Geochemistry and water quality of Lake Qarun, Egypt

Water geochemistry is a very important tool for studying the water quality in a given area. Geology and climate are the major natural factors controlling the chemistry of most natural waters. Anthropogenic impacts are the secondary sources of contamination in natural waters. This study presents the first integrative approach to the geochemistry and water quality of surface waters and Lake Qarun in the Fayoum catchment, Egypt. Moreover, geochemical modeling of Lake Qarun was firstly presented. The Nile River is the main source of water to the Fayoum watershed. To investigate the quality and geochemistry of this water, water samples from irrigation canals, drains and Lake Qarun were collected during the period 2010‒2013 from the whole Fayoum drainage basin to address the major processes and factors governing the evolution of water chemistry in the investigation area. About 34 physicochemical quality parameters, including major ions, oxygen isotopes, trace elements, nutrients and microbiological parameters were investigated in the water samples. Multivariable statistical analysis was used to interpret the interrelationship between the different studied parameters. Geochemical modeling of Lake Qarun was carried out using Hardie and Eugster’s evolutionary model and a model simulated by PHREEQC software. The crystallization sequence during evaporation of Lake Qarun brine was also studied using a Jänecke phase diagram involving the system Na‒K‒Mg‒ Cl‒SO4‒H2O. The results show that the chemistry of surface water in the Fayoum catchment evolves from Ca- Mg-HCO3 at the head waters to Ca‒Mg‒Cl‒SO4 and eventually to Na‒Cl downstream and at Lake Qarun. The main processes behind the high levels of Na, SO4 and Cl in downstream waters and in Lake Qarun are dissolution of evaporites from Fayoum soils followed by evapoconcentration. This was confirmed by binary plots between the different ions, Piper plot, Gibb’s plot and δ18O results. The modeled data proved that Lake Qarun brine evolves from drainage waters via an evaporation‒crystallization process. Through the precipitation of calcite and gypsum, the solution should reach the final composition "Na–Mg–SO4–Cl". As simulated by PHREEQC, further evaporation of lake brine can drive halite to precipitate in the final stages of evaporation. Significantly, the crystallization sequence during evaporation of the lake brine at the concentration ponds of the Egyptian Salts and Minerals Company (EMISAL) reflected the findings from both Hardie and Eugster’s evolutionary model and the PHREEQC simulated model. After crystallization of halite at the EMISAL ponds, the crystallization sequence during evaporation of the residual brine (bittern) was investigated using a Jänecke phase diagram at 35 °C. This diagram was more useful than PHREEQC for predicting the evaporation path especially in the case of this highly concentrated brine (bittern). The predicted crystallization path using a Jänecke phase diagram at 35 °C showed that halite, hexahydrite, kainite and kieserite should appear during bittern evaporation. Yet the actual crystallized mineral salts were only halite and hexahydrite. The absence of kainite was due to its metastability while the absence of kieserite was due to opposed relative humidity. The presence of a specific MgSO4.nH2O phase in ancient evaporite deposits can be used as a paleoclimatic indicator. Evaluation of surface water quality for agricultural purposes shows that some irrigation waters and all drainage waters have high salinities and therefore cannot be used for irrigation. Waters from irrigation canals used as a drinking water supply show higher concentrations of Al and suffer from high levels of total coliform (TC), fecal coliform (FC) and fecal streptococcus (FS). These waters cannot be used for drinking or agricultural purposes without treatment, because of their high health risk. Therefore it is crucial that environmental protection agencies and the media increase public awareness of this issue, especially in rural areas.

Simulation and material calibration of ultra high strength steel (UHSS) S960 welded joint under static tensile test utilizing finite element method (FEM)

The aim of this work was to calibrate the material properties including strength and strain values for different material zones of ultra-high strength steel (UHSS) welded joints under monotonic static loading. The UHSS is heat sensitive and softens by heat due to welding, the affected zone is heat affected zone (HAZ). In this regard, cylindrical specimens were cut out from welded joints of Strenx® 960 MC and Strenx® Tube 960 MH, were examined by tensile test. The hardness values of specimens’ cross section were measured. Using correlations between hardness and strength, initial material properties were obtained. The same size specimen with different zones of material same as real specimen were created and defined in finite element method (FEM) software with commercial brand Abaqus 6.14-1. The loading and boundary conditions were defined considering tensile test values. Using initial material properties made of hardness-strength correlations (true stress-strain values) as Abaqus main input, FEM is utilized to simulate the tensile test process. By comparing FEM Abaqus results with measured results of tensile test, initial material properties will be revised and reused as software input to be fully calibrated in such a way that FEM results and tensile test results deviate minimum. Two type of different S960 were used including 960 MC plates, and structural hollow section 960 MH X-joint. The joint is welded by BöhlerTM X96 filler material. In welded joints, typically the following zones appear: Weld (WEL), Heat affected zone (HAZ) coarse grained (HCG) and fine grained (HFG), annealed zone, and base material (BaM). Results showed that: The HAZ zone is softened due to heat input while welding. For all the specimens, the softened zone’s strength is decreased and makes it a weakest zone where fracture happens while loading. Stress concentration of a notched specimen can represent the properties of notched zone. The load-displacement diagram from FEM modeling matches with the experiments by the calibrated material properties by compromising two correlations of hardness and strength.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

Modelling the colour difference by artificial neural network

This thesis work studies the modelling of the colour difference using artificial neural network. Multilayer percepton (MLP) network is proposed to model CIEDE2000 colour difference formula. MLP is applied to classify colour points in CIE xy chromaticity diagram. In this context, the evaluation was performed using Munsell colour data and MacAdam colour discrimination ellipses. Moreover, in CIE xy chromaticity diagram just noticeable differences (JND) of MacAdam ellipses centres are computed by CIEDE2000, to compare JND of CIEDE2000 and MacAdam ellipses. CIEDE2000 changes the orientation of blue areas in CIE xy chromaticity diagram toward neutral areas, but on the whole it does not totally agree with the MacAdam ellipses. The proposed MLP for both modelling CIEDE2000 and classifying colour points showed good accuracy and achieved acceptable results.