Emission of greenhouse gases such as CO2 is highly dependent on the energy systems of the countries. In this regard, for accurate analysis of CO2 emission it is necessary to take into account the factors related to energy consumption. In the present paper, three countries including Turkey, Bulgaria and Greece are considered as case studies to model their CO2 by using an economic indicator (GDP) and consumptions of different energy sources. In this regard, Group Method of Data Handling (GMDH) is applied as the method and the required data for modeling between 2000 and 2019 are gathered. The results indicated that R2 values of the proposed model for training, test and overall datasets are 0.9997, 0.9991 and 0.9995, respectively. In addition, AARD of the mentioned datasets were around 0.71%, 1.18% and 0.85%, respectively. These values reveal significant exactness of the proposed which can be attributed to proper selection of both inputs and modeling method.
Heat transfer improvement has gained significant importance in the recent decades. In this regard, it is preferred to enhance the thermophysical properties of the fluids that affecting the heat transfer characteristics. To reach this goal, nanofluids have been introduced to be applied in thermal devices due to their relatively higher thermal conductivity that can cause remarkable augmentation in convective heat transfer. Thermal conductivity of these types of fluids is influenced by some elements including the temperature and volume fraction. Considering this fact, these factors must be considered for modeling this property of nanofluids. In the present article, thermal conductivity of the nanofluids with SiC particles is modeled by using artificial neural network as an intelligent method. It is observed that thermal conductivity of the nanofluids is forecasted with high precision. Mean Squared Error (MSE) of the model in optimal architecture was around 2.65× 10−5, for this network the R2 is 0.9986 revealing significant closeness of the forecasted data and corresponding experimental values.
The applications of unmanned aerial systems (UASs) have grown in popularity due to their simplicity and availability. The quality of UAS’s performance depends usually on adding several sensors and controllers that improve accuracy and flight performance. However, this typically increases the overall cost of the system. In this paper, a technique to enhance the performance while maintaining UAS affordability is proposed. This technique involves the use of an estimation strategy to extract hidden information from only a few sensors while improving the quality of the achieved signal. The simulation results of this method show strong performance, and are compared with another well-known estimation method.
The sliding innovation filter (SIF) is a newly developed filter that shares similar principles with sliding mode observers and variable structure techniques. The SIF is formulated as a predictor-corrector method that uses the innovation or measurement error as a switching hyperplane and forces the states to remain within a region of its state trajectory. In this brief paper, the SIF is reformulated as a two-pass smoother to reduce the effects of noise and improve the overall performance. The proposed method, known as the sliding innovation smoother (SIS), is applied on an aerospace flight surface actuator, and the results are compared to the original filter.
In this brief work, a novel filtering technique that combines the newly developed sliding innovation filter with a multiple model strategy is proposed. Introduced in 2020, the sliding innovation filter is a relatively new filter used for state and parameter estimation. Based on variable structure techniques, it shares the same principles with sliding mode observers. The filter is robust and stable under system modeling uncertainties. The proposed method multiple model-based sliding innovation filter is tested on an electrohydrostatic actuator (EHA) and the results are discussed.
This brief work introduces the use of the relatively new sliding innovation filter in the field of fault detection and diagnosis. This important area is part of signal processing techniques that are widely used in industrial practice, telecommunications, optical systems, and robotics, to name a few. This filter overcomes robustness issues during faults caused by modeling uncertainties. This brief work explores the properties and quality of the filter outputs applied on an electromechanical system. The results are compared with the well-known and studied Kalman Filter.
This paper contains a comparison of several sigma-point Kalman filters, including the unscented Kalman filter (UKF), the cubature Kalman filter (CKF), and the central difference Kalman filter (CDKF). The comparison is based on a simulated electro-hydrostatic actuator, which is commonly used for flight surface actuation in aerospace systems. This brief study compares the response, convergence rate, root mean square error, the maximum absolute error, and the stability of these sigma-point Kalman filters.
Spent Nuclear Fuel (SNF) management is one of the major challenges in the nuclear power field. Several disposals, reprocessing and recycling techniques and concepts are proposed and implemented, however, the associated challenges have not been completely resolved yet. Therefore, in this work another useful application of SNF in space applications is explored. The overarching goal of this work is to explore the possibility of using nuclear spent fuel in the so-called ion-thrusters. The proposed design consists of a jet engine that utilizes the extraordinary radioactivity from SNF to ionize a propellant that is used as the thrust.
A preliminary basic design is proposed and then evaluated based on simulation predictions. MCNP is used to model a simplified design of the proposed Spent Nuclear Fuel Ion Propulsion Engine (SNIP) and estimate the ionization reaction rate and therefore the thrust exit velocity and specific impulse of the thruster.
This work introduces a monte carlo based technique powered with the ability to estimate the individual uncertainty contributions of each model parameter. The proposed technique utilizes the so-called parameter space analysis to identify the importance of influential Degrees of Freedom (DoFs) with respect to the uncertainty quantification problem. Once determined, these DoFs can be used to define and solve a linear system of equations based on linearizing the model of interest to determine the uncertainty contribution of each DoFs in conjunction with the monte carlo based samples.
This paper gives an overview about the available geothermal power plants. The second part there is a comparison between Geothermal Energy with other sources of Renewable Energy. The advantages and disadvantages of geothermal energy and power plant are discussed. Finally, a case study of a geothermal power plant located in Paris, France was simulated using System Advisor Model to observe the results. All the data input was obtained from a published research paper. Moreover, this study reviews the main functions of dry, flash and binary geothermal power plants.
Double rotor wind turbines are studied for improving wind energy harvesting. The location, size and number of blades of the second rotor are important factors which affect performance of the double rotor wind turbines. These and other blade parameters may influence the drag and output power characteristics of the wind turbine. In the present work, the drag forces acting on two double rotor wind turbine configurations are experimentally investigated using wind tunnel testing. The two configurations are cocurrent and counter current double rotor wind turbines. A single rotor wind turbine is used as a comparison reference to compare with the two double rotor wind turbine configurations. Models of the three horizontal axis wind turbines were produced using 3D printing technology and were tested in the wind tunnel while wind power augmentation was also evaluated. The experimental results revealed an increase in the value of drag coefficient when a second rotor is added. The increase on the drag coefficient depends on the configuration, the size and location of the second rotor. The drag coefficient for the counter current rotation double rotor is close to the single rotor wind turbine; however, an increase of about 25% on drag coefficient is observed for the case of cocurrent double rotor wind turbine.
Geothermal energy is one of the most attractive clean, sustainable and renewable energy sources due to its independency on weather conditions as the case for solar and wind energy. A hybrid geothermal/solar system for power production is proposed. The proposed system could be considered as highly efficient and cost-effective system. A concentrated solar thermal power generation (CSP) of type parabolic trough collector (PTC) is selected to improve the efficiency of the cycle and increase the electricity output by increasing the temperature of the incoming geothermal fluid. By using this system, the net power generation will increase up to 10% in a month compared to normal systems, and 7.6% in a year.
This work investigates design of a drone for transporting valuable objects. All the required components for building the drone and discussed. The drone can carry a maximum payload of 10 kg for a long duration over reasonable distance. This is achieved by using a hybrid mechanism that combines two 25cc fuel engines with four electrical motors operating by two 6S lithium polymer (LiPo) batteries. The hybrid mechanism is chosen as it tackles the electric drone main problems which are: short flight duration and low payload-carrying ability.
As the world develops, new and more advanced ways of transportation are invented; i.e. drones. Drones are used in several applications. However, the drone market does not utilize the need of medical emergency drones today, where these drones can be used to save countless lives in severe cases, e.g. sudden cardiac arrest. In case of cardiac arrest, defibrillators may save the life if it reaches the victims within short time. It raises the survival rate exponentially. Nonetheless, reaching the victims in a short period of time is challenging as the weight of the equipment is large. This work aims to design an autonomous drone that will be able to carry heavy payloads (portable medical equipment) while being fast and agile. The medical equipment/components are studied to choose the most fit for the proposed design in terms of efficiency and weight. The drone’s components are compared and studied in detail, allowing to choose the fittest motors, ESCs, frame, battery, and propellers. After which the quadcopter’s ability is expected to successfully achieve the objective of trying to save victim life in the city of Sharjah. In addition, the work includes a SolidWorks analysis to the design of the drone’s mechanical components to estimate the possibility of failure.
Given the growing global demands on energy and fresh water, nuclear energy has become a promising source of power and freshwater production. Maximizing the nuclear power plant efficiency requires running the plant at maximum power capacity, however, the actual load might not require such huge power supply (1000 MWe +). Power plants operation with high to maximum efficiency has a profound effect on financial prices and environmental conditions for clear reasons which commands the attention towards various expensive and not efficient energy storage techniques (thermal, electrical and hydro). In this work, energy storage is substituted by a desalination plant that utilizes the excess energy to power the desalination unit. Therefore, this work explores the potential of water desalination as a proxy for energy storage systems in nuclear power plants. Various water desalination technologies are examined and compared in terms of economy, water quality and production capacity. Barakah nuclear power plant is used as a case study with APR1400 reactor design. On the desalination side, Reverse Osmosis (RO), Multi-Stage Flash (MSF), Multi-Effect Distillation (MED) and hybrid combinations are studied.
The Earth is made up of 71% water, but the world still has water shortage, so what is the reason? The answer to that question is that 97% of the water available is salty water, and all of it has high salt content, which makes is impossible for drinking, consuming, and irrigation. The solution for this problem is desalination, it is the only way that we can get drinkable water, other than fresh resources. But desalination usually consumes a huge amount of electricity, so other sustainable sources to help in the process of desalination in a cleaner and more cost-effective way should be considered. In this work, two main technologies for water desalination using geothermal-powered systems are presented and discussed. These technologies are promising, especially in gulf region, where geothermal energy is available generously.
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