Modeling technique for honeycomb FRP deck bridges via finite elements

Honeycomb structures have been used in different engineering fields. In civil engineering, honeycomb fiber-reinforced polymer (FRP) structures have been used as bridge decks to rehabilitate highway bridges in the United States. In this work, a simplified finite-element modeling technique for honeycomb FRP bridge decks is presented. The motivation is the combination of the complex geometry of honeycomb FRP decks and computational limits, which may prevent modeling of these decks in detail. The results from static and modal analyses indicate that the proposed modeling technique provides a viable tool for modeling the complex geometry of honeycomb FRP bridge decks. The modeling of other bridge components (e.g., steel girders, steel guardrails, deck-to-girder connections, and pier supports) is also presented in this work.

A hybrid commodity price-forecasting model applied to the sugar-alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

Modeling and measuring double-frequency jitter in one-way master-slave networks

The double-frequency jitter is one of the main problems in clock distribution networks. In previous works, sonic analytical and numerical aspects of this phenomenon were studied and results were obtained for one-way master-slave (OWMS) architectures. Here, an experimental apparatus is implemented, allowing to measure the power of the double-frequency signal and to confirm the theoretical conjectures. (C) 2008 Elsevier B.V. All rights reserved.

Inverse aerodynamic design applications using the MGM hybrid formulation

The well-known modified Garabedian-Mcfadden (MGM) method is an attractive alternative for aerodynamic inverse design, for its simplicity and effectiveness (P. Garabedian and G. Mcfadden, Design of supercritical swept wings, AIAA J. 20(3) (1982), 289-291; J.B. Malone, J. Vadyak, and L.N. Sankar, Inverse aerodynamic design method for aircraft components, J. Aircraft 24(2) (1987), 8-9; Santos, A hybrid optimization method for aerodynamic design of lifting surfaces, PhD Thesis, Georgia Institute of Technology, 1993). Owing to these characteristics, the method has been the subject of several authors over the years (G.S. Dulikravich and D.P. Baker, Aerodynamic shape inverse design using a Fourier series method, in AIAA paper 99-0185, AIAA Aerospace Sciences Meeting, Reno, NV, January 1999; D.H. Silva and L.N. Sankar, An inverse method for the design of transonic wings, in 1992 Aerospace Design Conference, No. 92-1025 in proceedings, AIAA, Irvine, CA, February 1992, 1-11; W. Bartelheimer, An Improved Integral Equation Method for the Design of Transonic Airfoils and Wings, AIAA Inc., 1995). More recently, a hybrid formulation and a multi-point algorithm were developed on the basis of the original MGM. This article discusses applications of those latest developments for airfoil and wing design. The test cases focus on wing-body aerodynamic interference and shock wave removal applications. The DLR-F6 geometry is picked as the baseline for the analysis.

Repeated disturbances and canopy disturbance regime in a tropical semi-deciduous forest

The canopy disturbance regime and the influence of gap methods on the interpretation of forest structure and dynamics were evaluated in a tropical semi-deciduous forest in south-eastern Brazil. We encountered a gap density of 11.2 gaps ha(-1) and an average size which varied from 121 to 333 m(2) depending on the gap delimitation method considered (minimum gap size was 10 m(2)). Although average size was slightly higher, the median value obtained (78 m(2)) was comparable to other tropical forest sites and the gap size-class distribution found supported the pattern described for such forest sites. Among 297 gap makers, snapping and uprooting were the most common modes of disturbance. The number and basal area of gap makers were good predictors of gap size. Almost 25% of all gaps suffered from repeated disturbance events that brought about larger gap sizes. Such processes, along with delimitation methods, strongly influenced the estimation of turnover rate and therefore the interpretation of forest dynamics. These results demonstrated the importance of further studies on repeated disturbances, which is often neglected in forest studies.

A frailty modeling approach for parental effects in animal breeding

Survival models involving frailties are commonly applied in studies where correlated event time data arise due to natural or artificial clustering. In this paper we present an application of such models in the animal breeding field. Specifically, a mixed survival model with a multivariate correlated frailty term is proposed for the analysis of data from over 3611 Brazilian Nellore cattle. The primary aim is to evaluate parental genetic effects on the trait length in days that their progeny need to gain a commercially specified standard weight gain. This trait is not measured directly but can be estimated from growth data. Results point to the importance of genetic effects and suggest that these models constitute a valuable data analysis tool for beef cattle breeding.

Toward sustainable soil and water resources use in China`s highly erodible semi-arid loess plateau

The water-wind crisscross region of the Loess Plateau in China is comprised of 17.8 million hectares of highly erodible soil under limited annual rainfall. This requires a sustainable water balance for the restoration of dryland ecosystems to reduce and manage soil erosion. In this region, alfalfa has been one of the main legumes grown to minimize soil erosion. However, alfalfa yields were significantly lower in years of reduced rainfall suggesting that high water use and deep rooting alfalfa make it an unsustainable crop due to the long-term decline in soil water storage and productivity. Our objectives in this Study were to evaluate the soil water balance of Loess Plateau soils during vegetative restoration and to evaluate practices that prevent soil desiccation and promote ecosystem restoration and sustainability. Field observations of soil moisture recovery and soil erosion were carried out for five years after alfalfa was replaced with different crops and with bare soil. Soil water content changes in cropland, rangeland, and bare soil were tracked over several years, using a water balance approach. Results indicate that growing forages significantly reduced runoff and sediment transport. A forage-food-crop rotation is a better choice than other cropping systems for achieving sustainable productivity and preventing soil erosion and desiccation. However, economic considerations have prevented its widespread adoption by local farmers. Alternatively, this study recommends consideration of grassland crops or forest ecosystems to provide a sustainable water balance in the Loess Plateau of China. (C) 2009 Elsevier B.V. All rights reserved.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

A generalized modified Weibull distribution for lifetime modeling

A four parameter generalization of the Weibull distribution capable of modeling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone as well as non-monotone failure rates, which are quite common in lifetime problems and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh and modified Weibull distributions, among others. We derive two infinite sum representations for its moments. The density of the order statistics is obtained. The method of maximum likelihood is used for estimating the model parameters. Also, the observed information matrix is obtained. Two applications are presented to illustrate the proposed distribution. (C) 2008 Elsevier B.V. All rights reserved.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Parametric and nonparametric statistical modelling of crop yield: implications for pricing crop insurance contracts

This article considers alternative methods to calculate the fair premium rate of crop insurance contracts based on county yields. The premium rate was calculated using parametric and nonparametric approaches to estimate the conditional agricultural yield density. These methods were applied to a data set of county yield provided by the Statistical and Geography Brazilian Institute (IBGE), for the period of 1990 through 2002, for soybean, corn and wheat, in the State of Paran. In this article, we propose methodological alternatives to pricing crop insurance contracts resulting in more accurate premium rates in a situation of limited data.

Inheritance of resistance to Puccinia psidii G. Winter in a eucalyptus interspecific hybrid progeny evaluated under conditions of natural infection

Inheritance of resistance to Puccinia psidii G. Winter in a eucalyptus interspecific hybrid progeny evaluated under conditions of natural infection Rust caused by the fungus Puccinia psidii is currently the most important disease of eucalyptus. It is widely disseminated in Brazil, and causes serious damage in nurseries and plantation areas. The identification of resistant germplasm along with knowledge of the genetic basis of resistance heredity are the first requirements for the success of breeding programs aiming to develop resistant varieties. Earlier studies carried out under controlled conditions suggested a monogenic control as well as the participation of at least two genes promoting resistance to rust. The goal of this study was to evaluate the resistance to P. psidii under field conditions in fourteen progenies from controlled crosses and self-crosses among four hybrid clones of Eucalyptus grandis Hill ex Maiden x Eucalyptus urophylla ST Blake that contrast for resistance to the fungus. Results indicated that resistance could be explained by one locus with main effects and at least three different alleles. However, loci with minor effects may influence the resistance, since variation on severity classes was observed. Differences in segregation of resistance between reciprocal crosses were not observed, indicating absence of cytoplasmic effects.

Water use and crop coefficient for hybrid DKB 390

Water use and crop coefficient for hybrid DKB 390. This work aims to characterize the water use of maize hybrid DKB 390 under suitable conditions of irrigation for both sufficient and below-optimal situations of nitrogen supply. Crop coefficient values for different stages are also presented as a result, in order to provide the basis for crop water budget and management throughout the cycle. A field experiment was carried Out during the main season, in which biomass, soil moisture, leaf area, climate data and light transmittance were evaluated. These have allowed deriving water balance, use and efficiency. The mentioned genotype requires around 600 nun for high yield targets, being less efficient when led under below-optimal nitrogen fertilization.

Modeling of transpiration reduction in van Genuchten-Mualem type soils

We derive an analytic expression for the matric flux potential (M) for van Genuchten-Mualem (VGM) type soils which can also be written in terms of a converging infinite series. Considering the first four terms of this series, the accuracy of the approximation was verified by comparing it to values of M estimated by numerical finite difference integration. Using values of the parameters for three soils from different texture classes, the proposed four-term approximation showed an almost perfect match with the numerical solution, except for effective saturations higher than 0.9. Including more terms reduced the discrepancy but also increased the complexity of the equation. The four-term equation can be used for most applications. Cases with special interest in nearly saturated soils should include more terms from the infinite series. A transpiration reduction function for use with the VGM equations is derived by combining the derived expression for M with a root water extraction model. The shape of the resulting reduction function and its dependency on the derivative of the soil hydraulic diffusivity D with respect to the soil water content theta is discussed. Positive and negative values of dD/d theta yield concave and convex or S-shaped reduction functions, respectively. On the basis of three data sets, the hydraulic properties of virtually all soils yield concave reduction curves. Such curves based solely on soil hydraulic properties do not account for the complex interactions between shoot growth, root growth, and water availability.

Spatial Modeling of a Soil Fertility Index using Visible-Near-Infrared Spectra and Terrain Attributes

Our objective was to develop a methodology to predict soil fertility using visible near-infrared (vis-NIR) diffuse reflectance spectra and terrain attributes derived from a digital elevation model (DEM). Specifically, our aims were to: (i) assemble a minimum data set to develop a soil fertility index for sugarcane (Sarcharum officinarum L.) (SFI-SC) for biofuel production in tropical soils; (ii) construct a model to predict the SFI-SC using soil vis-NIR spectra and terrain attributes; and (iii) produce a soil fertility map for our study area and assess it by comparing it with a green vegetation index (GVI). The study area was 185 ha located in sao Paulo State, Brazil. In total, 184 soil samples were collected and analyzed for a range of soil chemical and physical properties. Their vis-NIR spectra were collected from 400 to 2500 nm. The Shuttle Radar Topographic Mission 3-arcsec (90-m resolution) DEM of the area was used to derive 17 terrain attributes. A minimum data set of soil properties was selected to develop the SFI-SC. The SFI-SC consisted of three classes: Class 1, the highly fertile soils; Class 2, the fertile soils; and Class 3, the least fertile soils. It was derived heuristically with conditionals and using expert knowledge. The index was modeled with the spectra and terrain data using cross-validated decision trees. The cross-validation of the model correctly predicted Class 1 in 75% of cases, Class 2 in 61%, and Class 3 in 65%. A fertility map was derived for the study area and compared with a map of the GVI. Our approach offers a methodology that incorporates expert knowledge to derive the SFI-SC and uses a versatile spectro-spatial methodology that may be implemented for rapid and accurate determination of soil fertility and better exploration of areas suitable for production.