Evolutionary Synthesis of HVAC System Configurations: Algorithm Development.

This paper describes the development of an optimization procedure for the synthesis of novel heating, ventilating, and air-conditioning (HVAC) system configurations. Novel HVAC system designs can be synthesized using model-based optimization methods. The optimization problem can be considered as having three sub-optimization problems; the choice of a component set; the design of the topological connections between the components; and the design of a system operating strategy. In an attempt to limit the computational effort required to obtain a design solution, the approach adopted in this research is to solve all three sub-problems simultaneously. Further, the computational effort has been limited by implementing simplified component models and including the system performance evaluation as part of the optimization problem (there being no need in this respect to simulation the system performance). The optimization problem has been solved using a Genetic Algorithm (GA), with data structures and search operators that are specifically developed for the solution of HVAC system optimization problems (in some instances, certain of the novel operators may also be used in other topological optimization problems. The performance of the algorithm, and various search operators has been examined for a two-zone optimization problem (the objective of the optimization being to find a system design that minimizes the system energy use). In particular, the performance of the algorithm in finding feasible system designs has been examined. It was concluded that the search was unreliable when the component set was optimized, but if the component set was fixed as a boundary condition on the search, then the algorithm had an 81% probability of finding a feasible system design. The optimality of the solutions is not examined in this paper, but is described in an associated publication. It was concluded that, given a candidate set of system components, the algorithm described here provides an effective tool for exploring the novel design of HVAC systems. (c) HVAC & R journa

Basins of attraction in forced systems with time-varying dissipation

We consider dissipative periodically forced systems and investigate cases in which having information as to how the system behaves for constant dissipation may be used when dissipation varies in time before settling at a constant final value. First, we consider situations where one is interested in the basins of attraction for damping coefficients varying linearly between two given values over many different time intervals: we outline a method to reduce the computation time required to estimate numerically the relative areas of the basins and discuss its range of applicability. Second, we observe that sometimes very slight changes in the time interval may produce abrupt large variations in the relative areas of the basins of attraction of the surviving attractors: we show how comparing the contracted phase space at a time after the final value of dissipation has been reached with the basins of attraction corresponding to that value of constant dissipation can explain the presence of such variations. Both procedures are illustrated by application to a pendulum with periodically oscillating support.Comment: 16 pages, 13 figures, 7 table

Platelet-mediated metabolism of the common dietary flavonoid, quercetin.

BACKGROUND: Flavonoid metabolites remain in blood for periods of time potentially long enough to allow interactions with cellular components of this tissue. It is well-established that flavonoids are metabolised within the intestine and liver into methylated, sulphated and glucuronidated counterparts, which inhibit platelet function. METHODOLOGY/PRINCIPAL FINDINGS: We demonstrate evidence suggesting platelets which contain metabolic enzymes, as an alternative location for flavonoid metabolism. Quercetin and a plasma metabolite of this compound, 4'-O-methyl quercetin (tamarixetin) were shown to gain access to the cytosolic compartment of platelets, using confocal microscopy. High performance liquid chromatography (HPLC) and mass spectrometry (MS) showed that quercetin was transformed into a compound with a mass identical to tamarixetin, suggesting that the flavonoid was methylated by catechol-O-methyl transferase (COMT) within platelets. CONCLUSIONS/SIGNIFICANCE: Platelets potentially mediate a third phase of flavonoid metabolism, which may impact on the regulation of the function of these cells by metabolites of these dietary compounds

Constrained, mixed-integer and multi-objective optimisation of building designs by NSGA-II with fitness approximation

Reducing building energy demand is a crucial part of the global response to climate change, and evolutionary algorithms (EAs) coupled to building performance simulation (BPS) are an increasingly popular tool for this task. Further uptake of EAs in this industry is hindered by BPS being computationally intensive: optimisation runs taking days or longer are impractical in a time-competitive environment. Surrogate fitness models are a possible solution to this problem, but few approaches have been demonstrated for multi-objective, constrained or discrete problems, typical of the optimisation problems in building design. This paper presents a modified version of a surrogate based on radial basis function networks, combined with a deterministic scheme to deal with approximation error in the constraints by allowing some infeasible solutions in the population. Different combinations of these are integrated with Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and applied to three instances of a typical building optimisation problem. The comparisons show that the surrogate and constraint handling combined offer improved run-time and final solution quality. The paper concludes with detailed investigations of the constraint handling and fitness landscape to explain differences in performance

Applying Global And Local SA In Identification Of Variables Importance With The Use Of Multi-Objective Optimization

Methods for global and local Sensitivity analysis are designed to identify and rank variables importance for each design objective and constraint. This paper investigates the application of local sensitivity analysis to a set of Pareto optimum solutions resulting from the multi-objective minimization of energy use and capital cost, with occupant thermal comfort acting as a constraint. It is concluded that the local sensitivities vary along the trade-off and that these sensitivities are different to the global sensitivities. Different sensitivity behaviour is also observed both along the Pareto trade-off and between variables

A Comparison of Approaches to Stepwise Regression Analysis for Variables Sensitivity Measurements Used with a Multi-Objective Optimization Problem

Global sensitivity analysis can be used to identify and rank variables importance (sensitivities) for design objectives and constraints, where the solution space is sampled and a linear regression model is normally adopted in the stepwise manner. The relative importance of variables can be examined by three indicators: the order of variables entry into the linear regression model; the absolute values of the standardized regression coefficients or their rank transformation coefficients; and the size of the R2 changes (coefficient of determination) attributable to additional variables at each step. However, the robustness of the linear regression model constructed from a stepwise regression is related to the choice of procedure options, e.g. the set of samples and data formulation. Different procedure options could lead to different linear regression models, and therefore influence the indication of variables global sensitivities. Thus, this paper investigates the extent to which the procedure options of a stepwise regression can influence the indication of variables global sensitivities, measured by three different sensitivity indicators, for energy demand, capital costs and solution infeasibility, when using both the randomly generated samples and the biased solutions obtained at the start of a multi-objective optimization process (based on NSGA-II). It concludes that the most important variables are always ranked on the top no matter the choice of procedure options, but it is better to adopt both the entry-orders of variables and their standardized (rank) regression coefficients or the contributions to R2 changes, to provide robust orderings of variables importance, for design objectives and constraints. Moreover, when the sample size is smaller, re-generated separate set of samples for sensitivity analysis can avoid misleading variables importance, especially for the variables ranked in the middle. Finally, to improve computational efficiency, this paper concludes that the first 100 solutions obtained from a multi-objective optimization can be used to perform global sensitivity analysis, to identify the important variables for design objectives

Why the Crackling Deformations of Single Crystals, Metallic Glasses, Rock, Granular Materials, and the Earth’s Crust Are So Surprisingly Similar

Recent experiments show that the deformation properties of a wide range of solid materials are surprisingly similar. When slowly pushed, they deform via intermittent slips, similar to earthquakes. The statistics of these slips agree across vastly different structures and scales. A simple analytical model explains why this is the case. The model also predicts which statistical quantities are independent of the microscopic details (i.e., they are universal ), and which ones are not. The model provides physical intuition for the deformation mechanism and new ways to organize experimental data. It also shows how to transfer results from one scale to another. The model predictions agree with experiments. The results are expected to be relevant for failure prediction, hazard prevention, and the design of next-generation materials

Multi-dwelling Refurbishment Optimization: Problem Decomposition, Solution, and Trade-off Analysis

A methodology has been developed for the multiobjective optimization of the refurbishment of domestic building stock on a regional scale. The approach is based on the decomposition of the problem into two stages: first to find the energy-cost trade-off for individual houses, and then to apply it tomultiple houses. The approach has been applied to 759 dwellings using buildings data from a survey of the UK housing stock. The energy use of each building and their refurbished variants were simulated using EnergyPlus using automatically-generated input files. The variation in the contributing refurbishment options from least to highest cost along the Pareto front shows loft and cavity wall insulation to be optimal intially, and solid wall insulation and double glazing appearing later

Beyond the T Dwarfs: Theoretical Spectra, Colors, and Detectability of the Coolest Brown Dwarfs

We explore the spectral and atmospheric properties of brown dwarfs cooler than the latest known T dwarfs. Our focus is on the yet-to-be-discovered free-floating brown dwarfs in the \teff range from $\sim$800 K to $\sim$130 K and with masses from 25 to 1 \mj. This study is in anticipation of the new characterization capabilities enabled by the launch of SIRTF and the eventual launch of JWST. We provide spectra from $\sim$0.4 \mic to 30 \mic, highlight the evolution and mass dependence of the dominant H$_2$O, CH$_4$, and NH$_3$ molecular bands, consider the formation and effects of water-ice clouds, and compare our theoretical flux densities with the sensitivities of the instruments on board SIRTF and JWST. The latter can be used to determine the detection ranges from space of cool brown dwarfs. In the process, we determine the reversal point of the blueward trend in the near-infrared colors with decreasing \teff, the \teffs at which water and ammonia clouds appear, the strengths of gas-phase ammonia and methane bands, the masses and ages of the objects for which the neutral alkali metal lines are muted, and the increasing role as \teff decreases of the mid-infrared fluxes longward of 4 \mic. These changes suggest physical reasons to expect the emergence of at least one new stellar class beyond the T dwarfs. Our spectral models populate, with cooler brown dwarfs having progressively more planet-like features, the theoretical gap between the known T dwarfs and the known giant planets. Such objects likely inhabit the galaxy, but their numbers are as yet unknown.Comment: Includes 14 figures, most in color; accepted to the Astrophysical Journa

Predictions of children’s emotionality from evolutionary and epigenetic hypotheses

Sex-dependent effects of mismatched prenatal-postnatal maternal conditions are predicted by combining two evolutionary hypotheses: that foetal conditions provide a forecast of likely postnatal environments (Predictive Adaptive Response), and that the female foetus is better adapted than the male to maternal adversity (Trivers-Willard hypothesis). Animal studies have implicated glucocorticoid mechanisms modifiable by effects of postnatal tactile stimulation on glucocorticoid receptor gene expression. In this study we examined behavioural predictions in humans based on these evolutionary and epigenetic models. Mothers in a general population cohort provided self-reported anxiety scores at 20 weeks pregnancy, and at 9 weeks, 14 months and 3.5 years postpartum, and frequency of infant stroking at 9 weeks. Mothers and teachers reported child symptoms at 7 years. SEM models with maximum-likelihood estimates made use of data from 887 participants. There was a three-way interaction between prenatal and postnatal anxiety and maternal stroking in the prediction of irritability, seen only in girls. This arose because lower maternal stroking was associated with higher irritability, only in the mismatched, low-high and high-low maternal anxiety groups. We provide evidence that mechanisms likely to have evolved well before the emergence of humans, contribute to the development of children’s emotionality and risk for depression