A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE PAGES

Dai, Heng; Ye, Ming; Walker, Anthony P.; ...

2017-03-28

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Heng; Ye, Ming; Walker, Anthony P.

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

A Model of the Base Civil Engineering Work Request/Work Order Processing System.

DTIC Science & Technology

1979-09-01

changes to the work order processing system. This research identifies the variables that significantly affect the accomplishment time and proposes a... order processing system and its behavior with respect to work order processing time. A conceptual model was developed to describe the work request...work order processing system as a stochastic queueing system in which the processing times and the various distributions are treated as random variables

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

ERIC Educational Resources Information Center

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…

The (Mathematical) Modeling Process in Biosciences.

PubMed

Torres, Nestor V; Santos, Guido

2015-01-01

In this communication, we introduce a general framework and discussion on the role of models and the modeling process in the field of biosciences. The objective is to sum up the common procedures during the formalization and analysis of a biological problem from the perspective of Systems Biology, which approaches the study of biological systems as a whole. We begin by presenting the definitions of (biological) system and model. Particular attention is given to the meaning of mathematical model within the context of biology. Then, we present the process of modeling and analysis of biological systems. Three stages are described in detail: conceptualization of the biological system into a model, mathematical formalization of the previous conceptual model and optimization and system management derived from the analysis of the mathematical model. All along this work the main features and shortcomings of the process are analyzed and a set of rules that could help in the task of modeling any biological system are presented. Special regard is given to the formative requirements and the interdisciplinary nature of this approach. We conclude with some general considerations on the challenges that modeling is posing to current biology.

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

NASA Astrophysics Data System (ADS)

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.

How certain are the process parameterizations in our models?

NASA Astrophysics Data System (ADS)

Gharari, Shervan; Hrachowitz, Markus; Fenicia, Fabrizio; Matgen, Patrick; Razavi, Saman; Savenije, Hubert; Gupta, Hoshin; Wheater, Howard

2016-04-01

Environmental models are abstract simplifications of real systems. As a result, the elements of these models, including system architecture (structure), process parameterization and parameters inherit a high level of approximation and simplification. In a conventional model building exercise the parameter values are the only elements of a model which can vary while the rest of the modeling elements are often fixed a priori and therefore not subjected to change. Once chosen the process parametrization and model structure usually remains the same throughout the modeling process. The only flexibility comes from the changing parameter values, thereby enabling these models to reproduce the desired observation. This part of modeling practice, parameter identification and uncertainty, has attracted a significant attention in the literature during the last years. However what remains unexplored in our point of view is to what extent the process parameterization and system architecture (model structure) can support each other. In other words "Does a specific form of process parameterization emerge for a specific model given its system architecture and data while no or little assumption has been made about the process parameterization itself? In this study we relax the assumption regarding a specific pre-determined form for the process parameterizations of a rainfall/runoff model and examine how varying the complexity of the system architecture can lead to different or possibly contradictory parameterization forms than what would have been decided otherwise. This comparison implicitly and explicitly provides us with an assessment of how uncertain is our perception of model process parameterization in respect to the extent the data can support.

Social network supported process recommender system.

PubMed

Ye, Yanming; Yin, Jianwei; Xu, Yueshen

2014-01-01

Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

Conceptual Model-Based Systems Biology: Mapping Knowledge and Discovering Gaps in the mRNA Transcription Cycle

PubMed Central

Somekh, Judith; Choder, Mordechai; Dori, Dov

2012-01-01

We propose a Conceptual Model-based Systems Biology framework for qualitative modeling, executing, and eliciting knowledge gaps in molecular biology systems. The framework is an adaptation of Object-Process Methodology (OPM), a graphical and textual executable modeling language. OPM enables concurrent representation of the system's structure—the objects that comprise the system, and behavior—how processes transform objects over time. Applying a top-down approach of recursively zooming into processes, we model a case in point—the mRNA transcription cycle. Starting with this high level cell function, we model increasingly detailed processes along with participating objects. Our modeling approach is capable of modeling molecular processes such as complex formation, localization and trafficking, molecular binding, enzymatic stimulation, and environmental intervention. At the lowest level, similar to the Gene Ontology, all biological processes boil down to three basic molecular functions: catalysis, binding/dissociation, and transporting. During modeling and execution of the mRNA transcription model, we discovered knowledge gaps, which we present and classify into various types. We also show how model execution enhances a coherent model construction. Identification and pinpointing knowledge gaps is an important feature of the framework, as it suggests where research should focus and whether conjectures about uncertain mechanisms fit into the already verified model. PMID:23308089

Development and application of an acceptance testing model

NASA Technical Reports Server (NTRS)

Pendley, Rex D.; Noonan, Caroline H.; Hall, Kenneth R.

1992-01-01

The process of acceptance testing large software systems for NASA has been analyzed, and an empirical planning model of the process constructed. This model gives managers accurate predictions of the staffing needed, the productivity of a test team, and the rate at which the system will pass. Applying the model to a new system shows a high level of agreement between the model and actual performance. The model also gives managers an objective measure of process improvement.

A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

NASA Astrophysics Data System (ADS)

Tao, W. K.

2017-12-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

The analysis of magnesium oxide hydration in three-phase reaction system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, Xiaojia; Guo, Lin; Chen, Chen

In order to investigate the magnesium oxide hydration process in gas–liquid–solid (three-phase) reaction system, magnesium hydroxide was prepared by magnesium oxide hydration in liquid–solid (two-phase) and three-phase reaction systems. A semi-empirical model and the classical shrinking core model were used to fit the experimental data. The fitting result shows that both models describe well the hydration process of three-phase system, while only the semi-empirical model right for the hydration process of two-phase system. The characterization of the hydration product using X-Ray diffraction (XRD) and scanning electron microscope (SEM) was performed. The XRD and SEM show hydration process in the two-phasemore » system follows common dissolution/precipitation mechanism. While in the three-phase system, the hydration process undergo MgO dissolution, Mg(OH){sub 2} precipitation, Mg(OH){sub 2} peeling off from MgO particle and leaving behind fresh MgO surface. - Graphical abstract: There was existence of a peeling-off process in the gas–liquid–solid (three-phase) MgO hydration system. - Highlights: • Magnesium oxide hydration in gas–liquid–solid system was investigated. • The experimental data in three-phase system could be fitted well by two models. • The morphology analysis suggested that there was existence of a peel-off process.« less

Modeling and Analysis of Power Processing Systems. [use of a digital computer for designing power plants

NASA Technical Reports Server (NTRS)

Fegley, K. A.; Hayden, J. H.; Rehmann, D. W.

1974-01-01

The feasibility of formulating a methodology for the modeling and analysis of aerospace electrical power processing systems is investigated. It is shown that a digital computer may be used in an interactive mode for the design, modeling, analysis, and comparison of power processing systems.

Intelligent sensor-model automated control of PMR-15 autoclave processing

NASA Technical Reports Server (NTRS)

Hart, S.; Kranbuehl, D.; Loos, A.; Hinds, B.; Koury, J.

1992-01-01

An intelligent sensor model system has been built and used for automated control of the PMR-15 cure process in the autoclave. The system uses frequency-dependent FM sensing (FDEMS), the Loos processing model, and the Air Force QPAL intelligent software shell. The Loos model is used to predict and optimize the cure process including the time-temperature dependence of the extent of reaction, flow, and part consolidation. The FDEMS sensing system in turn monitors, in situ, the removal of solvent, changes in the viscosity, reaction advancement and cure completion in the mold continuously throughout the processing cycle. The sensor information is compared with the optimum processing conditions from the model. The QPAL composite cure control system allows comparison of the sensor monitoring with the model predictions to be broken down into a series of discrete steps and provides a language for making decisions on what to do next regarding time-temperature and pressure.

Principal process analysis of biological models.

PubMed

Casagranda, Stefano; Touzeau, Suzanne; Ropers, Delphine; Gouzé, Jean-Luc

2018-06-14

Understanding the dynamical behaviour of biological systems is challenged by their large number of components and interactions. While efforts have been made in this direction to reduce model complexity, they often prove insufficient to grasp which and when model processes play a crucial role. Answering these questions is fundamental to unravel the functioning of living organisms. We design a method for dealing with model complexity, based on the analysis of dynamical models by means of Principal Process Analysis. We apply the method to a well-known model of circadian rhythms in mammals. The knowledge of the system trajectories allows us to decompose the system dynamics into processes that are active or inactive with respect to a certain threshold value. Process activities are graphically represented by Boolean and Dynamical Process Maps. We detect model processes that are always inactive, or inactive on some time interval. Eliminating these processes reduces the complex dynamics of the original model to the much simpler dynamics of the core processes, in a succession of sub-models that are easier to analyse. We quantify by means of global relative errors the extent to which the simplified models reproduce the main features of the original system dynamics and apply global sensitivity analysis to test the influence of model parameters on the errors. The results obtained prove the robustness of the method. The analysis of the sub-model dynamics allows us to identify the source of circadian oscillations. We find that the negative feedback loop involving proteins PER, CRY, CLOCK-BMAL1 is the main oscillator, in agreement with previous modelling and experimental studies. In conclusion, Principal Process Analysis is a simple-to-use method, which constitutes an additional and useful tool for analysing the complex dynamical behaviour of biological systems.

Business Performer-Centered Design of User Interfaces

NASA Astrophysics Data System (ADS)

Sousa, Kênia; Vanderdonckt, Jean

Business Performer-Centered Design of User Interfaces is a new design methodology that adopts business process (BP) definition and a business performer perspective for managing the life cycle of user interfaces of enterprise systems. In this methodology, when the organization has a business process culture, the business processes of an organization are firstly defined according to a traditional methodology for this kind of artifact. These business processes are then transformed into a series of task models that represent the interactive parts of the business processes that will ultimately lead to interactive systems. When the organization has its enterprise systems, but not yet its business processes modeled, the user interfaces of the systems help derive tasks models, which are then used to derive the business processes. The double linking between a business process and a task model, and between a task model and a user interface model makes it possible to ensure traceability of the artifacts in multiple paths and enables a more active participation of business performers in analyzing the resulting user interfaces. In this paper, we outline how a human-perspective is used tied to a model-driven perspective.

Industrial process system assessment: bridging process engineering and life cycle assessment through multiscale modeling.

EPA Science Inventory

The Industrial Process System Assessment (IPSA) methodology is a multiple step allocation approach for connecting information from the production line level up to the facility level and vice versa using a multiscale model of process systems. The allocation procedure assigns inpu...

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

NASA Astrophysics Data System (ADS)

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.

Process Model of A Fusion Fuel Recovery System for a Direct Drive IFE Power Reactor

NASA Astrophysics Data System (ADS)

Natta, Saswathi; Aristova, Maria; Gentile, Charles

2008-11-01

A task has been initiated to develop a detailed representative model for the fuel recovery system (FRS) in the prospective direct drive inertial fusion energy (IFE) reactor. As part of the conceptual design phase of the project, a chemical process model is developed in order to observe the interaction of system components. This process model is developed using FEMLAB Multiphysics software with the corresponding chemical engineering module (CEM). Initially, the reactants, system structure, and processes are defined using known chemical species of the target chamber exhaust. Each step within the Fuel recovery system is modeled compartmentally and then merged to form the closed loop fuel recovery system. The output, which includes physical properties and chemical content of the products, is analyzed after each step of the system to determine the most efficient and productive system parameters. This will serve to attenuate possible bottlenecks in the system. This modeling evaluation is instrumental in optimizing and closing the fusion fuel cycle in a direct drive IFE power reactor. The results of the modeling are presented in this paper.

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei--Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2010-01-01

In recent years, exponentially increasing computer power extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale models can be run in grid size similar to cloud resolving models through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model). (2) a regional scale model (a NASA unified weather research and forecast, W8F). (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling systems to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use the multi-satellite simulator to improve precipitation processes will be discussed.

Using Multi-Scale Modeling Systems to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2010-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

Microphysics in the Multi-Scale Modeling Systems with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2011-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the microphysics developments of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the heavy precipitation processes will be presented.

System Engineering Concept Demonstration, Process Model. Volume 3

DTIC Science & Technology

1992-12-01

Process or Process Model The System Engineering process must be the enactment of the aforementioned definitions. Therefore, a process is an enactment of a...Prototype Tradeoff Scenario demonstrates six levels of abstraction in the Process Model. The Process Model symbology is explained within the "Help" icon ...dnofing no- ubeq t"vidi e /hn -am-a. lmi IzyuO ..pu Row _e._n au"c.ue-w’ ’- anuiildyidwile b ie htplup ?~imsav D symbo ,,ue,.dvu ,,dienl Flw s--..,fu..I

Social Network Supported Process Recommender System

PubMed Central

Ye, Yanming; Yin, Jianwei; Xu, Yueshen

2014-01-01

Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced. PMID:24672309

Single Plant Root System Modeling under Soil Moisture Variation

NASA Astrophysics Data System (ADS)

Yabusaki, S.; Fang, Y.; Chen, X.; Scheibe, T. D.

2016-12-01

A prognostic Virtual Plant-Atmosphere-Soil System (vPASS) model is being developed that integrates comprehensively detailed mechanistic single plant modeling with microbial, atmospheric, and soil system processes in its immediate environment. Three broad areas of process module development are targeted: Incorporating models for root growth and function, rhizosphere interactions with bacteria and other organisms, litter decomposition and soil respiration into established porous media flow and reactive transport models Incorporating root/shoot transport, growth, photosynthesis and carbon allocation process models into an integrated plant physiology model Incorporating transpiration, Volatile Organic Compounds (VOC) emission, particulate deposition and local atmospheric processes into a coupled plant/atmosphere model. The integrated plant ecosystem simulation capability is being developed as open source process modules and associated interfaces under a modeling framework. The initial focus addresses the coupling of root growth, vascular transport system, and soil under drought scenarios. Two types of root water uptake modeling approaches are tested: continuous root distribution and constitutive root system architecture. The continuous root distribution models are based on spatially averaged root development process parameters, which are relatively straightforward to accommodate in the continuum soil flow and reactive transport module. Conversely, the constitutive root system architecture models use root growth rates, root growth direction, and root branching to evolve explicit root geometries. The branching topologies require more complex data structures and additional input parameters. Preliminary results are presented for root model development and the vascular response to temporal and spatial variations in soil conditions.

ProcessGene-Connect: SOA Integration between Business Process Models and Enactment Transactions of Enterprise Software Systems

NASA Astrophysics Data System (ADS)

Wasser, Avi; Lincoln, Maya

In recent years, both practitioners and applied researchers have become increasingly interested in methods for integrating business process models and enterprise software systems through the deployment of enabling middleware. Integrative BPM research has been mainly focusing on the conversion of workflow notations into enacted application procedures, and less effort has been invested in enhancing the connectivity between design level, non-workflow business process models and related enactment systems such as: ERP, SCM and CRM. This type of integration is useful at several stages of an IT system lifecycle, from design and implementation through change management, upgrades and rollout. The paper presents an integration method that utilizes SOA for connecting business process models with corresponding enterprise software systems. The method is then demonstrated through an Oracle E-Business Suite procurement process and its ERP transactions.

Statistically qualified neuro-analytic failure detection method and system

DOEpatents

Vilim, Richard B.; Garcia, Humberto E.; Chen, Frederick W.

2002-03-02

An apparatus and method for monitoring a process involve development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two stages: deterministic model adaption and stochastic model modification of the deterministic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics, augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation error minimization technique. Stochastic model modification involves qualifying any remaining uncertainty in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system. Illustrative of the method and apparatus, the method is applied to a peristaltic pump system.

The (Mathematical) Modeling Process in Biosciences

PubMed Central

Torres, Nestor V.; Santos, Guido

2015-01-01

In this communication, we introduce a general framework and discussion on the role of models and the modeling process in the field of biosciences. The objective is to sum up the common procedures during the formalization and analysis of a biological problem from the perspective of Systems Biology, which approaches the study of biological systems as a whole. We begin by presenting the definitions of (biological) system and model. Particular attention is given to the meaning of mathematical model within the context of biology. Then, we present the process of modeling and analysis of biological systems. Three stages are described in detail: conceptualization of the biological system into a model, mathematical formalization of the previous conceptual model and optimization and system management derived from the analysis of the mathematical model. All along this work the main features and shortcomings of the process are analyzed and a set of rules that could help in the task of modeling any biological system are presented. Special regard is given to the formative requirements and the interdisciplinary nature of this approach. We conclude with some general considerations on the challenges that modeling is posing to current biology. PMID:26734063

Functional Fault Modeling of a Cryogenic System for Real-Time Fault Detection and Isolation

NASA Technical Reports Server (NTRS)

Ferrell, Bob; Lewis, Mark; Perotti, Jose; Oostdyk, Rebecca; Brown, Barbara

2010-01-01

The purpose of this paper is to present the model development process used to create a Functional Fault Model (FFM) of a liquid hydrogen (L H2) system that will be used for realtime fault isolation in a Fault Detection, Isolation and Recover (FDIR) system. The paper explains th e steps in the model development process and the data products required at each step, including examples of how the steps were performed fo r the LH2 system. It also shows the relationship between the FDIR req uirements and steps in the model development process. The paper concl udes with a description of a demonstration of the LH2 model developed using the process and future steps for integrating the model in a live operational environment.

On Using SysML, DoDAF 2.0 and UPDM to Model the Architecture for the NOAA's Joint Polar Satellite System (JPSS) Ground System (GS)

NASA Technical Reports Server (NTRS)

Hayden, Jeffrey L.; Jeffries, Alan

2012-01-01

The JPSS Ground System is a lIexible system of systems responsible for telemetry, tracking & command (TT &C), data acquisition, routing and data processing services for a varied lIeet of satellites to support weather prediction, modeling and climate modeling. To assist in this engineering effort, architecture modeling tools are being employed to translate the former NPOESS baseline to the new JPSS baseline, The paper will focus on the methodology for the system engineering process and the use of these architecture modeling tools within that process, The Department of Defense Architecture Framework version 2,0 (DoDAF 2.0) viewpoints and views that are being used to describe the JPSS GS architecture are discussed. The Unified Profile for DoOAF and MODAF (UPDM) and Systems Modeling Language (SysML), as ' provided by extensions to the MagicDraw UML modeling tool, are used to develop the diagrams and tables that make up the architecture model. The model development process and structure are discussed, examples are shown, and details of handling the complexities of a large System of Systems (SoS), such as the JPSS GS, with an equally complex modeling tool, are described

Modeling Business Processes of the Social Insurance Fund in Information System Runa WFE

NASA Astrophysics Data System (ADS)

Kataev, M. Yu; Bulysheva, L. A.; Xu, Li D.; Loseva, N. V.

2016-08-01

Introduction - Business processes are gradually becoming a tool that allows you at a new level to put employees or to make more efficient document management system. In these directions the main work, and presents the largest possible number of publications. However, business processes are still poorly implemented in public institutions, where it is very difficult to formalize the main existing processes. Us attempts to build a system of business processes for such state agencies as the Russian social insurance Fund (SIF), where virtually all of the processes, when different inputs have the same output: public service. The parameters of the state services (as a rule, time limits) are set by state laws and regulations. The article provides a brief overview of the FSS, the formulation of requirements to business processes, the justification of the choice of software for modeling business processes and create models of work in the system Runa WFE and optimization models one of the main business processes of the FSS. The result of the work of Runa WFE is an optimized model of the business process of FSS.

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

PubMed

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 demonstrate how such a framework may enable the better integration of process operations by providing a plant-wide process description to facilitate process improvement. Copyright 2009 American Institute of Chemical Engineers

Cognitive Theory within the Framework of an Information Processing Model and Learning Hierarchy: Viable Alternative to the Bloom-Mager System.

ERIC Educational Resources Information Center

Stahl, Robert J.

This review of the current status of the human information processing model presents the Stahl Perceptual Information Processing and Operations Model (SPInPrOM) as a model of how thinking, memory, and the processing of information take place within the individual learner. A related system, the Domain of Cognition, is presented as an alternative to…

Modeling of outpatient prescribing process in iran: a gateway toward electronic prescribing system.

PubMed

Ahmadi, Maryam; Samadbeik, Mahnaz; Sadoughi, Farahnaz

2014-01-01

Implementation of electronic prescribing system can overcome many problems of the paper prescribing system, and provide numerous opportunities of more effective and advantageous prescribing. Successful implementation of such a system requires complete and deep understanding of work content, human force, and workflow of paper prescribing. The current study was designed in order to model the current business process of outpatient prescribing in Iran and clarify different actions during this process. In order to describe the prescribing process and the system features in Iran, the methodology of business process modeling and analysis was used in the present study. The results of the process documentation were analyzed using a conceptual model of workflow elements and the technique of modeling "As-Is" business processes. Analysis of the current (as-is) prescribing process demonstrated that Iran stood at the first levels of sophistication in graduated levels of electronic prescribing, namely electronic prescription reference, and that there were problematic areas including bottlenecks, redundant and duplicated work, concentration of decision nodes, and communicative weaknesses among stakeholders of the process. Using information technology in some activities of medication prescription in Iran has not eliminated the dependence of the stakeholders on paper-based documents and prescriptions. Therefore, it is necessary to implement proper system programming in order to support change management and solve the problems in the existing prescribing process. To this end, a suitable basis should be provided for reorganization and improvement of the prescribing process for the future electronic systems.

Application fields for the new Object Management Group (OMG) Standards Case Management Model and Notation (CMMN) and Decision Management Notation (DMN) in the perioperative field.

PubMed

Wiemuth, M; Junger, D; Leitritz, M A; Neumann, J; Neumuth, T; Burgert, O

2017-08-01

Medical processes can be modeled using different methods and notations. Currently used modeling systems like Business Process Model and Notation (BPMN) are not capable of describing the highly flexible and variable medical processes in sufficient detail. We combined two modeling systems, Business Process Management (BPM) and Adaptive Case Management (ACM), to be able to model non-deterministic medical processes. We used the new Standards Case Management Model and Notation (CMMN) and Decision Management Notation (DMN). First, we explain how CMMN, DMN and BPMN could be used to model non-deterministic medical processes. We applied this methodology to model 79 cataract operations provided by University Hospital Leipzig, Germany, and four cataract operations provided by University Eye Hospital Tuebingen, Germany. Our model consists of 85 tasks and about 20 decisions in BPMN. We were able to expand the system with more complex situations that might appear during an intervention. An effective modeling of the cataract intervention is possible using the combination of BPM and ACM. The combination gives the possibility to depict complex processes with complex decisions. This combination allows a significant advantage for modeling perioperative processes.

Low level image processing techniques using the pipeline image processing engine in the flight telerobotic servicer

NASA Technical Reports Server (NTRS)

Nashman, Marilyn; Chaconas, Karen J.

1988-01-01

The sensory processing system for the NASA/NBS Standard Reference Model (NASREM) for telerobotic control is described. This control system architecture was adopted by NASA of the Flight Telerobotic Servicer. The control system is hierarchically designed and consists of three parallel systems: task decomposition, world modeling, and sensory processing. The Sensory Processing System is examined, and in particular the image processing hardware and software used to extract features at low levels of sensory processing for tasks representative of those envisioned for the Space Station such as assembly and maintenance are described.

Aligning grammatical theories and language processing models.

PubMed

Lewis, Shevaun; Phillips, Colin

2015-02-01

We address two important questions about the relationship between theoretical linguistics and psycholinguistics. First, do grammatical theories and language processing models describe separate cognitive systems, or are they accounts of different aspects of the same system? We argue that most evidence is consistent with the one-system view. Second, how should we relate grammatical theories and language processing models to each other?

Dual processing model of medical decision-making.

PubMed

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 large extent dominated by expected utility theory. The model also provides a platform for reconciling two groups of competing dual processing theories (parallel competitive with default-interventionalist theories).

Integrated control system for electron beam processes

NASA Astrophysics Data System (ADS)

Koleva, L.; Koleva, E.; Batchkova, I.; Mladenov, G.

2018-03-01

The ISO/IEC 62264 standard is widely used for integration of the business systems of a manufacturer with the corresponding manufacturing control systems based on hierarchical equipment models, functional data and manufacturing operations activity models. In order to achieve the integration of control systems, formal object communication models must be developed, together with manufacturing operations activity models, which coordinate the integration between different levels of control. In this article, the development of integrated control system for electron beam welding process is presented as part of a fully integrated control system of an electron beam plant, including also other additional processes: surface modification, electron beam evaporation, selective melting and electron beam diagnostics.

Dual Systems Competence [Image Omitted] Procedural Processing: A Relational Developmental Systems Approach to Reasoning

ERIC Educational Resources Information Center

Ricco, Robert B.; Overton, Willis F.

2011-01-01

Many current psychological models of reasoning minimize the role of deductive processes in human thought. In the present paper, we argue that deduction is an important part of ordinary cognition and we propose that a dual systems Competence [image omitted] Procedural processing model conceptualized within relational developmental systems theory…

Using explanatory crop models to develop simple tools for Advanced Life Support system studies

NASA Technical Reports Server (NTRS)

Cavazzoni, J.

2004-01-01

System-level analyses for Advanced Life Support require mathematical models for various processes, such as for biomass production and waste management, which would ideally be integrated into overall system models. Explanatory models (also referred to as mechanistic or process models) would provide the basis for a more robust system model, as these would be based on an understanding of specific processes. However, implementing such models at the system level may not always be practicable because of their complexity. For the area of biomass production, explanatory models were used to generate parameters and multivariable polynomial equations for basic models that are suitable for estimating the direction and magnitude of daily changes in canopy gas-exchange, harvest index, and production scheduling for both nominal and off-nominal growing conditions. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

The Modular Modeling System (MMS): User's Manual

USGS Publications Warehouse

Leavesley, G.H.; Restrepo, Pedro J.; Markstrom, S.L.; Dixon, M.; Stannard, L.G.

1996-01-01

The Modular Modeling System (MMS) is an integrated system of computer software that has been developed to provide the research and operational framework needed to support development, testing, and evaluation of physical-process algorithms and to facilitate integration of user-selected sets of algorithms into operational physical-process models. MMS uses a module library that contains modules for simulating a variety of water, energy, and biogeochemical processes. A model is created by selectively coupling the most appropriate modules from the library to create a 'suitable' model for the desired application. Where existing modules do not provide appropriate process algorithms, new modules can be developed. The MMS user's manual provides installation instructions and a detailed discussion of system concepts, module development, and model development and application using the MMS graphical user interface.

Detailed Modeling of Distillation Technologies for Closed-Loop Water Recovery Systems

NASA Technical Reports Server (NTRS)

Allada, Rama Kumar; Lange, Kevin E.; Anderson, Molly S.

2011-01-01

Detailed chemical process simulations are a useful tool in designing and optimizing complex systems and architectures for human life support. Dynamic and steady-state models of these systems help contrast the interactions of various operating parameters and hardware designs, which become extremely useful in trade-study analyses. NASA?s Exploration Life Support technology development project recently made use of such models to compliment a series of tests on different waste water distillation systems. This paper presents efforts to develop chemical process simulations for three technologies: the Cascade Distillation System (CDS), the Vapor Compression Distillation (VCD) system and the Wiped-Film Rotating Disk (WFRD) using the Aspen Custom Modeler and Aspen Plus process simulation tools. The paper discusses system design, modeling details, and modeling results for each technology and presents some comparisons between the model results and recent test data. Following these initial comparisons, some general conclusions and forward work are discussed.

MIMO model of an interacting series process for Robust MPC via System Identification.

PubMed

Wibowo, Tri Chandra S; Saad, Nordin

2010-07-01

This paper discusses the empirical modeling using system identification technique with a focus on an interacting series process. The study is carried out experimentally using a gaseous pilot plant as the process, in which the dynamic of such a plant exhibits the typical dynamic of an interacting series process. Three practical approaches are investigated and their performances are evaluated. The models developed are also examined in real-time implementation of a linear model predictive control. The selected model is able to reproduce the main dynamic characteristics of the plant in open-loop and produces zero steady-state errors in closed-loop control system. Several issues concerning the identification process and the construction of a MIMO state space model for a series interacting process are deliberated. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Modeling and Simulation of Metallurgical Process Based on Hybrid Petri Net

NASA Astrophysics Data System (ADS)

Ren, Yujuan; Bao, Hong

2016-11-01

In order to achieve the goals of energy saving and emission reduction of iron and steel enterprises, an increasing number of modeling and simulation technologies are used to research and analyse metallurgical production process. In this paper, the basic principle of Hybrid Petri net is used to model and analyse the Metallurgical Process. Firstly, the definition of Hybrid Petri Net System of Metallurgical Process (MPHPNS) and its modeling theory are proposed. Secondly, the model of MPHPNS based on material flow is constructed. The dynamic flow of materials and the real-time change of each technological state in metallurgical process are simulated vividly by using this model. The simulation process can implement interaction between the continuous event dynamic system and the discrete event dynamic system at the same level, and play a positive role in the production decision.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, Arthur; Cayan, Daniel; Pierce, David

This project addressed the ability of the Community Climate System Model (CCSM3 and CCSM4), the Community Earth System Model (CESM), and other models to simulate the processes involved in controlling winter storms affecting the U.S. West Coast as well as other precipitation processes in the climate system.

Formal Specification of Information Systems Requirements.

ERIC Educational Resources Information Center

Kampfner, Roberto R.

1985-01-01

Presents a formal model for specification of logical requirements of computer-based information systems that incorporates structural and dynamic aspects based on two separate models: the Logical Information Processing Structure and the Logical Information Processing Network. The model's role in systems development is discussed. (MBR)

Functional Fault Model Development Process to Support Design Analysis and Operational Assessment

NASA Technical Reports Server (NTRS)

Melcher, Kevin J.; Maul, William A.; Hemminger, Joseph A.

2016-01-01

A functional fault model (FFM) is an abstract representation of the failure space of a given system. As such, it simulates the propagation of failure effects along paths between the origin of the system failure modes and points within the system capable of observing the failure effects. As a result, FFMs may be used to diagnose the presence of failures in the modeled system. FFMs necessarily contain a significant amount of information about the design, operations, and failure modes and effects. One of the important benefits of FFMs is that they may be qualitative, rather than quantitative and, as a result, may be implemented early in the design process when there is more potential to positively impact the system design. FFMs may therefore be developed and matured throughout the monitored system's design process and may subsequently be used to provide real-time diagnostic assessments that support system operations. This paper provides an overview of a generalized NASA process that is being used to develop and apply FFMs. FFM technology has been evolving for more than 25 years. The FFM development process presented in this paper was refined during NASA's Ares I, Space Launch System, and Ground Systems Development and Operations programs (i.e., from about 2007 to the present). Process refinement took place as new modeling, analysis, and verification tools were created to enhance FFM capabilities. In this paper, standard elements of a model development process (i.e., knowledge acquisition, conceptual design, implementation & verification, and application) are described within the context of FFMs. Further, newer tools and analytical capabilities that may benefit the broader systems engineering process are identified and briefly described. The discussion is intended as a high-level guide for future FFM modelers.

DoD Lead System Integrator (LSI) Transformation - Creating a Model Based Acquisition Framework (MBAF)

DTIC Science & Technology

2014-04-30

cost to acquire systems as design maturity could be verified incrementally as the system was developed vice waiting for specific large “ big bang ...Framework (MBAF) be applied to simulate or optimize process variations on programs? LSI Roles and Responsibilities A review of the roles and...the model/process optimization process. It is the current intent that NAVAIR will use the model to run simulations on process changes in an attempt to

System Identification and Verification of Rotorcraft UAVs

NASA Astrophysics Data System (ADS)

Carlton, Zachary M.

The task of a controls engineer is to design and implement control logic. To complete this task, it helps tremendously to have an accurate model of the system to be controlled. Obtaining a very accurate system model is not a trivial one, as much time and money is usually associated with the development of such a model. A typical physics based approach can require hundreds of hours of flight time. In an iterative process the model is tuned in such a way that it accurately models the physical system's response. This process becomes even more complicated for unstable and highly non-linear systems such as the dynamics of rotorcraft. An alternate approach to solving this problem is to extract an accurate model by analyzing the frequency response of the system. This process involves recording the system's responses for a frequency range of input excitations. From this data, an accurate system model can then be deduced. Furthermore, it has been shown that with use of the software package CIFER® (Comprehensive Identification from FrEquency Responses), this process can both greatly reduce the cost of modeling a dynamic system and produce very accurate results. The topic of this thesis is to apply CIFER® to a quadcopter to extract a system model for the flight condition of hover. The quadcopter itself is comprised of off-the-shelf components with a Pixhack flight controller board running open source Ardupilot controller logic. In this thesis, both the closed and open loop systems are identified. The model is next compared to dissimilar flight data and verified in the time domain. Additionally, the ESC (Electronic Speed Controller) motor/rotor subsystem, which is comprised of all the vehicle's actuators, is also identified. This process required the development of a test bench environment, which included a GUI (Graphical User Interface), data pre and post processing, as well as the augmentation of the flight controller source code. This augmentation of code allowed for proper data logging rates of all needed parameters.

A systems-based approach for integrated design of materials, products and design process chains

NASA Astrophysics Data System (ADS)

Panchal, Jitesh H.; Choi, Hae-Jin; Allen, Janet K.; McDowell, David L.; Mistree, Farrokh

2007-12-01

The concurrent design of materials and products provides designers with flexibility to achieve design objectives that were not previously accessible. However, the improved flexibility comes at a cost of increased complexity of the design process chains and the materials simulation models used for executing the design chains. Efforts to reduce the complexity generally result in increased uncertainty. We contend that a systems based approach is essential for managing both the complexity and the uncertainty in design process chains and simulation models in concurrent material and product design. Our approach is based on simplifying the design process chains systematically such that the resulting uncertainty does not significantly affect the overall system performance. Similarly, instead of striving for accurate models for multiscale systems (that are inherently complex), we rely on making design decisions that are robust to uncertainties in the models. Accordingly, we pursue hierarchical modeling in the context of design of multiscale systems. In this paper our focus is on design process chains. We present a systems based approach, premised on the assumption that complex systems can be designed efficiently by managing the complexity of design process chains. The approach relies on (a) the use of reusable interaction patterns to model design process chains, and (b) consideration of design process decisions using value-of-information based metrics. The approach is illustrated using a Multifunctional Energetic Structural Material (MESM) design example. Energetic materials store considerable energy which can be released through shock-induced detonation; conventionally, they are not engineered for strength properties. The design objectives for the MESM in this paper include both sufficient strength and energy release characteristics. The design is carried out by using models at different length and time scales that simulate different aspects of the system. Finally, by applying the method to the MESM design problem, we show that the integrated design of materials and products can be carried out more efficiently by explicitly accounting for design process decisions with the hierarchy of models.

Current and Future Flight Operating Systems

NASA Technical Reports Server (NTRS)

Cudmore, Alan

2007-01-01

This viewgraph presentation reviews the current real time operating system (RTOS) type in use with current flight systems. A new RTOS model is described, i.e. the process model. Included is a review of the challenges of migrating from the classic RTOS to the Process Model type.

Modeling Business Processes in Public Administration

NASA Astrophysics Data System (ADS)

Repa, Vaclav

During more than 10 years of its existence business process modeling became a regular part of organization management practice. It is mostly regarded. as a part of information system development or even as a way to implement some supporting technology (for instance workflow system). Although I do not agree with such reduction of the real meaning of a business process, it is necessary to admit that information technologies play an essential role in business processes (see [1] for more information), Consequently, an information system is inseparable from a business process itself because it is a cornerstone of the general basic infrastructure of a business. This fact impacts on all dimensions of business process management. One of these dimensions is the methodology that postulates that the information systems development provide the business process management with exact methods and tools for modeling business processes. Also the methodology underlying the approach presented in this paper has its roots in the information systems development methodology.

A framework for human-hydrologic system model development integrating hydrology and water management: application to the Cutzamala water system in Mexico

NASA Astrophysics Data System (ADS)

Wi, S.; Freeman, S.; Brown, C.

2017-12-01

This study presents a general approach to developing computational models of human-hydrologic systems where human modification of hydrologic surface processes are significant or dominant. A river basin system is represented by a network of human-hydrologic response units (HHRUs) identified based on locations where river regulations happen (e.g., reservoir operation and diversions). Natural and human processes in HHRUs are simulated in a holistic framework that integrates component models representing rainfall-runoff, river routing, reservoir operation, flow diversion and water use processes. We illustrate the approach in a case study of the Cutzamala water system (CWS) in Mexico, a complex inter-basin water transfer system supplying the Mexico City Metropolitan Area (MCMA). The human-hydrologic system model for CWS (CUTZSIM) is evaluated in terms of streamflow and reservoir storages measured across the CWS and to water supplied for MCMA. The CUTZSIM improves the representation of hydrology and river-operation interaction and, in so doing, advances evaluation of system-wide water management consequences under altered climatic and demand regimes. The integrated modeling framework enables evaluation and simulation of model errors throughout the river basin, including errors in representation of the human component processes. Heretofore, model error evaluation, predictive error intervals and the resultant improved understanding have been limited to hydrologic processes. The general framework represents an initial step towards fuller understanding and prediction of the many and varied processes that determine the hydrologic fluxes and state variables in real river basins.

Hydrothermal Gasification for Waste to Energy

NASA Astrophysics Data System (ADS)

Epps, Brenden; Laser, Mark; Choo, Yeunun

2014-11-01

Hydrothermal gasification is a promising technology for harvesting energy from waste streams. Applications range from straightforward waste-to-energy conversion (e.g. municipal waste processing, industrial waste processing), to water purification (e.g. oil spill cleanup, wastewater treatment), to biofuel energy systems (e.g. using algae as feedstock). Products of the gasification process are electricity, bottled syngas (H2 + CO), sequestered CO2, clean water, and inorganic solids; further chemical reactions can be used to create biofuels such as ethanol and biodiesel. We present a comparison of gasification system architectures, focusing on efficiency and economic performance metrics. Various system architectures are modeled computationally, using a model developed by the coauthors. The physical model tracks the mass of each chemical species, as well as energy conversions and transfers throughout the gasification process. The generic system model includes the feedstock, gasification reactor, heat recovery system, pressure reducing mechanical expanders, and electricity generation system. Sensitivity analysis of system performance to various process parameters is presented. A discussion of the key technological barriers and necessary innovations is also presented.

Modeling formalisms in Systems Biology

PubMed Central

2011-01-01

Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of these models are specific to each kind of network. Their interconnection demands a whole-cell modeling framework for a complete understanding of cellular systems. We describe the features required by an integrated framework for modeling, analyzing and simulating biological processes, and review several modeling formalisms that have been used in Systems Biology including Boolean networks, Bayesian networks, Petri nets, process algebras, constraint-based models, differential equations, rule-based models, interacting state machines, cellular automata, and agent-based models. We compare the features provided by different formalisms, and discuss recent approaches in the integration of these formalisms, as well as possible directions for the future. PMID:22141422

Kinetic models for nitrogen inhibition in ANAMMOX and nitrification process on deammonification system at room temperature.

PubMed

De Prá, Marina C; Kunz, Airton; Bortoli, Marcelo; Scussiato, Lucas A; Coldebella, Arlei; Vanotti, Matias; Soares, Hugo M

2016-02-01

In this study were fitted the best kinetic model for nitrogen removal inhibition by ammonium and/or nitrite in three different nitrogen removal systems operated at 25 °C: a nitrifying system (NF) containing only ammonia oxidizing bacteria (AOB), an ANAMMOX system (AMX) containing only ANAMMOX bacteria, and a deammonification system (DMX) containing both AOB and ANAMMOX bacteria. NF system showed inhibition by ammonium and was best described by Andrews model. The AMX system showed a strong inhibition by nitrite and Edwards model presented a best system representation. For DMX system, the increased substrate concentration (until 1060 mg NH3-N/L) tested was not limiting for the ammonia consumption rate and the Monod model was the best model to describe this process. The AOB and ANAMMOX sludges combined in the DMX system displayed a better activity, substrate affinity and excellent substrate tolerance than in nitrifying and ANAMMOX process. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-fluid CFD analysis in Process Engineering

NASA Astrophysics Data System (ADS)

Hjertager, B. H.

2017-12-01

An overview of modelling and simulation of flow processes in gas/particle and gas/liquid systems are presented. Particular emphasis is given to computational fluid dynamics (CFD) models that use the multi-dimensional multi-fluid techniques. Turbulence modelling strategies for gas/particle flows based on the kinetic theory for granular flows are given. Sub models for the interfacial transfer processes and chemical kinetics modelling are presented. Examples are shown for some gas/particle systems including flow and chemical reaction in risers as well as gas/liquid systems including bubble columns and stirred tanks.

Distributed parallel computing in stochastic modeling of groundwater systems.

PubMed

Dong, Yanhui; Li, Guomin; Xu, Haizhen

2013-03-01

Stochastic modeling is a rapidly evolving, popular approach to the study of the uncertainty and heterogeneity of groundwater systems. However, the use of Monte Carlo-type simulations to solve practical groundwater problems often encounters computational bottlenecks that hinder the acquisition of meaningful results. To improve the computational efficiency, a system that combines stochastic model generation with MODFLOW-related programs and distributed parallel processing is investigated. The distributed computing framework, called the Java Parallel Processing Framework, is integrated into the system to allow the batch processing of stochastic models in distributed and parallel systems. As an example, the system is applied to the stochastic delineation of well capture zones in the Pinggu Basin in Beijing. Through the use of 50 processing threads on a cluster with 10 multicore nodes, the execution times of 500 realizations are reduced to 3% compared with those of a serial execution. Through this application, the system demonstrates its potential in solving difficult computational problems in practical stochastic modeling. © 2012, The Author(s). Groundwater © 2012, National Ground Water Association.

A Generic Modeling Process to Support Functional Fault Model Development

NASA Technical Reports Server (NTRS)

Maul, William A.; Hemminger, Joseph A.; Oostdyk, Rebecca; Bis, Rachael A.

2016-01-01

Functional fault models (FFMs) are qualitative representations of a system's failure space that are used to provide a diagnostic of the modeled system. An FFM simulates the failure effect propagation paths within a system between failure modes and observation points. These models contain a significant amount of information about the system including the design, operation and off nominal behavior. The development and verification of the models can be costly in both time and resources. In addition, models depicting similar components can be distinct, both in appearance and function, when created individually, because there are numerous ways of representing the failure space within each component. Generic application of FFMs has the advantages of software code reuse: reduction of time and resources in both development and verification, and a standard set of component models from which future system models can be generated with common appearance and diagnostic performance. This paper outlines the motivation to develop a generic modeling process for FFMs at the component level and the effort to implement that process through modeling conventions and a software tool. The implementation of this generic modeling process within a fault isolation demonstration for NASA's Advanced Ground System Maintenance (AGSM) Integrated Health Management (IHM) project is presented and the impact discussed.

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

DOE PAGES

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin; ...

2017-01-01

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

Simulating the decentralized processes of the human immune system in a virtual anatomy model.

PubMed

Sarpe, Vladimir; Jacob, Christian

2013-01-01

Many physiological processes within the human body can be perceived and modeled as large systems of interacting particles or swarming agents. The complex processes of the human immune system prove to be challenging to capture and illustrate without proper reference to the spatial distribution of immune-related organs and systems. Our work focuses on physical aspects of immune system processes, which we implement through swarms of agents. This is our first prototype for integrating different immune processes into one comprehensive virtual physiology simulation. Using agent-based methodology and a 3-dimensional modeling and visualization environment (LINDSAY Composer), we present an agent-based simulation of the decentralized processes in the human immune system. The agents in our model - such as immune cells, viruses and cytokines - interact through simulated physics in two different, compartmentalized and decentralized 3-dimensional environments namely, (1) within the tissue and (2) inside a lymph node. While the two environments are separated and perform their computations asynchronously, an abstract form of communication is allowed in order to replicate the exchange, transportation and interaction of immune system agents between these sites. The distribution of simulated processes, that can communicate across multiple, local CPUs or through a network of machines, provides a starting point to build decentralized systems that replicate larger-scale processes within the human body, thus creating integrated simulations with other physiological systems, such as the circulatory, endocrine, or nervous system. Ultimately, this system integration across scales is our goal for the LINDSAY Virtual Human project. Our current immune system simulations extend our previous work on agent-based simulations by introducing advanced visualizations within the context of a virtual human anatomy model. We also demonstrate how to distribute a collection of connected simulations over a network of computers. As a future endeavour, we plan to use parameter tuning techniques on our model to further enhance its biological credibility. We consider these in silico experiments and their associated modeling and optimization techniques as essential components in further enhancing our capabilities of simulating a whole-body, decentralized immune system, to be used both for medical education and research as well as for virtual studies in immunoinformatics.

The Challenges to Coupling Dynamic Geospatial Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldstein, N

2006-06-23

Many applications of modeling spatial dynamic systems focus on a single system and a single process, ignoring the geographic and systemic context of the processes being modeled. A solution to this problem is the coupled modeling of spatial dynamic systems. Coupled modeling is challenging for both technical reasons, as well as conceptual reasons. This paper explores the benefits and challenges to coupling or linking spatial dynamic models, from loose coupling, where information transfer between models is done by hand, to tight coupling, where two (or more) models are merged as one. To illustrate the challenges, a coupled model of Urbanizationmore » and Wildfire Risk is presented. This model, called Vesta, was applied to the Santa Barbara, California region (using real geospatial data), where Urbanization and Wildfires occur and recur, respectively. The preliminary results of the model coupling illustrate that coupled modeling can lead to insight into the consequences of processes acting on their own.« less

A systems engineering approach to AIS accreditation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, L.M.; Hunteman, W.J.

1994-04-01

The systems engineering model provides the vehicle for communication between the developer and the customer by presenting system facts and demonstrating the system in an organized form. The same model provides implementors with views of the system`s function and capability. The authors contend that the process of obtaining accreditation for a classified Automated Information System (AIS) adheres to the typical systems engineering model. The accreditation process is modeled as a ``roadmap`` with the customer represented by the Designed Accrediting Authority. The ``roadmap`` model reduces the amount of accreditation knowledge required of an AIS developer and maximizes the effectiveness of participationmore » in the accreditation process by making the understanding of accreditation a natural consequence of applying the model. This paper identifies ten ``destinations`` on the ``road`` to accreditation. The significance of each ``destination`` is explained, as are the potential consequences of its exclusion. The ``roadmap,`` which has been applied to a range of information systems throughout the DOE community, establishes a paradigm for the certification and accreditation of classified AISs.« less

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

NASA Astrophysics Data System (ADS)

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.

Statistically Qualified Neuro-Analytic system and Method for Process Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vilim, Richard B.; Garcia, Humberto E.; Chen, Frederick W.

1998-11-04

An apparatus and method for monitoring a process involves development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two steps: deterministic model adaption and stochastic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics,augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation emor minimization technique. Stochastic model adaptation involves qualifying any remaining uncertaintymore » in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system.« less

Conceptual models of information processing

NASA Technical Reports Server (NTRS)

Stewart, L. J.

1983-01-01

The conceptual information processing issues are examined. Human information processing is defined as an active cognitive process that is analogous to a system. It is the flow and transformation of information within a human. The human is viewed as an active information seeker who is constantly receiving, processing, and acting upon the surrounding environmental stimuli. Human information processing models are conceptual representations of cognitive behaviors. Models of information processing are useful in representing the different theoretical positions and in attempting to define the limits and capabilities of human memory. It is concluded that an understanding of conceptual human information processing models and their applications to systems design leads to a better human factors approach.

Self-conscious robotic system design process--from analysis to implementation.

PubMed

Chella, Antonio; Cossentino, Massimo; Seidita, Valeria

2011-01-01

Developing robotic systems endowed with self-conscious capabilities means realizing complex sub-systems needing ad-hoc software engineering techniques for their modelling, analysis and implementation. In this chapter the whole process (from analysis to implementation) to model the development of self-conscious robotic systems is presented and the new created design process, PASSIC, supporting each part of it, is fully illustrated.

Integration of a three-dimensional process-based hydrological model into the Object Modeling System

USDA-ARS?s Scientific Manuscript database

The integration of a spatial process model into an environmental modelling framework can enhance the model’s capabilities. We present the integration of the GEOtop model into the Object Modeling System (OMS) version 3.0 and illustrate its application in a small watershed. GEOtop is a physically base...

Engineered Barrier System: Physical and Chemical Environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

P. Dixon

2004-04-26

The conceptual and predictive models documented in this Engineered Barrier System: Physical and Chemical Environment Model report describe the evolution of the physical and chemical conditions within the waste emplacement drifts of the repository. The modeling approaches and model output data will be used in the total system performance assessment (TSPA-LA) to assess the performance of the engineered barrier system and the waste form. These models evaluate the range of potential water compositions within the emplacement drifts, resulting from the interaction of introduced materials and minerals in dust with water seeping into the drifts and with aqueous solutions forming bymore » deliquescence of dust (as influenced by atmospheric conditions), and from thermal-hydrological-chemical (THC) processes in the drift. These models also consider the uncertainty and variability in water chemistry inside the drift and the compositions of introduced materials within the drift. This report develops and documents a set of process- and abstraction-level models that constitute the engineered barrier system: physical and chemical environment model. Where possible, these models use information directly from other process model reports as input, which promotes integration among process models used for total system performance assessment. Specific tasks and activities of modeling the physical and chemical environment are included in the technical work plan ''Technical Work Plan for: In-Drift Geochemistry Modeling'' (BSC 2004 [DIRS 166519]). As described in the technical work plan, the development of this report is coordinated with the development of other engineered barrier system analysis model reports.« less

The Policy-Making Process of the State University System of Florida.

ERIC Educational Resources Information Center

Sullivan, Sandra M.

The policy-making process of the State University System of Florida is described using David Easton's model of a political system as the conceptual framwork. Two models describing the policy-making process were developed from personal interviews with the primary participants in the governance structure and from three case studies of policy…

Dual processing model of medical decision-making

PubMed Central

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 decision-making field, which is still to the large extent dominated by expected utility theory. The model also provides a platform for reconciling two groups of competing dual processing theories (parallel competitive with default-interventionalist theories). PMID:22943520

Teaching Tip: Using Activity Diagrams to Model Systems Analysis Techniques: Teaching What We Preach

ERIC Educational Resources Information Center

Lending, Diane; May, Jeffrey

2013-01-01

Activity diagrams are used in Systems Analysis and Design classes as a visual tool to model the business processes of "as-is" and "to-be" systems. This paper presents the idea of using these same activity diagrams in the classroom to model the actual processes (practices and techniques) of Systems Analysis and Design. This tip…

Modeling hospital surgical delivery process design using system simulation: optimizing patient flow and bed capacity as an illustration.

PubMed

Kumar, Sameer

2011-01-01

It is increasingly recognized that hospital operation is an intricate system with limited resources and many interacting sources of both positive and negative feedback. The purpose of this study is to design a surgical delivery process in a county hospital in the U.S where patient flow through a surgical ward is optimized. The system simulation modeling is used to address questions of capacity planning, throughput management and interacting resources which constitute the constantly changing complexity that characterizes designing a contemporary surgical delivery process in a hospital. The steps in building a system simulation model is demonstrated using an example of building a county hospital in a small city in the US. It is used to illustrate a modular system simulation modeling of patient surgery process flows. The system simulation model development will enable planners and designers how they can build in overall efficiencies in a healthcare facility through optimal bed capacity for peak patient flow of emergency and routine patients.

Business intelligence modeling in launch operations

NASA Astrophysics Data System (ADS)

Bardina, Jorge E.; Thirumalainambi, Rajkumar; Davis, Rodney D.

2005-05-01

The future of business intelligence in space exploration will focus on the intelligent system-of-systems real-time enterprise. In present business intelligence, a number of technologies that are most relevant to space exploration are experiencing the greatest change. Emerging patterns of set of processes rather than organizational units leading to end-to-end automation is becoming a major objective of enterprise information technology. The cost element is a leading factor of future exploration systems. This technology project is to advance an integrated Planning and Management Simulation Model for evaluation of risks, costs, and reliability of launch systems from Earth to Orbit for Space Exploration. The approach builds on research done in the NASA ARC/KSC developed Virtual Test Bed (VTB) to integrate architectural, operations process, and mission simulations for the purpose of evaluating enterprise level strategies to reduce cost, improve systems operability, and reduce mission risks. The objectives are to understand the interdependency of architecture and process on recurring launch cost of operations, provide management a tool for assessing systems safety and dependability versus cost, and leverage lessons learned and empirical models from Shuttle and International Space Station to validate models applied to Exploration. The systems-of-systems concept is built to balance the conflicting objectives of safety, reliability, and process strategy in order to achieve long term sustainability. A planning and analysis test bed is needed for evaluation of enterprise level options and strategies for transit and launch systems as well as surface and orbital systems. This environment can also support agency simulation based acquisition process objectives. The technology development approach is based on the collaborative effort set forth in the VTB's integrating operations, process models, systems and environment models, and cost models as a comprehensive disciplined enterprise analysis environment. Significant emphasis is being placed on adapting root cause from existing Shuttle operations to exploration. Technical challenges include cost model validation, integration of parametric models with discrete event process and systems simulations, and large-scale simulation integration. The enterprise architecture is required for coherent integration of systems models. It will also require a plan for evolution over the life of the program. The proposed technology will produce long-term benefits in support of the NASA objectives for simulation based acquisition, will improve the ability to assess architectural options verses safety/risk for future exploration systems, and will facilitate incorporation of operability as a systems design consideration, reducing overall life cycle cost for future systems.

Business Intelligence Modeling in Launch Operations

NASA Technical Reports Server (NTRS)

Bardina, Jorge E.; Thirumalainambi, Rajkumar; Davis, Rodney D.

2005-01-01

This technology project is to advance an integrated Planning and Management Simulation Model for evaluation of risks, costs, and reliability of launch systems from Earth to Orbit for Space Exploration. The approach builds on research done in the NASA ARC/KSC developed Virtual Test Bed (VTB) to integrate architectural, operations process, and mission simulations for the purpose of evaluating enterprise level strategies to reduce cost, improve systems operability, and reduce mission risks. The objectives are to understand the interdependency of architecture and process on recurring launch cost of operations, provide management a tool for assessing systems safety and dependability versus cost, and leverage lessons learned and empirical models from Shuttle and International Space Station to validate models applied to Exploration. The systems-of-systems concept is built to balance the conflicting objectives of safety, reliability, and process strategy in order to achieve long term sustainability. A planning and analysis test bed is needed for evaluation of enterprise level options and strategies for transit and launch systems as well as surface and orbital systems. This environment can also support agency simulation .based acquisition process objectives. The technology development approach is based on the collaborative effort set forth in the VTB's integrating operations. process models, systems and environment models, and cost models as a comprehensive disciplined enterprise analysis environment. Significant emphasis is being placed on adapting root cause from existing Shuttle operations to exploration. Technical challenges include cost model validation, integration of parametric models with discrete event process and systems simulations. and large-scale simulation integration. The enterprise architecture is required for coherent integration of systems models. It will also require a plan for evolution over the life of the program. The proposed technology will produce long-term benefits in support of the NASA objectives for simulation based acquisition, will improve the ability to assess architectural options verses safety/risk for future exploration systems, and will facilitate incorporation of operability as a systems design consideration, reducing overall life cycle cost for future systems. The future of business intelligence of space exploration will focus on the intelligent system-of-systems real-time enterprise. In present business intelligence, a number of technologies that are most relevant to space exploration are experiencing the greatest change. Emerging patterns of set of processes rather than organizational units leading to end-to-end automation is becoming a major objective of enterprise information technology. The cost element is a leading factor of future exploration systems.

An ecological process model of systems change.

PubMed

Peirson, Leslea J; Boydell, Katherine M; Ferguson, H Bruce; Ferris, Lorraine E

2011-06-01

In June 2007 the American Journal of Community Psychology published a special issue focused on theories, methods and interventions for systems change which included calls from the editors and authors for theoretical advancement in this field. We propose a conceptual model of systems change that integrates familiar and fundamental community psychology principles (succession, interdependence, cycling of resources, adaptation) and accentuates a process orientation. To situate our framework we offer a definition of systems change and a brief review of the ecological perspective and principles. The Ecological Process Model of Systems Change is depicted, described and applied to a case example of policy driven systems level change in publicly funded social programs. We conclude by identifying salient implications for thinking and action which flow from the Model.

Speech Perception as a Cognitive Process: The Interactive Activation Model.

ERIC Educational Resources Information Center

Elman, Jeffrey L.; McClelland, James L.

Research efforts to model speech perception in terms of a processing system in which knowledge and processing are distributed over large numbers of highly interactive--but computationally primative--elements are described in this report. After discussing the properties of speech that demand a parallel interactive processing system, the report…

Ontological Model of Business Process Management Systems

NASA Astrophysics Data System (ADS)

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.

Inferring Instantaneous, Multivariate and Nonlinear Sensitivities for the Analysis of Feedback Processes in a Dynamical System: Lorenz Model Case Study

NASA Technical Reports Server (NTRS)

Aires, Filipe; Rossow, William B.; Hansen, James E. (Technical Monitor)

2001-01-01

A new approach is presented for the analysis of feedback processes in a nonlinear dynamical system by observing its variations. The new methodology consists of statistical estimates of the sensitivities between all pairs of variables in the system based on a neural network modeling of the dynamical system. The model can then be used to estimate the instantaneous, multivariate and nonlinear sensitivities, which are shown to be essential for the analysis of the feedbacks processes involved in the dynamical system. The method is described and tested on synthetic data from the low-order Lorenz circulation model where the correct sensitivities can be evaluated analytically.

A Mixed Kijima Model Using the Weibull-Based Generalized Renewal Processes

PubMed Central

2015-01-01

Generalized Renewal Processes are useful for approaching the rejuvenation of dynamical systems resulting from planned or unplanned interventions. We present new perspectives for the Generalized Renewal Processes in general and for the Weibull-based Generalized Renewal Processes in particular. Disregarding from literature, we present a mixed Generalized Renewal Processes approach involving Kijima Type I and II models, allowing one to infer the impact of distinct interventions on the performance of the system under study. The first and second theoretical moments of this model are introduced as well as its maximum likelihood estimation and random sampling approaches. In order to illustrate the usefulness of the proposed Weibull-based Generalized Renewal Processes model, some real data sets involving improving, stable, and deteriorating systems are used. PMID:26197222

An Ontology for Identifying Cyber Intrusion Induced Faults in Process Control Systems

NASA Astrophysics Data System (ADS)

Hieb, Jeffrey; Graham, James; Guan, Jian

This paper presents an ontological framework that permits formal representations of process control systems, including elements of the process being controlled and the control system itself. A fault diagnosis algorithm based on the ontological model is also presented. The algorithm can identify traditional process elements as well as control system elements (e.g., IP network and SCADA protocol) as fault sources. When these elements are identified as a likely fault source, the possibility exists that the process fault is induced by a cyber intrusion. A laboratory-scale distillation column is used to illustrate the model and the algorithm. Coupled with a well-defined statistical process model, this fault diagnosis approach provides cyber security enhanced fault diagnosis information to plant operators and can help identify that a cyber attack is underway before a major process failure is experienced.

A Simulation Study Comparing Incineration and Composting in a Mars-Based Advanced Life Support System

NASA Technical Reports Server (NTRS)

Hogan, John; Kang, Sukwon; Cavazzoni, Jim; Levri, Julie; Finn, Cory; Luna, Bernadette (Technical Monitor)

2000-01-01

The objective of this study is to compare incineration and composting in a Mars-based advanced life support (ALS) system. The variables explored include waste pre-processing requirements, reactor sizing and buffer capacities. The study incorporates detailed mathematical models of biomass production and waste processing into an existing dynamic ALS system model. The ALS system and incineration models (written in MATLAB/SIMULINK(c)) were developed at the NASA Ames Research Center. The composting process is modeled using first order kinetics, with different degradation rates for individual waste components (carbohydrates, proteins, fats, cellulose and lignin). The biomass waste streams are generated using modified "Eneray Cascade" crop models, which use light- and dark-cycle temperatures, irradiance, photoperiod, [CO2], planting density, and relative humidity as model inputs. The study also includes an evaluation of equivalent system mass (ESM).

An engineering approach to modelling, decision support and control for sustainable systems.

PubMed

Day, W; Audsley, E; Frost, A R

2008-02-12

Engineering research and development contributes to the advance of sustainable agriculture both through innovative methods to manage and control processes, and through quantitative understanding of the operation of practical agricultural systems using decision models. This paper describes how an engineering approach, drawing on mathematical models of systems and processes, contributes new methods that support decision making at all levels from strategy and planning to tactics and real-time control. The ability to describe the system or process by a simple and robust mathematical model is critical, and the outputs range from guidance to policy makers on strategic decisions relating to land use, through intelligent decision support to farmers and on to real-time engineering control of specific processes. Precision in decision making leads to decreased use of inputs, less environmental emissions and enhanced profitability-all essential to sustainable systems.

APPLICATION OF A NEW LAND-SURFACE, DRY DEPOSITION, AND PBL MODEL IN THE MODELS-3 COMMUNITY MULTI-SCALE AIR QUALITY (CMAQ) MODEL SYSTEM

EPA Science Inventory

Like most air quality modeling systems, CMAQ divides the treatment of meteorological and chemical/transport processes into separate models run sequentially. A potential drawback to this approach is that it creates the illusion that these processes are minimally interdependent an...

Top-level modeling of an als system utilizing object-oriented techniques

NASA Astrophysics Data System (ADS)

Rodriguez, L. F.; Kang, S.; Ting, K. C.

The possible configuration of an Advanced Life Support (ALS) System capable of supporting human life for long-term space missions continues to evolve as researchers investigate potential technologies and configurations. To facilitate the decision process the development of acceptable, flexible, and dynamic mathematical computer modeling tools capable of system level analysis is desirable. Object-oriented techniques have been adopted to develop a dynamic top-level model of an ALS system.This approach has several advantages; among these, object-oriented abstractions of systems are inherently modular in architecture. Thus, models can initially be somewhat simplistic, while allowing for adjustments and improvements. In addition, by coding the model in Java, the model can be implemented via the World Wide Web, greatly encouraging the utilization of the model. Systems analysis is further enabled with the utilization of a readily available backend database containing information supporting the model. The subsystem models of the ALS system model include Crew, Biomass Production, Waste Processing and Resource Recovery, Food Processing and Nutrition, and the Interconnecting Space. Each subsystem model and an overall model have been developed. Presented here is the procedure utilized to develop the modeling tool, the vision of the modeling tool, and the current focus for each of the subsystem models.

Implementation of a GPS-RO data processing system for the KIAPS-LETKF data assimilation system

NASA Astrophysics Data System (ADS)

Kwon, H.; Kang, J.-S.; Jo, Y.; Kang, J. H.

2014-11-01

The Korea Institute of Atmospheric Prediction Systems (KIAPS) has been developing a new global numerical weather prediction model and an advanced data assimilation system. As part of the KIAPS Package for Observation Processing (KPOP) system for data assimilation, preprocessing and quality control modules for bending angle measurements of global positioning system radio occultation (GPS-RO) data have been implemented and examined. GPS-RO data processing system is composed of several steps for checking observation locations, missing values, physical values for Earth radius of curvature, and geoid undulation. An observation-minus-background check is implemented by use of a one-dimensional observational bending angle operator and tangent point drift is also considered in the quality control process. We have tested GPS-RO observations utilized by the Korean Meteorological Administration (KMA) within KPOP, based on both the KMA global model and the National Center for Atmospheric Research (NCAR) Community Atmosphere Model-Spectral Element (CAM-SE) as a model background. Background fields from the CAM-SE model are incorporated for the preparation of assimilation experiments with the KIAPS-LETKF data assimilation system, which has been successfully implemented to a cubed-sphere model with fully unstructured quadrilateral meshes. As a result of data processing, the bending angle departure statistics between observation and background shows significant improvement. Also, the first experiment in assimilating GPS-RO bending angle resulting from KPOP within KIAPS-LETKF shows encouraging results.

Model-Based Verification and Validation of the SMAP Uplink Processes

NASA Technical Reports Server (NTRS)

Khan, M. Omair; Dubos, Gregory F.; Tirona, Joseph; Standley, Shaun

2013-01-01

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 V&V development efforts.

Preparing systems engineering and computing science students in disciplined methods, quantitative, and advanced statistical techniques to improve process performance

NASA Astrophysics Data System (ADS)

McCray, Wilmon Wil L., Jr.

The research was prompted by a need to conduct a study that assesses process improvement, quality management and analytical techniques taught to students in U.S. colleges and universities undergraduate and graduate systems engineering and the computing science discipline (e.g., software engineering, computer science, and information technology) degree programs during their academic training that can be applied to quantitatively manage processes for performance. Everyone involved in executing repeatable processes in the software and systems development lifecycle processes needs to become familiar with the concepts of quantitative management, statistical thinking, process improvement methods and how they relate to process-performance. Organizations are starting to embrace the de facto Software Engineering Institute (SEI) Capability Maturity Model Integration (CMMI RTM) Models as process improvement frameworks to improve business processes performance. High maturity process areas in the CMMI model imply the use of analytical, statistical, quantitative management techniques, and process performance modeling to identify and eliminate sources of variation, continually improve process-performance; reduce cost and predict future outcomes. The research study identifies and provides a detail discussion of the gap analysis findings of process improvement and quantitative analysis techniques taught in U.S. universities systems engineering and computing science degree programs, gaps that exist in the literature, and a comparison analysis which identifies the gaps that exist between the SEI's "healthy ingredients " of a process performance model and courses taught in U.S. universities degree program. The research also heightens awareness that academicians have conducted little research on applicable statistics and quantitative techniques that can be used to demonstrate high maturity as implied in the CMMI models. The research also includes a Monte Carlo simulation optimization model and dashboard that demonstrates the use of statistical methods, statistical process control, sensitivity analysis, quantitative and optimization techniques to establish a baseline and predict future customer satisfaction index scores (outcomes). The American Customer Satisfaction Index (ACSI) model and industry benchmarks were used as a framework for the simulation model.

Simplifying and upscaling water resources systems models that combine natural and engineered components

NASA Astrophysics Data System (ADS)

McIntyre, N.; Keir, G.

2014-12-01

Water supply systems typically encompass components of both natural systems (e.g. catchment runoff, aquifer interception) and engineered systems (e.g. process equipment, water storages and transfers). Many physical processes of varying spatial and temporal scales are contained within these hybrid systems models. The need to aggregate and simplify system components has been recognised for reasons of parsimony and comprehensibility; and the use of probabilistic methods for modelling water-related risks also prompts the need to seek computationally efficient up-scaled conceptualisations. How to manage the up-scaling errors in such hybrid systems models has not been well-explored, compared to research in the hydrological process domain. Particular challenges include the non-linearity introduced by decision thresholds and non-linear relations between water use, water quality, and discharge strategies. Using a case study of a mining region, we explore the nature of up-scaling errors in water use, water quality and discharge, and we illustrate an approach to identification of a scale-adjusted model including an error model. Ways forward for efficient modelling of such complex, hybrid systems are discussed, including interactions with human, energy and carbon systems models.

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

NASA Astrophysics Data System (ADS)

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.

Automated information system for analysis and prediction of production situations in blast furnace plant

NASA Astrophysics Data System (ADS)

Lavrov, V. V.; Spirin, N. A.

2016-09-01

Advances in modern science and technology are inherently connected with the development, implementation, and widespread use of computer systems based on mathematical modeling. Algorithms and computer systems are gaining practical significance solving a range of process tasks in metallurgy of MES-level (Manufacturing Execution Systems - systems controlling industrial process) of modern automated information systems at the largest iron and steel enterprises in Russia. This fact determines the necessity to develop information-modeling systems based on mathematical models that will take into account the physics of the process, the basics of heat and mass exchange, the laws of energy conservation, and also the peculiarities of the impact of technological and standard characteristics of raw materials on the manufacturing process data. Special attention in this set of operations for metallurgic production is devoted to blast-furnace production, as it consumes the greatest amount of energy, up to 50% of the fuel used in ferrous metallurgy. The paper deals with the requirements, structure and architecture of BF Process Engineer's Automated Workstation (AWS), a computer decision support system of MES Level implemented in the ICS of the Blast Furnace Plant at Magnitogorsk Iron and Steel Works. It presents a brief description of main model subsystems as well as assumptions made in the process of mathematical modelling. Application of the developed system allows the engineering and process staff to analyze online production situations in the blast furnace plant, to solve a number of process tasks related to control of heat, gas dynamics and slag conditions of blast-furnace smelting as well as to calculate the optimal composition of blast-furnace slag, which eventually results in increasing technical and economic performance of blast-furnace production.

A situation-response model for intelligent pilot aiding

NASA Technical Reports Server (NTRS)

Schudy, Robert; Corker, Kevin

1987-01-01

An intelligent pilot aiding system needs models of the pilot information processing to provide the computational basis for successful cooperation between the pilot and the aiding system. By combining artificial intelligence concepts with the human information processing model of Rasmussen, an abstraction hierarchy of states of knowledge, processing functions, and shortcuts are developed, which is useful for characterizing the information processing both of the pilot and of the aiding system. This approach is used in the conceptual design of a real time intelligent aiding system for flight crews of transport aircraft. One promising result was the tentative identification of a particular class of information processing shortcuts, from situation characterizations to appropriate responses, as the most important reliable pathway for dealing with complex time critical situations.

Intelligent system of coordination and control for manufacturing

NASA Astrophysics Data System (ADS)

Ciortea, E. M.

2016-08-01

This paper wants shaping an intelligent system monitoring and control, which leads to optimizing material and information flows of the company. The paper presents a model for tracking and control system using intelligent real. Production system proposed for simulation analysis provides the ability to track and control the process in real time. Using simulation models be understood: the influence of changes in system structure, commands influence on the general condition of the manufacturing process conditions influence the behavior of some system parameters. Practical character consists of tracking and real-time control of the technological process. It is based on modular systems analyzed using mathematical models, graphic-analytical sizing, configuration, optimization and simulation.

Evaluation of Models of the Reading Process.

ERIC Educational Resources Information Center

Balajthy, Ernest

A variety of reading process models have been proposed and evaluated in reading research. Traditional approaches to model evaluation specify the workings of a system in a simplified fashion to enable organized, systematic study of the system's components. Following are several statistical methods of model evaluation: (1) empirical research on…

Modular System for Shelves and Coasts (MOSSCO v1.0) - a flexible and multi-component framework for coupled coastal ocean ecosystem modelling

NASA Astrophysics Data System (ADS)

Lemmen, Carsten; Hofmeister, Richard; Klingbeil, Knut; Hassan Nasermoaddeli, M.; Kerimoglu, Onur; Burchard, Hans; Kösters, Frank; Wirtz, Kai W.

2018-03-01

Shelf and coastal sea processes extend from the atmosphere through the water column and into the seabed. These processes reflect intimate interactions between physical, chemical, and biological states on multiple scales. As a consequence, coastal system modelling requires a high and flexible degree of process and domain integration; this has so far hardly been achieved by current model systems. The lack of modularity and flexibility in integrated models hinders the exchange of data and model components and has historically imposed the supremacy of specific physical driver models. We present the Modular System for Shelves and Coasts (MOSSCO; http://www.mossco.de), a novel domain and process coupling system tailored but not limited to the coupling challenges of and applications in the coastal ocean. MOSSCO builds on the Earth System Modeling Framework (ESMF) and on the Framework for Aquatic Biogeochemical Models (FABM). It goes beyond existing technologies by creating a unique level of modularity in both domain and process coupling, including a clear separation of component and basic model interfaces, flexible scheduling of several tens of models, and facilitation of iterative development at the lab and the station and on the coastal ocean scale. MOSSCO is rich in metadata and its concepts are also applicable outside the coastal domain. For coastal modelling, it contains dozens of example coupling configurations and tested set-ups for coupled applications. Thus, MOSSCO addresses the technology needs of a growing marine coastal Earth system community that encompasses very different disciplines, numerical tools, and research questions.

An Extended Petri-Net Based Approach for Supply Chain Process Enactment in Resource-Centric Web Service Environment

NASA Astrophysics Data System (ADS)

Wang, Xiaodong; Zhang, Xiaoyu; Cai, Hongming; Xu, Boyi

Enacting a supply-chain process involves variant partners and different IT systems. REST receives increasing attention for distributed systems with loosely coupled resources. Nevertheless, resource model incompatibilities and conflicts prevent effective process modeling and deployment in resource-centric Web service environment. In this paper, a Petri-net based framework for supply-chain process integration is proposed. A resource meta-model is constructed to represent the basic information of resources. Then based on resource meta-model, XML schemas and documents are derived, which represent resources and their states in Petri-net. Thereafter, XML-net, a high level Petri-net, is employed for modeling control and data flow of process. From process model in XML-net, RESTful services and choreography descriptions are deduced. Therefore, unified resource representation and RESTful services description are proposed for cross-system integration in a more effective way. A case study is given to illustrate the approach and the desirable features of the approach are discussed.

Availability Control for Means of Transport in Decisive Semi-Markov Models of Exploitation Process

NASA Astrophysics Data System (ADS)

Migawa, Klaudiusz

2012-12-01

The issues presented in this research paper refer to problems connected with the control process for exploitation implemented in the complex systems of exploitation for technical objects. The article presents the description of the method concerning the control availability for technical objects (means of transport) on the basis of the mathematical model of the exploitation process with the implementation of the decisive processes by semi-Markov. The presented method means focused on the preparing the decisive for the exploitation process for technical objects (semi-Markov model) and after that specifying the best control strategy (optimal strategy) from among possible decisive variants in accordance with the approved criterion (criteria) of the activity evaluation of the system of exploitation for technical objects. In the presented method specifying the optimal strategy for control availability in the technical objects means a choice of a sequence of control decisions made in individual states of modelled exploitation process for which the function being a criterion of evaluation reaches the extreme value. In order to choose the optimal control strategy the implementation of the genetic algorithm was chosen. The opinions were presented on the example of the exploitation process of the means of transport implemented in the real system of the bus municipal transport. The model of the exploitation process for the means of transports was prepared on the basis of the results implemented in the real transport system. The mathematical model of the exploitation process was built taking into consideration the fact that the model of the process constitutes the homogenous semi-Markov process.

Space Generic Open Avionics Architecture (SGOAA) standard specification

NASA Technical Reports Server (NTRS)

Wray, Richard B.; Stovall, John R.

1994-01-01

This standard establishes the Space Generic Open Avionics Architecture (SGOAA). The SGOAA includes a generic functional model, processing structural model, and an architecture interface model. This standard defines the requirements for applying these models to the development of spacecraft core avionics systems. The purpose of this standard is to provide an umbrella set of requirements for applying the generic architecture models to the design of a specific avionics hardware/software processing system. This standard defines a generic set of system interface points to facilitate identification of critical services and interfaces. It establishes the requirement for applying appropriate low level detailed implementation standards to those interfaces points. The generic core avionics functions and processing structural models provided herein are robustly tailorable to specific system applications and provide a platform upon which the interface model is to be applied.

Using object-oriented analysis techniques to support system testing

NASA Astrophysics Data System (ADS)

Zucconi, Lin

1990-03-01

Testing of real-time control systems can be greatly facilitated by use of object-oriented and structured analysis modeling techniques. This report describes a project where behavior, process and information models built for a real-time control system were used to augment and aid traditional system testing. The modeling techniques used were an adaptation of the Ward/Mellor method for real-time systems analysis and design (Ward85) for object-oriented development. The models were used to simulate system behavior by means of hand execution of the behavior or state model and the associated process (data and control flow) and information (data) models. The information model, which uses an extended entity-relationship modeling technique, is used to identify application domain objects and their attributes (instance variables). The behavioral model uses state-transition diagrams to describe the state-dependent behavior of the object. The process model uses a transformation schema to describe the operations performed on or by the object. Together, these models provide a means of analyzing and specifying a system in terms of the static and dynamic properties of the objects which it manipulates. The various models were used to simultaneously capture knowledge about both the objects in the application domain and the system implementation. Models were constructed, verified against the software as-built and validated through informal reviews with the developer. These models were then hand-executed.

Towards a multi-level approach to the emergence of meaning processes in living systems.

PubMed

Queiroz, João; El-Hani, Charbel Niño

2006-09-01

Any description of the emergence and evolution of different types of meaning processes (semiosis, sensu C.S.Peirce) in living systems must be supported by a theoretical framework which makes it possible to understand the nature and dynamics of such processes. Here we propose that the emergence of semiosis of different kinds can be understood as resulting from fundamental interactions in a triadically-organized hierarchical process. To grasp these interactions, we develop a model grounded on Stanley Salthe's hierarchical structuralism. This model can be applied to establish, in a general sense, a set of theoretical constraints for explaining the instantiation of different kinds of meaning processes (iconic, indexical, symbolic) in semiotic systems. We use it to model a semiotic process in the immune system, namely, B-cell activation, in order to offer insights into the heuristic role it can play in the development of explanations for specific semiotic processes.

Framework for Design of Traceability System on Organic Rice Certification

NASA Astrophysics Data System (ADS)

Purwandoko, P. B.; Seminar, K. B.; Sutrisno; Sugiyanta

2018-05-01

Nowadays, the preferences of organic products such as organic rice have been increased. It because of the people awareness of the healthy and eco-friendly food product consumption has grown. Therefore, it is very important to ensure organic quality of the product that will be produced. Certification is a series of process that holds to ensure the quality of products meets all criteria of organic standards. Currently, there is a problem that traceability information system for organic rice certification has been not available. The current system still conducts manually caused the loss of information during storage process. This paper aimed at developing a traceability framework on organic rice certification process. First, the main discussed issues are organic certification process. Second, unified modeling language (UML) is used to build the model of user requirement in order to develop traceability system for all actors in the certification process. Furthermore, the information captured model along certification process will be explained in this paper. The model shows the information flow that has to be recorded for each actor. Finally, the challenges in the implementation system will be discussed in this paper.

A question driven socio-hydrological modeling process

NASA Astrophysics Data System (ADS)

Garcia, M.; Portney, K.; Islam, S.

2016-01-01

Human and hydrological systems are coupled: human activity impacts the hydrological cycle and hydrological conditions can, but do not always, trigger changes in human systems. Traditional modeling approaches with no feedback between hydrological and human systems typically cannot offer insight into how different patterns of natural variability or human-induced changes may propagate through this coupled system. Modeling of coupled human-hydrological systems, also called socio-hydrological systems, recognizes the potential for humans to transform hydrological systems and for hydrological conditions to influence human behavior. However, this coupling introduces new challenges and existing literature does not offer clear guidance regarding model conceptualization. There are no universally accepted laws of human behavior as there are for the physical systems; furthermore, a shared understanding of important processes within the field is often used to develop hydrological models, but there is no such consensus on the relevant processes in socio-hydrological systems. Here we present a question driven process to address these challenges. Such an approach allows modeling structure, scope and detail to remain contingent on and adaptive to the question context. We demonstrate the utility of this process by revisiting a classic question in water resources engineering on reservoir operation rules: what is the impact of reservoir operation policy on the reliability of water supply for a growing city? Our example model couples hydrological and human systems by linking the rate of demand decreases to the past reliability to compare standard operating policy (SOP) with hedging policy (HP). The model shows that reservoir storage acts both as a buffer for variability and as a delay triggering oscillations around a sustainable level of demand. HP reduces the threshold for action thereby decreasing the delay and the oscillation effect. As a result, per capita demand decreases during periods of water stress are more frequent but less drastic and the additive effect of small adjustments decreases the tendency of the system to overshoot available supplies. This distinction between the two policies was not apparent using a traditional noncoupled model.

Modular modeling system for building distributed hydrologic models with a user-friendly software package

NASA Astrophysics Data System (ADS)

Wi, S.; Ray, P. A.; Brown, C.

2015-12-01

A software package developed to facilitate building distributed hydrologic models in a modular modeling system is presented. The software package provides a user-friendly graphical user interface that eases its practical use in water resources-related research and practice. The modular modeling system organizes the options available to users when assembling models according to the stages of hydrological cycle, such as potential evapotranspiration, soil moisture accounting, and snow/glacier melting processes. The software is intended to be a comprehensive tool that simplifies the task of developing, calibrating, validating, and using hydrologic models through the inclusion of intelligent automation to minimize user effort, and reduce opportunities for error. Processes so far automated include the definition of system boundaries (i.e., watershed delineation), climate and geographical input generation, and parameter calibration. Built-in post-processing toolkits greatly improve the functionality of the software as a decision support tool for water resources system management and planning. Example post-processing toolkits enable streamflow simulation at ungauged sites with predefined model parameters, and perform climate change risk assessment by means of the decision scaling approach. The software is validated through application to watersheds representing a variety of hydrologic regimes.

ISRU System Model Tool: From Excavation to Oxygen Production

NASA Technical Reports Server (NTRS)

Santiago-Maldonado, Edgardo; Linne, Diane L.

2007-01-01

In the late 80's, conceptual designs for an in situ oxygen production plant were documented in a study by Eagle Engineering [1]. In the "Summary of Findings" of this study, it is clearly pointed out that: "reported process mass and power estimates lack a consistent basis to allow comparison." The study goes on to say: "A study to produce a set of process mass, power, and volume requirements on a consistent basis is recommended." Today, approximately twenty years later, as humans plan to return to the moon and venture beyond, the need for flexible up-to-date models of the oxygen extraction production process has become even more clear. Multiple processes for the production of oxygen from lunar regolith are being investigated by NASA, academia, and industry. Three processes that have shown technical merit are molten regolith electrolysis, hydrogen reduction, and carbothermal reduction. These processes have been selected by NASA as the basis for the development of the ISRU System Model Tool (ISMT). In working to develop up-to-date system models for these processes NASA hopes to accomplish the following: (1) help in the evaluation process to select the most cost-effective and efficient process for further prototype development, (2) identify key parameters, (3) optimize the excavation and oxygen production processes, and (4) provide estimates on energy and power requirements, mass and volume of the system, oxygen production rate, mass of regolith required, mass of consumables, and other important parameters. Also, as confidence and high fidelity is achieved with each component's model, new techniques and processes can be introduced and analyzed at a fraction of the cost of traditional hardware development and test approaches. A first generation ISRU System Model Tool has been used to provide inputs to the Lunar Architecture Team studies.

Data Model as an Architectural View

DTIC Science & Technology

2009-10-01

store order - processing system. Logical. The logical data model is an evolution of the conceptual data model towards a data management technology (e.g...online store order - processing system at different stages. Perhaps the first draft was elaborated by the architect during discussion of requirements

Framework for developing hybrid process-driven, artificial neural network and regression models for salinity prediction in river systems

NASA Astrophysics Data System (ADS)

Hunter, Jason M.; Maier, Holger R.; Gibbs, Matthew S.; Foale, Eloise R.; Grosvenor, Naomi A.; Harders, Nathan P.; Kikuchi-Miller, Tahali C.

2018-05-01

Salinity modelling in river systems is complicated by a number of processes, including in-stream salt transport and various mechanisms of saline accession that vary dynamically as a function of water level and flow, often at different temporal scales. Traditionally, salinity models in rivers have either been process- or data-driven. The primary problem with process-based models is that in many instances, not all of the underlying processes are fully understood or able to be represented mathematically. There are also often insufficient historical data to support model development. The major limitation of data-driven models, such as artificial neural networks (ANNs) in comparison, is that they provide limited system understanding and are generally not able to be used to inform management decisions targeting specific processes, as different processes are generally modelled implicitly. In order to overcome these limitations, a generic framework for developing hybrid process and data-driven models of salinity in river systems is introduced and applied in this paper. As part of the approach, the most suitable sub-models are developed for each sub-process affecting salinity at the location of interest based on consideration of model purpose, the degree of process understanding and data availability, which are then combined to form the hybrid model. The approach is applied to a 46 km reach of the Murray River in South Australia, which is affected by high levels of salinity. In this reach, the major processes affecting salinity include in-stream salt transport, accession of saline groundwater along the length of the reach and the flushing of three waterbodies in the floodplain during overbank flows of various magnitudes. Based on trade-offs between the degree of process understanding and data availability, a process-driven model is developed for in-stream salt transport, an ANN model is used to model saline groundwater accession and three linear regression models are used to account for the flushing of the different floodplain storages. The resulting hybrid model performs very well on approximately 3 years of daily validation data, with a Nash-Sutcliffe efficiency (NSE) of 0.89 and a root mean squared error (RMSE) of 12.62 mg L-1 (over a range from approximately 50 to 250 mg L-1). Each component of the hybrid model results in noticeable improvements in model performance corresponding to the range of flows for which they are developed. The predictive performance of the hybrid model is significantly better than that of a benchmark process-driven model (NSE = -0.14, RMSE = 41.10 mg L-1, Gbench index = 0.90) and slightly better than that of a benchmark data-driven (ANN) model (NSE = 0.83, RMSE = 15.93 mg L-1, Gbench index = 0.36). Apart from improved predictive performance, the hybrid model also has advantages over the ANN benchmark model in terms of increased capacity for improving system understanding and greater ability to support management decisions.

Equivalent model construction for a non-linear dynamic system based on an element-wise stiffness evaluation procedure and reduced analysis of the equivalent system

NASA Astrophysics Data System (ADS)

Kim, Euiyoung; Cho, Maenghyo

2017-11-01

In most non-linear analyses, the construction of a system matrix uses a large amount of computation time, comparable to the computation time required by the solving process. If the process for computing non-linear internal force matrices is substituted with an effective equivalent model that enables the bypass of numerical integrations and assembly processes used in matrix construction, efficiency can be greatly enhanced. A stiffness evaluation procedure (STEP) establishes non-linear internal force models using polynomial formulations of displacements. To efficiently identify an equivalent model, the method has evolved such that it is based on a reduced-order system. The reduction process, however, makes the equivalent model difficult to parameterize, which significantly affects the efficiency of the optimization process. In this paper, therefore, a new STEP, E-STEP, is proposed. Based on the element-wise nature of the finite element model, the stiffness evaluation is carried out element-by-element in the full domain. Since the unit of computation for the stiffness evaluation is restricted by element size, and since the computation is independent, the equivalent model can be constructed efficiently in parallel, even in the full domain. Due to the element-wise nature of the construction procedure, the equivalent E-STEP model is easily characterized by design parameters. Various reduced-order modeling techniques can be applied to the equivalent system in a manner similar to how they are applied in the original system. The reduced-order model based on E-STEP is successfully demonstrated for the dynamic analyses of non-linear structural finite element systems under varying design parameters.

Modeling the Hydrologic Processes of a Permeable Pavement System

EPA Science Inventory

A permeable pavement system can capture stormwater to reduce runoff volume and flow rate, improve onsite groundwater recharge, and enhance pollutant controls within the site. A new unit process model for evaluating the hydrologic performance of a permeable pavement system has be...

Development and application of computer assisted optimal method for treatment of femoral neck fracture.

PubMed

Wang, Monan; Zhang, Kai; Yang, Ning

2018-04-09

To help doctors decide their treatment from the aspect of mechanical analysis, the work built a computer assisted optimal system for treatment of femoral neck fracture oriented to clinical application. The whole system encompassed the following three parts: Preprocessing module, finite element mechanical analysis module, post processing module. Preprocessing module included parametric modeling of bone, parametric modeling of fracture face, parametric modeling of fixed screw and fixed position and input and transmission of model parameters. Finite element mechanical analysis module included grid division, element type setting, material property setting, contact setting, constraint and load setting, analysis method setting and batch processing operation. Post processing module included extraction and display of batch processing operation results, image generation of batch processing operation, optimal program operation and optimal result display. The system implemented the whole operations from input of fracture parameters to output of the optimal fixed plan according to specific patient real fracture parameter and optimal rules, which demonstrated the effectiveness of the system. Meanwhile, the system had a friendly interface, simple operation and could improve the system function quickly through modifying single module.

System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling

DOE PAGES

Bacelli, Giorgio; Coe, Ryan; Patterson, David; ...

2017-04-01

Empirically based modeling is an essential aspect of design for a wave energy converter. These models are used in structural, mechanical and control design processes, as well as for performance prediction. The design of experiments and methods used to produce models from collected data have a strong impact on the quality of the model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followedmore » for wave tank testing. The general system identification processes are shown to have a number of advantages. The experimental data is then used to produce multiple models for the dynamics of the device. These models are validated and their performance is compared against one and other. Furthermore, while most models of wave energy converters use a formulation with wave elevation as an input, this study shows that a model using a hull pressure sensor to incorporate the wave excitation phenomenon has better accuracy.« less

System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bacelli, Giorgio; Coe, Ryan; Patterson, David

Empirically based modeling is an essential aspect of design for a wave energy converter. These models are used in structural, mechanical and control design processes, as well as for performance prediction. The design of experiments and methods used to produce models from collected data have a strong impact on the quality of the model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followedmore » for wave tank testing. The general system identification processes are shown to have a number of advantages. The experimental data is then used to produce multiple models for the dynamics of the device. These models are validated and their performance is compared against one and other. Furthermore, while most models of wave energy converters use a formulation with wave elevation as an input, this study shows that a model using a hull pressure sensor to incorporate the wave excitation phenomenon has better accuracy.« less

Evolution of the archaeal and mammalian information processing systems: towards an archaeal model for human disease.

PubMed

Lyu, Zhe; Whitman, William B

2017-01-01

Current evolutionary models suggest that Eukaryotes originated from within Archaea instead of being a sister lineage. To test this model of ancient evolution, we review recent studies and compare the three major information processing subsystems of replication, transcription and translation in the Archaea and Eukaryotes. Our hypothesis is that if the Eukaryotes arose within the archaeal radiation, their information processing systems will appear to be one of kind and not wholly original. Within the Eukaryotes, the mammalian or human systems are emphasized because of their importance in understanding health. Biochemical as well as genetic studies provide strong evidence for the functional similarity of archaeal homologs to the mammalian information processing system and their dissimilarity to the bacterial systems. In many independent instances, a simple archaeal system is functionally equivalent to more elaborate eukaryotic homologs, suggesting that evolution of complexity is likely an central feature of the eukaryotic information processing system. Because fewer components are often involved, biochemical characterizations of the archaeal systems are often easier to interpret. Similarly, the archaeal cell provides a genetically and metabolically simpler background, enabling convenient studies on the complex information processing system. Therefore, Archaea could serve as a parsimonious and tractable host for studying human diseases that arise in the information processing systems.

Simulating fail-stop in asynchronous distributed systems

NASA Technical Reports Server (NTRS)

Sabel, Laura; Marzullo, Keith

1994-01-01

The fail-stop failure model appears frequently in the distributed systems literature. However, in an asynchronous distributed system, the fail-stop model cannot be implemented. In particular, it is impossible to reliably detect crash failures in an asynchronous system. In this paper, we show that it is possible to specify and implement a failure model that is indistinguishable from the fail-stop model from the point of view of any process within an asynchronous system. We give necessary conditions for a failure model to be indistinguishable from the fail-stop model, and derive lower bounds on the amount of process replication needed to implement such a failure model. We present a simple one-round protocol for implementing one such failure model, which we call simulated fail-stop.

Mathematical modeling of heat treatment processes conserving biological activity of plant bioresources

NASA Astrophysics Data System (ADS)

Rodionova, N. S.; Popov, E. S.; Pozhidaeva, E. A.; Pynzar, S. S.; Ryaskina, L. O.

2018-05-01

The aim of this study is to develop a mathematical model of the heat exchange process of LT-processing to estimate the dynamics of temperature field changes and optimize the regime parameters, due to the non-stationarity process, the physicochemical and thermophysical properties of food systems. The application of LT-processing, based on the use of low-temperature modes in thermal culinary processing of raw materials with preliminary vacuum packaging in a polymer heat- resistant film is a promising trend in the development of technics and technology in the catering field. LT-processing application of food raw materials guarantees the preservation of biologically active substances in food environments, which are characterized by a certain thermolability, as well as extend the shelf life and high consumer characteristics of food systems that are capillary-porous bodies. When performing the mathematical modeling of the LT-processing process, the packet of symbolic mathematics “Maple” was used, as well as the mathematical packet flexPDE that uses the finite element method for modeling objects with distributed parameters. The processing of experimental results was evaluated with the help of the developed software in the programming language Python 3.4. To calculate and optimize the parameters of the LT processing process of polycomponent food systems, the differential equation of non-stationary thermal conductivity was used, the solution of which makes it possible to identify the temperature change at any point of the solid at different moments. The present study specifies data on the thermophysical characteristics of the polycomponent food system based on plant raw materials, with the help of which the physico-mathematical model of the LT- processing process has been developed. The obtained mathematical model allows defining of the dynamics of the temperature field in different sections of the LT-processed polycomponent food systems on the basis of calculating the evolution profiles of temperature fields, which enable one to analyze the efficiency of the regime parameters of heat treatment.

Model-based verification and validation of the SMAP uplink processes

NASA Astrophysics Data System (ADS)

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.

Model prototype utilization in the analysis of fault tolerant control and data processing systems

NASA Astrophysics Data System (ADS)

Kovalev, I. V.; Tsarev, R. Yu; Gruzenkin, D. V.; Prokopenko, A. V.; Knyazkov, A. N.; Laptenok, V. D.

2016-04-01

The procedure assessing the profit of control and data processing system implementation is presented in the paper. The reasonability of model prototype creation and analysis results from the implementing of the approach of fault tolerance provision through the inclusion of structural and software assessment redundancy. The developed procedure allows finding the best ratio between the development cost and the analysis of model prototype and earnings from the results of this utilization and information produced. The suggested approach has been illustrated by the model example of profit assessment and analysis of control and data processing system.

Effects of Pump-turbine S-shaped Characteristics on Transient Behaviours: Model Setup

NASA Astrophysics Data System (ADS)

Zeng, Wei; Yang, Jiandong; Hu, Jinhong

2017-04-01

Pumped storage stations undergo numerous transition processes, which make the pump turbines go through the unstable S-shaped region. The hydraulic transient in S-shaped region has normally been investigated through numerical simulations, while field experiments generally involve high risks and are difficult to perform. In this research, a pumped storage model composed of a piping system, two model units, two electrical control systems, a measurement system and a collection system was set up to study the transition processes. The model platform can be applied to simulate almost any hydraulic transition process that occurs in real power stations, such as load rejection, startup, frequency control and grid connection.

Implementation of a GPS-RO data processing system for the KIAPS-LETKF data assimilation system

NASA Astrophysics Data System (ADS)

Kwon, H.; Kang, J.-S.; Jo, Y.; Kang, J. H.

2015-03-01

The Korea Institute of Atmospheric Prediction Systems (KIAPS) has been developing a new global numerical weather prediction model and an advanced data assimilation system. As part of the KIAPS package for observation processing (KPOP) system for data assimilation, preprocessing, and quality control modules for bending-angle measurements of global positioning system radio occultation (GPS-RO) data have been implemented and examined. The GPS-RO data processing system is composed of several steps for checking observation locations, missing values, physical values for Earth radius of curvature, and geoid undulation. An observation-minus-background check is implemented by use of a one-dimensional observational bending-angle operator, and tangent point drift is also considered in the quality control process. We have tested GPS-RO observations utilized by the Korean Meteorological Administration (KMA) within KPOP, based on both the KMA global model and the National Center for Atmospheric Research Community Atmosphere Model with Spectral Element dynamical core (CAM-SE) as a model background. Background fields from the CAM-SE model are incorporated for the preparation of assimilation experiments with the KIAPS local ensemble transform Kalman filter (LETKF) data assimilation system, which has been successfully implemented to a cubed-sphere model with unstructured quadrilateral meshes. As a result of data processing, the bending-angle departure statistics between observation and background show significant improvement. Also, the first experiment in assimilating GPS-RO bending angle from KPOP within KIAPS-LETKF shows encouraging results.

Using the Unified Modelling Language (UML) to guide the systemic description of biological processes and systems.

PubMed

Roux-Rouquié, Magali; Caritey, Nicolas; Gaubert, Laurent; Rosenthal-Sabroux, Camille

2004-07-01

One of the main issues in Systems Biology is to deal with semantic data integration. Previously, we examined the requirements for a reference conceptual model to guide semantic integration based on the systemic principles. In the present paper, we examine the usefulness of the Unified Modelling Language (UML) to describe and specify biological systems and processes. This makes unambiguous representations of biological systems, which would be suitable for translation into mathematical and computational formalisms, enabling analysis, simulation and prediction of these systems behaviours.

Wave processes in the human cardiovascular system: The measuring complex, computing models, and diagnostic analysis

NASA Astrophysics Data System (ADS)

Ganiev, R. F.; Reviznikov, D. L.; Rogoza, A. N.; Slastushenskiy, Yu. V.; Ukrainskiy, L. E.

2017-03-01

A description of a complex approach to investigation of nonlinear wave processes in the human cardiovascular system based on a combination of high-precision methods of measuring a pulse wave, mathematical methods of processing the empirical data, and methods of direct numerical modeling of hemodynamic processes in an arterial tree is given.

Validating the ACE Model for Evaluating Student Performance Using a Teaching-Learning Process Based on Computational Modeling Systems

ERIC Educational Resources Information Center

Louzada, Alexandre Neves; Elia, Marcos da Fonseca; Sampaio, Fábio Ferrentini; Vidal, Andre Luiz Pestana

2014-01-01

The aim of this work is to adapt and test, in a Brazilian public school, the ACE model proposed by Borkulo for evaluating student performance as a teaching-learning process based on computational modeling systems. The ACE model is based on different types of reasoning involving three dimensions. In addition to adapting the model and introducing…

A Decision Tool that Combines Discrete Event Software Process Models with System Dynamics Pieces for Software Development Cost Estimation and Analysis

NASA Technical Reports Server (NTRS)

Mizell, Carolyn Barrett; Malone, Linda

2007-01-01

The development process for a large software development project is very complex and dependent on many variables that are dynamic and interrelated. Factors such as size, productivity and defect injection rates will have substantial impact on the project in terms of cost and schedule. These factors can be affected by the intricacies of the process itself as well as human behavior because the process is very labor intensive. The complex nature of the development process can be investigated with software development process models that utilize discrete event simulation to analyze the effects of process changes. The organizational environment and its effects on the workforce can be analyzed with system dynamics that utilizes continuous simulation. Each has unique strengths and the benefits of both types can be exploited by combining a system dynamics model and a discrete event process model. This paper will demonstrate how the two types of models can be combined to investigate the impacts of human resource interactions on productivity and ultimately on cost and schedule.

Adjustment of automatic control systems of production facilities at coal processing plants using multivariant physico- mathematical models

NASA Astrophysics Data System (ADS)

Evtushenko, V. F.; Myshlyaev, L. P.; Makarov, G. V.; Ivushkin, K. A.; Burkova, E. V.

2016-10-01

The structure of multi-variant physical and mathematical models of control system is offered as well as its application for adjustment of automatic control system (ACS) of production facilities on the example of coal processing plant.

Administrative Decision Making and Resource Allocation.

ERIC Educational Resources Information Center

Sardy, Susan; Sardy, Hyman

This paper considers selected aspects of the systems analysis of administrative decisionmaking regarding resource allocations in an educational system. A model of the instructional materials purchase system is presented. The major components of this model are: environment, input, decision process, conversion structure, conversion process, output,…

Integrating automatic and controlled processes into neurocognitive models of social cognition.

PubMed

Satpute, Ajay B; Lieberman, Matthew D

2006-03-24

Interest in the neural systems underlying social perception has expanded tremendously over the past few decades. However, gaps between behavioral literatures in social perception and neuroscience are still abundant. In this article, we apply the concept of dual-process models to neural systems in an effort to bridge the gap between many of these behavioral studies and neural systems underlying social perception. We describe and provide support for a neural division between reflexive and reflective systems. Reflexive systems correspond to automatic processes and include the amygdala, basal ganglia, ventromedial prefrontal cortex, dorsal anterior cingulate cortex, and lateral temporal cortex. Reflective systems correspond to controlled processes and include lateral prefrontal cortex, posterior parietal cortex, medial prefrontal cortex, rostral anterior cingulate cortex, and the hippocampus and surrounding medial temporal lobe region. This framework is considered to be a working model rather than a finished product. Finally, the utility of this model and its application to other social cognitive domains such as Theory of Mind are discussed.

An integrated model of clinical reasoning: dual-process theory of cognition and metacognition.

PubMed

Marcum, James A

2012-10-01

Clinical reasoning is an important component for providing quality medical care. The aim of the present paper is to develop a model of clinical reasoning that integrates both the non-analytic and analytic processes of cognition, along with metacognition. The dual-process theory of cognition (system 1 non-analytic and system 2 analytic processes) and the metacognition theory are used to develop an integrated model of clinical reasoning. In the proposed model, clinical reasoning begins with system 1 processes in which the clinician assesses a patient's presenting symptoms, as well as other clinical evidence, to arrive at a differential diagnosis. Additional clinical evidence, if necessary, is acquired and analysed utilizing system 2 processes to assess the differential diagnosis, until a clinical decision is made diagnosing the patient's illness and then how best to proceed therapeutically. Importantly, the outcome of these processes feeds back, in terms of metacognition's monitoring function, either to reinforce or to alter cognitive processes, which, in turn, enhances synergistically the clinician's ability to reason quickly and accurately in future consultations. The proposed integrated model has distinct advantages over other models proposed in the literature for explicating clinical reasoning. Moreover, it has important implications for addressing the paradoxical relationship between experience and expertise, as well as for designing a curriculum to teach clinical reasoning skills. © 2012 Blackwell Publishing Ltd.

Colored petri net modeling of small interfering RNA-mediated messenger RNA degradation.

PubMed

Nickaeen, Niloofar; Moein, Shiva; Heidary, Zarifeh; Ghaisari, Jafar

2016-01-01

Mathematical modeling of biological systems is an attractive way for studying complex biological systems and their behaviors. Petri Nets, due to their ability to model systems with various levels of qualitative information, have been wildly used in modeling biological systems in which enough qualitative data may not be at disposal. These nets have been used to answer questions regarding the dynamics of different cell behaviors including the translation process. In one stage of the translation process, the RNA sequence may be degraded. In the process of degradation of RNA sequence, small-noncoding RNA molecules known as small interfering RNA (siRNA) match the target RNA sequence. As a result of this matching, the target RNA sequence is destroyed. In this context, the process of matching and destruction is modeled using Colored Petri Nets (CPNs). The model is constructed using CPNs which allow tokens to have a value or type on them. Thus, CPN is a suitable tool to model string structures in which each element of the string has a different type. Using CPNs, long RNA, and siRNA strings are modeled with a finite set of colors. The model is simulated via CPN Tools. A CPN model of the matching between RNA and siRNA strings is constructed in CPN Tools environment. In previous studies, a network of stoichiometric equations was modeled. However, in this particular study, we modeled the mechanism behind the silencing process. Modeling this kind of mechanisms provides us with a tool to examine the effects of different factors such as mutation or drugs on the process.

Study on intelligent processing system of man-machine interactive garment frame model

NASA Astrophysics Data System (ADS)

Chen, Shuwang; Yin, Xiaowei; Chang, Ruijiang; Pan, Peiyun; Wang, Xuedi; Shi, Shuze; Wei, Zhongqian

2018-05-01

A man-machine interactive garment frame model intelligent processing system is studied in this paper. The system consists of several sensor device, voice processing module, mechanical parts and data centralized acquisition devices. The sensor device is used to collect information on the environment changes brought by the body near the clothes frame model, the data collection device is used to collect the information of the environment change induced by the sensor device, voice processing module is used for speech recognition of nonspecific person to achieve human-machine interaction, mechanical moving parts are used to make corresponding mechanical responses to the information processed by data collection device.it is connected with data acquisition device by a means of one-way connection. There is a one-way connection between sensor device and data collection device, two-way connection between data acquisition device and voice processing module. The data collection device is one-way connection with mechanical movement parts. The intelligent processing system can judge whether it needs to interact with the customer, realize the man-machine interaction instead of the current rigid frame model.

A global "imaging'' view on systems approaches in immunology.

PubMed

Ludewig, Burkhard; Stein, Jens V; Sharpe, James; Cervantes-Barragan, Luisa; Thiel, Volker; Bocharov, Gennady

2012-12-01

The immune system exhibits an enormous complexity. High throughput methods such as the "-omic'' technologies generate vast amounts of data that facilitate dissection of immunological processes at ever finer resolution. Using high-resolution data-driven systems analysis, causal relationships between complex molecular processes and particular immunological phenotypes can be constructed. However, processes in tissues, organs, and the organism itself (so-called higher level processes) also control and regulate the molecular (lower level) processes. Reverse systems engineering approaches, which focus on the examination of the structure, dynamics and control of the immune system, can help to understand the construction principles of the immune system. Such integrative mechanistic models can properly describe, explain, and predict the behavior of the immune system in health and disease by combining both higher and lower level processes. Moving from molecular and cellular levels to a multiscale systems understanding requires the development of methodologies that integrate data from different biological levels into multiscale mechanistic models. In particular, 3D imaging techniques and 4D modeling of the spatiotemporal dynamics of immune processes within lymphoid tissues are central for such integrative approaches. Both dynamic and global organ imaging technologies will be instrumental in facilitating comprehensive multiscale systems immunology analyses as discussed in this review. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Role of System Architecture in Architecture in Developing New Drafting Tools

NASA Astrophysics Data System (ADS)

Sorguç, Arzu Gönenç

In this study, the impact of information technologies in architectural design process is discussed. In this discussion, first the differences/nuances between the concept of software engineering and system architecture are clarified. Then, the design process in engineering, and design process in architecture has been compared by considering 3-D models as the center of design process over which the other disciplines involve the design. It is pointed out that in many high-end engineering applications, 3-D solid models and consequently digital mock-up concept has become a common practice. But, architecture as one of the important customers of CAD systems employing these tools has not started to use these 3-D models. It is shown that the reason of this time lag between architecture and engineering lies behind the tradition of design attitude. Therefore, it is proposed a new design scheme a meta-model to develop an integrated design model being centered on 3-D model. It is also proposed a system architecture to achieve the transformation of architectural design process by replacing 2-D thinking with 3-D thinking. It is stated that in the proposed system architecture, the CAD systems are included and adapted for 3-D architectural design in order to provide interfaces for integration of all possible disciplines to design process. It is also shown that such a change will allow to elaborate the intelligent or smart building concept in future.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology.

PubMed

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N; Mantalaris, Athanasios

2012-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology

PubMed Central

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N.; Mantalaris, Athanasios

2013-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals. PMID:24688682

Modelling and control for laser based welding processes: modern methods of process control to improve quality of laser-based joining methods

NASA Astrophysics Data System (ADS)

Zäh, Ralf-Kilian; Mosbach, Benedikt; Hollwich, Jan; Faupel, Benedikt

2017-02-01

To ensure the competitiveness of manufacturing companies it is indispensable to optimize their manufacturing processes. Slight variations of process parameters and machine settings have only marginally effects on the product quality. Therefore, the largest possible editing window is required. Such parameters are, for example, the movement of the laser beam across the component for the laser keyhole welding. That`s why it is necessary to keep the formation of welding seams within specified limits. Therefore, the quality of laser welding processes is ensured, by using post-process methods, like ultrasonic inspection, or special in-process methods. These in-process systems only achieve a simple evaluation which shows whether the weld seam is acceptable or not. Furthermore, in-process systems use no feedback for changing the control variables such as speed of the laser or adjustment of laser power. In this paper the research group presents current results of the research field of Online Monitoring, Online Controlling and Model predictive controlling in laser welding processes to increase the product quality. To record the characteristics of the welding process, tested online methods are used during the process. Based on the measurement data, a state space model is ascertained, which includes all the control variables of the system. Depending on simulation tools the model predictive controller (MPC) is designed for the model and integrated into an NI-Real-Time-System.

The Australian Computational Earth Systems Simulator

NASA Astrophysics Data System (ADS)

Mora, P.; Muhlhaus, H.; Lister, G.; Dyskin, A.; Place, D.; Appelbe, B.; Nimmervoll, N.; Abramson, D.

2001-12-01

Numerical simulation of the physics and dynamics of the entire earth system offers an outstanding opportunity for advancing earth system science and technology but represents a major challenge due to the range of scales and physical processes involved, as well as the magnitude of the software engineering effort required. However, new simulation and computer technologies are bringing this objective within reach. Under a special competitive national funding scheme to establish new Major National Research Facilities (MNRF), the Australian government together with a consortium of Universities and research institutions have funded construction of the Australian Computational Earth Systems Simulator (ACcESS). The Simulator or computational virtual earth will provide the research infrastructure to the Australian earth systems science community required for simulations of dynamical earth processes at scales ranging from microscopic to global. It will consist of thematic supercomputer infrastructure and an earth systems simulation software system. The Simulator models and software will be constructed over a five year period by a multi-disciplinary team of computational scientists, mathematicians, earth scientists, civil engineers and software engineers. The construction team will integrate numerical simulation models (3D discrete elements/lattice solid model, particle-in-cell large deformation finite-element method, stress reconstruction models, multi-scale continuum models etc) with geophysical, geological and tectonic models, through advanced software engineering and visualization technologies. When fully constructed, the Simulator aims to provide the software and hardware infrastructure needed to model solid earth phenomena including global scale dynamics and mineralisation processes, crustal scale processes including plate tectonics, mountain building, interacting fault system dynamics, and micro-scale processes that control the geological, physical and dynamic behaviour of earth systems. ACcESS represents a part of Australia's contribution to the APEC Cooperation for Earthquake Simulation (ACES) international initiative. Together with other national earth systems science initiatives including the Japanese Earth Simulator and US General Earthquake Model projects, ACcESS aims to provide a driver for scientific advancement and technological breakthroughs including: quantum leaps in understanding of earth evolution at global, crustal, regional and microscopic scales; new knowledge of the physics of crustal fault systems required to underpin the grand challenge of earthquake prediction; new understanding and predictive capabilities of geological processes such as tectonics and mineralisation.

Cox process representation and inference for stochastic reaction-diffusion processes

NASA Astrophysics Data System (ADS)

Schnoerr, David; Grima, Ramon; Sanguinetti, Guido

2016-05-01

Complex behaviour in many systems arises from the stochastic interactions of spatially distributed particles or agents. Stochastic reaction-diffusion processes are widely used to model such behaviour in disciplines ranging from biology to the social sciences, yet they are notoriously difficult to simulate and calibrate to observational data. Here we use ideas from statistical physics and machine learning to provide a solution to the inverse problem of learning a stochastic reaction-diffusion process from data. Our solution relies on a non-trivial connection between stochastic reaction-diffusion processes and spatio-temporal Cox processes, a well-studied class of models from computational statistics. This connection leads to an efficient and flexible algorithm for parameter inference and model selection. Our approach shows excellent accuracy on numeric and real data examples from systems biology and epidemiology. Our work provides both insights into spatio-temporal stochastic systems, and a practical solution to a long-standing problem in computational modelling.

Fault detection of Tennessee Eastman process based on topological features and SVM

NASA Astrophysics Data System (ADS)

Zhao, Huiyang; Hu, Yanzhu; Ai, Xinbo; Hu, Yu; Meng, Zhen

2018-03-01

Fault detection in industrial process is a popular research topic. Although the distributed control system(DCS) has been introduced to monitor the state of industrial process, it still cannot satisfy all the requirements for fault detection of all the industrial systems. In this paper, we proposed a novel method based on topological features and support vector machine(SVM), for fault detection of industrial process. The proposed method takes global information of measured variables into account by complex network model and predicts whether a system has generated some faults or not by SVM. The proposed method can be divided into four steps, i.e. network construction, network analysis, model training and model testing respectively. Finally, we apply the model to Tennessee Eastman process(TEP). The results show that this method works well and can be a useful supplement for fault detection of industrial process.

Application of fuzzy neural network technologies in management of transport and logistics processes in Arctic

NASA Astrophysics Data System (ADS)

Levchenko, N. G.; Glushkov, S. V.; Sobolevskaya, E. Yu; Orlov, A. P.

2018-05-01

The method of modeling the transport and logistics process using fuzzy neural network technologies has been considered. The analysis of the implemented fuzzy neural network model of the information management system of transnational multimodal transportation of the process showed the expediency of applying this method to the management of transport and logistics processes in the Arctic and Subarctic conditions. The modular architecture of this model can be expanded by incorporating additional modules, since the working conditions in the Arctic and the subarctic themselves will present more and more realistic tasks. The architecture allows increasing the information management system, without affecting the system or the method itself. The model has a wide range of application possibilities, including: analysis of the situation and behavior of interacting elements; dynamic monitoring and diagnostics of management processes; simulation of real events and processes; prediction and prevention of critical situations.

The Bilingual Language Interaction Network for Comprehension of Speech*

PubMed Central

Marian, Viorica

2013-01-01

During speech comprehension, bilinguals co-activate both of their languages, resulting in cross-linguistic interaction at various levels of processing. This interaction has important consequences for both the structure of the language system and the mechanisms by which the system processes spoken language. Using computational modeling, we can examine how cross-linguistic interaction affects language processing in a controlled, simulated environment. Here we present a connectionist model of bilingual language processing, the Bilingual Language Interaction Network for Comprehension of Speech (BLINCS), wherein interconnected levels of processing are created using dynamic, self-organizing maps. BLINCS can account for a variety of psycholinguistic phenomena, including cross-linguistic interaction at and across multiple levels of processing, cognate facilitation effects, and audio-visual integration during speech comprehension. The model also provides a way to separate two languages without requiring a global language-identification system. We conclude that BLINCS serves as a promising new model of bilingual spoken language comprehension. PMID:24363602

Global Sensitivity Analysis for Process Identification under Model Uncertainty

NASA Astrophysics Data System (ADS)

Ye, M.; Dai, H.; Walker, A. P.; Shi, L.; Yang, J.

2015-12-01

The environmental system consists of various physical, chemical, and biological processes, and environmental models are always built to simulate these processes and their interactions. For model building, improvement, and validation, it is necessary to identify important processes so that limited resources can be used to better characterize the processes. While global sensitivity analysis has been widely used to identify important processes, the process identification is always based on deterministic process conceptualization that uses a single model for representing a process. However, environmental systems are complex, and it happens often that a single process may be simulated by multiple alternative models. Ignoring the model uncertainty in process identification may lead to biased identification in that identified important processes may not be so in the real world. This study addresses this problem by developing a new method of global sensitivity analysis for process identification. The new method is based on the concept of Sobol sensitivity analysis and model averaging. Similar to the Sobol sensitivity analysis to identify important parameters, our new method evaluates variance change when a process is fixed at its different conceptualizations. The variance considers both parametric and model uncertainty using the method of model averaging. The method is demonstrated using a synthetic study of groundwater modeling that considers recharge process and parameterization process. Each process has two alternative models. Important processes of groundwater flow and transport are evaluated using our new method. The method is mathematically general, and can be applied to a wide range of environmental problems.

Welding process modelling and control

NASA Technical Reports Server (NTRS)

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.

Models for discrete-time self-similar vector processes with application to network traffic

NASA Astrophysics Data System (ADS)

Lee, Seungsin; Rao, Raghuveer M.; Narasimha, Rajesh

2003-07-01

The paper defines self-similarity for vector processes by employing the discrete-time continuous-dilation operation which has successfully been used previously by the authors to define 1-D discrete-time stochastic self-similar processes. To define self-similarity of vector processes, it is required to consider the cross-correlation functions between different 1-D processes as well as the autocorrelation function of each constituent 1-D process in it. System models to synthesize self-similar vector processes are constructed based on the definition. With these systems, it is possible to generate self-similar vector processes from white noise inputs. An important aspect of the proposed models is that they can be used to synthesize various types of self-similar vector processes by choosing proper parameters. Additionally, the paper presents evidence of vector self-similarity in two-channel wireless LAN data and applies the aforementioned systems to simulate the corresponding network traffic traces.

Dynamic modeling and parameter estimation of a radial and loop type distribution system network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jun Qui; Heng Chen; Girgis, A.A.

1993-05-01

This paper presents a new identification approach to three-phase power system modeling and model reduction taking power system network as multi-input, multi-output (MIMO) processes. The model estimate can be obtained in discrete-time input-output form, discrete- or continuous-time state-space variable form, or frequency-domain impedance transfer function matrix form. An algorithm for determining the model structure of this MIMO process is described. The effect of measurement noise on the approach is also discussed. This approach has been applied on a sample system and simulation results are also presented in this paper.

Modeling dynamic processes at stage of formation of parts previously subjected to high-energy laser effects

NASA Astrophysics Data System (ADS)

Efimov, A. E.; Maksarov, V. V.; Timofeev, D. Y.

2018-03-01

The present paper states the impact of a technological system on piece’s roughness and shape accuracy via simulation modeling. For this purpose, a theory was formulated and a mathematical model was generated to justify self-oscillations in a system. The method of oscillations eliminations based on workpiece’s high-energy laser irradiation with the purpose of further processing were suggested in compliance with the adopted theory and model. Modeling the behaviour of a system with the transient phenomenon indicated the tendency of reducing self-oscillations in unstable processing modes, which has a positive effect under the conditions of practical implementation over piece’s roughness and accuracy.

Measurement and modeling of moist processes

NASA Technical Reports Server (NTRS)

Cotton, William; Starr, David; Mitchell, Kenneth; Fleming, Rex; Koch, Steve; Smith, Steve; Mailhot, Jocelyn; Perkey, Don; Tripoli, Greg

1993-01-01

The keynote talk summarized five years of work simulating observed mesoscale convective systems with the RAMS (Regional Atmospheric Modeling System) model. Excellent results are obtained when simulating squall line or other convective systems that are strongly forced by fronts or other lifting mechanisms. Less highly forced systems are difficult to model. The next topic in this colloquium was measurement of water vapor and other constituents of the hydrologic cycle. Impressive accuracy was shown measuring water vapor with both the airborne DIAL (Differential Absorption Lidar) system and the the ground-based Raman Lidar. NMC's plans for initializing land water hydrology in mesoscale models was presented before water vapor measurement concepts for GCIP were discussed. The subject of using satellite data to provide mesoscale moisture and wind analyses was next. Recent activities in modeling of moist processes in mesoscale systems was reported on. These modeling activities at the Canadian Atmospheric Environment Service (AES) used a hydrostatic, variable-resolution grid model. Next the spatial resolution effects of moisture budgets was discussed; in particular, the effects of temporal resolution on heat and moisture budgets for cumulus parameterization. The conclusion of this colloquium was on modeling scale interaction processes.

Application of high-throughput mini-bioreactor system for systematic scale-down modeling, process characterization, and control strategy development.

PubMed

Janakiraman, Vijay; Kwiatkowski, Chris; Kshirsagar, Rashmi; Ryll, Thomas; Huang, Yao-Ming

2015-01-01

High-throughput systems and processes have typically been targeted for process development and optimization in the bioprocessing industry. For process characterization, bench scale bioreactors have been the system of choice. Due to the need for performing different process conditions for multiple process parameters, the process characterization studies typically span several months and are considered time and resource intensive. In this study, we have shown the application of a high-throughput mini-bioreactor system viz. the Advanced Microscale Bioreactor (ambr15(TM) ), to perform process characterization in less than a month and develop an input control strategy. As a pre-requisite to process characterization, a scale-down model was first developed in the ambr system (15 mL) using statistical multivariate analysis techniques that showed comparability with both manufacturing scale (15,000 L) and bench scale (5 L). Volumetric sparge rates were matched between ambr and manufacturing scale, and the ambr process matched the pCO2 profiles as well as several other process and product quality parameters. The scale-down model was used to perform the process characterization DoE study and product quality results were generated. Upon comparison with DoE data from the bench scale bioreactors, similar effects of process parameters on process yield and product quality were identified between the two systems. We used the ambr data for setting action limits for the critical controlled parameters (CCPs), which were comparable to those from bench scale bioreactor data. In other words, the current work shows that the ambr15(TM) system is capable of replacing the bench scale bioreactor system for routine process development and process characterization. © 2015 American Institute of Chemical Engineers.

Cascade process modeling with mechanism-based hierarchical neural networks.

PubMed

Cong, Qiumei; Yu, Wen; Chai, Tianyou

2010-02-01

Cascade process, such as wastewater treatment plant, includes many nonlinear sub-systems and many variables. When the number of sub-systems is big, the input-output relation in the first block and the last block cannot represent the whole process. In this paper we use two techniques to overcome the above problem. Firstly we propose a new neural model: hierarchical neural networks to identify the cascade process; then we use serial structural mechanism model based on the physical equations to connect with neural model. A stable learning algorithm and theoretical analysis are given. Finally, this method is used to model a wastewater treatment plant. Real operational data of wastewater treatment plant is applied to illustrate the modeling approach.

Modeling of Protein Subcellular Localization in Bacteria

NASA Astrophysics Data System (ADS)

Xu, Xiaohua; Kulkarni, Rahul

2006-03-01

Specific subcellular localization of proteins is a vital component of important bacterial processes: e.g. the Min proteins which regulate cell division in E. coli and Spo0J-Soj system which is critical for sporulation in B. subtilis. We examine how the processes of diffusion and membrane attachment contribute to protein subcellular localization for the above systems. We use previous experimental results to suggest minimal models for these processes. For the minimal models, we derive analytic expressions which provide insight into the processes that determine protein subcellular localization. Finally, we present the results of numerical simulations for the systems studied and make connections to the observed experiemental phenomenology.

Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modeled processes were examined and enhanced to suitably represent the extended space and timesca...

Process-driven selection of information systems for healthcare

NASA Astrophysics Data System (ADS)

Mills, Stephen F.; Yeh, Raymond T.; Giroir, Brett P.; Tanik, Murat M.

1995-05-01

Integration of networking and data management technologies such as PACS, RIS and HIS into a healthcare enterprise in a clinically acceptable manner is a difficult problem. Data within such a facility are generally managed via a combination of manual hardcopy systems and proprietary, special-purpose data processing systems. Process modeling techniques have been successfully applied to engineering and manufacturing enterprises, but have not generally been applied to service-based enterprises such as healthcare facilities. The use of process modeling techniques can provide guidance for the placement, configuration and usage of PACS and other informatics technologies within the healthcare enterprise, and thus improve the quality of healthcare. Initial process modeling activities conducted within the Pediatric ICU at Children's Medical Center in Dallas, Texas are described. The ongoing development of a full enterprise- level model for the Pediatric ICU is also described.

Performance modeling & simulation of complex systems (A systems engineering design & analysis approach)

NASA Technical Reports Server (NTRS)

Hall, Laverne

1995-01-01

Modeling of the Multi-mission Image Processing System (MIPS) will be described as an example of the use of a modeling tool to design a distributed system that supports multiple application scenarios. This paper examines: (a) modeling tool selection, capabilities, and operation (namely NETWORK 2.5 by CACl), (b) pointers for building or constructing a model and how the MIPS model was developed, (c) the importance of benchmarking or testing the performance of equipment/subsystems being considered for incorporation the design/architecture, (d) the essential step of model validation and/or calibration using the benchmark results, (e) sample simulation results from the MIPS model, and (f) how modeling and simulation analysis affected the MIPS design process by having a supportive and informative impact.

Dealing with the archetypes development process for a regional EHR system.

PubMed

Santos, M R; Bax, M P; Kalra, D

2012-01-01

This paper aims to present the archetype modelling process used for the Health Department of Minas Gerais State, Brazil (SES/MG), to support building its regional EHR system, and the lessons learned during this process. This study was undertaken within the Minas Gerais project. The EHR system architecture was built assuming the reference model from the ISO 13606 norm. The whole archetype development process took about ten months, coordinated by a clinical team co-ordinated by three health professionals and one systems analyst from the SES/MG. They were supported by around 30 health professionals from the internal SES/MG areas, and 5 systems analysts from the PRODEMGE. Based on a bottom-up approach, the project team used technical interviews and brainstorming sessions to conduct the modelling process. The main steps of the archetype modelling process were identified and described, and 20 archetypes were created. -The set of principles established during the selection of PCS elements helped the clinical team to keep the focus in their objectives;-The initial focus on the archetype structural organization aspects was important;-The data elements identified were subjected to a rigorous analysis aimed at determining the most suitable clinical domain;-Levelling the concepts to accommodate them within the hierarchical levels in the reference model was definitely no easy task, and the use of a mind mapping tool facilitated the modelling process;-Part of the difficulty experienced by the clinical team was related to a view focused on the original forms previously used;-The use of worksheets facilitated the modelling process by health professionals;-It was important to have a health professional that knew about the domain tables and health classifications from the Brazilian Federal Government as member in the clinical team. The archetypes (referencing terminology, domain tables and term lists) provided a favorable condition for the use of a controlled vocabulary between the central repository and the EMR systems and, probably, will increase the chances of preserving the semantics from the knowledge domain. Finally, the reference model from the ISO 13606 norm, along with the archetypes, proved sufficient to meet the specificities for the creation of an EHR system for basic healthcare in a Brazilian state.

Laboratory Modelling of Volcano Plumbing Systems: a review

NASA Astrophysics Data System (ADS)

Galland, Olivier; Holohan, Eoghan P.; van Wyk de Vries, Benjamin; Burchardt, Steffi

2015-04-01

Earth scientists have, since the XIX century, tried to replicate or model geological processes in controlled laboratory experiments. In particular, laboratory modelling has been used study the development of volcanic plumbing systems, which sets the stage for volcanic eruptions. Volcanic plumbing systems involve complex processes that act at length scales of microns to thousands of kilometres and at time scales from milliseconds to billions of years, and laboratory models appear very suitable to address them. This contribution reviews laboratory models dedicated to study the dynamics of volcano plumbing systems (Galland et al., Accepted). The foundation of laboratory models is the choice of relevant model materials, both for rock and magma. We outline a broad range of suitable model materials used in the literature. These materials exhibit very diverse rheological behaviours, so their careful choice is a crucial first step for the proper experiment design. The second step is model scaling, which successively calls upon: (1) the principle of dimensional analysis, and (2) the principle of similarity. The dimensional analysis aims to identify the dimensionless physical parameters that govern the underlying processes. The principle of similarity states that "a laboratory model is equivalent to his geological analogue if the dimensionless parameters identified in the dimensional analysis are identical, even if the values of the governing dimensional parameters differ greatly" (Barenblatt, 2003). The application of these two steps ensures a solid understanding and geological relevance of the laboratory models. In addition, this procedure shows that laboratory models are not designed to exactly mimic a given geological system, but to understand underlying generic processes, either individually or in combination, and to identify or demonstrate physical laws that govern these processes. From this perspective, we review the numerous applications of laboratory models to understand the distinct key features of volcanic plumbing systems: dykes, cone sheets, sills, laccoliths, caldera-related structures, ground deformation, magma/fault interactions, and explosive vents. Barenblatt, G.I., 2003. Scaling. Cambridge University Press, Cambridge. Galland, O., Holohan, E.P., van Wyk de Vries, B., Burchardt, S., Accepted. Laboratory modelling of volcanic plumbing systems: A review, in: Breitkreuz, C., Rocchi, S. (Eds.), Laccoliths, sills and dykes: Physical geology of shallow level magmatic systems. Springer.

Analysis of the packet formation process in packet-switched networks

NASA Astrophysics Data System (ADS)

Meditch, J. S.

Two new queueing system models for the packet formation process in packet-switched telecommunication networks are developed, and their applications in process stability, performance analysis, and optimization studies are illustrated. The first, an M/M/1 queueing system characterization of the process, is a highly aggregated model which is useful for preliminary studies. The second, a marked extension of an earlier M/G/1 model, permits one to investigate stability, performance characteristics, and design of the packet formation process in terms of the details of processor architecture, and hardware and software implementations with processor structure and as many parameters as desired as variables. The two new models together with the earlier M/G/1 characterization span the spectrum of modeling complexity for the packet formation process from basic to advanced.

Method and Tool for Design Process Navigation and Automatic Generation of Simulation Models for Manufacturing Systems

NASA Astrophysics Data System (ADS)

Nakano, Masaru; Kubota, Fumiko; Inamori, Yutaka; Mitsuyuki, Keiji

Manufacturing system designers should concentrate on designing and planning manufacturing systems instead of spending their efforts on creating the simulation models to verify the design. This paper proposes a method and its tool to navigate the designers through the engineering process and generate the simulation model automatically from the design results. The design agent also supports collaborative design projects among different companies or divisions with distributed engineering and distributed simulation techniques. The idea was implemented and applied to a factory planning process.

Representing functions/procedures and processes/structures for analysis of effects of failures on functions and operations

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Leifker, Daniel B.

1991-01-01

Current qualitative device and process models represent only the structure and behavior of physical systems. However, systems in the real world include goal-oriented activities that generally cannot be easily represented using current modeling techniques. An extension of a qualitative modeling system, known as functional modeling, which captures goal-oriented activities explicitly is proposed and how they may be used to support intelligent automation and fault management is shown.

[Systemic inflammation: theoretical and methodological approaches to description of general pathological process model. Part 3. Backgroung for nonsyndromic approach].

PubMed

Gusev, E Yu; Chereshnev, V A

2013-01-01

Theoretical and methodological approaches to description of systemic inflammation as general pathological process are discussed. It is shown, that there is a need of integration of wide range of types of researches to develop a model of systemic inflammation.

Aligning Grammatical Theories and Language Processing Models

ERIC Educational Resources Information Center

Lewis, Shevaun; Phillips, Colin

2015-01-01

We address two important questions about the relationship between theoretical linguistics and psycholinguistics. First, do grammatical theories and language processing models describe separate cognitive systems, or are they accounts of different aspects of the same system? We argue that most evidence is consistent with the one-system view. Second,…

Toward Process-resolving Synthesis and Prediction of Arctic Climate Change Using the Regional Arctic System Model

NASA Astrophysics Data System (ADS)

Maslowski, W.

2017-12-01

The Regional Arctic System Model (RASM) has been developed to better understand the operation of Arctic System at process scale and to improve prediction of its change at a spectrum of time scales. RASM is a pan-Arctic, fully coupled ice-ocean-atmosphere-land model with marine biogeochemistry extension to the ocean and sea ice models. The main goal of our research is to advance a system-level understanding of critical processes and feedbacks in the Arctic and their links with the Earth System. The secondary, an equally important objective, is to identify model needs for new or additional observations to better understand such processes and to help constrain models. Finally, RASM has been used to produce sea ice forecasts for September 2016 and 2017, in contribution to the Sea Ice Outlook of the Sea Ice Prediction Network. Future RASM forecasts, are likely to include increased resolution for model components and ecosystem predictions. Such research is in direct support of the US environmental assessment and prediction needs, including those of the U.S. Navy, Department of Defense, and the recent IARPC Arctic Research Plan 2017-2021. In addition to an overview of RASM technical details, selected model results are presented from a hierarchy of climate models together with available observations in the region to better understand potential oceanic contributions to polar amplification. RASM simulations are analyzed to evaluate model skill in representing seasonal climatology as well as interannual and multi-decadal climate variability and predictions. Selected physical processes and resulting feedbacks are discussed to emphasize the need for fully coupled climate model simulations, high model resolution and sensitivity of simulated sea ice states to scale dependent model parameterizations controlling ice dynamics, thermodynamics and coupling with the atmosphere and ocean.

(abstract) Generic Modeling of a Life Support System for Process Technology Comparisons

NASA Technical Reports Server (NTRS)

Ferrall, J. F.; Seshan, P. K.; Rohatgi, N. K.; Ganapathi, G. B.

1993-01-01

This paper describes a simulation model called the Life Support Systems Analysis Simulation Tool (LiSSA-ST), the spreadsheet program called the Life Support Systems Analysis Trade Tool (LiSSA-TT), and the Generic Modular Flow Schematic (GMFS) modeling technique. Results of using the LiSSA-ST and the LiSSA-TT will be presented for comparing life support systems and process technology options for a Lunar Base and a Mars Exploration Mission.

A simple analytical model for signal amplification by reversible exchange (SABRE) process.

PubMed

Barskiy, Danila A; Pravdivtsev, Andrey N; Ivanov, Konstantin L; Kovtunov, Kirill V; Koptyug, Igor V

2016-01-07

We demonstrate an analytical model for the description of the signal amplification by reversible exchange (SABRE) process. The model relies on a combined analysis of chemical kinetics and the evolution of the nuclear spin system during the hyperpolarization process. The presented model for the first time provides rationale for deciding which system parameters (i.e. J-couplings, relaxation rates, reaction rate constants) have to be optimized in order to achieve higher signal enhancement for a substrate of interest in SABRE experiments.

The use of discrete-event simulation modelling to improve radiation therapy planning processes.

PubMed

Werker, Greg; Sauré, Antoine; French, John; Shechter, Steven

2009-07-01

The planning portion of the radiation therapy treatment process at the British Columbia Cancer Agency is efficient but nevertheless contains room for improvement. The purpose of this study is to show how a discrete-event simulation (DES) model can be used to represent this complex process and to suggest improvements that may reduce the planning time and ultimately reduce overall waiting times. A simulation model of the radiation therapy (RT) planning process was constructed using the Arena simulation software, representing the complexities of the system. Several types of inputs feed into the model; these inputs come from historical data, a staff survey, and interviews with planners. The simulation model was validated against historical data and then used to test various scenarios to identify and quantify potential improvements to the RT planning process. Simulation modelling is an attractive tool for describing complex systems, and can be used to identify improvements to the processes involved. It is possible to use this technique in the area of radiation therapy planning with the intent of reducing process times and subsequent delays for patient treatment. In this particular system, reducing the variability and length of oncologist-related delays contributes most to improving the planning time.

A Model-Based Approach to Developing Your Mission Operations System

NASA Technical Reports Server (NTRS)

Smith, Robert R.; Schimmels, Kathryn A.; Lock, Patricia D; Valerio, Charlene P.

2014-01-01

Model-Based System Engineering (MBSE) is an increasingly popular methodology for designing complex engineering systems. As the use of MBSE has grown, it has begun to be applied to systems that are less hardware-based and more people- and process-based. We describe our approach to incorporating MBSE as a way to streamline development, and how to build a model consisting of core resources, such as requirements and interfaces, that can be adapted and used by new and upcoming projects. By comparing traditional Mission Operations System (MOS) system engineering with an MOS designed via a model, we will demonstrate the benefits to be obtained by incorporating MBSE in system engineering design processes.

The study of thermal processes in control systems of heat consumption of buildings

NASA Astrophysics Data System (ADS)

Tsynaeva, E.; A, Tsynaeva

2017-11-01

The article discusses the main thermal processes in the automated control systems for heat consumption (ACSHC) of buildings, schematic diagrams of these systems, mathematical models used for description of thermal processes in ACSHC. Conducted verification represented by mathematical models. It was found that the efficiency of the operation of ACSHC depend from the external and internal factors. Numerical study of dynamic modes of operation of ACSHC.

A multiresolution method for climate system modeling: application of spherical centroidal Voronoi tessellations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ringler, Todd; Ju, Lili; Gunzburger, Max

2008-11-14

During the next decade and beyond, climate system models will be challenged to resolve scales and processes that are far beyond their current scope. Each climate system component has its prototypical example of an unresolved process that may strongly influence the global climate system, ranging from eddy activity within ocean models, to ice streams within ice sheet models, to surface hydrological processes within land system models, to cloud processes within atmosphere models. These new demands will almost certainly result in the develop of multiresolution schemes that are able, at least regionally, to faithfully simulate these fine-scale processes. Spherical centroidal Voronoimore » tessellations (SCVTs) offer one potential path toward the development of a robust, multiresolution climate system model components. SCVTs allow for the generation of high quality Voronoi diagrams and Delaunay triangulations through the use of an intuitive, user-defined density function. In each of the examples provided, this method results in high-quality meshes where the quality measures are guaranteed to improve as the number of nodes is increased. Real-world examples are developed for the Greenland ice sheet and the North Atlantic ocean. Idealized examples are developed for ocean–ice shelf interaction and for regional atmospheric modeling. In addition to defining, developing, and exhibiting SCVTs, we pair this mesh generation technique with a previously developed finite-volume method. Our numerical example is based on the nonlinear, shallow water equations spanning the entire surface of the sphere. This example is used to elucidate both the potential benefits of this multiresolution method and the challenges ahead.« less

Oxygen production System Models for Lunar ISRU

NASA Technical Reports Server (NTRS)

Santiago-Maldonado, Edgardo

2007-01-01

In-Situ Resource Utilization (ISRU) seeks to make human space exploration feasible; by using available resources from a planet or the moon to produce consumables, parts, and structures that otherwise would be brought from Earth. Producing these in situ reduces the mass of such that must be launched and doing so allows more payload mass' for each mission. The production of oxygen from lunar regolith, for life support and propellant, is one of the tasks being studied under ISRU. NASA is currently funding three processes that have shown technical merit for the production of oxygen from regolith: Molten Salt Electrolysis, Hydrogen Reduction of Ilmenite, and Carbothermal Reduction. The ISRU program is currently developing system models of, the , abovementioned processes to: (1) help NASA in the evaluation process to select the most cost-effective and efficient process for further prototype development, (2) identify key parameters, (3) optimize the oxygen production process, (4) provide estimates on energy and power requirements, mass and volume.of the system, oxygen production rate, mass of regolith required, mass of consumables, and other important parameters, and (5) integrate into the overall end-to-end ISRU system model, which could be integrated with mission architecture models. The oxygen production system model is divided into modules that represent unit operations (e.g., reactor, water electrolyzer, heat exchanger). Each module is modeled theoretically using Excel and Visual Basic for Applications (VBA), and will be validated using experimental data from on-going laboratory work. This modularity (plug-n-play) feature of each unit operation allows the use of the same model on different oxygen production systems simulations resulting in comparable results. In this presentation, preliminary results for mass, power, volume will be presented along with brief description of the oxygen production system model.

On Roles of Models in Information Systems

NASA Astrophysics Data System (ADS)

Sølvberg, Arne

The increasing penetration of computers into all aspects of human activity makes it desirable that the interplay among software, data and the domains where computers are applied is made more transparent. An approach to this end is to explicitly relate the modeling concepts of the domains, e.g., natural science, technology and business, to the modeling concepts of software and data. This may make it simpler to build comprehensible integrated models of the interactions between computers and non-computers, e.g., interaction among computers, people, physical processes, biological processes, and administrative processes. This chapter contains an analysis of various facets of the modeling environment for information systems engineering. The lack of satisfactory conceptual modeling tools seems to be central to the unsatisfactory state-of-the-art in establishing information systems. The chapter contains a proposal for defining a concept of information that is relevant to information systems engineering.

On the analysis of complex biological supply chains: From Process Systems Engineering to Quantitative Systems Pharmacology.

PubMed

Rao, Rohit T; Scherholz, Megerle L; Hartmanshenn, Clara; Bae, Seul-A; Androulakis, Ioannis P

2017-12-05

The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models.

Application of System Operational Effectiveness Methodology to Space Launch Vehicle Development and Operations

NASA Technical Reports Server (NTRS)

Watson, Michael D.; Kelley, Gary W.

2012-01-01

The Department of Defense (DoD) defined System Operational Effectiveness (SOE) model provides an exceptional framework for an affordable approach to the development and operation of space launch vehicles and their supporting infrastructure. The SOE model provides a focal point from which to direct and measure technical effectiveness and process efficiencies of space launch vehicles. The application of the SOE model to a space launch vehicle's development and operation effort leads to very specific approaches and measures that require consideration during the design phase. This paper provides a mapping of the SOE model to the development of space launch vehicles for human exploration by addressing the SOE model key points of measurement including System Performance, System Availability, Technical Effectiveness, Process Efficiency, System Effectiveness, Life Cycle Cost, and Affordable Operational Effectiveness. In addition, the application of the SOE model to the launch vehicle development process is defined providing the unique aspects of space launch vehicle production and operations in lieu of the traditional broader SOE context that examines large quantities of fielded systems. The tailoring and application of the SOE model to space launch vehicles provides some key insights into the operational design drivers, capability phasing, and operational support systems.

Atmospheric Modeling And Sensor Simulation (AMASS) study

NASA Technical Reports Server (NTRS)

Parker, K. G.

1984-01-01

The capabilities of the atmospheric modeling and sensor simulation (AMASS) system were studied in order to enhance them. This system is used in processing atmospheric measurements which are utilized in the evaluation of sensor performance, conducting design-concept simulation studies, and also in the modeling of the physical and dynamical nature of atmospheric processes. The study tasks proposed in order to both enhance the AMASS system utilization and to integrate the AMASS system with other existing equipment to facilitate the analysis of data for modeling and image processing are enumerated. The following array processors were evaluated for anticipated effectiveness and/or improvements in throughput by attachment of the device to the P-e: (1) Floating Point Systems AP-120B; (2) Floating Point Systems 5000; (3) CSP, Inc. MAP-400; (4) Analogic AP500; (5) Numerix MARS-432; and (6) Star Technologies, Inc. ST-100.

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

PubMed

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.

A stochastic hybrid systems based framework for modeling dependent failure processes

PubMed Central

Fan, Mengfei; Zeng, Zhiguo; Zio, Enrico; Kang, Rui; Chen, Ying

2017-01-01

In this paper, we develop a framework to model and analyze systems that are subject to dependent, competing degradation processes and random shocks. The degradation processes are described by stochastic differential equations, whereas transitions between the system discrete states are triggered by random shocks. The modeling is, then, based on Stochastic Hybrid Systems (SHS), whose state space is comprised of a continuous state determined by stochastic differential equations and a discrete state driven by stochastic transitions and reset maps. A set of differential equations are derived to characterize the conditional moments of the state variables. System reliability and its lower bounds are estimated from these conditional moments, using the First Order Second Moment (FOSM) method and Markov inequality, respectively. The developed framework is applied to model three dependent failure processes from literature and a comparison is made to Monte Carlo simulations. The results demonstrate that the developed framework is able to yield an accurate estimation of reliability with less computational costs compared to traditional Monte Carlo-based methods. PMID:28231313

A stochastic hybrid systems based framework for modeling dependent failure processes.

PubMed

Fan, Mengfei; Zeng, Zhiguo; Zio, Enrico; Kang, Rui; Chen, Ying

2017-01-01

In this paper, we develop a framework to model and analyze systems that are subject to dependent, competing degradation processes and random shocks. The degradation processes are described by stochastic differential equations, whereas transitions between the system discrete states are triggered by random shocks. The modeling is, then, based on Stochastic Hybrid Systems (SHS), whose state space is comprised of a continuous state determined by stochastic differential equations and a discrete state driven by stochastic transitions and reset maps. A set of differential equations are derived to characterize the conditional moments of the state variables. System reliability and its lower bounds are estimated from these conditional moments, using the First Order Second Moment (FOSM) method and Markov inequality, respectively. The developed framework is applied to model three dependent failure processes from literature and a comparison is made to Monte Carlo simulations. The results demonstrate that the developed framework is able to yield an accurate estimation of reliability with less computational costs compared to traditional Monte Carlo-based methods.

A model framework to represent plant-physiology and rhizosphere processes in soil profile simulation models

NASA Astrophysics Data System (ADS)

Vanderborght, J.; Javaux, M.; Couvreur, V.; Schröder, N.; Huber, K.; Abesha, B.; Schnepf, A.; Vereecken, H.

2013-12-01

Plant roots play a crucial role in several key processes in soils. Besides their impact on biogeochemical cycles and processes, they also have an important influence on physical processes such as water flow and transport of dissolved substances in soils. Interaction between plant roots and soil processes takes place at different scales and ranges from the scale of an individual root and its directly surrounding soil or rhizosphere over the scale of a root system of an individual plant in a soil profile to the scale of vegetation patterns in landscapes. Simulation models that are used to predict water flow and solute transport in soil-plant systems mainly focus on the individual plant root system scale, parameterize single-root scale phenomena, and aggregate the root system scale to the vegetation scale. In this presentation, we will focus on the transition from the single root to the root system scale. Using high resolution non-invasive imaging techniques and methods, gradients in soil properties and states around roots and their difference from the bulk soil properties could be demonstrated. Recent developments in plant sciences provide new insights in the mechanisms that control water fluxes in plants and in the adaptation of root properties or root plasticity to changing soil conditions. However, since currently used approaches to simulate root water uptake neither resolve these small scale processes nor represent processes and controls within the root system, transferring this information to the whole soil-plant system scale is a challenge. Using a simulation model that describes flow and transport processes in the soil, resolves flow and transport towards individual roots, and describes flow and transport within the root system, such a transfer could be achieved. We present a few examples that illustrate: (i) the impact of changed rhizosphere hydraulic properties, (ii) the effect of root hydraulic properties and root system architecture, (iii) the regulation of plant transpiration by root-zone produced plant hormones, and (iv) the impact of salt accumulation at the soil-root interface on root water uptake. We further propose a framework how this process knowledge could be implemented in root zone simulation models that do not resolve small scale processes.

Capability Maturity Model (CMM) for Software Process Improvements

NASA Technical Reports Server (NTRS)

Ling, Robert Y.

2000-01-01

This slide presentation reviews the Avionic Systems Division's implementation of the Capability Maturity Model (CMM) for improvements in the software development process. The presentation reviews the process involved in implementing the model and the benefits of using CMM to improve the software development process.

Intercomparison of the community multiscale air quality model and CALGRID using process analysis.

PubMed

O'Neill, Susan M; Lamb, Brian K

2005-08-01

This study was designed to examine the similarities and differences between two advanced photochemical air quality modeling systems: EPA Models-3/CMAQ and CALGRID/CALMET. Both modeling systems were applied to an ozone episode that occurred along the I-5 urban corridor in western Washington and Oregon during July 11-14, 1996. Both models employed the same modeling domain and used the same detailed gridded emission inventory. The CMAQ model was run using both the CB-IV and RADM2 chemical mechanisms, while CALGRID was used with the SAPRC-97 chemical mechanism. Outputfrom the Mesoscale Meteorological Model (MM5) employed with observational nudging was used in both models. The two modeling systems, representing three chemical mechanisms and two sets of meteorological inputs, were evaluated in terms of statistical performance measures for both 1- and 8-h average observed ozone concentrations. The results showed that the different versions of the systems were more similar than different, and all versions performed well in the Portland region and downwind of Seattle but performed poorly in the more rural region north of Seattle. Improving the meteorological input into the CALGRID/CALMET system with planetary boundary layer (PBL) parameters from the Models-3/CMAQ meteorology preprocessor (MCIP) improved the performance of the CALGRID/CALMET system. The 8-h ensemble case was often the best performer of all the cases indicating that the models perform better over longer analysis periods. The 1-h ensemble case, derived from all runs, was not necessarily an improvement over the five individual cases, but the standard deviation about the mean provided a measure of overall modeling uncertainty. Process analysis was applied to examine the contribution of the individual processes to the species conservation equation. The process analysis results indicated that the two modeling systems arrive at similar solutions by very different means. Transport rates are faster and exhibit greater fluctuations in the CMAQ cases than in the CALGRID cases, which lead to different placement of the urban ozone plumes. The CALGRID cases, which rely on the SAPRC97 chemical mechanism, exhibited a greater diurnal production/loss cycle of ozone concentrations per hour compared to either the RADM2 or CBIV chemical mechanisms in the CMAQ cases. These results demonstrate the need for specialized process field measurements to confirm whether we are modeling ozone with valid processes.

Multidimensional Data Modeling for Business Process Analysis

NASA Astrophysics Data System (ADS)

Mansmann, Svetlana; Neumuth, Thomas; Scholl, Marc H.

The emerging area of business process intelligence attempts to enhance the analytical capabilities of business process management systems by employing data warehousing and mining technologies. This paper presents an approach to re-engineering the business process modeling in conformity with the multidimensional data model. Since the business process and the multidimensional model are driven by rather different objectives and assumptions, there is no straightforward solution to converging these models.

Chang'E-3 data pre-processing system based on scientific workflow

NASA Astrophysics Data System (ADS)

tan, xu; liu, jianjun; wang, yuanyuan; yan, wei; zhang, xiaoxia; li, chunlai

2016-04-01

The Chang'E-3(CE3) mission have obtained a huge amount of lunar scientific data. Data pre-processing is an important segment of CE3 ground research and application system. With a dramatic increase in the demand of data research and application, Chang'E-3 data pre-processing system(CEDPS) based on scientific workflow is proposed for the purpose of making scientists more flexible and productive by automating data-driven. The system should allow the planning, conduct and control of the data processing procedure with the following possibilities: • describe a data processing task, include:1)define input data/output data, 2)define the data relationship, 3)define the sequence of tasks,4)define the communication between tasks,5)define mathematical formula, 6)define the relationship between task and data. • automatic processing of tasks. Accordingly, Describing a task is the key point whether the system is flexible. We design a workflow designer which is a visual environment for capturing processes as workflows, the three-level model for the workflow designer is discussed:1) The data relationship is established through product tree.2)The process model is constructed based on directed acyclic graph(DAG). Especially, a set of process workflow constructs, including Sequence, Loop, Merge, Fork are compositional one with another.3)To reduce the modeling complexity of the mathematical formulas using DAG, semantic modeling based on MathML is approached. On top of that, we will present how processed the CE3 data with CEDPS.

A Multi Agent Based Approach for Prehospital Emergency Management.

PubMed

Safdari, Reza; Shoshtarian Malak, Jaleh; Mohammadzadeh, Niloofar; Danesh Shahraki, Azimeh

2017-07-01

To demonstrate an architecture to automate the prehospital emergency process to categorize the specialized care according to the situation at the right time for reducing the patient mortality and morbidity. Prehospital emergency process were analyzed using existing prehospital management systems, frameworks and the extracted process were modeled using sequence diagram in Rational Rose software. System main agents were identified and modeled via component diagram, considering the main system actors and by logically dividing business functionalities, finally the conceptual architecture for prehospital emergency management was proposed. The proposed architecture was simulated using Anylogic simulation software. Anylogic Agent Model, State Chart and Process Model were used to model the system. Multi agent systems (MAS) had a great success in distributed, complex and dynamic problem solving environments, and utilizing autonomous agents provides intelligent decision making capabilities.  The proposed architecture presents prehospital management operations. The main identified agents are: EMS Center, Ambulance, Traffic Station, Healthcare Provider, Patient, Consultation Center, National Medical Record System and quality of service monitoring agent. In a critical condition like prehospital emergency we are coping with sophisticated processes like ambulance navigation health care provider and service assignment, consultation, recalling patients past medical history through a centralized EHR system and monitoring healthcare quality in a real-time manner. The main advantage of our work has been the multi agent system utilization. Our Future work will include proposed architecture implementation and evaluation of its impact on patient quality care improvement.

A Multi Agent Based Approach for Prehospital Emergency Management

PubMed Central

Safdari, Reza; Shoshtarian Malak, Jaleh; Mohammadzadeh, Niloofar; Danesh Shahraki, Azimeh

2017-01-01

Objective: To demonstrate an architecture to automate the prehospital emergency process to categorize the specialized care according to the situation at the right time for reducing the patient mortality and morbidity. Methods: Prehospital emergency process were analyzed using existing prehospital management systems, frameworks and the extracted process were modeled using sequence diagram in Rational Rose software. System main agents were identified and modeled via component diagram, considering the main system actors and by logically dividing business functionalities, finally the conceptual architecture for prehospital emergency management was proposed. The proposed architecture was simulated using Anylogic simulation software. Anylogic Agent Model, State Chart and Process Model were used to model the system. Results: Multi agent systems (MAS) had a great success in distributed, complex and dynamic problem solving environments, and utilizing autonomous agents provides intelligent decision making capabilities.  The proposed architecture presents prehospital management operations. The main identified agents are: EMS Center, Ambulance, Traffic Station, Healthcare Provider, Patient, Consultation Center, National Medical Record System and quality of service monitoring agent. Conclusion: In a critical condition like prehospital emergency we are coping with sophisticated processes like ambulance navigation health care provider and service assignment, consultation, recalling patients past medical history through a centralized EHR system and monitoring healthcare quality in a real-time manner. The main advantage of our work has been the multi agent system utilization. Our Future work will include proposed architecture implementation and evaluation of its impact on patient quality care improvement. PMID:28795061

Adaptation, Learning, and the Art of War: A Cybernetic Perspective

DTIC Science & Technology

2014-05-14

William Ross Ashby and contemporary cybernetic thought, the study modeled the adaptive systems as control loops and the processes of adaptive systems...as a Markov process . Using this model , the study concluded that systems would return to the same relative equilibrium point, expressed in terms of...uncertain and ever-changing environment. Drawing from the works of William Ross Ashby and contemporary cybernetic thought, the study modeled the adaptive

Blueprint for Acquisition Reform, Version 3.0

DTIC Science & Technology

2008-07-01

represents a substantial and immediate step forward in establishing the Coast Guard as a model mid-sized federal agency for acquisition processes...Blueprint for Acquisition Reform in the U. S. Coast Guard “The Coast Guard must become the model for mid-sized Federal agency acquisition in process...acquisition (DoD 5000 model >CG Major Systems Acquisition Manual) • Deepwater Program Executive Officer (PEO): System of Systems performance-based

Using Model Based Systems Engineering and the Systems Modeling Language to Develop Space Mission Area Architectures

DTIC Science & Technology

2013-09-01

processes used in space system acquisitions, simply implementing a data exchange specification would not fundamentally improve how information is...instruction, searching existing data sources , gathering and maintaining the data needed, and completing and reviewing the collection of information ...and manage the configuration of all critical program models, processes , and tools used throughout the DoD. Second, mandate a data exchange

Processing speed enhances model-based over model-free reinforcement learning in the presence of high working memory functioning

PubMed Central

Schad, Daniel J.; Jünger, Elisabeth; Sebold, Miriam; Garbusow, Maria; Bernhardt, Nadine; Javadi, Amir-Homayoun; Zimmermann, Ulrich S.; Smolka, Michael N.; Heinz, Andreas; Rapp, Michael A.; Huys, Quentin J. M.

2014-01-01

Theories of decision-making and its neural substrates have long assumed the existence of two distinct and competing valuation systems, variously described as goal-directed vs. habitual, or, more recently and based on statistical arguments, as model-free vs. model-based reinforcement-learning. Though both have been shown to control choices, the cognitive abilities associated with these systems are under ongoing investigation. Here we examine the link to cognitive abilities, and find that individual differences in processing speed covary with a shift from model-free to model-based choice control in the presence of above-average working memory function. This suggests shared cognitive and neural processes; provides a bridge between literatures on intelligence and valuation; and may guide the development of process models of different valuation components. Furthermore, it provides a rationale for individual differences in the tendency to deploy valuation systems, which may be important for understanding the manifold neuropsychiatric diseases associated with malfunctions of valuation. PMID:25566131

Networks for image acquisition, processing and display

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.

1990-01-01

The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.

Simulation modelling of central order processing system under resource sharing strategy in demand-driven garment supply chains

NASA Astrophysics Data System (ADS)

Ma, K.; Thomassey, S.; Zeng, X.

2017-10-01

In this paper we proposed a central order processing system under resource sharing strategy for demand-driven garment supply chains to increase supply chain performances. We examined this system by using simulation technology. Simulation results showed that significant improvement in various performance indicators was obtained in new collaborative model with proposed system.

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rizzo, Davinia B.; Blackburn, Mark R.

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

DOE PAGES

Rizzo, Davinia B.; Blackburn, Mark R.

2018-03-30

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

Understanding Coupled Earth-Surface Processes through Experiments and Models (Invited)

NASA Astrophysics Data System (ADS)

Overeem, I.; Kim, W.

2013-12-01

Traditionally, both numerical models and experiments have been purposefully designed to ';isolate' singular components or certain processes of a larger mountain to deep-ocean interconnected source-to-sink (S2S) transport system. Controlling factors driven by processes outside of the domain of immediate interest were treated and simplified as input or as boundary conditions. Increasingly, earth surface processes scientists appreciate feedbacks and explore these feedbacks with more dynamically coupled approaches to their experiments and models. Here, we discuss key concepts and recent advances made in coupled modeling and experimental setups. In addition, we emphasize challenges and new frontiers to coupled experiments. Experiments have highlighted the important role of self-organization; river and delta systems do not always need to be forced by external processes to change or develop characteristic morphologies. Similarly modeling f.e. has shown that intricate networks in tidal deltas are stable because of the interplay between river avulsions and the tidal current scouring with both processes being important to develop and maintain the dentritic networks. Both models and experiment have demonstrated that seemingly stable systems can be perturbed slightly and show dramatic responses. Source-to-sink models were developed for both the Fly River System in Papua New Guinea and the Waipaoa River in New Zealand. These models pointed to the importance of upstream-downstream effects and enforced our view of the S2S system as a signal transfer and dampening conveyor belt. Coupled modeling showed that deforestation had extreme effects on sediment fluxes draining from the catchment of the Waipaoa River in New Zealand, and that this increase in sediment production rapidly shifted the locus of offshore deposition. The challenge in designing coupled models and experiments is both technological as well as intellectual. Our community advances to make numerical model coupling more straightforward through common interfaces and standardization of time-stepping, model domains and model parameters. At the same time major steps forward require an interdisciplinary approach, wherein the source to sink system contains ecological feedbacks and human actors.

Assessment of effectiveness of geologic isolation systems. Geologic-simulation model for a hypothetical site in the Columbia Plateau. Volume 2: results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foley, M.G.; Petrie, G.M.; Baldwin, A.J.

1982-06-01

This report contains the input data and computer results for the Geologic Simulation Model. This model is described in detail in the following report: Petrie, G.M., et. al. 1981. Geologic Simulation Model for a Hypothetical Site in the Columbia Plateau, Pacific Northwest Laboratory, Richland, Washington. The Geologic Simulation Model is a quasi-deterministic process-response model which simulates, for a million years into the future, the development of the geologic and hydrologic systems of the ground-water basin containing the Pasco Basin. Effects of natural processes on the ground-water hydrologic system are modeled principally by rate equations. The combined effects and synergistic interactionsmore » of different processes are approximated by linear superposition of their effects during discrete time intervals in a stepwise-integration approach.« less

An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health

PubMed Central

Mancy, Rebecca; Brock, Patrick M.; Kao, Rowland R.

2017-01-01

Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows) or groups of hosts (e.g., herds or farms), how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature. PMID:29021983

An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health.

PubMed

Mancy, Rebecca; Brock, Patrick M; Kao, Rowland R

2017-01-01

Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows) or groups of hosts (e.g., herds or farms), how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature.

Geochemistry and the Understanding of Groundwater Systems

NASA Astrophysics Data System (ADS)

Glynn, P. D.; Plummer, L. N.; Weissmann, G. S.; Stute, M.

2009-12-01

Geochemical techniques and concepts have made major contributions to the understanding of groundwater systems. Advances continue to be made through (1) development of measurement and characterization techniques, (2) improvements in computer technology, networks and numerical modeling, (3) investigation of coupled geologic, hydrologic, geochemical and biologic processes, and (4) scaling of individual observations, processes or subsystem models into larger coherent model frameworks. Many applications benefit from progress in these areas, such as: (1) understanding paleoenvironments, in particular paleoclimate, through the use of groundwater archives, (2) assessing the sustainability (recharge and depletion) of groundwater resources, and (3) their vulnerability to contamination, (4) evaluating the capacity and consequences of subsurface waste isolation (e.g. geologic carbon sequestration, nuclear and chemical waste disposal), (5) assessing the potential for mitigation/transformation of anthropogenic contaminants in groundwater systems, and (6) understanding the effect of groundwater lag times in ecosystem-scale responses to natural events, land-use changes, human impacts, and remediation efforts. Obtaining “representative” groundwater samples is difficult and progress in obtaining “representative” samples, or interpreting them, requires new techniques in characterizing groundwater system heterogeneity. Better characterization and simulation of groundwater system heterogeneity (both physical and geochemical) is critical to interpreting the meaning of groundwater “ages”; to understanding and predicting groundwater flow, solute transport, and geochemical evolution; and to quantifying groundwater recharge and discharge processes. Research advances will also come from greater use and progress (1) in the application of environmental tracers to ground water dating and in the analysis of new geochemical tracers (e.g. compound specific isotopic analyses, noble gas isotopes, analyses of natural organic tracers), (2) in inverse geochemical and hydrological modeling, (3) in the understanding and simulation of coupled biological, geological, geochemical and hydrological processes, and (4) in the description and quantification of processes occurring at the boundaries of groundwater systems (e.g. unsaturated zone processes, groundwater/surface water interactions, impacts of changing geomorphology and vegetation). Improvements are needed in the integration of widely diverse information. Better techniques are needed to construct coherent conceptual frameworks from individual observations, simulated or reconstructed information, process models, and intermediate scale models. Iterating between data collection, interpretation, and the application of forward, inverse, and statistical modeling tools is likely to provide progress in this area. Quantifying groundwater system processes by using an open-system thermodynamic approach in a common mass- and energy-flow framework will also facilitate comparison and understanding of diverse processes.

Application of Mathematical and Three-Dimensional Computer Modeling Tools in the Planning of Processes of Fuel and Energy Complexes

NASA Astrophysics Data System (ADS)

Aksenova, Olesya; Nikolaeva, Evgenia; Cehlár, Michal

2017-11-01

This work aims to investigate the effectiveness of mathematical and three-dimensional computer modeling tools in the planning of processes of fuel and energy complexes at the planning and design phase of a thermal power plant (TPP). A solution for purification of gas emissions at the design development phase of waste treatment systems is proposed employing mathematical and three-dimensional computer modeling - using the E-nets apparatus and the development of a 3D model of the future gas emission purification system. Which allows to visualize the designed result, to select and scientifically prove economically feasible technology, as well as to ensure the high environmental and social effect of the developed waste treatment system. The authors present results of a treatment of planned technological processes and the system for purifying gas emissions in terms of E-nets. using mathematical modeling in the Simulink application. What allowed to create a model of a device from the library of standard blocks and to perform calculations. A three-dimensional model of a system for purifying gas emissions has been constructed. It allows to visualize technological processes and compare them with the theoretical calculations at the design phase of a TPP and. if necessary, make adjustments.

Sleep, offline processing, and vocal learning

PubMed Central

Margoliash, Daniel; Schmidt, Marc F

2009-01-01

The study of song learning and the neural song system has provided an important comparative model system for the study of speech and language acquisition. We describe some recent advances in the bird song system, focusing on the role of offline processing including sleep in processing sensory information and in guiding developmental song learning. These observations motivate a new model of the organization and role of the sensory memories in vocal learning. PMID:19906416

DEVS Unified Process for Web-Centric Development and Testing of System of Systems

DTIC Science & Technology

2008-05-20

gathering from the user. Further, methodologies have been developed to generate DEVS models from BPMN /BPEL-based and message-based requirement specifications...27] 3. BPMN /BPEL based system specifications: Business Process Modeling Notation ( BPMN ) [bpm] or Business Process Execution Language (BPEL) provide a...information is stored in .wsdl and .bpel files for BPEL but in proprietary format for BPMN . 4. DoDAF-based requirement specifications: Department of

Industrial process surveillance system

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.; Singer, Ralph M.; Mott, Jack E.

1998-01-01

A system and method for monitoring an industrial process and/or industrial data source. The system includes generating time varying data from industrial data sources, processing the data to obtain time correlation of the data, determining the range of data, determining learned states of normal operation and using these states to generate expected values, comparing the expected values to current actual values to identify a current state of the process closest to a learned, normal state; generating a set of modeled data, and processing the modeled data to identify a data pattern and generating an alarm upon detecting a deviation from normalcy.

Industrial process surveillance system

DOEpatents

Gross, K.C.; Wegerich, S.W.; Singer, R.M.; Mott, J.E.

1998-06-09

A system and method are disclosed for monitoring an industrial process and/or industrial data source. The system includes generating time varying data from industrial data sources, processing the data to obtain time correlation of the data, determining the range of data, determining learned states of normal operation and using these states to generate expected values, comparing the expected values to current actual values to identify a current state of the process closest to a learned, normal state; generating a set of modeled data, and processing the modeled data to identify a data pattern and generating an alarm upon detecting a deviation from normalcy. 96 figs.

Industrial Process Surveillance System

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W; Singer, Ralph M.; Mott, Jack E.

2001-01-30

A system and method for monitoring an industrial process and/or industrial data source. The system includes generating time varying data from industrial data sources, processing the data to obtain time correlation of the data, determining the range of data, determining learned states of normal operation and using these states to generate expected values, comparing the expected values to current actual values to identify a current state of the process closest to a learned, normal state; generating a set of modeled data, and processing the modeled data to identify a data pattern and generating an alarm upon detecting a deviation from normalcy.

The FoReVer Methodology: A MBSE Framework for Formal Verification

NASA Astrophysics Data System (ADS)

Baracchi, Laura; Mazzini, Silvia; Cimatti, Alessandro; Tonetta, Stefano; Garcia, Gerald

2013-08-01

The need for high level of confidence and operational integrity in critical space (software) systems is well recognized in the Space industry and has been addressed so far through rigorous System and Software Development Processes and stringent Verification and Validation regimes. The Model Based Space System Engineering process (MBSSE) derived in the System and Software Functional Requirement Techniques study (SSFRT) focused on the application of model based engineering technologies to support the space system and software development processes, from mission level requirements to software implementation through model refinements and translations. In this paper we report on our work in the ESA-funded FoReVer project where we aim at developing methodological, theoretical and technological support for a systematic approach to the space avionics system development, in phases 0/A/B/C. FoReVer enriches the MBSSE process with contract-based formal verification of properties, at different stages from system to software, through a step-wise refinement approach, with the support for a Software Reference Architecture.

A two-stage predictive model to simultaneous control of trihalomethanes in water treatment plants and distribution systems: adaptability to treatment processes.

PubMed

Domínguez-Tello, Antonio; Arias-Borrego, Ana; García-Barrera, Tamara; Gómez-Ariza, José Luis

2017-10-01

The trihalomethanes (TTHMs) and others disinfection by-products (DBPs) are formed in drinking water by the reaction of chlorine with organic precursors contained in the source water, in two consecutive and linked stages, that starts at the treatment plant and continues in second stage along the distribution system (DS) by reaction of residual chlorine with organic precursors not removed. Following this approach, this study aimed at developing a two-stage empirical model for predicting the formation of TTHMs in the water treatment plant and subsequently their evolution along the water distribution system (WDS). The aim of the two-stage model was to improve the predictive capability for a wide range of scenarios of water treatments and distribution systems. The two-stage model was developed using multiple regression analysis from a database (January 2007 to July 2012) using three different treatment processes (conventional and advanced) in the water supply system of Aljaraque area (southwest of Spain). Then, the new model was validated using a recent database from the same water supply system (January 2011 to May 2015). The validation results indicated no significant difference in the predictive and observed values of TTHM (R 2 0.874, analytical variance <17%). The new model was applied to three different supply systems with different treatment processes and different characteristics. Acceptable predictions were obtained in the three distribution systems studied, proving the adaptability of the new model to the boundary conditions. Finally the predictive capability of the new model was compared with 17 other models selected from the literature, showing satisfactory results prediction and excellent adaptability to treatment processes.

Generic Modeling of a Life Support System for Process Technology Comparison

NASA Technical Reports Server (NTRS)

Ferrall, J. F.; Seshan, P. K.; Rohatgi, N. K.; Ganapathi, G. B.

1993-01-01

This paper describes a simulation model called the Life Support Systems Analysis Simulation Tool (LiSSA-ST), the spreadsheet program called the Life Support Systems Analysis Trade Tool (LiSSA-TT), and the Generic Modular Flow Schematic (GMFS) modeling technique. Results of using the LiSSA-ST and the LiSSA-TT will be presented for comparing life support system and process technology options for a Lunar Base with a crew size of 4 and mission lengths of 90 and 600 days. System configurations to minimize the life support system weight and power are explored.

The evolution and devolution of cognitive control: The costs of deliberation in a competitive world

PubMed Central

Tomlin, Damon; Rand, David G.; Ludvig, Elliot A.; Cohen, Jonathan D.

2015-01-01

Dual-system theories of human cognition, under which fast automatic processes can complement or compete with slower deliberative processes, have not typically been incorporated into larger scale population models used in evolutionary biology, macroeconomics, or sociology. However, doing so may reveal important phenomena at the population level. Here, we introduce a novel model of the evolution of dual-system agents using a resource-consumption paradigm. By simulating agents with the capacity for both automatic and controlled processing, we illustrate how controlled processing may not always be selected over rigid, but rapid, automatic processing. Furthermore, even when controlled processing is advantageous, frequency-dependent effects may exist whereby the spread of control within the population undermines this advantage. As a result, the level of controlled processing in the population can oscillate persistently, or even go extinct in the long run. Our model illustrates how dual-system psychology can be incorporated into population-level evolutionary models, and how such a framework can be used to examine the dynamics of interaction between automatic and controlled processing that transpire over an evolutionary time scale. PMID:26078086

The evolution and devolution of cognitive control: The costs of deliberation in a competitive world.

PubMed

Tomlin, Damon; Rand, David G; Ludvig, Elliot A; Cohen, Jonathan D

2015-06-16

Dual-system theories of human cognition, under which fast automatic processes can complement or compete with slower deliberative processes, have not typically been incorporated into larger scale population models used in evolutionary biology, macroeconomics, or sociology. However, doing so may reveal important phenomena at the population level. Here, we introduce a novel model of the evolution of dual-system agents using a resource-consumption paradigm. By simulating agents with the capacity for both automatic and controlled processing, we illustrate how controlled processing may not always be selected over rigid, but rapid, automatic processing. Furthermore, even when controlled processing is advantageous, frequency-dependent effects may exist whereby the spread of control within the population undermines this advantage. As a result, the level of controlled processing in the population can oscillate persistently, or even go extinct in the long run. Our model illustrates how dual-system psychology can be incorporated into population-level evolutionary models, and how such a framework can be used to examine the dynamics of interaction between automatic and controlled processing that transpire over an evolutionary time scale.

Adaptive Filtering Using Recurrent Neural Networks

NASA Technical Reports Server (NTRS)

Parlos, Alexander G.; Menon, Sunil K.; Atiya, Amir F.

2005-01-01

A method for adaptive (or, optionally, nonadaptive) filtering has been developed for estimating the states of complex process systems (e.g., chemical plants, factories, or manufacturing processes at some level of abstraction) from time series of measurements of system inputs and outputs. The method is based partly on the fundamental principles of the Kalman filter and partly on the use of recurrent neural networks. The standard Kalman filter involves an assumption of linearity of the mathematical model used to describe a process system. The extended Kalman filter accommodates a nonlinear process model but still requires linearization about the state estimate. Both the standard and extended Kalman filters involve the often unrealistic assumption that process and measurement noise are zero-mean, Gaussian, and white. In contrast, the present method does not involve any assumptions of linearity of process models or of the nature of process noise; on the contrary, few (if any) assumptions are made about process models, noise models, or the parameters of such models. In this regard, the method can be characterized as one of nonlinear, nonparametric filtering. The method exploits the unique ability of neural networks to approximate nonlinear functions. In a given case, the process model is limited mainly by limitations of the approximation ability of the neural networks chosen for that case. Moreover, despite the lack of assumptions regarding process noise, the method yields minimum- variance filters. In that they do not require statistical models of noise, the neural- network-based state filters of this method are comparable to conventional nonlinear least-squares estimators.

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

PubMed

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.

Behavior Models for Software Architecture

DTIC Science & Technology

2014-11-01

MP. Existing process modeling frameworks (BPEL, BPMN [Grosskopf et al. 2009], IDEF) usually follow the “single flowchart” paradigm. MP separates...Process: Business Process Modeling using BPMN , Meghan Kiffer Press. HAREL, D., 1987, A Visual Formalism for Complex Systems. Science of Computer

Process models as tools in forestry research and management

Treesearch

Kurt Johnsen; Lisa Samuelson; Robert Teskey; Steve McNulty; Tom Fox

2001-01-01

Forest process models are mathematical representations of biological systems that incorporate our understanding of physiological and ecological mechanisms into predictive algorithms. These models were originally designed and used for research purposes, but are being developed for use in practical forest management. Process models designed for research...

Modeling, simulation, and analysis of optical remote sensing systems

NASA Technical Reports Server (NTRS)

Kerekes, John Paul; Landgrebe, David A.

1989-01-01

Remote Sensing of the Earth's resources from space-based sensors has evolved in the past 20 years from a scientific experiment to a commonly used technological tool. The scientific applications and engineering aspects of remote sensing systems have been studied extensively. However, most of these studies have been aimed at understanding individual aspects of the remote sensing process while relatively few have studied their interrelations. A motivation for studying these interrelationships has arisen with the advent of highly sophisticated configurable sensors as part of the Earth Observing System (EOS) proposed by NASA for the 1990's. Two approaches to investigating remote sensing systems are developed. In one approach, detailed models of the scene, the sensor, and the processing aspects of the system are implemented in a discrete simulation. This approach is useful in creating simulated images with desired characteristics for use in sensor or processing algorithm development. A less complete, but computationally simpler method based on a parametric model of the system is also developed. In this analytical model the various informational classes are parameterized by their spectral mean vector and covariance matrix. These class statistics are modified by models for the atmosphere, the sensor, and processing algorithms and an estimate made of the resulting classification accuracy among the informational classes. Application of these models is made to the study of the proposed High Resolution Imaging Spectrometer (HRIS). The interrelationships among observational conditions, sensor effects, and processing choices are investigated with several interesting results.

Modeling nuclear processes by Simulink

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rashid, Nahrul Khair Alang Md, E-mail: nahrul@iium.edu.my

2015-04-29

Modelling and simulation are essential parts in the study of dynamic systems behaviours. In nuclear engineering, modelling and simulation are important to assess the expected results of an experiment before the actual experiment is conducted or in the design of nuclear facilities. In education, modelling can give insight into the dynamic of systems and processes. Most nuclear processes can be described by ordinary or partial differential equations. Efforts expended to solve the equations using analytical or numerical solutions consume time and distract attention from the objectives of modelling itself. This paper presents the use of Simulink, a MATLAB toolbox softwaremore » that is widely used in control engineering, as a modelling platform for the study of nuclear processes including nuclear reactor behaviours. Starting from the describing equations, Simulink models for heat transfer, radionuclide decay process, delayed neutrons effect, reactor point kinetic equations with delayed neutron groups, and the effect of temperature feedback are used as examples.« less

Towards Automatic Processing of Virtual City Models for Simulations

NASA Astrophysics Data System (ADS)

Piepereit, R.; Schilling, A.; Alam, N.; Wewetzer, M.; Pries, M.; Coors, V.

2016-10-01

Especially in the field of numerical simulations, such as flow and acoustic simulations, the interest in using virtual 3D models to optimize urban systems is increasing. The few instances in which simulations were already carried out in practice have been associated with an extremely high manual and therefore uneconomical effort for the processing of models. Using different ways of capturing models in Geographic Information System (GIS) and Computer Aided Engineering (CAE), increases the already very high complexity of the processing. To obtain virtual 3D models suitable for simulation, we developed a tool for automatic processing with the goal to establish ties between the world of GIS and CAE. In this paper we introduce a way to use Coons surfaces for the automatic processing of building models in LoD2, and investigate ways to simplify LoD3 models in order to reduce unnecessary information for a numerical simulation.

An architecture for object-oriented intelligent control of power systems in space

NASA Technical Reports Server (NTRS)

Holmquist, Sven G.; Jayaram, Prakash; Jansen, Ben H.

1993-01-01

A control system for autonomous distribution and control of electrical power during space missions is being developed. This system should free the astronauts from localizing faults and reconfiguring loads if problems with the power distribution and generation components occur. The control system uses an object-oriented simulation model of the power system and first principle knowledge to detect, identify, and isolate faults. Each power system component is represented as a separate object with knowledge of its normal behavior. The reasoning process takes place at three different levels of abstraction: the Physical Component Model (PCM) level, the Electrical Equivalent Model (EEM) level, and the Functional System Model (FSM) level, with the PCM the lowest level of abstraction and the FSM the highest. At the EEM level the power system components are reasoned about as their electrical equivalents, e.g, a resistive load is thought of as a resistor. However, at the PCM level detailed knowledge about the component's specific characteristics is taken into account. The FSM level models the system at the subsystem level, a level appropriate for reconfiguration and scheduling. The control system operates in two modes, a reactive and a proactive mode, simultaneously. In the reactive mode the control system receives measurement data from the power system and compares these values with values determined through simulation to detect the existence of a fault. The nature of the fault is then identified through a model-based reasoning process using mainly the EEM. Compound component models are constructed at the EEM level and used in the fault identification process. In the proactive mode the reasoning takes place at the PCM level. Individual components determine their future health status using a physical model and measured historical data. In case changes in the health status seem imminent the component warns the control system about its impending failure. The fault isolation process uses the FSM level for its reasoning base.

Event-Driven Process Chains (EPC)

NASA Astrophysics Data System (ADS)

Mendling, Jan

This chapter provides a comprehensive overview of Event-driven Process Chains (EPCs) and introduces a novel definition of EPC semantics. EPCs became popular in the 1990s as a conceptual business process modeling language in the context of reference modeling. Reference modeling refers to the documentation of generic business operations in a model such as service processes in the telecommunications sector, for example. It is claimed that reference models can be reused and adapted as best-practice recommendations in individual companies (see [230, 168, 229, 131, 400, 401, 446, 127, 362, 126]). The roots of reference modeling can be traced back to the Kölner Integrationsmodell (KIM) [146, 147] that was developed in the 1960s and 1970s. In the 1990s, the Institute of Information Systems (IWi) in Saarbrücken worked on a project with SAP to define a suitable business process modeling language to document the processes of the SAP R/3 enterprise resource planning system. There were two results from this joint effort: the definition of EPCs [210] and the documentation of the SAP system in the SAP Reference Model (see [92, 211]). The extensive database of this reference model contains almost 10,000 sub-models: 604 of them non-trivial EPC business process models. The SAP Reference model had a huge impact with several researchers referring to it in their publications (see [473, 235, 127, 362, 281, 427, 415]) as well as motivating the creation of EPC reference models in further domains including computer integrated manufacturing [377, 379], logistics [229] or retail [52]. The wide-spread application of EPCs in business process modeling theory and practice is supported by their coverage in seminal text books for business process management and information systems in general (see [378, 380, 49, 384, 167, 240]). EPCs are frequently used in practice due to a high user acceptance [376] and extensive tool support. Some examples of tools that support EPCs are ARIS Toolset by IDS Scheer AG, AENEIS by ATOSS Software AG, ADONIS by BOC GmbH, Visio by Microsoft Corp., Nautilus by Gedilan Consulting GmbH, and Bonapart by Pikos GmbH. In order to facilitate the interchange of EPC business process models between these tools, there is a tool neutral interchange format called EPC Markup Language (EPML) [283, 285, 286, 287, 289, 290, 291].

Process-oriented integration and coordination of healthcare services across organizational boundaries.

PubMed

Tello-Leal, Edgar; Chiotti, Omar; Villarreal, Pablo David

2012-12-01

The paper presents a methodology that follows a top-down approach based on a Model-Driven Architecture for integrating and coordinating healthcare services through cross-organizational processes to enable organizations providing high quality healthcare services and continuous process improvements. The methodology provides a modeling language that enables organizations conceptualizing an integration agreement, and identifying and designing cross-organizational process models. These models are used for the automatic generation of: the private view of processes each organization should perform to fulfill its role in cross-organizational processes, and Colored Petri Net specifications to implement these processes. A multi-agent system platform provides agents able to interpret Colored Petri-Nets to enable the communication between the Healthcare Information Systems for executing the cross-organizational processes. Clinical documents are defined using the HL7 Clinical Document Architecture. This methodology guarantees that important requirements for healthcare services integration and coordination are fulfilled: interoperability between heterogeneous Healthcare Information Systems; ability to cope with changes in cross-organizational processes; guarantee of alignment between the integrated healthcare service solution defined at the organizational level and the solution defined at technological level; and the distributed execution of cross-organizational processes keeping the organizations autonomy.

Empirical modeling for intelligent, real-time manufacture control

NASA Technical Reports Server (NTRS)

Xu, Xiaoshu

1994-01-01

Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, nonlinear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS's to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System and the Welding Penetration Monitoring System, are discussed in the body of this paper.

Methodology and Results of Mathematical Modelling of Complex Technological Processes

NASA Astrophysics Data System (ADS)

Mokrova, Nataliya V.

2018-03-01

The methodology of system analysis allows us to draw a mathematical model of the complex technological process. The mathematical description of the plasma-chemical process was proposed. The importance the quenching rate and initial temperature decrease time was confirmed for producing the maximum amount of the target product. The results of numerical integration of the system of differential equations can be used to describe reagent concentrations, plasma jet rate and temperature in order to achieve optimal mode of hardening. Such models are applicable both for solving control problems and predicting future states of sophisticated technological systems.

Comprehensive system models: Strategies for evaluation

NASA Technical Reports Server (NTRS)

Field, Christopher; Kutzbach, John E.; Ramanathan, V.; Maccracken, Michael C.

1992-01-01

The task of evaluating comprehensive earth system models is vast involving validations of every model component at every scale of organization, as well as tests of all the individual linkages. Even the most detailed evaluation of each of the component processes and the individual links among them should not, however, engender confidence in the performance of the whole. The integrated earth system is so rich with complex feedback loops, often involving components of the atmosphere, oceans, biosphere, and cryosphere, that it is certain to exhibit emergent properties very difficult to predict from the perspective of a narrow focus on any individual component of the system. Therefore, a substantial share of the task of evaluating comprehensive earth system models must reside at the level of whole system evaluations. Since complete, integrated atmosphere/ ocean/ biosphere/ hydrology models are not yet operational, questions of evaluation must be addressed at the level of the kinds of earth system processes that the models should be competent to simulate, rather than at the level of specific performance criteria. Here, we have tried to identify examples of earth system processes that are difficult to simulate with existing models and that involve a rich enough suite of feedbacks that they are unlikely to be satisfactorily described by highly simplified or toy models. Our purpose is not to specify a checklist of evaluation criteria but to introduce characteristics of the earth system that may present useful opportunities for model testing and, of course, improvement.

System approach to modeling of industrial technologies

NASA Astrophysics Data System (ADS)

Toropov, V. S.; Toropov, E. S.

2018-03-01

The authors presented a system of methods for modeling and improving industrial technologies. The system consists of information and software. The information part is structured information about industrial technologies. The structure has its template. The template has several essential categories used to improve the technological process and eliminate weaknesses in the process chain. The base category is the physical effect that takes place when the technical process proceeds. The programming part of the system can apply various methods of creative search to the content stored in the information part of the system. These methods pay particular attention to energy transformations in the technological process. The system application will allow us to systematize the approach to improving technologies and obtaining new technical solutions.

AgMIP: Next Generation Models and Assessments

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2014-12-01

Next steps in developing next-generation crop models fall into several categories: significant improvements in simulation of important crop processes and responses to stress; extension from simplified crop models to complex cropping systems models; and scaling up from site-based models to landscape, national, continental, and global scales. Crop processes that require major leaps in understanding and simulation in order to narrow uncertainties around how crops will respond to changing atmospheric conditions include genetics; carbon, temperature, water, and nitrogen; ozone; and nutrition. The field of crop modeling has been built on a single crop-by-crop approach. It is now time to create a new paradigm, moving from 'crop' to 'cropping system.' A first step is to set up the simulation technology so that modelers can rapidly incorporate multiple crops within fields, and multiple crops over time. Then the response of these more complex cropping systems can be tested under different sustainable intensification management strategies utilizing the updated simulation environments. Model improvements for diseases, pests, and weeds include developing process-based models for important diseases, frameworks for coupling air-borne diseases to crop models, gathering significantly more data on crop impacts, and enabling the evaluation of pest management strategies. Most smallholder farming in the world involves integrated crop-livestock systems that cannot be represented by crop modeling alone. Thus, next-generation cropping system models need to include key linkages to livestock. Livestock linkages to be incorporated include growth and productivity models for grasslands and rangelands as well as the usual annual crops. There are several approaches for scaling up, including use of gridded models and development of simpler quasi-empirical models for landscape-scale analysis. On the assessment side, AgMIP is leading a community process for coordinated contributions to IPCC AR6 that involves the key modeling groups from around the world including North America, Europe, South America, Sub-Saharan Africa, South Asia, East Asia, and Australia and Oceania. This community process will lead to mutually agreed protocols for coordinated global and regional assessments.

Final Report Collaborative Project. Improving the Representation of Coastal and Estuarine Processes in Earth System Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bryan, Frank; Dennis, John; MacCready, Parker

This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation. The main computational objectives were: 1. To develop computationally efficient, but physically based, parameterizations of estuary and continental shelf mixing processes for use in an Earth System Model (CESM). 2. Tomore » develop a two-way nested regional modeling framework in order to dynamically downscale the climate response of particular coastal ocean regions and to upscale the impact of the regional coastal processes to the global climate in an Earth System Model (CESM). 3. To develop computational infrastructure to enhance the efficiency of data transfer between specific sources and destinations, i.e., a point-to-point communication capability, (used in objective 1) within POP, the ocean component of CESM.« less

Microphysics, Radiation and Surface Processes in the Goddard Cumulus Ensemble (GCE) Model

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Starr, David (Technical Monitor)

2002-01-01

One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (size about 2-200 km). The CRMs also allow explicit interaction between out-going longwave (cooling) and in-coming solar (heating) radiation with clouds. Observations can provide the initial conditions and validation for CRM results. The Goddard Cumulus Ensemble (GCE) Model, a CRM, has been developed and improved at NASA/Goddard Space Flight Center over the past two decades. The GCE model has been used to understand the following: 1) water and energy cycles and their roles in the tropical climate system; 2) the vertical redistribution of ozone and trace constituents by individual clouds and well organized convective systems over various spatial scales; 3) the relationship between the vertical distribution of latent heating (phase change of water) and the large-scale (pre-storm) environment; 4) the validity of assumptions used in the representation of cloud processes in climate and global circulation models; and 5) the representation of cloud microphysical processes and their interaction with radiative forcing over tropical and midlatitude regions. Four-dimensional cloud and latent heating fields simulated from the GCE model have been provided to the TRMM Science Data and Information System (TSDIS) to develop and improve algorithms for retrieving rainfall and latent heating rates for TRMM and the NASA Earth Observing System (EOS). More than 90 referred papers using the GCE model have been published in the last two decades. Also, more than 10 national and international universities are currently using the GCE model for research and teaching. In this talk, five specific major GCE improvements: (1) ice microphysics, (2) longwave and shortwave radiative transfer processes, (3) land surface processes, (4) ocean surface fluxes and (5) ocean mixed layer processes are presented. The performance of these new GCE improvements will be examined. Observations are used for model validation.

A hybrid modeling system designed to support decision making in the optimization of extrusion of inhomogeneous materials

NASA Astrophysics Data System (ADS)

Kryuchkov, D. I.; Zalazinsky, A. G.

2017-12-01

Mathematical models and a hybrid modeling system are developed for the implementation of the experimental-calculation method for the engineering analysis and optimization of the plastic deformation of inhomogeneous materials with the purpose of improving metal-forming processes and machines. The created software solution integrates Abaqus/CAE, a subroutine for mathematical data processing, with the use of Python libraries and the knowledge base. Practical application of the software solution is exemplified by modeling the process of extrusion of a bimetallic billet. The results of the engineering analysis and optimization of the extrusion process are shown, the material damage being monitored.

Mathematical and Computational Modeling in Complex Biological Systems

PubMed Central

Li, Wenyang; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology. PMID:28386558

Mathematical and Computational Modeling in Complex Biological Systems.

PubMed

Ji, Zhiwei; Yan, Ke; Li, Wenyang; Hu, Haigen; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.

Is clinical cognition binary or continuous?

PubMed

Norman, Geoffrey; Monteiro, Sandra; Sherbino, Jonathan

2013-08-01

A dominant theory of clinical reasoning is the so-called "dual processing theory," in which the diagnostic process may proceed through a rapid, unconscious, intuitive process (System 1) or a slow, conceptual, analytical process (System 2). Diagnostic errors are thought to arise primarily from cognitive biases originating in System 1. In this issue, Custers points out that this model is unnecessarily restrictive and that it is more likely that diagnostic tasks may proceed through a variety of mental strategies ranging from "analytical" to "intuitive."The authors of this commentary agree that the notion that System 1 and System 2 processes are somehow in competition and will necessarily lead to different conclusions is unnecessarily restrictive. On the other hand, they argue that there is substantial evidence in support of a dual processing model, and that most objections to dual processing theory can be easily accommodated by simply presuming that both processes operate in concertand that solving any task may rely to varying degrees on both processes.

A model system for targeted drug release triggered by biomolecular signals logically processed through enzyme logic networks.

PubMed

Mailloux, Shay; Halámek, Jan; Katz, Evgeny

2014-03-07

A new Sense-and-Act system was realized by the integration of a biocomputing system, performing analytical processes, with a signal-responsive electrode. A drug-mimicking release process was triggered by biomolecular signals processed by different logic networks, including three concatenated AND logic gates or a 3-input OR logic gate. Biocatalytically produced NADH, controlled by various combinations of input signals, was used to activate the electrochemical system. A biocatalytic electrode associated with signal-processing "biocomputing" systems was electrically connected to another electrode coated with a polymer film, which was dissolved upon the formation of negative potential releasing entrapped drug-mimicking species, an enzyme-antibody conjugate, operating as a model for targeted immune-delivery and consequent "prodrug" activation. The system offers great versatility for future applications in controlled drug release and personalized medicine.

An Adaptive Technique for a Redundant-Sensor Navigation System. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chien, T. T.

1972-01-01

An on-line adaptive technique is developed to provide a self-contained redundant-sensor navigation system with a capability to utilize its full potentiality in reliability and performance. The gyro navigation system is modeled as a Gauss-Markov process, with degradation modes defined as changes in characteristics specified by parameters associated with the model. The adaptive system is formulated as a multistage stochastic process: (1) a detection system, (2) an identification system and (3) a compensation system. It is shown that the sufficient statistics for the partially observable process in the detection and identification system is the posterior measure of the state of degradation, conditioned on the measurement history.

Nonlinear modeling and dynamic analysis of a hydro-turbine governing system in the process of sudden load increase transient

NASA Astrophysics Data System (ADS)

Li, Huanhuan; Chen, Diyi; Zhang, Hao; Wang, Feifei; Ba, Duoduo

2016-12-01

In order to study the nonlinear dynamic behaviors of a hydro-turbine governing system in the process of sudden load increase transient, we establish a novel nonlinear dynamic model of the hydro-turbine governing system which considers the elastic water-hammer model of the penstock and the second-order model of the generator. The six nonlinear dynamic transfer coefficients of the hydro-turbine are innovatively proposed by utilizing internal characteristics and analyzing the change laws of the characteristic parameters of the hydro-turbine governing system. Moreover, from the point of view of engineering, the nonlinear dynamic behaviors of the above system are exhaustively investigated based on bifurcation diagrams and time waveforms. More importantly, all of the above analyses supply theoretical basis for allowing a hydropower station to maintain a stable operation in the process of sudden load increase transient.

Simulation Framework for Teaching in Modeling and Simulation Areas

ERIC Educational Resources Information Center

De Giusti, Marisa Raquel; Lira, Ariel Jorge; Villarreal, Gonzalo Lujan

2008-01-01

Simulation is the process of executing a model that describes a system with enough detail; this model has its entities, an internal state, some input and output variables and a list of processes bound to these variables. Teaching a simulation language such as general purpose simulation system (GPSS) is always a challenge, because of the way it…

Implementation of the Business Process Modelling Notation (BPMN) in the modelling of anatomic pathology processes.

PubMed

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.

Implementation of the Business Process Modelling Notation (BPMN) in the modelling of anatomic pathology processes

PubMed Central

Rojo, Marcial García; Rolón, Elvira; Calahorra, Luis; García, Felix Óscar; Sánchez, Rosario Paloma; Ruiz, Francisco; Ballester, Nieves; Armenteros, María; Rodríguez, Teresa; Espartero, Rafael Martín

2008-01-01

Background 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. Methods 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. Results 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. Conclusion 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. PMID:18673511

A secured e-tendering modeling using misuse case approach

NASA Astrophysics Data System (ADS)

Mohd, Haslina; Robie, Muhammad Afdhal Muhammad; Baharom, Fauziah; Darus, Norida Muhd; Saip, Mohamed Ali; Yasin, Azman

2016-08-01

Major risk factors relating to electronic transactions may lead to destructive impacts on trust and transparency in the process of tendering. Currently, electronic tendering (e-tendering) systems still remain uncertain in issues relating to legal and security compliance and most importantly it has an unclear security framework. Particularly, the available systems are lacking in addressing integrity, confidentiality, authentication, and non-repudiation in e-tendering requirements. Thus, one of the challenges in developing an e-tendering system is to ensure the system requirements include the function for secured and trusted environment. Therefore, this paper aims to model a secured e-tendering system using misuse case approach. The modeling process begins with identifying the e-tendering process, which is based on the Australian Standard Code of Tendering (AS 4120-1994). It is followed by identifying security threats and their countermeasure. Then, the e-tendering was modelled using misuse case approach. The model can contribute to e-tendering developers and also to other researchers or experts in the e-tendering domain.

User's guide to the Reliability Estimation System Testbed (REST)

NASA Technical Reports Server (NTRS)

Nicol, David M.; Palumbo, Daniel L.; Rifkin, Adam

1992-01-01

The Reliability Estimation System Testbed is an X-window based reliability modeling tool that was created to explore the use of the Reliability Modeling Language (RML). RML was defined to support several reliability analysis techniques including modularization, graphical representation, Failure Mode Effects Simulation (FMES), and parallel processing. These techniques are most useful in modeling large systems. Using modularization, an analyst can create reliability models for individual system components. The modules can be tested separately and then combined to compute the total system reliability. Because a one-to-one relationship can be established between system components and the reliability modules, a graphical user interface may be used to describe the system model. RML was designed to permit message passing between modules. This feature enables reliability modeling based on a run time simulation of the system wide effects of a component's failure modes. The use of failure modes effects simulation enhances the analyst's ability to correctly express system behavior when using the modularization approach to reliability modeling. To alleviate the computation bottleneck often found in large reliability models, REST was designed to take advantage of parallel processing on hypercube processors.

Development and Application of a Process-based River System Model at a Continental Scale

NASA Astrophysics Data System (ADS)

Kim, S. S. H.; Dutta, D.; Vaze, J.; Hughes, J. D.; Yang, A.; Teng, J.

2014-12-01

Existing global and continental scale river models, mainly designed for integrating with global climate model, are of very course spatial resolutions and they lack many important hydrological processes, such as overbank flow, irrigation diversion, groundwater seepage/recharge, which operate at a much finer resolution. Thus, these models are not suitable for producing streamflow forecast at fine spatial resolution and water accounts at sub-catchment levels, which are important for water resources planning and management at regional and national scale. A large-scale river system model has been developed and implemented for water accounting in Australia as part of the Water Information Research and Development Alliance between Australia's Bureau of Meteorology (BoM) and CSIRO. The model, developed using node-link architecture, includes all major hydrological processes, anthropogenic water utilisation and storage routing that influence the streamflow in both regulated and unregulated river systems. It includes an irrigation model to compute water diversion for irrigation use and associated fluxes and stores and a storage-based floodplain inundation model to compute overbank flow from river to floodplain and associated floodplain fluxes and stores. An auto-calibration tool has been built within the modelling system to automatically calibrate the model in large river systems using Shuffled Complex Evolution optimiser and user-defined objective functions. The auto-calibration tool makes the model computationally efficient and practical for large basin applications. The model has been implemented in several large basins in Australia including the Murray-Darling Basin, covering more than 2 million km2. The results of calibration and validation of the model shows highly satisfactory performance. The model has been operalisationalised in BoM for producing various fluxes and stores for national water accounting. This paper introduces this newly developed river system model describing the conceptual hydrological framework, methods used for representing different hydrological processes in the model and the results and evaluation of the model performance. The operational implementation of the model for water accounting is discussed.

SEIPS-based process modeling in primary care.

PubMed

Wooldridge, Abigail R; Carayon, Pascale; Hundt, Ann Schoofs; Hoonakker, Peter L T

2017-04-01

Process mapping, often used as part of the human factors and systems engineering approach to improve care delivery and outcomes, should be expanded to represent the complex, interconnected sociotechnical aspects of health care. Here, we propose a new sociotechnical process modeling method to describe and evaluate processes, using the SEIPS model as the conceptual framework. The method produces a process map and supplementary table, which identify work system barriers and facilitators. In this paper, we present a case study applying this method to three primary care processes. We used purposeful sampling to select staff (care managers, providers, nurses, administrators and patient access representatives) from two clinics to observe and interview. We show the proposed method can be used to understand and analyze healthcare processes systematically and identify specific areas of improvement. Future work is needed to assess usability and usefulness of the SEIPS-based process modeling method and further refine it. Copyright © 2016 Elsevier Ltd. All rights reserved.

SEIPS-Based Process Modeling in Primary Care

PubMed Central

Wooldridge, Abigail R.; Carayon, Pascale; Hundt, Ann Schoofs; Hoonakker, Peter

2016-01-01

Process mapping, often used as part of the human factors and systems engineering approach to improve care delivery and outcomes, should be expanded to represent the complex, interconnected sociotechnical aspects of health care. Here, we propose a new sociotechnical process modeling method to describe and evaluate processes, using the SEIPS model as the conceptual framework. The method produces a process map and supplementary table, which identify work system barriers and facilitators. In this paper, we present a case study applying this method to three primary care processes. We used purposeful sampling to select staff (care managers, providers, nurses, administrators and patient access representatives) from two clinics to observe and interview. We show the proposed method can be used to understand and analyze healthcare processes systematically and identify specific areas of improvement. Future work is needed to assess usability and usefulness of the SEIPS-based process modeling method and further refine it. PMID:28166883

Using system dynamics for collaborative design: a case study

PubMed Central

Elf, Marie; Putilova, Mariya; von Koch, Lena; Öhrn, Kerstin

2007-01-01

Background In order to facilitate the collaborative design, system dynamics (SD) with a group modelling approach was used in the early stages of planning a new stroke unit. During six workshops a SD model was created in a multiprofessional group. Aim To explore to which extent and how the use of system dynamics contributed to the collaborative design process. Method A case study was conducted using several data sources. Results SD supported a collaborative design, by facilitating an explicit description of stroke care process, a dialogue and a joint understanding. The construction of the model obliged the group to conceptualise the stroke care and experimentation with the model gave the opportunity to reflect on care. Conclusion SD facilitated the collaborative design process and should be integrated in the early stages of the design process as a quality improvement tool. PMID:17683519

Model-Based Systems Engineering for Capturing Mission Architecture System Processes with an Application Case Study - Orion Flight Test 1

NASA Technical Reports Server (NTRS)

Bonanne, Kevin H.

2011-01-01

Model-based Systems Engineering (MBSE) is an emerging methodology that can be leveraged to enhance many system development processes. MBSE allows for the centralization of an architecture description that would otherwise be stored in various locations and formats, thus simplifying communication among the project stakeholders, inducing commonality in representation, and expediting report generation. This paper outlines the MBSE approach taken to capture the processes of two different, but related, architectures by employing the Systems Modeling Language (SysML) as a standard for architecture description and the modeling tool MagicDraw. The overarching goal of this study was to demonstrate the effectiveness of MBSE as a means of capturing and designing a mission systems architecture. The first portion of the project focused on capturing the necessary system engineering activities that occur when designing, developing, and deploying a mission systems architecture for a space mission. The second part applies activities from the first to an application problem - the system engineering of the Orion Flight Test 1 (OFT-1) End-to-End Information System (EEIS). By modeling the activities required to create a space mission architecture and then implementing those activities in an application problem, the utility of MBSE as an approach to systems engineering can be demonstrated.

Development of a Water Recovery System Resource Tracking Model

NASA Technical Reports Server (NTRS)

Chambliss, Joe; Stambaugh, Imelda; Sargusingh, Miriam; Shull, Sarah; Moore, Michael

2015-01-01

A simulation model has been developed to track water resources in an exploration vehicle using Regenerative Life Support (RLS) systems. The Resource Tracking Model (RTM) integrates the functions of all the vehicle components that affect the processing and recovery of water during simulated missions. The approach used in developing the RTM enables its use as part of a complete vehicle simulation for real time mission studies. Performance data for the components in the RTM is focused on water processing. The data provided to the model has been based on the most recent information available regarding the technology of the component. This paper will describe the process of defining the RLS system to be modeled, the way the modeling environment was selected, and how the model has been implemented. Results showing how the RLS components exchange water are provided in a set of test cases.

Development of a Water Recovery System Resource Tracking Model

NASA Technical Reports Server (NTRS)

Chambliss, Joe; Stambaugh, Imelda; Sarguishm, Miriam; Shull, Sarah; Moore, Michael

2014-01-01

A simulation model has been developed to track water resources in an exploration vehicle using regenerative life support (RLS) systems. The model integrates the functions of all the vehicle components that affect the processing and recovery of water during simulated missions. The approach used in developing the model results in the RTM being a part of of a complete vehicle simulation that can be used in real time mission studies. Performance data for the variety of components in the RTM is focused on water processing and has been defined based on the most recent information available for the technology of the component. This paper will describe the process of defining the RLS system to be modeled and then the way the modeling environment was selected and how the model has been implemented. Results showing how the variety of RLS components exchange water are provided in a set of test cases.

System-level modeling of acetone-butanol-ethanol fermentation.

PubMed

Liao, Chen; Seo, Seung-Oh; Lu, Ting

2016-05-01

Acetone-butanol-ethanol (ABE) fermentation is a metabolic process of clostridia that produces bio-based solvents including butanol. It is enabled by an underlying metabolic reaction network and modulated by cellular gene regulation and environmental cues. Mathematical modeling has served as a valuable strategy to facilitate the understanding, characterization and optimization of this process. In this review, we highlight recent advances in system-level, quantitative modeling of ABE fermentation. We begin with an overview of integrative processes underlying the fermentation. Next we survey modeling efforts including early simple models, models with a systematic metabolic description, and those incorporating metabolism through simple gene regulation. Particular focus is given to a recent system-level model that integrates the metabolic reactions, gene regulation and environmental cues. We conclude by discussing the remaining challenges and future directions towards predictive understanding of ABE fermentation. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Modeling transport kinetics in clinoptilolite-phosphate rock systems

NASA Technical Reports Server (NTRS)

Allen, E. R.; Ming, D. W.; Hossner, L. R.; Henninger, D. L.

1995-01-01

Nutrient release in clinoptilolite-phosphate rock (Cp-PR) systems occurs through dissolution and cation-exchange reactions. Investigating the kinetics of these reactions expands our understanding of nutrient release processes. Research was conducted to model transport kinetics of nutrient release in Cp-PR systems. The objectives were to identify empirical models that best describe NH4, K, and P release and define diffusion-controlling processes. Materials included a Texas clinoptilolite (Cp) and North Carolina phosphate rock (PR). A continuous-flow thin-disk technique was used. Models evaluated included zero order, first order, second order, parabolic diffusion, simplified Elovich, Elovich, and power function. The power-function, Elovich, and parabolic-diffusion models adequately described NH4, K, and P release. The power-function model was preferred because of its simplicity. Models indicated nutrient release was diffusion controlled. Primary transport processes controlling nutrient release for the time span observed were probably the result of a combination of several interacting transport mechanisms.

The RiverFish Approach to Business Process Modeling: Linking Business Steps to Control-Flow Patterns

NASA Astrophysics Data System (ADS)

Zuliane, Devanir; Oikawa, Marcio K.; Malkowski, Simon; Alcazar, José Perez; Ferreira, João Eduardo

Despite the recent advances in the area of Business Process Management (BPM), today’s business processes have largely been implemented without clearly defined conceptual modeling. This results in growing difficulties for identification, maintenance, and reuse of rules, processes, and control-flow patterns. To mitigate these problems in future implementations, we propose a new approach to business process modeling using conceptual schemas, which represent hierarchies of concepts for rules and processes shared among collaborating information systems. This methodology bridges the gap between conceptual model description and identification of actual control-flow patterns for workflow implementation. We identify modeling guidelines that are characterized by clear phase separation, step-by-step execution, and process building through diagrams and tables. The separation of business process modeling in seven mutually exclusive phases clearly delimits information technology from business expertise. The sequential execution of these phases leads to the step-by-step creation of complex control-flow graphs. The process model is refined through intuitive table and diagram generation in each phase. Not only does the rigorous application of our modeling framework minimize the impact of rule and process changes, but it also facilitates the identification and maintenance of control-flow patterns in BPM-based information system architectures.

Application of queueing models to multiprogrammed computer systems operating in a time-critical environment

NASA Technical Reports Server (NTRS)

Eckhardt, D. E., Jr.

1979-01-01

A model of a central processor (CPU) which services background applications in the presence of time critical activity is presented. The CPU is viewed as an M/M/1 queueing system subject to periodic interrupts by deterministic, time critical process. The Laplace transform of the distribution of service times for the background applications is developed. The use of state of the art queueing models for studying the background processing capability of time critical computer systems is discussed and the results of a model validation study which support this application of queueing models are presented.

Successes and Challenges in Linking Observations and Modeling of Marine and Terrestrial Cryospheric Processes

NASA Astrophysics Data System (ADS)

Herzfeld, U. C.; Hunke, E. C.; Trantow, T.; Greve, R.; McDonald, B.; Wallin, B.

2014-12-01

Understanding of the state of the cryosphere and its relationship to other components of the Earth system requires both models of geophysical processes and observations of geophysical properties and processes, however linking observations and models is far from trivial. This paper looks at examples from sea ice and land ice model-observation linkages to examine some approaches, challenges and solutions. In a sea-ice example, ice deformation is analyzed as a key process that indicates fundamental changes in the Arctic sea ice cover. Simulation results from the Los Alamos Sea-Ice Model CICE, which is also the sea-ice component of the Community Earth System Model (CESM), are compared to parameters indicative of deformation as derived from mathematical analysis of remote sensing data. Data include altimeter, micro-ASAR and image data from manned and unmanned aircraft campaigns (NASA OIB and Characterization of Arctic Sea Ice Experiment, CASIE). The key problem to linking data and model results is the derivation of matching parameters on both the model and observation side.For terrestrial glaciology, we include an example of a surge process in a glacier system and and example of a dynamic ice sheet model for Greenland. To investigate the surge of the Bering Bagley Glacier System, we use numerical forward modeling experiments and, on the data analysis side, a connectionist approach to analyze crevasse provinces. In the Greenland ice sheet example, we look at the influence of ice surface and bed topography, as derived from remote sensing data, on on results from a dynamic ice sheet model.

Simulating Complex, Cold-region Process Interactions Using a Multi-scale, Variable-complexity Hydrological Model

NASA Astrophysics Data System (ADS)

Marsh, C.; Pomeroy, J. W.; Wheater, H. S.

2017-12-01

Accurate management of water resources is necessary for social, economic, and environmental sustainability worldwide. In locations with seasonal snowcovers, the accurate prediction of these water resources is further complicated due to frozen soils, solid-phase precipitation, blowing snow transport, and snowcover-vegetation-atmosphere interactions. Complex process interactions and feedbacks are a key feature of hydrological systems and may result in emergent phenomena, i.e., the arising of novel and unexpected properties within a complex system. One example is the feedback associated with blowing snow redistribution, which can lead to drifts that cause locally-increased soil moisture, thus increasing plant growth that in turn subsequently impacts snow redistribution, creating larger drifts. Attempting to simulate these emergent behaviours is a significant challenge, however, and there is concern that process conceptualizations within current models are too incomplete to represent the needed interactions. An improved understanding of the role of emergence in hydrological systems often requires high resolution distributed numerical hydrological models that incorporate the relevant process dynamics. The Canadian Hydrological Model (CHM) provides a novel tool for examining cold region hydrological systems. Key features include efficient terrain representation, allowing simulations at various spatial scales, reduced computational overhead, and a modular process representation allowing for an alternative-hypothesis framework. Using both physics-based and conceptual process representations sourced from long term process studies and the current cold regions literature allows for comparison of process representations and importantly, their ability to produce emergent behaviours. Examining the system in a holistic, process-based manner can hopefully derive important insights and aid in development of improved process representations.

Dealing with the Archetypes Development Process for a Regional EHR System

PubMed Central

Santos, M.R.; Bax, M.P.; Kalra, D.

2012-01-01

Objectives This paper aims to present the archetype modelling process used for the Health Department of Minas Gerais State, Brazil (SES/MG), to support building its regional EHR system, and the lessons learned during this process. Methods This study was undertaken within the Minas Gerais project. The EHR system architecture was built assuming the reference model from the ISO 13606 norm. The whole archetype development process took about ten months, coordinated by a clinical team co-ordinated by three health professionals and one systems analyst from the SES/MG. They were supported by around 30 health professionals from the internal SES/MG areas, and 5 systems analysts from the PRODEMGE. Based on a bottom-up approach, the project team used technical interviews and brainstorming sessions to conduct the modelling process. Results The main steps of the archetype modelling process were identified and described, and 20 archetypes were created. Lessons learned: –The set of principles established during the selection of PCS elements helped the clinical team to keep the focus in their objectives;–The initial focus on the archetype structural organization aspects was important;–The data elements identified were subjected to a rigorous analysis aimed at determining the most suitable clinical domain;–Levelling the concepts to accommodate them within the hierarchical levels in the reference model was definitely no easy task, and the use of a mind mapping tool facilitated the modelling process;–Part of the difficulty experienced by the clinical team was related to a view focused on the original forms previously used;–The use of worksheets facilitated the modelling process by health professionals;–It was important to have a health professional that knew about the domain tables and health classifications from the Brazilian Federal Government as member in the clinical team. Conclusion The archetypes (referencing terminology, domain tables and term lists) provided a favorable condition for the use of a controlled vocabulary between the central repository and the EMR systems and, probably, will increase the chances of preserving the semantics from the knowledge domain. Finally, the reference model from the ISO 13606 norm, along with the archetypes, proved sufficient to meet the specificities for the creation of an EHR system for basic healthcare in a Brazilian state. PMID:23646075

Application of dynamic models to estimate greenhouse gas emission by wastewater treatment plants of the pulp and paper industry.

PubMed

Ashrafi, Omid; Yerushalmi, Laleh; Haghighat, Fariborz

2013-03-01

Greenhouse gas (GHG) emission in wastewater treatment plants of the pulp-and-paper industry was estimated by using a dynamic mathematical model. Significant variations were shown in the magnitude of GHG generation in response to variations in operating parameters, demonstrating the limited capacity of steady-state models in predicting the time-dependent emissions of these harmful gases. The examined treatment systems used aerobic, anaerobic, and hybrid-anaerobic/aerobic-biological processes along with chemical coagulation/flocculation, anaerobic digester, nitrification and denitrification processes, and biogas recovery. The pertinent operating parameters included the influent substrate concentration, influent flow rate, and temperature. Although the average predictions by the dynamic model were only 10 % different from those of steady-state model during 140 days of operation of the examined systems, the daily variations of GHG emissions were different up to ± 30, ± 19, and ± 17 % in the aerobic, anaerobic, and hybrid systems, respectively. The variations of process variables caused fluctuations in energy generation from biogas recovery by ± 6, ± 7, and ± 4 % in the three examined systems, respectively. The lowest variations were observed in the hybrid system, showing the stability of this particular process design.

Using Unified Modelling Language (UML) as a process-modelling technique for clinical-research process improvement.

PubMed

Kumarapeli, P; De Lusignan, S; Ellis, T; Jones, B

2007-03-01

The Primary Care Data Quality programme (PCDQ) is a quality-improvement programme which processes routinely collected general practice computer data. Patient data collected from a wide range of different brands of clinical computer systems are aggregated, processed, and fed back to practices in an educational context to improve the quality of care. Process modelling is a well-established approach used to gain understanding and systematic appraisal, and identify areas of improvement of a business process. Unified modelling language (UML) is a general purpose modelling technique used for this purpose. We used UML to appraise the PCDQ process to see if the efficiency and predictability of the process could be improved. Activity analysis and thinking-aloud sessions were used to collect data to generate UML diagrams. The UML model highlighted the sequential nature of the current process as a barrier for efficiency gains. It also identified the uneven distribution of process controls, lack of symmetric communication channels, critical dependencies among processing stages, and failure to implement all the lessons learned in the piloting phase. It also suggested that improved structured reporting at each stage - especially from the pilot phase, parallel processing of data and correctly positioned process controls - should improve the efficiency and predictability of research projects. Process modelling provided a rational basis for the critical appraisal of a clinical data processing system; its potential maybe underutilized within health care.

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

NASA Technical Reports Server (NTRS)

Breckenridge, Jonathan T.; Johnson, Stephen B.

2013-01-01

This paper describes the core framework used to implement a Goal-Function Tree (GFT) based systems engineering process using the Systems Modeling Language. It defines a set of principles built upon by the theoretical approach described in the InfoTech 2013 ISHM paper titled "Goal-Function Tree Modeling for Systems Engineering and Fault Management" presented by Dr. Stephen B. Johnson. Using the SysML language, the principles in this paper describe the expansion of the SysML language as a baseline in order to: hierarchically describe a system, describe that system functionally within success space, and allocate detection mechanisms to success functions for system protection.

Modelling and analysis of the sugar cataract development process using stochastic hybrid systems.

PubMed

Riley, D; Koutsoukos, X; Riley, K

2009-05-01

Modelling and analysis of biochemical systems such as sugar cataract development (SCD) are critical because they can provide new insights into systems, which cannot be easily tested with experiments; however, they are challenging problems due to the highly coupled chemical reactions that are involved. The authors present a stochastic hybrid system (SHS) framework for modelling biochemical systems and demonstrate the approach for the SCD process. A novel feature of the framework is that it allows modelling the effect of drug treatment on the system dynamics. The authors validate the three sugar cataract models by comparing trajectories computed by two simulation algorithms. Further, the authors present a probabilistic verification method for computing the probability of sugar cataract formation for different chemical concentrations using safety and reachability analysis methods for SHSs. The verification method employs dynamic programming based on a discretisation of the state space and therefore suffers from the curse of dimensionality. To analyse the SCD process, a parallel dynamic programming implementation that can handle large, realistic systems was developed. Although scalability is a limiting factor, this work demonstrates that the proposed method is feasible for realistic biochemical systems.

Reusing models of actors and services in smart homecare to improve sustainability.

PubMed

Walderhaug, Ståle; Stav, Erlend; Mikalsen, Marius

2008-01-01

Industrial countries are faced with a growing elderly population. Homecare systems with assistive smart house technology enable elderly to live independently at home. Development of such smart home care systems is complex and expensive and there is no common reference model that can facilitate service reuse. This paper proposes reusable actor and service models based on a model-driven development process where end user organizations and domain healthcare experts from four European countries have been involved. The models, specified using UML can be reused actively as assets in the system design and development process and can reduce development costs, and improve interoperability and sustainability of systems. The models are being evaluated in the European IST project MPOWER.

Adiabatic cooling processes in frustrated magnetic systems with pyrochlore structure

NASA Astrophysics Data System (ADS)

Jurčišinová, E.; Jurčišin, M.

2017-11-01

We investigate in detail the process of adiabatic cooling in the framework of the exactly solvable antiferromagnetic spin-1/2 Ising model in the presence of the external magnetic field on an approximate lattice with pyrochlore structure. The behavior of the entropy of the model is studied and exact values of the residual entropies of all ground states are found. The temperature variation of the system under adiabatic (de)magnetization is investigated and the central role of the macroscopically degenerated ground states in cooling processes is explicitly demonstrated. It is shown that the model parameter space of the studied geometrically frustrated system is divided into five disjunct regions with qualitatively different processes of the adiabatic cooling. The effectiveness of the adiabatic (de)magnetization cooling in the studied model is compared to the corresponding processes in paramagnetic salts. It is shown that the processes of the adiabatic cooling in the antiferromagnetic frustrated systems are much more effective especially in nonzero external magnetic fields. It means that the frustrated magnetic materials with pyrochlore structure can be considered as very promising refrigerants mainly in the situations with nonzero final values of the magnetic field.

Adiabatic cooling processes in frustrated magnetic systems with pyrochlore structure.

PubMed

Jurčišinová, E; Jurčišin, M

2017-11-01

We investigate in detail the process of adiabatic cooling in the framework of the exactly solvable antiferromagnetic spin-1/2 Ising model in the presence of the external magnetic field on an approximate lattice with pyrochlore structure. The behavior of the entropy of the model is studied and exact values of the residual entropies of all ground states are found. The temperature variation of the system under adiabatic (de)magnetization is investigated and the central role of the macroscopically degenerated ground states in cooling processes is explicitly demonstrated. It is shown that the model parameter space of the studied geometrically frustrated system is divided into five disjunct regions with qualitatively different processes of the adiabatic cooling. The effectiveness of the adiabatic (de)magnetization cooling in the studied model is compared to the corresponding processes in paramagnetic salts. It is shown that the processes of the adiabatic cooling in the antiferromagnetic frustrated systems are much more effective especially in nonzero external magnetic fields. It means that the frustrated magnetic materials with pyrochlore structure can be considered as very promising refrigerants mainly in the situations with nonzero final values of the magnetic field.

A Low Cost Microcomputer System for Process Dynamics and Control Simulations.

ERIC Educational Resources Information Center

Crowl, D. A.; Durisin, M. J.

1983-01-01

Discusses a video simulator microcomputer system used to provide real-time demonstrations to strengthen students' understanding of process dynamics and control. Also discusses hardware/software and simulations developed using the system. The four simulations model various configurations of a process liquid level tank system. (JN)

Modeling and Advanced Control for Sustainable Process Systems

EPA Science Inventory

This book chapter introduces a novel process systems engineering framework that integrates process control with sustainability assessment tools for the simultaneous evaluation and optimization of process operations. The implemented control strategy consists of a biologically-insp...

The Specific Features of design and process engineering in branch of industrial enterprise

NASA Astrophysics Data System (ADS)

Sosedko, V. V.; Yanishevskaya, A. G.

2017-06-01

Production output of industrial enterprise is organized in debugged working mechanisms at each stage of product’s life cycle from initial design documentation to product and finishing it with utilization. The topic of article is mathematical model of the system design and process engineering in branch of the industrial enterprise, statistical processing of estimated implementation results of developed mathematical model in branch, and demonstration of advantages at application at this enterprise. During the creation of model a data flow about driving of information, orders, details and modules in branch of enterprise groups of divisions were classified. Proceeding from the analysis of divisions activity, a data flow, details and documents the state graph of design and process engineering was constructed, transitions were described and coefficients are appropriated. To each condition of system of the constructed state graph the corresponding limiting state probabilities were defined, and also Kolmogorov’s equations are worked out. When integration of sets of equations of Kolmogorov the state probability of system activity the specified divisions and production as function of time in each instant is defined. On the basis of developed mathematical model of uniform system of designing and process engineering and manufacture, and a state graph by authors statistical processing the application of mathematical model results was carried out, and also advantage at application at this enterprise is shown. Researches on studying of loading services probability of branch and third-party contractors (the orders received from branch within a month) were conducted. The developed mathematical model of system design and process engineering and manufacture can be applied to definition of activity state probability of divisions and manufacture as function of time in each instant that will allow to keep account of loading of performance of work in branches of the enterprise.

Modeling Quantum Dynamics in Multidimensional Systems

NASA Astrophysics Data System (ADS)

Liss, Kyle; Weinacht, Thomas; Pearson, Brett

2017-04-01

Coupling between different degrees-of-freedom is an inherent aspect of dynamics in multidimensional quantum systems. As experiments and theory begin to tackle larger molecular structures and environments, models that account for vibrational and/or electronic couplings are essential for interpretation. Relevant processes include intramolecular vibrational relaxation, conical intersections, and system-bath coupling. We describe a set of simulations designed to model coupling processes in multidimensional molecular systems, focusing on models that provide insight and allow visualization of the dynamics. Undergraduates carried out much of the work as part of a senior research project. In addition to the pedagogical value, the simulations allow for comparison between both explicit and implicit treatments of a system's many degrees-of-freedom.

Revisiting low-fidelity two-fluid models for gas-solids transport

NASA Astrophysics Data System (ADS)

Adeleke, Najeem; Adewumi, Michael; Ityokumbul, Thaddeus

2016-08-01

Two-phase gas-solids transport models are widely utilized for process design and automation in a broad range of industrial applications. Some of these applications include proppant transport in gaseous fracking fluids, air/gas drilling hydraulics, coal-gasification reactors and food processing units. Systems automation and real time process optimization stand to benefit a great deal from availability of efficient and accurate theoretical models for operations data processing. However, modeling two-phase pneumatic transport systems accurately requires a comprehensive understanding of gas-solids flow behavior. In this study we discuss the prevailing flow conditions and present a low-fidelity two-fluid model equation for particulate transport. The model equations are formulated in a manner that ensures the physical flux term remains conservative despite the inclusion of solids normal stress through the empirical formula for modulus of elasticity. A new set of Roe-Pike averages are presented for the resulting strictly hyperbolic flux term in the system of equations, which was used to develop a Roe-type approximate Riemann solver. The resulting scheme is stable regardless of the choice of flux-limiter. The model is evaluated by the prediction of experimental results from both pneumatic riser and air-drilling hydraulics systems. We demonstrate the effect and impact of numerical formulation and choice of numerical scheme on model predictions. We illustrate the capability of a low-fidelity one-dimensional two-fluid model in predicting relevant flow parameters in two-phase particulate systems accurately even under flow regimes involving counter-current flow.

Conceptual Modeling in Systems Biology Fosters Empirical Findings: The mRNA Lifecycle

PubMed Central

Dori, Dov; Choder, Mordechai

2007-01-01

One of the main obstacles to understanding complex biological systems is the extent and rapid evolution of information, way beyond the capacity individuals to manage and comprehend. Current modeling approaches and tools lack adequate capacity to model concurrently structure and behavior of biological systems. Here we propose Object-Process Methodology (OPM), a holistic conceptual modeling paradigm, as a means to model both diagrammatically and textually biological systems formally and intuitively at any desired number of levels of detail. OPM combines objects, e.g., proteins, and processes, e.g., transcription, in a way that is simple and easily comprehensible to researchers and scholars. As a case in point, we modeled the yeast mRNA lifecycle. The mRNA lifecycle involves mRNA synthesis in the nucleus, mRNA transport to the cytoplasm, and its subsequent translation and degradation therein. Recent studies have identified specific cytoplasmic foci, termed processing bodies that contain large complexes of mRNAs and decay factors. Our OPM model of this cellular subsystem, presented here, led to the discovery of a new constituent of these complexes, the translation termination factor eRF3. Association of eRF3 with processing bodies is observed after a long-term starvation period. We suggest that OPM can eventually serve as a comprehensive evolvable model of the entire living cell system. The model would serve as a research and communication platform, highlighting unknown and uncertain aspects that can be addressed empirically and updated consequently while maintaining consistency. PMID:17849002

DEVELOPMENT AND APPLICATION OF A NEW AIR POLLUTION MODELING SYSTEM--II. AEROSOL MODULE STRUCTURE AND DESIGN (R823186)

EPA Science Inventory

The methods used for simulating aerosol physical and chemical processes in a new air pollution modeling system are discussed and analyzed. Such processes include emissions, nucleation, coagulation, reversible chemistry, condensation, dissolution, evaporation, irreversible chem...

The Monash University Interactive Simple Climate Model

NASA Astrophysics Data System (ADS)

Dommenget, D.

2013-12-01

The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

A Management Information System Model for Program Management. Ph.D. Thesis - Oklahoma State Univ.; [Computerized Systems Analysis

NASA Technical Reports Server (NTRS)

Shipman, D. L.

1972-01-01

The development of a model to simulate the information system of a program management type of organization is reported. The model statistically determines the following parameters: type of messages, destinations, delivery durations, type processing, processing durations, communication channels, outgoing messages, and priorites. The total management information system of the program management organization is considered, including formal and informal information flows and both facilities and equipment. The model is written in General Purpose System Simulation 2 computer programming language for use on the Univac 1108, Executive 8 computer. The model is simulated on a daily basis and collects queue and resource utilization statistics for each decision point. The statistics are then used by management to evaluate proposed resource allocations, to evaluate proposed changes to the system, and to identify potential problem areas. The model employs both empirical and theoretical distributions which are adjusted to simulate the information flow being studied.

Development of Parametric Mass and Volume Models for an Aerospace SOFC/Gas Turbine Hybrid System

NASA Technical Reports Server (NTRS)

Tornabene, Robert; Wang, Xiao-yen; Steffen, Christopher J., Jr.; Freeh, Joshua E.

2005-01-01

In aerospace power systems, mass and volume are key considerations to produce a viable design. The utilization of fuel cells is being studied for a commercial aircraft electrical power unit. Based on preliminary analyses, a SOFC/gas turbine system may be a potential solution. This paper describes the parametric mass and volume models that are used to assess an aerospace hybrid system design. The design tool utilizes input from the thermodynamic system model and produces component sizing, performance, and mass estimates. The software is designed such that the thermodynamic model is linked to the mass and volume model to provide immediate feedback during the design process. It allows for automating an optimization process that accounts for mass and volume in its figure of merit. Each component in the system is modeled with a combination of theoretical and empirical approaches. A description of the assumptions and design analyses is presented.

Genetic Programming for Automatic Hydrological Modelling

NASA Astrophysics Data System (ADS)

Chadalawada, Jayashree; Babovic, Vladan

2017-04-01

One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development, Water Resources Research, 47(11).

An Accident Precursor Analysis Process Tailored for NASA Space Systems

NASA Technical Reports Server (NTRS)

Groen, Frank; Stamatelatos, Michael; Dezfuli, Homayoon; Maggio, Gaspare

2010-01-01

Accident Precursor Analysis (APA) serves as the bridge between existing risk modeling activities, which are often based on historical or generic failure statistics, and system anomalies, which provide crucial information about the failure mechanisms that are actually operative in the system and which may differ in frequency or type from those in the various models. These discrepancies between the models (perceived risk) and the system (actual risk) provide the leading indication of an underappreciated risk. This paper presents an APA process developed specifically for NASA Earth-to-Orbit space systems. The purpose of the process is to identify and characterize potential sources of system risk as evidenced by anomalous events which, although not necessarily presenting an immediate safety impact, may indicate that an unknown or insufficiently understood risk-significant condition exists in the system. Such anomalous events are considered accident precursors because they signal the potential for severe consequences that may occur in the future, due to causes that are discernible from their occurrence today. Their early identification allows them to be integrated into the overall system risk model used to intbrm decisions relating to safety.

A methodology proposal for collaborative business process elaboration using a model-driven approach

NASA Astrophysics Data System (ADS)

Mu, Wenxin; Bénaben, Frédérick; Pingaud, Hervé

2015-05-01

Business process management (BPM) principles are commonly used to improve processes within an organisation. But they can equally be applied to supporting the design of an Information System (IS). In a collaborative situation involving several partners, this type of BPM approach may be useful to support the design of a Mediation Information System (MIS), which would ensure interoperability between the partners' ISs (which are assumed to be service oriented). To achieve this objective, the first main task is to build a collaborative business process cartography. The aim of this article is to present a method for bringing together collaborative information and elaborating collaborative business processes from the information gathered (by using a collaborative situation framework, an organisational model, an informational model, a functional model and a metamodel and by using model transformation rules).

Applying Modeling Tools to Ground System Procedures

NASA Technical Reports Server (NTRS)

Di Pasquale, Peter

2012-01-01

As part of a long-term effort to revitalize the Ground Systems (GS) Engineering Section practices, Systems Modeling Language (SysML) and Business Process Model and Notation (BPMN) have been used to model existing GS products and the procedures GS engineers use to produce them.

Electronic Education System Model-2

ERIC Educational Resources Information Center

Güllü, Fatih; Kuusik, Rein; Laanpere, Mart

2015-01-01

In this study we presented new EES Model-2 extended from EES model for more productive implementation in e-learning process design and modelling in higher education. The most updates were related to uppermost instructional layer. We updated learning processes object of the layer for adaptation of educational process for young and old people,…

A Recommended Framework for the Network-Centric Acquisition Process

DTIC Science & Technology

2009-09-01

ISO /IEC 12207 , Systems and Software Engineering-Software Life-Cycle Processes  ANSI/EIA 632, Processes for Engineering a System. There are...engineering [46]. Some of the process models presented in the DAG are:  ISO /IEC 15288, Systems and Software Engineering-System Life-Cycle Processes...e.g., ISO , IA, Security, etc.). Vetting developers helps ensure that they are using industry best industry practices and maximize the IA compliance

Model-based Systems Engineering: Creation and Implementation of Model Validation Rules for MOS 2.0

NASA Technical Reports Server (NTRS)

Schmidt, Conrad K.

2013-01-01

Model-based Systems Engineering (MBSE) is an emerging modeling application that is used to enhance the system development process. MBSE allows for the centralization of project and system information that would otherwise be stored in extraneous locations, yielding better communication, expedited document generation and increased knowledge capture. Based on MBSE concepts and the employment of the Systems Modeling Language (SysML), extremely large and complex systems can be modeled from conceptual design through all system lifecycles. The Operations Revitalization Initiative (OpsRev) seeks to leverage MBSE to modernize the aging Advanced Multi-Mission Operations Systems (AMMOS) into the Mission Operations System 2.0 (MOS 2.0). The MOS 2.0 will be delivered in a series of conceptual and design models and documents built using the modeling tool MagicDraw. To ensure model completeness and cohesiveness, it is imperative that the MOS 2.0 models adhere to the specifications, patterns and profiles of the Mission Service Architecture Framework, thus leading to the use of validation rules. This paper outlines the process by which validation rules are identified, designed, implemented and tested. Ultimately, these rules provide the ability to maintain model correctness and synchronization in a simple, quick and effective manner, thus allowing the continuation of project and system progress.

Simulation of salt production process

NASA Astrophysics Data System (ADS)

Muraveva, E. A.

2017-10-01

In this paper an approach to the use of simulation software iThink to simulate the salt production system has been proposed. The dynamic processes of the original system are substituted by processes simulated in the abstract model, but in compliance with the basic rules of the original system, which allows one to accelerate and reduce the cost of the research. As a result, a stable workable simulation model was obtained that can display the rate of the salt exhaustion and many other parameters which are important for business planning.

System analysis through bond graph modeling

NASA Astrophysics Data System (ADS)

McBride, Robert Thomas

2005-07-01

Modeling and simulation form an integral role in the engineering design process. An accurate mathematical description of a system provides the design engineer the flexibility to perform trade studies quickly and accurately to expedite the design process. Most often, the mathematical model of the system contains components of different engineering disciplines. A modeling methodology that can handle these types of systems might be used in an indirect fashion to extract added information from the model. This research examines the ability of a modeling methodology to provide added insight into system analysis and design. The modeling methodology used is bond graph modeling. An investigation into the creation of a bond graph model using the Lagrangian of the system is provided. Upon creation of the bond graph, system analysis is performed. To aid in the system analysis, an object-oriented approach to bond graph modeling is introduced. A framework is provided to simulate the bond graph directly. Through object-oriented simulation of a bond graph, the information contained within the bond graph can be exploited to create a measurement of system efficiency. A definition of system efficiency is given. This measurement of efficiency is used in the design of different controllers of varying architectures. Optimal control of a missile autopilot is discussed within the framework of the calculated system efficiency.

Integrated process modeling for the laser inertial fusion energy (LIFE) generation system

NASA Astrophysics Data System (ADS)

Meier, W. R.; Anklam, T. M.; Erlandson, A. C.; Miles, R. R.; Simon, A. J.; Sawicki, R.; Storm, E.

2010-08-01

A concept for a new fusion-fission hybrid technology is being developed at Lawrence Livermore National Laboratory. The primary application of this technology is base-load electrical power generation. However, variants of the baseline technology can be used to "burn" spent nuclear fuel from light water reactors or to perform selective transmutation of problematic fission products. The use of a fusion driver allows very high burn-up of the fission fuel, limited only by the radiation resistance of the fuel form and system structures. As a part of this process, integrated process models have been developed to aid in concept definition. Several models have been developed. A cost scaling model allows quick assessment of design changes or technology improvements on cost of electricity. System design models are being used to better understand system interactions and to do design trade-off and optimization studies. Here we describe the different systems models and present systems analysis results. Different market entry strategies are discussed along with potential benefits to US energy security and nuclear waste disposal. Advanced technology options are evaluated and potential benefits from additional R&D targeted at the different options is quantified.

An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Peters-Lidard, Christa D.; Eastman, Joseph L.; Tao, Wei-Kuo

2007-01-01

Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

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

NASA Astrophysics Data System (ADS)

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.

A Q-Ising model application for linear-time image segmentation

NASA Astrophysics Data System (ADS)

Bentrem, Frank W.

2010-10-01

A computational method is presented which efficiently segments digital grayscale images by directly applying the Q-state Ising (or Potts) model. Since the Potts model was first proposed in 1952, physicists have studied lattice models to gain deep insights into magnetism and other disordered systems. For some time, researchers have realized that digital images may be modeled in much the same way as these physical systems ( i.e., as a square lattice of numerical values). A major drawback in using Potts model methods for image segmentation is that, with conventional methods, it processes in exponential time. Advances have been made via certain approximations to reduce the segmentation process to power-law time. However, in many applications (such as for sonar imagery), real-time processing requires much greater efficiency. This article contains a description of an energy minimization technique that applies four Potts (Q-Ising) models directly to the image and processes in linear time. The result is analogous to partitioning the system into regions of four classes of magnetism. This direct Potts segmentation technique is demonstrated on photographic, medical, and acoustic images.

Space Generic Open Avionics Architecture (SGOAA) reference model technical guide

NASA Technical Reports Server (NTRS)

Wray, Richard B.; Stovall, John R.

1993-01-01

This report presents a full description of the Space Generic Open Avionics Architecture (SGOAA). The SGOAA consists of a generic system architecture for the entities in spacecraft avionics, a generic processing architecture, and a six class model of interfaces in a hardware/software system. The purpose of the SGOAA is to provide an umbrella set of requirements for applying the generic architecture interface model to the design of specific avionics hardware/software systems. The SGOAA defines a generic set of system interface points to facilitate identification of critical interfaces and establishes the requirements for applying appropriate low level detailed implementation standards to those interface points. The generic core avionics system and processing architecture models provided herein are robustly tailorable to specific system applications and provide a platform upon which the interface model is to be applied.

Modeling and Analysis of Power Processing Systems (MAPPS). Volume 1: Technical report

NASA Technical Reports Server (NTRS)

Lee, F. C.; Rahman, S.; Carter, R. A.; Wu, C. H.; Yu, Y.; Chang, R.

1980-01-01

Computer aided design and analysis techniques were applied to power processing equipment. Topics covered include: (1) discrete time domain analysis of switching regulators for performance analysis; (2) design optimization of power converters using augmented Lagrangian penalty function technique; (3) investigation of current-injected multiloop controlled switching regulators; and (4) application of optimization for Navy VSTOL energy power system. The generation of the mathematical models and the development and application of computer aided design techniques to solve the different mathematical models are discussed. Recommendations are made for future work that would enhance the application of the computer aided design techniques for power processing systems.

A comparative study of the proposed models for the components of the national health information system.

PubMed

Ahmadi, Maryam; Damanabi, Shahla; Sadoughi, Farahnaz

2014-04-01

National Health Information System plays an important role in ensuring timely and reliable access to Health information, which is essential for strategic and operational decisions that improve health, quality and effectiveness of health care. In other words, using the National Health information system you can improve the quality of health data, information and knowledge used to support decision making at all levels and areas of the health sector. Since full identification of the components of this system - for better planning and management influential factors of performanceseems necessary, therefore, in this study different attitudes towards components of this system are explored comparatively. This is a descriptive and comparative kind of study. The society includes printed and electronic documents containing components of the national health information system in three parts: input, process and output. In this context, search for information using library resources and internet search were conducted, and data analysis was expressed using comparative tables and qualitative data. The findings showed that there are three different perspectives presenting the components of national health information system Lippeveld and Sauerborn and Bodart model in 2000, Health Metrics Network (HMN) model from World Health Organization in 2008, and Gattini's 2009 model. All three models outlined above in the input (resources and structure) require components of management and leadership, planning and design programs, supply of staff, software and hardware facilities and equipment. Plus, in the "process" section from three models, we pointed up the actions ensuring the quality of health information system, and in output section, except for Lippeveld Model, two other models consider information products and use and distribution of information as components of the national health information system. the results showed that all the three models have had a brief discussion about the components of health information in input section. But Lippeveld model has overlooked the components of national health information in process and output sections. Therefore, it seems that the health measurement model of network has a comprehensive presentation for the components of health system in all three sections-input, process and output.

Coupling biology and oceanography in models.

PubMed

Fennel, W; Neumann, T

2001-08-01

The dynamics of marine ecosystems, i.e. the changes of observable chemical-biological quantities in space and time, are driven by biological and physical processes. Predictions of future developments of marine systems need a theoretical framework, i.e. models, solidly based on research and understanding of the different processes involved. The natural way to describe marine systems theoretically seems to be the embedding of chemical-biological models into circulation models. However, while circulation models are relatively advanced the quantitative theoretical description of chemical-biological processes lags behind. This paper discusses some of the approaches and problems in the development of consistent theories and indicates the beneficial potential of the coupling of marine biology and oceanography in models.

Logistics Control Facility: A Normative Model for Total Asset Visibility in the Air Force Logistics System

DTIC Science & Technology

1994-09-01

IIssue Computers, information systems, and communication systems are being increasingly used in transportation, warehousing, order processing , materials...inventory levels, reduced order processing times, reduced order processing costs, and increased customer satisfaction. While purchasing and transportation...process, the speed in which crders are processed would increase significantly. Lowering the order processing time in turn lowers the lead time, which in

Modeling biochemical transformation processes and information processing with Narrator.

PubMed

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 specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from http://www.narrator-tool.org.

Modeling biochemical transformation processes and information processing with Narrator

PubMed Central

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

2007-01-01

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 flexible and intuitive systems biology tool. It is specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from . PMID:17389034

Computer Models of Personality: Implications for Measurement

ERIC Educational Resources Information Center

Cranton, P. A.

1976-01-01

Current research on computer models of personality is reviewed and categorized under five headings: (1) models of belief systems; (2) models of interpersonal behavior; (3) models of decision-making processes; (4) prediction models; and (5) theory-based simulations of specific processes. The use of computer models in personality measurement is…

An overview of the model integration process: From pre ...

EPA Pesticide Factsheets

Integration of models requires linking models which can be developed using different tools, methodologies, and assumptions. We performed a literature review with the aim of improving our understanding of model integration process, and also presenting better strategies for building integrated modeling systems. We identified five different phases to characterize integration process: pre-integration assessment, preparation of models for integration, orchestration of models during simulation, data interoperability, and testing. Commonly, there is little reuse of existing frameworks beyond the development teams and not much sharing of science components across frameworks. We believe this must change to enable researchers and assessors to form complex workflows that leverage the current environmental science available. In this paper, we characterize the model integration process and compare integration practices of different groups. We highlight key strategies, features, standards, and practices that can be employed by developers to increase reuse and interoperability of science software components and systems. The paper provides a review of the literature regarding techniques and methods employed by various modeling system developers to facilitate science software interoperability. The intent of the paper is to illustrate the wide variation in methods and the limiting effect the variation has on inter-framework reuse and interoperability. A series of recommendation

A simulation of remote sensor systems and data processing algorithms for spectral feature classification

NASA Technical Reports Server (NTRS)

Arduini, R. F.; Aherron, R. M.; Samms, R. W.

1984-01-01

A computational model of the deterministic and stochastic processes involved in multispectral remote sensing was designed to evaluate the performance of sensor systems and data processing algorithms for spectral feature classification. Accuracy in distinguishing between categories of surfaces or between specific types is developed as a means to compare sensor systems and data processing algorithms. The model allows studies to be made of the effects of variability of the atmosphere and of surface reflectance, as well as the effects of channel selection and sensor noise. Examples of these effects are shown.

Observation and integrated Earth-system science: A roadmap for 2016-2025

NASA Astrophysics Data System (ADS)

Simmons, Adrian; Fellous, Jean-Louis; Ramaswamy, Venkatachalam; Trenberth, Kevin; Asrar, Ghassem; Balmaseda, Magdalena; Burrows, John P.; Ciais, Philippe; Drinkwater, Mark; Friedlingstein, Pierre; Gobron, Nadine; Guilyardi, Eric; Halpern, David; Heimann, Martin; Johannessen, Johnny; Levelt, Pieternel F.; Lopez-Baeza, Ernesto; Penner, Joyce; Scholes, Robert; Shepherd, Ted

2016-05-01

This report is the response to a request by the Committee on Space Research of the International Council for Science to prepare a roadmap on observation and integrated Earth-system science for the coming ten years. Its focus is on the combined use of observations and modelling to address the functioning, predictability and projected evolution of interacting components of the Earth system on timescales out to a century or so. It discusses how observations support integrated Earth-system science and its applications, and identifies planned enhancements to the contributing observing systems and other requirements for observations and their processing. All types of observation are considered, but emphasis is placed on those made from space. The origins and development of the integrated view of the Earth system are outlined, noting the interactions between the main components that lead to requirements for integrated science and modelling, and for the observations that guide and support them. What constitutes an Earth-system model is discussed. Summaries are given of key cycles within the Earth system. The nature of Earth observation and the arrangements for international coordination essential for effective operation of global observing systems are introduced. Instances are given of present types of observation, what is already on the roadmap for 2016-2025 and some of the issues to be faced. Observations that are organised on a systematic basis and observations that are made for process understanding and model development, or other research or demonstration purposes, are covered. Specific accounts are given for many of the variables of the Earth system. The current status and prospects for Earth-system modelling are summarized. The evolution towards applying Earth-system models for environmental monitoring and prediction as well as for climate simulation and projection is outlined. General aspects of the improvement of models, whether through refining the representations of processes that are already incorporated or through adding new processes or components, are discussed. Some important elements of Earth-system models are considered more fully. Data assimilation is discussed not only because it uses observations and models to generate datasets for monitoring the Earth system and for initiating and evaluating predictions, in particular through reanalysis, but also because of the feedback it provides on the quality of both the observations and the models employed. Inverse methods for surface-flux or model-parameter estimation are also covered. Reviews are given of the way observations and the processed datasets based on them are used for evaluating models, and of the combined use of observations and models for monitoring and interpreting the behaviour of the Earth system and for predicting and projecting its future. A set of concluding discussions covers general developmental needs, requirements for continuity of space-based observing systems, further long-term requirements for observations and other data, technological advances and data challenges, and the importance of enhanced international co-operation.

Observation and integrated Earth-system science: A roadmap for 2016–2025

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simmons, Adrian; Fellous, Jean-Louis; Ramaswamy, V.

This report is the response to a request by the Committee on Space Research of the International Council for Science to prepare a roadmap on observation and integrated Earth-system science for the coming ten years. Its focus is on the combined use of observations and modelling to address the functioning, predictability and projected evolution of interacting components of the Earth system on timescales out to a century or so. It discusses how observations support integrated Earth-system science and its applications, and identifies planned enhancements to the contributing observing systems and other requirements for observations and their processing. All types ofmore » observation are considered, but emphasis is placed on those made from space. The origins and development of the integrated view of the Earth system are outlined, noting the interactions between the main components that lead to requirements for integrated science and modelling, and for the observations that guide and support them. What constitutes an Earth-system model is discussed. Summaries are given of key cycles within the Earth system. The nature of Earth observation and the arrangements for international coordination essential for effective operation of global observing systems are introduced. Instances are given of present types of observation, what is already on the roadmap for 2016–2025 and some of the issues to be faced. Observations that are organized on a systematic basis and observations that are made for process understanding and model development, or other research or demonstration purposes, are covered. Specific accounts are given for many of the variables of the Earth system. The current status and prospects for Earth-system modelling are summarized. The evolution towards applying Earth-system models for environmental monitoring and prediction as well as for climate simulation and projection is outlined. General aspects of the improvement of models, whether through refining the representations of processes that are already incorporated or through adding new processes or components, are discussed. Some important elements of Earth-system models are considered more fully. Data assimilation is discussed not only because it uses observations and models to generate datasets for monitoring the Earth system and for initiating and evaluating predictions, in particular through reanalysis, but also because of the feedback it provides on the quality of both the observations and the models employed. Inverse methods for surface-flux or model-parameter estimation are also covered. Reviews are given of the way observations and the processed datasets based on them are used for evaluating models, and of the combined use of observations and models for monitoring and interpreting the behaviour of the Earth system and for predicting and projecting its future. A set of concluding discussions covers general developmental needs, requirements for continuity of space-based observing systems, further long-term requirements for observations and other data, technological advances and data challenges, and the importance of enhanced international co-operation.« less

Unified Modeling Language (UML) for hospital-based cancer registration processes.

PubMed

Shiki, Naomi; Ohno, Yuko; Fujii, Ayumi; Murata, Taizo; Matsumura, Yasushi

2008-01-01

Hospital-based cancer registry involves complex processing steps that span across multiple departments. In addition, management techniques and registration procedures differ depending on each medical facility. Establishing processes for hospital-based cancer registry requires clarifying specific functions and labor needed. In recent years, the business modeling technique, in which management evaluation is done by clearly spelling out processes and functions, has been applied to business process analysis. However, there are few analytical reports describing the applications of these concepts to medical-related work. In this study, we initially sought to model hospital-based cancer registration processes using the Unified Modeling Language (UML), to clarify functions. The object of this study was the cancer registry of Osaka University Hospital. We organized the hospital-based cancer registration processes based on interview and observational surveys, and produced an As-Is model using activity, use-case, and class diagrams. After drafting every UML model, it was fed-back to practitioners to check its validity and improved. We were able to define the workflow for each department using activity diagrams. In addition, by using use-case diagrams we were able to classify each department within the hospital as a system, and thereby specify the core processes and staff that were responsible for each department. The class diagrams were effective in systematically organizing the information to be used for hospital-based cancer registries. Using UML modeling, hospital-based cancer registration processes were broadly classified into three separate processes, namely, registration tasks, quality control, and filing data. An additional 14 functions were also extracted. Many tasks take place within the hospital-based cancer registry office, but the process of providing information spans across multiple departments. Moreover, additional tasks were required in comparison to using a standardized system because the hospital-based cancer registration system was constructed with the pre-existing computer system in Osaka University Hospital. Difficulty of utilization of useful information for cancer registration processes was shown to increase the task workload. By using UML, we were able to clarify functions and extract the typical processes for a hospital-based cancer registry. Modeling can provide a basis of process analysis for establishment of efficient hospital-based cancer registration processes in each institute.

Data processing and optimization system to study prospective interstate power interconnections

NASA Astrophysics Data System (ADS)

Podkovalnikov, Sergei; Trofimov, Ivan; Trofimov, Leonid

2018-01-01

The paper presents Data processing and optimization system for studying and making rational decisions on the formation of interstate electric power interconnections, with aim to increasing effectiveness of their functioning and expansion. The technologies for building and integrating a Data processing and optimization system including an object-oriented database and a predictive mathematical model for optimizing the expansion of electric power systems ORIRES, are described. The technology of collection and pre-processing of non-structured data collected from various sources and its loading to the object-oriented database, as well as processing and presentation of information in the GIS system are described. One of the approaches of graphical visualization of the results of optimization model is considered on the example of calculating the option for expansion of the South Korean electric power grid.

From conceptual modeling to a map

NASA Astrophysics Data System (ADS)

Gotlib, Dariusz; Olszewski, Robert

2018-05-01

Nowadays almost every map is a component of the information system. Design and production of maps requires the use of specific rules for modeling information systems: conceptual, application and data modelling. While analyzing various stages of cartographic modeling the authors ask the question: at what stage of this process a map occurs. Can we say that the "life of the map" begins even before someone define its form of presentation? This question is particularly important at the time of exponentially increasing number of new geoinformation products. During the analysis of the theory of cartography and relations of the discipline to other fields of knowledge it has been attempted to define a few properties of cartographic modeling which distinguish the process from other methods of spatial modeling. Assuming that the map is a model of reality (created in the process of cartographic modeling supported by domain-modeling) the article proposes an analogy of the process of cartographic modeling to the scheme of conceptual modeling presented in ISO 19101 standard.

Superstructure-based Design and Optimization of Batch Biodiesel Production Using Heterogeneous Catalysts

NASA Astrophysics Data System (ADS)

Nuh, M. Z.; Nasir, N. F.

2017-08-01

Biodiesel as a fuel comprised of mono alkyl esters of long chain fatty acids derived from renewable lipid feedstock, such as vegetable oil and animal fat. Biodiesel production is complex process which need systematic design and optimization. However, no case study using the process system engineering (PSE) elements which are superstructure optimization of batch process, it involves complex problems and uses mixed-integer nonlinear programming (MINLP). The PSE offers a solution to complex engineering system by enabling the use of viable tools and techniques to better manage and comprehend the complexity of the system. This study is aimed to apply the PSE tools for the simulation of biodiesel process and optimization and to develop mathematical models for component of the plant for case A, B, C by using published kinetic data. Secondly, to determine economic analysis for biodiesel production, focusing on heterogeneous catalyst. Finally, the objective of this study is to develop the superstructure for biodiesel production by using heterogeneous catalyst. The mathematical models are developed by the superstructure and solving the resulting mixed integer non-linear model and estimation economic analysis by using MATLAB software. The results of the optimization process with the objective function of minimizing the annual production cost by batch process from case C is 23.2587 million USD. Overall, the implementation a study of process system engineering (PSE) has optimized the process of modelling, design and cost estimation. By optimizing the process, it results in solving the complex production and processing of biodiesel by batch.

Signal Processing in Periodically Forced Gradient Frequency Neural Networks

PubMed Central

Kim, Ji Chul; Large, Edward W.

2015-01-01

Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing. PMID:26733858

Chasing Perfection: Should We Reduce Model Uncertainty in Carbon Cycle-Climate Feedbacks

NASA Astrophysics Data System (ADS)

Bonan, G. B.; Lombardozzi, D.; Wieder, W. R.; Lindsay, K. T.; Thomas, R. Q.

2015-12-01

Earth system model simulations of the terrestrial carbon (C) cycle show large multi-model spread in the carbon-concentration and carbon-climate feedback parameters. Large differences among models are also seen in their simulation of global vegetation and soil C stocks and other aspects of the C cycle, prompting concern about model uncertainty and our ability to faithfully represent fundamental aspects of the terrestrial C cycle in Earth system models. Benchmarking analyses that compare model simulations with common datasets have been proposed as a means to assess model fidelity with observations, and various model-data fusion techniques have been used to reduce model biases. While such efforts will reduce multi-model spread, they may not help reduce uncertainty (and increase confidence) in projections of the C cycle over the twenty-first century. Many ecological and biogeochemical processes represented in Earth system models are poorly understood at both the site scale and across large regions, where biotic and edaphic heterogeneity are important. Our experience with the Community Land Model (CLM) suggests that large uncertainty in the terrestrial C cycle and its feedback with climate change is an inherent property of biological systems. The challenge of representing life in Earth system models, with the rich diversity of lifeforms and complexity of biological systems, may necessitate a multitude of modeling approaches to capture the range of possible outcomes. Such models should encompass a range of plausible model structures. We distinguish between model parameter uncertainty and model structural uncertainty. Focusing on improved parameter estimates may, in fact, limit progress in assessing model structural uncertainty associated with realistically representing biological processes. Moreover, higher confidence may be achieved through better process representation, but this does not necessarily reduce uncertainty.

Remaining useful life prediction of degrading systems subjected to imperfect maintenance: Application to draught fans

NASA Astrophysics Data System (ADS)

Wang, Zhao-Qiang; Hu, Chang-Hua; Si, Xiao-Sheng; Zio, Enrico

2018-02-01

Current degradation modeling and remaining useful life prediction studies share a common assumption that the degrading systems are not maintained or maintained perfectly (i.e., to an as-good-as new state). This paper concerns the issues of how to model the degradation process and predict the remaining useful life of degrading systems subjected to imperfect maintenance activities, which can restore the health condition of a degrading system to any degradation level between as-good-as new and as-bad-as old. Toward this end, a nonlinear model driven by Wiener process is first proposed to characterize the degradation trajectory of the degrading system subjected to imperfect maintenance, where negative jumps are incorporated to quantify the influence of imperfect maintenance activities on the system's degradation. Then, the probability density function of the remaining useful life is derived analytically by a space-scale transformation, i.e., transforming the constructed degradation model with negative jumps crossing a constant threshold level to a Wiener process model crossing a random threshold level. To implement the proposed method, unknown parameters in the degradation model are estimated by the maximum likelihood estimation method. Finally, the proposed degradation modeling and remaining useful life prediction method are applied to a practical case of draught fans belonging to a kind of mechanical systems from steel mills. The results reveal that, for a degrading system subjected to imperfect maintenance, our proposed method can obtain more accurate remaining useful life predictions than those of the benchmark model in literature.

Learner Performance Accounting: A Tri-Cycle Process

ERIC Educational Resources Information Center

Brown, Thomas C.; McCleary, Lloyd E.

1973-01-01

The Tri-Cycle Process described in the model permits for the first time an integrated system for designing an individualized instructional system that would permit a rational, diagnosis-prescription-evaluation system keyed to an accounting system. (Author)

Stochastic Models of Human Errors

NASA Technical Reports Server (NTRS)

Elshamy, Maged; Elliott, Dawn M. (Technical Monitor)

2002-01-01

Humans play an important role in the overall reliability of engineering systems. More often accidents and systems failure are traced to human errors. Therefore, in order to have meaningful system risk analysis, the reliability of the human element must be taken into consideration. Describing the human error process by mathematical models is a key to analyzing contributing factors. Therefore, the objective of this research effort is to establish stochastic models substantiated by sound theoretic foundation to address the occurrence of human errors in the processing of the space shuttle.

Automated Interactive Simulation Model (AISIM) VAX Version 5.0 Training Manual.

DTIC Science & Technology

1987-05-29

action, activity, decision , etc. that consumes time. The entity is automatically created by the system when an ACTION Primitive is placed. 1.3.2.4 The...MODELED SYSTEM 1.3.2.1 The Process Entity. A Process is used to represent the operations, decisions , actions or activities that can be decomposed and...is associated with the Action entity described below, is included in Process definitions to indicate the time a certain Action (or process, decision

A rigorous approach to investigating common assumptions about disease transmission: Process algebra as an emerging modelling methodology for epidemiology.

PubMed

McCaig, Chris; Begon, Mike; Norman, Rachel; Shankland, Carron

2011-03-01

Changing scale, for example, the ability to move seamlessly from an individual-based model to a population-based model, is an important problem in many fields. In this paper, we introduce process algebra as a novel solution to this problem in the context of models of infectious disease spread. Process algebra allows us to describe a system in terms of the stochastic behaviour of individuals, and is a technique from computer science. We review the use of process algebra in biological systems, and the variety of quantitative and qualitative analysis techniques available. The analysis illustrated here solves the changing scale problem: from the individual behaviour we can rigorously derive equations to describe the mean behaviour of the system at the level of the population. The biological problem investigated is the transmission of infection, and how this relates to individual interactions.

Applying STAMP in Accident Analysis

NASA Technical Reports Server (NTRS)

Leveson, Nancy; Daouk, Mirna; Dulac, Nicolas; Marais, Karen

2003-01-01

Accident models play a critical role in accident investigation and analysis. Most traditional models are based on an underlying chain of events. These models, however, have serious limitations when used for complex, socio-technical systems. Previously, Leveson proposed a new accident model (STAMP) based on system theory. In STAMP, the basic concept is not an event but a constraint. This paper shows how STAMP can be applied to accident analysis using three different views or models of the accident process and proposes a notation for describing this process.

Model-Based Diagnostics for Propellant Loading Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew John; Foygel, Michael; Smelyanskiy, Vadim N.

2011-01-01

The loading of spacecraft propellants is a complex, risky operation. Therefore, diagnostic solutions are necessary to quickly identify when a fault occurs, so that recovery actions can be taken or an abort procedure can be initiated. Model-based diagnosis solutions, established using an in-depth analysis and understanding of the underlying physical processes, offer the advanced capability to quickly detect and isolate faults, identify their severity, and predict their effects on system performance. We develop a physics-based model of a cryogenic propellant loading system, which describes the complex dynamics of liquid hydrogen filling from a storage tank to an external vehicle tank, as well as the influence of different faults on this process. The model takes into account the main physical processes such as highly nonequilibrium condensation and evaporation of the hydrogen vapor, pressurization, and also the dynamics of liquid hydrogen and vapor flows inside the system in the presence of helium gas. Since the model incorporates multiple faults in the system, it provides a suitable framework for model-based diagnostics and prognostics algorithms. Using this model, we analyze the effects of faults on the system, derive symbolic fault signatures for the purposes of fault isolation, and perform fault identification using a particle filter approach. We demonstrate the detection, isolation, and identification of a number of faults using simulation-based experiments.

Application of Advanced Process Control techniques to a pusher type reheating furnace

NASA Astrophysics Data System (ADS)

Zanoli, S. M.; Pepe, C.; Barboni, L.

2015-11-01

In this paper an Advanced Process Control system aimed at controlling and optimizing a pusher type reheating furnace located in an Italian steel plant is proposed. The designed controller replaced the previous control system, based on PID controllers manually conducted by process operators. A two-layer Model Predictive Control architecture has been adopted that, exploiting a chemical, physical and economic modelling of the process, overcomes the limitations of plant operators’ mental model and knowledge. In addition, an ad hoc decoupling strategy has been implemented, allowing the selection of the manipulated variables to be used for the control of each single process variable. Finally, in order to improve the system flexibility and resilience, the controller has been equipped with a supervision module. A profitable trade-off between conflicting specifications, e.g. safety, quality and production constraints, energy saving and pollution impact, has been guaranteed. Simulation tests and real plant results demonstrated the soundness and the reliability of the proposed system.

Model-Based PAT for Quality Management in Pharmaceuticals Freeze-Drying: State of the Art

PubMed Central

Fissore, Davide

2017-01-01

Model-based process analytical technologies can be used for the in-line control and optimization of a pharmaceuticals freeze-drying process, as well as for the off-line design of the process, i.e., the identification of the optimal operating conditions. This paper aims at presenting the state of the art in this field, focusing, particularly, on three groups of systems, namely, those based on the temperature measurement (i.e., the soft sensor), on the chamber pressure measurement (i.e., the systems based on the test of pressure rise and of pressure decrease), and on the sublimation flux estimate (i.e., the tunable diode laser absorption spectroscopy and the valveless monitoring system). The application of these systems for in-line process optimization (e.g., using a model predictive control algorithm) and to get a true quality by design (e.g., through the off-line calculation of the design space of the process) is presented and discussed. PMID:28224123

Multi-Hypothesis Modelling Capabilities for Robust Data-Model Integration

NASA Astrophysics Data System (ADS)

Walker, A. P.; De Kauwe, M. G.; Lu, D.; Medlyn, B.; Norby, R. J.; Ricciuto, D. M.; Rogers, A.; Serbin, S.; Weston, D. J.; Ye, M.; Zaehle, S.

2017-12-01

Large uncertainty is often inherent in model predictions due to imperfect knowledge of how to describe the mechanistic processes (hypotheses) that a model is intended to represent. Yet this model hypothesis uncertainty (MHU) is often overlooked or informally evaluated, as methods to quantify and evaluate MHU are limited. MHU is increased as models become more complex because each additional processes added to a model comes with inherent MHU as well as parametric unceratinty. With the current trend of adding more processes to Earth System Models (ESMs), we are adding uncertainty, which can be quantified for parameters but not MHU. Model inter-comparison projects do allow for some consideration of hypothesis uncertainty but in an ad hoc and non-independent fashion. This has stymied efforts to evaluate ecosystem models against data and intepret the results mechanistically because it is not simple to interpret exactly why a model is producing the results it does and identify which model assumptions are key as they combine models of many sub-systems and processes, each of which may be conceptualised and represented mathematically in various ways. We present a novel modelling framework—the multi-assumption architecture and testbed (MAAT)—that automates the combination, generation, and execution of a model ensemble built with different representations of process. We will present the argument that multi-hypothesis modelling needs to be considered in conjunction with other capabilities (e.g. the Predictive Ecosystem Analyser; PecAn) and statistical methods (e.g. sensitivity anaylsis, data assimilation) to aid efforts in robust data model integration to enhance our predictive understanding of biological systems.

“Docs 'n Drugs” - A System for Case-Oriented and Web-based Training in Medicine

PubMed Central

Martens, A.; Bernauer, J.

1999-01-01

The tutoring process of conventional case-oriented medical training systems can be characterised as either guided or unguided. In contrast to that, the aim of the system “Docs'n Drugs” is to distinguish between different levels of guidance. The author can realise the tutoring case either as a guided, a half guided or a unguided tutoring process. The system architecture distinguishes between an authoring system and a tutoring system. Fundaments of these are the tutoring process model and the case-based knowledge model. This structure allows the reuse of elements of existing tutoring cases. The tutoring cases can be realised in German and English.

The use of discrete-event simulation modeling to compare handwritten and electronic prescribing systems.

PubMed

Ghany, Ahmad; Vassanji, Karim; Kuziemsky, Craig; Keshavjee, Karim

2013-01-01

Electronic prescribing (e-prescribing) is expected to bring many benefits to Canadian healthcare, such as a reduction in errors and adverse drug reactions. As there currently is no functioning e-prescribing system in Canada that is completely electronic, we are unable to evaluate the performance of a live system. An alternative approach is to use simulation modeling for evaluation. We developed two discrete-event simulation models, one of the current handwritten prescribing system and one of a proposed e-prescribing system, to compare the performance of these two systems. We were able to compare the number of processes in each model, workflow efficiency, and the distribution of patients or prescriptions. Although we were able to compare these models to each other, using discrete-event simulation software was challenging. We were limited in the number of variables we could measure. We discovered non-linear processes and feedback loops in both models that could not be adequately represented using discrete-event simulation software. Finally, interactions between entities in both models could not be modeled using this type of software. We have come to the conclusion that a more appropriate approach to modeling both the handwritten and electronic prescribing systems would be to use a complex adaptive systems approach using agent-based modeling or systems-based modeling.

Simultaneous Sensor and Process Fault Diagnostics for Propellant Feed System

NASA Technical Reports Server (NTRS)

Cao, J.; Kwan, C.; Figueroa, F.; Xu, R.

2006-01-01

The main objective of this research is to extract fault features from sensor faults and process faults by using advanced fault detection and isolation (FDI) algorithms. A tank system that has some common characteristics to a NASA testbed at Stennis Space Center was used to verify our proposed algorithms. First, a generic tank system was modeled. Second, a mathematical model suitable for FDI has been derived for the tank system. Third, a new and general FDI procedure has been designed to distinguish process faults and sensor faults. Extensive simulations clearly demonstrated the advantages of the new design.

Modeling of materials supply, demand and prices

NASA Technical Reports Server (NTRS)

1982-01-01

The societal, economic, and policy tradeoffs associated with materials processing and utilization, are discussed. The materials system provides the materials engineer with the system analysis required for formulate sound materials processing, utilization, and resource development policies and strategies. Materials system simulation and modeling research program including assessments of materials substitution dynamics, public policy implications, and materials process economics was expanded. This effort includes several collaborative programs with materials engineers, economists, and policy analysts. The technical and socioeconomic issues of materials recycling, input-output analysis, and technological change and productivity are examined. The major thrust areas in materials systems research are outlined.

Integrated urban systems model with multiple transportation supply agents.

DOT National Transportation Integrated Search

2012-10-01

This project demonstrates the feasibility of developing quantitative models that can forecast future networks under : current and alternative transportation planning processes. The current transportation planning process is modeled : based on empiric...

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

NASA Technical Reports Server (NTRS)

Patterson, Jonathan D.; 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.

Task allocation model for minimization of completion time in distributed computer systems

NASA Astrophysics Data System (ADS)

Wang, Jai-Ping; Steidley, Carl W.

1993-08-01

A task in a distributed computing system consists of a set of related modules. Each of the modules will execute on one of the processors of the system and communicate with some other modules. In addition, precedence relationships may exist among the modules. Task allocation is an essential activity in distributed-software design. This activity is of importance to all phases of the development of a distributed system. This paper establishes task completion-time models and task allocation models for minimizing task completion time. Current work in this area is either at the experimental level or without the consideration of precedence relationships among modules. The development of mathematical models for the computation of task completion time and task allocation will benefit many real-time computer applications such as radar systems, navigation systems, industrial process control systems, image processing systems, and artificial intelligence oriented systems.

Progress of Aircraft System Noise Assessment with Uncertainty Quantification for the Environmentally Responsible Aviation Project

NASA Technical Reports Server (NTRS)

Thomas, Russell H.; Burley, Casey L.; Guo, Yueping

2016-01-01

Aircraft system noise predictions have been performed for NASA modeled hybrid wing body aircraft advanced concepts with 2025 entry-into-service technology assumptions. The system noise predictions developed over a period from 2009 to 2016 as a result of improved modeling of the aircraft concepts, design changes, technology development, flight path modeling, and the use of extensive integrated system level experimental data. In addition, the system noise prediction models and process have been improved in many ways. An additional process is developed here for quantifying the uncertainty with a 95% confidence level. This uncertainty applies only to the aircraft system noise prediction process. For three points in time during this period, the vehicle designs, technologies, and noise prediction process are documented. For each of the three predictions, and with the information available at each of those points in time, the uncertainty is quantified using the direct Monte Carlo method with 10,000 simulations. For the prediction of cumulative noise of an advanced aircraft at the conceptual level of design, the total uncertainty band has been reduced from 12.2 to 9.6 EPNL dB. A value of 3.6 EPNL dB is proposed as the lower limit of uncertainty possible for the cumulative system noise prediction of an advanced aircraft concept.

An approach to developing an integrated pyroprocessing simulator

NASA Astrophysics Data System (ADS)

Lee, Hyo Jik; Ko, Won Il; Choi, Sung Yeol; Kim, Sung Ki; Kim, In Tae; Lee, Han Soo

2014-02-01

Pyroprocessing has been studied for a decade as one of the promising fuel recycling options in Korea. We have built a pyroprocessing integrated inactive demonstration facility (PRIDE) to assess the feasibility of integrated pyroprocessing technology and scale-up issues of the processing equipment. Even though such facility cannot be replaced with a real integrated facility using spent nuclear fuel (SF), many insights can be obtained in terms of the world's largest integrated pyroprocessing operation. In order to complement or overcome such limited test-based research, a pyroprocessing Modelling and simulation study began in 2011. The Korea Atomic Energy Research Institute (KAERI) suggested a Modelling architecture for the development of a multi-purpose pyroprocessing simulator consisting of three-tiered models: unit process, operation, and plant-level-model. The unit process model can be addressed using governing equations or empirical equations as a continuous system (CS). In contrast, the operation model describes the operational behaviors as a discrete event system (DES). The plant-level model is an integrated model of the unit process and an operation model with various analysis modules. An interface with different systems, the incorporation of different codes, a process-centered database design, and a dynamic material flow are discussed as necessary components for building a framework of the plant-level model. As a sample model that contains methods decoding the above engineering issues was thoroughly reviewed, the architecture for building the plant-level-model was verified. By analyzing a process and operation-combined model, we showed that the suggested approach is effective for comprehensively understanding an integrated dynamic material flow. This paper addressed the current status of the pyroprocessing Modelling and simulation activity at KAERI, and also predicted its path forward.

An approach to developing an integrated pyroprocessing simulator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Hyo Jik; Ko, Won Il; Choi, Sung Yeol

Pyroprocessing has been studied for a decade as one of the promising fuel recycling options in Korea. We have built a pyroprocessing integrated inactive demonstration facility (PRIDE) to assess the feasibility of integrated pyroprocessing technology and scale-up issues of the processing equipment. Even though such facility cannot be replaced with a real integrated facility using spent nuclear fuel (SF), many insights can be obtained in terms of the world's largest integrated pyroprocessing operation. In order to complement or overcome such limited test-based research, a pyroprocessing Modelling and simulation study began in 2011. The Korea Atomic Energy Research Institute (KAERI) suggestedmore » a Modelling architecture for the development of a multi-purpose pyroprocessing simulator consisting of three-tiered models: unit process, operation, and plant-level-model. The unit process model can be addressed using governing equations or empirical equations as a continuous system (CS). In contrast, the operation model describes the operational behaviors as a discrete event system (DES). The plant-level model is an integrated model of the unit process and an operation model with various analysis modules. An interface with different systems, the incorporation of different codes, a process-centered database design, and a dynamic material flow are discussed as necessary components for building a framework of the plant-level model. As a sample model that contains methods decoding the above engineering issues was thoroughly reviewed, the architecture for building the plant-level-model was verified. By analyzing a process and operation-combined model, we showed that the suggested approach is effective for comprehensively understanding an integrated dynamic material flow. This paper addressed the current status of the pyroprocessing Modelling and simulation activity at KAERI, and also predicted its path forward.« less

Protection - Principles and practice.

NASA Technical Reports Server (NTRS)

Graham, G. S.; Denning, P. J.

1972-01-01

The protection mechanisms of computer systems control the access to objects, especially information objects. The principles of protection system design are formalized as a model (theory) of protection. Each process has a unique identification number which is attached by the system to each access attempted by the process. Details of system implementation are discussed, taking into account the storing of the access matrix, aspects of efficiency, and the selection of subjects and objects. Two systems which have protection features incorporating all the elements of the model are described.

Postures and Motions Library Development for Verification of Ground Crew Human Systems Integration Requirements

NASA Technical Reports Server (NTRS)

Jackson, Mariea Dunn; Dischinger, Charles; Stambolian, Damon; Henderson, Gena

2012-01-01

Spacecraft and launch vehicle ground processing activities require a variety of unique human activities. These activities are being documented in a Primitive motion capture library. The Library will be used by the human factors engineering in the future to infuse real to life human activities into the CAD models to verify ground systems human factors requirements. As the Primitive models are being developed for the library the project has selected several current human factors issues to be addressed for the SLS and Orion launch systems. This paper explains how the Motion Capture of unique ground systems activities are being used to verify the human factors analysis requirements for ground system used to process the STS and Orion vehicles, and how the primitive models will be applied to future spacecraft and launch vehicle processing.

Postures and Motions Library Development for Verification of Ground Crew Human Factors Requirements

NASA Technical Reports Server (NTRS)

Stambolian, Damon; Henderson, Gena; Jackson, Mariea Dunn; Dischinger, Charles

2013-01-01

Spacecraft and launch vehicle ground processing activities require a variety of unique human activities. These activities are being documented in a primitive motion capture library. The library will be used by human factors engineering analysts to infuse real to life human activities into the CAD models to verify ground systems human factors requirements. As the primitive models are being developed for the library, the project has selected several current human factors issues to be addressed for the Space Launch System (SLS) and Orion launch systems. This paper explains how the motion capture of unique ground systems activities is being used to verify the human factors engineering requirements for ground systems used to process the SLS and Orion vehicles, and how the primitive models will be applied to future spacecraft and launch vehicle processing.

The generic MESSy submodel TENDENCY (v1.0) for process-based analyses in Earth system models

NASA Astrophysics Data System (ADS)

Eichinger, R.; Jöckel, P.

2014-07-01

The tendencies of prognostic variables in Earth system models are usually only accessible, e.g. for output, as a sum over all physical, dynamical and chemical processes at the end of one time integration step. Information about the contribution of individual processes to the total tendency is lost, if no special precautions are implemented. The knowledge on individual contributions, however, can be of importance to track down specific mechanisms in the model system. We present the new MESSy (Modular Earth Submodel System) infrastructure submodel TENDENCY and use it exemplarily within the EMAC (ECHAM/MESSy Atmospheric Chemistry) model to trace process-based tendencies of prognostic variables. The main idea is the outsourcing of the tendency accounting for the state variables from the process operators (submodels) to the TENDENCY submodel itself. In this way, a record of the tendencies of all process-prognostic variable pairs can be stored. The selection of these pairs can be specified by the user, tailor-made for the desired application, in order to minimise memory requirements. Moreover, a standard interface allows the access to the individual process tendencies by other submodels, e.g. for on-line diagnostics or for additional parameterisations, which depend on individual process tendencies. An optional closure test assures the correct treatment of tendency accounting in all submodels and thus serves to reduce the model's susceptibility. TENDENCY is independent of the time integration scheme and therefore the concept is applicable to other model systems as well. Test simulations with TENDENCY show an increase of computing time for the EMAC model (in a setup without atmospheric chemistry) of 1.8 ± 1% due to the additional subroutine calls when using TENDENCY. Exemplary results reveal the dissolving mechanisms of the stratospheric tape recorder signal in height over time. The separation of the tendency of the specific humidity into the respective processes (large-scale clouds, convective clouds, large-scale advection, vertical diffusion and methane oxidation) show that the upward propagating water vapour signal dissolves mainly because of the chemical and the advective contribution. The TENDENCY submodel is part of version 2.42 or later of MESSy.

The generic MESSy submodel TENDENCY (v1.0) for process-based analyses in Earth System Models

NASA Astrophysics Data System (ADS)

Eichinger, R.; Jöckel, P.

2014-04-01

The tendencies of prognostic variables in Earth System Models are usually only accessible, e.g., for output, as sum over all physical, dynamical and chemical processes at the end of one time integration step. Information about the contribution of individual processes to the total tendency is lost, if no special precautions are implemented. The knowledge on individual contributions, however, can be of importance to track down specific mechanisms in the model system. We present the new MESSy (Modular Earth Submodel System) infrastructure submodel TENDENCY and use it exemplarily within the EMAC (ECHAM/MESSy Atmospheric Chemistry) model to trace process-based tendencies of prognostic variables. The main idea is the outsourcing of the tendency accounting for the state variables from the process operators (submodels) to the TENDENCY submodel itself. In this way, a record of the tendencies of all process-prognostic variable pairs can be stored. The selection of these pairs can be specified by the user, tailor-made for the desired application, in order to minimise memory requirements. Moreover a standard interface allows the access to the individual process tendencies by other submodels, e.g., for on-line diagnostics or for additional parameterisations, which depend on individual process tendencies. An optional closure test assures the correct treatment of tendency accounting in all submodels and thus serves to reduce the models susceptibility. TENDENCY is independent of the time integration scheme and therefore applicable to other model systems as well. Test simulations with TENDENCY show an increase of computing time for the EMAC model (in a setup without atmospheric chemistry) of 1.8 ± 1% due to the additional subroutine calls when using TENDENCY. Exemplary results reveal the dissolving mechanisms of the stratospheric tape recorder signal in height over time. The separation of the tendency of the specific humidity into the respective processes (large-scale clouds, convective clouds, large-scale advection, vertical diffusion and methane-oxidation) show that the upward propagating water vapour signal dissolves mainly because of the chemical and the advective contribution. The TENDENCY submodel is part of version 2.42 or later of MESSy.

Modeling and simulation of enzymatic gluconic acid production using immobilized enzyme and CSTR-PFTR circulation reaction system.

PubMed

Li, Can; Lin, Jianqun; Gao, Ling; Lin, Huibin; Lin, Jianqiang

2018-04-01

Production of gluconic acid by using immobilized enzyme and continuous stirred tank reactor-plug flow tubular reactor (CSTR-PFTR) circulation reaction system. A production system is constructed for gluconic acid production, which consists of a continuous stirred tank reactor (CSTR) for pH control and liquid storage and a plug flow tubular reactor (PFTR) filled with immobilized glucose oxidase (GOD) for gluconic acid production. Mathematical model is developed for this production system and simulation is made for the enzymatic reaction process. The pH inhibition effect on GOD is modeled by using a bell-type curve. Gluconic acid can be efficiently produced by using the reaction system and the mathematical model developed for this system can simulate and predict the process well.

A generic biogeochemical module for Earth system models: Next Generation BioGeoChemical Module (NGBGC), version 1.0

NASA Astrophysics Data System (ADS)

Fang, Y.; Huang, M.; Liu, C.; Li, H.; Leung, L. R.

2013-11-01

Physical and biogeochemical processes regulate soil carbon dynamics and CO2 flux to and from the atmosphere, influencing global climate changes. Integration of these processes into Earth system models (e.g., community land models (CLMs)), however, currently faces three major challenges: (1) extensive efforts are required to modify modeling structures and to rewrite computer programs to incorporate new or updated processes as new knowledge is being generated, (2) computational cost is prohibitively expensive to simulate biogeochemical processes in land models due to large variations in the rates of biogeochemical processes, and (3) various mathematical representations of biogeochemical processes exist to incorporate different aspects of fundamental mechanisms, but systematic evaluation of the different mathematical representations is difficult, if not impossible. To address these challenges, we propose a new computational framework to easily incorporate physical and biogeochemical processes into land models. The new framework consists of a new biogeochemical module, Next Generation BioGeoChemical Module (NGBGC), version 1.0, with a generic algorithm and reaction database so that new and updated processes can be incorporated into land models without the need to manually set up the ordinary differential equations to be solved numerically. The reaction database consists of processes of nutrient flow through the terrestrial ecosystems in plants, litter, and soil. This framework facilitates effective comparison studies of biogeochemical cycles in an ecosystem using different conceptual models under the same land modeling framework. The approach was first implemented in CLM and benchmarked against simulations from the original CLM-CN code. A case study was then provided to demonstrate the advantages of using the new approach to incorporate a phosphorus cycle into CLM. To our knowledge, the phosphorus-incorporated CLM is a new model that can be used to simulate phosphorus limitation on the productivity of terrestrial ecosystems. The method presented here could in theory be applied to simulate biogeochemical cycles in other Earth system models.

An Information-Processing Model of Crisis Management.

ERIC Educational Resources Information Center

Egelhoff, William G.; Sen, Falguni

1992-01-01

Develops a contingency model for managing a variety of corporate crises. Views crisis management as an information-processing situation and organizations that must cope with crisis as information-processing systems. Attempts to fit appropriate information-processing mechanisms to different categories of crises. (PRA)

Fuzzy control of burnout of multilayer ceramic actuators

NASA Astrophysics Data System (ADS)

Ling, Alice V.; Voss, David; Christodoulou, Leo

1996-08-01

To improve the yield and repeatability of the burnout process of multilayer ceramic actuators (MCAs), an intelligent processing of materials (IPM-based) control system has been developed for the manufacture of MCAs. IPM involves the active (ultimately adaptive) control of a material process using empirical or analytical models and in situ sensing of critical process states (part features and process parameters) to modify the processing conditions in real time to achieve predefined product goals. Thus, the three enabling technologies for the IPM burnout control system are process modeling, in situ sensing and intelligent control. This paper presents the design of an IPM-based control strategy for the burnout process of MCAs.

Digital data processing system dynamic loading analysis

NASA Technical Reports Server (NTRS)

Lagas, J. J.; Peterka, J. J.; Tucker, A. E.

1976-01-01

Simulation and analysis of the Space Shuttle Orbiter Digital Data Processing System (DDPS) are reported. The mated flight and postseparation flight phases of the space shuttle's approach and landing test configuration were modeled utilizing the Information Management System Interpretative Model (IMSIM) in a computerized simulation modeling of the ALT hardware, software, and workload. System requirements simulated for the ALT configuration were defined. Sensitivity analyses determined areas of potential data flow problems in DDPS operation. Based on the defined system requirements and the sensitivity analyses, a test design is described for adapting, parameterizing, and executing the IMSIM. Varying load and stress conditions for the model execution are given. The analyses of the computer simulation runs were documented as results, conclusions, and recommendations for DDPS improvements.

Space shuttle orbiter digital data processing system timing sensitivity analysis OFT ascent phase

NASA Technical Reports Server (NTRS)

Lagas, J. J.; Peterka, J. J.; Becker, D. A.

1977-01-01

Dynamic loads were investigated to provide simulation and analysis of the space shuttle orbiter digital data processing system (DDPS). Segments of the ascent test (OFT) configuration were modeled utilizing the information management system interpretive model (IMSIM) in a computerized simulation modeling of the OFT hardware and software workload. System requirements for simulation of the OFT configuration were defined, and sensitivity analyses determined areas of potential data flow problems in DDPS operation. Based on the defined system requirements and these sensitivity analyses, a test design was developed for adapting, parameterizing, and executing IMSIM, using varying load and stress conditions for model execution. Analyses of the computer simulation runs are documented, including results, conclusions, and recommendations for DDPS improvements.

Conceptual Models, Choices, and Benchmarks for Building Quality Work Cultures.

ERIC Educational Resources Information Center

Acker-Hocevar, Michele

1996-01-01

The two models in Florida's Educational Quality Benchmark System represent a new way of thinking about developing schools' work culture. The Quality Performance System Model identifies nine dimensions of work within a quality system. The Change Process Model provides a theoretical framework for changing existing beliefs, attitudes, and behaviors…

Identifiability Of Systems With Modeling Errors

NASA Technical Reports Server (NTRS)

Hadaegh, Yadolah " fred" ; Bekey, George A.

1988-01-01

Advances in theory of modeling errors reported. Recent paper on errors in mathematical models of deterministic linear or weakly nonlinear systems. Extends theoretical work described in NPO-16661 and NPO-16785. Presents concrete way of accounting for difference in structure between mathematical model and physical process or system that it represents.

Commentary on the shifting processes model: a conceptual model for weight management.

PubMed

Pagoto, Sherry; Rodrigues, Stephanie

2013-12-01

Macchi and colleagues propose a theoretical model that merges concepts from the biopsychosocial model and family systems theory to produce a broader framework for understanding weight loss and maintenance (see record 2013-28564-001). The Shifting Processes Model views individual weight loss and maintenance in the context of family dynamics, including family eating and exercise habits, home environment, and family relationships. The authors reason that traditional models put the burden of change on the individual rather than the family system, when the latter is an important context of individual behavior.

Diagnostic reasoning: where we've been, where we're going.

PubMed

Monteiro, Sandra M; Norman, Geoffrey

2013-01-01

Recently, clinical diagnostic reasoning has been characterized by "dual processing" models, which postulate a fast, unconscious (System 1) component and a slow, logical, analytical (System 2) component. However, there are a number of variants of this basic model, which may lead to conflicting claims. This paper critically reviews current theories and evidence about the nature of clinical diagnostic reasoning. We begin by briefly discussing the history of research in clinical reasoning. We then focus more specifically on the evidence to support dual-processing models. We conclude by identifying knowledge gaps about clinical reasoning and provide suggestions for future research. In contrast to work on analytical and nonanalytical knowledge as a basis for reasoning, these theories focus on the thinking process, not the nature of the knowledge retrieved. Ironically, this appears to be a revival of an outdated concept. Rather than defining diagnostic performance by problem-solving skills, it is now being defined by processing strategy. The version of dual processing that has received most attention in the literature in medical diagnosis might be labeled a "default/interventionist" model,(17) which suggests that a default system of cognitive processes (System 1) is responsible for cognitive biases that lead to diagnostic errors and that System 2 intervenes to correct these errors. Consequently, from this model, the best strategy for reducing errors is to make students aware of the biases and to encourage them to rely more on System 2. However, an accumulation of evidence suggests that (a) strategies directed at increasing analytical (System 2) processing, by slowing down, reducing distractions, paying conscious attention, and (b) strategies directed at making students aware of the effect of cognitive biases, have no impact on error rates. Conversely, strategies based on increasing application of relevant knowledge appear to have some success and are consistent with basic research on concept formation.

Mapping care processes within a hospital: from theory to a web-based proposal merging enterprise modelling and ISO normative principles.

PubMed

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.

Modeling the dynamics of evaluation: a multilevel neural network implementation of the iterative reprocessing model.

PubMed

Ehret, Phillip J; Monroe, Brian M; Read, Stephen J

2015-05-01

We present a neural network implementation of central components of the iterative reprocessing (IR) model. The IR model argues that the evaluation of social stimuli (attitudes, stereotypes) is the result of the IR of stimuli in a hierarchy of neural systems: The evaluation of social stimuli develops and changes over processing. The network has a multilevel, bidirectional feedback evaluation system that integrates initial perceptual processing and later developing semantic processing. The network processes stimuli (e.g., an individual's appearance) over repeated iterations, with increasingly higher levels of semantic processing over time. As a result, the network's evaluations of stimuli evolve. We discuss the implications of the network for a number of different issues involved in attitudes and social evaluation. The success of the network supports the IR model framework and provides new insights into attitude theory. © 2014 by the Society for Personality and Social Psychology, Inc.

Automatization of hydrodynamic modelling in a Floreon+ system

NASA Astrophysics Data System (ADS)

Ronovsky, Ales; Kuchar, Stepan; Podhoranyi, Michal; Vojtek, David

2017-07-01

The paper describes fully automatized hydrodynamic modelling as a part of the Floreon+ system. The main purpose of hydrodynamic modelling in the disaster management is to provide an accurate overview of the hydrological situation in a given river catchment. Automatization of the process as a web service could provide us with immediate data based on extreme weather conditions, such as heavy rainfall, without the intervention of an expert. Such a service can be used by non scientific users such as fire-fighter operators or representatives of a military service organizing evacuation during floods or river dam breaks. The paper describes the whole process beginning with a definition of a schematization necessary for hydrodynamic model, gathering of necessary data and its processing for a simulation, the model itself and post processing of a result and visualization on a web service. The process is demonstrated on a real data collected during floods in our Moravian-Silesian region in 2010.

Atmospheric Boundary Layer Modeling for Combined Meteorology and Air Quality Systems

EPA Science Inventory

Atmospheric Eulerian grid models for mesoscale and larger applications require sub-grid models for turbulent vertical exchange processes, particularly within the Planetary Boundary Layer (PSL). In combined meteorology and air quality modeling systems consistent PSL modeling of wi...

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system

PubMed Central

2010-01-01

Background The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the “in silico” stochastic event based modeling approach to find the molecular dynamics of the system. Results In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Conclusions Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics. PMID:21143785

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system.

PubMed

Ghosh, Preetam; Ghosh, Samik; Basu, Kalyan; Das, Sajal K; Zhang, Chaoyang

2010-12-01

The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the "in silico" stochastic event based modeling approach to find the molecular dynamics of the system. In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics.

A diagnostic interface for the ICOsahedral Non-hydrostatic (ICON) modelling framework based on the Modular Earth Submodel System (MESSy v2.50)

NASA Astrophysics Data System (ADS)

Kern, Bastian; Jöckel, Patrick

2016-10-01

Numerical climate and weather models have advanced to finer scales, accompanied by large amounts of output data. The model systems hit the input and output (I/O) bottleneck of modern high-performance computing (HPC) systems. We aim to apply diagnostic methods online during the model simulation instead of applying them as a post-processing step to written output data, to reduce the amount of I/O. To include diagnostic tools into the model system, we implemented a standardised, easy-to-use interface based on the Modular Earth Submodel System (MESSy) into the ICOsahedral Non-hydrostatic (ICON) modelling framework. The integration of the diagnostic interface into the model system is briefly described. Furthermore, we present a prototype implementation of an advanced online diagnostic tool for the aggregation of model data onto a user-defined regular coarse grid. This diagnostic tool will be used to reduce the amount of model output in future simulations. Performance tests of the interface and of two different diagnostic tools show, that the interface itself introduces no overhead in form of additional runtime to the model system. The diagnostic tools, however, have significant impact on the model system's runtime. This overhead strongly depends on the characteristics and implementation of the diagnostic tool. A diagnostic tool with high inter-process communication introduces large overhead, whereas the additional runtime of a diagnostic tool without inter-process communication is low. We briefly describe our efforts to reduce the additional runtime from the diagnostic tools, and present a brief analysis of memory consumption. Future work will focus on optimisation of the memory footprint and the I/O operations of the diagnostic interface.

Development of expert systems for modeling of technological process of pressure casting on the basis of artificial intelligence

NASA Astrophysics Data System (ADS)

Gavarieva, K. N.; Simonova, L. A.; Pankratov, D. L.; Gavariev, R. V.

2017-09-01

In article the main component of expert system of process of casting under pressure which consists of algorithms, united in logical models is considered. The characteristics of system showing data on a condition of an object of management are described. A number of logically interconnected steps allowing to increase quality of the received castings is developed

Process Improvement Should Link to Security: SEPG 2007 Security Track Recap

DTIC Science & Technology

2007-09-01

the Systems Security Engineering Capability Maturity Model (SSE- CMM / ISO 21827) and its use in system software developments ...software development life cycle ( SDLC )? 6. In what ways should process improvement support security in the SDLC ? 1.2 10BPANEL RESOURCES For each... project management, and support practices through the use of the capability maturity models including the CMMI and the Systems Security

Enterprise and system of systems capability development life-cycle processes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beck, David Franklin

2014-08-01

This report and set of appendices are a collection of memoranda originally drafted circa 2007-2009 for the purpose of describing and detailing a models-based systems engineering approach for satisfying enterprise and system-of-systems life cycle process requirements. At the time there was interest and support to move from Capability Maturity Model Integration (CMMI) Level One (ad hoc processes) to Level Three. The main thrust of the material presents a rational exposâe of a structured enterprise development life cycle that uses the scientific method as a framework, with further rigor added from adapting relevant portions of standard systems engineering processes. While themore » approach described invokes application of the Department of Defense Architectural Framework (DoDAF), it is suitable for use with other architectural description frameworks.« less

A model for simulating the grinding and classification cyclic system of waste PCBs recycling production line.

PubMed

Yang, Deming; Xu, Zhenming

2011-09-15

Crushing and separating technology is widely used in waste printed circuit boards (PCBs) recycling process. A set of automatic line without negative impact to environment for recycling waste PCBs was applied in industry scale. Crushed waste PCBs particles grinding and classification cyclic system is the most important part of the automatic production line, and it decides the efficiency of the whole production line. In this paper, a model for computing the process of the system was established, and matrix analysis method was adopted. The result showed that good agreement can be achieved between the simulation model and the actual production line, and the system is anti-jamming. This model possibly provides a basis for the automatic process control of waste PCBs production line. With this model, many engineering problems can be reduced, such as metals and nonmetals insufficient dissociation, particles over-pulverizing, incomplete comminuting, material plugging and equipment fever. Copyright © 2011 Elsevier B.V. All rights reserved.

SBML-SAT: a systems biology markup language (SBML) based sensitivity analysis tool

PubMed Central

Zi, Zhike; Zheng, Yanan; Rundell, Ann E; Klipp, Edda

2008-01-01

Background It has long been recognized that sensitivity analysis plays a key role in modeling and analyzing cellular and biochemical processes. Systems biology markup language (SBML) has become a well-known platform for coding and sharing mathematical models of such processes. However, current SBML compatible software tools are limited in their ability to perform global sensitivity analyses of these models. Results This work introduces a freely downloadable, software package, SBML-SAT, which implements algorithms for simulation, steady state analysis, robustness analysis and local and global sensitivity analysis for SBML models. This software tool extends current capabilities through its execution of global sensitivity analyses using multi-parametric sensitivity analysis, partial rank correlation coefficient, SOBOL's method, and weighted average of local sensitivity analyses in addition to its ability to handle systems with discontinuous events and intuitive graphical user interface. Conclusion SBML-SAT provides the community of systems biologists a new tool for the analysis of their SBML models of biochemical and cellular processes. PMID:18706080

SBML-SAT: a systems biology markup language (SBML) based sensitivity analysis tool.

PubMed

Zi, Zhike; Zheng, Yanan; Rundell, Ann E; Klipp, Edda

2008-08-15

It has long been recognized that sensitivity analysis plays a key role in modeling and analyzing cellular and biochemical processes. Systems biology markup language (SBML) has become a well-known platform for coding and sharing mathematical models of such processes. However, current SBML compatible software tools are limited in their ability to perform global sensitivity analyses of these models. This work introduces a freely downloadable, software package, SBML-SAT, which implements algorithms for simulation, steady state analysis, robustness analysis and local and global sensitivity analysis for SBML models. This software tool extends current capabilities through its execution of global sensitivity analyses using multi-parametric sensitivity analysis, partial rank correlation coefficient, SOBOL's method, and weighted average of local sensitivity analyses in addition to its ability to handle systems with discontinuous events and intuitive graphical user interface. SBML-SAT provides the community of systems biologists a new tool for the analysis of their SBML models of biochemical and cellular processes.

Design of distributed systems of hydrolithosphere processes management. A synthesis of distributed management systems

NASA Astrophysics Data System (ADS)

Pershin, I. M.; Pervukhin, D. A.; Ilyushin, Y. V.; Afanaseva, O. V.

2017-10-01

The paper considers an important problem of designing distributed systems of hydrolithosphere processes management. The control actions on the hydrolithosphere processes under consideration are implemented by a set of extractive wells. The article shows the method of defining the approximation links for description of the dynamic characteristics of hydrolithosphere processes. The structure of distributed regulators, used in the management systems by the considered processes, is presented. The paper analyses the results of the synthesis of the distributed management system and the results of modelling the closed-loop control system by the parameters of the hydrolithosphere process.

Computational modeling of residual stress formation during the electron beam melting process for Inconel 718

DOE PAGES

Prabhakar, P.; Sames, William J.; Dehoff, Ryan R.; ...

2015-03-28

Here, a computational modeling approach to simulate residual stress formation during the electron beam melting (EBM) process within the additive manufacturing (AM) technologies for Inconel 718 is presented in this paper. The EBM process has demonstrated a high potential to fabricate components with complex geometries, but the resulting components are influenced by the thermal cycles observed during the manufacturing process. When processing nickel based superalloys, very high temperatures (approx. 1000 °C) are observed in the powder bed, base plate, and build. These high temperatures, when combined with substrate adherence, can result in warping of the base plate and affect themore » final component by causing defects. It is important to have an understanding of the thermo-mechanical response of the entire system, that is, its mechanical behavior towards thermal loading occurring during the EBM process prior to manufacturing a component. Therefore, computational models to predict the response of the system during the EBM process will aid in eliminating the undesired process conditions, a priori, in order to fabricate the optimum component. Such a comprehensive computational modeling approach is demonstrated to analyze warping of the base plate, stress and plastic strain accumulation within the material, and thermal cycles in the system during different stages of the EBM process.« less

Nonlinear and Digital Man-machine Control Systems Modeling

NASA Technical Reports Server (NTRS)

Mekel, R.

1972-01-01

An adaptive modeling technique is examined by which controllers can be synthesized to provide corrective dynamics to a human operator's mathematical model in closed loop control systems. The technique utilizes a class of Liapunov functions formulated for this purpose, Liapunov's stability criterion and a model-reference system configuration. The Liapunov function is formulated to posses variable characteristics to take into consideration the identification dynamics. The time derivative of the Liapunov function generate the identification and control laws for the mathematical model system. These laws permit the realization of a controller which updates the human operator's mathematical model parameters so that model and human operator produce the same response when subjected to the same stimulus. A very useful feature is the development of a digital computer program which is easily implemented and modified concurrent with experimentation. The program permits the modeling process to interact with the experimentation process in a mutually beneficial way.

Combined Log Inventory and Process Simulation Models for the Planning and Control of Sawmill Operations

Treesearch

Guillermo A. Mendoza; Roger J. Meimban; Philip A. Araman; William G. Luppold

1991-01-01

A log inventory model and a real-time hardwood process simulation model were developed and combined into an integrated production planning and control system for hardwood sawmills. The log inventory model was designed to monitor and periodically update the status of the logs in the log yard. The process simulation model was designed to estimate various sawmill...

Transactions in domain-specific information systems

NASA Astrophysics Data System (ADS)

Zacek, Jaroslav

2017-07-01

Substantial number of the current information system (IS) implementations is based on transaction approach. In addition, most of the implementations are domain-specific (e.g. accounting IS, resource planning IS). Therefore, we have to have a generic transaction model to build and verify domain-specific IS. The paper proposes a new transaction model for domain-specific ontologies. This model is based on value oriented business process modelling technique. The transaction model is formalized by the Petri Net theory. First part of the paper presents common business processes and analyses related to business process modeling. Second part defines the transactional model delimited by REA enterprise ontology paradigm and introduces states of the generic transaction model. The generic model proposal is defined and visualized by the Petri Net modelling tool. Third part shows application of the generic transaction model. Last part of the paper concludes results and discusses a practical usability of the generic transaction model.

Fundamental properties of cooperative contagion processes

NASA Astrophysics Data System (ADS)

Chen, Li; Ghanbarnejad, Fakhteh; Brockmann, Dirk

2017-10-01

We investigate the effects of cooperativity between contagion processes that spread and persist in a host population. We propose and analyze a dynamical model in which individuals that are affected by one transmissible agent A exhibit a higher than baseline propensity of being affected by a second agent B and vice versa. The model is a natural extension of the traditional susceptible-infected-susceptible model used for modeling single contagion processes. We show that cooperativity changes the dynamics of the system considerably when cooperativity is strong. The system exhibits discontinuous phase transitions not observed in single agent contagion, multi-stability, a separation of the traditional epidemic threshold into different thresholds for inception and extinction as well as hysteresis. These properties are robust and are corroborated by stochastic simulations on lattices and generic network topologies. Finally, we investigate wave propagation and transients in a spatially extended version of the model and show that especially for intermediate values of baseline reproduction ratios the system is characterized by various types of wave-front speeds. The system can exhibit spatially heterogeneous stationary states for some parameters and negative front speeds (receding wave fronts). The two agent model can be employed as a starting point for more complex contagion processes, involving several interacting agents, a model framework particularly suitable for modeling the spread and dynamics of microbiological ecosystems in host populations.

10 Steps to Building an Architecture for Space Surveillance Projects

NASA Astrophysics Data System (ADS)

Gyorko, E.; Barnhart, E.; Gans, H.

Space surveillance is an increasingly complex task, requiring the coordination of a multitude of organizations and systems, while dealing with competing capabilities, proprietary processes, differing standards, and compliance issues. In order to fully understand space surveillance operations, analysts and engineers need to analyze and break down their operations and systems using what are essentially enterprise architecture processes and techniques. These techniques can be daunting to the first- time architect. This paper provides a summary of simplified steps to analyze a space surveillance system at the enterprise level in order to determine capabilities, services, and systems. These steps form the core of an initial Model-Based Architecting process. For new systems, a well defined, or well architected, space surveillance enterprise leads to an easier transition from model-based architecture to model-based design and provides a greater likelihood that requirements are fulfilled the first time. Both new and existing systems benefit from being easier to manage, and can be sustained more easily using portfolio management techniques, based around capabilities documented in the model repository. The resulting enterprise model helps an architect avoid 1) costly, faulty portfolio decisions; 2) wasteful technology refresh efforts; 3) upgrade and transition nightmares; and 4) non-compliance with DoDAF directives. The Model-Based Architecting steps are based on a process that Harris Corporation has developed from practical experience architecting space surveillance systems and ground systems. Examples are drawn from current work on documenting space situational awareness enterprises. The process is centered on DoDAF 2 and its corresponding meta-model so that terminology is standardized and communicable across any disciplines that know DoDAF architecting, including acquisition, engineering and sustainment disciplines. Each step provides a guideline for the type of data to collect, and also the appropriate views to generate. The steps include 1) determining the context of the enterprise, including active elements and high level capabilities or goals; 2) determining the desired effects of the capabilities and mapping capabilities against the project plan; 3) determining operational performers and their inter-relationships; 4) building information and data dictionaries; 5) defining resources associated with capabilities; 6) determining the operational behavior necessary to achieve each capability; 7) analyzing existing or planned implementations to determine systems, services and software; 8) cross-referencing system behavior to operational behavioral; 9) documenting system threads and functional implementations; and 10) creating any required textual documentation from the model.

Process identification of the SCR system of coal-fired power plant for de-NOx based on historical operation data.

PubMed

Li, Jian; Shi, Raoqiao; Xu, Chuanlong; Wang, Shimin

2018-05-08

The selective catalytic reduction (SCR) system, as one principal flue gas treatment method employed for the NO x emission control of the coal-fired power plant, is nonlinear and time-varying with great inertia and large time delay. It is difficult for the present SCR control system to achieve satisfactory performance with the traditional feedback and feedforward control strategies. Although some improved control strategies, such as the Smith predictor control and the model predictive control, have been proposed for this issue, a well-matched identification model is essentially required to realize a superior control of the SCR system. Industrial field experiment is an alternative way to identify the SCR system model in the coal-fired power plant. But it undesirably disturbs the operation system and is costly in time and manpower. In this paper, a process identification model of the SCR system is proposed and developed by applying the asymptotic method to the sufficiently excited data, selected from the original historical operation database of a 350 MW coal-fired power plant according to the condition number of the Fisher information matrix. Numerical simulations are carried out based on the practical historical operation data to evaluate the performance of the proposed model. Results show that the proposed model can efficiently achieve the process identification of the SCR system.

Flight crew aiding for recovery from subsystem failures

NASA Technical Reports Server (NTRS)

Hudlicka, E.; Corker, K.; Schudy, R.; Baron, Sheldon

1990-01-01

Some of the conceptual issues associated with pilot aiding systems are discussed and an implementation of one component of such an aiding system is described. It is essential that the format and content of the information the aiding system presents to the crew be compatible with the crew's mental models of the task. It is proposed that in order to cooperate effectively, both the aiding system and the flight crew should have consistent information processing models, especially at the point of interface. A general information processing strategy, developed by Rasmussen, was selected to serve as the bridge between the human and aiding system's information processes. The development and implementation of a model-based situation assessment and response generation system for commercial transport aircraft are described. The current implementation is a prototype which concentrates on engine and control surface failure situations and consequent flight emergencies. The aiding system, termed Recovery Recommendation System (RECORS), uses a causal model of the relevant subset of the flight domain to simulate the effects of these failures and to generate appropriate responses, given the current aircraft state and the constraints of the current flight phase. Since detailed information about the aircraft state may not always be available, the model represents the domain at varying levels of abstraction and uses the less detailed abstraction levels to make inferences when exact information is not available. The structure of this model is described in detail.

System Maturity and Architecture Assessment Methods, Processes, and Tools

DTIC Science & Technology

2012-03-02

Deshmukh , and M. Sarfaraz. Development of Systems Engineering Maturity Models and Management Tools. Systems Engineering Research Center Final Technical...Ramirez- Marquez, D. Nowicki, A. Deshmukh , and M. Sarfaraz. Development of Systems Engineering Maturity Models and Management Tools. Systems Engineering

A 3D Human-Machine Integrated Design and Analysis Framework for Squat Exercises with a Smith Machine.

PubMed

Lee, Haerin; Jung, Moonki; Lee, Ki-Kwang; Lee, Sang Hun

2017-02-06

In this paper, we propose a three-dimensional design and evaluation framework and process based on a probabilistic-based motion synthesis algorithm and biomechanical analysis system for the design of the Smith machine and squat training programs. Moreover, we implemented a prototype system to validate the proposed framework. The framework consists of an integrated human-machine-environment model as well as a squat motion synthesis system and biomechanical analysis system. In the design and evaluation process, we created an integrated model in which interactions between a human body and machine or the ground are modeled as joints with constraints at contact points. Next, we generated Smith squat motion using the motion synthesis program based on a Gaussian process regression algorithm with a set of given values for independent variables. Then, using the biomechanical analysis system, we simulated joint moments and muscle activities from the input of the integrated model and squat motion. We validated the model and algorithm through physical experiments measuring the electromyography (EMG) signals, ground forces, and squat motions as well as through a biomechanical simulation of muscle forces. The proposed approach enables the incorporation of biomechanics in the design process and reduces the need for physical experiments and prototypes in the development of training programs and new Smith machines.

A 3D Human-Machine Integrated Design and Analysis Framework for Squat Exercises with a Smith Machine

PubMed Central

Lee, Haerin; Jung, Moonki; Lee, Ki-Kwang; Lee, Sang Hun

2017-01-01

In this paper, we propose a three-dimensional design and evaluation framework and process based on a probabilistic-based motion synthesis algorithm and biomechanical analysis system for the design of the Smith machine and squat training programs. Moreover, we implemented a prototype system to validate the proposed framework. The framework consists of an integrated human–machine–environment model as well as a squat motion synthesis system and biomechanical analysis system. In the design and evaluation process, we created an integrated model in which interactions between a human body and machine or the ground are modeled as joints with constraints at contact points. Next, we generated Smith squat motion using the motion synthesis program based on a Gaussian process regression algorithm with a set of given values for independent variables. Then, using the biomechanical analysis system, we simulated joint moments and muscle activities from the input of the integrated model and squat motion. We validated the model and algorithm through physical experiments measuring the electromyography (EMG) signals, ground forces, and squat motions as well as through a biomechanical simulation of muscle forces. The proposed approach enables the incorporation of biomechanics in the design process and reduces the need for physical experiments and prototypes in the development of training programs and new Smith machines. PMID:28178184

Modeling of Solid Waste Processing Options in BIO-Plex

NASA Technical Reports Server (NTRS)

Rodriguez, Luis F.; Finn, Cory; Kang, Sukwon; Hogan, John; Luna, Bernadette (Technical Monitor)

2000-01-01

BIO-Plex is a ground-based test bed currently under development by NASA for testing technologies and practices that may be utilized in future long-term life support missions. All aspects of such an Advanced Life Support (ALS) System must be considered to confidently construct a reliable system, which will not only allow the crew to survive in harsh environments, but allow the crew time to perform meaningful research. Effective handling of solid wastes is a critical aspect of the system, especially when recovery of resources contained in the waste is required. This is particularly important for ALS Systems configurations that include a Biomass Production Chamber. In these cases, significant amounts of inedible biomass waste may be produced, which can ultimately serve as a repository of necessary resources for sustaining life, notably carbon, water, and plant nutrients. Numerous biological and physicochemical solid waste processing options have been considered. Biological options include composting, aerobic digestion, and anaerobic digestion. Physicochemical options include pyrolysis, SCWO (supercritical water oxidation), various incineration configurations, microwave incineration, magnetically assisted gasification, and low temperature plasma reaction. Modeling of these options is a necessary step to assist in the design process. A previously developed top-level model of BIO-Plex implemented in MATLAB Simulink (r) for the use of systems analysis and design has been adopted for this analysis. Presently, this model only considered incineration for solid waste processing. Present work, reported here, includes the expansion of this model to include a wider array of solid waste processing options selected from the above options, bearing in mind potential, near term solid waste treatment systems. Furthermore, a trade study has also been performed among these solid waste processing technologies in an effort to determine the ideal technology for long-term life support missions.

Identifying Model-Based Reconfiguration Goals through Functional Deficiencies

NASA Technical Reports Server (NTRS)

Benazera, Emmanuel; Trave-Massuyes, Louise

2004-01-01

Model-based diagnosis is now advanced to the point autonomous systems face some uncertain and faulty situations with success. The next step toward more autonomy is to have the system recovering itself after faults occur, a process known as model-based reconfiguration. After faults occur, given a prediction of the nominal behavior of the system and the result of the diagnosis operation, this paper details how to automatically determine the functional deficiencies of the system. These deficiencies are characterized in the case of uncertain state estimates. A methodology is then presented to determine the reconfiguration goals based on the deficiencies. Finally, a recovery process interleaves planning and model predictive control to restore the functionalities in prioritized order.

General methodology for nonlinear modeling of neural systems with Poisson point-process inputs.

PubMed

Marmarelis, V Z; Berger, T W

2005-07-01

This paper presents a general methodological framework for the practical modeling of neural systems with point-process inputs (sequences of action potentials or, more broadly, identical events) based on the Volterra and Wiener theories of functional expansions and system identification. The paper clarifies the distinctions between Volterra and Wiener kernels obtained from Poisson point-process inputs. It shows that only the Wiener kernels can be estimated via cross-correlation, but must be defined as zero along the diagonals. The Volterra kernels can be estimated far more accurately (and from shorter data-records) by use of the Laguerre expansion technique adapted to point-process inputs, and they are independent of the mean rate of stimulation (unlike their P-W counterparts that depend on it). The Volterra kernels can also be estimated for broadband point-process inputs that are not Poisson. Useful applications of this modeling approach include cases where we seek to determine (model) the transfer characteristics between one neuronal axon (a point-process 'input') and another axon (a point-process 'output') or some other measure of neuronal activity (a continuous 'output', such as population activity) with which a causal link exists.

Containerless processing of undercooled melts

NASA Technical Reports Server (NTRS)

Perepezko, J. H.

1993-01-01

The investigation focused on the control of microstructural evolution in Mn-Al, Fe-Ni, Ni-V, and Au-Pb-Sb alloys through the high undercooling levels provided by containerless processing, and provided fundamental new information on the control of nucleation. Solidification analysis was conducted by means of thermal analysis, x-ray diffraction, and metallographic characterization on samples processed in a laboratory scale drop tube system. The Mn-Al alloy system offers a useful model system with the capability of phase separation on an individual particle basis, thus permitting a more complete understanding of the operative kinetics and the key containerless processing variables. This system provided the opportunity of analyzing the nucleation rate as a function of processing conditions and allowed for the quantitative assessment of the relevant processing parameters. These factors are essential in the development of a containerless processing model which has a predictive capability. Similarly, Ni-V is a model system that was used to study duplex partitionless solidification, which is a structure possible only in high under cooling solidification processes. Nucleation kinetics for the competing bcc and fcc phases were studied to determine how this structure can develop and the conditions under which it may occur. The Fe-Ni alloy system was studied to identify microstructural transitions with controlled variations in sample size and composition during containerless solidification. This work was forwarded to develop a microstructure map which delineates regimes of structural evolution and provides a unified analysis of experimental observations. The Au-Pb-Sb system was investigated to characterize the thermodynamic properties of the undercooled liquid phase and to characterize the glass transition under a variety of processing conditions. By analyzing key containerless processing parameters in a ground based drop tube study, a carefully designed flight experiment may be planned to utilize the extended duration microgravity conditions of orbiting spacecraft.

Simulation of thermally induced processes of diffusion and phase formation in layered binary metallic systems

NASA Astrophysics Data System (ADS)

Rusakov, V. S.; Sukhorukov, I. A.; Zhankadamova, A. M.; Kadyrzhanov, K. K.

2010-05-01

Results of the simulation of thermally induced processes of diffusion and phase formation in model and experimentally investigated layered binary metallic systems are presented. The physical model is based on the Darken phenomenological theory and on the mechanism of interdiffusion of components along the continuous diffusion channels of phases in the two-phase regions of the system. The simulation of processes in the model systems showed that the thermally stabilized concentration profiles in two-layer binary metallic systems are virtually independent of the partial diffusion coefficients; for the systems with the average concentration of components that is the same over the sample depth, the time of the thermal stabilization of the structural and phase state inhomogeneous over the depth grows according to a power law with increasing thickness of the system in such a manner that the thicknesses of the surface layers grow, while the thickness of the intermediate layer approaches a constant value. The results of the simulation of the processes of diffusion and phase formation in experimentally investigated layered binary systems Fe-Ti and Cu-Be upon sequential isothermal and isochronous annealings agree well with the experimental data.

Microphysics, Radiation and Surface Processes in the Goddard Cumulus Ensemble (GCE) Model

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Simpson, J.; Baker, D.; Braun, S.; Chou, M.-D.; Ferrier, B.; Johnson, D.; Khain, A.; Lang, S.; Lynn, B.

2001-01-01

The response of cloud systems to their environment is an important link in a chain of processes responsible for monsoons, frontal depression, El Nino Southern Oscillation (ENSO) episodes and other climate variations (e.g., 30-60 day intra-seasonal oscillations). Numerical models of cloud properties provide essential insights into the interactions of clouds with each other, with their surroundings, and with land and ocean surfaces. Significant advances are currently being made in the modeling of rainfall and rain-related cloud processes, ranging in scales from the very small up to the simulation of an extensive population of raining cumulus clouds in a tropical- or midlatitude-storm environment. The Goddard Cumulus Ensemble (GCE) model is a multi-dimensional nonhydrostatic dynamic/microphysical cloud resolving model. It has been used to simulate many different mesoscale convective systems that occurred in various geographic locations. In this paper, recent GCE model improvements (microphysics, radiation and surface processes) will be described as well as their impact on the development of precipitation events from various geographic locations. The performance of these new physical processes will be examined by comparing the model results with observations. In addition, the explicit interactive processes between cloud, radiation and surface processes will be discussed.

Aligning observed and modelled behaviour based on workflow decomposition

NASA Astrophysics Data System (ADS)

Wang, Lu; Du, YuYue; Liu, Wei

2017-09-01

When business processes are mostly supported by information systems, the availability of event logs generated from these systems, as well as the requirement of appropriate process models are increasing. Business processes can be discovered, monitored and enhanced by extracting process-related information. However, some events cannot be correctly identified because of the explosion of the amount of event logs. Therefore, a new process mining technique is proposed based on a workflow decomposition method in this paper. Petri nets (PNs) are used to describe business processes, and then conformance checking of event logs and process models is investigated. A decomposition approach is proposed to divide large process models and event logs into several separate parts that can be analysed independently; while an alignment approach based on a state equation method in PN theory enhances the performance of conformance checking. Both approaches are implemented in programmable read-only memory (ProM). The correctness and effectiveness of the proposed methods are illustrated through experiments.

LISP based simulation generators for modeling complex space processes

NASA Technical Reports Server (NTRS)

Tseng, Fan T.; Schroer, Bernard J.; Dwan, Wen-Shing

1987-01-01

The development of a simulation assistant for modeling discrete event processes is presented. Included are an overview of the system, a description of the simulation generators, and a sample process generated using the simulation assistant.

Author’s response: A universal approach to modeling visual word recognition and reading: not only possible, but also inevitable.

PubMed

Frost, Ram

2012-10-01

I have argued that orthographic processing cannot be understood and modeled without considering the manner in which orthographic structure represents phonological, semantic, and morphological information in a given writing system. A reading theory, therefore, must be a theory of the interaction of the reader with his/her linguistic environment. This outlines a novel approach to studying and modeling visual word recognition, an approach that focuses on the common cognitive principles involved in processing printed words across different writing systems. These claims were challenged by several commentaries that contested the merits of my general theoretical agenda, the relevance of the evolution of writing systems, and the plausibility of finding commonalities in reading across orthographies. Other commentaries extended the scope of the debate by bringing into the discussion additional perspectives. My response addresses all these issues. By considering the constraints of neurobiology on modeling reading, developmental data, and a large scope of cross-linguistic evidence, I argue that front-end implementations of orthographic processing that do not stem from a comprehensive theory of the complex information conveyed by writing systems do not present a viable approach for understanding reading. The common principles by which writing systems have evolved to represent orthographic, phonological, and semantic information in a language reveal the critical distributional characteristics of orthographic structure that govern reading behavior. Models of reading should thus be learning models, primarily constrained by cross-linguistic developmental evidence that describes how the statistical properties of writing systems shape the characteristics of orthographic processing. When this approach is adopted, a universal model of reading is possible.

An integrative neural model of social perception, action observation, and theory of mind.

PubMed

Yang, Daniel Y-J; Rosenblau, Gabriela; Keifer, Cara; Pelphrey, Kevin A

2015-04-01

In the field of social neuroscience, major branches of research have been instrumental in describing independent components of typical and aberrant social information processing, but the field as a whole lacks a comprehensive model that integrates different branches. We review existing research related to the neural basis of three key neural systems underlying social information processing: social perception, action observation, and theory of mind. We propose an integrative model that unites these three processes and highlights the posterior superior temporal sulcus (pSTS), which plays a central role in all three systems. Furthermore, we integrate these neural systems with the dual system account of implicit and explicit social information processing. Large-scale meta-analyses based on Neurosynth confirmed that the pSTS is at the intersection of the three neural systems. Resting-state functional connectivity analysis with 1000 subjects confirmed that the pSTS is connected to all other regions in these systems. The findings presented in this review are specifically relevant for psychiatric research especially disorders characterized by social deficits such as autism spectrum disorder. Copyright © 2015 Elsevier Ltd. All rights reserved.

An integrative neural model of social perception, action observation, and theory of mind

PubMed Central

Yang, Daniel Y.-J.; Rosenblau, Gabriela; Keifer, Cara; Pelphrey, Kevin A.

2016-01-01

In the field of social neuroscience, major branches of research have been instrumental in describing independent components of typical and aberrant social information processing, but the field as a whole lacks a comprehensive model that integrates different branches. We review existing research related to the neural basis of three key neural systems underlying social information processing: social perception, action observation, and theory of mind. We propose an integrative model that unites these three processes and highlights the posterior superior temporal sulcus (pSTS), which plays a central role in all three systems. Furthermore, we integrate these neural systems with the dual system account of implicit and explicit social information processing. Large-scale meta-analyses based on Neurosynth confirmed that the pSTS is at the intersection of the three neural systems. Resting-state functional connectivity analysis with 1000 subjects confirmed that the pSTS is connected to all other regions in these systems. The findings presented in this review are specifically relevant for psychiatric research especially disorders characterized by social deficits such as autism spectrum disorder. PMID:25660957

An integrated decision model for the application of airborne sensors for improved response to accidental and terrorist chemical vapor releases

NASA Astrophysics Data System (ADS)

Kapitan, Loginn

This research created a new model which provides an integrated approach to planning the effective selection and employment of airborne sensor systems in response to accidental or intentional chemical vapor releases. The approach taken was to use systems engineering and decision analysis methods to construct a model architecture which produced a modular structure for integrating both new and existing components into a logical procedure to assess the application of airborne sensor systems to address chemical vapor hazards. The resulting integrated process model includes an internal aggregation model which allowed differentiation among alternative airborne sensor systems. Both models were developed and validated by experts and demonstrated using appropriate hazardous chemical release scenarios. The resultant prototype integrated process model or system fills a current gap in capability allowing improved planning, training and exercise for HAZMAT teams and first responders when considering the selection and employment of airborne sensor systems. Through the research process, insights into the current response structure and how current airborne capability may be most effectively used were generated. Furthermore, the resultant prototype system is tailorable for local, state, and federal application, and can potentially be modified to help evaluate investments in new airborne sensor technology and systems. Better planning, training and preparedness exercising holds the prospect for the effective application of airborne assets for improved response to large scale chemical release incidents. Improved response will result in fewer casualties and lives lost, reduced economic impact, and increased protection of critical infrastructure when faced with accidental and intentional terrorist release of hazardous industrial chemicals. With the prospect of more airborne sensor systems becoming available, this prototype system integrates existing and new tools into an effective process for the selection and employment of airborne sensors to better plan, train and exercise ahead of potential chemical release events.

Comparison of different modelling approaches of drive train temperature for the purposes of wind turbine failure detection

NASA Astrophysics Data System (ADS)

Tautz-Weinert, J.; Watson, S. J.

2016-09-01

Effective condition monitoring techniques for wind turbines are needed to improve maintenance processes and reduce operational costs. Normal behaviour modelling of temperatures with information from other sensors can help to detect wear processes in drive trains. In a case study, modelling of bearing and generator temperatures is investigated with operational data from the SCADA systems of more than 100 turbines. The focus is here on automated training and testing on a farm level to enable an on-line system, which will detect failures without human interpretation. Modelling based on linear combinations, artificial neural networks, adaptive neuro-fuzzy inference systems, support vector machines and Gaussian process regression is compared. The selection of suitable modelling inputs is discussed with cross-correlation analyses and a sensitivity study, which reveals that the investigated modelling techniques react in different ways to an increased number of inputs. The case study highlights advantages of modelling with linear combinations and artificial neural networks in a feedforward configuration.

Technical Note: The Modular Earth Submodel System (MESSy) - a new approach towards Earth System Modeling

NASA Astrophysics Data System (ADS)

Jöckel, P.; Sander, R.; Kerkweg, A.; Tost, H.; Lelieveld, J.

2005-02-01

The development of a comprehensive Earth System Model (ESM) to study the interactions between chemical, physical, and biological processes, requires coupling of the different domains (land, ocean, atmosphere, ...). One strategy is to link existing domain-specific models with a universal coupler, i.e. an independent standalone program organizing the communication between other programs. In many cases, however, a much simpler approach is more feasible. We have developed the Modular Earth Submodel System (MESSy). It comprises (1) a modular interface structure to connect to a , (2) an extendable set of such for miscellaneous processes, and (3) a coding standard. MESSy is therefore not a coupler in the classical sense, but exchanges data between a and several within one comprehensive executable. The internal complexity of the is controllable in a transparent and user friendly way. This provides remarkable new possibilities to study feedback mechanisms (by two-way coupling). Note that the MESSy and the coupler approach can be combined. For instance, an atmospheric model implemented according to the MESSy standard could easily be coupled to an ocean model by means of an external coupler. The vision is to ultimately form a comprehensive ESM which includes a large set of submodels, and a base model which contains only a central clock and runtime control. This can be reached stepwise, since each process can be included independently. Starting from an existing model, process submodels can be reimplemented according to the MESSy standard. This procedure guarantees the availability of a state-of-the-art model for scientific applications at any time of the development. In principle, MESSy can be implemented into any kind of model, either global or regional. So far, the MESSy concept has been applied to the general circulation model ECHAM5 and a number of process boxmodels.

A web platform for integrated surface water - groundwater modeling and data management

NASA Astrophysics Data System (ADS)

Fatkhutdinov, Aybulat; Stefan, Catalin; Junghanns, Ralf

2016-04-01

Model-based decision support systems are considered to be reliable and time-efficient tools for resources management in various hydrology related fields. However, searching and acquisition of the required data, preparation of the data sets for simulations as well as post-processing, visualization and publishing of the simulations results often requires significantly more work and time than performing the modeling itself. The purpose of the developed software is to combine data storage facilities, data processing instruments and modeling tools in a single platform which potentially can reduce time required for performing simulations, hence decision making. The system is developed within the INOWAS (Innovative Web Based Decision Support System for Water Sustainability under a Changing Climate) project. The platform integrates spatially distributed catchment scale rainfall - runoff, infiltration and groundwater flow models with data storage, processing and visualization tools. The concept is implemented in a form of a web-GIS application and is build based on free and open source components, including the PostgreSQL database management system, Python programming language for modeling purposes, Mapserver for visualization and publishing the data, Openlayers for building the user interface and others. Configuration of the system allows performing data input, storage, pre- and post-processing and visualization in a single not disturbed workflow. In addition, realization of the decision support system in the form of a web service provides an opportunity to easily retrieve and share data sets as well as results of simulations over the internet, which gives significant advantages for collaborative work on the projects and is able to significantly increase usability of the decision support system.

Red mud flocculation process in alumina production

NASA Astrophysics Data System (ADS)

Fedorova, E. R.; Firsov, A. Yu

2018-05-01

The process of thickening and washing red mud is a gooseneck of alumina production. The existing automated systems of the thickening process control involve stabilizing the parameters of the primary technological circuits of the thickener. The actual direction of scientific research is the creation and improvement of models and systems of the thickening process control by model. But the known models do not fully consider the presence of perturbing effects, in particular the particle size distribution in the feed process, distribution of floccules by size after the aggregation process in the feed barrel. The article is devoted to the basic concepts and terms used in writing the population balance algorithm. The population balance model is implemented in the MatLab environment. The result of the simulation is the particle size distribution after the flocculation process. This model allows one to foreseen the distribution range of floccules after the process of aggregation of red mud in the feed barrel. The mud of Jamaican bauxite was acting as an industrial sample of red mud; Cytec Industries of HX-3000 series with a concentration of 0.5% was acting as a flocculant. When simulating, model constants obtained in a tubular tank in the laboratories of CSIRO (Australia) were used.

Generating Systems Biology Markup Language Models from the Synthetic Biology Open Language.

PubMed

Roehner, Nicholas; Zhang, Zhen; Nguyen, Tramy; Myers, Chris J

2015-08-21

In the context of synthetic biology, model generation is the automated process of constructing biochemical models based on genetic designs. This paper discusses the use cases for model generation in genetic design automation (GDA) software tools and introduces the foundational concepts of standards and model annotation that make this process useful. Finally, this paper presents an implementation of model generation in the GDA software tool iBioSim and provides an example of generating a Systems Biology Markup Language (SBML) model from a design of a 4-input AND sensor written in the Synthetic Biology Open Language (SBOL).

Aspects regarding at 13C isotope separation column control using Petri nets system

NASA Astrophysics Data System (ADS)

Boca, M. L.; Ciortea, M. E.

2015-11-01

This paper is intended to show that Petri nets can be also applicable in the chemical industry. It used linear programming, modeling underlying Petri nets, especially discrete event systems for isotopic separation, the purpose of considering and control events in real-time through graphical representations. In this paper it is simulate the control of 13C Isotope Separation column using Petri nets. The major problem with 13C comes from the difficulty of obtaining it and raising its natural fraction. Carbon isotopes can be obtained using many methods, one of them being the cryogenic distillation of carbon monoxide. Some few aspects regarding operating conditions and the construction of such cryogenic plants are known today, and even less information are available as far as the separation process modeling and control are concerned. In fact, the efficient control of the carbon monoxide distillation process represents a necessity for large-scale 13C production. Referring to a classic distillation process, some models for carbon isotope separation have been proposed, some based on mass, component and energy balance equations, some on the nonlinear wave theory or the Cohen equations. For modeling the system it was used Petri nets because in this case it is deal with discrete event systems. In use of the non-timed and with auxiliary times Petri model, the transport stream was divided into sections and these sections will be analyzed successively. Because of the complexity of the system and the large amount of calculations required it was not possible to analyze the system as a unitary whole. A first attempt to model the system as a unitary whole led to the blocking of the model during simulation, because of the large processing times.

A Hybrid Multiscale Framework for Subsurface Flow and Transport Simulations

DOE PAGES

Scheibe, Timothy D.; Yang, Xiaofan; Chen, Xingyuan; ...

2015-06-01

Extensive research efforts have been invested in reducing model errors to improve the predictive ability of biogeochemical earth and environmental system simulators, with applications ranging from contaminant transport and remediation to impacts of biogeochemical elemental cycling (e.g., carbon and nitrogen) on local ecosystems and regional to global climate. While the bulk of this research has focused on improving model parameterizations in the face of observational limitations, the more challenging type of model error/uncertainty to identify and quantify is model structural error which arises from incorrect mathematical representations of (or failure to consider) important physical, chemical, or biological processes, properties, ormore » system states in model formulations. While improved process understanding can be achieved through scientific study, such understanding is usually developed at small scales. Process-based numerical models are typically designed for a particular characteristic length and time scale. For application-relevant scales, it is generally necessary to introduce approximations and empirical parameterizations to describe complex systems or processes. This single-scale approach has been the best available to date because of limited understanding of process coupling combined with practical limitations on system characterization and computation. While computational power is increasing significantly and our understanding of biological and environmental processes at fundamental scales is accelerating, using this information to advance our knowledge of the larger system behavior requires the development of multiscale simulators. Accordingly there has been much recent interest in novel multiscale methods in which microscale and macroscale models are explicitly coupled in a single hybrid multiscale simulation. A limited number of hybrid multiscale simulations have been developed for biogeochemical earth systems, but they mostly utilize application-specific and sometimes ad-hoc approaches for model coupling. We are developing a generalized approach to hierarchical model coupling designed for high-performance computational systems, based on the Swift computing workflow framework. In this presentation we will describe the generalized approach and provide two use cases: 1) simulation of a mixing-controlled biogeochemical reaction coupling pore- and continuum-scale models, and 2) simulation of biogeochemical impacts of groundwater – river water interactions coupling fine- and coarse-grid model representations. This generalized framework can be customized for use with any pair of linked models (microscale and macroscale) with minimal intrusiveness to the at-scale simulators. It combines a set of python scripts with the Swift workflow environment to execute a complex multiscale simulation utilizing an approach similar to the well-known Heterogeneous Multiscale Method. User customization is facilitated through user-provided input and output file templates and processing function scripts, and execution within a high-performance computing environment is handled by Swift, such that minimal to no user modification of at-scale codes is required.« less

Supporting BPMN choreography with system integration artefacts for enterprise process collaboration

NASA Astrophysics Data System (ADS)

Nie, Hongchao; Lu, Xudong; Duan, Huilong

2014-07-01

Business Process Model and Notation (BPMN) choreography modelling depicts externally visible message exchanges between collaborating processes of enterprise information systems. Implementation of choreography relies on designing system integration solutions to realise message exchanges between independently developed systems. Enterprise integration patterns (EIPs) are widely accepted artefacts to design integration solutions. If the choreography model represents coordination requirements between processes with behaviour mismatches, the integration designer needs to analyse the routing requirements and address these requirements by manually designing EIP message routers. As collaboration scales and complexity increases, manual design becomes inefficient. Thus, the research problem of this paper is to explore a method to automatically identify routing requirements from BPMN choreography model and to accordingly design routing in the integration solution. To achieve this goal, recurring behaviour mismatch scenarios are analysed as patterns, and corresponding solutions are proposed as EIP routers. Using this method, a choreography model can be analysed by computer to identify occurrences of mismatch patterns, leading to corresponding router selection. A case study demonstrates that the proposed method enables computer-assisted integration design to implement choreography. A further experiment reveals that the method is effective to improve the design quality and reduce time cost.

Zeolite formation from coal fly ash and heavy metal ion removal characteristics of thus-obtained Zeolite X in multi-metal systems.

PubMed

Jha, Vinay Kumar; Nagae, Masahiro; Matsuda, Motohide; Miyake, Michihiro

2009-06-01

Zeolitic materials have been prepared from coal fly ash as well as from a SiO(2)-Al(2)O(3) system upon NaOH fusion treatment, followed by subsequent hydrothermal processing at various NaOH concentrations and reaction times. During the preparation process, the starting material initially decomposed to an amorphous form, and the nucleation process of the zeolite began. The carbon content of the starting material influenced the formation of the zeolite by providing an active surface for nucleation. Zeolite A (Na-A) was transformed into zeolite X (Na-X) with increasing NaOH concentration and reaction time. The adsorption isotherms of the obtained Na-X based on the characteristics required to remove heavy ions such as Ni(2+), Cu(2+), Cd(2+) and Pb(2+) were examined in multi-metal systems. Thus obtained experimental data suggests that the Langmuir and Freundlich models are more accurate compared to the Dubinin-Kaganer-Radushkevich (DKR) model. However, the sorption energy obtained from the DKR model was helpful in elucidating the mechanism of the sorption process. Further, in going from a single- to multi-metal system, the degree of fitting for the Freundlich model compared with the Langmuir model was favored due to its basic assumption of a heterogeneity factor. The Extended-Langmuir model may be used in multi-metal systems, but gives a lower value for equilibrium sorption compared with the Langmuir model.

Class Model Development Using Business Rules

NASA Astrophysics Data System (ADS)

Skersys, Tomas; Gudas, Saulius

New developments in the area of computer-aided system engineering (CASE) greatly improve processes of the information systems development life cycle (ISDLC). Much effort is put into the quality improvement issues, but IS development projects still suffer from the poor quality of models during the system analysis and design cycles. At some degree, quality of models that are developed using CASE tools can be assured using various. automated. model comparison, syntax. checking procedures. It. is also reasonable to check these models against the business domain knowledge, but the domain knowledge stored in the repository of CASE tool (enterprise model) is insufficient (Gudas et al. 2004). Involvement of business domain experts into these processes is complicated because non- IT people often find it difficult to understand models that were developed by IT professionals using some specific modeling language.

The Modular Modeling System (MMS): A modeling framework for water- and environmental-resources management

USGS Publications Warehouse

Leavesley, G.H.; Markstrom, S.L.; Viger, R.J.

2004-01-01

The interdisciplinary nature and increasing complexity of water- and environmental-resource problems require the use of modeling approaches that can incorporate knowledge from a broad range of scientific disciplines. The large number of distributed hydrological and ecosystem models currently available are composed of a variety of different conceptualizations of the associated processes they simulate. Assessment of the capabilities of these distributed models requires evaluation of the conceptualizations of the individual processes, and the identification of which conceptualizations are most appropriate for various combinations of criteria, such as problem objectives, data constraints, and spatial and temporal scales of application. With this knowledge, "optimal" models for specific sets of criteria can be created and applied. The U.S. Geological Survey (USGS) Modular Modeling System (MMS) is an integrated system of computer software that has been developed to provide these model development and application capabilities. MMS supports the integration of models and tools at a variety of levels of modular design. These include individual process models, tightly coupled models, loosely coupled models, and fully-integrated decision support systems. A variety of visualization and statistical tools are also provided. MMS has been coupled with the Bureau of Reclamation (BOR) object-oriented reservoir and river-system modeling framework, RiverWare, under a joint USGS-BOR program called the Watershed and River System Management Program. MMS and RiverWare are linked using a shared relational database. The resulting database-centered decision support system provides tools for evaluating and applying optimal resource-allocation and management strategies to complex, operational decisions on multipurpose reservoir systems and watersheds. Management issues being addressed include efficiency of water-resources management, environmental concerns such as meeting flow needs for endangered species, and optimizing operations within the constraints of multiple objectives such as power generation, irrigation, and water conservation. This decision support system approach is being developed, tested, and implemented in the Gunni-son, Yakima, San Juan, Rio Grande, and Truckee River basins of the western United States. Copyright ASCE 2004.

Modeling of Electrocardiograph Telediagnosing System Based on Petri Net

NASA Astrophysics Data System (ADS)

Hu, Wensong; Li, Ming; Li, Lan

This paper analyzed the characteristics of the electrocardiograph telediagnosing system. Firstly, we introduce the system and Petri nets. Secondly, we built a topological diagram of this system. Then we use Petri nets to show the physical process of this system. Finally, we verified the model of the electrocardiograph telediagnosing system. With the help of model based on Petri nets, we analyzed the system performance and feasibility.

The Value of SysML Modeling During System Operations: A Case Study

NASA Technical Reports Server (NTRS)

Dutenhoffer, Chelsea; Tirona, Joseph

2013-01-01

System models are often touted as engineering tools that promote better understanding of systems, but these models are typically created during system design. The Ground Data System (GDS) team for the Dawn spacecraft took on a case study to see if benefits could be achieved by starting a model of a system already in operations. This paper focuses on the four steps the team undertook in modeling the Dawn GDS: defining a model structure, populating model elements, verifying that the model represented reality, and using the model to answer system-level questions and simplify day-to-day tasks. Throughout this paper the team outlines our thought processes and the system insights the model provided.

The value of SysML modeling during system operations: A case study

NASA Astrophysics Data System (ADS)

Dutenhoffer, C.; Tirona, J.

System models are often touted as engineering tools that promote better understanding of systems, but these models are typically created during system design. The Ground Data System (GDS) team for the Dawn spacecraft took on a case study to see if benefits could be achieved by starting a model of a system already in operations. This paper focuses on the four steps the team undertook in modeling the Dawn GDS: defining a model structure, populating model elements, verifying that the model represented reality, and using the model to answer system-level questions and simplify day-to-day tasks. Throughout this paper the team outlines our thought processes and the system insights the model provided.

On the next generation of reliability analysis tools

NASA Technical Reports Server (NTRS)

Babcock, Philip S., IV; Leong, Frank; Gai, Eli

1987-01-01

The current generation of reliability analysis tools concentrates on improving the efficiency of the description and solution of the fault-handling processes and providing a solution algorithm for the full system model. The tools have improved user efficiency in these areas to the extent that the problem of constructing the fault-occurrence model is now the major analysis bottleneck. For the next generation of reliability tools, it is proposed that techniques be developed to improve the efficiency of the fault-occurrence model generation and input. Further, the goal is to provide an environment permitting a user to provide a top-down design description of the system from which a Markov reliability model is automatically constructed. Thus, the user is relieved of the tedious and error-prone process of model construction, permitting an efficient exploration of the design space, and an independent validation of the system's operation is obtained. An additional benefit of automating the model construction process is the opportunity to reduce the specialized knowledge required. Hence, the user need only be an expert in the system he is analyzing; the expertise in reliability analysis techniques is supplied.

A corpus of full-text journal articles is a robust evaluation tool for revealing differences in performance of biomedical natural language processing tools

PubMed Central

2012-01-01

Background We introduce the linguistic annotation of a corpus of 97 full-text biomedical publications, known as the Colorado Richly Annotated Full Text (CRAFT) corpus. We further assess the performance of existing tools for performing sentence splitting, tokenization, syntactic parsing, and named entity recognition on this corpus. Results Many biomedical natural language processing systems demonstrated large differences between their previously published results and their performance on the CRAFT corpus when tested with the publicly available models or rule sets. Trainable systems differed widely with respect to their ability to build high-performing models based on this data. Conclusions The finding that some systems were able to train high-performing models based on this corpus is additional evidence, beyond high inter-annotator agreement, that the quality of the CRAFT corpus is high. The overall poor performance of various systems indicates that considerable work needs to be done to enable natural language processing systems to work well when the input is full-text journal articles. The CRAFT corpus provides a valuable resource to the biomedical natural language processing community for evaluation and training of new models for biomedical full text publications. PMID:22901054

Microphone Array Phased Processing System (MAPPS): Version 4.0 Manual

NASA Technical Reports Server (NTRS)

Watts, Michael E.; Mosher, Marianne; Barnes, Michael; Bardina, Jorge

1999-01-01

A processing system has been developed to meet increasing demands for detailed noise measurement of individual model components. The Microphone Array Phased Processing System (MAPPS) uses graphical user interfaces to control all aspects of data processing and visualization. The system uses networked parallel computers to provide noise maps at selected frequencies in a near real-time testing environment. The system has been successfully used in the NASA Ames 7- by 10-Foot Wind Tunnel.

The Application of Collaborative Business Intelligence Technology in the Hospital SPD Logistics Management Model.

PubMed

Liu, Tongzhu; Shen, Aizong; Hu, Xiaojian; Tong, Guixian; Gu, Wei

2017-06-01

We aimed to apply collaborative business intelligence (BI) system to hospital supply, processing and distribution (SPD) logistics management model. We searched Engineering Village database, China National Knowledge Infrastructure (CNKI) and Google for articles (Published from 2011 to 2016), books, Web pages, etc., to understand SPD and BI related theories and recent research status. For the application of collaborative BI technology in the hospital SPD logistics management model, we realized this by leveraging data mining techniques to discover knowledge from complex data and collaborative techniques to improve the theories of business process. For the application of BI system, we: (i) proposed a layered structure of collaborative BI system for intelligent management in hospital logistics; (ii) built data warehouse for the collaborative BI system; (iii) improved data mining techniques such as supporting vector machines (SVM) and swarm intelligence firefly algorithm to solve key problems in hospital logistics collaborative BI system; (iv) researched the collaborative techniques oriented to data and business process optimization to improve the business processes of hospital logistics management. Proper combination of SPD model and BI system will improve the management of logistics in the hospitals. The successful implementation of the study requires: (i) to innovate and improve the traditional SPD model and make appropriate implement plans and schedules for the application of BI system according to the actual situations of hospitals; (ii) the collaborative participation of internal departments in hospital including the department of information, logistics, nursing, medical and financial; (iii) timely response of external suppliers.

Experimental research on mathematical modelling and unconventional control of clinker kiln in cement plants

NASA Astrophysics Data System (ADS)

Rusu-Anghel, S.

2017-01-01

Analytical modeling of the flow of manufacturing process of the cement is difficult because of their complexity and has not resulted in sufficiently precise mathematical models. In this paper, based on a statistical model of the process and using the knowledge of human experts, was designed a fuzzy system for automatic control of clinkering process.

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

USDA-ARS?s Scientific Manuscript database

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...

Toward a Neural Basis of Music Perception – A Review and Updated Model

PubMed Central

Koelsch, Stefan

2011-01-01

Music perception involves acoustic analysis, auditory memory, auditory scene analysis, processing of interval relations, of musical syntax and semantics, and activation of (pre)motor representations of actions. Moreover, music perception potentially elicits emotions, thus giving rise to the modulation of emotional effector systems such as the subjective feeling system, the autonomic nervous system, the hormonal, and the immune system. Building on a previous article (Koelsch and Siebel, 2005), this review presents an updated model of music perception and its neural correlates. The article describes processes involved in music perception, and reports EEG and fMRI studies that inform about the time course of these processes, as well as about where in the brain these processes might be located. PMID:21713060

Processing of Visual Imagery by an Adaptive Model of the Visual System: Its Performance and its Significance. Final Report, June 1969-March 1970.

ERIC Educational Resources Information Center

Tallman, Oliver H.

A digital simulation of a model for the processing of visual images is derived from known aspects of the human visual system. The fundamental principle of computation suggested by a biological model is a transformation that distributes information contained in an input stimulus everywhere in a transform domain. Each sensory input contributes under…

Using fuzzy rule-based knowledge model for optimum plating conditions search

NASA Astrophysics Data System (ADS)

Solovjev, D. S.; Solovjeva, I. A.; Litovka, Yu V.; Arzamastsev, A. A.; Glazkov, V. P.; L’vov, A. A.

2018-03-01

The paper discusses existing approaches to plating process modeling in order to decrease the distribution thickness of plating surface cover. However, these approaches do not take into account the experience, knowledge, and intuition of the decision-makers when searching the optimal conditions of electroplating technological process. The original approach to optimal conditions search for applying the electroplating coatings, which uses the rule-based model of knowledge and allows one to reduce the uneven product thickness distribution, is proposed. The block diagrams of a conventional control system of a galvanic process as well as the system based on the production model of knowledge are considered. It is shown that the fuzzy production model of knowledge in the control system makes it possible to obtain galvanic coatings of a given thickness unevenness with a high degree of adequacy to the experimental data. The described experimental results confirm the theoretical conclusions.

Symbolic Number Comparison Is Not Processed by the Analog Number System: Different Symbolic and Non-symbolic Numerical Distance and Size Effects

PubMed Central

Krajcsi, Attila; Lengyel, Gábor; Kojouharova, Petia

2018-01-01

HIGHLIGHTS We test whether symbolic number comparison is handled by an analog noisy system.Analog system model has systematic biases in describing symbolic number comparison.This suggests that symbolic and non-symbolic numbers are processed by different systems. Dominant numerical cognition models suppose that both symbolic and non-symbolic numbers are processed by the Analog Number System (ANS) working according to Weber's law. It was proposed that in a number comparison task the numerical distance and size effects reflect a ratio-based performance which is the sign of the ANS activation. However, increasing number of findings and alternative models propose that symbolic and non-symbolic numbers might be processed by different representations. Importantly, alternative explanations may offer similar predictions to the ANS prediction, therefore, former evidence usually utilizing only the goodness of fit of the ANS prediction is not sufficient to support the ANS account. To test the ANS model more rigorously, a more extensive test is offered here. Several properties of the ANS predictions for the error rates, reaction times, and diffusion model drift rates were systematically analyzed in both non-symbolic dot comparison and symbolic Indo-Arabic comparison tasks. It was consistently found that while the ANS model's prediction is relatively good for the non-symbolic dot comparison, its prediction is poorer and systematically biased for the symbolic Indo-Arabic comparison. We conclude that only non-symbolic comparison is supported by the ANS, and symbolic number comparisons are processed by other representation. PMID:29491845

Physics and Process Modeling (PPM) and Other Propulsion R and T. Volume 1; Materials Processing, Characterization, and Modeling; Lifting Models

NASA Technical Reports Server (NTRS)

1997-01-01

This CP contains the extended abstracts and presentation figures of 36 papers presented at the PPM and Other Propulsion R&T Conference. The focus of the research described in these presentations is on materials and structures technologies that are parts of the various projects within the NASA Aeronautics Propulsion Systems Research and Technology Base Program. These projects include Physics and Process Modeling; Smart, Green Engine; Fast, Quiet Engine; High Temperature Engine Materials Program; and Hybrid Hyperspeed Propulsion. Also presented were research results from the Rotorcraft Systems Program and work supported by the NASA Lewis Director's Discretionary Fund. Authors from NASA Lewis Research Center, industry, and universities conducted research in the following areas: material processing, material characterization, modeling, life, applied life models, design techniques, vibration control, mechanical components, and tribology. Key issues, research accomplishments, and future directions are summarized in this publication.

Establishment of Textbook Information Management System Based on Active Server Page

ERIC Educational Resources Information Center

Geng, Lihua

2011-01-01

In the process of textbook management of universities, the flow of storage, collection and check of textbook is quite complicated and daily management flow and system also seriously constrains the efficiency of the management process. Thus, in order to combine the information management model and the traditional management model, it is necessary…

How Do Students Regulate their Learning of Complex Systems with Hypermedia?.

ERIC Educational Resources Information Center

Azevedo, Roger; Seibert, Diane; Guthrie, John T.; Cromley, Jennifer G.; Wang, Huei-yu; Tron, Myriam

This study examined the role of different goal-setting instructional interventions in facilitating students' shift to more sophisticated mental models of the circulatory system as indicated by both performance and process data. Researchers adopted the information processing model of self-regulated learning of P. Winne and colleagues (1998, 2001)…

Model Transformation for a System of Systems Dependability Safety Case

NASA Technical Reports Server (NTRS)

Murphy, Judy; Driskell, Steve

2011-01-01

The presentation reviews the dependability and safety effort of NASA's Independent Verification and Validation Facility. Topics include: safety engineering process, applications to non-space environment, Phase I overview, process creation, sample SRM artifact, Phase I end result, Phase II model transformation, fault management, and applying Phase II to individual projects.

Development of a robust space power system decision model

NASA Astrophysics Data System (ADS)

Chew, Gilbert; Pelaccio, Dennis G.; Jacobs, Mark; Stancati, Michael; Cataldo, Robert

2001-02-01

NASA continues to evaluate power systems to support human exploration of the Moon and Mars. The system(s) would address all power needs of surface bases and on-board power for space transfer vehicles. Prior studies have examined both solar and nuclear-based alternatives with respect to individual issues such as sizing or cost. What has not been addressed is a comprehensive look at the risks and benefits of the options that could serve as the analytical framework to support a system choice that best serves the needs of the exploration program. This paper describes the SAIC developed Space Power System Decision Model, which uses a formal Two-step Analytical Hierarchy Process (TAHP) methodology that is used in the decision-making process to clearly distinguish candidate power systems in terms of benefits, safety, and risk. TAHP is a decision making process based on the Analytical Hierarchy Process, which employs a hierarchic approach of structuring decision factors by weights, and relatively ranks system design options on a consistent basis. This decision process also includes a level of data gathering and organization that produces a consistent, well-documented assessment, from which the capability of each power system option to meet top-level goals can be prioritized. The model defined on this effort focuses on the comparative assessment candidate power system options for Mars surface application(s). This paper describes the principles of this approach, the assessment criteria and weighting procedures, and the tools to capture and assess the expert knowledge associated with space power system evaluation. .

An Interactive Teaching System for Bond Graph Modeling and Simulation in Bioengineering

ERIC Educational Resources Information Center

Roman, Monica; Popescu, Dorin; Selisteanu, Dan

2013-01-01

The objective of the present work was to implement a teaching system useful in modeling and simulation of biotechnological processes. The interactive system is based on applications developed using 20-sim modeling and simulation software environment. A procedure for the simulation of bioprocesses modeled by bond graphs is proposed and simulators…

Adaptive optimal input design and parametric estimation of nonlinear dynamical systems: application to neuronal modeling.

PubMed

Madi, Mahmoud K; Karameh, Fadi N

2018-05-11

Many physical models of biological processes including neural systems are characterized by parametric nonlinear dynamical relations between driving inputs, internal states, and measured outputs of the process. Fitting such models using experimental data (data assimilation) is a challenging task since the physical process often operates in a noisy, possibly non-stationary environment; moreover, conducting multiple experiments under controlled and repeatable conditions can be impractical, time consuming or costly. The accuracy of model identification, therefore, is dictated principally by the quality and dynamic richness of collected data over single or few experimental sessions. Accordingly, it is highly desirable to design efficient experiments that, by exciting the physical process with smart inputs, yields fast convergence and increased accuracy of the model. We herein introduce an adaptive framework in which optimal input design is integrated with Square root Cubature Kalman Filters (OID-SCKF) to develop an online estimation procedure that first, converges significantly quicker, thereby permitting model fitting over shorter time windows, and second, enhances model accuracy when only few process outputs are accessible. The methodology is demonstrated on common nonlinear models and on a four-area neural mass model with noisy and limited measurements. Estimation quality (speed and accuracy) is benchmarked against high-performance SCKF-based methods that commonly employ dynamically rich informed inputs for accurate model identification. For all the tested models, simulated single-trial and ensemble averages showed that OID-SCKF exhibited (i) faster convergence of parameter estimates and (ii) lower dependence on inter-trial noise variability with gains up to around 1000 msec in speed and 81% increase in variability for the neural mass models. In terms of accuracy, OID-SCKF estimation was superior, and exhibited considerably less variability across experiments, in identifying model parameters of (a) systems with challenging model inversion dynamics and (b) systems with fewer measurable outputs that directly relate to the underlying processes. Fast and accurate identification therefore carries particular promise for modeling of transient (short-lived) neuronal network dynamics using a spatially under-sampled set of noisy measurements, as is commonly encountered in neural engineering applications. © 2018 IOP Publishing Ltd.

Developing models that analyze the economic/environmental trade-offs implicit in water resource management

NASA Astrophysics Data System (ADS)

Howitt, R. E.

2016-12-01

Hydro-economic models have been used to analyze optimal supply management and groundwater use for the past 25 years. They are characterized by an objective function that usually maximizes economic measures such as consumer and producer surplus subject to hydrologic equations of motion or water distribution systems. The hydrologic and economic components are sometimes fully integrated. Alternatively they may use an iterative interactive process. Environmental considerations have been included in hydro-economic models as inequality constraints. Representing environmental requirements as constraints is a rigid approximation of the range of management alternatives that could be used to implement environmental objectives. The next generation of hydro-economic models, currently being developed, require that the environmental alternatives be represented by continuous or semi-continuous functions which relate water resource use allocated to the environment with the probabilities of achieving environmental objectives. These functions will be generated by process models of environmental and biological systems which are now advanced to the state that they can realistically represent environmental systems and flexibility to interact with economic models. Examples are crop growth models, climate modeling, and biological models of forest, fish, and fauna systems. These process models can represent environmental outcomes in a form that is similar to economic production functions. When combined with economic models the interacting process models can reproduce a range of trade-offs between economic and environmental objectives, and thus optimize social value of many water and environmental resources. Some examples of this next-generation of hydro-enviro- economic models are reviewed. In these models implicit production functions for environmental goods are combined with hydrologic equations of motion and economic response functions. We discuss models that show interaction between environmental goods and agricultural production, and others that address alternative climate change policies, or habitat provision.

Comparisons of in vitro root caries models.

PubMed

Wefel, J S; Heilman, J R; Jordan, T H

1995-01-01

The purpose of this article is to compare various model systems for the production of in vitro root caries and to assess their ability to simulate the naturally occurring root caries process. Partially saturated buffer models and gel models were evaluated using polarized light microscopy and both qualitative and quantitative microradiography. All model systems showed very similar lesion formation when examined under polarized light. When microradiographs were compared, the systems which contained fluoride, showed clear radiopaque bands within the lesion. The bands, which occurred only in the presence of fluoride, appeared to be due to remineralization. When using an in vitro system that simulates the natural root caries process, it is imperative to understand the components of the particular model, as well as its limitations, and to be aware of the need for more than one evaluative technique.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

The model is designed to enable decision makers to compare the economics of geothermal projects with the economics of alternative energy systems at an early stage in the decision process. The geothermal engineering and economic feasibility computer model (GEEF) is written in FORTRAN IV language and can be run on a mainframe or a mini-computer system. An abbreviated version of the model is being developed for usage in conjunction with a programmable desk calculator. The GEEF model has two main segments, namely (i) the engineering design/cost segment and (ii) the economic analysis segment. In the engineering segment, the model determinesmore » the numbers of production and injection wells, heat exchanger design, operating parameters for the system, requirement of supplementary system (to augment the working fluid temperature if the resource temperature is not sufficiently high), and the fluid flow rates. The model can handle single stage systems as well as two stage cascaded systems in which the second stage may involve a space heating application after a process heat application in the first stage.« less

Semantic Web Infrastructure Supporting NextFrAMES Modeling Platform

NASA Astrophysics Data System (ADS)

Lakhankar, T.; Fekete, B. M.; Vörösmarty, C. J.

2008-12-01

Emerging modeling frameworks offer new ways to modelers to develop model applications by offering a wide range of software components to handle common modeling tasks such as managing space and time, distributing computational tasks in parallel processing environment, performing input/output and providing diagnostic facilities. NextFrAMES, the next generation updates to the Framework for Aquatic Modeling of the Earth System originally developed at University of New Hampshire and currently hosted at The City College of New York takes a step further by hiding most of these services from modeler behind a platform agnostic modeling platform that allows scientists to focus on the implementation of scientific concepts in the form of a new modeling markup language and through a minimalist application programming interface that provide means to implement model processes. At the core of the NextFrAMES modeling platform there is a run-time engine that interprets the modeling markup language loads the module plugins establishes the model I/O and executes the model defined by the modeling XML and the accompanying plugins. The current implementation of the run-time engine is designed for single processor or symmetric multi processing (SMP) systems but future implementation of the run-time engine optimized for different hardware architectures are anticipated. The modeling XML and the accompanying plugins define the model structure and the computational processes in a highly abstract manner, which is not only suitable for the run-time engine, but has the potential to integrate into semantic web infrastructure, where intelligent parsers can extract information about the model configurations such as input/output requirements applicable space and time scales and underlying modeling processes. The NextFrAMES run-time engine itself is also designed to tap into web enabled data services directly, therefore it can be incorporated into complex workflow to implement End-to-End application from observation to the delivery of highly aggregated information. Our presentation will discuss the web services ranging from OpenDAP and WaterOneFlow data services to metadata provided through catalog services that could serve NextFrAMES modeling applications. We will also discuss the support infrastructure needed to streamline the integration of NextFrAMES into an End-to-End application to deliver highly processed information to end users. The End-to-End application will be demonstrated through examples from the State-of-the Global Water System effort that builds on data services provided through WMO's Global Terrestrial Network for Hydrology to deliver water resources related information to policy makers for better water management. Key components of this E2E system are promoted as Community of Practice examples for the Global Observing System of Systems therefore the State-of-the Global Water System can be viewed as test case for the interoperability of the incorporated web service components.

Legacy model integration for enhancing hydrologic interdisciplinary research

NASA Astrophysics Data System (ADS)

Dozier, A.; Arabi, M.; David, O.

2013-12-01

Many challenges are introduced to interdisciplinary research in and around the hydrologic science community due to advances in computing technology and modeling capabilities in different programming languages, across different platforms and frameworks by researchers in a variety of fields with a variety of experience in computer programming. Many new hydrologic models as well as optimization, parameter estimation, and uncertainty characterization techniques are developed in scripting languages such as Matlab, R, Python, or in newer languages such as Java and the .Net languages, whereas many legacy models have been written in FORTRAN and C, which complicates inter-model communication for two-way feedbacks. However, most hydrologic researchers and industry personnel have little knowledge of the computing technologies that are available to address the model integration process. Therefore, the goal of this study is to address these new challenges by utilizing a novel approach based on a publish-subscribe-type system to enhance modeling capabilities of legacy socio-economic, hydrologic, and ecologic software. Enhancements include massive parallelization of executions and access to legacy model variables at any point during the simulation process by another program without having to compile all the models together into an inseparable 'super-model'. Thus, this study provides two-way feedback mechanisms between multiple different process models that can be written in various programming languages and can run on different machines and operating systems. Additionally, a level of abstraction is given to the model integration process that allows researchers and other technical personnel to perform more detailed and interactive modeling, visualization, optimization, calibration, and uncertainty analysis without requiring deep understanding of inter-process communication. To be compatible, a program must be written in a programming language with bindings to a common implementation of the message passing interface (MPI), which includes FORTRAN, C, Java, the .NET languages, Python, R, Matlab, and many others. The system is tested on a longstanding legacy hydrologic model, the Soil and Water Assessment Tool (SWAT), to observe and enhance speed-up capabilities for various optimization, parameter estimation, and model uncertainty characterization techniques, which is particularly important for computationally intensive hydrologic simulations. Initial results indicate that the legacy extension system significantly decreases developer time, computation time, and the cost of purchasing commercial parallel processing licenses, while enhancing interdisciplinary research by providing detailed two-way feedback mechanisms between various process models with minimal changes to legacy code.

Integration agent-based models and GIS as a virtual urban dynamic laboratory

NASA Astrophysics Data System (ADS)

Chen, Peng; Liu, Miaolong

2007-06-01

Based on the Agent-based Model and spatial data model, a tight-coupling integrating method of GIS and Agent-based Model (ABM) is to be discussed in this paper. The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena such as urban dynamic. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, the agent-based model and spatial data model are discussed, and then the relationships affecting spatial data model and agent-based process models interaction. After that, a realistic crowd flow simulation experiment is presented. Using some tools provided by general GIS systems and a few specific programming languages, a new software system integrating GIS and MAS as a virtual laboratory applicable for simulating pedestrian flows in a crowd activity centre has been developed successfully. Under the environment supported by the software system, as an applicable case, a dynamic evolution process of the pedestrian's flows (dispersed process for the spectators) in a crowds' activity center - The Shanghai Stadium has been simulated successfully. At the end of the paper, some new research problems have been pointed out for the future.

Modeling selective attention using a neuromorphic analog VLSI device.

PubMed

Indiveri, G

2000-12-01

Attentional mechanisms are required to overcome the problem of flooding a limited processing capacity system with information. They are present in biological sensory systems and can be a useful engineering tool for artificial visual systems. In this article we present a hardware model of a selective attention mechanism implemented on a very large-scale integration (VLSI) chip, using analog neuromorphic circuits. The chip exploits a spike-based representation to receive, process, and transmit signals. It can be used as a transceiver module for building multichip neuromorphic vision systems. We describe the circuits that carry out the main processing stages of the selective attention mechanism and provide experimental data for each circuit. We demonstrate the expected behavior of the model at the system level by stimulating the chip with both artificially generated control signals and signals obtained from a saliency map, computed from an image containing several salient features.

Systems Biology-Driven Hypotheses Tested In Vivo: The Need to Advancing Molecular Imaging Tools.

PubMed

Verma, Garima; Palombo, Alessandro; Grigioni, Mauro; La Monaca, Morena; D'Avenio, Giuseppe

2018-01-01

Processing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties.

A system level model for preliminary design of a space propulsion solid rocket motor

NASA Astrophysics Data System (ADS)

Schumacher, Daniel M.

Preliminary design of space propulsion solid rocket motors entails a combination of components and subsystems. Expert design tools exist to find near optimal performance of subsystems and components. Conversely, there is no system level preliminary design process for space propulsion solid rocket motors that is capable of synthesizing customer requirements into a high utility design for the customer. The preliminary design process for space propulsion solid rocket motors typically builds on existing designs and pursues feasible rather than the most favorable design. Classical optimization is an extremely challenging method when dealing with the complex behavior of an integrated system. The complexity and combinations of system configurations make the number of the design parameters that are traded off unreasonable when manual techniques are used. Existing multi-disciplinary optimization approaches generally address estimating ratios and correlations rather than utilizing mathematical models. The developed system level model utilizes the Genetic Algorithm to perform the necessary population searches to efficiently replace the human iterations required during a typical solid rocket motor preliminary design. This research augments, automates, and increases the fidelity of the existing preliminary design process for space propulsion solid rocket motors. The system level aspect of this preliminary design process, and the ability to synthesize space propulsion solid rocket motor requirements into a near optimal design, is achievable. The process of developing the motor performance estimate and the system level model of a space propulsion solid rocket motor is described in detail. The results of this research indicate that the model is valid for use and able to manage a very large number of variable inputs and constraints towards the pursuit of the best possible design.

A Multi-Scale Integrated Approach to Representing Watershed Systems: Significance and Challenges

NASA Astrophysics Data System (ADS)

Kim, J.; Ivanov, V. Y.; Katopodes, N.

2013-12-01

A range of processes associated with supplying services and goods to human society originate at the watershed level. Predicting watershed response to forcing conditions has been of high interest to many practical societal problems, however, remains challenging due to two significant properties of the watershed systems, i.e., connectivity and non-linearity. Connectivity implies that disturbances arising at any larger scale will necessarily propagate and affect local-scale processes; their local effects consequently influence other processes, and often convey nonlinear relationships. Physically-based, process-scale modeling is needed to approach the understanding and proper assessment of non-linear effects between the watershed processes. We have developed an integrated model simulating hydrological processes, flow dynamics, erosion and sediment transport, tRIBS-OFM-HRM (Triangulated irregular network - based Real time Integrated Basin Simulator-Overland Flow Model-Hairsine and Rose Model). This coupled model offers the advantage of exploring the hydrological effects of watershed physical factors such as topography, vegetation, and soil, as well as their feedback mechanisms. Several examples investigating the effects of vegetation on flow movement, the role of soil's substrate on sediment dynamics, and the driving role of topography on morphological processes are illustrated. We show how this comprehensive modeling tool can help understand interconnections and nonlinearities of the physical system, e.g., how vegetation affects hydraulic resistance depending on slope, vegetation cover fraction, discharge, and bed roughness condition; how the soil's substrate condition impacts erosion processes with an non-unique characteristic at the scale of a zero-order catchment; and how topographic changes affect spatial variations of morphologic variables. Due to feedback and compensatory nature of mechanisms operating in different watershed compartments, our conclusion is that a key to representing watershed systems lies in an integrated, interdisciplinary approach, whereby a physically-based model is used for assessments/evaluations associated with future changes in landuse, climate, and ecosystems.

Inverse problems in the design, modeling and testing of engineering systems

NASA Technical Reports Server (NTRS)

Alifanov, Oleg M.

1991-01-01

Formulations, classification, areas of application, and approaches to solving different inverse problems are considered for the design of structures, modeling, and experimental data processing. Problems in the practical implementation of theoretical-experimental methods based on solving inverse problems are analyzed in order to identify mathematical models of physical processes, aid in input data preparation for design parameter optimization, help in design parameter optimization itself, and to model experiments, large-scale tests, and real tests of engineering systems.

Revisiting low-fidelity two-fluid models for gas–solids transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adeleke, Najeem, E-mail: najm@psu.edu; Adewumi, Michael, E-mail: m2a@psu.edu; Ityokumbul, Thaddeus

Two-phase gas–solids transport models are widely utilized for process design and automation in a broad range of industrial applications. Some of these applications include proppant transport in gaseous fracking fluids, air/gas drilling hydraulics, coal-gasification reactors and food processing units. Systems automation and real time process optimization stand to benefit a great deal from availability of efficient and accurate theoretical models for operations data processing. However, modeling two-phase pneumatic transport systems accurately requires a comprehensive understanding of gas–solids flow behavior. In this study we discuss the prevailing flow conditions and present a low-fidelity two-fluid model equation for particulate transport. The modelmore » equations are formulated in a manner that ensures the physical flux term remains conservative despite the inclusion of solids normal stress through the empirical formula for modulus of elasticity. A new set of Roe–Pike averages are presented for the resulting strictly hyperbolic flux term in the system of equations, which was used to develop a Roe-type approximate Riemann solver. The resulting scheme is stable regardless of the choice of flux-limiter. The model is evaluated by the prediction of experimental results from both pneumatic riser and air-drilling hydraulics systems. We demonstrate the effect and impact of numerical formulation and choice of numerical scheme on model predictions. We illustrate the capability of a low-fidelity one-dimensional two-fluid model in predicting relevant flow parameters in two-phase particulate systems accurately even under flow regimes involving counter-current flow.« less

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Structural model of control system for hydraulic stepper motor complex

NASA Astrophysics Data System (ADS)

Obukhov, A. D.; Dedov, D. L.; Kolodin, A. N.

2018-03-01

The article considers the problem of developing a structural model of the control system for a hydraulic stepper drive complex. A comparative analysis of stepper drives and assessment of the applicability of HSM for solving problems, requiring accurate displacement in space with subsequent positioning of the object, are carried out. The presented structural model of the automated control system of the multi-spindle complex of hydraulic stepper drives reflects the main components of the system, as well as the process of its control based on the control signals transfer to the solenoid valves by the controller. The models and methods described in the article can be used to formalize the control process in technical systems based on the application hydraulic stepper drives and allow switching from mechanical control to automated control.

Analysis and optimization of solid oxide fuel cell-based auxiliary power units using a generic zero-dimensional fuel cell model

NASA Astrophysics Data System (ADS)

Göll, S.; Samsun, R. C.; Peters, R.

Fuel-cell-based auxiliary power units can help to reduce fuel consumption and emissions in transportation. For this application, the combination of solid oxide fuel cells (SOFCs) with upstream fuel processing by autothermal reforming (ATR) is seen as a highly favorable configuration. Notwithstanding the necessity to improve each single component, an optimized architecture of the fuel cell system as a whole must be achieved. To enable model-based analyses, a system-level approach is proposed in which the fuel cell system is modeled as a multi-stage thermo-chemical process using the "flowsheeting" environment PRO/II™. Therein, the SOFC stack and the ATR are characterized entirely by corresponding thermodynamic processes together with global performance parameters. The developed model is then used to achieve an optimal system layout by comparing different system architectures. A system with anode and cathode off-gas recycling was identified to have the highest electric system efficiency. Taking this system as a basis, the potential for further performance enhancement was evaluated by varying four parameters characterizing different system components. Using methods from the design and analysis of experiments, the effects of these parameters and of their interactions were quantified, leading to an overall optimized system with encouraging performance data.

PanEurasian Experiment (PEEX): Modelling Platform for Earth System Observations and Forecasting

NASA Astrophysics Data System (ADS)

Baklanov, Alexander; Mahura, Alexander; Penenko, Vladimir; Zilitinkevich, Sergej; Kulmala, Markku

2014-05-01

As the part of the PEEX initiative, for the purpose of supporting the PEEX observational system and answering on the PEEX scientific questions, a hierarchy/ framework of modern multi-scale models for different elements of the Earth System integrated with the observation system is needed. One of the acute topics in the international debate on land-atmosphere interactions in relation to global change is the Earth System Modeling (ESM). The question is whether the ESM components actually represent how the Earth is functioning. The ESMs consist of equations describing the processes in the atmosphere, ocean, cryosphere, terrestrial and marine biosphere. ESMs are the best tools for analyzing the effect of different environmental changes on future climate or for studying the role of whole processes in the Earth System. These types of analysis and prediction of the future change are especially important in the Arctic latitudes, where climate change is proceeding fastest and where near-surface warming has been about twice the global average during the recent decades. The processes, and hence parameterization, in ESMs are still based on insufficient knowledge of physical, chemical and biological mechanisms involved in the climate system and the resolution of known processes is insufficient. Global scale modeling of land-atmosphere-ocean interactions using ESMs provides a way to explore the influence of spatial and temporal variation in the activities of land system and on climate. There is a lack, however, ways to forward a necessary process understanding effectively to ESMs and to link all this to the decision-making process. Arctic-boreal geographical domain plays significant role in terms of green-house gases and anthropogenic emissions and as an aerosol source area in the Earth System. The PEEX Modelling Platform (PEEX-MP) is characterized by: • An ensemble approach with the integration of modelling results from different models/ countries etc.; • A hierarchy of models, analysing scenarios, inverse modelling, modelling based on measurement needs and processes; • Model validation by remote sensing data and assimilation of satellite observations to constrain models to better understand processes, e.g., emissions and fluxes with top-down modelling; • Geophysical/ chemical model validation with experiments at various spatial and temporal scales. Added value of the comprehensive multi-platform observations and modeling; network of monitoring stations with the capacity to quantify those interactions between neighboring areas ranging from the Arctic and the Mediterranean to the Chinese industrial areas and the Asian steppes is needed. For example, apart from development of Russian stations in the PEEX area a strong co-operation with surrounding research infrastructures in the model of ACTRIS network needs to be established in order to obtain a global perspective of the emissions transport, transformation and ageing of pollutants incoming and exiting the PEEX area. The PEEX-MP aims to simulate and predict the physical aspects of the Earth system and to improve understanding of the bio-geochemical cycles in the PEEX domain, and beyond. The environmental change in this region implies that, from the point-of-view of atmospheric flow, the lower boundary conditions are changing. This is important for applications with immediate relevance for society, such as numerical weather prediction. The PEEX infrastructure will provide a unique view to the physical properties of the Earth surface, which can be used to improve assessment and prediction models. This will directly benefit citizens of the North in terms of better early warning of hazardous events, for instance. On longer time-scales, models of the bio-geochemical cycles in the PEEX domain absolutely need support from the new monitoring infra-structure to better measure and quantify soil and vegetation properties. In the most basic setup, the atmospheric and oceanic Global Circulation Models (GCMs) are connected to each other, sharing e.g. fluxes of momentum, water vapour and CO2. Traditionally, the land compartment has been an integral part of the atmospheric model, but in most modern ESMs the land model has been clearly separated. In most cases, the GCMs are complemented by other additional sub models covering, for example, atmospheric chemistry and aerosols, biogeochemistry or dynamic vegetation. Although the models can communicate also directly with each other, usually a separate coupler is used as an interface between different sub models. One of the main PEEX modelling activities is to evaluate process-models of chemistry-biota-atmosphere interactions in Pan Eurasian region and to improve GCM parameterizations. PEEX scientific plan is designed to serve a research chain that aims to advance our understanding of climate and air quality through a series of connected activities beginning at the molecular scale and extending to the regional and global scales. Past variations in climate in Pan Eurasian regions and corresponding forcing agents would be revealed by analysis of firn and ice cores in glaciers and ice sheets. A combination of direct and inverse modelling will be applied to diagnosing, designing, monitoring, and forecasting of air pollution in Siberia and Eurasia. Regional models coupled with the global one by means of orthogonal decomposition methods allow one to correctly introduce data about the global processes onto the regional level where environmental quality control strategies are typically implemented. Proceeding from the above mentioned limitations, a new concept and methodology considering the concept of 'one-atmosphere' as two-way interacted meteorological and chemical processes is suggested. The atmospheric chemistry transport models should include not only health-effecting pollutants (air quality components), but also green-house gases and aerosols effecting climate, meteorological processes, etc. Such concept requests a strategy of new generation integrated chemistry-climate modelling systems for predicting atmospheric composition, meteorology and climate change. The on-line integration of meteorological/ climate models and atmospheric aerosol and chemical transport models gives a possibility to utilise all meteorological 3D fields at each time step and to consider feedbacks of air pollution (e.g. aerosols) on meteorological processes and climate forcing, and further on the chemical composition (as a chain of dependent processes). This promising way for future atmospheric simulation systems (as a part of and a step to ESMs) will be considered in PEEX. It will lead to a new generation of models for climatic, meteorological, environmental and chemical weather forecasting.

Application of structured analysis to a telerobotic system

NASA Technical Reports Server (NTRS)

Dashman, Eric; Mclin, David; Harrison, F. W.; Soloway, Donald; Young, Steven

1990-01-01

The analysis and evaluation of a multiple arm telerobotic research and demonstration system developed by the NASA Intelligent Systems Research Laboratory (ISRL) is described. Structured analysis techniques were used to develop a detailed requirements model of an existing telerobotic testbed. Performance models generated during this process were used to further evaluate the total system. A commercial CASE tool called Teamwork was used to carry out the structured analysis and development of the functional requirements model. A structured analysis and design process using the ISRL telerobotic system as a model is described. Evaluation of this system focused on the identification of bottlenecks in this implementation. The results demonstrate that the use of structured methods and analysis tools can give useful performance information early in a design cycle. This information can be used to ensure that the proposed system meets its design requirements before it is built.

A Tri-network Model of Human Semantic Processing

PubMed Central

Xu, Yangwen; He, Yong; Bi, Yanchao

2017-01-01

Humans process the meaning of the world via both verbal and nonverbal modalities. It has been established that widely distributed cortical regions are involved in semantic processing, yet the global wiring pattern of this brain system has not been considered in the current neurocognitive semantic models. We review evidence from the brain-network perspective, which shows that the semantic system is topologically segregated into three brain modules. Revisiting previous region-based evidence in light of these new network findings, we postulate that these three modules support multimodal experiential representation, language-supported representation, and semantic control. A tri-network neurocognitive model of semantic processing is proposed, which generates new hypotheses regarding the network basis of different types of semantic processes. PMID:28955266

Attitude determination of a high altitude balloon system. Part 2: Development of the parameter determination process

NASA Technical Reports Server (NTRS)

Nigro, N. J.; Elkouh, A. F.

1975-01-01

The attitude of the balloon system is determined as a function of time if: (a) a method for simulating the motion of the system is available, and (b) the initial state is known. The initial state is obtained by fitting the system motion (as measured by sensors) to the corresponding output predicted by the mathematical model. In the case of the LACATE experiment the sensors consisted of three orthogonally oriented rate gyros and a magnetometer all mounted on the research platform. The initial state was obtained by fitting the angular velocity components measured with the gyros to the corresponding values obtained from the solution of the math model. A block diagram illustrating the attitude determination process employed for the LACATE experiment is shown. The process consists of three essential parts; a process for simulating the balloon system, an instrumentation system for measuring the output, and a parameter estimation process for systematically and efficiently solving the initial state. Results are presented and discussed.

Process Based on SysML for New Launchers System and Software Developments

NASA Astrophysics Data System (ADS)

Hiron, Emmanuel; Miramont, Philippe

2010-08-01

The purpose of this paper is to present the Astrium-ST engineering process based on SysML. This process is currently set-up in the frame of common CNES /Astrium-ST R&T studies related to the Ariane 5 electrical system and flight software modelling. The tool used to set up this process is Rhapsody release 7.3 from IBM-Software firm [1]. This process focuses on the system engineering phase dedicated to Software with the objective to generate both System documents (sequential system design and flight control) and Software specifications.

Behavior of the gypsy moth life system model and development of synoptic model formulations

Treesearch

J. J. Colbert; Xu Rumei

1991-01-01

Aims of the research: The gypsy moth life system model (GMLSM) is a complex model which incorporates numerous components (both biotic and abiotic) and ecological processes. It is a detailed simulation model which has much biological reality. However, it has not yet been tested with life system data. For such complex models, evaluation and testing cannot be adequately...

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2006-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CFWs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1 998 and 1999). In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Using ERP and WfM Systems for Implementing Business Processes: An Empirical Study

NASA Astrophysics Data System (ADS)

Aversano, Lerina; Tortorella, Maria

Software systems mainly considered from enterprises for dealing with a business process automation belong to the following two categories: Workflow Management Systems (WfMS) and Enterprise Resource Planning (ERP) systems. The wider diffusion of ERP systems tends to favourite this solution, but there are several limitations of most ERP systems for automating business processes. This paper reports an empirical study aiming at comparing the ability of implementing business processes of ERP systems and WfMSs. Two different case studies have been considered in the empirical study. It evaluates and analyses the correctness and completeness of the process models implemented by using ERP and WfM systems.

Automation and integration of components for generalized semantic markup of electronic medical texts.

PubMed

Dugan, J M; Berrios, D C; Liu, X; Kim, D K; Kaizer, H; Fagan, L M

1999-01-01

Our group has built an information retrieval system based on a complex semantic markup of medical textbooks. We describe the construction of a set of web-based knowledge-acquisition tools that expedites the collection and maintenance of the concepts required for text markup and the search interface required for information retrieval from the marked text. In the text markup system, domain experts (DEs) identify sections of text that contain one or more elements from a finite set of concepts. End users can then query the text using a predefined set of questions, each of which identifies a subset of complementary concepts. The search process matches that subset of concepts to relevant points in the text. The current process requires that the DE invest significant time to generate the required concepts and questions. We propose a new system--called ACQUIRE (Acquisition of Concepts and Queries in an Integrated Retrieval Environment)--that assists a DE in two essential tasks in the text-markup process. First, it helps her to develop, edit, and maintain the concept model: the set of concepts with which she marks the text. Second, ACQUIRE helps her to develop a query model: the set of specific questions that end users can later use to search the marked text. The DE incorporates concepts from the concept model when she creates the questions in the query model. The major benefit of the ACQUIRE system is a reduction in the time and effort required for the text-markup process. We compared the process of concept- and query-model creation using ACQUIRE to the process used in previous work by rebuilding two existing models that we previously constructed manually. We observed a significant decrease in the time required to build and maintain the concept and query models.

Performance evaluation of functioning of natural-industrial system of mining-processing complex with help of analytical and mathematical models

NASA Astrophysics Data System (ADS)

Bosikov, I. I.; Klyuev, R. V.; Revazov, V. Ch; Pilieva, D. E.

2018-03-01

The article describes research and analysis of hazardous processes occurring in the natural-industrial system and effectiveness assessment of its functioning using mathematical models. Studies of the functioning regularities of the natural and industrial system are becoming increasingly relevant in connection with the formulation of the task of modernizing production and the economy of Russia as a whole. In connection with a significant amount of poorly structured data, it is complicated by regulations for the effective functioning of production processes, social and natural complexes, under which a sustainable development of the natural-industrial system of the mining and processing complex would be ensured. Therefore, the scientific and applied problems, the solution of which allows one to formalize the hidden structural functioning patterns of the natural-industrial system and to make managerial decisions of organizational and technological nature to improve the efficiency of the system, are very relevant.

[Cognitive Functions in the Prefrontal Association Cortex; Transitive Inference and the Lateral Prefrontal Cortex].

PubMed

Tanaka, Shingo; Oguchi, Mineki; Sakagami, Masamichi

2016-11-01

To behave appropriately in a complex and uncertain world, the brain makes use of several distinct learning systems. One such system is called the "model-free process", via which conditioning allows the association between a stimulus or response and a given reward to be learned. Another system is called the "model-based process". Via this process, the state transition between a stimulus and a response is learned so that the brain is able to plan actions prior to their execution. Several studies have tried to relate the difference between model-based and model-free processes to the difference in functions of the lateral prefrontal cortex (LPFC) and the striatum. Here, we describe a series of studies that demonstrate the ability of LPFC neurons to categorize visual stimuli by their associated behavioral responses and to generate abstract information. If LPFC neurons utilize abstract code to associate a stimulus with a reward, they should be able to infer similar relationships between other stimuli of the same category and their rewards without direct experience of these stimulus-reward contingencies. We propose that this ability of LPFC neurons to utilize abstract information can contribute to the model-based learning process.

Potential of Laboratory Execution Systems (LESs) to Simplify the Application of Business Process Management Systems (BPMSs) in Laboratory Automation.

PubMed

Neubert, Sebastian; Göde, Bernd; Gu, Xiangyu; Stoll, Norbert; Thurow, Kerstin

2017-04-01

Modern business process management (BPM) is increasingly interesting for laboratory automation. End-to-end workflow automation and improved top-level systems integration for information technology (IT) and automation systems are especially prominent objectives. With the ISO Standard Business Process Model and Notation (BPMN) 2.X, a system-independent and interdisciplinary accepted graphical process control notation is provided, allowing process analysis, while also being executable. The transfer of BPM solutions to structured laboratory automation places novel demands, for example, concerning the real-time-critical process and systems integration. The article discusses the potential of laboratory execution systems (LESs) for an easier implementation of the business process management system (BPMS) in hierarchical laboratory automation. In particular, complex application scenarios, including long process chains based on, for example, several distributed automation islands and mobile laboratory robots for a material transport, are difficult to handle in BPMSs. The presented approach deals with the displacement of workflow control tasks into life science specialized LESs, the reduction of numerous different interfaces between BPMSs and subsystems, and the simplification of complex process modelings. Thus, the integration effort for complex laboratory workflows can be significantly reduced for strictly structured automation solutions. An example application, consisting of a mixture of manual and automated subprocesses, is demonstrated by the presented BPMS-LES approach.

Long-term care information systems: an overview of the selection process.

PubMed

Nahm, Eun-Shim; Mills, Mary Etta; Feege, Barbara

2006-06-01

Under the current Medicare Prospective Payment System method and the ever-changing managed care environment, the long-term care information system is vital to providing quality care and to surviving in business. system selection process should be an interdisciplinary effort involving all necessary stakeholders for the proposed system. The system selection process can be modeled following the Systems Developmental Life Cycle: identifying problems, opportunities, and objectives; determining information requirements; analyzing system needs; designing the recommended system; and developing and documenting software.

Framework based on stochastic L-Systems for modeling IP traffic with multifractal behavior

NASA Astrophysics Data System (ADS)

Salvador, Paulo S.; Nogueira, Antonio; Valadas, Rui

2003-08-01

In a previous work we have introduced a multifractal traffic model based on so-called stochastic L-Systems, which were introduced by biologist A. Lindenmayer as a method to model plant growth. L-Systems are string rewriting techniques, characterized by an alphabet, an axiom (initial string) and a set of production rules. In this paper, we propose a novel traffic model, and an associated parameter fitting procedure, which describes jointly the packet arrival and the packet size processes. The packet arrival process is modeled through a L-System, where the alphabet elements are packet arrival rates. The packet size process is modeled through a set of discrete distributions (of packet sizes), one for each arrival rate. In this way the model is able to capture correlations between arrivals and sizes. We applied the model to measured traffic data: the well-known pOct Bellcore, a trace of aggregate WAN traffic and two traces of specific applications (Kazaa and Operation Flashing Point). We assess the multifractality of these traces using Linear Multiscale Diagrams. The suitability of the traffic model is evaluated by comparing the empirical and fitted probability mass and autocovariance functions; we also compare the packet loss ratio and average packet delay obtained with the measured traces and with traces generated from the fitted model. Our results show that our L-System based traffic model can achieve very good fitting performance in terms of first and second order statistics and queuing behavior.

Scrutinizing UML Activity Diagrams

NASA Astrophysics Data System (ADS)

Al-Fedaghi, Sabah

Building an information system involves two processes: conceptual modeling of the “real world domain” and designing the software system. Object-oriented methods and languages (e.g., UML) are typically used for describing the software system. For the system analysis process that produces the conceptual description, object-oriented techniques or semantics extensions are utilized. Specifically, UML activity diagrams are the “flow charts” of object-oriented conceptualization tools. This chapter proposes an alternative to UML activity diagrams through the development of a conceptual modeling methodology based on the notion of flow.

Northeast Artificial Intelligence Consortium (NAIC). Volume 15. Strategies for Coupling Symbolic and Numerical Computation in Knowledge Base Systems

DTIC Science & Technology

1990-12-01

Implementation of Coupled System 18 15.4. CASE STUDIES & IMPLEMENTATION EXAMPLES 24 15.4.1. The Case Studies of Coupled System 24 15.4.2. Example: Coupled System...occurs during specific phases of the problem-solving process. By decomposing the coupling process into its component layers we effectively study the nature...by the qualitative model, appropriate mathematical model is invoked. 5) The results are verified. If successful, stop. Else go to (2) and use an

Fluid and electrolyte control systems in the human body: A study report

NASA Technical Reports Server (NTRS)

White, R. J.

1973-01-01

Research in the area of modeling of the fluid and electrolyte system is briefly reviewed and a model of this system, which is adequate for a basic description of the requisite physiological processes, is presented. The use of this model as an individual subsystem model and as a component of a more complete human model is discussed.

Teaching Climate Change Using System Models: An Understanding Global Change Project Pilot Study

NASA Astrophysics Data System (ADS)

Bean, J. R.; Stuhlsatz, M.; Bracey, Z. B.; Marshall, C. R.

2017-12-01

Teaching and learning about historical and anthropogenic climate change in the classroom requires integrating instructional resources that address physical, chemical, and biological processes. The Understanding Global Change (UGC) framework and system models developed at the University of California Museum of Paleontology (UCMP) provide visualizations of the relationships and feedbacks between Earth system processes, and the consequences of anthropogenic activities on global climate. This schema provides a mechanism for developing pedagogic narratives that are known to support comprehension and retention of information and relationships. We designed a nine-day instructional unit for middle and high school students that includes a sequence of hands-on, inquiry-based, data rich activities combined with conceptual modeling exercises intended to foster students' development of systems thinking and their understanding of human influences on Earth system processes. The pilot unit, Sea Level Rise in the San Francisco Bay Area, addresses the human causes and consequences of sea level rise and related Earth system processes (i.e., the water cycle and greenhouse effect). Most of the content is not Bay Area specific, and could be used to explore sea level rise in any coastal region. Students completed pre and post assessments, which included questions about the connectedness of components of the Earth system and probed their attitudes towards participating in environmental stewardship activities. Students sequentially drew models representing the content explored in the activities and wrote short descriptions of their system diagrams that were collected by teachers for analysis. We also randomly assigned classes to engage in a very short additional intervention that asked students to think about the role that humans play in the Earth system and to draw themselves into the models. The study will determine if these students have higher stewardship scores and more frequently discuss their personal impact on the Earth system in their writing tasks. The results from this pilot will inform the design of future resources using UGC system models.

Cross-disciplinary links in environmental systems science: Current state and claimed needs identified in a meta-review of process models.

PubMed

Ayllón, Daniel; Grimm, Volker; Attinger, Sabine; Hauhs, Michael; Simmer, Clemens; Vereecken, Harry; Lischeid, Gunnar

2018-05-01

Terrestrial environmental systems are characterised by numerous feedback links between their different compartments. However, scientific research is organized into disciplines that focus on processes within the respective compartments rather than on interdisciplinary links. Major feedback mechanisms between compartments might therefore have been systematically overlooked so far. Without identifying these gaps, initiatives on future comprehensive environmental monitoring schemes and experimental platforms might fail. We performed a comprehensive overview of feedbacks between compartments currently represented in environmental sciences and explores to what degree missing links have already been acknowledged in the literature. We focused on process models as they can be regarded as repositories of scientific knowledge that compile findings of numerous single studies. In total, 118 simulation models from 23 model types were analysed. Missing processes linking different environmental compartments were identified based on a meta-review of 346 published reviews, model intercomparison studies, and model descriptions. Eight disciplines of environmental sciences were considered and 396 linking processes were identified and ascribed to the physical, chemical or biological domain. There were significant differences between model types and scientific disciplines regarding implemented interdisciplinary links. The most wide-spread interdisciplinary links were between physical processes in meteorology, hydrology and soil science that drive or set the boundary conditions for other processes (e.g., ecological processes). In contrast, most chemical and biological processes were restricted to links within the same compartment. Integration of multiple environmental compartments and interdisciplinary knowledge was scarce in most model types. There was a strong bias of suggested future research foci and model extensions towards reinforcing existing interdisciplinary knowledge rather than to open up new interdisciplinary pathways. No clear pattern across disciplines exists with respect to suggested future research efforts. There is no evidence that environmental research would clearly converge towards more integrated approaches or towards an overarching environmental systems theory. Copyright © 2017 Elsevier B.V. All rights reserved.

Dynamic graph of an oxy-fuel combustion system using autocatalytic set model

NASA Astrophysics Data System (ADS)

Harish, Noor Ainy; Bakar, Sumarni Abu

2017-08-01

Evaporation process is one of the main processes besides combustion process in an oxy-combustion boiler system. An Autocatalytic Set (ASC) Model has successfully applied in developing graphical representation of the chemical reactions that occurs in the evaporation process in the system. Seventeen variables identified in the process are represented as nodes and the catalytic relationships are represented as edges in the graph. In addition, in this paper graph dynamics of ACS is further investigated. By using Dynamic Autocatalytic Set Graph Algorithm (DAGA), the adjacency matrix for each of the graphs and its relations to Perron-Frobenius Theorem is investigated. The dynamic graph obtained is further investigated where the connection of the graph to fuzzy graph Type 1 is established.

Modeling Web-Based Educational Systems: Process Design Teaching Model

ERIC Educational Resources Information Center

Rokou, Franca Pantano; Rokou, Elena; Rokos, Yannis

2004-01-01

Using modeling languages is essential to the construction of educational systems based on software engineering principles and methods. Furthermore, the instructional design is undoubtedly the cornerstone of the design and development of educational systems. Although several methodologies and languages have been proposed for the specification of…

Land transportation model for supply chain manufacturing industries

NASA Astrophysics Data System (ADS)

Kurniawan, Fajar

2017-12-01

Supply chain is a system that integrates production, inventory, distribution and information processes for increasing productivity and minimize costs. Transportation is an important part of the supply chain system, especially for supporting the material distribution process, work in process products and final products. In fact, Jakarta as the distribution center of manufacturing industries for the industrial area. Transportation system has a large influences on the implementation of supply chain process efficiency. The main problem faced in Jakarta is traffic jam that will affect on the time of distribution. Based on the system dynamic model, there are several scenarios that can provide solutions to minimize timing of distribution that will effect on the cost such as the construction of ports approaching industrial areas other than Tanjung Priok, widening road facilities, development of railways system, and the development of distribution center.

75 FR 75961 - Notice of Implementation of the Wind Erosion Prediction System for Soil Erodibility System...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-07

... Wind Erosion Prediction System for Soil Erodibility System Calculations for the Natural Resources... Erosion Prediction System (WEPS) for soil erodibility system calculations scheduled for implementation for... computer model is a process-based, daily time-step computer model that predicts soil erosion via simulation...

Cancer systems biology: signal processing for cancer research

PubMed Central

Yli-Harja, Olli; Ylipää, Antti; Nykter, Matti; Zhang, Wei

2011-01-01

In this editorial we introduce the research paradigms of signal processing in the era of systems biology. Signal processing is a field of science traditionally focused on modeling electronic and communications systems, but recently it has turned to biological applications with astounding results. The essence of signal processing is to describe the natural world by mathematical models and then, based on these models, develop efficient computational tools for solving engineering problems. Here, we underline, with examples, the endless possibilities which arise when the battle-hardened tools of engineering are applied to solve the problems that have tormented cancer researchers. Based on this approach, a new field has emerged, called cancer systems biology. Despite its short history, cancer systems biology has already produced several success stories tackling previously impracticable problems. Perhaps most importantly, it has been accepted as an integral part of the major endeavors of cancer research, such as analyzing the genomic and epigenomic data produced by The Cancer Genome Atlas (TCGA) project. Finally, we show that signal processing and cancer research, two fields that are seemingly distant from each other, have merged into a field that is indeed more than the sum of its parts. PMID:21439242

[Development method of healthcare information system integration based on business collaboration model].

PubMed

Li, Shasha; Nie, Hongchao; Lu, Xudong; Duan, Huilong

2015-02-01

Integration of heterogeneous systems is the key to hospital information construction due to complexity of the healthcare environment. Currently, during the process of healthcare information system integration, people participating in integration project usually communicate by free-format document, which impairs the efficiency and adaptability of integration. A method utilizing business process model and notation (BPMN) to model integration requirement and automatically transforming it to executable integration configuration was proposed in this paper. Based on the method, a tool was developed to model integration requirement and transform it to integration configuration. In addition, an integration case in radiology scenario was used to verify the method.

Sleep, Off-Line Processing, and Vocal Learning

ERIC Educational Resources Information Center

Margoliash, Daniel; Schmidt, Marc F.

2010-01-01

The study of song learning and the neural song system has provided an important comparative model system for the study of speech and language acquisition. We describe some recent advances in the bird song system, focusing on the role of off-line processing including sleep in processing sensory information and in guiding developmental song…

Toward a Generative Model of the Teaching-Learning Process.

ERIC Educational Resources Information Center

McMullen, David W.

Until the rise of cognitive psychology, models of the teaching-learning process (TLP) stressed external rather than internal variables. Models remained general descriptions until control theory introduced explicit system analyses. Cybernetic models emphasize feedback and adaptivity but give little attention to creativity. Research on artificial…

Sociohydrology of an Arid City: Development of a Coupled Model of Water Management in Las Vegas

NASA Astrophysics Data System (ADS)

Garcia, M. E.; Islam, S.; Portney, K. E.

2014-12-01

Rapidly growing cities in arid regions present a significant water management challenge. Key to tackling this challenge is understanding how and why some cities transition to more sustainable water management; acknowledging that urban water resources decisions are both responding to and precipitating hydrologic change, this question is best tackled through a sociohydrology approach. While coupling of natural and societal systems is in it's infancy in the field of hydrology, there is a strong tradition of studying coupled systems in the field of Socio-Ecological Systems. We build on Ostrom's Socio-Ecological Systems framework to develop a system dynamics model of water management for the Las Vegas metropolitan area using Vensim. A key objective our proposed modeling framework is to illuminate the dynamic interactions of the sociohydrologic system components and enable testing of various assumptions and strategies. The model of Las Vegas water management consists of five sub-modules: water supply, water demand, finances, public perception and policy making process. The development of the first three modules were based on clearly defined system structure. The public perception sub-module tracks the level public risk perception of a water supply shortage and represents the hypothesis that public risk perception is updated periodically when shortage events are experienced. The policy making process module uses an algorithm capturing the hypothesized decision making process to select policy actions (or in-action) from a set of feasible actions in response to the system states tracked by the model and observable to decision makers. The model was tested and parameterized using mix of quantitative data on water demands, supplies and costs and qualitative data from document analysis and interview data covering 1990 to 2010 period. Given that not only the parameters but also the structure of the public perception and the policy making process sub-systems is contested, a different approach must be taken to assess the robustness of these modules. Presented here is the development of the model, results of model testing against the historic reference modes using Las Vegas as an example, and future work planned to improve the robustness of the model.

Verification of Functional Fault Models and the Use of Resource Efficient Verification Tools

NASA Technical Reports Server (NTRS)

Bis, Rachael; Maul, William A.

2015-01-01

Functional fault models (FFMs) are a directed graph representation of the failure effect propagation paths within a system's physical architecture and are used to support development and real-time diagnostics of complex systems. Verification of these models is required to confirm that the FFMs are correctly built and accurately represent the underlying physical system. However, a manual, comprehensive verification process applied to the FFMs was found to be error prone due to the intensive and customized process necessary to verify each individual component model and to require a burdensome level of resources. To address this problem, automated verification tools have been developed and utilized to mitigate these key pitfalls. This paper discusses the verification of the FFMs and presents the tools that were developed to make the verification process more efficient and effective.

Modelling and simulating reaction-diffusion systems using coloured Petri nets.

PubMed

Liu, Fei; Blätke, Mary-Ann; Heiner, Monika; Yang, Ming

2014-10-01

Reaction-diffusion systems often play an important role in systems biology when developmental processes are involved. Traditional methods of modelling and simulating such systems require substantial prior knowledge of mathematics and/or simulation algorithms. Such skills may impose a challenge for biologists, when they are not equally well-trained in mathematics and computer science. Coloured Petri nets as a high-level and graphical language offer an attractive alternative, which is easily approachable. In this paper, we investigate a coloured Petri net framework integrating deterministic, stochastic and hybrid modelling formalisms and corresponding simulation algorithms for the modelling and simulation of reaction-diffusion processes that may be closely coupled with signalling pathways, metabolic reactions and/or gene expression. Such systems often manifest multiscaleness in time, space and/or concentration. We introduce our approach by means of some basic diffusion scenarios, and test it against an established case study, the Brusselator model. Copyright © 2014 Elsevier Ltd. All rights reserved.

Carotene Degradation and Isomerization during Thermal Processing: A Review on the Kinetic Aspects.

PubMed

Colle, Ines J P; Lemmens, Lien; Knockaert, Griet; Van Loey, Ann; Hendrickx, Marc

2016-08-17

Kinetic models are important tools for process design and optimization to balance desired and undesired reactions taking place in complex food systems during food processing and preservation. This review covers the state of the art on kinetic models available to describe heat-induced conversion of carotenoids, in particular lycopene and β-carotene. First, relevant properties of these carotenoids are discussed. Second, some general aspects of kinetic modeling are introduced, including both empirical single-response modeling and mechanism-based multi-response modeling. The merits of multi-response modeling to simultaneously describe carotene degradation and isomerization are demonstrated. The future challenge in this research field lies in the extension of the current multi-response models to better approach the real reaction pathway and in the integration of kinetic models with mass transfer models in case of reaction in multi-phase food systems.

Integrating the human element into the systems engineering process and MBSE methodology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tadros, Michael Samir

In response to the challenges related to the increasing size and complexity of systems, organizations have recognized the need to integrate human considerations in the beginning stages of systems development. Human Systems Integration (HSI) seeks to accomplish this objective by incorporating human factors within systems engineering (SE) processes and methodologies, which is the focus of this paper. A representative set of HSI methods from multiple sources are organized, analyzed, and mapped to the systems engineering Vee-model. These methods are then consolidated and evaluated against the SE process and Models-Based Systems Engineering (MBSE) methodology to determine where and how they couldmore » integrate within systems development activities in the form of specific enhancements. Overall conclusions based on these evaluations are presented and future research areas are proposed.« less

A Baseline Patient Model to Support Testing of Medical Cyber-Physical Systems.

PubMed

Silva, Lenardo C; Perkusich, Mirko; Almeida, Hyggo O; Perkusich, Angelo; Lima, Mateus A M; Gorgônio, Kyller C

2015-01-01

Medical Cyber-Physical Systems (MCPS) are currently a trending topic of research. The main challenges are related to the integration and interoperability of connected medical devices, patient safety, physiologic closed-loop control, and the verification and validation of these systems. In this paper, we focus on patient safety and MCPS validation. We present a formal patient model to be used in health care systems validation without jeopardizing the patient's health. To determine the basic patient conditions, our model considers the four main vital signs: heart rate, respiratory rate, blood pressure and body temperature. To generate the vital signs we used regression models based on statistical analysis of a clinical database. Our solution should be used as a starting point for a behavioral patient model and adapted to specific clinical scenarios. We present the modeling process of the baseline patient model and show its evaluation. The conception process may be used to build different patient models. The results show the feasibility of the proposed model as an alternative to the immediate need for clinical trials to test these medical systems.

Cockpit System Situational Awareness Modeling Tool

NASA Technical Reports Server (NTRS)

Keller, John; Lebiere, Christian; Shay, Rick; Latorella, Kara

2004-01-01

This project explored the possibility of predicting pilot situational awareness (SA) using human performance modeling techniques for the purpose of evaluating developing cockpit systems. The Improved Performance Research Integration Tool (IMPRINT) was combined with the Adaptive Control of Thought-Rational (ACT-R) cognitive modeling architecture to produce a tool that can model both the discrete tasks of pilots and the cognitive processes associated with SA. The techniques for using this tool to predict SA were demonstrated using the newly developed Aviation Weather Information (AWIN) system. By providing an SA prediction tool to cockpit system designers, cockpit concepts can be assessed early in the design process while providing a cost-effective complement to the traditional pilot-in-the-loop experiments and data collection techniques.

IDC Re-Engineering Phase 2 Iteration E2 Use Case Realizations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, James M.; Burns, John F.; Hamlet, Benjamin R.

2016-06-01

This architecturally significant use case describes how the System acquires meteorological data to build atmospheric models used in automatic and interactive processing of infrasound data. The System requests the latest available high-resolution global meteorological data from external data centers and puts it into the correct formats for generation of infrasound propagation models. The system moves the meteorological data from Data Acquisition Partition to the Data Processing Partition and stores the meteorological data. The System builds a new atmospheric model based on the meteorological data. This use case is architecturally significant because it describes acquiring meteorological data from various sources andmore » creating dynamic atmospheric transmission model to support the prediction of infrasonic signal detection« less

Using a simulation assistant in modeling manufacturing systems

NASA Technical Reports Server (NTRS)

Schroer, Bernard J.; Tseng, Fan T.; Zhang, S. X.; Wolfsberger, John W.

1988-01-01

Numerous simulation languages exist for modeling discrete event processes, and are now ported to microcomputers. Graphic and animation capabilities were added to many of these languages to assist the users build models and evaluate the simulation results. With all these languages and added features, the user is still plagued with learning the simulation language. Futhermore, the time to construct and then to validate the simulation model is always greater than originally anticipated. One approach to minimize the time requirement is to use pre-defined macros that describe various common processes or operations in a system. The development of a simulation assistant for modeling discrete event manufacturing processes is presented. A simulation assistant is defined as an interactive intelligent software tool that assists the modeler in writing a simulation program by translating the modeler's symbolic description of the problem and then automatically generating the corresponding simulation code. The simulation assistant is discussed with emphasis on an overview of the simulation assistant, the elements of the assistant, and the five manufacturing simulation generators. A typical manufacturing system will be modeled using the simulation assistant and the advantages and disadvantages discussed.

Computational Models of Neuron-Astrocyte Interactions Lead to Improved Efficacy in the Performance of Neural Networks

PubMed Central

Alvarellos-González, Alberto; Pazos, Alejandro; Porto-Pazos, Ana B.

2012-01-01

The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has been shown that systems which include artificial neurons and astrocytes (Artificial Neuron-Glia Networks) have well-known advantages over identical systems including only artificial neurons. Since the actual impact of astrocytes in neural network function is unknown, we have investigated, using computational models, different astrocyte-neuron interactions for information processing; different neuron-glia algorithms have been implemented for training and validation of multilayer Artificial Neuron-Glia Networks oriented toward classification problem resolution. The results of the tests performed suggest that all the algorithms modelling astrocyte-induced synaptic potentiation improved artificial neural network performance, but their efficacy depended on the complexity of the problem. PMID:22649480

Computational models of neuron-astrocyte interactions lead to improved efficacy in the performance of neural networks.

PubMed

Alvarellos-González, Alberto; Pazos, Alejandro; Porto-Pazos, Ana B

2012-01-01

The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has been shown that systems which include artificial neurons and astrocytes (Artificial Neuron-Glia Networks) have well-known advantages over identical systems including only artificial neurons. Since the actual impact of astrocytes in neural network function is unknown, we have investigated, using computational models, different astrocyte-neuron interactions for information processing; different neuron-glia algorithms have been implemented for training and validation of multilayer Artificial Neuron-Glia Networks oriented toward classification problem resolution. The results of the tests performed suggest that all the algorithms modelling astrocyte-induced synaptic potentiation improved artificial neural network performance, but their efficacy depended on the complexity of the problem.

Evaluation of computing systems using functionals of a Stochastic process

NASA Technical Reports Server (NTRS)

Meyer, J. F.; Wu, L. T.

1980-01-01

An intermediate model was used to represent the probabilistic nature of a total system at a level which is higher than the base model and thus closer to the performance variable. A class of intermediate models, which are generally referred to as functionals of a Markov process, were considered. A closed form solution of performability for the case where performance is identified with the minimum value of a functional was developed.

Submesoscale Flows and Mixing in the Oceanic Surface Layer Using the Regional Oceanic Modeling System (ROMS)

DTIC Science & Technology

2014-09-30

continuation of the evolution of the Regional Oceanic Modeling System (ROMS) as a multi-scale, multi-process model and its utilization for...hydrostatic component of ROMS (Kanarska et al., 2007) is required to increase its efficiency and generality. The non-hydrostatic ROMS involves the solution...instability and wind-driven mixing. For the computational regime where those processes can be partially, but not yet fully resolved, it will

Research recommendations

NASA Technical Reports Server (NTRS)

1979-01-01

The research and development sequences and priorities for CELSS development were established for each of the following areas: nutrition and food processing, food production, waste processing, systems engineering/modeling, and ecology-systems safety.

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

NASA Technical Reports Server (NTRS)

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.

Model Uncertainty Quantification Methods For Data Assimilation In Partially Observed Multi-Scale Systems

NASA Astrophysics Data System (ADS)

Pathiraja, S. D.; van Leeuwen, P. J.

2017-12-01

Model Uncertainty Quantification remains one of the central challenges of effective Data Assimilation (DA) in complex partially observed non-linear systems. Stochastic parameterization methods have been proposed in recent years as a means of capturing the uncertainty associated with unresolved sub-grid scale processes. Such approaches generally require some knowledge of the true sub-grid scale process or rely on full observations of the larger scale resolved process. We present a methodology for estimating the statistics of sub-grid scale processes using only partial observations of the resolved process. It finds model error realisations over a training period by minimizing their conditional variance, constrained by available observations. Special is that these realisations are binned conditioned on the previous model state during the minimization process, allowing for the recovery of complex error structures. The efficacy of the approach is demonstrated through numerical experiments on the multi-scale Lorenz 96' model. We consider different parameterizations of the model with both small and large time scale separations between slow and fast variables. Results are compared to two existing methods for accounting for model uncertainty in DA and shown to provide improved analyses and forecasts.

Examination of Modeling Languages to Allow Quantitative Analysis for Model-Based Systems Engineering

DTIC Science & Technology

2014-06-01

x THIS PAGE INTENTIONALLY LEFT BLANK xi LIST OF ACRONYMS AND ABBREVIATIONS BOM Base Object Model BPMN Business Process Model & Notation DOD...SysML. There are many variants such as the Unified Profile for DODAF/MODAF (UPDM) and Business Process Model & Notation ( BPMN ) that have origins in

Cognitive process modelling of controllers in en route air traffic control.

PubMed

Inoue, Satoru; Furuta, Kazuo; Nakata, Keiichi; Kanno, Taro; Aoyama, Hisae; Brown, Mark

2012-01-01

In recent years, various efforts have been made in air traffic control (ATC) to maintain traffic safety and efficiency in the face of increasing air traffic demands. ATC is a complex process that depends to a large degree on human capabilities, and so understanding how controllers carry out their tasks is an important issue in the design and development of ATC systems. In particular, the human factor is considered to be a serious problem in ATC safety and has been identified as a causal factor in both major and minor incidents. There is, therefore, a need to analyse the mechanisms by which errors occur due to complex factors and to develop systems that can deal with these errors. From the cognitive process perspective, it is essential that system developers have an understanding of the more complex working processes that involve the cooperative work of multiple controllers. Distributed cognition is a methodological framework for analysing cognitive processes that span multiple actors mediated by technology. In this research, we attempt to analyse and model interactions that take place in en route ATC systems based on distributed cognition. We examine the functional problems in an ATC system from a human factors perspective, and conclude by identifying certain measures by which to address these problems. This research focuses on the analysis of air traffic controllers' tasks for en route ATC and modelling controllers' cognitive processes. This research focuses on an experimental study to gain a better understanding of controllers' cognitive processes in air traffic control. We conducted ethnographic observations and then analysed the data to develop a model of controllers' cognitive process. This analysis revealed that strategic routines are applicable to decision making.

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Heng; Ye, Ming; Walker, Anthony P.

Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averagingmore » methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

Use of the self-organising map network (SOMNet) as a decision support system for regional mental health planning.

PubMed

Chung, Younjin; Salvador-Carulla, Luis; Salinas-Pérez, José A; Uriarte-Uriarte, Jose J; Iruin-Sanz, Alvaro; García-Alonso, Carlos R

2018-04-25

Decision-making in mental health systems should be supported by the evidence-informed knowledge transfer of data. Since mental health systems are inherently complex, involving interactions between its structures, processes and outcomes, decision support systems (DSS) need to be developed using advanced computational methods and visual tools to allow full system analysis, whilst incorporating domain experts in the analysis process. In this study, we use a DSS model developed for interactive data mining and domain expert collaboration in the analysis of complex mental health systems to improve system knowledge and evidence-informed policy planning. We combine an interactive visual data mining approach, the self-organising map network (SOMNet), with an operational expert knowledge approach, expert-based collaborative analysis (EbCA), to develop a DSS model. The SOMNet was applied to the analysis of healthcare patterns and indicators of three different regional mental health systems in Spain, comprising 106 small catchment areas and providing healthcare for over 9 million inhabitants. Based on the EbCA, the domain experts in the development team guided and evaluated the analytical processes and results. Another group of 13 domain experts in mental health systems planning and research evaluated the model based on the analytical information of the SOMNet approach for processing information and discovering knowledge in a real-world context. Through the evaluation, the domain experts assessed the feasibility and technology readiness level (TRL) of the DSS model. The SOMNet, combined with the EbCA, effectively processed evidence-based information when analysing system outliers, explaining global and local patterns, and refining key performance indicators with their analytical interpretations. The evaluation results showed that the DSS model was feasible by the domain experts and reached level 7 of the TRL (system prototype demonstration in operational environment). This study supports the benefits of combining health systems engineering (SOMNet) and expert knowledge (EbCA) to analyse the complexity of health systems research. The use of the SOMNet approach contributes to the demonstration of DSS for mental health planning in practice.

An assembly process model based on object-oriented hierarchical time Petri Nets

NASA Astrophysics Data System (ADS)

Wang, Jiapeng; Liu, Shaoli; Liu, Jianhua; Du, Zenghui

2017-04-01

In order to improve the versatility, accuracy and integrity of the assembly process model of complex products, an assembly process model based on object-oriented hierarchical time Petri Nets is presented. A complete assembly process information model including assembly resources, assembly inspection, time, structure and flexible parts is established, and this model describes the static and dynamic data involved in the assembly process. Through the analysis of three-dimensional assembly process information, the assembly information is hierarchically divided from the whole, the local to the details and the subnet model of different levels of object-oriented Petri Nets is established. The communication problem between Petri subnets is solved by using message database, and it reduces the complexity of system modeling effectively. Finally, the modeling process is presented, and a five layer Petri Nets model is established based on the hoisting process of the engine compartment of a wheeled armored vehicle.

Modeling Common-Sense Decisions in Artificial Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail

2010-01-01

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

The Modulation of Visual and Task Characteristics of a Writing System on Hemispheric Lateralization in Visual Word Recognition--A Computational Exploration

ERIC Educational Resources Information Center

Hsiao, Janet H.; Lam, Sze Man

2013-01-01

Through computational modeling, here we examine whether visual and task characteristics of writing systems alone can account for lateralization differences in visual word recognition between different languages without assuming influence from left hemisphere (LH) lateralized language processes. We apply a hemispheric processing model of face…

A neural network model to predict the wastewater inflow incorporating rainfall events.

PubMed

El-Din, Ahmed Gamal; Smith, Daniel W

2002-03-01

Under steady-state conditions, a wastewater treatment plant usually has a satisfactory performance because these conditions are similar to design conditions. However, load variations constitute a large portion of the operating life of a treatment facility and most of the observed problems in complying with permit requirements occur during these load transients. During storm events upsets to the different physical and biological processes may take place in a wastewater treatment plant, and therefore, the ability to predict the hydraulic load to a treatment facility during such events is very beneficial for the optimization of the treatment process. Most of the hydrologic and hydraulic models describing sewage collection systems are deterministic. Such models require detailed knowledge of the system and usually rely on a large number of parameters, some of which are uncertain or difficult to determine. Presented in this paper, an artificial neural network (ANN) model that is used to make short-term predictions of wastewater inflow rate that enters the Gold Bar Wastewater Treatment Plant (GBWWTP), the largest plant in the Edmonton area (Alberta, Canada). The neural model uses rainfall data, observed in the collection system discharging to the plant, as inputs. The building process of the model was conducted in a systematic way that allowed the identification of a parsimonious model that is able to learn (and not memorize) from past data and generalize very well to unseen data that was used to validate the model. The neural network model gave excellent results. The potential of using the model as part of a real-time process control system is also discussed.

A Typology for Modeling Processes in Clinical Guidelines and Protocols

NASA Astrophysics Data System (ADS)

Tu, Samson W.; Musen, Mark A.

We analyzed the graphical representations that are used by various guideline-modeling methods to express process information embodied in clinical guidelines and protocols. From this analysis, we distilled four modeling formalisms and the processes they typically model: (1) flowcharts for capturing problem-solving processes, (2) disease-state maps that link decision points in managing patient problems over time, (3) plans that specify sequences of activities that contribute toward a goal, (4) workflow specifications that model care processes in an organization. We characterized the four approaches and showed that each captures some aspect of what a guideline may specify. We believe that a general guideline-modeling system must provide explicit representation for each type of process.

ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT - REMOVAL OF PRECURSORS TO DISINFECTION BY-PRODUCTS IN DRINKING WATER, PCI MEMBRANE SYSTEMS FYNE PROCESS MODEL ROP 1434 WITH AFC-30 NANOFILTRATON AT BARROW, AK - NSF 00/19/EPADW395

EPA Science Inventory

Equipment testing and verification of PCI Membrane Systems Inc. Fyne Process nanofiltraton systems Model ROP 1434 equipped with a C10 module containing AFC-30 tubular membranes was conducted from 3/16-5/11/2000 in Barrow, AS. The source water was a moderate alkalinity, moderately...

Phased models for evaluating the performability of computing systems

NASA Technical Reports Server (NTRS)

Wu, L. T.; Meyer, J. F.

1979-01-01

A phase-by-phase modelling technique is introduced to evaluate a fault tolerant system's ability to execute different sets of computational tasks during different phases of the control process. Intraphase processes are allowed to differ from phase to phase. The probabilities of interphase state transitions are specified by interphase transition matrices. Based on constraints imposed on the intraphase and interphase transition probabilities, various iterative solution methods are developed for calculating system performability.

Changing the world: the design and implementation of comprehensive continuous integrated systems of care for individuals with co-occurring disorders.

PubMed

Minkoff, Kenneth; Cline, Christie A

2004-12-01

This article has described the CCISC model and the process of implementation of systemic implementation of co-occurring disorder services enhancements within the context of existing resources. Four projects were described as illustrations of current implementation activities. Clearly, there is need for improved services for these individuals, and increasing recognition of the need for systemic change models that are effective and efficient. The CCISC model has been recognized by SAMHSA as a consensus best practice for system design, and initial efforts at implementation appear to be promising. The existing toolkit may permit a more formal process of data-driven evaluation of system, program, clinician, and client outcomes, to better measure the effectiveness of this approach. Some projects have begun such formal evaluation processes, but more work is needed, not only with individual projects, but also to develop opportunities for multi-system evaluation, as more projects come on line.

Development of process control capability through the Browns Ferry Integrated Computer System using Reactor Water Clanup System as an example. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, J.; Mowrey, J.

1995-12-01

This report describes the design, development and testing of process controls for selected system operations in the Browns Ferry Nuclear Plant (BFNP) Reactor Water Cleanup System (RWCU) using a Computer Simulation Platform which simulates the RWCU System and the BFNP Integrated Computer System (ICS). This system was designed to demonstrate the feasibility of the soft control (video touch screen) of nuclear plant systems through an operator console. The BFNP Integrated Computer System, which has recently. been installed at BFNP Unit 2, was simulated to allow for operator control functions of the modeled RWCU system. The BFNP Unit 2 RWCU systemmore » was simulated using the RELAP5 Thermal/Hydraulic Simulation Model, which provided the steady-state and transient RWCU process variables and simulated the response of the system to control system inputs. Descriptions of the hardware and software developed are also included in this report. The testing and acceptance program and results are also detailed in this report. A discussion of potential installation of an actual RWCU process control system in BFNP Unit 2 is included. Finally, this report contains a section on industry issues associated with installation of process control systems in nuclear power plants.« less

Discrimination of dynamical system models for biological and chemical processes.

PubMed

Lorenz, Sönke; Diederichs, Elmar; Telgmann, Regina; Schütte, Christof

2007-06-01

In technical chemistry, systems biology and biotechnology, the construction of predictive models has become an essential step in process design and product optimization. Accurate modelling of the reactions requires detailed knowledge about the processes involved. However, when concerned with the development of new products and production techniques for example, this knowledge often is not available due to the lack of experimental data. Thus, when one has to work with a selection of proposed models, the main tasks of early development is to discriminate these models. In this article, a new statistical approach to model discrimination is described that ranks models wrt. the probability with which they reproduce the given data. The article introduces the new approach, discusses its statistical background, presents numerical techniques for its implementation and illustrates the application to examples from biokinetics.

Abrasive slurry jet cutting model based on fuzzy relations

NASA Astrophysics Data System (ADS)

Qiang, C. H.; Guo, C. W.

2017-12-01

The cutting process of pre-mixed abrasive slurry or suspension jet (ASJ) is a complex process affected by many factors, and there is a highly nonlinear relationship between the cutting parameters and cutting quality. In this paper, guided by fuzzy theory, the fuzzy cutting model of ASJ was developed. In the modeling of surface roughness, the upper surface roughness prediction model and the lower surface roughness prediction model were established respectively. The adaptive fuzzy inference system combines the learning mechanism of neural networks and the linguistic reasoning ability of the fuzzy system, membership functions, and fuzzy rules are obtained by adaptive adjustment. Therefore, the modeling process is fast and effective. In this paper, the ANFIS module of MATLAB fuzzy logic toolbox was used to establish the fuzzy cutting model of ASJ, which is found to be quite instrumental to ASJ cutting applications.

Theory of constraints for publicly funded health systems.

PubMed

Sadat, Somayeh; Carter, Michael W; Golden, Brian

2013-03-01

Originally developed in the context of publicly traded for-profit companies, theory of constraints (TOC) improves system performance through leveraging the constraint(s). While the theory seems to be a natural fit for resource-constrained publicly funded health systems, there is a lack of literature addressing the modifications required to adopt TOC and define the goal and performance measures. This paper develops a system dynamics representation of the classical TOC's system-wide goal and performance measures for publicly traded for-profit companies, which forms the basis for developing a similar model for publicly funded health systems. The model is then expanded to include some of the factors that affect system performance, providing a framework to apply TOC's process of ongoing improvement in publicly funded health systems. Future research is required to more accurately define the factors affecting system performance and populate the model with evidence-based estimates for various parameters in order to use the model to guide TOC's process of ongoing improvement.

Animal models and conserved processes

PubMed Central

2012-01-01

Background The concept of conserved processes presents unique opportunities for using nonhuman animal models in biomedical research. However, the concept must be examined in the context that humans and nonhuman animals are evolved, complex, adaptive systems. Given that nonhuman animals are examples of living systems that are differently complex from humans, what does the existence of a conserved gene or process imply for inter-species extrapolation? Methods We surveyed the literature including philosophy of science, biological complexity, conserved processes, evolutionary biology, comparative medicine, anti-neoplastic agents, inhalational anesthetics, and drug development journals in order to determine the value of nonhuman animal models when studying conserved processes. Results Evolution through natural selection has employed components and processes both to produce the same outcomes among species but also to generate different functions and traits. Many genes and processes are conserved, but new combinations of these processes or different regulation of the genes involved in these processes have resulted in unique organisms. Further, there is a hierarchy of organization in complex living systems. At some levels, the components are simple systems that can be analyzed by mathematics or the physical sciences, while at other levels the system cannot be fully analyzed by reducing it to a physical system. The study of complex living systems must alternate between focusing on the parts and examining the intact whole organism while taking into account the connections between the two. Systems biology aims for this holism. We examined the actions of inhalational anesthetic agents and anti-neoplastic agents in order to address what the characteristics of complex living systems imply for inter-species extrapolation of traits and responses related to conserved processes. Conclusion We conclude that even the presence of conserved processes is insufficient for inter-species extrapolation when the trait or response being studied is located at higher levels of organization, is in a different module, or is influenced by other modules. However, when the examination of the conserved process occurs at the same level of organization or in the same module, and hence is subject to study solely by reductionism, then extrapolation is possible. PMID:22963674

A Multiagent Modeling Environment for Simulating Work Practice in Organizations

NASA Technical Reports Server (NTRS)

Sierhuis, Maarten; Clancey, William J.; vanHoof, Ron

2004-01-01

In this paper we position Brahms as a tool for simulating organizational processes. Brahms is a modeling and simulation environment for analyzing human work practice, and for using such models to develop intelligent software agents to support the work practice in organizations. Brahms is the result of more than ten years of research at the Institute for Research on Learning (IRL), NYNEX Science & Technology (the former R&D institute of the Baby Bell telephone company in New York, now Verizon), and for the last six years at NASA Ames Research Center, in the Work Systems Design and Evaluation group, part of the Computational Sciences Division (Code IC). Brahms has been used on more than ten modeling and simulation research projects, and recently has been used as a distributed multiagent development environment for developing work practice support tools for human in-situ science exploration on planetary surfaces, in particular a human mission to Mars. Brahms was originally conceived of as a business process modeling and simulation tool that incorporates the social systems of work, by illuminating how formal process flow descriptions relate to people s actual located activities in the workplace. Our research started in the early nineties as a reaction to experiences with work process modeling and simulation . Although an effective tool for convincing management of the potential cost-savings of the newly designed work processes, the modeling and simulation environment was only able to describe work as a normative workflow. However, the social systems, uncovered in work practices studied by the design team played a significant role in how work actually got done-actual lived work. Multi- tasking, informal assistance and circumstantial work interactions could not easily be represented in a tool with a strict workflow modeling paradigm. In response, we began to develop a tool that would have the benefits of work process modeling and simulation, but be distinctively able to represent the relations of people, locations, systems, artifacts, communication and information content.

A Computational Workflow for the Automated Generation of Models of Genetic Designs.

PubMed

Misirli, Göksel; Nguyen, Tramy; McLaughlin, James Alastair; Vaidyanathan, Prashant; Jones, Timothy S; Densmore, Douglas; Myers, Chris; Wipat, Anil

2018-06-05

Computational models are essential to engineer predictable biological systems and to scale up this process for complex systems. Computational modeling often requires expert knowledge and data to build models. Clearly, manual creation of models is not scalable for large designs. Despite several automated model construction approaches, computational methodologies to bridge knowledge in design repositories and the process of creating computational models have still not been established. This paper describes a workflow for automatic generation of computational models of genetic circuits from data stored in design repositories using existing standards. This workflow leverages the software tool SBOLDesigner to build structural models that are then enriched by the Virtual Parts Repository API using Systems Biology Open Language (SBOL) data fetched from the SynBioHub design repository. The iBioSim software tool is then utilized to convert this SBOL description into a computational model encoded using the Systems Biology Markup Language (SBML). Finally, this SBML model can be simulated using a variety of methods. This workflow provides synthetic biologists with easy to use tools to create predictable biological systems, hiding away the complexity of building computational models. This approach can further be incorporated into other computational workflows for design automation.

Artificial intelligence in process control: Knowledge base for the shuttle ECS model

NASA Technical Reports Server (NTRS)

Stiffler, A. Kent

1989-01-01

The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

The System Dynamics Model User Sustainability Explorer (SD-MUSE) user interface: a user-friendly tool for interpreting system dynamic models

EPA Science Inventory

Sustainability-based decision making is a challenging process that requires balancing trade-offs among social, economic, and environmental components. System Dynamic (SD) models can be useful tools to inform sustainability-based decision making because they provide a holistic co...

A protocol for parameterization and calibration of RZWQM2 in field research

USDA-ARS?s Scientific Manuscript database

Use of agricultural system models in field research requires a full understanding of both the model and the system it simulates. Since the 1960s, agricultural system models have increased tremendously in their complexity due to greater understanding of the processes simulated, their application to r...

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

Treesearch

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...