Long term aging effect on the creep strength of the T92 steel

International audienceCreep strength loss of T92 steel after long-term creep exposure at 600°C and 650°C is partially due to a thermal aging of the steel during the first part of the test. In order to quantify the effect of long-term aging on the creep strength loss, creep tests were conducted at 600 and 650°C on T92 steel thermally aged for 10,000h at the same temperature and on as-received T92 steel. Laves phases precipitates were found after thermal aging at 600°C and 650°C with an average equivalent diameter of about 200nm and of about 350nm, respectively. No significant change in hardness and in the matrix substructure as revealed by electron backscatter diffraction occurred during aging. For stresses higher than 170MPa at 600°C and higher than 110MPa at 650°C the time to rupture is four times lower in the aged steels compared to the as-received steel, this is correlated to a secondary creep rate four times higher for the aged specimens compared to that of the as-received steel. Creep tests conducted at 650°C under lower stresses revealed a creep lifetime only twice lower after aging

Perceptions of oral health adequacy and access in Michigan nursing facilities

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72951/1/j.1741-2358.2007.00202.x.pd

Medical Conditions of Nursing Home Admissions

<p>Abstract</p> <p>Background</p> <p>As long-term nursing home care is likely to increase with the aging of the population, identifying chronic medical conditions is of particular interest. Although need factors have a strong impact on nursing home (NH) admission, the diseases causing these functional disabilities are lacking or unclear in the residents' file. We investigated the medical reason (primary diagnosis) of a nursing home admission with respect to the underlying disease.</p> <p>Methods</p> <p>This study is based on two independent, descriptive and comparative studies in Belgium and was conducted at two time points (1993 and 2005) to explore the evolution over twelve years. Data from the subjects were extracted from the resident's file; additional information was requested from the general practitioner, nursing home physician or the head nurse in a face-to-face interview. In 1993 we examined 1332 residents from 19 institutions, and in 2005 691 residents from 7 institutions. The diseases at the time of admission were mapped by means of the International Classification of Diseases - 9th edition (ICD-9). Longitudinal changes were assessed and compared by a chi-square test.</p> <p>Results</p> <p>The main chronic medical conditions associated with NH admission were dementia and stroke. Mental disorders represent 48% of all admissions, somatic disorders 43% and social/emotional problems 8%. Of the somatic disorders most frequently are mentioned diseases of the circulatory system (35%) [2/3 sequels of stroke and 1/5 heart failure], followed by diseases of the nervous system (15%) [mainly Parkinson's disease] and the musculoskeletal system (14%) [mainly osteoarthritis]. The most striking evolution from 1993 to 2005 consisted in complicated diabetes mellitus (from 4.3 to 11.4%; p < 0.0001) especially with amputations and blindness. Symptoms (functional limitations without specific disease) like dizziness, impaired vision and frailty are of relevance as an indicator of admission.</p> <p>Conclusion</p> <p>Diseases like stroke, diabetes and mobility problems are only important for institutionalisation if they cause functional disability. Diabetes related complications as cause of admission increased almost three-fold between 1993 and 2005.</p

Research trends in combinatorial optimization

Acknowledgments This work has been partially funded by the Spanish Ministry of Science, Innovation, and Universities through the project COGDRIVE (DPI2017-86915-C3-3-R). In this context, we would also like to thank the Karlsruhe Institute of Technology. Open access funding enabled and organized by Projekt DEAL.Peer reviewedPublisher PD

The decision rule approach to optimization under uncertainty: methodology and applications

Dynamic decision-making under uncertainty has a long and distinguished history in operations research. Due to the curse of dimensionality, solution schemes that naïvely partition or discretize the support of the random problem parameters are limited to small and medium-sized problems, or they require restrictive modeling assumptions (e.g., absence of recourse actions). In the last few decades, several solution techniques have been proposed that aim to alleviate the curse of dimensionality. Amongst these is the decision rule approach, which faithfully models the random process and instead approximates the feasible region of the decision problem. In this paper, we survey the major theoretical findings relating to this approach, and we investigate its potential in two applications areas