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• A waste heat recovery for an offshore oil platform was analyzed. • The heat recovery device is the most irreversible in the organic Rankine cycle. • The organic Rankine cycle contributes to electricity generation up to 20.3%. • The organic Rankine cycle contributes to increase up to 11% in overall efficiency. • A net present value of up to USD 16.84 million is possible with the proposed change. The organic Rankine cycle has been widely explored for energy recovery from several heat sources. In this paper, the maximization of the energy recovery of the exhaust gases from the General Electric LM 2500 gas turbines in a floating production offloading unit is studied in order to meet the demands of heat (pressurized hot water) and electricity over oil production lifetime. An off-design model of the system is developed to check the viability of an organic Rankine cycle under dynamic operating conditions. Energy and exergy analysis of the proposed system are conducted to determine main irreversibilities and performance characteristics of the system and, finally, the economic benefits of the energy recovery system application are discussed. The organic Rankine cycle is very flexible in the heat recovery in dynamic demand conditions, contributing up to 20.3% in electricity generation, which causes an increase in overall system efficiency of up to 11.3% and up to 18.3% in the utilization factor, as well as an average reduction of 22.0% in carbon dioxide emissions in the floating production offloading unit electricity generation process. The exergy efficiency of the system reaches 55.8% and the heat recovery devices are the most irreversible equipment in organic Rankine cycle, contributing up to 68% of the total exergy destroyed. The economic analysis demonstrated the attractiveness of the organic Rankine cycle implementation, allowing a net present value to Brazil's current economic scenario of up to USD 16.8 million. [ABSTRACT FROM AUTHOR]

Leak noise correlators are commonly used to detect and locate leaks in buried water pipes. They use the cross-correlation function between leak noise signals measured using hydrophones or accelerometers placed on the pipe either side of the leak. The efficacy of a correlator is dependent upon knowledge of the speed at which the leak noise propagates along the pipe as well as how much it attenuates with distance. The leak noise is carried in a predominantly fluid-borne wave in the pipe, which is heavily influenced by the pipe and soil properties. Although the pipe properties can be determined relatively easily, estimation of the soil properties surrounding the pipe is more problematic. It is desirable to have an accurate estimate of the soil properties, so that current models can be developed and used to improve understanding of leak noise propagation and hence leak detection capabilities. In this paper a novel approach to determining the bulk and shear moduli of the soil from measurements of the predominantly fluid-borne wave in a buried plastic pipe, is described. The measured data are compared with corresponding data predicted from a model, and the soil properties are determined using an optimization algorithm. The method is applied to two different sites, one in the UK, where the soil properties surrounding the pipe are representative of sandy soil, and one in Brazil, where the surrounding soil has properties that are representative of clay soil. It is found that the bulk and shear modulus can be estimated in the pipe buried in sandy soil, but in the clay soil it is only possible to estimate the shear modulus. • A new approach to determine the bulk and shear moduli of the soil is described. • The approach is based on measurements of the predominantly fluid-borne wave (s=1) in a buried plastic pipe. • Two experimental test sites with different geometry and properties are used to demonstrate the efficacy of the method. • In sandy and clay soil, the soil shear modulus can affect the speed of s=1 wave in the pipe. • The attenuation of s=1 wave is affected by the soil bulk modulus in sandy soil, and shear modulus in clay soil. [ABSTRACT FROM AUTHOR]

Abstract: Many works have shown the potential of the Brazilian sugarcane industry as an electricity supplier. However, few studies have studied how this potential could be achieved without jeopardizing the production of sugar and ethanol. Also, the impact of modifications in the cogeneration plant on the costs of production of sugar and ethanol has not been evaluated. This paper presents an approach to the problem of exergy optimization of cogeneration systems in sugarcane mills. A general model to the sugar and ethanol production processes is developed based on data supplied by a real plant, and an exergy analysis is performed. A discussion is made about the variables that most affect the performance of the processes. Then, a procedure is presented to evaluate modifications in the cogeneration system and in the process, and their impact on the production costs of sugar, ethanol and electricity. Furthermore, a discussion on the renewability of processes is made based on an exergy index of renewability. As a general conclusion, besides adding a new revenue to the mill, the generation of excess electricity improves the exergo-environmental performance of the mill as a whole. [Copyright &y& Elsevier]

Abstract: Broad-scale correlations between species richness and human population suggest that processes driving species richness, mainly related to high ecological productivity, may also drive human populations. However, it is still under debate if this coincidence implies conflicts between biodiversity conservation and human development. In this paper, we analyzed the relationships among human population size, species richness and irreplaceability in Brazilian Cerrado. We analyzed a dataset with 131 species of anurans distributed in 181 cells with 1° of spatial resolution covering the biome. We found a positive correlation between human population size and anuran species richness (r =0.46; P =0.033 with 19.5 geographically effective degrees of freedom, v*), but the irreplaceability of each cell was poorly correlated with human population size (r =0.075; P =0.323; v*=173.9). The 17 cells in the 97 optimal reserve networks contained a total human population ranging from 2942,195 to 4319,845 people, representing on average 11.8% of the human population in the entire Cerrado grid. The comparison of these observed values with 10,000 values from randomly generated networks suggests a relatively high flexibility in optimal complementarity sets for reserve selection. Our results indicated that correlation between richness and human population does not necessarily result in conflicts, given the opportunities for conciliating conservation and development. However, the analyses performed here are initial explorations within the framework of conservation biogeography, so more detailed studies are necessary to establish conservation planning at regional and local scales. [Copyright &y& Elsevier]

Low salinity water injection (LSWI) has been studied by several researchers as an enhanced oil recovery (EOR) method in laboratory experiments, numerical simulations, and field applications. However, its effects on oil recovery remain uncertain due to the complexity of the interactions among crude oil, brine, and the rock surface, for both sandstone and carbonate reservoirs, particularly when they contain a diversity of clay minerals. This paper investigates LSWI performance and mechanisms in sandstone rock, brine, and light crude oil with low polar compounds from a reservoir in Brazil. Core flooding experiments and reservoir simulations were carried out to understand the influence of key parameters on oil recovery. Zeta potential measurements were performed to investigate the influence of the formation water and NaCl and CaCl 2 brine solutions on rock and oil surface charges. Increased oil recovery, Ca++ desorption from the rock surface, and a substantial pH increase in the effluent were noticed during LSWI. Based on the zeta potential measurement, a thicker water film was also formed on the rock and oil surface with brine dilution. A recovery factor of 64% was reached by testing LSWI from the beginning of the waterflooding (secondary mode) and this was the highest recovery of all the scenarios evaluated. Ten parameters were successfully history matched to core flood data, and optimization and sensitivity analysis showed that the concentration of Na+ and Ca++, and the water injection rate were the most important parameters in the LSWI process. Overall, this study sheds light on the LSWI mechanisms for the Brazilian oil field investigated and provides useful operational parameters for designing and achieving better LSWI performance. [Display omitted] • Core flooding performed with samples from an oil field in northeastern Brazil. • Higher oil recovery the earlier the diluted SFW cycling is applied. • Development of core flooding model with laboratory data for similar reservoirs. • Optimization and uncertainty assessment of critical operational parameters. [ABSTRACT FROM AUTHOR]

• General framework for the optimal net present value of smart appliance investment. • A Tree Algorithm with Interior Point speedup the framework in days. • Forty important economic cities in Brazil taken as case studies using real data. • Payback and return on investment measures are not enough for economic analysis. • Full set of results available online. Smart homes allow optimized energy usage, allowing households to reduce electricity bills or even make profits. By 2020, 20% of all households in Europe will be expected to become smart homes. Although smart homes seem to be the future for homes, many customers have the perception that a transition from current homes to smart ones is unprofitable. Adopting a smart home concept requires investments for which the households desire a positive return. A question in this context is the following: for a given household, when and/or what set of home appliances/technologies should be acquired so that the investment made by householder has a positive financial return? The available tool to answer that question can be time-consuming from a practical perspective. Based on our previous work, this paper proposes a framework to help the transition from current houses to smart homes considering customized electricity usage and economic measures. A tree algorithm is developed to decrease the time needed by an economic analysis of each possible acquisition combination of smart appliances or equipment for a given user. The proposed framework is tested on 40 cases covering all Brazilian capital cities, whose results are available online and may be used directly as an approximation for economic analyses. An example of one case is described in detail. Results show that the proposed tree algorithm is able to reduce days of CPU time to solve the problem and Net Present Value should be used as an economic measure to answer the aforementioned question. [ABSTRACT FROM AUTHOR]

After the 2010 to 2015 crisis in Brazil's sugarcane sector, mainly caused by government mandated fuel price ceilings, the sector has entered a new growth cycle spurred by implementation of the " RenovaBio " program in 2017. The government created RenovaBio to achieve two overarching goals: increase 2028 ethanol output by roughly 53% and incrementally increase this biofuel's share in the national energy matrix to meet GHG reduction targets established at the Paris Climate Conference - COP21. The study presented in this paper addresses the expansion of mill output to meet expected future demand by 2028 through application of a mixed-integer linear optimization model to (1) determine the amount of additional sugarcane production and mill processing capacity required to meet expected 2028 Brazilian ethanol and sugar demand and (2) optimize the location of this additional capacity to minimize production and transportation costs through the multimodal transportation network. Modeling results estimate that 151,106 t of additional sugarcane processing capacity is needed to meet forecast 2028 Brazilian demand for 41,106 m³ of sugarcane ethanol and 49,106 t of sugar. Expanded mill output will require that sugarcane cultivation increase over an additional 6% of the area defined by Brazilian Sugarcane Agroecological Zoning regulations as suitable for sugarcane cultivation. Following the model's recommended optimal spatial distribution of 2028 mill processing capacity, their output can be produced and transported at a total cost of US$ 458.65/m³ of ethanol and US$ 304.27/t of sugar, slightly below 2016 minimum total costs. • Optimal location of sugarcane crushing capacity in Brazil to meet estimated 2028 demand for ethanol and sugar. • MILP model applied to investigate the best locations for greenfield sugarcane mills. • Spatial optimization of sugar and ethanol supply and interregional freight flows through the multimodal network in Brazil. [ABSTRACT FROM AUTHOR]

Forest systems represent an important source of biomass for biorefineries. However, very complex dynamics impose difficulties in its efficient design. The present work proposes an optimization framework for biorefineries design that considers these dynamics. Four interconnected decision layers were considered: biomass supply, conversion processes, storage, and markets. The model is formulated as a MILP for maximizing the operational Net Present Value. An illustrative case-study was presented for lignin extraction in eucalyptus Kraft Pulp mills in Brazil. Land availability, forest productivity, and interest rates were fundamental for the location and sizing of production facilities. Logistics networks prioritized the minimization of sales taxes over transportation distance. The precipitation technology has become financially attractive in a scenario with a 50% lignin price increase. The optimal technology location was Sao Paulo due to lower opportunities costs and markets' vicinity. These outcomes highlight the importance of the whole supply chain evaluation in biorefinery design. Image, graphical abstract [ABSTRACT FROM AUTHOR]