60 resultados para Hole building dynamic simulation

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Traditionally the simulation of the thermodynamic aspects of the internal combustion engine has been undertaken using one-dimensional gas-dynamic models to represent the intake and exhaust systems. CFD analysis of engines has been restricted to modelling of in-cylinder flow structures. With the increasing accessibility of CFD software it is now worth considering its use for complete gas-dynamic engine simulation. This paper appraises the accuracy of various CFD models in comparison to a 1D gas-dynamic simulation. All of the models are compared to experimental data acquired on an apparatus that generates a single gas-dynamic pressure wave. The progress of the wave along a constant area pipe and its subsequent reflection from the open pipe end are recorded with a number of high speed pressure transducers. It was found that there was little to choose between the accuracy of the 1D model and the best CFD model. The CFD model did not require experimentally derived loss coefficients to accurately represent the open pipe end; however, it took several hundred times longer to complete its analysis. The best congruency between the CFD models and the experimental data was achieved using the RNG k-e turbulence model. The open end of the pipe was most effectively represented by surrounding it with a relatively small volume of cells connected to the rest of the environment using a pressure boundary.

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This paper presents a new methodology for characterising the energy performance of buildings suitable for city-scale, top-down energy modelling. Building properties that have the greatest impact on simulated energy performance were identified via a review of sensitivity analysis studies. The methodology greatly simplifies the description of a building to decrease labour and simulation processing overheads. The methodology will be used in the EU FP7 INDICATE project which aims to create a master-planning tool that uses dynamic simulation to facilitate the design of sustainable, energy efficient smart cities.

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As one of the most successfully commercialized distributed energy resources, the long-term effects of microturbines (MTs) on the distribution network has not been fully investigated due to the complex thermo-fluid-mechanical energy conversion processes. This is further complicated by the fact that the parameter and internal data of MTs are not always available to the electric utility, due to different ownerships and confidentiality concerns. To address this issue, a general modeling approach for MTs is proposed in this paper, which allows for the long-term simulation of the distribution network with multiple MTs. First, the feasibility of deriving a simplified MT model for long-term dynamic analysis of the distribution network is discussed, based on the physical understanding of dynamic processes that occurred within MTs. Then a three-stage identification method is developed in order to obtain a piecewise MT model and predict electro-mechanical system behaviors with saturation. Next, assisted with the electric power flow calculation tool, a fast simulation methodology is proposed to evaluate the long-term impact of multiple MTs on the distribution network. Finally, the model is verified by using Capstone C30 microturbine experiments, and further applied to the dynamic simulation of a modified IEEE 37-node test feeder with promising results.

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Cholecystokinin receptor-2 (CCK2R) is a G protein receptor that regulates a number of physiological functions. Activation of CCK2R and/or expression of a constitutively active CCK2R variant may contribute to human diseases, including digestive cancers. Search for antagonists of the CCK2R has been an important challenge during the last few years, leading to discovery of a set of chemically distinct compounds. However, several early-discovered antagonists turned out to be partial agonists. In this context, we carried out pharmacological characterization of six CCK2R antagonists using COS-7 cells expressing the human CCK2R or a CCK2R mutant having a robust constitutive activity on inositol phosphates production, and we investigated the molecular mechanisms which, at a CCK2R binding site, account for these features. Results indicated that three compounds, 3R(+)-N-(2,3-dihydro-1-methyl-2-oxo-5-phenyl-1H-1,4-benzodiazepin-3- yl)-N'-(3-methylphenyl)urea (L365,260), 4-{[2-[[3-(lH-indol-3-yl)-2- methyl-1-oxo-2-[[[1.7.7-trimethyl-bicyclo[2.2.1]hept-2-yl)-oxy]carbonyl]amino] propyl]amino]-1-phenylethyl]amino-4-oxo-[lS-la.2[S*(S*)]4a]} -butanoate N-methyl-D-glucamine (PD135, 158), and (R)-1-naphthalenepropanoic acid, b-[2-[[2-(8-azaspiro-[4.5]dec-8-ylcarbonyl)-4,6-dimethylphenyl]amino]-2- oxoethyl] (CR2945), were partial agonists; one molecule, 1-[(R)-2,3-dihydro-1- (2,3-dihydro-1-(2-methylphenacyl)-2-oxo-5-phenyl-1H-1,4-benzodiazepin-3-yl] -3-(3-methylphenyl)urea (YM022), was a neutral antagonist; and two compounds, N-(+)-[1-(adamant-1-ylmethyl)-2,4-dioxo-5-phenyl2,3,4,5-tetrahydro-1H-1, 5-benzodiazepin-3-yl]-N'-phenylurea (GV150,013X) and ([(N-[methoxy-3 phenyl] N-[N-methyl N-phenyl carbamoylmethyl], carbomoylmethyl)-3 ureido]-3-phenyl)2-propionic acid (RPR101,048), were inverse agonists. Furthermore, target- and pharmacophore-based docking of ligands followed by molecular dynamic simulation experiments resulted in consistent motion of aromatic residues belonging to a network presumably important for activation, thus providing the first structural explanations for the different pharmacological profiles of tested compounds. This study confirms that several referenced so-called antagonists are in fact partial agonists, and because of this undesired activity, we suggest that newly generated molecules should be preferred to efficiently block CCK2R-related physiological effects. Furthermore, data on the structural basis for the different pharmacological features of CCK2R ligands will serve to further clarify CCK2R mechanism of activation. Copyright © 2006 The American Society for Pharmacology and Experimental Therapeutics.

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This short review establishes the conceptual bases and discusses the principal aspects of P4-shorthand for predictive, preventive, personalized and participatory medicine-medicine, in the framework of infectious diseases. P4 medicine is a new way to approach medical care; instead of acting when the patient is sick, physicians will be able to detect early warnings of disease to take early action. Furthermore, people might even be able to adjust their lifestyles to prevent disease. P4 medicine is fuelled by systems approaches to disease, including methods for personalized genome sequencing and new computational techniques for building dynamic disease predictive networks from massive amounts of data from a variety of OMICs. An excellent example of the effectiveness of the P4 medicine approach is the change in cancer treatments. Emphasis is placed on early detection, followed by genotyping of the patient to use the most adequate treatment according to the genetic background. Cardiovascular diseases and perhaps even neurodegenerative disorders will be the next targets for P4 medicine. The application of P4 medicine to infectious diseases is still in its infancy, but is a promising field that will provide much benefit to both the patients and the health-care system.

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This paper investigates the environmental conditions inside a highly-glazed cross-ventilated meeting room. A 3D computational fluid dynamics (CFD) model of an indoor environment is developed with the support of the field measurements performed in a normally operating room. The work presented here follows the steps of the formal calibration methodology for the development of CFD models of naturally ventilated environments. This paper utilises the calibration methodology in order to predict environmental conditions within the highly-glazed cross-ventilated room occupied by people. The CFD model is verified and validated with field measurements performed in an operating building. Moreover, parametric analysis determines the most influential boundary conditions on indoor air temperatures and air speeds

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Face-to-face interviews are a fundamental research tool in qualitative research. Whilst this form of data collection can provide many valuable insights, it can often fall short of providing a complete picture of a research subject's experiences. Point of view (PoV) interviewing is an elicitation technique used in the social sciences as a means of enriching data obtained from research interviews. Recording research subjects' first person perspectives, for example by wearing digital video glasses, can afford deeper insights into their experiences. PoV interviewing can promote making visible the unverbalizable and does not rely as much on memory as the traditional interview. The use of such relatively inexpensive technology is gaining interest in health profession educational research and pedagogy, such as dynamic simulation-based learning and research activities. In this interview, Dr Gerry Gormley (a medical education researcher) talks to Dr Jonathan Skinner (an anthropologist with an interest in PoV interviewing), exploring some of the many crossover implications with PoV interviewing for medical education research and practice.

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The creation of Causal Loop Diagrams (CLDs) is a major phase in the System Dynamics (SD) life-cycle, since the created CLDs express dependencies and feedback in the system under study, as well as, guide modellers in building meaningful simulation models. The cre-ation of CLDs is still subject to the modeller's domain expertise (mental model) and her ability to abstract the system, because of the strong de-pendency on semantic knowledge. Since the beginning of SD, available system data sources (written and numerical models) have always been sparsely available, very limited and imperfect and thus of little benefit to the whole modelling process. However, in recent years, we have seen an explosion in generated data, especially in all business related domains that are analysed via Business Dynamics (BD). In this paper, we intro-duce a systematic tool supported CLD creation approach, which analyses and utilises available disparate data sources within the business domain. We demonstrate the application of our methodology on a given business use-case and evaluate the resulting CLD. Finally, we propose directions for future research to further push the automation in the CLD creation and increase confidence in the generated CLDs.

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Presented is a study that expands the body of knowledge on the effect of in-cycle speed fluctuations on performance of small engines. It uses the engine and drivetrain models developed previously by Callahan, et al. (1) to examine a variety of engines. The predicted performance changes due to drivetrain effects are shown in each case, and conclusions are drawn from those results. The single-cylinder, high performance four-stroke engine showed significant changes in predicted performance compared to the prediction with zero speed fluctuation in the model. Measured speed fluctuations from a firing Yamaha YZ426 engine were applied to the simulation in addition to data from a simple free mass model. Both methods predicted similar changes in performance. The multiple-cylinder, high performance two-stroke engine also showed significant changes in performance depending on the firing configuration. With both engines, the change in performance diminished with increasing mean engine speed. The low output, single-cylinder two-stroke engine simulation showed only a negligible change in performance, even with high amplitude speed fluctuations. Because the torque versus engine speed characteristic for the engine was so flat, this was expected. The cross-charged, multi-cylinder two-stroke engine also showed only a negligible change in performance. In this case, the combination of a relatively high inertia rotating assembly and the multiple cylinder firing events within the revolution smoothing the torque pulsations reduced the speed fluctuation amplitude itself.

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The coupled heat, air and moisture transfer between building envelopes and indoor air is complicated, and has a significant influence on the indoor environment and the energy performance of buildings. In the paper, a model for predicting coupled multi-zone hygrothermal-airflow transfer is presented. Both heat and moisture transfer in the building envelope and multi-zone indoor airflow are simultaneously considered; their interactions are modeled. The coupled system model is implemented into Matlab–Simulink, and is validated by using a series of testing tools and experiments. The new program is applied to investigate the moisture transfer effect on indoor air humidity and building energy consumption in different climates (hot-humid, temperate and hot-dry climates). The results show that not accounting for hygrothermal effects in modeling will result in overestimation of energy costs for hot and humid climate situations and possible over sizing of plant leading to inefficient operation.