An integrated dynamic whole life costing analysis for air distribution systems

Air distribution systems are one of the major electrical energy consumers in air-conditioned commercial buildings which maintain comfortable indoor thermal environment and air quality by supplying specified amounts of treated air into different zones. The sizes of air distribution lines affect energy efficiency of the distribution systems. Equal friction and static regain are two well-known approaches for sizing the air distribution lines. Concerns to life cycle cost of the air distribution systems, T and IPS methods have been developed. Hitherto, all these methods are based on static design conditions. Therefore, dynamic performance of the system has not been yet addressed; whereas, the air distribution systems are mostly performed in dynamic rather than static conditions. Besides, none of the existing methods consider any aspects of thermal comfort and environmental impacts. This study attempts to investigate the existing methods for sizing of the air distribution systems and proposes a dynamic approach for size optimisation of the air distribution lines by taking into account optimisation criteria such as economic aspects, environmental impacts and technical performance. These criteria have been respectively addressed through whole life costing analysis, life cycle assessment and deviation from set-point temperature of different zones. Integration of these criteria into the TRNSYS software produces a novel dynamic optimisation approach for duct sizing. Due to the integration of different criteria into a well- known performance evaluation software, this approach could be easily adopted by designers in busy nature of design. Comparison of this integrated approach with the existing methods reveals that under the defined criteria, system performance is improved up to 15% compared to the existing methods. This approach is interpreted as a significant step forward reaching to the net zero emission building in future.

Closed loop design for a simple nonlinear aircraft model using eigenstructure assignment

Aircraft systems are highly nonlinear and time varying. High-performance aircraft at high angles of incidence experience undesired coupling of the lateral and longitudinal variables, resulting in departure from normal controlled flight. The aim of this work is to construct a robust closed-loop control that optimally extends the stable and decoupled flight envelope. For the study of these systems nonlinear analysis methods are needed. Previously, bifurcation techniques have been used mainly to analyze open-loop nonlinear aircraft models and investigate control effects on dynamic behavior. In this work linear feedback control designs calculated by eigenstructure assignment methods are investigated for a simple aircraft model at a fixed flight condition. Bifurcation analysis in conjunction with linear control design methods is shown to aid control law design for the nonlinear system.

First order k-th moment finite element analysis of nonlinear operator equations with stochastic data

We develop and analyze a class of efficient Galerkin approximation methods for uncertainty quantification of nonlinear operator equations. The algorithms are based on sparse Galerkin discretizations of tensorized linearizations at nominal parameters. Specifically, we consider abstract, nonlinear, parametric operator equations J(\alpha ,u)=0 for random input \alpha (\omega ) with almost sure realizations in a neighborhood of a nominal input parameter \alpha _0. Under some structural assumptions on the parameter dependence, we prove existence and uniqueness of a random solution, u(\omega ) = S(\alpha (\omega )). We derive a multilinear, tensorized operator equation for the deterministic computation of k-th order statistical moments of the random solution's fluctuations u(\omega ) - S(\alpha _0). We introduce and analyse sparse tensor Galerkin discretization schemes for the efficient, deterministic computation of the k-th statistical moment equation. We prove a shift theorem for the k-point correlation equation in anisotropic smoothness scales and deduce that sparse tensor Galerkin discretizations of this equation converge in accuracy vs. complexity which equals, up to logarithmic terms, that of the Galerkin discretization of a single instance of the mean field problem. We illustrate the abstract theory for nonstationary diffusion problems in random domains.

Dynamic picture of the inner asteroid belt: implications for the density, size and taxonomic distributions of real objects

In this paper, we construct a dynamic portrait of the inner asteroidal belt. We use information about the distribution of test particles, which were initially placed on a perfectly rectangular grid of initial conditions, after 4.2 Myr of gravitational interactions with the Sun and five planets, from Mars to Neptune. Using the spectral analysis method introduced by Michtchenko et al., the asteroidal behaviour is illustrated in detail on the dynamical, averaged and frequency maps. On the averaged and frequency maps, we superpose information on the proper elements and proper frequencies of real objects, extracted from the data base, AstDyS, constructed by Milani and Knezevic. A comparison of the maps with the distribution of real objects allows us to detect possible dynamical mechanisms acting in the domain under study; these mechanisms are related to mean-motion and secular resonances. We note that the two- and three-body mean-motion resonances and the secular resonances (strong linear and weaker non-linear) have an important role in the diffusive transportation of the objects. Their long-lasting action, overlaid with the Yarkovsky effect, may explain many observed features of the density, size and taxonomic distributions of the asteroids.

Coding behavioural data for cladistic analysis: using dynamic homology without parsimony

Many of the controversies around the concept of homology rest on the subjectivity inherent to primary homology propositions. Dynamic homology partially solves this problem, but there has been up to now scant application of it outside of the molecular domain. This is probably because morphological and behavioural characters are rich in properties, connections and qualities, so that there is less space for conflicting character delimitations. Here we present a new method for the direct optimization of behavioural data, a method that relies on the richness of this database to delimit the characters, and on dynamic procedures to establish character state identity. We use between-species congruence in the data matrix and topological stability to choose the best cladogram. We test the methodology using sequences of predatory behaviour in a group of spiders that evolved the highly modified predatory technique of spitting glue onto prey. The cladogram recovered is fully compatible with previous analyses in the literature, and thus the method seems consistent. Besides the advantage of enhanced objectivity in character proposition, the new procedure allows the use of complex, context-dependent behavioural characters in an evolutionary framework, an important step towards the practical integration of the evolutionary and ecological perspectives on diversity. (C) The Willi Hennig Society 2010.

Bayesian Analysis for Nonlinear Regression Model Under Skewed Errors, with Application in Growth Curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew-t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.

Dynamic Changes in the Mental Rotation Network Revealed by Pattern Recognition Analysis of fMRI Data

We investigated the temporal dynamics and changes in connectivity in the mental rotation network through the application of spatio-temporal support vector machines (SVMs). The spatio-temporal SVM [Mourao-Miranda, J., Friston, K. J., et al. (2007). Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage, 36, 88-99] is a pattern recognition approach that is suitable for investigating dynamic changes in the brain network during a complex mental task. It does not require a model describing each component of the task and the precise shape of the BOLD impulse response. By defining a time window including a cognitive event, one can use spatio-temporal fMRI observations from two cognitive states to train the SVM. During the training, the SVM finds the discriminating pattern between the two states and produces a discriminating weight vector encompassing both voxels and time (i.e., spatio-temporal maps). We showed that by applying spatio-temporal SVM to an event-related mental rotation experiment, it is possible to discriminate between different degrees of angular disparity (0 degrees vs. 20 degrees, 0 degrees vs. 60 degrees, and 0 degrees vs. 100 degrees), and the discrimination accuracy is correlated with the difference in angular disparity between the conditions. For the comparison with highest accuracy (08 vs. 1008), we evaluated how the most discriminating areas (visual regions, parietal regions, supplementary, and premotor areas) change their behavior over time. The frontal premotor regions became highly discriminating earlier than the superior parietal cortex. There seems to be a parcellation of the parietal regions with an earlier discrimination of the inferior parietal lobe in the mental rotation in relation to the superior parietal. The SVM also identified a network of regions that had a decrease in BOLD responses during the 100 degrees condition in relation to the 0 degrees condition (posterior cingulate, frontal, and superior temporal gyrus). This network was also highly discriminating between the two conditions. In addition, we investigated changes in functional connectivity between the most discriminating areas identified by the spatio-temporal SVM. We observed an increase in functional connectivity between almost all areas activated during the 100 degrees condition (bilateral inferior and superior parietal lobe, bilateral premotor area, and SMA) but not between the areas that showed a decrease in BOLD response during the 100 degrees condition.

Evaluation of Postpolymerization as a Function of the Storage Time of Triethylene Glycol Dimethacrylate/2,2-Bis[4-(2-Hydroxy-3-Methacryloxy-Prop-1-Oxy)-Phenyl]-propane Bisphenyl-alpha-Glycidyl Ether Dimethacrylate Copolymers Used in Dental Resins by Differential Scanning Calorimetry and Dynamic Mechanical Analysis

The aim of this work was to evaluate the effect of the storage time on the thermal properties of triethylene glycol dimethacrylate/2,2-bis[4-(2-hydroxy-3-methacryloxy-prop-1-oxy)-phenyl]propane bisphenyl-alpha-glycidyl ether dimethacrylate (TB) copolymers used in formulations of dental resins after photopolymerization. The TB copolymers were prepared by photopolymerization with an Ultrablue IS light-emitting diode, stored in the dark for 160 days at 37 degrees C, and characterized with differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), and Fourier transform infrared spectroscopy with attenuated total reflection. DSC curves indicated the presence of an exothermic peak, confirming that the reaction was not completed during the photopolymerization process. This exothermic peak became smaller as a function of the storage time and was shifted at higher temperatures. In DMA studies, a plot of the loss tangent versus the temperature initially showed the presence of two well-defined peaks. The presence of both peaks confirmed the presence of residual monomers that were not converted during the photopolymerization process. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 112: 679-684, 2009

Speculative bubbles and contagion: analysis of volatility’s clusters during the DotCom bubble based on the dynamic conditional correlation model

Revendo a definição e determinação de bolhas especulativas no contexto de contágio, este estudo analisa a bolha do DotCom nos mercados acionistas americanos e europeus usando o modelo de correlação condicional dinâmica (DCC) proposto por Engle e Sheppard (2001) como uma explicação econométrica e, por outro lado, as finanças comportamentais como uma explicação psicológica. Contágio é definido, neste contexto, como a quebra estatística nos DCC’s estimados, medidos através das alterações das suas médias e medianas. Surpreendentemente, o contágio é menor durante bolhas de preços, sendo que o resultado principal indica a presença de contágio entre os diferentes índices dos dois continentes e demonstra a presença de alterações estruturais durante a crise financeira.

Convergence analysis of sampling-based decomposition methods for risk-averse multistage stochastic convex programs

We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse functions. This formula can be used to obtain an efficient implementation of Stochastic Dual Dynamic Programming applied to convex nonlinear problems. We prove the almost sure convergence of these decomposition methods when the relatively complete recourse assumption holds. We also prove the almost sure convergence of these algorithms when applied to risk-averse multistage stochastic linear programs that do not satisfy the relatively complete recourse assumption. The analysis is first done assuming the underlying stochastic process is interstage independent and discrete, with a finite set of possible realizations at each stage. We then indicate two ways of extending the methods and convergence analysis to the case when the process is interstage dependent.

Speculative bubbles and contagion: analysis of volatility's clusters during the DotCom bubble based on the dynamic conditional correlation model

Reviewing the de nition and measurement of speculative bubbles in context of contagion, this paper analyses the DotCom bubble in American and European equity markets using the dynamic conditional correlation (DCC) model proposed by (Engle and Sheppard 2001) as on one hand as an econometrics explanation and on the other hand the behavioral nance as an psychological explanation. Contagion is de ned in this context as the statistical break in the computed DCCs as measured by the shifts in their means and medians. Even it is astonishing, that the contagion is lower during price bubbles, the main nding indicates the presence of contagion in the di¤erent indices among those two continents and proves the presence of structural changes during nancial crisis

About the Use of the HdHr Algorithm Group in Integrating the Movement Equation with Nonlinear Terms

This work summarizes the HdHr group of Hermitian integration algorithms for dynamic structural analysis applications. It proposes a procedure for their use when nonlinear terms are present in the equilibrium equation. The simple pendulum problem is solved as a first example and the numerical results are discussed. Directions to be pursued in future research are also mentioned. Copyright (C) 2009 H.M. Bottura and A. C. Rigitano.