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Background:Seawater greenhouse (SWGH) is a technology established to overcome issues related to open field cultivation in arid areas like high temperatures and freshwater shortage. So far, five pilot Seawater greenhouses were built around the world; in Spain, United Arab Emirates, Oman, Australia and Somaliland. All the patents related to the Seawater greenhouse components and designs mentioned were reviewed.Methods::The Seawater greenhouse adopts the humidification-dehumidification (HDH) concept where evaporated moisture from saline water source is condensed to produce freshwater within the greenhouse body. Many advancements have been made throughout the past 25 years to optimize the Seawater greenhouse by means of structural improvement, heat distribution, condenser design and material, source of feed water and the evaporator via both trial-and-error and simulation approaches. The latter included numerical, mathematical, analytical and artificial neural network simulations. Various condenser designs were adopted in order to increase freshwater production to meet the irrigation demand of the seawater greenhouse.Results and Conclusion:To make the Seawater greenhouse self-sufficient in terms of energy production, the use of renewable energies and nonconventional sources was also investigated like the use of geothermal, solar and wind energy to produce electricity for the greenhouse operation and for other requirements as well. The use of reverse osmosis along with reverse electro dialysis to produce freshwater and electricity in the seawater greenhouse, was also one of the ideas suggested to improve and solve the associated constraints. Direct contact dehumidification is another development suggested to improve the condensation rate. This new approach seems to be very promising as it involves low capital, operation and maintenance costs, high freshwater production, and fouling- and corrosion-free.

Background: With the advent of IoT, the deployment of batteries with a limited lifetime in remote areas is a major concern. In certain conditions, the network lifetime gets restricted due to limited battery constraints. Subsequently, the collaborative approaches for key facilities to reduce the constraint demands of the current security protocols. Objective: This work covers and combines a wide range of concepts linked by IoT based on security and energy efficiency. Specifically, this study examines the WSN energy efficiency problem among IoT devices and security for the management of threats in IoT through collaborative approaches and finally outlines the future. The concept of energy-efficient key protocols which clearly cover heterogeneous IoT communications among peers with different resources has been developed. Because of the low capacity of sensor nodes, the energy efficiency in WSNs has been an important concern. Methods: In this paper, we present an algorithm for Artificial Bee Colony (ABC) which reviews security and energy consumption to discuss their constraints in the IoT scenarios. Results: The results of a detailed experimental assessment are analyzed in terms of communication cost, energy consumption and security, which prove the relevance of a proposed ABC approach and a key establishment. Conclusion: The validation of DTLS-ABC consists of designing an inter-node cooperation trust model for the creation of a trusted community of elements that are mutually supportive. Initial attempts to design the key methods for management are appropriate individual IoT devices. This gives the system designers, an option that considers the question of scalability.

Background: The study of kerosene fuel for gasoline engines is of great significance to the supply, management, storage and transportation of military fuel, as well as its safety. Small aviation two-stroke kerosene engine fuel injection controller is the key technology of kerosene engines. It is very important to improve the performance of kerosene engine by controlling the air-fuel ratio accurately. Objective: The initial injection pulse spectrum was firstly obtained by numerical calculation in the absence of kerosene injection pulse spectrum, and then the injection controller was designed based on the initial injection pulse spectrum. Methodology: Firstly, a numerical model of the whole engine was established by using BOOST software. The air mass flow data of the inlet was obtained through numerical calculation. The amount of initial engine fuel injection was calculated according to the requirements of air-fuel ratios in each working condition, from which an initial injection pulse spectrum was obtained. Then, based on Free scale 16-bit embedded micro-controller MC9S12DP512, a kerosene engine fuel injection controller was developed, together with the circuit was also designed. According to the initial fuel injection pulse spectrum, a two-dimensional interpolation algorithm was developed by using assembly language and C language mixed programming, and the anti-electromagnetic interference ability of the controller was further enhanced. Finally, the accuracy of the initial injection pulse spectrum and the performance and reliability of the injection controller of the kerosene engine were verified by the kerosene engine bench test. Conclusion: The experimental results show that the numerical model was accurate, and the development time of the injection controller was shortened by using the numerical model to calculate the initial injection pulse spectra. The developed controller was stable and reliable, which can meet the control requirement.

Background: Most non-developing and under developing countries strive hard to tackle the situation of power crisis and to combat the imbalance between the power generation and load demand, especially in the case of increasing of the population. In this situation, the load shedding scheme has been extremely implemented as a fast solution for unbalance conditions. Thus, load shedding is crucial to investigate supply-demand balancing in order to protect the network from collapsing and to sustain stability as possible; however its implementation is mostly undesirable. Objective: prioritize the loads according to their importance and apply reduction strategy in the demands while the supplied power to the important loads such as health care and security installation are kept intact without any interruption as possible. Methods: The conventional methods of load shedding lead to over or under shedding and this may lead to many problems with the network. Under the scheme, these methods disconnect the load or the entire feeder without considering their priorities and may not perform as anticipated. In this work, we propose a logarithmic reduction method to reduce the load according to the priority and day life criticality. The method for shedding the load base on Reduction Matrix and which in turn depend on the priority demands. Results: The higher priority demands are fed with a reliable power source by the real time monitoring of the network accompanied with power reducing for the lower priority demands. Conclusion: We test a real data sample provided by the Iraqi national grid control center in Baghdad. Our simulation results prove effectiveness and practicality of the applied method paving the way for possible applications in power systems.

Background: With the rapid consumption of non-renewable energy such as coal, oil and natural gas, the growing demand for environmental protection, the re-utilization of low-grade waste heat energy has become an important approach to improve energy utilization efficiency. As a new technology, organic Rankine cycle (ORC) power generation technology can make full use of and convert heat waste. Objective: Both the suction and discharge pressures of the scroll expander have a certain influence on the output and motion characteristics of the orbiting scroll. By studying the position and arrangement of the suction and discharge ports of the expander, a theoretical basis can be provided for the design of these ports. Methods: For the scroll expander using working fluid R134a, establishing the geometrical and three-dimensional models of the suction and discharge ports of the scroll expander with different positions and structures, based on the Computational Fluid Dynamics (CFD) method. Results/Discussion: Through comprehensive comparison, it was found that the structure of the original suction pipe outperformed any of the other structures; the fluid flow in the original discharge pipe was more complicated, and the simplified model of the commonly used scroll mechanical discharge pipe had the optimal performance. Conclusion: Compared with the original prototype SEI2, the suction port area is increased, and the suction port pulsation intensity coefficient and the suction pressure loss coefficient of the prototype SEI4 are reduced by 34.833% and 5.264% respectively, which can make the suction process of the expander more stable. Since the unilateral discharge ports Outlet3 and Outlet5 are located in the moving and static regions, respectively, there is a difference in the perturbation of the outlet fluid by the movable scroll, so that the gas pulsation intensity at Outlet3 is nearly double that of Outlet5.

Background:Enabling industrial environment with automation is growing trend due to the recent developments as industry 4.0 centric production. The industrial wireless sensor network environments have a number of constraints, including densely deployed nodes, delay constraint for mechanical operation, and access constraints due to node position within instruments. The related literature have applied existing models of wireless sensor network in industrial environment without appropriate updating in the different layers of communication, which results in performance degradation in realistic industrial scenario.Method:This paper presents a framework for Energy Oriented Cross Layer Data Dissemination Path (E-CLD2P) towards enabling green computing in industrial wireless sensor network environments. It is a cross-layer design approach considering deployment of sensors at the physical layer up to data dissemination at the network layer and smart services at application layer. In particular, an energy centric virtual circular deployment visualization model is presented focusing on physical layer signal transmission characteristics in industrial WSNs scenario. A delay centric angular striping is designed for cluster based angular transmission to support deadline constrained industrial operation in the WSNs environments. Algorithms for energy centric delivery path formulation and node’s role transfer are developed to support green computing in restricted access industrial WSNs scenario.Results:The green computing framework is implemented to evaluate the performance in a realistic industrial WSNs environment.Conclusion:The performance evaluation attests the benefits in terms of number of metrics in realistic industrial constrained environments.

Background: The motor cooling system is mainly used in aerospace, automotive, and marine fields, where the motor system is cooled to extend the service life and safety of the motor. The running power of motors rises too fast, which leads to the failure of heat dissipation as expected and shortens the service life of motors. Therefore, it is necessary to choose an appropriate cooling mode for motors to improve their cooling structure, reduce their temperature rise, and improve their reliability and service life. The internal motor cooling system can perform fixed-point heat dissipation, but the overall heat dissipation is poor. The external motor cooling system can perform overall heat dissipation but has high requirements on the structure. Over the years, the application and development of motor cooling systems have gained more and more attention. Objective: This paper discusses the structural characteristics, advantages, and development trends of the motor cooling system in order to reduce the temperature rise of the motor and improve its reliability and service life. This paper aims to provide an overview and systematic guidance for future designs of the motor cooling system. Methods: According to the structural characteristics of the motor cooling system and the requirements of the motor application field, the most typical internal cooling system and external cooling system in the motor cooling system are summarized. Results: By analyzing the causes and hazards of motor heating, the limited requirements of the motor system in use are summarized. The motor system is classified and compared based on the structure, heat dissipation principle, and use of the motor heat dissipation system. The characteristics of small volume and strong heat dissipation ability are also summarized. Based on the analysis of the internal and external cooling system, the problems of complex structure and poor cooling effect are summarized, and the future development trend and direction of the motor cooling system are discussed in detail. Conclusion: This paper divides the motor cooling system into an internal cooling system and an external cooling system according to the specifications and operating environment. This paper expounds on internal and external cooling systems' different principles, advantages, and disadvantages. This paper summarizes the cooling systems in recent years in order to facilitate their subsequent development and use. The main components of additional patents for future inventions are motor cooling systems, innovation in structure simplification, and cost performance optimization.

Objective: The study aims to address the significance of fins in enhancing the heat transfer rate of engine cylinders and highlight their applications and advancements in various fields. Methods: Thermal analysis of fins using ANSYS Workbench is an invaluable tool for engineers and researchers in determining and optimizing the heat transfer characteristics of finned structures. ANSYS Workbench provides a comprehensive platform for evaluating the performance of fins in various applications using simulations of computational fluid dynamics (CFD) and finite element analysis (FEA). With ANSYS Workbench, it is possible to assess the thermal behaviour of fins under a variety of conditions, such as variable boundary conditions and thermal loads. Some significant recent patents on Engine fin are also discussed in this review article. Results: Fins are designed to maximize contact with the surrounding air or coolant, thereby facilitating engine heat transfer to the surrounding environment. Engineers can enhance heat dissipation capabilities by considering parameters such as fin geometry, density, material selection, and manufacturing techniques while minimizing associated drawbacks. Conclusion: The numerous applications of fins highlighted in this review article will encourage researchers to find novel strategies to improve heat transfer by employing fins for use in a variety of sectors.

Background: With the increasingly serious energy and environmental crises and shortages of conventional energy such as coal and oil, humans have been focusing on new energy sources, especially the abundant wave energy resource. Previous researchers have made great contributions to the design of wave energy converters and have also applied for many patents. However, advanced comprehensive wave energy evaluation and application systems are still scarce, which results in the primitive state of wave energy evaluation. Methods: The goal of this work is to overview the status and prospects of the evaluation of global wave energy to find an effective method to evaluate wave energy resources. This study divides the wave energy evaluation into 4 historical periods according to the data source. The future focus for wave energy resource evaluation is also presented in this study. Results: The wave energy evaluation includes 4 periods: the observational wave data period, the satellite-derived wave data period, the hindcast (simulation wave data from a wave model) wave data period and the reanalysis wave data period. In future research, the focus of wave energy evaluation should include the swell energy, the climatic characteristics of the wave energy resource, the characteristics of marine environments, the mid-to-long-term prediction of wave energy, the short-term forecasting of wave energy, and the evaluation of resources at a particular site. Conclusion: A scientific evaluation framework and application system (software) is urgently needed to provide a basis for decisions for the development of wave power generation, desalination and other developments of wave energy and to promote the sustainable development of human society.

: Load forecasting plays a crucial role in mitigating risks for utilities by predicting future usage of commodity markets transmission or supplied by the utility. To achieve this, various techniques such as price elastic demand, climate and consumer response, load analysis, and sustainable energy generation predictive modelling are used. As both supply and demand fluctuate, and weather and power prices can rise significantly during peak periods, accurate load forecasting becomes critical for utilities. By providing brief demand forecasts, load forecasting can assist in estimating load flows and making decisions that prevent overloading. Therefore, load forecasting is crucial in helping electric utilities make informed decisions related to power, load switching, voltage regulation, switching, and infrastructure development. Forecasting is a methodology used by electricity companies to forecast the amount of electricity or power production needed to maintain constant supply as well as load demand balance. It is required for the electrical industry to function properly. The smart grid is a new system that enables electricity providers and customers to communicate in real-time. The precise energy consumption sequence of the consumers is required to enhance the demand schedule. This is where predicting the future comes into play. Forecasting future power system load (electricity consumption) is a critical task in providing intelligence to the power grid. Accurate forecasting allows utility companies to allocate resources and assume system control in order to balance the same demand and availability for electricity. In this article, a study on load forecasting algorithms based on deep learning, machine learning, hybrid methods, bio-inspired techniques, and other techniques is carried out. Many other algorithms based on load forecasting are discussed in this study. Different methods of load forecasting were compared using three performance indices: RMSE (Root Mean Square Error), MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error), and Accuracy. Machine learning-based techniques showed a reduction of 9.17% in MAPE, 0.0429% in RMSE, and 5.23% in MSE, and achieved 90% accuracy. Deep learning-based techniques resulted in a 9.61% decrease in MAPE and achieved 91% accuracy. Bioinspired techniques provided a reduction of 9.66% in MAPE, 0.026% in RMSE, and 5.24% in MSE, and achieved 95% accuracy. These findings concluded that optimization techniques are more encouraging in predicting load demand and, as a result, can represent a reliable decision-making tool.