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The dynamic response of rigid walls retaining a cross-anisotropic poroelastic soil layer over bedrock to seismic horizontal excitation is determined analytically under conditions of plane strain. The problem is treated as a special case of that of a pair of rigid walls with a large separation distance. Use is made of Biot’s anisotropic poroelastodynamic theory. Assuming time harmonic excitation, one is able to achieve an exact u-p formulation of the problem in the frequency domain. Expansion of the displacements and the pore-water pressure in terms of Fourier sine and cosine series along the horizontal direction, reduces the partial differential equations of motion in the frequency domain into a system of three ordinary differential equations, which can be easily solved analytically. Thus, closed form expressions for the seismic soil pressure, the distance from the base of the point of application of the resultant seismic pressure and the base shear force and bending moment are obtained. From the above cross-anisotropic poroelastic solution its special cases of isotropic poroelastic solution and cross-anisotropic elastic solution are obtained and compared with the corresponding existing analytical solutions for validation purposes. Finally, parametric studies are performed in order to assess the effect of cross-anisotropy on the seismic response of the wall-soil system.

The dynamic response of rigid walls retaining a cross-anisotropic elastic soil layer over bedrock to seismic horizontal excitation is determined analytically under conditions of plane strain. The problem of a pair of rigid walls is solved first and the one with a single wall is obtained as a special case for a large separation distance between those walls. Assuming time harmonic motion, expansion of the unknown displacements in Fourier sine and cosine series along the horizontal direction, reduces the system of the two partial differential equations of motion in the frequency domain into a system of two ordinary differential equations, which is easily solved analytically. Thus, one can obtain closed form expressions for the seismic soil pressure, the distance from the base of the point of application of the resultant seismic pressure and the base shear force and bending moment. The above cross-anisotropic solution is first verified by comparing it for the special case of isotropy against existing isotropic solutions. Afterwards parametric studies are conducted in order to assess the effect of cross-anisotropy on the seismic response of the wall-soil system.

Efficient layout planning of a construction site is fundamental for successful project undertaking as it enhances both productivity and safety of operations. The site layout planning problem is a complex combinatorial optimization problem involving multiple objectives and it grows significantly in size as the numbers of facilities and constraints increase. In addition, as construction evolves, the site layout may need to be dynamically reorganized at various schedule intervals to accommodate operational needs. As opposed to considering only productivity issues, this paper presents an approach for site layout planning that considers, in addition, safety and environmental issues resulting from the proximity or remoteness of certain facilities to others or to existing eco-sensitive assets (e.g., rivers). The optimization model developed includes the necessary constraints resulting from physical and operational limitations and can additionally model given priorities or preferences set by the project or site manager depending on particularities of the project or the construction site. The model is developed to handle more than one project phases which may optimally require facility relocation (especially in projects where the site layout “is moving” regularly (e.g., highway construction). The inclusion of several project phases and site reorganization requires solving a significantly larger problem than considering a static layout, if full optimization is done. For this reason, the development integrates the required robust search objective with the optimization capabilities of genetic algorithms (GAs). The model has been tested on several case studies considering both static and dynamic site layout planning and results indicate that it provides rational solutions, in response to decision parameters and problem constraints, and that dynamic modeling develops more effective layout planning than a static one.

The Volterra/Wiener neural network (VWNN) has been shown to be an effective tool for on-line estimation of non-linear restoring forces and responses. However, the power of the VWNN for on-line identification has not been fully harnessed due to the high sensitivity of its parameters. This study adopts a probabilistic approach in examining the effects of the VWNN's parameters on the robustness and stability of its estimation capabilities. Large ensembles of simulations were conducted in which random (earthquake-like) ground motions were used to excite representative non-linear structures, and on-line estimation of their acceleration responses was performed. The nonlinearity in the system was introduced via hysteretic restoring forces, and a variety of cases were tested, including softening and hardening. The results showed that each design parameter within the VWNN was linked to a certain type of performance sensitivity. The adaptive gain that controls the change in the weights of the VWNN was also directly linked to the stability of the estimates, as small increases in the gain led to the estimates diverging. Within the neural network, the weight within the transfer function was found to directly correlate with accuracy. The optimum set of parameters for a given excitation often produced unstable solutions for other excitations, but by understanding the relationships between the parameters and their sensitivities, a set of parameters could be carefully chosen to consistently produce accurate and stable on-line estimates for all simulations. The knowledge gained from the relationships between VWNN parameters also allowed for informed decisions on parameter sets for simulations involving different classes of nonlinearities. Offering users a starting point provides a necessary and helpful feature so often missing from other non-linear identification schemes that deal with non-parametric identification of complex nonlinear systems.

Efficient layout planning of a construction site is fundamental for successful project undertaking as it enhances both productivity and safety in construction sites. This task usually consists of identifying the temporary facilities needed to support construction operations, determining their size and shape, and optimally positioning them in the unoccupied areas within the site boundaries. The site layout planning problem is a complex combinatorial optimization problem involving multiple objectives and it grows significantly in size as the number of facilities and constraints increases. The existing literature includes a variety of analytical, heuristic, and meta-heuristic techniques for solving the problem but existing studies usually examine a small number of facilities and focus on travel distance minimization, ignoring generally cost related or other decision parameters. The objective of this study is to develop feasible and efficient site layout solutions in a realistic representation scheme taking into consideration not only the total distance traveled but also cost and safety parameters as well. A multi-objective optimization model is developed aiming at minimizing a generalized cost function which results from the construction cost of a facility placed at alternative locations, the transportation cost among locations, and any safety concern in the form of preferred proximity or remoteness of particular facilities to other facilities or work areas. The development integrates the required robust search objective with the optimization capabilities of the genetic algorithms (GAs). The model has been tested on several test cases and the results of a comparative study with existing methods from the literature are presented. The evaluation indicates that the proposed model provides effective and rational solutions, in response to decision parameters and problem constraints, and that it results in more robust layout planning than previous methods both qualitatively and quantitatively.

The efficient deployment of construction projects depends partly on the effective communication among project participants. This communication, however, is hindered by the large amount and wide variation of the information involved and the spatial dispersion of construction sites. This paper presents a web-based system that facilitates construction information management and communication. Unlike common document-based systems, the present work focuses on demonstrating the potential of data-centric web databases in enhancing the communication process during project execution. Further, this work has aimed to put emphasis on information modelling, i.e., representation of the construction process in data to facilitate exchange and interoperability of information. The proposed system consists of a relational database and a dynamic data-driven web application. The database contains 32 appropriately designed tables. End users access the database through the internet and can perform certain transactions according to their authorisation. The system implementation and testing have shown that it can provide structured and reliable information, quick and remote access, and prompt updating capabilities.

In this paper, empty container movements in the Los Angeles and Long Beach (LA/LB) port area are studied in an effort to reduce congestion by optimizing the empty container reuse. The dynamic empty container reuse is modeled analytically, and techniques are developed to optimize empty container operations. Several case studies based on current and projected demand in the LA/LB port area are used to evaluate the proposed techniques. Simulation results demonstrate that significant cost and congestion reductions can be achieved in the area, through reuse of empty containers. © 2004 Elsevier Ltd. All rights reserved. 42 1 43 60

This paper presents a knowledge-based system that is used for maintenance planning of highway concrete bridges. The system includes functions for maintenance priority setting among bridges, feasible treatment assessment in each case, and maintenance planning for a bridge stock. Maintenance priorities are set using a scoring model with decision parameters appropriately weighted. Feasible treatments are determined based on bridge condition and other factors that accelerate deterioration. Decisions for maintenance planning result from a linear programming model and are based on priority ranking, cost and effectiveness characteristics of feasible treatments, and existing budget constraints. The system has been successfully evaluated with actual and simulated data.

Container movement by trucks with time constraints at origins and destinations is modeled as an asymmetric "multi-Traveling Salesmen Problem with Time Windows" (m-TSPTW) with social constraints. A two-phase exact algorithm based on dynamic programming (DP) is proposed that finds the best routes for a fleet of trucks. Since the m-TSPTW problem is NP-hard, the computational time for optimally solving large size problems becomes prohibitive. For large size problems, we develop a hybrid methodology consisting of DP in conjunction with genetic algorithms. The developed algorithms are compared with an insertion heuristic method. Computational results demonstrate the efficiency of the developed algorithms. © 2004 Elsevier Ltd. All rights reserved. 41 3 235 259 Cited By :69

Existing methods dealing with the time-cost trade-off problem, which is encountered in project planning, have focused on the solution of a basic problem that does not adequately represent actual engineering projects. The aim of this paper is to develop a solution method considering additional realistic project characteristics such as generalised activity precedence relations and external time constraints for particular activities. The proposed method is formulated as a linear/integer program and provides the optimal project time cost curve and the minimum cost schedule. Evaluation results indicate that the method can be reliably applied to engineering projects.

Building on the basic idea behind the Restoring Force Method for the non-parametric identification of non-linear systems, a general procedure is presented for the direct identification of the state equation of complex non-linear systems. No information about the system mass is required, and only the applied excitation(s) and resulting acceleration are needed to implement the procedure. Arbitrary non-linear phenomena spanning the range from polynomial non-linearities to the noisy Duffing–van der Pol oscillator (involving product-type non-linearities and multiple excitations) or hysteretic behavior such as the Bouc–Wen model can be handled without difficulty. In the case of polynomial-type non-linearities, the approach yields virtually exact results for sufficiently rich excitations. For other types of non-linearities, the approach yields the optimum (in least-squares sense) representation in non-parametric form of the dominant interaction forces induced by the motion of the system. Several examples involving synthetic data corresponding to a variety of highly non-linear phenomena are presented to demonstrate the utility as well as the range of validity of the proposed approach.

Adaptive estimation procedures have gained significant attention by the research community to perform real-time identification of non-linear hysteretic structural systems under arbitrary dynamic excitations. Such techniques promise to provide real-time, robust tracking of system response as well as the ability to track time variation within the system being modeled. An overview of some of the authors’ previous work in this area is presented, along with a discussion of some of the emerging issues being tackled with regard to this class of problems. The trade-offs between parametric-based modeling and non-parametric modeling of non-linear hysteretic dynamic system behavior are discussed. Particular attention is given to (1) the effects of over- and under-parameterization on parameter convergence and system output tracking performance, (2) identifiability in multi-degree-of-freedom structural systems, (3) trade-offs in setting user-defined parameters for adaptive laws, and (4) the effects of noise on measurement integration. Both simulation and experimental results indicating the performance of the parametric and non-parametric methods are presented and their implications are discussed in the context of adaptive structures and structural health monitoring.

The problem of the determination of the dynamic pressures and the associated forces on a rigid, vertical cantilever wall retaining a semi-infinite, uniform, fully-saturated poroelastic (with or without hysteretic damping) layer of soil under conditions of plane strain is considered. The rigid wall and the base of the soil layer are both excited by an acceleration harmonically varying with time and spatially invariant. The method of solution is based on the theory of Mei and Foda and considers the total field to be approximated by the superposition of an elastodynamic problem with modified elastic constants and mass density for the whole domain and a diffusion problem for the pore fluid pressure confined to a boundary layer at the free boundary (top) of the soil layer. Both problems are solved analytically in the frequency domain. Extensive parametric and comparison studies are conducted in order to assess the range of values of the various parameters (frequency, shear modulus, Poisson's ratio, porosity and permeability) for which the accuracy of the present method against the direct one, reported in a companion paper, is satisfactory.

A method to distinguish between incidents and compression waves in freeway traffic is presented. The method is based on shock-wave propagation characteristics and aims to identify specific cross-correlation patterns in occupancy data from adjacent sensors along the freeway. The method is implemented in a computer algorithm and used to improve the detection performance of DELOS, an existing incident detection algorithm. Results from testing the algorithm with traffic and incident data demonstrate superior performance to DELOS in terms of detection and false alarm rates.

A method based on the use of neural networks is developed for the identification of systems encountered in the field of structural dynamics. The methodology is applied to the identification of linear and nonlinear dynamic systems such as the damped Duffing oscillator and the Van der Pol equation. The “generalization” ability of the neural networks is used to predict the response of the identified systems under deterministic and stochastic excitations. It is shown that neural networks provide high fidelity models of unknown structural dynamic systems, which are used in applications such as structural control, health monitoring of structures, earthquake engineering, etc.

Insulin levels, insulin resistance, and leptin levels were evaluated in 47 women who developed ovarian hyperstimulation syndrome (OHSS) after participation in assisted reproduction technologies programs and in 47 matched controls who did not develop such a complication. Analysis of the results in relation to underlying polycystic ovarian syndrome and hyperinsulinemia revealed no association of insulin levels, insulin resistance, and leptin levels with the development of OHSS.

The structure and performance of existing freeway incident detection methods are reviewed and a new method is proposed. The new method reduces the likelihood of false incident decisions that occur during short duration traffic disturbances by smoothing detector occupancies. Temporal smoothing is performed by the statistical mean or median of a data window moved over time. The algorithm considers the smoothed spatial occupancy difference between detector stations, and detects an incident when the difference changes significantly in a short time period. The proposed algorithm and a set of existing algorithms are tested with traffic and incident data from I-35W in Minneapolis. Test results, expressed in terms of detection rate at indicative false alarm rates, demonstrate the improved performance of the new algorithm over previous algorithms.

This paper explores the potential of using parallel distributed processing (neural network) approaches to identify the internal forces of typical systems encountered in the field of structural dynamics. Such problems arise in the context of structural control and the “health monitoring” of dynamic systems. After formulating the identification task as a neural network learning procedure, the method is applied to a representative example problem under a variety of excitations. The range of validity of the approach is demonstrated, and some application issues are discussed.

The control of a long, highly flexible, one-link manipulator arm is considered. we introduce a new method of controlling such manipulators, namely pointwise actuators (e.g. reaction jets) located at specified points along the length of the arm, in addition to a torque at the base. we obtain the control law and we investigate the important problem of the optimal location of the pointwise controllers. Only the theory of the method is presented here. Simulations will be completed before the Symposium.