Infiltration Route Analysis Using Thermal Observation Devices (TOD) and Optimization Techniques in a GIS Environment

Infiltration-route analysis is a military application of geospatial information system (GIS) technology. In order to find susceptible routes, optimal-path-searching algorithms are applied to minimize the cost function, which is the summed result of detection probability. The cost function was determined according to the thermal observation device (TOD) detection probability, the viewshed analysis results, and two feature layers extracted from the vector product interim terrain data. The detection probability is computed and recorded for an individual cell (50 m × 50 m), and the optimal infiltration routes are determined with A* algorithm by minimizing the summed costs on the routes from a start point to an end point. In the present study, in order to simulate the dynamic nature of a real-world problem, one thousand cost surfaces in the GIS environment were generated with randomly located TODs and randomly selected infiltration start points. Accordingly, one thousand sets of vulnerable routes for infiltration purposes could be found, which could be accumulated and presented as an infiltration vulnerability map. This application can be further utilized for both optimal infiltration routing and surveillance network design. Indeed, dynamic simulation in the GIS environment is considered to be a powerful and practical solution for optimization problems. A similar approach can be applied to the dynamic optimal routing for civil infrastructure, which requires consideration of terrain-related constraints and cost functions

Multiobjective railway alignment optimization using ballastless track and reduced cross-section in tunnel

The increasing need for railway planning and design to connect growing cities in inland mountainous areas has pushed engineering efforts toward the research of railway tracks that must comply with more restrictive constraints. In this study, a multiobjective alignment optimization (HAO), commonly used for highway projects, was carried out to identify a better solution for constructing a high-speed railway track considering technical and economic feasibilities. Then, two different and innovative scenarios were investigated: an unconventional ballastless superstructure, which is more environment-friendly than a gravel superstructure, and a reduced cross-section in a tunnel, which enables a slower design speed and then, less restrictive geometric constraints and earthmoving. The results showed that the first solution obtained a better performance with a slight increase in cost. Moreover, both scenarios improved the preliminary alignment optimization, reducing the overall cost by 11% for the first scenario and 20% for the second one

A Comprehensive Framework for White-Box Damage Detection in Structural Systems Based on Extended Constitutive Relation Error Method

Early detection of the deterioration and degradation in civil infrastructure is critical for structural engineers and infrastructure managers to develop rehabilitation and maintenance plans. In the field of structural health monitoring, numerous techniques have been developed to detect and localize damage by examining changes in measured vibration response. Among vibration-based damage detection techniques, model-based approach has been widely used as its damage detection process incorporates the geometric configuration, physical properties, and behavioral characteristics of the structural system. However, the model-based approaches depend on a model calibration procedure that is based only on the outputs of numerical models without explicitly taking the knowledge regarding the mechanistic behavior of the system into account. Moreover, due to the limitation of measurement degrees of freedom (DOFs), the number of identified vibration modes are typically far fewer than the number of model variables to be calibrated. Consequently, these model-based damage detection methods frequently suffer from an ill-posed inverse-problem. This dissertation contributes to the field of model-based damage detection by implementing the Extended Constitutive Relation Error (ECRE), a method developed for error localization in finite element models for detecting structural damage. Implementing ECRE for damage detection leads to the localization of elements with high residual energy through the identification of discrepancies between experimental measurements and model predictions due to damage. The ECRE-based damage detection technique incorporates the underlying physics of the problem in a tangible and visible manner, and thus leading to more reliable solutions in the damage detection and localization process. This dissertation applies the ECRE-based damage detection in the context of both linear and nonlinear dynamical systems. In particular, the dissertation integrates the Multi-harmonic balance method with ECRE to accurate identify the modeling errors of locally nonlinear dynamical systems. This approach has a potential to be applied for damage detection in the nonlinear structural system, as well as to be used as a damage prognosis tool for the estimation of structural system\u27s remaining useful life

OPTIMIZATION OF STATION LOCATIONS AND TRACK ALIGNMENTS FOR RAIL TRANSIT LINES

Designing urban rail transit systems is a complex problem, which involves the determination of station locations, track geometry, right-of-way type, and various other system characteristics. The existing studies overlook the complex interactions between railway alignments and station locations in a practical design process. This study proposes a comprehensive methodology that helps transit planners to concurrently optimize station locations and track alignments for an urban rail transit line. The modeling framework resolves the essential trade-off between an economically efficient system with low initial and operation cost and an effective system that provides convenient service for the public. The proposed method accounts for various geometric requirements and real-world design constraints for track alignment and stations plans. This method integrates a genetic algorithm (GA) for optimization with comprehensive evaluation of various important measures of effectiveness based on processing Geographical Information System (GIS) data. The base model designs the track alignment through a sequence of preset stations. Detailed assumptions and formulations are presented for geometric requirements, design constraints, and evaluation criteria. Three extensions of the base model are proposed. The first extension explicitly incorporates vehicle dynamics in the design of track alignments, with the objective of better balancing the initial construction cost with the operation and user costs recurring throughout the system's life cycle. In the second extension, an integrated optimization model of rail transit station locations and track alignment is formulated for situations in which the locations of major stations are not preset. The concurrent optimization model searches through additional decision variables for station locations and station types, estimate rail transit demand, and incorporates demand and station cost in the evaluation framework. The third extension considers the existing road network when selecting sections of the alignment. Special algorithms are developed to allow the optimized alignment to take advantage of links in an existing network for construction cost reduction, and to account for disturbances of roadway traffic at highway/rail crossings. Numerical results show that these extensions have significantly enhanced the applicability of the proposed optimization methodology in concurrently selecting rail transit station locations and generating track alignment

An Alignment Optimization Model for a Simple Highway Network

A new highway addition to an existing road network is typically considered for improving traffic performance in that road network. However, finding the new highway that best improves the existing network is a very complex problem since many factors affect the road construction. Besides changes in traffic flow patterns due to the new highway, various costs associated with highway construction as well as design specifications, safety, environmental, and political issues affect such a project. Until recently, many studies have dealt separately with the problems of highway alignment optimization and network design. However, no models have been found that integrate these problems comprehensively and effectively. This dissertation seeks to find a realistic three-dimensional highway alignment that best improves an existing network, while considering its costs, geometric design, and environmental impacts on the study area. To fulfill this objective, an effective network model is developed that can simultaneously optimize (i) highway alignments and (ii) junction points with existing roads. In addition, the model's optimization process considers traffic impacts due to the highway addition as well as factors associated with its construction. This dissertation starts by investigating the major cost components and important constraints in the highway design processes. Next, existing models for optimizing highway alignments are reviewed by assessing their advantages and disadvantages. Effective solution search methods are then developed to help solve the complex optimization problem. Development of the search methods is essential since an equilibrium traffic assignment as well as alignment optimization is undertaken in the proposed network model. Precise formulations of various highway costs and constraints are also developed for evaluating the various candidate alternatives. Cost functions for system improvements that can be obtained from the new highway addition are proposed. These are calculated based on the equilibrium traffic flows found from the assignment process. Complex geographical constraints including user preferences and environmentally sensitive areas are realistically represented, along with design standards required for highways. To represent highway alignments, sets of tangents, circular curves and transition spirals are used; in addition, three-leg structure models are also developed for representing the highway endpoints. Finally, several case studies are conducted to test the performance of the proposed models