933 resultados para system models


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Unified Modeling Language (UML) is the most comprehensive and widely accepted object-oriented modeling language due to its multi-paradigm modeling capabilities and easy to use graphical notations, with strong international organizational support and industrial production quality tool support. However, there is a lack of precise definition of the semantics of individual UML notations as well as the relationships among multiple UML models, which often introduces incomplete and inconsistent problems for software designs in UML, especially for complex systems. Furthermore, there is a lack of methodologies to ensure a correct implementation from a given UML design. The purpose of this investigation is to verify and validate software designs in UML, and to provide dependability assurance for the realization of a UML design.^ In my research, an approach is proposed to transform UML diagrams into a semantic domain, which is a formal component-based framework. The framework I proposed consists of components and interactions through message passing, which are modeled by two-layer algebraic high-level nets and transformation rules respectively. In the transformation approach, class diagrams, state machine diagrams and activity diagrams are transformed into component models, and transformation rules are extracted from interaction diagrams. By applying transformation rules to component models, a (sub)system model of one or more scenarios can be constructed. Various techniques such as model checking, Petri net analysis techniques can be adopted to check if UML designs are complete or consistent. A new component called property parser was developed and merged into the tool SAM Parser, which realize (sub)system models automatically. The property parser generates and weaves runtime monitoring code into system implementations automatically for dependability assurance. The framework in the investigation is creative and flexible since it not only can be explored to verify and validate UML designs, but also provides an approach to build models for various scenarios. As a result of my research, several kinds of previous ignored behavioral inconsistencies can be detected.^

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While the robots gradually become a part of our daily lives, they already play vital roles in many critical operations. Some of these critical tasks include surgeries, battlefield operations, and tasks that take place in hazardous environments or distant locations such as space missions. ^ In most of these tasks, remotely controlled robots are used instead of autonomous robots. This special area of robotics is called teleoperation. Teleoperation systems must be reliable when used in critical tasks; hence, all of the subsystems must be dependable even under a subsystem or communication line failure. ^ These systems are categorized as unilateral or bilateral teleoperation. A special type of bilateral teleoperation is described as force-reflecting teleoperation, which is further investigated as limited- and unlimited-workspace teleoperation. ^ Teleoperation systems configured in this study are tested both in numerical simulations and experiments. A new method, Virtual Rapid Robot Prototyping, is introduced to create system models rapidly and accurately. This method is then extended to configure experimental setups with actual master systems working with system models of the slave robots accompanied with virtual reality screens as well as the actual slaves. Fault-tolerant design and modeling of the master and slave systems are also addressed at different levels to prevent subsystem failure. ^ Teleoperation controllers are designed to compensate for instabilities due to communication time delays. Modifications to the existing controllers are proposed to configure a controller that is reliable in communication line failures. Position/force controllers are also introduced for master and/or slave robots. Later, controller architecture changes are discussed in order to make these controllers dependable even in systems experiencing communication problems. ^ The customary and proposed controllers for teleoperation systems are tested in numerical simulations on single- and multi-DOF teleoperation systems. Experimental studies are then conducted on seven different systems that included limited- and unlimited-workspace teleoperation to verify and improve simulation studies. ^ Experiments of the proposed controllers were successful relative to the customary controllers. Overall, by employing the fault-tolerance features and the proposed controllers, a more reliable teleoperation system is possible to design and configure which allows these systems to be used in a wider range of critical missions. ^

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In - Service Management Concepts: Implications for Hospitality Management – a study by K. Michael Haywood, Associate Professor, School of Hotel and Food Administration, University of Guelph, Ontario, Canada, Associate Professor Haywood initially proffers: “The study and application of hospitality management has progressed on its own for many years; however, managers are not immune to the knowledge gained from study of other service industries. The author synthesizes what is happening in the area of service management, looks at its relevance to hospitality management, and identifies a few important implications of service management for hospitality managers.” The author draws a distinction between non-denominated service management, and service management as it applies to the hospitality industry. This is done to make an apparent comparison, as many people would assume the two are one in the same. They are not, and the contrast works well here. “While much of what we already know about effective management applies to service industries, some of the traditional concepts of management are inadequate in solving the problems faced by service businesses,” Haywood points out. “If a body of knowledge to be known as service management already exists, or is being developed, where does it fit relative to hospitality management,” Haywood asks. According to John Bateson, Testing a Conceptual Framework for Consumer Service Marketing, there are four criteria used to judge service management. Haywood details these for you, the reader, by way of citation. Haywood points to the difficulty in pin-pointing the intangibles that underpin the service industry. Since service is a concept rather than a touchable good, such as inventory, problems arise for both the organization and the client. Haywood points to a classic study of four service industries in France to illustrate the problems, although no realistic suggestions address the issues. “Over the past few years a variety of system models have been developed to explain the service process, that is, how the service is designed, produced, delivered, and consumed,” Haywood offers. These models are depicted in Appendices A-E. In offering perspectives on how the hospitality industry can gain from the experiences of service management, Haywood observes: “Service management places particular emphasis on a strategic outlook. Hospitality firms would be wise to carefully examine how they are perceived in the marketplace vis-a-vis their service concept, position, competitive situation, and management’s leadership abilities.” “Learning from the experiences of other service firms can help keep a company on track, that is, providing needed and valued services,” he closes the thought.

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Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. ^ There are two issues in using HLPNs—modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. ^ For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. ^ For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. ^ The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.^

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While the robots gradually become a part of our daily lives, they already play vital roles in many critical operations. Some of these critical tasks include surgeries, battlefield operations, and tasks that take place in hazardous environments or distant locations such as space missions. In most of these tasks, remotely controlled robots are used instead of autonomous robots. This special area of robotics is called teleoperation. Teleoperation systems must be reliable when used in critical tasks; hence, all of the subsystems must be dependable even under a subsystem or communication line failure. These systems are categorized as unilateral or bilateral teleoperation. A special type of bilateral teleoperation is described as force-reflecting teleoperation, which is further investigated as limited- and unlimited-workspace teleoperation. Teleoperation systems configured in this study are tested both in numerical simulations and experiments. A new method, Virtual Rapid Robot Prototyping, is introduced to create system models rapidly and accurately. This method is then extended to configure experimental setups with actual master systems working with system models of the slave robots accompanied with virtual reality screens as well as the actual slaves. Fault-tolerant design and modeling of the master and slave systems are also addressed at different levels to prevent subsystem failure. Teleoperation controllers are designed to compensate for instabilities due to communication time delays. Modifications to the existing controllers are proposed to configure a controller that is reliable in communication line failures. Position/force controllers are also introduced for master and/or slave robots. Later, controller architecture changes are discussed in order to make these controllers dependable even in systems experiencing communication problems. The customary and proposed controllers for teleoperation systems are tested in numerical simulations on single- and multi-DOF teleoperation systems. Experimental studies are then conducted on seven different systems that included limited- and unlimited-workspace teleoperation to verify and improve simulation studies. Experiments of the proposed controllers were successful relative to the customary controllers. Overall, by employing the fault-tolerance features and the proposed controllers, a more reliable teleoperation system is possible to design and configure which allows these systems to be used in a wider range of critical missions.

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Peatland ecosystems store about 500-600 Pg of organic carbon, largely accumulated since the last glaciation. Whether they continue to sequester carbon or release it as greenhouse gases, perhaps in large amounts, is important in Earth's temperature dynamics. Given both ages and depths of numerous dated sample peatlands, their rate of carbon sequestration can be estimated throughout the Holocene. Here we use average values for carbon content per unit volume, the geographical extent of peatlands, and ecological models of peatland establishment and growth, to reconstruct the time-trajectory of peatland carbon sequestration in North America and project it into the future. Peatlands there contain ~163 Pg of carbon. Ignoring effects of climate change and other major anthropogenic disturbances, the rate of carbon accumulation is projected to decline slowly over millennia as reduced net carbon accumulation in existing peatlands is largely balanced by new peatland establishment. Peatlands are one of few long-term terrestrial carbon sinks, probably important for global carbon regulation in future generations. This study contributes to a better understanding of these ecosystems that will assist their inclusion in earth-system models, and therefore their management to maintain carbon storage during climate change.

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Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. There are two issues in using HLPNs - modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.

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Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the "unit of accounting" in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size - picophytoplankton (0.5-2 µm in diameter), nanophytoplankton (2-20 µm) and microphytoplankton (20-50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield - 0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.

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The Greater Himalayan leucogranites are a discontinuous suite of intrusions emplaced in a thickened crust during the Miocene southward ductile extrusion of the Himalayan metamorphic core. Melt-induced weakening is thought to have played a critical role in strain localization that facilitated the extrusion. Recent advancements in centrifuge analogue modelling techniques allow for the replication of a broader range of crustal deformation behaviors, enhancing our understanding of large hot orogens. Polydimethylsiloxane (PDMS) is commonly used in centrifuge experiments to model weak melt zones. Difficulties in handling PDMS had, until now, limited its emplacement in models prior to any deformation. A new modelling technique has been developed where PDMS is emplaced into models that have been subjected to some shortening. This technique aims to better understand the effects of melt on strain localization and potential decoupling between structural levels within an evolving orogenic system. Models are subjected to an early stage of shortening, followed by the introduction of PDMS, and then a final stage of shortening. Theoretical percentages of partial melt and their effect on rock strength are considered when adding a specific percentage of PDMS in each model. Due to the limited size of the models, only PDMS sheets of 3 mm thickness were used, which varied in length and width. Within undeformed packages, minimal surface and internal deformation occurred when PDMS is emplaced in the lower layer of the model, showing a vertical volume increase of ~20% within the package; whereas the emplacement of PDMS into the middle layer showed internal dragging of the middle laminations into the lower layer and a vertical volume increase ~30%. Emplacement of PDMS results in ~7% shortening for undeformed and deformed models. Deformed models undergo ~20% additional shortening after two rounds of deformation. Strain localization and decoupling between units occur in deformed models where the degree of deformation changes based on the amount of partial melt present. Surface deformation visible by the formation of a bulge, mode 1 extension cracks and varying surface strain ellipses varies depending if PDMS is present. Better control during emplacement is exhibited when PDMS is added into cooler models, resulting in reduced internal deformation within the middle layer.

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Muddy floods occur when rainfall generates runoff on agricultural land, detaching and transporting sediment into the surrounding natural and built environment. In the Belgian Loess Belt, muddy floods occur regularly and lead to considerable economic costs associated with damage to property and infrastructure. Mitigation measures designed to manage the problem have been tested in a pilot area within Flanders and were found to be cost-effective within three years. This study assesses whether these mitigation measures will remain effective under a changing climate. To test this, the Water Erosion Prediction Project (WEPP) model was used to examine muddy flooding diagnostics (precipitation, runoff, soil loss and sediment yield) for a case study hillslope in Flanders where grass buffer strips are currently used as a mitigation measure. The model was run for present day conditions and then under 33 future site-specific climate scenarios. These future scenarios were generated from three earth system models driven by four representative concentration pathways and downscaled using quantile mapping and the weather generator CLIGEN. Results reveal that under the majority of future scenarios, muddy flooding diagnostics are projected to increase, mostly as a consequence of large scale precipitation events rather than mean changes. The magnitude of muddy flood events for a given return period is also generally projected to increase. These findings indicate that present day mitigation measures may have a reduced capacity to manage muddy flooding given the changes imposed by a warming climate with an enhanced hydrological cycle. Revisions to the design of existing mitigation measures within existing policy frameworks are considered the most effective way to account for the impacts of climate change in future mitigation planning. 

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The aim of this report is to give an overview of the results of Work Package 5 “Engineering Tools”. In this workpackage numerical tools have been developed for all relevant CHCP systems in the PolySMART demonstration projects (WP3). First, existing simulation platforms have been described and specific characteristics have been identified. Several different simulation platforms are in principle appropriate for the needs in the PolySMART project. The result is an evaluation of available simulation and engineering tools for CHCP simulation, and an agreement upon a common simulation environment within the PolySMART project. Next, numerical models for components in the demonstration projects have been developed. These models are available to the PolySMART consortium. Of all modeled components an overall and detailed working principle is formulated, including a parameter list and (in some cases) a control strategy. Finally, for four CHCP systems in the PolySMART project, a system simulation model has been developed. For each system simulation a separate deliverable is available (D5.5b to D5.5e) These deliverables replace deliverable 5.4 ‘system models’. The numerical models for components and systems developed in the Polysmart project form a valuable basis for the component development and optimisation and for the system optimisation, both within and outside the project. Developers and researchers interested in more information about specific models can refer to the institutes and contact persons involved in the model development. 

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Power system engineers face a double challenge: to operate electric power systems within narrow stability and security margins, and to maintain high reliability. There is an acute need to better understand the dynamic nature of power systems in order to be prepared for critical situations as they arise. Innovative measurement tools, such as phasor measurement units, can capture not only the slow variation of the voltages and currents but also the underlying oscillations in a power system. Such dynamic data accessibility provides us a strong motivation and a useful tool to explore dynamic-data driven applications in power systems. To fulfill this goal, this dissertation focuses on the following three areas: Developing accurate dynamic load models and updating variable parameters based on the measurement data, applying advanced nonlinear filtering concepts and technologies to real-time identification of power system models, and addressing computational issues by implementing the balanced truncation method. By obtaining more realistic system models, together with timely updated parameters and stochastic influence consideration, we can have an accurate portrait of the ongoing phenomena in an electrical power system. Hence we can further improve state estimation, stability analysis and real-time operation.

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Innate immunity now occupies a central role in immunology. However, artificial immune system models have largely been inspired by adaptive not innate immunity. This paper reviews the biological principles and properties of innate immunity and, adopting a conceptual framework, asks how these can be incorporated into artificial models. The aim is to outline a meta-framework for models of innate immunity.

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Innate immunity now occupies a central role in immunology. However, artificial immune system models have largely been inspired by adaptive not innate immunity. This paper reviews the biological principles and properties of innate immunity and, adopting a conceptual framework, asks how these can be incorporated into artificial models. The aim is to outline a meta-framework for models of innate immunity.

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In this thesis, we present a quantitative approach using probabilistic verification techniques for the analysis of reliability, availability, maintainability, and safety (RAMS) properties of satellite systems. The subject of our research is satellites used in mission critical industrial applications. A strong case for using probabilistic model checking to support RAMS analysis of satellite systems is made by our verification results. This study is intended to build a foundation to help reliability engineers with a basic background in model checking to apply probabilistic model checking to small satellite systems. We make two major contributions. One of these is the approach of RAMS analysis to satellite systems. In the past, RAMS analysis has been extensively applied to the field of electrical and electronics engineering. It allows system designers and reliability engineers to predict the likelihood of failures from the indication of historical or current operational data. There is a high potential for the application of RAMS analysis in the field of space science and engineering. However, there is a lack of standardisation and suitable procedures for the correct study of RAMS characteristics for satellite systems. This thesis considers the promising application of RAMS analysis to the case of satellite design, use, and maintenance, focusing on its system segments. Data collection and verification procedures are discussed, and a number of considerations are also presented on how to predict the probability of failure. Our second contribution is leveraging the power of probabilistic model checking to analyse satellite systems. We present techniques for analysing satellite systems that differ from the more common quantitative approaches based on traditional simulation and testing. These techniques have not been applied in this context before. We present the use of probabilistic techniques via a suite of detailed examples, together with their analysis. Our presentation is done in an incremental manner: in terms of complexity of application domains and system models, and a detailed PRISM model of each scenario. We also provide results from practical work together with a discussion about future improvements.