46 resultados para thermal spike model


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In this work, we address the thermal properties of selected members of a
homologous series of alkyltriethylammonium bisf(trifluoromethyl)sulfonylgimide ionic
liquids. Their phase and glass transition behavior, as well as their standard isobaric heat
capacities at 298.15 K, were studied using differential scanning calorimetry (DSC),
whereas their decomposition temperature was determined by thermal gravimetry analysis.
DSC was further used to measure standard molar heat capacities of the studied ionic liquids
and standard molar heat capacity as a function of temperature for hexyltriethylammonium,
octyltriethylammonium, and dodecyltriethylammonium bisf(trifluoromethyl)sulfonylgimide
ionic liquids. Based on the data obtained, we discuss the influence of the alkyl chain
length of the cation on the studied ionic liquids on the measured properties. Using viscosity
data obtained in a previous work, the liquid fragility of the ionic liquids is then discussed.
Viscosity data were correlated by the VTF equation using a robust regression along a
gnostic influence function. In this way, more reliable VTF model parameters were obtained than in our previous work and a good estimate of the liquid fragility of the ionic liquids was made.

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Solar heating systems have the potential to be an efficient renewable energy technology, provided they are sized correctly. Sizing a solar thermal system for domestic applications does not warrant the cost of a simulation. As a result simplified sizing procedures are required. The size of a system depends on a number of variables including the efficiency of the collector itself, the hot water demand and the solar radiation at a given location. Domestic Hot Water (DHW) demand varies with time and is assessed using a multi-parameter detailed model. Secondly, the national energy evaluation methodologies are evaluated from the perspective of solar thermal system sizing. Based on the assessment of the standards, limitations in the evaluation method for solar thermal systems are outlined and an adapted method, specific to the sizing of solar thermal systems, is proposed. The methodology is presented for two common dwelling scenarios. Results from this showed that it is difficult to achieve a high solar fraction given practical sizes of system infrastructure (storage tanks) for standard domestic properties. However, solar thermal systems can significantly offset energy loads due associated DHW consumption, particularly when sized appropriately. The presented methodology is valuable for simple solar system design and also for the quick comparison of salient criteria.

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Background: The oro-facial region is densely innervated by the trigeminal nerve, which when stimulated can induce noxious pain sensation and contribute to neurogenic inflammation in local tissues. Recent research on the expression of specialised ion channels on the trigeminal nerve has highlighted the need to undertake more extensive studies on ion channel expression/functionality with the aim of elucidating their role in pain sensations. A major family of such ion channels is the transient receptor potential (TRP) channels which are activated by a wide variety of thermal, mechanical or chemical stimuli and merit investigation as possible druggable targets for future analgesics.
Objective: Study of TRP channel expression and regulation in oro-facial tissues is hindered by the fact that the cell bodies of neurons innervating these tissues are located in the trigeminal ganglion. Using dental pulp stem cells differentiated towards peripheral neuronal equivalents (PNEs), we sought to determine TRP channel expression, functionality and potential modulation by cytokines in this novel model.
Method: Dental pulp stem cells (DPSCs) were grown on substrate-coated tissue culture plates and differentiated towards a neuronal phenotype using neuronal induction media. Quantitative polymerase chain reaction (qPCR) was performed on PNEs +/-cytokine treatment. Ion channel functionality was investigated using whole cell patch clamping.
Result: qPCR analysis showed that PNEs expressed the TRP channels TRPA1, TRPV1, TRPV4 and TRPM8. TRPA1 was the most abundantly expressed TRP channel studied whereas TRPM8 was lowly expressed. TRP channel expression was shown to be regulated by treatment with inflammatory cytokines. Patch clamp studies using specific agonists and antagonists for TRPA1 and TRPV1 showed these channels were functional.
Conclusion: PNEs differentiated from DPSCs provide a suitable model for TRP channel expression, regulation, and sensistisation in oro-facial tissues. This human neuronal model has potential for use in pre-clinical studies of novel analgesics.

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Li-ion batteries have been widely used in the EVs, and the battery thermal management is a key but challenging part of the battery management system. For EV batteries, only the battery surface temperature can be measured in real-time. However, it is the battery internal temperature that directly affects the battery performance, and large temperature difference may exist between surface and internal temperatures, especially in high power demand applications. In this paper, an online battery internal temperature estimation method is proposed based on a novel simplified thermoelectric model. The battery thermal behaviour is first described by a simplified thermal model, and battery electrical behaviour by an electric model. Then, these two models are interrelated to capture the interactions between battery thermal and electrical behaviours, thus offer a comprehensive description of the battery behaviour that is useful for battery management. Finally, based on the developed model, the battery internal temperature is estimated using an extended Kalman filter. The experimental results confirm the efficacy of the proposed method, and it can be used for online internal temperature estimation which is a key indicator for better real-time battery thermal management.

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Models of ground source heat pump (GSHP) systems are used as an aid for the correct design and optimization of the system. For this purpose, it is necessary to develop models which correctly reproduce the dynamic thermal behavior of each component in a short-term basis. Since the borehole heat exchanger (BHE) is one of the main components, special attention should be paid to ensuring a good accuracy on the prediction of the short-term response of the boreholes. The BHE models found in literature which are suitable for short-term simulations usually present high computational costs. In this work, a novel TRNSYS type implementing a borehole-to-ground (B2G) model, developed for modeling the short-term dynamic performance of a BHE with low computational cost, is presented. The model has been validated against experimental data from a GSHP system located at Universitat Politècnica de València, Spain. Validation results show the ability of the model to reproduce the short-term behavior of the borehole, both for a step-test and under normal operating conditions.

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Spectroscopic studies of line emission intensities and ratios offer an attractive option in the\r\ndevelopment of non-invasive plasma diagnostics. Evaluating ratios of selected He I line\r\nemission profiles from the singlet and triplet neutral helium spin systems allows for simultaneous\r\nmeasurement of electron density (ne) and temperature (Te) profiles. Typically, this powerful\r\ndiagnostic tool is limited by the relatively long relaxation times of the 3S metastable term of helium\r\nthat populates the triplet spin system, and on which electron temperature sensitive lines are based.\r\nBy developing a time dependent analytical solution, we model the time evolution of the two spin\r\nsystems. We present a hybrid time dependent/independent line ratio solution that improves the\r\nrange of application of this diagnostic technique in the scrape-off layer (SOL) and edge plasma\r\nregions when comparing it against the current equilibrium line ratio helium model used at\r\nTEXTOR.

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We extend the generalized Langevin equation (GLE) method [L. Stella, C. D. Lorenz, and L. Kantorovich, Phys. Rev. B 89, 134303 (2014)] to model a central classical region connected to two realistic thermal baths at two different temperatures. In such nonequilibrium conditions a heat flow is established, via the central system, in between the two baths. The GLE-2B (GLE two baths) scheme permits us to have a realistic description of both the dissipative central system and its surrounding baths. Following the original GLE approach, the extended Langevin dynamics scheme is modified to take into account two sets of auxiliary degrees of freedom corresponding to the mapping of the vibrational properties of each bath. These auxiliary variables are then used to solve the non-Markovian dissipative dynamics of the central region. The resulting algorithm is used to study a model of a short Al nanowire connected to two baths. The results of the simulations using the GLE-2B approach are compared to the results of other simulations that were carried out using standard thermostatting approaches (based on Markovian Langevin and Nosé-Hoover thermostats). We concentrate on the steady-state regime and study the establishment of a local temperature profile within the system. The conditions for obtaining a flat profile or a temperature gradient are examined in detail, in agreement with earlier studies. The results show that the GLE-2B approach is able to treat, within a single scheme, two widely different thermal transport regimes, i.e., ballistic systems, with no temperature gradient, and diffusive systems with a temperature gradient.

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The antimicrobial activity of atmospheric pressure non-thermal plasma has been exhaustively characterised, however elucidation of the interactions between biomolecules produced and utilised by bacteria and short plasma exposures are required for optimisation and clinical translation of cold plasma technology. This study characterizes the effects of non-thermal plasma exposure on acyl homoserine lactone (AHL)-dependent quorum sensing (QS). Plasma exposure of AHLs reduced the ability of such molecules to elicit a QS response in bacterial reporter strains in a dose-dependent manner. Short exposures (30-60 s) produce of a series of secondary compounds capable of eliciting a QS response, followed by the complete loss of AHL-dependent signalling following longer exposures. UPLC-MS analysis confirmed the time-dependent degradation of AHL molecules and their conversion into a series of by-products. FT-IR analysis of plasma-exposed AHLs highlighted the appearance of an OH group. In vivo assessment of the exposure of AHLs to plasma was examined using a standard in vivo model. Lettuce leaves injected with the rhlI/lasI mutant PAO-MW1 alongside plasma treated N-butyryl-homoserine lactone and n-(3-oxo-dodecanoyl)-homoserine lactone, exhibited marked attenuation of virulence. This study highlights the capacity of atmospheric pressure non-thermal plasma to modify and degrade AHL autoinducers thereby attenuating QS-dependent virulence in P. aeruginosa.

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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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Harnessing solar energy to provide for the thermal needs of buildings is one of the most promising solutions to the global energy issue. Exploiting the additional surface area provided by the building’s façade can significantly increase the solar energy output. Developing a range of integrated and adaptable products that do not significantly affect the building’s aesthetics is vital to enabling the building integrated solar thermal market to expand and prosper. This work reviews and evaluates solar thermal facades in terms of the standard collector type, which they are based on, and their component make-up. Daily efficiency models are presented, based on a combination of the Hottel Whillier Bliss model and finite element simulation. Novel and market available solar thermal systems are also reviewed and evaluated using standard evaluation methods, based on experimentally determined parameters ISO 9806. Solar thermal collectors integrated directly into the facade benefit from the additional wall insulation at the back; displaying higher efficiencies then an identical collector offset from the facade. Unglazed solar thermal facades with high capacitance absorbers (e.g. concrete) experience a shift in peak maximum energy yield and display a lower sensitivity to ambient conditions than the traditional metallic based unglazed collectors. Glazed solar thermal facades, used for high temperature applications (domestic hot water), result in overheating of the building’s interior which can be reduced significantly through the inclusion of high quality wall insulation. For low temperature applications (preheating systems), the cheaper unglazed systems offer the most economic solution. The inclusion of brighter colour for the glazing and darker colour for the absorber shows the lowest efficiency reductions (<4%). Novel solar thermal façade solutions include solar collectors integrated into balcony rails, shading devices, louvers, windows or gutters.

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Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

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Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

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Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.

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Forced convection heat transfer in a micro-channel filled with a porous material saturated with rarefied gas with internal heat generation is studied analytically in this work. The study is performed by analysing the boundary conditions for constant wall heat flux under local thermal non-equilibrium (LTNE) conditions. Invoking the velocity slip and temperature jump, the thermal behaviour of the porous-fluid system is studied by considering thermally and hydrodynamically fully-developed conditions. The flow inside the porous material is modelled by the Darcy–Brinkman equation. Exact solutions are obtained for both the fluid and solid temperature distributions for two primary approaches models A and B using constant wall heat flux boundary conditions. The temperature distributions and Nusselt numbers for models A and B are compared, and the limiting cases resulting in the convergence or divergence of the two models are also discussed. The effects of pertinent parameters such as fluid to solid effective thermal conductivity ratio, Biot number, Darcy number, velocity slip and temperature jump coefficients, and fluid and solid internal heat generations are also discussed. The results indicate that the Nusselt number decreases with the increase of thermal conductivity ratio for both models. This contrasts results from previous studies which for model A reported that the Nusselt number increases with the increase of thermal conductivity ratio. The Biot number and thermal conductivity ratio are found to have substantial effects on the role of temperature jump coefficient in controlling the Nusselt number for models A and B. The Nusselt numbers calculated using model A change drastically with the variation of solid internal heat generation. In contrast, the Nusselt numbers obtained for model B show a weak dependency on the variation of internal heat generation. The velocity slip coefficient has no noticeable effect on the Nusselt numbers for both models. The difference between the Nusselt numbers calculated using the two models decreases with an increase of the temperature jump coefficient.

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This work examines analytically the forced convection in a channel partially filled with a porous material and subjected to constant wall heat flux. The Darcy–Brinkman–Forchheimer model is used to represent the fluid transport through the porous material. The local thermal non-equilibrium, two-equation model is further employed as the solid and fluid heat transport equations. Two fundamental models (models A and B) represent the thermal boundary conditions at the interface between the porous medium and the clear region. The governing equations of the problem are manipulated, and for each interface model, exact solutions, for the solid and fluid temperature fields, are developed. These solutions incorporate the porous material thickness, Biot number, fluid to solid thermal conductivity ratio and Darcy number as parameters. The results can be readily used to validate numerical simulations. They are, further, applicable to the analysis of enhanced heat transfer, using porous materials, in heat exchangers.