Damage spreading transition in glasses: A probe for the ruggedness of the configurational landscape

We consider damage spreading transitions in the framework of mode-coupling theory. This theory describes relaxation processes in glasses in the mean-field approximation which are known to be characterized by the presence of an exponentially large number of metastable states. For systems evolving under identical but arbitrarily correlated noises, we demonstrate that there exists a critical temperature T0 which separates two different dynamical regimes depending on whether damage spreads or not in the asymptotic long-time limit. This transition exists for generic noise correlations such that the zero damage solution is stable at high temperatures, being minimal for maximal noise correlations. Although this dynamical transition depends on the type of noise correlations, we show that the asymptotic damage has the good properties of a dynamical order parameter, such as (i) independence of the initial damage; (ii) independence of the class of initial condition; and (iii) stability of the transition in the presence of asymmetric interactions which violate detailed balance. For maximally correlated noises we suggest that damage spreading occurs due to the presence of a divergent number of saddle points (as well as metastable states) in the thermodynamic limit consequence of the ruggedness of the free-energy landscape which characterizes the glassy state. These results are then compared to extensive numerical simulations of a mean-field glass model (the Bernasconi model) with Monte Carlo heat-bath dynamics. The freedom of choosing arbitrary noise correlations for Langevin dynamics makes damage spreading an interesting tool to probe the ruggedness of the configurational landscape.

Debris Mitigation Methods for Bridge Piers, Final Repory, June 2012

Debris accumulation on bridge piers is an on-going national problem that can obstruct the waterway openings at bridges and result in significant erosion of stream banks and scour at abutments and piers. In some cases, the accumulation of debris can adversely affect the operation of the waterway opening or cause failure of the structure. In addition, removal of debris accumulation is difficult, time consuming, and expensive for maintenance programs. This research involves a literature search of publications, products, and pier design recommendations that provide a cost effective method to mitigate debris accumulation at bridges. In addition, a nationwide survey was conducted to determine the state-of-the-practice and the results are presented within.

Effect of weather and climatological background on snow damage of forests in Southern Finland in November 1991

Summary

An Experimental Validation of a Statistical-Based Damage Detection Approach, January 2011

In this work, a previously-developed, statistical-based, damage-detection approach was validated for its ability to autonomously detect damage in bridges. The damage-detection approach uses statistical differences in the actual and predicted behavior of the bridge caused under a subset of ambient trucks. The predicted behavior is derived from a statistics-based model trained with field data from the undamaged bridge (not a finite element model). The differences between actual and predicted responses, called residuals, are then used to construct control charts, which compare undamaged and damaged structure data. Validation of the damage-detection approach was achieved by using sacrificial specimens that were mounted to the bridge and exposed to ambient traffic loads and which simulated actual damage-sensitive locations. Different damage types and levels were introduced to the sacrificial specimens to study the sensitivity and applicability. The damage-detection algorithm was able to identify damage, but it also had a high false-positive rate. An evaluation of the sub-components of the damage-detection methodology and methods was completed for the purpose of improving the approach. Several of the underlying assumptions within the algorithm were being violated, which was the source of the false-positives. Furthermore, the lack of an automatic evaluation process was thought to potentially be an impediment to widespread use. Recommendations for the improvement of the methodology were developed and preliminarily evaluated. These recommendations are believed to improve the efficacy of the damage-detection approach.

Evaluation of Mitigation for Safety Concerns on Low-Volume, Unpaved Rural Roads, 2013.

The Institute for Transportation (InTrans) at Iowa State University completed work on an in-depth study of crash history on lowvolume, rural roads in Iowa in December 2010. Results indicated that unpaved roads with traffic volumes greater than 100 vehicles per day (vpd) exhibit significantly higher crash frequencies, rates, and densities than any other class of low-volume road examined, paved or unpaved. The total mileage for this class of roadway in Iowa is only about 4,400 miles, spread over 99 counties in the state, which is certainly a manageable number of miles for individual rural agencies. The purpose of this study was to identify and examine several unpaved, local road segments with higher than average crash frequencies, select and undertake potentially-beneficial mitigation, and evaluate the results as time allowed. A variety of low-cost options were considered, including engineering improvements, enhanced efforts by law enforcement, and educational initiatives. Using input, active support, and participation from local agencies and state and Federal safety advocates, the study afforded a unique opportunity to examine useful tools for local rural agencies to utilize in addressing safety on this particular type of roadway.

Evaluation of Mitigation for Safety Concerns on Low-Volume, Unpaved Rural Roads: Tech Transfer Summary, 2013.

The Institute for Transportation (InTrans) at Iowa State University completed work on an in-depth study of crash history on lowvolume, rural roads in Iowa in December 2010. Results indicated that unpaved roads with traffic volumes greater than 100 vehicles per day (vpd) exhibit significantly higher crash frequencies, rates, and densities than any other class of low-volume road examined, paved or unpaved. The total mileage for this class of roadway in Iowa is only about 4,400 miles, spread over 99 counties in the state, which is certainly a manageable number of miles for individual rural agencies. The purpose of this study was to identify and examine several unpaved, local road segments with higher than average crash frequencies, select and undertake potentially-beneficial mitigation, and evaluate the results as time allowed. A variety of low-cost options were considered, including engineering improvements, enhanced efforts by law enforcement, and educational initiatives. Using input, active support, and participation from local agencies and state and Federal safety advocates, the study afforded a unique opportunity to examine useful tools for local rural agencies to utilize in addressing safety on this particular type of roadway.

Integration of Bridge Damage Detection Concepts and Components (3 volumes), TR-636, 2013

This work is divided into three volumes: Volume I: Strain-Based Damage Detection; Volume II: Acceleration-Based Damage Detection; Volume III: Wireless Bridge Monitoring Hardware. Volume I: In this work, a previously-developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The statistical damage-detection tool, control-chart-based damage-detection methodologies, were further investigated and advanced. For the validation of the damage-detection approaches, strain data were obtained from a sacrificial specimen attached to the previously-utilized US 30 Bridge over the South Skunk River (in Ames, Iowa), which had simulated damage,. To provide for an enhanced ability to detect changes in the behavior of the structural system, various control chart rules were evaluated. False indications and true indications were studied to compare the damage detection ability in regard to each methodology and each control chart rule. An autonomous software program called Bridge Engineering Center Assessment Software (BECAS) was developed to control all aspects of the damage detection processes. BECAS requires no user intervention after initial configuration and training. Volume II: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The objective of this part of the project was to validate/integrate a vibration-based damage-detection algorithm with the strain-based methodology formulated by the Iowa State University Bridge Engineering Center. This report volume (Volume II) presents the use of vibration-based damage-detection approaches as local methods to quantify damage at critical areas in structures. Acceleration data were collected and analyzed to evaluate the relationships between sensors and with changes in environmental conditions. A sacrificial specimen was investigated to verify the damage-detection capabilities and this volume presents a transmissibility concept and damage-detection algorithm that show potential to sense local changes in the dynamic stiffness between points across a joint of a real structure. The validation and integration of the vibration-based and strain-based damage-detection methodologies will add significant value to Iowa’s current and future bridge maintenance, planning, and management Volume III: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. This report volume (Volume III) summarizes the energy harvesting techniques and prototype development for a bridge monitoring system that uses wireless sensors. The wireless sensor nodes are used to collect strain measurements at critical locations on a bridge. The bridge monitoring hardware system consists of a base station and multiple self-powered wireless sensor nodes. The base station is responsible for the synchronization of data sampling on all nodes and data aggregation. Each wireless sensor node include a sensing element, a processing and wireless communication module, and an energy harvesting module. The hardware prototype for a wireless bridge monitoring system was developed and tested on the US 30 Bridge over the South Skunk River in Ames, Iowa. The functions and performance of the developed system, including strain data, energy harvesting capacity, and wireless transmission quality, were studied and are covered in this volume.

Different types of cell death are involved in brain damage of methylmalonic aciduria and glutaric aciduria type I

We previously showed that exposure of 3D organotypic rat brain cell cultures to 1mM 2-methylcitrate (2-MCA) or 3-hydroxyglutarate (3- OHGA) every 12h over three days (DIV11-DIV14) results in ammonium accumulation and cell death. The aim of this study was to define the time course (every 24h) of the observed effects. Ammonium in culture medium already increased at DIV12 staying stable on the following days under 3-OHGA exposure, while it increased consecutively up to much higher levels under 2-MCA exposure. Lactate increase and glucose decrease were observed from DIV13 and DIV14, respectively. We conclude that ammonium accumulation precedes alterations of energy metabolism. As observed by immunohistochemistry glial cells were the predominant dying cells. Immunoblotting and immunohistochemistry with cell death specific markers (caspase-3, alpha-fodrin, LC3) showed that 2-MCA exposure significantly increased apoptosis on DIV14, but did not alter autophagy or necrosis. In contrast, 3-OHGA exposure substantially increased necrosis already from DIV13, while no change was observed for apoptosis and autophagy. In conclusion, ammonium accumulation, secondary disturbance of energy metabolism and glial cell death are involved in the neuropathogenesis ofmethylmalonic aciduria and glutaric aciduria type I. Interestingly, brain cells are dying by necrosis under 3-OHGA exposure and by apoptosis under 2-MCA exposure.

GIS-based debris flow source and runout susceptibility assessment from DEM data - a case study in NW Nicaragua

In October 1998, Hurricane Mitch triggered numerous landslides (mainly debris flows) in Honduras and Nicaragua, resulting in a high death toll and in considerable damage to property. The potential application of relatively simple and affordable spatial prediction models for landslide hazard mapping in developing countries was studied. Our attention was focused on a region in NW Nicaragua, one of the most severely hit places during the Mitch event. A landslide map was obtained at 1:10 000 scale in a Geographic Information System (GIS) environment from the interpretation of aerial photographs and detailed field work. In this map the terrain failure zones were distinguished from the areas within the reach of the mobilized materials. A Digital Elevation Model (DEM) with 20 m×20 m of pixel size was also employed in the study area. A comparative analysis of the terrain failures caused by Hurricane Mitch and a selection of 4 terrain factors extracted from the DEM which, contributed to the terrain instability, was carried out. Land propensity to failure was determined with the aid of a bivariate analysis and GIS tools in a terrain failure susceptibility map. In order to estimate the areas that could be affected by the path or deposition of the mobilized materials, we considered the fact that under intense rainfall events debris flows tend to travel long distances following the maximum slope and merging with the drainage network. Using the TauDEM extension for ArcGIS software we generated automatically flow lines following the maximum slope in the DEM starting from the areas prone to failure in the terrain failure susceptibility map. The areas crossed by the flow lines from each terrain failure susceptibility class correspond to the runout susceptibility classes represented in a runout susceptibility map. The study of terrain failure and runout susceptibility enabled us to obtain a spatial prediction for landslides, which could contribute to landslide risk mitigation.