The creep behaviour of ASTM A437 grade B4B steel for steam turbine applications

This study is a continuation of a project to characterise ASTM A437 Grade B4B martensitic stainless steel for use In Hitachi Canadian Industries Ltd’s (HCI) steam turbine casing bolts. ASTM A437 Grade B4B steel is commercially available and was chosen for the study due to its chemical similarity to a proprietary steel currently used by HCI.High creep resistance is essential for any candidate so creep-rupture and creep-strain tests were performed at and above the intended service temperature of 538°C. Hardness measurements and transmission electron microscopy were performed on the steel in the as-received condition as well as on crept samples to determine the effect of elevated temperature on the development of the steel’s microstructure.During testing, it was found that ASTM A437 Grade B4B steel has a well defined second stage leading to an abrupt transition into the third stage. The second stage begins in the first 10% of its creep life, while the third stage begins at 90% of its creep life. This equates to 5% and 30% of the final strain, respectively, with an average final strain of 20%.Time-to-Rupture data show good similarity to the creep life as predicted using the Larson-Miller method. When plotted, the steady-state creep rate shows a definite correlation between the creep stress and temperature. From this an empirical relationship was developed to predict the steady-state creep rate. Transmission electron microscopy (TEM) results showed a significant change in the icrostructure between crept and as-received steel. Coarsening of carbides along grain boundaries most likely led to a recovery of the microstructure in the crept samples. Literature suggests that the composition of the carbides is most likely tungsten and molybdenum intermetalics and carbides that coarsened from the depletion of chromium from solution. This was supported by energy dispersive spectroscopy (EDS) analysis.The coarsening of carbides correlates with the decrease in creep resistance of the material and it is likely that the growth of precipitates and recovery of the microstructure causes the entry of the steel into third stage creep

Extracting individual trees from lidar point clouds using treeseg

Recent studies have demonstrated the potential of lidar-derived methods in plant ecology and forestry. One limitation to these methods is accessing the information content of point clouds, from which tree-scale metrics can be retrieved. This is currently undertaken through laborious and time-consuming manual segmentation of tree-level point clouds from larger-area point clouds, an effort that is impracticable across thousands of stems. Here, we present treeseg, an open-source software to automate this task. This method utilises generic point cloud processing techniques including Euclidean clustering, principal component analysis, region-based segmentation, shape fitting and connectivity testing. This data-driven approach uses few a priori assumptions of tree architecture, and transferability across lidar instruments is constrained only by data quality requirements. We demonstrate the treeseg algorithm here on data acquired from both a structurally simple open forest and a complex tropical forest. Across these data, we successfully automatically extract 96% and 70% of trees, respectively, with the remainder requiring some straightforward manual segmentation. treeseg allows ready and quick access to tree-scale information contained in lidar point clouds. treeseg should help contribute to more wide-scale uptake of lidar-derived methods to applications ranging from the estimation of carbon stocks through to descriptions of plant form and function

The Impact of Hedge Funds on Asset Markets

While there has been enormous interest in hedge funds from academics, prospective and current investors, and policymakers, rigorous empirical evidence of their impact on asset markets has been difficult to find. We construct a simple measure of the aggregate illiquidity of hedge fund portfolios, and show that it has strong in- and out-of-sample forecasting power for 72 portfolios of international equities, corporate bonds, and currencies over the 1994 to 2011 period. The forecasting ability of hedge fund illiquidity for asset returns is in most cases greater than, and provides independent information relative to, well-known predictive variables for each of these asset classes. We construct a simple equilibrium model to rationalize our findings, and empirically verify auxiliary predictions of the model

Graphical models for zero-inflated single cell gene expression

Bulk gene expression experiments relied on aggregations of thousands of cells to measure the average expression in an organism. Advances in microfluidic and droplet sequencing now permit expression profiling in single cells. This study of cell-to-cell variation reveals that individual cells lack detectable expression of transcripts that appear abundant on a population level, giving rise to zero-inflated expression patterns. To infer gene co-regulatory networks from such data, we propose a multivariate Hurdle model. It is comprised of a mixture of singular Gaussian distributions. We employ neighborhood selection with the pseudo-likelihood and a group lasso penalty to select and fit undirected graphical models that capture conditional independences between genes. The proposed method is more sensitive than existing approaches in simulations, even under departures from our Hurdle model. The method is applied to data for T follicular helper cells, and a high-dimensional profile of mouse dendritic cells. It infers network structure not revealed by other methods; or in bulk data sets. An R implementation is available at https://github.com/amcdavid/HurdleNormal .Comment: Fixed error in software UR

Protocol for the Reconstructing Consciousness and Cognition (ReCCognition) Study

Important scientific and clinical questions persist about general anesthesia despite the ubiquitous clinical use of anesthetic drugs in humans since their discovery. For example, it is not known how the brain reconstitutes consciousness and cognition after the profound functional perturbation of the anesthetized state, nor has a specific pattern of functional recovery been characterized. To date, there has been a lack of detailed investigation into rates of recovery and the potential orderly return of attention, sensorimotor function, memory, reasoning and logic, abstract thinking, and processing speed. Moreover, whether such neurobehavioral functions display an invariant sequence of return across individuals is similarly unknown. To address these questions, we designed a study of healthy volunteers undergoing general anesthesia with electroencephalography and serial testing of cognitive functions (NCT01911195). The aims of this study are to characterize the temporal patterns of neurobehavioral recovery over the first several hours following termination of a deep inhaled isoflurane general anesthetic and to identify common patterns of cognitive function recovery. Additionally, we will conduct spectral analysis and reconstruct functional networks from electroencephalographic data to identify any neural correlates (e.g., connectivity patterns, graph-theoretical variables) of cognitive recovery after the perturbation of general anesthesia. To accomplish these objectives, we will enroll a total of 60 consenting adults aged 20–40 across the three participating sites. Half of the study subjects will receive general anesthesia slowly titrated to loss of consciousness (LOC) with an intravenous infusion of propofol and thereafter be maintained for 3 h with 1.3 age adjusted minimum alveolar concentration of isoflurane, while the other half of subjects serves as awake controls to gauge effects of repeated neurobehavioral testing, spontaneous fatigue and endogenous rest-activity patterns

CO2 STORage Evaluation Database (CO2 Stored): the UK's online storage atlas

The CO2 Storage Evaluation Database (CO2 Stored) is the UK's offshore storage atlas. It provides online access to information for over 500 potential offshore storage units. CO2 Stored is hosted and developed in partnership by The Crown Estate (TCE) and The British Geological Survey (BGS). CO2 Stored provides access to some of the results of the UK Storage Appraisal Project (UKSAP; commissioned and funded by the Energy Technologies Institute). Through CO2 Stored information can be delivered for a range of storage types including saline aquifers and oil and gas fields concerning the geological parameters of the storage units, potential geological risks and economic projections for cost of storage