WorldWideScience

Sample records for dynamic models incorporating

  1. Incorporating Social System Dynamics into the Food-Energy-Water System Resilience-Sustainability Modeling Process

    Science.gov (United States)

    Givens, J.; Padowski, J.; Malek, K.; Guzman, C.; Boll, J.; Adam, J. C.; Witinok-Huber, R.

    2017-12-01

    In the face of climate change and multi-scalar governance objectives, achieving resilience of food-energy-water (FEW) systems requires interdisciplinary approaches. Through coordinated modeling and management efforts, we study "Innovations in the Food-Energy-Water Nexus (INFEWS)" through a case-study in the Columbia River Basin. Previous research on FEW system management and resilience includes some attention to social dynamics (e.g., economic, governance); however, more research is needed to better address social science perspectives. Decisions ultimately taken in this river basin would occur among stakeholders encompassing various institutional power structures including multiple U.S. states, tribal lands, and sovereign nations. The social science lens draws attention to the incompatibility between the engineering definition of resilience (i.e., return to equilibrium or a singular stable state) and the ecological and social system realities, more explicit in the ecological interpretation of resilience (i.e., the ability of a system to move into a different, possibly more resilient state). Social science perspectives include but are not limited to differing views on resilience as normative, system persistence versus transformation, and system boundary issues. To expand understanding of resilience and objectives for complex and dynamic systems, concepts related to inequality, heterogeneity, power, agency, trust, values, culture, history, conflict, and system feedbacks must be more tightly integrated into FEW research. We identify gaps in knowledge and data, and the value and complexity of incorporating social components and processes into systems models. We posit that socio-biophysical system resilience modeling would address important complex, dynamic social relationships, including non-linear dynamics of social interactions, to offer an improved understanding of sustainable management in FEW systems. Conceptual modeling that is presented in our study, represents

  2. Incorporating human-water dynamics in a hyper-resolution land surface model

    Science.gov (United States)

    Vergopolan, N.; Chaney, N.; Wanders, N.; Sheffield, J.; Wood, E. F.

    2017-12-01

    The increasing demand for water, energy, and food is leading to unsustainable groundwater and surface water exploitation. As a result, the human interactions with the environment, through alteration of land and water resources dynamics, need to be reflected in hydrologic and land surface models (LSMs). Advancements in representing human-water dynamics still leave challenges related to the lack of water use data, water allocation algorithms, and modeling scales. This leads to an over-simplistic representation of human water use in large-scale models; this is in turn leads to an inability to capture extreme events signatures and to provide reliable information at stakeholder-level spatial scales. The emergence of hyper-resolution models allows one to address these challenges by simulating the hydrological processes and interactions with the human impacts at field scales. We integrated human-water dynamics into HydroBlocks - a hyper-resolution, field-scale resolving LSM. HydroBlocks explicitly solves the field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs); and its HRU-based model parallelization allows computationally efficient long-term simulations as well as ensemble predictions. The implemented human-water dynamics include groundwater and surface water abstraction to meet agricultural, domestic and industrial water demands. Furthermore, a supply-demand water allocation scheme based on relative costs helps to determine sectoral water use requirements and tradeoffs. A set of HydroBlocks simulations over the Midwest United States (daily, at 30-m spatial resolution for 30 years) are used to quantify the irrigation impacts on water availability. The model captures large reductions in total soil moisture and water table levels, as well as spatiotemporal changes in evapotranspiration and runoff peaks, with their intensity related to the adopted water management strategy. By incorporating human-water dynamics in

  3. Incorporation of a Wind Generator Model into a Dynamic Power Flow Analysis

    Directory of Open Access Journals (Sweden)

    Angeles-Camacho C.

    2011-07-01

    Full Text Available Wind energy is nowadays one of the most cost-effective and practical options for electric generation from renewable resources. However, increased penetration of wind generation causes the power networks to be more depend on, and vulnerable to, the varying wind speed. Modeling is a tool which can provide valuable information about the interaction between wind farms and the power network to which they are connected. This paper develops a realistic characterization of a wind generator. The wind generator model is incorporated into an algorithm to investigate its contribution to the stability of the power network in the time domain. The tool obtained is termed dynamic power flow. The wind generator model takes on account the wind speed and the reactive power consumption by induction generators. Dynamic power flow analysis is carried-out using real wind data at 10-minute time intervals collected for one meteorological station. The generation injected at one point into the network provides active power locally and is found to reduce global power losses. However, the power supplied is time-varying and causes fluctuations in voltage magnitude and power fl ows in transmission lines.

  4. Global dynamics of a PDE model for aedes aegypti mosquitoe incorporating female sexual preference

    KAUST Repository

    Parshad, Rana

    2011-01-01

    In this paper we study the long time dynamics of a reaction diffusion system, describing the spread of Aedes aegypti mosquitoes, which are the primary cause of dengue infection. The system incorporates a control attempt via the sterile insect technique. The model incorporates female mosquitoes sexual preference for wild males over sterile males. We show global existence of strong solution for the system. We then derive uniform estimates to prove the existence of a global attractor in L-2(Omega), for the system. The attractor is shown to be L-infinity(Omega) regular and posess state of extinction, if the injection of sterile males is large enough. We also provide upper bounds on the Hausdorff and fractal dimensions of the attractor.

  5. Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

    Science.gov (United States)

    He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, A. David; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

    2015-01-01

    Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil RHwith both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

  6. A stochastic MILP energy planning model incorporating power market dynamics

    International Nuclear Information System (INIS)

    Koltsaklis, Nikolaos E.; Nazos, Konstantinos

    2017-01-01

    Highlights: •Stochastic MILP model for the optimal energy planning of a power system. •Power market dynamics (offers/bids) are incorporated in the proposed model. •Monte Carlo method for capturing the uncertainty of some key parameters. •Analytical supply cost composition per power producer and activity. •Clean dark and spark spreads are calculated for each power unit. -- Abstract: This paper presents an optimization-based methodological approach to address the problem of the optimal planning of a power system at an annual level in competitive and uncertain power markets. More specifically, a stochastic mixed integer linear programming model (MILP) has been developed, combining advanced optimization techniques with Monte Carlo method in order to deal with uncertainty issues. The main focus of the proposed framework is the dynamic formulation of the strategy followed by all market participants in volatile market conditions, as well as detailed economic assessment of the power system’s operation. The applicability of the proposed approach has been tested on a real case study of the interconnected Greek power system, quantifying in detail all the relevant technical and economic aspects of the system’s operation. The proposed work identifies in the form of probability distributions the optimal power generation mix, electricity trade at a regional level, carbon footprint, as well as detailed total supply cost composition, according to the assumed market structure. The paper demonstrates that the proposed optimization approach is able to provide important insights into the appropriate energy strategies designed by market participants, as well as on the strategic long-term decisions to be made by investors and/or policy makers at a national and/or regional level, underscoring potential risks and providing appropriate price signals on critical energy projects under real market operating conditions.

  7. Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

    Energy Technology Data Exchange (ETDEWEB)

    He, Yujie [Purdue Univ., West Lafayette, IN (United States). Dept. of Earth, Atmospheric, and Planetary Sciences; Yang, Jinyan [Univ. of Georgia, Athens, GA (United States). Warnell School of Forestry and Natural Resources; Northeast Forestry Univ., Harbin (China). Center for Ecological Research; Zhuang, Qianlai [Purdue Univ., West Lafayette, IN (United States). Dept. of Earth, Atmospheric, and Planetary Sciences; Purdue Univ., West Lafayette, IN (United States). Dept. of Agronomy; Harden, Jennifer W. [U.S. Geological Survey, Menlo Park, CA (United States); McGuire, Anthony D. [Alaska Cooperative Fish and Wildlife Research Unit, U.S. Geological Survey, Univ. of Alaska, Fairbanks, AK (United States). U.S. Geological Survey, Alaska Cooperative Fish and Wildlife Research Unit; Liu, Yaling [Purdue Univ., West Lafayette, IN (United States). Dept. of Earth, Atmospheric, and Planetary Sciences; Wang, Gangsheng [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Climate Change Science Inst. and Environmental Sciences Division; Gu, Lianhong [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Environmental Sciences Division

    2015-11-20

    Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here in this study we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 PgCyr-1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil RH with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

  8. Global dynamics of a PDE model for aedes aegypti mosquitoe incorporating female sexual preference

    KAUST Repository

    Parshad, Rana; Agusto, Folashade B.

    2011-01-01

    In this paper we study the long time dynamics of a reaction diffusion system, describing the spread of Aedes aegypti mosquitoes, which are the primary cause of dengue infection. The system incorporates a control attempt via the sterile insect

  9. Incorporating a Wheeled Vehicle Model in a New Monocular Visual Odometry Algorithm for Dynamic Outdoor Environments

    Science.gov (United States)

    Jiang, Yanhua; Xiong, Guangming; Chen, Huiyan; Lee, Dah-Jye

    2014-01-01

    This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, which are the two most important parameters that describe the motion of a wheeled vehicle. Additionally, the pitch angle is also considered since the planar-motion hypothesis often fails due to the dynamic characteristics of wheel suspensions and tires in real-world environments. Linearization is used to calculate a closed-form solution of the motion parameters that works as a hypothesis generator in a RAndom SAmple Consensus (RANSAC) scheme to reduce the complexity in solving equations involving trigonometric. All inliers found are used to refine the winner solution through minimizing the reprojection error. Finally, the algorithm is applied to real-time on-board visual localization applications. Its performance is evaluated by comparing against the state-of-the-art monocular visual odometry methods using both synthetic data and publicly available datasets over several kilometers in dynamic outdoor environments. PMID:25256109

  10. Incorporating a Wheeled Vehicle Model in a New Monocular Visual Odometry Algorithm for Dynamic Outdoor Environments

    Directory of Open Access Journals (Sweden)

    Yanhua Jiang

    2014-09-01

    Full Text Available This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, which are the two most important parameters that describe the motion of a wheeled vehicle. Additionally, the pitch angle is also considered since the planar-motion hypothesis often fails due to the dynamic characteristics of wheel suspensions and tires in real-world environments. Linearization is used to calculate a closed-form solution of the motion parameters that works as a hypothesis generator in a RAndom SAmple Consensus (RANSAC scheme to reduce the complexity in solving equations involving trigonometric. All inliers found are used to refine the winner solution through minimizing the reprojection error. Finally, the algorithm is applied to real-time on-board visual localization applications. Its performance is evaluated by comparing against the state-of-the-art monocular visual odometry methods using both synthetic data and publicly available datasets over several kilometers in dynamic outdoor environments.

  11. Models for Dynamic Applications

    DEFF Research Database (Denmark)

    Sales-Cruz, Mauricio; Morales Rodriguez, Ricardo; Heitzig, Martina

    2011-01-01

    This chapter covers aspects of the dynamic modelling and simulation of several complex operations that include a controlled blending tank, a direct methanol fuel cell that incorporates a multiscale model, a fluidised bed reactor, a standard chemical reactor and finally a polymerisation reactor...... be applied to formulate, analyse and solve these dynamic problems and how in the case of the fuel cell problem the model consists of coupledmeso and micro scale models. It is shown how data flows are handled between the models and how the solution is obtained within the modelling environment....

  12. Spinal motor control system incorporates an internal model of limb dynamics.

    Science.gov (United States)

    Shimansky, Y P

    2000-10-01

    The existence and utilization of an internal representation of the controlled object is one of the most important features of the functioning of neural motor control systems. This study demonstrates that this property already exists at the level of the spinal motor control system (SMCS), which is capable of generating motor patterns for reflex rhythmic movements, such as locomotion and scratching, without the aid of the peripheral afferent feedback, but substantially modifies the generated activity in response to peripheral afferent stimuli. The SMCS is presented as an optimal control system whose optimality requires that it incorporate an internal model (IM) of the controlled object's dynamics. A novel functional mechanism for the integration of peripheral sensory signals with the corresponding predictive output from the IM, the summation of information precision (SIP) is proposed. In contrast to other models in which the correction of the internal representation of the controlled object's state is based on the calculation of a mismatch between the internal and external information sources, the SIP mechanism merges the information from these sources in order to optimize the precision of the controlled object's state estimate. It is demonstrated, based on scratching in decerebrate cats as an example of the spinal control of goal-directed movements, that the results of computer modeling agree with the experimental observations related to the SMCS's reactions to phasic and tonic peripheral afferent stimuli. It is also shown that the functional requirements imposed by the mathematical model of the SMCS comply with the current knowledge about the related properties of spinal neuronal circuitry. The crucial role of the spinal presynaptic inhibition mechanism in the neuronal implementation of SIP is elucidated. Important differences between the IM and a state predictor employed for compensating for a neural reflex time delay are discussed.

  13. Incorporating teleconnection information into reservoir operating policies using Stochastic Dynamic Programming and a Hidden Markov Model

    Science.gov (United States)

    Turner, Sean; Galelli, Stefano; Wilcox, Karen

    2015-04-01

    Water reservoir systems are often affected by recurring large-scale ocean-atmospheric anomalies, known as teleconnections, that cause prolonged periods of climatological drought. Accurate forecasts of these events -- at lead times in the order of weeks and months -- may enable reservoir operators to take more effective release decisions to improve the performance of their systems. In practice this might mean a more reliable water supply system, a more profitable hydropower plant or a more sustainable environmental release policy. To this end, climate indices, which represent the oscillation of the ocean-atmospheric system, might be gainfully employed within reservoir operating models that adapt the reservoir operation as a function of the climate condition. This study develops a Stochastic Dynamic Programming (SDP) approach that can incorporate climate indices using a Hidden Markov Model. The model simulates the climatic regime as a hidden state following a Markov chain, with the state transitions driven by variation in climatic indices, such as the Southern Oscillation Index. Time series analysis of recorded streamflow data reveals the parameters of separate autoregressive models that describe the inflow to the reservoir under three representative climate states ("normal", "wet", "dry"). These models then define inflow transition probabilities for use in a classic SDP approach. The key advantage of the Hidden Markov Model is that it allows conditioning the operating policy not only on the reservoir storage and the antecedent inflow, but also on the climate condition, thus potentially allowing adaptability to a broader range of climate conditions. In practice, the reservoir operator would effect a water release tailored to a specific climate state based on available teleconnection data and forecasts. The approach is demonstrated on the operation of a realistic, stylised water reservoir with carry-over capacity in South-East Australia. Here teleconnections relating

  14. Modelling the Dynamics of Emotional Awareness

    NARCIS (Netherlands)

    Thilakarathne, D.J.; Treur, J.; Schaub, T.

    2014-01-01

    In this paper, based on literature from Cognitive and Affective Neuroscience, a computational agent model is introduced incorporating the role of emotional awareness states in the dynamics of action generation. More specifically, it covers both automatic, unconscious (bottom-up) and more cognitive

  15. A data-driven model for influenza transmission incorporating media effects.

    Science.gov (United States)

    Mitchell, Lewis; Ross, Joshua V

    2016-10-01

    Numerous studies have attempted to model the effect of mass media on the transmission of diseases such as influenza; however, quantitative data on media engagement has until recently been difficult to obtain. With the recent explosion of 'big data' coming from online social media and the like, large volumes of data on a population's engagement with mass media during an epidemic are becoming available to researchers. In this study, we combine an online dataset comprising millions of shared messages relating to influenza with traditional surveillance data on flu activity to suggest a functional form for the relationship between the two. Using this data, we present a simple deterministic model for influenza dynamics incorporating media effects, and show that such a model helps explain the dynamics of historical influenza outbreaks. Furthermore, through model selection we show that the proposed media function fits historical data better than other media functions proposed in earlier studies.

  16. Fuzzy Logic-Based Model That Incorporates Personality Traits for Heterogeneous Pedestrians

    Directory of Open Access Journals (Sweden)

    Zhuxin Xue

    2017-10-01

    Full Text Available Most models designed to simulate pedestrian dynamical behavior are based on the assumption that human decision-making can be described using precise values. This study proposes a new pedestrian model that incorporates fuzzy logic theory into a multi-agent system to address cognitive behavior that introduces uncertainty and imprecision during decision-making. We present a concept of decision preferences to represent the intrinsic control factors of decision-making. To realize the different decision preferences of heterogeneous pedestrians, the Five-Factor (OCEAN personality model is introduced to model the psychological characteristics of individuals. Then, a fuzzy logic-based approach is adopted for mapping the relationships between the personality traits and the decision preferences. Finally, we have developed an application using our model to simulate pedestrian dynamical behavior in several normal or non-panic scenarios, including a single-exit room, a hallway with obstacles, and a narrowing passage. The effectiveness of the proposed model is validated with a user study. The results show that the proposed model can generate more reasonable and heterogeneous behavior in the simulation and indicate that individual personality has a noticeable effect on pedestrian dynamical behavior.

  17. Dislocation climb models from atomistic scheme to dislocation dynamics

    OpenAIRE

    Niu, Xiaohua; Luo, Tao; Lu, Jianfeng; Xiang, Yang

    2016-01-01

    We develop a mesoscopic dislocation dynamics model for vacancy-assisted dislocation climb by upscalings from a stochastic model on the atomistic scale. Our models incorporate microscopic mechanisms of (i) bulk diffusion of vacancies, (ii) vacancy exchange dynamics between bulk and dislocation core, (iii) vacancy pipe diffusion along the dislocation core, and (iv) vacancy attachment-detachment kinetics at jogs leading to the motion of jogs. Our mesoscopic model consists of the vacancy bulk dif...

  18. Modelling dune evolution and dynamic roughness in rivers

    NARCIS (Netherlands)

    Paarlberg, Andries

    2008-01-01

    Accurate river flow models are essential tools for water managers, but these hydraulic simulation models often lack a proper description of dynamic roughness due to hysteresis effects in dune evolution. To incorporate the effects of dune evolution directly into the resistance coefficients of

  19. Modelling and Simulation of a Manipulator with Stable Viscoelastic Grasping Incorporating Friction

    Directory of Open Access Journals (Sweden)

    A. Khurshid

    2016-12-01

    Full Text Available Design, dynamics and control of a humanoid robotic hand based on anthropological dimensions, with joint friction, is modelled, simulated and analysed in this paper by using computer aided design and multibody dynamic simulation. Combined joint friction model is incorporated in the joints. Experimental values of coefficient of friction of grease lubricated sliding contacts representative of manipulator joints are presented. Human fingers deform to the shape of the grasped object (enveloping grasp at the area of interaction. A mass-spring-damper model of the grasp is developed. The interaction of the viscoelastic gripper of the arm with objects is analysed by using Bond Graph modelling method. Simulations were conducted for several material parameters. These results of the simulation are then used to develop a prototype of the proposed gripper. Bond graph model is experimentally validated by using the prototype. The gripper is used to successfully transport soft and fragile objects. This paper provides information on optimisation of friction and its inclusion in both dynamic modelling and simulation to enhance mechanical efficiency.

  20. RETRAN dynamic slip model

    International Nuclear Information System (INIS)

    McFadden, J.H.; Paulsen, M.P.; Gose, G.C.

    1981-01-01

    Thermal-hydraulic codes in general use for system calculations are based on extensive analyses of loss-of-coolant accidents following the postulated rupture of a large coolant pipe. In this study, time-dependent equation for the slip velocity in a two-phase flow condition has been incorporated into the RETRAN-02 computer code. This model addition was undertaken to remove a limitation in RETRAN-01 associated with the homogeneous equilibrium mixture model. The dynamic slip equation was derived from a set of two-fluid conservation equations. 18 refs

  1. Incorporation of quantum statistical features in molecular dynamics

    International Nuclear Information System (INIS)

    Ohnishi, Akira; Randrup, J.

    1995-01-01

    We formulate a method for incorporating quantum fluctuations into molecular-dynamics simulations of many-body systems, such as those employed for energetic nuclear collision processes. Based on Fermi's Golden Rule, we allow spontaneous transitions to occur between the wave packets which are not energy eigenstates. The ensuing diffusive evolution in the space of the wave packet parameters exhibits appealing physical properties, including relaxation towards quantum-statistical equilibrium. (author)

  2. Modelling sediment dynamics due to hillslope-river interactions : incorporating fluvial behaviour in landscape evolution model LAPSUS

    NARCIS (Netherlands)

    Baartman, Jantiene E. M.; van Gorp, Wouter; Temme, Arnaud J. A. M.; Schoorl, Jeroen M.

    Landscape evolution models (LEMs) simulate the three-dimensional development of landscapes over time. Different LEMs have different foci, e.g. erosional behaviour, river dynamics, the fluvial domain, hillslopes or a combination. LEM LAPSUS is a relatively simple cellular model operating on

  3. Incorporation of Markov reliability models for digital instrumentation and control systems into existing PRAs

    International Nuclear Information System (INIS)

    Bucci, P.; Mangan, L. A.; Kirschenbaum, J.; Mandelli, D.; Aldemir, T.; Arndt, S. A.

    2006-01-01

    Markov models have the ability to capture the statistical dependence between failure events that can arise in the presence of complex dynamic interactions between components of digital instrumentation and control systems. One obstacle to the use of such models in an existing probabilistic risk assessment (PRA) is that most of the currently available PRA software is based on the static event-tree/fault-tree methodology which often cannot represent such interactions. We present an approach to the integration of Markov reliability models into existing PRAs by describing the Markov model of a digital steam generator feedwater level control system, how dynamic event trees (DETs) can be generated from the model, and how the DETs can be incorporated into an existing PRA with the SAPHIRE software. (authors)

  4. New systematic methodology for incorporating dynamic heat transfer modelling in multi-phase biochemical reactors.

    Science.gov (United States)

    Fernández-Arévalo, T; Lizarralde, I; Grau, P; Ayesa, E

    2014-09-01

    This paper presents a new modelling methodology for dynamically predicting the heat produced or consumed in the transformations of any biological reactor using Hess's law. Starting from a complete description of model components stoichiometry and formation enthalpies, the proposed modelling methodology has integrated successfully the simultaneous calculation of both the conventional mass balances and the enthalpy change of reaction in an expandable multi-phase matrix structure, which facilitates a detailed prediction of the main heat fluxes in the biochemical reactors. The methodology has been implemented in a plant-wide modelling methodology in order to facilitate the dynamic description of mass and heat throughout the plant. After validation with literature data, as illustrative examples of the capability of the methodology, two case studies have been described. In the first one, a predenitrification-nitrification dynamic process has been analysed, with the aim of demonstrating the easy integration of the methodology in any system. In the second case study, the simulation of a thermal model for an ATAD has shown the potential of the proposed methodology for analysing the effect of ventilation and influent characterization. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. A dynamical model of terrorism

    Directory of Open Access Journals (Sweden)

    Firdaus Udwadia

    2006-01-01

    Full Text Available This paper develops a dynamical model of terrorism. We consider the population in a given region as being made up of three primary components: terrorists, those susceptible to both terrorist and pacifist propaganda, and nonsusceptibles, or pacifists. The dynamical behavior of these three populations is studied using a model that incorporates the effects of both direct military/police intervention to reduce the terrorist population, and nonviolent, persuasive intervention to influence the susceptibles to become pacifists. The paper proposes a new paradigm for studying terrorism, and looks at the long-term dynamical evolution in time of these three population components when such interventions are carried out. Many important features—some intuitive, others not nearly so—of the nature of terrorism emerge from the dynamical model proposed, and they lead to several important policy implications for the management of terrorism. The different circumstances in which nonviolent intervention and/or military/police intervention may be beneficial, and the specific conditions under which each mode of intervention, or a combination of both, may be useful, are obtained. The novelty of the model presented herein is that it deals with the time evolution of terrorist activity. It appears to be one of the few models that can be tested, evaluated, and improved upon, through the use of actual field data.

  6. Incorporating nitrogen fixing cyanobacteria in the global biogeochemical model HAMOCC

    Science.gov (United States)

    Paulsen, Hanna; Ilyina, Tatiana; Six, Katharina

    2015-04-01

    Nitrogen fixation by marine diazotrophs plays a fundamental role in the oceanic nitrogen and carbon cycle as it provides a major source of 'new' nitrogen to the euphotic zone that supports biological carbon export and sequestration. Since most global biogeochemical models include nitrogen fixation only diagnostically, they are not able to capture its spatial pattern sufficiently. Here we present the incorporation of an explicit, dynamic representation of diazotrophic cyanobacteria and the corresponding nitrogen fixation in the global ocean biogeochemical model HAMOCC (Hamburg Ocean Carbon Cycle model), which is part of the Max Planck Institute for Meteorology Earth system model (MPI-ESM). The parameterization of the diazotrophic growth is thereby based on available knowledge about the cyanobacterium Trichodesmium spp., which is considered as the most significant pelagic nitrogen fixer. Evaluation against observations shows that the model successfully reproduces the main spatial distribution of cyanobacteria and nitrogen fixation, covering large parts of the tropical and subtropical oceans. Besides the role of cyanobacteria in marine biogeochemical cycles, their capacity to form extensive surface blooms induces a number of bio-physical feedback mechanisms in the Earth system. The processes driving these interactions, which are related to the alteration of heat absorption, surface albedo and momentum input by wind, are incorporated in the biogeochemical and physical model of the MPI-ESM in order to investigate their impacts on a global scale. First preliminary results will be shown.

  7. Modelling, simulation and applications of longitudinal train dynamics

    Science.gov (United States)

    Cole, Colin; Spiryagin, Maksym; Wu, Qing; Sun, Yan Quan

    2017-10-01

    Significant developments in longitudinal train simulation and an overview of the approaches to train models and modelling vehicle force inputs are firstly presented. The most important modelling task, that of the wagon connection, consisting of energy absorption devices such as draft gears and buffers, draw gear stiffness, coupler slack and structural stiffness is then presented. Detailed attention is given to the modelling approaches for friction wedge damped and polymer draft gears. A significant issue in longitudinal train dynamics is the modelling and calculation of the input forces - the co-dimensional problem. The need to push traction performances higher has led to research and improvement in the accuracy of traction modelling which is discussed. A co-simulation method that combines longitudinal train simulation, locomotive traction control and locomotive vehicle dynamics is presented. The modelling of other forces, braking propulsion resistance, curve drag and grade forces are also discussed. As extensions to conventional longitudinal train dynamics, lateral forces and coupler impacts are examined in regards to interaction with wagon lateral and vertical dynamics. Various applications of longitudinal train dynamics are then presented. As an alternative to the tradition single wagon mass approach to longitudinal train dynamics, an example incorporating fully detailed wagon dynamics is presented for a crash analysis problem. Further applications of starting traction, air braking, distributed power, energy analysis and tippler operation are also presented.

  8. CFTSIM-ITER dynamic fuel cycle model

    International Nuclear Information System (INIS)

    Busigin, A.; Gierszewski, P.

    1998-01-01

    Dynamic system models have been developed for specific tritium systems with considerable detail and for integrated fuel cycles with lesser detail (e.g. D. Holland, B. Merrill, Analysis of tritium migration and deposition in fusion reactor systems, Proceedings of the Ninth Symposium Eng. Problems of Fusion Research (1981); M.A. Abdou, E. Vold, C. Gung, M. Youssef, K. Shin, DT fuel self-sufficiency in fusion reactors, Fusion Technol. (1986); G. Spannagel, P. Gierszewski, Dynamic tritium inventory of a NET/ITER fuel cycle with lithium salt solution blanket, Fusion Eng. Des. (1991); W. Kuan, M.A. Abdou, R.S. Willms, Dynamic simulation of a proposed ITER tritium processing system, Fusion Technol. (1995)). In order to provide a tool to understand and optimize the behavior of the ITER fuel cycle, a dynamic fuel cycle model called CFTSIM is under development. The CFTSIM code incorporates more detailed ITER models, specifically for the important isotope separation system, and also has an easier-to-use graphical interface. This paper provides an overview of CFTSIM Version 1.0. The models included are those with significant and varying tritium inventories over a test campaign: fueling, plasma and first wall, pumping, fuel cleanup, isotope separation and storage. An illustration of the results is shown. (orig.)

  9. 3.5D dynamic PET image reconstruction incorporating kinetics-based clusters

    International Nuclear Information System (INIS)

    Lu Lijun; Chen Wufan; Karakatsanis, Nicolas A; Rahmim, Arman; Tang Jing

    2012-01-01

    Standard 3D dynamic positron emission tomographic (PET) imaging consists of independent image reconstructions of individual frames followed by application of appropriate kinetic model to the time activity curves at the voxel or region-of-interest (ROI). The emerging field of 4D PET reconstruction, by contrast, seeks to move beyond this scheme and incorporate information from multiple frames within the image reconstruction task. Here we propose a novel reconstruction framework aiming to enhance quantitative accuracy of parametric images via introduction of priors based on voxel kinetics, as generated via clustering of preliminary reconstructed dynamic images to define clustered neighborhoods of voxels with similar kinetics. This is then followed by straightforward maximum a posteriori (MAP) 3D PET reconstruction as applied to individual frames; and as such the method is labeled ‘3.5D’ image reconstruction. The use of cluster-based priors has the advantage of further enhancing quantitative performance in dynamic PET imaging, because: (a) there are typically more voxels in clusters than in conventional local neighborhoods, and (b) neighboring voxels with distinct kinetics are less likely to be clustered together. Using realistic simulated 11 C-raclopride dynamic PET data, the quantitative performance of the proposed method was investigated. Parametric distribution-volume (DV) and DV ratio (DVR) images were estimated from dynamic image reconstructions using (a) maximum-likelihood expectation maximization (MLEM), and MAP reconstructions using (b) the quadratic prior (QP-MAP), (c) the Green prior (GP-MAP) and (d, e) two proposed cluster-based priors (CP-U-MAP and CP-W-MAP), followed by graphical modeling, and were qualitatively and quantitatively compared for 11 ROIs. Overall, the proposed dynamic PET reconstruction methodology resulted in substantial visual as well as quantitative accuracy improvements (in terms of noise versus bias performance) for parametric DV

  10. Rich dynamics of a food chain model with ratio-dependent type III ...

    African Journals Online (AJOL)

    user

    prey dynamics is to incorporate discrete delay into the predator equations. ... models may be found in classical books of Gopalsamy (1992), Macdonald (1989) .... Model (1) has 10 parameters in all, which make mathematical analysis complex.

  11. Incorporation of ice sheet models into an Earth system model: Focus on methodology of coupling

    Science.gov (United States)

    Rybak, Oleg; Volodin, Evgeny; Morozova, Polina; Nevecherja, Artiom

    2018-03-01

    Elaboration of a modern Earth system model (ESM) requires incorporation of ice sheet dynamics. Coupling of an ice sheet model (ICM) to an AOGCM is complicated by essential differences in spatial and temporal scales of cryospheric, atmospheric and oceanic components. To overcome this difficulty, we apply two different approaches for the incorporation of ice sheets into an ESM. Coupling of the Antarctic ice sheet model (AISM) to the AOGCM is accomplished via using procedures of resampling, interpolation and assigning to the AISM grid points annually averaged meanings of air surface temperature and precipitation fields generated by the AOGCM. Surface melting, which takes place mainly on the margins of the Antarctic peninsula and on ice shelves fringing the continent, is currently ignored. AISM returns anomalies of surface topography back to the AOGCM. To couple the Greenland ice sheet model (GrISM) to the AOGCM, we use a simple buffer energy- and water-balance model (EWBM-G) to account for orographically-driven precipitation and other sub-grid AOGCM-generated quantities. The output of the EWBM-G consists of surface mass balance and air surface temperature to force the GrISM, and freshwater run-off to force thermohaline circulation in the oceanic block of the AOGCM. Because of a rather complex coupling procedure of GrIS compared to AIS, the paper mostly focuses on Greenland.

  12. Tantalum strength model incorporating temperature, strain rate and pressure

    Science.gov (United States)

    Lim, Hojun; Battaile, Corbett; Brown, Justin; Lane, Matt

    Tantalum is a body-centered-cubic (BCC) refractory metal that is widely used in many applications in high temperature, strain rate and pressure environments. In this work, we propose a physically-based strength model for tantalum that incorporates effects of temperature, strain rate and pressure. A constitutive model for single crystal tantalum is developed based on dislocation kink-pair theory, and calibrated to measurements on single crystal specimens. The model is then used to predict deformations of single- and polycrystalline tantalum. In addition, the proposed strength model is implemented into Sandia's ALEGRA solid dynamics code to predict plastic deformations of tantalum in engineering-scale applications at extreme conditions, e.g. Taylor impact tests and Z machine's high pressure ramp compression tests, and the results are compared with available experimental data. Sandia National Laboratories is a multi program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

  13. Integrating microbial diversity in soil carbon dynamic models parameters

    Science.gov (United States)

    Louis, Benjamin; Menasseri-Aubry, Safya; Leterme, Philippe; Maron, Pierre-Alain; Viaud, Valérie

    2015-04-01

    Faced with the numerous concerns about soil carbon dynamic, a large quantity of carbon dynamic models has been developed during the last century. These models are mainly in the form of deterministic compartment models with carbon fluxes between compartments represented by ordinary differential equations. Nowadays, lots of them consider the microbial biomass as a compartment of the soil organic matter (carbon quantity). But the amount of microbial carbon is rarely used in the differential equations of the models as a limiting factor. Additionally, microbial diversity and community composition are mostly missing, although last advances in soil microbial analytical methods during the two past decades have shown that these characteristics play also a significant role in soil carbon dynamic. As soil microorganisms are essential drivers of soil carbon dynamic, the question about explicitly integrating their role have become a key issue in soil carbon dynamic models development. Some interesting attempts can be found and are dominated by the incorporation of several compartments of different groups of microbial biomass in terms of functional traits and/or biogeochemical compositions to integrate microbial diversity. However, these models are basically heuristic models in the sense that they are used to test hypotheses through simulations. They have rarely been confronted to real data and thus cannot be used to predict realistic situations. The objective of this work was to empirically integrate microbial diversity in a simple model of carbon dynamic through statistical modelling of the model parameters. This work is based on available experimental results coming from a French National Research Agency program called DIMIMOS. Briefly, 13C-labelled wheat residue has been incorporated into soils with different pedological characteristics and land use history. Then, the soils have been incubated during 104 days and labelled and non-labelled CO2 fluxes have been measured at ten

  14. A dynamic model of the greenhouse effect and its control

    International Nuclear Information System (INIS)

    Perman, R.; Nisbet, R.; Ma, Y.

    1991-01-01

    A dynamic model is developed for the analysis of programmes to control the greenhouse effect. The model uses simplified representations of physical processes determining climate change, linked to an economic model of emissions and emissions abatement. Feedbacks between physical and economic processes are incorporated, and the costs of emissions reduction are compared with the benefits through averted damage. Simulation analyses explore the relative merits of several intervention scenarios, each of which is compared with non intervention. Throughout the paper, emphasis is placed upon the long term consequences of behaviour, and the patterns of dynamic adjustment over time. (author)

  15. Incorporating parametric uncertainty into population viability analysis models

    Science.gov (United States)

    McGowan, Conor P.; Runge, Michael C.; Larson, Michael A.

    2011-01-01

    Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.

  16. Debris flow analysis with a one dimensional dynamic run-out model that incorporates entrained material

    Science.gov (United States)

    Luna, Byron Quan; Remaître, Alexandre; van Asch, Theo; Malet, Jean-Philippe; van Westen, Cees

    2010-05-01

    Estimating the magnitude and the intensity of rapid landslides like debris flows is fundamental to evaluate quantitatively the hazard in a specific location. Intensity varies through the travelled course of the flow and can be described by physical features such as deposited volume, velocities, height of the flow, impact forces and pressures. Dynamic run-out models are able to characterize the distribution of the material, its intensity and define the zone where the elements will experience an impact. These models can provide valuable inputs for vulnerability and risk calculations. However, most dynamic run-out models assume a constant volume during the motion of the flow, ignoring the important role of material entrained along its path. Consequently, they neglect that the increase of volume enhances the mobility of the flow and can significantly influence the size of the potential impact area. An appropriate erosion mechanism needs to be established in the analyses of debris flows that will improve the results of dynamic modeling and consequently the quantitative evaluation of risk. The objective is to present and test a simple 1D debris flow model with a material entrainment concept based on limit equilibrium considerations and the generation of excess pore water pressure through undrained loading of the in situ bed material. The debris flow propagation model is based on a one dimensional finite difference solution of a depth-averaged form of the Navier-Stokes equations of fluid motions. The flow is treated as a laminar one phase material, which behavior is controlled by a visco-plastic Coulomb-Bingham rheology. The model parameters are evaluated and the model performance is tested on a debris flow event that occurred in 2003 in the Faucon torrent (Southern French Alps).

  17. Incorporating H2 Dynamics and Inhibition into a Microbially Based Methanogenesis Model for Restored Wetland Sediments

    Science.gov (United States)

    Pal, David; Jaffe, Peter

    2015-04-01

    Estimates of global CH4 emissions from wetlands indicate that wetlands are the largest natural source of CH4 to the atmosphere. In this paper, we propose that there is a missing component to these models that should be addressed. CH4 is produced in wetland sediments from the microbial degradation of organic carbon through multiple fermentation steps and methanogenesis pathways. There are multiple sources of carbon for methananogenesis; in vegetated wetland sediments, microbial communities consume root exudates as a major source of organic carbon. In many methane models propionate is used as a model carbon molecule. This simple sugar is fermented into acetate and H2, acetate is transformed to methane and CO2, while the H2 and CO2 are used to form an additional CH4 molecule. The hydrogenotrophic pathway involves the equilibrium of two dissolved gases, CH4 and H2. In an effort to limit CH4 emissions from wetlands, there has been growing interest in finding ways to limit plant transport of soil gases through root systems. Changing planted species, or genetically modifying new species of plants may control this transport of soil gases. While this may decrease the direct emissions of methane, there is little understanding about how H2 dynamics may feedback into overall methane production. The results of an incubation study were combined with a new model of propionate degradation for methanogenesis that also examines other natural parameters (i.e. gas transport through plants). This presentation examines how we would expect this model to behave in a natural field setting with changing sulfate and carbon loading schemes. These changes can be controlled through new plant species and other management practices. Next, we compare the behavior of two variations of this model, with or without the incorporation of H2 interactions, with changing sulfate, carbon loading and root volatilization. Results show that while the models behave similarly there may be a discrepancy of nearly

  18. Incorporating free-floating car-sharing into an activity-based dynamic user equilibrium model : a demand-side model

    NARCIS (Netherlands)

    Li, Q.; Liao, F.; Timmermans, H.J.P.; Huang, H-J; Zhou, J.

    2018-01-01

    Free-floating car-sharing (FFC) has recently received increasing attention due to the flexibility in mobility services. Existing studies related to FFC mainly focus on the analysis of operational management and user preferences. Efforts to model the dynamic choices of free-floating shared cars (SCs)

  19. The general dynamic model

    DEFF Research Database (Denmark)

    Borregaard, Michael K.; Matthews, Thomas J.; Whittaker, Robert James

    2016-01-01

    Aim: Island biogeography focuses on understanding the processes that underlie a set of well-described patterns on islands, but it lacks a unified theoretical framework for integrating these processes. The recently proposed general dynamic model (GDM) of oceanic island biogeography offers a step...... towards this goal. Here, we present an analysis of causality within the GDM and investigate its potential for the further development of island biogeographical theory. Further, we extend the GDM to include subduction-based island arcs and continental fragment islands. Location: A conceptual analysis...... of evolutionary processes in simulations derived from the mechanistic assumptions of the GDM corresponded broadly to those initially suggested, with the exception of trends in extinction rates. Expanding the model to incorporate different scenarios of island ontogeny and isolation revealed a sensitivity...

  20. Conceptual Design Optimization of an Augmented Stability Aircraft Incorporating Dynamic Response Performance Constraints

    Science.gov (United States)

    Welstead, Jason

    2014-01-01

    This research focused on incorporating stability and control into a multidisciplinary de- sign optimization on a Boeing 737-class advanced concept called the D8.2b. A new method of evaluating the aircraft handling performance using quantitative evaluation of the sys- tem to disturbances, including perturbations, continuous turbulence, and discrete gusts, is presented. A multidisciplinary design optimization was performed using the D8.2b transport air- craft concept. The con guration was optimized for minimum fuel burn using a design range of 3,000 nautical miles. Optimization cases were run using xed tail volume coecients, static trim constraints, and static trim and dynamic response constraints. A Cessna 182T model was used to test the various dynamic analysis components, ensuring the analysis was behaving as expected. Results of the optimizations show that including stability and con- trol in the design process drastically alters the optimal design, indicating that stability and control should be included in conceptual design to avoid system level penalties later in the design process.

  1. MDESRAP: a model for understanding the dynamics of electricity supply, resources and pollution

    International Nuclear Information System (INIS)

    Qudrat-Ullah, H.

    2005-01-01

    The inherent dynamic complexity of the energy policy design problem makes the conventional 'closed-form' solution impossible. This paper contributes a dynamic simulation model as a possible solution. The model captures the dynamics of underlying sectors of electricity demand, investment, capital, resource, production, environment and costs and pricing. The existing feedback loops, nonlinearity and time-lag characteristics present in the real world electricity systems are incorporated in the model. The model is calibrated to Pakistan's case data. How the model has been used in policy assessments and the design of the alternative energy policies subject to various environmental and resource constraints is also discussed. (author)

  2. Dynamic Intellectual Capital Model in a Company

    Directory of Open Access Journals (Sweden)

    Vladimir Shatrevich

    2015-06-01

    Full Text Available The aim of this paper is to indicate the relations between company’s value added (VA and intangible assets. Authors declare that Intellectual capital (IC is one of the most relevant intangibles for a company, and the concept with measurement, and the relation with value creation is necessary for modern markets. Since relationship between IC elements and VA are complicated, this paper is aimed to create a usable dynamic model for building company’s value added through intellectual capital. The model is incorporating that outputs from IC elements are not homogeneously received and made some contributions to dynamic nature of IC relation and VA. Variables that will help companies to evaluate contribution of each element of IC are added to the model. This paper emphasizes the importance of a company’s IC and the positive interaction between them in generating profits for company.

  3. Incorporating groundwater flow into the WEPP model

    Science.gov (United States)

    William Elliot; Erin Brooks; Tim Link; Sue Miller

    2010-01-01

    The water erosion prediction project (WEPP) model is a physically-based hydrology and erosion model. In recent years, the hydrology prediction within the model has been improved for forest watershed modeling by incorporating shallow lateral flow into watershed runoff prediction. This has greatly improved WEPP's hydrologic performance on small watersheds with...

  4. Optimal parameters for the FFA-Beddoes dynamic stall model

    Energy Technology Data Exchange (ETDEWEB)

    Bjoerck, A; Mert, M [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden); Madsen, H A [Risoe National Lab., Roskilde (Denmark)

    1999-03-01

    Unsteady aerodynamic effects, like dynamic stall, must be considered in calculation of dynamic forces for wind turbines. Models incorporated in aero-elastic programs are of semi-empirical nature. Resulting aerodynamic forces therefore depend on values used for the semi-empiricial parameters. In this paper a study of finding appropriate parameters to use with the Beddoes-Leishman model is discussed. Minimisation of the `tracking error` between results from 2D wind tunnel tests and simulation with the model is used to find optimum values for the parameters. The resulting optimum parameters show a large variation from case to case. Using these different sets of optimum parameters in the calculation of blade vibrations, give rise to quite different predictions of aerodynamic damping which is discussed. (au)

  5. An Extended Non-Lane-Based Optimal Velocity Model with Dynamic Collaboration

    Directory of Open Access Journals (Sweden)

    Zhipeng Li

    2013-01-01

    Full Text Available Incorporating the effects of the lane width in traffic, in this paper, we propose a dynamical model based on the strategy of three-vehicle cooperation driving. We obtain the smoother acceleration distribution in the new model through considering the dynamic collaboration with the nearest preceding vehicle and the nearest following vehicle. It is proved that the stability of the new model is greatly improved compared to the early non-lane-based car following model by using the linear stability theory. We find that when the parameter of lateral separation distance is identified, the amplitude of traffic congestion decreases with increasing the strength of dynamic collaboration in the simulation experiments. In addition, we apply the new extended model to simulate the motions of cars starting from a traffic signal and the dissipating of the traffic congestion; it is found that our new model can predict realistic delay time and kinematic wave speed and obtained a faster dissipation speed of traffic congestion than the traffic flow model without considering the dynamic collaboration.

  6. Dynamic modelling and hardware-in-the-loop testing of PEMFC

    Energy Technology Data Exchange (ETDEWEB)

    Vath, Andreas; Soehn, Matthias; Nicoloso, Norbert; Hartkopf, Thomas [Technische Universitaet Darmstadt/Institut fuer Elektrische Energie wand lung, Landgraf-Georg-Str. 4, D-64283 Darmstadt (Germany); Lemes, Zijad; Maencher, Hubert [MAGNUM Automatisierungstechnik GmbH, Bunsenstr. 22, D-64293 Darmstadt (Germany)

    2006-07-03

    Modelling and hardware-in-the-loop (HIL) testing of fuel cell components and entire systems open new ways for the design and advance development of FCs. In this work proton exchange membrane fuel cells (PEMFC) are dynamically modelled within MATLAB-Simulink at various operation conditions in order to establish a comprehensive description of their dynamic behaviour as well as to explore the modelling facility as a diagnostic tool. Set-up of a hardware-in-the-loop (HIL) system enables real time interaction between the selected hardware and the model. The transport of hydrogen, nitrogen, oxygen, water vapour and liquid water in the gas diffusion and catalyst layers of the stack are incorporated into the model according to their physical and electrochemical characteristics. Other processes investigated include, e.g., the membrane resistance as a function of the water content during fast load changes. Cells are modelled three-dimensionally and dynamically. In case of system simulations a one-dimensional model is preferred to reduce computation time. The model has been verified by experiments with a water-cooled stack. (author)

  7. Torsional Dynamics of Steerable Needles: Modeling and Fluoroscopic Guidance

    Science.gov (United States)

    Swensen, John P.; Lin, MingDe; Okamura, Allison M.; Cowan, Noah J.

    2017-01-01

    Needle insertions underlie a diversity of medical interventions. Steerable needles provide a means by which to enhance existing needle-based interventions and facilitate new ones. Tip-steerable needles follow a curved path and can be steered by twisting the needle base during insertion, but this twisting excites torsional dynamics that introduce a discrepancy between the base and tip twist angles. Here, we model the torsional dynamics of a flexible rod—such as a tip-steerable needle—during subsurface insertion and develop a new controller based on the model. The torsional model incorporates time-varying mode shapes to capture the changing boundary conditions inherent during insertion. Numerical simulations and physical experiments using two distinct setups—stereo camera feedback in semi-transparent artificial tissue and feedback control with real-time X-ray imaging in optically opaque artificial tissue— demonstrate the need to account for torsional dynamics in control of the needle tip. PMID:24860026

  8. Chaotic Dynamics in Smart Grid and Suppression Scheme via Generalized Fuzzy Hyperbolic Model

    NARCIS (Netherlands)

    Sun, Q.; Wang, Y.; Yang, J.; Qiu, Y.; Zhang, H.

    2014-01-01

    This paper presents a method to control chaotic behavior of a typical Smart Grid based on generalized fuzzy hyperbolic model (GFHM). As more and more distributed generations (DG) are incorporated into the Smart Grid, the chaotic behavior occurs increasingly. To verify the behavior, a dynamic model

  9. Incorporating NDVI in a gravity model setting to describe spatio-temporal patterns of Lyme borreliosis incidence

    Science.gov (United States)

    Barrios, J. M.; Verstraeten, W. W.; Farifteh, J.; Maes, P.; Aerts, J. M.; Coppin, P.

    2012-04-01

    Lyme borreliosis (LB) is the most common tick-borne disease in Europe and incidence growth has been reported in several European countries during the last decade. LB is caused by the bacterium Borrelia burgdorferi and the main vector of this pathogen in Europe is the tick Ixodes ricinus. LB incidence and spatial spread is greatly dependent on environmental conditions impacting habitat, demography and trophic interactions of ticks and the wide range of organisms ticks parasite. The landscape configuration is also a major determinant of tick habitat conditions and -very important- of the fashion and intensity of human interaction with vegetated areas, i.e. human exposure to the pathogen. Hence, spatial notions as distance and adjacency between urban and vegetated environments are related to human exposure to tick bites and, thus, to risk. This work tested the adequacy of a gravity model setting to model the observed spatio-temporal pattern of LB as a function of location and size of urban and vegetated areas and the seasonal and annual change in the vegetation dynamics as expressed by MODIS NDVI. Opting for this approach implies an analogy with Newton's law of universal gravitation in which the attraction forces between two bodies are directly proportional to the bodies mass and inversely proportional to distance. Similar implementations have proven useful in fields like trade modeling, health care service planning, disease mapping among other. In our implementation, the size of human settlements and vegetated systems and the distance separating these landscape elements are considered the 'bodies'; and the 'attraction' between them is an indicator of exposure to pathogen. A novel element of this implementation is the incorporation of NDVI to account for the seasonal and annual variation in risk. The importance of incorporating this indicator of vegetation activity resides in the fact that alterations of LB incidence pattern observed the last decade have been ascribed

  10. The System Dynamics Model for Development of Organic Agriculture

    Science.gov (United States)

    Rozman, Črtomir; Škraba, Andrej; Kljajić, Miroljub; Pažek, Karmen; Bavec, Martina; Bavec, Franci

    2008-10-01

    Organic agriculture is the highest environmentally valuable agricultural system, and has strategic importance at national level that goes beyond the interests of agricultural sector. In this paper we address development of organic farming simulation model based on a system dynamics methodology (SD). The system incorporates relevant variables, which affect the development of the organic farming. The group decision support system (GDSS) was used in order to identify most relevant variables for construction of causal loop diagram and further model development. The model seeks answers to strategic questions related to the level of organically utilized area, levels of production and crop selection in a long term dynamic context and will be used for simulation of different policy scenarios for organic farming and their impact on economic and environmental parameters of organic production at an aggregate level.

  11. Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model

    Science.gov (United States)

    Smith, B.; Wårlind, D.; Arneth, A.; Hickler, T.; Leadley, P.; Siltberg, J.; Zaehle, S.

    2014-04-01

    The LPJ-GUESS dynamic vegetation model uniquely combines an individual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C-N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness of fit for broadleaved forests. N limitation associated with low N-mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N limitation associated with low N-mineralisation rates of colder soils reduces CO2 enhancement of net primary production (NPP) for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by ca. 10%; additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C-N interactions in studies of global terrestrial N cycling, and as a basis for understanding mechanisms on local scales and in different regional contexts.

  12. A computational model incorporating neural stem cell dynamics reproduces glioma incidence across the lifespan in the human population.

    Directory of Open Access Journals (Sweden)

    Roman Bauer

    Full Text Available Glioma is the most common form of primary brain tumor. Demographically, the risk of occurrence increases until old age. Here we present a novel computational model to reproduce the probability of glioma incidence across the lifespan. Previous mathematical models explaining glioma incidence are framed in a rather abstract way, and do not directly relate to empirical findings. To decrease this gap between theory and experimental observations, we incorporate recent data on cellular and molecular factors underlying gliomagenesis. Since evidence implicates the adult neural stem cell as the likely cell-of-origin of glioma, we have incorporated empirically-determined estimates of neural stem cell number, cell division rate, mutation rate and oncogenic potential into our model. We demonstrate that our model yields results which match actual demographic data in the human population. In particular, this model accounts for the observed peak incidence of glioma at approximately 80 years of age, without the need to assert differential susceptibility throughout the population. Overall, our model supports the hypothesis that glioma is caused by randomly-occurring oncogenic mutations within the neural stem cell population. Based on this model, we assess the influence of the (experimentally indicated decrease in the number of neural stem cells and increase of cell division rate during aging. Our model provides multiple testable predictions, and suggests that different temporal sequences of oncogenic mutations can lead to tumorigenesis. Finally, we conclude that four or five oncogenic mutations are sufficient for the formation of glioma.

  13. Dynamical regimes due to technological change in a microeconomical model of production

    Science.gov (United States)

    Hamacher, K.

    2012-09-01

    We develop a microeconomical model to investigate the impact of technological change onto production decisions of suppliers—modeling an effective feedback mechanism of the market. An important property—the time horizon of production planning—is related to the Kolmogorov entropy of the one-dimensional maps describing price dynamics. We simulate this price dynamics in an ensemble representing the whole macroeconomy. We show how this model can be used to support ongoing research in economic growth and incorporate the obtained microeconomic findings into the discussion about appropriate macroeconomic quantities such as the production function—thus effectively underpinning macroeconomics with microeconomical dynamics. From there we can show that the model exhibits different dynamical regimes (suggesting "phase transitions") with respect to an order parameter. The non-linear feedback under technological change was found to be the crucial mechanism. The implications of the obtained regimes are finally discussed.

  14. CSDMS2.0: Computational Infrastructure for Community Surface Dynamics Modeling

    Science.gov (United States)

    Syvitski, J. P.; Hutton, E.; Peckham, S. D.; Overeem, I.; Kettner, A.

    2012-12-01

    The Community Surface Dynamic Modeling System (CSDMS) is an NSF-supported, international and community-driven program that seeks to transform the science and practice of earth-surface dynamics modeling. CSDMS integrates a diverse community of more than 850 geoscientists representing 360 international institutions (academic, government, industry) from 60 countries and is supported by a CSDMS Interagency Committee (22 Federal agencies), and a CSDMS Industrial Consortia (18 companies). CSDMS presently distributes more 200 Open Source models and modeling tools, access to high performance computing clusters in support of developing and running models, and a suite of products for education and knowledge transfer. CSDMS software architecture employs frameworks and services that convert stand-alone models into flexible "plug-and-play" components to be assembled into larger applications. CSDMS2.0 will support model applications within a web browser, on a wider variety of computational platforms, and on other high performance computing clusters to ensure robustness and sustainability of the framework. Conversion of stand-alone models into "plug-and-play" components will employ automated wrapping tools. Methods for quantifying model uncertainty are being adapted as part of the modeling framework. Benchmarking data is being incorporated into the CSDMS modeling framework to support model inter-comparison. Finally, a robust mechanism for ingesting and utilizing semantic mediation databases is being developed within the Modeling Framework. Six new community initiatives are being pursued: 1) an earth - ecosystem modeling initiative to capture ecosystem dynamics and ensuing interactions with landscapes, 2) a geodynamics initiative to investigate the interplay among climate, geomorphology, and tectonic processes, 3) an Anthropocene modeling initiative, to incorporate mechanistic models of human influences, 4) a coastal vulnerability modeling initiative, with emphasis on deltas and

  15. A modified social force model for crowd dynamics

    Science.gov (United States)

    Hassan, Ummi Nurmasyitah; Zainuddin, Zarita; Abu-Sulyman, Ibtesam M.

    2017-08-01

    The Social Force Model (SFM) is one of the most successful models in microscopic pedestrian studies that is used to study the movement of pedestrians. Many modifications have been done to improvise the SFM by earlier researchers such as the incorporation of a constant respect factor into the self-stopping mechanism. Before the new mechanism is introduced, the researchers found out that a pedestrian will immediately come to a halt if other pedestrians are near to him, which seems to be an unrealistic behavior. Therefore, researchers introduce a self-slowing mechanism to gradually stop a pedestrian when he is approaching other pedestrians. Subsequently, the dynamic respect factor is introduced into the self-slowing mechanism based on the density of the pedestrians to make the model even more realistic. In real life situations, the respect factor of the pedestrians should be dynamic values instead of a constant value. However, when we reproduce the simulation of the dynamic respect factor, we found that the movement of the pedestrians are unrealistic because the pedestrians are lacking perception of the pedestrians in front of him. In this paper, we adopted both dynamic respect factor and dynamic angular parameter, called modified dynamic respect factor, which is dependent on the density of the pedestrians. Simulations are performed in a normal unidirectional walkway to compare the simulated pedestrians' movements produced by both models. The results obtained showed that the modified dynamic respect factor produces more realistic movement of the pedestrians which conform to the real situation. Moreover, we also found that the simulations endow the pedestrian with a self-slowing mechanism and a perception of other pedestrians in front of him.

  16. Incorporating direct marketing activity into latent attrition models

    NARCIS (Netherlands)

    Schweidel, David A.; Knox, George

    2013-01-01

    When defection is unobserved, latent attrition models provide useful insights about customer behavior and accurate forecasts of customer value. Yet extant models ignore direct marketing efforts. Response models incorporate the effects of direct marketing, but because they ignore latent attrition,

  17. Incorporating Context Dependency of Species Interactions in Species Distribution Models.

    Science.gov (United States)

    Lany, Nina K; Zarnetske, Phoebe L; Gouhier, Tarik C; Menge, Bruce A

    2017-07-01

    Species distribution models typically use correlative approaches that characterize the species-environment relationship using occurrence or abundance data for a single species. However, species distributions are determined by both abiotic conditions and biotic interactions with other species in the community. Therefore, climate change is expected to impact species through direct effects on their physiology and indirect effects propagated through their resources, predators, competitors, or mutualists. Furthermore, the sign and strength of species interactions can change according to abiotic conditions, resulting in context-dependent species interactions that may change across space or with climate change. Here, we incorporated the context dependency of species interactions into a dynamic species distribution model. We developed a multi-species model that uses a time-series of observational survey data to evaluate how abiotic conditions and species interactions affect the dynamics of three rocky intertidal species. The model further distinguishes between the direct effects of abiotic conditions on abundance and the indirect effects propagated through interactions with other species. We apply the model to keystone predation by the sea star Pisaster ochraceus on the mussel Mytilus californianus and the barnacle Balanus glandula in the rocky intertidal zone of the Pacific coast, USA. Our method indicated that biotic interactions between P. ochraceus and B. glandula affected B. glandula dynamics across >1000 km of coastline. Consistent with patterns from keystone predation, the growth rate of B. glandula varied according to the abundance of P. ochraceus in the previous year. The data and the model did not indicate that the strength of keystone predation by P. ochraceus varied with a mean annual upwelling index. Balanus glandula cover increased following years with high phytoplankton abundance measured as mean annual chlorophyll-a. M. californianus exhibited the same

  18. An approach to incorporate the detonation shock dynamics into the calculation of explosive acceleration of metals

    International Nuclear Information System (INIS)

    Li Qingzhong; Sun Chengwei; Zhao Feng; Gao Wen; Wen Shanggang; Liu Wenhan

    1999-11-01

    The generalized geometrical optics model for the detonation shock dynamics (DSD) has been incorporated into the two dimensional hydro-code WSU to form a combination code ADW for numerical simulation of explosive acceleration of metals. An analytical treatment of the coupling conditions at the nodes just behind the detonation front is proposed. The experiments on two kinds of explosive-flyer assemblies with different length/diameter ratio were carried out to verify the ADW calculations, where the tested explosive was HMX or TATB based. It is found that the combination of DSD and hydro-code can improve the calculation precision, and has advantages in larger meshes and less CPU time

  19. Dynamic model for the assessment of radiological exposure to marine biota

    Energy Technology Data Exchange (ETDEWEB)

    Vives i Batlle, J. [Westlakes Scientific Consulting Ltd, The Princess Royal Building, Westlakes Science and Technology Park, Moor Row, Cumbria CA24 3LN (United Kingdom)], E-mail: jordi.vives@westlakes.ac.uk; Wilson, R.C.; Watts, S.J.; Jones, S.R.; McDonald, P.; Vives-Lynch, S. [Westlakes Scientific Consulting Ltd, The Princess Royal Building, Westlakes Science and Technology Park, Moor Row, Cumbria CA24 3LN (United Kingdom)

    2008-11-15

    A generic approach has been developed to simulate dynamically the uptake and turnover of radionuclides by marine biota. The approach incorporates a three-compartment biokinetic model based on first order linear kinetics, with interchange rates between the organism and its surrounding environment. Model rate constants are deduced as a function of known parameters: biological half-lives of elimination, concentration factors and a sample point of the retention curve, allowing for the representation of multi-component release. The new methodology has been tested and validated in respect of non-dynamic assessment models developed for regulatory purposes. The approach has also been successfully tested against research dynamic models developed to represent the uptake of technetium and radioiodine by lobsters and winkles. Assessments conducted on two realistic test scenarios demonstrated the importance of simulating time-dependency for ecosystems in which environmental levels of radionuclides are not in equilibrium.

  20. Topics in Modeling of Cochlear Dynamics: Computation, Response and Stability Analysis

    Science.gov (United States)

    Filo, Maurice G.

    This thesis touches upon several topics in cochlear modeling. Throughout the literature, mathematical models of the cochlea vary according to the degree of biological realism to be incorporated. This thesis casts the cochlear model as a continuous space-time dynamical system using operator language. This framework encompasses a wider class of cochlear models and makes the dynamics more transparent and easier to analyze before applying any numerical method to discretize space. In fact, several numerical methods are investigated to study the computational efficiency of the finite dimensional realizations in space. Furthermore, we study the effects of the active gain perturbations on the stability of the linearized dynamics. The stability analysis is used to explain possible mechanisms underlying spontaneous otoacoustic emissions and tinnitus. Dynamic Mode Decomposition (DMD) is introduced as a useful tool to analyze the response of nonlinear cochlear models. Cochlear response features are illustrated using DMD which has the advantage of explicitly revealing the spatial modes of vibrations occurring in the Basilar Membrane (BM). Finally, we address the dynamic estimation problem of BM vibrations using Extended Kalman Filters (EKF). Due to the limitations of noninvasive sensing schemes, such algorithms are inevitable to estimate the dynamic behavior of a living cochlea.

  1. Dynamical patterns of calcium signaling in a functional model of neuron-astrocyte networks

    DEFF Research Database (Denmark)

    Postnov, D.E.; Koreshkov, R.N.; Brazhe, N.A.

    2009-01-01

    We propose a functional mathematical model for neuron-astrocyte networks. The model incorporates elements of the tripartite synapse and the spatial branching structure of coupled astrocytes. We consider glutamate-induced calcium signaling as a specific mode of excitability and transmission...... in astrocytic-neuronal networks. We reproduce local and global dynamical patterns observed experimentally....

  2. Thermodynamic model of a thermal storage air conditioning system with dynamic behavior

    International Nuclear Information System (INIS)

    Fleming, Evan; Wen, Shaoyi; Shi, Li; Silva, Alexandre K. da

    2013-01-01

    Highlights: • We developed an automotive thermal storage air conditioning system model. • The thermal storage unit utilizes phase change materials. • We use semi-analytic solution to the coupled phase change and forced convection. • We model the airside heat exchange using the NTU method. • The system model can incorporate dynamic inputs, e.g. variable inlet airflow. - Abstract: A thermodynamic model was developed to predict transient behavior of a thermal storage system, using phase change materials (PCMs), for a novel electric vehicle climate conditioning application. The main objectives of the paper are to consider the system’s dynamic behavior, such as a dynamic air flow rate into the vehicle’s cabin, and to characterize the transient heat transfer process between the thermal storage unit and the vehicle’s cabin, while still maintaining accurate solution to the complex phase change heat transfer. The system studied consists of a heat transfer fluid circulating between either of the on-board hot and cold thermal storage units, which we refer to as thermal batteries, and a liquid–air heat exchanger that provides heat exchange with the incoming air to the vehicle cabin. Each thermal battery is a shell-and-tube configuration where a heat transfer fluid flows through parallel tubes, which are surrounded by PCM within a larger shell. The system model incorporates computationally inexpensive semi-analytic solution to the conjugated laminar forced convection and phase change problem within the battery and accounts for airside heat exchange using the Number of Transfer Units (NTUs) method for the liquid–air heat exchanger. Using this approach, we are able to obtain an accurate solution to the complex heat transfer problem within the battery while also incorporating the impact of the airside heat transfer on the overall system performance. The implemented model was benchmarked against a numerical study for a melting process and against full system

  3. A mathematical model for incorporating biofeedback into human postural control

    Directory of Open Access Journals (Sweden)

    Ersal Tulga

    2013-02-01

    Full Text Available Abstract Background Biofeedback of body motion can serve as a balance aid and rehabilitation tool. To date, mathematical models considering the integration of biofeedback into postural control have represented this integration as a sensory addition and limited their application to a single degree-of-freedom representation of the body. This study has two objectives: 1 to develop a scalable method for incorporating biofeedback into postural control that is independent of the model’s degrees of freedom, how it handles sensory integration, and the modeling of its postural controller; and 2 to validate this new model using multidirectional perturbation experimental results. Methods Biofeedback was modeled as an additional torque to the postural controller torque. For validation, this biofeedback modeling approach was applied to a vibrotactile biofeedback device and incorporated into a two-link multibody model with full-state-feedback control that represents the dynamics of bipedal stance. Average response trajectories of body sway and center of pressure (COP to multidirectional surface perturbations of subjects with vestibular deficits were used for model parameterization and validation in multiple perturbation directions and for multiple display resolutions. The quality of fit was quantified using average error and cross-correlation values. Results The mean of the average errors across all tactor configurations and perturbations was 0.24° for body sway and 0.39 cm for COP. The mean of the cross-correlation value was 0.97 for both body sway and COP. Conclusions The biofeedback model developed in this study is capable of capturing experimental response trajectory shapes with low average errors and high cross-correlation values in both the anterior-posterior and medial-lateral directions for all perturbation directions and spatial resolution display configurations considered. The results validate that biofeedback can be modeled as an additional

  4. A mathematical model for incorporating biofeedback into human postural control

    Science.gov (United States)

    2013-01-01

    Background Biofeedback of body motion can serve as a balance aid and rehabilitation tool. To date, mathematical models considering the integration of biofeedback into postural control have represented this integration as a sensory addition and limited their application to a single degree-of-freedom representation of the body. This study has two objectives: 1) to develop a scalable method for incorporating biofeedback into postural control that is independent of the model’s degrees of freedom, how it handles sensory integration, and the modeling of its postural controller; and 2) to validate this new model using multidirectional perturbation experimental results. Methods Biofeedback was modeled as an additional torque to the postural controller torque. For validation, this biofeedback modeling approach was applied to a vibrotactile biofeedback device and incorporated into a two-link multibody model with full-state-feedback control that represents the dynamics of bipedal stance. Average response trajectories of body sway and center of pressure (COP) to multidirectional surface perturbations of subjects with vestibular deficits were used for model parameterization and validation in multiple perturbation directions and for multiple display resolutions. The quality of fit was quantified using average error and cross-correlation values. Results The mean of the average errors across all tactor configurations and perturbations was 0.24° for body sway and 0.39 cm for COP. The mean of the cross-correlation value was 0.97 for both body sway and COP. Conclusions The biofeedback model developed in this study is capable of capturing experimental response trajectory shapes with low average errors and high cross-correlation values in both the anterior-posterior and medial-lateral directions for all perturbation directions and spatial resolution display configurations considered. The results validate that biofeedback can be modeled as an additional torque to the postural

  5. Dynamic process model of a plutonium oxalate precipitator. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Miller, C.L.; Hammelman, J.E.; Borgonovi, G.M.

    1977-11-01

    In support of LLL material safeguards program, a dynamic process model was developed which simulates the performance of a plutonium (IV) oxalate precipitator. The plutonium oxalate precipitator is a component in the plutonium oxalate process for making plutonium oxide powder from plutonium nitrate. The model is based on state-of-the-art crystallization descriptive equations, the parameters of which are quantified through the use of batch experimental data. The dynamic model predicts performance very similar to general Hanford oxalate process experience. The utilization of such a process model in an actual plant operation could promote both process control and material safeguards control by serving as a baseline predictor which could give early warning of process upsets or material diversion. The model has been incorporated into a FORTRAN computer program and is also compatible with the DYNSYS 2 computer code which is being used at LLL for process modeling efforts.

  6. Dynamic process model of a plutonium oxalate precipitator. Final report

    International Nuclear Information System (INIS)

    Miller, C.L.; Hammelman, J.E.; Borgonovi, G.M.

    1977-11-01

    In support of LLL material safeguards program, a dynamic process model was developed which simulates the performance of a plutonium (IV) oxalate precipitator. The plutonium oxalate precipitator is a component in the plutonium oxalate process for making plutonium oxide powder from plutonium nitrate. The model is based on state-of-the-art crystallization descriptive equations, the parameters of which are quantified through the use of batch experimental data. The dynamic model predicts performance very similar to general Hanford oxalate process experience. The utilization of such a process model in an actual plant operation could promote both process control and material safeguards control by serving as a baseline predictor which could give early warning of process upsets or material diversion. The model has been incorporated into a FORTRAN computer program and is also compatible with the DYNSYS 2 computer code which is being used at LLL for process modeling efforts

  7. MO-E-17A-02: Incorporation of Contrast Medium Dynamics in Anthropomorphic Phantoms: The Advent of 5D XCAT Models

    Energy Technology Data Exchange (ETDEWEB)

    Sahbaee, P [NC State University, Raleigh, NC (United States); Samei, E [Duke University Medical Center, Durham, NC (United States); Segars, W [Duke University, Durham, NC (United States)

    2014-06-15

    Purpose: To develop a unique method to incorporate the dynamics of contrast-medium propagation into the anthropomorphic phantom, to generate a five-dimensional (5D) patient model for multimodality imaging studies. Methods: A compartmental model of blood circulation network within the body was embodied into an extended cardiac-torso (4D-XCAT) patient model. To do so, a computational physiologic model of the human cardiovascular system was developed which includes a series of compartments representing heart, vessels, and organs. Patient-specific cardiac output and blood volume were used as inputs influenced by the weight, height, age, and gender of the patient's model. For a given injection protocol and given XCAT model, the contrast-medium transmission within the body was described by a series of mass balance differential equations, the solutions to which provided the contrast enhancement-time curves for each organ; thereby defining the tissue materials including the contrastmedium within the XCAT model. A library of time-dependent organ materials was then defined. Each organ in each voxelized 4D-XCAT phantom was assigned to a corresponding time-varying material to create the 5D-XCAT phantom in which the fifth dimension is blood/contrast-medium within the temporal domain. Results: The model effectively predicts the time-varying concentration behavior of various contrast-medium administration in each organ for different patient models as function of patient size (weight/height) and different injection protocol factors (injection rate and pattern, iodine concentration or volume). The contrast enhanced XCAT patient models was developed based on the concentration of iodine as a function of time after injection. Conclusion: Majority of medical imaging systems take advantage of contrast-medium administration in terms of better image quality, the effect of which was ignored in previous optimization studies. The study enables a comprehensive optimization of contrast

  8. Modeling opinion dynamics: Theoretical analysis and continuous approximation

    International Nuclear Information System (INIS)

    Pinasco, Juan Pablo; Semeshenko, Viktoriya; Balenzuela, Pablo

    2017-01-01

    Highlights: • We study a simple model of persuasion dynamics with long range pairwise interactions. • The continuous limit of the master equation is a nonlinear, nonlocal, first order partial differential equation. • We compute the analytical solutions to this equation, and compare them with the simulations of the dynamics. - Abstract: Frequently we revise our first opinions after talking over with other individuals because we get convinced. Argumentation is a verbal and social process aimed at convincing. It includes conversation and persuasion and the agreement is reached because the new arguments are incorporated. Given the wide range of opinion formation mathematical approaches, there are however no models of opinion dynamics with nonlocal pair interactions analytically solvable. In this paper we present a novel analytical framework developed to solve the master equations with non-local kernels. For this we used a simple model of opinion formation where individuals tend to get more similar after each interactions, no matter their opinion differences, giving rise to nonlinear differential master equation with non-local terms. Simulation results show an excellent agreement with results obtained by the theoretical estimation.

  9. The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

    Directory of Open Access Journals (Sweden)

    Mark G Orr

    Full Text Available The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior, does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence. To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

  10. The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

    Science.gov (United States)

    Orr, Mark G; Thrush, Roxanne; Plaut, David C

    2013-01-01

    The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

  11. An FDTD algorithm for simulation of EM waves propagation in laser with static and dynamic gain models

    KAUST Repository

    Al-Jabr, Ahmad Ali; Alsunaidi, Mohammad A.; Ooi, Boon S.

    2013-01-01

    This paper presents methods of simulating gain media in the finite difference time-domain (FDTD) algorithm utilizing a generalized polarization formulation. The gain can be static or dynamic. For static gain, Lorentzian and non-Lorentzian models are presented and tested. For the dynamic gain, rate equations for two-level and four-level models are incorporated in the FDTD scheme. The simulation results conform with the expected behavior of wave amplification and dynamic population inversion.

  12. A Langevin model for fluctuating contact angle behaviour parametrised using molecular dynamics.

    Science.gov (United States)

    Smith, E R; Müller, E A; Craster, R V; Matar, O K

    2016-12-06

    Molecular dynamics simulations are employed to develop a theoretical model to predict the fluid-solid contact angle as a function of wall-sliding speed incorporating thermal fluctuations. A liquid bridge between counter-sliding walls is studied, with liquid-vapour interface-tracking, to explore the impact of wall-sliding speed on contact angle. The behaviour of the macroscopic contact angle varies linearly over a range of capillary numbers beyond which the liquid bridge pinches off, a behaviour supported by experimental results. Nonetheless, the liquid bridge provides an ideal test case to study molecular scale thermal fluctuations, which are shown to be well described by Gaussian distributions. A Langevin model for contact angle is parametrised to incorporate the mean, fluctuation and auto-correlations over a range of sliding speeds and temperatures. The resulting equations can be used as a proxy for the fully-detailed molecular dynamics simulation allowing them to be integrated within a continuum-scale solver.

  13. ITER Dynamic Tritium Inventory Modeling Code

    International Nuclear Information System (INIS)

    Cristescu, Ioana-R.; Doerr, L.; Busigin, A.; Murdoch, D.

    2005-01-01

    A tool for tritium inventory evaluation within each sub-system of the Fuel Cycle of ITER is vital, with respect to both the process of licensing ITER and also for operation. It is very likely that measurements of total tritium inventories may not be possible for all sub-systems, however tritium accounting may be achieved by modeling its hold-up within each sub-system and by validating these models in real-time against the monitored flows and tritium streams between the systems. To get reliable results, an accurate dynamic modeling of the tritium content in each sub-system is necessary. In order to optimize the configuration and operation of the ITER fuel cycle, a dynamic fuel cycle model was developed progressively in the decade up to 2000-2001. As the design for some sub-systems from the fuel cycle (i.e. Vacuum pumping, Neutral Beam Injectors (NBI)) have substantially progressed meanwhile, a new code developed under a different platform to incorporate these modifications has been developed. The new code is taking over the models and algorithms for some subsystems, such as Isotope Separation System (ISS); where simplified models have been previously considered, more detailed have been introduced, as for the Water Detritiation System (WDS). To reflect all these changes, the new code developed inside EU participating team was nominated TRIMO (Tritium Inventory Modeling), to emphasize the use of the code on assessing the tritium inventory within ITER

  14. Comparison of joint modeling and landmarking for dynamic prediction under an illness-death model.

    Science.gov (United States)

    Suresh, Krithika; Taylor, Jeremy M G; Spratt, Daniel E; Daignault, Stephanie; Tsodikov, Alexander

    2017-11-01

    Dynamic prediction incorporates time-dependent marker information accrued during follow-up to improve personalized survival prediction probabilities. At any follow-up, or "landmark", time, the residual time distribution for an individual, conditional on their updated marker values, can be used to produce a dynamic prediction. To satisfy a consistency condition that links dynamic predictions at different time points, the residual time distribution must follow from a prediction function that models the joint distribution of the marker process and time to failure, such as a joint model. To circumvent the assumptions and computational burden associated with a joint model, approximate methods for dynamic prediction have been proposed. One such method is landmarking, which fits a Cox model at a sequence of landmark times, and thus is not a comprehensive probability model of the marker process and the event time. Considering an illness-death model, we derive the residual time distribution and demonstrate that the structure of the Cox model baseline hazard and covariate effects under the landmarking approach do not have simple form. We suggest some extensions of the landmark Cox model that should provide a better approximation. We compare the performance of the landmark models with joint models using simulation studies and cognitive aging data from the PAQUID study. We examine the predicted probabilities produced under both methods using data from a prostate cancer study, where metastatic clinical failure is a time-dependent covariate for predicting death following radiation therapy. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Framework for optimal power flow incorporating dynamic system security

    International Nuclear Information System (INIS)

    El-Kady, M.A.; Owayedh, M.S.

    2006-01-01

    This paper introduces a novel framework and methodologies which are capable of tackling the complex issue of power system economy versus security in a practical and effective manner. At heart of achieving such a challenging and far-reaching objective is the incorporation of the Dyanamic Security Assessment (DSA) into production optimization techniques using the Transient Energy Function (TEF) method. In addition, and in parallel with the already well established concept of the system security, two new concepts pertaining to power system performance will be introduced in this paper, namely the concept of system dynamic susceptibility, which measures the level of systems weakness to a particular contingency and the concept of system consequent restorability, which measures the extent of contingency severity in terms of the required subsequent system restoration work should a particular contingency occur. (author)

  16. Progress and problems in modelling HTR core dynamics

    International Nuclear Information System (INIS)

    Scherer, W.; Gerwin, H.

    1991-01-01

    In recent years greater effort has been made to establish theoretical models for HTR core dynamics. At KFA Juelich the TINTE (TIme dependent Neutronics and TEmperatures) code system has been developed, which is able to model the primary circuit of an HTR plant using modern numerical techniques and taking into account the mutual interference of the relevant physical variables. The HTR core is treated in 2-D R-Z geometry for both nucleonics and thermo-fluid-dynamics. 2-energy-group diffusion theory is used in the nuclear part including 6 groups of delayed neutron precursors and 14 groups of decay heat producers. Local and non-local heat sources are incorporated, thus simulating gamma ray transport. The thermo-fluid-dynamics module accounts for heterogeneity effects due to the pebble bed structure. Pipes and other components of the primary loop are modelled in 1-D geometry. Forced convection may be treated as well as natural convection in case of blower breakdown accidents. Validation of TINTE has started using the results of a comprehensive experimental program that has been performed at the Arbeitsgemeinschaft Versuchsreaktor GmbH (AVR) high temperature pebble bed reactor at Juelich. In the frame of this program power transients were initiated by varying the helium blower rotational speed or by moving the control rods. In most cases a good accordance between experiment and calculation was found. Problems in modelling the special AVR reactor geometry in two dimensions are described and suggestions for overcoming the uncertainties of experimentally determined control rod reactivities are given. The influence of different polynomial expansions of xenon cross sections to long term transients is discussed together with effects of burnup during that time. Up to now the TINTE code has proven its general applicability to operational core transients of HTR. The effects of water ingress on reactivity, fuel element corrosion and cooling gas properties are now being

  17. Stability of a general delayed virus dynamics model with humoral immunity and cellular infection

    Science.gov (United States)

    Elaiw, A. M.; Raezah, A. A.; Alofi, A. S.

    2017-06-01

    In this paper, we investigate the dynamical behavior of a general nonlinear model for virus dynamics with virus-target and infected-target incidences. The model incorporates humoral immune response and distributed time delays. The model is a four dimensional system of delay differential equations where the production and removal rates of the virus and cells are given by general nonlinear functions. We derive the basic reproduction parameter R˜0 G and the humoral immune response activation number R˜1 G and establish a set of conditions on the general functions which are sufficient to determine the global dynamics of the models. We use suitable Lyapunov functionals and apply LaSalle's invariance principle to prove the global asymptotic stability of the all equilibria of the model. We confirm the theoretical results by numerical simulations.

  18. Estimation of Dynamic Panel Data Models with Stochastic Volatility Using Particle Filters

    Directory of Open Access Journals (Sweden)

    Wen Xu

    2016-10-01

    Full Text Available Time-varying volatility is common in macroeconomic data and has been incorporated into macroeconomic models in recent work. Dynamic panel data models have become increasingly popular in macroeconomics to study common relationships across countries or regions. This paper estimates dynamic panel data models with stochastic volatility by maximizing an approximate likelihood obtained via Rao-Blackwellized particle filters. Monte Carlo studies reveal the good and stable performance of our particle filter-based estimator. When the volatility of volatility is high, or when regressors are absent but stochastic volatility exists, our approach can be better than the maximum likelihood estimator which neglects stochastic volatility and generalized method of moments (GMM estimators.

  19. Robust and efficient parameter estimation in dynamic models of biological systems.

    Science.gov (United States)

    Gábor, Attila; Banga, Julio R

    2015-10-29

    Dynamic modelling provides a systematic framework to understand function in biological systems. Parameter estimation in nonlinear dynamic models remains a very challenging inverse problem due to its nonconvexity and ill-conditioning. Associated issues like overfitting and local solutions are usually not properly addressed in the systems biology literature despite their importance. Here we present a method for robust and efficient parameter estimation which uses two main strategies to surmount the aforementioned difficulties: (i) efficient global optimization to deal with nonconvexity, and (ii) proper regularization methods to handle ill-conditioning. In the case of regularization, we present a detailed critical comparison of methods and guidelines for properly tuning them. Further, we show how regularized estimations ensure the best trade-offs between bias and variance, reducing overfitting, and allowing the incorporation of prior knowledge in a systematic way. We illustrate the performance of the presented method with seven case studies of different nature and increasing complexity, considering several scenarios of data availability, measurement noise and prior knowledge. We show how our method ensures improved estimations with faster and more stable convergence. We also show how the calibrated models are more generalizable. Finally, we give a set of simple guidelines to apply this strategy to a wide variety of calibration problems. Here we provide a parameter estimation strategy which combines efficient global optimization with a regularization scheme. This method is able to calibrate dynamic models in an efficient and robust way, effectively fighting overfitting and allowing the incorporation of prior information.

  20. True dose from incorporated activities. Models for internal dosimetry

    International Nuclear Information System (INIS)

    Breustedt, B.; Eschner, W.; Nosske, D.

    2012-01-01

    The assessment of doses after incorporation of radionuclides cannot use direct measurements of the doses, as for example dosimetry in external radiation fields. The only observables are activities in the body or in excretions. Models are used to calculate the doses based on the measured activities. The incorporated activities and the resulting doses can vary by more than seven orders of magnitude between occupational and medical exposures. Nevertheless the models and calculations applied in both cases are similar. Since the models for the different applications have been developed independently by ICRP and MIRD different terminologies have been used. A unified terminology is being developed. (orig.)

  1. The importance of incorporating functional habitats into conservation planning for highly mobile species in dynamic systems.

    Science.gov (United States)

    Webb, Matthew H; Terauds, Aleks; Tulloch, Ayesha; Bell, Phil; Stojanovic, Dejan; Heinsohn, Robert

    2017-10-01

    The distribution of mobile species in dynamic systems can vary greatly over time and space. Estimating their population size and geographic range can be problematic and affect the accuracy of conservation assessments. Scarce data on mobile species and the resources they need can also limit the type of analytical approaches available to derive such estimates. We quantified change in availability and use of key ecological resources required for breeding for a critically endangered nomadic habitat specialist, the Swift Parrot (Lathamus discolor). We compared estimates of occupied habitat derived from dynamic presence-background (i.e., presence-only data) climatic models with estimates derived from dynamic occupancy models that included a direct measure of food availability. We then compared estimates that incorporate fine-resolution spatial data on the availability of key ecological resources (i.e., functional habitats) with more common approaches that focus on broader climatic suitability or vegetation cover (due to the absence of fine-resolution data). The occupancy models produced significantly (P increase or decrease in the area of one functional habitat (foraging or nesting) did not necessarily correspond to an increase or decrease in the other. Thus, an increase in the extent of occupied area may not equate to improved habitat quality or function. We argue these patterns are typical for mobile resource specialists but often go unnoticed because of limited data over relevant spatial and temporal scales and lack of spatial data on the availability of key resources. Understanding changes in the relative availability of functional habitats is crucial to informing conservation planning and accurately assessing extinction risk for mobile resource specialists. © 2017 Society for Conservation Biology.

  2. Equivalent Dynamic Models.

    Science.gov (United States)

    Molenaar, Peter C M

    2017-01-01

    Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.

  3. Incorporating interfacial phenomena in solidification models

    Science.gov (United States)

    Beckermann, Christoph; Wang, Chao Yang

    1994-01-01

    A general methodology is available for the incorporation of microscopic interfacial phenomena in macroscopic solidification models that include diffusion and convection. The method is derived from a formal averaging procedure and a multiphase approach, and relies on the presence of interfacial integrals in the macroscopic transport equations. In a wider engineering context, these techniques are not new, but their application in the analysis and modeling of solidification processes has largely been overlooked. This article describes the techniques and demonstrates their utility in two examples in which microscopic interfacial phenomena are of great importance.

  4. High-Strain Rate Failure Modeling Incorporating Shear Banding and Fracture

    Science.gov (United States)

    2017-11-22

    High Strain Rate Failure Modeling Incorporating Shear Banding and Fracture The views, opinions and/or findings contained in this report are those of...SECURITY CLASSIFICATION OF: 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13. SUPPLEMENTARY NOTES 12. DISTRIBUTION AVAILIBILITY STATEMENT 6. AUTHORS...Report as of 05-Dec-2017 Agreement Number: W911NF-13-1-0238 Organization: Columbia University Title: High Strain Rate Failure Modeling Incorporating

  5. Energy system investment model incorporating heat pumps with thermal storage in buildings and buffer tanks

    DEFF Research Database (Denmark)

    Hedegaard, Karsten; Balyk, Olexandr

    2013-01-01

    Individual compression heat pumps constitute a potentially valuable resource in supporting wind power integration due to their economic competitiveness and possibilities for flexible operation. When analysing the system benefits of flexible heat pump operation, effects on investments should...... be taken into account. In this study, we present a model that facilitates analysing individual heat pumps and complementing heat storages in integration with the energy system, while optimising both investments and operation. The model incorporates thermal building dynamics and covers various heat storage...... of operating heat pumps flexibly. This includes prioritising heat pump operation for hours with low marginal electricity production costs, and peak load shaving resulting in a reduced need for peak and reserve capacity investments....

  6. At the Frontiers of Modeling Intensive Longitudinal Data: Dynamic Structural Equation Models for the Affective Measurements from the COGITO Study.

    Science.gov (United States)

    Hamaker, E L; Asparouhov, T; Brose, A; Schmiedek, F; Muthén, B

    2018-04-06

    With the growing popularity of intensive longitudinal research, the modeling techniques and software options for such data are also expanding rapidly. Here we use dynamic multilevel modeling, as it is incorporated in the new dynamic structural equation modeling (DSEM) toolbox in Mplus, to analyze the affective data from the COGITO study. These data consist of two samples of over 100 individuals each who were measured for about 100 days. We use composite scores of positive and negative affect and apply a multilevel vector autoregressive model to allow for individual differences in means, autoregressions, and cross-lagged effects. Then we extend the model to include random residual variances and covariance, and finally we investigate whether prior depression affects later depression scores through the random effects of the daily diary measures. We end with discussing several urgent-but mostly unresolved-issues in the area of dynamic multilevel modeling.

  7. Development of Dynamic Environmental Effect Calculation Model

    International Nuclear Information System (INIS)

    Jeong, Chang Joon; Ko, Won Il

    2010-01-01

    The short-term, long-term decay heat, and radioactivity are considered as main environmental parameters of SF and HLA. In this study, the dynamic calculation models for radioactivity, short-term decay heat, and long-term heat load of the SF are developed and incorporated into the Doneness code. The spent fuel accumulation has become a major issue for sustainable operation of nuclear power plants. If a once-through fuel cycle is selected, the SF will be disposed into the repository. Otherwise, in case of fast reactor or reuse cycle, the SF will be reprocessed and the high level waste will be disposed

  8. Modelling the influence of sensory dynamics on linear and nonlinear driver steering control

    Science.gov (United States)

    Nash, C. J.; Cole, D. J.

    2018-05-01

    A recent review of the literature has indicated that sensory dynamics play an important role in the driver-vehicle steering task, motivating the design of a new driver model incorporating human sensory systems. This paper presents a full derivation of the linear driver model developed in previous work, and extends the model to control a vehicle with nonlinear tyres. Various nonlinear controllers and state estimators are compared with different approximations of the true system dynamics. The model simulation time is found to increase significantly with the complexity of the controller and state estimator. In general the more complex controllers perform best, although with certain vehicle and tyre models linearised controllers perform as well as a full nonlinear optimisation. Various extended Kalman filters give similar results, although the driver's sensory dynamics reduce control performance compared with full state feedback. The new model could be used to design vehicle systems which interact more naturally and safely with a human driver.

  9. A general science-based framework for dynamical spatio-temporal models

    Science.gov (United States)

    Wikle, C.K.; Hooten, M.B.

    2010-01-01

    Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic

  10. Incorporating intelligence into structured radiology reports

    Science.gov (United States)

    Kahn, Charles E.

    2014-03-01

    The new standard for radiology reporting templates being developed through the Integrating the Healthcare Enterprise (IHE) and DICOM organizations defines the storage and exchange of reporting templates as Hypertext Markup Language version 5 (HTML5) documents. The use of HTML5 enables the incorporation of "dynamic HTML," in which documents can be altered in response to their content. HTML5 documents can employ JavaScript, the HTML Document Object Model (DOM), and external web services to create intelligent reporting templates. Several reporting templates were created to demonstrate the use of scripts to perform in-template calculations and decision support. For example, a template for adrenal CT was created to compute contrast washout percentage from input values of precontrast, dynamic postcontrast, and delayed adrenal nodule attenuation values; the washout value can used to classify an adrenal nodule as a benign cortical adenoma. Dynamic templates were developed to compute volumes and apply diagnostic criteria, such as those for determination of internal carotid artery stenosis. Although reporting systems need not use a web browser to render the templates or their contents, the use of JavaScript creates innumerable opportunities to construct highly sophisticated HTML5 reporting templates. This report demonstrates the ability to incorporate dynamic content to enhance the use of radiology reporting templates.

  11. Hpm of Estrogen Model on the Dynamics of Breast Cancer

    Science.gov (United States)

    Govindarajan, A.; Balamuralitharan, S.; Sundaresan, T.

    2018-04-01

    We enhance a deterministic mathematical model involving universal dynamics on breast cancer with immune response. This is population model so includes Normal cells class, Tumor cells, Immune cells and Estrogen. The eects regarding Estrogen are below incorporated in the model. The effects show to that amount the arrival of greater Estrogen increases the danger over growing breast cancer. Furthermore, approximate solution regarding nonlinear differential equations is arrived by Homotopy Perturbation Method (HPM). Hes HPM is good and correct technique after solve nonlinear differential equation directly. Approximate solution learnt with the support of that method is suitable same as like the actual results in accordance with this models.

  12. Dynamics and Collapse in a Power System Model with Voltage Variation: The Damping Effect.

    Science.gov (United States)

    Ma, Jinpeng; Sun, Yong; Yuan, Xiaoming; Kurths, Jürgen; Zhan, Meng

    2016-01-01

    Complex nonlinear phenomena are investigated in a basic power system model of the single-machine-infinite-bus (SMIB) with a synchronous generator modeled by a classical third-order differential equation including both angle dynamics and voltage dynamics, the so-called flux decay equation. In contrast, for the second-order differential equation considering the angle dynamics only, it is the classical swing equation. Similarities and differences of the dynamics generated between the third-order model and the second-order one are studied. We mainly find that, for positive damping, these two models show quite similar behavior, namely, stable fixed point, stable limit cycle, and their coexistence for different parameters. However, for negative damping, the second-order system can only collapse, whereas for the third-order model, more complicated behavior may happen, such as stable fixed point, limit cycle, quasi-periodicity, and chaos. Interesting partial collapse phenomena for angle instability only and not for voltage instability are also found here, including collapse from quasi-periodicity and from chaos etc. These findings not only provide a basic physical picture for power system dynamics in the third-order model incorporating voltage dynamics, but also enable us a deeper understanding of the complex dynamical behavior and even leading to a design of oscillation damping in electric power systems.

  13. Incorporation of fractional-order dynamics into an existing PI/PID DC motor control loop.

    Science.gov (United States)

    Tepljakov, Aleksei; Gonzalez, Emmanuel A; Petlenkov, Eduard; Belikov, Juri; Monje, Concepción A; Petráš, Ivo

    2016-01-01

    The problem of changing the dynamics of an existing DC motor control system without the need of making internal changes is considered in the paper. In particular, this paper presents a method for incorporating fractional-order dynamics in an existing DC motor control system with internal PI or PID controller, through the addition of an external controller into the system and by tapping its original input and output signals. Experimental results based on the control of a real test plant from MATLAB/Simulink environment are presented, indicating the validity of the proposed approach. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  14. A Non-Isothermal Chemical Lattice Boltzmann Model Incorporating Thermal Reaction Kinetics and Enthalpy Changes

    Directory of Open Access Journals (Sweden)

    Stuart Bartlett

    2017-08-01

    Full Text Available The lattice Boltzmann method is an efficient computational fluid dynamics technique that can accurately model a broad range of complex systems. As well as single-phase fluids, it can simulate thermohydrodynamic systems and passive scalar advection. In recent years, it also gained attention as a means of simulating chemical phenomena, as interest in self-organization processes increased. This paper will present a widely-used and versatile lattice Boltzmann model that can simultaneously incorporate fluid dynamics, heat transfer, buoyancy-driven convection, passive scalar advection, chemical reactions and enthalpy changes. All of these effects interact in a physically accurate framework that is simple to code and readily parallelizable. As well as a complete description of the model equations, several example systems will be presented in order to demonstrate the accuracy and versatility of the method. New simulations, which analyzed the effect of a reversible reaction on the transport properties of a convecting fluid, will also be described in detail. This extra chemical degree of freedom was utilized by the system to augment its net heat flux. The numerical method outlined in this paper can be readily deployed for a vast range of complex flow problems, spanning a variety of scientific disciplines.

  15. Incorporating the life course model into MCH nutrition leadership education and training programs.

    Science.gov (United States)

    Haughton, Betsy; Eppig, Kristen; Looney, Shannon M; Cunningham-Sabo, Leslie; Spear, Bonnie A; Spence, Marsha; Stang, Jamie S

    2013-01-01

    Life course perspective, social determinants of health, and health equity have been combined into one comprehensive model, the life course model (LCM), for strategic planning by US Health Resources and Services Administration's Maternal and Child Health Bureau. The purpose of this project was to describe a faculty development process; identify strategies for incorporation of the LCM into nutrition leadership education and training at the graduate and professional levels; and suggest broader implications for training, research, and practice. Nineteen representatives from 6 MCHB-funded nutrition leadership education and training programs and 10 federal partners participated in a one-day session that began with an overview of the models and concluded with guided small group discussions on how to incorporate them into maternal and child health (MCH) leadership training using obesity as an example. Written notes from group discussions were compiled and coded emergently. Content analysis determined the most salient themes about incorporating the models into training. Four major LCM-related themes emerged, three of which were about training: (1) incorporation by training grants through LCM-framed coursework and experiences for trainees, and similarly framed continuing education and skills development for professionals; (2) incorporation through collaboration with other training programs and state and community partners, and through advocacy; and (3) incorporation by others at the federal and local levels through policy, political, and prevention efforts. The fourth theme focused on anticipated challenges of incorporating the model in training. Multiple methods for incorporating the LCM into MCH training and practice are warranted. Challenges to incorporating include the need for research and related policy development.

  16. Modeling capillary bridge dynamics and crack healing between surfaces of nanoscale roughness

    Science.gov (United States)

    Soylemez, Emrecan; de Boer, Maarten P.

    2017-12-01

    Capillary bridge formation between adjacent surfaces in humid environments is a ubiquitous phenomenon. It strongly influences tribological performance with respect to adhesion, friction and wear. Only a few studies, however, assess effects due to capillary dynamics. Here we focus on how capillary bridge evolution influences crack healing rates. Experimental results indicated a logarithmic decrease in average crack healing velocity as the energy release rate increases. Our objective is to model that trend. We assume that capillary dynamics involve two mechanisms: capillary bridge growth and subsequently nucleation followed by growth. We show that by incorporating interface roughness details and the presence of an adsorbed water layer, the behavior of capillary force dynamics can be understood quantitatively. We identify three important regimes that control the healing process, namely bridge growth, combined bridge growth and nucleation, and finally bridge nucleation. To fully capture the results, however, the theoretical model for nucleation time required an empirical modification. Our model enables significant insight into capillary bridge dynamics, with a goal of attaining a predictive capability for this important microelectromechanical systems (MEMS) reliability failure mechanism.

  17. Incorporating Daily Flood Control Objectives Into a Monthly Stochastic Dynamic Programing Model for a Hydroelectric Complex

    Science.gov (United States)

    Druce, Donald J.

    1990-01-01

    A monthly stochastic dynamic programing model was recently developed and implemented at British Columbia (B.C.) Hydro to provide decision support for short-term energy exports and, if necessary, for flood control on the Peace River in northern British Columbia. The model establishes the marginal cost of supplying energy from the B.C. Hydro system, as well as a monthly operating policy for the G.M. Shrum and Peace Canyon hydroelectric plants and the Williston Lake storage reservoir. A simulation model capable of following the operating policy then determines the probability of refilling Williston Lake and possible spill rates and volumes. Reservoir inflows are input to both models in daily and monthly formats. The results indicate that flood control can be accommodated without sacrificing significant export revenue.

  18. Incorporating daily flood control objectives into a monthly stochastic dynamic programming model for a hydroelectric complex

    Energy Technology Data Exchange (ETDEWEB)

    Druce, D.J. (British Columbia Hydro and Power Authority, Vancouver, British Columbia (Canada))

    1990-01-01

    A monthly stochastic dynamic programing model was recently developed and implemented at British Columbia (B.C.) Hydro to provide decision support for short-term energy exports and, if necessary, for flood control on the Peace River in northern British Columbia. The model established the marginal cost of supplying energy from the B.C. Hydro system, as well as a monthly operating policy for the G.M. Shrum and Peace Canyon hydroelectric plants and the Williston Lake storage reservoir. A simulation model capable of following the operating policy then determines the probability of refilling Williston Lake and possible spill rates and volumes. Reservoir inflows are input to both models in daily and monthly formats. The results indicate that flood control can be accommodated without sacrificing significant export revenue.

  19. Development of Dynamic Spent Nuclear Fuel Environmental Effect Analysis Model

    International Nuclear Information System (INIS)

    Jeong, Chang Joon; Ko, Won Il; Lee, Ho Hee; Cho, Dong Keun; Park, Chang Je

    2010-07-01

    The dynamic environmental effect evaluation model for spent nuclear fuel has been developed and incorporated into the system dynamic DANESS code. First, the spent nuclear fuel isotope decay model was modeled. Then, the environmental effects were modeled through short-term decay heat model, short-term radioactivity model, and long-term heat load model. By using the developed model, the Korean once-through nuclear fuel cycles was analyzed. The once-through fuel cycle analysis was modeled based on the Korean 'National Energy Basic Plan' up to 2030 and a postulated nuclear demand growth rate until 2150. From the once-through results, it is shown that the nuclear power demand would be ∼70 GWe and the total amount of the spent fuel accumulated by 2150 would be ∼168000 t. If the disposal starts from 2060, the short-term decay heat of Cs-137 and Sr-90 isotopes are W and 1.8x10 6 W in 2100. Also, the total long-term heat load in 2100 will be 4415 MW-y. From the calculation results, it was found that the developed model is very convenient and simple for evaluation of the environmental effect of the spent nuclear fuel

  20. 75 FR 20265 - Airworthiness Directives; Liberty Aerospace Incorporated Model XL-2 Airplanes

    Science.gov (United States)

    2010-04-19

    ... Office, 1701 Columbia Avenue, College Park, Georgia 30337; telephone: (404) 474-5524; facsimile: (404... Airworthiness Directives; Liberty Aerospace Incorporated Model XL-2 Airplanes AGENCY: Federal Aviation...-08- 05, which applies to certain Liberty Aerospace Incorporated Model XL-2 airplanes. AD 2009-08-05...

  1. A new modified resource budget model for nonlinear dynamics in citrus production

    International Nuclear Information System (INIS)

    Ye, Xujun; Sakai, Kenshi

    2016-01-01

    Highlights: • A theoretical modeling and simulation study of the nonlinear dynamics in citrus is conducted. • New leaf growth is incorporated into the model as a major factor responsible for the yield oscillations. • A Ricker-type equation for the relationship between costs for flowering and fruiting is proposed. • A generic form of the resource budget model for the nonlinear dynamics in citrus is obtained. • The new model is tested with experimental data for two citrus trees. - Abstract : Alternate bearing or masting is a general yield variability phenomenon in perennial tree crops. This paper first presents a theoretical modeling and simulation study of the mechanism for this dynamics in citrus, and then provides a test of the proposed models using data from a previous 16-year experiment in a citrus orchard. Our previous studies suggest that the mutual effects between vegetative and reproductive growths caused by resource allocation and budgeting in plant body might be considered as a major factor responsible for the yield oscillations in citrus. Based on the resource budget model proposed by Isagi et al. (J Theor Biol. 1997;187:231-9), we first introduce the new leaf growth as a major energy consumption component into the model. Further, we introduce a nonlinear Ricker-type equation to replace the linear relationship between costs for flowering and fruiting used in Isagi's model. Model simulations demonstrate that the proposed new models can successfully simulate the reproductive behaviors of citrus trees with different fruiting dynamics. These results may enrich the mechanical dynamics in tree crop reproductive models and help us to better understand the dynamics of vegetative-reproductive growth interactions in a real environment.

  2. Dynamics of an HBV/HCV infection model with intracellular delay and cell proliferation

    Science.gov (United States)

    Zhang, Fengqin; Li, Jianquan; Zheng, Chongwu; Wang, Lin

    2017-01-01

    A new mathematical model of hepatitis B/C virus (HBV/HCV) infection which incorporates the proliferation of healthy hepatocyte cells and the latent period of infected hepatocyte cells is proposed and studied. The dynamics is analyzed via Pontryagin's method and a newly proposed alternative geometric stability switch criterion. Sharp conditions ensuring stability of the infection persistent equilibrium are derived by applying Pontryagin's method. Using the intracellular delay as the bifurcation parameter and applying an alternative geometric stability switch criterion, we show that the HBV/HCV infection model undergoes stability switches. Furthermore, numerical simulations illustrate that the intracellular delay can induce complex dynamics such as persistence bubbles and chaos.

  3. Development of an end-of-life vehicle recovery model using system dynamics and future research needs

    Science.gov (United States)

    Mohamad-Ali, N.; Ghazilla, R. A. R.; Abdul-Rashid, S. H.; Sakundarini, N.; Ahmad-Yazid, A.; Stephenie, L.

    2017-06-01

    The implementation of end-of-life vehicle (ELV) recovery policy in Malaysia has led vehicle manufacturers to look at different ways to improve design and development of vehicles. Nowadays, it is crucial to incorporate end-of-life (EOL) design strategies into the vehicle design in order to enhance the effectiveness of the ELV recovery network. Although recent studies have shown that product design has a significant effect on the product recovery rate, there is a lack of studies on how EOL design strategies affects the effectiveness of ELV recovery, particularly when there are dynamic changes in the behaviour of the product recovery network. Thus, in this study, we developed a preliminary model based on the system dynamics approach in order to predict the effectiveness of ELV recovery in response to dynamic changes of various factors (including EOL design strategies) in the business environment. We developed this model based on preliminary data that we had gathered from unstructured interviews with the key stakeholders of ELV management in Malaysia. We believe that our model will greatly benefit product designers in incorporating the appropriate EOL design strategies in order to boost ELV recovery effectiveness in Malaysia.

  4. Integrating count and detection–nondetection data to model population dynamics

    Science.gov (United States)

    Zipkin, Elise F.; Rossman, Sam; Yackulic, Charles B.; Wiens, David; Thorson, James T.; Davis, Raymond J.; Grant, Evan H. Campbell

    2017-01-01

    There is increasing need for methods that integrate multiple data types into a single analytical framework as the spatial and temporal scale of ecological research expands. Current work on this topic primarily focuses on combining capture–recapture data from marked individuals with other data types into integrated population models. Yet, studies of species distributions and trends often rely on data from unmarked individuals across broad scales where local abundance and environmental variables may vary. We present a modeling framework for integrating detection–nondetection and count data into a single analysis to estimate population dynamics, abundance, and individual detection probabilities during sampling. Our dynamic population model assumes that site-specific abundance can change over time according to survival of individuals and gains through reproduction and immigration. The observation process for each data type is modeled by assuming that every individual present at a site has an equal probability of being detected during sampling processes. We examine our modeling approach through a series of simulations illustrating the relative value of count vs. detection–nondetection data under a variety of parameter values and survey configurations. We also provide an empirical example of the model by combining long-term detection–nondetection data (1995–2014) with newly collected count data (2015–2016) from a growing population of Barred Owl (Strix varia) in the Pacific Northwest to examine the factors influencing population abundance over time. Our model provides a foundation for incorporating unmarked data within a single framework, even in cases where sampling processes yield different detection probabilities. This approach will be useful for survey design and to researchers interested in incorporating historical or citizen science data into analyses focused on understanding how demographic rates drive population abundance.

  5. A stochastic agent-based model of pathogen propagation in dynamic multi-relational social networks

    Science.gov (United States)

    Khan, Bilal; Dombrowski, Kirk; Saad, Mohamed

    2015-01-01

    We describe a general framework for modeling and stochastic simulation of epidemics in realistic dynamic social networks, which incorporates heterogeneity in the types of individuals, types of interconnecting risk-bearing relationships, and types of pathogens transmitted across them. Dynamism is supported through arrival and departure processes, continuous restructuring of risk relationships, and changes to pathogen infectiousness, as mandated by natural history; dynamism is regulated through constraints on the local agency of individual nodes and their risk behaviors, while simulation trajectories are validated using system-wide metrics. To illustrate its utility, we present a case study that applies the proposed framework towards a simulation of HIV in artificial networks of intravenous drug users (IDUs) modeled using data collected in the Social Factors for HIV Risk survey. PMID:25859056

  6. Analyzing, Modeling, and Simulation for Human Dynamics in Social Network

    Directory of Open Access Journals (Sweden)

    Yunpeng Xiao

    2012-01-01

    Full Text Available This paper studies the human behavior in the top-one social network system in China (Sina Microblog system. By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time obeys power law distribution both at individual level and at group level. Statistical analysis also reveals that human behavior in social network is mainly driven by four basic elements: social pressure, social identity, social participation, and social relation between individuals. Empirical results present the four elements' impact on the human behavior and the relation between these elements. To further understand the mechanism of such dynamic phenomena, a hybrid human dynamic model which combines “interest” of individual and “interaction” among people is introduced, incorporating the four elements simultaneously. To provide a solid evaluation, we simulate both two-agent and multiagent interactions with real-life social network topology. We achieve the consistent results between empirical studies and the simulations. The model can provide a good understanding of human dynamics in social network.

  7. Ab Initio Molecular Dynamics of Uranium Incorporated in Goethite (α-FeOOH): Interpretation of X-ray Absorption Spectroscopy of Trace Polyvalent Metals.

    Science.gov (United States)

    Kerisit, Sebastien; Bylaska, Eric J; Massey, Michael S; McBriarty, Martin E; Ilton, Eugene S

    2016-11-21

    Incorporation of economically or environmentally consequential polyvalent metals into iron (oxyhydr)oxides has applications in environmental chemistry, remediation, and materials science. A primary tool for characterizing the local coordination environment of such metals, and therefore building models to predict their behavior, is extended X-ray absorption fine structure spectroscopy (EXAFS). Accurate structural information can be lacking yet is required to constrain and inform data interpretation. In this regard, ab initio molecular dynamics (AIMD) was used to calculate the local coordination environment of minor amounts of U incorporated in the structure of goethite (α-FeOOH). U oxidation states (VI, V, and IV) and charge compensation schemes were varied. Simulated trajectories were used to calculate the U L III -edge EXAFS function and fit experimental EXAFS data for U incorporated into goethite under reducing conditions. Calculations that closely matched the U EXAFS of the well-characterized mineral uraninite (UO 2 ), and constrained the S 0 2 parameter to be 0.909, validated the approach. The results for the U-goethite system indicated that U(V) substituted for structural Fe(III) in octahedral uranate coordination. Charge balance was achieved by the loss of one structural proton coupled to addition of one electron into the solid (-1 H + , +1 e - ). The ability of AIMD to model higher energy states thermally accessible at room temperature is particularly relevant for protonated systems such as goethite, where proton transfers between adjacent octahedra had a dramatic effect on the calculated EXAFS. Vibrational effects as a function of temperature were also estimated using AIMD, allowing separate quantification of thermal and configurational disorder. In summary, coupling AIMD structural modeling and EXAFS experiments enables modeling of the redox behavior of polyvalent metals that are incorporated in conductive materials such as iron (oxyhydr)oxides, with

  8. ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.

    Science.gov (United States)

    Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

    2017-07-20

    Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.

  9. Dynamic simulation of knee-joint loading during gait using force-feedback control and surrogate contact modelling.

    Science.gov (United States)

    Walter, Jonathan P; Pandy, Marcus G

    2017-10-01

    The aim of this study was to perform multi-body, muscle-driven, forward-dynamics simulations of human gait using a 6-degree-of-freedom (6-DOF) model of the knee in tandem with a surrogate model of articular contact and force control. A forward-dynamics simulation incorporating position, velocity and contact force-feedback control (FFC) was used to track full-body motion capture data recorded for multiple trials of level walking and stair descent performed by two individuals with instrumented knee implants. Tibiofemoral contact force errors for FFC were compared against those obtained from a standard computed muscle control algorithm (CMC) with a 6-DOF knee contact model (CMC6); CMC with a 1-DOF translating hinge-knee model (CMC1); and static optimization with a 1-DOF translating hinge-knee model (SO). Tibiofemoral joint loads predicted by FFC and CMC6 were comparable for level walking, however FFC produced more accurate results for stair descent. SO yielded reasonable predictions of joint contact loading for level walking but significant differences between model and experiment were observed for stair descent. CMC1 produced the least accurate predictions of tibiofemoral contact loads for both tasks. Our findings suggest that reliable estimates of knee-joint loading may be obtained by incorporating position, velocity and force-feedback control with a multi-DOF model of joint contact in a forward-dynamics simulation of gait. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

  10. Aggregated Residential Load Modeling Using Dynamic Bayesian Networks

    Energy Technology Data Exchange (ETDEWEB)

    Vlachopoulou, Maria; Chin, George; Fuller, Jason C.; Lu, Shuai

    2014-09-28

    Abstract—It is already obvious that the future power grid will have to address higher demand for power and energy, and to incorporate renewable resources of different energy generation patterns. Demand response (DR) schemes could successfully be used to manage and balance power supply and demand under operating conditions of the future power grid. To achieve that, more advanced tools for DR management of operations and planning are necessary that can estimate the available capacity from DR resources. In this research, a Dynamic Bayesian Network (DBN) is derived, trained, and tested that can model aggregated load of Heating, Ventilation, and Air Conditioning (HVAC) systems. DBNs can provide flexible and powerful tools for both operations and planing, due to their unique analytical capabilities. The DBN model accuracy and flexibility of use is demonstrated by testing the model under different operational scenarios.

  11. Stochastic Wilson–Cowan models of neuronal network dynamics with memory and delay

    International Nuclear Information System (INIS)

    Goychuk, Igor; Goychuk, Andriy

    2015-01-01

    We consider a simple Markovian class of the stochastic Wilson–Cowan type models of neuronal network dynamics, which incorporates stochastic delay caused by the existence of a refractory period of neurons. From the point of view of the dynamics of the individual elements, we are dealing with a network of non-Markovian stochastic two-state oscillators with memory, which are coupled globally in a mean-field fashion. This interrelation of a higher-dimensional Markovian and lower-dimensional non-Markovian dynamics is discussed in its relevance to the general problem of the network dynamics of complex elements possessing memory. The simplest model of this class is provided by a three-state Markovian neuron with one refractory state, which causes firing delay with an exponentially decaying memory within the two-state reduced model. This basic model is used to study critical avalanche dynamics (the noise sustained criticality) in a balanced feedforward network consisting of the excitatory and inhibitory neurons. Such avalanches emerge due to the network size dependent noise (mesoscopic noise). Numerical simulations reveal an intermediate power law in the distribution of avalanche sizes with the critical exponent around −1.16. We show that this power law is robust upon a variation of the refractory time over several orders of magnitude. However, the avalanche time distribution is biexponential. It does not reflect any genuine power law dependence. (paper)

  12. A System Dynamics Model for Planning Cardiovascular Disease Interventions

    Science.gov (United States)

    Homer, Jack; Evans, Elizabeth; Zielinski, Ann

    2010-01-01

    Planning programs for the prevention and treatment of cardiovascular disease (CVD) is a challenge to every community that wants to make the best use of its limited resources. Selecting programs that provide the greatest impact is difficult because of the complex set of causal pathways and delays that link risk factors to CVD. We describe a system dynamics simulation model developed for a county health department that incorporates and tracks the effects of those risk factors over time on both first-time and recurrent events. We also describe how the model was used to evaluate the potential impacts of various intervention strategies for reducing the county's CVD burden and present the results of those policy tests. PMID:20167899

  13. 3D Dynamic Modeling of the Head-Neck Complex for Fast Eye and Head Orientation Movements Research

    Directory of Open Access Journals (Sweden)

    Daniel A. Sierra

    2011-01-01

    Full Text Available A 3D dynamic computer model for the movement of the head-neck complex is presented. It incorporates anatomically correct information about the diverse elements forming the system. The skeleton is considered as a set of interconnected rigid 3D bodies following the Newton-Euler laws of movement. The muscles are modeled using Enderle's linear model, which shows equivalent dynamic characteristics to Loeb's virtual muscle model. The soft tissues, namely, the ligaments, intervertebral disks, and facet joints, are modeled considering their physiological roles and dynamics. In contrast with other head and neck models developed for safety research, the model is aimed to study the neural control of the complex during fast eye and head movements, such as saccades and gaze shifts. In particular, the time-optimal hypothesis and the feedback control ones are discussed.

  14. Dynamics modeling for a rigid-flexible coupling system with nonlinear deformation field

    International Nuclear Information System (INIS)

    Deng Fengyan; He Xingsuo; Li Liang; Zhang Juan

    2007-01-01

    In this paper, a moving flexible beam, which incorporates the effect of the geometrically nonlinear kinematics of deformation, is investigated. Considering the second-order coupling terms of deformation in the longitudinal and transverse deflections, the exact nonlinear strain-displacement relations for a beam element are described. The shear strains formulated by the present modeling method in this paper are zero, so it is reasonable to use geometrically nonlinear deformation fields to demonstrate and simplify a flexible beam undergoing large overall motions. Then, considering the coupling terms of deformation in two dimensions, finite element shape functions of a beam element and Lagrange's equations are employed for deriving the coupling dynamical formulations. The complete expression of the stiffness matrix and all coupling terms are included in the formulations. A model consisting of a rotating planar flexible beam is presented. Then the frequency and dynamical response are studied, and the differences among the zero-order model, first-order coupling model and the new present model are discussed. Numerical examples demonstrate that a 'stiffening beam' can be obtained, when more coupling terms of deformation are added to the longitudinal and transverse deformation field. It is shown that the traditional zero-order and first-order coupling models may not provide an exact dynamic model in some cases

  15. Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window.

    Science.gov (United States)

    Onorante, Luca; Raftery, Adrian E

    2016-01-01

    Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam's window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods.

  16. Incorporating territory compression into population models

    NARCIS (Netherlands)

    Ridley, J; Komdeur, J; Sutherland, WJ; Sutherland, William J.

    The ideal despotic distribution, whereby the lifetime reproductive success a territory's owner achieves is unaffected by population density, is a mainstay of behaviour-based population models. We show that the population dynamics of an island population of Seychelles warblers (Acrocephalus

  17. Radionuclide Incorporation and Long Term Performance of Apatite Waste Forms

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jianwei [Louisiana State Univ., Baton Rouge, LA (United States); Lian, Jie [Rensselaer Polytechnic Inst., Troy, NY (United States); Gao, Fei [Univ. of Michigan, Ann Arbor, MI (United States)

    2016-01-04

    This project aims to combines state-of-the-art experimental and characterization techniques with atomistic simulations based on density functional theory (DFT) and molecular dynamics (MD) simulations. With an initial focus on long-lived I-129 and other radionuclides such as Cs, Sr in apatite structure, specific research objectives include the atomic scale understanding of: (1) incorporation behavior of the radionuclides and their effects on the crystal chemistry and phase stability; (2) stability and microstructure evolution of designed waste forms under coupled temperature and radiation environments; (3) incorporation and migration energetics of radionuclides and release behaviors as probed by DFT and molecular dynamics (MD) simulations; and (4) chemical durability as measured in dissolution experiments for long term performance evaluation and model validation.

  18. Dynamic simulation of sustainable farm development scenarios using cognitive modeling

    Directory of Open Access Journals (Sweden)

    Tuzhyk Kateryna

    2017-03-01

    Full Text Available Dynamic simulation of sustainable farm development scenarios using cognitive modeling. The paper presents a dynamic simulation system of sustainable development scenarios on farms using cognitive modeling. The system incorporates relevant variables which affect the sustainable development of farms. Its user provides answers to strategic issues connected with the level of farm sustainability over a long-term perspective of dynamic development. The work contains a description of the model structure as well as the results of simulations carried out on 16 farms in northern Ukraine. The results show that the process of sustainability is based mainly on the potential for innovation in agricultural production and biodiversity. The user is able to simulate various scenarios for the sustainable development of a farm and visualize the influence of factors on the economic and social situation, as well as on environmental aspects. Upon carrying out a series of simulations, it was determined that the development of farms characterized by sustainable development is based on additional profit, which serves as the main motivation for transforming a conventional farm into a sustainable one. Nevertheless, additional profit is not the only driving force in the system of sustainable development. The standard of living, market condition, and legal regulations as well as government support also play a significant motivational role.

  19. Modelling and simulation of dynamic recrystallization (DRX) in OFHC copper at very high strain rates

    Science.gov (United States)

    Testa, G.; Bonora, N.; Ruggiero, A.; Iannitti, G.; Persechino, I.; Hörnqvist, M.; Mortazavi, N.

    2017-01-01

    At high strain rates, deformation processes are essentially adiabatic and if the plastic work is large enough dynamic recrystallization can occur. In this work, an examination on microstructure evolution of OFHC copper in Dynamic Tensile Extrusion (DTE) test, performed at 400 m/s, was carried out. EBSD investigations, along the center line of the fragment remaining in the extrusion die, showed a progressive elongation of the grains, and an accompanying development of a strong + dual fiber texture. Discontinuous dynamic recrystallization (DRX) occurred at larger strains, and it was showed that nucleation occurred during straining. A criterion for DRX to occur, based on the evolution of Zener-Hollomon parameter during the dynamic deformation process, is proposed. Finally, DTE test was simulated using the modified Rusinek-Klepaczko constitutive model incorporating a model for the prediction of DRX initiation.

  20. Coupling fast fluid dynamics and multizone airflow models in Modelica Buildings library to simulate the dynamics of HVAC systems

    Energy Technology Data Exchange (ETDEWEB)

    Tian, Wei [Univ. of Miami, FL (United States). Dept. of Civil, Architectural and Environmental Engineering; Sevilla, Thomas Alonso [Univ. of Miami, FL (United States). Dept. of Civil, Architectural and Environmental Engineering; Zuo, Wangda [Univ. of Miami, FL (United States). Dept. of Civil, Architectural and Environmental Engineering; Sohn, Michael D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Analysis and Environmental Impacts Div.

    2017-06-08

    Historically, multizone models are widely used in building airflow and energy performance simulations due to their fast computing speed. However, multizone models assume that the air in a room is well mixed, consequently limiting their application. In specific rooms where this assumption fails, the use of computational fluid dynamics (CFD) models may be an alternative option. Previous research has mainly focused on coupling CFD models and multizone models to study airflow in large spaces. While significant, most of these analyses did not consider the coupled simulation of the building airflow with the building's Heating, Ventilation, and Air-Conditioning (HVAC) systems. This paper tries to fill the gap by integrating the models for HVAC systems with coupled multizone and CFD simulations for airflows, using the Modelica simul ation platform. To improve the computational efficiency, we incorporated a simplified CFD model named fast fluid dynamics (FFD). We first introduce the data synchronization strategy and implementation in Modelica. Then, we verify the implementation using two case studies involving an isothermal and a non-isothermal flow by comparing model simulations to experiment data. Afterward, we study another three cases that are deemed more realistic. This is done by attaching a variable air volume (VAV) terminal box and a VAV system to previous flows to assess the capability of the models in studying the dynamic control of HVAC systems. Finally, we discuss further research needs on the coupled simulation using the models.

  1. Thermodynamic model of a thermal storage air conditioning system with dynamic behavior

    Energy Technology Data Exchange (ETDEWEB)

    Fleming, E; Wen, SY; Shi, L; da Silva, AK

    2013-12-01

    A thermodynamic model was developed to predict transient behavior of a thermal storage system, using phase change materials (PCMs), for a novel electric vehicle climate conditioning application. The main objectives of the paper are to consider the system's dynamic behavior, such as a dynamic air flow rate into the vehicle's cabin, and to characterize the transient heat transfer process between the thermal storage unit and the vehicle's cabin, while still maintaining accurate solution to the complex phase change heat transfer. The system studied consists of a heat transfer fluid circulating between either of the on-board hot and cold thermal storage units, which we refer to as thermal batteries, and a liquid-air heat exchanger that provides heat exchange with the incoming air to the vehicle cabin. Each thermal battery is a shell-and-tube configuration where a heat transfer fluid flows through parallel tubes, which are surrounded by PCM within a larger shell. The system model incorporates computationally inexpensive semianalytic solution to the conjugated laminar forced convection and phase change problem within the battery and accounts for airside heat exchange using the Number of Transfer Units (NTUs) method for the liquid-air heat exchanger. Using this approach, we are able to obtain an accurate solution to the complex heat transfer problem within the battery while also incorporating the impact of the airside heat transfer on the overall system performance. The implemented model was benchmarked against a numerical study for a melting process and against full system experimental data for solidification using paraffin wax as the PCM. Through modeling, we demonstrate the importance of capturing the airside heat exchange impact on system performance, and we investigate system response to dynamic operating conditions, e.g., air recirculation. (C) 2013 Elsevier Ltd. All rights reserved.

  2. Incorporation of the capillary hysteresis model HYSTR into the numerical code TOUGH

    International Nuclear Information System (INIS)

    Niemi, A.; Bodvarsson, G.S.; Pruess, K.

    1991-11-01

    As part of the work performed to model flow in the unsaturated zone at Yucca Mountain Nevada, a capillary hysteresis model has been developed. The computer program HYSTR has been developed to compute the hysteretic capillary pressure -- liquid saturation relationship through interpolation of tabulated data. The code can be easily incorporated into any numerical unsaturated flow simulator. A complete description of HYSTR, including a brief summary of the previous hysteresis literature, detailed description of the program, and instructions for its incorporation into a numerical simulator are given in the HYSTR user's manual (Niemi and Bodvarsson, 1991a). This report describes the incorporation of HYSTR into the numerical code TOUGH (Transport of Unsaturated Groundwater and Heat; Pruess, 1986). The changes made and procedures for the use of TOUGH for hysteresis modeling are documented

  3. Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection

    DEFF Research Database (Denmark)

    Bork, Lasse; Møller, Stig Vinther

    2015-01-01

    We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves substantia......We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves...

  4. Organic production in a dynamic CGE model

    DEFF Research Database (Denmark)

    Jacobsen, Lars Bo

    2004-01-01

    for conventional production into land for organic production, a period of two years must pass before the land being transformed can be used for organic production. During that time, the land is counted as land of the organic industry, but it can only produce the conventional product. To handle this rule, we make......Concerns about the impact of modern agriculture on the environment have in recent years led to an interest in supporting the development of organic farming. In addition to environmental benefits, the aim is to encourage the provision of other “multifunctional” properties of organic farming...... such as rural amenities and rural development that are spillover benefit additional to the supply of food. In this paper we further develop an existing dynamic general equilibrium model of the Danish economy to specifically incorporate organic farming. In the model and input-output data each primary...

  5. Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balance

    Science.gov (United States)

    Tang, G.; Bartlein, P. J.

    2012-01-01

    Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p 0.46, p 0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

  6. Automatic generation of predictive dynamic models reveals nuclear phosphorylation as the key Msn2 control mechanism.

    Science.gov (United States)

    Sunnåker, Mikael; Zamora-Sillero, Elias; Dechant, Reinhard; Ludwig, Christina; Busetto, Alberto Giovanni; Wagner, Andreas; Stelling, Joerg

    2013-05-28

    Predictive dynamical models are critical for the analysis of complex biological systems. However, methods to systematically develop and discriminate among systems biology models are still lacking. We describe a computational method that incorporates all hypothetical mechanisms about the architecture of a biological system into a single model and automatically generates a set of simpler models compatible with observational data. As a proof of principle, we analyzed the dynamic control of the transcription factor Msn2 in Saccharomyces cerevisiae, specifically the short-term mechanisms mediating the cells' recovery after release from starvation stress. Our method determined that 12 of 192 possible models were compatible with available Msn2 localization data. Iterations between model predictions and rationally designed phosphoproteomics and imaging experiments identified a single-circuit topology with a relative probability of 99% among the 192 models. Model analysis revealed that the coupling of dynamic phenomena in Msn2 phosphorylation and transport could lead to efficient stress response signaling by establishing a rate-of-change sensor. Similar principles could apply to mammalian stress response pathways. Systematic construction of dynamic models may yield detailed insight into nonobvious molecular mechanisms.

  7. A nonlinear dynamics approach for incorporating wind-speed patterns into wind-power project evaluation.

    Science.gov (United States)

    Huffaker, Ray; Bittelli, Marco

    2015-01-01

    Wind-energy production may be expanded beyond regions with high-average wind speeds (such as the Midwest U.S.A.) to sites with lower-average speeds (such as the Southeast U.S.A.) by locating favorable regional matches between natural wind-speed and energy-demand patterns. A critical component of wind-power evaluation is to incorporate wind-speed dynamics reflecting documented diurnal and seasonal behavioral patterns. Conventional probabilistic approaches remove patterns from wind-speed data. These patterns must be restored synthetically before they can be matched with energy-demand patterns. How to accurately restore wind-speed patterns is a vexing problem spurring an expanding line of papers. We propose a paradigm shift in wind power evaluation that employs signal-detection and nonlinear-dynamics techniques to empirically diagnose whether synthetic pattern restoration can be avoided altogether. If the complex behavior of observed wind-speed records is due to nonlinear, low-dimensional, and deterministic system dynamics, then nonlinear dynamics techniques can reconstruct wind-speed dynamics from observed wind-speed data without recourse to conventional probabilistic approaches. In the first study of its kind, we test a nonlinear dynamics approach in an application to Sugarland Wind-the first utility-scale wind project proposed in Florida, USA. We find empirical evidence of a low-dimensional and nonlinear wind-speed attractor characterized by strong temporal patterns that match up well with regular daily and seasonal electricity demand patterns.

  8. Modeling dynamic swarms

    KAUST Repository

    Ghanem, Bernard

    2013-01-01

    This paper proposes the problem of modeling video sequences of dynamic swarms (DSs). We define a DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal interdependency and stationarity, i.e., the motions are similar in any small spatiotemporal neighborhood. Examples of DS abound in nature, e.g., herds of animals and flocks of birds. To capture the local spatiotemporal properties of the DS, we present a probabilistic model that learns both the spatial layout of swarm elements (based on low-level image segmentation) and their joint dynamics that are modeled as linear transformations. To this end, a spatiotemporal neighborhood is associated with each swarm element, in which local stationarity is enforced both spatially and temporally. We assume that the prior on the swarm dynamics is distributed according to an MRF in both space and time. Embedding this model in a MAP framework, we iterate between learning the spatial layout of the swarm and its dynamics. We learn the swarm transformations using ICM, which iterates between estimating these transformations and updating their distribution in the spatiotemporal neighborhoods. We demonstrate the validity of our method by conducting experiments on real and synthetic video sequences. Real sequences of birds, geese, robot swarms, and pedestrians evaluate the applicability of our model to real world data. © 2012 Elsevier Inc. All rights reserved.

  9. Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival

    Directory of Open Access Journals (Sweden)

    Céline Christiansen-Jucht

    2015-05-01

    Full Text Available Climate change and global warming are emerging as important threats to human health, particularly through the potential increase in vector- and water-borne diseases. Environmental variables are known to affect substantially the population dynamics and abundance of the poikilothermic vectors of disease, but the exact extent of this sensitivity is not well established. Focusing on malaria and its main vector in Africa, Anopheles gambiae sensu stricto, we present a set of novel mathematical models of climate-driven mosquito population dynamics motivated by experimental data suggesting that in An. gambiae, mortality is temperature and age dependent. We compared the performance of these models to that of a “standard” model ignoring age dependence. We used a longitudinal dataset of vector abundance over 36 months in sub-Saharan Africa for comparison between models that incorporate age dependence and one that does not, and observe that age-dependent models consistently fitted the data better than the reference model. This highlights that including age dependence in the vector component of mosquito-borne disease models may be important to predict more reliably disease transmission dynamics. Further data and studies are needed to enable improved fitting, leading to more accurate and informative model predictions for the An. gambiae malaria vector as well as for other disease vectors.

  10. Conceptual Design Optimization of an Augmented Stability Aircraft Incorporating Dynamic Response and Actuator Constraints

    Science.gov (United States)

    Welstead, Jason; Crouse, Gilbert L., Jr.

    2014-01-01

    Empirical sizing guidelines such as tail volume coefficients have long been used in the early aircraft design phases for sizing stabilizers, resulting in conservatively stable aircraft. While successful, this results in increased empty weight, reduced performance, and greater procurement and operational cost relative to an aircraft with optimally sized surfaces. Including flight dynamics in the conceptual design process allows the design to move away from empirical methods while implementing modern control techniques. A challenge of flight dynamics and control is the numerous design variables, which are changing fluidly throughout the conceptual design process, required to evaluate the system response to some disturbance. This research focuses on addressing that challenge not by implementing higher order tools, such as computational fluid dynamics, but instead by linking the lower order tools typically used within the conceptual design process so each discipline feeds into the other. In thisresearch, flight dynamics and control was incorporated into the conceptual design process along with the traditional disciplines of vehicle sizing, weight estimation, aerodynamics, and performance. For the controller, a linear quadratic regulator structure with constant gains has been specified to reduce the user input. Coupling all the disciplines in the conceptual design phase allows the aircraft designer to explore larger design spaces where stabilizers are sized according to dynamic response constraints rather than historical static margin and volume coefficient guidelines.

  11. The Effects of Dynamic Root Distribution on Land–Atmosphere Carbon and Water Fluxes in the Community Earth System Model (CESM1.2.0

    Directory of Open Access Journals (Sweden)

    Yuanyuan Wang

    2018-03-01

    Full Text Available Roots are responsible for the uptake of water and nutrients by plants, and they have the plasticity to respond dynamically to different environmental conditions. However, currently, most climate models only prescribe rooting profiles as a function of the vegetation type of the land component, with no consideration of the surroundings. In this study, a dynamic rooting scheme describing root growth as a compromise between water and nitrogen availability in the subsurface was incorporated into the Community Earth System Model 1.2.0 (CESM1.2.0. The dynamic rooting scheme was incorporated to investigate the effects of land–atmosphere carbon and water fluxes, and their subsequent influences on climate. The modeling results of global land–atmosphere coupling simulations from 1982 to 2005 show that the dynamic rooting scheme can improve gross primary production (GPP and evapotranspiration (ET in most tropical regions, and in some high-latitude regions with lower mean biases (MBEs and root mean square errors (RMSEs. Obvious differences in 2-m air temperature were found in low-latitude areas, with decreases of up to 2 °C. Under the influence of local land-surface feedback and large-scale moisture advection, total precipitation in the northeastern area of the Amazon and the west coast of Africa increased by 200 mm year−1, and that of South America, central Africa, and Indonesia increased by 50 to 100 mm year−1. Overall, the model incorporating the dynamic rooting scheme may reveal cooling and humidifying effects, especially for tropical regions.

  12. Statistically accurate low-order models for uncertainty quantification in turbulent dynamical systems.

    Science.gov (United States)

    Sapsis, Themistoklis P; Majda, Andrew J

    2013-08-20

    A framework for low-order predictive statistical modeling and uncertainty quantification in turbulent dynamical systems is developed here. These reduced-order, modified quasilinear Gaussian (ROMQG) algorithms apply to turbulent dynamical systems in which there is significant linear instability or linear nonnormal dynamics in the unperturbed system and energy-conserving nonlinear interactions that transfer energy from the unstable modes to the stable modes where dissipation occurs, resulting in a statistical steady state; such turbulent dynamical systems are ubiquitous in geophysical and engineering turbulence. The ROMQG method involves constructing a low-order, nonlinear, dynamical system for the mean and covariance statistics in the reduced subspace that has the unperturbed statistics as a stable fixed point and optimally incorporates the indirect effect of non-Gaussian third-order statistics for the unperturbed system in a systematic calibration stage. This calibration procedure is achieved through information involving only the mean and covariance statistics for the unperturbed equilibrium. The performance of the ROMQG algorithm is assessed on two stringent test cases: the 40-mode Lorenz 96 model mimicking midlatitude atmospheric turbulence and two-layer baroclinic models for high-latitude ocean turbulence with over 125,000 degrees of freedom. In the Lorenz 96 model, the ROMQG algorithm with just a single mode captures the transient response to random or deterministic forcing. For the baroclinic ocean turbulence models, the inexpensive ROMQG algorithm with 252 modes, less than 0.2% of the total, captures the nonlinear response of the energy, the heat flux, and even the one-dimensional energy and heat flux spectra.

  13. Modeling the dynamic crush of impact mitigating materials

    International Nuclear Information System (INIS)

    Logan, R.W.; McMichael, L.D.

    1995-01-01

    Crushable materials are commonly utilized in the design of structural components to absorb energy and mitigate shock during the dynamic impact of a complex structure, such as an automobile chassis or drum-type shipping container. The development and application of several finite-element material models which have been developed at various times at LLNL for DYNA3D will be discussed. Between the models, they are able to account for several of the predominant mechanisms which typically influence the dynamic mechanical behavior of crushable materials. One issue we addressed was that no single existing model would account for the entire gambit of constitutive features which are important for crushable materials. Thus, we describe the implementation and use of an additional material model which attempts to provide a more comprehensive model of the mechanics of crushable material behavior. This model combines features of the pre-existing DYNA models and incorporates some new features as well in an invariant large-strain formulation. In addition to examining the behavior of a unit cell in uniaxial compression, two cases were chosen to evaluate the capabilities and accuracy of the various material models in DYNA. In the first case, a model for foam filled box beams was developed and compared to test data from a 4-point bend test. The model was subsequently used to study its effectiveness in energy absorption in an aluminum extrusion, spaceframe, vehicle chassis. The second case examined the response of the AT-400A shipping container and the performance of the overpack material during accident environments selected from 10CFR71 and IAEA regulations

  14. Unraveling the sub-processes of selective attention: insights from dynamic modeling and continuous behavior.

    Science.gov (United States)

    Frisch, Simon; Dshemuchadse, Maja; Görner, Max; Goschke, Thomas; Scherbaum, Stefan

    2015-11-01

    Selective attention biases information processing toward stimuli that are relevant for achieving our goals. However, the nature of this bias is under debate: Does it solely rely on the amplification of goal-relevant information or is there a need for additional inhibitory processes that selectively suppress currently distracting information? Here, we explored the processes underlying selective attention with a dynamic, modeling-based approach that focuses on the continuous evolution of behavior over time. We present two dynamic neural field models incorporating the diverging theoretical assumptions. Simulations with both models showed that they make similar predictions with regard to response times but differ markedly with regard to their continuous behavior. Human data observed via mouse tracking as a continuous measure of performance revealed evidence for the model solely based on amplification but no indication of persisting selective distracter inhibition.

  15. Review of various dynamic modeling methods and development of an intuitive modeling method for dynamic systems

    International Nuclear Information System (INIS)

    Shin, Seung Ki; Seong, Poong Hyun

    2008-01-01

    Conventional static reliability analysis methods are inadequate for modeling dynamic interactions between components of a system. Various techniques such as dynamic fault tree, dynamic Bayesian networks, and dynamic reliability block diagrams have been proposed for modeling dynamic systems based on improvement of the conventional modeling methods. In this paper, we review these methods briefly and introduce dynamic nodes to the existing Reliability Graph with General Gates (RGGG) as an intuitive modeling method to model dynamic systems. For a quantitative analysis, we use a discrete-time method to convert an RGGG to an equivalent Bayesian network and develop a software tool for generation of probability tables

  16. Dynamic Inversion for Hydrological Process Monitoring with Electrical Resistance Tomography Under Model Uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Lehikoinen, A.; Huttunen, J.M.J.; Finsterle, S.; Kowalsky, M.B.; Kaipio, J.P.

    2009-08-01

    We propose an approach for imaging the dynamics of complex hydrological processes. The evolution of electrically conductive fluids in porous media is imaged using time-lapse electrical resistance tomography. The related dynamic inversion problem is solved using Bayesian filtering techniques, that is, it is formulated as a sequential state estimation problem in which the target is an evolving posterior probability density of the system state. The dynamical inversion framework is based on the state space representation of the system, which involves the construction of a stochastic evolution model and an observation model. The observation model used in this paper consists of the complete electrode model for ERT, with Archie's law relating saturations to electrical conductivity. The evolution model is an approximate model for simulating flow through partially saturated porous media. Unavoidable modeling and approximation errors in both the observation and evolution models are considered by computing approximate statistics for these errors. These models are then included in the construction of the posterior probability density of the estimated system state. This approximation error method allows the use of approximate - and therefore computationally efficient - observation and evolution models in the Bayesian filtering. We consider a synthetic example and show that the incorporation of an explicit model for the model uncertainties in the state space representation can yield better estimates than a frame-by-frame imaging approach.

  17. Dynamic temperature dependence patterns in future energy demand models in the context of climate change

    International Nuclear Information System (INIS)

    Hekkenberg, M.; Moll, H.C.; Uiterkamp, A.J.M. Schoot

    2009-01-01

    Energy demand depends on outdoor temperature in a 'u' shaped fashion. Various studies have used this temperature dependence to investigate the effects of climate change on energy demand. Such studies contain implicit or explicit assumptions to describe expected socio-economic changes that may affect future energy demand. This paper critically analyzes these implicit or explicit assumptions and their possible effect on the studies' outcomes. First we analyze the interaction between the socio-economic structure and the temperature dependence pattern (TDP) of energy demand. We find that socio-economic changes may alter the TDP in various ways. Next we investigate how current studies manage these dynamics in socio-economic structure. We find that many studies systematically misrepresent the possible effect of socio-economic changes on the TDP of energy demand. Finally, we assess the consequences of these misrepresentations in an energy demand model based on temperature dependence and climate scenarios. Our model results indicate that expected socio-economic dynamics generally lead to an underestimation of future energy demand in models that misrepresent such dynamics. We conclude that future energy demand models should improve the incorporation of socio-economic dynamics. We propose dynamically modeling several key parameters and using direct meteorological data instead of degree days. (author)

  18. Hierarchical modelling of temperature and habitat size effects on population dynamics of North Atlantic cod

    DEFF Research Database (Denmark)

    Mantzouni, Irene; Sørensen, Helle; O'Hara, Robert B.

    2010-01-01

    and Beverton and Holt stock–recruitment (SR) models were extended by applying hierarchical methods, mixed-effects models, and Bayesian inference to incorporate the influence of these ecosystem factors on model parameters representing cod maximum reproductive rate and carrying capacity. We identified......Understanding how temperature affects cod (Gadus morhua) ecology is important for forecasting how populations will develop as climate changes in future. The effects of spawning-season temperature and habitat size on cod recruitment dynamics have been investigated across the North Atlantic. Ricker...

  19. Dynamic simulation of a beta-type Stirling engine with cam-drive mechanism via the combination of the thermodynamic and dynamic models

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, Chin-Hsiang; Yu, Ying-Ju [Department of Aeronautics and Astronautics, National Cheng Kung University, No. 1, Ta-Shieh Road, Tainan, Taiwan (China)

    2011-02-15

    Dynamic simulation of a beta-type Stirling engine with cam-drive mechanism used in concentrating solar power system has been performed. A dynamic model of the mechanism is developed and then incorporated with the thermodynamic model so as to predict the transient behavior of the engine in the hot-start period. In this study, the engine is started from an initial rotational speed. The torques exerted by the flywheel of the engine at any time instant can be calculated by the dynamic model as long as the gas pressures in the chambers, the mass inertia, the friction force, and the external load have been evaluated. The instantaneous rotation speed of the engine is then determined by integration of the equation of rotational motion with respect to time, which in return affects the instantaneous variations in pressure and other thermodynamic properties of the gas inside the chambers. Therefore, the transient variations in gas properties inside the engine chambers and the dynamic behavior of the engine mechanism should be handled simultaneously via the coupling of the thermodynamic and dynamic models. An extensive parametric study of the effects of different operating and geometrical parameters has been performed, and results regarding the effects of mass moment of inertia of the flywheel, initial rotational speed, initial charged pressure, heat source temperature, phase angle, gap size, displacer length, and piston stroke on the engine transient behavior are investigated. (author)

  20. An ocular biomechanic model for dynamic simulation of different eye movements.

    Science.gov (United States)

    Iskander, J; Hossny, M; Nahavandi, S; Del Porto, L

    2018-04-11

    Simulating and analysing eye movement is useful for assessing visual system contribution to discomfort with respect to body movements, especially in virtual environments where simulation sickness might occur. It can also be used in the design of eye prosthesis or humanoid robot eye. In this paper, we present two biomechanic ocular models that are easily integrated into the available musculoskeletal models. The model was previously used to simulate eye-head coordination. The models are used to simulate and analyse eye movements. The proposed models are based on physiological and kinematic properties of the human eye. They incorporate an eye-globe, orbital suspension tissues and six muscles with their connective tissues (pulleys). Pulleys were incorporated in rectus and inferior oblique muscles. The two proposed models are the passive pulleys and the active pulleys models. Dynamic simulations of different eye movements, including fixation, saccade and smooth pursuit, are performed to validate both models. The resultant force-length curves of the models were similar to the experimental data. The simulation results show that the proposed models are suitable to generate eye movement simulations with results comparable to other musculoskeletal models. The maximum kinematic root mean square error (RMSE) is 5.68° and 4.35° for the passive and active pulley models, respectively. The analysis of the muscle forces showed realistic muscle activation with increased muscle synergy in the active pulley model. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. Rail vehicle dynamic response to a nonlinear physical 'in-service' model of its secondary suspension hydraulic dampers

    Science.gov (United States)

    Wang, W. L.; Zhou, Z. R.; Yu, D. S.; Qin, Q. H.; Iwnicki, S.

    2017-10-01

    A full nonlinear physical 'in-service' model was built for a rail vehicle secondary suspension hydraulic damper with shim-pack-type valves. In the modelling process, a shim pack deflection theory with an equivalent-pressure correction factor was proposed, and a Finite Element Analysis (FEA) approach was applied. Bench test results validated the damper model over its full velocity range and thus also proved that the proposed shim pack deflection theory and the FEA-based parameter identification approach are effective. The validated full damper model was subsequently incorporated into a detailed vehicle dynamics simulation to study how its key in-service parameter variations influence the secondary-suspension-related vehicle system dynamics. The obtained nonlinear physical in-service damper model and the vehicle dynamic response characteristics in this study could be used in the product design optimization and nonlinear optimal specifications of high-speed rail hydraulic dampers.

  2. Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam’s Window*

    Science.gov (United States)

    Onorante, Luca; Raftery, Adrian E.

    2015-01-01

    Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam’s window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods. PMID:26917859

  3. Tracking the sleep onset process: an empirical model of behavioral and physiological dynamics.

    Directory of Open Access Journals (Sweden)

    Michael J Prerau

    2014-10-01

    Full Text Available The sleep onset process (SOP is a dynamic process correlated with a multitude of behavioral and physiological markers. A principled analysis of the SOP can serve as a foundation for answering questions of fundamental importance in basic neuroscience and sleep medicine. Unfortunately, current methods for analyzing the SOP fail to account for the overwhelming evidence that the wake/sleep transition is governed by continuous, dynamic physiological processes. Instead, current practices coarsely discretize sleep both in terms of state, where it is viewed as a binary (wake or sleep process, and in time, where it is viewed as a single time point derived from subjectively scored stages in 30-second epochs, effectively eliminating SOP dynamics from the analysis. These methods also fail to integrate information from both behavioral and physiological data. It is thus imperative to resolve the mismatch between the physiological evidence and analysis methodologies. In this paper, we develop a statistically and physiologically principled dynamic framework and empirical SOP model, combining simultaneously-recorded physiological measurements with behavioral data from a novel breathing task requiring no arousing external sensory stimuli. We fit the model using data from healthy subjects, and estimate the instantaneous probability that a subject is awake during the SOP. The model successfully tracked physiological and behavioral dynamics for individual nights, and significantly outperformed the instantaneous transition models implicit in clinical definitions of sleep onset. Our framework also provides a principled means for cross-subject data alignment as a function of wake probability, allowing us to characterize and compare SOP dynamics across different populations. This analysis enabled us to quantitatively compare the EEG of subjects showing reduced alpha power with the remaining subjects at identical response probabilities. Thus, by incorporating both

  4. Aspects of the incorporation of spatial data into radioecological and restoration analysis

    International Nuclear Information System (INIS)

    Beresford, N.A.; Wright, S.M.; Howard, B.J.; Crout, N.M.J.; Arkhipov, A.; Voigt, G.

    2002-01-01

    In the last decade geographical information systems have been increasingly used to incorporate spatial data into radioecological analysis. This has allowed the development of models with spatially variable outputs. Two main approaches have been adopted in the development of spatial models. Empirical Tag based models applied across a range of spatial scales utilize underlying soil type maps and readily available radioecological data. Soil processes can also be modelled to allow the dynamic prediction of radionuclide soil to plant transfer. We discuss a dynamic semi-mechanistic radiocaesium soil to plant-transfer model, which utilizes readily available spatially variable soil parameters. Both approaches allow the identification of areas that may be vulnerable to radionuclide deposition, therefore enabling the targeting of intervention measures. Improved estimates of radionuclide fluxes and ingestion doses can be achieved by incorporating spatially varying inputs such as agricultural production and dietary habits in to these models. In this paper, aspects of such models, including data requirements, implementation and outputs are discussed and critically evaluated. The relative merits and disadvantages of the two spatial model approaches adopted within radioecology are discussed. We consider the usefulness of such models to aid decision-makers and access the requirements and potential of further application within radiological protection. (author)

  5. Seasonal PCB bioaccumulation in an arctic marine ecosystem: a model analysis incorporating lipid dynamics, food-web productivity and migration.

    Science.gov (United States)

    Laender, Frederik De; Oevelen, Dick Van; Frantzen, Sylvia; Middelburg, Jack J; Soetaert, Karline

    2010-01-01

    Primary production and species' lipid contents in Arctic ecosystems are notoriously seasonal. Additionally, seasonal migration patterns of fish may alter prey availability and thus diet. Taking the southern Barents Sea as a study region and PCBs as model contaminants, we examined to what extent each of these factors cause bioaccumulation in fish to change throughout the year. Data on physiology and standing stocks of multiple trophic levels were used to estimated season-specific carbon budgets and by inference also corresponding values for food ingestion and production of cod, capelin, and herring. When combining these values with Arctic lipid dynamics for bioaccumulation model parameter setting, we predicted bioaccumulation factors (BAFs) that were in good agreement with BAFs for cod and capelin observed between 1998 and 2008. BAFs in all fish were 10 times lower in summer than in spring and fall/winter and were mainly driven by lipid dynamics. Trophic magnification factors (TMFs: increase in BAF per unit increase in trophic level as derived from our carbon budgets) were highest for PCB 153 during spring (2.3-2.4) and lowest for PCB 52 in summer and fall/winter (1.5-1.6) and were driven by seasonal shifts in trophic level and lipid dynamics.

  6. Incorporating time and income constraints in dynamic agent-based models of activity generation and time use : Approach and illustration

    NARCIS (Netherlands)

    Arentze, Theo; Ettema, D.F.; Timmermans, Harry

    Existing theories and models in economics and transportation treat households’ decisions regarding allocation of time and income to activities as a resource-allocation optimization problem. This stands in contrast with the dynamic nature of day-by-day activity-travel choices. Therefore, in the

  7. Dynamic Latent Classification Model

    DEFF Research Database (Denmark)

    Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre

    as possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics...

  8. Modeling viral coevolution: HIV multi-clonal persistence and competition dynamics

    Science.gov (United States)

    Bagnoli, F.; Liò, P.; Sguanci, L.

    2006-07-01

    The coexistence of different viral strains (quasispecies) within the same host are nowadays observed for a growing number of viruses, most notably HIV, Marburg and Ebola, but the conditions for the formation and survival of new strains have not yet been understood. We present a model of HIV quasispecies competition, which describes the conditions of viral quasispecies coexistence under different immune system conditions. Our model incorporates both T and B cells responses, and we show that the role of B cells is important and additive to that of T cells. Simulations of coinfection (simultaneous infection) and superinfection (delayed secondary infection) scenarios in the early stages (days) and in the late stages of the infection (years) are in agreement with emerging molecular biology findings. The immune response induces a competition among similar phenotypes, leading to differentiation (quasispeciation), escape dynamics and complex oscillations of viral strain abundance. We found that the quasispecies dynamics after superinfection or coinfection has time scales of several months and becomes even slower when the immune system response is weak. Our model represents a general framework to study the speed and distribution of HIV quasispecies during disease progression, vaccination and therapy.

  9. Modeling and dynamics of an autothermal JP5 fuel reformer for marine fuel cell applications

    International Nuclear Information System (INIS)

    Tsourapas, Vasilis; Sun, Jing; Nickens, Anthony

    2008-01-01

    In this work, a dynamic model of an integrated autothermal reformer (ATR) and proton exchange membrane fuel cell (PEM FC) system and model-based evaluation of its dynamic characteristics are presented. The ATR reforms JP5 fuel into a hydrogen rich flow. The hydrogen is extracted from the reformate flow by a separator membrane (SEP), then supplied to the PEM FC for power generation. A catalytic burner (CB) and a turbine are also incorporated to recuperate energy from the remaining SEP flow that would otherwise be wasted. A dynamic model of this system, based on the ideal gas law and energy balance principles, is developed and used to explore the effects of the operating setpoint selection of the SEP on the overall system efficiency. The analysis reveals that a trade-off exists between the SEP efficiency and the overall system efficiency. Finally the open loop system simulation results are presented and conclusions are drawn on the SEP operation

  10. Stability and bifurcation in a model for the dynamics of stem-like cells in leukemia under treatment

    Science.gov (United States)

    Rǎdulescu, I. R.; Cândea, D.; Halanay, A.

    2012-11-01

    A mathematical model for the dynamics of leukemic cells during treatment is introduced. Delay differential equations are used to model cells' evolution and are based on the Mackey-Glass approach, incorporating Goldie-Coldman law. Since resistance is propagated by cells that have the capacity of self-renewal, a population of stem-like cells is studied. Equilibrium points are calculated and their stability properties are investigated.

  11. Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network

    Science.gov (United States)

    Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing

    2016-01-01

    Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel “multi-feature SGP model” (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time. PMID:27746515

  12. Modeling dynamic swarms

    KAUST Repository

    Ghanem, Bernard; Ahuja, Narendra

    2013-01-01

    This paper proposes the problem of modeling video sequences of dynamic swarms (DSs). We define a DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal

  13. Models of Easter Island Human-Resource Dynamics: Advances and Gaps

    Directory of Open Access Journals (Sweden)

    Agostino Merico

    2017-12-01

    Full Text Available Finding solutions to the entangled problems of human population growth, resource exploitation, ecosystem degradation, and biodiversity loss is considered humanity's grand challenge. Small and isolated societies of the past, such as the Rapanui of Easter Island, constitute ideal laboratories for understanding the consequences of human-driven environmental degradation and associated crises. By integrating different processes into a coherent and quantitative framework, mathematical models can be effective tools for investigating the ecological and socioeconomic history of these ancient civilizations. Most models of Easter Island are grounded around the Malthusian theory of population growth and designed as Lotka-Volterra predator-prey systems. Within ranges of plausible parameter values, these dynamic systems models predict a population overshoot and collapse sequence, in line with the ecocidal view about the Rapanui. With new archaeological evidence coming to light, casting doubts on the classical narrative of a human-induced collapse, models have begun to incorporate the new pieces of evidence and started to describe a more complex historical ecology, in line with the view of a resilient society that suffered genocide after the contact with Europeans. Uncertainties affecting the archaeological evidence contribute to the formulation of contradictory narratives. Surprisingly, no agent-based models have been applied to Easter Island. I argue that these tools offer appealing possibilities for overcoming the limits of dynamic systems models and the uncertainties in the available archaeological data.

  14. Incorporating neurophysiological concepts in mathematical thermoregulation models

    Science.gov (United States)

    Kingma, Boris R. M.; Vosselman, M. J.; Frijns, A. J. H.; van Steenhoven, A. A.; van Marken Lichtenbelt, W. D.

    2014-01-01

    Skin blood flow (SBF) is a key player in human thermoregulation during mild thermal challenges. Various numerical models of SBF regulation exist. However, none explicitly incorporates the neurophysiology of thermal reception. This study tested a new SBF model that is in line with experimental data on thermal reception and the neurophysiological pathways involved in thermoregulatory SBF control. Additionally, a numerical thermoregulation model was used as a platform to test the function of the neurophysiological SBF model for skin temperature simulation. The prediction-error of the SBF-model was quantified by root-mean-squared-residual (RMSR) between simulations and experimental measurement data. Measurement data consisted of SBF (abdomen, forearm, hand), core and skin temperature recordings of young males during three transient thermal challenges (1 development and 2 validation). Additionally, ThermoSEM, a thermoregulation model, was used to simulate body temperatures using the new neurophysiological SBF-model. The RMSR between simulated and measured mean skin temperature was used to validate the model. The neurophysiological model predicted SBF with an accuracy of RMSR human thermoregulation models can be equipped with SBF control functions that are based on neurophysiology without loss of performance. The neurophysiological approach in modelling thermoregulation is favourable over engineering approaches because it is more in line with the underlying physiology.

  15. Incorporation of tritium into planctonic algae in a continuous culture under dynamic conditions

    International Nuclear Information System (INIS)

    Strack, S.; Kistner, G.; Emeis, C.C.

    1979-01-01

    For the purpose of modelling the ecologic behaviour of organically bound tritium (OBT) in aquatic food chains under dynamic conditions (i.e. by changing tritium concentrations), a continuous culture of algae was chosen to which tritium was added by a single injection as tritiated water (HTO). The culture was working according to the chemostatic principle where the concentration of cells is in a steady state. Therefore, according to the growth of algae, tritium is incorporated into the organic substance, while in a parallel process HTO and algae are eliminated from the system at the same rate. From these two processes of first-order kinetics, a special function resulted for the concentration process of OBT in the fermenter that is well known in the field of drug kinetics. Initially it increases until it reaches a maximum value where it intersects the elimination curve of HTO, then decreases and asymptotically approaches the time axis - in the same manner as the elimination curve - only at a superior level. A comparison of this theoretically calculated function with the concentration actually found shows that also under dynamic conditions tritium is undergoing discrimination because of isotopic effects up to a ratio of I=0.80. The calculation of the ratios R=(OBT)/(HTO) in the continuous culture by comparing the function for OBT with the elimination curve for HTO shows a linear increase of R-values during the experiment. At maximum tritium concentration in the algae, the ratio becomes greater than one, and at the end of the experiment it reaches a value of about 6. However, by extrapolating to a time of 40 half-lives, when the absolute concentration of HTO has already decreased by a factor of 10 -12 , a ratio of about 25 was found. The discrimination enters the estimation of R-values at a constant factor of 0.80. (author)

  16. Incorporating a prediction of postgrazing herbage mass into a whole-farm model for pasture-based dairy systems.

    Science.gov (United States)

    Gregorini, P; Galli, J; Romera, A J; Levy, G; Macdonald, K A; Fernandez, H H; Beukes, P C

    2014-07-01

    The DairyNZ whole-farm model (WFM; DairyNZ, Hamilton, New Zealand) consists of a framework that links component models for animal, pastures, crops, and soils. The model was developed to assist with analysis and design of pasture-based farm systems. New (this work) and revised (e.g., cow, pasture, crops) component models can be added to the WFM, keeping the model flexible and up to date. Nevertheless, the WFM does not account for plant-animal relationships determining herbage-depletion dynamics. The user has to preset the maximum allowable level of herbage depletion [i.e., postgrazing herbage mass (residuals)] throughout the year. Because residuals have a direct effect on herbage regrowth, the WFM in its current form does not dynamically simulate the effect of grazing pressure on herbage depletion and consequent effect on herbage regrowth. The management of grazing pressure is a key component of pasture-based dairy systems. Thus, the main objective of the present work was to develop a new version of the WFM able to predict residuals, and thereby simulate related effects of grazing pressure dynamically at the farm scale. This objective was accomplished by incorporating a new component model into the WFM. This model represents plant-animal relationships, for example sward structure and herbage intake rate, and resulting level of herbage depletion. The sensitivity of the new version of the WFM was evaluated and then the new WFM was tested against an experimental data set previously used to evaluate the WFM and to illustrate the adequacy and improvement of the model development. Key outputs variables of the new version pertinent to this work (milk production, herbage dry matter intake, intake rate, harvesting efficiency, and residuals) responded acceptably to a range of input variables. The relative prediction errors for monthly and mean annual residual predictions were 20 and 5%, respectively. Monthly predictions of residuals had a line bias (1.5%), with a proportion

  17. Incorporation of composite defects from ultrasonic NDE into CAD and FE models

    Science.gov (United States)

    Bingol, Onur Rauf; Schiefelbein, Bryan; Grandin, Robert J.; Holland, Stephen D.; Krishnamurthy, Adarsh

    2017-02-01

    Fiber-reinforced composites are widely used in aerospace industry due to their combined properties of high strength and low weight. However, owing to their complex structure, it is difficult to assess the impact of manufacturing defects and service damage on their residual life. While, ultrasonic testing (UT) is the preferred NDE method to identify the presence of defects in composites, there are no reasonable ways to model the damage and evaluate the structural integrity of composites. We have developed an automated framework to incorporate flaws and known composite damage automatically into a finite element analysis (FEA) model of composites, ultimately aiding in accessing the residual life of composites and make informed decisions regarding repairs. The framework can be used to generate a layer-by-layer 3D structural CAD model of the composite laminates replicating their manufacturing process. Outlines of structural defects, such as delaminations, are automatically detected from UT of the laminate and are incorporated into the CAD model between the appropriate layers. In addition, the framework allows for direct structural analysis of the resulting 3D CAD models with defects by automatically applying the appropriate boundary conditions. In this paper, we show a working proof-of-concept for the composite model builder with capabilities of incorporating delaminations between laminate layers and automatically preparing the CAD model for structural analysis using a FEA software.

  18. Modeling near-road air quality using a computational fluid dynamics model, CFD-VIT-RIT.

    Science.gov (United States)

    Wang, Y Jason; Zhang, K Max

    2009-10-15

    It is well recognized that dilution is an important mechanism governing the near-road air pollutant concentrations. In this paper, we aim to advance our understanding of turbulent mixing mechanisms on and near roadways using computation fluid dynamics. Turbulent mixing mechanisms can be classified into three categories according to their origins: vehicle-induced turbulence (VIT), road-induced turbulence (RIT), and atmospheric boundary layer turbulence. RIT includes the turbulence generated by road embankment, road surface thermal effects, and roadside structures. Both VIT and RIT are affected by the roadway designs. We incorporate the detailed treatment of VIT and RIT into the CFD (namely CFD-VIT-RIT) and apply the model in simulating the spatial gradients of carbon monoxide near two major highways with different traffic mix and roadway configurations. The modeling results are compared to the field measurements and those from CALINE4 and CFD without considering VIT and RIT. We demonstrate that the incorporation of VIT and RIT considerably improves the modeling predictions, especially on vertical gradients and seasonal variations of carbon monoxide. Our study implies that roadway design can significantly influence the near-road air pollution. Thus we recommend that mitigating near-road air pollution through roadway designs be considered in the air quality and transportation management In addition, thanks to the rigorous representation of turbulent mixing mechanisms, CFD-VIT-RIT can become valuable tools in the roadway designs process.

  19. Developing Baltic cod recruitment models II : Incorporation of environmental variability and species interaction

    DEFF Research Database (Denmark)

    Köster, Fritz; Hinrichsen, H.H.; St. John, Michael

    2001-01-01

    We investigate whether a process-oriented approach based on the results of field, laboratory, and modelling studies can be used to develop a stock-environment-recruitment model for Central Baltic cod (Gadus morhua). Based on exploratory statistical analysis, significant variables influencing...... cod in these areas, suggesting that key biotic and abiotic processes can be successfully incorporated into recruitment models....... survival of early life stages and varying systematically among spawning sites were incorporated into stock-recruitment models, first for major cod spawning sites and then combined for the entire Central Baltic. Variables identified included potential egg production by the spawning stock, abiotic conditions...

  20. Multiscale, multiphysics beam dynamics framework design and applications

    International Nuclear Information System (INIS)

    Amundson, J F; Spentzouris, P; Dechow, D; Stoltz, P; McInnes, L; Norris, B

    2008-01-01

    Modern beam dynamics simulations require nontrivial implementations of multiple physics models. We discuss how component framework design in combination with the Common Component Architecture's component model and implementation eases the process of incorporation of existing state-of-the-art models with newly-developed models. We discuss current developments in componentized beam dynamics software, emphasizing design issues and distribution issues

  1. A modelling approach for exploring muscle dynamics during cyclic contractions.

    Directory of Open Access Journals (Sweden)

    Stephanie A Ross

    2018-04-01

    Full Text Available Hill-type muscle models are widely used within the field of biomechanics to predict and understand muscle behaviour, and are often essential where muscle forces cannot be directly measured. However, these models have limited accuracy, particularly during cyclic contractions at the submaximal levels of activation that typically occur during locomotion. To address this issue, recent studies have incorporated effects into Hill-type models that are oftentimes neglected, such as size-dependent, history-dependent, and activation-dependent effects. However, the contribution of these effects on muscle performance has yet to be evaluated under common contractile conditions that reflect the range of activations, strains, and strain rates that occur in vivo. The purpose of this study was to develop a modelling framework to evaluate modifications to Hill-type muscle models when they contract in cyclic loops that are typical of locomotor muscle function. Here we present a modelling framework composed of a damped harmonic oscillator in series with a Hill-type muscle actuator that consists of a contractile element and parallel elastic element. The intrinsic force-length and force-velocity properties are described using Bézier curves where we present a system to relate physiological parameters to the control points for these curves. The muscle-oscillator system can be geometrically scaled while preserving dynamic and kinematic similarity to investigate the muscle size effects while controlling for the dynamics of the harmonic oscillator. The model is driven by time-varying muscle activations that cause the muscle to cyclically contract and drive the dynamics of the harmonic oscillator. Thus, this framework provides a platform to test current and future Hill-type model formulations and explore factors affecting muscle performance in muscles of different sizes under a range of cyclic contractile conditions.

  2. Dynamics of a delay differential equation model of hepatitis B virus infection.

    Science.gov (United States)

    Gourley, Stephen A; Kuang, Yang; Nagy, John D

    2008-04-01

    We formulate and systematically study the global dynamics of a simple model of hepatitis B virus in terms of delay differential equations. This model has two important and novel features compared to the well-known basic virus model in the literature. Specifically, it makes use of the more realistic standard incidence function and explicitly incorporates a time delay in virus production. As a result, the infection reproduction number is no longer dependent on the patient liver size (number of initial healthy liver cells). For this model, the existence and the component values of the endemic steady state are explicitly dependent on the time delay. In certain biologically interesting limiting scenarios, a globally attractive endemic equilibrium can exist regardless of the time delay length.

  3. Advanced Modeling and Uncertainty Quantification for Flight Dynamics; Interim Results and Challenges

    Science.gov (United States)

    Hyde, David C.; Shweyk, Kamal M.; Brown, Frank; Shah, Gautam

    2014-01-01

    As part of the NASA Vehicle Systems Safety Technologies (VSST), Assuring Safe and Effective Aircraft Control Under Hazardous Conditions (Technical Challenge #3), an effort is underway within Boeing Research and Technology (BR&T) to address Advanced Modeling and Uncertainty Quantification for Flight Dynamics (VSST1-7). The scope of the effort is to develop and evaluate advanced multidisciplinary flight dynamics modeling techniques, including integrated uncertainties, to facilitate higher fidelity response characterization of current and future aircraft configurations approaching and during loss-of-control conditions. This approach is to incorporate multiple flight dynamics modeling methods for aerodynamics, structures, and propulsion, including experimental, computational, and analytical. Also to be included are techniques for data integration and uncertainty characterization and quantification. This research shall introduce new and updated multidisciplinary modeling and simulation technologies designed to improve the ability to characterize airplane response in off-nominal flight conditions. The research shall also introduce new techniques for uncertainty modeling that will provide a unified database model comprised of multiple sources, as well as an uncertainty bounds database for each data source such that a full vehicle uncertainty analysis is possible even when approaching or beyond Loss of Control boundaries. Methodologies developed as part of this research shall be instrumental in predicting and mitigating loss of control precursors and events directly linked to causal and contributing factors, such as stall, failures, damage, or icing. The tasks will include utilizing the BR&T Water Tunnel to collect static and dynamic data to be compared to the GTM extended WT database, characterizing flight dynamics in off-nominal conditions, developing tools for structural load estimation under dynamic conditions, devising methods for integrating various modeling elements

  4. Incorporating time-delays in S-System model for reverse engineering genetic networks.

    Science.gov (United States)

    Chowdhury, Ahsan Raja; Chetty, Madhu; Vinh, Nguyen Xuan

    2013-06-18

    In any gene regulatory network (GRN), the complex interactions occurring amongst transcription factors and target genes can be either instantaneous or time-delayed. However, many existing modeling approaches currently applied for inferring GRNs are unable to represent both these interactions simultaneously. As a result, all these approaches cannot detect important interactions of the other type. S-System model, a differential equation based approach which has been increasingly applied for modeling GRNs, also suffers from this limitation. In fact, all S-System based existing modeling approaches have been designed to capture only instantaneous interactions, and are unable to infer time-delayed interactions. In this paper, we propose a novel Time-Delayed S-System (TDSS) model which uses a set of delay differential equations to represent the system dynamics. The ability to incorporate time-delay parameters in the proposed S-System model enables simultaneous modeling of both instantaneous and time-delayed interactions. Furthermore, the delay parameters are not limited to just positive integer values (corresponding to time stamps in the data), but can also take fractional values. Moreover, we also propose a new criterion for model evaluation exploiting the sparse and scale-free nature of GRNs to effectively narrow down the search space, which not only reduces the computation time significantly but also improves model accuracy. The evaluation criterion systematically adapts the max-min in-degrees and also systematically balances the effect of network accuracy and complexity during optimization. The four well-known performance measures applied to the experimental studies on synthetic networks with various time-delayed regulations clearly demonstrate that the proposed method can capture both instantaneous and delayed interactions correctly with high precision. The experiments carried out on two well-known real-life networks, namely IRMA and SOS DNA repair network in

  5. Dynamic Model for the Z Accelerator Vacuum Section Based on Transmission Line Code%Dynamic Model for the Z Accelerator Vacuum Section Based on Transmission Line Code

    Institute of Scientific and Technical Information of China (English)

    呼义翔; 雷天时; 吴撼宇; 郭宁; 韩娟娟; 邱爱慈; 王亮平; 黄涛; 丛培天; 张信军; 李岩; 曾正中; 孙铁平

    2011-01-01

    The transmission-line-circuit model of the Z accelerator, developed originally by W. A. STYGAR, P. A. CORCORAN, et al., is revised. The revised model uses different calculations for the electron loss and flow impedance in the magnetically insulated transmission line system of the Z accelerator before and after magnetic insulation is established. By including electron pressure and zero electric field at the cathode, a closed set of equations is obtained at each time step, and dynamic shunt resistance (used to represent any electron loss to the anode) and flow impedance are solved, which have been incorporated into the transmission line code for simulations of the vacuum section in the Z accelerator. Finally, the results are discussed in comparison with earlier findings to show the effectiveness and limitations of the model.

  6. Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

    Science.gov (United States)

    Heinonen, Johannes P M; Palmer, Stephen C F; Redpath, Steve M; Travis, Justin M J

    2014-01-01

    Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.

  7. Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

    Directory of Open Access Journals (Sweden)

    Johannes P M Heinonen

    Full Text Available Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.

  8. Incorporating Semantic Knowledge into Dynamic Data Processing for Smart Power Grids

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Qunzhi; Simmhan, Yogesh; Prasanna, Viktor

    2012-11-15

    Semantic Web allows us to model and query time-invariant or slowly evolving knowledge using ontologies. Emerging applications in Cyber Physical Systems such as Smart Power Grids that require continuous information monitoring and integration present novel opportunities and challenges for Semantic Web technologies. Semantic Web is promising to model diverse Smart Grid domain knowledge for enhanced situation awareness and response by multi-disciplinary participants. However, current technology does pose a performance overhead for dynamic analysis of sensor measurements. In this paper, we combine semantic web and complex event processing for stream based semantic querying. We illustrate its adoption in the USC Campus Micro-Grid for detecting and enacting dynamic response strategies to peak power situations by diverse user roles. We also describe the semantic ontology and event query model that supports this. Further, we introduce and evaluate caching techniques to improve the response time for semantic event queries to meet our application needs and enable sustainable energy management.

  9. A climatological model for risk computations incorporating site- specific dry deposition influences

    International Nuclear Information System (INIS)

    Droppo, J.G. Jr.

    1991-07-01

    A gradient-flux dry deposition module was developed for use in a climatological atmospheric transport model, the Multimedia Environmental Pollutant Assessment System (MEPAS). The atmospheric pathway model computes long-term average contaminant air concentration and surface deposition patterns surrounding a potential release site incorporating location-specific dry deposition influences. Gradient-flux formulations are used to incorporate site and regional data in the dry deposition module for this atmospheric sector-average climatological model. Application of these formulations provide an effective means of accounting for local surface roughness in deposition computations. Linkage to a risk computation module resulted in a need for separate regional and specific surface deposition computations. 13 refs., 4 figs., 2 tabs

  10. Corruption dynamics model

    Science.gov (United States)

    Malafeyev, O. A.; Nemnyugin, S. A.; Rylow, D.; Kolpak, E. P.; Awasthi, Achal

    2017-07-01

    The corruption dynamics is analyzed by means of the lattice model which is similar to the three-dimensional Ising model. Agents placed at nodes of the corrupt network periodically choose to perfom or not to perform the act of corruption at gain or loss while making decisions based on the process history. The gain value and its dynamics are defined by means of the Markov stochastic process modelling with parameters established in accordance with the influence of external and individual factors on the agent's gain. The model is formulated algorithmically and is studied by means of the computer simulation. Numerical results are obtained which demonstrate asymptotic behaviour of the corruption network under various conditions.

  11. Global sensitivity analysis of a dynamic model for gene expression in Drosophila embryos

    Science.gov (United States)

    McCarthy, Gregory D.; Drewell, Robert A.

    2015-01-01

    It is well known that gene regulation is a tightly controlled process in early organismal development. However, the roles of key processes involved in this regulation, such as transcription and translation, are less well understood, and mathematical modeling approaches in this field are still in their infancy. In recent studies, biologists have taken precise measurements of protein and mRNA abundance to determine the relative contributions of key factors involved in regulating protein levels in mammalian cells. We now approach this question from a mathematical modeling perspective. In this study, we use a simple dynamic mathematical model that incorporates terms representing transcription, translation, mRNA and protein decay, and diffusion in an early Drosophila embryo. We perform global sensitivity analyses on this model using various different initial conditions and spatial and temporal outputs. Our results indicate that transcription and translation are often the key parameters to determine protein abundance. This observation is in close agreement with the experimental results from mammalian cells for various initial conditions at particular time points, suggesting that a simple dynamic model can capture the qualitative behavior of a gene. Additionally, we find that parameter sensitivites are temporally dynamic, illustrating the importance of conducting a thorough global sensitivity analysis across multiple time points when analyzing mathematical models of gene regulation. PMID:26157608

  12. Capturing multi-stage fuzzy uncertainties in hybrid system dynamics and agent-based models for enhancing policy implementation in health systems research.

    Science.gov (United States)

    Liu, Shiyong; Triantis, Konstantinos P; Zhao, Li; Wang, Youfa

    2018-01-01

    In practical research, it was found that most people made health-related decisions not based on numerical data but on perceptions. Examples include the perceptions and their corresponding linguistic values of health risks such as, smoking, syringe sharing, eating energy-dense food, drinking sugar-sweetened beverages etc. For the sake of understanding the mechanisms that affect the implementations of health-related interventions, we employ fuzzy variables to quantify linguistic variable in healthcare modeling where we employ an integrated system dynamics and agent-based model. In a nonlinear causal-driven simulation environment driven by feedback loops, we mathematically demonstrate how interventions at an aggregate level affect the dynamics of linguistic variables that are captured by fuzzy agents and how interactions among fuzzy agents, at the same time, affect the formation of different clusters(groups) that are targeted by specific interventions. In this paper, we provide an innovative framework to capture multi-stage fuzzy uncertainties manifested among interacting heterogeneous agents (individuals) and intervention decisions that affect homogeneous agents (groups of individuals) in a hybrid model that combines an agent-based simulation model (ABM) and a system dynamics models (SDM). Having built the platform to incorporate high-dimension data in a hybrid ABM/SDM model, this paper demonstrates how one can obtain the state variable behaviors in the SDM and the corresponding values of linguistic variables in the ABM. This research provides a way to incorporate high-dimension data in a hybrid ABM/SDM model. This research not only enriches the application of fuzzy set theory by capturing the dynamics of variables associated with interacting fuzzy agents that lead to aggregate behaviors but also informs implementation research by enabling the incorporation of linguistic variables at both individual and institutional levels, which makes unstructured linguistic data

  13. Incorporating Handling Qualities Analysis into Rotorcraft Conceptual Design

    Science.gov (United States)

    Lawrence, Ben

    2014-01-01

    This paper describes the initial development of a framework to incorporate handling qualities analyses into a rotorcraft conceptual design process. In particular, the paper describes how rotorcraft conceptual design level data can be used to generate flight dynamics models for handling qualities analyses. Also, methods are described that couple a basic stability augmentation system to the rotorcraft flight dynamics model to extend analysis to beyond that of the bare airframe. A methodology for calculating the handling qualities characteristics of the flight dynamics models and for comparing the results to ADS-33E criteria is described. Preliminary results from the application of the handling qualities analysis for variations in key rotorcraft design parameters of main rotor radius, blade chord, hub stiffness and flap moment of inertia are shown. Varying relationships, with counteracting trends for different handling qualities criteria and different flight speeds are exhibited, with the action of the control system playing a complex part in the outcomes. Overall, the paper demonstrates how a broad array of technical issues across flight dynamics stability and control, simulation and modeling, control law design and handling qualities testing and evaluation had to be confronted to implement even a moderately comprehensive handling qualities analysis of relatively low fidelity models. A key outstanding issue is to how to 'close the loop' with an overall design process, and options for the exploration of how to feedback handling qualities results to a conceptual design process are proposed for future work.

  14. Using Scenario Visioning and Participatory System Dynamics Modeling to Investigate the Future: Lessons from Minnesota 2050

    Directory of Open Access Journals (Sweden)

    Kathryn J. Draeger

    2010-08-01

    Full Text Available Both scenario visioning and participatory system dynamics modeling emphasize the dynamic and uncontrollable nature of complex socio-ecological systems, and the significance of multiple feedback mechanisms. These two methodologies complement one another, but are rarely used together. We partnered with regional organizations in Minnesota to design a future visioning process that incorporated both scenarios and participatory system dynamics modeling. The three purposes of this exercise were: first, to assist regional leaders in making strategic decisions that would make their communities sustainable; second, to identify research gaps that could impede the ability of regional and state groups to plan for the future; and finally, to introduce more systems thinking into planning and policy-making around environmental issues. We found that scenarios and modeling complemented one another, and that both techniques allowed regional groups to focus on the sustainability of fundamental support systems (energy, food, and water supply. The process introduced some creative tensions between imaginative scenario visioning and quantitative system dynamics modeling, and between creating desired futures (a strong cultural norm and inhabiting the future (a premise of the Minnesota 2050 exercise. We suggest that these tensions can stimulate more agile, strategic thinking about the future.

  15. Dynamic Linear Models with R

    CERN Document Server

    Campagnoli, Patrizia; Petris, Giovanni

    2009-01-01

    State space models have gained tremendous popularity in as disparate fields as engineering, economics, genetics and ecology. Introducing general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. It illustrates the fundamental steps needed to use dynamic linear models in practice, using R package.

  16. Stochastic Modelling, Analysis, and Simulations of the Solar Cycle Dynamic Process

    Science.gov (United States)

    Turner, Douglas C.; Ladde, Gangaram S.

    2018-03-01

    Analytical solutions, discretization schemes and simulation results are presented for the time delay deterministic differential equation model of the solar dynamo presented by Wilmot-Smith et al. In addition, this model is extended under stochastic Gaussian white noise parametric fluctuations. The introduction of stochastic fluctuations incorporates variables affecting the dynamo process in the solar interior, estimation error of parameters, and uncertainty of the α-effect mechanism. Simulation results are presented and analyzed to exhibit the effects of stochastic parametric volatility-dependent perturbations. The results generalize and extend the work of Hazra et al. In fact, some of these results exhibit the oscillatory dynamic behavior generated by the stochastic parametric additative perturbations in the absence of time delay. In addition, the simulation results of the modified stochastic models influence the change in behavior of the very recently developed stochastic model of Hazra et al.

  17. Model dynamic behaviour analysis with chaotic noise using fuzzy logic based control

    International Nuclear Information System (INIS)

    Silva, Glauco Antonio Santos da

    2002-01-01

    This work presents an application of fuzzy control on dynamical system models. It has been observed that fuzzy controllers maybe used as a good alternative to the classical PI controller, once it incorporates human line behavior. Three implication relationships were used for the fussy controllers, namely, Mamdani Min, Larsen and Takagi-Sugeno. Performance comparisons were made aiming at achieving the best performance for each model used. The PI controller was used as a minimum standard, once it has been present in the industry for many years, giving acceptable performances and some degree of reliability . Two kinds of perturbations were introduced in the models to test the controllers: a ramp and chaotic perturbations. The first one is a monotonic, standard increase of an input parameter. The second one presents non-periodicity and irregularity in such a way to be quite rough to the controllers. The chaotic signal, as an analysis tool to dynamical systems, is an interesting contribution of this work. As a general conclusion it can be said the best performance, in this work, was achieved by the Takagi-Sugeno fuzzy controller. (author)

  18. Methods improvements incorporated into the SAPHIRE ASP models

    International Nuclear Information System (INIS)

    Sattison, M.B.; Blackman, H.S.; Novack, S.D.; Smith, C.L.; Rasmuson, D.M.

    1994-01-01

    The Office for Analysis and Evaluation of Operational Data (AEOD) has sought the assistance of the Idaho National Engineering Laboratory (INEL) to make some significant enhancements to the SAPHIRE-based Accident Sequence Precursor (ASP) models recently developed by the INEL. The challenge of this project is to provide the features of a full-scale PRA within the framework of the simplified ASP models. Some of these features include: (1) uncertainty analysis addressing the standard PRA uncertainties and the uncertainties unique to the ASP models and methodology, (2) incorporation and proper quantification of individual human actions and the interaction among human actions, (3) enhanced treatment of common cause failures, and (4) extension of the ASP models to more closely mimic full-scale PRAs (inclusion of more initiators, explicitly modeling support system failures, etc.). This paper provides an overview of the methods being used to make the above improvements

  19. Methods improvements incorporated into the SAPHIRE ASP models

    International Nuclear Information System (INIS)

    Sattison, M.B.; Blackman, H.S.; Novack, S.D.

    1995-01-01

    The Office for Analysis and Evaluation of Operational Data (AEOD) has sought the assistance of the Idaho National Engineering Laboratory (INEL) to make some significant enhancements to the SAPHIRE-based Accident Sequence Precursor (ASP) models recently developed by the INEL. The challenge of this project is to provide the features of a full-scale PRA within the framework of the simplified ASP models. Some of these features include: (1) uncertainty analysis addressing the standard PRA uncertainties and the uncertainties unique to the ASP models and methods, (2) incorporation and proper quantification of individual human actions and the interaction among human actions, (3) enhanced treatment of common cause failures, and (4) extension of the ASP models to more closely mimic full-scale PRAs (inclusion of more initiators, explicitly modeling support system failures, etc.). This paper provides an overview of the methods being used to make the above improvements

  20. Dynamical Analysis of bantam-Regulated Drosophila Circadian Rhythm Model

    Science.gov (United States)

    Li, Ying; Liu, Zengrong

    MicroRNAs (miRNAs) interact with 3‧untranslated region (UTR) elements of target genes to regulate mRNA stability or translation, and play a crucial role in regulating many different biological processes. bantam, a conserved miRNA, is involved in several functions, such as regulating Drosophila growth and circadian rhythm. Recently, it has been discovered that bantam plays a crucial role in the core circadian pacemaker. In this paper, based on experimental observations, a detailed dynamical model of bantam-regulated circadian clock system is developed to show the post-transcriptional behaviors in the modulation of Drosophila circadian rhythm, in which the regulation of bantam is incorporated into a classical model. The dynamical behaviors of the model are consistent with the experimental observations, which shows that bantam is an important regulator of Drosophila circadian rhythm. The sensitivity analysis of parameters demonstrates that with the regulation of bantam the system is more sensitive to perturbations, indicating that bantam regulation makes it easier for the organism to modulate its period against the environmental perturbations. The effectiveness in rescuing locomotor activity rhythms of mutated flies shows that bantam is necessary for strong and sustained rhythms. In addition, the biological mechanisms of bantam regulation are analyzed, which may help us more clearly understand Drosophila circadian rhythm regulated by other miRNAs.

  1. Mechanical Model of Geometric Cell and Topological Algorithm for Cell Dynamics from Single-Cell to Formation of Monolayered Tissues with Pattern

    KAUST Repository

    Kachalo, Së ma; Naveed, Hammad; Cao, Youfang; Zhao, Jieling; Liang, Jie

    2015-01-01

    development, and other emerging behavior. Here we describe a cell model and an efficient geometric algorithm for studying the dynamic process of tissue formation in 2D (e.g. epithelial tissues). Our approach improves upon previous methods by incorporating

  2. Modelling dynamic roughness during floods

    NARCIS (Netherlands)

    Paarlberg, Andries; Dohmen-Janssen, Catarine M.; Hulscher, Suzanne J.M.H.; Termes, A.P.P.

    2007-01-01

    In this paper, we present a dynamic roughness model to predict water levels during floods. Hysteresis effects of dune development are explicitly included. It is shown that differences between the new dynamic roughness model, and models where the roughness coefficient is calibrated, are most

  3. A gas dynamics scheme for a two moments model of radiative transfer

    International Nuclear Information System (INIS)

    Buet, Ch.; Despres, B.

    2007-01-01

    We address the discretization of the Levermore's two moments and entropy model of the radiative transfer equation. We present a new approach for the discretization of this model: first we rewrite the moment equations as a Compressible Gas Dynamics equation by introducing an additional quantity that plays the role of a density. After that we discretize using a Lagrange-projection scheme. The Lagrange-projection scheme permits us to incorporate the source terms in the fluxes of an acoustic solver in the Lagrange step, using the well-known piecewise steady approximation and thus to capture correctly the diffusion regime. Moreover we show that the discretization is entropic and preserve the flux-limited property of the moment model. Numerical examples illustrate the feasibility of our approach. (authors)

  4. Incorporating Vibration Test Results for the Advanced Stirling Convertor into the System Dynamic Model

    Science.gov (United States)

    Meer, David W.; Lewandowski, Edward J.

    2010-01-01

    The U.S. Department of Energy (DOE), Lockheed Martin Corporation (LM), and NASA Glenn Research Center (GRC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. As part of the extended operation testing of this power system, the Advanced Stirling Convertors (ASC) at NASA GRC undergo a vibration test sequence intended to simulate the vibration history that an ASC would experience when used in an ASRG for a space mission. During these tests, a data system collects several performance-related parameters from the convertor under test for health monitoring and analysis. Recently, an additional sensor recorded the slip table position during vibration testing to qualification level. The System Dynamic Model (SDM) integrates Stirling cycle thermodynamics, heat flow, mechanical mass, spring, damper systems, and electrical characteristics of the linear alternator and controller. This Paper presents a comparison of the performance of the ASC when exposed to vibration to that predicted by the SDM when exposed to the same vibration.

  5. Forecasting the shortage of neurosurgeons in Iran using a system dynamics model approach.

    Science.gov (United States)

    Rafiei, Sima; Daneshvaran, Arman; Abdollahzade, Sina

    2018-01-01

    Shortage of physicians particularly in specialty levels is considered as an important issue in Iran health system. Thus, in an uncertain environment, long-term planning is required for health professionals as a basic priority on a national scale. This study aimed to estimate the number of required neurosurgeons using system dynamic modeling. System dynamic modeling was applied to predict the gap between stock and number of required neurosurgeons in Iran up to 2020. A supply and demand simulation model was constructed for neurosurgeons using system dynamic approach. The demand model included epidemiological, demographic, and utilization variables along with supply model-incorporated current stock of neurosurgeons and flow variables such as attrition, migration, and retirement rate. Data were obtained from various governmental databases and were analyzed by Vensim PLE Version 3.0 to address the flow of health professionals, clinical infrastructure, population demographics, and disease prevalence during the time. It was forecasted that shortage in number of neurosurgeons would disappear at 2020. The most dominant determinants on predicted number of neurosurgeons were the prevalence of neurosurgical diseases, the rate for service utilization, and medical capacity of the region. Shortage of neurosurgeons in some areas of the country relates to maldistribution of the specialists. Accordingly, there is a need to reconsider the allocation system for health professionals within the country instead of increasing the overall number of acceptance quota in training positions.

  6. Dynamic modelling of n-of-1 data: powerful and flexible data analytics applied to individualised studies.

    Science.gov (United States)

    Vieira, Rute; McDonald, Suzanne; Araújo-Soares, Vera; Sniehotta, Falko F; Henderson, Robin

    2017-09-01

    N-of-1 studies are based on repeated observations within an individual or unit over time and are acknowledged as an important research method for generating scientific evidence about the health or behaviour of an individual. Statistical analyses of n-of-1 data require accurate modelling of the outcome while accounting for its distribution, time-related trend and error structures (e.g., autocorrelation) as well as reporting readily usable contextualised effect sizes for decision-making. A number of statistical approaches have been documented but no consensus exists on which method is most appropriate for which type of n-of-1 design. We discuss the statistical considerations for analysing n-of-1 studies and briefly review some currently used methodologies. We describe dynamic regression modelling as a flexible and powerful approach, adaptable to different types of outcomes and capable of dealing with the different challenges inherent to n-of-1 statistical modelling. Dynamic modelling borrows ideas from longitudinal and event history methodologies which explicitly incorporate the role of time and the influence of past on future. We also present an illustrative example of the use of dynamic regression on monitoring physical activity during the retirement transition. Dynamic modelling has the potential to expand researchers' access to robust and user-friendly statistical methods for individualised studies.

  7. Computational model to simulate the interplay effect in dynamic IMRT delivery

    International Nuclear Information System (INIS)

    Yoganathan, S A; Maria Das, K J; Kumar, Shaleen

    2014-01-01

    The purpose of this study was to develop and experimentally verify a patient specific model for simulating the interplay effect in a DMLC based IMRT delivery. A computational model was developed using MATLAB program to incorporate the interplay effect in a 2D beams eye view fluence of dynamic IMRT fields. To simulate interplay effect, the model requires two inputs: IMRT field (DMLC file with dose rate and MU) and the patient specific respiratory motion. The interplay between the DMLC leaf motion and target was simulated for three lung patients. The target trajectory data was acquired using RPM system during the treatment simulation. The model was verified experimentally for the same patients using Imatrix 2D array device placed over QUASAR motion platform in CL2100 linac. The simulated fluences and measured fluences were compared with the TPS generated static fluence (no motion) using an in-house developed gamma evaluation program (2%/2mm). The simulated results were well within agreement with the measured. Comparison of the simulated and measured fluences with the TPS static fluence resulted 55.3% and 58.5% pixels passed the gamma criteria. A patient specific model was developed and validated for simulating the interplay effect in the dynamic IMRT delivery. This model can be clinically used to quantify the dosimetric uncertainty due to the interplay effect prior to the treatment delivery.

  8. Impact of Cross-Axis Structural Dynamics on Validation of Linear Models for Space Launch System

    Science.gov (United States)

    Pei, Jing; Derry, Stephen D.; Zhou Zhiqiang; Newsom, Jerry R.

    2014-01-01

    A feasibility study was performed to examine the advisability of incorporating a set of Programmed Test Inputs (PTIs) during the Space Launch System (SLS) vehicle flight. The intent of these inputs is to provide validation to the preflight models for control system stability margins, aerodynamics, and structural dynamics. During October 2009, Ares I-X program was successful in carrying out a series of PTI maneuvers which provided a significant amount of valuable data for post-flight analysis. The resulting data comparisons showed excellent agreement with the preflight linear models across the frequency spectrum of interest. However unlike Ares I-X, the structural dynamics associated with the SLS boost phase configuration are far more complex and highly coupled in all three axes. This presents a challenge when implementing this similar system identification technique to SLS. Preliminary simulation results show noticeable mismatches between PTI validation and analytical linear models in the frequency range of the structural dynamics. An alternate approach was examined which demonstrates the potential for better overall characterization of the system frequency response as well as robustness of the control design.

  9. An electricity generation planning model incorporating demand response

    International Nuclear Information System (INIS)

    Choi, Dong Gu; Thomas, Valerie M.

    2012-01-01

    Energy policies that aim to reduce carbon emissions and change the mix of electricity generation sources, such as carbon cap-and-trade systems and renewable electricity standards, can affect not only the source of electricity generation, but also the price of electricity and, consequently, demand. We develop an optimization model to determine the lowest cost investment and operation plan for the generating capacity of an electric power system. The model incorporates demand response to price change. In a case study for a U.S. state, we show the price, demand, and generation mix implications of a renewable electricity standard, and of a carbon cap-and-trade policy with and without initial free allocation of carbon allowances. This study shows that both the demand moderating effects and the generation mix changing effects of the policies can be the sources of carbon emissions reductions, and also shows that the share of the sources could differ with different policy designs. The case study provides different results when demand elasticity is excluded, underscoring the importance of incorporating demand response in the evaluation of electricity generation policies. - Highlights: ► We develop an electric power system optimization model including demand elasticity. ► Both renewable electricity and carbon cap-and-trade policies can moderate demand. ► Both policies affect the generation mix, price, and demand for electricity. ► Moderated demand can be a significant source of carbon emission reduction. ► For cap-and-trade policies, initial free allowances change outcomes significantly.

  10. "Violent Intent Modeling: Incorporating Cultural Knowledge into the Analytical Process

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Nibbs, Faith G.

    2007-08-24

    While culture has a significant effect on the appropriate interpretation of textual data, the incorporation of cultural considerations into data transformations has not been systematic. Recognizing that the successful prevention of terrorist activities could hinge on the knowledge of the subcultures, Anthropologist and DHS intern Faith Nibbs has been addressing the need to incorporate cultural knowledge into the analytical process. In this Brown Bag she will present how cultural ideology is being used to understand how the rhetoric of group leaders influences the likelihood of their constituents to engage in violent or radicalized behavior, and how violent intent modeling can benefit from understanding that process.

  11. A Computational Fluid Dynamic Model for a Novel Flash Ironmaking Process

    Science.gov (United States)

    Perez-Fontes, Silvia E.; Sohn, Hong Yong; Olivas-Martinez, Miguel

    A computational fluid dynamic model for a novel flash ironmaking process based on the direct gaseous reduction of iron oxide concentrates is presented. The model solves the three-dimensional governing equations including both gas-phase and gas-solid reaction kinetics. The turbulence-chemistry interaction in the gas-phase is modeled by the eddy dissipation concept incorporating chemical kinetics. The particle cloud model is used to track the particle phase in a Lagrangian framework. A nucleation and growth kinetics rate expression is adopted to calculate the reduction rate of magnetite concentrate particles. Benchmark experiments reported in the literature for a nonreacting swirling gas jet and a nonpremixed hydrogen jet flame were simulated for validation. The model predictions showed good agreement with measurements in terms of gas velocity, gas temperature and species concentrations. The relevance of the computational model for the analysis of a bench reactor operation and the design of an industrial-pilot plant is discussed.

  12. A rheonomic model for the dynamical analysis of the structure-soil interaction

    International Nuclear Information System (INIS)

    Chiroiu, V.; Nicolae, V.

    1993-01-01

    The dynamical analysis of the structure-soil interaction requires an adequate modeling of the geometrical radiation phenomenon (g.r.) i.e. the propagation of the vibrating energy of the structure in the infinite medium. Newton's law of motion is not including the g.r., considered in this paper like an irreversible phenomenon. To incorporate this, a new wave motion equation is proposed, according to a complete analysis of the structure-soil interactions with an adequate formulation of the g.r. By using a system of fundamental dynamical solutions, the rheonom constraint applied to the half-space is represented as a restriction to the displacement solutions. A dimensionless formulation of the problem and the variation of dynamical and energetical quantities in respect to the frequency, as according to the diagram of the characteristic curve of g.r. are presented numerically. Sample results showing the importance of radiation energy for several motions are also shown

  13. Dynamical analysis of a model of social behavior: Criminal vs non-criminal population

    International Nuclear Information System (INIS)

    Abbas, Syed; Tripathi, Jai Prakash; Neha, A.A.

    2017-01-01

    Highlights: • A new social model of interaction between criminal and non-criminal population is proposed • The effect of law enforcement is studied • Many real life situations are analyzed • List of open problems is given for future work. - Abstract: In this paper, we construct a model motivated by the well known predator-prey model to study the interaction between criminal population and non-criminal population. Our aim is to study various possibilities of interactions between them. First we model it using simple predator-prey model, then we modify it by considering the logistic growth of non-criminal population. We clearly deduce that the model with logistic growth is better than classical one. More precisely, the role of carrying capacity on the dynamics of criminal minded population is discussed. Further, we incorporate law enforcement term in the model and study its effect. The result obtained suggest that by incorporating enforcement law, the criminal population reduces from the very beginning, which resembles with real life situation. Our result indicates that the criminal minded population exist as long as coefficient of enforcement l_c does not cross a threshold value and after this value the criminal minded population extinct. In addition, we also discuss the occurrence of saddle-node bifurcation in case of model system with law enforcement. Numerical examples and simulations are presented to illustrate the obtained results.

  14. An excitable cortex and memory model successfully predicts new pseudopod dynamics.

    Directory of Open Access Journals (Sweden)

    Robert M Cooper

    Full Text Available Motile eukaryotic cells migrate with directional persistence by alternating left and right turns, even in the absence of external cues. For example, Dictyostelium discoideum cells crawl by extending distinct pseudopods in an alternating right-left pattern. The mechanisms underlying this zig-zag behavior, however, remain unknown. Here we propose a new Excitable Cortex and Memory (EC&M model for understanding the alternating, zig-zag extension of pseudopods. Incorporating elements of previous models, we consider the cell cortex as an excitable system and include global inhibition of new pseudopods while a pseudopod is active. With the novel hypothesis that pseudopod activity makes the local cortex temporarily more excitable--thus creating a memory of previous pseudopod locations--the model reproduces experimentally observed zig-zag behavior. Furthermore, the EC&M model makes four new predictions concerning pseudopod dynamics. To test these predictions we develop an algorithm that detects pseudopods via hierarchical clustering of individual membrane extensions. Data from cell-tracking experiments agrees with all four predictions of the model, revealing that pseudopod placement is a non-Markovian process affected by the dynamics of previous pseudopods. The model is also compatible with known limits of chemotactic sensitivity. In addition to providing a predictive approach to studying eukaryotic cell motion, the EC&M model provides a general framework for future models, and suggests directions for new research regarding the molecular mechanisms underlying directional persistence.

  15. Models for dynamic analysis of backup ball bearings of an AMB-system

    Science.gov (United States)

    Halminen, Oskari; Aceituno, Javier F.; Escalona, José L.; Sopanen, Jussi; Mikkola, Aki

    2017-10-01

    Two detailed models of backup bearing are introduced for dynamic analysis of the dropdown event of a rotor supported by an active magnetic bearing (AMB). The proposed two-dimensional models of the backup bearings are based on a multibody approach. All parts of the bearing are modeled as rigid bodies with geometrical surfaces and the bodies interact with each other through contact forces. The first model describes a backup bearing without a cage, and the second model describes a backup bearing with a cage. The introduced models, which incorporate a realistic elastic contact model, are compared with previously presented simplified models through parametric study. In order to ensure the durability of backup bearings in challenging applications where ball bearings with an oversized bore are necessary, analysis of the forces affecting the bearing's cage and balls is required, and the models introduced in this work assist in this task as they enable optimal properties for the bearing's cage and balls to be found.

  16. Advanced High-Temperature Reactor Dynamic System Model Development: April 2012 Status

    Energy Technology Data Exchange (ETDEWEB)

    Qualls, A L; Cetiner, M S; Wilson, Jr, T L

    2012-04-30

    system relate to flows within the reactor vessel during severe events and the resulting temperature profiles (temperature and duration) for major components. Critical components include the fuel, reactor vessel, primary piping, and the primary-to-intermediate heat exchangers (P-IHXs). The major AHTR power system loops are shown in Fig. 3. The intermediate heat transfer system is a group of three pumped salt loops that transports the energy produced in the primary system to the power conversion system. Two dynamic system models are used to analyze the AHTR. A Matlab/Simulink-based model initiated in 2011 has been updated to reflect the evolving design parameters related to the heat flows associated with the reactor vessel. The Matlab model utilizes simplified flow assumptions within the vessel and incorporates an empirical representation of the Direct Reactor Auxiliary Cooling System (DRACS). A Dymola/Modelica model incorporates a more sophisticated representation of primary coolant flow and a physics-based representation of the three-loop DRACS thermal hydraulics. This model is not currently operating in a fully integrated mode. The Matlab model serves as a prototype and provides verification for the Dymola model, and its use will be phased out as the Dymola model nears completion. The heat exchangers in the system are sized using spreadsheet-based, steady-state calculations. The detail features of the heat exchangers are programmed into the dynamic models, and the overall dimensions are used to generate realistic plant designs. For the modeling cases where the emphasis is on understanding responses within the intermediate and primary systems, the power conversion system may be modeled as a simple boundary condition at the intermediate-to-power conversion system heat exchangers.

  17. Modelling MIZ dynamics in a global model

    Science.gov (United States)

    Rynders, Stefanie; Aksenov, Yevgeny; Feltham, Daniel; Nurser, George; Naveira Garabato, Alberto

    2016-04-01

    Exposure of large, previously ice-covered areas of the Arctic Ocean to the wind and surface ocean waves results in the Arctic pack ice cover becoming more fragmented and mobile, with large regions of ice cover evolving into the Marginal Ice Zone (MIZ). The need for better climate predictions, along with growing economic activity in the Polar Oceans, necessitates climate and forecasting models that can simulate fragmented sea ice with a greater fidelity. Current models are not fully fit for the purpose, since they neither model surface ocean waves in the MIZ, nor account for the effect of floe fragmentation on drag, nor include sea ice rheology that represents both the now thinner pack ice and MIZ ice dynamics. All these processes affect the momentum transfer to the ocean. We present initial results from a global ocean model NEMO (Nucleus for European Modelling of the Ocean) coupled to the Los Alamos sea ice model CICE. The model setup implements a novel rheological formulation for sea ice dynamics, accounting for ice floe collisions, thus offering a seamless framework for pack ice and MIZ simulations. The effect of surface waves on ice motion is included through wave pressure and the turbulent kinetic energy of ice floes. In the multidecadal model integrations we examine MIZ and basin scale sea ice and oceanic responses to the changes in ice dynamics. We analyse model sensitivities and attribute them to key sea ice and ocean dynamical mechanisms. The results suggest that the effect of the new ice rheology is confined to the MIZ. However with the current increase in summer MIZ area, which is projected to continue and may become the dominant type of sea ice in the Arctic, we argue that the effects of the combined sea ice rheology will be noticeable in large areas of the Arctic Ocean, affecting sea ice and ocean. With this study we assert that to make more accurate sea ice predictions in the changing Arctic, models need to include MIZ dynamics and physics.

  18. Dynamic modeling of sludge compaction and consolidation processes in wastewater secondary settling tanks.

    Science.gov (United States)

    Abusam, A; Keesman, K J

    2009-01-01

    The double exponential settling model is the widely accepted model for wastewater secondary settling tanks. However, this model does not estimate accurately solids concentrations in the settler underflow stream, mainly because sludge compression and consolidation processes are not considered. In activated sludge systems, accurate estimation of the solids in the underflow stream will facilitate the calibration process and can lead to correct estimates of particularly kinetic parameters related to biomass growth. Using principles of compaction and consolidation, as in soil mechanics, a dynamic model of the sludge consolidation processes taking place in the secondary settling tanks is developed and incorporated to the commonly used double exponential settling model. The modified double exponential model is calibrated and validated using data obtained from a full-scale wastewater treatment plant. Good agreement between predicted and measured data confirmed the validity of the modified model.

  19. Development of control method and dynamic model for multi-evaporator air conditioners (MEAC)

    International Nuclear Information System (INIS)

    Chen Wu; Zhou Xingxi; Deng Shiming

    2005-01-01

    Interference between operation parameters among the different evaporators makes the desirable control of MEAC hard to realize. A novel control strategy is herein proposed. The suction pressure was taken as the controlled variable to modulate the speed of its compressor, and at the same time, the room air temperatures were taken to regulate the openings of individual electronic expansion valves (EEV). A self tuning fuzzy control algorithm with a modifying factor was incorporated in the controller. A controllability test was conducted with a dynamic thermodynamic model developed with a special modeling methodology. The controllability test has shown that the control strategy and algorithm are feasible and can achieve desirable control results

  20. Multiscale Modeling of Blood Flow: Coupling Finite Elements with Smoothed Dissipative Particle Dynamics

    KAUST Repository

    Moreno Chaparro, Nicolas; Vignal, Philippe; Li, Jun; Calo, Victor M.

    2013-01-01

    A variational multi scale approach to model blood flow through arteries is proposed. A finite element discretization to represent the coarse scales (macro size), is coupled to smoothed dissipative particle dynamics that captures the fine scale features (micro scale). Blood is assumed to be incompressible, and flow is described through the Navier Stokes equation. The proposed cou- pling is tested with two benchmark problems, in fully coupled systems. Further refinements of the model can be incorporated in order to explicitly include blood constituents and non-Newtonian behavior. The suggested algorithm can be used with any particle-based method able to solve the Navier-Stokes equation.

  1. Development of control method and dynamic model for multi-evaporator air conditioners (MEAC)

    Energy Technology Data Exchange (ETDEWEB)

    Chen Wu; Zhou Xingxi; Deng Shiming E-mail: 02900058r@polyu.edu.hk

    2005-02-01

    Interference between operation parameters among the different evaporators makes the desirable control of MEAC hard to realize. A novel control strategy is herein proposed. The suction pressure was taken as the controlled variable to modulate the speed of its compressor, and at the same time, the room air temperatures were taken to regulate the openings of individual electronic expansion valves (EEV). A self tuning fuzzy control algorithm with a modifying factor was incorporated in the controller. A controllability test was conducted with a dynamic thermodynamic model developed with a special modeling methodology. The controllability test has shown that the control strategy and algorithm are feasible and can achieve desirable control results.

  2. Multiscale Modeling of Blood Flow: Coupling Finite Elements with Smoothed Dissipative Particle Dynamics

    KAUST Repository

    Moreno Chaparro, Nicolas

    2013-06-01

    A variational multi scale approach to model blood flow through arteries is proposed. A finite element discretization to represent the coarse scales (macro size), is coupled to smoothed dissipative particle dynamics that captures the fine scale features (micro scale). Blood is assumed to be incompressible, and flow is described through the Navier Stokes equation. The proposed cou- pling is tested with two benchmark problems, in fully coupled systems. Further refinements of the model can be incorporated in order to explicitly include blood constituents and non-Newtonian behavior. The suggested algorithm can be used with any particle-based method able to solve the Navier-Stokes equation.

  3. Modeling fish community dynamics in Florida Everglades: Role of temperature variation

    Science.gov (United States)

    Al-Rabai'ah, H. A.; Koh, H. L.; DeAngelis, Donald L.; Lee, Hooi-Ling

    2002-01-01

    Temperature variation is an important factor in Everglade wetlands ecology. A temperature fluctuation from 17°C to 32°C recorded in the Everglades may have significant impact on fish dynamics. The short life cycles of some of Everglade fishes has rendered this temperature variation to have even more impacts on the ecosystem. Fish population dynamic models, which do not explicitly consider seasonal oscillations in temperature, may fail to describe the details of such a population. Hence, a model for fish in freshwater marshes of the Florida Everglades that explicitly incorporates seasonal temperature variations is developed. The model's main objective is to assess the temporal pattern of fish population and densities through time subject to temperature variations. Fish population is divided into 2 functional groups (FGs) consisting of small fishes; each group is subdivided into 5-day age classes during their life cycles. Many governing sub-modules are set directly or indirectly to be temperature dependent. Growth, fecundity, prey availability, consumption rates and mortality are examples. Several mortality sub-modules are introduced in the model, of which starvation mortality is set to be proportional to the ratio of prey needed to prey available at that particular time step. As part of the calibration process, the model is run for 50 years to ensure that fish densities do not go to extinction, while the simulation period is about 8 years.

  4. Dynamic Evolution Of Off-Fault Medium During An Earthquake: A Micromechanics Based Model

    Science.gov (United States)

    Thomas, M. Y.; Bhat, H. S.

    2017-12-01

    Geophysical observations show a dramatic drop of seismic wave speeds in the shallow off-fault medium following earthquake ruptures. Seismic ruptures generate, or reactivate, damage around faults that alter the constitutive response of the surrounding medium, which in turn modifies the earthquake itself, the seismic radiation, and the near-fault ground motion. We present a micromechanics based constitutive model that accounts for dynamic evolution of elastic moduli at high-strain rates. We consider 2D in-plane models, with a 1D right lateral fault featuring slip-weakening friction law. The two scenarios studied here assume uniform initial off-fault damage and an observationally motivated exponential decay of initial damage with fault normal distance. Both scenarios produce dynamic damage that is consistent with geological observations. A small difference in initial damage actively impacts the final damage pattern. The second numerical experiment, in particular, highlights the complex feedback that exists between the evolving medium and the seismic event. We show that there is a unique off-fault damage pattern associated with supershear transition of an earthquake rupture that could be potentially seen as a geological signature of this transition. These scenarios presented here underline the importance of incorporating the complex structure of fault zone systems in dynamic models of earthquakes.

  5. Dynamic and impact contact mechanics of geologic materials: Grain-scale experiments and modeling

    International Nuclear Information System (INIS)

    Cole, David M.; Hopkins, Mark A.; Ketcham, Stephen A.

    2013-01-01

    High fidelity treatments of the generation and propagation of seismic waves in naturally occurring granular materials is becoming more practical given recent advancements in our ability to model complex particle shapes and their mechanical interaction. Of particular interest are the grain-scale processes that are activated by impact events and the characteristics of force transmission through grain contacts. To address this issue, we have developed a physics based approach that involves laboratory experiments to quantify the dynamic contact and impact behavior of granular materials and incorporation of the observed behavior indiscrete element models. The dynamic experiments do not involve particle damage and emphasis is placed on measured values of contact stiffness and frictional loss. The normal stiffness observed in dynamic contact experiments at low frequencies (e.g., 10 Hz) are shown to be in good agreement with quasistatic experiments on quartz sand. The results of impact experiments – which involve moderate to extensive levels of particle damage – are presented for several types of naturally occurring granular materials (several quartz sands, magnesite and calcium carbonate ooids). Implementation of the experimental findings in discrete element models is discussed and the results of impact simulations involving up to 5 × 105 grains are presented.

  6. Dynamic and impact contact mechanics of geologic materials: Grain-scale experiments and modeling

    Energy Technology Data Exchange (ETDEWEB)

    Cole, David M.; Hopkins, Mark A.; Ketcham, Stephen A. [Engineer Research and Development Center - Cold Regions Research and Engineering Laboratory, 72 Lyme Rd., Hanover, NH 03755 (United States)

    2013-06-18

    High fidelity treatments of the generation and propagation of seismic waves in naturally occurring granular materials is becoming more practical given recent advancements in our ability to model complex particle shapes and their mechanical interaction. Of particular interest are the grain-scale processes that are activated by impact events and the characteristics of force transmission through grain contacts. To address this issue, we have developed a physics based approach that involves laboratory experiments to quantify the dynamic contact and impact behavior of granular materials and incorporation of the observed behavior indiscrete element models. The dynamic experiments do not involve particle damage and emphasis is placed on measured values of contact stiffness and frictional loss. The normal stiffness observed in dynamic contact experiments at low frequencies (e.g., 10 Hz) are shown to be in good agreement with quasistatic experiments on quartz sand. The results of impact experiments - which involve moderate to extensive levels of particle damage - are presented for several types of naturally occurring granular materials (several quartz sands, magnesite and calcium carbonate ooids). Implementation of the experimental findings in discrete element models is discussed and the results of impact simulations involving up to 5 Multiplication-Sign 105 grains are presented.

  7. Dynamic Evolution Of Off-Fault Medium During An Earthquake: A Micromechanics Based Model

    Science.gov (United States)

    Thomas, Marion Y.; Bhat, Harsha S.

    2018-05-01

    Geophysical observations show a dramatic drop of seismic wave speeds in the shallow off-fault medium following earthquake ruptures. Seismic ruptures generate, or reactivate, damage around faults that alter the constitutive response of the surrounding medium, which in turn modifies the earthquake itself, the seismic radiation, and the near-fault ground motion. We present a micromechanics based constitutive model that accounts for dynamic evolution of elastic moduli at high-strain rates. We consider 2D in-plane models, with a 1D right lateral fault featuring slip-weakening friction law. The two scenarios studied here assume uniform initial off-fault damage and an observationally motivated exponential decay of initial damage with fault normal distance. Both scenarios produce dynamic damage that is consistent with geological observations. A small difference in initial damage actively impacts the final damage pattern. The second numerical experiment, in particular, highlights the complex feedback that exists between the evolving medium and the seismic event. We show that there is a unique off-fault damage pattern associated with supershear transition of an earthquake rupture that could be potentially seen as a geological signature of this transition. These scenarios presented here underline the importance of incorporating the complex structure of fault zone systems in dynamic models of earthquakes.

  8. Dynamic accelerator modeling

    International Nuclear Information System (INIS)

    Nishimura, Hiroshi.

    1993-05-01

    Object-Oriented Programming has been used extensively to model the LBL Advanced Light Source 1.5 GeV electron storage ring. This paper is on the present status of the class library construction with emphasis on a dynamic modeling

  9. Incorporating Dynamical Systems into the Traditional Curriculum.

    Science.gov (United States)

    Natov, Jonathan

    2001-01-01

    Presents a brief overview of dynamical systems. Gives examples from dynamical systems and where they fit into the current curriculum. Points out that these examples are accessible to undergraduate freshmen and sophomore students, add continuity to the standard curriculum, and are worth including in classes. (MM)

  10. Simulation of Forest Carbon Fluxes Using Model Incorporation and Data Assimilation

    OpenAIRE

    Min Yan; Xin Tian; Zengyuan Li; Erxue Chen; Xufeng Wang; Zongtao Han; Hong Sun

    2016-01-01

    This study improved simulation of forest carbon fluxes in the Changbai Mountains with a process-based model (Biome-BGC) using incorporation and data assimilation. Firstly, the original remote sensing-based MODIS MOD_17 GPP (MOD_17) model was optimized using refined input data and biome-specific parameters. The key ecophysiological parameters of the Biome-BGC model were determined through the Extended Fourier Amplitude Sensitivity Test (EFAST) sensitivity analysis. Then the optimized MOD_17 mo...

  11. Dynamic Modelling Of A SCARA Robot

    Science.gov (United States)

    Turiel, J. Perez; Calleja, R. Grossi; Diez, V. Gutierrez

    1987-10-01

    This paper describes a method for modelling industrial robots that considers dynamic approach to manipulation systems motion generation, obtaining the complete dynamic model for the mechanic part of the robot and taking into account the dynamic effect of actuators acting at the joints. For a four degree of freedom SCARA robot we obtain the dynamic model for the basic (minimal) configuration, that is, the three degrees of freedom that allow us to place the robot end effector in a desired point, using the Lagrange Method to obtain the dynamic equations in matrix form. The manipulator is considered to be a set of rigid bodies inter-connected by joints in the form of simple kinematic pairs. Then, the state space model is obtained for the actuators that move the robot joints, uniting the models of the single actuators, that is, two DC permanent magnet servomotors and an electrohydraulic actuator. Finally, using a computer simulation program written in FORTRAN language, we can compute the matrices of the complete model.

  12. INCORPORATING MULTIPLE OBJECTIVES IN PLANNING MODELS OF LOW-RESOURCE FARMERS

    OpenAIRE

    Flinn, John C.; Jayasuriya, Sisira; Knight, C. Gregory

    1980-01-01

    Linear goal programming provides a means of formally incorporating the multiple goals of a household into the analysis of farming systems. Using this approach, the set of plans which come as close as possible to achieving a set of desired goals under conditions of land and cash scarcity are derived for a Filipino tenant farmer. A challenge in making LGP models empirically operational is the accurate definition of the goals of the farm household being modelled.

  13. System Dynamics Modelling for a Balanced Scorecard

    DEFF Research Database (Denmark)

    Nielsen, Steen; Nielsen, Erland Hejn

    2008-01-01

    /methodology/approach - We use a case study model to develop time or dynamic dimensions by using a System Dynamics modelling (SDM) approach. The model includes five perspectives and a number of financial and non-financial measures. All indicators are defined and related to a coherent number of different cause...... have a major influence on other indicators and profit and may be impossible to predict without using a dynamic model. Practical implications - The model may be used as the first step in quantifying the cause-and-effect relationships of an integrated BSC model. Using the System Dynamics model provides......Purpose - To construct a dynamic model/framework inspired by a case study based on an international company. As described by the theory, one of the main difficulties of BSC is to foresee the time lag dimension of different types of indicators and their combined dynamic effects. Design...

  14. INCORPORATION OF MECHANISTIC INFORMATION IN THE ARSENIC PBPK MODEL DEVELOPMENT PROCESS

    Science.gov (United States)

    INCORPORATING MECHANISTIC INSIGHTS IN A PBPK MODEL FOR ARSENICElaina M. Kenyon, Michael F. Hughes, Marina V. Evans, David J. Thomas, U.S. EPA; Miroslav Styblo, University of North Carolina; Michael Easterling, Analytical Sciences, Inc.A physiologically based phar...

  15. Peri-dynamics

    International Nuclear Information System (INIS)

    Littlewood, D.

    2015-01-01

    Peri-dynamics, a nonlocal extension of continuum mechanics, is a natural framework for capturing constitutive response and modelling pervasive material failure and fracture. Unlike classical approaches incorporating partial derivatives, the peri-dynamic governing equations utilise integral expressions that remain valid in the presence of discontinuities such as cracks. The mathematical theory of peri-dynamics unifies the mechanics of continuous media, cracks, and discrete particles. The result is a consistent framework for capturing a wide range of constitutive responses, including inelasticity, in combination with robust material failure laws. Peri-dynamics has been implemented in a number of computational simulation codes, including the open source code Peridigm and the Sierra/SolidMechanics analysis code at Sandia National Laboratories. (author)

  16. Dynamic information architecture system (DIAS) : multiple model simulation management

    International Nuclear Information System (INIS)

    Simunich, K. L.; Sydelko, P.; Dolph, J.; Christiansen, J.

    2002-01-01

    Dynamic Information Architecture System (DIAS) is a flexible, extensible, object-based framework for developing and maintaining complex multidisciplinary simulations of a wide variety of application contexts. The modeling domain of a specific DIAS-based simulation is determined by (1) software Entity (domain-specific) objects that represent the real-world entities that comprise the problem space (atmosphere, watershed, human), and (2) simulation models and other data processing applications that express the dynamic behaviors of the domain entities. In DIAS, models communicate only with Entity objects, never with each other. Each Entity object has a number of Parameter and Aspect (of behavior) objects associated with it. The Parameter objects contain the state properties of the Entity object. The Aspect objects represent the behaviors of the Entity object and how it interacts with other objects. DIAS extends the ''Object'' paradigm by abstraction of the object's dynamic behaviors, separating the ''WHAT'' from the ''HOW.'' DIAS object class definitions contain an abstract description of the various aspects of the object's behavior (the WHAT), but no implementation details (the HOW). Separate DIAS models/applications carry the implementation of object behaviors (the HOW). Any model deemed appropriate, including existing legacy-type models written in other languages, can drive entity object behavior. The DIAS design promotes plug-and-play of alternative models, with minimal recoding of existing applications. The DIAS Context Builder object builds a constructs or scenario for the simulation, based on developer specification and user inputs. Because DIAS is a discrete event simulation system, there is a Simulation Manager object with which all events are processed. Any class that registers to receive events must implement an event handler (method) to process the event during execution. Event handlers can schedule other events; create or remove Entities from the

  17. Travelling wave solutions for the Richards equation incorporating non-equilibrium effects in the capillarity pressure

    NARCIS (Netherlands)

    van Duijn, C. J.; Mitra, K.; Pop, I. S.

    2018-01-01

    The Richards equation is a mathematical model for unsaturated flow through porous media. This paper considers an extension of the Richards equation, where non-equilibrium effects like hysteresis and dynamic capillarity are incorporated in the relationship that relates the water pressure and the

  18. System dynamics modeling of social/political factors in nuclear power plant operations

    International Nuclear Information System (INIS)

    Hansen, K.F.; Turek, M.G.; Eubanks, C.K.

    1995-01-01

    The safety and performance of nuclear power plants are a function of many technical factors such as initial design, service and maintenance programs, and utility investment in improvements. Safety and performance are also a function of the social/political influences that affect requirements on personnel, practices and procedures, and resource availability. This paper describes a process for constructing models of the social/political influences on plant operations using the system dynamics technique. The model incorporates representation of internal utility actions and decisions as affected by external factors such as public opinion, intervenor actions, safety and economic regulation, and the financial community. The feedback between external agents and plant performance is explicitly modeled. The resulting model can be used to simulate performance under a variety of different external and internal policy choices. In particular, the model can be used to study means of improving performance in response to externally imposed regulations

  19. A code reviewer assignment model incorporating the competence differences and participant preferences

    Directory of Open Access Journals (Sweden)

    Wang Yanqing

    2016-03-01

    Full Text Available A good assignment of code reviewers can effectively utilize the intellectual resources, assure code quality and improve programmers’ skills in software development. However, little research on reviewer assignment of code review has been found. In this study, a code reviewer assignment model is created based on participants’ preference to reviewing assignment. With a constraint of the smallest size of a review group, the model is optimized to maximize review outcomes and avoid the negative impact of “mutual admiration society”. This study shows that the reviewer assignment strategies incorporating either the reviewers’ preferences or the authors’ preferences get much improvement than a random assignment. The strategy incorporating authors’ preference makes higher improvement than that incorporating reviewers’ preference. However, when the reviewers’ and authors’ preference matrixes are merged, the improvement becomes moderate. The study indicates that the majority of the participants have a strong wish to work with reviewers and authors having highest competence. If we want to satisfy the preference of both reviewers and authors at the same time, the overall improvement of learning outcomes may be not the best.

  20. Energy system investment model incorporating heat pumps with thermal storage in buildings and buffer tanks

    International Nuclear Information System (INIS)

    Hedegaard, Karsten; Balyk, Olexandr

    2013-01-01

    Individual compression heat pumps constitute a potentially valuable resource in supporting wind power integration due to their economic competitiveness and possibilities for flexible operation. When analysing the system benefits of flexible heat pump operation, effects on investments should be taken into account. In this study, we present a model that facilitates analysing individual heat pumps and complementing heat storages in integration with the energy system, while optimising both investments and operation. The model incorporates thermal building dynamics and covers various heat storage options: passive heat storage in the building structure via radiator heating, active heat storage in concrete floors via floor heating, and use of thermal storage tanks for space heating and hot water. It is shown that the model is well qualified for analysing possibilities and system benefits of operating heat pumps flexibly. This includes prioritising heat pump operation for hours with low marginal electricity production costs, and peak load shaving resulting in a reduced need for peak and reserve capacity investments. - Highlights: • Model optimising heat pumps and heat storages in integration with the energy system. • Optimisation of both energy system investments and operation. • Heat storage in building structure and thermal storage tanks included. • Model well qualified for analysing system benefits of flexible heat pump operation. • Covers peak load shaving and operation prioritised for low electricity prices

  1. Sustainable infrastructure system modeling under uncertainties and dynamics

    Science.gov (United States)

    Huang, Yongxi

    Infrastructure systems support human activities in transportation, communication, water use, and energy supply. The dissertation research focuses on critical transportation infrastructure and renewable energy infrastructure systems. The goal of the research efforts is to improve the sustainability of the infrastructure systems, with an emphasis on economic viability, system reliability and robustness, and environmental impacts. The research efforts in critical transportation infrastructure concern the development of strategic robust resource allocation strategies in an uncertain decision-making environment, considering both uncertain service availability and accessibility. The study explores the performances of different modeling approaches (i.e., deterministic, stochastic programming, and robust optimization) to reflect various risk preferences. The models are evaluated in a case study of Singapore and results demonstrate that stochastic modeling methods in general offers more robust allocation strategies compared to deterministic approaches in achieving high coverage to critical infrastructures under risks. This general modeling framework can be applied to other emergency service applications, such as, locating medical emergency services. The development of renewable energy infrastructure system development aims to answer the following key research questions: (1) is the renewable energy an economically viable solution? (2) what are the energy distribution and infrastructure system requirements to support such energy supply systems in hedging against potential risks? (3) how does the energy system adapt the dynamics from evolving technology and societal needs in the transition into a renewable energy based society? The study of Renewable Energy System Planning with Risk Management incorporates risk management into its strategic planning of the supply chains. The physical design and operational management are integrated as a whole in seeking mitigations against the

  2. Incorporating model parameter uncertainty into inverse treatment planning

    International Nuclear Information System (INIS)

    Lian Jun; Xing Lei

    2004-01-01

    Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment

  3. Modelling nitrogen dynamics and distributions in the River Tweed, Scotland: an application of the INCA model

    Directory of Open Access Journals (Sweden)

    H. P. Jarvie

    2002-01-01

    Full Text Available The INCA (Integrated Nitrogen in Catchments model was applied to the River Tweed in the Scottish Borders, a large-scale (4400km2, spatially heterogeneous catchment, draining a wide range of agricultural land-use types, and which contributes approximately 20% of UK river flows to the North Sea. The model was calibrated for the first four years' data record (1994 to 1997 and tested over the following three years (1998 to 2000. The model calibration and testing periods incorporated a high degree of variability in climatic conditions and river flows within the Tweed catchment. The ability of the INCA model to reproduce broad-scale spatial patterns and seasonal dynamics in river flows and nitrate concentrations suggests that the processes controlling first order variability in river water nitrate concentrations have been represented successfully within the model. The tendency of the model to overestimate summer/early autumn baseflow nitrate concentrations during dry years may be linked to the operation of aquatic plant uptake effects. It is, therefore, suggested that consideration be given to incorporating a spatially and temporally variable in-stream plant uptake term for the application of INCA to lowland eutrophic rivers. Scenarios to examine possible impacts of environmental change on nitrate concentrations on the Tweed are examined. These include the effects of (i implementing different recommendations for fertiliser use and land use change under the Nitrate Sensitive Areas (NSA Scheme and the Scottish Code of Good Agricultural Practice, (ii worst case scenario changes linked to a dramatic reduction in livestock numbers as a result of a crisis in UK livestock farming and (iii changes in atmospheric nitrogen deposition. Keywords: Nitrate, nitrogen, modelling, Tweed, INCA

  4. Functional dynamic factor models with application to yield curve forecasting

    KAUST Repository

    Hays, Spencer

    2012-09-01

    Accurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasting has been elusive, and prior attempts often resulted in a trade-off between goodness of fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM with functional factor loading curves. This results in a model capable of forecasting functional time series. Further, in the yield curve context we show that the model retains economic interpretation. Model estimation is achieved through an expectation- maximization algorithm, where the time series parameters and factor loading curves are simultaneously estimated in a single step. Efficient computing is implemented and a data-driven smoothing parameter is nicely incorporated. We show that our model performs very well on forecasting actual yield data compared with existing approaches, especially in regard to profit-based assessment for an innovative trading exercise. We further illustrate the viability of our model to applications outside of yield forecasting.

  5. A stochastic spatial model of HIV dynamics with an asymmetric battle between the virus and the immune system

    International Nuclear Information System (INIS)

    Lin Hai; Shuai, J W

    2010-01-01

    A stochastic spatial model based on the Monte Carlo approach is developed to study the dynamics of human immunodeficiency virus (HIV) infection. We aim to propose a more detailed and realistic simulation frame by incorporating many important features of HIV dynamics, which include infections, replications and mutations of viruses, antigen recognitions, activations and proliferations of lymphocytes, and diffusions, encounters and interactions of virions and lymphocytes. Our model successfully reproduces the three-phase pattern observed in HIV infection, and the simulation results for the time distribution from infection to AIDS onset are also in good agreement with the clinical data. The interactions of viruses and the immune system in all the three phases are investigated. We assess the relative importance of various immune system components in the acute phase. The dynamics of how the two important factors, namely the viral diversity and the asymmetric battle between HIV and the immune system, result in AIDS are investigated in detail with the model.

  6. Generative Models of Conformational Dynamics

    Science.gov (United States)

    Langmead, Christopher James

    2014-01-01

    Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term ‘generative’ refers to a model of the joint probability distribution over the behaviors of the constituent atoms. In the context of molecular modeling, generative models reveal the correlation structure between the atoms, and may be used to predict how the system will respond to structural perturbations. We begin by discussing traditional methods, which produce multivariate Gaussian models. We then discuss GAMELAN (GrAphical Models of Energy LANdscapes), which produces generative models of complex, non-Gaussian conformational dynamics (e.g., allostery, binding, folding, etc) from long timescale simulation data. PMID:24446358

  7. A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making

    Directory of Open Access Journals (Sweden)

    Sabine Prezenski

    2017-08-01

    Full Text Available Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying

  8. A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making.

    Science.gov (United States)

    Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

    2017-01-01

    Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from

  9. Particle dynamics during electronic sputtering of solid krypton

    DEFF Research Database (Denmark)

    Dutkiewicz, L.; Pedrys, R.; Schou, Jørgen

    1995-01-01

    We have modeled electronic sputtering of solid krypton by excimer production with molecular dynamics. Both excimer evolution in the solid and deexcitation processes have been incorporated in the simulation. The excimer dynamics in the lattice has been analyzed: the excimers formed near the surface...

  10. Unsteady Vibration Aerodynamic Modeling and Evaluation of Dynamic Derivatives Using Computational Fluid Dynamics

    Directory of Open Access Journals (Sweden)

    Xu Liu

    2015-01-01

    Full Text Available Unsteady aerodynamic system modeling is widely used to solve the dynamic stability problems encountering aircraft design. In this paper, single degree-of-freedom (SDF vibration model and forced simple harmonic motion (SHM model for dynamic derivative prediction are developed on the basis of modified Etkin model. In the light of the characteristics of SDF time domain solution, the free vibration identification methods for dynamic stability parameters are extended and applied to the time domain numerical simulation of blunted cone calibration model examples. The dynamic stability parameters by numerical identification are no more than 0.15% deviated from those by experimental simulation, confirming the correctness of SDF vibration model. The acceleration derivatives, rotary derivatives, and combination derivatives of Army-Navy Spinner Rocket are numerically identified by using unsteady N-S equation and solving different SHV patterns. Comparison with the experimental result of Army Ballistic Research Laboratories confirmed the correctness of the SHV model and dynamic derivative identification. The calculation result of forced SHM is better than that by the slender body theory of engineering approximation. SDF vibration model and SHM model for dynamic stability parameters provide a solution to the dynamic stability problem encountering aircraft design.

  11. Dynamic Airspace Managment - Models and Algorithms

    OpenAIRE

    Cheng, Peng; Geng, Rui

    2010-01-01

    This chapter investigates the models and algorithms for implementing the concept of Dynamic Airspace Management. Three models are discussed. First two models are about how to use or adjust air route dynamically in order to speed up air traffic flow and reduce delay. The third model gives a way to dynamically generate the optimal sector configuration for an air traffic control center to both balance the controller’s workload and save control resources. The first model, called the Dynami...

  12. RETRAN dynamic slip model

    International Nuclear Information System (INIS)

    McFadden, J.H.; Paulsen, M.P.; Gose, G.C.

    1981-01-01

    A time dependent equation for the slip velocity in a two-phase flow condition has been incorporated into a developmental version of the RETRAN computer code. This model addition has been undertaken to remove a limitation in RETRAN-01 associated with the homogeneous equilibrium mixture model. In this paper, the development of the slip model is summarized and the corresponding constitutive equations are discussed. Comparisons of RETRAN analyses with steady-state void fraction data and data from the Semiscale S-02-6 small break test are also presented

  13. Modeling dynamic behavior of Radon-222 in the planetary boundary layer

    International Nuclear Information System (INIS)

    Yuan, Y.C.; Stunder, M.J.

    1983-01-01

    A model has been used to simulate the dynamic behavior of radon concentration in the lower atmosphere from naturally occurring sources. The model includes prediction of radon exhalation rate from the surface of the ground due to convection and diffusion processes and the radon concentration profile in the planetary boundary layer. A time-dependent radon exhalation rate, variable mixing height, and altitude-dependent diffusivity are incorporated into the diffusion model by transforming the governing equation. The Galerkin finite-element technique and Crank-Nicholson finite different time marching are used in solving the discretized differential equations. The model-simulated time-varying radon concentrations near the ground agree well with measurements made over a period of seven days. It has been demonstrated that the model provides a reasonably good prediction of ambient radon concentration. As a general tool, with the input of actual radon concentration measurements, the model is also capable of estimating average radon exhalation rate from the ground surface. With current techniques, radon flux measurement is still a time-consuming and difficult task

  14. Development of control method and dynamic model for multi-evaporator air conditioners (MEAC)

    Energy Technology Data Exchange (ETDEWEB)

    Chen Wu; Deng Shiming [Hong Kong Polytechnic University (China). Dept. of Building Services Engineering; Zhou Xingxi [Shanghai Jiao Tong University (China). Institute of Refrigeration and Cryogenics

    2005-02-01

    Interference between operation parameters among the different evaporators makes the desirable control of MEAC hard to realize. A novel control strategy is herein proposed. The suction pressure was taken as the controlled variable to modulate the speed of its compressor, and at the same time, the room air temperatures were taken to regulate the openings of individual electronic expansion valves (EEV). A self tuning fuzzy control algorithm with a modifying factor was incorporated in the controller. A controllability test was conducted with a dynamic thermodynamic model developed with a special modeling methodology. The controllability test has shown that the control strategy and algorithm are feasible and can achieve desirable control results. (author)

  15. Constraining Distributed Catchment Models by Incorporating Perceptual Understanding of Spatial Hydrologic Behaviour

    Science.gov (United States)

    Hutton, Christopher; Wagener, Thorsten; Freer, Jim; Han, Dawei

    2016-04-01

    Distributed models offer the potential to resolve catchment systems in more detail, and therefore simulate the hydrological impacts of spatial changes in catchment forcing (e.g. landscape change). Such models tend to contain a large number of poorly defined and spatially varying model parameters which are therefore computationally expensive to calibrate. Insufficient data can result in model parameter and structural equifinality, particularly when calibration is reliant on catchment outlet discharge behaviour alone. Evaluating spatial patterns of internal hydrological behaviour has the potential to reveal simulations that, whilst consistent with measured outlet discharge, are qualitatively dissimilar to our perceptual understanding of how the system should behave. We argue that such understanding, which may be derived from stakeholder knowledge across different catchments for certain process dynamics, is a valuable source of information to help reject non-behavioural models, and therefore identify feasible model structures and parameters. The challenge, however, is to convert different sources of often qualitative and/or semi-qualitative information into robust quantitative constraints of model states and fluxes, and combine these sources of information together to reject models within an efficient calibration framework. Here we present the development of a framework to incorporate different sources of data to efficiently calibrate distributed catchment models. For each source of information, an interval or inequality is used to define the behaviour of the catchment system. These intervals are then combined to produce a hyper-volume in state space, which is used to identify behavioural models. We apply the methodology to calibrate the Penn State Integrated Hydrological Model (PIHM) at the Wye catchment, Plynlimon, UK. Outlet discharge behaviour is successfully simulated when perceptual understanding of relative groundwater levels between lowland peat, upland peat

  16. Computer Modelling of Dynamic Processes

    Directory of Open Access Journals (Sweden)

    B. Rybakin

    2000-10-01

    Full Text Available Results of numerical modeling of dynamic problems are summed in the article up. These problems are characteristic for various areas of human activity, in particular for problem solving in ecology. The following problems are considered in the present work: computer modeling of dynamic effects on elastic-plastic bodies, calculation and determination of performances of gas streams in gas cleaning equipment, modeling of biogas formation processes.

  17. Hybrid dynamics for currency modeling

    OpenAIRE

    Theodosopoulos, Ted; Trifunovic, Alex

    2006-01-01

    We present a simple hybrid dynamical model as a tool to investigate behavioral strategies based on trend following. The multiplicative symbolic dynamics are generated using a lognormal diffusion model for the at-the-money implied volatility term structure. Thus, are model exploits information from derivative markets to obtain qualititative properties of the return distribution for the underlier. We apply our model to the JPY-USD exchange rate and the corresponding 1mo., 3mo., 6mo. and 1yr. im...

  18. Comparison of Two Mechanistic Microbial Growth Models to Estimate Shelf Life of Perishable Food Package under Dynamic Temperature Conditions

    Directory of Open Access Journals (Sweden)

    Dong Sun Lee

    2014-01-01

    Full Text Available Two mechanistic microbial growth models (Huang’s model and model of Baranyi and Roberts given in differential and integrated equation forms were compared in predicting the microbial growth and shelf life under dynamic temperature storage and distribution conditions. Literatures consistently reporting the microbial growth data under constant and changing temperature conditions were selected to obtain the primary model parameters, set up the secondary models, and apply them to predict the microbial growth and shelf life under fluctuating temperatures. When evaluated by general estimation behavior, bias factor, accuracy factor, and root-mean-square error, Huang’s model was comparable to Baranyi and Roberts’ model in the capability to estimate microbial growth under dynamic temperature conditions. Its simple form of single differential equation incorporating directly the growth rate and lag time may work as an advantage to be used in online shelf life estimation by using the electronic device.

  19. An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics.

    Science.gov (United States)

    Armen, Roger S; Chen, Jianhan; Brooks, Charles L

    2009-10-13

    Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and "noise" that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds.

  20. Estimating indices of range shifts in birds using dynamic models when detection is imperfect

    Science.gov (United States)

    Clement, Matthew J.; Hines, James E.; Nichols, James D.; Pardieck, Keith L.; Ziolkowski, David J.

    2016-01-01

    There is intense interest in basic and applied ecology about the effect of global change on current and future species distributions. Projections based on widely used static modeling methods implicitly assume that species are in equilibrium with the environment and that detection during surveys is perfect. We used multiseason correlated detection occupancy models, which avoid these assumptions, to relate climate data to distributional shifts of Louisiana Waterthrush in the North American Breeding Bird Survey (BBS) data. We summarized these shifts with indices of range size and position and compared them to the same indices obtained using more basic modeling approaches. Detection rates during point counts in BBS surveys were low, and models that ignored imperfect detection severely underestimated the proportion of area occupied and slightly overestimated mean latitude. Static models indicated Louisiana Waterthrush distribution was most closely associated with moderate temperatures, while dynamic occupancy models indicated that initial occupancy was associated with diurnal temperature ranges and colonization of sites was associated with moderate precipitation. Overall, the proportion of area occupied and mean latitude changed little during the 1997–2013 study period. Near-term forecasts of species distribution generated by dynamic models were more similar to subsequently observed distributions than forecasts from static models. Occupancy models incorporating a finite mixture model on detection – a new extension to correlated detection occupancy models – were better supported and may reduce bias associated with detection heterogeneity. We argue that replacing phenomenological static models with more mechanistic dynamic models can improve projections of future species distributions. In turn, better projections can improve biodiversity forecasts, management decisions, and understanding of global change biology.

  1. Dynamic wake meandering modeling

    Energy Technology Data Exchange (ETDEWEB)

    Larsen, Gunner C.; Aagaard Madsen, H.; Bingoel, F. (and others)

    2007-06-15

    We present a consistent, physically based theory for the wake meandering phenomenon, which we consider of crucial importance for the overall description of wind turbine loadings in wind farms. In its present version the model is confined to single wake situations. The model philosophy does, however, have the potential to include also mutual wake interaction phenomenons. The basic conjecture behind the dynamic wake meandering model is that wake transportation in the atmospheric boundary layer is driven by the large scale lateral- and vertical turbulence components. Based on this conjecture a stochastic model of the downstream wake meandering is formulated. In addition to the kinematic formulation of the dynamics of the 'meandering frame of reference', models characterizing the mean wake deficit as well as the added wake turbulence, described in the meandering frame of reference, are an integrated part the model complex. For design applications, the computational efficiency of wake deficit prediction is a key issue. Two computationally low cost models are developed for this purpose. The character of the added wake turbulence, generated by the up-stream turbine in the form of shed and trailed vorticity, has been approached by analytical as well as by numerical studies. The dynamic wake meandering philosophy has been verified by comparing model predictions with extensive full-scale measurements. These comparisons have demonstrated good agreement, both qualitatively and quantitatively, concerning both flow characteristics and turbine load characteristics. Contrary to previous attempts to model wake loading, the dynamic wake meandering approach opens for a unifying description in the sense that turbine power and load aspects can be treated simultaneously. This capability is a direct and attractive consequence of the model being based on the underlying physical process, and it potentially opens for optimization of wind farm topology, of wind farm operation as

  2. Incorporation particle creation and annihilation into Bohm's Pilot Wave model

    Energy Technology Data Exchange (ETDEWEB)

    Sverdlov, Roman [Raman Research Institute, C.V. Raman Avenue, Sadashiva Nagar, Bangalore, Karnataka, 560080 (India)

    2011-07-08

    The purpose of this paper is to come up with a Pilot Wave model of quantum field theory that incorporates particle creation and annihilation without sacrificing determinism; this theory is subsequently coupled with gravity.

  3. Dynamic modelling of nuclear steam generators

    International Nuclear Information System (INIS)

    Kerlin, T.W.; Katz, E.M.; Freels, J.; Thakkar, J.

    1980-01-01

    Moving boundary, nodal models with dynamic energy balances, dynamic mass balances, quasi-static momentum balances, and an equivalent single channel approach have been developed for steam generators used in nuclear power plants. The model for the U-tube recirculation type steam generator is described and comparisons are made of responses from models of different complexity; non-linear versus linear, high-order versus low order, detailed modeling of the control system versus a simple control assumption. The results of dynamic tests on nuclear power systems show that when this steam generator model is included in a system simulation there is good agreement with actual plant performance. (author)

  4. Towards a comprehensive framework for cosimulation of dynamic models with an emphasis on time stepping

    Science.gov (United States)

    Hoepfer, Matthias

    Over the last two decades, computer modeling and simulation have evolved as the tools of choice for the design and engineering of dynamic systems. With increased system complexities, modeling and simulation become essential enablers for the design of new systems. Some of the advantages that modeling and simulation-based system design allows for are the replacement of physical tests to ensure product performance, reliability and quality, the shortening of design cycles due to the reduced need for physical prototyping, the design for mission scenarios, the invoking of currently nonexisting technologies, and the reduction of technological and financial risks. Traditionally, dynamic systems are modeled in a monolithic way. Such monolithic models include all the data, relations and equations necessary to represent the underlying system. With increased complexity of these models, the monolithic model approach reaches certain limits regarding for example, model handling and maintenance. Furthermore, while the available computer power has been steadily increasing according to Moore's Law (a doubling in computational power every 10 years), the ever-increasing complexities of new models have negated the increased resources available. Lastly, modern systems and design processes are interdisciplinary, enforcing the necessity to make models more flexible to be able to incorporate different modeling and design approaches. The solution to bypassing the shortcomings of monolithic models is cosimulation. In a very general sense, co-simulation addresses the issue of linking together different dynamic sub-models to a model which represents the overall, integrated dynamic system. It is therefore an important enabler for the design of interdisciplinary, interconnected, highly complex dynamic systems. While a basic co-simulation setup can be very easy, complications can arise when sub-models display behaviors such as algebraic loops, singularities, or constraints. This work frames the

  5. Improving Watershed-Scale Hydrodynamic Models by Incorporating Synthetic 3D River Bathymetry Network

    Science.gov (United States)

    Dey, S.; Saksena, S.; Merwade, V.

    2017-12-01

    Digital Elevation Models (DEMs) have an incomplete representation of river bathymetry, which is critical for simulating river hydrodynamics in flood modeling. Generally, DEMs are augmented with field collected bathymetry data, but such data are available only at individual reaches. Creating a hydrodynamic model covering an entire stream network in the basin requires bathymetry for all streams. This study extends a conceptual bathymetry model, River Channel Morphology Model (RCMM), to estimate the bathymetry for an entire stream network for application in hydrodynamic modeling using a DEM. It is implemented at two large watersheds with different relief and land use characterizations: coastal Guadalupe River basin in Texas with flat terrain and a relatively urban White River basin in Indiana with more relief. After bathymetry incorporation, both watersheds are modeled using HEC-RAS (1D hydraulic model) and Interconnected Pond and Channel Routing (ICPR), a 2-D integrated hydrologic and hydraulic model. A comparison of the streamflow estimated by ICPR at the outlet of the basins indicates that incorporating bathymetry influences streamflow estimates. The inundation maps show that bathymetry has a higher impact on flat terrains of Guadalupe River basin when compared to the White River basin.

  6. A two-site mean field model of discontinuous dynamic recrystallization

    International Nuclear Information System (INIS)

    Bernard, P.; Bag, S.; Huang, K.; Loge, R.E.

    2011-01-01

    Highlights: → Discontinuous dynamic recrystallization (DDRX) is modelled at the grain scale. → The two-site mean field approach allows introducing topological information. → DDRX kinetics, flow stress curves and recrystallized grain size are well predicted. → Temperature, strain rate and initial grain size effects are successfully described. → Grain size dependence naturally emerges from the model and agrees with experiment. - Abstract: The paper describes a new model of discontinuous dynamic recrystallization (DDRX) which can operate in constant or variable thermomechanical conditions. The model considers the elementary physical phenomena at the grain scale such as strain hardening, recovery, grain boundary migration, and nucleation. The microstructure is represented through a set of representative grains defined by their size and dislocation density. It is linked to a constitutive law giving access to the polycrystal flow stress. Interaction between representative grains and the surrounding material is idealized using a two-site approach whereby two homogeneous equivalent media with different dislocation densities are considered. Topological information is incorporated into the model by prescribing the relative weight of these two equivalent media as a function of their volume fractions. This procedure allows accounting for the well-known necklace structures. The model is applied to the prediction of DDRX in 304 L stainless steel, with parameters identified using an inverse methodology based on a genetic algorithm. Results show good agreement with experimental data at different temperatures and strain rates, predicting recrystallization kinetics, recrystallized grain size and stress-strain curve. Parameters identified with one initial grain size lead to accurate results for another initial grain size without introducing any additional parameter.

  7. CERES: a model of forest stand biomass dynamics for predicting trace contaminant, nutrient, and water effects. I. Model description

    Energy Technology Data Exchange (ETDEWEB)

    Dixon, K R; Luxmoore, R J; Begovich, C L

    1978-06-01

    CERES is a forest stand growth model which incorporates sugar transport in order to predict both short-term effects and long-term accumulation of trace contaminants and/or nutrients when coupled with the soil chemistry model (SCHEM), and models of solute uptake (DIFMAS and DRYADS) of the Unified Transport Model, UTM. An important feature of CERES is its ability to interface with the soil--plant--atmosphere water model (PROSPER) as a means of both predicting and studying the effects of plant water status on growth and solute transport. CERES considers the biomass dynamics of plants, standing dead and litter with plants divided into leaves, stems, roots, and fruits. The plant parts are divided further into sugar substrate, storage, and in the case of stems and roots, heartwood components. Each ecosystem omponent is described by a mass balance equation written as a first-order ordinary differential equation.

  8. A paradigm for modeling and computation of gas dynamics

    Science.gov (United States)

    Xu, Kun; Liu, Chang

    2017-02-01

    modeling methods, such as DSMC, particle in cell, and smooth particle hydrodynamics, play a dominant role to incorporate the flow physics into the algorithm construction directly. It is fully legitimate to combine the modeling and computation together without going through the process of constructing PDEs. In other words, the CFD research is not only to obtain the numerical solution of governing equations but to model flow dynamics as well. This methodology leads to the unified gas-kinetic scheme (UGKS) for flow simulation in all flow regimes. Based on UGKS, the boundary for the validation of the Navier-Stokes equations can be quantitatively evaluated. The combination of modeling and computation provides a paradigm for the description of multiscale transport process.

  9. Mathematical modeling of alignment dynamics in active motor-filament systems

    Science.gov (United States)

    Swaminathan, Sumanth

    The formation of the cytoskeleton, via motor-mediated microtubule self-organization, is an important subject of study in the biological sciences as well as in nonequilibrium, soft matter physics. Accurate modeling of the dynamics is a formidable task as it involves intrinsic nonlinearities, structural anisotropies, nonequilibrium processes, and a broad window of time scales, length scales, and densities. In this thesis, we study the ordering dynamics and pattern formations arising from motor-mediated microtubule self-organization in dilute and semi-dilute filament solutions. In the dilute case, we use a probabilistic model in which microtubules interact through motor induced, inelastic binary collisions. This model shows that initially disordered filament solutions exhibit an ordering transition resulting in the emergence of well aligned rod bundles. We study the existence and dynamic interaction of microtubule bundles analytically and numerically. Our results show a long term attraction and coalescing of bundles indicating a clear coarsening in the system; microtubule bundles concentrate into fewer orientations on a slow logarithmic time scale. In the semi-dilute case, multiple motors can bind a filament to several others and, for a critical motor density, induce a transition to an ordered state with a nonzero mean orientation. We develop a spatially homogeneous, mean-field theory that explicitly accounts for motor forcing and thermal fluctuations which enter into the model as multiplicative and additive noises respectively. Our model further incorporates a force-dependent detachment rate of motors, which in turn affects the mean and the fluctuations of the net force acting on a filament. We demonstrate that the transition to the oriented state changes from second order to first order when the force-dependent detachment becomes important. In our final analysis, we add complex spatial inhomogeneities to our mean field theory. The revised model consists of a system

  10. BIOMAP A Daily Time Step, Mechanistic Model for the Study of Ecosystem Dynamics

    Science.gov (United States)

    Wells, J. R.; Neilson, R. P.; Drapek, R. J.; Pitts, B. S.

    2010-12-01

    BIOMAP simulates competition between two Plant Functional Types (PFT) at any given point in the conterminous U.S. using a time series of daily temperature (mean, minimum, maximum), precipitation, humidity, light and nutrients, with PFT-specific rooting within a multi-layer soil. The model employs a 2-layer canopy biophysics, Farquhar photosynthesis, the Beer-Lambert Law for light attenuation and a mechanistic soil hydrology. In essence, BIOMAP is a re-built version of the biogeochemistry model, BIOME-BGC, into the form of the MAPSS biogeography model. Specific enhancements are: 1) the 2-layer canopy biophysics of Dolman (1993); 2) the unique MAPSS-based hydrology, which incorporates canopy evaporation, snow dynamics, infiltration and saturated and unsaturated percolation with ‘fast’ flow and base flow and a ‘tunable aquifer’ capacity, a metaphor of D’Arcy’s Law; and, 3) a unique MAPSS-based stomatal conductance algorithm, which simultaneously incorporates vapor pressure and soil water potential constraints, based on physiological information and many other improvements. Over small domains the PFTs can be parameterized as individual species to investigate fundamental vs. potential niche theory; while, at more coarse scales the PFTs can be rendered as more general functional groups. Since all of the model processes are intrinsically leaf to plot scale (physiology to PFT competition), it essentially has no ‘intrinsic’ scale and can be implemented on a grid of any size, taking on the characteristics defined by the homogeneous climate of each grid cell. Currently, the model is implemented on the VEMAP 1/2 degree, daily grid over the conterminous U.S. Although both the thermal and water-limited ecotones are dynamic, following climate variability, the PFT distributions remain fixed. Thus, the model is currently being fitted with a ‘reproduction niche’ to allow full dynamic operation as a Dynamic General Vegetation Model (DGVM). While global simulations

  11. Wind Farm Decentralized Dynamic Modeling With Parameters

    DEFF Research Database (Denmark)

    Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran

    2010-01-01

    Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...

  12. An Agent Model Integrating an Adaptive Model for Environmental Dynamics

    NARCIS (Netherlands)

    Treur, J.; Umair, M.

    2011-01-01

    The environments in which agents are used often may be described by dynamical models, e.g., in the form of a set of differential equations. In this paper, an agent model is proposed that can perform model-based reasoning about the environment, based on a numerical (dynamical system) model of the

  13. Dynamic modeling method for infrared smoke based on enhanced discrete phase model

    Science.gov (United States)

    Zhang, Zhendong; Yang, Chunling; Zhang, Yan; Zhu, Hongbo

    2018-03-01

    The dynamic modeling of infrared (IR) smoke plays an important role in IR scene simulation systems and its accuracy directly influences the system veracity. However, current IR smoke models cannot provide high veracity, because certain physical characteristics are frequently ignored in fluid simulation; simplifying the discrete phase as a continuous phase and ignoring the IR decoy missile-body spinning. To address this defect, this paper proposes a dynamic modeling method for IR smoke, based on an enhanced discrete phase model (DPM). A mathematical simulation model based on an enhanced DPM is built and a dynamic computing fluid mesh is generated. The dynamic model of IR smoke is then established using an extended equivalent-blackbody-molecule model. Experiments demonstrate that this model realizes a dynamic method for modeling IR smoke with higher veracity.

  14. Supply based on demand dynamical model

    Science.gov (United States)

    Levi, Asaf; Sabuco, Juan; Sanjuán, Miguel A. F.

    2018-04-01

    We propose and numerically analyze a simple dynamical model that describes the firm behaviors under uncertainty of demand. Iterating this simple model and varying some parameter values, we observe a wide variety of market dynamics such as equilibria, periodic, and chaotic behaviors. Interestingly, the model is also able to reproduce market collapses.

  15. Dynamic neural network models of the premotoneuronal circuitry controlling wrist movements in primates.

    Science.gov (United States)

    Maier, M A; Shupe, L E; Fetz, E E

    2005-10-01

    Dynamic recurrent neural networks were derived to simulate neuronal populations generating bidirectional wrist movements in the monkey. The models incorporate anatomical connections of cortical and rubral neurons, muscle afferents, segmental interneurons and motoneurons; they also incorporate the response profiles of four populations of neurons observed in behaving monkeys. The networks were derived by gradient descent algorithms to generate the eight characteristic patterns of motor unit activations observed during alternating flexion-extension wrist movements. The resulting model generated the appropriate input-output transforms and developed connection strengths resembling those in physiological pathways. We found that this network could be further trained to simulate additional tasks, such as experimentally observed reflex responses to limb perturbations that stretched or shortened the active muscles, and scaling of response amplitudes in proportion to inputs. In the final comprehensive network, motor units are driven by the combined activity of cortical, rubral, spinal and afferent units during step tracking and perturbations. The model displayed many emergent properties corresponding to physiological characteristics. The resulting neural network provides a working model of premotoneuronal circuitry and elucidates the neural mechanisms controlling motoneuron activity. It also predicts several features to be experimentally tested, for example the consequences of eliminating inhibitory connections in cortex and red nucleus. It also reveals that co-contraction can be achieved by simultaneous activation of the flexor and extensor circuits without invoking features specific to co-contraction.

  16. Dynamic information architecture system (DIAS) : multiple model simulation management.

    Energy Technology Data Exchange (ETDEWEB)

    Simunich, K. L.; Sydelko, P.; Dolph, J.; Christiansen, J.

    2002-05-13

    Dynamic Information Architecture System (DIAS) is a flexible, extensible, object-based framework for developing and maintaining complex multidisciplinary simulations of a wide variety of application contexts. The modeling domain of a specific DIAS-based simulation is determined by (1) software Entity (domain-specific) objects that represent the real-world entities that comprise the problem space (atmosphere, watershed, human), and (2) simulation models and other data processing applications that express the dynamic behaviors of the domain entities. In DIAS, models communicate only with Entity objects, never with each other. Each Entity object has a number of Parameter and Aspect (of behavior) objects associated with it. The Parameter objects contain the state properties of the Entity object. The Aspect objects represent the behaviors of the Entity object and how it interacts with other objects. DIAS extends the ''Object'' paradigm by abstraction of the object's dynamic behaviors, separating the ''WHAT'' from the ''HOW.'' DIAS object class definitions contain an abstract description of the various aspects of the object's behavior (the WHAT), but no implementation details (the HOW). Separate DIAS models/applications carry the implementation of object behaviors (the HOW). Any model deemed appropriate, including existing legacy-type models written in other languages, can drive entity object behavior. The DIAS design promotes plug-and-play of alternative models, with minimal recoding of existing applications. The DIAS Context Builder object builds a constructs or scenario for the simulation, based on developer specification and user inputs. Because DIAS is a discrete event simulation system, there is a Simulation Manager object with which all events are processed. Any class that registers to receive events must implement an event handler (method) to process the event during execution. Event handlers

  17. Incorporating Twitter, Instagram, and Facebook in Economics Classrooms

    Science.gov (United States)

    Al-Bahrani, Abdullah; Patel, Darshak

    2015-01-01

    Social media is one of the most current and dynamic developments in education. In general, the field of economics has lagged behind other disciplines in incorporating technologies in the classroom. In this article, the authors provide a guide for economics educators on how to incorporate Twitter, Instagram, and Facebook inside and outside of the…

  18. Testing and modeling the dynamic response of foam materials for blast protection

    Science.gov (United States)

    Fitek, John H.

    The pressure wave released from an explosion can cause injury to the lungs. A personal armor system concept for blast lung injury protection consists of a polymer foam layer behind a rigid armor plate to be worn over the chest. This research develops a method for testing and modeling the dynamic response of foam materials to be used for down-selection of materials for this application. Constitutive equations for foam materials are incorporated into a lumped parameter model of the combined armor plate and foam system. Impact testing and shock tube testing are used to measure the foam model parameters and validate the model response to a pressure wave load. The plate and foam armor model is then coupled to a model of the human thorax. With a blast pressure wave input, the armor model is evaluated based on how it affects the injury-causing mechanism of chest wall motion. Results show that to reduce chest wall motion, the foam must compress at a relatively constant stress level, which requires a sufficient foam thickness.

  19. An age-structured model for the coupled dynamics of HIV and HSV-2.

    Science.gov (United States)

    Kapitanov, Georgi; Alvey, Christina; Vogt-Geisse, Katia; Feng, Zhilan

    2015-08-01

    Evidence suggests a strong correlation between the prevalence of HSV-2 (genital herpes) and the perseverance of the HIV epidemic. HSV-2 is an incurable viral infection, characterized by periodic reactivation. We construct a model of the co-infection dynamics between the two diseases by incorporating a time-since-infection variable to track the alternating periods of infectiousness of HSV-2. The model considers only heterosexual relationships and distinguishes three population groups: males, general population females, and female sex workers. We calculate the basic reproduction numbers for each disease that provide threshold conditions, which determine whether a disease dies out or becomes endemic in the absence of the other disease. We also derive the invasion reproduction numbers that determine whether or not a disease can invade into a population in which the other disease is endemic. The calculations of the invasion reproduction numbers suggest a new aspect in their interpretation - the class from which the initial disease carrier arises is important for understanding the invasion dynamics and biological interpretation of the expressions of the reproduction numbers. Sensitivity analysis is conducted to examine the role of model parameters in influencing the model outcomes. The results are discussed in the last section.

  20. Dynamic fuel cell models and their application in hardware in the loop simulation

    Energy Technology Data Exchange (ETDEWEB)

    Lemes, Zijad; Maencher, H. [MAGNUM Automatisierungstechnik GmbH, Bunsenstr. 22, D-64293 Darmstadt (Germany); Vath, Andreas; Hartkopf, Th. [Technische Universitaet Darmstadt/Institut fuer Elektrische Energiewandlung, Landgraf-Georg-Str. 4, D-64283 Darmstadt (Germany)

    2006-03-21

    Currently, fuel cell technology plays an important role in the development of alternative energy converters for mobile, portable and stationary applications. With the help of physical based models of fuel cell systems and appropriate test benches it is possible to design different applications and investigate their stationary and dynamic behaviour. The polymer electrolyte membrane (PEM) fuel cell system model includes gas humidifier, air and hydrogen supply, current converter and a detailed stack model incorporating the physical characteristics of the different layers. In particular, the use of these models together with hardware in the loop (HIL) capable test stands helps to decrease the costs and accelerate the development of fuel cell systems. The interface program provides fast data exchange between the test bench and the physical model of the fuel cell or any other systems in real time. So the flexibility and efficiency of the test bench increase fundamentally, because it is possible to replace real components with their mathematical models. (author)

  1. Computational fluid dynamics modelling in cardiovascular medicine.

    Science.gov (United States)

    Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P

    2016-01-01

    This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. Published by the BMJ Publishing Group Limited. For permission

  2. Dynamic modeling of IGCC power plants

    International Nuclear Information System (INIS)

    Casella, F.; Colonna, P.

    2012-01-01

    Integrated Gasification Combined Cycle (IGCC) power plants are an effective option to reduce emissions and implement carbon-dioxide sequestration. The combination of a very complex fuel-processing plant and a combined cycle power station leads to challenging problems as far as dynamic operation is concerned. Dynamic performance is extremely relevant because recent developments in the electricity market push toward an ever more flexible and varying operation of power plants. A dynamic model of the entire system and models of its sub-systems are indispensable tools in order to perform computer simulations aimed at process and control design. This paper presents the development of the lumped-parameters dynamic model of an entrained-flow gasifier, with special emphasis on the modeling approach. The model is implemented into software by means of the Modelica language and validated by comparison with one set of data related to the steady operation of the gasifier of the Buggenum power station in the Netherlands. Furthermore, in order to demonstrate the potential of the proposed modeling approach and the use of simulation for control design purposes, a complete model of an exemplary IGCC power plant, including its control system, has been developed, by re-using existing models of combined cycle plant components; the results of a load dispatch ramp simulation are presented and shortly discussed. - Highlights: ► The acausal dynamic model of an entrained gasifier has been developed. ► The model can be used to perform system optimization and control studies. ► The model has been validated using field data. ► Model use is illustrated with an example showing the transient of an IGCC plant.

  3. Dynamic Mean-Variance Asset Allocation

    OpenAIRE

    Basak, Suleyman; Chabakauri, Georgy

    2009-01-01

    Mean-variance criteria remain prevalent in multi-period problems, and yet not much is known about their dynamically optimal policies. We provide a fully analytical characterization of the optimal dynamic mean-variance portfolios within a general incomplete-market economy, and recover a simple structure that also inherits several conventional properties of static models. We also identify a probability measure that incorporates intertemporal hedging demands and facilitates much tractability in ...

  4. Electro-mechanical dynamics of spiral waves in a discrete 2D model of human atrial tissue.

    Directory of Open Access Journals (Sweden)

    Paul Brocklehurst

    Full Text Available We investigate the effect of mechano-electrical feedback and atrial fibrillation induced electrical remodelling (AFER of cellular ion channel properties on the dynamics of spiral waves in a discrete 2D model of human atrial tissue. The tissue electro-mechanics are modelled using the discrete element method (DEM. Millions of bonded DEM particles form a network of coupled atrial cells representing 2D cardiac tissue, allowing simulations of the dynamic behaviour of electrical excitation waves and mechanical contraction in the tissue. In the tissue model, each cell is modelled by nine particles, accounting for the features of individual cellular geometry; and discrete inter-cellular spatial arrangement of cells is also considered. The electro-mechanical model of a human atrial single-cell was constructed by strongly coupling the electrophysiological model of Colman et al. to the mechanical myofilament model of Rice et al., with parameters modified based on experimental data. A stretch-activated channel was incorporated into the model to simulate the mechano-electrical feedback. In order to investigate the effect of mechano-electrical feedback on the dynamics of spiral waves, simulations of spiral waves were conducted in both the electromechanical model and the electrical-only model in normal and AFER conditions, to allow direct comparison of the results between the models. Dynamics of spiral waves were characterized by tracing their tip trajectories, stability, excitation frequencies and meandering range of tip trajectories. It was shown that the developed DEM method provides a stable and efficient model of human atrial tissue with considerations of the intrinsically discrete and anisotropic properties of the atrial tissue, which are challenges to handle in traditional continuum mechanics models. This study provides mechanistic insights into the complex behaviours of spiral waves and the genesis of atrial fibrillation by showing an important role of

  5. Electro-mechanical dynamics of spiral waves in a discrete 2D model of human atrial tissue.

    Science.gov (United States)

    Brocklehurst, Paul; Ni, Haibo; Zhang, Henggui; Ye, Jianqiao

    2017-01-01

    We investigate the effect of mechano-electrical feedback and atrial fibrillation induced electrical remodelling (AFER) of cellular ion channel properties on the dynamics of spiral waves in a discrete 2D model of human atrial tissue. The tissue electro-mechanics are modelled using the discrete element method (DEM). Millions of bonded DEM particles form a network of coupled atrial cells representing 2D cardiac tissue, allowing simulations of the dynamic behaviour of electrical excitation waves and mechanical contraction in the tissue. In the tissue model, each cell is modelled by nine particles, accounting for the features of individual cellular geometry; and discrete inter-cellular spatial arrangement of cells is also considered. The electro-mechanical model of a human atrial single-cell was constructed by strongly coupling the electrophysiological model of Colman et al. to the mechanical myofilament model of Rice et al., with parameters modified based on experimental data. A stretch-activated channel was incorporated into the model to simulate the mechano-electrical feedback. In order to investigate the effect of mechano-electrical feedback on the dynamics of spiral waves, simulations of spiral waves were conducted in both the electromechanical model and the electrical-only model in normal and AFER conditions, to allow direct comparison of the results between the models. Dynamics of spiral waves were characterized by tracing their tip trajectories, stability, excitation frequencies and meandering range of tip trajectories. It was shown that the developed DEM method provides a stable and efficient model of human atrial tissue with considerations of the intrinsically discrete and anisotropic properties of the atrial tissue, which are challenges to handle in traditional continuum mechanics models. This study provides mechanistic insights into the complex behaviours of spiral waves and the genesis of atrial fibrillation by showing an important role of the mechano

  6. CFD modeling of the IRIS pressurizer dynamic

    International Nuclear Information System (INIS)

    Sanz, Ronny R.; Montesinos, Maria E.; Garcia, Carlos; Bueno, Elizabeth D.; Mazaira, Leorlen R.; Bezerra, Jair L.; Lira, Carlos A.B. Oliveira

    2015-01-01

    Integral layout of nuclear reactor IRIS makes possible the elimination of the spray system, which is usually used to mitigate in-surge transient and also help to Boron homogenization. The study of transients with deficiencies in the Boron homogenization in this technology is very important, because they can cause disturbances in the reactor power and insert a strong reactivity in the core. The detailed knowledge of the behavior of multiphase multicomponent flows is challenging due to the complex phenomena and interactions at the interface. In this context, the CFD modeling is employed in the design of equipment in the nuclear industry as it allows predicting accidents or predicting their performance in dissimilar applications. The aim of the present research is to model the IRIS pressurizer's dynamic using the commercial CFD code CFX. A symmetric tri dimensional model equivalent to 1/8 of the total geometry was adopted to reduce mesh size and minimize processing time. The model considers the coexistence of four phases and also takes into account the heat losses. The relationships for interfacial mass, energy, and momentum transport are programmed and incorporated into CFX. Moreover, two subdomains and several additional variables are defined to monitoring the boron dilution sequences and condensation-evaporation rates in different control volumes. For transient states a non - equilibrium stratification in the pressurizer is considered. This paper discusses the model developed and the behavior of the system for representative transients sequences. The results of analyzed transients of IRIS can be applied to the design of pressurizer internal structures and components. (author)

  7. CFD modeling of the IRIS pressurizer dynamic

    Energy Technology Data Exchange (ETDEWEB)

    Sanz, Ronny R.; Montesinos, Maria E.; Garcia, Carlos; Bueno, Elizabeth D.; Mazaira, Leorlen R., E-mail: rsanz@instec.cu, E-mail: mmontesi@instec.cu, E-mail: cgh@instec.cu, E-mail: leored1984@gmail.com [Instituto Superior de Tecnologias y Ciencias Aplicadas (InSTEC), La Habana (Cuba); Bezerra, Jair L.; Lira, Carlos A.B. Oliveira, E-mail: jair.lima@ufpe.br, E-mail: cabol@ufpe.br [Universida Federal de Pernambuco (UFPE), Recife, PE (Brazil). Dept. de Energia Nuclear

    2015-07-01

    Integral layout of nuclear reactor IRIS makes possible the elimination of the spray system, which is usually used to mitigate in-surge transient and also help to Boron homogenization. The study of transients with deficiencies in the Boron homogenization in this technology is very important, because they can cause disturbances in the reactor power and insert a strong reactivity in the core. The detailed knowledge of the behavior of multiphase multicomponent flows is challenging due to the complex phenomena and interactions at the interface. In this context, the CFD modeling is employed in the design of equipment in the nuclear industry as it allows predicting accidents or predicting their performance in dissimilar applications. The aim of the present research is to model the IRIS pressurizer's dynamic using the commercial CFD code CFX. A symmetric tri dimensional model equivalent to 1/8 of the total geometry was adopted to reduce mesh size and minimize processing time. The model considers the coexistence of four phases and also takes into account the heat losses. The relationships for interfacial mass, energy, and momentum transport are programmed and incorporated into CFX. Moreover, two subdomains and several additional variables are defined to monitoring the boron dilution sequences and condensation-evaporation rates in different control volumes. For transient states a non - equilibrium stratification in the pressurizer is considered. This paper discusses the model developed and the behavior of the system for representative transients sequences. The results of analyzed transients of IRIS can be applied to the design of pressurizer internal structures and components. (author)

  8. Parameters in dynamic models of complex traits are containers of missing heritability.

    Directory of Open Access Journals (Sweden)

    Yunpeng Wang

    Full Text Available Polymorphisms identified in genome-wide association studies of human traits rarely explain more than a small proportion of the heritable variation, and improving this situation within the current paradigm appears daunting. Given a well-validated dynamic model of a complex physiological trait, a substantial part of the underlying genetic variation must manifest as variation in model parameters. These parameters are themselves phenotypic traits. By linking whole-cell phenotypic variation to genetic variation in a computational model of a single heart cell, incorporating genotype-to-parameter maps, we show that genome-wide association studies on parameters reveal much more genetic variation than when using higher-level cellular phenotypes. The results suggest that letting such studies be guided by computational physiology may facilitate a causal understanding of the genotype-to-phenotype map of complex traits, with strong implications for the development of phenomics technology.

  9. Dynamic term structure models

    DEFF Research Database (Denmark)

    Andreasen, Martin Møller; Meldrum, Andrew

    This paper studies whether dynamic term structure models for US nominal bond yields should enforce the zero lower bound by a quadratic policy rate or a shadow rate specification. We address the question by estimating quadratic term structure models (QTSMs) and shadow rate models with at most four...

  10. Energy Balance Models and Planetary Dynamics

    Science.gov (United States)

    Domagal-Goldman, Shawn

    2012-01-01

    We know that planetary dynamics can have a significant affect on the climate of planets. Planetary dynamics dominate the glacial-interglacial periods on Earth, leaving a significant imprint on the geological record. They have also been demonstrated to have a driving influence on the climates of other planets in our solar system. We should therefore expect th.ere to be similar relationships on extrasolar planets. Here we describe a simple energy balance model that can predict the growth and thickness of glaciers, and their feedbacks on climate. We will also describe model changes that we have made to include planetary dynamics effects. This is the model we will use at the start of our collaboration to handle the influence of dynamics on climate.

  11. Aperiodic dynamics in a deterministic adaptive network model of attitude formation in social groups

    Science.gov (United States)

    Ward, Jonathan A.; Grindrod, Peter

    2014-07-01

    Adaptive network models, in which node states and network topology coevolve, arise naturally in models of social dynamics that incorporate homophily and social influence. Homophily relates the similarity between pairs of nodes' states to their network coupling strength, whilst social influence causes coupled nodes' states to convergence. In this paper we propose a deterministic adaptive network model of attitude formation in social groups that includes these effects, and in which the attitudinal dynamics are represented by an activato-inhibitor process. We illustrate that consensus, corresponding to all nodes adopting the same attitudinal state and being fully connected, may destabilise via Turing instability, giving rise to aperiodic dynamics with sensitive dependence on initial conditions. These aperiodic dynamics correspond to the formation and dissolution of sub-groups that adopt contrasting attitudes. We discuss our findings in the context of cultural polarisation phenomena. Social influence. This reflects the fact that people tend to modify their behaviour and attitudes in response to the opinions of others [22-26]. We model social influence via diffusion: agents adjust their state according to a weighted sum (dictated by the evolving network) of the differences between their state and the states of their neighbours. Homophily. This relates the similarity of individuals' states to their frequency and strength of interaction [27]. Thus in our model, homophily drives the evolution of the weighted ‘social' network. A precise formulation of our model is given in Section 2. Social influence and homophily underpin models of social dynamics [21], which cover a wide range of sociological phenomena, including the diffusion of innovations [28-32], complex contagions [33-36], collective action [37-39], opinion dynamics [19,20,40,10,11,13,15,41,16], the emergence of social norms [42-44], group stability [45], social differentiation [46] and, of particular relevance

  12. Multi-Body Ski Jumper Model with Nonlinear Dynamic Inversion Muscle Control for Trajectory Optimization

    Directory of Open Access Journals (Sweden)

    Patrick Piprek

    2018-02-01

    Full Text Available This paper presents an approach to model a ski jumper as a multi-body system for an optimal control application. The modeling is based on the constrained Newton-Euler-Equations. Within this paper the complete multi-body modeling methodology as well as the musculoskeletal modeling is considered. For the musculoskeletal modeling and its incorporation in the optimization model, we choose a nonlinear dynamic inversion control approach. This approach uses the muscle models as nonlinear reference models and links them to the ski jumper movement by a control law. This strategy yields a linearized input-output behavior, which makes the optimal control problem easier to solve. The resulting model of the ski jumper can then be used for trajectory optimization whose results are compared to literature jumps. Ultimately, this enables the jumper to get a very detailed feedback of the flight. To achieve the maximal jump length, exact positioning of his body with respect to the air can be displayed.

  13. Discrete dynamic modeling of cellular signaling networks.

    Science.gov (United States)

    Albert, Réka; Wang, Rui-Sheng

    2009-01-01

    Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

  14. Advanced Methods for Incorporating Solar Energy Technologies into Electric Sector Capacity-Expansion Models: Literature Review and Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Sullivan, P.; Eurek, K.; Margolis, R.

    2014-07-01

    Because solar power is a rapidly growing component of the electricity system, robust representations of solar technologies should be included in capacity-expansion models. This is a challenge because modeling the electricity system--and, in particular, modeling solar integration within that system--is a complex endeavor. This report highlights the major challenges of incorporating solar technologies into capacity-expansion models and shows examples of how specific models address those challenges. These challenges include modeling non-dispatchable technologies, determining which solar technologies to model, choosing a spatial resolution, incorporating a solar resource assessment, and accounting for solar generation variability and uncertainty.

  15. System dynamics modelling of situation awareness

    CSIR Research Space (South Africa)

    Oosthuizen, R

    2015-11-01

    Full Text Available . The feedback loops and delays in the Command and Control system also contribute to the complex dynamic behavior. This paper will build on existing situation awareness models to develop a System Dynamics model to support a qualitative investigation through...

  16. Modelling biased human trust dynamics

    NARCIS (Netherlands)

    Hoogendoorn, M.; Jaffry, S.W.; Maanen, P.P. van; Treur, J.

    2013-01-01

    Abstract. Within human trust related behaviour, according to the literature from the domains of Psychology and Social Sciences often non-rational behaviour can be observed. Current trust models that have been developed typically do not incorporate non-rational elements in the trust formation

  17. Dynamic response and transfer function of social systems: A neuro-inspired model of collective human activity patterns.

    Science.gov (United States)

    Lymperopoulos, Ilias N

    2017-10-01

    The interaction of social networks with the external environment gives rise to non-stationary activity patterns reflecting the temporal structure and strength of exogenous influences that drive social dynamical processes far from an equilibrium state. Following a neuro-inspired approach, based on the dynamics of a passive neuronal membrane, and the firing rate dynamics of single neurons and neuronal populations, we build a state-of-the-art model of the collective social response to exogenous interventions. In this regard, we analyze online activity patterns with a view to determining the transfer function of social systems, that is, the dynamic relationship between external influences and the resulting activity. To this end, first we estimate the impulse response (Green's function) of collective activity, and then we show that the convolution of the impulse response with a time-varying external influence field accurately reproduces empirical activity patterns. To capture the dynamics of collective activity when the generating process is in a state of statistical equilibrium, we incorporate into the model a noisy input convolved with the impulse response function, thus precisely reproducing the fluctuations of stationary collective activity around a resting value. The outstanding goodness-of-fit of the model results to empirical observations, indicates that the model explains human activity patterns generated by time-dependent external influences in various socio-economic contexts. The proposed model can be used for inferring the temporal structure and strength of external influences, as well as the inertia of collective social activity. Furthermore, it can potentially predict social activity patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. In silico investigation of the short QT syndrome, using human ventricle models incorporating electromechanical coupling

    Directory of Open Access Journals (Sweden)

    Ismail eAdeniran

    2013-07-01

    Full Text Available Introduction Genetic forms of the Short QT Syndrome (SQTS arise due to cardiac ion channel mutations leading to accelerated ventricular repolarisation, arrhythmias and sudden cardiac death. Results from experimental and simulation studies suggest that changes to refractoriness and tissue vulnerability produce a substrate favourable to re-entry. Potential electromechanical consequences of the SQTS are less well understood. The aim of this study was to utilize electromechanically coupled human ventricle models to explore electromechanical consequences of the SQTS. Methods and results: The Rice et al. mechanical model was coupled to the ten Tusscher et al. ventricular cell model. Previously validated K+ channel formulations for SQT variants 1 and 3 were incorporated. Functional effects of the SQTS mutations on transients, sarcomere length shortening and contractile force at the single cell level were evaluated with and without the consideration of stretch activated channel current (Isac. Without Isac, the SQTS mutations produced dramatic reductions in the amplitude of transients, sarcomere length shortening and contractile force. When Isac was incorporated, there was a considerable attenuation of the effects of SQTS-associated action potential shortening on Ca2+ transients, sarcomere shortening and contractile force. Single cell models were then incorporated into 3D human ventricular tissue models. The timing of maximum deformation was delayed in the SQTS setting compared to control. Conclusion: The incorporation of Isac appears to be an important consideration in modelling functional effects of SQT 1 and 3 mutations on cardiac electro-mechanical coupling. Whilst there is little evidence of profoundly impaired cardiac contractile function in SQTS patients, our 3D simulations correlate qualitatively with reported evidence for dissociation between ventricular repolarization and the end of mechanical systole.

  19. Investigations of incorporating source directivity into room acoustics computer models to improve auralizations

    Science.gov (United States)

    Vigeant, Michelle C.

    Room acoustics computer modeling and auralizations are useful tools when designing or modifying acoustically sensitive spaces. In this dissertation, the input parameter of source directivity has been studied in great detail to determine first its effect in room acoustics computer models and secondly how to better incorporate the directional source characteristics into these models to improve auralizations. To increase the accuracy of room acoustics computer models, the source directivity of real sources, such as musical instruments, must be included in the models. The traditional method for incorporating source directivity into room acoustics computer models involves inputting the measured static directivity data taken every 10° in a sphere-shaped pattern around the source. This data can be entered into the room acoustics software to create a directivity balloon, which is used in the ray tracing algorithm to simulate the room impulse response. The first study in this dissertation shows that using directional sources over an omni-directional source in room acoustics computer models produces significant differences both in terms of calculated room acoustics parameters and auralizations. The room acoustics computer model was also validated in terms of accurately incorporating the input source directivity. A recently proposed technique for creating auralizations using a multi-channel source representation has been investigated with numerous subjective studies, applied to both solo instruments and an orchestra. The method of multi-channel auralizations involves obtaining multi-channel anechoic recordings of short melodies from various instruments and creating individual channel auralizations. These auralizations are then combined to create a total multi-channel auralization. Through many subjective studies, this process was shown to be effective in terms of improving the realism and source width of the auralizations in a number of cases, and also modeling different

  20. GIS and dynamic phenomena modeling

    Czech Academy of Sciences Publication Activity Database

    Klimešová, Dana

    2006-01-01

    Roč. 4, č. 4 (2006), s. 11-15 ISSN 0139-570X Institutional research plan: CEZ:AV0Z10750506 Keywords : dynamic modelling * temporal analysis * dynamics evaluation * temporal space Subject RIV: BC - Control Systems Theory

  1. Making a difference: incorporating theories of autonomy into models of informed consent.

    Science.gov (United States)

    Delany, C

    2008-09-01

    Obtaining patients' informed consent is an ethical and legal obligation in healthcare practice. Whilst the law provides prescriptive rules and guidelines, ethical theories of autonomy provide moral foundations. Models of practice of consent, have been developed in the bioethical literature to assist in understanding and integrating the ethical theory of autonomy and legal obligations into the clinical process of obtaining a patient's informed consent to treatment. To review four models of consent and analyse the way each model incorporates the ethical meaning of autonomy and how, as a consequence, they might change the actual communicative process of obtaining informed consent within clinical contexts. An iceberg framework of consent is used to conceptualise how ethical theories of autonomy are positioned and underpin the above surface, and visible clinical communication, including associated legal guidelines and ethical rules. Each model of consent is critically reviewed from the perspective of how it might shape the process of informed consent. All four models would alter the process of obtaining consent. Two models provide structure and guidelines for the content and timing of obtaining patients' consent. The two other models rely on an attitudinal shift in clinicians. They provide ideas for consent by focusing on underlying values, attitudes and meaning associated with the ethical meaning of autonomy. The paper concludes that models of practice that explicitly incorporate the underlying ethical meaning of autonomy as their basis, provide less prescriptive, but more theoretically rich guidance for healthcare communicative practices.

  2. A Lagrangian dynamic subgrid-scale model turbulence

    Science.gov (United States)

    Meneveau, C.; Lund, T. S.; Cabot, W.

    1994-01-01

    A new formulation of the dynamic subgrid-scale model is tested in which the error associated with the Germano identity is minimized over flow pathlines rather than over directions of statistical homogeneity. This procedure allows the application of the dynamic model with averaging to flows in complex geometries that do not possess homogeneous directions. The characteristic Lagrangian time scale over which the averaging is performed is chosen such that the model is purely dissipative, guaranteeing numerical stability when coupled with the Smagorinsky model. The formulation is tested successfully in forced and decaying isotropic turbulence and in fully developed and transitional channel flow. In homogeneous flows, the results are similar to those of the volume-averaged dynamic model, while in channel flow, the predictions are superior to those of the plane-averaged dynamic model. The relationship between the averaged terms in the model and vortical structures (worms) that appear in the LES is investigated. Computational overhead is kept small (about 10 percent above the CPU requirements of the volume or plane-averaged dynamic model) by using an approximate scheme to advance the Lagrangian tracking through first-order Euler time integration and linear interpolation in space.

  3. PWR plant operator training used full scope simulator incorporated MAAP model

    International Nuclear Information System (INIS)

    Matsumoto, Y.; Tabuchi, T.; Yamashita, T.; Komatsu, Y.; Tsubouchi, K.; Banka, T.; Mochizuki, T.; Nishimura, K.; Iizuka, H.

    2015-01-01

    NTC makes an effort with the understanding of plant behavior of core damage accident as part of our advanced training. For the Fukushima Daiichi Nuclear Power Station accident, we introduced the MAAP model into PWR operator training full scope simulator and also made the Severe Accident Visual Display unit. From 2014, we will introduce new training program for a core damage accident with PWR operator training full scope simulator incorporated the MAAP model and the Severe Accident Visual Display unit. (author)

  4. Incorporating modelled subglacial hydrology into inversions for basal drag

    Directory of Open Access Journals (Sweden)

    C. P. Koziol

    2017-12-01

    Full Text Available A key challenge in modelling coupled ice-flow–subglacial hydrology is initializing the state and parameters of the system. We address this problem by presenting a workflow for initializing these values at the start of a summer melt season. The workflow depends on running a subglacial hydrology model for the winter season, when the system is not forced by meltwater inputs, and ice velocities can be assumed constant. Key parameters of the winter run of the subglacial hydrology model are determined from an initial inversion for basal drag using a linear sliding law. The state of the subglacial hydrology model at the end of winter is incorporated into an inversion of basal drag using a non-linear sliding law which is a function of water pressure. We demonstrate this procedure in the Russell Glacier area and compare the output of the linear sliding law with two non-linear sliding laws. Additionally, we compare the modelled winter hydrological state to radar observations and find that it is in line with summer rather than winter observations.

  5. Incorporation of stochastic engineering models as prior information in Bayesian medical device trials.

    Science.gov (United States)

    Haddad, Tarek; Himes, Adam; Thompson, Laura; Irony, Telba; Nair, Rajesh

    2017-01-01

    Evaluation of medical devices via clinical trial is often a necessary step in the process of bringing a new product to market. In recent years, device manufacturers are increasingly using stochastic engineering models during the product development process. These models have the capability to simulate virtual patient outcomes. This article presents a novel method based on the power prior for augmenting a clinical trial using virtual patient data. To properly inform clinical evaluation, the virtual patient model must simulate the clinical outcome of interest, incorporating patient variability, as well as the uncertainty in the engineering model and in its input parameters. The number of virtual patients is controlled by a discount function which uses the similarity between modeled and observed data. This method is illustrated by a case study of cardiac lead fracture. Different discount functions are used to cover a wide range of scenarios in which the type I error rates and power vary for the same number of enrolled patients. Incorporation of engineering models as prior knowledge in a Bayesian clinical trial design can provide benefits of decreased sample size and trial length while still controlling type I error rate and power.

  6. Optimization,Modeling, and Control: Applications to Klystron Designing and Hepatitis C Virus Dynamics

    Science.gov (United States)

    Lankford, George Bernard

    In this dissertation, we address applying mathematical and numerical techniques in the fields of high energy physics and biomedical sciences. The first portion of this thesis presents a method for optimizing the design of klystron circuits. A klystron is an electron beam tube lined with cavities that emit resonant frequencies to velocity modulate electrons that pass through the tube. Radio frequencies (RF) inserted in the klystron are amplified due to the velocity modulation of the electrons. The routine described in this work automates the selection of cavity positions, resonant frequencies, quality factors, and other circuit parameters to maximize the efficiency with required gain. The method is based on deterministic sampling methods. We will describe the procedure and give several examples for both narrow and wide band klystrons, using the klystron codes AJDISK (Java) and TESLA (Python). The rest of the dissertation is dedicated to developing, calibrating and using a mathematical model for hepatitis C dynamics with triple drug combination therapy. Groundbreaking new drugs, called direct acting antivirals, have been introduced recently to fight off chronic hepatitis C virus infection. The model we introduce is for hepatitis C dynamics treated with the direct acting antiviral drug, telaprevir, along with traditional interferon and ribavirin treatments to understand how this therapy affects the viral load of patients exhibiting different types of response. We use sensitivity and identifiability techniques to determine which parameters can be best estimated from viral load data. We use these estimations to give patient-specific fits of the model to partial viral response, end-of-treatment response, and breakthrough patients. We will then revise the model to incorporate an immune response dynamic to more accurately describe the dynamics. Finally, we will implement a suboptimal control to acquire a drug treatment regimen that will alleviate the systemic cost

  7. Simulation of windblown dust transport from a mine tailings impoundment using a computational fluid dynamics model

    Science.gov (United States)

    Stovern, Michael; Felix, Omar; Csavina, Janae; Rine, Kyle P.; Russell, MacKenzie R.; Jones, Robert M.; King, Matt; Betterton, Eric A.; Sáez, A. Eduardo

    2014-01-01

    Mining operations are potential sources of airborne particulate metal and metalloid contaminants through both direct smelter emissions and wind erosion of mine tailings. The warmer, drier conditions predicted for the Southwestern US by climate models may make contaminated atmospheric dust and aerosols increasingly important, due to potential deleterious effects on human health and ecology. Dust emissions and dispersion of dust and aerosol from the Iron King Mine tailings in Dewey-Humboldt, Arizona, a Superfund site, are currently being investigated through in situ field measurements and computational fluid dynamics modeling. These tailings are heavily contaminated with lead and arsenic. Using a computational fluid dynamics model, we model dust transport from the mine tailings to the surrounding region. The model includes gaseous plume dispersion to simulate the transport of the fine aerosols, while individual particle transport is used to track the trajectories of larger particles and to monitor their deposition locations. In order to improve the accuracy of the dust transport simulations, both regional topographical features and local weather patterns have been incorporated into the model simulations. Results show that local topography and wind velocity profiles are the major factors that control deposition. PMID:25621085

  8. Simulation of windblown dust transport from a mine tailings impoundment using a computational fluid dynamics model.

    Science.gov (United States)

    Stovern, Michael; Felix, Omar; Csavina, Janae; Rine, Kyle P; Russell, MacKenzie R; Jones, Robert M; King, Matt; Betterton, Eric A; Sáez, A Eduardo

    2014-09-01

    Mining operations are potential sources of airborne particulate metal and metalloid contaminants through both direct smelter emissions and wind erosion of mine tailings. The warmer, drier conditions predicted for the Southwestern US by climate models may make contaminated atmospheric dust and aerosols increasingly important, due to potential deleterious effects on human health and ecology. Dust emissions and dispersion of dust and aerosol from the Iron King Mine tailings in Dewey-Humboldt, Arizona, a Superfund site, are currently being investigated through in situ field measurements and computational fluid dynamics modeling. These tailings are heavily contaminated with lead and arsenic. Using a computational fluid dynamics model, we model dust transport from the mine tailings to the surrounding region. The model includes gaseous plume dispersion to simulate the transport of the fine aerosols, while individual particle transport is used to track the trajectories of larger particles and to monitor their deposition locations. In order to improve the accuracy of the dust transport simulations, both regional topographical features and local weather patterns have been incorporated into the model simulations. Results show that local topography and wind velocity profiles are the major factors that control deposition.

  9. Modeling of metal thin film growth: Linking angstrom-scale molecular dynamics results to micron-scale film topographies

    Science.gov (United States)

    Hansen, U.; Rodgers, S.; Jensen, K. F.

    2000-07-01

    A general method for modeling ionized physical vapor deposition is presented. As an example, the method is applied to growth of an aluminum film in the presence of an ionized argon flux. Molecular dynamics techniques are used to examine the surface adsorption, reflection, and sputter reactions taking place during ionized physical vapor deposition. We predict their relative probabilities and discuss their dependence on energy and incident angle. Subsequently, we combine the information obtained from molecular dynamics with a line of sight transport model in a two-dimensional feature, incorporating all effects of reemission and resputtering. This provides a complete growth rate model that allows inclusion of energy- and angular-dependent reaction rates. Finally, a level-set approach is used to describe the morphology of the growing film. We thus arrive at a computationally highly efficient and accurate scheme to model the growth of thin films. We demonstrate the capabilities of the model predicting the major differences on Al film topographies between conventional and ionized sputter deposition techniques studying thin film growth under ionized physical vapor deposition conditions with different Ar fluxes.

  10. Modelling group dynamic animal movement

    DEFF Research Database (Denmark)

    Langrock, Roland; Hopcraft, J. Grant C.; Blackwell, Paul G.

    2014-01-01

    makes its movement decisions relative to the group centroid. The basic idea is framed within the flexible class of hidden Markov models, extending previous work on modelling animal movement by means of multi-state random walks. While in simulation experiments parameter estimators exhibit some bias......, to date, practical statistical methods which can include group dynamics in animal movement models have been lacking. We consider a flexible modelling framework that distinguishes a group-level model, describing the movement of the group's centre, and an individual-level model, such that each individual......Group dynamic movement is a fundamental aspect of many species' movements. The need to adequately model individuals' interactions with other group members has been recognised, particularly in order to differentiate the role of social forces in individual movement from environmental factors. However...

  11. Modelling forest dynamics along climate gradients in Bolivia

    NARCIS (Netherlands)

    Seiler, C.; Hutjes, R.W.A.; Kruijt, B.; Quispe, J.; Añez, S.; Arora, V.K.; Melton, J.R.; Hickler, T.; Kabat, P.

    2014-01-01

    Dynamic vegetation models have been used to assess the resilience of tropical forests to climate change, but the global application of these modeling experiments often misrepresents carbon dynamics at a regional level, limiting the validity of future projections. Here a dynamic vegetation model

  12. Absorptive capacity, technological innovation, and product life cycle: a system dynamics model.

    Science.gov (United States)

    Zou, Bo; Guo, Feng; Guo, Jinyu

    2016-01-01

    While past research has recognized the importance of the dynamic nature of absorptive capacity, there is limited knowledge on how to generate a fair and comprehensive analytical framework. Based on interviews with 24 Chinese firms, this study develops a system-dynamics model that incorporates an important feedback loop among absorptive capacity, technological innovation, and product life cycle (PLC). The simulation results reveal that (1) PLC affects the dynamic process of absorptive capacity; (2) the absorptive capacity of a firm peaks in the growth stage of PLC, and (3) the market demand at different PLC stages is the main driving force in firms' technological innovations. This study also explores a sensitivity simulation using the variables of (1) time spent in founding an external knowledge network, (2) research and development period, and (3) knowledge diversity. The sensitivity simulation results show that the changes of these three variables have a greater impact on absorptive capacity and technological innovation during growth and maturity stages than in the introduction and declining stages of PLC. We provide suggestions on how firms can adjust management policies to improve their absorptive capacity and technological innovation performance during different PLC stages.

  13. Slow [Na+]i dynamics impacts arrhythmogenesis and spiral wave reentry in cardiac myocyte ionic model.

    Science.gov (United States)

    Krogh-Madsen, Trine; Christini, David J

    2017-09-01

    Accumulation of intracellular Na + is gaining recognition as an important regulator of cardiac myocyte electrophysiology. The intracellular Na + concentration can be an important determinant of the cardiac action potential duration, can modulate the tissue-level conduction of excitation waves, and can alter vulnerability to arrhythmias. Mathematical models of cardiac electrophysiology often incorporate a dynamic intracellular Na + concentration, which changes much more slowly than the remaining variables. We investigated the dependence of several arrhythmogenesis-related factors on [Na + ] i in a mathematical model of the human atrial action potential. In cell simulations, we found that [Na + ] i accumulation stabilizes the action potential duration to variations in several conductances and that the slow dynamics of [Na + ] i impacts bifurcations to pro-arrhythmic afterdepolarizations, causing intermittency between different rhythms. In long-lasting tissue simulations of spiral wave reentry, [Na + ] i becomes spatially heterogeneous with a decreased area around the spiral wave rotation center. This heterogeneous region forms a functional anchor, resulting in diminished meandering of the spiral wave. Our findings suggest that slow, physiological, rate-dependent variations in [Na + ] i may play complex roles in cellular and tissue-level cardiac dynamics.

  14. Dynamic vs. static social networks in models of parasite transmission: predicting Cryptosporidium spread in wild lemurs.

    Science.gov (United States)

    Springer, Andrea; Kappeler, Peter M; Nunn, Charles L

    2017-05-01

    Social networks provide an established tool to implement heterogeneous contact structures in epidemiological models. Dynamic temporal changes in contact structure and ranging behaviour of wildlife may impact disease dynamics. A consensus has yet to emerge, however, concerning the conditions in which network dynamics impact model outcomes, as compared to static approximations that average contact rates over longer time periods. Furthermore, as many pathogens can be transmitted both environmentally and via close contact, it is important to investigate the relative influence of both transmission routes in real-world populations. Here, we use empirically derived networks from a population of wild primates, Verreaux's sifakas (Propithecus verreauxi), and simulated networks to investigate pathogen spread in dynamic vs. static social networks. First, we constructed a susceptible-exposed-infected-recovered model of Cryptosporidium spread in wild Verreaux's sifakas. We incorporated social and environmental transmission routes and parameterized the model for two different climatic seasons. Second, we used simulated networks and greater variation in epidemiological parameters to investigate the conditions in which dynamic networks produce larger outbreak sizes than static networks. We found that average outbreak size of Cryptosporidium infections in sifakas was larger when the disease was introduced in the dry season than in the wet season, driven by an increase in home range overlap towards the end of the dry season. Regardless of season, dynamic networks always produced larger average outbreak sizes than static networks. Larger outbreaks in dynamic models based on simulated networks occurred especially when the probability of transmission and recovery were low. Variation in tie strength in the dynamic networks also had a major impact on outbreak size, while network modularity had a weaker influence than epidemiological parameters that determine transmission and recovery

  15. Making Invasion models useful for decision makers; incorporating uncertainty, knowledge gaps, and decision-making preferences

    Science.gov (United States)

    Denys Yemshanov; Frank H Koch; Mark Ducey

    2015-01-01

    Uncertainty is inherent in model-based forecasts of ecological invasions. In this chapter, we explore how the perceptions of that uncertainty can be incorporated into the pest risk assessment process. Uncertainty changes a decision maker’s perceptions of risk; therefore, the direct incorporation of uncertainty may provide a more appropriate depiction of risk. Our...

  16. A dynamic model-based estimate of the value of a vanadium redox flow battery for frequency regulation in Texas

    International Nuclear Information System (INIS)

    Fares, Robert L.; Meyers, Jeremy P.; Webber, Michael E.

    2014-01-01

    Highlights: • A model is implemented to describe the dynamic voltage of a vanadium flow battery. • The model is used with optimization to maximize the utility of the battery. • A vanadium flow battery’s value for regulation service is approximately $1500/kW. - Abstract: Building on past work seeking to value emerging energy storage technologies in grid-based applications, this paper introduces a dynamic model-based framework to value a vanadium redox flow battery (VRFB) participating in Texas’ organized electricity market. Our model describes the dynamic behavior of a VRFB system’s voltage and state of charge based on the instantaneous charging or discharging power required from the battery. We formulate an optimization problem that incorporates the model to show the potential value of a VRFB used for frequency regulation service in Texas. The optimization is implemented in Matlab using the large-scale, interior-point, nonlinear optimization algorithm, with the objective function gradient, nonlinear constraint gradients, and Hessian matrix specified analytically. Utilizing market prices and other relevant data from the Electric Reliability Council of Texas (ERCOT), we find that a VRFB system used for frequency regulation service could be worth approximately $1500/kW

  17. Application of a two-pool model to soil carbon dynamics under elevated CO2.

    Science.gov (United States)

    van Groenigen, Kees Jan; Xia, Jianyang; Osenberg, Craig W; Luo, Yiqi; Hungate, Bruce A

    2015-12-01

    Elevated atmospheric CO2 concentrations increase plant productivity and affect soil microbial communities, with possible consequences for the turnover rate of soil carbon (C) pools and feedbacks to the atmosphere. In a previous analysis (Van Groenigen et al., 2014), we used experimental data to inform a one-pool model and showed that elevated CO2 increases the decomposition rate of soil organic C, negating the storage potential of soil. However, a two-pool soil model can potentially explain patterns of soil C dynamics without invoking effects of CO2 on decomposition rates. To address this issue, we refit our data to a two-pool soil C model. We found that CO2 enrichment increases decomposition rates of both fast and slow C pools. In addition, elevated CO2 decreased the carbon use efficiency of soil microbes (CUE), thereby further reducing soil C storage. These findings are consistent with numerous empirical studies and corroborate the results from our previous analysis. To facilitate understanding of C dynamics, we suggest that empirical and theoretical studies incorporate multiple soil C pools with potentially variable decomposition rates. © 2015 John Wiley & Sons Ltd.

  18. Dynamic panel data models

    NARCIS (Netherlands)

    Bun, M.J.G.; Sarafidis, V.

    2013-01-01

    This Chapter reviews the recent literature on dynamic panel data models with a short time span and a large cross-section. Throughout the discussion we considerlinear models with additional endogenous covariates. First we give a broad overview of available inference methods placing emphasis on GMM.

  19. Simple Models for the Dynamic Modeling of Rotating Tires

    Directory of Open Access Journals (Sweden)

    J.C. Delamotte

    2008-01-01

    Full Text Available Large Finite Element (FE models of tires are currently used to predict low frequency behavior and to obtain dynamic model coefficients used in multi-body models for riding and comfort. However, to predict higher frequency behavior, which may explain irregular wear, critical rotating speeds and noise radiation, FE models are not practical. Detailed FE models are not adequate for optimization and uncertainty predictions either, as in such applications the dynamic solution must be computed a number of times. Therefore, there is a need for simpler models that can capture the physics of the tire and be used to compute the dynamic response with a low computational cost. In this paper, the spectral (or continuous element approach is used to derive such a model. A circular beam spectral element that takes into account the string effect is derived, and a method to simulate the response to a rotating force is implemented in the frequency domain. The behavior of a circular ring under different internal pressures is investigated using modal and frequency/wavenumber representations. Experimental results obtained with a real untreaded truck tire are presented and qualitatively compared with the simple model predictions with good agreement. No attempt is made to obtain equivalent parameters for the simple model from the real tire results. On the other hand, the simple model fails to represent the correct variation of the quotient of the natural frequency by the number of circumferential wavelengths with the mode count. Nevertheless, some important features of the real tire dynamic behavior, such as the generation of standing waves and part of the frequency/wavenumber behavior, can be investigated using the proposed simplified model.

  20. Incorporating Resilience into Dynamic Social Models

    Science.gov (United States)

    2016-07-20

    form contains classified information, stamp classification level on the top and bottom of this page. 17. LIMITATION OF ABSTRACT. This block must be...resilience as a multi- level resilience and study their resilience at individual, family and society levels . However, having more than one level on a...4] U. Fischbacher, S. Gächter, and E. Fehr, “Are People Conditionally Cooperative ? Evidence from a Public Goods Experiment,” Econ . Lett., vol

  1. Opinion dynamics model based on quantum formalism

    Energy Technology Data Exchange (ETDEWEB)

    Artawan, I. Nengah, E-mail: nengahartawan@gmail.com [Theoretical Physics Division, Department of Physics, Udayana University (Indonesia); Trisnawati, N. L. P., E-mail: nlptrisnawati@gmail.com [Biophysics, Department of Physics, Udayana University (Indonesia)

    2016-03-11

    Opinion dynamics model based on quantum formalism is proposed. The core of the quantum formalism is on the half spin dynamics system. In this research the implicit time evolution operators are derived. The analogy between the model with Deffuant dan Sznajd models is discussed.

  2. Differential equation models for sharp threshold dynamics.

    Science.gov (United States)

    Schramm, Harrison C; Dimitrov, Nedialko B

    2014-01-01

    We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally and globally change system behavior. We apply our novel modeling approach to two cases of interest: a model of infectious disease modified for malware where a detection event drastically changes dynamics by introducing a new class in competition with the original infection; and the Lanchester model of armed conflict, where the loss of a key capability drastically changes the effectiveness of one of the sides. We derive and demonstrate a step-by-step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system's random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations. Published by Elsevier Inc.

  3. A thermal and electrical dynamic mathematical model for squirrel cage induction motors; Modelamento matematico dinamico termico e eletrico de motores de inducao

    Energy Technology Data Exchange (ETDEWEB)

    Sousa, Ronaldo Martins de

    1996-01-01

    A thermal and electrical dynamic mathematical model for squirrel cage induction motors is presented. The electrical model is described by Park equation and the torque equation, while the thermal model is described by a system of four first order differential equations that represent the motor heat transfer process. The model presented can be used to determine thermal and electrical performance for any operation condition. However, it is suitable mainly for machines operating under continuously transient condition. The presented mathematical model also incorporate variation of rotor winding electrical parameters due to skin effect. (author)

  4. Coupling population dynamics with earth system models: the POPEM model.

    Science.gov (United States)

    Navarro, Andrés; Moreno, Raúl; Jiménez-Alcázar, Alfonso; Tapiador, Francisco J

    2017-09-16

    Precise modeling of CO 2 emissions is important for environmental research. This paper presents a new model of human population dynamics that can be embedded into ESMs (Earth System Models) to improve climate modeling. Through a system dynamics approach, we develop a cohort-component model that successfully simulates historical population dynamics with fine spatial resolution (about 1°×1°). The population projections are used to improve the estimates of CO 2 emissions, thus transcending the bulk approach of existing models and allowing more realistic non-linear effects to feature in the simulations. The module, dubbed POPEM (from Population Parameterization for Earth Models), is compared with current emission inventories and validated against UN aggregated data. Finally, it is shown that the module can be used to advance toward fully coupling the social and natural components of the Earth system, an emerging research path for environmental science and pollution research.

  5. Predator-prey-subsidy population dynamics on stepping-stone domains with dispersal delays.

    Science.gov (United States)

    Eide, Ragna M; Krause, Andrew L; Fadai, Nabil T; Van Gorder, Robert A

    2018-08-14

    We examine the role of the travel time of a predator along a spatial network on predator-prey population interactions, where the predator is able to partially or fully sustain itself on a resource subsidy. The impact of access to food resources on the stability and behaviour of the predator-prey-subsidy system is investigated, with a primary focus on how incorporating travel time changes the dynamics. The population interactions are modelled by a system of delay differential equations, where travel time is incorporated as discrete delay in the network diffusion term in order to model time taken to migrate between spatial regions. The model is motivated by the Arctic ecosystem, where the Arctic fox consumes both hunted lemming and scavenged seal carcass. The fox travels out on sea ice, in addition to quadrennially migrating over substantial distances. We model the spatial predator-prey-subsidy dynamics through a "stepping-stone" approach. We find that a temporal delay alone does not push species into extinction, but rather may stabilize or destabilize coexistence equilibria. We are able to show that delay can stabilize quasi-periodic or chaotic dynamics, and conclude that the incorporation of dispersal delay has a regularizing effect on dynamics, suggesting that dispersal delay can be proposed as a solution to the paradox of enrichment. Copyright © 2018 Elsevier Ltd. All rights reserved.

  6. Swarm Intelligence for Urban Dynamics Modelling

    International Nuclear Information System (INIS)

    Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.

    2009-01-01

    In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

  7. Swarm Intelligence for Urban Dynamics Modelling

    Science.gov (United States)

    Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gérard H. E.

    2009-04-01

    In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

  8. Dynamic optimization deterministic and stochastic models

    CERN Document Server

    Hinderer, Karl; Stieglitz, Michael

    2016-01-01

    This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.

  9. Hydration dynamics near a model protein surface

    International Nuclear Information System (INIS)

    Russo, Daniela; Hura, Greg; Head-Gordon, Teresa

    2003-01-01

    The evolution of water dynamics from dilute to very high concentration solutions of a prototypical hydrophobic amino acid with its polar backbone, N-acetyl-leucine-methylamide (NALMA), is studied by quasi-elastic neutron scattering and molecular dynamics simulation for both the completely deuterated and completely hydrogenated leucine monomer. We observe several unexpected features in the dynamics of these biological solutions under ambient conditions. The NALMA dynamics shows evidence of de Gennes narrowing, an indication of coherent long timescale structural relaxation dynamics. The translational water dynamics are analyzed in a first approximation with a jump diffusion model. At the highest solute concentrations, the hydration water dynamics is significantly suppressed and characterized by a long residential time and a slow diffusion coefficient. The analysis of the more dilute concentration solutions takes into account the results of the 2.0M solution as a model of the first hydration shell. Subtracting the first hydration layer based on the 2.0M spectra, the translational diffusion dynamics is still suppressed, although the rotational relaxation time and residential time are converged to bulk-water values. Molecular dynamics analysis shows spatially heterogeneous dynamics at high concentration that becomes homogeneous at more dilute concentrations. We discuss the hydration dynamics results of this model protein system in the context of glassy systems, protein function, and protein-protein interfaces

  10. Dynamic neutron scattering from conformational dynamics. I. Theory and Markov models.

    Science.gov (United States)

    Lindner, Benjamin; Yi, Zheng; Prinz, Jan-Hendrik; Smith, Jeremy C; Noé, Frank

    2013-11-07

    The dynamics of complex molecules can be directly probed by inelastic neutron scattering experiments. However, many of the underlying dynamical processes may exist on similar timescales, which makes it difficult to assign processes seen experimentally to specific structural rearrangements. Here, we show how Markov models can be used to connect structural changes observed in molecular dynamics simulation directly to the relaxation processes probed by scattering experiments. For this, a conformational dynamics theory of dynamical neutron and X-ray scattering is developed, following our previous approach for computing dynamical fingerprints of time-correlation functions [F. Noé, S. Doose, I. Daidone, M. Löllmann, J. Chodera, M. Sauer, and J. Smith, Proc. Natl. Acad. Sci. U.S.A. 108, 4822 (2011)]. Markov modeling is used to approximate the relaxation processes and timescales of the molecule via the eigenvectors and eigenvalues of a transition matrix between conformational substates. This procedure allows the establishment of a complete set of exponential decay functions and a full decomposition into the individual contributions, i.e., the contribution of every atom and dynamical process to each experimental relaxation process.

  11. Adaptive numerical modeling of dynamic crack propagation

    International Nuclear Information System (INIS)

    Adouani, H.; Tie, B.; Berdin, C.; Aubry, D.

    2006-01-01

    We propose an adaptive numerical strategy that aims at developing reliable and efficient numerical tools to model dynamic crack propagation and crack arrest. We use the cohesive zone theory as behavior of interface-type elements to model crack. Since the crack path is generally unknown beforehand, adaptive meshing is proposed to model the dynamic crack propagation. The dynamic study requires the development of specific solvers for time integration. As both geometry and finite element mesh of the studied structure evolve in time during transient analysis, the stability behavior of dynamic solver becomes a major concern. For this purpose, we use the space-time discontinuous Galerkin finite element method, well-known to provide a natural framework to manage meshes that evolve in time. As an important result, we prove that the space-time discontinuous Galerkin solver is unconditionally stable, when the dynamic crack propagation is modeled by the cohesive zone theory, which is highly non-linear. (authors)

  12. A particle based simulation model for glacier dynamics

    Directory of Open Access Journals (Sweden)

    J. A. Åström

    2013-10-01

    Full Text Available A particle-based computer simulation model was developed for investigating the dynamics of glaciers. In the model, large ice bodies are made of discrete elastic particles which are bound together by massless elastic beams. These beams can break, which induces brittle behaviour. At loads below fracture, beams may also break and reform with small probabilities to incorporate slowly deforming viscous behaviour in the model. This model has the advantage that it can simulate important physical processes such as ice calving and fracturing in a more realistic way than traditional continuum models. For benchmarking purposes the deformation of an ice block on a slip-free surface was compared to that of a similar block simulated with a Finite Element full-Stokes continuum model. Two simulations were performed: (1 calving of an ice block partially supported in water, similar to a grounded marine glacier terminus, and (2 fracturing of an ice block on an inclined plane of varying basal friction, which could represent transition to fast flow or surging. Despite several approximations, including restriction to two-dimensions and simplified water-ice interaction, the model was able to reproduce the size distributions of the debris observed in calving, which may be approximated by universal scaling laws. On a moderate slope, a large ice block was stable and quiescent as long as there was enough of friction against the substrate. For a critical length of frictional contact, global sliding began, and the model block disintegrated in a manner suggestive of a surging glacier. In this case the fragment size distribution produced was typical of a grinding process.

  13. Modelling the Dynamics of an Aedes albopictus Population

    Directory of Open Access Journals (Sweden)

    Thomas Anung Basuki

    2010-08-01

    Full Text Available We present a methodology for modelling population dynamics with formal means of computer science. This allows unambiguous description of systems and application of analysis tools such as simulators and model checkers. In particular, the dynamics of a population of Aedes albopictus (a species of mosquito and its modelling with the Stochastic Calculus of Looping Sequences (Stochastic CLS are considered. The use of Stochastic CLS to model population dynamics requires an extension which allows environmental events (such as changes in the temperature and rainfalls to be taken into account. A simulator for the constructed model is developed via translation into the specification language Maude, and used to compare the dynamics obtained from the model with real data.

  14. Modeling the Dynamic Digestive System Microbiome†

    OpenAIRE

    Estes, Anne M.

    2015-01-01

    Modeling the Dynamic Digestive System Microbiome” is a hands-on activity designed to demonstrate the dynamics of microbiome ecology using dried pasta and beans to model disturbance events in the human digestive system microbiome. This exercise demonstrates how microbiome diversity is influenced by: 1) niche availability and habitat space and 2) a major disturbance event, such as antibiotic use. Students use a pictorial key to examine prepared models of digestive system microbiomes to determi...

  15. An individual-based model of Zebrafish population dynamics accounting for energy dynamics

    DEFF Research Database (Denmark)

    Beaudouin, Remy; Goussen, Benoit; Piccini, Benjamin

    2015-01-01

    Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model...

  16. Dynamic dielectrophoresis model of multi-phase ionic fluids.

    Directory of Open Access Journals (Sweden)

    Ying Yan

    Full Text Available Ionic-based dielectrophoretic microchips have attracted significant attention due to their wide-ranging applications in electro kinetic and biological experiments. In this work, a numerical method is used to simulate the dynamic behaviors of ionic droplets in a microchannel under the effect of dielectrophoresis. When a discrete liquid dielectric is encompassed within a continuous fluid dielectric placed in an electric field, an electric force is produced due to the dielectrophoresis effect. If either or both of the fluids are ionic liquids, the magnitude and even the direction of the force will be changed because the net ionic charge induced by an electric field can affect the polarization degree of the dielectrics. However, using a dielectrophoresis model, assuming ideal dielectrics, results in significant errors. To avoid the inaccuracy caused by the model, this work incorporates the electrode kinetic equation and defines a relationship between the polarization charge and the net ionic charge. According to the simulation conditions presented herein, the electric force obtained in this work has an error exceeding 70% of the actual value if the false effect of net ionic charge is not accounted for, which would result in significant issues in the design and optimization of experimental parameters. Therefore, there is a clear motivation for developing a model adapted to ionic liquids to provide precise control for the dielectrophoresis of multi-phase ionic liquids.

  17. Dynamic dielectrophoresis model of multi-phase ionic fluids.

    Science.gov (United States)

    Yan, Ying; Luo, Jing; Guo, Dan; Wen, Shizhu

    2015-01-01

    Ionic-based dielectrophoretic microchips have attracted significant attention due to their wide-ranging applications in electro kinetic and biological experiments. In this work, a numerical method is used to simulate the dynamic behaviors of ionic droplets in a microchannel under the effect of dielectrophoresis. When a discrete liquid dielectric is encompassed within a continuous fluid dielectric placed in an electric field, an electric force is produced due to the dielectrophoresis effect. If either or both of the fluids are ionic liquids, the magnitude and even the direction of the force will be changed because the net ionic charge induced by an electric field can affect the polarization degree of the dielectrics. However, using a dielectrophoresis model, assuming ideal dielectrics, results in significant errors. To avoid the inaccuracy caused by the model, this work incorporates the electrode kinetic equation and defines a relationship between the polarization charge and the net ionic charge. According to the simulation conditions presented herein, the electric force obtained in this work has an error exceeding 70% of the actual value if the false effect of net ionic charge is not accounted for, which would result in significant issues in the design and optimization of experimental parameters. Therefore, there is a clear motivation for developing a model adapted to ionic liquids to provide precise control for the dielectrophoresis of multi-phase ionic liquids.

  18. Understanding and Modeling Teams As Dynamical Systems

    Science.gov (United States)

    Gorman, Jamie C.; Dunbar, Terri A.; Grimm, David; Gipson, Christina L.

    2017-01-01

    By its very nature, much of teamwork is distributed across, and not stored within, interdependent people working toward a common goal. In this light, we advocate a systems perspective on teamwork that is based on general coordination principles that are not limited to cognitive, motor, and physiological levels of explanation within the individual. In this article, we present a framework for understanding and modeling teams as dynamical systems and review our empirical findings on teams as dynamical systems. We proceed by (a) considering the question of why study teams as dynamical systems, (b) considering the meaning of dynamical systems concepts (attractors; perturbation; synchronization; fractals) in the context of teams, (c) describe empirical studies of team coordination dynamics at the perceptual-motor, cognitive-behavioral, and cognitive-neurophysiological levels of analysis, and (d) consider the theoretical and practical implications of this approach, including new kinds of explanations of human performance and real-time analysis and performance modeling. Throughout our discussion of the topics we consider how to describe teamwork using equations and/or modeling techniques that describe the dynamics. Finally, we consider what dynamical equations and models do and do not tell us about human performance in teams and suggest future research directions in this area. PMID:28744231

  19. Static and Dynamic Mechanical Properties of Graphene Oxide-Incorporated Woven Carbon Fiber/Epoxy Composite

    Science.gov (United States)

    Adak, Nitai Chandra; Chhetri, Suman; Kim, Nam Hoon; Murmu, Naresh Chandra; Samanta, Pranab; Kuila, Tapas

    2018-03-01

    This study investigates the synergistic effects of graphene oxide (GO) on the woven carbon fiber (CF)-reinforced epoxy composites. The GO nanofiller was incorporated into the epoxy resin with variations in the content, and the CF/epoxy composites were manufactured using a vacuum-assisted resin transfer molding process and then cured at 70 and 120 °C. An analysis of the mechanical properties of the GO (0.2 wt.%)/CF/epoxy composites showed an improvement in the tensile strength, Young's modulus, toughness, flexural strength and flexural modulus by 34, 20, 83, 55 and 31%, respectively, when compared to the CF/epoxy composite. The dynamic mechanical analysis of the composites exhibited an enhancement of 56, 114 and 22% in the storage modulus, loss modulus and damping capacity (tan δ), respectively, at its glass transition temperature. The fiber-matrix interaction was studied using a Cole-Cole plot analysis.

  20. A computational growth model for measuring dynamic cortical development in the first year of life.

    Science.gov (United States)

    Nie, Jingxin; Li, Gang; Wang, Li; Gilmore, John H; Lin, Weili; Shen, Dinggang

    2012-10-01

    Human cerebral cortex develops extremely fast in the first year of life. Quantitative measurement of cortical development during this early stage plays an important role in revealing the relationship between cortical structural and high-level functional development. This paper presents a computational growth model to simulate the dynamic development of the cerebral cortex from birth to 1 year old by modeling the cerebral cortex as a deformable elastoplasticity surface driven via a growth model. To achieve a high accuracy, a guidance model is also incorporated to estimate the growth parameters and cortical shapes at later developmental stages. The proposed growth model has been applied to 10 healthy subjects with longitudinal brain MR images acquired at every 3 months from birth to 1 year old. The experimental results show that our proposed method can capture the dynamic developmental process of the cortex, with the average surface distance error smaller than 0.6 mm compared with the ground truth surfaces, and the results also show that 1) the curvedness and sharpness decrease from 2 weeks to 12 months and 2) the frontal lobe shows rapidly increasing cortical folding during this period, with relatively slower increase of the cortical folding in the occipital and parietal lobes.

  1. Modeling interactions of soil hydrological dynamics and soil thermal and permafrost dynamics and their effects on carbon cycling in northern high latitudes

    Science.gov (United States)

    Zhuang, Q.; Tang, J.

    2008-12-01

    Large areas of northern high latitude ecosystems are underlain with permafrost. The warming temperature and fires deteriorate the stability of those permafrost, altering hydrological cycle, and consequently soil temperature and active layer depth. These changes will determine the fate of large carbon pools in soils and permafrost over the region. We developed a modeling framework of hydrology, permafrost, and biogeochemical dynamics based on our existing modules of these components. The framework was incorporated with a new snow dynamics module and the effects of soil moisture on soil thermal properties. The framework was tested for tundra and boreal forest ecosystems at field sites with respect to soil thermal and hydrological regimes in Alaska and was then applied to the whole Alaskan ecosystems for the period of 1923-2000 at a daily time step. Our two sets of simulations with and without considering soil moisture effects indicated that the soil temperature profile and active layer depth between two simulations are significant different. The differences of soil thermal regime would expect to result in different carbon dynamics. Next, we will verify the framework with the observed data of soil moisture and soil temperature at poor-drain, moderate-drain, and well-drain boreal forest sites in Alaska. With the verified framework, we will evaluate the effects of interactions of soil thermal and hydrological dynamics on carbon dynamics for the whole northern high latitudes.

  2. Incorporation of a wind generator model into a dynamic power flow analysis; Incorporacion de un modelo de generador eolico al analisis de flujos dinamicos de potencia

    Energy Technology Data Exchange (ETDEWEB)

    Angeles Camacho, C.; Banuelos Ruedas, F. [Instituto de Ingenieria, Universidad Nacional Autonoma de Mexico (Mexico)]. E-mail: cangelesc@iingen.unam.mx; fbanuelosr@iingen.unam.mx

    2011-07-15

    Wind energy is nowadays one of the most cost-effective and practical options for electric generation from renewable resources. However, increased penetration of wind generation causes the power networks to be more depend on, and vulnerable to, the varying wind speed. Modeling is a tool which can provide valuable information about the interaction between wind farms and the power network to which they are connected. This paper develops a realistic characterization of a wind generator. The wind generator model is incorporated into an algorithm to investigate its contribution to the stability of the power network in the time domain. The tool obtained is termed dynamic power flow. The wind generator model takes on account the wind speed and the reactive power consumption by induction generators. Dynamic power flow analysis is carried-out using real wind data at 10-minute time intervals collected for one meteorological station. The generation injected at one point into the network provides active power locally and is found to reduce global power losses. However, the power supplied is time-varying and causes fluctuations in voltage magnitude and power flows in transmission lines. [Spanish] La energia eolica es hoy en dia una de las opciones mas efectivas y practicas para la generacion de electricidad a partir de energias renovables. Sin embargo, el incremento de la penetracion de energia eolica provoca que los sistemas de potencia se vuelvan mas dependientes y vulnerables a las variaciones de la velocidad del viento. El modelado es una herramienta que provee informacion valiosa de la interaccion dinamica entre las turbinas eolicas y las redes de potencia a las que se conectan. El presente articulo desarrolla una caracterizacion realista de un modelo de la turbina eolica. El modelo de la turbina eolica se incorpora a un algoritmo para el analisis de su contribucion a la estabilidad de una red electrica en el dominio del tiempo. La herramienta obtenida se conoce como flujos

  3. System dynamics and control with bond graph modeling

    CERN Document Server

    Kypuros, Javier

    2013-01-01

    Part I Dynamic System ModelingIntroduction to System DynamicsIntroductionSystem Decomposition and Model ComplexityMathematical Modeling of Dynamic SystemsAnalysis and Design of Dynamic SystemsControl of Dynamic SystemsDiagrams of Dynamic SystemsA Graph-Centered Approach to ModelingSummaryPracticeExercisesBasic Bond Graph ElementsIntroductionPower and Energy VariablesBasic 1-Port ElementsBasic 2-Ports ElementsJunction ElementsSimple Bond Graph ExamplesSummaryPracticeExercisesBond Graph Synthesis and Equation DerivationIntroductionGeneral GuidelinesMechanical TranslationMechanical RotationElectrical CircuitsHydraulic CircuitsMixed SystemsState Equation DerivationState-Space RepresentationsAlgebraic Loops and Derivative CausalitySummaryPracticeExercisesImpedance Bond GraphsIntroductionLaplace Transform of the State-Space EquationBasic 1-Port ImpedancesImpedance Bond Graph SynthesisJunctions, Transformers, and GyratorsEffort and Flow DividersSign ChangesTransfer Function DerivationAlternative Derivation of Transf...

  4. Modeling fraud detection and the incorporation of forensic specialists in the audit process

    DEFF Research Database (Denmark)

    Sakalauskaite, Dominyka

    Financial statement audits are still comparatively poor in fraud detection. Forensic specialists can play a significant role in increasing audit quality. In this paper, based on prior academic research, I develop a model of fraud detection and the incorporation of forensic specialists in the audit...... process. The intention of the model is to identify the reasons why the audit is weak in fraud detection and to provide the analytical framework to assess whether the incorporation of forensic specialists can help to improve it. The results show that such specialists can potentially improve the fraud...... detection in the audit, but might also cause some negative implications. Overall, even though fraud detection is one of the main topics in research there are very few studies done on the subject of how auditors co-operate with forensic specialists. Thus, the paper concludes with suggestions for further...

  5. Multistability and complex dynamics in a simple discrete economic model

    International Nuclear Information System (INIS)

    Peng Mingshu; Jiang Zhonghao; Jiang Xiaoxia; Hu Jiping; Qu Youli

    2009-01-01

    In this paper, we will propose a generalized Cournot duopoly model with Z 2 symmetry. We demonstrate that cost functions incorporating an interfirm externality lead to a system of couple one-dimensional maps. In the situation where agents take turns, we find in an analytic way that there coexist multiple unstable/stable period-2 cycles or synchronized/asynchronized periodic orbits. Coupling one-dimension chaos can be observed. In a more general situation, where agents move simultaneously, a closer analysis reveals some well-known local bifurcations and global bifurcations which typically occur in two-parameter families of two-dimensional discrete time dynamical systems, including codimension-one (fold-, flip-, Neimark-Sacker-) bifurcations, codimension-two (fold/flip, 1:2 resonance, 1:3 resonance and 1:4 resonance) bifurcations, and hetero-clinic, homo-clinic bifurcations, etc. Multistability, including the coexistence of synchronized/asynchronized solutions are also discussed.

  6. Predictive Treatment Management: Incorporating a Predictive Tumor Response Model Into Robust Prospective Treatment Planning for Non-Small Cell Lung Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Pengpeng, E-mail: zhangp@mskcc.org [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Yorke, Ellen; Hu, Yu-Chi; Mageras, Gig [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Rimner, Andreas [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Deasy, Joseph O. [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States)

    2014-02-01

    Purpose: We hypothesized that a treatment planning technique that incorporates predicted lung tumor regression into optimization, predictive treatment planning (PTP), could allow dose escalation to the residual tumor while maintaining coverage of the initial target without increasing dose to surrounding organs at risk (OARs). Methods and Materials: We created a model to estimate the geometric presence of residual tumors after radiation therapy using planning computed tomography (CT) and weekly cone beam CT scans of 5 lung cancer patients. For planning purposes, we modeled the dynamic process of tumor shrinkage by morphing the original planning target volume (PTV{sub orig}) in 3 equispaced steps to the predicted residue (PTV{sub pred}). Patients were treated with a uniform prescription dose to PTV{sub orig}. By contrast, PTP optimization started with the same prescription dose to PTV{sub orig} but linearly increased the dose at each step, until reaching the highest dose achievable to PTV{sub pred} consistent with OAR limits. This method is compared with midcourse adaptive replanning. Results: Initial parenchymal gross tumor volume (GTV) ranged from 3.6 to 186.5 cm{sup 3}. On average, the primary GTV and PTV decreased by 39% and 27%, respectively, at the end of treatment. The PTP approach gave PTV{sub orig} at least the prescription dose, and it increased the mean dose of the true residual tumor by an average of 6.0 Gy above the adaptive approach. Conclusions: PTP, incorporating a tumor regression model from the start, represents a new approach to increase tumor dose without increasing toxicities, and reduce clinical workload compared with the adaptive approach, although model verification using per-patient midcourse imaging would be prudent.

  7. Explanatory Item Response Modeling of Children's Change on a Dynamic Test of Analogical Reasoning

    Science.gov (United States)

    Stevenson, Claire E.; Hickendorff, Marian; Resing, Wilma C. M.; Heiser, Willem J.; de Boeck, Paul A. L.

    2013-01-01

    Dynamic testing is an assessment method in which training is incorporated into the procedure with the aim of gauging cognitive potential. Large individual differences are present in children's ability to profit from training in analogical reasoning. The aim of this experiment was to investigate sources of these differences on a dynamic test of…

  8. Using integrated modeling for generating watershed-scale dynamic flood maps for Hurricane Harvey

    Science.gov (United States)

    Saksena, S.; Dey, S.; Merwade, V.; Singhofen, P. J.

    2017-12-01

    Hurricane Harvey, which was categorized as a 1000-year return period event, produced unprecedented rainfall and flooding in Houston. Although the expected rainfall was forecasted much before the event, there was no way to identify which regions were at higher risk of flooding, the magnitude of flooding, and when the impacts of rainfall would be highest. The inability to predict the location, duration, and depth of flooding created uncertainty over evacuation planning and preparation. This catastrophic event highlighted that the conventional approach to managing flood risk using 100-year static flood inundation maps is inadequate because of its inability to predict flood duration and extents for 500-year or 1000-year return period events in real-time. The purpose of this study is to create models that can dynamically predict the impacts of rainfall and subsequent flooding, so that necessary evacuation and rescue efforts can be planned in advance. This study uses a 2D integrated surface water-groundwater model called ICPR (Interconnected Channel and Pond Routing) to simulate both the hydrology and hydrodynamics for Hurricane Harvey. The methodology involves using the NHD stream network to create a 2D model that incorporates rainfall, land use, vadose zone properties and topography to estimate streamflow and generate dynamic flood depths and extents. The results show that dynamic flood mapping captures the flood hydrodynamics more accurately and is able to predict the magnitude, extent and time of occurrence for extreme events such as Hurricane Harvey. Therefore, integrated modeling has the potential to identify regions that are more susceptible to flooding, which is especially useful for large-scale planning and allocation of resources for protection against future flood risk.

  9. Do environmental dynamics matter in fate models? Exploring scenario dynamics for a terrestrial and an aquatic system.

    Science.gov (United States)

    Morselli, Melissa; Terzaghi, Elisa; Di Guardo, Antonio

    2018-01-24

    Nowadays, there is growing interest in inserting more ecological realism into risk assessment of chemicals. On the exposure evaluation side, this can be done by studying the complexity of exposure in the ecosystem, niche partitioning, e.g. variation of the exposure scenario. Current regulatory predictive approaches, to ensure simplicity and predictive ability, generally keep the scenario as static as possible. This could lead to under or overprediction of chemical exposure depending on the chemical and scenario simulated. To account for more realistic exposure conditions, varying temporally and spatially, additional scenario complexity should be included in currently used models to improve their predictive ability. This study presents two case studies (a terrestrial and an aquatic one) in which some polychlorinated biphenyls (PCBs) were simulated with the SoilPlusVeg and ChimERA models to show the importance of scenario variation in time (biotic and abiotic compartments). The results outlined the importance of accounting for planetary boundary layer variation and vegetation dynamics to accurately predict air concentration changes and the timing of chemical dispersion from the source in terrestrial systems. For the aquatic exercise, the results indicated the need to account for organic carbon forms (particulate and dissolved organic carbon) and vegetation biomass dynamics. In both cases the range of variation was up to two orders of magnitude depending on the congener and scenario, reinforcing the need for incorporating such knowledge into exposure assessment.

  10. A Dynamic Model of Sustainment Investment

    Science.gov (United States)

    2015-02-01

    Sustainment System Dynamics Model 11 Figure 7: Core Structure of Sustainment Work 12 Figure 8: Bandwagon Effect Loop 13 Figure 9: Limits to Growth Loop 14...Dynamics Model sustainment capacity sustainment performance gap Bandwagon Effect R1 Limits to Growth B1 S Work Smarter B3 Work Bigger B2 desired...which is of concern primarily when using the model as a vehicle for research. Figure 8 depicts a reinforcing loop called the “ Bandwagon Effect

  11. Are our dynamic water quality models too complex? A comparison of a new parsimonious phosphorus model, SimplyP, and INCA-P

    Science.gov (United States)

    Jackson-Blake, L. A.; Sample, J. E.; Wade, A. J.; Helliwell, R. C.; Skeffington, R. A.

    2017-07-01

    Catchment-scale water quality models are increasingly popular tools for exploring the potential effects of land management, land use change and climate change on water quality. However, the dynamic, catchment-scale nutrient models in common usage are complex, with many uncertain parameters requiring calibration, limiting their usability and robustness. A key question is whether this complexity is justified. To explore this, we developed a parsimonious phosphorus model, SimplyP, incorporating a rainfall-runoff model and a biogeochemical model able to simulate daily streamflow, suspended sediment, and particulate and dissolved phosphorus dynamics. The model's complexity was compared to one popular nutrient model, INCA-P, and the performance of the two models was compared in a small rural catchment in northeast Scotland. For three land use classes, less than six SimplyP parameters must be determined through calibration, the rest may be based on measurements, while INCA-P has around 40 unmeasurable parameters. Despite substantially simpler process-representation, SimplyP performed comparably to INCA-P in both calibration and validation and produced similar long-term projections in response to changes in land management. Results support the hypothesis that INCA-P is overly complex for the study catchment. We hope our findings will help prompt wider model comparison exercises, as well as debate among the water quality modeling community as to whether today's models are fit for purpose. Simpler models such as SimplyP have the potential to be useful management and research tools, building blocks for future model development (prototype code is freely available), or benchmarks against which more complex models could be evaluated.

  12. Model-based dynamic resistive wall mode identification and feedback control in the DIII-D tokamak

    International Nuclear Information System (INIS)

    In, Y.; Kim, J.S.; Edgell, D.H.; Strait, E.J.; Humphreys, D.A.; Walker, M.L.; Jackson, G.L.; Chu, M.S.; Johnson, R.; La Haye, R.J.; Okabayashi, M.; Garofalo, A.M.; Reimerdes, H.

    2006-01-01

    A new model-based dynamic resistive wall mode (RWM) identification and feedback control algorithm has been developed. While the overall RWM structure can be detected by a model-based matched filter in a similar manner to a conventional sensor-based scheme, it is significantly influenced by edge-localized-modes (ELMs). A recent study suggested that such ELM noise might cause the RWM control system to respond in an undesirable way. Thus, an advanced algorithm to discriminate ELMs from RWM has been incorporated into this model-based control scheme, dynamic Kalman filter. Specifically, the DIII-D [J. L. Luxon, Nucl. Fusion 42, 614 (2002)] resistive vessel wall was modeled in two ways: picture frame model or eigenmode treatment. Based on the picture frame model, the first real-time, closed-loop test results of the Kalman filter algorithms during DIII-D experimental operation are presented. The Kalman filtering scheme was experimentally confirmed to be effective in discriminating ELMs from RWM. As a result, the actuator coils (I-coils) were rarely excited during ELMs, while retaining the sensitivity to RWM. However, finding an optimized set of operating parameters for the control algorithm requires further analysis and design. Meanwhile, a more advanced Kalman filter based on a more accurate eigenmode model has been developed. According to this eigenmode approach, significant improvement in terms of control performance has been predicted, while maintaining good ELM discrimination

  13. Dynamic skin deformation simulation using musculoskeletal model and soft tissue dynamics

    Institute of Scientific and Technical Information of China (English)

    Akihiko Murai; Q. Youn Hong; Katsu Yamane; Jessica K. Hodgins

    2017-01-01

    Deformation of skin and muscle is essential for bringing an animated character to life. This deformation is difficult to animate in a realistic fashion using traditional techniques because of the subtlety of the skin deformations that must move appropriately for the character design. In this paper, we present an algorithm that generates natural, dynamic, and detailed skin deformation (movement and jiggle) from joint angle data sequences. The algorithm has two steps: identification of parameters for a quasi-static muscle deformation model, and simulation of skin deformation. In the identification step, we identify the model parameters using a musculoskeletal model and a short sequence of skin deformation data captured via a dense marker set. The simulation step first uses the quasi-static muscle deformation model to obtain the quasi-static muscle shape at each frame of the given motion sequence (slow jump). Dynamic skin deformation is then computed by simulating the passive muscle and soft tissue dynamics modeled as a mass–spring–damper system. Having obtained the model parameters, we can simulate dynamic skin deformations for subjects with similar body types from new motion data. We demonstrate our method by creating skin deformations for muscle co-contraction and external impacts from four different behaviors captured as skeletal motion capture data. Experimental results show that the simulated skin deformations are quantitatively and qualitatively similar to measured actual skin deformations.

  14. Dynamic skin deformation simulation using musculoskeletal model and soft tissue dynamics

    Institute of Scientific and Technical Information of China (English)

    Akihiko Murai; Q.Youn Hong; Katsu Yamane; Jessica K.Hodgins

    2017-01-01

    Deformation of skin and muscle is essential for bringing an animated character to life. This deformation is difficult to animate in a realistic fashion using traditional techniques because of the subtlety of the skin deformations that must move appropriately for the character design. In this paper, we present an algorithm that generates natural, dynamic, and detailed skin deformation(movement and jiggle) from joint angle data sequences. The algorithm has two steps: identification of parameters for a quasi-static muscle deformation model, and simulation of skin deformation. In the identification step, we identify the model parameters using a musculoskeletal model and a short sequence of skin deformation data captured via a dense marker set. The simulation step first uses the quasi-static muscle deformation model to obtain the quasi-static muscle shape at each frame of the given motion sequence(slow jump). Dynamic skin deformation is then computed by simulating the passive muscle and soft tissue dynamics modeled as a mass–spring–damper system. Having obtained the model parameters, we can simulate dynamic skin deformations for subjects with similar body types from new motion data. We demonstrate our method by creating skin deformations for muscle co-contraction and external impacts from four different behaviors captured as skeletal motion capture data. Experimental results show that the simulated skin deformations are quantitatively and qualitatively similar to measured actual skin deformations.

  15. Key Process Uncertainties in Soil Carbon Dynamics: Comparing Multiple Model Structures and Observational Meta-analysis

    Science.gov (United States)

    Sulman, B. N.; Moore, J.; Averill, C.; Abramoff, R. Z.; Bradford, M.; Classen, A. T.; Hartman, M. D.; Kivlin, S. N.; Luo, Y.; Mayes, M. A.; Morrison, E. W.; Riley, W. J.; Salazar, A.; Schimel, J.; Sridhar, B.; Tang, J.; Wang, G.; Wieder, W. R.

    2016-12-01

    Soil carbon (C) dynamics are crucial to understanding and predicting C cycle responses to global change and soil C modeling is a key tool for understanding these dynamics. While first order model structures have historically dominated this area, a recent proliferation of alternative model structures representing different assumptions about microbial activity and mineral protection is providing new opportunities to explore process uncertainties related to soil C dynamics. We conducted idealized simulations of soil C responses to warming and litter addition using models from five research groups that incorporated different sets of assumptions about processes governing soil C decomposition and stabilization. We conducted a meta-analysis of published warming and C addition experiments for comparison with simulations. Assumptions related to mineral protection and microbial dynamics drove strong differences among models. In response to C additions, some models predicted long-term C accumulation while others predicted transient increases that were counteracted by accelerating decomposition. In experimental manipulations, doubling litter addition did not change soil C stocks in studies spanning as long as two decades. This result agreed with simulations from models with strong microbial growth responses and limited mineral sorption capacity. In observations, warming initially drove soil C loss via increased CO2 production, but in some studies soil C rebounded and increased over decadal time scales. In contrast, all models predicted sustained C losses under warming. The disagreement with experimental results could be explained by physiological or community-level acclimation, or by warming-related changes in plant growth. In addition to the role of microbial activity, assumptions related to mineral sorption and protected C played a key role in driving long-term model responses. In general, simulations were similar in their initial responses to perturbations but diverged over

  16. High-energy outer radiation belt dynamic modeling

    International Nuclear Information System (INIS)

    Chiu, Y.T.; Nightingale, R.W.; Rinaldi, M.A.

    1989-01-01

    Specification of the average high-energy radiation belt environment in terms of phenomenological montages of satellite measurements has been available for some time. However, for many reasons both scientific and applicational (including concerns for a better understanding of the high-energy radiatino background in space), it is desirable to model the dynamic response of the high-energy radiation belts to sources, to losses, and to geomagnetic activity. Indeed, in the outer electron belt, this is the only mode of modeling that can handle the large intensity fluctuations. Anticipating the dynamic modeling objective of the upcoming Combined Release and Radiation Effects Satellite (CRRES) program, we have undertaken to initiate the study of the various essential elements in constructing a dynamic radiation belt model based on interpretation of satellite data according to simultaneous radial and pitch-angle diffusion theory. In order to prepare for the dynamic radiation belt modeling based on a large data set spanning a relatively large segment of L-values, such as required for CRRES, it is important to study a number of test cases with data of similar characteristics but more restricted in space-time coverage. In this way, models of increasing comprehensiveness can be built up from the experience of elucidating the dynamics of more restrictive data sets. The principal objectives of this paper are to discuss issues concerning dynamic modeling in general and to summarize in particular the good results of an initial attempt at constructing the dynamics of the outer electron radiation belt based on a moderately active data period from Lockheed's SC-3 instrument flown on board the SCATHA (P78-2) spacecraft. Further, we shall discuss the issues brought out and lessons learned in this test case

  17. System Dynamics Modeling for Supply Chain Information Sharing

    Science.gov (United States)

    Feng, Yang

    In this paper, we try to use the method of system dynamics to model supply chain information sharing. Firstly, we determine the model boundaries, establish system dynamics model of supply chain before information sharing, analyze the model's simulation results under different changed parameters and suggest improvement proposal. Then, we establish system dynamics model of supply chain information sharing and make comparison and analysis on the two model's simulation results, to show the importance of information sharing in supply chain management. We wish that all these simulations would provide scientific supports for enterprise decision-making.

  18. Incorporating damage mechanics into explosion simulation models

    International Nuclear Information System (INIS)

    Sammis, C.G.

    1993-01-01

    The source region of an underground explosion is commonly modeled as a nested series of shells. In the innermost open-quotes hydrodynamic regimeclose quotes pressures and temperatures are sufficiently high that the rock deforms as a fluid and may be described using a PVT equation of state. Just beyond the hydrodynamic regime, is the open-quotes non-linear regimeclose quotes in which the rock has shear strength but the deformation is nonlinear. This regime extends out to the open-quotes elastic radiusclose quotes beyond which the deformation is linear. In this paper, we develop a model for the non-linear regime in crystalline source rock where the nonlinearity is mostly due to fractures. We divide the non-linear regime into a open-quotes damage regimeclose quotes in which the stresses are sufficiently high to nucleate new fractures from preexisting ones and a open-quotes crack-slidingclose quotes regime where motion on preexisting cracks produces amplitude dependent attenuation and other non-linear effects, but no new cracks are nucleated. The boundary between these two regimes is called the open-quotes damage radius.close quotes The micromechanical damage mechanics recently developed by Ashby and Sammis (1990) is used to write an analytic expression for the damage radius in terms of the initial fracture spectrum of the source rock, and to develop an algorithm which may be used to incorporate damage mechanics into computer source models for the damage regime. Effects of water saturation and loading rate are also discussed

  19. A socio-hydrologic model of coupled water-agriculture dynamics with emphasis on farm size.

    Science.gov (United States)

    Brugger, D. R.; Maneta, M. P.

    2015-12-01

    Agricultural land cover dynamics in the U.S. are dominated by two trends: 1) total agricultural land is decreasing and 2) average farm size is increasing. These trends have important implications for the future of water resources because 1) growing more food on less land is due in large part to increased groundwater withdrawal and 2) larger farms can better afford both more efficient irrigation and more groundwater access. However, these large-scale trends are due to individual farm operators responding to many factors including climate, economics, and policy. It is therefore difficult to incorporate the trends into watershed-scale hydrologic models. Traditional scenario-based approaches are valuable for many applications, but there is typically no feedback between the hydrologic model and the agricultural dynamics and so limited insight is gained into the how agriculture co-evolves with water resources. We present a socio-hydrologic model that couples simplified hydrologic and agricultural economic dynamics, accounting for many factors that depend on farm size such as irrigation efficiency and returns to scale. We introduce an "economic memory" (EM) state variable that is driven by agricultural revenue and affects whether farms are sold when land market values exceed expected returns from agriculture. The model uses a Generalized Mixture Model of Gaussians to approximate the distribution of farm sizes in a study area, effectively lumping farms into "small," "medium," and "large" groups that have independent parameterizations. We apply the model in a semi-arid watershed in the upper Columbia River Basin, calibrating to data on streamflow, total agricultural land cover, and farm size distribution. The model is used to investigate the sensitivity of the coupled system to various hydrologic and economic scenarios such as increasing market value of land, reduced surface water availability, and increased irrigation efficiency in small farms.

  20. The FFA dynamic stall model. The Beddoes-Leishman dynamic stall model modified for lead-lag oscillations

    Energy Technology Data Exchange (ETDEWEB)

    Bjoerck, A. [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden)

    1997-08-01

    For calculations of the dynamics of wind turbines the inclusion of a dynamic stall model is necessary in order to obtain reliable results at high winds. For blade vibrations in the lead-lag motion the velocity relative to the blade will vary in time. In the present paper modifications to the Beddoes-Leishman model is presented in order to improve the model for calculations of cases with a varying relative velocity. Comparisons with measurement are also shown and the influence on the calculated aerodynamic damping by the modifications are investigated. (au)

  1. Effect of food microstructure on growth dynamics of Listeria monocytogenes in fish-based model systems.

    Science.gov (United States)

    Verheyen, Davy; Bolívar, Araceli; Pérez-Rodríguez, Fernando; Baka, Maria; Skåra, Torstein; Van Impe, Jan F

    2018-06-01

    Traditionally, predictive growth models for food pathogens are developed based on experiments in broth media, resulting in models which do not incorporate the influence of food microstructure. The use of model systems with various microstructures is a promising concept to get more insight into the influence of food microstructure on microbial dynamics. By means of minimal variation of compositional and physicochemical factors, these model systems can be used to study the isolated effect of certain microstructural aspects on microbial growth, survival and inactivation. In this study, the isolated effect on microbial growth dynamics of Listeria monocytogenes of two food microstructural aspects and one aspect influenced by food microstructure were investigated, i.e., the nature of the food matrix, the presence of fat droplets, and microorganism growth morphology, respectively. To this extent, fish-based model systems with various microstructures were used, i.e., a liquid, a second more viscous liquid system containing xanthan gum, an emulsion, an aqueous gel, and a gelled emulsion. Growth experiments were conducted at 4 and 10 °C, both using homogeneous and surface inoculation (only for the gelled systems). Results regarding the influence of the growth morphology indicated that the lag phase of planktonic cells in the liquid system was similar to the lag phase of submerged colonies in the xanthan system. The lag phase of submerged colonies in each gelled system was considerably longer than the lag phase of surface colonies on these respective systems. The maximum specific growth rate of planktonic cells in the liquid system was significantly lower than for submerged colonies in the xanthan system at 10 °C, while no significant differences were observed at 4 °C. The maximum cell density was higher for submerged colonies than for surface colonies. The nature of the food matrix only exerted an influence on the maximum specific growth rate, which was

  2. Fractional-order in a macroeconomic dynamic model

    Science.gov (United States)

    David, S. A.; Quintino, D. D.; Soliani, J.

    2013-10-01

    In this paper, we applied the Riemann-Liouville approach in order to realize the numerical simulations to a set of equations that represent a fractional-order macroeconomic dynamic model. It is a generalization of a dynamic model recently reported in the literature. The aforementioned equations have been simulated for several cases involving integer and non-integer order analysis, with some different values to fractional order. The time histories and the phase diagrams have been plotted to visualize the effect of fractional order approach. The new contribution of this work arises from the fact that the macroeconomic dynamic model proposed here involves the public sector deficit equation, which renders the model more realistic and complete when compared with the ones encountered in the literature. The results reveal that the fractional-order macroeconomic model can exhibit a real reasonable behavior to macroeconomics systems and might offer greater insights towards the understanding of these complex dynamic systems.

  3. Modeling Dynamic Regulatory Processes in Stroke

    Science.gov (United States)

    McDermott, Jason E.; Jarman, Kenneth; Taylor, Ronald; Lancaster, Mary; Shankaran, Harish; Vartanian, Keri B.; Stevens, Susan L.; Stenzel-Poore, Mary P.; Sanfilippo, Antonio

    2012-01-01

    The ability to examine the behavior of biological systems in silico has the potential to greatly accelerate the pace of discovery in diseases, such as stroke, where in vivo analysis is time intensive and costly. In this paper we describe an approach for in silico examination of responses of the blood transcriptome to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) from the data relating these functional clusters to each other in terms of their regulatory influence on one another. Dynamic models were developed by coupling these ODEs into a model that simulates the expression of regulated functional clusters. By changing the magnitude of gene expression in the initial input state it was possible to assess the behavior of the networks through time under varying conditions since the dynamic model only requires an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. We discuss the implications of our models on neuroprotection in stroke, explore the limitations of the approach, and report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different neuroprotective paradigms. PMID:23071432

  4. Dynamic models in research and management of biological invasions.

    Science.gov (United States)

    Buchadas, Ana; Vaz, Ana Sofia; Honrado, João P; Alagador, Diogo; Bastos, Rita; Cabral, João A; Santos, Mário; Vicente, Joana R

    2017-07-01

    Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Analytical dynamic modeling of fast trilayer polypyrrole bending actuators

    International Nuclear Information System (INIS)

    Amiri Moghadam, Amir Ali; Moavenian, Majid; Tahani, Masoud; Torabi, Keivan

    2011-01-01

    Analytical modeling of conjugated polymer actuators with complicated electro-chemo-mechanical dynamics is an interesting area for research, due to the wide range of applications including biomimetic robots and biomedical devices. Although there have been extensive reports on modeling the electrochemical dynamics of polypyrrole (PPy) bending actuators, mechanical dynamics modeling of the actuators remains unexplored. PPy actuators can operate with low voltage while producing large displacement in comparison to robotic joints, they do not have friction or backlash, but they suffer from some disadvantages such as creep and hysteresis. In this paper, a complete analytical dynamic model for fast trilayer polypyrrole bending actuators has been proposed and named the analytical multi-domain dynamic actuator (AMDDA) model. First an electrical admittance model of the actuator will be obtained based on a distributed RC line; subsequently a proper mechanical dynamic model will be derived, based on Hamilton's principle. The purposed modeling approach will be validated based on recently published experimental results

  6. Multi-day activity scheduling reactions to planned activities and future events in a dynamic model of activity-travel behavior

    Science.gov (United States)

    Nijland, Linda; Arentze, Theo; Timmermans, Harry

    2014-01-01

    Modeling multi-day planning has received scarce attention in activity-based transport demand modeling so far. However, new dynamic activity-based approaches are being developed at the current moment. The frequency and inflexibility of planned activities and events in activity schedules of individuals indicate the importance of incorporating those pre-planned activities in the new generation of dynamic travel demand models. Elaborating and combining previous work on event-driven activity generation, the aim of this paper is to develop and illustrate an extension of a need-based model of activity generation that takes into account possible influences of pre-planned activities and events. This paper describes the theory and shows the results of simulations of the extension. The simulation was conducted for six different activities, and the parameter values used were consistent with an earlier estimation study. The results show that the model works well and that the influences of the parameters are consistent, logical, and have clear interpretations. These findings offer further evidence of face and construct validity to the suggested modeling approach.

  7. Energy demand projections based on an uncertain dynamic system modeling approach

    International Nuclear Information System (INIS)

    Dong, S.

    2000-01-01

    Today, China has become the world's second largest pollution source of CO 2 . Owing to coal-based energy consumption, it is estimated that 85--90% of the SO 2 and CO 2 emission of China results from coal use. With high economic growth and increasing environmental concerns, China's energy consumption in the next few decades has become an issue of active concern. Forecasting of energy demand over long periods, however, is getting more complex and uncertain. It is believed that the economic and energy systems are chaotic and nonlinear. Traditional linear system modeling, used mostly in energy demand forecasts, therefore, is not a useful approach. In view of uncertainty and imperfect information about future economic growth and energy development, an uncertain dynamic system model, which has the ability to incorporate and absorb the nature of an uncertain system with imperfect or incomplete information, is developed. Using the model, the forecasting of energy demand in the next 25 years is provided. The model predicts that China's energy demand in 2020 will be about 2,700--3,000 Mtce, coal demand 3,500 Mt, increasing by 128% and 154%, respectively, compared with that of 1995

  8. Dynamic complexities in a parasitoid-host-parasitoid ecological model

    International Nuclear Information System (INIS)

    Yu Hengguo; Zhao Min; Lv Songjuan; Zhu Lili

    2009-01-01

    Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model

  9. Dynamic complexities in a parasitoid-host-parasitoid ecological model

    Energy Technology Data Exchange (ETDEWEB)

    Yu Hengguo [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China); Zhao Min [School of Life and Environmental Science, Wenzhou University, Wenzhou, Zhejiang 325027 (China)], E-mail: zmcn@tom.com; Lv Songjuan; Zhu Lili [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China)

    2009-01-15

    Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model.

  10. Multiscale model for pedestrian and infection dynamics during air travel

    Science.gov (United States)

    Namilae, Sirish; Derjany, Pierrot; Mubayi, Anuj; Scotch, Mathew; Srinivasan, Ashok

    2017-05-01

    In this paper we develop a multiscale model combining social-force-based pedestrian movement with a population level stochastic infection transmission dynamics framework. The model is then applied to study the infection transmission within airplanes and the transmission of the Ebola virus through casual contacts. Drastic limitations on air-travel during epidemics, such as during the 2014 Ebola outbreak in West Africa, carry considerable economic and human costs. We use the computational model to evaluate the effects of passenger movement within airplanes and air-travel policies on the geospatial spread of infectious diseases. We find that boarding policy by an airline is more critical for infection propagation compared to deplaning policy. Enplaning in two sections resulted in fewer infections than the currently followed strategy with multiple zones. In addition, we found that small commercial airplanes are better than larger ones at reducing the number of new infections in a flight. Aggregated results indicate that passenger movement strategies and airplane size predicted through these network models can have significant impact on an event like the 2014 Ebola epidemic. The methodology developed here is generic and can be readily modified to incorporate the impact from the outbreak of other directly transmitted infectious diseases.

  11. Analysis of in vitro and in vivo function of total knee replacements using dynamic contact models

    Science.gov (United States)

    Zhao, Dong

    Despite the high incidence of osteoarthritis in human knee joint, its causes remain unknown. Total knee replacement (TKR) has been shown clinically to be effective in restoring the knee function. However, wear of ultra-high molecular weight polyethylene has limited the longevity of TKRs. To address these important issues, it is necessary to investigate the in vitro and in vivo function of total knee replacements using dynamic contact models. A multibody dynamic model of an AMTI knee simulator was developed. Incorporating a wear prediction model into the contact model based on elastic foundation theory enables the contact surface to take into account creep and wear during the dynamic simulation. Comparisons of the predicted damage depth, area, and volume lost with worn retrievals from a physical machine were made to validate the model. In vivo tibial force distributions during dynamic and high flexion activities were investigated using the dynamic contact model. In vivo medial and lateral contact forces experienced by a well-aligned instrumented knee implant, as well as upper and lower bounds on contact pressures for a variety of activities were studied. For all activities, the predicted medial and lateral contact forces were insensitive to the selected material model. For this patient, the load split during the mid-stance phase of gait and during stair is more equal than anticipated. The external knee adduction torque has been proposed as a surrogate measure for medial compartment load during gait. However, a direct link between these two quantities has not been demonstrated using in vivo measurement of medial compartment load. In vivo data collected from a subject with an instrumented knee implant were analyzed to evaluate this link. The subject performed five different overground gait motions (normal, fast, slow, wide, and toe out) while instrumented implant, video motion, and ground reaction data were simultaneously collected. The high correlation coefficient

  12. Reservoir resistivity characterization incorporating flow dynamics

    KAUST Repository

    Arango, Santiago

    2016-04-07

    Systems and methods for reservoir resistivity characterization are provided, in various aspects, an integrated framework for the estimation of Archie\\'s parameters for a strongly heterogeneous reservoir utilizing the dynamics of the reservoir are provided. The framework can encompass a Bayesian estimation/inversion method for estimating the reservoir parameters, integrating production and time lapse formation conductivity data to achieve a better understanding of the subsurface rock conductivity properties and hence improve water saturation imaging.

  13. Reservoir resistivity characterization incorporating flow dynamics

    KAUST Repository

    Arango, Santiago; Sun, Shuyu; Hoteit, Ibrahim; Katterbauer, Klemens

    2016-01-01

    Systems and methods for reservoir resistivity characterization are provided, in various aspects, an integrated framework for the estimation of Archie's parameters for a strongly heterogeneous reservoir utilizing the dynamics of the reservoir are provided. The framework can encompass a Bayesian estimation/inversion method for estimating the reservoir parameters, integrating production and time lapse formation conductivity data to achieve a better understanding of the subsurface rock conductivity properties and hence improve water saturation imaging.

  14. A Multi-Actor Dynamic Integrated Assessment Model (MADIAM)

    OpenAIRE

    Weber, Michael

    2004-01-01

    The interactions between climate and the socio-economic system are investigated with a Multi-Actor Dynamic Integrated Assessment Model (MADIAM) obtained by coupling a nonlinear impulse response model of the climate sub-system (NICCS) to a multi-actor dynamic economic model (MADEM). The main goal is to initiate a model development that is able to treat the dynamics of the coupled climate socio-economic system, including endogenous technological change, in a non-equilibrium situation, thereby o...

  15. Incorporating vehicle mix in stimulus-response car-following models

    Directory of Open Access Journals (Sweden)

    Saidi Siuhi

    2016-06-01

    Full Text Available The objective of this paper is to incorporate vehicle mix in stimulus-response car-following models. Separate models were estimated for acceleration and deceleration responses to account for vehicle mix via both movement state and vehicle type. For each model, three sub-models were developed for different pairs of following vehicles including “automobile following automobile,” “automobile following truck,” and “truck following automobile.” The estimated model parameters were then validated against other data from a similar region and roadway. The results indicated that drivers' behaviors were significantly different among the different pairs of following vehicles. Also the magnitude of the estimated parameters depends on the type of vehicle being driven and/or followed. These results demonstrated the need to use separate models depending on movement state and vehicle type. The differences in parameter estimates confirmed in this paper highlight traffic safety and operational issues of mixed traffic operation on a single lane. The findings of this paper can assist transportation professionals to improve traffic simulation models used to evaluate the impact of different strategies on ameliorate safety and performance of highways. In addition, driver response time lag estimates can be used in roadway design to calculate important design parameters such as stopping sight distance on horizontal and vertical curves for both automobiles and trucks.

  16. Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

    Directory of Open Access Journals (Sweden)

    Nikola Simidjievski

    Full Text Available Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting, significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.

  17. Incorporating microbiota data into epidemiologic models: examples from vaginal microbiota research.

    Science.gov (United States)

    van de Wijgert, Janneke H; Jespers, Vicky

    2016-05-01

    Next generation sequencing and quantitative polymerase chain reaction technologies are now widely available, and research incorporating these methods is growing exponentially. In the vaginal microbiota (VMB) field, most research to date has been descriptive. The purpose of this article is to provide an overview of different ways in which next generation sequencing and quantitative polymerase chain reaction data can be used to answer clinical epidemiologic research questions using examples from VMB research. We reviewed relevant methodological literature and VMB articles (published between 2008 and 2015) that incorporated these methodologies. VMB data have been analyzed using ecologic methods, methods that compare the presence or relative abundance of individual taxa or community compositions between different groups of women or sampling time points, and methods that first reduce the complexity of the data into a few variables followed by the incorporation of these variables into traditional biostatistical models. To make future VMB research more clinically relevant (such as studying associations between VMB compositions and clinical outcomes and the effects of interventions on the VMB), it is important that these methods are integrated with rigorous epidemiologic methods (such as appropriate study designs, sampling strategies, and adjustment for confounding). Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

  18. Models with Men and Women: Representing Gender in Dynamic Modeling of Social Systems.

    Science.gov (United States)

    Palmer, Erika; Wilson, Benedicte

    2018-04-01

    Dynamic engineering models have yet to be evaluated in the context of feminist engineering ethics. Decision-making concerning gender in dynamic modeling design is a gender and ethical issue that is important to address regardless of the system in which the dynamic modeling is applied. There are many dynamic modeling tools that operationally include the female population, however, there is an important distinction between females and women; it is the difference between biological sex and the social construct of gender, which is fluid and changes over time and geography. The ethical oversight in failing to represent or misrepresenting gender in model design when it is relevant to the model purpose can have implications for model validity and policy model development. This paper highlights this gender issue in the context of feminist engineering ethics using a dynamic population model. Women are often represented in this type of model only in their biological capacity, while lacking their gender identity. This illustrative example also highlights how language, including the naming of variables and communication with decision-makers, plays a role in this gender issue.

  19. Quantifying the dynamics of coupled networks of switches and oscillators.

    Directory of Open Access Journals (Sweden)

    Matthew R Francis

    Full Text Available Complex network dynamics have been analyzed with models of systems of coupled switches or systems of coupled oscillators. However, many complex systems are composed of components with diverse dynamics whose interactions drive the system's evolution. We, therefore, introduce a new modeling framework that describes the dynamics of networks composed of both oscillators and switches. Both oscillator synchronization and switch stability are preserved in these heterogeneous, coupled networks. Furthermore, this model recapitulates the qualitative dynamics for the yeast cell cycle consistent with the hypothesized dynamics resulting from decomposition of the regulatory network into dynamic motifs. Introducing feedback into the cell-cycle network induces qualitative dynamics analogous to limitless replicative potential that is a hallmark of cancer. As a result, the proposed model of switch and oscillator coupling provides the ability to incorporate mechanisms that underlie the synchronized stimulus response ubiquitous in biochemical systems.

  20. Automated adaptive inference of phenomenological dynamical models

    Science.gov (United States)

    Daniels, Bryan

    Understanding the dynamics of biochemical systems can seem impossibly complicated at the microscopic level: detailed properties of every molecular species, including those that have not yet been discovered, could be important for producing macroscopic behavior. The profusion of data in this area has raised the hope that microscopic dynamics might be recovered in an automated search over possible models, yet the combinatorial growth of this space has limited these techniques to systems that contain only a few interacting species. We take a different approach inspired by coarse-grained, phenomenological models in physics. Akin to a Taylor series producing Hooke's Law, forgoing microscopic accuracy allows us to constrain the search over dynamical models to a single dimension. This makes it feasible to infer dynamics with very limited data, including cases in which important dynamical variables are unobserved. We name our method Sir Isaac after its ability to infer the dynamical structure of the law of gravitation given simulated planetary motion data. Applying the method to output from a microscopically complicated but macroscopically simple biological signaling model, it is able to adapt the level of detail to the amount of available data. Finally, using nematode behavioral time series data, the method discovers an effective switch between behavioral attractors after the application of a painful stimulus.

  1. Chaotic Dynamics in Smart Grid and Suppression Scheme via Generalized Fuzzy Hyperbolic Model

    Directory of Open Access Journals (Sweden)

    Qiuye Sun

    2014-01-01

    Full Text Available This paper presents a method to control chaotic behavior of a typical Smart Grid based on generalized fuzzy hyperbolic model (GFHM. As more and more distributed generations (DG are incorporated into the Smart Grid, the chaotic behavior occurs increasingly. To verify the behavior, a dynamic model which describes a power system with DG is presented firstly. Then, the simulation result shows that the power system can lead to chaos under certain initial conditions. Based on the universal approximation of GFHM, we confirm that the chaotic behavior could be suppressed by a new controller, which is designed by means of solving a linear matrix inequality (LMI. This approach could make a good application to suppress the chaos in Smart Grid. Finally, a numerical example is given to demonstrate the effectiveness of the proposed chaotic suppression strategy.

  2. Modelling and dynamic simulation of processes with 'MATLAB'. An application of a natural gas installation in a power plant

    International Nuclear Information System (INIS)

    Gonzalez-Bustamante, J.A.; Sala, J.M.; Lopez-Gonzalez, L.M.; Miguez, J.L.; Flores, I.

    2007-01-01

    In this paper, it is proposed to incorporate the analysis of the dynamic performance of the process into the design and engineering stage of projects as a means of analysing and resolving this type of problem. The following contributions are made with this objective in mind:(a)The barriers in the way of dynamic analysis are identified. (b)Software tools which make dynamic analysis accessible during the design and engineering phase of the project are proposed. To achieve this goal, modelling and mathematical simulation are used, with the following features: *strict modelling of mass, momentum and energy conservation equations as well as state equations, and *utilisation of the 'Matlab-Simulink' package as the base-software tool. (c)The procedure and tool proposed for dynamic analysis during the design phase should enable these studies to be carried out at a reasonable cost and time for regular industrial projects, and not just for large research projects or nuclear power plants. To complete this paper, we apply our method to a natural gas installation in a power plant. The model is applied to study the transients of a natural gas supply line to a steam-electric power plant. The results of the model have been validated with the actual data on the boiler trip obtained from the distributed control system of a steam-electric power plant

  3. Tuning hardness in calcite by incorporation of amino acids.

    Science.gov (United States)

    Kim, Yi-Yeoun; Carloni, Joseph D; Demarchi, Beatrice; Sparks, David; Reid, David G; Kunitake, Miki E; Tang, Chiu C; Duer, Melinda J; Freeman, Colin L; Pokroy, Boaz; Penkman, Kirsty; Harding, John H; Estroff, Lara A; Baker, Shefford P; Meldrum, Fiona C

    2016-08-01

    Structural biominerals are inorganic/organic composites that exhibit remarkable mechanical properties. However, the structure-property relationships of even the simplest building unit-mineral single crystals containing embedded macromolecules-remain poorly understood. Here, by means of a model biomineral made from calcite single crystals containing glycine (0-7 mol%) or aspartic acid (0-4 mol%), we elucidate the origin of the superior hardness of biogenic calcite. We analysed lattice distortions in these model crystals by using X-ray diffraction and molecular dynamics simulations, and by means of solid-state nuclear magnetic resonance show that the amino acids are incorporated as individual molecules. We also demonstrate that nanoindentation hardness increased with amino acid content, reaching values equivalent to their biogenic counterparts. A dislocation pinning model reveals that the enhanced hardness is determined by the force required to cut covalent bonds in the molecules.

  4. Dynamics of a delayed intraguild predation model with harvesting

    Science.gov (United States)

    Collera, Juancho A.; Balilo, Aldrin T.

    2018-03-01

    In [1], a delayed three-species intraguild predation (IGP) model was considered. This particular tri-trophic community module includes a predator and its prey which share a common basal resource for their sustenance [3]. Here, it is assumed that in the absence of predation, the growth of the basal resource follows the delayed logistic equation. Without delay time, the IGP model in [1] reduces to the system considered in [7] where it was shown that IGP may induce chaos even if the functional responses are linear. Meanwhile, in [2] the delayed IGP model in [1] was generalized to include harvesting. Under the assumption that the basal resource has some economic value, a constant harvesting term on the basal resource was incorporated. However, both models in [1] and [2] use the delay time as the main parameter. In this research, we studied the delayed IGP model in [1] with the addition of linear harvesting term on each of the three species. The dynamical behavior of this system is examined using the harvesting rates as main parameter. In particular, we give conditions on the existence, stability, and bifurcations of equilibrium solutions of this system. This allows us to better understand the effects of harvesting in terms of the survival or extinction of one or more species in our system. Numerical simulations are carried out to illustrate our results. In fact, we show that the chaotic behavior in [7] unfolds when the harvesting rate parameter is varied.

  5. Dynamic mapping of conical intersection seams: A general method for incorporating the geometric phase in adiabatic dynamics in polyatomic systems.

    Science.gov (United States)

    Xie, Changjian; Malbon, Christopher L; Yarkony, David R; Guo, Hua

    2017-07-28

    The incorporation of the geometric phase in single-state adiabatic dynamics near a conical intersection (CI) seam has so far been restricted to molecular systems with high symmetry or simple model Hamiltonians. This is due to the fact that the ab initio determined derivative coupling (DC) in a multi-dimensional space is not curl-free, thus making its line integral path dependent. In a recent work [C. L. Malbon et al., J. Chem. Phys. 145, 234111 (2016)], we proposed a new and general approach based on an ab initio determined diabatic representation consisting of only two electronic states, in which the DC is completely removable, so that its line integral is path independent in the simply connected domains that exclude the CI seam. Then with the CIs included, the line integral of the single-valued DC can be used to construct the complex geometry-dependent phase needed to exactly eliminate the double-valued character of the real-valued adiabatic electronic wavefunction. This geometry-dependent phase gives rise to a vector potential which, when included in the adiabatic representation, rigorously accounts for the geometric phase in a system with an arbitrary locus of the CI seam and an arbitrary number of internal coordinates. In this work, we demonstrate this approach in a three-dimensional treatment of the tunneling facilitated dissociation of the S 1 state of phenol, which is affected by a C s symmetry allowed but otherwise accidental seam of CI. Here, since the space is three-dimensional rather than two-dimensional, the seam is a curve rather than a point. The nodal structure of the ground state vibronic wavefunction is shown to map out the seam of CI.

  6. Urban eco-efficiency and system dynamics modelling

    Energy Technology Data Exchange (ETDEWEB)

    Hradil, P., Email: petr.hradil@vtt.fi

    2012-06-15

    Assessment of urban development is generally based on static models of economic, social or environmental impacts. More advanced dynamic models have been used mostly for prediction of population and employment changes as well as for other macro-economic issues. This feasibility study was arranged to test the potential of system dynamic modelling in assessing eco-efficiency changes during urban development. (orig.)

  7. Incorporating Social Anxiety Into a Model of College Problem Drinking: Replication and Extension

    OpenAIRE

    Ham, Lindsay S.; Hope, Debra A.

    2006-01-01

    Although research has found an association between social anxiety and alcohol use in noncollege samples, results have been mixed for college samples. College students face many novel social situations in which they may drink to reduce social anxiety. In the current study, the authors tested a model of college problem drinking, incorporating social anxiety and related psychosocial variables among 228 undergraduate volunteers. According to structural equation modeling (SEM) results, social anxi...

  8. GDP-tubulin incorporation into growing microtubules modulates polymer stability.

    Science.gov (United States)

    Valiron, Odile; Arnal, Isabelle; Caudron, Nicolas; Job, Didier

    2010-06-04

    Microtubule growth proceeds through the endwise addition of nucleotide-bound tubulin dimers. The microtubule wall is composed of GDP-tubulin subunits, which are thought to come exclusively from the incorporation of GTP-tubulin complexes at microtubule ends followed by GTP hydrolysis within the polymer. The possibility of a direct GDP-tubulin incorporation into growing polymers is regarded as hardly compatible with recent structural data. Here, we have examined GTP-tubulin and GDP-tubulin incorporation into polymerizing microtubules using a minimal assembly system comprised of nucleotide-bound tubulin dimers, in the absence of free nucleotide. We find that GDP-tubulin complexes can efficiently co-polymerize with GTP-tubulin complexes during microtubule assembly. GDP-tubulin incorporation into microtubules occurs with similar efficiency during bulk microtubule assembly as during microtubule growth from seeds or centrosomes. Microtubules formed from GTP-tubulin/GDP-tubulin mixtures display altered microtubule dynamics, in particular a decreased shrinkage rate, apparently due to intrinsic modifications of the polymer disassembly properties. Thus, although microtubules polymerized from GTP-tubulin/GDP-tubulin mixtures or from homogeneous GTP-tubulin solutions are both composed of GDP-tubulin subunits, they have different dynamic properties, and this may reveal a novel form of microtubule "structural plasticity."

  9. Benchmarking novel approaches for modelling species range dynamics.

    Science.gov (United States)

    Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

    2016-08-01

    Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches

  10. Complex networks under dynamic repair model

    Science.gov (United States)

    Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

    2018-01-01

    Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.

  11. Brand Equity Evolution: a System Dynamics Model

    Directory of Open Access Journals (Sweden)

    Edson Crescitelli

    2009-04-01

    Full Text Available One of the greatest challenges in brand management lies in monitoring brand equity over time. This paper aimsto present a simulation model able to represent this evolution. The model was drawn on brand equity concepts developed by Aaker and Joachimsthaler (2000, using the system dynamics methodology. The use ofcomputational dynamic models aims to create new sources of information able to sensitize academics and managers alike to the dynamic implications of their brand management. As a result, an easily implementable model was generated, capable of executing continuous scenario simulations by surveying casual relations among the variables that explain brand equity. Moreover, the existence of a number of system modeling tools will allow extensive application of the concepts used in this study in practical situations, both in professional and educational settings

  12. Dynamic hysteretic sensing model of bending-mode Galfenol transducer

    International Nuclear Information System (INIS)

    Cao, Shuying; Zheng, Jiaju; Sang, Jie; Zhang, Pengfei; Wang, Bowen; Huang, Wenmei

    2015-01-01

    A dynamic hysteretic sensing model has been developed to predict the dynamic responses of the magnetic induction, the stress, and the output voltage for a bending-mode Galfenol unimorph transducer subjected simultaneously to acceleration and bias magnetic field. This model is obtained by coupling the hysteretic Armstrong model and the structural dynamic model of the Galfenol unimorph beam. The structural dynamic model of the beam is founded based on the Euler-Bernouli beam theory, the nonlinear constitutive equations, and the Faraday law of electromagnetic induction. Comparisons between the calculated and measured results show the model can describe dynamic nonlinear voltage characteristics of the device, and can predict hysteretic behaviors between the magnetic induction and the stress. Moreover, the model can effectively analyze the effects of the bias magnetic field, the acceleration amplitude, and frequency on the root mean square voltage of the device

  13. Dynamic hysteretic sensing model of bending-mode Galfenol transducer

    Energy Technology Data Exchange (ETDEWEB)

    Cao, Shuying, E-mail: shuying-cao@hebut.edu.cn; Zheng, Jiaju; Sang, Jie; Zhang, Pengfei; Wang, Bowen; Huang, Wenmei [Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology, Tianjin 300130 (China)

    2015-05-07

    A dynamic hysteretic sensing model has been developed to predict the dynamic responses of the magnetic induction, the stress, and the output voltage for a bending-mode Galfenol unimorph transducer subjected simultaneously to acceleration and bias magnetic field. This model is obtained by coupling the hysteretic Armstrong model and the structural dynamic model of the Galfenol unimorph beam. The structural dynamic model of the beam is founded based on the Euler-Bernouli beam theory, the nonlinear constitutive equations, and the Faraday law of electromagnetic induction. Comparisons between the calculated and measured results show the model can describe dynamic nonlinear voltage characteristics of the device, and can predict hysteretic behaviors between the magnetic induction and the stress. Moreover, the model can effectively analyze the effects of the bias magnetic field, the acceleration amplitude, and frequency on the root mean square voltage of the device.

  14. Incorporating ligament laxity in a finite element model for the upper cervical spine.

    Science.gov (United States)

    Lasswell, Timothy L; Cronin, Duane S; Medley, John B; Rasoulinejad, Parham

    2017-11-01

    Predicting physiological range of motion (ROM) using a finite element (FE) model of the upper cervical spine requires the incorporation of ligament laxity. The effect of ligament laxity can be observed only on a macro level of joint motion and is lost once ligaments have been dissected and preconditioned for experimental testing. As a result, although ligament laxity values are recognized to exist, specific values are not directly available in the literature for use in FE models. The purpose of the current study is to propose an optimization process that can be used to determine a set of ligament laxity values for upper cervical spine FE models. Furthermore, an FE model that includes ligament laxity is applied, and the resulting ROM values are compared with experimental data for physiological ROM, as well as experimental data for the increase in ROM when a Type II odontoid fracture is introduced. The upper cervical spine FE model was adapted from a 50th percentile male full-body model developed with the Global Human Body Models Consortium (GHBMC). FE modeling was performed in LS-DYNA and LS-OPT (Livermore Software Technology Group) was used for ligament laxity optimization. Ordinate-based curve matching was used to minimize the mean squared error (MSE) between computed load-rotation curves and experimental load-rotation curves under flexion, extension, and axial rotation with pure moment loads from 0 to 3.5 Nm. Lateral bending was excluded from the optimization because the upper cervical spine was considered to be primarily responsible for flexion, extension, and axial rotation. Based on recommendations from the literature, four varying inputs representing laxity in select ligaments were optimized to minimize the MSE. Funding was provided by the Natural Sciences and Engineering Research Council of Canada as well as GHMBC. The present study was funded by the Natural Sciences and Engineering Research Council of Canada to support the work of one graduate student

  15. Nonlinear Dynamic Models in Advanced Life Support

    Science.gov (United States)

    Jones, Harry

    2002-01-01

    To facilitate analysis, ALS systems are often assumed to be linear and time invariant, but they usually have important nonlinear and dynamic aspects. Nonlinear dynamic behavior can be caused by time varying inputs, changes in system parameters, nonlinear system functions, closed loop feedback delays, and limits on buffer storage or processing rates. Dynamic models are usually cataloged according to the number of state variables. The simplest dynamic models are linear, using only integration, multiplication, addition, and subtraction of the state variables. A general linear model with only two state variables can produce all the possible dynamic behavior of linear systems with many state variables, including stability, oscillation, or exponential growth and decay. Linear systems can be described using mathematical analysis. Nonlinear dynamics can be fully explored only by computer simulations of models. Unexpected behavior is produced by simple models having only two or three state variables with simple mathematical relations between them. Closed loop feedback delays are a major source of system instability. Exceeding limits on buffer storage or processing rates forces systems to change operating mode. Different equilibrium points may be reached from different initial conditions. Instead of one stable equilibrium point, the system may have several equilibrium points, oscillate at different frequencies, or even behave chaotically, depending on the system inputs and initial conditions. The frequency spectrum of an output oscillation may contain harmonics and the sums and differences of input frequencies, but it may also contain a stable limit cycle oscillation not related to input frequencies. We must investigate the nonlinear dynamic aspects of advanced life support systems to understand and counter undesirable behavior.

  16. Double Dynamic Supramolecular Polymers of Covalent Oligo-Dynamers

    NARCIS (Netherlands)

    Schaeffer, Gaël; Buhler, Eric; Candau, Sauveur Jean; Lehn, Jean-Marie

    2013-01-01

    Double-dynamic polymers, incorporating both molecular and supramolecular dynamic features (“double dynamers”) have been generated, where these functions are present in a nonstoichiometric ratio in the main chain of the polymer. It has been achieved by (1) the formation of covalent oligo-dynamers in

  17. Modeling the Potential Effects of New Tobacco Products and Policies: A Dynamic Population Model for Multiple Product Use and Harm

    Science.gov (United States)

    Vugrin, Eric D.; Rostron, Brian L.; Verzi, Stephen J.; Brodsky, Nancy S.; Brown, Theresa J.; Choiniere, Conrad J.; Coleman, Blair N.; Paredes, Antonio; Apelberg, Benjamin J.

    2015-01-01

    Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use for the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health

  18. Nonparametric modeling of dynamic functional connectivity in fmri data

    DEFF Research Database (Denmark)

    Nielsen, Søren Føns Vind; Madsen, Kristoffer H.; Røge, Rasmus

    2015-01-01

    dynamic changes. The existing approaches modeling dynamic connectivity have primarily been based on time-windowing the data and k-means clustering. We propose a nonparametric generative model for dynamic FC in fMRI that does not rely on specifying window lengths and number of dynamic states. Rooted...

  19. Increased drought impacts on temperate rainforests from southern South America: results of a process-based, dynamic forest model.

    Directory of Open Access Journals (Sweden)

    Alvaro G Gutiérrez

    Full Text Available Increased droughts due to regional shifts in temperature and rainfall regimes are likely to affect forests in temperate regions in the coming decades. To assess their consequences for forest dynamics, we need predictive tools that couple hydrologic processes, soil moisture dynamics and plant productivity. Here, we developed and tested a dynamic forest model that predicts the hydrologic balance of North Patagonian rainforests on Chiloé Island, in temperate South America (42°S. The model incorporates the dynamic linkages between changing rainfall regimes, soil moisture and individual tree growth. Declining rainfall, as predicted for the study area, should mean up to 50% less summer rain by year 2100. We analysed forest responses to increased drought using the model proposed focusing on changes in evapotranspiration, soil moisture and forest structure (above-ground biomass and basal area. We compared the responses of a young stand (YS, ca. 60 years-old and an old-growth forest (OG, >500 years-old in the same area. Based on detailed field measurements of water fluxes, the model provides a reliable account of the hydrologic balance of these evergreen, broad-leaved rainforests. We found higher evapotranspiration in OG than YS under current climate. Increasing drought predicted for this century can reduce evapotranspiration by 15% in the OG compared to current values. Drier climate will alter forest structure, leading to decreases in above ground biomass by 27% of the current value in OG. The model presented here can be used to assess the potential impacts of climate change on forest hydrology and other threats of global change on future forests such as fragmentation, introduction of exotic tree species, and changes in fire regimes. Our study expands the applicability of forest dynamics models in remote and hitherto overlooked regions of the world, such as southern temperate rainforests.

  20. Increased drought impacts on temperate rainforests from southern South America: results of a process-based, dynamic forest model.

    Science.gov (United States)

    Gutiérrez, Alvaro G; Armesto, Juan J; Díaz, M Francisca; Huth, Andreas

    2014-01-01

    Increased droughts due to regional shifts in temperature and rainfall regimes are likely to affect forests in temperate regions in the coming decades. To assess their consequences for forest dynamics, we need predictive tools that couple hydrologic processes, soil moisture dynamics and plant productivity. Here, we developed and tested a dynamic forest model that predicts the hydrologic balance of North Patagonian rainforests on Chiloé Island, in temperate South America (42°S). The model incorporates the dynamic linkages between changing rainfall regimes, soil moisture and individual tree growth. Declining rainfall, as predicted for the study area, should mean up to 50% less summer rain by year 2100. We analysed forest responses to increased drought using the model proposed focusing on changes in evapotranspiration, soil moisture and forest structure (above-ground biomass and basal area). We compared the responses of a young stand (YS, ca. 60 years-old) and an old-growth forest (OG, >500 years-old) in the same area. Based on detailed field measurements of water fluxes, the model provides a reliable account of the hydrologic balance of these evergreen, broad-leaved rainforests. We found higher evapotranspiration in OG than YS under current climate. Increasing drought predicted for this century can reduce evapotranspiration by 15% in the OG compared to current values. Drier climate will alter forest structure, leading to decreases in above ground biomass by 27% of the current value in OG. The model presented here can be used to assess the potential impacts of climate change on forest hydrology and other threats of global change on future forests such as fragmentation, introduction of exotic tree species, and changes in fire regimes. Our study expands the applicability of forest dynamics models in remote and hitherto overlooked regions of the world, such as southern temperate rainforests.

  1. Incorporation and Effects of Nanoparticles in a Supramolecular Polymer

    Science.gov (United States)

    2016-05-01

    polymerizations and main-chain supramolecular polymers . Macromolecules. 2009;42:6823–6835. 17. Wojtecki RJ, Meador MA, Rowan SJ. Using the dynamic bond...ARL-TR-7687 ● MAY 2016 US Army Research Laboratory Incorporation and Effects of Nanoparticles in a Supramolecular Polymer by...Laboratory Incorporation and Effects of Nanoparticles in a Supramolecular Polymer by Alice M Savage Oak Ridge Institute of Science and Education

  2. Modeling Gas Dynamics in California Sea Lions

    Science.gov (United States)

    2015-09-30

    W. and Fahlman, A. (2009). Could beaked whales get the bends?. Effect of diving behaviour and physiology on modelled gas exchange for three species...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Modeling Gas Dynamics in California Sea Lions Andreas...to update a current gas dynamics model with recently acquired data for respiratory compliance (P-V), and body compartment size estimates in

  3. A stable algorithm for calculating phase equilibria with capillarity at specified moles, volume and temperature using a dynamic model

    KAUST Repository

    Kou, Jisheng

    2017-09-30

    Capillary pressure can significantly affect the phase properties and flow of liquid-gas fluids in porous media, and thus, the phase equilibrium calculation incorporating capillary pressure is crucial to simulate such problems accurately. Recently, the phase equilibrium calculation at specified moles, volume and temperature (NVT-flash) becomes an attractive issue. In this paper, capillarity is incorporated into the phase equilibrium calculation at specified moles, volume and temperature. A dynamical model for such problem is developed for the first time by using the laws of thermodynamics and Onsager\\'s reciprocal principle. This model consists of the evolutionary equations for moles and volume, and it can characterize the evolutionary process from a non-equilibrium state to an equilibrium state in the presence of capillarity effect at specified moles, volume and temperature. The phase equilibrium equations are naturally derived. To simulate the proposed dynamical model efficiently, we adopt the convex-concave splitting of the total Helmholtz energy, and propose a thermodynamically stable numerical algorithm, which is proved to preserve the second law of thermodynamics at the discrete level. Using the thermodynamical relations, we derive a phase stability condition with capillarity effect at specified moles, volume and temperature. Moreover, we propose a stable numerical algorithm for the phase stability testing, which can provide the feasible initial conditions. The performance of the proposed methods in predicting phase properties under capillarity effect is demonstrated on various cases of pure substance and mixture systems.

  4. Next Generation Carbon-Nitrogen Dynamics Model

    Science.gov (United States)

    Xu, C.; Fisher, R. A.; Vrugt, J. A.; Wullschleger, S. D.; McDowell, N. G.

    2012-12-01

    Nitrogen is a key regulator of vegetation dynamics, soil carbon release, and terrestrial carbon cycles. Thus, to assess energy impacts on the global carbon cycle and future climates, it is critical that we have a mechanism-based and data-calibrated nitrogen model that simulates nitrogen limitation upon both above and belowground carbon dynamics. In this study, we developed a next generation nitrogen-carbon dynamic model within the NCAR Community Earth System Model (CESM). This next generation nitrogen-carbon dynamic model utilized 1) a mechanistic model of nitrogen limitation on photosynthesis with nitrogen trade-offs among light absorption, electron transport, carboxylation, respiration and storage; 2) an optimal leaf nitrogen model that links soil nitrogen availability and leaf nitrogen content; and 3) an ecosystem demography (ED) model that simulates the growth and light competition of tree cohorts and is currently coupled to CLM. Our three test cases with changes in CO2 concentration, growing temperature and radiation demonstrate the model's ability to predict the impact of altered environmental conditions on nitrogen allocations. Currently, we are testing the model against different datasets including soil fertilization and Free Air CO2 enrichment (FACE) experiments across different forest types. We expect that our calibrated model will considerably improve our understanding and predictability of vegetation-climate interactions.itrogen allocation model evaluations. The figure shows the scatter plots of predicted and measured Vc,max and Jmax scaled to 25 oC (i.e.,Vc,max25 and Jmax25) at elevated CO2 (570 ppm, test case one), reduced radiation in canopy (0.1-0.9 of the radiation at the top of canopy, test case two) and reduced growing temperature (15oC, test case three). The model is first calibrated using control data under ambient CO2 (370 ppm), radiation at the top of the canopy (621 μmol photon/m2/s), the normal growing temperature (30oC). The fitted model

  5. Relating structure and dynamics in organisation models

    NARCIS (Netherlands)

    Jonkers, C.M.; Treur, J.

    2002-01-01

    To understand how an organisational structure relates to dynamics is an interesting fundamental challenge in the area of social modelling. Specifications of organisational structure usually have a diagrammatic form that abstracts from more detailed dynamics. Dynamic properties of agent systems,

  6. Relating structure and dynamics in organisation models

    NARCIS (Netherlands)

    Jonker, C.M.; Treur, J.

    2003-01-01

    To understand how an organisational structure relates to dynamics is an interesting fundamental challenge in the area of social modelling. Specifications of organisational structure usually have a diagrammatic form that abstracts from more detailed dynamics. Dynamic properties of agent systems, on

  7. Characteristic dynamics near two coalescing eigenvalues incorporating continuum threshold effects

    Science.gov (United States)

    Garmon, Savannah; Ordonez, Gonzalo

    2017-06-01

    It has been reported in the literature that the survival probability P(t) near an exceptional point where two eigenstates coalesce should generally exhibit an evolution P (t ) ˜t2e-Γ t, in which Γ is the decay rate of the coalesced eigenstate; this has been verified in a microwave billiard experiment [B. Dietz et al., Phys. Rev. E 75, 027201 (2007)]. However, the heuristic effective Hamiltonian that is usually employed to obtain this result ignores the possible influence of the continuum threshold on the dynamics. By contrast, in this work we employ an analytical approach starting from the microscopic Hamiltonian representing two simple models in order to show that the continuum threshold has a strong influence on the dynamics near exceptional points in a variety of circumstances. To report our results, we divide the exceptional points in Hermitian open quantum systems into two cases: at an EP2A two virtual bound states coalesce before forming a resonance, anti-resonance pair with complex conjugate eigenvalues, while at an EP2B two resonances coalesce before forming two different resonances. For the EP2B, which is the case studied in the microwave billiard experiment, we verify that the survival probability exhibits the previously reported modified exponential decay on intermediate time scales, but this is replaced with an inverse power law on very long time scales. Meanwhile, for the EP2A the influence from the continuum threshold is so strong that the evolution is non-exponential on all time scales and the heuristic approach fails completely. When the EP2A appears very near the threshold, we obtain the novel evolution P (t ) ˜1 -C1√{t } on intermediate time scales, while further away the parabolic decay (Zeno dynamics) on short time scales is enhanced.

  8. Investigation of the Dynamic Contact Angle Using a Direct Numerical Simulation Method.

    Science.gov (United States)

    Zhu, Guangpu; Yao, Jun; Zhang, Lei; Sun, Hai; Li, Aifen; Shams, Bilal

    2016-11-15

    A large amount of residual oil, which exists as isolated oil slugs, remains trapped in reservoirs after water flooding. Numerous numerical studies are performed to investigate the fundamental flow mechanism of oil slugs to improve flooding efficiency. Dynamic contact angle models are usually introduced to simulate an accurate contact angle and meniscus displacement of oil slugs under a high capillary number. Nevertheless, in the oil slug flow simulation process, it is unnecessary to introduce the dynamic contact angle model because of a negligible change in the meniscus displacement after using the dynamic contact angle model when the capillary number is small. Therefore, a critical capillary number should be introduced to judge whether the dynamic contact model should be incorporated into simulations. In this study, a direct numerical simulation method is employed to simulate the oil slug flow in a capillary tube at the pore scale. The position of the interface between water and the oil slug is determined using the phase-field method. The capacity and accuracy of the model are validated using a classical benchmark: a dynamic capillary filling process. Then, different dynamic contact angle models and the factors that affect the dynamic contact angle are analyzed. The meniscus displacements of oil slugs with a dynamic contact angle and a static contact angle (SCA) are obtained during simulations, and the relative error between them is calculated automatically. The relative error limit has been defined to be 5%, beyond which the dynamic contact angle model needs to be incorporated into the simulation to approach the realistic displacement. Thus, the desired critical capillary number can be determined. A three-dimensional universal chart of critical capillary number, which functions as static contact angle and viscosity ratio, is given to provide a guideline for oil slug simulation. Also, a fitting formula is presented for ease of use.

  9. Dynamical models of the Galaxy

    Directory of Open Access Journals (Sweden)

    McMillan P.J.

    2012-02-01

    Full Text Available I discuss the importance of dynamical models for exploiting survey data, focusing on the advantages of “torus” models. I summarize a number of applications of these models to the study of the Milky Way, including the determination of the peculiar Solar velocity and investigation of the Hyades moving group.

  10. Stochastic modeling of phosphorus transport in the Three Gorges Reservoir by incorporating variability associated with the phosphorus partition coefficient

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Lei; Fang, Hongwei; Xu, Xingya; He, Guojian; Zhang, Xuesong; Reible, Danny

    2017-08-01

    Phosphorus (P) fate and transport plays a crucial role in the ecology of rivers and reservoirs in which eutrophication is limited by P. A key uncertainty in models used to help manage P in such systems is the partitioning of P to suspended and bed sediments. By analyzing data from field and laboratory experiments, we stochastically characterize the variability of the partition coefficient (Kd) and derive spatio-temporal solutions for P transport in the Three Gorges Reservoir (TGR). We formulate a set of stochastic partial different equations (SPDEs) to simulate P transport by randomly sampling Kd from the measured distributions, to obtain statistical descriptions of the P concentration and retention in the TGR. The correspondence between predicted and observed P concentrations and P retention in the TGR combined with the ability to effectively characterize uncertainty suggests that a model that incorporates the observed variability can better describe P dynamics and more effectively serve as a tool for P management in the system. This study highlights the importance of considering parametric uncertainty in estimating uncertainty/variability associated with simulated P transport.

  11. Maritime piracy situation modelling with dynamic Bayesian networks

    CSIR Research Space (South Africa)

    Dabrowski, James M

    2015-05-01

    Full Text Available A generative model for modelling maritime vessel behaviour is proposed. The model is a novel variant of the dynamic Bayesian network (DBN). The proposed DBN is in the form of a switching linear dynamic system (SLDS) that has been extended into a...

  12. Incorporating drug delivery into an imaging-driven, mechanics-coupled reaction diffusion model for predicting the response of breast cancer to neoadjuvant chemotherapy: theory and preliminary clinical results

    Science.gov (United States)

    Jarrett, Angela M.; Hormuth, David A.; Barnes, Stephanie L.; Feng, Xinzeng; Huang, Wei; Yankeelov, Thomas E.

    2018-05-01

    Clinical methods for assessing tumor response to therapy are largely rudimentary, monitoring only temporal changes in tumor size. Our goal is to predict the response of breast tumors to therapy using a mathematical model that utilizes magnetic resonance imaging (MRI) data obtained non-invasively from individual patients. We extended a previously established, mechanically coupled, reaction-diffusion model for predicting tumor response initialized with patient-specific diffusion weighted MRI (DW-MRI) data by including the effects of chemotherapy drug delivery, which is estimated using dynamic contrast-enhanced (DCE-) MRI data. The extended, drug incorporated, model is initialized using patient-specific DW-MRI and DCE-MRI data. Data sets from five breast cancer patients were used—obtained before, after one cycle, and at mid-point of neoadjuvant chemotherapy. The DCE-MRI data was used to estimate spatiotemporal variations in tumor perfusion with the extended Kety–Tofts model. The physiological parameters derived from DCE-MRI were used to model changes in delivery of therapy drugs within the tumor for incorporation in the extended model. We simulated the original model and the extended model in both 2D and 3D and compare the results for this five-patient cohort. Preliminary results show reductions in the error of model predicted tumor cellularity and size compared to the experimentally-measured results for the third MRI scan when therapy was incorporated. Comparing the two models for agreement between the predicted total cellularity and the calculated total cellularity (from the DW-MRI data) reveals an increased concordance correlation coefficient from 0.81 to 0.98 for the 2D analysis and 0.85 to 0.99 for the 3D analysis (p  <  0.01 for each) when the extended model was used in place of the original model. This study demonstrates the plausibility of using DCE-MRI data as a means to estimate drug delivery on a patient-specific basis in predictive models and

  13. Optimal dynamic economic dispatch of generation: A review

    International Nuclear Information System (INIS)

    Xia, X.; Elaiw, A.M.

    2010-01-01

    This paper presents a review of the research of the optimal power dynamic dispatch problem. The dynamic dispatch problem differs from the static economic dispatch problem by incorporating generator ramp rate constraints. There are two different formulations of this problem in the literature. The first formulation is the optimal control dynamic dispatch (OCDD) where the power system generation has been modeled as a control system and optimization is done in the optimal control setting with respect to the ramp rates as input variables. The second one is a later formulation known as the dynamic economic dispatch (DED) where optimization is done with respect to the dispatchable powers of the committed generation units. In this paper we first outline the two formulations, then present an overview on the mathematical optimization methods, Artificial Intelligence (AI) techniques and hybrid methods used to solve the problem incorporating extended and complex objective functions or constraints. The DED problem in deregulated electricity markets is also reported. (author)

  14. Influence of vegetation dynamic modeling on the allocation of green and blue waters

    Science.gov (United States)

    Ruiz-Pérez, Guiomar; Francés, Félix

    2015-04-01

    The long history of the Mediterranean region is dominated by the interactions and co-evolution between man and its natural environment. It is important to consider that the Mediterranean region is recurrently or permanently confronted with the scarcity of the water. The issue of climate change is (and will be) aggravating this situation. This raises the question of a loss of services that ecosystems provide to human and also the amount of available water to be used by vegetation. The question of the water cycle, therefore, should be considered in an integrated manner by taking into account both blue water (water in liquid form used for the human needs or which flows into the oceans) and green water (water having the vapor for resulting from evaporation and transpiration processes). In spite of this, traditionally, very few hydrological models have incorporated the vegetation dynamic as a state variable. In fact, most of them are able to represent fairly well the observed discharge, but usually including the vegetation as a static parameter. However, in the last decade, the number of hydrological models which explicitly take into account the vegetation development as a state variable has increased substantially. In this work, we want to analyze if it is really necessary to use a dynamic vegetation model to quantify adequately the distribution of water into blue and green water. The study site is located in the Public Forest Monte de la Hunde y Palomeras (Spain). The vegetation in the study area is dominated by Aleppo pine of high tree density with scant presence of other species. Two different daily models were applied (with static and dynamic vegetation representation respectively) in three different scenarios: dry year (2005), normal year (2008) and wet year (2010). The static vegetation model simulates the evapotranspiration considering the vegetation as a stationary parameter. Contrarily, the dynamic vegetation model connects the hydrological model with a

  15. A Financial Market Model Incorporating Herd Behaviour.

    Science.gov (United States)

    Wray, Christopher M; Bishop, Steven R

    2016-01-01

    Herd behaviour in financial markets is a recurring phenomenon that exacerbates asset price volatility, and is considered a possible contributor to market fragility. While numerous studies investigate herd behaviour in financial markets, it is often considered without reference to the pricing of financial instruments or other market dynamics. Here, a trader interaction model based upon informational cascades in the presence of information thresholds is used to construct a new model of asset price returns that allows for both quiescent and herd-like regimes. Agent interaction is modelled using a stochastic pulse-coupled network, parametrised by information thresholds and a network coupling probability. Agents may possess either one or two information thresholds that, in each case, determine the number of distinct states an agent may occupy before trading takes place. In the case where agents possess two thresholds (labelled as the finite state-space model, corresponding to agents' accumulating information over a bounded state-space), and where coupling strength is maximal, an asymptotic expression for the cascade-size probability is derived and shown to follow a power law when a critical value of network coupling probability is attained. For a range of model parameters, a mixture of negative binomial distributions is used to approximate the cascade-size distribution. This approximation is subsequently used to express the volatility of model price returns in terms of the model parameter which controls the network coupling probability. In the case where agents possess a single pulse-coupling threshold (labelled as the semi-infinite state-space model corresponding to agents' accumulating information over an unbounded state-space), numerical evidence is presented that demonstrates volatility clustering and long-memory patterns in the volatility of asset returns. Finally, output from the model is compared to both the distribution of historical stock returns and the market

  16. A Financial Market Model Incorporating Herd Behaviour.

    Directory of Open Access Journals (Sweden)

    Christopher M Wray

    Full Text Available Herd behaviour in financial markets is a recurring phenomenon that exacerbates asset price volatility, and is considered a possible contributor to market fragility. While numerous studies investigate herd behaviour in financial markets, it is often considered without reference to the pricing of financial instruments or other market dynamics. Here, a trader interaction model based upon informational cascades in the presence of information thresholds is used to construct a new model of asset price returns that allows for both quiescent and herd-like regimes. Agent interaction is modelled using a stochastic pulse-coupled network, parametrised by information thresholds and a network coupling probability. Agents may possess either one or two information thresholds that, in each case, determine the number of distinct states an agent may occupy before trading takes place. In the case where agents possess two thresholds (labelled as the finite state-space model, corresponding to agents' accumulating information over a bounded state-space, and where coupling strength is maximal, an asymptotic expression for the cascade-size probability is derived and shown to follow a power law when a critical value of network coupling probability is attained. For a range of model parameters, a mixture of negative binomial distributions is used to approximate the cascade-size distribution. This approximation is subsequently used to express the volatility of model price returns in terms of the model parameter which controls the network coupling probability. In the case where agents possess a single pulse-coupling threshold (labelled as the semi-infinite state-space model corresponding to agents' accumulating information over an unbounded state-space, numerical evidence is presented that demonstrates volatility clustering and long-memory patterns in the volatility of asset returns. Finally, output from the model is compared to both the distribution of historical stock

  17. A Financial Market Model Incorporating Herd Behaviour

    Science.gov (United States)

    2016-01-01

    Herd behaviour in financial markets is a recurring phenomenon that exacerbates asset price volatility, and is considered a possible contributor to market fragility. While numerous studies investigate herd behaviour in financial markets, it is often considered without reference to the pricing of financial instruments or other market dynamics. Here, a trader interaction model based upon informational cascades in the presence of information thresholds is used to construct a new model of asset price returns that allows for both quiescent and herd-like regimes. Agent interaction is modelled using a stochastic pulse-coupled network, parametrised by information thresholds and a network coupling probability. Agents may possess either one or two information thresholds that, in each case, determine the number of distinct states an agent may occupy before trading takes place. In the case where agents possess two thresholds (labelled as the finite state-space model, corresponding to agents’ accumulating information over a bounded state-space), and where coupling strength is maximal, an asymptotic expression for the cascade-size probability is derived and shown to follow a power law when a critical value of network coupling probability is attained. For a range of model parameters, a mixture of negative binomial distributions is used to approximate the cascade-size distribution. This approximation is subsequently used to express the volatility of model price returns in terms of the model parameter which controls the network coupling probability. In the case where agents possess a single pulse-coupling threshold (labelled as the semi-infinite state-space model corresponding to agents’ accumulating information over an unbounded state-space), numerical evidence is presented that demonstrates volatility clustering and long-memory patterns in the volatility of asset returns. Finally, output from the model is compared to both the distribution of historical stock returns and the

  18. An empirical model of the Baltic Sea reveals the importance of social dynamics for ecological regime shifts.

    Science.gov (United States)

    Lade, Steven J; Niiranen, Susa; Hentati-Sundberg, Jonas; Blenckner, Thorsten; Boonstra, Wiebren J; Orach, Kirill; Quaas, Martin F; Österblom, Henrik; Schlüter, Maja

    2015-09-01

    Regime shifts triggered by human activities and environmental changes have led to significant ecological and socioeconomic consequences in marine and terrestrial ecosystems worldwide. Ecological processes and feedbacks associated with regime shifts have received considerable attention, but human individual and collective behavior is rarely treated as an integrated component of such shifts. Here, we used generalized modeling to develop a coupled social-ecological model that integrated rich social and ecological data to investigate the role of social dynamics in the 1980s Baltic Sea cod boom and collapse. We showed that psychological, economic, and regulatory aspects of fisher decision making, in addition to ecological interactions, contributed both to the temporary persistence of the cod boom and to its subsequent collapse. These features of the social-ecological system also would have limited the effectiveness of stronger fishery regulations. Our results provide quantitative, empirical evidence that incorporating social dynamics into models of natural resources is critical for understanding how resources can be managed sustainably. We also show that generalized modeling, which is well-suited to collaborative model development and does not require detailed specification of causal relationships between system variables, can help tackle the complexities involved in creating and analyzing social-ecological models.

  19. Model for macroevolutionary dynamics.

    Science.gov (United States)

    Maruvka, Yosef E; Shnerb, Nadav M; Kessler, David A; Ricklefs, Robert E

    2013-07-02

    The highly skewed distribution of species among genera, although challenging to macroevolutionists, provides an opportunity to understand the dynamics of diversification, including species formation, extinction, and morphological evolution. Early models were based on either the work by Yule [Yule GU (1925) Philos Trans R Soc Lond B Biol Sci 213:21-87], which neglects extinction, or a simple birth-death (speciation-extinction) process. Here, we extend the more recent development of a generic, neutral speciation-extinction (of species)-origination (of genera; SEO) model for macroevolutionary dynamics of taxon diversification. Simulations show that deviations from the homogeneity assumptions in the model can be detected in species-per-genus distributions. The SEO model fits observed species-per-genus distributions well for class-to-kingdom-sized taxonomic groups. The model's predictions for the appearance times (the time of the first existing species) of the taxonomic groups also approximately match estimates based on molecular inference and fossil records. Unlike estimates based on analyses of phylogenetic reconstruction, fitted extinction rates for large clades are close to speciation rates, consistent with high rates of species turnover and the relatively slow change in diversity observed in the fossil record. Finally, the SEO model generally supports the consistency of generic boundaries based on morphological differences between species and provides a comparator for rates of lineage splitting and morphological evolution.

  20. Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.

    Science.gov (United States)

    Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis

    2018-01-01

    Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.

  1. [Incorporation of an organic MAGIC (Model of Acidification of Groundwater in Catchments) and testing of the revised model using independent data sources]. [MAGIC Model

    Energy Technology Data Exchange (ETDEWEB)

    Sullivan, T.J.

    1992-09-01

    A project was initiated in March, 1992 to (1) incorporate a rigorous organic acid representation, based on empirical data and geochemical considerations, into the MAGIC model of acidification response, and (2) test the revised model using three sets of independent data. After six months of performance, the project is on schedule and the majority of the tasks outlined for Year 1 have been successfully completed. Major accomplishments to data include development of the organic acid modeling approach, using data from the Adirondack Lakes Survey Corporation (ALSC), and coupling the organic acid model with MAGIC for chemical hindcast comparisons. The incorporation of an organic acid representation into MAGIC can account for much of the discrepancy earlier observed between MAGIC hindcasts and paleolimnological reconstructions of preindustrial pH and alkalinity for 33 statistically-selected Adirondack lakes. Additional work is on-going for model calibration and testing with data from two whole-catchment artificial acidification projects. Results obtained thus far are being prepared as manuscripts for submission to the peer-reviewed scientific literature.

  2. Neural Population Dynamics during Reaching Are Better Explained by a Dynamical System than Representational Tuning.

    Science.gov (United States)

    Michaels, Jonathan A; Dann, Benjamin; Scherberger, Hansjörg

    2016-11-01

    Recent models of movement generation in motor cortex have sought to explain neural activity not as a function of movement parameters, known as representational models, but as a dynamical system acting at the level of the population. Despite evidence supporting this framework, the evaluation of representational models and their integration with dynamical systems is incomplete in the literature. Using a representational velocity-tuning based simulation of center-out reaching, we show that incorporating variable latency offsets between neural activity and kinematics is sufficient to generate rotational dynamics at the level of neural populations, a phenomenon observed in motor cortex. However, we developed a covariance-matched permutation test (CMPT) that reassigns neural data between task conditions independently for each neuron while maintaining overall neuron-to-neuron relationships, revealing that rotations based on the representational model did not uniquely depend on the underlying condition structure. In contrast, rotations based on either a dynamical model or motor cortex data depend on this relationship, providing evidence that the dynamical model more readily explains motor cortex activity. Importantly, implementing a recurrent neural network we demonstrate that both representational tuning properties and rotational dynamics emerge, providing evidence that a dynamical system can reproduce previous findings of representational tuning. Finally, using motor cortex data in combination with the CMPT, we show that results based on small numbers of neurons or conditions should be interpreted cautiously, potentially informing future experimental design. Together, our findings reinforce the view that representational models lack the explanatory power to describe complex aspects of single neuron and population level activity.

  3. Are adverse effects incorporated in economic models? An initial review of current practice.

    Science.gov (United States)

    Craig, D; McDaid, C; Fonseca, T; Stock, C; Duffy, S; Woolacott, N

    2009-12-01

    To identify methodological research on the incorporation of adverse effects in economic models and to review current practice. Major electronic databases (Cochrane Methodology Register, Health Economic Evaluations Database, NHS Economic Evaluation Database, EconLit, EMBASE, Health Management Information Consortium, IDEAS, MEDLINE and Science Citation Index) were searched from inception to September 2007. Health technology assessment (HTA) reports commissioned by the National Institute for Health Research (NIHR) HTA programme and published between 2004 and 2007 were also reviewed. The reviews of methodological research on the inclusion of adverse effects in decision models and of current practice were carried out according to standard methods. Data were summarised in a narrative synthesis. Of the 719 potentially relevant references in the methodological research review, five met the inclusion criteria; however, they contained little information of direct relevance to the incorporation of adverse effects in models. Of the 194 HTA monographs published from 2004 to 2007, 80 were reviewed, covering a range of research and therapeutic areas. In total, 85% of the reports included adverse effects in the clinical effectiveness review and 54% of the decision models included adverse effects in the model; 49% included adverse effects in the clinical review and model. The link between adverse effects in the clinical review and model was generally weak; only 3/80 (manipulation. Of the models including adverse effects, 67% used a clinical adverse effects parameter, 79% used a cost of adverse effects parameter, 86% used one of these and 60% used both. Most models (83%) used utilities, but only two (2.5%) used solely utilities to incorporate adverse effects and were explicit that the utility captured relevant adverse effects; 53% of those models that included utilities derived them from patients on treatment and could therefore be interpreted as capturing adverse effects. In total

  4. An Epidemiological Model of Rift Valley Fever with Spatial Dynamics

    Directory of Open Access Journals (Sweden)

    Tianchan Niu

    2012-01-01

    Full Text Available As a category A agent in the Center for Disease Control bioterrorism list, Rift Valley fever (RVF is considered a major threat to the United States (USA. Should the pathogen be intentionally or unintentionally introduced to the continental USA, there is tremendous potential for economic damages due to loss of livestock, trade restrictions, and subsequent food supply chain disruptions. We have incorporated the effects of space into a mathematical model of RVF in order to study the dynamics of the pathogen spread as affected by the movement of humans, livestock, and mosquitoes. The model accounts for the horizontal transmission of Rift Valley fever virus (RVFV between two mosquito and one livestock species, and mother-to-offspring transmission of virus in one of the mosquito species. Space effects are introduced by dividing geographic space into smaller patches and considering the patch-to-patch movement of species. For each patch, a system of ordinary differential equations models fractions of populations susceptible to, incubating, infectious with, or immune to RVFV. The main contribution of this work is a methodology for analyzing the likelihood of pathogen establishment should an introduction occur into an area devoid of RVF. Examples are provided for general and specific cases to illustrate the methodology.

  5. Linking spatial and dynamic models for traffic maneuvers

    DEFF Research Database (Denmark)

    Olderog, Ernst-Rüdiger; Ravn, Anders Peter; Wisniewski, Rafal

    2015-01-01

    For traffic maneuvers of multiple vehicles on highways we build an abstract spatial and a concrete dynamic model. In the spatial model we show the safety (collision freedom) of lane-change maneuvers. By linking the spatial and dynamic model via suitable refinements of the spatial atoms to distance...

  6. Dynamics in Higher Education Politics: A Theoretical Model

    Science.gov (United States)

    Kauko, Jaakko

    2013-01-01

    This article presents a model for analysing dynamics in higher education politics (DHEP). Theoretically the model draws on the conceptual history of political contingency, agenda-setting theories and previous research on higher education dynamics. According to the model, socio-historical complexity can best be analysed along two dimensions: the…

  7. Containing Terrorism: A Dynamic Model

    Directory of Open Access Journals (Sweden)

    Giti Zahedzadeh

    2017-06-01

    Full Text Available The strategic interplay between counterterror measures and terror activity is complex. Herein, we propose a dynamic model to depict this interaction. The model generates stylized prognoses: (i under conditions of inefficient counterterror measures, terror groups enjoy longer period of activity but only if recruitment into terror groups remains low; high recruitment shortens the period of terror activity (ii highly efficient counterterror measures effectively contain terror activity, but only if recruitment remains low. Thus, highly efficient counterterror measures can effectively contain terrorism if recruitment remains restrained. We conclude that the trajectory of the dynamics between counterterror measures and terror activity is heavily altered by recruitment.

  8. The Significance of Incorporating Nanoscale Fluctuations in a Constitutive Description of Glassy Polymers

    Science.gov (United States)

    Caruthers, James

    2015-03-01

    The current picture of the glass involves dynamic heterogeneity, where nanoscopic regions of the glass have order-of-magnitude differences in local mobility that evolve with time. Dynamic heterogeneity provides a critical challenge to the traditional nonlinear continuum models, where both temporal and spatial fluctuations are averaged as a result of the continuum postulate. In order to acknowledge dynamic heterogeneity, a Stochastic Constitutive Model (SCM) has been developed to describe the nonlinear viscoelastic behavior of polymeric glasses, where (i) temporal fluctuations are explicitly included and (ii) the local mobility depends upon the local state of the material (e.g. local stress and local entropy) vs. traditional viscoelastic/viscoelastic models where macroscopic mobility depends upon the macroscopic state. The SCM is able to describe a number of nonlinear relaxation phenomena that cannot be predicted by traditional nonlinear viscoelastic/viscoplastic models, including (i) post-yield stress softening and its dependence on annealing time, (ii) the inversion of the strain dependence of nonlinear stress relaxation with the loading rate, (iii) stress memory and (iv) tertiary creep and creep-recovery. This paper will argue that incorporation of nanoscopic fluctuations is a necessary component for a description of the thermomechanical behavior of polymeric glasses. Support from NSF Grant 1363326-CMMI.

  9. Model tests on dynamic performance of RC shear walls

    International Nuclear Information System (INIS)

    Nagashima, Toshio; Shibata, Akenori; Inoue, Norio; Muroi, Kazuo.

    1991-01-01

    For the inelastic dynamic response analysis of a reactor building subjected to earthquakes, it is essentially important to properly evaluate its restoring force characteristics under dynamic loading condition and its damping performance. Reinforced concrete shear walls are the main structural members of a reactor building, and dominate its seismic behavior. In order to obtain the basic information on the dynamic restoring force characteristics and damping performance of shear walls, the dynamic test using a large shaking table, static displacement control test and the pseudo-dynamic test on the models of a shear wall were conducted. In the dynamic test, four specimens were tested on a large shaking table. In the static test, four specimens were tested, and in the pseudo-dynamic test, three specimens were tested. These tests are outlined. The results of these tests were compared, placing emphasis on the restoring force characteristics and damping performance of the RC wall models. The strength was higher in the dynamic test models than in the static test models mainly due to the effect of loading rate. (K.I.)

  10. Incorporation of chemical kinetic models into process control

    International Nuclear Information System (INIS)

    Herget, C.J.; Frazer, J.W.

    1981-01-01

    An important consideration in chemical process control is to determine the precise rationing of reactant streams, particularly when a large time delay exists between the mixing of the reactants and the measurement of the product. In this paper, a method is described for incorporating chemical kinetic models into the control strategy in order to achieve optimum operating conditions. The system is first characterized by determining a reaction rate surface as a function of all input reactant concentrations over a feasible range. A nonlinear constrained optimization program is then used to determine the combination of reactants which produces the specified yield at minimum cost. This operating condition is then used to establish the nominal concentrations of the reactants. The actual operation is determined through a feedback control system employing a Smith predictor. The method is demonstrated on a laboratory bench scale enzyme reactor

  11. A dynamic model of renal blood flow autoregulation

    DEFF Research Database (Denmark)

    Holstein-Rathlou, N H; Marsh, D J

    1994-01-01

    To test whether a mathematical model combining dynamic models of the tubuloglomerular feedback (TGF) mechanism and the myogenic mechanism was sufficient to explain dynamic autoregulation of renal blood flow, we compared model simulations with experimental data. To assess the dynamic characteristics...... of renal autoregulation, a broad band perturbation of the arterial pressure was employed in both the simulations and the experiments. Renal blood flow and tubular pressure were used as response variables in the comparison. To better approximate the situation in vivo where a large number of individual...... data, which shows a unimodal curve for the admittance phase. The ability of the model to reproduce the experimental data supports the hypothesis that dynamic autoregulation of renal blood flow is due to the combined action of TGF and the myogenic response....

  12. Users' guide to system dynamics model describing Coho salmon survival in Olema Creek, Point Reyes National Seashore, Marin County, California

    Science.gov (United States)

    Woodward, Andrea; Torregrosa, Alicia; Madej, Mary Ann; Reichmuth, Michael; Fong, Darren

    2014-01-01

    The system dynamics model described in this report is the result of a collaboration between U.S. Geological Survey (USGS) scientists and National Park Service (NPS) San Francisco Bay Area Network (SFAN) staff, whose goal was to develop a methodology to integrate inventory and monitoring data to better understand ecosystem dynamics and trends using salmon in Olema Creek, Marin County, California, as an example case. The SFAN began monitoring multiple life stages of coho salmon (Oncorhynchus kisutch) in Olema Creek during 2003 (Carlisle and others, 2013), building on previous monitoring of spawning fish and redds. They initiated water-quality and habitat monitoring, and had access to flow and weather data from other sources. This system dynamics model of the freshwater portion of the coho salmon life cycle in Olema Creek integrated 8 years of existing monitoring data, literature values, and expert opinion to investigate potential factors limiting survival and production, identify data gaps, and improve monitoring and restoration prescriptions. A system dynamics model is particularly effective when (1) data are insufficient in time series length and/or measured parameters for a statistical or mechanistic model, and (2) the model must be easily accessible by users who are not modelers. These characteristics helped us meet the following overarching goals for this model: Summarize and synthesize NPS monitoring data with data and information from other sources to describe factors and processes affecting freshwater survival of coho salmon in Olema Creek. Provide a model that can be easily manipulated to experiment with alternative values of model parameters and novel scenarios of environmental drivers. Although the model describes the ecological dynamics of Olema Creek, these dynamics are structurally similar to numerous other coastal streams along the California coast that also contain anadromous fish populations. The model developed for Olema can be used, at least as a

  13. Two improvements to the dynamic wake meandering model: including the effects of atmospheric shear on wake turbulence and incorporating turbulence build-up in a row of wind turbines

    DEFF Research Database (Denmark)

    Keck, Rolf-Erik; de Mare, Martin Tobias; Churchfield, Matthew J.

    2015-01-01

    The dynamic wake meandering (DWM) model is an engineering wake model designed to physically model the wake deficit evolution and the unsteady meandering that occurs in wind turbine wakes. The present study aims at improving two features of the model: The effect of the atmospheric boundary layer s...

  14. A parametric study of a solar calcinator using computational fluid dynamics

    International Nuclear Information System (INIS)

    Fidaros, D.K.; Baxevanou, C.A.; Vlachos, N.S.

    2007-01-01

    In this work a horizontal rotating solar calcinator is studied numerically using computational fluid dynamics. The specific solar reactor is a 10 kW model designed and used for efficiency studies. The numerical model is based on the solution of the Navier-Stokes equations for the gas flow, and on Lagrangean dynamics for the discrete particles. All necessary mathematical models were developed and incorporated into a computational fluid dynamics model with the influence of turbulence simulated by a two-equation (RNG k-ε) model. The efficiency of the reactor was calculated for different thermal inputs, feed rates, rotational speeds and particle diameters. The numerically computed degrees of calcination compared well with equivalent experimental results

  15. Incorporating experience curves in appliance standards analysis

    International Nuclear Information System (INIS)

    Desroches, Louis-Benoit; Garbesi, Karina; Kantner, Colleen; Van Buskirk, Robert; Yang, Hung-Chia

    2013-01-01

    There exists considerable evidence that manufacturing costs and consumer prices of residential appliances have decreased in real terms over the last several decades. This phenomenon is generally attributable to manufacturing efficiency gained with cumulative experience producing a certain good, and is modeled by an empirical experience curve. The technical analyses conducted in support of U.S. energy conservation standards for residential appliances and commercial equipment have, until recently, assumed that manufacturing costs and retail prices remain constant during the projected 30-year analysis period. This assumption does not reflect real market price dynamics. Using price data from the Bureau of Labor Statistics, we present U.S. experience curves for room air conditioners, clothes dryers, central air conditioners, furnaces, and refrigerators and freezers. These experience curves were incorporated into recent energy conservation standards analyses for these products. Including experience curves increases the national consumer net present value of potential standard levels. In some cases a potential standard level exhibits a net benefit when considering experience, whereas without experience it exhibits a net cost. These results highlight the importance of modeling more representative market prices. - Highlights: ► Past appliance standards analyses have assumed constant equipment prices. ► There is considerable evidence of consistent real price declines. ► We incorporate experience curves for several large appliances into the analysis. ► The revised analyses demonstrate larger net present values of potential standards. ► The results imply that past standards analyses may have undervalued benefits.

  16. A model for plasticity kinetics and its role in simulating the dynamic behavior of Fe at high strain rates

    Energy Technology Data Exchange (ETDEWEB)

    Colvin, J D; Minich, R W; Kalantar, D H

    2007-03-29

    The recent diagnostic capability of the Omega laser to study solid-solid phase transitions at pressures greater than 10 GPa and at strain rates exceeding 10{sup 7} s{sup -1} has also provided valuable information on the dynamic elastic-plastic behavior of materials. We have found, for example, that plasticity kinetics modifies the effective loading and thermodynamic paths of the material. In this paper we derive a kinetics equation for the time-dependent plastic response of the material to dynamic loading, and describe the model's implementation in a radiation-hydrodynamics computer code. This model for plasticity kinetics incorporates the Gilman model for dislocation multiplication and saturation. We discuss the application of this model to the simulation of experimental velocity interferometry data for experiments on Omega in which Fe was shock compressed to pressures beyond the {alpha}-to-{var_epsilon} phase transition pressure. The kinetics model is shown to fit the data reasonably well in this high strain rate regime and further allows quantification of the relative contributions of dislocation multiplication and drag. The sensitivity of the observed signatures to the kinetics model parameters is presented.

  17. Comparative analysis of hourly and dynamic power balancing models for validating future energy scenarios

    DEFF Research Database (Denmark)

    Pillai, Jayakrishnan R.; Heussen, Kai; Østergaard, Poul Alberg

    2011-01-01

    Energy system analyses on the basis of fast and simple tools have proven particularly useful for interdisciplinary planning projects with frequent iterations and re-evaluation of alternative scenarios. As such, the tool “EnergyPLAN” is used for hourly balanced and spatially aggregate annual......, the model is verified on the basis of the existing energy mix on Bornholm as an islanded energy system. Future energy scenarios for the year 2030 are analysed to study a feasible technology mix for a higher share of wind power. Finally, the results of the hourly simulations are compared to dynamic frequency...... simulations incorporating the Vehicle-to-grid technology. The results indicate how the EnergyPLAN model may be improved in terms of intra-hour variability, stability and ancillary services to achieve a better reflection of energy and power capacity requirements....

  18. A comprehensive dynamic modeling approach for giant magnetostrictive material actuators

    International Nuclear Information System (INIS)

    Gu, Guo-Ying; Zhu, Li-Min; Li, Zhi; Su, Chun-Yi

    2013-01-01

    In this paper, a comprehensive modeling approach for a giant magnetostrictive material actuator (GMMA) is proposed based on the description of nonlinear electromagnetic behavior, the magnetostrictive effect and frequency response of the mechanical dynamics. It maps the relationships between current and magnetic flux at the electromagnetic part to force and displacement at the mechanical part in a lumped parameter form. Towards this modeling approach, the nonlinear hysteresis effect of the GMMA appearing only in the electrical part is separated from the linear dynamic plant in the mechanical part. Thus, a two-module dynamic model is developed to completely characterize the hysteresis nonlinearity and the dynamic behaviors of the GMMA. The first module is a static hysteresis model to describe the hysteresis nonlinearity, and the cascaded second module is a linear dynamic plant to represent the dynamic behavior. To validate the proposed dynamic model, an experimental platform is established. Then, the linear dynamic part and the nonlinear hysteresis part of the proposed model are identified in sequence. For the linear part, an approach based on axiomatic design theory is adopted. For the nonlinear part, a Prandtl–Ishlinskii model is introduced to describe the hysteresis nonlinearity and a constrained quadratic optimization method is utilized to identify its coefficients. Finally, experimental tests are conducted to demonstrate the effectiveness of the proposed dynamic model and the corresponding identification method. (paper)

  19. Dynamic Evolution Model Based on Social Network Services

    Science.gov (United States)

    Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen

    2013-11-01

    Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.

  20. The Quadrotor Dynamic Modeling and Indoor Target Tracking Control Method

    Directory of Open Access Journals (Sweden)

    Dewei Zhang

    2014-01-01

    Full Text Available A reliable nonlinear dynamic model of the quadrotor is presented. The nonlinear dynamic model includes actuator dynamic and aerodynamic effect. Since the rotors run near a constant hovering speed, the dynamic model is simplified at hovering operating point. Based on the simplified nonlinear dynamic model, the PID controllers with feedback linearization and feedforward control are proposed using the backstepping method. These controllers are used to control both the attitude and position of the quadrotor. A fully custom quadrotor is developed to verify the correctness of the dynamic model and control algorithms. The attitude of the quadrotor is measured by inertia measurement unit (IMU. The position of the quadrotor in a GPS-denied environment, especially indoor environment, is estimated from the downward camera and ultrasonic sensor measurements. The validity and effectiveness of the proposed dynamic model and control algorithms are demonstrated by experimental results. It is shown that the vehicle achieves robust vision-based hovering and moving target tracking control.

  1. Modeling emotional dynamics : currency versus field.

    Energy Technology Data Exchange (ETDEWEB)

    Sallach, D .L.; Decision and Information Sciences; Univ. of Chicago

    2008-08-01

    Randall Collins has introduced a simplified model of emotional dynamics in which emotional energy, heightened and focused by interaction rituals, serves as a common denominator for social exchange: a generic form of currency, except that it is active in a far broader range of social transactions. While the scope of this theory is attractive, the specifics of the model remain unconvincing. After a critical assessment of the currency theory of emotion, a field model of emotion is introduced that adds expressiveness by locating emotional valence within its cognitive context, thereby creating an integrated orientation field. The result is a model which claims less in the way of motivational specificity, but is more satisfactory in modeling the dynamic interaction between cognitive and emotional orientations at both individual and social levels.

  2. Incorporation of detailed eye model into polygon-mesh versions of ICRP-110 reference phantoms.

    Science.gov (United States)

    Nguyen, Thang Tat; Yeom, Yeon Soo; Kim, Han Sung; Wang, Zhao Jun; Han, Min Cheol; Kim, Chan Hyeong; Lee, Jai Ki; Zankl, Maria; Petoussi-Henss, Nina; Bolch, Wesley E; Lee, Choonsik; Chung, Beom Sun

    2015-11-21

    The dose coefficients for the eye lens reported in ICRP 2010 Publication 116 were calculated using both a stylized model and the ICRP-110 reference phantoms, according to the type of radiation, energy, and irradiation geometry. To maintain consistency of lens dose assessment, in the present study we incorporated the ICRP-116 detailed eye model into the converted polygon-mesh (PM) version of the ICRP-110 reference phantoms. After the incorporation, the dose coefficients for the eye lens were calculated and compared with those of the ICRP-116 data. The results showed generally a good agreement between the newly calculated lens dose coefficients and the values of ICRP 2010 Publication 116. Significant differences were found for some irradiation cases due mainly to the use of different types of phantoms. Considering that the PM version of the ICRP-110 reference phantoms preserve the original topology of the ICRP-110 reference phantoms, it is believed that the PM version phantoms, along with the detailed eye model, provide more reliable and consistent dose coefficients for the eye lens.

  3. A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology.

    Science.gov (United States)

    Tompkins, Adrian M; Ermert, Volker

    2013-02-18

    The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions.

  4. An airloads theory for morphing airfoils in dynamic stall with experimental correlation

    Science.gov (United States)

    Ahaus, Loren A.

    Helicopter rotor blades frequently encounter dynamic stall during normal flight conditions, limiting the applicability of classical thin-airfoil theory at large angles of attack. Also, it is evident that because of the largely different conditions on the advancing and retreating sides of the rotor, future rotorcraft may incorporate dynamically morphing airfoils (trailing-edge aps, dynamic camber, dynamic droop, etc.). Reduced-order aerodynamic models are needed for preliminary design and ight simulation. A unified model for predicting the airloads on a morphing airfoil in dynamic stall is presented, consisting of three components. First, a linear airloads theory allows for arbitrary airfoil deformations consistent with a morphing airfoil. Second, to capture the effects of the wake, the airloads theory is coupled to an induced ow model. Third, the overshoot and time delay associated with dynamic stall are modeled by a second-order dynamic filter, along the lines of the ONERA dynamic stall model. This paper presents a unified airloads model that allows arbitrary airfoil morphing with dynamic stall. Correlations with experimental data validate the theory.

  5. Participatory System Dynamics Modeling: Increasing Stakeholder Engagement and Precision to Improve Implementation Planning in Systems.

    Science.gov (United States)

    Zimmerman, Lindsey; Lounsbury, David W; Rosen, Craig S; Kimerling, Rachel; Trafton, Jodie A; Lindley, Steven E

    2016-11-01

    Implementation planning typically incorporates stakeholder input. Quality improvement efforts provide data-based feedback regarding progress. Participatory system dynamics modeling (PSD) triangulates stakeholder expertise, data and simulation of implementation plans prior to attempting change. Frontline staff in one VA outpatient mental health system used PSD to examine policy and procedural "mechanisms" they believe underlie local capacity to implement evidence-based psychotherapies (EBPs) for PTSD and depression. We piloted the PSD process, simulating implementation plans to improve EBP reach. Findings indicate PSD is a feasible, useful strategy for building stakeholder consensus, and may save time and effort as compared to trial-and-error EBP implementation planning.

  6. Direct modeling for computational fluid dynamics

    Science.gov (United States)

    Xu, Kun

    2015-06-01

    All fluid dynamic equations are valid under their modeling scales, such as the particle mean free path and mean collision time scale of the Boltzmann equation and the hydrodynamic scale of the Navier-Stokes (NS) equations. The current computational fluid dynamics (CFD) focuses on the numerical solution of partial differential equations (PDEs), and its aim is to get the accurate solution of these governing equations. Under such a CFD practice, it is hard to develop a unified scheme that covers flow physics from kinetic to hydrodynamic scales continuously because there is no such governing equation which could make a smooth transition from the Boltzmann to the NS modeling. The study of fluid dynamics needs to go beyond the traditional numerical partial differential equations. The emerging engineering applications, such as air-vehicle design for near-space flight and flow and heat transfer in micro-devices, do require further expansion of the concept of gas dynamics to a larger domain of physical reality, rather than the traditional distinguishable governing equations. At the current stage, the non-equilibrium flow physics has not yet been well explored or clearly understood due to the lack of appropriate tools. Unfortunately, under the current numerical PDE approach, it is hard to develop such a meaningful tool due to the absence of valid PDEs. In order to construct multiscale and multiphysics simulation methods similar to the modeling process of constructing the Boltzmann or the NS governing equations, the development of a numerical algorithm should be based on the first principle of physical modeling. In this paper, instead of following the traditional numerical PDE path, we introduce direct modeling as a principle for CFD algorithm development. Since all computations are conducted in a discretized space with limited cell resolution, the flow physics to be modeled has to be done in the mesh size and time step scales. Here, the CFD is more or less a direct

  7. A spring-mass-damper system dynamics-based driver-vehicle integrated model for representing heterogeneous traffic

    Science.gov (United States)

    Munigety, Caleb Ronald

    2018-04-01

    The traditional traffic microscopic simulation models consider driver and vehicle as a single unit to represent the movements of drivers in a traffic stream. Due to this very fact, the traditional car-following models have the driver behavior related parameters, but ignore the vehicle related aspects. This approach is appropriate for homogeneous traffic conditions where car is the major vehicle type. However, in heterogeneous traffic conditions where multiple vehicle types are present, it becomes important to incorporate the vehicle related parameters exclusively to account for the varying dynamic and static characteristics. Thus, this paper presents a driver-vehicle integrated model hinged on the principles involved in physics-based spring-mass-damper mechanical system. While the spring constant represents the driver’s aggressiveness, the damping constant and the mass component take care of the stability and size/weight related aspects, respectively. The proposed model when tested, behaved pragmatically in representing the vehicle-type dependent longitudinal movements of vehicles.

  8. On the dynamics of k-essence models

    International Nuclear Information System (INIS)

    Jorge, Pedro; Mimoso, Jose P; Wands, David

    2007-01-01

    We investigate cosmological dynamics of models with higher-order corrections to the canonical (second-order) kinetic lagrangian for a scalar field, which have been termed k -essence . We study the qualitative dynamics of simple purely kinetic k-essence models and find that the simplest attempts to construct non-singular cosmological models by including higher-order terms in the kinetic lagrangian fail because of a different type of singularity where the scalar field theory becomes ill-defined

  9. Online Learning of Industrial Manipulators' Dynamics Models

    DEFF Research Database (Denmark)

    Polydoros, Athanasios

    2017-01-01

    , it was compared with multiple other state-of-the-art machine learning algorithms. Moreover, the thesis presents the application of the proposed learning method on robot control for achieving trajectory execution while learning the inverse dynamics models  on-the-fly . Also it is presented the application...... of the dynamics models. Those mainly derive from physics-based methods and thus they are based on physical properties which are hard to be calculated.  In this thesis, is presented, a novel online machine learning approach  which is able to model both inverse and forward dynamics models of industrial manipulators....... The proposed method belongs to the class of deep learning and exploits the concepts of self-organization, recurrent neural networks and iterative multivariate Bayesian regression. It has been evaluated on multiple datasets captured from industrial robots while they were performing various tasks. Also...

  10. Using Difference Equation to Model Discrete-time Behavior in System Dynamics Modeling

    NARCIS (Netherlands)

    Hesan, R.; Ghorbani, A.; Dignum, M.V.

    2014-01-01

    In system dynamics modeling, differential equations have been used as the basic mathematical operator. Using difference equation to build system dynamics models instead of differential equation, can be insightful for studying small organizations or systems with micro behavior. In this paper we

  11. Dynamic model based on Bayesian method for energy security assessment

    International Nuclear Information System (INIS)

    Augutis, Juozas; Krikštolaitis, Ričardas; Pečiulytė, Sigita; Žutautaitė, Inga

    2015-01-01

    Highlights: • Methodology for dynamic indicator model construction and forecasting of indicators. • Application of dynamic indicator model for energy system development scenarios. • Expert judgement involvement using Bayesian method. - Abstract: The methodology for the dynamic indicator model construction and forecasting of indicators for the assessment of energy security level is presented in this article. An indicator is a special index, which provides numerical values to important factors for the investigated area. In real life, models of different processes take into account various factors that are time-dependent and dependent on each other. Thus, it is advisable to construct a dynamic model in order to describe these dependences. The energy security indicators are used as factors in the dynamic model. Usually, the values of indicators are obtained from statistical data. The developed dynamic model enables to forecast indicators’ variation taking into account changes in system configuration. The energy system development is usually based on a new object construction. Since the parameters of changes of the new system are not exactly known, information about their influences on indicators could not be involved in the model by deterministic methods. Thus, dynamic indicators’ model based on historical data is adjusted by probabilistic model with the influence of new factors on indicators using the Bayesian method

  12. A moving boundary problem and orthogonal collocation in solving a dynamic liquid surfactant membrane model including osmosis and breakage

    Directory of Open Access Journals (Sweden)

    E.C. Biscaia Junior

    2001-06-01

    Full Text Available A dynamic kinetic-diffusive model for the extraction of metallic ions from aqueous liquors using liquid surfactant membranes is proposed. The model incorporates undesirable intrinsic phenomena such as swelling and breakage of the emulsion globules that have to be controlled during process operation. These phenomena change the spatial location of the chemical reaction during the course of extraction, resulting in a transient moving boundary problem. The orthogonal collocation method was used to transform the partial differential equations into an ordinary differential equation set that was solved by an implicit numerical routine. The model was found to be numerically stable and reliable in predicting the behaviour of zinc extraction with acidic extractant for long residence times.

  13. Modelling of dynamic equivalents in electric power grids

    International Nuclear Information System (INIS)

    Craciun, Diana Iuliana

    2010-01-01

    In a first part, this research thesis proposes a description of the context and new constraints of electric grids: architecture, decentralized production with the impact of distributed energy resource systems, dynamic simulation, and interest of equivalent models. Then, the author discusses the modelling of the different components of electric grids: synchronous and asynchronous machines, distributed energy resource with power electronic interface, loading models. She addresses the techniques of reduction of electric grid models: conventional reduction methods, dynamic equivalence methods using non linear approaches or evolutionary algorithm-based methods of assessment of parameters. This last approach is then developed and implemented, and a new method of computation of dynamic equivalents is described

  14. Demand, credit and macroeconomic dynamics: A microsimulation model

    NARCIS (Netherlands)

    Meijers, H.H.M.; Nomaler, Z.O.; Verspagen, B.

    2014-01-01

    We develop a microsimulation model for the macroeconomic business cycle. Our model is based on three main ideas: (i) we want to specify how macroeconomic coordination is achieved without a dominating influence of price mechanisms, (ii) we want to incorporate the stock-flow-consistent approach that

  15. Myeloma Cell Dynamics in Response to Treatment Supports a Model of Hierarchical Differentiation and Clonal Evolution.

    Science.gov (United States)

    Tang, Min; Zhao, Rui; van de Velde, Helgi; Tross, Jennifer G; Mitsiades, Constantine; Viselli, Suzanne; Neuwirth, Rachel; Esseltine, Dixie-Lee; Anderson, Kenneth; Ghobrial, Irene M; San Miguel, Jesús F; Richardson, Paul G; Tomasson, Michael H; Michor, Franziska

    2016-08-15

    Since the pioneering work of Salmon and Durie, quantitative measures of tumor burden in multiple myeloma have been used to make clinical predictions and model tumor growth. However, such quantitative analyses have not yet been performed on large datasets from trials using modern chemotherapy regimens. We analyzed a large set of tumor response data from three randomized controlled trials of bortezomib-based chemotherapy regimens (total sample size n = 1,469 patients) to establish and validate a novel mathematical model of multiple myeloma cell dynamics. Treatment dynamics in newly diagnosed patients were most consistent with a model postulating two tumor cell subpopulations, "progenitor cells" and "differentiated cells." Differential treatment responses were observed with significant tumoricidal effects on differentiated cells and less clear effects on progenitor cells. We validated this model using a second trial of newly diagnosed patients and a third trial of refractory patients. When applying our model to data of relapsed patients, we found that a hybrid model incorporating both a differentiation hierarchy and clonal evolution best explains the response patterns. The clinical data, together with mathematical modeling, suggest that bortezomib-based therapy exerts a selection pressure on myeloma cells that can shape the disease phenotype, thereby generating further inter-patient variability. This model may be a useful tool for improving our understanding of disease biology and the response to chemotherapy regimens. Clin Cancer Res; 22(16); 4206-14. ©2016 AACR. ©2016 American Association for Cancer Research.

  16. DYNAMIC LOAD DAMPER MODELING

    Directory of Open Access Journals (Sweden)

    Loktev Aleksey Alekseevich

    2013-01-01

    Full Text Available The authors present their findings associated with their modeling of a dynamic load damper. According to the authors, the damper is to be installed onto a structure or its element that may be exposed to impact, vibration or any other dynamic loading. The damper is composed of paralleled or consecutively connected viscous and elastic elements. The authors study the influence of viscosity and elasticity parameters of the damper produced onto the regular displacement of points of the structure to be protected and onto the regular acceleration transmitted immediately from the damper to the elements positioned below it.

  17. Dynamic intersectoral models with power-law memory

    Science.gov (United States)

    Tarasova, Valentina V.; Tarasov, Vasily E.

    2018-01-01

    Intersectoral dynamic models with power-law memory are proposed. The equations of open and closed intersectoral models, in which the memory effects are described by the Caputo derivatives of non-integer orders, are derived. We suggest solutions of these equations, which have the form of linear combinations of the Mittag-Leffler functions and which are characterized by different effective growth rates. Examples of intersectoral dynamics with power-law memory are suggested for two sectoral cases. We formulate two principles of intersectoral dynamics with memory: the principle of changing of technological growth rates and the principle of domination change. It has been shown that in the input-output economic dynamics the effects of fading memory can change the economic growth rate and dominant behavior of economic sectors.

  18. Dynamical properties of the Rabi model

    International Nuclear Information System (INIS)

    Hu, Binglu; Zhou, Huili; Chen, Shujie; Xianlong, Gao; Wang, Kelin

    2017-01-01

    We study the dynamical properties of the quantum Rabi model using a systematic expansion method. Based on the observation that the parity symmetry of the Rabi model is kept during evolution of the states, we decompose the initial state and the time-dependent one into positive and negative parity parts expanded by superposition of the coherent states. The evolutions of the corresponding positive and the negative parities are obtained, in which the expansion coefficients in the dynamical equations are known from the derived recurrence relation. (paper)

  19. Agent Based Modeling on Organizational Dynamics of Terrorist Network

    OpenAIRE

    Bo Li; Duoyong Sun; Renqi Zhu; Ze Li

    2015-01-01

    Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model ...

  20. Particle hopping vs. fluid-dynamical models for traffic flow

    Energy Technology Data Exchange (ETDEWEB)

    Nagel, K.

    1995-12-31

    Although particle hopping models have been introduced into traffic science in the 19509, their systematic use has only started recently. Two reasons for this are, that they are advantageous on modem computers, and that recent theoretical developments allow analytical understanding of their properties and therefore more confidence for their use. In principle, particle hopping models fit between microscopic models for driving and fluiddynamical models for traffic flow. In this sense, they also help closing the conceptual gap between these two. This paper shows connections between particle hopping models and traffic flow theory. It shows that the hydrodynamical limits of certain particle hopping models correspond to the Lighthill-Whitham theory for traffic flow, and that only slightly more complex particle hopping models produce already the correct traffic jam dynamics, consistent with recent fluid-dynamical models for traffic flow. By doing so, this paper establishes that, on the macroscopic level, particle hopping models are at least as good as fluid-dynamical models. Yet, particle hopping models have at least two advantages over fluid-dynamical models: they straightforwardly allow microscopic simulations, and they include stochasticity.

  1. Dynamic Modelling with "MLE-Energy Dynamic" for Primary School

    Science.gov (United States)

    Giliberti, Enrico; Corni, Federico

    During the recent years simulation and modelling are growing instances in science education. In primary school, however, the main use of software is the simulation, due to the lack of modelling software tools specially designed to fit/accomplish the needs of primary education. In particular primary school teachers need to use simulation in a framework that is both consistent and simple enough to be understandable by children [2]. One of the possible area to approach modelling is about the construction of the concept of energy, in particular for what concerns the relations among substance, potential, power [3]. Following the previous initial research results with this approach [2], and with the static version of the software MLE Energy [1], we suggest the design and the experimentation of a dynamic modelling software—MLE dynamic-capable to represent dynamically the relations occurring when two substance-like quantities exchange energy, modifying their potential. By means of this software the user can graphically choose the dependent and independent variables and leave the other parameters fixed. The software has been initially evaluated, during a course of science education with a group of primary school teachers-to-be, to test the ability of the software to improve teachers' way of thinking in terms of substance-like quantities and their effects (graphical representation of the extensive, intensive variables and their mutual relations); moreover, the software has been tested with a group of primary school teachers, asking their opinion about the software didactical relevance in the class work.

  2. Hybrid photovoltaic–thermal solar collectors dynamic modeling

    International Nuclear Information System (INIS)

    Amrizal, N.; Chemisana, D.; Rosell, J.I.

    2013-01-01

    Highlights: ► A hybrid photovoltaic/thermal dynamic model is presented. ► The model, once calibrated, can predict the power output for any set of climate data. ► The physical electrical model includes explicitly thermal and irradiance dependences. ► The results agree with those obtained through steady-state characterization. ► The model approaches the junction cell temperature through the system energy balance. -- Abstract: A hybrid photovoltaic/thermal transient model has been developed and validated experimentally. The methodology extends the quasi-dynamic thermal model stated in the EN 12975 in order to involve the electrical performance and consider the dynamic behavior minimizing constraints when characterizing the collector. A backward moving average filtering procedure has been applied to improve the model response for variable working conditions. Concerning the electrical part, the model includes the thermal and radiation dependences in its variables. The results revealed that the characteristic parameters included in the model agree reasonably well with the experimental values obtained from the standard steady-state and IV characteristic curve measurements. After a calibration process, the model is a suitable tool to predict the thermal and electrical performance of a hybrid solar collector, for a specific weather data set.

  3. System Dynamics Modeling of Multipurpose Reservoir Operation

    Directory of Open Access Journals (Sweden)

    Ebrahim Momeni

    2006-03-01

    Full Text Available System dynamics, a feedback – based object – oriented simulation approach, not only represents complex dynamic systemic systems in a realistic way but also allows the involvement of end users in model development to increase their confidence in modeling process. The increased speed of model development, the possibility of group model development, the effective communication of model results, and the trust developed in the model due to user participation are the main strengths of this approach. The ease of model modification in response to changes in the system and the ability to perform sensitivity analysis make this approach more attractive compared with systems analysis techniques for modeling water management systems. In this study, a system dynamics model was developed for the Zayandehrud basin in central Iran. This model contains river basin, dam reservoir, plains, irrigation systems, and groundwater. Current operation rule is conjunctive use of ground and surface water. Allocation factor for each irrigation system is computed based on the feedback from groundwater storage in its zone. Deficit water is extracted from groundwater.The results show that applying better rules can not only satisfy all demands such as Gawkhuni swamp environmental demand, but it can also  prevent groundwater level drawdown in future.

  4. Cluster dynamics models of irradiation damage accumulation in ferritic iron. II. Effects of reaction dimensionality

    Energy Technology Data Exchange (ETDEWEB)

    Kohnert, Aaron A.; Wirth, Brian D. [University of Tennessee, Knoxville, Tennessee 37996-2300 (United States)

    2015-04-21

    The black dot damage features which develop in iron at low temperatures exhibit significant mobility during in situ irradiation experiments via a series of discrete, intermittent, long range hops. By incorporating this mobility into cluster dynamics models, the temperature dependence of such damage structures can be explained with a surprising degree of accuracy. Such motion, however, is one dimensional in nature. This aspect of the physics has not been fully considered in prior models. This article describes one dimensional reaction kinetics in the context of cluster dynamics and applies them to the black dot problem. This allows both a more detailed description of the mechanisms by which defects execute irradiation-induced hops while allowing a full examination of the importance of kinetic assumptions in accurately assessing the development of this irradiation microstructure. Results are presented to demonstrate whether one dimensional diffusion alters the dependence of the defect population on factors such as temperature and defect hop length. Finally, the size of interstitial loops that develop is shown to depend on the extent of the reaction volumes between interstitial clusters, as well as the dimensionality of these interactions.

  5. Generative Models of Conformational Dynamics

    OpenAIRE

    Langmead, Christopher James

    2014-01-01

    Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term ‘generative’ refers to a...

  6. Modelling and dynamic simulation of processes with 'MATLAB'. An application of a natural gas installation in a power plant

    Energy Technology Data Exchange (ETDEWEB)

    Gonzalez-Bustamante, J.A.; Sala, J.M.; Flores, I. [Escuela Superior de Ingenieros Industriales de Bilbao, Universidad del Pais Vasco, Alameda de Urquijo, s/n 48013 Bilbao (Bizkaia) (Spain); Lopez-Gonzalez, L.M. [Escuela Tecnica Superior de Ingenieria Industrial, Universidad de La Rioja, C/ Luis de Ulloa, 20. E 26004 Logrono (La Rioja) (Spain); Miguez, J.L. [Universidad de Vigo, Escuela Tecnica Superior de Ingenieros Industriales, C/Lagoas-Marcosende, s/n 36200 Vigo (Pontevedra) (Spain)

    2007-07-15

    In this paper, it is proposed to incorporate the analysis of the dynamic performance of the process into the design and engineering stage of projects as a means of analysing and resolving this type of problem. The following contributions are made with this objective in mind:(a)The barriers in the way of dynamic analysis are identified. (b)Software tools which make dynamic analysis accessible during the design and engineering phase of the project are proposed. To achieve this goal, modelling and mathematical simulation are used, with the following features: circle strict modelling of mass, momentum and energy conservation equations as well as state equations, and circle utilisation of the 'Matlab-Simulink' package as the base-software tool. (c)The procedure and tool proposed for dynamic analysis during the design phase should enable these studies to be carried out at a reasonable cost and time for regular industrial projects, and not just for large research projects or nuclear power plants. To complete this paper, we apply our method to a natural gas installation in a power plant. The model is applied to study the transients of a natural gas supply line to a steam-electric power plant. The results of the model have been validated with the actual data on the boiler trip obtained from the distributed control system of a steam-electric power plant. (author)

  7. Boltzmann-Langevin equation, dynamical instability and multifragmentation

    International Nuclear Information System (INIS)

    Feng-Shou Zhang

    1993-02-01

    By using simulations of the Boltzmann-Langevin equation which incorporates dynamical fluctuations beyond usual transport theories and by coupling it with a coalescence model, we obtain information on multifragmentation in heavy-ion collisions. From a calculation of the 40 Ca + 40 Ca system, we recover some trends of recent multifragmentation data

  8. Health Status and Health Dynamics in an Empirical Model of Expected Longevity*

    Science.gov (United States)

    Benítez-Silva, Hugo; Ni, Huan

    2010-01-01

    Expected longevity is an important factor influencing older individuals’ decisions such as consumption, savings, purchase of life insurance and annuities, claiming of Social Security benefits, and labor supply. It has also been shown to be a good predictor of actual longevity, which in turn is highly correlated with health status. A relatively new literature on health investments under uncertainty, which builds upon the seminal work by Grossman (1972), has directly linked longevity with characteristics, behaviors, and decisions by utility maximizing agents. Our empirical model can be understood within that theoretical framework as estimating a production function of longevity. Using longitudinal data from the Health and Retirement Study, we directly incorporate health dynamics in explaining the variation in expected longevities, and compare two alternative measures of health dynamics: the self-reported health change, and the computed health change based on self-reports of health status. In 38% of the reports in our sample, computed health changes are inconsistent with the direct report on health changes over time. And another 15% of the sample can suffer from information losses if computed changes are used to assess changes in actual health. These potentially serious problems raise doubts regarding the use and interpretation of the computed health changes and even the lagged measures of self-reported health as controls for health dynamics in a variety of empirical settings. Our empirical results, controlling for both subjective and objective measures of health status and unobserved heterogeneity in reporting, suggest that self-reported health changes are a preferred measure of health dynamics. PMID:18187217

  9. Extending dynamic segmentation with lead generation : A latent class Markov analysis of financial product portfolios

    NARCIS (Netherlands)

    Paas, L.J.; Bijmolt, T.H.A.; Vermunt, J.K.

    2004-01-01

    A recent development in marketing research concerns the incorporation of dynamics in consumer segmentation.This paper extends the latent class Markov model, a suitable technique for conducting dynamic segmentation, in order to facilitate lead generation.We demonstrate the application of the latent

  10. Molecular dynamics study of amorphous pocket formation in Si at low energies and its application to improve binary collision models

    International Nuclear Information System (INIS)

    Santos, Ivan; Marques, Luis A.; Pelaz, Lourdes; Lopez, Pedro

    2007-01-01

    In this paper, we present classical molecular dynamics results about the formation of amorphous pockets in silicon for energy transfers below the displacement threshold. While in binary collision simulations ions with different masses generate the same number of Frenkel pairs for the same deposited nuclear energy, in molecular dynamics simulations the amount of damage and its complexity increase with ion mass. We demonstrate that low-energy transfers to target atoms are able to generate complex damage structures. We have determined the conditions that have to be fulfilled to produce amorphous pockets, showing that the order-disorder transition depends on the particular competition between melting and heat diffusion processes. We have incorporated these molecular dynamics results in an improved binary collision model that is able to provide a good description of damage with a very low computational cost

  11. Selecting a Dynamic Simulation Modeling Method for Health Care Delivery Research—Part 2: Report of the ISPOR Dynamic Simulation Modeling Emerging Good Practices Task Force

    NARCIS (Netherlands)

    Marshall, Deborah A.; Burgos-Liz, Lina; IJzerman, Maarten Joost; Crown, William; Padula, William V.; Wong, Peter K.; Pasupathy, Kalyan S.; Higashi, Mitchell K.; Osgood, Nathaniel D.

    2015-01-01

    In a previous report, the ISPOR Task Force on Dynamic Simulation Modeling Applications in Health Care Delivery Research Emerging Good Practices introduced the fundamentals of dynamic simulation modeling and identified the types of health care delivery problems for which dynamic simulation modeling

  12. A system dynamic modeling approach for evaluating municipal solid waste generation, landfill capacity and related cost management issues

    International Nuclear Information System (INIS)

    Kollikkathara, Naushad; Feng Huan; Yu Danlin

    2010-01-01

    As planning for sustainable municipal solid waste management has to address several inter-connected issues such as landfill capacity, environmental impacts and financial expenditure, it becomes increasingly necessary to understand the dynamic nature of their interactions. A system dynamics approach designed here attempts to address some of these issues by fitting a model framework for Newark urban region in the US, and running a forecast simulation. The dynamic system developed in this study incorporates the complexity of the waste generation and management process to some extent which is achieved through a combination of simpler sub-processes that are linked together to form a whole. The impact of decision options on the generation of waste in the city, on the remaining landfill capacity of the state, and on the economic cost or benefit actualized by different waste processing options are explored through this approach, providing valuable insights into the urban waste-management process.

  13. A dynamic, climate-driven model of Rift Valley fever

    Directory of Open Access Journals (Sweden)

    Joseph Leedale

    2016-03-01

    Full Text Available Outbreaks of Rift Valley fever (RVF in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

  14. A Stochastic Model for Malaria Transmission Dynamics

    Directory of Open Access Journals (Sweden)

    Rachel Waema Mbogo

    2018-01-01

    Full Text Available Malaria is one of the three most dangerous infectious diseases worldwide (along with HIV/AIDS and tuberculosis. In this paper we compare the disease dynamics of the deterministic and stochastic models in order to determine the effect of randomness in malaria transmission dynamics. Relationships between the basic reproduction number for malaria transmission dynamics between humans and mosquitoes and the extinction thresholds of corresponding continuous-time Markov chain models are derived under certain assumptions. The stochastic model is formulated using the continuous-time discrete state Galton-Watson branching process (CTDSGWbp. The reproduction number of deterministic models is an essential quantity to predict whether an epidemic will spread or die out. Thresholds for disease extinction from stochastic models contribute crucial knowledge on disease control and elimination and mitigation of infectious diseases. Analytical and numerical results show some significant differences in model predictions between the stochastic and deterministic models. In particular, we find that malaria outbreak is more likely if the disease is introduced by infected mosquitoes as opposed to infected humans. These insights demonstrate the importance of a policy or intervention focusing on controlling the infected mosquito population if the control of malaria is to be realized.

  15. Dynamic root uptake model for neutral lipophilic organics

    DEFF Research Database (Denmark)

    Trapp, Stefan

    2002-01-01

    and output to stem with the transpiration stream plus first-order metabolism and dilution by exponential growth. For chemicals with low or intermediate lipophilicity (log Kow , 2), there was no relevant difference between dynamic model and equilibrium approach. For lipophilic compounds, the dynamic model...

  16. Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts.

    Science.gov (United States)

    Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A

    2014-08-01

    Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate

  17. Computational fluid dynamics modeling of bun baking process under different oven load conditions.

    Science.gov (United States)

    Tank, A; Chhanwal, N; Indrani, D; Anandharamakrishnan, C

    2014-09-01

    A computational fluid dynamics (CFD) model was developed to study the temperature profile of the bun during baking process. Evaporation-condensation mechanism and effect of the latent heat during phase change of water was incorporated in this model to represent actual bun baking process. Simulation results were validated with experimental measurements of bun temperature at two different positions. Baking process is completed within 20 min, after the temperature of crumb become stable at 98 °C. Further, this study was extended to investigate the effect of partially (two baking trays) loaded and fully loaded (eight baking trays) oven on temperature profile of bun. Velocity and temperature profile differs in partially loaded and fully loaded oven. Bun placed in top rack showed rapid baking while bun placed in bottom rack showed slower baking due to uneven temperature distribution in the oven. Hence, placement of bun inside the oven affects temperature of bun and consequently, the quality of the product.

  18. Concepts for dynamic modelling of energy-related flows in manufacturing

    International Nuclear Information System (INIS)

    Wright, A.J.; Oates, M.R.; Greenough, R.

    2013-01-01

    Highlights: ► Modelling of the thermal flows in factories and processes is usually separate. ► We propose a set of key features for an integrated thermal model. ► Such models can be used to improve the efficiency of manufacturing processes. - Abstract: Industry uses around one third of the world’s energy, and accounts for about 40% of global carbon dioxide emissions. There is increasing economic and social pressure to improve efficiency and create closed-loop industrial systems, in which energy efficiency plays a key role. This paper describes some of the key concepts involved in modelling the energy flows in manufacturing, both for the building services and the industrial processes. Detailed dynamic energy simulation of buildings is well established and routinely used, working on a time series basis – but current tools are inadequate to model the energy flows of many industrial processes. There are also well-established models of manufacturing flows, used to optimise production efficiency, but typically not modelling energy, and usually representing production and material flows as event-driven processes. The THERM project has developed new software tools to model energy-related and other utility flows in manufacturing, incorporating these into existing thermal models of factory buildings. This makes it possible to map out the whole energy system, and hence to test efficiency measures, to understand the effect of processes on building energy use, to investigate recycling of heat or cooling into other processes or building conditioning, and so on. The paper describes some of the key concepts and modelling approaches involved in developing these models, and gives examples of some real processes modelled in factories. It concludes that such models are entirely feasible and potentially very useful, although to develop a tool which comprehensively models both energy and manufacturing flows would be a major undertaking

  19. Transient dynamic and modeling parameter sensitivity analysis of 1D solid oxide fuel cell model

    International Nuclear Information System (INIS)

    Huangfu, Yigeng; Gao, Fei; Abbas-Turki, Abdeljalil; Bouquain, David; Miraoui, Abdellatif

    2013-01-01

    Highlights: • A multiphysics, 1D, dynamic SOFC model is developed. • The presented model is validated experimentally in eight different operating conditions. • Electrochemical and thermal dynamic transient time expressions are given in explicit forms. • Parameter sensitivity is discussed for different semi-empirical parameters in the model. - Abstract: In this paper, a multiphysics solid oxide fuel cell (SOFC) dynamic model is developed by using a one dimensional (1D) modeling approach. The dynamic effects of double layer capacitance on the electrochemical domain and the dynamic effect of thermal capacity on thermal domain are thoroughly considered. The 1D approach allows the model to predict the non-uniform distributions of current density, gas pressure and temperature in SOFC during its operation. The developed model has been experimentally validated, under different conditions of temperature and gas pressure. Based on the proposed model, the explicit time constant expressions for different dynamic phenomena in SOFC have been given and discussed in detail. A parameters sensitivity study has also been performed and discussed by using statistical Multi Parameter Sensitivity Analysis (MPSA) method, in order to investigate the impact of parameters on the modeling accuracy

  20. Large-Scale Modelling of the Environmentally-Driven Population Dynamics of Temperate Aedes albopictus (Skuse.

    Directory of Open Access Journals (Sweden)

    Kamil Erguler

    Full Text Available The Asian tiger mosquito, Aedes albopictus, is a highly invasive vector species. It is a proven vector of dengue and chikungunya viruses, with the potential to host a further 24 arboviruses. It has recently expanded its geographical range, threatening many countries in the Middle East, Mediterranean, Europe and North America. Here, we investigate the theoretical limitations of its range expansion by developing an environmentally-driven mathematical model of its population dynamics. We focus on the temperate strain of Ae. albopictus and compile a comprehensive literature-based database of physiological parameters. As a novel approach, we link its population dynamics to globally-available environmental datasets by performing inference on all parameters. We adopt a Bayesian approach using experimental data as prior knowledge and the surveillance dataset of Emilia-Romagna, Italy, as evidence. The model accounts for temperature, precipitation, human population density and photoperiod as the main environmental drivers, and, in addition, incorporates the mechanism of diapause and a simple breeding site model. The model demonstrates high predictive skill over the reference region and beyond, confirming most of the current reports of vector presence in Europe. One of the main hypotheses derived from the model is the survival of Ae. albopictus populations through harsh winter conditions. The model, constrained by the environmental datasets, requires that either diapausing eggs or adult vectors have increased cold resistance. The model also suggests that temperature and photoperiod control diapause initiation and termination differentially. We demonstrate that it is possible to account for unobserved properties and constraints, such as differences between laboratory and field conditions, to derive reliable inferences on the environmental dependence of Ae. albopictus populations.

  1. Developing a Dynamic Pharmacophore Model for HIV-1 Integrase

    International Nuclear Information System (INIS)

    Carlson, Heather A.; Masukawa, Keven M.; Rubins, Kathleen; Bushman, Frederic; Jorgensen, William L.; Lins, Roberto; Briggs, James; Mccammon, Andy

    2000-01-01

    We present the first receptor-based pharmacophore model for HIV-1 integrase. The development of ''dynamic'' pharmacophore models is a new method that accounts for the inherent flexibility of the active site and aims to reduce the entropic penalties associated with binding a ligand. Furthermore, this new drug discovery method overcomes the limitation of an incomplete crystal structure of the target protein. A molecular dynamics (MD) simulation describes the flexibility of the uncomplexed protein. Many conformational models of the protein are saved from the MD simulations and used in a series of multi-unit search for interacting conformers (MUSIC) simulations. MUSIC is a multiple-copy minimization method, available in the BOSS program; it is used to determine binding regions for probe molecules containing functional groups that complement the active site. All protein conformations from the MD are overlaid, and conserved binding regions for the probe molecules are identified. Those conserved binding regions define the dynamic pharmacophore model. Here, the dynamic model is compared to known inhibitors of the integrase as well as a three-point, ligand-based pharmacophore model from the literature. Also, a ''static'' pharmacophore model was determined in the standard fashion, using a single crystal structure. Inhibitors thought to bind in the active site of HIV-1 integrase fit the dynamic model but not the static model. Finally, we have identified a set of compounds from the Available Chemicals Directory that fit the dynamic pharmacophore model, and experimental testing of the compounds has confirmed several new inhibitors

  2. A ¤nonparametric dynamic additive regression model for longitudinal data

    DEFF Research Database (Denmark)

    Martinussen, T.; Scheike, T. H.

    2000-01-01

    dynamic linear models, estimating equations, least squares, longitudinal data, nonparametric methods, partly conditional mean models, time-varying-coefficient models......dynamic linear models, estimating equations, least squares, longitudinal data, nonparametric methods, partly conditional mean models, time-varying-coefficient models...

  3. A stochastic phase-field model determined from molecular dynamics

    KAUST Repository

    von Schwerin, Erik

    2010-03-17

    The dynamics of dendritic growth of a crystal in an undercooled melt is determined by macroscopic diffusion-convection of heat and by capillary forces acting on the nanometer scale of the solid-liquid interface width. Its modelling is useful for instance in processing techniques based on casting. The phase-field method is widely used to study evolution of such microstructural phase transformations on a continuum level; it couples the energy equation to a phenomenological Allen-Cahn/Ginzburg-Landau equation modelling the dynamics of an order parameter determining the solid and liquid phases, including also stochastic fluctuations to obtain the qualitatively correct result of dendritic side branching. This work presents a method to determine stochastic phase-field models from atomistic formulations by coarse-graining molecular dynamics. It has three steps: (1) a precise quantitative atomistic definition of the phase-field variable, based on the local potential energy; (2) derivation of its coarse-grained dynamics model, from microscopic Smoluchowski molecular dynamics (that is Brownian or over damped Langevin dynamics); and (3) numerical computation of the coarse-grained model functions. The coarse-grained model approximates Gibbs ensemble averages of the atomistic phase-field, by choosing coarse-grained drift and diffusion functions that minimize the approximation error of observables in this ensemble average. © EDP Sciences, SMAI, 2010.

  4. A stochastic phase-field model determined from molecular dynamics

    KAUST Repository

    von Schwerin, Erik; Szepessy, Anders

    2010-01-01

    The dynamics of dendritic growth of a crystal in an undercooled melt is determined by macroscopic diffusion-convection of heat and by capillary forces acting on the nanometer scale of the solid-liquid interface width. Its modelling is useful for instance in processing techniques based on casting. The phase-field method is widely used to study evolution of such microstructural phase transformations on a continuum level; it couples the energy equation to a phenomenological Allen-Cahn/Ginzburg-Landau equation modelling the dynamics of an order parameter determining the solid and liquid phases, including also stochastic fluctuations to obtain the qualitatively correct result of dendritic side branching. This work presents a method to determine stochastic phase-field models from atomistic formulations by coarse-graining molecular dynamics. It has three steps: (1) a precise quantitative atomistic definition of the phase-field variable, based on the local potential energy; (2) derivation of its coarse-grained dynamics model, from microscopic Smoluchowski molecular dynamics (that is Brownian or over damped Langevin dynamics); and (3) numerical computation of the coarse-grained model functions. The coarse-grained model approximates Gibbs ensemble averages of the atomistic phase-field, by choosing coarse-grained drift and diffusion functions that minimize the approximation error of observables in this ensemble average. © EDP Sciences, SMAI, 2010.

  5. Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

    International Nuclear Information System (INIS)

    Cai, X.; Zhang, X.

    2016-01-01

    Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

  6. Instantaneous Metabolic Cost of Walking: Joint-Space Dynamic Model with Subject-Specific Heat Rate.

    Directory of Open Access Journals (Sweden)

    Dustyn Roberts

    Full Text Available A subject-specific model of instantaneous cost of transport (ICOT is introduced from the joint-space formulation of metabolic energy expenditure using the laws of thermodynamics and the principles of multibody system dynamics. Work and heat are formulated in generalized coordinates as functions of joint kinematic and dynamic variables. Generalized heat rates mapped from muscle energetics are estimated from experimental walking metabolic data for the whole body, including upper-body and bilateral data synchronization. Identified subject-specific energetic parameters-mass, height, (estimated maximum oxygen uptake, and (estimated maximum joint torques-are incorporated into the heat rate, as opposed to the traditional in vitro and subject-invariant muscle parameters. The total model metabolic energy expenditure values are within 5.7 ± 4.6% error of the measured values with strong (R2 > 0.90 inter- and intra-subject correlations. The model reliably predicts the characteristic convexity and magnitudes (0.326-0.348 of the experimental total COT (0.311-0.358 across different subjects and speeds. The ICOT as a function of time provides insights into gait energetic causes and effects (e.g., normalized comparison and sensitivity with respect to walking speed and phase-specific COT, which are unavailable from conventional metabolic measurements or muscle models. Using the joint-space variables from commonly measured or simulated data, the models enable real-time and phase-specific evaluations of transient or non-periodic general tasks that use a range of (aerobic energy pathway similar to that of steady-state walking.

  7. Modeling Common-Sense Decisions

    Science.gov (United States)

    Zak, Michail

    This paper presents a methodology for efficient synthesis of dynamical model simulating a common-sense decision making process. The approach is based upon the extension of the physics' First Principles that includes behavior of living systems. The new architecture consists of motor dynamics simulating actual behavior of the object, and mental dynamics representing evolution of the corresponding knowledge-base and incorporating it in the form of information flows into the motor dynamics. The autonomy of the decision making process is achieved by a feedback from mental to motor dynamics. This feedback replaces unavailable external information by an internal knowledgebase stored in the mental model in the form of probability distributions.

  8. Further Results on Dynamic Additive Hazard Rate Model

    Directory of Open Access Journals (Sweden)

    Zhengcheng Zhang

    2014-01-01

    Full Text Available In the past, the proportional and additive hazard rate models have been investigated in the works. Nanda and Das (2011 introduced and studied the dynamic proportional (reversed hazard rate model. In this paper we study the dynamic additive hazard rate model, and investigate its aging properties for different aging classes. The closure of the model under some stochastic orders has also been investigated. Some examples are also given to illustrate different aging properties and stochastic comparisons of the model.

  9. Training the Next Generation of Scientists: System Dynamics Modeling of Chagas Disease (American Trypanosomiasis) transmission.

    Science.gov (United States)

    Goff, P.; Hulse, A.; Harder, H. R.; Pierce, L. A.; Rizzo, D.; Hanley, J.; Orantes, L.; Stevens, L.; Justi, S.; Monroy, C.

    2015-12-01

    A computational simulation has been designed as an investigative case study by high school students to introduce system dynamics modeling into high school curriculum. This case study approach leads users through the forensics necessary to diagnose an unknown disease in a Central American village. This disease, Chagas, is endemic to 21 Latin American countries. The CDC estimates that of the 110 million people living in areas with the disease, 8 million are infected, with as many as 300,000 US cases. Chagas is caused by the protozoan parasite, Trypanosoma cruzi, and is spread via blood feeding insect (vectors), that feed on vertebrates and live in crevasses in the walls and roofs of adobe homes. One-third of the infected people will develop chronic Chagas who are asymptomatic for years before their heart or GI tract become enlarged resulting in death. The case study has three parts. Students play the role of WHO field investigators and work collaboratively to: 1) use genetics to identify the host(s) and vector of the disease 2) use a STELLA™ SIR (Susceptible, Infected, Recovered) system dynamics model to study Chagas at the village scale and 3) develop management strategies. The simulations identify mitigation strategies known as Ecohealth Interventions (e.g., home improvements using local materials) to help stakeholders test and compare multiple optima. High school students collaborated with researchers from the University of Vermont, Loyola University and Universidad de San Carlos, Guatemala, working in labs, interviewing researchers, and incorporating mulitple field data as part of a NSF-funded multiyear grant. The model displays stable equilibria of hosts, vectors, and disease-states. Sensitivity analyses show measures of household condition and presence of vertebrates were significant leverage points, supporting other findings by the University research team. The village-scale model explores multiple solutions to disease mitigation for the purpose of producing

  10. Modeling Cancer Cell Growth Dynamics In vitro in Response to Antimitotic Drug Treatment

    Directory of Open Access Journals (Sweden)

    Alexander Lorz

    2017-08-01

    Full Text Available Investigating the role of intrinsic cell heterogeneity emerging from variations in cell-cycle parameters and apoptosis is a crucial step toward better informing drug administration. Antimitotic agents, widely used in chemotherapy, target exclusively proliferative cells and commonly induce a prolonged mitotic arrest followed by cell death via apoptosis. In this paper, we developed a physiologically motivated mathematical framework for describing cancer cell growth dynamics that incorporates the intrinsic heterogeneity in the time individual cells spend in the cell-cycle and apoptosis process. More precisely, our model comprises two age-structured partial differential equations for the proliferative and apoptotic cell compartments and one ordinary differential equation for the quiescent compartment. To reflect the intrinsic cell heterogeneity that governs the growth dynamics, proliferative and apoptotic cells are structured in “age,” i.e., the amount of time remaining to be spent in each respective compartment. In our model, we considered an antimitotic drug whose effect on the cellular dynamics is to induce mitotic arrest, extending the average cell-cycle length. The prolonged mitotic arrest induced by the drug can trigger apoptosis if the time a cell will spend in the cell cycle is greater than the mitotic arrest threshold. We studied the drug’s effect on the long-term cancer cell growth dynamics using different durations of prolonged mitotic arrest induced by the drug. Our numerical simulations suggest that at confluence and in the absence of the drug, quiescence is the long-term asymptotic behavior emerging from the cancer cell growth dynamics. This pattern is maintained in the presence of small increases in the average cell-cycle length. However, intermediate increases in cell-cycle length markedly decrease the total number of cells and can drive the cancer population to extinction. Intriguingly, a large

  11. Modeling Cancer Cell Growth Dynamics In vitro in Response to Antimitotic Drug Treatment

    Science.gov (United States)

    Lorz, Alexander; Botesteanu, Dana-Adriana; Levy, Doron

    2017-01-01

    Investigating the role of intrinsic cell heterogeneity emerging from variations in cell-cycle parameters and apoptosis is a crucial step toward better informing drug administration. Antimitotic agents, widely used in chemotherapy, target exclusively proliferative cells and commonly induce a prolonged mitotic arrest followed by cell death via apoptosis. In this paper, we developed a physiologically motivated mathematical framework for describing cancer cell growth dynamics that incorporates the intrinsic heterogeneity in the time individual cells spend in the cell-cycle and apoptosis process. More precisely, our model comprises two age-structured partial differential equations for the proliferative and apoptotic cell compartments and one ordinary differential equation for the quiescent compartment. To reflect the intrinsic cell heterogeneity that governs the growth dynamics, proliferative and apoptotic cells are structured in “age,” i.e., the amount of time remaining to be spent in each respective compartment. In our model, we considered an antimitotic drug whose effect on the cellular dynamics is to induce mitotic arrest, extending the average cell-cycle length. The prolonged mitotic arrest induced by the drug can trigger apoptosis if the time a cell will spend in the cell cycle is greater than the mitotic arrest threshold. We studied the drug’s effect on the long-term cancer cell growth dynamics using different durations of prolonged mitotic arrest induced by the drug. Our numerical simulations suggest that at confluence and in the absence of the drug, quiescence is the long-term asymptotic behavior emerging from the cancer cell growth dynamics. This pattern is maintained in the presence of small increases in the average cell-cycle length. However, intermediate increases in cell-cycle length markedly decrease the total number of cells and can drive the cancer population to extinction. Intriguingly, a large “switch-on/switch-off” increase in the average

  12. Modeling Cancer Cell Growth Dynamics In vitro in Response to Antimitotic Drug Treatment

    KAUST Repository

    Lorz, Alexander; Botesteanu, Dana-Adriana; Levy, Doron

    2017-01-01

    Investigating the role of intrinsic cell heterogeneity emerging from variations in cell-cycle parameters and apoptosis is a crucial step toward better informing drug administration. Antimitotic agents, widely used in chemotherapy, target exclusively proliferative cells and commonly induce a prolonged mitotic arrest followed by cell death via apoptosis. In this paper, we developed a physiologically motivated mathematical framework for describing cancer cell growth dynamics that incorporates the intrinsic heterogeneity in the time individual cells spend in the cell-cycle and apoptosis process. More precisely, our model comprises two age-structured partial differential equations for the proliferative and apoptotic cell compartments and one ordinary differential equation for the quiescent compartment. To reflect the intrinsic cell heterogeneity that governs the growth dynamics, proliferative and apoptotic cells are structured in “age,” i.e., the amount of time remaining to be spent in each respective compartment. In our model, we considered an antimitotic drug whose effect on the cellular dynamics is to induce mitotic arrest, extending the average cell-cycle length. The prolonged mitotic arrest induced by the drug can trigger apoptosis if the time a cell will spend in the cell cycle is greater than the mitotic arrest threshold. We studied the drug's effect on the long-term cancer cell growth dynamics using different durations of prolonged mitotic arrest induced by the drug. Our numerical simulations suggest that at confluence and in the absence of the drug, quiescence is the long-term asymptotic behavior emerging from the cancer cell growth dynamics. This pattern is maintained in the presence of small increases in the average cell-cycle length. However, intermediate increases in cell-cycle length markedly decrease the total number of cells and can drive the cancer population to extinction. Intriguingly, a large “switch-on/ switch-off” increase in the average

  13. Modeling Cancer Cell Growth Dynamics In vitro in Response to Antimitotic Drug Treatment

    KAUST Repository

    Lorz, Alexander

    2017-08-30

    Investigating the role of intrinsic cell heterogeneity emerging from variations in cell-cycle parameters and apoptosis is a crucial step toward better informing drug administration. Antimitotic agents, widely used in chemotherapy, target exclusively proliferative cells and commonly induce a prolonged mitotic arrest followed by cell death via apoptosis. In this paper, we developed a physiologically motivated mathematical framework for describing cancer cell growth dynamics that incorporates the intrinsic heterogeneity in the time individual cells spend in the cell-cycle and apoptosis process. More precisely, our model comprises two age-structured partial differential equations for the proliferative and apoptotic cell compartments and one ordinary differential equation for the quiescent compartment. To reflect the intrinsic cell heterogeneity that governs the growth dynamics, proliferative and apoptotic cells are structured in “age,” i.e., the amount of time remaining to be spent in each respective compartment. In our model, we considered an antimitotic drug whose effect on the cellular dynamics is to induce mitotic arrest, extending the average cell-cycle length. The prolonged mitotic arrest induced by the drug can trigger apoptosis if the time a cell will spend in the cell cycle is greater than the mitotic arrest threshold. We studied the drug\\'s effect on the long-term cancer cell growth dynamics using different durations of prolonged mitotic arrest induced by the drug. Our numerical simulations suggest that at confluence and in the absence of the drug, quiescence is the long-term asymptotic behavior emerging from the cancer cell growth dynamics. This pattern is maintained in the presence of small increases in the average cell-cycle length. However, intermediate increases in cell-cycle length markedly decrease the total number of cells and can drive the cancer population to extinction. Intriguin