catalytic effect on its combustion process, and significantly reduced the volatilization and ignition temperatures. The activation energy of the combustion process decreased from 112.32 to 106.71 kJ/mol. XRD, SEM-EDS, and FTIR analysis displayed that SiO2 in the ash has largely transformed into silicate structures. In SEM images, it was observed that the combustion ash of coal with Na2CO3 exhibited a very different morphological structure, compared to the combustion ash of raw coal. In the FT-IR analysis, the silicate (O-Si-O) structure, which is dominant in the raw coal ash, was replaced by Na-O-Si bonds with the addition of Na2CO3.

Industrial waste-based catalysts provide a sustainable and cost-efficient solution for biodiesel production, improving yield, quality, and environmental impact. When this biodiesel is used in advanced reactivity-controlled compression ignition (RCCI) mode, it enhances the combustion process within direct injection (DI) diesel engines. These strategies effectively reduce nitrogen oxide (NOx) emissions and smoke without compromising engine performance. This study used cottonseed (Gossypium arboreum) methyl ester (CSME) as the pilot injection fuel. It was produced under optimal conditions of 2 wt% industrial waste dolomite catalyst, an 8:1 methanol-to-oil molar ratio, and heating at 55 °C for 45 min during transesterification through the response surface methodology (RSM) with central composite design (CCD). The catalytic potential of the industrial waste dolomite catalyst is validated through X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET) analyses. Next, the n-butanol was injected into the intake manifold of the diesel engine at different energy shares of 10%, 20%, and 30% using an electronic primary fuel injection (EPFI) system in the RCCI mode. The fuel blends of diesel, CSME10 (10% CSME + 90% diesel), CSME20 (20% CSME + 80% diesel), and CSME100 (100% CSME) were tested as single-fuel in conventional mode, and CSME100 + 10% n-butanol, CSME100 + 20% n-butanol, and CSME100 + 30% n-butanol were tested in RCCI mode under variable load settings. Compared to the single-fuel operation, the RCCI combustion mode improved the performance and reduced emissions characteristics for all n-butanol energy shares. Especially, the CSME100 + 30% n-butanol mixture boosts brake thermal efficiency (BTE) by 22.25% and lowers brake specific fuel consumption (BSFC) by 23.33%. The unburnt hydrocarbon (HC) and carbon monoxide (CO) emissions were slightly increased by 28.13% and 27.37%, respectively. Also, the RCCI mode could simultaneously reduce smoke opacity (up to 58.07%) and NOx emission (up to 41%) through lower peak cylinder pressure and heat release rate (HRR) at 18 kg in 100% engine load operation. Based on these analyses, it is suggested that the RCCI mode with n-butanol injection by the EPFI system shows efficient fuel combustion and significantly reduced tailpipe emissions in DI diesel engine applications.