Design of a bridge bumper to protect bridge girders against collisions of overheight vehicles

Bridges with low clearance are vulnerable to collision with overheight vehicles. Collisions of overheight vehicles can cause fatalities and injuries to the drivers and passengers of the overheight vehicles, and damage to bridge girders. The repair of the damaged bridges can be costly and time consuming. This research investigates the feasibility of developing a bridge bumper that minimizes the physical injuries and the likelihood of fatalities and protects the structural elements of bridges by absorbing the impact energy. The thesis describes a small-scale impact experiment using the proposed bridge bumper with several options of energy absorbing materials to protect a reinforced concrete beam. A finite element analysis is done to simulate the small-scale impact experiments. Optimization of the finite element model is carried out for the response quantities of interest with respect to the geometrical parameters and the material properties of the proposed bridge bumper. Such analysis can guide the design of an optimal bridge bumper that maximizes the energy dissipation and minimizes the damage to the bridge girder and the likelihood of fatalities and injuries

A Chronological Survey of Theoretical Advancements in Generative Adversarial Networks for Computer Vision

Generative Adversarial Networks (GANs) have been workhorse generative models for last many years, especially in the research field of computer vision. Accordingly, there have been many significant advancements in the theory and application of GAN models, which are notoriously hard to train, but produce good results if trained well. There have been many a surveys on GANs, organizing the vast GAN literature from various focus and perspectives. However, none of the surveys brings out the important chronological aspect: how the multiple challenges of employing GAN models were solved one-by-one over time, across multiple landmark research works. This survey intends to bridge that gap and present some of the landmark research works on the theory and application of GANs, in chronological order

Performance-Based Reliability Analysis and Code Calibration for RC Column Subject to Vehicle Collision

Infrastructure and transportation facilities have increased rapidly over the years. The progress has been accompanied by an increasing number of vehicle collisions with structures. This type of collision might lead to the damage, and often, collapse of the structure. In reinforced concrete (RC) structures, columns are usually the most vulnerable members exposed to collisions. However, the existing design guidelines and provisions for protection of these members against collision of vehicles are not adequate. In particular, the desired behavior and the associated performance levels of a structure during a vehicle collision are not defined. Therefore, there is need to assess the vulnerability of structures against such collisions. This research aims to develop a framework for the performance-based analysis and design of RC columns subject to vehicle impact. It helps mitigate maximum damage and achieve an economical design. The current research takes into account performance-based analysis and design as opposed to only collapse prevention design. The performance level is tied to the impact levels to estimate the reliability of the RC column for the desired performance objectives. The performance-based probabilistic models for estimating shear resistance of RC column and shear demand on RC column are developed. The reliability of the RC column subject for selected performance levels is evaluated. The performance levels are tied to impact demand and load and resistance factors are proposed to achieve desired performance objectives of the RC column subject to vehicle collision

Optimal Folding of Data Flow Graphs based on Finite Projective Geometry using Lattice Embedding

A number of computations exist, especially in area of error-control coding and matrix computations, whose underlying data flow graphs are based on finite projective-geometry(PG) based balanced bipartite graphs. Many of these applications are actively being researched upon. Almost all these applications need bipartite graphs of the order of tens of thousands in practice, whose nodes represent parallel computations. To reduce its implementation cost, reducing amount of system/hardware resources during design is an important engineering objective. In this context, we present a scheme to reduce resource utilization when performing computations derived from PG-based graphs. In a fully parallel design based on PG concepts, the number of processing units is equal to the number of vertices, each performing an atomic computation. To reduce the number of processing units used for implementation, we present an easy way of partitioning the vertex set. Each block of partition is then assigned to a processing unit. A processing unit performs the computations corresponding to the vertices in the block assigned to it in a sequential fashion, thus creating the effect of folding the overall computation. These blocks have certain symmetric properties that enable us to develop a conflict-free schedule. The scheme achieves the best possible throughput, in lack of any overhead of shuffling data across memories while scheduling another computation on the same processing unit. This paper reports two folding schemes, which are based on same lattice embedding approach, based on partitioning. We first provide a scheme for a projective space of dimension five, and the corresponding schedules. Both the folding schemes that we present have been verified by both simulation and hardware prototyping for different applications. We later generalize this scheme to arbitrary projective spaces.Comment: 31 pages, to be submitted to some discrete mathematics journa

Incidence of patella baja following patellar eversion in total knee arthroplasty

Background: Patella baja is a rare complication of total knee arthroplasty (TKA) leading to decreased mechanical advantage of the extensor mechanism, decreased knee range of motion, anterior knee pain and increased wear of the tibial and patellar polyethylene. There exists a lack of evidence on whether patellar eversion leads to shortening of the patellar tendon. The present study aims to determine if eversion of patella during TKA leads to patella baja.Methods: Between August 2014 and August 2016, 55 knees undergoing primary TKA with a standard medial parapatellar arthrotomy and eversion of patella were included in this two point cross sectional study. Preoperative X-rays were taken to assess the length of the patellar tendon and Insall Salvati ratio (ISR). Postoperatively the Blackburne Peel Index (BPI), ISR and patellar tendon lengths were assessed on lateral X-rays to look for any incidence of patella baja.Results: The postoperative change in the length of the patellar tendon was unpredictable; though most of them decreased. The pre and post op difference in the length of patellar tendon was statistically significant in females (4.43±0.20 cm vs. 4.35±0.24 cm; p value-0.005). Significant decrease in length of patellar tendon was seen in patients aged 66-70 years (p= 0.024) and patients with BMI >30 kg/m2. No case of true patella baja was found postoperatively. No significant correlation could be established between ISR and age, sex or BMI of the patients.Conclusions: The different risk factors for post TKA shortening of patellar tendon include female gender and higher BMI (>30 Kg/m²). However eversion of patella during TKA may not lead to an increased incidence of true patella baja