659 research outputs found
Is isotropy restored at small scales in freely decaying strongly stratified turbulence?
No full textWe analyse the scale-dependent anisotropy of homogeneous stratified turbulence. The Ozmidov scale l_N (Ozmidov 1965) helps to compare the relative effects of inertia and of the buoyancy force, and thus to quantify the rise of anisotropy in different scale ranges: at large scales l >> l_N the anisotropy due to strong stratification is dominant, whereas at small scales l << l_N, universal 3D isotropic characteristic of turbulence appear to be restored. We investigate the corresponding dynamics using Direct Numerical Simulations (DNS) in freely decaying turbulence at different stratification rates. We confirm the return to isotropy of the small scales by analyzing the orientation-dependent power spectrum and poloidal/toroidal/density energy modes. To some extent, many characteristics of isotropic universality are restored at small scales but, surprisingly, the density spectrum (also potential energy spectrum) plays a particular role
Automation in sensing and raw material characterization - A conceptual framework
No full textThe use of sensor technologies for material characterization is rapidly growing and innovative advancement is observed. However, the use of sensor combinations for a raw material characterization in mining is very limited and automation of the material identification process using a combined sensor signal is not defined. Potential sensor technologies for raw material characterization were evaluated based on the applicability and technological maturity. To ensure a rapid implementation of the Real-time mining (RTM) project concept, mature technologies such as Red Green Blue (RGB) imaging, Visible Near Infrared (VNIR) hyperspectral imaging, Short Wave Infrared (SWIR) hyperspectral imaging, Fourier-Transform Infrared Spectroscopy (FTIR), Laser Induced Breakdown Spectroscopy (LIBS) and Raman were selected. Each selected technology was assessed for automation in sensing and applicability (for characterization of the test case materials). Based on the results the sensor data were further considered for data fusion. The proposed sensor combinations approach encompasses three levels of data fusion: low-level, mid-level and high-level. The data of the different sensors are fused together in order to acquire a wide range of mineral properties within each lithotype and an improved classification and predictive models. The preferred level of data fusion and preferred sensor data combinations will be used to develop a multi-variate statistical interpretation rule which relates combination of sensors signals with raw material properties. Thus a tool which integrates the combined sensor signal with materials properties will be developed and used to automate the material characterization process.Accepted Author ManuscriptResource Engineerin
Experimental and computational study of the influence of pre-damage patterns in unreinforced masonry crack propagation due to induced, repeated earthquakes
No full textInduced seismicity in the north of the Netherlands has recently exposed unprepared, unreinforced masonry structures to considerable earthquake risk. While the ultimate-limit state capacity of the structures is vital to assess the individual’s risk, their behavior during more frequent, lighter earthquakes, leading to ‘lighter damage’, has shown to be strongly linked to economic losses and societal unrest. When observing the light damage caused by minor earthquakes, the existing state of the structure appears to be highly relevant for the final damage intensity and configuration: earthquakes that may have otherwise caused no apparent damage, may intensify existing damage. In particular, incipient damage due to settlements is common in the baked-clay and calcium-silicate brick masonry structures of the region.This paper details the study of full-scale laboratory walls, pre-damaged following typical (crack) patterns caused by settlements and tested with quasi-static lateral loads. The aggravation of the damage during a relevant number of load cycles is monitored using full-field digital image correlation. The damage is quantified objectively using a purposely-developed damage parameter.The tests are used (together with previous studies) to further calibrate computational finite element models, which coupled with detailed soil-structure interaction boundary conditions, are then employed to assess a larger number of structural geometries and pre-damaged configurations exposed to (repeated) induced earthquake acceleration histories.Both experimental and computational approaches show that settlement pre-damage in masonry structures increases the likelihood and the amount of further damage. This is more easily observed when some initial, yet limited damage exists and the masonry wall is exposed to moderate earthquake vibrations in the order of 30 millimeters per second.Accepted Author ManuscriptApplied Mechanic
Re: An Institution Par Excellence: Prof. B. Ramamurthi 1922-2003. Surg Neurol 2004;61:511-14 [1]
No full text[No abstract available]0
Sensing and data fusion opportunities for raw material characterisation in mining: Technology and data-driven approach
No full textThe rising demands for mined products lead to the extraction of materials in geologically complex regions. This calls for mining process changes and interventions driven by technology and advanced data analytics. The dynamic development of state-of-the-art sensor technologies and their potential use in mining is projected to significantly reduce costs in the industry. However, despite rapid advances in sensor technologies, there is still a demand for novel data analytical approaches to enable accurate characterisation of material along the mining value chain, as advanced data analytics is key to gain knowledge from the complex sensor-derived data. Therefore, sensor technology, coupled with advanced data analytics is crucial for the rapid and accurate characterisation of material in mining operations. Access to rapid and accurate data on the key geological attributes (e.g., mineralogy and geochemistry) along the mining value chain has significant implications for the production process efficiency in commercial mines. Such data would greatly assist the improvement of deposit models, optimise ore processing, specify product quality and improve operational decision-making. Sensor technologies operate over a specific range of the electromagnetic spectrum and provide information on certain aspects of material properties that are of potential interest for mining extraction. However, a single sensor might not provide a sufficiently comprehensive description of a material’s composition. This introduces uncertainty into both resource estimation and requirements definition for mineral processing. Thus, it is necessary to utilise strategic sensor combinations to improve accuracy, minimise uncertainty, and enhance specific insights of material compositions. Combinations of sensors can be implemented using a data fusion approach. The fusion of sensed data can be realised at different levels: low-, mid-, and high-level, when the integration occurs at the data level, features level and decision level, respectively. This research aims to develop methods for the characterisation of raw materials using multiple sensor technologies and sensor combinations concept (data fusion at different levels), that can be potentially applicable to mining operations. The study involved the multispectral and hyperspectral imaging techniques, such as red-green-blue (RGB) imaging, visible and near-infrared (VNIR) and short-wave infrared (SWIR) hyperspectral imaging, and point spectroscopic techniques, such as mid-wave infrared (MWIR), long-wave infrared (LWIR) and Raman spectroscopy to acquire spectral information over a wider range of the electromagnetic spectrum. First, an investigation was conducted on the usability of the individual sensor technologies coupled with data analytics for the characterisation of a polymetallic sulphide deposit at different levels. The different levels of material characterisation aimed to allow mineral mapping, ore–waste discrimination, fragmentation analysis, and semi-quantitative analysis of elements and minerals. The positive outcomes of the use of the individual techniques led to the development of a data fusion framework that enables data integration (including multi-scale and multi-resolution data) at different levels (e.g., low-level and mid-level). The developed data fusion concept was implemented and validated using different test scenarios..
Adaptive data-driven reduced-order modelling techniques for nuclear reactor analysis
No full textLarge-scale complex systems require high-fidelity models to capture the dynamics of the system accurately. For example, models of nuclear reactors capture multiphysics interactions (e.g., radiation transport, thermodynamics, heat transfer, and fluid mechanics) occurring at various scales of time (prompt neutrons to burn-up calculations) and space (cell and core calculations). The complexity of thesemodels, however, renders their use intractable for applications relying on repeated evaluations, such as control, optimization, uncertainty quantification, and sensitivity studies.RST/Reactor Physics and Nuclear Material
Effects of optical filter drifts in wavelength division multiplexing system with cascaded optical amplifiers
No full text3D flow organization and dynamics in subsonic jets: Aeroacoustic source analysis by tomographic PIV
No full textTo meet the increasingly stringent noise regulation, aircraft manufacturers are searching for solutions to jet noise. This, which constitutes a significant amount of the total noise emitted by civil aircrafts, is generated by the mixing processes between the exhaust flow leaving the engine and the atmosphere. A detailed understanding of such mixing process is of paramount importance to identify mechanisms responsible for noise production, i.e. the aeroacoustic source, and, ultimately, to develop noise control strategies. This thesis proposes an unprecedented experimental-based approach to visualize and measure the aeroacoustic sources in jet flows. Time-resolved tomographic particle image velocimetry (TR-TOMO PIV) is employed to obtain time-dependent three-dimensional (3D) measurements of the turbulent flow patterns, while the instantaneous aeroacoustic source is explored using Powell’s aeroacoustic analogy. TR-TOMO PIV experiments are conducted in a tailored jet facility. Measurements are performed both on jets issued through circular and 6-chevron nozzles, with the latter configuration that is nowadays used in jet engines to reduce acoustic emissions. The attention is placed upon the 3D organization and dynamics of flow transition, where coherent flow structures play a role in the generation of noise. The full 3D approach enables unambiguous descriptions of the vortex topology, while the temporal resolution allows addressing the growth and development of the coherent flow structures along with their mutual interaction. In the circular jet, the characteristic pulsatile motion of vortex ring shedding and pairing is accompanied by the growth of azimuthal instabilities and the formation of streamwise vortices leading to the breakdown of the vortex rings. In the chevron jet, instead, the axisymmetric ring-like coherence is replaced by streamwise flow structures whose decay is accompanied by the formation of C-shaped structures. The relation between coherent structures and the instantaneous acoustic source is investigated recalling Powell’s aeroacoustic analogy, with the acoustic source that is identified by the second time derivative of the Lamb vector. The spatio-temporal evolution of the source is mapped and is compared to that of the vortices, to detect flow events involved in the acoustic generation. In the circular jet, most pronounced source activity is observed during the vortex-ring breakdown, whereas, in the chevron configuration, is associated with the process of streamwise vortex decay and C structure formation. Performing unbiased acoustic predictions of the jet noise with TR-TOMO PIV measurements is a challenging task due to the constraints on the extent of the instantaneous measurement domain and on the required spatial and temporal resolutions. To meet this challenge, the thesis finally proposes a strategy to perform far-field acoustic predictions by direct evaluation of Powell’s analogy using TR-TOMO PIV data.AerodynamicsAerospace Engineerin
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