• Energy Research
• US close
• KG close
• Energies close

We analyzed the peak spring tidal current speeds, annual mean tidal power densities ( T P D ) and annual energy production ( A E P ) obtained from experiment 06.1, referred as the “HYCOM model” throughout, of the three dimensional (3D), global model HYCOM in an area covering the Baja California Pacific and the Gulf of California. The HYCOM model is forced with astronomical tides and surface winds alone, and therefore is particularly suitable to assess the tidal current and wind-driven current contribution to in-stream energy resources. We find two areas within the Gulf of California, one in the Great Island Region and one in the Upper Gulf of California, where peak spring tidal flows reach speeds of 1.1 m per second. Second to fifth-generation tidal stream devices would be suitable for deployment in these two areas, which are very similar in terms of tidal in-stream energy resources. However, they are also very different in terms of sediment type and range in water depth, posing different challenges for in-stream technologies. The highest mean T P D value when excluding TPDs equal or less than 50 W m−2 (corresponding to the minimum velocity threshold for energy production) is of 172.8 W m−2, and is found near the town of San Felipe, at (lat lon) = (31.006–114.64); here energy would be produced during 39.00% of the time. Finally, wind-driven currents contribute very little to the mean T P D and the total A E P . Therefore, the device, the grid, and any energy storage plans need to take into account the periodic tidal current fluctuations, for optimal exploitation of the resources.

The paper presents a modified algorithm for determining the accuracy parameter of the system for differential corrections and monitoring (SDCM) navigation solution in air navigation. For this purpose, a solution to determine the resultant accuracy parameter was proposed by using two on-board global navigation satellite system (GNSS) receivers. The mathematical algorithm takes into account the calculation of a single point positioning accuracy for a given GNSS receiver and a weighting factor combining the position error values. The weighting factor was determined as a function of the number of tracked GNSS satellites used in the SDCM single point positioning solution. The resultant accuracy parameter was expressed in ellipsoidal coordinates BLh (B—latitude, L—longitude, h—ellipsoidal height). The study used GNSS kinematic data recorded by two on-board receivers: Trimble Alloy and Septentrio AsterRx2i, located in a Diamond DA 20-C1 aircraft. The test flight was performed near the city of Olsztyn in north-eastern Poland. Calculations and analyses were performed using RTKLIB software and the Scilab environment. On the basis of the performed tests, it was found that the proposed algorithm for SDCM system allows for improvement in the determination of the resultant accuracy value by 56–80% in relation to the results of position errors from a single GNSS receiver. Additionally, the proposed algorithm was tested for the European Geostationary Navigation Overlay Service (EGNOS) system, and in this case, the improvement in the accuracy parameter was even better and was in the range of 69–89%. The resulting SDCM and EGNOS positioning accuracy met the International Civil Aviation Organization (ICAO) certification requirements for SBAS systems in air navigation. The mathematical algorithm developed in this work was tested positively and can be implemented within the SBAS augmentation system in air navigation.

The prevailing need for a more sustainable management of natural resources depends not only on the decisions made by governments and the will of the population, but also on the knowledge of the role of energy in our society and the relevance of preserving natural resources. In this sense, critical work is being done to instill key concepts—such as the circular economy and sustainable energy—in higher education institutions. In this way, it is expected that future professionals and managers will be aware of the importance of energy optimization, and will learn a series of computational methods that can support the decision-making process. In the context of higher education, this paper reviews the main trends and challenges related to the concepts of circular economy and sustainable energy. Besides, we analyze the role of simulation and serious games as a learning tool for the aforementioned concepts. Finally, the paper provides insights and discusses open research opportunities regarding the use of these computational tools to incorporate circular economy concepts in higher education degrees. Our findings show that, while efforts are being made to include these concepts in current programs, there is still much work to be done, especially from the point of view of university management. In addition, the analysis of the teaching methodologies analyzed shows that, although their implementation has been successful in favoring the active learning of students, their use (especially that of serious games) is not yet widespread.

There are many real-world applications that require high-performance mobile computing systems for onboard, real-time processing of gathered data due to latency, reliability, security, or other application constraints. Unfortunately, most existing high-performance mobile computing systems require a prohibitively high power consumption in the face of the limited power available from the batteries typically used in these applications. For high-performance mobile computing to be practical, alternative hardware designs are needed to increase the computing performance while minimizing the required power consumption. This article surveys the state-of-the-art in high-efficiency, high-performance onboard mobile computing, focusing on the latest developments. It was found that more research is needed to design high-performance mobile computing systems while minimizing the required power consumption to meet the needs of these applications.

Fracture conductivity decline is a concern in the Tuscaloosa Marine Shale (TMS) wells due to the high content of clay in the shale. An analytical well productivity model was developed in this study considering the pressure-dependent conductivity of hydraulic fractures. The log-log diagnostic approach was used to identify the boundary-dominated flow regime rather than the linear flow regime. Case studies of seven TMS wells indicated that the proposed model allows approximation of the field data with good accuracy. Production data analyses with the model revealed that the pressure-dependent fracture conductivity in the TMS in the Mississippi section declines following a logarithmic mode, with dimensionless coefficient χ varying between 0.116 and 0.130. The pressure-dependent decline of fracture conductivity in the transient flow period is more significant than that in the boundary-dominated flow period.

In China, the power sector is currently the largest carbon emitter and the transportation sector is the fastest-growing carbon emitter. This paper proposes a model of solar-powered charging stations for electric vehicles to mitigate problems encountered in China’s renewable energy utilization processes and to cope with the increasing power demand by electric vehicles for the near future. This study applies the proposed model to Shenzhen City to verify its technical and economic feasibility. Modeling results showed that the total net present value of a photovoltaic power charging station that meets the daily electricity demand of 4500 kWh is $3,579,236 and that the cost of energy of the combined energy system is $0.098/kWh. In addition, the photovoltaic powered electric vehicle model has pollutant reduction potentials of 99.8%, 99.7% and 100% for carbon dioxide, sulfur dioxide, and nitrogen oxides, respectively, compared with a traditional gasoline-fueled car. Sensitivity analysis results indicated that interest rate has a relatively strong influence on COE (Cost of Energy). An increase in the interest rate from 0% to 6% increases COE from $0.027/kWh to $0.097/kWh. This analysis also suggests that carbon pricing promotes renewable energy only when the price of carbon is above $20/t.