A comprehensive literature classification of simulation optimisation methods

Simulation Optimization (SO) provides a structured approach to the system design and configuration when analytical expressions for input/output relationships are unavailable. Several excellent surveys have been written on this topic. Each survey concentrates on only few classification criteria. This paper presents a literature survey with all classification criteria on techniques for SO according to the problem of characteristics such as shape of the response surface (global as compared to local optimization), objective functions (single or multiple objectives) and parameter spaces (discrete or continuous parameters). The survey focuses specifically on the SO problem that involves single per-formance measureSimulation Optimization, classification methods, literature survey

Computational Fluid Dynamics Methods Used in the Development of the Space Launch System Liftoff and Transition Lineloads Databases

The objective of this paper is to document the reasoning and trade studies that supported the selection of appropriate tools for constructing aerodynamic lineload databases for the Liftoff and Transition phases of flight for launch vehicles. These decisions were made amid the maturation of an evolving workflow for generating databases on variants of the Space Launch System launch vehicle, with most being based on results from brief developmental studies performed in response to specific, unforeseen challenges that were encountered in analyzing a given configuration. This report is intended to provide a summary of the results and the decision-making processes chronologically over the design cycles of various configurations, starting with isolated free-air bodies for the Block 1 Crew, then the Block 1B Crew and Cargo configurations, and most recently the Block 1B Crew configuration in proximity to the launch tower. The results from these analyses led to the selection of the CREATE-AV Kestrel flowsolver for simulating these problems. The need to accurately capture the expected leeward-wake flow field characteristics required the use of Delayed Detached Eddy Simulation (DDES) method, for which the vorticity magnitude was employed as the solution Adaptive Mesh Refinement (AMR) function over the off-body Cartesian grid region. In addition, the Spalart-Allmaras (SA) model is used to account for the flow turbulence effects

Empiricism and stochastics in cellular automaton modeling of urban land use dynamics

An increasing number of models for predicting land use change in regions of rapidurbanization are being proposed and built using ideas from cellular automata (CA)theory. Calibrating such models to real situations is highly problematic and to date,serious attention has not been focused on the estimation problem. In this paper, wepropose a structure for simulating urban change based on estimating land usetransitions using elementary probabilistic methods which draw their inspiration fromBayes' theory and the related ?weights of evidence? approach. These land use changeprobabilities drive a CA model ? DINAMICA ? conceived at the Center for RemoteSensing of the Federal University of Minas Gerais (CSR-UFMG). This is based on aneight cell Moore neighborhood approach implemented through empirical land useallocation algorithms. The model framework has been applied to a medium-size townin the west of São Paulo State, Bauru. We show how various socio-economic andinfrastructural factors can be combined using the weights of evidence approach whichenables us to predict the probability of changes between land use types in differentcells of the system. Different predictions for the town during the period 1979-1988were generated, and statistical validation was then conducted using a multipleresolution fitting procedure. These modeling experiments support the essential logicof adopting Bayesian empirical methods which synthesize various information aboutspatial infrastructure as the driver of urban land use change. This indicates therelevance of the approach for generating forecasts of growth for Brazilian citiesparticularly and for world-wide cities in general

Partial differential equations for self-organization in cellular and developmental biology

Understanding the mechanisms governing and regulating the emergence of structure and heterogeneity within cellular systems, such as the developing embryo, represents a multiscale challenge typifying current integrative biology research, namely, explaining the macroscale behaviour of a system from microscale dynamics. This review will focus upon modelling how cell-based dynamics orchestrate the emergence of higher level structure. After surveying representative biological examples and the models used to describe them, we will assess how developments at the scale of molecular biology have impacted on current theoretical frameworks, and the new modelling opportunities that are emerging as a result. We shall restrict our survey of mathematical approaches to partial differential equations and the tools required for their analysis. We will discuss the gap between the modelling abstraction and biological reality, the challenges this presents and highlight some open problems in the field

Applications of stochastic simulation in two-stage multiple comparisons with the best problem and time average variance constant estimation

In this dissertation, we study two problems. In the first part, we consider the two-stage methods for comparing alternatives using simulation. Suppose there are a finite number of alternatives to compare, with each alternative having an unknown parameter that is the basis for comparison. The parameters are to be estimated using simulation, where the alternatives are simulated independently. We develop two-stage selection and multiple-comparison procedures for simulations under a general framework. The assumptions are that each alternative has a parameter estimation process that satisfies a random- time-change central limit theorem (CLT), and there is a weakly consistent variance estimator (WCVE) for the variance constant appearing in the CLT. The framework encompasses comparing means of independent populations, functions of means, and steady-state means. One problem we consider of considerable practical interest and not handled in previous work on two-stage multiple-comparison procedures is comparing quantiles of alternative populations. We establish the asymptotic validity of our procedures as the prescribed width of the confidence intervals or indifference-zone parameter shrinks to zero. Also, for the steady-state simulation context, we compare our procedures based on WCVEs with techniques that instead use standardized time series methods. In the second part, we propose a new technique of estimating the variance parameter of a wide variety of stochastic processes. This new technique is better than the existing techniques for some standard stochastic processes in terms of bias and variance properties, since it reduces bias at the cost of no significant increase in variance

Cross-platform validation of notional baseline architecture models of naval electric ship power systems

To support efforts in assessing the relative merit of alternative power system architectures for future naval combatants, the Electric Ship Research and Development Consortium (ESRDC) has developed notional baseline models for each of the primary candidate architectures currently considered, medium-voltage DC (MVDC), conventional 60 Hz medium-voltage (MVAC), and high-frequency medium-voltage (HFAC). Initial efforts have focused on the development of a consistent set of component models, of which the system models can be comprised, and the basic definition of the system models. The broader objectives of the consortium, however, go beyond the definition of the baseline models. The focus is on the process by which the models are implemented in software and validated, the process by which the performance of the disparate system models are objectively and quantitatively assessed and compared, and, ultimately, the process by which the relative merits of the architectures may be assessed. This paper focuses specifically on cross-platform component validation.Center for Electromechanic

A molecular basis for selective antagonist destabilization of dopamine D3 receptor quaternary organization

The dopamine D3 receptor (D3R) is a molecular target for both first-generation and several recently-developed antipsychotic agents. Following stable expression of this mEGFP-tagged receptor, Spatial Intensity Distribution Analysis indicated that a substantial proportion of the receptor was present within dimeric/oligomeric complexes and that increased expression levels of the receptor favored a greater dimer to monomer ratio. Addition of the antipsychotics, spiperone or haloperidol, resulted in re-organization of D3R quaternary structure to promote monomerization. This action was dependent on ligand concentration and reversed upon drug washout. By contrast, a number of other antagonists with high affinity at the D3R, did not alter the dimer/monomer ratio. Molecular dynamics simulations following docking of each of the ligands into a model of the D3R derived from the available atomic level structure, and comparisons to the receptor in the absence of ligand, were undertaken. They showed that, in contrast to the other antagonists, spiperone and haloperidol respectively increased the atomic distance between reference α carbon atoms of transmembrane domains IV and V and I and II, both of which provide key interfaces for D3R dimerization. These results offer a molecular explanation for the distinctive ability of spiperone and haloperidol to disrupt D3R dimerization