Numerical simulation of the 12 May 1997 CME Event: The role of magnetic reconnection

We perform a numerical study of the evolution of a Coronal Mass Ejection (CME) and its interaction with the coronal magnetic field based on the 12 May 1997, CME event using a global MagnetoHydroDynamic (MHD) model for the solar corona. The ambient solar wind steady-state solution is driven by photospheric magnetic field data, while the solar eruption is obtained by superimposing an unstable flux rope onto the steady-state solution. During the initial stage of CME expansion, the core flux rope reconnects with the neighboring field, which facilitates lateral expansion of the CME footprint in the low corona. The flux rope field also reconnects with the oppositely orientated overlying magnetic field in the manner of the breakout model. During this stage of the eruption, the simulated CME rotates counter-clockwise to achieve an orientation that is in agreement with the interplanetary flux rope observed at 1 AU. A significant component of the CME that expands into interplanetary space comprises one of the side lobes created mainly as a result of reconnection with the overlying field. Within 3 hours, reconnection effectively modifies the CME connectivity from the initial condition where both footpoints are rooted in the active region to a situation where one footpoint is displaced into the quiet Sun, at a significant distance (≈1R ) from the original source region. The expansion and rotation due to interaction with the overlying magnetic field stops when the CME reaches the outer edge of the helmet streamer belt, where the field is organized on a global scale. The simulation thus offers a new view of the role reconnection plays in rotating a CME flux rope and transporting its footpoints while preserving its core structure.

Simulation of milk production by dairy cows fed sugarcane top-based diets with locally available supplements under Indian conditions

A model of sugarcane digestion was applied to indicate the suitability of various locally available supplements for enhancing milk production of Indian crossbred dairy cattle. Milk production was calculated according to simulated energy, lipogenic, glucogenic and aminogenic substrate availability. The model identified the most limiting substrate for milk production from different sugarcane-based diets. For sugarcane tops/urea fed alone, milk production was most limited by amino acid followed by long chain fatty acid availability. Among the protein-rich oil cake supplements at 100, 200 and 300 g supplement/kg total DM, cottonseed oil cake proved superior with a milk yield of 5.5, 7.3 and 8.3 kg/day, respectively. This was followed by mustard oil cake with 5.1, 6.5 and 7.6 kg/day, respectively. In the case of a protein-rich supplement (fish meal), milk yield was limited to 6.6 kg/day due to a shortage of long chain fatty acids. However, at 300 g of supplementation, energy became limiting, with a milk yield of 6.7 kg/day. Supplementation with rice bran and rice polishings at 100, 200 and 300 g restricted milk yield to 4.3, 4.9 and 5.5 and 4.5, 5.3 and 6.1 kg/day, respectively, and amino acids became the factor limiting milk production. The diet comprising basal sugarcane tops supplemented by leguminous fodder, dry fodder (e.g. rice or wheat straw) and concentrates at levels of 100, 200 and 300 g supplements/kg total diet DM proved to be the most balanced with a milk yield of 5.1, 6.7 and 9.0 kg/day, respectively.

Quantifying uncertainty in the simulation of crop-climate processes

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (λ, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966–1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of λ near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Simulation of the impact of high temperature stress on annual crop yields

Brief periods of high temperature which occur near flowering can severely reduce the yield of annual crops such as wheat and groundnut. A parameterisation of this well-documented effect is presented for groundnut (i.e. peanut; Arachis hypogaeaL.). This parameterisation was combined with an existing crop model, allowing the impact of season-mean temperature, and of brief high-temperature episodes at various times near flowering, to be both independently and jointly examined. The extended crop model was tested with independent data from controlled environment experiments and field experiments. The impact of total crop duration was captured, with simulated duration being within 5% of observations for the range of season-mean temperatures used (20-28 degrees C). In simulations across nine differently timed high temperature events, eight of the absolute differences between observed and simulated yield were less than 10% of the control (no-stress) yield. The parameterisation of high temperature stress also allows the simulation of heat tolerance across different genotypes. Three parameter sets, representing tolerant, moderately sensitive and sensitive genotypes were developed and assessed. The new parameterisation can be used in climate change studies to estimate the impact of heat stress on yield. It can also be used to assess the potential for adaptation of cropping systems to increased temperature threshold exceedance via the choice of genotype characteristics. (c) 2005 Elsevier B.V. All rights reserved.

Simulation of crop yields using ERA-40: Limits to skill and nonstationarity in weather-yield relationships

Reanalysis data provide an excellent test bed for impacts prediction systems. because they represent an upper limit on the skill of climate models. Indian groundnut (Arachis hypogaea L.) yields have been simulated using the General Large-Area Model (GLAM) for annual crops and the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-yr reanalysis (ERA-40). The ability of ERA-40 to represent the Indian summer monsoon has been examined. The ability of GLAM. when driven with daily ERA-40 data, to model both observed yields and observed relationships between subseasonal weather and yield has been assessed. Mean yields "were simulated well across much of India. Correlations between observed and modeled yields, where these are significant. are comparable to correlations between observed yields and ERA-40 rainfall. Uncertainties due to the input planting window, crop duration, and weather data have been examined. A reduction in the root-mean-square error of simulated yields was achieved by applying bias correction techniques to the precipitation. The stability of the relationship between weather and yield over time has been examined. Weather-yield correlations vary on decadal time scales. and this has direct implications for the accuracy of yield simulations. Analysis of the skewness of both detrended yields and precipitation suggest that nonclimatic factors are partly responsible for this nonstationarity. Evidence from other studies, including data on cereal and pulse yields, indicates that this result is not particular to groundnut yield. The detection and modeling of nonstationary weather-yield relationships emerges from this study as an important part of the process of understanding and predicting the impacts of climate variability and change on crop yields.

Quantification of physical and biological uncertainty in the simulation of the yield of a tropical crop using present-day and doubled CO2 climates

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (lambda, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of lambda near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

First structural analysis of a naphthalene-based poly(ether ketone): Crystal and molecular simulation from X-ray powder data and diffraction modeling

Polycondensation of 2,6-dihydroxynaphthalene with 4,4'-bis(4"-fluorobenzoyl)biphenyl affords a novel, semicrystalline poly(ether ketone) with a melting point of 406 degreesC and glass transition temperature (onset) of 168 degreesC. Molecular modeling and diffraction-simulation studies of this polymer, coupled with data from the single-crystal structure of an oligomer model, have enabled the crystal and molecular structure of the polymer to be determined from X-ray powder data. This structure-the first for any naphthalene-containing poly(ether ketone)-is fully ordered, in monoclinic space group P2(1)/b, with two chains per unit cell. Rietveld refinement against the experimental powder data gave a final agreement factor (R-wp) of 6.7%.

Solid phases of cyclopentane: combined experimental and simulation study

The phase diagram of cyclopentane has been studied by powder neutron diffraction, providing diffraction patterns for phases I, II, and III, over a range of temperatures and pressures. The putative phase IV was not observed. The structure of the ordered phase III has been solved by single-crystal diffraction. Computational modeling reveals that there are many equienergetic ordered structures for cyclopentane within a small energy range. Molecular dynamics simulations reproduce the structures and diffraction patterns for phases I and III and also show an intermediate disordered phase, which is used to interpret phase II.

E-commerce system simulation for construction and demolition waste exchange

This article introduces a quantitative approach to e-commerce system evaluation based on the theory of process simulation. The general concept of e-commerce system simulation is presented based on the considerations of some limitations in e-commerce system development such as the huge amount of initial investments of time and money, and the long period from business planning to system development, then to system test and operation, and finally to exact return; in other words, currently used system analysis and development method cannot tell investors about some keen attentions such as how good their e-commerce system could be, how many investment repayments they could have, and which area they should improve regarding the initial business plan. In order to exam the value and its potential effects of an e-commerce business plan, it is necessary to use a quantitative evaluation approach and the authors of this article believe that process simulation is an appropriate option. The overall objective of this article is to apply the theory of process simulation to e-commerce system evaluation, and the authors will achieve this though an experimental study on a business plan for online construction and demolition waste exchange. The methodologies adopted in this article include literature review, system analysis and development, simulation modelling and analysis, and case study. The results from this article include the concept of e-commerce system simulation, a comprehensive review of simulation methods adopted in e-commerce system evaluation, and a real case study of applying simulation to e-commerce system evaluation. Furthermore, the authors hope that the adoption and implementation of the process simulation approach can effectively support business decision-making, and improve the efficiency of e-commerce systems.

Design, testing, and simulation of fibre composite leaf springs for heavy axle loads

This paper summarizes the design, manufacturing, testing, and finite element analysis (FEA) of glass-fibre-reinforced polyester leaf springs for rail freight vehicles. FEA predictions of load-deflection curves under static loading are presented, together with comparisons with test results. Bending stress distribution at typical load conditions is plotted for the springs. The springs have been mounted on a real wagon and drop tests at tare and full load have been carried out on a purpose-built shaker rig. The transient response of the springs from tests and FEA is presented and discussed.