Study of the microstructure of the grade 91 steel after more than 100.000h of creep exposure at 600°C

International audienceThis paper presents results on the evolution of microstructure (both matrix and precipitates) of an ASME Grade 91 steel that has been creep tested for 113,431 h at 600 °C under a load of 80 MPa. The microstructure was investigated using transmission electron microscopy (TEM) and revealed chromium rich M23C6 carbides, MX-type precipitates, Laves phases and modified Z-phases. Only a small amount of modified Z-phase was found. In order to quantify coarsening of precipitates and growth of new phases during creep, the size distributions of the identified precipitates were determined by analysis of TEM images. In addition to this, the size distribution of Laves phases was determined by image analysis of scanning electron micrographs. Substructure modifications and creep damage were investigated on cross sections of the creep specimen using Electron Backscatter Diffraction and Scanning Electron Microscopy

A visual demonstration of convergence properties of cooperative coevolution

We introduce a model for cooperative coevolutionary algorithms (CCEAs) using partial mixing, which allows us to compute the expected long-run convergence of such algorithms when individuals ’ fitness is based on the maximum payoff of some N evaluations with partners chosen at random from the other population. Using this model, we devise novel visualization mechanisms to attempt to qualitatively explain a difficult-to-conceptualize pathology in CCEAs: the tendency for them to converge to suboptimal Nash equilibria. We further demonstrate visually how increasing the size of N, or biasing the fitness to include an ideal-collaboration factor, both improve the likelihood of optimal convergence, and under which initial population configurations they are not much help

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

Secondary traumatic stress and burnout in healthcare workers during COVID-19 outbreak

Background: The present study aims to assess the level of professional burnout and secondary traumatic stress (STS), and to identify potential risk or protective factors among health care workers (HCWs) during the coronavirus disease 2019 (COVID-19) outbreak.; (2) Methods: This cross-sectional study, based on an online survey, collected demographic data and mental distress outcomes from 184 HCWs from 1 May 2020, to 15 June 2020, from 45 different countries. The degree of STS, perceived stress and burnout was assessed using the Secondary Traumatic Stress Scale (STSS), the Perceived Stress Scale (PSS) and Maslach Burnout Inventory Human Service Survey (MBI-HSS) respectively. Stepwise multiple regression analysis was performed to identify potential risk and protective factors for STS; (3) Results: 184 HCWs (M = 90; Age mean: 46.45; SD: 11.02) completed the survey. A considerable proportion of HCWs had symptoms of STS (41.3%), emotional exhaustion (56.0%), and depersonalization (48.9%). The prevalence of STS was 47.5% in frontline HCWs while in HCWs working in other units it was 30.3% (p < 0.023); 67.1% for the HCWs exposed to patients’ death and 32.9% for those HCWs which were not exposed to the same condition (p < 0.001). In stepwise multiple regression analysis, perceived stress, emotional exhaustion, and exposure to patients’ death remained as significant predictors in the final model for STS (adjusted R2 = 0.537, p < 0.001); (4) Conclusions: During the current COVID-19 pandemic, HCWs facing patients’ physical pain, psychological suffering, and death are more likely to develop STS. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Rational bidding using reinforcement learning: an application in automated resource allocation

The application of autonomous agents by the provisioning and usage of computational resources is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic resource provisioning and usage of computational resources, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems. The contributions of the paper are threefold. First, we present a framework for supporting consumers and providers in technical and economic preference elicitation and the generation of bids. Secondly, we introduce a consumer-side reinforcement learning bidding strategy which enables rational behavior by the generation and selection of bids. Thirdly, we evaluate and compare this bidding strategy against a truth-telling bidding strategy for two kinds of market mechanisms – one centralized and one decentralized

The transformation of the forest steppe in the lower Danube Plain of south-eastern Europe : 6000 years of vegetation and land use dynamics

Forest steppes are dynamic ecosystems, highly susceptible to changes in climate and land use. Here we examine the Holocene history of the European forest steppe ecotone in the Lower Danube Plain to better understand its sensitivity to climate fluctuations and human impact, and the timing of its transition into a cultural forest steppe. We used multi-proxy analyses (pollen, n-alkane, coprophilous fungi, charcoal, and geochemistry) of a 6000-year sequence from Lake Oltina (SE Romania), combined with a REVEALS model of quantitative vegetation cover. We found the greatest tree cover, composed of xerothermic (Carpinus orientalis and Quercus) and temperate (Carpinus betulus, Tilia, Ulmus and Fraxinus) tree taxa between 6000 and 2500 cal yr BP. Maximum tree cover (~ 50 %) occurred between 4200 and 2500 cal yr BP at a time of wetter climatic conditions. Compared to other European forest steppe areas, the dominance of Carpinus orientalis represents the most distinct feature of the woodland's composition during that time. Forest loss was under way by 2500 yr BP (Iron Age) with REVEALS estimates indicating a fall to ~ 20 % tree cover from the mid-Holocene forest maximum linked to clearance for agriculture, while climate conditions remained wet. Biomass burning increased markedly at 2500 cal yr BP suggesting that fire was regularly used as a management tool until 1000 cal yr BP when woody vegetation became scarce. A sparse tree cover, with only weak signs of forest recovery, then became a permanent characteristic of the Lower Danube Plain, highlighting recurring anthropogenic pressure. The timing of anthropogenic ecosystem transformation here (2500 cal yr BP) was in between that in central eastern (between 3700 and 3000 cal yr BP) and eastern (after 2000 cal yr BP) Europe. Our study is the first quantitative land cover estimate at the forest steppe ecotone in south eastern Europe spanning 6000 years and provides critical empirical evidence that the present-day forest steppe/woodlands reflects the potential natural vegetation in this region under current climate conditions. This study also highlights the potential of n-alkane indices for vegetation reconstruction, particularly in dry regions where pollen is poorly preserved

Q-Strategy: A Bidding Strategy for Market-Based Allocation of Grid Services

The application of autonomous agents by the provisioning and usage of computational services is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic service provisioning and usage of Grid services, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems. The contributions of the paper are threefold. First, we present a bidding agent framework for implementing artificial bidding agents, supporting consumers and providers in technical and economic preference elicitation as well as automated bid generation by the requesting and provisioning of Grid services. Secondly, we introduce a novel consumer-side bidding strategy, which enables a goal-oriented and strategic behavior by the generation and submission of consumer service requests and selection of provider offers. Thirdly, we evaluate and compare the Q-strategy, implemented within the presented framework, against the Truth-Telling bidding strategy in three mechanisms – a centralized CDA, a decentralized on-line machine scheduling and a FIFO-scheduling mechanisms

A Cordial Sync: Going Beyond Marginal Policies for Multi-Agent Embodied Tasks

Autonomous agents must learn to collaborate. It is not scalable to develop a new centralized agent every time a task's difficulty outpaces a single agent's abilities. While multi-agent collaboration research has flourished in gridworld-like environments, relatively little work has considered visually rich domains. Addressing this, we introduce the novel task FurnMove in which agents work together to move a piece of furniture through a living room to a goal. Unlike existing tasks, FurnMove requires agents to coordinate at every timestep. We identify two challenges when training agents to complete FurnMove: existing decentralized action sampling procedures do not permit expressive joint action policies and, in tasks requiring close coordination, the number of failed actions dominates successful actions. To confront these challenges we introduce SYNC-policies (synchronize your actions coherently) and CORDIAL (coordination loss). Using SYNC-policies and CORDIAL, our agents achieve a 58% completion rate on FurnMove, an impressive absolute gain of 25 percentage points over competitive decentralized baselines. Our dataset, code, and pretrained models are available at https://unnat.github.io/cordial-sync .Comment: Accepted to ECCV 2020 (spotlight); Project page: https://unnat.github.io/cordial-syn