Due to the long-term problem of electricity and potable water in most developing and undeveloped countries, predominantly rural areas, a novelty of the pendulum water pump, which uses a vertically excited parametric pendulum with variable-length using a sinusoidal excitation as a vibrating machine, is presented. With this, more oscillations can be achieved, reducing human effort further and having high output than the existing pendulum water pump with the conventional pendulum. The pendulum, lever, and piston assembly are modeled by a separate dynamical system and then joined into the many degrees-of-freedom dynamical systems. The present work includes friction while studying the system dynamics and then simulated to verify the system’s harmonic response. The study showed the effect of the pendulum length variability on the whole system’s performance. The vertically excited parametric pendulum with variable length in the system is established, giving faster and longer oscillations than... [more]

This paper is dedicated to studying and modeling the interdependence between the oil returns and exchange-rate movements of oil-exporting and oil-importing countries. Globally, twelve countries/regions are investigated, representing more than 60% and 67% of all oil exports and imports. The sample period encompasses economic and natural events like the Great Recession period (2007−2009) and the COVID-19 pandemic. We use the dynamic conditional correlation mixed-data sampling (DCC-MIDAS) model, with the aim of investigating the interdependencies expressed by the long-run correlation, which is a smoother (but always daily observed) version of the (daily) time-varying correlation. Focusing on the advent of the COVID-19 pandemic in 2020, the long-run correlations of the oil-exporting countries (Saudia Arabia, Russia, Iraq, Canada, United States, United Arab Emirates, and Nigeria) and (lagged) WTI crude oil returns strongly increase. For a subset of these countries (that is, Saudia Arabia, I... [more]

Given the substantial energy use for space cooling in buildings, integrating energy-efficient and sustainable cooling systems into buildings has become increasingly more important. Even though the cooling potential of a near-surface earth-to-air heat exchanger (EAHE) with grass cover was demonstrated in previous studies, the energy savings and environmental benefits resulting from using the EAHE have not yet been quantified. Therefore, in this study, we quantify the energy savings resulting from using a near-surface earth-to-air heat exchanger (EAHE) with grass-covered ground as a precooling unit in hot desert climates. The outlet air conditions of the EAHE during 9 months of the year (March to November), where space cooling is required, are predicted using a 3D transient CFD model, which is validated against field measurements. The EAHE is fabricated from a 1 mm thick aluminum tube with a diameter of 0.15 m and a length of 21.5 m, buried 0.4 m deep. The results showed that the EAHE ca... [more]

In recent decades, due to the increase in the capabilities of microprocessors and the advent of graphics processing units (GPUs), the use of machine learning methodologies has become popular in many fields of science and technology [...]

Interior permanent magnet (IPM) machines with hairpin windings have attracted significant attention in EV applications owing to their low DC resistance and excellent thermal capabilities. In this paper, we present a comprehensive investigation of AC winding losses in IPM machines for traction applications, including analytical modeling, the influence of design parameters, and finite element (FE) verification. The proposed analytical model can predict the trends in AC winding losses for any number of bar conductors and slot/pole combinations. The results of the parametric study, obtained via the analytical model, are presented to examine the effects of key design parameters, such as conductor width and height, phase arrangement, and slot-per-pole-per-phase (SPP). To incorporate more practical issues into the analysis of IPM machines with hairpin windings, extensive FE simulations were conducted. The results indicated that the AC winding losses decrease with an increasing number of condu... [more]

For a few years the multi-physics modelling of the resonance cavity (resonator) of MW-class continuous-wave gyrotrons, to be employed for electron cyclotron heating and current drive in magnetic confinement fusion machines, has gained increasing interest. The rising target power of the gyrotrons, which drives progressively higher Ohmic losses to be removed from the resonator, together with the need for limiting the resonator deformation as much as possible, has put more emphasis on the thermal-hydraulic and thermo-mechanic modeling of the cavity. To cope with that, a multi-physics simulator has been developed in recent years in a shared effort between several European institutions (the Karlsruher Institut für Technologie and Politecnico di Torino, supported by Fusion for Energy). In this paper the current status of the tool calibration and validation is addressed, aiming at highlighting where any direct or indirect comparisons with experimental data are missing and suggesting a possibl... [more]

CO2 storage is a greenhouse gas mitigation instrument for many countries. In this paper, we investigate the possibility of CO2 storage in the region of the Precaspian basin using the compositional flow model that was verified by the data of the Frio pilot project, USA. We use local grid refinement in the commercial reservoir simulator. In the reservoir simulation for data of the Frio Pilot project, we have achieved a good history matching of well pressure. Different scenarios were tested, and post-injection migration was shown for both case studies. The long-term reservoir simulation shows the potential amount of trapped CO2 by residual and dissolved trapping mechanisms in the Precaspian basin. The performed uncertainty study covered the uncertainty of the model’s parameters resulting in P10, P50 and P90 cases in terms of the amount of trapped CO2.

Due to the wide usability of thermoelectric generators (TEG) in the industry and research fields, it is plausible that mismatching conditions are present on the thermal surfaces of a TEG device, which induces negative-performance effects due to uneven surface temperature distributions. For this reason, the objective of this study is to characterize numerically the open-circuit electric output voltage of a TEG device when a mismatching condition is applied to both the cold and hot sides of the selected N and P-type semiconductor material Bi0.4Sb1.6Te3. A validated numerical simulation paired with a parametric study is conducted using the Thermal-Electric module of ANSYS 2020 R1, for which different thermal boundary and mismatching conditions are applied while considering the temperature-dependent thermoelectrical properties of the N and P-type material. The results show an inverse relationship between the open-circuit voltage and the mismatching temperature difference. When a mismatchin... [more]

The importance of mineral elements, both in animal and plant nutrition, has been well recognized, but, in the case of sedges, the mineral composition is relatively poorly known. Studies usually relate to the content of the elements in sedge communities, or sward or hay communities with sedge participation, and rarely of Carex representatives. The objective of our study was to determine the concentrations of C, N, Ca, P, Mg, Na, K, Si, Cu, Zn, Mn, Fe, Cr and Ni in the biomass of 11 Carex species commonly occurring on natural sites of Central European lowland. Interspecific differentiations have been observed in concentrations of the major and trace elements among studied sedge species. The elemental composition of examined Carex species is diversified but generally similar to the composition of grasses. The study shows that sedges can increase fodder value and, therefore, they should be considered in meadow management as a valuable component of economically important meadow communities.... [more]

Urea is the final product of protein metabolism in mammals and can be found in different biological fluids. Use of mammalian urine in agricultural production as organic fertilizer requires safe handling to avoid the formation of ammonia that will decrease the fertilizer value due to the loss of nitrogen. Safe handling is also required to minimize the decomposition of urea into condensed products such as biuret and cyanuric acid, which will also have a negative impact on the potential sustainable production of crops and sanitation technologies. The study of thermodynamics and reaction kinetics of urea stabilization plays a key role in understanding the conditions under which undesirable compounds and impurities in urea-based fertilizers and urea-based selective catalytic reduction systems are formed. For this reason, we studied the reaction of urea in acid media to achieve urea stabilization by modeling the reaction of urea with sulfuric acid and phosphoric acid, and estimating the reac... [more]

Since e-Mobility is on the rise worldwide, large charging infrastructure networks are required to satisfy the upcoming charging demand. Planning these networks not only involves different objectives from grid operators, drivers and Charging Station (CS) operators alike but it also underlies spatial and temporal uncertainties of the upcoming charging demand. Here, we aim at showing these uncertainties and assess different levers to enable the integration of e-Mobility. Therefore, we introduce an Agent-based model assessing regional charging demand and infrastructure networks with the interactions between charging infrastructure and electric vehicles. A global sensitivity analysis is applied to derive general guidelines for integrating e-Mobility effectively within a region by considering the grid impact, the economic viability and the Service Quality of the deployed Charging Infrastructure (SQCI). We show that an improved macro-economic framework should enable infrastructure investments... [more]

The shelf life of perishable products depends mainly on the conservation of air temperature. Packaging boxes are usually used to accommodate food products during cold storage and transport and/or display. The design of the vent-holes of the packaging box must promote cold airflow and remove the field heat of the produce after harvest at a short time. This study describes the influence of the vent-holes design and its performance during cold storage. The cooling performance of the different packaging boxes is evaluated experimentally and numerically using Computational Fluid Dynamics (CFD). Three new packaging box configurations with the same size but different vent-holes design (size, shape and position) and a reference box are modelled. The transient three-dimensional CFD model predicts the airflow pattern and temperature distribution within the different packaging boxes. The best thermal performance packaging achieved a fruit model temperature 1.5 K to 5 K lower than the other config... [more]

The integration of renewable energy sources into modern power systems requires simulations with smaller step sizes, larger network models and the incorporation of complex nonlinear component models. These features make it more difficult to meet computation time requirements in real-time simulations and have motivated the development of high-performance LU decomposition methods. Since nonlinear component models cause numerical variations in the system matrix between simulation steps, this paper places a particular focus on the recomputation of LU decomposition, i.e., on the refactorisation step. The main contribution is the adoption of a factorisation path algorithm for partial refactorisation, which takes into account that only a subset of matrix entries change their values. The approach is integrated into the modern LU decomposition method NICSLU and benchmarked against the methods SuperLU and KLU. A performance analysis was carried out considering benchmark as well as real power syst... [more]

Structural changes occurring in the crude oil market have stimulated the emergence of hypotheses suggesting that the relationship between prices of this raw material and the US dollar exchange rate can gradually become similar to that observed between oil prices and exchange rates of the currencies of the countries whose revenues from the export of this resource are a significant part of their current account balance. The purpose of this study was to determine and evaluate the time-varying dependence between oil prices and the exchange rate of the US dollar in the context of the same relationship for the Chinese, European, Japanese, Saudi, and Russian currencies. The results of our analyses implicate that a negative correlation between the variables in question grows stronger in time periods preceding global shocks and during thereof. The dominance of the USD in the crude oil market is reflected in similar characteristics of the correlations of the currencies of other countries, such a... [more]

The global maximum power point tracking of a PV array under partial shading represents a global optimization problem. Conventional maximum power point tracking algorithms fail to track the global maximum power point, and global optimization algorithms do not provide global maximum power point in real-time mode due to a slow convergence process. This paper presents an intelligent reconfigurable photovoltaic system on the basis of a modified fuzzy neural net that includes a convolutional block, recurrent networks, and fuzzy units. We tune the modified fuzzy neural net based on modified multi-dimension particle swarm optimization. Based on the processing of the sensors’ signals and the photovoltaic array’s image, the tuned modified fuzzy neural net generates an electrical interconnection matrix of a photovoltaic total-cross-tied array, which reaches the global maximum power point under non-homogeneous insolation. Thus, the intelligent reconfigurable photovoltaic system represents an effec... [more]

Transition to turbulence and changes in the fluid flow structure are subjects of continuous analysis and research, especially for unique fields of research such as the thermo-magnetic convection of weakly magnetic fluids. Therefore, an experimental and numerical research of the influence of an external magnetic field on a natural convection’s fluid flow was conducted in the presented research. The experimental part was performed for an enclosure with a 0.5 aspect ratio, which was filled with a paramagnetic fluid and placed in a superconducting magnet in a position granting the enhancement of the flow. The process was recorded as temperature signals from the thermocouples placed in the analyzed fluid. The numerical research enabled an investigation based not only on temperature, but velocities as well. Experimental and numerical data were analyzed with the application of extended fast Fourier transform and wavelet analysis. The obtained results allowed the determination of changes in th... [more]

This paper presents a detailed analysis of 1200 V Silicon Carbide (SiC) power MOSFET exhibiting different short-circuit failure mechanisms and improvement in reliability by VDS and VGS depolarization. The device robustness has undergone an incremental pulse under different density decreasing; either drain-source voltage or gate-driver voltage. Unlike silicon device, the SiC MOSFET failure mechanism firstly displays specific gradual gate-cracks mechanism and progressive gate-damage accumulations greater than 4 µs/9 J·cm−2. Secondly, a classical drain-source thermal runaway appears, as for silicon devices, in a time greater than 9 µs. Correlations with short-circuit energy measurements and temperature simulations are investigated. It is shown that the first mechanism is an incremental soft gate-failure-mode which can be easily used to detect and protect the device by a direct feedback on the gate-driver. Furthermore, it is highlighted that this new mechanism can be sufficiently consolida... [more]

In this study, a steady state model for burning of coal mine methane in a Reverse Flow Burner (RFB) with full kinetics was developed by analogy of a steady counter-flow reactor, and the developed model was used for quick prediction of the lean combustibility limit (LCL). The model was successfully validated with experimental and numerical results, and it was shown that the developed model has excellent accuracy and computational efficiency. Good agreement between the predicted temperature, LCL, and the experiments was observed. The LCL of the equivalence ratio of 0.022 for methane/air mixture was obtained by the developed model. The model was then used to evaluate LCL for the RFB, focusing on the effect of heat loss and burner length on LCL. This indicated that the computational time using the developed model can be reduced by a factor of 1560 compared to the complete transient model.

This paper presents the integration of advanced machine learning techniques in the medium voltage distributed monitoring system QuEEN. This system is aimed to monitor voltage dips in the Italian distribution network mainly for survey and research purposes. For each recorded event it is able to automatically evaluate its residual voltage and duration from the corresponding voltage rms values and provide its “validity” (invalidating any false events caused by voltage transformers saturation) and its “origin”(upstream or downstream from the measurement point) by proper procedures and algorithms (current techniques). On the other hand, in the last years new solutions have been proposed by RSE to improve the assessment of the validity and origin of the event: the DELFI classifier (DEep Learning for False voltage dips Identification) and the FExWaveS + SVM classifier (Features Extraction from Waveform Segmentation + Support Vector Machine classifier). These advanced functionalities have been... [more]

This paper newly proposes an interactive multiple model (IMM) algorithm to adaptively track distorted AC voltage with the grid frequency fluctuation. The usual tracking methods are Kalman filter (KF) algorithm with a fixed frequency and KF algorithm with frequency identifier. The KF algorithm with a fixed frequency has a larger covariance parameter to guarantee the tracking robustness. However, it has a large tracking error. The KF algorithm with frequency identifier overly depends on the accuracy and stability of frequency identifier. The advantage of the proposed method is that it is decoupled from frequency detection and does not depend on frequency detection accuracy. First, the orthogonal vector dynamic (OVD) tracking model of the sine wave is established. Then, a model set covering the grid frequency fluctuation range is formed, and a new OVD-IMM tracking algorithm is proposed in combination with IMM algorithm. In the end, the effectiveness and accuracy of the proposed OVD-IMM al... [more]

Wind energy has been recognized as the most promising and economical renewable energy source, attracting increasing attention in recent years. However, considering the variability and uncertainty of wind energy, accurate forecasting is crucial to propel high levels of wind energy penetration within electricity markets. In this paper, a comparative framework is proposed where a suite of long short-term memory (LSTM) recurrent neural networks (RNN) models, inclusive of standard, bidirectional, stacked, convolutional, and autoencoder architectures, are implemented to address the existing gaps and limitations of reported wind power forecasting methodologies. These integrated networks are implemented through an iterative process of varying hyperparameters to better assess their effect, and the overall performance of each architecture, when tackling one-hour to three-hours ahead wind power forecasting. The corresponding validation is carried out through hourly wind power data from the Spanis... [more]

Solar irradiance models contribute to mitigating the lack of measurement data at a ground station. Conventionally, the models relied on physical calculations or empirical correlations. Recently, machine learning as a sophisticated statistical method has gained popularity due to its accuracy and potential. While some studies compared machine learning models with other models, a study has not yet been performed that compares them side-by-side to assess their performance using the same datasets in different locations. Therefore, this study aims to evaluate the accuracy of three representative models for estimating solar irradiance using atmospheric variables measurement and cloud amount derived from satellite images as the input parameters. Based on its applicability and performance, this study selected the fast all-sky radiation model for solar applications (FARMS) derived from the radiative transfer approach, the Hammer model that simplified atmospheric correlation, and the long short-t... [more]

This article presents the methodology, description, and results of experimental studies aimed at determining the impact of the copper concentration in a carbon−metal composite contact strip on the maximum temperature of the copper contact wire during a contact event when used for operation in the railway industry in Europe. Based on these tests, we determined the minimum percentage of copper that is required for the composite to meet the normative requirements for current loads. In addition to experimental research, a 3D FEM numerical model was also developed in which the contact strip and contact wire geometry were mapped, along with imposed loads resulting from the test for current loads mentioned above. Fifteen simulation variants were carried out for the established model, where the value of the thermal conductivity coefficient and the specific heat coefficient were varied. On this basis, we analyzed the sensitivity of thermal coefficients to the contact wire temperature and determ... [more]

The vision of the smart city is inextricably linked with the concepts of intelligent transport, sustainable mobility and managerial decision making. Cities of the future not only entail the use of new technology, but also increasingly the interpenetration of technological and social aspects, with the simultaneous involvement of urban space users in the creation of such technologies. This provides an opportunity to introduce desired changes and create a more balanced space with a higher quality of life and improved energy efficiency. The article discusses the concepts of sustainable development and sustainable mobility with a particular emphasis on issues related to the smart city. The authors reviewed the various smart city solutions that have been implemented in the field of urban transport in Cracow, whose authorities have taken steps over the last few years to make the city smarter and more modern. The aim of the research was to assess the contribution made by smart city solutions t... [more]

This editorial document provides the main motivations and a brief description of each paper published in the “Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation” Special Issue. This Special Issue aims to present several innovative solutions on planning and operation of distribution power networks under smart grid paradigm where prosumers, electric vehicles, and other typical loads are usually connected. Some of those solutions and computational applications were covered in this Special Issue, namely probabilistic power flow, voltage and power factor control, agent-based simulation, digital twin, resilient energy scheduling, and uncertainty modeling are among the contributions. The published works are very timely and are of great interest, which will certainly drive the impact of future researchers in the near term concerning the field of this Special Issue.