Combustion Optimization Research Articles

The Effect of Heterogeneous Natural Gas–Hydrogen Input Into F-Class Gas Turbine Combustor As a Combustion Optimization Method

Abstract The global push to combat climate change by transitioning to clean power generation is accelerating. One promising avenue involves using hydrogen in place of natural gas in gas turbine-based power plants. While the development of new hydrogen combustors shows potential, advancements in operational technologies are needed to ensure higher hydrogen cofiring with existing combustion systems. In our study, we propose a novel approach called heterogeneous natural gas–hydrogen input: varying hydrogen content between different nozzle groups in gas turbine combustors. Using a full-scale combustor of an F-class gas turbine model, we experimentally investigated the impact of heterogeneous hydrogen concentrations at the center and outer nozzles on combustion dynamics and emissions, comparing these with homogeneous fuel supply cases of 100% natural gas and natural gas–hydrogen mixtures. While hydrogen cofiring did not change the maximum amplitude of combustion dynamic pressure across the total frequency range, peak amplitudes in the 125–245 Hz domain were linearly proportional to the hydrogen cofiring ratio, with a 41.2% increase at 30% cofiring identified as a possible limiting factor. Our findings revealed a significant correlation between NOx emissions and combustion stability under varying levels of heterogeneity. Higher heterogeneity with intensive hydrogen input into the center nozzle improved cofiring performance, reducing the peak amplitude in the limiting frequency domain by 22% for a 25% cofiring ratio, potentially extending the critical hydrogen cofiring ratio. Implementing heterogeneous natural gas-hydrogen inputs emerges as a promising method to enhance combustion stability and enable effective hydrogen cofiring.

Numerical Investigations on Reducing Unburned Hydrocarbon and Carbon Monoxide Emissions in Reactivity-Controlled Compression Ignition Using Partial Reactivity Stratification with Alternative Fuels and Additive

<div>A numerical investigation has been performed in the current work on reactivity-controlled compression ignition (RCCI), a low-temperature combustion (LTC) strategy that is beneficial for achieving lower oxides of nitrogen (NO<sub>x</sub>) and soot emission. A light-duty diesel engine was modified to run in RCCI mode. Experimental data were acquired using diesel as HRF (high-reactivity fuel) and gasoline as LRF (low reactivity fuel) to check the accuracy and fidelity of predicted results. Blends of ethanol and gasoline with DTBP (di-tert-butyl peroxide) addition in a small fraction on an energy basis were used in numerical simulations to promote ignitability and reactivity enhancement of PFI charge. Achieving stable, smooth, and gradual combustion in RCCI is challenging at low loads, especially in light-duty engines, due to misfiring and poor combustion stability. DTBP is known for enhancing cetane number and accelerating combustion, and it is mixed in a PFI blend to avoid combustion deterioration. The factors governing reactivity stratification to achieve optimal combustion phasing were investigated in the present study. DTBP decomposition and its low-temperature oxidation chemistry were found to be responsible for affecting combustion phasing, heat release patterns, and emission trends. DTBP additive and different in-cylinder strategies were applied and studied to reduce unburned emissions. Adopting a multiple injection approach utilizing dual-pulse assisted in reducing HC and CO levels. It enhances combustion quality by providing adequate control over combustion phasing. Altering operating parameters like intake temperatures reduced HC, CO, and soot emissions by 97.6%, 57.6%, and 52.8%, respectively, compared to baseline gasoline/diesel RCCI data. Optimizing the injection timings of the first and second pulse helps achieve optimal combustion phasing and a 72.95% reduction in NO<sub>x</sub> emissions. The higher injection pressure of DI helped lower the CO and soot emissions by 53.33% and 51.84%, respectively.</div>

Parametric study of combustion characteristics of diesel/methanol dual fuel engine using global sensitivity analysis and multi-objective optimization

The pursuit of clean and efficient internal combustion engine power necessitates the substitution of fossil fuels with methanol and the adoption of advanced combustion strategies. This study examines the combustion and emission characteristics of methanol/diesel dual-fuel compression ignition engines. To understand the intricate interplay between critical parameters and engine performance, the global sensitivity analysis (GSA) method is employed, utilizing Sobol sensitivity as the quantitative metric. The investigated parameters include methanol substitution rate, diesel injection parameters, and five thermodynamics parameters concerning in-cylinder conditions. A validated computational fluid dynamics (CFD) model, coupled with a chemical kinetic mechanism, is developed to predict the combustion behavior of the dual-fuel engine accurately. This predictive capability forms the basis for utilizing the tree-based process optimization (TPOT) algorithm. By implementing TPOT, a significant reduction in the mean square error (MSE) of the predicted characteristics model is achieved, averaging a decrease of 73.59%. Subsequently, a multi-objective optimization is conducted, exploring the impact of varying target weights on the optimal outcomes. Results show the initial pressure significantly impacts the engine's economy, power and emission characteristics, and NOx formation should be carefully considered in the combustion optimization of dual-fuel engines.

An advanced high dimensional model representation approach for internal combustion engine modeling and optimization

This work introduces an efficient data-driven approach for engine performance modeling and optimization. A highly accurate and robust high-dimensional model representation (HDMR) surrogate model is developed based on the dataset generated from a coupled KIVA4-CHEMKIN Ⅱ software. The HDMR model is integrated with a multi-objective optimization algorithm, enabling the automatic identification of optimal combustion strategies. Results suggest that the constructed HDMR model is able to accurately predict the engine performance and exhaust gas emissions with negligible CPU costs. Moreover, the model effectively identifies optimal engine operating conditions, leading to enhanced fuel efficiency.

A Review of Recent Developments in Hybrid Rocket Propulsion and Its Applications

This paper extensively reviews hybrid rocket propulsion-related activities from combustion engine designs to launch tests. Starting with a brief review of rocket propulsion development history, a comparison among the three bi-propellant rocket propulsion approaches, and hybrid rocket engine design guidelines, a very thorough review related to hybrid rocket propulsion and its applications is presented in this paper. In addition to propellant choice, engine design also affects the hybrid rocket performance and, therefore, a variety of engine designs, considering, e.g., fuel geometry, swirl injection, ignition designs, and some innovative flow-channel designs are also explored. Furthermore, many fundamental studies on increasing hybrid rocket engine performances, such as regression rate enhancement, mixing enhancement, and combustion optimization, are also reviewed. Many problems that will be encountered for practical applications are also reviewed and discussed, including the O/F ratio shift, low-frequency instability, and scale-up methods. For hybrid rocket engine applications in the future, advanced capabilities and lightweight design of the hybrid rocket engine, such as throttling capability, thrust vectoring control concept, insulation materials, 3D-printing manufacturing technologies, and flight demonstrations, are also included. Finally, some active hybrid rocket research teams and their plans for flight activities are briefly introduced.

CFD Modelling and Optimization of Solid Waste Combustion in a 1 MW Fixed Bed Combustion Chamber

The global population and energy consumption grow each year. Therefore, the tendency to use biofuels instead of fossil fuels assist the global requirement. Also, enhancing of the combustion efficiency and minimizing pollutant emissions during the combustion of municipal solid waste (MSW). The present study employed a CFD model to simulate solid fuel combustion in a grate combustion chamber which was commonly used in small-capacity boilers. computational fluid dynamics technique was used to simulate complex solid fuel reactions where 1 MW boiler was supposed for wood and coal combustion. The achievements found that 10%-dried MSW was used as fuel. The results of the study were related to the average gas flow temperatures and composition in the furnace outflow section, as well as the high combustion temperatures of fossil fuels. The results for the average temperature and average chemical molecular fractions (CO, O2, CO2, H2O, and N2) generated at the exit of the combustion process were positive. Thus, it was found that the thermal efficiency of the boiler was significantly affected by the amount of air supplied to the system at a temperature of 273 K and atmospheric pressure. We observed variations in flame morphology, temperature profiles, and corresponding numerical values.

Effects of inlet air holes on swirl flow characteristics and outlet temperature distribution in an axial swirl combustor

The air inlet holes on the swirl combustor are crucial for high-performance micro gas turbine (MGT), affecting internal airflow, fuel-air mixing, temperature distribution, and cooling. However, there are seldom studies that pay attention to the influence of the air inlet holes coupled with low volatility macromolecular fuels for fast and better fuel-air mixing and combustion processes in MGT. This study investigates the influence of primary and dilution hole positions on airflow, temperature, emissions, and combustion efficiency. Numerical simulations in ANSYS Fluent examine five inlet hole configurations in a two-stage axial swirl combustor. Simulation validation is conducted under three test conditions. The results showed that the cut-off effect of the primary hole affected the size of the swirl vortex core, and the backward movement of the primary hole resulted in a significant increase in the length of the recirculation zone and the coherence high-temperature zone, accelerated the droplet evaporation rate, and reduced CO and NO emissions. Backward movement of dilution hole alters flow field, affecting swirl vortex stability and reflow intensity. Case 3, with original dilution hole and backward extended primary hole, exhibits optimal outlet temperature distribution and combustion efficiency.

Investigation of the heating characteristics of turbulent non-premixed gas combustion in the industrial-scale walking beam type reheating furnace

Oxygen-enriched combustion is widely used in industrial furnaces. To elucidate the multi-physics properties of reheating process, this study numerically explores the flow and combustion characteristics of syngas oxygen enrichment combustion in an industrial-scale walking beam type reheating furnace. The findings demonstrate that gas flow patterns at the furnace inlet primarily encompass the billet periphery, enhancing heat transfer efficiency. Oxygen-enriched combustion achieves lower temperature differences, higher heating temperature and CO2 emissions. Additionally, increasing levels of oxygen enrichment correlates with elevated temperatures, though the increments diminish progressively. Specifically, temperatures at the outlet of the preheating section range from 1100 K to 1200 K, with the middle region of the heating section displaying slightly lower temperatures compared to the areas adjacent to the burner. High temperature zones are primarily concentrated around the burners in soaking and heating sections. In terms of heating temperature and thermal uniformity, 30 % oxygen-enriched condition yields superior performance, evidenced by higher heating temperatures and reduced temperature differentials. Moreover, oxygen-enriched combustion enlarges CO2 emissions, with a 124.5 % enhancement observed. The lowest NO emission content at the outlet occurs during combustion with 21 vol% air and 45 vol% oxygen enrichment, however, these values remain relatively high. The insights derived from this study provide a foundational framework and guiding principles for furnace design and optimization of multi-gradient oxy-enriched combustion.

Revolutionizing waste from household plastics to eco-friendly diesel alternatives through catalytic degradation with biogas utilization

The study tackled the pressing environmental issue of managing both biodegradable and non-biodegradable household plastic waste, aiming to convert this waste into valuable hydrocarbons, thus addressing critical concerns over plastic pollution and the quest for renewable energy sources. In the context of escalating environmental degradation and the urgent need for sustainable alternatives to fossil fuels, the ability to transform various forms of waste into energy presents a significant stride towards ecological and energy sustainability. Utilizing an innovative methodology, the research employed catalytic degradation of mixed plastic waste, leveraging fly ash as a catalyst and biogas produced from a combination of cow dung and kitchen waste as a renewable and sustainable heat source. This process was fine-tuned across several catalyst-to-polymer (cat/pol) ratios, specifically 0.10, 0.15, and 0.20, with detailed documentation of the degradation temperatures and yields of liquid and gaseous hydrocarbons for each 1 kg batch of plastic waste. Notably, at a cat/pol ratio of 0.20, a remarkable 100% conversion rate was achieved, highlighting the efficiency of this method. Following this, the resultant oil was segmented based on boiling points for further analysis and evaluation of its utility as a diesel fuel substitute. Significant findings include the highest liquid hydrocarbon yield of 65.1% at 378 °C, achieved with the 0.20 cat/pol ratio. Moreover, fractions boiling above 100 °C were identified to possess superior heating values and cetane numbers compared to conventional diesel, particularly the fraction boiling at 100 °C–150 °C (C2), which demonstrated optimal performance and combustion qualities. This fraction achieved a maximum brake thermal efficiency of 32.92%, exhibited low smoke density and hydrocarbon emissions of 48 HSU and 32ppm, but it also resulted in a significant increase in NOx emission. Among all the fractions, diesel C2 was observed to be the best in terms of performance & combustion and was lower in emission. The conclusions drawn underscore the method’s potential to mitigate plastic pollution and reduce fossil fuel reliance by converting both biodegradable and non-biodegradable waste into useful energy. This study’s novelty lies in its comprehensive approach to waste management and energy recovery, significantly advancing over previous literature by achieving a 100% conversion rate at a specific cat/pol ratio and optimizing the output for use as a diesel alternative. It stands out by producing a fraction with both high efficiency and lower emissions, offering a scalable, sustainable solution to waste management challenges and paving the way for future innovations in sustainable energy production.

Advanced orthogonal analysis of multi-factorial interactions influencing co-combustion performance and pollution reduction potential of coal gangue and biomass in oxy-fuel combustion conditions

In the current scenario of increasing energy scarcity and stricter environmental protection requirements, the utilization of coal gangue and biomass energy is gaining attention worldwide. Biomass and coal gangue are complementary in nature, and their co-combustion can improve the burnout efficiency of coal gangue and reduce pollutant emissions. In this study, coal gangue and wheat straw are selected as research subjects, the optimal process conditions for their co-combustion under the coupling of multiple parameters in oxy-fuel atmosphere through orthogonal experiments are investigated. The results indicate that the most significant factor influencing combustion characteristics is the heating rate. When the biomass content is 45 %, O2 concentration is 50 %, heating rate is 30℃/min and particle size is 180–250μm, the flammability and comprehensive combustion indexes of the samples are maximized, which indicates the optimum combustion characteristics. The primary factor affecting pollutant release is biomass content. When the biomass content is 45 %, O2 concentration is 75 %, combustion temperature is 700℃, and particle size is 180–250μm, the pollutant release concentration is minimized.

Numerical analysis of NOx reduction in large-scale MSW grate furnace through in-bed combustion optimization using multi-section fuel bed model with thermally thick treatment

This study focuses on reducing NOx emissions in large-scale municipal solid waste (MSW) grate furnaces through in-bed combustion control. A multi-section fuel bed model with thermally thick treatment is developed to accommodate the configurations of large-scale MSW grate furnaces. The model incorporates detailed sub-grid models to simulate the intraparticle gradient, and the stochastic mixing is accounted to deal with the multi-section fuel beds with vertical drop-offs. The influences of primary air distribution and average grate velocity on combustion status and NOx emissions are investigated numerically and validated in a 600 t/d MSW grate boiler. The results indicate that combining a relatively low primary air ratio with a thickened fuel bed ensures both reduced NOx emissions and high burnout efficiency. By reducing the excess air ratio of primary air from 1.2 to 0.9 and distributing it through a rear-enhanced air mode, the overall NOx emission decreased from 398.50 mg/Nm3 to 215.05 mg/Nm3, although at the expense of an increased unburned carbon content from 1.995 wt% to 3.063 wt%. Further lowering the grate velocity to thicken the fuel bed allowed for leveraging the heterogeneous reduction effect of the char layer, reducing the NOx emissions to 184.95 mg/Nm3. Additionally, the unburned carbon content was also remarkably reduced to 1.560 wt%. The proposed strategies of delaying the primary air supply and thickening the fuel bed offer a cost-effective alternative to post-combustion measures, with which the MSW grate boilers can achieve lower NOx emissions while maintaining efficient and stable combustion.

Optimization of direct-injection ammonia-diesel dual-fuel combustion under low load and higher ammonia energy ratios

Ammonia (NH3), as a potential zero-carbon fuel, has garnered significant attention for its application in compression ignition (CI) engines. Due to the low reactivity, ammonia is primarily used as dual fuel in CI engines. Therefore, the decarbonization potential is influenced by the ammonia energy ratio (AER). In this study, experimental research was conducted on expanding the AER at low load conditions in a direct-injection ammonia-diesel dual-fuel engine. The ammonia post-injection strategy was explored and significantly improved the suppression effect of high-concentration ammonia on diesel ignition, which could advance ignition timing and increase the peak heat release rate. As a result, coupled with intake heating, it expanded AER to 86 % at an indicated mean effective pressure (IMEP) of 4 bar. This strategy also increased the indicated thermal efficiency (ITE) by 8 % and significantly reduced unburned ammonia emissions. However, the combustion and emission performance was limited by the post-injection ammonia quantity and the injection timing of both diesel and ammonia, especially under high AER conditions.

Combustion characteristics and flame development of ammonia in an optical spark-ignition engine

To meet the ever-increasing serious challenges of global energy shortages and environmental pollution, it is urgent to apply alternative carbon-free fuels in the transportation field to reduce global carbon dioxide emissions. Ammonia is considered a prospective carbon-free fuel for engines due to its advantages in production, storage and transportation. The combustion and flame development characteristics of ammonia at different excess air ratios (λ) were researched in an optical spark ignition (SI) engine employing high-speed natural flame luminosity (NFL) imaging, OH* chemiluminescence imaging and flame spectra measurement. The combustion performance and flame development of ammonia were compared with methane. Results indicate that ammonia has the optimal combustion performance at λ = 0.9, with the most concentrated heat release, the highest power output and the best combustion stability. The peak natural flame luminosity intensity is highest at λ = 0.9, and the flame speed of 13.7 m/s is the fastest among testing cases, which results in the shortest ignition delay and combustion duration. OH* and NH2* spectra intensity of the ammonia flame were quantified and analyzed under different λ. The peak OH* intensity is highest at λ = 0.9, while the largest intensity of NH2* is obtained at the fuel-rich case (λ = 0.8). The maximum overall OH* chemiluminescence intensity at the same crank angles is obtained at λ = 0.9. Finally, despite the delayed spark timing, the combustion performance of methane presents higher indicated mean effective pressure (IMEP) and better combustion stability as well as faster flame propagation speed than ammonia at the same λ. In summary, ammonia shows the best combustion and flame development characteristics at λ = 0.9. The combustion performance of ammonia in SI mode is significantly worse than that of methane.

Prediction of NOx Emissions in Thermal Power Plants Using a Dynamic Soft Sensor Based on Random Forest and Just-in-Time Learning Methods.

Combustion optimization is an effective way to improve the efficiency of thermal power generation and reduce carbon and NOx emissions. Real-time and precise NOx emission prediction is the basis for combustion optimization control of thermal power plants. To construct an accurate NOx concentration prediction model, a novel just-in-time learning (JITL) method based on random forest (RF) is proposed in the present work. With this method, first, an improved permutation importance algorithm is proposed to extract important variables. In addition, a similarity index that incorporates temporal and spatial measures is defined to select a local training set representative of the process data. Moreover, considering the influence of model parameters on prediction performance under different working conditions, a process monitoring method based on a moving window (MW) is used to monitor the change in working conditions and guide online updating. The experimental results show that the proposed method has excellent prediction accuracy, with a coefficient of determination of 0.9319, a root-mean-square error of 3.6960 mg/m3, and an average absolute error of 2.7718 mg/m3 on the test set, making it superior to other traditional methods.

Investigation of biodiesel and its blends fueled diesel engine: An evaluation of the comprehensive performance of diesel engines

The carbon-neutral era and the increasing demand for energy worldwide are imperative for researching alternative energy. At the same time, biodiesel is considered one of the most prospective alternative energy due to its renewable nature and similar properties to diesel. A comparative study of the effects of different proportions of biodiesel-diesel blends (BD10, BD20, BD40, BD60, BD100) on emissions, vibration, lubricant ferrography, and tribological performance of cylinder liner-piston ring (CL-PR) of a direct injection diesel engine (ZS195) was carried out with a baseline of petroleum diesel. The results of the study demonstrated that the appropriate proportion (less than 20 %) of biodiesel significantly improves the comprehensive performance of diesel engines, primarily by combustion optimization and vibration shock reduction. The BD20 fuel blend achieves the best comprehensive diesel engine performance. The higher percentage of biodiesel results in enhanced vibration and severe degradation of CL-PR performance caused by the dilution of the lubricant and erosion of the components by the biodiesel. The study illuminates the mechanism and intrinsic connection of the effects of biodiesel on diesel engine performance. These results will facilitate the understanding of the effects of biodiesel-diesel blends on diesel engine performance and contribute to carbon neutrality in the transportation sector.

Numerical Study of Optimal Combustion in Tangentially Fired Coal Boiler 625 MW by Considering Rear Pass Temperature

Numerical Study of Optimal Combustion in Tangentially Fired Coal Boiler 625 MW by Considering Rear Pass Temperature

A shock-tube experimental and kinetic simulation study on the autoignition of methane at ultra-lean and lean conditions

Coalbed methane represents an important kind of natural gas resource in many countries. However, the low-concentration property of coalbed methane limits its applications. To gain insight into the combustion kinetics of coalbed methane and facilitate its combustion utilization, this work reports an experimental and kinetic simulation study on the autoignition properties of methane at ultra-lean and lean conditions. A shock-tube (ST) facility is used for ignition delay time (IDT) measurements with equivalence ratios at 0.5, 0.1, and 0.05 with pressure at 2 and 10 bar under the temperature ranging from 1320 to 1850 K. The measured IDTs can be correlated into a general Arrhenius expression, and the equivalence ratio effect on IDTs is then analyzed. Seven detailed chemical kinetic mechanisms are employed to predict the IDTs and statistical error indicators are used to evaluate their performance. Detailed kinetic analysis via sensitivity and reaction path analysis is performed to uncover the kinetic differences among the seven mechanisms. It is shown that some of the reaction paths only exist in the NUIGMech1.3 mechanism, while the other detailed mechanisms do not consider them. Reaction path analysis indicates that the reactions related to O2, OH and O species become more important compared to the reactions involving CH3 and H radicals as the equivalence ratio decreases from lean to ultra-lean conditions. Detailed chemical kinetics analysis is also conducted to demonstrate the uncertainty of key reactions. The present work should be valuable to gain insight into the methane ignition characteristics and to facilitate kinetic mechanism optimization of methane combustion.

Simultaneous improvements of thermal efficiencies and smoke emissions in semi-premixed diesel combustion with dual-injectors and a spatially divided combustion chamber

To simultaneously establish the high thermal efficiencies and the low smoke emissions in the semi-premixed diesel combustion with a twin peaked heat release consisting of the first-stage premixed combustion and the second-stage spray diffusive combustion, a combination of dual-injectors and a newly designed divided combustion chamber was proposed and the combustion characteristics were investigated. The divided chamber with a lip at the middle of the side wall can prevent the second fuel spray from entering the burned region of the premixture from the first-stage injection, realizing a suitable spatial distribution of spray flames and suppressing the soot formation. The dual-injectors can independently provide the fuel sprays into the upper and the lower layers of the divided chamber with the optional quantities and timings for the first and second injections, establishing the optimum combustion phasing. The distributions of the equivalence ratios and the soot formation characteristics in the divided chamber as well as in an ordinary re-entrant chamber as a reference were analysed with CFD simulations, showing that the soot formation is smaller in the divided chamber. The second-stage spray diffusive combustion is improved as well as the late afterburning and the combustion duration are reduced with the suppression of interference between the spray flames in the divided chamber. The cooling loss in the divided chamber is smaller due to the weaker gas motion and the lower heat transfer coefficient. The experiments also showed that the thermal efficiencies are better and the smoke emissions are lower in the divided chamber at medium loads. However, at higher loads, the smoke emissions increase due to the offset injector arrangement, and the CFD analysis showed that lower smoke emissions can be expected with optimization of the injector arrangement to locate the injector for the second fuel injection at the centre of cylinder.

A novel data-driven approach for coal-fired boiler under deep peak shaving to predict and optimize NOx emission and heat exchange performance

Coal-fired boilers considering deep peak shaving operate under wide and variable load requirements with complex and varying working conditions, making the prediction and optimization of combustion target variables challenging. This study proposed a data-driven approach for the prediction model building, tuning and combustion optimization. In this approach, a neural network for prediction based on Gaussian kernel and long short-term memory (LSTM), which captured and fused the working condition and temporal information, was first proposed. To address incomplete historical data coverage of working conditions, a fine-tuning framework with the idea of transfer and few-shot tuning was then introduced. Finally, an improved fitness function considering both optimization objectives and combustion adjustment limitations was designed to mitigate the risks associated with large-scale adjustments of operable variables. By conducting experiments on a 1000 MW boiler, targeting NOx concentration and the outlet temperature of the air pre-heater, the proposed method demonstrated high prediction accuracy with R2 values of 0.979 and 0.989, and significantly reduced mean squared error (MSE) by 98.05% and 97.37% on new conditions compared to untuned models. It achieved the reductions in NOx and temperature of 24.70 mgm−3 and 2.013 ∘C, and decreased the average changes of operable variables by 9.66% and 11.24% compared to using only rigid constraints.

Unlocking clean gas with hydrogen: A combustion optimization study

Combining hydrogen with natural gas, a hydrocarbon fuel, is seen as a critical step towards reaching net-zero emissions and creating a cleaner environment. To tackle climate change, major organizations like the U.S. Department of Energy, Energy Innovation, and the International Renewable Energy Agency are promoting the use of hydrogen blended with natural gas. This approach can potentially cut emissions in half compared to relying solely on natural gas. Using the Ansys 2022 R1 CHEMKIN tool, the study analyses combustion features in H2-CNG (compressed natural gas) -air mixtures, considering atmospheric conditions and operational parameters. Blending 50 % hydrogen with CNG results in significant changes, including an increase in laminar flame speed from 48.78 cm/s to 71.52 cm/s. As the hydrogen content in the CNG blend increases from 0 to 50 %, the concentration of free radicals like H, O, and OH rises by 42.86 %, 28.57 %, and 20.00 %, respectively, reaching these values at a 50 % hydrogen blend compared to pure CNG. NSGA-II multi-objective optimization identified that a 50 % hydrogen-blended CNG surpasses pure CNG in laminar flame speed and free radical generation. The research confirms that H2-CNG creates a promising fuel with several advantages. When combusted, H2-CNG mixtures exhibit superior characteristics, including potentially increased efficiency through increased free radical formation and laminar flame speed. This innovation has the potential to significantly reduce carbon footprint and contribute to achieving carbon neutrality goals. The cleaner and more efficient combustion properties of H2-CNG offer a compelling pathway for mitigating climate change.