Transforming Vulnerability Indexing for Saltwater Intrusion into Risk Indexing through a Fuzzy Catastrophe Scheme

Mapping vulnerability to Saltwater Intrusion (SWI) in coastal aquifers is studied in this paper using the GALDIT framework but with a novelty of transforming the concept of vulnerability indexing to risk indexing. GALDIT is the acronym of 6 data layers, which are put consensually together to invoke a sense of vulnerability to the intrusion of saltwater against aquifers with freshwater. It is a scoring system of prescribed rates to account for local variations; and prescribed weights to account for relative importance of each data layer but these suffer from subjectivity. Another novelty of the paper is to use fuzzy logic to learn rate values and catastrophe theory to learn weight values and these together are implemented as a scheme and hence Fuzzy-Catastrophe Scheme (FCS). The GALDIT data layers are divided into two groups of Passive Vulnerability Indices (PVI) and Active Vulnerability Indices (AVI), where their sum is Total Vulnerability Index (TVI) and equivalent to GALDIT. Two additional data layers (Pumping and Water table decline) are also introduced to serve as Risk Actuation Index (RAI). The product of TVI and RAI yields Risk Indices. The paper applies these new concepts to a study area, subject to groundwater decline and a possible saltwater intrusion problem. The results provide a proof-of-concept for PVI, AVI, RAI and RI by studying their correlation with groundwater quality samples using the fraction of saltwater (f_sea), Groundwater Quality Indices (GQI) and Piper diagram. Significant correlations between the appropriate values are found and these provide a new insight for the study area.

     

Silica aerogel/epoxy nanocomposites: Mechanical,vibrational, and morphological properties

The present study was an attempt to examine the effects that adding silica aerogel (SA) nanoparticles to epoxy would exert on its mechanical, vibrational, and morphological properties. Neat epoxy was consecutively combined with 1, 2, and 4 wt% of SA nanoparticles. A number of tests of mechanical properties were then performed on the samples, including tests of tensile, bending, compressive, dynamic mechanical thermal, hardness, and Izod impact. Vibration and water uptake tests were also conducted on the samples. The highest modulus and strength values were found in the nanocomposite sample with 4 wt% of SA, and the highest toughness and elongation values were detected in the sample with 1 wt% of SA. Furthermore, adding the SA nanoparticles to the epoxy improved the energy absorption and hardness of the epoxy matrix. The findings from the tests of dynamic mechanical thermal and vibration properties demonstrated that, with an increase in the nanoparticles content in the samples, the values of storage modulus and natural frequency increased while the values of tan δ and damping ratios decreased. A comparison between the values of natural frequency from the vibration test and the values from the Euler–Bernoulli beam theory showed a good agreement between the theoretical and experimental results.     

Fatigue and fracture properties of thin metallic foils

Metallic thin foils are essential structural parts in microsystems,which may be subjected to fatigue loading caused by thermal fluctuations and mechanical vibrations influencing their reliability in numerous engineering applications. It is well known that the fatigue properties of bulk material cannot be adopted for small scaled structures. For a better understanding of the `size-effect' in the present investigation fatigue crack growth near threshold in the high cycle fatigue regime and associated fracture processes were studied. Free- standing rolled and electrodeposited Cu-, Mo- and Al foils of thickness from 20 m to 250 m in different conditions have been tested in a special experimental set up operating at R=–1 and a testing frequency of 20 kHz. At a given constant strain value the fatigue crack growth behaviour has been recorded accompanied by intermittent observation of the change of the dislocation structure in the vicinity of the growing crack by use of the electron channeling contrast imaging (ECCI)-technique in a scanning electron microscope (SEM). In a load shedding technique fatigue threshold stress intensity factor values have been derived and compared with data of bulk material. Typical crack growth features were detected depending on thickness and grain sizes of the foils. Various criteria (compliance, extent of plastic zones and plastic strain gradients) were selected for the explanation of this anomalous behaviour. Additionally fractomicrographs of uniaxial strained and fatigued foils have been studied to obtain further insight of the effect of dimensional constraint.     

Modelling Energy Dissipation Over Stepped-gabion Weirs by Artificial Intelligence

The hydraulics of energy dissipation over stepped-gabion weirs is investigated by carrying out a series of laboratory experiments, building models to explain the experimental data, and testing their robustness by using the data reported by other researchers. The experiments comprise: six different stepped-gabion weirs tested in a horizontal laboratory flume, a wide range of discharge values, two weir slopes (V:H): 1:1 and 1:2, and gabion filling material gravel size (porosity equal to 38 %, 40 % and 42 %). These experimental setups were selected to ensure the development of both the nappe and skimming flow regimes within the measured dataset. The models developed for computing energy dissipation over stepped-gabion weirs comprise: multiple regression equations based on dimensional analysis theory, Artificial Neural Network (ANN) and Gene Expression Programming (GEP). The analysis shows that the measured data capture both flow regimes and the transition in between them and above all, and by using all of the data, it may be possible to identify the range of each regime. Energy dissipation modelled by the ANN formulation is successful and may be recommended for reliable estimates but those by GEP and regression analysis can still serve for rough-and-ready estimates in engineering applications.     

Friction Parameters for Flows in Nearly Flat Tidal Channels

A numerical study of friction parameters associated with nearly flat tidal channels is reported. Such empirical parameters are often back-calculated using complex flow equations through a procedure referred to as “inverse problems.” However, estimates of friction parameters of tidal channels are liable to substantial uncertainties if water levels are used in their inverse problems. Even if the parameters are optimized by mathematically comparing gauged and simulated values, the inverse problem must satisfy the quality conditions of “uniqueness,” “identifiability,” and “stability.” To obtain an insight into the problem, this paper focuses on flows where these conditions may not hold. The study concludes that friction parameters can be unidentifiable if the inverse problem employs gauged high tide water levels, because the effect of storage on water level dominates over friction. Gauged discharge values render identifiable, stable, and unique estimates of friction parameters even at high tides, but this is not a practical proposition. Low tide levels should be used to determine friction parameters, as the use of high-tide water levels can make friction parameters, and subsequently simulated discharge values, anomalous.     

Aldosterone precursors and hypertension with hypokalemia and adrenal module non caused by primary hyperaldosteronism

The purpose of the study was to evaluate the interest of aldosterone precursors assays in arterial hypertension with hypokaliemia and adrenal nodules non due to aldosterone. Seven hypertensive patients, 3 men and 4 women, aged 59.5 +/- 10.1 years were included in the study. After drug withdrawal, kaliemia was 3.1 +/- 0.3 mmol/l (2.7-3.6), active renin 2.9 +/- 1.4 ng/l, plasma aldosterone (aldo) 108 +/- 49.4 pg/ml, cortisol 13 +/- 3.1 micrograms/100 ml, and [S] 0.47 +/- 0.5 micrograms/100 ml. Adrenal CT scan showed an adenoma in 3 patients (30.5 +/- 5 mm) and an unilateral nodular hyperplasia in 4 patients. In all patients, the plasma levels (RIA, chomatographic step) of the following steroids in the mineralocorticoid (MC) pathway were determined: DOC, 18 OH-DOC, B, 18 OH-B and aldosterone. Two from 7 (28%) exerted aldosterone precursors excess, 1 with DOC-producing adenoma (DOC-PA) (table), and 1 with a partial 11 beta hydroxylase deficiency (DOC: 211 pg/ml; S: 1 mu/100 ml). Aldosterone/DOC + 18 OH-DOC ratio proposed as a malignancy index was decreased in the patient with DOC-PA (8.1). No dysfunction in the MC pathway was identified in the 5 other patients. [table: see text] The study suggests the relevance of aldosterone precursors assays in low renin hypertension non due to aldosterone and in incidentally discovered adrenal masses.     

Effective adsorption of ciprofloxacin antibiotic using powdered activated carbon magnetized by iron(III) oxide magnetic nanoparticles

Journal of Porous Materials - In the present work, the adsorption performance of powdered activated carbon magnetized by iron(III) oxide magnetic nanoparticles (PAC@Fe3O4-MN) for the removal of...     

Mapping Aquifer Vulnerability Indices Using Artificial Intelligence-running Multiple Frameworks (AIMF) with Supervised and Unsupervised Learning

DRASTIC-based vulnerability indices and their variations for an aquifer are investigated in this paper, each of which is regarded as a framework since their rationale of using seven DRASTIC data layers is consensual and lacks empirical or theoretical formulations. The Basic DRASTIC framework (BDF) is implemented by a set of prescribed rules; whereas its three variations involve unsupervised learning from the data, which comprise: (i) learning the rates by the Wilcoxon test (WDF) but using BDF weights; (ii) using BDF rates but learning the weights by Genetic Algorithm (BDF-GA); and (iii) learning rates as in WDF and the weights as in BDF-GA (WDF-GA). These four frameworks are not supervised, but the novelty of the paper is to introduce supervised learning at the second stage by Artificial Intelligence to run Multiple Frameworks (AIMF), for which the paper uses Support Vector Machine (SVM). AIMF uses the outputs of the four frameworks as its input data and a function of observed nitrate-N values as its target data. The AIMF strategy is evaluated in the aquifer of Ardabil plain, which is exposed to anthropogenic contamination such as nitrate-N. The coefficient of correlation (r-values) between the results and nitrate-N values for the above frameworks are: 0.2, 0.37, 0.38 and 0.45; whereas AIMF enhances it to 0.84; attributable to the supervised learning.     

Phase transformations in face centered cubic (Al0.32Cr0.68)2O3 thin films

Face centered cubic (Al_0.32Cr_0.68)₂O₃ thin films have been annealed in the temperature range of 500–1000 °C during 2–8 h. The fcc structure of the film remains intact when annealed at temperatures up to 700 °C for 8 h. X-ray diffraction and transmission electron microscopy show the onset of phase transformation to corundum phase alloys in the sample annealed at 900 °C for 2 h, where annealing at 1000 °C for 2 h results in complete phase transformation to α-(Al_0.32Cr_0.68)₂O₃. In-plane and out-of-plane line scans performed in EDX TEM and θ/2θ XRD patterns did not show any phase separation into α-Cr₂O₃ and Al₂O₃ prior and after the annealing. The apparent activation energy of this process is 380–480 kJ/mol as determined by the Johnson–Mehl–Avrami model.