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Abstract The analysis and optimization of flat plate fins of constant thickness and straight base has been conducted for different fin’s shapes. Performance of the fins is quantified through effectiveness and expressed as a function of fin’s shape, width, and area. A linear piecewise function with varying number of evenly spaced sections is used to generate shapes with different number of degrees of freedom, which are classified as constrained- or unconstrained-base depending on the width of the fin at the constant temperature base location. For one- and two-degrees of freedom shapes, a variety of rectangular, triangular, trapezoidal, and rhomboidal geometries are considered and optimized. For more than two-degrees of freedom, more complex resulting shapes are also considered. By adjusting the value of the corresponding shape parameters, the best possible distributions of available area to maximize heat transfer are obtained, which produce significant improvements favored by smaller width and larger area. Unconstrained-base performs better than constrained-base configurations as they allow the distribution of a larger area close to the high-temperature base. Optimal shape of unconstrained-base fins is in general convergent with non-zero wide tip, while, for constrained-base fins, it is divergent in the first linear section from the base and convergent in the remaining ones. For increasing number of degrees of freedom the optimized shapes tend to resemble natural structures while effectiveness increases asymptotically to a limit for constant width and area. Besides determining the optimal configurations, consideration has been made about the optimal regions where a variety of shapes produce virtually the same effectiveness of the absolute maximum, which can be used to design fins with almost maximum performance but having simpler shapes or being functional under possible space restrictions. The dimensionless model and the systematic analysis proposed in this work are not only appropriate to study a wide range of flat plate fins but also can be implemented to analyze and perform optimization over other type of fins and fins configurations.

While a firm knows the carbon price with certainty under a tax, it must form an expectation about future allowance prices to identify its cost-effective abatement investment under a capand-trade program. We illustrate graphically how errors in forming this expectation increase the costs of irreversible pollution abatement investment under cap-and-trade relative to a tax. We describe empirical “cost-effectiveness anomalies” in allowance markets that may be attributed to cap-and-trade's inherent uncertainty. We model investment under simulated US carbon tax and cap-and-trade policies and find that allowance price uncertainty can increase resource costs 20 percent for a given quantity of emission abatement.

© 2020 Elsevier Ltd Free cooling of buildings uses the nocturnal outdoor air as a heat sink via a ventilation process. This could be performed by storing the night coolness for use during the daytime as appropriate. Due to the latent heat capacity, phase change material (PCM) could play anessential role in the effective operation of the free cooling systems by shifting the daytime peak load to the night. However, there is a scarceness on the technology application in hot climates. This paper presents results of a parametric investigation into the application of PCMs as thermal energy storage (TES) to provide sustainable cooling to buildings in hot arid climate by making use of the night-time free cooling. The proposed TES medium comprises an arrangement of metallic modules filled with RT28HC PCM. Numerous geometrical configurations and operational parameters have been assessed. A transient CFD simulation has been employed using ANSYS Fluent software. Validation of the numerical results with experimental data has shown a good agreement. The results have demonstrated that the temperature difference between the PCM and the air, at appropriate air flow rate would have a significant impact on the performance of the system. A free cooling system based on the proposed arrangement has the potential to meet around 42% of a typical building cooling load and has the ability to save up to 67% of building cooling energy load in summer season compared to conventional air-conditioning systems in hot arid climates.

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 The effect of the thermal environment on performance and productivity has been a focus of interest among indoor environmental researchers for nearly a century, but most of that work has been conducted in relative isolation from the cognate disciplines of human performance evaluation. The present review examines thermal environmental effects on cognitive performance research conducted across multiple disciplines. After differentiating performance from productivity, we compare the two dominant conceptual models linking thermal stress to performance; (1) the inverted-U concept and (2) the extended-U relationship. The inverted-U specifies a single optimum temperature (or its corresponding subjective thermal sensation) at which performance is maximised. In contrast, the extended-U model posits a broad central plateau across which there is no discernible thermal effect on cognitive performance. This performance plateau is bounded by regions of progressive performance decrements in more extreme thermal conditions. The contradictions between these opposing conceptual models might derive from various confounding factors at play in their underlying research bases. These include, inter alia, environment-related, task-related, and performer-related factors, as well as their associated two-way and three-way interaction effects. Methodological discrepancies that might also contribute to the divergence of these conceptual models are evaluated, along with the proposed causal mechanisms underlying the two models. The weight of research evidence reviewed in this paper suggests that the extended-U hypothesis fits the relationship between moderate thermal environments and cognitive performance. In contrast to the inverted-U relationship, implemention of the extended-U in indoor climate control implies substantial reductions in building energy demand, since it permits the heating and cooling setpoint deadband to expand across the full width of the thermal comfort zone, or even slightly further during emergencies such as peak demand events on the electricity grid. Use of personal comfort systems can further extend the thermostat setpoint range beyond the comfort zone.

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.

Abstract With promising benefits such as traffic emission reduction, traffic congestion alleviation, and parking problem solving, Electric Vehicle (EV)-sharing systems have attracted large attentions in recent years. Different from other business modes, customers in sharing economy systems are usually price sensitive. Therefore, it is possible to shift the usage of shared EVs through a well-designed Dynamic Pricing Scheme (DPS), with the objective of maximizing the system operator's total profit. In this study, we propose a novel DPS for a large-scale EV-sharing network to address the EV unbalancing issue and satisfy the vehicle-grid-integration (VGI) service based on accurate station-level demand prediction. The proposed DPS is formulated as a complex optimization problem, which includes two Price Adjustment Level (PAL) decision variables for every origin-destination pair of stations. The two PALs are employed to affect the EV-sharing demand and travel time between each station pair, respectively. Physical and operational constraints from both EV demand and VGI service aspects are also included in the proposed model. Two case study are conducted to validate the effectiveness of the proposed method.