Discrete event simulation tool for analysis of qualitative models of continuous processing systems

NASA Technical Reports Server (NTRS)

Malin, Jane T. (Inventor); Basham, Bryan D. (Inventor); Harris, Richard A. (Inventor)

1990-01-01

An artificial intelligence design and qualitative modeling tool is disclosed for creating computer models and simulating continuous activities, functions, and/or behavior using developed discrete event techniques. Conveniently, the tool is organized in four modules: library design module, model construction module, simulation module, and experimentation and analysis. The library design module supports the building of library knowledge including component classes and elements pertinent to a particular domain of continuous activities, functions, and behavior being modeled. The continuous behavior is defined discretely with respect to invocation statements, effect statements, and time delays. The functionality of the components is defined in terms of variable cluster instances, independent processes, and modes, further defined in terms of mode transition processes and mode dependent processes. Model construction utilizes the hierarchy of libraries and connects them with appropriate relations. The simulation executes a specialized initialization routine and executes events in a manner that includes selective inherency of characteristics through a time and event schema until the event queue in the simulator is emptied. The experimentation and analysis module supports analysis through the generation of appropriate log files and graphics developments and includes the ability of log file comparisons.

An extension of the OpenModelica compiler for using Modelica models in a discrete event simulation

DOE PAGES

Nutaro, James

2014-11-03

In this article, a new back-end and run-time system is described for the OpenModelica compiler. This new back-end transforms a Modelica model into a module for the adevs discrete event simulation package, thereby extending adevs to encompass complex, hybrid dynamical systems. The new run-time system that has been built within the adevs simulation package supports models with state-events and time-events and that comprise differential-algebraic systems with high index. Finally, although the procedure for effecting this transformation is based on adevs and the Discrete Event System Specification, it can be adapted to any discrete event simulation package.

Parallel discrete event simulation using shared memory

NASA Technical Reports Server (NTRS)

Reed, Daniel A.; Malony, Allen D.; Mccredie, Bradley D.

1988-01-01

With traditional event-list techniques, evaluating a detailed discrete-event simulation-model can often require hours or even days of computation time. By eliminating the event list and maintaining only sufficient synchronization to ensure causality, parallel simulation can potentially provide speedups that are linear in the numbers of processors. A set of shared-memory experiments, using the Chandy-Misra distributed-simulation algorithm, to simulate networks of queues is presented. Parameters of the study include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential-simulation of most queueing network models.

Using a discrete-event simulation to balance ambulance availability and demand in static deployment systems.

PubMed

Wu, Ching-Han; Hwang, Kevin P

2009-12-01

To improve ambulance response time, matching ambulance availability with the emergency demand is crucial. To maintain the standard of 90% of response times within 9 minutes, the authors introduce a discrete-event simulation method to estimate the threshold for expanding the ambulance fleet when demand increases and to find the optimal dispatching strategies when provisional events create temporary decreases in ambulance availability. The simulation model was developed with information from the literature. Although the development was theoretical, the model was validated on the emergency medical services (EMS) system of Tainan City. The data are divided: one part is for model development, and the other for validation. For increasing demand, the effect was modeled on response time when call arrival rates increased. For temporary availability decreases, the authors simulated all possible alternatives of ambulance deployment in accordance with the number of out-of-routine-duty ambulances and the durations of three types of mass gatherings: marathon races (06:00-10:00 hr), rock concerts (18:00-22:00 hr), and New Year's Eve parties (20:00-01:00 hr). Statistical analysis confirmed that the model reasonably represented the actual Tainan EMS system. The response-time standard could not be reached when the incremental ratio of call arrivals exceeded 56%, which is the threshold for the Tainan EMS system to expand its ambulance fleet. When provisional events created temporary availability decreases, the Tainan EMS system could spare at most two ambulances from the standard configuration, except between 20:00 and 01:00, when it could spare three. The model also demonstrated that the current Tainan EMS has two excess ambulances that could be dropped. The authors suggest dispatching strategies to minimize the response times in routine daily emergencies. Strategies of capacity management based on this model improved response times. The more ambulances that are out of routine duty

An Overview of Importance Splitting for Rare Event Simulation

ERIC Educational Resources Information Center

Morio, Jerome; Pastel, Rudy; Le Gland, Francois

2010-01-01

Monte Carlo simulations are a classical tool to analyse physical systems. When unlikely events are to be simulated, the importance sampling technique is often used instead of Monte Carlo. Importance sampling has some drawbacks when the problem dimensionality is high or when the optimal importance sampling density is complex to obtain. In this…

Program For Simulation Of Trajectories And Events

NASA Technical Reports Server (NTRS)

Gottlieb, Robert G.

1992-01-01

Universal Simulation Executive (USE) program accelerates and eases generation of application programs for numerical simulation of continuous trajectories interrupted by or containing discrete events. Developed for simulation of multiple spacecraft trajectories with events as one spacecraft crossing the equator, two spacecraft meeting or parting, or firing rocket engine. USE also simulates operation of chemical batch processing factory. Written in Ada.

Using Discrete Event Simulation to Model Attacker Interactions with Cyber and Physical Security Systems

DOE PAGES

Perkins, Casey; Muller, George

2015-10-08

The number of connections between physical and cyber security systems is rapidly increasing due to centralized control from automated and remotely connected means. As the number of interfaces between systems continues to grow, the interactions and interdependencies between them cannot be ignored. Historically, physical and cyber vulnerability assessments have been performed independently. This independent evaluation omits important aspects of the integrated system, where the impacts resulting from malicious or opportunistic attacks are not easily known or understood. Here, we describe a discrete event simulation model that uses information about integrated physical and cyber security systems, attacker characteristics and simple responsemore » rules to identify key safeguards that limit an attacker's likelihood of success. Key features of the proposed model include comprehensive data generation to support a variety of sophisticated analyses, and full parameterization of safeguard performance characteristics and attacker behaviours to evaluate a range of scenarios. Lastly, we also describe the core data requirements and the network of networks that serves as the underlying simulation structure.« less

Using Discrete Event Simulation to Model Attacker Interactions with Cyber and Physical Security Systems

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

Perkins, Casey; Muller, George

The number of connections between physical and cyber security systems is rapidly increasing due to centralized control from automated and remotely connected means. As the number of interfaces between systems continues to grow, the interactions and interdependencies between them cannot be ignored. Historically, physical and cyber vulnerability assessments have been performed independently. This independent evaluation omits important aspects of the integrated system, where the impacts resulting from malicious or opportunistic attacks are not easily known or understood. Here, we describe a discrete event simulation model that uses information about integrated physical and cyber security systems, attacker characteristics and simple responsemore » rules to identify key safeguards that limit an attacker's likelihood of success. Key features of the proposed model include comprehensive data generation to support a variety of sophisticated analyses, and full parameterization of safeguard performance characteristics and attacker behaviours to evaluate a range of scenarios. Lastly, we also describe the core data requirements and the network of networks that serves as the underlying simulation structure.« less

A Simbol-X Event Simulator

NASA Astrophysics Data System (ADS)

Puccetti, S.; Fiore, F.; Giommi, P.

2009-05-01

The ASI Science Data Center (ASDC) has developed an X-ray event simulator to support users (and team members) in simulation of data taken with the two cameras on board the Simbol-X X-Ray Telescope. The Simbol-X simulator is very fast and flexible, compared to ray-tracing simulator. These properties make our simulator advantageous to support the user in planning proposals and comparing real data with the theoretical expectations and for a quick detection of unexpected features. We present here the simulator outline and a few examples of simulated data.

Visual Data-Analytics of Large-Scale Parallel Discrete-Event Simulations

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

Ross, Caitlin; Carothers, Christopher D.; Mubarak, Misbah

Parallel discrete-event simulation (PDES) is an important tool in the codesign of extreme-scale systems because PDES provides a cost-effective way to evaluate designs of highperformance computing systems. Optimistic synchronization algorithms for PDES, such as Time Warp, allow events to be processed without global synchronization among the processing elements. A rollback mechanism is provided when events are processed out of timestamp order. Although optimistic synchronization protocols enable the scalability of large-scale PDES, the performance of the simulations must be tuned to reduce the number of rollbacks and provide an improved simulation runtime. To enable efficient large-scale optimistic simulations, one has tomore » gain insight into the factors that affect the rollback behavior and simulation performance. We developed a tool for ROSS model developers that gives them detailed metrics on the performance of their large-scale optimistic simulations at varying levels of simulation granularity. Model developers can use this information for parameter tuning of optimistic simulations in order to achieve better runtime and fewer rollbacks. In this work, we instrument the ROSS optimistic PDES framework to gather detailed statistics about the simulation engine. We have also developed an interactive visualization interface that uses the data collected by the ROSS instrumentation to understand the underlying behavior of the simulation engine. The interface connects real time to virtual time in the simulation and provides the ability to view simulation data at different granularities. We demonstrate the usefulness of our framework by performing a visual analysis of the dragonfly network topology model provided by the CODES simulation framework built on top of ROSS. The instrumentation needs to minimize overhead in order to accurately collect data about the simulation performance. To ensure that the instrumentation does not introduce unnecessary overhead, we perform

Heinrich events simulated across the glacial

NASA Astrophysics Data System (ADS)

Ziemen, F. A.; Mikolajewicz, U.

2015-12-01

Heinrich events are among the most prominent climate change events recorded in proxies across the northern hemisphere. They are the archetype of ice sheet — climate interactions on millennial time scales. Nevertheless, the exact mechanisms that cause Heinrich events are still under discussion, and their climatic consequences are far from being fully understood. We contribute to answering the open questions by studying Heinrich events in a coupled ice sheet model (ISM) atmosphere-ocean-vegetation general circulation model (AOVGCM) framework, where this variability occurs as part of the model generated internal variability. The setup consists of a northern hemisphere setup of the modified Parallel Ice Sheet Model (mPISM) coupled to the global AOVGCM ECHAM5/MPIOM/LPJ. The simulations were performed fully coupled and with transient orbital and greenhouse gas forcing. They span from several millennia before the last glacial maximum into the deglaciation. We analyze simulations where the ISM is coupled asynchronously to the AOVGCM and simulations where the ISM and the ocean model are coupled synchronously and the atmosphere model is coupled asynchronously to them. The modeled Heinrich events show a marked influence of the ice discharge on the Atlantic circulation and heat transport.

Teaching sexual history-taking skills using the Sexual Events Classification System.

PubMed

Fidler, Donald C; Petri, Justin Daniel; Chapman, Mark

2010-01-01

The authors review the literature about educational programs for teaching sexual history-taking skills and describe novel techniques for teaching these skills. Psychiatric residents enrolled in a brief sexual history-taking course that included instruction on the Sexual Events Classification System, feedback on residents' video-recorded interviews with simulated patients, discussion of videos that simulated bad interviews, simulated patients, and a competency scoring form to score a video of a simulated interview. After the course, residents completed an anonymous survey to assess the usefulness of the experience. After the course, most residents felt more comfortable taking sexual histories. They described the Sexual Events Classification System and simulated interviews as practical methods for teaching sexual history-taking skills. The Sexual Events Classification System and simulated patient experiences may serve as a practical model for teaching sexual history-taking skills to general psychiatric residents.

LCG MCDB—a knowledgebase of Monte-Carlo simulated events

NASA Astrophysics Data System (ADS)

Belov, S.; Dudko, L.; Galkin, E.; Gusev, A.; Pokorski, W.; Sherstnev, A.

2008-02-01

In this paper we report on LCG Monte-Carlo Data Base (MCDB) and software which has been developed to operate MCDB. The main purpose of the LCG MCDB project is to provide a storage and documentation system for sophisticated event samples simulated for the LHC Collaborations by experts. In many cases, the modern Monte-Carlo simulation of physical processes requires expert knowledge in Monte-Carlo generators or significant amount of CPU time to produce the events. MCDB is a knowledgebase mainly dedicated to accumulate simulated events of this type. The main motivation behind LCG MCDB is to make the sophisticated MC event samples available for various physical groups. All the data from MCDB is accessible in several convenient ways. LCG MCDB is being developed within the CERN LCG Application Area Simulation project. Program summaryProgram title: LCG Monte-Carlo Data Base Catalogue identifier: ADZX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADZX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public Licence No. of lines in distributed program, including test data, etc.: 30 129 No. of bytes in distributed program, including test data, etc.: 216 943 Distribution format: tar.gz Programming language: Perl Computer: CPU: Intel Pentium 4, RAM: 1 Gb, HDD: 100 Gb Operating system: Scientific Linux CERN 3/4 RAM: 1 073 741 824 bytes (1 Gb) Classification: 9 External routines:perl >= 5.8.5; Perl modules DBD-mysql >= 2.9004, File::Basename, GD::SecurityImage, GD::SecurityImage::AC, Linux::Statistics, XML::LibXML > 1.6, XML::SAX, XML::NamespaceSupport; Apache HTTP Server >= 2.0.59; mod auth external >= 2.2.9; edg-utils-system RPM package; gd >= 2.0.28; rpm package CASTOR-client >= 2.1.2-4; arc-server (optional) Nature of problem: Often, different groups of experimentalists prepare similar samples of particle collision events or turn to the same group of authors of Monte-Carlo (MC

Modeling a Million-Node Slim Fly Network Using Parallel Discrete-Event Simulation

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

Wolfe, Noah; Carothers, Christopher; Mubarak, Misbah

As supercomputers close in on exascale performance, the increased number of processors and processing power translates to an increased demand on the underlying network interconnect. The Slim Fly network topology, a new lowdiameter and low-latency interconnection network, is gaining interest as one possible solution for next-generation supercomputing interconnect systems. In this paper, we present a high-fidelity Slim Fly it-level model leveraging the Rensselaer Optimistic Simulation System (ROSS) and Co-Design of Exascale Storage (CODES) frameworks. We validate our Slim Fly model with the Kathareios et al. Slim Fly model results provided at moderately sized network scales. We further scale the modelmore » size up to n unprecedented 1 million compute nodes; and through visualization of network simulation metrics such as link bandwidth, packet latency, and port occupancy, we get an insight into the network behavior at the million-node scale. We also show linear strong scaling of the Slim Fly model on an Intel cluster achieving a peak event rate of 36 million events per second using 128 MPI tasks to process 7 billion events. Detailed analysis of the underlying discrete-event simulation performance shows that a million-node Slim Fly model simulation can execute in 198 seconds on the Intel cluster.« less

Using Discrete Event Simulation for Programming Model Exploration at Extreme-Scale: Macroscale Components for the Structural Simulation Toolkit (SST).

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

Wilke, Jeremiah J; Kenny, Joseph P.

2015-02-01

Discrete event simulation provides a powerful mechanism for designing and testing new extreme- scale programming models for high-performance computing. Rather than debug, run, and wait for results on an actual system, design can first iterate through a simulator. This is particularly useful when test beds cannot be used, i.e. to explore hardware or scales that do not yet exist or are inaccessible. Here we detail the macroscale components of the structural simulation toolkit (SST). Instead of depending on trace replay or state machines, the simulator is architected to execute real code on real software stacks. Our particular user-space threading frameworkmore » allows massive scales to be simulated even on small clusters. The link between the discrete event core and the threading framework allows interesting performance metrics like call graphs to be collected from a simulated run. Performance analysis via simulation can thus become an important phase in extreme-scale programming model and runtime system design via the SST macroscale components.« less

Parallel discrete-event simulation of FCFS stochastic queueing networks

NASA Technical Reports Server (NTRS)

Nicol, David M.

1988-01-01

Physical systems are inherently parallel. Intuition suggests that simulations of these systems may be amenable to parallel execution. The parallel execution of a discrete-event simulation requires careful synchronization of processes in order to ensure the execution's correctness; this synchronization can degrade performance. Largely negative results were recently reported in a study which used a well-known synchronization method on queueing network simulations. Discussed here is a synchronization method (appointments), which has proven itself to be effective on simulations of FCFS queueing networks. The key concept behind appointments is the provision of lookahead. Lookahead is a prediction on a processor's future behavior, based on an analysis of the processor's simulation state. It is shown how lookahead can be computed for FCFS queueing network simulations, give performance data that demonstrates the method's effectiveness under moderate to heavy loads, and discuss performance tradeoffs between the quality of lookahead, and the cost of computing lookahead.

DynamO: a free O(N) general event-driven molecular dynamics simulator.

PubMed

Bannerman, M N; Sargant, R; Lue, L

2011-11-30

Molecular dynamics algorithms for systems of particles interacting through discrete or "hard" potentials are fundamentally different to the methods for continuous or "soft" potential systems. Although many software packages have been developed for continuous potential systems, software for discrete potential systems based on event-driven algorithms are relatively scarce and specialized. We present DynamO, a general event-driven simulation package, which displays the optimal O(N) asymptotic scaling of the computational cost with the number of particles N, rather than the O(N) scaling found in most standard algorithms. DynamO provides reference implementations of the best available event-driven algorithms. These techniques allow the rapid simulation of both complex and large (>10(6) particles) systems for long times. The performance of the program is benchmarked for elastic hard sphere systems, homogeneous cooling and sheared inelastic hard spheres, and equilibrium Lennard-Jones fluids. This software and its documentation are distributed under the GNU General Public license and can be freely downloaded from http://marcusbannerman.co.uk/dynamo. Copyright © 2011 Wiley Periodicals, Inc.

Desktop Modeling and Simulation: Parsimonious, yet Effective Discrete-Event Simulation Analysis

NASA Technical Reports Server (NTRS)

Bradley, James R.

2012-01-01

This paper evaluates how quickly students can be trained to construct useful discrete-event simulation models using Excel The typical supply chain used by many large national retailers is described, and an Excel-based simulation model is constructed of it The set of programming and simulation skills required for development of that model are then determined we conclude that six hours of training are required to teach the skills to MBA students . The simulation presented here contains all fundamental functionallty of a simulation model, and so our result holds for any discrete-event simulation model. We argue therefore that Industry workers with the same technical skill set as students having completed one year in an MBA program can be quickly trained to construct simulation models. This result gives credence to the efficacy of Desktop Modeling and Simulation whereby simulation analyses can be quickly developed, run, and analyzed with widely available software, namely Excel.

3D Simulation of External Flooding Events for the RISMC Pathway

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

Prescott, Steven; Mandelli, Diego; Sampath, Ramprasad

2015-09-01

Incorporating 3D simulations as part of the Risk-Informed Safety Margins Characterization (RISMIC) Toolkit allows analysts to obtain a more complete picture of complex system behavior for events including external plant hazards. External events such as flooding have become more important recently – however these can be analyzed with existing and validated simulated physics toolkits. In this report, we describe these approaches specific to flooding-based analysis using an approach called Smoothed Particle Hydrodynamics. The theory, validation, and example applications of the 3D flooding simulation are described. Integrating these 3D simulation methods into computational risk analysis provides a spatial/visual aspect to themore » design, improves the realism of results, and can prove visual understanding to validate the analysis of flooding.« less

An Advanced Simulation Framework for Parallel Discrete-Event Simulation

NASA Technical Reports Server (NTRS)

Li, P. P.; Tyrrell, R. Yeung D.; Adhami, N.; Li, T.; Henry, H.

1994-01-01

Discrete-event simulation (DEVS) users have long been faced with a three-way trade-off of balancing execution time, model fidelity, and number of objects simulated. Because of the limits of computer processing power the analyst is often forced to settle for less than desired performances in one or more of these areas.

Synchronization of autonomous objects in discrete event simulation

NASA Technical Reports Server (NTRS)

Rogers, Ralph V.

1990-01-01

Autonomous objects in event-driven discrete event simulation offer the potential to combine the freedom of unrestricted movement and positional accuracy through Euclidean space of time-driven models with the computational efficiency of event-driven simulation. The principal challenge to autonomous object implementation is object synchronization. The concept of a spatial blackboard is offered as a potential methodology for synchronization. The issues facing implementation of a spatial blackboard are outlined and discussed.

Simulating and Forecasting Flooding Events in the City of Jeddah, Saudi Arabia

NASA Astrophysics Data System (ADS)

Ghostine, Rabih; Viswanadhapalli, Yesubabu; Hoteit, Ibrahim

2014-05-01

Metropolitan cities in the Kingdom of Saudi Arabia, as Jeddah and Riyadh, are more frequently experiencing flooding events caused by strong convective storms that produce intense precipitation over a short span of time. The flooding in the city of Jeddah in November 2009 was described by civil defense officials as the worst in 27 years. As of January 2010, 150 people were reported killed and more than 350 were missing. Another flooding event, less damaging but comparably spectacular, occurred one year later (Jan 2011) in Jeddah. Anticipating floods before they occur could minimize human and economic losses through the implementation of appropriate protection, provision and rescue plans. We have developed a coupled hydro-meteorological model for simulating and predicting flooding events in the city of Jeddah. We use the Weather Research Forecasting (WRF) model assimilating all available data in the Jeddah region for simulating the storm events in Jeddah. The resulting rain is then used on 10 minutes intervals to feed up an advanced numerical shallow water model that has been discretized on an unstructured grid using different numerical schemes based on the finite elements or finite volume techniques. The model was integrated on a high-resolution grid size varying between 0.5m within the streets of Jeddah and 500m outside the city. This contribution will present the flooding simulation system and the simulation results, focusing on the comparison of the different numerical schemes on the system performances in terms of accuracy and computational efficiency.

Performance and cost evaluation of health information systems using micro-costing and discrete-event simulation.

PubMed

Rejeb, Olfa; Pilet, Claire; Hamana, Sabri; Xie, Xiaolan; Durand, Thierry; Aloui, Saber; Doly, Anne; Biron, Pierre; Perrier, Lionel; Augusto, Vincent

2018-06-01

Innovation and health-care funding reforms have contributed to the deployment of Information and Communication Technology (ICT) to improve patient care. Many health-care organizations considered the application of ICT as a crucial key to enhance health-care management. The purpose of this paper is to provide a methodology to assess the organizational impact of high-level Health Information System (HIS) on patient pathway. We propose an integrated performance evaluation of HIS approach through the combination of formal modeling using the Architecture of Integrated Information Systems (ARIS) models, a micro-costing approach for cost evaluation, and a Discrete-Event Simulation (DES) approach. The methodology is applied to the consultation for cancer treatment process. Simulation scenarios are established to conclude about the impact of HIS on patient pathway. We demonstrated that although high level HIS lengthen the consultation, occupation rate of oncologists are lower and quality of service is higher (through the number of available information accessed during the consultation to formulate the diagnostic). The provided method allows also to determine the most cost-effective ICT elements to improve the care process quality while minimizing costs. The methodology is flexible enough to be applied to other health-care systems.

USMC Inventory Control Using Optimization Modeling and Discrete Event Simulation

DTIC Science & Technology

2016-09-01

release. Distribution is unlimited. USMC INVENTORY CONTROL USING OPTIMIZATION MODELING AND DISCRETE EVENT SIMULATION by Timothy A. Curling...USING OPTIMIZATION MODELING AND DISCRETE EVENT SIMULATION 5. FUNDING NUMBERS 6. AUTHOR(S) Timothy A. Curling 7. PERFORMING ORGANIZATION NAME(S...optimization and discrete -event simulation. This construct can potentially provide an effective means in improving order management decisions. However

Simulations and Characteristics of Large Solar Events Propagating Throughout the Heliosphere and Beyond (Invited)

NASA Astrophysics Data System (ADS)

Intriligator, D. S.; Sun, W.; Detman, T. R.; Dryer, Ph D., M.; Intriligator, J.; Deehr, C. S.; Webber, W. R.; Gloeckler, G.; Miller, W. D.

2015-12-01

Large solar events can have severe adverse global impacts at Earth. These solar events also can propagate throughout the heliopshere and into the interstellar medium. We focus on the July 2012 and Halloween 2003 solar events. We simulate these events starting from the vicinity of the Sun at 2.5 Rs. We compare our three dimensional (3D) time-dependent simulations to available spacecraft (s/c) observations at 1 AU and beyond. Based on the comparisons of the predictions from our simulations with in-situ measurements we find that the effects of these large solar events can be observed in the outer heliosphere, the heliosheath, and even into the interstellar medium. We use two simulation models. The HAFSS (HAF Source Surface) model is a kinematic model. HHMS-PI (Hybrid Heliospheric Modeling System with Pickup protons) is a numerical magnetohydrodynamic solar wind (SW) simulation model. Both HHMS-PI and HAFSS are ideally suited for these analyses since starting at 2.5 Rs from the Sun they model the slowly evolving background SW and the impulsive, time-dependent events associated with solar activity. Our models naturally reproduce dynamic 3D spatially asymmetric effects observed throughout the heliosphere. Pre-existing SW background conditions have a strong influence on the propagation of shock waves from solar events. Time-dependence is a crucial aspect of interpreting s/c data. We show comparisons of our simulation results with STEREO A, ACE, Ulysses, and Voyager s/c observations.

Estimating rare events in biochemical systems using conditional sampling.

PubMed

Sundar, V S

2017-01-28

The paper focuses on development of variance reduction strategies to estimate rare events in biochemical systems. Obtaining this probability using brute force Monte Carlo simulations in conjunction with the stochastic simulation algorithm (Gillespie's method) is computationally prohibitive. To circumvent this, important sampling tools such as the weighted stochastic simulation algorithm and the doubly weighted stochastic simulation algorithm have been proposed. However, these strategies require an additional step of determining the important region to sample from, which is not straightforward for most of the problems. In this paper, we apply the subset simulation method, developed as a variance reduction tool in the context of structural engineering, to the problem of rare event estimation in biochemical systems. The main idea is that the rare event probability is expressed as a product of more frequent conditional probabilities. These conditional probabilities are estimated with high accuracy using Monte Carlo simulations, specifically the Markov chain Monte Carlo method with the modified Metropolis-Hastings algorithm. Generating sample realizations of the state vector using the stochastic simulation algorithm is viewed as mapping the discrete-state continuous-time random process to the standard normal random variable vector. This viewpoint opens up the possibility of applying more sophisticated and efficient sampling schemes developed elsewhere to problems in stochastic chemical kinetics. The results obtained using the subset simulation method are compared with existing variance reduction strategies for a few benchmark problems, and a satisfactory improvement in computational time is demonstrated.

Knowledge-based simulation for aerospace systems

NASA Technical Reports Server (NTRS)

Will, Ralph W.; Sliwa, Nancy E.; Harrison, F. Wallace, Jr.

1988-01-01

Knowledge-based techniques, which offer many features that are desirable in the simulation and development of aerospace vehicle operations, exhibit many similarities to traditional simulation packages. The eventual solution of these systems' current symbolic processing/numeric processing interface problem will lead to continuous and discrete-event simulation capabilities in a single language, such as TS-PROLOG. Qualitative, totally-symbolic simulation methods are noted to possess several intrinsic characteristics that are especially revelatory of the system being simulated, and capable of insuring that all possible behaviors are considered.

Advanced Simulation of Coupled Earthquake and Tsunami Events

NASA Astrophysics Data System (ADS)

Behrens, Joern

2013-04-01

Tsunami-Earthquakes represent natural catastrophes threatening lives and well-being of societies in a solitary and unexpected extreme event as tragically demonstrated in Sumatra (2004), Samoa (2009), Chile (2010), or Japan (2011). Both phenomena are consequences of the complex system of interactions of tectonic stress, fracture mechanics, rock friction, rupture dynamics, fault geometry, ocean bathymetry, and coastline geometry. The ASCETE project forms an interdisciplinary research consortium that couples the most advanced simulation technologies for earthquake rupture dynamics and tsunami propagation to understand the fundamental conditions of tsunami generation. We report on the latest research results in physics-based dynamic rupture and tsunami wave propagation simulation, using unstructured and adaptive meshes with continuous and discontinuous Galerkin discretization approaches. Coupling both simulation tools - the physics-based dynamic rupture simulation and the hydrodynamic tsunami wave propagation - will give us the possibility to conduct highly realistic studies of the interaction of rupture dynamics and tsunami impact characteristics.

Quality Improvement With Discrete Event Simulation: A Primer for Radiologists.

PubMed

Booker, Michael T; O'Connell, Ryan J; Desai, Bhushan; Duddalwar, Vinay A

2016-04-01

The application of simulation software in health care has transformed quality and process improvement. Specifically, software based on discrete-event simulation (DES) has shown the ability to improve radiology workflows and systems. Nevertheless, despite the successful application of DES in the medical literature, the power and value of simulation remains underutilized. For this reason, the basics of DES modeling are introduced, with specific attention to medical imaging. In an effort to provide readers with the tools necessary to begin their own DES analyses, the practical steps of choosing a software package and building a basic radiology model are discussed. In addition, three radiology system examples are presented, with accompanying DES models that assist in analysis and decision making. Through these simulations, we provide readers with an understanding of the theory, requirements, and benefits of implementing DES in their own radiology practices. Copyright © 2016 American College of Radiology. All rights reserved.

Discretely Integrated Condition Event (DICE) Simulation for Pharmacoeconomics.

PubMed

Caro, J Jaime

2016-07-01

Several decision-analytic modeling techniques are in use for pharmacoeconomic analyses. Discretely integrated condition event (DICE) simulation is proposed as a unifying approach that has been deliberately designed to meet the modeling requirements in a straightforward transparent way, without forcing assumptions (e.g., only one transition per cycle) or unnecessary complexity. At the core of DICE are conditions that represent aspects that persist over time. They have levels that can change and many may coexist. Events reflect instantaneous occurrences that may modify some conditions or the timing of other events. The conditions are discretely integrated with events by updating their levels at those times. Profiles of determinant values allow for differences among patients in the predictors of the disease course. Any number of valuations (e.g., utility, cost, willingness-to-pay) of conditions and events can be applied concurrently in a single run. A DICE model is conveniently specified in a series of tables that follow a consistent format and the simulation can be implemented fully in MS Excel, facilitating review and validation. DICE incorporates both state-transition (Markov) models and non-resource-constrained discrete event simulation in a single formulation; it can be executed as a cohort or a microsimulation; and deterministically or stochastically.

Manual for the Jet Event and Background Simulation Library

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

Heinz, M.; Soltz, R.; Angerami, A.

Jets are the collimated streams of particles resulting from hard scattering in the initial state of high-energy collisions. In heavy-ion collisions, jets interact with the quark-gluon plasma (QGP) before freezeout, providing a probe into the internal structure and properties of the QGP. In order to study jets, background must be subtracted from the measured event, potentially introducing a bias. We aim to understand and quantify this subtraction bias. PYTHIA, a library to simulate pure jet events, is used to simulate a model for a signature with one pure jet (a photon) and one quenched jet, where all quenched particle momentamore » are reduced by a user-de ned constant fraction. Background for the event is simulated using multiplicity values generated by the TRENTO initial state model of heavy-ion collisions fed into a thermal model consisting of a 3-dimensional Boltzmann distribution for particle types and momenta. Data from the simulated events is used to train a statistical model, which computes a posterior distribution of the quench factor for a data set. The model was tested rst on pure jet events and then on full events including the background. This model will allow for a quantitative determination of biases induced by various methods of background subtraction.« less

Discrete event simulation and the resultant data storage system response in the operational mission environment of Jupiter-Saturn /Voyager/ spacecraft

NASA Technical Reports Server (NTRS)

Mukhopadhyay, A. K.

1978-01-01

The Data Storage Subsystem Simulator (DSSSIM) simulating (by ground software) occurrence of discrete events in the Voyager mission is described. Functional requirements for Data Storage Subsystems (DSS) simulation are discussed, and discrete event simulation/DSSSIM processing is covered. Four types of outputs associated with a typical DSSSIM run are presented, and DSSSIM limitations and constraints are outlined.

Simulation of EAST vertical displacement events by tokamak simulation code

NASA Astrophysics Data System (ADS)

Qiu, Qinglai; Xiao, Bingjia; Guo, Yong; Liu, Lei; Xing, Zhe; Humphreys, D. A.

2016-10-01

Vertical instability is a potentially serious hazard for elongated plasma. In this paper, the tokamak simulation code (TSC) is used to simulate vertical displacement events (VDE) on the experimental advanced superconducting tokamak (EAST). Key parameters from simulations, including plasma current, plasma shape and position, flux contours and magnetic measurements match experimental data well. The growth rates simulated by TSC are in good agreement with TokSys results. In addition to modeling the free drift, an EAST fast vertical control model enables TSC to simulate the course of VDE recovery. The trajectories of the plasma current center and control currents on internal coils (IC) fit experimental data well.

Incorporating discrete event simulation into quality improvement efforts in health care systems.

PubMed

Rutberg, Matthew Harris; Wenczel, Sharon; Devaney, John; Goldlust, Eric Jonathan; Day, Theodore Eugene

2015-01-01

Quality improvement (QI) efforts are an indispensable aspect of health care delivery, particularly in an environment of increasing financial and regulatory pressures. The ability to test predictions of proposed changes to flow, policy, staffing, and other process-level changes using discrete event simulation (DES) has shown significant promise and is well reported in the literature. This article describes how to incorporate DES into QI departments and programs in order to support QI efforts, develop high-fidelity simulation models, conduct experiments, make recommendations, and support adoption of results. The authors describe how DES-enabled QI teams can partner with clinical services and administration to plan, conduct, and sustain QI investigations. © 2013 by the American College of Medical Quality.

Workflow in clinical trial sites & its association with near miss events for data quality: ethnographic, workflow & systems simulation.

PubMed

de Carvalho, Elias Cesar Araujo; Batilana, Adelia Portero; Claudino, Wederson; Reis, Luiz Fernando Lima; Schmerling, Rafael A; Shah, Jatin; Pietrobon, Ricardo

2012-01-01

With the exponential expansion of clinical trials conducted in (Brazil, Russia, India, and China) and VISTA (Vietnam, Indonesia, South Africa, Turkey, and Argentina) countries, corresponding gains in cost and enrolment efficiency quickly outpace the consonant metrics in traditional countries in North America and European Union. However, questions still remain regarding the quality of data being collected in these countries. We used ethnographic, mapping and computer simulation studies to identify/address areas of threat to near miss events for data quality in two cancer trial sites in Brazil. Two sites in Sao Paolo and Rio Janeiro were evaluated using ethnographic observations of workflow during subject enrolment and data collection. Emerging themes related to threats to near miss events for data quality were derived from observations. They were then transformed into workflows using UML-AD and modeled using System Dynamics. 139 tasks were observed and mapped through the ethnographic study. The UML-AD detected four major activities in the workflow evaluation of potential research subjects prior to signature of informed consent, visit to obtain subject́s informed consent, regular data collection sessions following study protocol and closure of study protocol for a given project. Field observations pointed to three major emerging themes: (a) lack of standardized process for data registration at source document, (b) multiplicity of data repositories and (c) scarcity of decision support systems at the point of research intervention. Simulation with policy model demonstrates a reduction of the rework problem. Patterns of threats to data quality at the two sites were similar to the threats reported in the literature for American sites. The clinical trial site managers need to reorganize staff workflow by using information technology more efficiently, establish new standard procedures and manage professionals to reduce near miss events and save time/cost. Clinical trial

Workflow in Clinical Trial Sites & Its Association with Near Miss Events for Data Quality: Ethnographic, Workflow & Systems Simulation

PubMed Central

Araujo de Carvalho, Elias Cesar; Batilana, Adelia Portero; Claudino, Wederson; Lima Reis, Luiz Fernando; Schmerling, Rafael A.; Shah, Jatin; Pietrobon, Ricardo

2012-01-01

Background With the exponential expansion of clinical trials conducted in (Brazil, Russia, India, and China) and VISTA (Vietnam, Indonesia, South Africa, Turkey, and Argentina) countries, corresponding gains in cost and enrolment efficiency quickly outpace the consonant metrics in traditional countries in North America and European Union. However, questions still remain regarding the quality of data being collected in these countries. We used ethnographic, mapping and computer simulation studies to identify/address areas of threat to near miss events for data quality in two cancer trial sites in Brazil. Methodology/Principal Findings Two sites in Sao Paolo and Rio Janeiro were evaluated using ethnographic observations of workflow during subject enrolment and data collection. Emerging themes related to threats to near miss events for data quality were derived from observations. They were then transformed into workflows using UML-AD and modeled using System Dynamics. 139 tasks were observed and mapped through the ethnographic study. The UML-AD detected four major activities in the workflow evaluation of potential research subjects prior to signature of informed consent, visit to obtain subject́s informed consent, regular data collection sessions following study protocol and closure of study protocol for a given project. Field observations pointed to three major emerging themes: (a) lack of standardized process for data registration at source document, (b) multiplicity of data repositories and (c) scarcity of decision support systems at the point of research intervention. Simulation with policy model demonstrates a reduction of the rework problem. Conclusions/Significance Patterns of threats to data quality at the two sites were similar to the threats reported in the literature for American sites. The clinical trial site managers need to reorganize staff workflow by using information technology more efficiently, establish new standard procedures and manage

Examining Passenger Flow Choke Points at Airports Using Discrete Event Simulation

NASA Technical Reports Server (NTRS)

Brown, Jeremy R.; Madhavan, Poomima

2011-01-01

The movement of passengers through an airport quickly, safely, and efficiently is the main function of the various checkpoints (check-in, security. etc) found in airports. Human error combined with other breakdowns in the complex system of the airport can disrupt passenger flow through the airport leading to lengthy waiting times, missing luggage and missed flights. In this paper we present a model of passenger flow through an airport using discrete event simulation that will provide a closer look into the possible reasons for breakdowns and their implications for passenger flow. The simulation is based on data collected at Norfolk International Airport (ORF). The primary goal of this simulation is to present ways to optimize the work force to keep passenger flow smooth even during peak travel times and for emergency preparedness at ORF in case of adverse events. In this simulation we ran three different scenarios: real world, increased check-in stations, and multiple waiting lines. Increased check-in stations increased waiting time and instantaneous utilization. while the multiple waiting lines decreased both the waiting time and instantaneous utilization. This simulation was able to show how different changes affected the passenger flow through the airport.

Design of virtual simulation experiment based on key events

NASA Astrophysics Data System (ADS)

Zhong, Zheng; Zhou, Dongbo; Song, Lingxiu

2018-06-01

Considering complex content and lacking of guidance in virtual simulation experiments, the key event technology in VR narrative theory was introduced for virtual simulation experiment to enhance fidelity and vividness process. Based on the VR narrative technology, an event transition structure was designed to meet the need of experimental operation process, and an interactive event processing model was used to generate key events in interactive scene. The experiment of" margin value of bees foraging" based on Biologic morphology was taken as an example, many objects, behaviors and other contents were reorganized. The result shows that this method can enhance the user's experience and ensure experimental process complete and effectively.

Disaster Response Modeling Through Discrete-Event Simulation

NASA Technical Reports Server (NTRS)

Wang, Jeffrey; Gilmer, Graham

2012-01-01

Organizations today are required to plan against a rapidly changing, high-cost environment. This is especially true for first responders to disasters and other incidents, where critical decisions must be made in a timely manner to save lives and resources. Discrete-event simulations enable organizations to make better decisions by visualizing complex processes and the impact of proposed changes before they are implemented. A discrete-event simulation using Simio software has been developed to effectively analyze and quantify the imagery capabilities of domestic aviation resources conducting relief missions. This approach has helped synthesize large amounts of data to better visualize process flows, manage resources, and pinpoint capability gaps and shortfalls in disaster response scenarios. Simulation outputs and results have supported decision makers in the understanding of high risk locations, key resource placement, and the effectiveness of proposed improvements.

Simulation Of Combat With An Expert System

NASA Technical Reports Server (NTRS)

Provenzano, J. P.

1989-01-01

Proposed expert system predicts outcomes of combat situations. Called "COBRA", combat outcome based on rules for attrition, system selects rules for mathematical modeling of losses and discrete events in combat according to previous experiences. Used with another software module known as the "Game". Game/COBRA software system, consisting of Game and COBRA modules, provides for both quantitative aspects and qualitative aspects in simulations of battles. COBRA intended for simulation of large-scale military exercises, concepts embodied in it have much broader applicability. In industrial research, knowledge-based system enables qualitative as well as quantitative simulations.

Symbolic discrete event system specification

NASA Technical Reports Server (NTRS)

Zeigler, Bernard P.; Chi, Sungdo

1992-01-01

Extending discrete event modeling formalisms to facilitate greater symbol manipulation capabilities is important to further their use in intelligent control and design of high autonomy systems. An extension to the DEVS formalism that facilitates symbolic expression of event times by extending the time base from the real numbers to the field of linear polynomials over the reals is defined. A simulation algorithm is developed to generate the branching trajectories resulting from the underlying nondeterminism. To efficiently manage symbolic constraints, a consistency checking algorithm for linear polynomial constraints based on feasibility checking algorithms borrowed from linear programming has been developed. The extended formalism offers a convenient means to conduct multiple, simultaneous explorations of model behaviors. Examples of application are given with concentration on fault model analysis.

Spiking neural network simulation: memory-optimal synaptic event scheduling.

PubMed

Stewart, Robert D; Gurney, Kevin N

2011-06-01

Spiking neural network simulations incorporating variable transmission delays require synaptic events to be scheduled prior to delivery. Conventional methods have memory requirements that scale with the total number of synapses in a network. We introduce novel scheduling algorithms for both discrete and continuous event delivery, where the memory requirement scales instead with the number of neurons. Superior algorithmic performance is demonstrated using large-scale, benchmarking network simulations.

Estimating ICU bed capacity using discrete event simulation.

PubMed

Zhu, Zhecheng; Hen, Bee Hoon; Teow, Kiok Liang

2012-01-01

The intensive care unit (ICU) in a hospital caters for critically ill patients. The number of the ICU beds has a direct impact on many aspects of hospital performance. Lack of the ICU beds may cause ambulance diversion and surgery cancellation, while an excess of ICU beds may cause a waste of resources. This paper aims to develop a discrete event simulation (DES) model to help the healthcare service providers determine the proper ICU bed capacity which strikes the balance between service level and cost effectiveness. The DES model is developed to reflect the complex patient flow of the ICU system. Actual operational data, including emergency arrivals, elective arrivals and length of stay, are directly fed into the DES model to capture the variations in the system. The DES model is validated by open box test and black box test. The validated model is used to test two what-if scenarios which the healthcare service providers are interested in: the proper number of the ICU beds in service to meet the target rejection rate and the extra ICU beds in service needed to meet the demand growth. A 12-month period of actual operational data was collected from an ICU department with 13 ICU beds in service. Comparison between the simulation results and the actual situation shows that the DES model accurately captures the variations in the system, and the DES model is flexible to simulate various what-if scenarios. DES helps the healthcare service providers describe the current situation, and simulate the what-if scenarios for future planning.

The cost of conservative synchronization in parallel discrete event simulations

NASA Technical Reports Server (NTRS)

Nicol, David M.

1990-01-01

The performance of a synchronous conservative parallel discrete-event simulation protocol is analyzed. The class of simulation models considered is oriented around a physical domain and possesses a limited ability to predict future behavior. A stochastic model is used to show that as the volume of simulation activity in the model increases relative to a fixed architecture, the complexity of the average per-event overhead due to synchronization, event list manipulation, lookahead calculations, and processor idle time approach the complexity of the average per-event overhead of a serial simulation. The method is therefore within a constant factor of optimal. The analysis demonstrates that on large problems--those for which parallel processing is ideally suited--there is often enough parallel workload so that processors are not usually idle. The viability of the method is also demonstrated empirically, showing how good performance is achieved on large problems using a thirty-two node Intel iPSC/2 distributed memory multiprocessor.

Implementing system simulation of C3 systems using autonomous objects

NASA Technical Reports Server (NTRS)

Rogers, Ralph V.

1987-01-01

The basis of all conflict recognition in simulation is a common frame of reference. Synchronous discrete-event simulation relies on the fixed points in time as the basic frame of reference. Asynchronous discrete-event simulation relies on fixed-points in the model space as the basic frame of reference. Neither approach provides sufficient support for autonomous objects. The use of a spatial template as a frame of reference is proposed to address these insufficiencies. The concept of a spatial template is defined and an implementation approach offered. Discussed are the uses of this approach to analyze the integration of sensor data associated with Command, Control, and Communication systems.

Modeling extreme (Carrington-type) space weather events using three-dimensional MHD code simulations

NASA Astrophysics Data System (ADS)

Ngwira, C. M.; Pulkkinen, A. A.; Kuznetsova, M. M.; Glocer, A.

2013-12-01

There is growing concern over possible severe societal consequences related to adverse space weather impacts on man-made technological infrastructure and systems. In the last two decades, significant progress has been made towards the modeling of space weather events. Three-dimensional (3-D) global magnetohydrodynamics (MHD) models have been at the forefront of this transition, and have played a critical role in advancing our understanding of space weather. However, the modeling of extreme space weather events is still a major challenge even for existing global MHD models. In this study, we introduce a specially adapted University of Michigan 3-D global MHD model for simulating extreme space weather events that have a ground footprint comparable (or larger) to the Carrington superstorm. Results are presented for an initial simulation run with ``very extreme'' constructed/idealized solar wind boundary conditions driving the magnetosphere. In particular, we describe the reaction of the magnetosphere-ionosphere system and the associated ground induced geoelectric field to such extreme driving conditions. We also discuss the results and what they might mean for the accuracy of the simulations. The model is further tested using input data for an observed space weather event to verify the MHD model consistence and to draw guidance for future work. This extreme space weather MHD model is designed specifically for practical application to the modeling of extreme geomagnetically induced electric fields, which can drive large currents in earth conductors such as power transmission grids.

The multinomial simulation algorithm for discrete stochastic simulation of reaction-diffusion systems.

PubMed

Lampoudi, Sotiria; Gillespie, Dan T; Petzold, Linda R

2009-03-07

The Inhomogeneous Stochastic Simulation Algorithm (ISSA) is a variant of the stochastic simulation algorithm in which the spatially inhomogeneous volume of the system is divided into homogeneous subvolumes, and the chemical reactions in those subvolumes are augmented by diffusive transfers of molecules between adjacent subvolumes. The ISSA can be prohibitively slow when the system is such that diffusive transfers occur much more frequently than chemical reactions. In this paper we present the Multinomial Simulation Algorithm (MSA), which is designed to, on the one hand, outperform the ISSA when diffusive transfer events outnumber reaction events, and on the other, to handle small reactant populations with greater accuracy than deterministic-stochastic hybrid algorithms. The MSA treats reactions in the usual ISSA fashion, but uses appropriately conditioned binomial random variables for representing the net numbers of molecules diffusing from any given subvolume to a neighbor within a prescribed distance. Simulation results illustrate the benefits of the algorithm.

Modeling Temporal Processes in Early Spacecraft Design: Application of Discrete-Event Simulations for Darpa's F6 Program

NASA Technical Reports Server (NTRS)

Dubos, Gregory F.; Cornford, Steven

2012-01-01

While the ability to model the state of a space system over time is essential during spacecraft operations, the use of time-based simulations remains rare in preliminary design. The absence of the time dimension in most traditional early design tools can however become a hurdle when designing complex systems whose development and operations can be disrupted by various events, such as delays or failures. As the value delivered by a space system is highly affected by such events, exploring the trade space for designs that yield the maximum value calls for the explicit modeling of time.This paper discusses the use of discrete-event models to simulate spacecraft development schedule as well as operational scenarios and on-orbit resources in the presence of uncertainty. It illustrates how such simulations can be utilized to support trade studies, through the example of a tool developed for DARPA's F6 program to assist the design of "fractionated spacecraft".

Asynchronous sampled-data approach for event-triggered systems

NASA Astrophysics Data System (ADS)

Mahmoud, Magdi S.; Memon, Azhar M.

2017-11-01

While aperiodically triggered network control systems save a considerable amount of communication bandwidth, they also pose challenges such as coupling between control and event-condition design, optimisation of the available resources such as control, communication and computation power, and time-delays due to computation and communication network. With this motivation, the paper presents separate designs of control and event-triggering mechanism, thus simplifying the overall analysis, asynchronous linear quadratic Gaussian controller which tackles delays and aperiodic nature of transmissions, and a novel event mechanism which compares the cost of the aperiodic system against a reference periodic implementation. The proposed scheme is simulated on a linearised wind turbine model for pitch angle control and the results show significant improvement against the periodic counterpart.

Statistical and Probabilistic Extensions to Ground Operations' Discrete Event Simulation Modeling

NASA Technical Reports Server (NTRS)

Trocine, Linda; Cummings, Nicholas H.; Bazzana, Ashley M.; Rychlik, Nathan; LeCroy, Kenneth L.; Cates, Grant R.

2010-01-01

NASA's human exploration initiatives will invest in technologies, public/private partnerships, and infrastructure, paving the way for the expansion of human civilization into the solar system and beyond. As it is has been for the past half century, the Kennedy Space Center will be the embarkation point for humankind's journey into the cosmos. Functioning as a next generation space launch complex, Kennedy's launch pads, integration facilities, processing areas, launch and recovery ranges will bustle with the activities of the world's space transportation providers. In developing this complex, KSC teams work through the potential operational scenarios: conducting trade studies, planning and budgeting for expensive and limited resources, and simulating alternative operational schemes. Numerous tools, among them discrete event simulation (DES), were matured during the Constellation Program to conduct such analyses with the purpose of optimizing the launch complex for maximum efficiency, safety, and flexibility while minimizing life cycle costs. Discrete event simulation is a computer-based modeling technique for complex and dynamic systems where the state of the system changes at discrete points in time and whose inputs may include random variables. DES is used to assess timelines and throughput, and to support operability studies and contingency analyses. It is applicable to any space launch campaign and informs decision-makers of the effects of varying numbers of expensive resources and the impact of off nominal scenarios on measures of performance. In order to develop representative DES models, methods were adopted, exploited, or created to extend traditional uses of DES. The Delphi method was adopted and utilized for task duration estimation. DES software was exploited for probabilistic event variation. A roll-up process was used, which was developed to reuse models and model elements in other less - detailed models. The DES team continues to innovate and expand

Complete event simulations of nuclear fission

NASA Astrophysics Data System (ADS)

Vogt, Ramona

2015-10-01

For many years, the state of the art for treating fission in radiation transport codes has involved sampling from average distributions. In these average fission models energy is not explicitly conserved and everything is uncorrelated because all particles are emitted independently. However, in a true fission event, the energies, momenta and multiplicities of the emitted particles are correlated. Such correlations are interesting for many modern applications. Event-by-event generation of complete fission events makes it possible to retain the kinematic information for all particles emitted: the fission products as well as prompt neutrons and photons. It is therefore possible to extract any desired correlation observables. Complete event simulations can be included in general Monte Carlo transport codes. We describe the general functionality of currently available fission event generators and compare results for several important observables. This work was performed under the auspices of the US DOE by LLNL, Contract DE-AC52-07NA27344. We acknowledge support of the Office of Defense Nuclear Nonproliferation Research and Development in DOE/NNSA.

Analysis hierarchical model for discrete event systems

NASA Astrophysics Data System (ADS)

Ciortea, E. M.

2015-11-01

The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.

Numerical simulation diagnostics of a flash flood event in Jeddah, Saudi Arabia

NASA Astrophysics Data System (ADS)

Samman, Ahmad

On 26 January 2011, a severe storm hit the city of Jeddah, the second largest city in the Kingdom of Saudi Arabia. The storm resulted in heavy rainfall, which produced a flash flood in a short period of time. This event caused at least eleven fatalities and more than 114 injuries. Unfortunately, the observed rainfall data are limited to the weather station at King Abdul Aziz International airport, which is north of the city, while the most extreme precipitation occurred over the southern part of the city. This observation was useful to compare simulation result even though it does not reflect the severity of the event. The Regional Atmospheric Modeling System (RAMS) developed at Colorado State University was used to study this storm event. RAMS simulations indicted that a quasi-stationary Mesoscale convective system developed over the city of Jeddah and lasted for several hours. It was the source of the huge amount of rainfall. The model computed a total rainfall of more than 110 mm in the southern part of the city, where the flash flood occurred. This precipitation estimation was confirmed by the actual observation of the weather radar. While the annual rainfall in Jeddah during the winter varies from 50 to 100 mm, the amount of the rainfall resulting from this storm event exceeded the climatological total annual rainfall. The simulation of this event showed that warm sea surface temperature, combined with high humidity in the lower atmosphere and a large amount of convective available potential energy (CAPE) provided a favorable environment for convection. It also showed the presence of a cyclonic system over the north and eastern parts of the Mediterranean Sea, and a subtropical anti-cyclone over Northeastern Africa that contributed to cold air advection bringing cold air to the Jeddah area. In addition, an anti-cyclone (blocking) centered over east and southeastern parts of the Arabian Peninsula and the Arabian Sea produced a low level jet over the southern

Three Dimensional Simulation of the Baneberry Nuclear Event

NASA Astrophysics Data System (ADS)

Lomov, Ilya N.; Antoun, Tarabay H.; Wagoner, Jeff; Rambo, John T.

2004-07-01

Baneberry, a 10-kiloton nuclear event, was detonated at a depth of 278 m at the Nevada Test Site on December 18, 1970. Shortly after detonation, radioactive gases emanating from the cavity were released into the atmosphere through a shock-induced fissure near surface ground zero. Extensive geophysical investigations, coupled with a series of 1D and 2D computational studies were used to reconstruct the sequence of events that led to the catastrophic failure. However, the geological profile of the Baneberry site is complex and inherently three-dimensional, which meant that some geological features had to be simplified or ignored in the 2D simulations. This left open the possibility that features unaccounted for in the 2D simulations could have had an important influence on the eventual containment failure of the Baneberry event. This paper presents results from a high-fidelity 3D Baneberry simulation based on the most accurate geologic and geophysical data available. The results are compared with available data, and contrasted against the results of the previous 2D computational studies.

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.

Enabling parallel simulation of large-scale HPC network systems

DOE PAGES

Mubarak, Misbah; Carothers, Christopher D.; Ross, Robert B.; ...

2016-04-07

Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks usedmore » in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations« less

Enabling parallel simulation of large-scale HPC network systems

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

Mubarak, Misbah; Carothers, Christopher D.; Ross, Robert B.

Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks usedmore » in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations« less

Optimization of Operations Resources via Discrete Event Simulation Modeling

NASA Technical Reports Server (NTRS)

Joshi, B.; Morris, D.; White, N.; Unal, R.

1996-01-01

The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistical methods. However, in a simulation environment that is characterized by search spaces of unknown topology and stochastic measures, these optimization approaches often prove inadequate. In this paper, we have explored the applicability of genetic algorithms to the simulation domain. Genetic algorithms provide a robust search strategy that does not require continuity and differentiability of the problem domain. The genetic algorithm successfully minimized the operation and support activities for a space vehicle, through a discrete event simulation model. The practical issues associated with simulation optimization, such as stochastic variables and constraints, were also taken into consideration.

StochKit2: software for discrete stochastic simulation of biochemical systems with events.

PubMed

Sanft, Kevin R; Wu, Sheng; Roh, Min; Fu, Jin; Lim, Rone Kwei; Petzold, Linda R

2011-09-01

StochKit2 is the first major upgrade of the popular StochKit stochastic simulation software package. StochKit2 provides highly efficient implementations of several variants of Gillespie's stochastic simulation algorithm (SSA), and tau-leaping with automatic step size selection. StochKit2 features include automatic selection of the optimal SSA method based on model properties, event handling, and automatic parallelism on multicore architectures. The underlying structure of the code has been completely updated to provide a flexible framework for extending its functionality. StochKit2 runs on Linux/Unix, Mac OS X and Windows. It is freely available under GPL version 3 and can be downloaded from http://sourceforge.net/projects/stochkit/. petzold@engineering.ucsb.edu.

Heinrich events modeled in transient glacial simulations

NASA Astrophysics Data System (ADS)

Ziemen, Florian; Kapsch, Marie; Mikolajewicz, Uwe

2017-04-01

Heinrich events are among the most prominent events of climate variability recorded in proxies across the northern hemisphere. They are the archetype of ice sheet — climate interactions on millennial time scales. Nevertheless, the exact mechanisms that cause Heinrich events are still under debate, and their climatic consequences are far from being fully understood. We address open questions by studying Heinrich events in a coupled ice sheet model (ISM) atmosphere-ocean-vegetation general circulation model (AOVGCM) framework, where this variability occurs as part of the model generated internal variability. The framework consists of a northern hemisphere setup of the modified Parallel Ice Sheet Model (mPISM) coupled to the global AOVGCM ECHAM5/MPIOM/LPJ. The simulations were performed fully coupled and with transient orbital and greenhouse gas forcing. They span from several millennia before the last glacial maximum into the deglaciation. To make these long simulations feasible, the atmosphere is accelerated by a factor of 10 relative to the other model components using a periodical-synchronous coupling technique. To disentangle effects of the Heinrich events and the deglaciation, we focus on the events occurring before the deglaciation. The modeled Heinrich events show a peak ice discharge of about 0.05 Sv and raise the sea level by 2.3 m on average. The resulting surface water freshening reduces the Atlantic meridional overturning circulation and ocean heat release. The reduction in ocean heat release causes a sub-surface warming and decreases the air temperature and precipitation regionally and downstream into Eurasia. The surface elevation decrease of the ice sheet enhances moisture transport onto the ice sheet and thus increases precipitation over the Hudson Bay area, thereby accelerating the recovery after an event.

High-speed event detector for embedded nanopore bio-systems.

PubMed

Huang, Yiyun; Magierowski, Sebastian; Ghafar-Zadeh, Ebrahim; Wang, Chengjie

2015-08-01

Biological measurements of microscopic phenomena often deal with discrete-event signals. The ability to automatically carry out such measurements at high-speed in a miniature embedded system is desirable but compromised by high-frequency noise along with practical constraints on filter quality and sampler resolution. This paper presents a real-time event-detection method in the context of nanopore sensing that helps to mitigate these drawbacks and allows accurate signal processing in an embedded system. Simulations show at least a 10× improvement over existing on-line detection methods.

Simulating flaring events in complex active regions driven by observed magnetograms

NASA Astrophysics Data System (ADS)

Dimitropoulou, M.; Isliker, H.; Vlahos, L.; Georgoulis, M. K.

2011-05-01

Context. We interpret solar flares as events originating in active regions that have reached the self organized critical state, by using a refined cellular automaton model with initial conditions derived from observations. Aims: We investigate whether the system, with its imposed physical elements, reaches a self organized critical state and whether well-known statistical properties of flares, such as scaling laws observed in the distribution functions of characteristic parameters, are reproduced after this state has been reached. Methods: To investigate whether the distribution functions of total energy, peak energy and event duration follow the expected scaling laws, we first applied a nonlinear force-free extrapolation that reconstructs the three-dimensional magnetic fields from two-dimensional vector magnetograms. We then locate magnetic discontinuities exceeding a threshold in the Laplacian of the magnetic field. These discontinuities are relaxed in local diffusion events, implemented in the form of cellular automaton evolution rules. Subsequent loading and relaxation steps lead the system to self organized criticality, after which the statistical properties of the simulated events are examined. Physical requirements, such as the divergence-free condition for the magnetic field vector, are approximately imposed on all elements of the model. Results: Our results show that self organized criticality is indeed reached when applying specific loading and relaxation rules. Power-law indices obtained from the distribution functions of the modeled flaring events are in good agreement with observations. Single power laws (peak and total flare energy) are obtained, as are power laws with exponential cutoff and double power laws (flare duration). The results are also compared with observational X-ray data from the GOES satellite for our active-region sample. Conclusions: We conclude that well-known statistical properties of flares are reproduced after the system has

Integration of scheduling and discrete event simulation systems to improve production flow planning

NASA Astrophysics Data System (ADS)

Krenczyk, D.; Paprocka, I.; Kempa, W. M.; Grabowik, C.; Kalinowski, K.

2016-08-01

The increased availability of data and computer-aided technologies such as MRPI/II, ERP and MES system, allowing producers to be more adaptive to market dynamics and to improve production scheduling. Integration of production scheduling and computer modelling, simulation and visualization systems can be useful in the analysis of production system constraints related to the efficiency of manufacturing systems. A integration methodology based on semi-automatic model generation method for eliminating problems associated with complexity of the model and labour-intensive and time-consuming process of simulation model creation is proposed. Data mapping and data transformation techniques for the proposed method have been applied. This approach has been illustrated through examples of practical implementation of the proposed method using KbRS scheduling system and Enterprise Dynamics simulation system.

Improving prospective memory performance with future event simulation in traumatic brain injury patients.

PubMed

Mioni, Giovanna; Bertucci, Erica; Rosato, Antonella; Terrett, Gill; Rendell, Peter G; Zamuner, Massimo; Stablum, Franca

2017-06-01

Previous studies have shown that traumatic brain injury (TBI) patients have difficulties with prospective memory (PM). Considering that PM is closely linked to independent living it is of primary interest to develop strategies that can improve PM performance in TBI patients. This study employed Virtual Week task as a measure of PM, and we included future event simulation to boost PM performance. Study 1 evaluated the efficacy of the strategy and investigated possible practice effects. Twenty-four healthy participants performed Virtual Week in a no strategy condition, and 24 healthy participants performed it in a mixed condition (no strategy - future event simulation). In Study 2, 18 TBI patients completed the mixed condition of Virtual Week and were compared with the 24 healthy controls who undertook the mixed condition of Virtual Week in Study 1. All participants also completed a neuropsychological evaluation to characterize the groups on level of cognitive functioning. Study 1 showed that participants in the future event simulation condition outperformed participants in the no strategy condition, and these results were not attributable to practice effects. Results of Study 2 showed that TBI patients performed PM tasks less accurately than controls, but that future event simulation can substantially reduce TBI-related deficits in PM performance. The future event simulation strategy also improved the controls' PM performance. These studies showed the value of future event simulation strategy in improving PM performance in healthy participants as well as in TBI patients. TBI patients performed PM tasks less accurately than controls, confirming prospective memory impairment in these patients. Participants in the future event simulation condition out-performed participants in the no strategy condition. Future event simulation can substantially reduce TBI-related deficits in PM performance. Future event simulation strategy also improved the controls' PM performance. �

Running Parallel Discrete Event Simulators on Sierra

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

Barnes, P. D.; Jefferson, D. R.

2015-12-03

In this proposal we consider porting the ROSS/Charm++ simulator and the discrete event models that run under its control so that they run on the Sierra architecture and make efficient use of the Volta GPUs.

Discrete event simulation: the preferred technique for health economic evaluations?

PubMed

Caro, Jaime J; Möller, Jörgen; Getsios, Denis

2010-12-01

To argue that discrete event simulation should be preferred to cohort Markov models for economic evaluations in health care. The basis for the modeling techniques is reviewed. For many health-care decisions, existing data are insufficient to fully inform them, necessitating the use of modeling to estimate the consequences that are relevant to decision-makers. These models must reflect what is known about the problem at a level of detail sufficient to inform the questions. Oversimplification will result in estimates that are not only inaccurate, but potentially misleading. Markov cohort models, though currently popular, have so many limitations and inherent assumptions that they are inadequate to inform most health-care decisions. An event-based individual simulation offers an alternative much better suited to the problem. A properly designed discrete event simulation provides more accurate, relevant estimates without being computationally prohibitive. It does require more data and may be a challenge to convey transparently, but these are necessary trade-offs to provide meaningful and valid results. In our opinion, discrete event simulation should be the preferred technique for health economic evaluations today. © 2010, International Society for Pharmacoeconomics and Outcomes Research (ISPOR).

ANALYSIS OF INPATIENT HOSPITAL STAFF MENTAL WORKLOAD BY MEANS OF DISCRETE-EVENT SIMULATION

DTIC Science & Technology

2016-03-24

ANALYSIS OF INPATIENT HOSPITAL STAFF MENTAL WORKLOAD BY MEANS OF DISCRETE -EVENT SIMULATION...in the United States. AFIT-ENV-MS-16-M-166 ANALYSIS OF INPATIENT HOSPITAL STAFF MENTAL WORKLOAD BY MEANS OF DISCRETE -EVENT SIMULATION...UNLIMITED. AFIT-ENV-MS-16-M-166 ANALYSIS OF INPATIENT HOSPITAL STAFF MENTAL WORKLOAD BY MEANS OF DISCRETE -EVENT SIMULATION Erich W

Manual for the Jet Event and Background Simulation Library(JEBSimLib)

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

Heinz, Matthias; Soltz, Ron; Angerami, Aaron

Jets are the collimated streams of particles resulting from hard scattering in the initial state of high-energy collisions. In heavy-ion collisions, jets interact with the quark-gluon plasma (QGP) before freezeout, providing a probe into the internal structure and properties of the QGP. In order to study jets, background must be subtracted from the measured event, potentially introducing a bias. We aim to understand and quantify this subtraction bias. PYTHIA, a library to simulate pure jet events, is used to simulate a model for a signature with one pure jet (a photon) and one quenched jet, where all quenched particle momentamore » are reduced by a user-de ned constant fraction. Background for the event is simulated using multiplicity values generated by the TRENTO initial state model of heavy-ion collisions fed into a thermal model consisting of a 3-dimensional Boltzmann distribution for particle types and momenta. Data from the simulated events is used to train a statistical model, which computes a posterior distribution of the quench factor for a data set. The model was tested rst on pure jet events and then on full events including the background. This model will allow for a quantitative determination of biases induced by various methods of background subtraction.« less

Simulation and study of small numbers of random events

NASA Technical Reports Server (NTRS)

Shelton, R. D.

1986-01-01

Random events were simulated by computer and subjected to various statistical methods to extract important parameters. Various forms of curve fitting were explored, such as least squares, least distance from a line, maximum likelihood. Problems considered were dead time, exponential decay, and spectrum extraction from cosmic ray data using binned data and data from individual events. Computer programs, mostly of an iterative nature, were developed to do these simulations and extractions and are partially listed as appendices. The mathematical basis for the compuer programs is given.

Variability of simulants used in recreating stab events.

PubMed

Carr, D J; Wainwright, A

2011-07-15

Forensic investigators commonly use simulants/backing materials to mount fabrics and/or garments on when recreating damage due to stab events. Such work may be conducted in support of an investigation to connect a particular knife to a stabbing event by comparing the severance morphology obtained in the laboratory to that observed in the incident. There does not appear to have been a comparison of the effect of simulant type on the morphology of severances in fabrics and simulants, nor on the variability of simulants. This work investigates three simulants (pork, gelatine, expanded polystyrene), two knife blades (carving, bread), and how severances in the simulants and an apparel fabric typically used to manufacture T-shirts (single jersey) were affected by (i) simulant type and (ii) blade type. Severances were formed using a laboratory impact apparatus to ensure a consistent impact velocity and hence impact energy independently of the other variables. The impact velocity was chosen so that the force measured was similar to that measured in human performance trials. Force-time and energy-time curves were analysed and severance morphology (y, z directions) investigated. Simulant type and knife type significantly affected the critical forensic measurements of severance length (y direction) in the fabric and 'skin' (Tuftane). The use of EPS resulted in the lowest variability in data, further the severances recorded in both the fabric and Tuftane more accurately reflected the dimensions of the impacting knives. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Terminal Dynamics Approach to Discrete Event Systems

NASA Technical Reports Server (NTRS)

Zak, Michail; Meyers, Ronald

1995-01-01

This paper presents and discusses a mathematical formalism for simulation of discrete event dynamic (DED)-a special type of 'man-made' systems to serve specific purposes of information processing. The main objective of this work is to demonstrate that the mathematical formalism for DED can be based upon a terminal model of Newtonian dynamics which allows one to relax Lipschitz conditions at some discrete points.!.

Repetition-Related Reductions in Neural Activity during Emotional Simulations of Future Events.

PubMed

Szpunar, Karl K; Jing, Helen G; Benoit, Roland G; Schacter, Daniel L

2015-01-01

Simulations of future experiences are often emotionally arousing, and the tendency to repeatedly simulate negative future outcomes has been identified as a predictor of the onset of symptoms of anxiety. Nonetheless, next to nothing is known about how the healthy human brain processes repeated simulations of emotional future events. In this study, we present a paradigm that can be used to study repeated simulations of the emotional future in a manner that overcomes phenomenological confounds between positive and negative events. The results show that pulvinar nucleus and orbitofrontal cortex respectively demonstrate selective reductions in neural activity in response to frequently as compared to infrequently repeated simulations of negative and positive future events. Implications for research on repeated simulations of the emotional future in both non-clinical and clinical populations are discussed.

Tutorial in medical decision modeling incorporating waiting lines and queues using discrete event simulation.

PubMed

Jahn, Beate; Theurl, Engelbert; Siebert, Uwe; Pfeiffer, Karl-Peter

2010-01-01

In most decision-analytic models in health care, it is assumed that there is treatment without delay and availability of all required resources. Therefore, waiting times caused by limited resources and their impact on treatment effects and costs often remain unconsidered. Queuing theory enables mathematical analysis and the derivation of several performance measures of queuing systems. Nevertheless, an analytical approach with closed formulas is not always possible. Therefore, simulation techniques are used to evaluate systems that include queuing or waiting, for example, discrete event simulation. To include queuing in decision-analytic models requires a basic knowledge of queuing theory and of the underlying interrelationships. This tutorial introduces queuing theory. Analysts and decision-makers get an understanding of queue characteristics, modeling features, and its strength. Conceptual issues are covered, but the emphasis is on practical issues like modeling the arrival of patients. The treatment of coronary artery disease with percutaneous coronary intervention including stent placement serves as an illustrative queuing example. Discrete event simulation is applied to explicitly model resource capacities, to incorporate waiting lines and queues in the decision-analytic modeling example.

An evaluation of an expert system for detecting critical events during anesthesia in a human patient simulator: a prospective randomized controlled study.

PubMed

Görges, Matthias; Winton, Pamela; Koval, Valentyna; Lim, Joanne; Stinson, Jonathan; Choi, Peter T; Schwarz, Stephan K W; Dumont, Guy A; Ansermino, J Mark

2013-08-01

Perioperative monitoring systems produce a large amount of uninterpreted data, use threshold alarms prone to artifacts, and rely on the clinician to continuously visually track changes in physiological data. To address these deficiencies, we developed an expert system that provides real-time clinical decisions for the identification of critical events. We evaluated the efficacy of the expert system for enhancing critical event detection in a simulated environment. We hypothesized that anesthesiologists would identify critical ventilatory events more rapidly and accurately with the expert system. We used a high-fidelity human patient simulator to simulate an operating room environment. Participants managed 4 scenarios (anesthetic vapor overdose, tension pneumothorax, anaphylaxis, and endotracheal tube cuff leak) in random order. In 2 of their 4 scenarios, participants were randomly assigned to the expert system, which provided trend-based alerts and potential differential diagnoses. Time to detection and time to treatment were measured. Workload questionnaires and structured debriefings were completed after each scenario, and a usability questionnaire at the conclusion of the session. Data were analyzed using a mixed-effects linear regression model; Fisher exact test was used for workload scores. Twenty anesthesiology trainees and 15 staff anesthesiologists with a combined median (range) of 36 (29-66) years of age and 6 (1-38) years of anesthesia experience participated. For the endotracheal tube cuff leak, the expert system caused mean reductions of 128 (99% confidence interval [CI], 54-202) seconds in time to detection and 140 (99% CI, 79-200) seconds in time to treatment. In the other 3 scenarios, a best-case decrease of 97 seconds (lower 99% CI) in time to diagnosis for anaphylaxis and a worst-case increase of 63 seconds (upper 99% CI) in time to treatment for anesthetic vapor overdose were found. Participants were highly satisfied with the expert system (median

Requirements analysis for a hardware, discrete-event, simulation engine accelerator

NASA Astrophysics Data System (ADS)

Taylor, Paul J., Jr.

1991-12-01

An analysis of a general Discrete Event Simulation (DES), executing on the distributed architecture of an eight mode Intel PSC/2 hypercube, was performed. The most time consuming portions of the general DES algorithm were determined to be the functions associated with message passing of required simulation data between processing nodes of the hypercube architecture. A behavioral description, using the IEEE standard VHSIC Hardware Description and Design Language (VHDL), for a general DES hardware accelerator is presented. The behavioral description specifies the operational requirements for a DES coprocessor to augment the hypercube's execution of DES simulations. The DES coprocessor design implements the functions necessary to perform distributed discrete event simulations using a conservative time synchronization protocol.

Modeling Anti-Air Warfare With Discrete Event Simulation and Analyzing Naval Convoy Operations

DTIC Science & Technology

2016-06-01

WARFARE WITH DISCRETE EVENT SIMULATION AND ANALYZING NAVAL CONVOY OPERATIONS by Ali E. Opcin June 2016 Thesis Advisor: Arnold H. Buss Co...REPORT DATE June 2016 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE MODELING ANTI-AIR WARFARE WITH DISCRETE EVENT...In this study, a discrete event simulation (DES) was built by modeling ships, and their sensors and weapons, to simulate convoy operations under

Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study

NASA Astrophysics Data System (ADS)

Li, Jun; Fu, Siyao; He, Haibo; Jia, Hongfei; Li, Yanzhong; Guo, Yi

2015-11-01

Large-scale regional evacuation is an important part of national security emergency response plan. Large commercial shopping area, as the typical service system, its emergency evacuation is one of the hot research topics. A systematic methodology based on Cellular Automata with the Dynamic Floor Field and event driven model has been proposed, and the methodology has been examined within context of a case study involving the evacuation within a commercial shopping mall. Pedestrians walking is based on Cellular Automata and event driven model. In this paper, the event driven model is adopted to simulate the pedestrian movement patterns, the simulation process is divided into normal situation and emergency evacuation. The model is composed of four layers: environment layer, customer layer, clerk layer and trajectory layer. For the simulation of movement route of pedestrians, the model takes into account purchase intention of customers and density of pedestrians. Based on evacuation model of Cellular Automata with Dynamic Floor Field and event driven model, we can reflect behavior characteristics of customers and clerks at the situations of normal and emergency evacuation. The distribution of individual evacuation time as a function of initial positions and the dynamics of the evacuation process is studied. Our results indicate that the evacuation model using the combination of Cellular Automata with Dynamic Floor Field and event driven scheduling can be used to simulate the evacuation of pedestrian flows in indoor areas with complicated surroundings and to investigate the layout of shopping mall.

Characterizing rare-event property distributions via replicate molecular dynamics simulations of proteins.

PubMed

Krishnan, Ranjani; Walton, Emily B; Van Vliet, Krystyn J

2009-11-01

As computational resources increase, molecular dynamics simulations of biomolecules are becoming an increasingly informative complement to experimental studies. In particular, it has now become feasible to use multiple initial molecular configurations to generate an ensemble of replicate production-run simulations that allows for more complete characterization of rare events such as ligand-receptor unbinding. However, there are currently no explicit guidelines for selecting an ensemble of initial configurations for replicate simulations. Here, we use clustering analysis and steered molecular dynamics simulations to demonstrate that the configurational changes accessible in molecular dynamics simulations of biomolecules do not necessarily correlate with observed rare-event properties. This informs selection of a representative set of initial configurations. We also employ statistical analysis to identify the minimum number of replicate simulations required to sufficiently sample a given biomolecular property distribution. Together, these results suggest a general procedure for generating an ensemble of replicate simulations that will maximize accurate characterization of rare-event property distributions in biomolecules.

A Madden-Julian oscillation event realistically simulated by a global cloud-resolving model.

PubMed

Miura, Hiroaki; Satoh, Masaki; Nasuno, Tomoe; Noda, Akira T; Oouchi, Kazuyoshi

2007-12-14

A Madden-Julian Oscillation (MJO) is a massive weather event consisting of deep convection coupled with atmospheric circulation, moving slowly eastward over the Indian and Pacific Oceans. Despite its enormous influence on many weather and climate systems worldwide, it has proven very difficult to simulate an MJO because of assumptions about cumulus clouds in global meteorological models. Using a model that allows direct coupling of the atmospheric circulation and clouds, we successfully simulated the slow eastward migration of an MJO event. Topography, the zonal sea surface temperature gradient, and interplay between eastward- and westward-propagating signals controlled the timing of the eastward transition of the convective center. Our results demonstrate the potential making of month-long MJO predictions when global cloud-resolving models with realistic initial conditions are used.

Optical eye simulator for laser dazzle events.

PubMed

Coelho, João M P; Freitas, José; Williamson, Craig A

2016-03-20

An optical simulator of the human eye and its application to laser dazzle events are presented. The simulator combines optical design software (ZEMAX) with a scientific programming language (MATLAB) and allows the user to implement and analyze a dazzle scenario using practical, real-world parameters. Contrary to conventional analytical glare analysis, this work uses ray tracing and the scattering model and parameters for each optical element of the eye. The theoretical background of each such element is presented in relation to the model. The overall simulator's calibration, validation, and performance analysis are achieved by comparison with a simpler model based uponCIE disability glare data. Results demonstrate that this kind of advanced optical eye simulation can be used to represent laser dazzle and has the potential to extend the range of applicability of analytical models.

The global event system

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

Winans, J.

The support for the global event system has been designed to allow an application developer to control the APS event generator and receiver boards. This is done by the use of four new record types. These records are customized and are only supported by the device support modules for the APS event generator and receiver boards. The use of the global event system and its associated records should not be confused with the vanilla EPICS events and the associated event records. They are very different.

Reaction Event Counting Statistics of Biopolymer Reaction Systems with Dynamic Heterogeneity.

PubMed

Lim, Yu Rim; Park, Seong Jun; Park, Bo Jung; Cao, Jianshu; Silbey, Robert J; Sung, Jaeyoung

2012-04-10

We investigate the reaction event counting statistics (RECS) of an elementary biopolymer reaction in which the rate coefficient is dependent on states of the biopolymer and the surrounding environment and discover a universal kinetic phase transition in the RECS of the reaction system with dynamic heterogeneity. From an exact analysis for a general model of elementary biopolymer reactions, we find that the variance in the number of reaction events is dependent on the square of the mean number of the reaction events when the size of measurement time is small on the relaxation time scale of rate coefficient fluctuations, which does not conform to renewal statistics. On the other hand, when the size of the measurement time interval is much greater than the relaxation time of rate coefficient fluctuations, the variance becomes linearly proportional to the mean reaction number in accordance with renewal statistics. Gillespie's stochastic simulation method is generalized for the reaction system with a rate coefficient fluctuation. The simulation results confirm the correctness of the analytic results for the time dependent mean and variance of the reaction event number distribution. On the basis of the obtained results, we propose a method of quantitative analysis for the reaction event counting statistics of reaction systems with rate coefficient fluctuations, which enables one to extract information about the magnitude and the relaxation times of the fluctuating reaction rate coefficient, without a bias that can be introduced by assuming a particular kinetic model of conformational dynamics and the conformation dependent reactivity. An exact relationship is established between a higher moment of the reaction event number distribution and the multitime correlation of the reaction rate for the reaction system with a nonequilibrium initial state distribution as well as for the system with the equilibrium initial state distribution.

Advanced Reactor Passive System Reliability Demonstration Analysis for an External Event

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

Bucknor, Matthew D.; Grabaskas, David; Brunett, Acacia J.

2016-01-01

Many advanced reactor designs rely on passive systems to fulfill safety functions during accident sequences. These systems depend heavily on boundary conditions to induce a motive force, meaning the system can fail to operate as intended due to deviations in boundary conditions, rather than as the result of physical failures. Furthermore, passive systems may operate in intermediate or degraded modes. These factors make passive system operation difficult to characterize within a traditional probabilistic framework that only recognizes discrete operating modes and does not allow for the explicit consideration of time-dependent boundary conditions. Argonne National Laboratory has been examining various methodologiesmore » for assessing passive system reliability within a probabilistic risk assessment for a station blackout event at an advanced small modular reactor. This paper provides an overview of a passive system reliability demonstration analysis for an external event. Centering on an earthquake with the possibility of site flooding, the analysis focuses on the behavior of the passive reactor cavity cooling system following potential physical damage and system flooding. The assessment approach seeks to combine mechanistic and simulation-based methods to leverage the benefits of the simulation-based approach without the need to substantially deviate from conventional probabilistic risk assessment techniques. While this study is presented as only an example analysis, the results appear to demonstrate a high level of reliability for the reactor cavity cooling system (and the reactor system in general) to the postulated transient event.« less

Advanced Reactor Passive System Reliability Demonstration Analysis for an External Event

DOE PAGES

Bucknor, Matthew; Grabaskas, David; Brunett, Acacia J.; ...

2017-01-24

We report that many advanced reactor designs rely on passive systems to fulfill safety functions during accident sequences. These systems depend heavily on boundary conditions to induce a motive force, meaning the system can fail to operate as intended because of deviations in boundary conditions, rather than as the result of physical failures. Furthermore, passive systems may operate in intermediate or degraded modes. These factors make passive system operation difficult to characterize within a traditional probabilistic framework that only recognizes discrete operating modes and does not allow for the explicit consideration of time-dependent boundary conditions. Argonne National Laboratory has beenmore » examining various methodologies for assessing passive system reliability within a probabilistic risk assessment for a station blackout event at an advanced small modular reactor. This paper provides an overview of a passive system reliability demonstration analysis for an external event. Considering an earthquake with the possibility of site flooding, the analysis focuses on the behavior of the passive Reactor Cavity Cooling System following potential physical damage and system flooding. The assessment approach seeks to combine mechanistic and simulation-based methods to leverage the benefits of the simulation-based approach without the need to substantially deviate from conventional probabilistic risk assessment techniques. Lastly, although this study is presented as only an example analysis, the results appear to demonstrate a high level of reliability of the Reactor Cavity Cooling System (and the reactor system in general) for the postulated transient event.« less

Non-Lipschitz Dynamics Approach to Discrete Event Systems

NASA Technical Reports Server (NTRS)

Zak, M.; Meyers, R.

1995-01-01

This paper presents and discusses a mathematical formalism for simulation of discrete event dynamics (DED) - a special type of 'man- made' system designed to aid specific areas of information processing. A main objective is to demonstrate that the mathematical formalism for DED can be based upon the terminal model of Newtonian dynamics which allows one to relax Lipschitz conditions at some discrete points.

Rare event simulation in radiation transport

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

Kollman, Craig

1993-10-01

This dissertation studies methods for estimating extremely small probabilities by Monte Carlo simulation. Problems in radiation transport typically involve estimating very rare events or the expected value of a random variable which is with overwhelming probability equal to zero. These problems often have high dimensional state spaces and irregular geometries so that analytic solutions are not possible. Monte Carlo simulation must be used to estimate the radiation dosage being transported to a particular location. If the area is well shielded the probability of any one particular particle getting through is very small. Because of the large number of particles involved,more » even a tiny fraction penetrating the shield may represent an unacceptable level of radiation. It therefore becomes critical to be able to accurately estimate this extremely small probability. Importance sampling is a well known technique for improving the efficiency of rare event calculations. Here, a new set of probabilities is used in the simulation runs. The results are multiple by the likelihood ratio between the true and simulated probabilities so as to keep the estimator unbiased. The variance of the resulting estimator is very sensitive to which new set of transition probabilities are chosen. It is shown that a zero variance estimator does exist, but that its computation requires exact knowledge of the solution. A simple random walk with an associated killing model for the scatter of neutrons is introduced. Large deviation results for optimal importance sampling in random walks are extended to the case where killing is present. An adaptive ``learning`` algorithm for implementing importance sampling is given for more general Markov chain models of neutron scatter. For finite state spaces this algorithm is shown to give with probability one, a sequence of estimates converging exponentially fast to the true solution.« less

Using Discrete Event Simulation to Model Integrated Commodities Consumption for a Launch Campaign of the Space Launch System

NASA Technical Reports Server (NTRS)

Leonard, Daniel; Parsons, Jeremy W.; Cates, Grant

2014-01-01

In May 2013, NASA's GSDO Program requested a study to develop a discrete event simulation (DES) model that analyzes the launch campaign process of the Space Launch System (SLS) from an integrated commodities perspective. The scope of the study includes launch countdown and scrub turnaround and focuses on four core launch commodities: hydrogen, oxygen, nitrogen, and helium. Previously, the commodities were only analyzed individually and deterministically for their launch support capability, but this study was the first to integrate them to examine the impact of their interactions on a launch campaign as well as the effects of process variability on commodity availability. The study produced a validated DES model with Rockwell Arena that showed that Kennedy Space Center's ground systems were capable of supporting a 48-hour scrub turnaround for the SLS. The model will be maintained and updated to provide commodity consumption analysis of future ground system and SLS configurations.

DEVS representation of dynamical systems - Event-based intelligent control. [Discrete Event System Specification

NASA Technical Reports Server (NTRS)

Zeigler, Bernard P.

1989-01-01

It is shown how systems can be advantageously represented as discrete-event models by using DEVS (discrete-event system specification), a set-theoretic formalism. Such DEVS models provide a basis for the design of event-based logic control. In this control paradigm, the controller expects to receive confirming sensor responses to its control commands within definite time windows determined by its DEVS model of the system under control. The event-based contral paradigm is applied in advanced robotic and intelligent automation, showing how classical process control can be readily interfaced with rule-based symbolic reasoning systems.

MHD simulation of the Bastille day event

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

Linker, Jon, E-mail: linkerj@predsci.com; Torok, Tibor; Downs, Cooper

2016-03-25

We describe a time-dependent, thermodynamic, three-dimensional MHD simulation of the July 14, 2000 coronal mass ejection (CME) and flare. The simulation starts with a background corona developed using an MDI-derived magnetic map for the boundary condition. Flux ropes using the modified Titov-Demoulin (TDm) model are used to energize the pre-event active region, which is then destabilized by photospheric flows that cancel flux near the polarity inversion line. More than 10{sup 33} ergs are impulsively released in the simulated eruption, driving a CME at 1500 km/s, close to the observed speed of 1700km/s. The post-flare emission in the simulation is morphologically similarmore » to the observed post-flare loops. The resulting flux rope that propagates to 1 AU is similar in character to the flux rope observed at 1 AU, but the simulated ICME center passes 15° north of Earth.« less

Episodic simulation of future events is impaired in mild Alzheimer's disease

PubMed Central

Addis, Donna Rose; Sacchetti, Daniel C.; Ally, Brandon A.; Budson, Andrew E.; Schacter, Daniel L.

2009-01-01

Recent neuroimaging studies have demonstrated that both remembering the past and simulating the future activate a core neural network including the medial temporal lobes. Regions of this network, in particular the medial temporal lobes, are prime sites for amyloid deposition and are structurally and functionally compromised in Alzheimer's disease (AD). While we know some functions of this core network, specifically episodic autobiographical memory, are impaired in AD, no study has examined whether future episodic simulation is similarly impaired. We tested the ability of sixteen AD patients and sixteen age-matched controls to generate past and future autobiographical events using an adapted version of the Autobiographical Interview. Participants also generated five remote autobiographical memories from across the lifespan. Event transcriptions were segmented into distinct details, classified as either internal (episodic) or external (non-episodic). AD patients exhibited deficits in both remembering past events and simulating future events, generating fewer internal and external episodic details than healthy older controls. The internal and external detail scores were strongly correlated across past and future events, providing further evidence of the close linkages between the mental representations of past and future. PMID:19497331

Rare Event Simulation for T-cell Activation

NASA Astrophysics Data System (ADS)

Lipsmeier, Florian; Baake, Ellen

2009-02-01

The problem of statistical recognition is considered, as it arises in immunobiology, namely, the discrimination of foreign antigens against a background of the body's own molecules. The precise mechanism of this foreign-self-distinction, though one of the major tasks of the immune system, continues to be a fundamental puzzle. Recent progress has been made by van den Berg, Rand, and Burroughs (J. Theor. Biol. 209:465-486, 2001), who modelled the probabilistic nature of the interaction between the relevant cell types, namely, T-cells and antigen-presenting cells (APCs). Here, the stochasticity is due to the random sample of antigens present on the surface of every APC, and to the random receptor type that characterises individual T-cells. It has been shown previously (van den Berg et al. in J. Theor. Biol. 209:465-486, 2001; Zint et al. in J. Math. Biol. 57:841-861, 2008) that this model, though highly idealised, is capable of reproducing important aspects of the recognition phenomenon, and of explaining them on the basis of stochastic rare events. These results were obtained with the help of a refined large deviation theorem and were thus asymptotic in nature. Simulations have, so far, been restricted to the straightforward simple sampling approach, which does not allow for sample sizes large enough to address more detailed questions. Building on the available large deviation results, we develop an importance sampling technique that allows for a convenient exploration of the relevant tail events by means of simulation. With its help, we investigate the mechanism of statistical recognition in some depth. In particular, we illustrate how a foreign antigen can stand out against the self background if it is present in sufficiently many copies, although no a priori difference between self and nonself is built into the model.

Model-Based Adaptive Event-Triggered Control of Strict-Feedback Nonlinear Systems.

PubMed

Li, Yuan-Xin; Yang, Guang-Hong

2018-04-01

This paper is concerned with the adaptive event-triggered control problem of nonlinear continuous-time systems in strict-feedback form. By using the event-sampled neural network (NN) to approximate the unknown nonlinear function, an adaptive model and an associated event-triggered controller are designed by exploiting the backstepping method. In the proposed method, the feedback signals and the NN weights are aperiodically updated only when the event-triggered condition is violated. A positive lower bound on the minimum intersample time is guaranteed to avoid accumulation point. The closed-loop stability of the resulting nonlinear impulsive dynamical system is rigorously proved via Lyapunov analysis under an adaptive event sampling condition. In comparing with the traditional adaptive backstepping design with a fixed sample period, the event-triggered method samples the state and updates the NN weights only when it is necessary. Therefore, the number of transmissions can be significantly reduced. Finally, two simulation examples are presented to show the effectiveness of the proposed control method.

Dual-stage periodic event-triggered output-feedback control for linear systems.

PubMed

Ruan, Zhen; Chen, Wu-Hua; Lu, Xiaomei

2018-05-01

This paper proposes an event-triggered control framework, called dual-stage periodic event-triggered control (DSPETC), which unifies periodic event-triggered control (PETC) and switching event-triggered control (SETC). Specifically, two period parameters h 1 and h 2 are introduced to characterize the new event-triggering rule, where h 1 denotes the sampling period, while h 2 denotes the monitoring period. By choosing some specified values of h 2 , the proposed control scheme can reduce to PETC or SETC scheme. In the DSPETC framework, the controlled system is represented as a switched system model and its stability is analyzed via a switching-time-dependent Lyapunov functional. Both the cases with/without network-induced delays are investigated. Simulation and experimental results show that the DSPETC scheme is superior to the PETC scheme and the SETC scheme. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

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.

Developing a discrete event simulation model for university student shuttle buses

NASA Astrophysics Data System (ADS)

Zulkepli, Jafri; Khalid, Ruzelan; Nawawi, Mohd Kamal Mohd; Hamid, Muhammad Hafizan

2017-11-01

Providing shuttle buses for university students to attend their classes is crucial, especially when their number is large and the distances between their classes and residential halls are far. These factors, in addition to the non-optimal current bus services, typically require the students to wait longer which eventually opens a space for them to complain. To considerably reduce the waiting time, providing the optimal number of buses to transport them from location to location and the effective route schedules to fulfil the students' demand at relevant time ranges are thus important. The optimal bus number and schedules are to be determined and tested using a flexible decision platform. This paper thus models the current services of student shuttle buses in a university using a Discrete Event Simulation approach. The model can flexibly simulate whatever changes configured to the current system and report its effects to the performance measures. How the model was conceptualized and formulated for future system configurations are the main interest of this paper.

Coupled atmosphere-ocean-wave simulations of a storm event over the Gulf of Lion and Balearic Sea

USGS Publications Warehouse

Renault, Lionel; Chiggiato, Jacopo; Warner, John C.; Gomez, Marta; Vizoso, Guillermo; Tintore, Joaquin

2012-01-01

The coastal areas of the North-Western Mediterranean Sea are one of the most challenging places for ocean forecasting. This region is exposed to severe storms events that are of short duration. During these events, significant air-sea interactions, strong winds and large sea-state can have catastrophic consequences in the coastal areas. To investigate these air-sea interactions and the oceanic response to such events, we implemented the Coupled Ocean-Atmosphere-Wave-Sediment Transport Modeling System simulating a severe storm in the Mediterranean Sea that occurred in May 2010. During this event, wind speed reached up to 25 m.s-1 inducing significant sea surface cooling (up to 2°C) over the Gulf of Lion (GoL) and along the storm track, and generating surface waves with a significant height of 6 m. It is shown that the event, associated with a cyclogenesis between the Balearic Islands and the GoL, is relatively well reproduced by the coupled system. A surface heat budget analysis showed that ocean vertical mixing was a major contributor to the cooling tendency along the storm track and in the GoL where turbulent heat fluxes also played an important role. Sensitivity experiments on the ocean-atmosphere coupling suggested that the coupled system is sensitive to the momentum flux parameterization as well as air-sea and air-wave coupling. Comparisons with available atmospheric and oceanic observations showed that the use of the fully coupled system provides the most skillful simulation, illustrating the benefit of using a fully coupled ocean-atmosphere-wave model for the assessment of these storm events.

Anticipating the Chaotic Behaviour of Industrial Systems Based on Stochastic, Event-Driven Simulations

NASA Astrophysics Data System (ADS)

Bruzzone, Agostino G.; Revetria, Roberto; Simeoni, Simone; Viazzo, Simone; Orsoni, Alessandra

2004-08-01

In logistics and industrial production managers must deal with the impact of stochastic events to improve performances and reduce costs. In fact, production and logistics systems are generally designed considering some parameters as deterministically distributed. While this assumption is mostly used for preliminary prototyping, it is sometimes also retained during the final design stage, and especially for estimated parameters (i.e. Market Request). The proposed methodology can determine the impact of stochastic events in the system by evaluating the chaotic threshold level. Such an approach, based on the application of a new and innovative methodology, can be implemented to find the condition under which chaos makes the system become uncontrollable. Starting from problem identification and risk assessment, several classification techniques are used to carry out an effect analysis and contingency plan estimation. In this paper the authors illustrate the methodology with respect to a real industrial case: a production problem related to the logistics of distributed chemical processing.

NEVESIM: event-driven neural simulation framework with a Python interface.

PubMed

Pecevski, Dejan; Kappel, David; Jonke, Zeno

2014-01-01

NEVESIM is a software package for event-driven simulation of networks of spiking neurons with a fast simulation core in C++, and a scripting user interface in the Python programming language. It supports simulation of heterogeneous networks with different types of neurons and synapses, and can be easily extended by the user with new neuron and synapse types. To enable heterogeneous networks and extensibility, NEVESIM is designed to decouple the simulation logic of communicating events (spikes) between the neurons at a network level from the implementation of the internal dynamics of individual neurons. In this paper we will present the simulation framework of NEVESIM, its concepts and features, as well as some aspects of the object-oriented design approaches and simulation strategies that were utilized to efficiently implement the concepts and functionalities of the framework. We will also give an overview of the Python user interface, its basic commands and constructs, and also discuss the benefits of integrating NEVESIM with Python. One of the valuable capabilities of the simulator is to simulate exactly and efficiently networks of stochastic spiking neurons from the recently developed theoretical framework of neural sampling. This functionality was implemented as an extension on top of the basic NEVESIM framework. Altogether, the intended purpose of the NEVESIM framework is to provide a basis for further extensions that support simulation of various neural network models incorporating different neuron and synapse types that can potentially also use different simulation strategies.

NEVESIM: event-driven neural simulation framework with a Python interface

PubMed Central

Pecevski, Dejan; Kappel, David; Jonke, Zeno

2014-01-01

NEVESIM is a software package for event-driven simulation of networks of spiking neurons with a fast simulation core in C++, and a scripting user interface in the Python programming language. It supports simulation of heterogeneous networks with different types of neurons and synapses, and can be easily extended by the user with new neuron and synapse types. To enable heterogeneous networks and extensibility, NEVESIM is designed to decouple the simulation logic of communicating events (spikes) between the neurons at a network level from the implementation of the internal dynamics of individual neurons. In this paper we will present the simulation framework of NEVESIM, its concepts and features, as well as some aspects of the object-oriented design approaches and simulation strategies that were utilized to efficiently implement the concepts and functionalities of the framework. We will also give an overview of the Python user interface, its basic commands and constructs, and also discuss the benefits of integrating NEVESIM with Python. One of the valuable capabilities of the simulator is to simulate exactly and efficiently networks of stochastic spiking neurons from the recently developed theoretical framework of neural sampling. This functionality was implemented as an extension on top of the basic NEVESIM framework. Altogether, the intended purpose of the NEVESIM framework is to provide a basis for further extensions that support simulation of various neural network models incorporating different neuron and synapse types that can potentially also use different simulation strategies. PMID:25177291

Event-driven simulations of nonlinear integrate-and-fire neurons.

PubMed

Tonnelier, Arnaud; Belmabrouk, Hana; Martinez, Dominique

2007-12-01

Event-driven strategies have been used to simulate spiking neural networks exactly. Previous work is limited to linear integrate-and-fire neurons. In this note, we extend event-driven schemes to a class of nonlinear integrate-and-fire models. Results are presented for the quadratic integrate-and-fire model with instantaneous or exponential synaptic currents. Extensions to conductance-based currents and exponential integrate-and-fire neurons are discussed.

SPEEDES - A multiple-synchronization environment for parallel discrete-event simulation

NASA Technical Reports Server (NTRS)

Steinman, Jeff S.

1992-01-01

Synchronous Parallel Environment for Emulation and Discrete-Event Simulation (SPEEDES) is a unified parallel simulation environment. It supports multiple-synchronization protocols without requiring users to recompile their code. When a SPEEDES simulation runs on one node, all the extra parallel overhead is removed automatically at run time. When the same executable runs in parallel, the user preselects the synchronization algorithm from a list of options. SPEEDES currently runs on UNIX networks and on the California Institute of Technology/Jet Propulsion Laboratory Mark III Hypercube. SPEEDES also supports interactive simulations. Featured in the SPEEDES environment is a new parallel synchronization approach called Breathing Time Buckets. This algorithm uses some of the conservative techniques found in Time Bucket synchronization, along with the optimism that characterizes the Time Warp approach. A mathematical model derived from first principles predicts the performance of Breathing Time Buckets. Along with the Breathing Time Buckets algorithm, this paper discusses the rules for processing events in SPEEDES, describes the implementation of various other synchronization protocols supported by SPEEDES, describes some new ones for the future, discusses interactive simulations, and then gives some performance results.

A geostatistical extreme-value framework for fast simulation of natural hazard events

PubMed Central

Stephenson, David B.

2016-01-01

We develop a statistical framework for simulating natural hazard events that combines extreme value theory and geostatistics. Robust generalized additive model forms represent generalized Pareto marginal distribution parameters while a Student’s t-process captures spatial dependence and gives a continuous-space framework for natural hazard event simulations. Efficiency of the simulation method allows many years of data (typically over 10 000) to be obtained at relatively little computational cost. This makes the model viable for forming the hazard module of a catastrophe model. We illustrate the framework by simulating maximum wind gusts for European windstorms, which are found to have realistic marginal and spatial properties, and validate well against wind gust measurements. PMID:27279768

Discrete Event Supervisory Control Applied to Propulsion Systems

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.; Shah, Neerav

2005-01-01

The theory of discrete event supervisory (DES) control was applied to the optimal control of a twin-engine aircraft propulsion system and demonstrated in a simulation. The supervisory control, which is implemented as a finite-state automaton, oversees the behavior of a system and manages it in such a way that it maximizes a performance criterion, similar to a traditional optimal control problem. DES controllers can be nested such that a high-level controller supervises multiple lower level controllers. This structure can be expanded to control huge, complex systems, providing optimal performance and increasing autonomy with each additional level. The DES control strategy for propulsion systems was validated using a distributed testbed consisting of multiple computers--each representing a module of the overall propulsion system--to simulate real-time hardware-in-the-loop testing. In the first experiment, DES control was applied to the operation of a nonlinear simulation of a turbofan engine (running in closed loop using its own feedback controller) to minimize engine structural damage caused by a combination of thermal and structural loads. This enables increased on-wing time for the engine through better management of the engine-component life usage. Thus, the engine-level DES acts as a life-extending controller through its interaction with and manipulation of the engine s operation.

Predicting System Accidents with Model Analysis During Hybrid Simulation

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Fleming, Land D.; Throop, David R.

2002-01-01

Standard discrete event simulation is commonly used to identify system bottlenecks and starving and blocking conditions in resources and services. The CONFIG hybrid discrete/continuous simulation tool can simulate such conditions in combination with inputs external to the simulation. This provides a means for evaluating the vulnerability to system accidents of a system's design, operating procedures, and control software. System accidents are brought about by complex unexpected interactions among multiple system failures , faulty or misleading sensor data, and inappropriate responses of human operators or software. The flows of resource and product materials play a central role in the hazardous situations that may arise in fluid transport and processing systems. We describe the capabilities of CONFIG for simulation-time linear circuit analysis of fluid flows in the context of model-based hazard analysis. We focus on how CONFIG simulates the static stresses in systems of flow. Unlike other flow-related properties, static stresses (or static potentials) cannot be represented by a set of state equations. The distribution of static stresses is dependent on the specific history of operations performed on a system. We discuss the use of this type of information in hazard analysis of system designs.

Relation of Parallel Discrete Event Simulation algorithms with physical models

NASA Astrophysics Data System (ADS)

Shchur, L. N.; Shchur, L. V.

2015-09-01

We extend concept of local simulation times in parallel discrete event simulation (PDES) in order to take into account architecture of the current hardware and software in high-performance computing. We shortly review previous research on the mapping of PDES on physical problems, and emphasise how physical results may help to predict parallel algorithms behaviour.

Simulation framework for intelligent transportation systems

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

Ewing, T.; Doss, E.; Hanebutte, U.

1996-10-01

A simulation framework has been developed for a large-scale, comprehensive, scaleable simulation of an Intelligent Transportation System (ITS). The simulator is designed for running on parallel computers and distributed (networked) computer systems, but can run on standalone workstations for smaller simulations. The simulator currently models instrumented smart vehicles with in-vehicle navigation units capable of optimal route planning and Traffic Management Centers (TMC). The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide two-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphicalmore » user interfaces to support human-factors studies. Realistic modeling of variations of the posted driving speed are based on human factors studies that take into consideration weather, road conditions, driver personality and behavior, and vehicle type. The prototype has been developed on a distributed system of networked UNIX computers but is designed to run on parallel computers, such as ANL`s IBM SP-2, for large-scale problems. A novel feature of the approach is that vehicles are represented by autonomous computer processes which exchange messages with other processes. The vehicles have a behavior model which governs route selection and driving behavior, and can react to external traffic events much like real vehicles. With this approach, the simulation is scaleable to take advantage of emerging massively parallel processor (MPP) systems.« less

Expert systems and simulation models; Proceedings of the Seminar, Tucson, AZ, November 18, 19, 1985

NASA Technical Reports Server (NTRS)

1986-01-01

The seminar presents papers on modeling and simulation methodology, artificial intelligence and expert systems, environments for simulation/expert system development, and methodology for simulation/expert system development. Particular attention is given to simulation modeling concepts and their representation, modular hierarchical model specification, knowledge representation, and rule-based diagnostic expert system development. Other topics include the combination of symbolic and discrete event simulation, real time inferencing, and the management of large knowledge-based simulation projects.

Simulating recurrent event data with hazard functions defined on a total time scale.

PubMed

Jahn-Eimermacher, Antje; Ingel, Katharina; Ozga, Ann-Kathrin; Preussler, Stella; Binder, Harald

2015-03-08

In medical studies with recurrent event data a total time scale perspective is often needed to adequately reflect disease mechanisms. This means that the hazard process is defined on the time since some starting point, e.g. the beginning of some disease, in contrast to a gap time scale where the hazard process restarts after each event. While techniques such as the Andersen-Gill model have been developed for analyzing data from a total time perspective, techniques for the simulation of such data, e.g. for sample size planning, have not been investigated so far. We have derived a simulation algorithm covering the Andersen-Gill model that can be used for sample size planning in clinical trials as well as the investigation of modeling techniques. Specifically, we allow for fixed and/or random covariates and an arbitrary hazard function defined on a total time scale. Furthermore we take into account that individuals may be temporarily insusceptible to a recurrent incidence of the event. The methods are based on conditional distributions of the inter-event times conditional on the total time of the preceeding event or study start. Closed form solutions are provided for common distributions. The derived methods have been implemented in a readily accessible R script. The proposed techniques are illustrated by planning the sample size for a clinical trial with complex recurrent event data. The required sample size is shown to be affected not only by censoring and intra-patient correlation, but also by the presence of risk-free intervals. This demonstrates the need for a simulation algorithm that particularly allows for complex study designs where no analytical sample size formulas might exist. The derived simulation algorithm is seen to be useful for the simulation of recurrent event data that follow an Andersen-Gill model. Next to the use of a total time scale, it allows for intra-patient correlation and risk-free intervals as are often observed in clinical trial data

Rare Event Simulation in Radiation Transport

NASA Astrophysics Data System (ADS)

Kollman, Craig

This dissertation studies methods for estimating extremely small probabilities by Monte Carlo simulation. Problems in radiation transport typically involve estimating very rare events or the expected value of a random variable which is with overwhelming probability equal to zero. These problems often have high dimensional state spaces and irregular geometries so that analytic solutions are not possible. Monte Carlo simulation must be used to estimate the radiation dosage being transported to a particular location. If the area is well shielded the probability of any one particular particle getting through is very small. Because of the large number of particles involved, even a tiny fraction penetrating the shield may represent an unacceptable level of radiation. It therefore becomes critical to be able to accurately estimate this extremely small probability. Importance sampling is a well known technique for improving the efficiency of rare event calculations. Here, a new set of probabilities is used in the simulation runs. The results are multiplied by the likelihood ratio between the true and simulated probabilities so as to keep our estimator unbiased. The variance of the resulting estimator is very sensitive to which new set of transition probabilities are chosen. It is shown that a zero variance estimator does exist, but that its computation requires exact knowledge of the solution. A simple random walk with an associated killing model for the scatter of neutrons is introduced. Large deviation results for optimal importance sampling in random walks are extended to the case where killing is present. An adaptive "learning" algorithm for implementing importance sampling is given for more general Markov chain models of neutron scatter. For finite state spaces this algorithm is shown to give, with probability one, a sequence of estimates converging exponentially fast to the true solution. In the final chapter, an attempt to generalize this algorithm to a continuous

Microbial ice nucleators scavenged from the atmosphere during simulated rain events

NASA Astrophysics Data System (ADS)

Hanlon, Regina; Powers, Craig; Failor, Kevin; Monteil, Caroline L.; Vinatzer, Boris A.; Schmale, David G.

2017-08-01

Rain and snow collected at ground level have been found to contain biological ice nucleators. These ice nucleators have been proposed to have originated in clouds, where they may have participated in the formation of precipitation via ice phase nucleation. We conducted a series of field experiments to test the hypothesis that at least some of the microbial ice nucleators (prokaryotes and eukaryotes) present in rain may not originate in clouds but instead be scavenged from the lower atmosphere by rainfall. Thirty-three simulated rain events were conducted over four months off the side of the Smart Road Bridge in Blacksburg, VA, USA. In each event, sterile water was dispensed over the side of the bridge and recovered in sterile containers in an open fallow agricultural field below (a distance of ∼55 m). Microbes scavenged from the simulated rain events were cultured and their ice nucleation activity was examined. Putative microbial ice nucleators were cultured from 94% (31/33) of the simulated rain events, and represented 1.5% (121/8331) of the total colonies assayed. Putative ice nucleators were subjected to additional droplet freezing assays, and those confirmed through these repeated assays represented 0.4% (34/8331) of the total. Mean CFUs scavenged by simulated rain ranged from 2 to 267 CFUs/mL. Scavenged ice nucleators belong to a number of taxa including the bacterial genera Pseudomonas, Pantoea, and Xanthomonas, and the fungal genera Fusarium, Humicola, and Mortierella. An ice-nucleating strain of the fungal genus Penicillium was also recovered from a volumetric air sampler at the study site. This work expands our knowledge of the scavenging properties of rainfall, and suggests that at least some ice nucleators in natural precipitation events may have been scrubbed from the atmosphere during rainfall, and thus are not likely to be involved in precipitation.

Convection-Resolving Climate Change Simulations: Intensification of Heavy Hourly Precipitation Events

NASA Astrophysics Data System (ADS)

Ban, N.; Schmidli, J.; Schar, C.

2014-12-01

Reliable climate-change projections of extreme precipitation events are of great interest to decision makers, due to potentially important hydrological impacts such as floods, land slides and debris flows. Low-resolution climate models generally project increases of heavy precipitation events with climate change, but there are large uncertainties related to the limited spatial resolution and the parameterized representation of atmospheric convection. Here we employ a convection-resolving version of the COSMO model across an extended region (1100 km x 1100 km) covering the European Alps to investigate the differences between parameterized and explicit convection in climate-change scenarios. We conduct 10-year long integrations at resolutions of 12 and 2km. Validation using ERA-Interim driven simulations reveals major improvements with the 2km resolution, in particular regarding the diurnal cycle of mean precipitation and the representation of hourly extremes. In addition, 2km simulations replicate the observed super-adiabatic scaling at precipitation stations, i.e. peak hourly events increase faster with temperature than the Clausius-Clapeyron scaling of 7%/K (see Ban et al. 2014). Convection-resolving climate change scenarios are conducted using control (1991-2000) and scenario (2081-2090) simulations driven by a CMIP5 GCM (i.e. the MPI-ESM-LR) under the IPCC RCP8.5 scenario. Comparison between 12 and 2km resolutions with parameterized and explicit convection, respectively, reveals close agreement in terms of mean summer precipitation amounts (decrease by 30%), and regarding slight increases of heavy day-long events (amounting to 15% for 90th-percentile for wet-day precipitation). However, the different resolutions yield large differences regarding extreme hourly precipitation, with the 2km version projecting substantially faster increases of heavy hourly precipitation events (about 30% increases for 90th-percentile hourly events). Ban, N., J. Schmidli and C. Sch

Distributed event-triggered consensus tracking of second-order multi-agent systems with a virtual leader

NASA Astrophysics Data System (ADS)

Jie, Cao; Zhi-Hai, Wu; Li, Peng

2016-05-01

This paper investigates the consensus tracking problems of second-order multi-agent systems with a virtual leader via event-triggered control. A novel distributed event-triggered transmission scheme is proposed, which is intermittently examined at constant sampling instants. Only partial neighbor information and local measurements are required for event detection. Then the corresponding event-triggered consensus tracking protocol is presented to guarantee second-order multi-agent systems to achieve consensus tracking. Numerical simulations are given to illustrate the effectiveness of the proposed strategy. Project supported by the National Natural Science Foundation of China (Grant Nos. 61203147, 61374047, and 61403168).

Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming.

PubMed

Zhang, Qichao; Zhao, Dongbin; Wang, Ding

2018-01-01

In this paper, the robust control problem for a class of continuous-time nonlinear system with unmatched uncertainties is investigated using an event-based control method. First, the robust control problem is transformed into a corresponding optimal control problem with an augmented control and an appropriate cost function. Under the event-based mechanism, we prove that the solution of the optimal control problem can asymptotically stabilize the uncertain system with an adaptive triggering condition. That is, the designed event-based controller is robust to the original uncertain system. Note that the event-based controller is updated only when the triggering condition is satisfied, which can save the communication resources between the plant and the controller. Then, a single network adaptive dynamic programming structure with experience replay technique is constructed to approach the optimal control policies. The stability of the closed-loop system with the event-based control policy and the augmented control policy is analyzed using the Lyapunov approach. Furthermore, we prove that the minimal intersample time is bounded by a nonzero positive constant, which excludes Zeno behavior during the learning process. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.

A discrete event simulation tool to support and predict hospital and clinic staffing.

PubMed

DeRienzo, Christopher M; Shaw, Ryan J; Meanor, Phillip; Lada, Emily; Ferranti, Jeffrey; Tanaka, David

2017-06-01

We demonstrate how to develop a simulation tool to help healthcare managers and administrators predict and plan for staffing needs in a hospital neonatal intensive care unit using administrative data. We developed a discrete event simulation model of nursing staff needed in a neonatal intensive care unit and then validated the model against historical data. The process flow was translated into a discrete event simulation model. Results demonstrated that the model can be used to give a respectable estimate of annual admissions, transfers, and deaths based upon two different staffing levels. The discrete event simulation tool model can provide healthcare managers and administrators with (1) a valid method of modeling patient mix, patient acuity, staffing needs, and costs in the present state and (2) a forecast of how changes in a unit's staffing, referral patterns, or patient mix would affect a unit in a future state.

Near Optimal Event-Triggered Control of Nonlinear Discrete-Time Systems Using Neurodynamic Programming.

PubMed

Sahoo, Avimanyu; Xu, Hao; Jagannathan, Sarangapani

2016-09-01

This paper presents an event-triggered near optimal control of uncertain nonlinear discrete-time systems. Event-driven neurodynamic programming (NDP) is utilized to design the control policy. A neural network (NN)-based identifier, with event-based state and input vectors, is utilized to learn the system dynamics. An actor-critic framework is used to learn the cost function and the optimal control input. The NN weights of the identifier, the critic, and the actor NNs are tuned aperiodically once every triggered instant. An adaptive event-trigger condition to decide the trigger instants is derived. Thus, a suitable number of events are generated to ensure a desired accuracy of approximation. A near optimal performance is achieved without using value and/or policy iterations. A detailed analysis of nontrivial inter-event times with an explicit formula to show the reduction in computation is also derived. The Lyapunov technique is used in conjunction with the event-trigger condition to guarantee the ultimate boundedness of the closed-loop system. The simulation results are included to verify the performance of the controller. The net result is the development of event-driven NDP.

A conceptual modeling framework for discrete event simulation using hierarchical control structures.

PubMed

Furian, N; O'Sullivan, M; Walker, C; Vössner, S; Neubacher, D

2015-08-01

Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM's applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models' system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example.

A conceptual modeling framework for discrete event simulation using hierarchical control structures

PubMed Central

Furian, N.; O’Sullivan, M.; Walker, C.; Vössner, S.; Neubacher, D.

2015-01-01

Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM’s applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models’ system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example. PMID:26778940

Monte Carlo generator ELRADGEN 2.0 for simulation of radiative events in elastic ep-scattering of polarized particles

NASA Astrophysics Data System (ADS)

Akushevich, I.; Filoti, O. F.; Ilyichev, A.; Shumeiko, N.

2012-07-01

The structure and algorithms of the Monte Carlo generator ELRADGEN 2.0 designed to simulate radiative events in polarized ep-scattering are presented. The full set of analytical expressions for the QED radiative corrections is presented and discussed in detail. Algorithmic improvements implemented to provide faster simulation of hard real photon events are described. Numerical tests show high quality of generation of photonic variables and radiatively corrected cross section. The comparison of the elastic radiative tail simulated within the kinematical conditions of the BLAST experiment at MIT BATES shows a good agreement with experimental data. Catalogue identifier: AELO_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AELO_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC license, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 1299 No. of bytes in distributed program, including test data, etc.: 11 348 Distribution format: tar.gz Programming language: FORTRAN 77 Computer: All Operating system: Any RAM: 1 MB Classification: 11.2, 11.4 Nature of problem: Simulation of radiative events in polarized ep-scattering. Solution method: Monte Carlo simulation according to the distributions of the real photon kinematic variables that are calculated by the covariant method of QED radiative correction estimation. The approach provides rather fast and accurate generation. Running time: The simulation of 108 radiative events for itest:=1 takes up to 52 seconds on Pentium(R) Dual-Core 2.00 GHz processor.

Simulating Heinrich events in a coupled atmosphere-ocean-ice sheet model

NASA Astrophysics Data System (ADS)

Mikolajewicz, Uwe; Ziemen, Florian

2016-04-01

Heinrich events are among the most prominent events of long-term climate variability recorded in proxies across the northern hemisphere. They are the archetype of ice sheet - climate interactions on millennial time scales. Nevertheless, the exact mechanisms that cause Heinrich events are still under discussion, and their climatic consequences are far from being fully understood. We contribute to answering the open questions by studying Heinrich events in a coupled ice sheet model (ISM) atmosphere-ocean-vegetation general circulation model (AOVGCM) framework, where this variability occurs as part of the model generated internal variability without the need to prescribe external perturbations, as was the standard approach in almost all model studies so far. The setup consists of a northern hemisphere setup of the modified Parallel Ice Sheet Model (mPISM) coupled to the global coarse resolution AOVGCM ECHAM5/MPIOM/LPJ. The simulations used for this analysis were an ensemble covering substantial parts of the late Glacial forced with transient insolation and prescribed atmospheric greenhouse gas concentrations. The modeled Heinrich events show a marked influence of the ice discharge on the Atlantic circulation and heat transport, but none of the Heinrich events during the Glacial did show a complete collapse of the North Atlantic meridional overturning circulation. The simulated main consequences of the Heinrich events are a freshening and cooling over the North Atlantic and a drying over northern Europe.

Discrete-Event Simulation in Chemical Engineering.

ERIC Educational Resources Information Center

Schultheisz, Daniel; Sommerfeld, Jude T.

1988-01-01

Gives examples, descriptions, and uses for various types of simulation systems, including the Flowtran, Process, Aspen Plus, Design II, GPSS, Simula, and Simscript. Explains similarities in simulators, terminology, and a batch chemical process. Tables and diagrams are included. (RT)

Behavior coordination of mobile robotics using supervisory control of fuzzy discrete event systems.

PubMed

Jayasiri, Awantha; Mann, George K I; Gosine, Raymond G

2011-10-01

In order to incorporate the uncertainty and impreciseness present in real-world event-driven asynchronous systems, fuzzy discrete event systems (DESs) (FDESs) have been proposed as an extension to crisp DESs. In this paper, first, we propose an extension to the supervisory control theory of FDES by redefining fuzzy controllable and uncontrollable events. The proposed supervisor is capable of enabling feasible uncontrollable and controllable events with different possibilities. Then, the extended supervisory control framework of FDES is employed to model and control several navigational tasks of a mobile robot using the behavior-based approach. The robot has limited sensory capabilities, and the navigations have been performed in several unmodeled environments. The reactive and deliberative behaviors of the mobile robotic system are weighted through fuzzy uncontrollable and controllable events, respectively. By employing the proposed supervisory controller, a command-fusion-type behavior coordination is achieved. The observability of fuzzy events is incorporated to represent the sensory imprecision. As a systematic analysis of the system, a fuzzy-state-based controllability measure is introduced. The approach is implemented in both simulation and real time. A performance evaluation is performed to quantitatively estimate the validity of the proposed approach over its counterparts.

Adaptive Event-Triggered Control Based on Heuristic Dynamic Programming for Nonlinear Discrete-Time Systems.

PubMed

Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo

2017-07-01

This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.

Validation of a DICE Simulation Against a Discrete Event Simulation Implemented Entirely in Code.

PubMed

Möller, Jörgen; Davis, Sarah; Stevenson, Matt; Caro, J Jaime

2017-10-01

Modeling is an essential tool for health technology assessment, and various techniques for conceptualizing and implementing such models have been described. Recently, a new method has been proposed-the discretely integrated condition event or DICE simulation-that enables frequently employed approaches to be specified using a common, simple structure that can be entirely contained and executed within widely available spreadsheet software. To assess if a DICE simulation provides equivalent results to an existing discrete event simulation, a comparison was undertaken. A model of osteoporosis and its management programmed entirely in Visual Basic for Applications and made public by the National Institute for Health and Care Excellence (NICE) Decision Support Unit was downloaded and used to guide construction of its DICE version in Microsoft Excel ® . The DICE model was then run using the same inputs and settings, and the results were compared. The DICE version produced results that are nearly identical to the original ones, with differences that would not affect the decision direction of the incremental cost-effectiveness ratios (<1% discrepancy), despite the stochastic nature of the models. The main limitation of the simple DICE version is its slow execution speed. DICE simulation did not alter the results and, thus, should provide a valid way to design and implement decision-analytic models without requiring specialized software or custom programming. Additional efforts need to be made to speed up execution.

The devil is in the details: Comparisons of episodic simulations of positive and negative future events.

PubMed

Puig, Vannia A; Szpunar, Karl K

2017-08-01

Over the past decade, psychologists have devoted considerable attention to episodic simulation-the ability to imagine specific hypothetical events. Perhaps one of the most consistent patterns of data to emerge from this literature is that positive simulations of the future are rated as more detailed than negative simulations of the future, a pattern of results that is commonly interpreted as evidence for a positivity bias in future thinking. In the present article, we demonstrate across two experiments that negative future events are consistently simulated in more detail than positive future events when frequency of prior thinking is taken into account as a possible confounding variable and when level of detail associated with simulated events is assessed using an objective scoring criterion. Our findings are interpreted in the context of the mobilization-minimization hypothesis of event cognition that suggests people are especially likely to devote cognitive resources to processing negative scenarios. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A Framework for the Optimization of Discrete-Event Simulation Models

NASA Technical Reports Server (NTRS)

Joshi, B. D.; Unal, R.; White, N. H.; Morris, W. D.

1996-01-01

With the growing use of computer modeling and simulation, in all aspects of engineering, the scope of traditional optimization has to be extended to include simulation models. Some unique aspects have to be addressed while optimizing via stochastic simulation models. The optimization procedure has to explicitly account for the randomness inherent in the stochastic measures predicted by the model. This paper outlines a general purpose framework for optimization of terminating discrete-event simulation models. The methodology combines a chance constraint approach for problem formulation, together with standard statistical estimation and analyses techniques. The applicability of the optimization framework is illustrated by minimizing the operation and support resources of a launch vehicle, through a simulation model.

The simulation library of the Belle II software system

NASA Astrophysics Data System (ADS)

Kim, D. Y.; Ritter, M.; Bilka, T.; Bobrov, A.; Casarosa, G.; Chilikin, K.; Ferber, T.; Godang, R.; Jaegle, I.; Kandra, J.; Kodys, P.; Kuhr, T.; Kvasnicka, P.; Nakayama, H.; Piilonen, L.; Pulvermacher, C.; Santelj, L.; Schwenker, B.; Sibidanov, A.; Soloviev, Y.; Starič, M.; Uglov, T.

2017-10-01

SuperKEKB, the next generation B factory, has been constructed in Japan as an upgrade of KEKB. This brand new e+ e- collider is expected to deliver a very large data set for the Belle II experiment, which will be 50 times larger than the previous Belle sample. Both the triggered physics event rate and the background event rate will be increased by at least 10 times than the previous ones, and will create a challenging data taking environment for the Belle II detector. The software system of the Belle II experiment is designed to execute this ambitious plan. A full detector simulation library, which is a part of the Belle II software system, is created based on Geant4 and has been tested thoroughly. Recently the library has been upgraded with Geant4 version 10.1. The library is behaving as expected and it is utilized actively in producing Monte Carlo data sets for various studies. In this paper, we will explain the structure of the simulation library and the various interfaces to other packages including geometry and beam background simulation.

A Coupled Earthquake-Tsunami Simulation Framework Applied to the Sumatra 2004 Event

NASA Astrophysics Data System (ADS)

Vater, Stefan; Bader, Michael; Behrens, Jörn; van Dinther, Ylona; Gabriel, Alice-Agnes; Madden, Elizabeth H.; Ulrich, Thomas; Uphoff, Carsten; Wollherr, Stephanie; van Zelst, Iris

2017-04-01

Large earthquakes along subduction zone interfaces have generated destructive tsunamis near Chile in 1960, Sumatra in 2004, and northeast Japan in 2011. In order to better understand these extreme events, we have developed tools for physics-based, coupled earthquake-tsunami simulations. This simulation framework is applied to the 2004 Indian Ocean M 9.1-9.3 earthquake and tsunami, a devastating event that resulted in the loss of more than 230,000 lives. The earthquake rupture simulation is performed using an ADER discontinuous Galerkin discretization on an unstructured tetrahedral mesh with the software SeisSol. Advantages of this approach include accurate representation of complex fault and sea floor geometries and a parallelized and efficient workflow in high-performance computing environments. Accurate and efficient representation of the tsunami evolution and inundation at the coast is achieved with an adaptive mesh discretizing the shallow water equations with a second-order Runge-Kutta discontinuous Galerkin (RKDG) scheme. With the application of the framework to this historic event, we aim to better understand the involved mechanisms between the dynamic earthquake within the earth's crust, the resulting tsunami wave within the ocean, and the final coastal inundation process. Earthquake model results are constrained by GPS surface displacements and tsunami model results are compared with buoy and inundation data. This research is part of the ASCETE Project, "Advanced Simulation of Coupled Earthquake and Tsunami Events", funded by the Volkswagen Foundation.

Aperiodic Robust Model Predictive Control for Constrained Continuous-Time Nonlinear Systems: An Event-Triggered Approach.

PubMed

Liu, Changxin; Gao, Jian; Li, Huiping; Xu, Demin

2018-05-01

The event-triggered control is a promising solution to cyber-physical systems, such as networked control systems, multiagent systems, and large-scale intelligent systems. In this paper, we propose an event-triggered model predictive control (MPC) scheme for constrained continuous-time nonlinear systems with bounded disturbances. First, a time-varying tightened state constraint is computed to achieve robust constraint satisfaction, and an event-triggered scheduling strategy is designed in the framework of dual-mode MPC. Second, the sufficient conditions for ensuring feasibility and closed-loop robust stability are developed, respectively. We show that robust stability can be ensured and communication load can be reduced with the proposed MPC algorithm. Finally, numerical simulations and comparison studies are performed to verify the theoretical results.

On-Die Sensors for Transient Events

NASA Astrophysics Data System (ADS)

Suchak, Mihir Vimal

Failures caused by transient electromagnetic events like Electrostatic Discharge (ESD) are a major concern for embedded systems. The component often failing is an integrated circuit (IC). Determining which IC is affected in a multi-device system is a challenging task. Debugging errors often requires sophisticated lab setups which require intentionally disturbing and probing various parts of the system which might not be easily accessible. Opening the system and adding probes may change its response to the transient event, which further compounds the problem. On-die transient event sensors were developed that require relatively little area on die, making them inexpensive, they consume negligible static current, and do not interfere with normal operation of the IC. These circuits can be used to determine the pin involved and the level of the event in the event of a transient event affecting the IC, thus allowing the user to debug system-level transient events without modifying the system. The circuit and detection scheme design has been completed and verified in simulations with Cadence Virtuoso environment. Simulations accounted for the impact of the ESD protection circuits, parasitics from the I/O pin, package and I/O ring, and included a model of an ESD gun to test the circuit's response to an ESD pulse as specified in IEC 61000-4-2. Multiple detection schemes are proposed. The final detection scheme consists of an event detector and a level sensor. The event detector latches on the presence of an event at a pad, to determine on which pin an event occurred. The level sensor generates current proportional to the level of the event. This current is converted to a voltage and digitized at the A/D converter to be read by the microprocessor. Detection scheme shows good performance in simulations when checked against process variations and different kind of events.

Advances in Discrete-Event Simulation for MSL Command Validation

NASA Technical Reports Server (NTRS)

Patrikalakis, Alexander; O'Reilly, Taifun

2013-01-01

In the last five years, the discrete event simulator, SEQuence GENerator (SEQGEN), developed at the Jet Propulsion Laboratory to plan deep-space missions, has greatly increased uplink operations capacity to deal with increasingly complicated missions. In this paper, we describe how the Mars Science Laboratory (MSL) project makes full use of an interpreted environment to simulate change in more than fifty thousand flight software parameters and conditional command sequences to predict the result of executing a conditional branch in a command sequence, and enable the ability to warn users whenever one or more simulated spacecraft states change in an unexpected manner. Using these new SEQGEN features, operators plan more activities in one sol than ever before.

High-speed extended-term time-domain simulation for online cascading analysis of power system

NASA Astrophysics Data System (ADS)

Fu, Chuan

A high-speed extended-term (HSET) time domain simulator (TDS), intended to become a part of an energy management system (EMS), has been newly developed for use in online extended-term dynamic cascading analysis of power systems. HSET-TDS includes the following attributes for providing situational awareness of high-consequence events: (i) online analysis, including n-1 and n-k events, (ii) ability to simulate both fast and slow dynamics for 1-3 hours in advance, (iii) inclusion of rigorous protection-system modeling, (iv) intelligence for corrective action ID, storage, and fast retrieval, and (v) high-speed execution. Very fast on-line computational capability is the most desired attribute of this simulator. Based on the process of solving algebraic differential equations describing the dynamics of power system, HSET-TDS seeks to develop computational efficiency at each of the following hierarchical levels, (i) hardware, (ii) strategies, (iii) integration methods, (iv) nonlinear solvers, and (v) linear solver libraries. This thesis first describes the Hammer-Hollingsworth 4 (HH4) implicit integration method. Like the trapezoidal rule, HH4 is symmetrically A-Stable but it possesses greater high-order precision (h4 ) than the trapezoidal rule. Such precision enables larger integration steps and therefore improves simulation efficiency for variable step size implementations. This thesis provides the underlying theory on which we advocate use of HH4 over other numerical integration methods for power system time-domain simulation. Second, motivated by the need to perform high speed extended-term time domain simulation (HSET-TDS) for on-line purposes, this thesis presents principles for designing numerical solvers of differential algebraic systems associated with power system time-domain simulation, including DAE construction strategies (Direct Solution Method), integration methods(HH4), nonlinear solvers(Very Dishonest Newton), and linear solvers(SuperLU). We have

A View on Future Building System Modeling and Simulation

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

Wetter, Michael

This chapter presents what a future environment for building system modeling and simulation may look like. As buildings continue to require increased performance and better comfort, their energy and control systems are becoming more integrated and complex. We therefore focus in this chapter on the modeling, simulation and analysis of building energy and control systems. Such systems can be classified as heterogeneous systems because they involve multiple domains, such as thermodynamics, fluid dynamics, heat and mass transfer, electrical systems, control systems and communication systems. Also, they typically involve multiple temporal and spatial scales, and their evolution can be described bymore » coupled differential equations, discrete equations and events. Modeling and simulating such systems requires a higher level of abstraction and modularisation to manage the increased complexity compared to what is used in today's building simulation programs. Therefore, the trend towards more integrated building systems is likely to be a driving force for changing the status quo of today's building simulation programs. Thischapter discusses evolving modeling requirements and outlines a path toward a future environment for modeling and simulation of heterogeneous building systems.A range of topics that would require many additional pages of discussion has been omitted. Examples include computational fluid dynamics for air and particle flow in and around buildings, people movement, daylight simulation, uncertainty propagation and optimisation methods for building design and controls. For different discussions and perspectives on the future of building modeling and simulation, we refer to Sahlin (2000), Augenbroe (2001) and Malkawi and Augenbroe (2004).« less

: A Scalable and Transparent System for Simulating MPI Programs

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

Perumalla, Kalyan S

2010-01-01

is a scalable, transparent system for experimenting with the execution of parallel programs on simulated computing platforms. The level of simulated detail can be varied for application behavior as well as for machine characteristics. Unique features of are repeatability of execution, scalability to millions of simulated (virtual) MPI ranks, scalability to hundreds of thousands of host (real) MPI ranks, portability of the system to a variety of host supercomputing platforms, and the ability to experiment with scientific applications whose source-code is available. The set of source-code interfaces supported by is being expanded to support a wider set of applications, andmore » MPI-based scientific computing benchmarks are being ported. In proof-of-concept experiments, has been successfully exercised to spawn and sustain very large-scale executions of an MPI test program given in source code form. Low slowdowns are observed, due to its use of purely discrete event style of execution, and due to the scalability and efficiency of the underlying parallel discrete event simulation engine, sik. In the largest runs, has been executed on up to 216,000 cores of a Cray XT5 supercomputer, successfully simulating over 27 million virtual MPI ranks, each virtual rank containing its own thread context, and all ranks fully synchronized by virtual time.« less

The added value of convection permitting simulations of extreme precipitation events over the eastern Mediterranean

NASA Astrophysics Data System (ADS)

Zittis, G.; Bruggeman, A.; Camera, C.; Hadjinicolaou, P.; Lelieveld, J.

2017-07-01

Climate change is expected to substantially influence precipitation amounts and distribution. To improve simulations of extreme rainfall events, we analyzed the performance of different convection and microphysics parameterizations of the WRF (Weather Research and Forecasting) model at very high horizontal resolutions (12, 4 and 1 km). Our study focused on the eastern Mediterranean climate change hot-spot. Five extreme rainfall events over Cyprus were identified from observations and were dynamically downscaled from the ERA-Interim (EI) dataset with WRF. We applied an objective ranking scheme, using a 1-km gridded observational dataset over Cyprus and six different performance metrics, to investigate the skill of the WRF configurations. We evaluated the rainfall timing and amounts for the different resolutions, and discussed the observational uncertainty over the particular extreme events by comparing three gridded precipitation datasets (E-OBS, APHRODITE and CHIRPS). Simulations with WRF capture rainfall over the eastern Mediterranean reasonably well for three of the five selected extreme events. For these three cases, the WRF simulations improved the ERA-Interim data, which strongly underestimate the rainfall extremes over Cyprus. The best model performance is obtained for the January 1989 event, simulated with an average bias of 4% and a modified Nash-Sutcliff of 0.72 for the 5-member ensemble of the 1-km simulations. We found overall added value for the convection-permitting simulations, especially over regions of high-elevation. Interestingly, for some cases the intermediate 4-km nest was found to outperform the 1-km simulations for low-elevation coastal parts of Cyprus. Finally, we identified significant and inconsistent discrepancies between the three, state of the art, gridded precipitation datasets for the tested events, highlighting the observational uncertainty in the region.

Assessment of Critical Events Corridors through Multivariate Cascading Outages Analysis

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

Makarov, Yuri V.; Samaan, Nader A.; Diao, Ruisheng

2011-10-17

Massive blackouts of electrical power systems in North America over the past decade has focused increasing attention upon ways to identify and simulate network events that may potentially lead to widespread network collapse. This paper summarizes a method to simulate power-system vulnerability to cascading failures to a supplied set of initiating events synonymously termed as Extreme Events. The implemented simulation method is currently confined to simulating steady state power-system response to a set of extreme events. The outlined method of simulation is meant to augment and provide a new insight into bulk power transmission network planning that at present remainsmore » mainly confined to maintaining power system security for single and double component outages under a number of projected future network operating conditions. Although one of the aims of this paper is to demonstrate the feasibility of simulating network vulnerability to cascading outages, a more important goal has been to determine vulnerable parts of the network that may potentially be strengthened in practice so as to mitigate system susceptibility to cascading failures. This paper proposes to demonstrate a systematic approach to analyze extreme events and identify vulnerable system elements that may be contributing to cascading outages. The hypothesis of critical events corridors is proposed to represent repeating sequential outages that can occur in the system for multiple initiating events. The new concept helps to identify system reinforcements that planners could engineer in order to 'break' the critical events sequences and therefore lessen the likelihood of cascading outages. This hypothesis has been successfully validated with a California power system model.« less

Simulation of Ionospheric Response During Solar Eclipse Events

NASA Astrophysics Data System (ADS)

Kordella, L.; Earle, G. D.; Huba, J.

2016-12-01

Total solar eclipses are rare, short duration events that present interesting case studies of ionospheric behavior because the structure of the ionosphere is determined and stabilized by varying energies of solar radiation (Lyman alpha, X-ray, U.V., etc.). The ionospheric response to eclipse events is a source of scientific intrigue that has been studied in various capacities over the past 50 years. Unlike the daily terminator crossings, eclipses cause highly localized, steep gradients of ionization efficiency due to their comparatively small solar zenith angle. However, the corona remains present even at full obscuration, meaning that the energy reduction never falls to the levels seen at night. Previous eclipse studies performed by research groups in the US, UK, China and Russia have shown a range of effects, some counter-intuitive and others contradictory. In the shadowed region of an eclipse (i.e. umbra) it is logical to assume a reduction in ionization rates correlating with the reduction of incident solar radiation. Results have shown that even this straightforward hypothesis may not be true; effects on plasma distribution, motion and temperature are more appreciable than might be expected. Recent advancements in ionospheric simulation codes present the opportunity to investigate the relationship between geophysical conditions and geomagnetic location on resulting eclipse event ionosphere. Here we present computational simulation results using the Naval Research Lab (NRL) developed ionospheric modeling codes Sami2 and Sami3 (Sami2 is Another Model of the Ionosphere) modified with spatio-temporal photoionization attenuation functions derived from theory and empirical data.

Markov modeling and discrete event simulation in health care: a systematic comparison.

PubMed

Standfield, Lachlan; Comans, Tracy; Scuffham, Paul

2014-04-01

The aim of this study was to assess if the use of Markov modeling (MM) or discrete event simulation (DES) for cost-effectiveness analysis (CEA) may alter healthcare resource allocation decisions. A systematic literature search and review of empirical and non-empirical studies comparing MM and DES techniques used in the CEA of healthcare technologies was conducted. Twenty-two pertinent publications were identified. Two publications compared MM and DES models empirically, one presented a conceptual DES and MM, two described a DES consensus guideline, and seventeen drew comparisons between MM and DES through the authors' experience. The primary advantages described for DES over MM were the ability to model queuing for limited resources, capture individual patient histories, accommodate complexity and uncertainty, represent time flexibly, model competing risks, and accommodate multiple events simultaneously. The disadvantages of DES over MM were the potential for model overspecification, increased data requirements, specialized expensive software, and increased model development, validation, and computational time. Where individual patient history is an important driver of future events an individual patient simulation technique like DES may be preferred over MM. Where supply shortages, subsequent queuing, and diversion of patients through other pathways in the healthcare system are likely to be drivers of cost-effectiveness, DES modeling methods may provide decision makers with more accurate information on which to base resource allocation decisions. Where these are not major features of the cost-effectiveness question, MM remains an efficient, easily validated, parsimonious, and accurate method of determining the cost-effectiveness of new healthcare interventions.

Simulating advanced life support systems to test integrated control approaches

NASA Astrophysics Data System (ADS)

Kortenkamp, D.; Bell, S.

Simulations allow for testing of life support control approaches before hardware is designed and built. Simulations also allow for the safe exploration of alternative control strategies during life support operation. As such, they are an important component of any life support research program and testbed. This paper describes a specific advanced life support simulation being created at NASA Johnson Space Center. It is a discrete-event simulation that is dynamic and stochastic. It simulates all major components of an advanced life support system, including crew (with variable ages, weights and genders), biomass production (with scalable plantings of ten different crops), water recovery, air revitalization, food processing, solid waste recycling and energy production. Each component is modeled as a producer of certain resources and a consumer of certain resources. The control system must monitor (via sensors) and control (via actuators) the flow of resources throughout the system to provide life support functionality. The simulation is written in an object-oriented paradigm that makes it portable, extensible and reconfigurable.

Introducing stochastics into the simulation of convective precipitation events

NASA Astrophysics Data System (ADS)

Pistotnik, Georg

2010-05-01

In a joint project, the Central Institute for Meteorology and Geodynamics (ZAMG) and the Vienna University of Technology aimed to characterize strong precipitation events and their impact in the Bucklige Welt region in Eastern Austria. Both the region's hydrological and meteorological characteristics, namely its composition of virtually countless small catchments with short response times and a high frequency of summertime convective storms, cause the occurrence of flooding to be strictly tied to convective rainfall events, which is why this study has been focused on this type of precipitation. The meteorological database consists of the ZAMG's high-resolution analysis and nowcasting system INCA ("Integrated Nowcasting through Comprehensive Analysis"), which provides a set of precipitation analyses generated by a statistically optimized combination of rain gauge measurements and radar data with a temporal resolution of 15 minutes and a spatial resolution of 1 kilometre. An intensity threshold of 3.8mm/15min has been used to classify any observed precipitation as a convective one, thus extracting 245 convection days with a total number of almost 1600 individual storm events over the project region out of the 5-year data set from 2003 to 2007. Consecutive analyses were used to compute the motion of these storms, a complex process that could not be completely automatized; due to the repeated occurrence of storm splits or coalescences, a manual control of the automatically provided "suggestion" of movement had to be performed in order to merge two or more precipitation maxima to a single storm if necessary, thus yielding the smoothest and most plausible storm tracks and ensuring a high quality of the database. In the first part of the project, distributions for all characteristic parameters have been derived, including the number of storms per day, their place and time of initiation, their motion, lifetime, maximum intensity and maximum "cell volume" (i.e. overall

Towards a Self-Consistent Simulation Capability of Catastrophic Solar Energetic Particle Events

NASA Astrophysics Data System (ADS)

Sokolov, I.; Gombosi, T. I.; Bindi, V.; Borovikov, D.; Kota, J.; Giacalone, J.

2016-12-01

Space weather refers to variations in the space environment that can affect technologies or endanger human life and health. Solar energetic particle (SEP) events can affect communications and airline safety. Satellites are affected by radiation damage to electronics and to components that produce power and provide images. Sun and star sensors are blinded during large SEP events. Protons of ≳30 MeV penetrate spacesuits and spacecraft walls. Events, like that of August 4, 1972, would have been fatal to moon-walking astronauts. Catastrophic events typically are characterized by hard particle energy spectra potentially containing large fluxes of hundreds of MeV-GeV type particles. These super-energetic particles can penetrate even into the "safest" areas of spacecraft and produce induced radioactivity. We describe several technologies which are to be combined into a physics-based, self consistent model to understand and forecast the origin and evolution of SEP events: The Alfvén Wave Solar-wind Model (AWSoM) simulates the chromosphere-to-Earth system using separate electron and ion temperatures and separate parallel and perpendicular temperatures. It solves the energy equations including thermal conduction and coronal heating by Alfvén wave turbulence. It uses adaptive mesh refinement (AMR), which allows us to cover a broad range of spacial scales. The Eruptive Event Generator using the Gibson-Low flux-rope model (EEGGL) allows the user to select an active region on the sun, select the polarity inversion line where the eruption is observed, and insert a Gibson-Low flux-rope to produce eruption. The Multiple-Field-Lines-Advection Model for Particle Acceleration (M-FLAMPA) solves the particle transport equation along a multitude of interplanetary magnetic field lines originating from the Sun, using time-dependent parameters for the shock and magnetic field obtained from the MHD simulation. It includes a self-consistent coupling of Alfvén wave turbulence to the SEPs

Computer Simulation as an Aid for Management of an Information System.

ERIC Educational Resources Information Center

Simmonds, W. H.; And Others

The aim of this study was to develop methods, based upon computer simulation, of designing information systems and illustrate the use of these methods by application to an information service. The method developed is based upon Monte Carlo and discrete event simulation techniques and is described in an earlier report - Sira report R412 Organizing…

Event-triggered consensus tracking of multi-agent systems with Lur'e nonlinear dynamics

NASA Astrophysics Data System (ADS)

Huang, Na; Duan, Zhisheng; Wen, Guanghui; Zhao, Yu

2016-05-01

In this paper, distributed consensus tracking problem for networked Lur'e systems is investigated based on event-triggered information interactions. An event-triggered control algorithm is designed with the advantages of reducing controller update frequency and sensor energy consumption. By using tools of ?-procedure and Lyapunov functional method, some sufficient conditions are derived to guarantee that consensus tracking is achieved under a directed communication topology. Meanwhile, it is shown that Zeno behaviour of triggering time sequences is excluded for the proposed event-triggered rule. Finally, some numerical simulations on coupled Chua's circuits are performed to illustrate the effectiveness of the theoretical algorithms.

Workshop on data acquisition and trigger system simulations for high energy physics

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

NONE

1992-12-31

This report discusses the following topics: DAQSIM: A data acquisition system simulation tool; Front end and DCC Simulations for the SDC Straw Tube System; Simulation of Non-Blocklng Data Acquisition Architectures; Simulation Studies of the SDC Data Collection Chip; Correlation Studies of the Data Collection Circuit & The Design of a Queue for this Circuit; Fast Data Compression & Transmission from a Silicon Strip Wafer; Simulation of SCI Protocols in Modsim; Visual Design with vVHDL; Stochastic Simulation of Asynchronous Buffers; SDC Trigger Simulations; Trigger Rates, DAQ & Online Processing at the SSC; Planned Enhancements to MODSEM II & SIMOBJECT -- anmore » Overview -- R.; DAGAR -- A synthesis system; Proposed Silicon Compiler for Physics Applications; Timed -- LOTOS in a PROLOG Environment: an Algebraic language for Simulation; Modeling and Simulation of an Event Builder for High Energy Physics Data Acquisition Systems; A Verilog Simulation for the CDF DAQ; Simulation to Design with Verilog; The DZero Data Acquisition System: Model and Measurements; DZero Trigger Level 1.5 Modeling; Strategies Optimizing Data Load in the DZero Triggers; Simulation of the DZero Level 2 Data Acquisition System; A Fast Method for Calculating DZero Level 1 Jet Trigger Properties and Physics Input to DAQ Studies.« less

Dermatopathology effects of simulated solar particle event radiation exposure in the porcine model.

PubMed

Sanzari, Jenine K; Diffenderfer, Eric S; Hagan, Sarah; Billings, Paul C; Gridley, Daila S; Seykora, John T; Kennedy, Ann R; Cengel, Keith A

2015-07-01

The space environment exposes astronauts to risks of acute and chronic exposure to ionizing radiation. Of particular concern is possible exposure to ionizing radiation from a solar particle event (SPE). During an SPE, magnetic disturbances in specific regions of the Sun result in the release of intense bursts of ionizing radiation, primarily consisting of protons that have a highly variable energy spectrum. Thus, SPE events can lead to significant total body radiation exposures to astronauts in space vehicles and especially while performing extravehicular activities. Simulated energy profiles suggest that SPE radiation exposures are likely to be highest in the skin. In the current report, we have used our established miniature pig model system to evaluate the skin toxicity of simulated SPE radiation exposures that closely resemble the energy and fluence profile of the September, 1989 SPE using either conventional radiation (electrons) or proton simulated SPE radiation. Exposure of animals to electron or proton radiation led to dose-dependent increases in epidermal pigmentation, the presence of necrotic keratinocytes at the dermal-epidermal boundary and pigment incontinence, manifested by the presence of melanophages in the derm is upon histological examination. We also observed epidermal hyperplasia and a reduction in vascular density at 30 days following exposure to electron or proton simulated SPE radiation. These results suggest that the doses of electron or proton simulated SPE radiation results in significant skin toxicity that is quantitatively and qualitatively similar. Radiation-induced skin damage is often one of the first clinical signs of both acute and non-acute radiation injury where infection may occur, if not treated. In this report, histopathology analyses of acute radiation-induced skin injury are discussed. Copyright © 2015 The Committee on Space Research (COSPAR). Published by Elsevier Ltd. All rights reserved.

A variational approach to probing extreme events in turbulent dynamical systems

PubMed Central

Farazmand, Mohammad; Sapsis, Themistoklis P.

2017-01-01

Extreme events are ubiquitous in a wide range of dynamical systems, including turbulent fluid flows, nonlinear waves, large-scale networks, and biological systems. We propose a variational framework for probing conditions that trigger intermittent extreme events in high-dimensional nonlinear dynamical systems. We seek the triggers as the probabilistically feasible solutions of an appropriately constrained optimization problem, where the function to be maximized is a system observable exhibiting intermittent extreme bursts. The constraints are imposed to ensure the physical admissibility of the optimal solutions, that is, significant probability for their occurrence under the natural flow of the dynamical system. We apply the method to a body-forced incompressible Navier-Stokes equation, known as the Kolmogorov flow. We find that the intermittent bursts of the energy dissipation are independent of the external forcing and are instead caused by the spontaneous transfer of energy from large scales to the mean flow via nonlinear triad interactions. The global maximizer of the corresponding variational problem identifies the responsible triad, hence providing a precursor for the occurrence of extreme dissipation events. Specifically, monitoring the energy transfers within this triad allows us to develop a data-driven short-term predictor for the intermittent bursts of energy dissipation. We assess the performance of this predictor through direct numerical simulations. PMID:28948226

Developing Flexible Discrete Event Simulation Models in an Uncertain Policy Environment

NASA Technical Reports Server (NTRS)

Miranda, David J.; Fayez, Sam; Steele, Martin J.

2011-01-01

On February 1st, 2010 U.S. President Barack Obama submitted to Congress his proposed budget request for Fiscal Year 2011. This budget included significant changes to the National Aeronautics and Space Administration (NASA), including the proposed cancellation of the Constellation Program. This change proved to be controversial and Congressional approval of the program's official cancellation would take many months to complete. During this same period an end-to-end discrete event simulation (DES) model of Constellation operations was being built through the joint efforts of Productivity Apex Inc. (PAl) and Science Applications International Corporation (SAIC) teams under the guidance of NASA. The uncertainty in regards to the Constellation program presented a major challenge to the DES team, as to: continue the development of this program-of-record simulation, while at the same time remain prepared for possible changes to the program. This required the team to rethink how it would develop it's model and make it flexible enough to support possible future vehicles while at the same time be specific enough to support the program-of-record. This challenge was compounded by the fact that this model was being developed through the traditional DES process-orientation which lacked the flexibility of object-oriented approaches. The team met this challenge through significant pre-planning that led to the "modularization" of the model's structure by identifying what was generic, finding natural logic break points, and the standardization of interlogic numbering system. The outcome of this work resulted in a model that not only was ready to be easily modified to support any future rocket programs, but also a model that was extremely structured and organized in a way that facilitated rapid verification. This paper discusses in detail the process the team followed to build this model and the many advantages this method provides builders of traditional process-oriented discrete

A hadron-nucleus collision event generator for simulations at intermediate energies

NASA Astrophysics Data System (ADS)

Ackerstaff, K.; Bisplinghoff, J.; Bollmann, R.; Cloth, P.; Diehl, O.; Dohrmann, F.; Drüke, V.; Eisenhardt, S.; Engelhardt, H. P.; Ernst, J.; Eversheim, P. D.; Filges, D.; Fritz, S.; Gasthuber, M.; Gebel, R.; Greiff, J.; Gross, A.; Gross-Hardt, R.; Hinterberger, F.; Jahn, R.; Lahr, U.; Langkau, R.; Lippert, G.; Maschuw, R.; Mayer-Kuckuk, T.; Mertler, G.; Metsch, B.; Mosel, F.; Paetz gen. Schieck, H.; Petry, H. R.; Prasuhn, D.; von Przewoski, B.; Rohdjeß, H.; Rosendaal, D.; Roß, U.; von Rossen, P.; Scheid, H.; Schirm, N.; Schulz-Rojahn, M.; Schwandt, F.; Scobel, W.; Sterzenbach, G.; Theis, D.; Weber, J.; Wellinghausen, A.; Wiedmann, W.; Woller, K.; Ziegler, R.; EDDA-Collaboration

2002-10-01

Several available codes for hadronic event generation and shower simulation are discussed and their predictions are compared to experimental data in order to obtain a satisfactory description of hadronic processes in Monte Carlo studies of detector systems for medium energy experiments. The most reasonable description is found for the intra-nuclear-cascade (INC) model of Bertini which employs microscopic description of the INC, taking into account elastic and inelastic pion-nucleon and nucleon-nucleon scattering. The isobar model of Sternheimer and Lindenbaum is used to simulate the inelastic elementary collisions inside the nucleus via formation and decay of the Δ33-resonance which, however, limits the model at higher energies. To overcome this limitation, the INC model has been extended by using the resonance model of the HADRIN code, considering all resonances in elementary collisions contributing more than 2% to the total cross-section up to kinetic energies of 5 GeV. In addition, angular distributions based on phase shift analysis are used for elastic nucleon-nucleon as well as elastic and charge exchange pion-nucleon scattering. Also kaons and antinucleons can be treated as projectiles. Good agreement with experimental data is found predominantly for lower projectile energies, i.e. in the regime of the Bertini code. The original as well as the extended Bertini model have been implemented as shower codes into the high energy detector simulation package GEANT-3.14, allowing now its use also in full Monte Carlo studies of detector systems at intermediate energies. The GEANT-3.14 here have been used mainly for its powerful geometry and analysing packages due to the complex EDDA detector system.

Simulations of Sea Level Rise Effects on Complex Coastal Systems

NASA Astrophysics Data System (ADS)

Niedoroda, A. W.; Ye, M.; Saha, B.; Donoghue, J. F.; Reed, C. W.

2009-12-01

It is now established that complex coastal systems with elements such as beaches, inlets, bays, and rivers adjust their morphologies according to time-varying balances in between the processes that control the exchange of sediment. Accelerated sea level rise introduces a major perturbation into the sediment-sharing systems. A modeling framework based on a new SL-PR model which is an advanced version of the aggregate-scale CST Model and the event-scale CMS-2D and CMS-Wave combination have been used to simulate the recent evolution of a portion of the Florida panhandle coast. This combination of models provides a method to evaluate coefficients in the aggregate-scale model that were previously treated as fitted parameters. That is, by carrying out simulations of a complex coastal system with runs of the event-scale model representing more than a year it is now possible to directly relate the coefficients in the large-scale SL-PR model to measureable physical parameters in the current and wave fields. This cross-scale modeling procedure has been used to simulate the shoreline evolution at the Santa Rosa Island, a long barrier which houses significant military infrastructure at the north Gulf Coast. The model has been used to simulate 137 years of measured shoreline change and to extend these to predictions of future rates of shoreline migration.

Using Simulation to Improve Systems-Based Practices.

PubMed

Gardner, Aimee K; Johnston, Maximilian; Korndorffer, James R; Haque, Imad; Paige, John T

2017-09-01

Ensuring the safe, effective management of patients requires efficient processes of care within a smoothly operating system in which highly reliable teams of talented, skilled health care providers are able to use the vast array of high-technology resources and intensive care techniques available. Simulation can play a unique role in exploring and improving the complex perioperative system by proactively identifying latent safety threats and mitigating their damage to ensure that all those who work in this critical health care environment can provide optimal levels of patient care. A panel of five experts from a wide range of institutions was brought together to discuss the added value of simulation-based training for improving systems-based aspects of the perioperative service line. Panelists shared the way in which simulation was demonstrated at their institutions. The themes discussed by each panel member were delineated into four avenues through which simulation-based techniques have been used. Simulation-based techniques are being used in (1) testing new clinical workspaces and facilities before they open to identify potential latent conditions; (2) practicing how to identify the deteriorating patient and escalate care in an effective manner; (3) performing prospective root cause analyses to address system weaknesses leading to sentinel events; and (4) evaluating the efficiency and effectiveness of the electronic health record in the perioperative setting. This focused review of simulation-based interventions to test and improve components of the perioperative microsystem, which includes literature that has emerged since the panel's presentation, highlights the broad-based utility of simulation-based technologies in health care. Copyright © 2017 The Joint Commission. Published by Elsevier Inc. All rights reserved.

Event-triggered decentralized adaptive fault-tolerant control of uncertain interconnected nonlinear systems with actuator failures.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2018-06-01

This paper investigates the event-triggered decentralized adaptive tracking problem of a class of uncertain interconnected nonlinear systems with unexpected actuator failures. It is assumed that local control signals are transmitted to local actuators with time-varying faults whenever predefined conditions for triggering events are satisfied. Compared with the existing control-input-based event-triggering strategy for adaptive control of uncertain nonlinear systems, the aim of this paper is to propose a tracking-error-based event-triggering strategy in the decentralized adaptive fault-tolerant tracking framework. The proposed approach can relax drastic changes in control inputs caused by actuator faults in the existing triggering strategy. The stability of the proposed event-triggering control system is analyzed in the Lyapunov sense. Finally, simulation comparisons of the proposed and existing approaches are provided to show the effectiveness of the proposed theoretical result in the presence of actuator faults. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Simulation Of A Photofission-Based Cargo Interrogation System

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

King, Michael; Gozani, Tsahi; Stevenson, John

A comprehensive model has been developed to characterize and optimize the detection of Bremsstrahlung x-ray induced fission signatures from nuclear materials hidden in cargo containers. An effective active interrogation system should not only induce a large number of fission events but also efficiently detect their signatures. The proposed scanning system utilizes a 9-MV commercially available linear accelerator and the detection of strong fission signals i.e. delayed gamma rays and prompt neutrons. Because the scanning system is complex and the cargo containers are large and often highly attenuating, the simulation method segments the model into several physical steps, representing each changemore » of radiation particle. Each approximation is carried-out separately, resulting in a major reduction in computational time and a significant improvement in tally statistics. The model investigates the effect on the fission rate and detection rate by various cargo types, densities and distributions. Hydrogenous and metallic cargos, homogeneous and heterogeneous, as well as various locations of the nuclear material inside the cargo container were studied. We will show that for the photofission-based interrogation system simulation, the final results are not only in good agreement with a full, single-step simulation but also with experimental results, further validating the full-system simulation.« less

Discrete-event simulation of a wide-area health care network.

PubMed Central

McDaniel, J G

1995-01-01

OBJECTIVE: Predict the behavior and estimate the telecommunication cost of a wide-area message store-and-forward network for health care providers that uses the telephone system. DESIGN: A tool with which to perform large-scale discrete-event simulations was developed. Network models for star and mesh topologies were constructed to analyze the differences in performances and telecommunication costs. The distribution of nodes in the network models approximates the distribution of physicians, hospitals, medical labs, and insurers in the Province of Saskatchewan, Canada. Modeling parameters were based on measurements taken from a prototype telephone network and a survey conducted at two medical clinics. Simulation studies were conducted for both topologies. RESULTS: For either topology, the telecommunication cost of a network in Saskatchewan is projected to be less than $100 (Canadian) per month per node. The estimated telecommunication cost of the star topology is approximately half that of the mesh. Simulations predict that a mean end-to-end message delivery time of two hours or less is achievable at this cost. A doubling of the data volume results in an increase of less than 50% in the mean end-to-end message transfer time. CONCLUSION: The simulation models provided an estimate of network performance and telecommunication cost in a specific Canadian province. At the expected operating point, network performance appeared to be relatively insensitive to increases in data volume. Similar results might be anticipated in other rural states and provinces in North America where a telephone-based network is desired. PMID:7583646

Analysis of extreme rain and flood events using a regional hydrologically enhanced hydrometeorological system

NASA Astrophysics Data System (ADS)

Yucel, Ismail; Onen, Alper

2013-04-01

Evidence is showing that global warming or climate change has a direct influence on changes in precipitation and the hydrological cycle. Extreme weather events such as heavy rainfall and flooding are projected to become much more frequent as climate warms. Regional hydrometeorological system model which couples the atmosphere with physical and gridded based surface hydrology provide efficient predictions for extreme hydrological events. This modeling system can be used for flood forecasting and warning issues as they provide continuous monitoring of precipitation over large areas at high spatial resolution. This study examines the performance of the Weather Research and Forecasting (WRF-Hydro) model that performs the terrain, sub-terrain, and channel routing in producing streamflow from WRF-derived forcing of extreme precipitation events. The capability of the system with different options such as data assimilation is tested for number of flood events observed in basins of western Black Sea Region in Turkey. Rainfall event structures and associated flood responses are evaluated with gauge and satellite-derived precipitation and measured streamflow values. The modeling system shows skills in capturing the spatial and temporal structure of extreme rainfall events and resulted flood hydrographs. High-resolution routing modules activated in the model enhance the simulated discharges.

A Spiking Neural Simulator Integrating Event-Driven and Time-Driven Computation Schemes Using Parallel CPU-GPU Co-Processing: A Case Study.

PubMed

Naveros, Francisco; Luque, Niceto R; Garrido, Jesús A; Carrillo, Richard R; Anguita, Mancia; Ros, Eduardo

2015-07-01

Time-driven simulation methods in traditional CPU architectures perform well and precisely when simulating small-scale spiking neural networks. Nevertheless, they still have drawbacks when simulating large-scale systems. Conversely, event-driven simulation methods in CPUs and time-driven simulation methods in graphic processing units (GPUs) can outperform CPU time-driven methods under certain conditions. With this performance improvement in mind, we have developed an event-and-time-driven spiking neural network simulator suitable for a hybrid CPU-GPU platform. Our neural simulator is able to efficiently simulate bio-inspired spiking neural networks consisting of different neural models, which can be distributed heterogeneously in both small layers and large layers or subsystems. For the sake of efficiency, the low-activity parts of the neural network can be simulated in CPU using event-driven methods while the high-activity subsystems can be simulated in either CPU (a few neurons) or GPU (thousands or millions of neurons) using time-driven methods. In this brief, we have undertaken a comparative study of these different simulation methods. For benchmarking the different simulation methods and platforms, we have used a cerebellar-inspired neural-network model consisting of a very dense granular layer and a Purkinje layer with a smaller number of cells (according to biological ratios). Thus, this cerebellar-like network includes a dense diverging neural layer (increasing the dimensionality of its internal representation and sparse coding) and a converging neural layer (integration) similar to many other biologically inspired and also artificial neural networks.

Prototype software model for designing intruder detection systems with simulation

NASA Astrophysics Data System (ADS)

Smith, Jeffrey S.; Peters, Brett A.; Curry, James C.; Gupta, Dinesh

1998-08-01

This article explores using discrete-event simulation for the design and control of defence oriented fixed-sensor- based detection system in a facility housing items of significant interest to enemy forces. The key issues discussed include software development, simulation-based optimization within a modeling framework, and the expansion of the framework to create real-time control tools and training simulations. The software discussed in this article is a flexible simulation environment where the data for the simulation are stored in an external database and the simulation logic is being implemented using a commercial simulation package. The simulation assesses the overall security level of a building against various intruder scenarios. A series of simulation runs with different inputs can determine the change in security level with changes in the sensor configuration, building layout, and intruder/guard strategies. In addition, the simulation model developed for the design stage of the project can be modified to produce a control tool for the testing, training, and real-time control of systems with humans and sensor hardware in the loop.

World, We Have Problems: Simulation for Large Complex, Risky Projects, and Events

NASA Technical Reports Server (NTRS)

Elfrey, Priscilla

2010-01-01

Prior to a spacewalk during the NASA STS/129 mission in November 2009, Columbia Broadcasting System (CBS) correspondent William Harwood reported astronauts, "were awakened again", as they had been the day previously. Fearing something not properly connected was causing a leak, the crew, both on the ground and in space, stopped and checked everything. The alarm proved false. The crew did complete its work ahead of schedule, but the incident reminds us that correctly connecting hundreds and thousands of entities, subsystems and systems, finding leaks, loosening stuck valves, and adding replacements to very large complex systems over time does not occur magically. Everywhere major projects present similar pressures. Lives are at - risk. Responsibility is heavy. Large natural and human-created disasters introduce parallel difficulties as people work across boundaries their countries, disciplines, languages, and cultures with known immediate dangers as well as the unexpected. NASA has long accepted that when humans have to go where humans cannot go that simulation is the sole solution. The Agency uses simulation to achieve consensus, reduce ambiguity and uncertainty, understand problems, make decisions, support design, do planning and troubleshooting, as well as for operations, training, testing, and evaluation. Simulation is at the heart of all such complex systems, products, projects, programs, and events. Difficult, hazardous short and, especially, long-term activities have a persistent need for simulation from the first insight into a possibly workable idea or answer until the final report perhaps beyond our lifetime is put in the archive. With simulation we create a common mental model, try-out breakdowns of machinery or teamwork, and find opportunity for improvement. Lifecycle simulation proves to be increasingly important as risks and consequences intensify. Across the world, disasters are increasing. We anticipate more of them, as the results of global warming

Can discrete event simulation be of use in modelling major depression?

PubMed

Le Lay, Agathe; Despiegel, Nicolas; François, Clément; Duru, Gérard

2006-12-05

Depression is among the major contributors to worldwide disease burden and adequate modelling requires a framework designed to depict real world disease progression as well as its economic implications as closely as possible. In light of the specific characteristics associated with depression (multiple episodes at varying intervals, impact of disease history on course of illness, sociodemographic factors), our aim was to clarify to what extent "Discrete Event Simulation" (DES) models provide methodological benefits in depicting disease evolution. We conducted a comprehensive review of published Markov models in depression and identified potential limits to their methodology. A model based on DES principles was developed to investigate the benefits and drawbacks of this simulation method compared with Markov modelling techniques. The major drawback to Markov models is that they may not be suitable to tracking patients' disease history properly, unless the analyst defines multiple health states, which may lead to intractable situations. They are also too rigid to take into consideration multiple patient-specific sociodemographic characteristics in a single model. To do so would also require defining multiple health states which would render the analysis entirely too complex. We show that DES resolve these weaknesses and that its flexibility allow patients with differing attributes to move from one event to another in sequential order while simultaneously taking into account important risk factors such as age, gender, disease history and patients attitude towards treatment, together with any disease-related events (adverse events, suicide attempt etc.). DES modelling appears to be an accurate, flexible and comprehensive means of depicting disease progression compared with conventional simulation methodologies. Its use in analysing recurrent and chronic diseases appears particularly useful compared with Markov processes.

The attributes of medical event-reporting systems: experience with a prototype medical event-reporting system for transfusion medicine.

PubMed

Battles, J B; Kaplan, H S; Van der Schaaf, T W; Shea, C E

1998-03-01

To design, develop, and implement a prototype medical event-reporting system for use in transfusion medicine to improve transfusion safety by studying incidents and errors. The IDEALS concept of design was used to identify specifications for the event-reporting system, and a Delphi and subsequent nominal group technique meetings were used to reach consensus on the development of the system. An interdisciplinary panel of experts from aviation safety, nuclear power, cognitive psychology, artificial intelligence, and education and representatives of major transfusion medicine organizations participated in the development process. Setting.- Three blood centers and three hospital transfusion services implemented the reporting system. A working prototype event-reporting system was recommended and implemented. The system has seven components: detection, selection, description, classification, computation, interpretation, and local evaluation. Its unique features include no-fault reporting initiated by the individual discovering the event, who submits a report that is investigated by local quality assurance personnel and forwarded to a nonregulatory central system for computation and interpretation. An event-reporting system incorporated into present quality assurance and risk management efforts can help organizations address system structural and procedural weakness where the potential for errors can adversely affect health care outcomes. Input from the end users of the system as well as from external experts should enable this reporting system to serve as a useful model for others who may develop event-reporting systems in other medical domains.

Improving outpatient phlebotomy service efficiency and patient experience using discrete-event simulation.

PubMed

Yip, Kenneth; Pang, Suk-King; Chan, Kui-Tim; Chan, Chi-Kuen; Lee, Tsz-Leung

2016-08-08

Purpose - The purpose of this paper is to present a simulation modeling application to reconfigure the outpatient phlebotomy service of an acute regional and teaching hospital in Hong Kong, with an aim to improve service efficiency, shorten patient queuing time and enhance workforce utilization. Design/methodology/approach - The system was modeled as an inhomogeneous Poisson process and a discrete-event simulation model was developed to simulate the current setting, and to evaluate how various performance metrics would change if switched from a decentralized to a centralized model. Variations were then made to the model to test different workforce arrangements for the centralized service, so that managers could decide on the service's final configuration via an evidence-based and data-driven approach. Findings - This paper provides empirical insights about the relationship between staffing arrangement and system performance via a detailed scenario analysis. One particular staffing scenario was chosen by manages as it was considered to strike the best balance between performance and workforce scheduled. The resulting centralized phlebotomy service was successfully commissioned. Practical implications - This paper demonstrates how analytics could be used for operational planning at the hospital level. The authors show that a transparent and evidence-based scenario analysis, made available through analytics and simulation, greatly facilitates management and clinical stakeholders to arrive at the ideal service configuration. Originality/value - The authors provide a robust method in evaluating the relationship between workforce investment, queuing reduction and workforce utilization, which is crucial for managers when deciding the delivery model for any outpatient-related service.

Using soft systems methodology to develop a simulation of out-patient services.

PubMed

Lehaney, B; Paul, R J

1994-10-01

Discrete event simulation is an approach to modelling a system in the form of a set of mathematical equations and logical relationships, usually used for complex problems, which are difficult to address by using analytical or numerical methods. Managing out-patient services is such a problem. However, simulation is not in itself a systemic approach, in that it provides no methodology by which system boundaries and system activities may be identified. The investigation considers the use of soft systems methodology as an aid to drawing system boundaries and identifying system activities, for the purpose of simulating the outpatients' department at a local hospital. The long term aims are to examine the effects that the participative nature of soft systems methodology has on the acceptability of the simulation model, and to provide analysts and managers with a process that may assist in planning strategies for health care.

Discrete-Event Simulation Unmasks the Quantum Cheshire Cat

NASA Astrophysics Data System (ADS)

Michielsen, Kristel; Lippert, Thomas; Raedt, Hans De

2017-05-01

It is shown that discrete-event simulation accurately reproduces the experimental data of a single-neutron interferometry experiment [T. Denkmayr {\\sl et al.}, Nat. Commun. 5, 4492 (2014)] and provides a logically consistent, paradox-free, cause-and-effect explanation of the quantum Cheshire cat effect without invoking the notion that the neutron and its magnetic moment separate. Describing the experimental neutron data using weak-measurement theory is shown to be useless for unravelling the quantum Cheshire cat effect.

A community-based event delivery protocol in publish/subscribe systems for delay tolerant sensor networks.

PubMed

Liu, Nianbo; Liu, Ming; Zhu, Jinqi; Gong, Haigang

2009-01-01

The basic operation of a Delay Tolerant Sensor Network (DTSN) is to finish pervasive data gathering in networks with intermittent connectivity, while the publish/subscribe (Pub/Sub for short) paradigm is used to deliver events from a source to interested clients in an asynchronous way. Recently, extension of Pub/Sub systems in DTSNs has become a promising research topic. However, due to the unique frequent partitioning characteristic of DTSNs, extension of a Pub/Sub system in a DTSN is a considerably difficult and challenging problem, and there are no good solutions to this problem in published works. To ad apt Pub/Sub systems to DTSNs, we propose CED, a community-based event delivery protocol. In our design, event delivery is based on several unchanged communities, which are formed by sensor nodes in the network according to their connectivity. CED consists of two components: event delivery and queue management. In event delivery, events in a community are delivered to mobile subscribers once a subscriber comes into the community, for improving the data delivery ratio. The queue management employs both the event successful delivery time and the event survival time to decide whether an event should be delivered or dropped for minimizing the transmission overhead. The effectiveness of CED is demonstrated through comprehensive simulation studies.

Non-fragile ?-? control for discrete-time stochastic nonlinear systems under event-triggered protocols

NASA Astrophysics Data System (ADS)

Sun, Ying; Ding, Derui; Zhang, Sunjie; Wei, Guoliang; Liu, Hongjian

2018-07-01

In this paper, the non-fragile ?-? control problem is investigated for a class of discrete-time stochastic nonlinear systems under event-triggered communication protocols, which determine whether the measurement output should be transmitted to the controller or not. The main purpose of the addressed problem is to design an event-based output feedback controller subject to gain variations guaranteeing the prescribed disturbance attenuation level described by the ?-? performance index. By utilizing the Lyapunov stability theory combined with S-procedure, a sufficient condition is established to guarantee both the exponential mean-square stability and the ?-? performance for the closed-loop system. In addition, with the help of the orthogonal decomposition, the desired controller parameter is obtained in terms of the solution to certain linear matrix inequalities. Finally, a simulation example is exploited to demonstrate the effectiveness of the proposed event-based controller design scheme.

Simulation of the last sapropel event using high-regional oceanic model

NASA Astrophysics Data System (ADS)

Vadsaria, Tristan; Ramstein, Gilles; Li, Laurent; Dutay, jean-Claude

2017-04-01

Since decades, the simulation of sapropel events remains a challenge. These events, occurring periodically in the Mediterranean Sea produce a strong stratification of the water column and break intermediate and deep convection, thereby leading to a decrease in deep water oxygen, of which evidence are recorded in marine sediment cores. Data from Mediterranean sediments have thus helped to better understand the anoxia process, in particular for the last sapropel event, S1, lasting 3000 years about 10 kyrs ago. However the causal link between insolation changes and the African monsoon variations - thought to be the trigger of sapropel events -, and anoxia has still to be quantified. From a modelling point of view, a requisite for studying sapropel events is to capture seasonal winds that are instrumental in producing convection in the Med Sea. Recently, the development of high-resolution several models studies intend to fill this gap, building different scenarios (Grimm et al, 2015). Combining an atmospheric GCM (LMDZ4) and a high-resolution oceanic model (NEMOMED8, resolution of 1/8 degree) dedicated to the Med Sea, our first objective is to test whether monsoon precipitation triggered by insolation changes can increase the Nile run-off enough to stratify the East Mediterranean Sea. We notably show that a 15 mSv Nile runoff increase triggers a large decrease of convection in the whole Eastern Mediterranean Sea associated with strong anoxia in bottom waters.. Comparisons of our first experiments with δ18O and ɛ-Nd data will also be presented. Future work includes extending our simulations to investigate whether sapropel events can be maintained on longer time scales.

Argonne simulation framework for intelligent transportation systems

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

Ewing, T.; Doss, E.; Hanebutte, U.

1996-04-01

A simulation framework has been developed which defines a high-level architecture for a large-scale, comprehensive, scalable simulation of an Intelligent Transportation System (ITS). The simulator is designed to run on parallel computers and distributed (networked) computer systems; however, a version for a stand alone workstation is also available. The ITS simulator includes an Expert Driver Model (EDM) of instrumented ``smart`` vehicles with in-vehicle navigation units. The EDM is capable of performing optimal route planning and communicating with Traffic Management Centers (TMC). A dynamic road map data base is sued for optimum route planning, where the data is updated periodically tomore » reflect any changes in road or weather conditions. The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide 2-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphical user interfaces that includes human-factors studies to support safety and operational research. Realistic modeling of variations of the posted driving speed are based on human factor studies that take into consideration weather, road conditions, driver`s personality and behavior and vehicle type. The simulator has been developed on a distributed system of networked UNIX computers, but is designed to run on ANL`s IBM SP-X parallel computer system for large scale problems. A novel feature of the developed simulator is that vehicles will be represented by autonomous computer processes, each with a behavior model which performs independent route selection and reacts to external traffic events much like real vehicles. Vehicle processes interact with each other and with ITS components by exchanging messages. With this approach, one will be able to take advantage of emerging massively parallel processor (MPP) systems.« less

Using Wavelet Analysis To Assist in Identification of Significant Events in Molecular Dynamics Simulations.

PubMed

Heidari, Zahra; Roe, Daniel R; Galindo-Murillo, Rodrigo; Ghasemi, Jahan B; Cheatham, Thomas E

2016-07-25

Long time scale molecular dynamics (MD) simulations of biological systems are becoming increasingly commonplace due to the availability of both large-scale computational resources and significant advances in the underlying simulation methodologies. Therefore, it is useful to investigate and develop data mining and analysis techniques to quickly and efficiently extract the biologically relevant information from the incredible amount of generated data. Wavelet analysis (WA) is a technique that can quickly reveal significant motions during an MD simulation. Here, the application of WA on well-converged long time scale (tens of μs) simulations of a DNA helix is described. We show how WA combined with a simple clustering method can be used to identify both the physical and temporal locations of events with significant motion in MD trajectories. We also show that WA can not only distinguish and quantify the locations and time scales of significant motions, but by changing the maximum time scale of WA a more complete characterization of these motions can be obtained. This allows motions of different time scales to be identified or ignored as desired.

Quantitative Simulation of QARBM Challenge Events During Radiation Belt Enhancements

NASA Astrophysics Data System (ADS)

Li, W.; Ma, Q.; Thorne, R. M.; Bortnik, J.; Chu, X.

2017-12-01

Various physical processes are known to affect energetic electron dynamics in the Earth's radiation belts, but their quantitative effects at different times and locations in space need further investigation. This presentation focuses on discussing the quantitative roles of various physical processes that affect Earth's radiation belt electron dynamics during radiation belt enhancement challenge events (storm-time vs. non-storm-time) selected by the GEM Quantitative Assessment of Radiation Belt Modeling (QARBM) focus group. We construct realistic global distributions of whistler-mode chorus waves, adopt various versions of radial diffusion models (statistical and event-specific), and use the global evolution of other potentially important plasma waves including plasmaspheric hiss, magnetosonic waves, and electromagnetic ion cyclotron waves from all available multi-satellite measurements. These state-of-the-art wave properties and distributions on a global scale are used to calculate diffusion coefficients, that are then adopted as inputs to simulate the dynamical electron evolution using a 3D diffusion simulation during the storm-time and the non-storm-time acceleration events respectively. We explore the similarities and differences in the dominant physical processes that cause radiation belt electron dynamics during the storm-time and non-storm-time acceleration events. The quantitative role of each physical process is determined by comparing against the Van Allen Probes electron observations at different energies, pitch angles, and L-MLT regions. This quantitative comparison further indicates instances when quasilinear theory is sufficient to explain the observed electron dynamics or when nonlinear interaction is required to reproduce the energetic electron evolution observed by the Van Allen Probes.

Widespread, Very Heavy Precipitation Events in Contemporary and Scenario Summer Climates from NARCCAP Simulations

NASA Astrophysics Data System (ADS)

Kawazoe, S.; Gutowski, W. J., Jr.

2015-12-01

We analyze the ability of regional climate models (RCMs) to simulate very heavy daily precipitation and supporting processes for both contemporary and future-scenario simulations during summer (JJA). RCM output comes from North American Regional Climate Change Assessment Program (NARCCAP) simulations, which are all run at a spatial resolution of 50 km. Analysis focuses on the upper Mississippi basin for summer, between 1982-1998 for the contemporary climate, and 2052-2068 during the scenario climate. We also compare simulated precipitation and supporting processes with those obtained from observed precipitation and reanalysis atmospheric states. Precipitation observations are from the University of Washington (UW) and the Climate Prediction Center (CPC) gridded dataset. Utilizing two observational datasets helps determine if any uncertainties arise from differences in precipitation gridding schemes. Reanalysis fields come from the North American Regional Reanalysis. The NARCCAP models generally reproduce well the precipitation-vs.-intensity spectrum seen in observations, while producing overly strong precipitation at high intensity thresholds. In the future-scenario climate, there is a decrease in frequency for light to moderate precipitation intensities, while an increase in frequency is seen for the higher intensity events. Further analysis focuses on precipitation events exceeding the 99.5 percentile that occur simultaneously at several points in the region, yielding so-called "widespread events". For widespread events, we analyze local and large scale environmental parameters, such as 2-m temperature and specific humidity, 500-hPa geopotential heights, Convective Available Potential Energy (CAPE), vertically integrated moisture flux convergence, among others, to compare atmospheric states and processes leading to such events in the models and observations. The results suggest that an analysis of atmospheric states supporting very heavy precipitation events is a

Can discrete event simulation be of use in modelling major depression?

PubMed Central

Le Lay, Agathe; Despiegel, Nicolas; François, Clément; Duru, Gérard

2006-01-01

Background Depression is among the major contributors to worldwide disease burden and adequate modelling requires a framework designed to depict real world disease progression as well as its economic implications as closely as possible. Objectives In light of the specific characteristics associated with depression (multiple episodes at varying intervals, impact of disease history on course of illness, sociodemographic factors), our aim was to clarify to what extent "Discrete Event Simulation" (DES) models provide methodological benefits in depicting disease evolution. Methods We conducted a comprehensive review of published Markov models in depression and identified potential limits to their methodology. A model based on DES principles was developed to investigate the benefits and drawbacks of this simulation method compared with Markov modelling techniques. Results The major drawback to Markov models is that they may not be suitable to tracking patients' disease history properly, unless the analyst defines multiple health states, which may lead to intractable situations. They are also too rigid to take into consideration multiple patient-specific sociodemographic characteristics in a single model. To do so would also require defining multiple health states which would render the analysis entirely too complex. We show that DES resolve these weaknesses and that its flexibility allow patients with differing attributes to move from one event to another in sequential order while simultaneously taking into account important risk factors such as age, gender, disease history and patients attitude towards treatment, together with any disease-related events (adverse events, suicide attempt etc.). Conclusion DES modelling appears to be an accurate, flexible and comprehensive means of depicting disease progression compared with conventional simulation methodologies. Its use in analysing recurrent and chronic diseases appears particularly useful compared with Markov processes

Adaptive Neural Network-Based Event-Triggered Control of Single-Input Single-Output Nonlinear Discrete-Time Systems.

PubMed

Sahoo, Avimanyu; Xu, Hao; Jagannathan, Sarangapani

2016-01-01

This paper presents a novel adaptive neural network (NN) control of single-input and single-output uncertain nonlinear discrete-time systems under event sampled NN inputs. In this control scheme, the feedback signals are transmitted, and the NN weights are tuned in an aperiodic manner at the event sampled instants. After reviewing the NN approximation property with event sampled inputs, an adaptive state estimator (SE), consisting of linearly parameterized NNs, is utilized to approximate the unknown system dynamics in an event sampled context. The SE is viewed as a model and its approximated dynamics and the state vector, during any two events, are utilized for the event-triggered controller design. An adaptive event-trigger condition is derived by using both the estimated NN weights and a dead-zone operator to determine the event sampling instants. This condition both facilitates the NN approximation and reduces the transmission of feedback signals. The ultimate boundedness of both the NN weight estimation error and the system state vector is demonstrated through the Lyapunov approach. As expected, during an initial online learning phase, events are observed more frequently. Over time with the convergence of the NN weights, the inter-event times increase, thereby lowering the number of triggered events. These claims are illustrated through the simulation results.

An accelerated algorithm for discrete stochastic simulation of reaction-diffusion systems using gradient-based diffusion and tau-leaping.

PubMed

Koh, Wonryull; Blackwell, Kim T

2011-04-21

Stochastic simulation of reaction-diffusion systems enables the investigation of stochastic events arising from the small numbers and heterogeneous distribution of molecular species in biological cells. Stochastic variations in intracellular microdomains and in diffusional gradients play a significant part in the spatiotemporal activity and behavior of cells. Although an exact stochastic simulation that simulates every individual reaction and diffusion event gives a most accurate trajectory of the system's state over time, it can be too slow for many practical applications. We present an accelerated algorithm for discrete stochastic simulation of reaction-diffusion systems designed to improve the speed of simulation by reducing the number of time-steps required to complete a simulation run. This method is unique in that it employs two strategies that have not been incorporated in existing spatial stochastic simulation algorithms. First, diffusive transfers between neighboring subvolumes are based on concentration gradients. This treatment necessitates sampling of only the net or observed diffusion events from higher to lower concentration gradients rather than sampling all diffusion events regardless of local concentration gradients. Second, we extend the non-negative Poisson tau-leaping method that was originally developed for speeding up nonspatial or homogeneous stochastic simulation algorithms. This method calculates each leap time in a unified step for both reaction and diffusion processes while satisfying the leap condition that the propensities do not change appreciably during the leap and ensuring that leaping does not cause molecular populations to become negative. Numerical results are presented that illustrate the improvement in simulation speed achieved by incorporating these two new strategies.

DeMO: An Ontology for Discrete-event Modeling and Simulation.

PubMed

Silver, Gregory A; Miller, John A; Hybinette, Maria; Baramidze, Gregory; York, William S

2011-09-01

Several fields have created ontologies for their subdomains. For example, the biological sciences have developed extensive ontologies such as the Gene Ontology, which is considered a great success. Ontologies could provide similar advantages to the Modeling and Simulation community. They provide a way to establish common vocabularies and capture knowledge about a particular domain with community-wide agreement. Ontologies can support significantly improved (semantic) search and browsing, integration of heterogeneous information sources, and improved knowledge discovery capabilities. This paper discusses the design and development of an ontology for Modeling and Simulation called the Discrete-event Modeling Ontology (DeMO), and it presents prototype applications that demonstrate various uses and benefits that such an ontology may provide to the Modeling and Simulation community.

DeMO: An Ontology for Discrete-event Modeling and Simulation

PubMed Central

Silver, Gregory A; Miller, John A; Hybinette, Maria; Baramidze, Gregory; York, William S

2011-01-01

Several fields have created ontologies for their subdomains. For example, the biological sciences have developed extensive ontologies such as the Gene Ontology, which is considered a great success. Ontologies could provide similar advantages to the Modeling and Simulation community. They provide a way to establish common vocabularies and capture knowledge about a particular domain with community-wide agreement. Ontologies can support significantly improved (semantic) search and browsing, integration of heterogeneous information sources, and improved knowledge discovery capabilities. This paper discusses the design and development of an ontology for Modeling and Simulation called the Discrete-event Modeling Ontology (DeMO), and it presents prototype applications that demonstrate various uses and benefits that such an ontology may provide to the Modeling and Simulation community. PMID:22919114

Hybrid stochastic simulations of intracellular reaction-diffusion systems.

PubMed

Kalantzis, Georgios

2009-06-01

With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.

Numerical simulations of an advection fog event over Shanghai Pudong International Airport with the WRF model

NASA Astrophysics Data System (ADS)

Lin, Caiyan; Zhang, Zhongfeng; Pu, Zhaoxia; Wang, Fengyun

2017-10-01

A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advection fog event over Shanghai Pudong International Airport (ZSPD) with the Weather Research and Forecasting (WRF) model. Using the current operational settings at the Meteorological Center of East China Air Traffic Management Bureau, the WRF model successfully predicts the fog event at ZSPD. Additional numerical experiments are performed to examine the physical processes associated with the fog event. The results indicate that prediction of this particular fog event is sensitive to microphysical schemes for the time of fog dissipation but not for the time of fog onset. The simulated timing of the arrival and dissipation of the fog, as well as the cloud distribution, is substantially sensitive to the planetary boundary layer and radiation (both longwave and shortwave) processes. Moreover, varying forecast lead times also produces different simulation results for the fog event regarding its onset and duration, suggesting a trade-off between more accurate initial conditions and a proper forecast lead time that allows model physical processes to spin up adequately during the fog simulation. The overall outcomes from this study imply that the complexity of physical processes and their interactions within the WRF model during fog evolution and dissipation is a key area of future research.

Can the GEOS CCM Simulate the Temperature Response to Warm Pool El Nino Events in the Antarctic Stratosphere?

NASA Technical Reports Server (NTRS)

Hurwitz, M. M.; Song, I.-S.; Oman, L. D.; Newman, P. A.; Molod, A. M.; Frith, S. M.; Nielsen, J. E.

2010-01-01

"Warm pool" (WP) El Nino events are characterized by positive sea surface temperature (SST) anomalies in the central equatorial Pacific. During austral spring. WP El Nino events are associated with an enhancement of convective activity in the South Pacific Convergence Zone, provoking a tropospheric planetary wave response and thus increasing planetary wave driving of the Southern Hemisphere stratosphere. These conditions lead to higher polar stratospheric temperatures and to a weaker polar jet during austral summer, as compared with neutral ENSO years. Furthermore, this response is sensitive to the phase of the quasi-biennial oscillation (QBO): a stronger warming is seen in WP El Nino events coincident with the easterly phase of the quasi-biennial oscillation (QBO) as compared with WP El Nino events coincident with a westerly or neutral QBO. The Goddard Earth Observing System (GEOS) chemistry-climate model (CCM) is used to further explore the atmospheric response to ENSO. Time-slice simulations are forced by composited SSTs from observed WP El Nino and neutral ENSO events. The modeled eddy heat flux, temperature and wind responses to WP El Nino events are compared with observations. A new gravity wave drag scheme has been implemented in the GEOS CCM, enabling the model to produce a realistic, internally generated QBO. By repeating the above time-slice simulations with this new model version, the sensitivity of the WP El Nino response to the phase of the quasi-biennial oscillation QBO is estimated.

Can the GEOS CCM Simulate the Temperature Response to Warm Pool El Nino Events in the Antarctic Stratosphere?

NASA Technical Reports Server (NTRS)

Hurwitz, M. M.; Song, I.-S.; Oman, L. D.; Newman, P. A.; Molod, A. M.; Frith, S. M.; Nielsen, J. E.

2011-01-01

"Warm pool" (WP) El Nino events are characterized by positive sea surface temperature (SST) anomalies in the central equatorial Pacific. During austral spring, WP El Nino events are associated with an enhancement of convective activity in the South Pacific Convergence Zone, provoking a tropospheric planetary wave response and thus increasing planetary wave driving of the Southern Hemisphere stratosphere. These conditions lead to higher polar stratospheric temperatures and to a weaker polar jet during austral summer, as compared with neutral ENSO years. Furthermore, this response is sensitive to the phase of the quasi-biennial oscillation (QBO): a stronger warming is seen in WP El Nino events coincident with the easterly phase of the quasi-biennial oscillation (QBO) as compared with WP El Nino events coincident with a westerly or neutral QBO. The Goddard Earth Observing System (GEOS) chemistry-climate model (CCM) is used to further explore the atmospheric response to ENSO. Time-slice simulations are forced by composited SSTs from observed NP El Nino and neutral ENSO events. The modeled eddy heat flux, temperature and wind responses to WP El Nino events are compared with observations. A new gravity wave drag scheme has been implemented in the GEOS CCM, enabling the model to produce e realistic, internally generated QBO. By repeating the above time-slice simulations with this new model version, the sensitivity of the WP El Nino response to the phase of the quasi-biennial oscillation QBO is estimated.

Simulating Flaring Events via an Intelligent Cellular Automata Mechanism

NASA Astrophysics Data System (ADS)

Dimitropoulou, M.; Vlahos, L.; Isliker, H.; Georgoulis, M.

2010-07-01

We simulate flaring events through a Cellular Automaton (CA) model, in which, for the first time, we use observed vector magnetograms as initial conditions. After non-linear force free extrapolation of the magnetic field from the vector magnetograms, we identify magnetic discontinuities, using two alternative criteria: (1) the average magnetic field gradient, or (2) the normalized magnetic field curl (i.e. the current). Magnetic discontinuities are identified at the grid-sites where the magnetic field gradient or curl exceeds a specified threshold. We then relax the magnetic discontinuities according to the rules of Lu and Hamilton (1991) or Lu et al. (1993), i.e. we redistribute the magnetic field locally so that the discontinuities disappear. In order to simulate the flaring events, we consider several alternative scenarios with regard to: (1) The threshold above which magnetic discontinuities are identified (applying low, high, and height-dependent threshold values); (2) The driving process that occasionally causes new discontinuities (at randomly chosen grid sites, magnetic field increments are added that are perpendicular (or may-be also parallel) to the existing magnetic field). We address the question whether the coronal active region magnetic fields can indeed be considered to be in the state of self-organized criticality (SOC).

Simulation of debris flow events in Sicily by cellular automata model SCIDDICA_SS3

NASA Astrophysics Data System (ADS)

Cancelliere, A.; Lupiano, V.; Peres, D. J.; Stancanelli, L.; Avolio, M.; Foti, E.; Di Gregorio, S.

2013-12-01

Debris flow models are widely used for hazard mapping or for evaluating the effectiveness of risk mitigation measures. Several models analyze the dynamics of debris flow runout solving Partial Differential Equations. In use of such models, difficulties arise in estimating kinematic geotechnical soil parameters for real phenomena. In order to overcome such difficulties, alternative semi-empirical approaches can be employed, such as macroscopic Cellular Automata (CA). In particular, for CA simulation purposes, the runout of debris flows emerges from local interactions in a dynamical system, subdivided into elementary parts, whose state evolves within a spatial and temporal discretum. The attributes of each cell (substates) describe physical characteristics. For computational reasons, the natural phenomenon is splitted into a number of elementary processes, whose proper composition makes up the CA transition function. By simultaneously applying this function to all the cells, the evolution of the phenomenon can be simulated in terms of modifications of the substates. In this study, we present an application of the macroscopic CA semi-empirical model SCIDDICA_SS3 to the Peloritani Mountains area in Sicily island, Italy. The model was applied using detailed data from the 1 October 2009 debris flow event, which was triggered by a rainfall event of about 250 mm falling in 9 hours, that caused the death of 37 persons. This region is characterized by river valleys with large hillslope angles (30°-60°), catchment basins of small extensions (0.5-12 km2) and soil composed by metamorphic material, which is easy to be eroded. CA usage implies a calibration phase, that identifies an optimal set of parameters capable of adequately play back the considered case, and a validation phase, that tests the model on a sufficient (and different) number of cases similar in terms of physical and geomorphological properties. The performance of the model can be measured in terms of a fitness

Reading sky and seeing a cloud: On the relevance of events for perceptual simulation.

PubMed

Ostarek, Markus; Vigliocco, Gabriella

2017-04-01

Previous research has shown that processing words with an up/down association (e.g., bird, foot) can influence the subsequent identification of visual targets in congruent location (at the top/bottom of the screen). However, as facilitation and interference were found under similar conditions, the nature of the underlying mechanisms remained unclear. We propose that word comprehension relies on the perceptual simulation of a prototypical event involving the entity denoted by a word in order to provide a general account of the different findings. In 3 experiments, participants had to discriminate between 2 target pictures appearing at the top or the bottom of the screen by pressing the left versus right button. Immediately before the targets appeared, they saw an up/down word belonging to the target's event, an up/down word unrelated to the target, or a spatially neutral control word. Prime words belonging to target event facilitated identification of targets at a stimulus onset asynchrony (SOA) of 250 ms (Experiment 1), but only when presented in the vertical location where they are typically seen, indicating that targets were integrated in the simulations activated by the prime words. Moreover, at the same SOA, there was a robust facilitation effect for targets appearing in their typical location regardless of the prime type. However, when words were presented for 100 ms (Experiment 2) or 800 ms (Experiment 3), only a location nonspecific priming effect was found, suggesting that the visual system was not activated. Implications for theories of semantic processing are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Generalized Detectability for Discrete Event Systems

PubMed Central

Shu, Shaolong; Lin, Feng

2011-01-01

In our previous work, we investigated detectability of discrete event systems, which is defined as the ability to determine the current and subsequent states of a system based on observation. For different applications, we defined four types of detectabilities: (weak) detectability, strong detectability, (weak) periodic detectability, and strong periodic detectability. In this paper, we extend our results in three aspects. (1) We extend detectability from deterministic systems to nondeterministic systems. Such a generalization is necessary because there are many systems that need to be modeled as nondeterministic discrete event systems. (2) We develop polynomial algorithms to check strong detectability. The previous algorithms are based on observer whose construction is of exponential complexity, while the new algorithms are based on a new automaton called detector. (3) We extend detectability to D-detectability. While detectability requires determining the exact state of a system, D-detectability relaxes this requirement by asking only to distinguish certain pairs of states. With these extensions, the theory on detectability of discrete event systems becomes more applicable in solving many practical problems. PMID:21691432

Using discrete event computer simulation to improve patient flow in a Ghanaian acute care hospital.

PubMed

Best, Allyson M; Dixon, Cinnamon A; Kelton, W David; Lindsell, Christopher J; Ward, Michael J

2014-08-01

Crowding and limited resources have increased the strain on acute care facilities and emergency departments worldwide. These problems are particularly prevalent in developing countries. Discrete event simulation is a computer-based tool that can be used to estimate how changes to complex health care delivery systems such as emergency departments will affect operational performance. Using this modality, our objective was to identify operational interventions that could potentially improve patient throughput of one acute care setting in a developing country. We developed a simulation model of acute care at a district level hospital in Ghana to test the effects of resource-neutral (eg, modified staff start times and roles) and resource-additional (eg, increased staff) operational interventions on patient throughput. Previously captured deidentified time-and-motion data from 487 acute care patients were used to develop and test the model. The primary outcome was the modeled effect of interventions on patient length of stay (LOS). The base-case (no change) scenario had a mean LOS of 292 minutes (95% confidence interval [CI], 291-293). In isolation, adding staffing, changing staff roles, and varying shift times did not affect overall patient LOS. Specifically, adding 2 registration workers, history takers, and physicians resulted in a 23.8-minute (95% CI, 22.3-25.3) LOS decrease. However, when shift start times were coordinated with patient arrival patterns, potential mean LOS was decreased by 96 minutes (95% CI, 94-98), and with the simultaneous combination of staff roles (registration and history taking), there was an overall mean LOS reduction of 152 minutes (95% CI, 150-154). Resource-neutral interventions identified through discrete event simulation modeling have the potential to improve acute care throughput in this Ghanaian municipal hospital. Discrete event simulation offers another approach to identifying potentially effective interventions to improve patient

Optimized Hypervisor Scheduler for Parallel Discrete Event Simulations on Virtual Machine Platforms

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

Yoginath, Srikanth B; Perumalla, Kalyan S

2013-01-01

With the advent of virtual machine (VM)-based platforms for parallel computing, it is now possible to execute parallel discrete event simulations (PDES) over multiple virtual machines, in contrast to executing in native mode directly over hardware as is traditionally done over the past decades. While mature VM-based parallel systems now offer new, compelling benefits such as serviceability, dynamic reconfigurability and overall cost effectiveness, the runtime performance of parallel applications can be significantly affected. In particular, most VM-based platforms are optimized for general workloads, but PDES execution exhibits unique dynamics significantly different from other workloads. Here we first present results frommore » experiments that highlight the gross deterioration of the runtime performance of VM-based PDES simulations when executed using traditional VM schedulers, quantitatively showing the bad scaling properties of the scheduler as the number of VMs is increased. The mismatch is fundamental in nature in the sense that any fairness-based VM scheduler implementation would exhibit this mismatch with PDES runs. We also present a new scheduler optimized specifically for PDES applications, and describe its design and implementation. Experimental results obtained from running PDES benchmarks (PHOLD and vehicular traffic simulations) over VMs show over an order of magnitude improvement in the run time of the PDES-optimized scheduler relative to the regular VM scheduler, with over 20 reduction in run time of simulations using up to 64 VMs. The observations and results are timely in the context of emerging systems such as cloud platforms and VM-based high performance computing installations, highlighting to the community the need for PDES-specific support, and the feasibility of significantly reducing the runtime overhead for scalable PDES on VM platforms.« less

Decentralized event-triggered consensus control strategy for leader-follower networked systems

NASA Astrophysics Data System (ADS)

Zhang, Shouxu; Xie, Duosi; Yan, Weisheng

2017-08-01

In this paper, the consensus problem of leader-follower networked systems is addressed. At first, a centralized and a decentralized event-triggered control strategy are proposed, which make the control actuators of followers update at aperiodic invent interval. In particular, the latter one makes each follower requires the local information only. After that, an improved triggering function that only uses the follower's own information and the neighbors' states at their latest event instants is developed to relax the requirement of the continuous state of the neighbors. In addition, the strategy does not require the information of the topology, nor the eigenvalues of the Laplacian matrix. And if the follower does not have direct connection to the leader, the leader's information is not required either. It is analytically shown that by using the proposed strategy the leader-follower networked system is able to reach consensus without continuous communication among followers. Simulation examples are given to show effectiveness of the proposed control strategy.

A coupled classification - evolutionary optimization model for contamination event detection in water distribution systems.

PubMed

Oliker, Nurit; Ostfeld, Avi

2014-03-15

This study describes a decision support system, alerts for contamination events in water distribution systems. The developed model comprises a weighted support vector machine (SVM) for the detection of outliers, and a following sequence analysis for the classification of contamination events. The contribution of this study is an improvement of contamination events detection ability and a multi-dimensional analysis of the data, differing from the parallel one-dimensional analysis conducted so far. The multivariate analysis examines the relationships between water quality parameters and detects changes in their mutual patterns. The weights of the SVM model accomplish two goals: blurring the difference between sizes of the two classes' data sets (as there are much more normal/regular than event time measurements), and adhering the time factor attribute by a time decay coefficient, ascribing higher importance to recent observations when classifying a time step measurement. All model parameters were determined by data driven optimization so the calibration of the model was completely autonomic. The model was trained and tested on a real water distribution system (WDS) data set with randomly simulated events superimposed on the original measurements. The model is prominent in its ability to detect events that were only partly expressed in the data (i.e., affecting only some of the measured parameters). The model showed high accuracy and better detection ability as compared to previous modeling attempts of contamination event detection. Copyright © 2013 Elsevier Ltd. All rights reserved.

Explicit simulation of a midlatitude Mesoscale Convective System

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

Alexander, G.D.; Cotton, W.R.

1996-04-01

We have explicitly simulated the mesoscale convective system (MCS) observed on 23-24 June 1985 during PRE-STORM, the Preliminary Regional Experiment for the Stormscale Operational and Research and Meterology Program. Stensrud and Maddox (1988), Johnson and Bartels (1992), and Bernstein and Johnson (1994) are among the researchers who have investigated various aspects of this MCS event. We have performed this MCS simulation (and a similar one of a tropical MCS; Alexander and Cotton 1994) in the spirit of the Global Energy and Water Cycle Experiment Cloud Systems Study (GCSS), in which cloud-resolving models are used to assist in the formulation andmore » testing of cloud parameterization schemes for larger-scale models. In this paper, we describe (1) the nature of our 23-24 June MCS dimulation and (2) our efforts to date in using our explicit MCS simulations to assist in the development of a GCM parameterization for mesoscale flow branches. The paper is organized as follows. First, we discuss the synoptic situation surrounding the 23-24 June PRE-STORM MCS followed by a discussion of the model setup and results of our simulation. We then discuss the use of our MCS simulation. We then discuss the use of our MCS simulations in developing a GCM parameterization for mesoscale flow branches and summarize our results.« less

Simulation of seismic events induced by CO2 injection at In Salah, Algeria

NASA Astrophysics Data System (ADS)

Verdon, James P.; Stork, Anna L.; Bissell, Rob C.; Bond, Clare E.; Werner, Maximilian J.

2015-09-01

Carbon capture and storage technology has the potential to reduce anthropogenic CO2 emissions. However, the geomechanical response of the reservoir and sealing caprocks must be modelled and monitored to ensure that injected CO2 is safely stored. To ensure confidence in model results, there is a clear need to develop ways of comparing model predictions with observations from the field. In this paper we develop an approach to simulate microseismic activity induced by injection, which allows us to compare geomechanical model predictions with observed microseismic activity. We apply this method to the In Salah CCS project, Algeria. A geomechanical reconstruction is used to simulate the locations, orientations and sizes of pre-existing fractures in the In Salah reservoir. The initial stress conditions, in combination with a history matched reservoir flow model, are used to determine when and where these fractures exceed Mohr-Coulomb limits, triggering failure. The sizes and orientations of fractures, and the stress conditions thereon, are used to determine the resulting micro-earthquake focal mechanisms and magnitudes. We compare our simulated event population with observations made at In Salah, finding good agreement between model and observations in terms of event locations, rates of seismicity, and event magnitudes.

Analysis of convection-permitting simulations for capturing heavy rainfall events over Myanmar Region

NASA Astrophysics Data System (ADS)

Acierto, R. A. E.; Kawasaki, A.

2017-12-01

Perennial flooding due to heavy rainfall events causes strong impacts on the society and economy. With increasing pressures of rapid development and potential for climate change impacts, Myanmar experiences a rapid increase in disaster risk. Heavy rainfall hazard assessment is key on quantifying such disaster risk in both current and future conditions. Downscaling using Regional Climate Models (RCM) such as Weather Research and Forecast model have been used extensively for assessing such heavy rainfall events. However, usage of convective parameterizations can introduce large errors in simulating rainfall. Convective-permitting simulations have been used to deal with this problem by increasing the resolution of RCMs to 4km. This study focuses on the heavy rainfall events during the six-year (2010-2015) wet period season from May to September in Myanmar. The investigation primarily utilizes rain gauge observation for comparing downscaled heavy rainfall events in 4km resolution using ERA-Interim as boundary conditions using 12km-4km one-way nesting method. The study aims to provide basis for production of high-resolution climate projections over Myanmar in order to contribute for flood hazard and risk assessment.

Discrete event simulation for exploring strategies: an urban water management case.

PubMed

Huang, Dong-Bin; Scholz, Roland W; Gujer, Willi; Chitwood, Derek E; Loukopoulos, Peter; Schertenleib, Roland; Siegrist, Hansruedi

2007-02-01

This paper presents a model structure aimed at offering an overview of the various elements of a strategy and exploring their multidimensional effects through time in an efficient way. It treats a strategy as a set of discrete events planned to achieve a certain strategic goal and develops a new form of causal networks as an interfacing component between decision makers and environment models, e.g., life cycle inventory and material flow models. The causal network receives a strategic plan as input in a discrete manner and then outputs the updated parameter sets to the subsequent environmental models. Accordingly, the potential dynamic evolution of environmental systems caused by various strategies can be stepwise simulated. It enables a way to incorporate discontinuous change in models for environmental strategy analysis, and enhances the interpretability and extendibility of a complex model by its cellular constructs. It is exemplified using an urban water management case in Kunming, a major city in Southwest China. By utilizing the presented method, the case study modeled the cross-scale interdependencies of the urban drainage system and regional water balance systems, and evaluated the effectiveness of various strategies for improving the situation of Dianchi Lake.

Discrete-Event Simulation Models of Plasmodium falciparum Malaria

PubMed Central

McKenzie, F. Ellis; Wong, Roger C.; Bossert, William H.

2008-01-01

We develop discrete-event simulation models using a single “timeline” variable to represent the Plasmodium falciparum lifecycle in individual hosts and vectors within interacting host and vector populations. Where they are comparable our conclusions regarding the relative importance of vector mortality and the durations of host immunity and parasite development are congruent with those of classic differential-equation models of malaria, epidemiology. However, our results also imply that in regions with intense perennial transmission, the influence of mosquito mortality on malaria prevalence in humans may be rivaled by that of the duration of host infectivity. PMID:18668185

Anomalous event diagnosis for environmental satellite systems

NASA Technical Reports Server (NTRS)

Ramsay, Bruce H.

1993-01-01

The National Oceanic and Atmospheric Administration's (NOAA) National Environmental Satellite, Data, and Information Service (NESDIS) is responsible for the operation of the NOAA geostationary and polar orbiting satellites. NESDIS provides a wide array of operational meteorological and oceanographic products and services and operates various computer and communication systems on a 24-hour, seven days per week schedule. The Anomaly Reporting System contains a database of anomalous events regarding the operations of the Geostationary Operational Environmental Satellite (GOES), communication, or computer systems that have degraded or caused the loss of GOES imagery. Data is currently entered manually via an automated query user interface. There are 21 possible symptoms (e.g., No Data), and 73 possible causes (e.g., Sectorizer - World Weather Building) of an anomalous event. The determination of an event's cause(s) is made by the on-duty computer operator, who enters the event in a paper based daily log, and by the analyst entering the data into the reporting system. The determination of the event's cause(s) impacts both the operational status of these systems, and the performance evaluation of the on-site computer and communication operations contractor.

Performance and efficiency of geotextile-supported erosion control measures during simulated rainfall events

NASA Astrophysics Data System (ADS)

Obriejetan, Michael; Rauch, Hans Peter; Florineth, Florin

2013-04-01

Erosion control systems consisting of technical and biological components are widely accepted and proven to work well if installed properly with regard to site-specific parameters. A wide range of implementation measures for this specific protection purpose is existent and new, in particular technical solutions are constantly introduced into the market. Nevertheless, especially vegetation aspects of erosion control measures are frequently disregarded and should be considered enhanced against the backdrop of the development and realization of adaptation strategies in an altering environment due to climate change associated effects. Technical auxiliaries such as geotextiles typically used for slope protection (nettings, blankets, turf reinforcement mats etc.) address specific features and due to structural and material diversity, differing effects on sediment yield, surface runoff and vegetational development seem evident. Nevertheless there is a knowledge gap concerning the mutual interaction processes between technical and biological components respectively specific comparable data on erosion-reducing effects of technical-biological erosion protection systems are insufficient. In this context, an experimental arrangement was set up to study the correlated influences of geotextiles and vegetation and determine its (combined) effects on surface runoff and soil loss during simulated heavy rainfall events. Sowing vessels serve as testing facilities which are filled with top soil under application of various organic and synthetic geotextiles and by using a reliable drought resistant seed mixture. Regular vegetational monitoring as well as two rainfall simulation runs with four repetitions of each variant were conducted. Therefore a portable rainfall simulator with standardized rainfall intensity of 240 mm h-1 and three minute rainfall duration was used to stress these systems on different stages of plant development at an inclination of 30 degrees. First results show

Simulating planetary wave propagation to the upper atmosphere during stratospheric warming events at different mountain wave scenarios

NASA Astrophysics Data System (ADS)

Gavrilov, Nikolai M.; Koval, Andrey V.; Pogoreltsev, Alexander I.; Savenkova, Elena N.

2018-04-01

Parameterization schemes of atmospheric normal modes (NMs) and orographic gravity waves (OGWs) have been implemented into the mechanistic Middle and Upper Atmosphere Model (MUAM) simulating atmospheric general circulation. Based on the 12-members ensemble of runs with the MUAM, a composite of the stratospheric warming (SW) has been constructed using the UK Met Office data as the lower boundary conditions. The simulation results show that OGW amplitudes increase at altitudes above 30 km in the Northern Hemisphere after the SW event. At altitudes of about 50 km, OGWs have largest amplitudes over North American and European mountain systems before and during the composite SW, and over Himalayas after the SW. Simulations demonstrate substantial (up to 50-70%) variations of amplitudes of stationary planetary waves (PWs) during and after the SW in the mesosphere-lower thermosphere of the Northern Hemisphere. Westward travelling NMs have amplitude maxima not only in the Northern, but also in the Southern Hemisphere, where these modes have waveguides in the middle and upper atmosphere. Simulated variations of PW and NM amplitudes correspond to changes in the mean zonal wind, EP-fluxes and wave refractive index at different phases of the composite SW events. Inclusion of the parameterization of OGW effects leads to decreases in amplitudes (up to 15%) of almost all SPWs before and after the SW event and their increase (up to 40-60%) after the SW in the stratosphere and mesosphere at middle and high northern latitudes. It is suggested that observed changes in NM amplitudes in the Southern Hemisphere during SW could be caused by divergence of increased southward EP-flux. This EP-flux increases due to OGW drag before SW and extends into the Southern Hemisphere.

Simulation of Greenhouse Climate Monitoring and Control with Wireless Sensor Network and Event-Based Control

PubMed Central

Pawlowski, Andrzej; Guzman, Jose Luis; Rodríguez, Francisco; Berenguel, Manuel; Sánchez, José; Dormido, Sebastián

2009-01-01

Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results. PMID:22389597

Simulation of greenhouse climate monitoring and control with wireless sensor network and event-based control.

PubMed

Pawlowski, Andrzej; Guzman, Jose Luis; Rodríguez, Francisco; Berenguel, Manuel; Sánchez, José; Dormido, Sebastián

2009-01-01

Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results.

MHD simulation of the shock wave event on October 24, 2003

NASA Astrophysics Data System (ADS)

Ogino, T.; Kajiwara, Y.; Nakao, M.; Park, K. S.; Fukazawa, K.; Yi, Y.

2007-11-01

A three-dimensional global MHD simulation of the interaction between the solar wind and the Earth's magnetosphere has been executed to study the shock wave event on space weather problem on October 24, 2003, when an abnormal operation happened in a satellite for Environment Observation Technology, ADEOS-II (Midori-II). Characteristic features of the event are the long duration of southward IMF, arrival of a strong shock wave, then large variation of IMF By from negative to positive for about 15 min duration. In the simulation, the shock wave compresses the magnetosphere for southward IMF and a hot plasma was injected around the geosynchronous orbit from plasma sheet. During the interval when IMF By changes from negative to positive, the magnitude of IMF extremely decreases to bring attenuation of magnetic reconnection. The open-closed boundary shrinks in the polar cap and the transient expansion of the magnetic field lines occurs to imply enhancement of particle precipitation. The reconnection site moves from dawn to dusk in the dayside magnetopause and a narrow cockscomb closed field region is formed in the high latitude tail.

Event detection and sub-state discovery from biomolecular simulations using higher-order statistics: application to enzyme adenylate kinase.

PubMed

Ramanathan, Arvind; Savol, Andrej J; Agarwal, Pratul K; Chennubhotla, Chakra S

2012-11-01

Biomolecular simulations at millisecond and longer time-scales can provide vital insights into functional mechanisms. Because post-simulation analyses of such large trajectory datasets can be a limiting factor in obtaining biological insights, there is an emerging need to identify key dynamical events and relating these events to the biological function online, that is, as simulations are progressing. Recently, we have introduced a novel computational technique, quasi-anharmonic analysis (QAA) (Ramanathan et al., PLoS One 2011;6:e15827), for partitioning the conformational landscape into a hierarchy of functionally relevant sub-states. The unique capabilities of QAA are enabled by exploiting anharmonicity in the form of fourth-order statistics for characterizing atomic fluctuations. In this article, we extend QAA for analyzing long time-scale simulations online. In particular, we present HOST4MD--a higher-order statistical toolbox for molecular dynamics simulations, which (1) identifies key dynamical events as simulations are in progress, (2) explores potential sub-states, and (3) identifies conformational transitions that enable the protein to access those sub-states. We demonstrate HOST4MD on microsecond timescale simulations of the enzyme adenylate kinase in its apo state. HOST4MD identifies several conformational events in these simulations, revealing how the intrinsic coupling between the three subdomains (LID, CORE, and NMP) changes during the simulations. Further, it also identifies an inherent asymmetry in the opening/closing of the two binding sites. We anticipate that HOST4MD will provide a powerful and extensible framework for detecting biophysically relevant conformational coordinates from long time-scale simulations. Copyright © 2012 Wiley Periodicals, Inc.

Distribution system simulator

NASA Technical Reports Server (NTRS)

Bahrami, K. A.; Kirkham, H.; Rahman, S.

1986-01-01

In a series of tests performed under the Department of Energy auspices, power line carrier propagation was observed to be anomalous under certain circumstances. To investigate the cause, a distribution system simulator was constructed. The simulator was a physical simulator that accurately represented the distribution system from below power frequency to above 50 kHz. Effects such as phase-to-phase coupling and skin effect were modeled. Construction details of the simulator, and experimental results from its use are presented.

Association rule mining in the US Vaccine Adverse Event Reporting System (VAERS).

PubMed

Wei, Lai; Scott, John

2015-09-01

Spontaneous adverse event reporting systems are critical tools for monitoring the safety of licensed medical products. Commonly used signal detection algorithms identify disproportionate product-adverse event pairs and may not be sensitive to more complex potential signals. We sought to develop a computationally tractable multivariate data-mining approach to identify product-multiple adverse event associations. We describe an application of stepwise association rule mining (Step-ARM) to detect potential vaccine-symptom group associations in the US Vaccine Adverse Event Reporting System. Step-ARM identifies strong associations between one vaccine and one or more adverse events. To reduce the number of redundant association rules found by Step-ARM, we also propose a clustering method for the post-processing of association rules. In sample applications to a trivalent intradermal inactivated influenza virus vaccine and to measles, mumps, rubella, and varicella (MMRV) vaccine and in simulation studies, we find that Step-ARM can detect a variety of medically coherent potential vaccine-symptom group signals efficiently. In the MMRV example, Step-ARM appears to outperform univariate methods in detecting a known safety signal. Our approach is sensitive to potentially complex signals, which may be particularly important when monitoring novel medical countermeasure products such as pandemic influenza vaccines. The post-processing clustering algorithm improves the applicability of the approach as a screening method to identify patterns that may merit further investigation. Copyright © 2015 John Wiley & Sons, Ltd.

Analysis and hindcast simulations of an extreme rainfall event in the Mediterranean area: The Genoa 2011 case

NASA Astrophysics Data System (ADS)

Fiori, E.; Comellas, A.; Molini, L.; Rebora, N.; Siccardi, F.; Gochis, D. J.; Tanelli, S.; Parodi, A.

2014-03-01

The city of Genoa, which places between the Tyrrhenian Sea and the Apennine mountains (Liguria, Italy) was rocked by severe flash floods on the 4th of November, 2011. Nearly 500 mm of rain, a third of the average annual rainfall, fell in six hours. Six people perished and millions of Euros in damages occurred. The synoptic-scale meteorological system moved across the Atlantic Ocean and into the Mediterranean generating floods that killed 5 people in Southern France, before moving over the Ligurian Sea and Genoa producing the extreme event studied here. Cloud-permitting simulations (1 km) of the finger-like convective system responsible for the torrential event over Genoa have been performed using Advanced Research Weather and Forecasting Model (ARW-WRF, version 3.3). Two different microphysics (WSM6 and Thompson) as well as three different convection closures (explicit, Kain-Fritsch, and Betts-Miller-Janjic) were evaluated to gain a deeper understanding of the physical processes underlying the observed heavy rain event and the model's capability to predict, in hindcast mode, its structure and evolution. The impact of forecast initialization and of model vertical discretization on hindcast results is also examined. Comparison between model hindcasts and observed fields provided by raingauge data, satellite data, and radar data show that this particular event is strongly sensitive to the details of the mesoscale initialization despite being evolved from a relatively large scale weather system. Only meso-γ details of the event were not well captured by the best setting of the ARW-WRF model and so peak hourly rainfalls were not exceptionally well reproduced. The results also show that specification of microphysical parameters suitable to these events have a positive impact on the prediction of heavy precipitation intensity values.

Numerical simulation of a mistral wind event occuring

NASA Astrophysics Data System (ADS)

Guenard, V.; Caccia, J. L.; Tedeschi, G.

2003-04-01

The experimental network of the ESCOMPTE field experiment (june-july 2001) is turned into account to investigate the Mistral wind affecting the Marseille area (South of France). Mistral wind is a northerly flow blowing across the Rhône valley and toward the Mediterranean sea resulting from the dynamical low pressure generated in the wake of the Alps ridge. It brings cold, dry air masses and clear sky conditions over the south-eastern part of France. Up to now, few scientific studies have been carried out on the Mistral wind especially the evolution of its 3-D structure so that its mesoscale numerical simulation is still relevant. Non-hydrostatic RAMS model is performed to better investigate this mesoscale phenomena. Simulations at a 12 km horizontal resolution are compared to boundary layer wind profilers and ground measurements. Preliminary results suit quite well with the Mistral statistical studies carried out by the operational service of Météo-France and observed wind profiles are correctly reproduced by the numerical model RAMS which appears to be an efficient tool for its understanding of Mistral. Owing to the absence of diabatic effect in Mistral events which complicates numerical simulations, the present work is the first step for the validation of RAMS model in that area. Further works will consist on the study of the interaction of Mistral wind with land-sea breeze. Also, RAMS simulations will be combined with aerosol production and ocean circulation models to supply chemists and oceanographers with some answers for their studies.

Productivity improvement using discrete events simulation

NASA Astrophysics Data System (ADS)

Hazza, M. H. F. Al; Elbishari, E. M. Y.; Ismail, M. Y. Bin; Adesta, E. Y. T.; Rahman, Nur Salihah Binti Abdul

2018-01-01

The increasing in complexity of the manufacturing systems has increased the cost of investment in many industries. Furthermore, the theoretical feasibility studies are not enough to take the decision in investing for that particular area. Therefore, the development of the new advanced software is protecting the manufacturer from investing money in production lines that may not be sufficient and effective with their requirement in terms of machine utilization and productivity issue. By conducting a simulation, using accurate model will reduce and eliminate the risk associated with their new investment. The aim of this research is to prove and highlight the importance of simulation in decision-making process. Delmia quest software was used as a simulation program to run a simulation for the production line. A simulation was first done for the existing production line and show that the estimated production rate is 261 units/day. The results have been analysed based on utilization percentage and idle time. Two different scenarios have been proposed based on different objectives. The first scenario is by focusing on low utilization machines and their idle time, this was resulted in minimizing the number of machines used by three with the addition of the works who maintain them without having an effect on the production rate. The second scenario is to increase the production rate by upgrading the curing machine which lead to the increase in the daily productivity by 7% from 261 units to 281 units.

Testing the anisotropy of the universe using the simulated gravitational wave events from advanced LIGO and Virgo

NASA Astrophysics Data System (ADS)

Lin, Hai-Nan; Li, Jin; Li, Xin

2018-05-01

The detection of gravitational waves (GWs) provides a powerful tool to constrain the cosmological parameters. In this paper, we investigate the possibility of using GWs as standard sirens in testing the anisotropy of the universe. We consider the GW signals produced by the coalescence of binary black hole systems and simulate hundreds of GW events from the advanced laser interferometer gravitational-wave observatory and Virgo. It is found that the anisotropy of the universe can be tightly constrained if the redshift of the GW source is precisely known. The anisotropic amplitude can be constrained with an accuracy comparable to the Union2.1 complication of type-Ia supernovae if ≳ 400 GW events are observed. As for the preferred direction, ≳ 800 GW events are needed in order to achieve the accuracy of Union2.1. With 800 GW events, the probability of pseudo anisotropic signals with an amplitude comparable to Union2.1 is negligible. These results show that GWs can provide a complementary tool to supernovae in testing the anisotropy of the universe.

Discrete Event Simulation Models for CT Examination Queuing in West China Hospital.

PubMed

Luo, Li; Liu, Hangjiang; Liao, Huchang; Tang, Shijun; Shi, Yingkang; Guo, Huili

2016-01-01

In CT examination, the emergency patients (EPs) have highest priorities in the queuing system and thus the general patients (GPs) have to wait for a long time. This leads to a low degree of satisfaction of the whole patients. The aim of this study is to improve the patients' satisfaction by designing new queuing strategies for CT examination. We divide the EPs into urgent type and emergency type and then design two queuing strategies: one is that the urgent patients (UPs) wedge into the GPs' queue with fixed interval (fixed priority model) and the other is that the patients have dynamic priorities for queuing (dynamic priority model). Based on the data from Radiology Information Database (RID) of West China Hospital (WCH), we develop some discrete event simulation models for CT examination according to the designed strategies. We compare the performance of different strategies on the basis of the simulation results. The strategy that patients have dynamic priorities for queuing makes the waiting time of GPs decrease by 13 minutes and the degree of satisfaction increase by 40.6%. We design a more reasonable CT examination queuing strategy to decrease patients' waiting time and increase their satisfaction degrees.

Discrete Event Simulation Models for CT Examination Queuing in West China Hospital

PubMed Central

Luo, Li; Tang, Shijun; Shi, Yingkang; Guo, Huili

2016-01-01

In CT examination, the emergency patients (EPs) have highest priorities in the queuing system and thus the general patients (GPs) have to wait for a long time. This leads to a low degree of satisfaction of the whole patients. The aim of this study is to improve the patients' satisfaction by designing new queuing strategies for CT examination. We divide the EPs into urgent type and emergency type and then design two queuing strategies: one is that the urgent patients (UPs) wedge into the GPs' queue with fixed interval (fixed priority model) and the other is that the patients have dynamic priorities for queuing (dynamic priority model). Based on the data from Radiology Information Database (RID) of West China Hospital (WCH), we develop some discrete event simulation models for CT examination according to the designed strategies. We compare the performance of different strategies on the basis of the simulation results. The strategy that patients have dynamic priorities for queuing makes the waiting time of GPs decrease by 13 minutes and the degree of satisfaction increase by 40.6%. We design a more reasonable CT examination queuing strategy to decrease patients' waiting time and increase their satisfaction degrees. PMID:27547237

Event Classification and Identification Based on the Characteristic Ellipsoid of Phasor Measurement

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

Ma, Jian; Diao, Ruisheng; Makarov, Yuri V.

2011-09-23

In this paper, a method to classify and identify power system events based on the characteristic ellipsoid of phasor measurement is presented. The decision tree technique is used to perform the event classification and identification. Event types, event locations and clearance times are identified by decision trees based on the indices of the characteristic ellipsoid. A sufficiently large number of transient events were simulated on the New England 10-machine 39-bus system based on different system configurations. Transient simulations taking into account different event types, clearance times and various locations are conducted to simulate phasor measurement. Bus voltage magnitudes and recordedmore » reactive and active power flows are used to build the characteristic ellipsoid. The volume, eccentricity, center and projection of the longest axis in the parameter space coordinates of the characteristic ellipsoids are used to classify and identify events. Results demonstrate that the characteristic ellipsoid and the decision tree are capable to detect the event type, location, and clearance time with very high accuracy.« less

Threat radar system simulations

NASA Astrophysics Data System (ADS)

Miller, L.

The capabilities, requirements, and goals of radar emitter simulators are discussed. Simulators are used to evaluate competing receiver designs, to quantify the performance envelope of a radar system, and to model the characteristics of a transmitted signal waveform. A database of candidate threat systems is developed and, in concert with intelligence data on a given weapons system, permits upgrading simulators to new projected threat capabilities. Four currently available simulation techniques are summarized, noting the usefulness of developing modular software for fast controlled-cost upgrades of simulation capabilities.

Test vs. simulation

NASA Technical Reports Server (NTRS)

Wood, Charles C.

1991-01-01

The following topics are presented in tabular form: (1) simulation capability assessments (no propulsion system test); (2) advanced vehicle simulation capability assessment; (3) systems tests identified events; (4) main propulsion test article (MPTA) testing evaluation; (5) Saturn 5, 1B, and 1 testing evaluation. Special vehicle simulation issues that are propulsion related are briefly addressed.

Using the Integration of Discrete Event and Agent-Based Simulation to Enhance Outpatient Service Quality in an Orthopedic Department.

PubMed

Kittipittayakorn, Cholada; Ying, Kuo-Ching

2016-01-01

Many hospitals are currently paying more attention to patient satisfaction since it is an important service quality index. Many Asian countries' healthcare systems have a mixed-type registration, accepting both walk-in patients and scheduled patients. This complex registration system causes a long patient waiting time in outpatient clinics. Different approaches have been proposed to reduce the waiting time. This study uses the integration of discrete event simulation (DES) and agent-based simulation (ABS) to improve patient waiting time and is the first attempt to apply this approach to solve this key problem faced by orthopedic departments. From the data collected, patient behaviors are modeled and incorporated into a massive agent-based simulation. The proposed approach is an aid for analyzing and modifying orthopedic department processes, allows us to consider far more details, and provides more reliable results. After applying the proposed approach, the total waiting time of the orthopedic department fell from 1246.39 minutes to 847.21 minutes. Thus, using the correct simulation model significantly reduces patient waiting time in an orthopedic department.

Using the Integration of Discrete Event and Agent-Based Simulation to Enhance Outpatient Service Quality in an Orthopedic Department

PubMed Central

Kittipittayakorn, Cholada

2016-01-01

Many hospitals are currently paying more attention to patient satisfaction since it is an important service quality index. Many Asian countries' healthcare systems have a mixed-type registration, accepting both walk-in patients and scheduled patients. This complex registration system causes a long patient waiting time in outpatient clinics. Different approaches have been proposed to reduce the waiting time. This study uses the integration of discrete event simulation (DES) and agent-based simulation (ABS) to improve patient waiting time and is the first attempt to apply this approach to solve this key problem faced by orthopedic departments. From the data collected, patient behaviors are modeled and incorporated into a massive agent-based simulation. The proposed approach is an aid for analyzing and modifying orthopedic department processes, allows us to consider far more details, and provides more reliable results. After applying the proposed approach, the total waiting time of the orthopedic department fell from 1246.39 minutes to 847.21 minutes. Thus, using the correct simulation model significantly reduces patient waiting time in an orthopedic department. PMID:27195606

Simulation System for Training in Laparoscopic Surgery

NASA Technical Reports Server (NTRS)

Basdogan, Cagatay; Ho, Chih-Hao

2003-01-01

A computer-based simulation system creates a visual and haptic virtual environment for training a medical practitioner in laparoscopic surgery. Heretofore, it has been common practice to perform training in partial laparoscopic surgical procedures by use of a laparoscopic training box that encloses a pair of laparoscopic tools, objects to be manipulated by the tools, and an endoscopic video camera. However, the surgical procedures simulated by use of a training box are usually poor imitations of the actual ones. The present computer-based system improves training by presenting a more realistic simulated environment to the trainee. The system includes a computer monitor that displays a real-time image of the affected interior region of the patient, showing laparoscopic instruments interacting with organs and tissues, as would be viewed by use of an endoscopic video camera and displayed to a surgeon during a laparoscopic operation. The system also includes laparoscopic tools that the trainee manipulates while observing the image on the computer monitor (see figure). The instrumentation on the tools consists of (1) position and orientation sensors that provide input data for the simulation and (2) actuators that provide force feedback to simulate the contact forces between the tools and tissues. The simulation software includes components that model the geometries of surgical tools, components that model the geometries and physical behaviors of soft tissues, and components that detect collisions between them. Using the measured positions and orientations of the tools, the software detects whether they are in contact with tissues. In the event of contact, the deformations of the tissues and contact forces are computed by use of the geometric and physical models. The image on the computer screen shows tissues deformed accordingly, while the actuators apply the corresponding forces to the distal ends of the tools. For the purpose of demonstration, the system has been set

Event Detection and Sub-state Discovery from Bio-molecular Simulations Using Higher-Order Statistics: Application To Enzyme Adenylate Kinase

PubMed Central

Ramanathan, Arvind; Savol, Andrej J.; Agarwal, Pratul K.; Chennubhotla, Chakra S.

2012-01-01

Biomolecular simulations at milli-second and longer timescales can provide vital insights into functional mechanisms. Since post-simulation analyses of such large trajectory data-sets can be a limiting factor in obtaining biological insights, there is an emerging need to identify key dynamical events and relating these events to the biological function online, that is, as simulations are progressing. Recently, we have introduced a novel computational technique, quasi-anharmonic analysis (QAA) (PLoS One 6(1): e15827), for partitioning the conformational landscape into a hierarchy of functionally relevant sub-states. The unique capabilities of QAA are enabled by exploiting anharmonicity in the form of fourth-order statistics for characterizing atomic fluctuations. In this paper, we extend QAA for analyzing long time-scale simulations online. In particular, we present HOST4MD - a higher-order statistical toolbox for molecular dynamics simulations, which (1) identifies key dynamical events as simulations are in progress, (2) explores potential sub-states and (3) identifies conformational transitions that enable the protein to access those sub-states. We demonstrate HOST4MD on micro-second time-scale simulations of the enzyme adenylate kinase in its apo state. HOST4MD identifies several conformational events in these simulations, revealing how the intrinsic coupling between the three sub-domains (LID, CORE and NMP) changes during the simulations. Further, it also identifies an inherent asymmetry in the opening/closing of the two binding sites. We anticipate HOST4MD will provide a powerful and extensible framework for detecting biophysically relevant conformational coordinates from long time-scale simulations. PMID:22733562

Evaluating resilience of DNP3-controlled SCADA systems against event buffer flooding

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

Yan, Guanhua; Nicol, David M; Jin, Dong

2010-12-16

The DNP3 protocol is widely used in SCADA systems (particularly electrical power) as a means of communicating observed sensor state information back to a control center. Typical architectures using DNP3 have a two level hierarchy, where a specialized data aggregator device receives observed state from devices within a local region, and the control center collects the aggregated state from the data aggregator. The DNP3 communication between control center and data aggregator is asynchronous with the DNP3 communication between data aggregator and relays; this leads to the possibility of completely filling a data aggregator's buffer of pending events, when a relaymore » is compromised or spoofed and sends overly many (false) events to the data aggregator. This paper investigates how a real-world SCADA device responds to event buffer flooding. A Discrete-Time Markov Chain (DTMC) model is developed for understanding this. The DTMC model is validated by a Moebius simulation model and data collected on real SCADA testbed.« less

Modeling solar energetic particle events using ENLIL heliosphere simulations

NASA Astrophysics Data System (ADS)

Luhmann, J. G.; Mays, M. L.; Odstrcil, D.; Li, Yan; Bain, H.; Lee, C. O.; Galvin, A. B.; Mewaldt, R. A.; Cohen, C. M. S.; Leske, R. A.; Larson, D.; Futaana, Y.

2017-07-01

Solar energetic particle (SEP) event modeling has gained renewed attention in part because of the availability of a decade of multipoint measurements from STEREO and L1 spacecraft at 1 AU. These observations are coupled with improving simulations of the geometry and strength of heliospheric shocks obtained by using coronagraph images to send erupted material into realistic solar wind backgrounds. The STEREO and ACE measurements in particular have highlighted the sometimes surprisingly widespread nature of SEP events. It is thus an opportune time for testing SEP models, which typically focus on protons 1-100 MeV, toward both physical insight to these observations and potentially useful space radiation environment forecasting tools. Some approaches emphasize the concept of particle acceleration and propagation from close to the Sun, while others emphasize the local field line connection to a traveling, evolving shock source. Among the latter is the previously introduced SEPMOD treatment, based on the widely accessible and well-exercised WSA-ENLIL-cone model. SEPMOD produces SEP proton time profiles at any location within the ENLIL domain. Here we demonstrate a SEPMOD version that accommodates multiple, concurrent shock sources occurring over periods of several weeks. The results illustrate the importance of considering longer-duration time periods and multiple CME contributions in analyzing, modeling, and forecasting SEP events.

Warriors Edge Simulation and Gaming System: The Squad Simulation

DTIC Science & Technology

2005-08-01

Warriors Edge Simulation and Gaming System: The Squad Simulation by Mark Thomas and Gary Moss ARL-TR-3564 August 2005...Edge Simulation and Gaming System: The Squad Simulation Mark Thomas and Gary Moss Computational and Information Sciences Directorate, ARL...2004–30 September 2004 5a. CONTRACT NUMBER 5b. GRANT NUMBER 4. TITLE AND SUBTITLE Warriors Edge Simulation and Gaming System: The Squad

A One Dimensional, Time Dependent Inlet/Engine Numerical Simulation for Aircraft Propulsion Systems

NASA Technical Reports Server (NTRS)

Garrard, Doug; Davis, Milt, Jr.; Cole, Gary

1999-01-01

The NASA Lewis Research Center (LeRC) and the Arnold Engineering Development Center (AEDC) have developed a closely coupled computer simulation system that provides a one dimensional, high frequency inlet/engine numerical simulation for aircraft propulsion systems. The simulation system, operating under the LeRC-developed Application Portable Parallel Library (APPL), closely coupled a supersonic inlet with a gas turbine engine. The supersonic inlet was modeled using the Large Perturbation Inlet (LAPIN) computer code, and the gas turbine engine was modeled using the Aerodynamic Turbine Engine Code (ATEC). Both LAPIN and ATEC provide a one dimensional, compressible, time dependent flow solution by solving the one dimensional Euler equations for the conservation of mass, momentum, and energy. Source terms are used to model features such as bleed flows, turbomachinery component characteristics, and inlet subsonic spillage while unstarted. High frequency events, such as compressor surge and inlet unstart, can be simulated with a high degree of fidelity. The simulation system was exercised using a supersonic inlet with sixty percent of the supersonic area contraction occurring internally, and a GE J85-13 turbojet engine.

Simulation of air admission in a propeller hydroturbine during transient events

NASA Astrophysics Data System (ADS)

Nicolle, J.; Morissette, J.-F.

2016-11-01

In this study, multiphysic simulations are carried out in order to model fluid loading and structural stresses on propeller blades during startup and runaway. It is found that air admission plays an important role during these transient events and that biphasic simulations are therefore required. At the speed no load regime, a large air pocket with vertical free surface forms in the centre of the runner displacing the water flow near the shroud. This significantly affects the torque developed on the blades and thus structural loading. The resulting pressures are applied to a quasi-static structural model and good agreement is obtained with experimental strain gauge data.

Event-triggered fault detection for a class of discrete-time linear systems using interval observers.

PubMed

Zhang, Zhi-Hui; Yang, Guang-Hong

2017-05-01

This paper provides a novel event-triggered fault detection (FD) scheme for discrete-time linear systems. First, an event-triggered interval observer is proposed to generate the upper and lower residuals by taking into account the influence of the disturbances and the event error. Second, the robustness of the residual interval against the disturbances and the fault sensitivity are improved by introducing l 1 and H ∞ performances. Third, dilated linear matrix inequalities are used to decouple the Lyapunov matrices from the system matrices. The nonnegative conditions for the estimation error variables are presented with the aid of the slack matrix variables. This technique allows considering a more general Lyapunov function. Furthermore, the FD decision scheme is proposed by monitoring whether the zero value belongs to the residual interval. It is shown that the information communication burden is reduced by designing the event-triggering mechanism, while the FD performance can still be guaranteed. Finally, simulation results demonstrate the effectiveness of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Instrumented Architectural Simulation System

NASA Technical Reports Server (NTRS)

Delagi, B. A.; Saraiya, N.; Nishimura, S.; Byrd, G.

1987-01-01

Simulation of systems at an architectural level can offer an effective way to study critical design choices if (1) the performance of the simulator is adequate to examine designs executing significant code bodies, not just toy problems or small application fragements, (2) the details of the simulation include the critical details of the design, (3) the view of the design presented by the simulator instrumentation leads to useful insights on the problems with the design, and (4) there is enough flexibility in the simulation system so that the asking of unplanned questions is not suppressed by the weight of the mechanics involved in making changes either in the design or its measurement. A simulation system with these goals is described together with the approach to its implementation. Its application to the study of a particular class of multiprocessor hardware system architectures is illustrated.

Identification of coronal heating events in 3D simulations

NASA Astrophysics Data System (ADS)

Kanella, Charalambos; Gudiksen, Boris V.

2017-07-01

Context. The solar coronal heating problem has been an open question in the science community since 1939. One of the proposed models for the transport and release of mechanical energy generated in the sub-photospheric layers and photosphere is the magnetic reconnection model that incorporates Ohmic heating, which releases a part of the energy stored in the magnetic field. In this model many unresolved flaring events occur in the solar corona, releasing enough energy to heat the corona. Aims: The problem with the verification and quantification of this model is that we cannot resolve small scale events due to limitations of the current observational instrumentation. Flaring events have scaling behavior extending from large X-class flares down to the so far unobserved nanoflares. Histograms of observable characteristics of flares show powerlaw behavior for energy release rate, size, and total energy. Depending on the powerlaw index of the energy release, nanoflares might be an important candidate for coronal heating; we seek to find that index. Methods: In this paper we employ a numerical three-dimensional (3D)-magnetohydrodynamic (MHD) simulation produced by the numerical code Bifrost, which enables us to look into smaller structures, and a new technique to identify the 3D heating events at a specific instant. The quantity we explore is the Joule heating, a term calculated directly by the code, which is explicitly correlated with the magnetic reconnection because it depends on the curl of the magnetic field. Results: We are able to identify 4136 events in a volume 24 × 24 × 9.5 Mm3 (I.e., 768 × 786 × 331 grid cells) of a specific snapshot. We find a powerlaw slope of the released energy per second equal to αP = 1.5 ± 0.02, and two powerlaw slopes of the identified volume equal to αV = 1.53 ± 0.03 and αV = 2.53 ± 0.22. The identified energy events do not represent all the released energy, but of the identified events, the total energy of the largest events

StratBAM: A Discrete-Event Simulation Model to Support Strategic Hospital Bed Capacity Decisions.

PubMed

Devapriya, Priyantha; Strömblad, Christopher T B; Bailey, Matthew D; Frazier, Seth; Bulger, John; Kemberling, Sharon T; Wood, Kenneth E

2015-10-01

The ability to accurately measure and assess current and potential health care system capacities is an issue of local and national significance. Recent joint statements by the Institute of Medicine and the Agency for Healthcare Research and Quality have emphasized the need to apply industrial and systems engineering principles to improving health care quality and patient safety outcomes. To address this need, a decision support tool was developed for planning and budgeting of current and future bed capacity, and evaluating potential process improvement efforts. The Strategic Bed Analysis Model (StratBAM) is a discrete-event simulation model created after a thorough analysis of patient flow and data from Geisinger Health System's (GHS) electronic health records. Key inputs include: timing, quantity and category of patient arrivals and discharges; unit-level length of care; patient paths; and projected patient volume and length of stay. Key outputs include: admission wait time by arrival source and receiving unit, and occupancy rates. Electronic health records were used to estimate parameters for probability distributions and to build empirical distributions for unit-level length of care and for patient paths. Validation of the simulation model against GHS operational data confirmed its ability to model real-world data consistently and accurately. StratBAM was successfully used to evaluate the system impact of forecasted patient volumes and length of stay in terms of patient wait times, occupancy rates, and cost. The model is generalizable and can be appropriately scaled for larger and smaller health care settings.

Distributed convex optimisation with event-triggered communication in networked systems

NASA Astrophysics Data System (ADS)

Liu, Jiayun; Chen, Weisheng

2016-12-01

This paper studies the distributed convex optimisation problem over directed networks. Motivated by practical considerations, we propose a novel distributed zero-gradient-sum optimisation algorithm with event-triggered communication. Therefore, communication and control updates just occur at discrete instants when some predefined condition satisfies. Thus, compared with the time-driven distributed optimisation algorithms, the proposed algorithm has the advantages of less energy consumption and less communication cost. Based on Lyapunov approaches, we show that the proposed algorithm makes the system states asymptotically converge to the solution of the problem exponentially fast and the Zeno behaviour is excluded. Finally, simulation example is given to illustrate the effectiveness of the proposed algorithm.

Simulation of rainfall-runoff for major flash flood events in Karachi

NASA Astrophysics Data System (ADS)

Zafar, Sumaira

2016-07-01

Metropolitan city Karachi has strategic importance for Pakistan. With the each passing decade the city is facing urban sprawl and rapid population growth. These rapid changes directly affecting the natural resources of city including its drainage pattern. Karachi has three major cities Malir River with the catchment area of 2252 sqkm and Lyari River has catchment area about 470.4 sqkm. These are non-perennial rivers and active only during storms. Change of natural surfaces into hard pavement causing an increase in rainfall-runoff response. Curve Number is increased which is now causing flash floods in the urban locality of Karachi. There is only one gauge installed on the upstream of the river but there no record for the discharge. Only one gauge located at the upstream is not sufficient for discharge measurements. To simulate the maximum discharge of Malir River rainfall (1985 to 2014) data were collected from Pakistan meteorological department. Major rainfall events use to simulate the rainfall runoff. Maximum rainfall-runoff response was recorded in during 1994, 2007 and 2013. This runoff causes damages and inundation in floodplain areas of Karachi. These flash flooding events not only damage the property but also cause losses of lives

Event-Triggered Distributed Control of Nonlinear Interconnected Systems Using Online Reinforcement Learning With Exploration.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-09-07

In this paper, a distributed control scheme for an interconnected system composed of uncertain input affine nonlinear subsystems with event triggered state feedback is presented by using a novel hybrid learning scheme-based approximate dynamic programming with online exploration. First, an approximate solution to the Hamilton-Jacobi-Bellman equation is generated with event sampled neural network (NN) approximation and subsequently, a near optimal control policy for each subsystem is derived. Artificial NNs are utilized as function approximators to develop a suite of identifiers and learn the dynamics of each subsystem. The NN weight tuning rules for the identifier and event-triggering condition are derived using Lyapunov stability theory. Taking into account, the effects of NN approximation of system dynamics and boot-strapping, a novel NN weight update is presented to approximate the optimal value function. Finally, a novel strategy to incorporate exploration in online control framework, using identifiers, is introduced to reduce the overall cost at the expense of additional computations during the initial online learning phase. System states and the NN weight estimation errors are regulated and local uniformly ultimately bounded results are achieved. The analytical results are substantiated using simulation studies.

Feasibility of performing high resolution cloud-resolving simulations of historic extreme events: The San Fruttuoso (Liguria, italy) case of 1915.

NASA Astrophysics Data System (ADS)

Parodi, Antonio; Boni, Giorgio; Ferraris, Luca; Gallus, William; Maugeri, Maurizio; Molini, Luca; Siccardi, Franco

2017-04-01

Recent studies show that highly localized and persistent back-building mesoscale convective systems represent one of the most dangerous flash-flood producing storms in the north-western Mediterranean area. Substantial warming of the Mediterranean Sea in recent decades raises concerns over possible increases in frequency or intensity of these types of events as increased atmospheric temperatures generally support increases in water vapor content. Analyses of available historical records do not provide a univocal answer, since these may be likely affected by a lack of detailed observations for older events. In the present study, 20th Century Reanalysis Project initial and boundary condition data in ensemble mode are used to address the feasibility of performing cloud-resolving simulations with 1 km horizontal grid spacing of a historic extreme event that occurred over Liguria (Italy): The San Fruttuoso case of 1915. The proposed approach focuses on the ensemble Weather Research and Forecasting (WRF) model runs, as they are the ones most likely to best simulate the event. It is found that these WRF runs generally do show wind and precipitation fields that are consistent with the occurrence of highly localized and persistent back-building mesoscale convective systems, although precipitation peak amounts are underestimated. Systematic small north-westward position errors with regard to the heaviest rain and strongest convergence areas imply that the Reanalysis members may not be adequately representing the amount of cool air over the Po Plain outflowing into the Liguria Sea through the Apennines gap. Regarding the role of historical data sources, this study shows that in addition to Reanalysis products, unconventional data, such as historical meteorological bulletins, newspapers and even photographs can be very valuable sources of knowledge in the reconstruction of past extreme events.

Simulation of the National Aerospace System for Safety Analysis

NASA Technical Reports Server (NTRS)

Pritchett, Amy; Goldsman, Dave; Statler, Irv (Technical Monitor)

2002-01-01

Work started on this project on January 1, 1999, the first year of the grant. Following the outline of the grant proposal, a simulator architecture has been established which can incorporate the variety of types of models needed to accurately simulate national airspace dynamics. For the sake of efficiency, this architecture was based on an established single-aircraft flight simulator, the Reconfigurable Flight Simulator (RFS), already developed at Georgia Tech. Likewise, in the first year substantive changes and additions were made to the RFS to convert it into a simulation of the National Airspace System, with the flexibility to incorporate many types of models: aircraft models; controller models; airspace configuration generators; discrete event generators; embedded statistical functions; and display and data outputs. The architecture has been developed with the capability to accept any models of these types; due to its object-oriented structure, individual simulator components can be added and removed during run-time, and can be compiled separately. Simulation objects from other projects should be easy to convert to meet architecture requirements, with the intent that both this project may now be able to incorporate established simulation components from other projects, and that other projects may easily use this simulation without significant time investment.

Comparative Effectiveness of Tacrolimus-Based Steroid Sparing versus Steroid Maintenance Regimens in Kidney Transplantation: Results from Discrete Event Simulation.

PubMed

Desai, Vibha C A; Ferrand, Yann; Cavanaugh, Teresa M; Kelton, Christina M L; Caro, J Jaime; Goebel, Jens; Heaton, Pamela C

2017-10-01

Corticosteroids used as immunosuppressants to prevent acute rejection (AR) and graft loss (GL) following kidney transplantation are associated with serious cardiovascular and other adverse events. Evidence from short-term randomized controlled trials suggests that many patients on a tacrolimus-based immunosuppressant regimen can withdraw from steroids without increased AR or GL risk. To measure the long-term tradeoff between GL and adverse events for a heterogeneous-risk population and determine the optimal timing of steroid withdrawal. A discrete event simulation was developed including, as events, AR, GL, myocardial infarction (MI), stroke, cytomegalovirus, and new onset diabetes mellitus (NODM), among others. Data from the United States Renal Data System were used to estimate event-specific parametric regressions, which accounted for steroid-sparing regimen (avoidance, early 7-d withdrawal, 6-mo withdrawal, 12-mo withdrawal, and maintenance) as well as patients' demographics, immunologic risks, and comorbidities. Regression-equation results were used to derive individual time-to-event Weibull distributions, used, in turn, to simulate the course of patients over 20 y. Patients on steroid avoidance or an early-withdrawal regimen were more likely to experience AR (45.9% to 55.0% v. 33.6%, P < 0.05) and GL (51.5% to 68.8% v. 37.8%, P < 0.05) compared to patients on steroid maintenance. Patients in 6-mo and 12-mo steroid withdrawal groups were less likely to experience MI (11.1% v. 13.3%, P < 0.05), NODM (30.7% to 34.4% v. 37.7%, P < 0.05), and cardiac death (29.9% to 30.5% v. 32.4%, P < 0.05), compared to steroid maintenance. Strategies of 6- and 12-mo steroid withdrawal post-kidney transplantation are expected to reduce the rates of adverse cardiovascular events and other outcomes with no worsening of AR or GL rates compared with steroid maintenance.

Surface Management System Departure Event Data Analysis

NASA Technical Reports Server (NTRS)

Monroe, Gilena A.

2010-01-01

This paper presents a data analysis of the Surface Management System (SMS) performance of departure events, including push-back and runway departure events.The paper focuses on the detection performance, or the ability to detect departure events, as well as the prediction performance of SMS. The results detail a modest overall detection performance of push-back events and a significantly high overall detection performance of runway departure events. The overall detection performance of SMS for push-back events is approximately 55%.The overall detection performance of SMS for runway departure events nears 100%. This paper also presents the overall SMS prediction performance for runway departure events as well as the timeliness of the Aircraft Situation Display for Industry data source for SMS predictions.

Simulation of an Extreme Off Season Rainy Event over Senegal Using WRF ARW Model: A focus on dynamic, thermodynamic processes and predictability

NASA Astrophysics Data System (ADS)

Sarr, A.

2016-12-01

This study investigates less known weather events, Off Season Rain affecting during boreal winter Western parts of Sahel region mainly, Senegal, Cape Verde and Mauritania. They are characterized by cloudy conditions at mid level, which can trigger light long lasting rains. In January 2002, an extreme case occurred from 09 to 11th producing unusual heavy rains, which had dramatic consequences on livestock and irrigated crops. The Weather and Research Forecast model (WRF ARW version 3.4) is used to simulate the event, which affected the western coast around the land/ocean interface and caused huge damages in Senegal and Mauritania. The model was able to reasonably simulate the event and its intensity 2 to 3 days in advance, demonstrating the usefulness of such a tools for early warning system (EWS), which could help mitigate the impacts. The location of the rain band was closer to the observed situation in higher resolution domains. The study showed keys dynamic and thermodynamic conditions associated with the event. Precipitable water (PW) evolution played a central role on the intensity of the event. The deep trough, associated with the disturbance, forced a northeast transport of moisture from the Inter Tropical Convergence Zone (ITCZ) over the Ocean towards Senegal and Mauritania.

High Level Architecture Distributed Space System Simulation for Simulation Interoperability Standards Organization Simulation Smackdown

NASA Technical Reports Server (NTRS)

Li, Zuqun

2011-01-01

Modeling and Simulation plays a very important role in mission design. It not only reduces design cost, but also prepares astronauts for their mission tasks. The SISO Smackdown is a simulation event that facilitates modeling and simulation in academia. The scenario of this year s Smackdown was to simulate a lunar base supply mission. The mission objective was to transfer Earth supply cargo to a lunar base supply depot and retrieve He-3 to take back to Earth. Federates for this scenario include the environment federate, Earth-Moon transfer vehicle, lunar shuttle, lunar rover, supply depot, mobile ISRU plant, exploratory hopper, and communication satellite. These federates were built by teams from all around the world, including teams from MIT, JSC, University of Alabama in Huntsville, University of Bordeaux from France, and University of Genoa from Italy. This paper focuses on the lunar shuttle federate, which was programmed by the USRP intern team from NASA JSC. The shuttle was responsible for provide transportation between lunar orbit and the lunar surface. The lunar shuttle federate was built using the NASA standard simulation package called Trick, and it was extended with HLA functions using TrickHLA. HLA functions of the lunar shuttle federate include sending and receiving interaction, publishing and subscribing attributes, and packing and unpacking fixed record data. The dynamics model of the lunar shuttle was modeled with three degrees of freedom, and the state propagation was obeying the law of two body dynamics. The descending trajectory of the lunar shuttle was designed by first defining a unique descending orbit in 2D space, and then defining a unique orbit in 3D space with the assumption of a non-rotating moon. Finally this assumption was taken away to define the initial position of the lunar shuttle so that it will start descending a second after it joins the execution. VPN software from SonicWall was used to connect federates with RTI during testing

Event management for large scale event-driven digital hardware spiking neural networks.

PubMed

Caron, Louis-Charles; D'Haene, Michiel; Mailhot, Frédéric; Schrauwen, Benjamin; Rouat, Jean

2013-09-01

The interest in brain-like computation has led to the design of a plethora of innovative neuromorphic systems. Individually, spiking neural networks (SNNs), event-driven simulation and digital hardware neuromorphic systems get a lot of attention. Despite the popularity of event-driven SNNs in software, very few digital hardware architectures are found. This is because existing hardware solutions for event management scale badly with the number of events. This paper introduces the structured heap queue, a pipelined digital hardware data structure, and demonstrates its suitability for event management. The structured heap queue scales gracefully with the number of events, allowing the efficient implementation of large scale digital hardware event-driven SNNs. The scaling is linear for memory, logarithmic for logic resources and constant for processing time. The use of the structured heap queue is demonstrated on a field-programmable gate array (FPGA) with an image segmentation experiment and a SNN of 65,536 neurons and 513,184 synapses. Events can be processed at the rate of 1 every 7 clock cycles and a 406×158 pixel image is segmented in 200 ms. Copyright © 2013 Elsevier Ltd. All rights reserved.

WRF simulation of downslope wind events in coastal Santa Barbara County

NASA Astrophysics Data System (ADS)

Cannon, Forest; Carvalho, Leila M. V.; Jones, Charles; Hall, Todd; Gomberg, David; Dumas, John; Jackson, Mark

2017-07-01

The National Weather Service (NWS) considers frequent gusty downslope winds, accompanied by rapid warming and decreased relative humidity, among the most significant weather events affecting southern California coastal areas in the vicinity of Santa Barbara (SB). These extreme conditions, commonly known as "sundowners", have affected the evolution of all major wildfires that impacted SB in recent years. Sundowners greatly increase fire, aviation and maritime navigation hazards and are thus a priority for regional forecasting. Currently, the NWS employs the Weather Research Forecasting (WRF) model at 2 km resolution to complement forecasts at regional-to-local scales. However, no systematic study has been performed to evaluate the skill of WRF in simulating sundowners. This research presents a case study of an 11-day period in spring 2004 during which sundowner events were observed on multiple nights. We perform sensitivity experiments for WRF using available observations for validation and demonstrate that WRF is skillful in representing the general mesoscale structure of these events, though important shortcomings exist. Furthermore, we discuss the generation and evolution of sundowners during the case study using the best performing configuration, and compare these results to hindcasts for two major SB fires. Unique, but similar, profiles of wind and stability are observed over SB between case studies despite considerable differences in large-scale circulation, indicating that common conditions may exist across all events. These findings aid in understanding the evolution of sundowner events and are potentially valuable for event prediction.

Simulation of Top Quark Pair Production as a Background for Higgs Events at the Compact Muon Solenoid

NASA Astrophysics Data System (ADS)

Justus, Christopher

2005-04-01

In this study, we simulated top-antitop (tt-bar) quark events at the Compact Muon Solenoid (CMS), an experiment presently being constructed at the Large Hadron Collider in Geneva, Switzerland. The tt-bar process is an important background for Higgs events. We used a chain of software to simulate and reconstruct processes that will occur inside the detector. CMKIN was used to generate and store Monte Carlo Events. OSCAR, a GEANT4 based CMS detector simulator, was used to simulate the CMS detector and how particles would interact with the detector. Next, we used ORCA to simulate the response of the readout electronics at CMS. Last, we used the Jet/MET Root maker to create root files of jets and missing energy. We are now using this software analysis chain to complete a systematic study of initial state radiation at hadron colliders. This study is essential because tt-bar is the main background for the Higgs boson and these processes are extremely sensitive to initial state radiation. Results of our initial state radiation study will be presented. We started this study at the new LHC Physics Center (LPC) located at Fermi National Accelerator Laboratory, and we are now completing the study at the University of Rochester.

Crash avoidance in response to challenging driving events: The roles of age, serialization, and driving simulator platform.

PubMed

Bélanger, Alexandre; Gagnon, Sylvain; Stinchcombe, Arne

2015-09-01

We examined the crash avoidance behaviors of older and middle-aged drivers in reaction to six simulated challenging road events using two different driving simulator platforms. Thirty-five healthy adults aged 21-36 years old (M=28.9±3.96) and 35 healthy adults aged 65-83 years old (M=72.1±4.34) were tested using a mid-level simulator, and 27 adults aged 21-38 years old (M=28.6±6.63) and 27 healthy adults aged 65-83 years old (M=72.7±5.39) were tested on a low-cost desktop simulator. Participants completed a set of six challenging events varying in terms of the maneuvers required, avoiding space given, directional avoidance cues, and time pressure. Results indicated that older drivers showed higher crash risk when events required multiple synchronized reactions. In situations that required simultaneous use of steering and braking, older adults tended to crash significantly more frequently. As for middle-aged drivers, their crashes were attributable to faster driving speed. The same age-related driving patterns were observed across simulator platforms. Our findings support the hypothesis that older adults tend to react serially while engaging in cognitively challenging road maneuvers. Copyright © 2015 Elsevier Ltd. All rights reserved.

Detection and Attribution of Simulated Climatic Extreme Events and Impacts: High Sensitivity to Bias Correction

NASA Astrophysics Data System (ADS)

Sippel, S.; Otto, F. E. L.; Forkel, M.; Allen, M. R.; Guillod, B. P.; Heimann, M.; Reichstein, M.; Seneviratne, S. I.; Kirsten, T.; Mahecha, M. D.

2015-12-01

Understanding, quantifying and attributing the impacts of climatic extreme events and variability is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit pronounced biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. We assess how biases and their correction affect the quantification and attribution of simulated extremes and variability in i) climatological variables and ii) impacts on ecosystem functioning as simulated by a terrestrial biosphere model. Our study demonstrates that assessments of simulated climatic extreme events and impacts in the terrestrial biosphere are highly sensitive to bias correction schemes with major implications for the detection and attribution of these events. We introduce a novel ensemble-based resampling scheme based on a large regional climate model ensemble generated by the distributed weather@home setup[1], which fully preserves the physical consistency and multivariate correlation structure of the model output. We use extreme value statistics to show that this procedure considerably improves the representation of climatic extremes and variability. Subsequently, biosphere-atmosphere carbon fluxes are simulated using a terrestrial ecosystem model (LPJ-GSI) to further demonstrate the sensitivity of ecosystem impacts to the methodology of bias correcting climate model output. We find that uncertainties arising from bias correction schemes are comparable in magnitude to model structural and parameter uncertainties. The present study consists of a first attempt to alleviate climate model biases in a physically consistent way and demonstrates that this yields improved simulations of

Uncertainty estimation of simulated water levels for the Mitch flood event in Tegucigalpa

NASA Astrophysics Data System (ADS)

Fuentes Andino, Diana Carolina; Halldin, Sven; Keith, Beven; Chong-Yu, Xu

2013-04-01

Hurricane Mitch in 1998 left a devastating flood in Tegucigalpa, the capital city of Honduras. Due to the extremely large magnitude of the Mitch flood, hydrometric measurements were not taken during the event. However, post-event indirect measurements of the discharge were obtained by the U.S. Geological Survey (USGS) and post-event surveyed high water marks were obtained by the Japan International Cooperation agency (JICA). This work proposes a methodology to simulate the water level during the Mitch event when the available data is associated with large uncertainty. The results of the two-dimensional hydrodynamic model LISFLOOD-FP will be evaluated using the Generalized Uncertainty Estimation (GLUE) framework. The main challenge in the proposed methodology is to formulate an approach to evaluate the model results when there are large uncertainties coming from both the model parameters and the evaluation data.

INTRODUCTION: New trends in simulating colloids and self-assembling systems New trends in simulating colloids and self-assembling systems

NASA Astrophysics Data System (ADS)

Foffi, Giuseppe; Kahl, Gerhard

2010-03-01

Interest in colloidal physics has grown at an incredible pace over the past few decades. To a great extent this remarkable development is due to the fact that colloidal systems are highly relevant in everyday applications as well as in basic research. On the one hand, colloids are ubiquitous in our daily lives and a deeper understanding of their physical properties is therefore highly relevant in applied areas ranging from biomedicine over food sciences to technology. On the other hand, a seemingly unlimited freedom in designing colloidal particles with desired properties in combination with new, low-cost experimental techniques, make them—compared to hard matter systems—considerably more attractive for a wide range of basic investigations. All these investigations are carried out with close cooperation between experimentalists, theoreticians and simulators, reuniting thereby, on a highly interdisciplinary level, physicists, chemists, and biologists. In an effort to give credit to some of these new developments in colloidal physics, two proposals for workshops were submitted independently to CECAM in the fall of 2008; both of them were approved and organized as consecutive events. This decision undoubtedly had many practical and organizational advantages. Furthermore, and from the scientific point of view more relevant, the organizers could welcome in total 69 participants, presenting 42 oral and 21 poster contributions. We are proud to say that nearly all the colleagues that we contacted at submission time accepted our invitation, and we are happy to say that the number of additional participants was rather high. Due to the fact that both workshops took place within one week, quite a few participants, registered originally for one of these meetings, extended their participation to the other event also. In total, 23 contributions have been submitted to this special issue, which cover the main scientific topics addressed in these workshops. We consider this

Capacity planning for maternal-fetal medicine using discrete event simulation.

PubMed

Ferraro, Nicole M; Reamer, Courtney B; Reynolds, Thomas A; Howell, Lori J; Moldenhauer, Julie S; Day, Theodore Eugene

2015-07-01

Maternal-fetal medicine is a rapidly growing field requiring collaboration from many subspecialties. We provide an evidence-based estimate of capacity needs for our clinic, as well as demonstrate how simulation can aid in capacity planning in similar environments. A Discrete Event Simulation of the Center for Fetal Diagnosis and Treatment and Special Delivery Unit at The Children's Hospital of Philadelphia was designed and validated. This model was then used to determine the time until demand overwhelms inpatient bed availability under increasing capacity. No significant deviation was found between historical inpatient censuses and simulated censuses for the validation phase (p = 0.889). Prospectively increasing capacity was found to delay time to balk (the inability of the center to provide bed space for a patient in need of admission). With current capacity, the model predicts mean time to balk of 276 days. Adding three beds delays mean time to first balk to 762 days; an additional six beds to 1,335 days. Providing sufficient access is a patient safety issue, and good planning is crucial for targeting infrastructure investments appropriately. Computer-simulated analysis can provide an evidence base for both medical and administrative decision making in a complex clinical environment. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Event-Triggered Distributed Approximate Optimal State and Output Control of Affine Nonlinear Interconnected Systems.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-06-08

This paper presents an approximate optimal distributed control scheme for a known interconnected system composed of input affine nonlinear subsystems using event-triggered state and output feedback via a novel hybrid learning scheme. First, the cost function for the overall system is redefined as the sum of cost functions of individual subsystems. A distributed optimal control policy for the interconnected system is developed using the optimal value function of each subsystem. To generate the optimal control policy, forward-in-time, neural networks are employed to reconstruct the unknown optimal value function at each subsystem online. In order to retain the advantages of event-triggered feedback for an adaptive optimal controller, a novel hybrid learning scheme is proposed to reduce the convergence time for the learning algorithm. The development is based on the observation that, in the event-triggered feedback, the sampling instants are dynamic and results in variable interevent time. To relax the requirement of entire state measurements, an extended nonlinear observer is designed at each subsystem to recover the system internal states from the measurable feedback. Using a Lyapunov-based analysis, it is demonstrated that the system states and the observer errors remain locally uniformly ultimately bounded and the control policy converges to a neighborhood of the optimal policy. Simulation results are presented to demonstrate the performance of the developed controller.

Real time digital propulsion system simulation for manned flight simulators

NASA Technical Reports Server (NTRS)

Mihaloew, J. R.; Hart, C. E.

1978-01-01

A real time digital simulation of a STOL propulsion system was developed which generates significant dynamics and internal variables needed to evaluate system performance and aircraft interactions using manned flight simulators. The simulation ran at a real-to-execution time ratio of 8.8. The model was used in a piloted NASA flight simulator program to evaluate the simulation technique and the propulsion system digital control. The simulation is described and results shown. Limited results of the flight simulation program are also presented.

Pesticide trapping efficiency of a modified backwater wetland using a simulated runoff event

USDA-ARS?s Scientific Manuscript database

This study examined the trapping efficiency of a modified backwater wetland amended with a mixture of three pesticides, atrazine, metolachlor, and fipronil, using a simulated runoff event. The 700 m long, 25 m wide wetland, located along the Coldwater River in Tunica County, Mississippi, was modifie...

Realization of planning design of mechanical manufacturing system by Petri net simulation model

NASA Astrophysics Data System (ADS)

Wu, Yanfang; Wan, Xin; Shi, Weixiang

1991-09-01

Planning design is to work out a more overall long-term plan. In order to guarantee a mechanical manufacturing system (MMS) designed to obtain maximum economical benefit, it is necessary to carry out a reasonable planning design for the system. First, some principles on planning design for MMS are introduced. Problems of production scheduling and their decision rules for computer simulation are presented. Realizable method of each production scheduling decision rule in Petri net model is discussed. Second, the solution of conflict rules for conflict problems during running Petri net is given. Third, based on the Petri net model of MMS which includes part flow and tool flow, according to the principle of minimum event time advance, a computer dynamic simulation of the Petri net model, that is, a computer dynamic simulation of MMS, is realized. Finally, the simulation program is applied to a simulation exmple, so the scheme of a planning design for MMS can be evaluated effectively.

Reducing ambulance response times using discrete event simulation.

PubMed

Wei Lam, Sean Shao; Zhang, Zhong Cheng; Oh, Hong Choon; Ng, Yih Ying; Wah, Win; Hock Ong, Marcus Eng

2014-01-01

The objectives of this study are to develop a discrete-event simulation (DES) model for the Singapore Emergency Medical Services (EMS), and to demonstrate the utility of this DES model for the evaluation of different policy alternatives to improve ambulance response times. A DES model was developed based on retrospective emergency call data over a continuous 6-month period in Singapore. The main outcome measure is the distribution of response times. The secondary outcome measure is ambulance utilization levels based on unit hour utilization (UHU) ratios. The DES model was used to evaluate different policy options in order to improve the response times, while maintaining reasonable fleet utilization. Three policy alternatives looking at the reallocation of ambulances, the addition of new ambulances, and alternative dispatch policies were evaluated. Modifications of dispatch policy combined with the reallocation of existing ambulances were able to achieve response time performance equivalent to that of adding 10 ambulances. The median (90th percentile) response time was 7.08 minutes (12.69 minutes). Overall, this combined strategy managed to narrow the gap between the ideal and existing response time distribution by 11-13%. Furthermore, the median UHU under this combined strategy was 0.324 with an interquartile range (IQR) of 0.047 versus a median utilization of 0.285 (IQR of 0.051) resulting from the introduction of additional ambulances. Response times were shown to be improved via a more effective reallocation of ambulances and dispatch policy. More importantly, the response time improvements were achieved without a reduction in the utilization levels and additional costs associated with the addition of ambulances. We demonstrated the effective use of DES as a versatile platform to model the dynamic system complexities of Singapore's national EMS systems for the evaluation of operational strategies to improve ambulance response times.

The Time Dependent Propensity Function for Acceleration of Spatial Stochastic Simulation of Reaction-Diffusion Systems

PubMed Central

Wu, Sheng; Li, Hong; Petzold, Linda R.

2015-01-01

The inhomogeneous stochastic simulation algorithm (ISSA) is a fundamental method for spatial stochastic simulation. However, when diffusion events occur more frequently than reaction events, simulating the diffusion events by ISSA is quite costly. To reduce this cost, we propose to use the time dependent propensity function in each step. In this way we can avoid simulating individual diffusion events, and use the time interval between two adjacent reaction events as the simulation stepsize. We demonstrate that the new algorithm can achieve orders of magnitude efficiency gains over widely-used exact algorithms, scales well with increasing grid resolution, and maintains a high level of accuracy. PMID:26609185

System-Level Reuse of Space Systems Simulations

NASA Technical Reports Server (NTRS)

Hazen, Michael R.; Williams, Joseph C.

2004-01-01

One of the best ways to enhance space systems simulation fidelity is to leverage off of (reuse) existing high-fidelity simulations. But what happens when the model you would like to reuse is in a different coding language or other barriers arise that make one want to just start over with a clean sheet of paper? Three diverse system-level simulation reuse case studies are described based on experience to date in the development of NASA's Space Station Training Facility (SSTF) at the Johnson Space Center in Houston, Texas. Case studies include (a) the Boeing/Rocketdyne-provided Electrical Power Simulation (EPSIM), (b) the NASA Automation and Robotics Division-provided TRICK robotics systems model, and (c) the Russian Space Agency- provided Russian Segment Trainer. In each case, there was an initial tendency to dismiss simulation reuse candidates based on an apparent lack of suitability. A more careful examination based on a more structured assessment of architectural and requirements-oriented representations of the reuse candidates revealed significant reuse potential. Specific steps used to conduct the detailed assessments are discussed. The steps include the following: 1) Identifying reuse candidates; 2) Requirements compatibility assessment; 3) Maturity assessment; 4) Life-cycle cost determination; and 5) Risk assessment. Observations and conclusions are presented related to the real cost of system-level simulation component reuse. Finally, lessons learned that relate to maximizing the benefits of space systems simulation reuse are shared. These concepts should be directly applicable for use in the development of space systems simulations in the future.

BEEC: An event generator for simulating the Bc meson production at an e+e- collider

NASA Astrophysics Data System (ADS)

Yang, Zhi; Wu, Xing-Gang; Wang, Xian-You

2013-12-01

The Bc meson is a doubly heavy quark-antiquark bound state and carries flavors explicitly, which provides a fruitful laboratory for testing potential models and understanding the weak decay mechanisms for heavy flavors. In view of the prospects in Bc physics at the hadronic colliders such as Tevatron and LHC, Bc physics is attracting more and more attention. It has been shown that a high luminosity e+e- collider running around the Z0-peak is also helpful for studying the properties of Bc meson and has its own advantages. For this purpose, we write down an event generator for simulating Bc meson production through e+e- annihilation according to relevant publications. We name it BEEC, in which the color-singlet S-wave and P-wave (cb¯)-quarkonium states together with the color-octet S-wave (cb¯)-quarkonium states can be generated. BEEC can also be adopted to generate the similar charmonium and bottomonium states via the semi-exclusive channels e++e-→|(QQ¯)[n]>+Q+Q¯ with Q=b and c respectively. To increase the simulation efficiency, we simplify the amplitude as compact as possible by using the improved trace technology. BEEC is a Fortran program written in a PYTHIA-compatible format and is written in a modular structure, one may apply it to various situations or experimental environments conveniently by using the GNU C compiler make. A method to improve the efficiency of generating unweighted events within PYTHIA environment is proposed. Moreover, BEEC will generate a standard Les Houches Event data file that contains useful information of the meson and its accompanying partons, which can be conveniently imported into PYTHIA to do further hadronization and decay simulation. Catalogue identifier: AEQC_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEQC_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in

Simulating Sustainment for an Unmanned Logistics System Concept of Operation in Support of Distributed Operations

DTIC Science & Technology

2017-06-01

designed experiment to model and explore a ship-to-shore logistics process supporting dispersed units via three types of ULSs, which vary primarily in...systems, simulation, discrete event simulation, design of experiments, data analysis, simplekit, nearly orthogonal and balanced designs 15. NUMBER OF... designed experiment to model and explore a ship-to-shore logistics process supporting dispersed units via three types of ULSs, which vary primarily

Budget impact analysis of thrombolysis for stroke in Spain: a discrete event simulation model.

PubMed

Mar, Javier; Arrospide, Arantzazu; Comas, Mercè

2010-01-01

Thrombolysis within the first 3 hours after the onset of symptoms of a stroke has been shown to be a cost-effective treatment because treated patients are 30% more likely than nontreated patients to have no residual disability. The objective of this study was to calculate by means of a discrete event simulation model the budget impact of thrombolysis in Spain. The budget impact analysis was based on stroke incidence rates and the estimation of the prevalence of stroke-related disability in Spain and its translation to hospital and social costs. A discrete event simulation model was constructed to represent the flow of patients with stroke in Spain. If 10% of patients with stroke from 2000 to 2015 would receive thrombolytic treatment, the prevalence of dependent patients in 2015 would decrease from 149,953 to 145,922. For the first 6 years, the cost of intervention would surpass the savings. Nevertheless, the number of cases in which patient dependency was avoided would steadily increase, and after 2006 the cost savings would be greater, with a widening difference between the cost of intervention and the cost of nonintervention, until 2015. The impact of thrombolysis on society's health and social budget indicates a net benefit after 6 years, and the improvement in health grows continuously. The validation of the model demonstrates the adequacy of the discrete event simulation approach in representing the epidemiology of stroke to calculate the budget impact.

Parallel discrete-event simulation schemes with heterogeneous processing elements.

PubMed

Kim, Yup; Kwon, Ikhyun; Chae, Huiseung; Yook, Soon-Hyung

2014-07-01

To understand the effects of nonidentical processing elements (PEs) on parallel discrete-event simulation (PDES) schemes, two stochastic growth models, the restricted solid-on-solid (RSOS) model and the Family model, are investigated by simulations. The RSOS model is the model for the PDES scheme governed by the Kardar-Parisi-Zhang equation (KPZ scheme). The Family model is the model for the scheme governed by the Edwards-Wilkinson equation (EW scheme). Two kinds of distributions for nonidentical PEs are considered. In the first kind computing capacities of PEs are not much different, whereas in the second kind the capacities are extremely widespread. The KPZ scheme on the complex networks shows the synchronizability and scalability regardless of the kinds of PEs. The EW scheme never shows the synchronizability for the random configuration of PEs of the first kind. However, by regularizing the arrangement of PEs of the first kind, the EW scheme is made to show the synchronizability. In contrast, EW scheme never shows the synchronizability for any configuration of PEs of the second kind.

Soil organic carbon loss and selective transportation under field simulated rainfall events.

PubMed

Nie, Xiaodong; Li, Zhongwu; Huang, Jinquan; Huang, Bin; Zhang, Yan; Ma, Wenming; Hu, Yanbiao; Zeng, Guangming

2014-01-01

The study on the lateral movement of soil organic carbon (SOC) during soil erosion can improve the understanding of global carbon budget. Simulated rainfall experiments on small field plots were conducted to investigate the SOC lateral movement under different rainfall intensities and tillage practices. Two rainfall intensities (High intensity (HI) and Low intensity (LI)) and two tillage practices (No tillage (NT) and Conventional tillage (CT)) were maintained on three plots (2 m width × 5 m length): HI-NT, LI-NT and LI-CT. The rainfall lasted 60 minutes after the runoff generated, the sediment yield and runoff volume were measured and sampled at 6-min intervals. SOC concentration of sediment and runoff as well as the sediment particle size distribution were measured. The results showed that most of the eroded organic carbon (OC) was lost in form of sediment-bound organic carbon in all events. The amount of lost SOC in LI-NT event was 12.76 times greater than that in LI-CT event, whereas this measure in HI-NT event was 3.25 times greater than that in LI-NT event. These results suggest that conventional tillage as well as lower rainfall intensity can reduce the amount of lost SOC during short-term soil erosion. Meanwhile, the eroded sediment in all events was enriched in OC, and higher enrichment ratio of OC (ERoc) in sediment was observed in LI events than that in HI event, whereas similar ERoc curves were found in LI-CT and LI-NT events. Furthermore, significant correlations between ERoc and different size sediment particles were only observed in HI-NT event. This indicates that the enrichment of OC is dependent on the erosion process, and the specific enrichment mechanisms with respect to different erosion processes should be studied in future.

Soil Organic Carbon Loss and Selective Transportation under Field Simulated Rainfall Events

PubMed Central

Nie, Xiaodong; Li, Zhongwu; Huang, Jinquan; Huang, Bin; Zhang, Yan; Ma, Wenming; Hu, Yanbiao; Zeng, Guangming

2014-01-01

The study on the lateral movement of soil organic carbon (SOC) during soil erosion can improve the understanding of global carbon budget. Simulated rainfall experiments on small field plots were conducted to investigate the SOC lateral movement under different rainfall intensities and tillage practices. Two rainfall intensities (High intensity (HI) and Low intensity (LI)) and two tillage practices (No tillage (NT) and Conventional tillage (CT)) were maintained on three plots (2 m width × 5 m length): HI-NT, LI-NT and LI-CT. The rainfall lasted 60 minutes after the runoff generated, the sediment yield and runoff volume were measured and sampled at 6-min intervals. SOC concentration of sediment and runoff as well as the sediment particle size distribution were measured. The results showed that most of the eroded organic carbon (OC) was lost in form of sediment-bound organic carbon in all events. The amount of lost SOC in LI-NT event was 12.76 times greater than that in LI-CT event, whereas this measure in HI-NT event was 3.25 times greater than that in LI-NT event. These results suggest that conventional tillage as well as lower rainfall intensity can reduce the amount of lost SOC during short-term soil erosion. Meanwhile, the eroded sediment in all events was enriched in OC, and higher enrichment ratio of OC (ERoc) in sediment was observed in LI events than that in HI event, whereas similar ERoc curves were found in LI-CT and LI-NT events. Furthermore, significant correlations between ERoc and different size sediment particles were only observed in HI-NT event. This indicates that the enrichment of OC is dependent on the erosion process, and the specific enrichment mechanisms with respect to different erosion processes should be studied in future. PMID:25166015

Performance Analysis of Cloud Computing Architectures Using Discrete Event Simulation

NASA Technical Reports Server (NTRS)

Stocker, John C.; Golomb, Andrew M.

2011-01-01

Cloud computing offers the economic benefit of on-demand resource allocation to meet changing enterprise computing needs. However, the flexibility of cloud computing is disadvantaged when compared to traditional hosting in providing predictable application and service performance. Cloud computing relies on resource scheduling in a virtualized network-centric server environment, which makes static performance analysis infeasible. We developed a discrete event simulation model to evaluate the overall effectiveness of organizations in executing their workflow in traditional and cloud computing architectures. The two part model framework characterizes both the demand using a probability distribution for each type of service request as well as enterprise computing resource constraints. Our simulations provide quantitative analysis to design and provision computing architectures that maximize overall mission effectiveness. We share our analysis of key resource constraints in cloud computing architectures and findings on the appropriateness of cloud computing in various applications.

Developing of operational hydro-meteorological simulating and displaying system

NASA Astrophysics Data System (ADS)

Wang, Y.; Shih, D.; Chen, C.

2010-12-01

Hydrological hazards, which often occur in conjunction with extreme precipitation events, are the most frequent type of natural disaster in Taiwan. Hence, the researchers at the Taiwan Typhoon and Flood Research Institute (TTFRI) are devoted to analyzing and gaining a better understanding of the causes and effects of natural disasters, and in particular, typhoons and floods. The long-term goal of the TTFRI is to develop a unified weather-hydrological-oceanic model suitable for simulations with local parameterizations in Taiwan. The development of a fully coupled weather-hydrology interaction model is not yet completed but some operational hydro-meteorological simulations are presented as a step in the direction of completing a full model. The predicted rainfall data from Weather Research Forecasting (WRF) are used as our meteorological forcing on watershed modeling. The hydrology and hydraulic modeling are conducted by WASH123D numerical model. And the WRF/WASH123D coupled system is applied to simulate floods during the typhoon landfall periods. The daily operational runs start at 04UTC, 10UTC, 16UTC and 22UTC, about 4 hours after data downloaded from NCEP GFS. This system will execute 72-hr weather forecasts. The simulation of WASH123D will sequentially trigger after receiving WRF rainfall data. This study presents the preliminary framework of establishing this system, and our goal is to build this earlier warning system to alert the public form dangerous. The simulation results are further display by a 3D GIS web service system. This system is established following the Open Geospatial Consortium (OGC) standardization process for GIS web service, such as Web Map Service (WMS) and Web Feature Service (WFS). The traditional 2D GIS data, such as high resolution aerial photomaps and satellite images are integrated into 3D landscape model. The simulated flooding and inundation area can be dynamically mapped on Wed 3D world. The final goal of this system is to real

Polar cap potential saturation during the Bastille Day storm event using global MHD simulation

NASA Astrophysics Data System (ADS)

Kubota, Y.; Nagatsuma, T.; Den, M.; Tanaka, T.; Fujita, S.

2017-04-01

We investigated the temporal variations and saturation of the cross polar cap potential (CPCP) in the Bastille Day storm event (15 July 2000) by global magnetohydrodynamics (MHD) simulation. The CPCP is considered to depend on the electric field and dynamic pressure of the solar wind as well as on the ionospheric conductivity. Previous studies considered only the ionospheric conductivity due to solar extreme ultraviolet (EUV) variations. In this paper, we dealt with the changes in the CPCP attributable to auroral conductivity variations caused by pressure enhancement in the inner magnetosphere owing to energy injection from the magnetosphere because the energy injection is considerably enhanced in a severe magnetic storm event. Our simulation reveals that the auroral conductivity enhancement is significant for the CPCP variation in a severe magnetic storm event. The numerical results concerning the Bastille Day event show that the ionospheric conductivity averaged over the auroral oval is enhanced up to 18 mho in the case of Bz of less than -59 nT. On the other hand, the average conductivity without the auroral effect is almost 6 mho throughout the entire period. Resultantly, the saturated CPCP is about 240 kV in the former and 704 kV in the latter when Bz is -59 nT. This result indicates that the CPCP variations could be correctly reproduced when the time variation of auroral conductivity caused by pressure enhancement due to the energy injection from the magnetosphere is correctly considered in a severe magnetic storm event.

Numerical Simulations of Slow Stick Slip Events with PFC, a DEM Based Code

NASA Astrophysics Data System (ADS)

Ye, S. H.; Young, R. P.

2017-12-01

Nonvolcanic tremors around subduction zone have become a fascinating subject in seismology in recent years. Previous studies have shown that the nonvolcanic tremor beneath western Shikoku is composed of low frequency seismic waves overlapping each other. This finding provides direct link between tremor and slow earthquakes. Slow stick slip events are considered to be laboratory scaled slow earthquakes. Slow stick slip events are traditionally studied with direct shear or double direct shear experiment setup, in which the sliding velocity can be controlled to model a range of fast and slow stick slips. In this study, a PFC* model based on double direct shear is presented, with a central block clamped by two side blocks. The gauge layers between the central and side blocks are modelled as discrete fracture networks with smooth joint bonds between pairs of discrete elements. In addition, a second model is presented in this study. This model consists of a cylindrical sample subjected to triaxial stress. Similar to the previous model, a weak gauge layer at a 45 degrees is added into the sample, on which shear slipping is allowed. Several different simulations are conducted on this sample. While the confining stress is maintained at the same level in different simulations, the axial loading rate (displacement rate) varies. By varying the displacement rate, a range of slipping behaviour, from stick slip to slow stick slip are observed based on the stress-strain relationship. Currently, the stick slip and slow stick slip events are strictly observed based on the stress-strain relationship. In the future, we hope to monitor the displacement and velocity of the balls surrounding the gauge layer as a function of time, so as to generate a synthetic seismogram. This will allow us to extract seismic waveforms and potentially simulate the tremor-like waves found around subduction zones. *Particle flow code, a discrete element method based numerical simulation code developed by

Simulation of long-range transport aerosols from the Asian Continent to Taiwan by a southward Asian high-pressure system.

PubMed

Chuang, Ming-Tung; Fu, Joshua S; Jang, Carey J; Chan, Chang-Chuan; Ni, Pei-Cheng; Lee, Chung-Te

2008-11-15

Aerosol is frequently transported by a southward high-pressure system from the Asian Continent to Taiwan and had been recorded a 100% increase in mass level compared to non-event days from 2002 to 2005. During this time period, PM2.5 sulfate was found to increase as high as 155% on event days as compared to non-event days. In this study, Asian emission estimations, Taiwan Emission Database System (TEDS), and meteorological simulation results from the fifth-generation Mesoscale Model (MM5) were used as inputs for the Community Multiscale Air Quality (CMAQ) model to simulate a long-range transport of PM2.5 event in a southward high-pressure system from the Asian Continent to Taiwan. The simulation on aerosol mass level and the associated aerosol components were found within a reasonable accuracy. During the transport process, the percentage of semi-volatile PM2.5 organic carbon in PM2.5 plume only slightly decreased from 22-24% in Shanghai to 21% near Taiwan. However, the percentage of PM2.5 nitrate in PM2.5 decreased from 16-25% to 1%. In contrast, the percentage of PM2.5 sulfate in PM2.5 increased from 16-19% to 35%. It is interesting to note that the percentage of PM2.5 ammonium and PM2.5 elemental carbon in PM2.5 remained nearly constant. Simulation results revealed that transported pollutants dominate the air quality in Taipei when the southward high-pressure system moved to Taiwan. Such condition demonstrates the dynamic chemical transformation of pollutants during the transport process from continental origin over the sea area and to the downwind land.

A Summary of Some Discrete-Event System Control Problems

NASA Astrophysics Data System (ADS)

Rudie, Karen

A summary of the area of control of discrete-event systems is given. In this research area, automata and formal language theory is used as a tool to model physical problems that arise in technological and industrial systems. The key ingredients to discrete-event control problems are a process that can be modeled by an automaton, events in that process that cannot be disabled or prevented from occurring, and a controlling agent that manipulates the events that can be disabled to guarantee that the process under control either generates all the strings in some prescribed language or as many strings as possible in some prescribed language. When multiple controlling agents act on a process, decentralized control problems arise. In decentralized discrete-event systems, it is presumed that the agents effecting control cannot each see all event occurrences. Partial observation leads to some problems that cannot be solved in polynomial time and some others that are not even decidable.

Cascading events in linked ecological and socioeconomic systems

USGS Publications Warehouse

Peters, Debra P.C.; Sala, O.E.; Allen, Craig D.; Covich, A.; Brunson, M.

2007-01-01

Cascading events that start at small spatial scales and propagate non-linearly through time to influence larger areas often have major impacts on ecosystem goods and services. Events such as wildfires and hurricanes are increasing in frequency and magnitude as systems become more connected through globalization processes. We need to improve our understanding of these events in order to predict their occurrence, minimize potential impacts, and allow for strategic recovery. Here, we synthesize information about cascading events in systems located throughout the Americas. We discuss a variety of examples of cascading events that share a common feature: they are often driven by linked ecological and human processes across scales. In this era of globalization, we recommend studies that explicitly examine connections across scales and examine the role of connectivity among non-contiguous as well as contiguous areas.

Analyzing discharge strategies during acute care: a discrete-event simulation study.

PubMed

Crawford, Elizabeth A; Parikh, Pratik J; Kong, Nan; Thakar, Charuhas V

2014-02-01

We developed a discrete-event simulation model of patient pathway through an acute care hospital that comprises an ED and several inpatient units. The effects of discharge timing on ED waiting and boarding times, ambulance diversions, leave without treatment, and readmissions were explicitly modeled. We then analyzed the impact of 1 static and 2 proactive discharge strategies on these system outcomes. Our analysis indicated that although the 2 proactive discharge strategies significantly reduced ED waiting and boarding times, and several other measures, compared with the static strategy (P < 0.01), the number of readmissions increased substantially. Further analysis indicated that these findings are sensitive to changes in patient arrival rate and conditions for ambulance diversion. Determining the appropriate time to discharge patients not only can affect individual patients' health outcomes, but also can affect various aspects of the hospital. The study improves our understanding of how individual inpatient discharge decisions can be objectively viewed in terms of their impact on other operations, such as ED crowding and readmission, in an acute care hospital.

Simulation System Fidelity Assessment at the Vertical Motion Simulator

NASA Technical Reports Server (NTRS)

Beard, Steven D.; Reardon, Scott E.; Tobias, Eric L.; Aponso, Bimal L.

2013-01-01

Fidelity is a word that is often used but rarely understood when talking about groundbased simulation. Assessing the cueing fidelity of a ground based flight simulator requires a comparison to actual flight data either directly or indirectly. Two experiments were conducted at the Vertical Motion Simulator using the GenHel UH-60A Black Hawk helicopter math model that was directly compared to flight data. Prior to the experiment the simulator s motion and visual system frequency responses were measured, the aircraft math model was adjusted to account for the simulator motion system delays, and the motion system gains and washouts were tuned for the individual tasks. The tuned motion system fidelity was then assessed against the modified Sinacori criteria. The first experiments showed similar handling qualities ratings (HQRs) to actual flight for a bob-up and sidestep maneuvers. The second experiment showed equivalent HQRs between flight and simulation for the ADS33 slalom maneuver for the two pilot participants. The ADS33 vertical maneuver HQRs were mixed with one pilot rating the flight and simulation the same while the second pilot rated the simulation worse. In addition to recording HQRs on the second experiment, an experimental Simulation Fidelity Rating (SFR) scale developed by the University of Liverpool was tested for applicability to engineering simulators. A discussion of the SFR scale for use on the Vertical Motion Simulator is included in this paper.

Use of the Hadoop structured storage tools for the ATLAS EventIndex event catalogue

NASA Astrophysics Data System (ADS)

Favareto, A.

2016-09-01

The ATLAS experiment at the LHC collects billions of events each data-taking year, and processes them to make them available for physics analysis in several different formats. An even larger amount of events is in addition simulated according to physics and detector models and then reconstructed and analysed to be compared to real events. The EventIndex is a catalogue of all events in each production stage; it includes for each event a few identification parameters, some basic non-mutable information coming from the online system, and the references to the files that contain the event in each format (plus the internal pointers to the event within each file for quick retrieval). Each EventIndex record is logically simple but the system has to hold many tens of billions of records, all equally important. The Hadoop technology was selected at the start of the EventIndex project development in 2012 and proved to be robust and flexible to accommodate this kind of information; both the insertion and query response times are acceptable for the continuous and automatic operation that started in Spring 2015. This paper describes the EventIndex data input and organisation in Hadoop and explains the operational challenges that were overcome in order to achieve the expected performance.

Adaptable, high recall, event extraction system with minimal configuration

PubMed Central

2015-01-01

Background Biomedical event extraction has been a major focus of biomedical natural language processing (BioNLP) research since the first BioNLP shared task was held in 2009. Accordingly, a large number of event extraction systems have been developed. Most such systems, however, have been developed for specific tasks and/or incorporated task specific settings, making their application to new corpora and tasks problematic without modification of the systems themselves. There is thus a need for event extraction systems that can achieve high levels of accuracy when applied to corpora in new domains, without the need for exhaustive tuning or modification, whilst retaining competitive levels of performance. Results We have enhanced our state-of-the-art event extraction system, EventMine, to alleviate the need for task-specific tuning. Task-specific details are specified in a configuration file, while extensive task-specific parameter tuning is avoided through the integration of a weighting method, a covariate shift method, and their combination. The task-specific configuration and weighting method have been employed within the context of two different sub-tasks of BioNLP shared task 2013, i.e. Cancer Genetics (CG) and Pathway Curation (PC), removing the need to modify the system specifically for each task. With minimal task specific configuration and tuning, EventMine achieved the 1st place in the PC task, and 2nd in the CG, achieving the highest recall for both tasks. The system has been further enhanced following the shared task by incorporating the covariate shift method and entity generalisations based on the task definitions, leading to further performance improvements. Conclusions We have shown that it is possible to apply a state-of-the-art event extraction system to new tasks with high levels of performance, without having to modify the system internally. Both covariate shift and weighting methods are useful in facilitating the production of high recall systems

Adaptable, high recall, event extraction system with minimal configuration.

PubMed

Miwa, Makoto; Ananiadou, Sophia

2015-01-01

Biomedical event extraction has been a major focus of biomedical natural language processing (BioNLP) research since the first BioNLP shared task was held in 2009. Accordingly, a large number of event extraction systems have been developed. Most such systems, however, have been developed for specific tasks and/or incorporated task specific settings, making their application to new corpora and tasks problematic without modification of the systems themselves. There is thus a need for event extraction systems that can achieve high levels of accuracy when applied to corpora in new domains, without the need for exhaustive tuning or modification, whilst retaining competitive levels of performance. We have enhanced our state-of-the-art event extraction system, EventMine, to alleviate the need for task-specific tuning. Task-specific details are specified in a configuration file, while extensive task-specific parameter tuning is avoided through the integration of a weighting method, a covariate shift method, and their combination. The task-specific configuration and weighting method have been employed within the context of two different sub-tasks of BioNLP shared task 2013, i.e. Cancer Genetics (CG) and Pathway Curation (PC), removing the need to modify the system specifically for each task. With minimal task specific configuration and tuning, EventMine achieved the 1st place in the PC task, and 2nd in the CG, achieving the highest recall for both tasks. The system has been further enhanced following the shared task by incorporating the covariate shift method and entity generalisations based on the task definitions, leading to further performance improvements. We have shown that it is possible to apply a state-of-the-art event extraction system to new tasks with high levels of performance, without having to modify the system internally. Both covariate shift and weighting methods are useful in facilitating the production of high recall systems. These methods and their

Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

NASA Astrophysics Data System (ADS)

Chawla, Ila; Osuri, Krishna K.; Mujumdar, Pradeep P.; Niyogi, Dev

2018-02-01

Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15-18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor-Yamada-Janjic PBL and Betts-Miller-Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through

Simulation of Rate-Related (Dead-Time) Losses In Passive Neutron Multiplicity Counting Systems

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

Evans, L.G.; Norman, P.I.; Leadbeater, T.W.

Passive Neutron Multiplicity Counting (PNMC) based on Multiplicity Shift Register (MSR) electronics (a form of time correlation analysis) is a widely used non-destructive assay technique for quantifying spontaneously fissile materials such as Pu. At high event rates, dead-time losses perturb the count rates with the Singles, Doubles and Triples being increasingly affected. Without correction these perturbations are a major source of inaccuracy in the measured count rates and assay values derived from them. This paper presents the simulation of dead-time losses and investigates the effect of applying different dead-time models on the observed MSR data. Monte Carlo methods have beenmore » used to simulate neutron pulse trains for a variety of source intensities and with ideal detection geometry, providing an event by event record of the time distribution of neutron captures within the detection system. The action of the MSR electronics was modelled in software to analyse these pulse trains. Stored pulse trains were perturbed in software to apply the effects of dead-time according to the chosen physical process; for example, the ideal paralysable (extending) and non-paralysable models with an arbitrary dead-time parameter. Results of the simulations demonstrate the change in the observed MSR data when the system dead-time parameter is varied. In addition, the paralysable and non-paralysable models of deadtime are compared. These results form part of a larger study to evaluate existing dead-time corrections and to extend their application to correlated sources. (authors)« less

Hydrological Simulation of Flood Events At Large Basins Using Distributed Modelling

NASA Astrophysics Data System (ADS)

Vélez, J.; Vélez, I.; Puricelli, M.; Francés, F.

Recent advances in technology allows to the scientist community advance in new pro- cedures in order to reduce the risk associated to flood events. A conceptual distributed model has been implemented to simulate the hydrological processes involved during floods. The model has been named TETIS. The basin is divided into rectangular cells, all of them connected according to the network drainage. The rainfall-runoff process is modelled using four linked tanks at each cell with different outflow relationships at each tank, which represent the ET, direct runoff, interflow and base flow, respectively. The routing along the channel network has been proposed using basin geomorpho- logic characteristics coupled to the cinematic wave procedure. The vertical movement along the cell is proposed using simple relationships based on soil properties as field capacity and the saturated hydraulic conductivities, which were previously obtained using land use, litology, edaphology and basin properties maps. The different vertical proccesses along the cell included are: capillar storage, infiltration, percolation and underground losses. Finally, snowmelting and reservoir routing has been included. TETIS has been implemented in the flood warning system of the Tagus River, with a basin of 59 200 km2. The time discretization of the input data is 15 minutes, and the cell size is 500x500 m. The basic parameter maps were estimated for the entire basin, and a calibration and validation processes were performed using some recorded events in the upper part of the basin. Calibration confirmed the initial parameter estimation. Additionally, the validation in time and space showed the robustness of these types of models

Nonlinear Control and Discrete Event Systems

NASA Technical Reports Server (NTRS)

Meyer, George; Null, Cynthia H. (Technical Monitor)

1995-01-01

As the operation of large systems becomes ever more dependent on extensive automation, the need for an effective solution to the problem of design and validation of the underlying software becomes more critical. Large systems possesses much detailed structure, typically hierarchical, and they are hybrid. Information processing at the top of the hierarchy is by means of formal logic and sentences; on the bottom it is by means of simple scalar differential equations and functions of time; and in the middle it is by an interacting mix of nonlinear multi-axis differential equations and automata, and functions of time and discrete events. The lecture will address the overall problem as it relates to flight vehicle management, describe the middle level, and offer a design approach that is based on Differential Geometry and Discrete Event Dynamic Systems Theory.

Modeling and simulation of queuing system for customer service improvement: A case study

NASA Astrophysics Data System (ADS)

Xian, Tan Chai; Hong, Chai Weng; Hawari, Nurul Nazihah

2016-10-01

This study aims to develop a queuing model at UniMall by using discrete event simulation approach in analyzing the service performance that affects customer satisfaction. The performance measures that considered in this model are such as the average time in system, the total number of student served, the number of student in waiting queue, the waiting time in queue as well as the maximum length of buffer. ARENA simulation software is used to develop a simulation model and the output is analyzed. Based on the analysis of output, it is recommended that management of UniMall consider introducing shifts and adding another payment counter in the morning.

Hydrocode simulation of the Chicxulub impact event and the production of climatically active gases

NASA Astrophysics Data System (ADS)

Pierazzo, Elisabetta; Kring, David A.; Melosh, H. Jay

1998-12-01

We constructed a numerical model of the Chicxulub impact event using the Chart-D Squared (CSQ) code coupled with the ANalytic Equation Of State (ANEOS) package. In the simulations we utilized a target stratigraphy based on borehole data and employed newly developed equations of state for the materials that are believed to play a crucial role in the impact-related extinction hypothesis: carbonates (calcite) and evaporites (anhydrite). Simulations explored the effects of different projectile sizes (10 to 30 km in diameter) and porosity (0 to 50%). The effect of impact speed is addressed by doing simulations of asteroid impacts (vi=20km/s) and comet impacts (vi=50km/s). The masses of climatically important species injected into the upper atmosphere by the impact increase with the energy of the impact event, ranging from 350 to 3500 Gt for CO2, from 40 to 560 Gt for S, and from 200 to 1400 Gt for water vapor. While our results are in good agreement with those of Ivanov et al. [1996], our estimated CO2 production is 1 to 2 orders of magnitude lower than the results of Takata and Ahrens [1994], indicating that the impact event enhanced the end-Cretaceous atmospheric CO2 inventory by, at most, 40%. Consequently, sulfur may have been the most important climatically active gas injected into the stratosphere. The amount of S released by the impact is several orders of magnitude higher than any known volcanic eruption and, with H2O, is high enough to produce a sudden and significant perturbation of Earth's climate.

Assessment of long-term knowledge retention following single-day simulation training for uncommon but critical obstetrical events

PubMed Central

Vadnais, Mary A.; Dodge, Laura E.; Awtrey, Christopher S.; Ricciotti, Hope A.; Golen, Toni H.; Hacker, Michele R.

2013-01-01

Objective The objectives were to determine (i) whether simulation training results in short-term and long-term improvement in the management of uncommon but critical obstetrical events and (ii) to determine whether there was additional benefit from annual exposure to the workshop. Methods Physicians completed a pretest to measure knowledge and confidence in the management of eclampsia, shoulder dystocia, postpartum hemorrhage and vacuum-assisted vaginal delivery. They then attended a simulation workshop and immediately completed a posttest. Residents completed the same posttests 4 and 12 months later, and attending physicians completed the posttest at 12 months. Physicians participated in the same simulation workshop 1 year later and then completed a final posttest. Scores were compared using paired t-tests. Results Physicians demonstrated improved knowledge and comfort immediately after simulation. Residents maintained this improvement at 1 year. Attending physicians remained more comfortable managing these scenarios up to 1 year later; however, knowledge retention diminished with time. Repeating the simulation after 1 year brought additional improvement to physicians. Conclusion Simulation training can result in short-term and contribute to long-term improvement in objective measures of knowledge and comfort level in managing uncommon but critical obstetrical events. Repeat exposure to simulation training after 1 year can yield additional benefits. PMID:22191668

Analysis, Simulation, and Verification of Knowledge-Based, Rule-Based, and Expert Systems

NASA Technical Reports Server (NTRS)

Hinchey, Mike; Rash, James; Erickson, John; Gracanin, Denis; Rouff, Chris

2010-01-01

Mathematically sound techniques are used to view a knowledge-based system (KBS) as a set of processes executing in parallel and being enabled in response to specific rules being fired. The set of processes can be manipulated, examined, analyzed, and used in a simulation. The tool that embodies this technology may warn developers of errors in their rules, but may also highlight rules (or sets of rules) in the system that are underspecified (or overspecified) and need to be corrected for the KBS to operate as intended. The rules embodied in a KBS specify the allowed situations, events, and/or results of the system they describe. In that sense, they provide a very abstract specification of a system. The system is implemented through the combination of the system specification together with an appropriate inference engine, independent of the algorithm used in that inference engine. Viewing the rule base as a major component of the specification, and choosing an appropriate specification notation to represent it, reveals how additional power can be derived from an approach to the knowledge-base system that involves analysis, simulation, and verification. This innovative approach requires no special knowledge of the rules, and allows a general approach where standardized analysis, verification, simulation, and model checking techniques can be applied to the KBS.

An investigation into pilot and system response to critical in-flight events, volume 2

NASA Technical Reports Server (NTRS)

Rockwell, T. H.; Giffin, W. C.

1981-01-01

Critical in-flight event is studied using mission simulation and written tests of pilot responses. Materials and procedures used in knowledge tests, written tests, and mission simulations are included

Accurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactions.

PubMed

Salis, Howard; Kaznessis, Yiannis

2005-02-01

The dynamical solution of a well-mixed, nonlinear stochastic chemical kinetic system, described by the Master equation, may be exactly computed using the stochastic simulation algorithm. However, because the computational cost scales with the number of reaction occurrences, systems with one or more "fast" reactions become costly to simulate. This paper describes a hybrid stochastic method that partitions the system into subsets of fast and slow reactions, approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the integral form of the "Next Reaction" variant of the stochastic simulation algorithm. The key innovation of this method is its mechanism of efficiently monitoring the occurrences of slow, discrete events while simultaneously simulating the dynamics of a continuous, stochastic or deterministic process. In addition, by introducing an approximation in which multiple slow reactions may occur within a time step of the numerical integration of the chemical Langevin equation, the hybrid stochastic method performs much faster with only a marginal decrease in accuracy. Multiple examples, including a biological pulse generator and a large-scale system benchmark, are simulated using the exact and proposed hybrid methods as well as, for comparison, a previous hybrid stochastic method. Probability distributions of the solutions are compared and the weak errors of the first two moments are computed. In general, these hybrid methods may be applied to the simulation of the dynamics of a system described by stochastic differential, ordinary differential, and Master equations.

Block Oriented Simulation System (BOSS)

NASA Technical Reports Server (NTRS)

Ratcliffe, Jaimie

1988-01-01

Computer simulation is assuming greater importance as a flexible and expedient approach to modeling system and subsystem behavior. Simulation has played a key role in the growth of complex, multiple access space communications such as those used by the space shuttle and the TRW-built Tracking and Data Relay Satellites (TDRS). A powerful new simulator for use in designing and modeling the communication system of NASA's planned Space Station is being developed. Progress to date on the Block (Diagram) Oriented Simulation System (BOSS) is described.

[Validation of an adverse event reporting system in primary care].

PubMed

de Lourdes Rojas-Armadillo, María; Jiménez-Báez, María Valeria; Chávez-Hernández, María Margarita; González-Fondón, Araceli

2016-01-01

Patient safety is a priority issue in health systems, due to the damage costs, institutional weakening, lack of credibility, and frustration on those who committed an error that resulted in an adverse event. There is no standardized instrument for recording, reporting, and analyzing sentinel or adverse events (AE) in primary care. Our aim was to design and validate a surveillance system for recording sentinel events, adverse events and near miss incidents in primary care. We made a review of systems for recording and reporting adverse events in primary care. Then, we proposed an instrument to record these events, and register faults in the structure and process, in primary health care units in the Instituto Mexicano del Seguro Social. We showed VENCER-MF format to 35 subjects. Out of them, 100% identified a failure in care process, 90% recorded a sentinel event, 85% identified the cause of this event, 75% of them suggested some measures for avoiding the recurrence of adverse events. We used a Cronbach's alpha of 0.6, p=0.03. The instrument VENCER-MF has a good consistency for the identification of adverse events.

The development of an incident event reporting system for nursing students.

PubMed

Chiou, Shwu-Fen; Huang, Ean-Wen; Chuang, Jen-Hsiang

2009-01-01

Incident events may occur when nursing students are present in the clinical setting. Their inexperience and unfamiliarity with clinical practice put them at risk for making mistakes that could potentially harm patients and themselves. However, there are deficiencies with incident event reporting systems, including incomplete data and delayed reports. The purpose of this study was to develop an incident event reporting system for nursing students in clinical settings and evaluate its effectiveness. This study was undertaken in three phases. In the first phase, a literature review and focus groups were used to develop the architecture of the reporting system. In the second phase, the reporting system was implemented. Data from incident events that involved nursing students were collected for a 12-month period. In the third phase, a pre-post trial was undertaken to evaluate the performance of the reporting system. The ASP.NET software and Microsoft Access 2003 were used to create an interactive web-based interface and design a database for the reporting system. Email notifications alerted the nursing student's teacher when an incident event was reported. One year after installing the reporting system, the number of reported incident events increased tenfold. However, the time to report the incident event and the time required to complete the reporting procedures were shorter than before implementation of the reporting system. The incident event reporting system appeared to be effective in more comprehensively reporting the number of incident events and shorten the time required for reporting them compared to traditional written reports.

SIGMA--A Graphical Approach to Teaching Simulation.

ERIC Educational Resources Information Center

Schruben, Lee W.

1992-01-01

SIGMA (Simulation Graphical Modeling and Analysis) is a computer graphics environment for building, testing, and experimenting with discrete event simulation models on personal computers. It uses symbolic representations (computer animation) to depict the logic of large, complex discrete event systems for easier understanding and has proven itself…

Linking Crystal Populations to Dynamic States: Crystal Dissolution and Growth During an Open-System Event

NASA Astrophysics Data System (ADS)

Bergantz, G. W.; Schleicher, J.; Burgisser, A.

2016-12-01

The identification of shared characteristics in zoned crystals has motivated the definition of crystal populations. These populations reflect the simultaneous transport of crystals, heat and composition during open-system events. An obstacle to interpreting the emergence of a population is the absence of a way to correlate specific dynamic conditions with the characteristic attributes of a population. By combining a boundary-layer diffusion controlled model for crystal growth/dissolution with discrete-element magma dynamics simulations of crystal-bearing magmas, the creation of populations can be simulated. We have implemented a method that decomposes the chemical potential into the thermal and compositional contributions to crystal dissolution/growth. This allows for the explicit treatment of thermal inertia and thermal-compositional decoupling as fluid circulation stirs the system during an open-system event. We have identified three distinct dynamic states producing crystal populations. They are based on the volume fraction of crystals. In a mushy system, thermal and compositional states are tightly linked as the volume involved in the mixing is constrained by the so-called mixing bowl (Bergantz et al., 2015). The mixing bowl volume is a function of the visco-plastic response of the mush and the intrusion width, not by the progressive entrainment of the new intrusion as commonly assumed. Crystal dissolution is the dominate response to input of more primitive magma. At the other endmember, under very dilute conditions, thermal and compositional conditions can become decoupled, and the in-coming magma forms a double-diffusive low-Re jet. This can allow for both dissolution and growth as crystals circulate widely into an increasingly stratified system. A middle range of crystal concentration produces a very complex feedback, as sedimenting crystals form fingers and chains that interact with the incoming magma, break-up the entrainment with chaotic stirring and add

Critical event management with geographic information system technology

NASA Astrophysics Data System (ADS)

Booth, John F.; Young, Jeffrey M.

1997-02-01

Critical event management at the Los Angeles County Regional Criminal Information Clearinghouse (LACRCIC) provides for the deconfliction of operations, such as reverse stings, arrests, undercover buys/busts, searches, surveillances, and site surveys in the Los Angeles, Orange, Riverside, and San Bernardino county area. During these operations, the opportunity for officer-to-officer confrontation is high, possibly causing a worse case scenario -- officers drawing on each other resulting in friendly fire injuries or casualties. In order to prevent local, state, and federal agencies in the Los Angeles area from experiencing this scenario, the LACRCIC provides around the clock critical event management services via its secure war room. The war room maintains a multicounty detailed street-level map base and geographic information system (GIS) application to support this effort. Operations are telephoned in by the participating agencies and posted in the critical event management system by war room analysts. The application performs both a proximity search around the address and a commonality of suspects search. If a conflict is found, the system alerts the analyst by sounding an audible alarm and flashing the conflicting events on the automated basemap. The analyst then notifies the respective agencies of the conflicting critical events so coordination or rescheduling can occur.

In situ simulated cardiac arrest exercises to detect system vulnerabilities.

PubMed

Barbeito, Atilio; Bonifacio, Alberto; Holtschneider, Mary; Segall, Noa; Schroeder, Rebecca; Mark, Jonathan

2015-06-01

Sudden cardiac arrest is the leading cause of death in the United States. Despite new therapies, progress in this area has been slow, and outcomes remain poor even in the hospital setting, where providers, drugs, and devices are readily available. This is partly attributed to the quality of resuscitation, which is an important determinant of survival for patients who experience cardiac arrest. Systems problems, such as deficiencies in the physical space or equipment design, hospital-level policies, work culture, and poor leadership and teamwork, are now known to contribute significantly to the quality of resuscitation provided. We describe an in situ simulation-based quality improvement program that was designed to continuously monitor the cardiac arrest response process for hazards and defects and to detect opportunities for system optimization. A total of 72 simulated unannounced cardiac arrest exercises were conducted between October 2010 and September 2013 at various locations throughout our medical center and at different times of the day. We detected several environmental, human-machine interface, culture, and policy hazards and defects. We used the Systems Engineering Initiative for Patient Safety (SEIPS) model to understand the structure, processes, and outcomes related to the hospital's emergency response system. Multidisciplinary solutions were crafted for each of the hazards detected, and the simulation program was used to iteratively test the redesigned processes before implementation in real clinical settings. We describe an ongoing program that uses in situ simulation to identify and mitigate latent hazards and defects in the hospital emergency response system. The SEIPS model provides a framework for describing and analyzing the structure, processes, and outcomes related to these events.

Hard Sphere Simulation by Event-Driven Molecular Dynamics: Breakthrough, Numerical Difficulty, and Overcoming the issues

NASA Astrophysics Data System (ADS)

Isobe, Masaharu

Hard sphere/disk systems are among the simplest models and have been used to address numerous fundamental problems in the field of statistical physics. The pioneering numerical works on the solid-fluid phase transition based on Monte Carlo (MC) and molecular dynamics (MD) methods published in 1957 represent historical milestones, which have had a significant influence on the development of computer algorithms and novel tools to obtain physical insights. This chapter addresses the works of Alder's breakthrough regarding hard sphere/disk simulation: (i) event-driven molecular dynamics, (ii) long-time tail, (iii) molasses tail, and (iv) two-dimensional melting/crystallization. From a numerical viewpoint, there are serious issues that must be overcome for further breakthrough. Here, we present a brief review of recent progress in this area.

Discrete event simulation modelling of patient service management with Arena

NASA Astrophysics Data System (ADS)

Guseva, Elena; Varfolomeyeva, Tatyana; Efimova, Irina; Movchan, Irina

2018-05-01

This paper describes the simulation modeling methodology aimed to aid in solving the practical problems of the research and analysing the complex systems. The paper gives the review of a simulation platform sand example of simulation model development with Arena 15.0 (Rockwell Automation).The provided example of the simulation model for the patient service management helps to evaluate the workload of the clinic doctors, determine the number of the general practitioners, surgeons, traumatologists and other specialized doctors required for the patient service and develop recommendations to ensure timely delivery of medical care and improve the efficiency of the clinic operation.

Facilitating Co-Design for Extreme-Scale Systems Through Lightweight Simulation

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

Engelmann, Christian; Lauer, Frank

This work focuses on tools for investigating algorithm performance at extreme scale with millions of concurrent threads and for evaluating the impact of future architecture choices to facilitate the co-design of high-performance computing (HPC) architectures and applications. The approach focuses on lightweight simulation of extreme-scale HPC systems with the needed amount of accuracy. The prototype presented in this paper is able to provide this capability using a parallel discrete event simulation (PDES), such that a Message Passing Interface (MPI) application can be executed at extreme scale, and its performance properties can be evaluated. The results of an initial prototype aremore » encouraging as a simple 'hello world' MPI program could be scaled up to 1,048,576 virtual MPI processes on a four-node cluster, and the performance properties of two MPI programs could be evaluated at up to 16,384 virtual MPI processes on the same system.« less

Developing future precipitation events from historic events: An Amsterdam case study.

NASA Astrophysics Data System (ADS)

Manola, Iris; van den Hurk, Bart; de Moel, Hans; Aerts, Jeroen

2016-04-01

Due to climate change, the frequency and intensity of extreme precipitation events is expected to increase. It is therefore of high importance to develop climate change scenarios tailored towards the local and regional needs of policy makers in order to develop efficient adaptation strategies to reduce the risks from extreme weather events. Current approaches to tailor climate scenarios are often not well adopted in hazard management, since average changes in climate are not a main concern to policy makers, and tailoring climate scenarios to simulate future extremes can be complex. Therefore, a new concept has been introduced recently that uses known historic extreme events as a basis, and modifies the observed data for these events so that the outcome shows how the same event would occur in a warmer climate. This concept is introduced as 'Future Weather', and appeals to the experience of stakeholders and users. This research presents a novel method of projecting a future extreme precipitation event, based on a historic event. The selected precipitation event took place over the broader area of Amsterdam, the Netherlands in the summer of 2014, which resulted in blocked highways, disruption of air transportation, flooded buildings and public facilities. An analysis of rain monitoring stations showed that an event of such intensity has a 5 to 15 years return period. The method of projecting a future event follows a non-linear delta transformation that is applied directly on the observed event assuming a warmer climate to produce an "up-scaled" future precipitation event. The delta transformation is based on the observed behaviour of the precipitation intensity as a function of the dew point temperature during summers. The outcome is then compared to a benchmark method using the HARMONIE numerical weather prediction model, where the boundary conditions of the event from the Ensemble Prediction System of ECMWF (ENS) are perturbed to indicate a warmer climate. The two

Sensitivity of diabetic retinopathy associated vision loss to screening interval in an agent-based/discrete event simulation model.

PubMed

Day, T Eugene; Ravi, Nathan; Xian, Hong; Brugh, Ann

2014-04-01

To examine the effect of changes to screening interval on the incidence of vision loss in a simulated cohort of Veterans with diabetic retinopathy (DR). This simulation allows us to examine potential interventions without putting patients at risk. Simulated randomized controlled trial. We develop a hybrid agent-based/discrete event simulation which incorporates a population of simulated Veterans--using abstracted data from a retrospective cohort of real-world diabetic Veterans--with a discrete event simulation (DES) eye clinic at which it seeks treatment for DR. We compare vision loss under varying screening policies, in a simulated population of 5000 Veterans over 50 independent ten-year simulation runs for each group. Diabetic Retinopathy associated vision loss increased as the screening interval was extended from one to five years (p<0.0001). This increase was concentrated in the third year of the screening interval (p<0.01). There was no increase in vision loss associated with increasing the screening interval from one year to two years (p=0.98). Increasing the screening interval for diabetic patients who have not yet developed diabetic retinopathy from 1 to 2 years appears safe, while increasing the interval to 3 years heightens risk for vision loss. Published by Elsevier Ltd.

A Simple Ensemble Simulation Technique for Assessment of Future Variations in Specific High-Impact Weather Events

NASA Astrophysics Data System (ADS)

Taniguchi, Kenji

2018-04-01

To investigate future variations in high-impact weather events, numerous samples are required. For the detailed assessment in a specific region, a high spatial resolution is also required. A simple ensemble simulation technique is proposed in this paper. In the proposed technique, new ensemble members were generated from one basic state vector and two perturbation vectors, which were obtained by lagged average forecasting simulations. Sensitivity experiments with different numbers of ensemble members, different simulation lengths, and different perturbation magnitudes were performed. Experimental application to a global warming study was also implemented for a typhoon event. Ensemble-mean results and ensemble spreads of total precipitation, atmospheric conditions showed similar characteristics across the sensitivity experiments. The frequencies of the maximum total and hourly precipitation also showed similar distributions. These results indicate the robustness of the proposed technique. On the other hand, considerable ensemble spread was found in each ensemble experiment. In addition, the results of the application to a global warming study showed possible variations in the future. These results indicate that the proposed technique is useful for investigating various meteorological phenomena and the impacts of global warming. The results of the ensemble simulations also enable the stochastic evaluation of differences in high-impact weather events. In addition, the impacts of a spectral nudging technique were also examined. The tracks of a typhoon were quite different between cases with and without spectral nudging; however, the ranges of the tracks among ensemble members were comparable. It indicates that spectral nudging does not necessarily suppress ensemble spread.

Simulation of rare events in quantum error correction

NASA Astrophysics Data System (ADS)

Bravyi, Sergey; Vargo, Alexander

2013-12-01

We consider the problem of calculating the logical error probability for a stabilizer quantum code subject to random Pauli errors. To access the regime of large code distances where logical errors are extremely unlikely we adopt the splitting method widely used in Monte Carlo simulations of rare events and Bennett's acceptance ratio method for estimating the free energy difference between two canonical ensembles. To illustrate the power of these methods in the context of error correction, we calculate the logical error probability PL for the two-dimensional surface code on a square lattice with a pair of holes for all code distances d≤20 and all error rates p below the fault-tolerance threshold. Our numerical results confirm the expected exponential decay PL˜exp[-α(p)d] and provide a simple fitting formula for the decay rate α(p). Both noiseless and noisy syndrome readout circuits are considered.

GRMHD Simulations of Visibility Amplitude Variability for Event Horizon Telescope Images of Sgr A*

NASA Astrophysics Data System (ADS)

Medeiros, Lia; Chan, Chi-kwan; Özel, Feryal; Psaltis, Dimitrios; Kim, Junhan; Marrone, Daniel P.; Sa¸dowski, Aleksander

2018-04-01

The Event Horizon Telescope will generate horizon scale images of the black hole in the center of the Milky Way, Sgr A*. Image reconstruction using interferometric visibilities rests on the assumption of a stationary image. We explore the limitations of this assumption using high-cadence disk- and jet-dominated GRMHD simulations of Sgr A*. We also employ analytic models that capture the basic characteristics of the images to understand the origin of the variability in the simulated visibility amplitudes. We find that, in all simulations, the visibility amplitudes for baselines oriented parallel and perpendicular to the spin axis of the black hole follow general trends that do not depend strongly on accretion-flow properties. This suggests that fitting Event Horizon Telescope observations with simple geometric models may lead to a reasonably accurate determination of the orientation of the black hole on the plane of the sky. However, in the disk-dominated models, the locations and depths of the minima in the visibility amplitudes are highly variable and are not related simply to the size of the black hole shadow. This suggests that using time-independent models to infer additional black hole parameters, such as the shadow size or the spin magnitude, will be severely affected by the variability of the accretion flow.

The impact of interoperability of electronic health records on ambulatory physician practices: a discrete-event simulation study.

PubMed

Zhou, Yuan; Ancker, Jessica S; Upadhye, Mandar; McGeorge, Nicolette M; Guarrera, Theresa K; Hegde, Sudeep; Crane, Peter W; Fairbanks, Rollin J; Bisantz, Ann M; Kaushal, Rainu; Lin, Li

2013-01-01

The effect of health information technology (HIT) on efficiency and workload among clinical and nonclinical staff has been debated, with conflicting evidence about whether electronic health records (EHRs) increase or decrease effort. None of this paper to date, however, examines the effect of interoperability quantitatively using discrete event simulation techniques. To estimate the impact of EHR systems with various levels of interoperability on day-to-day tasks and operations of ambulatory physician offices. Interviews and observations were used to collect workflow data from 12 adult primary and specialty practices. A discrete event simulation model was constructed to represent patient flows and clinical and administrative tasks of physicians and staff members. High levels of EHR interoperability were associated with reduced time spent by providers on four tasks: preparing lab reports, requesting lab orders, prescribing medications, and writing referrals. The implementation of an EHR was associated with less time spent by administrators but more time spent by physicians, compared with time spent at paper-based practices. In addition, the presence of EHRs and of interoperability did not significantly affect the time usage of registered nurses or the total visit time and waiting time of patients. This paper suggests that the impact of using HIT on clinical and nonclinical staff work efficiency varies, however, overall it appears to improve time efficiency more for administrators than for physicians and nurses.

A State Event Detection Algorithm for Numerically Simulating Hybrid Systems with Model Singularities

DTIC Science & Technology

2007-01-01

the case of non- constant step sizes. Therefore the event dynamics after the predictor and corrector phases are, respectively, gpk +1 = g( xk + hk+1{ m...the Extrapolation Polynomial Using a Taylor series expansion of the predicted event function eq.(6) gpk +1 = gk + hk+1 dgp dt ∣∣∣∣ (x,t)=(xk,tk) + h2k...1 2! d2gp dt2 ∣∣∣∣ (x,t)=(xk,tk) + . . . , (8) we can determine the value of gpk +1 as a function of the, yet undetermined, step size hk+1. Recalling

Sensitivity analysis of some critical factors affecting simulated intrusion volumes during a low pressure transient event in a full-scale water distribution system.

PubMed

Ebacher, G; Besner, M C; Clément, B; Prévost, M

2012-09-01

Intrusion events caused by transient low pressures may result in the contamination of a water distribution system (DS). This work aims at estimating the range of potential intrusion volumes that could result from a real downsurge event caused by a momentary pump shutdown. A model calibrated with transient low pressure recordings was used to simulate total intrusion volumes through leakage orifices and submerged air vacuum valves (AVVs). Four critical factors influencing intrusion volumes were varied: the external head of (untreated) water on leakage orifices, the external head of (untreated) water on submerged air vacuum valves, the leakage rate, and the diameter of AVVs' outlet orifice (represented by a multiplicative factor). Leakage orifices' head and AVVs' orifice head levels were assessed through fieldwork. Two sets of runs were generated as part of two statistically designed experiments. A first set of 81 runs was based on a complete factorial design in which each factor was varied over 3 levels. A second set of 40 runs was based on a latin hypercube design, better suited for experimental runs on a computer model. The simulations were conducted using commercially available transient analysis software. Responses, measured by total intrusion volumes, ranged from 10 to 366 L. A second degree polynomial was used to analyze the total intrusion volumes. Sensitivity analyses of both designs revealed that the relationship between the total intrusion volume and the four contributing factors is not monotonic, with the AVVs' orifice head being the most influential factor. When intrusion through both pathways occurs concurrently, interactions between the intrusion flows through leakage orifices and submerged AVVs influence intrusion volumes. When only intrusion through leakage orifices is considered, the total intrusion volume is more largely influenced by the leakage rate than by the leakage orifices' head. The latter mainly impacts the extent of the area affected by

Sequential Events Control System (SECS) Overview

NASA Technical Reports Server (NTRS)

Interbartolo, Michael

2009-01-01

This slide presentation will cover the Sequential Events Control System (SECS), which is the Apollo spacecraft subsystem that controls the automatically sequenced functions during the mission and during any a borts that could be performed. Included in this presentation are its general architecture, its integration into and use of the spacecraft' s other systems, and details on the functions it is responsible for c ontrolling during the mission. The objectives are to describe the system's architecture, the major components in the system, and the major system functions.

Numerical simulation of a winter hailstorm event over Delhi, India on 17 January 2013

NASA Astrophysics Data System (ADS)

Chevuturi, A.; Dimri, A. P.; Gunturu, U. B.

2014-09-01

This study analyzes the cause of rare occurrence of winter hailstorm over New Delhi/NCR (National Capital Region), India. The absence of increased surface temperature or low level of moisture incursion during winter cannot generate the deep convection required for sustaining a hailstorm. Consequently, NCR shows very few cases of hailstorms in the months of December-January-February, making the winter hail formation a question of interest. For this study, recent winter hailstorm event on 17 January 2013 (16:00-18:00 UTC) occurring over NCR is investigated. The storm is simulated using Weather Research and Forecasting (WRF) model with Goddard Cumulus Ensemble (GCE) microphysics scheme with two different options, hail or graupel. The aim of the study is to understand and describe the cause of hailstorm event during over NCR with comparative analysis of the two options of GCE microphysics. On evaluating the model simulations, it is observed that hail option shows similar precipitation intensity with TRMM observation than the graupel option and is able to simulate hail precipitation. Using the model simulated output with hail option; detailed investigation on understanding the dynamics of hailstorm is performed. The analysis based on numerical simulation suggests that the deep instability in the atmospheric column led to the formation of hailstones as the cloud formation reached upto the glaciated zone promoting ice nucleation. In winters, such instability conditions rarely form due to low level available potential energy and moisture incursion along with upper level baroclinic instability due to the presence of WD. Such rare positioning is found to be lowering the tropopause with increased temperature gradient, leading to winter hailstorm formation.

Recurrence time statistics of landslide events simulated by a cellular automaton model

NASA Astrophysics Data System (ADS)

Piegari, Ester; Di Maio, Rosa; Avella, Adolfo

2014-05-01

The recurrence time statistics of a cellular automaton modelling landslide events is analyzed by performing a numerical analysis in the parameter space and estimating Fano factor behaviors. The model is an extended version of the OFC model, which is a paradigm for SOC in non-conserved systems, but it works differently from the original OFC model as a finite value of the driving rate is applied. By driving the system to instability with different rates, the model exhibits a smooth transition from a correlated to an uncorrelated regime as the effect of a change in predominant mechanisms to propagate instability. If the rate at which instability is approached is small, chain processes dominate the landslide dynamics, and power laws govern probability distributions. However, the power-law regime typical of SOC-like systems is found in a range of return intervals that becomes shorter and shorter by increasing the values of the driving rates. Indeed, if the rates at which instability is approached are large, domino processes are no longer active in propagating instability, and large events simply occur because a large number of cells simultaneously reach instability. Such a gradual loss of the effectiveness of the chain propagation mechanism causes the system gradually enter to an uncorrelated regime where recurrence time distributions are characterized by Weibull behaviors. Simulation results are qualitatively compared with those from a recent analysis performed by Witt et al.(Earth Surf. Process. Landforms, 35, 1138, 2010) for the first complete databases of landslide occurrences over a period as large as fifty years. From the comparison with the extensive landslide data set, the numerical analysis suggests that statistics of such landslide data seem to be described by a crossover region between a correlated regime and an uncorrelated regime, where recurrence time distributions are characterized by power-law and Weibull behaviors for short and long return times

Multi-spacecraft observations and transport simulations of solar energetic particles for the May 17th 2012 event

NASA Astrophysics Data System (ADS)

Battarbee, M.; Guo, J.; Dalla, S.; Wimmer-Schweingruber, R.; Swalwell, B.; Lawrence, D. J.

2018-05-01

Context. The injection, propagation and arrival of solar energetic particles (SEPs) during eruptive solar events is an important and current research topic of heliospheric physics. During the largest solar events, particles may have energies up to a few GeVs and sometimes even trigger ground-level enhancements (GLEs) at Earth. These large SEP events are best investigated through multi-spacecraft observations. Aims: We aim to study the first GLE-event of solar cycle 24, from 17th May 2012, using data from multiple spacecraft (SOHO, GOES, MSL, STEREO-A, STEREO-B and MESSENGER). These spacecraft are located throughout the inner heliosphere, at heliocentric distances between 0.34 and 1.5 astronomical units (au), covering nearly the whole range of heliospheric longitudes. Methods: We present and investigate sub-GeV proton time profiles for the event at several energy channels, obtained via different instruments aboard the above spacecraft. We investigated issues caused by magnetic connectivity, and present results of three-dimensional SEP propagation simulations. We gathered virtual time profiles and perform qualitative and quantitative comparisons with observations, assessed longitudinal injection and transport effects as well as peak intensities. Results: We distinguish different time profile shapes for well-connected and weakly connected observers, and find our onset time analysis to agree with this distinction. At select observers, we identify an additional low-energy component of Energetic Storm Particles (ESPs). Using well-connected observers for normalisation, our simulations are able to accurately recreate both time profile shapes and peak intensities at multiple observer locations. Conclusions: This synergetic approach combining numerical modelling with multi-spacecraft observations is crucial for understanding the propagation of SEPs within the interplanetary magnetic field. Our novel analysis provides valuable proof of the ability to simulate SEP propagation

Public Health System Response to Extreme Weather Events.

PubMed

Hunter, Mark D; Hunter, Jennifer C; Yang, Jane E; Crawley, Adam W; Aragón, Tomás J

2016-01-01

Extreme weather events, unpredictable and often far-reaching, constitute a persistent challenge for public health preparedness. The goal of this research is to inform public health systems improvement through examination of extreme weather events, comparing across cases to identify recurring patterns in event and response characteristics. Structured telephone-based interviews were conducted with representatives from health departments to assess characteristics of recent extreme weather events and agencies' responses. Response activities were assessed using the Centers for Disease Control and Prevention Public Health Emergency Preparedness Capabilities framework. Challenges that are typical of this response environment are reported. Forty-five local health departments in 20 US states. Respondents described public health system responses to 45 events involving tornadoes, flooding, wildfires, winter weather, hurricanes, and other storms. Events of similar scale were infrequent for a majority (62%) of the communities involved; disruption to critical infrastructure was universal. Public Health Emergency Preparedness Capabilities considered most essential involved environmental health investigations, mass care and sheltering, surveillance and epidemiology, information sharing, and public information and warning. Unanticipated response activities or operational constraints were common. We characterize extreme weather events as a "quadruple threat" because (1) direct threats to population health are accompanied by damage to public health protective and community infrastructure, (2) event characteristics often impose novel and pervasive burdens on communities, (3) responses rely on critical infrastructures whose failure both creates new burdens and diminishes response capacity, and (4) their infrequency and scale further compromise response capacity. Given the challenges associated with extreme weather events, we suggest opportunities for organizational learning and

High-Performance Monitoring Architecture for Large-Scale Distributed Systems Using Event Filtering

NASA Technical Reports Server (NTRS)

Maly, K.

1998-01-01

Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated

Method for simulating discontinuous physical systems

DOEpatents

Baty, Roy S.; Vaughn, Mark R.

2001-01-01

The mathematical foundations of conventional numerical simulation of physical systems provide no consistent description of the behavior of such systems when subjected to discontinuous physical influences. As a result, the numerical simulation of such problems requires ad hoc encoding of specific experimental results in order to address the behavior of such discontinuous physical systems. In the present invention, these foundations are replaced by a new combination of generalized function theory and nonstandard analysis. The result is a class of new approaches to the numerical simulation of physical systems which allows the accurate and well-behaved simulation of discontinuous and other difficult physical systems, as well as simpler physical systems. Applications of this new class of numerical simulation techniques to process control, robotics, and apparatus design are outlined.

Discrete event simulation for healthcare organizations: a tool for decision making.

PubMed

Hamrock, Eric; Paige, Kerrie; Parks, Jennifer; Scheulen, James; Levin, Scott

2013-01-01

Healthcare organizations face challenges in efficiently accommodating increased patient demand with limited resources and capacity. The modern reimbursement environment prioritizes the maximization of operational efficiency and the reduction of unnecessary costs (i.e., waste) while maintaining or improving quality. As healthcare organizations adapt, significant pressures are placed on leaders to make difficult operational and budgetary decisions. In lieu of hard data, decision makers often base these decisions on subjective information. Discrete event simulation (DES), a computerized method of imitating the operation of a real-world system (e.g., healthcare delivery facility) over time, can provide decision makers with an evidence-based tool to develop and objectively vet operational solutions prior to implementation. DES in healthcare commonly focuses on (1) improving patient flow, (2) managing bed capacity, (3) scheduling staff, (4) managing patient admission and scheduling procedures, and (5) using ancillary resources (e.g., labs, pharmacies). This article describes applicable scenarios, outlines DES concepts, and describes the steps required for development. An original DES model developed to examine crowding and patient flow for staffing decision making at an urban academic emergency department serves as a practical example.

Integrating Urban Infrastructure and Health System Impact Modeling for Disasters and Mass-Casualty Events

NASA Astrophysics Data System (ADS)

Balbus, J. M.; Kirsch, T.; Mitrani-Reiser, J.

2017-12-01

Over recent decades, natural disasters and mass-casualty events in United States have repeatedly revealed the serious consequences of health care facility vulnerability and the subsequent ability to deliver care for the affected people. Advances in predictive modeling and vulnerability assessment for health care facility failure, integrated infrastructure, and extreme weather events have now enabled a more rigorous scientific approach to evaluating health care system vulnerability and assessing impacts of natural and human disasters as well as the value of specific interventions. Concurrent advances in computing capacity also allow, for the first time, full integration of these multiple individual models, along with the modeling of population behaviors and mass casualty responses during a disaster. A team of federal and academic investigators led by the National Center for Disaster Medicine and Public Health (NCDMPH) is develoing a platform for integrating extreme event forecasts, health risk/impact assessment and population simulations, critical infrastructure (electrical, water, transportation, communication) impact and response models, health care facility-specific vulnerability and failure assessments, and health system/patient flow responses. The integration of these models is intended to develop much greater understanding of critical tipping points in the vulnerability of health systems during natural and human disasters and build an evidence base for specific interventions. Development of such a modeling platform will greatly facilitate the assessment of potential concurrent or sequential catastrophic events, such as a terrorism act following a severe heat wave or hurricane. This presentation will highlight the development of this modeling platform as well as applications not just for the US health system, but also for international science-based disaster risk reduction efforts, such as the Sendai Framework and the WHO SMART hospital project.

Integrating Existing Simulation Components into a Cohesive Simulation System

NASA Technical Reports Server (NTRS)

McLaughlin, Brian J.; Barrett, Larry K.

2012-01-01

A tradition of leveraging the re-use of components to help manage costs has evolved in the development of complex system. This tradition continues on in the Joint Polar Satellite System (JPSS) Program with the cloning of the Suomi National Polar-orbiting Partnership (NPP) satellite for the JPSS-1 mission, including the instrument complement. One benefit of re-use on a mission is the availability of existing simulation assets from the systems that were previously built. An issue arises in the continual shift of technology over a long mission, or multi-mission, lifecycle. As the missions mature, the requirements for the observatory simulations evolve. The challenge in this environment becomes re-using the existing components in that ever-changing landscape. To meet this challenge, the system must: establish an operational architecture that minimizes impacts on the implementation of individual components, consolidate the satisfaction of new high-impact requirements into system-level infrastructure, and build in a long-term view of system adaptation that spans the full lifecycle of the simulation system. The Flight Vehicle Test Suite (FVTS) within the JPSS Program is defining and executing this approach to ensure a robust simulation capability for the JPSS multi-mission environment

Trunk muscle recruitment patterns in simulated precrash events.

PubMed

Ólafsdóttir, Jóna Marín; Fice, Jason B; Mang, Daniel W H; Brolin, Karin; Davidsson, Johan; Blouin, Jean-Sébastien; Siegmund, Gunter P

2018-02-28

To quantify trunk muscle activation levels during whole body accelerations that simulate precrash events in multiple directions and to identify recruitment patterns for the development of active human body models. Four subjects (1 female, 3 males) were accelerated at 0.55 g (net Δv = 4.0 m/s) in 8 directions while seated on a sled-mounted car seat to simulate a precrash pulse. Electromyographic (EMG) activity in 4 trunk muscles was measured using wire electrodes inserted into the left rectus abdominis, internal oblique, iliocostalis, and multifidus muscles at the L2-L3 level. Muscle activity evoked by the perturbations was normalized by each muscle's isometric maximum voluntary contraction (MVC) activity. Spatial tuning curves were plotted at 150, 300, and 600 ms after acceleration onset. EMG activity remained below 40% MVC for the three time points for most directions. At the 150- and 300 ms time points, the highest EMG amplitudes were observed during perturbations to the left (-90°) and left rearward (-135°). EMG activity diminished by 600 ms for the anterior muscles, but not for the posterior muscles. These preliminary results suggest that trunk muscle activity may be directionally tuned at the acceleration level tested here. Although data from more subjects are needed, these preliminary data support the development of modeled trunk muscle recruitment strategies in active human body models that predict occupant responses in precrash scenarios.

Human visual system-based smoking event detection

NASA Astrophysics Data System (ADS)

Odetallah, Amjad D.; Agaian, Sos S.

2012-06-01

Human action (e.g. smoking, eating, and phoning) analysis is an important task in various application domains like video surveillance, video retrieval, human-computer interaction systems, and so on. Smoke detection is a crucial task in many video surveillance applications and could have a great impact to raise the level of safety of urban areas, public parks, airplanes, hospitals, schools and others. The detection task is challenging since there is no prior knowledge about the object's shape, texture and color. In addition, its visual features will change under different lighting and weather conditions. This paper presents a new scheme of a system for detecting human smoking events, or small smoke, in a sequence of images. In developed system, motion detection and background subtraction are combined with motion-region-saving, skin-based image segmentation, and smoke-based image segmentation to capture potential smoke regions which are further analyzed to decide on the occurrence of smoking events. Experimental results show the effectiveness of the proposed approach. As well, the developed method is capable of detecting the small smoking events of uncertain actions with various cigarette sizes, colors, and shapes.

Numerical Propulsion System Simulation

NASA Technical Reports Server (NTRS)

Naiman, Cynthia

2006-01-01

The NASA Glenn Research Center, in partnership with the aerospace industry, other government agencies, and academia, is leading the effort to develop an advanced multidisciplinary analysis environment for aerospace propulsion systems called the Numerical Propulsion System Simulation (NPSS). NPSS is a framework for performing analysis of complex systems. The initial development of NPSS focused on the analysis and design of airbreathing aircraft engines, but the resulting NPSS framework may be applied to any system, for example: aerospace, rockets, hypersonics, power and propulsion, fuel cells, ground based power, and even human system modeling. NPSS provides increased flexibility for the user, which reduces the total development time and cost. It is currently being extended to support the NASA Aeronautics Research Mission Directorate Fundamental Aeronautics Program and the Advanced Virtual Engine Test Cell (AVETeC). NPSS focuses on the integration of multiple disciplines such as aerodynamics, structure, and heat transfer with numerical zooming on component codes. Zooming is the coupling of analyses at various levels of detail. NPSS development includes capabilities to facilitate collaborative engineering. The NPSS will provide improved tools to develop custom components and to use capability for zooming to higher fidelity codes, coupling to multidiscipline codes, transmitting secure data, and distributing simulations across different platforms. These powerful capabilities extend NPSS from a zero-dimensional simulation tool to a multi-fidelity, multidiscipline system-level simulation tool for the full development life cycle.

Two Hours of Teamwork Training Improves Teamwork in Simulated Cardiopulmonary Arrest Events.

PubMed

Mahramus, Tara L; Penoyer, Daleen A; Waterval, Eugene M E; Sole, Mary L; Bowe, Eileen M

2016-01-01

Teamwork during cardiopulmonary arrest events is important for resuscitation. Teamwork improvement programs are usually lengthy. This study assessed the effectiveness of a 2-hour teamwork training program. A prospective, pretest/posttest, quasi-experimental design assessed the teamwork training program targeted to resident physicians, nurses, and respiratory therapists. Participants took part in a simulated cardiac arrest. After the simulation, participants and trained observers assessed perceptions of teamwork using the Team Emergency Assessment Measure (TEAM) tool (ratings of 0 [low] to 4 [high]). A debriefing and 45 minutes of teamwork education followed. Participants then took part in a second simulated cardiac arrest scenario. Afterward, participants and observers assessed teamwork. Seventy-three team members participated-resident physicians (25%), registered nurses (32%), and respiratory therapists (41%). The physicians had significantly less experience on code teams (P < .001). Baseline teamwork scores were 2.57 to 2.72. Participants' mean (SD) scores on the TEAM tool for the first and second simulations were 3.2 (0.5) and 3.7 (0.4), respectively (P < .001). Observers' mean (SD) TEAM scores for the first and second simulations were 3.0 (0.5) and 3.7 (0.3), respectively (P < .001). Program evaluations by participants were positive. A 2-hour simulation-based teamwork educational intervention resulted in improved perceptions of teamwork behaviors. Participants reported interactions with other disciplines, teamwork behavior education, and debriefing sessions were beneficial for enhancing the program.

Simulation of a data archival and distribution system at GSFC

NASA Technical Reports Server (NTRS)

Bedet, Jean-Jacques; Bodden, Lee; Dwyer, AL; Hariharan, P. C.; Berbert, John; Kobler, Ben; Pease, Phil

1993-01-01

A version-0 of a Data Archive and Distribution System (DADS) is being developed at GSFC to support existing and pre-EOS Earth science datasets and test Earth Observing System Data and Information System (EOSDIS) concepts. The performance of DADS is predicted using a discrete event simulation model. The goals of the simulation were to estimate the amount of disk space needed and the time required to fulfill the DADS requirements for ingestion (14 GB/day) and distribution (48 GB/day). The model has demonstrated that 4 mm and 8 mm stackers can play a critical role in improving the performance of the DADS, since it takes, on average, 3 minutes to manually mount/dismount tapes compared to less than a minute with stackers. With two 4 mm stackers and two 8 mm stackers, and a single operator per shift, the DADS requirements can be met within 16 hours using a total of 9 GB of disk space. When the DADS has no stacker, and the DADS depends entirely on operators to handle the distribution tapes, the simulation has shown that the DADS requirements can still be met within 16 hours, but a minimum of 4 operators per shift were required. The compression/decompression of data sets is very CPU intensive, and relatively slow when performed in software, thereby contributing to an increase in the amount of disk space needed.

Design a Learning-Oriented Fall Event Reporting System Based on Kirkpatrick Model.

PubMed

Zhou, Sicheng; Kang, Hong; Gong, Yang

2017-01-01

Patient fall has been a severe problem in healthcare facilities around the world due to its prevalence and cost. Routine fall prevention training programs are not as effective as expected. Using event reporting systems is the trend for reducing patient safety events such as falls, although some limitations of the systems exist at current stage. We summarized these limitations through literature review, and developed an improved web-based fall event reporting system. The Kirkpatrick model, widely used in the business area for training program evaluation, has been integrated during the design of our system. Different from traditional event reporting systems that only collect and store the reports, our system automatically annotates and analyzes the reported events, and provides users with timely knowledge support specific to the reported event. The paper illustrates the design of our system and how its features are intended to reduce patient falls by learning from previous errors.

Numerical propulsion system simulation

NASA Technical Reports Server (NTRS)

Lytle, John K.; Remaklus, David A.; Nichols, Lester D.

1990-01-01

The cost of implementing new technology in aerospace propulsion systems is becoming prohibitively expensive. One of the major contributors to the high cost is the need to perform many large scale system tests. Extensive testing is used to capture the complex interactions among the multiple disciplines and the multiple components inherent in complex systems. The objective of the Numerical Propulsion System Simulation (NPSS) is to provide insight into these complex interactions through computational simulations. This will allow for comprehensive evaluation of new concepts early in the design phase before a commitment to hardware is made. It will also allow for rapid assessment of field-related problems, particularly in cases where operational problems were encountered during conditions that would be difficult to simulate experimentally. The tremendous progress taking place in computational engineering and the rapid increase in computing power expected through parallel processing make this concept feasible within the near future. However it is critical that the framework for such simulations be put in place now to serve as a focal point for the continued developments in computational engineering and computing hardware and software. The NPSS concept which is described will provide that framework.

Economic Evaluation of Bariatric Surgery in Mexico Using Discrete Event Simulation.

PubMed

Zanela, Olivo Omar; Cabra, Hermilo Arturo; Meléndez, Guillermo; Anaya, Pablo; Rupprecht, Frederic

2012-12-01

Morbid obesity represents high costs to health institutions in controlling associated comorbidities. It has been shown that bariatric surgery resolves or improves comorbidities, thus reducing resource utilization. This analysis estimated the total costs of treating morbid obesity and related comorbidities through conventional treatment compared to bariatric surgery under the Mexican public health system perspective. An economic evaluation model was developed by using discrete event simulation. One hundred fifty patients were created in each arm, with considered comorbidities allocated randomly. Preoperative comorbidity prevalences and bariatric surgery's efficacy for resolving them were obtained from published literature. Comorbidity treatment costs were obtained from the 2007 Mexican Institute of Social Security diagnosis-related group list and publications from the National Institute of Public Health. Only 12 patients were operated each month on the surgical arm. Complications associated with comorbidities were not considered. The considered time frame for simulation was 10 years, with a 4.5% annual discount rate. Return on investment, or cost breakeven point, for bariatric surgery was obtained after 6.8 years. Total costs for the surgical group were 52% less than conventional treatment group costs after 10 years. Bariatric surgery reduced the cost of treating type 2 diabetes, hypertension, and hypercholesterolemia by 59%, 53%, and 65%, respectively. Return on investment for bariatric surgery in patients with type 2 diabetes as the only comorbidity was 4.4 years. Despite conservative assumptions, investment in bariatric surgery is recouped in 6.8 years, generating relevant potential savings in the treatment of morbidly obese patients. In high-risk subpopulations, return on investment time is shorter. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Simulation Framework for Intelligent Transportation Systems

DOT National Transportation Integrated Search

1996-10-01

A simulation framework has been developed for a large-scale, comprehensive, scaleable simulation of an Intelligent Transportation System. The simulator is designed for running on parellel computers and distributed (networked) computer systems, but ca...

Managing the risk of extreme climate events in Australian major wheat production systems.

PubMed

Luo, Qunying; Trethowan, Richard; Tan, Daniel K Y

2018-06-04

Extreme climate events (ECEs) such as drought, frost risk and heat stress cause significant economic losses in Australia. The risk posed by ECEs in the wheat production systems of Australia could be better managed through the identification of safe flowering (SFW) and optimal time of sowing (TOS) windows. To address this issue, three locations (Narrabri, Roseworthy and Merredin), three cultivars (Suntop and Gregory for Narrabri, Mace for both Roseworthy and Merredin) and 20 TOS at 1-week intervals between 1 April and 12 August for the period from 1957 to 2007 were evaluated using the Agricultural Production System sIMulator (APSIM)-Wheat model. Simulation results show that (1) the average frequency of frost events decreased with TOS from 8 to 0 days (d) across the four cases (the combination of locations and cultivars), (2) the average frequency of heat stress events increased with TOS across all cases from 0 to 10 d, (3) soil moisture stress (SMS) increased with earlier TOS before reaching a plateau and then slightly decreasing for Suntop and Gregory at Narrabri and Mace at Roseworthy while SMS increased with TOS for Mace at Merredin from 0.1 to 0.8, (4) Mace at Merredin had the earliest and widest SFW (216-260) while Mace at Roseworthy had latest SFW (257-280), (5) frost risk and heat stress determine SFW at wetter sites (i.e. Narrabri and Roseworthy) while frost risk and SMS determine SFW at drier site (i.e. Merredin) and (6) the optimal TOS (window) to maximise wheat yield are 6-20 May, 13-27 May and 15 April at Narrabri, Roseworthy and Merredin, respectively. These findings provide important and specific information for wheat growers about the management of ECE risk on farm. Furthermore, the coupling of the APSIM crop models with state-of-the-art seasonal and intra-seasonal climate forecast information provides an important tool for improved management of the risk of ECEs in economically important cropping industries in the foreseeable future.

Managing the risk of extreme climate events in Australian major wheat production systems

NASA Astrophysics Data System (ADS)

Luo, Qunying; Trethowan, Richard; Tan, Daniel K. Y.

2018-06-01

Extreme climate events (ECEs) such as drought, frost risk and heat stress cause significant economic losses in Australia. The risk posed by ECEs in the wheat production systems of Australia could be better managed through the identification of safe flowering (SFW) and optimal time of sowing (TOS) windows. To address this issue, three locations (Narrabri, Roseworthy and Merredin), three cultivars (Suntop and Gregory for Narrabri, Mace for both Roseworthy and Merredin) and 20 TOS at 1-week intervals between 1 April and 12 August for the period from 1957 to 2007 were evaluated using the Agricultural Production System sIMulator (APSIM)-Wheat model. Simulation results show that (1) the average frequency of frost events decreased with TOS from 8 to 0 days (d) across the four cases (the combination of locations and cultivars), (2) the average frequency of heat stress events increased with TOS across all cases from 0 to 10 d, (3) soil moisture stress (SMS) increased with earlier TOS before reaching a plateau and then slightly decreasing for Suntop and Gregory at Narrabri and Mace at Roseworthy while SMS increased with TOS for Mace at Merredin from 0.1 to 0.8, (4) Mace at Merredin had the earliest and widest SFW (216-260) while Mace at Roseworthy had latest SFW (257-280), (5) frost risk and heat stress determine SFW at wetter sites (i.e. Narrabri and Roseworthy) while frost risk and SMS determine SFW at drier site (i.e. Merredin) and (6) the optimal TOS (window) to maximise wheat yield are 6-20 May, 13-27 May and 15 April at Narrabri, Roseworthy and Merredin, respectively. These findings provide important and specific information for wheat growers about the management of ECE risk on farm. Furthermore, the coupling of the APSIM crop models with state-of-the-art seasonal and intra-seasonal climate forecast information provides an important tool for improved management of the risk of ECEs in economically important cropping industries in the foreseeable future.

Issues in visual support to real-time space system simulation solved in the Systems Engineering Simulator

NASA Technical Reports Server (NTRS)

Yuen, Vincent K.

1989-01-01

The Systems Engineering Simulator has addressed the major issues in providing visual data to its real-time man-in-the-loop simulations. Out-the-window views and CCTV views are provided by three scene systems to give the astronauts their real-world views. To expand the window coverage for the Space Station Freedom workstation a rotating optics system is used to provide the widest field of view possible. To provide video signals to as many viewpoints as possible, windows and CCTVs, with a limited amount of hardware, a video distribution system has been developed to time-share the video channels among viewpoints at the selection of the simulation users. These solutions have provided the visual simulation facility for real-time man-in-the-loop simulations for the NASA space program.

Analytical Assessment of a Gross Leakage Event Within the International Space Station (ISS) Node 2 Internal Active Thermal Control System (IATCS)

NASA Technical Reports Server (NTRS)

Holt, James M.; Clanton, Stephen E.

1999-01-01

Results of the International Space Station (ISS) Node 2 Internal Active Thermal Control System (IATCS) gross leakage analysis are presented for evaluating total leakage flowrates and volume discharge caused by a gross leakage event (i.e. open boundary condition). A Systems Improved Numerical Differencing Analyzer and Fluid Integrator (SINDA/FLUINT) thermal hydraulic mathematical model (THMM) representing the Node 2 IATCS was developed to simulate system performance under steady-state nominal conditions as well as the transient flow effects resulting from an open line exposed to ambient. The objective of the analysis was to determine the adequacy of the leak detection software in limiting the quantity of fluid lost during a gross leakage event to within an acceptable level.

A Hardware-in-the-Loop Simulation Platform for the Verification and Validation of Safety Control Systems

NASA Astrophysics Data System (ADS)

Rankin, Drew J.; Jiang, Jin

2011-04-01

Verification and validation (V&V) of safety control system quality and performance is required prior to installing control system hardware within nuclear power plants (NPPs). Thus, the objective of the hardware-in-the-loop (HIL) platform introduced in this paper is to verify the functionality of these safety control systems. The developed platform provides a flexible simulated testing environment which enables synchronized coupling between the real and simulated world. Within the platform, National Instruments (NI) data acquisition (DAQ) hardware provides an interface between a programmable electronic system under test (SUT) and a simulation computer. Further, NI LabVIEW resides on this remote DAQ workstation for signal conversion and routing between Ethernet and standard industrial signals as well as for user interface. The platform is applied to the testing of a simplified implementation of Canadian Deuterium Uranium (CANDU) shutdown system no. 1 (SDS1) which monitors only the steam generator level of the simulated NPP. CANDU NPP simulation is performed on a Darlington NPP desktop training simulator provided by Ontario Power Generation (OPG). Simplified SDS1 logic is implemented on an Invensys Tricon v9 programmable logic controller (PLC) to test the performance of both the safety controller and the implemented logic. Prior to HIL simulation, platform availability of over 95% is achieved for the configuration used during the V&V of the PLC. Comparison of HIL simulation results to benchmark simulations shows good operational performance of the PLC following a postulated initiating event (PIE).

An RCM-E simulation of a steady magnetospheric convection event

NASA Astrophysics Data System (ADS)

Yang, J.; Toffoletto, F.; Wolf, R.; Song, Y.

2009-12-01

We present simulation results of an idealized steady magnetospheric convection (SMC) event using the Rice Convection Model coupled with an equilibrium magnetic field solver (RCM-E). The event is modeled by placing a plasma distribution with substantially depleted entropy parameter PV5/3 on the RCM's high latitude boundary. The calculated magnetic field shows a highly depressed configuration due to the enhanced westward current around geosynchronous orbit where the resulting partial ring current is stronger and more symmetric than in a typical substorm growth phase. The magnitude of BZ component in the mid plasma sheet is large compared to empirical magnetic field models. Contrary to some previous results, there is no deep BZ minimum in the near-Earth plasma sheet. This suggests that the magnetosphere could transfer into a strong adiabatic earthward convection mode without significant stretching of the plasma-sheet magnetic field, when there are flux tubes with depleted plasma content continuously entering the inner magnetosphere from the mid-tail. Virtual AU/AL and Dst indices are also calculated using a synthetic magnetogram code and are compared to typical features in published observations.

Simulation and field monitoring of moisture in alpine rock walls during freeze-thaw events

NASA Astrophysics Data System (ADS)

Rode, Matthias; Sass, Oliver

2013-04-01

Detachment of rock fragments from alpine rockwalls is mainly assigned to frost weathering. However, the actual process of frost weathering as well as the contribution of further weathering processes (e.g. hydration, thermal fatigue) is poorly understood. Rock moisture distribution during freeze-thaw events is key to understanding weathering. For this purpose, different measuring systems were set up in two study areas (Dachstein - permafrost area (2700m a.s.l.) and Gesäuse - non permafrost area (900m a.s.l.), Styria, Austria) within the framework of the research project ROCKING ALPS (FWF-P24244). We installed small-scale 2D-geoelectric survey lines in north and in south facing rockwalls, supplemented by high resolution temperature and moisture sensors. Moisture is determined by means of resistivity measurements which are difficult to calibrate, but provide good time series. Additional novel moisture sensors were developed which use the heat capacity of the surrounding rock as a proxy of water content. These sensors give point readings from a defined depth and are independent from soluble salt contents. Pore water pressure occurring during freeze-thaw events is recorded by means of pressure transducers (piezometers). First results from the Dachstein show that short term latent heat effects during the phase change have crucial influence on the moisture content. These results are cross-checked by simulation calculations. Based on meteorologic and lithologic input values, the simulation routine calculates, in an iterative procedure, the hourly energy and water transport at different depths, the latter in the liquid and in the vapor phase. The calculated profile lines and chronological sequences of rock moisture allow - in combination with temperature data - to detect possible periods of active weathering. First simulations from the Gesäuse show that maximum values of pore saturation occur from May to September. The thresholds of the "classical" frost shattering theory

Implementation of Tree and Butterfly Barriers with Optimistic Time Management Algorithms for Discrete Event Simulation

NASA Astrophysics Data System (ADS)

Rizvi, Syed S.; Shah, Dipali; Riasat, Aasia

The Time Wrap algorithm [3] offers a run time recovery mechanism that deals with the causality errors. These run time recovery mechanisms consists of rollback, anti-message, and Global Virtual Time (GVT) techniques. For rollback, there is a need to compute GVT which is used in discrete-event simulation to reclaim the memory, commit the output, detect the termination, and handle the errors. However, the computation of GVT requires dealing with transient message problem and the simultaneous reporting problem. These problems can be dealt in an efficient manner by the Samadi's algorithm [8] which works fine in the presence of causality errors. However, the performance of both Time Wrap and Samadi's algorithms depends on the latency involve in GVT computation. Both algorithms give poor latency for large simulation systems especially in the presence of causality errors. To improve the latency and reduce the processor ideal time, we implement tree and butterflies barriers with the optimistic algorithm. Our analysis shows that the use of synchronous barriers such as tree and butterfly with the optimistic algorithm not only minimizes the GVT latency but also minimizes the processor idle time.

Classification of single-trial auditory events using dry-wireless EEG during real and motion simulated flight.

PubMed

Callan, Daniel E; Durantin, Gautier; Terzibas, Cengiz

2015-01-01

Application of neuro-augmentation technology based on dry-wireless EEG may be considerably beneficial for aviation and space operations because of the inherent dangers involved. In this study we evaluate classification performance of perceptual events using a dry-wireless EEG system during motion platform based flight simulation and actual flight in an open cockpit biplane to determine if the system can be used in the presence of considerable environmental and physiological artifacts. A passive task involving 200 random auditory presentations of a chirp sound was used for evaluation. The advantage of this auditory task is that it does not interfere with the perceptual motor processes involved with piloting the plane. Classification was based on identifying the presentation of a chirp sound vs. silent periods. Evaluation of Independent component analysis (ICA) and Kalman filtering to enhance classification performance by extracting brain activity related to the auditory event from other non-task related brain activity and artifacts was assessed. The results of permutation testing revealed that single trial classification of presence or absence of an auditory event was significantly above chance for all conditions on a novel test set. The best performance could be achieved with both ICA and Kalman filtering relative to no processing: Platform Off (83.4% vs. 78.3%), Platform On (73.1% vs. 71.6%), Biplane Engine Off (81.1% vs. 77.4%), and Biplane Engine On (79.2% vs. 66.1%). This experiment demonstrates that dry-wireless EEG can be used in environments with considerable vibration, wind, acoustic noise, and physiological artifacts and achieve good single trial classification performance that is necessary for future successful application of neuro-augmentation technology based on brain-machine interfaces.

Model simulation of the Manasquan water-supply system in Monmouth County, New Jersey

USGS Publications Warehouse

Chang, Ming; Tasker, Gary D.; Nieswand, Steven

2001-01-01

Model simulation of the Manasquan Water Supply System in Monmouth County, New Jersey, was completed using historic hydrologic data to evaluate the effects of operational and withdrawal alternatives on the Manasquan reservoir and pumping system. Changes in the system operations can be simulated with the model using precipitation forecasts. The Manasquan Reservoir system model operates by using daily streamflow values, which were reconstructed from historical U.S. Geological Survey streamflow-gaging station records. The model is able to run in two modes--General Risk analysis Model (GRAM) and Position Analysis Model (POSA). The GRAM simulation procedure uses reconstructed historical streamflow records to provide probability estimates of certain events, such as reservoir storage levels declining below a specific level, when given an assumed set of operating rules and withdrawal rates. POSA can be used to forecast the likelihood of specified outcomes, such as streamflows falling below statutory passing flows, associated with a specific working plan for the water-supply system over a period of months. The user can manipulate the model and generate graphs and tables of streamflows and storage, for example. This model can be used as a management tool to facilitate the development of drought warning and drought emergency rule curves and safe yield values for the water-supply system.

A SAS-based solution to evaluate study design efficiency of phase I pediatric oncology trials via discrete event simulation.

PubMed

Barrett, Jeffrey S; Jayaraman, Bhuvana; Patel, Dimple; Skolnik, Jeffrey M

2008-06-01

Previous exploration of oncology study design efficiency has focused on Markov processes alone (probability-based events) without consideration for time dependencies. Barriers to study completion include time delays associated with patient accrual, inevaluability (IE), time to dose limiting toxicities (DLT) and administrative and review time. Discrete event simulation (DES) can incorporate probability-based assignment of DLT and IE frequency, correlated with cohort in the case of DLT, with time-based events defined by stochastic relationships. A SAS-based solution to examine study efficiency metrics and evaluate design modifications that would improve study efficiency is presented. Virtual patients are simulated with attributes defined from prior distributions of relevant patient characteristics. Study population datasets are read into SAS macros which select patients and enroll them into a study based on the specific design criteria if the study is open to enrollment. Waiting times, arrival times and time to study events are also sampled from prior distributions; post-processing of study simulations is provided within the decision macros and compared across designs in a separate post-processing algorithm. This solution is examined via comparison of the standard 3+3 decision rule relative to the "rolling 6" design, a newly proposed enrollment strategy for the phase I pediatric oncology setting.

Stability of model-based event-triggered control systems: a separation property

NASA Astrophysics Data System (ADS)

Hao, Fei; Yu, Hao

2017-04-01

To save resource of communication, this paper investigates the model-based event-triggered control systems. Two main problems are considered in this paper. One is, for given plant and model, to design event conditions to guarantee the stability of the systems. The other is to consider the effect of the model matrices on the stability. The results show that the closed-loop systems can be asymptotically stabilised with any model matrices in compact sets if the parameters in the event conditions are within the designed ranges. Then, a separation property of model-based event-triggered control is proposed. Namely, the design of the controller gain and the event condition can be separated from the selection of the model matrices. Based on this property, an adaption mechanism is introduced to the model-based event-triggered control systems, which can further improve the sampling performance. Finally, a numerical example is given to show the efficiency and feasibility of the developed results.

Patient flow improvement for an ophthalmic specialist outpatient clinic with aid of discrete event simulation and design of experiment.

PubMed

Pan, Chong; Zhang, Dali; Kon, Audrey Wan Mei; Wai, Charity Sue Lea; Ang, Woo Boon

2015-06-01

Continuous improvement in process efficiency for specialist outpatient clinic (SOC) systems is increasingly being demanded due to the growth of the patient population in Singapore. In this paper, we propose a discrete event simulation (DES) model to represent the patient and information flow in an ophthalmic SOC system in the Singapore National Eye Centre (SNEC). Different improvement strategies to reduce the turnaround time for patients in the SOC were proposed and evaluated with the aid of the DES model and the Design of Experiment (DOE). Two strategies for better patient appointment scheduling and one strategy for dilation-free examination are estimated to have a significant impact on turnaround time for patients. One of the improvement strategies has been implemented in the actual SOC system in the SNEC with promising improvement reported.

A Deep Space Orbit Determination Software: Overview and Event Prediction Capability

NASA Astrophysics Data System (ADS)

Kim, Youngkwang; Park, Sang-Young; Lee, Eunji; Kim, Minsik

2017-06-01

This paper presents an overview of deep space orbit determination software (DSODS), as well as validation and verification results on its event prediction capabilities. DSODS was developed in the MATLAB object-oriented programming environment to support the Korea Pathfinder Lunar Orbiter (KPLO) mission. DSODS has three major capabilities: celestial event prediction for spacecraft, orbit determination with deep space network (DSN) tracking data, and DSN tracking data simulation. To achieve its functionality requirements, DSODS consists of four modules: orbit propagation (OP), event prediction (EP), data simulation (DS), and orbit determination (OD) modules. This paper explains the highest-level data flows between modules in event prediction, orbit determination, and tracking data simulation processes. Furthermore, to address the event prediction capability of DSODS, this paper introduces OP and EP modules. The role of the OP module is to handle time and coordinate system conversions, to propagate spacecraft trajectories, and to handle the ephemerides of spacecraft and celestial bodies. Currently, the OP module utilizes the General Mission Analysis Tool (GMAT) as a third-party software component for highfidelity deep space propagation, as well as time and coordinate system conversions. The role of the EP module is to predict celestial events, including eclipses, and ground station visibilities, and this paper presents the functionality requirements of the EP module. The validation and verification results show that, for most cases, event prediction errors were less than 10 millisec when compared with flight proven mission analysis tools such as GMAT and Systems Tool Kit (STK). Thus, we conclude that DSODS is capable of predicting events for the KPLO in real mission applications.

Simulating X-ray bursts during a transient accretion event

NASA Astrophysics Data System (ADS)

Johnston, Zac; Heger, Alexander; Galloway, Duncan K.

2018-06-01

Modelling of thermonuclear X-ray bursts on accreting neutron stars has to date focused on stable accretion rates. However, bursts are also observed during episodes of transient accretion. During such events, the accretion rate can evolve significantly between bursts, and this regime provides a unique test for burst models. The accretion-powered millisecond pulsar SAX J1808.4-3658 exhibits accretion outbursts every 2-3 yr. During the well-sampled month-long outburst of 2002 October, four helium-rich X-ray bursts were observed. Using this event as a test case, we present the first multizone simulations of X-ray bursts under a time-dependent accretion rate. We investigate the effect of using a time-dependent accretion rate in comparison to constant, averaged rates. Initial results suggest that using a constant, average accretion rate between bursts may underestimate the recurrence time when the accretion rate is decreasing, and overestimate it when the accretion rate is increasing. Our model, with an accreted hydrogen fraction of X = 0.44 and a CNO metallicity of ZCNO = 0.02, reproduces the observed burst arrival times and fluences with root mean square (rms) errors of 2.8 h, and 0.11× 10^{-6} erg cm^{-2}, respectively. Our results support previous modelling that predicted two unobserved bursts and indicate that additional bursts were also missed by observations.

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

DKIST Adaptive Optics System: Simulation Results

NASA Astrophysics Data System (ADS)

Marino, Jose; Schmidt, Dirk

2016-05-01

The 4 m class Daniel K. Inouye Solar Telescope (DKIST), currently under construction, will be equipped with an ultra high order solar adaptive optics (AO) system. The requirements and capabilities of such a solar AO system are beyond those of any other solar AO system currently in operation. We must rely on solar AO simulations to estimate and quantify its performance.We present performance estimation results of the DKIST AO system obtained with a new solar AO simulation tool. This simulation tool is a flexible and fast end-to-end solar AO simulator which produces accurate solar AO simulations while taking advantage of current multi-core computer technology. It relies on full imaging simulations of the extended field Shack-Hartmann wavefront sensor (WFS), which directly includes important secondary effects such as field dependent distortions and varying contrast of the WFS sub-aperture images.

Improved transition path sampling methods for simulation of rare events

NASA Astrophysics Data System (ADS)

Chopra, Manan; Malshe, Rohit; Reddy, Allam S.; de Pablo, J. J.

2008-04-01

The free energy surfaces of a wide variety of systems encountered in physics, chemistry, and biology are characterized by the existence of deep minima separated by numerous barriers. One of the central aims of recent research in computational chemistry and physics has been to determine how transitions occur between deep local minima on rugged free energy landscapes, and transition path sampling (TPS) Monte-Carlo methods have emerged as an effective means for numerical investigation of such transitions. Many of the shortcomings of TPS-like approaches generally stem from their high computational demands. Two new algorithms are presented in this work that improve the efficiency of TPS simulations. The first algorithm uses biased shooting moves to render the sampling of reactive trajectories more efficient. The second algorithm is shown to substantially improve the accuracy of the transition state ensemble by introducing a subset of local transition path simulations in the transition state. The system considered in this work consists of a two-dimensional rough energy surface that is representative of numerous systems encountered in applications. When taken together, these algorithms provide gains in efficiency of over two orders of magnitude when compared to traditional TPS simulations.

Event-Triggered Model Predictive Control for Embedded Artificial Pancreas Systems.

PubMed

Chakrabarty, Ankush; Zavitsanou, Stamatina; Doyle, Francis J; Dassau, Eyal

2018-03-01

The development of artificial pancreas (AP) technology for deployment in low-energy, embedded devices is contingent upon selecting an efficient control algorithm for regulating glucose in people with type 1 diabetes mellitus. In this paper, we aim to lower the energy consumption of the AP by reducing controller updates, that is, the number of times the decision-making algorithm is invoked to compute an appropriate insulin dose. Physiological insights into glucose management are leveraged to design an event-triggered model predictive controller (MPC) that operates efficiently, without compromising patient safety. The proposed event-triggered MPC is deployed on a wearable platform. Its robustness to latent hypoglycemia, model mismatch, and meal misinformation is tested, with and without meal announcement, on the full version of the US-FDA accepted UVA/Padova metabolic simulator. The event-based controller remains on for 18 h of 41 h in closed loop with unannounced meals, while maintaining glucose in 70-180 mg/dL for 25 h, compared to 27 h for a standard MPC controller. With meal announcement, the time in 70-180 mg/dL is almost identical, with the controller operating a mere 25.88% of the time in comparison with a standard MPC. A novel control architecture for AP systems enables safe glycemic regulation with reduced processor computations. Our proposed framework integrated seamlessly with a wide variety of popular MPC variants reported in AP research, customizes tradeoff between glycemic regulation and efficacy according to prior design specifications, and eliminates judicious prior selection of controller sampling times.

Address-event-based platform for bioinspired spiking systems

NASA Astrophysics Data System (ADS)

Jiménez-Fernández, A.; Luján, C. D.; Linares-Barranco, A.; Gómez-Rodríguez, F.; Rivas, M.; Jiménez, G.; Civit, A.

2007-05-01

Address Event Representation (AER) is an emergent neuromorphic interchip communication protocol that allows a real-time virtual massive connectivity between huge number neurons, located on different chips. By exploiting high speed digital communication circuits (with nano-seconds timings), synaptic neural connections can be time multiplexed, while neural activity signals (with mili-seconds timings) are sampled at low frequencies. Also, neurons generate "events" according to their activity levels. More active neurons generate more events per unit time, and access the interchip communication channel more frequently, while neurons with low activity consume less communication bandwidth. When building multi-chip muti-layered AER systems, it is absolutely necessary to have a computer interface that allows (a) reading AER interchip traffic into the computer and visualizing it on the screen, and (b) converting conventional frame-based video stream in the computer into AER and injecting it at some point of the AER structure. This is necessary for test and debugging of complex AER systems. In the other hand, the use of a commercial personal computer implies to depend on software tools and operating systems that can make the system slower and un-robust. This paper addresses the problem of communicating several AER based chips to compose a powerful processing system. The problem was discussed in the Neuromorphic Engineering Workshop of 2006. The platform is based basically on an embedded computer, a powerful FPGA and serial links, to make the system faster and be stand alone (independent from a PC). A new platform is presented that allow to connect up to eight AER based chips to a Spartan 3 4000 FPGA. The FPGA is responsible of the network communication based in Address-Event and, at the same time, to map and transform the address space of the traffic to implement a pre-processing. A MMU microprocessor (Intel XScale 400MHz Gumstix Connex computer) is also connected to the FPGA

Core discrete event simulation model for the evaluation of health care technologies in major depressive disorder.

PubMed

Vataire, Anne-Lise; Aballéa, Samuel; Antonanzas, Fernando; Roijen, Leona Hakkaart-van; Lam, Raymond W; McCrone, Paul; Persson, Ulf; Toumi, Mondher

2014-03-01

A review of existing economic models in major depressive disorder (MDD) highlighted the need for models with longer time horizons that also account for heterogeneity in treatment pathways between patients. A core discrete event simulation model was developed to estimate health and cost outcomes associated with alternative treatment strategies. This model simulated short- and long-term clinical events (partial response, remission, relapse, recovery, and recurrence), adverse events, and treatment changes (titration, switch, addition, and discontinuation) over up to 5 years. Several treatment pathways were defined on the basis of fictitious antidepressants with three levels of efficacy, tolerability, and price (low, medium, and high) from first line to third line. The model was populated with input data from the literature for the UK setting. Model outputs include time in different health states, quality-adjusted life-years (QALYs), and costs from National Health Service and societal perspectives. The codes are open source. Predicted costs and QALYs from this model are within the range of results from previous economic evaluations. The largest cost components from the payer perspective were physician visits and hospitalizations. Key parameters driving the predicted costs and QALYs were utility values, effectiveness, and frequency of physician visits. Differences in QALYs and costs between two strategies with different effectiveness increased approximately twofold when the time horizon increased from 1 to 5 years. The discrete event simulation model can provide a more comprehensive evaluation of different therapeutic options in MDD, compared with existing Markov models, and can be used to compare a wide range of health care technologies in various groups of patients with MDD. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Simulating neural systems with Xyce.

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

Schiek, Richard Louis; Thornquist, Heidi K.; Mei, Ting

2012-12-01

Sandias parallel circuit simulator, Xyce, can address large scale neuron simulations in a new way extending the range within which one can perform high-fidelity, multi-compartment neuron simulations. This report documents the implementation of neuron devices in Xyce, their use in simulation and analysis of neuron systems.

The effects of indoor environmental exposures on pediatric asthma: a discrete event simulation model.

PubMed

Fabian, M Patricia; Stout, Natasha K; Adamkiewicz, Gary; Geggel, Amelia; Ren, Cizao; Sandel, Megan; Levy, Jonathan I

2012-09-18

In the United States, asthma is the most common chronic disease of childhood across all socioeconomic classes and is the most frequent cause of hospitalization among children. Asthma exacerbations have been associated with exposure to residential indoor environmental stressors such as allergens and air pollutants as well as numerous additional factors. Simulation modeling is a valuable tool that can be used to evaluate interventions for complex multifactorial diseases such as asthma but in spite of its flexibility and applicability, modeling applications in either environmental exposures or asthma have been limited to date. We designed a discrete event simulation model to study the effect of environmental factors on asthma exacerbations in school-age children living in low-income multi-family housing. Model outcomes include asthma symptoms, medication use, hospitalizations, and emergency room visits. Environmental factors were linked to percent predicted forced expiratory volume in 1 second (FEV1%), which in turn was linked to risk equations for each outcome. Exposures affecting FEV1% included indoor and outdoor sources of NO2 and PM2.5, cockroach allergen, and dampness as a proxy for mold. Model design parameters and equations are described in detail. We evaluated the model by simulating 50,000 children over 10 years and showed that pollutant concentrations and health outcome rates are comparable to values reported in the literature. In an application example, we simulated what would happen if the kitchen and bathroom exhaust fans were improved for the entire cohort, and showed reductions in pollutant concentrations and healthcare utilization rates. We describe the design and evaluation of a discrete event simulation model of pediatric asthma for children living in low-income multi-family housing. Our model simulates the effect of environmental factors (combustion pollutants and allergens), medication compliance, seasonality, and medical history on asthma outcomes

The effects of indoor environmental exposures on pediatric asthma: a discrete event simulation model

PubMed Central

2012-01-01

Background In the United States, asthma is the most common chronic disease of childhood across all socioeconomic classes and is the most frequent cause of hospitalization among children. Asthma exacerbations have been associated with exposure to residential indoor environmental stressors such as allergens and air pollutants as well as numerous additional factors. Simulation modeling is a valuable tool that can be used to evaluate interventions for complex multifactorial diseases such as asthma but in spite of its flexibility and applicability, modeling applications in either environmental exposures or asthma have been limited to date. Methods We designed a discrete event simulation model to study the effect of environmental factors on asthma exacerbations in school-age children living in low-income multi-family housing. Model outcomes include asthma symptoms, medication use, hospitalizations, and emergency room visits. Environmental factors were linked to percent predicted forced expiratory volume in 1 second (FEV1%), which in turn was linked to risk equations for each outcome. Exposures affecting FEV1% included indoor and outdoor sources of NO2 and PM2.5, cockroach allergen, and dampness as a proxy for mold. Results Model design parameters and equations are described in detail. We evaluated the model by simulating 50,000 children over 10 years and showed that pollutant concentrations and health outcome rates are comparable to values reported in the literature. In an application example, we simulated what would happen if the kitchen and bathroom exhaust fans were improved for the entire cohort, and showed reductions in pollutant concentrations and healthcare utilization rates. Conclusions We describe the design and evaluation of a discrete event simulation model of pediatric asthma for children living in low-income multi-family housing. Our model simulates the effect of environmental factors (combustion pollutants and allergens), medication compliance, seasonality

A Multi-Agent Approach to the Simulation of Robotized Manufacturing Systems

NASA Astrophysics Data System (ADS)

Foit, K.; Gwiazda, A.; Banaś, W.

2016-08-01

The recent years of eventful industry development, brought many competing products, addressed to the same market segment. The shortening of a development cycle became a necessity if the company would like to be competitive. Because of switching to the Intelligent Manufacturing model the industry search for new scheduling algorithms, while the traditional ones do not meet the current requirements. The agent-based approach has been considered by many researchers as an important way of evolution of modern manufacturing systems. Due to the properties of the multi-agent systems, this methodology is very helpful during creation of the model of production system, allowing depicting both processing and informational part. The complexity of such approach makes the analysis impossible without the computer assistance. Computer simulation still uses a mathematical model to recreate a real situation, but nowadays the 2D or 3D virtual environments or even virtual reality have been used for realistic illustration of the considered systems. This paper will focus on robotized manufacturing system and will present the one of possible approaches to the simulation of such systems. The selection of multi-agent approach is motivated by the flexibility of this solution that offers the modularity, robustness and autonomy.

Impact of including or excluding both-armed zero-event studies on using standard meta-analysis methods for rare event outcome: a simulation study

PubMed Central

Cheng, Ji; Pullenayegum, Eleanor; Marshall, John K; Thabane, Lehana

2016-01-01

Objectives There is no consensus on whether studies with no observed events in the treatment and control arms, the so-called both-armed zero-event studies, should be included in a meta-analysis of randomised controlled trials (RCTs). Current analytic approaches handled them differently depending on the choice of effect measures and authors' discretion. Our objective is to evaluate the impact of including or excluding both-armed zero-event (BA0E) studies in meta-analysis of RCTs with rare outcome events through a simulation study. Method We simulated 2500 data sets for different scenarios varying the parameters of baseline event rate, treatment effect and number of patients in each trial, and between-study variance. We evaluated the performance of commonly used pooling methods in classical meta-analysis—namely, Peto, Mantel-Haenszel with fixed-effects and random-effects models, and inverse variance method with fixed-effects and random-effects models—using bias, root mean square error, length of 95% CI and coverage. Results The overall performance of the approaches of including or excluding BA0E studies in meta-analysis varied according to the magnitude of true treatment effect. Including BA0E studies introduced very little bias, decreased mean square error, narrowed the 95% CI and increased the coverage when no true treatment effect existed. However, when a true treatment effect existed, the estimates from the approach of excluding BA0E studies led to smaller bias than including them. Among all evaluated methods, the Peto method excluding BA0E studies gave the least biased results when a true treatment effect existed. Conclusions We recommend including BA0E studies when treatment effects are unlikely, but excluding them when there is a decisive treatment effect. Providing results of including and excluding BA0E studies to assess the robustness of the pooled estimated effect is a sensible way to communicate the results of a meta-analysis when the treatment

Using Discrete Event Simulation to predict KPI's at a Projected Emergency Room.

PubMed

Concha, Pablo; Neriz, Liliana; Parada, Danilo; Ramis, Francisco

2015-01-01

Discrete Event Simulation (DES) is a powerful factor in the design of clinical facilities. DES enables facilities to be built or adapted to achieve the expected Key Performance Indicators (KPI's) such as average waiting times according to acuity, average stay times and others. Our computational model was built and validated using expert judgment and supporting statistical data. One scenario studied resulted in a 50% decrease in the average cycle time of patients compared to the original model, mainly by modifying the patient's attention model.

Simulation of extreme rainfall event of November 2009 over Jeddah, Saudi Arabia: the explicit role of topography and surface heating

NASA Astrophysics Data System (ADS)

Almazroui, Mansour; Raju, P. V. S.; Yusef, A.; Hussein, M. A. A.; Omar, M.

2018-04-01

In this paper, a nonhydrostatic Weather Research and Forecasting (WRF) model has been used to simulate the extreme precipitation event of 25 November 2009, over Jeddah, Saudi Arabia. The model is integrated in three nested (27, 9, and 3 km) domains with the initial and boundary forcing derived from the NCEP reanalysis datasets. As a control experiment, the model integrated for 48 h initiated at 0000 UTC on 24 November 2009. The simulated rainfall in the control experiment depicts in well agreement with Tropical Rainfall Measurement Mission rainfall estimates in terms of intensity as well as spatio-temporal distribution. Results indicate that a strong low-level (850 hPa) wind over Jeddah and surrounding regions enhanced the moisture and temperature gradient and created a conditionally unstable atmosphere that favored the development of the mesoscale system. The influences of topography and heat exchange process in the atmosphere were investigated on the development of extreme precipitation event; two sensitivity experiments are carried out: one without topography and another without exchange of surface heating to the atmosphere. The results depict that both surface heating and topography played crucial role in determining the spatial distribution and intensity of the extreme rainfall over Jeddah. The topography favored enhanced uplift motion that further strengthened the low-level jet and hence the rainfall over Jeddah and adjacent areas. On the other hand, the absence of surface heating considerably reduced the simulated rainfall by 30% as compared to the observations.

A simulation study of capacity utilization to predict future capacity for manufacturing system sustainability

NASA Astrophysics Data System (ADS)

Rimo, Tan Hauw Sen; Chai Tin, Ong

2017-12-01

Capacity utilization (CU) measurement is an important task in a manufacturing system, especially in make-to-order (MTO) type manufacturing system with product customization, in predicting capacity to meet future demand. A stochastic discrete-event simulation is developed using ARENA software to determine CU and capacity gap (CG) in short run production function. This study focused on machinery breakdown and product defective rate as random variables in the simulation. The study found that the manufacturing system run in 68.01% CU and 31.99% CG. It is revealed that machinery breakdown and product defective rate have a direct relationship with CU. By improving product defective rate into zero defect, manufacturing system can improve CU up to 73.56% and CG decrease to 26.44%. While improving machinery breakdown into zero breakdowns will improve CU up to 93.99% and the CG decrease to 6.01%. This study helps operation level to study CU using “what-if” analysis in order to meet future demand in more practical and easier method by using simulation approach. Further study is recommended by including other random variables that affect CU to make the simulation closer with the real-life situation for a better decision.

News and Events - Nanodelivery Systems and Devices Branch

Cancer.gov

The latest news from the Nanodelivery Systems and Devices Branch and the Alliance, as well as upcoming and past events attended by the Nanodelivery Systems and Devices Branchstaff, and relevant upcoming scientific meetings.

Direct generation of event-timing equations for generalized flow shop systems

NASA Astrophysics Data System (ADS)

Doustmohammadi, Ali; Kamen, Edward W.

1995-11-01

Flow shop production lines are very common in manufacturing systems such as car assemblies, manufacturing of electronic circuits, etc. In this paper, a systematic procedure is given for generating event-timing equations directly from the machine interconnections for a generalized flow shop system. The events considered here correspond to completion times of machine operations. It is assumed that the scheduling policy is cyclic (periodic). For a given flow shop system, the open connection dynamics of the machines are derived first. Then interconnection matrices characterizing the routing of parts in the system are obtained from the given system configuration. The open connection dynamics of the machines and the interconnection matrices are then combined together to obtain the overall system dynamics given by an equation of the form X(k+1) equals A(k)X(k) B(k)V(k+1) defined over the max-plus algebra. Here the state X(k) is the vector of completion times and V(k+1) is an external input vector consisting of the arrival times of parts. It is shown that if the machines are numbered in an appropriate way and the states are selected according to certain rules, the matrix A(k) will be in a special (canonical) form. The model obtained here is useful or the analysis of system behavior and for carrying out simulations. In particular, the canonical form of A(k) enables one to study system bottlenecks and the minimal cycle time during steady-state operation. The approach presented in this paper is believed to be more straightforward compared to existing max-plus algebra formulations of flow shop systems. In particular, three advantages of the proposed approach are: (1) it yields timing equations directly from the system configuration and hence there is no need to first derive a Petri net or a digraph equivalent of the system; (2) a change in the system configuration only affects the interconnection matrices and hence does not require rederiving the entire set of equations; (3

Lyapunov Stability of Fuzzy Discrete Event Systems

NASA Astrophysics Data System (ADS)

Liu, Fuchun; Qiu, Daowen

Fuzzy discrete event systems (FDESs) as a generalization of (crisp) discrete event systems (DESs) may better deal with the problems of fuzziness, impreciseness, and subjectivity. Qiu, Cao and Ying, Liu and Qiu interestingly developed the theory of FDESs. As a continuation of Qiu's work, this paper is to deal with the Lyapunov stability of FDESs, some main results of crisp DESs are generalized. We formalize the notions of the reachability of fuzzy states defined on a metric space. A linear algorithm of computing the r-reachable fuzzy state set is presented. Then we introduce the definitions of stability and asymptotical stability in the sense of Lyapunov to guarantee the convergence of the behaviors of fuzzy automaton to the desired fuzzy states when system engages in some illegal behaviors which can be tolerated. In particular, we present a necessary and sufficient condition for stability and another for asymptotical stability of FDESs.

Modelling machine ensembles with discrete event dynamical system theory

NASA Technical Reports Server (NTRS)

Hunter, Dan

1990-01-01

Discrete Event Dynamical System (DEDS) theory can be utilized as a control strategy for future complex machine ensembles that will be required for in-space construction. The control strategy involves orchestrating a set of interactive submachines to perform a set of tasks for a given set of constraints such as minimum time, minimum energy, or maximum machine utilization. Machine ensembles can be hierarchically modeled as a global model that combines the operations of the individual submachines. These submachines are represented in the global model as local models. Local models, from the perspective of DEDS theory , are described by the following: a set of system and transition states, an event alphabet that portrays actions that takes a submachine from one state to another, an initial system state, a partial function that maps the current state and event alphabet to the next state, and the time required for the event to occur. Each submachine in the machine ensemble is presented by a unique local model. The global model combines the local models such that the local models can operate in parallel under the additional logistic and physical constraints due to submachine interactions. The global model is constructed from the states, events, event functions, and timing requirements of the local models. Supervisory control can be implemented in the global model by various methods such as task scheduling (open-loop control) or implementing a feedback DEDS controller (closed-loop control).

A Risk Assessment System with Automatic Extraction of Event Types

NASA Astrophysics Data System (ADS)

Capet, Philippe; Delavallade, Thomas; Nakamura, Takuya; Sandor, Agnes; Tarsitano, Cedric; Voyatzi, Stavroula

In this article we describe the joint effort of experts in linguistics, information extraction and risk assessment to integrate EventSpotter, an automatic event extraction engine, into ADAC, an automated early warning system. By detecting as early as possible weak signals of emerging risks ADAC provides a dynamic synthetic picture of situations involving risk. The ADAC system calculates risk on the basis of fuzzy logic rules operated on a template graph whose leaves are event types. EventSpotter is based on a general purpose natural language dependency parser, XIP, enhanced with domain-specific lexical resources (Lexicon-Grammar). Its role is to automatically feed the leaves with input data.

Analytical Assessment of a Gross Leakage Event Within the International Space Station (ISS) Node 2 Internal Active Thermal Control System (IATCS)

NASA Technical Reports Server (NTRS)

Holt, James M.; Clanton, Stephen E.

2001-01-01

Results of the International Space Station (ISS) Node 2 Internal Active Thermal Control System (IATCS) gross leakage analysis are presented for evaluating total leakage flow rates and volume discharge caused by a gross leakage event (i.e. open boundary condition). A Systems Improved Numerical Differencing Analyzer and Fluid Integrator (SINDA85/FLUINT) thermal hydraulic mathematical model (THMM) representing the Node 2 IATCS was developed to simulate system performance under steady-state nominal conditions as well as the transient flow effect resulting from an open line exposed to ambient. The objective of the analysis was to determine the adequacy of the leak detection software in limiting the quantity of fluid lost during a gross leakage event to within an acceptable level.

A discrete event simulation model for evaluating the performances of an m/g/c/c state dependent queuing system.

PubMed

Khalid, Ruzelan; Nawawi, Mohd Kamal M; Kawsar, Luthful A; Ghani, Noraida A; Kamil, Anton A; Mustafa, Adli

2013-01-01

M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed.

A Discrete Event Simulation Model for Evaluating the Performances of an M/G/C/C State Dependent Queuing System

PubMed Central

Khalid, Ruzelan; M. Nawawi, Mohd Kamal; Kawsar, Luthful A.; Ghani, Noraida A.; Kamil, Anton A.; Mustafa, Adli

2013-01-01

M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed. PMID:23560037

Multiscale models and stochastic simulation methods for computing rare but key binding events in cell biology

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

Guerrier, C.; Holcman, D., E-mail: david.holcman@ens.fr; Mathematical Institute, Oxford OX2 6GG, Newton Institute

The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationallymore » greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.« less

Simulating spontaneous aseismic and seismic slip events on evolving faults

NASA Astrophysics Data System (ADS)

Herrendörfer, Robert; van Dinther, Ylona; Pranger, Casper; Gerya, Taras

2017-04-01

Plate motion along tectonic boundaries is accommodated by different slip modes: steady creep, seismic slip and slow slip transients. Due to mainly indirect observations and difficulties to scale results from laboratory experiments to nature, it remains enigmatic which fault conditions favour certain slip modes. Therefore, we are developing a numerical modelling approach that is capable of simulating different slip modes together with the long-term fault evolution in a large-scale tectonic setting. We extend the 2D, continuum mechanics-based, visco-elasto-plastic thermo-mechanical model that was designed to simulate slip transients in large-scale geodynamic simulations (van Dinther et al., JGR, 2013). We improve the numerical approach to accurately treat the non-linear problem of plasticity (see also EGU 2017 abstract by Pranger et al.). To resolve a wide slip rate spectrum on evolving faults, we develop an invariant reformulation of the conventional rate-and-state dependent friction (RSF) and adapt the time step (Lapusta et al., JGR, 2000). A crucial part of this development is a conceptual ductile fault zone model that relates slip rates along discrete planes to the effective macroscopic plastic strain rates in the continuum. We test our implementation first in a simple 2D setup with a single fault zone that has a predefined initial thickness. Results show that deformation localizes in case of steady creep and for very slow slip transients to a bell-shaped strain rate profile across the fault zone, which suggests that a length scale across the fault zone may exist. This continuum length scale would overcome the common mesh-dependency in plasticity simulations and question the conventional treatment of aseismic slip on infinitely thin fault zones. We test the introduction of a diffusion term (similar to the damage description in Lyakhovsky et al., JMPS, 2011) into the state evolution equation and its effect on (de-)localization during faster slip events. We compare

A multiprocessor operating system simulator

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

Johnston, G.M.; Campbell, R.H.

1988-01-01

This paper describes a multiprocessor operating system simulator that was developed by the authors in the Fall of 1987. The simulator was built in response to the need to provide students with an environment in which to build and test operating system concepts as part of the coursework of a third-year undergraduate operating systems course. Written in C++, the simulator uses the co-routine style task package that is distributed with the AT and T C++ Translator to provide a hierarchy of classes that represents a broad range of operating system software and hardware components. The class hierarchy closely follows thatmore » of the Choices family of operating systems for loosely and tightly coupled multiprocessors. During an operating system course, these classes are refined and specialized by students in homework assignments to facilitate experimentation with different aspects of operating system design and policy decisions. The current implementation runs on the IBM RT PC under 4.3bsd UNIX.« less

A Multiprocessor Operating System Simulator

NASA Technical Reports Server (NTRS)

Johnston, Gary M.; Campbell, Roy H.

1988-01-01

This paper describes a multiprocessor operating system simulator that was developed by the authors in the Fall semester of 1987. The simulator was built in response to the need to provide students with an environment in which to build and test operating system concepts as part of the coursework of a third-year undergraduate operating systems course. Written in C++, the simulator uses the co-routine style task package that is distributed with the AT&T C++ Translator to provide a hierarchy of classes that represents a broad range of operating system software and hardware components. The class hierarchy closely follows that of the 'Choices' family of operating systems for loosely- and tightly-coupled multiprocessors. During an operating system course, these classes are refined and specialized by students in homework assignments to facilitate experimentation with different aspects of operating system design and policy decisions. The current implementation runs on the IBM RT PC under 4.3bsd UNIX.

Cardiovascular Events in Systemic Lupus Erythematosus