991 resultados para Thermal Cracking


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The low-altitude aircraft inspection of powerlines, or other linear infrastructure networks, is emerging as an important application requiring specialised control technologies. Despite some recent advances in automated control related to this application, control of the underactuated aircraft vertical dynamics has not been completely achieved, especially in the presence of thermal disturbances. Rejection of thermal disturbances represents a key challenge to the control of inspection aircraft due to the underactuated nature of the dynamics and specified speed, altitude, and pitch constraints. This paper proposes a new vertical controller consisting of a backstepping elevator controller with feedforward-feedback throttle controller. The performance of our proposed approach is evaluated against two existing candidate controllers.

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Stress corrosion cracking (SCC) is a well known form of environmental attack in low carat gold jewellery. It is desirable to have a quick, easy and cost effective way to detect SCC in alloys and prevent them from being used and later failing in their application. A facile chemical method to investigate SCC of 9 carat gold alloys is demonstrated. It involves a simple application of tensile stress to a wire sample in a corrosive environment such as 1–10 % FeCl3 which induces failure in less than 5 minutes. In this study three quaternary (Au, Ag, Cu and Zn) 9 carat gold alloy compositions were investigated for their resistance to SCC and the relationship between time to failure and processing conditions is studied. It is envisaged that the use of such a rapid and facile screening procedure at the production stage may readily identify alloy treatments that produce jewellery that will be susceptible to SCC in its lifetime.

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Multi-Objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the thermoeconomic and Environmental aspects have been considered, simultaneously. The environmental objective function has been defined and expressed in cost terms. One of the most suitable optimization techniques developed using a particular class of search algorithms known as; Multi-Objective Particle Swarm Optimization (MOPSO) algorithm has been used here. This approach has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of fuzzy decision-making with the aid of Bellman-Zadeh approach has been presented and a final optimal solution has been introduced.

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Faulted stacking layers are ubiquitously observed during the crystal growth of semiconducting nanowires (NWs). In this paper, we employ the reverse non-equilibrium molecular dynamics simulation to elucidate the effect of various faulted stacking layers on the thermal conductivity (TC) of silicon (Si) NWs. We find that the stacking faults can greatly reduce the TC of the Si NW. Among the different stacking faults that are parallel to the NW's axis, the 9R polytype structure, the intrinsic and extrinsic stacking faults (iSFs and eSFs) exert more pronounced effects in the reduction of TC than the twin boundary (TB). However, for the perpendicularly aligned faulted stacking layers, the eSFs and 9R polytype structures are observed to induce a larger reduction to the TC of the NW than the TB and iSFs. For all considered NWs, the TC does not show a strong relation with the increasing number of faulted stacking layers. Our studies suggest the possibility of tuning the thermal properties of Si NWs by altering the crystal structure via the different faulted stacking layers.

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A series of NR composites filled with modified kaolinite (MK), carbon black (CB) and the hybrid fillercontained MK and CB, were prepared by melt blending. The microstructure, combustion and thermaldecomposition behaviors of NR composites were characterized by TEM, XRD, infrared spectroscopy, conecalorimeter test (CCT) and thermal-gravimetric analysis (TG). The results show that the filler hybridizationcan improve the dispensability and shape of the kaolinite sheets in the rubber matrix and change theinterface bond between kaolinite particles and rubber molecules. NR-3 filled by 10 phr MK and 40 phr CBhas the lowest heat release rate (HRR), mass loss rate (MLR), total heat release (THR), smoke productionrate (SPR) and the highest char residue among all the NR composites. Therefore, the hybridization ofthe carbon black particles with the kaolinite particles can effectively improve the thermal stability andcombustion properties of NR composites.

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Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

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Many applications can benefit from the accurate surface temperature estimates that can be made using a passive thermal-infrared camera. However, the process of radiometric calibration which enables this can be both expensive and time consuming. An ad hoc approach for performing radiometric calibration is proposed which does not require specialized equipment and can be completed in a fraction of the time of the conventional method. The proposed approach utilizes the mechanical properties of the camera to estimate scene temperatures automatically, and uses these target temperatures to model the effect of sensor temperature on the digital output. A comparison with a conventional approach using a blackbody radiation source shows that the accuracy of the method is sufficient for many tasks requiring temperature estimation. Furthermore, a novel visualization method is proposed for displaying the radiometrically calibrated images to human operators. The representation employs an intuitive coloring scheme and allows the viewer to perceive a large variety of temperatures accurately.

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Exploring thermal transport in graphene-polymer nanocomposite is significant to its applications with better thermal properties. Interfacial thermal conductance between graphene and polymer matrix plays a critical role in the improvement of thermal conductivity of graphene-polymer nanocomposite. Unfortunately, it is still challenging to understand the interfacial thermal transport between graphene nanofiller and polymer matrix at small material length scale. To this end, using non-equilibrium molecular dynamics simulations, we investigate the interfacial thermal conductance of graphene-polyethylene (PE) nanocomposite. The influence of functionalization with hydrocarbon chains on the interfacial thermal conductance of graphene-polymer nanocomposites was studied, taking into account of the effects of model size and thermal conductivity of graphene. An analytical model is also used to calculate the thermal conductivity of nanocomposite. The results are considered to contribute to development of new graphene-polymer nanocomposites with tailored thermal properties.

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Industrial transformer is one of the most critical assets in the power and heavy industry. Failures of transformers can cause enormous losses. The poor joints of the electrical circuit on transformers can cause overheating and results in stress concentration on the structure which is the major cause of catastrophic failure. Few researches have been focused on the mechanical properties of industrial transformers under overheating thermal conditions. In this paper, both mechanical and thermal properties of industrial transformers are jointly investigated using Finite Element Analysis (FEA). Dynamic response analysis is conducted on a modified transformer FEA model, and the computational results are compared with experimental results from literature to validate this simulation model. Based on the FEA model, thermal stress is calculated under different temperature conditions. These analysis results can provide insights to the understanding of the failure of transformers due to overheating, therefore are significant to assess winding fault, especially to the manufacturing and maintenance of large transformers.

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A series of styrene-butadiene rubber (SBR) nanocomposites filledwith different particle sized kaolinites are prepared via a latex blending method. The thermal stabilities of these clay polymer nanocomposites (CPN) are characterized by a range of techniques including thermogravimetry (TG), digital photos, scanning electron microscopy (SEM) and Raman spectroscopy. These CPN show some remarkable improvement in thermal stability compared to that of the pure SBR. With the increase of kaolinite particle size, the residual char content and the average activation energy of kaolinite SBR nanocomposites all decrease; the pyrolysis residues become porous; the crystal carbon in the pyrolysis residues decrease significantly from 58.23% to 44.41%. The above results prove that the increase of kaolinite particle size is not beneficial in improving the thermal stability of kaolinite SBR nanocomposites.

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Nucleation and growth of highly crystalline silicon nanoparticles in atmospheric-pressure low-temperature microplasmas at gas temperatures well below the Si crystallization threshold and within a short (100 μs) period of time are demonstrated and explained. The modeling reveals that collision-enhanced ion fluxes can effectively increase the heat flux on the nanoparticle surface and this heating is controlled by the ion density. It is shown that nanoparticles can be heated to temperatures above the crystallization threshold. These combined experimental and theoretical results confirm the effective heating and structure control of Si nanoparticles at atmospheric pressure and low gas temperatures.

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Controlling the electrical resistance of granular thin films is of great importance for many applications, yet a full understanding of electron transport in such films remains a major challenge. We have studied experimentally and by model calculations the temperature dependence of the electrical resistance of ultrathin gold films at temperatures between 2 K and 300 K. Using sputter deposition, the film morphology was varied from a discontinuous film of weakly coupled meandering islands to a continuous film of strongly coupled coalesced islands. In the weak-coupling regime, we compare the regular island array model, the cotunneling model, and the conduction percolation model with our experimental data. We show that the tunnel barriers and the Coulomb blockade energies are important at low temperatures and that the thermal expansion of the substrate and the island resistance affect the resistance at high temperatures. At low temperatures our experimental data show evidence for a transition from electron cotunneling to sequential tunneling but the data can also be interpreted in terms of conduction percolation. The resistivity and temperature coefficient of resistance of the meandering gold islands are found to resemble those of gold nanowires. We derive a simple expression for the temperature at which the resistance changes from non-metal-like behavior into metal-like behavior. In the case of strong island coupling, the total resistance is solely determined by the Ohmic island resistance.

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We report the study of the thermal transport management of monolayer graphene allotrope nanoribbons (size ∼20 × 4 nm2) by the modulation of their structures via molecular dynamics simulations. The thermal conductivity of graphyne (GY)-like geometries is observed to decrease monotonously with increasing number of acetylenic linkages between adjacent hexagons. Strikingly, by incorporating those GY or GY-like structures, the thermal performance of graphene can be effectively engineered. The resulting hetero-junctions possess a sharp local temperature jump at the interface, and show a much lower effective thermal conductivity due to the enhanced phonon–phonon scattering. More importantly, by controlling the percentage, type and distribution pattern of the GY or GY-like structures, the hetero-junctions are found to exhibit tunable thermal transport properties (including the effective thermal conductivity, interfacial thermal resistance and rectification). This study provides a heuristic guideline to manipulate the thermal properties of 2D carbon networks, ideal for application in thermoelectric devices with strongly suppressed thermal conductivity.

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The effect of plasmon oscillations on the DC tunnel current in a gold nanoisland thin film (GNITF) is investigated using low intensity P~1W/cm2 continuous wave lasers. While DC voltages (1–150 V) were applied to the GNITF, it was irradiated with lasers at different wavelengths (k¼473, 532, and 633 nm). Because of plasmon oscillations, the tunnel current increased. It is found that the tunnel current enhancement is mainly due to the thermal effect of plasmon oscillations rather than other plasmonic effects. The results are highly relevant to applications of plasmonic effects in opto-electronic devices.

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The axial coefficients of thermal expansion (CTE) of various carbon nanotubes (CNTs), i.e., single-wall carbon nanotubes (SWCNTs), and some multi-wall carbon nanotubes (MWCNTs), were predicted using molecular dynamics (MDs) simulations. The effects of two parameters, i.e., temperature and the CNT diameter, on CTE were investigated extensively. For all SWCNTs and MWCNTs, the obtained results clearly revealed that within a wide low temperature range, their axial CTEs are negative. As the diameter of CNTs decreases, this temperature range for negative axial CTEs becomes narrow, and positive axial CTEs appear in high temperature range. It was found that the axial CTEs vary nonlinearly with the temperature, however, they decrease linearly as the CNT diameter increases. Moreover, within a wide temperature range, a set of empirical formulations was proposed for evaluating the axial CTEs of armchair and zigzag SWCNTs using the above two parameters. Finally, it was found that the absolute value of the negative axial CTE of any MWCNT is much smaller than those of its constituent SWCNTs, and the average value of the CTEs of its constituent SWCNTs. The present fundamental study is very important for understanding the thermal behaviors of CNTs in such as nanocomposite temperature sensors, or nanoelectronics devices using CNTs.