Santiago Bermudez, Furkan Erdogan, Victoria Davis
et al.
Despite their widespread application, FeCrAl alloys face several challenges in maintaining performance under high thermal cycling and extreme oxidation conditions. Following the 2011 Fukushima Daiichi accident, there has been a growing interest on developing of accident tolerant fuel (ATF) cladding materials, as well as modifications to existing ones, for advanced nuclear reactors. This study investigates the role of nickel in enhancing the high-temperature oxidation resistance of FeCrAl alloys, which are being considered as potential replacements for zirconium alloys. Specifically, the oxidation behavior of FeCrAl alloys with 17 wt% chromium and varying nickel contents Fe-17Cr-5.5Al, Fe-17Cr-5.5Al-1Ni, and Fe-17Cr-5.5Al-3Ni were examined under steam environment at 1000 °C for 5000 s. The oxide layer thickness and compositional changes were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM-EDX) and transmission electron microscopy (TEM). The results indicate that low nickel concentrations significantly improve the oxidation resistance of FeCrAl alloys, making them more suitable for accident-tolerant fuel cladding applications in advanced nuclear reactors. This study provides valuable insights in optimizing FeCrAl alloy compositions to improve their oxidation resistance under extreme conditions.
Muhammad Khalid Jamil, Wouter Julius Smolenaars, Bashir Ahmad
et al.
Nearly 86 % of the 1.4 million agricultural tube wells extracting groundwater for irrigation of crops in Lower Indus Basin (LIB) Pakistan are powered by diesel fuel. Diesel is expensive, needs to be imported and contributes to global warming through CO2 emissions. The increasing global focus on clean energy sources has prompted a shift from diesel fuel to solar photovoltaic (PV) energy for powering irrigation tube wells. The broad availability of inexpensive/free operational energy and abundant solar energy for pumping can cause over-extraction of groundwater. This study investigates the impacts of converting diesel pumps to solar PV pumps on groundwater extraction in LIB Pakistan. We conducted one-to-one comparisons of solar vs diesel pumps in thirty pairs of farmers working in similar circumstances. We estimated annual water extracted by solar and diesel pump farmers in each pair utilizing the data collected through flow measurements and crop wise irrigation times for each pair of farms using a targeted survey questionnaire, followed by a validation process. We utilized validated “Global Solar Atlas” (GSA), an online tool that accounts for daily and seasonal variation in solar pumps flows. Flow rates of diesel-operated pumps were measured, and annual water volumes pumped by both types of pumps were compared. Results show that the introduction of solar pumps significantly increased groundwater pumping compared to diesel fuelled pumps (P = 0.005∗). The average annual water pumped by solar and diesel pumps was found to be 1.6 ∗ 103 and 1.3 ∗ 103 mm respectively. In 77 % of the cases, farms using solar pumps extracted more water than their diesel counterparts under comparable conditions. While acknowledging benefits of solar PV pumping for agriculture in LIB Pakistan, the outcome of the study emphasized the need for a cautious and well-informed upscaling approach to avoid overextraction of groundwater.
Agriculture (General), Nutrition. Foods and food supply
Abstract The Gulf-Europe transportation project, also known as Iraq’s Development Road Project (DRP), is a transformative supply chain initiative aimed at constructing a corridor from Al Faw Port in Iraq to Turkey, linking Gulf Cooperation Council (GCC) countries with Europe. The project’s goal is to establish a robust transport corridor through the extensive construction of roads and railways, facilitating the fast and seamless movement of goods between the East and the West. By creating land-based direct transportation routes to complement traditional maritime pathways, the project seeks to reduce transit times, lower shipping costs, increase trade flows, and improve regional integration. This study qualitatively examines how the corridor will impact trade, the economy, and transportation sustainability in the Gulf nations. We explore potential increases in trade volumes, foreign investments, logistics sustainability, and economic diversification within the region. Additionally, we recommend the adoption of hydrogen fuel cell vehicles (HFCVs) and hydrogen-powered trains in the corridor to align with the United Nations Sustainable Development Goals (SDGs). Furthermore, we suggest that the corridor’s development will create opportunities for economic diversification and reduce the GCC countries' reliance on oil revenues. Finally, the study provides strategic recommendations for policymakers and stakeholders to maximize the project’s benefits and address potential challenges, emphasizing its potential to drive long-term economic growth and strengthen the GCC countries’ global trade positioning.
Accurate extraction of polarization resistance is crucial in the application of proton exchange membrane fuel cells. It is generally assumed that the steady-state resistance obtained from the polarization curve model is equivalent to the AC impedance obtained from the electrochemical impedance spectroscopy (EIS) when the frequency approaches zero. However, due to the low-frequency stability and nonlinearity issues of the EIS method, this dynamic process leads to an additional rise in polarization resistance compared to the steady-state method. In this paper, a semi-empirical model and equivalent circuit models are developed to extract the steady-state and dynamic polarization resistances, respectively, while a static internal resistance correction method is proposed to represent the systematic error between the two. With the correction, the root mean square error of the steady-state resistance relative to the dynamic polarization resistance decreases from 26.12% to 7.42%, indicating that the weighted sum of the static internal resistance and the steady-state resistance can better correspond to the dynamic polarization resistance. The correction method can also simplify the EIS procedure by directly generating an estimate of the dynamic polarization resistance in the full current interval.
Microgrid autonomous networks need an effective plan and control of power supply, energy storage, and retransmission. Prediction and monitoring of power quality (PQ) along with efficient utilization of Renewable Energy (RE) is unavoidable to optimize the system performance without abnormalities. Alterations and irregularities in PQ must remain within the prescribed norm ranges and characteristics to allow fault-tolerant operation of the detached system in various modes of attached equipment. The PQ data for all possible combinations of grid-attached household appliances and different inside/outside conditions cannot be measured completely or described exactly by physical equations. PQ predictions on a daily basis using Artificial Intelligence (AI) models are needed because atmospheric fluctuations and anomalies in local weather with uncertainties in system states primarily influence the induced power and operation of real off-grids. A novel soft-computing method using Differential Learning, which allows modelling of complex dynamics of weather-dependent systems, is presented and compared with the recent standard deep and probabilistic machine learning. The AI models were evolved using weather data and the binary status of attached equipment in the test predetermined daily training periods. Daily statistical models process 24-h forecast data and definition load series of trained input variables to calculate the target PQ parameters at the same times. Optimal utilization, efficiency, and failure-free operation of smart grids can be planned according to the suggested operable power consumption scenarios based on their PQ verification on a day-horizon. Executable load sequences can be automatically combined and scheduled in the system to be adapted to user needs, considering the RE production potential, charge state, and optimal PQ characteristics over the next 24 h. A parametric C++ application software with applied PQ and weather data is free available to allow reproducibility of the results.
Mansoure Peyvandi, Ahmad Hajinezhad, Seyed Farhan Moosavian
The emission intensity is considered important data in determining technical and environmental efficiency in power plants. In this research, the goal is to determine the intensity of greenhouse gas emissions in the electricity production sector in Iran under the influence of new energies. To achieve this goal, the total greenhouse gases produced in a year in the electricity sector in fossil and renewable power plants are divided by the total electricity produced and obtained quantitatively in terms of tCO2/kWh. Also, the effect of each primary source of electricity generation is analyzed separately in terms of emission intensity. The results showed that the participation of renewable sources in the highest situation was about 9.5%, and their emission intensity was 2.2 tCO2/kWh. The fossil fuel-based power plant had an estimated emission intensity of 506 tCO2/kWh in the same year. Although the environmental policies in Iran seek to reduce the intensity of emissions, and generally, the growth of this index is negative, there are many fluctuations in this process. With the reduction of rainfall in Iran and the reduction of water behind the dams, the dependence of electricity production on water sources has decreased significantly So that in the year when the precipitation is significant, the intensity of emission has increased from its minimum value of 613.6 tCO2/kWh to 654.34 tCO2/kWh in the year of low rainfall. As a result, it has been suggested that the potential of solar resources, which emission intensity is lower than other renewable sources and is one of the most reliable and stable primary sources, should be used more effectively to reduce the emissions of electricity production sector.
Shymaa A. Hameed, Raja Ben Amar , Khaleel I. Hamad
et al.
Abstract: Clean fuel oil is crucial for a healthy environment and modern life. Therefore, removing sulfur-containing compounds is an effective issue using various techniques for desulfurization. In this study, the oxidation desulfurization (ODS) process was utilized with respect to the prepared new activated carbon (AC) made from apricot shells (AS) loaded by two combined active metals (Nickel-Cobalt-Manganese (NCM) and Nickel-Cobalt-Manganese-Molybdenum (NCMM)). Several characteristics related to the catalysts prepared (mainly SBET, pore volume, FTIR, TGA, SEM, EDX and XRD) have been investigated to analyze the produced nanocatalysts. The new nanocatalysts (NCM/AC and NCMM/AC) were generated by using the impregnation wetness incipient (IWI) method and evaluated for their ability to remove sulfur compounds from whole-cut fuel (from 29-345 °C) based on the air as an oxidant within batch reactor under the following conditions: air flow rate = 2 lit/min, reaction temperature = 90 °C, and reaction time of 60 min for both catalysts. It was found that Nano catalyst NCMM/AC performed better overall in removing sulfur components (57.29 %) than Nano catalyst NCM/AC (44.75 %), and excellent properties have been observed.
In this study, exhausted olive pomace (EOP) biochar prepared by carbonization at 400 °C is investigated as a fuel in a direct carbon fuel cell (DCFC) with an electrolyte-supported configuration. The feasibility of using the EOP biochar in the DCFC is confirmed, showing a maximum power density of 10 mW·cm<sup>−2</sup> at 700 °C. This limited DCFC performance is compared with other biochars prepared under similar conditions and interrelated with various biochar physico-chemical characteristics, as well as their impact on the DCFC’s chemical and electrochemical reaction mechanisms. A high ash content (21.55%) and a low volatile matter (40.62%) content of the EOP biochar are among the main causes of the DCFC’s limited output. Silica is the major impurity in the EOP biochar ash, which explains the limited cell performance as it causes low reactivity and limited electrical conductivity because of its non-crystal structure. The relatively poor DCFC performance when fueled by the EOP biochar can be overcome by further pre- and post-treatment of this renewable fuel.
Pre-mixing of magma and external water plays a key role in driving explosive phreatomagmatic and submarine volcanic eruptions. A thin film of water vapor forms at the magma–water interface as soon as hot magma comes in direct contact with the cold water (Leidenfrost effect). The presence of a stable vapor film drives efficient mixing and mingling between magma and water, as well as magma and wet and water-saturated sediments. Such mixing occurs before explosive molten fuel–coolant type interactions. Using high-temperature laboratory experiments, we investigate the effect of magma and water temperatures on the stability of vapor film, which has not been performed systematically for a magmatic heat source. The experiments were performed with re-melted volcanic rock material, from which spherically-shaped rock samples were produced. These samples were heated to 1,110°C and then submerged in a water pool with a constant temperature (3–93°C). The experiments were recorded on video, and, synchronously, sample and water temperatures were measured using thermocouples. The time-dependent thickness of the vapor film was measured from the video material. The vapor film tends to oscillate with time on the order of 102 Hz. We find that the vertical collapse rates of vapor films along the sample–water interfaces are 13.7 mm s−1 and 4.2 mm s−1 for water temperatures of 3.0°C and 65°C, respectively. For a given initial sample temperature, the thickness and stability time scales decrease with decreasing water temperature, which has implications for the efficiency of pre-mixing required for explosive eruptions. Using thermodynamics and previously measured material parameters, it is shown that a sudden collapse of the vapor film can start brittle fragmentation of the melt and thus serves as the starting point of thermohydraulic explosions.
The study aims to understand the irradiation behavior of multilayer coatings composed of high-entropy materials. Here, we report the structural stability and elemental segregation of high-entropy TiNbZrTa/CrFeCoNi metallic and nitride multilayer coatings under 3-MeV Xe20+ ion-irradiation at room temperature and 500 °C, respectively. Transmission electron microscopy analysis shows that the microstructure of nanocrystalline CrFeCoNi high-entropy-alloy sublayers are not stable and readily transforms into amorphous state at 500 °C and/or under irradiation conditions. The elemental distribution, acquired by energy-dispersive X-ray spectroscopy under scanning transmission electron microscopy mode, shows preferential diffusion of Co and Ni into TiNbZrTa sublayers, while Fe and Cr preferentially remain within the previous CrFeCoNi sublayers. TiNbZrTaN/CrFeCoNiNx nitride multilayers exhibit a higher crystallinity and structural stability as well as resistance to diffusion at high-temperature and/or irradiation conditions than their TiNbZrTa/CrFeCoNi metallic multilayer counterparts. These findings are explained by atomic size differences, the difference in Gibbs free energy of the mixing system, and interstitial-solute-induced chemical heterogeneity. Our findings thus provide a design strategy of high entropy nitride for nuclear fuel cladding.
Materials of engineering and construction. Mechanics of materials