This research addresses a novel technique to monitor safety of workers at height using artificially trained drones. A CNN deep learning model will be used to detect the personal fall arrest system (PFAS) components including the safety harness, lifeline, and the safety helmet. The model then will be implemented in one of Abu Dhabi's construction sites to test the accuracy and efficiency of the developed model.
This research investigates how land use changes due to sea level rise (SLR) may affect traffic network congestion and how preventive protection measures against SLR can significantly improve transportation network performance and possibly be cost effective. We use the San Francisco Bay Area shoreline, under a one-meter SLR, as a case study, and evaluate the results with different metrics: the number of commuters that are not able to execute their trip, and the Vehicle Hours Traveled increase. Our model considers both hydrodynamic and traffic effects. The results show that the relocation of commercial and residential buildings from inundated to dry areas will increase congestion levels, while preventive protection of the shoreline leads to lower levels of traffic congestion. Finally, we discuss other possible costs related to the absence of levee protection that should be evaluated by policy makers before developing SLR adaptation strategies.
As planners devise the most effective sea wall protection strategy on coastal cities to protect against sea level rise, they may face a large number of possible combinations, which are computationally infeasible to simulate. This paper presents a Genetic Algorithm (GA) that explores the full range of protection scenarios with a guided search. This GA varies levee length increments and mutation probabilities aiming to maximize benefits in terms of travel time savings. The benefits for this research were generated semi-randomly within a logical range obtained from the results of previous research. The performance of each algorithm with its sets of parameters was evaluated against a Pareto frontier obtained from the generated benefits. The results show a good performance while reducing the expected number of simulations to be run to a fraction of the total, displaying a promising search technique.
Plastic goods and end-of-life tires are designed and produced with excellent polymeric materials. However, at the end of their service life, they represent a massive source of waste. Recycling technologies are currently available for reprocessing both plastics and tires, but it is still challenging to deal with the impressive quantity of wastes accumulated over the years. The vast availability, together with the needs of the pavement industry for better performing materials, is leading the efforts to reuse both plastics and tires for paving applications. In this paper, the mechanical response in the linear viscoelastic region has been evaluated for asphalt binder modified with devulcanized tire rubber, waste low-density polyethylene, and polypropylene. Results indicate that devulcanized rubber and plastics together can replace the commercial polymer commonly used nowadays.
Several exiting bridges were not designed to withstand earthquake loads effectively. Therefore, there is a pressing need to estimate the seismic losses and mitigate the earthquake risk of these critical structures. This study aims to verify the modeling approach of Reinforced concrete (RC) bridge substructures by predicting the dynamic response of an as-built bridge bent. Multi-column bridge bent previously tested in another study using large-scale experiments and quasi-static cyclic loading is chosen for the numerical modeling verification. A detailed fiber-based model of the bridge bent is developed and subjected to the loading protocol used in the experiments. Evaluations of the dynamic response obtained from the previous testing and those of the developed fiber-based model verified the adopted numerical model and enabled utilizing this idealization approach in the seismic assessment of other RC bridges in the UAE.
Drought is a natural phenomenon that occurs due to low precipitation conditions, it has negative effects on various fields such as agriculture, environment, economy, and society. In this study, drought conditions in the northern United Arab Emirates (UAE) were assessed using the Standardized Precipitation Index (SPI) and Aridity Index (AI) for annual time span. Monthly observed rainfall and temperatures data was used for a period of 10 years (2010-2019) for multiple stations. SPI and AI had similar behaviors where both showed very similar trends of drought. The trend displayed an increasing in the values that indicates wetter conditions in the future. However, some parts of UAE still having hyper arid conditions, therefore, indicating the need for appropriate drought management and monitoring.
The impact of lockdown due to COVID- 19 on air quality in Abu Dhabi Emirate was evaluated. The study investigated the changes in concentrations of PM10, PM2.5, SO2 and NO2 before and during the lockdown period. To avoid the spread of the COVID-19 pandemic in Abu Dhabi Emirates, regional lockdown procedures were taken between March 23 and June 22, 2020. The daily average level of PM10 increased by 17.5 % while PM2.5, SO2 and NO2 decreased by 12.9 %, 4.16 % and 22.76 %, respectively. The study outcomes indicated that air quality in Abu Dhabi Emirates was improved during the lockdown due to limited human activities such as transportation of people and goods
Life cycle cost (LCC) of buildings in the construction sector is an integrated method commonly used to estimate building cost through their life cycle. The building LCC is an economic decision analysis process, which assists designers in investments in new construction. Design decisions made at early stages are determining the whole life effectiveness of the building. Locally, concrete is the most used construction material with about 25% of the construction cost. The research aims to develop a cost model for three different concrete mixtures, include all cost elements from cradle to grave. The concrete mixtures considered are standard concrete, concrete with ground granulated blast furnace slag composition, and concrete with fly ash composition. The LCC allows for enhancing the overall performance of buildings, especially in the early stages. To conclude, LCC analysis will track cost performance over the economic lifespan, monitor design progress within the capital, and operating cost budgets.
Microorganisms have a significant impact on upstream operations and ultimate recovery. These microbes possess diverse metabolic functions which can be beneficial or detrimental to upstream operators, which are obligatory to be fully aware of to enhance the quality and the quantity of the produced oil. Moreover, the UAE's onshore hydrocarbon reservoirs have not been explored from the microbial perspective. Obtaining data related to UAE reservoirs would aid in proactive decision making for preventing or controlling the existing issues such as souring, formation damage, and MIC in the upstream sector. Molecular microbiological methods, including flow cytometry, metagenomic sequencing and bioinformatics will be used to generate a map of the resident microbial communities at onshore field sites. These community datasets will be contextualized in light of site metadata (from SCADA systems and water chemistry measurements) to relate the microbiology with these environmental niches.
Foam flooding is designed to solve the high heterogeneity occurred in reservoirs and improve sweep efficiency. However, high temperature and high salinity in the Middle East reservoirs with high permeability contrast after secondary recovery poses a serious problem to foam stability. Four surfactants, including two amphoteric surfactants (B-1235 and LME-50) and two nonionic surfactants (Ethomeen C/12 and Duomeen TTM), were applied to generate foams under harsh conditions in this work. Surfactant screening is based on foam capacity and foam stability. Here, we identified that only B-1235 had excellent foaming ability and the foams generated by this amphoteric surfactant kept good foam stability. The impact of oil on foam stability was also checked. Foam stability with different foam quality under high pressure and high temperature in the foam cell was evaluated to choose the optimal foam quality.
