Household-electric equipment diffusion and the impacts in the demand of residential electric energy in Brazil

The sizing and the distribution of the circuits, equipments of illumination and wall sockets of a household building are planned to offer a certain comfort to the users. The comfort is associated to a psychological state of welfare and depends on an ample amount of factors. The residences consume about 26% of the total electric energy in Sao Paulo state and the tasks aimed to the optimization of the energy use must consider the household use. Currently, the Brazilian market of electric energy grows to a tax of 4.5% per year and during the last decades, the consumption of electrical energy presented superior tables of expansion to the gross domestic product (GDP). This growth showed up larger the household, commercial and agricultural consumers. The standards of comfort and performance change as the time goes by, with the incorporation of new technologies. The number of household appliances has been increased by the years, as well as the use of new equipments, demanding alterations in the electric projects to attend to this comfort of use.     

Mechanical and tribological properties of self-lubricating metal matrix nanocomposites reinforced by carbon nanotubes (CNTs) and graphene – A review

Rapid innovation in nanotechnology in recent years enabled development of advanced metal matrix nanocomposites for structural engineering and functional devices. Carbonous materials, such as graphite, carbon nanotubes (CNT's), and graphene possess unique electrical, mechanical, and thermal properties. Owe to their lubricious nature, these carbonous materials have attracted researchers to synthesize lightweight self-lubricating metal matrix nanocomposites with superior mechanical and tribological properties for several applications in automotive and aerospace industries. This review focuses on the recent development in mechanical and tribological behavior of self-lubricating metallic nanocomposites reinforced by carbonous nanomaterials such as CNT and graphene. The review includes development of self-lubricating nanocomposites, related issues in their processing, their characterization, and investigation of their tribological behavior. The results reveal that adding CNT and graphene to metals decreases both coefficient of friction and wear rate as well as increases the tensile strength. The mechanisms involved for the improved mechanical and tribological behavior is discussed.     

Optimization and analysis of an integrated energy system based on wind power utilization and on-site hydrogen refueling station

An integrated energy system coupled with wind turbines and an on-site hydrogen refueling station is proposed to simulate the future scenario, which can meet the demands of cooling, heating, power and hydrogen. The system was modeled to calculate the capacity and annual operation of each equipment with the total annual cost as the optimization objective. This study evaluates the performance of the system based on the results. When the system is configured with 0–10 wind turbines, the economics, energy consumption and carbon emissions improve as the scale of wind turbines increases. Energy utilization and wind power utilization are above 66.79% and 99.73%, respectively. The on-off coefficient of the power generation unit can affect energy efficiency. When the system contains 5 turbines, 91% of the hydrogen can be self-produced with the minimum amount of energy redundancy.     

考虑多腐蚀缺陷作用效应的海底管道失效压力分析

目的研究多种腐蚀缺陷及多腐蚀缺陷间相互作用对管道失效的影响,提出考虑多腐蚀缺陷作用效应的管道失效压力计算方法。方法基于腐蚀缺陷压力管道全尺寸压力爆破试验数据,采用有限元方法分析含不同尺寸多腐蚀缺陷的管道失效压力,提出重叠腐蚀缺陷相互作用系数概念,并将其应用到重叠腐蚀缺陷管道失效压力的计算中。结果腐蚀缺陷间不同的轴向间距及环向间距均对多腐蚀缺陷相互作用有显著影响,从而影响管道失效压力。多腐蚀缺陷间相互作用存在临界范围,且不同腐蚀缺陷尺寸对其相互作用临界值影响不同。当管道存在"十"字形重叠腐蚀缺陷时,失效压力明显降低。重叠腐蚀缺陷顶层缺陷的几何尺寸是决定失效压力变化趋势的主要原因,即随着顶层腐蚀缺陷轴向长度及深度的增加,失效压力出现大幅降低;而随着顶层缺陷宽度的增加,失效压力下降趋势缓慢。结论腐蚀缺陷几何尺寸是影响管道失效压力及腐蚀缺陷间相互作用的重要因素,结合腐蚀缺陷间相互作用系数能够有效进行多腐蚀缺陷管道的失效压力分析计算。     

Population evolution analysis in collective intelligence design ecosystem

The Collective Intelligent Design Ecosystem is a dynamic ecosystem founded on an online design platform that leverages collective intelligence to support the creation of novel products. The system's primary components are its users and designers. Maintaining the system's sustainability requires expanding the scale of the designer and user populations as it evolves to stabilize. However, the unity of ecological interactions between various populations is fragmented in contemporary studies of population-scale evolution, and the parameterization of evolutionary models is illogical. To overcome this gap, this research provides a population evolution model of collective intelligent design incorporating participants' intra- and interspecific ecological connections. The model's validity is verified by the evolutionary simulation of 110 designers and 5990 users of China's largest collective intelligence design platform, the Zhubajie platform, and illuminating conclusions are in turn drawn from this simulation. First, the designer's influence on the user is greater than the user's impact on the designer. Second, keeping current members engaged is more crucial to the system's viability than luring in new ones. Third, fostering collaboration among designers while retaining user competitiveness can promote system growth. Fourth, decreasing the reliance between particular designers and users might hasten the system's evolution.     

Efficient resource prediction framework for software-defined heterogeneous radio environmental infrastructures

Artificial Intelligence (AI) is defining the future of next-generation infrastructures as proactive and data-driven systems. AI-empowered radio systems are replacing the existing command and control radio networks due to their intelligence and capabilities to adapt to the radio environmental infrastructures that include intelligent networks, smart cities and AV/VR enabled factory premises or localities. An efficient resource prediction framework (ERPF) is proposed to provide proactive knowledge about the availability of radio resources in such software-defined heterogeneous radio environmental infrastructures (SD-HREIs). That prior information enables the coexistence of radio users in SD-HREIs. In a proposed framework, the radio activity is measured in both the unlicensed bands that include 2.4 and 5 GHz, respectively. The clustering algorithms k- means and DBSCAN are implemented to segregate the already measured radioactivity as signal (radio occupancy) and noise (radio opportunity). Machine learning techniques CNN and LRN are then trained and tested using the segregated data to predict the radio occupancy and radio opportunity in SD-HREIs. Finally, the performance of CNN and LRN is validated using the cross-validation metrics.     

The effect of bolt length in the fatigue strength of M24×3 bolt studs

In this study we evaluated the effect of bolt length on the fatigue behavior of joints with bolt studs used in the flange/housing assembly of a gas compressor for polyethylene polymerization. The bolt stud used is the M24×3 class 8.8. Two different bolt lengths were evaluated. A slim spread sleeve was used in the case of the longer bolts. The torque control was used to achieve the tightening preload. However, the preload and cyclic strains were monitored. The fatigue strength increases with increasing bolt stud length, even with the use of the slim spread sleeve. The study showed a difference between the theoretical and the experimental load factor for the case of short joints.     

Surface plasmon assisted photocatalytic hydrogen generation with Ag decorated g-C3N4 coupled SnO2 nanophotocatalyst under visible-light driven photocatalysis

Photocatalytic hydrogen evolution from water is a feasible technique to solve energy crises and reduce dependance on carbon fuels. As for this, silver nanoparticles were grown on the surface of SnO₂ coupled g-C₃N₄ nanocomposite for the generation of hydrogen gas from water under visible light photocatalysis. The prepared samples were properly characterized to investigate their light absorption characteristics followed by charge generation and separation for water splitting. The optimized nanocomposite produced 270 μmol h⁻¹ g⁻¹ hydrogen which was much superior to pure g-C₃N₄ and SnO₂. These upgraded photocatalytic activities were attached to the extended visible-light absorption due to the presence of Ag nanoparticles characterized by surface plasmon resonance (SPR) and suitable conduction bands position of g-C₃N₄ and SnO₂ for the separation of excited charges. The photoluminescence study, amount of produced hydroxyl free radicals and electrochemical investigation confirmed the long-rooted charge separation capability of the nanocomposites. We believe that this work will have more positive impacts on the synthesis of low cost SPR assisted photocatalysts for energy production and environmental purification.     

High electrochemical stability and low-agglomeration of defective Co3O4 nanoparticles supported on N-doped graphitic carbon nano-spheres for oxygen evolution reaction

The design of hybrid electrocatalysts with abundant active sites and long term stability is crucial for efficient oxygen evolution reaction (OER) application. Cobalt oxide is considered as one of the most promising electrocatalysts to replace noble metal due to its low cost, availability, and electrocatalytic activity towards the oxygen evolution reaction in alkaline media. However, nano-scale cobalt oxide suffers from severe surface self-agglomeration during the OER process, so that leading to poor activity and durability. Herein, ultra-small cobalt oxide nanoparticles are anchored on the surface of nitrogen doped porous 3D graphitic carbon nano-spheres (N-ACS@Co₃O₄) to increase the amount of exposed active site and avoid the self-agglomeration. The obtained electrocatalyst (N-ACS@Co₃O₄) is enriched with abundant oxygen vacancies and exhibits a superior OER activity (Overpotential of 237 mV at 10 mA.cm⁻²) and exceptional stability for at least 30 h in alkaline electrolyte (1 M KOH). The DFT calculations demonstrate that the strong adsorption of Co₃O₄ on N-doped graphene can prevent its agglomeration, and therefore improves the stability of Co₃O₄ nanoparticles during OER process in line with the experimental results.     

Incorporation of BIM-based probabilistic non-structural damage assessment into agent-based post-earthquake evacuation simulation

Earthquakes can cause severe damage to structural and non-structural elements of buildings; consequently, they pose high risks to human lives. To mitigate such risks, attention has been paid to enhancing the indoor environment for increased building safety. Yet little effort has been made to assess a building occupants' evacuation behaviors in response to damage to the indoor environment. This paper addresses this issue with a novel simulation framework that couples human behaviors with changes to the indoor building environment during post-earthquake evacuation. In particular, we present a building information modelling (BIM)-based prototype that simulates seismic damage to the non-structural indoor elements and visualizes its impacts on evacuation using a color-coded heat map. The simulated damage is then used as input to an agent-based model for post-earthquake evacuation. Using a probabilistic method to assess the non-structural elements' damage states, we are able to evaluate the impact of indoor damage on the evacuation process. We performed a trial of our prototype for a hypothetical earthquake in an educational building. The results revealed how the average evacuation time would increase as the earthquake intensity increases (from 38.6 s for the no-damage scenario to 122.9 for the highest-damage scenario). The proposed prototype has the potential to be joined with other tools, such as finite-element-based simulation, to incorporate structural analysis as well. Planners and designers can explicitly use our model's output to analyze the post-earthquake evacuation with the indoor non-structural damage to assess different building design geometries that increase the chances of a suitable evacuation process.