Showing papers in "Computer-aided Civil and Infrastructure Engineering in 2008"

How Reaction Time, Update Time, and Adaptation Time Influence the Stability of Traffic Flow

Abstract: When modeling the acceleration and decel- eration of drivers, there are three characteristic time con- stants that influence the dynamics and stability of traffic flow: The reaction time of the drivers, the velocity adap- tation time needed to accelerate to a new desired velocity, and the numerical update time. By means of numerical simulations with a time-continuous car-following model, we investigate how these times interplay with each other and effectively influence the longitudinal instability mech- anisms for a platoon of vehicles. The long-wavelength string instability is mainly driven by the velocity adapta- tion time while short-wavelength local instabilities arise for sufficiently high reaction and update times. Further- more, we investigate the relation between large update time steps and finite reaction times as they both introduce delays in the reaction to the traffic situation. Remarkably, the numerical update time is dynamically equivalent to about half the reaction time, which clarifies the meaning of the time step in models formulated as iterated maps such as the Newell and the Gipps model. Furthermore, with respect to stability, there is an optimal adaptation time as a function of the reaction time.

Multiobjective Optimization of Concrete Frames by Simulated Annealing

Abstract: This article aims to describe a methodology to design RC building frames based on a multiobjective simulated annealing (MOSA) algorithm applied to four objective functions, namely, the economic cost, the constructability, the environmental impact, and the overall safety of RC framed structures. The evaluation of solutions follows the Spanish Code for structural concrete. The methodology was applied to a symmetrical building frame with two bays and four floors. This example has 77 design variables. Pareto results of the MOSA algorithm indicate that more practical, more constructable, more sustainable, and safer solutions than the lowest cost solution are available at a cost increment acceptable in practice. Results N s -SMOSA1 and N s -SMOSA2 of the cost versus constructability Pareto front are finally recommended because they are especially good in terms of cost, constructability, and environmental impact. Further, the methodology proposed will help structural engineers to enhance their designs of building frames.

Perceptron Learning in Engineering Design

Abstract: A model of machine learning in engineering design is presented based on the concept of self-adjustment of internal control parameters and perceptron. A perceptron is defined as a four-tuple entity which can answer either “yes” or “no” in the problem domain. The problem of structural design is cast in a form that can be described by a perceptron without hidden units. Some results from our experimentation are presented in tabular form. The paper is concluded by a comparison of perceptron and explanation-based learning.

Traffic Estimation and Optimal Counting Location Without Path Enumeration Using Bayesian Networks

Abstract: This paper deals with the problem of estimating and updating the origin-destination (OD) matrix and link flows from traffic counts and its optimal location. A combination (bi-level) of an OD-pair matrix estimation model based on Bayesian networks, and a Wardrop-minimum-variance model, that identifies origins and destinations of link flows, is used to estimate OD-pair and unobserved link flows based on observations of links and/or OD-pair flows. The Bayesian network model is also used to select the optimal number and locations of the links counters based on maximum correlation. Lastly, the proposed methods are illustrated by their application to the Nguyen–Dupuis and Ciudad Real networks.

The Observability Problem in Traffic Network Models

Abstract: This paper examines the issue of observability of traffic networks, understanding as such the problem of identifying which is the subset of OD-pair and link flows that can be calculated based on a subset of observed OD-pair and link flows and related problems. Two algebraic methods for solving observability problems are given, one global approach based on null-spaces and a step by step procedure allowing updating the information once each item of information (OD-pair or link flow) becomes available. In particular, 7 different observability problems are stated and solved using the proposed methods, illustrated by their application to the Nguyen-Dupuis network problem. Results show that the proposed methods provide useful information on which OD-pair or link flows are informative on other OD-pair and link flows, and that the methods are applicable to large networks.

Fuzzy Modeling Approach for Combined Forecasting of Urban Traffic Flow

Abstract: This paper looks at the problem of accuracy of short-term traffic flow forecasting in the complex case of urban signalized arterial networks. A new, artificial intelligence-based approach is offered for improving accuracy of traffic predictions through suitably combining forecasts derived from a set of individual predictors. This approach employs a fuzzy rule-based system (FRBS), which is augmented with an appropriate metaheuristic (direct search) technique to automate the tuning of the system parameters within an online adaptive rolling horizon framework. The proposed hybrid FRBS is used to nonlinearly combine traffic flow forecasts resulting from an online adaptive Kalman filter and an artificial neural network model. Empirical results obtained from the model's implementation into an actual urban signalized arterial show the ability of the proposed approach to considerably overperform the given individual traffic predictors.

Modal Flexibility Analysis of Cable-Stayed Ting Kau Bridge for Damage Identification

Abstract: : The cable-stayed Ting Kau Bridge has been permanently instrumented with more than 230 sensors for long-term structural health monitoring. In this article, the feasibility of using the measured dynamic characteristics of the bridge for damage detection is studied. Making use of a validated three-dimensional (3D) finite element model (FEM), modal flexibility matrices of the bridge are constructed using a few truncated modes and incomplete modal vectors at the sensor locations. The relative flexibility change (RFC) between intact and damage states is then formulated as an index to locate damage. The applicability of this flexibility index for damage location in the cable-stayed bridge is examined by investigating various damage scenarios including those at stay cables, longitudinal stabilizing cables, bearings and supports, longitudinal girders and cross girders, and taking into account measurement noise in modal data. The influence of two ambient factors, that is, temperature change and traffic loading, on the damage detectability is also analyzed by approximately considering an equivalent alteration in the material and structural behaviors. It is revealed that in the absence of ambient effects the RFC index performs well for locating damage of different severities in single-damage cases. In multi-damage cases the RFC index may provide false-negative identification for damage at the members with low sensitivity. Eliminating ambient effects is requisite for reliable detection of damage at stay cables and cross girders. The capability of the RFC index for locating damage at cross girders is significantly dropped in the presence of measurement noise.

Tabu Search Strategies for the Public Transportation Network Optimizations with Variable Transit Demand

Abstract: In this article, systematic tabu search (TS)-based heuristic methods are put forward and applied for the design of public transportation networks with variable demand. A multi-objective nonlinear mixed integer model is formulated. Solution methodologies are proposed, which consist of 3 main components: an initial candidate route set generation procedure that generates all feasible routes incorporating practical bus transit industry guidelines; a network analysis procedure that decides transit demand matrix, assigns transit trips, determines service frequencies, and computes performance measures; and a Tabu search method (TSM) that combines these 2 parts, guides the candidate solution generation process, and selects an optimal set of routes from the huge solution space. Comprehensive tests are conducted and sensitivity analyses are performed. Characteristics analyses are undertaken and solution qualities from different algorithms are compared. Numerical results indicate that the preferred TSM outperforms the genetic algorithm used as a benchmark for the optimal bus transit route network design problem without zone demand aggregation.

Experimental Assessment of the Accuracy of GPS and RTS for the Determination of the Parameters of Oscillation of Major Structures

Abstract: Based on experimental evidence, the authors explore the possibility of using GPS and robotic total stations (RTS) for measurements of oscillations of relatively rigid structures (modal frequencies up to 3–4 Hz). The strategy was to compare uni-axial oscillations of known characteristics with simultaneous recordings of both GPS and RTS, and analyze obtained time series to determine amplitude and frequency of oscillations. The conclusion of this study is that GPS can record oscillations up to 4 Hz with a minimum amplitude of 5–10 mm with an accuracy of a few millimeters, and that RTS can record peak oscillations with submillimeters to a few millimeters accuracy, but at high frequencies some cycles were lost. Based on recordings of both instruments, frequencies of oscillations were also accurately determined, though noise seems to increase with increasing frequency. Spectral analysis was based on least-square-based software which permits one to analyze discontinuous, short, and non-equispaced time series. The latter derive either from GPS signal outages and hardware/software imperfections, or from a non-constant rate of sampling for RTS. The overall conclusion is that the adopted computational approaches permit some main disadvantages of these instruments to be overcome and also allow conventional GPS and RTS instrumentation to be used for a wide range of cases of structural monitoring, especially if displacements relative to an independent coordinate system are required.

Fuzzy Clustering of Stability Diagrams for Vibration-Based Structural Health Monitoring

Abstract: : A primary challenge to implementing structural health monitoring techniques on civil infrastructure is the identification of structural changes in the presence of natural changes in structural response due to environmental variables such as temperature. Data from the Z24 Bridge recorded over the course of nearly a year are analyzed in this article. Covariance-driven Stochastic Subspace Identification is applied to the data to identify the modal parameters of the structure. A large number of numerical poles are identified with the real physical poles. A Fuzzy Clustering Algorithm is then used to extract parameters indicative of the bridge's state from the mixture of real and numerical poles. The main benefit of this approach is the lack of need for mode shape information and thus its applicability to structures monitored with spatially sparse sensor grids. The method is shown to provide very encouraging results in separating the response data from the Z24 Bridge in healthy and damaged states in varying environmental conditions. The method does not explicitly identify the changes due to environmental variables but it is found that the changes in the parameters identified due to damage are greater than those due to environmental variability and therefore may be flagged. The procedure is also applied successfully to a second data set obtained from monitoring a tall building over several years of its early life to identify gradual or sudden structural changes.

Temporal Evolution of Short-Term Urban Traffic Flow : A Nonlinear Dynamics Approach

Abstract: Recognizing temporal patterns in traffic flow has been an important consideration in short- term traffic forecasting research. However, little work has been conducted on identifying and associating traffic pattern occurrence with prevailing traffic con- ditions. We propose a multilayer strategy that first identifies patterns of traffic based on their structure and evolution in time and then clusters the pattern- based evolution of traffic flow with respect to pre- vailing traffic flow conditions. Temporal pattern iden- tification is based on the statistical treatment of the recurrent behavior of jointly considered volume and oc- cupancy series; clustering is done via a two-level neural network approach. Results on urban signalized arterial 90-second traffic volume and occupancy data indicate that traffic pattern propagation exhibits variability with respect to its statistical characteristics such as determinis- tic structure and nonlinear evolution. Further, traffic pat- tern clustering uncovers four distinct classes of traffic pat- tern evolution, whereas transitional traffic conditions can be straightforwardly identified.

Damage Identification of a Composite Beam Using Finite Element Model Updating

Abstract: The damage identification study presented in this paper leveraged a full-scale sub-component experiment conducted in the Charles Lee Powell Structural Research Laboratories at the University of California, San Diego. As payload project attached to a quasi-static test of a full-scale composite beam, a high-quality set of low-amplitude vibration response data was acquired from the beam at various damage levels. The Eigensystem Realization Algorithm was applied to identify the modal parameters (natural frequencies, damping ratios, displacement and macro-strain mode shapes) of the composite beam based on its impulse responses recorded in its undamaged and various damaged states using accelerometers and long-gage fiber Bragg grating strain sensors. These identified modal parameters are then used to identify the damage in the beam through a finite element model updating procedure. The identified damage is consistent with the observed damage in the composite beam.

Modal Identification Study of Vincent Thomas Bridge Using Simulated Wind-Induced Ambient Vibration Data

Abstract: In this paper, wind-induced vibration response of Vincent Thomas Bridge, a suspension bridge located in San Pedro near Los Angeles, California, is simulated using a detailed three-dimensional finite element model of the bridge and a state-of-the-art stochastic wind excitation model. Based on the simulated wind-induced vibration data, the modal parameters (natural frequencies, damping ratios, and mode shapes) of the bridge are identified using the data-driven stochastic subspace identification method. The identified modal parameters are verified by the computed eigenproperties of the bridge model. Finally, effects of measurement noise on the system identification results are studied by adding zero-mean Gaussian white noise processes to the simulated response data. Statistical properties of the identified modal parameters are investigated under increasing level of measurement noise. The framework presented in this paper will allow to investigate the effects of various realistic damage scenarios in long-span cable-supported (suspension and cable-stayed) bridges on changes in modal identification results. Such studies are required in order to develop robust and reliable vibration-based structural health monitoring methods for this type of bridges, which is a long-term research objective of the authors.

A State‐Space Approach for Deriving Bridge Displacement from Acceleration

Abstract: : The dynamic response (i.e., acceleration and displacement) of a bridge under vehicular load is an important component of design and evaluation. Field measurement of girder displacement, however, is generally nontrivial. Traditional sensors often require a stationary reference such as temporary scaffolds or a suspended cable. In either form, there are added costs, restrictions, and labor. As a result, there are both economic and practical incentives for developing methods that can use an accelerometer to measure both acceleration and displacement. One difficulty of this, however, is the presence of small low-frequency errors in the measured signal, which become sufficiently large through successive integrations and lead to a significantly distorted displacement profile. The objective of this article is to examine an analytical model based on the state-space approach for minimizing such errors and to compare results with two time domain correction methods. Field measurements from a three-span continuous bridge are used to assess the accuracy of each routine.

Collapse of Reinforced Concrete Column by Vehicle Impact

Abstract: : Walk-up flats are typically supported by slender columns on the ground floor forming a soft storey. The column slenderness ratio can be in the order of 6–9. Some of these buildings are right next to busy streets and hence continuously exposed to the potential hazard of a vehicle impacting on a column in an accident. In the early part of this study, the ultimate energy absorption capacity of a reinforced concrete column is compared to the kinetic energy embodied in the moving vehicle. The energy-absorption capacity is calculated from the force-displacement curve of the column as determined from a nonlinear static (push-over) analysis. The ultimate displacement of the column is defined at the point when the column fails to continue carrying the full gravitational loading. Results obtained from the nonlinear static analysis have been evaluated by computer simulations of the dynamic behavior of the column following the impact. Limitations in the static analysis procedure have been demonstrated. The effects of strain rate have been discussed and the sensitivity of the result to changes in the velocity function and stiffness of the impacting vehicle has also been studied.

Using Evolutionary Optimization Techniques for Scheduling Water Pipe Renewal Considering a Short Planning Horizon

Abstract: : The maintenance and management of underground infrastructures is a growing problem for a majority of municipalities. The maintenance costs are increasing while the financial resources of municipalities remain limited. Water distribution system (WDS) managers therefore need tools to assist them in the elaboration of pipe renewal management plans. In this article, results of a newly developed strategy for pipe renewal based on a cost function are presented. The strategy allows the minimization of a cost function while also considering hydraulic criterion. This strategy was tested on a short planning horizon of five years. The pipe number to be replaced and the optimal moment for renewal are identified using three different optimization techniques: IGA (Island Genetic Algorithm), NPGA-2 (Niched Pareto Genetic Algorithm 2), and NSGA-II (Non-dominated Sorting Genetic Algorithm-II). The proposed approach has five distinctive features: (1) it is coupled with a flexible evolutionary framework that allows the user to select any type of operator for IGA or any kind of multiobjective genetic algorithm; (2) it uses the hydraulic simulator Epanet2.0 which allows steady state or dynamic simulations; (3) it considers a probabilistic break model to evaluate the structural deterioration of pipes; (4) it integrates a Bayesian approach for the estimation of the pipe break model parameters that take into account the influence of inherent uncertainties related to the quality of data during the decision-making process; and (5) it simulates the variation of the pipe's roughness over the years. The developed strategy/model is explained using an example that allows us to elucidate its most important components. Simulation experiments on a small network (100 pipes) are presented. A comparison of three evolutionary algorithm results is provided. Tests showed that IGA performs well, but for networks of larger sizes, we recommend increasing the number of demes to reach better solutions. Higher quality results were achieved with NSGA-II than NPGA-2 on differently sized networks. We recommend the use the NSGA-II to optimize large WDS. Future developments for this strategy are also discussed.

Optimizing Design of Highway Horizontal Alignments: New Substantive Safety Approach

Abstract: : Highway agencies are continually facing safety problems on highways, especially on horizontal alignments. Traditionally, the geometric design implicitly considers safety through satisfying minimum design requirements for different geometric elements. This article presents a new substantive-safety approach for the design of horizontal alignments based not only on minimum design guidelines, but also on actual collision experience. The curve radii, spiral lengths, lane width, shoulder width, and tangent lengths are determined to optimize the mean collision frequency along the highway. The model allows the parameters of the horizontal alignment to vary within specified ranges. The model also considers any specified physical obstructions in selecting the optimal alignment. Collision experience is addressed using existing collision prediction models for horizontal alignments and cross sections. The model is applicable to two-lane rural highways for which collision prediction models exist. Application of the model is presented using numerical examples. The proposed substantive-safety approach takes horizontal alignment design one step further beyond the minimum-guideline concept, and therefore should be of interest to highway designers.

Modeling Road Centerlines and Predicting Lengths in 3-D Using LIDAR Point Cloud and Planimetric Road Centerline Data

Abstract: : Transportation is one of a few engineering domains that work with linear objects—roads. Accurate road length information is critical to numerous transportation applications. Road lengths can be obtained via technologies such as ground surveying, global positioning systems (GPS), and Distance Measurement Instruments (DMI). But using these methods for data collection and length determination is time-consuming, labor intensive, and costly. The purpose of this study was to assess the accuracy and feasibility of an alternative. This article reports on a study that provides an alternative to obtaining road centerline lengths by measurement; instead it proposes using geographic information systems (GIS) and light detection and ranging (LIDAR) point cloud data. In this study, a three-dimensional (3-D) vector model based on linear referencing systems (LRS) concepts was developed to represent road centerlines in a 3-D space and to predict their 3-D lengths. A snapping approach and an interpolation approach to obtain 3-D points along lines when working with LIDAR point clouds were proposed and discussed. Quality control measures were initiated to validate the approach. The accuracy of the predicted 3-D distances was evaluated via a case study by comparing them to distances measured by DMI. The results were also compared to road lengths obtained by draping planimetric road centerlines on digital elevations models (DEMs) constructed from LIDAR points. The effects of the average density of 3-D points on the accuracy of the predicted distances were evaluated. This study concluded that the proposed 3-D approach using LIDAR data was efficient in obtaining 3-D road lengths with an accuracy that was satisfactory for most transportation applications.

Response and Modeling of Cantilever Retaining Walls Subjected to Seismic Motions

Abstract: @A series of nonlinear, explicit finite differ- ence analyses were performed to determine the dynamic response of a cantilever retaining wall subjected to earth- quake motions. This article outlines the calibration and validation of the numerical model used in the analyses and comparisons are presented between the results from the finite difference analyses and results from simplified techniques for computing dynamic earth pressures and permanent wall displacement (i.e., Mononobe-Okabe and Newmark sliding block methods). It was found that at very low levels of acceleration, the induced pressures were in general agreement with those predicted by the Mononobe- Okabe method. However, as the accelerations increased to those expected in regions of moderate seismicity, the induced pressures are larger than those predicted by the Mononobe-Okabe method. This deviation is attributed to the flexibility of the retaining wall system and to the observation that the driving soil wedge does not respond monolithically, but rather responds as several wedges. Ad- ∗ To whom correspondence should be addressed. E-mail: rugreen

A Polymorphic Dynamic Network Loading Model

Abstract: A polymorphic dynamic network loading (PDNL) model is developed and discretized to integrate a variety of macroscopic traffic flow and node models. The polymorphism, realized through a general node-link interface and proper discretization, offers several promi- nent advantages. First of all, PDNL allows road facilities in the same network to be represented by different traf- fic flow models based on the tradeoff of efficiency and realism and/or the characteristics of the targeted prob- lem. Second, new macroscopic link/node models can be easily plugged into the framework and compared against existing ones. Third, PDNL decouples links and nodes in network loading, and thus opens the door to parallel computing. Finally, PDNL keeps track of individual ve- hicular quanta of arbitrary size, which makes it possible to replicate analytical loading results as closely as desired. PDNL, thus, offers an ideal platform for studying both an- alytical dynamic traffic assignment problems of different kinds and macroscopic traffic simulation.

One-Dimensional Model for Multi-Barge Flotillas Impacting Bridge Piers

Abstract: : The serious consequence of barge-bridge collisions necessitates the study of barge impact loadings on bridges. This article introduces an elastoplastic spring-mass model for the analysis of multi-barge flotillas colliding with bridge piers at zero angle of attack. The model accounts for the essential factors pertaining to barge/flotilla impacts, such as pier geometry and stiffness, and dynamic interaction between barges. A method to identify the elastoplastic behavior of barge crushing is also presented. The proposed method generates impact force time-histories for a multitude of flotilla configurations in a matter of minutes, which is especially valuable in probabilistic analysis requiring many collision simulations. The results from this study are compatible with the respective impact time-histories produced by exhaustive finite element simulations. A bridge pier impacted by a three-barge and a 15-barge flotilla is studied.

Reference-Free Damage Classification Based on Cluster Analysis

Abstract: Fiber-reinforced polymer (FRP) composite materials have been used widely for retrofitting of civil infrastructure systems. The ultimate aim of this work was to develop an on-site non-destructive testing (NDT) technique that can continuously and autonomously inspect the bonding condition between a carbon FRP (CFRP) layer and a host reinforced concrete (RC) structure, when the CRFP layer is used for strengthening the RC structure. The uniqueness of this reference-free NDT is 2-fold: 1) features sensitive to CFRP debonding but insensitive to operational and environmental variations of the structure were extracted only from current data, without direct comparison with previously obtained baseline data; and 2) damage classification is performed instantaneously without relying on predetermined decision boundaries. The extraction of the reference-free features is accomplished based on the concept of time reversal acoustics; instantaneous decisionmaking is achieved using cluster analysis. Monotonic and fatigue load tests of large-scale CFRP-strengthened RC beams are conducted to demonstrate the potential of the proposed reference-free debonding monitoring technique. Based on experimental studies, it is shown that the proposed reference-free NDT technique may minimize false alarms of debonding and unnecessary data interpretation by end users.

A Model‐free Method for Damage Locating and Quantifying in a Beam‐like Structure Based on Dynamic Distributed Strain Measurements

Abstract: : A damage locating algorithm with no requirement for a detailed structural analytical model has been proposed in our previous research, named a modal macro-strain vector (MMSV) method by directly using the modal parameters extracted from dynamic macro-strain data recorded by a long-gage fiber optic sensors array distributed throughout the full or some partial areas of beam-like structures. This article is devoted to generalizing the originally proposed algorithm based on the correlation of modal parameters among the distributed fiber optic sensors to develop a method for both damage locating and quantifying. After a brief review of the distributed sensing techniques, the generalized method is proposed based on the originally proposed MMSV-based algorithm. Numerical case studies are performed to locate and quantify damage under different designed cases to verify the effectiveness and universality of the method. Experimental investigations on a simple beam under hammer impulsive excitation at different locations with arbitrary amplitudes are then carried out to verify the accuracy of the proposed method. An innovative idea on data interpretation and feature extraction is described. On the basis of the experimental and numerical investigations, an integrated model-free scheme for damage locating and quantifying is finally summarized for proposal.

Incorporating Maintenance Effectiveness in the Estimation of Dynamic Infrastructure Performance Models

Abstract: In this paper, the authors demonstrate how intervention analysis can be used in conjunction with dynamic performance modeling to analyze the effect of maintenance activities on the performance of infrastructure facilities. Specifically, state-space specifications of autoregressive moving averages with exogenous inputs models are considered to develop deterioration and inspection models for infrastructure facilities, and intervention analysis is used to estimate transitory and permanent effects of maintenance (e.g., performance jumps or deterioration rate changes). To illustrate the methodology, the effectiveness of an overlay on a flexible pavement section from the AASHO Road Test is analyzed. Results show the effect of the overlay on improvements both on surface distress (rutting and slope variance) as well as on the pavement's underlying serviceability. The results also provide evidence that the overlay changes the pavement's response to traffic; that is, the overlay causes a reduction in the rate at which traffic damages the pavement.

Development of an Estimation Procedure for an Activity-Based Travel Demand Model

Abstract: In this paper, the authors implement an estimation procedure for a particular mathematical programming activity-based model to estimate the relative importance of factors associated with spatial and temporal interrelationships among the out-of-home activities that motivate a household's need or desire to travel. The method uses a genetic algorithm to estimate coefficient values of the utility function, based on a particular multidimensional sequence alignment method to deal with the nominal, discrete attributes of the activity/travel pattern, and a time sequence alignment method to handle temporal attributes of the activity pattern. The estimation procedure is tested on data drawn from a well-known activity/travel survey.

Nondestructive Evaluation of Elastic Properties of Concrete Using Simulation of Surface Waves

Abstract: Nondestructive evaluation using the propa- gation of an impact-induced surface wave can be effec- tively applied in estimating in situ material properties. In this study, to evaluate information of a surface waveform beyond the simple wave velocity, artificial intelligence en- gines are employed to estimate simulation parameters, that is, the properties of elastic materials. The developed artificial neural networks are trained with a numerical database having secured its stability. In the process, the appropriate shape of the force-time function for an im- pact load is assumed so as to avoid Gibbs phenomenon, and the proposed principal wavelet-component analysis accomplishes a feature extraction with a wavelet trans- formed signal. The results of estimation are validated with experiments focused on concrete materials.

Estimation of Frequency‐Dependent Strong Motion Duration Via Wavelets and Its Influence on Nonlinear Seismic Response

Abstract: In this paper, a procedure for estimation of frequency-dependent strong motion duration (FDSMD) is developed. The proposed procedure utilizes the continuous wavelet transform and is based on the decomposition of the earthquake record into a number of component time histories (termed pseudo-details) with frequency content in a selected range. The significant strong motion duration of each pseudo-detail is calculated based on the accumulation of the Arias intensity (AI). Lastly, the FDSMD of the earthquake record in different frequency ranges is defined as the strong motion duration of the corresponding pseudo-detail scaled by a weight factor that depends on the AI of each pseudo-detail. The efficiency of this new strong motion definition as an intensity measure is evaluated using incremental dynamic analysis. Results obtained show that the proposed FDSMD influence the peak response of short-period structures with stiffness and strength degradation.

Development of a Bridge Bumper to Protect Bridge Girders from Overheight Vehicle Impacts

Abstract: Bridges with low clearance are vulnerable to collision with overheight vehicles. Collisions of overheight vehicles can cause fatalities and injuries to drivers and passengers of overheight vehicles, and damage to bridge girders. The repair of damaged bridges can be costly and time consuming. This article 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. This paper presents results of small-scale impact experiments using the proposed bridge bumper with several options of energy-absorbing materials to protect a reinforced concrete beam. Finite element (FE)analyses are conducted to simulate small-scale impact experiments. Optimization of the FE model is carried out for the response quantities of interest with respect to the geometrical parameters and 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 possible full-scale implementation of the proposed bridge bumper is also detailed.

A Computing Approach Using Probabilistic Neural Networks for Instantaneous Appraisal of Rear-End Crash Risk

Abstract: Computing and information technology has markedly increased the capabilities to collect, store, and analyze freeway traffic surveillance data. The most common forms of such data are collected using underground loop detectors. In the recent past the potential of using this data for identification of crash-prone conditions has been explored. In this paper, application of probabilistic neural networks (PNN) is explored to identify conditions prone to rear-end crashes on the freeway. PNN is a neural network implementation of the well-documented Bayesian classifier. In this research rear-end crashes observed on the Interstate-4 corridor in Orlando, FL, are divided into 2 groups based on average traffic speeds observed around the crash location prior to crash occurrence. Using decision tree-based classification it was noted that although the 2 groups of crashes have comparable frequencies, traffic conditions belonging to one of the groups (characterized by a low-speed traffic regime) are comparatively rare on the freeways. Hence, if those conditions are encountered on the freeway in real time, then conditions may be considered prone to rear-end crashes. As conditions belonging to the other group of rear-end crashes (characterized by a medium-to-high speed regime) are more commonly observed on the freeway, PNN-based classification models are developed for this group. The rear-end crashes along with a sample of randomly selected noncrash cases were used to calibrate the classifiers. The output layer of the PNN models was modified to provide a measure of crash risk, instead of binary classification based on an arbitrary threshold. A desirable threshold on this output may be established to separate crash-prone conditions from "normal" freeway traffic.

Parallel Structural Analysis Using Threads

Abstract: Practical solution of the structural analysis problem in a parallel processing environment is investigated through the use of the notion of cheap concurrency and the concept of threads. A thread is a lightweight process or independent instructions executing agent capable of concurrent execution with other threads. Portions of a structural analysis code implemented in C have been parallelized employing the Encore Parallel Threads on an Encore Multimax multiprocessor computer. The issues of racing condition, synchronization, and mapping are considered and discussed. Two synchronization mechanisms, semaphores and monitors, have been employed and compared. Two different mapping strategies have been implemented and studied. Results are reported on the effect of amount and frequency of shared memory access on the speed-up, the overhead time required for creating threads, and comparison of overall computational time performance using two space truss examples. An overall efficiency of 90–95% was achieved for 11 processors.