900 resultados para system dynamics analysis


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The generating functional method is employed to investigate the synchronous dynamics of Boolean networks, providing an exact result for the system dynamics via a set of macroscopic order parameters. The topology of the networks studied and its constituent Boolean functions represent the system's quenched disorder and are sampled from a given distribution. The framework accommodates a variety of topologies and Boolean function distributions and can be used to study both the noisy and noiseless regimes; it enables one to calculate correlation functions at different times that are inaccessible via commonly used approximations. It is also used to determine conditions for the annealed approximation to be valid, explore phases of the system under different levels of noise and obtain results for models with strong memory effects, where existing approximations break down. Links between Boolean networks and general Boolean formulas are identified and results common to both system types are highlighted. © 2012 Copyright Taylor and Francis Group, LLC.

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Elementary conformational changes of the backbone of a 21-residue peptide A5(A3RA)3A are studied using molecular dynamics simulations in explicit water. The processes of the conformational transitions and the regimes of stationary fluctuations between them are investigated using minimal perturbations of the system. The perturbations consist of a few degrees rotation of the velocity of one of the systems' atoms and keep the system on the same energy surface. It is found that (i) the system dynamics is insignificantly changed by the perturbations in the regimes between the transitions; (ii) it is very sensitive to the perturbations just before the transitions that prevents the peptide from making the transitions; and (iii) the perturbation of any atom of the system, including distant water molecules is equally effective in preventing the transition. The latter implies strongly collective dynamics of the peptide and water during the transitions.

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Simulation is an effective method for improving supply chain performance. However, there is limited advice available to assist practitioners in selecting the most appropriate method for a given problem. Much of the advice that does exist relies on custom and practice rather than a rigorous conceptual or empirical analysis. An analysis of the different modelling techniques applied in the supply chain domain was conducted, and the three main approaches to simulation used were identified; these are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). This research has examined these approaches in two stages. Firstly, a first principles analysis was carried out in order to challenge the received wisdom about their strengths and weaknesses and a series of propositions were developed from this initial analysis. The second stage was to use the case study approach to test these propositions and to provide further empirical evidence to support their comparison. The contributions of this research are both in terms of knowledge and practice. In terms of knowledge, this research is the first holistic cross paradigm comparison of the three main approaches in the supply chain domain. Case studies have involved building ‘back to back’ models of the same supply chain problem using SD and a discrete approach (either DES or ABM). This has led to contributions concerning the limitations of applying SD to operational problem types. SD has also been found to have risks when applied to strategic and policy problems. Discrete methods have been found to have potential for exploring strategic problem types. It has been found that discrete simulation methods can model material and information feedback successfully. Further insights have been gained into the relationship between modelling purpose and modelling approach. In terms of practice, the findings have been summarised in the form of a framework linking modelling purpose, problem characteristics and simulation approach.

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Visual field assessment is a core component of glaucoma diagnosis and monitoring, and the Standard Automated Perimetry (SAP) test is considered up until this moment, the gold standard of visual field assessment. Although SAP is a subjective assessment and has many pitfalls, it is being constantly used in the diagnosis of visual field loss in glaucoma. Multifocal visual evoked potential (mfVEP) is a newly introduced method used for visual field assessment objectively. Several analysis protocols have been tested to identify early visual field losses in glaucoma patients using the mfVEP technique, some were successful in detection of field defects, which were comparable to the standard SAP visual field assessment, and others were not very informative and needed more adjustment and research work. In this study, we implemented a novel analysis approach and evaluated its validity and whether it could be used effectively for early detection of visual field defects in glaucoma. OBJECTIVES: The purpose of this study is to examine the effectiveness of a new analysis method in the Multi-Focal Visual Evoked Potential (mfVEP) when it is used for the objective assessment of the visual field in glaucoma patients, compared to the gold standard technique. METHODS: 3 groups were tested in this study; normal controls (38 eyes), glaucoma patients (36 eyes) and glaucoma suspect patients (38 eyes). All subjects had a two standard Humphrey visual field HFA test 24-2 and a single mfVEP test undertaken in one session. Analysis of the mfVEP results was done using the new analysis protocol; the Hemifield Sector Analysis HSA protocol. Analysis of the HFA was done using the standard grading system. RESULTS: Analysis of mfVEP results showed that there was a statistically significant difference between the 3 groups in the mean signal to noise ratio SNR (ANOVA p<0.001 with a 95% CI). The difference between superior and inferior hemispheres in all subjects were all statistically significant in the glaucoma patient group 11/11 sectors (t-test p<0.001), partially significant 5/11 (t-test p<0.01) and no statistical difference between most sectors in normal group (only 1/11 was significant) (t-test p<0.9). sensitivity and specificity of the HAS protocol in detecting glaucoma was 97% and 86% respectively, while for glaucoma suspect were 89% and 79%. DISCUSSION: The results showed that the new analysis protocol was able to confirm already existing field defects detected by standard HFA, was able to differentiate between the 3 study groups with a clear distinction between normal and patients with suspected glaucoma; however the distinction between normal and glaucoma patients was especially clear and significant. CONCLUSION: The new HSA protocol used in the mfVEP testing can be used to detect glaucomatous visual field defects in both glaucoma and glaucoma suspect patient. Using this protocol can provide information about focal visual field differences across the horizontal midline, which can be utilized to differentiate between glaucoma and normal subjects. Sensitivity and specificity of the mfVEP test showed very promising results and correlated with other anatomical changes in glaucoma field loss.

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Several levels of complexity are available for modelling of wastewater treatment plants. Modelling local effects rely on computational fluid dynamics (CFD) approaches whereas activated sludge models (ASM) represent the global methodology. By applying both modelling approaches to pilot plant and full scale systems, this paper evaluates the value of each method and especially their potential combination. Model structure identification for ASM is discussed based on a full-scale closed loop oxidation ditch modelling. It is illustrated how and for what circumstances information obtained via CFD (computational fluid dynamics) analysis, residence time distribution (RTD) and other experimental means can be used. Furthermore, CFD analysis of the multiphase flow mechanisms is employed to obtain a correct description of the oxygenation capacity of the system studied, including an easy implementation of this information in the classical ASM modelling (e.g. oxygen transfer). The combination of CFD and activated sludge modelling of wastewater treatment processes is applied to three reactor configurations, a perfectly mixed reactor, a pilot scale activated sludge basin (ASB) and a real scale ASB. The application of the biological models to the CFD model is validated against experimentation for the pilot scale ASB and against a classical global ASM model response. A first step in the evaluation of the potential of the combined CFD-ASM model is performed using a full scale oxidation ditch system as testing scenario.

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Mobile messaging is an integral and vital part of the mobile industry and contributes significantly to worldwide total mobile service revenues. In today’s competitive world, differentiation is a significant factor in the success of the business communication. SMS (Short Message Service) provides a powerful vehicle for service differentiation. What is missing, however, is the availability of personalized SMS messages. In particular, the exploitation of user profile information allows a selection and content delivery that meets preferences and interests for the individual. Personalization of mobile messages is important in today’s service-oriented society, and has proven to be crucial for the acceptance of services provided by the mobile telecommunication networks. In this paper we focus on user profile description and the mechanism for delivering the relevant information to the mobile user in accordance with his/her profile.

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CONCLUSIONS: The new HSA protocol used in the mfVEP testing can be applied to detect glaucomatous visual field defects in both glaucoma and glaucoma suspect patients. Using this protocol can provide information about focal visual field differences across the horizontal midline, which can be utilized to differentiate between glaucoma and normal subjects. Sensitivity and specificity of the mfVEP test showed very promising results and correlated with other anatomical changes in glaucoma field loss. PURPOSE: Multifocal visual evoked potential (mfVEP) is a newly introduced method used for objective visual field assessment. Several analysis protocols have been tested to identify early visual field losses in glaucoma patients using the mfVEP technique, some were successful in detection of field defects, which were comparable to the standard automated perimetry (SAP) visual field assessment, and others were not very informative and needed more adjustment and research work. In this study we implemented a novel analysis approach and evaluated its validity and whether it could be used effectively for early detection of visual field defects in glaucoma. METHODS: Three groups were tested in this study; normal controls (38 eyes), glaucoma patients (36 eyes) and glaucoma suspect patients (38 eyes). All subjects had a two standard Humphrey field analyzer (HFA) test 24-2 and a single mfVEP test undertaken in one session. Analysis of the mfVEP results was done using the new analysis protocol; the hemifield sector analysis (HSA) protocol. Analysis of the HFA was done using the standard grading system. RESULTS: Analysis of mfVEP results showed that there was a statistically significant difference between the three groups in the mean signal to noise ratio (ANOVA test, p < 0.001 with a 95% confidence interval). The difference between superior and inferior hemispheres in all subjects were statistically significant in the glaucoma patient group in all 11 sectors (t-test, p < 0.001), partially significant in 5 / 11 (t-test, p < 0.01), and no statistical difference in most sectors of the normal group (1 / 11 sectors was significant, t-test, p < 0.9). Sensitivity and specificity of the HSA protocol in detecting glaucoma was 97% and 86%, respectively, and for glaucoma suspect patients the values were 89% and 79%, respectively.

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This dissertation delivers a framework to diagnose the Bull-Whip Effect (BWE) in supply chains and then identify methods to minimize it. Such a framework is needed because in spite of the significant amount of literature discussing the bull-whip effect, many companies continue to experience the wide variations in demand that are indicative of the bull-whip effect. While the theory and knowledge of the bull-whip effect is well established, there still is the lack of an engineering framework and method to systematically identify the problem, diagnose its causes, and identify remedies. ^ The present work seeks to fill this gap by providing a holistic, systems perspective to bull-whip identification and diagnosis. The framework employs the SCOR reference model to examine the supply chain processes with a baseline measure of demand amplification. Then, research of the supply chain structural and behavioral features is conducted by means of the system dynamics modeling method. ^ The contribution of the diagnostic framework, is called Demand Amplification Protocol (DAMP), relies not only on the improvement of existent methods but also contributes with original developments introduced to accomplish successful diagnosis. DAMP contributes a comprehensive methodology that captures the dynamic complexities of supply chain processes. The method also contributes a BWE measurement method that is suitable for actual supply chains because of its low data requirements, and introduces a BWE scorecard for relating established causes to a central BWE metric. In addition, the dissertation makes a methodological contribution to the analysis of system dynamic models with a technique for statistical screening called SS-Opt, which determines the inputs with the greatest impact on the bull-whip effect by means of perturbation analysis and subsequent multivariate optimization. The dissertation describes the implementation of the DAMP framework in an actual case study that exposes the approach, analysis, results and conclusions. The case study suggests a balanced solution between costs and demand amplification can better serve both firms and supply chain interests. Insights pinpoint to supplier network redesign, postponement in manufacturing operations and collaborative forecasting agreements with main distributors.^

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Environmentally conscious construction has received a significant amount of research attention during the last decades. Even though construction literature is rich in studies that emphasize the importance of environmental impact during the construction phase, most of the previous studies failed to combine environmental analysis with other project performance criteria in construction. This is mainly because most of the studies have overlooked the multi-objective nature of construction projects. In order to achieve environmentally conscious construction, multi-objectives and their relationships need to be successfully analyzed in the complex construction environment. The complex construction system is composed of changing project conditions that have an impact on the relationship between time, cost and environmental impact (TCEI) of construction operations. Yet, this impact is still unknown by construction professionals. Studying this impact is vital to fulfill multiple project objectives and achieve environmentally conscious construction. This research proposes an analytical framework to analyze the impact of changing project conditions on the relationship of TCEI. This study includes green house gas (GHG) emissions as an environmental impact category. The methodology utilizes multi-agent systems, multi-objective optimization, analytical network process, and system dynamics tools to study the relationships of TCEI and support decision-making under the influence of project conditions. Life cycle assessment (LCA) is applied to the evaluation of environmental impact in terms of GHG. The mixed method approach allowed for the collection and analysis of qualitative and quantitative data. Structured interviews of professionals in the highway construction field were conducted to gain their perspectives in decision-making under the influence of certain project conditions, while the quantitative data were collected from the Florida Department of Transportation (FDOT) for highway resurfacing projects. The data collected were used to test the framework. The framework yielded statistically significant results in simulating project conditions and optimizing TCEI. The results showed that the change in project conditions had a significant impact on the TCEI optimal solutions. The correlation between TCEI suggested that they affected each other positively, but in different strengths. The findings of the study will assist contractors to visualize the impact of their decision on the relationship of TCEI.

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This paper describes the implementation of a novel mitigation approach and subsequent adaptive management, designed to reduce the transfer of fine sediment in Glaisdale Beck; a small upland catchment in the UK. Hydro-meteorological and suspended sediment datasets are collected over a two year period spanning pre- and post-diversion periods in order to assess the impact of the channel reconfiguration scheme on the fluvial suspended sediment dynamics. Analysis of the river response demonstrates that the fluvial sediment system has become more restrictive with reduced fine sediment transfer. This is characterised by reductions in flow-weighted mean suspended sediment concentrations from 77.93 mg/l prior to mitigation, to 74.36 mg/l following the diversion. A Mann-Whitney U test found statistically significant differences (p < 0.001) between the pre- and post-monitoring median SSCs. Whilst application of one-way analysis of covariance (ANCOVA) on the coefficients of sediment rating curves developed before and after the diversion found statistically significant differences (p < 0.001), with both Log a and b coefficients becoming smaller following the diversion. Non-parametric analysis indicates a reduction in residuals through time (p < 0.001), with the developed LOWESS model over-predicting sediment concentrations as the channel stabilises. However, the channel is continuing to adjust to the reconfigured morphology, with evidence of a headward propagating knickpoint which has migrated 120 m at an exponentially decreasing rate over the last 7 years since diversion. The study demonstrates that channel reconfiguration can be effective in mitigating fine sediment flux in upland streams but the full value of this may take many years to achieve whilst the fluvial system, slowly readjusts.

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Due to high-speed rotation, the problems about rotor mechanics and dynamics for outer rotor high-speed machine are more serious than conventional ones, in view of above problems the mechanical and dynamics analysis for an outer rotor high-speed permanent magnet claw pole motor are carried out. The rotor stress analytical calculation model was derived, then the stress distribution is calculated by finite element method also, which is coincided with that calculated by analytical model. In addition, the stress distribution of outer rotor yoke and PMs considering centrifugal force and temperature effect has been calculated, some influence factors on rotor stress distribution have been analyzed such as pole-arc coefficient and speed. The rotor natural frequency and critical speed were calculated by vibration mode analysis, and its dynamics characteristics influenced by gyroscope effect were analyzed based on Campbell diagram. Based on the analysis results above an outer rotor permanent magnet high-speed claw pole motor is design and verified.

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Globally, the current state of freshwater resource management is insufficient and impeding the chance at a sustainable future. Human interference within the natural hydrologic cycle is becoming dangerously irreversible and the need to redefine resource managerial approaches is imminent. This research involves the development of a coupled natural-human freshwater resource supply model using a System Dynamics approach. The model was applied to two case studies, Somalia, Africa and the Phoenix Active Management Area in Arizona, USA. It is suggested that System Dynamic modeling would be an invaluable tool for achieving sustainable freshwater resource management in individual watersheds. Through a series of thought experiments, a thorough understanding of the systems’ dynamic behaviors is obtainable for freshwater resource managers and policy-makers to examine various courses of action for alleviating freshwater supply concerns. This thesis reviews the model, its development and an analysis of several thought experiments applied to the case studies.

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A generalized physicochemical model of the response of marine organisms' calcifying fluids to CO2-induced ocean acidification is proposed. The model is based upon the hypothesis that some marine calcifiers induce calcification by elevating pH, and thus Omega aragonite, of their calcifying fluid by removing protons (H+). The model is explored through two end-member scenarios: one in which a fixed number of H+ is removed from their calcifying fluid, regardless of atmospheric pCO2, and another in which a fixed external-internal proton ratio ([H+]E/[H+]I) is maintained. The model is able to generate the full range of calcification response patterns observed in prior ocean acidification experiments and is consistent with the assertion that organisms' calcification response to ocean acidification is more negative for marine calcifiers that exert weaker control over their calcifying fluid pH. The model is empirically evaluated for the temperate scleractinian coral Astrangia poculata with in situ pH microelectrode measurements of the coral's calcifying fluid under control and acidified conditions. These measurements reveal that (1) the pH of the coral's calcifying fluid is substantially elevated relative to its external seawater under both control and acidified conditions, (2) the coral's [H+]E/[H+]I remains constant under control and acidified conditions, and (3) the coral removes fewer H+ from its calcifying fluid under acidified conditions than under control conditions. Thus, the carbonate system dynamics of A. poculata's calcifying fluid appear to be most consistent with the fixed [H+]E/[H+]I end-member scenario. Similar microelectrode experiments performed on additional taxa are required to assess the model's general applicability.

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Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.