6 resultados para temperature-based models


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In establishing the reliability of performance-related design methods for concrete – which are relevant for resistance against chloride-induced corrosion - long-term experience of local materials and practices and detailed knowledge of the ambient and local micro-climate are critical. Furthermore, in the development of analytical models for performance-based design, calibration against test data representative of actual conditions in practice is required. To this end, the current study presents results from full-scale, concrete pier-stems under long-term exposure to a marine environment with work focussing on XS2 (below mid-tide level) in which the concrete is regarded as fully saturated and XS3 (tidal, splash and spray) in which the concrete is in an unsaturated condition. These exposures represent zones where concrete structures are most susceptible to ionic ingress and deterioration. Chloride profiles and chloride transport behaviour are studied using both an empirical model (erfc function) and a physical model (ClinConc). The time dependency of surface chloride concentration (Cs) and apparent diffusivity (Da) were established for the empirical model whereas, in the ClinConc model (originally based on saturated concrete), two new environmental factors were introduced for the XS3 environmental exposure zone. Although the XS3 is considered as one environmental exposure zone according to BS EN 206-1:2013, the work has highlighted that even within this zone, significant changes in chloride ingress are evident. This study aims to update the parameters of both models for predicting the long term transport behaviour of concrete subjected to environmental exposure classes XS2 and XS3.

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The stability of consumer-resource systems can depend on the form of feeding interactions (i.e. functional responses). Size-based models predict interactions - and thus stability - based on consumer-resource size ratios. However, little is known about how interaction contexts (e.g. simple or complex habitats) might alter scaling relationships. Addressing this, we experimentally measured interactions between a large size range of aquatic predators (4-6400 mg over 1347 feeding trials) and an invasive prey that transitions among habitats: from the water column (3D interactions) to simple and complex benthic substrates (2D interactions). Simple and complex substrates mediated successive reductions in capture rates - particularly around the unimodal optimum - and promoted prey population stability in model simulations. Many real consumer-resource systems transition between 2D and 3D interactions, and along complexity gradients. Thus, Context-Dependent Scaling (CDS) of feeding interactions could represent an unrecognised aspect of food webs, and quantifying the extent of CDS might enhance predictive ecology.

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Background: Implementing effective antenatal care models is a key global policy goal. However, the mechanisms of action of these multi-faceted models that would allow widespread implementation are seldom examined and poorly understood. In existing care model analyses there is little distinction between what is done, how it is done, and who does it. A new evidence-informed quality maternal and newborn care (QMNC) framework identifies key characteristics of quality care. This offers the opportunity to identify systematically the characteristics of care delivery that may be generalizable across contexts, thereby enhancing implementation. Our objective was to map the characteristics of antenatal care models tested in Randomised Controlled Trials (RCTs) to a new evidence-based framework for quality maternal and newborn care; thus facilitating the identification of characteristics of effective care.

Methods: A systematic review of RCTs of midwifery-led antenatal care models. Mapping and evaluation of these models’ characteristics to the QMNC framework using data extraction and scoring forms derived from the five framework components. Paired team members independently extracted data and conducted quality assessment using the QMNC framework and standard RCT criteria.

Results: From 13,050 citations initially retrieved we identified 17 RCTs of midwifery-led antenatal care models from Australia (7), the UK (4), China (2), and Sweden, Ireland, Mexico and Canada (1 each). QMNC framework scores ranged from 9 to 25 (possible range 0–32), with most models reporting fewer than half the characteristics associated with quality maternity care. Description of care model characteristics was lacking in many studies, but was better reported for the intervention arms. Organisation of care was the best-described component. Underlying values and philosophy of care were poorly reported.

Conclusions: The QMNC framework facilitates assessment of the characteristics of antenatal care models. It is vital to understand all the characteristics of multi-faceted interventions such as care models; not only what is done but why it is done, by whom, and how this differed from the standard care package. By applying the QMNC framework we have established a foundation for future reports of intervention studies so that the characteristics of individual models can be evaluated, and the impact of any differences appraised.

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Ground-source heat pump (GSHP) systems represent one of the most promising techniques for heating and cooling in buildings. These systems use the ground as a heat source/sink, allowing a better efficiency thanks to the low variations of the ground temperature along the seasons. The ground-source heat exchanger (GSHE) then becomes a key component for optimizing the overall performance of the system. Moreover, the short-term response related to the dynamic behaviour of the GSHE is a crucial aspect, especially from a regulation criteria perspective in on/off controlled GSHP systems. In this context, a novel numerical GSHE model has been developed at the Instituto de Ingeniería Energética, Universitat Politècnica de València. Based on the decoupling of the short-term and the long-term response of the GSHE, the novel model allows the use of faster and more precise models on both sides. In particular, the short-term model considered is the B2G model, developed and validated in previous research works conducted at the Instituto de Ingeniería Energética. For the long-term, the g-function model was selected, since it is a previously validated and widely used model, and presents some interesting features that are useful for its combination with the B2G model. The aim of the present paper is to describe the procedure of combining these two models in order to obtain a unique complete GSHE model for both short- and long-term simulation. The resulting model is then validated against experimental data from a real GSHP installation.

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In this paper strontium-site-deficient Sr2Fe1.4Co0.1Mo0.5O6-δ-based perovskite oxides (SxFCM) were prepared and evaluated as the cathode materials for intermediate temperature solid oxide fuel cells (IT-SOFCs). All samples exhibited a cubic phase structure and the lattice shrinked with increasing the Sr-deficiency as shown in XRD patterns. XPS results determined that the transition elements (Co/Fe/Mo) in SxFCM oxides were in a mixed valence state, demonstrating the small polaron hopping conductivity mechanism existed. Among the samples, S1.950FCM presented the lowest coefficient of thermal expansion of 15.62 × 10-6 K-1, the highest conductivity value of 28 S cm-1 at 500 °C, and the lowest interfacial polarization resistance of 0.093 Ω cm2 at 800 °C, respectively. Furthermore, an anode-supported single cell with a S1.950FCM cathode was prepared, demonstrating a maximum power density of 1.16 W cm-2 at 800 °C by using wet H2 (3% H2O) as the fuel and ambient air as the oxidant. These results indicate that the introduction of Sr-deficiency can dramatically improve the electrochemical performance of Sr2Fe1.4Co0.1Mo0.5O6-δ, showing great promise as a novel cathode candidate material for IT-SOFCs.

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The structure of a turbulent non-premixed flame of a biogas fuel in a hot and diluted coflow mimicking moderate and intense low dilution (MILD) combustion is studied numerically. Biogas fuel is obtained by dilution of Dutch natural gas (DNG) with CO2. The results of biogas combustion are compared with those of DNG combustion in the Delft Jet-in-Hot-Coflow (DJHC) burner. New experimental measurements of lift-off height and of velocity and temperature statistics have been made to provide a database for evaluating the capability of numerical methods in predicting the flame structure. Compared to the lift-off height of the DNG flame, addition of 30 % carbon dioxide to the fuel increases the lift-off height by less than 15 %. Numerical simulations are conducted by solving the RANS equations using Reynolds stress model (RSM) as turbulence model in combination with EDC (Eddy Dissipation Concept) and transported probability density function (PDF) as turbulence-chemistry interaction models. The DRM19 reduced mechanism is used as chemical kinetics with the EDC model. A tabulated chemistry model based on the Flamelet Generated Manifold (FGM) is adopted in the PDF method. The table describes a non-adiabatic three stream mixing problem between fuel, coflow and ambient air based on igniting counterflow diffusion flamelets. The results show that the EDC/DRM19 and PDF/FGM models predict the experimentally observed decreasing trend of lift-off height with increase of the coflow temperature. Although more detailed chemistry is used with EDC, the temperature fluctuations at the coflow inlet (approximately 100K) cannot be included resulting in a significant overprediction of the flame temperature. Only the PDF modeling results with temperature fluctuations predict the correct mean temperature profiles of the biogas case and compare well with the experimental temperature distributions.