Life-Cycle Cost of Bridges on Seismic Zones for Risk Management

In this paper the acceptable failure probability and the risk of important bridges, located on seismic zones, are calculated throughout the expected cost of failure consequences. Also, the bridge expected life-cycle cost is formulated in terms of the bridge seismic hazard and the potential consequences of failure. These consequences include aspects arising from the physical loss of the bridge to the human casualties and economical cost of the loss of service, which are estimated in monetary terms. Current codes do not explicitly deal with this issue and in practice subjective estimations from experience are considered for some general cases. Bridge reliability is an essential component of risk and in this paper is estimated in a simplified way and applied to the structural types given in the examples. Monte Carlo simulation techniques are used to explicitly account for the uncertainties. Initial and failure cost curves are determined for all possible seismic intensities and expected life-cycle costs conditional to these intensities are obtained. The unconditional expected lifecycle cost is calculated by convolution of the conditional costs by the occurrence probabilities of these intensities, which are obtained from the seismic hazard curve of the given site. The procedure is illustrated throughout three reinforced concrete bridges located 1 on the soft soil of Mexico City and the other two on other sites with less seismic activity and different traffic volumes. The results may be extended to get risk management policies for bridges and to improve the current Mexican codes and to enhance the practices on bridge design and maintenance on seismic zones

Peanut Shell for Energy: Properties and Its Potential to Respect the Environment

The peanut (Arachys hypogaea) is a plant of the Fabaceae family (legumes), as are chickpeas, lentils, beans, and peas. It is originally from South America and is used mainly for culinary purposes, in confectionery products, or as a nut as well as for the production of biscuits, breads, sweets, cereals, and salads. Also, due to its high percentage of fat, peanuts are used for industrialized products such as oils, flours, inks, creams, lipsticks, etc. According to the Food and Agriculture Organization (FAO) statistical yearbook in 2016, the production of peanuts was 43,982,066 t, produced in 27,660,802 hectares. Peanuts are grown mainly in Asia, with a global production rate of 65.3%, followed by Africa with 26.2%, the Americas with 8.4%, and Oceania with 0.1%. The peanut industry is one of the main generators of agroindustrial waste (shells). This residual biomass (25–30% of the total weight) has a high energy content that is worth exploring. The main objectives of this study are, firstly, to evaluate the energy parameters of peanut shells as a possible solid biofuel applied as an energy source in residential and industrial heating installations. Secondly, different models are analysed to estimate the higher heating value (HHV) for biomass proposed by different scientists and to determine which most accurately fits the determination of this value for peanut shells. Thirdly, we evaluate the reduction in global CO2 emissions that would result from the use of peanut shells as biofuel. The obtained HHV of peanut shells (18.547 MJ/kg) is higher than other biomass sources evaluated, such as olive stones (17.884 MJ/kg) or almond shells (18.200 MJ/kg), and similar to other sources of biomass used at present for home and industrial heating applications. Different prediction models of the HHV value proposed by scientists for different types of biomass have been analysed and the one that best fits the calculation for the peanut shell has been determined. The CO2 reduction that would result from the use of peanut shells as an energy source has been evaluated in all production countries, obtaining values above 0.5 ‰ of their total emissions

Wind Power Cogeneration to Reduce Peak Electricity Demand in Mexican States Along the Gulf of Mexico

The Energetic Transition Law in Mexico has established that in the next years, the country has to produce at least 35% of its energy from clean sources in 2024. Based on this, a proposal in this study is the cogeneration between the principal thermal power plants along the Mexican states of the Gulf of Mexico with modeled wind farms near to these thermal plants with the objective to reduce peak electricity demand. These microscale models were done with hourly MERRA-2 data that included wind speed, wind direction, temperature, and atmospheric pressure with records from 1980–2018 and taking into account roughness, orography, and climatology of the site. Wind speed daily profile for each model was compared to electricity demand trajectory, and it was seen that wind speed has a peak at the same time. The amount of power delivered to the electric grid with this cogeneration in Rio Bravo and Altamira (Northeast region) is 2657.02 MW and for Tuxpan and Dos Bocas from the Eastern region is 3196.18 MW. This implies a reduction at the peak demand. In the Northeast region, the power demand at the peak is 8000 MW, and for Eastern region 7200 MW. If wind farms and thermal power plants work at the same time in Northeast and Eastern regions, the amount of power delivered by other sources of energy at this moment will be 5342.98 MW and 4003.82 MW, respectively

Information Sharing in Major Events

This thesis argues that information sharing is crucial for creating and maintaining shared situational awareness in the context of routine operation and incident management at major events. Information sharing and situational awareness are needed for controlling and coordinating individuals from the police, fire, rescue, voluntary groups, organisers and the public, who were typically linked together in this naturalistic context. The research thus focuses on investigating how information sharing influences situational awareness, what motivates information sharing and what tools are used to mediate and control information sharing. Activity theory is utilised as a conceptual framework and as an analytical tool to portray the motivated activity of information sharing. This activity is directed at creating and maintaining shared situational awareness. Recognising this multi-voiced context, the research was founded upon a qualitative and interpretive paradigm. Review of organisational documentation, observation of current practices and interviews were employed to collect information for concerts and baseball matches in Mexico. Data collected were transcribed verbatim and an open, axial and selective coding approach was used to analyse the data. Themes and activity elements were recognised and utilised to uncover links in the light of contextual features to make sense of relationships between them. From those relationships, surface credibility and normative altruism as motivations and situational awareness as an abstract tool are proposed as contributions to knowledge. In addition, the Situational Awareness Modes in Incident Management (SAMIM) model is proposed to frame and exhibit the necessity for individuals to be aware of diverse situations in context. Moreover, the findings have practical implications concerning the development of adequate protocols for managing incidents; improvement of abstract and material tools; and training to tune the coordination and control of individuals serving as incident responders, including the public. This can be done through practice exercises in routine operation and simulated incident management at major events

GIS-Based Wind and Solar Power Assessment in Central Mexico

In Mexico, the economic and industrial development is in the center and north; this represents more than 50% of the country’s total consumption. Data on population and energy consumption will be obtained from the following sources: the National Institute of Geography and Statistics (INEGI), and the Energy Information System. Regarding meteorological data, two databases are used: the Automatic Weather Stations (AWS) (for solar irradiance data) and the MERRA-2 reanalysis data (for wind data). These data will be analyzed for use in a geographic information system (GIS) using kriging interpolation to create maps of solar and wind energy. The area studied includes the following states: Mexico City, Puebla, State of Mexico, Hidalgo, Morelos, Zacatecas, Queretaro, San Luis Potosi, Guanajuato, Aguascalientes and Tlaxcala. The results showed that the areas with the highest solar potential are Hidalgo, Estado de México, Morelos, northern Puebla, southern Queretaro, northwestern Guanajuato, and northern Zacatecas, with 5.89 kWh/m2/day, and the months with the highest solar potential are March, April, May, and June. Regarding wind potential, the maximum wind power density is in Puebla, with 517 W/m2, and the windy season in central Mexico spans June, July, August, September, October, and November

Latin American Production on Gender Violence on Scopus, 2010 -2019

The study describes the characteristics of publications on gender violence written by authors affiliated with Latin American institutions, in journals indexed to Scopus during the period 2010-2019. A descriptive and retrospective analysis of 2,568 articles is carried out. Latin American scientific production represents 5.3% of world production. Brazil is the country with the highest production, followed by Mexico and Chile. Latin American scientific production has been published in 572 journals. Ciencia e Saude Coletiva (Brazil) is the journal with the largest number of publications, followed by Cadernos de Saude Publica (Brazil) and Journal of Interpersonal Violence (United States). besides, the authors are mainly affiliated with the Universidade de Sao Paulo - USP, followed by the Fundacao Oswaldo Cruz Universidade Federal do Rio Grande do Sul. Finally, the keywords, domestic violence, intimate partner violence and gender violence present an increasing trend of studies since 2016. Therefore, it is necessary to strengthen and stimulate the generation and dissemination of scientific studies by Latin American researchers

Worldwide Research Trends on Optimizing Wind Turbine Efficiency

In a world in which electricity is increasingly necessary, it is vitally important to ensure that the supply of this electricity is safe, reliable, sustainable, and environmentally friendly, reducing CO2 emissions into the atmosphere and the use of fossil fuels. Renewable energies, and wind energy, in particular, make a significant contribution to this. Wind energy research dates to the last century, yet efforts to improve wind turbine performance continue around the world. Advances in blade aerodynamics and wind resource assessment are outstanding [...

Spatio-temporal changes in structure for a mediterranean urban forest: Santiago, Chile 2002 to 2014

There is little information on how urban forest ecosystems in South America and Mediterranean climates change across both space and time. This study statistically and spatially analyzed the spatio-temporal dynamics of Santiago, Chile's urban forest using tree and plot-level data from permanent plots from 2002 to 2014. We found mortality, ingrowth, and tree cover remained stable over the analysis period and similar patterns were observed for basal area (BA) and biomass. However, tree cover increased, and was greater in the highest socioeconomic stratum neighborhoods while it dropped in the medium and low strata. Growth rates for the five most common tree species averaged from 0.12 to 0.36 cm· year-1. Spatially, tree biomass and BA were greater in the affluent, northeastern sections of the city and in southwest peri-urban areas. Conversely, less affluent central, northwest, and southern areas showed temporal losses in BA and biomass. Overall, we found that Santiago's urban forest follows similar patterns as in other parts of the world; affluent areas tend to have more and better managed urban forests than poorer areas, and changes are primarily influenced by social and ecological drivers. Nonetheless, care is warranted when comparing urban forest structural metrics measured with similar sampling-monitoring approaches across ecologically disparate regions and biomes. © 2016 by the authors

Optimal location and sizing of PV sources in DC networks for minimizing greenhouse emissions in diesel generators

This paper addresses the problem of the optimal location and sizing of photovoltaic (PV) sources in direct current (DC) electrical networks considering time-varying load and renewable generation curves. To represent this problem, a mixed-integer nonlinear programming (MINLP) model is developed. The main idea of including PV sources in the DC grid is minimizing the total greenhouse emissions produced by diesel generators in isolated areas. An artificial neural network is employed for short-term forecasting to deal with uncertainties in the PV power generation. The general algebraic modeling system (GAMS) package is employed to solve the MINLP model by using the CONOPT solver that works with mixed and integer variables. Numerical results demonstrate important reductions of harmful gas emissions to the atmosphere when PV sources are optimally integrated (size and location) to the DC grid