Effect of Substrate and Process Parameters on the Gas-Substrate Convective Heat Transfer Coefficient During Cold Spraying

The final quality of cold-sprayed coatings can be significantly influenced by gas-substrate heat exchange, due to the dependence of the deposition efficiency of the particles on the substrate temperature distribution. In this study, the effect of the air temperature and pressure, as process parameters, and surface roughness and thickness, as substrate parameters, on the convective heat transfer coefficient of the impinging air jet was investigated. A low-pressure cold spraying unit was used to generate a compressed air jet that impinged on a flat substrate. A comprehensive mathematical model was developed and coupled with experimental data to estimate the heat transfer coefficient and the surface temperature of the substrate. The effect of the air total temperature and pressure on the heat transfer coefficient was studied. It was found that increasing the total pressure would increase the Nusselt number of the impinging air jet, while total temperature of the air jet had negligible effect on the Nusslet number. It was further found that increasing the roughness of the substrate enhanced the heat exchange between the impinging air jet and the substrate. As a result, higher surface temperatures on the rough substrate were measured. The study of the effect of the substrate thickness on the heat transfer coefficient showed that the Nusselt number that was predicted by the model was independent of the thickness of the substrate. The surface temperature profile, however, decreased in increasing radial distances from the stagnation point of the impinging jet as the thickness of the substrate increased. The results of the current study were aimed to inform on the influence and effect of substrate and process parameters on the gas-substrate heat exchange and the surface temperature of the substrate on the final quality of cold-sprayed coatings.     

A new link function in GLM-based control charts to improve monitoring of two-stage processes with Poisson response

In this paper, a new procedure is developed to monitor a two-stage process with a second stage Poisson quality characteristic. In the proposed method, log and square root link functions are first combined to introduce a new link function that establishes a relationship between the Poisson variable of the second stage and the quality characteristic of the first stage. Then, the standardized residual statistic, which is independent of the quality characteristic in the previous stage and follows approximately standardized normal distribution, is computed based on the proposed link function. Then, Shewhart and exponentially weighted moving average (EWMA) cause-selecting charts are utilized to monitor standardized residuals. Finally, two examples and a case study with a Poisson response variable are investigated, and the performance of the charts is evaluated by using average run length (ARL) criterion in comparison with the best literature method.     

A comparative evaluation of crumb rubber and devulcanized rubber modified binders

One of the most prominent uses of ground tire rubber (GTR) is in rubber-modified asphalt industry. Besides improving performance properties of binders, GTR induces some drawbacks like weak storage stability and inferior low temperature (LT) performance. This study sought to rectify these shortcomings through using devulcanized rubber (DVR) in place of common GTR. Binder performance grading, multiple stress creep and recovery, and storage stability tests were conducted. More resistance against traffic loads at high temperatures was observed as DVR's advantages over GTR, while its weaker LT characteristics and lower storage stability can prevent it from being a viable alternative.     

Functional Process Capability Indices for Circular Profile

Profile is a relation between one response variable and one or more explanatory variables that represent quality of a product or performance of a process. On the other hand, process capability indices are measures to help practitioners in improving the processes to satisfy the customer's expectations. Few researches are done to account for the process capability index in the areas of profile monitoring. All of these researches are focused on process capability index in simple linear profile. In all of these methods, response variables in different levels of explanatory variable are considered, and the relationship in all range of explanatory variable is neglected. In this paper, a functional method is proposed to measure process capability index of circular profiles in all range of explanatory variable. The proposed method follows the traditional definition of process capability indices. The functional method uses reference profile, functional specification limits and functional natural tolerance limits to present a functional form of process capability indices. This functional form results in measuring the process capability in each level of explanatory variable in circular profile as well as a unique value of process capability index for circular profile. The application of the proposed method is illustrated through a real case in automotive industry. Copyright © 2013 John Wiley & Sons, Ltd.     

Sequencing Batch Reactor (SBR) for the removal of Hg2+ and Cd2+ from synthetic petrochemical factory wastewater

Petrochemical factories which manufacture vinyl chloride monomer and poly vinyl chloride (PVC) are among the largest industries which produce wastewater contains mercury and cadmium. The objective of this research is to evaluate the performance of a lab-scale Sequencing Batch Reactor (SBR) to treat a synthetic petrochemical wastewater containing mercury and cadmium. After acclimatization of the system which lasted 60 days, the SBR was introduced to mercury and cadmium in low concentrations which then was increased gradually to 9.03±0.02 mg/L Hg and 15.52±0.02 mg/L Cd until day 110. The SBR performance was assessed by measuring Chemical Oxygen Demand, Total and Volatile Suspended Solids as well as Sludge Volume Index. At maximum concentrations of the heavy metals, the SBR was able to remove 76-90% of Hg(2+) and 96-98% of Cd(2+). The COD removal efficiency and MLVSS (microorganism population) in the SBR was affected by mercury and cadmium concentrations in influent. Different species of microorganisms such as Rhodospirilium-like bacteria, Gomphonema-like algae, and sulfate reducing-like bacteria were identified in the system. While COD removal efficiency and MLVSS concentration declined during addition of heavy metals, the appreciable performance of SBR in removal of Hg(2+) and Cd(2+) implies that the removal in SBR was not only a biological process, but also by the biosorption process of the sludge.     

Developing a Robust Multi-Attribute Decision-Making Framework to Evaluate Performance of Water System Design and Planning under Climate Change

In theory, emergence of robustness concept has pushed decision-makers toward designing alternatives, such as resistant against the potential fluctuations fueled by uncertain surrounding environment. This study promotes an objective-based multi-attributes decision-making framework that takes into account the uncertainties associated with the impacts of the climate change on water resources systems. To capture the uncertainties of climate change, Monte Carlo approach has been used to generate a series of ensembles. These generated ensembles represent the stochastic behavior of the hydro-climatic variables under climate change. This framework represents the inherent uncertainties associated with hydro-climatic simulations. Next, a coupled TOPSIS/Entropy multi-attribute decision-making framework has been formed to prioritize the feasible alternatives using system performance measures. The main objective of this framework is to minimize the risk of deceptive and subjective assessments during decision-making process. Karkheh River basin has been selected as a case study to demonstrate the implication of this framework. Using a set of system performance attributes, the performance of two hydropower systems has been estimated during the baseline period and under the future climate change conditions. According to the conducted frequency analysis, the alternative in which both hydropower projects would go under construction emerged as the robust solution (i.e., there was a 99.9% chance that it outperforms other solutions). The results indicate that the construction of these hydropower systems leads to the increase of Karkheh River basin robustness in the future.

     

Tuning Thermal Transport Through Atomically Thin Ti3C2Tz MXene by Current Annealing in Vacuum

Heat transport across vertical interfaces of heterogeneous 2D materials is usually governed by the weak Van der Waals interactions of the surface‐terminating atoms. Such interactions play a significant role in thermal transport across transition metal carbide and nitride (MXene) atomic layers due to their hydrophilic nature and variations in surface terminations. Here, the metallicity of atomically thin Ti₃C₂T_z MXene, which is also verified by scanning tunneling spectroscopy for the first time, is exploited to develop a self‐heating/self‐sensing platform to carry out direct‐current annealing experiments in high (<10^?8 bar) vacuum, while simultaneously evaluating the interfacial heat transport across a Ti₃C₂T_z/SiO₂ interface. At room temperature, the thermal boundary conductance (TBC) of this interface is found, on average, to increase from 10 to 27 MW m^?2 K^?1 upon current annealing up to the breakdown limit. In situ heating X‐ray diffraction and X‐ray photo‐electron spectroscopy reveal that the TBC values are mainly affected by interlayer and interface spacing due to the removal of absorbents, while the effect of surface termination is negligible. This study provides key insights into understanding energy transport in MXene nanostructures and other 2D material systems.