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To mitigate the temperature increase in urban environments and reduce its impact on energy consumption and the quality of the environment, urban retrofitting technologies have been developed and applied worldwide. High albedo in urban surfaces and additional vegetation are the most efficient strategies to accomplish these goals. The objective of this study is to estimate the weight of these strategies, both individually and integrated, on the cooling potential of two Latin American cities. To do this, 36 low and high urban density scenarios were simulated with the ENVI-Met software. The simulation models were calibrated using air temperature curves which were monitored during the summer periods from 2010 to 2013. A Principal Components Analysis was carried out to establish possible associations between the proposed mitigation strategies and then the weight of anthropogenic heat was evaluated according to the configuration. The results show that the integrated mitigation strategies in urban areas -i. e. increase vegetation and albedo on horizontal surfaces- has a great potential to mitigate urban warming, showing a more significant impact on low-density urban configuration. The contribution of anthropogenic heat mainly produced by motorized transport and air conditioning systems, is a crucial input data for the urban microclimate simulations. Its impact on the urban densification processes may cancel out the benefits derived by the application of the mitigation strategies considered.

Abstract In this paper, the prevention of negative technogenic impact on the environment of oil sludge by using it as a secondary resource is considered. Oil sludge from various objects of oil fields in Kazakhstan (Mangystau region) has been studied. The possibilities of using oil (after its separation from oil sludge by bioremidiation) as a partial substitute for bitumen base in the production of modified bitumen are considered. The main physical and mechanical characteristics of modified bitumen are determined. The results confirm that the modified bitumen prepared with oil sludge and oil separated by bioremiation method meets the requirements for polymer-bitumen binder to Kazakhstan standards and is suitable for the production of modified bitumen in its physico-chemical characteristics.

Accurate predictions of fuel spray behavior and mixture formation in simulations of direct-injection spark-ignition (DISI) engines are fundamental to ensure proper description of all subsequent processes including ignition, combustion, and emissions. In this work, the spray evolution in a single-cylinder optical DISI engine was studied experimentally and numerically with the goal of enabling predictive computational fluid dynamics (CFD) modeling of in-cylinder sprays. The authors explored a wide range of operating conditions characterized by several fuel injection temperatures and engine speeds, using a well-characterized nine-component gasoline surrogate known as PACE-20. The effect of flash boiling and intake crossflow on the spray is discussed, with a focus on evaluating the ability of the spray models to capture highly transient spray behavior. In the experiments, the fuel temperature was varied between 20°C and 80°C, allowing for non-flash- to flash-boiling transition to emerge with enhanced flashing intensity at the highest temperatures. Spray collapse resulted in vapor-rich regions, owing to the locally lower inertia of the fluid. Varying the engine speed from 650 to 1950 rpm promoted increasingly more turbulent in-cylinder crossflow which interacted with the spray during the injection event and resulted in enhanced spray dispersion. The CFD model was able to capture the spray morphology transition at different fuel temperatures and engine speeds adequately. It is shown that the spray breakup model could capture the transitional spray behavior induced by flash boiling atomization and intake flow via proper initialization of the spray cone angle and calibration of the spray models’ constants.

The Houston-Dallas (I-45) corridor is the busiest route among 18 traffic corridors in Texas, USA. The expected population growth and the surge in passenger mobility may result in a significant impact on the regional environment. This study uses a life cycle framework to predict and evaluate the net changes of environmental impact associated with the potential development of a high-speed rail (HSR) System along the I-45 corridor through its life cycle. The environmental impact is estimated in terms of CO2 and greenhouse gas (GHG) emissions per vehicle/passenger-kilometers traveled (V/PKT) using life cycle assessment. The analyses are performed referring to the Ecoinvent 3.4 inventory database through the phases: material extraction and processing, infrastructure construction, vehicle manufacturing, system operation, and end of life. The environmental benefit is evaluated by comparing the potential development of the HSR system with those of the existing transportation systems. The vehicle component, especially operation and maintenance of vehicles, is the primary contributor to the total global warming potential with about 93% of the life cycle GHG emissions. For the infrastructure component, 56.76% of GHG emissions result from the material extraction and processing phase (23.75 kgCO2eq/VKT). Various life cycle emissions of HSR except PM are significantly lower than for passenger cars.

To identify the DC bias state of transformers, a DC bias state identification method of transformer based on wavelet singular entropy is proposed in this paper. The vibration principle of transformers under DC bias has been analyzed. By combining continuous wavelet transform, singular value decomposition, and information entropy, the analysis method of wavelet singular entropy is proposed. The vibration signal of the transformer before and after DC bias is transformed by continuous wavelet transform, and then the wavelet time-frequency diagram is compared and analyzed. Furthermore, the DC bias state of the transformer is identified by wavelet singular entropy of vibration signal. The wavelet singular entropy under different states is in different numerical ranges, and the wavelet singular entropy of vibration signal under DC bias is significantly greater than that under no DC bias. The wavelet singular entropy effectively reflects the DC bias state of transformers. Then the proposed method is applied to a 500 kV transformer and a 220 kV transformer in the China Southern Power Grid. The results show that the proposed method can accurately and effectively identify the DC bias state of transformers.

A Y-type air-cooled structure has been proposed to improve the heat dissipation efficiency and temperature uniformity of battery thermal management systems (BTMSs) by reducing the flow path of air. By combining computational fluid dynamics (CFD) methods, the influence of the depths of the distribution and convergence plenums on the airflow velocity through battery cells was analyzed to improve heat dissipation efficiency. Adjusting the width of the first and ninth cooling channels can change the air velocity of these two channels, thereby improving the temperature uniformity of the BTMS. Further discussion was conducted regarding the influences of inlet and outlet depths. When the inlet width and outlet width were 20 mm, the maximum temperature and maximum temperature difference of the Y-type BTMS were 39.84 °C and 0.066 °C at a discharge rate of 2.5 °C, respectively; these temperatures were 1.537 °C (3.68%) and 0.059 °C (47.2%) lower than those of the T-type model. Meanwhile, the energy consumption of the sample also decreased by 13.1%. The results indicate that the heat dissipation performance of the proposed Y-type BTMS was improved, achieving excellent temperature uniformity, and the energy consumption was also reduced.