46 resultados para Coating. Load
Resumo:
IPLV overall coefficient, presented by Air-Conditioning and Refrigeration Institute (ARI) of America, shows running/operation status of air-conditioning system host only. For overall operation coefficient, logical solution has not been developed, to reflect the whole air-conditioning system under part load. In this research undertaking, the running time proportions of air-conditioning systems under part load have been obtained through analysis on energy consumption data during practical operation in all public buildings in Chongqing. This was achieved by using analysis methods, based on the statistical energy consumption data distribution of public buildings month-by-month. Comparing with the weight number of IPLV, part load operation coefficient of air-conditioning system, based on this research, does not only show the status of system refrigerating host, but also reflects and calculate energy efficiency of the whole air-conditioning system. The coefficient results from the processing and analyzing of practical running data, shows the practical running status of area and building type (actual and objective) – not clear. The method is different from model analysis which gets IPLV weight number, in the sense that this method of coefficient results in both four equal proportions and also part load operation coefficient of air-conditioning system under any load rate as necessary.
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coating composition comprising an oxidatively drying coating binder and a chelate comprising at least one group according to the following formula (I): forming a complex with a metal ion, A1 and A2 both being an aromatic residue, R1 and R3 being covalently bonded groups, and R2 being a divalent organic radical, wherein at least one solubilizing group is coivalently bonded to the chelating compound. The solubilizing group is a non-polar group, preferable an aliphatic group having at least four carbon atoms, covalently bonded to A1 and/or A2. The metal ion is a divalent ion of a metal selected from the group of manganese, cobalt, copper, lead, zirconium, iron, lanthanium, cerium, vanadium, and clacium or a trivalent ion of a metal selected from the group of manganese, cobalt, lead, zirconium, iron, lanthanium, cerium, and vanadium, combined with a monovalent counterion.
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The effects of dispersion, angle of illumination and temperature in coated layers of infrared semiconductors (the IV-VI) and semiinsulators (the II-VI) are described. Examples are given of microcomputer calculations of these.
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Load forecasting is an important task in the management of a power utility. The most recent developments in forecasting involve the use of artificial intelligence techniques, which offer powerful modelling capabilities. This paper discusses these techniques and provides a review of their application to load forecasting.
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Mitochondrial DNA (mtDNA) mutations are an important cause of genetic disease and have been proposed to play a role in the ageing process. Quantification of total mtDNA mutation load in ageing tissues is difficult as mutational events are rare in a background of wild-type molecules, and detection of individual mutated molecules is beyond the sensitivity of most sequencing based techniques. The methods currently most commonly used to document the incidence of mtDNA point mutations in ageing include post-PCR cloning, single-molecule PCR and the random mutation capture assay. The mtDNA mutation load obtained by these different techniques varies by orders of magnitude, but direct comparison of the three techniques on the same ageing human tissue has not been performed. We assess the procedures and practicalities involved in each of these three assays and discuss the results obtained by investigation of mutation loads in colonic mucosal biopsies from ten human subjects.
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There are varieties of physical and behavioral factors to determine energy demand load profile. The attainment of the optimum mix of measures and renewable energy system deployment requires a simple method suitable for using at the early design stage. A simple method of formulating load profile (SMLP) for UK domestic buildings has been presented in this paper. Domestic space heating load profile for different types of houses have been produced using thermal dynamic model which has been developed using thermal resistant network method. The daily breakdown energy demand load profile of appliance, domestic hot water and space heating can be predicted using this method. The method can produce daily load profile from individual house to urban community. It is suitable to be used at Renewable energy system strategic design stage.
Resumo:
The development of a combined engineering and statistical Artificial Neural Network model of UK domestic appliance load profiles is presented. The model uses diary-style appliance use data and a survey questionnaire collected from 51 suburban households and 46 rural households during the summer of 2010 and2011 respectively. It also incorporates measured energy data and is sensitive to socioeconomic, physical dwelling and temperature variables. A prototype model is constructed in MATLAB using a two layer feed forward network with back propagation training which has a 12:10:24 architecture. Model outputs include appliance load profiles which can be applied to the fields of energy planning (microrenewables and smart grids), building simulation tools and energy policy.
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Recursive Learning Control (RLC) has the potential to significantly reduce the tracking error in many repetitive trajectory applications. This paper presents an application of RLC to a soil testing load frame where non-adaptive techniques struggle with the highly nonlinear nature of soil. The main purpose of the controller is to apply a sinusoidal force reference trajectory on a soil sample with a high degree of accuracy and repeatability. The controller uses a feedforward control structure, recursive least squares adaptation algorithm and RLC to compensate for periodic errors. Tracking error is reduced and stability is maintained across various soil sample responses.
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Constrained principal component analysis (CPCA) with a finite impulse response (FIR) basis set was used to reveal functionally connected networks and their temporal progression over a multistage verbal working memory trial in which memory load was varied. Four components were extracted, and all showed statistically significant sensitivity to the memory load manipulation. Additionally, two of the four components sustained this peak activity, both for approximately 3 s (Components 1 and 4). The functional networks that showed sustained activity were characterized by increased activations in the dorsal anterior cingulate cortex, right dorsolateral prefrontal cortex, and left supramarginal gyrus, and decreased activations in the primary auditory cortex and "default network" regions. The functional networks that did not show sustained activity were instead dominated by increased activation in occipital cortex, dorsal anterior cingulate cortex, sensori-motor cortical regions, and superior parietal cortex. The response shapes suggest that although all four components appear to be invoked at encoding, the two sustained-peak components are likely to be additionally involved in the delay period. Our investigation provides a unique view of the contributions made by a network of brain regions over the course of a multiple-stage working memory trial.
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Accumulation of tephra fallout produced during explosive eruptions can cause roof collapses in areas near the volcano, when the weight of the deposit exceeds some threshold value that depends on the quality of buildings. The additional loading of water that remains trapped in the tephra deposits due to rainfall can contribute to increasing the loading of the deposits on the roofs. Here we propose a simple approach to estimate an upper bound for the contribution of rain to the load of pyroclastic deposits that is useful for hazard assessment purposes. As case study we present an application of the method in the area of Naples, Italy, for a reference eruption from Vesuvius volcano.
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A manageable, relatively inexpensive model was constructed to predict the loss of nitrogen and phosphorus from a complex catchment to its drainage system. The model used an export coefficient approach, calculating the total nitrogen (N) and total phosphorus (P) load delivered annually to a water body as the sum of the individual loads exported from each nutrient source in its catchment. The export coefficient modelling approach permits scaling up from plot-scale experiments to the catchment scale, allowing application of findings from field experimental studies at a suitable scale for catchment management. The catchment of the River Windrush, a tributary of the River Thames, UK, was selected as the initial study site. The Windrush model predicted nitrogen and phosphorus loading within 2% of observed total nitrogen load and 0.5% of observed total phosphorus load in 1989. The export coefficient modelling approach was then validated by application in a second research basin, the catchment of Slapton Ley, south Devon, which has markedly different catchment hydrology and land use. The Slapton model was calibrated within 2% of observed total nitrogen load and 2.5% of observed total phosphorus load in 1986. Both models proved sensitive to the impact of temporal changes in land use and management on water quality in both catchments, and were therefore used to evaluate the potential impact of proposed pollution control strategies on the nutrient loading delivered to the River Windrush and Slapton Ley
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A great deal of work recently has focused on suspended and bedload sediment transport, driven primarily by interest in contaminant transfer. However, uncertainties regarding the role of storm events, macrophyte beds and interactions between the two phases of sediment still exist. This paper compares two study sites within the same catchment whose geology varies significantly. The differences in hydrology, suspended sediment (SS) transport and bed load transport that this causes are examined. In addition, a method to predict the mobilization of different size fractions of sediment during given flows is investigated using critical entrainment thresholds.
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The oral administration of probiotic bacteria has shown potential in clinical trials for the alleviation of specific disorders of the gastrointestinal tract. However, cells must be alive in order to exert these benefits. The low pH of the stomach can greatly reduce the number of viable microorganisms that reach the intestine, thereby reducing the efficacy of the administration. Herein, a model probiotic, Bifidobacterium breve, has been encapsulated into an alginate matrix before coating in multilayers of alternating alginate and chitosan. The intention of this formulation was to improve the survival of B. breve during exposure to low pH and to target the delivery of the cells to the intestine. The material properties were first characterized before in vitro testing. Biacore™ experiments allowed for the polymer interactions to be confirmed; additionally, the stability of these multilayers to buffers simulating the pH of the gastrointestinal tract was demonstrated. Texture analysis was used to monitor changes in the gel strength during preparation, showing a weakening of the matrices during coating as a result of calcium ion sequestration. The build-up of multilayers was confirmed by confocal laser-scanning microscopy, which also showed the increase in the thickness of coat over time. During exposure to in vitro gastric conditions, an increase in viability from <3 log(CFU) per mL, seen in free cells, up to a maximum of 8.84 ± 0.17 log(CFU) per mL was noted in a 3-layer coated matrix. Multilayer-coated alginate matrices also showed a targeting of delivery to the intestine, with a gradual release of their loads over 240 min.
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Novel oxazoline-based comb-polymers possessing linoleyl or oleic side chains have been synthesized and used to produce low viscosity coatings. Inclusion of the polymers in model paint formulations results in coatings that exhibit faster drying times than commercially available alkyd resin formulations. The comb polymers were produced from diol substituted oxazoline monomers that were synthesized through a scalable, solvent free protocol and purified by simple recrystallisation. Co-polymerisation of the oxazolines with adipic acid at 160 °C in the bulk resulted in the targeted polyester comb type polymers. The polymers were soluble in a range of organic solvents and compatible with commercial alkyd resins. Model paint formulations containing up to 40 wt% of the linoleyl-based comb polymers exhibited a dramatic reduction in viscosity (from 35 to 13 Poise at 25 °C) with increasing quantities of polymer added. Dynamic mechanical analysis (DMA) studies revealed that the drying rate of the model paint formulations containing the comb polymers was enhanced when compared with that of commercial alkyd resins.