The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Alan R Kerstein - One of the best experts on this subject based on the ideXlab platform.

  • one dimensional turbulence simulation of turbulent jet diffusion flames Model Formulation and illustrative applications
    Combustion and Flame, 2001
    Co-Authors: Tarek Echekki, Alan R Kerstein, Thomas D Dreeben, Jyhyuan Chen
    Abstract:

    Abstract A novel Modeling approach to the simulation of turbulent jet diffusion flames based on the One-Dimensional Turbulence (ODT) Model is presented. The approach is based on the mechanistic distinction between molecular processes (reaction and diffusion), implemented by the direct solution of unsteady boundary-layer reaction-diffusion equations, and turbulent advection in a time-resolved simulation on a 1D domain. The 1D domain corresponds to a direction transverse to the mean flow of the jet. Temporal simulations of jet diffusion flames are performed to illustrate the Model’s predictions of turbulence-chemistry interactions in jet diffusion flames. ODT predictions of flow entrainment, finite-rate chemistry and differential diffusion effects are investigated in hydrogen-air diffusion flames at two Reynolds numbers. Two-dimensional renderings of stirring events from a single realization show that ODT reproduces a number of salient features of simple developing turbulent shear flows that reflect the growth of the boundary layer and the mechanisms of turbulence cascade and spatial intermittency. Multiple realizations of jet simulations are used to compute axial and conditional statistics of streamwise velocity, major species, NO, and temperature. Comparison with experimental measurements indicates that chemical properties of interest can be captured by a Model that involves a simplified representation of the flow structure. The results show. strong differential diffusion effects in the near field, with attenuation farther downstream.

  • One-dimensional turbulence : Model Formulation and application to homogeneous turbulence, shear flows, and buoyant stratified flows
    Journal of Fluid Mechanics, 1999
    Co-Authors: Alan R Kerstein
    Abstract:

    A stochastic Model, implemented as a Monte Carlo simulation, is used to compute statistical properties of velocity and scalar fields in stationary and decaying homogeneous turbulence, shear flow, and various buoyant stratified flows. Turbulent advection is represented by a random sequence of maps applied to a one-dimensional computational domain. Profiles of advected scalars and of one velocity component evolve on this domain. The rate expression governing the mapping sequence reflects turbulence production mechanisms. Viscous effects are implemented concurrently. Various flows of interest are simulated by applying appropriate initial and boundary conditions to the velocity profile. Simulated flow microstructure reproduces the −5/3 power-law scaling of the inertial-range energy spectrum and the dissipation-range spectral collapse based on the Kolmogorov microscale. Diverse behaviours of constant-density shear flows and buoyant stratified flows are reproduced, in some instances suggesting new interpretations of observed phenomena. Collectively, the results demonstrate that a variety of turbulent flow phenomena can be captured in a concise representation of the interplay of advection, molecular transport, and buoyant forcing.

Malte Fliedner - One of the best experts on this subject based on the ideXlab platform.

  • the assembly line balancing and scheduling problem with sequence dependent setup times problem extension Model Formulation and efficient heuristics
    OR Spectrum, 2013
    Co-Authors: Armin Scholl, Nils Boysen, Malte Fliedner
    Abstract:

    Assembly line balancing problems (ALBP) consist of distributing the total workload for manufacturing any unit of the products to be assembled among the work stations along a manufacturing line as used in the automotive or the electronics industries. Usually, theory assumes that, within each station, tasks can be executed in an arbitrary precedence-feasible sequence without changing station times. In practice, however, the task sequence may influence the station time considerably as sequence-dependent setups (e.g., walking distances, tool changes) have to be considered. Including this aspect leads to a joint balancing and scheduling problem, which we call SUALBSP (setup assembly line balancing and scheduling problem). In this paper, we modify the problem by Modeling setups more realistically, give a new, more compact mathematical Model Formulation and develop effective heuristic solution procedures. Computational experiments based on existing and new data sets indicate that the new procedures outperform formerly proposed heuristics. They are able to solve problem instances of real-world size with small deviations from optimality in computation times short enough to be accepted in real-world decision support systems.

  • the assembly line balancing and scheduling problem with sequence dependent setup times problem extension Model Formulation and efficient heuristics
    2009
    Co-Authors: Armin Scholl, Nils Boysen, Malte Fliedner
    Abstract:

    Assembly line balancing problems (ALBP) consist of distributing the total workload for manufacturing any unit of the products to be assembled among the work stations along a manufacturing line as used in the automotive or the electronics industries. Usually, it is assumed in research papers that, within each station, tasks can be executed in an arbitrary precedence-feasible sequence without changing station times. In practice, however, the task sequence may influence the station time considerably as sequence-dependent setups (e.g., walking distances, tool changes, withdrawal of parts from material boxes) have to be considered. Including this aspect leads to a joint balancing and scheduling problem, which we call SUALBSP (setup assembly line balancing and scheduling problem). In this paper, we modify the problem by Modeling setups more realistically, give a new, more compact mathematical Model Formulation and develop effective heuristic solution procedures. Computational experiments based on existing and new data sets indicate that the new procedures outperform formerly proposed heuristics and are able to solve problem instances of realworld size with small deviations from optimality in short time.

Chandra R Bhat - One of the best experts on this subject based on the ideXlab platform.

  • a multiple discrete continuous nested extreme value mdcnev Model Formulation and application to non worker activity time use and timing behavior on weekdays
    Transportation Research Part B-methodological, 2010
    Co-Authors: Abdul Rawoof Pinjari, Chandra R Bhat
    Abstract:

    This paper develops a multiple discrete-continuous nested extreme value (MDCNEV) Model that relaxes the independently distributed (or uncorrelated) error terms assumption of the multiple discrete-continuous extreme value (MDCEV) Model proposed by Bhat [Bhat, C.R., 2005. A multiple discrete-continuous extreme value Model: Formulation and application to discretionary time-use decisions. Transportation Research Part B 39 (8), 679-707; Bhat, C.R., 2008. The multiple discrete-continuous extreme value (MDCEV) Model: role of utility function parameters, identification considerations, and Model extensions. Transportation Research Part B 42 (3), 274-303]. The MDCNEV Model captures inter-alternative correlations among alternatives in mutually exclusive subsets (or nests) of the choice set, while maintaining the closed-form of probability expressions for any (and all) consumption pattern(s). The MDCNEV Model is applied to analyze non-worker out-of-home discretionary activity time-use and activity timing decisions on weekdays using data from the 2000 San Francisco Bay Area data. This empirical application contributes to the literature on activity time-use and activity timing analysis by considering daily activity time-use behavior and activity timing preferences in a unified utility maximization-based framework. The Model estimation results provide several insights into the determinants of non-workers' activity time-use and timing decisions. The MDCNEV Model performs better than the MDCEV Model in terms of goodness of fit. However, the nesting parameters are very close to 1, indicating low levels of correlation. Nonetheless, even with such low correlation levels, empirical policy simulations indicate non-negligible differences in policy predictions and substitution patterns exhibited by the two Models. Experiments conducted using simulated data also corroborate this result.

  • a multiple discrete continuous extreme value Model Formulation and application to discretionary time use decisions
    Transportation Research Part B-methodological, 2005
    Co-Authors: Chandra R Bhat
    Abstract:

    Several consumer demand choices are characterized by the choice of multiple alternatives simultaneously. An example of such a choice situation in activity-travel analysis is the type of discretionary (or leisure) activity to participate in and the duration of time investment of the participation. In this context, within a given temporal period (say a day or a week), an individual may decide to participate in multiple types of activities (for example, in-home social activities, out-of-home social activities, in-home recreational activities, out-of-home recreational activities, and out-of-home non-maintenance shopping activities). In this paper, we derive and formulate a utility theory-based Model for discrete/continuous choice that assumes diminishing marginal utility as the level of consumption of any particular alternative increases (i.e., satiation). This assumption yields a multiple discreteness Model (i.e., choice of multiple alternatives can occur simultaneously). This is in contrast to the standard discrete choice Model that is based on assuming the absence of any diminishing marginal utility as the level of consumption of any alternative increases (i.e., no satiation), leading to the case of strictly single discreteness. The econometric Model formulated here, which we refer to as the multiple discrete-continuous extreme value (MDCEV) Model, has a surprisingly simple and elegant closed form expression for the discrete-continuous probability of not consuming certain alternatives and consuming given levels of the remaining alternatives. To our knowledge, we are the first to develop such a simple and powerful closed-form Model for multiple discreteness in the literature. This Formulation should constitute an important milestone in the area of multiple discreteness, just as the multinomial logit (MNL) represented an important milestone in the area of single discreteness. Further, the MDCEV Model formulated here has the appealing property that it collapses to the familiar multinomial logit (MNL) choice Model in the case of single discreteness. Finally, heteroscedasticity and/or correlation in unobserved characteristics affecting the demand of different alternatives can be easily incorporated within the MDCEV Model framework using a mixing approach. The MDCEV Model and its mixed variant are applied to analyze time-use allocation decisions among a variety of discretionary activities on weekends using data from the 2000 San Francisco Bay Area survey.

  • a mixed spatially correlated logit Model Formulation and application to residential choice Modeling
    Transportation Research Part B-methodological, 2004
    Co-Authors: Chandra R Bhat, Jessica Y Guo
    Abstract:

    In recent years, there have been important developments in the simulation analysis of the mixed multinomial logit Model as well as in the Formulation of increasingly flexible closed-form Models belonging to the generalized extreme value class. In this paper, we bring these developments together to propose a mixed spatially correlated logit (MSCL) Model for location-related choices. The MSCL Model represents a powerful approach to capture both random taste variations as well as spatial correlation in location choice analysis. The MSCL Model is applied to an analysis of residential location choice using data drawn from the 1996 Dallas-Fort Worth household survey. The empirical results underscore the need to capture unobserved taste variations and spatial correlation, both for improved data fit and the realistic assessment of the effect of sociodemographic, transportation system, and land-use changes on residential location choice.

Andre Filiatrault - One of the best experts on this subject based on the ideXlab platform.

  • seismic analysis of woodframe structures i Model Formulation
    Journal of Structural Engineering-asce, 2004
    Co-Authors: Bryan Folz, Andre Filiatrault
    Abstract:

    A simple numerical Model to predict the dynamic characteristics, quasistatic pushover, and seismic response of woodframe buildings is presented. In this Model the building structure is composed of two primary components: rigid horizontal diaphragms and nonlinear lateral load resisting shear wall elements. The actual three-dimensional building is degenerated into a two-dimensional planar Model using zero-height shear wall spring elements connected between adjacent diaphragms or the foundation. The degrading strength and stiffness hysteretic behavior of each wood shear wall in the building can be characterized using an associated numerical Model that predicts the walls load-displacement response under general quasistatic cyclic loading. In turn, in this Model, the hysteretic behavior of each shear wall is represented by an equivalent nonlinear shear spring element. With this simple approach the response of the building is defined in terms of only three degrees of freedom per floor. This numerical Model has ...

Fengqi You - One of the best experts on this subject based on the ideXlab platform.

  • integrated scheduling and dynamic optimization by stackelberg game bilevel Model Formulation and efficient solution algorithm
    Industrial & Engineering Chemistry Research, 2014
    Co-Authors: Yunfei Chu, Fengqi You
    Abstract:

    We propose a novel method to solve the integrated scheduling and dynamic optimization problem for sequential batch processes. The scheduling problem and the dynamic optimization problems are collaborated by a Stackelberg game (leader–followers game). Mathematically, the integrated problem is formulated into a bilevel program. The scheduling problem in the upper level acts as the leader, while the dynamic optimization problems in the lower level are the followers. The follower problems have their own objectives, but the leader problem can coordinate the follower problems to pursue its objective. To efficiently solve the bilevel program, we develop a decomposition algorithm. It first solves the lower-level problems to determine the response functions. The response functions are then represented by piecewise linear functions to solve the upper-level problem. The integrated method is consistent with the ISA 95 standard and can be easily implemented in an IT infrastructure following the standard. The performan...