In the constant pursue of the sustainability of socio-industrial systems, the definition of useful, reliable and informative, and at the same time simple and transparent, indicators is an important step for the evaluation of the circularity of the assessed systems. In the circular economy (CE) context, scientific literature has already identified the lack of overarching indicators (social, urban, prevention-oriented, etc.), pointing out that mono-dimensional indicators are not able to grasp the complexity of the systemic, closed-loop, feedback features of CE. In this respect, Emergy accounting is one of the approaches that have been identified as holding the potential to capture both resource generation and product delivery dimensions and therefore to provide an enhanced systems’ evaluation in a CE perspective.
Because of Emergy’s intrinsic definition and its calculation structure, Emergy-based indicators conceptually lend themselves very well to the evaluation and monitoring of circular processes. Additionally, Emergy has the unique feature of enabling the evaluation of systems that are not necessarily only technosphere systems, but also of technological systems which embed nature (techno-ecological systems).
The present paper gives a perspective on a set of Emergy-based indicators that we have identified as suitable to evaluate circular systems, and outlines the different perspective compared to the circularity indicators defined in the “Circularity Indicators Project” launched by the Ellen MacArthur Foundation.
The paper presents new ensemble solutions, which can forecast the average level of particulate matters PM10 and PM2.5 with increased accuracy. The proposed network is composed of weak predictors integrated into a final expert system. The members of the ensemble are built based on deep multilayer perceptron and decision tree and use bagging and boosting principle in elaborating common decisions. The numerical experiments have been carried out for prediction of daily average pollution of PM10 and PM2.5 for the next day. The results of experiments have shown, that bagging and boosting ensembles employing these weak predictors improve greatly the quality of results. The mean absolute errors have been reduced by more than 30% in the case of PM10 and 20% in the case of PM2.5 in comparison to individually acting predictors.
The purpose of this paper is to propose a model of a novel quasi-resonant boost converter with a tapped inductor. This converter combines the advantages of zero voltage quasi-resonant techniques and different conduction modes with the possibility of obtaining a high voltage conversion ratio by using a tapped inductor, which results in high converter efficiency and soft switching in the whole output power range. The paper contains an analysis of converter operation, a determination of voltage conversion ratio and the maximum voltage across power semiconductor switches as well as a discussion of control methods in discontinuous, critical, and continuous conduction modes. In order to verify the novelty of the proposed converter, a laboratory prototype of 300 W power was built. The highest efficiency η = 94.7% was measured with the output power Po = 260 W and the input voltage Vin = 50 V. The lowest efficiency of 90.7% was obtained for the input voltage Vin = 30 V and the output power Po = 75 W. The model was tested at input voltages (30–50) V, output voltage 380 V and maximum switching frequency 100 kHz.
Large-signal input characteristics of three DC–DC converter types: buck, boost and flyback working in the discontinuous conduction mode (DCM), obtained by precise large signal PSpice simulations, calculations based on averaged models and measurements are presented. The parasitic resistances of the converter components are included in the simulations. The specific features of the input characteristics in theDCMand the differences between the continuous conduction mode (CCM) and DCM are discussed.
Large-signal input characteristics of three DC–DC converter types: buck, boost and flyback working in the continuous conduction mode (CCM), obtained by simulations and measurements are investigated. The results of investigations are presented in the form of the analytical formulas and the exemplary results of the measurements and two forms of simulations: based on the full description of the converter components and on the averaged models. The parasitic resistances of the converter components are included in the simulations and their influence on the simulation results is discussed.
DC-DC converters are popular switch-mode electronic circuits used in power supply systems of many electronic devices. Designing such converters requires reliable computation methods and models of components contained in these converters, allowing for accurate and fast computations of their characteristics. In the paper, a new averaged model of a diodetransistor switch containing an IGBT is proposed. The form of the developed model is presented. Its accuracy is verified by comparing the computed characteristics of the boost converter with the characteristics computed in SPICE using a transient analysis and literature models of a diode and an IGBT. The obtained results of computations proved the usefulness of the proposed model.