CyberMedVPS: visual programming for development of simulators.

PubMed

Morais, Aline M; Machado, Liliane S

2011-01-01

Computer applications based on Virtual Reality (VR) has been outstanding in training and teaching in the medical filed due to their ability to simulate realistic in which users can practice skills and decision making in different situations. But was realized in these frameworks a hard interaction of non-programmers users. Based on this problematic will be shown the CyberMedVPS, a graphical module which implement Visual Programming concepts to solve an interaction trouble. Frameworks to develop such simulators are available but their use demands knowledge of programming. Based on this problematic will be shown the CyberMedVPS, a graphical module for the CyberMed framework, which implements Visual Programming concepts to allow the development of simulators by non-programmers professionals of the medical field.

A Computational Framework for Efficient Low Temperature Plasma Simulations

NASA Astrophysics Data System (ADS)

Verma, Abhishek Kumar; Venkattraman, Ayyaswamy

2016-10-01

Over the past years, scientific computing has emerged as an essential tool for the investigation and prediction of low temperature plasmas (LTP) applications which includes electronics, nanomaterial synthesis, metamaterials etc. To further explore the LTP behavior with greater fidelity, we present a computational toolbox developed to perform LTP simulations. This framework will allow us to enhance our understanding of multiscale plasma phenomenon using high performance computing tools mainly based on OpenFOAM FVM distribution. Although aimed at microplasma simulations, the modular framework is able to perform multiscale, multiphysics simulations of physical systems comprises of LTP. Some salient introductory features are capability to perform parallel, 3D simulations of LTP applications on unstructured meshes. Performance of the solver is tested based on numerical results assessing accuracy and efficiency of benchmarks for problems in microdischarge devices. Numerical simulation of microplasma reactor at atmospheric pressure with hemispherical dielectric coated electrodes will be discussed and hence, provide an overview of applicability and future scope of this framework.

Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation

NASA Technical Reports Server (NTRS)

Afjeh, Abdollah A.; Reed, John A.

2003-01-01

The following reports are presented on this project:A first year progress report on: Development of a Dynamically Configurable,Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; A second year progress report on: Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; An Extensible, Interchangeable and Sharable Database Model for Improving Multidisciplinary Aircraft Design; Interactive, Secure Web-enabled Aircraft Engine Simulation Using XML Databinding Integration; and Improving the Aircraft Design Process Using Web-based Modeling and Simulation.

Towards a Theoretical Framework for Educational Simulations.

ERIC Educational Resources Information Center

Winer, Laura R.; Vazquez-Abad, Jesus

1981-01-01

Discusses the need for a sustained and systematic effort toward establishing a theoretical framework for educational simulations, proposes the adaptation of models borrowed from the natural and applied sciences, and describes three simulations based on such a model adapted using Brunerian learning theory. Sixteen references are listed. (LLS)

Interactive, Secure Web-enabled Aircraft Engine Simulation Using XML Databinding Integration

NASA Technical Reports Server (NTRS)

Lin, Risheng; Afjeh, Abdollah A.

2003-01-01

This paper discusses the detailed design of an XML databinding framework for aircraft engine simulation. The framework provides an object interface to access and use engine data. while at the same time preserving the meaning of the original data. The Language independent representation of engine component data enables users to move around XML data using HTTP through disparate networks. The application of this framework is demonstrated via a web-based turbofan propulsion system simulation using the World Wide Web (WWW). A Java Servlet based web component architecture is used for rendering XML engine data into HTML format and dealing with input events from the user, which allows users to interact with simulation data from a web browser. The simulation data can also be saved to a local disk for archiving or to restart the simulation at a later time.

A Generic Simulation Framework for Non-Entangled based Experimental Quantum Cryptography and Communication: Quantum Cryptography and Communication Simulator (QuCCs)

NASA Astrophysics Data System (ADS)

Buhari, Abudhahir; Zukarnain, Zuriati Ahmad; Khalid, Roszelinda; Zakir Dato', Wira Jaafar Ahmad

2016-11-01

The applications of quantum information science move towards bigger and better heights for the next generation technology. Especially, in the field of quantum cryptography and quantum computation, the world already witnessed various ground-breaking tangible product and promising results. Quantum cryptography is one of the mature field from quantum mechanics and already available in the markets. The current state of quantum cryptography is still under various researches in order to reach the heights of digital cryptography. The complexity of quantum cryptography is higher due to combination of hardware and software. The lack of effective simulation tool to design and analyze the quantum cryptography experiments delays the reaching distance of the success. In this paper, we propose a framework to achieve an effective non-entanglement based quantum cryptography simulation tool. We applied hybrid simulation technique i.e. discrete event, continuous event and system dynamics. We also highlight the limitations of a commercial photonic simulation tool based experiments. Finally, we discuss ideas for achieving one-stop simulation package for quantum based secure key distribution experiments. All the modules of simulation framework are viewed from the computer science perspective.

Extending the FairRoot framework to allow for simulation and reconstruction of free streaming data

NASA Astrophysics Data System (ADS)

Al-Turany, M.; Klein, D.; Manafov, A.; Rybalchenko, A.; Uhlig, F.

2014-06-01

The FairRoot framework is the standard framework for simulation, reconstruction and data analysis for the FAIR experiments. The framework is designed to optimise the accessibility for beginners and developers, to be flexible and to cope with future developments. FairRoot enhances the synergy between the different physics experiments. As a first step toward simulation of free streaming data, the time based simulation was introduced to the framework. The next step is the event source simulation. This is achieved via a client server system. After digitization the so called "samplers" can be started, where sampler can read the data of the corresponding detector from the simulation files and make it available for the reconstruction clients. The system makes it possible to develop and validate the online reconstruction algorithms. In this work, the design and implementation of the new architecture and the communication layer will be described.

A Framework for Determining the Return on Investment of Simulation-Based Training in Health Care

PubMed Central

Bukhari, Hatim; Andreatta, Pamela; Goldiez, Brian; Rabelo, Luis

2017-01-01

This article describes a framework that has been developed to monetize the real value of simulation-based training in health care. A significant consideration has been given to the incorporation of the intangible and qualitative benefits, not only the tangible and quantitative benefits of simulation-based training in health care. The framework builds from three works: the value measurement methodology (VMM) used by several departments of the US Government, a methodology documented in several books by Dr Jack Phillips to monetize various training approaches, and a traditional return on investment methodology put forth by Frost and Sullivan, and Immersion Medical. All 3 source materials were adapted to create an integrated methodology that can be readily implemented. This article presents details on each of these methods and how they can be integrated and presents a framework that integrates the previous methods. In addition to that, it describes the concept and the application of the developed framework. As a test of the applicability of the framework, a real case study has been used to demonstrate the application of the framework. This case study provides real data related to the correlation between the pediatric patient cardiopulmonary arrest (CPA) survival rates and a simulation-based mock codes at the University of Michigan tertiary care academic medical center. It is important to point out that the proposed framework offers the capability to consider a wide range of benefits and values, but on the other hand, there are several limitations that has been discussed and need to be taken in consideration. PMID:28133988

A Framework for Determining the Return on Investment of Simulation-Based Training in Health Care.

PubMed

Bukhari, Hatim; Andreatta, Pamela; Goldiez, Brian; Rabelo, Luis

2017-01-01

This article describes a framework that has been developed to monetize the real value of simulation-based training in health care. A significant consideration has been given to the incorporation of the intangible and qualitative benefits, not only the tangible and quantitative benefits of simulation-based training in health care. The framework builds from three works: the value measurement methodology (VMM) used by several departments of the US Government, a methodology documented in several books by Dr Jack Phillips to monetize various training approaches, and a traditional return on investment methodology put forth by Frost and Sullivan, and Immersion Medical. All 3 source materials were adapted to create an integrated methodology that can be readily implemented. This article presents details on each of these methods and how they can be integrated and presents a framework that integrates the previous methods. In addition to that, it describes the concept and the application of the developed framework. As a test of the applicability of the framework, a real case study has been used to demonstrate the application of the framework. This case study provides real data related to the correlation between the pediatric patient cardiopulmonary arrest (CPA) survival rates and a simulation-based mock codes at the University of Michigan tertiary care academic medical center. It is important to point out that the proposed framework offers the capability to consider a wide range of benefits and values, but on the other hand, there are several limitations that has been discussed and need to be taken in consideration.

A Metascalable Computing Framework for Large Spatiotemporal-Scale Atomistic Simulations

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

Nomura, K; Seymour, R; Wang, W

2009-02-17

A metascalable (or 'design once, scale on new architectures') parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials based on spatiotemporal data locality principles, which is expected to scale on emerging multipetaflops architectures. The framework consists of: (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms for high complexity problems; (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, while introducing multiple parallelization axes; and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these O(N) algorithms onto a multicore cluster based onmore » hybrid implementation combining message passing and critical section-free multithreading. The EDC-STEP-HCD framework exposes maximal concurrency and data locality, thereby achieving: (1) inter-node parallel efficiency well over 0.95 for 218 billion-atom molecular-dynamics and 1.68 trillion electronic-degrees-of-freedom quantum-mechanical simulations on 212,992 IBM BlueGene/L processors (superscalability); (2) high intra-node, multithreading parallel efficiency (nanoscalability); and (3) nearly perfect time/ensemble parallel efficiency (eon-scalability). The spatiotemporal scale covered by MD simulation on a sustained petaflops computer per day (i.e. petaflops {center_dot} day of computing) is estimated as NT = 2.14 (e.g. N = 2.14 million atoms for T = 1 microseconds).« less

Task-based image quality assessment in radiation therapy: initial characterization and demonstration with CT simulation images

NASA Astrophysics Data System (ADS)

Dolly, Steven R.; Anastasio, Mark A.; Yu, Lifeng; Li, Hua

2017-03-01

In current radiation therapy practice, image quality is still assessed subjectively or by utilizing physically-based metrics. Recently, a methodology for objective task-based image quality (IQ) assessment in radiation therapy was proposed by Barrett et al.1 In this work, we present a comprehensive implementation and evaluation of this new IQ assessment methodology. A modular simulation framework was designed to perform an automated, computer-simulated end-to-end radiation therapy treatment. A fully simulated framework was created that utilizes new learning-based stochastic object models (SOM) to obtain known organ boundaries, generates a set of images directly from the numerical phantoms created with the SOM, and automates the image segmentation and treatment planning steps of a radiation therapy work ow. By use of this computational framework, therapeutic operating characteristic (TOC) curves can be computed and the area under the TOC curve (AUTOC) can be employed as a figure-of-merit to guide optimization of different components of the treatment planning process. The developed computational framework is employed to optimize X-ray CT pre-treatment imaging. We demonstrate that use of the radiation therapy-based-based IQ measures lead to different imaging parameters than obtained by use of physical-based measures.

Component Framework for Loosely Coupled High Performance Integrated Plasma Simulations

NASA Astrophysics Data System (ADS)

Elwasif, W. R.; Bernholdt, D. E.; Shet, A. G.; Batchelor, D. B.; Foley, S.

2010-11-01

We present the design and implementation of a component-based simulation framework for the execution of coupled time-dependent plasma modeling codes. The Integrated Plasma Simulator (IPS) provides a flexible lightweight component model that streamlines the integration of stand alone codes into coupled simulations. Standalone codes are adapted to the IPS component interface specification using a thin wrapping layer implemented in the Python programming language. The framework provides services for inter-component method invocation, configuration, task, and data management, asynchronous event management, simulation monitoring, and checkpoint/restart capabilities. Services are invoked, as needed, by the computational components to coordinate the execution of different aspects of coupled simulations on Massive parallel Processing (MPP) machines. A common plasma state layer serves as the foundation for inter-component, file-based data exchange. The IPS design principles, implementation details, and execution model will be presented, along with an overview of several use cases.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.

PubMed

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator

PubMed Central

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation. PMID:28596730

An Example-Based Brain MRI Simulation Framework.

PubMed

He, Qing; Roy, Snehashis; Jog, Amod; Pham, Dzung L

2015-02-21

The simulation of magnetic resonance (MR) images plays an important role in the validation of image analysis algorithms such as image segmentation, due to lack of sufficient ground truth in real MR images. Previous work on MRI simulation has focused on explicitly modeling the MR image formation process. However, because of the overwhelming complexity of MR acquisition these simulations must involve simplifications and approximations that can result in visually unrealistic simulated images. In this work, we describe an example-based simulation framework, which uses an "atlas" consisting of an MR image and its anatomical models derived from the hard segmentation. The relationships between the MR image intensities and its anatomical models are learned using a patch-based regression that implicitly models the physics of the MR image formation. Given the anatomical models of a new brain, a new MR image can be simulated using the learned regression. This approach has been extended to also simulate intensity inhomogeneity artifacts based on the statistical model of training data. Results show that the example based MRI simulation method is capable of simulating different image contrasts and is robust to different choices of atlas. The simulated images resemble real MR images more than simulations produced by a physics-based model.

Metascalable molecular dynamics simulation of nano-mechano-chemistry

NASA Astrophysics Data System (ADS)

Shimojo, F.; Kalia, R. K.; Nakano, A.; Nomura, K.; Vashishta, P.

2008-07-01

We have developed a metascalable (or 'design once, scale on new architectures') parallel application-development framework for first-principles based simulations of nano-mechano-chemical processes on emerging petaflops architectures based on spatiotemporal data locality principles. The framework consists of (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms, (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these scalable algorithms onto hardware. The EDC-STEP-HCD framework exposes and expresses maximal concurrency and data locality, thereby achieving parallel efficiency as high as 0.99 for 1.59-billion-atom reactive force field molecular dynamics (MD) and 17.7-million-atom (1.56 trillion electronic degrees of freedom) quantum mechanical (QM) MD in the framework of the density functional theory (DFT) on adaptive multigrids, in addition to 201-billion-atom nonreactive MD, on 196 608 IBM BlueGene/L processors. We have also used the framework for automated execution of adaptive hybrid DFT/MD simulation on a grid of six supercomputers in the US and Japan, in which the number of processors changed dynamically on demand and tasks were migrated according to unexpected faults. The paper presents the application of the framework to the study of nanoenergetic materials: (1) combustion of an Al/Fe2O3 thermite and (2) shock initiation and reactive nanojets at a void in an energetic crystal.

A framework for modeling scenario-based barrier island storm impacts

USGS Publications Warehouse

Mickey, Rangley; Long, Joseph W.; Dalyander, P. Soupy; Plant, Nathaniel G.; Thompson, David M.

2018-01-01

Methods for investigating the vulnerability of existing or proposed coastal features to storm impacts often rely on simplified parametric models or one-dimensional process-based modeling studies that focus on changes to a profile across a dune or barrier island. These simple studies tend to neglect the impacts to curvilinear or alongshore varying island planforms, influence of non-uniform nearshore hydrodynamics and sediment transport, irregular morphology of the offshore bathymetry, and impacts from low magnitude wave events (e.g. cold fronts). Presented here is a framework for simulating regionally specific, low and high magnitude scenario-based storm impacts to assess the alongshore variable vulnerabilities of a coastal feature. Storm scenarios based on historic hydrodynamic conditions were derived and simulated using the process-based morphologic evolution model XBeach. Model results show that the scenarios predicted similar patterns of erosion and overwash when compared to observed qualitative morphologic changes from recent storm events that were not included in the dataset used to build the scenarios. The framework model simulations were capable of predicting specific areas of vulnerability in the existing feature and the results illustrate how this storm vulnerability simulation framework could be used as a tool to help inform the decision-making process for scientists, engineers, and stakeholders involved in coastal zone management or restoration projects.

Gathering Validity Evidence for Surgical Simulation: A Systematic Review.

PubMed

Borgersen, Nanna Jo; Naur, Therese M H; Sørensen, Stine M D; Bjerrum, Flemming; Konge, Lars; Subhi, Yousif; Thomsen, Ann Sofia S

2018-06-01

To identify current trends in the use of validity frameworks in surgical simulation, to provide an overview of the evidence behind the assessment of technical skills in all surgical specialties, and to present recommendations and guidelines for future validity studies. Validity evidence for assessment tools used in the evaluation of surgical performance is of paramount importance to ensure valid and reliable assessment of skills. We systematically reviewed the literature by searching 5 databases (PubMed, EMBASE, Web of Science, PsycINFO, and the Cochrane Library) for studies published from January 1, 2008, to July 10, 2017. We included original studies evaluating simulation-based assessments of health professionals in surgical specialties and extracted data on surgical specialty, simulator modality, participant characteristics, and the validity framework used. Data were synthesized qualitatively. We identified 498 studies with a total of 18,312 participants. Publications involving validity assessments in surgical simulation more than doubled from 2008 to 2010 (∼30 studies/year) to 2014 to 2016 (∼70 to 90 studies/year). Only 6.6% of the studies used the recommended contemporary validity framework (Messick). The majority of studies used outdated frameworks such as face validity. Significant differences were identified across surgical specialties. The evaluated assessment tools were mostly inanimate or virtual reality simulation models. An increasing number of studies have gathered validity evidence for simulation-based assessments in surgical specialties, but the use of outdated frameworks remains common. To address the current practice, this paper presents guidelines on how to use the contemporary validity framework when designing validity studies.

A framework using cluster-based hybrid network architecture for collaborative virtual surgery.

PubMed

Qin, Jing; Choi, Kup-Sze; Poon, Wai-Sang; Heng, Pheng-Ann

2009-12-01

Research on collaborative virtual environments (CVEs) opens the opportunity for simulating the cooperative work in surgical operations. It is however a challenging task to implement a high performance collaborative surgical simulation system because of the difficulty in maintaining state consistency with minimum network latencies, especially when sophisticated deformable models and haptics are involved. In this paper, an integrated framework using cluster-based hybrid network architecture is proposed to support collaborative virtual surgery. Multicast transmission is employed to transmit updated information among participants in order to reduce network latencies, while system consistency is maintained by an administrative server. Reliable multicast is implemented using distributed message acknowledgment based on cluster cooperation and sliding window technique. The robustness of the framework is guaranteed by the failure detection chain which enables smooth transition when participants join and leave the collaboration, including normal and involuntary leaving. Communication overhead is further reduced by implementing a number of management approaches such as computational policies and collaborative mechanisms. The feasibility of the proposed framework is demonstrated by successfully extending an existing standalone orthopedic surgery trainer into a collaborative simulation system. A series of experiments have been conducted to evaluate the system performance. The results demonstrate that the proposed framework is capable of supporting collaborative surgical simulation.

Next Generation Simulation Framework for Robotic and Human Space Missions

NASA Technical Reports Server (NTRS)

Cameron, Jonathan M.; Balaram, J.; Jain, Abhinandan; Kuo, Calvin; Lim, Christopher; Myint, Steven

2012-01-01

The Dartslab team at NASA's Jet Propulsion Laboratory (JPL) has a long history of developing physics-based simulations based on the Darts/Dshell simulation framework that have been used to simulate many planetary robotic missions, such as the Cassini spacecraft and the rovers that are currently driving on Mars. Recent collaboration efforts between the Dartslab team at JPL and the Mission Operations Directorate (MOD) at NASA Johnson Space Center (JSC) have led to significant enhancements to the Dartslab DSENDS (Dynamics Simulator for Entry, Descent and Surface landing) software framework. The new version of DSENDS is now being used for new planetary mission simulations at JPL. JSC is using DSENDS as the foundation for a suite of software known as COMPASS (Core Operations, Mission Planning, and Analysis Spacecraft Simulation) that is the basis for their new human space mission simulations and analysis. In this paper, we will describe the collaborative process with the JPL Dartslab and the JSC MOD team that resulted in the redesign and enhancement of the DSENDS software. We will outline the improvements in DSENDS that simplify creation of new high-fidelity robotic/spacecraft simulations. We will illustrate how DSENDS simulations are assembled and show results from several mission simulations.

A Component-Based Extension Framework for Large-Scale Parallel Simulations in NEURON

PubMed Central

King, James G.; Hines, Michael; Hill, Sean; Goodman, Philip H.; Markram, Henry; Schürmann, Felix

2008-01-01

As neuronal simulations approach larger scales with increasing levels of detail, the neurosimulator software represents only a part of a chain of tools ranging from setup, simulation, interaction with virtual environments to analysis and visualizations. Previously published approaches to abstracting simulator engines have not received wide-spread acceptance, which in part may be to the fact that they tried to address the challenge of solving the model specification problem. Here, we present an approach that uses a neurosimulator, in this case NEURON, to describe and instantiate the network model in the simulator's native model language but then replaces the main integration loop with its own. Existing parallel network models are easily adopted to run in the presented framework. The presented approach is thus an extension to NEURON but uses a component-based architecture to allow for replaceable spike exchange components and pluggable components for monitoring, analysis, or control that can run in this framework alongside with the simulation. PMID:19430597

A data-driven dynamics simulation framework for railway vehicles

NASA Astrophysics Data System (ADS)

Nie, Yinyu; Tang, Zhao; Liu, Fengjia; Chang, Jian; Zhang, Jianjun

2018-03-01

The finite element (FE) method is essential for simulating vehicle dynamics with fine details, especially for train crash simulations. However, factors such as the complexity of meshes and the distortion involved in a large deformation would undermine its calculation efficiency. An alternative method, the multi-body (MB) dynamics simulation provides satisfying time efficiency but limited accuracy when highly nonlinear dynamic process is involved. To maintain the advantages of both methods, this paper proposes a data-driven simulation framework for dynamics simulation of railway vehicles. This framework uses machine learning techniques to extract nonlinear features from training data generated by FE simulations so that specific mesh structures can be formulated by a surrogate element (or surrogate elements) to replace the original mechanical elements, and the dynamics simulation can be implemented by co-simulation with the surrogate element(s) embedded into a MB model. This framework consists of a series of techniques including data collection, feature extraction, training data sampling, surrogate element building, and model evaluation and selection. To verify the feasibility of this framework, we present two case studies, a vertical dynamics simulation and a longitudinal dynamics simulation, based on co-simulation with MATLAB/Simulink and Simpack, and a further comparison with a popular data-driven model (the Kriging model) is provided. The simulation result shows that using the legendre polynomial regression model in building surrogate elements can largely cut down the simulation time without sacrifice in accuracy.

A GPU-based framework for modeling real-time 3D lung tumor conformal dosimetry with subject-specific lung tumor motion.

PubMed

Min, Yugang; Santhanam, Anand; Neelakkantan, Harini; Ruddy, Bari H; Meeks, Sanford L; Kupelian, Patrick A

2010-09-07

In this paper, we present a graphics processing unit (GPU)-based simulation framework to calculate the delivered dose to a 3D moving lung tumor and its surrounding normal tissues, which are undergoing subject-specific lung deformations. The GPU-based simulation framework models the motion of the 3D volumetric lung tumor and its surrounding tissues, simulates the dose delivery using the dose extracted from a treatment plan using Pinnacle Treatment Planning System, Phillips, for one of the 3DCTs of the 4DCT and predicts the amount and location of radiation doses deposited inside the lung. The 4DCT lung datasets were registered with each other using a modified optical flow algorithm. The motion of the tumor and the motion of the surrounding tissues were simulated by measuring the changes in lung volume during the radiotherapy treatment using spirometry. The real-time dose delivered to the tumor for each beam is generated by summing the dose delivered to the target volume at each increase in lung volume during the beam delivery time period. The simulation results showed the real-time capability of the framework at 20 discrete tumor motion steps per breath, which is higher than the number of 4DCT steps (approximately 12) reconstructed during multiple breathing cycles.

Developing a Problem-Based Learning Simulation: An Economics Unit on Trade

ERIC Educational Resources Information Center

Maxwell, Nan L.; Mergendoller, John R.; Bellisimo, Yolanda

2004-01-01

This article argues that the merger of simulations and problem-based learning (PBL) can enhance both active-learning strategies. Simulations benefit by using a PBL framework to promote student-directed learning and problem-solving skills to explain a simulated dilemma with multiple solutions. PBL benefits because simulations structure the…

Agent-based modeling of the spread of influenza-like illness in an emergency department: a simulation study.

PubMed

Laskowski, Marek; Demianyk, Bryan C P; Witt, Julia; Mukhi, Shamir N; Friesen, Marcia R; McLeod, Robert D

2011-11-01

The objective of this paper was to develop an agent-based modeling framework in order to simulate the spread of influenza virus infection on a layout based on a representative hospital emergency department in Winnipeg, Canada. In doing so, the study complements mathematical modeling techniques for disease spread, as well as modeling applications focused on the spread of antibiotic-resistant nosocomial infections in hospitals. Twenty different emergency department scenarios were simulated, with further simulation of four infection control strategies. The agent-based modeling approach represents systems modeling, in which the emergency department was modeled as a collection of agents (patients and healthcare workers) and their individual characteristics, behaviors, and interactions. The framework was coded in C++ using Qt4 libraries running under the Linux operating system. A simple ordinary least squares (OLS) regression was used to analyze the data, in which the percentage of patients that became infected in one day within the simulation was the dependent variable. The results suggest that within the given instance context, patient-oriented infection control policies (alternate treatment streams, masking symptomatic patients) tend to have a larger effect than policies that target healthcare workers. The agent-based modeling framework is a flexible tool that can be made to reflect any given environment; it is also a decision support tool for practitioners and policymakers to assess the relative impact of infection control strategies. The framework illuminates scenarios worthy of further investigation, as well as counterintuitive findings.

A consensus-based framework for design, validation, and implementation of simulation-based training curricula in surgery.

PubMed

Zevin, Boris; Levy, Jeffrey S; Satava, Richard M; Grantcharov, Teodor P

2012-10-01

Simulation-based training can improve technical and nontechnical skills in surgery. To date, there is no consensus on the principles for design, validation, and implementation of a simulation-based surgical training curriculum. The aim of this study was to define such principles and formulate them into an interoperable framework using international expert consensus based on the Delphi method. Literature was reviewed, 4 international experts were queried, and consensus conference of national and international members of surgical societies was held to identify the items for the Delphi survey. Forty-five international experts in surgical education were invited to complete the online survey by ranking each item on a Likert scale from 1 to 5. Consensus was predefined as Cronbach's α ≥0.80. Items that 80% of experts ranked as ≥4 were included in the final framework. Twenty-four international experts with training in general surgery (n = 11), orthopaedic surgery (n = 2), obstetrics and gynecology (n = 3), urology (n = 1), plastic surgery (n = 1), pediatric surgery (n = 1), otolaryngology (n = 1), vascular surgery (n = 1), military (n = 1), and doctorate-level educators (n = 2) completed the iterative online Delphi survey. Consensus among participants was achieved after one round of the survey (Cronbach's α = 0.91). The final framework included predevelopment analysis; cognitive, psychomotor, and team-based training; curriculum validation evaluation and improvement; and maintenance of training. The Delphi methodology allowed for determination of international expert consensus on the principles for design, validation, and implementation of a simulation-based surgical training curriculum. These principles were formulated into a framework that can be used internationally across surgical specialties as a step-by-step guide for the development and validation of future simulation-based training curricula. Copyright © 2012 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Developing interprofessional health competencies in a virtual world

PubMed Central

King, Sharla; Chodos, David; Stroulia, Eleni; Carbonaro, Mike; MacKenzie, Mark; Reid, Andrew; Torres, Lisa; Greidanus, Elaine

2012-01-01

Background Virtual worlds provide a promising means of delivering simulations for developing interprofessional health skills. However, developing and implementing a virtual world simulation is a challenging process, in part because of the novelty of virtual worlds as a simulation platform and also because of the degree of collaboration required among technical and subject experts. Thus, it can be difficult to ensure that the simulation is both technically satisfactory and educationally appropriate. Methods To address this challenge, we propose the use of de Freitas and Oliver's four-dimensional framework as a means of guiding the development process. We give an overview of the framework and describe how its principles can be applied to the development of virtual world simulations. Results We present two virtual world simulation pilot projects that adopted this approach, and describe our development experience in these projects. We directly connect this experience to the four-dimensional framework, thus validating the framework's applicability to the projects and to the context of virtual world simulations in general. Conclusions We present a series of recommendations for developing virtual world simulations for interprofessional health education. These recommendations are based on the four-dimensional framework and are also informed by our experience with the pilot projects. PMID:23195649

Generic framework for mining cellular automata models on protein-folding simulations.

PubMed

Diaz, N; Tischer, I

2016-05-13

Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.

Imposing a Lagrangian Particle Framework on an Eulerian Hydrodynamics Infrastructure in Flash

NASA Technical Reports Server (NTRS)

Dubey, A.; Daley, C.; ZuHone, J.; Ricker, P. M.; Weide, K.; Graziani, C.

2012-01-01

In many astrophysical simulations, both Eulerian and Lagrangian quantities are of interest. For example, in a galaxy cluster merger simulation, the intracluster gas can have Eulerian discretization, while dark matter can be modeled using particles. FLASH, a component-based scientific simulation code, superimposes a Lagrangian framework atop an adaptive mesh refinement Eulerian framework to enable such simulations. The discretization of the field variables is Eulerian, while the Lagrangian entities occur in many different forms including tracer particles, massive particles, charged particles in particle-in-cell mode, and Lagrangian markers to model fluid structure interactions. These widely varying roles for Lagrangian entities are possible because of the highly modular, flexible, and extensible architecture of the Lagrangian framework. In this paper, we describe the Lagrangian framework in FLASH in the context of two very different applications, Type Ia supernovae and galaxy cluster mergers, which use the Lagrangian entities in fundamentally different ways.

Imposing a Lagrangian Particle Framework on an Eulerian Hydrodynamics Infrastructure in FLASH

NASA Astrophysics Data System (ADS)

Dubey, A.; Daley, C.; ZuHone, J.; Ricker, P. M.; Weide, K.; Graziani, C.

2012-08-01

In many astrophysical simulations, both Eulerian and Lagrangian quantities are of interest. For example, in a galaxy cluster merger simulation, the intracluster gas can have Eulerian discretization, while dark matter can be modeled using particles. FLASH, a component-based scientific simulation code, superimposes a Lagrangian framework atop an adaptive mesh refinement Eulerian framework to enable such simulations. The discretization of the field variables is Eulerian, while the Lagrangian entities occur in many different forms including tracer particles, massive particles, charged particles in particle-in-cell mode, and Lagrangian markers to model fluid-structure interactions. These widely varying roles for Lagrangian entities are possible because of the highly modular, flexible, and extensible architecture of the Lagrangian framework. In this paper, we describe the Lagrangian framework in FLASH in the context of two very different applications, Type Ia supernovae and galaxy cluster mergers, which use the Lagrangian entities in fundamentally different ways.

Numerical simulation of the casting process of titanium removable partial denture frameworks.

PubMed

Wu, Menghuai; Wagner, Ingo; Sahm, Peter R; Augthun, Michael

2002-03-01

The objective of this work was to study the filling incompleteness and porosity defects in titanium removal partial denture frameworks by means of numerical simulation. Two frameworks, one for lower jaw and one for upper jaw, were chosen according to dentists' recommendation to be simulated. Geometry of the frameworks were laser-digitized and converted into a simulation software (MAGMASOFT). Both mold filling and solidification of the castings with different sprue designs (e.g. tree, ball, and runner-bar) were numerically calculated. The shrinkage porosity was quantitatively predicted by a feeding criterion, the potential filling defect and gas pore sensitivity were estimated based on the filling and solidification results. A satisfactory sprue design with process parameters was finally recommended for real casting trials (four replica for each frameworks). All the frameworks were successfully cast. Through X-ray radiographic inspections it was found that all the castings were acceptably sound except for only one case in which gas bubbles were detected in the grasp region of the frame. It is concluded that numerical simulation aids to achieve understanding of the casting process and defect formation in titanium frameworks, hence to minimize the risk of producing defect casting by improving the sprue design and process parameters.

Conceptual Modeling Framework for E-Area PA HELP Infiltration Model Simulations

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

Dyer, J. A.

A conceptual modeling framework based on the proposed E-Area Low-Level Waste Facility (LLWF) closure cap design is presented for conducting Hydrologic Evaluation of Landfill Performance (HELP) model simulations of intact and subsided cap infiltration scenarios for the next E-Area Performance Assessment (PA).

Framework for Architecture Trade Study Using MBSE and Performance Simulation

NASA Technical Reports Server (NTRS)

Ryan, Jessica; Sarkani, Shahram; Mazzuchim, Thomas

2012-01-01

Increasing complexity in modern systems as well as cost and schedule constraints require a new paradigm of system engineering to fulfill stakeholder needs. Challenges facing efficient trade studies include poor tool interoperability, lack of simulation coordination (design parameters) and requirements flowdown. A recent trend toward Model Based System Engineering (MBSE) includes flexible architecture definition, program documentation, requirements traceability and system engineering reuse. As a new domain MBSE still lacks governing standards and commonly accepted frameworks. This paper proposes a framework for efficient architecture definition using MBSE in conjunction with Domain Specific simulation to evaluate trade studies. A general framework is provided followed with a specific example including a method for designing a trade study, defining candidate architectures, planning simulations to fulfill requirements and finally a weighted decision analysis to optimize system objectives.

A framework for service enterprise workflow simulation with multi-agents cooperation

NASA Astrophysics Data System (ADS)

Tan, Wenan; Xu, Wei; Yang, Fujun; Xu, Lida; Jiang, Chuanqun

2013-11-01

Process dynamic modelling for service business is the key technique for Service-Oriented information systems and service business management, and the workflow model of business processes is the core part of service systems. Service business workflow simulation is the prevalent approach to be used for analysis of service business process dynamically. Generic method for service business workflow simulation is based on the discrete event queuing theory, which is lack of flexibility and scalability. In this paper, we propose a service workflow-oriented framework for the process simulation of service businesses using multi-agent cooperation to address the above issues. Social rationality of agent is introduced into the proposed framework. Adopting rationality as one social factor for decision-making strategies, a flexible scheduling for activity instances has been implemented. A system prototype has been developed to validate the proposed simulation framework through a business case study.

A comparison between rate-and-state friction and microphysical models, based on numerical simulations of fault slip

NASA Astrophysics Data System (ADS)

van den Ende, M. P. A.; Chen, J.; Ampuero, J.-P.; Niemeijer, A. R.

2018-05-01

Rate-and-state friction (RSF) is commonly used for the characterisation of laboratory friction experiments, such as velocity-step tests. However, the RSF framework provides little physical basis for the extrapolation of these results to the scales and conditions of natural fault systems, and so open questions remain regarding the applicability of the experimentally obtained RSF parameters for predicting seismic cycle transients. As an alternative to classical RSF, microphysics-based models offer means for interpreting laboratory and field observations, but are generally over-simplified with respect to heterogeneous natural systems. In order to bridge the temporal and spatial gap between the laboratory and nature, we have implemented existing microphysical model formulations into an earthquake cycle simulator. Through this numerical framework, we make a direct comparison between simulations exhibiting RSF-controlled fault rheology, and simulations in which the fault rheology is dictated by the microphysical model. Even though the input parameters for the RSF simulation are directly derived from the microphysical model, the microphysics-based simulations produce significantly smaller seismic event sizes than the RSF-based simulation, and suggest a more stable fault slip behaviour. Our results reveal fundamental limitations in using classical rate-and-state friction for the extrapolation of laboratory results. The microphysics-based approach offers a more complete framework in this respect, and may be used for a more detailed study of the seismic cycle in relation to material properties and fault zone pressure-temperature conditions.

Onyx-Advanced Aeropropulsion Simulation Framework Created

NASA Technical Reports Server (NTRS)

Reed, John A.

2001-01-01

The Numerical Propulsion System Simulation (NPSS) project at the NASA Glenn Research Center is developing a new software environment for analyzing and designing aircraft engines and, eventually, space transportation systems. Its purpose is to dramatically reduce the time, effort, and expense necessary to design and test jet engines by creating sophisticated computer simulations of an aerospace object or system (refs. 1 and 2). Through a university grant as part of that effort, researchers at the University of Toledo have developed Onyx, an extensible Java-based (Sun Micro-systems, Inc.), objectoriented simulation framework, to investigate how advanced software design techniques can be successfully applied to aeropropulsion system simulation (refs. 3 and 4). The design of Onyx's architecture enables users to customize and extend the framework to add new functionality or adapt simulation behavior as required. It exploits object-oriented technologies, such as design patterns, domain frameworks, and software components, to develop a modular system in which users can dynamically replace components with others having different functionality.

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

Using subject-specific three-dimensional (3D) anthropometry data in digital human modelling: case study in hand motion simulation.

PubMed

Tsao, Liuxing; Ma, Liang

2016-11-01

Digital human modelling enables ergonomists and designers to consider ergonomic concerns and design alternatives in a timely and cost-efficient manner in the early stages of design. However, the reliability of the simulation could be limited due to the percentile-based approach used in constructing the digital human model. To enhance the accuracy of the size and shape of the models, we proposed a framework to generate digital human models using three-dimensional (3D) anthropometric data. The 3D scan data from specific subjects' hands were segmented based on the estimated centres of rotation. The segments were then driven in forward kinematics to perform several functional postures. The constructed hand models were then verified, thereby validating the feasibility of the framework. The proposed framework helps generate accurate subject-specific digital human models, which can be utilised to guide product design and workspace arrangement. Practitioner Summary: Subject-specific digital human models can be constructed under the proposed framework based on three-dimensional (3D) anthropometry. This approach enables more reliable digital human simulation to guide product design and workspace arrangement.

Simulation training: a systematic review of simulation in arthroscopy and proposal of a new competency-based training framework.

PubMed

Tay, Charison; Khajuria, Ankur; Gupte, Chinmay

2014-01-01

Traditional orthopaedic training has followed an apprenticeship model whereby trainees enhance their skills by operating under guidance. However the introduction of limitations on training hours and shorter training programmes mean that alternative training strategies are required. To perform a literature review on simulation training in arthroscopy and devise a framework that structures different simulation techniques that could be used in arthroscopic training. A systematic search of Medline, Embase, Google Scholar and the Cochrane Databases were performed. Search terms included "virtual reality OR simulator OR simulation" and "arthroscopy OR arthroscopic". 14 studies evaluating simulators in knee, shoulder and hip arthroplasty were included. The majority of the studies demonstrated construct and transference validity but only one showed concurrent validity. More studies are required to assess its potential as a training and assessment tool, skills transference between simulators and to determine the extent of skills decay from prolonged delays in training. We also devised a "ladder of arthroscopic simulation" that provides a competency-based framework to implement different simulation strategies. The incorporation of simulation into an orthopaedic curriculum will depend on a coordinated approach between many bodies. But the successful integration of simulators in other areas of surgery supports a possible role for simulation in advancing orthopaedic education. Copyright © 2014 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

A configurable distributed high-performance computing framework for satellite's TDI-CCD imaging simulation

NASA Astrophysics Data System (ADS)

Xue, Bo; Mao, Bingjing; Chen, Xiaomei; Ni, Guoqiang

2010-11-01

This paper renders a configurable distributed high performance computing(HPC) framework for TDI-CCD imaging simulation. It uses strategy pattern to adapt multi-algorithms. Thus, this framework help to decrease the simulation time with low expense. Imaging simulation for TDI-CCD mounted on satellite contains four processes: 1) atmosphere leads degradation, 2) optical system leads degradation, 3) electronic system of TDI-CCD leads degradation and re-sampling process, 4) data integration. Process 1) to 3) utilize diversity data-intensity algorithms such as FFT, convolution and LaGrange Interpol etc., which requires powerful CPU. Even uses Intel Xeon X5550 processor, regular series process method takes more than 30 hours for a simulation whose result image size is 1500 * 1462. With literature study, there isn't any mature distributing HPC framework in this field. Here we developed a distribute computing framework for TDI-CCD imaging simulation, which is based on WCF[1], uses Client/Server (C/S) layer and invokes the free CPU resources in LAN. The server pushes the process 1) to 3) tasks to those free computing capacity. Ultimately we rendered the HPC in low cost. In the computing experiment with 4 symmetric nodes and 1 server , this framework reduced about 74% simulation time. Adding more asymmetric nodes to the computing network, the time decreased namely. In conclusion, this framework could provide unlimited computation capacity in condition that the network and task management server are affordable. And this is the brand new HPC solution for TDI-CCD imaging simulation and similar applications.

A Systems Approach to Designing Effective Clinical Trials Using Simulations

PubMed Central

Fusaro, Vincent A.; Patil, Prasad; Chi, Chih-Lin; Contant, Charles F.; Tonellato, Peter J.

2013-01-01

Background Pharmacogenetics in warfarin clinical trials have failed to show a significant benefit compared to standard clinical therapy. This study demonstrates a computational framework to systematically evaluate pre-clinical trial design of target population, pharmacogenetic algorithms, and dosing protocols to optimize primary outcomes. Methods and Results We programmatically created an end-to-end framework that systematically evaluates warfarin clinical trial designs. The framework includes options to create a patient population, multiple dosing strategies including genetic-based and non-genetic clinical-based, multiple dose adjustment protocols, pharmacokinetic/pharmacodynamics (PK/PD) modeling and international normalization ratio (INR) prediction, as well as various types of outcome measures. We validated the framework by conducting 1,000 simulations of the CoumaGen clinical trial primary endpoints. The simulation predicted a mean time in therapeutic range (TTR) of 70.6% and 72.2% (P = 0.47) in the standard and pharmacogenetic arms, respectively. Then, we evaluated another dosing protocol under the same original conditions and found a significant difference in TTR between the pharmacogenetic and standard arm (78.8% vs. 73.8%; P = 0.0065), respectively. Conclusions We demonstrate that this simulation framework is useful in the pre-clinical assessment phase to study and evaluate design options and provide evidence to optimize the clinical trial for patient efficacy and reduced risk. PMID:23261867

Using computer simulations to facilitate conceptual understanding of electromagnetic induction

NASA Astrophysics Data System (ADS)

Lee, Yu-Fen

This study investigated the use of computer simulations to facilitate conceptual understanding in physics. The use of computer simulations in the present study was grounded in a conceptual framework drawn from findings related to the use of computer simulations in physics education. To achieve the goal of effective utilization of computers for physics education, I first reviewed studies pertaining to computer simulations in physics education categorized by three different learning frameworks and studies comparing the effects of different simulation environments. My intent was to identify the learning context and factors for successful use of computer simulations in past studies and to learn from the studies which did not obtain a significant result. Based on the analysis of reviewed literature, I proposed effective approaches to integrate computer simulations in physics education. These approaches are consistent with well established education principles such as those suggested by How People Learn (Bransford, Brown, Cocking, Donovan, & Pellegrino, 2000). The research based approaches to integrated computer simulations in physics education form a learning framework called Concept Learning with Computer Simulations (CLCS) in the current study. The second component of this study was to examine the CLCS learning framework empirically. The participants were recruited from a public high school in Beijing, China. All participating students were randomly assigned to two groups, the experimental (CLCS) group and the control (TRAD) group. Research based computer simulations developed by the physics education research group at University of Colorado at Boulder were used to tackle common conceptual difficulties in learning electromagnetic induction. While interacting with computer simulations, CLCS students were asked to answer reflective questions designed to stimulate qualitative reasoning and explanation. After receiving model reasoning online, students were asked to submit their revised answers electronically. Students in the TRAD group were not granted access to the CLCS material and followed their normal classroom routine. At the end of the study, both the CLCS and TRAD students took a post-test. Questions on the post-test were divided into "what" questions, "how" questions, and an open response question. Analysis of students' post-test performance showed mixed results. While the TRAD students scored higher on the "what" questions, the CLCS students scored higher on the "how" questions and the one open response questions. This result suggested that more TRAD students knew what kinds of conditions may or may not cause electromagnetic induction without understanding how electromagnetic induction works. Analysis of the CLCS students' learning also suggested that frequent disruption and technical trouble might pose threats to the effectiveness of the CLCS learning framework. Despite the mixed results of students' post-test performance, the CLCS learning framework revealed some limitations to promote conceptual understanding in physics. Improvement can be made by providing students with background knowledge necessary to understand model reasoning and incorporating the CLCS learning framework with other learning frameworks to promote integration of various physics concepts. In addition, the reflective questions in the CLCS learning framework may be refined to better address students' difficulties. Limitations of the study, as well as suggestions for future research, are also presented in this study.

Unified Simulation and Analysis Framework for Deep Space Navigation Design

NASA Technical Reports Server (NTRS)

Anzalone, Evan; Chuang, Jason; Olsen, Carrie

2013-01-01

As the technology that enables advanced deep space autonomous navigation continues to develop and the requirements for such capability continues to grow, there is a clear need for a modular expandable simulation framework. This tool's purpose is to address multiple measurement and information sources in order to capture system capability. This is needed to analyze the capability of competing navigation systems as well as to develop system requirements, in order to determine its effect on the sizing of the integrated vehicle. The development for such a framework is built upon Model-Based Systems Engineering techniques to capture the architecture of the navigation system and possible state measurements and observations to feed into the simulation implementation structure. These models also allow a common environment for the capture of an increasingly complex operational architecture, involving multiple spacecraft, ground stations, and communication networks. In order to address these architectural developments, a framework of agent-based modules is implemented to capture the independent operations of individual spacecraft as well as the network interactions amongst spacecraft. This paper describes the development of this framework, and the modeling processes used to capture a deep space navigation system. Additionally, a sample implementation describing a concept of network-based navigation utilizing digitally transmitted data packets is described in detail. This developed package shows the capability of the modeling framework, including its modularity, analysis capabilities, and its unification back to the overall system requirements and definition.

A Component-Based FPGA Design Framework for Neuronal Ion Channel Dynamics Simulations

PubMed Central

Mak, Terrence S. T.; Rachmuth, Guy; Lam, Kai-Pui; Poon, Chi-Sang

2008-01-01

Neuron-machine interfaces such as dynamic clamp and brain-implantable neuroprosthetic devices require real-time simulations of neuronal ion channel dynamics. Field Programmable Gate Array (FPGA) has emerged as a high-speed digital platform ideal for such application-specific computations. We propose an efficient and flexible component-based FPGA design framework for neuronal ion channel dynamics simulations, which overcomes certain limitations of the recently proposed memory-based approach. A parallel processing strategy is used to minimize computational delay, and a hardware-efficient factoring approach for calculating exponential and division functions in neuronal ion channel models is used to conserve resource consumption. Performances of the various FPGA design approaches are compared theoretically and experimentally in corresponding implementations of the AMPA and NMDA synaptic ion channel models. Our results suggest that the component-based design framework provides a more memory economic solution as well as more efficient logic utilization for large word lengths, whereas the memory-based approach may be suitable for time-critical applications where a higher throughput rate is desired. PMID:17190033

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

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

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

DOE PAGES

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek; ...

2017-04-24

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

Psycho-Motor and Error Enabled Simulations: Modeling Vulnerable Skills in the Pre-Mastery Phase Medical Practice Initiative Procedural Skill Decay and Maintenance (MPI-PSD)

DTIC Science & Technology

2014-04-01

laparoscopic ventral hernia repair. Additional simulation stations were added to the standards and purchases (including a motion tracking system) were...framework for laparoscopic ventral hernia; Incorporation of error-based simulators into an exit assessment of chief surgical residents; Development of...simulating a laparoscopic ventral hernia (LVH) repair. Based on collected data, the lab worked to finalize the incorporation of error-based simulators

From MetroII to Metronomy, Designing Contract-based Function-Architecture Co-simulation Framework for Timing Verification of Cyber-Physical Systems

DTIC Science & Technology

2015-03-13

A. Lee. “A Programming Model for Time - Synchronized Distributed Real- Time Systems”. In: Proceedings of Real Time and Em- bedded Technology and Applications Symposium. 2007, pp. 259–268. ...From MetroII to Metronomy, Designing Contract-based Function-Architecture Co-simulation Framework for Timing Verification of Cyber-Physical Systems...the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data

Iterative repair for scheduling and rescheduling

NASA Technical Reports Server (NTRS)

Zweben, Monte; Davis, Eugene; Deale, Michael

1991-01-01

An iterative repair search method is described called constraint based simulated annealing. Simulated annealing is a hill climbing search technique capable of escaping local minima. The utility of the constraint based framework is shown by comparing search performance with and without the constraint framework on a suite of randomly generated problems. Results are also shown of applying the technique to the NASA Space Shuttle ground processing problem. These experiments show that the search methods scales to complex, real world problems and reflects interesting anytime behavior.

A Simulation Environment for Benchmarking Sensor Fusion-Based Pose Estimators.

PubMed

Ligorio, Gabriele; Sabatini, Angelo Maria

2015-12-19

In-depth analysis and performance evaluation of sensor fusion-based estimators may be critical when performed using real-world sensor data. For this reason, simulation is widely recognized as one of the most powerful tools for algorithm benchmarking. In this paper, we present a simulation framework suitable for assessing the performance of sensor fusion-based pose estimators. The systems used for implementing the framework were magnetic/inertial measurement units (MIMUs) and a camera, although the addition of further sensing modalities is straightforward. Typical nuisance factors were also included for each sensor. The proposed simulation environment was validated using real-life sensor data employed for motion tracking. The higher mismatch between real and simulated sensors was about 5% of the measured quantity (for the camera simulation), whereas a lower correlation was found for an axis of the gyroscope (0.90). In addition, a real benchmarking example of an extended Kalman filter for pose estimation from MIMU and camera data is presented.

Quantifying uncertainty and computational complexity for pore-scale simulations

NASA Astrophysics Data System (ADS)

Chen, C.; Yuan, Z.; Wang, P.; Yang, X.; Zhenyan, L.

2016-12-01

Pore-scale simulation is an essential tool to understand the complex physical process in many environmental problems, from multi-phase flow in the subsurface to fuel cells. However, in practice, factors such as sample heterogeneity, data sparsity and in general, our insufficient knowledge of the underlying process, render many simulation parameters and hence the prediction results uncertain. Meanwhile, most pore-scale simulations (in particular, direct numerical simulation) incur high computational cost due to finely-resolved spatio-temporal scales, which further limits our data/samples collection. To address those challenges, we propose a novel framework based on the general polynomial chaos (gPC) and build a surrogate model representing the essential features of the underlying system. To be specific, we apply the novel framework to analyze the uncertainties of the system behavior based on a series of pore-scale numerical experiments, such as flow and reactive transport in 2D heterogeneous porous media and 3D packed beds. Comparing with recent pore-scale uncertainty quantification studies using Monte Carlo techniques, our new framework requires fewer number of realizations and hence considerably reduce the overall computational cost, while maintaining the desired accuracy.

Physics-based multiscale coupling for full core nuclear reactor simulation

DOE PAGES

Gaston, Derek R.; Permann, Cody J.; Peterson, John W.; ...

2015-10-01

Numerical simulation of nuclear reactors is a key technology in the quest for improvements in efficiency, safety, and reliability of both existing and future reactor designs. Historically, simulation of an entire reactor was accomplished by linking together multiple existing codes that each simulated a subset of the relevant multiphysics phenomena. Recent advances in the MOOSE (Multiphysics Object Oriented Simulation Environment) framework have enabled a new approach: multiple domain-specific applications, all built on the same software framework, are efficiently linked to create a cohesive application. This is accomplished with a flexible coupling capability that allows for a variety of different datamore » exchanges to occur simultaneously on high performance parallel computational hardware. Examples based on the KAIST-3A benchmark core, as well as a simplified Westinghouse AP-1000 configuration, demonstrate the power of this new framework for tackling—in a coupled, multiscale manner—crucial reactor phenomena such as CRUD-induced power shift and fuel shuffle. 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-SA license« less

Volcano Modelling and Simulation gateway (VMSg): A new web-based framework for collaborative research in physical modelling and simulation of volcanic phenomena

NASA Astrophysics Data System (ADS)

Esposti Ongaro, T.; Barsotti, S.; de'Michieli Vitturi, M.; Favalli, M.; Longo, A.; Nannipieri, L.; Neri, A.; Papale, P.; Saccorotti, G.

2009-12-01

Physical and numerical modelling is becoming of increasing importance in volcanology and volcanic hazard assessment. However, new interdisciplinary problems arise when dealing with complex mathematical formulations, numerical algorithms and their implementations on modern computer architectures. Therefore new frameworks are needed for sharing knowledge, software codes, and datasets among scientists. Here we present the Volcano Modelling and Simulation gateway (VMSg, accessible at http://vmsg.pi.ingv.it), a new electronic infrastructure for promoting knowledge growth and transfer in the field of volcanological modelling and numerical simulation. The new web portal, developed in the framework of former and ongoing national and European projects, is based on a dynamic Content Manager System (CMS) and was developed to host and present numerical models of the main volcanic processes and relationships including magma properties, magma chamber dynamics, conduit flow, plume dynamics, pyroclastic flows, lava flows, etc. Model applications, numerical code documentation, simulation datasets as well as model validation and calibration test-cases are also part of the gateway material.

gadfly: A pandas-based Framework for Analyzing GADGET Simulation Data

NASA Astrophysics Data System (ADS)

Hummel, Jacob A.

2016-11-01

We present the first public release (v0.1) of the open-source gadget Dataframe Library: gadfly. The aim of this package is to leverage the capabilities of the broader python scientific computing ecosystem by providing tools for analyzing simulation data from the astrophysical simulation codes gadget and gizmo using pandas, a thoroughly documented, open-source library providing high-performance, easy-to-use data structures that is quickly becoming the standard for data analysis in python. Gadfly is a framework for analyzing particle-based simulation data stored in the HDF5 format using pandas DataFrames. The package enables efficient memory management, includes utilities for unit handling, coordinate transformations, and parallel batch processing, and provides highly optimized routines for visualizing smoothed-particle hydrodynamics data sets.

Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast

PubMed Central

Pang, Wei; Coghill, George M.

2015-01-01

In this paper we demonstrate how Morven, a computational framework which can perform qualitative, semi-quantitative, and quantitative simulation of dynamical systems using the same model formalism, is applied to study the osmotic stress response pathway in yeast. First the Morven framework itself is briefly introduced in terms of the model formalism employed and output format. We then built a qualitative model for the biophysical process of the osmoregulation in yeast, and a global qualitative-level picture was obtained through qualitative simulation of this model. Furthermore, we constructed a Morven model based on existing quantitative model of the osmoregulation system. This model was then simulated qualitatively, semi-quantitatively, and quantitatively. The obtained simulation results are presented with an analysis. Finally the future development of the Morven framework for modelling the dynamic biological systems is discussed. PMID:25864377

Interventional radiology virtual simulator for liver biopsy.

PubMed

Villard, P F; Vidal, F P; ap Cenydd, L; Holbrey, R; Pisharody, S; Johnson, S; Bulpitt, A; John, N W; Bello, F; Gould, D

2014-03-01

Training in Interventional Radiology currently uses the apprenticeship model, where clinical and technical skills of invasive procedures are learnt during practice in patients. This apprenticeship training method is increasingly limited by regulatory restrictions on working hours, concerns over patient risk through trainees' inexperience and the variable exposure to case mix and emergencies during training. To address this, we have developed a computer-based simulation of visceral needle puncture procedures. A real-time framework has been built that includes: segmentation, physically based modelling, haptics rendering, pseudo-ultrasound generation and the concept of a physical mannequin. It is the result of a close collaboration between different universities, involving computer scientists, clinicians, clinical engineers and occupational psychologists. The technical implementation of the framework is a robust and real-time simulation environment combining a physical platform and an immersive computerized virtual environment. The face, content and construct validation have been previously assessed, showing the reliability and effectiveness of this framework, as well as its potential for teaching visceral needle puncture. A simulator for ultrasound-guided liver biopsy has been developed. It includes functionalities and metrics extracted from cognitive task analysis. This framework can be useful during training, particularly given the known difficulties in gaining significant practice of core skills in patients.

USING THE ECLPSS SOFTWARE ENVIRONMENT TO BUILD A SPATIALLY EXPLICIT COMPONENT-BASED MODEL OF OZONE EFFECTS ON FOREST ECOSYSTEMS. (R827958)

EPA Science Inventory

We have developed a modeling framework to support grid-based simulation of ecosystems at multiple spatial scales, the Ecological Component Library for Parallel Spatial Simulation (ECLPSS). ECLPSS helps ecologists to build robust spatially explicit simulations of ...

HexSim - A general purpose framework for spatially-explicit, individual-based modeling

EPA Science Inventory

HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications. This talk will focus on a subset of those ap...

Trace Replay and Network Simulation Tool

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

Acun, Bilge; Jain, Nikhil; Bhatele, Abhinav

2015-03-23

TraceR is a trace reply tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performances and understanding network behavior by simulating messaging in High Performance Computing applications on interconnection networks.

Trace Replay and Network Simulation Tool

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

Jain, Nikhil; Bhatele, Abhinav; Acun, Bilge

TraceR Is a trace replay tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performance and understanding network behavior by simulating messaging In High Performance Computing applications on interconnection networks.

Development of a software framework for data assimilation and its applications for streamflow forecasting in Japan

NASA Astrophysics Data System (ADS)

Noh, S. J.; Tachikawa, Y.; Shiiba, M.; Yorozu, K.; Kim, S.

2012-04-01

Data assimilation methods have received increased attention to accomplish uncertainty assessment and enhancement of forecasting capability in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modeling software are based on a deterministic approach. In this study, we developed a hydrological modeling framework for sequential data assimilation, so called MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modeling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. Sequential data assimilation based on the particle filters is available for any hydrologic models based on MPI-OHyMoS considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for short-term streamflow forecasting of several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and remotely-sensed rainfall data such as X-band or C-band radar is estimated and mitigated in the sequential data assimilation.

A framework for optimization and quantification of uncertainty and sensitivity for developing carbon capture systems

DOE PAGES

Eslick, John C.; Ng, Brenda; Gao, Qianwen; ...

2014-12-31

Under the auspices of the U.S. Department of Energy’s Carbon Capture Simulation Initiative (CCSI), a Framework for Optimization and Quantification of Uncertainty and Sensitivity (FOQUS) has been developed. This tool enables carbon capture systems to be rapidly synthesized and rigorously optimized, in an environment that accounts for and propagates uncertainties in parameters and models. FOQUS currently enables (1) the development of surrogate algebraic models utilizing the ALAMO algorithm, which can be used for superstructure optimization to identify optimal process configurations, (2) simulation-based optimization utilizing derivative free optimization (DFO) algorithms with detailed black-box process models, and (3) rigorous uncertainty quantification throughmore » PSUADE. FOQUS utilizes another CCSI technology, the Turbine Science Gateway, to manage the thousands of simulated runs necessary for optimization and UQ. Thus, this computational framework has been demonstrated for the design and analysis of a solid sorbent based carbon capture system.« less

Generalizing Gillespie’s Direct Method to Enable Network-Free Simulations

DOE PAGES

Suderman, Ryan T.; Mitra, Eshan David; Lin, Yen Ting; ...

2018-03-28

Gillespie’s direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie’s direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termedmore » network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie’s direct method for network-free simulation. Lastly, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.« less

Generalizing Gillespie’s Direct Method to Enable Network-Free Simulations

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

Suderman, Ryan T.; Mitra, Eshan David; Lin, Yen Ting

Gillespie’s direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie’s direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termedmore » network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie’s direct method for network-free simulation. Lastly, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.« less

MOOSE: A PARALLEL COMPUTATIONAL FRAMEWORK FOR COUPLED SYSTEMS OF NONLINEAR EQUATIONS.

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

G. Hansen; C. Newman; D. Gaston

Systems of coupled, nonlinear partial di?erential equations often arise in sim- ulation of nuclear processes. MOOSE: Multiphysics Ob ject Oriented Simulation Environment, a parallel computational framework targeted at solving these systems is presented. As opposed to traditional data / ?ow oriented com- putational frameworks, MOOSE is instead founded on mathematics based on Jacobian-free Newton Krylov (JFNK). Utilizing the mathematical structure present in JFNK, physics are modularized into “Kernels” allowing for rapid production of new simulation tools. In addition, systems are solved fully cou- pled and fully implicit employing physics based preconditioning allowing for a large amount of ?exibility even withmore » large variance in time scales. Background on the mathematics, an inspection of the structure of MOOSE and several rep- resentative solutions from applications built on the framework are presented.« less

Moose: An Open-Source Framework to Enable Rapid Development of Collaborative, Multi-Scale, Multi-Physics Simulation Tools

NASA Astrophysics Data System (ADS)

Slaughter, A. E.; Permann, C.; Peterson, J. W.; Gaston, D.; Andrs, D.; Miller, J.

2014-12-01

The Idaho National Laboratory (INL)-developed Multiphysics Object Oriented Simulation Environment (MOOSE; www.mooseframework.org), is an open-source, parallel computational framework for enabling the solution of complex, fully implicit multiphysics systems. MOOSE provides a set of computational tools that scientists and engineers can use to create sophisticated multiphysics simulations. Applications built using MOOSE have computed solutions for chemical reaction and transport equations, computational fluid dynamics, solid mechanics, heat conduction, mesoscale materials modeling, geomechanics, and others. To facilitate the coupling of diverse and highly-coupled physical systems, MOOSE employs the Jacobian-free Newton-Krylov (JFNK) method when solving the coupled nonlinear systems of equations arising in multiphysics applications. The MOOSE framework is written in C++, and leverages other high-quality, open-source scientific software packages such as LibMesh, Hypre, and PETSc. MOOSE uses a "hybrid parallel" model which combines both shared memory (thread-based) and distributed memory (MPI-based) parallelism to ensure efficient resource utilization on a wide range of computational hardware. MOOSE-based applications are inherently modular, which allows for simulation expansion (via coupling of additional physics modules) and the creation of multi-scale simulations. Any application developed with MOOSE supports running (in parallel) any other MOOSE-based application. Each application can be developed independently, yet easily communicate with other applications (e.g., conductivity in a slope-scale model could be a constant input, or a complete phase-field micro-structure simulation) without additional code being written. This method of development has proven effective at INL and expedites the development of sophisticated, sustainable, and collaborative simulation tools.

JAMS - a software platform for modular hydrological modelling

NASA Astrophysics Data System (ADS)

Kralisch, Sven; Fischer, Christian

2015-04-01

Current challenges of understanding and assessing the impacts of climate and land use changes on environmental systems demand for an ever-increasing integration of data and process knowledge in corresponding simulation models. Software frameworks that allow for a seamless creation of integrated models based on less complex components (domain models, process simulation routines) have therefore gained increasing attention during the last decade. JAMS is an Open-Source software framework that has been especially designed to cope with the challenges of eco-hydrological modelling. This is reflected by (i) its flexible approach for representing time and space, (ii) a strong separation of process simulation components from the declarative description of more complex models using domain specific XML, (iii) powerful analysis and visualization functions for spatial and temporal input and output data, and (iv) parameter optimization and uncertainty analysis functions commonly used in environmental modelling. Based on JAMS, different hydrological and nutrient-transport simulation models were implemented and successfully applied during the last years. We will present the JAMS core concepts and give an overview of models, simulation components and support tools available for that framework. Sample applications will be used to underline the advantages of component-based model designs and to show how JAMS can be used to address the challenges of integrated hydrological modelling.

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.

A collection of sprouting parameters for simulating regeneration establishment in the Missouri Ozarks

Treesearch

Lance A. Vickers; David R. Larsen; John M. Kabrick; Daniel C. Dey; Benjamin O. Knapp

2016-01-01

Predicting the effects of silvicultural choices on tree regeneration has traditionally been difficult with the tools currently available to foresters. In an effort to improve this, we have developed a simulation framework based on hypotheses of stand dynamics for several species found in the Missouri Ozarks. This framework includes separate modules for establishment,...

Going DEEP: guidelines for building simulation-based team assessments.

PubMed

Grand, James A; Pearce, Marina; Rench, Tara A; Chao, Georgia T; Fernandez, Rosemarie; Kozlowski, Steve W J

2013-05-01

Whether for team training, research or evaluation, making effective use of simulation-based technologies requires robust, reliable and accurate assessment tools. Extant literature on simulation-based assessment practices has primarily focused on scenario and instructional design; however, relatively little direct guidance has been provided regarding the challenging decisions and fundamental principles related to assessment development and implementation. The objective of this manuscript is to introduce a generalisable assessment framework supplemented by specific guidance on how to construct and ensure valid and reliable simulation-based team assessment tools. The recommendations reflect best practices in assessment and are designed to empower healthcare educators, professionals and researchers with the knowledge to design and employ valid and reliable simulation-based team assessments. Information and actionable recommendations associated with creating assessments of team processes (non-technical 'teamwork' activities) and performance (demonstration of technical proficiency) are presented which provide direct guidance on how to Distinguish the underlying competencies one aims to assess, Elaborate the measures used to capture team member behaviours during simulation activities, Establish the content validity of these measures and Proceduralise the measurement tools in a way that is systematically aligned with the goals of the simulation activity while maintaining methodological rigour (DEEP). The DEEP framework targets fundamental principles and critical activities that are important for effective assessment, and should benefit healthcare educators, professionals and researchers seeking to design or enhance any simulation-based assessment effort.

In Vivo Investigation of the Effectiveness of a Hyper-viscoelastic Model in Simulating Brain Retraction

NASA Astrophysics Data System (ADS)

Li, Ping; Wang, Weiwei; Zhang, Chenxi; An, Yong; Song, Zhijian

2016-07-01

Intraoperative brain retraction leads to a misalignment between the intraoperative positions of the brain structures and their previous positions, as determined from preoperative images. In vitro swine brain sample uniaxial tests showed that the mechanical response of brain tissue to compression and extension could be described by the hyper-viscoelasticity theory. The brain retraction caused by the mechanical process is a combination of brain tissue compression and extension. In this paper, we first constructed a hyper-viscoelastic framework based on the extended finite element method (XFEM) to simulate intraoperative brain retraction. To explore its effectiveness, we then applied this framework to an in vivo brain retraction simulation. The simulation strictly followed the clinical scenario, in which seven swine were subjected to brain retraction. Our experimental results showed that the hyper-viscoelastic XFEM framework is capable of simulating intraoperative brain retraction and improving the navigation accuracy of an image-guided neurosurgery system (IGNS).

Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast.

PubMed

Pang, Wei; Coghill, George M

2015-05-01

In this paper we demonstrate how Morven, a computational framework which can perform qualitative, semi-quantitative, and quantitative simulation of dynamical systems using the same model formalism, is applied to study the osmotic stress response pathway in yeast. First the Morven framework itself is briefly introduced in terms of the model formalism employed and output format. We then built a qualitative model for the biophysical process of the osmoregulation in yeast, and a global qualitative-level picture was obtained through qualitative simulation of this model. Furthermore, we constructed a Morven model based on existing quantitative model of the osmoregulation system. This model was then simulated qualitatively, semi-quantitatively, and quantitatively. The obtained simulation results are presented with an analysis. Finally the future development of the Morven framework for modelling the dynamic biological systems is discussed. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Role-playing simulation as an educational tool for health care personnel: developing an embedded assessment framework.

PubMed

Libin, Alexander; Lauderdale, Manon; Millo, Yuri; Shamloo, Christine; Spencer, Rachel; Green, Brad; Donnellan, Joyce; Wellesley, Christine; Groah, Suzanne

2010-04-01

Simulation- and video game-based role-playing techniques have been proven effective in changing behavior and enhancing positive decision making in a variety of professional settings, including education, the military, and health care. Although the need for developing assessment frameworks for learning outcomes has been clearly defined, there is a significant gap between the variety of existing multimedia-based instruction and technology-mediated learning systems and the number of reliable assessment algorithms. This study, based on a mixed methodology research design, aims to develop an embedded assessment algorithm, a Knowledge Assessment Module (NOTE), to capture both user interaction with the educational tool and knowledge gained from the training. The study is regarded as the first step in developing an assessment framework for a multimedia educational tool for health care professionals, Anatomy of Care (AOC), that utilizes Virtual Experience Immersive Learning Simulation (VEILS) technology. Ninety health care personnel of various backgrounds took part in online AOC training, choosing from five possible scenarios presenting difficult situations of everyday care. The results suggest that although the simulation-based training tool demonstrated partial effectiveness in improving learners' decision-making capacity, a differential learner-oriented approach might be more effective and capable of synchronizing educational efforts with identifiable relevant individual factors such as sociobehavioral profile and professional background.

MOOSE: A parallel computational framework for coupled systems of nonlinear equations.

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

Derek Gaston; Chris Newman; Glen Hansen

Systems of coupled, nonlinear partial differential equations (PDEs) often arise in simulation of nuclear processes. MOOSE: Multiphysics Object Oriented Simulation Environment, a parallel computational framework targeted at the solution of such systems, is presented. As opposed to traditional data-flow oriented computational frameworks, MOOSE is instead founded on the mathematical principle of Jacobian-free Newton-Krylov (JFNK) solution methods. Utilizing the mathematical structure present in JFNK, physics expressions are modularized into `Kernels,'' allowing for rapid production of new simulation tools. In addition, systems are solved implicitly and fully coupled, employing physics based preconditioning, which provides great flexibility even with large variance in timemore » scales. A summary of the mathematics, an overview of the structure of MOOSE, and several representative solutions from applications built on the framework are presented.« less

Next Generation Extended Lagrangian Quantum-based Molecular Dynamics

NASA Astrophysics Data System (ADS)

Negre, Christian

2017-06-01

A new framework for extended Lagrangian first-principles molecular dynamics simulations is presented, which overcomes shortcomings of regular, direct Born-Oppenheimer molecular dynamics, while maintaining important advantages of the unified extended Lagrangian formulation of density functional theory pioneered by Car and Parrinello three decades ago. The new framework allows, for the first time, energy conserving, linear-scaling Born-Oppenheimer molecular dynamics simulations, which is necessary to study larger and more realistic systems over longer simulation times than previously possible. Expensive, self-consinstent-field optimizations are avoided and normal integration time steps of regular, direct Born-Oppenheimer molecular dynamics can be used. Linear scaling electronic structure theory is presented using a graph-based approach that is ideal for parallel calculations on hybrid computer platforms. For the first time, quantum based Born-Oppenheimer molecular dynamics simulation is becoming a practically feasible approach in simulations of +100,000 atoms-representing a competitive alternative to classical polarizable force field methods. In collaboration with: Anders Niklasson, Los Alamos National Laboratory.

Using Computer Simulations for Promoting Model-based Reasoning. Epistemological and Educational Dimensions

NASA Astrophysics Data System (ADS)

Develaki, Maria

2017-11-01

Scientific reasoning is particularly pertinent to science education since it is closely related to the content and methodologies of science and contributes to scientific literacy. Much of the research in science education investigates the appropriate framework and teaching methods and tools needed to promote students' ability to reason and evaluate in a scientific way. This paper aims (a) to contribute to an extended understanding of the nature and pedagogical importance of model-based reasoning and (b) to exemplify how using computer simulations can support students' model-based reasoning. We provide first a background for both scientific reasoning and computer simulations, based on the relevant philosophical views and the related educational discussion. This background suggests that the model-based framework provides an epistemologically valid and pedagogically appropriate basis for teaching scientific reasoning and for helping students develop sounder reasoning and decision-taking abilities and explains how using computer simulations can foster these abilities. We then provide some examples illustrating the use of computer simulations to support model-based reasoning and evaluation activities in the classroom. The examples reflect the procedure and criteria for evaluating models in science and demonstrate the educational advantages of their application in classroom reasoning activities.

Simulation Framework to Estimate the Performance of CO2 and O2 Sensing from Space and Airborne Platforms for the ASCENDS Mission Requirements Analysis

NASA Technical Reports Server (NTRS)

Plitau, Denis; Prasad, Narasimha S.

2012-01-01

The Active Sensing of CO2 Emissions over Nights Days and Seasons (ASCENDS) mission recommended by the NRC Decadal Survey has a desired accuracy of 0.3% in carbon dioxide mixing ratio (XCO2) retrievals requiring careful selection and optimization of the instrument parameters. NASA Langley Research Center (LaRC) is investigating 1.57 micron carbon dioxide as well as the 1.26-1.27 micron oxygen bands for our proposed ASCENDS mission requirements investigation. Simulation studies are underway for these bands to select optimum instrument parameters. The simulations are based on a multi-wavelength lidar modeling framework being developed at NASA LaRC to predict the performance of CO2 and O2 sensing from space and airborne platforms. The modeling framework consists of a lidar simulation module and a line-by-line calculation component with interchangeable lineshape routines to test the performance of alternative lineshape models in the simulations. As an option the line-by-line radiative transfer model (LBLRTM) program may also be used for line-by-line calculations. The modeling framework is being used to perform error analysis, establish optimum measurement wavelengths as well as to identify the best lineshape models to be used in CO2 and O2 retrievals. Several additional programs for HITRAN database management and related simulations are planned to be included in the framework. The description of the modeling framework with selected results of the simulation studies for CO2 and O2 sensing is presented in this paper.

Applying Kane's Validity Framework to a Simulation Based Assessment of Clinical Competence

ERIC Educational Resources Information Center

Tavares, Walter; Brydges, Ryan; Myre, Paul; Prpic, Jason; Turner, Linda; Yelle, Richard; Huiskamp, Maud

2018-01-01

Assessment of clinical competence is complex and inference based. Trustworthy and defensible assessment processes must have favourable evidence of validity, particularly where decisions are considered high stakes. We aimed to organize, collect and interpret validity evidence for a high stakes simulation based assessment strategy for certifying…

BioASF: a framework for automatically generating executable pathway models specified in BioPAX.

PubMed

Haydarlou, Reza; Jacobsen, Annika; Bonzanni, Nicola; Feenstra, K Anton; Abeln, Sanne; Heringa, Jaap

2016-06-15

Biological pathways play a key role in most cellular functions. To better understand these functions, diverse computational and cell biology researchers use biological pathway data for various analysis and modeling purposes. For specifying these biological pathways, a community of researchers has defined BioPAX and provided various tools for creating, validating and visualizing BioPAX models. However, a generic software framework for simulating BioPAX models is missing. Here, we attempt to fill this gap by introducing a generic simulation framework for BioPAX. The framework explicitly separates the execution model from the model structure as provided by BioPAX, with the advantage that the modelling process becomes more reproducible and intrinsically more modular; this ensures natural biological constraints are satisfied upon execution. The framework is based on the principles of discrete event systems and multi-agent systems, and is capable of automatically generating a hierarchical multi-agent system for a given BioPAX model. To demonstrate the applicability of the framework, we simulated two types of biological network models: a gene regulatory network modeling the haematopoietic stem cell regulators and a signal transduction network modeling the Wnt/β-catenin signaling pathway. We observed that the results of the simulations performed using our framework were entirely consistent with the simulation results reported by the researchers who developed the original models in a proprietary language. The framework, implemented in Java, is open source and its source code, documentation and tutorial are available at http://www.ibi.vu.nl/programs/BioASF CONTACT: j.heringa@vu.nl. © The Author 2016. Published by Oxford University Press.

Modeling Real-Time Coordination of Distributed Expertise and Event Response in NASA Mission Control Center Operations

NASA Astrophysics Data System (ADS)

Onken, Jeffrey

This dissertation introduces a multidisciplinary framework for the enabling of future research and analysis of alternatives for control centers for real-time operations of safety-critical systems. The multidisciplinary framework integrates functional and computational models that describe the dynamics in fundamental concepts of previously disparate engineering and psychology research disciplines, such as group performance and processes, supervisory control, situation awareness, events and delays, and expertise. The application in this dissertation is the real-time operations within the NASA Mission Control Center in Houston, TX. This dissertation operationalizes the framework into a model and simulation, which simulates the functional and computational models in the framework according to user-configured scenarios for a NASA human-spaceflight mission. The model and simulation generates data according to the effectiveness of the mission-control team in supporting the completion of mission objectives and detecting, isolating, and recovering from anomalies. Accompanying the multidisciplinary framework is a proof of concept, which demonstrates the feasibility of such a framework. The proof of concept demonstrates that variability occurs where expected based on the models. The proof of concept also demonstrates that the data generated from the model and simulation is useful for analyzing and comparing MCC configuration alternatives because an investigator can give a diverse set of scenarios to the simulation and the output compared in detail to inform decisions about the effect of MCC configurations on mission operations performance.

A Risk-Based Framework for Assessing the Effectiveness of Stratospheric Aerosol Geoengineering

PubMed Central

Ferraro, Angus J.; Charlton-Perez, Andrew J.; Highwood, Eleanor J.

2014-01-01

Geoengineering by stratospheric aerosol injection has been proposed as a policy response to warming from human emissions of greenhouse gases, but it may produce unequal regional impacts. We present a simple, intuitive risk-based framework for classifying these impacts according to whether geoengineering increases or decreases the risk of substantial climate change, with further classification by the level of existing risk from climate change from increasing carbon dioxide concentrations. This framework is applied to two climate model simulations of geoengineering counterbalancing the surface warming produced by a quadrupling of carbon dioxide concentrations, with one using a layer of sulphate aerosol in the lower stratosphere, and the other a reduction in total solar irradiance. The solar dimming model simulation shows less regional inequality of impacts compared with the aerosol geoengineering simulation. In the solar dimming simulation, 10% of the Earth's surface area, containing 10% of its population and 11% of its gross domestic product, experiences greater risk of substantial precipitation changes under geoengineering than under enhanced carbon dioxide concentrations. In the aerosol geoengineering simulation the increased risk of substantial precipitation change is experienced by 42% of Earth's surface area, containing 36% of its population and 60% of its gross domestic product. PMID:24533155

Integrating the fundamentals of care framework in baccalaureate nursing education: An example from a nursing school in Denmark.

PubMed

Voldbjerg, Siri Lygum; Laugesen, Britt; Bahnsen, Iben Bøgh; Jørgensen, Lone; Sørensen, Ingrid Maria; Grønkjaer, Mette; Sørensen, Erik Elgaard

2018-06-01

To describe and discuss the process of integrating the Fundamentals of Care framework in a baccalaureate nursing education at a School of Nursing in Denmark. Nursing education plays an essential role in educating nurses to work within healthcare systems in which a demanding workload on nurses results in fundamental nursing care being left undone. Newly graduated nurses often lack knowledge and skills to meet the challenges of delivering fundamental care in clinical practice. To develop nursing students' understanding of fundamental nursing, the conceptual Fundamentals of Care framework has been integrated in nursing education at a School of Nursing in Denmark. Discursive paper using an adjusted descriptive case study design for describing and discussing the process of integrating the conceptual Fundamentals of Care Framework in nursing education. The process of integrating the Fundamentals of Care framework is illuminated through a description of the context, in which the process occurs including the faculty members, lectures, case-based work and simulation laboratory in nursing education. Based on this description, opportunities such as supporting a holistic approach to an evidence-based integrative patient care and challenges such as scepticism among the faculty are discussed. It is suggested how integration of Fundamentals of Care Framework in lectures, case-based work and simulation laboratory can make fundamental nursing care more explicit in nursing education, support critical thinking and underline the relevance of evidence-based practice. The process relies on a supportive context, a well-informed and engaged faculty, and continuous reflections on how the conceptual framework can be integrated. Integrating the Fundamentals of Care framework can support nursing students' critical thinking and reflection on what fundamental nursing care is and requires and eventually educate nurses in providing evidence-based fundamental nursing care. © 2018 John Wiley & Sons Ltd.

Comparative Evaluation of a Four-Implant-Supported Polyetherketoneketone Framework Prosthesis: A Three-Dimensional Finite Element Analysis Based on Cone Beam Computed Tomography and Computer-Aided Design.

PubMed

Lee, Ki-Sun; Shin, Sang-Wan; Lee, Sang-Pyo; Kim, Jong-Eun; Kim, Jee-Hwan; Lee, Jeong-Yol

The purpose of this pilot study was to evaluate and compare polyetherketoneketone (PEKK) with different framework materials for implant-supported prostheses by means of a three-dimensional finite element analysis (3D-FEA) based on cone beam computed tomography (CBCT) and computer-aided design (CAD) data. A geometric model that consisted of four maxillary implants supporting a prosthesis framework was constructed from CBCT and CAD data of a treated patient. Three different materials (zirconia, titanium, and PEKK) were selected, and their material properties were simulated using FEA software in the generated geometric model. In the PEKK framework (ie, low elastic modulus) group, the stress transferred to the implant and simulated adjacent tissue was reduced when compressive stress was dominant, but increased when tensile stress was dominant. This study suggests that the shock-absorbing effects of a resilient implant-supported framework are limited in some areas and that rigid framework material shows a favorable stress distribution and safety of overall components of the prosthesis.

Virtual machine-based simulation platform for mobile ad-hoc network-based cyber infrastructure

DOE PAGES

Yoginath, Srikanth B.; Perumalla, Kayla S.; Henz, Brian J.

2015-09-29

In modeling and simulating complex systems such as mobile ad-hoc networks (MANETs) in de-fense communications, it is a major challenge to reconcile multiple important considerations: the rapidity of unavoidable changes to the software (network layers and applications), the difficulty of modeling the critical, implementation-dependent behavioral effects, the need to sustain larger scale scenarios, and the desire for faster simulations. Here we present our approach in success-fully reconciling them using a virtual time-synchronized virtual machine(VM)-based parallel ex-ecution framework that accurately lifts both the devices as well as the network communications to a virtual time plane while retaining full fidelity. At themore » core of our framework is a scheduling engine that operates at the level of a hypervisor scheduler, offering a unique ability to execute multi-core guest nodes over multi-core host nodes in an accurate, virtual time-synchronized manner. In contrast to other related approaches that suffer from either speed or accuracy issues, our framework provides MANET node-wise scalability, high fidelity of software behaviors, and time-ordering accuracy. The design and development of this framework is presented, and an ac-tual implementation based on the widely used Xen hypervisor system is described. Benchmarks with synthetic and actual applications are used to identify the benefits of our approach. The time inaccuracy of traditional emulation methods is demonstrated, in comparison with the accurate execution of our framework verified by theoretically correct results expected from analytical models of the same scenarios. In the largest high fidelity tests, we are able to perform virtual time-synchronized simulation of 64-node VM-based full-stack, actual software behaviors of MANETs containing a mix of static and mobile (unmanned airborne vehicle) nodes, hosted on a 32-core host, with full fidelity of unmodified ad-hoc routing protocols, unmodified application executables, and user-controllable physical layer effects including inter-device wireless signal strength, reachability, and connectivity.« less

Virtual machine-based simulation platform for mobile ad-hoc network-based cyber infrastructure

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

Yoginath, Srikanth B.; Perumalla, Kayla S.; Henz, Brian J.

In modeling and simulating complex systems such as mobile ad-hoc networks (MANETs) in de-fense communications, it is a major challenge to reconcile multiple important considerations: the rapidity of unavoidable changes to the software (network layers and applications), the difficulty of modeling the critical, implementation-dependent behavioral effects, the need to sustain larger scale scenarios, and the desire for faster simulations. Here we present our approach in success-fully reconciling them using a virtual time-synchronized virtual machine(VM)-based parallel ex-ecution framework that accurately lifts both the devices as well as the network communications to a virtual time plane while retaining full fidelity. At themore » core of our framework is a scheduling engine that operates at the level of a hypervisor scheduler, offering a unique ability to execute multi-core guest nodes over multi-core host nodes in an accurate, virtual time-synchronized manner. In contrast to other related approaches that suffer from either speed or accuracy issues, our framework provides MANET node-wise scalability, high fidelity of software behaviors, and time-ordering accuracy. The design and development of this framework is presented, and an ac-tual implementation based on the widely used Xen hypervisor system is described. Benchmarks with synthetic and actual applications are used to identify the benefits of our approach. The time inaccuracy of traditional emulation methods is demonstrated, in comparison with the accurate execution of our framework verified by theoretically correct results expected from analytical models of the same scenarios. In the largest high fidelity tests, we are able to perform virtual time-synchronized simulation of 64-node VM-based full-stack, actual software behaviors of MANETs containing a mix of static and mobile (unmanned airborne vehicle) nodes, hosted on a 32-core host, with full fidelity of unmodified ad-hoc routing protocols, unmodified application executables, and user-controllable physical layer effects including inter-device wireless signal strength, reachability, and connectivity.« less

A general CFD framework for fault-resilient simulations based on multi-resolution information fusion

NASA Astrophysics Data System (ADS)

Lee, Seungjoon; Kevrekidis, Ioannis G.; Karniadakis, George Em

2017-10-01

We develop a general CFD framework for multi-resolution simulations to target multiscale problems but also resilience in exascale simulations, where faulty processors may lead to gappy, in space-time, simulated fields. We combine approximation theory and domain decomposition together with statistical learning techniques, e.g. coKriging, to estimate boundary conditions and minimize communications by performing independent parallel runs. To demonstrate this new simulation approach, we consider two benchmark problems. First, we solve the heat equation (a) on a small number of spatial "patches" distributed across the domain, simulated by finite differences at fine resolution and (b) on the entire domain simulated at very low resolution, thus fusing multi-resolution models to obtain the final answer. Second, we simulate the flow in a lid-driven cavity in an analogous fashion, by fusing finite difference solutions obtained with fine and low resolution assuming gappy data sets. We investigate the influence of various parameters for this framework, including the correlation kernel, the size of a buffer employed in estimating boundary conditions, the coarseness of the resolution of auxiliary data, and the communication frequency across different patches in fusing the information at different resolution levels. In addition to its robustness and resilience, the new framework can be employed to generalize previous multiscale approaches involving heterogeneous discretizations or even fundamentally different flow descriptions, e.g. in continuum-atomistic simulations.

Towards a conceptual multi-agent-based framework to simulate the spatial group decision-making process

NASA Astrophysics Data System (ADS)

Ghavami, Seyed Morsal; Taleai, Mohammad

2017-04-01

Most spatial problems are multi-actor, multi-issue and multi-phase in nature. In addition to their intrinsic complexity, spatial problems usually involve groups of actors from different organizational and cognitive backgrounds, all of whom participate in a social structure to resolve or reduce the complexity of a given problem. Hence, it is important to study and evaluate what different aspects influence the spatial problem resolution process. Recently, multi-agent systems consisting of groups of separate agent entities all interacting with each other have been put forward as appropriate tools to use to study and resolve such problems. In this study, then in order to generate a better level of understanding regarding the spatial problem group decision-making process, a conceptual multi-agent-based framework is used that represents and specifies all the necessary concepts and entities needed to aid group decision making, based on a simulation of the group decision-making process as well as the relationships that exist among the different concepts involved. The study uses five main influencing entities as concepts in the simulation process: spatial influence, individual-level influence, group-level influence, negotiation influence and group performance measures. Further, it explains the relationship among different concepts in a descriptive rather than explanatory manner. To illustrate the proposed framework, the approval process for an urban land use master plan in Zanjan—a provincial capital in Iran—is simulated using MAS, the results highlighting the effectiveness of applying an MAS-based framework when wishing to study the group decision-making process used to resolve spatial problems.

Agent Based Modeling of Air Carrier Behavior for Evaluation of Technology Equipage and Adoption

NASA Technical Reports Server (NTRS)

Horio, Brant M.; DeCicco, Anthony H.; Stouffer, Virginia L.; Hasan, Shahab; Rosenbaum, Rebecca L.; Smith, Jeremy C.

2014-01-01

As part of ongoing research, the National Aeronautics and Space Administration (NASA) and LMI developed a research framework to assist policymakers in identifying impacts on the U.S. air transportation system (ATS) of potential policies and technology related to the implementation of the Next Generation Air Transportation System (NextGen). This framework, called the Air Transportation System Evolutionary Simulation (ATS-EVOS), integrates multiple models into a single process flow to best simulate responses by U.S. commercial airlines and other ATS stakeholders to NextGen-related policies, and in turn, how those responses impact the ATS. Development of this framework required NASA and LMI to create an agent-based model of airline and passenger behavior. This Airline Evolutionary Simulation (AIRLINE-EVOS) models airline decisions about tactical airfare and schedule adjustments, and strategic decisions related to fleet assignments, market prices, and equipage. AIRLINE-EVOS models its own heterogeneous population of passenger agents that interact with airlines; this interaction allows the model to simulate the cycle of action-reaction as airlines compete with each other and engage passengers. We validated a baseline configuration of AIRLINE-EVOS against Airline Origin and Destination Survey (DB1B) data and subject matter expert opinion, and we verified the ATS-EVOS framework and agent behavior logic through scenario-based experiments. These experiments demonstrated AIRLINE-EVOS's capabilities in responding to an input price shock in fuel prices, and to equipage challenges in a series of analyses based on potential incentive policies for best equipped best served, optimal-wind routing, and traffic management initiative exemption concepts..

A generic framework for individual-based modelling and physical-biological interaction

PubMed Central

2018-01-01

The increased availability of high-resolution ocean data globally has enabled more detailed analyses of physical-biological interactions and their consequences to the ecosystem. We present IBMlib, which is a versatile, portable and computationally effective framework for conducting Lagrangian simulations in the marine environment. The purpose of the framework is to handle complex individual-level biological models of organisms, combined with realistic 3D oceanographic model of physics and biogeochemistry describing the environment of the organisms without assumptions about spatial or temporal scales. The open-source framework features a minimal robust interface to facilitate the coupling between individual-level biological models and oceanographic models, and we provide application examples including forward/backward simulations, habitat connectivity calculations, assessing ocean conditions, comparison of physical circulation models, model ensemble runs and recently posterior Eulerian simulations using the IBMlib framework. We present the code design ideas behind the longevity of the code, our implementation experiences, as well as code performance benchmarking. The framework may contribute substantially to progresses in representing, understanding, predicting and eventually managing marine ecosystems. PMID:29351280

Computer-Simulation Surrogates for Optimization: Application to Trapezoidal Ducts and Axisymmetric Bodies

NASA Technical Reports Server (NTRS)

Otto, John C.; Paraschivoiu, Marius; Yesilyurt, Serhat; Patera, Anthony T.

1995-01-01

Engineering design and optimization efforts using computational systems rapidly become resource intensive. The goal of the surrogate-based approach is to perform a complete optimization with limited resources. In this paper we present a Bayesian-validated approach that informs the designer as to how well the surrogate performs; in particular, our surrogate framework provides precise (albeit probabilistic) bounds on the errors incurred in the surrogate-for-simulation substitution. The theory and algorithms of our computer{simulation surrogate framework are first described. The utility of the framework is then demonstrated through two illustrative examples: maximization of the flowrate of fully developed ow in trapezoidal ducts; and design of an axisymmetric body that achieves a target Stokes drag.

Open-source framework for documentation of scientific software written on MATLAB-compatible programming languages

NASA Astrophysics Data System (ADS)

Konnik, Mikhail V.; Welsh, James

2012-09-01

Numerical simulators for adaptive optics systems have become an essential tool for the research and development of the future advanced astronomical instruments. However, growing software code of the numerical simulator makes it difficult to continue to support the code itself. The problem of adequate documentation of the astronomical software for adaptive optics simulators may complicate the development since the documentation must contain up-to-date schemes and mathematical descriptions implemented in the software code. Although most modern programming environments like MATLAB or Octave have in-built documentation abilities, they are often insufficient for the description of a typical adaptive optics simulator code. This paper describes a general cross-platform framework for the documentation of scientific software using open-source tools such as LATEX, mercurial, Doxygen, and Perl. Using the Perl script that translates M-files MATLAB comments into C-like, one can use Doxygen to generate and update the documentation for the scientific source code. The documentation generated by this framework contains the current code description with mathematical formulas, images, and bibliographical references. A detailed description of the framework components is presented as well as the guidelines for the framework deployment. Examples of the code documentation for the scripts and functions of a MATLAB-based adaptive optics simulator are provided.

The Role of Multiphysics Simulation in Multidisciplinary Analysis

NASA Technical Reports Server (NTRS)

Rifai, Steven M.; Ferencz, Robert M.; Wang, Wen-Ping; Spyropoulos, Evangelos T.; Lawrence, Charles; Melis, Matthew E.

1998-01-01

This article describes the applications of the Spectrum(Tm) Solver in Multidisciplinary Analysis (MDA). Spectrum, a multiphysics simulation software based on the finite element method, addresses compressible and incompressible fluid flow, structural, and thermal modeling as well as the interaction between these disciplines. Multiphysics simulation is based on a single computational framework for the modeling of multiple interacting physical phenomena. Interaction constraints are enforced in a fully-coupled manner using the augmented-Lagrangian method. Within the multiphysics framework, the finite element treatment of fluids is based on Galerkin-Least-Squares (GLS) method with discontinuity capturing operators. The arbitrary-Lagrangian-Eulerian method is utilized to account for deformable fluid domains. The finite element treatment of solids and structures is based on the Hu-Washizu variational principle. The multiphysics architecture lends itself naturally to high-performance parallel computing. Aeroelastic, propulsion, thermal management and manufacturing applications are presented.

Realistic Simulations of Coronagraphic Observations with Future Space Telescopes

NASA Astrophysics Data System (ADS)

Rizzo, M. J.; Roberge, A.; Lincowski, A. P.; Zimmerman, N. T.; Juanola-Parramon, R.; Pueyo, L.; Hu, M.; Harness, A.

2017-11-01

We present a framework to simulate realistic observations of future space-based coronagraphic instruments. This gathers state-of-the-art scientific and instrumental expertise allowing robust characterization of future instrument concepts.

Simulation-Based Approach for Site-Specific Optimization of Hydrokinetic Turbine Arrays

NASA Astrophysics Data System (ADS)

Sotiropoulos, F.; Chawdhary, S.; Yang, X.; Khosronejad, A.; Angelidis, D.

2014-12-01

A simulation-based approach has been developed to enable site-specific optimization of tidal and current turbine arrays in real-life waterways. The computational code is based on the St. Anthony Falls Laboratory Virtual StreamLab (VSL3D), which is able to carry out high-fidelity simulations of turbulent flow and sediment transport processes in rivers and streams taking into account the arbitrary geometrical complexity characterizing natural waterways. The computational framework can be used either in turbine-resolving mode, to take into account all geometrical details of the turbine, or with the turbines parameterized as actuator disks or actuator lines. Locally refined grids are employed to dramatically increase the resolution of the simulation and enable efficient simulations of multi-turbine arrays. Turbine/sediment interactions are simulated using the coupled hydro-morphodynamic module of VSL3D. The predictive capabilities of the resulting computational framework will be demonstrated by applying it to simulate turbulent flow past a tri-frame configuration of hydrokinetic turbines in a rigid-bed turbulent open channel flow as well as turbines mounted on mobile bed open channels to investigate turbine/sediment interactions. The utility of the simulation-based approach for guiding the optimal development of turbine arrays in real-life waterways will also be discussed and demonstrated. This work was supported by NSF grant IIP-1318201. Simulations were carried out at the Minnesota Supercomputing Institute.

The UPSF code: a metaprogramming-based high-performance automatically parallelized plasma simulation framework

NASA Astrophysics Data System (ADS)

Gao, Xiatian; Wang, Xiaogang; Jiang, Binhao

2017-10-01

UPSF (Universal Plasma Simulation Framework) is a new plasma simulation code designed for maximum flexibility by using edge-cutting techniques supported by C++17 standard. Through use of metaprogramming technique, UPSF provides arbitrary dimensional data structures and methods to support various kinds of plasma simulation models, like, Vlasov, particle in cell (PIC), fluid, Fokker-Planck, and their variants and hybrid methods. Through C++ metaprogramming technique, a single code can be used to arbitrary dimensional systems with no loss of performance. UPSF can also automatically parallelize the distributed data structure and accelerate matrix and tensor operations by BLAS. A three-dimensional particle in cell code is developed based on UPSF. Two test cases, Landau damping and Weibel instability for electrostatic and electromagnetic situation respectively, are presented to show the validation and performance of the UPSF code.

A Level-set based framework for viscous simulation of particle-laden supersonic flows

NASA Astrophysics Data System (ADS)

Das, Pratik; Sen, Oishik; Jacobs, Gustaaf; Udaykumar, H. S.

2017-06-01

Particle-laden supersonic flows are important in natural and industrial processes, such as, volcanic eruptions, explosions, pneumatic conveyance of particle in material processing etc. Numerical study of such high-speed particle laden flows at the mesoscale calls for a numerical framework which allows simulation of supersonic flow around multiple moving solid objects. Only a few efforts have been made toward development of numerical frameworks for viscous simulation of particle-fluid interaction in supersonic flow regime. The current work presents a Cartesian grid based sharp-interface method for viscous simulations of interaction between supersonic flow with moving rigid particles. The no-slip boundary condition is imposed at the solid-fluid interfaces using a modified ghost fluid method (GFM). The current method is validated against the similarity solution of compressible boundary layer over flat-plate and benchmark numerical solution for steady supersonic flow over cylinder. Further validation is carried out against benchmark numerical results for shock induced lift-off of a cylinder in a shock tube. 3D simulation of steady supersonic flow over sphere is performed to compare the numerically obtained drag co-efficient with experimental results. A particle-resolved viscous simulation of shock interaction with a cloud of particles is performed to demonstrate that the current method is suitable for large-scale particle resolved simulations of particle-laden supersonic flows.

Mission Simulation Toolkit

NASA Technical Reports Server (NTRS)

Pisaich, Gregory; Flueckiger, Lorenzo; Neukom, Christian; Wagner, Mike; Buchanan, Eric; Plice, Laura

2007-01-01

The Mission Simulation Toolkit (MST) is a flexible software system for autonomy research. It was developed as part of the Mission Simulation Facility (MSF) project that was started in 2001 to facilitate the development of autonomous planetary robotic missions. Autonomy is a key enabling factor for robotic exploration. There has been a large gap between autonomy software (at the research level), and software that is ready for insertion into near-term space missions. The MST bridges this gap by providing a simulation framework and a suite of tools for supporting research and maturation of autonomy. MST uses a distributed framework based on the High Level Architecture (HLA) standard. A key feature of the MST framework is the ability to plug in new models to replace existing ones with the same services. This enables significant simulation flexibility, particularly the mixing and control of fidelity level. In addition, the MST provides automatic code generation from robot interfaces defined with the Unified Modeling Language (UML), methods for maintaining synchronization across distributed simulation systems, XML-based robot description, and an environment server. Finally, the MSF supports a number of third-party products including dynamic models and terrain databases. Although the communication objects and some of the simulation components that are provided with this toolkit are specifically designed for terrestrial surface rovers, the MST can be applied to any other domain, such as aerial, aquatic, or space.

Event-based simulation of networks with pulse delayed coupling

NASA Astrophysics Data System (ADS)

Klinshov, Vladimir; Nekorkin, Vladimir

2017-10-01

Pulse-mediated interactions are common in networks of different nature. Here we develop a general framework for simulation of networks with pulse delayed coupling. We introduce the discrete map governing the dynamics of such networks and describe the computation algorithm for its numerical simulation.

A Model-Based Approach for Bridging Virtual and Physical Sensor Nodes in a Hybrid Simulation Framework

PubMed Central

Mozumdar, Mohammad; Song, Zhen Yu; Lavagno, Luciano; Sangiovanni-Vincentelli, Alberto L.

2014-01-01

The Model Based Design (MBD) approach is a popular trend to speed up application development of embedded systems, which uses high-level abstractions to capture functional requirements in an executable manner, and which automates implementation code generation. Wireless Sensor Networks (WSNs) are an emerging very promising application area for embedded systems. However, there is a lack of tools in this area, which would allow an application developer to model a WSN application by using high level abstractions, simulate it mapped to a multi-node scenario for functional analysis, and finally use the refined model to automatically generate code for different WSN platforms. Motivated by this idea, in this paper we present a hybrid simulation framework that not only follows the MBD approach for WSN application development, but also interconnects a simulated sub-network with a physical sub-network and then allows one to co-simulate them, which is also known as Hardware-In-the-Loop (HIL) simulation. PMID:24960083

Two-phase simulation-based location-allocation optimization of biomass storage distribution

USDA-ARS?s Scientific Manuscript database

This study presents a two-phase simulation-based framework for finding the optimal locations of biomass storage facilities that is a very critical link on the biomass supply chain, which can help to solve biorefinery concerns (e.g. steady supply, uniform feedstock properties, stable feedstock costs,...

Mechanosensitive Channels: Insights from Continuum-Based Simulations

PubMed Central

Tang, Yuye; Yoo, Jejoong; Yethiraj, Arun; Cui, Qiang; Chen, Xi

2009-01-01

Mechanotransduction plays an important role in regulating cell functions and it is an active topic of research in biophysics. Despite recent advances in experimental and numerical techniques, the intrinsic multiscale nature imposes tremendous challenges for revealing the working mechanisms of mechanosensitive channels. Recently, a continuum-mechanics based hierarchical modeling and simulation framework has been established and applied to study the mechanical responses and gating behaviors of a prototypical mechanosensitive channel, the mechanosensitive channel of large conductance (MscL) in bacteria Escherichia coli (E. coli), from which several putative gating mechanisms have been tested and new insights deduced. This article reviews these latest findings using the continuum mechanics framework and suggests possible improvements for future simulation studies. This computationally efficient and versatile continuum-mechanics based protocol is poised to make contributions to the study of a variety of mechanobiology problems. PMID:18787764

Advanced Information Technology in Simulation Based Life Cycle Design

NASA Technical Reports Server (NTRS)

Renaud, John E.

2003-01-01

In this research a Collaborative Optimization (CO) approach for multidisciplinary systems design is used to develop a decision based design framework for non-deterministic optimization. To date CO strategies have been developed for use in application to deterministic systems design problems. In this research the decision based design (DBD) framework proposed by Hazelrigg is modified for use in a collaborative optimization framework. The Hazelrigg framework as originally proposed provides a single level optimization strategy that combines engineering decisions with business decisions in a single level optimization. By transforming this framework for use in collaborative optimization one can decompose the business and engineering decision making processes. In the new multilevel framework of Decision Based Collaborative Optimization (DBCO) the business decisions are made at the system level. These business decisions result in a set of engineering performance targets that disciplinary engineering design teams seek to satisfy as part of subspace optimizations. The Decision Based Collaborative Optimization framework more accurately models the existing relationship between business and engineering in multidisciplinary systems design.

Web-based Visual Analytics for Extreme Scale Climate Science

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

Steed, Chad A; Evans, Katherine J; Harney, John F

In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via newmore » visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.« less

A Program Structure for Event-Based Speech Synthesis by Rules within a Flexible Segmental Framework.

ERIC Educational Resources Information Center

Hill, David R.

1978-01-01

A program structure based on recently developed techniques for operating system simulation has the required flexibility for use as a speech synthesis algorithm research framework. This program makes synthesis possible with less rigid time and frequency-component structure than simpler schemes. It also meets real-time operation and memory-size…

Advances in the spatially distributed ages-w model: parallel computation, java connection framework (JCF) integration, and streamflow/nitrogen dynamics assessment

USDA-ARS?s Scientific Manuscript database

AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic and water quality (H/WQ) simulation components under the Java Connection Framework (JCF) and the Object Modeling System (OMS) environmental modeling framework. AgES-W is implicitly scala...

Incorporating physically-based microstructures in materials modeling: Bridging phase field and crystal plasticity frameworks

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

Lim, Hojun; Abdeljawad, Fadi; Owen, Steven J.

Here, the mechanical properties of materials systems are highly influenced by various features at the microstructural level. The ability to capture these heterogeneities and incorporate them into continuum-scale frameworks of the deformation behavior is considered a key step in the development of complex non-local models of failure. In this study, we present a modeling framework that incorporates physically-based realizations of polycrystalline aggregates from a phase field (PF) model into a crystal plasticity finite element (CP-FE) framework. Simulated annealing via the PF model yields ensembles of materials microstructures with various grain sizes and shapes. With the aid of a novel FEmore » meshing technique, FE discretizations of these microstructures are generated, where several key features, such as conformity to interfaces, and triple junction angles, are preserved. The discretizations are then used in the CP-FE framework to simulate the mechanical response of polycrystalline α-iron. It is shown that the conformal discretization across interfaces reduces artificial stress localization commonly observed in non-conformal FE discretizations. The work presented herein is a first step towards incorporating physically-based microstructures in lieu of the overly simplified representations that are commonly used. In broader terms, the proposed framework provides future avenues to explore bridging models of materials processes, e.g. additive manufacturing and microstructure evolution of multi-phase multi-component systems, into continuum-scale frameworks of the mechanical properties.« less

Incorporating physically-based microstructures in materials modeling: Bridging phase field and crystal plasticity frameworks

DOE PAGES

Lim, Hojun; Abdeljawad, Fadi; Owen, Steven J.; ...

2016-04-25

Here, the mechanical properties of materials systems are highly influenced by various features at the microstructural level. The ability to capture these heterogeneities and incorporate them into continuum-scale frameworks of the deformation behavior is considered a key step in the development of complex non-local models of failure. In this study, we present a modeling framework that incorporates physically-based realizations of polycrystalline aggregates from a phase field (PF) model into a crystal plasticity finite element (CP-FE) framework. Simulated annealing via the PF model yields ensembles of materials microstructures with various grain sizes and shapes. With the aid of a novel FEmore » meshing technique, FE discretizations of these microstructures are generated, where several key features, such as conformity to interfaces, and triple junction angles, are preserved. The discretizations are then used in the CP-FE framework to simulate the mechanical response of polycrystalline α-iron. It is shown that the conformal discretization across interfaces reduces artificial stress localization commonly observed in non-conformal FE discretizations. The work presented herein is a first step towards incorporating physically-based microstructures in lieu of the overly simplified representations that are commonly used. In broader terms, the proposed framework provides future avenues to explore bridging models of materials processes, e.g. additive manufacturing and microstructure evolution of multi-phase multi-component systems, into continuum-scale frameworks of the mechanical properties.« less

Scenario Based Education as a Framework for Understanding Students Engagement and Learning in a Project Management Simulation Game

ERIC Educational Resources Information Center

Misfeldt, Morten

2015-01-01

In this paper I describe how students use a project management simulation game based on an attack-defense mechanism where two teams of players compete by challenging each other's projects. The project management simulation game is intended to be played by pre-service construction workers and engineers. The gameplay has two parts: a planning part,…

The Parallel System for Integrating Impact Models and Sectors (pSIMS)

NASA Technical Reports Server (NTRS)

Elliott, Joshua; Kelly, David; Chryssanthacopoulos, James; Glotter, Michael; Jhunjhnuwala, Kanika; Best, Neil; Wilde, Michael; Foster, Ian

2014-01-01

We present a framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS accelerates computational research, encourages model intercomparison, and enhances reproducibility of simulation results. We present the pSIMS design and use example assessments to demonstrate its multi-model, multi-scale, and multi-sector versatility.

Spatial-temporal-covariance-based modeling, analysis, and simulation of aero-optics wavefront aberrations.

PubMed

Vogel, Curtis R; Tyler, Glenn A; Wittich, Donald J

2014-07-01

We introduce a framework for modeling, analysis, and simulation of aero-optics wavefront aberrations that is based on spatial-temporal covariance matrices extracted from wavefront sensor measurements. Within this framework, we present a quasi-homogeneous structure function to analyze nonhomogeneous, mildly anisotropic spatial random processes, and we use this structure function to show that phase aberrations arising in aero-optics are, for an important range of operating parameters, locally Kolmogorov. This strongly suggests that the d5/3 power law for adaptive optics (AO) deformable mirror fitting error, where d denotes actuator separation, holds for certain important aero-optics scenarios. This framework also allows us to compute bounds on AO servo lag error and predictive control error. In addition, it provides us with the means to accurately simulate AO systems for the mitigation of aero-effects, and it may provide insight into underlying physical processes associated with turbulent flow. The techniques introduced here are demonstrated using data obtained from the Airborne Aero-Optics Laboratory.

Extending MAM5 Meta-Model and JaCalIV E Framework to Integrate Smart Devices from Real Environments.

PubMed

Rincon, J A; Poza-Lujan, Jose-Luis; Julian, V; Posadas-Yagüe, Juan-Luis; Carrascosa, C

2016-01-01

This paper presents the extension of a meta-model (MAM5) and a framework based on the model (JaCalIVE) for developing intelligent virtual environments. The goal of this extension is to develop augmented mirror worlds that represent a real and virtual world coupled, so that the virtual world not only reflects the real one, but also complements it. A new component called a smart resource artifact, that enables modelling and developing devices to access the real physical world, and a human in the loop agent to place a human in the system have been included in the meta-model and framework. The proposed extension of MAM5 has been tested by simulating a light control system where agents can access both virtual and real sensor/actuators through the smart resources developed. The results show that the use of real environment interactive elements (smart resource artifacts) in agent-based simulations allows to minimize the error between simulated and real system.

Extending MAM5 Meta-Model and JaCalIV E Framework to Integrate Smart Devices from Real Environments

PubMed Central

2016-01-01

This paper presents the extension of a meta-model (MAM5) and a framework based on the model (JaCalIVE) for developing intelligent virtual environments. The goal of this extension is to develop augmented mirror worlds that represent a real and virtual world coupled, so that the virtual world not only reflects the real one, but also complements it. A new component called a smart resource artifact, that enables modelling and developing devices to access the real physical world, and a human in the loop agent to place a human in the system have been included in the meta-model and framework. The proposed extension of MAM5 has been tested by simulating a light control system where agents can access both virtual and real sensor/actuators through the smart resources developed. The results show that the use of real environment interactive elements (smart resource artifacts) in agent-based simulations allows to minimize the error between simulated and real system. PMID:26926691

XIMPOL: a new x-ray polarimetry observation-simulation and analysis framework

NASA Astrophysics Data System (ADS)

Omodei, Nicola; Baldini, Luca; Pesce-Rollins, Melissa; di Lalla, Niccolò

2017-08-01

We present a new simulation framework, XIMPOL, based on the python programming language and the Scipy stack, specifically developed for X-ray polarimetric applications. XIMPOL is not tied to any specific mission or instrument design and is meant to produce fast and yet realistic observation-simulations, given as basic inputs: (i) an arbitrary source model including morphological, temporal, spectral and polarimetric information, and (ii) the response functions of the detector under study, i.e., the effective area, the energy dispersion, the point-spread function and the modulation factor. The format of the response files is OGIP compliant, and the framework has the capability of producing output files that can be directly fed into the standard visualization and analysis tools used by the X-ray community, including XSPEC which make it a useful tool not only for simulating physical systems, but also to develop and test end-to-end analysis chains.

A Framework for Image-Based Modeling of Acute Myocardial Ischemia Using Intramurally Recorded Extracellular Potentials.

PubMed

Burton, Brett M; Aras, Kedar K; Good, Wilson W; Tate, Jess D; Zenger, Brian; MacLeod, Rob S

2018-05-21

The biophysical basis for electrocardiographic evaluation of myocardial ischemia stems from the notion that ischemic tissues develop, with relative uniformity, along the endocardial aspects of the heart. These injured regions of subendocardial tissue give rise to intramural currents that lead to ST segment deflections within electrocardiogram (ECG) recordings. The concept of subendocardial ischemic regions is often used in clinical practice, providing a simple and intuitive description of ischemic injury; however, such a model grossly oversimplifies the presentation of ischemic disease-inadvertently leading to errors in ECG-based diagnoses. Furthermore, recent experimental studies have brought into question the subendocardial ischemia paradigm suggesting instead a more distributed pattern of tissue injury. These findings come from experiments and so have both the impact and the limitations of measurements from living organisms. Computer models have often been employed to overcome the constraints of experimental approaches and have a robust history in cardiac simulation. To this end, we have developed a computational simulation framework aimed at elucidating the effects of ischemia on measurable cardiac potentials. To validate our framework, we simulated, visualized, and analyzed 226 experimentally derived acute myocardial ischemic events. Simulation outcomes agreed both qualitatively (feature comparison) and quantitatively (correlation, average error, and significance) with experimentally obtained epicardial measurements, particularly under conditions of elevated ischemic stress. Our simulation framework introduces a novel approach to incorporating subject-specific, geometric models and experimental results that are highly resolved in space and time into computational models. We propose this framework as a means to advance the understanding of the underlying mechanisms of ischemic disease while simultaneously putting in place the computational infrastructure necessary to study and improve ischemia models aimed at reducing diagnostic errors in the clinic.

Generalizable open source urban water portfolio simulation framework demonstrated using a multi-objective risk-based planning benchmark problem.

NASA Astrophysics Data System (ADS)

Trindade, B. C.; Reed, P. M.

2017-12-01

The growing access and reduced cost for computing power in recent years has promoted rapid development and application of multi-objective water supply portfolio planning. As this trend continues there is a pressing need for flexible risk-based simulation frameworks and improved algorithm benchmarking for emerging classes of water supply planning and management problems. This work contributes the Water Utilities Management and Planning (WUMP) model: a generalizable and open source simulation framework designed to capture how water utilities can minimize operational and financial risks by regionally coordinating planning and management choices, i.e. making more efficient and coordinated use of restrictions, water transfers and financial hedging combined with possible construction of new infrastructure. We introduce the WUMP simulation framework as part of a new multi-objective benchmark problem for planning and management of regionally integrated water utility companies. In this problem, a group of fictitious water utilities seek to balance the use of the mentioned reliability driven actions (e.g., restrictions, water transfers and infrastructure pathways) and their inherent financial risks. Several traits of this problem make it ideal for a benchmark problem, namely the presence of (1) strong non-linearities and discontinuities in the Pareto front caused by the step-wise nature of the decision making formulation and by the abrupt addition of storage through infrastructure construction, (2) noise due to the stochastic nature of the streamflows and water demands, and (3) non-separability resulting from the cooperative formulation of the problem, in which decisions made by stakeholder may substantially impact others. Both the open source WUMP simulation framework and its demonstration in a challenging benchmarking example hold value for promoting broader advances in urban water supply portfolio planning for regions confronting change.

A novel framework for virtual prototyping of rehabilitation exoskeletons.

PubMed

Agarwal, Priyanshu; Kuo, Pei-Hsin; Neptune, Richard R; Deshpande, Ashish D

2013-06-01

Human-worn rehabilitation exoskeletons have the potential to make therapeutic exercises increasingly accessible to disabled individuals while reducing the cost and labor involved in rehabilitation therapy. In this work, we propose a novel human-model-in-the-loop framework for virtual prototyping (design, control and experimentation) of rehabilitation exoskeletons by merging computational musculoskeletal analysis with simulation-based design techniques. The framework allows to iteratively optimize design and control algorithm of an exoskeleton using simulation. We introduce biomechanical, morphological, and controller measures to quantify the performance of the device for optimization study. Furthermore, the framework allows one to carry out virtual experiments for testing specific "what-if" scenarios to quantify device performance and recovery progress. To illustrate the application of the framework, we present a case study wherein the design and analysis of an index-finger exoskeleton is carried out using the proposed framework.

In Vivo Investigation of the Effectiveness of a Hyper-viscoelastic Model in Simulating Brain Retraction

PubMed Central

Li, Ping; Wang, Weiwei; Zhang, Chenxi; An, Yong; Song, Zhijian

2016-01-01

Intraoperative brain retraction leads to a misalignment between the intraoperative positions of the brain structures and their previous positions, as determined from preoperative images. In vitro swine brain sample uniaxial tests showed that the mechanical response of brain tissue to compression and extension could be described by the hyper-viscoelasticity theory. The brain retraction caused by the mechanical process is a combination of brain tissue compression and extension. In this paper, we first constructed a hyper-viscoelastic framework based on the extended finite element method (XFEM) to simulate intraoperative brain retraction. To explore its effectiveness, we then applied this framework to an in vivo brain retraction simulation. The simulation strictly followed the clinical scenario, in which seven swine were subjected to brain retraction. Our experimental results showed that the hyper-viscoelastic XFEM framework is capable of simulating intraoperative brain retraction and improving the navigation accuracy of an image-guided neurosurgery system (IGNS). PMID:27387301

An Object-Oriented Finite Element Framework for Multiphysics Phase Field Simulations

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

Michael R Tonks; Derek R Gaston; Paul C Millett

2012-01-01

The phase field approach is a powerful and popular method for modeling microstructure evolution. In this work, advanced numerical tools are used to create a phase field framework that facilitates rapid model development. This framework, called MARMOT, is based on Idaho National Laboratory's finite element Multiphysics Object-Oriented Simulation Environment. In MARMOT, the system of phase field partial differential equations (PDEs) are solved simultaneously with PDEs describing additional physics, such as solid mechanics and heat conduction, using the Jacobian-Free Newton Krylov Method. An object-oriented architecture is created by taking advantage of commonalities in phase fields models to facilitate development of newmore » models with very little written code. In addition, MARMOT provides access to mesh and time step adaptivity, reducing the cost for performing simulations with large disparities in both spatial and temporal scales. In this work, phase separation simulations are used to show the numerical performance of MARMOT. Deformation-induced grain growth and void growth simulations are included to demonstrate the muliphysics capability.« less

The Framework for 0-D Atmospheric Modeling (F0AM) v3.1

NASA Technical Reports Server (NTRS)

Wolfe, Glenn M.; Marvin, Margaret R.; Roberts, Sandra J.; Travis, Katherine R.; Liao, Jin

2016-01-01

The Framework for 0-D Atmospheric Modeling(F0AM) is a flexible and user-friendly MATLAB-based platform for simulation of atmospheric chemistry systems. The F0AM interface incorporates front-end configuration of observational constraints and model setups, making it readily adaptable to simulation of photochemical chambers, Lagrangian plumes, and steady-state or time-evolving solar cycles. Six different chemical mechanisms and three options for calculation of photolysis frequencies are currently available. Example simulations are presented to illustrate model capabilities and, more generally, highlight some of the advantages and challenges of 0-D box modeling.

Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation. Volume 1: Study results

NASA Technical Reports Server (NTRS)

Lowrie, J. W.; Fermelia, A. J.; Haley, D. C.; Gremban, K. D.; Vanbaalen, J.; Walsh, R. W.

1982-01-01

A variety of artificial intelligence techniques which could be used with regard to NASA space applications and robotics were evaluated. The techniques studied were decision tree manipulators, problem solvers, rule based systems, logic programming languages, representation language languages, and expert systems. The overall structure of a robotic simulation tool was defined and a framework for that tool developed. Nonlinear and linearized dynamics equations were formulated for n link manipulator configurations. A framework for the robotic simulation was established which uses validated manipulator component models connected according to a user defined configuration.

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

DTIC Science & Technology

2014-04-30

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

A generalized framework for nucleosynthesis calculations

NASA Astrophysics Data System (ADS)

Sprouse, Trevor; Mumpower, Matthew; Aprahamian, Ani

2014-09-01

Simulating astrophysical events is a difficult process, requiring a detailed pairing of knowledge from both astrophysics and nuclear physics. Astrophysics guides the thermodynamic evolution of an astrophysical event. We present a nucleosynthesis framework written in Fortran that combines as inputs a thermodynamic evolution and nuclear data to time evolve the abundances of nuclear species. Through our coding practices, we have emphasized the applicability of our framework to any astrophysical event, including those involving nuclear fission. Because these calculations are often very complicated, our framework dynamically optimizes itself based on the conditions at each time step in order to greatly minimize total computation time. To highlight the power of this new approach, we demonstrate the use of our framework to simulate both Big Bang nucleosynthesis and r-process nucleosynthesis with speeds competitive with current solutions dedicated to either process alone.

Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

NASA Technical Reports Server (NTRS)

Spear, Ashley D.; Priest, Amanda R.; Veilleux, Michael G.; Ingraffea, Anthony R.; Hochhalter, Jacob D.

2011-01-01

A surrogate model methodology is described for predicting in real time the residual strength of flight structures with discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. A residual strength test of a metallic, integrally-stiffened panel is simulated to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data would, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high-fidelity fracture simulation framework provide useful tools for adaptive flight technology.

Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

NASA Technical Reports Server (NTRS)

Spear, Ashley D.; Priest, Amanda R.; Veilleux, Michael G.; Ingraffea, Anthony R.; Hochhalter, Jacob D.

2011-01-01

A surrogate model methodology is described for predicting, during flight, the residual strength of aircraft structures that sustain discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. Two ductile fracture simulations are presented to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data does, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high fidelity fracture simulation framework provide useful tools for adaptive flight technology.

Inventory-based landscape-scale simulation of management effectiveness and economic feasibility with BioSum

Treesearch

Jeremy S. Fried; Larry D. Potts; Sara M. Loreno; Glenn A. Christensen; R. Jamie Barbour

2017-01-01

The Forest Inventory and Analysis (FIA)-based BioSum (Bioregional Inventory Originated Simulation Under Management) is a free policy analysis framework and workflow management software solution. It addresses complex management questions concerning forest health and vulnerability for large, multimillion acre, multiowner landscapes using FIA plot data as the initial...

GADEN: A 3D Gas Dispersion Simulator for Mobile Robot Olfaction in Realistic Environments.

PubMed

Monroy, Javier; Hernandez-Bennets, Victor; Fan, Han; Lilienthal, Achim; Gonzalez-Jimenez, Javier

2017-06-23

This work presents a simulation framework developed under the widely used Robot Operating System (ROS) to enable the validation of robotics systems and gas sensing algorithms under realistic environments. The framework is rooted in the principles of computational fluid dynamics and filament dispersion theory, modeling wind flow and gas dispersion in 3D real-world scenarios (i.e., accounting for walls, furniture, etc.). Moreover, it integrates the simulation of different environmental sensors, such as metal oxide gas sensors, photo ionization detectors, or anemometers. We illustrate the potential and applicability of the proposed tool by presenting a simulation case in a complex and realistic office-like environment where gas leaks of different chemicals occur simultaneously. Furthermore, we accomplish quantitative and qualitative validation by comparing our simulated results against real-world data recorded inside a wind tunnel where methane was released under different wind flow profiles. Based on these results, we conclude that our simulation framework can provide a good approximation to real world measurements when advective airflows are present in the environment.

GADEN: A 3D Gas Dispersion Simulator for Mobile Robot Olfaction in Realistic Environments

PubMed Central

Hernandez-Bennetts, Victor; Fan, Han; Lilienthal, Achim; Gonzalez-Jimenez, Javier

2017-01-01

This work presents a simulation framework developed under the widely used Robot Operating System (ROS) to enable the validation of robotics systems and gas sensing algorithms under realistic environments. The framework is rooted in the principles of computational fluid dynamics and filament dispersion theory, modeling wind flow and gas dispersion in 3D real-world scenarios (i.e., accounting for walls, furniture, etc.). Moreover, it integrates the simulation of different environmental sensors, such as metal oxide gas sensors, photo ionization detectors, or anemometers. We illustrate the potential and applicability of the proposed tool by presenting a simulation case in a complex and realistic office-like environment where gas leaks of different chemicals occur simultaneously. Furthermore, we accomplish quantitative and qualitative validation by comparing our simulated results against real-world data recorded inside a wind tunnel where methane was released under different wind flow profiles. Based on these results, we conclude that our simulation framework can provide a good approximation to real world measurements when advective airflows are present in the environment. PMID:28644375

Development of an integrated economic and ecological framework for ecosystem-based fisheries management in New England

NASA Astrophysics Data System (ADS)

Jin, D.; Hoagland, P.; Dalton, T. M.; Thunberg, E. M.

2012-09-01

We present an integrated economic-ecological framework designed to help assess the implementation of ecosystem-based fisheries management (EBFM) in New England. We develop the framework by linking a computable general equilibrium (CGE) model of a coastal economy to an end-to-end (E2E) model of a marine food web for Georges Bank. We focus on the New England region using coastal county economic data for a restricted set of industry sectors and marine ecological data for three top level trophic feeding guilds: planktivores, benthivores, and piscivores. We undertake numerical simulations to model the welfare effects of changes in alternative combinations of yields from feeding guilds and alternative manifestations of biological productivity. We estimate the economic and distributional effects of these alternative simulations across a range of consumer income levels. This framework could be used to extend existing methodologies for assessing the impacts on human communities of groundfish stock rebuilding strategies, such as those expected through the implementation of the sector management program in the US northeast fishery. We discuss other possible applications of and modifications and limitations to the framework.

High-Performance Computer Modeling of the Cosmos-Iridium Collision

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

Olivier, S; Cook, K; Fasenfest, B

2009-08-28

This paper describes the application of a new, integrated modeling and simulation framework, encompassing the space situational awareness (SSA) enterprise, to the recent Cosmos-Iridium collision. This framework is based on a flexible, scalable architecture to enable efficient simulation of the current SSA enterprise, and to accommodate future advancements in SSA systems. In particular, the code is designed to take advantage of massively parallel, high-performance computer systems available, for example, at Lawrence Livermore National Laboratory. We will describe the application of this framework to the recent collision of the Cosmos and Iridium satellites, including (1) detailed hydrodynamic modeling of the satellitemore » collision and resulting debris generation, (2) orbital propagation of the simulated debris and analysis of the increased risk to other satellites (3) calculation of the radar and optical signatures of the simulated debris and modeling of debris detection with space surveillance radar and optical systems (4) determination of simulated debris orbits from modeled space surveillance observations and analysis of the resulting orbital accuracy, (5) comparison of these modeling and simulation results with Space Surveillance Network observations. We will also discuss the use of this integrated modeling and simulation framework to analyze the risks and consequences of future satellite collisions and to assess strategies for mitigating or avoiding future incidents, including the addition of new sensor systems, used in conjunction with the Space Surveillance Network, for improving space situational awareness.« less

Analysis of GEANT4 Physics List Properties in the 12 GeV MOLLER Simulation Framework

NASA Astrophysics Data System (ADS)

Haufe, Christopher; Moller Collaboration

2013-10-01

To determine the validity of new physics beyond the scope of the electroweak theory, nuclear physicists across the globe have been collaborating on future endeavors that will provide the precision needed to confirm these speculations. One of these is the MOLLER experiment - a low-energy particle experiment that will utilize the 12 GeV upgrade of Jefferson Lab's CEBAF accelerator. The motivation of this experiment is to measure the parity-violating asymmetry of scattered polarized electrons off unpolarized electrons in a liquid hydrogen target. This measurement would allow for a more precise determination of the electron's weak charge and weak mixing angle. While still in its planning stages, the MOLLER experiment requires a detailed simulation framework in order to determine how the project should be run in the future. The simulation framework for MOLLER, called ``remoll'', is written in GEANT4 code. As a result, the simulation can utilize a number of GEANT4 coded physics lists that provide the simulation with a number of particle interaction constraints based off of different particle physics models. By comparing these lists with one another using the data-analysis application ROOT, the most optimal physics list for the MOLLER simulation can be determined and implemented. This material is based upon work supported by the National Science Foundation under Grant No. 714001.

Numerical Propulsion System Simulation Architecture

NASA Technical Reports Server (NTRS)

Naiman, Cynthia G.

2004-01-01

The Numerical Propulsion System Simulation (NPSS) is a framework for performing analysis of complex systems. Because the NPSS was developed using the object-oriented paradigm, the resulting architecture is an extensible and flexible framework that is currently being used by a diverse set of participants in government, academia, and the aerospace industry. NPSS is being used by over 15 different institutions to support rockets, hypersonics, power and propulsion, fuel cells, ground based power, and aerospace. Full system-level simulations as well as subsystems may be modeled using NPSS. The NPSS architecture enables the coupling of analyses at various levels of detail, which is called numerical zooming. The middleware used to enable zooming and distributed simulations is the Common Object Request Broker Architecture (CORBA). The NPSS Developer's Kit offers tools for the developer to generate CORBA-based components and wrap codes. The Developer's Kit enables distributed multi-fidelity and multi-discipline simulations, preserves proprietary and legacy codes, and facilitates addition of customized codes. The platforms supported are PC, Linux, HP, Sun, and SGI.

Detoxification of Chemical Warfare Agents Using a Zr6 -Based Metal-Organic Framework/Polymer Mixture.

PubMed

Moon, Su-Young; Proussaloglou, Emmanuel; Peterson, Gregory W; DeCoste, Jared B; Hall, Morgan G; Howarth, Ashlee J; Hupp, Joseph T; Farha, Omar K

2016-10-10

Owing to their high surface area, periodic distribution of metal sites, and water stability, zirconium-based metal-organic frameworks (Zr 6 -MOFs) have shown promising activity for the hydrolysis of nerve agents GD and VX, as well as the simulant, dimethyl 4-nitrophenylphosphate (DMNP), in buffered solutions. A hurdle to using MOFs for this application is the current need for a buffer solution. Here the destruction of the simulant DMNP, as well as the chemical warfare agents (GD and VX) through hydrolysis using a MOF catalyst mixed with a non-volatile, water-insoluble, heterogeneous buffer is reported. The hydrolysis of the simulant and nerve agents in the presence of the heterogeneous buffer was fast and effective. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

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

Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung

2011-01-01

The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level.more » It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.« less

Simulation-based optimization framework for reuse of agricultural drainage water in irrigation.

PubMed

Allam, A; Tawfik, A; Yoshimura, C; Fleifle, A

2016-05-01

A simulation-based optimization framework for agricultural drainage water (ADW) reuse has been developed through the integration of a water quality model (QUAL2Kw) and a genetic algorithm. This framework was applied to the Gharbia drain in the Nile Delta, Egypt, in summer and winter 2012. First, the water quantity and quality of the drain was simulated using the QUAL2Kw model. Second, uncertainty analysis and sensitivity analysis based on Monte Carlo simulation were performed to assess QUAL2Kw's performance and to identify the most critical variables for determination of water quality, respectively. Finally, a genetic algorithm was applied to maximize the total reuse quantity from seven reuse locations with the condition not to violate the standards for using mixed water in irrigation. The water quality simulations showed that organic matter concentrations are critical management variables in the Gharbia drain. The uncertainty analysis showed the reliability of QUAL2Kw to simulate water quality and quantity along the drain. Furthermore, the sensitivity analysis showed that the 5-day biochemical oxygen demand, chemical oxygen demand, total dissolved solids, total nitrogen and total phosphorous are highly sensitive to point source flow and quality. Additionally, the optimization results revealed that the reuse quantities of ADW can reach 36.3% and 40.4% of the available ADW in the drain during summer and winter, respectively. These quantities meet 30.8% and 29.1% of the drainage basin requirements for fresh irrigation water in the respective seasons. Copyright © 2016 Elsevier Ltd. All rights reserved.

Learning Theory Foundations of Simulation-Based Mastery Learning.

PubMed

McGaghie, William C; Harris, Ilene B

2018-06-01

Simulation-based mastery learning (SBML), like all education interventions, has learning theory foundations. Recognition and comprehension of SBML learning theory foundations are essential for thoughtful education program development, research, and scholarship. We begin with a description of SBML followed by a section on the importance of learning theory foundations to shape and direct SBML education and research. We then discuss three principal learning theory conceptual frameworks that are associated with SBML-behavioral, constructivist, social cognitive-and their contributions to SBML thought and practice. We then discuss how the three learning theory frameworks converge in the course of planning, conducting, and evaluating SBML education programs in the health professions. Convergence of these learning theory frameworks is illustrated by a description of an SBML education and research program in advanced cardiac life support. We conclude with a brief coda.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE PAGES

Hagos, Samson; Feng, Zhe; Plant, Robert S.; ...

2018-02-20

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

NASA Astrophysics Data System (ADS)

Hagos, Samson; Feng, Zhe; Plant, Robert S.; Houze, Robert A.; Xiao, Heng

2018-02-01

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

An ice sheet model validation framework for the Greenland ice sheet.

PubMed

Price, Stephen F; Hoffman, Matthew J; Bonin, Jennifer A; Howat, Ian M; Neumann, Thomas; Saba, Jack; Tezaur, Irina; Guerber, Jeffrey; Chambers, Don P; Evans, Katherine J; Kennedy, Joseph H; Lenaerts, Jan; Lipscomb, William H; Perego, Mauro; Salinger, Andrew G; Tuminaro, Raymond S; van den Broeke, Michiel R; Nowicki, Sophie M J

2017-01-01

We propose a new ice sheet model validation framework - the Cryospheric Model Comparison Tool (CmCt) - that takes advantage of ice sheet altimetry and gravimetry observations collected over the past several decades and is applied here to modeling of the Greenland ice sheet. We use realistic simulations performed with the Community Ice Sheet Model (CISM) along with two idealized, non-dynamic models to demonstrate the framework and its use. Dynamic simulations with CISM are forced from 1991 to 2013 using combinations of reanalysis-based surface mass balance and observations of outlet glacier flux change. We propose and demonstrate qualitative and quantitative metrics for use in evaluating the different model simulations against the observations. We find that the altimetry observations used here are largely ambiguous in terms of their ability to distinguish one simulation from another. Based on basin- and whole-ice-sheet scale metrics, we find that simulations using both idealized conceptual models and dynamic, numerical models provide an equally reasonable representation of the ice sheet surface (mean elevation differences of <1 m). This is likely due to their short period of record, biases inherent to digital elevation models used for model initial conditions, and biases resulting from firn dynamics, which are not explicitly accounted for in the models or observations. On the other hand, we find that the gravimetry observations used here are able to unambiguously distinguish between simulations of varying complexity, and along with the CmCt, can provide a quantitative score for assessing a particular model and/or simulation. The new framework demonstrates that our proposed metrics can distinguish relatively better from relatively worse simulations and that dynamic ice sheet models, when appropriately initialized and forced with the right boundary conditions, demonstrate predictive skill with respect to observed dynamic changes occurring on Greenland over the past few decades. An extensible design will allow for continued use of the CmCt as future altimetry, gravimetry, and other remotely sensed data become available for use in ice sheet model validation.

Numerical modeling of the fracture process in a three-unit all-ceramic fixed partial denture.

PubMed

Kou, Wen; Kou, Shaoquan; Liu, Hongyuan; Sjögren, Göran

2007-08-01

The main objectives were to examine the fracture mechanism and process of a ceramic fixed partial denture (FPD) framework under simulated mechanical loading using a recently developed numerical modeling code, the R-T(2D) code, and also to evaluate the suitability of R-T(2D) code as a tool for this purpose. Using the recently developed R-T(2D) code the fracture mechanism and process of a 3U yttria-tetragonal zirconia polycrystal ceramic (Y-TZP) FPD framework was simulated under static loading. In addition, the fracture pattern obtained using the numerical simulation was compared with the fracture pattern obtained in a previous laboratory test. The result revealed that the framework fracture pattern obtained using the numerical simulation agreed with that observed in a previous laboratory test. Quasi-photoelastic stress fringe pattern and acoustic emission showed that the fracture mechanism was tensile failure and that the crack started at the lower boundary of the framework. The fracture process could be followed both in step-by-step and step-in-step. Based on the findings in the current study, the R-T(2D) code seems suitable for use as a complement to other tests and clinical observations in studying stress distribution, fracture mechanism and fracture processes in ceramic FPD frameworks.

A multi-model framework for simulating wildlife population response to land-use and climate change

USGS Publications Warehouse

McRae, B.H.; Schumaker, N.H.; McKane, R.B.; Busing, R.T.; Solomon, A.M.; Burdick, C.A.

2008-01-01

Reliable assessments of how human activities will affect wildlife populations are essential for making scientifically defensible resource management decisions. A principle challenge of predicting effects of proposed management, development, or conservation actions is the need to incorporate multiple biotic and abiotic factors, including land-use and climate change, that interact to affect wildlife habitat and populations through time. Here we demonstrate how models of land-use, climate change, and other dynamic factors can be integrated into a coherent framework for predicting wildlife population trends. Our framework starts with land-use and climate change models developed for a region of interest. Vegetation changes through time under alternative future scenarios are predicted using an individual-based plant community model. These predictions are combined with spatially explicit animal habitat models to map changes in the distribution and quality of wildlife habitat expected under the various scenarios. Animal population responses to habitat changes and other factors are then projected using a flexible, individual-based animal population model. As an example application, we simulated animal population trends under three future land-use scenarios and four climate change scenarios in the Cascade Range of western Oregon. We chose two birds with contrasting habitat preferences for our simulations: winter wrens (Troglodytes troglodytes), which are most abundant in mature conifer forests, and song sparrows (Melospiza melodia), which prefer more open, shrubby habitats. We used climate and land-use predictions from previously published studies, as well as previously published predictions of vegetation responses using FORCLIM, an individual-based forest dynamics simulator. Vegetation predictions were integrated with other factors in PATCH, a spatially explicit, individual-based animal population simulator. Through incorporating effects of landscape history and limited dispersal, our framework predicted population changes that typically exceeded those expected based on changes in mean habitat suitability alone. Although land-use had greater impacts on habitat quality than did climate change in our simulations, we found that small changes in vital rates resulting from climate change or other stressors can have large consequences for population trajectories. The ability to integrate bottom-up demographic processes like these with top-down constraints imposed by climate and land-use in a dynamic modeling environment is a key advantage of our approach. The resulting framework should allow researchers to synthesize existing empirical evidence, and to explore complex interactions that are difficult or impossible to capture through piecemeal modeling approaches. ?? 2008 Elsevier B.V.

Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part I: Template-Based Generic Programming

DOE PAGES

Pawlowski, Roger P.; Phipps, Eric T.; Salinger, Andrew G.

2012-01-01

An approach for incorporating embedded simulation and analysis capabilities in complex simulation codes through template-based generic programming is presented. This approach relies on templating and operator overloading within the C++ language to transform a given calculation into one that can compute a variety of additional quantities that are necessary for many state-of-the-art simulation and analysis algorithms. An approach for incorporating these ideas into complex simulation codes through general graph-based assembly is also presented. These ideas have been implemented within a set of packages in the Trilinos framework and are demonstrated on a simple problem from chemical engineering.

Reusable Component Model Development Approach for Parallel and Distributed Simulation

PubMed Central

Zhu, Feng; Yao, Yiping; Chen, Huilong; Yao, Feng

2014-01-01

Model reuse is a key issue to be resolved in parallel and distributed simulation at present. However, component models built by different domain experts usually have diversiform interfaces, couple tightly, and bind with simulation platforms closely. As a result, they are difficult to be reused across different simulation platforms and applications. To address the problem, this paper first proposed a reusable component model framework. Based on this framework, then our reusable model development approach is elaborated, which contains two phases: (1) domain experts create simulation computational modules observing three principles to achieve their independence; (2) model developer encapsulates these simulation computational modules with six standard service interfaces to improve their reusability. The case study of a radar model indicates that the model developed using our approach has good reusability and it is easy to be used in different simulation platforms and applications. PMID:24729751

An Agent-Based Modeling Framework and Application for the Generic Nuclear Fuel Cycle

NASA Astrophysics Data System (ADS)

Gidden, Matthew J.

Key components of a novel methodology and implementation of an agent-based, dynamic nuclear fuel cycle simulator, Cyclus , are presented. The nuclear fuel cycle is a complex, physics-dependent supply chain. To date, existing dynamic simulators have not treated constrained fuel supply, time-dependent, isotopic-quality based demand, or fuel fungibility particularly well. Utilizing an agent-based methodology that incorporates sophisticated graph theory and operations research techniques can overcome these deficiencies. This work describes a simulation kernel and agents that interact with it, highlighting the Dynamic Resource Exchange (DRE), the supply-demand framework at the heart of the kernel. The key agent-DRE interaction mechanisms are described, which enable complex entity interaction through the use of physics and socio-economic models. The translation of an exchange instance to a variant of the Multicommodity Transportation Problem, which can be solved feasibly or optimally, follows. An extensive investigation of solution performance and fidelity is then presented. Finally, recommendations for future users of Cyclus and the DRE are provided.

A Novel Probabilistic Multi-Scale Modeling and Sensing Framework for Fatigue Life Prediction of Aerospace Structures and Materials: DCT Project

DTIC Science & Technology

2012-08-25

Accel- erated Crystal Plasticity FEM Simulations (submitted). 5. M. Anahid, M. Samal and S. Ghosh, Dwell fatigue crack nucleation model based on using...4] M. Anahid, M. K. Samal , and S. Ghosh. Dwell fatigue crack nucleation model based on crystal plasticity finite element simulations of

A Framework for Validating Traffic Simulation Models at the Vehicle Trajectory Level

DOT National Transportation Integrated Search

2017-03-01

Based on current practices, traffic simulation models are calibrated and validated using macroscopic measures such as 15-minute averages of traffic counts or average point-to-point travel times. For an emerging number of applications, including conne...

Heartbeat-based error diagnosis framework for distributed embedded systems

NASA Astrophysics Data System (ADS)

Mishra, Swagat; Khilar, Pabitra Mohan

2012-01-01

Distributed Embedded Systems have significant applications in automobile industry as steer-by-wire, fly-by-wire and brake-by-wire systems. In this paper, we provide a general framework for fault detection in a distributed embedded real time system. We use heartbeat monitoring, check pointing and model based redundancy to design a scalable framework that takes care of task scheduling, temperature control and diagnosis of faulty nodes in a distributed embedded system. This helps in diagnosis and shutting down of faulty actuators before the system becomes unsafe. The framework is designed and tested using a new simulation model consisting of virtual nodes working on a message passing system.

Heartbeat-based error diagnosis framework for distributed embedded systems

NASA Astrophysics Data System (ADS)

Mishra, Swagat; Khilar, Pabitra Mohan

2011-12-01

Distributed Embedded Systems have significant applications in automobile industry as steer-by-wire, fly-by-wire and brake-by-wire systems. In this paper, we provide a general framework for fault detection in a distributed embedded real time system. We use heartbeat monitoring, check pointing and model based redundancy to design a scalable framework that takes care of task scheduling, temperature control and diagnosis of faulty nodes in a distributed embedded system. This helps in diagnosis and shutting down of faulty actuators before the system becomes unsafe. The framework is designed and tested using a new simulation model consisting of virtual nodes working on a message passing system.

Simulation of transmission electron microscope images of biological specimens.

PubMed

Rullgård, H; Ofverstedt, L-G; Masich, S; Daneholt, B; Oktem, O

2011-09-01

We present a new approach to simulate electron cryo-microscope images of biological specimens. The framework for simulation consists of two parts; the first is a phantom generator that generates a model of a specimen suitable for simulation, the second is a transmission electron microscope simulator. The phantom generator calculates the scattering potential of an atomic structure in aqueous buffer and allows the user to define the distribution of molecules in the simulated image. The simulator includes a well defined electron-specimen interaction model based on the scalar Schrödinger equation, the contrast transfer function for optics, and a noise model that includes shot noise as well as detector noise including detector blurring. To enable optimal performance, the simulation framework also includes a calibration protocol for setting simulation parameters. To test the accuracy of the new framework for simulation, we compare simulated images to experimental images recorded of the Tobacco Mosaic Virus (TMV) in vitreous ice. The simulated and experimental images show good agreement with respect to contrast variations depending on dose and defocus. Furthermore, random fluctuations present in experimental and simulated images exhibit similar statistical properties. The simulator has been designed to provide a platform for development of new instrumentation and image processing procedures in single particle electron microscopy, two-dimensional crystallography and electron tomography with well documented protocols and an open source code into which new improvements and extensions are easily incorporated. © 2011 The Authors Journal of Microscopy © 2011 Royal Microscopical Society.

Framework of passive millimeter-wave scene simulation based on material classification

NASA Astrophysics Data System (ADS)

Park, Hyuk; Kim, Sung-Hyun; Lee, Ho-Jin; Kim, Yong-Hoon; Ki, Jae-Sug; Yoon, In-Bok; Lee, Jung-Min; Park, Soon-Jun

2006-05-01

Over the past few decades, passive millimeter-wave (PMMW) sensors have emerged as useful implements in transportation and military applications such as autonomous flight-landing system, smart weapons, night- and all weather vision system. As an efficient way to predict the performance of a PMMW sensor and apply it to system, it is required to test in SoftWare-In-the-Loop (SWIL). The PMMW scene simulation is a key component for implementation of this simulator. However, there is no commercial on-the-shelf available to construct the PMMW scene simulation; only there have been a few studies on this technology. We have studied the PMMW scene simulation method to develop the PMMW sensor SWIL simulator. This paper describes the framework of the PMMW scene simulation and the tentative results. The purpose of the PMMW scene simulation is to generate sensor outputs (or image) from a visible image and environmental conditions. We organize it into four parts; material classification mapping, PMMW environmental setting, PMMW scene forming, and millimeter-wave (MMW) sensorworks. The background and the objects in the scene are classified based on properties related with MMW radiation and reflectivity. The environmental setting part calculates the following PMMW phenomenology; atmospheric propagation and emission including sky temperature, weather conditions, and physical temperature. Then, PMMW raw images are formed with surface geometry. Finally, PMMW sensor outputs are generated from PMMW raw images by applying the sensor characteristics such as an aperture size and noise level. Through the simulation process, PMMW phenomenology and sensor characteristics are simulated on the output scene. We have finished the design of framework of the simulator, and are working on implementation in detail. As a tentative result, the flight observation was simulated in specific conditions. After implementation details, we plan to increase the reliability of the simulation by data collecting using actual PMMW sensors. With the reliable PMMW scene simulator, it will be more efficient to apply the PMMW sensor to various applications.

SU-F-J-178: A Computer Simulation Model Observer for Task-Based Image Quality Assessment in Radiation Therapy

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

Dolly, S; Mutic, S; Anastasio, M

Purpose: Traditionally, image quality in radiation therapy is assessed subjectively or by utilizing physically-based metrics. Some model observers exist for task-based medical image quality assessment, but almost exclusively for diagnostic imaging tasks. As opposed to disease diagnosis, the task for image observers in radiation therapy is to utilize the available images to design and deliver a radiation dose which maximizes patient disease control while minimizing normal tissue damage. The purpose of this study was to design and implement a new computer simulation model observer to enable task-based image quality assessment in radiation therapy. Methods: A modular computer simulation framework wasmore » developed to resemble the radiotherapy observer by simulating an end-to-end radiation therapy treatment. Given images and the ground-truth organ boundaries from a numerical phantom as inputs, the framework simulates an external beam radiation therapy treatment and quantifies patient treatment outcomes using the previously defined therapeutic operating characteristic (TOC) curve. As a preliminary demonstration, TOC curves were calculated for various CT acquisition and reconstruction parameters, with the goal of assessing and optimizing simulation CT image quality for radiation therapy. Sources of randomness and bias within the system were analyzed. Results: The relationship between CT imaging dose and patient treatment outcome was objectively quantified in terms of a singular value, the area under the TOC (AUTOC) curve. The AUTOC decreases more rapidly for low-dose imaging protocols. AUTOC variation introduced by the dose optimization algorithm was approximately 0.02%, at the 95% confidence interval. Conclusion: A model observer has been developed and implemented to assess image quality based on radiation therapy treatment efficacy. It enables objective determination of appropriate imaging parameter values (e.g. imaging dose). Framework flexibility allows for incorporation of additional modules to include any aspect of the treatment process, and therefore has great potential for both assessment and optimization within radiation therapy.« less

Semantics-enabled service discovery framework in the SIMDAT pharma grid.

PubMed

Qu, Cangtao; Zimmermann, Falk; Kumpf, Kai; Kamuzinzi, Richard; Ledent, Valérie; Herzog, Robert

2008-03-01

We present the design and implementation of a semantics-enabled service discovery framework in the data Grids for process and product development using numerical simulation and knowledge discovery (SIMDAT) Pharma Grid, an industry-oriented Grid environment for integrating thousands of Grid-enabled biological data services and analysis services. The framework consists of three major components: the Web ontology language (OWL)-description logic (DL)-based biological domain ontology, OWL Web service ontology (OWL-S)-based service annotation, and semantic matchmaker based on the ontology reasoning. Built upon the framework, workflow technologies are extensively exploited in the SIMDAT to assist biologists in (semi)automatically performing in silico experiments. We present a typical usage scenario through the case study of a biological workflow: IXodus.

Simulating human behavior for national security human interactions.

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

Bernard, Michael Lewis; Hart, Dereck H.; Verzi, Stephen J.

2007-01-01

This 3-year research and development effort focused on what we believe is a significant technical gap in existing modeling and simulation capabilities: the representation of plausible human cognition and behaviors within a dynamic, simulated environment. Specifically, the intent of the ''Simulating Human Behavior for National Security Human Interactions'' project was to demonstrate initial simulated human modeling capability that realistically represents intra- and inter-group interaction behaviors between simulated humans and human-controlled avatars as they respond to their environment. Significant process was made towards simulating human behaviors through the development of a framework that produces realistic characteristics and movement. The simulated humansmore » were created from models designed to be psychologically plausible by being based on robust psychological research and theory. Progress was also made towards enhancing Sandia National Laboratories existing cognitive models to support culturally plausible behaviors that are important in representing group interactions. These models were implemented in the modular, interoperable, and commercially supported Umbra{reg_sign} simulation framework.« less

Early Validation of Failure Detection, Isolation, and Recovery Design Using Heterogeneous Modelling and Simulation

NASA Astrophysics Data System (ADS)

van der Plas, Peter; Guerriero, Suzanne; Cristiano, Leorato; Rugina, Ana

2012-08-01

Modelling and simulation can support a number of use cases across the spacecraft development life-cycle. Given the increasing complexity of space missions, the observed general trend is for a more extensive usage of simulation already in the early phases. A major perceived advantage is that modelling and simulation can enable the validation of critical aspects of the spacecraft design before the actual development is started, as such reducing the risk in later phases.Failure Detection, Isolation, and Recovery (FDIR) is one of the areas with a high potential to benefit from early modelling and simulation. With the increasing level of required spacecraft autonomy, FDIR specifications can grow in such a way that the traditional document-based review process soon becomes inadequate.This paper shows that FDIR modelling and simulation in a system context can provide a powerful tool to support the FDIR verification process. It is highlighted that FDIR modelling at this early stage requires heterogeneous modelling tools and languages, in order to provide an adequate functional description of the different components (i.e. FDIR functions, environment, equipment, etc.) to be modelled.For this reason, an FDIR simulation framework is proposed in this paper. This framework is based on a number of tools already available in the Avionics Systems Laboratory at ESTEC, which are the Avionics Test Bench Functional Engineering Simulator (ATB FES), Matlab/Simulink, TASTE, and Real Time Developer Studio (RTDS).The paper then discusses the application of the proposed simulation framework to a real case-study, i.e. the FDIR modelling of a satellite in support of actual ESA mission. Challenges and benefits of the approach are described. Finally, lessons learned and the generality of the proposed approach are discussed.

A hybrid parallel framework for the cellular Potts model simulations

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

Jiang, Yi; He, Kejing; Dong, Shoubin

2009-01-01

The Cellular Potts Model (CPM) has been widely used for biological simulations. However, most current implementations are either sequential or approximated, which can't be used for large scale complex 3D simulation. In this paper we present a hybrid parallel framework for CPM simulations. The time-consuming POE solving, cell division, and cell reaction operation are distributed to clusters using the Message Passing Interface (MPI). The Monte Carlo lattice update is parallelized on shared-memory SMP system using OpenMP. Because the Monte Carlo lattice update is much faster than the POE solving and SMP systems are more and more common, this hybrid approachmore » achieves good performance and high accuracy at the same time. Based on the parallel Cellular Potts Model, we studied the avascular tumor growth using a multiscale model. The application and performance analysis show that the hybrid parallel framework is quite efficient. The hybrid parallel CPM can be used for the large scale simulation ({approx}10{sup 8} sites) of complex collective behavior of numerous cells ({approx}10{sup 6}).« less

Unsteady Analyses of Valve Systems in Rocket Engine Testing Environments

NASA Technical Reports Server (NTRS)

Shipman, Jeremy; Hosangadi, Ashvin; Ahuja, Vineet

2004-01-01

This paper discusses simulation technology used to support the testing of rocket propulsion systems by performing high fidelity analyses of feed system components. A generalized multi-element framework has been used to perform simulations of control valve systems. This framework provides the flexibility to resolve the structural and functional complexities typically associated with valve-based high pressure feed systems that are difficult to deal with using traditional Computational Fluid Dynamics (CFD) methods. In order to validate this framework for control valve systems, results are presented for simulations of a cryogenic control valve at various plug settings and compared to both experimental data and simulation results obtained at NASA Stennis Space Center. A detailed unsteady analysis has also been performed for a pressure regulator type control valve used to support rocket engine and component testing at Stennis Space Center. The transient simulation captures the onset of a modal instability that has been observed in the operation of the valve. A discussion of the flow physics responsible for the instability and a prediction of the dominant modes associated with the fluctuations is presented.

Gating Mechanisms of Mechanosensitive Channels of Large Conductance, I: A Continuum Mechanics-Based Hierarchical Framework

PubMed Central

Chen, Xi; Cui, Qiang; Tang, Yuye; Yoo, Jejoong; Yethiraj, Arun

2008-01-01

A hierarchical simulation framework that integrates information from molecular dynamics (MD) simulations into a continuum model is established to study the mechanical response of mechanosensitive channel of large-conductance (MscL) using the finite element method (FEM). The proposed MD-decorated FEM (MDeFEM) approach is used to explore the detailed gating mechanisms of the MscL in Escherichia coli embedded in a palmitoyloleoylphosphatidylethanolamine lipid bilayer. In Part I of this study, the framework of MDeFEM is established. The transmembrane and cytoplasmic helices are taken to be elastic rods, the loops are modeled as springs, and the lipid bilayer is approximated by a three-layer sheet. The mechanical properties of the continuum components, as well as their interactions, are derived from molecular simulations based on atomic force fields. In addition, analytical closed-form continuum model and elastic network model are established to complement the MDeFEM approach and to capture the most essential features of gating. In Part II of this study, the detailed gating mechanisms of E. coli-MscL under various types of loading are presented and compared with experiments, structural model, and all-atom simulations, as well as the analytical models established in Part I. It is envisioned that such a hierarchical multiscale framework will find great value in the study of a variety of biological processes involving complex mechanical deformations such as muscle contraction and mechanotransduction. PMID:18390626

POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations

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

Auld, Joshua; Hope, Michael; Ley, Hubert

This paper discusses the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typicallymore » done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.« less

Heuristic Identification of Biological Architectures for Simulating Complex Hierarchical Genetic Interactions

PubMed Central

Moore, Jason H; Amos, Ryan; Kiralis, Jeff; Andrews, Peter C

2015-01-01

Simulation plays an essential role in the development of new computational and statistical methods for the genetic analysis of complex traits. Most simulations start with a statistical model using methods such as linear or logistic regression that specify the relationship between genotype and phenotype. This is appealing due to its simplicity and because these statistical methods are commonly used in genetic analysis. It is our working hypothesis that simulations need to move beyond simple statistical models to more realistically represent the biological complexity of genetic architecture. The goal of the present study was to develop a prototype genotype–phenotype simulation method and software that are capable of simulating complex genetic effects within the context of a hierarchical biology-based framework. Specifically, our goal is to simulate multilocus epistasis or gene–gene interaction where the genetic variants are organized within the framework of one or more genes, their regulatory regions and other regulatory loci. We introduce here the Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (HIBACHI) method and prototype software for simulating data in this manner. This approach combines a biological hierarchy, a flexible mathematical framework, a liability threshold model for defining disease endpoints, and a heuristic search strategy for identifying high-order epistatic models of disease susceptibility. We provide several simulation examples using genetic models exhibiting independent main effects and three-way epistatic effects. PMID:25395175

Proof of Concept for the Trajectory-Level Validation Framework for Traffic Simulation Models

DOT National Transportation Integrated Search

2017-10-30

Based on current practices, traffic simulation models are calibrated and validated using macroscopic measures such as 15-minute averages of traffic counts or average point-to-point travel times. For an emerging number of applications, including conne...

High performance cellular level agent-based simulation with FLAME for the GPU.

PubMed

Richmond, Paul; Walker, Dawn; Coakley, Simon; Romano, Daniela

2010-05-01

Driven by the availability of experimental data and ability to simulate a biological scale which is of immediate interest, the cellular scale is fast emerging as an ideal candidate for middle-out modelling. As with 'bottom-up' simulation approaches, cellular level simulations demand a high degree of computational power, which in large-scale simulations can only be achieved through parallel computing. The flexible large-scale agent modelling environment (FLAME) is a template driven framework for agent-based modelling (ABM) on parallel architectures ideally suited to the simulation of cellular systems. It is available for both high performance computing clusters (www.flame.ac.uk) and GPU hardware (www.flamegpu.com) and uses a formal specification technique that acts as a universal modelling format. This not only creates an abstraction from the underlying hardware architectures, but avoids the steep learning curve associated with programming them. In benchmarking tests and simulations of advanced cellular systems, FLAME GPU has reported massive improvement in performance over more traditional ABM frameworks. This allows the time spent in the development and testing stages of modelling to be drastically reduced and creates the possibility of real-time visualisation for simple visual face-validation.

Patient-Specific Simulation of Cardiac Blood Flow From High-Resolution Computed Tomography.

PubMed

Lantz, Jonas; Henriksson, Lilian; Persson, Anders; Karlsson, Matts; Ebbers, Tino

2016-12-01

Cardiac hemodynamics can be computed from medical imaging data, and results could potentially aid in cardiac diagnosis and treatment optimization. However, simulations are often based on simplified geometries, ignoring features such as papillary muscles and trabeculae due to their complex shape, limitations in image acquisitions, and challenges in computational modeling. This severely hampers the use of computational fluid dynamics in clinical practice. The overall aim of this study was to develop a novel numerical framework that incorporated these geometrical features. The model included the left atrium, ventricle, ascending aorta, and heart valves. The framework used image registration to obtain patient-specific wall motion, automatic remeshing to handle topological changes due to the complex trabeculae motion, and a fast interpolation routine to obtain intermediate meshes during the simulations. Velocity fields and residence time were evaluated, and they indicated that papillary muscles and trabeculae strongly interacted with the blood, which could not be observed in a simplified model. The framework resulted in a model with outstanding geometrical detail, demonstrating the feasibility as well as the importance of a framework that is capable of simulating blood flow in physiologically realistic hearts.

pyBadlands: A framework to simulate sediment transport, landscape dynamics and basin stratigraphic evolution through space and time

PubMed Central

2018-01-01

Understanding Earth surface responses in terms of sediment dynamics to climatic variability and tectonics forcing is hindered by limited ability of current models to simulate long-term evolution of sediment transfer and associated morphological changes. This paper presents pyBadlands, an open-source python-based framework which computes over geological time (1) sediment transport from landmasses to coasts, (2) reworking of marine sediments by longshore currents and (3) development of coral reef systems. pyBadlands is cross-platform, distributed under the GPLv3 license and available on GitHub (http://github.com/badlands-model). Here, we describe the underlying physical assumptions behind the simulated processes and the main options already available in the numerical framework. Along with the source code, a list of hands-on examples is provided that illustrates the model capabilities. In addition, pre and post-processing classes have been built and are accessible as a companion toolbox which comprises a series of workflows to efficiently build, quantify and explore simulation input and output files. While the framework has been primarily designed for research, its simplicity of use and portability makes it a great tool for teaching purposes. PMID:29649301

Application of Psychological Theories in Agent-Based Modeling: The Case of the Theory of Planned Behavior.

PubMed

Scalco, Andrea; Ceschi, Andrea; Sartori, Riccardo

2018-01-01

It is likely that computer simulations will assume a greater role in the next future to investigate and understand reality (Rand & Rust, 2011). Particularly, agent-based models (ABMs) represent a method of investigation of social phenomena that blend the knowledge of social sciences with the advantages of virtual simulations. Within this context, the development of algorithms able to recreate the reasoning engine of autonomous virtual agents represents one of the most fragile aspects and it is indeed crucial to establish such models on well-supported psychological theoretical frameworks. For this reason, the present work discusses the application case of the theory of planned behavior (TPB; Ajzen, 1991) in the context of agent-based modeling: It is argued that this framework might be helpful more than others to develop a valid representation of human behavior in computer simulations. Accordingly, the current contribution considers issues related with the application of the model proposed by the TPB inside computer simulations and suggests potential solutions with the hope to contribute to shorten the distance between the fields of psychology and computer science.

Enhancing 4D PC-MRI in an aortic phantom considering numerical simulations

NASA Astrophysics Data System (ADS)

Kratzke, Jonas; Schoch, Nicolai; Weis, Christian; Müller-Eschner, Matthias; Speidel, Stefanie; Farag, Mina; Beller, Carsten J.; Heuveline, Vincent

2015-03-01

To date, cardiovascular surgery enables the treatment of a wide range of aortic pathologies. One of the current challenges in this field is given by the detection of high-risk patients for adverse aortic events, who should be treated electively. Reliable diagnostic parameters, which indicate the urge of treatment, have to be determined. Functional imaging by means of 4D phase contrast-magnetic resonance imaging (PC-MRI) enables the time-resolved measurement of blood flow velocity in 3D. Applied to aortic phantoms, three dimensional blood flow properties and their relation to adverse dynamics can be investigated in vitro. Emerging "in silico" methods of numerical simulation can supplement these measurements in computing additional information on crucial parameters. We propose a framework that complements 4D PC-MRI imaging by means of numerical simulation based on the Finite Element Method (FEM). The framework is developed on the basis of a prototypic aortic phantom and validated by 4D PC-MRI measurements of the phantom. Based on physical principles of biomechanics, the derived simulation depicts aortic blood flow properties and characteristics. The framework might help identifying factors that induce aortic pathologies such as aortic dilatation or aortic dissection. Alarming thresholds of parameters such as wall shear stress distribution can be evaluated. The combined techniques of 4D PC-MRI and numerical simulation can be used as complementary tools for risk-stratification of aortic pathology.

The Application of SNiPER to the JUNO Simulation

NASA Astrophysics Data System (ADS)

Lin, Tao; Zou, Jiaheng; Li, Weidong; Deng, Ziyan; Fang, Xiao; Cao, Guofu; Huang, Xingtao; You, Zhengyun; JUNO Collaboration

2017-10-01

The JUNO (Jiangmen Underground Neutrino Observatory) is a multipurpose neutrino experiment which is designed to determine neutrino mass hierarchy and precisely measure oscillation parameters. As one of the important systems, the JUNO offline software is being developed using the SNiPER software. In this proceeding, we focus on the requirements of JUNO simulation and present the working solution based on the SNiPER. The JUNO simulation framework is in charge of managing event data, detector geometries and materials, physics processes, simulation truth information etc. It glues physics generator, detector simulation and electronics simulation modules together to achieve a full simulation chain. In the implementation of the framework, many attractive characteristics of the SNiPER have been used, such as dynamic loading, flexible flow control, multiple event management and Python binding. Furthermore, additional efforts have been made to make both detector and electronics simulation flexible enough to accommodate and optimize different detector designs. For the Geant4-based detector simulation, each sub-detector component is implemented as a SNiPER tool which is a dynamically loadable and configurable plugin. So it is possible to select the detector configuration at runtime. The framework provides the event loop to drive the detector simulation and interacts with the Geant4 which is implemented as a passive service. All levels of user actions are wrapped into different customizable tools, so that user functions can be easily extended by just adding new tools. The electronics simulation has been implemented by following an event driven scheme. The SNiPER task component is used to simulate data processing steps in the electronics modules. The electronics and trigger are synchronized by triggered events containing possible physics signals. The JUNO simulation software has been released and is being used by the JUNO collaboration to do detector design optimization, event reconstruction algorithm development and physics sensitivity studies.

Methodology development for evaluation of selective-fidelity rotorcraft simulation

NASA Technical Reports Server (NTRS)

Lewis, William D.; Schrage, D. P.; Prasad, J. V. R.; Wolfe, Daniel

1992-01-01

This paper addressed the initial step toward the goal of establishing performance and handling qualities acceptance criteria for realtime rotorcraft simulators through a planned research effort to quantify the system capabilities of 'selective fidelity' simulators. Within this framework the simulator is then classified based on the required task. The simulator is evaluated by separating the various subsystems (visual, motion, etc.) and applying corresponding fidelity constants based on the specific task. This methodology not only provides an assessment technique, but also provides a technique to determine the required levels of subsystem fidelity for a specific task.

Approaches to incorporating climate change effects in state and transition simulation models of vegetation

Treesearch

Becky K. Kerns; Miles A. Hemstrom; David Conklin; Gabriel I. Yospin; Bart Johnson; Dominique Bachelet; Scott Bridgham

2012-01-01

Understanding landscape vegetation dynamics often involves the use of scientifically-based modeling tools that are capable of testing alternative management scenarios given complex ecological, management, and social conditions. State-and-transition simulation model (STSM) frameworks and software such as PATH and VDDT are commonly used tools that simulate how landscapes...

Design Patterns for Learning and Assessment: Facilitating the Introduction of a Complex Simulation-Based Learning Environment into a Community of Instructors

NASA Astrophysics Data System (ADS)

Frezzo, Dennis C.; Behrens, John T.; Mislevy, Robert J.

2010-04-01

Simulation environments make it possible for science and engineering students to learn to interact with complex systems. Putting these capabilities to effective use for learning, and assessing learning, requires more than a simulation environment alone. It requires a conceptual framework for the knowledge, skills, and ways of thinking that are meant to be developed, in order to design activities that target these capabilities. The challenges of using simulation environments effectively are especially daunting in dispersed social systems. This article describes how these challenges were addressed in the context of the Cisco Networking Academies with a simulation tool for computer networks called Packet Tracer. The focus is on a conceptual support framework for instructors in over 9,000 institutions around the world for using Packet Tracer in instruction and assessment, by learning to create problem-solving scenarios that are at once tuned to the local needs of their students and consistent with the epistemic frame of "thinking like a network engineer." We describe a layered framework of tools and interfaces above the network simulator that supports the use of Packet Tracer in the distributed community of instructors and students.

Using connectivity to identify climatic drivers of local adaptation: a response to Macdonald et al.

PubMed

Prunier, Jérôme G; Blanchet, Simon

2018-04-30

Macdonald et al. (Ecol. Lett., 21, 2018, 207-216) proposed an analytical framework for identifying evolutionary processes underlying trait-environment relationships observed in natural populations. Here, we propose an expanded and refined framework based on simulations and bootstrap-based approaches, and we elaborate on an important statistical caveat common to most datasets. © 2018 John Wiley & Sons Ltd/CNRS.

A novel medical image data-based multi-physics simulation platform for computational life sciences.

PubMed

Neufeld, Esra; Szczerba, Dominik; Chavannes, Nicolas; Kuster, Niels

2013-04-06

Simulating and modelling complex biological systems in computational life sciences requires specialized software tools that can perform medical image data-based modelling, jointly visualize the data and computational results, and handle large, complex, realistic and often noisy anatomical models. The required novel solvers must provide the power to model the physics, biology and physiology of living tissue within the full complexity of the human anatomy (e.g. neuronal activity, perfusion and ultrasound propagation). A multi-physics simulation platform satisfying these requirements has been developed for applications including device development and optimization, safety assessment, basic research, and treatment planning. This simulation platform consists of detailed, parametrized anatomical models, a segmentation and meshing tool, a wide range of solvers and optimizers, a framework for the rapid development of specialized and parallelized finite element method solvers, a visualization toolkit-based visualization engine, a Python scripting interface for customized applications, a coupling framework, and more. Core components are cross-platform compatible and use open formats. Several examples of applications are presented: hyperthermia cancer treatment planning, tumour growth modelling, evaluating the magneto-haemodynamic effect as a biomarker and physics-based morphing of anatomical models.

Opportunities and Challenges in Supply-Side Simulation: Physician-Based Models

PubMed Central

Gresenz, Carole Roan; Auerbach, David I; Duarte, Fabian

2013-01-01

Objective To provide a conceptual framework and to assess the availability of empirical data for supply-side microsimulation modeling in the context of health care. Data Sources Multiple secondary data sources, including the American Community Survey, Health Tracking Physician Survey, and SK&A physician database. Study Design We apply our conceptual framework to one entity in the health care market—physicians—and identify, assess, and compare data available for physician-based simulation models. Principal Findings Our conceptual framework describes three broad types of data required for supply-side microsimulation modeling. Our assessment of available data for modeling physician behavior suggests broad comparability across various sources on several dimensions and highlights the need for significant integration of data across multiple sources to provide a platform adequate for modeling. A growing literature provides potential estimates for use as behavioral parameters that could serve as the models' engines. Sources of data for simulation modeling that account for the complex organizational and financial relationships among physicians and other supply-side entities are limited. Conclusions A key challenge for supply-side microsimulation modeling is optimally combining available data to harness their collective power. Several possibilities also exist for novel data collection. These have the potential to serve as catalysts for the next generation of supply-side-focused simulation models to inform health policy. PMID:23347041

Development of a Dynamically Configurable,Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation

NASA Technical Reports Server (NTRS)

Afjeh, Abdollah A.; Reed, John A.

2003-01-01

This research is aimed at developing a neiv and advanced simulation framework that will significantly improve the overall efficiency of aerospace systems design and development. This objective will be accomplished through an innovative integration of object-oriented and Web-based technologies ivith both new and proven simulation methodologies. The basic approach involves Ihree major areas of research: Aerospace system and component representation using a hierarchical object-oriented component model which enables the use of multimodels and enforces component interoperability. Collaborative software environment that streamlines the process of developing, sharing and integrating aerospace design and analysis models. . Development of a distributed infrastructure which enables Web-based exchange of models to simplify the collaborative design process, and to support computationally intensive aerospace design and analysis processes. Research for the first year dealt with the design of the basic architecture and supporting infrastructure, an initial implementation of that design, and a demonstration of its application to an example aircraft engine system simulation.

IGMS: An Integrated ISO-to-Appliance Scale Grid Modeling System

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

Palmintier, Bryan; Hale, Elaine; Hansen, Timothy M.

This paper describes the Integrated Grid Modeling System (IGMS), a novel electric power system modeling platform for integrated transmission-distribution analysis that co-simulates off-the-shelf tools on high performance computing (HPC) platforms to offer unprecedented resolution from ISO markets down to appliances and other end uses. Specifically, the system simultaneously models hundreds or thousands of distribution systems in co-simulation with detailed Independent System Operator (ISO) markets and AGC-level reserve deployment. IGMS uses a new MPI-based hierarchical co-simulation framework to connect existing sub-domain models. Our initial efforts integrate opensource tools for wholesale markets (FESTIV), bulk AC power flow (MATPOWER), and full-featured distribution systemsmore » including physics-based end-use and distributed generation models (many instances of GridLAB-D[TM]). The modular IGMS framework enables tool substitution and additions for multi-domain analyses. This paper describes the IGMS tool, characterizes its performance, and demonstrates the impacts of the coupled simulations for analyzing high-penetration solar PV and price responsive load scenarios.« less

Development of solute transport models in YMPYRÄ framework to simulate solute migration in military shooting and training areas

NASA Astrophysics Data System (ADS)

Warsta, L.; Karvonen, T.

2017-12-01

There are currently 25 shooting and training areas in Finland managed by The Finnish Defence Forces (FDF), where military activities can cause contamination of open waters and groundwater reservoirs. In the YMPYRÄ project, a computer software framework is being developed that combines existing open environmental data and proprietary information collected by FDF with computational models to investigate current and prevent future environmental problems. A data centric philosophy is followed in the development of the system, i.e. the models are updated and extended to handle available data from different areas. The results generated by the models are summarized as easily understandable flow and risk maps that can be opened in GIS programs and used in environmental assessments by experts. Substances investigated with the system include explosives and metals such as lead, and both surface and groundwater dominated areas can be simulated. The YMPYRÄ framework is composed of a three dimensional soil and groundwater flow model, several solute transport models and an uncertainty assessment system. Solute transport models in the framework include particle based, stream tube and finite volume based approaches. The models can be used to simulate solute dissolution from source area, transport in the unsaturated layers to groundwater and finally migration in groundwater to water extraction wells and springs. The models can be used to simulate advection, dispersion, equilibrium adsorption on soil particles, solubility and dissolution from solute phase and dendritic solute decay chains. Correct numerical solutions were confirmed by comparing results to analytical 1D and 2D solutions and by comparing the numerical solutions to each other. The particle based and stream tube type solute transport models were useful as they could complement the traditional finite volume based approach which in certain circumstances produced numerical dispersion due to piecewise solution of the governing equations in computational grids and included computationally intensive and in some cases unstable iterative solutions. The YMPYRÄ framework is being developed by WaterHope, Gain Oy, and SITO Oy consulting companies and funded by FDF.

Multi-sources data fusion framework for remote triage prioritization in telehealth.

PubMed

Salman, O H; Rasid, M F A; Saripan, M I; Subramaniam, S K

2014-09-01

The healthcare industry is streamlining processes to offer more timely and effective services to all patients. Computerized software algorithm and smart devices can streamline the relation between users and doctors by providing more services inside the healthcare telemonitoring systems. This paper proposes a multi-sources framework to support advanced healthcare applications. The proposed framework named Multi Sources Healthcare Architecture (MSHA) considers multi-sources: sensors (ECG, SpO2 and Blood Pressure) and text-based inputs from wireless and pervasive devices of Wireless Body Area Network. The proposed framework is used to improve the healthcare scalability efficiency by enhancing the remote triaging and remote prioritization processes for the patients. The proposed framework is also used to provide intelligent services over telemonitoring healthcare services systems by using data fusion method and prioritization technique. As telemonitoring system consists of three tiers (Sensors/ sources, Base station and Server), the simulation of the MSHA algorithm in the base station is demonstrated in this paper. The achievement of a high level of accuracy in the prioritization and triaging patients remotely, is set to be our main goal. Meanwhile, the role of multi sources data fusion in the telemonitoring healthcare services systems has been demonstrated. In addition to that, we discuss how the proposed framework can be applied in a healthcare telemonitoring scenario. Simulation results, for different symptoms relate to different emergency levels of heart chronic diseases, demonstrate the superiority of our algorithm compared with conventional algorithms in terms of classify and prioritize the patients remotely.

Cybersecurity Protection: Design Science Research toward an Intercloud Transparent Bridge Architecture (ITCOBRA)

ERIC Educational Resources Information Center

Wilson, Joe M.

2013-01-01

This dissertation uses design science research and engineering to develop a cloud-based simulator for modeling next-generation cybersecurity protection frameworks in the United States. The claim is made that an agile and neutral framework extending throughout the cyber-threat plane is needed for critical infrastructure protection (CIP). This…

A surrogate-based sensitivity quantification and Bayesian inversion of a regional groundwater flow model

NASA Astrophysics Data System (ADS)

Chen, Mingjie; Izady, Azizallah; Abdalla, Osman A.; Amerjeed, Mansoor

2018-02-01

Bayesian inference using Markov Chain Monte Carlo (MCMC) provides an explicit framework for stochastic calibration of hydrogeologic models accounting for uncertainties; however, the MCMC sampling entails a large number of model calls, and could easily become computationally unwieldy if the high-fidelity hydrogeologic model simulation is time consuming. This study proposes a surrogate-based Bayesian framework to address this notorious issue, and illustrates the methodology by inverse modeling a regional MODFLOW model. The high-fidelity groundwater model is approximated by a fast statistical model using Bagging Multivariate Adaptive Regression Spline (BMARS) algorithm, and hence the MCMC sampling can be efficiently performed. In this study, the MODFLOW model is developed to simulate the groundwater flow in an arid region of Oman consisting of mountain-coast aquifers, and used to run representative simulations to generate training dataset for BMARS model construction. A BMARS-based Sobol' method is also employed to efficiently calculate input parameter sensitivities, which are used to evaluate and rank their importance for the groundwater flow model system. According to sensitivity analysis, insensitive parameters are screened out of Bayesian inversion of the MODFLOW model, further saving computing efforts. The posterior probability distribution of input parameters is efficiently inferred from the prescribed prior distribution using observed head data, demonstrating that the presented BMARS-based Bayesian framework is an efficient tool to reduce parameter uncertainties of a groundwater system.

A multi-fidelity framework for physics based rotor blade simulation and optimization

NASA Astrophysics Data System (ADS)

Collins, Kyle Brian

New helicopter rotor designs are desired that offer increased efficiency, reduced vibration, and reduced noise. Rotor Designers in industry need methods that allow them to use the most accurate simulation tools available to search for these optimal designs. Computer based rotor analysis and optimization have been advanced by the development of industry standard codes known as "comprehensive" rotorcraft analysis tools. These tools typically use table look-up aerodynamics, simplified inflow models and perform aeroelastic analysis using Computational Structural Dynamics (CSD). Due to the simplified aerodynamics, most design studies are performed varying structural related design variables like sectional mass and stiffness. The optimization of shape related variables in forward flight using these tools is complicated and results are viewed with skepticism because rotor blade loads are not accurately predicted. The most accurate methods of rotor simulation utilize Computational Fluid Dynamics (CFD) but have historically been considered too computationally intensive to be used in computer based optimization, where numerous simulations are required. An approach is needed where high fidelity CFD rotor analysis can be utilized in a shape variable optimization problem with multiple objectives. Any approach should be capable of working in forward flight in addition to hover. An alternative is proposed and founded on the idea that efficient hybrid CFD methods of rotor analysis are ready to be used in preliminary design. In addition, the proposed approach recognizes the usefulness of lower fidelity physics based analysis and surrogate modeling. Together, they are used with high fidelity analysis in an intelligent process of surrogate model building of parameters in the high fidelity domain. Closing the loop between high and low fidelity analysis is a key aspect of the proposed approach. This is done by using information from higher fidelity analysis to improve predictions made with lower fidelity models. This thesis documents the development of automated low and high fidelity physics based rotor simulation frameworks. The low fidelity framework uses a comprehensive code with simplified aerodynamics. The high fidelity model uses a parallel processor capable CFD/CSD methodology. Both low and high fidelity frameworks include an aeroacoustic simulation for prediction of noise. A synergistic process is developed that uses both the low and high fidelity frameworks together to build approximate models of important high fidelity metrics as functions of certain design variables. To test the process, a 4-bladed hingeless rotor model is used as a baseline. The design variables investigated include tip geometry and spanwise twist distribution. Approximation models are built for metrics related to rotor efficiency and vibration using the results from 60+ high fidelity (CFD/CSD) experiments and 400+ low fidelity experiments. Optimization using the approximation models found the Pareto Frontier anchor points, or the design having maximum rotor efficiency and the design having minimum vibration. Various Pareto generation methods are used to find designs on the frontier between these two anchor designs. When tested in the high fidelity framework, the Pareto anchor designs are shown to be very good designs when compared with other designs from the high fidelity database. This provides evidence that the process proposed has merit. Ultimately, this process can be utilized by industry rotor designers with their existing tools to bring high fidelity analysis into the preliminary design stage of rotors. In conclusion, the methods developed and documented in this thesis have made several novel contributions. First, an automated high fidelity CFD based forward flight simulation framework has been built for use in preliminary design optimization. The framework was built around an integrated, parallel processor capable CFD/CSD/AA process. Second, a novel method of building approximate models of high fidelity parameters has been developed. The method uses a combination of low and high fidelity results and combines Design of Experiments, statistical effects analysis, and aspects of approximation model management. And third, the determination of rotor blade shape variables through optimization using CFD based analysis in forward flight has been performed. This was done using the high fidelity CFD/CSD/AA framework and method mentioned above. While the low and high fidelity predictions methods used in the work still have inaccuracies that can affect the absolute levels of the results, a framework has been successfully developed and demonstrated that allows for an efficient process to improve rotor blade designs in terms of a selected choice of objective function(s). Using engineering judgment, this methodology could be applied today to investigate opportunities to improve existing designs. With improvements in the low and high fidelity prediction components that will certainly occur, this framework could become a powerful tool for future rotorcraft design work. (Abstract shortened by UMI.)

Old Dog New Tricks: Use of Point-based Crop Models in Grid-based Regional Assessment of Crop Management Technologies Impact on Future Food Security

NASA Astrophysics Data System (ADS)

Koo, J.; Wood, S.; Cenacchi, N.; Fisher, M.; Cox, C.

2012-12-01

HarvestChoice (harvestchoice.org) generates knowledge products to guide strategic investments to improve the productivity and profitability of smallholder farming systems in sub-Saharan Africa (SSA). A keynote component of the HarvestChoice analytical framework is a grid-based overlay of SSA - a cropping simulation platform powered by process-based, crop models. Calibrated around the best available representation of cropping production systems in SSA, the simulation platform engages the DSSAT Crop Systems Model with the CENTURY Soil Organic Matter model (DSSAT-CENTURY) and provides a virtual experimentation module with which to explore the impact of a range of technological, managerial and environmental metrics on future crop productivity and profitability, as well as input use. For each of 5 (or 30) arc-minute grid cells in SSA, a stack of model input underlies it: datasets that cover soil properties and fertility, historic and future climate scenarios and farmers' management practices; all compiled from analyses of existing global and regional databases and consultations with other CGIAR centers. Running a simulation model is not always straightforward, especially when certain cropping systems or management practices are not even practiced by resource-poor farmers yet (e.g., precision agriculture) or they were never included in the existing simulation framework (e.g., water harvesting). In such cases, we used DSSAT-CENTURY as a function to iteratively estimate relative responses of cropping systems to technology-driven changes in water and nutrient balances compared to zero-adoption by farmers, while adjusting model input parameters to best mimic farmers' implementation of technologies in the field. We then fed the results of the simulation into to the economic and food trade model framework, IMPACT, to assess the potential implications on future food security. The outputs of the overall simulation analyses are packaged as a web-accessible database and published on the web with an interface that allows users to explore the simulation results in each country with user-defined baseline and what-if scenarios. The results are dynamically presented on maps, charts, and tables. This paper discusses the development of the simulation platform and its underlying data layers, a case study that assessed the role of potential crop management technology development, and the development of a web-based application that visualizes the simulation results.

An Overview of Atmospheric Composition OSSE Activities at NASA's Global Modeling and Assimilation Office

NASA Technical Reports Server (NTRS)

daSilva, Arlinda

2012-01-01

A model-based Observing System Simulation Experiment (OSSE) is a framework for numerical experimentation in which observables are simulated from fields generated by an earth system model, including a parameterized description of observational error characteristics. Simulated observations can be used for sampling studies, quantifying errors in analysis or retrieval algorithms, and ultimately being a planning tool for designing new observing missions. While this framework has traditionally been used to assess the impact of observations on numerical weather prediction, it has a much broader applicability, in particular to aerosols and chemical constituents. In this talk we will give a general overview of Observing System Simulation Experiments (OSSE) activities at NASA's Global Modeling and Assimilation Office, with focus on its emerging atmospheric composition component.

Dual-Function Metal-Organic Framework as a Versatile Catalyst for Detoxifying Chemical Warfare Agent Simulants.

PubMed

Liu, Yangyang; Moon, Su-Young; Hupp, Joseph T; Farha, Omar K

2015-12-22

The nanocrystals of a porphyrin-based zirconium(IV) metal-organic framework (MOF) are used as a dual-function catalyst for the simultaneous detoxification of two chemical warfare agent simulants at room temperature. Simulants of nerve agent (such as GD, VX) and mustard gas, dimethyl 4-nitrophenyl phosphate and 2-chloroethyl ethyl sulfide, have been hydrolyzed and oxidized, respectively, to nontoxic products via a pair of pathways catalyzed by the same MOF. Phosphotriesterase-like activity of the Zr6-containing node combined with photoactivity of the porphyrin linker gives rise to a versatile MOF catalyst. In addition, bringing the MOF crystals down to the nanoregime leads to acceleration of the catalysis.

SCALING AN URBAN EMERGENCY EVACUATION FRAMEWORK: CHALLENGES AND PRACTICES

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

Karthik, Rajasekar; Lu, Wei

2014-01-01

Critical infrastructure disruption, caused by severe weather events, natural disasters, terrorist attacks, etc., has significant impacts on urban transportation systems. We built a computational framework to simulate urban transportation systems under critical infrastructure disruption in order to aid real-time emergency evacuation. This framework will use large scale datasets to provide a scalable tool for emergency planning and management. Our framework, World-Wide Emergency Evacuation (WWEE), integrates population distribution and urban infrastructure networks to model travel demand in emergency situations at global level. Also, a computational model of agent-based traffic simulation is used to provide an optimal evacuation plan for traffic operationmore » purpose [1]. In addition, our framework provides a web-based high resolution visualization tool for emergency evacuation modelers and practitioners. We have successfully tested our framework with scenarios in both United States (Alexandria, VA) and Europe (Berlin, Germany) [2]. However, there are still some major drawbacks for scaling this framework to handle big data workloads in real time. On our back-end, lack of proper infrastructure limits us in ability to process large amounts of data, run the simulation efficiently and quickly, and provide fast retrieval and serving of data. On the front-end, the visualization performance of microscopic evacuation results is still not efficient enough due to high volume data communication between server and client. We are addressing these drawbacks by using cloud computing and next-generation web technologies, namely Node.js, NoSQL, WebGL, Open Layers 3 and HTML5 technologies. We will describe briefly about each one and how we are using and leveraging these technologies to provide an efficient tool for emergency management organizations. Our early experimentation demonstrates that using above technologies is a promising approach to build a scalable and high performance urban emergency evacuation framework that can improve traffic mobility and safety under critical infrastructure disruption in today s socially connected world.« less

War-gaming application for future space systems acquisition: MATLAB implementation of war-gaming acquisition models and simulation results

NASA Astrophysics Data System (ADS)

Vienhage, Paul; Barcomb, Heather; Marshall, Karel; Black, William A.; Coons, Amanda; Tran, Hien T.; Nguyen, Tien M.; Guillen, Andy T.; Yoh, James; Kizer, Justin; Rogers, Blake A.

2017-05-01

The paper describes the MATLAB (MathWorks) programs that were developed during the REU workshop1 to implement The Aerospace Corporation developed Unified Game-based Acquisition Framework and Advanced Game - based Mathematical Framework (UGAF-AGMF) and its associated War-Gaming Engine (WGE) models. Each game can be played from the perspectives of the Department of Defense Acquisition Authority (DAA) or of an individual contractor (KTR). The programs also implement Aerospace's optimum "Program and Technical Baseline (PTB) and associated acquisition" strategy that combines low Total Ownership Cost (TOC) with innovative designs while still meeting warfighter needs. The paper also describes the Bayesian Acquisition War-Gaming approach using Monte Carlo simulations, a numerical analysis technique to account for uncertainty in decision making, which simulate the PTB development and acquisition processes and will detail the procedure of the implementation and the interactions between the games.

PM2.5 Population Exposure in New Delhi Using a Probabilistic Simulation Framework.

PubMed

Saraswat, Arvind; Kandlikar, Milind; Brauer, Michael; Srivastava, Arun

2016-03-15

This paper presents a Geographical Information System (GIS) based probabilistic simulation framework to estimate PM2.5 population exposure in New Delhi, India. The framework integrates PM2.5 output from spatiotemporal LUR models and trip distribution data using a Gravity model based on zonal data for population, employment and enrollment in educational institutions. Time-activity patterns were derived from a survey of randomly sampled individuals (n = 1012) and in-vehicle exposure was estimated using microenvironmental monitoring data based on field measurements. We simulated population exposure for three different scenarios to capture stay-at-home populations (Scenario 1), working population exposed to near-road concentrations during commutes (Scenario 2), and the working population exposed to on-road concentrations during commutes (Scenario 3). Simulated annual average levels of PM2.5 exposure across the entire city were very high, and particularly severe in the winter months: ∼200 μg m(-3) in November, roughly four times higher compared to the lower levels in the monsoon season. Mean annual exposures ranged from 109 μg m(-3) (IQR: 97-120 μg m(-3)) for Scenario 1, to 121 μg m(-3) (IQR: 110-131 μg m(-3)), and 125 μg m(-3) (IQR: 114-136 μ gm(-3)) for Scenarios 2 and 3 respectively. Ignoring the effects of mobility causes the average annual PM2.5 population exposure to be underestimated by only 11%.

Design Patterns for Learning and Assessment: Facilitating the Introduction of a Complex Simulation-Based Learning Environment into a Community of Instructors

ERIC Educational Resources Information Center

Frezzo, Dennis C.; Behrens, John T.; Mislevy, Robert J.

2010-01-01

Simulation environments make it possible for science and engineering students to learn to interact with complex systems. Putting these capabilities to effective use for learning, and assessing learning, requires more than a simulation environment alone. It requires a conceptual framework for the knowledge, skills, and ways of thinking that are…

Monitoring and modeling as a continuing learning process: the use of hydrological models in a general probabilistic framework.

NASA Astrophysics Data System (ADS)

Baroni, G.; Gräff, T.; Reinstorf, F.; Oswald, S. E.

2012-04-01

Nowadays uncertainty and sensitivity analysis are considered basic tools for the assessment of hydrological models and the evaluation of the most important sources of uncertainty. In this context, in the last decades several methods have been developed and applied in different hydrological conditions. However, in most of the cases, the studies have been done by investigating mainly the influence of the parameter uncertainty on the simulated outputs and few approaches tried to consider also other sources of uncertainty i.e. input and model structure. Moreover, several constrains arise when spatially distributed parameters are involved. To overcome these limitations a general probabilistic framework based on Monte Carlo simulations and the Sobol method has been proposed. In this study, the general probabilistic framework was applied at field scale using a 1D physical-based hydrological model (SWAP). Furthermore, the framework was extended at catchment scale in combination with a spatially distributed hydrological model (SHETRAN). The models are applied in two different experimental sites in Germany: a relatively flat cropped field close to Potsdam (Brandenburg) and a small mountainous catchment with agricultural land use (Schaefertal, Harz Mountains). For both cases, input and parameters are considered as major sources of uncertainty. Evaluation of the models was based on soil moisture detected at plot scale in different depths and, for the catchment site, also with daily discharge values. The study shows how the framework can take into account all the various sources of uncertainty i.e. input data, parameters (either in scalar or spatially distributed form) and model structures. The framework can be used in a loop in order to optimize further monitoring activities used to improve the performance of the model. In the particular applications, the results show how the sources of uncertainty are specific for each process considered. The influence of the input data as well as the presence of compensating errors become clear by the different processes simulated.

The Umbra Simulation and Integration Framework Applied to Emergency Response Training

NASA Technical Reports Server (NTRS)

Hamilton, Paul Lawrence; Britain, Robert

2010-01-01

The Mine Emergency Response Interactive Training Simulation (MERITS) is intended to prepare personnel to manage an emergency in an underground coal mine. The creation of an effective training environment required realistic emergent behavior in response to simulation events and trainee interventions, exploratory modification of miner behavior rules, realistic physics, and incorporation of legacy code. It also required the ability to add rich media to the simulation without conflicting with normal desktop security settings. Our Umbra Simulation and Integration Framework facilitated agent-based modeling of miners and rescuers and made it possible to work with subject matter experts to quickly adjust behavior through script editing, rather than through lengthy programming and recompilation. Integration of Umbra code with the WebKit browser engine allowed the use of JavaScript-enabled local web pages for media support. This project greatly extended the capabilities of Umbra in support of training simulations and has implications for simulations that combine human behavior, physics, and rich media.

syris: a flexible and efficient framework for X-ray imaging experiments simulation.

PubMed

Faragó, Tomáš; Mikulík, Petr; Ershov, Alexey; Vogelgesang, Matthias; Hänschke, Daniel; Baumbach, Tilo

2017-11-01

An open-source framework for conducting a broad range of virtual X-ray imaging experiments, syris, is presented. The simulated wavefield created by a source propagates through an arbitrary number of objects until it reaches a detector. The objects in the light path and the source are time-dependent, which enables simulations of dynamic experiments, e.g. four-dimensional time-resolved tomography and laminography. The high-level interface of syris is written in Python and its modularity makes the framework very flexible. The computationally demanding parts behind this interface are implemented in OpenCL, which enables fast calculations on modern graphics processing units. The combination of flexibility and speed opens new possibilities for studying novel imaging methods and systematic search of optimal combinations of measurement conditions and data processing parameters. This can help to increase the success rates and efficiency of valuable synchrotron beam time. To demonstrate the capabilities of the framework, various experiments have been simulated and compared with real data. To show the use case of measurement and data processing parameter optimization based on simulation, a virtual counterpart of a high-speed radiography experiment was created and the simulated data were used to select a suitable motion estimation algorithm; one of its parameters was optimized in order to achieve the best motion estimation accuracy when applied on the real data. syris was also used to simulate tomographic data sets under various imaging conditions which impact the tomographic reconstruction accuracy, and it is shown how the accuracy may guide the selection of imaging conditions for particular use cases.

In Situ Probes of Capture and Decomposition of Chemical Warfare Agent Simulants by Zr-Based Metal Organic Frameworks

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

Plonka, Anna M.; Wang, Qi; Gordon, Wesley O.

Recently, Zr-based metal organic frameworks (MOFs) were shown to be among the fastest catalysts of nerve-agent hydrolysis in solution. Here, we report a detailed study of the adsorption and decomposition of a nerve-agent simulant, dimethyl methylphosphonate (DMMP), on UiO-66, UiO-67, MOF-808, and NU-1000 using synchrotron-based X-ray powder diffraction, X-ray absorption, and infrared spectroscopy, which reveals key aspects of the reaction mechanism. The diffraction measurements indicate that all four MOFs adsorb DMMP (introduced at atmospheric pressures through a flow of helium or air) within the pore space. In addition, the combination of X-ray absorption and infrared spectra suggests direct coordination ofmore » DMMP to the Zr6 cores of all MOFs, which ultimately leads to decomposition to phosphonate products. Our experimental probes into the mechanism of adsorption and decomposition of chemical warfare agent simulants on Zr-based MOFs open new opportunities in rational design of new and superior decontamination materials.« less

In Situ Probes of Capture and Decomposition of Chemical Warfare Agent Simulants by Zr-Based Metal Organic Frameworks

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

Plonka, Anna M.; Wang, Qi; Gordon, Wesley O.

Zr-based metal organic frameworks (MOFs) have been recently shown to be among the fastest catalysts of nerve-agent hydrolysis in solution. We report a detailed study of the adsorption and decomposition of a nerve-agent simulant, dimethyl methylphosphonate (DMMP), on UiO-66, UiO-67, MOF-808, and NU-1000 using synchrotron-based X-ray powder diffraction, X-ray absorption, and infrared spectroscopy, which reveals key aspects of the reaction mechanism. The diffraction measurements indicate that all four MOFs adsorb DMMP (introduced at atmospheric pressures through a flow of helium or air) within the pore space. In addition, the combination of X-ray absorption and infrared spectra suggests direct coordination ofmore » DMMP to the Zr6 cores of all MOFs, which ultimately leads to decomposition to phosphonate products. These experimental probes into the mechanism of adsorption and decomposition of chemical warfare agent simulants on Zr-based MOFs open new opportunities in rational design of new and superior decontamination materials.« less

In Situ Probes of Capture and Decomposition of Chemical Warfare Agent Simulants by Zr-Based Metal Organic Frameworks

DOE PAGES

Plonka, Anna M.; Wang, Qi; Gordon, Wesley O.; ...

2016-12-30

Recently, Zr-based metal organic frameworks (MOFs) were shown to be among the fastest catalysts of nerve-agent hydrolysis in solution. Here, we report a detailed study of the adsorption and decomposition of a nerve-agent simulant, dimethyl methylphosphonate (DMMP), on UiO-66, UiO-67, MOF-808, and NU-1000 using synchrotron-based X-ray powder diffraction, X-ray absorption, and infrared spectroscopy, which reveals key aspects of the reaction mechanism. The diffraction measurements indicate that all four MOFs adsorb DMMP (introduced at atmospheric pressures through a flow of helium or air) within the pore space. In addition, the combination of X-ray absorption and infrared spectra suggests direct coordination ofmore » DMMP to the Zr6 cores of all MOFs, which ultimately leads to decomposition to phosphonate products. Our experimental probes into the mechanism of adsorption and decomposition of chemical warfare agent simulants on Zr-based MOFs open new opportunities in rational design of new and superior decontamination materials.« less

A Cloud-Based Simulation Architecture for Pandemic Influenza Simulation

PubMed Central

Eriksson, Henrik; Raciti, Massimiliano; Basile, Maurizio; Cunsolo, Alessandro; Fröberg, Anders; Leifler, Ola; Ekberg, Joakim; Timpka, Toomas

2011-01-01

High-fidelity simulations of pandemic outbreaks are resource consuming. Cluster-based solutions have been suggested for executing such complex computations. We present a cloud-based simulation architecture that utilizes computing resources both locally available and dynamically rented online. The approach uses the Condor framework for job distribution and management of the Amazon Elastic Computing Cloud (EC2) as well as local resources. The architecture has a web-based user interface that allows users to monitor and control simulation execution. In a benchmark test, the best cost-adjusted performance was recorded for the EC2 H-CPU Medium instance, while a field trial showed that the job configuration had significant influence on the execution time and that the network capacity of the master node could become a bottleneck. We conclude that it is possible to develop a scalable simulation environment that uses cloud-based solutions, while providing an easy-to-use graphical user interface. PMID:22195089

Optimal Wastewater Loading under Conflicting Goals and Technology Limitations in a Riverine System.

PubMed

Rafiee, Mojtaba; Lyon, Steve W; Zahraie, Banafsheh; Destouni, Georgia; Jaafarzadeh, Nemat

2017-03-01

  This paper investigates a novel simulation-optimization (S-O) framework for identifying optimal treatment levels and treatment processes for multiple wastewater dischargers to rivers. A commonly used water quality simulation model, Qual2K, was linked to a Genetic Algorithm optimization model for exploration of relevant fuzzy objective-function formulations for addressing imprecision and conflicting goals of pollution control agencies and various dischargers. Results showed a dynamic flow dependence of optimal wastewater loading with good convergence to near global optimum. Explicit considerations of real-world technological limitations, which were developed here in a new S-O framework, led to better compromise solutions between conflicting goals than those identified within traditional S-O frameworks. The newly developed framework, in addition to being more technologically realistic, is also less complicated and converges on solutions more rapidly than traditional frameworks. This technique marks a significant step forward for development of holistic, riverscape-based approaches that balance the conflicting needs of the stakeholders.

Open-source framework for power system transmission and distribution dynamics co-simulation

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

Huang, Renke; Fan, Rui; Daily, Jeff

The promise of the smart grid entails more interactions between the transmission and distribution networks, and there is an immediate need for tools to provide the comprehensive modelling and simulation required to integrate operations at both transmission and distribution levels. Existing electromagnetic transient simulators can perform simulations with integration of transmission and distribution systems, but the computational burden is high for large-scale system analysis. For transient stability analysis, currently there are only separate tools for simulating transient dynamics of the transmission and distribution systems. In this paper, we introduce an open source co-simulation framework “Framework for Network Co-Simulation” (FNCS), togethermore » with the decoupled simulation approach that links existing transmission and distribution dynamic simulators through FNCS. FNCS is a middleware interface and framework that manages the interaction and synchronization of the transmission and distribution simulators. Preliminary testing results show the validity and capability of the proposed open-source co-simulation framework and the decoupled co-simulation methodology.« less

Pika: A snow science simulation tool built using the open-source framework MOOSE

NASA Astrophysics Data System (ADS)

Slaughter, A.; Johnson, M.

2017-12-01

The Department of Energy (DOE) is currently investing millions of dollars annually into various modeling and simulation tools for all aspects of nuclear energy. An important part of this effort includes developing applications based on the open-source Multiphysics Object Oriented Simulation Environment (MOOSE; mooseframework.org) from Idaho National Laboratory (INL).Thanks to the efforts of the DOE and outside collaborators, MOOSE currently contains a large set of physics modules, including phase-field, level set, heat conduction, tensor mechanics, Navier-Stokes, fracture and crack propagation (via the extended finite-element method), flow in porous media, and others. The heat conduction, tensor mechanics, and phase-field modules, in particular, are well-suited for snow science problems. Pika--an open-source MOOSE-based application--is capable of simulating both 3D, coupled nonlinear continuum heat transfer and large-deformation mechanics applications (such as settlement) and phase-field based micro-structure applications. Additionally, these types of problems may be coupled tightly in a single solve or across length and time scales using a loosely coupled Picard iteration approach. In addition to the wide range of physics capabilities, MOOSE-based applications also inherit an extensible testing framework, graphical user interface, and documentation system; tools that allow MOOSE and other applications to adhere to nuclear software quality standards. The snow science community can learn from the nuclear industry and harness the existing effort to build simulation tools that are open, modular, and share a common framework. In particular, MOOSE-based multiphysics solvers are inherently parallel, dimension agnostic, adaptive in time and space, fully coupled, and capable of interacting with other applications. The snow science community should build on existing tools to enable collaboration between researchers and practitioners throughout the world, and advance the state-of-the-art in line with other scientific research efforts.

An ice sheet model validation framework for the Greenland ice sheet

NASA Astrophysics Data System (ADS)

Price, Stephen F.; Hoffman, Matthew J.; Bonin, Jennifer A.; Howat, Ian M.; Neumann, Thomas; Saba, Jack; Tezaur, Irina; Guerber, Jeffrey; Chambers, Don P.; Evans, Katherine J.; Kennedy, Joseph H.; Lenaerts, Jan; Lipscomb, William H.; Perego, Mauro; Salinger, Andrew G.; Tuminaro, Raymond S.; van den Broeke, Michiel R.; Nowicki, Sophie M. J.

2017-01-01

We propose a new ice sheet model validation framework - the Cryospheric Model Comparison Tool (CmCt) - that takes advantage of ice sheet altimetry and gravimetry observations collected over the past several decades and is applied here to modeling of the Greenland ice sheet. We use realistic simulations performed with the Community Ice Sheet Model (CISM) along with two idealized, non-dynamic models to demonstrate the framework and its use. Dynamic simulations with CISM are forced from 1991 to 2013, using combinations of reanalysis-based surface mass balance and observations of outlet glacier flux change. We propose and demonstrate qualitative and quantitative metrics for use in evaluating the different model simulations against the observations. We find that the altimetry observations used here are largely ambiguous in terms of their ability to distinguish one simulation from another. Based on basin-scale and whole-ice-sheet-scale metrics, we find that simulations using both idealized conceptual models and dynamic, numerical models provide an equally reasonable representation of the ice sheet surface (mean elevation differences of < 1 m). This is likely due to their short period of record, biases inherent to digital elevation models used for model initial conditions, and biases resulting from firn dynamics, which are not explicitly accounted for in the models or observations. On the other hand, we find that the gravimetry observations used here are able to unambiguously distinguish between simulations of varying complexity, and along with the CmCt, can provide a quantitative score for assessing a particular model and/or simulation. The new framework demonstrates that our proposed metrics can distinguish relatively better from relatively worse simulations and that dynamic ice sheet models, when appropriately initialized and forced with the right boundary conditions, demonstrate a predictive skill with respect to observed dynamic changes that have occurred on Greenland over the past few decades. An extensible design will allow for continued use of the CmCt as future altimetry, gravimetry, and other remotely sensed data become available for use in ice sheet model validation.

An ice sheet model validation framework for the Greenland ice sheet

PubMed Central

Price, Stephen F.; Hoffman, Matthew J.; Bonin, Jennifer A.; Howat, Ian M.; Neumann, Thomas; Saba, Jack; Tezaur, Irina; Guerber, Jeffrey; Chambers, Don P.; Evans, Katherine J.; Kennedy, Joseph H.; Lenaerts, Jan; Lipscomb, William H.; Perego, Mauro; Salinger, Andrew G.; Tuminaro, Raymond S.; van den Broeke, Michiel R.; Nowicki, Sophie M. J.

2018-01-01

We propose a new ice sheet model validation framework – the Cryospheric Model Comparison Tool (CmCt) – that takes advantage of ice sheet altimetry and gravimetry observations collected over the past several decades and is applied here to modeling of the Greenland ice sheet. We use realistic simulations performed with the Community Ice Sheet Model (CISM) along with two idealized, non-dynamic models to demonstrate the framework and its use. Dynamic simulations with CISM are forced from 1991 to 2013 using combinations of reanalysis-based surface mass balance and observations of outlet glacier flux change. We propose and demonstrate qualitative and quantitative metrics for use in evaluating the different model simulations against the observations. We find that the altimetry observations used here are largely ambiguous in terms of their ability to distinguish one simulation from another. Based on basin- and whole-ice-sheet scale metrics, we find that simulations using both idealized conceptual models and dynamic, numerical models provide an equally reasonable representation of the ice sheet surface (mean elevation differences of <1 m). This is likely due to their short period of record, biases inherent to digital elevation models used for model initial conditions, and biases resulting from firn dynamics, which are not explicitly accounted for in the models or observations. On the other hand, we find that the gravimetry observations used here are able to unambiguously distinguish between simulations of varying complexity, and along with the CmCt, can provide a quantitative score for assessing a particular model and/or simulation. The new framework demonstrates that our proposed metrics can distinguish relatively better from relatively worse simulations and that dynamic ice sheet models, when appropriately initialized and forced with the right boundary conditions, demonstrate predictive skill with respect to observed dynamic changes occurring on Greenland over the past few decades. An extensible design will allow for continued use of the CmCt as future altimetry, gravimetry, and other remotely sensed data become available for use in ice sheet model validation. PMID:29697704

An Ice Sheet Model Validation Framework for the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Price, Stephen F.; Hoffman, Matthew J.; Bonin, Jennifer A.; Howat, Ian M.; Neumann, Thomas A.; Saba, Jack; Tezaur, Irina; Guerber, Jeffrey R.; Chambers, Don P.; Evans, Katherine J.;

plasmaFoam: An OpenFOAM framework for computational plasma physics and chemistry

NASA Astrophysics Data System (ADS)

Venkattraman, Ayyaswamy; Verma, Abhishek Kumar

2016-09-01

As emphasized in the 2012 Roadmap for low temperature plasmas (LTP), scientific computing has emerged as an essential tool for the investigation and prediction of the fundamental physical and chemical processes associated with these systems. While several in-house and commercial codes exist, with each having its own advantages and disadvantages, a common framework that can be developed by researchers from all over the world will likely accelerate the impact of computational studies on advances in low-temperature plasma physics and chemistry. In this regard, we present a finite volume computational toolbox to perform high-fidelity simulations of LTP systems. This framework, primarily based on the OpenFOAM solver suite, allows us to enhance our understanding of multiscale plasma phenomenon by performing massively parallel, three-dimensional simulations on unstructured meshes using well-established high performance computing tools that are widely used in the computational fluid dynamics community. In this talk, we will present preliminary results obtained using the OpenFOAM-based solver suite with benchmark three-dimensional simulations of microplasma devices including both dielectric and plasma regions. We will also discuss the future outlook for the solver suite.

NUMERICAL SIMULATION OF NANOINDENTATION AND PATCH CLAMP EXPERIMENTS ON MECHANOSENSITIVE CHANNELS OF LARGE CONDUCTANCE IN ESCHERICHIA COLI

PubMed Central

Tang, Yuye; Chen, Xi; Yoo, Jejoong; Yethiraj, Arun; Cui, Qiang

2010-01-01

A hierarchical simulation framework that integrates information from all-atom simulations into a finite element model at the continuum level is established to study the mechanical response of a mechanosensitive channel of large conductance (MscL) in bacteria Escherichia Coli (E.coli) embedded in a vesicle formed by the dipalmitoylphosphatidycholine (DPPC) lipid bilayer. Sufficient structural details of the protein are built into the continuum model, with key parameters and material properties derived from molecular mechanics simulations. The multi-scale framework is used to analyze the gating of MscL when the lipid vesicle is subjective to nanoindentation and patch clamp experiments, and the detailed structural transitions of the protein are obtained explicitly as a function of external load; it is currently impossible to derive such information based solely on all-atom simulations. The gating pathways of E.coli-MscL qualitatively agree with results from previous patch clamp experiments. The gating mechanisms under complex indentation-induced deformation are also predicted. This versatile hierarchical multi-scale framework may be further extended to study the mechanical behaviors of cells and biomolecules, as well as to guide and stimulate biomechanics experiments. PMID:21874098

Development of an OSSE Framework for a Global Atmospheric Data Assimilation System

NASA Technical Reports Server (NTRS)

Gelaro, Ronald; Errico, Ronald M.; Prive, N.

2012-01-01

Observing system simulation experiments (OSSEs) are powerful tools for estimating the usefulness of various configurations of envisioned observing systems and data assimilation techniques. Their utility stems from their being conducted in an entirely simulated context, utilizing simulated observations having simulated errors and drawn from a simulation of the earth's environment. Observations are generated by applying physically based algorithms to the simulated state, such as performed during data assimilation or using other appropriate algorithms. Adding realistic instrument plus representativeness errors, including their biases and correlations, can be critical for obtaining realistic assessments of the impact of a proposed observing system or analysis technique. If estimates of the expected accuracy of proposed observations are realistic, then the OSSE can be also used to learn how best to utilize the new information, accelerating its transition to operations once the real data are available. As with any inferences from simulations, however, it is first imperative that some baseline OSSEs are performed and well validated against corresponding results obtained with a real observing system. This talk provides an overview of, and highlights critical issues related to, the development of an OSSE framework for the tropospheric weather prediction component of the NASA GEOS-5 global atmospheric data assimilation system. The framework includes all existing observations having significant impact on short-term forecast skill. Its validity has been carefully assessed using a range of metrics that can be evaluated in both the OSSE and real contexts, including adjoint-based estimates of observation impact. A preliminary application to the Aeolus Doppler wind lidar mission, scheduled for launch by the European Space Agency in 2014, has also been investigated.

A framework to simulate small shallow inland water bodies in semi-arid regions

NASA Astrophysics Data System (ADS)

Abbasi, Ali; Ohene Annor, Frank; van de Giesen, Nick

2017-12-01

In this study, a framework for simulating the flow field and heat transfer processes in small shallow inland water bodies has been developed. As the dynamics and thermal structure of these water bodies are crucial in studying the quality of stored water , and in assessing the heat fluxes from their surfaces as well, the heat transfer and temperature simulations were modeled. The proposed model is able to simulate the full 3-D water flow and heat transfer in the water body by applying complex and time varying boundary conditions. In this model, the continuity, momentum and temperature equations together with the turbulence equations, which comprise the buoyancy effect, have been solved. This model is built on the Reynolds Averaged Navier Stokes (RANS) equations with the widely used Boussinesq approach to solve the turbulence issues of the flow field. Micrometeorological data were obtained from an Automatic Weather Station (AWS) installed on the site and combined with field bathymetric measurements for the model. In the framework developed, a simple, applicable and generalizable approach is proposed for preparing the geometry of small shallow water bodies using coarsely measured bathymetry. All parts of the framework are based on open-source tools, which is essential for developing countries.

Filtering in Hybrid Dynamic Bayesian Networks

NASA Technical Reports Server (NTRS)

Andersen, Morten Nonboe; Andersen, Rasmus Orum; Wheeler, Kevin

2000-01-01

We implement a 2-time slice dynamic Bayesian network (2T-DBN) framework and make a 1-D state estimation simulation, an extension of the experiment in (v.d. Merwe et al., 2000) and compare different filtering techniques. Furthermore, we demonstrate experimentally that inference in a complex hybrid DBN is possible by simulating fault detection in a watertank system, an extension of the experiment in (Koller & Lerner, 2000) using a hybrid 2T-DBN. In both experiments, we perform approximate inference using standard filtering techniques, Monte Carlo methods and combinations of these. In the watertank simulation, we also demonstrate the use of 'non-strict' Rao-Blackwellisation. We show that the unscented Kalman filter (UKF) and UKF in a particle filtering framework outperform the generic particle filter, the extended Kalman filter (EKF) and EKF in a particle filtering framework with respect to accuracy in terms of estimation RMSE and sensitivity with respect to choice of network structure. Especially we demonstrate the superiority of UKF in a PF framework when our beliefs of how data was generated are wrong. Furthermore, we investigate the influence of data noise in the watertank simulation using UKF and PFUKD and show that the algorithms are more sensitive to changes in the measurement noise level that the process noise level. Theory and implementation is based on (v.d. Merwe et al., 2000).

Towards a Holistic Framework for the Evaluation of Emergency Plans in Indoor Environments

PubMed Central

Serrano, Emilio; Poveda, Geovanny; Garijo, Mercedes

2014-01-01

One of the most promising fields for ambient intelligence is the implementation of intelligent emergency plans. Because the use of drills and living labs cannot reproduce social behaviors, such as panic attacks, that strongly affect these plans, the use of agent-based social simulation provides an approach to evaluate these plans more thoroughly. (1) The hypothesis presented in this paper is that there has been little interest in describing the key modules that these simulators must include, such as formally represented knowledge and a realistic simulated sensor model, and especially in providing researchers with tools to reuse, extend and interconnect modules from different works. This lack of interest hinders researchers from achieving a holistic framework for evaluating emergency plans and forces them to reconsider and to implement the same components from scratch over and over. In addition to supporting this hypothesis by considering over 150 simulators, this paper: (2) defines the main modules identified and proposes the use of semantic web technologies as a cornerstone for the aforementioned holistic framework; (3) provides a basic methodology to achieve the framework; (4) identifies the main challenges; and (5) presents an open and free software tool to hint at the potential of such a holistic view of emergency plan evaluation in indoor environments. PMID:24662453

The framework for simulation of bioinspired security mechanisms against network infrastructure attacks.

PubMed

Shorov, Andrey; Kotenko, Igor

2014-01-01

The paper outlines a bioinspired approach named "network nervous system" and methods of simulation of infrastructure attacks and protection mechanisms based on this approach. The protection mechanisms based on this approach consist of distributed procedures of information collection and processing, which coordinate the activities of the main devices of a computer network, identify attacks, and determine necessary countermeasures. Attacks and protection mechanisms are specified as structural models using a set-theoretic approach. An environment for simulation of protection mechanisms based on the biological metaphor is considered; the experiments demonstrating the effectiveness of the protection mechanisms are described.

A discrete mechanics framework for real time virtual surgical simulations with application to virtual laparoscopic nephrectomy.

PubMed

Zhou, Xiangmin; Zhang, Nan; Sha, Desong; Shen, Yunhe; Tamma, Kumar K; Sweet, Robert

2009-01-01

The inability to render realistic soft-tissue behavior in real time has remained a barrier to face and content aspects of validity for many virtual reality surgical training systems. Biophysically based models are not only suitable for training purposes but also for patient-specific clinical applications, physiological modeling and surgical planning. When considering the existing approaches for modeling soft tissue for virtual reality surgical simulation, the computer graphics-based approach lacks predictive capability; the mass-spring model (MSM) based approach lacks biophysically realistic soft-tissue dynamic behavior; and the finite element method (FEM) approaches fail to meet the real-time requirement. The present development stems from physics fundamental thermodynamic first law; for a space discrete dynamic system directly formulates the space discrete but time continuous governing equation with embedded material constitutive relation and results in a discrete mechanics framework which possesses a unique balance between the computational efforts and the physically realistic soft-tissue dynamic behavior. We describe the development of the discrete mechanics framework with focused attention towards a virtual laparoscopic nephrectomy application.

Adaptive Agent Modeling of Distributed Language: Investigations on the Effects of Cultural Variation and Internal Action Representations

ERIC Educational Resources Information Center

Cangelosi, Angelo

2007-01-01

In this paper we present the "grounded adaptive agent" computational framework for studying the emergence of communication and language. This modeling framework is based on simulations of population of cognitive agents that evolve linguistic capabilities by interacting with their social and physical environment (internal and external symbol…

A Qualitative Simulation Framework in Smalltalk Based on Fuzzy Arithmetic

Treesearch

Richard L. Olson; Daniel L. Schmoldt; David L. Peterson

1996-01-01

For many systems, it is not practical to collect and correlate empirical data necessary to formulate a mathematical model. However, it is often sufficient to predict qualitative dynamics effects (as opposed to system quantities), especially for research purposes. In this effort, an object-oriented application framework (AF) was developed for the qualitative modeling of...

A web GIS based integrated flood assessment modeling tool for coastal urban watersheds

NASA Astrophysics Data System (ADS)

Kulkarni, A. T.; Mohanty, J.; Eldho, T. I.; Rao, E. P.; Mohan, B. K.

2014-03-01

Urban flooding has become an increasingly important issue in many parts of the world. In this study, an integrated flood assessment model (IFAM) is presented for the coastal urban flood simulation. A web based GIS framework has been adopted to organize the spatial datasets for the study area considered and to run the model within this framework. The integrated flood model consists of a mass balance based 1-D overland flow model, 1-D finite element based channel flow model based on diffusion wave approximation and a quasi 2-D raster flood inundation model based on the continuity equation. The model code is written in MATLAB and the application is integrated within a web GIS server product viz: Web Gram Server™ (WGS), developed at IIT Bombay, using Java, JSP and JQuery technologies. Its user interface is developed using open layers and the attribute data are stored in MySQL open source DBMS. The model is integrated within WGS and is called via Java script. The application has been demonstrated for two coastal urban watersheds of Navi Mumbai, India. Simulated flood extents for extreme rainfall event of 26 July, 2005 in the two urban watersheds of Navi Mumbai city are presented and discussed. The study demonstrates the effectiveness of the flood simulation tool in a web GIS environment to facilitate data access and visualization of GIS datasets and simulation results.

The Trick Simulation Toolkit: A NASA/Open source Framework for Running Time Based Physics Models

NASA Technical Reports Server (NTRS)

Penn, John M.; Lin, Alexander S.

2016-01-01

This paper describes the design and use at of the Trick Simulation Toolkit, a simulation development environment for creating high fidelity training and engineering simulations at the NASA Johnson Space Center and many other NASA facilities. It describes Trick's design goals and how the development environment attempts to achieve those goals. It describes how Trick is used in some of the many training and engineering simulations at NASA. Finally it describes the Trick NASA/Open source project on Github.

Sensor Based Framework for Secure Multimedia Communication in VANET

PubMed Central

Rahim, Aneel; Khan, Zeeshan Shafi; Bin Muhaya, Fahad T.; Sher, Muhammad; Kim, Tai-Hoon

2010-01-01

Secure multimedia communication enhances the safety of passengers by providing visual pictures of accidents and danger situations. In this paper we proposed a framework for secure multimedia communication in Vehicular Ad-Hoc Networks (VANETs). Our proposed framework is mainly divided into four components: redundant information, priority assignment, malicious data verification and malicious node verification. The proposed scheme jhas been validated with the help of the NS-2 network simulator and the Evalvid tool. PMID:22163462

Managing simulation-based training: A framework for optimizing learning, cost, and time

NASA Astrophysics Data System (ADS)

Richmond, Noah Joseph

This study provides a management framework for optimizing training programs for learning, cost, and time when using simulation based training (SBT) and reality based training (RBT) as resources. Simulation is shown to be an effective means for implementing activity substitution as a way to reduce risk. The risk profile of 22 US Air Force vehicles are calculated, and the potential risk reduction is calculated under the assumption of perfect substitutability of RBT and SBT. Methods are subsequently developed to relax the assumption of perfect substitutability. The transfer effectiveness ratio (TER) concept is defined and modeled as a function of the quality of the simulator used, and the requirements of the activity trained. The Navy F/A-18 is then analyzed in a case study illustrating how learning can be maximized subject to constraints in cost and time, and also subject to the decision maker's preferences for the proportional and absolute use of simulation. Solution methods for optimizing multiple activities across shared resources are next provided. Finally, a simulation strategy including an operations planning program (OPP), an implementation program (IP), an acquisition program (AP), and a pedagogical research program (PRP) is detailed. The study provides the theoretical tools to understand how to leverage SBT, a case study demonstrating these tools' efficacy, and a set of policy recommendations to enable the US military to better utilize SBT in the future.

An Integrated Software Package to Enable Predictive Simulation Capabilities

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

Chen, Yousu; Fitzhenry, Erin B.; Jin, Shuangshuang

The power grid is increasing in complexity due to the deployment of smart grid technologies. Such technologies vastly increase the size and complexity of power grid systems for simulation and modeling. This increasing complexity necessitates not only the use of high-performance-computing (HPC) techniques, but a smooth, well-integrated interplay between HPC applications. This paper presents a new integrated software package that integrates HPC applications and a web-based visualization tool based on a middleware framework. This framework can support the data communication between different applications. Case studies with a large power system demonstrate the predictive capability brought by the integrated software package,more » as well as the better situational awareness provided by the web-based visualization tool in a live mode. Test results validate the effectiveness and usability of the integrated software package.« less

Simulation-Based Joint Estimation of Body Deformation and Elasticity Parameters for Medical Image Analysis

PubMed Central

Foskey, Mark; Niethammer, Marc; Krajcevski, Pavel; Lin, Ming C.

2014-01-01

Estimation of tissue stiffness is an important means of noninvasive cancer detection. Existing elasticity reconstruction methods usually depend on a dense displacement field (inferred from ultrasound or MR images) and known external forces. Many imaging modalities, however, cannot provide details within an organ and therefore cannot provide such a displacement field. Furthermore, force exertion and measurement can be difficult for some internal organs, making boundary forces another missing parameter. We propose a general method for estimating elasticity and boundary forces automatically using an iterative optimization framework, given the desired (target) output surface. During the optimization, the input model is deformed by the simulator, and an objective function based on the distance between the deformed surface and the target surface is minimized numerically. The optimization framework does not depend on a particular simulation method and is therefore suitable for different physical models. We show a positive correlation between clinical prostate cancer stage (a clinical measure of severity) and the recovered elasticity of the organ. Since the surface correspondence is established, our method also provides a non-rigid image registration, where the quality of the deformation fields is guaranteed, as they are computed using a physics-based simulation. PMID:22893381

Gas adsorption in Mg-porphyrin-based porous organic frameworks: A computational simulation by first-principles derived force field.

PubMed

Pang, Yujia; Li, Wenliang; Zhang, Jingping

2017-09-15

A novel type of porous organic frameworks, based on Mg-porphyrin, with diamond-like topology, named POF-Mgs is computationally designed, and the gas uptakes of CO 2 , H 2 , N 2 , and H 2 O in POF-Mgs are investigated by Grand canonical Monte Carlo simulations based on first-principles derived force fields (FF). The FF, which describes the interactions between POF-Mgs and gases, are fitted by dispersion corrected double-hybrid density functional theory, B2PLYP-D3. The good agreement between the obtained FF and the first-principle energies data confirms the reliability of the FF. Furthermore our simulation shows the presence of a small amount of H 2 O (≤ 0.01 kPa) does not much affect the adsorption quantity of CO 2 , but the presence of higher partial pressure of H 2 O (≥ 0.1 kPa) results in the CO 2 adsorption decrease significantly. The good performance of POF-Mgs in the simulation inspires us to design novel porous materials experimentally for gas adsorption and purification. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Spectrum simulation in DTSA-II.

PubMed

Ritchie, Nicholas W M

2009-10-01

Spectrum simulation is a useful practical and pedagogical tool. Particularly with complex samples or trace constituents, a simulation can help to understand the limits of the technique and the instrument parameters for the optimal measurement. DTSA-II, software for electron probe microanalysis, provides both easy to use and flexible tools for simulating common and less common sample geometries and materials. Analytical models based on (rhoz) curves provide quick simulations of simple samples. Monte Carlo models based on electron and X-ray transport provide more sophisticated models of arbitrarily complex samples. DTSA-II provides a broad range of simulation tools in a framework with many different interchangeable physical models. In addition, DTSA-II provides tools for visualizing, comparing, manipulating, and quantifying simulated and measured spectra.

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

PubMed

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

2017-02-06

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

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

PubMed Central

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

2017-01-01

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

Arcade: A Web-Java Based Framework for Distributed Computing

NASA Technical Reports Server (NTRS)

Chen, Zhikai; Maly, Kurt; Mehrotra, Piyush; Zubair, Mohammad; Bushnell, Dennis M. (Technical Monitor)

2000-01-01

Distributed heterogeneous environments are being increasingly used to execute a variety of large size simulations and computational problems. We are developing Arcade, a web-based environment to design, execute, monitor, and control distributed applications. These targeted applications consist of independent heterogeneous modules which can be executed on a distributed heterogeneous environment. In this paper we describe the overall design of the system and discuss the prototype implementation of the core functionalities required to support such a framework.

Towards identifying nurse educator competencies required for simulation-based learning: A systemised rapid review and synthesis.

PubMed

Topping, Anne; Bøje, Rikke Buus; Rekola, Leena; Hartvigsen, Tina; Prescott, Stephen; Bland, Andrew; Hope, Angela; Haho, Paivi; Hannula, Leena

2015-11-01

This paper presents the results of a systemised rapid review and synthesis of the literature undertaken to identify competencies required by nurse educators to facilitate simulation-based learning (SBL). An international collaboration undertook a protocol-based search, retrieval and critical review. Web of Science, PubMed, CINAHL Plus, PsycInfo, ERIC, the Cochrane Library and Science Direct. The search was limited to articles published in English, 2002-2012. The search terms used: nurse*, learn*, facilitator, simula*, lecturer, competence, skill*, qualificat*, educator, health care, "patient simulation", "nursing education" and "faculty". The search yielded 2156 "hits", following a review of the abstracts, 72 full-text articles were extracted. These were screened against predetermined inclusion/exclusion criteria and nine articles were retained. Following critical appraisal, the articles were analyzed using an inductive approach to extract statements for categorization and synthesis as competency statements. This review confirmed that there was a modest amount of empirical evidence on which to base a competency framework. Those papers that provided descriptions of educator preparation identified simulation-based workshops, or experiential training, as the most common approaches for enhancing skills. SBL was not associated with any one theoretical perspective. Delivery of SBL appeared to demand competencies associated with planning and designing simulations, facilitating learning in "safe" environments, expert nursing knowledge based on credible clinical realism, reference to evidence-based knowledge and demonstration of professional values and identity. This review derived a preliminary competency framework. This needs further development as a model for educators delivering SBL as part of nursing curricula. Copyright © 2015. Published by Elsevier Ltd.

Interpreting the NLN Jeffries Framework in the context of Nurse Educator preparation.

PubMed

Young, Patricia K; Shellenbarger, Teresa

2012-08-01

The NLN Jeffries Framework describing simulation in nursing education has been used widely to guide construction of human patient simulation scenarios and serve as a theoretical framework for research on the use of simulation. This framework was developed with a focus on prelicensure nursing education. However, use of human patient simulation scenarios is also a way of providing practice experiences for graduate students learning the educator role. High-fidelity human patient simulation offers nurse educator faculty a unique opportunity to cultivate the practical knowledge of teaching in an interactive and dynamic environment. This article describes how the components of The NLN Jeffries Framework can help to guide simulation design for nurse educator preparation. Adapting the components of the framework-which include teacher, student, educational practices, design characteristics, and outcomes-helps to ensure that future faculty gain hands-on experience with nurse educator core competencies. Copyright 2012, SLACK Incorporated.

Symphony: A Framework for Accurate and Holistic WSN Simulation

PubMed Central

Riliskis, Laurynas; Osipov, Evgeny

2015-01-01

Research on wireless sensor networks has progressed rapidly over the last decade, and these technologies have been widely adopted for both industrial and domestic uses. Several operating systems have been developed, along with a multitude of network protocols for all layers of the communication stack. Industrial Wireless Sensor Network (WSN) systems must satisfy strict criteria and are typically more complex and larger in scale than domestic systems. Together with the non-deterministic behavior of network hardware in real settings, this greatly complicates the debugging and testing of WSN functionality. To facilitate the testing, validation, and debugging of large-scale WSN systems, we have developed a simulation framework that accurately reproduces the processes that occur inside real equipment, including both hardware- and software-induced delays. The core of the framework consists of a virtualized operating system and an emulated hardware platform that is integrated with the general purpose network simulator ns-3. Our framework enables the user to adjust the real code base as would be done in real deployments and also to test the boundary effects of different hardware components on the performance of distributed applications and protocols. Additionally we have developed a clock emulator with several different skew models and a component that handles sensory data feeds. The new framework should substantially shorten WSN application development cycles. PMID:25723144

Quantifying the impact of respiratory-gated 4D CT acquisition on thoracic image quality: a digital phantom study.

PubMed

Bernatowicz, K; Keall, P; Mishra, P; Knopf, A; Lomax, A; Kipritidis, J

2015-01-01

Prospective respiratory-gated 4D CT has been shown to reduce tumor image artifacts by up to 50% compared to conventional 4D CT. However, to date no studies have quantified the impact of gated 4D CT on normal lung tissue imaging, which is important in performing dose calculations based on accurate estimates of lung volume and structure. To determine the impact of gated 4D CT on thoracic image quality, the authors developed a novel simulation framework incorporating a realistic deformable digital phantom driven by patient tumor motion patterns. Based on this framework, the authors test the hypothesis that respiratory-gated 4D CT can significantly reduce lung imaging artifacts. Our simulation framework synchronizes the 4D extended cardiac torso (XCAT) phantom with tumor motion data in a quasi real-time fashion, allowing simulation of three 4D CT acquisition modes featuring different levels of respiratory feedback: (i) "conventional" 4D CT that uses a constant imaging and couch-shift frequency, (ii) "beam paused" 4D CT that interrupts imaging to avoid oversampling at a given couch position and respiratory phase, and (iii) "respiratory-gated" 4D CT that triggers acquisition only when the respiratory motion fulfills phase-specific displacement gating windows based on prescan breathing data. Our framework generates a set of ground truth comparators, representing the average XCAT anatomy during beam-on for each of ten respiratory phase bins. Based on this framework, the authors simulated conventional, beam-paused, and respiratory-gated 4D CT images using tumor motion patterns from seven lung cancer patients across 13 treatment fractions, with a simulated 5.5 cm(3) spherical lesion. Normal lung tissue image quality was quantified by comparing simulated and ground truth images in terms of overall mean square error (MSE) intensity difference, threshold-based lung volume error, and fractional false positive/false negative rates. Averaged across all simulations and phase bins, respiratory-gating reduced overall thoracic MSE by 46% compared to conventional 4D CT (p ∼ 10(-19)). Gating leads to small but significant (p < 0.02) reductions in lung volume errors (1.8%-1.4%), false positives (4.0%-2.6%), and false negatives (2.7%-1.3%). These percentage reductions correspond to gating reducing image artifacts by 24-90 cm(3) of lung tissue. Similar to earlier studies, gating reduced patient image dose by up to 22%, but with scan time increased by up to 135%. Beam paused 4D CT did not significantly impact normal lung tissue image quality, but did yield similar dose reductions as for respiratory-gating, without the added cost in scanning time. For a typical 6 L lung, respiratory-gated 4D CT can reduce image artifacts affecting up to 90 cm(3) of normal lung tissue compared to conventional acquisition. This image improvement could have important implications for dose calculations based on 4D CT. Where image quality is less critical, beam paused 4D CT is a simple strategy to reduce imaging dose without sacrificing acquisition time.

A Simulation Study of Acoustic-Assisted Tracking of Whales for Mark-Recapture Surveys

PubMed Central

Peel, David; Miller, Brian S.; Kelly, Natalie; Dawson, Steve; Slooten, Elisabeth; Double, Michael C.

2014-01-01

Collecting enough data to obtain reasonable abundance estimates of whales is often difficult, particularly when studying rare species. Passive acoustics can be used to detect whale sounds and are increasingly used to estimate whale abundance. Much of the existing effort centres on the use of acoustics to estimate abundance directly, e.g. analysing detections in a distance sampling framework. Here, we focus on acoustics as a tool incorporated within mark-recapture surveys. In this context, acoustic tools are used to detect and track whales, which are then photographed or biopsied to provide data for mark-recapture analyses. The purpose of incorporating acoustics is to increase the encounter rate beyond using visual searching only. While this general approach is not new, its utility is rarely quantified. This paper predicts the “acoustically-assisted” encounter rate using a discrete-time individual-based simulation of whales and survey vessel. We validate the simulation framework using existing data from studies of sperm whales. We then use the framework to predict potential encounter rates in a study of Antarctic blue whales. We also investigate the effects of a number of the key parameters on encounter rate. Mean encounter rates from the simulation of sperm whales matched well with empirical data. Variance of encounter rate, however, was underestimated. The simulation of Antarctic blue whales found that passive acoustics should provide a 1.7–3.0 fold increase in encounter rate over visual-only methods. Encounter rate was most sensitive to acoustic detection range, followed by vocalisation rate. During survey planning and design, some indication of the relationship between expected sample size and effort is paramount; this simulation framework can be used to predict encounter rates and establish this relationship. For a case in point, the simulation framework indicates unequivocally that real-time acoustic tracking should be considered for quantifying the abundance of Antarctic blue whales via mark-recapture methods. PMID:24827919

A simulation study of acoustic-assisted tracking of whales for mark-recapture surveys.

PubMed

Peel, David; Miller, Brian S; Kelly, Natalie; Dawson, Steve; Slooten, Elisabeth; Double, Michael C

2014-01-01

Collecting enough data to obtain reasonable abundance estimates of whales is often difficult, particularly when studying rare species. Passive acoustics can be used to detect whale sounds and are increasingly used to estimate whale abundance. Much of the existing effort centres on the use of acoustics to estimate abundance directly, e.g. analysing detections in a distance sampling framework. Here, we focus on acoustics as a tool incorporated within mark-recapture surveys. In this context, acoustic tools are used to detect and track whales, which are then photographed or biopsied to provide data for mark-recapture analyses. The purpose of incorporating acoustics is to increase the encounter rate beyond using visual searching only. While this general approach is not new, its utility is rarely quantified. This paper predicts the "acoustically-assisted" encounter rate using a discrete-time individual-based simulation of whales and survey vessel. We validate the simulation framework using existing data from studies of sperm whales. We then use the framework to predict potential encounter rates in a study of Antarctic blue whales. We also investigate the effects of a number of the key parameters on encounter rate. Mean encounter rates from the simulation of sperm whales matched well with empirical data. Variance of encounter rate, however, was underestimated. The simulation of Antarctic blue whales found that passive acoustics should provide a 1.7-3.0 fold increase in encounter rate over visual-only methods. Encounter rate was most sensitive to acoustic detection range, followed by vocalisation rate. During survey planning and design, some indication of the relationship between expected sample size and effort is paramount; this simulation framework can be used to predict encounter rates and establish this relationship. For a case in point, the simulation framework indicates unequivocally that real-time acoustic tracking should be considered for quantifying the abundance of Antarctic blue whales via mark-recapture methods.

Simulation in interprofessional education for patient-centred collaborative care.

PubMed

Baker, Cynthia; Pulling, Cheryl; McGraw, Robert; Dagnone, Jeffrey Damon; Hopkins-Rosseel, Diana; Medves, Jennifer

2008-11-01

This paper is a report of preliminary evaluations of an interprofessional education through simulation project by focusing on learner and teacher reactions to the pilot modules. Approaches to interprofessional education vary widely. Studies indicate, however, that active, experiential learning facilitate it. Patient simulators require learners to incorporate knowing, being and doing in action. A theoretically based competency framework was developed to guide interprofessional education using simulation. The framework includes a typology of shared, complementary and profession-specific competencies. Each competency type is associated with an intraprofessional, multiprofessional, or interprofessional teaching modality and with the professional composition of learner groups. The project is guided by an action research approach in which ongoing evaluation generates knowledge to modify and further develop it. Preliminary evaluations of the first pilot module, cardiac resuscitation rounds, among 101 nursing students, 42 medical students and 70 junior medical residents were conducted in 2005-2007 using a questionnaire with rating scales and open-ended questions. Another 20 medical students, 7 junior residents and 45 nursing students completed a questionnaire based on the Interdisciplinary Education Perception scale. Simulation-based learning provided students with interprofessional activities they saw as relevant for their future as practitioners. They embraced both the interprofessional and simulation components enthusiastically. Attitudinal scores and responses were consistently positive among both medical and nursing students. Interprofessional education through simulation offers a promising approach to preparing future healthcare professionals for the collaborative models of healthcare delivery being developed internationally.

A simulation framework for mapping risks in clinical processes: the case of in-patient transfers.

PubMed

Dunn, Adam G; Ong, Mei-Sing; Westbrook, Johanna I; Magrabi, Farah; Coiera, Enrico; Wobcke, Wayne

2011-05-01

To model how individual violations in routine clinical processes cumulatively contribute to the risk of adverse events in hospital using an agent-based simulation framework. An agent-based simulation was designed to model the cascade of common violations that contribute to the risk of adverse events in routine clinical processes. Clinicians and the information systems that support them were represented as a group of interacting agents using data from direct observations. The model was calibrated using data from 101 patient transfers observed in a hospital and results were validated for one of two scenarios (a misidentification scenario and an infection control scenario). Repeated simulations using the calibrated model were undertaken to create a distribution of possible process outcomes. The likelihood of end-of-chain risk is the main outcome measure, reported for each of the two scenarios. The simulations demonstrate end-of-chain risks of 8% and 24% for the misidentification and infection control scenarios, respectively. Over 95% of the simulations in both scenarios are unique, indicating that the in-patient transfer process diverges from prescribed work practices in a variety of ways. The simulation allowed us to model the risk of adverse events in a clinical process, by generating the variety of possible work subject to violations, a novel prospective risk analysis method. The in-patient transfer process has a high proportion of unique trajectories, implying that risk mitigation may benefit from focusing on reducing complexity rather than augmenting the process with further rule-based protocols.

BeamDyn: a high-fidelity wind turbine blade solver in the FAST modular framework

DOE PAGES

Wang, Qi; Sprague, Michael A.; Jonkman, Jason; ...

2017-03-14

Here, this paper presents a numerical implementation of the geometrically exact beam theory based on the Legendre-spectral-finite-element (LSFE) method. The displacement-based geometrically exact beam theory is presented, and the special treatment of three-dimensional rotation parameters is reviewed. An LSFE is a high-order finite element with nodes located at the Gauss-Legendre-Lobatto points. These elements can be an order of magnitude more computationally efficient than low-order finite elements for a given accuracy level. The new module, BeamDyn, is implemented in the FAST modularization framework for dynamic simulation of highly flexible composite-material wind turbine blades within the FAST aeroelastic engineering model. The frameworkmore » allows for fully interactive simulations of turbine blades in operating conditions. Numerical examples are provided to validate BeamDyn and examine the LSFE performance as well as the coupling algorithm in the FAST modularization framework. BeamDyn can also be used as a stand-alone high-fidelity beam tool.« less

BeamDyn: a high-fidelity wind turbine blade solver in the FAST modular framework

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

Wang, Qi; Sprague, Michael A.; Jonkman, Jason

Here, this paper presents a numerical implementation of the geometrically exact beam theory based on the Legendre-spectral-finite-element (LSFE) method. The displacement-based geometrically exact beam theory is presented, and the special treatment of three-dimensional rotation parameters is reviewed. An LSFE is a high-order finite element with nodes located at the Gauss-Legendre-Lobatto points. These elements can be an order of magnitude more computationally efficient than low-order finite elements for a given accuracy level. The new module, BeamDyn, is implemented in the FAST modularization framework for dynamic simulation of highly flexible composite-material wind turbine blades within the FAST aeroelastic engineering model. The frameworkmore » allows for fully interactive simulations of turbine blades in operating conditions. Numerical examples are provided to validate BeamDyn and examine the LSFE performance as well as the coupling algorithm in the FAST modularization framework. BeamDyn can also be used as a stand-alone high-fidelity beam tool.« less

Multi-Dielectric Brownian Dynamics and Design-Space-Exploration Studies of Permeation in Ion Channels.

PubMed

Siksik, May; Krishnamurthy, Vikram

2017-09-01

This paper proposes a multi-dielectric Brownian dynamics simulation framework for design-space-exploration (DSE) studies of ion-channel permeation. The goal of such DSE studies is to estimate the channel modeling-parameters that minimize the mean-squared error between the simulated and expected "permeation characteristics." To address this computational challenge, we use a methodology based on statistical inference that utilizes the knowledge of channel structure to prune the design space. We demonstrate the proposed framework and DSE methodology using a case study based on the KcsA ion channel, in which the design space is successfully reduced from a 6-D space to a 2-D space. Our results show that the channel dielectric map computed using the framework matches with that computed directly using molecular dynamics with an error of 7%. Finally, the scalability and resolution of the model used are explored, and it is shown that the memory requirements needed for DSE remain constant as the number of parameters (degree of heterogeneity) increases.

JCell--a Java-based framework for inferring regulatory networks from time series data.

PubMed

Spieth, C; Supper, J; Streichert, F; Speer, N; Zell, A

2006-08-15

JCell is a Java-based application for reconstructing gene regulatory networks from experimental data. The framework provides several algorithms to identify genetic and metabolic dependencies based on experimental data conjoint with mathematical models to describe and simulate regulatory systems. Owing to the modular structure, researchers can easily implement new methods. JCell is a pure Java application with additional scripting capabilities and thus widely usable, e.g. on parallel or cluster computers. The software is freely available for download at http://www-ra.informatik.uni-tuebingen.de/software/JCell.

LDRD project final report : hybrid AI/cognitive tactical behavior framework for LVC.

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

Djordjevich, Donna D.; Xavier, Patrick Gordon; Brannon, Nathan Gregory

This Lab-Directed Research and Development (LDRD) sought to develop technology that enhances scenario construction speed, entity behavior robustness, and scalability in Live-Virtual-Constructive (LVC) simulation. We investigated issues in both simulation architecture and behavior modeling. We developed path-planning technology that improves the ability to express intent in the planning task while still permitting an efficient search algorithm. An LVC simulation demonstrated how this enables 'one-click' layout of squad tactical paths, as well as dynamic re-planning for simulated squads and for real and simulated mobile robots. We identified human response latencies that can be exploited in parallel/distributed architectures. We did an experimentalmore » study to determine where parallelization would be productive in Umbra-based force-on-force (FOF) simulations. We developed and implemented a data-driven simulation composition approach that solves entity class hierarchy issues and supports assurance of simulation fairness. Finally, we proposed a flexible framework to enable integration of multiple behavior modeling components that model working memory phenomena with different degrees of sophistication.« less

A hybrid computational model to explore the topological characteristics of epithelial tissues.

PubMed

González-Valverde, Ismael; García-Aznar, José Manuel

2017-11-01

Epithelial tissues show a particular topology where cells resemble a polygon-like shape, but some biological processes can alter this tissue topology. During cell proliferation, mitotic cell dilation deforms the tissue and modifies the tissue topology. Additionally, cells are reorganized in the epithelial layer and these rearrangements also alter the polygon distribution. We present here a computer-based hybrid framework focused on the simulation of epithelial layer dynamics that combines discrete and continuum numerical models. In this framework, we consider topological and mechanical aspects of the epithelial tissue. Individual cells in the tissue are simulated by an off-lattice agent-based model, which keeps the information of each cell. In addition, we model the cell-cell interaction forces and the cell cycle. Otherwise, we simulate the passive mechanical behaviour of the cell monolayer using a material that approximates the mechanical properties of the cell. This continuum approach is solved by the finite element method, which uses a dynamic mesh generated by the triangulation of cell polygons. Forces generated by cell-cell interaction in the agent-based model are also applied on the finite element mesh. Cell movement in the agent-based model is driven by the displacements obtained from the deformed finite element mesh of the continuum mechanical approach. We successfully compare the results of our simulations with some experiments about the topology of proliferating epithelial tissues in Drosophila. Our framework is able to model the emergent behaviour of the cell monolayer that is due to local cell-cell interactions, which have a direct influence on the dynamics of the epithelial tissue. Copyright © 2017 John Wiley & Sons, Ltd.

Numerical simulation of the fracture process in ceramic FPD frameworks caused by oblique loading.

PubMed

Kou, Wen; Qiao, Jiyan; Chen, Li; Ding, Yansheng; Sjögren, Göran

2015-10-01

Using a newly developed three-dimensional (3D) numerical modeling code, an analysis was performed of the fracture behavior in a three-unit ceramic-based fixed partial denture (FPD) framework subjected to oblique loading. All the materials in the study were treated heterogeneously; Weibull׳s distribution law was applied to the description of the heterogeneity. The Mohr-Coulomb failure criterion with tensile strength cut-off was utilized in judging whether the material was in an elastic or failed state. The simulated loading area was placed either on the buccal or the lingual cusp of a premolar-shaped pontic with the loading direction at 30°, 45°, 60°, 75° or 90° angles to the occlusal surface. The stress distribution, fracture initiation and propagation in the framework during the loading and fracture process were analyzed. This numerical simulation allowed the cause of the framework fracture to be identified as tensile stress failure. The decisive fracture was initiated in the gingival embrasure of the pontic, regardless of whether the buccal or lingual cusp of the pontic was loaded. The stress distribution and fracture propagation process of the framework could be followed step by step from beginning to end. The bearing capacity and the rigidity of the framework vary with the loading position and direction. The framework loaded with 90° towards the occlusal surface has the highest bearing capacity and the greatest rigidity. The framework loaded with 30° towards the occlusal surface has the least rigidity indicating that oblique loading has a major impact on the fracture of ceramic frameworks. Copyright © 2015 Elsevier Ltd. All rights reserved.

A unified framework for heat and mass transport at the atomic scale

NASA Astrophysics Data System (ADS)

Ponga, Mauricio; Sun, Dingyi

2018-04-01

We present a unified framework to simulate heat and mass transport in systems of particles. The proposed framework is based on kinematic mean field theory and uses a phenomenological master equation to compute effective transport rates between particles without the need to evaluate operators. We exploit this advantage and apply the model to simulate transport phenomena at the nanoscale. We demonstrate that, when calibrated to experimentally-measured transport coefficients, the model can accurately predict transient and steady state temperature and concentration profiles even in scenarios where the length of the device is comparable to the mean free path of the carriers. Through several example applications, we demonstrate the validity of our model for all classes of materials, including ones that, until now, would have been outside the domain of computational feasibility.

Simbios: an NIH national center for physics-based simulation of biological structures.

PubMed

Delp, Scott L; Ku, Joy P; Pande, Vijay S; Sherman, Michael A; Altman, Russ B

2012-01-01

Physics-based simulation provides a powerful framework for understanding biological form and function. Simulations can be used by biologists to study macromolecular assemblies and by clinicians to design treatments for diseases. Simulations help biomedical researchers understand the physical constraints on biological systems as they engineer novel drugs, synthetic tissues, medical devices, and surgical interventions. Although individual biomedical investigators make outstanding contributions to physics-based simulation, the field has been fragmented. Applications are typically limited to a single physical scale, and individual investigators usually must create their own software. These conditions created a major barrier to advancing simulation capabilities. In 2004, we established a National Center for Physics-Based Simulation of Biological Structures (Simbios) to help integrate the field and accelerate biomedical research. In 6 years, Simbios has become a vibrant national center, with collaborators in 16 states and eight countries. Simbios focuses on problems at both the molecular scale and the organismal level, with a long-term goal of uniting these in accurate multiscale simulations.

Simbios: an NIH national center for physics-based simulation of biological structures

PubMed Central

Delp, Scott L; Ku, Joy P; Pande, Vijay S; Sherman, Michael A

2011-01-01

Physics-based simulation provides a powerful framework for understanding biological form and function. Simulations can be used by biologists to study macromolecular assemblies and by clinicians to design treatments for diseases. Simulations help biomedical researchers understand the physical constraints on biological systems as they engineer novel drugs, synthetic tissues, medical devices, and surgical interventions. Although individual biomedical investigators make outstanding contributions to physics-based simulation, the field has been fragmented. Applications are typically limited to a single physical scale, and individual investigators usually must create their own software. These conditions created a major barrier to advancing simulation capabilities. In 2004, we established a National Center for Physics-Based Simulation of Biological Structures (Simbios) to help integrate the field and accelerate biomedical research. In 6 years, Simbios has become a vibrant national center, with collaborators in 16 states and eight countries. Simbios focuses on problems at both the molecular scale and the organismal level, with a long-term goal of uniting these in accurate multiscale simulations. PMID:22081222

Simulation of orographic effects with a Quasi-3-D Multiscale Modeling Framework: Basic algorithm and preliminary results

DOE PAGES

Jung, Joon -Hee

2016-10-11

Here, the global atmospheric models based on the Multi-scale Modeling Framework (MMF) are able to explicitly resolve subgrid-scale processes by using embedded 2-D Cloud-Resolving Models (CRMs). Up to now, however, those models do not include the orographic effects on the CRM grid scale. This study shows that the effects of CRM grid-scale orography can be simulated reasonably well by the Quasi-3-D MMF (Q3D MMF), which has been developed as a second-generation MMF. In the Q3D framework, the surface topography can be included in the CRM component by using a block representation of the mountains, so that no smoothing of themore » topographic height is necessary. To demonstrate the performance of such a model, the orographic effects over a steep mountain are simulated in an idealized experimental setup with each of the Q3D MMF and the full 3-D CRM. The latter is used as a benchmark. Comparison of the results shows that the Q3D MMF is able to reproduce the horizontal distribution of orographic precipitation and the flow changes around mountains as simulated by the 3-D CRM, even though the embedded CRMs of the Q3D MMF recognize only some aspects of the complex 3-D topography. It is also shown that the use of 3-D CRMs in the Q3D framework, rather than 2-D CRMs, has positive impacts on the simulation of wind fields but does not substantially change the simulated precipitation.« less

Simulation of orographic effects with a Quasi-3-D Multiscale Modeling Framework: Basic algorithm and preliminary results

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

Jung, Joon -Hee

Here, the global atmospheric models based on the Multi-scale Modeling Framework (MMF) are able to explicitly resolve subgrid-scale processes by using embedded 2-D Cloud-Resolving Models (CRMs). Up to now, however, those models do not include the orographic effects on the CRM grid scale. This study shows that the effects of CRM grid-scale orography can be simulated reasonably well by the Quasi-3-D MMF (Q3D MMF), which has been developed as a second-generation MMF. In the Q3D framework, the surface topography can be included in the CRM component by using a block representation of the mountains, so that no smoothing of themore » topographic height is necessary. To demonstrate the performance of such a model, the orographic effects over a steep mountain are simulated in an idealized experimental setup with each of the Q3D MMF and the full 3-D CRM. The latter is used as a benchmark. Comparison of the results shows that the Q3D MMF is able to reproduce the horizontal distribution of orographic precipitation and the flow changes around mountains as simulated by the 3-D CRM, even though the embedded CRMs of the Q3D MMF recognize only some aspects of the complex 3-D topography. It is also shown that the use of 3-D CRMs in the Q3D framework, rather than 2-D CRMs, has positive impacts on the simulation of wind fields but does not substantially change the simulated precipitation.« less

Simulation of orographic effects with a Quasi-3-D Multiscale Modeling Framework: Basic algorithm and preliminary results

NASA Astrophysics Data System (ADS)

Jung, Joon-Hee

2016-12-01

The global atmospheric models based on the Multi-scale Modeling Framework (MMF) are able to explicitly resolve subgrid-scale processes by using embedded 2-D Cloud-Resolving Models (CRMs). Up to now, however, those models do not include the orographic effects on the CRM grid scale. This study shows that the effects of CRM grid-scale orography can be simulated reasonably well by the Quasi-3-D MMF (Q3D MMF), which has been developed as a second-generation MMF. In the Q3D framework, the surface topography can be included in the CRM component by using a block representation of the mountains, so that no smoothing of the topographic height is necessary. To demonstrate the performance of such a model, the orographic effects over a steep mountain are simulated in an idealized experimental setup with each of the Q3D MMF and the full 3-D CRM. The latter is used as a benchmark. Comparison of the results shows that the Q3D MMF is able to reproduce the horizontal distribution of orographic precipitation and the flow changes around mountains as simulated by the 3-D CRM, even though the embedded CRMs of the Q3D MMF recognize only some aspects of the complex 3-D topography. It is also shown that the use of 3-D CRMs in the Q3D framework, rather than 2-D CRMs, has positive impacts on the simulation of wind fields but does not substantially change the simulated precipitation.

A simple and accurate rule-based modeling framework for simulation of autocrine/paracrine stimulation of glioblastoma cell motility and proliferation by L1CAM in 2-D culture.

PubMed

Caccavale, Justin; Fiumara, David; Stapf, Michael; Sweitzer, Liedeke; Anderson, Hannah J; Gorky, Jonathan; Dhurjati, Prasad; Galileo, Deni S

2017-12-11

Glioblastoma multiforme (GBM) is a devastating brain cancer for which there is no known cure. Its malignancy is due to rapid cell division along with high motility and invasiveness of cells into the brain tissue. Simple 2-dimensional laboratory assays (e.g., a scratch assay) commonly are used to measure the effects of various experimental perturbations, such as treatment with chemical inhibitors. Several mathematical models have been developed to aid the understanding of the motile behavior and proliferation of GBM cells. However, many are mathematically complicated, look at multiple interdependent phenomena, and/or use modeling software not freely available to the research community. These attributes make the adoption of models and simulations of even simple 2-dimensional cell behavior an uncommon practice by cancer cell biologists. Herein, we developed an accurate, yet simple, rule-based modeling framework to describe the in vitro behavior of GBM cells that are stimulated by the L1CAM protein using freely available NetLogo software. In our model L1CAM is released by cells to act through two cell surface receptors and a point of signaling convergence to increase cell motility and proliferation. A simple graphical interface is provided so that changes can be made easily to several parameters controlling cell behavior, and behavior of the cells is viewed both pictorially and with dedicated graphs. We fully describe the hierarchical rule-based modeling framework, show simulation results under several settings, describe the accuracy compared to experimental data, and discuss the potential usefulness for predicting future experimental outcomes and for use as a teaching tool for cell biology students. It is concluded that this simple modeling framework and its simulations accurately reflect much of the GBM cell motility behavior observed experimentally in vitro in the laboratory. Our framework can be modified easily to suit the needs of investigators interested in other similar intrinsic or extrinsic stimuli that influence cancer or other cell behavior. This modeling framework of a commonly used experimental motility assay (scratch assay) should be useful to both researchers of cell motility and students in a cell biology teaching laboratory.

Audit Workplace Simulations as a Methodology to Increase Undergraduates' Awareness of Competences

ERIC Educational Resources Information Center

Bautista-Mesa, Rafael; Molina Sánchez, Horacio; Ramírez Sobrino, Jesús Nicolás

2018-01-01

This paper describes an audit workplace simulation and investigates its effects on students' perceptions of competences, required as important in the auditing industry. Within the competence-based teaching framework, this training activity involves cooperative learning as it combines first-undergraduate and senior students within one team. First,…

Simulation and the Need for Practice in Teacher Preparation

ERIC Educational Resources Information Center

Girod, Mark; Girod, Gerald R.

2008-01-01

Recognizing the power of high quality practice in teacher preparation, a web-based simulation called Cook School District was designed to allow teacher candidates to practice the skills necessary to connect their teaching to the learning of all children employing the framework of teacher work samples (TWS). Pilot study data comparing simulation…

A framework for the use of agent based modeling to simulate inter- and intraindividual variation in human behaviors

EPA Science Inventory

Simulation of human behavior in exposure modeling is a complex task. Traditionally, inter-individual variation in human activity has been modeled by drawing from a pool of single day time-activity diaries such as the US EPA Consolidated Human Activity Database (CHAD). Here, an ag...

Framework for incorporating simulation into urology training.

PubMed

Arora, Sonal; Lamb, Benjamin; Undre, Shabnam; Kneebone, Roger; Darzi, Ara; Sevdalis, Nick

2011-03-01

• Changes to working hours, new technologies and increased accountability have rendered the need for alternative training environments for urologists. • Simulation offers a promising arena for learning to take place in a safe, realistic setting. • Despite its benefits, the incorporation of simulation into urological training programmes remains minimal. • The current status and future directions of simulation for training in technical and non-technical skills are reviewed as they pertain to urology. • A framework is presented for how simulation-based training could be incorporated into the entire urological curriculum. • The literature on simulation in technical and non-technical skills training is reviewed, with a specific focus upon urology. • To fully integrate simulation into a training curriculum, its possibilities for addressing all the competencies required by a urologist must be realized. • At an early stage of training, simulation has been used to develop basic technical skills and cognitive skills, such as decision-making and communication. • At an intermediate stage, the studies focus upon more advanced technical skills learnt with virtual reality simulators. • Non-technical skills training would include leadership and could be delivered with in situ models. • At the final stage, experienced trainees can practise technical and non-technical skills in full crisis simulations situated within a fully-simulated operating rooms. • Simulation can provide training in the technical and non-technical skills required to be a competent urologist. • The framework presented may guide how best to incorporate simulation into training curricula. • Future work should determine whether acquired skills transfer to clinical practice and improve patient care. © 2010 THE AUTHORS. BJU INTERNATIONAL © 2010 BJU INTERNATIONAL.

Bayesian integration of flux tower data into a process-based simulator for quantifying uncertainty in simulated output

NASA Astrophysics Data System (ADS)

Raj, Rahul; van der Tol, Christiaan; Hamm, Nicholas Alexander Samuel; Stein, Alfred

2018-01-01

Parameters of a process-based forest growth simulator are difficult or impossible to obtain from field observations. Reliable estimates can be obtained using calibration against observations of output and state variables. In this study, we present a Bayesian framework to calibrate the widely used process-based simulator Biome-BGC against estimates of gross primary production (GPP) data. We used GPP partitioned from flux tower measurements of a net ecosystem exchange over a 55-year-old Douglas fir stand as an example. The uncertainties of both the Biome-BGC parameters and the simulated GPP values were estimated. The calibrated parameters leaf and fine root turnover (LFRT), ratio of fine root carbon to leaf carbon (FRC : LC), ratio of carbon to nitrogen in leaf (C : Nleaf), canopy water interception coefficient (Wint), fraction of leaf nitrogen in RuBisCO (FLNR), and effective soil rooting depth (SD) characterize the photosynthesis and carbon and nitrogen allocation in the forest. The calibration improved the root mean square error and enhanced Nash-Sutcliffe efficiency between simulated and flux tower daily GPP compared to the uncalibrated Biome-BGC. Nevertheless, the seasonal cycle for flux tower GPP was not reproduced exactly and some overestimation in spring and underestimation in summer remained after calibration. We hypothesized that the phenology exhibited a seasonal cycle that was not accurately reproduced by the simulator. We investigated this by calibrating the Biome-BGC to each month's flux tower GPP separately. As expected, the simulated GPP improved, but the calibrated parameter values suggested that the seasonal cycle of state variables in the simulator could be improved. It was concluded that the Bayesian framework for calibration can reveal features of the modelled physical processes and identify aspects of the process simulator that are too rigid.

An ice sheet model validation framework for the Greenland ice sheet

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

Price, Stephen F.; Hoffman, Matthew J.; Bonin, Jennifer A.

We propose a new ice sheet model validation framework the Cryospheric Model Comparison Tool (CMCT) that takes advantage of ice sheet altimetry and gravimetry observations collected over the past several decades and is applied here to modeling of the Greenland ice sheet. We use realistic simulations performed with the Community Ice Sheet Model (CISM) along with two idealized, non-dynamic models to demonstrate the framework and its use. Dynamic simulations with CISM are forced from 1991 to 2013 using combinations of reanalysis-based surface mass balance and observations of outlet glacier flux change. We propose and demonstrate qualitative and quanti- tative metricsmore » for use in evaluating the different model simulations against the observations. We find 10 that the altimetry observations used here are largely ambiguous in terms of their ability to distinguish one simulation from another. Based on basin- and whole-ice-sheet scale metrics, the model initial condition as well as output from idealized and dynamic models all provide an equally reasonable representation of the ice sheet surface (mean elevation differences of <1 m). This is likely due to their short period of record, biases inherent to digital elevation models used for model initial conditions, and biases resulting from firn dynamics, which are not explicitly accounted for in the models or observations. On the other hand, we find that the gravimetry observations used here are able to unambiguously distinguish between simulations of varying complexity, and along with the CMCT, can provide a quantitative score for assessing a particular model and/or simulation. The new framework demonstrates that our proposed metrics can distinguish relatively better from relatively worse simulations and that dynamic ice sheet models, when appropriately initialized and forced with the right boundary conditions, demonstrate predictive skill with respect to observed dynamic changes occurring on Greenland over the past few decades. An extensible design will allow for continued use of the CMCT as future altimetry, gravimetry, and other remotely sensed data become available for use in ice sheet model validation.« less

An ice sheet model validation framework for the Greenland ice sheet

DOE PAGES

Price, Stephen F.; Hoffman, Matthew J.; Bonin, Jennifer A.; ...

2017-01-17

We propose a new ice sheet model validation framework the Cryospheric Model Comparison Tool (CMCT) that takes advantage of ice sheet altimetry and gravimetry observations collected over the past several decades and is applied here to modeling of the Greenland ice sheet. We use realistic simulations performed with the Community Ice Sheet Model (CISM) along with two idealized, non-dynamic models to demonstrate the framework and its use. Dynamic simulations with CISM are forced from 1991 to 2013 using combinations of reanalysis-based surface mass balance and observations of outlet glacier flux change. We propose and demonstrate qualitative and quanti- tative metricsmore » for use in evaluating the different model simulations against the observations. We find 10 that the altimetry observations used here are largely ambiguous in terms of their ability to distinguish one simulation from another. Based on basin- and whole-ice-sheet scale metrics, the model initial condition as well as output from idealized and dynamic models all provide an equally reasonable representation of the ice sheet surface (mean elevation differences of <1 m). This is likely due to their short period of record, biases inherent to digital elevation models used for model initial conditions, and biases resulting from firn dynamics, which are not explicitly accounted for in the models or observations. On the other hand, we find that the gravimetry observations used here are able to unambiguously distinguish between simulations of varying complexity, and along with the CMCT, can provide a quantitative score for assessing a particular model and/or simulation. The new framework demonstrates that our proposed metrics can distinguish relatively better from relatively worse simulations and that dynamic ice sheet models, when appropriately initialized and forced with the right boundary conditions, demonstrate predictive skill with respect to observed dynamic changes occurring on Greenland over the past few decades. An extensible design will allow for continued use of the CMCT as future altimetry, gravimetry, and other remotely sensed data become available for use in ice sheet model validation.« less

Compromise-based Robust Prioritization of Climate Change Adaptation Strategies for Watershed Management

NASA Astrophysics Data System (ADS)

Kim, Y.; Chung, E. S.

2014-12-01

This study suggests a robust prioritization framework for climate change adaptation strategies under multiple climate change scenarios with a case study of selecting sites for reusing treated wastewater (TWW) in a Korean urban watershed. The framework utilizes various multi-criteria decision making techniques, including the VIKOR method and the Shannon entropy-based weights. In this case study, the sustainability of TWW use is quantified with indicator-based approaches with the DPSIR framework, which considers both hydro-environmental and socio-economic aspects of the watershed management. Under the various climate change scenarios, the hydro-environmental responses to reusing TWW in potential alternative sub-watersheds are determined using the Hydrologic Simulation Program in Fortran (HSPF). The socio-economic indicators are obtained from the statistical databases. Sustainability scores for multiple scenarios are estimated individually and then integrated with the proposed approach. At last, the suggested framework allows us to prioritize adaptation strategies in a robust manner with varying levels of compromise between utility-based and regret-based strategies.

An Empirical Agent-Based Model to Simulate the Adoption of Water Reuse Using the Social Amplification of Risk Framework.

PubMed

Kandiah, Venu; Binder, Andrew R; Berglund, Emily Z

2017-10-01

Water reuse can serve as a sustainable alternative water source for urban areas. However, the successful implementation of large-scale water reuse projects depends on community acceptance. Because of the negative perceptions that are traditionally associated with reclaimed water, water reuse is often not considered in the development of urban water management plans. This study develops a simulation model for understanding community opinion dynamics surrounding the issue of water reuse, and how individual perceptions evolve within that context, which can help in the planning and decision-making process. Based on the social amplification of risk framework, our agent-based model simulates consumer perceptions, discussion patterns, and their adoption or rejection of water reuse. The model is based on the "risk publics" model, an empirical approach that uses the concept of belief clusters to explain the adoption of new technology. Each household is represented as an agent, and parameters that define their behavior and attributes are defined from survey data. Community-level parameters-including social groups, relationships, and communication variables, also from survey data-are encoded to simulate the social processes that influence community opinion. The model demonstrates its capabilities to simulate opinion dynamics and consumer adoption of water reuse. In addition, based on empirical data, the model is applied to investigate water reuse behavior in different regions of the United States. Importantly, our results reveal that public opinion dynamics emerge differently based on membership in opinion clusters, frequency of discussion, and the structure of social networks. © 2017 Society for Risk Analysis.

Soft tissue deformation for surgical simulation: a position-based dynamics approach.

PubMed

Camara, Mafalda; Mayer, Erik; Darzi, Ara; Pratt, Philip

2016-06-01

To assist the rehearsal and planning of robot-assisted partial nephrectomy, a real-time simulation platform is presented that allows surgeons to visualise and interact with rapidly constructed patient-specific biomechanical models of the anatomical regions of interest. Coupled to a framework for volumetric deformation, the platform furthermore simulates intracorporeal 2D ultrasound image acquisition, using preoperative imaging as the data source. This not only facilitates the planning of optimal transducer trajectories and viewpoints, but can also act as a validation context for manually operated freehand 3D acquisitions and reconstructions. The simulation platform was implemented within the GPU-accelerated NVIDIA FleX position-based dynamics framework. In order to validate the model and determine material properties and other simulation parameter values, a porcine kidney with embedded fiducial beads was CT-scanned and segmented. Acquisitions for the rest position and three different levels of probe-induced deformation were collected. Optimal values of the cluster stiffness coefficients were determined for a range of different particle radii, where the objective function comprised the mean distance error between real and simulated fiducial positions over the sequence of deformations. The mean fiducial error at each deformation stage was found to be compatible with the level of ultrasound probe calibration error typically observed in clinical practice. Furthermore, the simulation exhibited unconditional stability on account of its use of clustered shape-matching constraints. A novel position-based dynamics implementation of soft tissue deformation has been shown to facilitate several desirable simulation characteristics: real-time performance, unconditional stability, rapid model construction enabling patient-specific behaviour and accuracy with respect to reference CT images.

Progress towards and barriers to implementation of a risk framework for US federal wildland fire policy and decision making

Treesearch

David C. Calkin; Mark A. Finney; Alan A. Ager; Matthew P. Thompson; Krista M. Gebert

2011-01-01

In this paper we review progress towards the implementation of a riskmanagement framework for US federal wildland fire policy and operations. We first describe new developments in wildfire simulation technology that catalyzed the development of risk-based decision support systems for strategic wildfire management. These systems include new analytical methods to measure...

A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs.

PubMed

Yan, Yiming; Su, Nan; Zhao, Chunhui; Wang, Liguo

2017-09-19

In this paper, a novel framework of the 3D reconstruction of buildings is proposed, focusing on remote sensing super-generalized stereo-pairs (SGSPs). As we all know, 3D reconstruction cannot be well performed using nonstandard stereo pairs, since reliable stereo matching could not be achieved when the image-pairs are collected at a great difference of views, and we always failed to obtain dense 3D points for regions of buildings, and cannot do further 3D shape reconstruction. We defined SGSPs as two or more optical images collected in less constrained views but covering the same buildings. It is even more difficult to reconstruct the 3D shape of a building by SGSPs using traditional frameworks. As a result, a dynamic multi-projection-contour approximating (DMPCA) framework was introduced for SGSP-based 3D reconstruction. The key idea is that we do an optimization to find a group of parameters of a simulated 3D model and use a binary feature-image that minimizes the total differences between projection-contours of the building in the SGSPs and that in the simulated 3D model. Then, the simulated 3D model, defined by the group of parameters, could approximate the actual 3D shape of the building. Certain parameterized 3D basic-unit-models of typical buildings were designed, and a simulated projection system was established to obtain a simulated projection-contour in different views. Moreover, the artificial bee colony algorithm was employed to solve the optimization. With SGSPs collected by the satellite and our unmanned aerial vehicle, the DMPCA framework was verified by a group of experiments, which demonstrated the reliability and advantages of this work.

Modeling and simulating industrial land-use evolution in Shanghai, China

NASA Astrophysics Data System (ADS)

Qiu, Rongxu; Xu, Wei; Zhang, John; Staenz, Karl

2018-01-01

This study proposes a cellular automata-based Industrial and Residential Land Use Competition Model to simulate the dynamic spatial transformation of industrial land use in Shanghai, China. In the proposed model, land development activities in a city are delineated as competitions among different land-use types. The Hedonic Land Pricing Model is adopted to implement the competition framework. To improve simulation results, the Land Price Agglomeration Model was devised to simulate and adjust classic land price theory. A new evolutionary algorithm-based parameter estimation method was devised in place of traditional methods. Simulation results show that the proposed model closely resembles actual land transformation patterns and the model can not only simulate land development, but also redevelopment processes in metropolitan areas.

A hybrid simulation approach for integrating safety behavior into construction planning: An earthmoving case study.

PubMed

Goh, Yang Miang; Askar Ali, Mohamed Jawad

2016-08-01

One of the key challenges in improving construction safety and health is the management of safety behavior. From a system point of view, workers work unsafely due to system level issues such as poor safety culture, excessive production pressure, inadequate allocation of resources and time and lack of training. These systemic issues should be eradicated or minimized during planning. However, there is a lack of detailed planning tools to help managers assess the impact of their upstream decisions on worker safety behavior. Even though simulation had been used in construction planning, the review conducted in this study showed that construction safety management research had not been exploiting the potential of simulation techniques. Thus, a hybrid simulation framework is proposed to facilitate integration of safety management considerations into construction activity simulation. The hybrid framework consists of discrete event simulation (DES) as the core, but heterogeneous, interactive and intelligent (able to make decisions) agents replace traditional entities and resources. In addition, some of the cognitive processes and physiological aspects of agents are captured using system dynamics (SD) approach. The combination of DES, agent-based simulation (ABS) and SD allows a more "natural" representation of the complex dynamics in construction activities. The proposed hybrid framework was demonstrated using a hypothetical case study. In addition, due to the lack of application of factorial experiment approach in safety management simulation, the case study demonstrated sensitivity analysis and factorial experiment to guide future research. Copyright © 2015 Elsevier Ltd. All rights reserved.

Integrated Instrument Simulator Suites for Earth Science

NASA Technical Reports Server (NTRS)

Tanelli, Simone; Tao, Wei-Kuo; Matsui, Toshihisa; Hostetler, Chris; Hair, Johnathan; Butler, Carolyn; Kuo, Kwo-Sen; Niamsuwan, Noppasin; Johnson, Michael P.; Jacob, Joseph C.;

A Modular Simulation Framework for Assessing Swarm Search Models

DTIC Science & Technology

2014-09-01

SUBTITLE A MODULAR SIMULATION FRAMEWORK FOR ASSESSING SWARM SEARCH MODELS 5. FUNDING NUMBERS 6. AUTHOR(S) Blake M. Wanier 7. PERFORMING ORGANIZATION...Numerical studies demonstrate the ability to leverage the developed simulation and analysis framework to investigate three canonical swarm search models ...as benchmarks for future exploration of more sophisticated swarm search scenarios. 14. SUBJECT TERMS Swarm Search, Search Theory, Modeling Framework

Damage/fault diagnosis in an operating wind turbine under uncertainty via a vibration response Gaussian mixture random coefficient model based framework

NASA Astrophysics Data System (ADS)

Avendaño-Valencia, Luis David; Fassois, Spilios D.

2017-07-01

The study focuses on vibration response based health monitoring for an operating wind turbine, which features time-dependent dynamics under environmental and operational uncertainty. A Gaussian Mixture Model Random Coefficient (GMM-RC) model based Structural Health Monitoring framework postulated in a companion paper is adopted and assessed. The assessment is based on vibration response signals obtained from a simulated offshore 5 MW wind turbine. The non-stationarity in the vibration signals originates from the continually evolving, due to blade rotation, inertial properties, as well as the wind characteristics, while uncertainty is introduced by random variations of the wind speed within the range of 10-20 m/s. Monte Carlo simulations are performed using six distinct structural states, including the healthy state and five types of damage/fault in the tower, the blades, and the transmission, with each one of them characterized by four distinct levels. Random vibration response modeling and damage diagnosis are illustrated, along with pertinent comparisons with state-of-the-art diagnosis methods. The results demonstrate consistently good performance of the GMM-RC model based framework, offering significant performance improvements over state-of-the-art methods. Most damage types and levels are shown to be properly diagnosed using a single vibration sensor.

Distributed collaborative environments for virtual capability-based planning

NASA Astrophysics Data System (ADS)

McQuay, William K.

2003-09-01

Distributed collaboration is an emerging technology that will significantly change how decisions are made in the 21st century. Collaboration involves two or more geographically dispersed individuals working together to share and exchange data, information, knowledge, and actions. The marriage of information, collaboration, and simulation technologies provides the decision maker with a collaborative virtual environment for planning and decision support. This paper reviews research that is focusing on the applying open standards agent-based framework with integrated modeling and simulation to a new Air Force initiative in capability-based planning and the ability to implement it in a distributed virtual environment. Virtual Capability Planning effort will provide decision-quality knowledge for Air Force resource allocation and investment planning including examining proposed capabilities and cost of alternative approaches, the impact of technologies, identification of primary risk drivers, and creation of executable acquisition strategies. The transformed Air Force business processes are enabled by iterative use of constructive and virtual modeling, simulation, and analysis together with information technology. These tools are applied collaboratively via a technical framework by all the affected stakeholders - warfighter, laboratory, product center, logistics center, test center, and primary contractor.

MEqTrees Telescope and Radio-sky Simulations and CPU Benchmarking

NASA Astrophysics Data System (ADS)

Shanmugha Sundaram, G. A.

2009-09-01

MEqTrees is a Python-based implementation of the classical Measurement Equation, wherein the various 2×2 Jones matrices are parametrized representations in the spatial and sky domains for any generic radio telescope. Customized simulations of radio-source sky models and corrupt Jones terms are demonstrated based on a policy framework, with performance estimates derived for array configurations, ``dirty''-map residuals and processing power requirements for such computations on conventional platforms.

Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

NASA Astrophysics Data System (ADS)

Hadjidoukas, P. E.; Angelikopoulos, P.; Papadimitriou, C.; Koumoutsakos, P.

2015-03-01

We present Π4U, an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

Intercomparison of Streamflow Simulations between WRF-Hydro and Hydrology Laboratory-Research Distributed Hydrologic Model Frameworks

NASA Astrophysics Data System (ADS)

KIM, J.; Smith, M. B.; Koren, V.; Salas, F.; Cui, Z.; Johnson, D.

2017-12-01

The National Oceanic and Atmospheric Administration (NOAA)-National Weather Service (NWS) developed the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) framework as an initial step towards spatially distributed modeling at River Forecast Centers (RFCs). Recently, the NOAA/NWS worked with the National Center for Atmospheric Research (NCAR) to implement the National Water Model (NWM) for nationally-consistent water resources prediction. The NWM is based on the WRF-Hydro framework and is run at a 1km spatial resolution and 1-hour time step over the contiguous United States (CONUS) and contributing areas in Canada and Mexico. In this study, we compare streamflow simulations from HL-RDHM and WRF-Hydro to observations from 279 USGS stations. For streamflow simulations, HL-RDHM is run on 4km grids with the temporal resolution of 1 hour for a 5-year period (Water Years 2008-2012), using a priori parameters provided by NOAA-NWS. The WRF-Hydro streamflow simulations for the same time period are extracted from NCAR's 23 retrospective run of the NWM (version 1.0) over CONUS based on 1km grids. We choose 279 USGS stations which are relatively less affected by dams or reservoirs, in the domains of six different RFCs. We use the daily average values of simulations and observations for the convenience of comparison. The main purpose of this research is to evaluate how HL-RDHM and WRF-Hydro perform at USGS gauge stations. We compare daily time-series of observations and both simulations, and calculate the error values using a variety of error functions. Using these plots and error values, we evaluate the performances of HL-RDHM and WRF-Hydro models. Our results show a mix of model performance across geographic regions.

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

Rizzi, Silvio; Hereld, Mark; Insley, Joseph

In this work we perform in-situ visualization of molecular dynamics simulations, which can help scientists to visualize simulation output on-the-fly, without incurring storage overheads. We present a case study to couple LAMMPS, the large-scale molecular dynamics simulation code with vl3, our parallel framework for large-scale visualization and analysis. Our motivation is to identify effective approaches for covisualization and exploration of large-scale atomistic simulations at interactive frame rates.We propose a system of coupled libraries and describe its architecture, with an implementation that runs on GPU-based clusters. We present the results of strong and weak scalability experiments, as well as future researchmore » avenues based on our results.« less

On Market-Based Coordination of Thermostatically Controlled Loads With User Preference

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

Li, Sen; Zhang, Wei; Lian, Jianming

2014-12-15

This paper presents a market-based control framework to coordinate a group of autonomous Thermostatically Controlled Loads (TCL) to achieve the system-level objectives with pricing incentives. The problem is formulated as maximizing the social welfare subject to feeder power constraint. It allows the coordinator to affect the aggregated power of a group of dynamical systems, and creates an interactive market where the users and the coordinator cooperatively determine the optimal energy allocation and energy price. The optimal pricing strategy is derived, which maximizes social welfare while respecting the feeder power constraint. The bidding strategy is also designed to compute the optimalmore » price in real time (e.g., every 5 minutes) based on local device information. The coordination framework is validated with realistic simulations in GridLab-D. Extensive simulation results demonstrate that the proposed approach effectively maximizes the social welfare and decreases power congestion at key times.« less

Executing Medical Guidelines on the Web: Towards Next Generation Healthcare

NASA Astrophysics Data System (ADS)

Argüello, M.; Des, J.; Fernandez-Prieto, M. J.; Perez, R.; Paniagua, H.

There is still a lack of full integration between current Electronic Health Records (EHRs) and medical guidelines that encapsulate evidence-based medicine. Thus, general practitioners (GPs) and specialised physicians still have to read document-based medical guidelines and decide among various options for managing common non-life-threatening conditions where the selection of the most appropriate therapeutic option for each individual patient can be a difficult task. This paper presents a simulation framework and computational test-bed, called V.A.F. Framework, for supporting simulations of clinical situations that boosted the integration between Health Level Seven (HL7) and Semantic Web technologies (OWL, SWRL, and OWL-S) to achieve content layer interoperability between online clinical cases and medical guidelines, and therefore, it proves that higher integration between EHRs and evidence-based medicine can be accomplished which could lead to a next generation of healthcare systems that provide more support to physicians and increase patients' safety.

High-resolution, regional-scale crop yield simulations for the Southwestern United States

NASA Astrophysics Data System (ADS)

Stack, D. H.; Kafatos, M.; Medvigy, D.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Prasad, A. K.; Tremback, C.; Walko, R. L.; Asrar, G. R.

2012-12-01

Over the past few decades, there have been many process-based crop models developed with the goal of better understanding the impacts of climate, soils, and management decisions on crop yields. These models simulate the growth and development of crops in response to environmental drivers. Traditionally, process-based crop models have been run at the individual farm level for yield optimization and management scenario testing. Few previous studies have used these models over broader geographic regions, largely due to the lack of gridded high-resolution meteorological and soil datasets required as inputs for these data intensive process-based models. In particular, assessment of regional-scale yield variability due to climate change requires high-resolution, regional-scale, climate projections, and such projections have been unavailable until recently. The goal of this study was to create a framework for extending the Agricultural Production Systems sIMulator (APSIM) crop model for use at regional scales and analyze spatial and temporal yield changes in the Southwestern United States (CA, AZ, and NV). Using the scripting language Python, an automated pipeline was developed to link Regional Climate Model (RCM) output with the APSIM crop model, thus creating a one-way nested modeling framework. This framework was used to combine climate, soil, land use, and agricultural management datasets in order to better understand the relationship between climate variability and crop yield at the regional-scale. Three different RCMs were used to drive APSIM: OLAM, RAMS, and WRF. Preliminary results suggest that, depending on the model inputs, there is some variability between simulated RCM driven maize yields and historical yields obtained from the United States Department of Agriculture (USDA). Furthermore, these simulations showed strong non-linear correlations between yield and meteorological drivers, with critical threshold values for some of the inputs (e.g. minimum and maximum temperature), beyond which the yields were negatively affected. These results are now being used for further regional-scale yield analysis as the aforementioned framework is adaptable to multiple geographic regions and crop types.

A Novel Framework for Characterizing Exposure-Related Behaviors Using Agent-Based Models Embedded with Needs-Based Artificial Intelligence (CSSSA2016)

EPA Science Inventory

Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments. Herein we create an agent-based model (ABM) that is able to simulate longitudinal patterns in behaviors. By basing o...

High-resolution coupled physics solvers for analysing fine-scale nuclear reactor design problems.

PubMed

Mahadevan, Vijay S; Merzari, Elia; Tautges, Timothy; Jain, Rajeev; Obabko, Aleksandr; Smith, Michael; Fischer, Paul

2014-08-06

An integrated multi-physics simulation capability for the design and analysis of current and future nuclear reactor models is being investigated, to tightly couple neutron transport and thermal-hydraulics physics under the SHARP framework. Over several years, high-fidelity, validated mono-physics solvers with proven scalability on petascale architectures have been developed independently. Based on a unified component-based architecture, these existing codes can be coupled with a mesh-data backplane and a flexible coupling-strategy-based driver suite to produce a viable tool for analysts. The goal of the SHARP framework is to perform fully resolved coupled physics analysis of a reactor on heterogeneous geometry, in order to reduce the overall numerical uncertainty while leveraging available computational resources. The coupling methodology and software interfaces of the framework are presented, along with verification studies on two representative fast sodium-cooled reactor demonstration problems to prove the usability of the SHARP framework.

High-resolution coupled physics solvers for analysing fine-scale nuclear reactor design problems

PubMed Central

Mahadevan, Vijay S.; Merzari, Elia; Tautges, Timothy; Jain, Rajeev; Obabko, Aleksandr; Smith, Michael; Fischer, Paul

2014-01-01

An integrated multi-physics simulation capability for the design and analysis of current and future nuclear reactor models is being investigated, to tightly couple neutron transport and thermal-hydraulics physics under the SHARP framework. Over several years, high-fidelity, validated mono-physics solvers with proven scalability on petascale architectures have been developed independently. Based on a unified component-based architecture, these existing codes can be coupled with a mesh-data backplane and a flexible coupling-strategy-based driver suite to produce a viable tool for analysts. The goal of the SHARP framework is to perform fully resolved coupled physics analysis of a reactor on heterogeneous geometry, in order to reduce the overall numerical uncertainty while leveraging available computational resources. The coupling methodology and software interfaces of the framework are presented, along with verification studies on two representative fast sodium-cooled reactor demonstration problems to prove the usability of the SHARP framework. PMID:24982250

The Framework for Simulation of Bioinspired Security Mechanisms against Network Infrastructure Attacks

PubMed Central

Kotenko, Igor

2014-01-01

The paper outlines a bioinspired approach named “network nervous system" and methods of simulation of infrastructure attacks and protection mechanisms based on this approach. The protection mechanisms based on this approach consist of distributed prosedures of information collection and processing, which coordinate the activities of the main devices of a computer network, identify attacks, and determine nessesary countermeasures. Attacks and protection mechanisms are specified as structural models using a set-theoretic approach. An environment for simulation of protection mechanisms based on the biological metaphor is considered; the experiments demonstrating the effectiveness of the protection mechanisms are described. PMID:25254229

Covert rapid action-memory simulation (CRAMS): a hypothesis of hippocampal-prefrontal interactions for adaptive behavior.

PubMed

Wang, Jane X; Cohen, Neal J; Voss, Joel L

2015-01-01

Effective choices generally require memory, yet little is known regarding the cognitive or neural mechanisms that allow memory to influence choices. We outline a new framework proposing that covert memory processing of hippocampus interacts with action-generation processing of prefrontal cortex in order to arrive at optimal, memory-guided choices. Covert, rapid action-memory simulation (CRAMS) is proposed here as a framework for understanding cognitive and/or behavioral choices, whereby prefrontal-hippocampal interactions quickly provide multiple simulations of potential outcomes used to evaluate the set of possible choices. We hypothesize that this CRAMS process is automatic, obligatory, and covert, meaning that many cycles of action-memory simulation occur in response to choice conflict without an individual's necessary intention and generally without awareness of the simulations, leading to adaptive behavior with little perceived effort. CRAMS is thus distinct from influential proposals that adaptive memory-based behavior in humans requires consciously experienced memory-based construction of possible future scenarios and deliberate decisions among possible future constructions. CRAMS provides an account of why hippocampus has been shown to make critical contributions to the short-term control of behavior, and it motivates several new experimental approaches and hypotheses that could be used to better understand the ubiquitous role of prefrontal-hippocampal interactions in situations that require adaptively using memory to guide choices. Importantly, this framework provides a perspective that allows for testing decision-making mechanisms in a manner that translates well across human and nonhuman animal model systems. Copyright © 2014 Elsevier Inc. All rights reserved.

An efficient surrogate-based simulation-optimization method for calibrating a regional MODFLOW model

NASA Astrophysics Data System (ADS)

Chen, Mingjie; Izady, Azizallah; Abdalla, Osman A.

2017-01-01

Simulation-optimization method entails a large number of model simulations, which is computationally intensive or even prohibitive if the model simulation is extremely time-consuming. Statistical models have been examined as a surrogate of the high-fidelity physical model during simulation-optimization process to tackle this problem. Among them, Multivariate Adaptive Regression Splines (MARS), a non-parametric adaptive regression method, is superior in overcoming problems of high-dimensions and discontinuities of the data. Furthermore, the stability and accuracy of MARS model can be improved by bootstrap aggregating methods, namely, bagging. In this paper, Bagging MARS (BMARS) method is integrated to a surrogate-based simulation-optimization framework to calibrate a three-dimensional MODFLOW model, which is developed to simulate the groundwater flow in an arid hardrock-alluvium region in northwestern Oman. The physical MODFLOW model is surrogated by the statistical model developed using BMARS algorithm. The surrogate model, which is fitted and validated using training dataset generated by the physical model, can approximate solutions rapidly. An efficient Sobol' method is employed to calculate global sensitivities of head outputs to input parameters, which are used to analyze their importance for the model outputs spatiotemporally. Only sensitive parameters are included in the calibration process to further improve the computational efficiency. Normalized root mean square error (NRMSE) between measured and simulated heads at observation wells is used as the objective function to be minimized during optimization. The reasonable history match between the simulated and observed heads demonstrated feasibility of this high-efficient calibration framework.

Multi-Scale Modeling of Liquid Phase Sintering Affected by Gravity: Preliminary Analysis

NASA Technical Reports Server (NTRS)

Olevsky, Eugene; German, Randall M.

2012-01-01

A multi-scale simulation concept taking into account impact of gravity on liquid phase sintering is described. The gravity influence can be included at both the micro- and macro-scales. At the micro-scale, the diffusion mass-transport is directionally modified in the framework of kinetic Monte-Carlo simulations to include the impact of gravity. The micro-scale simulations can provide the values of the constitutive parameters for macroscopic sintering simulations. At the macro-scale, we are attempting to embed a continuum model of sintering into a finite-element framework that includes the gravity forces and substrate friction. If successful, the finite elements analysis will enable predictions relevant to space-based processing, including size and shape and property predictions. Model experiments are underway to support the models via extraction of viscosity moduli versus composition, particle size, heating rate, temperature and time.

Quasi-classical approaches to vibronic spectra revisited

NASA Astrophysics Data System (ADS)

Karsten, Sven; Ivanov, Sergei D.; Bokarev, Sergey I.; Kühn, Oliver

2018-03-01

The framework to approach quasi-classical dynamics in the electronic ground state is well established and is based on the Kubo-transformed time correlation function (TCF), being the most classical-like quantum TCF. Here we discuss whether the choice of the Kubo-transformed TCF as a starting point for simulating vibronic spectra is as unambiguous as it is for vibrational ones. Employing imaginary-time path integral techniques in combination with the interaction representation allowed us to formulate a method for simulating vibronic spectra in the adiabatic regime that takes nuclear quantum effects and dynamics on multiple potential energy surfaces into account. Further, a generalized quantum TCF is proposed that contains many well-established TCFs, including the Kubo one, as particular cases. Importantly, it also provides a framework to construct new quantum TCFs. Applying the developed methodology to the generalized TCF leads to a plethora of simulation protocols, which are based on the well-known TCFs as well as on new ones. Their performance is investigated on 1D anharmonic model systems at finite temperatures. It is shown that the protocols based on the new TCFs may lead to superior results with respect to those based on the common ones. The strategies to find the optimal approach are discussed.

Bayesian Framework for Water Quality Model Uncertainty Estimation and Risk Management

EPA Science Inventory

A formal Bayesian methodology is presented for integrated model calibration and risk-based water quality management using Bayesian Monte Carlo simulation and maximum likelihood estimation (BMCML). The primary focus is on lucid integration of model calibration with risk-based wat...

Simulation-Based Valuation of Transactive Energy Systems

DOE PAGES

Huang, Qiuhua; McDermott, Tom; Tang, Yingying; ...

2018-05-18

Transactive Energy (TE) has been recognized as a promising technique for integrating responsive loads and distributed energy resources as well as advancing grid modernization. To help the industry better understand the value of TE and compare different TE schemes in a systematic and transparent manner, a comprehensive simulation-based TE valuation method is developed. The method has the following salient features: 1) it formally defines the valuation scenarios, use cases, baseline and valuation metrics; 2) an open-source simulation platform for transactive energy systems has been developed by integrating transmission, distribution and building simulators, and plugin TE and non-TE agents through themore » Framework for Network Co-Simulation (FNCS); 3) transparency and flexibility of the valuation is enhanced through separation of simulation and valuation, base valuation metrics and final valuation metrics. In conclusion, a valuation example based on the Smart Grid Interoperability Panel (SGIP) Use Case 1 is provided to demonstrate the developed TE simulation program and the valuation method.« less

Simulation-Based Valuation of Transactive Energy Systems

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

Huang, Qiuhua; McDermott, Tom; Tang, Yingying

Transactive Energy (TE) has been recognized as a promising technique for integrating responsive loads and distributed energy resources as well as advancing grid modernization. To help the industry better understand the value of TE and compare different TE schemes in a systematic and transparent manner, a comprehensive simulation-based TE valuation method is developed. The method has the following salient features: 1) it formally defines the valuation scenarios, use cases, baseline and valuation metrics; 2) an open-source simulation platform for transactive energy systems has been developed by integrating transmission, distribution and building simulators, and plugin TE and non-TE agents through themore » Framework for Network Co-Simulation (FNCS); 3) transparency and flexibility of the valuation is enhanced through separation of simulation and valuation, base valuation metrics and final valuation metrics. In conclusion, a valuation example based on the Smart Grid Interoperability Panel (SGIP) Use Case 1 is provided to demonstrate the developed TE simulation program and the valuation method.« less

The Offline Software Framework of the NA61/SHINE Experiment

NASA Astrophysics Data System (ADS)

Sipos, Roland; Laszlo, Andras; Marcinek, Antoni; Paul, Tom; Szuba, Marek; Unger, Michael; Veberic, Darko; Wyszynski, Oskar

2012-12-01

NA61/SHINE (SHINE = SPS Heavy Ion and Neutrino Experiment) is an experiment at the CERN SPS using the upgraded NA49 hadron spectrometer. Among its physics goals are precise hadron production measurements for improving calculations of the neutrino beam flux in the T2K neutrino oscillation experiment as well as for more reliable simulations of cosmic-ray air showers. Moreover, p+p, p+Pb and nucleus+nucleus collisions will be studied extensively to allow for a study of properties of the onset of deconfinement and search for the critical point of strongly interacting matter. Currently NA61/SHINE uses the old NA49 software framework for reconstruction, simulation and data analysis. The core of this legacy framework was developed in the early 1990s. It is written in different programming and scripting languages (C, pgi-Fortran, shell) and provides several concurrent data formats for the event data model, which includes also obsolete parts. In this contribution we will introduce the new software framework, called Shine, that is written in C++ and designed to comprise three principal parts: a collection of processing modules which can be assembled and sequenced by the user via XML files, an event data model which contains all simulation and reconstruction information based on STL and ROOT streaming, and a detector description which provides data on the configuration and state of the experiment. To assure a quick migration to the Shine framework, wrappers were introduced that allow to run legacy code parts as modules in the new framework and we will present first results on the cross validation of the two frameworks.

A general framework for numerical simulation of improvised explosive device (IED)-detection scenarios using density functional theory (DFT) and terahertz (THz) spectra.

PubMed

Shabaev, Andrew; Lambrakos, Samuel G; Bernstein, Noam; Jacobs, Verne L; Finkenstadt, Daniel

2011-04-01

We have developed a general framework for numerical simulation of various types of scenarios that can occur for the detection of improvised explosive devices (IEDs) through the use of excitation using incident electromagnetic waves. A central component model of this framework is an S-matrix representation of a multilayered composite material system. Each layer of the system is characterized by an average thickness and an effective electric permittivity function. The outputs of this component are the reflectivity and the transmissivity as functions of frequency and angle of the incident electromagnetic wave. The input of the component is a parameterized analytic-function representation of the electric permittivity as a function of frequency, which is provided by another component model of the framework. The permittivity function is constructed by fitting response spectra calculated using density functional theory (DFT) and parameter adjustment according to any additional information that may be available, e.g., experimentally measured spectra or theory-based assumptions concerning spectral features. A prototype simulation is described that considers response characteristics for THz excitation of the high explosive β-HMX. This prototype simulation includes a description of a procedure for calculating response spectra using DFT as input to the Smatrix model. For this purpose, the DFT software NRLMOL was adopted. © 2011 Society for Applied Spectroscopy

An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing.

PubMed

Wu, Zujian; Pang, Wei; Coghill, George M

2015-01-01

Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.

Design of a Modular Monolithic Implicit Solver for Multi-Physics Applications

NASA Technical Reports Server (NTRS)

Carton De Wiart, Corentin; Diosady, Laslo T.; Garai, Anirban; Burgess, Nicholas; Blonigan, Patrick; Ekelschot, Dirk; Murman, Scott M.

2018-01-01

The design of a modular multi-physics high-order space-time finite-element framework is presented together with its extension to allow monolithic coupling of different physics. One of the main objectives of the framework is to perform efficient high- fidelity simulations of capsule/parachute systems. This problem requires simulating multiple physics including, but not limited to, the compressible Navier-Stokes equations, the dynamics of a moving body with mesh deformations and adaptation, the linear shell equations, non-re effective boundary conditions and wall modeling. The solver is based on high-order space-time - finite element methods. Continuous, discontinuous and C1-discontinuous Galerkin methods are implemented, allowing one to discretize various physical models. Tangent and adjoint sensitivity analysis are also targeted in order to conduct gradient-based optimization, error estimation, mesh adaptation, and flow control, adding another layer of complexity to the framework. The decisions made to tackle these challenges are presented. The discussion focuses first on the "single-physics" solver and later on its extension to the monolithic coupling of different physics. The implementation of different physics modules, relevant to the capsule/parachute system, are also presented. Finally, examples of coupled computations are presented, paving the way to the simulation of the full capsule/parachute system.

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

PubMed Central

Khan, Bilal; Dombrowski, Kirk; Saad, Mohamed

2015-01-01

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

A physically-based channel-modeling framework integrating HEC-RAS sediment transport capabilities and the USDA-ARS bank-stability and toe-erosion model (BSTEM)

USDA-ARS?s Scientific Manuscript database

Classical, one-dimensional, mobile bed, sediment-transport models simulate vertical channel adjustment, raising or lowering cross-section node elevations to simulate erosion or deposition. This approach does not account for bank erosion processes including toe scour and mass failure. In many systems...

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...

Multi-Sensor Fusion of Infrared and Electro-Optic Signals for High Resolution Night Images

PubMed Central

Huang, Xiaopeng; Netravali, Ravi; Man, Hong; Lawrence, Victor

2012-01-01

Electro-optic (EO) image sensors exhibit the properties of high resolution and low noise level at daytime, but they do not work in dark environments. Infrared (IR) image sensors exhibit poor resolution and cannot separate objects with similar temperature. Therefore, we propose a novel framework of IR image enhancement based on the information (e.g., edge) from EO images, which improves the resolution of IR images and helps us distinguish objects at night. Our framework superimposing/blending the edges of the EO image onto the corresponding transformed IR image improves their resolution. In this framework, we adopt the theoretical point spread function (PSF) proposed by Hardie et al. for the IR image, which has the modulation transfer function (MTF) of a uniform detector array and the incoherent optical transfer function (OTF) of diffraction-limited optics. In addition, we design an inverse filter for the proposed PSF and use it for the IR image transformation. The framework requires four main steps: (1) inverse filter-based IR image transformation; (2) EO image edge detection; (3) registration; and (4) blending/superimposing of the obtained image pair. Simulation results show both blended and superimposed IR images, and demonstrate that blended IR images have better quality over the superimposed images. Additionally, based on the same steps, simulation result shows a blended IR image of better quality when only the original IR image is available. PMID:23112602

Multi-sensor fusion of infrared and electro-optic signals for high resolution night images.

PubMed

Huang, Xiaopeng; Netravali, Ravi; Man, Hong; Lawrence, Victor

2012-01-01

Electro-optic (EO) image sensors exhibit the properties of high resolution and low noise level at daytime, but they do not work in dark environments. Infrared (IR) image sensors exhibit poor resolution and cannot separate objects with similar temperature. Therefore, we propose a novel framework of IR image enhancement based on the information (e.g., edge) from EO images, which improves the resolution of IR images and helps us distinguish objects at night. Our framework superimposing/blending the edges of the EO image onto the corresponding transformed IR image improves their resolution. In this framework, we adopt the theoretical point spread function (PSF) proposed by Hardie et al. for the IR image, which has the modulation transfer function (MTF) of a uniform detector array and the incoherent optical transfer function (OTF) of diffraction-limited optics. In addition, we design an inverse filter for the proposed PSF and use it for the IR image transformation. The framework requires four main steps: (1) inverse filter-based IR image transformation; (2) EO image edge detection; (3) registration; and (4) blending/superimposing of the obtained image pair. Simulation results show both blended and superimposed IR images, and demonstrate that blended IR images have better quality over the superimposed images. Additionally, based on the same steps, simulation result shows a blended IR image of better quality when only the original IR image is available.

Breaking Down Chemical Weapons by Metal-Organic Frameworks.

PubMed

Mondal, Suvendu Sekhar; Holdt, Hans-Jürgen

2016-01-04

Seek and destroy: Filtration schemes and self-detoxifying protective fabrics based on the Zr(IV)-containing metal-organic frameworks (MOFs) MOF-808 and UiO-66 doped with LiOtBu have been developed that capture and hydrolytically detoxify simulants of nerve agents and mustard gas. Both MOFs function as highly catalytic elements in these applications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Flexible Residential Smart Grid Simulation Framework

NASA Astrophysics Data System (ADS)

Xiang, Wang

Different scheduling and coordination algorithms controlling household appliances' operations can potentially lead to energy consumption reduction and/or load balancing in conjunction with different electricity pricing methods used in smart grid programs. In order to easily implement different algorithms and evaluate their efficiency against other ideas, a flexible simulation framework is desirable in both research and business fields. However, such a platform is currently lacking or underdeveloped. In this thesis, we provide a simulation framework to focus on demand side residential energy consumption coordination in response to different pricing methods. This simulation framework, equipped with an appliance consumption library using realistic values, aims to closely represent the average usage of different types of appliances. The simulation results of traditional usage yield close matching values compared to surveyed real life consumption records. Several sample coordination algorithms, pricing schemes, and communication scenarios are also implemented to illustrate the use of the simulation framework.

Analysis of the Assignment Scheduling Capability for Unmanned Aerial Vehicles (ASC-U) Simulation Tool

DTIC Science & Technology

2006-06-01

dynamic programming approach known as a “rolling horizon” approach. This method accounts for state transitions within the simulation rather than modeling ... model is based on the framework developed for Dynamic Allocation of Fires and Sensors used to evaluate factors associated with networking assets in the...of UAVs required by all types of maneuver and support brigades. (Witsken, 2004) The Modeling , Virtual Environments, and Simulations Institute

3D numerical simulations of oblique droplet impact onto a deep liquid pool

NASA Astrophysics Data System (ADS)

Gelderblom, Hanneke; Reijers, Sten A.; Gielen, Marise; Sleutel, Pascal; Lohse, Detlef; Xie, Zhihua; Pain, Christopher C.; Matar, Omar K.

2017-11-01

We study the fluid dynamics of three-dimensional oblique droplet impact, which results in phenomena that include splashing and cavity formation. An adaptive, unstructured mesh modelling framework is employed here, which can modify and adapt unstructured meshes to better represent the underlying physics of droplet dynamics, and reduce computational effort without sacrificing accuracy. The numerical framework consists of a mixed control-volume and finite-element formulation, a volume-of-fluid-type method for the interface-capturing based on a compressive control-volume advection method. The framework also features second-order finite-element methods, and a force-balanced algorithm for the surface tension implementation, minimising the spurious velocities often found in many simulations involving capillary-driven flows. The numerical results generated using this framework are compared with high-speed images of the interfacial shapes of the deformed droplet, and the cavity formed upon impact, yielding good agreement. EPSRC, UK, MEMPHIS program Grant (EP/K003976/1), RAEng Research Chair (OKM).

A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints.

PubMed

Sundharam, Sakthivel Manikandan; Navet, Nicolas; Altmeyer, Sebastian; Havet, Lionel

2018-02-20

Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system.

A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints

PubMed Central

Navet, Nicolas; Havet, Lionel

2018-01-01

Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system. PMID:29461489

A Generalized Framework for Different Drought Indices: Testing its Suitability in a Simulation of the last two Millennia for Europe

NASA Astrophysics Data System (ADS)

Raible, Christoph C.; Baerenbold, Oliver; Gomez-Navarro, Juan Jose

2016-04-01

Over the past decades, different drought indices have been suggested in the literature. This study tackles the problem of how to characterize drought by defining a general framework and proposing a generalized family of drought indices that is flexible regarding the use of different water balance models. The sensitivity of various indices and its skill to represent drought conditions is evaluated using a regional model simulation in Europe spanning the last two millennia as test bed. The framework combines an exponentially damped memory with a normalization method based on quantile mapping. Both approaches are more robust and physically meaningful compared to the existing methods used to define drought indices. Still, framework is flexible with respect to the water balance, enabling users to adapt the index formulation to the data availability of different locations. Based on the framework, indices with different complex water balances are compared with each other. The comparison shows that a drought index considering only precipitation in the water balance is sufficient for Western to Central Europe. However, in the Mediterranean temperature effects via evapotranspiration need to be considered in order to produce meaningful indices representative of actual water deficit. Similarly, our results indicate that in north-eastern Europe and Scandinavia, snow and runoff effects needs to be considered in the index definition to obtain accurate results.

A Web-based Distributed Voluntary Computing Platform for Large Scale Hydrological Computations

NASA Astrophysics Data System (ADS)

Demir, I.; Agliamzanov, R.

2014-12-01

Distributed volunteer computing can enable researchers and scientist to form large parallel computing environments to utilize the computing power of the millions of computers on the Internet, and use them towards running large scale environmental simulations and models to serve the common good of local communities and the world. Recent developments in web technologies and standards allow client-side scripting languages to run at speeds close to native application, and utilize the power of Graphics Processing Units (GPU). Using a client-side scripting language like JavaScript, we have developed an open distributed computing framework that makes it easy for researchers to write their own hydrologic models, and run them on volunteer computers. Users will easily enable their websites for visitors to volunteer sharing their computer resources to contribute running advanced hydrological models and simulations. Using a web-based system allows users to start volunteering their computational resources within seconds without installing any software. The framework distributes the model simulation to thousands of nodes in small spatial and computational sizes. A relational database system is utilized for managing data connections and queue management for the distributed computing nodes. In this paper, we present a web-based distributed volunteer computing platform to enable large scale hydrological simulations and model runs in an open and integrated environment.

Collaborative enterprise and virtual prototyping (CEVP): a product-centric approach to distributed simulation

NASA Astrophysics Data System (ADS)

Saunders, Vance M.

1999-06-01

The downsizing of the Department of Defense (DoD) and the associated reduction in budgets has re-emphasized the need for commonality, reuse, and standards with respect to the way DoD does business. DoD has implemented significant changes in how it buys weapon systems. The new emphasis is on concurrent engineering with Integrated Product and Process Development and collaboration with Integrated Product Teams. The new DoD vision includes Simulation Based Acquisition (SBA), a process supported by robust, collaborative use of simulation technology that is integrated across acquisition phases and programs. This paper discusses the Air Force Research Laboratory's efforts to use Modeling and Simulation (M&S) resources within a Collaborative Enterprise Environment to support SBA and other Collaborative Enterprise and Virtual Prototyping (CEVP) applications. The paper will discuss four technology areas: (1) a Processing Ontology that defines a hierarchically nested set of collaboration contexts needed to organize and support multi-disciplinary collaboration using M&S, (2) a partial taxonomy of intelligent agents needed to manage different M&S resource contributions to advancing the state of product development, (3) an agent- based process for interfacing disparate M&S resources into a CEVP framework, and (4) a Model-View-Control based approach to defining `a new way of doing business' for users of CEVP frameworks/systems.

Action Recommendation for Cyber Resilience

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

Choudhury, Sutanay; Rodriguez, Luke R.; Curtis, Darren S.

2015-09-01

This paper presents an unifying graph-based model for representing the infrastructure, behavior and missions of an enterprise. We describe how the model can be used to achieve resiliency against a wide class of failures and attacks. We introduce an algorithm for recommending resilience establishing actions based on dynamic updates to the models. Without loss of generality, we show the effectiveness of the algorithm for preserving latency based quality of service (QoS). Our models and the recommendation algorithms are implemented in a software framework that we seek to release as an open source framework for simulating resilient cyber systems.

Vehicle security encryption based on unlicensed encryption

NASA Astrophysics Data System (ADS)

Huang, Haomin; Song, Jing; Xu, Zhijia; Ding, Xiaoke; Deng, Wei

2018-03-01

The current vehicle key is easy to be destroyed and damage, proposing the use of elliptical encryption algorithm is improving the reliability of vehicle security system. Based on the encryption rules of elliptic curve, the chip's framework and hardware structure are designed, then the chip calculation process simulation has been analyzed by software. The simulation has been achieved the expected target. Finally, some issues pointed out in the data calculation about the chip's storage control and other modules.

Simulation-Based Extreme Value Marked Correlations in Fatigue of Advanced Engineering Alloys (PREPRINT)

DTIC Science & Technology

2010-04-01

000 the response of damage dependent processes like fatigue crack formation, a framework is needed that accounts for the extreme value life...many different damage processes (e.g. fatigue, creep, fracture). In this work, multiple material volumes for both IN100 and Ti-6Al-4V are simulated via...polycrystalline P/M Ni-base superalloy IN100 Typically, fatigue damage formation in polycrystalline superalloys has been linked to the existence of

A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold Recovery in Highly Accelerated Dynamic MRI.

PubMed

Nakarmi, Ukash; Wang, Yanhua; Lyu, Jingyuan; Liang, Dong; Ying, Leslie

2017-11-01

While many low rank and sparsity-based approaches have been developed for accelerated dynamic magnetic resonance imaging (dMRI), they all use low rankness or sparsity in input space, overlooking the intrinsic nonlinear correlation in most dMRI data. In this paper, we propose a kernel-based framework to allow nonlinear manifold models in reconstruction from sub-Nyquist data. Within this framework, many existing algorithms can be extended to kernel framework with nonlinear models. In particular, we have developed a novel algorithm with a kernel-based low-rank model generalizing the conventional low rank formulation. The algorithm consists of manifold learning using kernel, low rank enforcement in feature space, and preimaging with data consistency. Extensive simulation and experiment results show that the proposed method surpasses the conventional low-rank-modeled approaches for dMRI.

Open-source Framework for Storing and Manipulation of Plasma Chemical Reaction Data

NASA Astrophysics Data System (ADS)

Jenkins, T. G.; Averkin, S. N.; Cary, J. R.; Kruger, S. E.

2017-10-01

We present a new open-source framework for storage and manipulation of plasma chemical reaction data that has emerged from our in-house project MUNCHKIN. This framework consists of python scripts and C + + programs. It stores data in an SQL data base for fast retrieval and manipulation. For example, it is possible to fit cross-section data into most widely used analytical expressions, calculate reaction rates for Maxwellian distribution functions of colliding particles, and fit them into different analytical expressions. Another important feature of this framework is the ability to calculate transport properties based on the cross-section data and supplied distribution functions. In addition, this framework allows the export of chemical reaction descriptions in LaTeX format for ease of inclusion in scientific papers. With the help of this framework it is possible to generate corresponding VSim (Particle-In-Cell simulation code) and USim (unstructured multi-fluid code) input blocks with appropriate cross-sections.

A Novel Switching-Based Control Framework for Improved Task Performance in Teleoperation System With Asymmetric Time-Varying Delays.

PubMed

Zhai, Di-Hua; Xia, Yuanqing

2018-02-01

This paper addresses the adaptive control for task-space teleoperation systems with constrained predefined synchronization error, where a novel switched control framework is investigated. Based on multiple Lyapunov-Krasovskii functionals method, the stability of the resulting closed-loop system is established in the sense of state-independent input-to-output stability. Compared with previous work, the developed method can simultaneously handle the unknown kinematics/dynamics, asymmetric varying time delays, and prescribed performance control in a unified framework. It is shown that the developed controller can guarantee the prescribed transient-state and steady-state synchronization performances between the master and slave robots, which is demonstrated by the simulation study.

What are the assets and weaknesses of HFO detectors? A benchmark framework based on realistic simulations

PubMed Central

Pizzo, Francesca; Bartolomei, Fabrice; Wendling, Fabrice; Bénar, Christian-George

2017-01-01

High-frequency oscillations (HFO) have been suggested as biomarkers of epileptic tissues. While visual marking of these short and small oscillations is tedious and time-consuming, automatic HFO detectors have not yet met a large consensus. Even though detectors have been shown to perform well when validated against visual marking, the large number of false detections due to their lack of robustness hinder their clinical application. In this study, we developed a validation framework based on realistic and controlled simulations to quantify precisely the assets and weaknesses of current detectors. We constructed a dictionary of synthesized elements—HFOs and epileptic spikes—from different patients and brain areas by extracting these elements from the original data using discrete wavelet transform coefficients. These elements were then added to their corresponding simulated background activity (preserving patient- and region- specific spectra). We tested five existing detectors against this benchmark. Compared to other studies confronting detectors, we did not only ranked them according their performance but we investigated the reasons leading to these results. Our simulations, thanks to their realism and their variability, enabled us to highlight unreported issues of current detectors: (1) the lack of robust estimation of the background activity, (2) the underestimated impact of the 1/f spectrum, and (3) the inadequate criteria defining an HFO. We believe that our benchmark framework could be a valuable tool to translate HFOs into a clinical environment. PMID:28406919

MRXCAT: Realistic numerical phantoms for cardiovascular magnetic resonance

PubMed Central

2014-01-01

Background Computer simulations are important for validating novel image acquisition and reconstruction strategies. In cardiovascular magnetic resonance (CMR), numerical simulations need to combine anatomical information and the effects of cardiac and/or respiratory motion. To this end, a framework for realistic CMR simulations is proposed and its use for image reconstruction from undersampled data is demonstrated. Methods The extended Cardiac-Torso (XCAT) anatomical phantom framework with various motion options was used as a basis for the numerical phantoms. Different tissue, dynamic contrast and signal models, multiple receiver coils and noise are simulated. Arbitrary trajectories and undersampled acquisition can be selected. The utility of the framework is demonstrated for accelerated cine and first-pass myocardial perfusion imaging using k-t PCA and k-t SPARSE. Results MRXCAT phantoms allow for realistic simulation of CMR including optional cardiac and respiratory motion. Example reconstructions from simulated undersampled k-t parallel imaging demonstrate the feasibility of simulated acquisition and reconstruction using the presented framework. Myocardial blood flow assessment from simulated myocardial perfusion images highlights the suitability of MRXCAT for quantitative post-processing simulation. Conclusion The proposed MRXCAT phantom framework enables versatile and realistic simulations of CMR including breathhold and free-breathing acquisitions. PMID:25204441

Argonne Simulation Framework for Intelligent Transportation Systems

DOT National Transportation Integrated Search

1996-01-01

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 distribu...

Crowdsourcing: A Primer and Its implications for Systems Engineering

DTIC Science & Technology

2012-08-01

detailing areas to be improved within current crowdsourcing frameworks. Finally, an agent-based simulation using machine learning techniques is defined, preliminary results are presented, and future research directions are described.

Quantifying the impact of respiratory-gated 4D CT acquisition on thoracic image quality: A digital phantom study

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

Bernatowicz, K., E-mail: kingab@student.ethz.ch; Knopf, A.; Lomax, A.

Purpose: Prospective respiratory-gated 4D CT has been shown to reduce tumor image artifacts by up to 50% compared to conventional 4D CT. However, to date no studies have quantified the impact of gated 4D CT on normal lung tissue imaging, which is important in performing dose calculations based on accurate estimates of lung volume and structure. To determine the impact of gated 4D CT on thoracic image quality, the authors developed a novel simulation framework incorporating a realistic deformable digital phantom driven by patient tumor motion patterns. Based on this framework, the authors test the hypothesis that respiratory-gated 4D CTmore » can significantly reduce lung imaging artifacts. Methods: Our simulation framework synchronizes the 4D extended cardiac torso (XCAT) phantom with tumor motion data in a quasi real-time fashion, allowing simulation of three 4D CT acquisition modes featuring different levels of respiratory feedback: (i) “conventional” 4D CT that uses a constant imaging and couch-shift frequency, (ii) “beam paused” 4D CT that interrupts imaging to avoid oversampling at a given couch position and respiratory phase, and (iii) “respiratory-gated” 4D CT that triggers acquisition only when the respiratory motion fulfills phase-specific displacement gating windows based on prescan breathing data. Our framework generates a set of ground truth comparators, representing the average XCAT anatomy during beam-on for each of ten respiratory phase bins. Based on this framework, the authors simulated conventional, beam-paused, and respiratory-gated 4D CT images using tumor motion patterns from seven lung cancer patients across 13 treatment fractions, with a simulated 5.5 cm{sup 3} spherical lesion. Normal lung tissue image quality was quantified by comparing simulated and ground truth images in terms of overall mean square error (MSE) intensity difference, threshold-based lung volume error, and fractional false positive/false negative rates. Results: Averaged across all simulations and phase bins, respiratory-gating reduced overall thoracic MSE by 46% compared to conventional 4D CT (p ∼ 10{sup −19}). Gating leads to small but significant (p < 0.02) reductions in lung volume errors (1.8%–1.4%), false positives (4.0%–2.6%), and false negatives (2.7%–1.3%). These percentage reductions correspond to gating reducing image artifacts by 24–90 cm{sup 3} of lung tissue. Similar to earlier studies, gating reduced patient image dose by up to 22%, but with scan time increased by up to 135%. Beam paused 4D CT did not significantly impact normal lung tissue image quality, but did yield similar dose reductions as for respiratory-gating, without the added cost in scanning time. Conclusions: For a typical 6 L lung, respiratory-gated 4D CT can reduce image artifacts affecting up to 90 cm{sup 3} of normal lung tissue compared to conventional acquisition. This image improvement could have important implications for dose calculations based on 4D CT. Where image quality is less critical, beam paused 4D CT is a simple strategy to reduce imaging dose without sacrificing acquisition time.« less

Ftmp-Based Simulation of Twin Nucleation and Substructure Evolution Under Hypervelocity Impact

NASA Astrophysics Data System (ADS)

Okuda, Tatsuya; Imiya, Kazuhiro; Hasebe, Tadashi

2013-01-01

The deformation twinning model based on Field Theory of Multiscale Plasticity (FTMP) represents the twin degrees of freedom with the incompatibility tensor, which is incorporated into the hardening law of the FTMP-based crystalline plasticity framework. The model is further implemented into a finite element code. In the present study, the model is adapted to a single slip-oriented FCC single crystal sample, and preliminary simulations are conducted under static conditions to confirm the model's basic capabilities. The simulation results exhibit nucleation and growth of twinned regions, accompanied by serrated stress response and overall softening. Simulations under hypervelocity impact conditions are also conducted to investigate the model's descriptive capabilities of induced complex substructures composing of both twins and dislocations. The simulated nucleation of twins is examined in detail by using duality diagrams in terms of the flow-evolutionary hypothesis.

Mirrored continuum and molecular scale simulations of the ignition of gamma phase RDX

NASA Astrophysics Data System (ADS)

Stewart, D. Scott; Chaudhuri, Santanu; Joshi, Kaushik; Lee, Kibaek

2017-01-01

We describe the ignition of an explosive crystal of gamma-phase RDX due to a thermal hot spot with reactive molecular dynamics (RMD), with first-principles trained, reactive force field based molecular potentials that represents an extremely complex reaction network. The RMD simulation is analyzed by sorting molecular product fragments into high and low molecular weight groups, to represent identifiable components that can be interpreted by a continuum model. A continuum model based on a Gibbs formulation has a single temperature and stress state for the mixture. The continuum simulation that mirrors the atomistic simulation allows us to study the atomistic simulation in the familiar physical chemistry framework and provides an essential, continuum/atomistic link.

GridLAB-D: An Agent-Based Simulation Framework for Smart Grids

DOE PAGES

Chassin, David P.; Fuller, Jason C.; Djilali, Ned

2014-01-01

Simulation of smart grid technologies requires a fundamentally new approach to integrated modeling of power systems, energy markets, building technologies, and the plethora of other resources and assets that are becoming part of modern electricity production, delivery, and consumption systems. As a result, the US Department of Energy’s Office of Electricity commissioned the development of a new type of power system simulation tool called GridLAB-D that uses an agent-based approach to simulating smart grids. This paper presents the numerical methods and approach to time-series simulation used by GridLAB-D and reviews applications in power system studies, market design, building control systemmore » design, and integration of wind power in a smart grid.« less

GridLAB-D: An Agent-Based Simulation Framework for Smart Grids

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

Chassin, David P.; Fuller, Jason C.; Djilali, Ned

2014-06-23

Simulation of smart grid technologies requires a fundamentally new approach to integrated modeling of power systems, energy markets, building technologies, and the plethora of other resources and assets that are becoming part of modern electricity production, delivery, and consumption systems. As a result, the US Department of Energy’s Office of Electricity commissioned the development of a new type of power system simulation tool called GridLAB-D that uses an agent-based approach to simulating smart grids. This paper presents the numerical methods and approach to time-series simulation used by GridLAB-D and reviews applications in power system studies, market design, building control systemmore » design, and integration of wind power in a smart grid.« less

Reliability based design optimization: Formulations and methodologies

NASA Astrophysics Data System (ADS)

Agarwal, Harish

Modern products ranging from simple components to complex systems should be designed to be optimal and reliable. The challenge of modern engineering is to ensure that manufacturing costs are reduced and design cycle times are minimized while achieving requirements for performance and reliability. If the market for the product is competitive, improved quality and reliability can generate very strong competitive advantages. Simulation based design plays an important role in designing almost any kind of automotive, aerospace, and consumer products under these competitive conditions. Single discipline simulations used for analysis are being coupled together to create complex coupled simulation tools. This investigation focuses on the development of efficient and robust methodologies for reliability based design optimization in a simulation based design environment. Original contributions of this research are the development of a novel efficient and robust unilevel methodology for reliability based design optimization, the development of an innovative decoupled reliability based design optimization methodology, the application of homotopy techniques in unilevel reliability based design optimization methodology, and the development of a new framework for reliability based design optimization under epistemic uncertainty. The unilevel methodology for reliability based design optimization is shown to be mathematically equivalent to the traditional nested formulation. Numerical test problems show that the unilevel methodology can reduce computational cost by at least 50% as compared to the nested approach. The decoupled reliability based design optimization methodology is an approximate technique to obtain consistent reliable designs at lesser computational expense. Test problems show that the methodology is computationally efficient compared to the nested approach. A framework for performing reliability based design optimization under epistemic uncertainty is also developed. A trust region managed sequential approximate optimization methodology is employed for this purpose. Results from numerical test studies indicate that the methodology can be used for performing design optimization under severe uncertainty.

A risk-based framework to assess long-term effects of policy and water supply changes on water resources systems

NASA Astrophysics Data System (ADS)

Hassanzadeh, Elmira; Elshorbagy, Amin; Wheater, Howard; Gober, Patricia

2015-04-01

Climate uncertainty can affect water resources availability and management decisions. Sustainable water resources management therefore requires evaluation of policy and management decisions under a wide range of possible future water supply conditions. This study proposes a risk-based framework to integrate water supply uncertainty into a forward-looking decision making context. To apply this framework, a stochastic reconstruction scheme is used to generate a large ensemble of flow series. For the Rocky Mountain basins considered here, two key characteristics of the annual hydrograph are its annual flow volume and the timing of the seasonal flood peak. These are perturbed to represent natural randomness and potential changes due to future climate. 30-year series of perturbed flows are used as input to the SWAMP model - an integrated water resources model that simulates regional water supply-demand system and estimates economic productivity of water and other sustainability indicators, including system vulnerability and resilience. The simulation results are used to construct 2D-maps of net revenue of a particular water sector; e.g., hydropower, or for all sectors combined. Each map cell represents a risk scenario of net revenue based on a particular annual flow volume, timing of the peak flow, and 200 stochastic realizations of flow series. This framework is demonstrated for a water resources system in the Saskatchewan River Basin (SaskRB) in Saskatchewan, Canada. Critical historical drought sequences, derived from tree-ring reconstructions of several hundred years of annual river flows, are used to evaluate the system's performance (net revenue risk) under extremely low flow conditions and also to locate them on the previously produced 2D risk maps. This simulation and analysis framework is repeated under various reservoir operation strategies (e.g., maximizing flood protection or maximizing water supply security); development proposals, such as irrigation expansion; and change in energy prices. Such risk-based analysis demonstrates relative reduction/increase of risk associated with management and policy decisions and allow decision makers to explore the relative importance of policy versus natural water supply change in a water resources system.

ReSTART: A Novel Framework for Resource-Based Triage in Mass-Casualty Events.

PubMed

Mills, Alex F; Argon, Nilay T; Ziya, Serhan; Hiestand, Brian; Winslow, James

2014-01-01

Current guidelines for mass-casualty triage do not explicitly use information about resource availability. Even though this limitation has been widely recognized, how it should be addressed remains largely unexplored. The authors present a novel framework developed using operations research methods to account for resource limitations when determining priorities for transportation of critically injured patients. To illustrate how this framework can be used, they also develop two specific example methods, named ReSTART and Simple-ReSTART, both of which extend the widely adopted triage protocol Simple Triage and Rapid Treatment (START) by using a simple calculation to determine priorities based on the relative scarcity of transportation resources. The framework is supported by three techniques from operations research: mathematical analysis, optimization, and discrete-event simulation. The authors? algorithms were developed using mathematical analysis and optimization and then extensively tested using 9,000 discrete-event simulations on three distributions of patient severity (representing low, random, and high acuity). For each incident, the expected number of survivors was calculated under START, ReSTART, and Simple-ReSTART. A web-based decision support tool was constructed to help providers make prioritization decisions in the aftermath of mass-casualty incidents based on ReSTART. In simulations, ReSTART resulted in significantly lower mortality than START regardless of which severity distribution was used (paired t test, p<.01). Mean decrease in critical mortality, the percentage of immediate and delayed patients who die, was 8.5% for low-acuity distribution (range ?2.2% to 21.1%), 9.3% for random distribution (range ?0.2% to 21.2%), and 9.1% for high-acuity distribution (range ?0.7% to 21.1%). Although the critical mortality improvement due to ReSTART was different for each of the three severity distributions, the variation was less than 1 percentage point, indicating that the ReSTART policy is relatively robust to different severity distributions. Taking resource limitations into account in mass-casualty situations, triage has the potential to increase the expected number of survivors. Further validation is required before field implementation; however, the framework proposed in here can serve as the foundation for future work in this area. 2014.

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

The Integrated Plasma Simulator: A Flexible Python Framework for Coupled Multiphysics Simulation

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

Foley, Samantha S; Elwasif, Wael R; Bernholdt, David E

2011-11-01

High-fidelity coupled multiphysics simulations are an increasingly important aspect of computational science. In many domains, however, there has been very limited experience with simulations of this sort, therefore research in coupled multiphysics often requires computational frameworks with significant flexibility to respond to the changing directions of the physics and mathematics. This paper presents the Integrated Plasma Simulator (IPS), a framework designed for loosely coupled simulations of fusion plasmas. The IPS provides users with a simple component architecture into which a wide range of existing plasma physics codes can be inserted as components. Simulations can take advantage of multiple levels ofmore » parallelism supported in the IPS, and can be controlled by a high-level ``driver'' component, or by other coordination mechanisms, such as an asynchronous event service. We describe the requirements and design of the framework, and how they were implemented in the Python language. We also illustrate the flexibility of the framework by providing examples of different types of simulations that utilize various features of the IPS.« less

Visualizing dynamic geosciences phenomena using an octree-based view-dependent LOD strategy within virtual globes

NASA Astrophysics Data System (ADS)

Li, Jing; Wu, Huayi; Yang, Chaowei; Wong, David W.; Xie, Jibo

2011-09-01

Geoscientists build dynamic models to simulate various natural phenomena for a better understanding of our planet. Interactive visualizations of these geoscience models and their outputs through virtual globes on the Internet can help the public understand the dynamic phenomena related to the Earth more intuitively. However, challenges arise when the volume of four-dimensional data (4D), 3D in space plus time, is huge for rendering. Datasets loaded from geographically distributed data servers require synchronization between ingesting and rendering data. Also the visualization capability of display clients varies significantly in such an online visualization environment; some may not have high-end graphic cards. To enhance the efficiency of visualizing dynamic volumetric data in virtual globes, this paper proposes a systematic framework, in which an octree-based multiresolution data structure is implemented to organize time series 3D geospatial data to be used in virtual globe environments. This framework includes a view-dependent continuous level of detail (LOD) strategy formulated as a synchronized part of the virtual globe rendering process. Through the octree-based data retrieval process, the LOD strategy enables the rendering of the 4D simulation at a consistent and acceptable frame rate. To demonstrate the capabilities of this framework, data of a simulated dust storm event are rendered in World Wind, an open source virtual globe. The rendering performances with and without the octree-based LOD strategy are compared. The experimental results show that using the proposed data structure and processing strategy significantly enhances the visualization performance when rendering dynamic geospatial phenomena in virtual globes.

Creation and Global Deployment of a Mobile, Application-Based Cognitive Simulator for Cardiac Surgical Procedures.

PubMed

Brewer, Zachary E; Ogden, William David; Fann, James I; Burdon, Thomas A; Sheikh, Ahmad Y

Several modern learning frameworks (eg, cognitive apprenticeship, anchored instruction, and situated cognition) posit the utility of nontraditional methods for effective experiential learning. Thus, development of novel educational tools emphasizing the cognitive framework of operative sequences may be of benefit to surgical trainees. We propose the development and global deployment of an effective, mobile cognitive cardiac surgical simulator. In methods, 16 preclinical medical students were assessed. Overall, 4 separate surgical modules (sternotomy, cannulation, decannulation, and sternal closure) were created utilizing the Touch Surgery (London, UK) platform. Modules were made available to download free of charge for use on mobile devices. Usage data were collected over a 6-month period. Educational efficacy of the modules was evaluated by randomizing a cohort of medical students to either module usage or traditional, reading-based self-study, followed by a multiple-choice learning assessment tool. In results, downloads of the simulator achieved global penetrance, with highest usage in the USA, Brazil, Italy, UK, and India. Overall, 5368 unique users conducted a total of 1971 hours of simulation. Evaluation of the medical student cohort revealed significantly higher assessment scores in those randomized to module use versus traditional reading (75% ± 9% vs 61% ± 7%, respectively; P < 0.05). In conclusion, this study represents the first effort to create a mobile, interactive cognitive simulator for cardiac surgery. Simulators of this type may be effective for the training and assessment of surgical students. We investigated whether an interactive, mobile-computing-based cognitive task simulator for cardiac surgery could be developed, deployed, and validated. Our findings suggest that such simulators may be a useful learning tool. Copyright © 2016. Published by Elsevier Inc.

A Hierarchical Learning Control Framework for an Aerial Manipulation System

NASA Astrophysics Data System (ADS)

Ma, Le; Chi, yanxun; Li, Jiapeng; Li, Zhongsheng; Ding, Yalei; Liu, Lixing

2017-07-01

A hierarchical learning control framework for an aerial manipulation system is proposed. Firstly, the mechanical design of aerial manipulation system is introduced and analyzed, and the kinematics and the dynamics based on Newton-Euler equation are modeled. Secondly, the framework of hierarchical learning for this system is presented, in which flight platform and manipulator are controlled by different controller respectively. The RBF (Radial Basis Function) neural networks are employed to estimate parameters and control. The Simulation and experiment demonstrate that the methods proposed effective and advanced.

QuantumOptics.jl: A Julia framework for simulating open quantum systems

NASA Astrophysics Data System (ADS)

Krämer, Sebastian; Plankensteiner, David; Ostermann, Laurin; Ritsch, Helmut

2018-06-01

We present an open source computational framework geared towards the efficient numerical investigation of open quantum systems written in the Julia programming language. Built exclusively in Julia and based on standard quantum optics notation, the toolbox offers speed comparable to low-level statically typed languages, without compromising on the accessibility and code readability found in dynamic languages. After introducing the framework, we highlight its features and showcase implementations of generic quantum models. Finally, we compare its usability and performance to two well-established and widely used numerical quantum libraries.

COMPUTERIZED TRAINING OF CRYOSURGERY – A SYSTEM APPROACH

PubMed Central

Keelan, Robert; Yamakawa, Soji; Shimada, Kenji; Rabin, Yoed

2014-01-01

The objective of the current study is to provide the foundation for a computerized training platform for cryosurgery. Consistent with clinical practice, the training process targets the correlation of the frozen region contour with the target region shape, using medical imaging and accepted criteria for clinical success. The current study focuses on system design considerations, including a bioheat transfer model, simulation techniques, optimal cryoprobe layout strategy, and a simulation core framework. Two fundamentally different approaches were considered for the development of a cryosurgery simulator, based on a finite-elements (FE) commercial code (ANSYS) and a proprietary finite-difference (FD) code. Results of this study demonstrate that the FE simulator is superior in terms of geometric modeling, while the FD simulator is superior in terms of runtime. Benchmarking results further indicate that the FD simulator is superior in terms of usage of memory resources, pre-processing, parallel processing, and post-processing. It is envisioned that future integration of a human-interface module and clinical data into the proposed computer framework will make computerized training of cryosurgery a practical reality. PMID:23995400

Model of dissolution in the framework of tissue engineering and drug delivery.

PubMed

Sanz-Herrera, J A; Soria, L; Reina-Romo, E; Torres, Y; Boccaccini, A R

2018-05-22

Dissolution phenomena are ubiquitously present in biomaterials in many different fields. Despite the advantages of simulation-based design of biomaterials in medical applications, additional efforts are needed to derive reliable models which describe the process of dissolution. A phenomenologically based model, available for simulation of dissolution in biomaterials, is introduced in this paper. The model turns into a set of reaction-diffusion equations implemented in a finite element numerical framework. First, a parametric analysis is conducted in order to explore the role of model parameters on the overall dissolution process. Then, the model is calibrated and validated versus a straightforward but rigorous experimental setup. Results show that the mathematical model macroscopically reproduces the main physicochemical phenomena that take place in the tests, corroborating its usefulness for design of biomaterials in the tissue engineering and drug delivery research areas.

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions.

PubMed

Wilmoth, Jared L; Doak, Peter W; Timm, Andrea; Halsted, Michelle; Anderson, John D; Ginovart, Marta; Prats, Clara; Portell, Xavier; Retterer, Scott T; Fuentes-Cabrera, Miguel

2018-01-01

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P . aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions

PubMed Central

Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea; Halsted, Michelle; Anderson, John D.; Ginovart, Marta; Prats, Clara; Portell, Xavier; Retterer, Scott T.; Fuentes-Cabrera, Miguel

2018-01-01

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models. PMID:29467721

Simulation Credibility: Advances in Verification, Validation, and Uncertainty Quantification

NASA Technical Reports Server (NTRS)

Mehta, Unmeel B. (Editor); Eklund, Dean R.; Romero, Vicente J.; Pearce, Jeffrey A.; Keim, Nicholas S.

2016-01-01

Decision makers and other users of simulations need to know quantified simulation credibility to make simulation-based critical decisions and effectively use simulations, respectively. The credibility of a simulation is quantified by its accuracy in terms of uncertainty, and the responsibility of establishing credibility lies with the creator of the simulation. In this volume, we present some state-of-the-art philosophies, principles, and frameworks. The contributing authors involved in this publication have been dedicated to advancing simulation credibility. They detail and provide examples of key advances over the last 10 years in the processes used to quantify simulation credibility: verification, validation, and uncertainty quantification. The philosophies and assessment methods presented here are anticipated to be useful to other technical communities conducting continuum physics-based simulations; for example, issues related to the establishment of simulation credibility in the discipline of propulsion are discussed. We envision that simulation creators will find this volume very useful to guide and assist them in quantitatively conveying the credibility of their simulations.

A flexible object-oriented software framework for developing complex multimedia simulations.

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

Sydelko, P. J.; Dolph, J. E.; Christiansen, J. H.

Decision makers involved in brownfields redevelopment and long-term stewardship must consider environmental conditions, future-use potential, site ownership, area infrastructure, funding resources, cost recovery, regulations, risk and liability management, community relations, and expected return on investment in a comprehensive and integrated fashion to achieve desired results. Successful brownfields redevelopment requires the ability to assess the impacts of redevelopment options on multiple interrelated aspects of the ecosystem, both natural and societal. Computer-based tools, such as simulation models, databases, and geographical information systems (GISs) can be used to address brownfields planning and project execution. The transparent integration of these tools into a comprehensivemore » and dynamic decision support system would greatly enhance the brownfields assessment process. Such a system needs to be able to adapt to shifting and expanding analytical requirements and contexts. The Dynamic Information Architecture System (DIAS) is a flexible, extensible, object-oriented framework for developing and maintaining complex multidisciplinary simulations of a wide variety of application domains. The modeling domain of a specific DIAS-based simulation is determined by (1) software objects that represent the real-world entities that comprise the problem space (atmosphere, watershed, human), and (2) simulation models and other data processing applications that express the dynamic behaviors of the domain entities. Models and applications used to express dynamic behaviors can be either internal or external to DIAS, including existing legacy models written in various languages (FORTRAN, C, etc.). The flexible design framework of DIAS makes the objects adjustable to the context of the problem without a great deal of recoding. The DIAS Spatial Data Set facility allows parameters to vary spatially depending on the simulation context according to any of a number of 1-D, 2-D, or 3-D topologies. DIAS is also capable of interacting with other GIS packages and can import many standard spatial data formats. DIAS simulation capabilities can also be extended by including societal process models. Models that implement societal behaviors of individuals and organizations within larger DIAS-based natural systems simulations allow for interaction and feedback among natural and societal processes. The ability to simulate the complex interplay of multimedia processes makes DIAS a promising tool for constructing applications for comprehensive community planning, including the assessment of multiple development and redevelopment scenarios.« less

Performance of technology-driven simulators for medical students--a systematic review.

PubMed

Michael, Michael; Abboudi, Hamid; Ker, Jean; Shamim Khan, Mohammed; Dasgupta, Prokar; Ahmed, Kamran

2014-12-01

Simulation-based education has evolved as a key training tool in high-risk industries such as aviation and the military. In parallel with these industries, the benefits of incorporating specialty-oriented simulation training within medical schools are vast. Adoption of simulators into medical school education programs has shown great promise and has the potential to revolutionize modern undergraduate education. An English literature search was carried out using MEDLINE, EMBASE, and psychINFO databases to identify all randomized controlled studies pertaining to "technology-driven" simulators used in undergraduate medical education. A validity framework incorporating the "framework for technology enhanced learning" report by the Department of Health, United Kingdom, was used to evaluate the capabilities of each technology-driven simulator. Information was collected regarding the simulator type, characteristics, and brand name. Where possible, we extracted information from the studies on the simulators' performance with respect to validity status, reliability, feasibility, education impact, acceptability, and cost effectiveness. We identified 19 studies, analyzing simulators for medical students across a variety of procedure-based specialities including; cardiovascular (n = 2), endoscopy (n = 3), laparoscopic surgery (n = 8), vascular access (n = 2), ophthalmology (n = 1), obstetrics and gynecology (n = 1), anesthesia (n = 1), and pediatrics (n = 1). Incorporation of simulators has so far been on an institutional level; no national or international trends have yet emerged. Simulators are capable of providing a highly educational and realistic experience for the medical students within a variety of speciality-oriented teaching sessions. Further research is needed to establish how best to incorporate simulators into a more primary stage of medical education; preclinical and clinical undergraduate medicine. Copyright © 2014 Elsevier Inc. All rights reserved.

GeNeDA: An Open-Source Workflow for Design Automation of Gene Regulatory Networks Inspired from Microelectronics.

PubMed

Madec, Morgan; Pecheux, François; Gendrault, Yves; Rosati, Elise; Lallement, Christophe; Haiech, Jacques

2016-10-01

The topic of this article is the development of an open-source automated design framework for synthetic biology, specifically for the design of artificial gene regulatory networks based on a digital approach. In opposition to other tools, GeNeDA is an open-source online software based on existing tools used in microelectronics that have proven their efficiency over the last 30 years. The complete framework is composed of a computation core directly adapted from an Electronic Design Automation tool, input and output interfaces, a library of elementary parts that can be achieved with gene regulatory networks, and an interface with an electrical circuit simulator. Each of these modules is an extension of microelectronics tools and concepts: ODIN II, ABC, the Verilog language, SPICE simulator, and SystemC-AMS. GeNeDA is first validated on a benchmark of several combinatorial circuits. The results highlight the importance of the part library. Then, this framework is used for the design of a sequential circuit including a biological state machine.

BEATBOX v1.0: Background Error Analysis Testbed with Box Models

NASA Astrophysics Data System (ADS)

Knote, Christoph; Barré, Jérôme; Eckl, Max

2018-02-01

The Background Error Analysis Testbed (BEATBOX) is a new data assimilation framework for box models. Based on the BOX Model eXtension (BOXMOX) to the Kinetic Pre-Processor (KPP), this framework allows users to conduct performance evaluations of data assimilation experiments, sensitivity analyses, and detailed chemical scheme diagnostics from an observation simulation system experiment (OSSE) point of view. The BEATBOX framework incorporates an observation simulator and a data assimilation system with the possibility of choosing ensemble, adjoint, or combined sensitivities. A user-friendly, Python-based interface allows for the tuning of many parameters for atmospheric chemistry and data assimilation research as well as for educational purposes, for example observation error, model covariances, ensemble size, perturbation distribution in the initial conditions, and so on. In this work, the testbed is described and two case studies are presented to illustrate the design of a typical OSSE experiment, data assimilation experiments, a sensitivity analysis, and a method for diagnosing model errors. BEATBOX is released as an open source tool for the atmospheric chemistry and data assimilation communities.

A Framework for the Design of Effective Graphics for Scientific Visualization

NASA Technical Reports Server (NTRS)

Miceli, Kristina D.

1992-01-01

This proposal presents a visualization framework, based on a data model, that supports the production of effective graphics for scientific visualization. Visual representations are effective only if they augment comprehension of the increasing amounts of data being generated by modern computer simulations. These representations are created by taking into account the goals and capabilities of the scientist, the type of data to be displayed, and software and hardware considerations. This framework is embodied in an assistant-based visualization system to guide the scientist in the visualization process. This will improve the quality of the visualizations and decrease the time the scientist is required to spend in generating the visualizations. I intend to prove that such a framework will create a more productive environment for tile analysis and interpretation of large, complex data sets.

A motion sensing-based framework for robotic manipulation.

PubMed

Deng, Hao; Xia, Zeyang; Weng, Shaokui; Gan, Yangzhou; Fang, Peng; Xiong, Jing

2016-01-01

To data, outside of the controlled environments, robots normally perform manipulation tasks operating with human. This pattern requires the robot operators with high technical skills training for varied teach-pendant operating system. Motion sensing technology, which enables human-machine interaction in a novel and natural interface using gestures, has crucially inspired us to adopt this user-friendly and straightforward operation mode on robotic manipulation. Thus, in this paper, we presented a motion sensing-based framework for robotic manipulation, which recognizes gesture commands captured from motion sensing input device and drives the action of robots. For compatibility, a general hardware interface layer was also developed in the framework. Simulation and physical experiments have been conducted for preliminary validation. The results have shown that the proposed framework is an effective approach for general robotic manipulation with motion sensing control.

A new framework for quantifying uncertainties in modelling studies for future climates - how more certain are CMIP5 precipitation and temperature simulations compared to CMIP3?

NASA Astrophysics Data System (ADS)

Sharma, A.; Woldemeskel, F. M.; Sivakumar, B.; Mehrotra, R.

2014-12-01

We outline a new framework for assessing uncertainties in model simulations, be they hydro-ecological simulations for known scenarios, or climate simulations for assumed scenarios representing the future. This framework is illustrated here using GCM projections for future climates for hydrologically relevant variables (precipitation and temperature), with the uncertainty segregated into three dominant components - model uncertainty, scenario uncertainty (representing greenhouse gas emission scenarios), and ensemble uncertainty (representing uncertain initial conditions and states). A novel uncertainty metric, the Square Root Error Variance (SREV), is used to quantify the uncertainties involved. The SREV requires: (1) Interpolating raw and corrected GCM outputs to a common grid; (2) Converting these to percentiles; (3) Estimating SREV for model, scenario, initial condition and total uncertainty at each percentile; and (4) Transforming SREV to a time series. The outcome is a spatially varying series of SREVs associated with each model that can be used to assess how uncertain the system is at each simulated point or time. This framework, while illustrated in a climate change context, is completely applicable for assessment of uncertainties any modelling framework may be subject to. The proposed method is applied to monthly precipitation and temperature from 6 CMIP3 and 13 CMIP5 GCMs across the world. For CMIP3, B1, A1B and A2 scenarios whereas for CMIP5, RCP2.6, RCP4.5 and RCP8.5 representing low, medium and high emissions are considered. For both CMIP3 and CMIP5, model structure is the largest source of uncertainty, which reduces significantly after correcting for biases. Scenario uncertainly increases, especially for temperature, in future due to divergence of the three emission scenarios analysed. While CMIP5 precipitation simulations exhibit a small reduction in total uncertainty over CMIP3, there is almost no reduction observed for temperature projections. Estimation of uncertainty in both space and time sheds lights on the spatial and temporal patterns of uncertainties in GCM outputs, providing an effective platform for risk-based assessments of any alternate plans or decisions that may be formulated using GCM simulations.

The Trick Simulation Toolkit: A NASA/Opensource Framework for Running Time Based Physics Models

NASA Technical Reports Server (NTRS)

Penn, John M.

2016-01-01

The Trick Simulation Toolkit is a simulation development environment used to create high fidelity training and engineering simulations at the NASA Johnson Space Center and many other NASA facilities. Its purpose is to generate a simulation executable from a collection of user-supplied models and a simulation definition file. For each Trick-based simulation, Trick automatically provides job scheduling, numerical integration, the ability to write and restore human readable checkpoints, data recording, interactive variable manipulation, a run-time interpreter, and many other commonly needed capabilities. This allows simulation developers to concentrate on their domain expertise and the algorithms and equations of their models. Also included in Trick are tools for plotting recorded data and various other supporting utilities and libraries. Trick is written in C/C++ and Java and supports both Linux and MacOSX computer operating systems. This paper describes Trick's design and use at NASA Johnson Space Center.

NetMOD Version 2.0 Mathematical Framework

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

Merchant, Bion J.; Young, Christopher J.; Chael, Eric P.

2015-08-01

NetMOD ( Net work M onitoring for O ptimal D etection) is a Java-based software package for conducting simulation of seismic, hydroacoustic and infrasonic networks. Network simulations have long been used to study network resilience to station outages and to determine where additional stations are needed to reduce monitoring thresholds. NetMOD makes use of geophysical models to determine the source characteristics, signal attenuation along the path between the source and station, and the performance and noise properties of the station. These geophysical models are combined to simulate the relative amplitudes of signal and noise that are observed at each ofmore » the stations. From these signal-to-noise ratios (SNR), the probabilities of signal detection at each station and event detection across the network of stations can be computed given a detection threshold. The purpose of this document is to clearly and comprehensively present the mathematical framework used by NetMOD, the software package developed by Sandia National Laboratories to assess the monitoring capability of ground-based sensor networks. Many of the NetMOD equations used for simulations are inherited from the NetSim network capability assessment package developed in the late 1980s by SAIC (Sereno et al., 1990).« less

20th Annual Systems Engineering Conference, Thursday, Volume 4

DTIC Science & Technology

2017-10-26

Daniel Dault, Air Force Research Lab 19809 Physics Based Modeling & Simulation For Shock and Vulnerability Assessments - Navy Enhanced Sierra...19811 Version 1.0 of the New INCOSE Competency Framework u Mr. Don Gelosh 19515 A Proposed Engineering Training Framework and Competency Methodology...nonlinearity ▪ QEV, Transient, Frequency Domain ▪ Inverse Methods Capability ▪ Coupled Physics ▪ Fluids: nemo, aero and sigma ▪ Thermal (unidirection): fuego

High performance hydrogen storage from Be-BTB metal-organic framework at room temperature.

PubMed

Lim, Wei-Xian; Thornton, Aaron W; Hill, Anita J; Cox, Barry J; Hill, James M; Hill, Matthew R

2013-07-09

The metal-organic framework beryllium benzene tribenzoate (Be-BTB) has recently been reported to have one of the highest gravimetric hydrogen uptakes at room temperature. Storage at room temperature is one of the key requirements for the practical viability of hydrogen-powered vehicles. Be-BTB has an exceptional 298 K storage capacity of 2.3 wt % hydrogen. This result is surprising given that the low adsorption enthalpy of 5.5 kJ mol(-1). In this work, a combination of atomistic simulation and continuum modeling reveals that the beryllium rings contribute strongly to the hydrogen interaction with the framework. These simulations are extended with a thermodynamic energy optimization (TEO) model to compare the performance of Be-BTB to a compressed H2 tank and benchmark materials MOF-5 and MOF-177 in a MOF-based fuel cell. Our investigation shows that none of the MOF-filled tanks satisfy the United States Department of Energy (DOE) storage targets within the required operating temperatures and pressures. However, the Be-BTB tank delivers the most energy per volume and mass compared to the other material-based storage tanks. The pore size and the framework mass are shown to be contributing factors responsible for the superior room temperature hydrogen adsorption of Be-BTB.

Design of the HELICS High-Performance Transmission-Distribution-Communication-Market Co-Simulation Framework

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

Palmintier, Bryan S; Krishnamurthy, Dheepak; Top, Philip

This paper describes the design rationale for a new cyber-physical-energy co-simulation framework for electric power systems. This new framework will support very large-scale (100,000+ federates) co-simulations with off-the-shelf power-systems, communication, and end-use models. Other key features include cross-platform operating system support, integration of both event-driven (e.g. packetized communication) and time-series (e.g. power flow) simulation, and the ability to co-iterate among federates to ensure model convergence at each time step. After describing requirements, we begin by evaluating existing co-simulation frameworks, including HLA and FMI, and conclude that none provide the required features. Then we describe the design for the new layeredmore » co-simulation architecture.« less

Design of the HELICS High-Performance Transmission-Distribution-Communication-Market Co-Simulation Framework: Preprint

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

Palmintier, Bryan S; Krishnamurthy, Dheepak; Top, Philip

This paper describes the design rationale for a new cyber-physical-energy co-simulation framework for electric power systems. This new framework will support very large-scale (100,000+ federates) co-simulations with off-the-shelf power-systems, communication, and end-use models. Other key features include cross-platform operating system support, integration of both event-driven (e.g. packetized communication) and time-series (e.g. power flow) simulation, and the ability to co-iterate among federates to ensure model convergence at each time step. After describing requirements, we begin by evaluating existing co-simulation frameworks, including HLA and FMI, and conclude that none provide the required features. Then we describe the design for the new layeredmore » co-simulation architecture.« less

Simulation and modeling of the temporal performance of path-based restoration schemes in planar mesh networks

NASA Astrophysics Data System (ADS)

Bhardwaj, Manish; McCaughan, Leon; Olkhovets, Anatoli; Korotky, Steven K.

2006-12-01

We formulate an analytic framework for the restoration performance of path-based restoration schemes in planar mesh networks. We analyze various switch architectures and signaling schemes and model their total restoration interval. We also evaluate the network global expectation value of the time to restore a demand as a function of network parameters. We analyze a wide range of nominally capacity-optimal planar mesh networks and find our analytic model to be in good agreement with numerical simulation data.

From Sub-basin to Grid Scale Soil Moisture Disaggregation in SMART, A Semi-distributed Hydrologic Modeling Framework

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.

2016-12-01

A computationally efficient, semi-distributed hydrologic modeling framework is developed to simulate water balance at a catchment scale. The Soil Moisture and Runoff simulation Toolkit (SMART) is based upon the delineation of contiguous and topologically connected Hydrologic Response Units (HRUs). In SMART, HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are distributed cross sections or equivalent cross sections (ECS) delineated in first order sub-basins. ECSs are formulated by aggregating topographic and physiographic properties of the part or entire first order sub-basins to further reduce computational time in SMART. Previous investigations using SMART have shown that temporal dynamics of soil moisture are well captured at a HRU level using the ECS delineation approach. However, spatial variability of soil moisture within a given HRU is ignored. Here, we examined a number of disaggregation schemes for soil moisture distribution in each HRU. The disaggregation schemes are either based on topographic based indices or a covariance matrix obtained from distributed soil moisture simulations. To assess the performance of the disaggregation schemes, soil moisture simulations from an integrated land surface-groundwater model, ParFlow.CLM in Baldry sub-catchment, Australia are used. ParFlow is a variably saturated sub-surface flow model that is coupled to the Common Land Model (CLM). Our results illustrate that the statistical disaggregation scheme performs better than the methods based on topographic data in approximating soil moisture distribution at a 60m scale. Moreover, the statistical disaggregation scheme maintains temporal correlation of simulated daily soil moisture while preserves the mean sub-basin soil moisture. Future work is focused on assessing the performance of this scheme in catchments with various topographic and climate settings.

Simulation framework for electromagnetic effects in plasmonics, filter apertures, wafer scattering, grating mirrors, and nano-crystals

NASA Astrophysics Data System (ADS)

Ceperley, Daniel Peter

This thesis presents a Finite-Difference Time-Domain simulation framework as well as both scientific observations and quantitative design data for emerging optical devices. These emerging applications required the development of simulation capabilities to carefully control numerical experimental conditions, isolate and quantifying specific scattering processes, and overcome memory and run-time limitations on large device structures. The framework consists of a new version 7 of TEMPEST and auxiliary tools implemented as Matlab scripts. In improving the geometry representation and absorbing boundary conditions in TEMPEST from v6 the accuracy has been sustained and key improvements have yielded application specific speed and accuracy improvements. These extensions include pulsed methods, PML for plasmon termination, and plasmon and scattered field sources. The auxiliary tools include application specific methods such as signal flow graphs of plasmon couplers, Bloch mode expansions of sub-wavelength grating waves, and back-propagation methods to characterize edge scattering in diffraction masks. Each application posed different numerical hurdles and physical questions for the simulation framework. The Terrestrial Planet Finder Coronagraph required accurate modeling of diffraction mask structures too large for solely FDTD analysis. This analysis was achieved through a combination of targeted TEMPEST simulations and full system simulator based on thin mask scalar diffraction models by Ball Aerospace for JPL. TEMPEST simulation showed that vertical sidewalls were the strongest scatterers, adding nearly 2lambda of light per mask edge, which could be reduced by 20° undercuts. TEMPEST assessment of coupling in rapid thermal annealing was complicated by extremely sub-wavelength features and fine meshes. Near 100% coupling and low variability was confirmed even in the presence of unidirectional dense metal gates. Accurate analysis of surface plasmon coupling efficiency by small surface features required capabilities to isolate these features and cleanly illuminate them with plasmons and plane-waves. These features were shown to have coupling cross-sections up to and slightly exceeding their physical size. Long run-times for TEMPEST simulations of finite length gratings were overcome with a signal flow graph method. With these methods a plasmon coupler with over a 10lambda 100% capture length was demonstrated. Simulation of 3D nano-particle arrays utilized TEMPEST v7's pulsed methods to minimize the number of multi-day simulations. These simulations led to the discovery that interstitial plasmons were responsible for resonant absorption and transmission but not reflection. Simulation of a sub-wavelength grating mirror using pulsed sources to map resonant spectra showed that neither coupled guided waves nor coupled isolated resonators accurately described the operation. However, a new model based on vertical propagation of lateral Bloch modes with zero phase progression efficiently characterized the device and provided principles for designing similar devices at other wavelengths.

A Bayesian Framework for False Belief Reasoning in Children: A Rational Integration of Theory-Theory and Simulation Theory

PubMed Central

Asakura, Nobuhiko; Inui, Toshio

2016-01-01

Two apparently contrasting theories have been proposed to account for the development of children's theory of mind (ToM): theory-theory and simulation theory. We present a Bayesian framework that rationally integrates both theories for false belief reasoning. This framework exploits two internal models for predicting the belief states of others: one of self and one of others. These internal models are responsible for simulation-based and theory-based reasoning, respectively. The framework further takes into account empirical studies of a developmental ToM scale (e.g., Wellman and Liu, 2004): developmental progressions of various mental state understandings leading up to false belief understanding. By representing the internal models and their interactions as a causal Bayesian network, we formalize the model of children's false belief reasoning as probabilistic computations on the Bayesian network. This model probabilistically weighs and combines the two internal models and predicts children's false belief ability as a multiplicative effect of their early-developed abilities to understand the mental concepts of diverse beliefs and knowledge access. Specifically, the model predicts that children's proportion of correct responses on a false belief task can be closely approximated as the product of their proportions correct on the diverse belief and knowledge access tasks. To validate this prediction, we illustrate that our model provides good fits to a variety of ToM scale data for preschool children. We discuss the implications and extensions of our model for a deeper understanding of developmental progressions of children's ToM abilities. PMID:28082941

A Bayesian Framework for False Belief Reasoning in Children: A Rational Integration of Theory-Theory and Simulation Theory.

PubMed

Asakura, Nobuhiko; Inui, Toshio

2016-01-01

Two apparently contrasting theories have been proposed to account for the development of children's theory of mind (ToM): theory-theory and simulation theory. We present a Bayesian framework that rationally integrates both theories for false belief reasoning. This framework exploits two internal models for predicting the belief states of others: one of self and one of others. These internal models are responsible for simulation-based and theory-based reasoning, respectively. The framework further takes into account empirical studies of a developmental ToM scale (e.g., Wellman and Liu, 2004): developmental progressions of various mental state understandings leading up to false belief understanding. By representing the internal models and their interactions as a causal Bayesian network, we formalize the model of children's false belief reasoning as probabilistic computations on the Bayesian network. This model probabilistically weighs and combines the two internal models and predicts children's false belief ability as a multiplicative effect of their early-developed abilities to understand the mental concepts of diverse beliefs and knowledge access. Specifically, the model predicts that children's proportion of correct responses on a false belief task can be closely approximated as the product of their proportions correct on the diverse belief and knowledge access tasks. To validate this prediction, we illustrate that our model provides good fits to a variety of ToM scale data for preschool children. We discuss the implications and extensions of our model for a deeper understanding of developmental progressions of children's ToM abilities.

Haptic simulation framework for determining virtual dental occlusion.

PubMed

Wu, Wen; Chen, Hui; Cen, Yuhai; Hong, Yang; Khambay, Balvinder; Heng, Pheng Ann

2017-04-01

The surgical treatment of many dentofacial deformities is often complex due to its three-dimensional nature. To determine the dental occlusion in the most stable position is essential for the success of the treatment. Computer-aided virtual planning on individualized patient-specific 3D model can help formulate the surgical plan and predict the surgical change. However, in current computer-aided planning systems, it is not possible to determine the dental occlusion of the digital models in the intuitive way during virtual surgical planning because of absence of haptic feedback. In this paper, a physically based haptic simulation framework is proposed, which can provide surgeons with the intuitive haptic feedback to determine the dental occlusion of the digital models in their most stable position. To provide the physically realistic force feedback when the dental models contact each other during the searching process, the contact model is proposed to describe the dynamic and collision properties of the dental models during the alignment. The simulated impulse/contact-based forces are integrated into the unified simulation framework. A validation study has been conducted on fifteen sets of virtual dental models chosen at random and covering a wide range of the dental relationships found clinically. The dental occlusions obtained by an expert were employed as a benchmark to compare the virtual occlusion results. The mean translational and angular deviations of the virtual occlusion results from the benchmark were small. The experimental results show the validity of our method. The simulated forces can provide valuable insights to determine the virtual dental occlusion. The findings of this work and the validation of proposed concept lead the way for full virtual surgical planning on patient-specific virtual models allowing fully customized treatment plans for the surgical correction of dentofacial deformities.

A framework for plasticity implementation on the SpiNNaker neural architecture.

PubMed

Galluppi, Francesco; Lagorce, Xavier; Stromatias, Evangelos; Pfeiffer, Michael; Plana, Luis A; Furber, Steve B; Benosman, Ryad B

2014-01-01

Many of the precise biological mechanisms of synaptic plasticity remain elusive, but simulations of neural networks have greatly enhanced our understanding of how specific global functions arise from the massively parallel computation of neurons and local Hebbian or spike-timing dependent plasticity rules. For simulating large portions of neural tissue, this has created an increasingly strong need for large scale simulations of plastic neural networks on special purpose hardware platforms, because synaptic transmissions and updates are badly matched to computing style supported by current architectures. Because of the great diversity of biological plasticity phenomena and the corresponding diversity of models, there is a great need for testing various hypotheses about plasticity before committing to one hardware implementation. Here we present a novel framework for investigating different plasticity approaches on the SpiNNaker distributed digital neural simulation platform. The key innovation of the proposed architecture is to exploit the reconfigurability of the ARM processors inside SpiNNaker, dedicating a subset of them exclusively to process synaptic plasticity updates, while the rest perform the usual neural and synaptic simulations. We demonstrate the flexibility of the proposed approach by showing the implementation of a variety of spike- and rate-based learning rules, including standard Spike-Timing dependent plasticity (STDP), voltage-dependent STDP, and the rate-based BCM rule. We analyze their performance and validate them by running classical learning experiments in real time on a 4-chip SpiNNaker board. The result is an efficient, modular, flexible and scalable framework, which provides a valuable tool for the fast and easy exploration of learning models of very different kinds on the parallel and reconfigurable SpiNNaker system.

A framework for plasticity implementation on the SpiNNaker neural architecture

PubMed Central

Galluppi, Francesco; Lagorce, Xavier; Stromatias, Evangelos; Pfeiffer, Michael; Plana, Luis A.; Furber, Steve B.; Benosman, Ryad B.

2015-01-01

Many of the precise biological mechanisms of synaptic plasticity remain elusive, but simulations of neural networks have greatly enhanced our understanding of how specific global functions arise from the massively parallel computation of neurons and local Hebbian or spike-timing dependent plasticity rules. For simulating large portions of neural tissue, this has created an increasingly strong need for large scale simulations of plastic neural networks on special purpose hardware platforms, because synaptic transmissions and updates are badly matched to computing style supported by current architectures. Because of the great diversity of biological plasticity phenomena and the corresponding diversity of models, there is a great need for testing various hypotheses about plasticity before committing to one hardware implementation. Here we present a novel framework for investigating different plasticity approaches on the SpiNNaker distributed digital neural simulation platform. The key innovation of the proposed architecture is to exploit the reconfigurability of the ARM processors inside SpiNNaker, dedicating a subset of them exclusively to process synaptic plasticity updates, while the rest perform the usual neural and synaptic simulations. We demonstrate the flexibility of the proposed approach by showing the implementation of a variety of spike- and rate-based learning rules, including standard Spike-Timing dependent plasticity (STDP), voltage-dependent STDP, and the rate-based BCM rule. We analyze their performance and validate them by running classical learning experiments in real time on a 4-chip SpiNNaker board. The result is an efficient, modular, flexible and scalable framework, which provides a valuable tool for the fast and easy exploration of learning models of very different kinds on the parallel and reconfigurable SpiNNaker system. PMID:25653580

SILHIL Replication of Electric Aircraft Powertrain Dynamics and Inner-Loop Control for V&V of System Health Management Routines

NASA Technical Reports Server (NTRS)

Bole, Brian; Teubert, Christopher Allen; Cuong Chi, Quach; Hogge, Edward; Vazquez, Sixto; Goebel, Kai; George, Vachtsevanos

2013-01-01

Software-in-the-loop and Hardware-in-the-loop testing of failure prognostics and decision making tools for aircraft systems will facilitate more comprehensive and cost-effective testing than what is practical to conduct with flight tests. A framework is described for the offline recreation of dynamic loads on simulated or physical aircraft powertrain components based on a real-time simulation of airframe dynamics running on a flight simulator, an inner-loop flight control policy executed by either an autopilot routine or a human pilot, and a supervisory fault management control policy. The creation of an offline framework for verifying and validating supervisory failure prognostics and decision making routines is described for the example of battery charge depletion failure scenarios onboard a prototype electric unmanned aerial vehicle.

High-fidelity simulations of unsteady civil aircraft aerodynamics: stakes and perspectives. Application of zonal detached eddy simulation

PubMed Central

Deck, Sébastien; Gand, Fabien; Brunet, Vincent; Ben Khelil, Saloua

2014-01-01

This paper provides an up-to-date survey of the use of zonal detached eddy simulations (ZDES) for unsteady civil aircraft applications as a reflection on the stakes and perspectives of the use of hybrid methods in the framework of industrial aerodynamics. The issue of zonal or non-zonal treatment of turbulent flows for engineering applications is discussed. The ZDES method used in this article and based on a fluid problem-dependent zonalization is briefly presented. Some recent landmark achievements for conditions all over the flight envelope are presented, including low-speed (aeroacoustics of high-lift devices and landing gear), cruising (engine–airframe interactions), propulsive jets and off-design (transonic buffet and dive manoeuvres) applications. The implications of such results and remaining challenges in a more global framework are further discussed. PMID:25024411

Thermostating extended Lagrangian Born-Oppenheimer molecular dynamics.

PubMed

Martínez, Enrique; Cawkwell, Marc J; Voter, Arthur F; Niklasson, Anders M N

2015-04-21

Extended Lagrangian Born-Oppenheimer molecular dynamics is developed and analyzed for applications in canonical (NVT) simulations. Three different approaches are considered: the Nosé and Andersen thermostats and Langevin dynamics. We have tested the temperature distribution under different conditions of self-consistent field (SCF) convergence and time step and compared the results to analytical predictions. We find that the simulations based on the extended Lagrangian Born-Oppenheimer framework provide accurate canonical distributions even under approximate SCF convergence, often requiring only a single diagonalization per time step, whereas regular Born-Oppenheimer formulations exhibit unphysical fluctuations unless a sufficiently high degree of convergence is reached at each time step. The thermostated extended Lagrangian framework thus offers an accurate approach to sample processes in the canonical ensemble at a fraction of the computational cost of regular Born-Oppenheimer molecular dynamics simulations.

Quantification of uncertainties for application in detonation simulation

NASA Astrophysics Data System (ADS)

Zheng, Miao; Ma, Zhibo

2016-06-01

Numerical simulation has become an important means in designing detonation systems, and the quantification of its uncertainty is also necessary to reliability certification. As to quantifying the uncertainty, it is the most important to analyze how the uncertainties occur and develop, and how the simulations develop from benchmark models to new models. Based on the practical needs of engineering and the technology of verification & validation, a framework of QU(quantification of uncertainty) is brought forward in the case that simulation is used on detonation system for scientific prediction. An example is offered to describe the general idea of quantification of simulation uncertainties.

GillesPy: A Python Package for Stochastic Model Building and Simulation.

PubMed

Abel, John H; Drawert, Brian; Hellander, Andreas; Petzold, Linda R

2016-09-01

GillesPy is an open-source Python package for model construction and simulation of stochastic biochemical systems. GillesPy consists of a Python framework for model building and an interface to the StochKit2 suite of efficient simulation algorithms based on the Gillespie stochastic simulation algorithms (SSA). To enable intuitive model construction and seamless integration into the scientific Python stack, we present an easy to understand, action-oriented programming interface. Here, we describe the components of this package and provide a detailed example relevant to the computational biology community.

GillesPy: A Python Package for Stochastic Model Building and Simulation

PubMed Central

Abel, John H.; Drawert, Brian; Hellander, Andreas; Petzold, Linda R.

2017-01-01

GillesPy is an open-source Python package for model construction and simulation of stochastic biochemical systems. GillesPy consists of a Python framework for model building and an interface to the StochKit2 suite of efficient simulation algorithms based on the Gillespie stochastic simulation algorithms (SSA). To enable intuitive model construction and seamless integration into the scientific Python stack, we present an easy to understand, action-oriented programming interface. Here, we describe the components of this package and provide a detailed example relevant to the computational biology community. PMID:28630888

A methodology towards virtualisation-based high performance simulation platform supporting multidisciplinary design of complex products

NASA Astrophysics Data System (ADS)

Ren, Lei; Zhang, Lin; Tao, Fei; (Luke) Zhang, Xiaolong; Luo, Yongliang; Zhang, Yabin

2012-08-01

Multidisciplinary design of complex products leads to an increasing demand for high performance simulation (HPS) platforms. One great challenge is how to achieve high efficient utilisation of large-scale simulation resources in distributed and heterogeneous environments. This article reports a virtualisation-based methodology to realise a HPS platform. This research is driven by the issues concerning large-scale simulation resources deployment and complex simulation environment construction, efficient and transparent utilisation of fine-grained simulation resources and high reliable simulation with fault tolerance. A framework of virtualisation-based simulation platform (VSIM) is first proposed. Then the article investigates and discusses key approaches in VSIM, including simulation resources modelling, a method to automatically deploying simulation resources for dynamic construction of system environment, and a live migration mechanism in case of faults in run-time simulation. Furthermore, the proposed methodology is applied to a multidisciplinary design system for aircraft virtual prototyping and some experiments are conducted. The experimental results show that the proposed methodology can (1) significantly improve the utilisation of fine-grained simulation resources, (2) result in a great reduction in deployment time and an increased flexibility for simulation environment construction and (3)achieve fault tolerant simulation.

Computer simulation-based framework for transportation evacuation in major trip generator.

DOT National Transportation Integrated Search

2009-01-01

Since emergencies including both natural disasters and man-made incidents, are happening more and more : frequently, evacuation, especially transportation evacuation, is becoming a hot research focus in recent years. : Currently, transportation evacu...

A Petascale Non-Hydrostatic Atmospheric Dynamical Core in the HOMME Framework

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

Tufo, Henry

The High-Order Method Modeling Environment (HOMME) is a framework for building scalable, conserva- tive atmospheric models for climate simulation and general atmospheric-modeling applications. Its spatial discretizations are based on Spectral-Element (SE) and Discontinuous Galerkin (DG) methods. These are local methods employing high-order accurate spectral basis-functions that have been shown to perform well on massively parallel supercomputers at any resolution and scale particularly well at high resolutions. HOMME provides the framework upon which the CAM-SE community atmosphere model dynamical-core is constructed. In its current incarnation, CAM-SE employs the hydrostatic primitive-equations (PE) of motion, which limits its resolution to simulations coarser thanmore » 0.1 per grid cell. The primary objective of this project is to remove this resolution limitation by providing HOMME with the capabilities needed to build nonhydrostatic models that solve the compressible Euler/Navier-Stokes equations.« less

An innovative strategy in evaluation: using a student engagement framework to evaluate a role-based simulation.

PubMed

Smith, Morgan; Warland, Jane; Smith, Colleen

2012-03-01

Online role-play has the potential to actively engage students in authentic learning experiences and help develop their clinical reasoning skills. However, evaluation of student learning for this kind of simulation focuses mainly on the content and outcome of learning, rather than on the process of learning through student engagement. This article reports on the use of a student engagement framework to evaluate an online role-play offered as part of a course in Bachelor of Nursing and Bachelor of Midwifery programs. Instruments that measure student engagement to date have targeted large numbers of students at program and institutional levels, rather than at the level of a specific learning activity. Although the framework produced some useful findings for evaluation purposes, further refinement of the questions is required to be certain that deep learning results from the engagement that occurs with course-level learning initiatives. Copyright 2012, SLACK Incorporated.

Verifiable fault tolerance in measurement-based quantum computation

NASA Astrophysics Data System (ADS)

Fujii, Keisuke; Hayashi, Masahito

2017-09-01

Quantum systems, in general, cannot be simulated efficiently by a classical computer, and hence are useful for solving certain mathematical problems and simulating quantum many-body systems. This also implies, unfortunately, that verification of the output of the quantum systems is not so trivial, since predicting the output is exponentially hard. As another problem, the quantum system is very delicate for noise and thus needs an error correction. Here, we propose a framework for verification of the output of fault-tolerant quantum computation in a measurement-based model. In contrast to existing analyses on fault tolerance, we do not assume any noise model on the resource state, but an arbitrary resource state is tested by using only single-qubit measurements to verify whether or not the output of measurement-based quantum computation on it is correct. Verifiability is equipped by a constant time repetition of the original measurement-based quantum computation in appropriate measurement bases. Since full characterization of quantum noise is exponentially hard for large-scale quantum computing systems, our framework provides an efficient way to practically verify the experimental quantum error correction.

A simulation framework for auditory discrimination experiments: Revealing the importance of across-frequency processing in speech perception.

PubMed

Schädler, Marc René; Warzybok, Anna; Ewert, Stephan D; Kollmeier, Birger

2016-05-01

A framework for simulating auditory discrimination experiments, based on an approach from Schädler, Warzybok, Hochmuth, and Kollmeier [(2015). Int. J. Audiol. 54, 100-107] which was originally designed to predict speech recognition thresholds, is extended to also predict psychoacoustic thresholds. The proposed framework is used to assess the suitability of different auditory-inspired feature sets for a range of auditory discrimination experiments that included psychoacoustic as well as speech recognition experiments in noise. The considered experiments were 2 kHz tone-in-broadband-noise simultaneous masking depending on the tone length, spectral masking with simultaneously presented tone signals and narrow-band noise maskers, and German Matrix sentence test reception threshold in stationary and modulated noise. The employed feature sets included spectro-temporal Gabor filter bank features, Mel-frequency cepstral coefficients, logarithmically scaled Mel-spectrograms, and the internal representation of the Perception Model from Dau, Kollmeier, and Kohlrausch [(1997). J. Acoust. Soc. Am. 102(5), 2892-2905]. The proposed framework was successfully employed to simulate all experiments with a common parameter set and obtain objective thresholds with less assumptions compared to traditional modeling approaches. Depending on the feature set, the simulated reference-free thresholds were found to agree with-and hence to predict-empirical data from the literature. Across-frequency processing was found to be crucial to accurately model the lower speech reception threshold in modulated noise conditions than in stationary noise conditions.

A Software Framework for Aircraft Simulation

NASA Technical Reports Server (NTRS)

Curlett, Brian P.

2008-01-01

The National Aeronautics and Space Administration Dryden Flight Research Center has a long history in developing simulations of experimental fixed-wing aircraft from gliders to suborbital vehicles on platforms ranging from desktop simulators to pilot-in-the-loop/aircraft-in-the-loop simulators. Regardless of the aircraft or simulator hardware, much of the software framework is common to all NASA Dryden simulators. Some of this software has withstood the test of time, but in recent years the push toward high-fidelity user-friendly simulations has resulted in some significant changes. This report presents an overview of the current NASA Dryden simulation software framework and capabilities with an emphasis on the new features that have permitted NASA to develop more capable simulations while maintaining the same staffing levels.

A New Simulation Framework for the Electron-Ion Collider

NASA Astrophysics Data System (ADS)

Arrington, John

2017-09-01

Last year, a collaboration between Physics Division and High-Energy Physics at Argonne was formed to enable significantly broader contributions to the development of the Electron-Ion Collider. This includes efforts in accelerator R&D, theory, simulations, and detector R&D. I will give a brief overview of the status of these efforts, with emphasis on the aspects aimed at enabling the community to more easily become involved in evaluation of physics, detectors, and details of spectrometer designs. We have put together a new, easy-to-use simulation framework using flexible software tools. The goal is to enable detailed simulations to evaluate detector performance and compare detector designs. In addition, a common framework capable of providing detailed simulations of different spectrometer designs will allow for fully consistent evaluations of the physics reach of different spectrometer designs or detector systems for a variety of physics channels. In addition, new theory efforts will provide self-consistent models of GPDs (including QCD evolution) and TMDs in nucleons and light nuclei, as well as providing more detailed physics input for the evaluation of some new observables. This material is based upon work supported by Laboratory Directed Research and Development (LDRD) funding from Argonne National Laboratory, provided by the Director, Office of Science, of the U.S. Department of Energy under Contract DE-AC02-06CH11357.

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.

Impact of model structure on flow simulation and hydrological realism: from a lumped to a semi-distributed approach

NASA Astrophysics Data System (ADS)

Garavaglia, Federico; Le Lay, Matthieu; Gottardi, Fréderic; Garçon, Rémy; Gailhard, Joël; Paquet, Emmanuel; Mathevet, Thibault

2017-08-01

Model intercomparison experiments are widely used to investigate and improve hydrological model performance. However, a study based only on runoff simulation is not sufficient to discriminate between different model structures. Hence, there is a need to improve hydrological models for specific streamflow signatures (e.g., low and high flow) and multi-variable predictions (e.g., soil moisture, snow and groundwater). This study assesses the impact of model structure on flow simulation and hydrological realism using three versions of a hydrological model called MORDOR: the historical lumped structure and a revisited formulation available in both lumped and semi-distributed structures. In particular, the main goal of this paper is to investigate the relative impact of model equations and spatial discretization on flow simulation, snowpack representation and evapotranspiration estimation. Comparison of the models is based on an extensive dataset composed of 50 catchments located in French mountainous regions. The evaluation framework is founded on a multi-criterion split-sample strategy. All models were calibrated using an automatic optimization method based on an efficient genetic algorithm. The evaluation framework is enriched by the assessment of snow and evapotranspiration modeling against in situ and satellite data. The results showed that the new model formulations perform significantly better than the initial one in terms of the various streamflow signatures, snow and evapotranspiration predictions. The semi-distributed approach provides better calibration-validation performance for the snow cover area, snow water equivalent and runoff simulation, especially for nival catchments.

A framework for incorporating DTI Atlas Builder registration into Tract-Based Spatial Statistics and a simulated comparison to standard TBSS.

PubMed

Leming, Matthew; Steiner, Rachel; Styner, Martin

2016-02-27

Tract-based spatial statistics (TBSS) 6 is a software pipeline widely employed in comparative analysis of the white matter integrity from diffusion tensor imaging (DTI) datasets. In this study, we seek to evaluate the relationship between different methods of atlas registration for use with TBSS and different measurements of DTI (fractional anisotropy, FA, axial diffusivity, AD, radial diffusivity, RD, and medial diffusivity, MD). To do so, we have developed a novel tool that builds on existing diffusion atlas building software, integrating it into an adapted version of TBSS called DAB-TBSS (DTI Atlas Builder-Tract-Based Spatial Statistics) by using the advanced registration offered in DTI Atlas Builder 7 . To compare the effectiveness of these two versions of TBSS, we also propose a framework for simulating population differences for diffusion tensor imaging data, providing a more substantive means of empirically comparing DTI group analysis programs such as TBSS. In this study, we used 33 diffusion tensor imaging datasets and simulated group-wise changes in this data by increasing, in three different simulations, the principal eigenvalue (directly altering AD), the second and third eigenvalues (RD), and all three eigenvalues (MD) in the genu, the right uncinate fasciculus, and the left IFO. Additionally, we assessed the benefits of comparing the tensors directly using a functional analysis of diffusion tensor tract statistics (FADTTS 10 ). Our results indicate comparable levels of FA-based detection between DAB-TBSS and TBSS, with standard TBSS registration reporting a higher rate of false positives in other measurements of DTI. Within the simulated changes investigated here, this study suggests that the use of DTI Atlas Builder's registration enhances TBSS group-based studies.

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

A Unified Framework for Complex Networks with Degree Trichotomy Based on Markov Chains.

PubMed

Hui, David Shui Wing; Chen, Yi-Chao; Zhang, Gong; Wu, Weijie; Chen, Guanrong; Lui, John C S; Li, Yingtao

2017-06-16

This paper establishes a Markov chain model as a unified framework for describing the evolution processes in complex networks. The unique feature of the proposed model is its capability in addressing the formation mechanism that can reflect the "trichotomy" observed in degree distributions, based on which closed-form solutions can be derived. Important special cases of the proposed unified framework are those classical models, including Poisson, Exponential, Power-law distributed networks. Both simulation and experimental results demonstrate a good match of the proposed model with real datasets, showing its superiority over the classical models. Implications of the model to various applications including citation analysis, online social networks, and vehicular networks design, are also discussed in the paper.

Status on the Development of a Modeling and Simulation Framework for the Economic Assessment of Nuclear Hybrid Energy Systems

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

Bragg-Sitton, Shannon Michelle; Rabiti, Cristian; Kinoshita, Robert Arthur

An effort to design and build a modeling and simulation framework to assess the economic viability of Nuclear Hybrid Energy Systems (NHES) was undertaken in fiscal year 2015 (FY15). The purpose of this report is to document the various tasks associated with the development of such a framework and to provide a status on its progress. Several tasks have been accomplished. First, starting from a simulation strategy, a rigorous mathematical formulation has been achieved in which the economic optimization of a Nuclear Hybrid Energy System is presented as a constrained robust (under uncertainty) optimization problem. Some possible algorithms for themore » solution of the optimization problem are presented. A variation of the Simultaneous Perturbation Stochastic Approximation algorithm has been implemented in RAVEN and preliminary tests have been performed. The development of the software infrastructure to support the simulation of the whole NHES has also moved forward. The coupling between RAVEN and an implementation of the Modelica language (OpenModelica) has been implemented, migrated under several operating systems and tested using an adapted model of a desalination plant. In particular, this exercise was focused on testing the coupling of the different code systems; testing parallel, computationally expensive simulations on the INL cluster; and providing a proof of concept for the possibility of using surrogate models to represent the different NHES subsystems. Another important step was the porting of the RAVEN code under the Windows™ operating system. This accomplishment makes RAVEN compatible with the development environment that is being used for dynamic simulation of NHES components. A very simplified model of a NHES on the electric market has been built in RAVEN to confirm expectations on the analysis capability of RAVEN to provide insight into system economics and to test the capability of RAVEN to identify limit surfaces even for stochastic constraints. This capability will be needed in the future to enforce the stochastic constraints on the electric demand coverage from the NHES. The development team gained experience with many of the tools that are currently envisioned for use in the economic analysis of NHES and completed several important steps. Given the complexity of the project, preference has been given to a structural approach in which several independent efforts have been used to build the cornerstone of the simulation framework. While this is good approach in establishing such a complex framework, it may delay reaching more complete results on the performance of analyzed system configurations. The integration of the previously reported exergy analysis approach was initially proposed as part of this milestone. However, in reality, the exergy-based apportioning of cost will take place only in a second stage of the implementation since it will be used to properly allocate cost among the different NHES subsystems. Therefore, exergy does not appear at the level of the main drivers in the analysis framework; the latter development of the base framework is the focus of this report.« less

High-Performance Agent-Based Modeling Applied to Vocal Fold Inflammation and Repair.

PubMed

Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y K

2018-01-01

Fast and accurate computational biology models offer the prospect of accelerating the development of personalized medicine. A tool capable of estimating treatment success can help prevent unnecessary and costly treatments and potential harmful side effects. A novel high-performance Agent-Based Model (ABM) was adopted to simulate and visualize multi-scale complex biological processes arising in vocal fold inflammation and repair. The computational scheme was designed to organize the 3D ABM sub-tasks to fully utilize the resources available on current heterogeneous platforms consisting of multi-core CPUs and many-core GPUs. Subtasks are further parallelized and convolution-based diffusion is used to enhance the performance of the ABM simulation. The scheme was implemented using a client-server protocol allowing the results of each iteration to be analyzed and visualized on the server (i.e., in-situ ) while the simulation is running on the same server. The resulting simulation and visualization software enables users to interact with and steer the course of the simulation in real-time as needed. This high-resolution 3D ABM framework was used for a case study of surgical vocal fold injury and repair. The new framework is capable of completing the simulation, visualization and remote result delivery in under 7 s per iteration, where each iteration of the simulation represents 30 min in the real world. The case study model was simulated at the physiological scale of a human vocal fold. This simulation tracks 17 million biological cells as well as a total of 1.7 billion signaling chemical and structural protein data points. The visualization component processes and renders all simulated biological cells and 154 million signaling chemical data points. The proposed high-performance 3D ABM was verified through comparisons with empirical vocal fold data. Representative trends of biomarker predictions in surgically injured vocal folds were observed.

High-Performance Agent-Based Modeling Applied to Vocal Fold Inflammation and Repair

PubMed Central

Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y. K.

2018-01-01

Fast and accurate computational biology models offer the prospect of accelerating the development of personalized medicine. A tool capable of estimating treatment success can help prevent unnecessary and costly treatments and potential harmful side effects. A novel high-performance Agent-Based Model (ABM) was adopted to simulate and visualize multi-scale complex biological processes arising in vocal fold inflammation and repair. The computational scheme was designed to organize the 3D ABM sub-tasks to fully utilize the resources available on current heterogeneous platforms consisting of multi-core CPUs and many-core GPUs. Subtasks are further parallelized and convolution-based diffusion is used to enhance the performance of the ABM simulation. The scheme was implemented using a client-server protocol allowing the results of each iteration to be analyzed and visualized on the server (i.e., in-situ) while the simulation is running on the same server. The resulting simulation and visualization software enables users to interact with and steer the course of the simulation in real-time as needed. This high-resolution 3D ABM framework was used for a case study of surgical vocal fold injury and repair. The new framework is capable of completing the simulation, visualization and remote result delivery in under 7 s per iteration, where each iteration of the simulation represents 30 min in the real world. The case study model was simulated at the physiological scale of a human vocal fold. This simulation tracks 17 million biological cells as well as a total of 1.7 billion signaling chemical and structural protein data points. The visualization component processes and renders all simulated biological cells and 154 million signaling chemical data points. The proposed high-performance 3D ABM was verified through comparisons with empirical vocal fold data. Representative trends of biomarker predictions in surgically injured vocal folds were observed. PMID:29706894

A stochastic hybrid systems based framework for modeling dependent failure processes

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

High-resolution coupled physics solvers for analysing fine-scale nuclear reactor design problems

DOE PAGES

Mahadevan, Vijay S.; Merzari, Elia; Tautges, Timothy; ...

2014-06-30

An integrated multi-physics simulation capability for the design and analysis of current and future nuclear reactor models is being investigated, to tightly couple neutron transport and thermal-hydraulics physics under the SHARP framework. Over several years, high-fidelity, validated mono-physics solvers with proven scalability on petascale architectures have been developed independently. Based on a unified component-based architecture, these existing codes can be coupled with a mesh-data backplane and a flexible coupling-strategy-based driver suite to produce a viable tool for analysts. The goal of the SHARP framework is to perform fully resolved coupled physics analysis of a reactor on heterogeneous geometry, in ordermore » to reduce the overall numerical uncertainty while leveraging available computational resources. Finally, the coupling methodology and software interfaces of the framework are presented, along with verification studies on two representative fast sodium-cooled reactor demonstration problems to prove the usability of the SHARP framework.« less

OpenDanubia - An integrated, modular simulation system to support regional water resource management

NASA Astrophysics Data System (ADS)

Muerth, M.; Waldmann, D.; Heinzeller, C.; Hennicker, R.; Mauser, W.

2012-04-01

The already completed, multi-disciplinary research project GLOWA-Danube has developed a regional scale, integrated modeling system, which was successfully applied on the 77,000 km2 Upper Danube basin to investigate the impact of Global Change on both the natural and anthropogenic water cycle. At the end of the last project phase, the integrated modeling system was transferred into the open source project OpenDanubia, which now provides both the core system as well as all major model components to the general public. First, this will enable decision makers from government, business and management to use OpenDanubia as a tool for proactive management of water resources in the context of global change. Secondly, the model framework to support integrated simulations and all simulation models developed for OpenDanubia in the scope of GLOWA-Danube are further available for future developments and research questions. OpenDanubia allows for the investigation of water-related scenarios considering different ecological and economic aspects to support both scientists and policy makers to design policies for sustainable environmental management. OpenDanubia is designed as a framework-based, distributed system. The model system couples spatially distributed physical and socio-economic process during run-time, taking into account their mutual influence. To simulate the potential future impacts of Global Change on agriculture, industrial production, water supply, households and tourism businesses, so-called deep actor models are implemented in OpenDanubia. All important water-related fluxes and storages in the natural environment are implemented in OpenDanubia as spatially explicit, process-based modules. This includes the land surface water and energy balance, dynamic plant water uptake, ground water recharge and flow as well as river routing and reservoirs. Although the complete system is relatively demanding on data requirements and hardware requirements, the modular structure and the generic core system (Core Framework, Actor Framework) allows the application in new regions and the selection of a reduced number of modules for simulation. As part of the Open Source Initiative in GLOWA-Danube (opendanubia.glowa-danube.de) a comprehensive documentation for the system installation was created and both the program code of the framework and of all major components is licensed under the GNU General Public License. In addition, some helpful programs and scripts necessary for the operation and processing of input and result data sets are provided.

Seldon v.3.0

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

Berry, Nina; Ko, Teresa; Shneider, Max

Seldon is an agent-based social simulation framework that uniquely integrates concepts from a variety of different research areas including psychology, social science, and agent-based modeling. Development has been taking place for a number of years, previously focusing on gang and terrorist recruitment. The toolkit consists of simple agents (individuals) and abstract agents (groups of individuals representing social/institutional concepts) that interact according to exchangeable rule sets (i.e. linear attraction, linear reinforcement). Each agent has a set of customizable attributes that get modified during the interactions. Interactions create relationships between agents, and each agent has a maximum amount of relationship energy thatmore » it can expend. As relationships evolve, they form multiple levels of social networks (i.e. acquaintances, friends, cliques) that in turn drive future interactions. Agents can also interact randomly if they are not connected through a network, mimicking the chance interactions that real people have in everyday life. We are currently integrating Seldon with the cognitive framework (also developed at Sandia). Each individual agent has a lightweight cognitive model that is created automatically from textual sources. Cognitive information is exchanged during interactions, and can also be injected into a running simulation. The entire framework has been parallelized to allow for larger simulations in an HPC environment. We have also added more detail to the agents themselves (a"Big Five" personality model) and their interactions (an enhanced relationship model) for a more realistic representation.« less

Investigating the constraint imposed by column averaged PBL CO2 data within an atmospheric inversion framework

NASA Astrophysics Data System (ADS)

Schuh, A. E.; Kawa, S. R.; Denning, A. S.; Baker, D. F.; Ramanathan, A. K.

2014-12-01

It was initially hoped that the proposed Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) NASA mission could rectify diurnal fluxes through it's ability to measure during both days and nights. However, initial simulation results (Kawa et al 2010) showed limited skill at identifying diurnal differences in fluxes. We investigate the possibility of (1) supplementing ASCENDS with well chosen in-situ surface sites and/or (2) adding distinct column measurements for the PBL and free troposphere into the inversion framework to determine the impact on recovering net ecosystem exchange (NEE), as well as distinct gross primary production (GPP) and respiration fluxes. In particular, we run forward simulations and inversions with distinct respiration and GPP fluxes calculated from the SiB model (Baker et al 2008) and test the ability of an EnKF based inversion framework to recover a hypothetical tropical CO2 fertilization effect resulting in enhanced GPP. Baker, I. T.; Prihodko, L.; Denning, A. S.; Goulden, M.; Miller, S. & da Rocha, H. R. (2008), 'Seasonal drought stress in the Amazon: Reconciling 3 models and observations', Journal of Geophysical Research 113. Kawa, S. R.; MAO, J.; ABSHIRE, J. B.; J., C. G.; SUN, X. & WEAVER, C. J. (2010), 'Simulation studies for a space-based CO2 lidar mission.', Tellus B 62, 759-769.

Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

USGS Publications Warehouse

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-01-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology

NASA Astrophysics Data System (ADS)

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-11-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

FSM-F: Finite State Machine Based Framework for Denial of Service and Intrusion Detection in MANET.

PubMed

N Ahmed, Malik; Abdullah, Abdul Hanan; Kaiwartya, Omprakash

2016-01-01

Due to the continuous advancements in wireless communication in terms of quality of communication and affordability of the technology, the application area of Mobile Adhoc Networks (MANETs) significantly growing particularly in military and disaster management. Considering the sensitivity of the application areas, security in terms of detection of Denial of Service (DoS) and intrusion has become prime concern in research and development in the area. The security systems suggested in the past has state recognition problem where the system is not able to accurately identify the actual state of the network nodes due to the absence of clear definition of states of the nodes. In this context, this paper proposes a framework based on Finite State Machine (FSM) for denial of service and intrusion detection in MANETs. In particular, an Interruption Detection system for Adhoc On-demand Distance Vector (ID-AODV) protocol is presented based on finite state machine. The packet dropping and sequence number attacks are closely investigated and detection systems for both types of attacks are designed. The major functional modules of ID-AODV includes network monitoring system, finite state machine and attack detection model. Simulations are carried out in network simulator NS-2 to evaluate the performance of the proposed framework. A comparative evaluation of the performance is also performed with the state-of-the-art techniques: RIDAN and AODV. The performance evaluations attest the benefits of proposed framework in terms of providing better security for denial of service and intrusion detection attacks.

Effect of Coupling Point Selection on Distortion in Internet-distributed Hardware-in-the-Loop Simulation (PREPRINT)

DTIC Science & Technology

2011-04-01

USA, with a hybrid-powertrain-system simulator in Santa Clara, CA, USA ( Compere et al. 2006; Goodell et al. 2006; Brudnak et al. 2007) and, as a...based ( Compere et al. 2006; Goodell et al. 2006; Brudnak et al. 2007) frameworks, to address stability and distortion issues under a delayed coupling...loop simulation." Mechatronics 19(7): 1041-1042. Brudnak, M., M. Pozolo, V. Paul, S. Mohammad, W. Smith, M. Compere , J. Goodell, D. Holtz, T

A numerical framework for the direct simulation of dense particulate flow under explosive dispersal

NASA Astrophysics Data System (ADS)

Mo, H.; Lien, F.-S.; Zhang, F.; Cronin, D. S.

2018-05-01

In this paper, we present a Cartesian grid-based numerical framework for the direct simulation of dense particulate flow under explosive dispersal. This numerical framework is established through the integration of the following numerical techniques: (1) operator splitting for partitioned fluid-solid interaction in the time domain, (2) the second-order SSP Runge-Kutta method and third-order WENO scheme for temporal and spatial discretization of governing equations, (3) the front-tracking method for evolving phase interfaces, (4) a field function proposed for low-memory-cost multimaterial mesh generation and fast collision detection, (5) an immersed boundary method developed for treating arbitrarily irregular and changing boundaries, and (6) a deterministic multibody contact and collision model. Employing the developed framework, this paper further studies particle jet formation under explosive dispersal by considering the effects of particle properties, particulate payload morphologies, and burster pressures. By the simulation of the dispersal processes of dense particle systems driven by pressurized gas, in which the driver pressure reaches 1.01325× 10^{10} Pa (10^5 times the ambient pressure) and particles are impulsively accelerated from stationary to a speed that is more than 12000 m/s within 15 μ s, it is demonstrated that the presented framework is able to effectively resolve coupled shock-shock, shock-particle, and particle-particle interactions in complex fluid-solid systems with shocked flow conditions, arbitrarily irregular particle shapes, and realistic multibody collisions.

Reduced-Order Aerothermoelastic Analysis of Hypersonic Vehicle Structures

NASA Astrophysics Data System (ADS)

Falkiewicz, Nathan J.

Design and simulation of hypersonic vehicles require consideration of a variety of disciplines due to the highly coupled nature of the flight regime. In order to capture all of the potential effects on vehicle dynamics, one must consider the aerodynamics, aerodynamic heating, heat transfer, and structural dynamics as well as the interactions between these disciplines. The problem is further complicated by the large computational expense involved in capturing all of these effects and their interactions in a full-order sense. While high-fidelity modeling techniques exist for each of these disciplines, the use of such techniques is computationally infeasible in a vehicle design and control system simulation setting for such a highly coupled problem. Early in the design stage, many iterations of analyses may need to be carried out as the vehicle design matures, thus requiring quick analysis turnaround time. Additionally, the number of states used in the analyses must be small enough to allow for efficient control simulation and design. As a result, alternatives to full-order models must be considered. This dissertation presents a fully coupled, reduced-order aerothermoelastic framework for the modeling and analysis of hypersonic vehicle structures. The reduced-order transient thermal solution is a modal solution based on the proper orthogonal decomposition. The reduced-order structural dynamic model is based on projection of the equations of motion onto a Ritz modal subspace that is identified a priori. The reduced-order models are assembled into a time-domain aerothermoelastic simulation framework which uses a partitioned time-marching scheme to account for the disparate time scales of the associated physics. The aerothermoelastic modeling framework is outlined and the formulations associated with the unsteady aerodynamics, aerodynamic heating, transient thermal, and structural dynamics are outlined. Results demonstrate the accuracy of the reduced-order transient thermal and structural dynamic models under variation in boundary conditions and flight conditions. The framework is applied to representative hypersonic vehicle control surface structures and a variety of studies are conducted to assess the impact of aerothermoelastic effects on hypersonic vehicle dynamics. The results presented in this dissertation demonstrate the ability of the proposed framework to perform efficient aerothermoelastic analysis.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The approach used follows the non-equilibrium statistical mechanical approach through a master equation. The aim is to represent the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and mass flux is a non-linear function of convective cell area, mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated mass flux variability under diurnally varying forcing. Besides its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to be capable of providing alternative, non-equilibrium, closure formulations for spectral mass flux parameterizations.« less

Ca-Pri a Cellular Automata Phenomenological Research Investigation: Simulation Results

NASA Astrophysics Data System (ADS)

Iannone, G.; Troisi, A.

2013-05-01

Following the introduction of a phenomenological cellular automata (CA) model capable to reproduce city growth and urban sprawl, we develop a toy model simulation considering a realistic framework. The main characteristic of our approach is an evolution algorithm based on inhabitants preferences. The control of grown cells is obtained by means of suitable functions which depend on the initial condition of the simulation. New born urban settlements are achieved by means of a logistic evolution of the urban pattern while urban sprawl is controlled by means of the population evolution function. In order to compare model results with a realistic urban framework we have considered, as the area of study, the island of Capri (Italy) in the Mediterranean Sea. Two different phases of the urban evolution on the island have been taken into account: a new born initial growth as induced by geographic suitability and the simulation of urban spread after 1943 induced by the population evolution after this date.

Particle acceleration in solar active regions being in the state of self-organized criticality.

NASA Astrophysics Data System (ADS)

Vlahos, Loukas

We review the recent observational results on flare initiation and particle acceleration in solar active regions. Elaborating a statistical approach to describe the spatiotemporally intermittent electric field structures formed inside a flaring solar active region, we investigate the efficiency of such structures in accelerating charged particles (electrons and protons). The large-scale magnetic configuration in the solar atmosphere responds to the strong turbulent flows that convey perturbations across the active region by initiating avalanche-type processes. The resulting unstable structures correspond to small-scale dissipation regions hosting strong electric fields. Previous research on particle acceleration in strongly turbulent plasmas provides a general framework for addressing such a problem. This framework combines various electromagnetic field configurations obtained by magnetohydrodynamical (MHD) or cellular automata (CA) simulations, or by employing a statistical description of the field’s strength and configuration with test particle simulations. We work on data-driven 3D magnetic field extrapolations, based on a self-organized criticality models (SOC). A relativistic test-particle simulation traces each particle’s guiding center within these configurations. Using the simulated particle-energy distributions we test our results against observations, in the framework of the collisional thick target model (CTTM) of solar hard X-ray (HXR) emission and compare our results with the current observations.

Teaching professionalism in graduate medical education: What is the role of simulation?

PubMed

Wali, Eisha; Pinto, Jayant M; Cappaert, Melissa; Lambrix, Marcie; Blood, Angela D; Blair, Elizabeth A; Small, Stephen D

2016-09-01

We systematically reviewed the literature concerning simulation-based teaching and assessment of the Accreditation Council for Graduate Medical Education professionalism competencies to elucidate best practices and facilitate further research. A systematic review of English literature for "professionalism" and "simulation(s)" yielded 697 abstracts. Two independent raters chose abstracts that (1) focused on graduate medical education, (2) described the simulation method, and (3) used simulation to train or assess professionalism. Fifty abstracts met the criteria, and seven were excluded for lack of relevant information. The raters, 6 professionals with medical education, simulation, and clinical experience, discussed 5 of these articles as a group; they calibrated coding and applied further refinements, resulting in a final, iteratively developed evaluation form. The raters then divided into 2 teams to read and assess the remaining articles. Overall, 15 articles were eliminated, and 28 articles underwent final analysis. Papers addressed a heterogeneous range of professionalism content via multiple methods. Common specialties represented were surgery (46.4%), pediatrics (17.9%), and emergency medicine (14.3%). Sixteen articles (57%) referenced a professionalism framework; 14 (50%) incorporated an assessment tool; and 17 (60.7%) reported debriefing participants, though in limited detail. Twenty-three (82.1%) articles evaluated programs, mostly using subjective trainee reports. Despite early innovation, reporting of simulation-based professionalism training and assessment is nonstandardized in methods and terminology and lacks the details required for replication. We offer minimum standards for reporting of future professionalism-focused simulation training and assessment as well as a basic framework for better mapping proper simulation methods to the targeted domain of professionalism. Copyright © 2016 Elsevier Inc. All rights reserved.

A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion

NASA Astrophysics Data System (ADS)

Lee, Seungjoon; Kevrekidis, Ioannis G.; Karniadakis, George Em

2017-09-01

Exascale-level simulations require fault-resilient algorithms that are robust against repeated and expected software and/or hardware failures during computations, which may render the simulation results unsatisfactory. If each processor can share some global information about the simulation from a coarse, limited accuracy but relatively costless auxiliary simulator we can effectively fill-in the missing spatial data at the required times by a statistical learning technique - multi-level Gaussian process regression, on the fly; this has been demonstrated in previous work [1]. Based on the previous work, we also employ another (nonlinear) statistical learning technique, Diffusion Maps, that detects computational redundancy in time and hence accelerate the simulation by projective time integration, giving the overall computation a "patch dynamics" flavor. Furthermore, we are now able to perform information fusion with multi-fidelity and heterogeneous data (including stochastic data). Finally, we set the foundations of a new framework in CFD, called patch simulation, that combines information fusion techniques from, in principle, multiple fidelity and resolution simulations (and even experiments) with a new adaptive timestep refinement technique. We present two benchmark problems (the heat equation and the Navier-Stokes equations) to demonstrate the new capability that statistical learning tools can bring to traditional scientific computing algorithms. For each problem, we rely on heterogeneous and multi-fidelity data, either from a coarse simulation of the same equation or from a stochastic, particle-based, more "microscopic" simulation. We consider, as such "auxiliary" models, a Monte Carlo random walk for the heat equation and a dissipative particle dynamics (DPD) model for the Navier-Stokes equations. More broadly, in this paper we demonstrate the symbiotic and synergistic combination of statistical learning, domain decomposition, and scientific computing in exascale simulations.

Pitting corrosion as a mixed system: coupled deterministic-probabilistic simulation of pit growth

NASA Astrophysics Data System (ADS)

Ibrahim, Israr B. M.; Fonna, S.; Pidaparti, R.

2018-05-01

Stochastic behavior of pitting corrosion poses a unique challenge in its computational analysis. However, it also stems from electrochemical activity causing general corrosion. In this paper, a framework for corrosion pit growth simulation based on the coupling of the Cellular Automaton (CA) and Boundary Element Methods (BEM) is presented. The framework assumes that pitting corrosion is controlled by electrochemical activity inside the pit cavity. The BEM provides the prediction of electrochemical activity given the geometrical data and polarization curves, while the CA is used to simulate the evolution of pit shapes based on electrochemical activity provided by BEM. To demonstrate the methodology, a sample case of local corrosion cells formed in pitting corrosion with varied dimensions and polarization functions is considered. Results show certain shapes tend to grow in certain types of environments. Some pit shapes appear to pose a higher risk by being potentially significant stress raisers or potentially increasing the rate of corrosion under the surface. Furthermore, these pits are comparable to commonly observed pit shapes in general corrosion environments.

Merging Problem-Based Learning with Simulation-Based Learning in the Medical Undergraduate Curriculum: The PAIRED Framework for Enhancing Lifelong Learning

PubMed Central

Koh, Jansen

2016-01-01

Lifelong learning is an essential trait that is expected of every physician. The CanMeds 2005 Physician Competency Framework emphasizes lifelong learning as a key competency that physicians must achieve in becoming better physicians. However, many physicians are not competent at engaging in lifelong learning. The current medical education system is deficient in preparing medical students to develop and carry out their own lifelong learning curriculum upon graduation. Despite understanding how physicians learn at work, medical students are not trained to learn while working. Similarly, although barriers to lifelong learning are known, medical students are not adequately skilled in overcoming these barriers. Learning to learn is just as important, if not more, as acquiring the skills and knowledge required of a physician. The medical undergraduate curriculum lacks a specific learning strategy to prepare medical students in becoming an adept lifelong learner. In this article, we propose a learning strategy for lifelong learning at the undergraduate level. In developing this novel strategy, we paid particular attention to two parameters. First, this strategy should be grounded on literature describing a physician’s lifelong learning process. Second, the framework for implementing this strategy must be based on existing undergraduate learning strategies to obviate the need for additional resources, learner burden, and faculty time. In this paper, we propose a Problem, Analysis, Independent Research Reporting, Experimentation Debriefing (PAIRED) framework that follows the learning process of a physician and serves to synergize the components of problem-based learning and simulation-based learning in specifically targeting the barriers to lifelong learning. PMID:27446767

Modeling wildlife populations with HexSim

EPA Science Inventory

HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications including population viability analysis for on...

Agent-based large-scale emergency evacuation using real-time open government data.

DOT National Transportation Integrated Search

2014-01-01

The open government initiatives have provided tremendous data resources for the : transportation system and emergency services in urban areas. This paper proposes : a traffic simulation framework using high temporal resolution demographic data : and ...

Framework for multi-resolution analyses of advanced traffic management strategies [summary].

DOT National Transportation Integrated Search

2017-01-01

Transportation planning relies extensively on software that can simulate and predict travel behavior in response to alternative transportation networks. However, different software packages view traffic at different scales. Some programs are based on...

Life cycle assessment framework of traffic systems based on microscopic simulation.

DOT National Transportation Integrated Search

2014-03-01

Transportation is an important infrastructure process needed in many steps of the supply chain of any product. Transportation-associated global impacts are therefore important factor influencing the sustainability of any product cycle. Moreover, traf...

Texas two-step: a framework for optimal multi-input single-output deconvolution.

PubMed

Neelamani, Ramesh; Deffenbaugh, Max; Baraniuk, Richard G

2007-11-01

Multi-input single-output deconvolution (MISO-D) aims to extract a deblurred estimate of a target signal from several blurred and noisy observations. This paper develops a new two step framework--Texas Two-Step--to solve MISO-D problems with known blurs. Texas Two-Step first reduces the MISO-D problem to a related single-input single-output deconvolution (SISO-D) problem by invoking the concept of sufficient statistics (SSs) and then solves the simpler SISO-D problem using an appropriate technique. The two-step framework enables new MISO-D techniques (both optimal and suboptimal) based on the rich suite of existing SISO-D techniques. In fact, the properties of SSs imply that a MISO-D algorithm is mean-squared-error optimal if and only if it can be rearranged to conform to the Texas Two-Step framework. Using this insight, we construct new wavelet- and curvelet-based MISO-D algorithms with asymptotically optimal performance. Simulated and real data experiments verify that the framework is indeed effective.

An Efficient Finite Element Framework to Assess Flexibility Performances of SMA Self-Expandable Carotid Artery Stents

PubMed Central

Ferraro, Mauro; Auricchio, Ferdinando; Boatti, Elisa; Scalet, Giulia; Conti, Michele; Morganti, Simone; Reali, Alessandro

2015-01-01

Computer-based simulations are nowadays widely exploited for the prediction of the mechanical behavior of different biomedical devices. In this aspect, structural finite element analyses (FEA) are currently the preferred computational tool to evaluate the stent response under bending. This work aims at developing a computational framework based on linear and higher order FEA to evaluate the flexibility of self-expandable carotid artery stents. In particular, numerical simulations involving large deformations and inelastic shape memory alloy constitutive modeling are performed, and the results suggest that the employment of higher order FEA allows accurately representing the computational domain and getting a better approximation of the solution with a widely-reduced number of degrees of freedom with respect to linear FEA. Moreover, when buckling phenomena occur, higher order FEA presents a superior capability of reproducing the nonlinear local effects related to buckling phenomena. PMID:26184329

Simulation of Blast Loading on an Ultrastructurally-based Computational Model of the Ocular Lens

DTIC Science & Technology

2016-12-01

organelles. Additionally, the cell membranes demonstrated the classic ball-and-socket loops . For the SEM images, they were placed in two fixatives and mounted...considered (fibrous network and matrix), both components are modelled using a hyper - elastic framework, and the resulting constitutive model is embedded in a...within the framework of hyper - elasticity). Full details on the linearization procedures that were adopted in these previous models or the convergence

Embedding Task-Based Neural Models into a Connectome-Based Model of the Cerebral Cortex.

PubMed

Ulloa, Antonio; Horwitz, Barry

2016-01-01

A number of recent efforts have used large-scale, biologically realistic, neural models to help understand the neural basis for the patterns of activity observed in both resting state and task-related functional neural imaging data. An example of the former is The Virtual Brain (TVB) software platform, which allows one to apply large-scale neural modeling in a whole brain framework. TVB provides a set of structural connectomes of the human cerebral cortex, a collection of neural processing units for each connectome node, and various forward models that can convert simulated neural activity into a variety of functional brain imaging signals. In this paper, we demonstrate how to embed a previously or newly constructed task-based large-scale neural model into the TVB platform. We tested our method on a previously constructed large-scale neural model (LSNM) of visual object processing that consisted of interconnected neural populations that represent, primary and secondary visual, inferotemporal, and prefrontal cortex. Some neural elements in the original model were "non-task-specific" (NS) neurons that served as noise generators to "task-specific" neurons that processed shapes during a delayed match-to-sample (DMS) task. We replaced the NS neurons with an anatomical TVB connectome model of the cerebral cortex comprising 998 regions of interest interconnected by white matter fiber tract weights. We embedded our LSNM of visual object processing into corresponding nodes within the TVB connectome. Reciprocal connections between TVB nodes and our task-based modules were included in this framework. We ran visual object processing simulations and showed that the TVB simulator successfully replaced the noise generation originally provided by NS neurons; i.e., the DMS tasks performed with the hybrid LSNM/TVB simulator generated equivalent neural and fMRI activity to that of the original task-based models. Additionally, we found partial agreement between the functional connectivities using the hybrid LSNM/TVB model and the original LSNM. Our framework thus presents a way to embed task-based neural models into the TVB platform, enabling a better comparison between empirical and computational data, which in turn can lead to a better understanding of how interacting neural populations give rise to human cognitive behaviors.

A scalable delivery framework and a pricing model for streaming media with advertisements

NASA Astrophysics Data System (ADS)

Al-Hadrusi, Musab; Sarhan, Nabil J.

2008-01-01

This paper presents a delivery framework for streaming media with advertisements and an associated pricing model. The delivery model combines the benefits of periodic broadcasting and stream merging. The advertisements' revenues are used to subsidize the price of the media content. The pricing is determined based on the total ads' viewing time. Moreover, this paper presents an efficient ad allocation scheme and three modified scheduling policies that are well suited to the proposed delivery framework. Furthermore, we study the effectiveness of the delivery framework and various scheduling polices through extensive simulation in terms of numerous metrics, including customer defection probability, average number of ads viewed per client, price, arrival rate, profit, and revenue.

1D-3D hybrid modeling-from multi-compartment models to full resolution models in space and time.

PubMed

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator-which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics.

The SCEC Unified Community Velocity Model (UCVM) Software Framework for Distributing and Querying Seismic Velocity Models

NASA Astrophysics Data System (ADS)

Maechling, P. J.; Taborda, R.; Callaghan, S.; Shaw, J. H.; Plesch, A.; Olsen, K. B.; Jordan, T. H.; Goulet, C. A.

2017-12-01

Crustal seismic velocity models and datasets play a key role in regional three-dimensional numerical earthquake ground-motion simulation, full waveform tomography, modern physics-based probabilistic earthquake hazard analysis, as well as in other related fields including geophysics, seismology, and earthquake engineering. The standard material properties provided by a seismic velocity model are P- and S-wave velocities and density for any arbitrary point within the geographic volume for which the model is defined. Many seismic velocity models and datasets are constructed by synthesizing information from multiple sources and the resulting models are delivered to users in multiple file formats, such as text files, binary files, HDF-5 files, structured and unstructured grids, and through computer applications that allow for interactive querying of material properties. The Southern California Earthquake Center (SCEC) has developed the Unified Community Velocity Model (UCVM) software framework to facilitate the registration and distribution of existing and future seismic velocity models to the SCEC community. The UCVM software framework is designed to provide a standard query interface to multiple, alternative velocity models, even if the underlying velocity models are defined in different formats or use different geographic projections. The UCVM framework provides a comprehensive set of open-source tools for querying seismic velocity model properties, combining regional 3D models and 1D background models, visualizing 3D models, and generating computational models in the form of regular grids or unstructured meshes that can be used as inputs for ground-motion simulations. The UCVM framework helps researchers compare seismic velocity models and build equivalent simulation meshes from alternative velocity models. These capabilities enable researchers to evaluate the impact of alternative velocity models in ground-motion simulations and seismic hazard analysis applications. In this poster, we summarize the key components of the UCVM framework and describe the impact it has had in various computational geoscientific applications.

Overarching framework for data-based modelling

NASA Astrophysics Data System (ADS)

Schelter, Björn; Mader, Malenka; Mader, Wolfgang; Sommerlade, Linda; Platt, Bettina; Lai, Ying-Cheng; Grebogi, Celso; Thiel, Marco

2014-02-01

One of the main modelling paradigms for complex physical systems are networks. When estimating the network structure from measured signals, typically several assumptions such as stationarity are made in the estimation process. Violating these assumptions renders standard analysis techniques fruitless. We here propose a framework to estimate the network structure from measurements of arbitrary non-linear, non-stationary, stochastic processes. To this end, we propose a rigorous mathematical theory that underlies this framework. Based on this theory, we present a highly efficient algorithm and the corresponding statistics that are immediately sensibly applicable to measured signals. We demonstrate its performance in a simulation study. In experiments of transitions between vigilance stages in rodents, we infer small network structures with complex, time-dependent interactions; this suggests biomarkers for such transitions, the key to understand and diagnose numerous diseases such as dementia. We argue that the suggested framework combines features that other approaches followed so far lack.

Market-Based Coordination of Thermostatically Controlled Loads—Part II: Unknown Parameters and Case Studies

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

Li, Sen; Zhang, Wei; Lian, Jianming

This two-part paper considers the coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the bidding and market clearing strategy to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. The companion paper (Part I) formulates the problem and proposes a load coordination framework using the mechanism design approach. To address the unknown parameters, Part II of this paper presents a joint state and parameter estimation framework based on the expectation maximization algorithm. The overall framework is then validated using real-world weather data andmore » price data, and is compared with other approaches in terms of aggregated power response. Simulation results indicate that our coordination framework can effectively improve the efficiency of the power grid operations and reduce power congestion at key times.« less

An application framework of three-dimensional reconstruction and measurement for endodontic research.

PubMed

Gao, Yuan; Peters, Ove A; Wu, Hongkun; Zhou, Xuedong

2009-02-01

The purpose of this study was to customize an application framework by using the MeVisLab image processing and visualization platform for three-dimensional reconstruction and assessment of tooth and root canal morphology. One maxillary first molar was scanned before and after preparation with ProTaper by using micro-computed tomography. With a customized application framework based on MeVisLab, internal and external anatomy was reconstructed. Furthermore, the dimensions of root canal and radicular dentin were quantified, and effects of canal preparation were assessed. Finally, a virtual preparation with risk analysis was performed to simulate the removal of a broken instrument. This application framework provided an economical platform and met current requirements of endodontic research. The broad-based use of high-quality free software and the resulting exchange of experience might help to improve the quality of endodontic research with micro-computed tomography.

Comparing volume of fluid and level set methods for evaporating liquid-gas flows

NASA Astrophysics Data System (ADS)

Palmore, John; Desjardins, Olivier

2016-11-01

This presentation demonstrates three numerical strategies for simulating liquid-gas flows undergoing evaporation. The practical aim of this work is to choose a framework capable of simulating the combustion of liquid fuels in an internal combustion engine. Each framework is analyzed with respect to its accuracy and computational cost. All simulations are performed using a conservative, finite volume code for simulating reacting, multiphase flows under the low-Mach assumption. The strategies used in this study correspond to different methods for tracking the liquid-gas interface and handling the transport of the discontinuous momentum and vapor mass fractions fields. The first two strategies are based on conservative, geometric volume of fluid schemes using directionally split and un-split advection, respectively. The third strategy is the accurate conservative level set method. For all strategies, special attention is given to ensuring the consistency between the fluxes of mass, momentum, and vapor fractions. The study performs three-dimensional simulations of an isolated droplet of a single component fuel evaporating into air. Evaporation rates and vapor mass fractions are compared to analytical results.

Computational system identification of continuous-time nonlinear systems using approximate Bayesian computation

NASA Astrophysics Data System (ADS)

Krishnanathan, Kirubhakaran; Anderson, Sean R.; Billings, Stephen A.; Kadirkamanathan, Visakan

2016-11-01

In this paper, we derive a system identification framework for continuous-time nonlinear systems, for the first time using a simulation-focused computational Bayesian approach. Simulation approaches to nonlinear system identification have been shown to outperform regression methods under certain conditions, such as non-persistently exciting inputs and fast-sampling. We use the approximate Bayesian computation (ABC) algorithm to perform simulation-based inference of model parameters. The framework has the following main advantages: (1) parameter distributions are intrinsically generated, giving the user a clear description of uncertainty, (2) the simulation approach avoids the difficult problem of estimating signal derivatives as is common with other continuous-time methods, and (3) as noted above, the simulation approach improves identification under conditions of non-persistently exciting inputs and fast-sampling. Term selection is performed by judging parameter significance using parameter distributions that are intrinsically generated as part of the ABC procedure. The results from a numerical example demonstrate that the method performs well in noisy scenarios, especially in comparison to competing techniques that rely on signal derivative estimation.

Consistent Simulation Framework for Efficient Mass Discharge and Source Depletion Time Predictions of DNAPL Contaminants in Heterogeneous Aquifers Under Uncertainty

NASA Astrophysics Data System (ADS)

Nowak, W.; Koch, J.

2014-12-01

Predicting DNAPL fate and transport in heterogeneous aquifers is challenging and subject to an uncertainty that needs to be quantified. Models for this task needs to be equipped with an accurate source zone description, i.e., the distribution of mass of all partitioning phases (DNAPL, water, and soil) in all possible states ((im)mobile, dissolved, and sorbed), mass-transfer algorithms, and the simulation of transport processes in the groundwater. Such detailed models tend to be computationally cumbersome when used for uncertainty quantification. Therefore, a selective choice of the relevant model states, processes, and scales are both sensitive and indispensable. We investigate the questions: what is a meaningful level of model complexity and how to obtain an efficient model framework that is still physically and statistically consistent. In our proposed model, aquifer parameters and the contaminant source architecture are conceptualized jointly as random space functions. The governing processes are simulated in a three-dimensional, highly-resolved, stochastic, and coupled model that can predict probability density functions of mass discharge and source depletion times. We apply a stochastic percolation approach as an emulator to simulate the contaminant source formation, a random walk particle tracking method to simulate DNAPL dissolution and solute transport within the aqueous phase, and a quasi-steady-state approach to solve for DNAPL depletion times. Using this novel model framework, we test whether and to which degree the desired model predictions are sensitive to simplifications often found in the literature. With this we identify that aquifer heterogeneity, groundwater flow irregularity, uncertain and physically-based contaminant source zones, and their mutual interlinkages are indispensable components of a sound model framework.

A virtual surgical training system that simulates cutting of soft tissue using a modified pre-computed elastic model.

PubMed

Toe, Kyaw Kyar; Huang, Weimin; Yang, Tao; Duan, Yuping; Zhou, Jiayin; Su, Yi; Teo, Soo-Kng; Kumar, Selvaraj Senthil; Lim, Calvin Chi-Wan; Chui, Chee Kong; Chang, Stephen

2015-08-01

This work presents a surgical training system that incorporates cutting operation of soft tissue simulated based on a modified pre-computed linear elastic model in the Simulation Open Framework Architecture (SOFA) environment. A precomputed linear elastic model used for the simulation of soft tissue deformation involves computing the compliance matrix a priori based on the topological information of the mesh. While this process may require a few minutes to several hours, based on the number of vertices in the mesh, it needs only to be computed once and allows real-time computation of the subsequent soft tissue deformation. However, as the compliance matrix is based on the initial topology of the mesh, it does not allow any topological changes during simulation, such as cutting or tearing of the mesh. This work proposes a way to modify the pre-computed data by correcting the topological connectivity in the compliance matrix, without re-computing the compliance matrix which is computationally expensive.

Investigations into phase effects from diffracted Gaussian beams for high-precision interferometry

NASA Astrophysics Data System (ADS)

Lodhia, Deepali

Gravitational wave detectors are a new class of observatories aiming to detect gravitational waves from cosmic sources. All-reflective interferometer configurations have been proposed for future detectors, replacing transmissive optics with diffractive elements, thereby reducing thermal issues associated with power absorption. However, diffraction gratings introduce additional phase noise, creating more stringent conditions for alignment stability, and further investigations are required into all-reflective interferometers. A suitable mathematical framework using Gaussian modes is required for analysing the alignment stability using diffraction gratings. Such a framework was created, whereby small beam displacements are modelled using a modal technique. It was confirmed that the original modal-based model does not contain the phase changes associated with grating displacements. Experimental tests verified that the phase of a diffracted Gaussian beam is independent of the beam shape. Phase effects were further examined using a rigorous time-domain simulation tool. These findings show that the perceived phase difference is based on an intrinsic change of coordinate system within the modal-based model, and that the extra phase can be added manually to the modal expansion. This thesis provides a well-tested and detailed mathematical framework that can be used to develop simulation codes to model more complex layouts of all-reflective interferometers.

Cooperative interactions in dense thermal Rb vapour confined in nm-scale cells

NASA Astrophysics Data System (ADS)

Keaveney, James

Gravitational wave detectors are a new class of observatories aiming to detect gravitational waves from cosmic sources. All-reflective interferometer configurations have been proposed for future detectors, replacing transmissive optics with diffractive elements, thereby reducing thermal issues associated with power absorption. However, diffraction gratings introduce additional phase noise, creating more stringent conditions for alignment stability, and further investigations are required into all-reflective interferometers. A suitable mathematical framework using Gaussian modes is required for analysing the alignment stability using diffraction gratings. Such a framework was created, whereby small beam displacements are modelled using a modal technique. It was confirmed that the original modal-based model does not contain the phase changes associated with grating displacements. Experimental tests verified that the phase of a diffracted Gaussian beam is independent of the beam shape. Phase effects were further examined using a rigorous time-domain simulation tool. These findings show that the perceived phase difference is based on an intrinsic change of coordinate system within the modal-based model, and that the extra phase can be added manually to the modal expansion. This thesis provides a well-tested and detailed mathematical framework that can be used to develop simulation codes to model more complex layouts of all-reflective interferometers.

Towards a voxel-based geographic automata for the simulation of geospatial processes

NASA Astrophysics Data System (ADS)

Jjumba, Anthony; Dragićević, Suzana

2016-07-01

Many geographic processes evolve in a three dimensional space and time continuum. However, when they are represented with the aid of geographic information systems (GIS) or geosimulation models they are modelled in a framework of two-dimensional space with an added temporal component. The objective of this study is to propose the design and implementation of voxel-based automata as a methodological approach for representing spatial processes evolving in the four-dimensional (4D) space-time domain. Similar to geographic automata models which are developed to capture and forecast geospatial processes that change in a two-dimensional spatial framework using cells (raster geospatial data), voxel automata rely on the automata theory and use three-dimensional volumetric units (voxels). Transition rules have been developed to represent various spatial processes which range from the movement of an object in 3D to the diffusion of airborne particles and landslide simulation. In addition, the proposed 4D models demonstrate that complex processes can be readily reproduced from simple transition functions without complex methodological approaches. The voxel-based automata approach provides a unique basis to model geospatial processes in 4D for the purpose of improving representation, analysis and understanding their spatiotemporal dynamics. This study contributes to the advancement of the concepts and framework of 4D GIS.

Sequential-Optimization-Based Framework for Robust Modeling and Design of Heterogeneous Catalytic Systems

DOE PAGES

Rangarajan, Srinivas; Maravelias, Christos T.; Mavrikakis, Manos

2017-11-09

Here, we present a general optimization-based framework for (i) ab initio and experimental data driven mechanistic modeling and (ii) optimal catalyst design of heterogeneous catalytic systems. Both cases are formulated as a nonlinear optimization problem that is subject to a mean-field microkinetic model and thermodynamic consistency requirements as constraints, for which we seek sparse solutions through a ridge (L 2 regularization) penalty. The solution procedure involves an iterative sequence of forward simulation of the differential algebraic equations pertaining to the microkinetic model using a numerical tool capable of handling stiff systems, sensitivity calculations using linear algebra, and gradient-based nonlinear optimization.more » A multistart approach is used to explore the solution space, and a hierarchical clustering procedure is implemented for statistically classifying potentially competing solutions. An example of methanol synthesis through hydrogenation of CO and CO 2 on a Cu-based catalyst is used to illustrate the framework. The framework is fast, is robust, and can be used to comprehensively explore the model solution and design space of any heterogeneous catalytic system.« less

Sequential-Optimization-Based Framework for Robust Modeling and Design of Heterogeneous Catalytic Systems

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

Rangarajan, Srinivas; Maravelias, Christos T.; Mavrikakis, Manos

Here, we present a general optimization-based framework for (i) ab initio and experimental data driven mechanistic modeling and (ii) optimal catalyst design of heterogeneous catalytic systems. Both cases are formulated as a nonlinear optimization problem that is subject to a mean-field microkinetic model and thermodynamic consistency requirements as constraints, for which we seek sparse solutions through a ridge (L 2 regularization) penalty. The solution procedure involves an iterative sequence of forward simulation of the differential algebraic equations pertaining to the microkinetic model using a numerical tool capable of handling stiff systems, sensitivity calculations using linear algebra, and gradient-based nonlinear optimization.more » A multistart approach is used to explore the solution space, and a hierarchical clustering procedure is implemented for statistically classifying potentially competing solutions. An example of methanol synthesis through hydrogenation of CO and CO 2 on a Cu-based catalyst is used to illustrate the framework. The framework is fast, is robust, and can be used to comprehensively explore the model solution and design space of any heterogeneous catalytic system.« less

A Modeling Framework for Optimal Computational Resource Allocation Estimation: Considering the Trade-offs between Physical Resolutions, Uncertainty and Computational Costs

NASA Astrophysics Data System (ADS)

Moslehi, M.; de Barros, F.; Rajagopal, R.

2014-12-01

Hydrogeological models that represent flow and transport in subsurface domains are usually large-scale with excessive computational complexity and uncertain characteristics. Uncertainty quantification for predicting flow and transport in heterogeneous formations often entails utilizing a numerical Monte Carlo framework, which repeatedly simulates the model according to a random field representing hydrogeological characteristics of the field. The physical resolution (e.g. grid resolution associated with the physical space) for the simulation is customarily chosen based on recommendations in the literature, independent of the number of Monte Carlo realizations. This practice may lead to either excessive computational burden or inaccurate solutions. We propose an optimization-based methodology that considers the trade-off between the following conflicting objectives: time associated with computational costs, statistical convergence of the model predictions and physical errors corresponding to numerical grid resolution. In this research, we optimally allocate computational resources by developing a modeling framework for the overall error based on a joint statistical and numerical analysis and optimizing the error model subject to a given computational constraint. The derived expression for the overall error explicitly takes into account the joint dependence between the discretization error of the physical space and the statistical error associated with Monte Carlo realizations. The accuracy of the proposed framework is verified in this study by applying it to several computationally extensive examples. Having this framework at hand aims hydrogeologists to achieve the optimum physical and statistical resolutions to minimize the error with a given computational budget. Moreover, the influence of the available computational resources and the geometric properties of the contaminant source zone on the optimum resolutions are investigated. We conclude that the computational cost associated with optimal allocation can be substantially reduced compared with prevalent recommendations in the literature.

Enabling Big Geoscience Data Analytics with a Cloud-Based, MapReduce-Enabled and Service-Oriented Workflow Framework

PubMed Central

Li, Zhenlong; Yang, Chaowei; Jin, Baoxuan; Yu, Manzhu; Liu, Kai; Sun, Min; Zhan, Matthew

2015-01-01

Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists. PMID:25742012

Enabling big geoscience data analytics with a cloud-based, MapReduce-enabled and service-oriented workflow framework.

PubMed

Li, Zhenlong; Yang, Chaowei; Jin, Baoxuan; Yu, Manzhu; Liu, Kai; Sun, Min; Zhan, Matthew

2015-01-01

Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists.

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions

DOE PAGES

Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea; ...

2018-02-06

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density andmore » local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.« less

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions

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

Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density andmore » local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.« less

Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier–Stokes simulations: A data-driven, physics-informed Bayesian approach

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

Xiao, H., E-mail: hengxiao@vt.edu; Wu, J.-L.; Wang, J.-X.

Despite their well-known limitations, Reynolds-Averaged Navier–Stokes (RANS) models are still the workhorse tools for turbulent flow simulations in today's engineering analysis, design and optimization. While the predictive capability of RANS models depends on many factors, for many practical flows the turbulence models are by far the largest source of uncertainty. As RANS models are used in the design and safety evaluation of many mission-critical systems such as airplanes and nuclear power plants, quantifying their model-form uncertainties has significant implications in enabling risk-informed decision-making. In this work we develop a data-driven, physics-informed Bayesian framework for quantifying model-form uncertainties in RANS simulations.more » Uncertainties are introduced directly to the Reynolds stresses and are represented with compact parameterization accounting for empirical prior knowledge and physical constraints (e.g., realizability, smoothness, and symmetry). An iterative ensemble Kalman method is used to assimilate the prior knowledge and observation data in a Bayesian framework, and to propagate them to posterior distributions of velocities and other Quantities of Interest (QoIs). We use two representative cases, the flow over periodic hills and the flow in a square duct, to evaluate the performance of the proposed framework. Both cases are challenging for standard RANS turbulence models. Simulation results suggest that, even with very sparse observations, the obtained posterior mean velocities and other QoIs have significantly better agreement with the benchmark data compared to the baseline results. At most locations the posterior distribution adequately captures the true model error within the developed model form uncertainty bounds. The framework is a major improvement over existing black-box, physics-neutral methods for model-form uncertainty quantification, where prior knowledge and details of the models are not exploited. This approach has potential implications in many fields in which the governing equations are well understood but the model uncertainty comes from unresolved physical processes. - Highlights: • Proposed a physics–informed framework to quantify uncertainty in RANS simulations. • Framework incorporates physical prior knowledge and observation data. • Based on a rigorous Bayesian framework yet fully utilizes physical model. • Applicable for many complex physical systems beyond turbulent flows.« less

High-fidelity simulations of unsteady civil aircraft aerodynamics: stakes and perspectives. Application of zonal detached eddy simulation.

PubMed

Deck, Sébastien; Gand, Fabien; Brunet, Vincent; Ben Khelil, Saloua

2014-08-13

This paper provides an up-to-date survey of the use of zonal detached eddy simulations (ZDES) for unsteady civil aircraft applications as a reflection on the stakes and perspectives of the use of hybrid methods in the framework of industrial aerodynamics. The issue of zonal or non-zonal treatment of turbulent flows for engineering applications is discussed. The ZDES method used in this article and based on a fluid problem-dependent zonalization is briefly presented. Some recent landmark achievements for conditions all over the flight envelope are presented, including low-speed (aeroacoustics of high-lift devices and landing gear), cruising (engine-airframe interactions), propulsive jets and off-design (transonic buffet and dive manoeuvres) applications. The implications of such results and remaining challenges in a more global framework are further discussed. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Faunus: An object oriented framework for molecular simulation

PubMed Central

Lund, Mikael; Trulsson, Martin; Persson, Björn

2008-01-01

Background We present a C++ class library for Monte Carlo simulation of molecular systems, including proteins in solution. The design is generic and highly modular, enabling multiple developers to easily implement additional features. The statistical mechanical methods are documented by extensive use of code comments that – subsequently – are collected to automatically build a web-based manual. Results We show how an object oriented design can be used to create an intuitively appealing coding framework for molecular simulation. This is exemplified in a minimalistic C++ program that can calculate protein protonation states. We further discuss performance issues related to high level coding abstraction. Conclusion C++ and the Standard Template Library (STL) provide a high-performance platform for generic molecular modeling. Automatic generation of code documentation from inline comments has proven particularly useful in that no separate manual needs to be maintained. PMID:18241331

Thermostating extended Lagrangian Born-Oppenheimer molecular dynamics

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

Martínez, Enrique; Cawkwell, Marc J.; Voter, Arthur F.

Here, Extended Lagrangian Born-Oppenheimer molecular dynamics is developed and analyzed for applications in canonical (NVT) simulations. Three different approaches are considered: the Nosé and Andersen thermostats and Langevin dynamics. We have tested the temperature distribution under different conditions of self-consistent field (SCF) convergence and time step and compared the results to analytical predictions. We find that the simulations based on the extended Lagrangian Born-Oppenheimer framework provide accurate canonical distributions even under approximate SCF convergence, often requiring only a single diagonalization per time step, whereas regular Born-Oppenheimer formulations exhibit unphysical fluctuations unless a sufficiently high degree of convergence is reached atmore » each time step. Lastly, the thermostated extended Lagrangian framework thus offers an accurate approach to sample processes in the canonical ensemble at a fraction of the computational cost of regular Born-Oppenheimer molecular dynamics simulations.« less

Thermostating extended Lagrangian Born-Oppenheimer molecular dynamics

DOE PAGES

Martínez, Enrique; Cawkwell, Marc J.; Voter, Arthur F.; ...

2015-04-21

Here, Extended Lagrangian Born-Oppenheimer molecular dynamics is developed and analyzed for applications in canonical (NVT) simulations. Three different approaches are considered: the Nosé and Andersen thermostats and Langevin dynamics. We have tested the temperature distribution under different conditions of self-consistent field (SCF) convergence and time step and compared the results to analytical predictions. We find that the simulations based on the extended Lagrangian Born-Oppenheimer framework provide accurate canonical distributions even under approximate SCF convergence, often requiring only a single diagonalization per time step, whereas regular Born-Oppenheimer formulations exhibit unphysical fluctuations unless a sufficiently high degree of convergence is reached atmore » each time step. Lastly, the thermostated extended Lagrangian framework thus offers an accurate approach to sample processes in the canonical ensemble at a fraction of the computational cost of regular Born-Oppenheimer molecular dynamics simulations.« less

Forecasting peaks of seasonal influenza epidemics.

PubMed

Nsoesie, Elaine; Mararthe, Madhav; Brownstein, John

2013-06-21

We present a framework for near real-time forecast of influenza epidemics using a simulation optimization approach. The method combines an individual-based model and a simple root finding optimization method for parameter estimation and forecasting. In this study, retrospective forecasts were generated for seasonal influenza epidemics using web-based estimates of influenza activity from Google Flu Trends for 2004-2005, 2007-2008 and 2012-2013 flu seasons. In some cases, the peak could be forecasted 5-6 weeks ahead. This study adds to existing resources for influenza forecasting and the proposed method can be used in conjunction with other approaches in an ensemble framework.

Predictor-Based Model Reference Adaptive Control

NASA Technical Reports Server (NTRS)

Lavretsky, Eugene; Gadient, Ross; Gregory, Irene M.

2010-01-01

This paper is devoted to the design and analysis of a predictor-based model reference adaptive control. Stable adaptive laws are derived using Lyapunov framework. The proposed architecture is compared with the now classical model reference adaptive control. A simulation example is presented in which numerical evidence indicates that the proposed controller yields improved transient characteristics.

Problem-Based Learning in Instrumentation: Synergism of Real and Virtual Modular Acquisition Chains

ERIC Educational Resources Information Center

Nonclercq, A.; Biest, A. V.; De Cuyper, K.; Leroy, E.; Martinez, D. L.; Robert, F.

2010-01-01

As part of an instrumentation course, a problem-based learning framework was selected for laboratory instruction. Two acquisition chains were designed to help students carry out realistic instrumentation problems. The first tool is a virtual (simulated) modular acquisition chain that allows rapid overall understanding of the main problems in…

1D-3D hybrid modeling—from multi-compartment models to full resolution models in space and time

PubMed Central

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M.; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator—which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics. PMID:25120463

The Development of Design Tools for Fault Tolerant Quantum Dot Cellular Automata Based Logic

NASA Technical Reports Server (NTRS)

Armstrong, Curtis D.; Humphreys, William M.

2003-01-01

We are developing software to explore the fault tolerance of quantum dot cellular automata gate architectures in the presence of manufacturing variations and device defects. The Topology Optimization Methodology using Applied Statistics (TOMAS) framework extends the capabilities of the A Quantum Interconnected Network Array Simulator (AQUINAS) by adding front-end and back-end software and creating an environment that integrates all of these components. The front-end tools establish all simulation parameters, configure the simulation system, automate the Monte Carlo generation of simulation files, and execute the simulation of these files. The back-end tools perform automated data parsing, statistical analysis and report generation.

Empirical force field-based kinetic Monte Carlo simulation of precipitate evolution and growth in Al-Cu alloys

NASA Astrophysics Data System (ADS)

Joshi, Kaushik; Chaudhuri, Santanu

2016-10-01

Ability to accelerate the morphological evolution of nanoscale precipitates is a fundamental challenge for atomistic simulations. Kinetic Monte Carlo (KMC) methodology is an effective approach for accelerating the evolution of nanoscale systems that are dominated by so-called rare events. The quality and accuracy of energy landscape used in KMC calculations can be significantly improved using DFT-informed interatomic potentials. Using newly developed computational framework that uses molecular simulator LAMMPS as a library function inside KMC solver SPPARKS, we investigated formation and growth of Guiner-Preston (GP) zones in dilute Al-Cu alloys at different temperature and copper concentrations. The KMC simulations with angular dependent potential (ADP) predict formation of coherent disc-shaped monolayers of copper atoms (GPI zones) in early stage. Such monolayers are then gradually transformed into energetically favored GPII phase that has two aluminum layers sandwiched between copper layers. We analyzed the growth kinetics of KMC trajectory using Johnson-Mehl-Avrami (JMA) theory and obtained a phase transformation index close to 1.0. In the presence of grain boundaries, the KMC calculations predict the segregation of copper atoms near the grain boundaries instead of formation of GP zones. The computational framework presented in this work is based on open source potentials and MD simulator and can predict morphological changes during the evolution of the alloys in the bulk and around grain boundaries.

An assessment of geographical distribution of different plant functional types over North America simulated using the CLASS-CTEM modelling framework

NASA Astrophysics Data System (ADS)

Shrestha, Rudra K.; Arora, Vivek K.; Melton, Joe R.; Sushama, Laxmi

2017-10-01

The performance of the competition module of the CLASS-CTEM (Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem Model) modelling framework is assessed at 1° spatial resolution over North America by comparing the simulated geographical distribution of its plant functional types (PFTs) with two observation-based estimates. The model successfully reproduces the broad geographical distribution of trees, grasses and bare ground although limitations remain. In particular, compared to the two observation-based estimates, the simulated fractional vegetation coverage is lower in the arid southwest North American region and higher in the Arctic region. The lower-than-observed simulated vegetation coverage in the southwest region is attributed to lack of representation of shrubs in the model and plausible errors in the observation-based data sets. The observation-based data indicate vegetation fractional coverage of more than 60 % in this arid region, despite only 200-300 mm of precipitation that the region receives annually, and observation-based leaf area index (LAI) values in the region are lower than one. The higher-than-observed vegetation fractional coverage in the Arctic is likely due to the lack of representation of moss and lichen PFTs and also likely because of inadequate representation of permafrost in the model as a result of which the C3 grass PFT performs overly well in the region. The model generally reproduces the broad spatial distribution and the total area covered by the two primary tree PFTs (needleleaf evergreen trees, NDL-EVG; and broadleaf cold deciduous trees, BDL-DCD-CLD) reasonably well. The simulated fractional coverage of tree PFTs increases after the 1960s in response to the CO2 fertilization effect and climate warming. Differences between observed and simulated PFT coverages highlight model limitations and suggest that the inclusion of shrubs, and moss and lichen PFTs, and an adequate representation of permafrost will help improve model performance.

Death of a Simulated Pediatric Patient: Toward a More Robust Theoretical Framework.

PubMed

McBride, Mary E; Schinasi, Dana Aronson; Moga, Michael Alice; Tripathy, Shreepada; Calhoun, Aaron

2017-12-01

A theoretical framework was recently proposed that encapsulates learner responses to simulated death due to action or inaction in the pediatric context. This framework, however, was developed at an institution that allows simulated death and thus does not address the experience of those centers at which this technique is not used. To address this, we performed a parallel qualitative study with the intent of augmenting the initial framework. We conducted focus groups, using a constructivist grounded theory approach, using physicians and nurses who have experienced a simulated cardiac arrest. The participants were recruited via e-mail. Transcripts were analyzed by coders blinded to the original framework to generate a list of provisional themes that were iteratively refined. These themes were then compared with the themes from the original article and used to derive a consensus model that incorporated the most relevant features of each. Focus group data yielded 7 themes. Six were similar to those developed in the original framework. One important exception was noted; however, those learners not exposed to patient death due to action or inaction often felt that the mannequin's survival was artificial. This additional theme was incorporated into a revised framework. The original framework addresses most aspects of learner reactions to simulated death. Our work suggests that adding the theme pertaining to the lack of realism that can be perceived when the mannequin is unexpectedly saved results in a more robust theoretical framework transferable to centers that do not allow mannequin death.

Developing a Novel Parameter Estimation Method for Agent-Based Model in Immune System Simulation under the Framework of History Matching: A Case Study on Influenza A Virus Infection

PubMed Central

Li, Tingting; Cheng, Zhengguo; Zhang, Le

2017-01-01

Since they can provide a natural and flexible description of nonlinear dynamic behavior of complex system, Agent-based models (ABM) have been commonly used for immune system simulation. However, it is crucial for ABM to obtain an appropriate estimation for the key parameters of the model by incorporating experimental data. In this paper, a systematic procedure for immune system simulation by integrating the ABM and regression method under the framework of history matching is developed. A novel parameter estimation method by incorporating the experiment data for the simulator ABM during the procedure is proposed. First, we employ ABM as simulator to simulate the immune system. Then, the dimension-reduced type generalized additive model (GAM) is employed to train a statistical regression model by using the input and output data of ABM and play a role as an emulator during history matching. Next, we reduce the input space of parameters by introducing an implausible measure to discard the implausible input values. At last, the estimation of model parameters is obtained using the particle swarm optimization algorithm (PSO) by fitting the experiment data among the non-implausible input values. The real Influeza A Virus (IAV) data set is employed to demonstrate the performance of our proposed method, and the results show that the proposed method not only has good fitting and predicting accuracy, but it also owns favorable computational efficiency. PMID:29194393

Developing a Novel Parameter Estimation Method for Agent-Based Model in Immune System Simulation under the Framework of History Matching: A Case Study on Influenza A Virus Infection.

PubMed

Li, Tingting; Cheng, Zhengguo; Zhang, Le

2017-12-01

Since they can provide a natural and flexible description of nonlinear dynamic behavior of complex system, Agent-based models (ABM) have been commonly used for immune system simulation. However, it is crucial for ABM to obtain an appropriate estimation for the key parameters of the model by incorporating experimental data. In this paper, a systematic procedure for immune system simulation by integrating the ABM and regression method under the framework of history matching is developed. A novel parameter estimation method by incorporating the experiment data for the simulator ABM during the procedure is proposed. First, we employ ABM as simulator to simulate the immune system. Then, the dimension-reduced type generalized additive model (GAM) is employed to train a statistical regression model by using the input and output data of ABM and play a role as an emulator during history matching. Next, we reduce the input space of parameters by introducing an implausible measure to discard the implausible input values. At last, the estimation of model parameters is obtained using the particle swarm optimization algorithm (PSO) by fitting the experiment data among the non-implausible input values. The real Influeza A Virus (IAV) data set is employed to demonstrate the performance of our proposed method, and the results show that the proposed method not only has good fitting and predicting accuracy, but it also owns favorable computational efficiency.

Integrating neuroinformatics tools in TheVirtualBrain.

PubMed

Woodman, M Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

2014-01-01

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting.

Integrating neuroinformatics tools in TheVirtualBrain

PubMed Central

Woodman, M. Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A.; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R.; Jirsa, Viktor

2014-01-01

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting. PMID:24795617

Performance of In-Pixel Circuits for Photon Counting Arrays (PCAs) Based on Polycrystalline Silicon TFTs

PubMed Central

Liang, Albert K.; Koniczek, Martin; Antonuk, Larry E.; El-Mohri, Youcef; Zhao, Qihua; Street, Robert A.; Lu, Jeng Ping

2017-01-01

Photon counting arrays (PCAs), defined as pixelated imagers which measure the absorbed energy of x-ray photons individually and record this information digitally, are of increasing clinical interest. A number of PCA prototypes with a 1 mm pixel-to-pixel pitch have recently been fabricated with polycrystalline silicon (poly-Si) — a thin-film technology capable of creating monolithic imagers of a size commensurate with human anatomy. In this study, analog and digital simulation frameworks were developed to provide insight into the influence of individual poly-Si transistors on pixel circuit performance — information that is not readily available through empirical means. The simulation frameworks were used to characterize the circuit designs employed in the prototypes. The analog framework, which determines the noise produced by individual transistors, was used to estimate energy resolution, as well as to identify which transistors contribute the most noise. The digital framework, which analyzes how well circuits function in the presence of significant variations in transistor properties, was used to estimate how fast a circuit can produce an output (referred to as output count rate). In addition, an algorithm was developed and used to estimate the minimum pixel pitch that could be achieved for the pixel circuits of the current prototypes. The simulation frameworks predict that the analog component of the PCA prototypes could have energy resolution as low as 8.9% FWHM at 70 keV; and the digital components should work well even in the presence of significant TFT variations, with the fastest component having output count rates as high as 3 MHz. Finally, based on conceivable improvements in the underlying fabrication process, the algorithm predicts that the 1 mm pitch of the current PCA prototypes could be reduced significantly, potentially to between ~240 and 290 μm. PMID:26878107

Performance of in-pixel circuits for photon counting arrays (PCAs) based on polycrystalline silicon TFTs.

PubMed

Liang, Albert K; Koniczek, Martin; Antonuk, Larry E; El-Mohri, Youcef; Zhao, Qihua; Street, Robert A; Lu, Jeng Ping

2016-03-07

Photon counting arrays (PCAs), defined as pixelated imagers which measure the absorbed energy of x-ray photons individually and record this information digitally, are of increasing clinical interest. A number of PCA prototypes with a 1 mm pixel-to-pixel pitch have recently been fabricated with polycrystalline silicon (poly-Si)-a thin-film technology capable of creating monolithic imagers of a size commensurate with human anatomy. In this study, analog and digital simulation frameworks were developed to provide insight into the influence of individual poly-Si transistors on pixel circuit performance-information that is not readily available through empirical means. The simulation frameworks were used to characterize the circuit designs employed in the prototypes. The analog framework, which determines the noise produced by individual transistors, was used to estimate energy resolution, as well as to identify which transistors contribute the most noise. The digital framework, which analyzes how well circuits function in the presence of significant variations in transistor properties, was used to estimate how fast a circuit can produce an output (referred to as output count rate). In addition, an algorithm was developed and used to estimate the minimum pixel pitch that could be achieved for the pixel circuits of the current prototypes. The simulation frameworks predict that the analog component of the PCA prototypes could have energy resolution as low as 8.9% full width at half maximum (FWHM) at 70 keV; and the digital components should work well even in the presence of significant thin-film transistor (TFT) variations, with the fastest component having output count rates as high as 3 MHz. Finally, based on conceivable improvements in the underlying fabrication process, the algorithm predicts that the 1 mm pitch of the current PCA prototypes could be reduced significantly, potentially to between ~240 and 290 μm.

Validation of educational assessments: a primer for simulation and beyond.

PubMed

Cook, David A; Hatala, Rose

2016-01-01

Simulation plays a vital role in health professions assessment. This review provides a primer on assessment validation for educators and education researchers. We focus on simulation-based assessment of health professionals, but the principles apply broadly to other assessment approaches and topics. Validation refers to the process of collecting validity evidence to evaluate the appropriateness of the interpretations, uses, and decisions based on assessment results. Contemporary frameworks view validity as a hypothesis, and validity evidence is collected to support or refute the validity hypothesis (i.e., that the proposed interpretations and decisions are defensible). In validation, the educator or researcher defines the proposed interpretations and decisions, identifies and prioritizes the most questionable assumptions in making these interpretations and decisions (the "interpretation-use argument"), empirically tests those assumptions using existing or newly-collected evidence, and then summarizes the evidence as a coherent "validity argument." A framework proposed by Messick identifies potential evidence sources: content, response process, internal structure, relationships with other variables, and consequences. Another framework proposed by Kane identifies key inferences in generating useful interpretations: scoring, generalization, extrapolation, and implications/decision. We propose an eight-step approach to validation that applies to either framework: Define the construct and proposed interpretation, make explicit the intended decision(s), define the interpretation-use argument and prioritize needed validity evidence, identify candidate instruments and/or create/adapt a new instrument, appraise existing evidence and collect new evidence as needed, keep track of practical issues, formulate the validity argument, and make a judgment: does the evidence support the intended use? Rigorous validation first prioritizes and then empirically evaluates key assumptions in the interpretation and use of assessment scores. Validation science would be improved by more explicit articulation and prioritization of the interpretation-use argument, greater use of formal validation frameworks, and more evidence informing the consequences and implications of assessment.

Model-based framework for multi-axial real-time hybrid simulation testing

NASA Astrophysics Data System (ADS)

Fermandois, Gaston A.; Spencer, Billie F.

2017-10-01

Real-time hybrid simulation is an efficient and cost-effective dynamic testing technique for performance evaluation of structural systems subjected to earthquake loading with rate-dependent behavior. A loading assembly with multiple actuators is required to impose realistic boundary conditions on physical specimens. However, such a testing system is expected to exhibit significant dynamic coupling of the actuators and suffer from time lags that are associated with the dynamics of the servo-hydraulic system, as well as control-structure interaction (CSI). One approach to reducing experimental errors considers a multi-input, multi-output (MIMO) controller design, yielding accurate reference tracking and noise rejection. In this paper, a framework for multi-axial real-time hybrid simulation (maRTHS) testing is presented. The methodology employs a real-time feedback-feedforward controller for multiple actuators commanded in Cartesian coordinates. Kinematic transformations between actuator space and Cartesian space are derived for all six-degrees-offreedom of the moving platform. Then, a frequency domain identification technique is used to develop an accurate MIMO transfer function of the system. Further, a Cartesian-domain model-based feedforward-feedback controller is implemented for time lag compensation and to increase the robustness of the reference tracking for given model uncertainty. The framework is implemented using the 1/5th-scale Load and Boundary Condition Box (LBCB) located at the University of Illinois at Urbana- Champaign. To demonstrate the efficacy of the proposed methodology, a single-story frame subjected to earthquake loading is tested. One of the columns in the frame is represented physically in the laboratory as a cantilevered steel column. For realtime execution, the numerical substructure, kinematic transformations, and controllers are implemented on a digital signal processor. Results show excellent performance of the maRTHS framework when six-degrees-of-freedom are controlled at the interface between substructures.

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.

A probabilistic model framework for evaluating year-to-year variation in crop productivity

NASA Astrophysics Data System (ADS)

Yokozawa, M.; Iizumi, T.; Tao, F.

2008-12-01

Most models describing the relation between crop productivity and weather condition have so far been focused on mean changes of crop yield. For keeping stable food supply against abnormal weather as well as climate change, evaluating the year-to-year variations in crop productivity rather than the mean changes is more essential. We here propose a new framework of probabilistic model based on Bayesian inference and Monte Carlo simulation. As an example, we firstly introduce a model on paddy rice production in Japan. It is called PRYSBI (Process- based Regional rice Yield Simulator with Bayesian Inference; Iizumi et al., 2008). The model structure is the same as that of SIMRIW, which was developed and used widely in Japan. The model includes three sub- models describing phenological development, biomass accumulation and maturing of rice crop. These processes are formulated to include response nature of rice plant to weather condition. This model inherently was developed to predict rice growth and yield at plot paddy scale. We applied it to evaluate the large scale rice production with keeping the same model structure. Alternatively, we assumed the parameters as stochastic variables. In order to let the model catch up actual yield at larger scale, model parameters were determined based on agricultural statistical data of each prefecture of Japan together with weather data averaged over the region. The posterior probability distribution functions (PDFs) of parameters included in the model were obtained using Bayesian inference. The MCMC (Markov Chain Monte Carlo) algorithm was conducted to numerically solve the Bayesian theorem. For evaluating the year-to-year changes in rice growth/yield under this framework, we firstly iterate simulations with set of parameter values sampled from the estimated posterior PDF of each parameter and then take the ensemble mean weighted with the posterior PDFs. We will also present another example for maize productivity in China. The framework proposed here provides us information on uncertainties, possibilities and limitations on future improvements in crop model as well.

LEMS: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2.

PubMed

Cannon, Robert C; Gleeson, Padraig; Crook, Sharon; Ganapathy, Gautham; Marin, Boris; Piasini, Eugenio; Silver, R Angus

2014-01-01

Computational models are increasingly important for studying complex neurophysiological systems. As scientific tools, it is essential that such models can be reproduced and critically evaluated by a range of scientists. However, published models are currently implemented using a diverse set of modeling approaches, simulation tools, and computer languages making them inaccessible and difficult to reproduce. Models also typically contain concepts that are tightly linked to domain-specific simulators, or depend on knowledge that is described exclusively in text-based documentation. To address these issues we have developed a compact, hierarchical, XML-based language called LEMS (Low Entropy Model Specification), that can define the structure and dynamics of a wide range of biological models in a fully machine readable format. We describe how LEMS underpins the latest version of NeuroML and show that this framework can define models of ion channels, synapses, neurons and networks. Unit handling, often a source of error when reusing models, is built into the core of the language by specifying physical quantities in models in terms of the base dimensions. We show how LEMS, together with the open source Java and Python based libraries we have developed, facilitates the generation of scripts for multiple neuronal simulators and provides a route for simulator free code generation. We establish that LEMS can be used to define models from systems biology and map them to neuroscience-domain specific simulators, enabling models to be shared between these traditionally separate disciplines. LEMS and NeuroML 2 provide a new, comprehensive framework for defining computational models of neuronal and other biological systems in a machine readable format, making them more reproducible and increasing the transparency and accessibility of their underlying structure and properties.

LEMS: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2

PubMed Central

Cannon, Robert C.; Gleeson, Padraig; Crook, Sharon; Ganapathy, Gautham; Marin, Boris; Piasini, Eugenio; Silver, R. Angus

2014-01-01

Computational models are increasingly important for studying complex neurophysiological systems. As scientific tools, it is essential that such models can be reproduced and critically evaluated by a range of scientists. However, published models are currently implemented using a diverse set of modeling approaches, simulation tools, and computer languages making them inaccessible and difficult to reproduce. Models also typically contain concepts that are tightly linked to domain-specific simulators, or depend on knowledge that is described exclusively in text-based documentation. To address these issues we have developed a compact, hierarchical, XML-based language called LEMS (Low Entropy Model Specification), that can define the structure and dynamics of a wide range of biological models in a fully machine readable format. We describe how LEMS underpins the latest version of NeuroML and show that this framework can define models of ion channels, synapses, neurons and networks. Unit handling, often a source of error when reusing models, is built into the core of the language by specifying physical quantities in models in terms of the base dimensions. We show how LEMS, together with the open source Java and Python based libraries we have developed, facilitates the generation of scripts for multiple neuronal simulators and provides a route for simulator free code generation. We establish that LEMS can be used to define models from systems biology and map them to neuroscience-domain specific simulators, enabling models to be shared between these traditionally separate disciplines. LEMS and NeuroML 2 provide a new, comprehensive framework for defining computational models of neuronal and other biological systems in a machine readable format, making them more reproducible and increasing the transparency and accessibility of their underlying structure and properties. PMID:25309419

A partial differential equation-based general framework adapted to Rayleigh's, Rician's and Gaussian's distributed noise for restoration and enhancement of magnetic resonance image.

PubMed

Yadav, Ram Bharos; Srivastava, Subodh; Srivastava, Rajeev

2016-01-01

The proposed framework is obtained by casting the noise removal problem into a variational framework. This framework automatically identifies the various types of noise present in the magnetic resonance image and filters them by choosing an appropriate filter. This filter includes two terms: the first term is a data likelihood term and the second term is a prior function. The first term is obtained by minimizing the negative log likelihood of the corresponding probability density functions: Gaussian or Rayleigh or Rician. Further, due to the ill-posedness of the likelihood term, a prior function is needed. This paper examines three partial differential equation based priors which include total variation based prior, anisotropic diffusion based prior, and a complex diffusion (CD) based prior. A regularization parameter is used to balance the trade-off between data fidelity term and prior. The finite difference scheme is used for discretization of the proposed method. The performance analysis and comparative study of the proposed method with other standard methods is presented for brain web dataset at varying noise levels in terms of peak signal-to-noise ratio, mean square error, structure similarity index map, and correlation parameter. From the simulation results, it is observed that the proposed framework with CD based prior is performing better in comparison to other priors in consideration.

Feasibility study for application of the compressed-sensing framework to interior computed tomography (ICT) for low-dose, high-accurate dental x-ray imaging

NASA Astrophysics Data System (ADS)

Je, U. K.; Cho, H. M.; Cho, H. S.; Park, Y. O.; Park, C. K.; Lim, H. W.; Kim, K. S.; Kim, G. A.; Park, S. Y.; Woo, T. H.; Choi, S. I.

2016-02-01

In this paper, we propose a new/next-generation type of CT examinations, the so-called Interior Computed Tomography (ICT), which may presumably lead to dose reduction to the patient outside the target region-of-interest (ROI), in dental x-ray imaging. Here an x-ray beam from each projection position covers only a relatively small ROI containing a target of diagnosis from the examined structure, leading to imaging benefits such as decreasing scatters and system cost as well as reducing imaging dose. We considered the compressed-sensing (CS) framework, rather than common filtered-backprojection (FBP)-based algorithms, for more accurate ICT reconstruction. We implemented a CS-based ICT algorithm and performed a systematic simulation to investigate the imaging characteristics. Simulation conditions of two ROI ratios of 0.28 and 0.14 between the target and the whole phantom sizes and four projection numbers of 360, 180, 90, and 45 were tested. We successfully reconstructed ICT images of substantially high image quality by using the CS framework even with few-view projection data, still preserving sharp edges in the images.

Video event classification and image segmentation based on noncausal multidimensional hidden Markov models.

PubMed

Ma, Xiang; Schonfeld, Dan; Khokhar, Ashfaq A

2009-06-01

In this paper, we propose a novel solution to an arbitrary noncausal, multidimensional hidden Markov model (HMM) for image and video classification. First, we show that the noncausal model can be solved by splitting it into multiple causal HMMs and simultaneously solving each causal HMM using a fully synchronous distributed computing framework, therefore referred to as distributed HMMs. Next we present an approximate solution to the multiple causal HMMs that is based on an alternating updating scheme and assumes a realistic sequential computing framework. The parameters of the distributed causal HMMs are estimated by extending the classical 1-D training and classification algorithms to multiple dimensions. The proposed extension to arbitrary causal, multidimensional HMMs allows state transitions that are dependent on all causal neighbors. We, thus, extend three fundamental algorithms to multidimensional causal systems, i.e., 1) expectation-maximization (EM), 2) general forward-backward (GFB), and 3) Viterbi algorithms. In the simulations, we choose to limit ourselves to a noncausal 2-D model whose noncausality is along a single dimension, in order to significantly reduce the computational complexity. Simulation results demonstrate the superior performance, higher accuracy rate, and applicability of the proposed noncausal HMM framework to image and video classification.

A comprehensive combined experimental and computational framework for pre-clinical wear simulation of total knee replacements.

PubMed

Abdelgaied, A; Fisher, J; Jennings, L M

2018-02-01

A more robust pre-clinical wear simulation framework is required in order to simulate wider and higher ranges of activities, observed in different patient populations such as younger more active patients. Such a framework will help to understand and address the reported higher failure rates for younger and more active patients (National_Joint_Registry, 2016). The current study has developed and validated a comprehensive combined experimental and computational framework for pre-clinical wear simulation of total knee replacements (TKR). The input mechanical (elastic modulus and Poisson's ratio) and wear parameters of the moderately cross-linked ultra-high molecular weight polyethylene (UHMWPE) bearing material were independently measured from experimental studies under realistic test conditions, similar to the loading conditions found in the total knee replacements. The wear predictions from the computational wear simulation were validated against the direct experimental wear measurements for size 3 Sigma curved total knee replacements (DePuy, UK) in an independent experimental wear simulation study under three different daily activities; walking, deep squat, and stairs ascending kinematic conditions. The measured compressive mechanical properties of the moderately cross-linked UHMWPE material were more than 20% lower than that reported in the literature under tensile test conditions. The pin-on-plate wear coefficient of moderately cross-linked UHMWPE was significantly dependant of the contact stress and the degree of cross-shear at the articulating surfaces. The computational wear predictions for the TKR from the current framework were consistent and in a good agreement with the independent full TKR experimental wear simulation measurements, with 0.94 coefficient of determination of the framework. In addition, the comprehensive combined experimental and computational framework was able to explain the complex experimental wear trends from the three different daily activities investigated. Therefore, such a framework can be adopted as a pre-clinical simulation approach to optimise different designs, materials, as well as patient's specific total knee replacements for a range of activities. Copyright © 2017. Published by Elsevier Ltd.

Sampling-based ensemble segmentation against inter-operator variability

NASA Astrophysics Data System (ADS)

Huo, Jing; Okada, Kazunori; Pope, Whitney; Brown, Matthew

2011-03-01

Inconsistency and a lack of reproducibility are commonly associated with semi-automated segmentation methods. In this study, we developed an ensemble approach to improve reproducibility and applied it to glioblastoma multiforme (GBM) brain tumor segmentation on T1-weigted contrast enhanced MR volumes. The proposed approach combines samplingbased simulations and ensemble segmentation into a single framework; it generates a set of segmentations by perturbing user initialization and user-specified internal parameters, then fuses the set of segmentations into a single consensus result. Three combination algorithms were applied: majority voting, averaging and expectation-maximization (EM). The reproducibility of the proposed framework was evaluated by a controlled experiment on 16 tumor cases from a multicenter drug trial. The ensemble framework had significantly better reproducibility than the individual base Otsu thresholding method (p<.001).

Validating a new methodology for strain estimation from cardiac cine MRI

NASA Astrophysics Data System (ADS)

Elnakib, Ahmed; Beache, Garth M.; Gimel'farb, Georgy; Inanc, Tamer; El-Baz, Ayman

2013-10-01

This paper focuses on validating a novel framework for estimating the functional strain from cine cardiac magnetic resonance imaging (CMRI). The framework consists of three processing steps. First, the left ventricle (LV) wall borders are segmented using a level-set based deformable model. Second, the points on the wall borders are tracked during the cardiac cycle based on solving the Laplace equation between the LV edges. Finally, the circumferential and radial strains are estimated at the inner, mid-wall, and outer borders of the LV wall. The proposed framework is validated using synthetic phantoms of the material strains that account for the physiological features and the LV response during the cardiac cycle. Experimental results on simulated phantom images confirm the accuracy and robustness of our method.

A Framework for Modeling and Simulation of the Artificial

DTIC Science & Technology

2012-01-01

y or n) >> y Name: petra Simple Aspects: face_shape/thin, nose/small, skintone/light, hair_color/black, hair_type/curly Integrated Aspects...Multiconference. Orlando, FL (2012) 23. Mittal, S., Risco- Martin , J.: Netcentric System of Systems Engineering with DEVS Unified Process. CRC Press (2012) 24...Mittal, S., Risco- Martin , J., Zeigler, B.: DEVS-based simulation web services for net-centric T&E. In: Proceedings of the 2007 summer computer

A Framework for the Measurement of Simulated Behavior Performance

DTIC Science & Technology

2011-03-24

and thesis work and through more than just words. Second, to my committee members, Maj Mendenhall and Dr. Lamont, wise gurus in their own right, who...flag.htm. [4] Random House Dictionary. Random House, Inc, 2011. URL http:// dictionary.reference.com/browse/behavior. [5] Abbott, Robert . “Behavioral...Model-Based Methodologies: An Integrative View”. Simulation Model Validation, Oren, et al., 1984. 66 [45] Sargent, Robert G. “Verification and

Ray tracing the Wigner distribution function for optical simulations

NASA Astrophysics Data System (ADS)

Mout, Marco; Wick, Michael; Bociort, Florian; Petschulat, Joerg; Urbach, Paul

2018-01-01

We study a simulation method that uses the Wigner distribution function to incorporate wave optical effects in an established framework based on geometrical optics, i.e., a ray tracing engine. We use the method to calculate point spread functions and show that it is accurate for paraxial systems but produces unphysical results in the presence of aberrations. The cause of these anomalies is explained using an analytical model.

Direct Visuo-Haptic 4D Volume Rendering Using Respiratory Motion Models.

PubMed

Fortmeier, Dirk; Wilms, Matthias; Mastmeyer, Andre; Handels, Heinz

2015-01-01

This article presents methods for direct visuo-haptic 4D volume rendering of virtual patient models under respiratory motion. Breathing models are computed based on patient-specific 4D CT image data sequences. Virtual patient models are visualized in real-time by ray casting based rendering of a reference CT image warped by a time-variant displacement field, which is computed using the motion models at run-time. Furthermore, haptic interaction with the animated virtual patient models is provided by using the displacements computed at high rendering rates to translate the position of the haptic device into the space of the reference CT image. This concept is applied to virtual palpation and the haptic simulation of insertion of a virtual bendable needle. To this aim, different motion models that are applicable in real-time are presented and the methods are integrated into a needle puncture training simulation framework, which can be used for simulated biopsy or vessel puncture in the liver. To confirm real-time applicability, a performance analysis of the resulting framework is given. It is shown that the presented methods achieve mean update rates around 2,000 Hz for haptic simulation and interactive frame rates for volume rendering and thus are well suited for visuo-haptic rendering of virtual patients under respiratory motion.

GPU-powered model analysis with PySB/cupSODA.

PubMed

Harris, Leonard A; Nobile, Marco S; Pino, James C; Lubbock, Alexander L R; Besozzi, Daniela; Mauri, Giancarlo; Cazzaniga, Paolo; Lopez, Carlos F

2017-11-01

A major barrier to the practical utilization of large, complex models of biochemical systems is the lack of open-source computational tools to evaluate model behaviors over high-dimensional parameter spaces. This is due to the high computational expense of performing thousands to millions of model simulations required for statistical analysis. To address this need, we have implemented a user-friendly interface between cupSODA, a GPU-powered kinetic simulator, and PySB, a Python-based modeling and simulation framework. For three example models of varying size, we show that for large numbers of simulations PySB/cupSODA achieves order-of-magnitude speedups relative to a CPU-based ordinary differential equation integrator. The PySB/cupSODA interface has been integrated into the PySB modeling framework (version 1.4.0), which can be installed from the Python Package Index (PyPI) using a Python package manager such as pip. cupSODA source code and precompiled binaries (Linux, Mac OS/X, Windows) are available at github.com/aresio/cupSODA (requires an Nvidia GPU; developer.nvidia.com/cuda-gpus). Additional information about PySB is available at pysb.org. paolo.cazzaniga@unibg.it or c.lopez@vanderbilt.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Assessing uncertainties in global cropland futures using a conditional probabilistic modelling framework

NASA Astrophysics Data System (ADS)

Engström, Kerstin; Olin, Stefan; Rounsevell, Mark D. A.; Brogaard, Sara; van Vuuren, Detlef P.; Alexander, Peter; Murray-Rust, Dave; Arneth, Almut

2016-11-01

We present a modelling framework to simulate probabilistic futures of global cropland areas that are conditional on the SSP (shared socio-economic pathway) scenarios. Simulations are based on the Parsimonious Land Use Model (PLUM) linked with the global dynamic vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) using socio-economic data from the SSPs and climate data from the RCPs (representative concentration pathways). The simulated range of global cropland is 893-2380 Mha in 2100 (± 1 standard deviation), with the main uncertainties arising from differences in the socio-economic conditions prescribed by the SSP scenarios and the assumptions that underpin the translation of qualitative SSP storylines into quantitative model input parameters. Uncertainties in the assumptions for population growth, technological change and cropland degradation were found to be the most important for global cropland, while uncertainty in food consumption had less influence on the results. The uncertainties arising from climate variability and the differences between climate change scenarios do not strongly affect the range of global cropland futures. Some overlap occurred across all of the conditional probabilistic futures, except for those based on SSP3. We conclude that completely different socio-economic and climate change futures, although sharing low to medium population development, can result in very similar cropland areas on the aggregated global scale.

A pervasive visual-haptic framework for virtual delivery training.

PubMed

Abate, Andrea F; Acampora, Giovanni; Loia, Vincenzo; Ricciardi, Stefano; Vasilakos, Athanasios V

2010-03-01

Thanks to the advances of voltage regulator (VR) technologies and haptic systems, virtual simulators are increasingly becoming a viable alternative to physical simulators in medicine and surgery, though many challenges still remain. In this study, a pervasive visual-haptic framework aimed to the training of obstetricians and midwives to vaginal delivery is described. The haptic feedback is provided by means of two hand-based haptic devices able to reproduce force-feedbacks on fingers and arms, thus enabling a much more realistic manipulation respect to stylus-based solutions. The interactive simulation is not solely driven by an approximated model of complex forces and physical constraints but, instead, is approached by a formal modeling of the whole labor and of the assistance/intervention procedures performed by means of a timed automata network and applied to a parametrical 3-D model of the anatomy, able to mimic a wide range of configurations. This novel methodology is able to represent not only the sequence of the main events associated to either a spontaneous or to an operative childbirth process, but also to help in validating the manual intervention as the actions performed by the user during the simulation are evaluated according to established medical guidelines. A discussion on the first results as well as on the challenges still unaddressed is included.

Drag Reduction of an Airfoil Using Deep Learning

NASA Astrophysics Data System (ADS)

Jiang, Chiyu; Sun, Anzhu; Marcus, Philip

2017-11-01

We reduced the drag of a 2D airfoil by starting with a NACA-0012 airfoil and used deep learning methods. We created a database which consists of simulations of 2D external flow over randomly generated shapes. We then developed a machine learning framework for external flow field inference given input shapes. Past work which utilized machine learning in Computational Fluid Dynamics focused on estimations of specific flow parameters, but this work is novel in the inference of entire flow fields. We further showed that learned flow patterns are transferable to cases that share certain similarities. This study illustrates the prospects of deeper integration of data-based modeling into current CFD simulation frameworks for faster flow inference and more accurate flow modeling.

Neuroanatomical distribution of five semantic components of verbs: evidence from fMRI.

PubMed

Kemmerer, David; Castillo, Javier Gonzalez; Talavage, Thomas; Patterson, Stephanie; Wiley, Cynthia

2008-10-01

The Simulation Framework, also known as the Embodied Cognition Framework, maintains that conceptual knowledge is grounded in sensorimotor systems. To test several predictions that this theory makes about the neural substrates of verb meanings, we used functional magnetic resonance imaging (fMRI) to scan subjects' brains while they made semantic judgments involving five classes of verbs-specifically, Running verbs (e.g., run, jog, walk), Speaking verbs (e.g., shout, mumble, whisper), Hitting verbs (e.g., hit, poke, jab), Cutting verbs (e.g., cut, slice, hack), and Change of State verbs (e.g., shatter, smash, crack). These classes were selected because they vary with respect to the presence or absence of five distinct semantic components-specifically, ACTION, MOTION, CONTACT, CHANGE OF STATE, and TOOL USE. Based on the Simulation Framework, we hypothesized that the ACTION component depends on the primary motor and premotor cortices, that the MOTION component depends on the posterolateral temporal cortex, that the CONTACT component depends on the intraparietal sulcus and inferior parietal lobule, that the CHANGE OF STATE component depends on the ventral temporal cortex, and that the TOOL USE component depends on a distributed network of temporal, parietal, and frontal regions. Virtually all of the predictions were confirmed. Taken together, these findings support the Simulation Framework and extend our understanding of the neuroanatomical distribution of different aspects of verb meaning.

A generic framework to simulate realistic lung, liver and renal pathologies in CT imaging

NASA Astrophysics Data System (ADS)

Solomon, Justin; Samei, Ehsan

2014-11-01

Realistic three-dimensional (3D) mathematical models of subtle lesions are essential for many computed tomography (CT) studies focused on performance evaluation and optimization. In this paper, we develop a generic mathematical framework that describes the 3D size, shape, contrast, and contrast-profile characteristics of a lesion, as well as a method to create lesion models based on CT data of real lesions. Further, we implemented a technique to insert the lesion models into CT images in order to create hybrid CT datasets. This framework was used to create a library of realistic lesion models and corresponding hybrid CT images. The goodness of fit of the models was assessed using the coefficient of determination (R2) and the visual appearance of the hybrid images was assessed with an observer study using images of both real and simulated lesions and receiver operator characteristic (ROC) analysis. The average R2 of the lesion models was 0.80, implying that the models provide a good fit to real lesion data. The area under the ROC curve was 0.55, implying that the observers could not readily distinguish between real and simulated lesions. Therefore, we conclude that the lesion-modeling framework presented in this paper can be used to create realistic lesion models and hybrid CT images. These models could be instrumental in performance evaluation and optimization of novel CT systems.

A proposal for a computer-based framework of support for public health in the management of biological incidents: the Czech Republic experience.

PubMed

Bures, Vladimír; Otcenásková, Tereza; Cech, Pavel; Antos, Karel

2012-11-01

Biological incidents jeopardising public health require decision-making that consists of one dominant feature: complexity. Therefore, public health decision-makers necessitate appropriate support. Based on the analogy with business intelligence (BI) principles, the contextual analysis of the environment and available data resources, and conceptual modelling within systems and knowledge engineering, this paper proposes a general framework for computer-based decision support in the case of a biological incident. At the outset, the analysis of potential inputs to the framework is conducted and several resources such as demographic information, strategic documents, environmental characteristics, agent descriptors and surveillance systems are considered. Consequently, three prototypes were developed, tested and evaluated by a group of experts. Their selection was based on the overall framework scheme. Subsequently, an ontology prototype linked with an inference engine, multi-agent-based model focusing on the simulation of an environment, and expert-system prototypes were created. All prototypes proved to be utilisable support tools for decision-making in the field of public health. Nevertheless, the research revealed further issues and challenges that might be investigated by both public health focused researchers and practitioners.

NOTE: Implementation of angular response function modeling in SPECT simulations with GATE

NASA Astrophysics Data System (ADS)

Descourt, P.; Carlier, T.; Du, Y.; Song, X.; Buvat, I.; Frey, E. C.; Bardies, M.; Tsui, B. M. W.; Visvikis, D.

2010-05-01

Among Monte Carlo simulation codes in medical imaging, the GATE simulation platform is widely used today given its flexibility and accuracy, despite long run times, which in SPECT simulations are mostly spent in tracking photons through the collimators. In this work, a tabulated model of the collimator/detector response was implemented within the GATE framework to significantly reduce the simulation times in SPECT. This implementation uses the angular response function (ARF) model. The performance of the implemented ARF approach has been compared to standard SPECT GATE simulations in terms of the ARF tables' accuracy, overall SPECT system performance and run times. Considering the simulation of the Siemens Symbia T SPECT system using high-energy collimators, differences of less than 1% were measured between the ARF-based and the standard GATE-based simulations, while considering the same noise level in the projections, acceleration factors of up to 180 were obtained when simulating a planar 364 keV source seen with the same SPECT system. The ARF-based and the standard GATE simulation results also agreed very well when considering a four-head SPECT simulation of a realistic Jaszczak phantom filled with iodine-131, with a resulting acceleration factor of 100. In conclusion, the implementation of an ARF-based model of collimator/detector response for SPECT simulations within GATE significantly reduces the simulation run times without compromising accuracy.

A discrete event modelling framework for simulation of long-term outcomes of sequential treatment strategies for ankylosing spondylitis.

PubMed

Tran-Duy, An; Boonen, Annelies; van de Laar, Mart A F J; Franke, Angelinus C; Severens, Johan L

2011-12-01

To develop a modelling framework which can simulate long-term quality of life, societal costs and cost-effectiveness as affected by sequential drug treatment strategies for ankylosing spondylitis (AS). Discrete event simulation paradigm was selected for model development. Drug efficacy was modelled as changes in disease activity (Bath Ankylosing Spondylitis Disease Activity Index (BASDAI)) and functional status (Bath Ankylosing Spondylitis Functional Index (BASFI)), which were linked to costs and health utility using statistical models fitted based on an observational AS cohort. Published clinical data were used to estimate drug efficacy and time to events. Two strategies were compared: (1) five available non-steroidal anti-inflammatory drugs (strategy 1) and (2) same as strategy 1 plus two tumour necrosis factor α inhibitors (strategy 2). 13,000 patients were followed up individually until death. For probability sensitivity analysis, Monte Carlo simulations were performed with 1000 sets of parameters sampled from the appropriate probability distributions. The models successfully generated valid data on treatments, BASDAI, BASFI, utility, quality-adjusted life years (QALYs) and costs at time points with intervals of 1-3 months during the simulation length of 70 years. Incremental cost per QALY gained in strategy 2 compared with strategy 1 was €35,186. At a willingness-to-pay threshold of €80,000, it was 99.9% certain that strategy 2 was cost-effective. The modelling framework provides great flexibility to implement complex algorithms representing treatment selection, disease progression and changes in costs and utilities over time of patients with AS. Results obtained from the simulation are plausible.

Interaction of railway vehicles with track in cross-winds

NASA Astrophysics Data System (ADS)

Xu, Y. L.; Ding, Q. S.

2006-04-01

This paper presents a framework for simulating railway vehicle and track interaction in cross-wind. Each 4-axle vehicle in a train is modeled by a 27-degree-of-freedom dynamic system. Two parallel rails of a track are modeled as two continuous beams supported by a discrete-elastic foundation of three layers with sleepers and ballasts included. The vehicle subsystem and the track subsystem are coupled through contacts between wheels and rails based on contact theory. Vertical and lateral rail irregularities simulated using an inverse Fourier transform are also taken into consideration. The simulation of steady and unsteady aerodynamic forces on a moving railway vehicle in cross-wind is then discussed in the time domain. The Hilber Hughes Taylor α-method is employed to solve the nonlinear equations of motion of coupled vehicle and track systems in cross-wind. The proposed framework is finally applied to a railway vehicle running on a straight track substructure in cross-wind. The safety and comfort performance of the moving vehicle in cross-wind are discussed. The results demonstrate that the proposed framework and the associated computer program can be used to investigate interaction problems of railway vehicles with track in cross-wind.

Challenges in first-principles NPT molecular dynamics of soft porous crystals: A case study on MIL-53(Ga)

NASA Astrophysics Data System (ADS)

Haigis, Volker; Belkhodja, Yacine; Coudert, François-Xavier; Vuilleumier, Rodolphe; Boutin, Anne

2014-08-01

Soft porous crystals present a challenge to molecular dynamics simulations with flexible size and shape of the simulation cell (i.e., in the NPT ensemble), since their framework responds very sensitively to small external stimuli. Hence, all interactions have to be described very accurately in order to obtain correct equilibrium structures. Here, we report a methodological study on the nanoporous metal-organic framework MIL-53(Ga), which undergoes a large-amplitude transition between a narrow- and a large-pore phase upon a change in temperature. Since this system has not been investigated by density functional theory (DFT)-based NPT simulations so far, we carefully check the convergence of the stress tensor with respect to computational parameters. Furthermore, we demonstrate the importance of dispersion interactions and test two different ways of incorporating them into the DFT framework. As a result, we propose two computational schemes which describe accurately the narrow- and the large-pore phase of the material, respectively. These schemes can be used in future work on the delicate interplay between adsorption in the nanopores and structural flexibility of the host material.

Influence of the veneer-framework interface on the mechanical behavior of ceramic veneers: a nonlinear finite element analysis.

PubMed

Lazari, Priscilla Cardoso; Sotto-Maior, Bruno Salles; Rocha, Eduardo Passos; de Villa Camargos, Germana; Del Bel Cury, Altair Antoninha

2014-10-01

The chipping of ceramic veneers is a common problem for zirconia-based restorations and is due to the weak interface between both structures. The purpose of this study was to evaluate the mechanical behavior of ceramic veneers on zirconia and metal frameworks under 2 different bond-integrity conditions. The groups were created to simulate framework-veneer bond integrity with the crowns partially debonded (frictional coefficient, 0.3) or completely bonded as follows: crown with a silver-palladium framework cemented onto a natural tooth, ceramic crown with a zirconia framework cemented onto a natural tooth, crown with a silver-palladium framework cemented onto a Morse taper implant, and ceramic crown with a zirconia framework cemented onto a Morse taper implant. The test loads were 49 N applied to the palatal surface at 45 degrees to the long axis of the crown and 25.5 N applied perpendicular to the incisal edge of the crown. The maximum principal stress, shear stress, and deformation values were calculated for the ceramic veneer; and the von Mises stress was determined for the framework. Veneers with partial debonding to the framework (frictional coefficient, 0.3) had greater stress concentrations in all structures compared with the completely bonded veneers. The metal ceramic crowns experienced lower stress values than ceramic crowns in models that simulate a perfect bond between the ceramic and the framework. Frameworks cemented to a tooth exhibited greater stress values than frameworks cemented to implants, regardless of the material used. Incomplete bonding between the ceramic veneer and the prosthetic framework affects the mechanical performance of the ceramic veneer, which makes it susceptible to failure, independent of the framework material or complete crown support. Copyright © 2014 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Predicted range expansion of Chinese tallow tree (Triadica sebifera) in forestlands of the southern United States

Treesearch

Hsiao-Hsuan Wang; William Grant; Todd Swannack; Jianbang Gan; William Rogers; Tomasz Koralewski; James Miller; John W. Taylor Jr.

2011-01-01

We present an integrated approach for predicting future range expansion of an invasive species (Chinese tallow tree) that incorporates statistical forecasting and analytical techniques within a spatially explicit, agent-based, simulation framework.

"Fab 13": The Learning Factory.

ERIC Educational Resources Information Center

Crooks, Steven M.; Eucker, Tom R.

2001-01-01

Describes how situated learning theory was employed in the design of Fab 13, a four-day simulation-based learning experience for manufacturing professionals at Intel Corporation. Presents a conceptual framework for understanding situated learning and discusses context, content, anchored instruction, facilitation, scaffolding, collaborating,…

Making Sense of the Data from Complex Assessments.

ERIC Educational Resources Information Center

Mislevy, Robert J.; Steinberg, Linda S.; Breyer, F. Jay; Almond, Russell G.; Johnson, Lynn

2002-01-01

Presents a design framework that incorporates integrated structures for modeling knowledge and skills, designing tasks, and extracting and synthesizing evidence. Illustrates these ideas in the context of a project that assesses problem solving in dental hygiene through computer-based simulations. (SLD)

Lattice Boltzmann simulations of the bead-spring microswimmer with a responsive stroke—from an individual to swarms

NASA Astrophysics Data System (ADS)

Pickl, Kristina; Pande, Jayant; Köstler, Harald; Rüde, Ulrich; Smith, Ana-Sunčana

2017-03-01

Propulsion at low Reynolds numbers is often studied by defining artificial microswimmers which exhibit a particular stroke. The disadvantage of such an approach is that the stroke does not adjust to the environment, in particular the fluid flow, which can diminish the effect of hydrodynamic interactions. To overcome this limitation, we simulate a microswimmer consisting of three beads connected by springs and dampers, using the self-developed waLBerla and pe framework based on the lattice Boltzmann method and the discrete element method. In our approach, the swimming stroke of a swimmer emerges as a balance of the drag, the driving and the elastic internal forces. We validate the simulations by comparing the obtained swimming velocity to the velocity found analytically using a perturbative method where the bead oscillations are taken to be small. Including higher-order terms in the hydrodynamic interactions between the beads improves the agreement to the simulations in parts of the parameter space. Encouraged by the agreement between the theory and the simulations and aided by the massively parallel capabilities of the waLBerla-pe framework, we simulate more than ten thousand such swimmers together, thus presenting the first fully resolved simulations of large swarms with active responsive components.

An Information Theoretic Framework and Self-organizing Agent- based Sensor Network Architecture for Power Plant Condition Monitoring

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

Loparo, Kenneth; Kolacinski, Richard; Threeanaew, Wanchat

A central goal of the work was to enable both the extraction of all relevant information from sensor data, and the application of information gained from appropriate processing and fusion at the system level to operational control and decision-making at various levels of the control hierarchy through: 1. Exploiting the deep connection between information theory and the thermodynamic formalism, 2. Deployment using distributed intelligent agents with testing and validation in a hardware-in-the loop simulation environment. Enterprise architectures are the organizing logic for key business processes and IT infrastructure and, while the generality of current definitions provides sufficient flexibility, the currentmore » architecture frameworks do not inherently provide the appropriate structure. Of particular concern is that existing architecture frameworks often do not make a distinction between ``data'' and ``information.'' This work defines an enterprise architecture for health and condition monitoring of power plant equipment and further provides the appropriate foundation for addressing shortcomings in current architecture definition frameworks through the discovery of the information connectivity between the elements of a power generation plant. That is, to identify the correlative structure between available observations streams using informational measures. The principle focus here is on the implementation and testing of an emergent, agent-based, algorithm based on the foraging behavior of ants for eliciting this structure and on measures for characterizing differences between communication topologies. The elicitation algorithms are applied to data streams produced by a detailed numerical simulation of Alstom’s 1000 MW ultra-super-critical boiler and steam plant. The elicitation algorithm and topology characterization can be based on different informational metrics for detecting connectivity, e.g. mutual information and linear correlation.« less

Enhancements to the SHARP Build System and NEK5000 Coupling

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

McCaskey, Alex; Bennett, Andrew R.; Billings, Jay Jay

The SHARP project for the Department of Energy's Nuclear Energy Advanced Modeling and Simulation (NEAMS) program provides a multiphysics framework for coupled simulations of advanced nuclear reactor designs. It provides an overall coupling environment that utilizes custom interfaces to couple existing physics codes through a common spatial decomposition and unique solution transfer component. As of this writing, SHARP couples neutronics, thermal hydraulics, and structural mechanics using PROTEUS, Nek5000, and Diablo respectively. This report details two primary SHARP improvements regarding the Nek5000 and Diablo individual physics codes: (1) an improved Nek5000 coupling interface that lets SHARP achieve a vast increase inmore » overall solution accuracy by manipulating the structure of the internal Nek5000 spatial mesh, and (2) the capability to seamlessly couple structural mechanics calculations into the framework through improvements to the SHARP build system. The Nek5000 coupling interface now uses a barycentric Lagrange interpolation method that takes the vertex-based power and density computed from the PROTEUS neutronics solver and maps it to the user-specified, general-order Nek5000 spectral element mesh. Before this work, SHARP handled this vertex-based solution transfer in an averaging-based manner. SHARP users can now achieve higher levels of accuracy by specifying any arbitrary Nek5000 spectral mesh order. This improvement takes the average percentage error between the PROTEUS power solution and the Nek5000 interpolated result down drastically from over 23 % to just above 2 %, and maintains the correct power profile. We have integrated Diablo into the SHARP build system to facilitate the future coupling of structural mechanics calculations into SHARP. Previously, simulations involving Diablo were done in an iterative manner, requiring a large amount manual work, and left only as a task for advanced users. This report will detail a new Diablo build system that was implemented using GNU Autotools, mirroring much of the current SHARP build system, and easing the use of structural mechanics calculations for end-users of the SHARP multiphysics framework. It lets users easily build and use Diablo as a stand-alone simulation, as well as fully couple with the other SHARP physics modules. The top-level SHARP build system was modified to allow Diablo to hook in directly. New dependency handlers were implemented to let SHARP users easily build the framework with these new simulation capabilities. The remainder of this report will describe this work in full, with a detailed discussion of the overall design philosophy of SHARP, the new solution interpolation method introduced, and the Diablo integration work. We will conclude with a discussion of possible future SHARP improvements that will serve to increase solution accuracy and framework capability.« less

Multi-Mission Simulation and Visualization for Real-Time Telemetry Display, Playback and EDL Event Reconstruction

NASA Technical Reports Server (NTRS)

Pomerantz, M. I.; Lim, C.; Myint, S.; Woodward, G.; Balaram, J.; Kuo, C.

2012-01-01

he Jet Propulsion Laboratory's Entry, Descent and Landing (EDL) Reconstruction Task has developed a software system that provides mission operations personnel and analysts with a real time telemetry-based live display, playback and post-EDL reconstruction capability that leverages the existing high-fidelity, physics-based simulation framework and modern game engine-derived 3D visualization system developed in the JPL Dynamics and Real Time Simulation (DARTS) Lab. Developed as a multi-mission solution, the EDL Telemetry Visualization (ETV) system has been used for a variety of projects including NASA's Mars Science Laboratory (MSL), NASA'S Low Density Supersonic Decelerator (LDSD) and JPL's MoonRise Lunar sample return proposal.

Conceptual Modeling of a Quantum Key Distribution Simulation Framework Using the Discrete Event System Specification

DTIC Science & Technology

2014-09-18

and full/scale experimental verifications towards ground/ satellite quantum key distribution0 Oat Qhotonics 4235>9+7,=5;9!អ \\58^ Zin K. Dao Z. Miu T...Conceptual Modeling of a Quantum Key Distribution Simulation Framework Using the Discrete Event System Specification DISSERTATION Jeffrey D. Morris... QUANTUM KEY DISTRIBUTION SIMULATION FRAMEWORK USING THE DISCRETE EVENT SYSTEM SPECIFICATION DISSERTATION Presented to the Faculty Department of Systems

Interactive Resource Planning—An Anticipative Concept in the Simulation-Based Decision Support System EXPOSIM

NASA Astrophysics Data System (ADS)

Leopold-Wildburger, Ulrike; Pickl, Stefan

2008-10-01

In our research we intend to use experiments to study human behavior in a simulation environment based on a simple Lotka-Volterra predator-prey ecology. The aim is to study the influence of participants' harvesting strategies and certain personality traits derived from [1] on the outcome in terms of sustainability and economic performance. Such an approach is embedded in a research program which intends to develop and understand interactive resource planning processes. We present the general framework as well as the new decision support system EXPOSIM. The key element is the combination of experimental design, analytical understanding of time-discrete systems (especially Lotka-Volterra systems) and economic performance. In the first part, the general role of laboratory experiments is discussed. The second part summarizes the concept of sustainable development. It is taken from [18]. As we use Lotka-Volterra systems as the basis for our simulations a theoretical framework is described afterwards. It is possible to determine optimal behavior for those systems. The empirical setting is based on the empirical approach that the subjects are put into the position of a decision-maker. They are able to model the environment in such a way that harvesting can be observed. We suggest an experimental setting which might lead to new insights in an anticipatory sense.

Establishing a Numerical Modeling Framework for Hydrologic Engineering Analyses of Extreme Storm Events

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

Chen, Xiaodong; Hossain, Faisal; Leung, L. Ruby

In this study a numerical modeling framework for simulating extreme storm events was established using the Weather Research and Forecasting (WRF) model. Such a framework is necessary for the derivation of engineering parameters such as probable maximum precipitation that are the cornerstone of large water management infrastructure design. Here this framework was built based on a heavy storm that occurred in Nashville (USA) in 2010, and verified using two other extreme storms. To achieve the optimal setup, several combinations of model resolutions, initial/boundary conditions (IC/BC), cloud microphysics and cumulus parameterization schemes were evaluated using multiple metrics of precipitation characteristics. Themore » evaluation suggests that WRF is most sensitive to IC/BC option. Simulation generally benefits from finer resolutions up to 5 km. At the 15km level, NCEP2 IC/BC produces better results, while NAM IC/BC performs best at the 5km level. Recommended model configuration from this study is: NAM or NCEP2 IC/BC (depending on data availability), 15km or 15km-5km nested grids, Morrison microphysics and Kain-Fritsch cumulus schemes. Validation of the optimal framework suggests that these options are good starting choices for modeling extreme events similar to the test cases. This optimal framework is proposed in response to emerging engineering demands of extreme storm events forecasting and analyses for design, operations and risk assessment of large water infrastructures.« less

A simulation framework for the CMS Track Trigger electronics

NASA Astrophysics Data System (ADS)

Amstutz, C.; Magazzù, G.; Weber, M.; Palla, F.

2015-03-01

A simulation framework has been developed to test and characterize algorithms, architectures and hardware implementations of the vastly complex CMS Track Trigger for the high luminosity upgrade of the CMS experiment at the Large Hadron Collider in Geneva. High-level SystemC models of all system components have been developed to simulate a portion of the track trigger. The simulation of the system components together with input data from physics simulations allows evaluating figures of merit, like delays or bandwidths, under realistic conditions. The use of SystemC for high-level modelling allows co-simulation with models developed in Hardware Description Languages, e.g. VHDL or Verilog. Therefore, the simulation framework can also be used as a test bench for digital modules developed for the final system.

Agent-based model for the h-index - exact solution

NASA Astrophysics Data System (ADS)

Żogała-Siudem, Barbara; Siudem, Grzegorz; Cena, Anna; Gagolewski, Marek

2016-01-01

Hirsch's h-index is perhaps the most popular citation-based measure of scientific excellence. In 2013, Ionescu and Chopard proposed an agent-based model describing a process for generating publications and citations in an abstract scientific community [G. Ionescu, B. Chopard, Eur. Phys. J. B 86, 426 (2013)]. Within such a framework, one may simulate a scientist's activity, and - by extension - investigate the whole community of researchers. Even though the Ionescu and Chopard model predicts the h-index quite well, the authors provided a solution based solely on simulations. In this paper, we complete their results with exact, analytic formulas. What is more, by considering a simplified version of the Ionescu-Chopard model, we obtained a compact, easy to compute formula for the h-index. The derived approximate and exact solutions are investigated on a simulated and real-world data sets.

"Observing" the Circumnuclear Stars and Gas in Disk Galaxy Simulations

NASA Astrophysics Data System (ADS)

Cook, Angela; Hicks, Erin K. S.

2018-06-01

We present simulations based on theoretical models of common disk processes designed to represent potential inflow observed within the central 500 pc of local Seyfert galaxies. Mock observations of these n-body plus smoothed particle hydrodynamical simulations provide the conceptual framework in which to identify the driving inflow mechanism, for example nuclear bars, and to quantify to the inflow based on observable properties. From these mock observations the azimuthal average of the flux distribution, velocity dispersion, and velocity of both the stars and interstellar medium on scales of 50pc have been measured at a range of inclinations angles. A comparison of the simulated disk galaxies with these observed azimuthal averages in 40 Seyfert galaxies measured as part of the KONA (Keck OSIRIS Nearby AGN) survey will be presented.

Realistic wave-optics simulation of X-ray phase-contrast imaging at a human scale

PubMed Central

Sung, Yongjin; Segars, W. Paul; Pan, Adam; Ando, Masami; Sheppard, Colin J. R.; Gupta, Rajiv

2015-01-01

X-ray phase-contrast imaging (XPCI) can dramatically improve soft tissue contrast in X-ray medical imaging. Despite worldwide efforts to develop novel XPCI systems, a numerical framework to rigorously predict the performance of a clinical XPCI system at a human scale is not yet available. We have developed such a tool by combining a numerical anthropomorphic phantom defined with non-uniform rational B-splines (NURBS) and a wave optics-based simulator that can accurately capture the phase-contrast signal from a human-scaled numerical phantom. Using a synchrotron-based, high-performance XPCI system, we provide qualitative comparison between simulated and experimental images. Our tool can be used to simulate the performance of XPCI on various disease entities and compare proposed XPCI systems in an unbiased manner. PMID:26169570

Realistic wave-optics simulation of X-ray phase-contrast imaging at a human scale

NASA Astrophysics Data System (ADS)

Sung, Yongjin; Segars, W. Paul; Pan, Adam; Ando, Masami; Sheppard, Colin J. R.; Gupta, Rajiv

2015-07-01

X-ray phase-contrast imaging (XPCI) can dramatically improve soft tissue contrast in X-ray medical imaging. Despite worldwide efforts to develop novel XPCI systems, a numerical framework to rigorously predict the performance of a clinical XPCI system at a human scale is not yet available. We have developed such a tool by combining a numerical anthropomorphic phantom defined with non-uniform rational B-splines (NURBS) and a wave optics-based simulator that can accurately capture the phase-contrast signal from a human-scaled numerical phantom. Using a synchrotron-based, high-performance XPCI system, we provide qualitative comparison between simulated and experimental images. Our tool can be used to simulate the performance of XPCI on various disease entities and compare proposed XPCI systems in an unbiased manner.

Reconstructing the regulatory network controlling commitment and sporulation in Physarum polycephalum based on hierarchical Petri Net modelling and simulation.

PubMed

Marwan, Wolfgang; Sujatha, Arumugam; Starostzik, Christine

2005-10-21

We reconstruct the regulatory network controlling commitment and sporulation of Physarum polycephalum from experimental results using a hierarchical Petri Net-based modelling and simulation framework. The stochastic Petri Net consistently describes the structure and simulates the dynamics of the molecular network as analysed by genetic, biochemical and physiological experiments within a single coherent model. The Petri Net then is extended to simulate time-resolved somatic complementation experiments performed by mixing the cytoplasms of mutants altered in the sporulation response, to systematically explore the network structure and to probe its dynamics. This reverse engineering approach presumably can be employed to explore other molecular or genetic signalling systems where the activity of genes or their products can be experimentally controlled in a time-resolved manner.

Post Pareto optimization-A case

NASA Astrophysics Data System (ADS)

Popov, Stoyan; Baeva, Silvia; Marinova, Daniela

2017-12-01

Simulation performance may be evaluated according to multiple quality measures that are in competition and their simultaneous consideration poses a conflict. In the current study we propose a practical framework for investigating such simulation performance criteria, exploring the inherent conflicts amongst them and identifying the best available tradeoffs, based upon multi-objective Pareto optimization. This approach necessitates the rigorous derivation of performance criteria to serve as objective functions and undergo vector optimization. We demonstrate the effectiveness of our proposed approach by applying it with multiple stochastic quality measures. We formulate performance criteria of this use-case, pose an optimization problem, and solve it by means of a simulation-based Pareto approach. Upon attainment of the underlying Pareto Frontier, we analyze it and prescribe preference-dependent configurations for the optimal simulation training.