Comparison of dynamic effects of high-speed traffic load on ballasted track using a simplified two-dimensional and full three-dimensional model.

The vertical dynamic actions transmitted by railway vehicles to the ballasted track infrastructure is evaluated taking into account models with different degree of detail. In particular, we have studied this matter from a two-dimensional (2D) finite element model to a fully coupled three-dimensional (3D) multi-body finite element model. The vehicle and track are coupled via a non-linear Hertz contact mechanism. The method of Lagrange multipliers is used for the contact constraint enforcement between wheel and rail. Distributed elevation irregularities are generated based on power spectral density (PSD) distributions which are taken into account for the interaction. The numerical simulations are performed in the time domain, using a direct integration method for solving the transient problem due to the contact nonlinearities. The results obtained include contact forces, forces transmitted to the infrastructure (sleeper) by railpads and envelopes of relevant results for several track irregularities and speed ranges. The main contribution of this work is to identify and discuss coincidences and differences between discrete 2D models and continuum 3D models, as wheel as assessing the validity of evaluating the dynamic loading on the track with simplified 2D models

Background traffic modeling for large-scale network simulation

Network simulation is an indispensable tool for studying Internet-scale networks due to the heterogeneous structure, immense size and changing properties. It is crucial for network simulators to generate representative traffic, which is necessary for effectively evaluating next-generation network protocols and applications. With network simulation, we can make a distinction between foreground traffic, which is generated by the target applications the researchers intend to study and therefore must be simulated with high fidelity, and background traffic, which represents the network traffic that is generated by other applications and does not require significant accuracy. The background traffic has a significant impact on the foreground traffic, since it competes with the foreground traffic for network resources and therefore can drastically affect the behavior of the applications that produce the foreground traffic. This dissertation aims to provide a solution to meaningfully generate background traffic in three aspects. First is realism. Realistic traffic characterization plays an important role in determining the correct outcome of the simulation studies. This work starts from enhancing an existing fluid background traffic model by removing its two unrealistic assumptions. The improved model can correctly reflect the network conditions in the reverse direction of the data traffic and can reproduce the traffic burstiness observed from measurements. Second is scalability. The trade-off between accuracy and scalability is a constant theme in background traffic modeling. This work presents a fast rate-based TCP (RTCP) traffic model, which originally used analytical models to represent TCP congestion control behavior. This model outperforms other existing traffic models in that it can correctly capture the overall TCP behavior and achieve a speedup of more than two orders of magnitude over the corresponding packet-oriented simulation. Third is network-wide traffic generation. Regardless of how detailed or scalable the models are, they mainly focus on how to generate traffic on one single link, which cannot be extended easily to studies of more complicated network scenarios. This work presents a cluster-based spatio-temporal background traffic generation model that considers spatial and temporal traffic characteristics as well as their correlations. The resulting model can be used effectively for the evaluation work in network studies.

Background Traffic Modeling for Large-Scale Network Simulation

Network simulation is an indispensable tool for studying Internet-scale networks due to the heterogeneous structure, immense size and changing properties. It is crucial for network simulators to generate representative traffic, which is necessary for effectively evaluating next-generation network protocols and applications. With network simulation, we can make a distinction between foreground traffic, which is generated by the target applications the researchers intend to study and therefore must be simulated with high fidelity, and background traffic, which represents the network traffic that is generated by other applications and does not require significant accuracy. The background traffic has a significant impact on the foreground traffic, since it competes with the foreground traffic for network resources and therefore can drastically affect the behavior of the applications that produce the foreground traffic. This dissertation aims to provide a solution to meaningfully generate background traffic in three aspects. First is realism. Realistic traffic characterization plays an important role in determining the correct outcome of the simulation studies. This work starts from enhancing an existing fluid background traffic model by removing its two unrealistic assumptions. The improved model can correctly reflect the network conditions in the reverse direction of the data traffic and can reproduce the traffic burstiness observed from measurements. Second is scalability. The trade-off between accuracy and scalability is a constant theme in background traffic modeling. This work presents a fast rate-based TCP (RTCP) traffic model, which originally used analytical models to represent TCP congestion control behavior. This model outperforms other existing traffic models in that it can correctly capture the overall TCP behavior and achieve a speedup of more than two orders of magnitude over the corresponding packet-oriented simulation. Third is network-wide traffic generation. Regardless of how detailed or scalable the models are, they mainly focus on how to generate traffic on one single link, which cannot be extended easily to studies of more complicated network scenarios. This work presents a cluster-based spatio-temporal background traffic generation model that considers spatial and temporal traffic characteristics as well as their correlations. The resulting model can be used effectively for the evaluation work in network studies.

Association between Long-Term Exposure to Traffic-Related Air Pollution and Subclinical Atherosclerosis: The REGICOR Study

Background: Epidemiological evidence of the effects of long-term exposure to air pollu tion on the chronic processes of athero genesis is limited. Objective: We investigated the association of long-term exposure to traffic-related air pollu tion with subclinical atherosclerosis, measured by carotid intima media thickness (IMT) and ankle–brachial index (ABI). Methods: We performed a cross-sectional analysis using data collected during the reexamination (2007–2010) of 2,780 participants in the REGICOR (Registre Gironí del Cor: the Gerona Heart Register) study, a population-based prospective cohort in Girona, Spain. Long-term exposure across residences was calculated as the last 10 years’ time-weighted average of residential nitrogen dioxide (NO2) estimates (based on a local-scale land-use regression model), traffic intensity in the nearest street, and traffic intensity in a 100 m buffer. Associations with IMT and ABI were estimated using linear regression and multinomial logistic regression, respectively, controlling for sex, age, smoking status, education, marital status, and several other potential confounders or intermediates. Results: Exposure contrasts between the 5th and 95th percentiles for NO2 (25 μg/m), traffic intensity in the nearest street (15,000 vehicles/day), and traffic load within 100 m (7,200,000 vehicle-m/day) were associated with differences of 0.56% (95% CI: –1.5, 2.6%), 2.32% (95% CI: 0.48, 4.17%), and 1.91% (95% CI: –0.24, 4.06) percent difference in IMT, respectively. Exposures were positively associated with an ABI of > 1.3, but not an ABI of < 0.9. Stronger associations were observed among those with a high level of education and in men ≥ 60 years of age. Conclusions: Long-term traffic-related exposures were associated with subclinical markers of atherosclerosis. Prospective studies are needed to confirm associations and further examine differences among population subgroups.key words: ankle–brachial index, average daily traffic, cardiovascular disease, exposure assessment, exposure to tailpipe emissions, intima media thickness, land use regression model, Mediterranean diet, nitrogen dioxide

Impact of a program for the prevention of traffic accidents in a Southern Brazilian city: a model for implementation in a developing country

Background: Traffic accidents constitute the main cause of death in the first decades of life. Traumatic brain injury is the event most responsible for the severity of these accidents. The SBN started an educational program for the prevention of traffic accidents, adapted from the American model ""Think First"" to the Brazilian environment, since 1995, with special effort devoted to the prevention of TBI by using seat belts and motorcycle helmets. The objective of the present study was to set up a traffic accident prevention program based on the adapted Think First and to evaluate its impact by comparing epidemiological variables before and after the beginning of the program. Methods: The program was executed in Maringa city, from September 2004 to August 2005, with educational actions targeting the entire population, especially teenagers and young adults. The program was implemented by building a network of information facilitators and multipliers inside the organized civil society, with widespread population dissemination. To measure the impact of the program, a specific software was developed for the storage and processing of the epidemiological variables. Results: The results showed a reduction of trauma severity due to traffic accidents after the execution of the program, mainly TBI. Conclusions: The adapted Think First was systematically implemented and its impact measured for the first time in Brazil, revealing the usefulness of the program for reducing trauma and TBI severity in traffic accidents through public education and representing a standardized model of implementation in a developing country. (C) 2009 Elsevier Inc. All rights reserved.

Association of education and receiving social transfers with allostatic load in the Swiss population-based CoLaus study.

BACKGROUND: Allostatic load reflects cumulative exposure to stressors throughout lifetime and has been associated with several adverse health outcomes. It is hypothesized that people with low socioeconomic status (SES) are exposed to higher chronic stress and have therefore greater levels of allostatic load. OBJECTIVE: To assess the association of receiving social transfers and low education with allostatic load. METHODS: We included 3589 participants (1812 women) aged over 35years and under retirement age from the population-based CoLaus study (Lausanne, Switzerland, 2003-2006). We computed an allostatic load index aggregating cardiovascular, metabolic, dyslipidemic and inflammatory markers. A novel index additionally including markers of oxidative stress was also examined. RESULTS: Men with low vs. high SES were more likely to have higher levels of allostatic load (odds ratio (OR)=1.93/2.34 for social transfers/education, 95%CI from 1.45 to 4.17). The same patterns were observed among women. Associations persisted after controlling for health behaviors and marital status. CONCLUSIONS: Low education and receiving social transfers independently and cumulatively predict high allostatic load and dysregulation of several homeostatic systems in a Swiss population-based study. Participants with low SES are at higher risk of oxidative stress, which may justify its inclusion as a separate component of allostatic load.

MaxMAC: a Maximally Traffic-Adaptive MAC Protocol for Wireless Sensor Networks

Energy efficiency is a major concern in the design of Wireless Sensor Networks (WSNs) and their communication protocols. As the radio transceiver typically accounts for a major portion of a WSN node’s power consumption, researchers have proposed Energy-Efficient Medium Access (E2-MAC) protocols that switch the radio transceiver off for a major part of the time. Such protocols typically trade off energy-efficiency versus classical quality of service parameters (throughput, latency, reliability). Today’s E2-MAC protocols are able to deliver little amounts of data with a low energy footprint, but introduce severe restrictions with respect to throughput and latency. Regrettably, they yet fail to adapt to varying traffic load at run-time. This paper presents MaxMAC, an E2-MAC protocol that targets at achieving maximal adaptivity with respect to throughput and latency. By adaptively tuning essential parameters at run-time, the protocol reaches the throughput and latency of energy-unconstrained CSMA in high-traffic phases, while still exhibiting a high energy-efficiency in periods of sparse traffic. The paper compares the protocol against a selection of today’s E2-MAC protocols and evaluates its advantages and drawbacks.

Traffic-Adaptive and Link-Quality-Aware Communication in Wireless Sensor Networks

This paper is a summary of the main contribu- tions of the PhD thesis published in [1]. The main research contributions of the thesis are driven by the research question how to design simple, yet efficient and robust run-time adaptive resource allocation schemes within the commu- nication stack of Wireless Sensor Network (WSN) nodes. The thesis addresses several problem domains with con- tributions on different layers of the WSN communication stack. The main contributions can be summarized as follows: First, a a novel run-time adaptive MAC protocol is intro- duced, which stepwise allocates the power-hungry radio interface in an on-demand manner when the encountered traffic load requires it. Second, the thesis outlines a metho- dology for robust, reliable and accurate software-based energy-estimation, which is calculated at network run- time on the sensor node itself. Third, the thesis evaluates several Forward Error Correction (FEC) strategies to adap- tively allocate the correctional power of Error Correcting Codes (ECCs) to cope with timely and spatially variable bit error rates. Fourth, in the context of TCP-based communi- cations in WSNs, the thesis evaluates distributed caching and local retransmission strategies to overcome the perfor- mance degrading effects of packet corruption and trans- mission failures when transmitting data over multiple hops. The performance of all developed protocols are eval- uated on a self-developed real-world WSN testbed and achieve superior performance over selected existing ap- proaches, especially where traffic load and channel condi- tions are suspect to rapid variations over time.

Traffic based energy consumption optimisation to improve the lifetime and performance of ad hoc wireless sensor networks

Ad hoc wireless sensor networks (WSNs) are formed from self-organising configurations of distributed, energy constrained, autonomous sensor nodes. The service lifetime of such sensor nodes depends on the power supply and the energy consumption, which is typically dominated by the communication subsystem. One of the key challenges in unlocking the potential of such data gathering sensor networks is conserving energy so as to maximize their post deployment active lifetime. This thesis described the research carried on the continual development of the novel energy efficient Optimised grids algorithm that increases the WSNs lifetime and improves on the QoS parameters yielding higher throughput, lower latency and jitter for next generation of WSNs. Based on the range and traffic relationship the novel Optimised grids algorithm provides a robust traffic dependent energy efficient grid size that minimises the cluster head energy consumption in each grid and balances the energy use throughout the network. Efficient spatial reusability allows the novel Optimised grids algorithm improves on network QoS parameters. The most important advantage of this model is that it can be applied to all one and two dimensional traffic scenarios where the traffic load may fluctuate due to sensor activities. During traffic fluctuations the novel Optimised grids algorithm can be used to re-optimise the wireless sensor network to bring further benefits in energy reduction and improvement in QoS parameters. As the idle energy becomes dominant at lower traffic loads, the new Sleep Optimised grids model incorporates the sleep energy and idle energy duty cycles that can be implemented to achieve further network lifetime gains in all wireless sensor network models. Another key advantage of the novel Optimised grids algorithm is that it can be implemented with existing energy saving protocols like GAF, LEACH, SMAC and TMAC to further enhance the network lifetimes and improve on QoS parameters. The novel Optimised grids algorithm does not interfere with these protocols, but creates an overlay to optimise the grids sizes and hence transmission range of wireless sensor nodes.

Traffic congestion control in communication networks

Next generation networks are characterized by ever increasing complexity, intelligence, heterogeneous technologies and increasing user expectations. Telecommunication networks in particular have become truly global, consisting of a variety of national and regional networks, both wired and wireless. Consequently, the management of telecommunication networks is becoming increasingly complex. In addition, network security and reliability requirements require additional overheads which increase the size of the data records. This in turn causes acute network traffic congestions. There is no single network management methodology to control the various requirements of today's networks, and provides a good level of Quality of Service (QoS), and network security. Therefore, an integrated approach is needed in which a combination of methodologies can provide solutions and answers to network events (which cause severe congestions and compromise the quality of service and security). The proposed solution focused on a systematic approach to design a network management system based upon the recent advances in the mobile agent technologies. This solution has provided a new traffic management system for telecommunication networks that is capable of (1) reducing the network traffic load (thus reducing traffic congestion), (2) overcoming existing network latency, (3) adapting dynamically to the traffic load of the system, (4) operating in heterogeneous environments with improved security, and (5) having robust and fault tolerance behavior. This solution has solved several key challenges in the development of network management for telecommunication networks using mobile agents. We have designed several types of agents, whose interactions will allow performing some complex management actions, and integrating them. Our solution is decentralized to eliminate excessive bandwidth usage and at the same time has extended the capabilities of the Simple Network Management Protocol (SNMP). Our solution is fully compatible with the existing standards.

Predictive and distributed routing balancing (PR-DRB): high speed interconnection networks

Current parallel applications running on clusters require the use of an interconnection network to perform communications among all computing nodes available. Imbalance of communications can produce network congestion, reducing throughput and increasing latency, degrading the overall system performance. On the other hand, parallel applications running on these networks posses representative stages which allow their characterization, as well as repetitive behavior that can be identified on the basis of this characterization. This work presents the Predictive and Distributed Routing Balancing (PR-DRB), a new method developed to gradually control network congestion, based on paths expansion, traffic distribution and effective traffic load, in order to maintain low latency values. PR-DRB monitors messages latencies on intermediate routers, makes decisions about alternative paths and record communication pattern information encountered during congestion situation. Based on the concept of applications repetitiveness, best solution recorded are reapplied when saved communication pattern re-appears. Traffic congestion experiments were conducted in order to evaluate the performance of the method, and improvements were observed.

On The Spot Damage Detection Methodology for Highway Bridges, July 2010

Vibration-based damage identification (VBDI) techniques have been developed in part to address the problems associated with an aging civil infrastructure. To assess the potential of VBDI as it applies to highway bridges in Iowa, three applications of VBDI techniques were considered in this study: numerical simulation, laboratory structures, and field structures. VBDI techniques were found to be highly capable of locating and quantifying damage in numerical simulations. These same techniques were found to be accurate in locating various types of damage in a laboratory setting with actual structures. Although there is the potential for these techniques to quantify damage in a laboratory setting, the ability of the methods to quantify low-level damage in the laboratory is not robust. When applying these techniques to an actual bridge, it was found that some traditional applications of VBDI methods are capable of describing the global behavior of the structure but are most likely not suited for the identification of typical damage scenarios found in civil infrastructure. Measurement noise, boundary conditions, complications due to substructures and multiple material types, and transducer sensitivity make it very difficult for present VBDI techniques to identify, much less quantify, highly localized damage (such as small cracks and minor changes in thickness). However, while investigating VBDI techniques in the field, it was found that if the frequency-domain response of the structure can be generated from operating traffic load, the structural response can be animated and used to develop a holistic view of the bridge’s response to various automobile loadings. By animating the response of a field bridge, concrete cracking (in the abutment and deck) was correlated with structural motion and problem frequencies (i.e., those that cause significant torsion or tension-compression at beam ends) were identified. Furthermore, a frequency-domain study of operational traffic was used to identify both common and extreme frequencies for a given structure and loading. Common traffic frequencies can be compared to problem frequencies so that cost-effective, preventative solutions (either structural or usage-based) can be developed for a wide range of IDOT bridges. Further work should (1) perfect the process of collecting high-quality operational frequency response data; (2) expand and simplify the process of correlating frequency response animations with damage; and (3) develop efficient, economical, preemptive solutions to common damage types.

On the spot damage detection methodology for highway bridges (tech transfer summary)

The objective of this work was to develop a low-cost portable damage detection tool to assess and predict damage areas in highway bridges. The proposed tool was based on standard vibration-based damage identification (VBDI) techniques but was extended to a new approach based on operational traffic load. The methodology was tested using numerical simulations, laboratory experiments, and field testing.

Structural Analysis of Aggregate Blends Using the SHRP Gyratory Compactor, MLR-95-8, 1996

The Iowa Department of Transportation (IDOT) received a Strategic Highway Research Program (SHRP) gyratory compactor in December 1994. Since then IDOT has been studying the ability of the compactor to analyze fundamental properties of aggregates such as shape, texture, and gradation by studying the volumetrics of the aggregate blends under a standard load using the SHRP gyratory compactor. This method of analyzing the volumetrics of aggregate blends is similar to SHRP's fine aggregate angularity procedure, which analyzes void levels in noncompacted aggregate blends, which in turn can be used to evaluate the texture or shape of aggregates, what SHRP refers to as angularity. Research is showing that by splitting the aggregate blend on the 2.36-mm (#8) sieve and analyzing the volumetrics or angularity of the separated blend, important fundamental properties can be determined. Most important is structure (the degree and location of aggregate interlock). In addition, analysis of the volumes of the coarse and fine portions can predict the voids in the mineral aggregate and the desired asphalt content. By predicting these properties, it can be determined whether the combined aggregate blend, when mixed with asphalt cement, will produce a mix with structural adequacy to carry the designed traffic load.