Energy-related emissions from telework

Telework is a growing phenomenon that is thought to save energy and air emissions. This paper applies a systems model to telework and nontelework scenarios in order to quantify greenhouse gas and other air emissions from transportation, heating, cooling, lighting, and electronic and electrical equipment use both at the company and the home office. Using United States data, a WWW-based, scalable decision-support tool was created to evaluate the environmental impacts of teleworkers. For a typical case reflecting United States teleworker patterns, the analysis found that telework has the potential to reduce air emissions. However, Monte Carlo simulation employed to perform a probabilistic analysis over a set of likely parameters has revealed that telework may not affect equally the emissions of all types of pollutants. It may decrease CO2, NOx, SO2, PM10, and CO but not N2O and CH4 emissions. Therefore, the scope and goal of telework programs must be defined early in the implementation process. Work-related transportation (commuting) impacts could be reduced as a result of telework; however, home-related impacts due to an employee spending additional time at home could potentially offset these reductions. Company office-related impacts may not be reduced unless the office space is shared with other employees during telework days or eliminated entirely. In states with high telework potential (California, Georgia, Illinois, New York, Texas), telework could save emissions, but it would depend on commuting and climatic patterns and the electricity mix. Environmentally beneficial telework programs are found to depend mainly on commuting patterns, induced energy usage, and characteristics of the office and home space and equipment use.     

CD28null and Regulatory T Cells Are Substantially Disrupted in Patients with End-Stage Renal Disease Due to Diabetes Mellitus

Background: End-stage renal disease (ESRD) is associated with alterations in T-cell immunity, including increased CD28null and reduced regulatory T cells (Tregs). However, whether immune disturbances are due to ESRD or primary disease is not yet clear. As diabetes mellitus is the leading cause of ESRD, we evaluated its impact on the immune profile of ESRD patients. Methods: CD28null, Tregs, and natural killer cells were initially analyzed by flow cytometry in 30 predialysis ESRD patients due to diabetes (DM), 30 non-DM (NDM), and 25 healthy controls. Measurements were repeated after 6 months on hemodialysis (HD) or peritoneal dialysis (CAPD). Results: The percentage of CD4 + CD28null cells, CD8 + CD28null cells, and Tregs showed significant differences in DM, NDM, and controls; mean rank 33.71 vs. 25.68 vs. 18.88, p = 0.006, 37.79 vs. 28.82 vs. 17.08, p = 0.008, and 20.79 vs. 26.12 vs. 41.33, p = 0.001, respectively. DM vs. NDM had increased CD4 + CD28null and CD8 + CD28null cells, 11.5% (1.5%–24%) vs. 4.1% (0–42.3%), p = 0.02 and 61.3% (24%–76%) vs. 43% (5.7%–85%), p = 0.04, respectively. After 6 months on HD but not CAPD, DM showed a significant further increase in CD4 + CD28null cells, from 30 (14–100) to 52.7 (15–203), p = 0.02; and CD8 + CD28null cells, from 137 (56–275) to 266 (103–456), p = 0.01. Conclusions: Diabetes mellitus affects T-cell subtypes even at predialysis stage, though changes become more prominent after commencement on HD.     

Microstructure and failure of a welded ZnTiCu tube

A failure analysis of a cracked ZnTiCu welded tube was conducted primarily by using microstructural observations of the weld joint and mechanical testing of related material. The presence of pre-existing welding defects was a major contributor to the failure.     

The use of empirical data sources in HRA

This paper presents a review of available information related to human performance to support Human Reliability Analysis (HRA) performed for nuclear power plants (NPPs). A number of data sources are identified as potentially useful. These include NPP licensee event reports, augmented inspection team reports, operator requalification data, results from the literature in experimental psychology, and the Aviation Safety Reporting System. The paper discusses how utilizing such information improves our capability to model and quantify human performance. In particular, the paper discusses how information related to performance shaping factors can be extracted from empirical data to determine their size effect, their relative effects, as well as their interactions. The paper concludes that appropriate use of existing sources can help addressing some of the important issues we are currently facing in HRA.     

Failure analysis of fractured deep-drawn 1050 aluminum circles

A failure analysis of fractured deep-drawn 1050 aluminum (Al) circles revealed that the tensile strength and especially the tensile elongation of the stock material were out of specifications, leading to fracture during the drawing process. The cracks appeared on the walls of the drawn components, which are produced from 0.40 mm thick 1050 Al circles. The circle stock originated from an unknown supplier. The microstructural characterization of the circle stock indicated a coarse grain structure (180 to 220 μm), and observations of the failure areas revealed the presence of pronounced “orange peel.” Comparison was made with a raw material that originated from a registered and certified supplier in order to demonstrate the differences between the raw materials of the defective and sound products.     

Expert elicitation approach for performing ATHEANA quantification

An expert elicitation approach has been developed to estimate probabilities for unsafe human actions (UAs) based on error-forcing contexts (EFCs) identified through the ATHEANA (A Technique for Human Event Analysis) search process. The expert elicitation approach integrates the knowledge of informed analysts to quantify UAs and treat uncertainty (‘quantification-including-uncertainty’). The analysis focuses on (a) the probabilistic risk assessment (PRA) sequence EFCs for which the UAs are being assessed, (b) the knowledge and experience of analysts (who should include trainers, operations staff, and PRA/human reliability analysis experts), and (c) facilitated translation of information into probabilities useful for PRA purposes. Rather than simply asking the analysts their opinion about failure probabilities, the approach emphasizes asking the analysts what experience and information they have that is relevant to the probability of failure. The facilitator then leads the group in combining the different kinds of information into a consensus probability distribution. This paper describes the expert elicitation process, presents its technical basis, and discusses the controls that are exercised to use it appropriately. The paper also points out the strengths and weaknesses of the approach and how it can be improved. Specifically, it describes how generalized contextually anchored probabilities (GCAPs) can be developed to serve as reference points for estimates of the likelihood of UAs and their distributions.