Conference Papers

A6: Life Sciences I

C-C Cross Coupling Reactions and Wittig Olefination in One Pot

Areej Elamin (UAEU & uAE, United Arab Emirates)


With semi-stabilized and stabilized phosphoranes , Wittig reactions can be run in combination with C-C cross-coupling reactions such as with the Suzuki reaction. When 2-formylphenylboronic acid is used as substrate, these reactions can be combined with a Heck-reaction and a hydrolysis in one pot.

CO2 Enrichment Affects Ecophysiological Parameters of Maize Plants under Different Water Stress Regimes in UAE

Taoufik Ksiksi (UAE University, United Arab Emirates); Shaijal Thru Ppoyil (United Arab Emirates University, United Arab Emirates); Abdul Rasheed Palakkott (UAEU, United Arab Emirates)


Drought stress mitigating effects of CO2 enrichment were assessed on the growth of maize (Zea mays L.) plants inside a greenhouse in Al Foah, UAE. For the study, maize seeds were planted inside three custom-built plastic cage structures. Each cage was set for one of the three CO2 concentrations: 1000 ppm CO2, 700 ppm CO2, and ambient CO2 (i.e. 435 ppm). Additionally, three water stress treatments, HWS (200 ml per week), MWS (400 ml per week), and CWS (600 ml per week) were applied on two-weeks old seedlings until flowering. The results showed that the total chlorophyll content and stomatal length increased, and stomatal density decreased, under enriched (700 ppm and 1000 ppm CO2), when compared to ambient CO2 concentrations. Overall, maize plants were taller and bigger in drought-stressed enriched (700 ppm and 1000 ppm) CO2 environments. We posit as much as 33% irrigation savings under enriched CO2 concentrations.

Life Cycle Analysis of Conventional, Organic Green-House and Hydroponic Tomato Cultivation Systems in Abu Dhabi

Mona Al marzooqi (Masdar Institute A Part of Khalifa University of Science and Technology, United Arab Emirates); Lina Yousef (A Part of Khalifa University of Science and Technology)


This study compares the environmental impact of the life cycles of three cultivation systems (conventional open field, organic green-house, and hydroponic) for tomato production in the UAE using Abu Dhabi fields as a case study. The burdens associated with all phases of cultivation were considered using 1 kg of loose commercial tomato as a reference point. The study also aims to evaluate the energy and water demands in these phases in order to identify the most sustainable option for the UAE. The life cycle assessment (LCA) inventories were created based on primary data acquired from farm owners and a commercial company planning to set-up operations in Abu Dhabi. The results of the study are aimed to get a better understanding of the costs and benefits of each cultivation system and the development of best management practices for farming in the UAE.

A7: Industrial Engineering

CO2 Corrosion Inhibitor Behavior under Different Hydrodynamic Condition

Ning Wang and Yansong Bai (Khalifa University of Science and Technology, United Arab Emirates)


Influence of hydrodynamic conditions on the film resistance behavior of two corrosion inhibitors was studied using jet impingement apparatus. Linear polarization resistance (LPR) was carried out to obtain a live corrosion data, which depicts the inhibitor efficiency change along with the flow speed and time. Inhibitor efficiency increase firstly and then decreased with the pump speed. On the other hand, electrochemical impedance spectroscopy (EIS) interpreted the details of corrosion behavior. Inductive loops emerged as a negative factor to reduce the film resistance. At last, it's proved that proper change in the inhibitor formation can improve corrosion resistance a lot.

Organizational Culture and Innovation: A Conceptual Relationship and Change Framework

Amir Shikhli (University of Sharjah, United Arab Emirates); Refaat Hassan Abdel-Razek (University of Sharjah, Sharjah, UAE, United Arab Emirates); Salaheddine Bendak (University of Sharjah, United Arab Emirates)


The interrelationship between organizational culture and innovation is rarely investigated. The objectives of this paper are to develop a framework that would determine existing culture and innovation types in any given organization, model the interrelationships between them and help the management to adjust organizational culture to achieve desired innovation type. First step of the framework consists of using the Organizational Culture Assessment Instrument (OCAI), a questionnaire based on the Competing Value Framework (CVF), to determine culture types within the organization, and the Community Innovation Survey (CIS) to determine existing innovation types. Then multiple linear regression analysis is used to find out the interrelationship between them. This framework is validated by implementing it in one of the largest information technology organizations in UAE. The model gave adjusted R2 values ranging between 0.53 and 0.83, which indicate that the model is workable and gives reliable results. The results reveal that for each innovation type there is a recommended combination of the four culture types.

Routing of Autonomous Vehicle

Batool Madani and Malick Ndiaye (American University of Sharjah, United Arab Emirates)


This enormous growth in the market of e-commerce increased the need for solving the Last Mile delivery problem that refers to the process of conveying goods from transportation hubs to a destination in the supply chain management. Autonomous vehicles can be used to make the delivery of the purchased products to the customer. The aim of the paper is to find the optimal routes for small autonomous delivery machine filled with parcels by an autonomous vehicle to minimize the delivery time and increase the delivery efficiency. A classification of system-tosystem handover is introduced as well as a review of AVs technologies in Last Mile delivery is presented.

Fault Detection via Nonlinear Profile Monitoring Utilizing Artificial Neural Networks

Ahmed F Mohamed, Mahmoud Awad and Mohammad AlHamaydeh (American University of Sharjah, United Arab Emirates)


Fault detection is the characterization of a normal behavior of a system using a response function or profile of interest, and identification of any deviation from such normal behavior. As system complexity grows, predicting the underlying structure or form of response function becomes challenging if not impossible. This article presents a data-driven approach for fault detection of complex systems using multivariate statistical process control based on Artificial Neural Networks (ANNs) characterization. In this approach, the quality of a system is characterized where one explanatory variable is adequately explained as a function of the other variables using an ANN model. The vector of weights and biases of the ANN model is monitored using Hotelling T^2 through control charts. The proposed method is tested and compared to existing methods such as polynomial and sum of sine function regression for three cases from the literature. Moreover, it is applied to a 4-story reinforced concrete building that utilizes continuous monitoring to avoid potentially catastrophic failures. The proposed ANN approach outperforms the existing methods for small shifts (deviations) from healthy states. For large and medium shifts, it provides comparable results that are on the conservative side

Optimization of P-Chart For Processes With Multiple Assignable Causes

Emad Aldin M. Abdelkreem and Mahmoud Awad (American University of Sharjah, United Arab Emirates)


Attribute control charts are used extensively in many industries to detect assignable causes for processes. They are particularly useful in service industries and in transactional business processes, because many of the characteristic in those fields are not easily measured on a numerical scale. In addition, several critical-to-quality characteristics can be combined to determine whether to accept or reject the product. The optimization design of fraction nonconforming p-chart has been mainly addressed from either statistical or economic prospective or considering only single assignable cause. In this research, we propose a constrained economicstatistical model for processes with multiple assignable causes to determine the optimum sample size and sampling interval. The model will be validated by comparing it to existing model. A realistic dataset from water filling company is used as a case study as well.

A8: Petroleum

Characterizing the Impact of ZnO and ZnSO4 Smart Brines in Improving Oil Recovery from Carbonate Reservoirs

Mariam Malas (Khalifa University of Science and Technology, United Arab Emirates); Obaid Alhmoudi (Khalifa University of Science, Technology and Research, United Arab Emirates); Islam Elseaday (The Petroleum Institute, United Arab Emirates); Hadi Belhaj (Hadi Belhaj, United Arab Emirates)


The main parameters that can aid in recovering oil are wettability alteration and interfacial tension reduction. Since the majority of carbonate rock reservoirs tend to be oil-wet, altering the wettability can increase the oil recovery. In addition, introducing nanoparticles to the oil and gas industry have shown promising results in the applications of Enhanced Oil Recovery. In order to alter the wettability of the rock surface, it was reported that increasing the sulfate ions is a dominant factor for enhancing the displacement efficiency that increases the oil recovery from the reservoir. Smart brines were prepared using varying sulfate ions from seawater, moreover ZnSO4 were compared with ZnO smart brines. Impact of ZnO and ZnSO4 on wettability alteration, IFT and zeta potential has been analyzed using low concentrations of EDTA. Core-flooding experiments were performed with pre-conditioning of low Mg and Ca brine to compensate for the effect of EDTA with heavy metals. SARA, LC-ICPMS, CT Scanning and XRD analyses were also integrated on a material balance format. The tests employed assessed the potential mechanisms present upon contact of the smart brines with carbonate reservoir rocks in enhancing zeta potential change, wettability alteration and IFT reduction compared to core-flooding performance as a function of PV injected.

Enhanced Dynamic Simulation Assessment of Fracture Propagation in Shale Gas Reservoirs

Abhijith Suboyin (Khalifa University of Science and Technology, United Arab Emirates); Mohammed Motiur Rahman and Mohammed Haroun (The Petroleum Institute, United Arab Emirates)


Augmented by the recent activities in the oil and gas industry, it can be easily said that hydraulic fracturing has become a pivotal component for the successful development of unconventional reservoirs. This tremendous growth has fuelled significant advancements in numerical modeling. This paper describes enhanced dynamic simulation assessment of fracture propagation behavior. Enhanced discrete fracture network methodologies are applied to a shale gas reservoir and investigated with the help of industrial simulators. Fracture parameters along with propagation and interaction behavior between natural fractures and hydraulic fractures are analyzed and quantified. This is followed by verification of the models which further illustrates the accuracy and relevance of the prediction models currently used in the industry. The interaction behavior and quantification of fracture properties are further investigated from the simulation results along with diagnosis of the primary contributors. In addition, a sensitivity analysis is also conducted to examine the hierarchy of the main contributing parameters and their response.

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