This paper refers to the issue of modelling characteristics of SiC power bipolar junction transistor (BJT), including the self-heating phenomenon. The electrothermal model of the tested device is demonstrated and experimentally verified. The electrical model is based on the isothermal Gummel−Poon model, but several modifications were made including the improved current gain factor (β) model and the modified model of the quasi-saturation region. The accuracy of the presented model was assessed by comparison of measurement and simulation results of selected characteristics of the BT1206-AC SiC BJT manufactured by TranSiC. In this paper, a single device characterization has only been performed. The demonstrated results of research show the evident temperature impact on the transistor d.c. characteristics. A good compliance between the measured and calculated characteristics of the considered transistor is observed even in quasi-saturation mode.

In this paper, a non-contact degradation evaluation method for insulated gate bipolar transistor (IGBT) modules is proposed based on eddy current pulsed thermography approach. In non-contact heat excitation procedures, a high-power induction heater is introduced to generate heat excitation in IGBT modules. The thermographs of the whole temperature mapping are recorded non-invasively by an IR camera. As a result, the joint degradation of IGBT modules can be evaluated by the transient thermal response curves derived from the recorded thermographs. Firstly, the non-destructive evaluation principle of the eddy current pulsed thermography (ECPT) system for an IGBT module with a heat sink is introduced. A 3D simulation module is built with physical parameters in ANSYS simulations, and then thermal propagation behavior considering the degradation impact is investigated. An experimental ECPT system is set up to verify the effectiveness of the proposed method. The experimental results show that... [more]

Harmonic simulations play a key role in studying and predicting the impact of nonlinear devices on the power quality level of distribution grids. A frequency-domain approach allows higher computational efficiency, which has key importance as long as complex networks have to be studied. However, this requires proper frequency-domain behavioral models able to represent the nonlinear voltage−current relationship characterizing these devices. The Frequency Transfer Matrix (FTM) method is one of the most widespread frequency domain modeling approaches for power system applications. However, others suitable techniques have been developed in the last years, in particular the X-parameters approach, which comes from radiofrequency and microwave applications, and the simplified Volterra models under quasi-sinusoidal conditions, that have been specifically tailored for power system devices. In this paper FTM, X-parameters and simplified Volterra approaches are compared in representing the nonline... [more]

The post-closure performance of a generic horizontal drillhole repository for the disposal of spent nuclear fuel (SNF) is quantitatively evaluated using a physics-based numerical model that accounts for coupled thermal-hydrological flow and radionuclide transport processes. The model incorporates most subcomponents of the repository system, from individual waste canisters to the geological far field. The main performance metric is the maximum annual dose to an individual drinking potentially contaminated water taken from a well located above the center of the repository. Safety is evaluated for a wide range of conditions and alternative system evolutions, using deterministic simulations, sensitivity analyses, and a sampling-based uncertainty propagation analysis. These analyses show that the estimated maximum annual dose is low (on the order of 10−4 mSv yr−1, which is 1000 times smaller than a typical dose standard), and that the conclusions drawn from this dose estimate remain valid e... [more]

This paper introduces an R package ForecastTB that can be used to compare the accuracy of different forecasting methods as related to the characteristics of a time series dataset. The ForecastTB is a plug-and-play structured module, and several forecasting methods can be included with simple instructions. The proposed test-bench is not limited to the default forecasting and error metric functions, and users are able to append, remove, or choose the desired methods as per requirements. Besides, several plotting functions and statistical performance metrics are provided to visualize the comparative performance and accuracy of different forecasting methods. Furthermore, this paper presents real application examples with natural time series datasets (i.e., wind speed and solar radiation) to exhibit the features of the ForecastTB package to evaluate forecasting comparison analysis as affected by the characteristics of a dataset. Modeling results indicated the applicability and robustness of... [more]

The UK nuclear innovation programme supported by the government includes preparation for future ABWR construction. The UK has significant expertise in building and operating gas-cooled nuclear reactors and some experience with PWRs, while there is limited knowledge in BWR technologies. Hence, an important aim of this work is to understand the discrepancies between codes to assess uncertainties in BWR lattice and depletion calculations, while identifying specific development demands to progress existing tools into extended applications. The objective of the study is to quantify the discrepancy between SCALE-6.2, CASMO5 and the UK WIMS-10A deterministic lattice code for BWR lattice and burnup modelling. Two models of BWR systems were considered for this new systematic comparison. They are a single BWR pin-cell with UO2 fuel only, and a 3 by 3 array of BWR UO2 fuel rods with gadolinia rod in the centre. Criticality over burnup was estimated for both models using these codes. Spectral inde... [more]

Solar energy is a key renewable energy source; however, its intermittent nature and potential for use in distributed systems make power prediction an important aspect of grid integration. This research analyzed a variety of machine learning techniques to predict power output for horizontal solar panels using 14 months of data collected from 12 northern-hemisphere locations. We performed our data collection and analysis in the absence of irradiation data—an approach not commonly found in prior literature. Using latitude, month, hour, ambient temperature, pressure, humidity, wind speed, and cloud ceiling as independent variables, a distributed random forest regression algorithm modeled the combined dataset with an R2 value of 0.94. As a comparative measure, other machine learning algorithms resulted in R2 values of 0.50−0.94. Additionally, the data from each location was modeled separately with R2 values ranging from 0.91 to 0.97, indicating a range of consistency across all sites. Using... [more]

Integrated assessment modeling at a higher spatial scale is a prerequisite for deriving region-specific implications from the model. The Global Change Assessment Model (GCAM) was chosen for GCAM-Korea, a detailed integrated assessment model (IAM) of Korea’s socioeconomic and energy systems. GCAM-Korea is developed based on GCAM-USA. Data for 16 provinces have been collected from various sources. Some data have been pre-processed to fit within the specific structure of GCAM-USA data. Other types of data were newly added through new structures. The model results were validated to be compatible with historical trends. It was found that provincial energy plans or policies could be compiled in detail using the proposed model while maintaining consistency with national level modeling results. The cross-border air pollution issue in Northeast Asia could also be addressed by combining GCAM-Korea and air quality models in the future.

In this numerical study, the temperature, pressure and flow structure inside the rotary compressor are obtained to analyze the work consumption and efficiency. The geometry of the compressor such as volume, inlet angle, and mass of reed valve are varied to look for optimal performance and design margin as the suggestions for manufacturing. The work done on refrigerant increases proportionally with the volume of the compressor. However, there is an optimal volume for efficiency. The design margin for inlet angle is determined. The best efficiency exists in a specific inlet angle. Larger mass of reed valve leads to the increase of input power due to the additional resistance from greater inertia, which causes a decrease of efficiency. The flow visualization by simulation diagnoses the potential factors, which may cause noise problem.

This paper presents an analysis of the time complexity of algorithms prepared for solving heat transfer problems at nanoscale. The first algorithm uses the classic Dual-Phase-Lag model, whereas the second algorithm employs a reduced version of the model obtained using a Krylov subspace method. This manuscript includes a description of the finite difference method approximation prepared for analysis of the real microelectromechanical system (MEMS) structure manufactured by the Polish Institute of Electron Technology. In addition, an approximation scheme of the model, as well as the Krylov subspace-based model order reduction technique are also described. The paper considers simulation results obtained using both investigated versions of the Dual-Phase-Lag model. Moreover, the relative error generated by the reduced model, as well as the computational complexity of both algorithms, and a convergence of the proposed approach are analyzed. Finally, all analyses are discussed in detail.

One way to mitigate the variability of wind and solar power generation is to install the corresponding plants in nearby locations. For example, in Kuwait, the facility at Shagaya Renewable Energy Park is located in a desert area with both photovoltaic panels and wind turbines that allow the continuous generation of renewable energy throughout the day. The National Center for Atmospheric Research (NCAR) has developed a system to generate probabilistic wind and solar predictions for the Shagaya facility. These predictions are based on the analog ensemble technique that post-processes the wind speed and solar irradiance predictions based on a combination of multiple models including the Weather Research and Forecasting (WRF) numerical model. The ensemble forecasts have 20 members and are generated independently at each wind and solar power production facility. Here we present a method based on the Schaake Shuffle (SS) technique to pair the ensemble members from the independent systems to... [more]

Cyberspace has become an indispensable factor for all areas of the modern world. The world is becoming more and more dependent on the internet for everyday living. The increasing dependency on the internet has also widened the risks of malicious threats. On account of growing cybersecurity risks, cybersecurity has become the most pivotal element in the cyber world to battle against all cyber threats, attacks, and frauds. The expanding cyberspace is highly exposed to the intensifying possibility of being attacked by interminable cyber threats. The objective of this survey is to bestow a brief review of different machine learning (ML) techniques to get to the bottom of all the developments made in detection methods for potential cybersecurity risks. These cybersecurity risk detection methods mainly comprise of fraud detection, intrusion detection, spam detection, and malware detection. In this review paper, we build upon the existing literature of applications of ML models in cybersecuri... [more]

New O-type high-power vacuum resonant microwave devices are considered in this study: COM klystrons, CSM klystrons and resotrodes. All these devices can output a large amount of power (up to units of MW and higher) with an efficiency of up to 90%. Such devices are promising microwave sources for industrial microwave technologies as well as for microwave energy. The principle of GSP-equivalence for klystrons is described herein, allowing a complete physical analog of this device with other parameters to be created. The existing mathematical and computer models of klystrons are analyzed. The processes of stage-by-stage optimization and the embedding procedure, which leads to COM and to CSM klystrons, are considered. Resotrodes, IOT-type devices with energy regeneration in the input circuit, are also considered. It is shown that these devices can combine high power with an efficiency of up to 90% and a gain of more than 30 dB. Resotrodes with 0-regeneration can be effective sources of rad... [more]

Recently, given the increased integration of renewables and growing uncertainty in demand, the wholesale market price has become highly volatile. Energy communities connected to the main electricity grid may be exposed to this increasing price volatility. Additionally, they may also be exposed to local network congestions, resulting in price spikes. Motivated by this problem, in this paper, we present a coordination mechanism between entities at the distribution grid to reduce price volatility. The mechanism relies on the concept of duality theory in mathematical programming through which explicit constraints can be imposed on the local electricity price. Constraining the dual variable related to price enables the quantification of the demand-side flexibility required to guarantee a certain price limit. We illustrate our approach with a case study of a congested distribution grid and an energy storage system as the source of the required demand-side flexibility. Through detailed simula... [more]

Aquifer thermal energy storage (ATES) combined with ground-source heat pumps (GSHP) offer an attractive technology to match supply and demand by efficiently recycling heating and cooling loads. This study analyses the integration of the ATES−GSHP system in both district heating and cooling networks of an urban district in southwestern Finland, in terms of technoeconomic feasibility, efficiency, and impact on the aquifer area. A novel mathematical modeling for GSHP operation and energy system management is proposed and demonstrated, using hourly data for heating and cooling demand. Hydrogeological and geographic data from different Finnish data sources is retrieved in order to calibrate and validate a groundwater model. Two different scenarios for ATES operation are investigated, limited by the maximum pumping flow rate of the groundwater area. The additional precooling exchanger in the second scenario resulted in an important advantage, since it increased the heating and cooling demand... [more]

Power system load growth and transmission corridor constraints are driving industry activity in the area of high surge impedance loading (HSIL). Examples include compact structure design and uprating existing transmission lines. Recent research relating electric field uniformity to transmission line capacity and critical flashover voltage underscored the need for better overvoltage data to quantify insulation margins for HSIL design. To that end, this work extends the finite difference time domain (FDTD) method with distributed corona losses to transmission lines with bundled conductors. The model was adapted for practical use in high-volume statistical transient simulation and applied to an example 500 kV line. Transients included line energization and trapped charge reclosing. Overvoltage profiles and statistical distributions were generated from 9500 simulations obtained by random breaker close timing and variation in line length and altitude. Distributed corona losses reduced 98th... [more]

This paper optimizes opening positions on building facades to maximize the natural ventilation’s potential for ventilation and cooling purposes. The paper demonstrates how to apply computational fluid dynamics (CFD) simulation results to architectural design processes, and how the CFD-driven decisions impact ventilation and cooling: (1) background: A CFD helps predict the natural ventilation’s potential, the integration of CFD results into design decision-making has not been actively practiced; (2) methods: Pressure data on building facades were obtained from CFD simulations and mapped into the 3D modeling environment, which were then used to identify optimal positions of two openings of a zone. The effect of the selected opening positions was validated with building energy simulations; (3) results: The cross-comparison study of different window positions based on different geographical locations quantified the impact on natural ventilation effectiveness; and (4) conclusions: The optim... [more]

The presented paper dealt with the concept of an innovative manifold header for evacuated tube solar collectors. The proposed concept eliminates the drawbacks of conventional manifold headers, especially the serial connection of heat pipes that operate under uneven conditions. The advantage of the proposed design of the manifold header is also an increase in the heat exchange surface and the possibility of conducting the heat transfer media flow in a parallel flow arrangement, which increases the overall efficiency. The concept of the manifold header was evaluated on five variations of design with the use of the computational fluid dynamics (CFD) analysis. The results of the CFD analysis confirmed the functionality of the concept and also enabled the selection of the most suitable design elements, which were incorporated into the final design of a manifold header in the pre-prototype phase of manufacturing.

To the best of our knowledge, this study provides new insight into the forecasting of crude oil futures price crashes in America, employing a moving window. One is the fixed-length window and the other is the expanding-length window, which has never been reported in the past. We aimed to investigate if there is any difference when historical data are discarded. As the explanatory variables, we adapted 13 variables to obtain two datasets, 16 explanatory variables for Dataset1 and 121 explanatory variables for Dataset2. We try to observe results from the different-sized sets of explanatory variables. Specifically, we leverage the merits of a series of machine learning techniques, which include random forests, logistic regression, support vector machines, and extreme gradient boosting (XGBoost). Finally, we employ the evaluation metrics that are broadly used to assess the discriminatory power of imbalanced datasets. Our results indicate that we should occasionally discard distant historic... [more]

This paper demonstrates a new method by which the energy storage density of compressed air systems is increased by 56.8% by changing the composition of the compressed gas to include a condensable component. A higher storage density of 7.33 MJ/m3 is possible using a mixture of 88% CO2 and 12% N2 compared to 4.67 MJ/m3 using pure N2. This ratio of gases representing an optimum mixture was determined through computer simulations that considered a variety of different proportions from pure CO2 to pure N2. The computer simulations are based on a thermodynamic equilibrium model that predicts the mixture composition as a function of volume and pressure under progressive compression to ultimately identify the optimal mixture composition (88% CO2 + 12% N2). The model and simulations predict that the optimal gas mixture attains a higher energy storage density than using either of the pure gases.

The increased demand for wind power is related to changes in the sizes of wind turbines and the development of flow control devices, such as vortex generators (VGs). In the present study, an analysis of the vortices generated by a vane-type VG is performed. To that end, the aerodynamic performance of a DU97W300 airfoil with and without VG is evaluated. The jBAY source term model was implemented for simulation of a triangular-shaped VG and the resolution of the fully meshed computational fluid dynamics (CFD) model. Reynolds-averaged Navier−Stokes (RANS) based simulations were used to calculate the effect of VGs in steady state, and the detached eddy simulation (DES) method was used for angles of attack (AoAs) around the stall situation. All jBAY based numerical simulations were carried out with a Reynolds number of Re = 2 × 106 to analyze the influence of VGs with AoAs between 0 and 20° and were validated versus experimental wind tunnel results. The results show that setting up a VG dev... [more]

This study was conducted to develop a simulation model of a 120 kW class electric all-wheel-drive (AWD) tractor and verify the model by comparing the measurement and simulation results. The platform was developed based on the power transmission system, including batteries, electric motors, reducers, wheels, and a charging system composed of a generator, an AC/DC converter, and chargers on each axle. The data measurement system was installed on the platform, consisting of an analog (current) and a digital part (rotational speed of electric motors and voltage and SOC (state of charge) level of batteries) by a CAN (controller area network) bus. The axle torque was calculated using the current and torque curves of the electric motor. The simulation model was developed by 1D simulation software and used axle torque and vehicle velocity data to create the simulation conditions. To compare the results of the simulation, a driving test using the platform was performed at a ground speed of 10 k... [more]

A novel and intelligent product development approach is required in this fast-growing and advanced technological era. Therefore, textile researchers have worked intensively to create efficient and transparent solutions for complex developments by using advanced modeling and simulation tools and techniques. This paper addresses a process for the thermal simulation of sportswear by considering the human thermophysiological model and important thermal properties of fabrics, i.e., thermal resistance, evaporative resistance, and permeability index. The results of the simulation are illustrated in terms of core body and mean skin temperatures. Moreover, results are validated by wear trials showing good consistency. This study is beneficial to the development of clothing for specific sports and the evaluation of comfort and heat stress during different sports activities.

Various mitigation strategies have been proposed to reduce the CO2 emissions from ships, which have become a major contributor to global emissions. The fuel consumption under different mitigation strategies can be evaluated based on two data sources, real data from the real ship systems and simulated data from the simulation models. In practice, the uncertainties in the obtained data may have non-negligible impacts on the evaluation of mitigation strategies. In this paper, a Gaussian process metamodel-based approach is proposed to evaluate the ship fuel consumption under different mitigation strategies. The proposed method not only can incorporate different data sources but also consider the uncertainties in the data to obtain a more reliable evaluation. A cost-effectiveness analysis based on the fuel consumption prediction is then applied to rank the mitigation strategies under uncertainty. The accuracy and efficiency of the proposed method is illustrated in a chemical tanker case stu... [more]

Fired bricks represent one of the most popular building materials, of which production is still growing. Since the functional properties of bricks have reached their physical limits, the current development aims at an optimization of production procedures as it goes along with heavy environmental loads. This paper is focused on tailoring the firing procedure to optimize the energy demands. Dealing with five different clays, their heat storage properties are determined using inverse analysis of calorimetric data so that the measurement errors are reduced. Moreover, effective values incorporate the thermal processes that occur during firing. A simplified model of clay samples is then used to calculate the energy demands for reaching an optimal firing scheme. The results show that specific treatment is necessary for particular clays as the energy demands may range between 89 and 173 MJ·m−2, depending on a clay composition. The highest demands were found in the case of clays containing the... [more]