Multiscale modeling of delamination fracture in multilayered structures

In the recent years, there has been increased interest in using multilayered structures in the construction of mechanical devices and vehicles, such as turbines, wind-blades, aircrafts or ships. These structures are often subjected to severe mechanical loads and a wide range of operational temperatures. Under such loading conditions, the stresses in multilayered structures may exceed the elastic limit, and delaminations and debonds may form and propagate as a consequence of the high interfacial tractions caused by the inhomogeneous material structure. To design layered systems and define their load-bearing capacity and life, accurate understanding of their mechanical behavior in the elastic and post-elastic regimes is needed

Uncovering the Facebook Experience: Insights into Users’ Behavior and Motivations

Academic literature on Facebook in the fields of management, economics and psychology is reviewed in this article, where we focus on users of this social network to understand why they signed up, how they form networks and how they engage, and how companies can exploit and benefit from Facebook. Although many interesting topics have been covered, the study clearly reveals that much of the work done so far has been limited to certain situations, it analyzes the strengths and weaknesses of the studies, and suggests avenues of research for the future

Latent Ties: Reconnection of Organizations to Boost Innovation

This paper highlights the temporality dimension of ties. Doing so we respond to recent calls for a more dynamic and processual understanding of networks. We proposed a model in which two antecedents of latent ties, network similarity, and length of the tie, will be tested. Also, our study addresses the relationship between tie latency and innovation. The model tests the impact of the interaction between the number of latent and strong ties on organizations innovative output will be studied. The study highlights the significance of latent ties in coping with the problems of redundancy of dense network and overloading of new weak ties

Mode II dominant fracture of layered composite beams and wide-plates: a homogenized structural approach

Brittle delamination fracture under Mode II dominant conditions in unidirectional composite and layered beams and wide-plates is studied using a homogenized structural model based on a zigzag approach. The model captures the unstable propagation of cracks, snap-back and -through instabilities, the effects of the interaction of multiple cracks on the macrostructural response and of the layered structure on the energy release rate. The layered structure and the delaminations are described by introducing local enrichments, in the form of zigzag functions and cohesive interfaces, to a classical first-order shear deformation plate theory. The model applies to layers with principal material directions parallel to the geometrical axes, depends on only three displacement variables and the solution of specific problems requires only in-plane discretization, for any numbers of layers and delaminations. Closed form solutions are derived for the energy release rate in bi-material beams and applications are presented to homogeneous, bi-material and layered, simply supported and cantilever, bend-beams, with one and two delaminations

Short-term crash risk prediction considering proactive, reactive, and driver behavior factors

Providing a safe and efficient transportation system is the primary goal of transportation engineering and planning. Highway crashes are among the most significant challenges to achieving this goal. They result in significant societal toll reflected in numerous fatalities, personal injuries, property damage, and traffic congestion. To that end, much attention has been given to predictive models of crash occurrence and severity. Most of these models are reactive: they use the data about crashes that have occurred in the past to identify the significant crash factors, crash hot-spots and crash-prone roadway locations, analyze and select the most effective countermeasures for reducing the number and severity of crashes. More recently, the advancements have been made in developing proactive crash risk models to assess short-term crash risks in near-real time. Such models could be applied as part of traffic management strategies to prevent and mitigate the crashes. The driver behavior is found to be the leading cause of highway crashes. Nevertheless, due to data unavailability, limited studies have explored and quantified the role of driver behavior in crashes. The Strategic Highway Research Program Naturalistic Driving Study (SHRP 2 NDS) offers an unprecedented opportunity to perform an in-depth analysis of the impacts of driver behavior on crashes events. The research presented in this dissertation is divided into three parts, corresponding to the research objectives. The first part investigates the application of advanced data modeling methods for proactive crash risk analysis. Several proactive models for segment level crash risk and severity assessment are developed and tested, considering the proactive data available to most transportation agencies in real time at a regional network scale. The data include roadway geometry characteristics, traffic flow characteristics, and weather condition data. The analysis methods include Random-effect Bayesian Logistics Regression, Random Forest, Gradient Boosting Machine, K-Nearest Neighbor, Gaussian Naive Bayes (GNB), and Multi-layer Feedforward Deep Neural Network (MLFDNN). The random oversampling technique is applied to deal with the problem of data imbalance associated with the injury severity analysis. The model training and testing are completed using a dataset containing records of 10,155 crashes that occurred on two interstate highways in New Jersey over a period of two years. The second part of the study analyzes the potential improvement in the prediction abilities of the proposed models by adding reactive data (such as vehicle characteristics and driver characteristics) to the analysis. Commonly, the reactive data is only available (known) after the crash occurs. In the proposed research, the crash analysis is performed by classifying crashes in multiple groupings (instead of a single group), constructed based on the age of drivers and vehicles to account for the impact of reactive data on driver injury severity outcomes. The results of the second part of the study show that while the simultaneous use of reactive and proactive data can improve the prediction performance of the models, the absolute crash probability values must be further improved for operational crash risk prediction. To this end, in the third part of the study, the Naturalistic Driving Study data is used to calibrate the crash risk models, including the driver behavior risk factors. The findings show significant improvement in crash prediction accuracy with the inclusion of driver behavior risk factors, which confirms the driver behavior to be the most critical risk factor affecting the crash likelihood and the associated injury severity

THE EFFECT OF PLANTING DISTANCE AND TYPES OF MANURE ON THE GROWTH AND BIOMASS OF INDIGOFERA

The study aims to determine the effect of planting distance and types of manure on the growth and biomass of Indigofera plants. The study was conducted in practice garden of Faculty of Agriculture UPN “Veteran” Yogyakarta, is a field experiment using a Complete Randomized Group Design consisting of J1: planting distance 1 m x 1 m ; J2: 1 m x 1,25 m ; J3: 1 m x 1,5 m ; J4: 1 m x 1,75 m. The second factor is types of manure, which consist of: M1: cow manure dosage 20 t/ha; M2: goat manure dosage 20 t/ha. The study result shows that there is no interaction between planting distance and types of manure toward growth and biomass yield of Indigofera plant. The planting distance treatment of 1 m x 1 m (J1) and planting distance of 1 m x 1,5 m (J3) gives insignificant influence on all parameters observed at 9 weeks observation after planting. The manure types treatment gives insignificant difference on all observed parameters.Keyword: planting distance, manure, indigofer