Identification of Composite Action Through Truck Load Testing

The continual increase of truck weights on our transportation system is a growing concern among bridge engineers. The load carrying capacity of the structures within the system must withstand this ever-growing demand. For multi-girder steel bridges, the load carrying capacity is heavily influenced by the presence of composite action between the girders and the concrete deck slab. While detailing to ensure reliable composite action is typically included in new designs, for many existing structures, the owner may not fully know the level of composite action. This may be due to administrative issues like insufficient original construction drawings or mechanical issues like breakdown of the shear transfer components. Even in situations where composite action was not intended there exists some partial interaction due to chemical bond and friction. Clearly understanding the presence and reliability of composite action in multi-girder structures is key to managing these structures effectively. This paper explores how load testing has been utilized to identify the level of composite action for existing bridges. The challenges associated with field identification of composite action are presented. In addition, three case studies of truck load testing are discussed. The first case utilized uncontrolled ambient truck measurements of an instrumented structure to field determine the composite behavior. The second and third cases perform a controlled load test with variations in truck weights and positions. Overall, the paper illustrates the advantages and disadvantages of truck load testing for identification of composite action and provides recommendations for future studies

Dense and accurate motion and strain estimation in high resolution speckle images using an image-adaptive approach

Digital image processing methods represent a viable and well acknowledged alternative to strain gauges and interferometric techniques for determining full-field displacements and strains in materials under stress. This paper presents an image adaptive technique for dense motion and strain estimation using high-resolution speckle images that show the analyzed material in its original and deformed states. The algorithm starts by dividing the speckle image showing the original state into irregular cells taking into consideration both spatial and gradient image information present. Subsequently the Newton-Raphson digital image correlation technique is applied to calculate the corresponding motion for each cell. Adaptive spatial regularization in the form of the Geman-McClure robust spatial estimator is employed to increase the spatial consistency of the motion components of a cell with respect to the components of neighbouring cells. To obtain the final strain information, local least-squares fitting using a linear displacement model is performed on the horizontal and vertical displacement fields. To evaluate the presented image partitioning and strain estimation techniques two numerical and two real experiments are employed. The numerical experiments simulate the deformation of a specimen with constant strain across the surface as well as small rigid-body rotations present while real experiments consist specimens that undergo uniaxial stress. The results indicate very good accuracy of the recovered strains as well as better rotation insensitivity compared to classical techniques

Haploinsufficiency for p190B RhoGAP inhibits MMTV-Neu tumor progression

Introduction: Rho signaling regulates key cellular processes including proliferation, survival, and migration, and it has been implicated in the development of many types of cancer including breast cancer. P190B Rho GTPase activating protein (RhoGAP) functions as a major inhibitor of the Rho GTPases. P190B is required for mammary gland morphogenesis, and overexpression of p190B in the mammary gland induces hyperplastic lesions. Hence, we hypothesized that p190B may play a pivotal role in mammary tumorigenesis. Methods: To investigate the effects of loss of p190B function on mammary tumor progression, p190B heterozygous mice were crossed with an MMTV-Neu breast cancer model. Effects of p190B deficiency on tumor latency, multiplicity, growth, preneoplastic progression and metastasis were evaluated. To investigate potential differences in tumor angiogenesis between the two groups, immunohistochemistry to detect von Willebrand factor was performed and quantified. To examine gene expression of potential mediators of the angiogenic switch, an angiogenesis PCR array was utilized and results were confirmed using immunohistochemistry. Finally, reciprocal transplantation of tumor fragments was performed to determine the impact of stromal deficiency of p190B on tumor angiogenesis. Results: P190B deficiency reduced tumor penetrance (53% of $p190B^{+/-}Neu$ mice vs. 100% of $p190B^{+/+}Neu$ mice formed tumors) and markedly delayed tumor onset by an average of 46 weeks. Tumor multiplicity was also decreased, but an increase in the number of preneoplastic lesions was detected indicating that p190B deficiency inhibited preneoplastic progression. Angiogenesis was decreased in the p190B heterozygous tumors, and expression of a potent angiogenic inhibitor, thrombospondin-1, was elevated in $p190B^{+/-}Neu$ mammary glands. Transplantation of $p190B^{+/-}Neu$ tumor fragments into wild-type recipients restored tumor angiogenesis. Strikingly, $p190B^{+/+}Neu$ tumor fragments were unable to grow when transplanted into $p190B^{+/-}Neu$ recipients. Conclusions: These data suggest that p190B haploinsufficiency in the epithelium inhibits MMTV-Neu tumor initiation. Furthermore, p190B deficiency in the vasculature is responsible, in part, for the inhibition of MMTV-Neu tumor progression

Digital Twin Technologies towards Understanding the Interactions between Transportation and Other Civil Infrastructure Systems

69A3551747119Digital Twin (DT) technology is the next step in the gradual shift from physical to digital models in civil engineering. Computer-Aided Drafting (CAD) revolutionized the industry by reducing the time and costs associated with documenting design. Building Information Modeling (BIM) has eliminated the need for physical design descriptors (i.e., drawings or physical models). DT models build off CAD and BIM but are utilized over the operational life of the infrastructure as a management tool. A DT is a relevant abstraction of the physical asset; it is most frequently used to model, improve, and control manufacturing systems. Civil engineering applications using DTs have been emerging, but transportation infrastructure represents a challenging extension of DT technology because of its spatial scale, as well as its voluminous and time-varying data. However, DT is a powerful decision support tool for the design, maintenance, and management of transportation infrastructure, particularly for studying its interdependencies with other infrastructure systems, which is of relevance to smart cities. The primary objective of this research was to explore the effectiveness of DT technology as a tool to visualize and understand interactions between transportation and other related civil infrastructure systems

Mantle reflectivity structure beneath oceanic hotspots

This study applies high-resolution Radon transform to a large set of SS precursors and explores the mantle reflectivity structure beneath 17 potentially ‘deep-rooted’ hotspots. The combined reduced time (Τ) and ray parameter ( p ) information effectively constrains the depth, spatial distribution and sharpness of upper-/mid-mantle reflectors. The olivine to wadsleyite phase boundary is deeper than the ocean and global averages and produces a dominant Τ– p domain signal. Laterally coherent observations of the deep 410-km seismic discontinuity, thin upper mantle transition zone and weak/absent 520-km reflector beneath hotspots make compelling arguments for large-scale, hot thermal anomalies in the top 400–600 km of the mantle. On the other hand, a relatively ‘flat’ and weak reflector at ∼653 km is inconsistent with ringwoodite to silicate perovskite + magnesiowÜstite transformation at temperatures greater than 2000 K. The lack of a negative correlation between topography and temperature implies (1) average or below-average temperatures at 600–700 km depths or (2) high temperatures and a dominating majorite garnet to Ca perovskite phase transformation. The proper choice between these two scenarios will directly impact the origin and depth of mantle plumes beneath hotspots. We further identify lower-mantle reflectors at 800–950 and 1100–1350 km depths beneath a number of the hotspots. Their presence implies that the chemistry and thermodynamics of the mid-mantle may be more complex than suggested by seismic tomography.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74768/1/j.1365-246X.2009.04242.x.pd

Consensus guidelines for the use and interpretation of angiogenesis assays

The formation of new blood vessels, or angiogenesis, is a complex process that plays important roles in growth and development, tissue and organ regeneration, as well as numerous pathological conditions. Angiogenesis undergoes multiple discrete steps that can be individually evaluated and quantified by a large number of bioassays. These independent assessments hold advantages but also have limitations. This article describes in vivo, ex vivo, and in vitro bioassays that are available for the evaluation of angiogenesis and highlights critical aspects that are relevant for their execution and proper interpretation. As such, this collaborative work is the first edition of consensus guidelines on angiogenesis bioassays to serve for current and future reference

Structural identification of a complex structure using both conventional and multiple model approaches

The confluence of a debilitated, often obsolete bridge population nearing the end of its design life with a massive shortfall of funding for rehabilitation and replacement has led to an unsustainable balancing act for bridge owners. One tool for addressing this issue is Structural Identification (St-Id), a six-step process for effectively integrating subjective information from visual inspections, with analytical modeling and experimental investigations to provide a more robust and defendable foundation for decision-making regarding constructed systems.In an effort to understand and document St-Id from a global perspective, the International Bridge Study (IBS) brought researchers from all over the world to demonstrate various techniques and technologies on a single test specimen in New Jersey. Through this application a comprehensive documentation of a best-practices application of St-Id was developed and numerous advances to each step of the process and their integration were achieved. These advances included formalization of the criteria for bridge selection as a candidate for St-Id, development of a framework for instrumentation design considering safety and test objectives, design and implementation of a distributed data acquisition system with a real-time visualization interface and spatially-correlated data interpretation.As part of this application some shortcomings associated with conventional model-experiment correlation approaches were identified. The second phase of the research aimed to develop and validate rigorous methods to mitigate these shortcomings. This research examined multiple-model approaches such Markov Chain Monte Carlo (MCMC) and multi-dimensional MCMC methods through both a benchmark numerical problem and the IBS Bridge. The primary findings in this phase included the difficulty in framing the problem to fully map the model space using Reversible Jump MCMC, an alternative approach through a multi-dimensional MCMC method, the difficulty in applying MCMC to actual bridges due to the complexity of the likelihood space and that MCMC can implicitly account for interaction between parameters through covariance and correlation coefficients. In general, the response predictions from the MCMC chains were more robust and informative than the results from the single model correlation.Ph.D., Structural Engineering -- Drexel University, 201

How to Select Typical Objects

In many practical situations, we have a large number of objects, too many to be able to thoroughly analyze each of them. To get a general understanding, we need to select a representative sample. For us, this problem was motivated to analyze the possible effect of an earthquake on buildings in El Paso, Texas. In this paper, we provide a reasonable formalization of this problem, and provide a feasible algorithm for solving thus formalized problem