• Energy Research
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Abstract This study evaluates the mechanical behaviour of a ceramic disk which makes up an innovative volumetric absorber design. The new receiver design is formed by a group of disks which are rotating inside a cavity, distributing the radiation absorbed in the aperture to the whole cavity. This research studies the stress fields due to thermal gradients and its effect in the crack propagation in the disks. The complete analysis has been carried out in three steps: the mechanical characterization of the material, in order to know its fracture properties, the computational fluid dynamics (CFD) analysis of the disk, in order to know the temperature distribution in the disk and the finite element model (FEM), which uses as inputs the results of the two previous steps and solves the stress fields in the disk and the fracture behaviour. Fracture and crack growing in the disk have been modelled by using a cohesive element, which, from the fracture properties of the material, allows simulating the crack growing in the disk. This investigation, by means of stress fields and crack propagation analysis, demonstrates the mechanical viability of the disks concept.

Abstract Catalytic co-liquefaction of high-density polyethylene and sugarcane bagasse over metal salt and oxide catalysts in ethanol solvent was investigated. The obtained bio-oil samples were analyzed and characterized by gas chromatography–mass spectroscopy (GC–MS), nuclear magnetic resonance (NMR), ultimate analysis (CHNS/O), Fourier transform infrared spectroscopy (FTIR) and different solid products characterized by x-ray fluorescence (XRF) and Scanning Electron Microscope (SEM) analysis. The results suggested that adding ZnSO4 gives the highest HHV (34.61 MJ/kg), while CuSO4 gives the highest bio-oil yield (38.42 %) and conversion (69.54 %). GC–MS analysis suggested that the bio-oils contained large amounts of hydrocarbons, phenols, ketone aldehydes, alcohols and esters. The 1H and 13C NMR spectra were integrated over spectral regions to quantify classes of carbon and hydrogen atoms in each bio-oil and suggested that bio-oils largely contain alkanes, aliphatics and alcohols. The liquid products are promising bio-fuel precursors for further utilization.

This paper shows how to exploit the degree of freedom represented by the common-mode voltage, which is inherent in three-phase Cascaded H-Bridge (CHB) converters, to minimize the total Root Mean Square (RMS) current value of the distributed dc sources. An optimal common-mode voltage injection law is derived, constituting a Maximum Power Per Ampere (MPPA) modulation strategy with respect to the currents of the dc sources. The potential benefits introduced by the proposed algorithm are analyzed in the context of battery-fed CHB converters and validated experimentally with a three-time-constant Randles model of a battery cell. The MPPA strategy is compared with traditional common-mode voltage injection methods, and battery loss reduction is demonstrated. The obtained battery energy saving is dependent on the converter modulation index and power factor. Experimental tests on a 36-cell full-bridge CHB converter validates the simulation and numerical derivation. To demonstrate the efficacy of the proposed method in practical applications, a 3 MW Energy Storage System (ESS) and a 110 kW Battery Electric Vehicle (BEV) undergoing standard drive cycles are presented as case studies. Compared to traditional modulation strategies, the MPPA strategy reduces the battery losses by up to 10.9% in the ESS and 27.5% in the BEV application.

Abstract During the last decades, the safety analysis of nuclear power plants, have been shifting from conservative models and hypotheses to Best Estimate. Within this trend, the different safety analyses can be categorized depending on their associated conservatisms. The approach that includes Expanded Event Trees together with Best Estimate model and conditions plus uncertainty avoiding conservatisms in system availability can be referred as Extended BEPU (EBEPU). In this sense, an Extended BEPU safety analysis relies on Expanded Event Trees and Best Estimate models to study an accidental sequence. In the present paper, an EBEPU study is performed, using a loss of coolant accident in a pressurized water reactor modeled with the TRACE code. A 5% core power uprate is used as an example of safety margin EBEPU analysis. The paper presents parametric and non-parametric uncertainty approaches. Observing the results from all event tree sequences, it is seen that the branches that contribute the most to the Core Damage frequency are successful branches, with all safety systems available, and some Core Damage branches have a possibility of success.

Abstract 3D printing technologies are being called on to revolutionize the manufacturing industry of the energy sector, especially when involving functional materials and complete devices. These additive manufacturing technologies show competitive advantages over conventional processes, however only a few studies have assessed their environmental implications. In this work, the environmental performance of a Solid Oxide Fuel Cell stack produced using a novel 3D printing approach is conducted for the first time using Life Cycle Assessment. In addition, a comparative study with conventional manufacturing methods is carried out. The results reveal that the production of the 3D printing materials has the highest environmental impact (between 50% and 98%) in half of the categories studied. In contrast, the end-of-life stage represents less than 1% of the total impact. End-of-life scenarios are also presented and discussed, indicating that a recycling rate of 70% for Nickel and YSZ materials performs better than the defined landfill and incineration disposal scenarios. Furthermore, 3D printing shows the best overall environmental performance compared to other conventional methods. The main improvement is seen in the material production stage, where a savings ranging from 37% to 97% (depending on the category analysed) is observed. This is mainly due to the use of a ceramic material for the interconnects instead of Chromium-based alloys used in a more conventional approach. Finally, it was observed that the energy required for 3D printing in the manufacturing stage is a sensible parameter to the environmental performance of the SOFC 3D printing technology.

Urbanization, economic growth, and intensity of electricity consumption are the important causative factors of environmental degradation in South Asia. The present study has revealed this while investigating the relationship between the level of CO2 emissions and important economic variables in the context of five South Asian countries. Panel data are used for this study over the period 1974–2017. Panel co-integration tests and the Panel Autoregressive Distributive Lag (PARDL) model are applied for empirical analysis. Robust results of the analysis indicate that urbanization, Gross Domestic Product (GDP) and the intensity of electricity consumption are contributing factors to carbon emissions. Based on the results of the Dumitrescu Hurlin Panel Causality test, it is concluded that there is a bi-directional causal link between urbanization and CO2 emissions and unidirectional causal links from GDP to CO2 emissions, from GDP to urbanization, and from the intensity of electricity consumption to urbanization. This study focuses on planned urbanization, eco-efficient income growth, and sensible use of electricity to control CO2 emissions in this region. Considering the nature of these developing economies in South Asia, collaborative measures and strategic planning are suggested on a regional basis to address the concerns in the above-mentioned areas that minimize carbon emissions and thereby aid sustainable development in this region.

Abstract Using a panel data analysis of a newly developed sample of monthly data by state for January 2005 to December 2019, we estimate a series of error correction models for US residential electricity demand postulated to move with electricity price, natural gas price, income, and weather. Our key findings are as follows. First, the short-run own-price elasticity estimate is not statistically different from zero (p-value > 0.8). Second, the long-run own- and cross-price elasticity estimates are −0.054 (p-value = 0.000) and 0.019 (p-value = 0.000) under the double-log specification, smaller in size than the long-run own- and cross-price elasticity estimates of −0.120 (p-value = 0.000) and 0.069 (p-value = 0.000) under the linear demand specification. Third, price elasticity estimates have been shrinking in size over time. Fourth, erroneously ignoring the panel data's cross-sectional dependence tends to more than double the long-run price elasticity estimates. Fifth, mismatching the timing of price information's availability and consumption decision leads to anomalous price elasticity estimates. Finally, our new empirics' key takeaway of low price-responsiveness supports continuation of energy efficiency standards and demand-side management programs.