Porous carbons as solid adsorbent materials possess effective porosity characteristics that are the most important factors for gas storage. The chemical activating routes facilitate hydrogen storage by adsorbing on the high surface area and microporous features of porous carbon-based adsorbents. The present research proposed to predict H2 storage using four nature-inspired algorithms applied in the random forest (RF) model. Various carbon-based adsorbents, chemical activating agents, ratios, micro-structural features, and operational parameters as input variables are applied in the ML model to predict H2 uptake (wt%). Particle swarm and gray wolf optimizations (PSO and GWO) in the RF model display accuracy in the train and test phases, with an R2 of ~0.98 and 0.91, respectively. Sensitivity analysis demonstrated the ranks for temperature, total pore volume, specific surface area, and micropore volume in first to fourth, with relevancy scores of 1 and 0.48. The feasibility of algorithms... [more]

The present study focused on the analysis of a new geometrical modification of the conventional zig-zag channel for Printed Circuit Heat Exchangers. The research was carried out using OpenFOAM and Salome software, which were used for the CFD analysis and the construction of the computational domain. For the development of the study, three types of channel geometries were defined: a modified zig-zag channel, a conventional zig-zag channel, and a straight channel. The results show that the modified zig-zag channel achieves better thermal hydraulic performance compared to that of the conventional zig-zag channel, evidenced by a 7.6% increase in the thermal performance factor. The modified zig-zag channel proposed in the research caused a 1.5% reduction of the power consumption of supercritical Brayton cycle compressors. Additionally, the modified zig-zag channel achieves a maximum efficiency of 49.1%, which is 1.5% higher compared to that of the conventional zig-zag channel. The above res... [more]

The lead halide-based perovskite solar cells have attracted much attention in the photovoltaic industry due to their high efficiency, easy manufacturing, lightweight, and low cost. However, these lead halide-based perovskite solar cells are not manufactured commercially due to lead-based toxicity. To investigate lead-free inorganic perovskite solar cells (PSCs), we investigated a novel Cs3Bi2I9-based perovskite configuration in SCAPS-1D software using different hole transport layers (HTLs). At the same time, WS2 is applied as an electron transport layer (ETL). Comparative analysis of the various design configurations reveals that ITO/WS2/Cs3Bi2I9/PEDOT:PSS/Au offers the best performance with 20.12% of power conversion efficiency (PCE). After optimizing the thickness, bandgap, defect density, and carrier density, the efficiency of the configuration is increased from 20.12 to 24.91%. Improvement in other performance parameters such as short circuit current (17.325 mA/cm2), open circuit v... [more]

The fracture field and permeability distribution model of comprehensive working face goaf was integrated upon the theoretical examination to investigate the fracture field distribution law of goaf and gas migration and accumulation characteristics, and this model has been applied to the mathematical model of gas migration and accumulation in goaf. The ANSYS FLUENT numerical simulation software was used to obtain the characteristics of gas migration and accumulation in goaf and its influencing factors and analyze the applicability of solving the features of gas migration and proliferation using the porosity model of layer division in goaf. The results were as follows: the porosity around the caving zone was a little big, whereas the porosity in the middle was a little small. The porosity was almost equal along the inclination and strike in a symmetrical distribution. The porosity occurred at the fracture zone with an “O” shape. As the gob layer height increased, the porosity tended to b... [more]

The need for a “smarter” energy grid infrastructure, with the large-scale integration of renewables and a better demand−response mechanism, is leading to an ever-increasing complexity of next-generation energy networks [...]

Renewable energies, such as solar and wind power, have become promising sources of energy to address the increase in greenhouse gases caused by the use of fossil fuels and to resolve the current energy crisis. Integrating wind energy into a large-scale electric grid presents a significant challenge due to the high intermittency and nonlinear behavior of wind power. Accurate wind power forecasting is essential for safe and efficient integration into the grid system. Many prediction models have been developed to predict the uncertain and nonlinear time series of wind power, but most neglect the use of Bayesian optimization to optimize the hyperparameters while training deep learning algorithms. The efficiency of grid search strategies decreases as the number of hyperparameters increases, and computation time complexity becomes an issue. This paper presents a robust and optimized long-short term memory network for forecasting wind power generation in the day ahead in the context of Ethiop... [more]

In order to study the dynamic characteristics of the 660 MW ultra-supercritical circulating fluidized bed (CFB) boiler when the main fuel trip (MFT) and boiler trip (BT) are triggered, a dynamic simulation model of the 660 MW ultra-supercritical circulating fluidized bed boiler was established on the Apros simulation platform. The model dynamically simulated the MFT and BT processes at 100% BMCR, 75% THA, and 50% THA conditions, respectively. The steady-state simulation results showed a high accuracy compared with the designed parameters. The dynamic simulation results showed that after triggering the MFT and BT, owing to the huge thermal inertia, the bed temperature and steam temperature decreased lowly. For 100% BMCR and 75% THA conditions, the moisture separator always worked in dry state during the MFT and BT processes. For the 50% THA condition, the moisture separator quickly switched from dry to wet operation after the boiler triggers MFT and BT and gradually switched from wet to... [more]

In the study of solar greenhouses, microclimate, soil, and back walls have an important influence on the greenhouse thermal environment because of their good heat storage and release characteristics. The transpiration of crops makes indoor humidity increase sharply, which is the main factor affecting indoor humidity distribution. Therefore, it is of great significance to grasp the microclimate change law of solar greenhouses and study the coupling effect of thermal and humidity environment. In this paper, based on computational fluid dynamics (CFD), a three-dimensional model of the thermal and humidity environment of a solar greenhouse is established, and the indoor temperature and humidity distribution under the influence of soil, crops, and back walls are considered. The CFD model initialization uses binary fitting functions to fit the temperature distribution of soil, back wall, and air. The distribution law of the temperature field and relative humidity field of the solar greenhous... [more]

A new energy ship is being developed to address energy shortages and greenhouse gas emissions. New energy ships feature low operational costs and zero emissions. This study discusses the characteristics and development of solar-powered ships, wind-powered ships, fuel cell-powered ships, and new energy hybrid ships. Three important technologies are used for the power system of the new energy ship: new-energy spatio-temporal prediction, ship power scheduling, and Digital Twin (DT). Research shows that new energy spatio-temporal prediction reduces the uncertainty for a ship power system. Ship power scheduling technology guarantees safety and low-carbon operation for the ship. DT simulates the navigational environment for the new energy ship to characterize the boundary of the shipboard’s new energy power generation. The future technical direction for new energy ship power systems is also being discussed.

Stochastic simulations enable researchers to incorporate uncertainties beyond numerical discretization errors in computational fluid dynamics (CFD). Here, the authors provide examples of stochastic simulations of incompressible flows and numerical solutions for validating these newly emerging stochastic modeling methods. A numerical scheme is constructed for finding solutions to stochastic parabolic equations. The scheme is second-order accurate in time for the constant coefficient of the Wiener process term. The stability analysis of the scheme is also provided. The scheme is applied to the dimensionless heat and mass transfer model of mixed convective non-Newtonian nanofluid flow over oscillatory sheets. Both the deterministic and stochastic energy equations use temperature-dependent thermal conductivity. The stochastic model is more general than the deterministic model. The results are calculated for both flat and oscillatory plates. Casson parameter, mixed convective parameter, the... [more]

Wireless Underground Sensor Networks (WUGSNs) transmit data collected from underground objects such as water substances, oil substances, soil contents, and others. In addition, the underground sensor nodes transmit the data to the surface nodes regarding underground irregularities, earthquake, landslides, military border surveillance, and other issues. The channel difficulties of WUGSNs create uncertain communication barriers. Recent research works have proposed different types of channel assessment techniques and security approaches. Moreover, the existing techniques are inadequate to learn the real-time channel attributes in order to build reactive data transmission models. The proposed system implements Deep Learning-based Multi-Channel Learning and Protection Model (DMCAP) using the optimal set of channel attribute classification techniques. The proposed model uses Multi-Channel Ensemble Model, Ensemble Multi-Layer Perceptron (EMLP) Classifiers, Nonlinear Channel Regression models... [more]

Forecasting the electrical load is essential in power system design and growth. It is critical from both a technical and a financial standpoint as it improves the power system performance, reliability, safety, and stability as well as lowers operating costs. The main aim of this paper is to make forecasting models to accurately estimate the electrical load based on the measurements of current electrical loads of the electricity company. The importance of having forecasting models is in predicting the future electrical loads, which will lead to reducing costs and resources, as well as better electric load distribution for electric companies. In this paper, deep learning algorithms are used to forecast the electrical loads; namely: (1) Long Short-Term Memory (LSTM), (2) Gated Recurrent Units (GRU), and (3) Recurrent Neural Networks (RNN). The models were tested, and the GRU model achieved the best performance in terms of accuracy and the lowest error. Results show that the GRU model achi... [more]

UC (unit commitment) for grid operation has been attracting increasing attention due to the growing interest in global warming. Compared to other methods, MILP, which is one of the calculation methods for UC, has the disadvantage of a long calculation time, although it is more accurate in considering constraints and in finding solutions. However, RLCs (representative load curves) require a more accurate clustering method to select representative dates because the calculation results vary greatly depending on the clustering method. DBSCAN, one of the clustering methods, has the feature that the clustering accuracy varies depending on two parameters. Therefore, this paper proposes two algorithms to automatically determine the two parameters of DBSCAN to perform RLCs using DBSCAN. In addition, since DBSCAN has the feature of being able to represent different data as two-dimensional elements, a survey of the data to be used as clustering was conducted. As a result, the proposed algorithms... [more]

The generation of mathematical models for the analysis of buildings with multiple thermal zones is a large and complex task. Furthermore, the order and complexity of the dynamical model are increased by the number of included thermal zones. To overcome this problem, this paper presents an algorithm to define the mathematical model automatically, using the geometric and physics parameters as inputs. Additionally, the spatial position of each thermal zone must be recorded in an arrangement called a contact matrix. The algorithm for modeling systems with multiple thermal zones is the main contribution of this work. This algorithm is presented in pseudocode format and as an annex, an implementation in MATLAB software. One of the advantages of this methodology is that it allows us to work with parallelepipeds and not necessarily cubic thermal zones. The algorithm allows us to generate mathematical models with symbolic variables, starting from the knowledge of how many thermal zones compose... [more]

A scaled-down test section representative of an Outboard Segment manifold of the Water-Cooled Lithium Lead Breeding Blanket for the European DEMO has been designed for installation and test in a high- mass flow branch of the W-HYDRA facility, under construction at the premises of ENEA Brasimone Research Center. The test section should confirm the flow repartition recently computed in the different breeding units on the full-scale manifold, validating at the same time the computational tools used for the design and analysis. The detailed objectives and requirements of the test section, as well as the scaling rationale and procedure adopted for its design, are presented in the paper. The final design of the test section is discussed. The preliminary analyses of the developed design are also presented and show that it is compliant with the initial objectives.

Hysteresis loops constitute the source of important information for the designers of magnetic circuits in power transformers. The paper focused on the possibility to interpret the phenomenological T(x) model in terms of effective field vs. magnetization dependence. The interdependence of anhysteretic curve and hysteresis loops was emphasized. The concept of the anhysteretic plane introduced at the end of the last century by Sablik and Langman was subject to a tangible interpretation within the hyperbolic model framework. A novel geometric interpretation of the “effective field” related to the concept of affine transformation was introduced. It was shown in the paper that minor hysteresis loops of grain-oriented electrical steel may be described with the proposed formalism.

The thermal management problems of traction drive systems for high-speed trains are of great importance for the operation reliability of high-speed trains. The thermal performance of transformer and traction rectifier are mainly affected by the aerodynamic performance of pantograph. Nine bowheads with different sawtooth structures on the lower surface are proposed and a CFD numerical model is built with Transition SST turbulence model. The influence of the number and height of sawteeth on the aerodynamic characteristics of the bowhead flow field are investigated. The results show that compared with the rectangular bowhead, the aerodynamic drag of the 5w3h-shaped bowhead is reduced by 8.6%, 8.7%, and 9.9% at train speeds of 250 km/h, 300 km/h, and 350 km/h, respectively. The promotion of aerodynamic performance of pantograph is beneficial to improve the thermal characteristics of traction drive systems for high-speed trains.

The late Eocene succession of the Dongying Depression forms a highly productive hydrocarbon source. However, due to lack of an unambiguous fine chronostratigraphic framework for the late Eocene stratigraphy, it is challenging to understand the paleolake’s evolution and the driven mechanism of lake-level variation, a limitation which hinders hydrocarbon exploration. In this work, high-resolution gamma-ray logging data were analyzed to carry out the cyclostratigraphic analysis of the third member (Es3) of the Shahejie Formation in the Dongying Depression. Significant 405-kyr eccentricity cycles were recognized based on time series analysis and statistical modeling of estimated sedimentation rates. We abstracted ~57 m cycles of the GR data in the Es3 member, which were comparable with the long eccentricity cycles (~405-kyr) of the La2004 astronomical solution, yielding a 6.43 Myr long astronomical time scale (ATS) for the whole Es3 member. The calibrated astronomical age of the third/four... [more]

This research paper presents studies on the operation process of the Honker 2000 light utility vehicles that are part of the Polish Armed Forces transport system. The phase space of the process was identified based on the assumption that at any given moment the vehicle remains in one of four states, namely, task execution, awaiting a transport task, periodic maintenance, or repair. Vehicle functional readiness and technical suitability indices were adopted as performance measures for the technical system. A simulation model based on Monte Carlo methods was developed to determine the changes in the operational states. The occurrence of the periodic maintenance state is strictly determined by a planned and preventive strategy of operation applied within the analysed system. Other states are implementations of stochastic processes. The original source code was developed in the MATLAB environment to implement the model. Based on estimated probabilistic characteristics, the authors validate... [more]

The modular multilevel converter (MMC) is a keystone of modern energy transmission systems. Consequently, there is an ongoing pursue for mathematical models to represent it under different configurations and control approaches. In short, this paper introduces an analytical Thévenin-equivalent model for representing the MMC when it is controlled with inner current- and an outer voltage-loop altogether. The model is based on a linearized representation of the converter and conveys the dynamics of passive components, such as submodule capacitors and arm reactors, as well as both control loops. Besides that, the proposed model is divided into a close-loop transfer matrix and the equivalent impedance matrix, both of which represent the relationships between the ac-side dq voltages and currents. We also propose a framework for implementing electromagnetic−transient simulations using the impedance model of this power electronic converter. The framework reduces a multi-bus power grid to a mult... [more]

This work describes the Grid-Enhanced, Mobility-Integrated Network Infrastructures for Extreme Fast Charging (GEMINI) architecture for the co-simulation of distribution and transportation systems to evaluate EV charging impacts on electric distribution systems of a large metropolitan area and the surrounding rural regions with high fidelity. The current co-simulation is applied to Oakland and Alameda, California, and in future work will be extended to the full San Francisco Bay Area. It uses the HELICS co-simulation framework to enable parallel instances of vetted grid and transportation software programs to interact at every model timestep, allowing high-fidelity simulations at a large scale. This enables not only the impacts of electrified transportation systems across a larger interconnected collection of distribution feeders to be evaluated, but also the feedbacks between the two systems, such as through control systems, to be captured and compared. The findings are that with moder... [more]

This paper presents a methodology to program the weak coupling between magnetic and structural vector fields in an electromagnetic device modeled in two dimensions. The magneto-mechanical coupling phenomenon is present in electromagnetic devices where magnetic forces cause displacements in metallic materials. This work proposes a numerical solution to this problem by applying the 2D finite element method to the governing equations of this coupled multiphysics phenomenon. The well-known formulation yields accurate results; however, it is often not properly integrated into a computer program. This manuscript proposes a flexible and intuitive methodology for the implementation of the complex mathematics involved in this phenomenon into a computer program. The computer code receives the input parameters, discretizes the geometry by generating a 2D finite mesh, solves the resulting equations using the finite element method, and finally exports the results of the magnetic ang mechanical fiel... [more]

Selected structures intended to absorb impact energy have been analysed in respect of their use in the rear underrun protective devices (RUPD) of motor trucks. The main purpose of the RUPD is to prevent a passenger car from running under the rear of a motor truck provided with such a device. From the point of view of the safety of the car occupants, it is important to take into account the components whose additional role would be to absorb a part of the impact energy so that the loads on the said occupants were minimised. This article presents experimental test results concerning selected energy-absorbing structures. Based on quasi-static strength tests, simplified material models were defined. As a result of experimental crash tests, the possible applications of selected energy absorbers to the RUPDs as their components accountable for the passive safety of passenger cars were indicated. Absorbers proposed in this paper can be considered effective energy-absorbing structures, e.g., i... [more]

To meet the target of carbon neutrality by the year 2050 and decrease the dependence on fossil fuels, renewable energy sources (RESs), specifically wind power, and Electric Vehicles (EVs) have to be massively deployed. Nevertheless, the integration of a large amount of wind power, with an intermittent nature, into the grid and the variability of the load on the demand side require an efficient and reliable energy management system (EMS) for operation, scheduling, maintenance and energy trading in the modern power system. This article proposes a new Energy Management Protocol (EMP) based on the combination of Machine Learning (ML) and Game-Theoretic (GT) algorithms to manage the operation of the charging/discharging of EVs from an energy storage system (ESS) via EV supply equipment (EVSE) when the main source of energy is wind power. The ESS can be linked to the grid to overcome downtimes of wind power production. Case study results of wind power forecasting using an ML algorithm and 10... [more]

To minimize the impact of snowfall and ice formation on safety of transportation, salt is sprinkled on the asphalt every winter. However, the use of salt has economical as well as ecological disadvantages. To resolve these problems, road heating systems are used in the northern regions of Europe and America. Despite their widespread usage, considerable potential of the operational optimization is evident. The current systems are controlled under predefined weather conditions such as start of operation at 5 °C air temperature, even when snowfall is absent. Consequently, loss of energy input to heat the system is caused. To avoid unnecessary financial and energetic expense, this study presents CFD-based performance investigation as a basis for a novel predictive controller to increase the operational efficiency of hydronic road heating systems (HRS). The simulation model was developed based on a real operational HRS located in Ingolstadt and composed of bridges and ramps for a total surf... [more]