Influence of Yield Strength Variability over Cross-Section to Steel Beam Load-Carrying Capacity

Authors of article analysed influence of variability of yield strength over cross-section of hot rolled steel member to its load-carrying capacity. In calculation models, the yield strength is usually taken as constant. But yield strength of a steel hot-rolled beam is generally a random quantity. Not only the whole beam but also its parts have slightly different material characteristics. According to the results of more accurate measurements, the statistical characteristics of the material taken from various cross-section points (e.g. from a web and a flange) are, however, more or less different. This variation is described by one dimensional random field. The load-carrying capacity of the beam IPE300 under bending moment at its ends with the lateral buckling influence included is analysed, nondimensional slenderness according to EC3 is λ¯ = 0.6. For this relatively low slender beam the influence of the yield strength on the load-carrying capacity is large. Also the influence of all the other imperfections as accurately as possible, the load-carrying capacity was determined by geometrically and materially nonlinear solution of very accurate FEM model by the ANSYS programme

Evaluation of a WRF ensemble using GCM boundary conditions to quantify mean and extreme climate for the southwest of Western Australia (1970-1999)

A high resolution (5 km), single initialization, 30 year (1970–1999) Weather Research and Forecast regional climate model (RCM) ensemble for southwest Western Australia (SWWA) is evaluated. The article focuses on the ability of the RCM to simulate winter cold fronts, which are the main source of rainfall for the region, and assesses the spatial and temporal characteristics of climate extremes within the region's cereal crop growing season. To explore uncertainty, a four-member ensemble was run, using lateral boundary conditions from general circulation models (GCMs) of the Coupled Model Intercomparison Project Phase 3; ECHAM5, Model for Interdisciplinary Research on Climate 3.2 (MIROC 3.2), Community Climate System Model version 3 (CCSM3) and Commonwealth Scientific and Industrial Research Organisation (CSIRO) mk3.5. Simulations are evaluated against gridded observations of temperature and precipitation and atmospheric conditions are compared to a simulation using ERA-Interim reanalysis boundary conditions, which is used as a surrogate truth. Results show that generally, the RCM simulations were able to represent the climatology of SWWA well, however differences in the positioning of the subtropical high pressure belt were apparent which influenced the number of fronts traversing the region and hence winter precipitation biases. Systematic temperature biases were present in some ensemble members and the RCM was found to be colder than the driving GCM in all simulations. Biases impacted model skill in representing temperature extremes and this was particularly apparent in the MIROC-forced simulation, which was the worst performing RCM for both temperature and precipitation. The dynamical causes of the biases are explored and findings show that nonetheless, the RCM provides added value, particularly in the spatio-temporal representation of wet season rainfall

System Reliability Estimation in Multicomponent Exponential-Lindley Stress-Strength Models

A stress-strength model is formulated for a multi-component system consisting of k identical components. The k components of the system with random strengths ( ) 1 2 , ,..., k X X X are subjected to one of the r random stresses ( ) 1 2 , ,..., r Y Y Y . The estimation of system reliability based on maximum likelihood estimates (MLEs) and Bayes estimators in k component system are obtained when the system is either parallel or series with the assumption that strengths and stresses follow Lindley distribution and Exponential distribution respectively. A simulation study is conducted to compare MLE and Bayes estimator through the mean squared errors of the estimators

An analysis of regional climate simulations for Western Australia's wine regions-model evaluation and future climate projections

The Weather Research and Forecasting (WRF) Model is evaluated as a regional climate model for the simulation of climate indices that are relevant to viticulture in Western Australia's wine regions at a 5-km resolution under current and future climate. WRF is driven with ERA-Interim reanalysis for the current climate and three global climate models (GCMs) for both current and future climate. The focus of the analysis is on a selection of climate indices that are commonly used in climate-viticulture research. Simulations of current climate are evaluated against an observational dataset to quantify model errors over the 1981-2010 period. Changes to the indices under future climate based on the SRES A2 emissions scenario are then assessed through an analysis of future (2030-59) minus present (1970-99) climate. Results show that when WRF is driven with ERA-Interim there is generally good agreement with observations for all of the indices although there is a noticeable negative bias for the simulation of precipitation. The results for the GCM-forced simulations were less consistent. Namely, while the GCM-forced simulations performed reasonably well for the temperature indices, all simulations performed inconsistently for the precipitation index. Climate projections showed significant warming for both of the temperature indices and indicated potential risks to Western Australia's wine growing regions under future climate, particularly in the north. There was disagreement between simulations with regard to the projections of the precipitation indices and hence greater uncertainty as to how these will be characterized under future climate

Dynamical downscaling for the southwest of Western Australia using the WRF modelling system

The southwest of Western Australia (SWWA) is a region of significant cereal production, with the main crops being winter grown wheat and barley. The most important factors influencing wheat growth and production are temperature extremes and precipitation, and hence, it is critical to have an understanding of how these environmental factors have changed in the past, and how they are likely to change in the future. One method of addressing this important research question is by using regional climate models (RCMs) to dynamically downscale re-analysis products and/or output form Global Circulation Models to a fine resolution. One tool which is being increasingly used for this purpose is the Weather Research and Forecasting Model (WRF) Advanced Research (ARW). However, like any modeling system, WRF-ARW requires thorough testing before it is implemented to carry out long-term climate runs. This paper examines the influence of different input data sources, as well as model physics options on simulated precipitation and maximum and minimum temperatures in SWWA by comparing the simulations against an observational gridded dataset. It is found that running WRF3.3 with the 1.0 × 1.0 degree National Center for Environmental Prediction Final analysis (NCEP-FNL), as compared to the 2.5 × 2.5 degree NCEP / National Center for Atmospheric Research (NCEP/NCAR or NNRP) results in much improved simulations of precipitation and temperatures. Using the National Oceanic and Atmospheric Administration 1.0 × 1.0 degree resolution sea surface temperature (SST) dataset does not result in markedly different results as compared to using the NNRP surface skin temperatures as SSTs. Using the Betts-Miller-Jajic (BMJ) scheme for cumulus/convection parameterisation rather than the more widely used Kain Fritsch (KF) scheme results in slightly higher errors for precipitation, and no marked change in temperatures. The latest version of the Rapid Radiative Transfer Model (RRTMG) is found to result in improved simulations of maximum and minimum temperatures, as compared to the RRTM, Community Atmosphere Model (CAM) 3.0, and Dudhia schemes. Use of the Asymmetric Convective Model as the planetary boundary-layer scheme rather than the more widely used Yonsei University scheme results in over-prediction of maximum and minimum temperatures

Australian climate extremes in the 21st century according to a regional climate model ensemble: Implications for health and agriculture

The negative impacts of climate extremes on socioeconomic sectors in Australia makes understanding their behaviour under future climate change necessary for regional planning. Providing robust and actionable climate information at regional scales relies on the downscaling of global climate model data and its translation into impact-relevant information. The New South Wales/Australian Capital Territory Regional Climate Modelling (NARCliM) project contains downscaled climate data over all of Australia at a 50 km resolution, with ensembles of simulations for the recent past (1990–2009), near future (2020–2039) and far future (2060–2079). Here we calculate and examine sector-relevant indices of climate extremes recommended by the Expert Team on Sector-specific Climate Indices (ET-SCI). We demonstrate the utility of NARCliM and the ET-SCI indices in understanding how future changes in climate extremes could impact aspects of the health and agricultural sectors in Australia. Consistent with previous climate projections, our results indicate that increases in heat and drought related extremes throughout the 21st century will occur. In the far future, maximum day time temperatures are projected to increase by up to 3.5 °C depending on season and location. The number of heatwaves and the duration of the most intense heatwaves will increase significantly in the near and far future, with greater increases in the north than south. All capital cities are projected to experience at least a tripling of heatwave days each year by the far future, compared to the recent past. Applying published heat-health relationships to projected changes in temperature shows that increases in mortality due to high temperatures for all cities examined would occur if projected future climates occurred today. Drought and the number of days above 30 °C are also projected to increase over the major wheat-growing regions of the country, particularly during spring when sensitivity of wheat to heat stress is greatest. Assuming no adaptation or acclimatisation, published statistical relationships between drought and national wheat yield suggest that national yields will have a less than one quarter chance of exceeding the annual historical average under far future precipitation change (excluding impacts of future temperature change and CO2 fertilization). The NARCliM data examined here, along with the ET-SCI indices calculated, provide a powerful and publicly available dataset for regional planning against future changes in climate extremes

Earlier green-up and spring warming amplification over Europe

The onset of green-up of plants has advanced in response to climate change. This advance has the potential to affect heat waves via biogeochemical and biophysical processes. Here a climate model was used to investigate only the biophysical feedbacks of earlier green-up on climate as the biogeochemical feedbacks have been well addressed. Earlier green-up by 5 to 30 days amplifies spring warming in Europe, especially heat waves, but makes few differences to heat waves in summer. This spring warming is most noticeable within 30 days of advanced green-up and is associated with a decrease in low- and middle-layer clouds and associated increases of downward short wave and net radiation. We find negligible differences in the Southern Hemisphere and low latitudes of the Northern Hemisphere. Our results provide an estimate of the level of skill necessary in phenology models to avoid introducing biases in climate simulations

Prophylactic amnioinfusion in oligohydramnios

Background: Oligohydramnios causes many intrapartum maternal and fetal complications. Intrapartum amnioinfusion effectively increases amniotic fluid volume and thereby decreases FH decelerations. The objective of this study was to compare the frequency of fetal heart decelerations and its perinatal outcome with and without amnioinfusion in patients with oligohydramnios and the cesarean rates for fetal distress between them.Methods: In study group, 100 patients in labour with AFI < 5 cm, oligohydramnios and IUGR with normal doppler, postdated pregnancies with AFI ≤ 5 cm with normal doppler were selected and prophylactic amnioinfusion with 300 ml lukewarm saline is given aseptically for 15 minutes after amniotomy. Continuous CTG monitoring done till delivery. If FH decelerations occur, the bolus was repeated up to 3 times. 100 age matched controls managed with conventional methods without amnioinfusion were selected retrospectively from labour room case records.Results: Incidence of FH decelerations was lower in study group (59% versus 84%). Cesarean section for fetal distress was reduced (20.9% versus 79.1%) Perinatal outcome was better. Babies with normal 1-minute Apgar was 86% compared to 75% in controls. Frequency of FH decelerations was reduced (20% versus 73%). Occurrence of 2 FH decelerations were 13% versus 33%, 3 FH decelerations were 7% versus 27% and > 3 times was 0% versus 13%.Conclusions: Prophylactic amnioinfusion can easily and effectively reduce the FH decelerations and caesarean section rate for fetal distress in oligohydramnios improving both maternal and fetal outcomes with negligible risks