The APR1400 nuclear power plants (NPPs) in the UAE are using fuel systems with UO2 fuel and ZIRLO cladding. So far, the fuel systems during normal operation conditions have shown good performance in other NPPs. However, the hydrogen explosion that had occurred during the Fukushima-Daiichi NPP Accident was caused by zirconium-steam reactions at high temperature. Since then, Research & Development (R&D) activities have been extensively performed in many countries for developing new fuel systems. Such new fuel systems are called Accident Tolerant Fuels (ATF) that can tolerate loss of active cooling in the reactor core for a considerably longer time than the conventional UO2/Zircaloy systems. Since only four NPPs will be operated in the UAE, it would not be recommended to develop a new fuel system by themselves. Instead, the UAE would adopt one from candidate ATF concepts developed by other countries. For this purpose, there must be (i) ATF selection methodology and (ii) Emirati experts on ATFs who will be in charge of the ATF adoption process.
This project aims at developing the selection methodology and strategy of an ATF for APR1400 and training Emirati professional manpower on the ATF R&D. To achieve these goals, three tasks will be conducted: (i) Task 1 – Development of ATF selection criteria for APR1400; (ii) Task 2 – Evaluation of high-temperature oxidation behavior of coated ATF cladding materials; (iii) Task 3 – Development of ATF selection methodology for APR1400. All the tasks will be conducted under the collaboration with KAIST and KAERI that have extensive experience on ATFs. Emirates Nuclear Energy Corporation (ENEC) employees and graduate students at Khalifa University will participate in all the tasks, which will contribute to the capacity building for ATFs in the UAE. By adopting an ATF concept to the NPPs in the UAE, it is expected that the possibility of hydrogen explosion during severe accidents will be eliminated. Also, by widening the safety margin for the operation of the NPPs and increasing coping time during severe accidents, the safety of the NPPs during normal operational conditions will be greatly enhanced.
One of the main issues of hydrogen economy is the electrolytic production of H2 from aqueous solutions and its utilization in fuel cells to generate energy. In this scheme, hydrogen acts as an energy carrier. This scenario is gaining increasing attention together with other energy-generating technologies, such as solar and nuclear technologies. Electrolysis is in principle a clean technology, but it requires a great consumption of electrical energy. The present work concerns selection, production, and optimization of electrocatalytic materials to improve the efficiency of hydrogen electrolytic production by reducing operational costs.
From a catalytical point of view, H2 evolution is a facile reaction. It is possible to further reduce energy losses by maximizing the surface area of electrodes or by activating cathodes. In the meantime, scrutiny of efficient electrode materials for O2 anodic evolution is needed. In fact, the reaction of O2 evolution is more energy demanding and affects the global energy balance severely. Therefore, development and optimization of the technology of electrolytic hydrogen production implies the evaluation of both cathodic and anodic reactions.
Following a research project conducted from 2018-2019 at a laboratory scale called Suntrap, Khalifa University, Masdar, and Azelio AB (Sweden) signed a new research collaborative agreement in September 2019 to install Azelio’s electrical thermal energy storage system at the Masdar Institute Solar Platform in summer 2020.
The innovative system utilizes recycled aluminum used as a phase change material (PCM) to store electricity or heat as thermal energy and can be applied to renewable energy in general (photovoltaic (PV), concentrated solar power (CSP), or wind) or to excess grid electricity. A Stirling engine can convert this stored heat into electricity on demand. The pilot will be installed at MISP. It will be charged using clean electricity from PV panels and will produce 50 kW of electricity at night to power the Masdar Park.
The Seawater Energy and Agriculture System (SEAS) requires a very well-integrated operation of aquaculture, halo-agriculture, and mangrove silviculture systems to produce sustainable biofuels for aviation among other relevant outputs. In order to achieve an optimal design and operation in a SEAS, a reliable detailed understanding of the dynamic interactions between process subunits and elements is essential. We propose an approach consisting of two main lines of work towards a primary goal of optimized design and operation of SEAS plants.
A first line of work aims at building up reliable analytical techniques, monitoring protocols and SOPs to achieve and maintain in situ detailed knowledge of the chemical composition and microbial activity across the different SEAS subunits and compartments. Such characterization knowledge, and the capacity to monitor its changes, is essential to know the state of the complete system. A comprehensive sampling campaign, tailoring existing and developing new analytical techniques to the SEAS conditions, will produce robust protocols and SOPs to ensure high-reliability information about the system state at any moment in time. A second line of work aims at the development of a detailed predictive dynamic mathematical model of the integrated process and its subunits. The model will be based on material balances and contain detailed biokinetic descriptions of both chemical and biological conversions and transport processes of relevance. Advance space resolution modeling will be developed for parts of relevance in specific SEAS subunits. The model, coupled with good quality data for calibration, will have predictive capabilities allowing for its direct application to the optimization of SEAS design and operation under multiple scenarios that will be evaluated to inform the SBRC for scale-up design and operation. The principal investigator, Dr. Rodriguez, brings his world class expertise in bioprocess modeling in addition to the excellent lab facilities and resources available at Khalifa University’s Masdar Institute.
The energy consumption in Abu Dhabi has tripled within the last 10 years. Much attention has been devoted to the challenge of increasing generation capacity to meet this demand; yet, of equal concern is the increased load on the system and the extent to which this will stress the transmission network and increase susceptibility to dynamic instabilities.
Power system stability is one of the most important issues for secure and reliable network operation. Any failure to address stability concerns can lead to widespread blackouts and even system collapse. This problem is particularly relevant in the UAE context given the stated objective of the Abu Dhabi and UAE governments to significantly increase the penetration of renewable energy (RE). This will result in greater spatial distribution and temporal variability in electricity generation, both of which would impose additional strain and stability threats on existing networks. In addition, the recent completion of GCC interconnections between the UAE, Oman, and KSA has significantly changed the stability profile of the UAE power system and raised concerns about inter-area oscillations (IAOs). IAOs are a threat to wide-area stability, which are very difficult to detect using conventional Energy Management Systems and could lead to sweeping blackouts that occur within minutes. Existing tools for power system stability assessment are mainly based on “what if” scenarios about system disturbances, and may be inadequate given the complexity of these challenges due to the uncertainty of RE power generation and nonlinearities of power system.
Therefore, the primary goal of this research project is to develop a prototype for a commercial (offline/online) tool (for the power system operator) that will facilitate effective power system stability assessment, visualization, and enhancement (SAVE). The SAVE tool will utilize real-time measurements and full system observability to reliably determine stability margins in the presence of uncertainty resulting from RE power generation and load demand, and will enable small and large signal stability assessments. In this context, advanced methods of individual invariance and functions will be developed and combined with Artificial Intelligence (AI) algorithm, along with data analytics based classification engine to precisely estimate the domain of stability and to predict the system transient stability margins. Furthermore, a visualization system will be developed to support human-in-the-loop classification, diagnosis of the transmission system events, and the visualization of system stability. In addition, power system stability enhancement and the IAOs problems at the interconnections will be investigated, focusing on two key aspects: the real-time detection of IAOs and the development of an advanced damping controller. Finally, the SAVE tool will be implemented and validated for TRANSC network operation. This project is conducted with the active collaboration and support from TRANSCO and Manitoba Hydro International.
The Advanced Thermal-hydraulic Test Loop for Accident Simulation (ATLAS) test facility was constructed with the aim of developing new safety concepts and performance verification of the APR1400 power plant. As a result, valuable large-scale integral effect test (IET) database has been generated and effectively utilized for the Domestic Standard Program (DSP) and the International Standard Program (ISP). Furthermore, due to the successful completion of the ISP-50, in which 14 organizations from 11 OECD countries participated, ATLAS has been recognized as one of the important IET facilities worldwide.
A follow up international project has been initiated since 2014 and continued to the second phase by OECD/NEA to use the ATLAS facility in providing additional experimental measurements for common safety issues relevant to PWR consisting of five topics related to beyond design basis accidents. The United Arab Emirates is one of the countries participating in this project with the goal of increasing the local human capabilities and the required know-how on safety analysis studies. To achieve this, FANR and Khalifa University are planning to cooperate in taking part of the ATLAS project to produce numerical predictions for the pre-test prediction and the post-test simulations. The pre-tests rely on only the specification of the experiment given by the operating agency (OA). The post-test simulation can be performed after acquiring experiment data from OA. The codes to be used for this numerical study are the system codes RELAP5 developed by the US Nuclear Regulatory Commission (NRC).
At the start of the project, the steady-state input deck of RELAP5/MOD3 for ATLAS facility is to be provided by the facility operating agency, KAERI, to all participants. Then, each participating agency has to generate its transient input in accordance with proposed experiment scenarios. It goes without saying that even if the steady-state input deck is readily provided, the generation of transient input is toughly dependent on experience and know-how of user groups. Additionally, the given steady-state inputs also need to be modified and some components have to be remodeled in order to cope with the newly proposed scenario. For this reason, each participating agency comes back with different results even though they are using the same safety analysis code.
As mentioned above, RELAP5 will be used for both pre-test and post-test numerical predictions. The symbolic nuclear analysis package (SNAP) will help the input preparation. The schedule of pre-test and post-test runs to be performed will follow the planned schedule by the OA. Preparation of input, running simulation, debugging process, interpretation of results, and all lessons learned will be consolidated as a training material for increasing local human capability on safety analysis.
Additionally, at least one local component will be selected from each proposed scenario to investigate the detailed thermal hydraulic phenomena using the CFD approach. Simulation results from RELAP5 will then be mutually compared and validated with the CFD predictions, to be conducted at Khalifa University, and with the experimental data from the ATLAS facility.
The nuclear power plants (NPPs) in one site may share (cross-tie) structures, systems, and components (SSCs) either in normal operation or in demand. For instance, the sharing of electrical power source as a cross-tie of emergency diesel generators (EDGs) could add advantages to the reduction of the station blackout (SBO) frequency for the unit with extended SBO. At the same time, the cross-tie is associated with risks that can limit the shared systems from performing its intended functions. The cross-tie risks that introduced from sharing need to be addressed and managed systemically.
First, the research will start with the framework of the development of a methodology for risk analysis and management in sharing of electrical power in nuclear power plants. Second, we will investigate detailed identified issues of the electrical cross-tie in extended SBO event as a risk of dependency between multi-unit site. Third, we will elaborate the probabilistic risk assessment (PRA) in assessing the safety of the NPP with the examination of common cause failures (CCFs) impact on the PRA risk quantification as a case study. The methodology of quantifying the risk of sharing of electrical cross-tie is developed in this stage and will be modeled in different cases. Lastly, we conclude the risk management process to access the cross-tie risk of multi-unit in different accident scenarios of SBO. Related analysis such as sensitivity, importance measures, risk, and cost analysis will be utilized in supporting the risk-informed decision-making process in selecting between mitigation options and reducing the SBO risk.
The Alibaba Cloud-Khalifa University Joint Innovation Laboratory of Artificial Intelligence for Clean Energy focuses on three research themes: (i) AI-assisted subsurface energy production and gas processing; (ii) machine learning-enabled energy materials development and smart manufacturing; (iii) and AI/cloud computing-empowered smart renewable energy systems. With the sponsorship and cloud computing support from Alibaba, nine KU professors, three postdoctoral research fellows, and multiple PhD students are dedicated to proposing innovative and smart solutions towards the Fourth Industrial Revolution.
In this project we aim the development of economically feasible production and recovery of VFAs as valuable platform chemicals, at high concentration and purity, from agro-industrial hydrolysed bio-waste. To achieve this, natural mixed microbial culture fermentation (MCF) reactors will be integrated with in-situ product recovery via Deep Eutectic Solvent (DES) and extraction. Such integration will achieve higher purities and both microbial product inhibition and variability be subsided.
The input of the process is hydrolyzed wet agro-industrial wastewater streams. This input will be converted into targeted high-value products including acids as propionate, butyrate, lactate, succinate, and alcohols. By coupling the continuous production with extraction of products and inhibition removal a boost in microbial productivity is sought to the next level of economic feasibility.
The cutting research led by the Co-PI and participants in developing powerful and very novel solvents together with the PIs’ expertise in reactor design, modelling, and operation of microbial fermentation reactors and advanced microflow extraction technology provide a unique opportunity to achieve a breakthrough in the economics of bio-waste valorization.
Electrification of transportation presents a paradigm shift and a key enabler for the future 21st century city concept. “More” electric planes, ships, cars, and trains are finding more interest and are receiving increased attention from policy makers and researchers globally. In the UAE, the government has setup plans to develop suitable infrastructure for autonomous electric vehicles under the “UAE Green Agenda 2015-2030.” At least 25% of vehicles on the road in the UAE need to be electrically propelled vehicles by 2030. Yet, a number of obstacles still exist that make electrically propelled vehicles less attractive compared to internal combustion engine vehicles. One of the biggest challenges in this domain has to do with the limited energy storage capabilities of batteries. The energy density of current Li-ion batteries is still far-less than that of gasoline, which significantly limits the driving distance. In addition, the high cost of battery packs, relatively long-charging time required, and relatively short lifetime are all challenges that need more attention.
This project will consider the system and component level performance of a conventional electric vehicle powertrain system, which basically consists of 1- Storage Unit (Battery Pack) 2- Power Electronic Drive Circuit 3-Electric Motor 4- Speed Step-Down Gear Box 5- Control Circuitry. On a component level, special attention is allocated to the design of the propulsion motor were the development of a high-speed, magnetically geared in-wheel electric motor for direct drive connection will be pursued. Power conversion efficiency, size, and mass are some major metrics to be considered in the design process. A proto-type should be built and tested at the end of the project.
The plan to operate the UAE’s first nuclear plant in 2018, installation of up to 5000 MW of renewables in Mohammad Bin Rashid Al Maktoum Solar Park, initiatives to increase smart meters and energy storage in the UAE’s distribution system, the Ministry of Energy’s new incentives for using electric vehicles, and the Dubai Electricity and Water Authority’s plans to install up to an additional 200 electric vehicle chargers coupled with the upcoming 900 megawatt solar photovoltaic (PV) plant in Sweihan make it the perfect moment for positioning a center on Advanced Power and Energy. This rapid and increasing change in the UAE’s power system will open the doors to new challenges but also unique opportunities for developing innovative ideas and solutions for optimizing and advancing energy delivery. The Center covers a broad spectrum of pressing and important energy-related issues, including renewable energy integration, power electronics and conditioning, distribution and transmission system operation and high-voltage engineering.
The Emirates Nuclear Technology Center (ENTC) is designed to provide a hub to address the present and future research requirements to support the UAE’s nuclear power program and deliver our key stakeholder’s goals for the delivery of safe, clean and efficient nuclear energy to meet the UAE’s 2030/2050 visions, while protecting the public, workers and the environment. Safe operation and management of nuclear power is based on the highest standards of engineering design, construction, operation, and waste mitigation and the Emirates Nuclear Energy Corporation (ENEC) is presently building four 1,400 MWe nuclear power plants to meet the industry’s highest standards, which will be overseen and safeguarded by the Federal Authority of Nuclear Regulation (FANR); ENEC and FANR being the ENTC’s key stakeholders.
The ENTC’s mission is to conduct research in the main thematic areas of nuclear technology necessary to provide a risk informed decision basis for the safe operation of the nuclear power plants, while estimating the consequences should faults occur. Our research in the main thematic areas of Nuclear Safety and Systems, Nuclear Materials/Chemistry and Radiation Safety in the Environment will provide data for informed decision while innovation in methodology and practices will aim to minimize the risks of faults. We will aim to provide the UAE with branded products to be a leader in future nuclear technology.
Current challenges faced by energy and environment sectors necessitate the development of advanced and efficient materials and technologies. For instance, effective systems are needed to store energy, remove pollutants from water streams, separate different acid gases from gas streams, catalyze reactions, enhance the lifetime of existing infrastructure, etc.
In this respect, the main objective of the project research is to develop nanostructured materials with a multitude of applications related to adsorption, energy storage, and environment sectors. Some of these nanostructured materials include doped graphene, graphene/metal oxide nanoparticles, graphene/MOF-COF hybrids, graphene cryogels, etc., which can also be incorporated in various polymer matrices to further enhance their application.
Ocean color measured from satellites provides daily global estimates of marine inherent optical properties (IOPs). The IOPs refer to absorption and backscattering of the water. The IOPs of natural waters are the most significant factors affecting light propagation within water columns, and thus play indispensable roles on estimation of aquatic biomass, primary production, and carbon pools.
While numerous IOPs retrieval model exist, most are similarly constructed and few are appropriately parameterized for all water masses (inland, clear, turbid, shallow and deep) for all seasons.
For shallow and turbid regions like Arabian Gulf, IOPs-based model is often preferred for estimating chlorophyll-a (Chl-a) concentration over empirical and some semi-empirical algorithms. However, IOPs have never been studied in the Arabian Gulf and yet uncharacterized.
Therefore, the objective of this project is to develop a satellite based model for estimating both IOPs and Chl-a and understanding the bio-optical properties of these waters.
Open source ocean color satellite data such as MODIS, VIIRS, LandSat, and Sentinel will be used. To validate the performance of the developed model and make it robust, in situ measurements of IOPs have to be collected in this region.
The energy dependence on fossil fuels is no longer a solution for the future, and therefore, cleaner-renewable energy technologies is the way forward to a sustainable, energy efficient economy. This project aims for the effective reutilization of two major waste products of fuel industry, i.e., bioglycerol and sulfur, into a cleaner, cost-efficient energy technology. This will be achieved by, i) utilization of sulfur to produce efficient S-doped MWCNT electrodes; ii) utilizing bioglycerol as a renewable fuel; and iii) indirectly utilizing sulfur via peroxodisulfate as a novel glycerol oxidant in developing an electro catalytic “Bioglycerol-Peroxodisulfate fuel cell”. The reutilization of bioglycerol and sulfur into clean energy efficient technologies shall provide longevity to both the biodiesel and petroleum industry, while the development of bioglycerol- peroxodisulfate fuel cell could provide an alternative pathway to address the energy needs of the society, while simultaneously preserving the environment for development of a sustainable, energy sufficient society.
Iron & steel (I&S) and aluminum (Al) manufacturing are energy- and GHG-emissions intensive, and considered among the most difficult-to-decarbonize sectors. The project seeks to develop sustainable power-to-gas (PtG)-based strategies driven by competitively priced low-carbon electricity toward the decarbonization of these industries, focusing on direct reduction of iron (DRI)-electric arc furnace (EAF) I&S processes and alumina refining calcination processes. These strategies will enable switching from natural gas to electrolytic hydrogen and synthetic natural gas (SNG) to supply process heat, reducing agents and electricity. Tailored PtG processes will be developed and integrated with I&S/Al processes, while minimizing changes in process equipment and cost. Oxyfuel combustion processes will also be integrated to efficiently and affordably sink and recycle CO2 for SNG synthesis, in conjunction with waste energy/material utilization. The integrated PtG-I&S/Al processes will be thermodynamically, economically, and environmentally evaluated and optimized, and benchmarked with existing industrial and alternative decarbonization (carbon capture) approaches.
This project will focus on the design, development, and demonstration of transparent, tracking integrated photovoltaic concentrator (CPV) modules for integration into buildings and greenhouses. Of particular interest to the region, the technology under study has the potential to substantially alter the cost structure and sustainability of greenhouse agriculture by providing sufficient integrated energy generation to power climate control, irrigation, and automated maintenance systems. Furthermore, such technology is expected to find commercial success in the building sector, enabling the development of high-efficiency, aesthetically interesting building integrated photovoltaic products. The project will draw on the PIs’ experience in solar optics and tracking system design, photovoltaic device design and characterization, energy use in buildings, and solar energy economics to develop workable solutions for building-integrated and agricultural CPV. We anticipate the development of systems that will be ready for scale-up and commercialization by the end of the project.
The UAE’s Barakah nuclear power plant will start operation soon. However, past disasters (e.g., the Fukushima Nuclear Power Plant in 2011 and the Chernobyl disaster in 1986) arose significant social/environmental concerns. Advanced technologies are therefore needed to ensure reliable collection and treatment of radioactive nuclear waste streams. This project will develop low-cost, highly efficient bio-adsorbents for removing radioactive isotopes such as iodine (129I, 131I and metals ions 60Co) produced in a nuclear reactor and found in its waste-waters. Bench and Pilot-scale experiments will be conducted. Chitosan, a derivative of chin (shell of shrimps/crabs/lobsters) will be cross linked with various cross linkers, molecularly imprinted for each isotope and tested for their practical separation performance. Such adsorbents can be economically produced in large quantities and able to remove specific isotopes at a very low concentration.
The energy sector enters the era of smart grids where loads changed from AC to a mix of AC and DC. Accompanying these changes is the transformation of conventional AC distribution systems into hybrid AC/DC Active Distribution Systems (ADSs). These ADSs host distributed and renewable generation units, energy storage devices, load management controllers, and grid-automation devices.
This project aims to facilitate the seamless integration of hybrid AC/DC networks into existing ADSs through:
The main goal of the proposed research work is to design and develop a practical crowdsourcing-based solution (both power electronics hardware interface and software platform) for vehicle-to-vehicle (V2V) power transfer that would enable the following: (i) allow electric vehicle (EV) users to publish their charging needs; (ii) search for EV users who are willing to support charge/energy and identify the best supplier (based on charging time, price, EV battery type, etc); (iii) decide the best suitable charging option (external dc/dc converter interface, existing on-board chargers, or wireless); (iv) after energy/charge transfer, execute a secure payment; and (v) based on previous V2V experiences and using social networking, update/increase the trust level of users. The primary outcome of this project would be demonstrating V2V as a viable option to further electric transportation where EV users will not only help each other but can also earn money by selling battery charge/energy.
Streets play significant roles in meeting multiple sustainability objectives. This research addresses Abu Dhabi’s and Dubai’s street connectivity at the neighborhood (local) and city (global) scales. It focuses on two parameters of street network analysis: efficiency and centrality. Efficiency is evaluated in terms of directness, noting that network designs that provide short and direct access between origins and destinations are more efficient. Centrality is evaluated using graph theory metrics that enable the identification of high- and low-accessibility locations within networks. Research has shown that network centrality metrics are useful for capturing location advantage, a significant factor for land use distribution. An understanding of centrality and its impacts makes it possible to plan land uses that bring destinations closer to residences, an important factor in environmental, economical, and social sustainability. The proposed project will offer scientifically grounded strategies and policies that will enable various stakeholders to design more sustainable street systems and land uses.
There has been an increasing global interest in the integration of renewable energy resources (RESs) and energy storage systems into the distribution networks. Moreover, large-scale deployment of electric vehicles and their charging stations has been gaining interest worldwide. Inspired by the “System of Systems (SoS)” concept, we envision the future power distribution systems as “Microgrid of Microgrids (MoM),” which is a group of dedicated microgrids with their own generation, storage, and controllable loads that are capable of operating independently and flexibly reconfigure themselves to create new groups of more complex system(s) that improve system reliability, stability, and efficiency through an adaptive control and self-healing strategies. Such MoM concept has never been proposed or investigated before. This proposal intends to develop a new three-level, hierarchical adaptive control, and self-healing strategies for smart MoM distribution networks to enable flexible-boundaries and coordinated-structure of multiple microgrids to improve the overall distribution system performance.
The proposed project combines renewable solar energy and combustion engines. It is proposed to make feasible the use of fuels, which can be produced by utilizing (i) solar energy to electrolyze water and produce hydrogen and (ii) CO2 released by combustion processes to produce high-energy-density liquid fuels, such as alcohols. So far, the major obstacle in the use of such fuels is the toxicity of their exhaust gases. The main goal of the project is to identify specific additives, which will reduce the toxic products, either directly by chemical means or indirectly by modifying the ignition delay. These additives will be identified algorithmically with the CSP method and the resulting findings will be validated by experiments, in which the toxicity of the exhaust gases will be measured. Successful completion of the project will establish a route that will effectively reverse combustion and regenerate fuel from combustion products.