922 resultados para Order of magnitude
Resumo:
We present a mass-conservative vertex-centred finite volume method for efficiently solving the mixed form of Richards’ equation in heterogeneous porous media. The spatial discretisation is particularly well-suited to heterogeneous media because it produces consistent flux approximations at quadrature points where material properties are continuous. Combined with the method of lines, the spatial discretisation gives a set of differential algebraic equations amenable to solution using higher-order implicit solvers. We investigate the solution of the mixed form using a Jacobian-free inexact Newton solver, which requires the solution of an extra variable for each node in the mesh compared to the pressure-head form. By exploiting the structure of the Jacobian for the mixed form, the size of the preconditioner is reduced to that for the pressure-head form, and there is minimal computational overhead for solving the mixed form. The proposed formulation is tested on two challenging test problems. The solutions from the new formulation offer conservation of mass at least one order of magnitude more accurate than a pressure head formulation, and the higher-order temporal integration significantly improves both the mass balance and computational efficiency of the solution.
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While recent research has provided valuable information as to the composition of laser printer particles, their formation mechanisms, and explained why some printers are emitters whilst others are low emitters, fundamental questions relating to the potential exposure of office workers remained unanswered. In particular, (i) what impact does the operation of laser printers have on the background particle number concentration (PNC) of an office environment over the duration of a typical working day?; (ii) what is the airborne particle exposure to office workers in the vicinity of laser printers; (iii) what influence does the office ventilation have upon the transport and concentration of particles?; (iv) is there a need to control the generation of, and/or transport of particles arising from the operation of laser printers within an office environment?; (v) what instrumentation and methodology is relevant for characterising such particles within an office location? We present experimental evidence on printer temporal and spatial PNC during the operation of 107 laser printers within open plan offices of five buildings. We show for the first time that the eight-hour time-weighted average printer particle exposure is significantly less than the eight-hour time-weighted local background particle exposure, but that peak printer particle exposure can be greater than two orders of magnitude higher than local background particle exposure. The particle size range is predominantly ultrafine (< 100nm diameter). In addition we have established that office workers are constantly exposed to non-printer derived particle concentrations, with up to an order of magnitude difference in such exposure amongst offices, and propose that such exposure be controlled along with exposure to printer derived particles. We also propose, for the first time, that peak particle reference values be calculated for each office area analogous to the criteria used in Australia and elsewhere for evaluating exposure excursion above occupational hazardous chemical exposure standards. A universal peak particle reference value of 2.0 x 104 particles cm-3 has been proposed.
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Residual amplitude modulation (RAM) mechanisms in electro-optic phase modulators are detrimental in applications that require high purity phase modulation of the incident laser beam. While the origins of RAMare not fully understood, measurements have revealed that it depends on the beam properties of the laser as well as the properties of the medium. Here we present experimental and theoretical results that demonstrate, for the first time, the dependence of RAM production in electro-optic phase modulators on beam intensity. The results show an order of magnitude increase in the level of RAM, around 10 dB, with a fifteenfold enhancement in the input intensity from 12 to 190 mW/mm 2. We show that this intensity dependent RAM is photorefractive in origin. © 2012 Optical Society of America.
Resumo:
The first representative chemical, structural, and morphological analysis of the solid particles from a single collection surface has been performed. This collection surface sampled the stratosphere between 17 and 19km in altitude in the summer of 1981, and therefore before the 1982 eruptions of El Chichón. A particle collection surface was washed free of all particles with rinses of Freon and hexane, and the resulting wash was directed through a series of vertically stacked Nucleopore filters. The size cutoff for the solid particle collection process in the stratosphere is found to be considerably less than 1 μm. The total stratospheric number density of solid particles larger than 1μm in diameter at the collection time is calculated to be about 2.7×10−1 particles per cubic meter, of which approximately 95% are smaller than 5μm in diameter. Previous classification schemes are expanded to explicitly recognize low atomic number material. With the single exception of the calcium-aluminum-silicate (CAS) spheres all solid particle types show a logarithmic increase in number concentration with decreasing diameter. The aluminum-rich particles are unique in showing bimodal size distributions. In addition, spheres constitute only a minor fraction of the aluminum-rich material. About 2/3 of the particles examined were found to be shards of rhyolitic glass. This abundant volcanic material could not be correlated with any eruption plume known to have vented directly to the stratosphere. The micrometeorite number density calculated from this data set is 5×10−2 micrometeorites per cubic meter of air, an order of magnitude greater than the best previous estimate. At the collection altitude, the maximum collision frequency of solid particles >5μm in average diameter is calculated to be 6.91×10−16 collisions per second, which indicates negligible contamination of extraterrestrial particles in the stratosphere by solid anthropogenic particles.
Resumo:
Many state of the art vision-based Simultaneous Localisation And Mapping (SLAM) and place recognition systems compute the salience of visual features in their environment. As computing salience can be problematic in radically changing environments new low resolution feature-less systems have been introduced, such as SeqSLAM, all of which consider the whole image. In this paper, we implement a supervised classifier system (UCS) to learn the salience of image regions for place recognition by feature-less systems. SeqSLAM only slightly benefits from the results of training, on the challenging real world Eynsham dataset, as it already appears to filter less useful regions of a panoramic image. However, when recognition is limited to specific image regions performance improves by more than an order of magnitude by utilising the learnt image region saliency. We then investigate whether the region salience generated from the Eynsham dataset generalizes to another car-based dataset using a perspective camera. The results suggest the general applicability of an image region salience mask for optimizing route-based navigation applications.
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Located in the Gulf of Mexico in nearly 8,000 ft of water, the Perdido project is the deepest spar application to date in the world and Shell’s first fully integrated application of its inhouse digital oilfield technology— called “Smart Field”—in the Western hemisphere. Developed by Shell on behalf of partners BP and Chevron, the spar and the subsea equipment connected to it will eventually capture about an order of magnitude more data than is collected from any other Shelldesigned and -managed development operating in the Gulf of Mexico. This article describes Shell’s digital oilfield design philosophy, briefly explains the five design elements that underpin “smartness” in Shell’s North and South American operations and sheds light on the process by which a highly customized digital oilfield development and management plan was put together for Perdido. Although Perdido is the first instance in North and South America in which these design elements and processes were applied in an integrated way, all of Shell’s future new developments in the Western hemisphere are expected to follow the same overarching design principles. Accordingly, this article uses Perdido as a real-world example to outline the high-level details of Shell’s digital oilfield design philosophy and processes.
Resumo:
Located in the Gulf of Mexico in nearly 8,000 feet of water, the Perdido development is the world’s deepest spar and Shell’s first Smart Field in the Western hemisphere. Jointly developed by Shell, BP, and Chevron, the spar and the subsea equipment connected to it will eventually capture approximately an order of magnitude more data than is collected from any other Shell-designed and managed development currently operating in the Gulf of Mexico. This paper will describe Shell’s Smart Fields design philosophy, briefly explain the five design elements that underpin “smartness” in Shell’s North and South American operations—specifically, remote assisted operations, exception-based surveillance, collaborative work environments, hydrocarbon development tools and workflows, and Smart Fields Foundation IT infrastructure—and shed light on the process by which a highly customized Smart Fields development and management plan was put together for Perdido.
Resumo:
Nanosecond dynamics of two separated discharge cycles in an asymmetric dielectric barrier discharge is studied using time-resolved current and voltage measurements synchronized with high-speed (∼5 ns) optical imaging. Nanosecond dc pulses with tailored raise and fall times are used to generate solitary filamentary structures (SFSs) during the first cycle and a uniform glow during the second. The SFSs feature ∼1.5 mm thickness, ∼1.9 A peak current, and a lifetime of several hundred nanoseconds, at least an order of magnitude larger than in common microdischarges. This can be used in alternating localized and uniform high-current plasma treatments in various applications.
Resumo:
The response of an originally developed catalytic sensor with a Nb2 O5 nanowire array at its outer surface to the varying density of O atoms is experimentally and numerically studied. This technique can be used to measure one order of magnitude lower densities of O atoms and achieve a stable linear response in a significantly broader pressure range compared to conventional catalytic probes with a flat surface. The nanostructured outer surface also acts as a thermal barrier against sensor overheating. This approach is generic and can be used for reactive species detection in other reactive gas environments.
Resumo:
Multiscale hybrid simulations that bridge the nine-order-of-magnitude spatial gap between the macroscopic plasma nanotools and microscopic surface processes on nanostructured solids are described. Two specific examples of carbon nanotip-like and semiconductor quantum dot nanopatterns are considered. These simulations are instrumental in developing physical principles of nanoscale assembly processes on solid surfaces exposed to low-temperature plasmas.
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Hailstones in wet growth are commonly found in thunderclouds. While the ice-ice relative growth rate mechanism is generally accepted as the most likely cause of thunderstorm electrification, it is uncertain if this mechanism will operate under wet growth conditions because ice crystals are more likely to stick to the wet surface of a hailstone rather than bounce off it. Experiments were carried out in the laboratory to investigate if there was any charge separated when vapor-grown ice crystals bounced off a wet hailstone. A cloud of supercooled droplets, with and without ice crystals, was drawn past a simulated hailstone. In the dry growth regime, the hailstone charged strongly positive when droplets and crystals co-existed in the cloud. With only droplets in the cloud, there was no charging in the dry growth regime. However, as the hailstone attained wet growth, positive charging currents of about 0.5 and 3.5 pA were observed at 12 and 20 m s-1, respectively. We hypothesize that this observed charging was due to the evaporation of melt water. This so called Dinger-Gunn Effect is due to the ejection of negatively charged minute droplets produced by air bubbles bursting at the surface of the melt water. However the charge separated in wet growth was an order of magnitude smaller than that in dry growth and, therefore, we conclude that it is unlikely to play an important role in the electrification of thunderstorms.
Resumo:
Effective control of morphology and electrical connectivity of networks of single-walled carbon nanotubes (SWCNTs) by using rough, nanoporous silica supports of Fe catalyst nanoparticles in catalytic chemical vapor deposition is demonstrated experimentally. The very high quality of the nanotubes is evidenced by the G-to-D Raman peak ratios (>50) within the range of the highest known ratios. Transitions from separated nanotubes on smooth SiO2 surface to densely interconnected networks on the nanoporous SiO2 are accompanied by an almost two-order of magnitude increase of the nanotube density. These transitions herald the hardly detectable onset of the nanoscale connectivity and are confirmed by the microanalysis and electrical measurements. The achieved effective nanotube interconnection leads to the dramatic, almost three-orders of magnitude decrease of the SWCNT network resistivity compared to networks of similar density produced by wet chemistry-based assembly of preformed nanotubes. The growth model, supported by multiscale, multiphase modeling of SWCNT nucleation reveals multiple constructive roles of the porous catalyst support in facilitating the catalyst saturation and SWCNT nucleation, consistent with the observed higher density of longer nanotubes. The associated mechanisms are related to the unique surface conditions (roughness, wettability, and reduced catalyst coalescence) on the porous SiO2 and the increased carbon supply through the supporting porous structure. This approach is promising for the direct integration of SWCNT networks into Si-based nanodevice platforms and multiple applications ranging from nanoelectronics and energy conversion to bio- and environmental sensing.
Resumo:
Particle number concentrations vary significantly with environment and, in this study, we attempt to assess the significance of these differences. Towards this aim, we reviewed 85 papers that have reported particle number concentrations levels at 126 sites covering different environments. We grouped the results into eight categories according to measurement location including: road tunnel, on-road, road-side, street canyon, urban, urban background, rural, and clean background. From these reports, the overall median number concentration for each of the eight site categories was calculated. The eight location categories may be classified into four distinct groups. The mean median particle number locations for these four types were found to be statistically different from each other. Rural and clean background sites had the lowest concentrations of about 3x103 cm-3. Urban and urban background sites showed concentrations that were three times higher (9x103 cm-3). The mean concentration for the street canyon, roadside and on-road measurement sites was 4.6x104 cm-3, while the highest concentrations were observed in the road tunnels (8.6x104 cm-3). This variation is important when assessing human exposure-response for which there is very little data available, making it difficult to develop health guidelines, a basis for national regulations. Our analyses shows that the current levels in environments affected by vehicle emissions are 3 to 28 times higher than in the natural environments. At present, there is no threshold level in response to exposure to ultrafine particles. Therefore, future control and management strategies should target a decrease of these particles in urban environments by more than one order of magnitude to bring them down to the natural background. At present there is a long way to go to achieve this.
Resumo:
Electrochemical aptamer-based (E-AB) sensors represent an emerging class of recently developed sensors. However, numerous of these sensors are limited by a low surface density of electrode-bound redox-oligonucleotides which are used as probe. Here we propose to use the concept of electrochemical current rectification (ECR) for the enhancement of the redox signal of E-AB sensors. Commonly, the probe-DNA performs a change in conformation during target binding and enables a nonrecurring charge transfer between redox-tag and electrode. In our system, the redox-tag of the probe-DNA is continuously replenished by solution-phase redox molecules. A unidirectional electron transfer from electrode via surface-linked redox-tag to the solution-phase redox molecules arises that efficiently amplifies the current response. Using this robust and straight-forward strategy, the developed sensor showed a substantial signal amplification and consequently improved sensitivity with a calculated detection limit of 114 nM for ATP, which was improved by one order of magnitude compared with the amplification-free detection and superior to other previous detection results using enzymes or nanomaterials-based signal amplification. To the best of our knowledge, this is the first demonstration of an aptamer-based electrochemical biosensor involving electrochemical rectification, which can be presumably transferred to other biomedical sensor systems.
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This paper presents visual detection and classification of light vehicles and personnel on a mine site.We capitalise on the rapid advances of ConvNet based object recognition but highlight that a naive black box approach results in a significant number of false positives. In particular, the lack of domain specific training data and the unique landscape in a mine site causes a high rate of errors. We exploit the abundance of background-only images to train a k-means classifier to complement the ConvNet. Furthermore, localisation of objects of interest and a reduction in computation is enabled through region proposals. Our system is tested on over 10km of real mine site data and we were able to detect both light vehicles and personnel. We show that the introduction of our background model can reduce the false positive rate by an order of magnitude.