1,232 research outputs found

    A multiscale approach to state estimation with applications in process operability analysis and model predictive control

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    Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2000.Includes bibliographical references.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.This thesis explores the application of multiscale ideas to the areas of state estimation and control. The work represents a significant departure from the traditional representations in the time and frequency domains, and provides a novel framework that leads to fast, efficient, and modular estimation algorithms. Multiscale methods were rediscovered through wavelet theory in the mid-eighties, as a tool for the geophysics community. Like Fourier theory, it provides a more instructive representation of data than time series alone, by decomposition into a different set of orthonormal basis functions. Multiscale models and data sets exist on multiscale trees of nodes. Each node represents a place holder corresponding to a time point in a time series. The nodes of a tree form a structure which may contain measurements, states, inputs, outputs, and uncertainties. Each level of the tree represents the set of data at a given level of resolution. This dual localization in time and frequency has benefits in the storage of information, since irrelevant data and pure noise can be identified and discarded. It also preserves time and frequency information in a way that Fourier theory cannot. Grouping and condensing of important information follows naturally, which facilitates the making of decisions at a level of detail relevant to the question being asked. Multiscale systems theory is a general approach for multiscale model construction on a tree. This thesis derives the multiscale models corresponding to the Haar transform, which produces a modified hat transform for input data. Autoregressive models, commonly used in time series analysis, give rise to multiscale models on the tree. These allow us to construct numerical algorithms that are effcient and parallelizable, and scale logarithmically with the number of data points, rather than the linear performance typical for similar time-series algorithms. This multiscale systems theory generalizes easily to other wavelet bases. Multiscale models of the underlying physics and the measurement model can be combined to construct a cost function which estimates the underlying physical states from a set of measurements. The resulting set of normal equations is sparse and contains a specialized structure, leading to a highly efficient solution strategy. A modified multiscale state estimation algorithm incorporates prior estimates, consistent with the Kalman filter, with which it is linked. A constrained multiscale state estimator incorporates constraints in the states, and in linear combinations of the states. All incarnations of the multiscale state estimator provide a framework for the optimal fusion of multiple sets of measurements, including those taken at different levels of resolution. This is particularly useful in estimation and control problems where measurement data and control strategies occur at multiple rates. The arbitrary size of the state allows for the use of higher order underlying physical models, without modification of the estimation algorithm. Finally, the algorithm accommodates an arbitrary specification of the uncertainty estimates at any combination of time points or level of resolution. The structure of the solution algorithm is sufficiently flexible to use the same intermediate variables for all of these modifications, leading to considerable reusability, both of code, and of prior calculations. Thus, the multiscale state estimation algorithm is modular and parallelizable. An uncertainty analysis of the algorithm represents state estimation error in terms of the underlying model and measurement uncertainties. Depending on the size of the problem, different techniques should be used to construct the probability distribution functions of the error estimates. This thesis demonstrates direct integration, propagation of the moments of the measurement and model errors, polynomial chaos expansions, and an approximation using Gaussian quadrature and Monte Carlo simulation. A sample of smaller case studies shows the range of uses of the algorithm. Three larger case studies demonstrate the multiscale state estimator in realistic chemical engineering examples. The terephthalic acid plant case study successfully incorporates a non-linear model of the first continuously stirred tank reactor into the multiscale state estimator. The paper-rolling case study compares the multiscale state estimator to the Karhunen-Loeve transform as a means of state estimation. Finally, the heavy oil fractionator of the Shell Control Problem demonstrates the multiscale state estimator in a control setting.by Matthew Simon Dyer.Ph.D

    Investigating avian competition for surface water in an arid zone bioregion

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    Interference competition has the potential to alter avian assemblages at long-lasting arid zone waterholes, particularly in a warming world, as more potentially aggressive species frequent these sites to drink. We used camera traps and observational surveys to investigate interference competition between terrestrial avian species at six long-lasting waterholes across three sampling seasons (two summers and one winter) within the MacDonnell Ranges Bioregion in central Australia. The proportion of individuals drinking for each of four dietary classes (granivores, nectarivores, omnivores, and insectivores) was modelled in relation to their abundance in the immediate waterhole habitat, which informed the potential for competition in each season. We then used the temporal overlap estimators to quantify the degree of competition between species at waterholes with species grouped into families (Meliphagidae, Ptilonorhynchidae, Estrildidae, and Rhipiduridae). We found the proportion of individuals drinking at waterholes was greatest during hot and dry periods, suggesting the potential for interference competition is greatest during these times. This was particularly the case for nectarivores where, in hot and dry conditions, the proportion of drinking individuals increased significantly as their abundance also increased in the waterhole habitat. We predicted that subordinate species would alter their activity periods to avoid competitive interactions with meliphagids (honeyeaters), however, we found there was a high degree of temporal overlap between all families sampled across all seasons. These results suggest subordinate species are unlikely to be excluded from long-lasting waterholes by potentially aggressive species, such as honeyeaters. However, some species may face trade-offs between foraging and accessing waterholes to stay hydrated as they shift their activity to avoid the hottest parts of the day during the summer months. Under global warming, extended hot and dry periods will likely create conditions where balancing energy and hydration requirements becomes increasingly difficult and results in the loss of body condition.</p

    Fact or Fiction: Oil Sands Reclamation

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    Surface mining for oil sands is radically transforming the Athabasca Boreal region of northeastern Alberta. The feverish expansion in oil sands development is based on the untested assumption that mined landscapes can be recovered to something close to the pre-development ecosystem after mining is complete. Reclamation is the final step mining companies are required to complete before mine closure. Defined in Alberta as the “stabilization, contouring, maintenance, conditioning or reconstruction of the surface of land,” reclamation is an essential component of responsible oil sands development. However, an assessment of the current policies and practices governing oil sands mine reclamation reveals an alarming range of challenges, uncertainties and risks that deserve immediate attention and broader public discussion. This report explores these issues to help demonstrate what is fact and what is fiction about oil sands mine reclamation

    Visual search in ecological and non-ecological displays: Evidence for a non-monotonic effect of complexity on performance

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    Copyright @ 2013 PLoSThis article has been made available through the Brunel Open Access Publishing Fund.Considerable research has been carried out on visual search, with single or multiple targets. However, most studies have used artificial stimuli with low ecological validity. In addition, little is known about the effects of target complexity and expertise in visual search. Here, we investigate visual search in three conditions of complexity (detecting a king, detecting a check, and detecting a checkmate) with chess players of two levels of expertise (novices and club players). Results show that the influence of target complexity depends on level of structure of the visual display. Different functional relationships were found between artificial (random chess positions) and ecologically valid (game positions) stimuli: With artificial, but not with ecologically valid stimuli, a “pop out” effect was present when a target was visually more complex than distractors but could be captured by a memory chunk. This suggests that caution should be exercised when generalising from experiments using artificial stimuli with low ecological validity to real-life stimuli.This study is funded by Brunel University and the article is made available through the Brunel Open Access Publishing Fund

    A pan-African high-resolution drought index dataset

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    Droughts in Africa cause severe problems, such as crop failure, food shortages, famine, epidemics and even mass migration. To minimize the effects of drought on water and food security on Africa, a high-resolution drought dataset is essential to establish robust drought hazard probabilities and to assess drought vulnerability considering a multi- and cross-sectional perspective that includes crops, hydrological systems, rangeland and environmental systems. Such assessments are essential for policymakers, their advisors and other stakeholders to respond to the pressing humanitarian issues caused by these environmental hazards. In this study, a high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset is presented to support these assessments. We compute historical SPEI data based on Climate Hazards group InfraRed Precipitation with Station data (CHIRPS) precipitation estimates and Global Land Evaporation Amsterdam Model (GLEAM) potential evaporation estimates. The high-resolution SPEI dataset (SPEI-HR) presented here spans from 1981 to 2016 (36 years) with 5 km spatial resolution over the whole of Africa. To facilitate the diagnosis of droughts of different durations, accumulation periods from 1 to 48 months are provided. The quality of the resulting dataset was compared with coarse-resolution SPEI based on Climatic Research Unit (CRU) Time Series (TS) datasets, Normalized Difference Vegetation Index (NDVI) calculated from the Global Inventory Monitoring and Modeling System (GIMMS) project and root zone soil moisture modelled by GLEAM. Agreement found between coarse-resolution SPEI from CRU TS (SPEI-CRU) and the developed SPEI-HR provides confidence in the estimation of temporal and spatial variability of droughts in Africa with SPEI-HR. In addition, agreement of SPEI-HR versus NDVI and root zone soil moisture – with an average correlation coefficient (R) of 0.54 and 0.77, respectively – further implies that SPEI-HR can provide valuable information for the study of drought-related processes and societal impacts at sub-basin and district scales in Africa. The dataset is archived in Centre for Environmental Data Analysis (CEDA) via the following link: https://doi.org/10.5285/bbdfd09a04304158b366777eba0d2aeb (Peng et al., 2019a)

    A STATIC TEST FACILITY FOR THE STUDY OF DEPOSIT FOULING ON STEAM TURBINE BLADES

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    ABSTRACT For several decades it has been recognised that deposition on the surfaces of steam turbine blades during operation can result in significant loss in thermal performance and, in some cases, a large reduction in the steam swallowing capacity. One principal cause of deposit fouling on HP turbines is copper, although other elements, for example silicon, can also be problematic. Copper is initially corroded from condenser and feedheater tubes by the water which then contaminates the inner surfaces of the boiler as the water is evaporated. The steam from the boiler becomes contaminated with copper oxides as a result of the copper fouling inside the boiler. The solubility of copper compounds in steam is a strong function of pressure. As the steam expands through the turbine and pressure reduces, the copper oxides deposit out onto the blade surfaces, roughening them and resulting in loss of performanc

    A microstructured fiber source of photon pairs at widely separated wavelengths

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    We demonstrate a source of photon pairs with widely separated wavelengths, 810 nm and 1548 nm, generated through spontaneous four-wave mixing in a microstructured fiber. The second-order auto-correlation function g^{(2)}(0) was measured to confirm the non-classical nature of a heralded single photon source constructed from the fiber. The microstructured fiber presented herein has the interesting property of generating photon pairs with wavelengths suitable for a quantum repeater able to link free-space channels with fiber channels, as well as for a high quality telecommunication wavelength heralded single photon source. It also has the advantage of straightforward coupling into optical fiber. These reasons make this photon pair source particularly interesting for long distance quantum communication.Comment: 3 pages, 3 figures. Published versio
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