Dehalogenation of chlorinated aliphatic contaminants at the surface of zero-valent iron metal (Fe0) is mediated by the thin film of iron (hydr)oxides found on Fe0 under environmental conditions. To evaluate the role this oxide film plays in the reduction of chlorinated methanes, carbon tetrachloride (CCl4) degradation by Fe0 was studied under the influence of various anions, ligands, and initial CCl4 concentrations ([P]o). Over the range of conditions examined in these batch experiments, the reaction kinetics could be characterized by surface-area-normalized rate constants that were pseudo-first order for CCl4 disappearance (kCCl4), and zero order for the appearance of dissolved Fe2+ (kFe2+). The rate of dechlorination exhibits saturation kinetics with respect to [P]o, suggesting that CCl4 is transformed at a limited number of reactive surface sites. Because oxidation of Fe0 by CCl4 is the major corrosion reaction in these systems, kFe2+ also approaches a limiting value at high CCl4 concentrations. The adsorption of borate strongly inhibited reduction of CCl4, but a concomitant addition of chloride partially offset this effect by destabilizing the film. Redox active ligands (catechol and ascorbate), and those that are not redox active (EDTA and acetate), all decreased kCCl4 (and kFe2+). Thus, it appears that the relatively strong complexation of these ligands at the oxide–electrolyte interface blocks the sites where weak interactions with the metal oxide lead to dehalogenation of chlorinated aliphatic compounds. 相似文献
Hydrogen (H2) explosion effects recently examined, are confirming the devastating loss scenarios to humans, environment, assets, and associated business interruption. H2 production is a core process in refineries used in further process steps. Steam reforming of natural gas or a mix with naphtha or LPG is a common hydrogen production technique, where the latest technologies have adopted enhanced metallurgies to minimize explosion risk and the associated maintenance cost following plant degradation owing to corrosion effects. However, corrosion rates are still high in specific areas of piping and process equipment. The aim of this paper is to present a methodology based on semi-quantitative RBI modeling according to regulations by API and recent EN standards, adopting a family of linear regression forecasting models that depict the yearly corrosion rate (per corrosion loop) of a hydrogen production steam reforming unit; this is done under different operating conditions (e.g., temperature, pressure, and fluid speed), metallurgy and other related physicochemical variables. The model is based on the examination of both ultrasonic wall thinning measurements and the examination of quantitative crosslinking total corrosion effects along with the physicochemical properties prevailing in different plant corrosion loops. The outcome of the regression analysis is an expansive family of multivariable equations describing, with a defined accuracy, the yearly corrosion rate and associated lifespan forecast per corrosion loop, and per examined part. These equations were further utilized in a custom-made database that can be used as an additional loss prevention tool by the hydrogen production unit management team. Evaluation results regarding the tool efficiency are presented in the following of this paper. 相似文献
Corrosion in seawater is simultaneously influenced by multiple environmental factors including dissolved oxygen (DO), temperature, salinity, pH, and so on. These factors vary along with time and are different in different locations. The spatial-temporal variation of the actual marine environment cannot be ignored in corrosion prediction models. This paper proposes a new method for corrosion prediction in the actual time-varying marine environment which includes the design of experiments, calibration of acceleration models, and the modeling of marine environment. Acceleration models capture the effects of environmental factors and acts as the link between the environment and the corrosion process. The marine environment is described with the Kriging spatial-temporal model. Then the proposed method is used to give corrosion predictions for metals in different locations and vessels travel in different waters. This method could be helpful for corrosion resistance evaluation and environment corrosivity assessment. 相似文献
Objective: The objective of this article was to estimate the prevalence of alcohol impairment in crashes involving farm equipment on public roadways and the effect of alcohol impairment on the odds of crash injury or fatality.
Methods: On-road farm equipment crashes were collected from 4 Great Plains state departments of transportation during 2005–2010. Alcohol impairment was defined as an involved driver having blood alcohol content of ≥0.08 g/100 ml or a finding of alcohol impairment as a driver contributing circumstance recorded on the police crash report. Injury or fatality was categorized as (a) no injury (no and possible injury combined), (b) injury (nonincapacitating or incapacitating injury), and (c) fatality. Hierarchical multivariable logistic regression modeling, clustered on crash, was used to estimate the odds of an injury/fatality in crashes involving an alcohol-impaired driver.
Results: During the 5 years under study, 3.1% (61 of 1971) of on-road farm equipment crashes involved an alcohol-impaired driver. One in 20 (5.6%) injury crashes and 1 in 6 (17.8%) fatality crashes involved an alcohol-impaired driver. The non-farm equipment driver was significantly more likely to be alcohol impaired than the farm equipment driver (2.4% versus 1.1% respectively, P = .0012). After controlling for covariates, crashes involving an alcohol-impaired driver had 4.10 (95% confidence interval [CI], 2.30–7.28) times the odds of an injury or fatality. In addition, the non-farm vehicle driver was at 2.28 (95% CI, 1.92–2.71) times higher odds of an injury or fatality than the farm vehicle driver. No differences in rurality of the crash site were found in the multivariable model.
Conclusion: On-road farm equipment crashes involving alcohol result in greater odds of an injury or fatality. The risk of injury or fatality is higher among the non-farm equipment vehicle drivers who are also more likely to be alcohol impaired. Further studies are needed to measure the impact of alcohol impairment in on-road farm equipment crashes. 相似文献