The automotive armoring industry, which protects against ballistic attacks, lacks studies regarding damage to the human body during a collision. In this work, we study the mass changes in a vehicle undergoing a level III armored process, through a numerical evaluation of the full-frontal impact of a sport utility vehicle (SUV)—a Ford Explorer 2002. In this work, we present two evaluations. We first analyze the displacement suffered by the vehicle during an impact due to the increase in mass and structural stiffness and we then evaluate the deceleration loads that the user suffers in the event of a crash. In addition, dynamic analyses were performed to quantify the head injury criterion (HIC) and chest severity index (CSI) on a 50th percentile dummy to calculate the probability of the occupant suffering possible injuries. The outcome shows a comparison between the acceleration severity index (ASI) of a commercial vehicle adapted to an armored process and an unshielded vehicle.

The limitation of transmission lines thermal capacity plays a crucial role in the safety and reliability of power systems. Dynamic thermal line rating approaches aim to estimate the transmission line’s temperature and assess its compliance with the limitations above. Existing physics-based standards estimate the temperature based on environment and line conditions measured by several sensors. This manuscript shows that estimation accuracy can be improved by adopting a data-driven Digital Twin approach. The proposed method exploits machine learning by learning the input−output relation between the physical sensors data and the actual conductor temperature, serving as a digital equivalent to physics-based standards. An experimental assessment on real data, comparing the proposed approach with the IEEE 738 standard, shows a reduction of 60% of the Root Mean Squared Error and a decrease in the maximum estimation error from above 10 °C to below 7 °C. These preliminary results suggest that t... [more]

Real-time Simulation (RTS) is one of the effective means via which to study device level or system level dynamics, such as power converter online testing, evaluation, and control, and power system stability analysis. The RTS -enabled design-chain offers a time -effective, low-cost, and fail-safe development process. As the penetration of renewable energy is becoming higher, the demand in hybrid system real-time simulation becomes imperative, where fast-dynamic device level power converters and slow -dynamic large -scale power systems are simulated at the same time. This paper introduces a novel hybrid real-time simulation architecture based on the central processing unit (CPU) and the field-programmable gate array (FPGA). Compared with the off-the-shelf power system real-time simulation system, it offers both wide time scale simulation and high accuracy. The multi-time scale model can perform electromechanical electromagnetic transient hybrid simulation, which can be applied to the res... [more]

Microgrids, or distributed systems of local energy generation, transmission, and demand, are now technologically and operationally capable of providing power to communities, especially in rural and peri-urban regions of developing nations. The reliability of the system, the cost of power generation, and the operating environmental impact are the major issues when designing and evaluating the performance of an off-grid hybrid renewable energy microgrid (HREM). This paper presents an integrated method for optimal sizing and operation of an HREM for rural agricultural communities in the Southern Philippines composed of run-of-the-river hydropower, photovoltaics (PV), diesel generator, and a battery energy storage system (BESS) using multi-objective particle swarm optimization (MOPSO) and a proposed multi-case power management strategy. The three conflicting objective functions that were simultaneously minimized were: loss of power supply probability (LPSP), levelized cost of energy (LCOE)... [more]

Capacitive technology for wireless power transmission has been shown to be a good option for charging the batteries of electric vehicles. It offers better coupling between the transmitter and the receiver than inductive power transmission. On the other hand, it has some disadvantages; for example, it is very sensitive to the distance between plates. Several ideas have recently been proposed to overcome this disadvantage. However, a proper analysis methodology is still lacking, as is a proper design procedure for the circuits used in capacitive transmission. In this paper, an analysis and design methodology is presented for applying the Z-tank resonant circuit to capacitive power transmission, and the theoretical design methodology is based on normalized equations with respect to the operating resonance frequency. The analysis methodology and design procedure result in a circuit where the resonance frequency remains constant despite changes in the distance between the capacitive plates.... [more]

Contact cooling using thermopressor technologies is a promising direction for the development of energy-efficient technologies. This technology is based on the implementation of the thermo-gas-dynamic compression effect in special contact heat exchangers that consists of increasing the pressure while decreasing the temperature during the evaporation of a finely dispersed liquid injected into a gas flow moving at a speed close to sound. Upon application of the thermopressor for charge air cooling of the engine, the following result was obtained: an increase in the air pressure after the turbocharger by 340 to 480 kPa. The thermopressor can be used as a boost stage after the turbocharger, resulting in the reduction of a basic turbocharger compression work and the increase of engine power output accordingly. Reducing the work allows for the same air flow rate on the internal combustion engine to reduce the compressor power by 10 to 12%. This increases the temperature of the exhaust gases... [more]

The benefits of networked microgrids in terms of economics and resilience are investigated and validated in this work. Considering the stochastic unintentional islanding conditions and conventional forecast errors of both renewable generation and loads, a two-stage adaptive robust optimization is proposed to minimize the total operating cost of networked microgrids in the worst scenario of the modeled uncertainties. By coordinating the dispatch of distributed energy resources (DERs) and responsive demand among networked microgrids, the total operating cost is minimized, which includes the start-up and shut-down cost of distributed generators (DGs), the operation and maintenance (O&M) cost of DGs, the cost of buying/selling power from/to the utility grid, the degradation cost of energy storage systems (ESSs), and the cost associated with load shedding. The proposed optimization is solved with the column and constraint generation (C&CG) algorithm. The results of case studies demonstrate... [more]

The increased adoption of intermittent renewable sources in the energy sector has also increased the use of battery storage systems. However, the negative impact which the improper disposal of batteries has on the environment has stirred debates on its sustainability. To ensure the proper disposal of battery waste, there is a need to identify and rank the most preferred battery ‘end-of-life’ handling alternatives. This paper focuses on identifying the most preferred ‘end-of-life’ handling alternatives for batteries using a modified triangular intuitionistic fuzzy aggregating and ranking function (TIFARF) model. To test the proposed modified TIFARF model, opinions from experts in the Nigerian renewable energy sector were collected, and the results show that the most preferred alternative is incineration, with a closeness coefficient of 0.130, while the least preferred alternative is recycling, whose closeness coefficient is 0.112. The results are an indication of a lack of facilities ne... [more]

This paper presents a filterless sensorless control scheme with an optimized time sequence based on high-frequency (HF) square-wave voltage injection for a five-phase interior permanent magnet machine (IPMSM) drive. To avoid the utilization of low-pass filters (LPFs) in signal processing, an effective method without filters is proposed in this paper. Moreover, the cross-coupling magnetic saturation is analyzed and the online position error compensation is applied based on the offline measurements and finite-element analysis (FEA). Besides, compared with the conventional time sequence of senseorless control, the proposed optimized time sequence can eliminate the additional position estimation error caused by the time delay in digital implementation. Numerical simulations and experiments with a 2-kW five-phase IPMSM are carried out. The results verify the feasibility and effectiveness of the proposed sensorless control scheme with an optimized time sequence adopted by the IPMSM drives.

In this paper, we present a trajectory period folding method for numerical modelling of nuclear transformations. The method uses the linear chain method, commonly applied for modelling of isotopic changes in matter. The developed method folds two consecutive periods of time and forms linear chain representations. In the same way as in the linear chain method, the mass flow of straight nuclide-to-nuclide transitions following the formation of nuclide transmutation chains in every step is considered over the total period of interest. Therefore, all quantitative data about the isotopic transformations for the period beyond a particular calculation step are preserved. Moreover, it is possible to investigate the formation history of any isotope from the beginning of irradiation to the arbitrary time step, including cooling periods and multi-recycling for any designed nuclear fuel cycle. We present a case study for the transition from 238U to 239Pu and define the properties of the developed... [more]

The paper presents problems related to the processing of signals recorded with differential field probes E and H. The fundamental problem to which special attention has been paid is the result of the integration operation. Due to the presence of constant/slowly-varying components in the raw signal, there is a drift present in the outcome of integration. This line wander can be enormous. This is particularly evident if the integration is performed in a standard manner, uniformly over the entire recorded waveform. The paper contains the Authors’ proposition to segment the signal and perform the integration independently in each of the sub-regions. This approach is based on the assumption of a local mean value instead of its global character for the recorded waveform. Although this leads to more complex signal processing, it gives significantly better results as it is suppressing the deterioration drift in the integrated signal more than 400 times. The results are presented on laboratory... [more]

Incorporating solar energy into a grid necessitates an accurate power production forecast for photovoltaic (PV) facilities. In this research, output PV power was predicted at an hour ahead on yearly basis for three different PV plants based on polycrystalline (p-si), monocrystalline (m-si), and thin-film (a-si) technologies over a four-year period. Wind speed, module temperature, ambiance, and solar irradiation were among the input characteristics taken into account. Each PV plant power output was the output parameter. A deep learning method (RNN-LSTM) was developed and evaluated against existing techniques to forecast the PV output power of the selected PV plant. The proposed technique was compared with regression (GPR, GPR (PCA)), hybrid ANFIS (grid partitioning, subtractive clustering and FCM) and machine learning (ANN, SVR, SVR (PCA)) methods. Furthermore, different LSTM structures were also investigated, with recurrent neural networks (RNN) based on 2019 data to determine the best... [more]

Distributed generation (DG) plays a vital role in electrical power networks. However, power loss reduction, voltage profile improvement, friendly environment, and reliability are all benefits of DG units. In this research work, a worthwhile methodology is recommended for optimal allocation of traditional (gas turbine) and renewable energy sources that are based on distributed generators which include solar and wind in the distribution system. The major objective of the research paper is the minimization of real, reactive power losses and emissions produced during the application of these conventional sources. Originally, the best locations to place this DG are identified using the concept of water, energy, and food algorithm (WEFA). The number and sizes of these renewable energy sources selected (wind and solar) are determined by applying the concepts of the Dragonfly Algorithm. The Weibull and beta distribution functions are modeled to extract the exact position to fix our DGs to mini... [more]

Baking ovens are necessary to be installed in a paint shop of assembly automotive manufacturers for drying the paint of automotive bodies (i.e., in the coating process). In this process, a large amount of heat is provided by burning the natural gas in the gas burner. Practically, the design of the heat confinement in the oven is often poor, which results in considerable heat losses (i.e., waste heat) which are released during the drying process and significantly raise the temperature of a working environment thereby lowering the thermal comfort of the factory staff. To address this issue and limit the waste heat transfer to the surroundings, the application of a waste heat recovery system of a specific design employing the organic Rankine cycle (ORC) may be a viable alternative solution. A combined design of such a system utilizing an evaporator and thermal energy storage (TES) device in a simple ORC layout will be discussed in this article. The obtained simulation result was computed... [more]

This paper is an introduction to the cycle proposed by the authors related to research directions concerning the problems of condensation of zeotropic refrigerant mixtures. For over a hundred years, research has been conducted on the search for new working fluids in the cycles for cooling devices and heat pumps. Initially, the natural refrigerants used were replaced with homogeneous synthetic refrigerants, followed by mixtures of two or more refrigerants. Among the mixtures, there are azeotropic and zeotropic mixtures. In the case of an azeotrope mixture, a liquid solution of two or more chemical compounds is in thermodynamic equilibrium with the saturated vapor resulting from this mixture. The chemical composition of the liquid and vapor is identical. A zeotropic mixture is a liquid-vapor system in which the composition of a liquid mixture (solution) of two or more chemical compounds is always different from that of the saturated vapor generated from this liquid. This is due to the di... [more]

Achieving a fully integrated energy market under the EU electricity target model constitutes an ongoing process. Given that the integration of spot markets is already at a mature stage, the next step forward is the successful integration of the balancing markets across European control areas. An analytical review of all the aspects governing the European balancing market integration is presented in this paper, providing a detailed description on the European regulatory framework on this topic. In addition, the design variables that need to be harmonized among national balancing markets as well as the available balancing market arrangements for the exchange of cross-border balancing services are presented. Numerical examples of the essence of the balancing market integration are provided, and the implementation projects initiated by European transmission system operators (TSOs) towards this direction are described. The review concludes that balancing market integration may indeed lead t... [more]

The COVID pandemic has caused a major exodus of passengers who chose urban and suburban transport. In many countries, especially in the European Union, there is a tendency to choose individual means of transport, causing damage to the environment and contributing significantly to greenhouse gas emissions. One method to promote urban transport is replacing bus fleets with newer ones, thus making public transport more attractive and reducing the emission of harmful exhaust fume components into the atmosphere. The aim of this study was to show a methodology for calculating CO2e for bus fleets. When determining CO2e, the principal greenhouse gases, such as CO2, CH4, and N2O, are usually considered. However, CO emissions also have indirect effects on climate through enhanced levels of tropospheric O3 and increased lifetime of CH4; therefore, CO2, CH4, N2O, and CO emissions were determined for CO2e emission calculations. Two bus fleet variant scenarios were analysed; the first non-investment... [more]

The state of health and remaining useful life of lithium-ion batteries are key indicators for the normal operation of electrical devices. To address the problem of the capacity of lithium-ion batteries being difficult to measure online, in this paper, we propose an online method based on particle swarm optimization and support vector regression to estimation the state of health and remaining useful life. First, a novel health indicator is extracted from the discharge voltage to characterize the capacity of lithium-ion batteries. Then, based on the capacity degradation characteristics, support vector regression is used to predict the remaining useful life of these batteries, and particle swarm optimization is selected to optimize the parameters of the support vector regression, which effectively enhances the predictive performance of the model. Validated for the NASA battery aging dataset, when training with the first 40% of the dataset, the maximum error of the predicted remaining usef... [more]

The effects of two different metal oxide catalysts, SnO and Li2O, on the dehydrogenation temperature of Carbazole and N-Ethylcarbazole (NE), respectively, were investigated by the Thermogravimetric analyzer and Differential Scanning Calorimetry. Thermogravimetric experiments were performed with 10wt% SnO and Li2O added to Carbazole and N-Ethylcarbazole, respectively, and compared to pure Carbazole and N-Ethylcarbazole. The results showed that the dehydrogenation temperature of N-Ethylcarbazole was lower than that of Carbazole, and the dehydrogenation temperature of N-Ethylcarbazole +SnO was the lowest, and SnO is an ideal dehydrogenation catalyst for N-Ethylcarbazole. Experiments using Differential Scanning Calorimetry and a Thermogravimetric analyzer showed that with the addition of catalyst, the activation energy of the mixture was more significant and stable, and the thermal hazard was reduced, whereas the relative dehydrogenation temperature was increased. This study provides impor... [more]

The intensity in energy consumption due to food production systems represents a major issue in a context of natural resources depletion and an increasing worldwide population. In this framework, at least a third of global food production is being lost or wasted. Moreover, about 38% of the energy embedded in total food production is being lost. Consequently, the assessment of energy consumption in food systems, and in food loss and waste valorization systems, is an increasing trend in recent years. In this line, this work presents a systematic review, selecting 74 articles from a search of 16,930 papers regarding the key words “energy assessment food”. The aim was to determine the current and historical trends in this field of research. Results pointed to a worldwide acceleration in trends since 2014, standing out in China and other Asian countries. Concerning the topics of the publications, energy consumption in the food sector is a research field which has existed since 1979. Moreover... [more]

Traditional reactive power optimization mainly considers the constraints of active management elements and ignores the randomness and volatility of distributed energy sources, which cannot meet the actual demand. Therefore, this paper establishes a reactive power optimization model for active distribution networks, which is solved by a second-order cone relaxation method and interval optimization theory. On the one hand, the second-order cone relaxation technique transforms the non-convex optimal dynamic problem into a convex optimization model to improve the solving efficiency. On the other hand, the interval optimization strategy can solve the source−load uncertainty problem in the distribution network and obtain the interval solution of the optimization problem. Specially, we use confidence interval estimation to shorten the interval range, thereby improving the accuracy of the interval solution. The model takes the minimum economy as the objective function and considers a variety o... [more]

To ensure effective heat recovery of thermoelectric generators, a cooling system is necessary to maintain the working temperature difference of the thermoelectric couples, which decreases continuously due to thermal diffusion. In order to evaluate and improve the thermoelectric performance of a concentric annular thermoelectric generator under various cooling methods, a comprehensive numerical model of the thermo-fluid-electric multi-physics field for an annular thermoelectric generator with a concentric annular heat exchanger was developed using the finite-element method. The effects of four cooling methods and different exhaust parameters on the thermoelectric performance were investigated. The results show that, in comparison to the cocurrent cooling pattern, the countercurrent cooling pattern effectively reduces temperature distribution non-uniformity and hence increases the maximum output power; however, it requires more thermoelectric semiconductor materials. Furthermore, when us... [more]

This paper presents the challenges of increasing the energy efficiency investments in European Union (EU) residential buildings in the context of achieving climate neutrality by 2050. The paper presents the results of the PRIMES buildings model in key energy policy applications to support cost-effective and fair policy making in buildings across Europe. The model covers, in detail, the building sector for all the EU Member States (MS), segmenting the buildings into many categories. The approach proposed includes non-market barriers in conventional microeconomic modelling, which combined with idiosyncratic preferences can capture poor energy efficiency choices and still represent rational behaviours. The model includes a detailed portrayal of policies specific to the sector, comprising economic and regulatory policies as well as institutional measures. The results of the model show that the removal of non-market barriers is of great importance in reducing energy consumption and increasi... [more]

Currently, floating offshore wind is experiencing rapid development towards a commercial scale. However, the research to design new control strategies requires numerical models of low computational cost accounting for the most relevant dynamics. In this paper, a reduced linear time-domain model is presented and validated. The model represents the main floating offshore wind turbine dynamics with four planar degrees of freedom: surge, heave, pitch, first tower fore-aft deflection, and rotor speed to account for rotor dynamics. The model relies on multibody and modal theories to develop the equation of motion. Aerodynamic loads are calculated using the wind turbine power performance curves obtained in a preprocessing step. Hydrodynamic loads are precomputed using a panel code solver and the mooring forces are obtained using a look-up table for different system displacements. Without any adjustment, the model accurately predicts the system motions for coupled stochastic wind−wave conditio... [more]

The importance of a flexible and comprehensive vehicle fuel consumption model cannot be understated for understanding the implications of the modal changes currently occurring in the transportation sector. In this study, a model is developed to determine the tank-to-wheel energy demand for passenger and freight transportation within Germany for different modes of transport. These modes include light-duty vehicles (LDVs), heavy-duty vehicles (HDVs), airplanes, trains, ships, and unmanned aviation. The model further estimates future development through 2050. Utilizing standard driving cycles, backward-looking longitudinal vehicle models are employed to determine the energy demand for all on-road vehicle modes. For non-road vehicle modes, energy demand from the literature is drawn upon to develop the model. It is found that various vehicle parameters exert different effects on vehicle energy demand, depending on the driving scenario. Public transportation offers the most energy-efficient... [more]