scholarly journals Conceptual Approach on Feasible Hydrogen Contents for Retrofit of CNG to HCNG under Heavy-Duty Spark Ignition Engine at Low-to-Middle Speed Ranges

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3861
Author(s):  
Bum Youl Park ◽  
Ki-Hyung Lee ◽  
Jungsoo Park
Keyword(s):  
Natural Gas ◽  
Sampling Method ◽  
Latin Hypercube Sampling ◽  
Internal Combustion ◽  
Operating Conditions ◽  
Spark Ignition Engine ◽  
Latin Hypercube ◽  
Compressed Natural Gas ◽  
Performance And Emission ◽  
Base Engine

Hydrogen-based engines are progressively becoming more important with the increasing utilization of hydrogen and layouts (e.g., onboard reforming systems) in internal combustion engines. To investigate the possibility of HICE (hydrogen fueled internal combustion engine), such as an engine with an onboard reforming system, which is introduced as recent technologies, various operating areas and parameters should be considered to obtain feasible hydrogen contents itself. In this study, a virtual hydrogen-added compressed natural gas (HCNG) model is built from a modified 11-L CNG (Compressed Natural Gas) engine, and a response surface model is derived through a parametric study via the Latin hypercube sampling method. Based on the results, performance and emission trends relative to hydrogen in the HCNG engine system are suggested. The operating conditions are 1000, 1300, and 1500 rpm under full load. For the Latin hypercube sampling method, the dominant variables include spark timing, excess air ratio (i.e., λCH4+H2), and H2 addition. Under target operating conditions of 1000, 1300, and 1500 rpm, the addition of 6–10% hydrogen enables the virtual HCNG engine to reach similar levels of torque and BSFC (brake specific fuel consumption) compared to same lambda condition of λCH4. For the relatively low 1000 rpm speed under conditions similar to those of the base engine, NOx formation is greater than base engine condition, while a similar NOx level can be maintained under the middle speed range (1300 and 1500 rpm) despite hydrogen addition. Upon addition of 6–10% hydrogen under the middle speed operation range, the target engine achieves performance and emission similar to those of the base engine.

scholarly journals Impact of Compressed Natural Gas (CNG) Fuel Systems in Small Engine Wood Chippers on Exhaust Emissions and Fuel Consumption

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6709
Author(s):  
Łukasz Warguła ◽  
Mateusz Kukla ◽  
Piotr Lijewski ◽  
Michał Dobrzyński ◽  
Filip Markiewicz
Keyword(s):  
Natural Gas ◽  
Fuel Consumption ◽  
Average Power ◽  
Spark Ignition ◽  
Operating Conditions ◽  
Spark Ignition Engine ◽  
Maximum Diameter ◽  
Nox Emissions ◽  
Compressed Natural Gas ◽  
Hc Emissions

The projected increase in the availability of gaseous fuels by growing popularity of household natural gas (NG) filling stations and the increase in the production of gaseous biogas-derived fuels is conducive to an increase in the use of NG fuel. Currently, natural gas in various forms (compressed natural gas (CNG), liquefied natural gas (LNG)) is popular in maritime, rail and road transport. A new direction of natural gas application may be non-road mobile machines powered by a small spark-ignition engine (SI). The use of these engines in the wood chippers can cause the reduction of machine costs and emissions of harmful exhaust gases. In addition, plant material chippers intended for composting in bio-gas plants can be driven by the gas they are used to produce. The biogas can be purified to bio-methane to meet natural gas quality standards. The article presents the design of the natural gas supply system, which is an upgrade of the Lifan GX 390 combustion engine spark ignition engine (Four-stroke, OHV (over head valve) with a maximum power of 9.56 kW), which is a common representative of small gasoline engines. The engine is mounted in a cylindrical chipper designed for shredding branches with a maximum diameter of up to 100 mm, which is a typical machine used for cleaning work in urban areas. The engine powered by CNG and traditionally gasoline has been tested in real working conditions, when shredding cherry plum (Prunus cerasifera Ehrh. Beitr. Naturk. 4:17. 1789 (Gartenkalender4:189–204. 1784)). Their diameter was ca. 80 mm, 3-metere-long, and humidity content ca. 25%. The systems were tested under the same actual operating conditions, the average power generated by the drives during shredding is about 0.69 kW. Based on the recorded results, it was found that the CNG-fuelled engine was characterized by nitrogen oxides (NOx) emissions higher by 45%. The other effects of CNG were a reduction in carbon dioxide (CO2), carbon monoxide (CO) and hydrocarbon (HC) emissions of about 81%, 26% and 57%, respectively. Additionally, the use of CNG reduced fuel consumption by 31% and hourly estimated machine operating costs resulting from fuel costs by 53% (for average fuel price in Poland: gasoline: 0.99 EUR/L and CNG: 0.71 EUR/m3 on 08 November 2020). The modernization performed by the authors ensured the work of the drive unit during shredding, closer to the value of stoichiometric mixtures. The average (AVG) value of the air fuel ratio (AFR) for CNG was enriched by 1.2% (AVG AFR was 17), while for the gasoline engine the mixture was more enriched by 4.8% (AVG AFR was 14). The operation of spark-ignition (SI) combustion engines is most advantageous when burning stoichiometric mixtures due to the cooperation with exhaust aftertreatment systems (e.g., three-function catalytic converter). A system powered by CNG may be beneficial in systems adapting to operating conditions, used in low-power shredding machines, whose problem is increased HC emissions, and CNG combustion may reduce them. The developed system does not exceed the emission standards applicable in the European Union. For CO emissions expressed in g/kWh, it was about 95% lower than the permissible value, and HC + NOx emissions were 85% lower. This suggests that the use of the fuel in question may contribute to tightening up the permissible emission regulations for non-road machinery.

Laminar flame speed correlations for methane, ethane, propane and their mixtures, and natural gas and gasoline for spark-ignition engine simulations

2017 ◽  
Vol 18 (9) ◽  
pp. 951-970 ◽  
Author(s):  
Riccardo Amirante ◽  
Elia Distaso ◽  
Paolo Tamburrano ◽  
Rolf D Reitz
Keyword(s):  
Natural Gas ◽  
Laminar Flame ◽  
Spark Ignition ◽  
Flame Speed ◽  
Operating Conditions ◽  
Spark Ignition Engine ◽  
Computational Time ◽  
Laminar Flame Speed ◽  
Spark Ignition Engines ◽  
Empirical Correlations

The laminar flame speed plays an important role in spark-ignition engines, as well as in many other combustion applications, such as in designing burners and predicting explosions. For this reason, it has been object of extensive research. Analytical correlations that allow it to be calculated have been developed and are used in engine simulations. They are usually preferred to detailed chemical kinetic models for saving computational time. Therefore, an accurate as possible formulation for such expressions is needed for successful simulations. However, many previous empirical correlations have been based on a limited set of experimental measurements, which have been often carried out over a limited range of operating conditions. Thus, it can result in low accuracy and usability. In this study, measurements of laminar flame speeds obtained by several workers are collected, compared and critically analyzed with the aim to develop more accurate empirical correlations for laminar flame speeds as a function of equivalence ratio and unburned mixture temperature and pressure over a wide range of operating conditions, namely [Formula: see text], [Formula: see text] and [Formula: see text]. The purpose is to provide simple and workable expressions for modeling the laminar flame speed of practical fuels used in spark-ignition engines. Pure compounds, such as methane and propane and binary mixtures of methane/ethane and methane/propane, as well as more complex fuels including natural gas and gasoline, are considered. A comparison with available empirical correlations in the literature is also provided.

Uncertainty Quantification of Turbulence Model Coefficients via Latin Hypercube Sampling Method

2010 ◽  
Author(s):  
Matthew C. Dunn ◽  
Babak Shotorban ◽  
Abdelkader Frendi
Keyword(s):  
Uncertainty Quantification ◽  
Turbulent Flows ◽  
Turbulence Model ◽  
Sampling Method ◽  
Latin Hypercube Sampling ◽  
Recirculation Region ◽  
Free Shear Layer ◽  
Latin Hypercube ◽  
Reattachment Point ◽  
Turbulent Dissipation

This paper is concerned with the propagation of uncertainties in the values of turbulence model coefficients and parameters in turbulent flows. These coefficients and parameters are determined from experiments performed on elementary flows and they are subject to uncertainty. The widely used k–ε turbulence model is considered. It consists of model transport equations for the turbulence kinetic energy and rate of turbulent dissipation. Both equations involve various model coefficients about which adequate knowledge is assumed known in the form of probability density functions. The study is carried out for the flow over a 2D backward-facing step configuration. The Latin Hypercube Sampling method is employed for the uncertainty quantification purposes as it requires a smaller number of samples compared to the conventional Monte-Carlo method. The mean values are reported for the flow output parameters of interest along with their associated uncertainties. The results show that model coefficient variability has significant effects on the streamwise velocity component in the recirculation region near the reattachment point and turbulence intensity along the free shear layer. The reattachment point location, pressure, and wall shear are also significantly affected.

Development of Statistical Core Thermal Design Methodology Using a Modified Latin Hypercube Sampling Method

1991 ◽  
Vol 94 (3) ◽  
pp. 407-415 ◽  
Author(s):  
Seung-Hyuk Lee ◽  
Hyun-Koon Kim ◽  
Sang-Ryeol Park ◽  
Soon-Heung Chang
Keyword(s):  
Design Methodology ◽  
Sampling Method ◽  
Latin Hypercube Sampling ◽  
Thermal Design ◽  
Latin Hypercube
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