Relative Error Parameters Research Articles

Adaptability of different mechanisms and kinetic study of methane combustion in steam diluted environments

The chemical kinetics of methane oxidation in a steam-diluted environment are studied in the present study. Various well-validated mechanisms for methane combustion are adopted and compared with experimental data. Ignition delay, laminar flame speed, and emissions for CH4 combustion with steam dilution are discussed. Cumulative relative error parameter was determined for all mechanisms considered in this study to evaluate the prediction level in quantifiable terms. Reaction pathways under no and steam-diluted environments are analyzed, and key elementary reactions and species are identified in these conditions. The analysis gives a relative idea of the applicability of some of the reduced mechanisms for the diluted steam conditions. This study aims to guide future computational fluid dynamics simulations to accurately predict combustion characteristics in these conditions. Computations of laminar flame speed from GRI-3.0, Aramco3.0, Curran, and San Diego mechanisms were the most precise under diluted steam conditions. Similarly, for the calculation of ignition delay of methane under the steam dilution, the Aramco mechanism and the Curran’s mechanism were able to predict the experimentally observed values most closely. Sensitivity study for the OH concentrations shows that the H-abstraction of methane from OH radicals has an opposing trend with dilution for Aramco and GRI-3.0 mechanism. On the other hand, CO and NO emissions were reduced significantly, with the dilution increased from 0 to 20%. The third-body effect of steam is observed to dominate the deviation observed between the detailed and reduced mechanism. For low operating pressure conditions, the GRI-3.0 mechanism gives an excellent prediction, whereas, for applications like gas turbines and furnaces, Aramco-3.0 and Curran mechanisms can be adopted to give good results. The San Diego mechanism can be chosen for low computational facility purposes as it shows very good predictions for ignition delay and laminar flame speed computations.

Evaluation of Climate Change Impacts on Rice Production under Water Management in Northern Iran

This research studied the effects of climate change on rice yield under irrigation by using the AquaCrop model and the various climate change scenarios for the crop years 2017 and 2018 at the research farm of the Rice Research Institute of Iran, Rasht. The LARS-WG6 model was employed to simulate the meteorological data obtained from Rasht Meteorological Station under the RCP8.5 and RCP4.5 scenarios for the 2020-2050 and 2060-2090 periods. The simulated values were assessed based on the measured values of total biomass and grain yields using the coefficient of determination (R2 ), the relative error parameters, and the normalized root mean square error (RMSEn). The calculated values of RMSEn varied from 7 to 4% for grain yield and from 3 to 7% for biomass yield at the calibration and validation stages, respectively. The results suggested that the AquaCrop model had suitable accuracy in predicting biomass and grain yields. The findings indicate that climate change decreased mean rice grain yield by 17 to 23% under the RCP4.5 scenario and by 18 to 23% under the RCP8.5 scenario for 2050 and 2090, respectively, in non-flooded irrigation management. The lowest simulated mean biomass and grain yields were obtained under irrigation at 11-day intervals in scenario RCP8.5 for the second future period (2060-2090). In general, non-flooded irrigation management had negative effects on rice grain yield under climate change. Moreover, the mean rice growing period under both RCP8.5 and RCP4.5 scenarios declined by 2090. These findings can be used for a broad spectrum of users such as farmers, agricultural engineers, and project managers in practical policymaking and making correct decisions compatible with the region in order to increase rice grain yield productivity under future climate conditions in northern Iran.

On Inexact Relative-Error Hybrid Proximal Extragradient, Forward-Backward and Tseng’s Modified Forward-Backward Methods with Inertial Effects

For solving monotone inclusion problems, we propose an inertial under-relaxed version of the relative-error hybrid proximal extragradient method. We study the asymptotic convergence of the method, as well as its nonasymptotic global convergence rates in terms of iteration complexity. We analyze the new method under more flexible assumptions than existing ones, both on the extrapolation and on the relative-error parameters. The approach is applied to two types of forward-backward type methods for solving structured monotone inclusions.

Dynamic Mechanical Characteristics and Constitutive Modeling of Rail Steel over a Wide Range of Temperatures and Strain Rates

Rail steel plays an indispensable role in the safety and stability of the railway system. Therefore, a suitable constitutive model is quite significant to understand the mechanical behavior of this material. Here, the compressive mechanical behavior of heat-treated U71Mn rail steel over a wide range of strain rates (0.001 s−1–10000 s−1) and temperatures (20°C–800°C) was systematically investigated via uniaxial quasistatic and dynamic tests. The split Hopkinson pressure bar (SHPB) apparatus was utilized to perform dynamic mechanical tests. The effects of temperature, strain, and strain rate on the dynamic compressive characteristics of U71Mn were discussed, respectively. The results indicate that the flow response of U71Mn is both temperature-sensitive and strain rate-sensitive. However, the influence of temperature on the flow response is more remarkable than that of strain rate. On the basis of the experimental data, the original and modified Johnson-Cook (JC) models of the studied material were established, respectively. Using correlation coefficient and average absolute relative error parameters, it is revealed that better agreement between the experimental and predicted stress is reached by the modified JC model, which demonstrates that the modified one can characterize the mechanical behavior of the studied material preferably.