WorldWideScience

Sample records for process based models

  1. A general model for membrane-based separation processes

    DEFF Research Database (Denmark)

    Soni, Vipasha; Abildskov, Jens; Jonsson, Gunnar Eigil

    2009-01-01

    behaviour will play an important role. In this paper, modelling of membrane-based processes for separation of gas and liquid mixtures are considered. Two general models, one for membrane-based liquid separation processes (with phase change) and another for membrane-based gas separation are presented....... The separation processes covered are: membrane-based gas separation processes, pervaporation and various types of membrane distillation processes. The specific model for each type of membrane-based process is generated from the two general models by applying the specific system descriptions and the corresponding...

  2. Model based process-product design and analysis

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    This paper gives a perspective on modelling and the important role it has within product-process design and analysis. Different modelling issues related to development and application of systematic model-based solution approaches for product-process design is discussed and the need for a hybrid...... model-based framework is highlighted. This framework should be able to manage knowledge-data, models, and associated methods and tools integrated with design work-flows and data-flows for specific product-process design problems. In particular, the framework needs to manage models of different types......, forms and complexity, together with their associated parameters. An example of a model-based system for design of chemicals based formulated products is also given....

  3. 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.

  4. Genetic Process Mining: Alignment-based Process Model Mutation

    NARCIS (Netherlands)

    Eck, van M.L.; Buijs, J.C.A.M.; Dongen, van B.F.; Fournier, F.; Mendling, J.

    2015-01-01

    The Evolutionary Tree Miner (ETM) is a genetic process discovery algorithm that enables the user to guide the discovery process based on preferences with respect to four process model quality dimensions: replay fitness, precision, generalization and simplicity. Traditionally, the ETM algorithm uses

  5. Model-based internal wave processing

    Energy Technology Data Exchange (ETDEWEB)

    Candy, J.V.; Chambers, D.H.

    1995-06-09

    A model-based approach is proposed to solve the oceanic internal wave signal processing problem that is based on state-space representations of the normal-mode vertical velocity and plane wave horizontal velocity propagation models. It is shown that these representations can be utilized to spatially propagate the modal (dept) vertical velocity functions given the basic parameters (wave numbers, Brunt-Vaisala frequency profile etc.) developed from the solution of the associated boundary value problem as well as the horizontal velocity components. Based on this framework, investigations are made of model-based solutions to the signal enhancement problem for internal waves.

  6. Model-based processing for underwater acoustic arrays

    CERN Document Server

    Sullivan, Edmund J

    2015-01-01

    This monograph presents a unified approach to model-based processing for underwater acoustic arrays. The use of physical models in passive array processing is not a new idea, but it has been used on a case-by-case basis, and as such, lacks any unifying structure. This work views all such processing methods as estimation procedures, which then can be unified by treating them all as a form of joint estimation based on a Kalman-type recursive processor, which can be recursive either in space or time, depending on the application. This is done for three reasons. First, the Kalman filter provides a natural framework for the inclusion of physical models in a processing scheme. Second, it allows poorly known model parameters to be jointly estimated along with the quantities of interest. This is important, since in certain areas of array processing already in use, such as those based on matched-field processing, the so-called mismatch problem either degrades performance or, indeed, prevents any solution at all. Third...

  7. The evolution of process-based hydrologic models

    NARCIS (Netherlands)

    Clark, Martyn P.; Bierkens, Marc F.P.; Samaniego, Luis; Woods, Ross A.; Uijlenhoet, Remko; Bennett, Katrina E.; Pauwels, Valentijn R.N.; Cai, Xitian; Wood, Andrew W.; Peters-Lidard, Christa D.

    2017-01-01

    The diversity in hydrologic models has historically led to great controversy on the "correct" approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this

  8. A model-based framework for design of intensified enzyme-based processes

    DEFF Research Database (Denmark)

    Román-Martinez, Alicia

    This thesis presents a generic and systematic model-based framework to design intensified enzyme-based processes. The development of the presented methodology was motivated by the needs of the bio-based industry for a more systematic approach to achieve intensification in its production plants...... in enzyme-based processes which have found significant application in the pharmaceutical, food, and renewable fuels sector. The framework uses model-based strategies for (bio)-chemical process design and optimization, including the use of a superstructure to generate all potential reaction......(s)-separation(s) options according to a desired performance criteria and a generic mathematical model represented by the superstructure to derive the specific models corresponding to a specific process option. In principle, three methods of intensification of bioprocess are considered in this thesis: 1. enzymatic one...

  9. Group Contribution Based Process Flowsheet Synthesis, Design and Modelling

    DEFF Research Database (Denmark)

    d'Anterroches, Loïc; Gani, Rafiqul

    2004-01-01

    This paper presents a process-group-contribution Method to model. simulate and synthesize a flowsheet. The process-group based representation of a flowsheet together with a process "property" model are presented. The process-group based synthesis method is developed on the basis of the computer...... aided molecular design methods and gives the ability to screen numerous process alternatives without the need to use the rigorous process simulation models. The process "property" model calculates the design targets for the generated flowsheet alternatives while a reverse modelling method (also...... developed) determines the design variables matching the target. A simple illustrative example highlighting the main features of the methodology is also presented....

  10. Modeling and knowledge acquisition processes using case-based inference

    Directory of Open Access Journals (Sweden)

    Ameneh Khadivar

    2017-03-01

    Full Text Available The method of acquisition and presentation of the organizational Process Knowledge has considered by many KM researches. In this research a model for process knowledge acquisition and presentation has been presented by using the approach of Case Base Reasoning. The validation of the presented model was evaluated by conducting an expert panel. Then a software has been developed based on the presented model and implemented in Eghtesad Novin Bank of Iran. In this company, based on the stages of the presented model, first the knowledge intensive processes has been identified, then the Process Knowledge was stored in a knowledge base in the format of problem/solution/consequent .The retrieval of the knowledge was done based on the similarity of the nearest neighbor algorithm. For validating of the implemented system, results of the system has compared by the results of the decision making of the expert of the process.

  11. Detecting Difference between Process Models Based on the Refined Process Structure Tree

    Directory of Open Access Journals (Sweden)

    Jing Fan

    2017-01-01

    Full Text Available The development of mobile workflow management systems (mWfMS leads to large number of business process models. In the meantime, the location restriction embedded in mWfMS may result in different process models for a single business process. In order to help users quickly locate the difference and rebuild the process model, detecting the difference between different process models is needed. Existing detection methods either provide a dissimilarity value to represent the difference or use predefined difference template to generate the result, which cannot reflect the entire composition of the difference. Hence, in this paper, we present a new approach to solve this problem. Firstly, we parse the process models to their corresponding refined process structure trees (PSTs, that is, decomposing a process model into a hierarchy of subprocess models. Then we design a method to convert the PST to its corresponding task based process structure tree (TPST. As a consequence, the problem of detecting difference between two process models is transformed to detect difference between their corresponding TPSTs. Finally, we obtain the difference between two TPSTs based on the divide and conquer strategy, where the difference is described by an edit script and we make the cost of the edit script close to minimum. The extensive experimental evaluation shows that our method can meet the real requirements in terms of precision and efficiency.

  12. A Petri Net-Based Software Process Model for Developing Process-Oriented Information Systems

    Science.gov (United States)

    Li, Yu; Oberweis, Andreas

    Aiming at increasing flexibility, efficiency, effectiveness, and transparency of information processing and resource deployment in organizations to ensure customer satisfaction and high quality of products and services, process-oriented information systems (POIS) represent a promising realization form of computerized business information systems. Due to the complexity of POIS, explicit and specialized software process models are required to guide POIS development. In this chapter we characterize POIS with an architecture framework and present a Petri net-based software process model tailored for POIS development with consideration of organizational roles. As integrated parts of the software process model, we also introduce XML nets, a variant of high-level Petri nets as basic methodology for business processes modeling, and an XML net-based software toolset providing comprehensive functionalities for POIS development.

  13. [GSH fermentation process modeling using entropy-criterion based RBF neural network model].

    Science.gov (United States)

    Tan, Zuoping; Wang, Shitong; Deng, Zhaohong; Du, Guocheng

    2008-05-01

    The prediction accuracy and generalization of GSH fermentation process modeling are often deteriorated by noise existing in the corresponding experimental data. In order to avoid this problem, we present a novel RBF neural network modeling approach based on entropy criterion. It considers the whole distribution structure of the training data set in the parameter learning process compared with the traditional MSE-criterion based parameter learning, and thus effectively avoids the weak generalization and over-learning. Then the proposed approach is applied to the GSH fermentation process modeling. Our results demonstrate that this proposed method has better prediction accuracy, generalization and robustness such that it offers a potential application merit for the GSH fermentation process modeling.

  14. Bridging process-based and empirical approaches to modeling tree growth

    Science.gov (United States)

    Harry T. Valentine; Annikki Makela; Annikki Makela

    2005-01-01

    The gulf between process-based and empirical approaches to modeling tree growth may be bridged, in part, by the use of a common model. To this end, we have formulated a process-based model of tree growth that can be fitted and applied in an empirical mode. The growth model is grounded in pipe model theory and an optimal control model of crown development. Together, the...

  15. Model based methods and tools for process systems engineering

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    need to be integrated with work-flows and data-flows for specific product-process synthesis-design problems within a computer-aided framework. The framework therefore should be able to manage knowledge-data, models and the associated methods and tools needed by specific synthesis-design work...... of model based methods and tools within a computer aided framework for product-process synthesis-design will be highlighted.......Process systems engineering (PSE) provides means to solve a wide range of problems in a systematic and efficient manner. This presentation will give a perspective on model based methods and tools needed to solve a wide range of problems in product-process synthesis-design. These methods and tools...

  16. A security modeling approach for web-service-based business processes

    DEFF Research Database (Denmark)

    Jensen, Meiko; Feja, Sven

    2009-01-01

    a transformation that automatically derives WS-SecurityPolicy-conformant security policies from the process model, which in conjunction with the generated WS-BPEL processes and WSDL documents provides the ability to deploy and run the complete security-enhanced process based on Web Service technology.......The rising need for security in SOA applications requires better support for management of non-functional properties in web-based business processes. Here, the model-driven approach may provide valuable benefits in terms of maintainability and deployment. Apart from modeling the pure functionality...... of a process, the consideration of security properties at the level of a process model is a promising approach. In this work-in-progress paper we present an extension to the ARIS SOA Architect that is capable of modeling security requirements as a separate security model view. Further we provide...

  17. On Process Modelling Using Physical Oriented And Phenomena Based Principles

    Directory of Open Access Journals (Sweden)

    Mihai Culea

    2000-12-01

    Full Text Available This work presents a modelling framework based on phenomena description of the process. The approach is taken to easy understand and construct process model in heterogeneous possible distributed modelling and simulation environments. A simplified case study of a heat exchanger is considered and Modelica modelling language to check the proposed concept. The partial results are promising and the research effort will be extended in a computer aided modelling environment based on phenomena.

  18. Model-based software process improvement

    Science.gov (United States)

    Zettervall, Brenda T.

    1994-01-01

    The activities of a field test site for the Software Engineering Institute's software process definition project are discussed. Products tested included the improvement model itself, descriptive modeling techniques, the CMM level 2 framework document, and the use of process definition guidelines and templates. The software process improvement model represents a five stage cyclic approach for organizational process improvement. The cycles consist of the initiating, diagnosing, establishing, acting, and leveraging phases.

  19. Knowledge-based inspection:modelling complex processes with the integrated Safeguards Modelling Method (iSMM)

    International Nuclear Information System (INIS)

    Abazi, F.

    2011-01-01

    Increased level of complexity in almost every discipline and operation today raises the demand for knowledge in order to successfully run an organization whether to generate profit or to attain a non-profit mission. Traditional way of transferring knowledge to information systems rich in data structures and complex algorithms continue to hinder the ability to swiftly turnover concepts into operations. Diagrammatic modelling commonly applied in engineering in order to represent concepts or reality remains to be an excellent way of converging knowledge from domain experts. The nuclear verification domain represents ever more a matter which has great importance to the World safety and security. Demand for knowledge about nuclear processes and verification activities used to offset potential misuse of nuclear technology will intensify with the growth of the subject technology. This Doctoral thesis contributes with a model-based approach for representing complex process such as nuclear inspections. The work presented contributes to other domains characterized with knowledge intensive and complex processes. Based on characteristics of a complex process a conceptual framework was established as the theoretical basis for creating a number of modelling languages to represent the domain. The integrated Safeguards Modelling Method (iSMM) is formalized through an integrated meta-model. The diagrammatic modelling languages represent the verification domain and relevant nuclear verification aspects. Such a meta-model conceptualizes the relation between practices of process management, knowledge management and domain specific verification principles. This fusion is considered as necessary in order to create quality processes. The study also extends the formalization achieved through a meta-model by contributing with a formalization language based on Pattern Theory. Through the use of graphical and mathematical constructs of the theory, process structures are formalized enhancing

  20. Process-Based Modeling of Constructed Wetlands

    Science.gov (United States)

    Baechler, S.; Brovelli, A.; Rossi, L.; Barry, D. A.

    2007-12-01

    Constructed wetlands (CWs) are widespread facilities for wastewater treatment. In subsurface flow wetlands, contaminated wastewater flows through a porous matrix, where oxidation and detoxification phenomena occur. Despite the large number of working CWs, system design and optimization are still mainly based upon empirical equations or simplified first-order kinetics. This results from an incomplete understanding of the system functioning, and may in turn hinder the performance and effectiveness of the treatment process. As a result, CWs are often considered not suitable to meet high water quality-standards, or to treat water contaminated with recalcitrant anthropogenic contaminants. To date, only a limited number of detailed numerical models have been developed and successfully applied to simulate constructed wetland behavior. Among these, one of the most complete and powerful is CW2D, which is based on Hydrus2D. The aim of this work is to develop a comprehensive simulator tailored to model the functioning of horizontal flow constructed wetlands and in turn provide a reliable design and optimization tool. The model is based upon PHWAT, a general reactive transport code for saturated flow. PHWAT couples MODFLOW, MT3DMS and PHREEQC-2 using an operator-splitting approach. The use of PHREEQC to simulate reactions allows great flexibility in simulating biogeochemical processes. The biogeochemical reaction network is similar to that of CW2D, and is based on the Activated Sludge Model (ASM). Kinetic oxidation of carbon sources and nutrient transformations (nitrogen and phosphorous primarily) are modeled via Monod-type kinetic equations. Oxygen dissolution is accounted for via a first-order mass-transfer equation. While the ASM model only includes a limited number of kinetic equations, the new simulator permits incorporation of an unlimited number of both kinetic and equilibrium reactions. Changes in pH, redox potential and surface reactions can be easily incorporated

  1. Symbolic Processing Combined with Model-Based Reasoning

    Science.gov (United States)

    James, Mark

    2009-01-01

    A computer program for the detection of present and prediction of future discrete states of a complex, real-time engineering system utilizes a combination of symbolic processing and numerical model-based reasoning. One of the biggest weaknesses of a purely symbolic approach is that it enables prediction of only future discrete states while missing all unmodeled states or leading to incorrect identification of an unmodeled state as a modeled one. A purely numerical approach is based on a combination of statistical methods and mathematical models of the applicable physics and necessitates development of a complete model to the level of fidelity required for prediction. In addition, a purely numerical approach does not afford the ability to qualify its results without some form of symbolic processing. The present software implements numerical algorithms to detect unmodeled events and symbolic algorithms to predict expected behavior, correlate the expected behavior with the unmodeled events, and interpret the results in order to predict future discrete states. The approach embodied in this software differs from that of the BEAM methodology (aspects of which have been discussed in several prior NASA Tech Briefs articles), which provides for prediction of future measurements in the continuous-data domain.

  2. Process optimization of friction stir welding based on thermal models

    DEFF Research Database (Denmark)

    Larsen, Anders Astrup

    2010-01-01

    This thesis investigates how to apply optimization methods to numerical models of a friction stir welding process. The work is intended as a proof-of-concept using different methods that are applicable to models of high complexity, possibly with high computational cost, and without the possibility...... information of the high-fidelity model. The optimization schemes are applied to stationary thermal models of differing complexity of the friction stir welding process. The optimization problems considered are based on optimizing the temperature field in the workpiece by finding optimal translational speed....... Also an optimization problem based on a microstructure model is solved, allowing the hardness distribution in the plate to be optimized. The use of purely thermal models represents a simplification of the real process; nonetheless, it shows the applicability of the optimization methods considered...

  3. A model-based approach to on-line process disturbance management

    International Nuclear Information System (INIS)

    Kim, I.S.

    1988-01-01

    The methodology developed can be applied to the design of a real-time expert system to aid control-room operators in coping with process abnormalities. The approach encompasses diverse functional aspects required for an effective on-line process disturbance management: (1) intelligent process monitoring and alarming, (2) on-line sensor data validation, (3) on-line sensor and hardware (except sensors) fault diagnosis, and (4) real-time corrective measure synthesis. Accomplishment of these functions is made possible through the application of various models, goal-tree success-tree, process monitor-tree, sensor failure diagnosis, and hardware failure diagnosis models. The models used in the methodology facilitate not only the knowledge-acquisition process - a bottleneck in the development of an expert system - but also the reasoning process of the knowledge-based system. These transparent models and model-based reasoning significantly enhance the maintainability of the real-time expert systems. The proposed approach was applied to the feedwater control system of a nuclear power plant, and implemented into a real-time expert system, MOAS II, using the expert system shell, PICON, on the LMI machine

  4. Strategies to Automatically Derive a Process Model from a Configurable Process Model Based on Event Data

    Directory of Open Access Journals (Sweden)

    Mauricio Arriagada-Benítez

    2017-10-01

    Full Text Available Configurable process models are frequently used to represent business workflows and other discrete event systems among different branches of large organizations: they unify commonalities shared by all branches and describe their differences, at the same time. The configuration of such models is usually done manually, which is challenging. On the one hand, when the number of configurable nodes in the configurable process model grows, the size of the search space increases exponentially. On the other hand, the person performing the configuration may lack the holistic perspective to make the right choice for all configurable nodes at the same time, since choices influence each other. Nowadays, information systems that support the execution of business processes create event data reflecting how processes are performed. In this article, we propose three strategies (based on exhaustive search, genetic algorithms and a greedy heuristic that use event data to automatically derive a process model from a configurable process model that better represents the characteristics of the process in a specific branch. These strategies have been implemented in our proposed framework and tested in both business-like event logs as recorded in a higher educational enterprise resource planning system and a real case scenario involving a set of Dutch municipalities.

  5. A Model of Process-Based Automation: Cost and Quality Implications in the Medication Management Process

    Science.gov (United States)

    Spaulding, Trent Joseph

    2011-01-01

    The objective of this research is to understand how a set of systems, as defined by the business process, creates value. The three studies contained in this work develop the model of process-based automation. The model states that complementarities among systems are specified by handoffs in the business process. The model also provides theory to…

  6. A Sensitivity Analysis Method to Study the Behavior of Complex Process-based Models

    Science.gov (United States)

    Brugnach, M.; Neilson, R.; Bolte, J.

    2001-12-01

    The use of process-based models as a tool for scientific inquiry is becoming increasingly relevant in ecosystem studies. Process-based models are artificial constructs that simulate the system by mechanistically mimicking the functioning of its component processes. Structurally, a process-based model can be characterized, in terms of its processes and the relationships established among them. Each process comprises a set of functional relationships among several model components (e.g., state variables, parameters and input data). While not encoded explicitly, the dynamics of the model emerge from this set of components and interactions organized in terms of processes. It is the task of the modeler to guarantee that the dynamics generated are appropriate and semantically equivalent to the phenomena being modeled. Despite the availability of techniques to characterize and understand model behavior, they do not suffice to completely and easily understand how a complex process-based model operates. For example, sensitivity analysis studies model behavior by determining the rate of change in model output as parameters or input data are varied. One of the problems with this approach is that it considers the model as a "black box", and it focuses on explaining model behavior by analyzing the relationship input-output. Since, these models have a high degree of non-linearity, understanding how the input affects an output can be an extremely difficult task. Operationally, the application of this technique may constitute a challenging task because complex process-based models are generally characterized by a large parameter space. In order to overcome some of these difficulties, we propose a method of sensitivity analysis to be applicable to complex process-based models. This method focuses sensitivity analysis at the process level, and it aims to determine how sensitive the model output is to variations in the processes. Once the processes that exert the major influence in

  7. Model-based design of self-Adapting networked signal processing systems

    NARCIS (Netherlands)

    Oliveira Filho, J.A. de; Papp, Z.; Djapic, R.; Oostveen, J.C.

    2013-01-01

    The paper describes a model based approach for architecture design of runtime reconfigurable, large-scale, networked signal processing applications. A graph based modeling formalism is introduced to describe all relevant aspects of the design (functional, concurrency, hardware, communication,

  8. Model-based verification and validation of the SMAP uplink processes

    Science.gov (United States)

    Khan, M. O.; Dubos, G. F.; Tirona, J.; Standley, S.

    Model-Based Systems Engineering (MBSE) is being used increasingly within the spacecraft design community because of its benefits when compared to document-based approaches. As the complexity of projects expands dramatically with continually increasing computational power and technology infusion, the time and effort needed for verification and validation (V& V) increases geometrically. Using simulation to perform design validation with system-level models earlier in the life cycle stands to bridge the gap between design of the system (based on system-level requirements) and verifying those requirements/validating the system as a whole. This case study stands as an example of how a project can validate a system-level design earlier in the project life cycle than traditional V& V processes by using simulation on a system model. Specifically, this paper describes how simulation was added to a system model of the Soil Moisture Active-Passive (SMAP) mission's uplink process. Also discussed are the advantages and disadvantages of the methods employed and the lessons learned; which are intended to benefit future model-based and simulation-based development efforts.

  9. A model evaluation checklist for process-based environmental models

    Science.gov (United States)

    Jackson-Blake, Leah

    2015-04-01

    the conceptual model on which it is based. In this study, a number of model structural shortcomings were identified, such as a lack of dissolved phosphorus transport via infiltration excess overland flow, potential discrepancies in the particulate phosphorus simulation and a lack of spatial granularity. (4) Conceptual challenges, as conceptual models on which predictive models are built are often outdated, having not kept up with new insights from monitoring and experiments. For example, soil solution dissolved phosphorus concentration in INCA-P is determined by the Freundlich adsorption isotherm, which could potentially be replaced using more recently-developed adsorption models that take additional soil properties into account. This checklist could be used to assist in identifying why model performance may be poor or unreliable. By providing a model evaluation framework, it could help prioritise which areas should be targeted to improve model performance or model credibility, whether that be through using alternative calibration techniques and statistics, improved data collection, improving or simplifying the model structure or updating the model to better represent current understanding of catchment processes.

  10. On the upscaling of process-based models in deltaic applications

    Science.gov (United States)

    Li, L.; Storms, J. E. A.; Walstra, D. J. R.

    2018-03-01

    Process-based numerical models are increasingly used to study the evolution of marine and terrestrial depositional environments. Whilst a detailed description of small-scale processes provides an accurate representation of reality, application on geological timescales is restrained by the associated increase in computational time. In order to reduce the computational time, a number of acceleration methods are combined and evaluated for a schematic supply-driven delta (static base level) and an accommodation-driven delta (variable base level). The performance of the combined acceleration methods is evaluated by comparing the morphological indicators such as distributary channel networking and delta volumes derived from the model predictions for various levels of acceleration. The results of the accelerated models are compared to the outcomes from a series of simulations to capture autogenic variability. Autogenic variability is quantified by re-running identical models on an initial bathymetry with 1 cm added noise. The overall results show that the variability of the accelerated models fall within the autogenic variability range, suggesting that the application of acceleration methods does not significantly affect the simulated delta evolution. The Time-scale compression method (the acceleration method introduced in this paper) results in an increased computational efficiency of 75% without adversely affecting the simulated delta evolution compared to a base case. The combination of the Time-scale compression method with the existing acceleration methods has the potential to extend the application range of process-based models towards geologic timescales.

  11. A Realistic Process Example for MIMO MPC based on Autoregressive Models

    DEFF Research Database (Denmark)

    Huusom, Jakob Kjøbsted; Jørgensen, John Bagterp

    2014-01-01

    for advanced control design develo pment which may be used by non experts in control theory. This paper presents and illustra tes the use of a simple methodology to design an offset-free MPC based on ARX models. Hence a mecha nistic process model is not required. The forced circulation evaporator by Newell...... and Lee is used to illustrate the offset-free MPC based on ARX models for a nonlinear multivariate process ....

  12. Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model

    Science.gov (United States)

    Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

    2014-02-01

    Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation

  13. Discovering and Exploring State-based Models for Multi-perspective Processes

    NARCIS (Netherlands)

    van Eck, M.L.; Sidorova, N.; van der Aalst, W.M.P.; La Rosa, M.; Loos, P.; Pastor, O.

    2016-01-01

    Process mining provides fact-based insights into process behaviour captured in event data. In this work we aim to discover models for processes where different facets, or perspectives, of the process can be identified. Instead of focussing on the events or activities that are executed in the context

  14. Turn-based evolution in a simplified model of artistic creative process

    DEFF Research Database (Denmark)

    Dahlstedt, Palle

    2015-01-01

    Evolutionary computation has often been presented as a possible model for creativity in computers. In this paper, evolution is discussed in the light of a theoretical model of human artistic process, recently presented by the author. Some crucial differences between human artistic creativity......, and the results of initial experiments are presented and discussed. Artistic creativity is here modeled as an iterated turn-based process, alternating between a conceptual representation and a material representation of the work-to-be. Evolutionary computation is proposed as a heuristic solution to the principal...... and natural evolution are observed and discussed, also in the light of other creative processes occurring in nature. As a tractable way to overcome these limitations, a new kind of evolutionary implementation of creativity is proposed, based on a simplified version of the previously presented model...

  15. Security Process Capability Model Based on ISO/IEC 15504 Conformant Enterprise SPICE

    Directory of Open Access Journals (Sweden)

    Mitasiunas Antanas

    2014-07-01

    Full Text Available In the context of modern information systems, security has become one of the most critical quality attributes. The purpose of this paper is to address the problem of quality of information security. An approach to solve this problem is based on the main assumption that security is a process oriented activity. According to this approach, product quality can be achieved by means of process quality - process capability. Introduced in the paper, SPICE conformant information security process capability model is based on process capability modeling elaborated by world-wide software engineering community during the last 25 years, namely ISO/IEC 15504 that defines the capability dimension and the requirements for process definition and domain independent integrated model for enterprise-wide assessment and Enterprise SPICE improvement

  16. A model-based framework for incremental scale-up of wastewater treatment processes

    DEFF Research Database (Denmark)

    Mauricio Iglesias, Miguel; Sin, Gürkan

    Scale-up is traditionally done following specific ratios or rules of thumb which do not lead to optimal results. We present a generic framework to assist in scale-up of wastewater treatment processes based on multiscale modelling, multiobjective optimisation and a validation of the model at the new...... large scale. The framework is illustrated by the scale-up of a complete autotropic nitrogen removal process. The model based multiobjective scaleup offers a promising improvement compared to the rule of thumbs based emprical scale up rules...

  17. A model-data based systems approach to process intensification

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    . Their developments, however, are largely due to experiment based trial and error approaches and while they do not require validation, they can be time consuming and resource intensive. Also, one may ask, can a truly new intensified unit operation be obtained in this way? An alternative two-stage approach is to apply...... a model-based synthesis method to systematically generate and evaluate alternatives in the first stage and an experiment-model based validation in the second stage. In this way, the search for alternatives is done very quickly, reliably and systematically over a wide range, while resources are preserved...... for focused validation of only the promising candidates in the second-stage. This approach, however, would be limited to intensification based on “known” unit operations, unless the PI process synthesis/design is considered at a lower level of aggregation, namely the phenomena level. That is, the model-based...

  18. A model-based systems approach to pharmaceutical product-process design and analysis

    DEFF Research Database (Denmark)

    Gernaey, Krist; Gani, Rafiqul

    2010-01-01

    This is a perspective paper highlighting the need for systematic model-based design and analysis in pharmaceutical product-process development. A model-based framework is presented and the role, development and use of models of various types are discussed together with the structure of the models...

  19. DEVELOPMENT OF SCIENCE PROCESS SKILLS STUDENTS WITH PROJECT BASED LEARNING MODEL- BASED TRAINING IN LEARNING PHYSICS

    Directory of Open Access Journals (Sweden)

    Ratna Malawati

    2016-06-01

    Full Text Available This study aims to improve the physics Science Process Skills Students on cognitive and psychomotor aspects by using model based Project Based Learning training.The object of this study is the Project Based Learning model used in the learning process of Computationa Physics.The method used is classroom action research through two learning cycles, each cycle consisting of the stages of planning, implementation, observation and reflection. In the first cycle of treatment with their emphasis given training in the first phase up to third in the model Project Based Learning, while the second cycle is given additional treatment with emphasis discussion is collaboration in achieving the best results for each group of products. The results of data analysis showed increased ability to think Students on cognitive and Science Process Skills in the psychomotor.

  20. Consensual decision-making model based on game theory for LNG processes

    International Nuclear Information System (INIS)

    Castillo, Luis; Dorao, Carlos A.

    2012-01-01

    Highlights: ► A Decision Making (DM) approach for LNG projects based on game theory is presented. ► DM framework was tested with two different cases, using analytical models and a simple LNG process. ► The problems were solved by using a Genetic Algorithm (GA) binary coding and Nash-GA. ► Integrated models from the design and optimization of the process could result in more realistic outcome. ► The major challenge in such a framework is related to the uncertainties in the market models. - Abstract: Decision-Making (DM) in LNG projects is a quite complex process due to the number of actors, approval phases, large investments and capital return in the long time. Furthermore, due to the very high investment of a LNG project, a detailed and efficient DM process is required in order to minimize risks. In this work a Decision-Making (DM) approach for LNG projects is presented. The approach is based on a consensus algorithm to address the consensus output over a common value using cost functions within a framework based on game theory. The DM framework was tested with two different cases. The first case was used for evaluating the performance of the framework with analytical models, while the second case corresponds to a simple LNG process. The problems were solved by using a Genetic Algorithm (GA) binary coding and Nash-GA. The results of the DM framework in the LNG project indicate that considering an integrated DM model and including the markets role from the design and optimization of the process more realistic outcome could be obtained. However, the major challenge in such a framework is related to the uncertainties in the market models.

  1. Modelling and simulating decision processes of linked lives: An approach based on concurrent processes and stochastic race

    NARCIS (Netherlands)

    Warnke, T.; Reinhardt, O.; Klabunde, A.; Willekens, F.J.; Uhrmacher, A.

    2017-01-01

    Individuals’ decision processes play a central role in understanding modern migration phenomena and other demographic processes. Their integration into agent-based computational demography depends largely on suitable support by a modelling language. We are developing the Modelling Language for

  2. Matérn-based nonstationary cross-covariance models for global processes

    KAUST Repository

    Jun, Mikyoung

    2014-01-01

    -covariance models, based on the Matérn covariance model class, that are suitable for describing prominent nonstationary characteristics of the global processes. In particular, we seek nonstationary versions of Matérn covariance models whose smoothness parameters

  3. Integrating textual and model-based process descriptions for comprehensive process search

    NARCIS (Netherlands)

    Leopold, Henrik; van der Aa, Han; Pittke, Fabian; Raffel, Manuel; Mendling, Jan; Reijers, Hajo A.

    2016-01-01

    Documenting business processes using process models is common practice in many organizations. However, not all process information is best captured in process models. Hence, many organizations complement these models with textual descriptions that specify additional details. The problem with this

  4. Modelling and simulating decision processes of linked lives: An approach based on concurrent processes and stochastic race.

    Science.gov (United States)

    Warnke, Tom; Reinhardt, Oliver; Klabunde, Anna; Willekens, Frans; Uhrmacher, Adelinde M

    2017-10-01

    Individuals' decision processes play a central role in understanding modern migration phenomena and other demographic processes. Their integration into agent-based computational demography depends largely on suitable support by a modelling language. We are developing the Modelling Language for Linked Lives (ML3) to describe the diverse decision processes of linked lives succinctly in continuous time. The context of individuals is modelled by networks the individual is part of, such as family ties and other social networks. Central concepts, such as behaviour conditional on agent attributes, age-dependent behaviour, and stochastic waiting times, are tightly integrated in the language. Thereby, alternative decisions are modelled by concurrent processes that compete by stochastic race. Using a migration model, we demonstrate how this allows for compact description of complex decisions, here based on the Theory of Planned Behaviour. We describe the challenges for the simulation algorithm posed by stochastic race between multiple concurrent complex decisions.

  5. Automatic support for product based workflow design : generation of process models from a product data model

    NARCIS (Netherlands)

    Vanderfeesten, I.T.P.; Reijers, H.A.; Aalst, van der W.M.P.; Vogelaar, J.J.C.L.; Meersman, R.; Dillon, T.; Herrero, P.

    2010-01-01

    Product Based Workflow Design (PBWD) is one of the few scientific methodologies for the (re)design of workflow processes. It is based on an analysis of the product that is produced in the workflow process and derives a process model from the product structure. Until now this derivation has been a

  6. Process-based models are required to manage ecological systems in a changing world

    Science.gov (United States)

    K. Cuddington; M.-J. Fortin; L.R. Gerber; A. Hastings; A. Liebhold; M. OConnor; C. Ray

    2013-01-01

    Several modeling approaches can be used to guide management decisions. However, some approaches are better fitted than others to address the problem of prediction under global change. Process-based models, which are based on a theoretical understanding of relevant ecological processes, provide a useful framework to incorporate specific responses to altered...

  7. A Process Model for Goal-Based Information Retrieval

    Directory of Open Access Journals (Sweden)

    Harvey Hyman

    2014-12-01

    Full Text Available In this paper we examine the domain of information search and propose a "goal-based" approach to study search strategy. We describe "goal-based information search" using a framework of Knowledge Discovery. We identify two Information Retrieval (IR goals using the constructs of Knowledge Acquisition (KA and Knowledge Explanation (KE. We classify these constructs into two specific information problems: An exploration-exploitation problem and an implicit-explicit problem. Our proposed framework is an extension of prior work in this domain, applying an IR Process Model originally developed for Legal-IR and adapted to Medical-IR. The approach in this paper is guided by the recent ACM-SIG Medical Information Retrieval (MedIR Workshop definition: "methodologies and technologies that seek to improve access to medical information archives via a process of information retrieval."

  8. Agent-Based Modeling of Consumer Decision making Process Based on Power Distance and Personality

    NARCIS (Netherlands)

    Roozmand, O.; Ghasem-Aghaee, N.; Hofstede, G.J.; Nematbakhsh, M.A.; Baraani, A.; Verwaart, T.

    2011-01-01

    Simulating consumer decision making processes involves different disciplines such as: sociology, social psychology, marketing, and computer science. In this paper, we propose an agent-based conceptual and computational model of consumer decision-making based on culture, personality and human needs.

  9. A General Accelerated Degradation Model Based on the Wiener Process.

    Science.gov (United States)

    Liu, Le; Li, Xiaoyang; Sun, Fuqiang; Wang, Ning

    2016-12-06

    Accelerated degradation testing (ADT) is an efficient tool to conduct material service reliability and safety evaluations by analyzing performance degradation data. Traditional stochastic process models are mainly for linear or linearization degradation paths. However, those methods are not applicable for the situations where the degradation processes cannot be linearized. Hence, in this paper, a general ADT model based on the Wiener process is proposed to solve the problem for accelerated degradation data analysis. The general model can consider the unit-to-unit variation and temporal variation of the degradation process, and is suitable for both linear and nonlinear ADT analyses with single or multiple acceleration variables. The statistical inference is given to estimate the unknown parameters in both constant stress and step stress ADT. The simulation example and two real applications demonstrate that the proposed method can yield reliable lifetime evaluation results compared with the existing linear and time-scale transformation Wiener processes in both linear and nonlinear ADT analyses.

  10. A General Accelerated Degradation Model Based on the Wiener Process

    Directory of Open Access Journals (Sweden)

    Le Liu

    2016-12-01

    Full Text Available Accelerated degradation testing (ADT is an efficient tool to conduct material service reliability and safety evaluations by analyzing performance degradation data. Traditional stochastic process models are mainly for linear or linearization degradation paths. However, those methods are not applicable for the situations where the degradation processes cannot be linearized. Hence, in this paper, a general ADT model based on the Wiener process is proposed to solve the problem for accelerated degradation data analysis. The general model can consider the unit-to-unit variation and temporal variation of the degradation process, and is suitable for both linear and nonlinear ADT analyses with single or multiple acceleration variables. The statistical inference is given to estimate the unknown parameters in both constant stress and step stress ADT. The simulation example and two real applications demonstrate that the proposed method can yield reliable lifetime evaluation results compared with the existing linear and time-scale transformation Wiener processes in both linear and nonlinear ADT analyses.

  11. Matérn-based nonstationary cross-covariance models for global processes

    KAUST Repository

    Jun, Mikyoung

    2014-07-01

    Many spatial processes in environmental applications, such as climate variables and climate model errors on a global scale, exhibit complex nonstationary dependence structure, in not only their marginal covariance but also their cross-covariance. Flexible cross-covariance models for processes on a global scale are critical for an accurate description of each spatial process as well as the cross-dependences between them and also for improved predictions. We propose various ways to produce cross-covariance models, based on the Matérn covariance model class, that are suitable for describing prominent nonstationary characteristics of the global processes. In particular, we seek nonstationary versions of Matérn covariance models whose smoothness parameters vary over space, coupled with a differential operators approach for modeling large-scale nonstationarity. We compare their performance to the performance of some existing models in terms of the aic and spatial predictions in two applications: joint modeling of surface temperature and precipitation, and joint modeling of errors in climate model ensembles. © 2014 Elsevier Inc.

  12. Improving the Aircraft Design Process Using Web-based Modeling and Simulation

    Science.gov (United States)

    Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.

    2003-01-01

    Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and muitifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

  13. Research on application of intelligent computation based LUCC model in urbanization process

    Science.gov (United States)

    Chen, Zemin

    2007-06-01

    Global change study is an interdisciplinary and comprehensive research activity with international cooperation, arising in 1980s, with the largest scopes. The interaction between land use and cover change, as a research field with the crossing of natural science and social science, has become one of core subjects of global change study as well as the front edge and hot point of it. It is necessary to develop research on land use and cover change in urbanization process and build an analog model of urbanization to carry out description, simulation and analysis on dynamic behaviors in urban development change as well as to understand basic characteristics and rules of urbanization process. This has positive practical and theoretical significance for formulating urban and regional sustainable development strategy. The effect of urbanization on land use and cover change is mainly embodied in the change of quantity structure and space structure of urban space, and LUCC model in urbanization process has been an important research subject of urban geography and urban planning. In this paper, based upon previous research achievements, the writer systematically analyzes the research on land use/cover change in urbanization process with the theories of complexity science research and intelligent computation; builds a model for simulating and forecasting dynamic evolution of urban land use and cover change, on the basis of cellular automation model of complexity science research method and multi-agent theory; expands Markov model, traditional CA model and Agent model, introduces complexity science research theory and intelligent computation theory into LUCC research model to build intelligent computation-based LUCC model for analog research on land use and cover change in urbanization research, and performs case research. The concrete contents are as follows: 1. Complexity of LUCC research in urbanization process. Analyze urbanization process in combination with the contents

  14. Enhancing Users' Participation in Business Process Modeling through Ontology-Based Training

    Science.gov (United States)

    Macris, A.; Malamateniou, F.; Vassilacopoulos, G.

    Successful business process design requires active participation of users who are familiar with organizational activities and business process modelling concepts. Hence, there is a need to provide users with reusable, flexible, agile and adaptable training material in order to enable them instil their knowledge and expertise in business process design and automation activities. Knowledge reusability is of paramount importance in designing training material on process modelling since it enables users participate actively in process design/redesign activities stimulated by the changing business environment. This paper presents a prototype approach for the design and use of training material that provides significant advantages to both the designer (knowledge - content reusability and semantic web enabling) and the user (semantic search, knowledge navigation and knowledge dissemination). The approach is based on externalizing domain knowledge in the form of ontology-based knowledge networks (i.e. training scenarios serving specific training needs) so that it is made reusable.

  15. Pipeline Processing with an Iterative, Context-Based Detection Model

    Science.gov (United States)

    2016-01-22

    wave precursor artifacts. Distortion definitely is reduced with the addition of more channels to the processed data stream (comparing trace 3 to...limitations of fully automatic hypothesis evaluation with a test case of two events in Central Asia – a deep Hindu Kush earthquake and a shallow earthquake in...AFRL-RV-PS- AFRL-RV-PS- TR-2016-0080 TR-2016-0080 PIPELINE PROCESSING WITH AN ITERATIVE, CONTEXT-BASED DETECTION MODEL T. Kværna, et al

  16. A 2-D process-based model for suspended sediment dynamics: a first step towards ecological modeling

    Science.gov (United States)

    Achete, F. M.; van der Wegen, M.; Roelvink, D.; Jaffe, B.

    2015-06-01

    In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions. This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011. Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.

  17. A 2-D process-based model for suspended sediment dynamics: A first step towards ecological modeling

    Science.gov (United States)

    Achete, F. M.; van der Wegen, M.; Roelvink, D.; Jaffe, B.

    2015-01-01

    In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions. This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011. Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.

  18. The human body metabolism process mathematical simulation based on Lotka-Volterra model

    Science.gov (United States)

    Oliynyk, Andriy; Oliynyk, Eugene; Pyptiuk, Olexandr; DzierŻak, RóŻa; Szatkowska, Małgorzata; Uvaysova, Svetlana; Kozbekova, Ainur

    2017-08-01

    The mathematical model of metabolism process in human organism based on Lotka-Volterra model has beeng proposed, considering healing regime, nutrition system, features of insulin and sugar fragmentation process in the organism. The numerical algorithm of the model using IV-order Runge-Kutta method has been realized. After the result of calculations the conclusions have been made, recommendations about using the modeling results have been showed, the vectors of the following researches are defined.

  19. An innovative service process development based on a reference model

    Directory of Open Access Journals (Sweden)

    Lorenzo Sanfelice Frazzon

    2015-06-01

    Full Text Available This article examines the new service development (NSD process, focusing specifically in a case of a financial service, guided by the following research questions: what are the processes and practices used in the development and design of new financial services? How the results of the financial NSD proposal reflects on the NSD are as a whole? Therefore, the study aims to show and describe a financial service development, conducted at Helpinveste. The paper focuses on the Conceptual Design service (activities: definition of specifications and development of alternative solutions for the service and Service Process Design (Service Representation phases. The methodological procedures are based on the process approach, using a reference model for developing new services. In order to operationalize the model, several techniques for the various stages of the project were used, e.g. QFD and Service Blueprint. Lastly, conclusions report contributions from the reference model application, both theoretical and practical contributions, as well the limitations and further research recommendations.

  20. Model-based dispersive wave processing: A recursive Bayesian solution

    International Nuclear Information System (INIS)

    Candy, J.V.; Chambers, D.H.

    1999-01-01

    Wave propagation through dispersive media represents a significant problem in many acoustic applications, especially in ocean acoustics, seismology, and nondestructive evaluation. In this paper we propose a propagation model that can easily represent many classes of dispersive waves and proceed to develop the model-based solution to the wave processing problem. It is shown that the underlying wave system is nonlinear and time-variable requiring a recursive processor. Thus the general solution to the model-based dispersive wave enhancement problem is developed using a Bayesian maximum a posteriori (MAP) approach and shown to lead to the recursive, nonlinear extended Kalman filter (EKF) processor. The problem of internal wave estimation is cast within this framework. The specific processor is developed and applied to data synthesized by a sophisticated simulator demonstrating the feasibility of this approach. copyright 1999 Acoustical Society of America.

  1. Process correlation analysis model for process improvement identification.

    Science.gov (United States)

    Choi, Su-jin; Kim, Dae-Kyoo; Park, Sooyong

    2014-01-01

    Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.

  2. Semantic Business Process Modeling

    OpenAIRE

    Markovic, Ivan

    2010-01-01

    This book presents a process-oriented business modeling framework based on semantic technologies. The framework consists of modeling languages, methods, and tools that allow for semantic modeling of business motivation, business policies and rules, and business processes. Quality of the proposed modeling framework is evaluated based on the modeling content of SAP Solution Composer and several real-world business scenarios.

  3. A Process-based Model of Global Lichen Productivity

    Science.gov (United States)

    Porada, P.; Kleidon, A.

    2012-04-01

    Lichens and biotic crusts are abundant in most ecosystems of the world. They are the main autotrophic organisms in many deserts and at high altitudes and they can also be found in large amounts as epiphytes in some forests, especially in the boreal zone. They are characterised by a great variety of physiological properties, such as growth form, productivity or color. Due to the vast land surface areas covered by lichens, they may contribute significantly to the global terrestrial net carbon uptake. Furthermore, they potentially play an important role with respect to nutrient cycles in some ecosystems and they have the ability to enhance weathering at the surface on which they grow. A possible way to quantify these processes at the global scale is presented here in form of a process-based lichen model. This approach is based on the concepts used in many dynamical vegetation models and extends these methods to account for the specific properties of lichens. Hence, processes such as photosynthesis, respiration and water exchange are implemented as well as important trade-offs like photosynthetic capacity versus respiratory load and water content versus CO2 conductivity. The great physiological variability of lichens is incorporated directly into the model through ranges of possible parameter values, which are randomly sampled. In this way, many artificial lichen "species" are created and climate then acts as a filter to determine the species which are able to survive permanently. By averaging over the surviving "species", the model predicts lichen productivity as a function of climate input data such as temperature, radiation and precipitation at the global scale. Consequently, the contribution of lichens to the global carbon balance can be quantified. Moreover, global patterns of lichen biodiversity and other properties can be illustrated. The model can be extended to account for the nutrient dynamics of lichens, such as nitrogen fixation and the acquisition and

  4. Soft-sensing Modeling Based on MLS-SVM Inversion for L-lysine Fermentation Processes

    Directory of Open Access Journals (Sweden)

    Bo Wang

    2015-06-01

    Full Text Available A modeling approach 63 based on multiple output variables least squares support vector machine (MLS-SVM inversion is presented by a combination of inverse system and support vector machine theory. Firstly, a dynamic system model is developed based on material balance relation of a fed-batch fermentation process, with which it is analyzed whether an inverse system exists or not, and into which characteristic information of a fermentation process is introduced to set up an extended inversion model. Secondly, an initial extended inversion model is developed off-line by the use of the fitting capacity of MLS-SVM; on-line correction is made by the use of a differential evolution (DE algorithm on the basis of deviation information. Finally, a combined pseudo-linear system is formed by means of a serial connection of a corrected extended inversion model behind the L-lysine fermentation processes; thereby crucial biochemical parameters of a fermentation process could be predicted on-line. The simulation experiment shows that this soft-sensing modeling method features very high prediction precision and can predict crucial biochemical parameters of L-lysine fermentation process very well.

  5. An information theory-based approach to modeling the information processing of NPP operators

    International Nuclear Information System (INIS)

    Kim, Jong Hyun; Seong, Poong Hyun

    2002-01-01

    This paper proposes a quantitative approach to modeling the information processing of NPP operators. The aim of this work is to derive the amount of the information processed during a certain control task. The focus will be on i) developing a model for information processing of NPP operators and ii) quantifying the model. To resolve the problems of the previous approaches based on the information theory, i.e. the problems of single channel approaches, we primarily develop the information processing model having multiple stages, which contains information flows. Then the uncertainty of the information is quantified using the Conant's model, a kind of information theory

  6. Process-Based Quality (PBQ) Tools Development

    Energy Technology Data Exchange (ETDEWEB)

    Cummins, J.L.

    2001-12-03

    The objective of this effort is to benchmark the development of process-based quality tools for application in CAD (computer-aided design) model-based applications. The processes of interest are design, manufacturing, and quality process applications. A study was commissioned addressing the impact, current technologies, and known problem areas in application of 3D MCAD (3-dimensional mechanical computer-aided design) models and model integrity on downstream manufacturing and quality processes. The downstream manufacturing and product quality processes are profoundly influenced and dependent on model quality and modeling process integrity. The goal is to illustrate and expedite the modeling and downstream model-based technologies for available or conceptual methods and tools to achieve maximum economic advantage and advance process-based quality concepts.

  7. Coupling process-based models and plant architectural models: A key issue for simulating crop production

    NARCIS (Netherlands)

    Reffye, de P.; Heuvelink, E.; Guo, Y.; Hu, B.G.; Zhang, B.G.

    2009-01-01

    Process-Based Models (PBMs) can successfully predict the impact of environmental factors (temperature, light, CO2, water and nutrients) on crop growth and yield. These models are used widely for yield prediction and optimization of water and nutrient supplies. Nevertheless, PBMs do not consider

  8. Switching and optimizing control for coal flotation process based on a hybrid model

    Science.gov (United States)

    Dong, Zhiyong; Wang, Ranfeng; Fan, Minqiang; Fu, Xiang

    2017-01-01

    Flotation is an important part of coal preparation, and the flotation column is widely applied as efficient flotation equipment. This process is complex and affected by many factors, with the froth depth and reagent dosage being two of the most important and frequently manipulated variables. This paper proposes a new method of switching and optimizing control for the coal flotation process. A hybrid model is built and evaluated using industrial data. First, wavelet analysis and principal component analysis (PCA) are applied for signal pre-processing. Second, a control model for optimizing the set point of the froth depth is constructed based on fuzzy control, and a control model is designed to optimize the reagent dosages based on expert system. Finally, the least squares-support vector machine (LS-SVM) is used to identify the operating conditions of the flotation process and to select one of the two models (froth depth or reagent dosage) for subsequent operation according to the condition parameters. The hybrid model is developed and evaluated on an industrial coal flotation column and exhibits satisfactory performance. PMID:29040305

  9. Extracting business vocabularies from business process models: SBVR and BPMN standards-based approach

    Science.gov (United States)

    Skersys, Tomas; Butleris, Rimantas; Kapocius, Kestutis

    2013-10-01

    Approaches for the analysis and specification of business vocabularies and rules are very relevant topics in both Business Process Management and Information Systems Development disciplines. However, in common practice of Information Systems Development, the Business modeling activities still are of mostly empiric nature. In this paper, basic aspects of the approach for business vocabularies' semi-automated extraction from business process models are presented. The approach is based on novel business modeling-level OMG standards "Business Process Model and Notation" (BPMN) and "Semantics for Business Vocabularies and Business Rules" (SBVR), thus contributing to OMG's vision about Model-Driven Architecture (MDA) and to model-driven development in general.

  10. Numerical Model based Reliability Estimation of Selective Laser Melting Process

    DEFF Research Database (Denmark)

    Mohanty, Sankhya; Hattel, Jesper Henri

    2014-01-01

    Selective laser melting is developing into a standard manufacturing technology with applications in various sectors. However, the process is still far from being at par with conventional processes such as welding and casting, the primary reason of which is the unreliability of the process. While...... of the selective laser melting process. A validated 3D finite-volume alternating-direction-implicit numerical technique is used to model the selective laser melting process, and is calibrated against results from single track formation experiments. Correlation coefficients are determined for process input...... parameters such as laser power, speed, beam profile, etc. Subsequently, uncertainties in the processing parameters are utilized to predict a range for the various outputs, using a Monte Carlo method based uncertainty analysis methodology, and the reliability of the process is established....

  11. A Process-Based Transport-Distance Model of Aeolian Transport

    Science.gov (United States)

    Naylor, A. K.; Okin, G.; Wainwright, J.; Parsons, A. J.

    2017-12-01

    We present a new approach to modeling aeolian transport based on transport distance. Particle fluxes are based on statistical probabilities of particle detachment and distributions of transport lengths, which are functions of particle size classes. A computational saltation model is used to simulate transport distances over a variety of sizes. These are fit to an exponential distribution, which has the advantages of computational economy, concordance with current field measurements, and a meaningful relationship to theoretical assumptions about mean and median particle transport distance. This novel approach includes particle-particle interactions, which are important for sustaining aeolian transport and dust emission. Results from this model are compared with results from both bulk- and particle-sized-specific transport equations as well as empirical wind tunnel studies. The transport-distance approach has been successfully used for hydraulic processes, and extending this methodology from hydraulic to aeolian transport opens up the possibility of modeling joint transport by wind and water using consistent physics. Particularly in nutrient-limited environments, modeling the joint action of aeolian and hydraulic transport is essential for understanding the spatial distribution of biomass across landscapes and how it responds to climatic variability and change.

  12. Bearing Degradation Process Prediction Based on the Support Vector Machine and Markov Model

    Directory of Open Access Journals (Sweden)

    Shaojiang Dong

    2014-01-01

    Full Text Available Predicting the degradation process of bearings before they reach the failure threshold is extremely important in industry. This paper proposed a novel method based on the support vector machine (SVM and the Markov model to achieve this goal. Firstly, the features are extracted by time and time-frequency domain methods. However, the extracted original features are still with high dimensional and include superfluous information, and the nonlinear multifeatures fusion technique LTSA is used to merge the features and reduces the dimension. Then, based on the extracted features, the SVM model is used to predict the bearings degradation process, and the CAO method is used to determine the embedding dimension of the SVM model. After the bearing degradation process is predicted by SVM model, the Markov model is used to improve the prediction accuracy. The proposed method was validated by two bearing run-to-failure experiments, and the results proved the effectiveness of the methodology.

  13. Integration of a Three-Dimensional Process-Based Hydrological Model into the Object Modeling System

    Directory of Open Access Journals (Sweden)

    Giuseppe Formetta

    2016-01-01

    Full Text Available The integration of a spatial process model into an environmental modeling framework can enhance the model’s capabilities. This paper describes a general methodology for integrating environmental models into the Object Modeling System (OMS regardless of the model’s complexity, the programming language, and the operating system used. We present the integration of the GEOtop model into the OMS version 3.0 and illustrate its application in a small watershed. OMS is an environmental modeling framework that facilitates model development, calibration, evaluation, and maintenance. It provides innovative techniques in software design such as multithreading, implicit parallelism, calibration and sensitivity analysis algorithms, and cloud-services. GEOtop is a physically based, spatially distributed rainfall-runoff model that performs three-dimensional finite volume calculations of water and energy budgets. Executing GEOtop as an OMS model component allows it to: (1 interact directly with the open-source geographical information system (GIS uDig-JGrass to access geo-processing, visualization, and other modeling components; and (2 use OMS components for automatic calibration, sensitivity analysis, or meteorological data interpolation. A case study of the model in a semi-arid agricultural catchment is presented for illustration and proof-of-concept. Simulated soil water content and soil temperature results are compared with measured data, and model performance is evaluated using goodness-of-fit indices. This study serves as a template for future integration of process models into OMS.

  14. A dual-process perspective on fluency-based aesthetics: the pleasure-interest model of aesthetic liking.

    Science.gov (United States)

    Graf, Laura K M; Landwehr, Jan R

    2015-11-01

    In this article, we develop an account of how aesthetic preferences can be formed as a result of two hierarchical, fluency-based processes. Our model suggests that processing performed immediately upon encountering an aesthetic object is stimulus driven, and aesthetic preferences that accrue from this processing reflect aesthetic evaluations of pleasure or displeasure. When sufficient processing motivation is provided by a perceiver's need for cognitive enrichment and/or the stimulus' processing affordance, elaborate perceiver-driven processing can emerge, which gives rise to fluency-based aesthetic evaluations of interest, boredom, or confusion. Because the positive outcomes in our model are pleasure and interest, we call it the Pleasure-Interest Model of Aesthetic Liking (PIA Model). Theoretically, this model integrates a dual-process perspective and ideas from lay epistemology into processing fluency theory, and it provides a parsimonious framework to embed and unite a wealth of aesthetic phenomena, including contradictory preference patterns for easy versus difficult-to-process aesthetic stimuli. © 2015 by the Society for Personality and Social Psychology, Inc.

  15. SmartWeld/SmartProcess - intelligent model based system for the design and validation of welding processes

    Energy Technology Data Exchange (ETDEWEB)

    Mitchner, J.

    1996-04-01

    Diagrams are presented on an intelligent model based system for the design and validation of welding processes. Key capabilities identified include `right the first time` manufacturing, continuous improvement, and on-line quality assurance.

  16. A first packet processing subdomain cluster model based on SDN

    Science.gov (United States)

    Chen, Mingyong; Wu, Weimin

    2017-08-01

    For the current controller cluster packet processing performance bottlenecks and controller downtime problems. An SDN controller is proposed to allocate the priority of each device in the SDN (Software Defined Network) network, and the domain contains several network devices and Controller, the controller is responsible for managing the network equipment within the domain, the switch performs data delivery based on the load of the controller, processing network equipment data. The experimental results show that the model can effectively solve the risk of single point failure of the controller, and can solve the performance bottleneck of the first packet processing.

  17. E-Business Models in B2B: Process Based Categorization and Analysis of B2B Models

    OpenAIRE

    Mahesh S. Raisinghani; Turan Melemez; Lijie Zou; Chris Paslowski; Irma Kimvidze; Susanne Taha; Klaus Simons

    2005-01-01

    The business models in business-to-business (B2B) e-commerce and their effectiveness have been a major topic of research in recent years. Due to the variety of existing models, it seems difficult to find a widely accepted categorization that can be analyzed and assessed. An in-depth study that provides a process-based approach to B2B e-commerce is presented and illustrated with examples from industry. A comparative examination of both the buy and the sell side based on a process-related appro...

  18. Control of Process Operations and Monitoring of Product Qualities through Generic Model-based Framework in Crystallization Processes

    DEFF Research Database (Denmark)

    Abdul Samad, Noor Asma Fazli Bin

    A generic and systematic model-based framework for the design of a process monitoring and control system to achieve the desired crystal size distribution (CSD) and crystal shape for a wide range of crystallization processes has been developed. This framework combines a generic multi-dimensional m...

  19. Modeling and Analysis of 3d Printing Ws-Bpel Business Processes Based on Servicenet

    Directory of Open Access Journals (Sweden)

    Zhang Cheng-Lei

    2017-01-01

    Full Text Available To solve the problem that whether the described Web service by business process execution language were interactive compatible, a method of WS-BPEL(Web Services Business Process Execution Language parsing and execution was proposed. The service compatibility checking algorithm based on the Mediation model, which can provide multi-level service checking compatibility, and realize the goal of Service Cooperation or the demand of Value-Added Services. Based on BPMN specification, a task modeling and management tool was proposed to support the service components for assembly component. It supports both Web service automatic retrieval and service content analysis based on QoS information, and the task execution model between the BPMN specification task descriptions was transformed into the BPEL specification task description model. Finally, a model transformation strategy based on meta-model mapping was put forward. The algorithm was designed and examples were given to demonstrate the efficiency of 3D Printing WS-BPEL.

  20. Physically based modelling and optimal operation for product drying during post-harvest processing.

    NARCIS (Netherlands)

    Boxtel, van A.J.B.; Lukasse, L.; Farkas, I.; Rendik, Z.

    1996-01-01

    The development of new procedures for crop production and post-harvest processing requires models. Models based on physical backgrounds are most useful for this purpose because of their extrapolation potential. An optimal procedure is developed for alfalfa drying using a physical model. The model

  1. Demand-based maintenance and operators support based on process models; Behovsstyrt underhaall och operatoersstoed baserat paa process modeller

    Energy Technology Data Exchange (ETDEWEB)

    Dahlquist, Erik; Widarsson, Bjoern; Tomas-Aparicio, Elena

    2012-02-15

    There is a strong demand for systems that can give early warnings on upcoming problems in process performance or sensor measurements. In this project we have developed and implemented such a system on-line. The goal with the system is to give warnings about both faults needing urgent actions, as well giving advice on roughly when service may be needed for specific functions. The use of process simulation models on-line can offer a significant tool for operators and process engineers to analyse the performance of the process and make the most correct and fastest decision when problems arise. In this project physical simulation models are used in combination with decision support tools. By using a physical model it is possible to compare the measured data to the data obtained from the simulation and give these deviations as input to a decision support tool with Bayesian Networks (BN) that will result in information about the probability for wrong measurement in the instruments, process problems and maintenance needs. The application has been implemented in a CFB boiler at Maelarenergi AB. After tuning the model the system has been used online during September - October 2010 and May - October 2011, showing that the system is working on-line with respect to running the simulation model but with batch runs with respect to the BN. Examples have been made for several variables where trends of the deviation between simulation results and measured data have been used as input to a BN, where the probability for different faults has been calculated. Combustion up in the separator/cyclones has been detected several times, problems with fuel feed on both sides of the boiler as well. A moisture sensor not functioning as it should and suspected malfunctioning temperature meters as well. Deeper investigations of the true cause of problems have been used as input to tune the BN

  2. Model Optimization Identification Method Based on Closed-loop Operation Data and Process Characteristics Parameters

    Directory of Open Access Journals (Sweden)

    Zhiqiang GENG

    2014-01-01

    Full Text Available Output noise is strongly related to input in closed-loop control system, which makes model identification of closed-loop difficult, even unidentified in practice. The forward channel model is chosen to isolate disturbance from the output noise to input, and identified by optimization the dynamic characteristics of the process based on closed-loop operation data. The characteristics parameters of the process, such as dead time and time constant, are calculated and estimated based on the PI/PID controller parameters and closed-loop process input/output data. And those characteristics parameters are adopted to define the search space of the optimization identification algorithm. PSO-SQP optimization algorithm is applied to integrate the global search ability of PSO with the local search ability of SQP to identify the model parameters of forward channel. The validity of proposed method has been verified by the simulation. The practicability is checked with the PI/PID controller parameter turning based on identified forward channel model.

  3. A model-based combinatorial optimisation approach for energy-efficient processing of microalgae

    NARCIS (Netherlands)

    Slegers, P.M.; Koetzier, B.J.; Fasaei, F.; Wijffels, R.H.; Straten, van G.; Boxtel, van A.J.B.

    2014-01-01

    The analyses of algae biorefinery performance are commonly based on fixed performance data for each processing step. In this work, we demonstrate a model-based combinatorial approach to derive the design-specific upstream energy consumption and biodiesel yield in the production of biodiesel from

  4. Process-Based Quality (PBQ) Tools Development; TOPICAL

    International Nuclear Information System (INIS)

    Cummins, J.L.

    2001-01-01

    The objective of this effort is to benchmark the development of process-based quality tools for application in CAD (computer-aided design) model-based applications. The processes of interest are design, manufacturing, and quality process applications. A study was commissioned addressing the impact, current technologies, and known problem areas in application of 3D MCAD (3-dimensional mechanical computer-aided design) models and model integrity on downstream manufacturing and quality processes. The downstream manufacturing and product quality processes are profoundly influenced and dependent on model quality and modeling process integrity. The goal is to illustrate and expedite the modeling and downstream model-based technologies for available or conceptual methods and tools to achieve maximum economic advantage and advance process-based quality concepts

  5. Transforming Collaborative Process Models into Interface Process Models by Applying an MDA Approach

    Science.gov (United States)

    Lazarte, Ivanna M.; Chiotti, Omar; Villarreal, Pablo D.

    Collaborative business models among enterprises require defining collaborative business processes. Enterprises implement B2B collaborations to execute these processes. In B2B collaborations the integration and interoperability of processes and systems of the enterprises are required to support the execution of collaborative processes. From a collaborative process model, which describes the global view of the enterprise interactions, each enterprise must define the interface process that represents the role it performs in the collaborative process in order to implement the process in a Business Process Management System. Hence, in this work we propose a method for the automatic generation of the interface process model of each enterprise from a collaborative process model. This method is based on a Model-Driven Architecture to transform collaborative process models into interface process models. By applying this method, interface processes are guaranteed to be interoperable and defined according to a collaborative process.

  6. Soft Sensor Modeling Based on Multiple Gaussian Process Regression and Fuzzy C-mean Clustering

    Directory of Open Access Journals (Sweden)

    Xianglin ZHU

    2014-06-01

    Full Text Available In order to overcome the difficulties of online measurement of some crucial biochemical variables in fermentation processes, a new soft sensor modeling method is presented based on the Gaussian process regression and fuzzy C-mean clustering. With the consideration that the typical fermentation process can be distributed into 4 phases including lag phase, exponential growth phase, stable phase and dead phase, the training samples are classified into 4 subcategories by using fuzzy C- mean clustering algorithm. For each sub-category, the samples are trained using the Gaussian process regression and the corresponding soft-sensing sub-model is established respectively. For a new sample, the membership between this sample and sub-models are computed based on the Euclidean distance, and then the prediction output of soft sensor is obtained using the weighting sum. Taking the Lysine fermentation as example, the simulation and experiment are carried out and the corresponding results show that the presented method achieves better fitting and generalization ability than radial basis function neutral network and single Gaussian process regression model.

  7. Research of Cadastral Data Modelling and Database Updating Based on Spatio-temporal Process

    Directory of Open Access Journals (Sweden)

    ZHANG Feng

    2016-02-01

    Full Text Available The core of modern cadastre management is to renew the cadastre database and keep its currentness,topology consistency and integrity.This paper analyzed the changes and their linkage of various cadastral objects in the update process.Combined object-oriented modeling technique with spatio-temporal objects' evolution express,the paper proposed a cadastral data updating model based on the spatio-temporal process according to people's thought.Change rules based on the spatio-temporal topological relations of evolution cadastral spatio-temporal objects are drafted and further more cascade updating and history back trace of cadastral features,land use and buildings are realized.This model implemented in cadastral management system-ReGIS.Achieved cascade changes are triggered by the direct driving force or perceived external events.The system records spatio-temporal objects' evolution process to facilitate the reconstruction of history,change tracking,analysis and forecasting future changes.

  8. Process modelling on a canonical basis[Process modelling; Canonical modelling

    Energy Technology Data Exchange (ETDEWEB)

    Siepmann, Volker

    2006-12-20

    Based on an equation oriented solving strategy, this thesis investigates a new approach to process modelling. Homogeneous thermodynamic state functions represent consistent mathematical models of thermodynamic properties. Such state functions of solely extensive canonical state variables are the basis of this work, as they are natural objective functions in optimisation nodes to calculate thermodynamic equilibrium regarding phase-interaction and chemical reactions. Analytical state function derivatives are utilised within the solution process as well as interpreted as physical properties. By this approach, only a limited range of imaginable process constraints are considered, namely linear balance equations of state variables. A second-order update of source contributions to these balance equations is obtained by an additional constitutive equation system. These equations are general dependent on state variables and first-order sensitivities, and cover therefore practically all potential process constraints. Symbolic computation technology efficiently provides sparsity and derivative information of active equations to avoid performance problems regarding robustness and computational effort. A benefit of detaching the constitutive equation system is that the structure of the main equation system remains unaffected by these constraints, and a priori information allows to implement an efficient solving strategy and a concise error diagnosis. A tailor-made linear algebra library handles the sparse recursive block structures efficiently. The optimisation principle for single modules of thermodynamic equilibrium is extended to host entire process models. State variables of different modules interact through balance equations, representing material flows from one module to the other. To account for reusability and encapsulation of process module details, modular process modelling is supported by a recursive module structure. The second-order solving algorithm makes it

  9. D-FNN Based Modeling and BP Neural Network Decoupling Control of PVC Stripping Process

    Directory of Open Access Journals (Sweden)

    Shu-zhi Gao

    2014-01-01

    Full Text Available PVC stripping process is a kind of complicated industrial process with characteristics of highly nonlinear and time varying. Aiming at the problem of establishing the accurate mathematics model due to the multivariable coupling and big time delay, the dynamic fuzzy neural network (D-FNN is adopted to establish the PVC stripping process model based on the actual process operation datum. Then, the PVC stripping process is decoupled by the distributed neural network decoupling module to obtain two single-input-single-output (SISO subsystems (slurry flow to top tower temperature and steam flow to bottom tower temperature. Finally, the PID controller based on BP neural networks is used to control the decoupled PVC stripper system. Simulation results show the effectiveness of the proposed integrated intelligent control method.

  10. Process-based distributed modeling approach for analysis of sediment dynamics in a river basin

    Directory of Open Access Journals (Sweden)

    M. A. Kabir

    2011-04-01

    Full Text Available Modeling of sediment dynamics for developing best management practices of reducing soil erosion and of sediment control has become essential for sustainable management of watersheds. Precise estimation of sediment dynamics is very important since soils are a major component of enormous environmental processes and sediment transport controls lake and river pollution extensively. Different hydrological processes govern sediment dynamics in a river basin, which are highly variable in spatial and temporal scales. This paper presents a process-based distributed modeling approach for analysis of sediment dynamics at river basin scale by integrating sediment processes (soil erosion, sediment transport and deposition with an existing process-based distributed hydrological model. In this modeling approach, the watershed is divided into an array of homogeneous grids to capture the catchment spatial heterogeneity. Hillslope and river sediment dynamic processes have been modeled separately and linked to each other consistently. Water flow and sediment transport at different land grids and river nodes are modeled using one dimensional kinematic wave approximation of Saint-Venant equations. The mechanics of sediment dynamics are integrated into the model using representative physical equations after a comprehensive review. The model has been tested on river basins in two different hydro climatic areas, the Abukuma River Basin, Japan and Latrobe River Basin, Australia. Sediment transport and deposition are modeled using Govers transport capacity equation. All spatial datasets, such as, Digital Elevation Model (DEM, land use and soil classification data, etc., have been prepared using raster "Geographic Information System (GIS" tools. The results of relevant statistical checks (Nash-Sutcliffe efficiency and R–squared value indicate that the model simulates basin hydrology and its associated sediment dynamics reasonably well. This paper presents the

  11. Model of Values-Based Management Process in Schools: A Mixed Design Study

    Science.gov (United States)

    Dogan, Soner

    2016-01-01

    The aim of this paper is to evaluate the school administrators' values-based management behaviours according to the teachers' perceptions and opinions and, accordingly, to build a model of values-based management process in schools. The study was conducted using explanatory design which is inclusive of both quantitative and qualitative methods.…

  12. Petri Net-Based R&D Process Modeling and Optimization for Composite Materials

    Directory of Open Access Journals (Sweden)

    Xiaomei Hu

    2013-01-01

    Full Text Available Considering the current R&D process for new composite materials involves some complex details, such as formula design, specimen/sample production, materials/sample test, assessment, materials/sample feedback from customers, and mass production, the workflow model of Petri net-based R&D process for new composite materials’ is proposed. By analyzing the time property of the whole Petri net, the optimized model for new composite materials R&D workflow is further proposed. By analyzing the experiment data and application in some materials R&D enterprise, it is demonstrated that the workflow optimization model shortens the period of R&D on new materials for 15%, definitely improving the R&D efficiency. This indicates the feasibility and availability of the model.

  13. Building v/s Exploring Models: Comparing Learning of Evolutionary Processes through Agent-based Modeling

    Science.gov (United States)

    Wagh, Aditi

    Two strands of work motivate the three studies in this dissertation. Evolutionary change can be viewed as a computational complex system in which a small set of rules operating at the individual level result in different population level outcomes under different conditions. Extensive research has documented students' difficulties with learning about evolutionary change (Rosengren et al., 2012), particularly in terms of levels slippage (Wilensky & Resnick, 1999). Second, though building and using computational models is becoming increasingly common in K-12 science education, we know little about how these two modalities compare. This dissertation adopts agent-based modeling as a representational system to compare these modalities in the conceptual context of micro-evolutionary processes. Drawing on interviews, Study 1 examines middle-school students' productive ways of reasoning about micro-evolutionary processes to find that the specific framing of traits plays a key role in whether slippage explanations are cued. Study 2, which was conducted in 2 schools with about 150 students, forms the crux of the dissertation. It compares learning processes and outcomes when students build their own models or explore a pre-built model. Analysis of Camtasia videos of student pairs reveals that builders' and explorers' ways of accessing rules, and sense-making of observed trends are of a different character. Builders notice rules through available blocks-based primitives, often bypassing their enactment while explorers attend to rules primarily through the enactment. Moreover, builders' sense-making of observed trends is more rule-driven while explorers' is more enactment-driven. Pre and posttests reveal that builders manifest a greater facility with accessing rules, providing explanations manifesting targeted assembly. Explorers use rules to construct explanations manifesting non-targeted assembly. Interviews reveal varying degrees of shifts away from slippage in both

  14. Improving Prediction Accuracy of a Rate-Based Model of an MEA-Based Carbon Capture Process for Large-Scale Commercial Deployment

    Directory of Open Access Journals (Sweden)

    Xiaobo Luo

    2017-04-01

    Full Text Available Carbon capture and storage (CCS technology will play a critical role in reducing anthropogenic carbon dioxide (CO2 emission from fossil-fired power plants and other energy-intensive processes. However, the increment of energy cost caused by equipping a carbon capture process is the main barrier to its commercial deployment. To reduce the capital and operating costs of carbon capture, great efforts have been made to achieve optimal design and operation through process modeling, simulation, and optimization. Accurate models form an essential foundation for this purpose. This paper presents a study on developing a more accurate rate-based model in Aspen Plus® for the monoethanolamine (MEA-based carbon capture process by multistage model validations. The modeling framework for this process was established first. The steady-state process model was then developed and validated at three stages, which included a thermodynamic model, physical properties calculations, and a process model at the pilot plant scale, covering a wide range of pressures, temperatures, and CO2 loadings. The calculation correlations of liquid density and interfacial area were updated by coding Fortran subroutines in Aspen Plus®. The validation results show that the correlation combination for the thermodynamic model used in this study has higher accuracy than those of three other key publications and the model prediction of the process model has a good agreement with the pilot plant experimental data. A case study was carried out for carbon capture from a 250 MWe combined cycle gas turbine (CCGT power plant. Shorter packing height and lower specific duty were achieved using this accurate model.

  15. PGD-based modeling of materials, structures and processes

    CERN Document Server

    Chinesta, Francisco

    2014-01-01

    This book focuses on the development of a new simulation paradigm allowing for the solution of models that up to now have never been resolved and which result in spectacular CPU time savings (in the order of millions) that, combined with supercomputing, could revolutionize future ICT (information and communication technologies) at the heart of science and technology. The authors have recently proposed a new paradigm for simulation-based engineering sciences called Proper Generalized Decomposition, PGD, which has proved a tremendous potential in many aspects of forming process simulation. In this book a review of the basics of the technique is made, together with different examples of application.

  16. Mathematical Modeling and Simulation of SWRO Process Based on Simultaneous Method

    Directory of Open Access Journals (Sweden)

    Aipeng Jiang

    2014-01-01

    Full Text Available Reverse osmosis (RO technique is one of the most efficient ways for seawater desalination to solve the shortage of freshwater. For prediction and analysis of the performance of seawater reverse osmosis (SWRO process, an accurate and detailed model based on the solution-diffusion and mass transfer theory is established. Since the accurate formulation of the model includes many differential equations and strong nonlinear equations (differential and algebraic equations, DAEs, to solve the problem efficiently, the simultaneous method through orthogonal collocation on finite elements and large scale solver were used to obtain the solutions. The model was fully discretized into NLP (nonlinear programming with large scale variables and equations, and then the NLP was solved by large scale solver of IPOPT. Validation of the formulated model and solution method is verified by case study on a SWRO plant. Then simulation and analysis are carried out to demonstrate the performance of reverse osmosis process; operational conditions such as feed pressure and feed flow rate as well as feed temperature are also analyzed. This work is of significant meaning for the detailed understanding of RO process and future energy saving through operational optimization.

  17. An Ontology-Based Conceptual Model For Accumulating And Reusing Knowledge In A DMAIC Process

    Science.gov (United States)

    Nguyen, ThanhDat; Kifor, Claudiu Vasile

    2015-09-01

    DMAIC (Define, Measure, Analyze, Improve, and Control) is an important process used to enhance quality of processes basing on knowledge. However, it is difficult to access DMAIC knowledge. Conventional approaches meet a problem arising from structuring and reusing DMAIC knowledge. The main reason is that DMAIC knowledge is not represented and organized systematically. In this article, we overcome the problem basing on a conceptual model that is a combination of DMAIC process, knowledge management, and Ontology engineering. The main idea of our model is to utilizing Ontologies to represent knowledge generated by each of DMAIC phases. We build five different knowledge bases for storing all knowledge of DMAIC phases with the support of necessary tools and appropriate techniques in Information Technology area. Consequently, these knowledge bases provide knowledge available to experts, managers, and web users during or after DMAIC execution in order to share and reuse existing knowledge.

  18. Monte Carlo based toy model for fission process

    International Nuclear Information System (INIS)

    Kurniadi, R.; Waris, A.; Viridi, S.

    2014-01-01

    There are many models and calculation techniques to obtain visible image of fission yield process. In particular, fission yield can be calculated by using two calculations approach, namely macroscopic approach and microscopic approach. This work proposes another calculation approach in which the nucleus is treated as a toy model. Hence, the fission process does not represent real fission process in nature completely. The toy model is formed by Gaussian distribution of random number that randomizes distance like the distance between particle and central point. The scission process is started by smashing compound nucleus central point into two parts that are left central and right central points. These three points have different Gaussian distribution parameters such as mean (μ CN , μ L , μ R ), and standard deviation (σ CN , σ L , σ R ). By overlaying of three distributions, the number of particles (N L , N R ) that are trapped by central points can be obtained. This process is iterated until (N L , N R ) become constant numbers. Smashing process is repeated by changing σ L and σ R , randomly

  19. Equifinality and process-based modelling

    Science.gov (United States)

    Khatami, S.; Peel, M. C.; Peterson, T. J.; Western, A. W.

    2017-12-01

    Equifinality is understood as one of the fundamental difficulties in the study of open complex systems, including catchment hydrology. A review of the hydrologic literature reveals that the term equifinality has been widely used, but in many cases inconsistently and without coherent recognition of the various facets of equifinality, which can lead to ambiguity but also methodological fallacies. Therefore, in this study we first characterise the term equifinality within the context of hydrological modelling by reviewing the genesis of the concept of equifinality and then presenting a theoretical framework. During past decades, equifinality has mainly been studied as a subset of aleatory (arising due to randomness) uncertainty and for the assessment of model parameter uncertainty. Although the connection between parameter uncertainty and equifinality is undeniable, we argue there is more to equifinality than just aleatory parameter uncertainty. That is, the importance of equifinality and epistemic uncertainty (arising due to lack of knowledge) and their implications is overlooked in our current practice of model evaluation. Equifinality and epistemic uncertainty in studying, modelling, and evaluating hydrologic processes are treated as if they can be simply discussed in (or often reduced to) probabilistic terms (as for aleatory uncertainty). The deficiencies of this approach to conceptual rainfall-runoff modelling are demonstrated for selected Australian catchments by examination of parameter and internal flux distributions and interactions within SIMHYD. On this basis, we present a new approach that expands equifinality concept beyond model parameters to inform epistemic uncertainty. The new approach potentially facilitates the identification and development of more physically plausible models and model evaluation schemes particularly within the multiple working hypotheses framework, and is generalisable to other fields of environmental modelling as well.

  20. Performance of a process-based hydrodynamic model in predicting shoreline change

    Science.gov (United States)

    Safak, I.; Warner, J. C.; List, J. H.

    2012-12-01

    Shoreline change is controlled by a complex combination of processes that include waves, currents, sediment characteristics and availability, geologic framework, human interventions, and sea level rise. A comprehensive data set of shoreline position (14 shorelines between 1978-2002) along the continuous and relatively non-interrupted North Carolina Coast from Oregon Inlet to Cape Hatteras (65 km) reveals a spatial pattern of alternating erosion and accretion, with an erosional average shoreline change rate of -1.6 m/yr and up to -8 m/yr in some locations. This data set gives a unique opportunity to study long-term shoreline change in an area hit by frequent storm events while relatively uninfluenced by human interventions and the effects of tidal inlets. Accurate predictions of long-term shoreline change may require a model that accurately resolves surf zone processes and sediment transport patterns. Conventional methods for predicting shoreline change such as one-line models and regression of shoreline positions have been designed for computational efficiency. These methods, however, not only have several underlying restrictions (validity for small angle of wave approach, assuming bottom contours and shoreline to be parallel, depth of closure, etc.) but also their empirical estimates of sediment transport rates in the surf zone have been shown to vary greatly from the calculations of process-based hydrodynamic models. We focus on hind-casting long-term shoreline change using components of the process-based, three-dimensional coupled-ocean-atmosphere-wave-sediment transport modeling system (COAWST). COAWST is forced with historical predictions of atmospheric and oceanographic data from public-domain global models. Through a method of coupled concurrent grid-refinement approach in COAWST, the finest grid with resolution of O(10 m) that covers the surf zone along the section of interest is forced at its spatial boundaries with waves and currents computed on the grids

  1. Developing a Data Driven Process-Based Model for Remote Sensing of Ecosystem Production

    Science.gov (United States)

    Elmasri, B.; Rahman, A. F.

    2010-12-01

    Estimating ecosystem carbon fluxes at various spatial and temporal scales is essential for quantifying the global carbon cycle. Numerous models have been developed for this purpose using several environmental variables as well as vegetation indices derived from remotely sensed data. Here we present a data driven modeling approach for gross primary production (GPP) that is based on a process based model BIOME-BGC. The proposed model was run using available remote sensing data and it does not depend on look-up tables. Furthermore, this approach combines the merits of both empirical and process models, and empirical models were used to estimate certain input variables such as light use efficiency (LUE). This was achieved by using remotely sensed data to the mathematical equations that represent biophysical photosynthesis processes in the BIOME-BGC model. Moreover, a new spectral index for estimating maximum photosynthetic activity, maximum photosynthetic rate index (MPRI), is also developed and presented here. This new index is based on the ratio between the near infrared and the green bands (ρ858.5/ρ555). The model was tested and validated against MODIS GPP product and flux measurements from two eddy covariance flux towers located at Morgan Monroe State Forest (MMSF) in Indiana and Harvard Forest in Massachusetts. Satellite data acquired by the Advanced Microwave Scanning Radiometer (AMSR-E) and MODIS were used. The data driven model showed a strong correlation between the predicted and measured GPP at the two eddy covariance flux towers sites. This methodology produced better predictions of GPP than did the MODIS GPP product. Moreover, the proportion of error in the predicted GPP for MMSF and Harvard forest was dominated by unsystematic errors suggesting that the results are unbiased. The analysis indicated that maintenance respiration is one of the main factors that dominate the overall model outcome errors and improvement in maintenance respiration estimation

  2. It's the parameters, stupid! Moving beyond multi-model and multi-physics approaches to characterize and reduce predictive uncertainty in process-based hydrological models

    Science.gov (United States)

    Clark, Martyn; Samaniego, Luis; Freer, Jim

    2014-05-01

    Multi-model and multi-physics approaches are a popular tool in environmental modelling, with many studies focusing on optimally combining output from multiple model simulations to reduce predictive errors and better characterize predictive uncertainty. However, a careful and systematic analysis of different hydrological models reveals that individual models are simply small permutations of a master modeling template, and inter-model differences are overwhelmed by uncertainty in the choice of the parameter values in the model equations. Furthermore, inter-model differences do not explicitly represent the uncertainty in modeling a given process, leading to many situations where different models provide the wrong results for the same reasons. In other cases, the available morphological data does not support the very fine spatial discretization of the landscape that typifies many modern applications of process-based models. To make the uncertainty characterization problem worse, the uncertain parameter values in process-based models are often fixed (hard-coded), and the models lack the agility necessary to represent the tremendous heterogeneity in natural systems. This presentation summarizes results from a systematic analysis of uncertainty in process-based hydrological models, where we explicitly analyze the myriad of subjective decisions made throughout both the model development and parameter estimation process. Results show that much of the uncertainty is aleatory in nature - given a "complete" representation of dominant hydrologic processes, uncertainty in process parameterizations can be represented using an ensemble of model parameters. Epistemic uncertainty associated with process interactions and scaling behavior is still important, and these uncertainties can be represented using an ensemble of different spatial configurations. Finally, uncertainty in forcing data can be represented using ensemble methods for spatial meteorological analysis. Our systematic

  3. Difference-based Model Synchronization in an Industrial MDD Process

    DEFF Research Database (Denmark)

    Könemann, Patrick; Kindler, Ekkart; Unland, Ludger

    2009-01-01

    Models play a central role in model-driven software engineering. There are different kinds of models during the development process, which are related to each other and change over time. Therefore, it is difficult to keep the different models consistent with each other. Consistency of different m...... model versions, and for synchronizing other types of models. The main concern is to apply our concepts to an industrial process, in particular keeping usability and performance in mind. Keyword: Model Differencing, Model Merging, Model Synchronization...

  4. Process fault diagnosis using knowledge-based systems

    International Nuclear Information System (INIS)

    Sudduth, A.L.

    1991-01-01

    Advancing technology in process plants has led to increased need for computer based process diagnostic systems to assist the operator. One approach to this problem is to use an embedded knowledge based system to interpret measurement signals. Knowledge based systems using only symptom based rules are inadequate for real time diagnosis of dynamic systems; therefore a model based approach is necessary. Though several forms of model based reasoning have been proposed, the use of qualitative causal models incorporating first principles knowledge of process behavior structure, and function appear to have the most promise as a robust modeling methodology. In this paper the structure of a diagnostic system is described which uses model based reasoning and conventional numerical methods to perform process diagnosis. This system is being applied to emergency diesel generator system in nuclear stations

  5. Erosion risk assessment in the southern Amazon - Data Preprocessing, data base application and process based modelling

    Science.gov (United States)

    Schindewolf, Marcus; Herrmann, Marie-Kristin; Herrmann, Anne-Katrin; Schultze, Nico; Amorim, Ricardo S. S.; Schmidt, Jürgen

    2015-04-01

    The study region along the BR 16 highway belongs to the "Deforestation Arc" at the southern border of the Amazon rainforest. At the same time, it incorporates a land use gradient as colonization started in the 1975-1990 in Central Mato Grosso in 1990 in northern Mato Grosso and most recently in 2004-2005 in southern Pará. Based on present knowledge soil erosion is one of the key driver of soil degradation. Hence, there is a strong need to implement soil erosion control measures in eroding landscapes. Planning and dimensioning of such measures require reliable and detailed information on the temporal and spatial distribution of soil loss, sediment transport and deposition. Soil erosion models are increasingly used, in order to simulate the physical processes involved and to predict the effects of soil erosion control measures. The process based EROSION 3D simulation model is used for surveying soil erosion and deposition on regional catchments. Although EROSION 3D is a widespread, extensively validated model, the application of the model on regional scale remains challenging due to the enormous data requirements and complex data processing operations. In this context the study includes the compilation, validation and generalisation of existing land use and soil data in order to generate a consistent EROSION 3D input datasets. As a part of this process a GIS-linked data base application allows to transfer the original soil and land use data into model specific parameter files. This combined methodology provides different risk assessment maps for certain demands on regional scale. Besides soil loss and sediment transport, sediment pass over points into surface water bodies and particle enrichment can be simulated using the EROSION 3D model. Thus the estimation of particle bound nutrient and pollutant inputs into surface water bodies becomes possible. The study ended up in a user-friendly, timesaving and improved software package for the simulation of soil loss and

  6. Comparing statistical and process-based flow duration curve models in ungauged basins and changing rain regimes

    Science.gov (United States)

    Müller, M. F.; Thompson, S. E.

    2016-02-01

    The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash-Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drivers of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by frequent wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are favored over statistical models.

  7. Testing a Dual Process Model of Gender-Based Violence: A Laboratory Examination.

    Science.gov (United States)

    Berke, Danielle S; Zeichner, Amos

    2016-01-01

    The dire impact of gender-based violence on society compels development of models comprehensive enough to capture the diversity of its forms. Research has established hostile sexism (HS) as a robust predictor of gender-based violence. However, to date, research has yet to link men's benevolent sexism (BS) to physical aggression toward women, despite correlations between BS and HS and between BS and victim blaming. One model, the opposing process model of benevolent sexism (Sibley & Perry, 2010), suggests that, for men, BS acts indirectly through HS to predict acceptance of hierarchy-enhancing social policy as an expression of a preference for in-group dominance (i. e., social dominance orientation [SDO]). The extent to which this model applies to gender-based violence remains untested. Therefore, in this study, 168 undergraduate men in a U. S. university participated in a competitive reaction time task, during which they had the option to shock an ostensible female opponent as a measure of gender-based violence. Results of multiple-mediation path analyses indicated dual pathways potentiating gender-based violence and highlight SDO as a particularly potent mechanism of this violence. Findings are discussed in terms of group dynamics and norm-based violence prevention.

  8. Model-based Prognostics with Concurrent Damage Progression Processes

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based prognostics approaches rely on physics-based models that describe the behavior of systems and their components. These models must account for the several...

  9. Estimation of the PCR efficiency based on a size-dependent modelling of the amplification process

    NARCIS (Netherlands)

    Lalam, N.; Jacob, C.; Jagers, P.

    2005-01-01

    We propose a stochastic modelling of the PCR amplification process by a size-dependent branching process starting as a supercritical Bienaymé–Galton–Watson transient phase and then having a saturation near-critical size-dependent phase. This model based on the concept of saturation allows one to

  10. Flexible software process lines in practice: A metamodel-based approach to effectively construct and manage families of software process models

    DEFF Research Database (Denmark)

    Kuhrmann, Marco; Ternité, Thomas; Friedrich, Jan

    2017-01-01

    Process flexibility and adaptability is frequently discussed, and several proposals aim to improve software processes for a given organization-/project context. A software process line (SPrL) is an instrument to systematically construct and manage variable software processes, by combining pre-def......: A metamodel-based approach to effectively construct and manage families of software process models [Ku16]. This paper was published as original research article in the Journal of Systems and Software.......Process flexibility and adaptability is frequently discussed, and several proposals aim to improve software processes for a given organization-/project context. A software process line (SPrL) is an instrument to systematically construct and manage variable software processes, by combining pre...... to construct flexible SPrLs and show its practical application in the German V-Modell XT. We contribute a proven approach that is presented as metamodel fragment for reuse and implementation in further process modeling approaches. This summary refers to the paper Flexible software process lines in practice...

  11. A generalized logarithmic image processing model based on the gigavision sensor model.

    Science.gov (United States)

    Deng, Guang

    2012-03-01

    The logarithmic image processing (LIP) model is a mathematical theory providing generalized linear operations for image processing. The gigavision sensor (GVS) is a new imaging device that can be described by a statistical model. In this paper, by studying these two seemingly unrelated models, we develop a generalized LIP (GLIP) model. With the LIP model being its special case, the GLIP model not only provides new insights into the LIP model but also defines new image representations and operations for solving general image processing problems that are not necessarily related to the GVS. A new parametric LIP model is also developed. To illustrate the application of the new scalar multiplication operation, we propose an energy-preserving algorithm for tone mapping, which is a necessary step in image dehazing. By comparing with results using two state-of-the-art algorithms, we show that the new scalar multiplication operation is an effective tool for tone mapping.

  12. Designing the database for a reliability aware Model-Based System Engineering process

    International Nuclear Information System (INIS)

    Cressent, Robin; David, Pierre; Idasiak, Vincent; Kratz, Frederic

    2013-01-01

    This article outlines the need for a reliability database to implement model-based description of components failure modes and dysfunctional behaviors. We detail the requirements such a database should honor and describe our own solution: the Dysfunctional Behavior Database (DBD). Through the description of its meta-model, the benefits of integrating the DBD in the system design process is highlighted. The main advantages depicted are the possibility to manage feedback knowledge at various granularity and semantic levels and to ease drastically the interactions between system engineering activities and reliability studies. The compliance of the DBD with other reliability database such as FIDES is presented and illustrated. - Highlights: ► Model-Based System Engineering is more and more used in the industry. ► It results in a need for a reliability database able to deal with model-based description of dysfunctional behavior. ► The Dysfunctional Behavior Database aims to fulfill that need. ► It helps dealing with feedback management thanks to its structured meta-model. ► The DBD can profit from other reliability database such as FIDES.

  13. Quasilinear Extreme Learning Machine Model Based Internal Model Control for Nonlinear Process

    Directory of Open Access Journals (Sweden)

    Dazi Li

    2015-01-01

    Full Text Available A new strategy for internal model control (IMC is proposed using a regression algorithm of quasilinear model with extreme learning machine (QL-ELM. Aimed at the chemical process with nonlinearity, the learning process of the internal model and inverse model is derived. The proposed QL-ELM is constructed as a linear ARX model with a complicated nonlinear coefficient. It shows some good approximation ability and fast convergence. The complicated coefficients are separated into two parts. The linear part is determined by recursive least square (RLS, while the nonlinear part is identified through extreme learning machine. The parameters of linear part and the output weights of ELM are estimated iteratively. The proposed internal model control is applied to CSTR process. The effectiveness and accuracy of the proposed method are extensively verified through numerical results.

  14. [Modeling a clinical process for differentiated thyroid cancer health care in Hospital Base Valdivia, Chile].

    Science.gov (United States)

    Ávila-Schwerter, C; Torres-Andrade, M C; Méndez, C A; Márquez-Manzano, M

    2016-01-01

    To design a clinical process model in the management of differentiated thyroid cancer in order to improve accessibility to this treatment. Based on modified Participatory Action Research, a model design process was conducted using a literature review and meetings with organisations committed to the redesigning process, and to agree an improved and feasible process. The process map was constructed by participatory action including, characterisation of the value chain, fault detection in the flow of the process, relevant documents and process for proposing modifications and approvals necessary for this purpose. Links were established between the main process and the support and strategic processes. The participatory model helped to cut the waiting times for diagnosis and treatment of this disease from 12 to 4 months. For each unit to be able to fully visualise the map of the process and understand their contribution as a set of integrated contributions and not fragmented, helps in the comprehensive management of patients and operation processes based on the hierarchical and dominant organisational model in Chilean hospitals. To analyse and remodel clinical processes by participatory action helps to limit failures in the fluidity of care of the patients, by presenting each participating unit with a general view of the process, the problems, and the possible solutions. Furthermore, this approach helps to clarify the process in order to make it more efficient, to harmonise relationships, and to improve coordination in order to optimise patient care. Copyright © 2015 SECA. Publicado por Elsevier España, S.L.U. All rights reserved.

  15. An overview of current applications, challenges, and future trends in distributed process-based models in hydrology

    Science.gov (United States)

    Fatichi, Simone; Vivoni, Enrique R.; Odgen, Fred L; Ivanov, Valeriy Y; Mirus, Benjamin B.; Gochis, David; Downer, Charles W; Camporese, Matteo; Davison, Jason H; Ebel, Brian A.; Jones, Norm; Kim, Jongho; Mascaro, Giuseppe; Niswonger, Richard G.; Restrepo, Pedro; Rigon, Riccardo; Shen, Chaopeng; Sulis, Mauro; Tarboton, David

    2016-01-01

    Process-based hydrological models have a long history dating back to the 1960s. Criticized by some as over-parameterized, overly complex, and difficult to use, a more nuanced view is that these tools are necessary in many situations and, in a certain class of problems, they are the most appropriate type of hydrological model. This is especially the case in situations where knowledge of flow paths or distributed state variables and/or preservation of physical constraints is important. Examples of this include: spatiotemporal variability of soil moisture, groundwater flow and runoff generation, sediment and contaminant transport, or when feedbacks among various Earth’s system processes or understanding the impacts of climate non-stationarity are of primary concern. These are situations where process-based models excel and other models are unverifiable. This article presents this pragmatic view in the context of existing literature to justify the approach where applicable and necessary. We review how improvements in data availability, computational resources and algorithms have made detailed hydrological simulations a reality. Avenues for the future of process-based hydrological models are presented suggesting their use as virtual laboratories, for design purposes, and with a powerful treatment of uncertainty.

  16. An overview of current applications, challenges, and future trends in distributed process-based models in hydrology

    Science.gov (United States)

    Fatichi, Simone; Vivoni, Enrique R.; Ogden, Fred L.; Ivanov, Valeriy Y.; Mirus, Benjamin; Gochis, David; Downer, Charles W.; Camporese, Matteo; Davison, Jason H.; Ebel, Brian; Jones, Norm; Kim, Jongho; Mascaro, Giuseppe; Niswonger, Richard; Restrepo, Pedro; Rigon, Riccardo; Shen, Chaopeng; Sulis, Mauro; Tarboton, David

    2016-06-01

    Process-based hydrological models have a long history dating back to the 1960s. Criticized by some as over-parameterized, overly complex, and difficult to use, a more nuanced view is that these tools are necessary in many situations and, in a certain class of problems, they are the most appropriate type of hydrological model. This is especially the case in situations where knowledge of flow paths or distributed state variables and/or preservation of physical constraints is important. Examples of this include: spatiotemporal variability of soil moisture, groundwater flow and runoff generation, sediment and contaminant transport, or when feedbacks among various Earth's system processes or understanding the impacts of climate non-stationarity are of primary concern. These are situations where process-based models excel and other models are unverifiable. This article presents this pragmatic view in the context of existing literature to justify the approach where applicable and necessary. We review how improvements in data availability, computational resources and algorithms have made detailed hydrological simulations a reality. Avenues for the future of process-based hydrological models are presented suggesting their use as virtual laboratories, for design purposes, and with a powerful treatment of uncertainty.

  17. Kinect Posture Reconstruction Based on a Local Mixture of Gaussian Process Models.

    Science.gov (United States)

    Liu, Zhiguang; Zhou, Liuyang; Leung, Howard; Shum, Hubert P H

    2016-11-01

    Depth sensor based 3D human motion estimation hardware such as Kinect has made interactive applications more popular recently. However, it is still challenging to accurately recognize postures from a single depth camera due to the inherently noisy data derived from depth images and self-occluding action performed by the user. In this paper, we propose a new real-time probabilistic framework to enhance the accuracy of live captured postures that belong to one of the action classes in the database. We adopt the Gaussian Process model as a prior to leverage the position data obtained from Kinect and marker-based motion capture system. We also incorporate a temporal consistency term into the optimization framework to constrain the velocity variations between successive frames. To ensure that the reconstructed posture resembles the accurate parts of the observed posture, we embed a set of joint reliability measurements into the optimization framework. A major drawback of Gaussian Process is its cubic learning complexity when dealing with a large database due to the inverse of a covariance matrix. To solve the problem, we propose a new method based on a local mixture of Gaussian Processes, in which Gaussian Processes are defined in local regions of the state space. Due to the significantly decreased sample size in each local Gaussian Process, the learning time is greatly reduced. At the same time, the prediction speed is enhanced as the weighted mean prediction for a given sample is determined by the nearby local models only. Our system also allows incrementally updating a specific local Gaussian Process in real time, which enhances the likelihood of adapting to run-time postures that are different from those in the database. Experimental results demonstrate that our system can generate high quality postures even under severe self-occlusion situations, which is beneficial for real-time applications such as motion-based gaming and sport training.

  18. Fostering Organizational Innovation based on modeling the Marketing Research Process through Event-driven Process Chain (EPC

    Directory of Open Access Journals (Sweden)

    Elena Fleacă

    2016-11-01

    Full Text Available Enterprises competing in an actual business framework are required to win and maintain their competitiveness by flexibility, fast reaction and conformation to the changing customers' needs based on innovation of work related to products, services, and internal processes. The paper addresses these challenges which gain more complex bonds in a case of high pressure for innovation. The methodology commences with a literature review of the current knowledge on innovation through business processes management. Secondly, it has been applied the Event-driven Process Chain tool from the scientific literature to model the variables of marketing research process. The findings highlight benefits of marketing research workflow that enhances the value of market information while reducing costs of obtaining it, in a coherent way.

  19. Physics-based process model approach for detecting discontinuity during friction stir welding

    Energy Technology Data Exchange (ETDEWEB)

    Shrivastava, Amber; Pfefferkorn, Frank E.; Duffie, Neil A.; Ferrier, Nicola J.; Smith, Christopher B.; Malukhin, Kostya; Zinn, Michael

    2015-02-12

    The goal of this work is to develop a method for detecting the creation of discontinuities during friction stir welding. This in situ weld monitoring method could significantly reduce the need for post-process inspection. A process force model and a discontinuity force model were created based on the state-of-the-art understanding of flow around an friction stir welding (FSW) tool. These models are used to predict the FSW forces and size of discontinuities formed in the weld. Friction stir welds with discontinuities and welds without discontinuities were created, and the differences in force dynamics were observed. In this paper, discontinuities were generated by reducing the tool rotation frequency and increasing the tool traverse speed in order to create "cold" welds. Experimental force data for welds with discontinuities and welds without discontinuities compared favorably with the predicted forces. The model currently overpredicts the discontinuity size.

  20. Exploring C-water-temperature interactions and non-linearities in soils through developments in process-based models

    Science.gov (United States)

    Esteban Moyano, Fernando; Vasilyeva, Nadezda; Menichetti, Lorenzo

    2016-04-01

    Soil carbon models developed over the last couple of decades are limited in their capacity to accurately predict the magnitudes and temporal variations in observed carbon fluxes and stocks. New process-based models are now emerging that attempt to address the shortcomings of their more simple, empirical counterparts. While a spectrum of ideas and hypothetical mechanisms are finding their way into new models, the addition of only a few processes known to significantly affect soil carbon (e.g. enzymatic decomposition, adsorption, Michaelis-Menten kinetics) has shown the potential to resolve a number of previous model-data discrepancies (e.g. priming, Birch effects). Through model-data validation, such models are a means of testing hypothetical mechanisms. In addition, they can lead to new insights into what soil carbon pools are and how they respond to external drivers. In this study we develop a model of soil carbon dynamics based on enzymatic decomposition and other key features of process based models, i.e. simulation of carbon in particulate, soluble and adsorbed states, as well as enzyme and microbial components. Here we focus on understanding how moisture affects C decomposition at different levels, both directly (e.g. by limiting diffusion) or through interactions with other components. As the medium where most reactions and transport take place, water is central en every aspect of soil C dynamics. We compare results from a number of alternative models with experimental data in order to test different processes and parameterizations. Among other observations, we try to understand: 1. typical moisture response curves and associated temporal changes, 2. moisture-temperature interactions, and 3. diffusion effects under changing C concentrations. While the model aims at being a process based approach and at simulating fluxes at short time scales, it remains a simplified representation using the same inputs as classical soil C models, and is thus potentially

  1. A Model-based B2B (Batch to Batch) Control for An Industrial Batch Polymerization Process

    Science.gov (United States)

    Ogawa, Morimasa

    This paper describes overview of a model-based B2B (batch to batch) control for an industrial batch polymerization process. In order to control the reaction temperature precisely, several methods based on the rigorous process dynamics model are employed at all design stage of the B2B control, such as modeling and parameter estimation of the reaction kinetics which is one of the important part of the process dynamics model. The designed B2B control consists of the gain scheduled I-PD/II2-PD control (I-PD with double integral control), the feed-forward compensation at the batch start time, and the model adaptation utilizing the results of the last batch operation. Throughout the actual batch operations, the B2B control provides superior control performance compared with that of conventional control methods.

  2. Model-based reasoning and the control of process plants

    International Nuclear Information System (INIS)

    Vaelisuo, Heikki

    1993-02-01

    In addition to feedback control, safe and economic operation of industrial process plants requires discrete-event type logic control like for example automatic control sequences, interlocks, etc. A lot of complex routine reasoning is involved in the design and verification and validation (VandV) of such automatics. Similar reasoning tasks are encountered during plant operation in action planning and fault diagnosis. The low-level part of the required problem solving is so straightforward that it could be accomplished by a computer if only there were plant models which allow versatile mechanised reasoning. Such plant models and corresponding inference algorithms are the main subject of this report. Deep knowledge and qualitative modelling play an essential role in this work. Deep knowledge refers to mechanised reasoning based on the first principles of the phenomena in the problem domain. Qualitative modelling refers to knowledge representation formalism and related reasoning methods which allow solving problems on an abstraction level higher than for example traditional simulation and optimisation. Prolog is a commonly used platform for artificial intelligence (Al) applications. Constraint logic languages like CLP(R) and Prolog-III extend the scope of logic programming to numeric problem solving. In addition they allow a programming style which often reduces the computational complexity significantly. An approach to model-based reasoning implemented in constraint logic programming language CLP(R) is presented. The approach is based on some of the principles of QSIM, an algorithm for qualitative simulation. It is discussed how model-based reasoning can be applied in the design and VandV of plant automatics and in action planning during plant operation. A prototype tool called ISIR is discussed and some initial results obtained during the development of the tool are presented. The results presented originate from preliminary test results of the prototype obtained

  3. Mathematical Foundation Based Inter-Connectivity modelling of Thermal Image processing technique for Fire Protection

    Directory of Open Access Journals (Sweden)

    Sayantan Nath

    2015-09-01

    Full Text Available In this paper, integration between multiple functions of image processing and its statistical parameters for intelligent alarming series based fire detection system is presented. The proper inter-connectivity mapping between processing elements of imagery based on classification factor for temperature monitoring and multilevel intelligent alarm sequence is introduced by abstractive canonical approach. The flow of image processing components between core implementation of intelligent alarming system with temperature wise area segmentation as well as boundary detection technique is not yet fully explored in the present era of thermal imaging. In the light of analytical perspective of convolutive functionalism in thermal imaging, the abstract algebra based inter-mapping model between event-calculus supported DAGSVM classification for step-by-step generation of alarm series with gradual monitoring technique and segmentation of regions with its affected boundaries in thermographic image of coal with respect to temperature distinctions is discussed. The connectedness of the multifunctional operations of image processing based compatible fire protection system with proper monitoring sequence is presently investigated here. The mathematical models representing the relation between the temperature affected areas and its boundary in the obtained thermal image defined in partial derivative fashion is the core contribution of this study. The thermal image of coal sample is obtained in real-life scenario by self-assembled thermographic camera in this study. The amalgamation between area segmentation, boundary detection and alarm series are described in abstract algebra. The principal objective of this paper is to understand the dependency pattern and the principles of working of image processing components and structure an inter-connected modelling technique also for those components with the help of mathematical foundation.

  4. Physics-based simulation modeling and optimization of microstructural changes induced by machining and selective laser melting processes in titanium and nickel based alloys

    Science.gov (United States)

    Arisoy, Yigit Muzaffer

    Manufacturing processes may significantly affect the quality of resultant surfaces and structural integrity of the metal end products. Controlling manufacturing process induced changes to the product's surface integrity may improve the fatigue life and overall reliability of the end product. The goal of this study is to model the phenomena that result in microstructural alterations and improve the surface integrity of the manufactured parts by utilizing physics-based process simulations and other computational methods. Two different (both conventional and advanced) manufacturing processes; i.e. machining of Titanium and Nickel-based alloys and selective laser melting of Nickel-based powder alloys are studied. 3D Finite Element (FE) process simulations are developed and experimental data that validates these process simulation models are generated to compare against predictions. Computational process modeling and optimization have been performed for machining induced microstructure that includes; i) predicting recrystallization and grain size using FE simulations and the Johnson-Mehl-Avrami-Kolmogorov (JMAK) model, ii) predicting microhardness using non-linear regression models and the Random Forests method, and iii) multi-objective machining optimization for minimizing microstructural changes. Experimental analysis and computational process modeling of selective laser melting have been also conducted including; i) microstructural analysis of grain sizes and growth directions using SEM imaging and machine learning algorithms, ii) analysis of thermal imaging for spattering, heating/cooling rates and meltpool size, iii) predicting thermal field, meltpool size, and growth directions via thermal gradients using 3D FE simulations, iv) predicting localized solidification using the Phase Field method. These computational process models and predictive models, once utilized by industry to optimize process parameters, have the ultimate potential to improve performance of

  5. The Process Model of Group-Based Emotion: Integrating Intergroup Emotion and Emotion Regulation Perspectives.

    Science.gov (United States)

    Goldenberg, Amit; Halperin, Eran; van Zomeren, Martijn; Gross, James J

    2016-05-01

    Scholars interested in emotion regulation have documented the different goals and strategies individuals have for regulating their emotions. However, little attention has been paid to the regulation of group-based emotions, which are based on individuals' self-categorization as a group member and occur in response to situations perceived as relevant for that group. We propose a model for examining group-based emotion regulation that integrates intergroup emotions theory and the process model of emotion regulation. This synergy expands intergroup emotion theory by facilitating further investigation of different goals (i.e., hedonic or instrumental) and strategies (e.g., situation selection and modification strategies) used to regulate group-based emotions. It also expands emotion regulation research by emphasizing the role of self-categorization (e.g., as an individual or a group member) in the emotional process. Finally, we discuss the promise of this theoretical synergy and suggest several directions for future research on group-based emotion regulation. © 2015 by the Society for Personality and Social Psychology, Inc.

  6. Dynamic flowgraph modeling of process and control systems of a nuclear-based hydrogen production plant

    Energy Technology Data Exchange (ETDEWEB)

    Al-Dabbagh, Ahmad W. [Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario (Canada); Lu, Lixuan [Faculty of Energy Systems and Nuclear Science, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario (Canada)

    2010-09-15

    Modeling and analysis of system reliability facilitate the identification of areas of potential improvement. The Dynamic Flowgraph Methodology (DFM) is an emerging discrete modeling framework that allows for capturing time dependent behaviour, switching logic and multi-state representation of system components. The objective of this research is to demonstrate the process of dynamic flowgraph modeling of a nuclear-based hydrogen production plant with the copper-chlorine (Cu-Cl) cycle. Modeling of the thermochemical process of the Cu-Cl cycle in conjunction with a networked control system proposed for monitoring and control of the process is provided. This forms the basis for future component selection. (author)

  7. EvoBuild: A Quickstart Toolkit for Programming Agent-Based Models of Evolutionary Processes

    Science.gov (United States)

    Wagh, Aditi; Wilensky, Uri

    2018-04-01

    Extensive research has shown that one of the benefits of programming to learn about scientific phenomena is that it facilitates learning about mechanisms underlying the phenomenon. However, using programming activities in classrooms is associated with costs such as requiring additional time to learn to program or students needing prior experience with programming. This paper presents a class of programming environments that we call quickstart: Environments with a negligible threshold for entry into programming and a modest ceiling. We posit that such environments can provide benefits of programming for learning without incurring associated costs for novice programmers. To make this claim, we present a design-based research study conducted to compare programming models of evolutionary processes with a quickstart toolkit with exploring pre-built models of the same processes. The study was conducted in six seventh grade science classes in two schools. Students in the programming condition used EvoBuild, a quickstart toolkit for programming agent-based models of evolutionary processes, to build their NetLogo models. Students in the exploration condition used pre-built NetLogo models. We demonstrate that although students came from a range of academic backgrounds without prior programming experience, and all students spent the same number of class periods on the activities including the time students took to learn programming in this environment, EvoBuild students showed greater learning about evolutionary mechanisms. We discuss the implications of this work for design research on programming environments in K-12 science education.

  8. CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

    Science.gov (United States)

    Rose, B. E. J.

    2015-12-01

    Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling.

  9. Ab initio assisted process modeling for Si-based nanoelectronic devices

    International Nuclear Information System (INIS)

    Windl, Wolfgang

    2005-01-01

    In this paper, we discuss concepts and examples of ab initio calculations assisting physics-based process simulation. We focus on how to determine diffusion and reaction constants, where modern methods such as the nudged elastic band method allow a systematic and reliable search for the minimum energy migration path and barrier. We show that once the saddle point is determined, the underlying harmonic transition state theory also allows to calculate the prefactors. The discussed examples include nitrogen diffusion, boron deactivation and boron interface segregation. Finally, some concepts are discussed for future device technologies such as molecular devices, where the currently prevalent multiscale approach (kinetic parameters used in higher level models like diffusion-reaction or kinetic Monte Carlo modeling) would not be sensible anymore. As an example, we described the ab initio temperature-accelerated dynamics modeling of contact formation in carbon nanotube devices

  10. Quantum-like model of processing of information in the brain based on classical electromagnetic field.

    Science.gov (United States)

    Khrennikov, Andrei

    2011-09-01

    We propose a model of quantum-like (QL) processing of mental information. This model is based on quantum information theory. However, in contrast to models of "quantum physical brain" reducing mental activity (at least at the highest level) to quantum physical phenomena in the brain, our model matches well with the basic neuronal paradigm of the cognitive science. QL information processing is based (surprisingly) on classical electromagnetic signals induced by joint activity of neurons. This novel approach to quantum information is based on representation of quantum mechanics as a version of classical signal theory which was recently elaborated by the author. The brain uses the QL representation (QLR) for working with abstract concepts; concrete images are described by classical information theory. Two processes, classical and QL, are performed parallely. Moreover, information is actively transmitted from one representation to another. A QL concept given in our model by a density operator can generate a variety of concrete images given by temporal realizations of the corresponding (Gaussian) random signal. This signal has the covariance operator coinciding with the density operator encoding the abstract concept under consideration. The presence of various temporal scales in the brain plays the crucial role in creation of QLR in the brain. Moreover, in our model electromagnetic noise produced by neurons is a source of superstrong QL correlations between processes in different spatial domains in the brain; the binding problem is solved on the QL level, but with the aid of the classical background fluctuations. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  11. Model and system learners, optimal process constructors and kinetic theory-based goal-oriented design: A new paradigm in materials and processes informatics

    Science.gov (United States)

    Abisset-Chavanne, Emmanuelle; Duval, Jean Louis; Cueto, Elias; Chinesta, Francisco

    2018-05-01

    Traditionally, Simulation-Based Engineering Sciences (SBES) has relied on the use of static data inputs (model parameters, initial or boundary conditions, … obtained from adequate experiments) to perform simulations. A new paradigm in the field of Applied Sciences and Engineering has emerged in the last decade. Dynamic Data-Driven Application Systems [9, 10, 11, 12, 22] allow the linkage of simulation tools with measurement devices for real-time control of simulations and applications, entailing the ability to dynamically incorporate additional data into an executing application, and in reverse, the ability of an application to dynamically steer the measurement process. It is in that context that traditional "digital-twins" are giving raise to a new generation of goal-oriented data-driven application systems, also known as "hybrid-twins", embracing models based on physics and models exclusively based on data adequately collected and assimilated for filling the gap between usual model predictions and measurements. Within this framework new methodologies based on model learners, machine learning and kinetic goal-oriented design are defining a new paradigm in materials, processes and systems engineering.

  12. A novel model-based control strategy for aerobic filamentous fungal fed-batch fermentation processes

    DEFF Research Database (Denmark)

    Mears, Lisa; Stocks, Stuart M.; Albaek, Mads O.

    2017-01-01

    A novel model-based control strategy has been developed for filamentous fungal fed-batch fermentation processes. The system of interest is a pilot scale (550 L) filamentous fungus process operating at Novozymes A/S. In such processes, it is desirable to maximize the total product achieved...... is recursively updated using on-line measurements. The model was applied in order to predict the current system states, including the biomass concentration, and to simulate the expected future trajectory of the system until a specified end time. In this way, the desired feed rate is updated along the progress...

  13. Process-based modelling of NH3 exchange with grazed grasslands

    Science.gov (United States)

    Móring, Andrea; Vieno, Massimo; Doherty, Ruth M.; Milford, Celia; Nemitz, Eiko; Twigg, Marsailidh M.; Horváth, László; Sutton, Mark A.

    2017-09-01

    In this study the GAG model, a process-based ammonia (NH3) emission model for urine patches, was extended and applied for the field scale. The new model (GAG_field) was tested over two modelling periods, for which micrometeorological NH3 flux data were available. Acknowledging uncertainties in the measurements, the model was able to simulate the main features of the observed fluxes. The temporal evolution of the simulated NH3 exchange flux was found to be dominated by NH3 emission from the urine patches, offset by simultaneous NH3 deposition to areas of the field not affected by urine. The simulations show how NH3 fluxes over a grazed field in a given day can be affected by urine patches deposited several days earlier, linked to the interaction of volatilization processes with soil pH dynamics. Sensitivity analysis showed that GAG_field was more sensitive to soil buffering capacity (β), field capacity (θfc) and permanent wilting point (θpwp) than the patch-scale model. The reason for these different sensitivities is dual. Firstly, the difference originates from the different scales. Secondly, the difference can be explained by the different initial soil pH and physical properties, which determine the maximum volume of urine that can be stored in the NH3 source layer. It was found that in the case of urine patches with a higher initial soil pH and higher initial soil water content, the sensitivity of NH3 exchange to β was stronger. Also, in the case of a higher initial soil water content, NH3 exchange was more sensitive to the changes in θfc and θpwp. The sensitivity analysis showed that the nitrogen content of urine (cN) is associated with high uncertainty in the simulated fluxes. However, model experiments based on cN values randomized from an estimated statistical distribution indicated that this uncertainty is considerably smaller in practice. Finally, GAG_field was tested with a constant soil pH of 7.5. The variation of NH3 fluxes simulated in this way

  14. The Structured Process Modeling Theory (SPMT) : a cognitive view on why and how modelers benefit from structuring the process of process modeling

    NARCIS (Netherlands)

    Claes, J.; Vanderfeesten, I.T.P.; Gailly, F.; Grefen, P.W.P.J.; Poels, G.

    2015-01-01

    After observing various inexperienced modelers constructing a business process model based on the same textual case description, it was noted that great differences existed in the quality of the produced models. The impression arose that certain quality issues originated from cognitive failures

  15. Model-free stochastic processes studied with q-wavelet-based informational tools

    International Nuclear Information System (INIS)

    Perez, D.G.; Zunino, L.; Martin, M.T.; Garavaglia, M.; Plastino, A.; Rosso, O.A.

    2007-01-01

    We undertake a model-free investigation of stochastic processes employing q-wavelet based quantifiers, that constitute a generalization of their Shannon counterparts. It is shown that (i) interesting physical information becomes accessible in such a way (ii) for special q values the quantifiers are more sensitive than the Shannon ones and (iii) there exist an implicit relationship between the Hurst parameter H and q within this wavelet framework

  16. Sustainable Manufacturing via Multi-Scale, Physics-Based Process Modeling and Manufacturing-Informed Design

    Energy Technology Data Exchange (ETDEWEB)

    None

    2017-04-01

    This factsheet describes a project that developed and demonstrated a new manufacturing-informed design framework that utilizes advanced multi-scale, physics-based process modeling to dramatically improve manufacturing productivity and quality in machining operations while reducing the cost of machined components.

  17. WWTP Process Tank Modelling

    DEFF Research Database (Denmark)

    Laursen, Jesper

    The present thesis considers numerical modeling of activated sludge tanks on municipal wastewater treatment plants. Focus is aimed at integrated modeling where the detailed microbiological model the Activated Sludge Model 3 (ASM3) is combined with a detailed hydrodynamic model based on a numerical...... solution of the Navier-Stokes equations in a multiphase scheme. After a general introduction to the activated sludge tank as a system, the activated sludge tank model is gradually setup in separate stages. The individual sub-processes that are often occurring in activated sludge tanks are initially...... hydrofoil shaped propellers. These two sub-processes deliver the main part of the supplied energy to the activated sludge tank, and for this reason they are important for the mixing conditions in the tank. For other important processes occurring in the activated sludge tank, existing models and measurements...

  18. Time series modeling by a regression approach based on a latent process.

    Science.gov (United States)

    Chamroukhi, Faicel; Samé, Allou; Govaert, Gérard; Aknin, Patrice

    2009-01-01

    Time series are used in many domains including finance, engineering, economics and bioinformatics generally to represent the change of a measurement over time. Modeling techniques may then be used to give a synthetic representation of such data. A new approach for time series modeling is proposed in this paper. It consists of a regression model incorporating a discrete hidden logistic process allowing for activating smoothly or abruptly different polynomial regression models. The model parameters are estimated by the maximum likelihood method performed by a dedicated Expectation Maximization (EM) algorithm. The M step of the EM algorithm uses a multi-class Iterative Reweighted Least-Squares (IRLS) algorithm to estimate the hidden process parameters. To evaluate the proposed approach, an experimental study on simulated data and real world data was performed using two alternative approaches: a heteroskedastic piecewise regression model using a global optimization algorithm based on dynamic programming, and a Hidden Markov Regression Model whose parameters are estimated by the Baum-Welch algorithm. Finally, in the context of the remote monitoring of components of the French railway infrastructure, and more particularly the switch mechanism, the proposed approach has been applied to modeling and classifying time series representing the condition measurements acquired during switch operations.

  19. Model-based Computer Aided Framework for Design of Process Monitoring and Analysis Systems

    DEFF Research Database (Denmark)

    Singh, Ravendra; Gernaey, Krist; Gani, Rafiqul

    2009-01-01

    In the manufacturing industry, for example, the pharmaceutical industry, a thorough understanding of the process is necessary in addition to a properly designed monitoring and analysis system (PAT system) to consistently obtain the desired end-product properties. A model-based computer....... The knowledge base provides the necessary information/data during the design of the PAT system while the model library generates additional or missing data needed for design and analysis. Optimization of the PAT system design is achieved in terms of product data analysis time and/or cost of monitoring equipment......-aided framework including the methods and tools through which the design of monitoring and analysis systems for product quality control can be generated, analyzed and/or validated, has been developed. Two important supporting tools developed as part of the framework are a knowledge base and a model library...

  20. Applying the Business Process and Practice Alignment Meta-model: Daily Practices and Process Modelling

    Directory of Open Access Journals (Sweden)

    Ventura Martins Paula

    2017-03-01

    Full Text Available Background: Business Process Modelling (BPM is one of the most important phases of information system design. Business Process (BP meta-models allow capturing informational and behavioural aspects of business processes. Unfortunately, standard BP meta-modelling approaches focus just on process description, providing different BP models. It is not possible to compare and identify related daily practices in order to improve BP models. This lack of information implies that further research in BP meta-models is needed to reflect the evolution/change in BP. Considering this limitation, this paper introduces a new BP meta-model designed by Business Process and Practice Alignment Meta-model (BPPAMeta-model. Our intention is to present a meta-model that addresses features related to the alignment between daily work practices and BP descriptions. Objectives: This paper intends to present a metamodel which is going to integrate daily work information into coherent and sound process definitions. Methods/Approach: The methodology employed in the research follows a design-science approach. Results: The results of the case study are related to the application of the proposed meta-model to align the specification of a BP model with work practices models. Conclusions: This meta-model can be used within the BPPAM methodology to specify or improve business processes models based on work practice descriptions.

  1. Ares Upper Stage Processes to Implement Model Based Design - Going Paperless

    Science.gov (United States)

    Gregory, Melanie

    2012-01-01

    Computer-Aided Design (CAD) has all but replaced the drafting board for design work. Increased productivity and accuracy should be natural outcomes of using CAD. Going from paper drawings only to paper drawings based on CAD models to CAD models and no drawings, or Model Based Design (MBD), is a natural progression in today?s world. There are many advantages to MBD over traditional design methods. To make the most of those advantages, standards should be in place and the proper foundation should be laid prior to transitioning to MBD. However, without a full understanding of the implications of MBD and the proper control of the data, the advantages are greatly diminished. Transitioning from a paper design world to an electronic design world means re-thinking how information gets controlled at its origin and distributed from one point to another. It means design methodology is critical, especially for large projects. It means preparation of standardized parts and processes as well as strong communication between all parties in order to maximize the benefits of MBD.

  2. Optimization Model for Uncertain Statistics Based on an Analytic Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Yongchao Hou

    2014-01-01

    Full Text Available Uncertain statistics is a methodology for collecting and interpreting the expert’s experimental data by uncertainty theory. In order to estimate uncertainty distributions, an optimization model based on analytic hierarchy process (AHP and interpolation method is proposed in this paper. In addition, the principle of least squares method is presented to estimate uncertainty distributions with known functional form. Finally, the effectiveness of this method is illustrated by an example.

  3. Modelling continuous pharmaceutical and bio-based processes at plant-wide level: A roadmap towards efficient decision-making

    DEFF Research Database (Denmark)

    Ramin, Pedram; Mansouri, Seyed Soheil; Udugama, Isuru A.

    2018-01-01

    The importance of developing simulation models for decision making in pharmaceutical and bio-based production processes is elaborated in this article. The advantages of modelling continuous processes are outlined and certain barriers in this regard are identified. Although there have been some...

  4. A geomorphology-based ANFIS model for multi-station modeling of rainfall-runoff process

    Science.gov (United States)

    Nourani, Vahid; Komasi, Mehdi

    2013-05-01

    This paper demonstrates the potential use of Artificial Intelligence (AI) techniques for predicting daily runoff at multiple gauging stations. Uncertainty and complexity of the rainfall-runoff process due to its variability in space and time in one hand and lack of historical data on the other hand, cause difficulties in the spatiotemporal modeling of the process. In this paper, an Integrated Geomorphological Adaptive Neuro-Fuzzy Inference System (IGANFIS) model conjugated with C-means clustering algorithm was used for rainfall-runoff modeling at multiple stations of the Eel River watershed, California. The proposed model could be used for predicting runoff in the stations with lack of data or any sub-basin within the watershed because of employing the spatial and temporal variables of the sub-basins as the model inputs. This ability of the integrated model for spatiotemporal modeling of the process was examined through the cross validation technique for a station. In this way, different ANFIS structures were trained using Sugeno algorithm in order to estimate daily discharge values at different stations. In order to improve the model efficiency, the input data were then classified into some clusters by the means of fuzzy C-means (FCMs) method. The goodness-of-fit measures support the gainful use of the IGANFIS and FCM methods in spatiotemporal modeling of hydrological processes.

  5. Thermo-mechanical modeling of the obduction process based on the Oman ophiolite case

    OpenAIRE

    Duretz , Thibault; Agard , Philippe; Yamato , Philippe; Ducassou , Céline; Burov , Evgenii ,; Gerya , T. V.

    2016-01-01

    International audience; Obduction emplaces regional-scale fragments of oceanic lithosphere (ophiolites) over continental lithosphere margins of much lower density. For this reason, the mechanisms responsible for obduction remain enigmatic in the framework of plate tectonics. We present two-dimensional (2D) thermo-mechanical models of obduction and investigate possible dynamics and physical controls of this process. Model geometry and boundary conditions are based on available geological and g...

  6. Unifying Model-Based and Reactive Programming within a Model-Based Executive

    Science.gov (United States)

    Williams, Brian C.; Gupta, Vineet; Norvig, Peter (Technical Monitor)

    1999-01-01

    Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.

  7. Real-Time Model Based Process Monitoring of Enzymatic Biodiesel Production

    DEFF Research Database (Denmark)

    Price, Jason Anthony; Nordblad, Mathias; Woodley, John

    2015-01-01

    In this contribution we extend our modelling work on the enzymatic production of biodiesel where we demonstrate the application of a Continuous-Discrete Extended Kalman Filter (a state estimator). The state estimator is used to correct for mismatch between the process data and the process model...... for Fed-batch production of biodiesel. For the three process runs investigated, using a single tuning parameter, qx=2 x 10-2 which represents the uncertainty in the process model, it was possible over the entire course of the reaction to reduce the overall mean and standard deviation of the error between......, there was over a ten-fold decrease in the overall mean error for the state estimator prediction compared with the predictions from the pure model simulations. It is also shown that the state estimator can be used as a tool for detection of outliers in the measurement data. For the enzymatic biodiesel process...

  8. Advanced autonomous model-based operation of industrial process systems (Autoprofit) : technological developments and future perspectives

    NARCIS (Netherlands)

    Ozkan, L.; Bombois, X.J.A.; Ludlage, J.H.A.; Rojas, C.R.; Hjalmarsson, H.; Moden, P.E.; Lundh, M.; Backx, A.C.P.M.; Van den Hof, P.M.J.

    2016-01-01

    Model-based operation support technology such as Model Predictive Control (MPC) is a proven and accepted technology for multivariable and constrained large scale control problems in process industry. Despite the growing number of successful implementations, the low level of operational efficiency of

  9. Modeling of yield and environmental impact categories in tea processing units based on artificial neural networks.

    Science.gov (United States)

    Khanali, Majid; Mobli, Hossein; Hosseinzadeh-Bandbafha, Homa

    2017-12-01

    In this study, an artificial neural network (ANN) model was developed for predicting the yield and life cycle environmental impacts based on energy inputs required in processing of black tea, green tea, and oolong tea in Guilan province of Iran. A life cycle assessment (LCA) approach was used to investigate the environmental impact categories of processed tea based on the cradle to gate approach, i.e., from production of input materials using raw materials to the gate of tea processing units, i.e., packaged tea. Thus, all the tea processing operations such as withering, rolling, fermentation, drying, and packaging were considered in the analysis. The initial data were obtained from tea processing units while the required data about the background system was extracted from the EcoInvent 2.2 database. LCA results indicated that diesel fuel and corrugated paper box used in drying and packaging operations, respectively, were the main hotspots. Black tea processing unit caused the highest pollution among the three processing units. Three feed-forward back-propagation ANN models based on Levenberg-Marquardt training algorithm with two hidden layers accompanied by sigmoid activation functions and a linear transfer function in output layer, were applied for three types of processed tea. The neural networks were developed based on energy equivalents of eight different input parameters (energy equivalents of fresh tea leaves, human labor, diesel fuel, electricity, adhesive, carton, corrugated paper box, and transportation) and 11 output parameters (yield, global warming, abiotic depletion, acidification, eutrophication, ozone layer depletion, human toxicity, freshwater aquatic ecotoxicity, marine aquatic ecotoxicity, terrestrial ecotoxicity, and photochemical oxidation). The results showed that the developed ANN models with R 2 values in the range of 0.878 to 0.990 had excellent performance in predicting all the output variables based on inputs. Energy consumption for

  10. Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating.

    Science.gov (United States)

    Lu, Xiaoman; Zheng, Guang; Miller, Colton; Alvarado, Ernesto

    2017-09-08

    Monitoring and understanding the spatio-temporal variations of forest aboveground biomass (AGB) is a key basis to quantitatively assess the carbon sequestration capacity of a forest ecosystem. To map and update forest AGB in the Greater Khingan Mountains (GKM) of China, this work proposes a physical-based approach. Based on the baseline forest AGB from Landsat Enhanced Thematic Mapper Plus (ETM+) images in 2008, we dynamically updated the annual forest AGB from 2009 to 2012 by adding the annual AGB increment (ABI) obtained from the simulated daily and annual net primary productivity (NPP) using the Boreal Ecosystem Productivity Simulator (BEPS) model. The 2012 result was validated by both field- and aerial laser scanning (ALS)-based AGBs. The predicted forest AGB for 2012 estimated from the process-based model can explain 31% ( n = 35, p forest AGBs, respectively. However, due to the saturation of optical remote sensing-based spectral signals and contribution of understory vegetation, the BEPS-based AGB tended to underestimate/overestimate the AGB for dense/sparse forests. Generally, our results showed that the remotely sensed forest AGB estimates could serve as the initial carbon pool to parameterize the process-based model for NPP simulation, and the combination of the baseline forest AGB and BEPS model could effectively update the spatiotemporal distribution of forest AGB.

  11. Stochastic Interest Model Based on Compound Poisson Process and Applications in Actuarial Science

    OpenAIRE

    Li, Shilong; Yin, Chuancun; Zhao, Xia; Dai, Hongshuai

    2017-01-01

    Considering stochastic behavior of interest rates in financial market, we construct a new class of interest models based on compound Poisson process. Different from the references, this paper describes the randomness of interest rates by modeling the force of interest with Poisson random jumps directly. To solve the problem in calculation of accumulated interest force function, one important integral technique is employed. And a conception called the critical value is introduced to investigat...

  12. How does higher frequency monitoring data affect the calibration of a process-based water quality model?

    Science.gov (United States)

    Jackson-Blake, Leah; Helliwell, Rachel

    2015-04-01

    Process-based catchment water quality models are increasingly used as tools to inform land management. However, for such models to be reliable they need to be well calibrated and shown to reproduce key catchment processes. Calibration can be challenging for process-based models, which tend to be complex and highly parameterised. Calibrating a large number of parameters generally requires a large amount of monitoring data, spanning all hydrochemical conditions. However, regulatory agencies and research organisations generally only sample at a fortnightly or monthly frequency, even in well-studied catchments, often missing peak flow events. The primary aim of this study was therefore to investigate how the quality and uncertainty of model simulations produced by a process-based, semi-distributed catchment model, INCA-P (the INtegrated CAtchment model of Phosphorus dynamics), were improved by calibration to higher frequency water chemistry data. Two model calibrations were carried out for a small rural Scottish catchment: one using 18 months of daily total dissolved phosphorus (TDP) concentration data, another using a fortnightly dataset derived from the daily data. To aid comparability, calibrations were carried out automatically using the Markov Chain Monte Carlo - DiffeRential Evolution Adaptive Metropolis (MCMC-DREAM) algorithm. Calibration to daily data resulted in improved simulation of peak TDP concentrations and improved model performance statistics. Parameter-related uncertainty in simulated TDP was large when fortnightly data was used for calibration, with a 95% credible interval of 26 μg/l. This uncertainty is comparable in size to the difference between Water Framework Directive (WFD) chemical status classes, and would therefore make it difficult to use this calibration to predict shifts in WFD status. The 95% credible interval reduced markedly with the higher frequency monitoring data, to 6 μg/l. The number of parameters that could be reliably auto

  13. Prediction of Proper Temperatures for the Hot Stamping Process Based on the Kinetics Models

    Science.gov (United States)

    Samadian, P.; Parsa, M. H.; Mirzadeh, H.

    2015-02-01

    Nowadays, the application of kinetics models for predicting microstructures of steels subjected to thermo-mechanical treatments has increased to minimize direct experimentation, which is costly and time consuming. In the current work, the final microstructures of AISI 4140 steel sheets after the hot stamping process were predicted using the Kirkaldy and Li kinetics models combined with new thermodynamically based models in order for the determination of the appropriate process temperatures. In this way, the effect of deformation during hot stamping on the Ae3, Acm, and Ae1 temperatures was considered, and then the equilibrium volume fractions of phases at different temperatures were calculated. Moreover, the ferrite transformation rate equations of the Kirkaldy and Li models were modified by a term proposed by Åkerström to consider the influence of plastic deformation. Results showed that the modified Kirkaldy model is satisfactory for the determination of appropriate austenitization temperatures for the hot stamping process of AISI 4140 steel sheets because of agreeable microstructure predictions in comparison with the experimental observations.

  14. Process-based karst modelling to relate hydrodynamic and hydrochemical characteristics to system properties

    Directory of Open Access Journals (Sweden)

    A. Hartmann

    2013-08-01

    Full Text Available More than 30% of Europe's land surface is made up of karst exposures. In some countries, water from karst aquifers constitutes almost half of the drinking water supply. Hydrological simulation models can predict the large-scale impact of future environmental change on hydrological variables. However, the information needed to obtain model parameters is not available everywhere and regionalisation methods have to be applied. The responsive behaviour of hydrological systems can be quantified by individual metrics, so-called system signatures. This study explores their value for distinguishing the dominant processes and properties of five different karst systems in Europe and the Middle East. By defining ten system signatures derived from hydrodynamic and hydrochemical observations, a process-based karst model is applied to the five karst systems. In a stepwise model evaluation strategy, optimum parameters and their sensitivity are identified using automatic calibration and global variance-based sensitivity analysis. System signatures and sensitive parameters serve as proxies for dominant processes, and optimised parameters are used to determine system properties. By sensitivity analysis, the set of system signatures was able to distinguish the karst systems from one another by providing separate information about dominant soil, epikarst, and fast and slow groundwater flow processes. Comparing sensitive parameters to the system signatures revealed that annual discharge can serve as a proxy for the recharge area, that the slopes of the high flow parts of the flow duration curves correlate with the fast flow storage constant, and that the dampening of the isotopic signal of the rain as well as the medium flow parts of the flow duration curves have a non-linear relation to the distribution of groundwater storage constants that represent the variability of groundwater flow dynamics. Our approach enabled us to identify dominant processes of the

  15. The Cognitive Processes Underlying Event-Based Prospective Memory In School Age Children and Young Adults: A Formal Model-Based Study

    OpenAIRE

    Smith, Rebekah E.; Bayen, Ute Johanna; Martin, Claudia

    2010-01-01

    Fifty 7-year-olds (29 female), 53 10-year-olds (29 female), and 36 young adults (19 female), performed a computerized event-based prospective memory task. All three groups differed significantly in prospective memory performance with adults showing the best performance and 7-year-olds the poorest performance. We used a formal multinomial process tree model of event-based prospective memory to decompose age differences in cognitive processes that jointly contribute to prospective memory perfor...

  16. Modeling and Simulation of Voids in Composite Tape Winding Process Based on Domain Superposition Technique

    Science.gov (United States)

    Deng, Bo; Shi, Yaoyao

    2017-11-01

    The tape winding technology is an effective way to fabricate rotationally composite materials. Nevertheless, some inevitable defects will seriously influence the performance of winding products. One of the crucial ways to identify the quality of fiber-reinforced composite material products is examining its void content. Significant improvement in products' mechanical properties can be achieved by minimizing the void defect. Two methods were applied in this study, finite element analysis and experimental testing, respectively, to investigate the mechanism of how void forming in composite tape winding processing. Based on the theories of interlayer intimate contact and Domain Superposition Technique (DST), a three-dimensional model of prepreg tape void with SolidWorks has been modeled in this paper. Whereafter, ABAQUS simulation software was used to simulate the void content change with pressure and temperature. Finally, a series of experiments were performed to determine the accuracy of the model-based predictions. The results showed that the model is effective for predicting the void content in the composite tape winding process.

  17. Computer Aided Continuous Time Stochastic Process Modelling

    DEFF Research Database (Denmark)

    Kristensen, N.R.; Madsen, Henrik; Jørgensen, Sten Bay

    2001-01-01

    A grey-box approach to process modelling that combines deterministic and stochastic modelling is advocated for identification of models for model-based control of batch and semi-batch processes. A computer-aided tool designed for supporting decision-making within the corresponding modelling cycle...

  18. Process-based Cost Estimation for Ramjet/Scramjet Engines

    Science.gov (United States)

    Singh, Brijendra; Torres, Felix; Nesman, Miles; Reynolds, John

    2003-01-01

    Process-based cost estimation plays a key role in effecting cultural change that integrates distributed science, technology and engineering teams to rapidly create innovative and affordable products. Working together, NASA Glenn Research Center and Boeing Canoga Park have developed a methodology of process-based cost estimation bridging the methodologies of high-level parametric models and detailed bottoms-up estimation. The NASA GRC/Boeing CP process-based cost model provides a probabilistic structure of layered cost drivers. High-level inputs characterize mission requirements, system performance, and relevant economic factors. Design alternatives are extracted from a standard, product-specific work breakdown structure to pre-load lower-level cost driver inputs and generate the cost-risk analysis. As product design progresses and matures the lower level more detailed cost drivers can be re-accessed and the projected variation of input values narrowed, thereby generating a progressively more accurate estimate of cost-risk. Incorporated into the process-based cost model are techniques for decision analysis, specifically, the analytic hierarchy process (AHP) and functional utility analysis. Design alternatives may then be evaluated not just on cost-risk, but also user defined performance and schedule criteria. This implementation of full-trade study support contributes significantly to the realization of the integrated development environment. The process-based cost estimation model generates development and manufacturing cost estimates. The development team plans to expand the manufacturing process base from approximately 80 manufacturing processes to over 250 processes. Operation and support cost modeling is also envisioned. Process-based estimation considers the materials, resources, and processes in establishing cost-risk and rather depending on weight as an input, actually estimates weight along with cost and schedule.

  19. Physics-based process modeling, reliability prediction, and design guidelines for flip-chip devices

    Science.gov (United States)

    Michaelides, Stylianos

    Flip Chip on Board (FCOB) and Chip-Scale Packages (CSPs) are relatively new technologies that are being increasingly used in the electronic packaging industry. Compared to the more widely used face-up wirebonding and TAB technologies, flip-chips and most CSPs provide the shortest possible leads, lower inductance, higher frequency, better noise control, higher density, greater input/output (I/O), smaller device footprint and lower profile. However, due to the short history and due to the introduction of several new electronic materials, designs, and processing conditions, very limited work has been done to understand the role of material, geometry, and processing parameters on the reliability of flip-chip devices. Also, with the ever-increasing complexity of semiconductor packages and with the continued reduction in time to market, it is too costly to wait until the later stages of design and testing to discover that the reliability is not satisfactory. The objective of the research is to develop integrated process-reliability models that will take into consideration the mechanics of assembly processes to be able to determine the reliability of face-down devices under thermal cycling and long-term temperature dwelling. The models incorporate the time and temperature-dependent constitutive behavior of various materials in the assembly to be able to predict failure modes such as die cracking and solder cracking. In addition, the models account for process-induced defects and macro-micro features of the assembly. Creep-fatigue and continuum-damage mechanics models for the solder interconnects and fracture-mechanics models for the die have been used to determine the reliability of the devices. The results predicted by the models have been successfully validated against experimental data. The validated models have been used to develop qualification and test procedures for implantable medical devices. In addition, the research has helped develop innovative face

  20. Self-optimisation and model-based design of experiments for developing a C–H activation flow process

    Directory of Open Access Journals (Sweden)

    Alexander Echtermeyer

    2017-01-01

    Full Text Available A recently described C(sp3–H activation reaction to synthesise aziridines was used as a model reaction to demonstrate the methodology of developing a process model using model-based design of experiments (MBDoE and self-optimisation approaches in flow. The two approaches are compared in terms of experimental efficiency. The self-optimisation approach required the least number of experiments to reach the specified objectives of cost and product yield, whereas the MBDoE approach enabled a rapid generation of a process model.

  1. Clinical Processes - The Killer Application for Constraint-Based Process Interactions

    DEFF Research Database (Denmark)

    Jiménez-Ramírez, Andrés; Barba, Irene; Reichert, Manfred

    2018-01-01

    . The scenario is subject to complex temporal constraints and entails the need for coordinating the constraint-based interactions among the processes related to a patient treatment process. As demonstrated in this work, the selected real process scenario can be suitably modeled through a declarative approach....... examples. However, to the best of our knowledge, they have not been used to model complex, real-world scenarios that comprise constraints going beyond control-flow. In this paper, we propose the use of a declarative language for modeling a sophisticated healthcare process scenario from the real world......For more than a decade, the interest in aligning information systems in a process-oriented way has been increasing. To enable operational support for business processes, the latter are usually specified in an imperative way. The resulting process models, however, tend to be too rigid to meet...

  2. Activated sludge model (ASM) based modelling of membrane bioreactor (MBR) processes: a critical review with special regard to MBR specificities.

    Science.gov (United States)

    Fenu, A; Guglielmi, G; Jimenez, J; Spèrandio, M; Saroj, D; Lesjean, B; Brepols, C; Thoeye, C; Nopens, I

    2010-08-01

    Membrane bioreactors (MBRs) have been increasingly employed for municipal and industrial wastewater treatment in the last decade. The efforts for modelling of such wastewater treatment systems have always targeted either the biological processes (treatment quality target) as well as the various aspects of engineering (cost effective design and operation). The development of Activated Sludge Models (ASM) was an important evolution in the modelling of Conventional Activated Sludge (CAS) processes and their use is now very well established. However, although they were initially developed to describe CAS processes, they have simply been transferred and applied to MBR processes. Recent studies on MBR biological processes have reported several crucial specificities: medium to very high sludge retention times, high mixed liquor concentration, accumulation of soluble microbial products (SMP) rejected by the membrane filtration step, and high aeration rates for scouring purposes. These aspects raise the question as to what extent the ASM framework is applicable to MBR processes. Several studies highlighting some of the aforementioned issues are scattered through the literature. Hence, through a concise and structured overview of the past developments and current state-of-the-art in biological modelling of MBR, this review explores ASM-based modelling applied to MBR processes. The work aims to synthesize previous studies and differentiates between unmodified and modified applications of ASM to MBR. Particular emphasis is placed on influent fractionation, biokinetics, and soluble microbial products (SMPs)/exo-polymeric substances (EPS) modelling, and suggestions are put forward as to good modelling practice with regard to MBR modelling both for end-users and academia. A last section highlights shortcomings and future needs for improved biological modelling of MBR processes. (c) 2010 Elsevier Ltd. All rights reserved.

  3. Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

    Science.gov (United States)

    Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.

    2014-01-01

    Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2 yr−1and total NPP in the range of 318–490 Tg C yr−1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2 yr−1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m−2 yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

  4. Deferred Action: Theoretical model of process architecture design for emergent business processes

    Directory of Open Access Journals (Sweden)

    Patel, N.V.

    2007-01-01

    Full Text Available E-Business modelling and ebusiness systems development assumes fixed company resources, structures, and business processes. Empirical and theoretical evidence suggests that company resources and structures are emergent rather than fixed. Planning business activity in emergent contexts requires flexible ebusiness models based on better management theories and models . This paper builds and proposes a theoretical model of ebusiness systems capable of catering for emergent factors that affect business processes. Drawing on development of theories of the ‘action and design’class the Theory of Deferred Action is invoked as the base theory for the theoretical model. A theoretical model of flexible process architecture is presented by identifying its core components and their relationships, and then illustrated with exemplar flexible process architectures capable of responding to emergent factors. Managerial implications of the model are considered and the model’s generic applicability is discussed.

  5. The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

    Science.gov (United States)

    Clark, M. P.; Nijssen, B.; Wood, A.; Mizukami, N.; Newman, A. J.

    2017-12-01

    The diversity in hydrologic models has historically led to great controversy on the "correct" approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this paper, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We illustrate how modeling advances have been made by groups using models of different type and complexity, and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.

  6. Event-Based Conceptual Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    The paper demonstrates that a wide variety of event-based modeling approaches are based on special cases of the same general event concept, and that the general event concept can be used to unify the otherwise unrelated fields of information modeling and process modeling. A set of event......-based modeling approaches are analyzed and the results are used to formulate a general event concept that can be used for unifying the seemingly unrelated event concepts. Events are characterized as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms...... of information structures. The general event concept can be used to guide systems analysis and design and to improve modeling approaches....

  7. Mathematical model of silicon smelting process basing on pelletized charge from technogenic raw materials

    Science.gov (United States)

    Nemchinova, N. V.; Tyutrin, A. A.; Salov, V. M.

    2018-03-01

    The silicon production process in the electric arc reduction furnaces (EAF) is studied using pelletized charge as an additive to the standard on the basis of the generated mathematical model. The results obtained due to the model will contribute to the analysis of the charge components behavior during melting with the achievement of optimum final parameters of the silicon production process. The authors proposed using technogenic waste as a raw material for the silicon production in a pelletized form using liquid glass and aluminum production dust from the electrostatic precipitators as a binder. The method of mathematical modeling with the help of the ‘Selector’ software package was used as a basis for the theoretical study. A model was simulated with the imitation of four furnace temperature zones and a crystalline silicon phase (25 °C). The main advantage of the created model is the ability to analyze the behavior of all burden materials (including pelletized charge) in the carbothermic process. The behavior analysis is based on the thermodynamic probability data of the burden materials interactions in the carbothermic process. The model accounts for 17 elements entering the furnace with raw materials, electrodes and air. The silicon melt, obtained by the modeling, contained 91.73 % wt. of the target product. The simulation results showed that in the use of the proposed combined charge, the recovery of silicon reached 69.248 %, which is in good agreement with practical data. The results of the crystalline silicon chemical composition modeling are compared with the real silicon samples of chemical analysis data, which showed the results of convergence. The efficiency of the mathematical modeling methods in the studying of the carbothermal silicon obtaining process with complex interphase transformations and the formation of numerous intermediate compounds using a pelletized charge as an additive to the traditional one is shown.

  8. Process models and model-data fusion in dendroecology

    Directory of Open Access Journals (Sweden)

    Joel eGuiot

    2014-08-01

    Full Text Available Dendrochronology (i.e. the study of annually dated tree-ring time series has proved to be a powerful technique to understand tree-growth. This paper intends to show the interest of using ecophysiological modeling not only to understand and predict tree-growth (dendroecology but also to reconstruct past climates (dendroclimatology. Process models have been used for several decades in dendroclimatology, but it is only recently that methods of model-data fusion have led to significant progress in modeling tree-growth as a function of climate and in reconstructing past climates. These model-data fusion (MDF methods, mainly based on the Bayesian paradigm, have been shown to be powerful for both model calibration and model inversion. After a rapid survey of tree-growth modeling, we illustrate MDF with examples based on series of Southern France Aleppo pines and Central France oaks. These examples show that if plants experienced CO2 fertilization, this would have a significant effect on tree-growth which in turn would bias the climate reconstructions. This bias could be extended to other environmental non-climatic factors directly or indirectly affecting annual ring formation and not taken into account in classical empirical models, which supports the use of more complex process-based models. Finally, we conclude by showing the interest of the data assimilation methods applied in climatology to produce climate re-analyses.

  9. Diff-based model synchronization in an industrial MDD process

    DEFF Research Database (Denmark)

    Kindler, Ekkart; Könemann, Patrick; Unland, Ludger

    of different models is maintained manually in many cases today. This paper presents an approach for automated model differencing, so that the differences between two model versions (called delta) can be extracted and stored. It can then be re-used independently of the models it was created from...... to interactively merge different model versions, and for synchronizing other types of models. The main concern was to apply our concepts to an industrial process, so usability and performance were important issues....

  10. Declarative modeling for process supervision

    International Nuclear Information System (INIS)

    Leyval, L.

    1989-01-01

    Our work is a contribution to computer aided supervision of continuous processes. It is inspired by an area of Artificial Intelligence: qualitative physics. Here, supervision is based on a model which continuously provides operators with a synthetic view of the process; but this model is founded on general principles of control theory rather than on physics. It involves concepts such as high gain or small time response. It helps in linking temporally the evolution of various variables. Moreover, the model provides predictions of the future behaviour of the process, which allows action advice and alarm filtering. This should greatly reduce the famous cognitive overload associated to any complex and dangerous evolution of the process

  11. Social Models: Blueprints or Processes?

    Science.gov (United States)

    Little, Graham R.

    1981-01-01

    Discusses the nature and implications of two different models for societal planning: (1) the problem-solving process approach based on Karl Popper; and (2) the goal-setting "blueprint" approach based on Karl Marx. (DC)

  12. Measurement-based reliability/performability models

    Science.gov (United States)

    Hsueh, Mei-Chen

    1987-01-01

    Measurement-based models based on real error-data collected on a multiprocessor system are described. Model development from the raw error-data to the estimation of cumulative reward is also described. A workload/reliability model is developed based on low-level error and resource usage data collected on an IBM 3081 system during its normal operation in order to evaluate the resource usage/error/recovery process in a large mainframe system. Thus, both normal and erroneous behavior of the system are modeled. The results provide an understanding of the different types of errors and recovery processes. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A sensitivity analysis is performed to investigate the significance of using a semi-Markov process, as opposed to a Markov process, to model the measured system.

  13. Modeling and Security Threat Assessments of Data Processed in Cloud Based Information Systems

    Directory of Open Access Journals (Sweden)

    Darya Sergeevna Simonenkova

    2016-03-01

    Full Text Available The subject of the research is modeling and security threat assessments of data processed in cloud based information systems (CBIS. This method allow to determine the current security threats of CBIS, state of the system in which vulnerabilities exists, level of possible violators, security properties and to generate recommendations for neutralizing security threats of CBIS.

  14. A Java-based fMRI processing pipeline evaluation system for assessment of univariate general linear model and multivariate canonical variate analysis-based pipelines.

    Science.gov (United States)

    Zhang, Jing; Liang, Lichen; Anderson, Jon R; Gatewood, Lael; Rottenberg, David A; Strother, Stephen C

    2008-01-01

    As functional magnetic resonance imaging (fMRI) becomes widely used, the demands for evaluation of fMRI processing pipelines and validation of fMRI analysis results is increasing rapidly. The current NPAIRS package, an IDL-based fMRI processing pipeline evaluation framework, lacks system interoperability and the ability to evaluate general linear model (GLM)-based pipelines using prediction metrics. Thus, it can not fully evaluate fMRI analytical software modules such as FSL.FEAT and NPAIRS.GLM. In order to overcome these limitations, a Java-based fMRI processing pipeline evaluation system was developed. It integrated YALE (a machine learning environment) into Fiswidgets (a fMRI software environment) to obtain system interoperability and applied an algorithm to measure GLM prediction accuracy. The results demonstrated that the system can evaluate fMRI processing pipelines with univariate GLM and multivariate canonical variates analysis (CVA)-based models on real fMRI data based on prediction accuracy (classification accuracy) and statistical parametric image (SPI) reproducibility. In addition, a preliminary study was performed where four fMRI processing pipelines with GLM and CVA modules such as FSL.FEAT and NPAIRS.CVA were evaluated with the system. The results indicated that (1) the system can compare different fMRI processing pipelines with heterogeneous models (NPAIRS.GLM, NPAIRS.CVA and FSL.FEAT) and rank their performance by automatic performance scoring, and (2) the rank of pipeline performance is highly dependent on the preprocessing operations. These results suggest that the system will be of value for the comparison, validation, standardization and optimization of functional neuroimaging software packages and fMRI processing pipelines.

  15. Stochastic Interest Model Based on Compound Poisson Process and Applications in Actuarial Science

    Directory of Open Access Journals (Sweden)

    Shilong Li

    2017-01-01

    Full Text Available Considering stochastic behavior of interest rates in financial market, we construct a new class of interest models based on compound Poisson process. Different from the references, this paper describes the randomness of interest rates by modeling the force of interest with Poisson random jumps directly. To solve the problem in calculation of accumulated interest force function, one important integral technique is employed. And a conception called the critical value is introduced to investigate the validity condition of this new model. We also discuss actuarial present values of several life annuities under this new interest model. Simulations are done to illustrate the theoretical results and the effect of parameters in interest model on actuarial present values is also analyzed.

  16. Geometric Model of Induction Heating Process of Iron-Based Sintered Materials

    Science.gov (United States)

    Semagina, Yu V.; Egorova, M. A.

    2018-03-01

    The article studies the issue of building multivariable dependences based on the experimental data. A constructive method for solving the issue is presented in the form of equations of (n-1) – surface compartments of the extended Euclidean space E+n. The dimension of space is taken to be equal to the sum of the number of parameters and factors of the model of the system being studied. The basis for building multivariable dependencies is the generalized approach to n-space used for the surface compartments of 3D space. The surface is designed on the basis of the kinematic method, moving one geometric object along a certain trajectory. The proposed approach simplifies the process aimed at building the multifactorial empirical dependencies which describe the process being investigated.

  17. Neuroscientific Model of Motivational Process

    OpenAIRE

    Kim, Sung-il

    2013-01-01

    Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Rewa...

  18. Individual-based modeling of ecological and evolutionary processes

    NARCIS (Netherlands)

    DeAngelis, D.L.; Mooij, W.M.

    2005-01-01

    Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential and difference equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis

  19. A process-based agricultural model for the irrigated agriculture sector in Alberta, Canada

    Science.gov (United States)

    Ammar, M. E.; Davies, E. G.

    2015-12-01

    Connections between land and water, irrigation, agricultural productivity and profitability, policy alternatives, and climate change and variability are complex, poorly understood, and unpredictable. Policy assessment for agriculture presents a large potential for development of broad-based simulation models that can aid assessment and quantification of policy alternatives over longer temporal scales. The Canadian irrigated agriculture sector is concentrated in Alberta, where it represents two thirds of the irrigated land-base in Canada and is the largest consumer of surface water. Despite interest in irrigation expansion, its potential in Alberta is uncertain given a constrained water supply, significant social and economic development and increasing demands for both land and water, and climate change. This paper therefore introduces a system dynamics model as a decision support tool to provide insights into irrigation expansion in Alberta, and into trade-offs and risks associated with that expansion. It is intended to be used by a wide variety of users including researchers, policy analysts and planners, and irrigation managers. A process-based cropping system approach is at the core of the model and uses a water-driven crop growth mechanism described by AquaCrop. The tool goes beyond a representation of crop phenology and cropping systems by permitting assessment and quantification of the broader, long-term consequences of agricultural policies for Alberta's irrigation sector. It also encourages collaboration and provides a degree of transparency that gives confidence in simulation results. The paper focuses on the agricultural component of the systems model, describing the process involved; soil water and nutrients balance, crop growth, and water, temperature, salinity, and nutrients stresses, and how other disciplines can be integrated to account for the effects of interactions and feedbacks in the whole system. In later stages, other components such as

  20. Rate-based modelling of combined SO2 removal and NH3 recycling integrated with an aqueous NH3-based CO2 capture process

    International Nuclear Information System (INIS)

    Li, Kangkang; Yu, Hai; Qi, Guojie; Feron, Paul; Tade, Moses; Yu, Jingwen; Wang, Shujuan

    2015-01-01

    Highlights: • A rigorous, rate-based model for an NH 3 –CO 2 –SO 2 –H 2 O system was developed. • Model predictions are in good agreement with pilot plant results. • >99.9% of SO 2 was captured and >99.9% of slipped ammonia was reused. • The process is highly adaptable to the variations of SO 2 /NH 3 level, temperatures. - Abstract: To reduce the costs of controlling emissions from coal-fired power stations, we propose an advanced and effective process of combined SO 2 removal and NH 3 recycling, which can be integrated with the aqueous NH 3 -based CO 2 capture process to simultaneously achieve SO 2 and CO 2 removal, NH 3 recycling and flue gas cooling in one process. A rigorous, rate-based model for an NH 3 –CO 2 –SO 2 –H 2 O system was developed and used to simulate the proposed process. The model was thermodynamically and kinetically validated by experimental results from the open literature and pilot-plant trials, respectively. Under typical flue gas conditions, the proposed process has SO 2 removal and NH 3 reuse efficiencies of >99.9%. The process is strongly adaptable to different scenarios such as high SO 2 levels in flue gas, high NH 3 levels from the CO 2 absorber and high flue gas temperatures, and has a low energy requirement. Because the process simplifies flue gas desulphurisation and resolves the problems of NH 3 loss and SO 2 removal, it could significantly reduce the cost of CO 2 and SO 2 capture by aqueous NH 3

  1. Multivariate statistical process control of batch processes based on three-way models

    NARCIS (Netherlands)

    Louwerse, D. J.; Smilde, A. K.

    2000-01-01

    The theory of batch MSPC control charts is extended and improved control charts an developed. Unfold-PCA, PARAFAC and Tucker3 models are discussed and used as a basis for these charts. The results of the different models are compared and the performance of the control charts based on these models is

  2. A flexible object-based software framework for modeling complex systems with interacting natural and societal processes.

    Energy Technology Data Exchange (ETDEWEB)

    Christiansen, J. H.

    2000-06-15

    The Dynamic Information Architecture System (DIAS) is a flexible, extensible, object-based framework for developing and maintaining complex multidisciplinary simulations. The DIAS infrastructure makes it feasible to build and manipulate complex simulation scenarios in which many thousands of objects can interact via dozens to hundreds of concurrent dynamic processes. The flexibility and extensibility of the DIAS software infrastructure stem mainly from (1) the abstraction of object behaviors, (2) the encapsulation and formalization of model functionality, and (3) the mutability of domain object contents. DIAS simulation objects are inherently capable of highly flexible and heterogeneous spatial realizations. Geospatial graphical representation of DIAS simulation objects is addressed via the GeoViewer, an object-based GIS toolkit application developed at ANL. DIAS simulation capabilities have been extended by inclusion of societal process models generated by the Framework for Addressing Cooperative Extended Transactions (FACET), another object-based framework developed at Argonne National Laboratory. By using FACET models to implement societal behaviors of individuals and organizations within larger DIAS-based natural systems simulations, it has become possible to conveniently address a broad range of issues involving interaction and feedback among natural and societal processes. Example DIAS application areas discussed in this paper include a dynamic virtual oceanic environment, detailed simulation of clinical, physiological, and logistical aspects of health care delivery, and studies of agricultural sustainability of urban centers under environmental stress in ancient Mesopotamia.

  3. A Fuzzy Neural Network Based on Non-Euclidean Distance Clustering for Quality Index Model in Slashing Process

    Directory of Open Access Journals (Sweden)

    Yuxian Zhang

    2015-01-01

    Full Text Available The quality index model in slashing process is difficult to build by reason of the outliers and noise data from original data. To the above problem, a fuzzy neural network based on non-Euclidean distance clustering is proposed in which the input space is partitioned into many local regions by the fuzzy clustering based on non-Euclidean distance so that the computation complexity is decreased, and fuzzy rule number is determined by validity function based on both the separation and the compactness among clusterings. Then, the premise parameters and consequent parameters are trained by hybrid learning algorithm. The parameters identification is realized; meanwhile the convergence condition of consequent parameters is obtained by Lyapunov function. Finally, the proposed method is applied to build the quality index model in slashing process in which the experimental data come from the actual slashing process. The experiment results show that the proposed fuzzy neural network for quality index model has lower computation complexity and faster convergence time, comparing with GP-FNN, BPNN, and RBFNN.

  4. Functional Dual Adaptive Control with Recursive Gaussian Process Model

    International Nuclear Information System (INIS)

    Prüher, Jakub; Král, Ladislav

    2015-01-01

    The paper deals with dual adaptive control problem, where the functional uncertainties in the system description are modelled by a non-parametric Gaussian process regression model. Current approaches to adaptive control based on Gaussian process models are severely limited in their practical applicability, because the model is re-adjusted using all the currently available data, which keeps growing with every time step. We propose the use of recursive Gaussian process regression algorithm for significant reduction in computational requirements, thus bringing the Gaussian process-based adaptive controllers closer to their practical applicability. In this work, we design a bi-criterial dual controller based on recursive Gaussian process model for discrete-time stochastic dynamic systems given in an affine-in-control form. Using Monte Carlo simulations, we show that the proposed controller achieves comparable performance with the full Gaussian process-based controller in terms of control quality while keeping the computational demands bounded. (paper)

  5. Lévy-based growth models

    DEFF Research Database (Denmark)

    Jónsdóttir, Kristjana Ýr; Schmiegel, Jürgen; Jensen, Eva Bjørn Vedel

    2008-01-01

    In the present paper, we give a condensed review, for the nonspecialist reader, of a new modelling framework for spatio-temporal processes, based on Lévy theory. We show the potential of the approach in stochastic geometry and spatial statistics by studying Lévy-based growth modelling of planar o...... objects. The growth models considered are spatio-temporal stochastic processes on the circle. As a by product, flexible new models for space–time covariance functions on the circle are provided. An application of the Lévy-based growth models to tumour growth is discussed....

  6. Dynamic modeling of ultrafiltration membranes for whey separation processes

    NARCIS (Netherlands)

    Saltik, M.B.; Ozkan, L.; Jacobs, M.; van der Padt, A.

    2017-01-01

    In this paper, we present a control relevant rigorous dynamic model for an ultrafiltration membrane unit in a whey separation process. The model consists of a set of differential algebraic equations and is developed for online model based applications such as model based control and process

  7. Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

    Science.gov (United States)

    Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun

    2017-08-01

    Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM 2.5 is a promising way to fill the areas that are not covered by ground PM 2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM 2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM 2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R 2  = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM 2.5 estimates.

  8. A process-based model for cattle manure compost windrows: Model performance and application

    Science.gov (United States)

    A model was developed and incorporated in the Integrated Farm System Model (IFSM, v.4.3) that simulates important processes occurring during windrow composting of manure. The model, documented in an accompanying paper, predicts changes in windrow properties and conditions and the resulting emissions...

  9. Synergy of modeling processes in the area of soft and hard modeling

    Directory of Open Access Journals (Sweden)

    Sika Robert

    2017-01-01

    Full Text Available High complexity of production processes results in more frequent use of computer systems for their modeling and simulation. Process modeling helps to find optimal solution, verify some assumptions before implementation and eliminate errors. In practice, modeling of production processes concerns two areas: hard modeling (based on differential equations of mathematical physics and soft (based on existing data. In the paper the possibility of synergistic connection of these two approaches was indicated: it means hard modeling support based on the tools used in soft modeling. It aims at significant reducing the time in order to obtain final results with the use of hard modeling. Some test were carried out in the Calibrate module of NovaFlow&Solid (NF&S simulation system in the frame of thermal analysis (ATAS-cup. The authors tested output values forecasting in NF&S system (solidification time on the basis of variable parameters of the thermal model (heat conduction, specific heat, density. Collected data was used as an input to prepare soft model with the use of MLP (Multi-Layer Perceptron neural network regression model. The approach described above enable to reduce the time of production process modeling with use of hard modeling and should encourage production companies to use it.

  10. Using a symbolic process model as input for model-based fMRI analysis : Locating the neural correlates of problem state replacements

    NARCIS (Netherlands)

    Borst, J.P.; Taatgen, N.A.; Van Rijn, D.H.

    2011-01-01

    In this paper, a model-based analysis method for fMRI is used with a high-level symbolic process model. Participants performed a triple-task in which intermediate task information needs to be updated frequently. Previous work has shown that the associated resource - the problem state resource - acts

  11. Modelling continuous pharmaceutical and bio-based processes at plant-wide level: A roadmap towards efficient decision-making

    DEFF Research Database (Denmark)

    Ramin, Pedram; Mansouri, Seyed Soheil; Udugama, Isuru A.

    2018-01-01

    The importance of developing simulation models for decision making in pharmaceutical and bio-based production processes is elaborated in this article. The advantages of modelling continuous processes are outlined and certain barriers in this regard are identified. Although there have been some...... advancements in the field, there needs to be a larger international collaboration in this regard for providing reliable data for model validation, for development of generic modelbased frameworks and implementing them in computer-aided platforms in the form of software tools....

  12. Reliability Analysis Based on a Jump Diffusion Model with Two Wiener Processes for Cloud Computing with Big Data

    Directory of Open Access Journals (Sweden)

    Yoshinobu Tamura

    2015-06-01

    Full Text Available At present, many cloud services are managed by using open source software, such as OpenStack and Eucalyptus, because of the unification management of data, cost reduction, quick delivery and work savings. The operation phase of cloud computing has a unique feature, such as the provisioning processes, the network-based operation and the diversity of data, because the operation phase of cloud computing changes depending on many external factors. We propose a jump diffusion model with two-dimensional Wiener processes in order to consider the interesting aspects of the network traffic and big data on cloud computing. In particular, we assess the stability of cloud software by using the sample paths obtained from the jump diffusion model with two-dimensional Wiener processes. Moreover, we discuss the optimal maintenance problem based on the proposed jump diffusion model. Furthermore, we analyze actual data to show numerical examples of dependability optimization based on the software maintenance cost considering big data on cloud computing.

  13. A Comparative of business process modelling techniques

    Science.gov (United States)

    Tangkawarow, I. R. H. T.; Waworuntu, J.

    2016-04-01

    In this era, there is a lot of business process modeling techniques. This article is the research about differences of business process modeling techniques. For each technique will explain about the definition and the structure. This paper presents a comparative analysis of some popular business process modelling techniques. The comparative framework is based on 2 criteria: notation and how it works when implemented in Somerleyton Animal Park. Each technique will end with the advantages and disadvantages. The final conclusion will give recommend of business process modeling techniques that easy to use and serve the basis for evaluating further modelling techniques.

  14. Forward and Reverse Process Models for the Squeeze Casting Process Using Neural Network Based Approaches

    Directory of Open Access Journals (Sweden)

    Manjunath Patel Gowdru Chandrashekarappa

    2014-01-01

    Full Text Available The present research work is focussed to develop an intelligent system to establish the input-output relationship utilizing forward and reverse mappings of artificial neural networks. Forward mapping aims at predicting the density and secondary dendrite arm spacing (SDAS from the known set of squeeze cast process parameters such as time delay, pressure duration, squeezes pressure, pouring temperature, and die temperature. An attempt is also made to meet the industrial requirements of developing the reverse model to predict the recommended squeeze cast parameters for the desired density and SDAS. Two different neural network based approaches have been proposed to carry out the said task, namely, back propagation neural network (BPNN and genetic algorithm neural network (GA-NN. The batch mode of training is employed for both supervised learning networks and requires huge training data. The requirement of huge training data is generated artificially at random using regression equation derived through real experiments carried out earlier by the same authors. The performances of BPNN and GA-NN models are compared among themselves with those of regression for ten test cases. The results show that both models are capable of making better predictions and the models can be effectively used in shop floor in selection of most influential parameters for the desired outputs.

  15. Numerical simulation of hot-melt extrusion processes for amorphous solid dispersions using model-based melt viscosity.

    Science.gov (United States)

    Bochmann, Esther S; Steffens, Kristina E; Gryczke, Andreas; Wagner, Karl G

    2018-03-01

    Simulation of HME processes is a valuable tool for increased process understanding and ease of scale-up. However, the experimental determination of all required input parameters is tedious, namely the melt rheology of the amorphous solid dispersion (ASD) in question. Hence, a procedure to simplify the application of hot-melt extrusion (HME) simulation for forming amorphous solid dispersions (ASD) is presented. The commercial 1D simulation software Ludovic ® was used to conduct (i) simulations using a full experimental data set of all input variables including melt rheology and (ii) simulations using model-based melt viscosity data based on the ASDs glass transition and the physical properties of polymeric matrix only. Both types of HME computation were further compared to experimental HME results. Variation in physical properties (e.g. heat capacity, density) and several process characteristics of HME (residence time distribution, energy consumption) among the simulations and experiments were evaluated. The model-based melt viscosity was calculated by using the glass transition temperature (T g ) of the investigated blend and the melt viscosity of the polymeric matrix by means of a T g -viscosity correlation. The results of measured melt viscosity and model-based melt viscosity were similar with only few exceptions, leading to similar HME simulation outcomes. At the end, the experimental effort prior to HME simulation could be minimized and the procedure enables a good starting point for rational development of ASDs by means of HME. As model excipients, Vinylpyrrolidone-vinyl acetate copolymer (COP) in combination with various APIs (carbamazepine, dipyridamole, indomethacin, and ibuprofen) or polyethylene glycol (PEG 1500) as plasticizer were used to form the ASDs. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Rule-based decision making model

    International Nuclear Information System (INIS)

    Sirola, Miki

    1998-01-01

    A rule-based decision making model is designed in G2 environment. A theoretical and methodological frame for the model is composed and motivated. The rule-based decision making model is based on object-oriented modelling, knowledge engineering and decision theory. The idea of safety objective tree is utilized. Advanced rule-based methodologies are applied. A general decision making model 'decision element' is constructed. The strategy planning of the decision element is based on e.g. value theory and utility theory. A hypothetical process model is built to give input data for the decision element. The basic principle of the object model in decision making is division in tasks. Probability models are used in characterizing component availabilities. Bayes' theorem is used to recalculate the probability figures when new information is got. The model includes simple learning features to save the solution path. A decision analytic interpretation is given to the decision making process. (author)

  17. Pattern-based translation of BPMN process models to BPEL web services

    NARCIS (Netherlands)

    Ouyang, C.; Dumas, M.; Hofstede, ter A.H.M.; Aalst, van der W.M.P.

    2008-01-01

    The business process modeling notation (BPMN) is a graph-oriented language primarily targeted at domain analysts and supported by many modeling tools. The business process execution language for Web services (BPEL) on the other hand is a mainly block-structured language targeted at software

  18. On the Representation of Subgrid Microtopography Effects in Process-based Hydrologic Models

    Science.gov (United States)

    Jan, A.; Painter, S. L.; Coon, E. T.

    2017-12-01

    Increased availability of high-resolution digital elevation are enabling process-based hydrologic modeling on finer and finer scales. However, spatial variability in surface elevation (microtopography) exists below the scale of a typical hyper-resolution grid cell and has the potential to play a significant role in water retention, runoff, and surface/subsurface interactions. Though the concept of microtopographic features (depressions, obstructions) and the associated implications on flow and discharge are well established, representing those effects in watershed-scale integrated surface/subsurface hydrology models remains a challenge. Using the complex and coupled hydrologic environment of the Arctic polygonal tundra as an example, we study the effects of submeter topography and present a subgrid model parameterized by small-scale spatial heterogeneities for use in hyper-resolution models with polygons at a scale of 15-20 meters forming the surface cells. The subgrid model alters the flow and storage terms in the diffusion wave equation for surface flow. We compare our results against sub-meter scale simulations (acts as a benchmark for our simulations) and hyper-resolution models without the subgrid representation. The initiation of runoff in the fine-scale simulations is delayed and the recession curve is slowed relative to simulated runoff using the hyper-resolution model with no subgrid representation. Our subgrid modeling approach improves the representation of runoff and water retention relative to models that ignore subgrid topography. We evaluate different strategies for parameterizing subgrid model and present a classification-based method to efficiently move forward to larger landscapes. This work was supported by the Interoperable Design of Extreme-scale Application Software (IDEAS) project and the Next-Generation Ecosystem Experiments-Arctic (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the

  19. Gradient-based model calibration with proxy-model assistance

    Science.gov (United States)

    Burrows, Wesley; Doherty, John

    2016-02-01

    Use of a proxy model in gradient-based calibration and uncertainty analysis of a complex groundwater model with large run times and problematic numerical behaviour is described. The methodology is general, and can be used with models of all types. The proxy model is based on a series of analytical functions that link all model outputs used in the calibration process to all parameters requiring estimation. In enforcing history-matching constraints during the calibration and post-calibration uncertainty analysis processes, the proxy model is run for the purposes of populating the Jacobian matrix, while the original model is run when testing parameter upgrades; the latter process is readily parallelized. Use of a proxy model in this fashion dramatically reduces the computational burden of complex model calibration and uncertainty analysis. At the same time, the effect of model numerical misbehaviour on calculation of local gradients is mitigated, this allowing access to the benefits of gradient-based analysis where lack of integrity in finite-difference derivatives calculation would otherwise have impeded such access. Construction of a proxy model, and its subsequent use in calibration of a complex model, and in analysing the uncertainties of predictions made by that model, is implemented in the PEST suite.

  20. QUALITY IMPROVEMENT MODEL AT THE MANUFACTURING PROCESS PREPARATION LEVEL

    Directory of Open Access Journals (Sweden)

    Dusko Pavletic

    2009-12-01

    Full Text Available The paper expresses base for an operational quality improvement model at the manufacturing process preparation level. A numerous appropriate related quality assurance and improvement methods and tools are identified. Main manufacturing process principles are investigated in order to scrutinize one general model of manufacturing process and to define a manufacturing process preparation level. Development and introduction of the operational quality improvement model is based on a research conducted and results of methods and tools application possibilities in real manufacturing processes shipbuilding and automotive industry. Basic model structure is described and presented by appropriate general algorithm. Operational quality improvement model developed lays down main guidelines for practical and systematic application of quality improvements methods and tools.

  1. Strategy for design NIR calibration sets based on process spectrum and model space: An innovative approach for process analytical technology.

    Science.gov (United States)

    Cárdenas, V; Cordobés, M; Blanco, M; Alcalà, M

    2015-10-10

    The pharmaceutical industry is under stringent regulations on quality control of their products because is critical for both, productive process and consumer safety. According to the framework of "process analytical technology" (PAT), a complete understanding of the process and a stepwise monitoring of manufacturing are required. Near infrared spectroscopy (NIRS) combined with chemometrics have lately performed efficient, useful and robust for pharmaceutical analysis. One crucial step in developing effective NIRS-based methodologies is selecting an appropriate calibration set to construct models affording accurate predictions. In this work, we developed calibration models for a pharmaceutical formulation during its three manufacturing stages: blending, compaction and coating. A novel methodology is proposed for selecting the calibration set -"process spectrum"-, into which physical changes in the samples at each stage are algebraically incorporated. Also, we established a "model space" defined by Hotelling's T(2) and Q-residuals statistics for outlier identification - inside/outside the defined space - in order to select objectively the factors to be used in calibration set construction. The results obtained confirm the efficacy of the proposed methodology for stepwise pharmaceutical quality control, and the relevance of the study as a guideline for the implementation of this easy and fast methodology in the pharma industry. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. Modeling biochemical transformation processes and information processing with Narrator.

    Science.gov (United States)

    Mandel, Johannes J; Fuss, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

    2007-03-27

    Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Narrator is a flexible and intuitive systems biology tool. It is

  3. Online Rule Generation Software Process Model

    OpenAIRE

    Sudeep Marwaha; Alka Aroa; Satma M C; Rajni Jain; R C Goyal

    2013-01-01

    For production systems like expert systems, a rule generation software can facilitate the faster deployment. The software process model for rule generation using decision tree classifier refers to the various steps required to be executed for the development of a web based software model for decision rule generation. The Royce’s final waterfall model has been used in this paper to explain the software development process. The paper presents the specific output of various steps of modified wat...

  4. Process Modelling of Rapid Manufacturing Based Mass Customisation System for Fabrication of Custom Foot Orthoses: Review Paper

    Directory of Open Access Journals (Sweden)

    Saleh Jumani

    2013-04-01

    Full Text Available The need for custom-made devices, rehabilitation aids and treatments is explicit in the medical sector. Applications of rapid manufacturing techniques based on additive fabrication processes combined with medical digitising technologies can generate high quality solutions in situations where the need for custom-made devices and rehabilitation aids and low-lead times are very important factors. Foot orthoses are medical devices applied in the treatment of biomechanical foot disorders, foot injuries and foot diseases including rheumatoid arthritis and diabetes. The significant challenge in the treatment of foot related diseases is progressing pathological deterioration in the affected sites of the foot which requires quick provision of the orthoses. A process model is developed using the IDEF0 modelling technique in which a rapid manufacturing approach is integrated in the design and fabrication process of custom foot orthoses. The process model will be used in the development of rapid manufacturing based design and fabrication system for mass customisation of foot orthoses. The developed system is aimed at mass scale production of custom foot orthoses with the advantages of reduced cost, reduced lead-time and improved product in terms of increased fit, consistency and accuracy in the final product.

  5. Modelling energy spot prices by Lévy semistationary processes

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole; Benth, Fred Espen; Veraart, Almut

    This paper introduces a new modelling framework for energy spot prices based on Lévy semistationary processes. Lévy semistationary processes are special cases of the general class of ambit processes. We provide a detailed analysis of the probabilistic properties of such models and we show how...... they are able to capture many of the stylised facts observed in energy markets. Furthermore, we derive forward prices based on our spot price model. As it turns out, many of the classical spot models can be embedded into our novel modelling framework....

  6. Pre-Processing and Modeling Tools for Bigdata

    Directory of Open Access Journals (Sweden)

    Hashem Hadi

    2016-09-01

    Full Text Available Modeling tools and operators help the user / developer to identify the processing field on the top of the sequence and to send into the computing module only the data related to the requested result. The remaining data is not relevant and it will slow down the processing. The biggest challenge nowadays is to get high quality processing results with a reduced computing time and costs. To do so, we must review the processing sequence, by adding several modeling tools. The existing processing models do not take in consideration this aspect and focus on getting high calculation performances which will increase the computing time and costs. In this paper we provide a study of the main modeling tools for BigData and a new model based on pre-processing.

  7. Animated-simulation modeling facilitates clinical-process costing.

    Science.gov (United States)

    Zelman, W N; Glick, N D; Blackmore, C C

    2001-09-01

    Traditionally, the finance department has assumed responsibility for assessing process costs in healthcare organizations. To enhance process-improvement efforts, however, many healthcare providers need to include clinical staff in process cost analysis. Although clinical staff often use electronic spreadsheets to model the cost of specific processes, PC-based animated-simulation tools offer two major advantages over spreadsheets: they allow clinicians to interact more easily with the costing model so that it more closely represents the process being modeled, and they represent cost output as a cost range rather than as a single cost estimate, thereby providing more useful information for decision making.

  8. Computer-Aided Multiscale Modelling for Chemical Process Engineering

    DEFF Research Database (Denmark)

    Morales Rodriguez, Ricardo; Gani, Rafiqul

    2007-01-01

    Chemical processes are generally modeled through monoscale approaches, which, while not adequate, satisfy a useful role in product-process design. In this case, use of a multi-dimensional and multi-scale model-based approach has importance in product-process development. A computer-aided framework...

  9. Guided interaction exploration in artifact-centric process models

    NARCIS (Netherlands)

    van Eck, M.L.; Sidorova, N.; van der Aalst, W.M.P.

    2017-01-01

    Artifact-centric process models aim to describe complex processes as a collection of interacting artifacts. Recent development in process mining allow for the discovery of such models. However, the focus is often on the representation of the individual artifacts rather than their interactions. Based

  10. Conceptual modelling of human resource evaluation process

    Directory of Open Access Journals (Sweden)

    Negoiţă Doina Olivia

    2017-01-01

    Full Text Available Taking into account the highly diverse tasks which employees have to fulfil due to complex requirements of nowadays consumers, the human resource within an enterprise has become a strategic element for developing and exploiting products which meet the market expectations. Therefore, organizations encounter difficulties when approaching the human resource evaluation process. Hence, the aim of the current paper is to design a conceptual model of the aforementioned process, which allows the enterprises to develop a specific methodology. In order to design the conceptual model, Business Process Modelling instruments were employed - Adonis Community Edition Business Process Management Toolkit using the ADONIS BPMS Notation. The conceptual model was developed based on an in-depth secondary research regarding the human resource evaluation process. The proposed conceptual model represents a generic workflow (sequential and/ or simultaneously activities, which can be extended considering the enterprise’s needs regarding their requirements when conducting a human resource evaluation process. Enterprises can benefit from using software instruments for business process modelling as they enable process analysis and evaluation (predefined / specific queries and also model optimization (simulations.

  11. Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

    Science.gov (United States)

    Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

    2018-04-01

    A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

  12. Cortical processing of pitch: Model-based encoding and decoding of auditory fMRI responses to real-life sounds.

    Science.gov (United States)

    De Angelis, Vittoria; De Martino, Federico; Moerel, Michelle; Santoro, Roberta; Hausfeld, Lars; Formisano, Elia

    2017-11-13

    Pitch is a perceptual attribute related to the fundamental frequency (or periodicity) of a sound. So far, the cortical processing of pitch has been investigated mostly using synthetic sounds. However, the complex harmonic structure of natural sounds may require different mechanisms for the extraction and analysis of pitch. This study investigated the neural representation of pitch in human auditory cortex using model-based encoding and decoding analyses of high field (7 T) functional magnetic resonance imaging (fMRI) data collected while participants listened to a wide range of real-life sounds. Specifically, we modeled the fMRI responses as a function of the sounds' perceived pitch height and salience (related to the fundamental frequency and the harmonic structure respectively), which we estimated with a computational algorithm of pitch extraction (de Cheveigné and Kawahara, 2002). First, using single-voxel fMRI encoding, we identified a pitch-coding region in the antero-lateral Heschl's gyrus (HG) and adjacent superior temporal gyrus (STG). In these regions, the pitch representation model combining height and salience predicted the fMRI responses comparatively better than other models of acoustic processing and, in the right hemisphere, better than pitch representations based on height/salience alone. Second, we assessed with model-based decoding that multi-voxel response patterns of the identified regions are more informative of perceived pitch than the remainder of the auditory cortex. Further multivariate analyses showed that complementing a multi-resolution spectro-temporal sound representation with pitch produces a small but significant improvement to the decoding of complex sounds from fMRI response patterns. In sum, this work extends model-based fMRI encoding and decoding methods - previously employed to examine the representation and processing of acoustic sound features in the human auditory system - to the representation and processing of a relevant

  13. Validation of a Process-Based Agro-Ecosystem Model (Agro-IBIS for Maize in Xinjiang, Northwest China

    Directory of Open Access Journals (Sweden)

    Tureniguli Amuti

    2018-03-01

    Full Text Available Agricultural oasis expansion and intensive management practices have occurred in arid and semiarid regions of China during the last few decades. Accordingly, regional carbon and water budgets have been profoundly impacted by agroecosystems in these regions. Therefore, study on the methods used to accurately estimate energy, water, and carbon exchanges is becoming increasingly important. Process-based models can represent the complex processes between land and atmosphere among agricultural ecosystems. However, before the models can be applied they must be validated under different environmental and climatic conditions. In this study, a process-based agricultural ecosystem model (Agro-IBIS was validated for maize crops using 3 years of soil and biometric measurements at Wulanwusu agrometeorological site (WAS located in the Shihezi oasis in Xinjiang, northwest China. The model satisfactorily represented leaf area index (LAI during the growing season, simulating its peak values within the magnitude of 0–10%. The total biomass carbon was overestimated by 15%, 8%, and 16% in 2004, 2005, and 2006, respectively. The model satisfactorily simulated the soil temperature (0–10 cm and volumetric water content (VWC (0–25 cm of farmland during the growing season. However, it overestimated soil temperature approximately by 4 °C and VWC by 15–30% during the winter, coinciding with the period of no vegetation cover in Xinjiang. Overall, the results indicate that the model could represent crop growth, and seems to be applicable in multiple sites in arid oases agroecosystems of Xinjiang. Future application of the model will impose more comprehensive validation using eddy covariance flux data, and consider including dynamics of crop residue and improving characterization of the final stage of leaf development.

  14. Pedestrians' intention to jaywalk: Automatic or planned? A study based on a dual-process model in China.

    Science.gov (United States)

    Xu, Yaoshan; Li, Yongjuan; Zhang, Feng

    2013-01-01

    The present study investigates the determining factors of Chinese pedestrians' intention to violate traffic laws using a dual-process model. This model divides the cognitive processes of intention formation into controlled analytical processes and automatic associative processes. Specifically, the process explained by the augmented theory of planned behavior (TPB) is controlled, whereas the process based on past behavior is automatic. The results of a survey conducted on 323 adult pedestrian respondents showed that the two added TPB variables had different effects on the intention to violate, i.e., personal norms were significantly related to traffic violation intention, whereas descriptive norms were non-significant predictors. Past behavior significantly but uniquely predicted the intention to violate: the results of the relative weight analysis indicated that the largest percentage of variance in pedestrians' intention to violate was explained by past behavior (42%). According to the dual-process model, therefore, pedestrians' intention formation relies more on habit than on cognitive TPB components and social norms. The implications of these findings for the development of intervention programs are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  15. Process-based software project management

    CERN Document Server

    Goodman, F Alan

    2006-01-01

    Not connecting software project management (SPM) to actual, real-world development processes can lead to a complete divorcing of SPM to software engineering that can undermine any successful software project. By explaining how a layered process architectural model improves operational efficiency, Process-Based Software Project Management outlines a new method that is more effective than the traditional method when dealing with SPM. With a clear and easy-to-read approach, the book discusses the benefits of an integrated project management-process management connection. The described tight coup

  16. Modeling and Control of Multivariable Process Using Intelligent Techniques

    Directory of Open Access Journals (Sweden)

    Subathra Balasubramanian

    2010-10-01

    Full Text Available For nonlinear dynamic systems, the first principles based modeling and control is difficult to implement. In this study, a fuzzy controller and recurrent fuzzy controller are developed for MIMO process. Fuzzy logic controller is a model free controller designed based on the knowledge about the process. In fuzzy controller there are two types of rule-based fuzzy models are available: one the linguistic (Mamdani model and the other is Takagi–Sugeno model. Of these two, Takagi-Sugeno model (TS has attracted most attention. The fuzzy controller application is limited to static processes due to their feedforward structure. But, most of the real-time processes are dynamic and they require the history of input/output data. In order to store the past values a memory unit is needed, which is introduced by the recurrent structure. The proposed recurrent fuzzy structure is used to develop a controller for the two tank heating process. Both controllers are designed and implemented in a real time environment and their performance is compared.

  17. From Process to Practice: Towards a Practice-Based Model of Digital Innovation

    DEFF Research Database (Denmark)

    Ciriello, Raffaele; Richter, Alexander; Schwabe, Gerhard

    2017-01-01

    companies and an extensive set of empirical data, this paper conceptualizes four interrelated digital innovation practices, namely making sense of an idea, aligning mental models, negotiating solution paths, and crafting an idea. We suggest a practice-based model of digital innovation, specify a set......The ongoing digitalization of many corporate functions, including the innovation process, brings about fundamental changes that urge us to rethink established theories. Facilitating digital innovation requires a deep understanding of the actual practices that are carried out by innovating people...... with the help of artifacts. In this paper, we study the use of artifacts and illustrate their different roles in the underlying innovation practices to provide rich insights into digital innovation from a practice perspective. Grounded in a nearly three year-long, qualitative case study at two Swiss software...

  18. Aerospace Materials Process Modelling

    Science.gov (United States)

    1988-08-01

    Cooling Transformation diagram ( CCT diagram ) When a IT diagram is used in the heat process modelling, we suppose that a sudden cooling (instantaneous...processes. CE, chooses instead to study thermo-mechanical properties referring to a CCT diagram . This is thinked to be more reliable to give a true...k , mm-_____sml l ml A I 1 III 12.4 This determination is however based on the following approximations: i) A CCT diagram is valid only for the

  19. Model medication management process in Australian nursing homes using business process modeling.

    Science.gov (United States)

    Qian, Siyu; Yu, Ping

    2013-01-01

    One of the reasons for end user avoidance or rejection to use health information systems is poor alignment of the system with healthcare workflow, likely causing by system designers' lack of thorough understanding about healthcare process. Therefore, understanding the healthcare workflow is the essential first step for the design of optimal technologies that will enable care staff to complete the intended tasks faster and better. The often use of multiple or "high risk" medicines by older people in nursing homes has the potential to increase medication error rate. To facilitate the design of information systems with most potential to improve patient safety, this study aims to understand medication management process in nursing homes using business process modeling method. The paper presents study design and preliminary findings from interviewing two registered nurses, who were team leaders in two nursing homes. Although there were subtle differences in medication management between the two homes, major medication management activities were similar. Further field observation will be conducted. Based on the data collected from observations, an as-is process model for medication management will be developed.

  20. Cost Models for MMC Manufacturing Processes

    Science.gov (United States)

    Elzey, Dana M.; Wadley, Haydn N. G.

    1996-01-01

    Processes for the manufacture of advanced metal matrix composites are rapidly approaching maturity in the research laboratory and there is growing interest in their transition to industrial production. However, research conducted to date has almost exclusively focused on overcoming the technical barriers to producing high-quality material and little attention has been given to the economical feasibility of these laboratory approaches and process cost issues. A quantitative cost modeling (QCM) approach was developed to address these issues. QCM are cost analysis tools based on predictive process models relating process conditions to the attributes of the final product. An important attribute, of the QCM approach is the ability to predict the sensitivity of material production costs to product quality and to quantitatively explore trade-offs between cost and quality. Applications of the cost models allow more efficient direction of future MMC process technology development and a more accurate assessment of MMC market potential. Cost models were developed for two state-of-the art metal matrix composite (MMC) manufacturing processes: tape casting and plasma spray deposition. Quality and Cost models are presented for both processes and the resulting predicted quality-cost curves are presented and discussed.

  1. Identifying potential misfit items in cognitive process of learning engineering mathematics based on Rasch model

    International Nuclear Information System (INIS)

    Ataei, Sh; Mahmud, Z; Khalid, M N

    2014-01-01

    The students learning outcomes clarify what students should know and be able to demonstrate after completing their course. So, one of the issues on the process of teaching and learning is how to assess students' learning. This paper describes an application of the dichotomous Rasch measurement model in measuring the cognitive process of engineering students' learning of mathematics. This study provides insights into the perspective of 54 engineering students' cognitive ability in learning Calculus III based on Bloom's Taxonomy on 31 items. The results denote that some of the examination questions are either too difficult or too easy for the majority of the students. This analysis yields FIT statistics which are able to identify if there is data departure from the Rasch theoretical model. The study has identified some potential misfit items based on the measurement of ZSTD where the removal misfit item was accomplished based on the MNSQ outfit of above 1.3 or less than 0.7 logit. Therefore, it is recommended that these items be reviewed or revised to better match the range of students' ability in the respective course.

  2. Testing seasonal and long-term controls of streamwater DOC using empirical and process-based models.

    Science.gov (United States)

    Futter, Martyn N; de Wit, Heleen A

    2008-12-15

    Concentrations of dissolved organic carbon (DOC) in surface waters are increasing across Europe and parts of North America. Several mechanisms have been proposed to explain these increases including reductions in acid deposition, change in frequency of winter storms and changes in temperature and precipitation patterns. We used two modelling approaches to identify the mechanisms responsible for changing surface water DOC concentrations. Empirical regression analysis and INCA-C, a process-based model of stream-water DOC, were used to simulate long-term (1986--2003) patterns in stream water DOC concentrations in a small boreal stream. Both modelling approaches successfully simulated seasonal and inter-annual patterns in DOC concentration. In both models, seasonal patterns of DOC concentration were controlled by hydrology and inter-annual patterns were explained by climatic variation. There was a non-linear relationship between warmer summer temperatures and INCA-C predicted DOC. Only the empirical model was able to satisfactorily simulate the observed long-term increase in DOC. The observed long-term trends in DOC are likely to be driven by in-soil processes controlled by SO4(2-) and Cl(-) deposition, and to a lesser extent by temperature-controlled processes. Given the projected changes in climate and deposition, future modelling and experimental research should focus on the possible effects of soil temperature and moisture on organic carbon production, sorption and desorption rates, and chemical controls on organic matter solubility.

  3. Welding process modelling and control

    Science.gov (United States)

    Romine, Peter L.; Adenwala, Jinen A.

    1993-01-01

    The research and analysis performed, and software developed, and hardware/software recommendations made during 1992 in development of the PC-based data acquisition system for support of Welding Process Modeling and Control is reported. A need was identified by the Metals Processing Branch of NASA Marshall Space Flight Center, for a mobile data aquisition and analysis system, customized for welding measurement and calibration. Several hardware configurations were evaluated and a PC-based system was chosen. The Welding Measurement System (WMS) is a dedicated instrument, strictly for the use of data aquisition and analysis. Although the WMS supports many of the functions associated with the process control, it is not the intention for this system to be used for welding process control.

  4. Computer-Aided Model Based Analysis for Design and Operation of a Copolymerization Process

    DEFF Research Database (Denmark)

    Lopez-Arenas, Maria Teresa; Sales-Cruz, Alfonso Mauricio; Gani, Rafiqul

    2006-01-01

    . This will allow analysis of the process behaviour, contribute to a better understanding of the polymerization process, help to avoid unsafe conditions of operation, and to develop operational and optimizing control strategies. In this work, through a computer-aided modeling system ICAS-MoT, two first......The advances in computer science and computational algorithms for process modelling, process simulation, numerical methods and design/synthesis algorithms, makes it advantageous and helpful to employ computer-aided modelling systems and tools for integrated process analysis. This is illustrated......-principles models have been investigated with respect to design and operational issues for solution copolymerization reactors in general, and for the methyl methacrylate/vinyl acetate system in particular. The Model 1 is taken from literature and is commonly used for low conversion region, while the Model 2 has...

  5. Process-Based Development of Competence Models to Computer Science Education

    Science.gov (United States)

    Zendler, Andreas; Seitz, Cornelia; Klaudt, Dieter

    2016-01-01

    A process model ("cpm.4.CSE") is introduced that allows the development of competence models in computer science education related to curricular requirements. It includes eight subprocesses: (a) determine competence concept, (b) determine competence areas, (c) identify computer science concepts, (d) assign competence dimensions to…

  6. Design and Implementation of Hydrologic Process Knowledge-base Ontology: A case study for the Infiltration Process

    Science.gov (United States)

    Elag, M.; Goodall, J. L.

    2013-12-01

    Hydrologic modeling often requires the re-use and integration of models from different disciplines to simulate complex environmental systems. Component-based modeling introduces a flexible approach for integrating physical-based processes across disciplinary boundaries. Several hydrologic-related modeling communities have adopted the component-based approach for simulating complex physical systems by integrating model components across disciplinary boundaries in a workflow. However, it is not always straightforward to create these interdisciplinary models due to the lack of sufficient knowledge about a hydrologic process. This shortcoming is a result of using informal methods for organizing and sharing information about a hydrologic process. A knowledge-based ontology provides such standards and is considered the ideal approach for overcoming this challenge. The aims of this research are to present the methodology used in analyzing the basic hydrologic domain in order to identify hydrologic processes, the ontology itself, and how the proposed ontology is integrated with the Water Resources Component (WRC) ontology. The proposed ontology standardizes the definitions of a hydrologic process, the relationships between hydrologic processes, and their associated scientific equations. The objective of the proposed Hydrologic Process (HP) Ontology is to advance the idea of creating a unified knowledge framework for components' metadata by introducing a domain-level ontology for hydrologic processes. The HP ontology is a step toward an explicit and robust domain knowledge framework that can be evolved through the contribution of domain users. Analysis of the hydrologic domain is accomplished using the Formal Concept Approach (FCA), in which the infiltration process, an important hydrologic process, is examined. Two infiltration methods, the Green-Ampt and Philip's methods, were used to demonstrate the implementation of information in the HP ontology. Furthermore, a SPARQL

  7. Spatio-Temporal Data Analysis at Scale Using Models Based on Gaussian Processes

    Energy Technology Data Exchange (ETDEWEB)

    Stein, Michael [Univ. of Chicago, IL (United States)

    2017-03-13

    Gaussian processes are the most commonly used statistical model for spatial and spatio-temporal processes that vary continuously. They are broadly applicable in the physical sciences and engineering and are also frequently used to approximate the output of complex computer models, deterministic or stochastic. We undertook research related to theory, computation, and applications of Gaussian processes as well as some work on estimating extremes of distributions for which a Gaussian process assumption might be inappropriate. Our theoretical contributions include the development of new classes of spatial-temporal covariance functions with desirable properties and new results showing that certain covariance models lead to predictions with undesirable properties. To understand how Gaussian process models behave when applied to deterministic computer models, we derived what we believe to be the first significant results on the large sample properties of estimators of parameters of Gaussian processes when the actual process is a simple deterministic function. Finally, we investigated some theoretical issues related to maxima of observations with varying upper bounds and found that, depending on the circumstances, standard large sample results for maxima may or may not hold. Our computational innovations include methods for analyzing large spatial datasets when observations fall on a partially observed grid and methods for estimating parameters of a Gaussian process model from observations taken by a polar-orbiting satellite. In our application of Gaussian process models to deterministic computer experiments, we carried out some matrix computations that would have been infeasible using even extended precision arithmetic by focusing on special cases in which all elements of the matrices under study are rational and using exact arithmetic. The applications we studied include total column ozone as measured from a polar-orbiting satellite, sea surface temperatures over the

  8. Decision support based on process mining

    NARCIS (Netherlands)

    Aalst, van der W.M.P.; Burstein, F.; Holsapple, C.W.

    2008-01-01

    Process mining techniques allow for the analysis of business processes based on event logs. For example, the audit trails of a workflow management system, the transaction logs of an enterprise resource planning system, and the electronic patient records in a hospital can be used to discover models

  9. Probabilistic modeling of discourse-aware sentence processing.

    Science.gov (United States)

    Dubey, Amit; Keller, Frank; Sturt, Patrick

    2013-07-01

    Probabilistic models of sentence comprehension are increasingly relevant to questions concerning human language processing. However, such models are often limited to syntactic factors. This restriction is unrealistic in light of experimental results suggesting interactions between syntax and other forms of linguistic information in human sentence processing. To address this limitation, this article introduces two sentence processing models that augment a syntactic component with information about discourse co-reference. The novel combination of probabilistic syntactic components with co-reference classifiers permits them to more closely mimic human behavior than existing models. The first model uses a deep model of linguistics, based in part on probabilistic logic, allowing it to make qualitative predictions on experimental data; the second model uses shallow processing to make quantitative predictions on a broad-coverage reading-time corpus. Copyright © 2013 Cognitive Science Society, Inc.

  10. Business Process Simulation: Requirements for Business and Resource Models

    Directory of Open Access Journals (Sweden)

    Audrius Rima

    2015-07-01

    Full Text Available The purpose of Business Process Model and Notation (BPMN is to provide easily understandable graphical representation of business process. Thus BPMN is widely used and applied in various areas one of them being a business process simulation. This paper addresses some BPMN model based business process simulation problems. The paper formulate requirements for business process and resource models in enabling their use for business process simulation.

  11. Modeling biochemical transformation processes and information processing with Narrator

    Directory of Open Access Journals (Sweden)

    Palfreyman Niall M

    2007-03-01

    Full Text Available Abstract Background Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs, which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Results Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Conclusion Narrator is a

  12. Technology Evaluation of Process Configurations for Second Generation Bioethanol Production using Dynamic Model-based Simulations

    DEFF Research Database (Denmark)

    Morales Rodriguez, Ricardo; Meyer, Anne S.; Gernaey, Krist

    2011-01-01

    An assessment of a number of different process flowsheets for bioethanol production was performed using dynamic model-based simulations. The evaluation employed diverse operational scenarios such as, fed-batch, continuous and continuous with recycle configurations. Each configuration was evaluated...... against the following benchmark criteria, yield (kg ethanol/kg dry-biomass), final product concentration and number of unit operations required in the different process configurations. The results has shown the process configuration for simultaneous saccharification and co-fermentation (SSCF) operating...... in continuous mode with a recycle of the SSCF reactor effluent, results in the best productivity of bioethanol among the proposed process configurations, with a yield of 0.18 kg ethanol /kg dry-biomass....

  13. Integrating statistical and process-based models to produce probabilistic landslide hazard at regional scale

    Science.gov (United States)

    Strauch, R. L.; Istanbulluoglu, E.

    2017-12-01

    We develop a landslide hazard modeling approach that integrates a data-driven statistical model and a probabilistic process-based shallow landslide model for mapping probability of landslide initiation, transport, and deposition at regional scales. The empirical model integrates the influence of seven site attribute (SA) classes: elevation, slope, curvature, aspect, land use-land cover, lithology, and topographic wetness index, on over 1,600 observed landslides using a frequency ratio (FR) approach. A susceptibility index is calculated by adding FRs for each SA on a grid-cell basis. Using landslide observations we relate susceptibility index to an empirically-derived probability of landslide impact. This probability is combined with results from a physically-based model to produce an integrated probabilistic map. Slope was key in landslide initiation while deposition was linked to lithology and elevation. Vegetation transition from forest to alpine vegetation and barren land cover with lower root cohesion leads to higher frequency of initiation. Aspect effects are likely linked to differences in root cohesion and moisture controlled by solar insulation and snow. We demonstrate the model in the North Cascades of Washington, USA and identify locations of high and low probability of landslide impacts that can be used by land managers in their design, planning, and maintenance.

  14. Modeling styles in business process modeling

    NARCIS (Netherlands)

    Pinggera, J.; Soffer, P.; Zugal, S.; Weber, B.; Weidlich, M.; Fahland, D.; Reijers, H.A.; Mendling, J.; Bider, I.; Halpin, T.; Krogstie, J.; Nurcan, S.; Proper, E.; Schmidt, R.; Soffer, P.; Wrycza, S.

    2012-01-01

    Research on quality issues of business process models has recently begun to explore the process of creating process models. As a consequence, the question arises whether different ways of creating process models exist. In this vein, we observed 115 students engaged in the act of modeling, recording

  15. Integrated Main Propulsion System Performance Reconstruction Process/Models

    Science.gov (United States)

    Lopez, Eduardo; Elliott, Katie; Snell, Steven; Evans, Michael

    2013-01-01

    The Integrated Main Propulsion System (MPS) Performance Reconstruction process provides the MPS post-flight data files needed for postflight reporting to the project integration management and key customers to verify flight performance. This process/model was used as the baseline for the currently ongoing Space Launch System (SLS) work. The process utilizes several methodologies, including multiple software programs, to model integrated propulsion system performance through space shuttle ascent. It is used to evaluate integrated propulsion systems, including propellant tanks, feed systems, rocket engine, and pressurization systems performance throughout ascent based on flight pressure and temperature data. The latest revision incorporates new methods based on main engine power balance model updates to model higher mixture ratio operation at lower engine power levels.

  16. Fuzzy-based HAZOP study for process industry

    Energy Technology Data Exchange (ETDEWEB)

    Ahn, Junkeon; Chang, Daejun, E-mail: djchang@kaist.edu

    2016-11-05

    Highlights: • HAZOP is the important technique to evaluate system safety and its risks while process operations. • Fuzzy theory can handle the inherent uncertainties of process systems for the HAZOP. • Fuzzy-based HAZOP considers the aleatory and epistemic uncertainties and provides the risk level with less uncertainty. • Risk acceptance criteria should be considered regarding the transition region for each risk. - Abstract: This study proposed a fuzzy-based HAZOP for analyzing process hazards. Fuzzy theory was used to express uncertain states. This theory was found to be a useful approach to overcome the inherent uncertainty in HAZOP analyses. Fuzzy logic sharply contrasted with classical logic and provided diverse risk values according to its membership degree. Appropriate process parameters and guidewords were selected to describe the frequency and consequence of an accident. Fuzzy modeling calculated risks based on the relationship between the variables of an accident. The modeling was based on the mean expected value, trapezoidal fuzzy number, IF-THEN rules, and the center of gravity method. A cryogenic LNG (liquefied natural gas) testing facility was the objective process for the fuzzy-based and conventional HAZOPs. The most significant index is the frequency to determine risks. The comparison results showed that the fuzzy-based HAZOP provides better sophisticated risks than the conventional HAZOP. The fuzzy risk matrix presents the significance of risks, negligible risks, and necessity of risk reduction.

  17. Dynamic Model of Basic Oxygen Steelmaking Process Based on Multi-zone Reaction Kinetics: Model Derivation and Validation

    Science.gov (United States)

    Rout, Bapin Kumar; Brooks, Geoff; Rhamdhani, M. Akbar; Li, Zushu; Schrama, Frank N. H.; Sun, Jianjun

    2018-04-01

    A multi-zone kinetic model coupled with a dynamic slag generation model was developed for the simulation of hot metal and slag composition during the basic oxygen furnace (BOF) operation. The three reaction zones (i) jet impact zone, (ii) slag-bulk metal zone, (iii) slag-metal-gas emulsion zone were considered for the calculation of overall refining kinetics. In the rate equations, the transient rate parameters were mathematically described as a function of process variables. A micro and macroscopic rate calculation methodology (micro-kinetics and macro-kinetics) were developed to estimate the total refining contributed by the recirculating metal droplets through the slag-metal emulsion zone. The micro-kinetics involves developing the rate equation for individual droplets in the emulsion. The mathematical models for the size distribution of initial droplets, kinetics of simultaneous refining of elements, the residence time in the emulsion, and dynamic interfacial area change were established in the micro-kinetic model. In the macro-kinetics calculation, a droplet generation model was employed and the total amount of refining by emulsion was calculated by summing the refining from the entire population of returning droplets. A dynamic FetO generation model based on oxygen mass balance was developed and coupled with the multi-zone kinetic model. The effect of post-combustion on the evolution of slag and metal composition was investigated. The model was applied to a 200-ton top blowing converter and the simulated value of metal and slag was found to be in good agreement with the measured data. The post-combustion ratio was found to be an important factor in controlling FetO content in the slag and the kinetics of Mn and P in a BOF process.

  18. Cost analysis of simulated base-catalyzed biodiesel production processes

    International Nuclear Information System (INIS)

    Tasić, Marija B.; Stamenković, Olivera S.; Veljković, Vlada B.

    2014-01-01

    Highlights: • Two semi-continuous biodiesel production processes from sunflower oil are simulated. • Simulations were based on the kinetics of base-catalyzed methanolysis reactions. • The total energy consumption was influenced by the kinetic model. • Heterogeneous base-catalyzed process is a preferable industrial technology. - Abstract: The simulation and economic feasibility evaluation of semi-continuous biodiesel production from sunflower oil were based on the kinetics of homogeneously (Process I) and heterogeneously (Process II) base-catalyzed methanolysis reactions. The annual plant’s capacity was determined to be 8356 tonnes of biodiesel. The total energy consumption was influenced by the unit model describing the methanolysis reaction kinetics. The energy consumption of the Process II was more than 2.5 times lower than that of the Process I. Also, the simulation showed the Process I had more and larger process equipment units, compared with the Process II. Based on lower total capital investment costs and biodiesel selling price, the Process II was economically more feasible than the Process I. Sensitivity analysis was conducted using variable sunflower oil and biodiesel prices. Using a biodiesel selling price of 0.990 $/kg, Processes I and II were shown to be economically profitable if the sunflower oil price was 0.525 $/kg and 0.696 $/kg, respectively

  19. Stochastic dynamical model of a growing citation network based on a self-exciting point process.

    Science.gov (United States)

    Golosovsky, Michael; Solomon, Sorin

    2012-08-31

    We put under experimental scrutiny the preferential attachment model that is commonly accepted as a generating mechanism of the scale-free complex networks. To this end we chose a citation network of physics papers and traced the citation history of 40,195 papers published in one year. Contrary to common belief, we find that the citation dynamics of the individual papers follows the superlinear preferential attachment, with the exponent α=1.25-1.3. Moreover, we show that the citation process cannot be described as a memoryless Markov chain since there is a substantial correlation between the present and recent citation rates of a paper. Based on our findings we construct a stochastic growth model of the citation network, perform numerical simulations based on this model and achieve an excellent agreement with the measured citation distributions.

  20. A stream-based mathematical model for distributed information processing systems - SysLab system model

    OpenAIRE

    Klein, Cornel; Rumpe, Bernhard; Broy, Manfred

    2014-01-01

    In the SysLab project we develop a software engineering method based on a mathematical foundation. The SysLab system model serves as an abstract mathematical model for information systems and their components. It is used to formalize the semantics of all used description techniques such as object diagrams state automata sequence charts or data-flow diagrams. Based on the requirements for such a reference model, we define the system model including its different views and their relationships.

  1. Modelling Template for the Development of the Process Flowsheet

    DEFF Research Database (Denmark)

    Fedorova, Marina; Gani, Rafiqul

    2015-01-01

    Models are playing important roles in design and analysis of chemicals/bio-chemicals based products and the processes that manufacture them. Model-based methods and tools have the potential to decrease the number of experiments, which can be expensive and time consuming, and point to candidates...... in connection to other modelling tools within the modelling framework are forming a user-friendly system, which will make the model development process easier and faster and provide the way for unified and consistent model documentation. The modeller can use the template for their specific problem or to extend...... models systematically, efficiently and reliably. In this way, development of products and processes can be faster, cheaper and very efficient. The developed modelling framework involves three main parts: 1) a modelling tool, that includes algorithms for model generation; 2) a template library, which...

  2. Dual processing model of medical decision-making

    OpenAIRE

    Djulbegovic, Benjamin; Hozo, Iztok; Beckstead, Jason; Tsalatsanis, Athanasios; Pauker, Stephen G

    2012-01-01

    Abstract Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administe...

  3. Neuroscientific Model of Motivational Process

    Science.gov (United States)

    Kim, Sung-il

    2013-01-01

    Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area) in which basic stimulus-action association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision-making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously. The striatum and the orbitofrontal cortex (valuation area) play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area) and the dorsolateral prefrontal cortex (cognitive control area) are the main neural circuits related to regulation of motivation. These three sub processes interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment. PMID:23459598

  4. Neuroscientific model of motivational process.

    Science.gov (United States)

    Kim, Sung-Il

    2013-01-01

    Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area) in which basic stimulus-action association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision-making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously. The striatum and the orbitofrontal cortex (valuation area) play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area) and the dorsolateral prefrontal cortex (cognitive control area) are the main neural circuits related to regulation of motivation. These three sub processes interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment.

  5. Modelling of solidification processing and continuous strip casting for copper-base alloys

    Energy Technology Data Exchange (ETDEWEB)

    Mahmoudi, Jafar [Royal Inst. of Tech., Stockholm (Sweden). Dept. of Materials Processing

    2000-04-01

    An experimental and numerical study was carried out to investigate the solidification process in a copper continuous strip casting process. Heat flow and solidification process has been experimentally studied. Cooling curves during solidification were registered using a thermocouple of type K connected to a data acquisition system. Temperature measurements in the mould and cooling water were also performed. The numerical model considers a generalized set of mass, momentum and heat equations that is valid for the solid, liquid and solidification interval in the cast. A k-{epsilon} turbulence model, produced with the commercial program CFX, is used to analyse the solidification process of pure copper in the mould region of the caster. The fluid flow, temperature and heat flux distributions in the mould region of the caster were computed. The shape and location of the solidification front were also determined. The effects of the parameters such as heat transfer coefficient, casting speed, casting temperature, heat of fusion and specific heat on the shape and location of the solidification front and the heat transport at the mould-cast interface were investigated. The predicted temperature and heat flux distributions were compared with experimental measurements, and reasonable agreement was obtained. The solidification behaviour of pure copper and different copper base alloys has been studied. A series of solidification experiments using DTA furnace, mirror furnace and levitation technique were performed on different copper-base alloys. The undercooling, cooling rates of the liquid and the solid states, solidification times and temperatures were evaluated from the curves. The cooling curves for different samples were simulated using a FEM solidification program. It was found that the calculated values of the heat of fusion were much lower than the tabulated ones. The fraction of solid formed before quenching, in the DTA experiments, has been observed to be much higher

  6. A novel model-based control strategy for aerobic filamentous fungal fed-batch fermentation processes.

    Science.gov (United States)

    Mears, Lisa; Stocks, Stuart M; Albaek, Mads O; Cassells, Benny; Sin, Gürkan; Gernaey, Krist V

    2017-07-01

    A novel model-based control strategy has been developed for filamentous fungal fed-batch fermentation processes. The system of interest is a pilot scale (550 L) filamentous fungus process operating at Novozymes A/S. In such processes, it is desirable to maximize the total product achieved in a batch in a defined process time. In order to achieve this goal, it is important to maximize both the product concentration, and also the total final mass in the fed-batch system. To this end, we describe the development of a control strategy which aims to achieve maximum tank fill, while avoiding oxygen limited conditions. This requires a two stage approach: (i) calculation of the tank start fill; and (ii) on-line control in order to maximize fill subject to oxygen transfer limitations. First, a mechanistic model was applied off-line in order to determine the appropriate start fill for processes with four different sets of process operating conditions for the stirrer speed, headspace pressure, and aeration rate. The start fills were tested with eight pilot scale experiments using a reference process operation. An on-line control strategy was then developed, utilizing the mechanistic model which is recursively updated using on-line measurements. The model was applied in order to predict the current system states, including the biomass concentration, and to simulate the expected future trajectory of the system until a specified end time. In this way, the desired feed rate is updated along the progress of the batch taking into account the oxygen mass transfer conditions and the expected future trajectory of the mass. The final results show that the target fill was achieved to within 5% under the maximum fill when tested using eight pilot scale batches, and over filling was avoided. The results were reproducible, unlike the reference experiments which show over 10% variation in the final tank fill, and this also includes over filling. The variance of the final tank fill is

  7. Measures of quality of process models created in BPMN

    Directory of Open Access Journals (Sweden)

    Radek Hronza

    2015-12-01

    Full Text Available Description, documentation, evaluation and redesign of key processes during their execution should be an essential part of the strategic management of any organization. All organizations live in a dynamically changing environment. Therefore they must adapt its internal processes to market changes. These processes must be described. Suitable way of description could be BPMN notation. Right after description of processes via BPMN, processes should be controlled to ensure expected of their quality. System (which could be automated based on mathematical expression of qualitative characteristics of process models (i.e. measures of quality of process models can support mentioned process controls. Research team trying to design and get into practical use such a tool. The aim of this publication is description of mentioned system – based on measures of the quality of process models - and answer associated scientific questions.

  8. Feature-based tolerancing for intelligent inspection process definition

    International Nuclear Information System (INIS)

    Brown, C.W.

    1993-07-01

    This paper describes a feature-based tolerancing capability that complements a geometric solid model with an explicit representation of conventional and geometric tolerances. This capability is focused on supporting an intelligent inspection process definition system. The feature-based tolerance model's benefits include advancing complete product definition initiatives (e.g., STEP -- Standard for Exchange of Product model dam), suppling computer-integrated manufacturing applications (e.g., generative process planning and automated part programming) with product definition information, and assisting in the solution of measurement performance issues. A feature-based tolerance information model was developed based upon the notion of a feature's toleranceable aspects and describes an object-oriented scheme for representing and relating tolerance features, tolerances, and datum reference frames. For easy incorporation, the tolerance feature entities are interconnected with STEP solid model entities. This schema will explicitly represent the tolerance specification for mechanical products, support advanced dimensional measurement applications, and assist in tolerance-related methods divergence issues

  9. Process modeling style

    CERN Document Server

    Long, John

    2014-01-01

    Process Modeling Style focuses on other aspects of process modeling beyond notation that are very important to practitioners. Many people who model processes focus on the specific notation used to create their drawings. While that is important, there are many other aspects to modeling, such as naming, creating identifiers, descriptions, interfaces, patterns, and creating useful process documentation. Experience author John Long focuses on those non-notational aspects of modeling, which practitioners will find invaluable. Gives solid advice for creating roles, work produ

  10. Qualitative simulation in formal process modelling

    International Nuclear Information System (INIS)

    Sivertsen, Elin R.

    1999-01-01

    In relation to several different research activities at the OECD Halden Reactor Project, the usefulness of formal process models has been identified. Being represented in some appropriate representation language, the purpose of these models is to model process plants and plant automatics in a unified way to allow verification and computer aided design of control strategies. The present report discusses qualitative simulation and the tool QSIM as one approach to formal process models. In particular, the report aims at investigating how recent improvements of the tool facilitate the use of the approach in areas like process system analysis, procedure verification, and control software safety analysis. An important long term goal is to provide a basis for using qualitative reasoning in combination with other techniques to facilitate the treatment of embedded programmable systems in Probabilistic Safety Analysis (PSA). This is motivated from the potential of such a combination in safety analysis based on models comprising both software, hardware, and operator. It is anticipated that the research results from this activity will benefit V and V in a wide variety of applications where formal process models can be utilized. Examples are operator procedures, intelligent decision support systems, and common model repositories (author) (ml)

  11. Markov Decision Process Measurement Model.

    Science.gov (United States)

    LaMar, Michelle M

    2018-03-01

    Within-task actions can provide additional information on student competencies but are challenging to model. This paper explores the potential of using a cognitive model for decision making, the Markov decision process, to provide a mapping between within-task actions and latent traits of interest. Psychometric properties of the model are explored, and simulation studies report on parameter recovery within the context of a simple strategy game. The model is then applied to empirical data from an educational game. Estimates from the model are found to correlate more strongly with posttest results than a partial-credit IRT model based on outcome data alone.

  12. Mathematical model of seed germination process

    International Nuclear Information System (INIS)

    Gładyszewska, B.; Koper, R.; Kornarzyński, K.

    1999-01-01

    An analytical model of seed germination process was described. The model based on proposed working hypothesis leads - by analogy - to a law corresponding with Verhulst-Pearl's law, known from the theory of population kinetics. The model was applied to describe the germination kinetics of tomato seeds, Promyk field cultivar, biostimulated by laser treatment. Close agreement of experimental and model data was obtained [pl

  13. Solution processed deposition of electron transport layers on perovskite crystal surface—A modeling based study

    Energy Technology Data Exchange (ETDEWEB)

    Mortuza, S.M.; Taufique, M.F.N.; Banerjee, Soumik, E-mail: soumik.banerjee@wsu.edu

    2017-02-01

    Highlights: • The model determined the surface coverage of solution-processed film on perovskite. • Calculated surface density map provides insight into morphology of the monolayer. • Carbonyl oxygen atom of PCBM strongly attaches to the (110) surface of perovskite. • Uniform distribution of clusters on perovskite surface at lower PCBM concentration. • Deposition rate of PCBM on the surface is very high at initial stage of film growth. - Abstract: The power conversion efficiency (PCE) of planar perovskite solar cells (PSCs) has reached up to ∼20%. However, structural and chemicals defects that lead to hysteresis in the perovskite based thin film pose challenges. Recent work has shown that thin films of [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) deposited on the photo absorption layer, using solution processing techniques, minimize surface pin holes and defects thereby increasing the PCE. We developed and employed a multiscale model based on molecular dynamics (MD) and kinetic Monte Carlo (kMC) to establish a relationship between deposition rate and surface coverage on perovskite surface. The MD simulations of PCBMs dispersed in chlorobenzene, sandwiched between (110) perovskite substrates, indicate that PCBMs are deposited through anchoring of the oxygen atom of carbonyl group to the exposed lead (Pb) atom of (110) perovskite surface. Based on rates of distinct deposition events calculated from MD, kMC simulations were run to determine surface coverage at much larger time and length scales than accessible by MD alone. Based on the model, a generic relationship is established between deposition rate of PCBMs and surface coverage on perovskite crystal. The study also provides detailed insights into the morphology of the deposited film.

  14. Solution processed deposition of electron transport layers on perovskite crystal surface—A modeling based study

    International Nuclear Information System (INIS)

    Mortuza, S.M.; Taufique, M.F.N.; Banerjee, Soumik

    2017-01-01

    Highlights: • The model determined the surface coverage of solution-processed film on perovskite. • Calculated surface density map provides insight into morphology of the monolayer. • Carbonyl oxygen atom of PCBM strongly attaches to the (110) surface of perovskite. • Uniform distribution of clusters on perovskite surface at lower PCBM concentration. • Deposition rate of PCBM on the surface is very high at initial stage of film growth. - Abstract: The power conversion efficiency (PCE) of planar perovskite solar cells (PSCs) has reached up to ∼20%. However, structural and chemicals defects that lead to hysteresis in the perovskite based thin film pose challenges. Recent work has shown that thin films of [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) deposited on the photo absorption layer, using solution processing techniques, minimize surface pin holes and defects thereby increasing the PCE. We developed and employed a multiscale model based on molecular dynamics (MD) and kinetic Monte Carlo (kMC) to establish a relationship between deposition rate and surface coverage on perovskite surface. The MD simulations of PCBMs dispersed in chlorobenzene, sandwiched between (110) perovskite substrates, indicate that PCBMs are deposited through anchoring of the oxygen atom of carbonyl group to the exposed lead (Pb) atom of (110) perovskite surface. Based on rates of distinct deposition events calculated from MD, kMC simulations were run to determine surface coverage at much larger time and length scales than accessible by MD alone. Based on the model, a generic relationship is established between deposition rate of PCBMs and surface coverage on perovskite crystal. The study also provides detailed insights into the morphology of the deposited film.

  15. SLS Navigation Model-Based Design Approach

    Science.gov (United States)

    Oliver, T. Emerson; Anzalone, Evan; Geohagan, Kevin; Bernard, Bill; Park, Thomas

    2018-01-01

    The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and

  16. Self-exciting point process in modeling earthquake occurrences

    International Nuclear Information System (INIS)

    Pratiwi, H.; Slamet, I.; Respatiwulan; Saputro, D. R. S.

    2017-01-01

    In this paper, we present a procedure for modeling earthquake based on spatial-temporal point process. The magnitude distribution is expressed as truncated exponential and the event frequency is modeled with a spatial-temporal point process that is characterized uniquely by its associated conditional intensity process. The earthquakes can be regarded as point patterns that have a temporal clustering feature so we use self-exciting point process for modeling the conditional intensity function. The choice of main shocks is conducted via window algorithm by Gardner and Knopoff and the model can be fitted by maximum likelihood method for three random variables. (paper)

  17. Modeling of Rocket Fuel Heating and Cooling Processes in the Interior Receptacle Space of Ground-Based Systems

    Directory of Open Access Journals (Sweden)

    K. I. Denisova

    2016-01-01

    Full Text Available The propellant to fill the fuel tanks of the spacecraft, upper stages, and space rockets on technical and ground-based launch sites before fueling should be prepared to ensure many of its parameters, including temperature, in appropriate condition. Preparation of fuel temperature is arranged through heating and cooling the rocket propellants (RP in the tanks of fueling equipment. Processes of RP temperature preparation are the most energy-intensive and timeconsuming ones, which require that a choice of sustainable technologies and modes of cooling (heating RP provided by the ground-based equipment has been made through modeling of the RP [1] temperature preparation processes at the stage of design and operation of the groundbased fueling equipment.The RP temperature preparation in the tanks of the ground-based systems can be provided through the heat-exchangers built-in the internal space and being external with respect to the tank in which antifreeze, air or liquid nitrogen may be used as the heat transfer media. The papers [1-12], which note a promising use of the liquid nitrogen to cool PR, present schematic diagrams and modeling systems for the RP temperature preparation in the fueling equipment of the ground-based systems.We consider the RP temperature preparation using heat exchangers to be placed directly in RP tanks. Feeding the liquid nitrogen into heat exchanger with the antifreeze provides the cooling mode of PR while a heated air fed there does that of heating. The paper gives the systems of equations and results of modeling the processes of RP temperature preparation, and its estimated efficiency.The systems of equations of cooling and heating RP are derived on the assumption that the heat exchange between the fuel and the antifreeze, as well as between the storage tank and the environment is quasi-stationary.The paper presents calculation results of the fuel temperature in the tank, and coolant temperature in the heat exchanger, as

  18. Progress toward forecasting product quality and quantity of mammalian cell culture processes by performance-based modeling.

    Science.gov (United States)

    Schmidberger, Timo; Posch, Christoph; Sasse, Alexandra; Gülch, Carina; Huber, Robert

    2015-01-01

    The production of biopharmaceuticals requires highly sophisticated, complex cell based processes. Once a process has been developed, acceptable ranges for various control parameters are typically defined based on process characterization studies often comprising several dozens of small scale bioreactor cultivations. A lot of data is generated during these studies and usually only the information needed to define acceptable ranges is processed in more detail. Making use of the wealth of information contained in such data sets, we present here a methodology that uses performance data (such as metabolite profiles) to forecast the product quality and quantity of mammalian cell culture processes based on a toolbox of advanced statistical methods. With this performance based modeling (PBM) the final product concentration and 12 quality attributes (QAs) for two different biopharmaceutical products were predicted in daily intervals throughout the main stage process. The best forecast was achieved for product concentration in a very early phase of the process. Furthermore, some glycan isoforms were predicted with good accuracy several days before the bioreactor was harvested. Overall, PBM clearly demonstrated its capability of early process endpoint prediction by only using commonly available data, even though it was not possible to predict all QAs with the desired accuracy. Knowing the product quality prior to the harvest allows the manufacturer to take counter measures in case the forecasted quality or quantity deviates from what is expected. This would be a big step towards real-time release, an important element of the FDA's PAT initiative. © 2015 American Institute of Chemical Engineers.

  19. GIS-based modelling of odour emitted from the waste processing plant: case study

    Directory of Open Access Journals (Sweden)

    Sόwka Izabela

    2017-01-01

    Full Text Available The emission of odours into the atmospheric air from the municipal economy and industrial plants, especially in urbanized areas, causes a serious problem, which the mankind has been struggling with for years. The excessive exposure of people to odours may result in many negative health effects, including, for example, headaches and vomiting. There are many different methods that are used in order to evaluate the odour nuisance. The results obtained through those methods can then be used to carry out a visualization and an analysis of a distribution of the odour concentrations in a given area by using the GIS (Geographic Information System. By their application to the spatial analysis of the impact of odours, we can enable the assessment of the magnitude and likelihood of the occurrence of odour nuisance. Modelling using GIS tools and spatial interpolation like IDW method and kriging can provide an alternative to the standard modelling tools, which generally use the emission values from sources that are identified as major emitters of odours. The work presents the result, based on the odour measurements data from waste processing plant, of the attempt to connect two different tools – the reference model OPERAT FB and GIS-based dispersion modelling performed using IDW method and ordinary kriging to analyse their behaviour in terms of limited observation values.

  20. Implicit Schemata and Categories in Memory-Based Language Processing

    Science.gov (United States)

    van den Bosch, Antal; Daelemans, Walter

    2013-01-01

    Memory-based language processing (MBLP) is an approach to language processing based on exemplar storage during learning and analogical reasoning during processing. From a cognitive perspective, the approach is attractive as a model for human language processing because it does not make any assumptions about the way abstractions are shaped, nor any…

  1. Nitrogen Cycling in Permeable Sediments: Process-based Models for Streams and the Coastal Ocean

    OpenAIRE

    Azizian, Morvarid

    2017-01-01

    Bioavailable forms of nitrogen, such as nitrate, are necessary for aquatic ecosystem productivity. Excess nitrate in aquatic systems, however, can adversely affect ecosystems and degrade both surface water and groundwater. Some of this excess nitrate can be removed in the sediments that line the bottom of rivers and coastal waters, through the exchange of water between surface water and groundwater (known as hyporheic exchange).Several process-based models have been proposed for estimating ni...

  2. Process based model sheds light on climate sensitivity of Mediterranean tree-ring width

    Directory of Open Access Journals (Sweden)

    R. Touchan

    2012-03-01

    Full Text Available We use the process-based VS (Vaganov-Shashkin model to investigate whether a regional Pinus halepensis tree-ring chronology from Tunisia can be simulated as a function of climate alone by employing a biological model linking day length and daily temperature and precipitation (AD 1959–2004 from a climate station to ring-width variations. We check performance of the model on independent data by a validation exercise in which the model's parameters are tuned using data for 1982–2004 and the model is applied to generate tree-ring indices for 1959–1981. The validation exercise yields a highly significant positive correlation between the residual chronology and estimated growth curve (r=0.76 p<0.0001, n=23. The model shows that the average duration of the growing season is 191 days, with considerable variation from year to year. On average, soil moisture limits tree-ring growth for 128 days and temperature for 63 days. Model results depend on chosen values of parameters, in particular a parameter specifying a balance ratio between soil moisture and precipitation. Future work in the Mediterranean region should include multi-year natural experiments to verify patterns of cambial-growth variation suggested by the VS model.

  3. Modeling gross primary production of agro-forestry ecosystems by assimilation of satellite-derived information in a process-based model.

    Science.gov (United States)

    Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

    2009-01-01

    In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

  4. Modeling Gross Primary Production of Agro-Forestry Ecosystems by Assimilation of Satellite-Derived Information in a Process-Based Model

    Directory of Open Access Journals (Sweden)

    Guenther Seufert

    2009-02-01

    Full Text Available In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC with the aims of i improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

  5. Individual-based modeling of ecological and evolutionary processes

    Science.gov (United States)

    DeAngelis, Donald L.; Mooij, Wolf M.

    2005-01-01

    Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential-equation and difference-equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis for IBMs by describing five major types of individual variation in IBMs: spatial, ontogenetic, phenotypic, cognitive, and genetic. IBMs are now used in almost all subfields of ecology and evolutionary biology. We map those subfields and look more closely at selected key papers on fish recruitment, forest dynamics, sympatric speciation, metapopulation dynamics, maintenance of diversity, and species conservation. Theorists are currently divided on whether IBMs represent only a practical tool for extending classical theory to more complex situations, or whether individual-based theory represents a radically new research program. We feel that the tension between these two poles of thinking can be a source of creativity in ecology and evolutionary theory.

  6. Performance of process-based models for simulation of grain N in crop rotations across Europe

    DEFF Research Database (Denmark)

    Yin, Xiaogang; Kersebaum, KC; Kollas, C

    2017-01-01

    The accurate estimation of crop grain nitrogen (N; N in grain yield) is crucial for optimizing agricultural N management, especially in crop rotations. In the present study, 12 process-based models were applied to simulate the grain N of i) seven crops in rotations, ii) across various pedo...... (Brassica napus L.). These differences are linked to the intensity of parameterization with better parameterized crops showing lower prediction errors. The model performance was influenced by N fertilization and irrigation treatments, and a majority of the predictions were more accurate under low N...

  7. Understanding Quality in Process Modelling: Towards a Holistic Perspective

    Directory of Open Access Journals (Sweden)

    Jan Recker

    2007-09-01

    Full Text Available Quality is one of the main topics in current conceptual modelling research, as is the field of business process modelling. Yet, widely acknowledged academic contributions towards an understanding or measurement of business process model quality are limited at best. In this paper I argue that the development of methodical theories concerning the measurement or establishment of process model quality must be preceded by methodological elaborations on business process modelling. I further argue that existing epistemological foundations of process modelling are insufficient for describing all extrinsic and intrinsic traits of model quality. This in turn has led to a lack of holistic understanding of process modelling. Taking into account the inherent social and purpose-oriented character of process modelling in contemporary organizations I present a socio-pragmatic constructionist methodology of business process modelling and sketch out implications of this perspective towards an understanding of process model quality. I anticipate that, based on this research, theories can be developed that facilitate the evaluation of the ’goodness’ of a business process model.

  8. Transforming Existing Procedural Business Processes into a Constraint-Based Formalism

    NARCIS (Netherlands)

    dr. Martijn Zoet; Eline de Haan; Floor Vermeer; Jeroen van Grondelle; Slinger Jansen

    2013-01-01

    Many organizations use business process management to manage and model their processes. Currently, flow-based process formalisms, such as BPMN, are considered the standard for modeling processes. However, recent literature describes several limitations of this type of formalism that can be solved by

  9. Developing a framework to model the primary drying step of a continuous freeze-drying process based on infrared radiation

    DEFF Research Database (Denmark)

    Van Bockstal, Pieter-Jan; Corver, Jos; Mortier, Séverine Thérèse F.C.

    2018-01-01

    . These results assist in the selection of proper materials which could serve as IR window in the continuous freeze-drying prototype. The modelling framework presented in this paper fits the model-based design approach used for the development of this prototype and shows the potential benefits of this design...... requires the fundamental mechanistic modelling of each individual process step. Therefore, a framework is presented for the modelling and control of the continuous primary drying step based on non-contact IR radiation. The IR radiation emitted by the radiator filaments passes through various materials...

  10. Three-dimensional model analysis and processing

    CERN Document Server

    Yu, Faxin; Luo, Hao; Wang, Pinghui

    2011-01-01

    This book focuses on five hot research directions in 3D model analysis and processing in computer science:  compression, feature extraction, content-based retrieval, irreversible watermarking and reversible watermarking.

  11. Neuroscientific Model of Motivational Process

    Directory of Open Access Journals (Sweden)

    Sung-Il eKim

    2013-03-01

    Full Text Available Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three subprocesses, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous subprocesses, namely reward-driven approach, value-based decision making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area in which basic stimulus-action association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously. The striatum and the orbitofrontal cortex (valuation area play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area and the dorsolateral prefrontal cortex (cognitive control area are the main neural circuits related to regulation of motivation. These three subprocesses interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment.

  12. Remote Sensing Image Enhancement Based on Non-subsampled Shearlet Transform and Parameterized Logarithmic Image Processing Model

    Directory of Open Access Journals (Sweden)

    TAO Feixiang

    2015-08-01

    Full Text Available Aiming at parts of remote sensing images with dark brightness and low contrast, a remote sensing image enhancement method based on non-subsampled Shearlet transform and parameterized logarithmic image processing model is proposed in this paper to improve the visual effects and interpretability of remote sensing images. Firstly, a remote sensing image is decomposed into a low-frequency component and high frequency components by non-subsampled Shearlet transform.Then the low frequency component is enhanced according to PLIP (parameterized logarithmic image processing model, which can improve the contrast of image, while the improved fuzzy enhancement method is used to enhance the high frequency components in order to highlight the information of edges and details. A large number of experimental results show that, compared with five kinds of image enhancement methods such as bidirectional histogram equalization method, the method based on stationary wavelet transform and the method based on non-subsampled contourlet transform, the proposed method has advantages in both subjective visual effects and objective quantitative evaluation indexes such as contrast and definition, which can more effectively improve the contrast of remote sensing image and enhance edges and texture details with better visual effects.

  13. Tree-based flood damage modeling of companies: Damage processes and model performance

    Science.gov (United States)

    Sieg, Tobias; Vogel, Kristin; Merz, Bruno; Kreibich, Heidi

    2017-07-01

    Reliable flood risk analyses, including the estimation of damage, are an important prerequisite for efficient risk management. However, not much is known about flood damage processes affecting companies. Thus, we conduct a flood damage assessment of companies in Germany with regard to two aspects. First, we identify relevant damage-influencing variables. Second, we assess the prediction performance of the developed damage models with respect to the gain by using an increasing amount of training data and a sector-specific evaluation of the data. Random forests are trained with data from two postevent surveys after flood events occurring in the years 2002 and 2013. For a sector-specific consideration, the data set is split into four subsets corresponding to the manufacturing, commercial, financial, and service sectors. Further, separate models are derived for three different company assets: buildings, equipment, and goods and stock. Calculated variable importance values reveal different variable sets relevant for the damage estimation, indicating significant differences in the damage process for various company sectors and assets. With an increasing number of data used to build the models, prediction errors decrease. Yet the effect is rather small and seems to saturate for a data set size of several hundred observations. In contrast, the prediction improvement achieved by a sector-specific consideration is more distinct, especially for damage to equipment and goods and stock. Consequently, sector-specific data acquisition and a consideration of sector-specific company characteristics in future flood damage assessments is expected to improve the model performance more than a mere increase in data.

  14. Process Models for Security Architectures

    Directory of Open Access Journals (Sweden)

    Floarea NASTASE

    2006-01-01

    Full Text Available This paper presents a model for an integrated security system, which can be implemented in any organization. It is based on security-specific standards and taxonomies as ISO 7498-2 and Common Criteria. The functionalities are derived from the classes proposed in the Common Criteria document. In the paper we present the process model for each functionality and also we focus on the specific components.

  15. Event-Based Conceptual Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2009-01-01

    The purpose of the paper is to obtain insight into and provide practical advice for event-based conceptual modeling. We analyze a set of event concepts and use the results to formulate a conceptual event model that is used to identify guidelines for creation of dynamic process models and static...... information models. We characterize events as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms of information structures. The conceptual event model is used to characterize a variety of event concepts and it is used to illustrate how events can...... be used to integrate dynamic modeling of processes and static modeling of information structures. The results are unique in the sense that no other general event concept has been used to unify a similar broad variety of seemingly incompatible event concepts. The general event concept can be used...

  16. Process-based coastal erosion modeling for Drew Point (North Slope, Alaska)

    Science.gov (United States)

    Ravens, Thomas M.; Jones, Benjamin M.; Zhang, Jinlin; Arp, Christopher D.; Schmutz, Joel A.

    2012-01-01

    A predictive, coastal erosion/shoreline change model has been developed for a small coastal segment near Drew Point, Beaufort Sea, Alaska. This coastal setting has experienced a dramatic increase in erosion since the early 2000’s. The bluffs at this site are 3-4 m tall and consist of ice-wedge bounded blocks of fine-grained sediments cemented by ice-rich permafrost and capped with a thin organic layer. The bluffs are typically fronted by a narrow (∼ 5  m wide) beach or none at all. During a storm surge, the sea contacts the base of the bluff and a niche is formed through thermal and mechanical erosion. The niche grows both vertically and laterally and eventually undermines the bluff, leading to block failure or collapse. The fallen block is then eroded both thermally and mechanically by waves and currents, which must occur before a new niche forming episode may begin. The erosion model explicitly accounts for and integrates a number of these processes including: (1) storm surge generation resulting from wind and atmospheric forcing, (2) erosional niche growth resulting from wave-induced turbulent heat transfer and sediment transport (using the Kobayashi niche erosion model), and (3) thermal and mechanical erosion of the fallen block. The model was calibrated with historic shoreline change data for one time period (1979-2002), and validated with a later time period (2002-2007).

  17. Plasma Processing of Model Residential Solid Waste

    Science.gov (United States)

    Messerle, V. E.; Mossé, A. L.; Nikonchuk, A. N.; Ustimenko, A. B.; Baimuldin, R. V.

    2017-09-01

    The authors have tested the technology of processing of model residential solid waste. They have developed and created a pilot plasma unit based on a plasma chamber incinerator. The waste processing technology has been tested and prepared for commercialization.

  18. A subjective and objective fuzzy-based analytical hierarchy process model for prioritization of lean product development practices

    Directory of Open Access Journals (Sweden)

    Daniel O. Aikhuele

    2017-06-01

    Full Text Available In this paper, a subjective and objective fuzzy-based Analytical Hierarchy Process (AHP model is proposed. The model which is based on a newly defined evaluation matrix replaces the fuzzy comparison matrix (FCM in the traditional fuzzy AHP model, which has been found ineffective and time-consuming when criteria/alternatives are increased. The main advantage of the new model is that it is straightforward and completely eliminates the repetitive adjustment of data that is common with the FCM in traditional AHP model. The model reduces the complete dependen-cy on human judgment in prioritization assessment since the weights values are solved automati-cally using the evaluation matrix and the modified priority weight formula in the proposed mod-el. By virtue of a numerical case study, the model is successfully applied in the determination of the implementation priorities of lean practices for a product development environment and com-pared with similar computational methods in the literature.

  19. Pavement maintenance optimization model using Markov Decision Processes

    Science.gov (United States)

    Mandiartha, P.; Duffield, C. F.; Razelan, I. S. b. M.; Ismail, A. b. H.

    2017-09-01

    This paper presents an optimization model for selection of pavement maintenance intervention using a theory of Markov Decision Processes (MDP). There are some particular characteristics of the MDP developed in this paper which distinguish it from other similar studies or optimization models intended for pavement maintenance policy development. These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear programming solution. The limited information or discussions that are available on these matters in terms of stochastic based optimization model in road network management motivates this study. This paper uses a data set acquired from road authorities of state of Victoria, Australia, to test the model and recommends steps in the computation of MDP based stochastic optimization model, leading to the development of optimum pavement maintenance policy.

  20. Edgar Schein's Process versus Content Consultation Models.

    Science.gov (United States)

    Rockwood, Gary F.

    1993-01-01

    Describes Schein's three models of consultation based on assumptions inherent in different helping styles: purchase of expertise and doctor-patient models, which focus on content of organization problems; and process consultation model, which focuses on how organizational problems are solved. Notes that Schein has suggested that consultants begin…

  1. The Methodical Bases of Assessment of Innovation Processes in the Sphere of Power Generation with Use of Opportunities of Cognitive Modeling

    Directory of Open Access Journals (Sweden)

    Vikhlyaeva Nataliya V.

    2017-10-01

    Full Text Available The article presents the methodical bases of assessing the innovation processes of power generating companies with use of opportunities of cognitive modeling. It is specified that the method of cognitive modeling allows to remove contradictions concerning the interrelationship of the factors determining the innovation processes of the energy generating companies that usually arise when the results of research on the elements of the innovation system are being coordinated. Based on the arguments and practical examples, provided in the article, it was concluded that application of the method of cognitive modeling in the process of assessing the innovative capabilities of energy-generating companies is a sufficiently flexible and effective tool for supporting decision-making on strategic directions of their development.

  2. Decision Making under Uncertainty: A Neural Model based on Partially Observable Markov Decision Processes

    Directory of Open Access Journals (Sweden)

    Rajesh P N Rao

    2010-11-01

    Full Text Available A fundamental problem faced by animals is learning to select actions based on noisy sensory information and incomplete knowledge of the world. It has been suggested that the brain engages in Bayesian inference during perception but how such probabilistic representations are used to select actions has remained unclear. Here we propose a neural model of action selection and decision making based on the theory of partially observable Markov decision processes (POMDPs. Actions are selected based not on a single optimal estimate of state but on the posterior distribution over states (the belief state. We show how such a model provides a unified framework for explaining experimental results in decision making that involve both information gathering and overt actions. The model utilizes temporal difference (TD learning for maximizing expected reward. The resulting neural architecture posits an active role for the neocortex in belief computation while ascribing a role to the basal ganglia in belief representation, value computation, and action selection. When applied to the random dots motion discrimination task, model neurons representing belief exhibit responses similar to those of LIP neurons in primate neocortex. The appropriate threshold for switching from information gathering to overt actions emerges naturally during reward maximization. Additionally, the time course of reward prediction error in the model shares similarities with dopaminergic responses in the basal ganglia during the random dots task. For tasks with a deadline, the model learns a decision making strategy that changes with elapsed time, predicting a collapsing decision threshold consistent with some experimental studies. The model provides a new framework for understanding neural decision making and suggests an important role for interactions between the neocortex and the basal ganglia in learning the mapping between probabilistic sensory representations and actions that maximize

  3. Energy and environment efficiency analysis based on an improved environment DEA cross-model: Case study of complex chemical processes

    International Nuclear Information System (INIS)

    Geng, ZhiQiang; Dong, JunGen; Han, YongMing; Zhu, QunXiong

    2017-01-01

    Highlights: •An improved environment DEA cross-model method is proposed. •Energy and environment efficiency analysis framework of complex chemical processes is obtained. •This proposed method is efficient in energy-saving and emission reduction of complex chemical processes. -- Abstract: The complex chemical process is a high pollution and high energy consumption industrial process. Therefore, it is very important to analyze and evaluate the energy and environment efficiency of the complex chemical process. Data Envelopment Analysis (DEA) is used to evaluate the relative effectiveness of decision-making units (DMUs). However, the traditional DEA method usually cannot genuinely distinguish the effective and inefficient DMU due to its extreme or unreasonable weight distribution of input and output variables. Therefore, this paper proposes an energy and environment efficiency analysis method based on an improved environment DEA cross-model (DEACM) method. The inputs of the complex chemical process are divided into energy and non-energy inputs. Meanwhile, the outputs are divided into desirable and undesirable outputs. And then the energy and environment performance index (EEPI) based on the cross evaluation is used to represent the overall performance of each DMU. Moreover, the improvement direction of energy-saving and carbon emission reduction of each inefficiency DMU is quantitatively obtained based on the self-evaluation model of the improved environment DEACM. The results show that the improved environment DEACM method has a better effective discrimination than the original DEA method by analyzing the energy and environment efficiency of the ethylene production process in complex chemical processes, and it can obtain the potential of energy-saving and carbon emission reduction of ethylene plants, especially the improvement direction of inefficient DMUs to improve energy efficiency and reduce carbon emission.

  4. Mashup Model and Verification Using Mashup Processing Network

    Science.gov (United States)

    Zahoor, Ehtesham; Perrin, Olivier; Godart, Claude

    Mashups are defined to be lightweight Web applications aggregating data from different Web services, built using ad-hoc composition and being not concerned with long term stability and robustness. In this paper we present a pattern based approach, called Mashup Processing Network (MPN). The idea is based on Event Processing Network and is supposed to facilitate the creation, modeling and the verification of mashups. MPN provides a view of how different actors interact for the mashup development namely the producer, consumer, mashup processing agent and the communication channels. It also supports modeling transformations and validations of data and offers validation of both functional and non-functional requirements, such as reliable messaging and security, that are key issues within the enterprise context. We have enriched the model with a set of processing operations and categorize them into data composition, transformation and validation categories. These processing operations can be seen as a set of patterns for facilitating the mashup development process. MPN also paves a way for realizing Mashup Oriented Architecture where mashups along with services are used as building blocks for application development.

  5. Property Modelling for Applications in Chemical Product and Process Design

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    such as database, property model library, model parameter regression, and, property-model based product-process design will be presented. The database contains pure component and mixture data for a wide range of organic chemicals. The property models are based on the combined group contribution and atom...... is missing, the atom connectivity based model is employed to predict the missing group interaction. In this way, a wide application range of the property modeling tool is ensured. Based on the property models, targeted computer-aided techniques have been developed for design and analysis of organic chemicals......, polymers, mixtures as well as separation processes. The presentation will highlight the framework (ICAS software) for property modeling, the property models and issues such as prediction accuracy, flexibility, maintenance and updating of the database. Also, application issues related to the use of property...

  6. Facilitating Change to a Problem-based Model

    DEFF Research Database (Denmark)

    Kolmos, Anette

    2002-01-01

    The paper presents the barriers which arise during the change process from a traditional educational system to a problem-based educational model.......The paper presents the barriers which arise during the change process from a traditional educational system to a problem-based educational model....

  7. Two Undergraduate Process Modeling Courses Taught Using Inductive Learning Methods

    Science.gov (United States)

    Soroush, Masoud; Weinberger, Charles B.

    2010-01-01

    This manuscript presents a successful application of inductive learning in process modeling. It describes two process modeling courses that use inductive learning methods such as inquiry learning and problem-based learning, among others. The courses include a novel collection of multi-disciplinary complementary process modeling examples. They were…

  8. Estimating Diurnal Courses of Gross Primary Production for Maize: A Comparison of Sun-Induced Chlorophyll Fluorescence, Light-Use Efficiency and Process-Based Models

    Directory of Open Access Journals (Sweden)

    Tianxiang Cui

    2017-12-01

    Full Text Available Accurately quantifying gross primary production (GPP is of vital importance to understanding the global carbon cycle. Light-use efficiency (LUE models and process-based models have been widely used to estimate GPP at different spatial and temporal scales. However, large uncertainties remain in quantifying GPP, especially for croplands. Recently, remote measurements of solar-induced chlorophyll fluorescence (SIF have provided a new perspective to assess actual levels of plant photosynthesis. In the presented study, we evaluated the performance of three approaches, including the LUE-based multi-source data synergized quantitative (MuSyQ GPP algorithm, the process-based boreal ecosystem productivity simulator (BEPS model, and the SIF-based statistical model, in estimating the diurnal courses of GPP at a maize site in Zhangye, China. A field campaign was conducted to acquire synchronous far-red SIF (SIF760 observations and flux tower-based GPP measurements. Our results showed that both SIF760 and GPP were linearly correlated with APAR, and the SIF760-GPP relationship was adequately characterized using a linear function. The evaluation of the modeled GPP against the GPP measured from the tower demonstrated that all three approaches provided reasonable estimates, with R2 values of 0.702, 0.867, and 0.667 and RMSE values of 0.247, 0.153, and 0.236 mg m−2 s−1 for the MuSyQ-GPP, BEPS and SIF models, respectively. This study indicated that the BEPS model simulated the GPP best due to its efficiency in describing the underlying physiological processes of sunlit and shaded leaves. The MuSyQ-GPP model was limited by its simplification of some critical ecological processes and its weakness in characterizing the contribution of shaded leaves. The SIF760-based model demonstrated a relatively limited accuracy but showed its potential in modeling GPP without dependency on climate inputs in short-term studies.

  9. Simulation Models of Human Decision-Making Processes

    Directory of Open Access Journals (Sweden)

    Nina RIZUN

    2014-10-01

    Full Text Available The main purpose of the paper is presentation of the new concept of human decision-making process modeling via using the analogy with Automatic Control Theory. From the author's point of view this concept allows to develop and improve the theory of decision-making in terms of the study and classification of specificity of the human intellectual processes in different conditions. It was proved that the main distinguishing feature between the Heuristic / Intuitive and Rational Decision-Making Models is the presence of so-called phenomenon of "enrichment" of the input information with human propensity, hobbies, tendencies, expectations, axioms and judgments, presumptions or bias and their justification. In order to obtain additional knowledge about the basic intellectual processes as well as the possibility of modeling the decision results in various parameters characterizing the decision-maker, the complex of the simulation models was developed. These models are based on the assumptions that:  basic intellectual processes of the Rational Decision-Making Model can be adequately simulated and identified by the transient processes of the proportional-integral-derivative controller; basic intellectual processes of the Bounded Rationality and Intuitive Models can be adequately simulated and identified by the transient processes of the nonlinear elements.The taxonomy of the most typical automatic control theory elements and their compliance with certain decision-making models with a point of view of decision-making process specificity and decision-maker behavior during a certain time of professional activity was obtained.

  10. The Use of Modeling-Based Text to Improve Students' Modeling Competencies

    Science.gov (United States)

    Jong, Jing-Ping; Chiu, Mei-Hung; Chung, Shiao-Lan

    2015-01-01

    This study investigated the effects of a modeling-based text on 10th graders' modeling competencies. Fifteen 10th graders read a researcher-developed modeling-based science text on the ideal gas law that included explicit descriptions and representations of modeling processes (i.e., model selection, model construction, model validation, model…

  11. Modeling analysis of pulsed magnetization process of magnetic core based on inverse Jiles-Atherton model

    Science.gov (United States)

    Liu, Yi; Zhang, He; Liu, Siwei; Lin, Fuchang

    2018-05-01

    The J-A (Jiles-Atherton) model is widely used to describe the magnetization characteristics of magnetic cores in a low-frequency alternating field. However, this model is deficient in the quantitative analysis of the eddy current loss and residual loss in a high-frequency magnetic field. Based on the decomposition of magnetization intensity, an inverse J-A model is established which uses magnetic flux density B as an input variable. Static and dynamic core losses under high frequency excitation are separated based on the inverse J-A model. Optimized parameters of the inverse J-A model are obtained based on particle swarm optimization. The platform for the pulsed magnetization characteristic test is designed and constructed. The hysteresis curves of ferrite and Fe-based nanocrystalline cores at high magnetization rates are measured. The simulated and measured hysteresis curves are presented and compared. It is found that the inverse J-A model can be used to describe the magnetization characteristics at high magnetization rates and to separate the static loss and dynamic loss accurately.

  12. Rapid core field variations during the satellite era: Investigations using stochastic process based field models

    DEFF Research Database (Denmark)

    Finlay, Chris; Olsen, Nils; Gillet, Nicolas

    We present a new ensemble of time-dependent magnetic field models constructed from satellite and observatory data spanning 1997-2013 that are compatible with prior information concerning the temporal spectrum of core field variations. These models allow sharper field changes compared to tradition...... physical hypotheses can be tested by asking questions of the entire ensemble of core field models, rather than by interpreting any single model.......We present a new ensemble of time-dependent magnetic field models constructed from satellite and observatory data spanning 1997-2013 that are compatible with prior information concerning the temporal spectrum of core field variations. These models allow sharper field changes compared to traditional...... regularization methods based on minimizing the square of second or third time derivative. We invert satellite and observatory data directly by adopting the external field and crustal field modelling framework of the CHAOS model, but apply the stochastic process method of Gillet et al. (2013) to the core field...

  13. Models and Modelling Tools for Chemical Product and Process Design

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    2016-01-01

    The design, development and reliability of a chemical product and the process to manufacture it, need to be consistent with the end-use characteristics of the desired product. One of the common ways to match the desired product-process characteristics is through trial and error based experiments......-based framework is that in the design, development and/or manufacturing of a chemical product-process, the knowledge of the applied phenomena together with the product-process design details can be provided with diverse degrees of abstractions and details. This would allow the experimental resources...... to be employed for validation and fine-tuning of the solutions from the model-based framework, thereby, removing the need for trial and error experimental steps. Also, questions related to economic feasibility, operability and sustainability, among others, can be considered in the early stages of design. However...

  14. Ontological Model of Business Process Management Systems

    Science.gov (United States)

    Manoilov, G.; Deliiska, B.

    2008-10-01

    The activities which constitute business process management (BPM) can be grouped into five categories: design, modeling, execution, monitoring and optimization. Dedicated software packets for business process management system (BPMS) are available on the market. But the efficiency of its exploitation depends on used ontological model in the development time and run time of the system. In the article an ontological model of BPMS in area of software industry is investigated. The model building is preceded by conceptualization of the domain and taxonomy of BPMS development. On the base of the taxonomy an simple online thesaurus is created.

  15. [The dual process model of addiction. Towards an integrated model?].

    Science.gov (United States)

    Vandermeeren, R; Hebbrecht, M

    2012-01-01

    Neurobiology and cognitive psychology have provided us with a dual process model of addiction. According to this model, behavior is considered to be the dynamic result of a combination of automatic and controlling processes. In cases of addiction the balance between these two processes is severely disturbed. Automated processes will continue to produce impulses that ensure the continuance of addictive behavior. Weak, reflective or controlling processes are both the reason for and the result of the inability to forgo addiction. To identify features that are common to current neurocognitive insights into addiction and psychodynamic views on addiction. The picture that emerges from research is not clear. There is some evidence that attentional bias has a causal effect on addiction. There is no evidence that automatic associations have a causal effect, but there is some evidence that automatic action-tendencies do have a causal effect. Current neurocognitive views on the dual process model of addiction can be integrated with an evidence-based approach to addiction and with psychodynamic views on addiction.

  16. An automated process for building reliable and optimal in vitro/in vivo correlation models based on Monte Carlo simulations.

    Science.gov (United States)

    Sutton, Steven C; Hu, Mingxiu

    2006-05-05

    Many mathematical models have been proposed for establishing an in vitro/in vivo correlation (IVIVC). The traditional IVIVC model building process consists of 5 steps: deconvolution, model fitting, convolution, prediction error evaluation, and cross-validation. This is a time-consuming process and typically a few models at most are tested for any given data set. The objectives of this work were to (1) propose a statistical tool to screen models for further development of an IVIVC, (2) evaluate the performance of each model under different circumstances, and (3) investigate the effectiveness of common statistical model selection criteria for choosing IVIVC models. A computer program was developed to explore which model(s) would be most likely to work well with a random variation from the original formulation. The process used Monte Carlo simulation techniques to build IVIVC models. Data-based model selection criteria (Akaike Information Criteria [AIC], R2) and the probability of passing the Food and Drug Administration "prediction error" requirement was calculated. To illustrate this approach, several real data sets representing a broad range of release profiles are used to illustrate the process and to demonstrate the advantages of this automated process over the traditional approach. The Hixson-Crowell and Weibull models were often preferred over the linear. When evaluating whether a Level A IVIVC model was possible, the model selection criteria AIC generally selected the best model. We believe that the approach we proposed may be a rapid tool to determine which IVIVC model (if any) is the most applicable.

  17. A Queuing Model of the Airport Departure Process

    OpenAIRE

    Balakrishnan, Hamsa; Simaiakis, Ioannis

    2013-01-01

    This paper presents an analytical model of the aircraft departure process at an airport. The modeling procedure includes the estimation of unimpeded taxi-out time distributions and the development of a queuing model of the departure runway system based on the transient analysis of D/E/1 queuing systems. The parameters of the runway service process are estimated using operational data. Using the aircraft pushback schedule as input, the model predicts the expected runway schedule and takeoff ti...

  18. A condition-based maintenance of a dependent degradation-threshold-shock model in a system with multiple degradation processes

    International Nuclear Information System (INIS)

    Caballé, N.C.; Castro, I.T.; Pérez, C.J.; Lanza-Gutiérrez, J.M.

    2015-01-01

    This paper proposes a condition-based maintenance strategy for a system subject to two dependent causes of failure: degradation and sudden shocks. The internal degradation is reflected by the presence of multiple degradation processes in the system. Degradation processes start at random times following a Non-homogeneous Poisson process and their growths are modelled by using a gamma process. When the deterioration level of a degradation process exceeds a predetermined value, we assume that a degradation failure occurs. Furthermore, the system is subject to sudden shocks that arrive at the system following a Doubly Stochastic Poisson Process. A sudden shock provokes the total breakdown of the system. Thus, the state of the system is evaluated at inspection times and different maintenance tasks can be carried out. If the system is still working at an inspection time, a preventive maintenance task is performed if the deterioration level of a degradation process exceeds a certain threshold. A corrective maintenance task is performed if the system is down at an inspection time. A preventive (corrective) maintenance task implies the replacement of the system by a new one. Under this maintenance strategy, the expected cost rate function is obtained. A numerical example illustrates the analytical results. - Highlights: • A condition-based maintenance model is proposed. • Two dependent causes of failure are considered: deterioration and external shocks. • Deterioration is given by multiple degradation processes growing by a gamma process. • The initiation of degradation processes follows a Non-homogeneous Poisson process. • External shocks arrive at the system by using a Doubly Stochastic Poisson Process

  19. A Data-Driven Air Transportation Delay Propagation Model Using Epidemic Process Models

    Directory of Open Access Journals (Sweden)

    B. Baspinar

    2016-01-01

    Full Text Available In air transport network management, in addition to defining the performance behavior of the system’s components, identification of their interaction dynamics is a delicate issue in both strategic and tactical decision-making process so as to decide which elements of the system are “controlled” and how. This paper introduces a novel delay propagation model utilizing epidemic spreading process, which enables the definition of novel performance indicators and interaction rates of the elements of the air transportation network. In order to understand the behavior of the delay propagation over the network at different levels, we have constructed two different data-driven epidemic models approximating the dynamics of the system: (a flight-based epidemic model and (b airport-based epidemic model. The flight-based epidemic model utilizing SIS epidemic model focuses on the individual flights where each flight can be in susceptible or infected states. The airport-centric epidemic model, in addition to the flight-to-flight interactions, allows us to define the collective behavior of the airports, which are modeled as metapopulations. In network model construction, we have utilized historical flight-track data of Europe and performed analysis for certain days involving certain disturbances. Through this effort, we have validated the proposed delay propagation models under disruptive events.

  20. Processes of behavior change and weight loss in a theory-based weight loss intervention program: a test of the process model for lifestyle behavior change.

    Science.gov (United States)

    Gillison, Fiona; Stathi, Afroditi; Reddy, Prasuna; Perry, Rachel; Taylor, Gordon; Bennett, Paul; Dunbar, James; Greaves, Colin

    2015-01-16

    Process evaluation is important for improving theories of behavior change and behavioral intervention methods. The present study reports on the process outcomes of a pilot test of the theoretical model (the Process Model for Lifestyle Behavior Change; PMLBC) underpinning an evidence-informed, theory-driven, group-based intervention designed to promote healthy eating and physical activity for people with high cardiovascular risk. 108 people at high risk of diabetes or heart disease were randomized to a group-based weight management intervention targeting diet and physical activity plus usual care, or to usual care. The intervention comprised nine group based sessions designed to promote motivation, social support, self-regulation and understanding of the behavior change process. Weight loss, diet, physical activity and theoretically defined mediators of change were measured pre-intervention, and after four and 12 months. The intervention resulted in significant improvements in fiber intake (M between-group difference = 5.7 g/day, p behavior change, and the predicted mechanisms of change specified in the PMBLC were largely supported. Improvements in self-efficacy and understanding of the behavior change process were associated with engagement in coping planning and self-monitoring activities, and successful dietary change at four and 12 months. While participants reported improvements in motivational and social support variables, there was no effect of these, or of the intervention overall, on physical activity. The data broadly support the theoretical model for supporting some dietary changes, but not for physical activity. Systematic intervention design allowed us to identify where improvements to the intervention may be implemented to promote change in all proposed mediators. More work is needed to explore effective mechanisms within interventions to promote physical activity behavior.

  1. Application of agent-based system for bioprocess description and process improvement.

    Science.gov (United States)

    Gao, Ying; Kipling, Katie; Glassey, Jarka; Willis, Mark; Montague, Gary; Zhou, Yuhong; Titchener-Hooker, Nigel J

    2010-01-01

    Modeling plays an important role in bioprocess development for design and scale-up. Predictive models can also be used in biopharmaceutical manufacturing to assist decision-making either to maintain process consistency or to identify optimal operating conditions. To predict the whole bioprocess performance, the strong interactions present in a processing sequence must be adequately modeled. Traditionally, bioprocess modeling considers process units separately, which makes it difficult to capture the interactions between units. In this work, a systematic framework is developed to analyze the bioprocesses based on a whole process understanding and considering the interactions between process operations. An agent-based approach is adopted to provide a flexible infrastructure for the necessary integration of process models. This enables the prediction of overall process behavior, which can then be applied during process development or once manufacturing has commenced, in both cases leading to the capacity for fast evaluation of process improvement options. The multi-agent system comprises a process knowledge base, process models, and a group of functional agents. In this system, agent components co-operate with each other in performing their tasks. These include the description of the whole process behavior, evaluating process operating conditions, monitoring of the operating processes, predicting critical process performance, and providing guidance to decision-making when coping with process deviations. During process development, the system can be used to evaluate the design space for process operation. During manufacture, the system can be applied to identify abnormal process operation events and then to provide suggestions as to how best to cope with the deviations. In all cases, the function of the system is to ensure an efficient manufacturing process. The implementation of the agent-based approach is illustrated via selected application scenarios, which

  2. Implementation of a Web-Based Organ Donation Educational Intervention: Development and Use of a Refined Process Evaluation Model

    Science.gov (United States)

    Harker, Laura; Bamps, Yvan; Flemming, Shauna St. Clair; Perryman, Jennie P; Thompson, Nancy J; Patzer, Rachel E; Williams, Nancy S DeSousa; Arriola, Kimberly R Jacob

    2017-01-01

    Background The lack of available organs is often considered to be the single greatest problem in transplantation today. Internet use is at an all-time high, creating an opportunity to increase public commitment to organ donation through the broad reach of Web-based behavioral interventions. Implementing Internet interventions, however, presents challenges including preventing fraudulent respondents and ensuring intervention uptake. Although Web-based organ donation interventions have increased in recent years, process evaluation models appropriate for Web-based interventions are lacking. Objective The aim of this study was to describe a refined process evaluation model adapted for Web-based settings and used to assess the implementation of a Web-based intervention aimed to increase organ donation among African Americans. Methods We used a randomized pretest-posttest control design to assess the effectiveness of the intervention website that addressed barriers to organ donation through corresponding videos. Eligible participants were African American adult residents of Georgia who were not registered on the state donor registry. Drawing from previously developed process evaluation constructs, we adapted reach (the extent to which individuals were found eligible, and participated in the study), recruitment (online recruitment mechanism), dose received (intervention uptake), and context (how the Web-based setting influenced study implementation) for Internet settings and used the adapted model to assess the implementation of our Web-based intervention. Results With regard to reach, 1415 individuals completed the eligibility screener; 948 (67.00%) were determined eligible, of whom 918 (96.8%) completed the study. After eliminating duplicate entries (n=17), those who did not initiate the posttest (n=21) and those with an invalid ZIP code (n=108), 772 valid entries remained. Per the Internet protocol (IP) address analysis, only 23 of the 772 valid entries (3.0%) were

  3. CONSTRUCCIÓN DE MODELOS SEMIFÍSICOS DE BASE FENOMENOLÓGICA: CASO PROCESO DE FERMENTACIÓN BUILDING PHENOMENOLOGICAL BASED SEMI-PHYSICAL MODELS: FERMENTATION PROCESS CASE

    Directory of Open Access Journals (Sweden)

    CÉSAR AUGUSTO GÓMEZ

    2008-12-01

    Full Text Available Este trabajo presenta un método para la construcción de Modelos Semifisicos de Base Fenomenológica (MSBF. El método se basa en los fenómenos de transporte, tránsito, transmisión o transferencia, y en el principio de conservación. Se da una descripción detallada de los pasos del método propuesto. Luego se aplica el método en la construcción de un modelo que describe el comportamiento de cinco dinámicas (volumen, biomasa, sustrato, producto y temperatura en un proceso de fermentación en continuo. La simulación muestra que el modelo obtenido puede predecir de forma adecuada el comportamiento dinámico de dicho bioproceso.This work presents a method for building Phenomenological Based Semiphysical Models (PBSM. The method is based on transport, transfer, transmission or transit phenomena and conservation principle. A detailed description of proposed method steps is given. Next, the method is applied to attaining a model for describing the behavior of five dynamics (volume, biomass, substrate, product and temperature of a continuous fermentation process. Model simulation shows that obtained model can predict dynamic performance of real process adequately.

  4. Standard Model processes

    CERN Document Server

    Mangano, M.L.; Aguilar-Saavedra, Juan Antonio; Alekhin, S.; Badger, S.; Bauer, C.W.; Becher, T.; Bertone, V.; Bonvini, M.; Boselli, S.; Bothmann, E.; Boughezal, R.; Cacciari, M.; Carloni Calame, C.M.; Caola, F.; Campbell, J.M.; Carrazza, S.; Chiesa, M.; Cieri, L.; Cimaglia, F.; Febres Cordero, F.; Ferrarese, P.; D'Enterria, D.; Ferrera, G.; Garcia i Tormo, X.; Garzelli, M.V.; Germann, E.; Hirschi, V.; Han, T.; Ita, H.; Jäger, B.; Kallweit, S.; Karlberg, A.; Kuttimalai, S.; Krauss, F.; Larkoski, A.J.; Lindert, J.; Luisoni, G.; Maierhöfer, P.; Mattelaer, O.; Martinez, H.; Moch, S.; Montagna, G.; Moretti, M.; Nason, P.; Nicrosini, O.; Oleari, C.; Pagani, D.; Papaefstathiou, A.; Petriello, F.; Piccinini, F.; Pierini, M.; Pierog, T.; Pozzorini, S.; Re, E.; Robens, T.; Rojo, J.; Ruiz, R.; Sakurai, K.; Salam, G.P.; Salfelder, L.; Schönherr, M.; Schulze, M.; Schumann, S.; Selvaggi, M.; Shivaji, A.; Siodmok, A.; Skands, P.; Torrielli, P.; Tramontano, F.; Tsinikos, I.; Tweedie, B.; Vicini, A.; Westhoff, S.; Zaro, M.; Zeppenfeld, D.; CERN. Geneva. ATS Department

    2017-06-22

    This report summarises the properties of Standard Model processes at the 100 TeV pp collider. We document the production rates and typical distributions for a number of benchmark Standard Model processes, and discuss new dynamical phenomena arising at the highest energies available at this collider. We discuss the intrinsic physics interest in the measurement of these Standard Model processes, as well as their role as backgrounds for New Physics searches.

  5. A task based design procedure and modelling approached for industrial crystallization processes

    NARCIS (Netherlands)

    Menon, A.R.

    2006-01-01

    A synthesis-based approach to the design of crystallizers and industrial crystallization processes is introduced in this thesis. An ontology for a task-based design procedure has been developed which breaks the crystallization process into a subset of basic functions (physical tasks) which transform

  6. Modelling and control of dynamic systems using gaussian process models

    CERN Document Server

    Kocijan, Juš

    2016-01-01

    This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior know...

  7. Modelling of transport and biogeochemical processes in pollution plumes: Literature review of model development

    DEFF Research Database (Denmark)

    Brun, A.; Engesgaard, Peter Knudegaard

    2002-01-01

    A literature survey shows how biogeochemical (coupled organic and inorganic reaction processes) transport models are based on considering the complete biodegradation process as either a single- or as a two-step process. It is demonstrated that some two-step process models rely on the Partial...... Equilibrium Approach (PEA). The PEA assumes the organic degradation step, and not the electron acceptor consumption step, is rate limiting. This distinction is not possible in one-step process models, where consumption of both the electron donor and acceptor are treated kinetically. A three-dimensional, two......-step PEA model is developed. The model allows for Monod kinetics and biomass growth, features usually included only in one-step process models. The biogeochemical part of the model is tested for a batch system with degradation of organic matter under the consumption of a sequence of electron acceptors...

  8. Visualizing the process of process modeling with PPMCharts

    NARCIS (Netherlands)

    Claes, J.; Vanderfeesten, I.T.P.; Pinggera, J.; Reijers, H.A.; Weber, B.; Poels, G.; La Rosa, M.; Soffer, P.

    2013-01-01

    In the quest for knowledge about how to make good process models, recent research focus is shifting from studying the quality of process models to studying the process of process modeling (often abbreviated as PPM) itself. This paper reports on our efforts to visualize this specific process in such

  9. Process modeling and control applied to real-time monitoring of distillation processes by near-infrared spectroscopy.

    Science.gov (United States)

    de Oliveira, Rodrigo R; Pedroza, Ricardo H P; Sousa, A O; Lima, Kássio M G; de Juan, Anna

    2017-09-08

    A distillation device that acquires continuous and synchronized measurements of temperature, percentage of distilled fraction and NIR spectra has been designed for real-time monitoring of distillation processes. As a process model, synthetic commercial gasoline batches produced in Brazil, which contain mixtures of pure gasoline blended with ethanol have been analyzed. The information provided by this device, i.e., distillation curves and NIR spectra, has served as initial information for the proposal of new strategies of process modeling and multivariate statistical process control (MSPC). Process modeling based on PCA batch analysis provided global distillation trajectories, whereas multiset MCR-ALS analysis is proposed to obtain a component-wise characterization of the distillation evolution and distilled fractions. Distillation curves, NIR spectra or compressed NIR information under the form of PCA scores and MCR-ALS concentration profiles were tested as the seed information to build MSPC models. New on-line PCA-based MSPC approaches, some inspired on local rank exploratory methods for process analysis, are proposed and work as follows: a) MSPC based on individual process observation models, where multiple local PCA models are built considering the sole information in each observation point; b) Fixed Size Moving Window - MSPC, in which local PCA models are built considering a moving window of the current and few past observation points; and c) Evolving MSPC, where local PCA models are built with an increasing window of observations covering all points since the beginning of the process until the current observation. Performance of different approaches has been assessed in terms of sensitivity to fault detection and number of false alarms. The outcome of this work will be of general use to define strategies for on-line process monitoring and control and, in a more specific way, to improve quality control of petroleum derived fuels and other substances submitted

  10. Theoretical modelling of carbon deposition processes

    International Nuclear Information System (INIS)

    Marsh, G.R.; Norfolk, D.J.; Skinner, R.F.

    1985-01-01

    Work based on capsule experiments in the BNL Gamma Facility, aimed at elucidating the chemistry involved in the formation of carbonaceous deposit on CAGR fuel pin surfaces is described. Using a data-base derived from capsule experiments together with literature values for the kinetics of the fundamental reactions, a chemical model of the gas-phase processes has been developed. This model successfully reproduces the capsule results, whilst preliminary application to the WAGR coolant circuit indicates the likely concentration profiles of various radical species within the fuel channels. (author)

  11. Process-based modeling of species' responses to climate change - a proof of concept using western North American trees

    Science.gov (United States)

    Evans, M. E.; Merow, C.; Record, S.; Menlove, J.; Gray, A.; Cundiff, J.; McMahon, S.; Enquist, B. J.

    2013-12-01

    Current attempts to forecast how species' distributions will change in response to climate change suffer under a fundamental trade-off: between modeling many species superficially vs. few species in detail (between correlative vs. mechanistic models). The goals of this talk are two-fold: first, we present a Bayesian multilevel modeling framework, dynamic range modeling (DRM), for building process-based forecasts of many species' distributions at a time, designed to address the trade-off between detail and number of distribution forecasts. In contrast to 'species distribution modeling' or 'niche modeling', which uses only species' occurrence data and environmental data, DRMs draw upon demographic data, abundance data, trait data, occurrence data, and GIS layers of climate in a single framework to account for two processes known to influence range dynamics - demography and dispersal. The vision is to use extensive databases on plant demography, distributions, and traits - in the Botanical Information and Ecology Network, the Forest Inventory and Analysis database (FIA), and the International Tree Ring Data Bank - to develop DRMs for North American trees. Second, we present preliminary results from building the core submodel of a DRM - an integral projection model (IPM) - for a sample of dominant tree species in western North America. IPMs are used to infer demographic niches - i.e., the set of environmental conditions under which population growth rate is positive - and project population dynamics through time. Based on >550,000 data points derived from FIA for nine tree species in western North America, we show IPM-based models of their current and future distributions, and discuss how IPMs can be used to forecast future forest productivity, mortality patterns, and inform efforts at assisted migration.

  12. The research on construction and application of machining process knowledge base

    Science.gov (United States)

    Zhao, Tan; Qiao, Lihong; Qie, Yifan; Guo, Kai

    2018-03-01

    In order to realize the application of knowledge in machining process design, from the perspective of knowledge in the application of computer aided process planning(CAPP), a hierarchical structure of knowledge classification is established according to the characteristics of mechanical engineering field. The expression of machining process knowledge is structured by means of production rules and the object-oriented methods. Three kinds of knowledge base models are constructed according to the representation of machining process knowledge. In this paper, the definition and classification of machining process knowledge, knowledge model, and the application flow of the process design based on the knowledge base are given, and the main steps of the design decision of the machine tool are carried out as an application by using the knowledge base.

  13. Analytical and regression models of glass rod drawing process

    Science.gov (United States)

    Alekseeva, L. B.

    2018-03-01

    The process of drawing glass rods (light guides) is being studied. The parameters of the process affecting the quality of the light guide have been determined. To solve the problem, mathematical models based on general equations of continuum mechanics are used. The conditions for the stable flow of the drawing process have been found, which are determined by the stability of the motion of the glass mass in the formation zone to small uncontrolled perturbations. The sensitivity of the formation zone to perturbations of the drawing speed and viscosity is estimated. Experimental models of the drawing process, based on the regression analysis methods, have been obtained. These models make it possible to customize a specific production process to obtain light guides of the required quality. They allow one to find the optimum combination of process parameters in the chosen area and to determine the required accuracy of maintaining them at a specified level.

  14. Data-driven process decomposition and robust online distributed modelling for large-scale processes

    Science.gov (United States)

    Shu, Zhang; Lijuan, Li; Lijuan, Yao; Shipin, Yang; Tao, Zou

    2018-02-01

    With the increasing attention of networked control, system decomposition and distributed models show significant importance in the implementation of model-based control strategy. In this paper, a data-driven system decomposition and online distributed subsystem modelling algorithm was proposed for large-scale chemical processes. The key controlled variables are first partitioned by affinity propagation clustering algorithm into several clusters. Each cluster can be regarded as a subsystem. Then the inputs of each subsystem are selected by offline canonical correlation analysis between all process variables and its controlled variables. Process decomposition is then realised after the screening of input and output variables. When the system decomposition is finished, the online subsystem modelling can be carried out by recursively block-wise renewing the samples. The proposed algorithm was applied in the Tennessee Eastman process and the validity was verified.

  15. Testing process predictions of models of risky choice: a quantitative model comparison approach

    Science.gov (United States)

    Pachur, Thorsten; Hertwig, Ralph; Gigerenzer, Gerd; Brandstätter, Eduard

    2013-01-01

    This article presents a quantitative model comparison contrasting the process predictions of two prominent views on risky choice. One view assumes a trade-off between probabilities and outcomes (or non-linear functions thereof) and the separate evaluation of risky options (expectation models). Another view assumes that risky choice is based on comparative evaluation, limited search, aspiration levels, and the forgoing of trade-offs (heuristic models). We derived quantitative process predictions for a generic expectation model and for a specific heuristic model, namely the priority heuristic (Brandstätter et al., 2006), and tested them in two experiments. The focus was on two key features of the cognitive process: acquisition frequencies (i.e., how frequently individual reasons are looked up) and direction of search (i.e., gamble-wise vs. reason-wise). In Experiment 1, the priority heuristic predicted direction of search better than the expectation model (although neither model predicted the acquisition process perfectly); acquisition frequencies, however, were inconsistent with both models. Additional analyses revealed that these frequencies were primarily a function of what Rubinstein (1988) called “similarity.” In Experiment 2, the quantitative model comparison approach showed that people seemed to rely more on the priority heuristic in difficult problems, but to make more trade-offs in easy problems. This finding suggests that risky choice may be based on a mental toolbox of strategies. PMID:24151472

  16. Testing Process Predictions of Models of Risky Choice: A Quantitative Model Comparison Approach

    Directory of Open Access Journals (Sweden)

    Thorsten ePachur

    2013-09-01

    Full Text Available This article presents a quantitative model comparison contrasting the process predictions of two prominent views on risky choice. One view assumes a trade-off between probabilities and outcomes (or nonlinear functions thereof and the separate evaluation of risky options (expectation models. Another view assumes that risky choice is based on comparative evaluation, limited search, aspiration levels, and the forgoing of trade-offs (heuristic models. We derived quantitative process predictions for a generic expectation model and for a specific heuristic model, namely the priority heuristic (Brandstätter, Gigerenzer, & Hertwig, 2006, and tested them in two experiments. The focus was on two key features of the cognitive process: acquisition frequencies (i.e., how frequently individual reasons are looked up and direction of search (i.e., gamble-wise vs. reason-wise. In Experiment 1, the priority heuristic predicted direction of search better than the expectation model (although neither model predicted the acquisition process perfectly; acquisition frequencies, however, were inconsistent with both models. Additional analyses revealed that these frequencies were primarily a function of what Rubinstein (1988 called similarity. In Experiment 2, the quantitative model comparison approach showed that people seemed to rely more on the priority heuristic in difficult problems, but to make more trade-offs in easy problems. This finding suggests that risky choice may be based on a mental toolbox of strategies.

  17. Real-time interferometric monitoring and measuring of photopolymerization based stereolithographic additive manufacturing process: sensor model and algorithm

    International Nuclear Information System (INIS)

    Zhao, X; Rosen, D W

    2017-01-01

    As additive manufacturing is poised for growth and innovations, it faces barriers of lack of in-process metrology and control to advance into wider industry applications. The exposure controlled projection lithography (ECPL) is a layerless mask-projection stereolithographic additive manufacturing process, in which parts are fabricated from photopolymers on a stationary transparent substrate. To improve the process accuracy with closed-loop control for ECPL, this paper develops an interferometric curing monitoring and measuring (ICM and M) method which addresses the sensor modeling and algorithms issues. A physical sensor model for ICM and M is derived based on interference optics utilizing the concept of instantaneous frequency. The associated calibration procedure is outlined for ICM and M measurement accuracy. To solve the sensor model, particularly in real time, an online evolutionary parameter estimation algorithm is developed adopting moving horizon exponentially weighted Fourier curve fitting and numerical integration. As a preliminary validation, simulated real-time measurement by offline analysis of a video of interferograms acquired in the ECPL process is presented. The agreement between the cured height estimated by ICM and M and that measured by microscope indicates that the measurement principle is promising as real-time metrology for global measurement and control of the ECPL process. (paper)

  18. A new model for anaerobic processes of up-flow anaerobic sludge blanket reactors based on cellular automata

    DEFF Research Database (Denmark)

    Skiadas, Ioannis V.; Ahring, Birgitte Kiær

    2002-01-01

    characteristics and lead to different reactor behaviour. A dynamic mathematical model has been developed for the anaerobic digestion of a glucose based synthetic wastewater in UASB reactors. Cellular automata (CA) theory has been applied to simulate the granule development process. The model takes...... into consideration that granule diameter and granule microbial composition are functions of the reactor operational parameters and is capable of predicting the UASB performance and the layer structure of the granules....

  19. Improving Science Process Skills for Primary School Students Through 5E Instructional Model-Based Learning

    Science.gov (United States)

    Choirunnisa, N. L.; Prabowo, P.; Suryanti, S.

    2018-01-01

    The main objective of this study is to describe the effectiveness of 5E instructional model-based learning to improve primary school students’ science process skills. The science process skills is important for students as it is the foundation for enhancing the mastery of concepts and thinking skills needed in the 21st century. The design of this study was experimental involving one group pre-test and post-test design. The result of this study shows that (1) the implementation of learning in both of classes, IVA and IVB, show that the percentage of learning implementation increased which indicates a better quality of learning and (2) the percentage of students’ science process skills test results on the aspects of observing, formulating hypotheses, determining variable, interpreting data and communicating increased as well.

  20. Symmetries and modelling functions for diffusion processes

    International Nuclear Information System (INIS)

    Nikitin, A G; Spichak, S V; Vedula, Yu S; Naumovets, A G

    2009-01-01

    A constructive approach to the theory of diffusion processes is proposed, which is based on application of both symmetry analysis and the method of modelling functions. An algorithm for construction of the modelling functions is suggested. This algorithm is based on the error function expansion (ERFEX) of experimental concentration profiles. The high-accuracy analytical description of the profiles provided by ERFEX approximation allows a convenient extraction of the concentration dependence of diffusivity from experimental data and prediction of the diffusion process. Our analysis is exemplified by its employment in experimental results obtained for surface diffusion of lithium on the molybdenum (1 1 2) surface precovered with dysprosium. The ERFEX approximation can be directly extended to many other diffusion systems.

  1. Process Cost Modeling for Multi-Disciplinary Design Optimization

    Science.gov (United States)

    Bao, Han P.; Freeman, William (Technical Monitor)

    2002-01-01

    For early design concepts, the conventional approach to cost is normally some kind of parametric weight-based cost model. There is now ample evidence that this approach can be misleading and inaccurate. By the nature of its development, a parametric cost model requires historical data and is valid only if the new design is analogous to those for which the model was derived. Advanced aerospace vehicles have no historical production data and are nowhere near the vehicles of the past. Using an existing weight-based cost model would only lead to errors and distortions of the true production cost. This report outlines the development of a process-based cost model in which the physical elements of the vehicle are costed according to a first-order dynamics model. This theoretical cost model, first advocated by early work at MIT, has been expanded to cover the basic structures of an advanced aerospace vehicle. Elemental costs based on the geometry of the design can be summed up to provide an overall estimation of the total production cost for a design configuration. This capability to directly link any design configuration to realistic cost estimation is a key requirement for high payoff MDO problems. Another important consideration in this report is the handling of part or product complexity. Here the concept of cost modulus is introduced to take into account variability due to different materials, sizes, shapes, precision of fabrication, and equipment requirements. The most important implication of the development of the proposed process-based cost model is that different design configurations can now be quickly related to their cost estimates in a seamless calculation process easily implemented on any spreadsheet tool. In successive sections, the report addresses the issues of cost modeling as follows. First, an introduction is presented to provide the background for the research work. Next, a quick review of cost estimation techniques is made with the intention to

  2. Lattice Gas Model Based Optimization of Plasma-Surface Processes for GaN-Based Compound Growth

    Science.gov (United States)

    Nonokawa, Kiyohide; Suzuki, Takuma; Kitamori, Kazutaka; Sawada, Takayuki

    2001-10-01

    Progress of the epitaxial growth technique for GaN-based compounds makes these materials attractive for applications in high temperature/high-power electronic devices as well as in short-wavelength optoelectronic devices. For MBE growth of GaN epilayer, atomic nitrogen is usually supplied from ECR-plasma while atomic Ga is supplied from conventional K-cell. To grow high-quality epilayer, fundamental knowledge of the detailed atomic process, such as adsorption, surface migration, incorporation, desorption and so forth, is required. We have studied the influence of growth conditions on the flatness of the growth front surface and the growth rate using Monte Carlo simulation based on the lattice gas model. Under the fixed Ga flux condition, the lower the nitrogen flux and/or the higher the growth temperature, the better the flatness of the front surface at the sacrifice of the growth rate of the epilayer. When the nitrogen flux is increased, the growth rate reaches saturation value determined from the Ga flux. At a fixed growth temperature, increasing of nitrogen to Ga flux ratio results in rough surface owing to 3-dimensional island formation. Other characteristics of MBE-GaN growth using ECR-plasma can be well reproduced.

  3. Retort process modelling for Indian traditional foods.

    Science.gov (United States)

    Gokhale, S V; Lele, S S

    2014-11-01

    Indian traditional staple and snack food is typically a heterogeneous recipe that incorporates varieties of vegetables, lentils and other ingredients. Modelling the retorting process of multilayer pouch packed Indian food was achieved using lumped-parameter approach. A unified model is proposed to estimate cold point temperature. Initial process conditions, retort temperature and % solid content were the significantly affecting independent variables. A model was developed using combination of vegetable solids and water, which was then validated using four traditional Indian vegetarian products: Pulav (steamed rice with vegetables), Sambar (south Indian style curry containing mixed vegetables and lentils), Gajar Halawa (carrot based sweet product) and Upama (wheat based snack product). The predicted and experimental values of temperature profile matched with ±10 % error which is a good match considering the food was a multi component system. Thus the model will be useful as a tool to reduce number of trials required to optimize retorting of various Indian traditional vegetarian foods.

  4. Model of diffusers / permeators for hydrogen processing

    International Nuclear Information System (INIS)

    Jacobs, W. D.; Hang, T.

    2008-01-01

    Palladium-silver (Pd-Ag) diffusers are mainstays of hydrogen processing. Diffusers separate hydrogen from inert species such as nitrogen, argon or helium. The tubing becomes permeable to hydrogen when heated to more than 250 C and a differential pressure is created across the membrane. The hydrogen diffuses better at higher temperatures. Experimental or experiential results have been the basis for determining or predicting a diffuser's performance. However, the process can be mathematically modeled, and comparison to experimental or other operating data can be utilized to improve the fit of the model. A reliable model-based diffuser system design is the goal which will have impacts on tritium and hydrogen processing. A computer model has been developed to solve the differential equations for diffusion given the operating boundary conditions. The model was compared to operating data for a low pressure diffuser system. The modeling approach and the results are presented in this paper. (authors)

  5. Analysis of Using Resources in Business Process Modeling and Simulation

    Directory of Open Access Journals (Sweden)

    Vasilecas Olegas

    2014-12-01

    Full Text Available One of the key purposes of Business Process Model and Notation (BPMN is to support graphical representation of the process model. However, such models have a lack of support for the graphical representation of resources, whose processes are used during simulation or execution of process instance. The paper analyzes different methods and their extensions for resource modeling. Further, this article presents a selected set of resource properties that are relevant for resource modeling. The paper proposes an approach that explains how to use the selected set of resource properties for extension of process modeling using BPMN and simulation tools. They are based on BPMN, where business process instances use resources in a concurrency manner.

  6. Web-Based Modelling and Collaborative Simulation of Declarative Processes

    DEFF Research Database (Denmark)

    Slaats, Tijs; Marquard, Morten; Shahzad, Muhammad

    2015-01-01

    -user discussions on how knowledge workers really work, by enabling collaborative simulation of processes. In earlier work we reported on the integration of DCR Graphs as a workflow execution formalism in the existing Exformatics ECM products. In this paper we report on the advances we have made over the last two......As a provider of Electronic Case Management solutions to knowledge-intensive businesses and organizations, the Danish company Exformatics has in recent years identified a need for flexible process support in the tools that we provide to our customers. We have addressed this need by adapting DCR...... Graphs, a formal declarative workflow notation developed at the IT University of Copenhagen. Through close collaboration with academia we first integrated execution support for the notation into our existing tools, by leveraging a cloud-based process engine implementing the DCR formalism. Over the last...

  7. Development and evaluation of spatial point process models for epidermal nerve fibers.

    Science.gov (United States)

    Olsbo, Viktor; Myllymäki, Mari; Waller, Lance A; Särkkä, Aila

    2013-06-01

    We propose two spatial point process models for the spatial structure of epidermal nerve fibers (ENFs) across human skin. The models derive from two point processes, Φb and Φe, describing the locations of the base and end points of the fibers. Each point of Φe (the end point process) is connected to a unique point in Φb (the base point process). In the first model, both Φe and Φb are Poisson processes, yielding a null model of uniform coverage of the skin by end points and general baseline results and reference values for moments of key physiologic indicators. The second model provides a mechanistic model to generate end points for each base, and we model the branching structure more directly by defining Φe as a cluster process conditioned on the realization of Φb as its parent points. In both cases, we derive distributional properties for observable quantities of direct interest to neurologists such as the number of fibers per base, and the direction and range of fibers on the skin. We contrast both models by fitting them to data from skin blister biopsy images of ENFs and provide inference regarding physiological properties of ENFs. Copyright © 2013 Elsevier Inc. All rights reserved.

  8. Stochastic modeling for neural spiking events based on fractional superstatistical Poisson process

    Science.gov (United States)

    Konno, Hidetoshi; Tamura, Yoshiyasu

    2018-01-01

    In neural spike counting experiments, it is known that there are two main features: (i) the counting number has a fractional power-law growth with time and (ii) the waiting time (i.e., the inter-spike-interval) distribution has a heavy tail. The method of superstatistical Poisson processes (SSPPs) is examined whether these main features are properly modeled. Although various mixed/compound Poisson processes are generated with selecting a suitable distribution of the birth-rate of spiking neurons, only the second feature (ii) can be modeled by the method of SSPPs. Namely, the first one (i) associated with the effect of long-memory cannot be modeled properly. Then, it is shown that the two main features can be modeled successfully by a class of fractional SSPP (FSSPP).

  9. Modelling Of Flotation Processes By Classical Mathematical Methods - A Review

    Science.gov (United States)

    Jovanović, Ivana; Miljanović, Igor

    2015-12-01

    Flotation process modelling is not a simple task, mostly because of the process complexity, i.e. the presence of a large number of variables that (to a lesser or a greater extent) affect the final outcome of the mineral particles separation based on the differences in their surface properties. The attempts toward the development of the quantitative predictive model that would fully describe the operation of an industrial flotation plant started in the middle of past century and it lasts to this day. This paper gives a review of published research activities directed toward the development of flotation models based on the classical mathematical rules. The description and systematization of classical flotation models were performed according to the available references, with emphasize exclusively given to the flotation process modelling, regardless of the model application in a certain control system. In accordance with the contemporary considerations, models were classified as the empirical, probabilistic, kinetic and population balance types. Each model type is presented through the aspects of flotation modelling at the macro and micro process levels.

  10. Plant operator performance evaluation based on cognitive process analysis experiment

    International Nuclear Information System (INIS)

    Ujita, H.; Fukuda, M.

    1990-01-01

    This paper reports on an experiment to clarify plant operators' cognitive processes that has been performed, to improve the man-machine interface which supports their diagnoses and decisions. The cognitive processes under abnormal conditions were evaluated by protocol analyses interviews, etc. in the experiment using a plant training simulator. A cognitive process model is represented by a stochastic network, based on Rasmussen's decision making model. Each node of the network corresponds to an element of the cognitive process, such as observation, interpretation, execution, etc. Some observations were obtained as follows, by comparison of Monte Carlo simulation results with the experiment results: A process to reconfirm the plant parameters after execution of a task and feedback paths from this process to the observation and the task definition of next task were observed. The feedback probability average and standard deviation should be determined for each incident type to explain correctly the individual differences in the cognitive processes. The tendency for the operator's cognitive level to change from skill-based to knowledge-based via rule-based behavior was observed during the feedback process

  11. Software Engineering Laboratory (SEL) cleanroom process model

    Science.gov (United States)

    Green, Scott; Basili, Victor; Godfrey, Sally; Mcgarry, Frank; Pajerski, Rose; Waligora, Sharon

    1991-01-01

    The Software Engineering Laboratory (SEL) cleanroom process model is described. The term 'cleanroom' originates in the integrated circuit (IC) production process, where IC's are assembled in dust free 'clean rooms' to prevent the destructive effects of dust. When applying the clean room methodology to the development of software systems, the primary focus is on software defect prevention rather than defect removal. The model is based on data and analysis from previous cleanroom efforts within the SEL and is tailored to serve as a guideline in applying the methodology to future production software efforts. The phases that are part of the process model life cycle from the delivery of requirements to the start of acceptance testing are described. For each defined phase, a set of specific activities is discussed, and the appropriate data flow is described. Pertinent managerial issues, key similarities and differences between the SEL's cleanroom process model and the standard development approach used on SEL projects, and significant lessons learned from prior cleanroom projects are presented. It is intended that the process model described here will be further tailored as additional SEL cleanroom projects are analyzed.

  12. Implementation of a Goal-Based Systems Engineering Process Using the Systems Modeling Language (SysML)

    Science.gov (United States)

    Breckenridge, Jonathan T.; Johnson, Stephen B.

    2013-01-01

    Building upon the purpose, theoretical approach, and use of a Goal-Function Tree (GFT) being presented by Dr. Stephen B. Johnson, described in a related Infotech 2013 ISHM abstract titled "Goal-Function Tree Modeling for Systems Engineering and Fault Management", this paper will describe the core framework used to implement the GFTbased systems engineering process using the Systems Modeling Language (SysML). These two papers are ideally accepted and presented together in the same Infotech session. Statement of problem: SysML, as a tool, is currently not capable of implementing the theoretical approach described within the "Goal-Function Tree Modeling for Systems Engineering and Fault Management" paper cited above. More generally, SysML's current capabilities to model functional decompositions in the rigorous manner required in the GFT approach are limited. The GFT is a new Model-Based Systems Engineering (MBSE) approach to the development of goals and requirements, functions, and its linkage to design. As a growing standard for systems engineering, it is important to develop methods to implement GFT in SysML. Proposed Method of Solution: Many of the central concepts of the SysML language are needed to implement a GFT for large complex systems. In the implementation of those central concepts, the following will be described in detail: changes to the nominal SysML process, model view definitions and examples, diagram definitions and examples, and detailed SysML construct and stereotype definitions.

  13. Investigations on Temperature Fields during Laser Beam Melting by Means of Process Monitoring and Multiscale Process Modelling

    Directory of Open Access Journals (Sweden)

    J. Schilp

    2014-07-01

    Full Text Available Process monitoring and modelling can contribute to fostering the industrial relevance of additive manufacturing. Process related temperature gradients and thermal inhomogeneities cause residual stresses, and distortions and influence the microstructure. Variations in wall thickness can cause heat accumulations. These occur predominantly in filigree part areas and can be detected by utilizing off-axis thermographic monitoring during the manufacturing process. In addition, numerical simulation models on the scale of whole parts can enable an analysis of temperature fields upstream to the build process. In a microscale domain, modelling of several exposed single hatches allows temperature investigations at a high spatial and temporal resolution. Within this paper, FEM-based micro- and macroscale modelling approaches as well as an experimental setup for thermographic monitoring are introduced. By discussing and comparing experimental data with simulation results in terms of temperature distributions both the potential of numerical approaches and the complexity of determining suitable computation time efficient process models are demonstrated. This paper contributes to the vision of adjusting the transient temperature field during manufacturing in order to improve the resulting part's quality by simulation based process design upstream to the build process and the inline process monitoring.

  14. Mechanistic Fermentation Models for Process Design, Monitoring, and Control

    DEFF Research Database (Denmark)

    Mears, Lisa; Stocks, Stuart M.; Albæk, Mads Orla

    2017-01-01

    Mechanistic models require a significant investment of time and resources, but their application to multiple stages of fermentation process development and operation can make this investment highly valuable. This Opinion article discusses how an established fermentation model may be adapted...... for application to different stages of fermentation process development: planning, process design, monitoring, and control. Although a longer development time is required for such modeling methods in comparison to purely data-based model techniques, the wide range of applications makes them a highly valuable tool...... for fermentation research and development. In addition, in a research environment, where collaboration is important, developing mechanistic models provides a platform for knowledge sharing and consolidation of existing process understanding....

  15. Model-Based Integration and Interpretation of Data

    DEFF Research Database (Denmark)

    Petersen, Johannes

    2004-01-01

    Data integration and interpretation plays a crucial role in supervisory control. The paper defines a set of generic inference steps for the data integration and interpretation process based on a three-layer model of system representations. The three-layer model is used to clarify the combination...... of constraint and object-centered representations of the work domain throwing new light on the basic principles underlying the data integration and interpretation process of Rasmussen's abstraction hierarchy as well as other model-based approaches combining constraint and object-centered representations. Based...

  16. Nitrogen gas emissions and nitrate leaching dynamics under different tillage practices based on data synthesis and process-based modeling

    Science.gov (United States)

    Huang, Y.; Ren, W.; Tao, B.; Zhu, X.

    2017-12-01

    Nitrogen losses from the agroecosystems have been of great concern to global changes due to the effects on global warming and water pollution in the form of nitrogen gas emissions (e.g., N2O) and mineral nitrogen leaching (e.g., NO3-), respectively. Conservation tillage, particularly no-tillage (NT), may enhance soil carbon sequestration, soil aggregation and moisture; therefore it has the potential of promoting N2O emissions and reducing NO3- leaching, comparing with conventional tillage (CT). However, associated processes are significantly affected by various factors, such as soil properties, climate, and crop types. How tillage management practices affect nitrogen transformations and fluxes is still far from clear, with inconsistent even opposite results from previous studies. To fill this knowledge gap, we quantitatively investigated gaseous and leaching nitrogen losses from NT and CT agroecosystems based on data synthesis and an improved process-based agroecosystem model. Our preliminary results suggest that NT management is more efficient in reducing NO3- leaching, and meanwhile it simultaneously increases N2O emissions by approximately 10% compared with CT. The effects of NT on N2O emissions and NO3- leaching are highly influenced by the placement of nitrogen fertilizer and are more pronounced in humid climate conditions. The effect of crop types is a less dominant factor in determining N2O and NO3- losses. Both our data synthesis and process-based modeling suggest that the enhanced carbon sequestration capacity from NT could be largely compromised by relevant NT-induced increases in N2O emissions. This study provides the comprehensive quantitative assessment of NT on the nitrogen emissions and leaching in agroecosystems. It provides scientific information for identifying proper management practices for ensuring food security and minimizing the adverse environmental impacts. The results also underscore the importance of suitable nitrogen management in the NT

  17. Guideline validation in multiple trauma care through business process modeling.

    Science.gov (United States)

    Stausberg, Jürgen; Bilir, Hüseyin; Waydhas, Christian; Ruchholtz, Steffen

    2003-07-01

    Clinical guidelines can improve the quality of care in multiple trauma. In our Department of Trauma Surgery a specific guideline is available paper-based as a set of flowcharts. This format is appropriate for the use by experienced physicians but insufficient for electronic support of learning, workflow and process optimization. A formal and logically consistent version represented with a standardized meta-model is necessary for automatic processing. In our project we transferred the paper-based into an electronic format and analyzed the structure with respect to formal errors. Several errors were detected in seven error categories. The errors were corrected to reach a formally and logically consistent process model. In a second step the clinical content of the guideline was revised interactively using a process-modeling tool. Our study reveals that guideline development should be assisted by process modeling tools, which check the content in comparison to a meta-model. The meta-model itself could support the domain experts in formulating their knowledge systematically. To assure sustainability of guideline development a representation independent of specific applications or specific provider is necessary. Then, clinical guidelines could be used for eLearning, process optimization and workflow management additionally.

  18. Stochastic modeling for neural spiking events based on fractional superstatistical Poisson process

    Directory of Open Access Journals (Sweden)

    Hidetoshi Konno

    2018-01-01

    Full Text Available In neural spike counting experiments, it is known that there are two main features: (i the counting number has a fractional power-law growth with time and (ii the waiting time (i.e., the inter-spike-interval distribution has a heavy tail. The method of superstatistical Poisson processes (SSPPs is examined whether these main features are properly modeled. Although various mixed/compound Poisson processes are generated with selecting a suitable distribution of the birth-rate of spiking neurons, only the second feature (ii can be modeled by the method of SSPPs. Namely, the first one (i associated with the effect of long-memory cannot be modeled properly. Then, it is shown that the two main features can be modeled successfully by a class of fractional SSPP (FSSPP.

  19. Fuzzy Pruning Based LS-SVM Modeling Development for a Fermentation Process

    Directory of Open Access Journals (Sweden)

    Weili Xiong

    2014-01-01

    Full Text Available Due to the complexity and uncertainty of microbial fermentation processes, data coming from the plants often contain some outliers. However, these data may be treated as the normal support vectors, which always deteriorate the performance of soft sensor modeling. Since the outliers also contaminate the correlation structure of the least square support vector machine (LS-SVM, the fuzzy pruning method is provided to deal with the problem. Furthermore, by assigning different fuzzy membership scores to data samples, the sensitivity of the model to the outliers can be reduced greatly. The effectiveness and efficiency of the proposed approach are demonstrated through two numerical examples as well as a simulator case of penicillin fermentation process.

  20. Business process model repositories : efficient process retrieval

    NARCIS (Netherlands)

    Yan, Z.

    2012-01-01

    As organizations increasingly work in process-oriented manner, the number of business process models that they develop and have to maintain increases. As a consequence, it has become common for organizations to have collections of hundreds or even thousands of business process models. When a

  1. Activity-based DEVS modeling

    DEFF Research Database (Denmark)

    Alshareef, Abdurrahman; Sarjoughian, Hessam S.; Zarrin, Bahram

    2018-01-01

    architecture and the UML concepts. In this paper, we further this work by grounding Activity-based DEVS modeling and developing a fully-fledged modeling engine to demonstrate applicability. We also detail the relevant aspects of the created metamodel in terms of modeling and simulation. A significant number......Use of model-driven approaches has been increasing to significantly benefit the process of building complex systems. Recently, an approach for specifying model behavior using UML activities has been devised to support the creation of DEVS models in a disciplined manner based on the model driven...... of the artifacts of the UML 2.5 activities and actions, from the vantage point of DEVS behavioral modeling, is covered in details. Their semantics are discussed to the extent of time-accurate requirements for simulation. We characterize them in correspondence with the specification of the atomic model behavior. We...

  2. A Unified Toolset for Business Process Model Formalization

    NARCIS (Netherlands)

    B. Changizi (Behnaz); N. Kokash (Natallia); F. Arbab (Farhad)

    2010-01-01

    htmlabstractIn this paper, we present a toolset to automate the transformation of Business Process Modeling Notation (BPMN), UML Sequence Diagrams, and Business Process Execution Language (BPEL), into their proposed formal semantics expressed in the channel-based coordination language Reo. Such

  3. Motivation and performance within a collaborative computer-based modeling task: Relations between students' achievement goal orientation, self-efficacy, cognitive processing and achievement

    OpenAIRE

    Sins, P.H.M.; van Joolingen, W.R.; Savelsbergh, E.R.; van Hout-Wolters, B.H.A.M.

    2008-01-01

    Purpose of the present study was to test a conceptual model of relations among achievement goal orientation, self-efficacy, cognitive processing, and achievement of students working within a particular collaborative task context. The task involved a collaborative computer-based modeling task. In order to test the model, group measures of mastery-approach goal orientation, performance-avoidance goal orientation, self-efficacy, and achievement were employed. Students’ cognitive processing was a...

  4. Modeling Aspects of Activated Sludge Processes Part l l: Mathematical Process Modeling and Biokinetics of Activated Sludge Processes

    Energy Technology Data Exchange (ETDEWEB)

    AbdElHaleem, H S [Cairo Univ.-CivlI Eng. Dept., Giza (Egypt); EI-Ahwany, A H [CairoUlmrsity- Faculty ofEngincering - Chemical Engineering Department, Giza (Egypt); Ibrahim, H I [Helwan University- Faculty of Engineering - Biomedical Engineering Department, Helwan (Egypt); Ibrahim, G [Menofia University- Faculty of Engineering Sbebin EI Kom- Basic Eng. Sc. Dept., Menofia (Egypt)

    2004-07-01

    Mathematical process modeling and biokinetics of activated sludge process were reviewed considering different types of models. It has been evaluated the task group models of ASMI. and 2, and 3 versioned by Henze et al considering the conditions of each model and the different processes of which every model consists. It is revealed that ASMI contains some defects avoided in ASM3. Relied on homogeneity, Models can be classified into homogenous models characterized by taking the activated sludge process as one phase. In this type of models, the internal mass transfer inside the floes was neglected.. Hence, the kinetic parameter produces can be considered inaccurate. The other type of models is the heterogeneous model This type considers the mass transfer operations in addition to the biochemical reaction processes; hence, the resulted kinetic parameters can be considered more accurate than that of homogenous type.

  5. Modeling Aspects of Activated Sludge Processes Part l l: Mathematical Process Modeling and Biokinetics of Activated Sludge Processes

    International Nuclear Information System (INIS)

    AbdElHaleem, H.S.; EI-Ahwany, A. H.; Ibrahim, H.I.; Ibrahim, G.

    2004-01-01

    Mathematical process modeling and biokinetics of activated sludge process were reviewed considering different types of models. It has been evaluated the task group models of ASMI. and 2, and 3 versioned by Henze et al considering the conditions of each model and the different processes of which every model consists. It is revealed that ASMI contains some defects avoided in ASM3. Relied on homogeneity, Models can be classified into homogenous models characterized by taking the activated sludge process as one phase. In this type of models, the internal mass transfer inside the floes was neglected.. Hence, the kinetic parameter produces can be considered inaccurate. The other type of models is the heterogeneous model This type considers the mass transfer operations in addition to the biochemical reaction processes; hence, the resulted kinetic parameters can be considered more accurate than that of homogenous type

  6. Applying 3-PG, a simple process-based model designed to produce practical results, to data from loblolly pine experiments

    Science.gov (United States)

    Joe J. Landsberg; Kurt H. Johnsen; Timothy J. Albaugh; H. Lee Allen; Steven E. McKeand

    2001-01-01

    3-PG is a simple process-based model that requires few parameter values and only readily available input data. We tested the structure of the model by calibrating it against loblolly pine data from the control treatment of the SETRES experiment in Scotland County, NC, then altered the fertility rating to simulate the effects of fertilization. There was excellent...

  7. A CSP-Based Agent Modeling Framework for the Cougaar Agent-Based Architecture

    Science.gov (United States)

    Gracanin, Denis; Singh, H. Lally; Eltoweissy, Mohamed; Hinchey, Michael G.; Bohner, Shawn A.

    2005-01-01

    Cognitive Agent Architecture (Cougaar) is a Java-based architecture for large-scale distributed agent-based applications. A Cougaar agent is an autonomous software entity with behaviors that represent a real-world entity (e.g., a business process). A Cougaar-based Model Driven Architecture approach, currently under development, uses a description of system's functionality (requirements) to automatically implement the system in Cougaar. The Communicating Sequential Processes (CSP) formalism is used for the formal validation of the generated system. Two main agent components, a blackboard and a plugin, are modeled as CSP processes. A set of channels represents communications between the blackboard and individual plugins. The blackboard is represented as a CSP process that communicates with every agent in the collection. The developed CSP-based Cougaar modeling framework provides a starting point for a more complete formal verification of the automatically generated Cougaar code. Currently it is used to verify the behavior of an individual agent in terms of CSP properties and to analyze the corresponding Cougaar society.

  8. Modelling on optimal portfolio with exchange rate based on discontinuous stochastic process

    Science.gov (United States)

    Yan, Wei; Chang, Yuwen

    2016-12-01

    Considering the stochastic exchange rate, this paper is concerned with the dynamic portfolio selection in financial market. The optimal investment problem is formulated as a continuous-time mathematical model under mean-variance criterion. These processes follow jump-diffusion processes (Weiner process and Poisson process). Then the corresponding Hamilton-Jacobi-Bellman(HJB) equation of the problem is presented and its efferent frontier is obtained. Moreover, the optimal strategy is also derived under safety-first criterion.

  9. The impact of working memory and the "process of process modelling" on model quality: Investigating experienced versus inexperienced modellers

    DEFF Research Database (Denmark)

    Martini, Markus; Pinggera, Jakob; Neurauter, Manuel

    2016-01-01

    of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling....... the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension...

  10. Rapid response tools and datasets for post-fire modeling: Linking Earth Observations and process-based hydrological models to support post-fire remediation

    Science.gov (United States)

    M. E. Miller; M. Billmire; W. J. Elliot; K. A. Endsley; P. R. Robichaud

    2015-01-01

    Preparation is key to utilizing Earth Observations and process-based models to support post-wildfire mitigation. Post-fire flooding and erosion can pose a serious threat to life, property and municipal water supplies. Increased runoff and sediment delivery due to the loss of surface cover and fire-induced changes in soil properties are of great concern. Remediation...

  11. Product and Process Modelling

    DEFF Research Database (Denmark)

    Cameron, Ian T.; Gani, Rafiqul

    . These approaches are put into the context of life cycle modelling, where multiscale and multiform modelling is increasingly prevalent in the 21st century. The book commences with a discussion of modern product and process modelling theory and practice followed by a series of case studies drawn from a variety......This book covers the area of product and process modelling via a case study approach. It addresses a wide range of modelling applications with emphasis on modelling methodology and the subsequent in-depth analysis of mathematical models to gain insight via structural aspects of the models...... to biotechnology applications, food, polymer and human health application areas. The book highlights to important nature of modern product and process modelling in the decision making processes across the life cycle. As such it provides an important resource for students, researchers and industrial practitioners....

  12. Computer-Aided Modeling of Lipid Processing Technology

    DEFF Research Database (Denmark)

    Diaz Tovar, Carlos Axel

    2011-01-01

    increase along with growing interest in biofuels, the oleochemical industry faces in the upcoming years major challenges in terms of design and development of better products and more sustainable processes to make them. Computer-aided methods and tools for process synthesis, modeling and simulation...... are widely used for design, analysis, and optimization of processes in the chemical and petrochemical industries. These computer-aided tools have helped the chemical industry to evolve beyond commodities toward specialty chemicals and ‘consumer oriented chemicals based products’. Unfortunately...... to develop systematic computer-aided methods (property models) and tools (database) related to the prediction of the necessary physical properties suitable for design and analysis of processes employing lipid technologies. The methods and tools include: the development of a lipid-database (CAPEC...

  13. Modeling of Multicomponent Mixture Separation Processes Using Hollow fiber Membrane

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sin-Ah; Kim, Jin-Kuk; Lee, Young Moo; Yeo, Yeong-Koo [Hanyang University, Seoul (Korea, Republic of)

    2015-02-15

    So far, most of research activities on modeling of membrane separation processes have been focused on binary feed mixture. But, in actual separation operations, binary feed is hard to find and most separation processes involve multicomponent feed mixture. In this work models for membrane separation processes treating multicomponent feed mixture are developed. Various model types are investigated and validity of proposed models are analysed based on experimental data obtained using hollowfiber membranes. The proposed separation models show quick convergence and exhibit good tracking performance.

  14. Model parameters conditioning on regional hydrologic signatures for process-based design flood estimation in ungauged basins.

    Science.gov (United States)

    Biondi, Daniela; De Luca, Davide Luciano

    2015-04-01

    The use of rainfall-runoff models represents an alternative to statistical approaches (such as at-site or regional flood frequency analysis) for design flood estimation, and constitutes an answer to the increasing need for synthetic design hydrographs (SDHs) associated to a specific return period. However, the lack of streamflow observations and the consequent high uncertainty associated with parameter estimation, usually pose serious limitations to the use of process-based approaches in ungauged catchments, which in contrast represent the majority in practical applications. This work presents the application of a Bayesian procedure that, for a predefined rainfall-runoff model, allows for the assessment of posterior parameters distribution, using the limited and uncertain information available for the response of an ungauged catchment (Bulygina et al. 2009; 2011). The use of regional estimates of river flow statistics, interpreted as hydrological signatures that measure theoretically relevant system process behaviours (Gupta et al. 2008), within this framework represents a valuable option and has shown significant developments in recent literature to constrain the plausible model response and to reduce the uncertainty in ungauged basins. In this study we rely on the first three L-moments of annual streamflow maxima, for which regressions are available from previous studies (Biondi et al. 2012; Laio et al. 2011). The methodology was carried out for a catchment located in southern Italy, and used within a Monte Carlo scheme (MCs) considering both event-based and continuous simulation approaches for design flood estimation. The applied procedure offers promising perspectives to perform model calibration and uncertainty analysis in ungauged basins; moreover, in the context of design flood estimation, process-based methods coupled with MCs approach have the advantage of providing simulated floods uncertainty analysis that represents an asset in risk-based decision

  15. A simplified computational memory model from information processing.

    Science.gov (United States)

    Zhang, Lanhua; Zhang, Dongsheng; Deng, Yuqin; Ding, Xiaoqian; Wang, Yan; Tang, Yiyuan; Sun, Baoliang

    2016-11-23

    This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracting memory function and simulating memory information processing. At first meta-memory is defined to express the neuron or brain cortices based on the biology and graph theories, and we develop an intra-modular network with the modeling algorithm by mapping the node and edge, and then the bi-modular network is delineated with intra-modular and inter-modular. At last a polynomial retrieval algorithm is introduced. In this paper we simulate the memory phenomena and functions of memorization and strengthening by information processing algorithms. The theoretical analysis and the simulation results show that the model is in accordance with the memory phenomena from information processing view.

  16. Cognitive components underpinning the development of model-based learning.

    Science.gov (United States)

    Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

    2017-06-01

    Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  17. A Model-driven and Service-oriented framework for the business process improvement

    Directory of Open Access Journals (Sweden)

    Andrea Delgado

    2010-07-01

    Full Text Available Business Process Management (BPM importance and benefits for organizations to focus on their business processes is nowadays broadly recognized, as business and technology areas are embracing and adopting the paradigm. The Service Oriented Computing (SOC paradigm bases software development on services to realize business processes. The implementation of business processes as services helps in reducing the gap between these two areas, easing the communication and understanding of business needs. The Model Driven Development (MDD paradigm bases software development in models, metamodels and languages that allow transformation between them. The automatic generation of service models from business process models is a key issue to support the separation of its definition from its technical implementation. In this article, we present MINERVA framework which applies Model Driven Development (MDD and Service Oriented Computing (SOC paradigms to business processes for the continuous business process improvement in organizations, giving support to the stages defined in the business process lifecycle from modeling to evaluation of its execution.

  18. Crowdsourcing Based 3d Modeling

    Science.gov (United States)

    Somogyi, A.; Barsi, A.; Molnar, B.; Lovas, T.

    2016-06-01

    Web-based photo albums that support organizing and viewing the users' images are widely used. These services provide a convenient solution for storing, editing and sharing images. In many cases, the users attach geotags to the images in order to enable using them e.g. in location based applications on social networks. Our paper discusses a procedure that collects open access images from a site frequently visited by tourists. Geotagged pictures showing the image of a sight or tourist attraction are selected and processed in photogrammetric processing software that produces the 3D model of the captured object. For the particular investigation we selected three attractions in Budapest. To assess the geometrical accuracy, we used laser scanner and DSLR as well as smart phone photography to derive reference values to enable verifying the spatial model obtained from the web-album images. The investigation shows how detailed and accurate models could be derived applying photogrammetric processing software, simply by using images of the community, without visiting the site.

  19. Near Field Environment Process Model Report

    Energy Technology Data Exchange (ETDEWEB)

    R.A. Wagner

    2000-11-14

    Waste emplacement and activities associated with construction of a repository system potentially will change environmental conditions within the repository system. These environmental changes principally result from heat generated by the decay of the radioactive waste, which elevates temperatures within the repository system. Elevated temperatures affect distribution of water, increase kinetic rates of geochemical processes, and cause stresses to change in magnitude and orientation from the stresses resulting from the overlying rock and from underground construction activities. The recognition of this evolving environment has been reflected in activities, studies and discussions generally associated with what has been termed the Near-Field Environment (NFE). The NFE interacts directly with waste packages and engineered barriers as well as potentially changing the fluid composition and flow conditions within the mountain. As such, the NFE defines the environment for assessing the performance of a potential Monitored Geologic Repository at Yucca Mountain, Nevada. The NFe evolves over time, and therefore is not amenable to direct characterization or measurement in the ambient system. Analysis or assessment of the NFE must rely upon projections based on tests and models that encompass the long-term processes of the evolution of this environment. This NFE Process Model Report (PMR) describes the analyses and modeling based on current understanding of the evolution of the near-field within the rock mass extending outward from the drift wall.

  20. Modeling, estimation and optimal filtration in signal processing

    CERN Document Server

    Najim, Mohamed

    2010-01-01

    The purpose of this book is to provide graduate students and practitioners with traditional methods and more recent results for model-based approaches in signal processing.Firstly, discrete-time linear models such as AR, MA and ARMA models, their properties and their limitations are introduced. In addition, sinusoidal models are addressed.Secondly, estimation approaches based on least squares methods and instrumental variable techniques are presented.Finally, the book deals with optimal filters, i.e. Wiener and Kalman filtering, and adaptive filters such as the RLS, the LMS and the

  1. Kinetics of pulp mill effluent treatment by ozone-based processes

    International Nuclear Information System (INIS)

    Ko, Chun-Han; Hsieh, Po-Hung; Chang, Meng-Wen; Chern, Jia-Ming; Chiang, Shih-Min; Tzeng, Chewn-Jeng

    2009-01-01

    The wastewaters generated from wood pulping and paper production processes are traditionally treated by biological and physicochemical processes. In order to reduce chemical oxygen demand (COD) and color to meet increasingly strict discharge standards, advanced oxidation processes (AOPs) are being adapted as polishing treatment units. Various ozone-based processes were used in this study to treat simulated wastewaters prepared from black liquor from a hardwood Kraft pulp mill in Taiwan. The experimental results showed that the COD and color were primarily removed by direct ozone oxidation and activated carbon adsorption. While the addition of activated carbon could enhance the COD and color removal during ozonation, the addition of hydrogen peroxide improved the color removal only. For the various ozone-based treatment processes, kinetic models were developed to satisfactorily predict the COD and color removal rates. According to the kinetic parameters obtained from the various ozone-based processes, the enhanced COD and color removal of ozonation in the presence of activated carbon was attributed to the regeneration of the activated carbon by ozonation. These kinetic models can be used for reactor design and process design to treat pulping wastewater using ozone-based processes.

  2. Stimulating Scientific Reasoning with Drawing-Based Modeling

    Science.gov (United States)

    Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

    2018-01-01

    We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each…

  3. Comparative analysis of business rules and business process modeling languages

    Directory of Open Access Journals (Sweden)

    Audrius Rima

    2013-03-01

    Full Text Available During developing an information system is important to create clear models and choose suitable modeling languages. The article analyzes the SRML, SBVR, PRR, SWRL, OCL rules specifying language and UML, DFD, CPN, EPC and IDEF3 BPMN business process modeling language. The article presents business rules and business process modeling languages theoretical comparison. The article according to selected modeling aspects of the comparison between different business process modeling languages ​​and business rules representation languages sets. Also, it is selected the best fit of language set for three layer framework for business rule based software modeling.

  4. Structured spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

    DEFF Research Database (Denmark)

    Møller, Jesper; Diaz-Avalos, Carlos

    Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... dataset consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

  5. Structured Spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

    DEFF Research Database (Denmark)

    Møller, Jesper; Diaz-Avalos, Carlos

    2010-01-01

    Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... data set consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

  6. Modeling of biopharmaceutical processes. Part 2: Process chromatography unit operation

    DEFF Research Database (Denmark)

    Kaltenbrunner, Oliver; McCue, Justin; Engel, Philip

    2008-01-01

    Process modeling can be a useful tool to aid in process development, process optimization, and process scale-up. When modeling a chromatography process, one must first select the appropriate models that describe the mass transfer and adsorption that occurs within the porous adsorbent. The theoret......Process modeling can be a useful tool to aid in process development, process optimization, and process scale-up. When modeling a chromatography process, one must first select the appropriate models that describe the mass transfer and adsorption that occurs within the porous adsorbent...

  7. Modeling Elevation and Aspect Controls on Emerging Ecohydrologic Processes and Ecosystem Patterns Using the Component-based Landlab Framework

    Science.gov (United States)

    Nudurupati, S. S.; Istanbulluoglu, E.; Adams, J. M.; Hobley, D. E. J.; Gasparini, N. M.; Tucker, G. E.; Hutton, E. W. H.

    2014-12-01

    Topography plays a commanding role on the organization of ecohydrologic processes and resulting vegetation patterns. In southwestern United States, climate conditions lead to terrain aspect- and elevation-controlled ecosystems, with mesic north-facing and xeric south-facing vegetation types; and changes in biodiversity as a function of elevation from shrublands in low desert elevations, to mixed grass/shrublands in mid elevations, and forests at high elevations and ridge tops. These observed patterns have been attributed to differences in topography-mediated local soil moisture availability, micro-climatology, and life history processes of plants that control chances of plant establishment and survival. While ecohydrologic models represent local vegetation dynamics in sufficient detail up to sub-hourly time scales, plant life history and competition for space and resources has not been adequately represented in models. In this study we develop an ecohydrologic cellular automata model within the Landlab component-based modeling framework. This model couples local vegetation dynamics (biomass production, death) and plant establishment and competition processes for resources and space. This model is used to study the vegetation organization in a semiarid New Mexico catchment where elevation and hillslope aspect play a defining role on plant types. Processes that lead to observed plant types across the landscape are examined by initializing the domain with randomly assigned plant types and systematically changing model parameters that couple plant response with soil moisture dynamics. Climate perturbation experiments are conducted to examine the plant response in space and time. Understanding the inherently transient ecohydrologic systems is critical to improve predictions of climate change impacts on ecosystems.

  8. Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

    Science.gov (United States)

    Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

    2017-12-01

    Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

  9. Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

    Science.gov (United States)

    Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

    2018-06-01

    Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

  10. The impact of working memory and the "process of process modelling" on model quality: Investigating experienced versus inexperienced modellers.

    Science.gov (United States)

    Martini, Markus; Pinggera, Jakob; Neurauter, Manuel; Sachse, Pierre; Furtner, Marco R; Weber, Barbara

    2016-05-09

    A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling.

  11. An integrated model of statistical process control and maintenance based on the delayed monitoring

    International Nuclear Information System (INIS)

    Yin, Hui; Zhang, Guojun; Zhu, Haiping; Deng, Yuhao; He, Fei

    2015-01-01

    This paper develops an integrated model of statistical process control and maintenance decision. The proposal of delayed monitoring policy postpones the sampling process till a scheduled time and contributes to ten-scenarios of the production process, where equipment failure may occur besides quality shift. The equipment failure and the control chart alert trigger the corrective maintenance and the predictive maintenance, respectively. The occurrence probability, the cycle time and the cycle cost of each scenario are obtained by integral calculation; therefore, a mathematical model is established to minimize the expected cost by using the genetic algorithm. A Monte Carlo simulation experiment is conducted and compared with the integral calculation in order to ensure the analysis of the ten-scenario model. Another ordinary integrated model without delayed monitoring is also established as comparison. The results of a numerical example indicate satisfactory economic performance of the proposed model. Finally, a sensitivity analysis is performed to investigate the effect of model parameters. - Highlights: • We develop an integrated model of statistical process control and maintenance. • We propose delayed monitoring policy and derive an economic model with 10 scenarios. • We consider two deterioration mechanisms, quality shift and equipment failure. • The delayed monitoring policy will help reduce the expected cost

  12. Diagnosing Soil Moisture Anomalies and Neglected Soil Moisture Source/Sink Processes via a Thermal Infrared-based Two-Source Energy Balance Model

    Science.gov (United States)

    Hain, C.; Crow, W. T.; Anderson, M. C.; Yilmaz, M. T.

    2014-12-01

    Atmospheric processes, especially those that occur in the surface and boundary layer, are significantly impacted by soil moisture (SM). Due to the observational gaps in the ground-based monitoring of SM, methodologies have been developed to monitor SM from satellite platforms. While many have focused on microwave methods, observations of thermal infrared land surface temperature (LST) also provides a means of providing SM information. One particular TIR SM method exploits surface flux predictions retrieved from the Atmosphere Land Exchange Inverse (ALEXI) model. ALEXI uses a time-differential measurement of morning LST rise to diagnose the partitioning of net radiation into surface energy fluxes. Here an analysis will be presented to study relationships between three SM products during a multi-year period (2000-2013) from an active/passive microwave dataset (ECV), a TIR-based model (ALEXI), and a land surface model (Noah) over the CONUS. Additionally, all three will be compared against in-situ SM observations from the North American Soil Moisture Database. The second analysis will focus on the use of ALEXI towards diagnosing SM source/sink processes. Traditional soil water balance modeling is based on one-dimensional (vertical-only) water flow, free drainage at the bottom of the soil column, and neglecting ancillary inputs due to processes such as irrigation. However, recent work has highlighted the importance of secondary water source (e.g., irrigation, groundwater extraction, inland wetlands, lateral flows) and sink (e.g., tile drainage in agricultural areas) processes on the partitioning of evaporative and sensible heat fluxes. ALEXI offers a top-down approach for mapping areas where SM source/sink processes have a significant impact on the surface energy balance. Here we present an index, ASSET, that is based on comparisons between ALEXI latent heat flux (LE) estimates and LE predicted by a free-drainage prognostic LSM lacking irrigation, groundwater and tile

  13. Agent Behavior-Based Simulation Study on Mass Collaborative Product Development Process

    Directory of Open Access Journals (Sweden)

    Shuo Zhang

    2015-01-01

    Full Text Available Mass collaborative product development (MCPD benefits people by high innovation products with lower cost and shorter lead time due to quick development of group innovation, Internet-based customization, and prototype manufacturing. Simulation is an effective way to study the evolution process and therefore to guarantee the success of MCPD. In this paper, an agent behavior-based simulation approach of MCPD is developed, which models the MCPD process as the interactive process of design agents and the environment objects based on Complex Adaptive System (CAS theory. Next, the structure model of design agent is proposed, and the modification and collaboration behaviors are described. Third, the agent behavior-based simulation flow of MCPD is designed. At last, simulation experiments are carried out based on an engineering case of mobile phone design. The experiment results show the following: (1 the community scale has significant influence on MCPD process; (2 the simulation process can explicitly represent the modification and collaboration behaviors of design agents; (3 the community evolution process can be observed and analyzed dynamically based on simulation data.

  14. Computer-aided process planning in prismatic shape die components based on Standard for the Exchange of Product model data

    Directory of Open Access Journals (Sweden)

    Awais Ahmad Khan

    2015-11-01

    Full Text Available Insufficient technologies made good integration between the die components in design, process planning, and manufacturing impossible in the past few years. Nowadays, the advanced technologies based on Standard for the Exchange of Product model data are making it possible. This article discusses the three main steps for achieving the complete process planning for prismatic parts of the die components. These three steps are data extraction, feature recognition, and process planning. The proposed computer-aided process planning system works as part of an integrated system to cover the process planning of any prismatic part die component. The system is built using Visual Basic with EWDraw system for visualizing the Standard for the Exchange of Product model data file. The system works successfully and can cover any type of sheet metal die components. The case study discussed in this article is taken from a large design of progressive die.

  15. An integrated modeling framework of socio-economic, biophysical, and hydrological processes in Midwest landscapes: Remote sensing data, agro-hydrological model, and agent-based model

    Science.gov (United States)

    Ding, Deng

    Intensive human-environment interactions are taking place in Midwestern agricultural systems. An integrated modeling framework is suitable for predicting dynamics of key variables of the socio-economic, biophysical, hydrological processes as well as exploring the potential transitions of system states in response to changes of the driving factors. The purpose of this dissertation is to address issues concerning the interacting processes and consequent changes in land use, water balance, and water quality using an integrated modeling framework. This dissertation is composed of three studies in the same agricultural watershed, the Clear Creek watershed in East-Central Iowa. In the first study, a parsimonious hydrologic model, the Threshold-Exceedance-Lagrangian Model (TELM), is further developed into RS-TELM (Remote Sensing TELM) to integrate remote sensing vegetation data for estimating evapotranspiration. The goodness of fit of RS-TELM is comparable to a well-calibrated SWAT (Soil and Water Assessment Tool) and even slightly superior in capturing intra-seasonal variability of stream flow. The integration of RS LAI (Leaf Area Index) data improves the model's performance especially over the agriculture dominated landscapes. The input of rainfall datasets with spatially explicit information plays a critical role in increasing the model's goodness of fit. In the second study, an agent-based model is developed to simulate farmers' decisions on crop type and fertilizer application in response to commodity and biofuel crop prices. The comparison between simulated crop land percentage and crop rotations with satellite-based land cover data suggest that farmers may be underestimating the effects that continuous corn production has on yields (yield drag). The simulation results given alternative market scenarios based on a survey of agricultural land owners and operators in the Clear Creek Watershed show that, farmers see cellulosic biofuel feedstock production in the form

  16. Modeling and Simulation of Membrane-Based Dehumidification and Energy Recovery Process

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Zhiming [ORNL; Abdelaziz, Omar [ORNL; Qu, Ming [ORNL

    2017-01-01

    This paper introduces a first-order physics-based model that accounts for the fundamental heat and mass transfer between a humid-air vapor stream on feed side to another flow stream on permeate side. The model comprises a few optional submodels for membrane mass transport; and it adopts a segment-by-segment method for discretizing heat and mass transfer governing equations for flow streams on feed and permeate sides. The model is able to simulate both dehumidifiers and energy recovery ventilators in parallel-flow, cross-flow, and counter-flow configurations. The predicted tresults are compared reasonably well with the measurements. The open-source codes are written in C++. The model and open-source codes are expected to become a fundament tool for the analysis of membrane-based dehumidification in the future.

  17. Towards simplification of hydrologic modeling: Identification of dominant processes

    Science.gov (United States)

    Markstrom, Steven; Hay, Lauren E.; Clark, Martyn P.

    2016-01-01

    The Precipitation–Runoff Modeling System (PRMS), a distributed-parameter hydrologic model, has been applied to the conterminous US (CONUS). Parameter sensitivity analysis was used to identify: (1) the sensitive input parameters and (2) particular model output variables that could be associated with the dominant hydrologic process(es). Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) and model performance statistic (mean, coefficient of variation, and autoregressive lag 1). Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters. The results of this study indicate that: (1) the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2) the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3) different processes require different numbers of parameters for simulation, and (4) some sensitive parameters influence only one hydrologic process, while others may influence many

  18. ANNIE - INTERACTIVE PROCESSING OF DATA BASES FOR HYDROLOGIC MODELS.

    Science.gov (United States)

    Lumb, Alan M.; Kittle, John L.

    1985-01-01

    ANNIE is a data storage and retrieval system that was developed to reduce the time and effort required to calibrate, verify, and apply watershed models that continuously simulate water quantity and quality. Watershed models have three categories of input: parameters to describe segments of a drainage area, linkage of the segments, and time-series data. Additional goals for ANNIE include the development of software that is easily implemented on minicomputers and some microcomputers and software that has no special requirements for interactive display terminals. Another goal is for the user interaction to be based on the experience of the user so that ANNIE is helpful to the inexperienced user and yet efficient and brief for the experienced user. Finally, the code should be designed so that additional hydrologic models can easily be added to ANNIE.

  19. Towards automatic model based controller design for reconfigurable plants

    DEFF Research Database (Denmark)

    Michelsen, Axel Gottlieb; Stoustrup, Jakob; Izadi-Zamanabadi, Roozbeh

    2008-01-01

    This paper introduces model-based Plug and Play Process Control, a novel concept for process control, which allows a model-based control system to be reconfigured when a sensor or an actuator is plugged into a controlled process. The work reported in this paper focuses on composing a monolithic m...

  20. Application of a process-based shallow landslide hazard model over a broad area in Central Italy

    Science.gov (United States)

    Gioia, Eleonora; Speranza, Gabriella; Ferretti, Maurizio; Godt, Jonathan W.; Baum, Rex L.; Marincioni, Fausto

    2015-01-01

    Process-based models are widely used for rainfall-induced shallow landslide forecasting. Previous studies have successfully applied the U.S. Geological Survey’s Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model (Baum et al. 2002) to compute infiltration-driven changes in the hillslopes’ factor of safety on small scales (i.e., tens of square kilometers). Soil data input for such models are difficult to obtain across larger regions. This work describes a novel methodology for the application of TRIGRS over broad areas with relatively uniform hydrogeological properties. The study area is a 550-km2 region in Central Italy covered by post-orogenic Quaternary sediments. Due to the lack of field data, we assigned mechanical and hydrological property values through a statistical analysis based on literature review of soils matching the local lithologies. We calibrated the model using rainfall data from 25 historical rainfall events that triggered landslides. We compared the variation of pressure head and factor of safety with the landslide occurrence to identify the best fitting input conditions. Using calibrated inputs and a soil depth model, we ran TRIGRS for the study area. Receiver operating characteristic (ROC) analysis, comparing the model’s output with a shallow landslide inventory, shows that TRIGRS effectively simulated the instability conditions in the post-orogenic complex during historical rainfall scenarios. The implication of this work is that rainfall-induced landslides over large regions may be predicted by a deterministic model, even where data on geotechnical and hydraulic properties as well as temporal changes in topography or subsurface conditions are not available.

  1. A continuum based fem model for friction stir welding-model development

    Energy Technology Data Exchange (ETDEWEB)

    Buffa, G. [Ohio State University, Department of Industrial, Welding and Systems Engineering, 1971 Neil Avenue, 210 Baker Systems, Columbus, OH 43210 (United States) and Dipartimento di Tecnologia Meccanica, Produzione e Ingegneria Gestionale, Universita di Palermo, Viale delle Scienze, 90128 Palermo (Italy)]. E-mail: g.buffa@dtpm.unipa.it; Hua, J. [Ohio State University, Department of Industrial, Welding and Systems Engineering, 1971 Neil Avenue, 210 Baker Systems, Columbus, OH 43210 (United States)]. E-mail: hua.14@osu.edu; Shivpuri, R. [Ohio State University, Department of Industrial, Welding and Systems Engineering, 1971 Neil Avenue, 210 Baker Systems, Columbus, OH 43210 (United States)]. E-mail: shivpuri.1@osu.edu; Fratini, L. [Dipartimento di Tecnologia Meccanica, Produzione e Ingegneria Gestionale, Universita di Palermo, Viale delle Scienze, 90128 Palermo (Italy)]. E-mail: abaqus@dtpm.unipa.it

    2006-03-15

    Although friction stir welding (FSW) has been successfully used to join materials that are difficult-to-weld or unweldeable by fusion welding methods, it is still in its early development stage and, therefore, a scientific knowledge based predictive model is of significant help for thorough understanding of FSW process. In this paper, a continuum based FEM model for friction stir welding process is proposed, that is 3D Lagrangian implicit, coupled, rigid-viscoplastic. This model is calibrated by comparing with experimental results of force and temperature distribution, then is used to investigate the distribution of temperature and strain in heat affect zone and the weld nugget. The model correctly predicts the non-symmetric nature of FSW process, and the relationships between the tool forces and the variation in the process parameters. It is found that the effective strain distribution is non-symmetric about the weld line while the temperature profile is almost symmetric in the weld zone.

  2. A continuum based fem model for friction stir welding-model development

    International Nuclear Information System (INIS)

    Buffa, G.; Hua, J.; Shivpuri, R.; Fratini, L.

    2006-01-01

    Although friction stir welding (FSW) has been successfully used to join materials that are difficult-to-weld or unweldeable by fusion welding methods, it is still in its early development stage and, therefore, a scientific knowledge based predictive model is of significant help for thorough understanding of FSW process. In this paper, a continuum based FEM model for friction stir welding process is proposed, that is 3D Lagrangian implicit, coupled, rigid-viscoplastic. This model is calibrated by comparing with experimental results of force and temperature distribution, then is used to investigate the distribution of temperature and strain in heat affect zone and the weld nugget. The model correctly predicts the non-symmetric nature of FSW process, and the relationships between the tool forces and the variation in the process parameters. It is found that the effective strain distribution is non-symmetric about the weld line while the temperature profile is almost symmetric in the weld zone

  3. Implementation of a Web-Based Organ Donation Educational Intervention: Development and Use of a Refined Process Evaluation Model.

    Science.gov (United States)

    Redmond, Nakeva; Harker, Laura; Bamps, Yvan; Flemming, Shauna St Clair; Perryman, Jennie P; Thompson, Nancy J; Patzer, Rachel E; Williams, Nancy S DeSousa; Arriola, Kimberly R Jacob

    2017-11-30

    The lack of available organs is often considered to be the single greatest problem in transplantation today. Internet use is at an all-time high, creating an opportunity to increase public commitment to organ donation through the broad reach of Web-based behavioral interventions. Implementing Internet interventions, however, presents challenges including preventing fraudulent respondents and ensuring intervention uptake. Although Web-based organ donation interventions have increased in recent years, process evaluation models appropriate for Web-based interventions are lacking. The aim of this study was to describe a refined process evaluation model adapted for Web-based settings and used to assess the implementation of a Web-based intervention aimed to increase organ donation among African Americans. We used a randomized pretest-posttest control design to assess the effectiveness of the intervention website that addressed barriers to organ donation through corresponding videos. Eligible participants were African American adult residents of Georgia who were not registered on the state donor registry. Drawing from previously developed process evaluation constructs, we adapted reach (the extent to which individuals were found eligible, and participated in the study), recruitment (online recruitment mechanism), dose received (intervention uptake), and context (how the Web-based setting influenced study implementation) for Internet settings and used the adapted model to assess the implementation of our Web-based intervention. With regard to reach, 1415 individuals completed the eligibility screener; 948 (67.00%) were determined eligible, of whom 918 (96.8%) completed the study. After eliminating duplicate entries (n=17), those who did not initiate the posttest (n=21) and those with an invalid ZIP code (n=108), 772 valid entries remained. Per the Internet protocol (IP) address analysis, only 23 of the 772 valid entries (3.0%) were within Georgia, and only 17 of those

  4. Mapping care processes within a hospital: from theory to a web-based proposal merging enterprise modelling and ISO normative principles.

    Science.gov (United States)

    Staccini, Pascal; Joubert, Michel; Quaranta, Jean-François; Fieschi, Marius

    2005-03-01

    Today, the economic and regulatory environment, involving activity-based and prospective payment systems, healthcare quality and risk analysis, traceability of the acts performed and evaluation of care practices, accounts for the current interest in clinical and hospital information systems. The structured gathering of information relative to users' needs and system requirements is fundamental when installing such systems. This stage takes time and is generally misconstrued by caregivers and is of limited efficacy to analysts. We used a modelling technique designed for manufacturing processes (IDEF0/SADT). We enhanced the basic model of an activity with descriptors extracted from the Ishikawa cause-and-effect diagram (methods, men, materials, machines, and environment). We proposed an object data model of a process and its components, and programmed a web-based tool in an object-oriented environment. This tool makes it possible to extract the data dictionary of a given process from the description of its elements and to locate documents (procedures, recommendations, instructions) according to each activity or role. Aimed at structuring needs and storing information provided by directly involved teams regarding the workings of an institution (or at least part of it), the process-mapping approach has an important contribution to make in the analysis of clinical information systems.

  5. Enforcement of entailment constraints in distributed service-based business processes.

    Science.gov (United States)

    Hummer, Waldemar; Gaubatz, Patrick; Strembeck, Mark; Zdun, Uwe; Dustdar, Schahram

    2013-11-01

    A distributed business process is executed in a distributed computing environment. The service-oriented architecture (SOA) paradigm is a popular option for the integration of software services and execution of distributed business processes. Entailment constraints, such as mutual exclusion and binding constraints, are important means to control process execution. Mutually exclusive tasks result from the division of powerful rights and responsibilities to prevent fraud and abuse. In contrast, binding constraints define that a subject who performed one task must also perform the corresponding bound task(s). We aim to provide a model-driven approach for the specification and enforcement of task-based entailment constraints in distributed service-based business processes. Based on a generic metamodel, we define a domain-specific language (DSL) that maps the different modeling-level artifacts to the implementation-level. The DSL integrates elements from role-based access control (RBAC) with the tasks that are performed in a business process. Process definitions are annotated using the DSL, and our software platform uses automated model transformations to produce executable WS-BPEL specifications which enforce the entailment constraints. We evaluate the impact of constraint enforcement on runtime performance for five selected service-based processes from existing literature. Our evaluation demonstrates that the approach correctly enforces task-based entailment constraints at runtime. The performance experiments illustrate that the runtime enforcement operates with an overhead that scales well up to the order of several ten thousand logged invocations. Using our DSL annotations, the user-defined process definition remains declarative and clean of security enforcement code. Our approach decouples the concerns of (non-technical) domain experts from technical details of entailment constraint enforcement. The developed framework integrates seamlessly with WS-BPEL and the Web

  6. Quality prediction modeling for sintered ores based on mechanism models of sintering and extreme learning machine based error compensation

    Science.gov (United States)

    Tiebin, Wu; Yunlian, Liu; Xinjun, Li; Yi, Yu; Bin, Zhang

    2018-06-01

    Aiming at the difficulty in quality prediction of sintered ores, a hybrid prediction model is established based on mechanism models of sintering and time-weighted error compensation on the basis of the extreme learning machine (ELM). At first, mechanism models of drum index, total iron, and alkalinity are constructed according to the chemical reaction mechanism and conservation of matter in the sintering process. As the process is simplified in the mechanism models, these models are not able to describe high nonlinearity. Therefore, errors are inevitable. For this reason, the time-weighted ELM based error compensation model is established. Simulation results verify that the hybrid model has a high accuracy and can meet the requirement for industrial applications.

  7. A simplified computational memory model from information processing

    Science.gov (United States)

    Zhang, Lanhua; Zhang, Dongsheng; Deng, Yuqin; Ding, Xiaoqian; Wang, Yan; Tang, Yiyuan; Sun, Baoliang

    2016-01-01

    This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracting memory function and simulating memory information processing. At first meta-memory is defined to express the neuron or brain cortices based on the biology and graph theories, and we develop an intra-modular network with the modeling algorithm by mapping the node and edge, and then the bi-modular network is delineated with intra-modular and inter-modular. At last a polynomial retrieval algorithm is introduced. In this paper we simulate the memory phenomena and functions of memorization and strengthening by information processing algorithms. The theoretical analysis and the simulation results show that the model is in accordance with the memory phenomena from information processing view. PMID:27876847

  8. Modeling post-wildfire hydrological processes with ParFlow

    Science.gov (United States)

    Escobar, I. S.; Lopez, S. R.; Kinoshita, A. M.

    2017-12-01

    Wildfires alter the natural processes within a watershed, such as surface runoff, evapotranspiration rates, and subsurface water storage. Post-fire hydrologic models are typically one-dimensional, empirically-based models or two-dimensional, conceptually-based models with lumped parameter distributions. These models are useful for modeling and predictions at the watershed outlet; however, do not provide detailed, distributed hydrologic processes at the point scale within the watershed. This research uses ParFlow, a three-dimensional, distributed hydrologic model to simulate post-fire hydrologic processes by representing the spatial and temporal variability of soil burn severity (via hydrophobicity) and vegetation recovery. Using this approach, we are able to evaluate the change in post-fire water components (surface flow, lateral flow, baseflow, and evapotranspiration). This work builds upon previous field and remote sensing analysis conducted for the 2003 Old Fire Burn in Devil Canyon, located in southern California (USA). This model is initially developed for a hillslope defined by a 500 m by 1000 m lateral extent. The subsurface reaches 12.4 m and is assigned a variable cell thickness to explicitly consider soil burn severity throughout the stages of recovery and vegetation regrowth. We consider four slope and eight hydrophobic layer configurations. Evapotranspiration is used as a proxy for vegetation regrowth and is represented by the satellite-based Simplified Surface Energy Balance (SSEBOP) product. The pre- and post-fire surface runoff, subsurface storage, and surface storage interactions are evaluated at the point scale. Results will be used as a basis for developing and fine-tuning a watershed-scale model. Long-term simulations will advance our understanding of post-fire hydrological partitioning between water balance components and the spatial variability of watershed processes, providing improved guidance for post-fire watershed management. In reference

  9. EVALUATING REGIONAL PREDICTIVE CAPACITY OF A PROCESS-BASED MERCURY EXPOSURE MODEL, REGIONAL-MERCURY CYCLING MODEL (R-MCM), APPLIED TO 91 VERMONT AND NEW HAMPSHIRE LAKES AND PONDS, USA

    Science.gov (United States)

    Regulatory agencies must develop fish consumption advisories for many lakes and rivers with limited resources. Process-based mathematical models are potentially valuable tools for developing regional fish advisories. The Regional Mercury Cycling model (R-MCM) was specifically d...

  10. Process modeling and supply chain design for advanced biofuel production based on bio-oil gasification

    Science.gov (United States)

    Li, Qi

    As a potential substitute for petroleum-based fuel, second generation biofuels are playing an increasingly important role due to their economic, environmental, and social benefits. With the rapid development of biofuel industry, there has been an increasing literature on the techno-economic analysis and supply chain design for biofuel production based on a variety of production pathways. A recently proposed production pathway of advanced biofuel is to convert biomass to bio-oil at widely distributed small-scale fast pyrolysis plants, then gasify the bio-oil to syngas and upgrade the syngas to transportation fuels in centralized biorefinery. This thesis aims to investigate two types of assessments on this bio-oil gasification pathway: techno-economic analysis based on process modeling and literature data; supply chain design with a focus on optimal decisions for number of facilities to build, facility capacities and logistic decisions considering uncertainties. A detailed process modeling with corn stover as feedstock and liquid fuels as the final products is presented. Techno-economic analysis of the bio-oil gasification pathway is also discussed to assess the economic feasibility. Some preliminary results show a capital investment of 438 million dollar and minimum fuel selling price (MSP) of $5.6 per gallon of gasoline equivalent. The sensitivity analysis finds that MSP is most sensitive to internal rate of return (IRR), biomass feedstock cost, and fixed capital cost. A two-stage stochastic programming is formulated to solve the supply chain design problem considering uncertainties in biomass availability, technology advancement, and biofuel price. The first-stage makes the capital investment decisions including the locations and capacities of the decentralized fast pyrolysis plants and the centralized biorefinery while the second-stage determines the biomass and biofuel flows. The numerical results and case study illustrate that considering uncertainties can be

  11. Processing Technology Selection for Municipal Sewage Treatment Based on a Multi-Objective Decision Model under Uncertainty.

    Science.gov (United States)

    Chen, Xudong; Xu, Zhongwen; Yao, Liming; Ma, Ning

    2018-03-05

    This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.

  12. Embedding a State Space Model Into a Markov Decision Process

    DEFF Research Database (Denmark)

    Nielsen, Lars Relund; Jørgensen, Erik; Højsgaard, Søren

    2011-01-01

    In agriculture Markov decision processes (MDPs) with finite state and action space are often used to model sequential decision making over time. For instance, states in the process represent possible levels of traits of the animal and transition probabilities are based on biological models...

  13. Thermodynamics of information processing based on enzyme kinetics: An exactly solvable model of an information pump.

    Science.gov (United States)

    Cao, Yuansheng; Gong, Zongping; Quan, H T

    2015-06-01

    Motivated by the recent proposed models of the information engine [Proc. Natl. Acad. Sci. USA 109, 11641 (2012)] and the information refrigerator [Phys. Rev. Lett. 111, 030602 (2013)], we propose a minimal model of the information pump and the information eraser based on enzyme kinetics. This device can either pump molecules against the chemical potential gradient by consuming the information to be encoded in the bit stream or (partially) erase the information initially encoded in the bit stream by consuming the Gibbs free energy. The dynamics of this model is solved exactly, and the "phase diagram" of the operation regimes is determined. The efficiency and the power of the information machine is analyzed. The validity of the second law of thermodynamics within our model is clarified. Our model offers a simple paradigm for the investigating of the thermodynamics of information processing involving the chemical potential in small systems.

  14. A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction

    International Nuclear Information System (INIS)

    Yu, Jie; Chen, Kuilin; Mori, Junichi; Rashid, Mudassir M.

    2013-01-01

    Optimizing wind power generation and controlling the operation of wind turbines to efficiently harness the renewable wind energy is a challenging task due to the intermittency and unpredictable nature of wind speed, which has significant influence on wind power production. A new approach for long-term wind speed forecasting is developed in this study by integrating GMCM (Gaussian mixture copula model) and localized GPR (Gaussian process regression). The time series of wind speed is first classified into multiple non-Gaussian components through the Gaussian mixture copula model and then Bayesian inference strategy is employed to incorporate the various non-Gaussian components using the posterior probabilities. Further, the localized Gaussian process regression models corresponding to different non-Gaussian components are built to characterize the stochastic uncertainty and non-stationary seasonality of the wind speed data. The various localized GPR models are integrated through the posterior probabilities as the weightings so that a global predictive model is developed for the prediction of wind speed. The proposed GMCM–GPR approach is demonstrated using wind speed data from various wind farm locations and compared against the GMCM-based ARIMA (auto-regressive integrated moving average) and SVR (support vector regression) methods. In contrast to GMCM–ARIMA and GMCM–SVR methods, the proposed GMCM–GPR model is able to well characterize the multi-seasonality and uncertainty of wind speed series for accurate long-term prediction. - Highlights: • A novel predictive modeling method is proposed for long-term wind speed forecasting. • Gaussian mixture copula model is estimated to characterize the multi-seasonality. • Localized Gaussian process regression models can deal with the random uncertainty. • Multiple GPR models are integrated through Bayesian inference strategy. • The proposed approach shows higher prediction accuracy and reliability

  15. 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.

  16. 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

  17. Modeling multiphase materials processes

    CERN Document Server

    Iguchi, Manabu

    2010-01-01

    ""Modeling Multiphase Materials Processes: Gas-Liquid Systems"" describes the methodology and application of physical and mathematical modeling to multi-phase flow phenomena in materials processing. The book focuses on systems involving gas-liquid interaction, the most prevalent in current metallurgical processes. The performance characteristics of these processes are largely dependent on transport phenomena. This volume covers the inherent characteristics that complicate the modeling of transport phenomena in such systems, including complex multiphase structure, intense turbulence, opacity of

  18. Evidence-based quantification of uncertainties induced via simulation-based modeling

    International Nuclear Information System (INIS)

    Riley, Matthew E.

    2015-01-01

    The quantification of uncertainties in simulation-based modeling traditionally focuses upon quantifying uncertainties in the parameters input into the model, referred to as parametric uncertainties. Often neglected in such an approach are the uncertainties induced by the modeling process itself. This deficiency is often due to a lack of information regarding the problem or the models considered, which could theoretically be reduced through the introduction of additional data. Because of the nature of this epistemic uncertainty, traditional probabilistic frameworks utilized for the quantification of uncertainties are not necessarily applicable to quantify the uncertainties induced in the modeling process itself. This work develops and utilizes a methodology – incorporating aspects of Dempster–Shafer Theory and Bayesian model averaging – to quantify uncertainties of all forms for simulation-based modeling problems. The approach expands upon classical parametric uncertainty approaches, allowing for the quantification of modeling-induced uncertainties as well, ultimately providing bounds on classical probability without the loss of epistemic generality. The approach is demonstrated on two different simulation-based modeling problems: the computation of the natural frequency of a simple two degree of freedom non-linear spring mass system and the calculation of the flutter velocity coefficient for the AGARD 445.6 wing given a subset of commercially available modeling choices. - Highlights: • Modeling-induced uncertainties are often mishandled or ignored in the literature. • Modeling-induced uncertainties are epistemic in nature. • Probabilistic representations of modeling-induced uncertainties are restrictive. • Evidence theory and Bayesian model averaging are integrated. • Developed approach is applicable for simulation-based modeling problems

  19. Through-process modelling of texture and anisotropy in AA5182

    Science.gov (United States)

    Crumbach, M.; Neumann, L.; Goerdeler, M.; Aretz, H.; Gottstein, G.; Kopp, R.

    2006-07-01

    A through-process texture and anisotropy prediction for AA5182 sheet production from hot rolling through cold rolling and annealing is reported. Thermo-mechanical process data predicted by the finite element method (FEM) package T-Pack based on the software LARSTRAN were fed into a combination of physics based microstructure models for deformation texture (GIA), work hardening (3IVM), nucleation texture (ReNuc), and recrystallization texture (StaRT). The final simulated sheet texture was fed into a FEM simulation of cup drawing employing a new concept of interactively updated texture based yield locus predictions. The modelling results of texture development and anisotropy were compared to experimental data. The applicability to other alloys and processes is discussed.

  20. Towards simplification of hydrologic modeling: identification of dominant processes

    Directory of Open Access Journals (Sweden)

    S. L. Markstrom

    2016-11-01

    Full Text Available parameter hydrologic model, has been applied to the conterminous US (CONUS. Parameter sensitivity analysis was used to identify: (1 the sensitive input parameters and (2 particular model output variables that could be associated with the dominant hydrologic process(es. Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff and model performance statistic (mean, coefficient of variation, and autoregressive lag 1. Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters. The results of this study indicate that: (1 the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2 the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3 different processes require different numbers of parameters for simulation, and (4 some sensitive parameters influence only one hydrologic process, while others may influence many.

  1. Modelling of a Naphtha Recovery Unit (NRU with Implications for Process Optimization

    Directory of Open Access Journals (Sweden)

    Jiawei Du

    2018-06-01

    Full Text Available The naphtha recovery unit (NRU is an integral part of the processes used in the oil sands industry for bitumen extraction. The principle role of the NRU is to recover naphtha from the tailings for reuse in this process. This process is energy-intensive, and environmental guidelines for naphtha recovery must be met. Steady-state models for the NRU system are developed in this paper using two different approaches. The first approach is a statistical, data-based modelling approach where linear regression models have been developed using Minitab® from plant data collected during a performance test. The second approach involves the development of a first-principles model in Aspen Plus® based on the NRU process flow diagram. A novel refinement to this latter model, called “withdraw and remix”, is proposed based on comparing actual plant data to model predictions around the two units used to separate water and naphtha. The models developed in this paper suggest some interesting ideas for the further optimization of the process, in that it may be possible to achieve the required naphtha recovery using less energy. More plant tests are required to validate these ideas.

  2. Advances in modeling plastic waste pyrolysis processes

    Energy Technology Data Exchange (ETDEWEB)

    Safadi, Y. [Department of Mechanical Engineering, American University of Beirut, PO Box 11-0236, Beirut (Lebanon); Zeaiter, J. [Chemical Engineering Program, American University of Beirut, PO Box 11-0236, Beirut (Lebanon)

    2013-07-01

    The tertiary recycling of plastics via pyrolysis is recently gaining momentum due to promising economic returns from the generated products that can be used as a chemical feedstock or fuel. The need for prediction models to simulate such processes is essential in understanding in depth the mechanisms that take place during the thermal or catalytic degradation of the waste polymer. This paper presents key different models used successfully in literature so far. Three modeling schemes are identified: Power-Law, Lumped-Empirical, and Population-Balance based equations. The categorization is based mainly on the level of detail and prediction capability from each modeling scheme. The data shows that the reliability of these modeling approaches vary with the degree of details the experimental work and product analysis are trying to achieve.

  3. A process-based model for the definition of hydrological alert systems in landslide risk mitigation

    Directory of Open Access Journals (Sweden)

    M. Floris

    2012-11-01

    Full Text Available The definition of hydrological alert systems for rainfall-induced landslides is strongly related to a deep knowledge of the geological and geomorphological features of the territory. Climatic conditions, spatial and temporal evolution of the phenomena and characterization of landslide triggering, together with propagation mechanisms, are the key elements to be considered. Critical steps for the development of the systems consist of the identification of the hydrological variable related to landslide triggering and of the minimum rainfall threshold for landslide occurrence.

    In this paper we report the results from a process-based model to define a hydrological alert system for the Val di Maso Landslide, located in the northeastern Italian Alps and included in the Vicenza Province (Veneto region, NE Italy. The instability occurred in November 2010, due to an exceptional rainfall event that hit the Vicenza Province and the entire NE Italy. Up to 500 mm in 3-day cumulated rainfall generated large flood conditions and triggered hundreds of landslides. During the flood, the Soil Protection Division of the Vicenza Province received more than 500 warnings of instability phenomena. The complexity of the event and the high level of risk to infrastructure and private buildings are the main reasons for deepening the specific phenomenon occurred at Val di Maso.

    Empirical and physically-based models have been used to identify the minimum rainfall threshold for the occurrence of instability phenomena in the crown area of Val di Maso landslide, where a retrogressive evolution by multiple rotational slides is expected. Empirical models helped in the identification and in the evaluation of recurrence of critical rainfall events, while physically-based modelling was essential to verify the effects on the slope stability of determined rainfall depths. Empirical relationships between rainfall and landslide consist of the calculation of rainfall

  4. Model-based optimization biofilm based systems performing autotrophic nitrogen removal using the comprehensive NDHA model

    DEFF Research Database (Denmark)

    Valverde Pérez, Borja; Ma, Yunjie; Morset, Martin

    Completely autotrophic nitrogen removal (CANR) can be obtained in single stage biofilm-based bioreactors. However, their environmental footprint is compromised due to elevated N2O emissions. We developed novel spatially explicit biochemical process model of biofilm based CANR systems that predicts...

  5. PID controller auto-tuning based on process step response and damping optimum criterion.

    Science.gov (United States)

    Pavković, Danijel; Polak, Siniša; Zorc, Davor

    2014-01-01

    This paper presents a novel method of PID controller tuning suitable for higher-order aperiodic processes and aimed at step response-based auto-tuning applications. The PID controller tuning is based on the identification of so-called n-th order lag (PTn) process model and application of damping optimum criterion, thus facilitating straightforward algebraic rules for the adjustment of both the closed-loop response speed and damping. The PTn model identification is based on the process step response, wherein the PTn model parameters are evaluated in a novel manner from the process step response equivalent dead-time and lag time constant. The effectiveness of the proposed PTn model parameter estimation procedure and the related damping optimum-based PID controller auto-tuning have been verified by means of extensive computer simulations. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Comparing single- and dual-process models of memory development.

    Science.gov (United States)

    Hayes, Brett K; Dunn, John C; Joubert, Amy; Taylor, Robert

    2017-11-01

    This experiment examined single-process and dual-process accounts of the development of visual recognition memory. The participants, 6-7-year-olds, 9-10-year-olds and adults, were presented with a list of pictures which they encoded under shallow or deep conditions. They then made recognition and confidence judgments about a list containing old and new items. We replicated the main trends reported by Ghetti and Angelini () in that recognition hit rates increased from 6 to 9 years of age, with larger age changes following deep than shallow encoding. Formal versions of the dual-process high threshold signal detection model and several single-process models (equal variance signal detection, unequal variance signal detection, mixture signal detection) were fit to the developmental data. The unequal variance and mixture signal detection models gave a better account of the data than either of the other models. A state-trace analysis found evidence for only one underlying memory process across the age range tested. These results suggest that single-process memory models based on memory strength are a viable alternative to dual-process models for explaining memory development. © 2016 John Wiley & Sons Ltd.

  7. Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity

    Directory of Open Access Journals (Sweden)

    Isao Ishida

    2015-01-01

    Full Text Available We introduce and investigate some properties of a class of nonlinear time series models based on the moving sample quantiles in the autoregressive data generating process. We derive a test fit to detect this type of nonlinearity. Using the daily realized volatility data of Standard & Poor’s 500 (S&P 500 and several other indices, we obtained good performance using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear heterogeneous autoregressive and other models of realized volatility.

  8. Process-based costing.

    Science.gov (United States)

    Lee, Robert H; Bott, Marjorie J; Forbes, Sarah; Redford, Linda; Swagerty, Daniel L; Taunton, Roma Lee

    2003-01-01

    Understanding how quality improvement affects costs is important. Unfortunately, low-cost, reliable ways of measuring direct costs are scarce. This article builds on the principles of process improvement to develop a costing strategy that meets both criteria. Process-based costing has 4 steps: developing a flowchart, estimating resource use, valuing resources, and calculating direct costs. To illustrate the technique, this article uses it to cost the care planning process in 3 long-term care facilities. We conclude that process-based costing is easy to implement; generates reliable, valid data; and allows nursing managers to assess the costs of new or modified processes.

  9. Business Process Modeling: Perceived Benefits

    Science.gov (United States)

    Indulska, Marta; Green, Peter; Recker, Jan; Rosemann, Michael

    The process-centered design of organizations and information systems is globally seen as an appropriate response to the increased economic pressure on organizations. At the methodological core of process-centered management is process modeling. However, business process modeling in large initiatives can be a time-consuming and costly exercise, making it potentially difficult to convince executive management of its benefits. To date, and despite substantial interest and research in the area of process modeling, the understanding of the actual benefits of process modeling in academia and practice is limited. To address this gap, this paper explores the perception of benefits derived from process modeling initiatives, as reported through a global Delphi study. The study incorporates the views of three groups of stakeholders - academics, practitioners and vendors. Our findings lead to the first identification and ranking of 19 unique benefits associated with process modeling. The study in particular found that process modeling benefits vary significantly between practitioners and academics. We argue that the variations may point to a disconnect between research projects and practical demands.

  10. CROWDSOURCING BASED 3D MODELING

    Directory of Open Access Journals (Sweden)

    A. Somogyi

    2016-06-01

    Full Text Available Web-based photo albums that support organizing and viewing the users’ images are widely used. These services provide a convenient solution for storing, editing and sharing images. In many cases, the users attach geotags to the images in order to enable using them e.g. in location based applications on social networks. Our paper discusses a procedure that collects open access images from a site frequently visited by tourists. Geotagged pictures showing the image of a sight or tourist attraction are selected and processed in photogrammetric processing software that produces the 3D model of the captured object. For the particular investigation we selected three attractions in Budapest. To assess the geometrical accuracy, we used laser scanner and DSLR as well as smart phone photography to derive reference values to enable verifying the spatial model obtained from the web-album images. The investigation shows how detailed and accurate models could be derived applying photogrammetric processing software, simply by using images of the community, without visiting the site.

  11. Thermodynamics of information processing based on enzyme kinetics: An exactly solvable model of an information pump

    Science.gov (United States)

    Cao, Yuansheng; Gong, Zongping; Quan, H. T.

    2015-06-01

    Motivated by the recent proposed models of the information engine [Proc. Natl. Acad. Sci. USA 109, 11641 (2012), 10.1073/pnas.1204263109] and the information refrigerator [Phys. Rev. Lett. 111, 030602 (2013), 10.1103/PhysRevLett.111.030602], we propose a minimal model of the information pump and the information eraser based on enzyme kinetics. This device can either pump molecules against the chemical potential gradient by consuming the information to be encoded in the bit stream or (partially) erase the information initially encoded in the bit stream by consuming the Gibbs free energy. The dynamics of this model is solved exactly, and the "phase diagram" of the operation regimes is determined. The efficiency and the power of the information machine is analyzed. The validity of the second law of thermodynamics within our model is clarified. Our model offers a simple paradigm for the investigating of the thermodynamics of information processing involving the chemical potential in small systems.

  12. Outlooks for mathematical modelling of the glass melting process

    Energy Technology Data Exchange (ETDEWEB)

    Waal, H. de [TNO Institute of Applied Physics, Delft (Netherlands)

    1997-12-31

    Mathematical modelling is nowadays a standard tool for major producers of float glass, T.V. glass and fiberglass. Also for container glass furnaces, glass tank modelling proves to be a valuable method to optimize process conditions. Mathematical modelling is no longer just a way to visualize the flow patterns and to provide data on heat transfer. It can also predict glass quality in relation to process parameters, because all chemical and physical phenomena are included in the latest generation of models, based on experimental and theoretical research on these phenomena.

  13. Model-based high-throughout process development for chromatographic whey proteins separation

    NARCIS (Netherlands)

    Nfor, B.; Ripic, J.; Padt, van der A.; Jacobs, M.; Ottens, M.

    2012-01-01

    In this study, an integrated approach involving the combined use of high-throughput screening (HTS) and column modeling during process development was applied to an industrial case involving the evaluation of four anion-exchange chromatography (AEX) resins and four hydrophobic interaction

  14. Processing Technology Selection for Municipal Sewage Treatment Based on a Multi-Objective Decision Model under Uncertainty

    Directory of Open Access Journals (Sweden)

    Xudong Chen

    2018-03-01

    Full Text Available This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.

  15. Customer-centered careflow modeling based on guidelines.

    Science.gov (United States)

    Huang, Biqing; Zhu, Peng; Wu, Cheng

    2012-10-01

    In contemporary society, customer-centered health care, which stresses customer participation and long-term tailored care, is inevitably becoming a trend. Compared with the hospital or physician-centered healthcare process, the customer-centered healthcare process requires more knowledge and modeling such a process is extremely complex. Thus, building a care process model for a special customer is cost prohibitive. In addition, during the execution of a care process model, the information system should have flexibility to modify the model so that it adapts to changes in the healthcare process. Therefore, supporting the process in a flexible, cost-effective way is a key challenge for information technology. To meet this challenge, first, we analyze various kinds of knowledge used in process modeling, illustrate their characteristics, and detail their roles and effects in careflow modeling. Secondly, we propose a methodology to manage a lifecycle of the healthcare process modeling, with which models could be built gradually with convenience and efficiency. In this lifecycle, different levels of process models are established based on the kinds of knowledge involved, and the diffusion strategy of these process models is designed. Thirdly, architecture and prototype of the system supporting the process modeling and its lifecycle are given. This careflow system also considers the compatibility of legacy systems and authority problems. Finally, an example is provided to demonstrate implementation of the careflow system.

  16. Upscaling Empirically Based Conceptualisations to Model Tropical Dominant Hydrological Processes for Historical Land Use Change

    Science.gov (United States)

    Toohey, R.; Boll, J.; Brooks, E.; Jones, J.

    2009-12-01

    Surface runoff and percolation to ground water are two hydrological processes of concern to the Atlantic slope of Costa Rica because of their impacts on flooding and drinking water contamination. As per legislation, the Costa Rican Government funds land use management from the farm to the regional scale to improve or conserve hydrological ecosystem services. In this study, we examined how land use (e.g., forest, coffee, sugar cane, and pasture) affects hydrological response at the point, plot (1 m2), and the field scale (1-6ha) to empirically conceptualize the dominant hydrological processes in each land use. Using our field data, we upscaled these conceptual processes into a physically-based distributed hydrological model at the field, watershed (130 km2), and regional (1500 km2) scales. At the point and plot scales, the presence of macropores and large roots promoted greater vertical percolation and subsurface connectivity in the forest and coffee field sites. The lack of macropores and large roots, plus the addition of management artifacts (e.g., surface compaction and a plough layer), altered the dominant hydrological processes by increasing lateral flow and surface runoff in the pasture and sugar cane field sites. Macropores and topography were major influences on runoff generation at the field scale. Also at the field scale, antecedent moisture conditions suggest a threshold behavior as a temporal control on surface runoff generation. However, in this tropical climate with very intense rainstorms, annual surface runoff was less than 10% of annual precipitation at the field scale. Significant differences in soil and hydrological characteristics observed at the point and plot scales appear to have less significance when upscaled to the field scale. At the point and plot scales, percolation acted as the dominant hydrological process in this tropical environment. However, at the field scale for sugar cane and pasture sites, saturation-excess runoff increased as

  17. Towards Using Reo for Compliance-Aware Business Process Modeling

    Science.gov (United States)

    Arbab, Farhad; Kokash, Natallia; Meng, Sun

    Business process modeling and implementation of process supporting infrastructures are two challenging tasks that are not fully aligned. On the one hand, languages such as Business Process Modeling Notation (BPMN) exist to capture business processes at the level of domain analysis. On the other hand, programming paradigms and technologies such as Service-Oriented Computing (SOC) and web services have emerged to simplify the development of distributed web systems that underly business processes. BPMN is the most recognized language for specifying process workflows at the early design steps. However, it is rather declarative and may lead to the executable models which are incomplete or semantically erroneous. Therefore, an approach for expressing and analyzing BPMN models in a formal setting is required. In this paper we describe how BPMN diagrams can be represented by means of a semantically precise channel-based coordination language called Reo which admits formal analysis using model checking and bisimulation techniques. Moreover, since additional requirements may come from various regulatory/legislative documents, we discuss the opportunities offered by Reo and its mathematical abstractions for expressing process-related constraints such as Quality of Service (QoS) or time-aware conditions on process states.

  18. Agent Based Modeling Applications for Geosciences

    Science.gov (United States)

    Stein, J. S.

    2004-12-01

    Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in

  19. Bayesian model selection validates a biokinetic model for zirconium processing in humans

    Science.gov (United States)

    2012-01-01

    Background In radiation protection, biokinetic models for zirconium processing are of crucial importance in dose estimation and further risk analysis for humans exposed to this radioactive substance. They provide limiting values of detrimental effects and build the basis for applications in internal dosimetry, the prediction for radioactive zirconium retention in various organs as well as retrospective dosimetry. Multi-compartmental models are the tool of choice for simulating the processing of zirconium. Although easily interpretable, determining the exact compartment structure and interaction mechanisms is generally daunting. In the context of observing the dynamics of multiple compartments, Bayesian methods provide efficient tools for model inference and selection. Results We are the first to apply a Markov chain Monte Carlo approach to compute Bayes factors for the evaluation of two competing models for zirconium processing in the human body after ingestion. Based on in vivo measurements of human plasma and urine levels we were able to show that a recently published model is superior to the standard model of the International Commission on Radiological Protection. The Bayes factors were estimated by means of the numerically stable thermodynamic integration in combination with a recently developed copula-based Metropolis-Hastings sampler. Conclusions In contrast to the standard model the novel model predicts lower accretion of zirconium in bones. This results in lower levels of noxious doses for exposed individuals. Moreover, the Bayesian approach allows for retrospective dose assessment, including credible intervals for the initially ingested zirconium, in a significantly more reliable fashion than previously possible. All methods presented here are readily applicable to many modeling tasks in systems biology. PMID:22863152

  20. Towards elicitation of users requirements for hospital information system: from a care process modelling technique to a web based collaborative tool.

    Science.gov (United States)

    Staccini, Pascal M; Joubert, Michel; Quaranta, Jean-Francois; Fieschi, Marius

    2002-01-01

    Growing attention is being given to the use of process modeling methodology for user requirements elicitation. In the analysis phase of hospital information systems, the usefulness of care-process models has been investigated to evaluate the conceptual applicability and practical understandability by clinical staff and members of users teams. Nevertheless, there still remains a gap between users and analysts in their mutual ability to share conceptual views and vocabulary, keeping the meaning of clinical context while providing elements for analysis. One of the solutions for filling this gap is to consider the process model itself in the role of a hub as a centralized means of facilitating communication between team members. Starting with a robust and descriptive technique for process modeling called IDEF0/SADT, we refined the basic data model by extracting concepts from ISO 9000 process analysis and from enterprise ontology. We defined a web-based architecture to serve as a collaborative tool and implemented it using an object-oriented database. The prospects of such a tool are discussed notably regarding to its ability to generate data dictionaries and to be used as a navigation tool through the medium of hospital-wide documentation.

  1. Model-Based Reasoning in Humans Becomes Automatic with Training.

    Directory of Open Access Journals (Sweden)

    Marcos Economides

    2015-09-01

    Full Text Available Model-based and model-free reinforcement learning (RL have been suggested as algorithmic realizations of goal-directed and habitual action strategies. Model-based RL is more flexible than model-free but requires sophisticated calculations using a learnt model of the world. This has led model-based RL to be identified with slow, deliberative processing, and model-free RL with fast, automatic processing. In support of this distinction, it has recently been shown that model-based reasoning is impaired by placing subjects under cognitive load--a hallmark of non-automaticity. Here, using the same task, we show that cognitive load does not impair model-based reasoning if subjects receive prior training on the task. This finding is replicated across two studies and a variety of analysis methods. Thus, task familiarity permits use of model-based reasoning in parallel with other cognitive demands. The ability to deploy model-based reasoning in an automatic, parallelizable fashion has widespread theoretical implications, particularly for the learning and execution of complex behaviors. It also suggests a range of important failure modes in psychiatric disorders.

  2. A Model of the Creative Process Based on Quantum Physics and Vedic Science.

    Science.gov (United States)

    Rose, Laura Hall

    1988-01-01

    Using tenets from Vedic science and quantum physics, this model of the creative process suggests that the unified field of creation is pure consciousness, and that the development of the creative process within individuals mirrors the creative process within the universe. Rational and supra-rational creative thinking techniques are also described.…

  3. Nonlinear model-based control of the Czochralski process III: Proper choice of manipulated variables and controller parameter scheduling

    Science.gov (United States)

    Neubert, M.; Winkler, J.

    2012-12-01

    This contribution continues an article series [1,2] about the nonlinear model-based control of the Czochralski crystal growth process. The key idea of the presented approach is to use a sophisticated combination of nonlinear model-based and conventional (linear) PI controllers for tracking of both, crystal radius and growth rate. Using heater power and pulling speed as manipulated variables several controller structures are possible. The present part tries to systematize the properties of the materials to be grown in order to get unambiguous decision criteria for a most profitable choice of the controller structure. For this purpose a material specific constant M called interface mobility and a more process specific constant S called system response number are introduced. While the first one summarizes important material properties like thermal conductivity and latent heat the latter one characterizes the process by evaluating the average axial thermal gradients at the phase boundary and the actual growth rate at which the crystal is grown. Furthermore these characteristic numbers are useful for establishing a scheduling strategy for the PI controller parameters in order to improve the controller performance. Finally, both numbers give a better understanding of the general thermal system dynamics of the Czochralski technique.

  4. Integrated process-based hydrologic and ephemeral gully modeling for better assessment of soil erosion in small watersheds

    Science.gov (United States)

    Sheshukov, A. Y.; Karimov, V. R.

    2017-12-01

    Excessive soil erosion in agriculturally dominated watersheds causes degradation of arable land and affects agricultural productivity. Structural and soil-quality best management practices can be beneficial in reducing sheet and rill erosion, however, larger rills, ephemeral gullies, and concentrated flow channels still remain to be significant sources of sediment. A better understanding of channelized soil erosion, underlying physical processes, and ways to mitigate the problem is needed to develop innovative approaches for evaluation of soil losses from various sediment sources. The goal of this study was to develop a novel integrated process-based catchment-scale model for sheet, rill, and ephemeral gully erosion and assess soil erosion mitigation practices. Geospatially, a catchment was divided into ephemeral channels and contributing hillslopes. Surface runoff hydrograph and sheet-rill erosion rates from contributing hillslopes were calculated based on the Water Erosion Prediction Project (WEPP) model. For ephemeral channels, a dynamic ephemeral gully erosion model was developed. Each channel was divided into segments, and channel flow was routed according to the kinematic wave equation. Reshaping of the channel profile in each segment (sediment deposition, soil detachment) was simulated at each time-step according to acting shear stress distribution along the channel boundary and excess shear stress equation. The approach assumed physically-consistent channel shape reconfiguration representing channel walls failure and deposition in the bottom of the channel. Soil erodibility and critical shear stress parameters were dynamically adjusted due to seepage/drainage forces based on computed infiltration gradients. The model was validated on the data obtained from the field study by Karimov et al. (2014) yielding agreement with NSE coefficient of 0.72. The developed model allowed to compute ephemeral gully erosion while accounting for antecedent soil moisture

  5. Mathematical modelling of the laser processing of compose materials

    International Nuclear Information System (INIS)

    Gromyko, G.F.; Matsuka, N.P.

    2009-01-01

    Expansion of the protective coating scope led to the necessity to work out lower priced methods of treatment of machine elements. Making of an adequate, agreed with process features, mathematical model and development of effective methods of its solving are promising directions in this fields. In this paper the mathematical model of high-temperature laser treatment via moving source of pre-sprayed with composite powder padding is developed. Presented model describes accurately enough the heat processes taking place by laser processing of machine elements. Varying input parameters of model (laser power, temperature and composition of environment, characteristics and quantitative composition of using materials, etc.) one can get a cheap tool of preliminary estimates for wide range of similar problems. Difference method, based on process physical features and taking into account main process-dependent parameters had been developed for solving of the built system of nonlinear equations. (authors)

  6. A case study on point process modelling in disease mapping

    DEFF Research Database (Denmark)

    Møller, Jesper; Waagepetersen, Rasmus Plenge; Benes, Viktor

    2005-01-01

    of the risk on the covariates. Instead of using the common areal level approaches we base the analysis on a Bayesian approach for a log Gaussian Cox point process with covariates. Posterior characteristics for a discretized version of the log Gaussian Cox process are computed using Markov chain Monte Carlo...... methods. A particular problem which is thoroughly discussed is to determine a model for the background population density. The risk map shows a clear dependency with the population intensity models and the basic model which is adopted for the population intensity determines what covariates influence...... the risk of TBE. Model validation is based on the posterior predictive distribution of various summary statistics....

  7. Mathematical modeling of biomass fuels formation process

    International Nuclear Information System (INIS)

    Gaska, Krzysztof; Wandrasz, Andrzej J.

    2008-01-01

    The increasing demand for thermal and electric energy in many branches of industry and municipal management accounts for a drastic diminishing of natural resources (fossil fuels). Meanwhile, in numerous technical processes, a huge mass of wastes is produced. A segregated and converted combustible fraction of the wastes, with relatively high calorific value, may be used as a component of formed fuels. The utilization of the formed fuel components from segregated groups of waste in associated processes of co-combustion with conventional fuels causes significant savings resulting from partial replacement of fossil fuels, and reduction of environmental pollution resulting directly from the limitation of waste migration to the environment (soil, atmospheric air, surface and underground water). The realization of technological processes with the utilization of formed fuel in associated thermal systems should be qualified by technical criteria, which means that elementary processes as well as factors of sustainable development, from a global viewpoint, must not be disturbed. The utilization of post-process waste should be preceded by detailed technical, ecological and economic analyses. In order to optimize the mixing process of fuel components, a mathematical model of the forming process was created. The model is defined as a group of data structures which uniquely identify a real process and conversion of this data in algorithms based on a problem of linear programming. The paper also presents the optimization of parameters in the process of forming fuels using a modified simplex algorithm with a polynomial worktime. This model is a datum-point in the numerical modeling of real processes, allowing a precise determination of the optimal elementary composition of formed fuels components, with assumed constraints and decision variables of the task

  8. Developing cloud-based Business Process Management (BPM): a survey

    Science.gov (United States)

    Mercia; Gunawan, W.; Fajar, A. N.; Alianto, H.; Inayatulloh

    2018-03-01

    In today’s highly competitive business environment, modern enterprises are dealing difficulties to cut unnecessary costs, eliminate wastes and delivery huge benefits for the organization. Companies are increasingly turning to a more flexible IT environment to help them realize this goal. For this reason, the article applies cloud based Business Process Management (BPM) that enables to focus on modeling, monitoring and process management. Cloud based BPM consists of business processes, business information and IT resources, which help build real-time intelligence systems, based on business management and cloud technology. Cloud computing is a paradigm that involves procuring dynamically measurable resources over the internet as an IT resource service. Cloud based BPM service enables to address common problems faced by traditional BPM, especially in promoting flexibility, event-driven business process to exploit opportunities in the marketplace.

  9. Design of learner-centred constructivism based learning process

    OpenAIRE

    Schreurs, Jeanne; Al-Huneidi, Ahmad

    2012-01-01

    A Learner-centered learning is constructivism based and Competence directed. We define general competencies, domain competencies and specific course competencies. Constructivism based learning activities are based on constructivism theory. For each course module the intended learning level will be defined. A model is built for the design of a learner centered constructivism based and competency directed learning process. The application of it in two courses are presented. Constructivism ba...

  10. The quark-gluon model for particle production processes

    International Nuclear Information System (INIS)

    Volkovitskij, P.E.

    1983-01-01

    The quark-gluon model for hadronization of strings produced in soft and hard processes is suggested. The model is based on the distribution functions of valence quarks in hadrons which have correct Regge behaviour. The simplest case is discussed in which only the longitudinal degrees of freedom are taken into account

  11. Devil is in the details: Using logic models to investigate program process.

    Science.gov (United States)

    Peyton, David J; Scicchitano, Michael

    2017-12-01

    Theory-based logic models are commonly developed as part of requirements for grant funding. As a tool to communicate complex social programs, theory based logic models are an effective visual communication. However, after initial development, theory based logic models are often abandoned and remain in their initial form despite changes in the program process. This paper examines the potential benefits of committing time and resources to revising the initial theory driven logic model and developing detailed logic models that describe key activities to accurately reflect the program and assist in effective program management. The authors use a funded special education teacher preparation program to exemplify the utility of drill down logic models. The paper concludes with lessons learned from the iterative revision process and suggests how the process can lead to more flexible and calibrated program management. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. a Geometric Processing Workflow for Transforming Reality-Based 3d Models in Volumetric Meshes Suitable for Fea

    Science.gov (United States)

    Gonizzi Barsanti, S.; Guidi, G.

    2017-02-01

    Conservation of Cultural Heritage is a key issue and structural changes and damages can influence the mechanical behaviour of artefacts and buildings. The use of Finite Elements Methods (FEM) for mechanical analysis is largely used in modelling stress behaviour. The typical workflow involves the use of CAD 3D models made by Non-Uniform Rational B-splines (NURBS) surfaces, representing the ideal shape of the object to be simulated. Nowadays, 3D documentation of CH has been widely developed through reality-based approaches, but the models are not suitable for a direct use in FEA: the mesh has in fact to be converted to volumetric, and the density has to be reduced since the computational complexity of a FEA grows exponentially with the number of nodes. The focus of this paper is to present a new method aiming at generate the most accurate 3D representation of a real artefact from highly accurate 3D digital models derived from reality-based techniques, maintaining the accuracy of the high-resolution polygonal models in the solid ones. The approach proposed is based on a wise use of retopology procedures and a transformation of this model to a mathematical one made by NURBS surfaces suitable for being processed by volumetric meshers typically embedded in standard FEM packages. The strong simplification with little loss of consistency possible with the retopology step is used for maintaining as much coherence as possible between the original acquired mesh and the simplified model, creating in the meantime a topology that is more favourable for the automatic NURBS conversion.

  13. Process based modelling of soil organic carbon redistribution on landscape scale

    Science.gov (United States)

    Schindewolf, Marcus; Seher, Wiebke; Amorim, Amorim S. S.; Maeso, Daniel L.; Jürgen, Schmidt

    2014-05-01

    Recent studies have pointed out the great importance of erosion processes in global carbon cycling. Continuous erosion leads to a massive loss of top soils including the loss of organic carbon accumulated over long time in the soil humus fraction. Lal (2003) estimates that 20% of the organic carbon eroded with top soils is emitted into atmosphere, due to aggregate breakdown and carbon mineralization during transport by surface runoff. Furthermore soil erosion causes a progressive decrease of natural soil fertility, since cation exchange capacity is associated with organic colloids. As a consequence the ability of soils to accumulate organic carbon is reduced proportionately to the drop in soil productivity. The colluvial organic carbon might be protected from further degradation depending on the depth of the colluvial cover and local decomposing conditions. Some colluvial sites can act as long-term sinks for organic carbon. The erosional transport of organic carbon may have an effect on the global carbon budget, however, it is uncertain, whether erosion is a sink or a source for carbon in the atmosphere. Another part of eroded soils and organic carbon will enter surface water bodies and might be transported over long distances. These sediments might be deposited in the riparian zones of river networks. Erosional losses of organic carbon will not pass over into atmosphere for the most part. But soil erosion limits substantially the potential of soils to sequester atmospheric CO2 by generating humus. The present study refers to lateral carbon flux modelling on landscape scale using the process based EROSION 3D soil loss simulation model, using existing parameter values. The selective nature of soil erosion results in a preferentially transport of fine particles while less carbonic larger particles remain on site. Consequently organic carbon is enriched in the eroded sediment compared to the origin soil. For this reason it is essential that EROSION 3D provides the

  14. Weather-Driven Variation in Dengue Activity in Australia Examined Using a Process-Based Modeling Approach

    Science.gov (United States)

    Bannister-Tyrrell, Melanie; Williams, Craig; Ritchie, Scott A.; Rau, Gina; Lindesay, Janette; Mercer, Geoff; Harley, David

    2013-01-01

    The impact of weather variation on dengue transmission in Cairns, Australia, was determined by applying a process-based dengue simulation model (DENSiM) that incorporated local meteorologic, entomologic, and demographic data. Analysis showed that inter-annual weather variation is one of the significant determinants of dengue outbreak receptivity. Cross-correlation analyses showed that DENSiM simulated epidemics of similar relative magnitude and timing to those historically recorded in reported dengue cases in Cairns during 1991–2009, (r = 0.372, P < 0.01). The DENSiM model can now be used to study the potential impacts of future climate change on dengue transmission. Understanding the impact of climate variation on the geographic range, seasonality, and magnitude of dengue transmission will enhance development of adaptation strategies to minimize future disease burden in Australia. PMID:23166197

  15. The Probability Model of Expectation Disconfirmation Process

    Directory of Open Access Journals (Sweden)

    Hui-Hsin HUANG

    2015-06-01

    Full Text Available This paper proposes a probability model to explore the dynamic process of customer’s satisfaction. Bases on expectation disconfirmation theory, the satisfaction is constructed with customer’s expectation before buying behavior and the perceived performance after purchase. The experiment method is designed to measure expectation disconfirmation effects and we also use the collection data to estimate the overall satisfaction and model calibration. The results show good fitness between the model and the real data. This model has application for business marketing areas in order to manage relationship satisfaction.

  16. Construction Process Simulation and Safety Analysis Based on Building Information Model and 4D Technology

    Institute of Scientific and Technical Information of China (English)

    HU Zhenzhong; ZHANG Jianping; DENG Ziyin

    2008-01-01

    Time-dependent structure analysis theory has been proved to be more accurate and reliable com-pared to commonly used methods during construction. However, so far applications are limited to partial pe-riod and part of the structure because of immeasurable artificial intervention. Based on the building informa-tion model (BIM) and four-dimensional (4D) technology, this paper proposes an improves structure analysis method, which can generate structural geometry, resistance model, and loading conditions automatically by a close interlink of the schedule information, architectural model, and material properties. The method was applied to a safety analysis during a continuous and dynamic simulation of the entire construction process.The results show that the organic combination of the BIM, 4D technology, construction simulation, and safety analysis of time-dependent structures is feasible and practical. This research also lays a foundation for further researches on building lifecycle management by combining architectural design, structure analy-sis, and construction management.

  17. A Companion Model Approach to Modelling and Simulation of Industrial Processes

    International Nuclear Information System (INIS)

    Juslin, K.

    2005-09-01

    Modelling and simulation provides for huge possibilities if broadly taken up by engineers as a working method. However, when considering the launching of modelling and simulation tools in an engineering design project, they shall be easy to learn and use. Then, there is no time to write equations, to consult suppliers' experts, or to manually transfer data from one tool to another. The answer seems to be in the integration of easy to use and dependable simulation software with engineering tools. Accordingly, the modelling and simulation software shall accept as input such structured design information on industrial unit processes and their connections, as provided for by e.g. CAD software and product databases. The software technology, including required specification and communication standards, is already available. Internet based service repositories make it possible for equipment manufacturers to supply 'extended products', including such design data as needed by engineers engaged in process and automation integration. There is a market niche evolving for simulation service centres, operating in co-operation with project consultants, equipment manufacturers, process integrators, automation designers, plant operating personnel, and maintenance centres. The companion model approach for specification and solution of process simulation models, as presented herein, is developed from the above premises. The focus is on how to tackle real world processes, which from the modelling point of view are heterogeneous, dynamic, very stiff, very nonlinear and only piece vice continuous, without extensive manual interventions of human experts. An additional challenge, to solve the arising equations fast and reliable, is dealt with, as well. (orig.)

  18. A Teacher Competency Enhancement Model based on the Coaching Processes to Increase Mathematical Reasoning Abilities of Lower-Secondary Students

    Directory of Open Access Journals (Sweden)

    Uaychai Sukanalam

    2017-09-01

    Full Text Available This research study aimed to: 1 investigate problems and needs for the learning management that helps increase capacities of mathematics teachers at the lower-secondary level, 2 develop a teacher competency enhancement model based on the coaching processes to enhance mathematical reasoning abilities of lower-secondary students, 3 find out the educational supervisors’ opinions on the model designed. The samples of the study comprised 212 mathematics teachers at the lower-secondary level from 60 schools under jurisdiction of the Office of Secondary Educational Service Area 27, who were selected through the simple random sampling technique ; and 201 educational supervisors in charge of the mathematics learning strand from 42 educational service areas, who were selected through the purposive sampling technique. This study was conducted in the academic year 2015. The research instruments included: 1 a teacher competency enhancement manual that illustrated the steps and procedures for increasing the teacher’s capacities based on the coaching processes in order to enhance mathematical reasoning abilities of lower-secondary students, 2 a survey on problems and needs for the learning management to enhance capacities of mathematics teachers at the lower-secondary level, 3 A questionnaire concerning the educational supervisor’s opinion on the model designed. The statistics used included percentage, mean, and standard deviation. The study results showed that: 1. According to the study and analysis of basic data, problems and needs, it was found that the needs for increasing capacities of mathematics teachers at the lower-secondary level was overall at the high level. In terms of identifying behaviors as “mathematical competencies”, there were some problems associated with thinking and reasoning abilities of the teachers, and their needs in developing the learning management were at the highest level. To solve such problems, it is suggested that

  19. Technology for the product and process data base

    Science.gov (United States)

    Barnes, R. D.

    1984-01-01

    The computerized product and process data base is increasingly recognized to be the cornerstone component of an overall system aimed at the integrated automation of the industrial processes of a given company or enterprise. The technology needed to support these more effective computer integrated design and manufacturing methods, especially the concept of 3-D computer-sensible product definitions rather than engineering drawings, is not fully available and rationalized. Progress is being made, however, in bridging this technology gap with concentration on the modeling of sophisticated information and data structures, high-performance interactive user interfaces and comprehensive tools for managing the resulting computerized product definition and process data base.

  20. Integrated Process Modeling-A Process Validation Life Cycle Companion.

    Science.gov (United States)

    Zahel, Thomas; Hauer, Stefan; Mueller, Eric M; Murphy, Patrick; Abad, Sandra; Vasilieva, Elena; Maurer, Daniel; Brocard, Cécile; Reinisch, Daniela; Sagmeister, Patrick; Herwig, Christoph

    2017-10-17

    During the regulatory requested process validation of pharmaceutical manufacturing processes, companies aim to identify, control, and continuously monitor process variation and its impact on critical quality attributes (CQAs) of the final product. It is difficult to directly connect the impact of single process parameters (PPs) to final product CQAs, especially in biopharmaceutical process development and production, where multiple unit operations are stacked together and interact with each other. Therefore, we want to present the application of Monte Carlo (MC) simulation using an integrated process model (IPM) that enables estimation of process capability even in early stages of process validation. Once the IPM is established, its capability in risk and criticality assessment is furthermore demonstrated. IPMs can be used to enable holistic production control strategies that take interactions of process parameters of multiple unit operations into account. Moreover, IPMs can be trained with development data, refined with qualification runs, and maintained with routine manufacturing data which underlines the lifecycle concept. These applications will be shown by means of a process characterization study recently conducted at a world-leading contract manufacturing organization (CMO). The new IPM methodology therefore allows anticipation of out of specification (OOS) events, identify critical process parameters, and take risk-based decisions on counteractions that increase process robustness and decrease the likelihood of OOS events.

  1. Motivation and performance within a collaborative computer-based modeling task: Relations between student's achievement goal orientation, self-efficiacy, cognitive processing and achievement.

    NARCIS (Netherlands)

    Sins, Patrick H.M.; van Joolingen, Wouter; Savelsbergh, Elwin R.; van Hout-Wolters, Bernadette

    2008-01-01

    Purpose of the present study was to test a conceptual model of relations among achievement goal orientation, self-efficacy, cognitive processing, and achievement of students working within a particular collaborative task context. The task involved a collaborative computer-based modeling task. In

  2. Motivation and performance within a collaborative computer-based modeling task: Relations between students' achievement goal orientation, self-efficacy, cognitive processing and achievement

    NARCIS (Netherlands)

    Sins, P.H.M.; van Joolingen, W.R.; Savelsbergh, E.R.; van Hout-Wolters, B.H.A.M.

    2008-01-01

    Purpose of the present study was to test a conceptual model of relations among achievement goal orientation, self-efficacy, cognitive processing, and achievement of students working within a particular collaborative task context. The task involved a collaborative computer-based modeling task. In

  3. Modeling Dynamic Food Choice Processes to Understand Dietary Intervention Effects.

    Science.gov (United States)

    Marcum, Christopher Steven; Goldring, Megan R; McBride, Colleen M; Persky, Susan

    2018-02-17

    Meal construction is largely governed by nonconscious and habit-based processes that can be represented as a collection of in dividual, micro-level food choices that eventually give rise to a final plate. Despite this, dietary behavior intervention research rarely captures these micro-level food choice processes, instead measuring outcomes at aggregated levels. This is due in part to a dearth of analytic techniques to model these dynamic time-series events. The current article addresses this limitation by applying a generalization of the relational event framework to model micro-level food choice behavior following an educational intervention. Relational event modeling was used to model the food choices that 221 mothers made for their child following receipt of an information-based intervention. Participants were randomized to receive either (a) control information; (b) childhood obesity risk information; (c) childhood obesity risk information plus a personalized family history-based risk estimate for their child. Participants then made food choices for their child in a virtual reality-based food buffet simulation. Micro-level aspects of the built environment, such as the ordering of each food in the buffet, were influential. Other dynamic processes such as choice inertia also influenced food selection. Among participants receiving the strongest intervention condition, choice inertia decreased and the overall rate of food selection increased. Modeling food selection processes can elucidate the points at which interventions exert their influence. Researchers can leverage these findings to gain insight into nonconscious and uncontrollable aspects of food selection that influence dietary outcomes, which can ultimately improve the design of dietary interventions.

  4. Learning of Chemical Equilibrium through Modelling-Based Teaching

    Science.gov (United States)

    Maia, Poliana Flavia; Justi, Rosaria

    2009-01-01

    This paper presents and discusses students' learning process of chemical equilibrium from a modelling-based approach developed from the use of the "Model of Modelling" diagram. The investigation was conducted in a regular classroom (students 14-15 years old) and aimed at discussing how modelling-based teaching can contribute to students…

  5. Learning to maximize reward rate: a model based on semi-Markov decision processes.

    Science.gov (United States)

    Khodadadi, Arash; Fakhari, Pegah; Busemeyer, Jerome R

    2014-01-01

    WHEN ANIMALS HAVE TO MAKE A NUMBER OF DECISIONS DURING A LIMITED TIME INTERVAL, THEY FACE A FUNDAMENTAL PROBLEM: how much time they should spend on each decision in order to achieve the maximum possible total outcome. Deliberating more on one decision usually leads to more outcome but less time will remain for other decisions. In the framework of sequential sampling models, the question is how animals learn to set their decision threshold such that the total expected outcome achieved during a limited time is maximized. The aim of this paper is to provide a theoretical framework for answering this question. To this end, we consider an experimental design in which each trial can come from one of the several possible "conditions." A condition specifies the difficulty of the trial, the reward, the penalty and so on. We show that to maximize the expected reward during a limited time, the subject should set a separate value of decision threshold for each condition. We propose a model of learning the optimal value of decision thresholds based on the theory of semi-Markov decision processes (SMDP). In our model, the experimental environment is modeled as an SMDP with each "condition" being a "state" and the value of decision thresholds being the "actions" taken in those states. The problem of finding the optimal decision thresholds then is cast as the stochastic optimal control problem of taking actions in each state in the corresponding SMDP such that the average reward rate is maximized. Our model utilizes a biologically plausible learning algorithm to solve this problem. The simulation results show that at the beginning of learning the model choses high values of decision threshold which lead to sub-optimal performance. With experience, however, the model learns to lower the value of decision thresholds till finally it finds the optimal values.

  6. On some approaches to model reversible magnetization processes

    Science.gov (United States)

    Chwastek, K.; Baghel, A. P. S.; Sai Ram, B.; Borowik, B.; Daniel, L.; Kulkarni, S. V.

    2018-04-01

    This paper focuses on the problem of how reversible magnetization processes are taken into account in contemporary descriptions of hysteresis curves. For comparison, three versions of the phenomenological T(x) model based on hyperbolic tangent mapping are considered. Two of them are based on summing the output of the hysteresis operator with a linear or nonlinear mapping. The third description is inspired by the concept of the product Preisach model. Total susceptibility is modulated with a magnetization-dependent function. The models are verified using measurement data for grain-oriented electrical steel. The proposed third description represents minor loops most accurately.

  7. Process Analytical Technology for Advanced Process Control in Biologics Manufacturing with the Aid of Macroscopic Kinetic Modeling

    Directory of Open Access Journals (Sweden)

    Martin Kornecki

    2018-03-01

    Full Text Available Productivity improvements of mammalian cell culture in the production of recombinant proteins have been made by optimizing cell lines, media, and process operation. This led to enhanced titers and process robustness without increasing the cost of the upstream processing (USP; however, a downstream bottleneck remains. In terms of process control improvement, the process analytical technology (PAT initiative, initiated by the American Food and Drug Administration (FDA, aims to measure, analyze, monitor, and ultimately control all important attributes of a bioprocess. Especially, spectroscopic methods such as Raman or near-infrared spectroscopy enable one to meet these analytical requirements, preferably in-situ. In combination with chemometric techniques like partial least square (PLS or principal component analysis (PCA, it is possible to generate soft sensors, which estimate process variables based on process and measurement models for the enhanced control of bioprocesses. Macroscopic kinetic models can be used to simulate cell metabolism. These models are able to enhance the process understanding by predicting the dynamic of cells during cultivation. In this article, in-situ turbidity (transmission, 880 nm and ex-situ Raman spectroscopy (785 nm measurements are combined with an offline macroscopic Monod kinetic model in order to predict substrate concentrations. Experimental data of Chinese hamster ovary cultivations in bioreactors show a sufficiently linear correlation (R2 ≥ 0.97 between turbidity and total cell concentration. PLS regression of Raman spectra generates a prediction model, which was validated via offline viable cell concentration measurement (RMSE ≤ 13.82, R2 ≥ 0.92. Based on these measurements, the macroscopic Monod model can be used to determine different process attributes, e.g., glucose concentration. In consequence, it is possible to approximately calculate (R2 ≥ 0.96 glucose concentration based on online cell

  8. Process Analytical Technology for Advanced Process Control in Biologics Manufacturing with the Aid of Macroscopic Kinetic Modeling.

    Science.gov (United States)

    Kornecki, Martin; Strube, Jochen

    2018-03-16

    Productivity improvements of mammalian cell culture in the production of recombinant proteins have been made by optimizing cell lines, media, and process operation. This led to enhanced titers and process robustness without increasing the cost of the upstream processing (USP); however, a downstream bottleneck remains. In terms of process control improvement, the process analytical technology (PAT) initiative, initiated by the American Food and Drug Administration (FDA), aims to measure, analyze, monitor, and ultimately control all important attributes of a bioprocess. Especially, spectroscopic methods such as Raman or near-infrared spectroscopy enable one to meet these analytical requirements, preferably in-situ. In combination with chemometric techniques like partial least square (PLS) or principal component analysis (PCA), it is possible to generate soft sensors, which estimate process variables based on process and measurement models for the enhanced control of bioprocesses. Macroscopic kinetic models can be used to simulate cell metabolism. These models are able to enhance the process understanding by predicting the dynamic of cells during cultivation. In this article, in-situ turbidity (transmission, 880 nm) and ex-situ Raman spectroscopy (785 nm) measurements are combined with an offline macroscopic Monod kinetic model in order to predict substrate concentrations. Experimental data of Chinese hamster ovary cultivations in bioreactors show a sufficiently linear correlation (R² ≥ 0.97) between turbidity and total cell concentration. PLS regression of Raman spectra generates a prediction model, which was validated via offline viable cell concentration measurement (RMSE ≤ 13.82, R² ≥ 0.92). Based on these measurements, the macroscopic Monod model can be used to determine different process attributes, e.g., glucose concentration. In consequence, it is possible to approximately calculate (R² ≥ 0.96) glucose concentration based on online cell

  9. Dispersive processes in models of regional radionuclide migration. Technical memorandum

    International Nuclear Information System (INIS)

    Evenson, D.E.; Dettinger, M.D.

    1980-05-01

    Three broad areas of concern in the development of aquifer scale transport models will be local scale diffusion and dispersion processes, regional scale dispersion processes, and numerical problems associated with the advection-dispersion equation. Local scale dispersion processes are fairly well understood and accessible to observation. These processes will generally be dominated in large scale systems by regional processes, or macro-dispersion. Macro-dispersion is primarily the result of large scale heterogeneities in aquifer properties. In addition, the effects of many modeling approximations are often included in the process. Because difficulties arise in parameterization of this large scale phenomenon, parameterization should be based on field measurements made at the same scale as the transport process of interest or else partially circumvented through the application of a probabilistic advection model. Other problems associated with numerical transport models include difficulties with conservation of mass, stability, numerical dissipation, overshoot, flexibility, and efficiency. We recommend the random-walk model formulation for Lawrence Livermore Laboratory's purposes as the most flexible, accurate and relatively efficient modeling approach that overcomes these difficulties

  10. Mathematical modelling of the process of quality control of construction products

    Directory of Open Access Journals (Sweden)

    Pogorelov Vadim

    2017-01-01

    Full Text Available The study presents the results of years of research in the field of quality management of industrial production construction production, based on mathematical modelling techniques, process and results of implementing the developed programme of monitoring and quality control in the production process of the enterprise. The aim of this work is the presentation of scientific community of the practical results of mathematical modelling in application programs. In the course of the research addressed the description of the applied mathematical models, views, practical results of its application in the applied field to assess quality control. The authors used this mathematical model in practice. The article presents the results of applying this model. The authors developed the experimental software management and quality assessment by using mathematical modeling methods. The authors continue research in this direction to improve the diagnostic systems and quality management systems based on mathematical modeling methods prognostic and diagnostic processes.

  11. Implementation of the Business Process Modelling Notation (BPMN) in the modelling of anatomic pathology processes.

    Science.gov (United States)

    Rojo, Marcial García; Rolón, Elvira; Calahorra, Luis; García, Felix Oscar; Sánchez, Rosario Paloma; Ruiz, Francisco; Ballester, Nieves; Armenteros, María; Rodríguez, Teresa; Espartero, Rafael Martín

    2008-07-15

    Process orientation is one of the essential elements of quality management systems, including those in use in healthcare. Business processes in hospitals are very complex and variable. BPMN (Business Process Modelling Notation) is a user-oriented language specifically designed for the modelling of business (organizational) processes. Previous experiences of the use of this notation in the processes modelling within the Pathology in Spain or another country are not known. We present our experience in the elaboration of the conceptual models of Pathology processes, as part of a global programmed surgical patient process, using BPMN. With the objective of analyzing the use of BPMN notation in real cases, a multidisciplinary work group was created, including software engineers from the Dep. of Technologies and Information Systems from the University of Castilla-La Mancha and health professionals and administrative staff from the Hospital General de Ciudad Real. The work in collaboration was carried out in six phases: informative meetings, intensive training, process selection, definition of the work method, process describing by hospital experts, and process modelling. The modelling of the processes of Anatomic Pathology is presented using BPMN. The presented subprocesses are those corresponding to the surgical pathology examination of the samples coming from operating theatre, including the planning and realization of frozen studies. The modelling of Anatomic Pathology subprocesses has allowed the creation of an understandable graphical model, where management and improvements are more easily implemented by health professionals.

  12. Structural assessment of aerospace components using image processing algorithms and Finite Element models

    DEFF Research Database (Denmark)

    Stamatelos, Dimtrios; Kappatos, Vassilios

    2017-01-01

    Purpose – This paper presents the development of an advanced structural assessment approach for aerospace components (metallic and composites). This work focuses on developing an automatic image processing methodology based on Non Destructive Testing (NDT) data and numerical models, for predicting...... the residual strength of these components. Design/methodology/approach – An image processing algorithm, based on the threshold method, has been developed to process and quantify the geometric characteristics of damages. Then, a parametric Finite Element (FE) model of the damaged component is developed based...... on the inputs acquired from the image processing algorithm. The analysis of the metallic structures is employing the Extended FE Method (XFEM), while for the composite structures the Cohesive Zone Model (CZM) technique with Progressive Damage Modelling (PDM) is used. Findings – The numerical analyses...

  13. modeling grinding modeling grinding processes as micro processes

    African Journals Online (AJOL)

    eobe

    industrial precision grinding processes are cylindrical, center less and ... Several model shave been proposed and used to study grinding ..... grinding force for the two cases were 9.07237N/mm ..... International Journal of Machine Tools &.

  14. A PROCESS-BASED APPROACH TO KNOWLEDGE MANAGEMENT

    OpenAIRE

    Kovačić, Andrej; Bosilj Vukšić, Vesna; Lončar, Anita

    2006-01-01

    This paper analyses the relationship between business process modelling, knowledge management and information systems development projects. The paper’s main objective is to present business rules as the encoded knowledge of corporate business practices. Further, it introduces a rule-based business activity meta-model as a repository in which business knowledge can be captured and traced from their origin in the business environment through to their implementation in information systems. The c...

  15. Patterns for a log-based strengthening of declarative compliance models

    NARCIS (Netherlands)

    Schunselaar, Dennis M.M.; Maggi, Fabrizio M.; Sidorova, Natalia

    2012-01-01

    LTL-based declarative process models are very effective when modelling loosely structured processes or working in environments with a lot of variability. A process model is represented by a set of constraints that must be satisfied during the process execution. An important application of such

  16. EVALUATING THE REGIONAL PREDICTIVE CAPACITY OF A PROCESS-BASED MERCURY EXPOSURE MODEL (R-MCM) FOR LAKES ACROSS VERMONT AND NEW HAMPSHIRE, USA

    Science.gov (United States)

    Regulatory agencies are confronted with a daunting task of developing fish consumption advisories for a large number of lakes and rivers with little resources. A feasible mechanism to develop region-wide fish advisories is by using a process-based mathematical model. One model of...

  17. Cutting force model for high speed machining process

    International Nuclear Information System (INIS)

    Haber, R. E.; Jimenez, J. E.; Jimenez, A.; Lopez-Coronado, J.

    2004-01-01

    This paper presents cutting force-based models able to describe a high speed machining process. The model considers the cutting force as output variable, essential for the physical processes that are taking place in high speed machining. Moreover, this paper shows the mathematical development to derive the integral-differential equations, and the algorithms implemented in MATLAB to predict the cutting force in real time MATLAB is a software tool for doing numerical computations with matrices and vectors. It can also display information graphically and includes many toolboxes for several research and applications areas. Two end mill shapes are considered (i. e. cylindrical and ball end mill) for real-time implementation of the developed algorithms. the developed models are validated in slot milling operations. The results corroborate the importance of the cutting force variable for predicting tool wear in high speed machining operations. The developed models are the starting point for future work related with vibration analysis, process stability and dimensional surface finish in high speed machining processes. (Author) 19 refs

  18. Modelling of tetrahydrofuran promoted gas hydrate systems for carbon dioxide capture processes

    DEFF Research Database (Denmark)

    Herslund, Peter Jørgensen; Thomsen, Kaj; Abildskov, Jens

    2014-01-01

    A thermodynamic study of a novel gas hydrate based CO2 capture process is presented.•Model predicts this process unsuitable for CO2 capture from power station flue gases. A thermodynamic modelling study of both fluid phase behaviour and hydrate phase behaviour is presented for the quaternary system...... of water, tetrahydrofuran, carbon dioxide and nitrogen. The applied model incorporates the Cubic-Plus-Association (CPA) equation of state for the fluid phase description and the van der Waals-Platteeuw hydrate model for the solid (hydrate) phase. Six binary pairs are studied for their fluid phase behaviour...... accurate descriptions of both fluid- and hydrate phase equilibria in the studied system and its subsystems. The developed model is applied to simulate two simplified, gas hydrate-based processes for post-combustion carbon dioxide capture from power station flue gases. The first process, an unpromoted...

  19. Model-based safety analysis of a control system using Simulink and Simscape extended models

    Directory of Open Access Journals (Sweden)

    Shao Nian

    2017-01-01

    Full Text Available The aircraft or system safety assessment process is an integral part of the overall aircraft development cycle. It is usually characterized by a very high timely and financial effort and can become a critical design driver in certain cases. Therefore, an increasing demand of effective methods to assist the safety assessment process arises within the aerospace community. One approach is the utilization of model-based technology, which is already well-established in the system development, for safety assessment purposes. This paper mainly describes a new tool for Model-Based Safety Analysis. A formal model for an example system is generated and enriched with extended models. Then, system safety analyses are performed on the model with the assistance of automation tools and compared to the results of a manual analysis. The objective of this paper is to improve the increasingly complex aircraft systems development process. This paper develops a new model-based analysis tool in Simulink/Simscape environment.

  20. Fit Gap Analysis – The Role of Business Process Reference Models

    Directory of Open Access Journals (Sweden)

    Dejan Pajk

    2013-12-01

    Full Text Available Enterprise resource planning (ERP systems support solutions for standard business processes such as financial, sales, procurement and warehouse. In order to improve the understandability and efficiency of their implementation, ERP vendors have introduced reference models that describe the processes and underlying structure of an ERP system. To select and successfully implement an ERP system, the capabilities of that system have to be compared with a company’s business needs. Based on a comparison, all of the fits and gaps must be identified and further analysed. This step usually forms part of ERP implementation methodologies and is called fit gap analysis. The paper theoretically overviews methods for applying reference models and describes fit gap analysis processes in detail. The paper’s first contribution is its presentation of a fit gap analysis using standard business process modelling notation. The second contribution is the demonstration of a process-based comparison approach between a supply chain process and an ERP system process reference model. In addition to its theoretical contributions, the results can also be practically applied to projects involving the selection and implementation of ERP systems.

  1. Integrated Site Model Process Model Report

    International Nuclear Information System (INIS)

    Booth, T.

    2000-01-01

    The Integrated Site Model (ISM) provides a framework for discussing the geologic features and properties of Yucca Mountain, which is being evaluated as a potential site for a geologic repository for the disposal of nuclear waste. The ISM is important to the evaluation of the site because it provides 3-D portrayals of site geologic, rock property, and mineralogic characteristics and their spatial variabilities. The ISM is not a single discrete model; rather, it is a set of static representations that provide three-dimensional (3-D), computer representations of site geology, selected hydrologic and rock properties, and mineralogic-characteristics data. These representations are manifested in three separate model components of the ISM: the Geologic Framework Model (GFM), the Rock Properties Model (RPM), and the Mineralogic Model (MM). The GFM provides a representation of the 3-D stratigraphy and geologic structure. Based on the framework provided by the GFM, the RPM and MM provide spatial simulations of the rock and hydrologic properties, and mineralogy, respectively. Functional summaries of the component models and their respective output are provided in Section 1.4. Each of the component models of the ISM considers different specific aspects of the site geologic setting. Each model was developed using unique methodologies and inputs, and the determination of the modeled units for each of the components is dependent on the requirements of that component. Therefore, while the ISM represents the integration of the rock properties and mineralogy into a geologic framework, the discussion of ISM construction and results is most appropriately presented in terms of the three separate components. This Process Model Report (PMR) summarizes the individual component models of the ISM (the GFM, RPM, and MM) and describes how the three components are constructed and combined to form the ISM

  2. Dual processing model of medical decision-making

    Science.gov (United States)

    2012-01-01

    Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. Methods We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. Results We show that physician’s beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker’s threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. Conclusions We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical

  3. Dual processing model of medical decision-making.

    Science.gov (United States)

    Djulbegovic, Benjamin; Hozo, Iztok; Beckstead, Jason; Tsalatsanis, Athanasios; Pauker, Stephen G

    2012-09-03

    Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. We show that physician's beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker's threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical decision-making field, which is still to the

  4. CHIRP-Like Signals: Estimation, Detection and Processing A Sequential Model-Based Approach

    Energy Technology Data Exchange (ETDEWEB)

    Candy, J. V. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-08-04

    Chirp signals have evolved primarily from radar/sonar signal processing applications specifically attempting to estimate the location of a target in surveillance/tracking volume. The chirp, which is essentially a sinusoidal signal whose phase changes instantaneously at each time sample, has an interesting property in that its correlation approximates an impulse function. It is well-known that a matched-filter detector in radar/sonar estimates the target range by cross-correlating a replicant of the transmitted chirp with the measurement data reflected from the target back to the radar/sonar receiver yielding a maximum peak corresponding to the echo time and therefore enabling the desired range estimate. In this application, we perform the same operation as a radar or sonar system, that is, we transmit a “chirp-like pulse” into the target medium and attempt to first detect its presence and second estimate its location or range. Our problem is complicated by the presence of disturbance signals from surrounding broadcast stations as well as extraneous sources of interference in our frequency bands and of course the ever present random noise from instrumentation. First, we discuss the chirp signal itself and illustrate its inherent properties and then develop a model-based processing scheme enabling both the detection and estimation of the signal from noisy measurement data.

  5. IT vendor selection model by using structural equation model & analytical hierarchy process

    Science.gov (United States)

    Maitra, Sarit; Dominic, P. D. D.

    2012-11-01

    Selecting and evaluating the right vendors is imperative for an organization's global marketplace competitiveness. Improper selection and evaluation of potential vendors can dwarf an organization's supply chain performance. Numerous studies have demonstrated that firms consider multiple criteria when selecting key vendors. This research intends to develop a new hybrid model for vendor selection process with better decision making. The new proposed model provides a suitable tool for assisting decision makers and managers to make the right decisions and select the most suitable vendor. This paper proposes a Hybrid model based on Structural Equation Model (SEM) and Analytical Hierarchy Process (AHP) for long-term strategic vendor selection problems. The five steps framework of the model has been designed after the thorough literature study. The proposed hybrid model will be applied using a real life case study to assess its effectiveness. In addition, What-if analysis technique will be used for model validation purpose.

  6. Firm Based Trade Models and Turkish Economy

    Directory of Open Access Journals (Sweden)

    Nilüfer ARGIN

    2015-12-01

    Full Text Available Among all international trade models, only The Firm Based Trade Models explains firm’s action and behavior in the world trade. The Firm Based Trade Models focuses on the trade behavior of individual firms that actually make intra industry trade. Firm Based Trade Models can explain globalization process truly. These approaches include multinational cooperation, supply chain and outsourcing also. Our paper aims to explain and analyze Turkish export with Firm Based Trade Models’ context. We use UNCTAD data on exports by SITC Rev 3 categorization to explain total export and 255 products and calculate intensive-extensive margins of Turkish firms.

  7. Process-based modeling of silicate mineral weathering responses to increasing atmospheric CO2 and climate change

    Science.gov (United States)

    Banwart, Steven A.; Berg, Astrid; Beerling, David J.

    2009-12-01

    A mathematical model describes silicate mineral weathering processes in modern soils located in the boreal coniferous region of northern Europe. The process model results demonstrate a stabilizing biological feedback mechanism between atmospheric CO2 levels and silicate weathering rates as is generally postulated for atmospheric evolution. The process model feedback response agrees within a factor of 2 of that calculated by a weathering feedback function of the type generally employed in global geochemical carbon cycle models of the Earth's Phanerozoic CO2 history. Sensitivity analysis of parameter values in the process model provides insight into the key mechanisms that influence the strength of the biological feedback to weathering. First, the process model accounts for the alkalinity released by weathering, whereby its acceleration stabilizes pH at values that are higher than expected. Although the process model yields faster weathering with increasing temperature, because of activation energy effects on mineral dissolution kinetics at warmer temperature, the mineral dissolution rate laws utilized in the process model also result in lower dissolution rates at higher pH values. Hence, as dissolution rates increase under warmer conditions, more alkalinity is released by the weathering reaction, helping maintain higher pH values thus stabilizing the weathering rate. Second, the process model yields a relatively low sensitivity of soil pH to increasing plant productivity. This is due to more rapid decomposition of dissolved organic carbon (DOC) under warmer conditions. Because DOC fluxes strongly influence the soil water proton balance and pH, this increased decomposition rate dampens the feedback between productivity and weathering. The process model is most sensitive to parameters reflecting soil structure; depth, porosity, and water content. This suggests that the role of biota to influence these characteristics of the weathering profile is as important, if not

  8. The impact of design-based modeling instruction on seventh graders' spatial abilities and model-based argumentation

    Science.gov (United States)

    McConnell, William J.

    models to better assist them in scientific argumentation over paper drawing models. In fact, when given a choice, students rarely used paper drawing to assist in argument. There was also a difference in model utility between the two different model types. Participants explicitly used 3D printed models to complete gestural modeling, while participants rarely looked at 2D models when involved in gestural modeling. This study's findings added to current theory dealing with the varied spatial challenges involved in different modes of expressed models. This study found that depth, symmetry and the manipulation of perspectives are typically spatial challenges students will attend to using CAD while they will typically ignore them when drawing using paper and pencil. This study also revealed a major difference in model-based argument in a design-based instruction context as opposed to model-based argument in a typical science classroom context. In the context of design-based instruction, data revealed that design process is an important part of model-based argument. Due to the importance of design process in model-based argumentation in this context, trusted methods of argument analysis, like the coding system of the IASCA, was found lacking in many respects. Limitations and recommendations for further research were also presented.

  9. Prediction of temperature and HAZ in thermal-based processes with Gaussian heat source by a hybrid GA-ANN model

    Science.gov (United States)

    Fazli Shahri, Hamid Reza; Mahdavinejad, Ramezanali

    2018-02-01

    Thermal-based processes with Gaussian heat source often produce excessive temperature which can impose thermally-affected layers in specimens. Therefore, the temperature distribution and Heat Affected Zone (HAZ) of materials are two critical factors which are influenced by different process parameters. Measurement of the HAZ thickness and temperature distribution within the processes are not only difficult but also expensive. This research aims at finding a valuable knowledge on these factors by prediction of the process through a novel combinatory model. In this study, an integrated Artificial Neural Network (ANN) and genetic algorithm (GA) was used to predict the HAZ and temperature distribution of the specimens. To end this, a series of full factorial design of experiments were conducted by applying a Gaussian heat flux on Ti-6Al-4 V at first, then the temperature of the specimen was measured by Infrared thermography. The HAZ width of each sample was investigated through measuring the microhardness. Secondly, the experimental data was used to create a GA-ANN model. The efficiency of GA in design and optimization of the architecture of ANN was investigated. The GA was used to determine the optimal number of neurons in hidden layer, learning rate and momentum coefficient of both output and hidden layers of ANN. Finally, the reliability of models was assessed according to the experimental results and statistical indicators. The results demonstrated that the combinatory model predicted the HAZ and temperature more effective than a trial-and-error ANN model.

  10. Short review of runoff and erosion physically based models

    Directory of Open Access Journals (Sweden)

    Gabrić Ognjen

    2015-01-01

    Full Text Available Processes of runoff and erosion are one of the main research subjects in hydrological science. Based on the field and laboratory measurements, and analogous with development of computational techniques, runoff and erosion models based on equations which describe the physics of the process are also developed. Several models of runoff and erosion which describes entire process of genesis and sediment transport on the catchment are described and compared.

  11. Modeling of column apparatus processes

    CERN Document Server

    Boyadjiev, Christo; Boyadjiev, Boyan; Popova-Krumova, Petya

    2016-01-01

    This book presents a new approach for the modeling of chemical and interphase mass transfer processes in industrial column apparatuses, using convection-diffusion and average-concentration models. The convection-diffusion type models are used for a qualitative analysis of the processes and to assess the main, small and slight physical effects, and then reject the slight effects. As a result, the process mechanism can be identified. It also introduces average concentration models for quantitative analysis, which use the average values of the velocity and concentration over the cross-sectional area of the column. The new models are used to analyze different processes (simple and complex chemical reactions, absorption, adsorption and catalytic reactions), and make it possible to model the processes of gas purification with sulfur dioxide, which form the basis of several patents.

  12. Investigating the Process of Process Modeling with Eye Movement Analysis

    OpenAIRE

    Pinggera, Jakob; Furtner, Marco; Martini, Markus; Sachse, Pierre; Reiter, Katharina; Zugal, Stefan; Weber, Barbara

    2015-01-01

    Research on quality issues of business process models has recently begun to explore the process of creating process models by analyzing the modeler's interactions with the modeling environment. In this paper we aim to complement previous insights on the modeler's modeling behavior with data gathered by tracking the modeler's eye movements when engaged in the act of modeling. We present preliminary results and outline directions for future research to triangulate toward a more comprehensive un...

  13. The avalanche process of the multilinear fiber bundles model

    International Nuclear Information System (INIS)

    Hao, Da-Peng; Tang, Gang; Xun, Zhi-Peng; Xia, Hui; Han, Kui

    2012-01-01

    In order to describe the smooth nonlinear constitutive behavior in the process of fracture of ductile micromechanics structures, the multilinear fiber bundle model was constructed, based on the bilinear fiber bundle model. In the multilinear fiber bundle model, the Young modulus of a fiber is assumed to decay K max times before the final failure occurs. For the large K max region, this model can describe the smooth nonlinear constitutive behavior well. By means of analytical approximation and numerical simulation, we show that the two critical parameters, i.e. the decay ratio of the Young modulus and the maximum number of decays, have substantial effects on the failure process of the bundle. From a macroscopic view, the model can provide various shapes of constitutive curves, which represent diverse kinds of tensile fracture processes. However, at the microscopic scale, the statistical properties of the model are in accord with the classical fiber bundle model. (paper)

  14. Optimization of Power Consumption for Centrifugation Process Based on Attenuation Measurements

    Science.gov (United States)

    Salim, M. S.; Abd Malek, M. F.; Sabri, Naseer; Omar, M. Iqbal bin; Mohamed, Latifah; Juni, K. M.

    2013-04-01

    The main objective of this research is to produce a mathematical model that allows decreasing the electrical power consumption of centrifugation process based on attenuation measurements. The centrifugation time for desired separation efficiency may be measured to determine the power consumed of laboratory centrifuge device. The power consumption is one of several parameters that affect the system reliability and productivity. Attenuation measurements of wave propagated through blood sample during centrifugation process were used indirectly to measure the power consumption of device. A mathematical model for power consumption was derived and used to modify the speed profile of centrifuge controller. The power consumption model derived based on attenuation measurements has successfully save the power consumption of centrifugation process keeping high separation efficiency. 18kW.h monthly for 100 daily time device operation had been saved using the proposed model.

  15. Optimization of Power Consumption for Centrifugation Process Based on Attenuation Measurements

    International Nuclear Information System (INIS)

    Salim, M S; Iqbal bin Omar, M; Malek, M F Abd; Mohamed, Latifah; Sabri, Naseer; Juni, K M

    2013-01-01

    The main objective of this research is to produce a mathematical model that allows decreasing the electrical power consumption of centrifugation process based on attenuation measurements. The centrifugation time for desired separation efficiency may be measured to determine the power consumed of laboratory centrifuge device. The power consumption is one of several parameters that affect the system reliability and productivity. Attenuation measurements of wave propagated through blood sample during centrifugation process were used indirectly to measure the power consumption of device. A mathematical model for power consumption was derived and used to modify the speed profile of centrifuge controller. The power consumption model derived based on attenuation measurements has successfully save the power consumption of centrifugation process keeping high separation efficiency. 18kW.h monthly for 100 daily time device operation had been saved using the proposed model.

  16. What makes process models understandable?

    NARCIS (Netherlands)

    Mendling, J.; Reijers, H.A.; Cardoso, J.; Alonso, G.; Dadam, P.; Rosemann, M.

    2007-01-01

    Despite that formal and informal quality aspects are of significant importance to business process modeling, there is only little empirical work reported on process model quality and its impact factors. In this paper we investigate understandability as a proxy for quality of process models and focus

  17. Verification and completion of a soil data base for process based erosion model applications in Mato Grosso/Brazil

    Science.gov (United States)

    Schindewolf, Marcus; Schultze, Nico; Schönke, Daniela; Amorim, Ricardo S. S.; Schmidt, Jürgen

    2014-05-01

    The study area of central Mato Grosso is subjected to severe soil erosion. Continuous erosion leads to massive losses of top soil and related organic carbon. Consequently agricultural soil soils suffer a drop in soil fertility which only can be balanced by mineral fertilization. In order to control soil degradation and organic carbon losses of Mato Grosso cropland soils a process based soil loss and deposition model is used. Applying the model it will be possible to: - identify the main areas affected by soil erosion or deposition in different scales under present and future climate and socio-economic conditions - estimate the related nutrient and organic carbon losses/yields - figure out site-related causes of soil mobilization/deposition - locate sediment and sediment related nutrient and organic matter pass over points into surface water bodies - estimate the impacts of climate and land use changes on the losses of top soil, sediment bound nutrients and organic carbon. Model input parameters include digital elevation data, precipitation characteristics and standard soil properties as particle size distribution, total organic carbon (TOC) and bulk density. The effects of different types of land use and agricultural management practices are accounted for by varying site-specific parameters predominantly related to soil surface properties such as erosional resistance, hydraulic roughness and percentage ground cover. In this context the existing EROSION 3D soil parameter data base deducted from large scale rainfall simulations in Germany is verified for application in the study area, using small scale disc type rainfall simulator with an additional runoff reflux approach. Thus it's possible to enlarge virtual plot length up to at least 10 m. Experimental plots are located in Cuiabá region of central Mato Grosso in order to cover the most relevant land use variants and tillage practices in the region. Results show that derived model parameters are highly influenced

  18. Licensing process for safety-critical software-based systems

    Energy Technology Data Exchange (ETDEWEB)

    Haapanen, P. [VTT Automation, Espoo (Finland); Korhonen, J. [VTT Electronics, Espoo (Finland); Pulkkinen, U. [VTT Automation, Espoo (Finland)

    2000-12-01

    System vendors nowadays propose software-based technology even for the most critical safety functions in nuclear power plants. Due to the nature of software faults and the way they cause system failures new methods are needed for the safety and reliability evaluation of these systems. In the research project 'Programmable automation systems in nuclear power plants (OHA)', financed together by the Radiation and Nuclear Safety Authority (STUK), the Ministry of Trade and Industry (KTM) and the Technical Research Centre of Finland (VTT), various safety assessment methods and tools for software based systems are developed and evaluated. As a part of the OHA-work a reference model for the licensing process for software-based safety automation systems is defined. The licensing process is defined as the set of interrelated activities whose purpose is to produce and assess evidence concerning the safety and reliability of the system/application to be licensed and to make the decision about the granting the construction and operation permissions based on this evidence. The parties of the licensing process are the authority, the licensee (the utility company), system vendors and their subcontractors and possible external independent assessors. The responsibility about the production of the evidence in first place lies at the licensee who in most cases rests heavily on the vendor expertise. The evaluation and gauging of the evidence is carried out by the authority (possibly using external experts), who also can acquire additional evidence by using their own (independent) methods and tools. Central issue in the licensing process is to combine the quality evidence about the system development process with the information acquired through tests, analyses and operational experience. The purpose of the licensing process described in this report is to act as a reference model both for the authority and the licensee when planning the licensing of individual applications

  19. Licensing process for safety-critical software-based systems

    International Nuclear Information System (INIS)

    Haapanen, P.; Korhonen, J.; Pulkkinen, U.

    2000-12-01

    System vendors nowadays propose software-based technology even for the most critical safety functions in nuclear power plants. Due to the nature of software faults and the way they cause system failures new methods are needed for the safety and reliability evaluation of these systems. In the research project 'Programmable automation systems in nuclear power plants (OHA)', financed together by the Radiation and Nuclear Safety Authority (STUK), the Ministry of Trade and Industry (KTM) and the Technical Research Centre of Finland (VTT), various safety assessment methods and tools for software based systems are developed and evaluated. As a part of the OHA-work a reference model for the licensing process for software-based safety automation systems is defined. The licensing process is defined as the set of interrelated activities whose purpose is to produce and assess evidence concerning the safety and reliability of the system/application to be licensed and to make the decision about the granting the construction and operation permissions based on this evidence. The parties of the licensing process are the authority, the licensee (the utility company), system vendors and their subcontractors and possible external independent assessors. The responsibility about the production of the evidence in first place lies at the licensee who in most cases rests heavily on the vendor expertise. The evaluation and gauging of the evidence is carried out by the authority (possibly using external experts), who also can acquire additional evidence by using their own (independent) methods and tools. Central issue in the licensing process is to combine the quality evidence about the system development process with the information acquired through tests, analyses and operational experience. The purpose of the licensing process described in this report is to act as a reference model both for the authority and the licensee when planning the licensing of individual applications. Many of the

  20. Numerical Simulation of a Grinding Process Model for the Spatial Work-pieces: Development of Modeling Techniques

    Directory of Open Access Journals (Sweden)

    S. A. Voronov

    2015-01-01

    Full Text Available The article presents a literature review in simulation of grinding processes. It takes into consideration the statistical, energy based, and imitation approaches to simulation of grinding forces. Main stages of interaction between abrasive grains and machined surface are shown. The article describes main approaches to the geometry modeling of forming new surfaces when grinding. The review of approaches to the chip and pile up effect numerical modeling is shown. Advantages and disadvantages of grain-to-surface interaction by means of finite element method and molecular dynamics method are considered. The article points out that it is necessary to take into consideration the system dynamics and its effect on the finished surface. Structure of the complex imitation model of grinding process dynamics for flexible work-pieces with spatial surface geometry is proposed from the literature review. The proposed model of spatial grinding includes the model of work-piece dynamics, model of grinding wheel dynamics, phenomenological model of grinding forces based on 3D geometry modeling algorithm. Model gives the following results for spatial grinding process: vibration of machining part and grinding wheel, machined surface geometry, static deflection of the surface and grinding forces under various cutting conditions.

  1. Modeling the Object-Oriented Software Process: OPEN and the Unified Process

    NARCIS (Netherlands)

    van den Berg, Klaas; Aksit, Mehmet; van den Broek, P.M.

    A short introduction to software process modeling is presented, particularly object-oriented modeling. Two major industrial process models are discussed: the OPEN model and the Unified Process model. In more detail, the quality assurance in the Unified Process tool (formally called Objectory) is

  2. Fuzzy model for Laser Assisted Bending Process

    Directory of Open Access Journals (Sweden)

    Giannini Oliviero

    2016-01-01

    Full Text Available In the present study, a fuzzy model was developed to predict the residual bending in a conventional metal bending process assisted by a high power diode laser. The study was focused on AA6082T6 aluminium thin sheets. In most dynamic sheet metal forming operations, the highly nonlinear deformation processes cause large amounts of elastic strain energy stored in the formed material. The novel hybrid forming process was thus aimed at inducing the local heating of the mechanically bent workpiece in order to decrease or eliminate the related springback phenomena. In particular, the influence on the extent of springback phenomena of laser process parameters such as source power, scan speed and starting elastic deformation of mechanically bent sheets, was experimentally assessed. Consistent trends in experimental response according to operational parameters were found. Accordingly, 3D process maps of the extent of the springback phenomena according to operational parameters were constructed. The effect of the inherent uncertainties on the predicted residual bending caused by the approximation in the model parameters was evaluated. In particular, a fuzzy-logic based approach was used to describe the model uncertainties and the transformation method was applied to propagate their effect on the residual bending.

  3. An explicit solution of the mathematical model for osmotic desalination process

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Do Yeon; Gu, Boram; Yang, Dae Ryook [Korea University, Seoul (Korea, Republic of)

    2013-09-15

    Membrane processes such as reverse osmosis and forward osmosis for seawater desalination have gained attention in recent years. Mathematical models have been used to interpret the mechanism of membrane processes. The membr