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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.

Abstract Dimethyl ether appears to be a better choice among various diesel alternatives due to its high cetane number and sootless combustion. However, the physical and chemical properties of dimethyl ether are very different from those of diesel. The physical properties influence spray formation and atomization characteristics, while chemical properties determine combustion and emission formation characteristics. Thus, fuel's physical and chemical properties significantly determine engine performance and emissions. In the present work, spray combustion and emission formation characteristics of n-heptane, dimethyl ether, and their blends (10, 25, and 50% dimethyl ether in n-heptane) were numerically studied in a constant volume chamber. Results show that the n-heptane spray combustion has the highest heat release rate with an intense premix combustion phase, whereas dimethyl ether spray combustion has the lowest heat release rate and shortest premix combustion phase. The magnitude of the premixed phase and heat release rate decreases with the increase in dimethyl ether mass fraction in the blends. Soot, carbon monoxide (CO), unburned hydrocarbon (UHC), and nitric oxide (NO) emissions decreased with the increase in the dimethyl ether mass fraction in the blends and were lowest for the dimethyl ether.

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.

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.

In this study, levulinic acid (LA) was produced from rice straw biomass in co-solvent biphasic reactor system consisting of hydrochloric acid and dichloromethane organic solvent. The modified protocol achieved a 15% wt LA yield through the synergistic effect of acid and acidic products (auto-catalysis) and the designed system allowed facile recovery of LA to the organic phase. Further purification of the resulting extractant was achieved through traditional column chromatography, which yielded a high purity LA product while recovering ∼85% wt. Upon charcoal treatment of the resultant fraction generated an industrial grade target molecule of ∼99% purity with ∼95% wt recovery. The system allows the solvent to be easily recovered, in excess of 90%, which was shown to be able to be recycled up to 5 runs without significant loss of final product concentrations. Overall, this system points to a method to significantly reduce manufacturing cost during large-scale LA preparation.

Abstract Pollution control strategies currently in use by electric power systems are reviewed and a new minimum emission dispatch (MED) method is developed. This new method minimizes overall emission levels at an increased cost in large-scale power systems while simultaneously accommodating local pollution level requirements, as well as economic constraints.

Given the considerable scale of distribution networks in urban and rural areas, as well as the lack of management records, adjustments of switches during the distribution system operation are poorly documented. Such deficiency results in the inaccuracy of models stored in the distribution network automation system, and thus misleads the state estimation. With the emergence of information and communication technology, a large number of the feeder and residential smart meter data are accumulated. Such data can help recognize the operation modes of distribution networks by analyzing the relationships between the on/off states of switches and the voltage correlations among buses. However, the limited quantity and quality of the sampling data restrict the implementation of data-driven recognition. In this paper, a physical-probabilistic-network (PPN) model applied for inferring overall operation mode of distribution networks is proposed. Based on which, a belief propagation-based algorithm is proposed for the inference even under situations when there are only partial bus voltages data available. Meanwhile, the required variable for inference can be reduced from the active trail analysis. Experiment results are used to compare its performance with classic methods and to prove its effectiveness and advantages.

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.