963 resultados para Complex Engineering Systems


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Free and open source software development is an alternative to traditional software engineering as an approach to the development of complex software systems. It is a way of developing software based on geographically distributed teams of volunteers without apparent central plan or traditional mechanisms of coordination. The purpose of this thesis is to summarize the current knowledge about free and open source software development and explore the ways on which further understanding on it could be gained. The results of research on the field as well as the research methods are introduced and discussed. Also adapting software process metrics to the context of free and open source software development is illustrated and the possibilities to utilize them as tools to validate other research are discussed.

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Any plan for decoupling growth from fossil fuel use needs to prioritise locally appropriate, integrated and multi-faceted outcomes. Such transitions can be highly complex, given the physical and institutional characteristics of existing electricity infrastructure as well as various financial, technical and practical challenges. This Chapter applies a whole systems perspective to developing decoupling solutions, reflecting on the Dutch Sustainable Technology Development Program and Townsville City (Queensland, Australia). Key aspects considered include the need for demonstrating outcomes to multiple stakeholders, using pilot projects with integrated monitoring and evaluation, fostering collaborative approaches to energy management, cultivating cultures of ‘learning by doing’, and seeking synergies across multiple agendas.

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Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

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Tank irrigation systems in the semiarid regions of India are discussed in this paper. To optimize the grain yield of rice, it is essential to start the agricultural operations in the second week of July so that favorable climatic conditions will prevail during flowering and yield formation stages. Because of low inflow during the initial few weeks of the crop season, often farmers are forced to delay planting until sufficient sowing rain and inflow have occurred or to adopt deficit irrigation during this period. The delayed start affects the grain yield, but will lead to an improved irrigation efficiency. A delayed start of agricultural operations with increased irrigation efficiency leads to the energy resources becoming critical during the peak requirement week, particularly those of female labor and animal power. This necessitates augmenting these resources during weeks of their peak use, either by reorganizing the traditional methods of cultivation or by importing from outside the system.

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We offer a technique, motivated by feedback control and specifically sliding mode control, for the simulation of differential-algebraic equations (DAEs) that describe common engineering systems such as constrained multibody mechanical structures and electric networks. Our algorithm exploits the basic results from sliding mode control theory to establish a simulation environment that then requires only the most primitive of numerical solvers. We circumvent the most important requisite for the conventionalsimulation of DAEs: the calculation of a set of consistent initial conditions. Our algorithm, which relies on the enforcement and occurrence of sliding mode, will ensure that the algebraic equation is satisfied by the dynamic system even for inconsistent initial conditions and for all time thereafter. [DOI:10.1115/1.4001904]

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Biomimetics involves transfer from one or more biological examples to a technical system. This study addresses four questions. What are the essential steps in a biomimetic process? What is transferred? How can the transferred knowledge be structured in a way useful for biologists and engineers? Which guidelines can be given to support transfer in biomimetic design processes? In order to identify the essential steps involved in carrying out biomimetics, several procedures found in the literature were summarized, and four essential steps that are common across these procedures were identified. For identification of mechanisms for transfer, 20 biomimetic examples were collected and modeled according to a model. of causality called the SAPPhIRE model. These examples were then analyzed for identifying the underlying similarity between each biological and corresponding analogue technical system. Based on the SAPPhIRE model, four levels of abstraction at which transfer takes place were identified. Taking into account similarity, the biomimetic examples were assigned to the appropriate levels of abstraction of transfer. Based on the essential steps and the levels of transfer, guidelines for supporting transfer in biomimetic design were proposed and evaluated using design experiments. The 20 biological and analogue technical systems that were analyzed were similar in the physical effects used and at the most abstract levels of description of their functionality, but they were the least similar at the lowest levels of abstraction: the parts involved. Transfer most often was carried out at the physical effect level of abstraction. Compared to a generic set of guidelines based on the literature, the proposed guidelines improved design performance by about 60%. Further, the SAPPhIRE model turned out to be a useful representation for modeling complex biological systems and their functionality. Databases of biological systems, which are structured using the SAPPhIRE model, have the potential to aid biomimetic concept generation.

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Modelling of city traffic involves capturing of all the dynamics that exist in real-time traffic. Probabilistic models and queuing theory have been used for mathematical representation of the traffic system. This paper proposes the concept of modelling the traffic system using bond graphs wherein traffic flow is based on energy conservation. The proposed modelling approach uses switched junctions to model complex traffic networks. This paper presents the modelling, simulation and experimental validation aspects.

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Uncertainties in complex dynamic systems play an important role in the prediction of a dynamic response in the mid- and high-frequency ranges. For distributed parameter systems, parametric uncertainties can be represented by random fields leading to stochastic partial differential equations. Over the past two decades, the spectral stochastic finite-element method has been developed to discretize the random fields and solve such problems. On the other hand, for deterministic distributed parameter linear dynamic systems, the spectral finite-element method has been developed to efficiently solve the problem in the frequency domain. In spite of the fact that both approaches use spectral decomposition (one for the random fields and the other for the dynamic displacement fields), very little overlap between them has been reported in literature. In this paper, these two spectral techniques are unified with the aim that the unified approach would outperform any of the spectral methods considered on their own. An exponential autocorrelation function for the random fields, a frequency-dependent stochastic element stiffness, and mass matrices are derived for the axial and bending vibration of rods. Closed-form exact expressions are derived by using the Karhunen-Loève expansion. Numerical examples are given to illustrate the unified spectral approach.

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Complex biological systems such as the human brain can be expected to be inherently nonlinear and hence difficult to model. Most of the previous studies on investigations of brain function have either used linear models or parametric nonlinear models. In this paper, we propose a novel application of a nonlinear measure of phase synchronization based on recurrences, correlation between probabilities of recurrence (CPR), to study seizures in the brain. The advantage of this nonparametric method is that it makes very few assumptions thus making it possible to investigate brain functioning in a data-driven way. We have demonstrated the utility of CPR measure for the study of phase synchronization in multichannel seizure EEG recorded from patients with global as well as focal epilepsy. For the case of global epilepsy, brain synchronization using thresholded CPR matrix of multichannel EEG signals showed clear differences in results obtained for epileptic seizure and pre-seizure. Brain headmaps obtained for seizure and preseizure cases provide meaningful insights about synchronization in the brain in those states. The headmap in the case of focal epilepsy clearly enables us to identify the focus of the epilepsy which provides certain diagnostic value. Comparative studies with linear correlation have shown that the nonlinear measure CPR outperforms the linear correlation measure. (C) 2014 Elsevier Ltd. All rights reserved.

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This paper proposes a novel experimental test procedure to estimate the reliability of structural dynamical systems under excitations specified via random process models. The samples of random excitations to be used in the test are modified by the addition of an artificial control force. An unbiased estimator for the reliability is derived based on measured ensemble of responses under these modified inputs based on the tenets of Girsanov transformation. The control force is selected so as to reduce the sampling variance of the estimator. The study observes that an acceptable choice for the control force can be made solely based on experimental techniques and the estimator for the reliability can be deduced without taking recourse to mathematical model for the structure under study. This permits the proposed procedure to be applied in the experimental study of time-variant reliability of complex structural systems that are difficult to model mathematically. Illustrative example consists of a multi-axes shake table study on bending-torsion coupled, geometrically non-linear, five-storey frame under uni/bi-axial, non-stationary, random base excitation. Copyright (c) 2014 John Wiley & Sons, Ltd.

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The Alliance for Coastal Technologies (ACT) Workshop "Making Oxygen Measurements Routine Like Temperature" was convened in St. Petersburg, Florida, January 4th - 6th, 2006. This event was sponsored by the University of South Florida (USF) College of Marine Science, an ACT partner institution and co-hosted by the Ocean Research Interactive Observatory Networks (ORION). Participants from researcldacademia, resource management, industry, and engineering sectors collaborated with the aim to foster ideas and information on how to make measuring dissolved oxygen a routine part of a coastal or open ocean observing system. Plans are in motion to develop large scale ocean observing systems as part of the US Integrated Ocean Observing System (100s; see http://ocean.us) and the NSF Ocean Observatory Initiative (001; see http://www.orionprogram.org/00I/default.hl). These systems will require biological and chemical sensors that can be deployed in large numbers, with high reliability, and for extended periods of time (years). It is also likely that the development cycle for new sensors is sufficiently long enough that completely new instruments, which operate on novel principles, cannot be developed before these complex observing systems will be deployed. The most likely path to development of robust, reliable, high endurance sensors in the near future is to move the current generation of sensors to a much greater degree of readiness. The ACT Oxygen Sensor Technology Evaluation demonstrated two important facts that are related to the need for sensors. There is a suite of commercially available sensors that can, in some circumstances, generate high quality data; however, the evaluation also showed that none of the sensors were able to generate high quality data in all circumstances for even one month time periods due to biofouling issues. Many groups are attempting to use oxygen sensors in large observing programs; however, there often seems to be limited communication between these groups and they often do not have access to sophisticated engineering resources. Instrument manufacturers also do not have sufficient resources to bring sensors, which are marketable, but of limited endurance or reliability, to a higher state of readiness. The goal of this ACT/ORION Oxygen Sensor Workshop was to bring together a group of experienced oceanographers who are now deploying oxygen sensors in extended arrays along with a core of experienced and interested academic and industrial engineers, and manufacturers. The intended direction for this workshop was for this group to exchange information accumulated through a variety of sensor deployments, examine failure mechanisms and explore a variety of potential solutions to these problems. One anticipated outcome was for there to be focused recommendations to funding agencies on development needs and potential solutions for 02 sensors. (pdf contains 19 pages)

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This dissertation is concerned with the problem of determining the dynamic characteristics of complicated engineering systems and structures from the measurements made during dynamic tests or natural excitations. Particular attention is given to the identification and modeling of the behavior of structural dynamic systems in the nonlinear hysteretic response regime. Once a model for the system has been identified, it is intended to use this model to assess the condition of the system and to predict the response to future excitations.

A new identification methodology based upon a generalization of the method of modal identification for multi-degree-of-freedom dynaimcal systems subjected to base motion is developed. The situation considered herein is that in which only the base input and the response of a small number of degrees-of-freedom of the system are measured. In this method, called the generalized modal identification method, the response is separated into "modes" which are analogous to those of a linear system. Both parametric and nonparametric models can be employed to extract the unknown nature, hysteretic or nonhysteretic, of the generalized restoring force for each mode.

In this study, a simple four-term nonparametric model is used first to provide a nonhysteretic estimate of the nonlinear stiffness and energy dissipation behavior. To extract the hysteretic nature of nonlinear systems, a two-parameter distributed element model is then employed. This model exploits the results of the nonparametric identification as an initial estimate for the model parameters. This approach greatly improves the convergence of the subsequent optimization process.

The capability of the new method is verified using simulated response data from a three-degree-of-freedom system. The new method is also applied to the analysis of response data obtained from the U.S.-Japan cooperative pseudo-dynamic test of a full-scale six-story steel-frame structure.

The new system identification method described has been found to be both accurate and computationally efficient. It is believed that it will provide a useful tool for the analysis of structural response data.

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The solution behavior of linear polymer chains is well understood, having been the subject of intense study throughout the previous century. As plastics have become ubiquitous in everyday life, polymer science has grown into a major field of study. The conformation of a polymer in solution depends on the molecular architecture and its interactions with the surroundings. Developments in synthetic techniques have led to the creation of precision-tailored polymeric materials with varied topologies and functionalities. In order to design materials with the desired properties, it is imperative to understand the relationships between polymer architecture and their conformation and behavior. To meet that need, this thesis investigates the conformation and self-assembly of three architecturally complex macromolecular systems with rich and varied behaviors driven by the resolution of intramolecular conflicts. First we describe the development of a robust and facile synthetic approach to reproducible bottlebrush polymers (Chapter 2). The method was used to produce homologous series of bottlebrush polymers with polynorbornene backbones, which revealed the effect of side-chain and backbone length on the overall conformation in both good and theta solvent conditions (Chapter 3). The side-chain conformation was obtained from a series of SANS experiments and determined to be indistinguishable from the behavior of free linear polymer chains. Using deuterium-labeled bottlebrushes, we were able for the first time to directly observe the backbone conformation of a bottlebrush polymer which showed self-avoiding walk behavior. Secondly, a series of SANS experiments was conducted on a homologous series of Side Group Liquid Crystalline Polymers (SGLCPs) in a perdeuterated small molecule liquid crystal (5CB). Monodomain, aligned, dilute samples of SGLCP-b-PS block copolymers were seen to self-assemble into complex micellar structures with mutually orthogonally oriented anisotropies at different length scales (Chapter 4). Finally, we present the results from the first scattering experiments on a set of fuel-soluble, associating telechelic polymers. We observed the formation of supramolecular aggregates in dilute (≤0.5wt%) solutions of telechelic polymers and determined that the choice of solvent has a significant effect on the strength of association and the size of the supramolecules (Chapter 5). A method was developed for the direct estimation of supramolecular aggregation number from SANS data. The insight into structure-property relationships obtained from this work will enable the more targeted development of these molecular architectures for their respective applications.

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Cancellation of interfering frequency-modulated (FM) signals is investigated with emphasis towards applications on the cellular telephone channel as an important example of a multiple access communications system. In order to fairly evaluate analog FM multiaccess systems with respect to more complex digital multiaccess systems, a serious attempt to mitigate interference in the FM systems must be made. Information-theoretic results in the field of interference channels are shown to motivate the estimation and subtraction of undesired interfering signals. This thesis briefly examines the relative optimality of the current FM techniques in known interference channels, before pursuing the estimation and subtracting of interfering FM signals.

The capture-effect phenomenon of FM reception is exploited to produce simple interference-cancelling receivers with a cross-coupled topology. The use of phase-locked loop receivers cross-coupled with amplitude-tracking loops to estimate the FM signals is explored. The theory and function of these cross-coupled phase-locked loop (CCPLL) interference cancellers are examined. New interference cancellers inspired by optimal estimation and the CCPLL topology are developed, resulting in simpler receivers than those in prior art. Signal acquisition and capture effects in these complex dynamical systems are explained using the relationship of the dynamical systems to adaptive noise cancellers.

FM interference-cancelling receivers are considered for increasing the frequency reuse in a cellular telephone system. Interference mitigation in the cellular environment is seen to require tracking of the desired signal during time intervals when it is not the strongest signal present. Use of interference cancelling in conjunction with dynamic frequency-allocation algorithms is viewed as a way of improving spectrum efficiency. Performance of interference cancellers indicates possibilities for greatly increased frequency reuse. The economics of receiver improvements in the cellular system is considered, including both the mobile subscriber equipment and the provider's tower (base station) equipment.

The thesis is divided into four major parts and a summary: the introduction, motivations for the use of interference cancellation, examination of the CCPLL interference canceller, and applications to the cellular channel. The parts are dependent on each other and are meant to be read as a whole.