• Energy Research
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The conveniency between remanufacturing a single mechanical product and its new production is a highly investigated topic across various disciplines, including supply chain management. To this end, a comparison was made among three different configurations of the supply chain network: the traditional network for new production, the network with remanufacturing and direct interaction between customer and manufacturer, and the network with remanufacturing and indirect interaction between customer and manufacturer through a distribution center. The evaluation of scenarios for the remanufacturing conveniency of remanufacturing was conducted from both an economic and energetic perspective, generating 10'000 cases using the Sobol quasi-random low-discrepancy sequence. The generation was carried out for both economic and energetic analyses for three types of materials, namely steel, aluminum, and titanium, for which complete datasets are provided: Steel_EconomicAnalysis.xlsx: dataset for economic analysis for the remanufacturing conveniency of mechanical products in steel Steel_EnergeticAnalysis.xlsx: dataset for energetic analysis for the remanufacturing conveniency of mechanical products in steel Aluminum_EconomicAnalysis.xlsx: dataset for economic analysis for the remanufacturing conveniency of mechanical products in aluminum Aluminum_EnergeticAnalysis.xlsx: dataset for energetic analysis for the remanufacturing conveniency of mechanical products in aluminum Titanium_EconomicAnalysis.xlsx: dataset for economic analysis for the remanufacturing conveniency of mechanical products in titanium Titanium_EnergeticAnalysis.xlsx: dataset for energetic analysis for the remanufacturing conveniency of mechanical products in titanium

Electric vehicles (EVs) are pivotal in the global shift towards sustainable energy systems. As EV adoption rises, effective integration into the power grid becomes vital. Vehicle-to-grid (V2G) operations, enabling bidirectional power flow between EVs and the grid, enhance grid resilience and leverage EVs as distributed energy resources. This article presents a comprehensive framework addressing gaps in EV integration. It combines EV travel energy forecasts and electricity market engagement, coordinating forecast-based optimization with real-time management. Our approach introduces a novel prioritization mechanism, optimizing power allocation based on forecasted state-of-charge for upcoming trips. The optimization follows a multi-objective function that aims to minimize the operational costs and maximize both the upward and downward flexibility to provide ancillary services. The study assesses EV participation in Replacement Reserve, Secondary Reserve, and energy arbitrage. Simulations compare scenarios, unveiling optimal performances. The framework showcases EVs' potential to bolster grid stability, yielding economic value for EV owners and the power system. This article pioneers a holistic approach to EV integration, bridging current limitations, and emphasizing economic and technical benefits.

Renewable energy sources—which are available in abundance all around us and are provided by the sun, wind, water, waste, and heat from the Earth—are replenished by nature and emit little to no greenhouse gases or pollutants into the air. This paper builds upon a preceding study that examined beliefs, perceptions, and attitudes regarding renewable energy technologies. In this study, we examine the implications renewable energy sources may have on science, technology policies, and education. This study embraced a sequential mixed-methods methodology to accomplish its objectives. The primary goal of this study was to ascertain the impact of global warming, education, and renewable energy on healthcare expenditure. In order to determine the impact of renewable energy on health care expenditure, the present research study coupled renewable energy with gross domestic product (GDP). Based on the long-term outcomes derived from our Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) estimators, GDP, renewable energy, and education were found to be adversely correlated with healthcare expenditure. To collect data, we conducted interview sessions, which were subsequently complemented by a survey that was completed by 400 respondents (specifically chosen research participants). We then conducted thematic analyses. The findings of this study underscore a compelling inverse relationship linking GDP, renewable energy integration, and education with healthcare spending. Regions displaying lower healthcare outlays are seemingly less strained ecologically due to their judicious utilization of renewable energy sources. Furthermore, based on our findings, a noteworthy correlation between healthcare expenditure and global warming was observed, underscoring the potential escalation of financial burdens with intensifying climate shifts. In light of our findings, advocating for the amplification of renewable energy deployment emerges as a prudent strategy to fortify public health while mitigating healthcare expenses. Augmenting investments in education acts as a pivotal lever to steer sustainable growth. It is noteworthy that the survey participants’ level of familiarity with renewable energy technology was not found to be connected to their educational backgrounds, revealing a disparity in knowledge. The prevailing unfamiliarity with sustainability principles among the respondents underscores the need for widespread awareness initiatives. This study acts as a holistic exploration of the ramifications of renewable energy on healthcare expenditure; this is intertwined with the complex tapestry of global warming and education. The implications of renewable energy reverberate across policy and practice, accentuating the urgency of sustainable energy adoption for the betterment of public health and economic resilience. Future studies should focus on conducting more nuanced assessments of socio-economic aspects and generate strategies for bridging knowledge gaps among diverse stakeholders.

Abstract. Design and verification of control strategies for floating wind turbines often makes use of aero-hydro-servo-elastic modeling tools. Aerodynamic loads calculation in these tools has been recently validated against experiments not including active wind turbine control. This work investigates the aerodynamic response of a floating wind turbine scale model with active control and platform pitch motion. This is done in wind tunnel testing and with modeling of the scaled system in the offshore tool OpenFAST. A control design framework is developed to include the reference wind turbine controller ROSCO in the wind tunnel experiment. With platform pitch motion, the turbine aerodynamic response is predicted by the numerical model with different accuracy depending on the turbine control regime. Below rated wind, oscillations of aerodynamic torque in simulations are of lower amplitude than in the experiment, also when dynamic inflow is considered in the aerodynamic model. Above rated wind, where the turbine is controlled with collective blade pitch actuation, the response is not quasi-steady, and differences between the experiment and simulation are larger than in below-rated wind, in particular for phase with respect to motion.

This dataset contains all the data and processing needed to produce results and figures reported in the manuscript "Rethinking energy planning to mitigate environmental and climatic impacts of future African hydropower". The README file guides through the material available to support replication of the results and figures.

This paper analyzes the autogenous self-healing capacity of early-age Ultra-High-Performance Fiber-Reinforced concretes (UHPFRCs) by measuring the crack closure and the possible mechanical recovery on healed specimens. The main parameters considered in this research were the healing exposure conditions (humidity chamber, immersion in tap water, immersion in seawater and heat curing) and the precracking levels (microcracks and macrocracks). For the microcrack level, four-point bending tests were performed on prismatic specimens (100 × 100 × 500 mm3) obtaining a multiple cracking pattern characterized by crack widths ranged from 10 to 20 µm. Whereas for the macrocrack level (behavior after crack localization), splitting tests were carried out on notched cubic specimens (100 × 100 × 100 mm3) obtaining crack widths of up to 0.4 mm. For both precracking levels, specimens were precracked at two days and were cured for one month in the mentioned exposure conditions. Healing products were analyzed on the specimen surface and also inside the cracks; to this purpose, their microstructure was analyzed by means of SEM and EDS analyses. The results have shown that the highest crack closure values were obtained for the heat-cured specimens and for the specimens immersed in water (tap water and seawater) whereas the less efficient condition was the humidity chamber.

The purpose of this study is to determine the safety effectiveness of an intervention on an existing road by using predictive methods. Predictive methods allow the benefit of the intervention to be quantified in terms of crash reduction. Currently, the most widely used model is reported in the Highway Safety Manual, developed in the US. The HSM model is adapted to the Italian context through a calibration procedure. The model is then applied to two future scenarios: in the absence and presence of intervention. The redesign intervention consists of rehabilitating some road sections and constructing five tunnel bypasses to avoid crossing residential areas. The comparison between the ‘with’ and ‘without’ scenario estimated an overall reduction in the number of accidents of around 45%. The variant scenario is based on reasonable assumptions that allowed the determination of the proportion of traffic that will be diverted to the variant. In addition, several alternative future scenarios are considered to assess a possible different trend in assumed traffic distribution. Moreover, a possible overall increase or reduction in total traffic affecting the road is taken into account. The results showed that the intervention provided significant benefits even with increased traffic, proving the resilience of the intervention.

The debate on public real estate enhancement is prominent and requires innovative strategies to assure economic and social sustainability. This article aims at systematizing the currently available methods and tools of public property enhancement in Italy, proposing a system of criteria to support the public administration (PA) in the decision-making process when managing public real estate enhancement oriented towards public utility. Namely, this article considers and assesses consolidated and innovative public real estate enhancement methods and tools currently available to the Italian PA according to the “endogenous criteria” of the real estate tools and “criteria of purpose” of the public administration promoting the enhancement process. The final aim is to support the decision-making process of PAs and help both public and private actors in grasping and managing the complexity of public real estate enhancement. An overview of the literature and of reference laws on public property enhancement builds the research framework, together with a path of research, dialogues, and fieldworks with the Italian State Property Agency (Agenzia del Demanio). The decision-making process of PAs for selecting a suitable enhancement strategy or tool should rest on endogenous criteria and criteria of purpose. Specifically: (i) the distinct technical features of each public asset; (ii) the public utility aim that the public entity intends to pursue; (iii) the needs of the community (i.e., the demand); (iv) the skills available within the PA that promotes the strategy.