Stability Analysis and the Stabilisation of Flexural Toppling Failure

Flexural toppling is a mode of failure that may occur in a wide range of layered rock strata in both rock slopes and large underground excavations. Whenever rock mass is composed of a set of parallel discontinuities dipping steeply against the excavated face plane, the rock mass will have the potential of flexural toppling failure as well. In such cases, the rock mass behaves like inclined superimposed cantilever beams that bend under their own weight while transferring the load to the underlying strata. If the bending stress exceeds the rock column’s tensile strength, flexural toppling failure will be initiated. Since the rock columns are “statically indeterminate,” thus, their factors of safety may not be determined solely by equations of equilibrium. The paper describes an analytical model with a sequence of inclined superimposed cantilever rock columns with a potential of flexural topping failure. The model is based on the principle of compatibility equations and leads to a new method by which the magnitudes and points of application of intercolumn forces are determined. On the basis of the proposed model, a safety factor for each rock column can be computed independently. Hence, every rock column will have a unique factor of safety. The least factor of safety that exists in any rock column is selected as the rock mass representative safety factor based on which simple equations are proposed for a conservative rock mass stability analysis and design. As a result, some new relations are established in order to design the length, cross-sectional area and pattern of fully grouted rock bolts for the stabilisation of such rock mass. Finally, the newly proposed equations are compared with the results of existing experimental flexural toppling failure models (base friction and centrifuge tests) for further verification.     

Vertical distribution and source identification of polycyclic aromatic hydrocarbons in anoxic sediment cores of Chini Lake, Malaysia: Perylene as indicator of land plant-derived hydrocarbons

Four anoxic sediment cores were collected from Chini Lake, Malaysia in order to investigate the variability of polycyclic aromatic hydrocarbon (PAH) and perylene concentrations. The study also determined significant differences of perylene concentrations in different sediment layers. Total PAH concentrations ranged from 248 to 8098 ng g⁻¹ in the samples. Diagnostic PAH ratios such as methylphenanthrenes/phenanthrene (MP/P), phenanthrene/anthracene (P/A) and fluoranthene/(fluoranthene + pyrene) (Fl/(Fl + Py) revealed a dominance of pyrogenic influences and partial petrogenic inputs to the top sediment layers. Perylene concentrations were high in the top layers (<12 cm) and increased with increasing depth. There is a significant positive correlation (r = 0.705, p = 0.01) between perylene concentrations and TOC. Analysis of variance (ANOVA) and LSD revealed significant differences (p < 0.05) in TOC-normalized perylene concentrations between the upper (<12 cm) and bottom layers (>12 cm). The average perylene concentrations accounted for 26–50% (0–12 cm) and 50–77% (12–36 cm) of pentacyclic-aromatic hydrocarbon isomers (PAI) present whereas it made up 10–34% (0–12 cm) and 46–66% (12–36 cm) of the total PAH. The average pyrene concentrations decreased with increasing depth and accounted for 62% (0–3 cm), 20–23% (3–12 cm) and 3–1.4% (12–36 cm) of perylene present. The results of hierarchical cluster analysis based on these ratios suggested different input sources for the top and bottom layers. It is concluded that the activity of termites on woody plants produced perylene which is supplied to the lake by run-off from the heavy and frequent rains in this Asian tropical climate. In addition, there was also in situ formation of perylene in the bottom layers due to diagenetic processes.     

Spatiotemporal analysis of dust patterns over Mesopotamia and their impact on Khuzestan province,Iran

Dust storms are yet quite frequent in various parts of the world, particularly ancient Mesopotamia (approximately corresponding to most parts of Iraq as well as certain surrounding regions toward its north). To add to the ongoing difficulty, monitoring dust patterns has been proven to be a rather difficult endeavor given the absence of reliable ground-based monitoring stations in the corresponding area. Additionally, western provinces of Iran, especially Khuzestan in the southwest of Iran, have been severely affected by dust storms carried by the westerly winds, blown through neighboring countries in ancient Mesopotamia. This study proceeds to employ aerosol optical depth (AOD), extracted from the MODerate-resolution Imaging Spectroradiometer onboard the Terra spacecraft, to assess spatial dust variations between 2001 and 2017 over the Khuzestan province and ancient Mesopotamia. The variations were also correlated with the temporal dust changes in the Khuzestan province. Frequency of occurrence for AOD?>?1 was used to identify and categorize major dust sources in the aforementioned regions. The findings were indicative of an increasing trend in the annual AODs of the Khuzestan province, which eventually led to a significant increase from 2008 toward the end of 2012, but decreased again in the following years. Correspondingly, the entire time period (2001–2017) was further divided into three sub-periods: the first time period spanning from 2001 to 2007, followed by the second from 2008 to 2012 and finally a third time period from 2013 to 2017. Dust source identification was speculative of numerous dust spots in Iraq, Syria, Kuwait and also the southern parts of Khuzestan province which have become more active in recent years. Additionally, a large active dust spot was pinpointed between the northwest Iraq and eastern Syria border which has become extremely active during the second time period, possibly due to a severe drought in the Fertile Crescent.

     

Pyroclastic dune bedforms: macroscale structures and lateral variations. Examples from the 2006 pyroclastic currents at Tungurahua (Ecuador)

Pyroclastic currents are catastrophic flows of gas and particles triggered by explosive volcanic eruptions. For much of their dynamics, they behave as particulate density currents and share similarities with turbidity currents. Pyroclastic currents occasionally deposit dune bedforms with peculiar lamination patterns, from what is thought to represent the dilute low concentration and fluid‐turbulence supported end member of the pyroclastic currents. This article presents a high resolution dataset of sediment plates (lacquer peels) with several closely spaced lateral profiles representing sections through single pyroclastic bedforms from the August 2006 eruption of Tungurahua (Ecuador). Most of the sedimentary features contain backset bedding and preferential stoss‐face deposition. From the ripple scale (a few centimetres) to the largest dune bedform scale (several metres in length), similar patterns of erosive‐based backset beds are evidenced. Recurrent trains of sub‐vertical truncations on the stoss side of structures reshape and steepen the bedforms. In contrast, sporadic coarse‐grained lenses and lensoidal layers flatten bedforms by filling troughs. The coarsest (clasts up to 10 cm), least sorted and massive structures still exhibit lineation patterns that follow the general backset bedding trend. The stratal architecture exhibits strong lateral variations within tens of centimetres, with very local truncations both in flow‐perpendicular and flow‐parallel directions. This study infers that the sedimentary patterns of bedforms result from four formation mechanisms: (i) differential draping; (ii) slope‐influenced saltation; (iii) truncative bursts; and (iv) granular‐based events. Whereas most of the literature makes a straightforward link between backset bedding and Froude‐supercritical flows, this interpretation is reconsidered here. Indeed, features that would be diagnostic of subcritical dunes, antidunes and ‘chute and pools’ can be found on the same horizon and in a single bedform, only laterally separated by short distances (tens of centimetres). These data stress the influence of the pulsating and highly turbulent nature of the currents and the possible role of coherent flow structures such as Görtler vortices. Backset bedding is interpreted here as a consequence of a very high sedimentation environment of weak and waning currents that interact with the pre‐existing morphology. Quantification of near‐bed flow velocities is made via comparison with wind tunnel experiments. It is estimated that shear velocities of ca 0·30 m.s^?1 (equivalent to pure wind velocity of 6 to 8 m.s^?1 at 10 cm above the bed) could emplace the constructive bedsets, whereas the truncative phases would result from bursts with impacting wind velocities of at least 30 to 40 m.s^?1.     

Copper(II) Biosorption on Soda Lignin From Oil Palm Empty Fruit Bunches (EFB)

The adsorption of Cu(II) ions from aqueous solutions by soda lignin as an absorbent using a batch adsorption system is presented in this paper. The soda lignin used in this study was extracted from black liquor derived from oil palm empty fruit bunches (EFB) using 20% v/v sulfuric acid. The effects of varying experimental parameters such as pH value, adsorbent dosage, different concentrations of Cu(II) ions, and agitation period were investigated. The results revealed that the optimum adsorption of Cu(II) onto soda lignin was recorded at a pH of 5.0 at an adsorbent dosage of 0.5 g soda lignin and an agitation period of 40 min. The adsorption capacities and rates of Cu(II) ions onto soda lignin was evaluated. The Langmuir and Freundlich adsorption models were applied to calculate the isotherm constants. It was found that the adsorption isothermal data could be well interpreted by the Freundlich model. The kinetic experimental data properly correlated with the pseudo‐second‐order kinetic model, which implies that chemical sorption is the rate‐limiting step.     

Input variable selection for water resources systems using a modified minimum redundancy maximum relevance (mMRMR) algorithm

Input variable selection (IVS) is a necessary step in modeling water resources systems. Neglecting this step may lead to unnecessary model complexity and reduced model accuracy. In this paper, we apply the minimum redundancy maximum relevance (MRMR) algorithm to identifying the most relevant set of inputs in modeling a water resources system. We further introduce two modified versions of the MRMR algorithm (α-MRMR and β-MRMR), where α and β are correction factors that are found to increase and decrease as a power-law function, respectively, with the progress of the input selection algorithms and the increase of the number of selected input variables. We apply the proposed algorithms to 22 reservoirs in California to predict daily releases based on a set from a 121 potential input variables. Results indicate that the two proposed algorithms are good measures of model inputs as reflected in enhanced model performance. The α-MRMR and β-MRMR values exhibit strong negative correlation to model performance as depicted in lower root-mean-square-error (RMSE) values.     

Chemical models for the contracting W3 IRS4

We have studied the chemical evolution in the central core of a contracting cloud representing W3 IRS4. We modified the equation of temperature to satisfy the physical conditions of W3 IRS4. The chemical rate equations and the hydrodynamics are integrated simultaneously. The contraction is followed from a very low density of n = 10 cm⁻³ to high core density of n = 10⁶ cm⁻³. The chemical evolution is studied for various chemical conditions, including both the effects of varying cosmic ray ionization rate and the effect of ion–dipole molecule collisions.

The main results by using the more extensive chemical network with the most updating reaction rates show that the calculated fractional abundances are in agreement with observation at intermediate and enhanced cosmic ray ionization rate at high depletion of elemental atoms.     

Water and wastewater treatment from BTEX by carbon nanotubes and Nano-Fe

The removal of benzene, toluene, ethylbenzene, and xylene (BTEX) from aqueous solution by multi- and single-walled carbon nanotubes (MWCNTs and SWCNTs), hybrid carbon nanotubes (HCNTs) and nano-Fe was evaluated for a nanomaterials dose of 1 g/L and a BTEX concentration of 10 mg/L and pH 7. The equilibrium amount (q _e ) (mg/g) removed by SWCNTs (B: 9.98, T: 9.96, E: 9.97, and X: 9.97 mg/g) was higher than for MWCNTs, HCNTs and nano-Fe in a c ₀ of 10 mg/L and for a contact time of 10 min. The q _e of total BTEX removed via SWCNTs was 39.89 mg/g. The order of uptake for SWCNTs is X > T = E > B, which is related to the increasing water solubility and the decreasing molecular weight of the compounds. The SWCNTs performed better for BTEX sorption than the MWCNTs, HCNTs and nano-Fe. The results of desorption study show that BTEX adsorbed on SWCNTs can easily be desorbed at 105 ± 2°C. It was concluded that recycling CNTs using heat improved the performance of the CNTs. For the first time, better adsorption performance was observed for recycled CNTs than for raw CNTs. SWCNTs are efficient BTEX adsorbents that could be used for cleaning up environmental pollution.     

Groundwater Quality Modeling with a Small Data Set

Seventeen groundwater quality variables collected during an 8‐year period (2006 to 2013) in Andimeshk, Iran, were used to implement an artificial neural network (NN) with the purpose of constructing a water quality index (WQI). The method leading to the WQI avoids instabilities and overparameterization, two problems common when working with relatively small data sets. The groundwater quality variables used to construct the WQI were selected based on principal component analysis (PCA) by which the number of variables were decreased to six. To fulfill the goals of this study, the performance of three methods (1) bootstrap aggregation with early stopping; (2) noise injection; and (3) ensemble averaging with early stopping was compared. The criteria used for performance analysis was based on mean squared error (MSE) and coefficient of determination (R²) of the test data set and the correlation coefficients between WQI targets and NN predictions. This study confirmed the importance of PCA for variable selection and dimensionality reduction to reduce the risk of overfitting. Ensemble averaging with early stopping proved to be the best performed method. Owing to its high coefficient of determination (R² = 0.80) and correlation coefficient (r=0.91), we recommended ensemble averaging with early stopping as an accurate NN modeling procedure for water quality prediction in similar studies.