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Many decisions are based on more than one criterion, judged by more than a single evaluator. Multievaluator multicriterion (MEMC) decision making can be controversial if bias or uncertainty find their way into the final decision. In fact, both public and private organizations have recently faced challenges when making decisions. In a previous study, the authors of this paper developed a multievaluator decision making model that reduces the effect of possible uncertainty resulting from an evaluator's insufficient expertise in a particular criterion. This paper builds on the previous model by also correcting for any possible evaluator favoritism or bias. It presents a more comprehensive mathematical model that supports MEMC decisions and protects decision makers and their agencies from potential criticism. Testing of the model shows that it performs better than the simple averaging method on 100% of the simulations. [ABSTRACT FROM AUTHOR]

The estimation of the atmospheric refraction coefficient by conducting simultaneous and mutual zenith observations is a well-known geodetic procedure. The respective mathematical model is based on certain assumptions regarding the actual path followed by the optical ray while propagating in the atmosphere (spherical symmetric model). Starting from this model an approximate solution can be derived, which is generally accepted in the literature on the subject. The present paper examines the mathematical model of this geodetic technique in a rigorous manner, which results in an exact solution for the computation of the atmospheric refraction coefficient or equivalent for the zenith angle correction that is due to the effect of the atmospheric refraction. As the direct computation of the exact solution is rather complicated, an iterative way of computing the same quantity is derived, which can be realized easily on any pocket calculator. In order to assess the derived formulas we investigate the applicability of the exact, the convergence rate of the iterative and the errors introduced by the approximate formulas, by conducting a representative series of synthetic numerical experiments. The overall discussion aims to provide a helpful insight into the geometric and theoretical features of this traditional geodetic method. To practitioners that attempt to apply the standard correction formulas to zenith observations in order to compensate the effect of atmospheric refraction in the frame of typical surveying applications, such as trigonometric leveling, the paper also points out possible numerical errors introduced by the traditional approximate formulas. [ABSTRACT FROM AUTHOR]

Mathematical and numerical models are used to simulate the transport of pollutants released into a water body. Such simulations can be computationally burdensome, however. One approach to overcome computational burdens associated with the simulation of pollutant transport is to use data-mining tools. The aim of this study is to simulate the concentration of methyl tertiary butyl ether (MTBE) at various locations within a river-reservoir system using the support vector regression (SVR) data-mining tool. The SVR tool is optimized by means of a genetic algorithm (GA). This paper's results indicate that the developed and optimized SVR tool is more accurate than artificial neural networks (ANN) and genetic programming (GP) when judged by the correlation coefficient of regression analysis (R2). [ABSTRACT FROM AUTHOR]

Because of the ongoing expansion of urban areas, transportation systems are being increasingly moved beneath the ground into tunnels. However, the construction of tunnels is very challenging regarding unexpected geological conditions, the protection of existing buildings from damage, and the control of financial and safety risks. During the tunnel construction process, different simulations are performed to predict, for example, settlements, soil excavation, or grouting behavior. Although these simulations should strongly interact, they often use independent heterogeneous geological data models and resources, thus resulting in unreliable predictions. This paper presents a hybrid ground data model along with necessary access concepts to support the automated management and exchange of continuously updated geological information among interacting simulations. The ground data model uses a boundary and a decomposition representation of the ground geometry with material information attached to each representation. These representations are converted to one another on demand to make up-to-date ground information available for participating tunneling simulations. To validate the proposed model and concepts, a case study is presented in which two typical simulations are coupled using the prototypically implemented hybrid ground data model. [ABSTRACT FROM AUTHOR]

This paper presents results of experimental and numerical modeling of ductile fracture and failure of elements made of S235JR steel subjected to static tension. The prediction of failure was generally based on the stress modified critical strain (SMCS) model. The numerical simulations were performed using the Gurson-Tvergaard-Needleman (GTN) model, which takes into consideration the material structure. The approach applied in this study was based on the computational cells with microstructurally based length scales. The cell size and initial porosity were determined through microstructural examinations of S235JR steel. The parameters of the GTN model for S235JR steel were established on the basis of the microstructural analysis and the numerical modeling of tensile strength tests. As a result, it was possible to determine the SMCS failure criterion to predict ductile fracture for S235JR steel. [ABSTRACT FROM AUTHOR]

Current processes for design and detailing in structural engineering are often broken up into a sequence of partial processes because of the complexity of the problem. But sequential additions of separate solutions rarely lead to an optimal design. For example, the basic structural system is often developed with its geometry and topology but without consideration of important aspects of structural performance, like robustness, redundancy, ductility. Decisions on performance are left for later design stages, when it is still possible to change details but too late to improve the structural system. A design that takes into account multiple objectives, such as safety, functionality, and aesthetics, requires a complete reconsideration of the authors' conventional sequential structural design process. Most engineering tools were developed many years ago as technology was much more limited, resulting in separate tools for separate objectives to be used in succession. In this paper, a new approach is presented as integrative structural design (ISD), where separate state-of-the-art solutions are synchronized in such a way that designers are not confined to predetermined solution paths but rather are enabled to consider different objectives concurrently including interactions between objectives. The resulting design tool for the conceptual, interactive modeling, simulation, and visualization of structural design or integrative design is presented under the term integrative structural design system (ISDS). [ABSTRACT FROM AUTHOR]

The paper focuses on the design of a robust H-infinity attitude controller for an unmanned small-scale helicopter. To take into account the salient nonlinearities, a model with six-degrees-of-freedom nonlinear dynamics and some linear approximation of the aerodynamic parts are used when extracting a linear model and performing simulations to check the performance of the designed controller. To design a robust H-infinity controller, an augmented plant is constructed by adjusting several weighting functions. Then, a robust controller is synthesized utilizing the augmented system with the weighting functions and H-infinity control methodology. Using computer simulation it is shown that the H-infinity controller works well when applied to the nonlinear model even though it is designed using a linear model approximation. Through frequency response analysis, it is shown that the proposed controller can overcome more than half of the uncertainty variations around a nominal point at the input side. The time-domain simulation with the nonlinear model demonstrates that the proposed controller is very robust in relation to the uncertainties, as was expected, overcoming large gain uncertainties and time delay in each input channel. The analysis and simulation results also show that the control system satisfies the Level 1 handling requirements, as defined in Aeronautical Design Standard ADS-33E-PRF. [ABSTRACT FROM AUTHOR]

In Part I of this two-part study, a theory is provided for the extension of the lattice discrete particle model (LDPM) to include fiber reinforcing capability. The resulting model, LDPM-F, is calibrated and validated in the present paper by comparing numerical simulations with experimental data gathered from the literature. The analyzed experiments include direct tension, confined and unconfined compression, and notched three-point bending tests. [ABSTRACT FROM AUTHOR]

The research into modeling walking-induced dynamic loading and its effects on footbridge structures and people using them has been intensified in the past decade after some high profile vibration serviceability failures. In particular, the crowd induced loading, characterized by spatially restricted movement of pedestrians, has kept attracting attention of researchers. However, it is the normal spatially unrestricted pedestrian traffic, and its vertical dynamic loading component, that is the most relevant for vibration serviceability checks for most footbridges. Despite the existence of numerous design procedures concerned with this loading, the current confidence in its modeling is low due to lack of verification of the models on as-built structures. This is the motivation behind reviewing the existing design procedures for modeling normal pedestrian traffic in this paper and evaluating their performance against the experimental data acquired on two as-built footbridges. Additionally, the use of Monte Carlo simulations is also investigated. Possible factors that cause discrepancies between measured and calculated vibration responses, including possibility of existence of pedestrian-structure dynamic interaction, are discussed. [ABSTRACT FROM AUTHOR]

This research proposes a hybrid simulation approach based upon the principles of system dynamics (SD) and discrete event simulation (DES), which facilitates a better understanding of complex interactions among various processes in large-scale construction. The significance of the construction context that interacts with construction operations is highlighted, and a hybrid SD-DES approach is proposed as a means to capture the feedback between the two. In particular, this paper focuses on how to seamlessly integrate SD and DES within the framework of a modeling perspective. For the purpose of substantiating the discussion, a pipeline installation process is modeled using the proposed hybrid approach, with specific consideration given to how the approach can serve to address complex interactions between operation and context. [ABSTRACT FROM AUTHOR]

Both the crushing and indentation behaviors of sandwich materials are important aspects in failure analysis and energy absorption. In this paper, the core crushing strength of honeycomb materials from the experiment is briefly introduced, and the indentation of sandwich structures is studied in detail. Using the beam on elastic-plastic foundation models, theoretical formulations for predicting indentation behavior of sandwich materials are proposed, from which the mechanical response of elastic-plastic sandwich beams are obtained. Three stages of failure are clearly depicted by the global stiffness changes in the load versus displacement curve of elastic-plastic beams. The models are compared with the available experimental data and numerical simulation, and relatively close agreements are achieved. The compliance and compliance gradient derived form the indentation models are then incorporated with the equation of motion of the projectile to study impact response of elastic-plastic beams, and the impact energy dissipation due to the plasticity of elastic-plastic sandwich beam is uniquely recovered from the derived damping ratio. The beam on elastic-plastic foundation models proposed can be used to predict the indentation behavior of honeycomb sandwich materials, and the unique incorporation of the compliance and compliance gradient of the elastic-plastic sandwich beams in the standard mass-spring model can be utilized to characterize the effect of core compression and plasticity in the impact process. [ABSTRACT FROM AUTHOR]

Conventional limit equilibrium methods are commonly used to assess the stability of embankments. The finite-element method, as an alternative to limit equilibrium methods, is being increasingly used in the deterministic stability analysis of slopes or embankments. In this paper, a practical procedure for integrating the finite-element method and the limit equilibrium methods into probabilistic stability analysis for embankments is presented. The response surface method is adopted to approximate the performance function for the stability problems and the first-order reliability method is used to calculate the reliability index based on an intuitive expanding ellipsoid perspective. The advantages of the response surface method as a bridge between stand-alone numerical packages and spreadsheet-based reliability analysis via automatic constrained optimization are demonstrated and discussed through a hypothetical two-layer slope and an actual case of the James Bay Dykes. The results show the ease and successful implementation of the proposed procedure for reliability analysis of embankments. [ABSTRACT FROM AUTHOR]

The integration of modeling and simulation tools with robust and efficient methods of optimal design offers a rational approach to explore new concepts and designs. However, a widespread adaptation of these tools in the industry design environment will require that they incorporate a systematic analysis of uncertainty in all aspects of the design process. A lack of confidence in designs generated in a simulation-based approach is the result of uncertainties in the predictive capabilities of physics-based models used in the simulations, and poor representation of uncertainties and their propagation in a coupled systems engineering design problem. A data- and knowledge-lean environment, typical of a design process involving novel concepts, further exacerbates the situation; design engineers often make gross assumptions about distributional information of random variables and parameters, thereby adding to the uncertainty associated with the design results. The paper focuses on numerical and analytical tools by which to model uncertainty and risk in a simulation-based design environment, including cases where the uncertainty does not conform to standard probabilistic distributions. A specific focus of the modeling effort is an approach to establish confidence intervals for response predictions available from analytical and numerical models, as well as surrogate approximations used in the design process. Innovative adaptations of formal optimization methods in a nondeterministic design setting are discussed, including design problem formulations that examine the nondeterministic design problem in a multicriteria optimization framework. Simple design problems are used to illustrate the concepts and to underscore the deficiencies in a purely deterministic approach to the design problem. [ABSTRACT FROM AUTHOR]

Computer analysis of structures has traditionally been carried out using the displacement method combined with an incremental iterative scheme for nonlinear problems. In this paper, a Lagrangian approach is developed, which is a mixed method, where besides displacements, the stress resultants and other variables of state are primary unknowns. The method can potentially be used for the analysis of collapse of structures subjected to severe vibrations resulting from shocks or dynamic loads. The evolution of the structural state in time is provided a weak formulation using Hamilton’s principle. It is shown that a certain class of structures, known as reciprocal structures, has a mixed Lagrangian formulation in terms of displacements and internal forces. The form of the Lagrangian is invariant under finite displacements and can be used in geometric nonlinear analysis. For numerical solution, a discrete variational integrator is derived starting from the weak formulation. This integrator inherits the energy and momentum conservation characteristics for conservative systems and the contractivity of dissipative systems. The integration of each step is a constrained minimization problem and it is solved using an augmented Lagrangian algorithm. In contrast to the traditional displacement-based method, the Lagrangian method provides a generalized formulation which clearly separates the modeling of components from the numerical solution. Phenomenological models of components, essential to simulate collapse, can be incorporated without having to implement model-specific incremental state determination algorithms. The state variables are determined at the global level by the optimization method. [ABSTRACT FROM AUTHOR]

The focus of this paper is to demonstrate the application of a recently developed Bayesian state estimation method to the recorded seismic response of a building and to discuss the issue of model selection. The method, known as the particle filter, is based on stochastic simulation. Unlike the well-known extended Kalman filter, it is applicable to highly nonlinear systems with non-Gaussian uncertainties. The particle filter is applied to strong motion data recorded in the 1994 Northridge earthquake in a seven-story hotel whose structural system consists of nonductile reinforced-concrete moment frames, two of which were severely damaged during the earthquake. We address the issue of model selection. Two identification models are proposed: a time-varying linear model and a simplified time-varying nonlinear degradation model. The latter is derived from a nonlinear finite-element model of the building previously developed at Caltech. For the former model, the resulting performance is poor since the parameters need to vary significantly with time in order to capture the structural degradation of the building during the earthquake. The latter model performs better because it is able to characterize this degradation to a certain extent even with its parameters fixed. For this case study, the particle filter provides consistent state and parameter estimates, in contrast to the extended Kalman filter, which provides inconsistent estimates. It is concluded that for a state estimation procedure to be successful, at least two factors are essential: an appropriate estimation algorithm and a suitable identification model. [ABSTRACT FROM AUTHOR]

This paper presents a comparison of two algorithms—the forward-elimination and branch-segment transformation equations—for separating out end-node variables for each branch to model both steady and unsteady flows in branched and looped canal networks. In addition, the performance of the recursive forward-elimination method is compared with the standard forward-elimination method. The Saint–Venant equations are discretized using the four-point implicit Preissmann scheme, and the resulting nonlinear system of equations is solved using the Newton–Raphson method. The algorithm using branch-segment transformation equations is found to be at least five times faster than the algorithm using the forward-elimination method. Further, the algorithm using branch-segment transformation equations requires less computer storage than the algorithm using the forward-elimination method, particularly when only nonzero elements of the global matrix are stored. Comparison between the Gauss-elimination method and the sparse matrix solution technique for the solution of the global matrix revealed that the sparse matrix solution technique takes less computational time than the Gauss-elimination method. [ABSTRACT FROM AUTHOR]

Mathematical modeling using the cellular automata (CA) approach is an attractive alternative to models based on partial differential equations when the domains to be simulated have complex boundary conditions. The computational efficiency of CA models is readily observed when using parallel processors, but implementations in personal computers are, although feasible, not quite efficient. In an effort to improve the computational efficiency of CA implementations in personal computers, we introduce in this paper a bitwise implementation based on the use of each bit as a different CA cell. Thus, in a 32-bit processor, each computer word stores information about 32 different CA cells. We illustrate the bitwise implementation with a biofilm model that simulates substrate diffusion and microbial growth of a single-species, single-substrate, structurally heterogeneous biofilm. The efficiency of the bitwise implementation was evaluated by comparing the computational time of equivalent CA biofilm models that used more common low-level implementations, namely, if-then operators and look-up tables. The processing speed of the bitwise implementation was over an order of magnitude higher than the processing speed of the other two implementations. Regarding the biofilm simulations, the CA model exhibited self-organization of the biofilm morphology as a function of kinetic and physical parameters. [ABSTRACT FROM AUTHOR]

Permeability is an important property that influences the performance of hot-mix asphalt (HMA). It is a function of compaction effort, and several properties of HMA such as asphalt content, and the shape and size distribution of aggregates. Due to the different laboratory and field methods for measuring permeability, and the interaction among the factors that influence its value, it would be difficult to develop an analytical equation that accurately relates permeability to all factors contributing to HMA permeability. This paper presents a simple equation for approximating the permeability of asphalt mixes. It utilizes the percent air voids and surface area of aggregates. The equation is empirical but it is derived based on the well-known Kozeny–Carman equation for calculating the permeability of granular materials. The developed equation was used successfully to fit permeability data collected from several studies that carried field and laboratory measurements of HMA permeability. A finite element model was developed to investigate the influence of the gradient of percent air voids in HMA on water flow patterns. The x-ray computed tomography was used to measure the percent air void gradients among sublayers of the asphalt mix. The permeability of these sublayers was calculated using the developed equation, and used as an input to the finite element model. The simulation results show that air void gradients in HMA encourage lateral flow in the horizontal direction and reduce the flow in the vertical direction. [ABSTRACT FROM AUTHOR]

This paper describes a mathematical model for the hydraulic characterization of a field-scale solid set sprinkler irrigation system with a double-line lateral layout configuration. Formulation of the basic hydraulic equations along the mainline and laterals is based on manifold hydraulics. Lateral hydraulics remains the same as that described in a previously published paper, for systems with single-line laterals. A description of the mainline hydraulics of systems with a double-line lateral layout configuration, which requires the formulation and iterative solution of a system of nonlinear equations, is presented here. The hydraulic characterization functionality of the model, described in a previously published paper, serves as an interface for coupling the numerical solutions of the lateral and mainline hydraulic equations. In addition, this paper presents a description of the simulation functionality of the sprinkler hydraulic model and a related numerical algorithm, which is based on one-dimensional optimization. A comparison of model output with field data suggests that model performance is satisfactory. Example problems, consisting of field-scale solid set sprinkler systems with single-line and double-line laterals, are used to highlight the practical application of the hydraulic model. [ABSTRACT FROM AUTHOR]

A mathematical model for a field-scale hydraulic characterization and simulation of solid set sprinkler systems with single-line and double-line lateral layout configurations is developed. This paper describes the hydraulic equations, numerical solution algorithms, and the hydraulic characterization functionality of the model for a system with single-line laterals. Numerical solutions of the lateral and mainline hydraulic equations are based on standard manifold hydraulics. A rigorous and flexible formulation of the sprinkler hydraulic problem is obtained by coupling the energy equation for each lateral and mainline segment with the continuity equation at a node. The resulting set of equations is then solved iteratively, starting from the distal end sprinkler or mainline outlet and moving sequentially upstream. The hydraulic characteristics of the sprinklers is defined based on manufacture's pressure head and discharge data, and the hydraulic characteristics of each mainline outlet are computed by the system hydraulic characterization functionality of the model. The cubic spline method is used to interpolate mainline outlet discharges from the respective hydraulic characteristics curves as a function of total heads, effectively providing the interface for coupling the numerical solutions of the laterals and the mainline hydraulic equations. Evaluation of the hydraulic model with field data suggests that the hydraulic model is accurate. A companion paper describes the formulation of the hydraulic equations and numerical solutions for sprinkler systems with double-line laterals and the system simulation functionality of the model. [ABSTRACT FROM AUTHOR]

Operational performance in residential construction production systems is assessed based on measures such as average house-completion time, number of houses under construction, lead time, and customer service. These systems, however, are prone to nonuniformity and interruptions caused by a wide range of variables such as inclement weather conditions, accidents at worksites, fluctuations in demand for houses, and rework. The availability and capacity of resources therefore are not the sole measures for evaluating construction production systems capacity, especially when rework is involved. The writers' aim is to investigate the effects of rework timeframe and frequency/length on tangible performance measures. Different call-back timeframes for rework and their impact on house-completion times are modeled and analyzed. Volume home-building was chosen as the industry sector studied in the research reported in this paper because it is a data-rich environment. The writers designed several experiments to model on time, late, and early call-back timeframes in the presence of rework with different length and frequency. Both mathematical modeling and discrete-event simulation were then used to compare and contrast outputs. The measurements showed that the average completion time is shorter in systems interrupted by frequent but short rework. In other words, a smaller downstream buffer between processes is required to avoid work starvation than those systems affected by infrequent but long interruptions. Early call-backs for rework can significantly increase the number of house completions over the long run. This indicates that there is an opportunity for the mass house-building sector to improve work practice and project delivery by effectively managing rework and its related variables. The research reported in this paper builds on the current body-of-knowledge by applying even-flow production theory to the analysis of rework in the residential construction sector, with the intention of ensuring minimal disruption to construction production process and improving productivity. [ABSTRACT FROM AUTHOR]