Influences of Environmental and Operational Factors on Dark Fermentative Hydrogen Production: A Review

Hydrogen (H₂) is one of renewable energy sources known for its non‐polluting and environmentally friendly nature, as its end combustion product is water (H₂O). The biological production of H₂ is a less energy intensive alternative where processes can be operated at ambient temperature and pressure. Dark fermentation by bacterial biomass is one of multitude of approaches to produce hydrogen which is known as the cleanest renewable energy and is thus receiving increasing attention worldwide. The present study briefly reviews the biohydrogen production process with special attention on the effects of several environmental and operational factors towards the process. Factors such as organic loading rate, hydraulic retention time, temperature, and pH studied in published reports were compared and their influences are discussed in this work. This review highlights the variations in examined operating ranges for the factors as well as their reported optimum values. Divergent values observed for the environmental/operational factors merit further exploration in this field.     

Ground-roll attenuation using modified common-offset–common-reflection-surface stacking

We modified the common-offset–common-reflection-surface (COCRS) method to attenuate ground roll, the coherent noise typically generated by a low-velocity, low-frequency, and high-amplitude Rayleigh wave. The COCRS operator is based on hyperbolas, thus it fits events with hyperbolic traveltimes such as reflection events in prestack data. Conversely, ground roll is linear in the common-midpoint (CMP) and common-shot gathers and can be distinguished and attenuated by the COCRS operator. Thus, we search for the dip and curvature of the reflections in the common-shot gathers prior to the common-offset section. Because it is desirable to minimize the damage to the reflection amplitudes, we only stack the multicoverage data in the ground-roll areas. Searching the CS gathers before the CO section is another modification of the conventional COCRS stacking. We tested the proposed method using synthetic and real data sets from western Iran. The results of the ground-roll attenuation with the proposed method were compared with results of the f–k filtering and conventional COCRS stacking after f–k filtering. The results show that the proposed method attenuates the aliased and nonaliased ground roll better than the f–k filtering and conventional CRS stacking. However, the computation time was higher than other common methods such as f–k filtering.     

Rainfall-runoff modeling considering soil moisture accounting algorithm,case study: Karoon III River basin

In contrast to event based hydrologic models which reveal how a basin responds to an individual rainfall event, continuous ones synthesize hydrologic processes over a longer time period that includes both dry and wet conditions. With respect to the importance of infiltration method in Rainfall-Runoff (RR) modeling, the objective of this study was to assess HEC-HMS with Soil Moisture Accounting (SMA) infiltration algorithm, considering several components of hydrologic cycle such as canopy interception, surface depression, infiltration into the soil profile storage, percolation to the ground water aquifer and base flow caused by available soil storage vs. maximum saturated capacity of soil layer, to model daily flows of Karoon III basin (Iran). The model showed satisfied performance by accounting initial moisture condition by SMA model with Nash-Sutcliffe (NS) coefficient of 0.76 and 0.64 for calibration and verification. Sensitivity analysis showed that saturated hydraulic conductivity (K), Clark storage coefficient (R) and time of concentration (t _c) were the most effective parameters on the simulated Peak Over Thresholds (POT). Results from this study assist in improving model accuracy and ability to predict future conditions based upon basin characteristic change.     

Shear wave velocity prediction using seismic attributes and well log data

Formation’s properties can be estimated indirectly using joint analysis of compressional and shear wave velocities. Shear wave data is not usually acquired during well logging, which is most likely for cost saving purposes. Even if shear data is available, the logging programs provide only sparsely sampled one-dimensional measurements: this information is inadequate to estimate reservoir rock properties. Thus, if the shear wave data can be obtained using seismic methods, the results can be used across the field to estimate reservoir properties. The aim of this paper is to use seismic attributes for prediction of shear wave velocity in a field located in southern part of Iran. Independent component analysis (ICA) was used to select the most relevant attributes to shear velocity data. Considering the nonlinear relationship between seismic attributes and shear wave velocity, multi-layer feed forward neural network was used for prediction of shear wave velocity and promising results were presented.     

Experimental study on the unconfined compressive strength of carbon fiber reinforced clay soil

To study the effect and mechanism of carbon fiber reinforced clay, a series of unconfined compression tests for clay reinforced with carbon fiber have been performed under the conditions of controlled water content and dry density. The carbon fiber is mixed into soil with the quality percentage of 0.01, 0.02, 0.03, 0.05, 0.1, 0.15, 0.25, 0.35, and 0.5%, then a certain quality of water was added in the soil to achieve the optimum soil water content. Ten groups of samples were tested by the unconfined compression experiment. The results showed that the incorporation of carbon fiber elements can effectively improve the unconfined compressive strength and brittle failure mode of soil. The soil is strengthened at the beginning and then weakened with the increased incorporation of carbon fiber, the effect is especially significant when the mix percentage becomes 0.1%. The interaction at the interface between carbon fiber surface and soil matrix is analyzed by using scanning electron microscopy (SEM). It is found that the enhancement mechanisms of carbon fiber reinforced soil are one-dimensional reinforcement of a single carbon fiber thread and three-dimensional reinforcement caused by fiber network respectively.     

Assessing the Performance of Independent Component Analysis in Remote Sensing Data Processing

Independent component analysis (ICA) is a novel method to be considered as a powerful type of analysis in the process of source signal separation. Based on the capabilities of this particular analysis, there will be a hypothesis of applying ICA in the image processing of remote sensing data. This paper aims to introduce the ability of ICA in contrasting and highlighting some area with potential of mineralization. Considering and applying ICA transformation on the ETM⁺ image of southern Masule, Iran has resulted in finding some favorable points for further investigation. Moreover, sampling program on the indicated area has led to identify some huge, unexpected lithology and dikes. ICA analysis is a robust method even in remote sensing data processing with the high speed and capabilities in separating source signals from noise.