Flow Modeling (flow + modeling)

Distribution by Scientific Domains

Selected Abstracts

A Bayesian Approach to Prediction Using the Gravity Model, with an Application to Patient Flow Modeling

Peter Congdon
This paper investigates the potential for estimation and prediction by Bayesian methods of hospitalization flows classified by place of residence and hospital site. The focus is especially with respect to emergency (unplanned) admissions to hospitals. The need for strategic modeling and forecasting arises since the structure of U.K. emergency service provision is subject to changes involving site closures or changes in bed numbers. The gravity model, reflecting patient demand, hospital supply, and distance effects has been applied to patient flows, but generally in a situation of unchanged destination states. It may be modified, however, in accordance with major changes in hospital service structure, to include access effects (the interplay of supply and distance) and temporal variation in its parameters. Therefore, prediction may be applied to a "new" situation defined, for example, by closures of entire hospital sites. The modeling approach used may be adapted to other flow models where destinations may be added or eliminated (for example, trade-area models). A case study involves a sector of London subject to such a restructuring following the U.K. government's 1997,98 review of London's emergency services. [source]

Foreword: Ground Water Flow Modeling with the Analytic Element Method

GROUND WATER, Issue 1 2006
Hendrik M. Haitjema
No abstract is available for this article. [source]

A Probabilistic Method for Estimating Monitoring Point Density for Containment System Leak Detection

GROUND WATER, Issue 4 2000
Randall R. Ross
The use of physical and hydraulic containment systems for the isolation of contaminated ground water and aquifer materials associated with hazardous waste sites has increased during the last decade. The existing methodologies for monitoring and evaluating leakage from hazardous waste containment systems rely primarily on limited hydraulic head data. The number of hydraulic head monitoring points available at most sites employing physical containment systems may be insufficient to identify significant leaks from the systems. A probabilistic approach for evaluating the performance of containment systems, based on estimations of apparent leakage rates, is used to introduce a methodology for determining the minimum number of monitoring points necessary to identify the hydraulic signature of leakage from a containment system. The probabilistic method is based on the principles of geometric probability. The method is demonstrated using three-dimensional ground water flow modeling results of leakage through a vertical barrier. The results indicate that the monitoring point spacing used at many hazardous waste sites likely is inadequate to detect the hydraulic signatures of all but the largest leaks. [source]

Comprehensive process design study for layered-NOX -control in a tangentially coal fired boiler

AICHE JOURNAL, Issue 3 2010
Wei Zhou
Abstract As emissions regulations for coal-fired power plants become stricter worldwide, layering combustion modification and post-combustion NOX control technologies can be an attractive option for efficient and cost-effective NOX control in comparison to selective catalytic reduction (SCR) technology. The layered control technology approach designed in this article consists of separate overfire air (SOFA), reburn, and selective noncatalytic reduction (SNCR). The combined system can achieve up to 75% NOX reduction. The work presented in this article successfully applied this technology to NRG Somerset Unit 6, a 120-MW tangential coal-fired utility boiler, to reduce NOX emissions to 0.11 lb/MMBtu (130 mg/Nm3), well under the US EPA SIP Call target of 0.15 lb/MMBtu. The article reviews an integrated design study for the layered system at Somerset and evaluates the performance of different layered-NOX -control scenarios including standalone SNCR (baseline), separated overfire air (SOFA) with SNCR, and gas reburn with SNCR. Isothermal physical flow modeling and computational fluid dynamics simulation (CFD) were applied to understand the boiler flow patterns, the combustible distributions and the impact of combustion modifications on boiler operation and SNCR performance. The modeling results were compared with field data for model validation and verification. The study demonstrates that a comprehensive process design using advanced engineering tools is beneficial to the success of a layered low NOX system. 2009 American Institute of Chemical Engineers AIChE J, 2010 [source]


Francesco Lisi
ABSTRACT: This paper considers the problem of forecasting the discharge time series of a river by means of a chaotic approach. To this aim, we first check for some evidence of chaotic behavior in the dynamic by considering a set of different procedures, namely, the phase portrait of the attractor, the correlation dimension, and the largest Lyapunov exponent. Their joint application seems to confirm the presence of a nonlinear deterministic dynamic of chaotic type. Second, we consider the so-called nearest neighbors predictor and we compare it with a classical linear model. By comparing these two predictors, it seems that nonlinear river flow modeling, and in particular chaotic modeling, is an effective method to improve predictions. [source]

Modeling process flow using diagrams

Benjamin Kemper
Abstract In the practice of process improvement, tools such as the flowchart, the value-stream map (VSM), and a variety of ad hoc variants of such diagrams are commonly used. The purpose of this paper is to present a clear, precise, and consistent framework for the use of such flow diagrams in process improvement projects. The paper finds that traditional diagrams, such as the flowchart, the VSM, and OR-type of diagrams, have severe limitations, miss certain elements, or are based on implicit but consequential premises. These limitations restrict the applicability of traditional diagrams in non-manufacturing areas such as service and healthcare processes. We show that a rational reconstruction for the use of diagrams in various disciplines regarding process flow boils down to a generic framework of elements, definitions of generic process metrics, and three classes of applications, namely the ,as-is', ,could-be', and ,should-be' analysis. The goal is not to replace all currently used diagrams, but merely to discuss the role of diagram usage in process flow modeling. This paper provides an explicit framework that is unambiguous and flexible, and has the potential to serve as a guideline for the practitioner, in manufacturing as well as in service and healthcare. Besides, it may serve as a starting point to develop an ontology of business processes. Copyright 2009 John Wiley & Sons, Ltd. [source]